Embedding Open-domain Common-sense Knowledge from Text

PubMed Central

Goodwin, Travis; Harabagiu, Sanda

2017-01-01

Our ability to understand language often relies on common-sense knowledge – background information the speaker can assume is known by the reader. Similarly, our comprehension of the language used in complex domains relies on access to domain-specific knowledge. Capturing common-sense and domain-specific knowledge can be achieved by taking advantage of recent advances in open information extraction (IE) techniques and, more importantly, of knowledge embeddings, which are multi-dimensional representations of concepts and relations. Building a knowledge graph for representing common-sense knowledge in which concepts discerned from noun phrases are cast as vertices and lexicalized relations are cast as edges leads to learning the embeddings of common-sense knowledge accounting for semantic compositionality as well as implied knowledge. Common-sense knowledge is acquired from a vast collection of blogs and books as well as from WordNet. Similarly, medical knowledge is learned from two large sets of electronic health records. The evaluation results of these two forms of knowledge are promising: the same knowledge acquisition methodology based on learning knowledge embeddings works well both for common-sense knowledge and for medical knowledge Interestingly, the common-sense knowledge that we have acquired was evaluated as being less neutral than than the medical knowledge, as it often reflected the opinion of the knowledge utterer. In addition, the acquired medical knowledge was evaluated as more plausible than the common-sense knowledge, reflecting the complexity of acquiring common-sense knowledge due to the pragmatics and economicity of language. PMID:28649676

Testing the sensitivity of terrestrial carbon models using remotely sensed biomass estimates

NASA Astrophysics Data System (ADS)

Hashimoto, H.; Saatchi, S. S.; Meyer, V.; Milesi, C.; Wang, W.; Ganguly, S.; Zhang, G.; Nemani, R. R.

2010-12-01

There is a large uncertainty in carbon allocation and biomass accumulation in forest ecosystems. With the recent availability of remotely sensed biomass estimates, we now can test some of the hypotheses commonly implemented in various ecosystem models. We used biomass estimates derived by integrating MODIS, GLAS and PALSAR data to verify above-ground biomass estimates simulated by a number of ecosystem models (CASA, BIOME-BGC, BEAMS, LPJ). This study extends the hierarchical framework (Wang et al., 2010) for diagnosing ecosystem models by incorporating independent estimates of biomass for testing and calibrating respiration, carbon allocation, turn-over algorithms or parameters.

Dynamical prediction of flu seasonality driven by ambient temperature: influenza vs. common cold

NASA Astrophysics Data System (ADS)

Postnikov, Eugene B.

2016-01-01

This work presents a comparative analysis of Influenzanet data for influenza itself and common cold in the Netherlands during the last 5 years, from the point of view of modelling by linearised SIRS equations parametrically driven by the ambient temperature. It is argued that this approach allows for the forecast of common cold, but not of influenza in a strict sense. The difference in their kinetic models is discussed with reference to the clinical background.

Decision Making in the Short Run.

ERIC Educational Resources Information Center

Lopes, Lola L.

1981-01-01

The commonly accepted idea that the only rational measure of the worth of a gamble is its expected value or some subjective counterpart such as expected utility is examined. Also discussed are the changes called for in theories of rational choice when prescriptions of rational models violate common sense. (Author/GK)

Disruptive Innovations for Adjunct Faculty: Common Sense for Common Good

ERIC Educational Resources Information Center

Rhoades, Gary

2013-01-01

Policy and practice in higher education today are defined and limited by what many have claimed are "new realities" confronting colleges and universities. Gary Rhoades contends that three of these are embedded in the just-in-time hiring practices, the at-will conditions of work, and the depersonalized curricular delivery models assigned…

An Optical Model for Estimating the Underwater Light Field from Remote Sensing

NASA Technical Reports Server (NTRS)

Liu, Cheng-Chien; Miller, Richard L.

2002-01-01

A model of the wavelength-integrated scalar irradiance for a vertically homogeneous water column is developed. It runs twenty thousand times faster than simulations obtained using full Hydrolight code and limits the percentage error to less than 3.7%. Both the distribution of incident sky radiance and a wind-roughened surface are integrated in the model. Our model removes common limitations of earlier models and can be applied to waters with any composition of the inherent optical properties. Implementation of this new model, as well as the ancillary information required for processing global-scale satellite data, is discussed. This new model is fast, accurate, and flexible and therefore provides important information of the underwater light field from remote sensing.

A new capacitive long-range displacement nanometer sensor with differential sensing structure based on time-grating

NASA Astrophysics Data System (ADS)

Yu, Zhicheng; Peng, Kai; Liu, Xiaokang; Pu, Hongji; Chen, Ziran

2018-05-01

High-precision displacement sensors, which can measure large displacements with nanometer resolution, are key components in many ultra-precision fabrication machines. In this paper, a new capacitive nanometer displacement sensor with differential sensing structure is proposed for long-range linear displacement measurements based on an approach denoted time grating. Analytical models established using electric field coupling theory and an area integral method indicate that common-mode interference will result in a first-harmonic error in the measurement results. To reduce the common-mode interference, the proposed sensor design employs a differential sensing structure, which adopts a second group of induction electrodes spatially separated from the first group of induction electrodes by a half-pitch length. Experimental results based on a prototype sensor demonstrate that the measurement accuracy and the stability of the sensor are substantially improved after adopting the differential sensing structure. Finally, a prototype sensor achieves a measurement accuracy of  ±200 nm over the full 200 mm measurement range of the sensor.

Evaluating a Health Behaviour Model for Persons with and without an Intellectual Disability

ERIC Educational Resources Information Center

Brehmer-Rinderer, B.; Zigrovic, L.; Weber, G.

2014-01-01

Background: Based on the idea of the Common Sense Model of Illness Representations by Leventhal as well as Lohaus's concepts of health and illness, a health behaviour model was designed to explain health behaviours applied by persons with intellectual disabilities (ID). The key proposal of this model is that the way someone understands the…

Chemical Sensor Array Response Modeling Using Quantitative Structure-Activity Relationships Technique

NASA Astrophysics Data System (ADS)

Shevade, Abhijit V.; Ryan, Margaret A.; Homer, Margie L.; Zhou, Hanying; Manfreda, Allison M.; Lara, Liana M.; Yen, Shiao-Pin S.; Jewell, April D.; Manatt, Kenneth S.; Kisor, Adam K.

We have developed a Quantitative Structure-Activity Relationships (QSAR) based approach to correlate the response of chemical sensors in an array with molecular descriptors. A novel molecular descriptor set has been developed; this set combines descriptors of sensing film-analyte interactions, representing sensor response, with a basic analyte descriptor set commonly used in QSAR studies. The descriptors are obtained using a combination of molecular modeling tools and empirical and semi-empirical Quantitative Structure-Property Relationships (QSPR) methods. The sensors under investigation are polymer-carbon sensing films which have been exposed to analyte vapors at parts-per-million (ppm) concentrations; response is measured as change in film resistance. Statistically validated QSAR models have been developed using Genetic Function Approximations (GFA) for a sensor array for a given training data set. The applicability of the sensor response models has been tested by using it to predict the sensor activities for test analytes not considered in the training set for the model development. The validated QSAR sensor response models show good predictive ability. The QSAR approach is a promising computational tool for sensing materials evaluation and selection. It can also be used to predict response of an existing sensing film to new target analytes.

Common Sense Illness Beliefs of Diabetes among At-Risk Latino College Students

PubMed Central

Santos, Silvia J.; Hurtado-Ortiz, Maria T.; Lewis, Laurenne; Ramirez-Garcia, Julia

2017-01-01

This study examined the validity of the Implicit Model of Illness Questionnaire (IMIQ - Schiaffino & Cea, 1995) when used with Latino college students (n = 156; 34% male, 66% female) who are at-risk for developing diabetes due to family history of this disease. An exploratory principal-axis factor analysis yielded four significant factors – curability, personal responsibility, symptom variability/seriousness, and personal attributions – which accounted for 35% of variance and reflected a psychosocial-biomedical common sense perspective of diabetes. Factor-based analyses revealed differences in diabetes illness beliefs based on students’ age, generational status, acculturation orientation, and disease experience of the afflicted relative. PMID:29056849

The Houdini Transformation: True, but Illusory.

PubMed

Bentler, Peter M; Molenaar, Peter C M

2012-01-01

Molenaar (2003, 2011) showed that a common factor model could be transformed into an equivalent model without factors, involving only observed variables and residual errors. He called this invertible transformation the Houdini transformation. His derivation involved concepts from time series and state space theory. This paper verifies the Houdini transformation on a general latent variable model using algebraic methods. The results show that the Houdini transformation is illusory, in the sense that the Houdini transformed model remains a latent variable model. Contrary to common knowledge, a model that is a path model with only observed variables and residual errors may, in fact, be a latent variable model.

The Houdini Transformation: True, but Illusory

PubMed Central

Bentler, Peter M.; Molenaar, Peter C. M.

2012-01-01

Molenaar (2003, 2011) showed that a common factor model could be transformed into an equivalent model without factors, involving only observed variables and residual errors. He called this invertible transformation the Houdini transformation. His derivation involved concepts from time series and state space theory. This paper verifies the Houdini transformation on a general latent variable model using algebraic methods. The results show that the Houdini transformation is illusory, in the sense that the Houdini transformed model remains a latent variable model. Contrary to common knowledge, a model that is a path model with only observed variables and residual errors may, in fact, be a latent variable model. PMID:23180888

The shifting sands of self: a framework for the experience of self in addiction.

PubMed

Gray, Mary Tod

2005-04-01

The self is a common yet unclear theme in addiction studies. William James's model of self provides a framework to explore the experience of self. His model details the subjective and objective constituents, the sense of self-continuity through time, and the ephemeral and plural nature of the changing self. This exploration yields insights into the self that can be usefully applied to subjective experiences with psychoactive drugs of addiction. Results of this application add depth to the common understanding of self in addiction, acknowledge the importance of feelings and choice in the sense of self created in addiction experiences, and affirm the values salient to these interior experiences in addiction. These results suggest meaning derived from those values, and provide important background knowledge for the nurse interacting with these clients.

Suitability of Lake Erie for bigheaded carps based on bioenergetic models and remote sensing

USGS Publications Warehouse

Anderson, Karl R.; Chapman, Duane C.; Wynne, Timothy; Masagounder, Karthik; Paukert, Craig P.

2015-01-01

Algal blooms in the Great Lakes are a potential food source for silver carp (Hypophthalmichthys molitrix) and bighead carp (H. nobilis; together bigheaded carps). Understanding these blooms thus plays an important role in understanding the invasion potential of bigheaded carps. We used remote sensing imagery, temperatures, and improved species specific bioenergetics models to determine algal concentrations sufficient for adult bigheaded carps. Depending on water temperature we found that bigheaded carp require between 2 and 7 μg/L chlorophyll or between 0.3 and 1.26 × 105cells/mL Microcystis to maintain body weight. Algal concentrations in the western basin and shoreline were found to be commonly several times greater than the concentrations required for weight maintenance. The remote sensing images show that area of sufficient algal foods commonly encompassed several hundred square kilometers to several thousands of square kilometers when blooms form. From 2002 to 2011, mean algal concentrations increased 273%–411%. This indicates Lake Erie provides increasingly adequate planktonic algal food for bigheaded carps. The water temperatures and algal concentrations detected in Lake Erie from 2008 to 2012 support positive growth rates such that a 4 kg silver carp could gain between 19 and 57% of its body weight in a year. A 5 kg bighead carp modeled at the same water temperatures could gain 20–81% of their body weight in the same period. The remote sensing imagery and bioenergetic models suggest that bigheaded carps would not be food limited if they invaded Lake Erie.

A Reasoning Hardware Platform for Real-Time Common-Sense Inference

PubMed Central

Barba, Jesús; Santofimia, Maria J.; Dondo, Julio; Rincón, Fernando; Sánchez, Francisco; López, Juan Carlos

2012-01-01

Enabling Ambient Intelligence systems to understand the activities that are taking place in a supervised context is a rather complicated task. Moreover, this task cannot be successfully addressed while overlooking the mechanisms (common-sense knowledge and reasoning) that entitle us, as humans beings, to successfully undertake it. This work is based on the premise that Ambient Intelligence systems will be able to understand and react to context events if common-sense capabilities are embodied in them. However, there are some difficulties that need to be resolved before common-sense capabilities can be fully deployed to Ambient Intelligence. This work presents a hardware accelerated implementation of a common-sense knowledge-base system intended to improve response time and efficiency. PMID:23012540

Neighboring and Urbanism: Commonality versus Friendship.

ERIC Educational Resources Information Center

Silverman, Carol J.

1986-01-01

Examines a dimension of neighboring that need not assume friendship as the role model. When the model assumes only a sense of connectedness as defining neighboring, then the residential correlation, shown in many studies between urbanism and neighboring, disappears. Theories of neighboring, study variables, methods, and analysis are discussed.…

Quality Assurance in Clinical Chemistry: A Touch of Statistics and A Lot of Common Sense

PubMed Central

2016-01-01

Summary Working in laboratories of clinical chemistry, we risk feeling that our personal contribution to quality is small and that statistical models and manufacturers play the major roles. It is seldom sufficiently acknowledged that personal knowledge, skills and common sense are crucial for quality assurance in the interest of patients. The employees, environment and procedures inherent to the laboratory including its interactions with the clients are crucial for the overall result of the total testing chain. As the measurement systems, reagents and procedures are gradually improved, work on the preanalytical, postanalytical and clinical phases is likely to pay the most substantial dividends in accomplishing further quality improvements. This means changing attitudes and behaviour, especially of the users of the laboratory. It requires understanding people and how to engage them in joint improvement processes. We need to use our knowledge and common sense expanded with new skills e.g. from the humanities, management, business and change sciences in order to bring this about together with the users of the laboratory. PMID:28356868

Older Adults’ Fears about Diabetes: Using Common Sense Models of Disease to Understand Fear Origins and Implications for Self-Management

PubMed Central

Reynolds, Teresa; Chapman, Christine; Bell, Ronny A.; Grzywacz, Joseph G.; Ip, Edward H.; Kirk, Julienne K.; Arcury, Thomas A.

2013-01-01

This study examines older adults’ fears of diabetes complications and their effects on self-management practices. Existing models of diabetes self-management posit that patients’ actions are grounded in disease beliefs and experience, but there is little supporting evidence. In-depth qualitative interviews were conducted with a community-based sample of 74 African American, American Indian, and white older adults with diabetes. Analysis uses Leventhal’s Common Sense Model of Diabetes to link fears to early experience and current self-management. Sixty-three identified fears focused on complications that could limit carrying out normal activities: amputation, blindness, low blood glucose and coma, and disease progression to insulin use and dialysis. Most focused self-management on actions to prevent specific complications, rather than on managing the disease as a whole. Early experiences focused attention on the inevitability of complications and the limited ability of patients to prevent them. Addressing older adults’ fears about diabetes may improve their diabetes self-management practices. PMID:25364096

Cognitive science speaks to the "common-sense" of chronic illness management.

PubMed

Leventhal, Howard; Leventhal, Elaine A; Breland, Jessica Y

2011-04-01

We describe the parallels between findings from cognitive science and neuroscience and Common-Sense Models in four areas: (1) Activation of illness representations by the automatic linkage of symptoms and functional changes with concepts (an integration of declarative and perceptual and procedural knowledge); (2) Action plans for the management of symptoms and disease; (3) Cognitive and behavioral heuristics (executive functions parallel to recent findings in cognitive science) involved in monitoring and modifying automatic control processes; (4) Perceiving and communicating to "other minds" during medical visits to address the declarative and non-declarative (perceptual and procedural) knowledge that comprise a patient's representations of illness and treatment (the transparency of other minds).

A Tale of Two Models: Sources of Confusion in Achievement Testing. Research Report. ETS RR-17-44

ERIC Educational Resources Information Center

Reckase, Mark D.

2017-01-01

A common interpretation of achievement test results is that they provide measures of achievement that are much like other measures we commonly use for height, weight, or the cost of goods. In a limited sense, such interpretations are correct, but some nuances of these interpretations have important implications for the use of achievement test…

Disability and Popular Common Sense in India: Noun versus Adjective

ERIC Educational Resources Information Center

Shahid, Mohd; Raza, Md. Shahid; Alam, Md. Aftab

2016-01-01

Reflecting through the Indian experiences, a brief attempt is made to explore how disability as a noun takes shape in popular common sense "call names" (adjectives) and how does the popular common sense legitimise and normalise the oppressive language and the oppressed reality of the persons with disabilities? In the Indian context, the…

Lay understanding of familial risk of common chronic diseases: a systematic review and synthesis of qualitative research.

PubMed

Walter, Fiona M; Emery, Jon; Braithwaite, Dejana; Marteau, Theresa M

2004-01-01

Although the family history is increasingly used for genetic risk assessment of common chronic diseases in primary care, evidence suggests that lay understanding about inheritance may conflict with medical models. This study systematically reviewed and synthesized the qualitative literature exploring understanding about familial risk held by persons with a family history of cancer, coronary artery disease, and diabetes mellitus. Twenty-two qualitative articles were found after a comprehensive literature search and were critically appraised; 11 were included. A meta-ethnographic approach was used to translate the studies across each other, synthesize the translation, and express the synthesis. A dynamic process emerged by which a personal sense of vulnerability included some features that mirror the medical factors used to assess risk, such as the number of affected relatives. Other features are more personal, such as experience of a relative's disease, sudden or premature death, perceived patterns of illness relating to gender or age at death, and comparisons between a person and an affected relative. The developing vulnerability is interpreted using personal mental models, including models of disease causation, inheritance, and fatalism. A person's sense of vulnerability affects how that person copes with, and attempts to control, any perceived familial risk. Persons with a family history of a common chronic disease develop a personal sense of vulnerability that is informed by the salience of their family history and interpreted within their personal models of disease causation and inheritance. Features that give meaning to familial risk may be perceived differently by patients and professionals. This review identifies key areas for health professionals to explore with patients that may improve the effectiveness of communication about disease risk and management.

Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications.

PubMed

Le, Duc V; Nguyen, Thuong; Scholten, Hans; Havinga, Paul J M

2017-11-29

Energy consumption is a critical performance and user experience metric when developing mobile sensing applications, especially with the significantly growing number of sensing applications in recent years. As proposed a decade ago when mobile applications were still not popular and most mobile operating systems were single-tasking, conventional sensing paradigms such as opportunistic sensing and participatory sensing do not explore the relationship among concurrent applications for energy-intensive tasks. In this paper, inspired by social relationships among living creatures in nature, we propose a symbiotic sensing paradigm that can conserve energy, while maintaining equivalent performance to existing paradigms. The key idea is that sensing applications should cooperatively perform common tasks to avoid acquiring the same resources multiple times. By doing so, this sensing paradigm executes sensing tasks with very little extra resource consumption and, consequently, extends battery life. To evaluate and compare the symbiotic sensing paradigm with the existing ones, we develop mathematical models in terms of the completion probability and estimated energy consumption. The quantitative evaluation results using various parameters obtained from real datasets indicate that symbiotic sensing performs better than opportunistic sensing and participatory sensing in large-scale sensing applications, such as road condition monitoring, air pollution monitoring, and city noise monitoring.

Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications

PubMed Central

Scholten, Hans; Havinga, Paul J. M.

2017-01-01

Energy consumption is a critical performance and user experience metric when developing mobile sensing applications, especially with the significantly growing number of sensing applications in recent years. As proposed a decade ago when mobile applications were still not popular and most mobile operating systems were single-tasking, conventional sensing paradigms such as opportunistic sensing and participatory sensing do not explore the relationship among concurrent applications for energy-intensive tasks. In this paper, inspired by social relationships among living creatures in nature, we propose a symbiotic sensing paradigm that can conserve energy, while maintaining equivalent performance to existing paradigms. The key idea is that sensing applications should cooperatively perform common tasks to avoid acquiring the same resources multiple times. By doing so, this sensing paradigm executes sensing tasks with very little extra resource consumption and, consequently, extends battery life. To evaluate and compare the symbiotic sensing paradigm with the existing ones, we develop mathematical models in terms of the completion probability and estimated energy consumption. The quantitative evaluation results using various parameters obtained from real datasets indicate that symbiotic sensing performs better than opportunistic sensing and participatory sensing in large-scale sensing applications, such as road condition monitoring, air pollution monitoring, and city noise monitoring. PMID:29186037

Sensors with centroid-based common sensing scheme and their multiplexing

NASA Astrophysics Data System (ADS)

Berkcan, Ertugrul; Tiemann, Jerome J.; Brooksby, Glen W.

1993-03-01

The ability to multiplex sensors with different measurands but with a common sensing scheme is of importance in aircraft and aircraft engine applications; this unification of the sensors into a common interface has major implications for weight, cost, and reliability. A new class of sensors based on a common sensing scheme and their E/O Interface has been developed. The approach detects the location of the centroid of a beam of light; the set of fiber optic sensors with this sensing scheme include linear and rotary position, temperature, pressure, as well as duct Mach number. The sensing scheme provides immunity to intensity variations of the source or due to environmental effects on the fiber. A detector spatially multiplexed common electro-optic interface for the sensors has been demonstrated with a position and a temperature sensor.

First-rank symptoms in schizophrenia: reexamining mechanisms of self-recognition.

PubMed

Waters, Flavie A V; Badcock, Johanna C

2010-05-01

Disturbances of self are a common feature of schizophrenic psychopathology, with patients reporting that their thoughts and actions are controlled by external forces, as shown in first-rank symptoms (FRS). One widely accepted explanatory model of FRS suggests a deficiency in the internal forward model system. Recent studies in the field of cognitive sciences, however, have generated new insights into how complex sensory and motor systems contribute to the sense of self-recognition, and it is becoming clear that the forward model conceptualization does not have unique access to representations about the self. We briefly evaluate the forward model explanation of FRS, reassess the distinction made between the sense of agency and body ownership, and outline recent developments in 4 domains of sensory-motor control that have supplemented our understanding of the processes underlying the sense of self-recognition. The application of these findings to FRS will open up new research directions into the processes underlying these symptoms.

Barriers to Self-Management Behaviors in College Students with Food Allergies

ERIC Educational Resources Information Center

Duncan, Sarah E.; Annunziato, Rachel A.

2018-01-01

Objective: This study examined barriers to engagement in self-management behaviors among food-allergic college students (1) within the frameworks of the health belief model (HBM) and common sense self-regulation model (CS-SRM) and (2) in the context of overall risky behaviors. Participants: Undergraduate college students who reported having a…

Preserving Pelicans with Models That Make Sense

ERIC Educational Resources Information Center

Moore, Tamara J.; Doerr, Helen M.; Glancy, Aran W.; Ntow, Forster D.

2015-01-01

Getting students to think deeply about mathematical concepts is not an easy job, which is why we often use problem-solving tasks to engage students in higher-level mathematical thinking. Mathematical modeling, one of the mathematical practices found in the Common Core State Standards for Mathematics (CCSSM), is a type of problem solving that can…

Proceedings of the 1974 Lyndon B. Johnson Space Center Wheat-Yield Conference

NASA Technical Reports Server (NTRS)

Pitts, D. E.; Barger, G. L.

1975-01-01

The proceedings of the 1974 Lyndon B. Johnson Space Center Wheat-Yield Conference are presented. The state of art of wheat-yield forecasting and the feasibility of incorporating remote sensing into this forecasting were discussed with emphasis on formulating common approach to wheat-yield forecasting, primarily using conventional meteorological measurements, which can later include the various applications of remote sensing. Papers are presented which deal with developments in the field of crop modelling.

Modeling, simulation, and analysis of optical remote sensing systems

NASA Technical Reports Server (NTRS)

Kerekes, John Paul; Landgrebe, David A.

1989-01-01

Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.

Spectrum sensing and resource allocation for multicarrier cognitive radio systems under interference and power constraints

NASA Astrophysics Data System (ADS)

Dikmese, Sener; Srinivasan, Sudharsan; Shaat, Musbah; Bader, Faouzi; Renfors, Markku

2014-12-01

Multicarrier waveforms have been commonly recognized as strong candidates for cognitive radio. In this paper, we study the dynamics of spectrum sensing and spectrum allocation functions in cognitive radio context using very practical signal models for the primary users (PUs), including the effects of power amplifier nonlinearities. We start by sensing the spectrum with energy detection-based wideband multichannel spectrum sensing algorithm and continue by investigating optimal resource allocation methods. Along the way, we examine the effects of spectral regrowth due to the inevitable power amplifier nonlinearities of the PU transmitters. The signal model includes frequency selective block-fading channel models for both secondary and primary transmissions. Filter bank-based wideband spectrum sensing techniques are applied for detecting spectral holes and filter bank-based multicarrier (FBMC) modulation is selected for transmission as an alternative multicarrier waveform to avoid the disadvantage of limited spectral containment of orthogonal frequency-division multiplexing (OFDM)-based multicarrier systems. The optimization technique used for the resource allocation approach considered in this study utilizes the information obtained through spectrum sensing and knowledge of spectrum leakage effects of the underlying waveforms, including a practical power amplifier model for the PU transmitter. This study utilizes a computationally efficient algorithm to maximize the SU link capacity with power and interference constraints. It is seen that the SU transmission capacity depends critically on the spectral containment of the PU waveform, and these effects are quantified in a case study using an 802.11-g WLAN scenario.

Investigating the relationship between tree heights derived from SIBBORK forest model and remote sensing measurements

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Feliciano, E. A.; Armstrong, A. H.; Sun, G.; Montesano, P.; Ranson, K.

2017-12-01

Tree heights are one of the most commonly used remote sensing parameters to measure biomass of a forest. In this project, we investigate the relationship between remotely sensed tree heights (e.g. G-LiHT lidar and commercially available high resolution satellite imagery, HRSI) and the SIBBORK modeled tree heights. G-LiHT is a portable, airborne imaging system that simultaneously maps the composition, structure, and function of terrestrial ecosystems using lidar, imaging spectroscopy and thermal mapping. Ground elevation and canopy height models were generated using the lidar data acquired in 2012. A digital surface model was also generated using the HRSI technique from the commercially available WorldView data in 2016. The HRSI derived height and biomass products are available at the plot (10x10m) level. For this study, we parameterized the SIBBORK individual-based gap model for Howland forest, Maine. The parameterization was calibrated using field data for the study site and results show that the simulated forest reproduces the structural complexity of Howland old growth forest, based on comparisons of key variables including, aboveground biomass, forest height and basal area. Furthermore carbon cycle and ecosystem observational capabilities will be enhanced over the next 6 years via the launch of two LiDAR (NASA's GEDI and ICESAT 2) and two SAR (NASA's ISRO NiSAR and ESA's Biomass) systems. Our aim is to present the comparison of canopy height models obtained with SIBBORK forest model and remote sensing techniques, highlighting the synergy between individual-based forest modeling and high-resolution remote sensing.

Dealing with Diversity: On the Uses of Common Sense in Descartes and Montaigne

ERIC Educational Resources Information Center

De Marzio, Darryl M.

2010-01-01

This essay attempts to retrieve the notion of "common sense" within the writings of Descartes and Montaigne. I suggest that both writers represent distinct traditions in which the notion is employed. Descartes represents a modernist tradition in which common sense is understood to be a cognitive faculty, while Montaigne represents a humanist…

Exploring Sense of Community in a University Common Book Program

ERIC Educational Resources Information Center

Ferguson, Kristen; Brown, Natalya; Piper, Linda

2015-01-01

Many post-secondary common book programs purport to increase a sense of community on campus. This study explored whether a common book program at a Canadian university was able to create a sense of community among students. Results indicate that in-class discussions about the book, liking the Facebook page, attending the author lecture, and…

The Rise and Fall of Boot Camps: A Case Study in Common-Sense Corrections

ERIC Educational Resources Information Center

Cullen, Francis T.; Blevins, Kristie R.; Trager, Jennifer S.; Gendreau, Paul

2005-01-01

"Common sense" is often used as a powerful rationale for implementing correctional programs that have no basis in criminology and virtually no hope of reducing recidivism. Within this context, we undertake a case study in "common-sense' corrections by showing how the rise of boot camps, although having multiple causes, was ultimately legitimized…

Revisiting "The Master's Tools": Challenging Common Sense in Cross-Cultural Teacher Education

ERIC Educational Resources Information Center

Chinnery, Ann

2008-01-01

According to Kevin Kumashiro (2004), education toward a socially just society requires a commitment to challenge common sense notions or assumptions about the world and about teaching and learning. Recalling Audre Lorde's (1984) classic essay, "The Master's Tools Will Never Dismantle the Master's House," I focus on three common sense notions and…

Scientists' sense making when hypothesizing about disease mechanisms from expression data and their needs for visualization support.

PubMed

Mirel, Barbara; Görg, Carsten

2014-04-26

A common class of biomedical analysis is to explore expression data from high throughput experiments for the purpose of uncovering functional relationships that can lead to a hypothesis about mechanisms of a disease. We call this analysis expression driven, -omics hypothesizing. In it, scientists use interactive data visualizations and read deeply in the research literature. Little is known, however, about the actual flow of reasoning and behaviors (sense making) that scientists enact in this analysis, end-to-end. Understanding this flow is important because if bioinformatics tools are to be truly useful they must support it. Sense making models of visual analytics in other domains have been developed and used to inform the design of useful and usable tools. We believe they would be helpful in bioinformatics. To characterize the sense making involved in expression-driven, -omics hypothesizing, we conducted an in-depth observational study of one scientist as she engaged in this analysis over six months. From findings, we abstracted a preliminary sense making model. Here we describe its stages and suggest guidelines for developing visualization tools that we derived from this case. A single case cannot be generalized. But we offer our findings, sense making model and case-based tool guidelines as a first step toward increasing interest and further research in the bioinformatics field on scientists' analytical workflows and their implications for tool design.

Scientists’ sense making when hypothesizing about disease mechanisms from expression data and their needs for visualization support

PubMed Central

2014-01-01

A common class of biomedical analysis is to explore expression data from high throughput experiments for the purpose of uncovering functional relationships that can lead to a hypothesis about mechanisms of a disease. We call this analysis expression driven, -omics hypothesizing. In it, scientists use interactive data visualizations and read deeply in the research literature. Little is known, however, about the actual flow of reasoning and behaviors (sense making) that scientists enact in this analysis, end-to-end. Understanding this flow is important because if bioinformatics tools are to be truly useful they must support it. Sense making models of visual analytics in other domains have been developed and used to inform the design of useful and usable tools. We believe they would be helpful in bioinformatics. To characterize the sense making involved in expression-driven, -omics hypothesizing, we conducted an in-depth observational study of one scientist as she engaged in this analysis over six months. From findings, we abstracted a preliminary sense making model. Here we describe its stages and suggest guidelines for developing visualization tools that we derived from this case. A single case cannot be generalized. But we offer our findings, sense making model and case-based tool guidelines as a first step toward increasing interest and further research in the bioinformatics field on scientists’ analytical workflows and their implications for tool design. PMID:24766796

A Web Service-Based Framework Model for People-Centric Sensing Applications Applied to Social Networking

PubMed Central

Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

2012-01-01

As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users’ activities and locations, sharing this information amongst the user’s friends within a social networking site. We also present some screenshot results of our experimental prototype. PMID:22438732

A Web Service-based framework model for people-centric sensing applications applied to social networking.

PubMed

Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

2012-01-01

As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users' activities and locations, sharing this information amongst the user's friends within a social networking site. We also present some screenshot results of our experimental prototype.

Correlation between Knowledge, Experience and Common Sense, with Critical Thinking Capability of Medical Faculty's Students at Indonesia Christian University

ERIC Educational Resources Information Center

Nadeak, Bernadetha

2015-01-01

This research discusses correlation between knowledge, experience and common sense with critical thinking of Medical Faculty's Student. As to the objective of this research is to find the correlation between knowledge, experience and common sense with critical thinking of Medical Faculty's Students at Christian University of Indonesia. It is…

Acute oxygen sensing by the carotid body: from mitochondria to plasma membrane.

PubMed

Chang, Andy J

2017-11-01

Maintaining oxygen homeostasis is crucial to the survival of animals. Mammals respond acutely to changes in blood oxygen levels by modulating cardiopulmonary function. The major sensor of blood oxygen that regulates breathing is the carotid body (CB), a small chemosensory organ located at the carotid bifurcation. When arterial blood oxygen levels drop in hypoxia, neuroendocrine cells in the CB called glomus cells are activated to signal to afferent nerves that project to the brain stem. The mechanism by which hypoxia stimulates CB sensory activity has been the subject of many studies over the past 90 years. Two discrete models emerged that argue for the seat of oxygen sensing to lie either in the plasma membrane or mitochondria of CB cells. Recent studies are bridging the gap between these models by identifying hypoxic signals generated by changes in mitochondrial function in the CB that can be sensed by plasma membrane proteins on glomus cells. The CB is important for physiological adaptation to hypoxia, and its dysfunction contributes to sympathetic hyperactivity in common conditions such as sleep-disordered breathing, chronic heart failure, and insulin resistance. Understanding the basic mechanism of oxygen sensing in the CB could allow us to develop strategies to target this organ for therapy. In this short review, I will describe two historical models of CB oxygen sensing and new findings that are integrating these models. Copyright © 2017 the American Physiological Society.

Representation of illness in Familial Amyloidotic Polyneuropathy Portuguese Association newspaper: A documental study.

PubMed

Novais, Sónia Alexandra de Lemos; Mendes, Felismina Rosa Parreira

2016-03-01

This study explores illness representations within Familial Amyloidotic Polyneuropathy Portuguese Association newspaper . A content analysis was performed of the issue data using provisional coding related to the conceptual framework of the study. All dimensions of illness representation in Leventhal's Common Sense Model of illness cognitions and behaviors are present in the data and reflect the experience of living with this disease. Understanding how a person living with an hereditary, rare, neurodegenerative illness is important for developing community nursing interventions. In conclusion, we suggest an integration of common sense knowledge with other approaches for designing an intervention program centered on people living with an hereditary neurodegenerative illness, such as familial amyloidotic polyneuropathy. © 2015 Wiley Publishing Asia Pty Ltd.

The Limits of Role Modeling as a Basis for Critical Multicultural Education: The Case of Black Male Teachers in Urban Schools

ERIC Educational Resources Information Center

Martino, Wayne J.

2015-01-01

This article provides a critical analysis of the political significance of role modelling as it relates to envisaging a critical multicultural approach to educational reform. While not rejecting role modelling outright, it calls for a commitment to questioning the limits of common sense understandings that underpin the logic of gender and racial…

Exploring Yellowstone National Park with Mathematical Modeling

ERIC Educational Resources Information Center

Wickstrom, Megan H.; Carr, Ruth; Lackey, Dacia

2017-01-01

Mathematical modeling, a practice standard in the Common Core State Standards for Mathematics (CCSSM) (CCSSI 2010), is a process by which students develop and use mathematics as a tool to make sense of the world around them. Students investigate a real-world situation by asking mathematical questions; along the way, they need to decide how to use…

The Impact of Intimate Partner Violence on Decisions to Leave Dating Relationships: A Test of the Investment Model

ERIC Educational Resources Information Center

Rhatigan, Deborah L.; Street, Amy E.

2005-01-01

This study explored the impact of violence exposure on investment-model constructs within a sample of college women involved in heterosexual dating relationships. Results generally supported the "common sense" hypothesis, suggesting that violence negatively impacts satisfaction for and commitment to one's relationship and is positively associated…

Leading the Common Core State Standards: From Common Sense to Common Practice

ERIC Educational Resources Information Center

Dunkle, Cheryl A.

2012-01-01

Many educators agree that we already know how to foster student success, so what is keeping common sense from becoming common practice? The author provides step-by-step guidance for overcoming the barriers to adopting the Common Core State Standards (CCSS) and achieving equity and excellence for all students. As an experienced teacher and…

Intelligent Detection of Structure from Remote Sensing Images Based on Deep Learning Method

NASA Astrophysics Data System (ADS)

Xin, L.

2018-04-01

Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.

Quorum Sensing Gene Regulation by LuxR/HapR Master Regulators in Vibrios

PubMed Central

Ball, Alyssa S.; Chaparian, Ryan R.

2017-01-01

ABSTRACT The coordination of group behaviors in bacteria is accomplished via the cell-cell signaling process called quorum sensing. Vibrios have historically been models for studying bacterial communication due to the diverse and remarkable behaviors controlled by quorum sensing in these bacteria, including bioluminescence, type III and type VI secretion, biofilm formation, and motility. Here, we discuss the Vibrio LuxR/HapR family of proteins, the master global transcription factors that direct downstream gene expression in response to changes in cell density. These proteins are structurally similar to TetR transcription factors but exhibit distinct biochemical and genetic features from TetR that determine their regulatory influence on the quorum sensing gene network. We review here the gene groups regulated by LuxR/HapR and quorum sensing and explore the targets that are common and unique among Vibrio species. PMID:28484045

Adequacy of satellite derived rainfall data for stream flow modeling

USGS Publications Warehouse

Artan, G.; Gadain, Hussein; Smith, Jodie; Asante, Kwasi; Bandaragoda, C.J.; Verdin, J.P.

2007-01-01

Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated. ?? Springer Science+Business Media, Inc. 2007.

Commonsense Geography.

ERIC Educational Resources Information Center

McHoul, Alec

1990-01-01

Presents an ethnomethodological study of how Australian high school geography teachers and students rely on common sense knowledge and reasoning to facilitate learning. Analyzes portions of transcripts from a class activity in which students built a scale model of a city. Explains location categorization devices, illustrating how learning involves…

Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research

USGS Publications Warehouse

Maxwell, S.K.; Meliker, J.R.; Goovaerts, P.

2010-01-01

In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.

A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling

NASA Astrophysics Data System (ADS)

Dorigo, W. A.; Zurita-Milla, R.; de Wit, A. J. W.; Brazile, J.; Singh, R.; Schaepman, M. E.

2007-05-01

During the last 50 years, the management of agroecosystems has been undergoing major changes to meet the growing demand for food, timber, fibre and fuel. As a result of this intensified use, the ecological status of many agroecosystems has been severely deteriorated. Modeling the behavior of agroecosystems is, therefore, of great help since it allows the definition of management strategies that maximize (crop) production while minimizing the environmental impacts. Remote sensing can support such modeling by offering information on the spatial and temporal variation of important canopy state variables which would be very difficult to obtain otherwise. In this paper, we present an overview of different methods that can be used to derive biophysical and biochemical canopy state variables from optical remote sensing data in the VNIR-SWIR regions. The overview is based on an extensive literature review where both statistical-empirical and physically based methods are discussed. Subsequently, the prevailing techniques of assimilating remote sensing data into agroecosystem models are outlined. The increasing complexity of data assimilation methods and of models describing agroecosystem functioning has significantly increased computational demands. For this reason, we include a short section on the potential of parallel processing to deal with the complex and computationally intensive algorithms described in the preceding sections. The studied literature reveals that many valuable techniques have been developed both for the retrieval of canopy state variables from reflective remote sensing data as for assimilating the retrieved variables in agroecosystem models. However, for agroecosystem modeling and remote sensing data assimilation to be commonly employed on a global operational basis, emphasis will have to be put on bridging the mismatch between data availability and accuracy on one hand, and model and user requirements on the other. This could be achieved by integrating imagery with different spatial, temporal, spectral, and angular resolutions, and the fusion of optical data with data of different origin, such as LIDAR and radar/microwave.

Compressed sampling and dictionary learning framework for wavelength-division-multiplexing-based distributed fiber sensing.

PubMed

Weiss, Christian; Zoubir, Abdelhak M

2017-05-01

We propose a compressed sampling and dictionary learning framework for fiber-optic sensing using wavelength-tunable lasers. A redundant dictionary is generated from a model for the reflected sensor signal. Imperfect prior knowledge is considered in terms of uncertain local and global parameters. To estimate a sparse representation and the dictionary parameters, we present an alternating minimization algorithm that is equipped with a preprocessing routine to handle dictionary coherence. The support of the obtained sparse signal indicates the reflection delays, which can be used to measure impairments along the sensing fiber. The performance is evaluated by simulations and experimental data for a fiber sensor system with common core architecture.

Common and Innovative Visuals: A sparsity modeling framework for video.

PubMed

Abdolhosseini Moghadam, Abdolreza; Kumar, Mrityunjay; Radha, Hayder

2014-05-02

Efficient video representation models are critical for many video analysis and processing tasks. In this paper, we present a framework based on the concept of finding the sparsest solution to model video frames. To model the spatio-temporal information, frames from one scene are decomposed into two components: (i) a common frame, which describes the visual information common to all the frames in the scene/segment, and (ii) a set of innovative frames, which depicts the dynamic behaviour of the scene. The proposed approach exploits and builds on recent results in the field of compressed sensing to jointly estimate the common frame and the innovative frames for each video segment. We refer to the proposed modeling framework by CIV (Common and Innovative Visuals). We show how the proposed model can be utilized to find scene change boundaries and extend CIV to videos from multiple scenes. Furthermore, the proposed model is robust to noise and can be used for various video processing applications without relying on motion estimation and detection or image segmentation. Results for object tracking, video editing (object removal, inpainting) and scene change detection are presented to demonstrate the efficiency and the performance of the proposed model.

An anthropological exploration of contemporary bioethics: the varieties of common sense.

PubMed

Turner, L

1998-04-01

Patients and physicians can inhabit distinctive social worlds where they are guided by diverse understandings of moral practice. Despite the contemporary presence of multiple moral traditions, religious communities and ethnic backgrounds, two of the major methodological approaches in bioethics, casuistry and principlism, rely upon the notion of a common morality. However, the heterogeneity of ethnic, moral, and religious traditions raises questions concerning the singularity of common sense. Indeed, it might be more appropriate to consider plural traditions of moral reasoning. This poses a considerable challenge for bioethicists because the existence of plural moral traditions can lead to difficulties regarding "closure" in moral reasoning. The topics of truth-telling, informed consent, euthanasia, and brain death and organ transplantation reveal the presence of different understandings of common sense. With regard to these subjects, plural accounts of "common sense" moral reasoning exist.

Number-unconstrained quantum sensing

NASA Astrophysics Data System (ADS)

Mitchell, Morgan W.

2017-12-01

Quantum sensing is commonly described as a constrained optimization problem: maximize the information gained about an unknown quantity using a limited number of particles. Important sensors including gravitational wave interferometers and some atomic sensors do not appear to fit this description, because there is no external constraint on particle number. Here, we develop the theory of particle-number-unconstrained quantum sensing, and describe how optimal particle numbers emerge from the competition of particle-environment and particle-particle interactions. We apply the theory to optical probing of an atomic medium modeled as a resonant, saturable absorber, and observe the emergence of well-defined finite optima without external constraints. The results contradict some expectations from number-constrained quantum sensing and show that probing with squeezed beams can give a large sensitivity advantage over classical strategies when each is optimized for particle number.

Does this interface make my sensor look bad? Basic principles for designing usable, useful interfaces for sensor technology operators

NASA Astrophysics Data System (ADS)

McNamara, Laura A.; Berg, Leif; Butler, Karin; Klein, Laura

2017-05-01

Even as remote sensing technology has advanced in leaps and bounds over the past decade, the remote sensing community lacks interfaces and interaction models that facilitate effective human operation of our sensor platforms. Interfaces that make great sense to electrical engineers and flight test crews can be anxiety-inducing to operational users who lack professional experience in the design and testing of sophisticated remote sensing platforms. In this paper, we reflect on an 18-month collaboration which our Sandia National Laboratory research team partnered with an industry software team to identify and fix critical issues in a widely-used sensor interface. Drawing on basic principles from cognitive and perceptual psychology and interaction design, we provide simple, easily learned guidance for minimizing common barriers to system learnability, memorability, and user engagement.

Mapping Tamarix: New techniques for field measurements, spatial modeling and remote sensing

NASA Astrophysics Data System (ADS)

Evangelista, Paul H.

Native riparian ecosystems throughout the southwestern United States are being altered by the rapid invasion of Tamarix species, commonly known as tamarisk. The effects that tamarisk has on ecosystem processes have been poorly quantified largely due to inadequate survey methods. I tested new approaches for field measurements, spatial models and remote sensing to improve our ability measure and to map tamarisk occurrence, and provide new methods that will assist in management and control efforts. Examining allometric relationships between basal cover and height measurements collected in the field, I was able to produce several models to accurately estimate aboveground biomass. The best two models were explained 97% of the variance (R 2 = 0.97). Next, I tested five commonly used predictive spatial models to identify which methods performed best for tamarisk using different types of data collected in the field. Most spatial models performed well for tamarisk, with logistic regression performing best with an Area Under the receiver-operating characteristic Curve (AUC) of 0.89 and overall accuracy of 85%. The results of this study also suggested that models may not perform equally with different invasive species, and that results may be influenced by species traits and their interaction with environmental factors. Lastly, I tested several approaches to improve the ability to remotely sense tamarisk occurrence. Using Landsat7 ETM+ satellite scenes and derived vegetation indices for six different months of the growing season, I examined their ability to detect tamarisk individually (single-scene analyses) and collectively (time-series). My results showed that time-series analyses were best suited to distinguish tamarisk from other vegetation and landscape features (AUC = 0.96, overall accuracy = 90%). June, August and September were the best months to detect unique phenological attributes that are likely related to the species' extended growing season and green-up during peak growing months. These studies demonstrate that new techniques can further our understanding of tamarisk's impacts on ecosystem processes, predict potential distribution and new invasions, and improve our ability to detect occurrence using remote sensing techniques. Collectively, the results of my studies may increase our ability to map tamarisk distributions and better quantify its impacts over multiple spatial and temporal scales.

An anthropological exploration of contemporary bioethics: the varieties of common sense.

PubMed Central

Turner, L

1998-01-01

Patients and physicians can inhabit distinctive social worlds where they are guided by diverse understandings of moral practice. Despite the contemporary presence of multiple moral traditions, religious communities and ethnic backgrounds, two of the major methodological approaches in bioethics, casuistry and principlism, rely upon the notion of a common morality. However, the heterogeneity of ethnic, moral, and religious traditions raises questions concerning the singularity of common sense. Indeed, it might be more appropriate to consider plural traditions of moral reasoning. This poses a considerable challenge for bioethicists because the existence of plural moral traditions can lead to difficulties regarding "closure" in moral reasoning. The topics of truth-telling, informed consent, euthanasia, and brain death and organ transplantation reveal the presence of different understandings of common sense. With regard to these subjects, plural accounts of "common sense" moral reasoning exist. PMID:9603001

Integrating remote sensing with species distribution models; Mapping tamarisk invasions using the Software for Assisted Habitat Modeling (SAHM)

USGS Publications Warehouse

West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Young, Nicholas E.; Stohlgren, Thomas J.; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan

2016-01-01

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM).

PubMed

West, Amanda M; Evangelista, Paul H; Jarnevich, Catherine S; Young, Nicholas E; Stohlgren, Thomas J; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan

2016-10-11

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

Black on White: A Common Sense Approach

ERIC Educational Resources Information Center

Munn, Carol

1972-01-01

Carol Munn makes suggestions for integration based on experience in a large university's residence hall, which may provide some ideas from which a model, suitable to individual needs can be drawn. A comment by J.J. Pietrofesa and D.L. Shappell and a rejoinder by C. Munn follow. (Author/BY)

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links

PubMed Central

Liang, Zhuo-qian

2017-01-01

This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method. PMID:29206188

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links.

PubMed

Liu, Tong; Liang, Zhuo-Qian

2017-12-05

This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method.

Field-effect sensors - from pH sensing to biosensing: sensitivity enhancement using streptavidin-biotin as a model system.

PubMed

Lowe, Benjamin M; Sun, Kai; Zeimpekis, Ioannis; Skylaris, Chris-Kriton; Green, Nicolas G

2017-11-06

Field-Effect Transistor sensors (FET-sensors) have been receiving increasing attention for biomolecular sensing over the last two decades due to their potential for ultra-high sensitivity sensing, label-free operation, cost reduction and miniaturisation. Whilst the commercial application of FET-sensors in pH sensing has been realised, their commercial application in biomolecular sensing (termed BioFETs) is hindered by poor understanding of how to optimise device design for highly reproducible operation and high sensitivity. In part, these problems stem from the highly interdisciplinary nature of the problems encountered in this field, in which knowledge of biomolecular-binding kinetics, surface chemistry, electrical double layer physics and electrical engineering is required. In this work, a quantitative analysis and critical review has been performed comparing literature FET-sensor data for pH-sensing with data for sensing of biomolecular streptavidin binding to surface-bound biotin systems. The aim is to provide the first systematic, quantitative comparison of BioFET results for a single biomolecular analyte, specifically streptavidin, which is the most commonly used model protein in biosensing experiments, and often used as an initial proof-of-concept for new biosensor designs. This novel quantitative and comparative analysis of the surface potential behaviour of a range of devices demonstrated a strong contrast between the trends observed in pH-sensing and those in biomolecule-sensing. Potential explanations are discussed in detail and surface-chemistry optimisation is shown to be a vital component in sensitivity-enhancement. Factors which can influence the response, yet which have not always been fully appreciated, are explored and practical suggestions are provided on how to improve experimental design.

Justifying group-specific common morality.

PubMed

Strong, Carson

2008-01-01

Some defenders of the view that there is a common morality have conceived such morality as being universal, in the sense of extending across all cultures and times. Those who deny the existence of such a common morality often argue that the universality claim is implausible. Defense of common morality must take account of the distinction between descriptive and normative claims that there is a common morality. This essay considers these claims separately and identifies the nature of the arguments for each claim. It argues that the claim that there is a universal common morality in the descriptive sense has not been successfully defended to date. It maintains that the claim that there is a common morality in the normative sense need not be understood as universalist. This paper advocates the concept of group specific common morality, including country-specific versions. It suggests that both the descriptive and the normative claims that there are country-specific common moralities are plausible, and that a country-specific normative common morality could provide the basis for a country's bioethics.

Common sense model of mental illness: Understanding the impact of cognitive and emotional representations of mental illness on recovery through the mediation of self-stigma.

PubMed

Chan, Randolph C H; Mak, Winnie W S

2016-12-30

The present study applied the common sense model to understand the underlying mechanism of how cognitive and emotional representations of mental illness among people in recovery of mental illness would impact their endorsement of self-stigma, and how that would, in turn, affect clinical and personal recovery. A cross-sectional survey was administered to 376 people in recovery. Participants were recruited from seven public specialty outpatient clinics and substance abuse assessment clinics across various districts in Hong Kong. They were asked to report their perception towards their mental illness, self-stigma, symptom severity, and personal recovery. The results of structural equation modeling partially supported the hypothesized mediation model indicating that controllability, consequences, and emotional concern of mental illness, but not cause, timeline, and identity, were associated with self-stigma, which was subsequently negatively associated with clinical and personal recovery. The present study demonstrated the mediating role of self-stigma in the relationship between individuals' illness representations towards their mental illness and their recovery. Illness management programs aimed at addressing the maladaptive mental illness-related beliefs and emotions are recommended. Implications on developing self-directed and empowering mental health services are discussed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Common Sense Initiative’s Recommendation on Cathode Ray Tube (CRT) Glass-to-Glass

EPA Pesticide Factsheets

From 1994 through 1998, EPA’s Common Sense Initiative (CSI) Computers and Electronics Subcommittee (CES) formed a workgroup to examine regulatory barriers to pollution prevention and electronic waste recycling.

A one- and two-layer model for estimating evapotranspiration with remotely sensed surface temperature and ground-based meteorological data over partial canopy cover

NASA Technical Reports Server (NTRS)

Kustas, William P.; Choudhury, Bhaskar J.; Kunkel, Kenneth E.

1989-01-01

Surface-air temperature differences are commonly used in a bulk resistance equation for estimating sensible heat flux (H), which is inserted in the one-dimensional energy balance equation to solve for the latent heat flux (LE) as a residual. Serious discrepancies between estimated and measured LE have been observed for partial-canopy-cover conditions, which are mainly attributed to inappropriate estimates of H. To improve the estimates of H over sparse canopies, one- and two-layer resistance models that account for some of the factors causing poor agreement are developed. The utility of the two models is tested with remotely sensed and micrometeorological data for a furrowed cotton field with 20 percent cover and a dry soil surface. It is found that the one-layer model performs better than the two-layer model when a theoretical bluff-body correction for heat transfer is used instead of an empirical adjustment; otherwise, the two-layer model is better.

Human Facial Shape and Size Heritability and Genetic Correlations.

PubMed

Cole, Joanne B; Manyama, Mange; Larson, Jacinda R; Liberton, Denise K; Ferrara, Tracey M; Riccardi, Sheri L; Li, Mao; Mio, Washington; Klein, Ophir D; Santorico, Stephanie A; Hallgrímsson, Benedikt; Spritz, Richard A

2017-02-01

The human face is an array of variable physical features that together make each of us unique and distinguishable. Striking familial facial similarities underscore a genetic component, but little is known of the genes that underlie facial shape differences. Numerous studies have estimated facial shape heritability using various methods. Here, we used advanced three-dimensional imaging technology and quantitative human genetics analysis to estimate narrow-sense heritability, heritability explained by common genetic variation, and pairwise genetic correlations of 38 measures of facial shape and size in normal African Bantu children from Tanzania. Specifically, we fit a linear mixed model of genetic relatedness between close and distant relatives to jointly estimate variance components that correspond to heritability explained by genome-wide common genetic variation and variance explained by uncaptured genetic variation, the sum representing total narrow-sense heritability. Our significant estimates for narrow-sense heritability of specific facial traits range from 28 to 67%, with horizontal measures being slightly more heritable than vertical or depth measures. Furthermore, for over half of facial traits, >90% of narrow-sense heritability can be explained by common genetic variation. We also find high absolute genetic correlation between most traits, indicating large overlap in underlying genetic loci. Not surprisingly, traits measured in the same physical orientation (i.e., both horizontal or both vertical) have high positive genetic correlations, whereas traits in opposite orientations have high negative correlations. The complex genetic architecture of facial shape informs our understanding of the intricate relationships among different facial features as well as overall facial development. Copyright © 2017 by the Genetics Society of America.

Computational Studies of pH Sensing Design Principles in Proteins

NASA Astrophysics Data System (ADS)

Garrido Ruiz, Diego

Changes in pH are important regulatory signals for biological function, under physiological and pathological conditions. Recent advances in computer simulations strategies have made the exploration of the effects of charge titrations on protein function possible. In this work, I make use of these strategies to investigate the thermodynamic coupling between conformation and protonation states that give rise to pH-dependent function. As motivation for the rest of the work, I start by presenting a collaborative investigation on a pH-sensing mutant of the EGFR tyrosine kinase common to a set of distinct cancers. From then, I reduce the complexity of the systems under study to build models where exact enumeration of states is possible to inquire about the nature of the couplings between protonation states and conformation. Finally, I discuss detailed simulations of pH-sensing proteins for which I use the expectations and insights generated with simple models to identify and interpret couplings of interest for pH-dependent behavior.

Effects of radiation upon the light-sensing elements of the retina as characterized by scanning electron microscopy

NASA Technical Reports Server (NTRS)

Malachowski, M. J.; Tobias, C. A.; Leith, J. T.

1977-01-01

A model system using Necturus maculosus, the common mudpuppy, was established for evaluating effects of radiation upon the light-sensing elements of the retina. Accelerated heavy ions of helium and neon from the Berkeley Bevalac were used. A number of criteria were chosen to characterize radiation damage by observing morphological changes with the scanning electron microscope. The studies indicated retina sensitivity to high-LET (neon) particles at radiation levels below 10 rads (7 particles per visual element) whereas no significant effects were seen from fast helium ions below 50 rads.

Probing Student Teachers' Subject Content Knowledge in Chemistry: Case Studies Using Dynamic Computer Models

ERIC Educational Resources Information Center

Toplis, Rob

2008-01-01

This paper reports case study research into the knowledge and understanding of chemistry for six secondary science student teachers. It combines innovative student-generated computer animations, using "ChemSense" software, with interviews to probe understanding of four common chemical processes used in the secondary school curriculum. Findings…

Properties of Endogenous Post-Stratified Estimation using remote sensing data

Treesearch

John Tipton; Jean Opsomer; Gretchen Moisen

2013-01-01

Post-stratification is commonly used to improve the precision of survey estimates. In traditional poststratification methods, the stratification variable must be known at the population level. When suitable covariates are available at the population level, an alternative approach consists of fitting a model on the covariates, making predictions for the population and...

Fracking: Drilling into Math and Social Justice

ERIC Educational Resources Information Center

Hendrickson, Katie A.

2015-01-01

Mathematical modeling, a focus of the Common Core State Standards for School Mathematics (CCSSI 2010) and one of the Standards for Mathematical Practice, is generally considered to be the process of exploring a real-world situation and making sense of it using mathematics (Lesh and Zawojewski 2007). Teachers need to create opportunities for…

Trying Three-Act Tasks with Primary Students

ERIC Educational Resources Information Center

Lomax, Kendra; Alfonzo, Kristin; Dietz, Sarah; Kleyman, Ellen; Kazemi, Elham

2017-01-01

The goals of problem-solving activities in the elementary grades often include making sense of story problems, developing a range of strategies, and reaching accurate solutions. These are important mathematical aims, but they do not fully address the demands of modeling with mathematics as described in the fourth of the Common Core's eight…

Research: Reflecting Practice. Papers from the SCUTREA Annual Conference (23rd, Manchester, England, July 6-8, 1993).

ERIC Educational Resources Information Center

Miller, Nod, Ed.; Jones, David J., Ed.

The following papers are included: "Social Classification of Women's Work" (Benn, Burton); "Developing Models of Learning from Experience" (Boud, Walker); "'Research Reflecting Practice?'" (Edwards, Usher); "Metaphors and Their Implications for Research and Practice in Adult and Community Education" (Hunt); "'Common-Sense' Approach to Reflection"…

Forum: The challenge of global change

NASA Astrophysics Data System (ADS)

Roederer, Juan G.

1990-09-01

How can we sustain a public sense of the common danger of global change while remaining honest in view of the realities of scientific uncertainty? How can we nurture this sense of common danger without making statements based on half-baked ideas, statistically unreliable results, or oversimplified models? How can we strike a balance between the need to overstate a case to attract the attention of the media and the obligation to adhere strictly to the ethos of science?The task of achieving a scientific understanding of the inner workings of the terrestrial environment is one of the most difficult and ambitious endeavors of humankind. It is full of traps, temptations and deceptions for the participating scientists. We are dealing with a horrendously complex, strongly interactive, highly non-linear system. Lessons learned from disciplines such as plasma physics and solid state physics which have been dealing with complex non-linear systems for decades, are not very encouraging. The first thing one learns is that there are intrinsic, physical limits to the quantitative predictability of a complex system that have nothing to do with the particular techniques employed to model it.

Use of Common-Sense Knowledge, Language and Reality in Mathematical Word Problem Solving

ERIC Educational Resources Information Center

Sepeng, Percy

2014-01-01

The study reported in this article sought to explore and observe how grade 9 learners solve real-wor(l)d problems (a) without real context and (b) without real meaning. Learners' abilities to make sense of the decontextualised word problems set in the real world were investigated with regard to learners' use of common sense in relation to problem…

Luminescent sensing and imaging of oxygen: Fierce competition to the Clark electrode

PubMed Central

2015-01-01

Luminescence‐based sensing schemes for oxygen have experienced a fast growth and are in the process of replacing the Clark electrode in many fields. Unlike electrodes, sensing is not limited to point measurements via fiber optic microsensors, but includes additional features such as planar sensing, imaging, and intracellular assays using nanosized sensor particles. In this essay, I review and discuss the essentials of (i) common solid‐state sensor approaches based on the use of luminescent indicator dyes and host polymers; (ii) fiber optic and planar sensing schemes; (iii) nanoparticle‐based intracellular sensing; and (iv) common spectroscopies. Optical sensors are also capable of multiple simultaneous sensing (such as O2 and temperature). Sensors for O2 are produced nowadays in large quantities in industry. Fields of application include sensing of O2 in plant and animal physiology, in clinical chemistry, in marine sciences, in the chemical industry and in process biotechnology. PMID:26113255

Sentiment Analysis Using Common-Sense and Context Information

PubMed Central

Mittal, Namita; Bansal, Pooja; Garg, Sonal

2015-01-01

Sentiment analysis research has been increasing tremendously in recent times due to the wide range of business and social applications. Sentiment analysis from unstructured natural language text has recently received considerable attention from the research community. In this paper, we propose a novel sentiment analysis model based on common-sense knowledge extracted from ConceptNet based ontology and context information. ConceptNet based ontology is used to determine the domain specific concepts which in turn produced the domain specific important features. Further, the polarities of the extracted concepts are determined using the contextual polarity lexicon which we developed by considering the context information of a word. Finally, semantic orientations of domain specific features of the review document are aggregated based on the importance of a feature with respect to the domain. The importance of the feature is determined by the depth of the feature in the ontology. Experimental results show the effectiveness of the proposed methods. PMID:25866505

Sentiment analysis using common-sense and context information.

PubMed

Agarwal, Basant; Mittal, Namita; Bansal, Pooja; Garg, Sonal

2015-01-01

Sentiment analysis research has been increasing tremendously in recent times due to the wide range of business and social applications. Sentiment analysis from unstructured natural language text has recently received considerable attention from the research community. In this paper, we propose a novel sentiment analysis model based on common-sense knowledge extracted from ConceptNet based ontology and context information. ConceptNet based ontology is used to determine the domain specific concepts which in turn produced the domain specific important features. Further, the polarities of the extracted concepts are determined using the contextual polarity lexicon which we developed by considering the context information of a word. Finally, semantic orientations of domain specific features of the review document are aggregated based on the importance of a feature with respect to the domain. The importance of the feature is determined by the depth of the feature in the ontology. Experimental results show the effectiveness of the proposed methods.

A health hierarchy of effects model: a synthesis of advertising and health hierarchy conceptualizations.

PubMed

Rouse, R A

1991-01-01

Work by both advertising and health researchers has independently yielded hierarchy of effects models which can be used to predict campaign success. Unfortunately, however, previous work has been criticized as "common sense" approaches which are more "assumed" than "proven." This analysis argues that much of the problem is due to the lack of precision often associated with over-simplified "uni-dimensional" models. Instead, this perspective synthesized a "two-dimensional" health hierarchy of effects model and outlines a pragmatic strategy for campaign measurement.

Revealing livestock effects on bunchgrass vegetation with Landsat ETM+ data across a grazing season

NASA Astrophysics Data System (ADS)

Jansen, Vincent S.

Remote sensing provides monitoring solutions for more informed grazing management. To investigate the ability to detect the effects of cattle grazing on bunchgrass vegetation with Landsat Enhanced Thematic Mapper Plus (ETM+) data, we conducted a study on the Zumwalt Prairie in northeastern Oregon across a gradient of grazing intensities. Biophysical vegetation data was collected on vertical structure, biomass, and cover at three different time periods during the grazing season: June, August, and October 2012. To relate these measures to the remotely sensed Landsat ETM+ data, Pearson's correlations and multiple regression models were computed. Using the best models, predicted vegetation metrics were then mapped across the study area. Results indicated that models using common vegetation indices had the ability to discern different levels of grazing across the study area. Results can be distributed to land managers to help guide grassland conservation by improving monitoring of bunchgrass vegetation for sustainable livestock management.

Primary Respiratory Chain Disease Causes Tissue-Specific Dysregulation of the Global Transcriptome and Nutrient-Sensing Signaling Network

PubMed Central

Zhang, Zhe; Tsukikawa, Mai; Peng, Min; Polyak, Erzsebet; Nakamaru-Ogiso, Eiko; Ostrovsky, Julian; McCormack, Shana; Place, Emily; Clarke, Colleen; Reiner, Gail; McCormick, Elizabeth; Rappaport, Eric; Haas, Richard; Baur, Joseph A.; Falk, Marni J.

2013-01-01

Primary mitochondrial respiratory chain (RC) diseases are heterogeneous in etiology and manifestations but collectively impair cellular energy metabolism. Mechanism(s) by which RC dysfunction causes global cellular sequelae are poorly understood. To identify a common cellular response to RC disease, integrated gene, pathway, and systems biology analyses were performed in human primary RC disease skeletal muscle and fibroblast transcriptomes. Significant changes were evident in muscle across diverse RC complex and genetic etiologies that were consistent with prior reports in other primary RC disease models and involved dysregulation of genes involved in RNA processing, protein translation, transport, and degradation, and muscle structure. Global transcriptional and post-transcriptional dysregulation was also found to occur in a highly tissue-specific fashion. In particular, RC disease muscle had decreased transcription of cytosolic ribosomal proteins suggestive of reduced anabolic processes, increased transcription of mitochondrial ribosomal proteins, shorter 5′-UTRs that likely improve translational efficiency, and stabilization of 3′-UTRs containing AU-rich elements. RC disease fibroblasts showed a strikingly similar pattern of global transcriptome dysregulation in a reverse direction. In parallel with these transcriptional effects, RC disease dysregulated the integrated nutrient-sensing signaling network involving FOXO, PPAR, sirtuins, AMPK, and mTORC1, which collectively sense nutrient availability and regulate cellular growth. Altered activities of central nodes in the nutrient-sensing signaling network were validated by phosphokinase immunoblot analysis in RC inhibited cells. Remarkably, treating RC mutant fibroblasts with nicotinic acid to enhance sirtuin and PPAR activity also normalized mTORC1 and AMPK signaling, restored NADH/NAD+ redox balance, and improved cellular respiratory capacity. These data specifically highlight a common pathogenesis extending across different molecular and biochemical etiologies of individual RC disorders that involves global transcriptome modifications. We further identify the integrated nutrient-sensing signaling network as a common cellular response that mediates, and may be amenable to targeted therapies for, tissue-specific sequelae of primary mitochondrial RC disease. PMID:23894440

Accent Priority in a Thai University Context: A Common Sense Revisited

ERIC Educational Resources Information Center

Jindapitak, Naratip; Teo, Adisa

2013-01-01

In Thailand, there has been much debate regarding what accents should be prioritized and adopted as models for learning and use in the context of English language education. However, it is not a debate in which the voices of English learners have sufficiently been heard. Several world Englishes scholars have maintained that being a denationalized…

Plenary Speech: Researching Complex Dynamic Systems--"Retrodictive Qualitative Modelling" in the Language Classroom

ERIC Educational Resources Information Center

Dörnyei, Zoltán

2014-01-01

While approaching second language acquisition from a complex dynamic systems perspective makes a lot of intuitive sense, it is difficult for a number of reasons to operationalise such a dynamic approach in research terms. For example, the most common research paradigms in the social sciences tend to examine variables in relative isolation rather…

The Guerrillas in the Boardroom: What COIN Theory Teaches Leaders about Organizational Change, and How Corporate Change Models Could Transform Military Doctrine

DTIC Science & Technology

2016-09-25

Niccolo Machiavelli, The Prince Introduction The idea that war and unarmed competition are much alike is common. Athletes, especially football players ...... research , Kotter formulated eight steps: (1) Establish a Sense of Urgency, (2) Create a Guiding Coalition, (3) Develop a Change Vision, (4) Communicate a

Predicting Self-Management Behaviors in Familial Hypercholesterolemia Using an Integrated Theoretical Model: the Impact of Beliefs About Illnesses and Beliefs About Behaviors.

PubMed

Hagger, Martin S; Hardcastle, Sarah J; Hingley, Catherine; Strickland, Ella; Pang, Jing; Watts, Gerald F

2016-06-01

Patients with familial hypercholesterolemia (FH) are at markedly increased risk of coronary artery disease. Regular participation in three self-management behaviors, physical activity, healthy eating, and adherence to medication, can significantly reduce this risk in FH patients. We aimed to predict intentions to engage in these self-management behaviors in FH patients using a multi-theory, integrated model that makes the distinction between beliefs about illness and beliefs about self-management behaviors. Using a cross-sectional, correlational design, patients (N = 110) diagnosed with FH from a clinic in Perth, Western Australia, self-completed a questionnaire that measured constructs from three health behavior theories: the common sense model of illness representations (serious consequences, timeline, personal control, treatment control, illness coherence, emotional representations); theory of planned behavior (attitudes, subjective norms, perceived behavioral control); and social cognitive theory (self-efficacy). Structural equation models for each self-management behavior revealed consistent and statistically significant effects of attitudes on intentions across the three behaviors. Subjective norms predicted intentions for health eating only and self-efficacy predicted intentions for physical activity only. There were no effects for the perceived behavioral control and common sense model constructs in any model. Attitudes feature prominently in determining intentions to engage in self-management behaviors in FH patients. The prominence of these attitudinal beliefs about self-management behaviors, as opposed to illness beliefs, suggest that addressing these beliefs may be a priority in the management of FH.

Glucose sensing in the peritoneal space offers faster kinetics than sensing in the subcutaneous space.

PubMed

Burnett, Daniel R; Huyett, Lauren M; Zisser, Howard C; Doyle, Francis J; Mensh, Brett D

2014-07-01

The paramount goal in the treatment of type 1 diabetes is the maintenance of normoglycemia. Continuous glucose monitoring (CGM) technologies enable frequent sensing of glucose to inform exogenous insulin delivery timing and dosages. The most commonly available CGMs are limited by the physiology of the subcutaneous space in which they reside. The very same advantages of this minimally invasive approach are disadvantages with respect to speed. Because subcutaneous blood flow is sensitive to local fluctuations (e.g., temperature, mechanical pressure), subcutaneous sensing can be slow and variable. We propose the use of a more central, physiologically stable body space for CGM: the intraperitoneal space. We compared the temporal response characteristics of simultaneously placed subcutaneous and intraperitoneal sensors during intravenous glucose tolerance tests in eight swine. Using compartmental modeling based on simultaneous intravenous sensing, blood draws, and intraarterial sensing, we found that intraperitoneal kinetics were more than twice as fast as subcutaneous kinetics (mean time constant of 5.6 min for intraperitoneal vs. 12.4 min for subcutaneous). Combined with the known faster kinetics of intraperitoneal insulin delivery over subcutaneous delivery, our findings suggest that artificial pancreas technologies may be optimized by sensing glucose and delivering insulin in the intraperitoneal space. © 2014 by the American Diabetes Association.

Glucose Sensing in the Peritoneal Space Offers Faster Kinetics Than Sensing in the Subcutaneous Space

PubMed Central

Burnett, Daniel R.; Huyett, Lauren M.; Zisser, Howard C.; Doyle, Francis J.

2014-01-01

The paramount goal in the treatment of type 1 diabetes is the maintenance of normoglycemia. Continuous glucose monitoring (CGM) technologies enable frequent sensing of glucose to inform exogenous insulin delivery timing and dosages. The most commonly available CGMs are limited by the physiology of the subcutaneous space in which they reside. The very same advantages of this minimally invasive approach are disadvantages with respect to speed. Because subcutaneous blood flow is sensitive to local fluctuations (e.g., temperature, mechanical pressure), subcutaneous sensing can be slow and variable. We propose the use of a more central, physiologically stable body space for CGM: the intraperitoneal space. We compared the temporal response characteristics of simultaneously placed subcutaneous and intraperitoneal sensors during intravenous glucose tolerance tests in eight swine. Using compartmental modeling based on simultaneous intravenous sensing, blood draws, and intraarterial sensing, we found that intraperitoneal kinetics were more than twice as fast as subcutaneous kinetics (mean time constant of 5.6 min for intraperitoneal vs. 12.4 min for subcutaneous). Combined with the known faster kinetics of intraperitoneal insulin delivery over subcutaneous delivery, our findings suggest that artificial pancreas technologies may be optimized by sensing glucose and delivering insulin in the intraperitoneal space. PMID:24622798

The Concept of Common Sense in Workplace Learning and Experience.

ERIC Educational Resources Information Center

Gerber, Rod

2001-01-01

A phenomenological study of 56 manufacturing workers revealed 7 different conceptions of "common sense" in workplace experiences: gut feeling, innate ability, knowing how, learning, using others purposefully, demonstrable cognitive ability, and personal attributes. These varied conceptions should be taken into account in workplace…

George Combe and common sense.

PubMed

Dyde, Sean

2015-06-01

This article examines the history of two fields of enquiry in late eighteenth- and early nineteenth-century Scotland: the rise and fall of the common sense school of philosophy and phrenology as presented in the works of George Combe. Although many previous historians have construed these histories as separate, indeed sometimes incommensurate, I propose that their paths were intertwined to a greater extent than has previously been given credit. The philosophy of common sense was a response to problems raised by Enlightenment thinkers, particularly David Hume, and spurred a theory of the mind and its mode of study. In order to succeed, or even to be considered a rival of these established understandings, phrenologists adapted their arguments for the sake of engaging in philosophical dispute. I argue that this debate contributed to the relative success of these groups: phrenology as a well-known historical subject, common sense now largely forgotten. Moreover, this history seeks to question the place of phrenology within the sciences of mind in nineteenth-century Britain.

Luminescent sensing and imaging of oxygen: fierce competition to the Clark electrode.

PubMed

Wolfbeis, Otto S

2015-08-01

Luminescence-based sensing schemes for oxygen have experienced a fast growth and are in the process of replacing the Clark electrode in many fields. Unlike electrodes, sensing is not limited to point measurements via fiber optic microsensors, but includes additional features such as planar sensing, imaging, and intracellular assays using nanosized sensor particles. In this essay, I review and discuss the essentials of (i) common solid-state sensor approaches based on the use of luminescent indicator dyes and host polymers; (ii) fiber optic and planar sensing schemes; (iii) nanoparticle-based intracellular sensing; and (iv) common spectroscopies. Optical sensors are also capable of multiple simultaneous sensing (such as O2 and temperature). Sensors for O2 are produced nowadays in large quantities in industry. Fields of application include sensing of O2 in plant and animal physiology, in clinical chemistry, in marine sciences, in the chemical industry and in process biotechnology. © 2015 The Author. Bioessays published by WILEY Periodicals, Inc.

Concept Development and Experimentation Policy and Process: How Analysis Provides Rigour

DTIC Science & Technology

2010-04-01

modelling and simulation techniques, but in reality the main tool in use is common sense and logic. The main goal of OA analyst is to bring forward those...doing so she should distinguish between the ideal and the intended or desired models to approach the reality as much as possible. Subsequently, the...and collection of measurements to be conducted. In doing so the analyst must ensure to distinguish between the actual and the perceived reality . From

Historical review: another 50th anniversary--new periodicities in coiled coils.

PubMed

Gruber, Markus; Lupas, Andrei N

2003-12-01

In 1953, Francis Crick and Linus Pauling both proposed models of supercoiled alpha helices ('coiled coils') for the structure of keratin. These were the first attempts at modelling the tertiary structure of a protein. Crick emphasized the packing mode of the side-chains ('knobs-into-holes'), which required a periodicity of seven residues over two helical turns (7/2) and a supercoil in the opposite sense of the constituent helices. By contrast, Pauling envisaged a broader set of periodicities (4/1, 7/2, 18/5, 15/4, 11/3) and supercoils of both senses. Crick's model became canonical and the 'heptad repeat' essentially synonymous with coiled coils, but 50 years later new crystal structures and protein sequences show that the less common periodicities envisaged by Pauling also occur in coiled coils, adding a variant packing mode ('knobs-to-knobs') to the standard model. Pauling's laboratory notebooks suggest that he searched unsuccessfully for this packing mode in 1953.

Retaking the Test

ERIC Educational Resources Information Center

Backer, David Isaac; Lewis, Tyson Edward

2015-01-01

"Data-driven" teaching and learning is common sense in education today, and it is common sense that these data should come from standardized tests. Critiques of standardization either make no constructive suggestions for what to use in place of the tests or they call for better, more scientifically rigorous, reliable, and…

Thomas Paine's "Common Sense": A Study in Polarity.

ERIC Educational Resources Information Center

Blair, Carole

Thomas Paine's "Common Sense," published in 1776, was a significant rhetorical event, having a polarizing effect on a situation marked by confusion and conflicting loyalties, in which prevailing views favored reconciliation of the American colonies with England. Paine's rhetoric intensified the conflict, forcing a cognitive restructuring…

Expert Testimony, "Regular People," and Public Values: Arguing Common Sense at a Death Penalty Trial.

ERIC Educational Resources Information Center

Chappell, Virginia A.

1995-01-01

Presents a case study of a particular courtroom case dealing with the death penalty. Analyzes the processes and communications of the trial jury. Discusses the interplay of common-sense and expert claims at three crucial stages of the trial. (HB)

An introduction to quantitative remote sensing. [data processing

NASA Technical Reports Server (NTRS)

Lindenlaub, J. C.; Russell, J.

1974-01-01

The quantitative approach to remote sensing is discussed along with the analysis of remote sensing data. Emphasis is placed on the application of pattern recognition in numerically oriented remote sensing systems. A common background and orientation for users of the LARS computer software system is provided.

A Macroecological Analysis of SERA Derived Forest Heights and Implications for Forest Volume Remote Sensing

PubMed Central

Brolly, Matthew; Woodhouse, Iain H.; Niklas, Karl J.; Hammond, Sean T.

2012-01-01

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H100, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H100 and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 102–106 plants/hectare and heights 6–49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H100. PMID:22457800

A macroecological analysis of SERA derived forest heights and implications for forest volume remote sensing.

PubMed

Brolly, Matthew; Woodhouse, Iain H; Niklas, Karl J; Hammond, Sean T

2012-01-01

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H₁₀₀, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H₁₀₀ and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 10²-10⁶ plants/hectare and heights 6-49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H₁₀₀.

Proceedings of the Military Operations Research Society (MORS) Simulation Validation Workshop (SIMVAL II) Held at Alexandria, Virginia on 31 March-2 April 1992

DTIC Science & Technology

1992-04-02

learned . demanded by VV&A. * The CM should maintain a knowl- The cost of configuration manage- edgeable staff that can support ade- ment is increased by of...Carter note: a model before seeing that the results make even the vaguest sense, or learning what ...the argument for paying aspect of the model drives...that person the researcher can find model. Strong teanis have certain things in what are the variables of interest, what will common. They are made up

Organic electrochemical transistors for cell-based impedance sensing

NASA Astrophysics Data System (ADS)

Rivnay, Jonathan; Ramuz, Marc; Leleux, Pierre; Hama, Adel; Huerta, Miriam; Owens, Roisin M.

2015-01-01

Electrical impedance sensing of biological systems, especially cultured epithelial cell layers, is now a common technique to monitor cell motion, morphology, and cell layer/tissue integrity for high throughput toxicology screening. Existing methods to measure electrical impedance most often rely on a two electrode configuration, where low frequency signals are challenging to obtain for small devices and for tissues with high resistance, due to low current. Organic electrochemical transistors (OECTs) are conducting polymer-based devices, which have been shown to efficiently transduce and amplify low-level ionic fluxes in biological systems into electronic output signals. In this work, we combine OECT-based drain current measurements with simultaneous measurement of more traditional impedance sensing using the gate current to produce complex impedance traces, which show low error at both low and high frequencies. We apply this technique in vitro to a model epithelial tissue layer and show that the data can be fit to an equivalent circuit model yielding trans-epithelial resistance and cell layer capacitance values in agreement with literature. Importantly, the combined measurement allows for low biases across the cell layer, while still maintaining good broadband signal.

Common-Sense Chemistry: The Use of Assumptions and Heuristics in Problem Solving

ERIC Educational Resources Information Center

Maeyer, Jenine Rachel

2013-01-01

Students experience difficulty learning and understanding chemistry at higher levels, often because of cognitive biases stemming from common sense reasoning constraints. These constraints can be divided into two categories: assumptions (beliefs held about the world around us) and heuristics (the reasoning strategies or rules used to build…

Moving Forward: Common Sense Policies to Promote Prosperity for Working Texans

ERIC Educational Resources Information Center

Baylor, Don, Jr.

2006-01-01

This report proposes several distinct--yet interrelated--policy opportunities that can move more Texans into the middle class. These proposals blend greater state-level investments with common sense policy changes to increase economic well-being for working Texans. While Texas policy makers have recognized the connection between workforce…

Natural Learning Case Study Archives

ERIC Educational Resources Information Center

Lawler, Robert W.

2015-01-01

Natural Learning Case Study Archives (NLCSA) is a research facility for those interested in using case study analysis to deepen their understanding of common sense knowledge and natural learning (how the mind interacts with everyday experiences to develop common sense knowledge). The database comprises three case study corpora based on experiences…

John Dewey's Dual Theory of Inquiry and Its Value for the Creation of an Alternative Curriculum

ERIC Educational Resources Information Center

Harris, Fred

2014-01-01

Dewey's theory of inquiry cannot be reduced to the pattern of inquiry common to both common-sense inquiry and scientific inquiry, which is grounded in the human life process, since such a reduction ignores Dewey's differentiation of the two forms of inquiry. The difference has to do with the focus of inquiry, with common-sense inquiry…

Hegemony of the "Great Equalizer" and the Fragmentation of Common Sense: A Gramscian Model of Inflated Ambitions for Schooling

ERIC Educational Resources Information Center

Isseks, Jerald

2017-01-01

Increasingly over the past 50 years, the mission statement of schooling in dominant US-American discourse has coalesced around a "Great Equalizer" narrative of education; that is, it has identified schools as the primary means through which individuals can achieve social mobility. In this article, I employ a Gramscian framework to…

Geothermal Target Areas in Colorado as Identified by Remote Sensing Techniques

DOE Data Explorer

Khalid Hussein

2012-02-01

This layer contains the areas identified as targets of potential geothermal activity. The Criteria used to identify the target areas include: hot/warm surface exposures modeled from ASTER/Landsat satellite imagery and geological characteristics, alteration mineral commonly associated with hot springs (clays, Si, and FeOx) modeled from ASTER and Landsat data, Colorado Geological Survey (CGS) known thermal hot springs/wells and heat-flow data points, Colorado deep-seated fault zones, weakened basement identified from isostatic gravity data, and Colorado sedimentary and topographic characteristics.

Euthanasia and common sense: a reply to Garcia.

PubMed

Seay, Gary

2011-06-01

J. L. A. Garcia holds that my defense of voluntary euthanasia in an earlier paper amounts to an "assault on traditional common sense" about what medical ethics permits physicians to do, particularly insofar as I hold that a physician's duty to abstain from intentionally killing is only a defeasible duty, not an unconditional one. But I argue here that it is Garcia's views that are more at odds with common sense, and that voluntary euthanasia is in fact a humane alternative that respects patient autonomy and is consistent with the most fundamental moral duties of physicians. Among these is a duty to relieve suffering, which can sometimes outweigh the fundamental duty to conserve life.

Combining machine learning and remotely sensed bandratios to investigate chlorophyll content and photosynthetic processes

NASA Astrophysics Data System (ADS)

Gholizadeh, Hamed

Photosynthesis in aquatic and terrestrial ecosystems is the key component of the food chain and the most important driver of the global carbon cycle. Therefore, estimation of photosynthesis at large spatial scales is of great scientific importance and can only practically be achieved by remote sensing data and techniques. In this dissertation, remotely sensed information and techniques, as well as field measurements, are used to improve current approaches of assessing photosynthetic processes. More specifically, three topics are the focus here: (1) investigating the application of spectral vegetation indices as proxies for terrestrial chlorophyll in a mangrove ecosystem, (2) evaluating and improving one of the most common empirical ocean-color algorithms (OC4), and (3) developing an improved approach based on sunlit-to-shaded scaled photochemical reflectance index (sPRI) ratios for detecting drought signals in a deciduous forest at eastern United States. The results indicated that although the green normalized difference vegetation index (GNDVI) is an efficient proxy for terrestrial chlorophyll content, there are opportunities to improve the performance of vegetation indices by optimizing the band weights. In regards to the second topic, we concluded that the parameters of the OC4 algorithm and similar empirical models should be tuned regionally and the addition of sea-surface temperature makes the global ocean-color approaches more valid. Results obtained from the third topic showed that considering shaded and sunlit portions of the canopy (i.e., two-leaf models instead of single big leaf models) and taking into account the divergent stomatal behavior of the species (i.e. isohydric and anisohydric) can improve the capability of sPRI in detecting drought. In addition to investigating the photosynthetic processes, the other common theme of the three research topics is the evaluation of "off- the-shelf" solutions to remote-sensing problems. Although widely used approaches such as normalized difference vegetation index (NDVI) are easy to apply and are often efficient choices in remote sensing applications, the use of these approaches should be justified and their shortcomings need to be considered in the context of the research application. When developing new remote sensing approaches, special attention should be paid to (1) initial data analysis such as statistical data transformations (e.g. Tukey ladder-of-powers transformation) and (2) rigorous validation design by creating separate training and validation data sets preferably using both field measurements and satellite-based data. Developing a sound approach and applying a rigorous validation methodology go hand in hand. In sum, all approaches have advantages and disadvantages or as George Box puts it, "all models are wrong but some are useful".

Interactive object recognition assistance: an approach to recognition starting from target objects

NASA Astrophysics Data System (ADS)

Geisler, Juergen; Littfass, Michael

1999-07-01

Recognition of target objects in remotely sensed imagery required detailed knowledge about the target object domain as well as about mapping properties of the sensing system. The art of object recognition is to combine both worlds appropriately and to provide models of target appearance with respect to sensor characteristics. Common approaches to support interactive object recognition are either driven from the sensor point of view and address the problem of displaying images in a manner adequate to the sensing system. Or they focus on target objects and provide exhaustive encyclopedic information about this domain. Our paper discusses an approach to assist interactive object recognition based on knowledge about target objects and taking into account the significance of object features with respect to characteristics of the sensed imagery, e.g. spatial and spectral resolution. An `interactive recognition assistant' takes the image analyst through the interpretation process by indicating step-by-step the respectively most significant features of objects in an actual set of candidates. The significance of object features is expressed by pregenerated trees of significance, and by the dynamic computation of decision relevance for every feature at each step of the recognition process. In the context of this approach we discuss the question of modeling and storing the multisensorial/multispectral appearances of target objects and object classes as well as the problem of an adequate dynamic human-machine-interface that takes into account various mental models of human image interpretation.

Understanding and Accommodating Online Social Communities: A Common Sense Approach

ERIC Educational Resources Information Center

Lennon, Sean M.

2013-01-01

Online social networks such as Facebook have changed the context and definitions of socialization. Focusing on teacher use, this article considers the size and impact of these forums and the importance many young professionals feel toward them. Themed as a common sense approach, the author uses anecdotal points and discussions with…

Thomas Paine: An Englishman Who Became an American Patriot.

ERIC Educational Resources Information Center

Scanlon, Thomas M.

The life of Thomas Paine had been one of constant failure and misfortune until he arrived in Philadelphia (Pennsylvania) where he rose to fame as the politically astute author of "Common Sense." Published in January 1776, "Common Sense" called for the colonies' independence from England and was written in the simple,…

Hyper-temporal remote sensing for digital soil mapping: Characterizing soil-vegetation response to climatic variability

USDA-ARS?s Scientific Manuscript database

Indices derived from remotely-sensed imagery are commonly used to predict soil properties with digital soil mapping (DSM) techniques. The use of images from single dates or a small number of dates is most common for DSM; however, selection of the appropriate images is complicated by temporal variabi...

The Call to Critique "Common Sense" Understandings about Boys and Masculinity(ies)

ERIC Educational Resources Information Center

Dalley-Trim, Leanne

2009-01-01

This paper is founded upon the premise that "common sense" understandings about boys persist within schools and, given this continuing circulation of such understandings, advocates the need to critique such conceptualising. It does so on the grounds that such understandings, and the essentialist discursive knowledges informing these, fail to take…

Values Education: Common Sense and Bugaboos.

ERIC Educational Resources Information Center

Seeley, David S.

Three "bugaboos" frighten schools to the degree that they do not use common sense to implement values education curricula in the public schools. These bugaboos are the problematic issues of prayer, piety, and pluralism. They are not necessarily barriers. School administrators and boards of education should inform themselves so they will be able to…

What's Love Got to Do with It? Rethinking Common Sense Assumptions

ERIC Educational Resources Information Center

Trachman, Matthew; Bluestone, Cheryl

2005-01-01

One of the most basic tasks in introductory social science classes is to get students to reexamine their common sense assumptions concerning human behavior. This article introduces a shared assignment developed for a learning community that paired an introductory sociology and psychology class. The assignment challenges students to rethink the…

Evolution of Bacterial Suicide

NASA Astrophysics Data System (ADS)

Tchernookov, Martin; Nemenman, Ilya

2013-03-01

While active, controlled cellular suicide (autolysis) in bacteria is commonly observed, it has been hard to argue that autolysis can be beneficial to an individual who commits it. We propose a theoretical model that predicts that bacterial autolysis is evolutionarily advantageous to an individualand would fixate in physically structured environments for stationary phase colonies. We perform spatially resolved agent-based simulations of the model, which predict that lower mixing in the environment results in fixation of a higher autolysis rate from a single mutated cell, regardless of the colony's genetic diversity. We argue that quorum sensing will fixate as well, even if initially rare, if it is coupled to controlling the autolysis rate. The model does not predict a strong additional competitive advantage for cells where autolysis is controlled by quorum sensing systems that distinguish self from nonself. These predictions are broadly supported by recent experimental results in B. subtilisand S. pneumoniae. Research partially supported by the James S McDonnell Foundation grant No. 220020321 and by HFSP grant No. RGY0084/2011.

Design optimization of piezoresistive cantilevers for force sensing in air and water

PubMed Central

Doll, Joseph C.; Park, Sung-Jin; Pruitt, Beth L.

2009-01-01

Piezoresistive cantilevers fabricated from doped silicon or metal films are commonly used for force, topography, and chemical sensing at the micro- and macroscales. Proper design is required to optimize the achievable resolution by maximizing sensitivity while simultaneously minimizing the integrated noise over the bandwidth of interest. Existing analytical design methods are insufficient for modeling complex dopant profiles, design constraints, and nonlinear phenomena such as damping in fluid. Here we present an optimization method based on an analytical piezoresistive cantilever model. We use an existing iterative optimizer to minimimize a performance goal, such as minimum detectable force. The design tool is available as open source software. Optimal cantilever design and performance are found to strongly depend on the measurement bandwidth and the constraints applied. We discuss results for silicon piezoresistors fabricated by epitaxy and diffusion, but the method can be applied to any dopant profile or material which can be modeled in a similar fashion or extended to other microelectromechanical systems. PMID:19865512

Reducing mechanical cross-coupling in phased array transducers using stop band material as backing

NASA Astrophysics Data System (ADS)

Henneberg, J.; Gerlach, A.; Storck, H.; Cebulla, H.; Marburg, S.

2018-06-01

Phased array transducers are widely used for acoustic imaging and surround sensing applications. A major design challenge is the achievement of low mechanical cross-coupling between the single transducer elements. Cross-coupling induces a loss of imaging resolution. In this work, the mechanical cross-coupling between acoustic transducers is investigated for a generic model. The model contains a common backing with two bending elements bonded on top. The dimensions of the backing are small; thus, wave reflections on the backing edges have to be considered. This is different to other researches. The operating frequency in the generic model is set to a low kHz range. Low operating frequencies are typical for surround sensing applications. The influence of the backing on cross-coupling is investigated numerically. In order to reduce mechanical cross-coupling a stop band material is designed. It is shown numerically that a reduction in mechanical cross-coupling can be achieved by using stop band material as backing. The effect is validated with experimental testing.

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

USDA-ARS?s Scientific Manuscript database

Surface soil moisture is critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purpo...

Visual Reasoning Tools in Action: Double Number Lines, Area Models, and Other Diagrams Power Up Students' Ability to Solve and Make Sense of Various Problems

ERIC Educational Resources Information Center

Watanabe, Tad

2015-01-01

The Common Core State Standards for Mathematics (CCSSM) (CCSSI 2010) identifies the strategic use of appropriate tools as one of the mathematical practices and emphasizes the use of pictures and diagrams as reasoning tools. Starting with the early elementary grades, CCSSM discusses students' solving of problems "by drawing." In later…

Clean copy association of production diseases with motor activity-sensing devices and milk progesterone concentrations in dairy cows.

PubMed

Williams, J; Ntallaris, T; Routly, J E; Jones, D N; Cameron, J; Holman-Coates, A; Smith, R F; Humblot, P; Dobson, H

2018-05-31

We have previously established that the efficiency of identifying oestrus with activity-sensing devices can be compromised by common production diseases; the present study was undertaken to determine how these diseases may affect device readings. A total of 67 Holstein-Friesian cows, >20 days postpartum, were equipped with activity-sensing neck collars and pedometers, and simultaneous milk progesterone profiles were also monitored twice a week. The influences of common production stressors on maximum activity and progesterone values were analysed. Approximately 30% potential oestrus events (low progesterone value between two high values) remained unrecognised by both activity methods, and progesterone values in these animals were higher on the potential day of oestrus when both activity methods did not detect an event (0.043 ± 0.004 versus 0.029 ± 0.004 ng/mL; P = 0.03). Data from a subset of 45 cows (two events each) were subjected to mixed models and multiple regression modelling to investigate associations with production diseases. Cow motor activity was lower in lame cows. Maximum progesterone concentrations prior to oestrus increased as time postpartum and body condition score (BCS) increased. There were also fewer days of low progesterone prior to oestrus associated with increases in BCS and maximum progesterone concentrations prior to oestrus. In conclusion, lameness was associated with lower activity values, but this suppression was insufficient to account for lowered oestrus detection efficiency of either device. However, associations were identified between production diseases and progesterone profiles. Copyright © 2018. Published by Elsevier Inc.

A synthetic genetic edge detection program.

PubMed

Tabor, Jeffrey J; Salis, Howard M; Simpson, Zachary Booth; Chevalier, Aaron A; Levskaya, Anselm; Marcotte, Edward M; Voigt, Christopher A; Ellington, Andrew D

2009-06-26

Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E. coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.

A Synthetic Genetic Edge Detection Program

PubMed Central

Tabor, Jeffrey J.; Salis, Howard; Simpson, Zachary B.; Chevalier, Aaron A.; Levskaya, Anselm; Marcotte, Edward M.; Voigt, Christopher A.; Ellington, Andrew D.

2009-01-01

Summary Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E.coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks. PMID:19563759

Comparison of Atmospheric Parameters Derived from In-Situ and Hyper-/Multispectral Remote Sensing Data of Beautiful Bavarian Lakes

NASA Astrophysics Data System (ADS)

Riedel, S.; Gege, P.; Schneider, M.; Pfug, B.; Oppelt, N.

2016-08-01

Atmospheric correction is a critical step and can be a limiting factor in the extraction of aquatic ecosystem parameters from remote sensing data of coastal and lake waters. Atmospheric correction models commonly in use for open ocean water and land surfaces can lead to large errors when applied to hyperspectral images taken from satellite or aircraft. The main problems arise from uncertainties in aerosol parameters and neglecting the adjacency effect, which originates from multiple scattering of upwelling radiance from the surrounding land. To better understand the challenges for developing an atmospheric correction model suitable for lakes, we compare atmospheric parameters derived from Sentinel- 2A and airborne hyperspectral data (HySpex) of two Bavarian lakes (Klostersee, Lake Starnberg) with in-situ measurements performed with RAMSES and Ibsen spectrometer systems and a Microtops sun photometer.

Neoliberal Common Sense and Race-Neutral Discourses: A Critique of "Evidence-Based" Policy-Making in School Policing

ERIC Educational Resources Information Center

Nolan, Kathleen

2015-01-01

The author of this paper uses critical discourse analysis and draws on critical social theory and policy studies to analyze the interdiscursivity between neoliberal common sense discourses around crime and safety and race-neutral discourses, "evidence-based" policy, and the research that supports school policing programs. The author…

Common Sense Parenting of Toddlers and Preschoolers. A Girls and Boys Town Program.

ERIC Educational Resources Information Center

Barnes, Bridget A.; York, Steven M.

Based on the view that parents need to balance nurturing behaviors that demonstrate love and affection with the discipline that children need in order to learn and thrive, this book presents the Common Sense Parenting program from Girls and Boys Town as adapted for parents of toddlers and preschoolers. Offering logical techniques and foundations…

Common Sense Parenting: A Practical Approach from Boys Town.

ERIC Educational Resources Information Center

Burke, Raymond V.; Herron, Ronald W.

This workbook is designed to help parents develop a "common sense" approach to child rearing and become more effective parents. Each of the 15 chapters suggests a parenting skill and gives examples for using the skill in a variety of situations. Each chapter also includes exercises designed to help parents put these skills into practice…

The Not So Common Sense: Differences in How People Judge Social and Political Life.

ERIC Educational Resources Information Center

Rosenberg, Shawn W.

This interdisciplinary book challenges two basic assumptions that orient much contemporary social scientific thinking. Offering theory and empirical research, the book rejects the classic liberal view that people share a basic common sense or rationality; while at the same time, it questions the view of contemporary social theory that meaning is…

Job Choice and Personality: A Profile of Michigan Occupational and Physical Therapists.

ERIC Educational Resources Information Center

Lysack, Catherine; McNevin, Nancy; Dunleavy, Kim

2001-01-01

A Keirsey-Bates personality inventory was completed by 128 occupational therapists (OTs) and 166 physical therapists (PTs). PTs were far more likely to have sensing-judging temperament; OTs were predominantly sensing-perceiving or intuitive-feeling. The five most common OT types accounted for only 19% of PTs and the five most common PT types for…

Functional Fixedness and Functional Reduction as Common Sense Reasonings in Chemical Equilibrium and in Geometry and Polarity of Molecules.

ERIC Educational Resources Information Center

Furio, C.; Calatayud, M. L.; Barcenas, S. L.; Padilla, O. M.

2000-01-01

Focuses on learning difficulties in procedural knowledge, and assesses the procedural difficulties of grade 12 and first- and third-year university students based on common sense reasoning in two areas of chemistry--chemical equilibrium and geometry, and polarity of molecules. (Contains 55 references.) (Author/YDS)

Technology: Technology and Common Sense

ERIC Educational Resources Information Center

Van Horn, Royal

2004-01-01

The absence of common sense in the world of technology continues to amaze the author. Things that seem so logical to just aren nott for many people. The installation of Voice-over IP (VoIP, with IP standing for Internet Protocol) in many school districts is a good example. Schools have always had trouble with telephones. Many districts don't even…

Oligonucleotides targeting TCF4 triplet repeat expansion inhibit RNA foci and mis-splicing in Fuchs' dystrophy.

PubMed

Hu, Jiaxin; Rong, Ziye; Gong, Xin; Zhou, Zhengyang; Sharma, Vivek K; Xing, Chao; Watts, Jonathan K; Corey, David R; Mootha, V Vinod

2018-03-15

Fuchs' endothelial corneal dystrophy (FECD) is the most common repeat expansion disorder. FECD impacts 4% of U.S. population and is the leading indication for corneal transplantation. Most cases are caused by an expanded intronic CUG tract in the TCF4 gene that forms nuclear foci, sequesters splicing factors and impairs splicing. We investigated the sense and antisense RNA landscape at the FECD gene and find that the sense-expanded repeat transcript is the predominant species in patient corneas. In patient tissue, sense foci number were negatively correlated with age and showed no correlation with sex. Each endothelial cell has ∼2 sense foci and each foci is single RNA molecule. We designed antisense oligonucleotides (ASOs) to target the mutant-repetitive RNA and demonstrated potent inhibition of foci in patient-derived cells. Ex vivo treatment of FECD human corneas effectively inhibits foci and reverses pathological changes in splicing. FECD has the potential to be a model for treating many trinucleotide repeat diseases and targeting the TCF4 expansion with ASOs represents a promising therapeutic strategy to prevent and treat FECD.

The Learning Styles of Agriculture Preservice Teachers as Assessed by the MBTI.

ERIC Educational Resources Information Center

Cano, Jamie; Garton, Bryan L.

1994-01-01

The Myers Briggs Type Indicator was completed by 82 preservice agricultural education teachers. All 16 types were reflected; the most common were Extrovert Sensing Thinking Judging (23%), Introvert Sensing Thinking Judging (18%), and Extrovert Sensing Feeling Judging (13%). (SK)

An assessment of aerosol optical properties from remote-sensing observations and regional chemistry-climate coupled models over Europe

NASA Astrophysics Data System (ADS)

Palacios-Peña, Laura; Baró, Rocío; Baklanov, Alexander; Balzarini, Alessandra; Brunner, Dominik; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; María López-Romero, José; Montávez, Juan Pedro; Pérez, Juan Luis; Pirovano, Guido; San José, Roberto; Schröder, Wolfram; Werhahn, Johannes; Wolke, Ralf; Žabkar, Rahela; Jiménez-Guerrero, Pedro

2018-04-01

Atmospheric aerosols modify the radiative budget of the Earth due to their optical, microphysical and chemical properties, and are considered one of the most uncertain climate forcing agents. In order to characterise the uncertainties associated with satellite and modelling approaches to represent aerosol optical properties, mainly aerosol optical depth (AOD) and Ångström exponent (AE), their representation by different remote-sensing sensors and regional online coupled chemistry-climate models over Europe are evaluated. This work also characterises whether the inclusion of aerosol-radiation (ARI) or/and aerosol-cloud interactions (ACI) help improve the skills of modelling outputs.Two case studies were selected within the EuMetChem COST Action ES1004 framework when important aerosol episodes in 2010 all over Europe took place: a Russian wildfire episode and a Saharan desert dust outbreak that covered most of the Mediterranean Sea. The model data came from different regional air-quality-climate simulations performed by working group 2 of EuMetChem, which differed according to whether ARI or ACI was included or not. The remote-sensing data came from three different sensors: MODIS, OMI and SeaWIFS. The evaluation used classical statistical metrics to first compare satellite data versus the ground-based instrument network (AERONET) and then to evaluate model versus the observational data (both satellite and ground-based data).Regarding the uncertainty in the satellite representation of AOD, MODIS presented the best agreement with the AERONET observations compared to other satellite AOD observations. The differences found between remote-sensing sensors highlighted the uncertainty in the observations, which have to be taken into account when evaluating models. When modelling results were considered, a common trend for underestimating high AOD levels was observed. For the AE, models tended to underestimate its variability, except when considering a sectional approach in the aerosol representation. The modelling results showed better skills when ARI+ACI interactions were included; hence this improvement in the representation of AOD (above 30 % in the model error) and AE (between 20 and 75 %) is important to provide a better description of aerosol-radiation-cloud interactions in regional climate models.

Exploring Symptom Severity, Illness Perceptions, Coping Styles, and Well-Being in Gastroparesis Patients Using the Common Sense Model.

PubMed

Woodhouse, Sally; Hebbard, Geoff; Knowles, Simon R

2018-04-01

This study aimed to examine the relationships between gastroparesis symptom severity, illness perceptions, coping styles, quality of life (QoL), and psychological distress in patients with gastroparesis, guided by the common sense model. One hundred and seventy-nine adults with gastroparesis (165 females, 14 males; mean age 41.82 years) completed an online questionnaire. The Gastroparesis Cardinal Symptom Index was used to measure gastroparesis symptom severity, QoL was explored using the PAGI-QOL, illness perceptions were measured using the Brief Illness Perception Questionnaire, the Carver Brief COPE scale assessed coping styles, and psychological distress was investigated using the DASS21. Structural equation modeling resulted in a final model with excellent fit. Gastroparesis symptom severity directly influenced illness perceptions (β = .52, p < .001) and QoL (β = .30, p < .001). Illness perceptions directly influenced maladaptive coping (β = - .64, p < .001), psychological distress (β = - .32, p < .001), and QoL (β = .30, p = .01). Maladaptive coping directly influenced psychological distress (β = .62, p < .001), which in turn had a direct influence on QoL (β = - .38, p < .001). The final model showed that the influence of gastroparesis symptom severity on psychological distress was fully mediated by illness perceptions, while the influence on QoL was partially mediated by illness perceptions. The study provides guidance for the development of psychological interventions targeted toward improving mediating psychological factors.

Use of the VS-sense swab in diagnosing vulvovaginitis.

PubMed

Sobel, Jack D; Nyirjesy, Paul; Kessary, Hadar; Ferris, Daron G

2009-09-01

Although pH assessment of vaginal secretions is beneficial for diagnosing vaginitis, it is not commonly done. The purpose of this study was to determine the performance characteristics of the VS-Sense (pH test) swab (Common Sense, Ltd., Caesarea, Israel) in augmenting the diagnosis of vaginitis. We prospectively studied 193 women with acute vulvovaginal symptoms and 74 asymptomatic controls at three medical centers. The VS-Sense swab was administered intravaginally, and results were interpreted by a nurse. These results were compared with final clinical and laboratory diagnoses. In women with an elevated pH caused by bacterial vaginosis (BV), trichomonas, and other types of vaginitis, the VS-Sense test sensitivity and specificity were 82.3% (102 of 124) (95% CI 74.4%-88.5%) and 94.2% (129 of 137) (95% CI 88.8%-97.4%), respectively. There was an 86.2% (95% CI 81.3%-90.1%) overall agreement between pH paper and VS-Sense swab results. The VS-Sense test offers an alternative approach to measuring vaginal pH with nitrazine paper. Use of this simple, more rapid test may facilitate the diagnosis of vulvovaginitis.

A Calibration Method for Nanowire Biosensors to Suppress Device-to-device Variation

PubMed Central

Ishikawa, Fumiaki N.; Curreli, Marco; Chang, Hsiao-Kang; Chen, Po-Chiang; Zhang, Rui; Cote, Richard J.; Thompson, Mark E.; Zhou, Chongwu

2009-01-01

Nanowire/nanotube biosensors have stimulated significant interest; however the inevitable device-to-device variation in the biosensor performance remains a great challenge. We have developed an analytical method to calibrate nanowire biosensor responses that can suppress the device-to-device variation in sensing response significantly. The method is based on our discovery of a strong correlation between the biosensor gate dependence (dIds/dVg) and the absolute response (absolute change in current, ΔI). In2O3 nanowire based biosensors for streptavidin detection were used as the model system. Studying the liquid gate effect and ionic concentration dependence of strepavidin sensing indicates that electrostatic interaction is the dominant mechanism for sensing response. Based on this sensing mechanism and transistor physics, a linear correlation between the absolute sensor response (ΔI) and the gate dependence (dIds/dVg) is predicted and confirmed experimentally. Using this correlation, a calibration method was developed where the absolute response is divided by dIds/dVg for each device, and the calibrated responses from different devices behaved almost identically. Compared to the common normalization method (normalization of the conductance/resistance/current by the initial value), this calibration method was proved advantageous using a conventional transistor model. The method presented here substantially suppresses device-to-device variation, allowing the use of nanosensors in large arrays. PMID:19921812

Targeting agr- and agr-Like Quorum Sensing Systems for Development of Common Therapeutics to Treat Multiple Gram-Positive Bacterial Infections

PubMed Central

Gray, Brian; Hall, Pamela; Gresham, Hattie

2013-01-01

Invasive infection by the Gram-positive pathogen Staphylococcus aureus is controlled by a four gene operon, agr that encodes a quorum sensing system for the regulation of virulence. While agr has been well studied in S. aureus, the contribution of agr homologues and analogues in other Gram-positive pathogens is just beginning to be understood. Intriguingly, other significant human pathogens, including Clostridium perfringens, Listeria monocytogenes, and Enterococcus faecalis contain agr or analogues linked to virulence. Moreover, other significant human Gram-positive pathogens use peptide based quorum sensing systems to establish or maintain infection. The potential for commonality in aspects of these signaling systems across different species raises the prospect of identifying therapeutics that could target multiple pathogens. Here, we review the status of research into these agr homologues, analogues, and other peptide based quorum sensing systems in Gram-positive pathogens as well as the potential for identifying common pathways and signaling mechanisms for therapeutic discovery. PMID:23598501

How the contractualist account of preconception negligence undermines prenatal reproductive autonomy.

PubMed

Melanson, Glen

2013-08-01

Suppose a physician advises a woman to delay her planned pregnancy for a few months in order to significantly reduce the likelihood that her baby will suffer with Spina Bifida. If the woman chooses to ignore this advice and conceives soon after, I believe most people would consider it a matter of common sense that the child thus born is a victim of this woman's negligence, even if it is fortunate enough to not be burdened with Spina Bifida. This common sense judgement appeared to have been done in by the fact that the timing of conception can be identity-influencing, and so the child that is born only exists because of its mother's decision to ignore her physician's advice. However, recently, contemporary contractualist theories have been used to make sense of preconception negligence towards persons whose existence is a result of that same negligence. I will briefly discuss this interesting development and then show how this retrieval of the common sense judgement comes at a great cost to prenatal reproductive autonomy.

Debunking Common Sense and the Taken for Granted: A Pedagogical Strategy for Teaching Social Problems

ERIC Educational Resources Information Center

LeMoyne, Terri; Davis, Jean Marie

2011-01-01

In this article, the authors argue that one approach to teaching Introduction to Social Problems is to structure the course content around taken-for-granted beliefs that many students have about the social world. In doing so, the authors discuss the social construction of social problems, how sociology differs from common sense, and the importance…

Organic electrochemical transistors for cell-based impedance sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rivnay, Jonathan, E-mail: rivnay@emse.fr, E-mail: owens@emse.fr; Ramuz, Marc; Hama, Adel

2015-01-26

Electrical impedance sensing of biological systems, especially cultured epithelial cell layers, is now a common technique to monitor cell motion, morphology, and cell layer/tissue integrity for high throughput toxicology screening. Existing methods to measure electrical impedance most often rely on a two electrode configuration, where low frequency signals are challenging to obtain for small devices and for tissues with high resistance, due to low current. Organic electrochemical transistors (OECTs) are conducting polymer-based devices, which have been shown to efficiently transduce and amplify low-level ionic fluxes in biological systems into electronic output signals. In this work, we combine OECT-based drain currentmore » measurements with simultaneous measurement of more traditional impedance sensing using the gate current to produce complex impedance traces, which show low error at both low and high frequencies. We apply this technique in vitro to a model epithelial tissue layer and show that the data can be fit to an equivalent circuit model yielding trans-epithelial resistance and cell layer capacitance values in agreement with literature. Importantly, the combined measurement allows for low biases across the cell layer, while still maintaining good broadband signal.« less

Vegetation Species Composition and Canopy Architecture Information Expressed in Leaf Water Absorption Measured in the 1000nm and 2200 nm Spectral Region by an Imaging Spectometer

NASA Technical Reports Server (NTRS)

Green, R. O.; Roberts, D. A.

1994-01-01

Plant species composition and plant architectural attributes are critical parameters required for the measuring, monitoring and modeling of terrestrial ecosystems. Remote sensing is commonly cited as an important tool for deriving vegetation properties at an appropriate scale for ecosystem studies, ranging from local, to regional and even synoptic scales (e.g. Wessman 1992).

Plasma Flow Past Cometary and Planetary Satellite Atmospheres

NASA Technical Reports Server (NTRS)

Combi, Michael R.; Gombosi, Tamas I.; Kabin, Konstantin

2000-01-01

The tenuous atmospheres and ionospheres of comets and outer planet satellites share many common properties and features. Such similarities include a strong interaction with their outer radiation, fields and particles environs. For comets the interaction is with the magnetized solar wind plasma, whereas for satellites the interaction is with the strongly magnetized and corotating planetary magnetospheric plasma. For this reason there are many common or analogous physical regimes, and many of the same modeling techniques are used to interpret remote sensing and in situ measurements in order to study the important underlying physical phenomena responsible for their appearances. We present here a review of various modeling approaches which are used to elucidate the basic properties and processes shaping the energetics and dynamics of these systems which are similar in many respects.

Enhancing Privacy in Participatory Sensing Applications with Multidimensional Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Groat, Michael; Forrest, Stephanie; Horey, James L

2012-01-01

Participatory sensing applications rely on individuals to share local and personal data with others to produce aggregated models and knowledge. In this setting, privacy is an important consideration, and lack of privacy could discourage widespread adoption of many exciting applications. We present a privacy-preserving participatory sensing scheme for multidimensional data which uses negative surveys. Multidimensional data, such as vectors of attributes that include location and environment fields, pose a particular challenge for privacy protection and are common in participatory sensing applications. When reporting data in a negative survey, an individual participant randomly selects a value from the set complement ofmore » the sensed data value, once for each dimension, and returns the negative values to a central collection server. Using algorithms described in this paper, the server can reconstruct the probability density functions of the original distributions of sensed values, without knowing the participants actual data. As a consequence, complicated encryption and key management schemes are avoided, conserving energy. We study trade-offs between accuracy and privacy, and their relationships to the number of dimensions, categories, and participants. We introduce dimensional adjustment, a method that reduces the magnification of error associated with earlier work. Two simulation scenarios illustrate how the approach can protect the privacy of a participant's multidimensional data while allowing useful population information to be aggregated.« less

Polya's bees: A model of decentralized decision-making.

PubMed

Golman, Russell; Hagmann, David; Miller, John H

2015-09-01

How do social systems make decisions with no single individual in control? We observe that a variety of natural systems, including colonies of ants and bees and perhaps even neurons in the human brain, make decentralized decisions using common processes involving information search with positive feedback and consensus choice through quorum sensing. We model this process with an urn scheme that runs until hitting a threshold, and we characterize an inherent tradeoff between the speed and the accuracy of a decision. The proposed common mechanism provides a robust and effective means by which a decentralized system can navigate the speed-accuracy tradeoff and make reasonably good, quick decisions in a variety of environments. Additionally, consensus choice exhibits systemic risk aversion even while individuals are idiosyncratically risk-neutral. This too is adaptive. The model illustrates how natural systems make decentralized decisions, illuminating a mechanism that engineers of social and artificial systems could imitate.

Polya’s bees: A model of decentralized decision-making

PubMed Central

Golman, Russell; Hagmann, David; Miller, John H.

2015-01-01

How do social systems make decisions with no single individual in control? We observe that a variety of natural systems, including colonies of ants and bees and perhaps even neurons in the human brain, make decentralized decisions using common processes involving information search with positive feedback and consensus choice through quorum sensing. We model this process with an urn scheme that runs until hitting a threshold, and we characterize an inherent tradeoff between the speed and the accuracy of a decision. The proposed common mechanism provides a robust and effective means by which a decentralized system can navigate the speed-accuracy tradeoff and make reasonably good, quick decisions in a variety of environments. Additionally, consensus choice exhibits systemic risk aversion even while individuals are idiosyncratically risk-neutral. This too is adaptive. The model illustrates how natural systems make decentralized decisions, illuminating a mechanism that engineers of social and artificial systems could imitate. PMID:26601255

Development of novel optical fiber sensors for measuring tilts and displacements of geotechnical structures

NASA Astrophysics Data System (ADS)

Pei, Hua-Fu; Yin, Jian-Hua; Jin, Wei

2013-09-01

Two kinds of innovative sensors based on optical fiber sensing technologies have been proposed and developed for measuring tilts and displacements in geotechnical structures. The newly developed tilt sensors are based on classical beam theory and were successfully used to measure the inclinations in a physical model test. The conventional inclinometers including in-place and portable types, as a key instrument, are very commonly used in geotechnical engineering. In this paper, fiber Bragg grating sensing technology is used to measure strains along a standard inclinometer casing and these strains are used to calculate the lateral and/or horizontal deflections of the casing using the beam theory and a finite difference method. Finally, the monitoring results are verified by laboratory tests.

Channel Estimation and Pilot Design for Massive MIMO Systems with Block-Structured Compressive Sensing

NASA Astrophysics Data System (ADS)

Lv, ZhuoKai; Yang, Tiejun; Zhu, Chunhua

2018-03-01

Through utilizing the technology of compressive sensing (CS), the channel estimation methods can achieve the purpose of reducing pilots and improving spectrum efficiency. The channel estimation and pilot design scheme are explored during the correspondence under the help of block-structured CS in massive MIMO systems. The block coherence property of the aggregate system matrix can be minimized so that the pilot design scheme based on stochastic search is proposed. Moreover, the block sparsity adaptive matching pursuit (BSAMP) algorithm under the common sparsity model is proposed so that the channel estimation can be caught precisely. Simulation results are to be proved the proposed design algorithm with superimposed pilots design and the BSAMP algorithm can provide better channel estimation than existing methods.

Are High-IQ Individuals Deficient in Common Sense? A Critical Examination of the "Clever Sillies" Hypothesis

ERIC Educational Resources Information Center

Woodley, Michael A.

2010-01-01

A controversial hypothesis [Charlton (2009). "Clever sillies: Why high-IQ people tend to be deficient in common sense." "Medical Hypotheses," 73, 867-870] has recently been proposed to account for why individuals of high-IQ and high social status tend to hold counter-intuitive views on social phenomena. It is claimed that these "clever sillies"…

Intelligence Involves Risk-Awareness and Intellectual Disability Involves Risk-Unawareness: Implications of a Theory of Common Sense

ERIC Educational Resources Information Center

Greenspan, Stephen; Switzky, Harvey N.; Woods, George W.

2011-01-01

Survival in the everyday world (in both social and practical functioning) depends on one's ability to recognise and avoid going down the worst possible path, especially when doing so places one at risk of death, injury, or social disaster. Most people possess "common sense" (the ability to recognise obvious risk) but some people lack that ability…

Information content of in situ and remotely sensed chlorophyll-a: Learning from size-structured phytoplankton model

NASA Astrophysics Data System (ADS)

Laiolo, Leonardo; Matear, Richard; Baird, Mark E.; Soja-Woźniak, Monika; Doblin, Martina A.

2018-07-01

Chlorophyll-a measurements in the form of in situ observations and satellite ocean colour products are commonly used in data assimilation to calibrate marine biogeochemical models. Here, a two size-class phytoplankton biogeochemical model, with a 0D configuration, was used to simulate the surface chlorophyll-a dynamics (simulated surface Chl-a) for cyclonic and anticyclonic eddies off East Australia. An optical model was then used to calculate the inherent optical properties from the simulation and convert them into remote-sensing reflectance (Rrs). Subsequently, Rrs was used to produce a satellite-like estimate of the simulated surface Chl-a concentrations through the MODIS OC3M algorithm (simulated OC3M Chl-a). Identical parameter optimisation experiments were performed through the assimilation of the two separate datasets (simulated surface Chl-a and simulated OC3M Chl-a), with the purpose of investigating the contrasting information content of simulated surface Chl-a and remotely-sensed data sources. The results we present are based on the analysis of the distribution of a cost function, varying four parameters of the biogeochemical model. In our idealized experiments the simulated OC3M Chl-a product is a poor proxy for the total simulated surface Chl-a concentration. Furthermore, our result show the OC3M algorithm can underestimate the simulated chlorophyll-a concentration in offshore eddies off East Australia (Case I waters), because of the weak relationship between large-sized phytoplankton and remote-sensing reflectance. Although Case I waters are usually characteristic of oligotrophic environments, with a photosynthetic community typically represented by relatively small-sized phytoplankton, mesoscale features such as eddies can generate seasonally favourable conditions for a photosynthetic community with a greater proportion of large phytoplankton cells. Furthermore, our results show that in mesoscale features such as eddies, in situ chlorophyll-a observations and the ocean colour products can carry different information related to phytoplankton sizes. Assimilating both remote-sensing reflectance and measurements of in situ chlorophyll-a concentration reduces the uncertainty of the parameter values more than either data set alone, thus reducing the spread of acceptable solutions, giving an improved simulation of the natural environment.

Estimation of Multiple Parameters over Vegetated Surfaces by Integrating Optical-Thermal Remote Sensing Observations

NASA Astrophysics Data System (ADS)

Ma, H.

2016-12-01

Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface parameters are generally parameter-specific algorithms and are based on instantaneous physical models, which result in spatial, temporal and physical inconsistencies in current global products. Besides, optical and Thermal Infrared (TIR) remote sensing observations are usually separated to use based on different models , and the Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal that mixes both reflected and emitted fluxes. In this paper, we proposed a unified algorithm for simultaneously retrieving a total of seven land surface parameters, including Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Temperature (LST), surface emissivity, downward and upward longwave radiation, by exploiting remote sensing observations from visible to TIR domain based on a common physical Radiative Transfer (RT) model and a data assimilation framework. The coupled PROSPECT-VISIR and 4SAIL RT model were used for canopy reflectance modeling. At first, LAI was estimated using a data assimilation method that combines MODIS daily reflectance observation and a phenology model. The estimated LAI values were then input into the RT model to simulate surface spectral emissivity and surface albedo. Besides, the background albedo and the transmittance of solar radiation, and the canopy albedo were also calculated to produce FAPAR. Once the spectral emissivity of seven MODIS MIR to TIR bands were retrieved, LST can be estimated from the atmospheric corrected surface radiance by exploiting an optimization method. At last, the upward longwave radiation were estimated using the retrieved LST, broadband emissivity (converted from spectral emissivity) and the downward longwave radiation (modeled by MODTRAN). These seven parameters were validated over several representative sites with different biome type, and compared with MODIS and GLASS product. Results showed that this unified inversion algorithm can retrieve temporally complete and physical consistent land surface parameters with high accuracy.

Operational evapotranspiration mapping using remote sensing and weather datasets: a new parameterization for the SSEB approach

USGS Publications Warehouse

Senay, Gabriel B.; Bohms, Stefanie; Singh, Ramesh K.; Gowda, Prasanna H.; Velpuri, Naga Manohar; Alemu, Henok; Verdin, James P.

2013-01-01

The increasing availability of multi-scale remotely sensed data and global weather datasets is allowing the estimation of evapotranspiration (ET) at multiple scales. We present a simple but robust method that uses remotely sensed thermal data and model-assimilated weather fields to produce ET for the contiguous United States (CONUS) at monthly and seasonal time scales. The method is based on the Simplified Surface Energy Balance (SSEB) model, which is now parameterized for operational applications, renamed as SSEBop. The innovative aspect of the SSEBop is that it uses predefined boundary conditions that are unique to each pixel for the "hot" and "cold" reference conditions. The SSEBop model was used for computing ET for 12 years (2000-2011) using the MODIS and Global Data Assimilation System (GDAS) data streams. SSEBop ET results compared reasonably well with monthly eddy covariance ET data explaining 64% of the observed variability across diverse ecosystems in the CONUS during 2005. Twelve annual ET anomalies (2000-2011) depicted the spatial extent and severity of the commonly known drought years in the CONUS. More research is required to improve the representation of the predefined boundary conditions in complex terrain at small spatial scales. SSEBop model was found to be a promising approach to conduct water use studies in the CONUS, with a similar opportunity in other parts of the world. The approach can also be applied with other thermal sensors such as Landsat.

Forest Disturbance Analysis with LANDSAT-8 Oli Data Related to a Parametric Wind Field: a Case Study for Typhoon Rammasun (201409)

NASA Astrophysics Data System (ADS)

Tan, C.; Fang, W.

2018-04-01

Forest disturbance induced by tropical cyclone often has significant and profound effects on the structure and function of forest ecosystem. Detection and analysis of post-disaster forest disturbance based on remote sensing technology has been widely applied. At present, it is necessary to conduct further quantitative analysis of the magnitude of forest disturbance with the intensity of typhoon. In this study, taking the case of super typhoon Rammasun (201409), we analysed the sensitivity of four common used remote sensing indices and explored the relationship between remote sensing index and corresponding wind speeds based on pre-and post- Landsat-8 OLI (Operational Land Imager) images and a parameterized wind field model. The results proved that NBR is the most sensitive index for the detection of forest disturbance induced by Typhoon Rammasun and the variation of NBR has a significant linear dependence relation with the simulated 3-second gust wind speed.

Making Common Sense of Vaccines: An Example of Discussing the Recombinant Attenuated Salmonella Vaccine with the Public.

PubMed

Dankel, Dorothy J; Roland, Kenneth L; Fisher, Michael; Brenneman, Karen; Delgado, Ana; Santander, Javier; Baek, Chang-Ho; Clark-Curtiss, Josephine; Strand, Roger; Curtiss, Roy

2014-01-01

Researchers have iterated that the future of synthetic biology and biotechnology lies in novel consumer applications of crossing biology with engineering. However, if the new biology's future is to be sustainable, early and serious efforts must be made towards social sustainability. Therefore, the crux of new applications of synthetic biology and biotechnology is public understanding and acceptance. The RASVaccine is a novel recombinant design not found in nature that re-engineers a common bacteria ( Salmonella ) to produce a strong immune response in humans. Synthesis of the RASVaccine has the potential to improve public health as an inexpensive, non-injectable product. But how can scientists move forward to create a dialogue of creating a 'common sense' of this new technology in order to promote social sustainability? This paper delves into public issues raised around these novel technologies and uses the RASVaccine as an example of meeting the public with a common sense of its possibilities and limitations.

Illness representations, coping, and illness outcomes in people with cancer: a systematic review and meta-analysis.

PubMed

Richardson, Emma M; Schüz, Natalie; Sanderson, Kristy; Scott, Jennifer L; Schüz, Benjamin

2017-06-01

Cancer is associated with negative health and emotional outcomes in those affected by it, suggesting the need to better understand the psychosocial determinants of illness outcomes and coping. The common sense model is the leading psychological model of self-regulation in the face of illness and assumes that subjective illness representations explain how people attempt to cope with illness. This systematic review and meta-analysis examines the associations of the common sense model's illness representation dimensions with health and coping outcomes in people with cancer. A systematic literature search located 54 studies fulfilling the inclusion criteria, with 38 providing sufficient data for meta-analysis. A narrative review of the remaining studies was also conducted. Random-effects models revealed small to moderate effect sizes (Fisher Z) for the relations between illness representations and coping behaviors (in particular between control perceptions, problem-focused coping, and cognitive reappraisal) and moderate to large effect sizes between illness representations and illness outcomes (in particular between identity, consequences, emotional representations, and psychological distress). The narrative review of studies with insufficient data provided similar results. The results indicate how illness representations relate to illness outcomes in people with cancer. However, more high-quality studies are needed to examine causal effects of illness representations on coping and outcomes. High heterogeneity indicates potential moderators of the relationships between illness representations and health and coping outcomes, including diagnostic, prognostic, and treatment-related variables. This review can inform the design of interventions to improve coping strategies and mental health outcomes in people with cancer. Copyright © 2016 John Wiley & Sons, Ltd.

Learn good from bad: Effects of good and bad neighbors in spatial prisoners' dilemma games

NASA Astrophysics Data System (ADS)

Lu, Peng

2015-10-01

Cooperation is vital for the human society and this study focuses on how to promote cooperation. In our stratification model, there exist three classes: two minorities are elites who are prone to cooperate and scoundrels who are born to defect; one majority is the class of common people. Agents of these three classes interact with each other on a square lattice. Commons' cooperation and its factors are investigated. Contradicting our common sense, it indicates that elites play a negative role while scoundrels play a positive one in promoting commons' cooperation. Besides, effects of good and bad neighbors vary with temptation. When the temptation is smaller the positive effect is able to overcome the negative effect, but the later prevails when the temptation is larger. It concludes that common people are more prone to cooperate in harsh environment with bad neighbors, and a better environment with good neighbors merely leads to laziness and free riding of commons.

Editor’s message: Groundwater modeling fantasies - Part 1, adrift in the details

USGS Publications Warehouse

Voss, Clifford I.

2011-01-01

Fools ignore complexity. Pragmatists suffer it. Some can avoid it. Geniuses remove it. …Simplicity does not precede complexity, but follows it. (Epigrams in Programming by Alan Perlis, a computer scientist; Perlis 1982).A doctoral student creating a groundwater model of a regional aquifer put individual circular regions around data points where he had hydraulic head measurements, so that each region’s parameter values could be adjusted to get perfect fit with the measurement at that point. Nearly every measurement point had its own parameter-value region. After calibration, the student was satisfied because his model correctly reproduced all of his data. Did he really get the true field values of parameters in this manner? Did this approach result in a realistic, meaningful and useful groundwater model?—truly doubtful. Is this story a sign of a common style of educating hydrogeology students these days? Where this is the case, major changes are needed to add back ‘common-sense hydrogeology’ to the curriculum. Worse, this type of modeling approach has become an industry trend in application of groundwater models to real systems, encouraged by the advent of automatic model calibration software that has no problem providing numbers for as many parameter value estimates as desired. Just because a computer program can easily create such values does not mean that they are in any sense useful—but unquestioning practitioners are happy to follow such software developments, perhaps because of an implied promise that highly parameterized models, here referred to as ‘complex’, are somehow superior. This and other fallacies are implicit in groundwater modeling studies, most usually not acknowledged when presenting results. This two-part Editor’s Message deals with the state of groundwater modeling: part 1 (here) focuses on problems and part 2 (Voss 2011) on prospects.

Common-Path Wavefront Sensing for Advanced Coronagraphs

NASA Technical Reports Server (NTRS)

Wallace, J. Kent; Serabyn, Eugene; Mawet, Dimitri

2012-01-01

Imaging of faint companions around nearby stars is not limited by either intrinsic resolution of a coronagraph/telescope system, nor is it strictly photon limited. Typically, it is both the magnitude and temporal variation of small phase and amplitude errors imparted to the electric field by elements in the optical system which will limit ultimate performance. Adaptive optics systems, particularly those with multiple deformable mirrors, can remove these errors, but they need to be sensed in the final image plane. If the sensing system is before the final image plane, which is typical for most systems, then the non-common path optics between the wavefront sensor and science image plane will lead to un-sensed errors. However, a new generation of high-performance coronagraphs naturally lend themselves to wavefront sensing in the final image plane. These coronagraphs and the wavefront sensing will be discussed, as well as plans for demonstrating this with a high-contrast system on the ground. Such a system will be a key system-level proof for a future space-based coronagraph mission, which will also be discussed.

Specific coil design for SENSE: a six-element cardiac array.

PubMed

Weiger, M; Pruessmann, K P; Leussler, C; Röschmann, P; Boesiger, P

2001-03-01

In sensitivity encoding (SENSE), the effects of inhomogeneous spatial sensitivity of surface coils are utilized for signal localization in addition to common Fourier encoding using magnetic field gradients. Unlike standard Fourier MRI, SENSE images exhibit an inhomogeneous noise distribution, which crucially depends on the geometrical sensitivity relations of the coils used. Thus, for optimum signal-to-noise-ratio (SNR) and noise homogeneity, specialized coil configurations are called for. In this article we study the implications of SENSE imaging for coil layout by means of simulations and imaging experiments in a phantom and in vivo. New, specific design principles are identified. For SENSE imaging, the elements of a coil array should be smaller than for common phased-array imaging. Furthermore, adjacent coil elements should not overlap. Based on the findings of initial investigations, a configuration of six coils was designed and built specifically for cardiac applications. The in vivo evaluation of this array showed a considerable SNR increase in SENSE images, as compared with a conventional array. Magn Reson Med 45:495-504, 2001. Copyright 2001 Wiley-Liss, Inc.

Common sense reasoning about petroleum flow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosenberg, S.

1981-02-01

This paper describes an expert system for understanding and Reasoning in a petroleum resources domain. A basic model is implemented in FRL (Frame Representation Language). Expertise is encoded as rule frames. The model consists of a set of episodic contexts which are sequentially generated over time. Reasoning occurs in separate reasoning contexts consisting of a buffer frame and packets of rules. These function similar to small production systems. reasoning is linked to the model through an interface of Sentinels (instance driven demons) which notice anomalous conditions. Heuristics and metaknowledge are used through the creation of further reasoning contexts which overlaymore » the simpler ones.« less

Computational Introspection.

DTIC Science & Technology

1983-02-01

committee: Marvin Minsky , Carl Hewitt, and Tomas Lozano-Perez for letting me read the papers I wanted to, and for an entertaining defense of my paper. Hal...problem by postulating that the self-model be incomplete or inaccurate. Such an approach is taken by [ Minsky , 1965]. However, my line is even stronger...Intelligence, 19. McCarthy, J. (1968) "Programs With Common Sense," in Semantic Information Processing,, M. Minsky , d. MIT Press. " McCarthy, J. and Hayes, P

A common visual metric for approximate number and density

PubMed Central

Dakin, Steven C.; Tibber, Marc S.; Greenwood, John A.; Kingdom, Frederick A. A.; Morgan, Michael J.

2011-01-01

There is considerable interest in how humans estimate the number of objects in a scene in the context of an extensive literature on how we estimate the density (i.e., spacing) of objects. Here, we show that our sense of number and our sense of density are intertwined. Presented with two patches, observers found it more difficult to spot differences in either density or numerosity when those patches were mismatched in overall size, and their errors were consistent with larger patches appearing both denser and more numerous. We propose that density is estimated using the relative response of mechanisms tuned to low and high spatial frequencies (SFs), because energy at high SFs is largely determined by the number of objects, whereas low SF energy depends more on the area occupied by elements. This measure is biased by overall stimulus size in the same way as human observers, and by estimating number using the same measure scaled by relative stimulus size, we can explain all of our results. This model is a simple, biologically plausible common metric for perceptual number and density. PMID:22106276

The Seduction of Common Sense: How the Right Has Framed the Debate on America's Schools. Teaching for Social Justice

ERIC Educational Resources Information Center

Kumashiro, Kevin K.

2008-01-01

Just in time for the 2008 elections, "The Seduction of Common Sense" offers a powerful examination of current education policy initiatives as framed by the rhetoric of the political Right and the political Left. Critical of both sides, Kumashiro first provides a searching look at the Right and shows why it has succeeded so well in winning the…

Ten reasons to embrace scientism.

PubMed

Peels, Rik

2017-06-01

A strong version of scientism, such as that of Alex Rosenberg, says, roughly, that natural science reliably delivers rational belief or knowledge, whereas common sense sources of belief, such as moral intuition, memory, and introspection, do not. In this paper I discuss ten reasons that adherents of scientism have or might put forward in defence of scientism. The aim is to show which considerations could plausibly count in favour of scientism and what this implies for the way scientism ought to be formulated. I argue that only three out of these ten reasons potentially hold water and that the evidential weight is, therefore, on their shoulders. These three reasons for embracing scientism are, respectively, particular empirical arguments to the effect that there are good debunking explanations for certain common sense beliefs, that there are incoherences and biases in the doxastic outputs of certain common sense sources of belief, and that beliefs that issue from certain common sense doxastic sources are illusory. From what I argue, it follows that only a version of scientism that is significantly weaker than many versions of scientism that we find in the literature is potentially tenable. I conclude the paper by stating what such a significantly weaker version of scientism could amount to. Copyright © 2017 Elsevier Ltd. All rights reserved.

Unifying model of shoot gravitropism reveals proprioception as a central feature of posture control in plants

PubMed Central

Bastien, Renaud; Bohr, Tomas; Moulia, Bruno; Douady, Stéphane

2013-01-01

Gravitropism, the slow reorientation of plant growth in response to gravity, is a key determinant of the form and posture of land plants. Shoot gravitropism is triggered when statocysts sense the local angle of the growing organ relative to the gravitational field. Lateral transport of the hormone auxin to the lower side is then enhanced, resulting in differential gene expression and cell elongation causing the organ to bend. However, little is known about the dynamics, regulation, and diversity of the entire bending and straightening process. Here, we modeled the bending and straightening of a rod-like organ and compared it with the gravitropism kinematics of different organs from 11 angiosperms. We show that gravitropic straightening shares common traits across species, organs, and orders of magnitude. The minimal dynamic model accounting for these traits is not the widely cited gravisensing law but one that also takes into account the sensing of local curvature, what we describe here as a graviproprioceptive law. In our model, the entire dynamics of the bending/straightening response is described by a single dimensionless “bending number” B that reflects the ratio between graviceptive and proprioceptive sensitivities. The parameter B defines both the final shape of the organ at equilibrium and the timing of curving and straightening. B can be estimated from simple experiments, and the model can then explain most of the diversity observed in experiments. Proprioceptive sensing is thus as important as gravisensing in gravitropic control, and the B ratio can be measured as phenotype in genetic studies. PMID:23236182

Unifying model of shoot gravitropism reveals proprioception as a central feature of posture control in plants.

PubMed

Bastien, Renaud; Bohr, Tomas; Moulia, Bruno; Douady, Stéphane

2013-01-08

Gravitropism, the slow reorientation of plant growth in response to gravity, is a key determinant of the form and posture of land plants. Shoot gravitropism is triggered when statocysts sense the local angle of the growing organ relative to the gravitational field. Lateral transport of the hormone auxin to the lower side is then enhanced, resulting in differential gene expression and cell elongation causing the organ to bend. However, little is known about the dynamics, regulation, and diversity of the entire bending and straightening process. Here, we modeled the bending and straightening of a rod-like organ and compared it with the gravitropism kinematics of different organs from 11 angiosperms. We show that gravitropic straightening shares common traits across species, organs, and orders of magnitude. The minimal dynamic model accounting for these traits is not the widely cited gravisensing law but one that also takes into account the sensing of local curvature, what we describe here as a graviproprioceptive law. In our model, the entire dynamics of the bending/straightening response is described by a single dimensionless "bending number" B that reflects the ratio between graviceptive and proprioceptive sensitivities. The parameter B defines both the final shape of the organ at equilibrium and the timing of curving and straightening. B can be estimated from simple experiments, and the model can then explain most of the diversity observed in experiments. Proprioceptive sensing is thus as important as gravisensing in gravitropic control, and the B ratio can be measured as phenotype in genetic studies.

Models for integrated and differential scattering optical properties of encapsulated light absorbing carbon aggregates.

PubMed

Kahnert, Michael; Nousiainen, Timo; Lindqvist, Hannakaisa

2013-04-08

Optical properties of light absorbing carbon (LAC) aggregates encapsulated in a shell of sulfate are computed for realistic model geometries based on field measurements. Computations are performed for wavelengths from the UV-C to the mid-IR. Both climate- and remote sensing-relevant optical properties are considered. The results are compared to commonly used simplified model geometries, none of which gives a realistic representation of the distribution of the LAC mass within the host material and, as a consequence, fail to predict the optical properties accurately. A new core-gray shell model is introduced, which accurately reproduces the size- and wavelength dependence of the integrated and differential optical properties.

Models of an In-Situ Propellant Production Plant for Mars Exploration

NASA Technical Reports Server (NTRS)

Goodrich, Charlie; Kurien, James; Millar, Bill; Sweet, Adam; Waterman, Sue; Clancy, Daniel (Technical Monitor)

2001-01-01

An in-situ propellant production system (ISPP) is designed to make rocket fuel from chemicals in the Martian atmosphere in order to reduce the amount of materials that would need to be brought from Earth to support Mars missions. We have developed a description of a hypothetical ISPP system that we would like to make available to researchers who are interested in the problem of automatically diagnosing failures in complex NASA systems. This problem description will help researchers to investigate problems of interest to NASA. We would like to make the following material publicly available: (1) a 'common sense' model of an ISPP system; (2) low- and medium-fidelity simulations of the ISPP system written in Microsoft Excel and HCC; and (3) previously published data and diagrams concerning ISPP components. We do not believe there are any export considerations on these materials for the following reasons: (1) These models are not useful for guidance and real time control of vehicles, encrpytion, or any other software purpose categorized under the Export Control Classification Numbers; and (2) The models are very high level and would not by themselves enable real-time control of a real hardware system. The models are at the level of common sense. They capture, for example, that if a heater is turned on an increase in temperature should result(see the attached excerpt). We do not believe there is any commercial value to this material, given the low commercial demand for propellant plants on mars. We have spoken to acting Code IC Division Chief Dan Clancy, and he concurs with our desire to make these materials publicly available via a technical report.

Modal sensing and control of paraboloidal shell structronic system

NASA Astrophysics Data System (ADS)

Yue, Honghao; Lu, Yifan; Deng, Zongquan; Tzou, Hornsen

2018-02-01

Paraboloidal shells of revolution are commonly used as important components in the field of advanced aerospace structures and aviation mechanical systems. This study is to investigate the modal sensing behavior and the modal vibration control effect of distributed PVDF patches laminated on the paraboloidal shell. A paraboloidal shell sensing and control testing platform is set up first. Frequencies of lower order modes of the shell are obtained with the PVDF sensor and compared with the previous testing results to prove its accuracy. Then sensor patches are laminated on different positions (or different sides) of the shell and tested to reveal the relation between the sensing behaviors and their locations. Finally, a mathematical model of the structronic system is built by parameter identifications and the transfer function is derived. Independent and coupled modal controllers are designed based on the pole placement method and modal vibration control experiments are performed. The amplitude suppression ratio of each mode controlled by the pole placement controller is calculated and compared with the results obtained by using a PPF controller. Advantages of both methods are concluded and suggestions are given on how to choose control algorithm for different purpose.

A Prototype Hydrologic Observatory for the Neuse River Basin Using Remote Sensing Data as a Part of the CUAHSI-HIS Effort

NASA Astrophysics Data System (ADS)

Kanwar, R.; Narayan, U.; Lakshmi, V.

2005-12-01

Remote sensing has the potential to immensely advance the science and application of hydrology as it provides multi-scale and multi-temporal measurements of several hydrologic parameters. There is a wide variety of remote sensing data sources available to a hydrologist with a myriad of data formats, access techniques, data quality issues and temporal and spatial extents. It is very important to make data availability and its usage as convenient as possible for potential users. The CUAHSI Hydrologic Information System (HIS) initiative addresses this issue of better data access and management for hydrologists with a focus on in-situ data, that is point measurements of water and energy fluxes which make up the 'more conventional' sources of hydrologic data. This paper explores various sources of remotely sensed hydrologic data available, their data formats and volumes, current modes of data acquisition by end users, metadata associated with data itself, and requirements from potential data models that would allow a seamless integration of remotely sensed hydrologic observations into the Hydrologic Information System. Further, a prototype hydrologic observatory (HO) for the Neuse River Basin is developed using surface temperature, vegetation indices and soil moisture estimates available from remote sensing. The prototype (HO) uses the CUAHSI digital library system (DLS) on the back (server) end. On the front (client) end, a rich visual environment has been developed in order to provide better decision making tools in order to make an optimal choice in the selection of remote sensing data for a particular application. An easy point and click interface to the remote sensing data is also implemented for common users who are just interested in location based query of hydrologic variable values.

[Ambivalence--a key concept in gerontology? Elements of heuristics exemplified by identity formation in old age].

PubMed

Lüscher, Kurt; Haller, Miriam

2016-01-01

Ambivalence is a widely used concept in gerontology, mostly used in the common sense meaning. We propose that an elaborated notion based on the historical and systematic analysis, reveals important theoretical, methodological and practical potentials of the idea of ambivalence for the study of aging. We exemplify this view by proposing a heuristic perspective for the analysis of processes to constitute and reconstitute identities in old age using a model based on a multidimensional understanding of ambivalence. Ambivalence is defined as referring to the experiences of vacillating between polar contradictions of feeling, thinking, wanting and social structures in the search for the sense and meaning of social relationships, facts and texts, which are important for unfolding and altering facets of the self and agency.

Magnetic Field Sensors Based on Giant Magnetoresistance (GMR) Technology: Applications in Electrical Current Sensing

PubMed Central

Reig, Candid; Cubells-Beltran, María-Dolores; Muñoz, Diego Ramírez

2009-01-01

The 2007 Nobel Prize in Physics can be understood as a global recognition to the rapid development of the Giant Magnetoresistance (GMR), from both the physics and engineering points of view. Behind the utilization of GMR structures as read heads for massive storage magnetic hard disks, important applications as solid state magnetic sensors have emerged. Low cost, compatibility with standard CMOS technologies and high sensitivity are common advantages of these sensors. This way, they have been successfully applied in a lot different environments. In this work, we are trying to collect the Spanish contributions to the progress of the research related to the GMR based sensors covering, among other subjects, the applications, the sensor design, the modelling and the electronic interfaces, focusing on electrical current sensing applications. PMID:22408486

USGS Provision of Near Real Time Remotely Sensed Imagery for Emergency Response

NASA Astrophysics Data System (ADS)

Jones, B. K.

2014-12-01

The use of remotely sensed imagery in the aftermath of a disaster can have an important impact on the effectiveness of the response for many types of disasters such as floods, earthquakes, volcanic eruptions, landslides, and other natural or human-induced disasters. Ideally, responders in areas that are commonly affected by disasters would have access to archived remote sensing imagery plus the ability to easily obtain the new post event data products. The cost of obtaining and storing the data and the lack of trained professionals who can process the data into a mapping product oftentimes prevent this from happening. USGS Emergency Operations provides remote sensing and geospatial support to emergency managers by providing access to satellite images from numerous domestic and international space agencies including those affiliated with the International Charter Space and Major Disasters and their space-based assets and by hosting and distributing thousands of near real time event related images and map products through the Hazards Data Distribution System (HDDS). These data may include digital elevation models, hydrographic models, base satellite images, vector data layers such as roads, aerial photographs, and other pre and post disaster data. These layers are incorporated into a Web-based browser and data delivery service, the Hazards Data Distribution System (HDDS). The HDDS can be made accessible either to the general public or to specific response agencies. The HDDS concept anticipates customer requirements and provides rapid delivery of data and services. This presentation will provide an overview of remotely sensed imagery that is currently available to support emergency response operations and examples of products that have been created for past events that have provided near real time situational awareness for responding agencies.

Remote sensing of impervious surface growth: A framework for quantifying urban expansion and re-densification mechanisms

NASA Astrophysics Data System (ADS)

Shahtahmassebi, Amir Reza; Song, Jie; Zheng, Qing; Blackburn, George Alan; Wang, Ke; Huang, Ling Yan; Pan, Yi; Moore, Nathan; Shahtahmassebi, Golnaz; Sadrabadi Haghighi, Reza; Deng, Jing Song

2016-04-01

A substantial body of literature has accumulated on the topic of using remotely sensed data to map impervious surfaces which are widely recognized as an important indicator of urbanization. However, the remote sensing of impervious surface growth has not been successfully addressed. This study proposes a new framework for deriving and summarizing urban expansion and re-densification using time series of impervious surface fractions (ISFs) derived from remotely sensed imagery. This approach integrates multiple endmember spectral mixture analysis (MESMA), analysis of regression residuals, spatial statistics (Getis_Ord) and urban growth theories; hence, the framework is abbreviated as MRGU. The performance of MRGU was compared with commonly used change detection techniques in order to evaluate the effectiveness of the approach. The results suggested that the ISF regression residuals were optimal for detecting impervious surface changes while Getis_Ord was effective for mapping hotspot regions in the regression residuals image. Moreover, the MRGU outputs agreed with the mechanisms proposed in several existing urban growth theories, but importantly the outputs enable the refinement of such models by explicitly accounting for the spatial distribution of both expansion and re-densification mechanisms. Based on Landsat data, the MRGU is somewhat restricted in its ability to measure re-densification in the urban core but this may be improved through the use of higher spatial resolution satellite imagery. The paper ends with an assessment of the present gaps in remote sensing of impervious surface growth and suggests some solutions. The application of impervious surface fractions in urban change detection is a stimulating new research idea which is driving future research with new models and algorithms.

A feed-forward Hopfield neural network algorithm (FHNNA) with a colour satellite image for water quality mapping

NASA Astrophysics Data System (ADS)

Asal Kzar, Ahmed; Mat Jafri, M. Z.; Hwee San, Lim; Al-Zuky, Ali A.; Mutter, Kussay N.; Hassan Al-Saleh, Anwar

2016-06-01

There are many techniques that have been given for water quality problem, but the remote sensing techniques have proven their success, especially when the artificial neural networks are used as mathematical models with these techniques. Hopfield neural network is one type of artificial neural networks which is common, fast, simple, and efficient, but it when it deals with images that have more than two colours such as remote sensing images. This work has attempted to solve this problem via modifying the network that deals with colour remote sensing images for water quality mapping. A Feed-forward Hopfield Neural Network Algorithm (FHNNA) was modified and used with a satellite colour image from type of Thailand earth observation system (THEOS) for TSS mapping in the Penang strait, Malaysia, through the classification of TSS concentrations. The new algorithm is based essentially on three modifications: using HNN as feed-forward network, considering the weights of bitplanes, and non-self-architecture or zero diagonal of weight matrix, in addition, it depends on a validation data. The achieved map was colour-coded for visual interpretation. The efficiency of the new algorithm has found out by the higher correlation coefficient (R=0.979) and the lower root mean square error (RMSE=4.301) between the validation data that were divided into two groups. One used for the algorithm and the other used for validating the results. The comparison was with the minimum distance classifier. Therefore, TSS mapping of polluted water in Penang strait, Malaysia, can be performed using FHNNA with remote sensing technique (THEOS). It is a new and useful application of HNN, so it is a new model with remote sensing techniques for water quality mapping which is considered important environmental problem.

Modeling landscape evapotranspiration by integrating land surface phenology and a water balance algorithm

USGS Publications Warehouse

Senay, Gabriel B.

2008-01-01

The main objective of this study is to present an improved modeling technique called Vegetation ET (VegET) that integrates commonly used water balance algorithms with remotely sensed Land Surface Phenology (LSP) parameter to conduct operational vegetation water balance modeling of rainfed systems at the LSP’s spatial scale using readily available global data sets. Evaluation of the VegET model was conducted using Flux Tower data and two-year simulation for the conterminous US. The VegET model is capable of estimating actual evapotranspiration (ETa) of rainfed crops and other vegetation types at the spatial resolution of the LSP on a daily basis, replacing the need to estimate crop- and region-specific crop coefficients.

A spectral-spatial-dynamic hierarchical Bayesian (SSD-HB) model for estimating soybean yield

NASA Astrophysics Data System (ADS)

Kazama, Yoriko; Kujirai, Toshihiro

2014-10-01

A method called a "spectral-spatial-dynamic hierarchical-Bayesian (SSD-HB) model," which can deal with many parameters (such as spectral and weather information all together) by reducing the occurrence of multicollinearity, is proposed. Experiments conducted on soybean yields in Brazil fields with a RapidEye satellite image indicate that the proposed SSD-HB model can predict soybean yield with a higher degree of accuracy than other estimation methods commonly used in remote-sensing applications. In the case of the SSD-HB model, the mean absolute error between estimated yield of the target area and actual yield is 0.28 t/ha, compared to 0.34 t/ha when conventional PLS regression was applied, showing the potential effectiveness of the proposed model.

The Study of Graphic Sense and Its Effects on the Acquisition of Literacy. Final Report.

ERIC Educational Resources Information Center

Hernandez-Chavez, Eduardo; Curtis, Jan

This report describes a study on the development of children's conceptualizations of written language, that is, their graphic sense. The study investigated three issues: (1) whether acquisition of literacy is a developmental process common to all normal children, (2) whether the levels of graphic sense tend to be associated with particular…

Common-Sense Rule Inference

NASA Astrophysics Data System (ADS)

Lombardi, Ilaria; Console, Luca

In the paper we show how rule-based inference can be made more flexible by exploiting semantic information associated with the concepts involved in the rules. We introduce flexible forms of common sense reasoning in which whenever no rule applies to a given situation, the inference engine can fire rules that apply to more general or to similar situations. This can be obtained by defining new forms of match between rules and the facts in the working memory and new forms of conflict resolution. We claim that in this way we can overcome some of the brittleness problems that are common in rule-based systems.

La crianza practica de los hijos: una guia paso a paso para formar hijos responsables y hogares felices (Common Sense Parenting: A Practical Approach from Boys Town).

ERIC Educational Resources Information Center

Burke, Ray; Herron, Ron

This workbook is designed to help parents develop a "common sense" approach to child rearing and become more effective parents. Each of the 15 chapters suggests a parenting skill and gives examples for using the skill in a variety of situations. Each chapter also includes exercises designed to help parents put these skills into practice…

An Improved Cochlea Model with a General User Interface

NASA Astrophysics Data System (ADS)

Duifhuis, H.; Kruseman, J. M.; van Hengel, P. W. J.

2003-02-01

We have developed a flexible 1D cochlea model to test hypotheses and data against physical and mathematical constraints. The model is flexible in the sense that several linear and nonlinear model characteristics can be selected, and different boundary conditions can be tested. The software model runs at a reasonable speed at a modern PC. As an example, we will show the results of the model in comparison with the systematic study of the phase behavior (group delay) of distortion product otoacoustic emissions (DPOAEs) in the guinea pig (S. Schneider, V. Prijs and R. Schoonhoven, [9]). We also will demonstrate the effects of some common non-physical boundary conditions. Finally, we briefly indicate that this model of the auditory periphery provides a superior front end for an ASR (automatic speech recognition)-system.

Mapping of Polar Areas Based on High-Resolution Satellite Images: The Example of the Henryk Arctowski Polish Antarctic Station

NASA Astrophysics Data System (ADS)

Kurczyński, Zdzisław; Różycki, Sebastian; Bylina, Paweł

2017-12-01

To produce orthophotomaps or digital elevation models, the most commonly used method is photogrammetric measurement. However, the use of aerial images is not easy in polar regions for logistical reasons. In these areas, remote sensing data acquired from satellite systems is much more useful. This paper presents the basic technical requirements of different products which can be obtain (in particular orthoimages and digital elevation model (DEM)) using Very-High-Resolution Satellite (VHRS) images. The study area was situated in the vicinity of the Henryk Arctowski Polish Antarctic Station on the Western Shore of Admiralty Bay, King George Island, Western Antarctic. Image processing was applied on two triplets of images acquired by the Pléiades 1A and 1B in March 2013. The results of the generation of orthoimages from the Pléiades systems without control points showed that the proposed method can achieve Root Mean Squared Error (RMSE) of 3-9 m. The presented Pléiades images are useful for thematic remote sensing analysis and processing of measurements. Using satellite images to produce remote sensing products for polar regions is highly beneficial and reliable and compares well with more expensive airborne photographs or field surveys.

Direct correlation between potentiometric and impedance biosensing of antibody-antigen interactions using an integrated system

NASA Astrophysics Data System (ADS)

Tsai, Meng-Yen; Creedon, Niamh; Brightbill, Eleanor; Pavlidis, Spyridon; Brown, Billyde; Gray, Darren W.; Shields, Niall; Sayers, Ríona; Mooney, Mark H.; O'Riordan, Alan; Vogel, Eric M.

2017-08-01

A fully integrated system that combines extended gate field-effect transistor (EGFET)-based potentiometric biosensors and electrochemical impedance spectroscopy (EIS)-based biosensors has been demonstrated. This integrated configuration enables the sequential measurement of the same immunological binding event on the same sensing surface and consequently sheds light on the fundamental origins of sensing signals produced by FET and EIS biosensors, as well as the correlation between the two. Detection of both the bovine serum albumin (BSA)/anti-BSA model system in buffer solution and bovine parainfluenza antibodies in complex blood plasma samples was demonstrated using the integrated biosensors. Comparison of the EGFET and EIS sensor responses reveals similar dynamic ranges, while equivalent circuit modeling of the EIS response shows that the commonly reported total impedance change (ΔZtotal) is dominated by the change in charge transfer resistance (Rct) rather than surface capacitance (Csurface). Using electrochemical kinetics and the Butler-Volmer equation, we unveil that the surface potential and charge transfer resistance, measured by potentiometric and impedance biosensors, respectively, are, in fact, intrinsically linked. This observation suggests that there is no significant gain in using the FET/EIS integrated system and leads to the demonstration that low-cost EGFET biosensors are sufficient as a detection tool to resolve the charge information of biomolecules for practical sensing applications.

Wind Sensing and Modeling | Grid Modernization | NREL

Science.gov Websites

Simulation at the turbine, wind plant, and regional scales for resource prospecting, resource assessment Sensing and Modeling Wind Sensing and Modeling NREL's wind sensing and modeling work supports the deployment of wind-based generation technologies for all stages of a plant's life, from resource estimates to

The White-hat Bot: A Novel Botnet Defense Strategy

DTIC Science & Technology

2012-06-14

etc. I will briefly discuss one common exploit here. One fraudulent activity 4 perpetuated by botnets involves ad services such as Google’s AdSense ...which pays website owners revenue for posting the AdSense banner on their web site (Google, 2012). The AdSense banner displays messages from...botmaster creates a bot that is programmed to visit the botmaster’s own websites to click on the advertisements displayed in the AdSense banners. Since

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, J. A.

1993-01-01

Progress report on remote sensing of Earth terrain covering the period from Jan. to June 1993 is presented. Areas of research include: radiative transfer model for active and passive remote sensing of vegetation canopy; polarimetric thermal emission from rough ocean surfaces; polarimetric passive remote sensing of ocean wind vectors; polarimetric thermal emission from periodic water surfaces; layer model with tandom spheriodal scatterers for remote sensing of vegetation canopy; application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated mie scatterers with size distributions and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

Capacitive touch sensing : signal and image processing algorithms

NASA Astrophysics Data System (ADS)

Baharav, Zachi; Kakarala, Ramakrishna

2011-03-01

Capacitive touch sensors have been in use for many years, and recently gained center stage with the ubiquitous use in smart-phones. In this work we will analyze the most common method of projected capacitive sensing, that of absolute capacitive sensing, together with the most common sensing pattern, that of diamond-shaped sensors. After a brief introduction to the problem, and the reasons behind its popularity, we will formulate the problem as a reconstruction from projections. We derive analytic solutions for two simple cases: circular finger on a wire grid, and square finger on a square grid. The solutions give insight into the ambiguities of finding finger location from sensor readings. The main contribution of our paper is the discussion of interpolation algorithms including simple linear interpolation , curve fitting (parabolic and Gaussian), filtering, general look-up-table, and combinations thereof. We conclude with observations on the limits of the present algorithmic methods, and point to possible future research.

A Polygon Model for Wireless Sensor Network Deployment with Directional Sensing Areas

PubMed Central

Wu, Chun-Hsien; Chung, Yeh-Ching

2009-01-01

The modeling of the sensing area of a sensor node is essential for the deployment algorithm of wireless sensor networks (WSNs). In this paper, a polygon model is proposed for the sensor node with directional sensing area. In addition, a WSN deployment algorithm is presented with topology control and scoring mechanisms to maintain network connectivity and improve sensing coverage rate. To evaluate the proposed polygon model and WSN deployment algorithm, a simulation is conducted. The simulation results show that the proposed polygon model outperforms the existed disk model and circular sector model in terms of the maximum sensing coverage rate. PMID:22303159

Comparison of Aerial and Terrestrial Remote Sensing Techniques for Quantifying Forest Canopy Structural Complexity and Estimating Net Primary Productivity

NASA Astrophysics Data System (ADS)

Fahey, R. T.; Tallant, J.; Gough, C. M.; Hardiman, B. S.; Atkins, J.; Scheuermann, C. M.

2016-12-01

Canopy structure can be an important driver of forest ecosystem functioning - affecting factors such as radiative transfer and light use efficiency, and consequently net primary production (NPP). Both above- (aerial) and below-canopy (terrestrial) remote sensing techniques are used to assess canopy structure and each has advantages and disadvantages. Aerial techniques can cover large geographical areas and provide detailed information on canopy surface and canopy height, but are generally unable to quantitatively assess interior canopy structure. Terrestrial methods provide high resolution information on interior canopy structure and can be cost-effectively repeated, but are limited to very small footprints. Although these methods are often utilized to derive similar metrics (e.g., rugosity, LAI) and to address equivalent ecological questions and relationships (e.g., link between LAI and productivity), rarely are inter-comparisons made between techniques. Our objective is to compare methods for deriving canopy structural complexity (CSC) metrics and to assess the capacity of commonly available aerial remote sensing products (and combinations) to match terrestrially-sensed data. We also assess the potential to combine CSC metrics with image-based analysis to predict plot-based NPP measurements in forests of different ages and different levels of complexity. We use combinations of data from drone-based imagery (RGB, NIR, Red Edge), aerial LiDAR (commonly available medium-density leaf-off), terrestrial scanning LiDAR, portable canopy LiDAR, and a permanent plot network - all collected at the University of Michigan Biological Station. Our results will highlight the potential for deriving functionally meaningful CSC metrics from aerial imagery, LiDAR, and combinations of data sources. We will also present results of modeling focused on predicting plot-level NPP from combinations of image-based vegetation indices (e.g., NDVI, EVI) with LiDAR- or image-derived metrics of CSC (e.g., rugosity, porosity), canopy density, (e.g., LAI), and forest structure (e.g., canopy height). This work builds toward future efforts that will use other data combinations, such as those available at NEON sites, and could be used to inform and test popular ecosystem models (e.g., ED2) incorporating structure.

Summary of human social, cultural, behavioral (HSCB) modeling for information fusion panel discussion

NASA Astrophysics Data System (ADS)

Blasch, Erik; Salerno, John; Kadar, Ivan; Yang, Shanchieh J.; Fenstermacher, Laurie; Endsley, Mica; Grewe, Lynne

2013-05-01

During the SPIE 2012 conference, panelists convened to discuss "Real world issues and challenges in Human Social/Cultural/Behavioral modeling with Applications to Information Fusion." Each panelist presented their current trends and issues. The panel had agreement on advanced situation modeling, working with users for situation awareness and sense-making, and HSCB context modeling in focusing research activities. Each panelist added different perspectives based on the domain of interest such as physical, cyber, and social attacks from which estimates and projections can be forecasted. Also, additional techniques were addressed such as interest graphs, network modeling, and variable length Markov Models. This paper summarizes the panelists discussions to highlight the common themes and the related contrasting approaches to the domains in which HSCB applies to information fusion applications.

Imputing forest structure attributes from stand inventory and remotely sensed data in western Oregon, USA

Treesearch

Andrew T. Hudak; A. Tod Haren; Nicholas L. Crookston; Robert J. Liebermann; Janet L. Ohmann

2014-01-01

Imputation is commonly used to assign reference stand observations to target stands based on covariate relationships to remotely sensed data to assign inventory attributes across the entire landscape. However, most remotely sensed data are collected at higher resolution than the stand inventory data often used by operational foresters. Our primary goal was to compare...

A model that helps explain Sr-isotope disequilibrium between feldspar phenocrysts and melt in large-volume silicic magma systems

USGS Publications Warehouse

Duffield, W.A.; Ruiz, J.

1998-01-01

Feldspar phenocrysts of silicic volcanic rocks are commonly in Sr-isotopic disequilibrium with groundmass. In some cases the feldspar is more radiogenic, and in others it is less radiogenic. Several explanations have been published previously, but none of these is able to accommodate both senses of disequilibrium. We present a model by which either more- or less-radiogenic feldspar (or even both within a single eruptive unit) can originate. The model requires a magma body open to interaction with biotite- and feldspar-bearing wall rock. Magma is incrementally contaminated as wall rock melts incongruently. Biotite preferentially melts first, followed by feldspar. Such melting behavior, which is supported by both field and experimental studies, first contaminates magma with a relatively radiogenic addition, followed by a less-radiogenic addition. Feldspar phenocrysts lag behind melt (groundmass of volcanic rock) in incorporating the influx of contaminant, thus resulting in Sr-isotopic disequilibrium between the crystals and melt. The sense of disequilibrium recorded in a volcanic rock depends on when eruption quenches the contamination process. This model is testable by isotopic fingerprinting of individual feldspar crystals. For a given set of geologic boundary conditions, specific core-to-rim Sr-isotopic profiles are expectable. Moreover, phenocrysts that nucleate at different times during the contamination process should record different and predictable parts of the history. Initial results of Sr-isotopic fingerprinting of sanidine phenocrysts from the Taylor Creek Rhyolite are consistent with the model. More tests of the model are desirable.Feldspar phenocrysts of silicic volcanic rocks are commonly in Sr-isotopic disequilibrium with groundmass. In some cases the feldspar is more radiogenic, and in others it is less radiogenic. Several explanations have been published previously, but none of these is able to accommodate both senses of disequilibrium. We present a model by which either more- or less-radiogenic feldspar (or even both within a single eruptive unit) can originate. The model requires a magma body open to interaction with biotite- and feldspar-bearing wall rock. Magma is incrementally contaminated as wall rock melts incongruently. Biotite preferentially melts first, followed by feldspar. Such melting behavior, which is supported by both field and experimental studies, first contaminates magma with a relatively radiogenic addition, followed by a less-radiogenic addition. Feldspar phenocrysts lag behind melt (groundmass of volcanic rock) in incorporating the influx of contaminant, thus resulting in Sr-isotopic disequilibrium between the crystals and melt. The sense of disequilibrium recorded in a volcanic rock depends on when eruption quenches the contamination process. This model is testable by isotopic fingerprinting of individual feldspar crystals. For a given set of geologic boundary conditions, specific core-to-rim Sr-isotopic profiles are expectable. Moreover, phenocrysts that nucleate at different times during the contamination process should record different and predictable parts of the history. Initial results of Sr-isotopic fingerprinting of sanidine phenocrysts from the Taylor Creek Rhyolite are consistent with the model. More tests of the model are desirable.

Analysis of portfolio optimization with lot of stocks amount constraint: case study index LQ45

NASA Astrophysics Data System (ADS)

Chin, Liem; Chendra, Erwinna; Sukmana, Agus

2018-01-01

To form an optimum portfolio (in the sense of minimizing risk and / or maximizing return), the commonly used model is the mean-variance model of Markowitz. However, there is no amount of lots of stocks constraint. And, retail investors in Indonesia cannot do short selling. So, in this study we will develop an existing model by adding an amount of lot of stocks and short-selling constraints to get the minimum risk of portfolio with and without any target return. We will analyse the stocks listed in the LQ45 index based on the stock market capitalization. To perform this analysis, we will use Solver that available in Microsoft Excel.

Numerical analysis of ossicular chain lesion of human ear

NASA Astrophysics Data System (ADS)

Liu, Yingxi; Li, Sheng; Sun, Xiuzhen

2009-04-01

Lesion of ossicular chain is a common ear disease impairing the sense of hearing. A comprehensive numerical model of human ear can provide better understanding of sound transmission. In this study, we propose a three-dimensional finite element model of human ear that incorporates the canal, tympanic membrane, ossicular bones, middle ear suspensory ligaments/muscles, middle ear cavity and inner ear fluid. Numerical analysis is conducted and employed to predict the effects of middle ear cavity, malleus handle defect, hypoplasia of the long process of incus, and stapedial crus defect on sound transmission. The present finite element model is shown to be reasonable in predicting the ossicular mechanics of human ear.

The availability of conventional forms of remotely sensed data

USGS Publications Warehouse

Sturdevant, James A.; Holm, Thomas M.

1982-01-01

For decades Federal and State agencies have been collecting aerial photographs of various film types and scales over parts of the United States. More recently, worldwide Earth resources data acquired by orbiting satellites have inundated the remote sensing community. Determining the types of remotely sensed data that are publicly available can be confusing to the land-resource manager, planner, and scientist. This paper is a summary of the more commonly used types of remotely sensed data (aircraft and satellite) and their public availability. Special emphasis is placed on the National High-Altitude Photography (NHAP) program and future remote-sensing satellites.

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

NASA Astrophysics Data System (ADS)

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

2018-02-01

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. About 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). The relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.

Application of High Resolution Air-Borne Remote Sensing Observations for Monitoring NOx Emissions

NASA Astrophysics Data System (ADS)

Souri, A.; Choi, Y.; Pan, S.; Curci, G.; Janz, S. J.; Kowalewski, M. G.; Liu, J.; Herman, J. R.; Weinheimer, A. J.

2017-12-01

Nitrogen oxides (NOx=NO+NO2) are one of the air pollutants, responsible for the formation of tropospheric ozone, acid rain and particulate nitrate. The anthropogenic NOx emissions are commonly estimated based on bottom-up inventories which are complicated by many potential sources of error. One way to improve the emission inventories is to use relevant observations to constrain them. Fortunately, Nitrogen dioxide (NO2) is one of the most successful detected species from remote sensing. Although many studies have shown the capability of using space-borne remote sensing observations for monitoring emissions, the insufficient sample number and footprint of current measurements have introduced a burden to constrain emissions at fine scales. Promisingly, there are several air-borne sensors collected for NASA's campaigns providing high spatial resolution of NO2 columns. Here, we use the well-characterized NO2 columns from the Airborne Compact Atmospheric Mapper (ACAM) onboard NASA's B200 aircraft into a 1×1 km regional model to constrain anthropogenic NOx emissions in the Houston-Galveston-Brazoria area. Firstly, in order to incorporate the data, we convert the NO2 slant column densities to vertical ones using a joint of a radiative transfer model and the 1x1 km regional model constrained by P3-B aircraft measurements. After conducting an inverse modeling method using the Kalman filter, we find the ACAM observations are resourceful at mitigating the overprediction of model in reproducing NO2 on regular days. Moreover, the ACAM provides a unique opportunity to detect an anomaly in emissions leading to strong air quality degradation that is lacking in previous works. Our study provides convincing evidence that future geostationary satellites with high spatial and temporal resolutions will give us insights into uncertainties associated with the emissions at regional scales.

Remote sensing: a tool for park planning and management

USGS Publications Warehouse

Draeger, William C.; Pettinger, Lawrence R.

1981-01-01

Remote sensing may be defined as the science of imaging or measuring objects from a distance. More commonly, however, the term is used in reference to the acquisition and use of photographs, photo-like images, and other data acquired from aircraft and satellites. Thus, remote sensing includes the use of such diverse materials as photographs taken by hand from a light aircraft, conventional aerial photographs obtained with a precision mapping camera, satellite images acquired with sophisticated scanning devices, radar images, and magnetic and gravimetric data that may not even be in image form. Remotely sensed images may be color or black and white, can vary in scale from those that cover only a few hectares of the earth's surface to those that cover tens of thousands of square kilometers, and they may be interpreted visually or with the assistance of computer systems. This article attempts to describe several of the commonly available types of remotely sensed data, to discuss approaches to data analysis, and to demonstrate (with image examples) typical applications that might interest managers of parks and natural areas.

A case study of comparing radiometrically calibrated reflectance of an image mosaic from unmanned aerial system with that of a single image from manned aircraft over a same area

USDA-ARS?s Scientific Manuscript database

Although conventional high-altitude airborne remote sensing and low-altitude unmanned aerial system (UAS) based remote sensing share many commonalities, one of the major differences between the two remote sensing platforms is that the latter has much smaller image footprint. To cover the same area o...

Developmental neuroscience of time and number: implications for autism and other neurodevelopmental disabilities

PubMed Central

Allman, Melissa J.; Pelphrey, Kevin A.; Meck, Warren H.

2011-01-01

Estimations of time and number share many similarities in both non-humans and man. The primary focus of this review is on the development of time and number sense across infancy and childhood, and neuropsychological findings as they relate to time and number discrimination in infants and adults. Discussion of these findings is couched within a mode-control model of timing and counting which assumes time and number share a common magnitude representation system. A basic sense of time and number likely serves as the foundation for advanced numerical and temporal competence, and aspects of higher cognition—this will be discussed as it relates to typical childhood, and certain developmental disorders, including autism spectrum disorder. Directions for future research in the developmental neuroscience of time and number (NEUTIN) will also be highlighted. PMID:22408612

Evaluation of a 6-wire thermocouple psychrometer for determination of in-situ water potentials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loskot, C.L.; Rousseau, J.P.; Kurzmack, M.A.

1994-12-31

A 6-wire, Peltier-type thermocouple psychrometer was designed and evaluated by the U.S. Geological Survey for monitoring in-situ water potentials in dry-drilled boreholes in the unsaturated zone at Yucca Mountain, Nye County, Nevada. The psychrometer consists of a wet-bulb, chromel-constantan, sensing junction and a separate dry-bulb, copper-constantan, reference junction. Two additional reference junctions are formed where the chromel and constantan wires of the wet-bulb sensing junction are soldered to separate, paired, copper, lead wires. In contrast, in the standard 3-wire thermocouple psychrometer, both the wet bulb and dry bulb share a common wire. The new design has resulted in a psychrometermore » that has an expanded range and greater reliability, sensitivity, and accuracy compared to the standard model.« less

Langasite surface acoustic wave gas sensors: modeling and verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peng Zheng,; Greve, D. W.; Oppenheim, I. J.

2013-03-01

We report finite element simulations of the effect of conductive sensing layers on the surface wave velocity of langasite substrates. The simulations include both the mechanical and electrical influences of the conducting sensing layer. We show that three-dimensional simulations are necessary because of the out-of-plane displacements of the commonly used (0, 138.5, 26.7) Euler angle. Measurements of the transducer input admittance in reflective delay-line devices yield a value for the electromechanical coupling coefficient that is in good agreement with the three-dimensional simulations on bare langasite substrate. The input admittance measurements also show evidence of excitation of an additional wave modemore » and excess loss due to the finger resistance. The results of these simulations and measurements will be useful in the design of surface acoustic wave gas sensors.« less

Bio-Optics of the Chesapeake Bay from Measurements and Radiative Transfer Calculations

NASA Technical Reports Server (NTRS)

Tzortziou, Maria; Herman, Jay R.; Gallegos, Charles L.; Neale, Patrick J.; Subramaniam, Ajit; Harding, Lawrence W., Jr.; Ahmad, Ziauddin

2005-01-01

We combined detailed bio-optical measurements and radiative transfer (RT) modeling to perform an optical closure experiment for optically complex and biologically productive Chesapeake Bay waters. We used this experiment to evaluate certain assumptions commonly used when modeling bio-optical processes, and to investigate the relative importance of several optical characteristics needed to accurately model and interpret remote sensing ocean-color observations in these Case 2 waters. Direct measurements were made of the magnitude, variability, and spectral characteristics of backscattering and absorption that are critical for accurate parameterizations in satellite bio-optical algorithms and underwater RT simulations. We found that the ratio of backscattering to total scattering in the mid-mesohaline Chesapeake Bay varied considerably depending on particulate loading, distance from land, and mixing processes, and had an average value of 0.0128 at 530 nm. Incorporating information on the magnitude, variability, and spectral characteristics of particulate backscattering into the RT model, rather than using a volume scattering function commonly assumed for turbid waters, was critical to obtaining agreement between RT calculations and measured radiometric quantities. In situ measurements of absorption coefficients need to be corrected for systematic overestimation due to scattering errors, and this correction commonly employs the assumption that absorption by particulate matter at near infrared wavelengths is zero.

Environmental Sciences: YIP: Combining Remotely Sensed Vegetation Data and Ecohydrologic Process Models to Improve Estimation of Root Zone Moisture at Spatial Scales Relevant to the Army

DTIC Science & Technology

2016-04-01

vegetation arising due to contrasts in incoming solar radiation that is associated with hillslope aspects. At lower elevations, shrubs can be present on North...whereas shrubs are more prevalent on South-facing aspects. At watershed scales, the transition from grasses at lower elevations to coniferous evergreens...Mountain sage communities, adapted to cooler temperatures, are also found at higher elevations in RCEW, with ceanothus shrubs common   Mean annual

Stochasticity in numerical solutions of the nonlinear Schroedinger equation

NASA Technical Reports Server (NTRS)

Shen, Mei-Mei; Nicholson, D. R.

1987-01-01

The cubically nonlinear Schroedinger equation is an important model of nonlinear phenomena in fluids and plasmas. Numerical solutions in a spatially periodic system commonly involve truncation to a finite number of Fourier modes. These solutions are found to be stochastic in the sense that the largest Liapunov exponent is positive. As the number of modes is increased, the size of this exponent appears to converge to zero, in agreement with the recent demonstration of the integrability of the spatially periodic case.

Towards Modeling False Memory With Computational Knowledge Bases.

PubMed

Li, Justin; Kohanyi, Emma

2017-01-01

One challenge to creating realistic cognitive models of memory is the inability to account for the vast common-sense knowledge of human participants. Large computational knowledge bases such as WordNet and DBpedia may offer a solution to this problem but may pose other challenges. This paper explores some of these difficulties through a semantic network spreading activation model of the Deese-Roediger-McDermott false memory task. In three experiments, we show that these knowledge bases only capture a subset of human associations, while irrelevant information introduces noise and makes efficient modeling difficult. We conclude that the contents of these knowledge bases must be augmented and, more important, that the algorithms must be refined and optimized, before large knowledge bases can be widely used for cognitive modeling. Copyright © 2016 Cognitive Science Society, Inc.

An object-based storage model for distributed remote sensing images

NASA Astrophysics Data System (ADS)

Yu, Zhanwu; Li, Zhongmin; Zheng, Sheng

2006-10-01

It is very difficult to design an integrated storage solution for distributed remote sensing images to offer high performance network storage services and secure data sharing across platforms using current network storage models such as direct attached storage, network attached storage and storage area network. Object-based storage, as new generation network storage technology emerged recently, separates the data path, the control path and the management path, which solves the bottleneck problem of metadata existed in traditional storage models, and has the characteristics of parallel data access, data sharing across platforms, intelligence of storage devices and security of data access. We use the object-based storage in the storage management of remote sensing images to construct an object-based storage model for distributed remote sensing images. In the storage model, remote sensing images are organized as remote sensing objects stored in the object-based storage devices. According to the storage model, we present the architecture of a distributed remote sensing images application system based on object-based storage, and give some test results about the write performance comparison of traditional network storage model and object-based storage model.

A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications.

PubMed

Dinh, Thanh; Kim, Younghan; Lee, Hyukjoon

2017-03-01

This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model.

A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications †

PubMed Central

Dinh, Thanh; Kim, Younghan; Lee, Hyukjoon

2017-01-01

This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model. PMID:28257067

Strategies for using remotely sensed data in hydrologic models

NASA Technical Reports Server (NTRS)

Peck, E. L.; Keefer, T. N.; Johnson, E. R. (Principal Investigator)

1981-01-01

Present and planned remote sensing capabilities were evaluated. The usefulness of six remote sensing capabilities (soil moisture, land cover, impervious area, areal extent of snow cover, areal extent of frozen ground, and water equivalent of the snow cover) with seven hydrologic models (API, CREAMS, NWSRFS, STORM, STANFORD, SSARR, and NWSRFS Snowmelt) were reviewed. The results indicate remote sensing information has only limited value for use with the hydrologic models in their present form. With minor modifications to the models the usefulness would be enhanced. Specific recommendations are made for incorporating snow covered area measurements in the NWSRFS Snowmelt model. Recommendations are also made for incorporating soil moisture measurements in NWSRFS. Suggestions are made for incorporating snow covered area, soil moisture, and others in STORM and SSARR. General characteristics of a hydrologic model needed to make maximum use of remotely sensed data are discussed. Suggested goals for improvements in remote sensing for use in models are also established.

Limits to the precision of gradient sensing with spatial communication and temporal integration.

PubMed

Mugler, Andrew; Levchenko, Andre; Nemenman, Ilya

2016-02-09

Gradient sensing requires at least two measurements at different points in space. These measurements must then be communicated to a common location to be compared, which is unavoidably noisy. Although much is known about the limits of measurement precision by cells, the limits placed by the communication are not understood. Motivated by recent experiments, we derive the fundamental limits to the precision of gradient sensing in a multicellular system, accounting for communication and temporal integration. The gradient is estimated by comparing a "local" and a "global" molecular reporter of the external concentration, where the global reporter is exchanged between neighboring cells. Using the fluctuation-dissipation framework, we find, in contrast to the case when communication is ignored, that precision saturates with the number of cells independently of the measurement time duration, because communication establishes a maximum length scale over which sensory information can be reliably conveyed. Surprisingly, we also find that precision is improved if the local reporter is exchanged between cells as well, albeit more slowly than the global reporter. The reason is that whereas exchange of the local reporter weakens the comparison, it decreases the measurement noise. We term such a model "regional excitation-global inhibition." Our results demonstrate that fundamental sensing limits are necessarily sharpened when the need to communicate information is taken into account.

Shape and Stress Sensing of Multilayered Composite and Sandwich Structures Using an Inverse Finite Element Method

NASA Technical Reports Server (NTRS)

Cerracchio, Priscilla; Gherlone, Marco; Di Sciuva, Marco; Tessler, Alexander

2013-01-01

The marked increase in the use of composite and sandwich material systems in aerospace, civil, and marine structures leads to the need for integrated Structural Health Management systems. A key capability to enable such systems is the real-time reconstruction of structural deformations, stresses, and failure criteria that are inferred from in-situ, discrete-location strain measurements. This technology is commonly referred to as shape- and stress-sensing. Presented herein is a computationally efficient shape- and stress-sensing methodology that is ideally suited for applications to laminated composite and sandwich structures. The new approach employs the inverse Finite Element Method (iFEM) as a general framework and the Refined Zigzag Theory (RZT) as the underlying plate theory. A three-node inverse plate finite element is formulated. The element formulation enables robust and efficient modeling of plate structures instrumented with strain sensors that have arbitrary positions. The methodology leads to a set of linear algebraic equations that are solved efficiently for the unknown nodal displacements. These displacements are then used at the finite element level to compute full-field strains, stresses, and failure criteria that are in turn used to assess structural integrity. Numerical results for multilayered, highly heterogeneous laminates demonstrate the unique capability of this new formulation for shape- and stress-sensing.

Leveraging EAP-Sparsity for Compressed Sensing of MS-HARDI in (k, q)-Space.

PubMed

Sun, Jiaqi; Sakhaee, Elham; Entezari, Alireza; Vemuri, Baba C

2015-01-01

Compressed Sensing (CS) for the acceleration of MR scans has been widely investigated in the past decade. Lately, considerable progress has been made in achieving similar speed ups in acquiring multi-shell high angular resolution diffusion imaging (MS-HARDI) scans. Existing approaches in this context were primarily concerned with sparse reconstruction of the diffusion MR signal S(q) in the q-space. More recently, methods have been developed to apply the compressed sensing framework to the 6-dimensional joint (k, q)-space, thereby exploiting the redundancy in this 6D space. To guarantee accurate reconstruction from partial MS-HARDI data, the key ingredients of compressed sensing that need to be brought together are: (1) the function to be reconstructed needs to have a sparse representation, and (2) the data for reconstruction ought to be acquired in the dual domain (i.e., incoherent sensing) and (3) the reconstruction process involves a (convex) optimization. In this paper, we present a novel approach that uses partial Fourier sensing in the 6D space of (k, q) for the reconstruction of P(x, r). The distinct feature of our approach is a sparsity model that leverages surfacelets in conjunction with total variation for the joint sparse representation of P(x, r). Thus, our method stands to benefit from the practical guarantees for accurate reconstruction from partial (k, q)-space data. Further, we demonstrate significant savings in acquisition time over diffusion spectral imaging (DSI) which is commonly used as the benchmark for comparisons in reported literature. To demonstrate the benefits of this approach,.we present several synthetic and real data examples.

[Conserved motifs in voltage sensing proteins].

PubMed

Wang, Chang-He; Xie, Zhen-Li; Lv, Jian-Wei; Yu, Zhi-Dan; Shao, Shu-Li

2012-08-25

This paper was aimed to study conserved motifs of voltage sensing proteins (VSPs) and establish a voltage sensing model. All VSPs were collected from the Uniprot database using a comprehensive keyword search followed by manual curation, and the results indicated that there are only two types of known VSPs, voltage gated ion channels and voltage dependent phosphatases. All the VSPs have a common domain of four helical transmembrane segments (TMS, S1-S4), which constitute the voltage sensing module of the VSPs. The S1 segment was shown to be responsible for membrane targeting and insertion of these proteins, while S2-S4 segments, which can sense membrane potential, for protein properties. Conserved motifs/residues and their functional significance of each TMS were identified using profile-to-profile sequence alignments. Conserved motifs in these four segments are strikingly similar for all VSPs, especially, the conserved motif [RK]-X(2)-R-X(2)-R-X(2)-[RK] was presented in all the S4 segments, with positively charged arginine (R) alternating with two hydrophobic or uncharged residues. Movement of these arginines across the membrane electric field is the core mechanism by which the VSPs detect changes in membrane potential. The negatively charged aspartate (D) in the S3 segment is universally conserved in all the VSPs, suggesting that the aspartate residue may be involved in voltage sensing properties of VSPs as well as the electrostatic interactions with the positively charged residues in the S4 segment, which may enhance the thermodynamic stability of the S4 segments in plasma membrane.

Impaired vibrotactile sense in children and adolescents with type 1 diabetes - Signs of peripheral neuropathy.

PubMed

Ising, Erik; Dahlin, Lars B; Elding Larsson, Helena

2018-01-01

To investigate whether multi-frequency vibrometry can identify individuals with elevated vibration perception thresholds (VPTs), reflecting impaired vibrotactile sense, among children and adolescents with type 1 diabetes. In 72 pediatric patients with type 1 diabetes, VPTs were evaluated for seven frequencies on two sites of the hand, and five frequencies on two sites of the foot. Z-scores, based on previously collected reference data, were calculated. Perception to light touch was investigated using monofilaments. Subjects' characteristics were analyzed in comparison to normal and impaired vibrotactile sense. Subjects' median age, disease duration and age at disease onset were 12.8, 5.3 and 6.9 years, respectively. A total of 13 out of 72 (18%) subjects had impaired vibrotactile sense on at least one foot site. Impaired vibrotactile sense was more common among subjects treated with multiple daily insulin injections (MDI) compared to subjects treated with continuous subcutaneous insulin infusion (CSII) (p = 0.013). Age at disease onset was higher among subjects with impaired vibrotactile sense (p = 0.046). No significant correlations were found with gender, HbA1c or duration of diabetes. Impaired vibrotactile sense, mirroring diabetic peripheral neuropathy, was found in 1/5 of the children and adolescents in the study, and was more common in patients treated with MDI than in subjects treated with CSII.

Freshwater wetlands: fertile grounds for the invasive Phragmites australis in a climate change context

PubMed Central

Tougas-Tellier, Marie-Andrée; Morin, Jean; Hatin, Daniel; Lavoie, Claude

2015-01-01

Climate change will likely affect flooding regimes, which have a large influence on the functioning of freshwater riparian wetlands. Low water levels predicted for several fluvial systems make wetlands especially vulnerable to the spread of invaders, such as the common reed (Phragmites australis), one of the most invasive species in North America. We developed a model to map the distribution of potential germination grounds of the common reed in freshwater wetlands of the St. Lawrence River (Québec, Canada) under current climate conditions and used this model to predict their future distribution under two climate change scenarios simulated for 2050. We gathered historical and recent (remote sensing) data on the distribution of common reed stands for model calibration and validation purposes, then determined the parameters controlling the species establishment by seed. A two-dimensional model and the identified parameters were used to simulate the current (2010) and future (2050) distribution of germination grounds. Common reed stands are not widespread along the St. Lawrence River (212 ha), but our model suggests that current climate conditions are already conducive to considerable further expansion (>16,000 ha). Climate change may also exacerbate the expansion, particularly if river water levels drop, which will expose large bare areas propitious to seed germination. This phenomenon may be particularly important in one sector of the river, where existing common reed stands could increase their areas by a factor of 100, potentially creating the most extensive reedbed complex in North America. After colonizing salt and brackishwater marshes, the common reed could considerably expand into the freshwater marshes of North America which cover several million hectares. The effects of common reed expansion on biodiversity are difficult to predict, but likely to be highly deleterious given the competitiveness of the invader and the biological richness of freshwater wetlands. PMID:26380675

[Common sense, science and philosophy: the links of knowledge necessary for promoting health care].

PubMed

Rios, Ediara Rabello Girão; Franchi, Kristiane Mesquita Barros; da Silva, Raimunda Magalhães; de Amorim, Rosendo Freitas; Costa, Nhandeyjara de Carvalho

2007-01-01

In its evolution, humanity has accumulated data which were systematized as knowledge. Philosophy through self examination helps us in its practical and theoretical functions to reach a concept of the universe. Common sense helps science evolve. People's daily difficulties stir up the need for research, for deepening data interpretation and to propose solutions to overcome the population's problems. Science exists to explain difficult aspects of common sense, to support questions, as well as to substantiate knowledge produced as a response to demands. Thus, knowledge involved in this reflection sets out to foster an articulation between basic forms of knowledge and to develop a satisfactory understanding of the health care process, through a shared and critically consciousness view of the changes in the health system's paradigm. We understand that health education is an essential component within this process, provided that it is focused primarily on an individual belonging to a community with its multiple relationships, especially between the community context and the subjective dimension, which can provide citizenship empowerment redemption.

Cooperation in the dark: signalling and collective action in quorum-sensing bacteria.

PubMed

Brown, S P; Johnstone, R A

2001-05-07

The study of quorum-sensing bacteria has revealed a widespread mechanism of coordinating bacterial gene expression with cell density. By monitoring a constitutively produced signal molecule, individual bacteria can limit their expression of group-beneficial phenotypes to cell densities that guarantee an effective group outcome. In this paper, we attempt to move away from a commonly expressed view that these impressive feats of coordination are examples of multicellularity in prokaryotic populations. Here, we look more closely at the individual conflict underlying this cooperation, illustrating that, even under significant levels of genetic conflict, signalling and resultant cooperative behaviour can stably exist. A predictive two-trait model of signal strength and of the extent of cooperation is developed as a function of relatedness (reflecting multiplicity of infection) and basic population demographic parameters. The model predicts that the strength of quorum signalling will increase as conflict (multiplicity of infecting strains) increases, as individuals attempt to coax more cooperative contributions from their competitors, leading to a devaluation of the signal as an indicator of density. Conversely, as genetic conflict increases, the model predicts that the threshold density for cooperation will increase and the subsequent strength of group cooperation will be depressed.

Disaggregating census data for population mapping using random forests with remotely-sensed and ancillary data.

PubMed

Stevens, Forrest R; Gaughan, Andrea E; Linard, Catherine; Tatem, Andrew J

2015-01-01

High resolution, contemporary data on human population distributions are vital for measuring impacts of population growth, monitoring human-environment interactions and for planning and policy development. Many methods are used to disaggregate census data and predict population densities for finer scale, gridded population data sets. We present a new semi-automated dasymetric modeling approach that incorporates detailed census and ancillary data in a flexible, "Random Forest" estimation technique. We outline the combination of widely available, remotely-sensed and geospatial data that contribute to the modeled dasymetric weights and then use the Random Forest model to generate a gridded prediction of population density at ~100 m spatial resolution. This prediction layer is then used as the weighting surface to perform dasymetric redistribution of the census counts at a country level. As a case study we compare the new algorithm and its products for three countries (Vietnam, Cambodia, and Kenya) with other common gridded population data production methodologies. We discuss the advantages of the new method and increases over the accuracy and flexibility of those previous approaches. Finally, we outline how this algorithm will be extended to provide freely-available gridded population data sets for Africa, Asia and Latin America.

Predictive monitoring research: Summary of the PREMON system

NASA Technical Reports Server (NTRS)

Doyle, Richard J.; Sellers, Suzanne M.; Atkinson, David J.

1987-01-01

Traditional approaches to monitoring are proving inadequate in the face of two important issues: the dynamic adjustment of expectations about sensor values when the behavior of the device is too complex to enumerate beforehand, and the selective but effective interpretation of sensor readings when the number of sensors becomes overwhelming. This system addresses these issues by building an explicit model of a device and applying common-sense theories of physics to model causality in the device. The resulting causal simulation of the device supports planning decisions about how to efficiently yet reliably utilize a limited number of sensors to verify correct operation of the device.

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

USGS Publications Warehouse

Zimmermann, N.E.; Edwards, T.C.; Moisen, Gretchen G.; Frescino, T.S.; Blackard, J.A.

2007-01-01

1. Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. 2. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. 3. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. 4. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. 5. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. ?? 2007 The Authors.

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

PubMed Central

ZIMMERMANN, N E; EDWARDS, T C; MOISEN, G G; FRESCINO, T S; BLACKARD, J A

2007-01-01

Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. PMID:18642470

A remote sensing tool to monitor and predict epidemiologic outbreaks of Hanta virus infections and Lyme disease

NASA Astrophysics Data System (ADS)

Barrios, J. M.

2009-04-01

Lyme disease and Hanta virus infection are the result of the conjunction of several climatic and ecological conditions. Although both affections have different causal agents, they share an important characteristic which is the fact that rodents play an important role in the contagium. One of the most important agents in the dispersion of these diseases is the bank vole (Clethrionomys glareoulus). The bank vole is a common host for both, the Borrelia bacteria which via the ticks (Ixodes ricinus) reaches the human body and causes the Lyme disease, and the Nephropatia epidemica which is caused by Puumala Hantavirus and affects kidneys in humans. The prefered habitat of bank voles is broad-leaf forests with an important presence of beeches (Fagus sylvatica) and oaks (Quercus sp.) and a relatively dense low vegetation layer. These vegetation systems are common in West-Europe and their dynamics have a great influence in the bank voles population and, therefore, in the spreading of the infections this study is concerned about. The fact that the annual seed production is not stable in time has an important effect in bank voles population and, as it has been described in other studies, in the number of reported cases of Hanta virus infections and Lyme disease. The years in which an abundant production of seeds is observed are referred to as mast years which are believed to obey to cyclic patterns and to certain climatological characteristics of the preceding years. Statistical analysis have confirmed the correlation in the behaviour of the number of infected cases and the presence of mast years. This project aims at the design of a remote sensing based system (INFOPRESS - INFectious disease Outbreak Prediction REmote Sensing based System) that should enable local and national health care instances to predict and locate the occurrence of infection outbreaks and design policies to counteract undesired effects. The predictive capabilities of the system are based on the understanding and modelling of the interactions between relevant climatic parameters (temperature, humidity, precipitation) and the main features of vegetation systems which host the vectors and determine the survival and infectious potential of the causal agents. Among the most important study subjects in this research initiative one can mention the time series analysis of vegetation parameters derived from satellite remote sensing and its relatation to climatic time series and historical records of infected cases; with special attention to the assessment of remotely sensed evidences of the mast phenomenon. These analysis will constitute important buildind bricks in the construction of the INFOPRESS system in what concerns the assessment of the potentials of satellite remote sensing as information source for the prediction of infection outbreaks. The bank voles habitat description will also be supported by on-gound remote sensing techniques, specially Lidar technology and soil humidity modelling. These measurements are to be coupled to bank voles and ticks epidemiologic features obtained from field capturing and lab analysis.

How robust are burn severity indices when applied in a new region? Evaluation of alternate field-based and remote-sensing methods

Treesearch

C. Alina Cansler; Donald McKenzie

2012-01-01

Remotely sensed indices of burn severity are now commonly used by researchers and land managers to assess fire effects, but their relationship to field-based assessments of burn severity has been evaluated only in a few ecosystems. This analysis illustrates two cases in which methodological refinements to field-based and remotely sensed indices of burn severity...

Acetaminophen and acetone sensing capabilities of nickel ferrite nanostructures

NASA Astrophysics Data System (ADS)

Mondal, Shrabani; Kumari, Manisha; Madhuri, Rashmi; Sharma, Prashant K.

2017-07-01

Present work elucidates the gas sensing and electrochemical sensing capabilities of sol-gel-derived nickel ferrite (NF) nanostructures based on the electrical and electrochemical properties. In current work, the choices of target species (acetone and acetaminophen) are strictly governed by their practical utility and concerning the safety measures. Acetone, the target analyte for gas sensing measurement is a common chemical used in varieties of application as well as provides an indirect way to monitor diabetes. The gas sensing experiments were performed within a homemade sensing chamber designed by our group. Acetone gas sensor (NF pellet sensor) response was monitored by tracking the change in resistance both in the presence and absence of acetone. At optimum operating temperature 300 °C, NF pellet sensor exhibits selective response for acetone in the presence of other common interfering gases like ethanol, benzene, and toluene. The electrochemical sensor fabricated to determine acetaminophen is prepared by coating NF onto the surface of pre-treated/cleaned pencil graphite electrode (NF-PGE). The common name of target analyte acetaminophen is paracetamol (PC), which is widespread worldwide as a well-known pain killer. Overdose of PC can cause renal failure even fatal diseases in children and demand accurate monitoring. Under optimal conditions NF-PGE shows a detection limit as low as 0.106 μM with selective detection ability towards acetaminophen in the presence of ascorbic acid (AA), which co-exists in our body. Use of cheap and abundant PGE instead of other electrodes (gold/Pt/glassy carbon electrode) can effectively reduce the cost barrier of such sensors. The obtained results elucidate an ample appeal of NF-sensors in real analytical applications viz. in environmental monitoring, pharmaceutical industry, drug detection, and health monitoring.

Advanced Remote Sensing Research

USGS Publications Warehouse

Slonecker, Terrence; Jones, John W.; Price, Susan D.; Hogan, Dianna

2008-01-01

'Remote sensing' is a generic term for monitoring techniques that collect information without being in physical contact with the object of study. Overhead imagery from aircraft and satellite sensors provides the most common form of remotely sensed data and records the interaction of electromagnetic energy (usually visible light) with matter, such as the Earth's surface. Remotely sensed data are fundamental to geographic science. The Eastern Geographic Science Center (EGSC) of the U.S. Geological Survey (USGS) is currently conducting and promoting the research and development of three different aspects of remote sensing science: spectral analysis, automated orthorectification of historical imagery, and long wave infrared (LWIR) polarimetric imagery (PI).

Thermotropic Liquid Crystal-Assisted Chemical and Biological Sensors

PubMed Central

Honaker, Lawrence W.; Usol’tseva, Nadezhda; Mann, Elizabeth K.

2017-01-01

In this review article, we analyze recent progress in the application of liquid crystal-assisted advanced functional materials for sensing biological and chemical analytes. Multiple research groups demonstrate substantial interest in liquid crystal (LC) sensing platforms, generating an increasing number of scientific articles. We review trends in implementing LC sensing techniques and identify common problems related to the stability and reliability of the sensing materials as well as to experimental set-ups. Finally, we suggest possible means of bridging scientific findings to viable and attractive LC sensor platforms. PMID:29295530

A Novel Optical Model for Remote Sensing of Near-Surface Soil Moisture

NASA Astrophysics Data System (ADS)

Babaeian, E.; Sadeghi, M.; Jones, S. B.; Tuller, M.

2016-12-01

Common triangle and trapezoid methods that are based on both optical and thermal remote sensing (RS) information have been widely applied in the past to estimate near-surface soil moisture from the soil temperature - vegetation index space (e.g., LST-NDVI). For most cases, this approach assumes a linear relationship between soil moisture and temperature. Though this linearity assumption yields reasonable moisture estimates, it is not always justified as evidenced by laboratory and field measurements. Furthermore, this approach requires optical as well as thermal RS data for definition of the land surface temperature (LST) - vegetation index space, therefore, it is not applicable to satellites that do not provide thermal output such as the ESA Sentinel-2. To overcome these limitations, we propose a novel trapezoid model that only relies on optical NIR and SWIR data. The new model was validated using Sentinel-2 and Landsat-8 data for the semiarid Walnut Gulch (AZ) and sub humid Little Washita (OK) watersheds that vastly differ in land use and surface cover and provide excellent ground-truth moisture information from extensive sensor networks. Preliminary results for 2015-2016 indicate significant potential of the new model with a RMSE smaller than 4% volumetric near-surface moisture content and also confirm the enhanced utility of the high spatially and temporally resolved Sentinel-2 data.

Light- and water-use efficiency model synergy: a revised look at crop yield estimation for agricultural decision-making

NASA Astrophysics Data System (ADS)

Marshall, M.; Tu, K. P.

2015-12-01

Large-area crop yield models (LACMs) are commonly employed to address climate-driven changes in crop yield and inform policy makers concerned with climate change adaptation. Production efficiency models (PEMs), a class of LACMs that rely on the conservative response of carbon assimilation to incoming solar radiation absorbed by a crop contingent on environmental conditions, have increasingly been used over large areas with remote sensing spectral information to improve the spatial resolution of crop yield estimates and address important data gaps. Here, we present a new PEM that combines model principles from the remote sensing-based crop yield and evapotranspiration (ET) model literature. One of the major limitations of PEMs is that they are evaluated using data restricted in both space and time. To overcome this obstacle, we first validated the model using 2009-2014 eddy covariance flux tower Gross Primary Production data in a rice field in the Central Valley of California- a critical agro-ecosystem of the United States. This evaluation yielded a Willmot's D and mean absolute error of 0.81 and 5.24 g CO2/d, respectively, using CO2, leaf area, temperature, and moisture constraints from the MOD16 ET model, Priestley-Taylor ET model, and the Global Production Efficiency Model (GLOPEM). A Monte Carlo simulation revealed that the model was most sensitive to the Enhanced Vegetation Index (EVI) input, followed by Photosynthetically Active Radiation, vapor pressure deficit, and air temperature. The model will now be evaluated using 30 x 30m (Landsat resolution) biomass transects developed in 2011 and 2012 from spectroradiometric and other non-destructive in situ metrics for several cotton, maize, and rice fields across the Central Valley. Finally, the model will be driven by Daymet and MODIS data over the entire State of California and compared with county-level crop yield statistics. It is anticipated that the new model will facilitate agro-climatic decision-making in various regions across the globe and with different remote sensing inputs, given its interpretability, low data requirement, flexibility, and high correlation with in situ data.

Hyperspectral narrowband and multispectral broadband indices for remote sensing of crop evapotranspiration and its components (transpiration and soil evaporation)

USGS Publications Warehouse

Marshall, Michael T.; Thenkabail, Prasad S.; Biggs, Trent; Post, Kirk

2016-01-01

Evapotranspiration (ET) is an important component of micro- and macro-scale climatic processes. In agriculture, estimates of ET are frequently used to monitor droughts, schedule irrigation, and assess crop water productivity over large areas. Currently, in situ measurements of ET are difficult to scale up for regional applications, so remote sensing technology has been increasingly used to estimate crop ET. Ratio-based vegetation indices retrieved from optical remote sensing, like the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index, and Enhanced Vegetation Index are critical components of these models, particularly for the partitioning of ET into transpiration and soil evaporation. These indices have their limitations, however, and can induce large model bias and error. In this study, micrometeorological and spectroradiometric data collected over two growing seasons in cotton, maize, and rice fields in the Central Valley of California were used to identify spectral wavelengths from 428 to 2295 nm that produced the highest correlation to and lowest error with ET, transpiration, and soil evaporation. The analysis was performed with hyperspectral narrowbands (HNBs) at 10 nm intervals and multispectral broadbands (MSBBs) commonly retrieved by Earth observation platforms. The study revealed that (1) HNB indices consistently explained more variability in ET (ΔR2 = 0.12), transpiration (ΔR2 = 0.17), and soil evaporation (ΔR2 = 0.14) than MSBB indices; (2) the relationship between transpiration using the ratio-based index most commonly used for ET modeling, NDVI, was strong (R2 = 0.51), but the hyperspectral equivalent was superior (R2 = 0.68); and (3) soil evaporation was not estimated well using ratio-based indices from the literature (highest R2 = 0.37), but could be after further evaluation, using ratio-based indices centered on 743 and 953 nm (R2 = 0.72) or 428 and 1518 nm (R2 = 0.69).

The human genome as common heritage: common sense or legal nonsense?

PubMed

Ossorio, Pilar N

2007-01-01

This essay identifies two legal lineages underlying the common heritage concept, and applies each to the human genome. The essay notes some advantages and disadvantages of each approach, and argues that patenting of human genes would be allowable under either approach.

Common diagnoses and treatments in professional voice users.

PubMed

Franco, Ramon A; Andrus, Jennifer G

2007-10-01

Common problems among all patients seen by the laryngologist are also common among professional voice users. These include laryngopharyngeal reflux, muscle tension dysphonia, fibrovascular vocal fold lesions (eg, nodules and polyps), cysts, vocal fold scarring, changes in vocal fold mobility, and age-related changes. Microvascular lesions and their associated sequelae of vocal fold hemorrhage and laryngitis due to voice overuse are more common among professional voice users. Much more common among professional voice users is the negative impact that voice problems have on their ability to work, on their overall sense of well-being, and sometimes on their very sense of self. This article reviews the diagnosis and treatment options for these and other problems among professional voice users, describing the relevant roles of medical treatment, voice therapy, and surgery. The common scenario of multiple concomitant entities contributing to a symptom complex is underscored. Emphasis is placed on gaining insight into the "whole" patient so that individualized management plans can be developed. Videos of select diagnoses accompany this content online.

Phase detector for three-phase power factor controller

NASA Technical Reports Server (NTRS)

Nola, F. J. (Inventor)

1984-01-01

A phase detector for the three phase power factor controller (PFC) is described. The phase detector for each phase includes an operational amplifier which senses the current phase angle for that phase by sensing the voltage across the phase thyristor. Common mode rejection is achieved by providing positive feedback between the input and output of the voltage sensing operational amplifier. this feedback preferably comprises a resistor connected between the output and input of the operational amplifier. The novelty of the invention resides in providing positive feedback such that switching of the operational amplifier is synchronized with switching of the voltage across the thyristor. The invention provides a solution to problems associated with high common mode voltage and enables use of lower cost components than would be required by other approaches.

Potential Collaborative Research topics with Korea’s Agency for Defense Development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrar, Charles R.; Todd, Michael D.

2012-08-23

This presentation provides a high level summary of current research activities at the Los Alamos National Laboratory (LANL)-University of California Jacobs School of Engineering (UCSD) Engineering Institute that will be presented at Korea's Agency for Defense Development (ADD). These research activities are at the basic engineering science level with different level of maturity ranging from initial concepts to field proof-of-concept demonstrations. We believe that all of these activities are appropriate for collaborative research activities with ADD subject to approval by each institution. All the activities summarized herein have the common theme that they are multi-disciplinary in nature and typically involvedmore » the integration of high-fidelity predictive modeling, advanced sensing technologies and new development in information technology. These activities include: Wireless Sensor Systems, Swarming Robot sensor systems, Advanced signal processing (compressed sensing) and pattern recognition, Model Verification and Validation, Optimal/robust sensor system design, Haptic systems for large-scale data processing, Cyber-physical security for robots, Multi-source energy harvesting, Reliability-based approaches to damage prognosis, SHMTools software development, and Cyber-physical systems advanced study institute.« less

Specific absorption and backscatter coefficient signatures in southeastern Atlantic coastal waters

NASA Astrophysics Data System (ADS)

Bostater, Charles R., Jr.

1998-12-01

Measurements of natural water samples in the field and laboratory of hyperspectral signatures of total absorption and reflectance were obtained using long pathlength absorption systems (50 cm pathlength). Water was sampled in Indian River Lagoon, Banana River and Port Canaveral, Florida. Stations were also occupied in near coastal waters out to the edge of the Gulf Stream in the vicinity of Kennedy Space Center, Florida and estuarine waters along Port Royal Sound and along the Beaufort River tidal area in South Carolina. The measurements were utilized to calculate natural water specific absorption, total backscatter and specific backscatter optical signatures. The resulting optical cross section signatures suggest different models are needed for the different water types and that the common linear model may only appropriate for coastal and oceanic water types. Mean particle size estimates based on the optical cross section, suggest as expected, that particle size of oceanic particles are smaller than more turbid water types. The data discussed and presented are necessary for remote sensing applications of sensors as well as for development and inversion of remote sensing algorithms.

Processing Motion: Using Code to Teach Newtonian Physics

NASA Astrophysics Data System (ADS)

Massey, M. Ryan

Prior to instruction, students often possess a common-sense view of motion, which is inconsistent with Newtonian physics. Effective physics lessons therefore involve conceptual change. To provide a theoretical explanation for concepts and how they change, the triangulation model brings together key attributes of prototypes, exemplars, theories, Bayesian learning, ontological categories, and the causal model theory. The triangulation model provides a theoretical rationale for why coding is a viable method for physics instruction. As an experiment, thirty-two adolescent students participated in summer coding academies to learn how to design Newtonian simulations. Conceptual and attitudinal data was collected using the Force Concept Inventory and the Colorado Learning Attitudes about Science Survey. Results suggest that coding is an effective means for teaching Newtonian physics.

Research Advances on Radiation Transfer Modeling and Inversion for Multi-Scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.

2011-09-01

At first, research advances on radiation transfer modeling on multi-scale remote sensing data are presented: after a general overview of remote sensing radiation transfer modeling, several recent research advances are presented, including leaf spectrum model (dPROS-PECT), vegetation canopy BRDF models, directional thermal infrared emission models(TRGM, SLEC), rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed. The land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation etc. are taken as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is designed and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China will be introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

An inquiry into computer understanding

NASA Technical Reports Server (NTRS)

Cheeseman, Peter

1988-01-01

The paper examines issues connected with the choice of the best method for representing and reasoning about common sense. McDermott (1978) has shown that a direct translation of common sense reasoning into logical form leads to insurmountable difficulties. It is shown, in the present work, that if Bayesian probability is used instead of logic as the language of such reasoning, none of the technical difficulties found in using logic arise. Bayesian inference is applied to a simple example of linguistic information to illustrate the potential of this type of inference for artificial intelligence.

Sensing in the collaborative Internet of Things.

PubMed

Borges Neto, João B; Silva, Thiago H; Assunção, Renato Martins; Mini, Raquel A F; Loureiro, Antonio A F

2015-03-19

We are entering a new era of computing technology, the era of Internet of Things (IoT). An important element for this popularization is the large use of off-the-shelf sensors. Most of those sensors will be deployed by different owners, generally common users, creating what we call the Collaborative IoT. This collaborative IoT helps to increase considerably the amount and availability of collected data for different purposes, creating new interesting opportunities, but also several challenges. For example, it is very challenging to search for and select a desired sensor or a group of sensors when there is no description about the provided sensed data or when it is imprecise. Given that, in this work we characterize the properties of the sensed data in the Internet of Things, mainly the sensed data contributed by several sources, including sensors from common users. We conclude that, in order to safely use data available in the IoT, we need a filtering process to increase the data reliability. In this direction, we propose a new simple and powerful approach that helps to select reliable sensors. We tested our method for different types of sensed data, and the results reveal the effectiveness in the correct selection of sensor data.

Can hyperspectral remote sensing detect species specific biochemicals?

USDA-ARS?s Scientific Manuscript database

Discrimination of a few plants scattered among many plants is a goal common to detection of agricultural weeds and invasive species. Detection of clandestinely grown Cannabis sativa L. is in many ways a special case of weed detection. Remote sensing technology provides an automated, computer based,...

Rapid, highly sensitive detection of Gram-negative bacteria with lipopolysaccharide based disposable aptasensor.

PubMed

Zhang, Jian; Oueslati, Rania; Cheng, Cheng; Zhao, Ling; Chen, Jiangang; Almeida, Raul; Wu, Jayne

2018-07-30

Gram-negative bacteria are one of the most common microorganisms in the environment. Their differential detection and recognition from Gram-positive bacteria has been attracting much attention over the years. Using Escherichia coli (E. coli) as a model, we demonstrated on-site detection of Gram-negative bacteria by an AC electrokinetics-based capacitive sensing method using commercial microelectrodes functionalized with an aptamer specific to lipopolysaccharides. Dielectrophoresis effect was utilized to enrich viable bacteria to the microelectrodes rapidly, achieving a detection limit of 10 2 cells/mL within a 30 s' response time. The sensor showed a negligible response to Staphylococcus aureus (S. aureus), a Gram-positive species. The developed sensor showed significant advantages in sensitivity, selectivity, cost, operation simplicity, and response time. Therefore, this sensing method has shown great application potential for environmental monitoring, food safety, and real-time diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.

Start making sense: Art informing health psychology

PubMed Central

Hughes, Brian M; Murray, Michael; Smyth, Joshua M

2018-01-01

Growing evidence suggests that the arts may be useful in health care and in the training of health care professionals. Four art genres – novels, films, paintings and music – are examined for their potential contribution to enhancing patient health and/or making better health care providers. Based on a narrative literature review, we examine the effects of passive (e.g. reading, watching, viewing and listening) and active (e.g. writing, producing, painting and performing) exposure to the four art genres, by both patients and health care providers. Overall, an emerging body of empirical evidence indicates positive effects on psychological and physiological outcome measures in patients and some benefits to medical training. Expressive writing/emotional disclosure, psychoneuroimmunology, Theory of Mind and the Common Sense Model of Self-Regulation are considered as possible theoretical frameworks to help incorporate art genres as sources of inspiration for the further development of health psychology research and clinical applications. PMID:29552350

The Life Course Perspective: a Guide for Genetic Counselors.

PubMed

Hamilton, Rebekah J; Innella, Nancy A; Bounds, Dawn T

2016-02-01

This is the first article in a two part series about utilizing the life course perspective (LCP) in genetic counseling. LCP can be a useful tool for genetic counselors when counseling people with a known genetic mutation. Previous theories such as Protection Motivation Theory (PMT) and Common Sense Model of Self-Regulation (CSMSR) examine current reactions to a positive genetic test result. LCP extends beyond the current time to explore temporal and contextual elements of the experience. A review of research revealed, LCP has been used to study the perspective of caregivers of people with Alzheimer's disease, referral for a family history of breast cancer, Mexican American caregivers of older adult, social class and cancer incidence and cancer and the sense of mastery. Incorporating LCP into a study explaining the experiences of people living with a positive test result for a genetic mutation such as the BRCA mutation provides a comprehensive exploration of this experience.

Fast Detection of Airports on Remote Sensing Images with Single Shot MultiBox Detector

NASA Astrophysics Data System (ADS)

Xia, Fei; Li, HuiZhou

2018-01-01

This paper introduces a method for fast airport detection on remote sensing images (RSIs) using Single Shot MultiBox Detector (SSD). To our knowledge, this could be the first study which introduces an end-to-end detection model into airport detection on RSIs. Based on the common low-level features between natural images and RSIs, a convolution neural network trained on large amounts of natural images was transferred to tackle the airport detection problem with limited annotated data. To deal with the specific characteristics of RSIs, some related parameters in the SSD, such as the scales and layers, were modified for more accurate and rapider detection. The experiments show that the proposed method could achieve 83.5% Average Recall at 8 FPS on RSIs with the size of 1024*1024. In contrast to Faster R-CNN, an improvement on AP and speed could be obtained.

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, J. A.

1992-01-01

Research findings are summarized for projects dealing with the following: application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated Mie scatterers with size distribution and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; theoretical modeling for passive microwave remote sensing of earth terrain; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

Root gravitropism: an experimental tool to investigate basic cellular and molecular processes underlying mechanosensing and signal transmission in plants

NASA Technical Reports Server (NTRS)

Boonsirichai, K.; Guan, C.; Chen, R.; Masson, P. H.

2002-01-01

The ability of plant organs to use gravity as a guide for growth, named gravitropism, has been recognized for over two centuries. This growth response to the environment contributes significantly to the upward growth of shoots and the downward growth of roots commonly observed throughout the plant kingdom. Root gravitropism has received a great deal of attention because there is a physical separation between the primary site for gravity sensing, located in the root cap, and the site of differential growth response, located in the elongation zones (EZs). Hence, this system allows identification and characterization of different phases of gravitropism, including gravity perception, signal transduction, signal transmission, and curvature response. Recent studies support some aspects of an old model for gravity sensing, which postulates that root-cap columellar amyloplasts constitute the susceptors for gravity perception. Such studies have also allowed the identification of several molecules that appear to function as second messengers in gravity signal transduction and of potential signal transducers. Auxin has been implicated as a probable component of the signal that carries the gravitropic information between the gravity-sensing cap and the gravity-responding EZs. This has allowed the identification and characterization of important molecular processes underlying auxin transport and response in plants. New molecular models can be elaborated to explain how the gravity signal transduction pathway might regulate the polarity of auxin transport in roots. Further studies are required to test these models, as well as to study the molecular mechanisms underlying a poorly characterized phase of gravitropism that is independent of an auxin gradient.

A crisis of meaning: promoting new directions in science education

NASA Astrophysics Data System (ADS)

Heywood, David

2015-06-01

The polemic in science education of pupils being alienated, of the ideas that they encounter in science learning having little or no meaning because they do not resonate with their common sense experience, has been of concern for some considerable time in a science curriculum that privileges knowing over understanding. This is the context for the argument set out in: Enracinement or The earth, the originary ark, does not move— on the phenomenological (historical and ontogenetic) origin of common and scientific sense and the genetic method of teaching (for) understanding. At the core of the proposal is a call for a radical shift in pedagogy; finding more appropriate approaches to support learning in science that not only recognises, but proactively embraces learner experience of being in the world (quite literally earth bound) as the ` fundamental condition for conceiving.' The discussion sets out a theoretical rationale for a move to what is termed `the genetic method' in science education predicated on Husserl's contention that new understandings are only possible because they derive from a projection of grounded (literally in and of the earth, enracinement, i.e. rooting). In one sense, this implicitly challenges traditional orthodoxy in science education research in which (arguably) there is an implicit, however unintentionally, perceived deficit model of the learner typified in the use of terms such as misconception. In another, such a claim could appear overambitious and contentious. In an attempt to provide a balanced perspective, these tensions are explored through a focus on language in relation to the central hypothesis being offered.

Estimating Temperature Retrieval Accuracy Associated With Thermal Band Spatial Resolution Requirements for Center Pivot Irrigation Monitoring and Management

NASA Technical Reports Server (NTRS)

Ryan, Robert E.; Irons, James; Spruce, Joseph P.; Underwood, Lauren W.; Pagnutti, Mary

2006-01-01

This study explores the use of synthetic thermal center pivot irrigation scenes to estimate temperature retrieval accuracy for thermal remote sensed data, such as data acquired from current and proposed Landsat-like thermal systems. Center pivot irrigation is a common practice in the western United States and in other parts of the world where water resources are scarce. Wide-area ET (evapotranspiration) estimates and reliable water management decisions depend on accurate temperature information retrieval from remotely sensed data. Spatial resolution, sensor noise, and the temperature step between a field and its surrounding area impose limits on the ability to retrieve temperature information. Spatial resolution is an interrelationship between GSD (ground sample distance) and a measure of image sharpness, such as edge response or edge slope. Edge response and edge slope are intuitive, and direct measures of spatial resolution are easier to visualize and estimate than the more common Modulation Transfer Function or Point Spread Function. For these reasons, recent data specifications, such as those for the LDCM (Landsat Data Continuity Mission), have used GSD and edge response to specify spatial resolution. For this study, we have defined a 400-800 m diameter center pivot irrigation area with a large 25 K temperature step associated with a 300 K well-watered field surrounded by an infinite 325 K dry area. In this context, we defined the benchmark problem as an easily modeled, highly common stressing case. By parametrically varying GSD (30-240 m) and edge slope, we determined the number of pixels and field area fraction that meet a given temperature accuracy estimate for 400-m, 600-m, and 800-m diameter field sizes. Results of this project will help assess the utility of proposed specifications for the LDCM and other future thermal remote sensing missions and for water resource management.

Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria

USGS Publications Warehouse

Stumpf, Rick P; Davis, Timothy W.; Wynne, Timothy T.; Graham, Jennifer L.; Loftin, Keith A.; Johengen, T.H.; Gossiaux, D.; Palladino, D.; Burtner, A.

2016-01-01

Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments – since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins – especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates of microcystins from cyanobacterial biomass is described, provided cyanotoxin variability is addressed.

Testing the time-of-flight model for flagellar length sensing.

PubMed

Ishikawa, Hiroaki; Marshall, Wallace F

2017-11-07

Cilia and flagella are microtubule-based organelles that protrude from the surface of most cells, are important to the sensing of extracellular signals, and make a driving force for fluid flow. Maintenance of flagellar length requires an active transport process known as intraflagellar transport (IFT). Recent studies reveal that the amount of IFT injection negatively correlates with the length of flagella. These observations suggest that a length-dependent feedback regulates IFT. However, it is unknown how cells recognize the length of flagella and control IFT. Several theoretical models try to explain this feedback system. We focused on one of the models, the "time-of-flight" model, which measures the length of flagella on the basis of the travel time of IFT protein in the flagellar compartment. We tested the time-of-flight model using Chlamydomonas dynein mutant cells, which show slower retrograde transport speed. The amount of IFT injection in dynein mutant cells was higher than that in control cells. This observation does not support the prediction of the time-of-flight model and suggests that Chlamydomonas uses another length-control feedback system rather than that described by the time-of-flight model. © 2017 Ishikawa and Marshall. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Free acquisition and dissemination of data through remote sensing. [Landsat program legal aspects

NASA Technical Reports Server (NTRS)

Hosenball, S. N.

1976-01-01

Free acquisition and dissemination of data through remote sensing is discussed with reference to the Landsat program. The role of the Scientific and Technical Subcommittee of the U.N. General Assembly's Committee on the Peaceful Uses of Outer Space has made recommendations on the expansion of existing ground stations and on the establishment of an experimental center for training in remote sensing. The working group for the legal subcommittee of the same U.N. committee indicates that there are common elements in the three drafts on remote sensing submitted to it: a call for international cooperation and the belief that remote sensing should be conducted for the benefit of all mankind.

Advances in a distributed approach for ocean model data interoperability

USGS Publications Warehouse

Signell, Richard P.; Snowden, Derrick P.

2014-01-01

An infrastructure for earth science data is emerging across the globe based on common data models and web services. As we evolve from custom file formats and web sites to standards-based web services and tools, data is becoming easier to distribute, find and retrieve, leaving more time for science. We describe recent advances that make it easier for ocean model providers to share their data, and for users to search, access, analyze and visualize ocean data using MATLAB® and Python®. These include a technique for modelers to create aggregated, Climate and Forecast (CF) metadata convention datasets from collections of non-standard Network Common Data Form (NetCDF) output files, the capability to remotely access data from CF-1.6-compliant NetCDF files using the Open Geospatial Consortium (OGC) Sensor Observation Service (SOS), a metadata standard for unstructured grid model output (UGRID), and tools that utilize both CF and UGRID standards to allow interoperable data search, browse and access. We use examples from the U.S. Integrated Ocean Observing System (IOOS®) Coastal and Ocean Modeling Testbed, a project in which modelers using both structured and unstructured grid model output needed to share their results, to compare their results with other models, and to compare models with observed data. The same techniques used here for ocean modeling output can be applied to atmospheric and climate model output, remote sensing data, digital terrain and bathymetric data.

Evaluation of the Intel RealSense SR300 camera for image-guided interventions and application in vertebral level localization

NASA Astrophysics Data System (ADS)

House, Rachael; Lasso, Andras; Harish, Vinyas; Baum, Zachary; Fichtinger, Gabor

2017-03-01

PURPOSE: Optical pose tracking of medical instruments is often used in image-guided interventions. Unfortunately, compared to commonly used computing devices, optical trackers tend to be large, heavy, and expensive devices. Compact 3D vision systems, such as Intel RealSense cameras can capture 3D pose information at several magnitudes lower cost, size, and weight. We propose to use Intel SR300 device for applications where it is not practical or feasible to use conventional trackers and limited range and tracking accuracy is acceptable. We also put forward a vertebral level localization application utilizing the SR300 to reduce risk of wrong-level surgery. METHODS: The SR300 was utilized as an object tracker by extending the PLUS toolkit to support data collection from RealSense cameras. Accuracy of the camera was tested by comparing to a high-accuracy optical tracker. CT images of a lumbar spine phantom were obtained and used to create a 3D model in 3D Slicer. The SR300 was used to obtain a surface model of the phantom. Markers were attached to the phantom and a pointer and tracked using Intel RealSense SDK's built-in object tracking feature. 3D Slicer was used to align CT image with phantom using landmark registration and display the CT image overlaid on the optical image. RESULTS: Accuracy of the camera yielded a median position error of 3.3mm (95th percentile 6.7mm) and orientation error of 1.6° (95th percentile 4.3°) in a 20x16x10cm workspace, constantly maintaining proper marker orientation. The model and surface correctly aligned demonstrating the vertebral level localization application. CONCLUSION: The SR300 may be usable for pose tracking in medical procedures where limited accuracy is acceptable. Initial results suggest the SR300 is suitable for vertebral level localization.

Georeferencing CAMS data: Polynomial rectification and beyond

NASA Astrophysics Data System (ADS)

Yang, Xinghe

The Calibrated Airborne Multispectral Scanner (CAMS) is a sensor used in the commercial remote sensing program at NASA Stennis Space Center. In geographic applications of the CAMS data, accurate geometric rectification is essential for the analysis of the remotely sensed data and for the integration of the data into Geographic Information Systems (GIS). The commonly used rectification techniques such as the polynomial transformation and ortho rectification have been very successful in the field of remote sensing and GIS for most remote sensing data such as Landsat imagery, SPOT imagery and aerial photos. However, due to the geometric nature of the airborne line scanner which has high spatial frequency distortions, the polynomial model and the ortho rectification technique in current commercial software packages such as Erdas Imagine are not adequate for obtaining sufficient geometric accuracy. In this research, the geometric nature, especially the major distortions, of the CAMS data has been described. An analytical step-by-step geometric preprocessing has been utilized to deal with the potential high frequency distortions of the CAMS data. A generic sensor-independent photogrammetric model has been developed for the ortho-rectification of the CAMS data. Three generalized kernel classes and directional elliptical basis have been formulated into a rectification model of summation of multisurface functions, which is a significant extension to the traditional radial basis functions. The preprocessing mechanism has been fully incorporated into the polynomial, the triangle-based finite element analysis as well as the summation of multisurface functions. While the multisurface functions and the finite element analysis have the characteristics of localization, piecewise logic has been applied to the polynomial and photogrammetric methods, which can produce significant accuracy improvement over the global approach. A software module has been implemented with full integration of data preprocessing and rectification techniques under Erdas Imagine development environment. The final root mean square (RMS) errors for the test CAMS data are about two pixels which are compatible with the random RMS errors existed in the reference map coordinates.

Enriching Group Counseling through Integrating Yoga Concepts and Practices

ERIC Educational Resources Information Center

Rybak, Christopher; Deuskar, Megha

2010-01-01

Integrating practices from yoga with group counseling offers many creative paths of therapeutic learning. While yoga emphasizes the increased sense of connection with the self, group counseling emphasizes the increased sense of authenticity in relationship with oneself and with others. Common aims of both yoga and counseling are liberation from…

Applications of satellite remote sensing to forested ecosystems

Treesearch

Louis R. Iverson; Robin Lambert Graham; Elizabeth A. Cook; Elizabeth A. Cook

1989-01-01

Since the launch of the first civilian earth-observing satellite in 1972, satellite remote sensing has provided increasingly sophisticated information on the structure and function of forested ecosystems. Forest classification and mapping, common uses of satellite data, have improved over the years as a result of more discriminating sensors, better classification...

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. Aboutmore » 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). In conclusion, the relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.« less

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

DOE PAGES

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

2018-02-27

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. Aboutmore » 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). In conclusion, the relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.« less

[Estimation of desert vegetation coverage based on multi-source remote sensing data].

PubMed

Wan, Hong-Mei; Li, Xia; Dong, Dao-Rui

2012-12-01

Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study areaAbstract: Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study area and based on the ground investigation and the multi-source remote sensing data of different resolutions, the estimation models for desert vegetation coverage were built, with the precisions of different estimation methods and models compared. The results showed that with the increasing spatial resolution of remote sensing data, the precisions of the estimation models increased. The estimation precision of the models based on the high, middle-high, and middle-low resolution remote sensing data was 89.5%, 87.0%, and 84.56%, respectively, and the precisions of the remote sensing models were higher than that of vegetation index method. This study revealed the change patterns of the estimation precision of desert vegetation coverage based on different spatial resolution remote sensing data, and realized the quantitative conversion of the parameters and scales among the high, middle, and low spatial resolution remote sensing data of desert vegetation coverage, which would provide direct evidence for establishing and implementing comprehensive remote sensing monitoring scheme for the ecological restoration in the study area.

Radio frequency security system, method for a building facility or the like, and apparatus and methods for remotely monitoring the status of fire extinguishers

DOEpatents

Runyon, Larry [Richland, WA; Gunter, Wayne M [Richland, WA; Gilbert, Ronald W [Gilroy, CA

2006-07-25

A system for remotely monitoring the status of one or more fire extinguishers includes means for sensing at least one parameter of each of the fire extinguishers; means for selectively transmitting the sensed parameters along with information identifying the fire extinguishers from which the parameters were sensed; and means for receiving the sensed parameters and identifying information for the fire extinguisher or extinguishers at a common location. Other systems and methods for remotely monitoring the status of multiple fire extinguishers are also provided.

47 CFR 73.57 - Remote reading antenna and common point ammeters.

Code of Federal Regulations, 2010 CFR

2010-10-01

... remote leads to the indicating instruments. (2) Inductive coupling to radio frequency current sensing... 47 Telecommunication 4 2010-10-01 2010-10-01 false Remote reading antenna and common point... RADIO SERVICES RADIO BROADCAST SERVICES AM Broadcast Stations § 73.57 Remote reading antenna and common...

Robotic Quantification of Position Sense in Children With Perinatal Stroke.

PubMed

Kuczynski, Andrea M; Dukelow, Sean P; Semrau, Jennifer A; Kirton, Adam

2016-09-01

Background Perinatal stroke is the leading cause of hemiparetic cerebral palsy. Motor deficits and their treatment are commonly emphasized in the literature. Sensory dysfunction may be an important contributor to disability, but it is difficult to measure accurately clinically. Objective Use robotics to quantify position sense deficits in hemiparetic children with perinatal stroke and determine their association with common clinical measures. Methods Case-control study. Participants were children aged 6 to 19 years with magnetic resonance imaging-confirmed unilateral perinatal arterial ischemic stroke or periventricular venous infarction and symptomatic hemiparetic cerebral palsy. Participants completed a position matching task using an exoskeleton robotic device (KINARM). Position matching variability, shift, and expansion/contraction area were measured with and without vision. Robotic outcomes were compared across stroke groups and controls and to clinical measures of disability (Assisting Hand Assessment) and sensory function. Results Forty stroke participants (22 arterial, 18 venous, median age 12 years, 43% female) were compared with 60 healthy controls. Position sense variability was impaired in arterial (6.01 ± 1.8 cm) and venous (5.42 ± 1.8 cm) stroke compared to controls (3.54 ± 0.9 cm, P < .001) with vision occluded. Impairment remained when vision was restored. Robotic measures correlated with functional disability. Sensitivity and specificity of clinical sensory tests were modest. Conclusions Robotic assessment of position sense is feasible in children with perinatal stroke. Impairment is common and worse in arterial lesions. Limited correction with vision suggests cortical sensory network dysfunction. Disordered position sense may represent a therapeutic target in hemiparetic cerebral palsy. © The Author(s) 2016.

IGARSS 89: Canadian Symposium on Remote Sensing (12th) (Symposium Canadien sur la Teledetection): Quantitative Remote Sensing: An Economic Tool for the Nineties Held in Vancouver, Canada on 10-14 July 1989. Volume 2. Tuesday, July 11

DTIC Science & Technology

1989-07-14

active SAR calibration up bottom of lake, a flat desert, a surface of the target (Brunfeldt, 1982) is commonly used because still water or a largo place...Margalef, R., "Composicion y distribucion del Smith, and R. G. Steward, "Remote Sensing fitoplancton", Memoria , Sociedad de algorithms for

Estimators of primary production for interpretation of remotely sensed data on ocean color

NASA Technical Reports Server (NTRS)

Platt, Trevor; Sathyendranath, Shubha

1993-01-01

The theoretical basis is explained for some commonly used estimators of daily primary production in a vertically uniform water column. These models are recast into a canonical form, with dimensionless arguments, to facilitate comparison with each other and with an analytic solution. The limitations of each model are examined. The values of the photoadaptation parameter I(k) observed in the ocean are analyzed, and I(k) is used as a scale to normalize the surface irradiance. The range of this scaled irradiance is presented. An equation is given for estimation of I(k) from recent light history. It is shown how the models for water column production can be adapted for estimation of the production in finite layers. The distinctions between model formulation, model implementation and model evaluation are discussed. Recommendations are given on the choice of algorithm for computation of daily production according to the degree of approximation acceptable in the result.

Limits to the precision of gradient sensing with spatial communication and temporal integration

PubMed Central

Mugler, Andrew; Levchenko, Andre; Nemenman, Ilya

2016-01-01

Gradient sensing requires at least two measurements at different points in space. These measurements must then be communicated to a common location to be compared, which is unavoidably noisy. Although much is known about the limits of measurement precision by cells, the limits placed by the communication are not understood. Motivated by recent experiments, we derive the fundamental limits to the precision of gradient sensing in a multicellular system, accounting for communication and temporal integration. The gradient is estimated by comparing a “local” and a “global” molecular reporter of the external concentration, where the global reporter is exchanged between neighboring cells. Using the fluctuation–dissipation framework, we find, in contrast to the case when communication is ignored, that precision saturates with the number of cells independently of the measurement time duration, because communication establishes a maximum length scale over which sensory information can be reliably conveyed. Surprisingly, we also find that precision is improved if the local reporter is exchanged between cells as well, albeit more slowly than the global reporter. The reason is that whereas exchange of the local reporter weakens the comparison, it decreases the measurement noise. We term such a model “regional excitation–global inhibition.” Our results demonstrate that fundamental sensing limits are necessarily sharpened when the need to communicate information is taken into account. PMID:26792517

The I/O transform of a chemical sensor

PubMed Central

Katta, Nalin; Meier, Douglas C.; Benkstein, Kurt D.; Semancik, Steve; Raman, Baranidharan

2016-01-01

A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing. PMID:27932855

Migration and pension.

PubMed

Razin, A; Sadka, E

1998-11-01

"Migration has important implications for the financial soundness of the pension system.... While it is common sense to expect that young migrants, even if low-skilled, can help society pay the benefits to the currently elderly, it may nevertheless be reasonable to argue that these migrants would adversely affect current young since, after all, the migrants are net beneficiaries of the welfare state. In contrast to the adverse effects of low skilled migration in a static model, [the authors] show that in a Samuelsonian overlapping generations model...migration is a Pareto-improving measure. All the existing income (low and high) and age (young and old) groups living at the time of the migrant's arrival would be better off." excerpt

A study of remote sensing as applied to regional and small watersheds. Volume 1: Summary report

NASA Technical Reports Server (NTRS)

Ambaruch, R.

1974-01-01

The accuracy of remotely sensed measurements to provide inputs to hydrologic models of watersheds is studied. A series of sensitivity analyses on continuous simulation models of three watersheds determined: (1)Optimal values and permissible tolerances of inputs to achieve accurate simulation of streamflow from the watersheds; (2) Which model inputs can be quantified from remote sensing, directly, indirectly or by inference; and (3) How accurate remotely sensed measurements (from spacecraft or aircraft) must be to provide a basis for quantifying model inputs within permissible tolerances.

Self-sensing in Bacillus subtilis quorum-sensing systems

PubMed Central

Bareia, Tasneem; Pollak, Shaul; Eldar, Avigdor

2017-01-01

Bacterial cell-cell signaling, or quorum sensing, is characterized by the secretion and group-wide detection of small diffusible signal molecules called autoinducers. This mechanism allows cells to coordinate their behavior in a density-dependent manner. A quorum-sensing cell may directly respond to the autoinducers it produces in a cell-autonomous and quorum-independent manner, but the strength of such self-sensing effect and its impact on bacterial physiology are unclear. Here, we explored the existence and impact of self-sensing in the Bacillus subtilis ComQXP and Rap-Phr quorum-sensing systems. By comparing the quorum-sensing response of autoinducer-secreting and non-secreting cells in co-culture, we found that secreting cells consistently showed a stronger response than non-secreting cells. Combining genetic and quantitative analyses, we demonstrated this effect to be a direct result of self-sensing and ruled out an indirect regulatory effect of the autoinducer production genes on response sensitivity. In addition, self-sensing in the ComQXP system affected persistence to antibiotic treatment. Together, these findings indicate the existence of self-sensing in the two most common designs of quorum-sensing systems of Gram-positive bacteria. PMID:29038467

Most genetic risk for autism resides with common variation.

PubMed

Gaugler, Trent; Klei, Lambertus; Sanders, Stephan J; Bodea, Corneliu A; Goldberg, Arthur P; Lee, Ann B; Mahajan, Milind; Manaa, Dina; Pawitan, Yudi; Reichert, Jennifer; Ripke, Stephan; Sandin, Sven; Sklar, Pamela; Svantesson, Oscar; Reichenberg, Abraham; Hultman, Christina M; Devlin, Bernie; Roeder, Kathryn; Buxbaum, Joseph D

2014-08-01

A key component of genetic architecture is the allelic spectrum influencing trait variability. For autism spectrum disorder (herein termed autism), the nature of the allelic spectrum is uncertain. Individual risk-associated genes have been identified from rare variation, especially de novo mutations. From this evidence, one might conclude that rare variation dominates the allelic spectrum in autism, yet recent studies show that common variation, individually of small effect, has substantial impact en masse. At issue is how much of an impact relative to rare variation this common variation has. Using a unique epidemiological sample from Sweden, new methods that distinguish total narrow-sense heritability from that due to common variation and synthesis of results from other studies, we reach several conclusions about autism's genetic architecture: its narrow-sense heritability is ∼52.4%, with most due to common variation, and rare de novo mutations contribute substantially to individual liability, yet their contribution to variance in liability, 2.6%, is modest compared to that for heritable variation.

Data Quality Screening Service

NASA Technical Reports Server (NTRS)

Strub, Richard; Lynnes, Christopher; Hearty, Thomas; Won, Young-In; Fox, Peter; Zednik, Stephan

2013-01-01

A report describes the Data Quality Screening Service (DQSS), which is designed to help automate the filtering of remote sensing data on behalf of science users. Whereas this process often involves much research through quality documents followed by laborious coding, the DQSS is a Web Service that provides data users with data pre-filtered to their particular criteria, while at the same time guiding the user with filtering recommendations of the cognizant data experts. The DQSS design is based on a formal semantic Web ontology that describes data fields and the quality fields for applying quality control within a data product. The accompanying code base handles several remote sensing datasets and quality control schemes for data products stored in Hierarchical Data Format (HDF), a common format for NASA remote sensing data. Together, the ontology and code support a variety of quality control schemes through the implementation of the Boolean expression with simple, reusable conditional expressions as operands. Additional datasets are added to the DQSS simply by registering instances in the ontology if they follow a quality scheme that is already modeled in the ontology. New quality schemes are added by extending the ontology and adding code for each new scheme.

Tipping Points, Great and Small

NASA Astrophysics Data System (ADS)

Morrison, Foster

2010-12-01

The Forum by Jordan et al. [2010] addressed environmental problems of various scales in great detail, but getting the critical message through to the formulators of public policies requires going back to basics, namely, that exponential growth (of a population, an economy, or most anything else) is not sustainable. When have you heard any politician or economist from anywhere across the ideological spectrum say anything other than that more growth is essential? There is no need for computer models to demonstrate “limits to growth,” as was done in the 1960s. Of course, as one seeks more details, the complexity of modeling will rapidly outstrip the capabilities of both observation and computing. This is common with nonlinear systems, even simple ones. Thus, identifying all possible “tipping points,” as suggested by Jordan et al. [2010], and then stopping just short of them, is impractical if not impossible. The main thing needed to avoid environmental disasters is a bit of common sense.

A Mathematical Model for the Hippocampus: Towards the Understanding of Episodic Memory and Imagination

NASA Astrophysics Data System (ADS)

Tsuda, I.; Yamaguti, Y.; Kuroda, S.; Fukushima, Y.; Tsukada, M.

How does the brain encode episode? Based on the fact that the hippocampus is responsible for the formation of episodic memory, we have proposed a mathematical model for the hippocampus. Because episodic memory includes a time series of events, an underlying dynamics for the formation of episodic memory is considered to employ an association of memories. David Marr correctly pointed out in his theory of archecortex for a simple memory that the hippocampal CA3 is responsible for the formation of associative memories. However, a conventional mathematical model of associative memory simply guarantees a single association of memory unless a rule for an order of successive association of memories is given. The recent clinical studies in Maguire's group for the patients with the hippocampal lesion show that the patients cannot make a new story, because of the lack of ability of imagining new things. Both episodic memory and imagining things include various common characteristics: imagery, the sense of now, retrieval of semantic information, and narrative structures. Taking into account these findings, we propose a mathematical model of the hippocampus in order to understand the common mechanism of episodic memory and imagination.

DARLA: Data Assimilation and Remote Sensing for Littoral Applications

NASA Astrophysics Data System (ADS)

Jessup, A.; Holman, R. A.; Chickadel, C.; Elgar, S.; Farquharson, G.; Haller, M. C.; Kurapov, A. L.; Özkan-Haller, H. T.; Raubenheimer, B.; Thomson, J. M.

2012-12-01

DARLA is 5-year collaborative project that couples state-of-the-art remote sensing and in situ measurements with advanced data assimilation (DA) modeling to (a) evaluate and improve remote sensing retrieval algorithms for environmental parameters, (b) determine the extent to which remote sensing data can be used in place of in situ data in models, and (c) infer bathymetry for littoral environments by combining remotely-sensed parameters and data assimilation models. The project uses microwave, electro-optical, and infrared techniques to characterize the littoral ocean with a focus on wave and current parameters required for DA modeling. In conjunction with the RIVET (River and Inlets) Project, extensive in situ measurements provide ground truth for both the remote sensing retrieval algorithms and the DA modeling. Our goal is to use remote sensing to constrain data assimilation models of wave and circulation dynamics in a tidal inlet and surrounding beaches. We seek to improve environmental parameter estimation via remote sensing fusion, determine the success of using remote sensing data to drive DA models, and produce a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments. The objectives are to test the following three hypotheses: 1. Environmental parameter estimation using remote sensing techniques can be significantly improved by fusion of multiple sensor products. 2. Data assimilation models can be adequately constrained (i.e., forced or guided) with environmental parameters derived from remote sensing measurements. 3. Bathymetry on open beaches, river mouths, and at tidal inlets can be inferred from a combination of remotely-sensed parameters and data assimilation models. Our approach is to conduct a series of field experiments combining remote sensing and in situ measurements to investigate signature physics and to gather data for developing and testing DA models. A preliminary experiment conducted at the Field Research Facility at Duck, NC in September 2010 focused on assimilation of tower-based electo-optical, infrared, and radar measurements in predictions of longshore currents. Here we provide an overview of our contribution to the RIVET I experiment at New River Inlet, NC in May 2012. During the course of the 3-week measurement period, continuous tower-based remote sensing measurements were made using electro-optical, infrared, and radar techniques covering the nearshore zone and the inlet mouth. A total of 50 hours of airborne measurements were made using high-resolution infrared imagers and a customized along track interferometric synthetic aperture radar (ATI SAR). The airborne IR imagery provides kilometer-scale mapping of frontal features that evolve as the inlet flow interacts with the oceanic wave and current fields. The ATI SAR provides maps of the two-dimensional surface currents. Near-surface measurements of turbulent velocities and surface waves using SWIFT drifters, designed to measures near-surface properties relevant to remote sensing, complimented the extensive in situ measurements by RIVET investigators.

Swimming Upstream: The Experience of Academic Mothers of Young Children

ERIC Educational Resources Information Center

Hirakata, Pam E.; Daniluk, Judith C.

2009-01-01

A qualitative phenomenological approach was used to explore the experiences of 10 tenured and untenured women from various disciplines who were engaged in academic careers while mothering pre-teen children. Analysis of the in-depth interview data uncovered six themes common to the participants: (a) sense of vulnerability, (b) sense of isolation,…

Comparison of standard maximum likelihood classification and polytomous logistic regression used in remote sensing

Treesearch

John Hogland; Nedret Billor; Nathaniel Anderson

2013-01-01

Discriminant analysis, referred to as maximum likelihood classification within popular remote sensing software packages, is a common supervised technique used by analysts. Polytomous logistic regression (PLR), also referred to as multinomial logistic regression, is an alternative classification approach that is less restrictive, more flexible, and easy to interpret. To...

Create a Sense of Place for the Mobile Learner

ERIC Educational Resources Information Center

Hemmig, William; Johnstone, Brian T.; Montet, Margaret

2012-01-01

"Sense of place" no longer applies only to the physical library. All students are distance learners to one extent or another, and all distance services must be considered as a single virtual learning commons. Librarians at Bucks County (PA) Community College implement and integrate current teaching, learning, virtual reference, and mobile access…

Biomimicry of quorum sensing using bacterial lifecycle model.

PubMed

Niu, Ben; Wang, Hong; Duan, Qiqi; Li, Li

2013-01-01

Recent microbiologic studies have shown that quorum sensing mechanisms, which serve as one of the fundamental requirements for bacterial survival, exist widely in bacterial intra- and inter-species cell-cell communication. Many simulation models, inspired by the social behavior of natural organisms, are presented to provide new approaches for solving realistic optimization problems. Most of these simulation models follow population-based modelling approaches, where all the individuals are updated according to the same rules. Therefore, it is difficult to maintain the diversity of the population. In this paper, we present a computational model termed LCM-QS, which simulates the bacterial quorum-sensing (QS) mechanism using an individual-based modelling approach under the framework of Agent-Environment-Rule (AER) scheme, i.e. bacterial lifecycle model (LCM). LCM-QS model can be classified into three main sub-models: chemotaxis with QS sub-model, reproduction and elimination sub-model and migration sub-model. The proposed model is used to not only imitate the bacterial evolution process at the single-cell level, but also concentrate on the study of bacterial macroscopic behaviour. Comparative experiments under four different scenarios have been conducted in an artificial 3-D environment with nutrients and noxious distribution. Detailed study on bacterial chemotatic processes with quorum sensing and without quorum sensing are compared. By using quorum sensing mechanisms, artificial bacteria working together can find the nutrient concentration (or global optimum) quickly in the artificial environment. Biomimicry of quorum sensing mechanisms using the lifecycle model allows the artificial bacteria endowed with the communication abilities, which are essential to obtain more valuable information to guide their search cooperatively towards the preferred nutrient concentrations. It can also provide an inspiration for designing new swarm intelligence optimization algorithms, which can be used for solving the real-world problems.

Biomimicry of quorum sensing using bacterial lifecycle model

PubMed Central

2013-01-01

Background Recent microbiologic studies have shown that quorum sensing mechanisms, which serve as one of the fundamental requirements for bacterial survival, exist widely in bacterial intra- and inter-species cell-cell communication. Many simulation models, inspired by the social behavior of natural organisms, are presented to provide new approaches for solving realistic optimization problems. Most of these simulation models follow population-based modelling approaches, where all the individuals are updated according to the same rules. Therefore, it is difficult to maintain the diversity of the population. Results In this paper, we present a computational model termed LCM-QS, which simulates the bacterial quorum-sensing (QS) mechanism using an individual-based modelling approach under the framework of Agent-Environment-Rule (AER) scheme, i.e. bacterial lifecycle model (LCM). LCM-QS model can be classified into three main sub-models: chemotaxis with QS sub-model, reproduction and elimination sub-model and migration sub-model. The proposed model is used to not only imitate the bacterial evolution process at the single-cell level, but also concentrate on the study of bacterial macroscopic behaviour. Comparative experiments under four different scenarios have been conducted in an artificial 3-D environment with nutrients and noxious distribution. Detailed study on bacterial chemotatic processes with quorum sensing and without quorum sensing are compared. By using quorum sensing mechanisms, artificial bacteria working together can find the nutrient concentration (or global optimum) quickly in the artificial environment. Conclusions Biomimicry of quorum sensing mechanisms using the lifecycle model allows the artificial bacteria endowed with the communication abilities, which are essential to obtain more valuable information to guide their search cooperatively towards the preferred nutrient concentrations. It can also provide an inspiration for designing new swarm intelligence optimization algorithms, which can be used for solving the real-world problems. PMID:23815296

A remote sensing tool to monitor and predict epidemiologic outbreaks of Hanta virus infections and Lyme disease

NASA Astrophysics Data System (ADS)

Barrios, M.; Verstraeten, W. W.; Amipour, S.; Wambacq, J.; Aerts, J.-M.; Maes, P.; Berckmans, D.; Lagrou, K.; van Ranst, M.; Coppin, P.

2009-04-01

Lyme disease and Hanta virus infection are the result of the conjunction of several climatic and ecological conditions. Although both affections have different causal agents, they share an important characteristic which is the fact that rodents play an important role in the contagion. One of the most important agents in the dispersion of these diseases is the bank vole (Clethrionomys glareoulus). The bank vole is a common host for both, the Borrelia bacteria which via the ticks (Ixodes ricinus) reaches the human body and causes the Lyme disease, and the Nephropatia epidemica which is caused by Puumala Hantavirus and affects kidneys in humans. The prefered habitat of bank voles is broad-leaf forests with an important presence of beeches (Fagus sylvatica) and oaks (Quercus sp.) and a relatively dense low vegetation layer. These vegetation systems are common in West-Europe and their dynamics have a great influence in the bank voles population and, therefore, in the spreading of the infections this study is concerned about. The fact that the annual seed production is not stable in time has an important effect in bank voles population and, as it has been described in other studies, in the number of reported cases of Hanta virus infections and Lyme disease. The years in which an abundant production of seeds is observed are referred to as mast years which are believed to obey to cyclic patterns and to certain climatologically characteristics of the preceding years. Statistical analysis have confirmed the correlation in the behaviour of the number of infected cases and the presence of mast years. This project aims at the design of a remote sensing based system (INFOPRESS - INFectious disease Outbreak Prediction REmote Sensing based System) that should enable local and national health care instances to predict and locate the occurrence of infection outbreaks and design policies to counteract undesired effects. The predictive capabilities of the system are based on the understanding and modelling of the interactions between relevant climatic parameters (temperature, humidity, precipitation) and the main features of vegetation systems which host the vectors and determine the survival and infectious potential of the causal agents. Among the most important study subjects in this research initiative one can mention the time series analysis of vegetation parameters derived from satellite remote sensing and its relation to climatic time series and historical records of infected cases; with special attention to the assessment of remotely sensed evidences of the mast phenomenon. This analysis will constitute important buildind bricks in the construction of the INFOPRESS system in what concerns the assessment of the potentials of satellite remote sensing as information source for the prediction of infection outbreaks. The bank voles habitat description will also be supported by on-ground remote sensing techniques, specially LiDAR technology and soil humidity modelling. These measurements are to be coupled to bank voles epidemiologic features obtained from field capturing and lab analysis in which the presence of Hanta virus will be assessed.

Disentangling Gratitude: A Theoretical and Psychometric Examination of the Gratitude Resentment and Appreciation Test-Revised Short (GRAT-RS).

PubMed

Hammer, Joseph H; Brenner, Rachel E

2017-07-14

This study extended our theoretical and applied understanding of gratitude through a psychometric examination of the most popular multidimensional measure of gratitude, the Gratitude, Resentment, and Appreciation Test-Revised Short form (GRAT-RS). Namely, the dimensionality of the GRAT-RS, the model-based reliability of the GRAT-RS total score and 3 subscale scores, and the incremental evidence of validity for its latent factors were assessed. Dimensionality measures (e.g., explained common variance) and confirmatory factor analysis results with 426 community adults indicated that the GRAT-RS conformed to a multidimensional (bifactor) structure. Model-based reliability measures (e.g., omega hierarchical) provided support for the future use of the Lack of a Sense of Deprivation raw subscale score, but not for the raw GRAT-RS total score, Simple Appreciation subscale score, or Appreciation of Others subscale score. Structural equation modeling results indicated that only the general gratitude factor and the lack of a sense of deprivation specific factor accounted for significant variance in life satisfaction, positive affect, and distress. These findings support the 3 pillars of gratitude conceptualization of gratitude over competing conceptualizations, the position that the specific forms of gratitude are theoretically distinct, and the argument that appreciation is distinct from the superordinate construct of gratitude.

Disaggregating Census Data for Population Mapping Using Random Forests with Remotely-Sensed and Ancillary Data

PubMed Central

Stevens, Forrest R.; Gaughan, Andrea E.; Linard, Catherine; Tatem, Andrew J.

2015-01-01

High resolution, contemporary data on human population distributions are vital for measuring impacts of population growth, monitoring human-environment interactions and for planning and policy development. Many methods are used to disaggregate census data and predict population densities for finer scale, gridded population data sets. We present a new semi-automated dasymetric modeling approach that incorporates detailed census and ancillary data in a flexible, “Random Forest” estimation technique. We outline the combination of widely available, remotely-sensed and geospatial data that contribute to the modeled dasymetric weights and then use the Random Forest model to generate a gridded prediction of population density at ~100 m spatial resolution. This prediction layer is then used as the weighting surface to perform dasymetric redistribution of the census counts at a country level. As a case study we compare the new algorithm and its products for three countries (Vietnam, Cambodia, and Kenya) with other common gridded population data production methodologies. We discuss the advantages of the new method and increases over the accuracy and flexibility of those previous approaches. Finally, we outline how this algorithm will be extended to provide freely-available gridded population data sets for Africa, Asia and Latin America. PMID:25689585

Dynamic sensing model for accurate delectability of environmental phenomena using event wireless sensor network

NASA Astrophysics Data System (ADS)

Missif, Lial Raja; Kadhum, Mohammad M.

2017-09-01

Wireless Sensor Network (WSN) has been widely used for monitoring where sensors are deployed to operate independently to sense abnormal phenomena. Most of the proposed environmental monitoring systems are designed based on a predetermined sensing range which does not reflect the sensor reliability, event characteristics, and the environment conditions. Measuring of the capability of a sensor node to accurately detect an event within a sensing field is of great important for monitoring applications. This paper presents an efficient mechanism for even detection based on probabilistic sensing model. Different models have been presented theoretically in this paper to examine their adaptability and applicability to the real environment applications. The numerical results of the experimental evaluation have showed that the probabilistic sensing model provides accurate observation and delectability of an event, and it can be utilized for different environment scenarios.

Human eye haptics-based multimedia.

PubMed

Velandia, David; Uribe-Quevedo, Alvaro; Perez-Gutierrez, Byron

2014-01-01

Immersive and interactive multimedia applications offer complementary study tools in anatomy as users can explore 3D models while obtaining information about the organ, tissue or part being explored. Haptics increases the sense of interaction with virtual objects improving user experience in a more realistic manner. Common eye studying tools are books, illustrations, assembly models, and more recently these are being complemented with mobile apps whose 3D capabilities, computing power and customers are increasing. The goal of this project is to develop a complementary eye anatomy and pathology study tool using deformable models within a multimedia application, offering the students the opportunity for exploring the eye from up close and within with relevant information. Validation of the tool provided feedback on the potential of the development, along with suggestions on improving haptic feedback and navigation.

Contextual Sensing: Integrating Contextual Information with Human and Technical Geo-Sensor Information for Smart Cities

PubMed Central

Sagl, Günther; Resch, Bernd; Blaschke, Thomas

2015-01-01

In this article we critically discuss the challenge of integrating contextual information, in particular spatiotemporal contextual information, with human and technical sensor information, which we approach from a geospatial perspective. We start by highlighting the significance of context in general and spatiotemporal context in particular and introduce a smart city model of interactions between humans, the environment, and technology, with context at the common interface. We then focus on both the intentional and the unintentional sensing capabilities of today’s technologies and discuss current technological trends that we consider have the ability to enrich human and technical geo-sensor information with contextual detail. The different types of sensors used to collect contextual information are analyzed and sorted into three groups on the basis of names considering frequently used related terms, and characteristic contextual parameters. These three groups, namely technical in situ sensors, technical remote sensors, and human sensors are analyzed and linked to three dimensions involved in sensing (data generation, geographic phenomena, and type of sensing). In contrast to other scientific publications, we found a large number of technologies and applications using in situ and mobile technical sensors within the context of smart cities, and surprisingly limited use of remote sensing approaches. In this article we further provide a critical discussion of possible impacts and influences of both technical and human sensing approaches on society, pointing out that a larger number of sensors, increased fusion of information, and the use of standardized data formats and interfaces will not necessarily result in any improvement in the quality of life of the citizens of a smart city. This article seeks to improve our understanding of technical and human geo-sensing capabilities, and to demonstrate that the use of such sensors can facilitate the integration of different types of contextual information, thus providing an additional, namely the geo-spatial perspective on the future development of smart cities. PMID:26184221

Contextual Sensing: Integrating Contextual Information with Human and Technical Geo-Sensor Information for Smart Cities.

PubMed

Sagl, Günther; Resch, Bernd; Blaschke, Thomas

2015-07-14

In this article we critically discuss the challenge of integrating contextual information, in particular spatiotemporal contextual information, with human and technical sensor information, which we approach from a geospatial perspective. We start by highlighting the significance of context in general and spatiotemporal context in particular and introduce a smart city model of interactions between humans, the environment, and technology, with context at the common interface. We then focus on both the intentional and the unintentional sensing capabilities of today's technologies and discuss current technological trends that we consider have the ability to enrich human and technical geo-sensor information with contextual detail. The different types of sensors used to collect contextual information are analyzed and sorted into three groups on the basis of names considering frequently used related terms, and characteristic contextual parameters. These three groups, namely technical in situ sensors, technical remote sensors, and human sensors are analyzed and linked to three dimensions involved in sensing (data generation, geographic phenomena, and type of sensing). In contrast to other scientific publications, we found a large number of technologies and applications using in situ and mobile technical sensors within the context of smart cities, and surprisingly limited use of remote sensing approaches. In this article we further provide a critical discussion of possible impacts and influences of both technical and human sensing approaches on society, pointing out that a larger number of sensors, increased fusion of information, and the use of standardized data formats and interfaces will not necessarily result in any improvement in the quality of life of the citizens of a smart city. This article seeks to improve our understanding of technical and human geo-sensing capabilities, and to demonstrate that the use of such sensors can facilitate the integration of different types of contextual information, thus providing an additional, namely the geo-spatial perspective on the future development of smart cities.

Research Advances on Radiation Transfer Modeling and Inversion for Multi-scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.; Li, J.; Du, Y.; Wen, J.; Zhong, B.; Wang, K.

2011-12-01

As the remote sensing data accumulating, it is a challenge and significant issue how to generate high accurate and consistent land surface parameter product from the multi source remote observation and the radiation transfer modeling and inversion methodology are the theoretical bases. In this paper, recent research advances and unresolved issues are presented. At first, after a general overview, recent research advances on multi-scale remote sensing radiation transfer modeling are presented, including leaf spectrum model, vegetation canopy BRDF models, directional thermal infrared emission models, rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed, taking the land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is suggested and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China are introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

NASA Astrophysics Data System (ADS)

Diao, Chunyuan

In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of saltcedar. The multiyear spectral angle clustering model could guide the selection of the most representative remotely sensed image for repetitive saltcedar mapping over space and time. Through incorporating spatial autocorrelation, the species distribution model developed in the study could identify the suitable habitats of saltcedar at a fine spatial scale and locate appropriate areas at high risk of saltcedar infestation. Among 10 environmental variables, the distance to the river and the phenological attributes summarized by the time series remote sensing were regarded as the most important. These methods developed in the study provide new perspectives on how the continuous time series can be leveraged under various conditions to investigate the plant invasion dynamics.

Sensing in the Collaborative Internet of Things

PubMed Central

Borges Neto, João B.; Silva, Thiago H.; Assunção, Renato Martins; Mini, Raquel A. F.; Loureiro, Antonio A. F.

2015-01-01

We are entering a new era of computing technology, the era of Internet of Things (IoT). An important element for this popularization is the large use of off-the-shelf sensors. Most of those sensors will be deployed by different owners, generally common users, creating what we call the Collaborative IoT. This collaborative IoT helps to increase considerably the amount and availability of collected data for different purposes, creating new interesting opportunities, but also several challenges. For example, it is very challenging to search for and select a desired sensor or a group of sensors when there is no description about the provided sensed data or when it is imprecise. Given that, in this work we characterize the properties of the sensed data in the Internet of Things, mainly the sensed data contributed by several sources, including sensors from common users. We conclude that, in order to safely use data available in the IoT, we need a filtering process to increase the data reliability. In this direction, we propose a new simple and powerful approach that helps to select reliable sensors. We tested our method for different types of sensed data, and the results reveal the effectiveness in the correct selection of sensor data. PMID:25808766

DOE Office of Scientific and Technical Information (OSTI.GOV)

Herbert, J.H.

This brief note describes the probabilistic structure of the Arps/Roberts (A/R) model of petroleum discovery. A model similar to the A/R model is derived from probabilistic propositions demonstrated to be similar to the E. Barouch/G.M. Kaufman (B/K) model, and also demonstrated to be similar to the Drew, Schuenemeyer, and Root (D/S/R) model. This note attempts to elucidate and to simplify some fundamental ideas contained in an unpublished paper by Barouch and Kaufman. This note and its predecessor paper does not attempt to address a wide variety of statistical approaches for estimating petroleum resource availability. Rather, an attempt is made tomore » draw attention to characteristics of certain methods that are commonly used, both formally and informally, to estimate a petroleum resource base for a basin or a nation. Some of these characteristics are statistical, but many are not, except in the broadest sense of the term.« less

Development of mathematical techniques for the assimilation of remote sensing data into atmospheric models

NASA Technical Reports Server (NTRS)

Seinfeld, J. H. (Principal Investigator)

1982-01-01

The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The data assimilation problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three-dimensional concentration fields from atmospheric diffusion models. General conditions were derived for the reconstructability of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data was developed.

Development of mathematical techniques for the assimilation of remote sensing data into atmospheric models

NASA Technical Reports Server (NTRS)

Seinfeld, J. H. (Principal Investigator)

1982-01-01

The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three dimensional concentration fields from atmospheric diffusion models. General conditions are derived for the "reconstructability' of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data is developed.

Observing and modeling dynamics in terrestrial gross primary productivity and phenology from remote sensing: An assessment using in-situ measurements

NASA Astrophysics Data System (ADS)

Verma, Manish K.

Terrestrial gross primary productivity (GPP) is the largest and most variable component of the carbon cycle and is strongly influenced by phenology. Realistic characterization of spatio-temporal variation in GPP and phenology is therefore crucial for understanding dynamics in the global carbon cycle. In the last two decades, remote sensing has become a widely-used tool for this purpose. However, no study has comprehensively examined how well remote sensing models capture spatiotemporal patterns in GPP, and validation of remote sensing-based phenology models is limited. Using in-situ data from 144 eddy covariance towers located in all major biomes, I assessed the ability of 10 remote sensing-based methods to capture spatio-temporal variation in GPP at annual and seasonal scales. The models are based on different hypotheses regarding ecophysiological controls on GPP and span a range of structural and computational complexity. The results lead to four main conclusions: (i) at annual time scale, models were more successful capturing spatial variability than temporal variability; (ii) at seasonal scale, models were more successful in capturing average seasonal variability than interannual variability; (iii) simpler models performed as well or better than complex models; and (iv) models that were best at explaining seasonal variability in GPP were different from those that were best able to explain variability in annual scale GPP. Seasonal phenology of vegetation follows bounded growth and decay, and is widely modeled using growth functions. However, the specific form of the growth function affects how phenological dynamics are represented in ecosystem and remote sensing-base models. To examine this, four different growth functions (the logistic, Gompertz, Mirror-Gompertz and Richards function) were assessed using remotely sensed and in-situ data collected at several deciduous forest sites. All of the growth functions provided good statistical representation of in-situ and remote sensing time series. However, the Richards function captured observed asymmetric dynamics that were not captured by the other functions. The timing of key phenophase transitions derived using the Richards function therefore agreed best with observations. This suggests that ecosystem models and remote-sensing algorithms would benefit from using the Richards function to represent phenological dynamics.

Interpreting intracorporeal landscapes: how patients visualize pathophysiology and utilize medical images in their understanding of chronic musculoskeletal illness.

PubMed

Moore, Andrew J; Richardson, Jane C; Bernard, Miriam; Sim, Julius

2018-02-26

Medical science and other sources, such as the media, increasingly inform the general public's understanding of disease. There is often discordance between this understanding and the diagnostic interpretations of health care practitioners (HCPs). In this paper - based on a supra-analysis of qualitative interview data from two studies of joint pain, including osteoarthritis - we investigate how people imagine and make sense of the pathophysiology of their illness, and how these understandings may affect self-management behavior. We then explore how HCPs' use of medical images and models can inform patients' understanding. In conceptualizing their illness to make sense of their experience of the disease, individuals often used visualizations of their inner body; these images may arise from their own lay understanding, or may be based on images provided by HCPs. When HCPs used anatomical models or medical images judiciously, patients' orientation to their illness changed. Including patients in a more collaborative diagnostic event that uses medical images and visual models to support explanations about their condition may help them to achieve a more meaningful understanding of their illness and to manage their condition more effectively. Implications for Rehabilitation Chronic musculoskeletal pain is a leading cause of pain and years lived with disability, and despite its being common, patients and healthcare professionals often have a different understanding of the underlying disease. An individual's understanding of his or her pathophysiology plays an important role in making sense of painful joint conditions and in decision-making about self-management and care. Including patients in a more collaborative diagnostic event using medical images and anatomical models to support explanations about their symptoms may help them to better understand their condition and manage it more effectively. Using visually informed explanations and anatomical models may also help to reassure patients about the safety and effectiveness of core treatments such as physical exercise and thereby help restore or improve patients' activity levels and return to social participation.

Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

NASA Technical Reports Server (NTRS)

Miller, L. D.; Tom, C.; Nualchawee, K.

1977-01-01

A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

Assimilation of remote sensing observations into a sediment transport model of China's largest freshwater lake: spatial and temporal effects.

PubMed

Zhang, Peng; Chen, Xiaoling; Lu, Jianzhong; Zhang, Wei

2015-12-01

Numerical models are important tools that are used in studies of sediment dynamics in inland and coastal waters, and these models can now benefit from the use of integrated remote sensing observations. This study explores a scheme for assimilating remotely sensed suspended sediment (from charge-coupled device (CCD) images obtained from the Huanjing (HJ) satellite) into a two-dimensional sediment transport model of Poyang Lake, the largest freshwater lake in China. Optimal interpolation is used as the assimilation method, and model predictions are obtained by combining four remote sensing images. The parameters for optimal interpolation are determined through a series of assimilation experiments evaluating the sediment predictions based on field measurements. The model with assimilation of remotely sensed sediment reduces the root-mean-square error of the predicted sediment concentrations by 39.4% relative to the model without assimilation, demonstrating the effectiveness of the assimilation scheme. The spatial effect of assimilation is explored by comparing model predictions with remotely sensed sediment, revealing that the model with assimilation generates reasonable spatial distribution patterns of suspended sediment. The temporal effect of assimilation on the model's predictive capabilities varies spatially, with an average temporal effect of approximately 10.8 days. The current velocities which dominate the rate and direction of sediment transport most likely result in spatial differences in the temporal effect of assimilation on model predictions.

Is eating science or common sense? Knowledge about "natural foods" among self-identified "natural food" consumers, vendors and producers in rural and urban Mexico.

PubMed

Kooijmans, Anneke; Flores-Palacios, Fátima

2014-10-01

To explore the common sense knowledge that consumers, vendors and producers hold of "natural foods". The focus was on common knowledge because this is infrequently explored in social psychology where most studies focus on the implementation of scientific knowledge. The focus was on natural foods because the naturalness of foods seems to be one of the particular concerns that current consumers have about today's food market and because a specific natural food preference was observed in the contexts of study. Fifty-seven informants in a rural context and 58 informants in an urban context participated in either a free association study or an interview study. Data content were analyzed. In the urban context natural foods obtain their significance in the relationship between food and the self-concept; eating natural (or good) food is a task that requires effort and attitude, and foods obtain a moral value. In the rural context natural foods obtain their significance as an expression of a social and cultural system of interdependence that establishes practices and customs that have a long history in the community. It is suggested that these common knowledge systems are related to practical challenges that are particular to the informants' context and that the structure of their common sense knowledge systems depend on the mediation of the flow of scientific knowledge and technological knowledge in each context. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cognitive and affective determinants of decisions to attend a group psychosocial support program for women with breast cancer.

PubMed

Cameron, Linda D; Booth, Roger J; Schlatter, Melanie; Ziginskas, Danute; Harman, John E; Benson, Stephen R C

2005-01-01

This prospective study assesses the roles of illness beliefs, emotion regulation factors, and sociodemographic characteristics in decisions to participate in a group support program for women recently diagnosed with breast cancer. Women recruited during clinic visits 2 to 4 weeks after diagnosis completed measures of affective and cognitive factors identified by Leventhal's Common-Sense Model of illness self-regulation: cancer-related distress, avoidance tendencies, beliefs that the breast cancer was caused by stress and altered immunity, and personal control beliefs. Measures of general anxiety and depression, social support, and demographic characteristics were also completed; prognostic status information was obtained from medical records. All women were encouraged to participate in a free, 12-week program offering coping skills training and group support. Participation was recorded by program staff. Of the 110 women, 54 (49%) participated in the group support program and 56 (51%) did not. Logistic regression analyses revealed that participation was predicted by stronger beliefs that the cancer was caused by altered immunity, higher cancer-related distress, lower avoidance tendencies, and younger age. Participation in the group psychosocial support program appeared to be guided by cognitive and affective factors identified by the Common-Sense Model. Psychosocial support programs and informational materials promoting their use may attract more participants if they are tailored to focus on resolving cancer-related distress rather than on general anxiety or depression, appeal to those with high avoidance tendencies, address the role of immune function in cancer progression, and meet the needs of older participants.

Understanding surgery choices for breast cancer: how might the Theory of Planned Behaviour and the Common Sense Model contribute to decision support interventions?

PubMed Central

Sivell, Stephanie; Edwards, Adrian; Elwyn, Glyn; Manstead, Antony S. R.

2010-01-01

Abstract Objective  To describe the evidence about factors influencing breast cancer patients’ surgery choices and the implications for designing decision support in reference to an extended Theory of Planned Behaviour (TPB) and the Common Sense Model of Illness Representations (CSM). Background  A wide range of factors are known to influence the surgery choices of women diagnosed with early breast cancer facing the choice of mastectomy or breast conservation surgery with radiotherapy. However, research does not always reflect the complexities of decision making and is often atheoretical. A theoretical approach, as provided by the CSM and the TPB, could help to identify and tailor support by focusing on patients’ representations of their breast cancer and predicting surgery choices. Design  Literature search and narrative synthesis of data. Synthesis  Twenty‐six studies reported women’s surgery choices to be influenced by perceived clinical outcomes of surgery, appearance and body image, treatment concerns, involvement in decision making and preferences of clinicians. These factors can be mapped onto the key constructs of both the TPB and CSM and used to inform the design and development of decision support interventions to ensure accurate information is provided in areas most important to patients. Conclusions  The TPB and CSM have the potential to inform the design of decision support for breast cancer patients, with accurate and clear information that avoids leading patients to make decisions they may come to regret. Further research is needed examining how the components of the extended TPB and CSM account for patients’ surgery choices. PMID:20579123

Evaporation from irrigated crops: Its measurement, modeling and estimation from remotely sensed data

NASA Astrophysics Data System (ADS)

Garatuza-Payan, Jaime

The research described in this dissertation is predicated on the hypothesis that remotely sensed information from climatological satellites can be used to estimate the actual evapotranspiration from agricultural crops to improve irrigation scheduling and water use efficiency. The goal of the enabling research program described here was to facilitate and demonstrate the potential use of satellite data for the rapid and routine estimation of water use by irrigated crops in the Yaqui Valley irrigation scheme, an extensive irrigated area in Sonora, Mexico. The approach taken was first, to measure and model the evapotranspiration and crop factors for wheat and cotton, the most common irrigated crops in the Yaqui Valley scheme. Second, to develop and test a high-resolution (4 km x 4 km) method for determining cloud cover and solar radiation from GOES satellite data. Then third, to demonstrate the application of satellite data to calculate the actual evaporation for sample crops in the Yaqui Valley scheme by combining estimates of potential rate with relevant crop factors and information on crop management. Results show that it is feasible to provide routine estimates of evaporation for the most common crops in the Yaqui Valley irrigation scheme from satellite data. Accordingly, a system to provide such estimates has been established and the Water Users Association, the entity responsible for water distribution in Yaqui Valley, can now use them to decide whether specific fields need irrigation. A Web site (teka-pucem.itson.mx) is also being created which will allow individual farmers to have direct access to the evaporation estimates via the Internet.

ATHENA: Remote Sensing Science Center for Cultural Heritage in Cyprus

NASA Astrophysics Data System (ADS)

Hadjimitsis, Diofantos G.; Agapiou, Athos; Lysandrou, Vasiliki; Themistocleous, Kyriakos; Cuca, Branka; Lasaponara, Rosa; Masini, Nicola; Krauss, Thomas; Cerra, Daniele; Gessner, Ursula; Schreier, Gunter

2016-04-01

The Cultural Heritage (CH) sector, especially those of monuments and sites has always been facing a number of challenges from environmental pressure, pollution, human intervention from tourism to destruction by terrorism.Within this context, CH professionals are seeking to improve currently used methodologies, in order to better understand, protect and valorise the common European past and common identity. "ATHENA" H2020-TWINN-2015 project will seek to improve and expand the capabilities of the Cyprus University of Technology, involving professionals dealing with remote sensing technologies for supporting CH sector from the National Research Center of Italy (CNR) and German Aerospace Centre (DLR). The ATHENA centre will be devoted to the development, introduction and systematic use of advanced remote sensing science and technologies in the field of archaeology, built cultural heritage, their multi-temporal analysis and interpretation and the distant monitoring of their natural and anthropogenic environment in the area of Eastern Mediterranean.

Sense of Belonging and Persistence in White and African American First-Year Students

ERIC Educational Resources Information Center

Hausmann, Leslie R. M.; Ye, Feifei; Schofield, Janet Ward; Woods, Rochelle L.

2009-01-01

The authors argue for the inclusion of students' subjective sense of belonging in an integrated model of student persistence (Cabrera et al., J Higher Educ 64:123-139, 1993). The effects of sense of belonging and a simple intervention designed to increase sense of belonging are tested in the context of this model. The intervention increased sense…

Feedback about action performed can alter the sense of self-agency

PubMed Central

Kumar, Neeraj; Manjaly, Jaison A.; Miyapuram, Krishna P.

2014-01-01

Sense of agency refers to the sense of authorship of an action and its outcome. Sense of agency is often explained through computational models of motor control (e.g., the comparator model). Previous studies using the comparator model have manipulated action-outcome contingency to understand its effect on the sense of agency. More recent studies have shown that cues related to outcome, priming outcome and priming action have an effect on agency attribution. However, relatively few studies have focused on the effect of recalibrating internal predictions on the sense of agency. This study aims to investigate how feedback about action can recalibrate prediction and modulates the sense of agency. While participants performed a Flanker task, we manipulated the feedback about the validity of the action performed, independent of their responses. When true feedback is given, the sense of agency would reflect congruency between the sensory outcome and the action performed. The results show an opposite effect on the sense of agency when false feedback was given. We propose that feedback about action performed can recalibrate the prediction of sensory outcome and thus alter the sense of agency. PMID:24611059

Remote sensing-based predictors improve distribution models of rare, early successional and boradleaf tree species in Utah

Treesearch

N. E. Zimmermann; T. C. Edwards; G. G. Moisen; T. S. Frescino; J. A. Blackard

2007-01-01

Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species...

Offshore Wind Resource Characterization | Wind | NREL

Science.gov Websites

identify critical data needed. Remote Sensing and Modeling Photo of the SeaZephIR Prototype at sea. 2009 techniques such as remote sensing and modeling to provide data on design conditions. Research includes comparing the data provided by remote sensing devices and models to data collected by traditional methods

Microwave Remote Sensing Modeling of Ocean Surface Salinity and Winds Using an Empirical Sea Surface Spectrum

NASA Technical Reports Server (NTRS)

Yueh, Simon H.

2004-01-01

Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.

Integrating Remote Sensing and Citizen Science to Study the Environmental Context and Ecological Consequences of Returning Avian Predators

NASA Astrophysics Data System (ADS)

Zuckerberg, B.; McCabe, J.; Yin, H.; Pidgeon, A. M.; Bonter, D. N.; Radeloff, V.

2017-12-01

Urbanization causes the simplification of animal communities dominated by exotic and invasive species with few top predators. In recent years, however, many animal predators (e.g., coyotes, cougars, and hawks) have become increasingly common in urban environments. As predator recovery is central to the mission of conservation biology, this colonization of urban environments represents a unique experiment in predator colonization and its associated ecological consequences. One such predator that is recovering from decades of widespread population declines are accipiter hawks. These woodland hawks are widely distributed throughout North America and are increasingly common in urban and suburban landscapes. Using data from Project FeederWatch, a national citizen science program, we quantified 25 years (1990-2015) of changes in the spatiotemporal dynamics of accipiter hawks in Washington D.C. and Chicago. We estimated change in hawk occupancy over time and identified the environmental characteristics associated with occupancy for two accipiter hawk species, Cooper's Hawk (Accipiter cooperii) and Sharp-shinned Hawk (Accipiter striatus), using Bayesian hierarchical models and remotely-sensed temperature (MODIS) and land cover data (NLCD). We found the proportion of sites recording the presence of accipiter hawks increased from 10% in the early 1990's to over 80% in 2015. This increase in occupancy followed a discrete pattern of establishment, growth, and saturation. Colonizing hawks were more strongly associated with remnant forest patches in urban environments. Over time, we found hawks became more tolerant of urban landscapes with higher amounts of impervious surface, suggesting that these predators became adapted to urbanization. The implications of returning predators and altered ecological dynamics in urban environments is of critical importance to conservation biology, and integrating remote sensing observations and citizen science allowed for an unprecedented investigation of the urban characteristics facilitating predator colonization.

An Eye Does Not Make an I: Expanding the Sensorium

ERIC Educational Resources Information Center

Duncum, Paul

2012-01-01

While visual art appeals to the sense of sight, both recent art and popular visual culture appeal to the whole sensorium, the sum total of the ways we experience the world. Common assumptions about the senses regarding their number, their relative importance, and their relation to one another are problematized in light of recent psychological and…

Principled Neglect and Compliance: Responses to NCLB and the CCSS at an Expeditionary Learning Middle School

ERIC Educational Resources Information Center

Stern, Rebecca

2016-01-01

This qualitative study explored educators' sense making of and responses to No Child Left Behind and the Common Core State Standards at one urban Expeditionary Learning middle school. Sense-making theory (Spillane, Reiser, & Reimer, 2002) and inquiry as stance (Cochran-Smith & Lytle, 2009) were used as complementary conceptual frameworks…

Common Sense Government. Works Better and Costs Less. Third Report of the National Performance Review.

ERIC Educational Resources Information Center

Gore, Al

This publication reports on the progress of the Clinton Administration's effort to reinvent the Federal government bureaucracy and how it operates and serves citizens. Part 1, "A Government that Makes Sense," describes the progress that reinventing government has made and reviews the context in which the initiative was launched including…

A model framework for actuation and sensing of ionic polymer-metal composites: prospective on frequency and shear response through simulation tools

NASA Astrophysics Data System (ADS)

Stalbaum, Tyler; Shen, Qi; Kim, Kwang J.

2017-04-01

Ionic polymer-metal composite (IPMC) is a promising material for soft-robotic actuator and sensor applications. This material system offers large deformation response for low input voltage and has an aptitude for operation in hydrated environments. Researchers have been developing IPMC actuators and sensors for applications with examples of self-sensing actuators, artificial fish fins and biomimicry of other aquatic lifeforms, and in medical operations such as in guided catheter devices. IPMCs have been developed in a range of geometric configurations, with tube or cylindrical and flat-plate rectangular as the most common shapes. Several mathematical and physics-based models have been developed for describing the transduction effects of IPMCs. In this work, the underlying theories of electromechanical and mechanoelectrical transduction in IPMCs are discussed, and simulated results of frequency response and shear response are presented. A model backbone is utilized which is primarily based on ion-transport and charge dynamics within the polymer membrane. The electromechanical model, that is with an IPMC as an actuator, is caused when an electric field is applied across the membrane causing ionic migration and swelling in the polymer membrane, which is based on the Poisson-Nernst-Planck equations and solid mechanics models. The mechanoelectric model is similar in underlying physics; however, the primary mechanisms of transduction are of different significance, where anion concentrations are as important as cations. COMSOL Multiphysics is utilized for simulations. Example applications of the modeling framework are presented. The simulated results provide additional support for the underlying physics theories discussed.

Research on bathymetry estimation by Worldview-2 based with the semi-analytical model

NASA Astrophysics Data System (ADS)

Sheng, L.; Bai, J.; Zhou, G.-W.; Zhao, Y.; Li, Y.-C.

2015-04-01

South Sea Islands of China are far away from the mainland, the reefs takes more than 95% of south sea, and most reefs scatter over interested dispute sensitive area. Thus, the methods of obtaining the reefs bathymetry accurately are urgent to be developed. Common used method, including sonar, airborne laser and remote sensing estimation, are limited by the long distance, large area and sensitive location. Remote sensing data provides an effective way for bathymetry estimation without touching over large area, by the relationship between spectrum information and bathymetry. Aimed at the water quality of the south sea of China, our paper develops a bathymetry estimation method without measured water depth. Firstly the semi-analytical optimization model of the theoretical interpretation models has been studied based on the genetic algorithm to optimize the model. Meanwhile, OpenMP parallel computing algorithm has been introduced to greatly increase the speed of the semi-analytical optimization model. One island of south sea in China is selected as our study area, the measured water depth are used to evaluate the accuracy of bathymetry estimation from Worldview-2 multispectral images. The results show that: the semi-analytical optimization model based on genetic algorithm has good results in our study area;the accuracy of estimated bathymetry in the 0-20 meters shallow water area is accepted.Semi-analytical optimization model based on genetic algorithm solves the problem of the bathymetry estimation without water depth measurement. Generally, our paper provides a new bathymetry estimation method for the sensitive reefs far away from mainland.

Helping Behavior: Effects of Stress and Commonality of Fate on Females.

ERIC Educational Resources Information Center

Hayden, Shelly R.; And Others

Research has suggested that people not sharing a common fate lack a sense of group identity, thus decreasing the tendency for helping behavior. To study the effects of stress and commonality of fate on helping behavior, 60 female college students participated in a replication of an earlier study which used male subjects. Participants were assigned…

The Common Sense Guide to the Common Core: Teacher-Tested Tools for Implementation

ERIC Educational Resources Information Center

McKnight, Katherine

2014-01-01

Based on the original source document for the Common Core State Standards and tested by 1,000 educators in diverse classrooms across the country, these research-based tools will help readers examine their current practices and adapt existing curriculum. Each of the 40 tools is clearly presented, explained, and exemplified, guiding educators…

Remote sensing applications to hydrologic modeling

NASA Technical Reports Server (NTRS)

Dozier, J.; Estes, J. E.; Simonett, D. S.; Davis, R.; Frew, J.; Marks, D.; Schiffman, K.; Souza, M.; Witebsky, E.

1977-01-01

An energy balance snowmelt model for rugged terrain was devised and coupled to a flow model. A literature review of remote sensing applications to hydrologic modeling was included along with a software development outline.

Semantic labeling of high-resolution aerial images using an ensemble of fully convolutional networks

NASA Astrophysics Data System (ADS)

Sun, Xiaofeng; Shen, Shuhan; Lin, Xiangguo; Hu, Zhanyi

2017-10-01

High-resolution remote sensing data classification has been a challenging and promising research topic in the community of remote sensing. In recent years, with the rapid advances of deep learning, remarkable progress has been made in this field, which facilitates a transition from hand-crafted features designing to an automatic end-to-end learning. A deep fully convolutional networks (FCNs) based ensemble learning method is proposed to label the high-resolution aerial images. To fully tap the potentials of FCNs, both the Visual Geometry Group network and a deeper residual network, ResNet, are employed. Furthermore, to enlarge training samples with diversity and gain better generalization, in addition to the commonly used data augmentation methods (e.g., rotation, multiscale, and aspect ratio) in the literature, aerial images from other datasets are also collected for cross-scene learning. Finally, we combine these learned models to form an effective FCN ensemble and refine the results using a fully connected conditional random field graph model. Experiments on the ISPRS 2-D Semantic Labeling Contest dataset show that our proposed end-to-end classification method achieves an overall accuracy of 90.7%, a state-of-the-art in the field.

Effects of vegetation types on soil moisture estimation from the normalized land surface temperature versus vegetation index space

NASA Astrophysics Data System (ADS)

Zhang, Dianjun; Zhou, Guoqing

2015-12-01

Soil moisture (SM) is a key variable that has been widely used in many environmental studies. Land surface temperature versus vegetation index (LST-VI) space becomes a common way to estimate SM in optical remote sensing applications. Normalized LST-VI space is established by the normalized LST and VI to obtain the comparable SM in Zhang et al. (Validation of a practical normalized soil moisture model with in situ measurements in humid and semiarid regions [J]. International Journal of Remote Sensing, DOI: 10.1080/01431161.2015.1055610). The boundary conditions in the study were set to limit the point A (the driest bare soil) and B (the wettest bare soil) for surface energy closure. However, no limitation was installed for point D (the full vegetation cover). In this paper, many vegetation types are simulated by the land surface model - Noah LSM 3.2 to analyze the effects on soil moisture estimation, such as crop, grass and mixed forest. The locations of point D are changed with vegetation types. The normalized LST of point D for forest is much lower than crop and grass. The location of point D is basically unchanged for crop and grass.

A Model of Rapid Radicalization Behavior Using Agent-Based Modeling and Quorum Sensing

NASA Technical Reports Server (NTRS)

Schwartz, Noah; Drucker, Nick; Campbell, Kenyth

2012-01-01

Understanding the dynamics of radicalization, especially rapid radicalization, has become increasingly important to US policy in the past several years. Traditionally, radicalization is considered a slow process, but recent social and political events demonstrate that the process can occur quickly. Examining this rapid process, in real time, is impossible. However, recreating an event using modeling and simulation (M&S) allows researchers to study some of the complex dynamics associated with rapid radicalization. We propose to adapt the biological mechanism of quorum sensing as a tool to explore, or possibly explain, rapid radicalization. Due to the complex nature of quorum sensing, M&S allows us to examine events that we could not otherwise examine in real time. For this study, we employ Agent Based Modeling (ABM), an M&S paradigm suited to modeling group behavior. The result of this study was the successful creation of rapid radicalization using quorum sensing. The Battle of Mogadishu was the inspiration for this model and provided the testing conditions used to explore quorum sensing and the ideas behind rapid radicalization. The final product has wider applicability however, using quorum sensing as a possible tool for examining other catalytic rapid radicalization events.

No matter how large or how small, oilwell servicing firms work safely

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lyle, D.

1995-07-01

In working safely, the size of the company doesn`t matter as much as the dedication of the people in maintaining a safe workplace. Poe Servicing Inc. of Oberlin, Kan., earned the 1994 Association of Oilwell Servicing Contractors (AOSC) gold safety award for smaller companies that put in 10,000 to 50,000 man-hours of work. AOSC`s group one. The employees watch out for each other, and they use common sense. The common sense part of the program means the company knows new people are most susceptible to accidents, so they send them out to observe before putting them to work.

Attention versus consciousness in the visual brain: differences in conception, phenomenology, behavior, neuroanatomy, and physiology.

PubMed

Baars, B J

1999-07-01

A common confound between consciousness and attention makes it difficult to think clearly about recent advances in the understanding of the visual brain. Visual consciousness involves phenomenal experience of the visual world, but visual attention is more plausibly treated as a function that selects and maintains the selection of potential conscious contents, often unconsciously. In the same sense, eye movements select conscious visual events, which are not the same as conscious visual experience. According to common sense, visual experience is consciousness, and selective processes are labeled as attention. The distinction is reflected in very different behavioral measures and in very different brain anatomy and physiology. Visual consciousness tends to be associated with the "what" stream of visual feature neurons in the ventral temporal lobe. In contrast, attentional selection and maintenance are mediated by other brain regions, ranging from superior colliculi to thalamus, prefrontal cortex, and anterior cingulate. The author applied the common-sense distinction between attention and consciousness to the theoretical positions of M. I. Posner (1992, 1994) and D. LaBerge (1997, 1998) to show how it helps to clarify the evidence. He concluded that clarity of thought is served by calling a thing by its proper name.

Improvement of mechanical performance for vibratory microgyroscope based on sense mode closed-loop control

NASA Astrophysics Data System (ADS)

Xiao, Dingbang; Su, Jianbin; Chen, Zhihua; Hou, Zhanqiang; Wang, Xinghua; Wu, Xuezhong

2013-04-01

In order to improve its structural sensitivity, a vibratory microgyroscope is commonly sealed in high vacuum to increase the drive mode quality factor. The sense mode quality factor of the microgyroscope will also increase simultaneously after vacuum sealing, which will lead to a long decay time of free response and even self-oscillation of the sense mode. As a result, the mechanical performance of the microgyroscope will be seriously degraded. In order to solve this problem, a closed-loop control technique is presented to adjust and optimize the sense mode quality factor. A velocity feedback loop was designed to increase the electric damping of the sense mode vibration. A circuit was fabricated based on this technique, and experimental results indicate that the sense mode quality factor of the microgyroscope was adjusted from 8052 to 428. The decay time of the sense mode free response was shortened from 3 to 0.5 s, and the vibration-rejecting ability of the microgyroscope was improved obviously without sensitivity degradation.

Valuing psychiatric patients' stories: belief in and use of the supernatural in the Jamaican psychiatric setting.

PubMed

James, Caryl C A B; Carpenter, Karen A; Peltzer, Karl; Weaver, Steve

2014-04-01

The aim of this study was to examine illness presentation and understand how psychiatric patients make meaning of the causes of their mental illnesses. Six Jamaican psychiatric patients were interviewed using the McGill Illness Narrative Interview Schedule. Of the 6, 3 representative case studies were chosen. The hermeneutic phenomenological approach and the common sense model were used in the formulation of patients' explanatory models. Results indicate that psychiatric patients actively conceptualized the causes and resultant treatment of their mental illnesses. Patients' satisfaction and compliance with treatment were dependent on the extent to which practitioners' conceptualization matched their own, as well as practitioners' acknowledgement of patients' concerns about causation, prognosis, and treatment.

Automated space vehicle control for rendezvous proximity operations

NASA Technical Reports Server (NTRS)

Lea, Robert N.

1988-01-01

Rendezvous during the unmanned space exploration missions, such as a Mars Rover/Sample Return will require a completely automatic system from liftoff to docking. A conceptual design of an automated rendezvous, proximity operations, and docking system is being implemented and validated at the Johnson Space Center (JSC). The emphasis is on the progress of the development and testing of a prototype system for control of the rendezvous vehicle during proximity operations that is currently being developed at JSC. Fuzzy sets are used to model the human capability of common sense reasoning in decision making tasks and such models are integrated with the expert systems and engineering control system technology to create a system that performs comparably to a manned system.

Automated space vehicle control for rendezvous proximity operations

NASA Technical Reports Server (NTRS)

Lea, Robert N.

1988-01-01

Rendezvous during the unmanned space exploration missions, such as a Mars Rover/Sample Return will require a completely automatic system from liftoff to docking. A conceptual design of an automated rendezvous, proximity operations, and docking system is being implemented and validated at the Johnson Space Center (JSC). The emphasis is on the progress of the development and testing of a prototype system for control of the rendezvous vehicle during proximity operations that is currently being developed at JSC. Fuzzy sets are used to model the human capability of common sense reasoning in decision-making tasks and such models are integrated with the expert systems and engineering control system technology to create a system that performs comparably to a manned system.

Ridge, Lasso and Bayesian additive-dominance genomic models.

PubMed

Azevedo, Camila Ferreira; de Resende, Marcos Deon Vilela; E Silva, Fabyano Fonseca; Viana, José Marcelo Soriano; Valente, Magno Sávio Ferreira; Resende, Márcio Fernando Ribeiro; Muñoz, Patricio

2015-08-25

A complete approach for genome-wide selection (GWS) involves reliable statistical genetics models and methods. Reports on this topic are common for additive genetic models but not for additive-dominance models. The objective of this paper was (i) to compare the performance of 10 additive-dominance predictive models (including current models and proposed modifications), fitted using Bayesian, Lasso and Ridge regression approaches; and (ii) to decompose genomic heritability and accuracy in terms of three quantitative genetic information sources, namely, linkage disequilibrium (LD), co-segregation (CS) and pedigree relationships or family structure (PR). The simulation study considered two broad sense heritability levels (0.30 and 0.50, associated with narrow sense heritabilities of 0.20 and 0.35, respectively) and two genetic architectures for traits (the first consisting of small gene effects and the second consisting of a mixed inheritance model with five major genes). G-REML/G-BLUP and a modified Bayesian/Lasso (called BayesA*B* or t-BLASSO) method performed best in the prediction of genomic breeding as well as the total genotypic values of individuals in all four scenarios (two heritabilities x two genetic architectures). The BayesA*B*-type method showed a better ability to recover the dominance variance/additive variance ratio. Decomposition of genomic heritability and accuracy revealed the following descending importance order of information: LD, CS and PR not captured by markers, the last two being very close. Amongst the 10 models/methods evaluated, the G-BLUP, BAYESA*B* (-2,8) and BAYESA*B* (4,6) methods presented the best results and were found to be adequate for accurately predicting genomic breeding and total genotypic values as well as for estimating additive and dominance in additive-dominance genomic models.

Visibility in a pure model of golden spiral phyllotaxis.

PubMed

Herrmann, Burghard

2018-07-01

This paper considers the geometry of plants with golden spiral phyllotaxis, i.e. growing leaf by leaf on a spiral with golden divergence angle, via the simplest mathematical model, a cylinder with regular arrangement of points on its surface. As is well-known, Fibonacci numbers appear by means of the order of parastichies. This fact is shown to be a straightforward application of logical consequences to a particular model with respect to pure visibility. This notion is very similar to that of contact parastichies. The 3-D cylindrical model of golden spiral phyllotaxis abstracts from the form of leaves and identifies them with points. Pure visibility is specified in the 2-D representation so that common sense parastichies can be scrutinized. The main Theorem states that the orders of the purely most visible parastichies are Fibonacci numbers. Copyright © 2018 Elsevier Inc. All rights reserved.

More Than Meets the Eye: Toward a Post-Materialist Model of Consciousness.

PubMed

Brabant, Olivier

2016-01-01

Commonly accepted models of human consciousness have substantial shortcomings, in the sense that they cannot account for the entire scope of human experiences. The goal of this article is to describe a model with higher explanatory power, by integrating ideas from psychology and quantum mechanics. In the first part, the need for a paradigm change will be justified by presenting three types of phenomena that challenge the materialistic view of consciousness. The second part is about proposing an alternative view of reality and mind-matter manifestation that is able to accommodate these phenomena. Finally, the ideas from the previous parts will be combined with the psychological concepts developed by Frederic W. H. Myers. The result is a more comprehensive model of human consciousness that offers a novel perspective on altered states of consciousness, genius, and mental health. Copyright © 2016 Elsevier Inc. All rights reserved.

From ecological test site to geographic information system: lessons for the 1980's

USGS Publications Warehouse

Alexander, Robert H.

1981-01-01

Geographic information systems were common elements in two kinds of interdisciplinary regional demonstration projects in the 1970's. Ecological test sits attempted to provide for more efficient remote-sensing data delivery for regional environmental management. Regional environmental systems analysis attempted to formally describe and model the interacting regional social and environmental processes, including the resource-use decision making process. Lessons for the 1980's are drawn from recent evaluations and assessments of these programs, focusing on cost, rates of system development and technology transfer, program coordination, integrative analysis capability, and the involvement of system users and decision makers.

Application of thermal scanning to the study of transverse mixing in rivers

NASA Technical Reports Server (NTRS)

Eheart, J. W.

1975-01-01

Remote sensing has shown itself to be a valuable research tool in the study of transverse mixing in rivers. It is desirable, for a number of reasons, to study and predict the two-dimensional movement of pollutants in the region just downstream of a pollutant discharge point. While many of the more common pollutants do not exhibit a spectral signature, it was shown that the temperature difference between the pollutant and the receiving water could be successfully exploited by applying a mathematical model of mass transport processes to heat transport, and testing and calibrating it with thermal scanning data.

Teaching Disaster Preparedness to Rural Communities in El Salvador.

NASA Astrophysics Data System (ADS)

Barton, T.

2014-12-01

Natural disasters are becoming more common around the world, and it is widely accepted that developing nations show the highest rates of vulnerability. It makes sense to focus preparedness and mitigation efforts in these countries. However, it is important to realize that different teaching styles are required for different cultures with varying education systems and classroom atmospheres. The pedagogical models we use in the US can't be directly exported. A realistic assessment of the situation seen during two years living and working in rural El Salvador is presented, along with methods used and lessons learned.

Remote sensing as a source of data for outdoor recreation planning

NASA Technical Reports Server (NTRS)

Reed, W. E.; Goodell, H. G.; Emmitt, G. D.

1972-01-01

Specific data needs for outdoor recreation planning and the ability of tested remote sensors to provide sources for these data are examined. Data needs, remote sensor capabilities, availability of imagery, and advantages and problems of incorporating remote sensing data sources into ongoing planning data collection programs are discussed in detail. Examples of the use of imagery to derive data for a range of common planning analyses are provided. A selected bibliography indicates specific uses of data in planning, basic background materials on remote sensing technology, and sources of information on environmental information systems expected to use remote sensing to provide new environmental data of use in outdoor recreation planning.

A Review and Analysis of Remote Sensing Capability for Air Quality Measurements as a Potential Decision Support Tool Conducted by the NASA DEVELOP Program

NASA Technical Reports Server (NTRS)

Ross, A.; Richards, A.; Keith, K.; Frew, C.; Boseck, J.; Sutton, S.; Watts, C.; Rickman, D.

2007-01-01

This project focused on a comprehensive utilization of air quality model products as decision support tools (DST) needed for public health applications. A review of past and future air quality measurement methods and their uncertainty, along with the relationship of air quality to national and global public health, is vital. This project described current and future NASA satellite remote sensing and ground sensing capabilities and the potential for using these sensors to enhance the prediction, prevention, and control of public health effects that result from poor air quality. The qualitative uncertainty of current satellite remotely sensed air quality, the ground-based remotely sensed air quality, the air quality/public health model, and the decision making process is evaluated in this study. Current peer-reviewed literature suggests that remotely sensed air quality parameters correlate well with ground-based sensor data. A satellite remote-sensed and ground-sensed data complement is needed to enhance the models/tools used by policy makers for the protection of national and global public health communities

Gating currents from Kv7 channels carrying neuronal hyperexcitability mutations in the voltage-sensing domain.

PubMed

Miceli, Francesco; Vargas, Ernesto; Bezanilla, Francisco; Taglialatela, Maurizio

2012-03-21

Changes in voltage-dependent gating represent a common pathogenetic mechanism for genetically inherited channelopathies, such as benign familial neonatal seizures or peripheral nerve hyperexcitability caused by mutations in neuronal K(v)7.2 channels. Mutation-induced changes in channel voltage dependence are most often inferred from macroscopic current measurements, a technique unable to provide a detailed assessment of the structural rearrangements underlying channel gating behavior; by contrast, gating currents directly measure voltage-sensor displacement during voltage-dependent gating. In this work, we describe macroscopic and gating current measurements, together with molecular modeling and molecular-dynamics simulations, from channels carrying mutations responsible for benign familial neonatal seizures and/or peripheral nerve hyperexcitability; K(v)7.4 channels, highly related to K(v)7.2 channels both functionally and structurally, were used for these experiments. The data obtained showed that mutations affecting charged residues located in the more distal portion of S(4) decrease the stability of the open state and the active voltage-sensing domain configuration but do not directly participate in voltage sensing, whereas mutations affecting a residue (R4) located more proximally in S(4) caused activation of gating-pore currents at depolarized potentials. These results reveal that distinct molecular mechanisms underlie the altered gating behavior of channels carrying disease-causing mutations at different voltage-sensing domain locations, thereby expanding our current view of the pathogenesis of neuronal hyperexcitability diseases. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing

NASA Technical Reports Server (NTRS)

Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi

1998-01-01

Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.

Modelling Rift Valley fever (RVF) disease vector habitats using active and passive remote sensing systems

NASA Technical Reports Server (NTRS)

Ambrosia, Vincent G.; Linthicum, K. G.; Bailey, C. L.; Sebesta, P.

1989-01-01

The NASA Ames Ecosystem Science and Technology Branch and the U.S. Army Medical Research Institute of Infectious Diseases are conducting research to detect Rift Valley fever (RVF) vector habitats in eastern Africa using active and passive remote-sensing. The normalized difference vegetation index (NDVI) calculated from Landsat TM and SPOT data is used to characterize the vegetation common to the Aedes mosquito. Relationships have been found between the highest NDVI and the 'dambo' habitat areas near Riuru, Kenya on both wet and dry data. High NDVI values, when combined with the vegetation classifications, are clearly related to the areas of vector habitats. SAR data have been proposed for use during the rainy season when optical systems are of minimal use and the short frequency and duration of the optimum RVF mosquito habitat conditions necessitate rapid evaluation of the vegetation/moisture conditions; only then can disease potential be stemmed and eradication efforts initiated.

Positive experiences for participants in suicide bereavement groups: a grounded theory model.

PubMed

Groos, Anita D; Shakespeare-Finch, Jane

2013-01-01

Grounded Theory was used to examine the experiences of 13 participants who had attended psycho-educational support groups for those bereaved by suicide. Results demonstrated core and central categories that fit well with group therapeutic factors developed by I. D. Yalom (1995) and emphasized the importance of universality, imparting information and instilling hope, catharsis and self-disclosure, and broader meaning-making processes surrounding acceptance or adjustment. Participants were commonly engaged in a lengthy process of oscillating between loss-oriented and restoration-focused reappraisals. The functional experience of the group comprised feeling normal within the group, providing a sense of permission to feel and to express emotions and thoughts and to bestow meaning. Structural variables of information and guidance and different perspectives on the suicide and bereavement were gained from other participants, the facilitators, group content, and process. Personal changes, including in relationships and in their sense of self assisted participants to develop an altered and more positive personal narrative.

Most genetic risk for autism resides with common variation

PubMed Central

Gaugler, Trent; Klei, Lambertus; Sanders, Stephan J.; Bodea, Corneliu A.; Goldberg, Arthur P.; Lee, Ann B.; Mahajan, Milind; Manaa, Dina; Pawitan, Yudi; Reichert, Jennifer; Ripke, Stephan; Sandin, Sven; Sklar, Pamela; Svantesson, Oscar; Reichenberg, Abraham; Hultman, Christina M.; Devlin, Bernie

2014-01-01

A key component of genetic architecture is the allelic spectrum influencing trait variability. For autism spectrum disorder (henceforth autism) the nature of its allelic spectrum is uncertain. Individual risk genes have been identified from rare variation, especially de novo mutations1–8. From this evidence one might conclude that rare variation dominates its allelic spectrum, yet recent studies show that common variation, individually of small effect, has substantial impact en masse9,10. At issue is how much of an impact relative to rare variation. Using a unique epidemiological sample from Sweden, novel methods that distinguish total narrow-sense heritability from that due to common variation, and by synthesizing results from other studies, we reach several conclusions about autism’s genetic architecture: its narrow-sense heritability is ≈54% and most traces to common variation; rare de novo mutations contribute substantially to individuals’ liability; still their contribution to variance in liability, 2.6%, is modest compared to heritable variation. PMID:25038753

Multivariate Density Estimation and Remote Sensing

NASA Technical Reports Server (NTRS)

Scott, D. W.

1983-01-01

Current efforts to develop methods and computer algorithms to effectively represent multivariate data commonly encountered in remote sensing applications are described. While this may involve scatter diagrams, multivariate representations of nonparametric probability density estimates are emphasized. The density function provides a useful graphical tool for looking at data and a useful theoretical tool for classification. This approach is called a thunderstorm data analysis.

A Framework for Mathematics Graphical Tasks: The Influence of the Graphic Element on Student Sense Making

ERIC Educational Resources Information Center

Lowrie, Tom; Diezmann, Carmel M.; Logan, Tracy

2012-01-01

Graphical tasks have become a prominent aspect of mathematics assessment. From a conceptual stance, the purpose of this study was to better understand the composition of graphical tasks commonly used to assess students' mathematics understandings. Through an iterative design, the investigation described the sense making of 11-12-year-olds as they…

Airplane detection based on fusion framework by combining saliency model with Deep Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Dou, Hao; Sun, Xiao; Li, Bin; Deng, Qianqian; Yang, Xubo; Liu, Di; Tian, Jinwen

2018-03-01

Aircraft detection from very high resolution remote sensing images, has gained more increasing interest in recent years due to the successful civil and military applications. However, several problems still exist: 1) how to extract the high-level features of aircraft; 2) locating objects within such a large image is difficult and time consuming; 3) A common problem of multiple resolutions of satellite images still exists. In this paper, inspirited by biological visual mechanism, the fusion detection framework is proposed, which fusing the top-down visual mechanism (deep CNN model) and bottom-up visual mechanism (GBVS) to detect aircraft. Besides, we use multi-scale training method for deep CNN model to solve the problem of multiple resolutions. Experimental results demonstrate that our method can achieve a better detection result than the other methods.

Depth Estimation of Submerged Aquatic Vegetation in Clear Water Streams Using Low-Altitude Optical Remote Sensing

PubMed Central

Visser, Fleur; Buis, Kerst; Verschoren, Veerle; Meire, Patrick

2015-01-01

UAVs and other low-altitude remote sensing platforms are proving very useful tools for remote sensing of river systems. Currently consumer grade cameras are still the most commonly used sensors for this purpose. In particular, progress is being made to obtain river bathymetry from the optical image data collected with such cameras, using the strong attenuation of light in water. No studies have yet applied this method to map submergence depth of aquatic vegetation, which has rather different reflectance characteristics from river bed substrate. This study therefore looked at the possibilities to use the optical image data to map submerged aquatic vegetation (SAV) depth in shallow clear water streams. We first applied the Optimal Band Ratio Analysis method (OBRA) of Legleiter et al. (2009) to a dataset of spectral signatures from three macrophyte species in a clear water stream. The results showed that for each species the ratio of certain wavelengths were strongly associated with depth. A combined assessment of all species resulted in equally strong associations, indicating that the effect of spectral variation in vegetation is subsidiary to spectral variation due to depth changes. Strongest associations (R2-values ranging from 0.67 to 0.90 for different species) were found for combinations including one band in the near infrared (NIR) region between 825 and 925 nm and one band in the visible light region. Currently data of both high spatial and spectral resolution is not commonly available to apply the OBRA results directly to image data for SAV depth mapping. Instead a novel, low-cost data acquisition method was used to obtain six-band high spatial resolution image composites using a NIR sensitive DSLR camera. A field dataset of SAV submergence depths was used to develop regression models for the mapping of submergence depth from image pixel values. Band (combinations) providing the best performing models (R2-values up to 0.77) corresponded with the OBRA findings. A 10% error was achieved under sub-optimal data collection conditions, which indicates that the method could be suitable for many SAV mapping applications. PMID:26437410

Depth Estimation of Submerged Aquatic Vegetation in Clear Water Streams Using Low-Altitude Optical Remote Sensing.

PubMed

Visser, Fleur; Buis, Kerst; Verschoren, Veerle; Meire, Patrick

2015-09-30

UAVs and other low-altitude remote sensing platforms are proving very useful tools for remote sensing of river systems. Currently consumer grade cameras are still the most commonly used sensors for this purpose. In particular, progress is being made to obtain river bathymetry from the optical image data collected with such cameras, using the strong attenuation of light in water. No studies have yet applied this method to map submergence depth of aquatic vegetation, which has rather different reflectance characteristics from river bed substrate. This study therefore looked at the possibilities to use the optical image data to map submerged aquatic vegetation (SAV) depth in shallow clear water streams. We first applied the Optimal Band Ratio Analysis method (OBRA) of Legleiter et al. (2009) to a dataset of spectral signatures from three macrophyte species in a clear water stream. The results showed that for each species the ratio of certain wavelengths were strongly associated with depth. A combined assessment of all species resulted in equally strong associations, indicating that the effect of spectral variation in vegetation is subsidiary to spectral variation due to depth changes. Strongest associations (R²-values ranging from 0.67 to 0.90 for different species) were found for combinations including one band in the near infrared (NIR) region between 825 and 925 nm and one band in the visible light region. Currently data of both high spatial and spectral resolution is not commonly available to apply the OBRA results directly to image data for SAV depth mapping. Instead a novel, low-cost data acquisition method was used to obtain six-band high spatial resolution image composites using a NIR sensitive DSLR camera. A field dataset of SAV submergence depths was used to develop regression models for the mapping of submergence depth from image pixel values. Band (combinations) providing the best performing models (R²-values up to 0.77) corresponded with the OBRA findings. A 10% error was achieved under sub-optimal data collection conditions, which indicates that the method could be suitable for many SAV mapping applications.

Comparison between remote sensing and a dynamic vegetation model for estimating terrestrial primary production of Africa.

PubMed

Ardö, Jonas

2015-12-01

Africa is an important part of the global carbon cycle. It is also a continent facing potential problems due to increasing resource demand in combination with climate change-induced changes in resource supply. Quantifying the pools and fluxes constituting the terrestrial African carbon cycle is a challenge, because of uncertainties in meteorological driver data, lack of validation data, and potentially uncertain representation of important processes in major ecosystems. In this paper, terrestrial primary production estimates derived from remote sensing and a dynamic vegetation model are compared and quantified for major African land cover types. Continental gross primary production estimates derived from remote sensing were higher than corresponding estimates derived from a dynamic vegetation model. However, estimates of continental net primary production from remote sensing were lower than corresponding estimates from the dynamic vegetation model. Variation was found among land cover classes, and the largest differences in gross primary production were found in the evergreen broadleaf forest. Average carbon use efficiency (NPP/GPP) was 0.58 for the vegetation model and 0.46 for the remote sensing method. Validation versus in situ data of aboveground net primary production revealed significant positive relationships for both methods. A combination of the remote sensing method with the dynamic vegetation model did not strongly affect this relationship. Observed significant differences in estimated vegetation productivity may have several causes, including model design and temperature sensitivity. Differences in carbon use efficiency reflect underlying model assumptions. Integrating the realistic process representation of dynamic vegetation models with the high resolution observational strength of remote sensing may support realistic estimation of components of the carbon cycle and enhance resource monitoring, providing suitable validation data is available.

Understanding the role of emotion in sense-making: a semiotic psychoanalytic oriented perspective.

PubMed

Salvatore, Sergio; Venuleo, Claudia

2008-03-01

We propose a model of emotion grounded on Ignacio Matte Blanco's theory of the unconscious. According to this conceptualization, emotion is a generalized representation of the social context actors are involved in. We discuss how this model can help to better understand the sensemaking processes. For this purpose we present a hierarchical model of sensemaking based on the distinction between significance--the content of the sign--and sense--the psychological value of the act of producing the sign in the given contingence of the social exchange. According to this model, emotion categorization produces the frame of sense regulating the interpretation of the sense of the signs, therefore creating the psychological value of the sensemaking.

Near-earth orbital guidance and remote sensing

NASA Technical Reports Server (NTRS)

Powers, W. F.

1972-01-01

The curriculum of a short course in remote sensing and parameter optimization is presented. The subjects discussed are: (1) basics of remote sensing and the user community, (2) multivariant spectral analysis, (3) advanced mathematics and physics of remote sensing, (4) the atmospheric environment, (5) imaging sensing, and (6)nonimaging sensing. Mathematical models of optimization techniques are developed.

Effects of artificial lighting on the detection of plant stress with spectral reflectance remote sensing in bioregenerative life support systems

NASA Astrophysics Data System (ADS)

Schuerger, Andrew C.; Richards, Jeffrey T.

2006-09-01

Plant-based life support systems that utilize bioregenerative technologies have been proposed for long-term human missions to both the Moon and Mars. Bioregenerative life support systems will utilize higher plants to regenerate oxygen, water, and edible biomass for crews, and are likely to significantly lower the ‘equivalent system mass’ of crewed vehicles. As part of an ongoing effort to begin the development of an automatic remote sensing system to monitor plant health in bioregenerative life support modules, we tested the efficacy of seven artificial illumination sources on the remote detection of plant stresses. A cohort of pepper plants (Capsicum annuum L.) were grown 42 days at 25 °C, 70% relative humidity, and 300 μmol m-2 s-1 of photosynthetically active radiation (PAR; from 400 to 700 nm). Plants were grown under nutritional stresses induced by irrigating subsets of the plants with 100, 50, 25, or 10% of a standard nutrient solution. Reflectance spectra of the healthy and stressed plants were collected under seven artificial lamps including two tungsten halogen lamps, plus high pressure sodium, metal halide, fluorescent, microwave, and red/blue light emitting diode (LED) sources. Results indicated that several common algorithms used to estimate biomass and leaf chlorophyll content were effective in predicting plant stress under all seven illumination sources. However, the two types of tungsten halogen lamps and the microwave illumination source yielded linear models with the highest residuals and thus the highest predictive capabilities of all lamps tested. The illumination sources with the least predictive capabilities were the red/blue LEDs and fluorescent lamps. Although the red/blue LEDs yielded the lowest residuals for linear models derived from the remote sensing data, the LED arrays used in these experiments were optimized for plant productivity and not the collection of remote sensing data. Thus, we propose that if adjusted to optimize the collectio n of remote sensing information from plants, LEDs remain the best candidates for illumination sources for monitoring plant stresses in bioregenerative life support systems.

Hydrological Relevant Parameters from Remote Sensing - Spatial Modelling Input and Validation Basis

NASA Astrophysics Data System (ADS)

Hochschild, V.

2012-12-01

This keynote paper will demonstrate how multisensoral remote sensing data is used as spatial input for mesoscale hydrological modeling as well as for sophisticated validation purposes. The tasks of Water Resources Management are subject as well as the role of remote sensing in regional catchment modeling. Parameters derived from remote sensing discussed in this presentation will be land cover, topographical information from digital elevation models, biophysical vegetation parameters, surface soil moisture, evapotranspiration estimations, lake level measurements, determination of snow covered area, lake ice cycles, soil erosion type, mass wasting monitoring, sealed area, flash flood estimation. The actual possibilities of recent satellite and airborne systems are discussed, as well as the data integration into GIS and hydrological modeling, scaling issues and quality assessment will be mentioned. The presentation will provide an overview of own research examples from Germany, Tibet and Africa (Ethiopia, South Africa) as well as other international research activities. Finally the paper gives an outlook on upcoming sensors and concludes the possibilities of remote sensing in hydrology.

Estimating spatially distributed soil texture using time series of thermal remote sensing - a case study in central Europe

NASA Astrophysics Data System (ADS)

Müller, Benjamin; Bernhardt, Matthias; Jackisch, Conrad; Schulz, Karsten

2016-09-01

For understanding water and solute transport processes, knowledge about the respective hydraulic properties is necessary. Commonly, hydraulic parameters are estimated via pedo-transfer functions using soil texture data to avoid cost-intensive measurements of hydraulic parameters in the laboratory. Therefore, current soil texture information is only available at a coarse spatial resolution of 250 to 1000 m. Here, a method is presented to derive high-resolution (15 m) spatial topsoil texture patterns for the meso-scale Attert catchment (Luxembourg, 288 km2) from 28 images of ASTER (advanced spaceborne thermal emission and reflection radiometer) thermal remote sensing. A principle component analysis of the images reveals the most dominant thermal patterns (principle components, PCs) that are related to 212 fractional soil texture samples. Within a multiple linear regression framework, distributed soil texture information is estimated and related uncertainties are assessed. An overall root mean squared error (RMSE) of 12.7 percentage points (pp) lies well within and even below the range of recent studies on soil texture estimation, while requiring sparser sample setups and a less diverse set of basic spatial input. This approach will improve the generation of spatially distributed topsoil maps, particularly for hydrologic modeling purposes, and will expand the usage of thermal remote sensing products.

Combining Hydrological Modeling and Remote Sensing Observations to Enable Data-Driven Decision Making for Devils Lake Flood Mitigation in a Changing Climate

NASA Technical Reports Server (NTRS)

Zhang, Xiaodong; Kirilenko, Andrei; Lim, Howe; Teng, Williams

2010-01-01

This slide presentation reviews work to combine the hydrological models and remote sensing observations to monitor Devils Lake in North Dakota, to assist in flood damage mitigation. This reports on the use of a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model.

Effects of 4D-Var data assimilation using remote sensing precipitation products in a WRF over the complex Heihe River Basin

NASA Astrophysics Data System (ADS)

Pan, Xiaoduo; Li, Xin; Cheng, Guodong

2017-04-01

Traditionally, ground-based, in situ observations, remote sensing, and regional climate modeling, individually, cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrain. Data assimilation techniques are often used to assimilate ground observations and remote sensing products into models for dynamic downscaling. In this study, the Weather Research and Forecasting (WRF) model was used to assimilate two satellite precipitation products (TRMM 3B42 and FY-2D) using the 4D-Var data assimilation method. The results show that the assimilation of remote sensing precipitation products can improve the initial WRF fields of humidity and temperature, thereby improving precipitation forecasting and decreasing the spin-up time. Hence, assimilating TRMM and FY-2D remote sensing precipitation products using WRF 4D-Var can be viewed as a positive step toward improving the accuracy and lead time of numerical weather prediction models, particularly for short-term weather forecasting. Future work is proposed to assimilate a suite of remote sensing data, e.g., the combination of precipitation and soil moisture data, into a WRF model to improve 7-8 day forecasts of precipitation and other atmospheric variables.

Progress in remote sensing of global land surface heat fluxes and evaporations with a turbulent heat exchange parameterization method

NASA Astrophysics Data System (ADS)

Chen, Xuelong; Su, Bob

2017-04-01

Remote sensing has provided us an opportunity to observe Earth land surface with a much higher resolution than any of GCM simulation. Due to scarcity of information for land surface physical parameters, up-to-date GCMs still have large uncertainties in the coupled land surface process modeling. One critical issue is a large amount of parameters used in their land surface models. Thus remote sensing of land surface spectral information can be used to provide information on these parameters or assimilated to decrease the model uncertainties. Satellite imager could observe the Earth land surface with optical, thermal and microwave bands. Some basic Earth land surface status (land surface temperature, canopy height, canopy leaf area index, soil moisture etc.) has been produced with remote sensing technique, which already help scientists understanding Earth land and atmosphere interaction more precisely. However, there are some challenges when applying remote sensing variables to calculate global land-air heat and water exchange fluxes. Firstly, a global turbulent exchange parameterization scheme needs to be developed and verified, especially for global momentum and heat roughness length calculation with remote sensing information. Secondly, a compromise needs to be innovated to overcome the spatial-temporal gaps in remote sensing variables to make the remote sensing based land surface fluxes applicable for GCM model verification or comparison. A flux network data library (more 200 flux towers) was collected to verify the designed method. Important progress in remote sensing of global land flux and evaporation will be presented and its benefits for GCM models will also be discussed. Some in-situ studies on the Tibetan Plateau and problems of land surface process simulation will also be discussed.

Evaluation of computational endomicroscopy architectures for minimally-invasive optical biopsy

NASA Astrophysics Data System (ADS)

Dumas, John P.; Lodhi, Muhammad A.; Bajwa, Waheed U.; Pierce, Mark C.

2017-02-01

We are investigating compressive sensing architectures for applications in endomicroscopy, where the narrow diameter probes required for tissue access can limit the achievable spatial resolution. We hypothesize that the compressive sensing framework can be used to overcome the fundamental pixel number limitation in fiber-bundle based endomicroscopy by reconstructing images with more resolvable points than fibers in the bundle. An experimental test platform was assembled to evaluate and compare two candidate architectures, based on introducing a coded amplitude mask at either a conjugate image or Fourier plane within the optical system. The benchtop platform consists of a common illumination and object path followed by separate imaging arms for each compressive architecture. The imaging arms contain a digital micromirror device (DMD) as a reprogrammable mask, with a CCD camera for image acquisition. One arm has the DMD positioned at a conjugate image plane ("IP arm"), while the other arm has the DMD positioned at a Fourier plane ("FP arm"). Lenses were selected and positioned within each arm to achieve an element-to-pixel ratio of 16 (230,400 mask elements mapped onto 14,400 camera pixels). We discuss our mathematical model for each system arm and outline the importance of accounting for system non-idealities. Reconstruction of a 1951 USAF resolution target using optimization-based compressive sensing algorithms produced images with higher spatial resolution than bicubic interpolation for both system arms when system non-idealities are included in the model. Furthermore, images generated with image plane coding appear to exhibit higher spatial resolution, but more noise, than images acquired through Fourier plane coding.

Dual PECCS: a cognitive system for conceptual representation and categorization

NASA Astrophysics Data System (ADS)

Lieto, Antonio; Radicioni, Daniele P.; Rho, Valentina

2017-03-01

In this article we present an advanced version of Dual-PECCS, a cognitively-inspired knowledge representation and reasoning system aimed at extending the capabilities of artificial systems in conceptual categorization tasks. It combines different sorts of common-sense categorization (prototypical and exemplars-based categorization) with standard monotonic categorization procedures. These different types of inferential procedures are reconciled according to the tenets coming from the dual process theory of reasoning. On the other hand, from a representational perspective, the system relies on the hypothesis of conceptual structures represented as heterogeneous proxytypes. Dual-PECCS has been experimentally assessed in a task of conceptual categorization where a target concept illustrated by a simple common-sense linguistic description had to be identified by resorting to a mix of categorization strategies, and its output has been compared to human responses. The obtained results suggest that our approach can be beneficial to improve the representational and reasoning conceptual capabilities of standard cognitive artificial systems, and - in addition - that it may be plausibly applied to different general computational models of cognition. The current version of the system, in fact, extends our previous work, in that Dual- PECCS is now integrated and tested into two cognitive architectures, ACT-R and CLARION, implementing different assumptions on the underlying invariant structures governing human cognition. Such integration allowed us to extend our previous evaluation.

Beliefs About Dysmenorrhea and Their Relationship to Self-Management.

PubMed

Chen, Chen X; Kwekkeboom, Kristine L; Ward, Sandra E

2016-08-01

Dysmenorrhea is highly prevalent and is the leading cause of work and school absences among women of reproductive age. However, self-management of dysmenorrhea is not well understood in the US, and little evidence is available on factors that influence dysmenorrhea self-management. Guided by the Common Sense Model, we examined women's representations of dysmenorrhea (beliefs about causes, symptoms, consequences, timeline, controllability, coherence, and emotional responses), described their dysmenorrhea self-management behaviors, and investigated the relationship between representations and self-management behaviors. We conducted a cross-sectional, web-based survey of 762 adult women who had dysmenorrhea symptoms in the last six months. Participants had varied beliefs about the causes of their dysmenorrhea symptoms, which were perceived as a normal part of life. Dysmenorrhea symptoms were reported as moderately severe, with consequences that moderately affected daily life. Women believed they understood their symptoms moderately well and perceived them as moderately controllable but them to continue through menopause. Most women did not seek professional care but rather used a variety of pharmacologic and complementary health approaches. Care-seeking and use of self-management strategies were associated with common sense beliefs about dysmenorrhea cause, consequences, timeline, and controllability. The findings may inform development and testing of self-management interventions that address dysmenorrhea representations and facilitate evidence-based management. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Evaluating high temporal and spatial resolution vegetation index for crop yield prediction

USDA-ARS?s Scientific Manuscript database

Remote sensing data have been widely used in estimating crop yield. Remote sensing derived parameters such as Vegetation Index (VI) were used either directly in building empirical models or by assimilating with crop growth models to predict crop yield. The abilities of remote sensing VI in crop yiel...

Bushland Evapotranspiration and Agricultural Remote Sensing System (BEARS) software

NASA Astrophysics Data System (ADS)

Gowda, P. H.; Moorhead, J.; Brauer, D. K.

2017-12-01

Evapotranspiration (ET) is a major component of the hydrologic cycle. ET data are used for a variety of water management and research purposes such as irrigation scheduling, water and crop modeling, streamflow, water availability, and many more. Remote sensing products have been widely used to create spatially representative ET data sets which provide important information from field to regional scales. As UAV capabilities increase, remote sensing use is likely to also increase. For that purpose, scientists at the USDA-ARS research laboratory in Bushland, TX developed the Bushland Evapotranspiration and Agricultural Remote Sensing System (BEARS) software. The BEARS software is a Java based software that allows users to process remote sensing data to generate ET outputs using predefined models, or enter custom equations and models. The capability to define new equations and build new models expands the applicability of the BEARS software beyond ET mapping to any remote sensing application. The software also includes an image viewing tool that allows users to visualize outputs, as well as draw an area of interest using various shapes. This software is freely available from the USDA-ARS Conservation and Production Research Laboratory website.

The determinations of remote sensing satellite data delivery service quality: A positivistic case study in Chinese context

NASA Astrophysics Data System (ADS)

Jin, Jiahua; Yan, Xiangbin; Tan, Qiaoqiao; Li, Yijun

2014-03-01

With the development of remote sensing technology, remote-sensing satellite has been widely used in many aspects of national construction. Big data with different standards and massive users with different needs, make the satellite data delivery service to be a complex giant system. How to deliver remote-sensing satellite data efficiently and effectively is a big challenge. Based on customer service theory, this paper proposes a hierarchy conceptual model for examining the determinations of remote-sensing satellite data delivery service quality in the Chinese context. Three main dimensions: service expectation, service perception and service environment, and 8 sub-dimensions are included in the model. Large amount of first-hand data on the remote-sensing satellite data delivery service have been obtained through field research, semi-structured questionnaire and focused interview. A positivist case study is conducted to validate and develop the proposed model, as well as to investigate the service status and related influence mechanisms. Findings from the analysis demonstrate the explanatory validity of the model, and provide potentially helpful insights for future practice.

Using Remotely Sensed Fluorescence and Soil Moisture to Better Understand the Seasonal Cycle of Tropical Grasslands

NASA Astrophysics Data System (ADS)

Smith, Dakota Carlysle

Seasonal grasslands account for a large area of Earth's land cover. Annual and seasonal changes in these grasslands have profound impacts on Earth's carbon, energy, and water cycles. In tropical grasslands, growth is commonly water-limited and the landscape oscillates between highly productive and unproductive. As the monsoon begins, soils moisten providing dry grasses the water necessary to photosynthesize. However, along with the rain come clouds that obscure satellite products that are commonly used to study productivity in these areas. To navigate this issue, we used solar induced fluorescence (SIF) products from OCO-2 along with soil moisture products from the Soil Moisture Active Passive satellite (SMAP) to "see through" the clouds to monitor grassland productivity. To get a broader understanding of the vegetation dynamics, we used the Simple Biosphere Model (SiB4) to simulate the seasonal cycles of vegetation. In conjunction with SiB4, the remotely sensed SIF and soil moisture observations were utilized to paint a clearer picture of seasonal productivity in tropical grasslands. The remotely sensed data is not available for every place at one time or at every time for one place. Thus, the study was focused on a large area from 15° E to 35° W and from 8°S to 20°N in the African Sahel. Instead of studying productivity relative to time, we studied it relative to soil moisture. Through this investigation we found soil moisture thresholds for the emergence of grassland growth, near linear grassland growth, and maturity of grassland growth. We also found that SiB4 overestimates SIF by about a factor of two for nearly every value of soil moisture. On the whole, SiB4 does a surprisingly good job of predicting the response of seasonal growth in tropical grasslands to soil moisture. Future work will continue to integrate remotely sensed SIF & soil moisture with SiB4 to add to our growing knowledge of carbon, water, and energy cycling in tropical grasslands.

Common sense: folk wisdom that ethnobiological and ethnomedical research cannot afford to ignore

PubMed Central

2013-01-01

Common sense [CS], especially that of the non-scientist, can have predictive power to identify promising research avenues, as humans anywhere on Earth have always looked for causal links to understand, shape and control the world around them. CS is based on the experience of many individuals and is thus believed to hold some truths. Outcomes predicted by CS are compatible with observations made by whole populations and have survived tests conducted by a plethora of non-scientists. To explore our claim, we provide 4 examples of empirical insights (relevant to probably all ethnic groups on Earth) into causal phenomena predicted by CS: (i) “humans must have a sense of time”, (ii) “at extreme latitudes, more people have the winter blues”, (iii) “sleep is a cure for many ills” and (iv) “social networks affect health and disease”. While CS is fallible, it should not be ignored by science – however improbable or self-evident the causal relationships predicted by CS may appear to be. PMID:24295068

What is the opposite of cat? A gentle introduction to group theory

NASA Astrophysics Data System (ADS)

Leron, Uri; Rye Ejersbo, Lisser

2016-01-01

This paper has originated from our interest in approaching mathematical concepts starting from people's common-sense intuitions and building up from there. This goal is challenging both in designing the didactical transposition and sequencing of the mathematical subject matter, and in adopting the open and interactive teaching approach needed to achieve students' active participation and reflection. To demonstrate these challenges, and our experience of trying to cope with them, we have chosen the concept of 'inverses' as used in group theory, and its common-sense precursor 'opposites'. We present our approach via a series of workshop iterations, which summarizes our experience in the many actual workshops we ran in Israel and in Denmark.

The added value of remote sensing products in constraining hydrological models

NASA Astrophysics Data System (ADS)

Nijzink, Remko C.; Almeida, Susana; Pechlivanidis, Ilias; Capell, René; Gustafsson, David; Arheimer, Berit; Freer, Jim; Han, Dawei; Wagener, Thorsten; Sleziak, Patrik; Parajka, Juraj; Savenije, Hubert; Hrachowitz, Markus

2017-04-01

The calibration of a hydrological model still depends on the availability of streamflow data, even though more additional sources of information (i.e. remote sensed data products) have become more widely available. In this research, the model parameters of four different conceptual hydrological models (HYPE, HYMOD, TUW, FLEX) were constrained with remotely sensed products. The models were applied over 27 catchments across Europe to cover a wide range of climates, vegetation and landscapes. The fluxes and states of the models were correlated with the relevant products (e.g. MOD10A snow with modelled snow states), after which new a-posteriori parameter distributions were determined based on a weighting procedure using conditional probabilities. Briefly, each parameter was weighted with the coefficient of determination of the relevant regression between modelled states/fluxes and products. In this way, final feasible parameter sets were derived without the use of discharge time series. Initial results show that improvements in model performance, with regard to streamflow simulations, are obtained when the models are constrained with a set of remotely sensed products simultaneously. In addition, we present a more extensive analysis to assess a model's ability to reproduce a set of hydrological signatures, such as rising limb density or peak distribution. Eventually, this research will enhance our understanding and recommendations in the use of remotely sensed products for constraining conceptual hydrological modelling and improving predictive capability, especially for data sparse regions.

Joint Center for Satellite Data Assimilation Overview and Research Activities

NASA Astrophysics Data System (ADS)

Auligne, T.

2017-12-01

In 2001 NOAA/NESDIS, NOAA/NWS, NOAA/OAR, and NASA, subsequently joined by the US Navy and Air Force, came together to form the Joint Center for Satellite Data Assimilation (JCSDA) for the common purpose of accelerating the use of satellite data in environmental numerical prediction modeling by developing, using, and anticipating advances in numerical modeling, satellite-based remote sensing, and data assimilation methods. The primary focus was to bring these advances together to improve operational numerical model-based forecasting, under the premise that these partners have common technical and logistical challenges assimilating satellite observations into their modeling enterprises that could be better addressed through cooperative action and/or common solutions. Over the last 15 years, the JCSDA has made and continues to make major contributions to operational assimilation of satellite data. The JCSDA is a multi-agency U.S. government-owned-and-operated organization that was conceived as a venue for the several agencies NOAA, NASA, USAF and USN to collaborate on advancing the development and operational use of satellite observations into numerical model-based environmental analysis and forecasting. The primary mission of the JCSDA is to "accelerate and improve the quantitative use of research and operational satellite data in weather, ocean, climate and environmental analysis and prediction systems." This mission is fulfilled through directed research targeting the following key science objectives: Improved radiative transfer modeling; new instrument assimilation; assimilation of humidity, clouds, and precipitation observations; assimilation of land surface observations; assimilation of ocean surface observations; atmospheric composition; and chemistry and aerosols. The goal of this presentation is to briefly introduce the JCSDA's mission and vision, and to describe recent research activities across various JCSDA partners.

Four Paths to Spirit at Work: Journeys of Personal Meaning, Fulfillment, Well-Being, and Transcendence through Work

ERIC Educational Resources Information Center

Kinjerski, Val; Skrypnek, Berna J.

2008-01-01

Spirit at work involves profound feelings of well-being, a belief that one's work makes a contribution, a sense of connection to others and common purpose, an awareness of a connection to something larger than self, and a sense of perfection and transcendence. This exploratory qualitative study revealed 4 paths leading to spirit at work: the…

Feasibility Study of TRISCAN Landing System.

DTIC Science & Technology

1977-10-01

as inclinometers, tiltmeters , vertical sensors , level sensors , pendulums, and gravity sensing electrolytic transducers. Of course, the common...5.0 NAVTOLAND SENSOR REQUIREMENTS 5.1 TRISCAN PERFORMANCE _ --* L 5.2 SHIPS MOTION SENSING 5.3 DATA LINK Dit.S.ia 6.0 CONCLUSIONS AND RECOMMENDATIONS...involved in enabling the pilot to fly V/STOL Aircraft onto Navy Ships and Marine Corps tactical sites. Guidance sensors have been identified as being

Students' Perceptions of Group Journal Writing as a Tool for Enhancing Sense of Community on Wilderness Educational Expeditions

ERIC Educational Resources Information Center

Asfeldt, Morten; Purc-Stephenson, Rebecca; Hvenegaard, Glen

2017-01-01

Journal writing is a common practice in outdoor education (OE) and there is a long-standing claim that OE programs enhance sense of community (SOC). However, there remains a call for additional evidence to support the relationship between participation in outdoor programs and SOC. This study examines students' perceptions of the role of a group…

Zonal wavefront sensing using a grating array printed on a polyester film

NASA Astrophysics Data System (ADS)

Pathak, Biswajit; Kumar, Suraj; Boruah, Bosanta R.

2015-12-01

In this paper, we describe the development of a zonal wavefront sensor that comprises an array of binary diffraction gratings realized on a transparent sheet (i.e., polyester film) followed by a focusing lens and a camera. The sensor works in a manner similar to that of a Shack-Hartmann wavefront sensor. The fabrication of the array of gratings is immune to certain issues associated with the fabrication of the lenslet array which is commonly used in zonal wavefront sensing. Besides the sensing method offers several important advantages such as flexible dynamic range, easy configurability, and option to enhance the sensing frame rate. Here, we have demonstrated the working of the proposed sensor using a proof-of-principle experimental arrangement.

A common pathway for charge transport through voltage-sensing domains.

PubMed

Chanda, Baron; Bezanilla, Francisco

2008-02-07

Voltage-gated ion channels derive their voltage sensitivity from the movement of specific charged residues in response to a change in transmembrane potential. Several studies on mechanisms of voltage sensing in ion channels support the idea that these gating charges move through a well-defined permeation pathway. This gating pathway in a voltage-gated ion channel can also be mutated to transport free cations, including protons. The recent discovery of proton channels with sequence homology to the voltage-sensing domains suggests that evolution has perhaps exploited the same gating pathway to generate a bona fide voltage-dependent proton transporter. Here we will discuss implications of these findings on the mechanisms underlying charge (and ion) transport by voltage-sensing domains.

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters. Part 1; Equivalent Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, Galina; DaSilva, Arlindo M.; Norris, Peter M.; Platnick, Steven E.

2013-01-01

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

2013-01-01

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

3-D Numerical Simulations of Biofilm Dynamics with Quorum Sensing in a Flow Cell

DTIC Science & Technology

2014-01-01

resistant mutants [?]. Inspired by experimental findings, researchers have come up with some mathematical models to study biofilm formation and function...develop a full 3D mathematical model to study how quorum sensing regulates biofilm formation and development as well as the pros and cons of quorum...have given an overview of current advances in mathematical modeling of biofilms. Concerning coupling biofilm growth with quorum sensing features

A Heuristic Decision Making Model to Mitigate Adverse Consequences in a Network Centric Warfare/Sense and Respond System

DTIC Science & Technology

2005-05-01

made. 4. Do military decision makers identify / analyze adverse consequences presently? Few do based on this research and most don’t do it effectively ...A HEURISTIC DECISION MAKING MODEL TO MITIGATE ADVERSE CONSEQUENCES IN A NETWORK CENTRIC WARFARE / SENSE AND RESPOND SYSTEM...ENS/05-01 A HEURISTIC DECISION MAKING MODEL TO MITIGATE ADVERSE CONSEQUENCES IN A NETWORK CENTRIC WARFARE / SENSE AND RESPOND SYSTEM

Mathematic modeling of the Earth's surface and the process of remote sensing

NASA Technical Reports Server (NTRS)

Balter, B. M.

1979-01-01

It is shown that real data from remote sensing of the Earth from outer space are not best suited to the search for optimal procedures with which to process such data. To work out the procedures, it was proposed that data synthesized with the help of mathematical modeling be used. A criterion for simularity to reality was formulated. The basic principles for constructing methods for modeling the data from remote sensing are recommended. A concrete method is formulated for modeling a complete cycle of radiation transformations in remote sensing. A computer program is described which realizes the proposed method. Some results from calculations are presented which show that the method satisfies the requirements imposed on it.

Gambling with Nonsense: Play and the Secondary English Classroom

ERIC Educational Resources Information Center

Garfath, Toby

2015-01-01

Dominant and common-sense contemporary conceptions of practice tend to frame the emotional volatility of the classroom--most commonly explored in discussions about student behaviour--as a fundamental obstacle to teaching and learning. The "outstanding" classroom is both orderly and, paradoxically perhaps, characterised by its passionate,…

Making Sense of Fear Testing - Validating Common Behavioral Tests used in Swine

USDA-ARS?s Scientific Manuscript database

Tests to assess fear are commonly used in laboratory animals, such as mice and rats, when researchers wish to understand the implications of specific drugs, such as anxiolytics, or specific environments which may be used to house experimental animals. Researchers who study the welfare of livestock ...

Practical Tools for Foster Parents. Foster Care Solutions.

ERIC Educational Resources Information Center

Temple-Plotz, Lana, Ed.; Stricklett, Ted P., Ed.; Baker, Christena B., Ed.; Sterba, Michael N., Ed.

Based on the Girls and Boys Town's "Common Sense Parenting" approach, this book presents an approach to foster parenting focusing on building relationships with children, teaching them skills, and empowering them by teaching self-discipline and self-control. Research-based solutions are provided for common concerns, including building a…

Scripps Ocean Modeling and Remote Sensing (SOMARS)

DTIC Science & Technology

1988-09-20

Topics in this brief reports include: Kalman filtering of oceanographic data; Remote sensing of sea surface temperature; Altimetry and Surface heat fluxes; Ocean models of the marine mixed layer; Radar altimetry; Mathematical model of California current eddies.

Modeling and control of a self-sensing polymer metal composite actuator

NASA Astrophysics Data System (ADS)

Nam, Doan Ngoc Chi; Ahn, Kyoung Kwan

2014-02-01

An ion polymer metal composite (IPMC) is an electro-active polymer (EAP) that bends in response to a small applied electrical field as a result of mobility of cations in the polymer network and vice versa. One drawback in the use of an IPMC is the sensing problem for such a small size actuator. The aim of this paper is to develop a physical model for a self-sensing IPMC actuator and to verify its applicability for practical position control. Firstly, ion dynamics inside a polymer membrane is investigated with an asymmetric solution in the presence of distributed surface resistance. Based on this analysis, a modified equivalent circuit and a simple configuration to realize the self-sensing IPMC actuator are proposed. Mathematical modelling and experimental evaluation indicate that the bending curvature can be obtained accurately using several feedback voltage signals along with the IPMC length. Finally, the controllability of the developed self-sensing IPMC actuator is investigated using a robust position control. Experimental results prove that the self-sensing characteristics can be applied in engineering control problems to provide a more convenient sensing method for IPMC actuating systems.

Experiments in sensing transient rotational acceleration cues on a flight simulator

NASA Technical Reports Server (NTRS)

Parrish, R. V.

1979-01-01

Results are presented for two transient motion sensing experiments which were motivated by the identification of an anomalous roll cue (a 'jerk' attributed to an acceleration spike) in a prior investigation of realistic fighter motion simulation. The experimental results suggest the consideration of several issues for motion washout and challenge current sensory system modeling efforts. Although no sensory modeling effort is made it is argued that such models must incorporate the ability to handle transient inputs of short duration (some of which are less than the accepted latency times for sensing), and must represent separate channels for rotational acceleration and velocity sensing.

Remote sensing sensors and applications in environmental resources mapping and modeling

USGS Publications Warehouse

Melesse, Assefa M.; Weng, Qihao; Thenkabail, Prasad S.; Senay, Gabriel B.

2007-01-01

The history of remote sensing and development of different sensors for environmental and natural resources mapping and data acquisition is reviewed and reported. Application examples in urban studies, hydrological modeling such as land-cover and floodplain mapping, fractional vegetation cover and impervious surface area mapping, surface energy flux and micro-topography correlation studies is discussed. The review also discusses the use of remotely sensed-based rainfall and potential evapotranspiration for estimating crop water requirement satisfaction index and hence provides early warning information for growers. The review is not an exhaustive application of the remote sensing techniques rather a summary of some important applications in environmental studies and modeling.

The review of dynamic monitoring technology for crop growth

NASA Astrophysics Data System (ADS)

Zhang, Hong-wei; Chen, Huai-liang; Zou, Chun-hui; Yu, Wei-dong

2010-10-01

In this paper, crop growth monitoring methods are described elaborately. The crop growth models, Netherlands-Wageningen model system, the United States-GOSSYM model and CERES models, Australia APSIM model and CCSODS model system in China, are introduced here more focus on the theories of mechanism, applications, etc. The methods and application of remote sensing monitoring methods, which based on leaf area index (LAI) and biomass were proposed by different scholars at home and abroad, are highly stressed in the paper. The monitoring methods of remote sensing coupling with crop growth models are talked out at large, including the method of "forced law" which using remote sensing retrieval state parameters as the crop growth model parameters input, and then to enhance the dynamic simulation accuracy of crop growth model and the method of "assimilation of Law" which by reducing the gap difference between the value of remote sensing retrieval and the simulated values of crop growth model and thus to estimate the initial value or parameter values to increasing the simulation accuracy. At last, the developing trend of monitoring methods are proposed based on the advantages and shortcomings in previous studies, it is assured that the combination of remote sensing with moderate resolution data of FY-3A, MODIS, etc., crop growth model, "3S" system and observation in situ are the main methods in refinement of dynamic monitoring and quantitative assessment techniques for crop growth in future.

The Evolution of Quorum Sensing as a Mechanism to Infer Kinship

PubMed Central

Schluter, Jonas; Schoech, Armin P.; Foster, Kevin R.; Mitri, Sara

2016-01-01

Bacteria regulate many phenotypes via quorum sensing systems. Quorum sensing is typically thought to evolve because the regulated cooperative phenotypes are only beneficial at certain cell densities. However, quorum sensing systems are also threatened by non-cooperative “cheaters” that may exploit quorum-sensing regulated cooperation, which begs the question of how quorum sensing systems are maintained in nature. Here we study the evolution of quorum sensing using an individual-based model that captures the natural ecology and population structuring of microbial communities. We first recapitulate the two existing observations on quorum sensing evolution: density-dependent benefits favor quorum sensing but competition and cheating will destabilize it. We then model quorum sensing in a dense community like a biofilm, which reveals a novel benefit to quorum sensing that is intrinsically evolutionarily stable. In these communities, competing microbial genotypes gradually segregate over time leading to positive correlation between density and genetic similarity between neighboring cells (relatedness). This enables quorum sensing to track genetic relatedness and ensures that costly cooperative traits are only activated once a cell is safely surrounded by clonemates. We hypothesize that under similar natural conditions, the benefits of quorum sensing will not result from an assessment of density but from the ability to infer kinship. PMID:27120081

Current NASA Earth Remote Sensing Observations

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.; Sprigg, William A.; Huete, Alfredo; Pejanovic, Goran; Nickovic, Slobodan; Ponce-Campos, Guillermo; Krapfl, Heide; Budge, Amy; Zelicoff, Alan; Myers, Orrin;

SenseLab

PubMed Central

Crasto, Chiquito J.; Marenco, Luis N.; Liu, Nian; Morse, Thomas M.; Cheung, Kei-Hoi; Lai, Peter C.; Bahl, Gautam; Masiar, Peter; Lam, Hugo Y.K.; Lim, Ernest; Chen, Huajin; Nadkarni, Prakash; Migliore, Michele; Miller, Perry L.; Shepherd, Gordon M.

2009-01-01

This article presents the latest developments in neuroscience information dissemination through the SenseLab suite of databases: NeuronDB, CellPropDB, ORDB, OdorDB, OdorMapDB, ModelDB and BrainPharm. These databases include information related to: (i) neuronal membrane properties and neuronal models, and (ii) genetics, genomics, proteomics and imaging studies of the olfactory system. We describe here: the new features for each database, the evolution of SenseLab’s unifying database architecture and instances of SenseLab database interoperation with other neuroscience online resources. PMID:17510162

Assessing Surface Fuel Hazard in Coastal Conifer Forests through the Use of LiDAR Remote Sensing

NASA Astrophysics Data System (ADS)

Koulas, Christos

The research problem that this thesis seeks to examine is a method of predicting conventional fire hazards using data drawn from specific regions, namely the Sooke and Goldstream watershed regions in coastal British Columbia. This thesis investigates whether LiDAR data can be used to describe conventional forest stand fire hazard classes. Three objectives guided this thesis: to discuss the variables associated with fire hazard, specifically the distribution and makeup of fuel; to examine the relationship between derived LiDAR biometrics and forest attributes related to hazard assessment factors defined by the Capitol Regional District (CRD); and to assess the viability of the LiDAR biometric decision tree in the CRD based on current frameworks for use. The research method uses quantitative datasets to assess the optimal generalization of these types of fire hazard data through discriminant analysis. Findings illustrate significant LiDAR-derived data limitations, and reflect the literature in that flawed field application of data modelling techniques has led to a disconnect between the ways in which fire hazard models have been intended to be used by scholars and the ways in which they are used by those tasked with prevention of forest fires. It can be concluded that a significant trade-off exists between computational requirements for wildfire simulation models and the algorithms commonly used by field teams to apply these models with remote sensing data, and that CRD forest management practices would need to change to incorporate a decision tree model in order to decrease risk.

Colombian forensic genetics as a form of public science: The role of race, nation and common sense in the stabilization of DNA populations.

PubMed

Schwartz-Marín, Ernesto; Wade, Peter; Cruz-Santiago, Arely; Cárdenas, Roosbelinda

2015-12-01

Abstract This article examines the role that vernacular notions of racialized-regional difference play in the constitution and stabilization of DNA populations in Colombian forensic science, in what we frame as a process of public science. In public science, the imaginations of the scientific world and common-sense public knowledge are integral to the production and circulation of science itself. We explore the origins and circulation of a scientific object--'La Tabla', published in Paredes et al. and used in genetic forensic identification procedures--among genetic research institutes, forensic genetics laboratories and courtrooms in Bogotá. We unveil the double life of this central object of forensic genetics. On the one hand, La Tabla enjoys an indisputable public place in the processing of forensic genetic evidence in Colombia (paternity cases, identification of bodies, etc.). On the other hand, the relations it establishes between 'race', geography and genetics are questioned among population geneticists in Colombia. Although forensic technicians are aware of the disputes among population geneticists, they use and endorse the relations established between genetics, 'race' and geography because these fit with common-sense notions of visible bodily difference and the regionalization of race in the Colombian nation.

Colombian forensic genetics as a form of public science: The role of race, nation and common sense in the stabilization of DNA populations

PubMed Central

Schwartz-Marín, Ernesto; Wade, Peter; Cruz-Santiago, Arely; Cárdenas, Roosbelinda

2015-01-01

This article examines the role that vernacular notions of racialized-regional difference play in the constitution and stabilization of DNA populations in Colombian forensic science, in what we frame as a process of public science. In public science, the imaginations of the scientific world and common-sense public knowledge are integral to the production and circulation of science itself. We explore the origins and circulation of a scientific object – ‘La Tabla’, published in Paredes et al. and used in genetic forensic identification procedures – among genetic research institutes, forensic genetics laboratories and courtrooms in Bogotá. We unveil the double life of this central object of forensic genetics. On the one hand, La Tabla enjoys an indisputable public place in the processing of forensic genetic evidence in Colombia (paternity cases, identification of bodies, etc.). On the other hand, the relations it establishes between ‘race’, geography and genetics are questioned among population geneticists in Colombia. Although forensic technicians are aware of the disputes among population geneticists, they use and endorse the relations established between genetics, ‘race’ and geography because these fit with common-sense notions of visible bodily difference and the regionalization of race in the Colombian nation. PMID:27480000

Intelligence involves risk-awareness and intellectual disability involves risk-unawareness: implications of a theory of common sense.

PubMed

Greenspan, Stephen; Switzky, Harvey N; Woods, George W

2011-12-01

Survival in the everyday world (in both social and practical functioning) depends on one's ability to recognise and avoid going down the worst possible path, especially when doing so places one at risk of death, injury, or social disaster. Most people possess "common sense" (the ability to recognise obvious risk) but some people lack that ability and thus are at high risk of engaging in "foolish" (i.e., risk-unaware) action. People who have a cognitive impairment are much less able to recognise and avoid risk, and this is what causes them to be seen as needing protection and support. In this paper, we argue that the answer to the question "What is intellectual disability (ID)?" is more likely to come from the question "What is unintelligent behavior?" than "What is intelligence?" The answer which comes from such a question is that "ID is a common sense deficit disorder characterised by unawareness of obvious social and practical risk." Several implications of this answer are explored for the field of intellectual disability. These implications are explored primarily for adults who may have ID, given that the inspiration for this paper came from the way existing ID definitions are applied or misapplied in the US adult criminal justice system.

Cross-Language Translation Priming Asymmetry with Chinese-English Bilinguals: A Test of the Sense Model

ERIC Educational Resources Information Center

Chen, Baoguo; Zhou, Huixia; Gao, Yiwen; Dunlap, Susan

2014-01-01

The present study aimed to test the Sense Model of cross-linguistic masked translation priming asymmetry, proposed by Finkbeiner et al. ("J Mem Lang" 51:1-22, 2004), by manipulating the number of senses that bilingual participants associated with words from both languages. Three lexical decision experiments were conducted with…

Terahertz absorption spectra of commonly used antimalarial drugs

NASA Astrophysics Data System (ADS)

Bawuah, Prince; Zeitler, J. Axel; Ketolainen, Jarkko; Peiponen, Kai-Erik

2018-06-01

Terahertz (THz) spectra from the pure forms [i.e. the active pharmaceutical ingredients (APIs)] of four commonly used antimalarial drugs are reported. The well-defined spectral fingerprints obtained for these APIs in the spectral range of 0.1 THz-3 THz show the sensitivity of the THz time-domain spectroscopic (THz-TDS) method for screening antimalarial drugs. For identification purpose, two commercially available antimalarial tablets were detected. Clear spectral fingerprints of the APIs in the antimalarial tablets were obtained even amidst the several types of excipients present in the tablets. This observation further proves the high sensitivity of the THz techniques in tracking the presence or absence of API in a pharmaceutical tablet. We envisage that the spectral data obtained for these drugs can contribute to a spectroscopic database in the far infrared spectral region and hence support the modelling of THz sensing to differentiate between genuine and counterfeit antimalarial tablets.

Eliciting probabilistic expectations: Collaborations between psychologists and economists

PubMed Central

Bruine de Bruin, Wändi

2017-01-01

We describe two collaborations in which psychologists and economists provided essential support on foundational projects in major research programs. One project involved eliciting adolescents’ expectations regarding significant future life events affecting their psychological and economic development. The second project involved eliciting consumers’ expectations regarding inflation, a potentially vital input to their investment, saving, and purchasing decisions. In each project, we sought questions with the precision needed for economic modeling and the simplicity needed for lay respondents. We identify four conditions that, we believe, promoted our ability to sustain these transdisciplinary collaborations and coproduce the research: (i) having a shared research goal, which neither discipline could achieve on its own; (ii) finding common ground in shared methodology, which met each discipline’s essential evidentiary conditions, but without insisting on its culturally acquired tastes; (iii) sharing the effort throughout, with common language and sense of ownership; and (iv) gaining mutual benefit from both the research process and its products. PMID:28270610

Terahertz absorption spectra of commonly used antimalarial drugs

NASA Astrophysics Data System (ADS)

Bawuah, Prince; Zeitler, J. Axel; Ketolainen, Jarkko; Peiponen, Kai-Erik

2018-03-01

Terahertz (THz) spectra from the pure forms [i.e. the active pharmaceutical ingredients (APIs)] of four commonly used antimalarial drugs are reported. The well-defined spectral fingerprints obtained for these APIs in the spectral range of 0.1 THz-3 THz show the sensitivity of the THz time-domain spectroscopic (THz-TDS) method for screening antimalarial drugs. For identification purpose, two commercially available antimalarial tablets were detected. Clear spectral fingerprints of the APIs in the antimalarial tablets were obtained even amidst the several types of excipients present in the tablets. This observation further proves the high sensitivity of the THz techniques in tracking the presence or absence of API in a pharmaceutical tablet. We envisage that the spectral data obtained for these drugs can contribute to a spectroscopic database in the far infrared spectral region and hence support the modelling of THz sensing to differentiate between genuine and counterfeit antimalarial tablets.

Eliciting probabilistic expectations: Collaborations between psychologists and economists.

PubMed

Bruine de Bruin, Wändi; Fischhoff, Baruch

2017-03-28

We describe two collaborations in which psychologists and economists provided essential support on foundational projects in major research programs. One project involved eliciting adolescents' expectations regarding significant future life events affecting their psychological and economic development. The second project involved eliciting consumers' expectations regarding inflation, a potentially vital input to their investment, saving, and purchasing decisions. In each project, we sought questions with the precision needed for economic modeling and the simplicity needed for lay respondents. We identify four conditions that, we believe, promoted our ability to sustain these transdisciplinary collaborations and coproduce the research: ( i ) having a shared research goal, which neither discipline could achieve on its own; ( ii ) finding common ground in shared methodology, which met each discipline's essential evidentiary conditions, but without insisting on its culturally acquired tastes; ( iii ) sharing the effort throughout, with common language and sense of ownership; and ( iv ) gaining mutual benefit from both the research process and its products.

Episodic Reasoning for Vision-Based Human Action Recognition

PubMed Central

Martinez-del-Rincon, Jesus

2014-01-01

Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning. PMID:24959602

A metacognitive model of the sense of agency over thoughts.

PubMed

Carruthers, Glenn

2012-01-01

The sense of agency over thoughts is the experience of oneself qua agent of mental action. Those suffering certain psychotic symptoms are thought to have a deficient sense of agency. Here I seek to explain this sense of agency in terms of metacognition. I start with the proposal that the sense of agency is elicited by metacognitive monitoring representations that are used in the intentional inhibition of thoughts. I apply this model to verbal hallucinations and the like and examine the plausibility of this model explaining deficits associated with these symptoms. By tying the sense of agency to metacognitive inhibition I propose that the loss of a sense of agency in certain psychotic symptoms is accompanied by a particular deficit in the patient's ability to control their own thinking. This is consistent with the experiences of those at high risk of developing hallucinations, who report more intrusive thoughts than controls. The model I present is able to explain why those at risk of developing verbal hallucinations and those suffering from verbal hallucinations have deficits in the intentional inhibition of thought. I defend this account from a possible objection by distinguishing the form of the intentional inhibition deficit displayed by those suffering verbal hallucination from that displayed by those suffering from orbital-frontal cortex lesions and posttraumatic stress disorder. A plausible hypothesis is that the sense of agency over thoughts is elicited by the metacognitive monitoring representation used to intentionally inhibit thoughts. The deficit in the sense of agency over thoughts associated with certain psychotic symptoms could be explained by a failure to properly metacognitively monitor certain thought processes.

Directional gravity sensing in gravitropism.

PubMed

Morita, Miyo Terao

2010-01-01

Plants can reorient their growth direction by sensing organ tilt relative to the direction of gravity. With respect to gravity sensing in gravitropism, the classic starch statolith hypothesis, i.e., that starch-accumulating amyloplast movement along the gravity vector within gravity-sensing cells (statocytes) is the probable trigger of subsequent intracellular signaling, is widely accepted. Several lines of experimental evidence have demonstrated that starch is important but not essential for gravity sensing and have suggested that it is reasonable to regard plastids (containers of starch) as statoliths. Although the word statolith means sedimented stone, actual amyloplasts are not static but instead possess dynamic movement. Recent studies combining genetic and cell biological approaches, using Arabidopsis thaliana, have demonstrated that amyloplast movement is an intricate process involving vacuolar membrane structures and the actin cytoskeleton. This review covers current knowledge regarding gravity sensing, particularly gravity susception, and the factors modulating the function of amyloplasts for sensing the directional change of gravity. Specific emphasis is made on the remarkable differences in the cytological properties, developmental origins, tissue locations, and response of statocytes between root and shoot systems. Such an approach reveals a common theme in directional gravity-sensing mechanisms in these two disparate organs.

Active touch sensing

PubMed Central

Prescott, Tony J.; Diamond, Mathew E.; Wing, Alan M.

2011-01-01

Active sensing systems are purposive and information-seeking sensory systems. Active sensing usually entails sensor movement, but more fundamentally, it involves control of the sensor apparatus, in whatever manner best suits the task, so as to maximize information gain. In animals, active sensing is perhaps most evident in the modality of touch. In this theme issue, we look at active touch across a broad range of species from insects, terrestrial and marine mammals, through to humans. In addition to analysing natural touch, we also consider how engineering is beginning to exploit physical analogues of these biological systems so as to endow robots with rich tactile sensing capabilities. The different contributions show not only the varieties of active touch—antennae, whiskers and fingertips—but also their commonalities. They explore how active touch sensing has evolved in different animal lineages, how it serves to provide rapid and reliable cues for controlling ongoing behaviour, and even how it can disintegrate when our brains begin to fail. They demonstrate that research on active touch offers a means both to understand this essential and primary sensory modality, and to investigate how animals, including man, combine movement with sensing so as to make sense of, and act effectively in, the world. PMID:21969680

Study on algorithm of process neural network for soft sensing in sewage disposal system

NASA Astrophysics Data System (ADS)

Liu, Zaiwen; Xue, Hong; Wang, Xiaoyi; Yang, Bin; Lu, Siying

2006-11-01

A new method of soft sensing based on process neural network (PNN) for sewage disposal system is represented in the paper. PNN is an extension of traditional neural network, in which the inputs and outputs are time-variation. An aggregation operator is introduced to process neuron, and it makes the neuron network has the ability to deal with the information of space-time two dimensions at the same time, so the data processing enginery of biological neuron is imitated better than traditional neuron. Process neural network with the structure of three layers in which hidden layer is process neuron and input and output are common neurons for soft sensing is discussed. The intelligent soft sensing based on PNN may be used to fulfill measurement of the effluent BOD (Biochemical Oxygen Demand) from sewage disposal system, and a good training result of soft sensing was obtained by the method.

Contesting nonfiction: Fourth graders making sense of words and images in science information book discussions

NASA Astrophysics Data System (ADS)

Belfatti, Monica A.

Recently developed common core standards echo calls by educators for ensuring that upper elementary students become proficient readers of informational texts. Informational texts have been theorized as causing difficulty for students because they contain linguistic and visual features different from more familiar narrative genres (Lemke, 2004). It has been argued that learning to read informational texts, particularly those with science subject matter, requires making sense of words, images, and the relationships among them (Pappas, 2006). Yet, conspicuously absent in the research are empirical studies documenting ways students make use of textual resources to build textual and conceptual understandings during classroom literacy instruction. This 10-month practitioner research study was designed to investigate the ways a group of ethnically and linguistically diverse fourth graders in one metropolitan school made sense of science information books during dialogically organized literature discussions. In this nontraditional instructional context, I wondered whether and how young students might make use of science informational text features, both words and images, in the midst of collaborative textual and conceptual inquiry. Drawing on methods of constructivist grounded theory and classroom discourse analysis, I analyzed student and teacher talk in 25 discussions of earth and life science books. Digital voice recordings and transcriptions served as the main data sources for this study. I found that, without teacher prompts or mandates to do so, fourth graders raised a wide range of textual and conceptual inquiries about words, images, scientific figures, and phenomena. In addition, my analysis yielded a typology of ways students constructed relationships between words and images within and across page openings of the information books read for their sense-making endeavors. The diversity of constructed word-image relationships aided students in raising, exploring, and contesting textual and conceptual ideas. Moreover, through their joint inquiries, students marshaled and evaluated a rich array of resources. Students' sense-making of information books was not contained by the words and images alone; it involved a situated, complex process of making sense of multiple texts, discourses, and epistemologies. These findings suggest educators, theorists, and policy makers reconsider acontextual, linear, hierarchical models for developing elementary students as sense-makers of nonfiction.

Learning from Massive Distributed Data Sets (Invited)

NASA Astrophysics Data System (ADS)

Kang, E. L.; Braverman, A. J.

2013-12-01

Technologies for remote sensing and ever-expanding computer experiments in climate science are generating massive data sets. Meanwhile, it has been common in all areas of large-scale science to have these 'big data' distributed over multiple different physical locations, and moving large amounts of data can be impractical. In this talk, we will discuss efficient ways for us to summarize and learn from distributed data. We formulate a graphical model to mimic the main characteristics of a distributed-data network, including the size of the data sets and speed of moving data. With this nominal model, we investigate the trade off between prediction accurate and cost of data movement, theoretically and through simulation experiments. We will also discuss new implementations of spatial and spatio-temporal statistical methods optimized for distributed data.

Modeling an integrative physical examination program for the Departments of Defense and Veterans Affairs.

PubMed

Goodrich, Scott G

2006-10-01

Current policies governing the Departments of Defense and Veterans Affairs physical examination programs are out of step with current evidence-based medical practice. Replacing periodic and other routine physical examination types with annual preventive health assessments would afford our service members additional health benefit at reduced cost. Additionally, the Departments of Defense and Veterans Affairs repeat the physical examination process at separation and have been unable to reconcile their respective disability evaluation systems to reduce duplication and waste. A clear, coherent, and coordinated strategy to improve the relevance and utility of our physical examination programs is long overdue. This article discusses existing physical examination programs and proposes a model for a new integrative physical examination program based on need, science, and common sense.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.

2014-08-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.

Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties

PubMed Central

Braun, Efrem; Carraro, Carlo; Smit, Berend

2017-01-01

Some nanoporous, crystalline materials possess dynamic constituents, for example, rotatable moieties. These moieties can undergo a conformation change in response to the adsorption of guest molecules, which qualitatively impacts adsorption behavior. We pose and solve a statistical mechanical model of gas adsorption in a porous crystal whose cages share a common ligand that can adopt two distinct rotational conformations. Guest molecules incentivize the ligands to adopt a different rotational configuration than maintained in the empty host. Our model captures inflections, steps, and hysteresis that can arise in the adsorption isotherm as a signature of the rotating ligands. The insights disclosed by our simple model contribute a more intimate understanding of the response and consequence of rotating ligands integrated into porous materials to harness them for gas storage and separations, chemical sensing, drug delivery, catalysis, and nanoscale devices. Particularly, our model reveals design strategies to exploit these moving constituents and engineer improved adsorbents with intrinsic thermal management for pressure-swing adsorption processes. PMID:28049851

Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties.

PubMed

Simon, Cory M; Braun, Efrem; Carraro, Carlo; Smit, Berend

2017-01-17

Some nanoporous, crystalline materials possess dynamic constituents, for example, rotatable moieties. These moieties can undergo a conformation change in response to the adsorption of guest molecules, which qualitatively impacts adsorption behavior. We pose and solve a statistical mechanical model of gas adsorption in a porous crystal whose cages share a common ligand that can adopt two distinct rotational conformations. Guest molecules incentivize the ligands to adopt a different rotational configuration than maintained in the empty host. Our model captures inflections, steps, and hysteresis that can arise in the adsorption isotherm as a signature of the rotating ligands. The insights disclosed by our simple model contribute a more intimate understanding of the response and consequence of rotating ligands integrated into porous materials to harness them for gas storage and separations, chemical sensing, drug delivery, catalysis, and nanoscale devices. Particularly, our model reveals design strategies to exploit these moving constituents and engineer improved adsorbents with intrinsic thermal management for pressure-swing adsorption processes.

Scaling field data to calibrate and validate moderate spatial resolution remote sensing models

USGS Publications Warehouse

Baccini, A.; Friedl, M.A.; Woodcock, C.E.; Zhu, Z.

2007-01-01

Validation and calibration are essential components of nearly all remote sensing-based studies. In both cases, ground measurements are collected and then related to the remote sensing observations or model results. In many situations, and particularly in studies that use moderate resolution remote sensing, a mismatch exists between the sensor's field of view and the scale at which in situ measurements are collected. The use of in situ measurements for model calibration and validation, therefore, requires a robust and defensible method to spatially aggregate ground measurements to the scale at which the remotely sensed data are acquired. This paper examines this challenge and specifically considers two different approaches for aggregating field measurements to match the spatial resolution of moderate spatial resolution remote sensing data: (a) landscape stratification; and (b) averaging of fine spatial resolution maps. The results show that an empirically estimated stratification based on a regression tree method provides a statistically defensible and operational basis for performing this type of procedure. 

Clever sillies: why high IQ people tend to be deficient in common sense.

PubMed

Charlton, Bruce G

2009-12-01

In previous editorials I have written about the absent-minded and socially-inept 'nutty professor' stereotype in science, and the phenomenon of 'psychological neoteny' whereby intelligent modern people (including scientists) decline to grow-up and instead remain in a state of perpetual novelty-seeking adolescence. These can be seen as specific examples of the general phenomenon of 'clever sillies' whereby intelligent people with high levels of technical ability are seen (by the majority of the rest of the population) as having foolish ideas and behaviours outside the realm of their professional expertise. In short, it has often been observed that high IQ types are lacking in 'common sense'--and especially when it comes to dealing with other human beings. General intelligence is not just a cognitive ability; it is also a cognitive disposition. So, the greater cognitive abilities of higher IQ tend also to be accompanied by a distinctive high IQ personality type including the trait of 'Openness to experience', 'enlightened' or progressive left-wing political values, and atheism. Drawing on the ideas of Kanazawa, my suggested explanation for this association between intelligence and personality is that an increasing relative level of IQ brings with it a tendency differentially to over-use general intelligence in problem-solving, and to over-ride those instinctive and spontaneous forms of evolved behaviour which could be termed common sense. Preferential use of abstract analysis is often useful when dealing with the many evolutionary novelties to be found in modernizing societies; but is not usually useful for dealing with social and psychological problems for which humans have evolved 'domain-specific' adaptive behaviours. And since evolved common sense usually produces the right answers in the social domain; this implies that, when it comes to solving social problems, the most intelligent people are more likely than those of average intelligence to have novel but silly ideas, and therefore to believe and behave maladaptively. I further suggest that this random silliness of the most intelligent people may be amplified to generate systematic wrongness when intellectuals are in addition 'advertising' their own high intelligence in the evolutionarily novel context of a modern IQ meritocracy. The cognitively-stratified context of communicating almost-exclusively with others of similar intelligence, generates opinions and behaviours among the highest IQ people which are not just lacking in common sense but perversely wrong. Hence the phenomenon of 'political correctness' (PC); whereby false and foolish ideas have come to dominate, and moralistically be enforced upon, the ruling elites of whole nations.

The emergence of asymmetric normal fault systems under symmetric boundary conditions

NASA Astrophysics Data System (ADS)

Schöpfer, Martin P. J.; Childs, Conrad; Manzocchi, Tom; Walsh, John J.; Nicol, Andrew; Grasemann, Bernhard

2017-11-01

Many normal fault systems and, on a smaller scale, fracture boudinage often exhibit asymmetry with one fault dip direction dominating. It is a common belief that the formation of domino and shear band boudinage with a monoclinic symmetry requires a component of layer parallel shearing. Moreover, domains of parallel faults are frequently used to infer the presence of a décollement. Using Distinct Element Method (DEM) modelling we show, that asymmetric fault systems can emerge under symmetric boundary conditions. A statistical analysis of DEM models suggests that the fault dip directions and system polarities can be explained using a random process if the strength contrast between the brittle layer and the surrounding material is high. The models indicate that domino and shear band boudinage are unreliable shear-sense indicators. Moreover, the presence of a décollement should not be inferred on the basis of a domain of parallel faults alone.

Remote Sensing based modelling of Annual Surface Mass Balances of Chhota Shigiri Glacier, Western Himalayas, India

NASA Astrophysics Data System (ADS)

Chandrasekharan, Anita; Ramsankaran, Raaj

2017-04-01

The current study aims at modelling glacier mass balances over Chhota Shigiri glacier (32.28o N; 77.58° E) in Himachal Pradesh, India using the Equilibrium Line Altitude (ELA) gradient approach proposed by Rabatel et al. (2005). The model requires yearly ELA, average mass balance and mass balance gradient to estimate annual mass balance of a glacier which can be obtained either through field measurements or remote sensing observations. However, in view of the general scenario of lack of field data for Himalayan glaciers, in this study the model has been applied only using the inputs derived through multi-temporal satellite remote sensing observations thus eliminating the need for any field measurements. Preliminary analysis show that the obtained results are comparable with the observed field mass balance. The results also demonstrate that this approach with remote sensing inputs has potential to be used for glacier mass balance estimations provided good quality multi-temporal remote sensing dataset are available.

SPASE: The Connection Among Solar and Space Physics Data Centers

NASA Technical Reports Server (NTRS)

Thieman, James R.; King, Todd A.; Roberts, D. Aaron

2011-01-01

The Space Physics Archive Search and Extract (SPASE) project is an international collaboration among Heliophysics (solar and space physics) groups concerned with data acquisition and archiving. Within this community there are a variety of old and new data centers, resident archives, "virtual observatories", etc. acquiring, holding, and distributing data. A researcher interested in finding data of value for his or her study faces a complex data environment. The SPASE group has simplified the search for data through the development of the SPASE Data Model as a common method to describe data sets in the various archives. The data model is an XML-based schema and is now in operational use. There are both positives and negatives to this approach. The advantage is the common metadata language enabling wide-ranging searches across the archives, but it is difficult to inspire the data holders to spend the time necessary to describe their data using the Model. Software tools have helped, but the main motivational factor is wide-ranging use of the standard by the community. The use is expanding, but there are still other groups who could benefit from adopting SPASE. The SPASE Data Model is also being expanded in the sense of providing the means for more detailed description of data sets with the aim of enabling more automated ingestion and use of the data through detailed format descriptions. We will discuss the present state of SPASE usage and how we foresee development in the future. The evolution is based on a number of lessons learned - some unique to Heliophysics, but many common to the various data disciplines.

Estimating crop biophysical properties from remote sensing data by inverting linked radiative transfer and ecophysiological models

USDA-ARS?s Scientific Manuscript database

Remote sensing technology can rapidly provide spatial information on crop growth status, which ideally could be used to invert radiative transfer models or ecophysiological models for estimating a variety of crop biophysical properties. However, the outcome of the model inversion procedure will be ...

Critical Pedagogy and Participatory Democracy: Creating Classroom Contexts That Challenge "Common Sense." A Response to "The Political Nuances of Narratives and an Urban Educator's Response"

ERIC Educational Resources Information Center

Monzó, Lilia; Morales, P. Zitlali

2016-01-01

In this response to "The Political Nuances of Narratives and an Urban Educator's Response," the authors applaud Pearman's critical approach to deconstructing and challenging narratives of heroic figures who single-handedly change the world and agree with him that these narratives restrict the sense of agency that may propel citizens to…

QCL-based nonlinear sensing of independent targets dynamics.

PubMed

Mezzapesa, F P; Columbo, L L; Dabbicco, M; Brambilla, M; Scamarcio, G

2014-03-10

We demonstrate a common-path interferometer to measure the independent displacement of multiple targets through nonlinear frequency mixing in a quantum-cascade laser (QCL). The sensing system exploits the unique stability of QCLs under strong optical feedback to access the intrinsic nonlinearity of the active medium. The experimental results using an external dual cavity are in excellent agreement with the numerical simulations based on the Lang-Kobayashi equations.

Predicting needs for nursing home admission - does sense of coherence delay nursing home admission in care dependent older people? A longitudinal study.

PubMed

Thygesen, Elin; Saevareid, Hans Inge; Lindstrom, Torill Christine; Nygaard, Harald A; Engedal, Knut

2009-03-01

Objectives.  This study examined predisposing, enabling and need variables (Andersen's Behavioral Model) influencing the need for nursing home admission (NHA) in older people receiving home nursing care. In particular, the potential role of coping ability, measured as 'sense of coherence' (SOC), was studied. Design, sample, and measurements.  A survey with baseline- and follow-up data after a 2-year period was undertaken with 208 patients aged 75+. The measures used were: gender, education, age, social visits, SOC, social provision scale (SPS), self-rated health (SRH), general health questionnaire (GHQ), clinical dementia rating (CDR), Barthel activities of daily living (ADL) index, and registered illnesses (RI). A Cox proportional model was used to examine factors that could explain risk of NHA. Results.  Measures with predictive properties were Barthel ADL index, SPS, SRH, and gender. SOC, along with subjective health complaints, general health questionnaire, RI and social visits did not predict NHA. Conclusions.  It is concluded that the patients' subjective evaluations of both their health and perceived social support were important predictors of future NHA needs, and should be seriously taken into consideration, along with the more commonly used objective measures of ADL and CDR. © 2008 The Authors. Journal compilation © 2008 Blackwell Publishing Ltd.

The experience of epilepsy in later life: A qualitative exploration of illness representations.

PubMed

Yennadiou, Haris; Wolverson, Emma

2017-05-01

The objective of this study was to explore how older people living with epilepsy appraise their condition through their lived-experience. The common-sense model of illness representations (CSMIR) provides a framework to explain how individuals make sense of and manage health threats. Semi-structured in-depth interviews based on the CSMIR were conducted with ten people with epilepsy who were above the age of 65. The results were analyzed using Interpretative Phenomenological Analysis. Three overarching themes emerged from the analysis: 'the power of epilepsy', 'they say you can live a normal life but you can't' and 'attempts to adjust and cope'. Epilepsy was described as a threatening, persistent, and unpredictable condition associated with distressing experiences. Participants described a process of balancing negative psychosocial consequences including stigma, loss of control, and reliance on other people and medication with parallel co-existing coping strategies. These attempts to manage the condition were characterized by a desire for acceptance and increased awareness of epilepsy, strategies to restore loss of control, and strength derived from supportive relationships. We conclude that there is large scope for psychosocial interventions in healthcare provision for this patient group. The roles of specialist nursing, relationship-centered models, psychotherapy, educational, and self-management programs are highlighted. Copyright © 2017 Elsevier Inc. All rights reserved.

Cosmological Conundrums and Discoveries Since Newton

NASA Astrophysics Data System (ADS)

Topper, David R.

Cosmology is key branch of astronomy, dealing with questions around the structure of the universe. The ancient cosmos - systematically codified by Aristotle, and later given empirical support, especially by Ptolemy - was geocentric, geostatic, and finite. Based on a common sense view of the world being as it appears to our senses, the ancient model prevailed well into the seventeenth century. The subsequent scientific revolution, however, bequeathed to the eighteenth century and after a radically different cosmic model. The radical change came in two stages. First Copernicus in the fifteenth century moved the Sun to Earth's previous place at the center of the universe, an idea adopted by Galileo, Kepler, and a few other key thinkers up to Newton. The second stage, often called the "breaking of the sphere," replaced the sphere of a few thousand stars at the edge of the finite universe with myriad stars extending into an infinite universe, filled with Newton's invisible gravity, and with our Earth being the third planet from the Sun in our solar system somewhere within that Euclidean space. Two planets were added to our solar system (one in the eighteenth and one in the nineteenth centuries), but the overall structure remained essentially as conceived by Newton when he died in 1727. This was the universe Einstein was born into in 1879.

Using a Topological Model in Psychology: Developing Sense and Choice Categories.

PubMed

Mammen, Jens

2016-06-01

A duality of sense categories and choice categories is introduced to map two distinct but co-operating ways in which we as humans are relating actively to the world. We are sensing similarities and differences in our world of objects and persons, but we are also as bodies moving around in this world encountering, selecting, and attaching to objects beyond our sensory interactions and in this way also relating to the individual objects' history. This duality is necessary if we shall understand man as relating to the historical depth of our natural and cultural world, and to understand our cognitions and affections. Our personal affections and attachments, as well as our shared cultural values are centered around objects and persons chosen as reference points and landmarks in our lives, uniting and separating, not to be understood only in terms of sensory selections. The ambition is to bridge the gap between psychology as part of Naturwissenschaft and of Geisteswissenschaft, and at the same time establish a common frame for understanding cognition and affection, and our practical and cultural life (Mammen and Mironenko 2015). The duality of sense and choice categories can be described formally using concepts from modern mathematics, primarily topology, surmounting the reductions rooted in the mechanistic concepts from Renaissance science and mathematics. The formal description is based on 11 short and simple axioms held in ordinary language and visualized with instructive figures. The axioms are bridging psychology and mathematics and not only enriching psychology but also opening for a new interpretation of parts of the foundation of mathematics and logic.

Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing

PubMed Central

Liu, Jiayin; Tang, Zhenmin; Cui, Ying; Wu, Guoxing

2017-01-01

Remote sensing technologies have been widely applied in urban environments’ monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the “salt and pepper” phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC), which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF), which is estimated by Kernel Density Estimation (KDE) with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD) and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive. PMID:28604641

Shape and crystallographic orientation of nanodiamonds for quantum sensing.

PubMed

Ong, S Y; Chipaux, M; Nagl, A; Schirhagl, R

2017-05-03

Nanodiamonds with dimensions down to a few tens of nanometers containing nitrogen-vacancy (NV) color centers have revealed their potential as powerful and versatile quantum sensors with a unique combination of spatial resolution and sensitivity. The NV centers allow transducing physical properties, such as strain, temperature, and electric or magnetic field, to an optical transition that can be detected in the single photon range. For example, this makes it possible to sense a single electron spin or a few nuclear spins by detecting their magnetic resonance. The location and orientation of these defects with respect to the diamond surface play a crucial role in interpreting the data and predicting their sensitivities. Despite its relevance, the geometry of these nanodiamonds has never been thoroughly investigated. Without accurate data, spherical models have been applied to interpret or predict results in the past. With the use of High Resolution Transmission Electron Microscopy (HR-TEM), Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM), we investigated nanodiamonds with an average hydrodynamic diameter of 25 nm (the most common type for quantum sensing) and found a flake-like geometry, with 23.2 nm and 4.5 nm being the average lateral and vertical dimensions. We have also found evidence for a preferred crystallographic orientation of the main facet in the (110) direction. Furthermore, we discuss the consequences of this difference in geometry on diamond-based applications. Shape not only influences the creation efficiency of nitrogen-vacancy centers and their quantum coherence properties (and thus sensing performance), but also the optical properties of the nanodiamonds, their interaction with living cells, and their surface chemistry.

Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing.

PubMed

Liu, Jiayin; Tang, Zhenmin; Cui, Ying; Wu, Guoxing

2017-06-12

Remote sensing technologies have been widely applied in urban environments' monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the "salt and pepper" phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC), which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF), which is estimated by Kernel Density Estimation (KDE) with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD) and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive.

Universal quantum computation with little entanglement.

PubMed

Van den Nest, Maarten

2013-02-08

We show that universal quantum computation can be achieved in the standard pure-state circuit model while the entanglement entropy of every bipartition is small in each step of the computation. The entanglement entropy required for large-scale quantum computation even tends to zero. Moreover we show that the same conclusion applies to many entanglement measures commonly used in the literature. This includes e.g., the geometric measure, localizable entanglement, multipartite concurrence, squashed entanglement, witness-based measures, and more generally any entanglement measure which is continuous in a certain natural sense. These results demonstrate that many entanglement measures are unsuitable tools to assess the power of quantum computers.

How to get the most out of your orthopaedic fellowship: thinking about practice-based learning.

PubMed

Templeman, David

2012-09-01

Practice-based learning and improvement is an important skill set to develop during an orthopaedic trauma fellowship and is 1 of the 6 core competencies stated by the ACGME. The review of clinic cases is best done using a few simple models to develop a structured approach for studying cases. Three common sense and easy-to-use strategies to improve clinical practice are as follows: performing each case three times, studying the 4 quadrants of patient outcomes, and the application of the Pareto 80/20 rule. These principles help to develop a structured approach for analyzing and thinking about practice-based experiences.

Bioinspired active whisker sensor for robotic vibrissal tactile sensing

NASA Astrophysics Data System (ADS)

Ju, Feng; Ling, Shih-Fu

2014-12-01

A whisker transducer (WT) inspired by rat’s vibrissal tactile perception is proposed based on a transduction matrix model characterizing the electro-mechanical transduction process in both forward and backward directions. It is capable of acting as an actuator to sweep the whisker and simultaneously as a sensor to sense the force, motion, and mechanical impedance at whisker tip. Its validity is confirmed by numerical simulation using a finite element model. A prototype is then fabricated and its transduction matrix is determined by parameter identification. The calibrated WT can accurately sense mechanical impedance which is directly related to stiffness, mass and damping. Subsequent vibrissal tactile sensing of sandpaper texture reveals that the real part of mechanical impedance sensed by WT is correlated with sandpaper roughness. Texture discrimination is successfully achieved by inputting the real part to a k-means clustering algorithm. The mechanical impedance sensing ability as well as other features of the WT such as simultaneous-actuation-and-sensing makes it a good solution to robotic tactile sensing.

Dual permeability FEM models for distributed fiber optic sensors development

NASA Astrophysics Data System (ADS)

Aguilar-López, Juan Pablo; Bogaard, Thom

2017-04-01

Fiber optic cables are commonly known for being robust and reliable mediums for transferring information at the speed of light in glass. Billions of kilometers of cable have been installed around the world for internet connection and real time information sharing. Yet, fiber optic cable is not only a mean for information transfer but also a way to sense and measure physical properties of the medium in which is installed. For dike monitoring, it has been used in the past for detecting inner core and foundation temperature changes which allow to estimate water infiltration during high water events. The DOMINO research project, aims to develop a fiber optic based dike monitoring system which allows to directly sense and measure any pore pressure change inside the dike structure. For this purpose, questions like which location, how many sensors, which measuring frequency and which accuracy are required for the sensor development. All these questions may be initially answered with a finite element model which allows to estimate the effects of pore pressure change in different locations along the cross section while having a time dependent estimation of a stability factor. The sensor aims to monitor two main failure mechanisms at the same time; The piping erosion failure mechanism and the macro-stability failure mechanism. Both mechanisms are going to be modeled and assessed in detail with a finite element based dual permeability Darcy-Richards numerical solution. In that manner, it is possible to assess different sensing configurations with different loading scenarios (e.g. High water levels, rainfall events and initial soil moisture and permeability conditions). The results obtained for the different configurations are later evaluated based on an entropy based performance evaluation. The added value of this kind of modelling approach for the sensor development is that it allows to simultaneously model the piping erosion and macro-stability failure mechanisms in a time dependent manner. In that way, the estimated pore pressures may be related to the monitored one and to both failure mechanisms. Furthermore, the approach is intended to be used in a later stage for the real time monitoring of the failure.

Wind Streaks on Earth; Exploration and Interpretation

NASA Astrophysics Data System (ADS)

Cohen-Zada, Aviv Lee; Blumberg, Dan G.; Maman, Shimrit

2015-04-01

Wind streaks, one of the most common aeolian features on planetary surfaces, are observable on the surface of the planets Earth, Mars and Venus. Due to their reflectance properties, wind streaks are distinguishable from their surroundings, and they have thus been widely studied by remote sensing since the early 1970s, particularly on Mars. In imagery, these streaks are interpreted as the presence - or lack thereof - of small loose particles on the surface deposited or eroded by wind. The existence of wind streaks serves as evidence for past or present active aeolian processes. Therefore, wind streaks are thought to represent integrative climate processes. As opposed to the comprehensive and global studies of wind streaks on Mars and Venus, wind streaks on Earth are understudied and poorly investigated, both geomorphologically and by remote sensing. The aim of this study is, thus, to fill the knowledge gap about the wind streaks on Earth by: generating a global map of Earth wind streaks from modern high-resolution remotely sensed imagery; incorporating the streaks in a geographic information system (GIS); and overlaying the GIS layers with boundary layer wind data from general circulation models (GCMs) and data from the ECMWF Reanalysis Interim project. The study defines wind streaks (and thereby distinguishes them from other aeolian features) based not only on their appearance in imagery but more importantly on their surface appearance. This effort is complemented by a focused field investigation to study wind streaks on the ground and from a variety of remotely sensed images (both optical and radar). In this way, we provide a better definition of the physical and geomorphic characteristics of wind streaks and acquire a deeper knowledge of terrestrial wind streaks as a means to better understand global and planetary climate and climate change. In a preliminary study, we detected and mapped over 2,900 wind streaks in the desert regions of Earth distributed in approximately 500 sites. Most terrestrial wind streaks are formed on a relatively young geological surface and are concentrated along the equator (± 30°). They are categorized by the combination of their planform and reflectance; with linear-bright and dark are the most common. A site-specific examination of remote-sensing effects on wind streaks identification has been conducted. The results thus far, indicate that in images with varying spatial and spectral specifications some wind streaks are actually composed of other aeolian bedforms, especially dunes. Specific regions of the Earth were then compared qualitatively to surface wind data extracted from a general circulation model. Understanding the mechanism and spatial and temporal distribution of wind streak formation is important not only for understanding surface modifications in the geomorphological context but also for shedding light on past and present climatic processes and atmospheric circulation on Earth. This study yields an explanation for wind streaks as a geomorphological feature. Moreover, it is in this planet-wide geomorphological research ability to lay down the foundations for comparative planetary research.

Remote Sensing Sensors and Applications in Environmental Resources Mapping and Modelling

PubMed Central

Melesse, Assefa M.; Weng, Qihao; S.Thenkabail, Prasad; Senay, Gabriel B.

2007-01-01

The history of remote sensing and development of different sensors for environmental and natural resources mapping and data acquisition is reviewed and reported. Application examples in urban studies, hydrological modeling such as land-cover and floodplain mapping, fractional vegetation cover and impervious surface area mapping, surface energy flux and micro-topography correlation studies is discussed. The review also discusses the use of remotely sensed-based rainfall and potential evapotranspiration for estimating crop water requirement satisfaction index and hence provides early warning information for growers. The review is not an exhaustive application of the remote sensing techniques rather a summary of some important applications in environmental studies and modeling. PMID:28903290

A Quiet Voice

ERIC Educational Resources Information Center

Schrader, Teri

2009-01-01

The Common Principles have been at the very center of the author's professional practice. When she first read Ted Sizer's writing and learned about the Coalition of Essential Schools, she felt as though he was talking directly to her. Not only did every word of the then nine Common Principles make sense, but after reading Sizer's work, her own…

Discovering Common Ground: How Future Search Conferences Bring People Together To Achieve Breakthrough Innovation, Empowerment, Shared Vision, and Collaborative Action.

ERIC Educational Resources Information Center

Weisbord, Marvin R.; And Others

This book contains 35 papers about planning and holding future search conferences, as well as their benefits and likely future directions. The following papers are included: "Applied Common Sense" (Weisbord); "Inventing the Search Conference" (Weisbord); "Building Collaborative Communities" (Schindler-Rainman,…

Integration of DAS (distributed acoustic sensing) vertical seismic profile and geostatistically modeled lithology data to characterize an enhanced geothermal system.

NASA Astrophysics Data System (ADS)

Cronin, S. P.; Trainor Guitton, W.; Team, P.; Pare, A.; Jreij, S.; Powers, H.

2017-12-01

In March 2016, a 4-week field data acquisition took place at Brady's Natural Lab (BNL), an enhanced geothermal system (EGS) in Fallan, NV. During these 4 weeks, a vibe truck executed 6,633 sweeps, recorded by nodal seismometers, horizontal distributed acoustic sensing (DAS) cable, and 400 meters of vertical DAS cable. DAS provides lower signal to noise ratio than traditional geophones but better spatial resolution. The analysis of DAS VSP included Fourier transform, and filtering to remove all up-going energy. Thus, allowing for accurate first arrival picking. We present an example of the Gradual Deformation Method (GDM) using DAS VSP and lithological data to produce a distribution of valid velocity models of BNL. GDM generates continuous perturbations of prior model realizations seeking the best match to the data (i.e. minimize the misfit). Prior model realizations honoring the lithological data were created using sequential Gaussian simulation, a commonly used noniterative geostatistical method. Unlike least-squares-based methods of inversion, GDM readily incorporates a priori information, such as a variogram calculated from well-based lithology information. Additionally, by producing a distribution of models, as opposed to one optimal model, GDM allows for uncertainty quantification. This project aims at assessing the integrated technologies ability to monitor changes in the water table (possibly to one meter resolution) by exploiting the dependence of seismic wave velocities on water saturation of the subsurface. This project, which was funded in part by the National Science Foundation, is a part of the PoroTomo project, funded by a grant from the U.S. Department of Energy.

Modeling Diurnal and Seasonal 3D Light Profiles in Amazon Forests

NASA Astrophysics Data System (ADS)

Morton, D. C.; Rubio, J.; Gastellu-Etchegorry, J.; Cook, B. D.; Hunter, M. O.; Yin, T.; Nagol, J. R.; Keller, M. M.

2013-12-01

The complex horizontal and vertical structure in tropical forests generates a diversity of light environments for canopy and understory trees. These 3D light profiles are dynamic on diurnal and seasonal time scales based on changes in solar illumination and the fraction of diffuse light. Understanding this variability is critical for improving ecosystem models and interpreting optical and LiDAR remote sensing data from tropical forests. Here, we initialized the Discrete Anisotropic Radiative Transfer (DART) model using dense airborne LiDAR data (>20 returns m2) from three forest sites in the central and eastern Amazon. Forest scenes derived from airborne LiDAR data were tested using modeled and observed large-footprint LiDAR data from the ICESat-GLAS sensor. Next, diurnal and seasonal profiles of photosynthetically active radiation (PAR) for each forest site were simulated under clear sky and cloudy conditions using DART. Incident PAR was summarized for canopy, understory, and ground levels. Our study illustrates the importance of realistic canopy models for accurate representation of LiDAR and optical radiative transfer. In particular, canopy rugosity and ground topography information from airborne LiDAR data provided critical 3D information that cannot be recreated using stem maps and allometric relationships for crown dimensions. The spatial arrangement of canopy trees altered PAR availability, even for dominant individuals, compared to downwelling measurements from nearby eddy flux towers. Pseudo-realistic branch and leaf architecture was also essential for recreating multiple scattering within canopies at near-infrared wavelengths commonly used for LiDAR remote sensing and quantifying PAR attenuation from shading within and between canopies. These findings point to the need for more spatial information on forest structure to improve the representation of light availability in models of tropical forest productivity.

IPRT polarized radiative transfer model intercomparison project - Three-dimensional test cases (phase B)

NASA Astrophysics Data System (ADS)

Emde, Claudia; Barlakas, Vasileios; Cornet, Céline; Evans, Frank; Wang, Zhen; Labonotte, Laurent C.; Macke, Andreas; Mayer, Bernhard; Wendisch, Manfred

2018-04-01

Initially unpolarized solar radiation becomes polarized by scattering in the Earth's atmosphere. In particular molecular scattering (Rayleigh scattering) polarizes electromagnetic radiation, but also scattering of radiation at aerosols, cloud droplets (Mie scattering) and ice crystals polarizes. Each atmospheric constituent produces a characteristic polarization signal, thus spectro-polarimetric measurements are frequently employed for remote sensing of aerosol and cloud properties. Retrieval algorithms require efficient radiative transfer models. Usually, these apply the plane-parallel approximation (PPA), assuming that the atmosphere consists of horizontally homogeneous layers. This allows to solve the vector radiative transfer equation (VRTE) efficiently. For remote sensing applications, the radiance is considered constant over the instantaneous field-of-view of the instrument and each sensor element is treated independently in plane-parallel approximation, neglecting horizontal radiation transport between adjacent pixels (Independent Pixel Approximation, IPA). In order to estimate the errors due to the IPA approximation, three-dimensional (3D) vector radiative transfer models are required. So far, only a few such models exist. Therefore, the International Polarized Radiative Transfer (IPRT) working group of the International Radiation Commission (IRC) has initiated a model intercomparison project in order to provide benchmark results for polarized radiative transfer. The group has already performed an intercomparison for one-dimensional (1D) multi-layer test cases [phase A, 1]. This paper presents the continuation of the intercomparison project (phase B) for 2D and 3D test cases: a step cloud, a cubic cloud, and a more realistic scenario including a 3D cloud field generated by a Large Eddy Simulation (LES) model and typical background aerosols. The commonly established benchmark results for 3D polarized radiative transfer are available at the IPRT website (http://www.meteo.physik.uni-muenchen.de/ iprt).

The feasibility of using a universal Random Forest model to map tree height across different locations and vegetation types

NASA Astrophysics Data System (ADS)

Su, Y.; Guo, Q.; Jin, S.; Gao, S.; Hu, T.; Liu, J.; Xue, B. L.

2017-12-01

Tree height is an important forest structure parameter for understanding forest ecosystem and improving the accuracy of global carbon stock quantification. Light detection and ranging (LiDAR) can provide accurate tree height measurements, but its use in large-scale tree height mapping is limited by the spatial availability. Random Forest (RF) has been one of the most commonly used algorithms for mapping large-scale tree height through the fusion of LiDAR and other remotely sensed datasets. However, how the variances in vegetation types, geolocations and spatial scales of different study sites influence the RF results is still a question that needs to be addressed. In this study, we selected 16 study sites across four vegetation types in United States (U.S.) fully covered by airborne LiDAR data, and the area of each site was 100 km2. The LiDAR-derived canopy height models (CHMs) were used as the ground truth to train the RF algorithm to predict canopy height from other remotely sensed variables, such as Landsat TM imagery, terrain information and climate surfaces. To address the abovementioned question, 22 models were run under different combinations of vegetation types, geolocations and spatial scales. The results show that the RF model trained at one specific location or vegetation type cannot be used to predict tree height in other locations or vegetation types. However, by training the RF model using samples from all locations and vegetation types, a universal model can be achieved for predicting canopy height across different locations and vegetation types. Moreover, the number of training samples and the targeted spatial resolution of the canopy height product have noticeable influence on the RF prediction accuracy.

Zonal wavefront sensing using a grating array printed on a polyester film

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pathak, Biswajit; Boruah, Bosanta R., E-mail: brboruah@iitg.ernet.in; Kumar, Suraj

2015-12-15

In this paper, we describe the development of a zonal wavefront sensor that comprises an array of binary diffraction gratings realized on a transparent sheet (i.e., polyester film) followed by a focusing lens and a camera. The sensor works in a manner similar to that of a Shack-Hartmann wavefront sensor. The fabrication of the array of gratings is immune to certain issues associated with the fabrication of the lenslet array which is commonly used in zonal wavefront sensing. Besides the sensing method offers several important advantages such as flexible dynamic range, easy configurability, and option to enhance the sensing framemore » rate. Here, we have demonstrated the working of the proposed sensor using a proof-of-principle experimental arrangement.« less

Developing a Learning Progression for Number Sense Based on the Rule Space Model in China

ERIC Educational Resources Information Center

Chen, Fu; Yan, Yue; Xin, Tao

2017-01-01

The current study focuses on developing the learning progression of number sense for primary school students, and it applies a cognitive diagnostic model, the rule space model, to data analysis. The rule space model analysis firstly extracted nine cognitive attributes and their hierarchy model from the analysis of previous research and the…

The role of grief symptoms and a sense of injustice in the pathways to post-traumatic stress symptoms in post-conflict Timor-Leste.

PubMed

Tay, A K; Rees, S; Steel, Z; Liddell, B; Nickerson, A; Tam, N; Silove, D

2017-08-01

Grief symptoms and a sense of injustice may be interrelated responses amongst persons exposed to mass conflict and both reactions may contribute to post-traumatic stress disorder (PTSD) symptoms. As yet, however, there is a dearth of data examining these relationships. Our study examined the contributions of grief and a sense of injustice to a model of PTSD symptoms that included the established determinants of trauma events, ongoing adversity and severe psychological distress. The study involved a large population sample (n = 2964, response rate: 82.4%) surveyed in post-conflict Timor-Leste. The survey sites included an urban administrative area (suco) in Dili, the capital of Timor-Leste and a rural village located an hour's drive away. Culturally adapted measures were applied to assess conflict related traumatic events (TEs), ongoing adversity, persisting preoccupations with injustice, symptoms of grief, psychological distress (including depressive symptoms) and PTSD symptoms. We tested a series of structural equation models, the final comprehensive model, which included indices of grief symptoms and injustice, producing a good fit. Locating grief symptoms as the endpoint of the model produced a non-converging model. In the final model, strong associations were evident between grief and injustice (β = 0.34, s.e. = 0.02, p < 0.01) and grief and PTSD symptoms (β = 0.14, s.e. = 0.02, p < 0.01). The sense of injustice exerted a considerable effect on PTSD symptoms (β = 0.13, s.e. = 0.03, p < 0.01). In addition, multiple indirect paths were evident, most involving grief and a sense of injustice, attesting to the complex inter-relationship of these factors in contributing to PTSD symptoms. Our findings support an expanded model of PTSD symptoms relevant to post-conflict populations, in which grief symptoms and a sense of injustice play pivotal roles. The model supports the importance of a focus on loss, grief and a sense of injustice in conducting trauma-focused psychotherapies for PTSD amongst populations exposed to mass conflict and violence. Further research is needed to identify the precise mechanisms whereby grief symptoms and the sense of injustice impact on PTSD symptoms.

Role of spatial averaging in multicellular gradient sensing.

PubMed

Smith, Tyler; Fancher, Sean; Levchenko, Andre; Nemenman, Ilya; Mugler, Andrew

2016-05-20

Gradient sensing underlies important biological processes including morphogenesis, polarization, and cell migration. The precision of gradient sensing increases with the length of a detector (a cell or group of cells) in the gradient direction, since a longer detector spans a larger range of concentration values. Intuition from studies of concentration sensing suggests that precision should also increase with detector length in the direction transverse to the gradient, since then spatial averaging should reduce the noise. However, here we show that, unlike for concentration sensing, the precision of gradient sensing decreases with transverse length for the simplest gradient sensing model, local excitation-global inhibition. The reason is that gradient sensing ultimately relies on a subtraction of measured concentration values. While spatial averaging indeed reduces the noise in these measurements, which increases precision, it also reduces the covariance between the measurements, which results in the net decrease in precision. We demonstrate how a recently introduced gradient sensing mechanism, regional excitation-global inhibition (REGI), overcomes this effect and recovers the benefit of transverse averaging. Using a REGI-based model, we compute the optimal two- and three-dimensional detector shapes, and argue that they are consistent with the shapes of naturally occurring gradient-sensing cell populations.

Role of spatial averaging in multicellular gradient sensing

NASA Astrophysics Data System (ADS)

Smith, Tyler; Fancher, Sean; Levchenko, Andre; Nemenman, Ilya; Mugler, Andrew

2016-06-01

Gradient sensing underlies important biological processes including morphogenesis, polarization, and cell migration. The precision of gradient sensing increases with the length of a detector (a cell or group of cells) in the gradient direction, since a longer detector spans a larger range of concentration values. Intuition from studies of concentration sensing suggests that precision should also increase with detector length in the direction transverse to the gradient, since then spatial averaging should reduce the noise. However, here we show that, unlike for concentration sensing, the precision of gradient sensing decreases with transverse length for the simplest gradient sensing model, local excitation-global inhibition. The reason is that gradient sensing ultimately relies on a subtraction of measured concentration values. While spatial averaging indeed reduces the noise in these measurements, which increases precision, it also reduces the covariance between the measurements, which results in the net decrease in precision. We demonstrate how a recently introduced gradient sensing mechanism, regional excitation-global inhibition (REGI), overcomes this effect and recovers the benefit of transverse averaging. Using a REGI-based model, we compute the optimal two- and three-dimensional detector shapes, and argue that they are consistent with the shapes of naturally occurring gradient-sensing cell populations.

Applying narrowband remote-sensing reflectance models to wideband data.

PubMed

Lee, Zhongping

2009-06-10

Remote sensing of coastal and inland waters requires sensors to have a high spatial resolution to cover the spatial variation of biogeochemical properties in fine scales. High spatial-resolution sensors, however, are usually equipped with spectral bands that are wide in bandwidth (50 nm or wider). In this study, based on numerical simulations of hyperspectral remote-sensing reflectance of optically-deep waters, and using Landsat band specifics as an example, the impact of a wide spectral channel on remote sensing is analyzed. It is found that simple adoption of a narrowband model may result in >20% underestimation in calculated remote-sensing reflectance, and inversely may result in >20% overestimation in inverted absorption coefficients even under perfect conditions, although smaller (approximately 5%) uncertainties are found for higher absorbing waters. These results provide a cautious note, but also a justification for turbid coastal waters, on applying narrowband models to wideband data.

Advancing the citizen scientist's contributions to documenting and understanding natural hazards: a proof of concept for linking crowdsourced and remotely sensed data on landslide hazards in El Salvador

NASA Astrophysics Data System (ADS)

Anderson, E. R.; Griffin, R.; Markert, K. N.

2017-12-01

Scientists, practitioners, policymakers, and citizen groups, share a role in ensuring "that all sectors have access to, understand and can use scientific information for better informed decision-making" (Sendai Framework 2015-2030). When it comes to understanding hazards and exposure, inventories on disaster events are often limited. Thus, there are many opportunities for citizen scientists to engage in improving the collective understanding—and ultimately reduction—of disaster risk. Landslides are very difficult to forecast on spatial and temporal scales meaningful for early warning and evacuation. Heuristic hazard mapping methods are very common in regional hazard zonation and rely on expert knowledge of previous events and local conditions, but they often lack a temporal component. As new data analysis packages are becoming more open and accessible, probabilistic approaches that consider high resolution spatial and temporal dimensions are becoming more common, but this is only possible when rich inventories of landslide events exist. The work presented offers a proof of concept on incorporating crowd-sourced data to improve landslide hazard model performance. Starting with a national inventory of 90 catalogued landslides in El Salvador for a study period of 1998 to 2011, we simulate the addition of over 600 additional crowd-sourced landslide events that would have been identified through human interpretation of high resolution imagery in the Google Earth time slider feature. There is a noticeable improvement in performance statistics between static heuristic hazard models and probabilistic models that incorporate the events identified by the "crowd." Such a dynamic incorporation of crowd-sourced data on hazard events is not so far-fetched. Given the engagement of "local observers" in El Salvador who augment in situ hydro-meteorological measurements, the growing access to Earth observation data to the lay person, and immense interest behind connecting citizen scientists to remote sensing data through hackathons such as the NASA Space Apps Challenges, we envision a much more dynamic, collective understanding of landslide hazards. Here we present a better scenario of what we could have known had data from the crowd been incorporated into probabilistic hazard models on a regular basis.

WaterSense Program: Methodology for National Water Savings Analysis Model Indoor Residential Water Use

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whitehead, Camilla Dunham; McNeil, Michael; Dunham_Whitehead, Camilla

2008-02-28

The U.S. Environmental Protection Agency (EPA) influences the market for plumbing fixtures and fittings by encouraging consumers to purchase products that carry the WaterSense label, which certifies those products as performing at low flow rates compared to unlabeled fixtures and fittings. As consumers decide to purchase water-efficient products, water consumption will decline nationwide. Decreased water consumption should prolong the operating life of water and wastewater treatment facilities.This report describes the method used to calculate national water savings attributable to EPA?s WaterSense program. A Microsoft Excel spreadsheet model, the National Water Savings (NWS) analysis model, accompanies this methodology report. Version 1.0more » of the NWS model evaluates indoor residential water consumption. Two additional documents, a Users? Guide to the spreadsheet model and an Impacts Report, accompany the NWS model and this methodology document. Altogether, these four documents represent Phase One of this project. The Users? Guide leads policy makers through the spreadsheet options available for projecting the water savings that result from various policy scenarios. The Impacts Report shows national water savings that will result from differing degrees of market saturation of high-efficiency water-using products.This detailed methodology report describes the NWS analysis model, which examines the effects of WaterSense by tracking the shipments of products that WaterSense has designated as water-efficient. The model estimates market penetration of products that carry the WaterSense label. Market penetration is calculated for both existing and new construction. The NWS model estimates savings based on an accounting analysis of water-using products and of building stock. Estimates of future national water savings will help policy makers further direct the focus of WaterSense and calculate stakeholder impacts from the program.Calculating the total gallons of water the WaterSense program saves nationwide involves integrating two components, or modules, of the NWS model. Module 1 calculates the baseline national water consumption of typical fixtures, fittings, and appliances prior to the program (as described in Section 2.0 of this report). Module 2 develops trends in efficiency for water-using products both in the business-as-usual case and as a result of the program (Section 3.0). The NWS model combines the two modules to calculate total gallons saved by the WaterSense program (Section 4.0). Figure 1 illustrates the modules and the process involved in modeling for the NWS model analysis.The output of the NWS model provides the base case for each end use, as well as a prediction of total residential indoor water consumption during the next two decades. Based on the calculations described in Section 4.0, we can project a timeline of water savings attributable to the WaterSense program. The savings increase each year as the program results in the installation of greater numbers of efficient products, which come to compose more and more of the product stock in households throughout the United States.« less

Modeling the Hydrological Regime of Turkana Lake (Kenya, Ethiopia) by Combining Spatially Distributed Hydrological Modeling and Remote Sensing Datasets

NASA Astrophysics Data System (ADS)

Anghileri, D.; Kaelin, A.; Peleg, N.; Fatichi, S.; Molnar, P.; Roques, C.; Longuevergne, L.; Burlando, P.

2017-12-01

Hydrological modeling in poorly gauged basins can benefit from the use of remote sensing datasets although there are challenges associated with the mismatch in spatial and temporal scales between catchment scale hydrological models and remote sensing products. We model the hydrological processes and long-term water budget of the Lake Turkana catchment, a transboundary basin between Kenya and Ethiopia, by integrating several remote sensing products into a spatially distributed and physically explicit model, Topkapi-ETH. Lake Turkana is the world largest desert lake draining a catchment of 145'500 km2. It has three main contributing rivers: the Omo river, which contributes most of the annual lake inflow, the Turkwel river, and the Kerio rivers, which contribute the remaining part. The lake levels have shown great variations in the last decades due to long-term climate fluctuations and the regulation of three reservoirs, Gibe I, II, and III, which significantly alter the hydrological seasonality. Another large reservoir is planned and may be built in the next decade, generating concerns about the fate of Lake Turkana in the long run because of this additional anthropogenic pressure and increasing evaporation driven by climate change. We consider different remote sensing datasets, i.e., TRMM-V7 for precipitation, MERRA-2 for temperature, as inputs to the spatially distributed hydrological model. We validate the simulation results with other remote sensing datasets, i.e., GRACE for total water storage anomalies, GLDAS-NOAH for soil moisture, ERA-Interim/Land for surface runoff, and TOPEX/Poseidon for satellite altimetry data. Results highlight how different remote sensing products can be integrated into a hydrological modeling framework accounting for their relative uncertainties. We also carried out simulations with the artificial reservoirs planned in the north part of the catchment and without any reservoirs, to assess their impacts on the catchment hydrological regime and the Lake Turkana level variability.

Modeling and Validation of Environmental Suitability for Schistosomiasis Transmission Using Remote Sensing

PubMed Central

Walz, Yvonne; Wegmann, Martin; Dech, Stefan; Vounatsou, Penelope; Poda, Jean-Noël; N'Goran, Eliézer K.; Utzinger, Jürg; Raso, Giovanna

2015-01-01

Background Schistosomiasis is the most widespread water-based disease in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and human water contact patterns. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. We investigated the potential of remote sensing to characterize habitat conditions of parasite and intermediate host snails and discuss the relevance for public health. Methodology We employed high-resolution remote sensing data, environmental field measurements, and ecological data to model environmental suitability for schistosomiasis-related parasite and snail species. The model was developed for Burkina Faso using a habitat suitability index (HSI). The plausibility of remote sensing habitat variables was validated using field measurements. The established model was transferred to different ecological settings in Côte d’Ivoire and validated against readily available survey data from school-aged children. Principal Findings Environmental suitability for schistosomiasis transmission was spatially delineated and quantified by seven habitat variables derived from remote sensing data. The strengths and weaknesses highlighted by the plausibility analysis showed that temporal dynamic water and vegetation measures were particularly useful to model parasite and snail habitat suitability, whereas the measurement of water surface temperature and topographic variables did not perform appropriately. The transferability of the model showed significant relations between the HSI and infection prevalence in study sites of Côte d’Ivoire. Conclusions/Significance A predictive map of environmental suitability for schistosomiasis transmission can support measures to gain and sustain control. This is particularly relevant as emphasis is shifting from morbidity control to interrupting transmission. Further validation of our mechanistic model needs to be complemented by field data of parasite- and snail-related fitness. Our model provides a useful tool to monitor the development of new hotspots of potential schistosomiasis transmission based on regularly updated remote sensing data. PMID:26587839

Modeling and Validation of Environmental Suitability for Schistosomiasis Transmission Using Remote Sensing.

PubMed

Walz, Yvonne; Wegmann, Martin; Dech, Stefan; Vounatsou, Penelope; Poda, Jean-Noël; N'Goran, Eliézer K; Utzinger, Jürg; Raso, Giovanna

2015-11-01

Schistosomiasis is the most widespread water-based disease in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and human water contact patterns. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. We investigated the potential of remote sensing to characterize habitat conditions of parasite and intermediate host snails and discuss the relevance for public health. We employed high-resolution remote sensing data, environmental field measurements, and ecological data to model environmental suitability for schistosomiasis-related parasite and snail species. The model was developed for Burkina Faso using a habitat suitability index (HSI). The plausibility of remote sensing habitat variables was validated using field measurements. The established model was transferred to different ecological settings in Côte d'Ivoire and validated against readily available survey data from school-aged children. Environmental suitability for schistosomiasis transmission was spatially delineated and quantified by seven habitat variables derived from remote sensing data. The strengths and weaknesses highlighted by the plausibility analysis showed that temporal dynamic water and vegetation measures were particularly useful to model parasite and snail habitat suitability, whereas the measurement of water surface temperature and topographic variables did not perform appropriately. The transferability of the model showed significant relations between the HSI and infection prevalence in study sites of Côte d'Ivoire. A predictive map of environmental suitability for schistosomiasis transmission can support measures to gain and sustain control. This is particularly relevant as emphasis is shifting from morbidity control to interrupting transmission. Further validation of our mechanistic model needs to be complemented by field data of parasite- and snail-related fitness. Our model provides a useful tool to monitor the development of new hotspots of potential schistosomiasis transmission based on regularly updated remote sensing data.

Carbon nanotubes and nanowires for biological sensing

NASA Technical Reports Server (NTRS)

Li, Jun; Ng, Hou Tee; Chen, Hua

2005-01-01

This chapter reviews the recent development in biological sensing using nanotechnologies based on carbon nanotubes and various nanowires. These 1D materials have shown unique properties that are efficient in interacting with biomolecules of similar dimensions, i.e., on a nanometer scale. Various aspects including synthesis, materials properties, device fabrication, biofunctionalization, and biological sensing applications of such materials are reviewed. The potential of such integrated nanobiosensors in providing ultrahigh sensitivity, fast response, and high-degree multiplex detection, yet with minimum sample requirements is demonstrated. This chapter is intended to provide comprehensive updated information for people from a variety of backgrounds but with common interests in the fast-moving interdisciplinary field of nanobiotechnology.

Assimilating Leaf Area Index Estimates from Remote Sensing into the Simulations of a Cropping Systems Model

USDA-ARS?s Scientific Manuscript database

Spatial extrapolation of cropping systems models for regional crop growth and water use assessment and farm-level precision management has been limited by the vast model input requirements and the model sensitivity to parameter uncertainty. Remote sensing has been proposed as a viable source of spat...

A comparison of operational remote sensing-based models for estimating crop evapotranspiration

USDA-ARS?s Scientific Manuscript database

The integration of remotely sensed data into models of actual evapotranspiration has allowed for the estimation of water consumption across agricultural regions. Two modeling approaches have been successfully applied. The first approach computes a surface energy balance using the radiometric surface...

Feasibility of remote sensing for detecting thermal pollution. Part 1: Feasibility study. Part 2: Implementation plan. [coastal ecology

NASA Technical Reports Server (NTRS)

Veziroglu, T. N.; Lee, S. S.

1973-01-01

A feasibility study for the development of a three-dimensional generalized, predictive, analytical model involving remote sensing, in-situ measurements, and an active system to remotely measure turbidity is presented. An implementation plan for the development of the three-dimensional model and for the application of remote sensing of temperature and turbidity measurements is outlined.

Modeling Behavioral Experiment Interaction and Environmental Stimuli for a Synthetic C. elegans.

PubMed

Mujika, Andoni; Leškovský, Peter; Álvarez, Roberto; Otaduy, Miguel A; Epelde, Gorka

2017-01-01

This paper focusses on the simulation of the neural network of the Caenorhabditis elegans living organism, and more specifically in the modeling of the stimuli applied within behavioral experiments and the stimuli that is generated in the interaction of the C. elegans with the environment. To the best of our knowledge, all efforts regarding stimuli modeling for the C. elegans are focused on a single type of stimulus, which is usually tested with a limited subnetwork of the C. elegans neural system. In this paper, we follow a different approach where we model a wide-range of different stimuli, with more flexible neural network configurations and simulations in mind. Moreover, we focus on the stimuli sensation by different types of sensory organs or various sensory principles of the neurons. As part of this work, most common stimuli involved in behavioral assays have been modeled. It includes models for mechanical, thermal, chemical, electrical and light stimuli, and for proprioception-related self-sensed information exchange with the neural network. The developed models have been implemented and tested with the hardware-based Si elegans simulation platform.

Energy risk in the arbitrage pricing model: an empirical and theoretical study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bremer, M.A.

1986-01-01

This dissertation empirically explores the Arbitrage Pricing Theory in the context of energy risk for securities over the 1960s, 1970s, and early 1980s. Starting from a general multifactor pricing model, the paper develops a two factor model based on a market-like factor and an energy factor. This model is then tested on portfolios of securities grouped according to industrial classification using several econometric techniques designed to overcome some of the more serious estimation problems common to these models. The paper concludes that energy risk is priced in the 1970s and possibly even in the 1960s. Energy risk is found tomore » be priced in the sense that investors who hold assets subjected to energy risk are paid for this risk. The classic version of the Capital Asset Pricing Model which posits the market as the single priced factor is rejected in favor of the Arbitrage Pricing Theory or multi-beta versions of the Capital Asset Pricing Model. The study introduces some original econometric methodology to carry out empirical tests.« less

Modeling Behavioral Experiment Interaction and Environmental Stimuli for a Synthetic C. elegans

PubMed Central

Mujika, Andoni; Leškovský, Peter; Álvarez, Roberto; Otaduy, Miguel A.; Epelde, Gorka

2017-01-01

This paper focusses on the simulation of the neural network of the Caenorhabditis elegans living organism, and more specifically in the modeling of the stimuli applied within behavioral experiments and the stimuli that is generated in the interaction of the C. elegans with the environment. To the best of our knowledge, all efforts regarding stimuli modeling for the C. elegansare focused on a single type of stimulus, which is usually tested with a limited subnetwork of the C. elegansneural system. In this paper, we follow a different approach where we model a wide-range of different stimuli, with more flexible neural network configurations and simulations in mind. Moreover, we focus on the stimuli sensation by different types of sensory organs or various sensory principles of the neurons. As part of this work, most common stimuli involved in behavioral assays have been modeled. It includes models for mechanical, thermal, chemical, electrical and light stimuli, and for proprioception-related self-sensed information exchange with the neural network. The developed models have been implemented and tested with the hardware-based Si elegans simulation platform. PMID:29276485

A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States.

PubMed

Beckerman, Bernardo S; Jerrett, Michael; Serre, Marc; Martin, Randall V; Lee, Seung-Jae; van Donkelaar, Aaron; Ross, Zev; Su, Jason; Burnett, Richard T

2013-07-02

Airborne fine particulate matter exhibits spatiotemporal variability at multiple scales, which presents challenges to estimating exposures for health effects assessment. Here we created a model to predict ambient particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) across the contiguous United States to be applied to health effects modeling. We developed a hybrid approach combining a land use regression model (LUR) selected with a machine learning method, and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals. The PM2.5 data set included 104,172 monthly observations at 1464 monitoring locations with approximately 10% of locations reserved for cross-validation. LUR models were based on remote sensing estimates of PM2.5, land use and traffic indicators. Normalized cross-validated R(2) values for LUR were 0.63 and 0.11 with and without remote sensing, respectively, suggesting remote sensing is a strong predictor of ground-level concentrations. In the models including the BME interpolation of the residuals, cross-validated R(2) were 0.79 for both configurations; the model without remotely sensed data described more fine-scale variation than the model including remote sensing. Our results suggest that our modeling framework can predict ground-level concentrations of PM2.5 at multiple scales over the contiguous U.S.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Karssenberg, D.; Wanders, N.; de Roo, A.; de Jong, S.; Bierkens, M. F.

2013-12-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system that is not directly linked to discharge, in particular the unsaturated zone, remains uncalibrated, or might be modified unrealistically. Soil moisture observations from satellites have the potential to fill this gap, as these provide the closest thing to a direct measurement of the state of the unsaturated zone, and thus are potentially useful in calibrating unsaturated zone model parameters. This is expected to result in a better identification of the complete hydrological system, potentially leading to improved forecasts of the hydrograph as well. Here we evaluate this added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: 1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? 2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to approaches that calibrate only with discharge, such that this leads to improved forecasts of soil moisture content and discharge as well? To answer these questions we use a dual state and parameter ensemble Kalman filter to calibrate the hydrological model LISFLOOD for the Upper Danube area. Calibration is done with discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS and ASCAT. Four scenarios are studied: no calibration (expert knowledge), calibration on discharge, calibration on remote sensing data (three satellites) and calibration on both discharge and remote sensing data. Using a split-sample approach, the model is calibrated for a period of 2 years and validated for the calibrated model parameters on a validation period of 10 years. Results show that calibration with discharge data improves the estimation of groundwater parameters (e.g., groundwater reservoir constant) and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate calibration of parameters related to land surface process (e.g., the saturated conductivity of the soil), which is not possible when calibrating on discharge alone. For the upstream area up to 40000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30 % in the RMSE for discharge simulations, compared to calibration on discharge alone. For discharge in the downstream area, the model performance due to assimilation of remotely sensed soil moisture is not increased or slightly decreased, most probably due to the longer relative importance of the routing and contribution of groundwater in downstream areas. When microwave soil moisture is used for calibration the RMSE of soil moisture simulations decreases from 0.072 m3m-3 to 0.062 m3m-3. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models leading to a better simulation of soil moisture content throughout and a better simulation of discharge in upstream areas, particularly if discharge observations are sparse.

Introduction to This Special Issue on Geostatistics and Geospatial Techniques in Remote Sensing

NASA Technical Reports Server (NTRS)

Atkinson, Peter; Quattrochi, Dale A.; Goodman, H. Michael (Technical Monitor)

2000-01-01

The germination of this special Computers & Geosciences (C&G) issue began at the Royal Geographical Society (with the Institute of British Geographers) (RGS-IBG) annual meeting in January 1997 held at the University of Exeter, UK. The snow and cold of the English winter were tempered greatly by warm and cordial discussion of how to stimulate and enhance cooperation on geostatistical and geospatial research in remote sensing 'across the big pond' between UK and US researchers. It was decided that one way forward would be to hold parallel sessions in 1998 on geostatistical and geospatial research in remote sensing at appropriate venues in both the UK and the US. Selected papers given at these sessions would be published as special issues of C&G on the UK side and Photogrammetric Engineering and Remote Sensing (PE&RS) on the US side. These issues would highlight the commonality in research on geostatistical and geospatial research in remote sensing on both sides of the Atlantic Ocean. As a consequence, a session on "Geostatistics and Geospatial Techniques for Remote Sensing of Land Surface Processes" was held at the RGS-IBG annual meeting in Guildford, Surrey, UK in January 1998, organized by the Modeling and Advanced Techniques Special Interest Group (MAT SIG) of the Remote Sensing Society (RSS). A similar session was held at the Association of American Geographers (AAG) annual meeting in Boston, Massachusetts in March 1998, sponsored by the AAG's Remote Sensing Specialty Group (RSSG). The 10 papers that make up this issue of C&G, comprise 7 papers from the UK and 3 papers from the LIS. We are both co-editors of each of the journal special issues, with the lead editor of each journal issue being from their respective side of the Atlantic. The special issue of PE&RS (vol. 65) that constitutes the other half of this co-edited journal series was published in early 1999, comprising 6 papers by US authors. We are indebted to the International Association for Mathematical Geology for allowing us to use C&G as a vehicle to convey how geostatistics and geospatial techniques can be used to analyze remote sensing and other types of spatial data. We see this special issue of C&G. and its complementary issue of PE&RS. as a testament to the vitality and interest in the application of geostatistical and geospatial techniques in remote sensing. We also see these special journal issues as the beginning of a fruitful. and hopefully long-term relationship, between American and British geographers and other researchers interested in geostatistical and geospatial techniques applied to remote sensing and other spatial data.

A Sense of Place: Integrating Environmental Psychology into Marine Socio-Ecological Models

NASA Astrophysics Data System (ADS)

van Putten, I. E.; Fleming, A.; Fulton, E.; Plaganyi-Lloyd, E.

2016-02-01

Sense of place is a concept that is increasingly applied in different social research contexts where it can act as a bridge between disciplines that might otherwise work in parallel. A sense of place is a well established and flexible concept that has been empirically measured using different survey methods. The psychological principals and theories that underpin sense of place have been inextricably linked to the quality of ecological systems and the impact on development of the system, and vice versa. Ecological models and scenario analyses play an important role in characterising, assessing and predicting the potential impacts of alternative developments and other changes affecting ecological systems. To improve the predictive accuracy of ecological models, human drivers, interactions, and uses have been dynamically incorporated, for instance, through management strategy evaluation applied to marine ecosystem models. However, to date no socio-ecological models (whether terrestrial or marine) have been developed that incorporate a dynamic feedback between ecosystem characteristics and peoples' sense of place. These models thus essentially ignore the influence of environmental psychology on the way people use and interact with ecosystems. We develop a proof of concept and provide a mathematical basis for a Sense of Place Index (SoPI) that allows the quantitative integration of environmental psychology into socio-ecological models. Incorporating dynamic feedback between the SoPI for different resource user groups and the ecological system improves the accuracy and precision of predictions regarding future resource use as well as, ultimately, the potential state of the resource to be developed.

A Novel Approach for Forecasting Crop Production and Yield Using Remotely Sensed Satellite Images

NASA Astrophysics Data System (ADS)

Singh, R. K.; Budde, M. E.; Senay, G. B.; Rowland, J.

2017-12-01

Forecasting crop production in advance of crop harvest plays a significant role in drought impact management, improved food security, stabilizing food grain market prices, and poverty reduction. This becomes essential, particularly in Sub-Saharan Africa, where agriculture is a critical source of livelihoods, but lacks good quality agricultural statistical data. With increasing availability of low cost satellite data, faster computing power, and development of modeling algorithms, remotely sensed images are becoming a common source for deriving information for agricultural, drought, and water management. Many researchers have shown that the Normalized Difference Vegetation Index (NDVI), based on red and near-infrared reflectance, can be effectively used for estimating crop production and yield. Similarly, crop production and yield have been closely related to evapotranspiration (ET) also as there are strong linkages between production/yield and transpiration based on plant physiology. Thus, we combined NDVI and ET information from remotely sensed images for estimating total production and crop yield prior to crop harvest for Niger and Burkina Faso in West Africa. We identified the optimum time (dekads 23-29) for cumulating NDVI and ET and developed a new algorithm for estimating crop production and yield. We used the crop data from 2003 to 2008 to calibrate our model and the data from 2009 to 2013 for validation. Our results showed that total crop production can be estimated within 5% of actual production (R2 = 0.98) about 30-45 days before end of the harvest season. This novel approach can be operationalized to provide a valuable tool to decision makers for better drought impact management in drought-prone regions of the world.

Providing a Spatial Context for Crop Insurance in Ethiopia: Multiscale Comparisons of Vegetation Metrics in Tigray

NASA Astrophysics Data System (ADS)

Mann, B. F.; Small, C.

2014-12-01

Weather-based index insurance projects are rapidly expanding across the developing world. Many of these projects use satellite-based observations to detect extreme weather events, which inform and trigger payouts to smallholder farmers. While most index insurance programs use precipitation measurements to determine payouts, the use of remotely sensed observations of vegetation is currently being explored. In order to use vegetation indices as a basis for payouts, it is necessary to establish a consistent relationship between the vegetation index and the health and abundance of agriculture on the ground. The accuracy with which remotely sensed vegetation indices can detect changes in agriculture depends on both the spatial scale of the agriculture and the spatial resolution of the sensor. This study analyzes the relationship between meter and decameter scale vegetation fraction estimates derived from linear spectral mixture models with a more commonly used vegetation index (NDVI, EVI) at hectometer spatial scales. In addition, the analysis incorporates land cover/land use field observations collected in Tigray Ethiopia in July 2013. . It also tests the flexibility and utility of a standardized spectral mixture model in which land cover is represented as continuous fields of rock and soil substrate (S), vegetation (V) and dark surfaces (D; water, shadow). This analysis found strong linear relationships with vegetation metrics at 1.6-meter, 30-meter and 250-meter resolutions across spectrally diverse subsets of Tigray, Ethiopia and significantly correlated relationships using the Spearman's rho statistic. The observed linear scaling has positive implications for future use of moderate resolution vegetation indices in similar landscapes; especially index insurance projects that are scaling up across the developing world using remotely-sensed environmental information.

Real-time sensing of epithelial cell-cell and cell-substrate interactions by impedance spectroscopy on porous substrates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mondal, D.; RoyChaudhuri, C., E-mail: chirosreepram@yahoo.com; Pal, D.

2015-07-28

Oxidized porous silicon (PS) is a common topographical biocompatible substrate that potentially provides a distinct in vitro environment for better understanding of in vivo behavior. But in the reported studies on oxidized PS, cell-cell and cell-substrate interactions have been detected only by fluorescent labeling. This paper is the first attempt to investigate real-time sensing of these interactions on HaCaT cells by label-free impedance spectroscopy on oxidized PS of two pore diameters (50 and 500 nm). One of the major requirements for successful impedance spectroscopy measurement is to restrict the channeling of electric field lines through the pores. To satisfy this criterion,more » we have designed the pore depths after analyzing the penetration of the medium by using computational fluid dynamics simulation. A distributed electrical model was also developed for estimating the various cellular attributes by considering a pseudorandom distribution of pores. It is observed from the impedance measurements and from the model that the proliferation rate increases for 50 nm pores but decreases for 500 nm pores compared to that for planar substrates. The rate of decrease in cell substrate separation (h) in the initial stage is more than the rate of increase in cell-cell junction resistance (R{sub b}) corresponding to the initial adhesion phase of cells. It is observed that R{sub b} and h are higher for 50 nm pores than those for planar substrates, corresponding to the fact that substrates more conducive toward cell adhesion encourage cell-cell interactions than direct cell-substrate interactions. Thus, the impedance spectroscopy coupled with the proposed theoretical framework for PS substrates can sense and quantify the cellular interactions.« less

The landslide susceptibility mapping and assessment with ZY satellite data

NASA Astrophysics Data System (ADS)

Zhang, R.; Zhang, Z.; Zhao, Y.

2012-12-01

Natural hazards can result in enormous property damage and casualties in mountainous regions. In China, the direct loss of hazards is about 400 million yuan in 2011. Especially the landslide, the most common natural hazards, got the wide attention of each country. Landslide susceptibility mapping is of great importance for landslide hazard mitigation efforts throughout the world. In Southwest Hubei, there are much mineral mining activities, which may trigger the landslide. In addition the Three Gorges reservoir is located in this area, and the storage changed the geological and hydrological environment, which may increase the frequency of the ancient landslide reactivation, and the new landslide occurrence. There are more than 200 landslide hazards happened since 2003. So producing a regional-scaled landslide susceptibility map is necessary. For the above purpose, the landslide susceptibility mapping was produced by using the ZY-3 and ZY-1-02C satellite data, the DEMs and the conventional topographic data.(1) The DEM derivatives slope gradient, the slope aspect and the topographic wetness index (TWI) ; (2) in order to acquire the spatially continuous vegetation information, Normalized Difference Vegetation Index (NDVI) was computed using ZY-1-02C and ZY-3; (3) the regional lithologic information (i.e. mineral distribution) and the tectonic information obtained from remote sensing data in combination with regional geological survey; (4) the regional hydrogeological information was produced by using the remote sensing data in combination with the DEMs; (5) the existed landslides information obtained from remote sensing. To model the landslide hazard assessment using variety of statistic methods and evaluation methods, the cross application model yields reasonable results which can be applied for preliminary landslide hazard mapping and the hazard grade division.

A Sub-Millimetric 3-DOF Force Sensing Instrument with Integrated Fiber Bragg Grating for Retinal Microsurgery

PubMed Central

He, Xingchi; Handa, James; Gehlbach, Peter; Taylor, Russell; Iordachita, Iulian

2013-01-01

Vitreoretinal surgery requires very fine motor control to perform precise manipulation of the delicate tissue in the interior of the eye. Besides physiological hand tremor, fatigue, poor kinesthetic feedback, and patient movement, the absence of force sensing is one of the main technical challenges. Previous two degrees of freedom (DOF) force sensing instruments have demonstrated robust force measuring performance. The main design challenge is to incorporate high sensitivity axial force sensing. This paper reports the development of a sub-millimetric 3-DOF force sensing pick instrument based on fiber Bragg grating (FBG) sensors. The configuration of the four FBG sensors is arranged to maximize the decoupling between axial and transverse force sensing. A super-elastic nitinol flexure is designed to achieve high axial force sensitivity. An automated calibration system was developed for repeatability testing, calibration, and validation. Experimental results demonstrate a FBG sensor repeatability of 1.3 pm. The linear model for calculating the transverse forces provides an accurate global estimate. While the linear model for axial force is only locally accurate within a conical region with a 30° vertex angle, a second-order polynomial model can provide a useful global estimate for axial force. Combining the linear model for transverse forces and nonlinear model for axial force, the 3-DOF force sensing instrument can provide sub-millinewton resolution for axial force and a quarter millinewton for transverse forces. Validation with random samples show the force sensor can provide consistent and accurate measurement of three dimensional forces. PMID:24108455

Matching student personality types and learning preferences to teaching methodologies.

PubMed

Jessee, Stephen A; O'Neill, Paula N; Dosch, Robert O

2006-06-01

The purpose of this study was to identify teaching styles that complement the learning preferences of undergraduate dental students while enhancing the quality of patient care. A formidable challenge to reform in dental education has been overcoming the resistance by faculty and administration to recommended changes. The organizational structure of dental institutions, with their independent departments, makes obtaining consensus on educational issues difficult. For beneficial change to occur, clear evidence of the benefits to all within the organization must be presented. The objectives of the study were to 1) identify the most common personality types among first- and second-year undergraduate dental students at the University of Texas Dental Branch at Houston using the Myers-Briggs Type Indicator (MBTI); 2) identify the learning preferences of these personality types; and 3) determine a more effective approach to teaching clinical dentistry based upon student personality types and learning preferences. Four common personality types were identified among respondents: ISTJ, ESFJ, ESTJ, and ISFJ, with a predisposition for Sensing (S) (desire for facts, use of senses) over Intuition (N) (look for possibilities, relationships) and Judging (J) (prefers decisiveness, closure) over Perceiving (P) (desire flexibility, spontaneity). The most common occurring personality type, ISTJ, represents an Introverted, Sensing, Thinking, Judging individual. Specific clinical curricular techniques that would appeal to these common personality types are identified, and an explanation of their benefit is provided. Results of this study demonstrate the importance of faculty understanding and acknowledging different student personality types and related learning preferences as a way to initiate improvement of undergraduate dental education, promote student motivation, and allow for an expression of learning style preference.

Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

NASA Technical Reports Server (NTRS)

Goetz, Scott J.; Bockstael, Nancy E.; Jantz, Claire A.

2005-01-01

This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has undertaken analyses of these models. One (the CA model) is driven largely by observations on past patterns of land use change, while the other (the EC model) is driven by mechanisms of the land use change decision at the parcel level. Our project may be the first serious attempt at developing both types of models for the same area, using as much common data as possible. We have identified the strengths and weaknesses of the two approaches and plan to continue to revise each model in the light of new data and new lessons learned through continued collaboration. Questions, approaches, findings, publication and presentation lists concerning the research are also presented.

Improving subjective pattern recognition in chemical senses through reduction of nonlinear effects in evaluation of sparse data

NASA Astrophysics Data System (ADS)

Assadi, Amir H.; Rasouli, Firooz; Wrenn, Susan E.; Subbiah, M.

2002-11-01

Artificial neural network models are typically useful in pattern recognition and extraction of important features in large data sets. These models are implemented in a wide variety of contexts and with diverse type of input-output data. The underlying mathematics of supervised training of neural networks is ultimately tied to the ability to approximate the nonlinearities that are inherent in network"s generalization ability. The quality and availability of sufficient data points for training and validation play a key role in the generalization ability of the network. A potential domain of applications of neural networks is in analysis of subjective data, such as in consumer science, affective neuroscience and perception of chemical senses. In applications of ANN to subjective data, it is common to rely on knowledge of the science and context for data acquisition, for instance as a priori probabilities in the Bayesian framework. In this paper, we discuss the circumstances that create challenges for success of neural network models for subjective data analysis, such as sparseness of data and cost of acquisition of additional samples. In particular, in the case of affect and perception of chemical senses, we suggest that inherent ambiguity of subjective responses could be offset by a combination of human-machine expert. We propose a method of pre- and post-processing for blind analysis of data that that relies on heuristics from human performance in interpretation of data. In particular, we offer an information-theoretic smoothing (ITS) algorithm that optimizes that geometric visualization of multi-dimensional data and improves human interpretation of the input-output view of neural network implementations. The pre- and post-processing algorithms and ITS are unsupervised. Finally, we discuss the details of an example of blind data analysis from actual taste-smell subjective data, and demonstrate the usefulness of PCA in reduction of dimensionality, as well as ITS.

Integrating remotely sensed surface water extent into continental scale hydrology

NASA Astrophysics Data System (ADS)

Revilla-Romero, Beatriz; Wanders, Niko; Burek, Peter; Salamon, Peter; de Roo, Ad

2016-12-01

In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data. However, the limited availability of continuous and up-to-date ground streamflow data is one of the main constraints for large-scale flood forecasting models. This is the first study that assess the impact of assimilating daily remotely sensed surface water extent at a 0.1° × 0.1° spatial resolution derived from the Global Flood Detection System (GFDS) into a global rainfall-runoff including large ungauged areas at the continental spatial scale in Africa and South America. Surface water extent is observed using a range of passive microwave remote sensors. The methodology uses the brightness temperature as water bodies have a lower emissivity. In a time series, the satellite signal is expected to vary with changes in water surface, and anomalies can be correlated with flood events. The Ensemble Kalman Filter (EnKF) is a Monte-Carlo implementation of data assimilation and used here by applying random sampling perturbations to the precipitation inputs to account for uncertainty obtaining ensemble streamflow simulations from the LISFLOOD model. Results of the updated streamflow simulation are compared to baseline simulations, without assimilation of the satellite-derived surface water extent. Validation is done in over 100 in situ river gauges using daily streamflow observations in the African and South American continent over a one year period. Some of the more commonly used metrics in hydrology were calculated: KGE', NSE, PBIAS%, R2, RMSE, and VE. Results show that, for example, NSE score improved on 61 out of 101 stations obtaining significant improvements in both the timing and volume of the flow peaks. Whereas the validation at gauges located in lowland jungle obtained poorest performance mainly due to the closed forest influence on the satellite signal retrieval. The conclusion is that remotely sensed surface water extent holds potential for improving rainfall-runoff streamflow simulations, potentially leading to a better forecast of the peak flow.

What is a picture worth? A history of remote sensing

USGS Publications Warehouse

Moore, Gerald K.

1979-01-01

Remote sensing is the use of electromagnetic energy to measure the physical properties of distant objects. It includes photography and geophysical surveying as well as newer techniques that use other parts of the electromagnetic spectrum. The history of remote sensing begins with photography. The origin of other types of remote sensing can be traced to World War II, with the development of radar, sonar, and thermal infrared detection systems. Since the 1960s, sensors have been designed to operate in virtually all of the electromagnetic spectrum. Today a wide variety of remote sensing instruments are available for use in hydrological studies; satellite data, such as Skylab photographs and Landsat images are particularly suitable for regional problems and studies. Planned future satellites will provide a ground resolution of 10–80 m. Remote sensing is currently used for hydrological applications in most countries of the world. The range of applications includes groundwater exploration determination of physical water quality, snowfield mapping, flood-inundation delineation, and making inventories of irrigated land. The use of remote sensing commonly results in considerable hydrological information at minimal cost. This information can be used to speed-up the development of water resources, to improve management practices, and to monitor environmental problems.

Fusion of Remote Sensing Methods, UAV Photogrammetry and LiDAR Scanning products for monitoring fluvial dynamics

NASA Astrophysics Data System (ADS)

Lendzioch, Theodora; Langhammer, Jakub; Hartvich, Filip

2015-04-01

Fusion of remote sensing data is a common and rapidly developing discipline, which combines data from multiple sources with different spatial and spectral resolution, from satellite sensors, aircraft and ground platforms. Fusion data contains more detailed information than each of the source and enhances the interpretation performance and accuracy of the source data and produces a high-quality visualisation of the final data. Especially, in fluvial geomorphology it is essential to get valuable images in sub-meter resolution to obtain high quality 2D and 3D information for a detailed identification, extraction and description of channel features of different river regimes and to perform a rapid mapping of changes in river topography. In order to design, test and evaluate a new approach for detection of river morphology, we combine different research techniques from remote sensing products to drone-based photogrammetry and LiDAR products (aerial LiDAR Scanner and TLS). Topographic information (e.g. changes in river channel morphology, surface roughness, evaluation of floodplain inundation, mapping gravel bars and slope characteristics) will be extracted either from one single layer or from combined layers in accordance to detect fluvial topographic changes before and after flood events. Besides statistical approaches for predictive geomorphological mapping and the determination of errors and uncertainties of the data, we will also provide 3D modelling of small fluvial features.

Kurdish men's experiences of migration-related mental health issues.

PubMed

Taloyan, Marina; Al-Windi, Ahmad; Johansson, Leena Maria; Saleh-Stattin, Nuha

2011-10-01

The migration process may impose stress on the mental health of immigrants. To describe the experiences of immigrant men of Kurdish ethnicity during and after migration to Sweden with regard to mental health issues. Using the grounded theory method, we conducted a focus group interview with four Kurdish men and in-depth individual interviews with 10 other Kurdish men. A model with two major themes and interlinked categories was developed. The themes were (1) protective factors for good mental health (sense of belonging, creation and re-creation of Kurdish identity, sense of freedom, satisfaction with oneself) and (2) risk factors for poor mental health (worry about current political situation in the home country, yearning, lack of sense of freedom, dissatisfaction with Swedish society). The study provides insights into the psychological and emotional experiences of immigrant men of Kurdish ethnicity during and after migration to Sweden. It is important for primary health care providers to be aware of the impact that similar migration-related and life experiences have on the health status of immigrants, and also to be aware that groups are comprised of unique individuals with differing experiences and reactions to these experiences. The findings highlight the common themes of the men's experiences and suggest ways to ameliorate mental health issues, including feeling like one is seen as an individual, is a full participant in society, and can contribute to one's own culture.

Neural-like growing networks

NASA Astrophysics Data System (ADS)

Yashchenko, Vitaliy A.

2000-03-01

On the basis of the analysis of scientific ideas reflecting the law in the structure and functioning the biological structures of a brain, and analysis and synthesis of knowledge, developed by various directions in Computer Science, also there were developed the bases of the theory of a new class neural-like growing networks, not having the analogue in world practice. In a base of neural-like growing networks the synthesis of knowledge developed by classical theories - semantic and neural of networks is. The first of them enable to form sense, as objects and connections between them in accordance with construction of the network. With thus each sense gets a separate a component of a network as top, connected to other tops. In common it quite corresponds to structure reflected in a brain, where each obvious concept is presented by certain structure and has designating symbol. Secondly, this network gets increased semantic clearness at the expense owing to formation not only connections between neural by elements, but also themselves of elements as such, i.e. here has a place not simply construction of a network by accommodation sense structures in environment neural of elements, and purely creation of most this environment, as of an equivalent of environment of memory. Thus neural-like growing networks are represented by the convenient apparatus for modeling of mechanisms of teleological thinking, as a fulfillment of certain psychophysiological of functions.

Findings and Challenges in Fine-Resolution Large-Scale Hydrological Modeling

NASA Astrophysics Data System (ADS)

Her, Y. G.

2017-12-01

Fine-resolution large-scale (FL) modeling can provide the overall picture of the hydrological cycle and transport while taking into account unique local conditions in the simulation. It can also help develop water resources management plans consistent across spatial scales by describing the spatial consequences of decisions and hydrological events extensively. FL modeling is expected to be common in the near future as global-scale remotely sensed data are emerging, and computing resources have been advanced rapidly. There are several spatially distributed models available for hydrological analyses. Some of them rely on numerical methods such as finite difference/element methods (FDM/FEM), which require excessive computing resources (implicit scheme) to manipulate large matrices or small simulation time intervals (explicit scheme) to maintain the stability of the solution, to describe two-dimensional overland processes. Others make unrealistic assumptions such as constant overland flow velocity to reduce the computational loads of the simulation. Thus, simulation efficiency often comes at the expense of precision and reliability in FL modeling. Here, we introduce a new FL continuous hydrological model and its application to four watersheds in different landscapes and sizes from 3.5 km2 to 2,800 km2 at the spatial resolution of 30 m on an hourly basis. The model provided acceptable accuracy statistics in reproducing hydrological observations made in the watersheds. The modeling outputs including the maps of simulated travel time, runoff depth, soil water content, and groundwater recharge, were animated, visualizing the dynamics of hydrological processes occurring in the watersheds during and between storm events. Findings and challenges were discussed in the context of modeling efficiency, accuracy, and reproducibility, which we found can be improved by employing advanced computing techniques and hydrological understandings, by using remotely sensed hydrological observations such as soil moisture and radar rainfall depth and by sharing the model and its codes in public domain, respectively.

Task directed sensing

NASA Technical Reports Server (NTRS)

Firby, R. James

1990-01-01

High-level robot control research must confront the limitations imposed by real sensors if robots are to be controlled effectively in the real world. In particular, sensor limitations make it impossible to maintain a complete, detailed world model of the situation surrounding the robot. To address the problems involved in planning with the resulting incomplete and uncertain world models, traditional robot control architectures must be altered significantly. Task-directed sensing and control is suggested as a way of coping with world model limitations by focusing sensing and analysis resources on only those parts of the world relevant to the robot's active goals. The RAP adaptive execution system is used as an example of a control architecture designed to deploy sensing resources in this way to accomplish both action and knowledge goals.

The VI-SENSE-vaginal discharge self-test to facilitate management of vaginal symptoms.

PubMed

Geva, Adam; Bornstein, Jacob; Dan, Michael; Shoham, Hadar Kessary; Sobel, Jack D

2006-11-01

This study was undertaken to evaluate a diagnostic panty liner (VI-SENSE) (Common Sense, Caesarea, Israel) developed to facilitate diagnosis of vaginal infections by detecting disordered acidity level. Five hundred sixteen women with vulvovaginal symptoms were enrolled. Final clinical diagnosis included Amsel criteria, Gram stain analysis, pH determination, and Trichomonas vaginalis and Candida culture. VI-SENSE strip color status estimated by patients was compared with clinical diagnosis and pH measurement by using nitrazine paper. Statistical analysis included sensitivity and specificity calculations. The VI-SENSE test was positive in 226 of 249 patients (90.8%) with bacterial vaginosis or trichomoniasis. Nitrazine pH paper revealed elevated pH in 165 (66.5%) and the amine test was positive in 160 (64.3%) patients. The VI-SENSE test was negative in 217 of 267 patients (81.3%) without trichomoniasis or bacterial vaginosis. The VI-SENSE was positive in 85 of 92 women (92%), with mixed vaginal infection including Candida and bacterial vaginosis or trichomoniasis. Amine test, nitrazine pH paper and physician diagnosis relying only on speculum examination were inferior and positive in only 65 (70%), 59 (64%), and 66 (72%) patients, respectively. The VI-SENSE test was found to be superior to traditional individual tests in facilitating preliminary diagnosis of vaginal infections.

[Study on artificial neural network combined with multispectral remote sensing imagery for forest site evaluation].

PubMed

Gong, Yin-Xi; He, Cheng; Yan, Fei; Feng, Zhong-Ke; Cao, Meng-Lei; Gao, Yuan; Miao, Jie; Zhao, Jin-Long

2013-10-01

Multispectral remote sensing data containing rich site information are not fully used by the classic site quality evaluation system, as it merely adopts artificial ground survey data. In order to establish a more effective site quality evaluation system, a neural network model which combined remote sensing spectra factors with site factors and site index relations was established and used to study the sublot site quality evaluation in the Wangyedian Forest Farm in Inner Mongolia Province, Chifeng City. Based on the improved back propagation artificial neural network (BPANN), this model combined multispectral remote sensing data with sublot survey data, and took larch as example, Through training data set sensitivity analysis weak or irrelevant factor was excluded, the size of neural network was simplified, and the efficiency of network training was improved. This optimal site index prediction model had an accuracy up to 95.36%, which was 9.83% higher than that of the neural network model based on classic sublot survey data, and this shows that using multi-spectral remote sensing and small class survey data to determine the status of larch index prediction model has the highest predictive accuracy. The results fully indicate the effectiveness and superiority of this method.

Mass segregation phenomena using the Hamiltonian Mean Field model

NASA Astrophysics Data System (ADS)

Steiner, J. R.; Zolacir, T. O.

2018-02-01

Mass segregation problem is thought to be entangled with the dynamical evolution of young stellar clusters (Olczak, 2011 [1]). This is a common sense in the astrophysical community. In this work, the Hamiltonian Mean Field (HMF) model with different masses is studied. A mass segregation phenomenon (MSP) arises from this study as a dynamical feature. The MSP in the HMF model is a consequence of the Landau damping (LD) and it appears in systems that the interactions belongs to a long range regime. Actually HMF is a toy model known to show up the main characteristics of astrophysical systems due to the mean field character of the potential and for different masses, as stellar and galaxies clusters, also exhibits MSP. It is in this sense that computational simulations focusing in what happens over the mass distribution in the phase space are performed for this system. What happens through the violent relaxation period and what stands for the quasi-stationary states (QSS) of this dynamics is analyzed. The results obtained support the fact that MSP is observed already in the violent relaxation time and is maintained during the QSS. Some structures in the mass distribution function are observed. As a result of this study the mass distribution is determined by the system dynamics and is independent of the dimensionality of the system. MSP occurs in a one dimensional system as a result of the long range forces that acts in the system. In this approach MSP emerges as a dynamical feature. We also show that for HMF with different masses, the dynamical time scale is N.

An Error-Reduction Algorithm to Improve Lidar Turbulence Estimates for Wind Energy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Newman, Jennifer F.; Clifton, Andrew

2016-08-01

Currently, cup anemometers on meteorological (met) towers are used to measure wind speeds and turbulence intensity to make decisions about wind turbine class and site suitability. However, as modern turbine hub heights increase and wind energy expands to complex and remote sites, it becomes more difficult and costly to install met towers at potential sites. As a result, remote sensing devices (e.g., lidars) are now commonly used by wind farm managers and researchers to estimate the flow field at heights spanned by a turbine. While lidars can accurately estimate mean wind speeds and wind directions, there is still a largemore » amount of uncertainty surrounding the measurement of turbulence with lidars. This uncertainty in lidar turbulence measurements is one of the key roadblocks that must be overcome in order to replace met towers with lidars for wind energy applications. In this talk, a model for reducing errors in lidar turbulence estimates is presented. Techniques for reducing errors from instrument noise, volume averaging, and variance contamination are combined in the model to produce a corrected value of the turbulence intensity (TI), a commonly used parameter in wind energy. In the next step of the model, machine learning techniques are used to further decrease the error in lidar TI estimates.« less

Moving across scales: Challenges and opportunities in upscaling carbon fluxes

NASA Astrophysics Data System (ADS)

Naithani, K. J.

2016-12-01

Light use efficiency (LUE) type models are commonly used to upscale terrestrial C fluxes and estimate regional and global C budgets. Model parameters are often estimated for each land cover type (LCT) using flux observations from one or more eddy covariance towers, and then spatially extrapolated by integrating land cover, meteorological, and remotely sensed data. Decisions regarding the type of input data (spatial resolution of land cover data, spatial and temporal length of flux data), representation of landscape structure (land use vs. disturbance regime), and the type of modeling framework (common risk vs. hierarchical) all influence the estimates CO2 fluxes and the associated uncertainties, but are rarely considered together. This work presents a synthesis of past and present efforts for upscaling CO2 fluxes and associated uncertainties in the ChEAS (Chequamegon Ecosystem Atmosphere Study) region in northern Wisconsin and the Upper Peninsula of Michigan. This work highlights two key future research needs. First, the characterization of uncertainties due to all of the abovementioned factors reflects only a (hopefully relevant) subset the overall uncertainties. Second, interactions among these factors are likely critical, but are poorly represented by the tower network at landscape scales. Yet, results indicate significant spatial and temporal heterogeneity of uncertainty in CO2 fluxes which can inform carbon management efforts and prioritize data needs.

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques.

PubMed

Gholizadeh, Mohammad Haji; Melesse, Assefa M; Reddi, Lakshmi

2016-08-16

Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM), chlorophyll-a, and pollutants). A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water's surface. In this review paper, various properties (spectral, spatial and temporal, etc.) of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD).

Even with a green card, you can be put out to pasture and still have to work: non-native intuitions of the transparency of common English idioms.

PubMed

Malt, Barbara C; Eiter, Brianna

2004-09-01

Native speakers of English use idioms such as put your foot down and spill the beans to label events that are not described literally by the words that compose the idioms. For many such expressions, the idiomatic meanings are transparent; that is, the connection between the literal expression and its figurative meaning makes sense to native speakers. We tested Keysar and Bly's (1995) hypothesis that this sense of transparency for the meaning of everyday idioms does not necessarily obtain because the idiomatic meanings are derived from motivating literal meanings or conceptual metaphors, but rather (at least in part) because language users construct explanations after the fact for whatever meaning is conventionally assigned to the expression. Non-native speakers of English were exposed to common English idioms and taught either the conventional idiomatic meaning or an alternative meaning. In agreement with Keysar and Bly's suggestion, their subsequent sense of transparency was greater for the meaning that the speakers had learned and used, regardless of which one it was.