7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2011 CFR

2011-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2013 CFR

2013-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2010 CFR

2010-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2014 CFR

2014-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

Treadmill training and body weight support for walking after stroke.

PubMed

Mehrholz, Jan; Thomas, Simone; Elsner, Bernhard

2017-08-17

Treadmill training, with or without body weight support using a harness, is used in rehabilitation and might help to improve walking after stroke. This is an update of the Cochrane review first published in 2003 and updated in 2005 and 2014. To determine if treadmill training and body weight support, individually or in combination, improve walking ability, quality of life, activities of daily living, dependency or death, and institutionalisation or death, compared with other physiotherapy gait-training interventions after stroke. The secondary objective was to determine the safety and acceptability of this method of gait training. We searched the Cochrane Stroke Group Trials Register (last searched 14 February 2017), the Cochrane Central Register of Controlled Trials (CENTRAL) and the Database of Reviews of Effects (DARE) (the Cochrane Library 2017, Issue 2), MEDLINE (1966 to 14 February 2017), Embase (1980 to 14 February 2017), CINAHL (1982 to 14 February 2017), AMED (1985 to 14 February 2017) and SPORTDiscus (1949 to 14 February 2017). We also handsearched relevant conference proceedings and ongoing trials and research registers, screened reference lists, and contacted trialists to identify further trials. Randomised or quasi-randomised controlled and cross-over trials of treadmill training and body weight support, individually or in combination, for the treatment of walking after stroke. Two review authors independently selected trials, extracted data, and assessed risk of bias and methodological quality. The primary outcomes investigated were walking speed, endurance, and dependency. We included 56 trials with 3105 participants in this updated review. The average age of the participants was 60 years, and the studies were carried out in both inpatient and outpatient settings. All participants had at least some walking difficulties and many could not walk without assistance. Overall, the use of treadmill training did not increase the chances of walking

Over ground walking and body weight supported walking improve mobility equally in cerebral palsy: a randomised controlled trial.

PubMed

Swe, Ni Ni; Sendhilnnathan, Sunitha; van Den Berg, Maayken; Barr, Christopher

2015-11-01

To assess partial body weight supported treadmill training versus over ground training for walking ability in children with mild to moderate cerebral palsy. Randomised controlled trial. A Special Needs school in Singapore. Thirty children with cerebral palsy, aged 6-18, with a Gross Motor Function Classification System score of II-III. Two times 30 minute sessions of walking training per week for 8 weeks, progressed as tolerated, either over ground (control) or using partial body weight supported treadmill training (intervention). The 10 metre walk test, and the 6 minute walk test. Secondary measures were sub-sections D and E on the Gross Motor Function Measure. Outcomes were assessed at baseline, and after 4 and 8 weeks of training. There was no effect of group allocation on any outcome measure, while time was a significant factor for all outcomes. Walking speed improved significantly more in the intervention group by week 4 (0.109 (0.067)m/s vs 0.048 (0.071)m/s, P=0.024) however by week 8 the change from baseline was similar (intervention 0.0160 (0.069)m/s vs control 0.173 (0.109)m/s, P=0.697). All gains made by week 4 were significantly improved on by week 8 for the 10 metre walk test, 6 minute walk test, and the gross motor function measure. Partial body weight supported treadmill training is no more effective than over ground walking at improving aspects of walking and function in children with mild to moderate cerebral palsy. Gains seen in 4 weeks can be furthered by 8 weeks. © The Author(s) 2015.

Effects of Progressive Body Weight Support Treadmill Forward and Backward Walking Training on Stroke Patients' Affected Side Lower Extremity's Walking Ability.

PubMed

Kim, Kyunghoon; Lee, Sukmin; Lee, Kyoungbo

2014-12-01

[Purpose] The purpose of the present study was to examine the effects of progressive body weight supported treadmill forward and backward walking training (PBWSTFBWT), progressive body weight supported treadmill forward walking training (PBWSTFWT), progressive body weight supported treadmill backward walking training (PBWSTBWT), on stroke patients' affected side lower extremity's walking ability. [Subjects and Methods] A total of 36 chronic stroke patients were divided into three groups with 12 subjects in each group. Each of the groups performed one of the progressive body weight supported treadmill training methods for 30 minute, six times per week for three weeks, and then received general physical therapy without any other intervention until the follow-up tests. For the assessment of the affected side lower extremity's walking ability, step length of the affected side, stance phase of the affected side, swing phase of the affected side, single support of the affected side, and step time of the affected side were measured using optogait and the symmetry index. [Results] In the within group comparisons, all the three groups showed significant differences between before and after the intervention and in the comparison of the three groups, the PBWSTFBWT group showed more significant differences in all of the assessed items than the other two groups. [Conclusion] In the present study progressive body weight supported treadmill training was performed in an environment in which the subjects were actually walked, and PBWSTFBWT was more effective at efficiently training stroke patients' affected side lower extremity's walking ability.

Geographically Weighted Regression Model with Kernel Bisquare and Tricube Weighted Function on Poverty Percentage Data in Central Java Province

NASA Astrophysics Data System (ADS)

Nugroho, N. F. T. A.; Slamet, I.

2018-05-01

Poverty is a socio-economic condition of a person or group of people who can not fulfil their basic need to maintain and develop a dignified life. This problem still cannot be solved completely in Central Java Province. Currently, the percentage of poverty in Central Java is 13.32% which is higher than the national poverty rate which is 11.13%. In this research, data of percentage of poor people in Central Java Province has been analyzed through geographically weighted regression (GWR). The aim of this research is therefore to model poverty percentage data in Central Java Province using GWR with weighted function of kernel bisquare, and tricube. As the results, we obtained GWR model with bisquare and tricube kernel weighted function on poverty percentage data in Central Java province. From the GWR model, there are three categories of region which are influenced by different of significance factors.

Graph Kernels for Molecular Similarity.

PubMed

Rupp, Matthias; Schneider, Gisbert

2010-04-12

Molecular similarity measures are important for many cheminformatics applications like ligand-based virtual screening and quantitative structure-property relationships. Graph kernels are formal similarity measures defined directly on graphs, such as the (annotated) molecular structure graph. Graph kernels are positive semi-definite functions, i.e., they correspond to inner products. This property makes them suitable for use with kernel-based machine learning algorithms such as support vector machines and Gaussian processes. We review the major types of kernels between graphs (based on random walks, subgraphs, and optimal assignments, respectively), and discuss their advantages, limitations, and successful applications in cheminformatics. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Weighted Bergman Kernels and Quantization}

NASA Astrophysics Data System (ADS)

Engliš, Miroslav

Let Ω be a bounded pseudoconvex domain in CN, φ, ψ two positive functions on Ω such that - log ψ, - log φ are plurisubharmonic, and z∈Ω a point at which - log φ is smooth and strictly plurisubharmonic. We show that as k-->∞, the Bergman kernels with respect to the weights φkψ have an asymptotic expansion for x,y near z, where φ(x,y) is an almost-analytic extension of &\\phi(x)=φ(x,x) and similarly for ψ. Further, . If in addition Ω is of finite type, φ,ψ behave reasonably at the boundary, and - log φ, - log ψ are strictly plurisubharmonic on Ω, we obtain also an analogous asymptotic expansion for the Berezin transform and give applications to the Berezin quantization. Finally, for Ω smoothly bounded and strictly pseudoconvex and φ a smooth strictly plurisubharmonic defining function for Ω, we also obtain results on the Berezin-Toeplitz quantization.

Ability to walk 1/4 mile predicts subsequent disability, mortality, and health care costs.

PubMed

Hardy, Susan E; Kang, Yihuang; Studenski, Stephanie A; Degenholtz, Howard B

2011-02-01

Mobility, such as walking 1/4 mile, is a valuable but underutilized health indicator among older adults. For mobility to be successfully integrated into clinical practice and health policy, an easily assessed marker that predicts subsequent health outcomes is required. To determine the association between mobility, defined as self-reported ability to walk 1/4 mile, and mortality, functional decline, and health care utilization and costs during the subsequent year. Analysis of longitudinal data from the 2003-2004 Medicare Current Beneficiary Survey, a nationally representative sample of Medicare beneficiaries. Participants comprised 5895 community-dwelling adults aged 65 years or older enrolled in Medicare. Mobility (self-reported ability to walk 1/4 mile), mortality, incident difficulty with activities of daily living (ADLs), total annual health care costs, and hospitalization rates. Among older adults, 28% reported difficulty and 17% inability to walk 1/4 mile at baseline. Compared to those without difficulty and adjusting for demographics, socioeconomic status, chronic conditions, and health behaviors, mortality was greater in those with difficulty [AOR (95% CI): 1.57 (1.10-2.24)] and inability [AOR (CI): 2.73 (1.79-4.15)]. New functional disability also occurred more frequently as self-reported ability to walk 1/4 mile declined (subsequent incident disability among those with no difficulty, difficulty, or inability to walk 1/4 mile at baseline was 11%, 29%, and 47% for instrumental ADLs, and 4%, 14%, and 23% for basic ADLs). Total annual health care costs were $2773 higher (95% CI $1443-4102) in persons with difficulty and $3919 higher (CI $1948-5890) in those who were unable. For each 100 persons, older adults reporting difficulty walking 1/4 mile at baseline experienced an additional 14 hospitalizations (95% CI 8-20), and those who were unable experienced an additional 22 hospitalizations (CI 14-30) during the follow-up period, compared to persons without

Ability to Walk 1/4 Mile Predicts Subsequent Disability, Mortality, and Health Care Costs

PubMed Central

Kang, Yihuang; Studenski, Stephanie A.; Degenholtz, Howard B.

2010-01-01

ABSTRACT Background Mobility, such as walking 1/4 mile, is a valuable but underutilized health indicator among older adults. For mobility to be successfully integrated into clinical practice and health policy, an easily assessed marker that predicts subsequent health outcomes is required. Objective To determine the association between mobility, defined as self-reported ability to walk 1/4 mile, and mortality, functional decline, and health care utilization and costs during the subsequent year. Design Analysis of longitudinal data from the 2003–2004 Medicare Current Beneficiary Survey, a nationally representative sample of Medicare beneficiaries. Participants Participants comprised 5895 community-dwelling adults aged 65 years or older enrolled in Medicare. Main Measures Mobility (self-reported ability to walk 1/4 mile), mortality, incident difficulty with activities of daily living (ADLs), total annual health care costs, and hospitalization rates. Key Results Among older adults, 28% reported difficulty and 17% inability to walk 1/4 mile at baseline. Compared to those without difficulty and adjusting for demographics, socioeconomic status, chronic conditions, and health behaviors, mortality was greater in those with difficulty [AOR (95% CI): 1.57 (1.10-2.24)] and inability [AOR (CI): 2.73 (1.79-4.15)]. New functional disability also occurred more frequently as self-reported ability to walk 1/4 mile declined (subsequent incident disability among those with no difficulty, difficulty, or inability to walk 1/4 mile at baseline was 11%, 29%, and 47% for instrumental ADLs, and 4%, 14%, and 23% for basic ADLs). Total annual health care costs were $2773 higher (95% CI $1443-4102) in persons with difficulty and $3919 higher (CI $1948-5890) in those who were unable. For each 100 persons, older adults reporting difficulty walking 1/4 mile at baseline experienced an additional 14 hospitalizations (95% CI 8-20), and those who were unable experienced an additional 22

Lifestyle medicine consulting walking meetings for sustained weight loss

PubMed Central

Frates, Elizabeth Pegg; Crane, Margaret E

2016-01-01

With rates of obesity and diabetes rising worldwide, effective ways of managing weight are becoming more important. We present the case study of a middle-aged Caucasian-American woman (body mass index (BMI) 27.8, overweight category) who wanted to lose weight. The patient participated in a behaviour modification programme with a physician trained in lifestyle medicine as well as health and wellness coaching. After the 14-week programme, which included 9, 1 h long walking sessions with the clinician, the patient lost 11 Ibs (BMI 24.7, normal category). The programme included a combination of increasing physical activity, eating appropriate quantities of healthy foods, goal setting and a positive attitude. The patient has kept her BMI at or below 24.1 for over 2 years. This case demonstrates a novel approach to weight loss management—walking therapeutic sessions—and also outlines critical components of lifestyle medicine counselling that facilitate the process of sustainable weight loss and lasting change. PMID:26833954

Determining weight and moisture properties of sound and fusarium-damaged single wheat kernels by near infrared spectroscopy

USDA-ARS?s Scientific Manuscript database

Single kernel moisture content (MC) is important in the measurement of other quality traits in single kernels since many traits are expressed on a dry weight basis, and MC affects viability, storage quality, and price. Also, if near-infrared (NIR) spectroscopy is used to measure grain traits, the in...

Empirical scaling of the length of the longest increasing subsequences of random walks

NASA Astrophysics Data System (ADS)

Mendonça, J. Ricardo G.

2017-02-01

We provide Monte Carlo estimates of the scaling of the length L n of the longest increasing subsequences of n-step random walks for several different distributions of step lengths, short and heavy-tailed. Our simulations indicate that, barring possible logarithmic corrections, {{L}n}∼ {{n}θ} with the leading scaling exponent 0.60≲ θ ≲ 0.69 for the heavy-tailed distributions of step lengths examined, with values increasing as the distribution becomes more heavy-tailed, and θ ≃ 0.57 for distributions of finite variance, irrespective of the particular distribution. The results are consistent with existing rigorous bounds for θ, although in a somewhat surprising manner. For random walks with step lengths of finite variance, we conjecture that the correct asymptotic behavior of L n is given by \\sqrt{n}\\ln n , and also propose the form for the subleading asymptotics. The distribution of L n was found to follow a simple scaling form with scaling functions that vary with θ. Accordingly, when the step lengths are of finite variance they seem to be universal. The nature of this scaling remains unclear, since we lack a working model, microscopic or hydrodynamic, for the behavior of the length of the longest increasing subsequences of random walks.

The genetic architecture of maize (Zea mays L.) kernel weight determination.

PubMed

Alvarez Prado, Santiago; López, César G; Senior, M Lynn; Borrás, Lucas

2014-09-18

Individual kernel weight is an important trait for maize yield determination. We have identified genomic regions controlling this trait by using the B73xMo17 population; however, the effect of genetic background on control of this complex trait and its physiological components is not yet known. The objective of this study was to understand how genetic background affected our previous results. Two nested stable recombinant inbred line populations (N209xMo17 and R18xMo17) were designed for this purpose. A total of 408 recombinant inbred lines were genotyped and phenotyped at two environments for kernel weight and five other traits related to kernel growth and development. All traits showed very high and significant (P < 0.001) phenotypic variability and medium-to-high heritability (0.60-0.90). When N209xMo17 and R18xMo17 were analyzed separately, a total of 23 environmentally stable quantitative trait loci (QTL) and five epistatic interactions were detected for N209xMo17. For R18xMo17, 59 environmentally stable QTL and 17 epistatic interactions were detected. A joint analysis detected 14 stable QTL regardless of the genetic background. Between 57 and 83% of detected QTL were population specific, denoting medium-to-high genetic background effects. This percentage was dependent on the trait. A meta-analysis including our previous B73xMo17 results identified five relevant genomic regions deserving further characterization. In summary, our grain filling traits were dominated by small additive QTL with several epistatic and few environmental interactions and medium-to-high genetic background effects. This study demonstrates that the number of detected QTL and additive effects for different physiologically related grain filling traits need to be understood relative to the specific germplasm. Copyright © 2014 Alvarez Prado et al.

Practicable group testing method to evaluate weight/weight GMO content in maize grains.

PubMed

Mano, Junichi; Yanaka, Yuka; Ikezu, Yoko; Onishi, Mari; Futo, Satoshi; Minegishi, Yasutaka; Ninomiya, Kenji; Yotsuyanagi, Yuichi; Spiegelhalter, Frank; Akiyama, Hiroshi; Teshima, Reiko; Hino, Akihiro; Naito, Shigehiro; Koiwa, Tomohiro; Takabatake, Reona; Furui, Satoshi; Kitta, Kazumi

2011-07-13

Because of the increasing use of maize hybrids with genetically modified (GM) stacked events, the established and commonly used bulk sample methods for PCR quantification of GM maize in non-GM maize are prone to overestimate the GM organism (GMO) content, compared to the actual weight/weight percentage of GM maize in the grain sample. As an alternative method, we designed and assessed a group testing strategy in which the GMO content is statistically evaluated based on qualitative analyses of multiple small pools, consisting of 20 maize kernels each. This approach enables the GMO content evaluation on a weight/weight basis, irrespective of the presence of stacked-event kernels. To enhance the method's user-friendliness in routine application, we devised an easy-to-use PCR-based qualitative analytical method comprising a sample preparation step in which 20 maize kernels are ground in a lysis buffer and a subsequent PCR assay in which the lysate is directly used as a DNA template. This method was validated in a multilaboratory collaborative trial.

The effectiveness of body weight-supported gait training and floor walking in patients with chronic stroke.

PubMed

Peurala, Sinikka H; Tarkka, Ina M; Pitkänen, Kauko; Sivenius, Juhani

2005-08-01

To compare body weight-supported exercise on a gait trainer with walking exercise overground. Randomized controlled trial. Rehabilitation hospital. Forty-five ambulatory patients with chronic stroke. Patients were randomized to 3 groups: (1) gait trainer exercise with functional electric stimulation (GTstim), (2) gait trainer exercise without stimulation (GT), and (3) walking overground (WALK). All patients practiced gait for 15 sessions during 3 weeks (each session, 20 min), and they received additional physiotherapy 55 minutes daily. Ten-meter walk test (10MWT), six-minute walk test (6MWT), lower-limb spasticity and muscle force, postural sway tests, Modified Motor Assessment Scale (MMAS), and FIM instrument scores were recorded before, during, and after the rehabilitation and at 6 months follow-up. The mean walking distance using the gait trainer was 6900+/-1200 m in the GTstim group and 6500+/-1700 m in GT group. In the WALK group, the distance was 4800+/-2800 m, which was less than the walking distance obtained in the GTstim group (P=.027). The body-weight support was individually reduced from 30% to 9% of the body weight over the course of the program. In the pooled 45 patients, the 10MWT (P<.001), 6MWT (P<.001), MMAS (P<.001), dynamic balance test time (P<.001), and test trip (P=.005) scores improved; however, no differences were found between the groups. Both the body weight-supported training and walking exercise training programs resulted in faster gait after the intensive rehabilitation program. Patients' motor performance remained improved at the follow-up.

Parametric output-only identification of time-varying structures using a kernel recursive extended least squares TARMA approach

NASA Astrophysics Data System (ADS)

Ma, Zhi-Sai; Liu, Li; Zhou, Si-Da; Yu, Lei; Naets, Frank; Heylen, Ward; Desmet, Wim

2018-01-01

The problem of parametric output-only identification of time-varying structures in a recursive manner is considered. A kernelized time-dependent autoregressive moving average (TARMA) model is proposed by expanding the time-varying model parameters onto the basis set of kernel functions in a reproducing kernel Hilbert space. An exponentially weighted kernel recursive extended least squares TARMA identification scheme is proposed, and a sliding-window technique is subsequently applied to fix the computational complexity for each consecutive update, allowing the method to operate online in time-varying environments. The proposed sliding-window exponentially weighted kernel recursive extended least squares TARMA method is employed for the identification of a laboratory time-varying structure consisting of a simply supported beam and a moving mass sliding on it. The proposed method is comparatively assessed against an existing recursive pseudo-linear regression TARMA method via Monte Carlo experiments and shown to be capable of accurately tracking the time-varying dynamics. Furthermore, the comparisons demonstrate the superior achievable accuracy, lower computational complexity and enhanced online identification capability of the proposed kernel recursive extended least squares TARMA approach.

Unconventional protein sources: apricot seed kernels.

PubMed

Gabrial, G N; El-Nahry, F I; Awadalla, M Z; Girgis, S M

1981-09-01

Hamawy apricot seed kernels (sweet), Amar apricot seed kernels (bitter) and treated Amar apricot kernels (bitterness removed) were evaluated biochemically. All kernels were found to be high in fat (42.2--50.91%), protein (23.74--25.70%) and fiber (15.08--18.02%). Phosphorus, calcium, and iron were determined in all experimental samples. The three different apricot seed kernels were used for extensive study including the qualitative determination of the amino acid constituents by acid hydrolysis, quantitative determination of some amino acids, and biological evaluation of the kernel proteins in order to use them as new protein sources. Weanling albino rats failed to grow on diets containing the Amar apricot seed kernels due to low food consumption because of its bitterness. There was no loss in weight in that case. The Protein Efficiency Ratio data and blood analysis results showed the Hamawy apricot seed kernels to be higher in biological value than treated apricot seed kernels. The Net Protein Ratio data which accounts for both weight, maintenance and growth showed the treated apricot seed kernels to be higher in biological value than both Hamawy and Amar kernels. The Net Protein Ratio for the last two kernels were nearly equal.

Associations of lifetime walking and weight bearing exercise with accelerometer-measured high impact physical activity in later life.

PubMed

Elhakeem, Ahmed; Hannam, Kimberly; Deere, Kevin C; Hartley, April; Clark, Emma M; Moss, Charlotte; Edwards, Mark H; Dennison, Elaine; Gaysin, Tim; Kuh, Diana; Wong, Andrew; Fox, Kenneth R; Cooper, Cyrus; Cooper, Rachel; Tobias, Jon H

2017-12-01

High impact physical activity (PA) is thought to benefit bone. We examined associations of lifetime walking and weight bearing exercise with accelerometer-measured high impact and overall PA in later life. Data were from 848 participants (66.2% female, mean age = 72.4 years) from the Cohort for Skeletal Health in Bristol and Avon, Hertfordshire Cohort Study and MRC National Survey of Health and Development. Acceleration peaks from seven-day hip-worn accelerometer recordings were used to derive counts of high impact and overall PA. Walking and weight bearing exercise up to age 18, between 18-29, 30-49 and since age 50 were recalled using questionnaires. Responses in each age category were dichotomised and cumulative scores derived. Linear regression was used for analysis. Greater lifetime walking was related to higher overall, but not high impact PA, whereas greater lifetime weight bearing exercise was related to higher overall and high impact PA. For example, fully-adjusted differences in log-overall and log-high impact PA respectively for highest versus lowest lifetime scores were: walking [0.224 (0.087, 0.362) and 0.239 (- 0.058, 0.536)], and weight bearing exercise [0.754 (0.432, 1.076) and 0.587 (0.270, 0.904)]. For both walking and weight bearing exercise, associations were strongest in the 'since age 50' category. Those reporting the most walking and weight bearing exercise since age 50 had highest overall and high impact PA, e.g. fully-adjusted difference in log-high impact PA versus least walking and weight bearing exercise = 0.588 (0.226, 0.951). Promoting walking and weight bearing exercise from midlife may help increase potentially osteogenic PA levels in later life.

Inverse relationship between changes of maximal aerobic capacity and changes in walking economy after weight loss.

PubMed

Borges, Juliano H; Carter, Stephen J; Singh, Harshvardhan; Hunter, Gary R

2018-05-16

The aims of this study were to: (1) determine the relationships between maximum oxygen uptake ([Formula: see text]O 2max ) and walking economy during non-graded and graded walking among overweight women and (2) examine potential differences in [Formula: see text]O 2max and walking economy before and after weight loss. One-hundred and twenty-four premenopausal women with a body mass index (BMI) between 27 and 30 kg/m 2 were randomly assigned to one of three groups: (a) diet only; (b) diet and aerobic exercise training; and (c) diet and resistance exercise training. All were furnished with standard, very-low calorie diet to reduce BMI to < 25 kg/m 2 . [Formula: see text]O 2max was measured using a modified-Bruce protocol while walking economy (1-net [Formula: see text]O 2 ) was obtained during fixed-speed (4.8 k·h -1 ), steady-state treadmill walking at 0% grade and 2.5% grade. Assessments were conducted before and after achieving target BMI. Prior to weight loss, [Formula: see text]O 2max was inversely related (P < 0.05) with non-graded and graded walking economy (r = - 0.28 to - 0.35). Similar results were also observed following weight loss (r = - 0.22 to - 0.28). Additionally, we also detected a significant inverse relationship (P < 0.05) between the changes (∆, after weight loss) in ∆[Formula: see text]O 2max , adjusted for fat-free mass, with non-graded and graded ∆walking economy (r = - 0.37 to - 0.41). Our results demonstrate [Formula: see text]O 2max and walking economy are inversely related (cross-sectional) before and after weight loss. Importantly though, ∆[Formula: see text]O 2max and ∆walking economy were also found to be inversely related, suggesting a strong synchrony between maximal aerobic capacity and metabolic cost of exercise.

Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

PubMed

Maulik, Ujjwal; Sarkar, Anasua

2013-01-01

Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request. sarkar@labri.fr.

Average receiving scaling of the weighted polygon Koch networks with the weight-dependent walk

NASA Astrophysics Data System (ADS)

Ye, Dandan; Dai, Meifeng; Sun, Yanqiu; Shao, Shuxiang; Xie, Qi

2016-09-01

Based on the weighted Koch networks and the self-similarity of fractals, we present a family of weighted polygon Koch networks with a weight factor r(0 < r ≤ 1) . We study the average receiving time (ART) on weight-dependent walk (i.e., the walker moves to any of its neighbors with probability proportional to the weight of edge linking them), whose key step is to calculate the sum of mean first-passage times (MFPTs) for all nodes absorpt at a hub node. We use a recursive division method to divide the weighted polygon Koch networks in order to calculate the ART scaling more conveniently. We show that the ART scaling exhibits a sublinear or linear dependence on network order. Thus, the weighted polygon Koch networks are more efficient than expended Koch networks in receiving information. Finally, compared with other previous studies' results (i.e., Koch networks, weighted Koch networks), we find out that our models are more general.

Regulation of maize kernel weight and carbohydrate metabolism by abscisic acid applied at the early and middle post-pollination stages in vitro.

PubMed

Zhang, Li; Li, Xu-Hui; Gao, Zhen; Shen, Si; Liang, Xiao-Gui; Zhao, Xue; Lin, Shan; Zhou, Shun-Li

2017-09-01

Abscisic acid (ABA) accumulates in plants under drought stress, but views on the role of ABA in kernel formation and abortion are not unified. The response of the developing maize kernel to exogenous ABA was investigated by excising kernels from cob sections at four days after pollination and culturing in vitro with different concentrations of ABA (0, 5, 10, 100μM). When ABA was applied at the early post-pollination stage (EPPS), significant weight loss was observed at high ABA concentration (100μM), which could be attributed to jointly affected sink capacity and activity. Endosperm cells and starch granules were decreased significantly with high concentration, and ABA inhibited the activities of soluble acid invertase and acid cell wall invertase, together with earlier attainment of peak values. When ABA was applied at the middle post-pollination stage (MPPS), kernel weight was observably reduced with high concentration and mildly increased with low concentration, which was regulated due to sink activity. The inhibitory effect of high concentration and the mild stimulatory effect of low concentration on sucrose synthase and starch synthase activities were noted, but a peak level of ADP-glucose pyrophosphorylase (AGPase) was stimulated in all ABA treatments. Interestingly, AGPase peak values were advanced by low concentration and postponed by high concentration. In addition, compared with the control, the weight of low ABA concentration treatments were not statistically significant at the two stages, whereas weight loss from high concentration applied at EPPS was considerably obvious compared with that of the MPPS, but neither led to kernel abortion. The temporal- and dose-dependent impacts of ABA reveal a complex process of maize kernel growth and development. Copyright © 2017 Elsevier GmbH. All rights reserved.

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

PubMed

Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

2014-06-01

In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both

Searching Remote Homology with Spectral Clustering with Symmetry in Neighborhood Cluster Kernels

PubMed Central

Maulik, Ujjwal; Sarkar, Anasua

2013-01-01

Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of “recent” paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request. Contact: sarkar@labri.fr. PMID:23457439

Body weight-supported treadmill training vs. overground walking training for persons with chronic stroke: a pilot randomized controlled trial.

PubMed

Combs-Miller, Stephanie A; Kalpathi Parameswaran, Anu; Colburn, Dawn; Ertel, Tara; Harmeyer, Amanda; Tucker, Lindsay; Schmid, Arlene A

2014-09-01

To compare the effects of body weight-supported treadmill training and overground walking training when matched for task and dose (duration/frequency/intensity) on improving walking function, activity, and participation after stroke. Single-blind, pilot randomized controlled trial with three-month follow-up. University and community settings. A convenience sample of participants (N = 20) at least six months post-stroke and able to walk independently were recruited. Thirty-minute walking interventions (body weight-supported treadmill training or overground walking training) were administered five times a week for two weeks. Intensity was monitored with the Borg Rating of Perceived Exertion Scale at five-minute increments to maintain a moderate training intensity. Walking speed (comfortable/fast 10-meter walk), walking endurance (6-minute walk), spatiotemporal symmetry, and the ICF Measure of Participation and ACTivity were assessed before, immediately after, and three months following the intervention. The overground walking training group demonstrated significantly greater improvements in comfortable walking speed compared with the body weight-supported treadmill training group immediately (change of 0.11 m/s vs. 0.06 m/s, respectively; p = 0.047) and three months (change of 0.14 m/s vs. 0.08 m/s, respectively; p = 0.029) after training. Only the overground walking training group significantly improved comfortable walking speed (p = 0.001), aspects of gait symmetry (p = 0.032), and activity (p = 0.003) immediately after training. Gains were maintained at the three-month follow-up (p < 0.05) for all measures except activity. Improvements in participation were not demonstrated. Overgound walking training was more beneficial than body weight-supported treadmill training at improving self-selected walking speed for the participants in this study. © The Author(s) 2014.

Effects of kernel vitreousness and protein level on protein molecular weight distribution, milling quality, and breadmaking quality in hard red spring wheat

USDA-ARS?s Scientific Manuscript database

Dark, hard, and vitreous kernel content is an important grading characteristic for hard red spring (HRS) wheat in the U.S. This research aimed to determine the associations of kernel vitreousness (KV) with protein molecular weight distribution (MWD) and quality traits that were not biased by quanti...

Unified heat kernel regression for diffusion, kernel smoothing and wavelets on manifolds and its application to mandible growth modeling in CT images.

PubMed

Chung, Moo K; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K

2015-05-01

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel method is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, the method is applied to characterize the localized growth pattern of mandible surfaces obtained in CT images between ages 0 and 20 by regressing the length of displacement vectors with respect to a surface template. Copyright © 2015 Elsevier B.V. All rights reserved.

Metabolic Cost, Mechanical Work, and Efficiency during Normal Walking in Obese and Normal-Weight Children

ERIC Educational Resources Information Center

Huang, Liang; Chen, Peijie; Zhuang, Jie; Zhang, Yanxin; Walt, Sharon

2013-01-01

Purpose: This study aimed to investigate the influence of childhood obesity on energetic cost during normal walking and to determine if obese children choose a walking strategy optimizing their gait pattern. Method: Sixteen obese children with no functional abnormalities were matched by age and gender with 16 normal-weight children. All…

Effect of Body Weight-supported Walking on Exercise Capacity and Walking Speed in Patients with Knee Osteoarthritis: A Randomized Controlled Trial

PubMed Central

Someya, Fujiko

2013-01-01

Abstract Objective: To compare the effect of body-weight-supported treadmill training (BWSTT) and full-body-weight treadmill training (FBWTT) on patients with knee osteoarthritis (OA). Methods: Design was Randomized controlled trial. Patients with knee osteoarthritis (n = 30; mean age, 76.0±7.5 y) were randomly assigned to BWSTT or FBWTT group. All patients performed 20 min walking exercise twice a week for 6 weeks under the supervision of the therapist. Main measures were 10-meter walking test (10MWT), functional reach test (FRT), timed get up and go test (TUG), one-leg standing test, 6-minute walking test (6MWT), the parameters set on the treadmill, MOS Short-Form 36-Item Health Survey (SF36), Japanese Knee Osteoarthritis Measure (JKOM). Results: Twenty-five patients (10 men, 15 women; mean age, 76.5 ± 8.0 y) completed the experiment. Exercise capacity, indicated by the heart rate, was similar in both groups. After 3 weeks of BWSTT, the patients performed significantly better in the 10-m and 6-min walking tests. This was not the case with FBWTT even after 6 weeks training. Pain levels assessed were significantly improved after 3 weeks of BWSTT and 6 weeks of FBWTT. There were no significant improvements in either group assessed by the FRT, one-leg standing time test, TUG, or SF -36 questionnaire. Conclusions: BWSTT enhanced exercise capacity in terms of walking speed and pain reduction after 3 weeks; however, there was no significant improvement in patients' functional abilities or quality of life. PMID:25792901

Cardiometabolic risk after weight loss and subsequent weight regain in overweight and obese postmenopausal women.

PubMed

Beavers, Daniel P; Beavers, Kristen M; Lyles, Mary F; Nicklas, Barbara J

2013-06-01

Little is known about the effect of intentional weight loss and subsequent weight regain on cardiometabolic risk factors in older adults. The objective of this study was to determine how cardiometabolic risk factors change in the year following significant intentional weight loss in postmenopausal women, and if observed changes were affected by weight and fat regain. Eighty, overweight and obese, older women (age = 58.8±5.1 years) were followed through a 5-month weight loss intervention and a subsequent 12-month nonintervention period. Body weight/composition and cardiometabolic risk factors (blood pressure; total, high-density lipoprotein, and low-density lipoprotein cholesterol; triglycerides; fasting glucose and insulin; and Homeostatic Model Assessment of Insulin Resistance) were analyzed at baseline, immediately postintervention, and 6- and 12-months postintervention. Average weight loss during the 5-month intervention was 11.4±4.1kg and 31.4% of lost weight was regained during the 12-month follow-up. On average, all risk factor variables were significantly improved with weight loss but regressed toward baseline values during the year subsequent to weight loss. Increases in total cholesterol, triglycerides, glucose, insulin, and Homeostatic Model Assessment of Insulin Resistance during the postintervention follow-up were significantly (p < .05) associated with weight and fat mass regain. Among women who regained weight, model-adjusted total cholesterol (205.8±4.0 vs 199.7±2.9mg/dL), low-density lipoprotein cholesterol (128.4±3.4 vs 122.7±2.4mg/dL), insulin (12.6±0.7 vs 11.4±0.7mg/dL), and Homeostatic Model Assessment of Insulin Resistance (55.8±3.5 vs 50.9±3.7mg/dL) were higher at follow-up compared with baseline. For postmenopausal women, even partial weight regain following intentional weight loss is associated with increased cardiometabolic risk. Conversely, maintenance of or continued weight loss is associated with sustained improvement in the

Smoking cessation and subsequent weight change.

PubMed

Robertson, Lindsay; McGee, Rob; Hancox, Robert J

2014-06-01

People who quit smoking tend to gain more weight over time than those who continue to smoke. Previous research using clinical samples of smokers suggests that quitters typically experience a weight gain of approximately 5 kg in the year following smoking cessation, but these studies may overestimate the extent of weight gain in the general population. The existing population-based research in this area has some methodological limitations. We assessed a cohort of individuals born in Dunedin, New Zealand, between 1972-1973 at regular intervals from age 15 to 38. We used multiple linear regression analysis to investigate the association between smoking cessation at ages 21 years to 38 years and subsequent change in body mass index (BMI) and weight, controlling for baseline BMI, socioeconomic status, physical activity, alcohol use, and parity (women). Smoking status and outcome data were available at baseline and at follow-up for 914 study members. People who smoked at age 21 and who had quit by age 38 had a BMI on average 1.5 kg/m(2) greater than those who continued to smoke at age 38. This equated to a weight gain of approximately 5.7 kg in men and 5.1 kg in women above that of continuing smokers. However, the weight gain between age 21 and 38 among quitters was not significantly different to that of never-smokers. The amount of long-term weight gained after quitting smoking is likely to be lower than previous estimates based on research with clinical samples. On average, quitters do not experience greater weight gain than never-smokers.

Coactivation of lower leg muscles during body weight-supported treadmill walking decreases with age in adolescents.

PubMed

Deffeyes, Joan E; Karst, Gregory M; Stuberg, Wayne A; Kurz, Max J

2012-08-01

The kinematics of children's walking are nearly adult-like by about age 3-4 years, but metabolic efficiency of walking does not reach adult values until late in adolescence or early adulthood, perhaps due to higher coactivation of agonist/antagonist muscle pairs in adolescents. Additionally, it is unknown how use of a body weight-supported treadmill device affects coactivation, but because unloading will alter the activity of anti-gravity muscles, it was hypothesized that muscle coactivation will be altered as well. Muscle coactivation during treadmill walking was evaluated for adolescents (ages 10 to 17 years, M = 13.2, SD = 2.2) and adults (ages 22 to 35 years, M = 25.2, SD = 4.3), for thigh muscles (vastus lateralis/biceps femoris) and lower leg muscles (tibialis anterior/gastrocnemius). Conditions included body weight unloadings from nearly 0% to 80% of body weight, while walking at a preferred speed (self-selected, overground speed) or a reduced speed. Unloading was accomplished using a lower body positive pressure support system. Coactivation was found to be higher in adolescents than in adults, but only for the lower leg muscles.

Independent genetic control of maize (Zea mays L.) kernel weight determination and its phenotypic plasticity.

PubMed

Alvarez Prado, Santiago; Sadras, Víctor O; Borrás, Lucas

2014-08-01

Maize kernel weight (KW) is associated with the duration of the grain-filling period (GFD) and the rate of kernel biomass accumulation (KGR). It is also related to the dynamics of water and hence is physiologically linked to the maximum kernel water content (MWC), kernel desiccation rate (KDR), and moisture concentration at physiological maturity (MCPM). This work proposed that principles of phenotypic plasticity can help to consolidated the understanding of the environmental modulation and genetic control of these traits. For that purpose, a maize population of 245 recombinant inbred lines (RILs) was grown under different environmental conditions. Trait plasticity was calculated as the ratio of the variance of each RIL to the overall phenotypic variance of the population of RILs. This work found a hierarchy of plasticities: KDR ≈ GFD > MCPM > KGR > KW > MWC. There was no phenotypic and genetic correlation between traits per se and trait plasticities. MWC, the trait with the lowest plasticity, was the exception because common quantitative trait loci were found for the trait and its plasticity. Independent genetic control of a trait per se and genetic control of its plasticity is a condition for the independent evolution of traits and their plasticities. This allows breeders potentially to select for high or low plasticity in combination with high or low values of economically relevant traits. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations.

PubMed

Liu, Zhengbin; Garcia, Arturo; McMullen, Michael D; Flint-Garcia, Sherry A

2016-08-09

Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays) kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis). In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL) for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits. Copyright © 2016 Liu et al.

Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations

PubMed Central

Liu, Zhengbin; Garcia, Arturo; McMullen, Michael D.; Flint-Garcia, Sherry A.

2016-01-01

Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays) kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis). In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL) for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits. PMID:27317774

Dimensional feature weighting utilizing multiple kernel learning for single-channel talker location discrimination using the acoustic transfer function.

PubMed

Takashima, Ryoichi; Takiguchi, Tetsuya; Ariki, Yasuo

2013-02-01

This paper presents a method for discriminating the location of the sound source (talker) using only a single microphone. In a previous work, the single-channel approach for discriminating the location of the sound source was discussed, where the acoustic transfer function from a user's position is estimated by using a hidden Markov model of clean speech in the cepstral domain. In this paper, each cepstral dimension of the acoustic transfer function is newly weighted, in order to obtain the cepstral dimensions having information that is useful for classifying the user's position. Then, this paper proposes a feature-weighting method for the cepstral parameter using multiple kernel learning, defining the base kernels for each cepstral dimension of the acoustic transfer function. The user's position is trained and classified by support vector machine. The effectiveness of this method has been confirmed by sound source (talker) localization experiments performed in different room environments.

Mapping QTLs controlling kernel dimensions in a wheat inter-varietal RIL mapping population.

PubMed

Cheng, Ruiru; Kong, Zhongxin; Zhang, Liwei; Xie, Quan; Jia, Haiyan; Yu, Dong; Huang, Yulong; Ma, Zhengqiang

2017-07-01

Seven kernel dimension QTLs were identified in wheat, and kernel thickness was found to be the most important dimension for grain weight improvement. Kernel morphology and weight of wheat (Triticum aestivum L.) affect both yield and quality; however, the genetic basis of these traits and their interactions has not been fully understood. In this study, to investigate the genetic factors affecting kernel morphology and the association of kernel morphology traits with kernel weight, kernel length (KL), width (KW) and thickness (KT) were evaluated, together with hundred-grain weight (HGW), in a recombinant inbred line population derived from Nanda2419 × Wangshuibai, with data from five trials (two different locations over 3 years). The results showed that HGW was more closely correlated with KT and KW than with KL. A whole genome scan revealed four QTLs for KL, one for KW and two for KT, distributed on five different chromosomes. Of them, QKl.nau-2D for KL, and QKt.nau-4B and QKt.nau-5A for KT were newly identified major QTLs for the respective traits, explaining up to 32.6 and 41.5% of the phenotypic variations, respectively. Increase of KW and KT and reduction of KL/KT and KW/KT ratios always resulted in significant higher grain weight. Lines combining the Nanda 2419 alleles of the 4B and 5A intervals had wider, thicker, rounder kernels and a 14% higher grain weight in the genotype-based analysis. A strong, negative linear relationship of the KW/KT ratio with grain weight was observed. It thus appears that kernel thickness is the most important kernel dimension factor in wheat improvement for higher yield. Mapping and marker identification of the kernel dimension-related QTLs definitely help realize the breeding goals.

Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Images

PubMed Central

Chung, Moo K.; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K.

2014-01-01

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel regression is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. Unlike many previous partial differential equation based approaches involving diffusion, our approach represents the solution of diffusion analytically, reducing numerical inaccuracy and slow convergence. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, we have applied the method in characterizing the localized growth pattern of mandible surfaces obtained in CT images from subjects between ages 0 and 20 years by regressing the length of displacement vectors with respect to the template surface. PMID:25791435

The effects of body weight unloading on kinetics and muscle activity of overweight males during Overground walking.

PubMed

Fischer, Arielle G; Wolf, Alon

2018-02-01

Excess body weight has become a major worldwide health and social epidemic. Training with body weight unloading, is a common method for gait corrections for various neuromuscular impairments. In the present study we assessed the effects of body weight unloading on knee and ankle kinetics and muscle activation of overweight subjects walking overground under various levels of body weight unloading. Ten overweight subjects (25 ≤ BMI < 29.9 kg/m 2 ) walked overground under a control and three (0%, 15%, 30%) body weight unloading experimental conditions. Gait parameters assessed under these conditions included knee and ankle flexion moments and the Electromygraphic activity of the Tibialis Anterior, Lateral Gastrocnemius and Vastus Lateralis. Increasing body weight unloading levels from 0% to 30% was found to significantly reduce the peak knee flexion and ankle plantarflexion moments. Also observed was a significant reduction in muscle activity of the Tibialis Anterior, Lateral Gastrocnemius and Vastus Lateralis under the three body-weight unloading conditions. Our results demonstrate that a reduction of up to 30% overweight subjects' body weight during gait is conducive to a reduction in the knee and ankle flexion moments and in the balancing net quadriceps moment and ankle flexors moment. The newly devised body weight unloading device is therefore an effective method for reducing joint loads allowing overweight people who require controlled weight bearing scenarios to retrain their gait while engaging in sustained walking exercise. Copyright © 2018 Elsevier Ltd. All rights reserved.

Longitudinal associations between sleep duration and subsequent weight gain: A systematic review

PubMed Central

Magee, Lorrie

2011-01-01

Objective To systematically examine the relationship between sleep duration and subsequent weight gain in observational longitudinal human studies Methods Systematic review of twenty longitudinal studies published from 2004-October 31, 2010 Results While adult studies (n=13) reported inconsistent results on the relationship between sleep duration and subsequent weight gain, studies with children (n=7) more consistently reported a positive relationship between short sleep duration and weight gain. Conclusion While shorter sleep duration consistently predicts subsequent weight gain in children, the relationship is not clear in adults. We discuss possible limitations of the current studies: 1.) the diminishing association between short sleep duration on weight gain over time after transition to short sleep, 2.) lack of inclusion of appropriate confounding, mediating, and moderating variables (i.e. sleep complaints and sedentary behavior), and 3.) measurement issues. PMID:21784678

The effect of simulating weight gain on the energy cost of walking in unimpaired children and children with cerebral palsy.

PubMed

Plasschaert, Frank; Jones, Kim; Forward, Malcolm

2008-12-01

To examine the effect of simulating weight gain on the energy cost of walking in children with cerebral palsy (CP) compared with unimpaired children. Repeated measures, matched subjects, controlled. University hospital clinical gait and movement analysis laboratory. Children (n=42) with CP and unimpaired children (n=42). Addition of 10% of body mass in weight belt. Energy cost of walking parameters consisting of walking speed, Physiological Cost Index, Total Heart Beat Index, oxygen uptake (VO2), gross oxygen cost, nondimensional net oxygen cost, and net oxygen cost with speed normalized to height were measured by using a breath-by-breath gas analysis system (K4b2) and a light beam timing gate system arranged around a figure 8 track. Two walking trials were performed in random order, with and the other without wearing a weighted belt. Children with CP and their unimpaired counterparts responded in fundamentally different ways to weight gain. The unimpaired population maintained speed and VO2 but the children with CP trended toward a drop in their speed and an increase in their VO2. The oxygen consumption of children with CP showed a greater dependence on mass than the unimpaired group (P=.043). An increase of a relatively small percentage in body mass began to significantly impact the energy cost of walking in children with CP. This result highlights the need for weight control to sustain the level of functional walking in these children.

Quality changes in macadamia kernel between harvest and farm-gate.

PubMed

Walton, David A; Wallace, Helen M

2011-02-01

Macadamia integrifolia, Macadamia tetraphylla and their hybrids are cultivated for their edible kernels. After harvest, nuts-in-shell are partially dried on-farm and sorted to eliminate poor-quality kernels before consignment to a processor. During these operations, kernel quality may be lost. In this study, macadamia nuts-in-shell were sampled at five points of an on-farm postharvest handling chain from dehusking to the final storage silo to assess quality loss prior to consignment. Shoulder damage, weight of pieces and unsound kernel were assessed for raw kernels, and colour, mottled colour and surface damage for roasted kernels. Shoulder damage, weight of pieces and unsound kernel for raw kernels increased significantly between the dehusker and the final silo. Roasted kernels displayed a significant increase in dark colour, mottled colour and surface damage during on-farm handling. Significant loss of macadamia kernel quality occurred on a commercial farm during sorting and storage of nuts-in-shell before nuts were consigned to a processor. Nuts-in-shell should be dried as quickly as possible and on-farm handling minimised to maintain optimum kernel quality. 2010 Society of Chemical Industry.

Influence of Weight Classification on Walking and Jogging Energy Expenditure Prediction in Women

ERIC Educational Resources Information Center

Heden, Timothy D.; LeCheminant, James D.; Smith, John D.

2012-01-01

The purpose of this study was to determine the influence of weight classification on predicting energy expenditure (EE) in women. Twelve overweight (body mass index [BMI] = 25-29.99 kg/m[superscript 2]) and 12 normal-weight (BMI = 18.5-24.99 kg/m[superscript 2]) women walked and jogged 1,609 m at 1.34 m.s[superscript -1] and 2.23 m.s[superscript…

Reliability and relative weighting of visual and nonvisual information for perceiving direction of self-motion during walking

PubMed Central

Saunders, Jeffrey A.

2014-01-01

Direction of self-motion during walking is indicated by multiple cues, including optic flow, nonvisual sensory cues, and motor prediction. I measured the reliability of perceived heading from visual and nonvisual cues during walking, and whether cues are weighted in an optimal manner. I used a heading alignment task to measure perceived heading during walking. Observers walked toward a target in a virtual environment with and without global optic flow. The target was simulated to be infinitely far away, so that it did not provide direct feedback about direction of self-motion. Variability in heading direction was low even without optic flow, with average RMS error of 2.4°. Global optic flow reduced variability to 1.9°–2.1°, depending on the structure of the environment. The small amount of variance reduction was consistent with optimal use of visual information. The relative contribution of visual and nonvisual information was also measured using cue conflict conditions. Optic flow specified a conflicting heading direction (±5°), and bias in walking direction was used to infer relative weighting. Visual feedback influenced heading direction by 16%–34% depending on scene structure, with more effect with dense motion parallax. The weighting of visual feedback was close to the predictions of an optimal integration model given the observed variability measures. PMID:24648194

Weight maintenance as a tight rope walk - a Grounded Theory study.

PubMed

Lindvall, Kristina; Larsson, Christel; Weinehall, Lars; Emmelin, Maria

2010-02-01

Overweight and obesity are considerable public health problems internationally as well as in Sweden. The long-term results of obesity treatment are modest as reported by other studies. The importance of extending the focus to not only comprise obesity treatment but also prevention of weight gain is therefore being emphasized. However, despite the suggested change in focus there is still no consensus on how to prevent obesity or maintain weight. This study reports findings from a qualitative study focusing on attitudes, behaviors and strategies important for primary weight maintenance in a middle-aged population. In depth interviews were conducted with 23 maintainers and four slight gainers in Sweden. The interviews were transcribed and an analysis of weight maintenance was performed using Grounded Theory. Based on the informants' stories, describing attitudes, behaviors and strategies of importance for primary weight maintenance, a model illustrating the main findings, was constructed. Weight maintenance was seen as "a tightrope walk" and four strategies of significance for this "tightrope walk" were described as "to rely on heritage", "to find the joy", "to find the routine" and "to be in control". Eleven "ideal types" were included in the model to illustrate different ways of relating to the main strategies. These "ideal types" described more specific attitudes and behaviors such as; eating food that is both tasteful and nutritious, and choosing exercise that provides joy. However, other somewhat contradictory behaviors were also found such as; only eating nutritious food regardless of taste, and being physically active to control stress and emotions. This study show great variety with regards to attitudes, strategies and behaviors important for weight maintenance, and considerations need to be taken before putting the model into practice. However, the results from this study can be used within primary health care by enhancing the understanding of how people

Prediction of Heterodimeric Protein Complexes from Weighted Protein-Protein Interaction Networks Using Novel Features and Kernel Functions

PubMed Central

Ruan, Peiying; Hayashida, Morihiro; Maruyama, Osamu; Akutsu, Tatsuya

2013-01-01

Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes. PMID:23776458

A non-synonymous SNP within the isopentenyl transferase 2 locus is associated with kernel weight in Chinese maize inbreds (Zea mays L.).

PubMed

Weng, Jianfeng; Li, Bo; Liu, Changlin; Yang, Xiaoyan; Wang, Hongwei; Hao, Zhuanfang; Li, Mingshun; Zhang, Degui; Ci, Xiaoke; Li, Xinhai; Zhang, Shihuang

2013-07-05

Kernel weight, controlled by quantitative trait loci (QTL), is an important component of grain yield in maize. Cytokinins (CKs) participate in determining grain morphology and final grain yield in crops. ZmIPT2, which is expressed mainly in the basal transfer cell layer, endosperm, and embryo during maize kernel development, encodes an isopentenyl transferase (IPT) that is involved in CK biosynthesis. The coding region of ZmIPT2 was sequenced across a panel of 175 maize inbred lines that are currently used in Chinese maize breeding programs. Only 16 single nucleotide polymorphisms (SNPs) and seven haplotypes were detected among these inbred lines. Nucleotide diversity (π) within the ZmIPT2 window and coding region were 0.347 and 0.0047, respectively, and they were significantly lower than the mean nucleotide diversity value of 0.372 for maize Chromosome 2 (P < 0.01). Association mapping revealed that a single nucleotide change from cytosine (C) to thymine (T) in the ZmIPT2 coding region, which converted a proline residue into a serine residue, was significantly associated with hundred kernel weight (HKW) in three environments (P <0.05), and explained 4.76% of the total phenotypic variation. In vitro characterization suggests that the dimethylallyl diphospate (DMAPP) IPT activity of ZmIPT2-T is higher than that of ZmIPT2-C, as the amounts of adenosine triphosphate (ATP), adenosine diphosphate (ADP), and adenosine monophosphate (AMP) consumed by ZmIPT2-T were 5.48-, 2.70-, and 1.87-fold, respectively, greater than those consumed by ZmIPT2-C. The effects of artificial selection on the ZmIPT2 coding region were evaluated using Tajima's D tests across six subgroups of Chinese maize germplasm, with the most frequent favorable allele identified in subgroup PB (Partner B). These results showed that ZmIPT2, which is associated with kernel weight, was subjected to artificial selection during the maize breeding process. ZmIPT2-T had higher IPT activity than ZmIPT2-C, and

The Combined Effects of Body Weight Support and Gait Speed on Gait Related Muscle Activity: A Comparison between Walking in the Lokomat Exoskeleton and Regular Treadmill Walking

PubMed Central

Van Kammen, Klaske; Boonstra, Annemarijke; Reinders-Messelink, Heleen; den Otter, Rob

2014-01-01

Background For the development of specialized training protocols for robot assisted gait training, it is important to understand how the use of exoskeletons alters locomotor task demands, and how the nature and magnitude of these changes depend on training parameters. Therefore, the present study assessed the combined effects of gait speed and body weight support (BWS) on muscle activity, and compared these between treadmill walking and walking in the Lokomat exoskeleton. Methods Ten healthy participants walked on a treadmill and in the Lokomat, with varying levels of BWS (0% and 50% of the participants’ body weight) and gait speed (0.8, 1.8, and 2.8 km/h), while temporal step characteristics and muscle activity from Erector Spinae, Gluteus Medius, Vastus Lateralis, Biceps Femoris, Gastrocnemius Medialis, and Tibialis Anterior muscles were recorded. Results The temporal structure of the stepping pattern was altered when participants walked in the Lokomat or when BWS was provided (i.e. the relative duration of the double support phase was reduced, and the single support phase prolonged), but these differences normalized as gait speed increased. Alternations in muscle activity were characterized by complex interactions between walking conditions and training parameters: Differences between treadmill walking and walking in the exoskeleton were most prominent at low gait speeds, and speed effects were attenuated when BWS was provided. Conclusion Walking in the Lokomat exoskeleton without movement guidance alters the temporal step regulation and the neuromuscular control of walking, although the nature and magnitude of these effects depend on complex interactions with gait speed and BWS. If normative neuromuscular control of gait is targeted during training, it is recommended that very low speeds and high levels of BWS should be avoided when possible. PMID:25226302

The influence of applying additional weight to the affected leg on gait patterns during aquatic treadmill walking in people poststroke.

PubMed

Jung, Taeyou; Lee, Dokyeong; Charalambous, Charalambos; Vrongistinos, Konstantinos

2010-01-01

Jung T, Lee D, Charalambous C, Vrongistinos K. The influence of applying additional weight to the affected leg on gait patterns during aquatic treadmill walking in people poststroke. To investigate how the application of additional weights to the affected leg influences gait patterns of people poststroke during aquatic treadmill walking. Comparative gait analysis. University-based aquatic therapy center. Community-dwelling volunteers (n=22) with chronic hemiparesis caused by stroke. Not applicable. Spatiotemporal and kinematic gait parameters. The use of an ankle weight showed an increase in the stance phase percentage of gait cycle (3%, P=.015) when compared with no weight. However, the difference was not significant after a Bonferroni adjustment was applied for a more stringent statistical analysis. No significant differences were found in cadence and stride length. The use of an ankle weight showed a significant decrease of the peak hip flexion (7.9%, P=.001) of the affected limb as compared with no weight condition. This decrease was marked as the reduction of unwanted limb flotation because people poststroke typically show excessive hip flexion of the paretic leg in the late swing phase followed by fluctuating hip movements during aquatic treadmill walking. The frontal and transverse plane hip motions did not show any significant differences but displayed a trend of a decrease in the peak hip abduction during the swing phase with additional weights. The use of additional weight did not alter sagittal plane kinematics of the knee and ankle joints. The use of applied weight on the affected limb can reduce unwanted limb flotation on the paretic side during aquatic treadmill walking. It can also assist the stance stability by increasing the stance phase percentage closer to 60% of gait cycle. Both findings can contribute to the development of more efficient motor patterns in gait training for people poststroke. The use of a cuff weight does not seem to reduce the

Nonlinear Deep Kernel Learning for Image Annotation.

PubMed

Jiu, Mingyuan; Sahbi, Hichem

2017-02-08

Multiple kernel learning (MKL) is a widely used technique for kernel design. Its principle consists in learning, for a given support vector classifier, the most suitable convex (or sparse) linear combination of standard elementary kernels. However, these combinations are shallow and often powerless to capture the actual similarity between highly semantic data, especially for challenging classification tasks such as image annotation. In this paper, we redefine multiple kernels using deep multi-layer networks. In this new contribution, a deep multiple kernel is recursively defined as a multi-layered combination of nonlinear activation functions, each one involves a combination of several elementary or intermediate kernels, and results into a positive semi-definite deep kernel. We propose four different frameworks in order to learn the weights of these networks: supervised, unsupervised, kernel-based semisupervised and Laplacian-based semi-supervised. When plugged into support vector machines (SVMs), the resulting deep kernel networks show clear gain, compared to several shallow kernels for the task of image annotation. Extensive experiments and analysis on the challenging ImageCLEF photo annotation benchmark, the COREL5k database and the Banana dataset validate the effectiveness of the proposed method.

Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

PubMed Central

2016-01-01

This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour. PMID:27379165

Metabolic network prediction through pairwise rational kernels.

PubMed

Roche-Lima, Abiel; Domaratzki, Michael; Fristensky, Brian

2014-09-26

Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to another reaction. Many pathways remain incompletely characterized. One of the major challenges of computational biology is to obtain better models of metabolic pathways. Existing models are dependent on the annotation of the genes. This propagates error accumulation when the pathways are predicted by incorrectly annotated genes. Pairwise classification methods are supervised learning methods used to classify new pair of entities. Some of these classification methods, e.g., Pairwise Support Vector Machines (SVMs), use pairwise kernels. Pairwise kernels describe similarity measures between two pairs of entities. Using pairwise kernels to handle sequence data requires long processing times and large storage. Rational kernels are kernels based on weighted finite-state transducers that represent similarity measures between sequences or automata. They have been effectively used in problems that handle large amount of sequence information such as protein essentiality, natural language processing and machine translations. We create a new family of pairwise kernels using weighted finite-state transducers (called Pairwise Rational Kernel (PRK)) to predict metabolic pathways from a variety of biological data. PRKs take advantage of the simpler representations and faster algorithms of transducers. Because raw sequence data can be used, the predictor model avoids the errors introduced by incorrect gene annotations. We then developed several experiments with PRKs and Pairwise SVM to validate our methods using the metabolic network of Saccharomyces cerevisiae. As a result, when PRKs are used, our method executes faster in comparison with other pairwise kernels. Also, when we use PRKs combined with other simple kernels that include evolutionary information, the accuracy

Effect of glycemic index and fructose content in lunch on substrate utilization during subsequent brisk walking.

PubMed

Sun, Feng-Hua; Wong, Stephen Heung-Sang; Chen, Ya-Jun; Huang, Ya-Jun; Hsieh, Sandy Shen-Yu

2011-12-01

The purpose of the present study was to investigate the effect of glycemic index (GI) and fructose content in lunch on substrate utilization during subsequent brisk walking. Ten healthy young males completed 3 main trials in a counterbalanced crossover design. They completed 60 min of brisk walking at approximately 50% maximal oxygen consumption after consuming a standard breakfast and 1 of 3 lunch meals, i.e., a low GI meal without fructose (LGI), a low GI meal that included fructose beverage (LGIF), or a high GI meal (HGI). The 3 lunch meals were isocaloric and provided 1.0 g·kg⁻¹ carbohydrate. Substrate utilization was measured using indirect respiratory calorimetry method. Blood samples were collected at certain time points. During the 2-h postprandial period after lunch, the incremental area under the blood response curve values of glucose and insulin were higher (p < 0.05) in the HGI trial than those in the LGI and LGIF trials (HGI vs. LGI and LGIF: glucose, 223.5 ± 24.4 vs. 92.5 ± 10.4 and 128.0 ± 17.7 mmol·min·L⁻¹; insulin, 3603 ± 593 vs. 1425 ± 289 and 1888 ± 114 mU·min·L⁻¹). During brisk walking, decreased carbohydrate oxidation was observed (p < 0.05) in the LGI trial than in the LGIF and HGI trials (LGI vs. LGIF and HGI: 60.8 ± 4.0 vs. 68.1 ± 6.0 and 74.4 ± 4.7 g). No difference was found in fat oxidation among the 3 trials (LGI vs. LGIF vs. HGI: 21.6 ± 2.3 vs. 19.2 ± 2.3 vs. 16.4 ± 2.2 g). It appeared that fructose content was an important influencing factor when considering the effect of different GI lunch meals on substrate utilization during subsequent moderate intensity exercise.

Body weight-supported gait training for restoration of walking in people with an incomplete spinal cord injury: a systematic review.

PubMed

Wessels, Monique; Lucas, Cees; Eriks, Inge; de Groot, Sonja

2010-06-01

To evaluate the effect of body weight-supported gait training on restoration of walking, activities of daily living, and quality of life in persons with an incomplete spinal cord injury by a systematic review of the literature. Cochrane, MEDLINE, EMBASE, CINAHL, PEDro, DocOnline were searched and identified studies were assessed for eligibility and methodological quality and described regarding population, training protocol, and effects on walking ability, activities of daily living and quality of life. A descriptive and quantitative synthesis was conducted. Eighteen articles (17 studies) were included. Two randomized controlled trials showed that subjects with injuries of less than one year duration reached higher scores on the locomotor item of the Functional Independence Measure (range 1-7) in the over-ground training group compared with the body weight-supported treadmill training group. Only for persons with an American Spinal Injury Association Impairment Scale C or D was the mean difference significant, with 0.80 (95% confidence interval 0.04-1.56). No differences were found regarding walking velocity, activities of daily living or quality of life. Subjects with subacute motor incomplete spinal cord injury reached a higher level of independent walking after over-ground training, compared with body weight-supported treadmill training. More randomized controlled trials are needed to clarify the effectiveness of body weight-supported gait training on walking, activities of daily living, and quality of life for subgroups of persons with an incomplete spinal cord injury.

The six-minute walk test and body weight-walk distance product in healthy Brazilian subjects.

PubMed

Iwama, A M; Andrade, G N; Shima, P; Tanni, S E; Godoy, I; Dourado, V Z

2009-11-01

We assessed the 6-min walk distance (6MWD) and body weight x distance product (6MWw) in healthy Brazilian subjects and compared measured 6MWD with values predicted in five reference equations developed for other populations. Anthropometry, spirometry, reported physical activity, and two walk tests in a 30-m corridor were evaluated in 134 subjects (73 females, 13-84 years). Mean 6MWD and 6MWw were significantly greater in males than in females (622 +/- 80 m, 46,322 +/- 10,539 kg.m vs 551 +/- 71 m, 36,356 +/- 8,289 kg.m, P < 0.05). Four equations significantly overestimated measured 6MWD (range, 32 +/- 71 to 137 +/- 74 m; P < 0.001), and one significantly underestimated it (-36 +/- 86 m; P < 0.001). 6MWD significantly correlated with age (r = -0.39), height (r = 0.44), body mass index (r = -0.24), and reported physical activity (r = 0.25). 6MWw significantly correlated with age (r = -0.21), height (r = 0.66) and reported physical activity (r = 0.25). The reference equation devised for walk distance was 6MWDm = 622.461 - (1.846 x Ageyears) + (61.503 x Gendermales = 1; females = 0); r2 = 0.300. In an additional group of 85 subjects prospectively studied, the difference between measured and the 6MWD predicted with the equation proposed here was not significant (-3 +/- 68 m; P = 0.938). The measured 6MWD represented 99.6 +/- 11.9% of the predicted value. We conclude that 6MWD and 6MWw variances were adequately explained by demographic and anthropometric attributes. This reference equation is probably most appropriate for evaluating the exercise capacity of Brazilian patients with chronic diseases.

Do we really need a large number of particles to simulate bimolecular reactive transport with random walk methods? A kernel density estimation approach

NASA Astrophysics Data System (ADS)

Rahbaralam, Maryam; Fernàndez-Garcia, Daniel; Sanchez-Vila, Xavier

2015-12-01

Random walk particle tracking methods are a computationally efficient family of methods to solve reactive transport problems. While the number of particles in most realistic applications is in the order of 106-109, the number of reactive molecules even in diluted systems might be in the order of fractions of the Avogadro number. Thus, each particle actually represents a group of potentially reactive molecules. The use of a low number of particles may result not only in loss of accuracy, but also may lead to an improper reproduction of the mixing process, limited by diffusion. Recent works have used this effect as a proxy to model incomplete mixing in porous media. In this work, we propose using a Kernel Density Estimation (KDE) of the concentrations that allows getting the expected results for a well-mixed solution with a limited number of particles. The idea consists of treating each particle as a sample drawn from the pool of molecules that it represents; this way, the actual location of a tracked particle is seen as a sample drawn from the density function of the location of molecules represented by that given particle, rigorously represented by a kernel density function. The probability of reaction can be obtained by combining the kernels associated to two potentially reactive particles. We demonstrate that the observed deviation in the reaction vs time curves in numerical experiments reported in the literature could be attributed to the statistical method used to reconstruct concentrations (fixed particle support) from discrete particle distributions, and not to the occurrence of true incomplete mixing. We further explore the evolution of the kernel size with time, linking it to the diffusion process. Our results show that KDEs are powerful tools to improve computational efficiency and robustness in reactive transport simulations, and indicates that incomplete mixing in diluted systems should be modeled based on alternative mechanistic models and not on a

Limb contribution to increased self-selected walking speeds during body weight support in individuals poststroke.

PubMed

Hurt, Christopher P; Burgess, Jamie K; Brown, David A

2015-03-01

Individuals poststroke walk at faster self-selected speeds under some nominal level of body weight support (BWS) whereas nonimpaired individuals walk slower after adding BWS. The purpose of this study was to determine whether increases in self-selected overground walking speed under BWS conditions of individuals poststroke can be explained by changes in their paretic and nonparetic ground reaction forces (GRF). We hypothesize that increased self-selected walking speed, recorded at some nominal level of BWS, will relate to decreased braking GRFs by the paretic limb. We recruited 10 chronic (>12 months post-ictus, 57.5±9.6 y.o.) individuals poststroke and eleven nonimpaired participants (53.3±4.1 y.o.). Participants walked overground in a robotic device, the KineAssist Walking and Balance Training System that provided varying degrees of BWS (0-20% in 5% increments) while individuals self-selected their walking speed. Self-selected walking speed and braking and propulsive GRF impulses were quantified. Out of 10 poststroke individuals, 8 increased their walking speed 13% (p=0.004) under some level of BWS (5% n=2, 10% n=3, 20% n=3) whereas nonimpaired controls did not change speed (p=0.470). In individuals poststroke, changes to self-selected walking speed were correlated with changes in paretic propulsive impulses (r=0.68, p=0.003) and nonparetic braking impulses (r=-0.80, p=0.006), but were not correlated with decreased paretic braking impulses (r=0.50 p=0.14). This investigation demonstrates that when individuals poststroke are provided with BWS and allowed to self-select their overground walking speed, they are capable of achieving faster speeds by modulating braking impulses on the nonparetic limb and propulsive impulses of the paretic limb. Copyright © 2015 Elsevier B.V. All rights reserved.

Differential Associations of Walking and Cycling with Body Weight, Body Fat and Fat Distribution - the ACTI-Cités Project.

PubMed

Menai, Mehdi; Charreire, Hélène; Galan, Pilar; Simon, Chantal; Nazare, Julie-Anne; Perchoux, Camille; Weber, Christiane; Enaux, Christophe; Hercberg, Serge; Fezeu, Léopold; Oppert, Jean-Michel

2018-06-22

Research on the associations between walking and cycling with obesity-related phenotypes is growing but relies mostly on the use of BMI. The purpose of this study was to analyze associations of walking and cycling behaviors assessed separately with various obesity markers in French adults. In 12,776 adult participants (71.3% women) of the on-going NutriNet Santé web-cohort, we assessed by self-report past-month walking and cycling (for commuting, errands and leisure), and obesity measures were taken during a visit at a clinical center (weight, height, waist circumference, and percent body fat by bioimpedance). In analyses not taking into account other types of physical activity (household, leisure), walking more than 2.5 h/week was associated in women with lower weight (-1.8 kg), waist circumference (-1.7 cm) and percent body fat (-1.1%) (all p < 0.001). Cycling more than 1.5 h/week was associated in men and women with lower weight (-4.3 and -1.4 kg, respectively), waist circumference (-4.4 and -2.1 cm, respectively), and percent body fat (-2.5 and -1.9 % respectively) (all p < 0.001). Results were unaltered when analyses were further adjusted on household and leisure physical activity. These results show important differences between walking and cycling in their association with obesity markers in men and women. These findings provide some evidence for the need to consider separately walking and cycling when designing public health measures for prevention of obesity in adults. © 2018 The Author(s) Published by S. Karger GmbH, Freiburg.

Improved modeling of clinical data with kernel methods.

PubMed

Daemen, Anneleen; Timmerman, Dirk; Van den Bosch, Thierry; Bottomley, Cecilia; Kirk, Emma; Van Holsbeke, Caroline; Valentin, Lil; Bourne, Tom; De Moor, Bart

2012-02-01

Despite the rise of high-throughput technologies, clinical data such as age, gender and medical history guide clinical management for most diseases and examinations. To improve clinical management, available patient information should be fully exploited. This requires appropriate modeling of relevant parameters. When kernel methods are used, traditional kernel functions such as the linear kernel are often applied to the set of clinical parameters. These kernel functions, however, have their disadvantages due to the specific characteristics of clinical data, being a mix of variable types with each variable its own range. We propose a new kernel function specifically adapted to the characteristics of clinical data. The clinical kernel function provides a better representation of patients' similarity by equalizing the influence of all variables and taking into account the range r of the variables. Moreover, it is robust with respect to changes in r. Incorporated in a least squares support vector machine, the new kernel function results in significantly improved diagnosis, prognosis and prediction of therapy response. This is illustrated on four clinical data sets within gynecology, with an average increase in test area under the ROC curve (AUC) of 0.023, 0.021, 0.122 and 0.019, respectively. Moreover, when combining clinical parameters and expression data in three case studies on breast cancer, results improved overall with use of the new kernel function and when considering both data types in a weighted fashion, with a larger weight assigned to the clinical parameters. The increase in AUC with respect to a standard kernel function and/or unweighted data combination was maximum 0.127, 0.042 and 0.118 for the three case studies. For clinical data consisting of variables of different types, the proposed kernel function--which takes into account the type and range of each variable--has shown to be a better alternative for linear and non-linear classification problems

The effects of postexercise consumption of high-molecular-weight versus low-molecular-weight carbohydrate solutions on subsequent high-intensity interval-running capacity.

PubMed

McGlory, Chris; Morton, James P

2010-10-01

The aim of this study was to determine the effects of postexercise ingestion of different-molecular-weight glucose polymer solutions on subsequent high-intensity interval-running capacity. In a repeated-measures design, 6 men ran for 60 min in the morning at 70% VO2max. Immediately post- and at 1 and 2 hr postexercise, participants consumed a 15% low-molecular-weight (LMW) or high-molecular-weight (HMW) carbohydrate solution, at a rate of 1.2 g of carbohydrate/kg body mass, or an equivalent volume of flavored water (WAT). After recovery, participants performed repeated 1-min intervals at 90% VO2max interspersed with 1 min active recovery (walking) until volitional exhaustion. Throughout the 3-hr recovery period, plasma glucose concentrations were higher (p=.002) during the HMW and LMW conditions than with WAT (M 7.0±0.8, 7.5±1.0, and 5.6±0.2 mmol/L, respectively), although there was no difference (p=.723) between HMW and LMW conditions. Exercise capacity was 13 (43±10 min; 95% CI for differences: 8-18; p=.001) and 11 min (41±9 min; 95% CI for differences; 2-18: p=.016) longer with HMW and LMW solutions, respectively, than with WAT (30±9 min). There was no substantial difference (2 min; 95% CI for differences: -5 to 10; p=.709) in exercise capacity between LMW and HMW solutions. Although this magnitude of difference is most likely trivial in nature, the uncertainty allows for a possible small substantial enhancement of physiological significance, and further research is required to clarify the true nature of the effect.

Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels.

PubMed

Cid, Jaime A; von Davier, Alina A

2015-05-01

Test equating is a method of making the test scores from different test forms of the same assessment comparable. In the equating process, an important step involves continuizing the discrete score distributions. In traditional observed-score equating, this step is achieved using linear interpolation (or an unscaled uniform kernel). In the kernel equating (KE) process, this continuization process involves Gaussian kernel smoothing. It has been suggested that the choice of bandwidth in kernel smoothing controls the trade-off between variance and bias. In the literature on estimating density functions using kernels, it has also been suggested that the weight of the kernel depends on the sample size, and therefore, the resulting continuous distribution exhibits bias at the endpoints, where the samples are usually smaller. The purpose of this article is (a) to explore the potential effects of atypical scores (spikes) at the extreme ends (high and low) on the KE method in distributions with different degrees of asymmetry using the randomly equivalent groups equating design (Study I), and (b) to introduce the Epanechnikov and adaptive kernels as potential alternative approaches to reducing boundary bias in smoothing (Study II). The beta-binomial model is used to simulate observed scores reflecting a range of different skewed shapes.

Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.

PubMed

Ma, Yuntao; Chen, Youjia; Zhu, Jinyu; Meng, Lei; Guo, Yan; Li, Baoguo; Hoogenboom, Gerrit

2018-02-13

Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel). The model used potential individual kernel growth rates to characterize the individual potential sink demand. The remobilization of non-structural carbohydrates from reserve organs to kernels was also incorporated. Two years of field experiments were conducted to determine the model parameter values and to evaluate the model using two maize hybrids with different plant densities and pollination treatments. Detailed observations were made on the dimensions and dry weights of individual kernels and other above-ground plant organs throughout the seasons. Three basic traits characterizing an individual kernel were compared on simulated and measured individual kernels: (1) final kernel size; (2) kernel growth rate; and (3) duration of kernel filling. Simulations of individual kernel growth closely corresponded to experimental data. The model was able to reproduce the observed dry weight of plant organs well. Then, the source-sink dynamics and the remobilization of carbohydrates for kernel growth were quantified to show that remobilization processes accompanied source-sink dynamics during the kernel-filling process. We conclude that the model may be used to explore options for optimizing plant kernel yield by matching maize management to the environment, taking into account responses at the level of individual kernels. © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Effect of leg length inequality on body weight distribution during walking with load: A pilot study

NASA Astrophysics Data System (ADS)

Zabri, S. W. K. Ali; Basaruddin, K. S.; Salleh, A. F.; Rusli, W. M. R.; Daud, R.

2017-09-01

This paper presents a pilot study on the effect of leg length inequality (LLI) on the body weight distribution. Plywood block was used to mimic the artificial LLI. The height of the plywood was increased up to 4.0 cm with 0.5 cm increment. Hence, eight different height of LLI was considered in order to investigate which height of LLI initiated the significant effect. The experiment was conducted on a healthy subject that walking on the force plate in two conditions; with a load of 2 kg (carried by a backpack worn by the subject) and without load. Qualisys Track Manager (QTM) system was employed for data processing. The results showed that the short leg subjected to more weight compared to the long leg during walking with inequality of leg length especially when carrying additional load.

Multiple kernel learning in protein-protein interaction extraction from biomedical literature.

PubMed

Yang, Zhihao; Tang, Nan; Zhang, Xiao; Lin, Hongfei; Li, Yanpeng; Yang, Zhiwei

2011-03-01

Knowledge about protein-protein interactions (PPIs) unveils the molecular mechanisms of biological processes. The volume and content of published biomedical literature on protein interactions is expanding rapidly, making it increasingly difficult for interaction database administrators, responsible for content input and maintenance to detect and manually update protein interaction information. The objective of this work is to develop an effective approach to automatic extraction of PPI information from biomedical literature. We present a weighted multiple kernel learning-based approach for automatic PPI extraction from biomedical literature. The approach combines the following kernels: feature-based, tree, graph and part-of-speech (POS) path. In particular, we extend the shortest path-enclosed tree (SPT) and dependency path tree to capture richer contextual information. Our experimental results show that the combination of SPT and dependency path tree extensions contributes to the improvement of performance by almost 0.7 percentage units in F-score and 2 percentage units in area under the receiver operating characteristics curve (AUC). Combining two or more appropriately weighed individual will further improve the performance. Both on the individual corpus and cross-corpus evaluation our combined kernel can achieve state-of-the-art performance with respect to comparable evaluations, with 64.41% F-score and 88.46% AUC on the AImed corpus. As different kernels calculate the similarity between two sentences from different aspects. Our combined kernel can reduce the risk of missing important features. More specifically, we use a weighted linear combination of individual kernels instead of assigning the same weight to each individual kernel, thus allowing the introduction of each kernel to incrementally contribute to the performance improvement. In addition, SPT and dependency path tree extensions can improve the performance by including richer context information

Weight-control behaviors and subsequent weight change among adolescents and young adult females123

PubMed Central

Haines, Jess; Rosner, Bernard; Willett, Walter C

2010-01-01

Background: Little is known about the effectiveness of behavioral strategies to prevent long-term weight gain among adolescents and young adults. Objective: The objective was to assess the relation of dietary and physical activity weight-control strategies, alone and together, with subsequent weight change. Design: This was a prospective study of 4456 female adolescents and young adults aged 14–22 y in the ongoing Growing Up Today Study. Weight-control behaviors, including dietary approaches and physical activity, were self-reported in 2001 and were used to predict weight change from 2001 to 2005. Results: In 2001–2002, 23.7% of female adolescents and young adults were trying to maintain their weight and another 54.4% were trying to lose weight. Approximately 25% used each of the following weight-control strategies: not eating snacks, following low-calorie or low-fat diets, and limiting portion sizes. In addition, 47.7% reported exercising at least occasionally for weight control. During 4 y of follow-up, participants gained an average of 3.3 kg. None of the dietary approaches to weight control predicted less weight change; however, females who exercised ≥5 d/wk gained significantly less weight than did their peers (−0.9 kg; 95% CI: −1.4, −0.4). The most successful strategy for weight-gain prevention among the females was to limit portion sizes (−1.9 kg; 95% CI: −2.6, −1.1) combined with frequent exercise. Conclusions: Our results suggest that physical activity is a necessary strategy for long-term weight control among adolescents and young adult females. Combining dietary weight-control approaches with physical activity is the most effective method for reducing weight gain. PMID:19889827

Maximum of the modulus of kernels in Gauss-Turan quadratures

NASA Astrophysics Data System (ADS)

Milovanovic, Gradimir V.; Spalevic, Miodrag M.; Pranic, Miroslav S.

2008-06-01

We study the kernels K_{n,s}(z) in the remainder terms R_{n,s}(f) of the Gauss-Turan quadrature formulae for analytic functions on elliptical contours with foci at pm 1 , when the weight omega is a generalized Chebyshev weight function. For the generalized Chebyshev weight of the first (third) kind, it is shown that the modulus of the kernel \\vert K_{n,s}(z)\\vert attains its maximum on the real axis (positive real semi-axis) for each ngeq n_0, n_0Dn_0(rho,s) . It was stated as a conjecture in [Mathematics of Computation 72 (2003), 1855-1872]. For the generalized Chebyshev weight of the second kind, in the case when the number of the nodes n in the corresponding Gauss-Turan quadrature formula is even, it is shown that the modulus of the kernel attains its maximum on the imaginary axis for each ngeq n_0, n_0Dn_0(rho,s) . Numerical examples are included. Retrieve articles in all Journals with MSC (1991): [41]41A55, [42]65D30, [43]65D32

Locally adaptive methods for KDE-based random walk models of reactive transport in porous media

NASA Astrophysics Data System (ADS)

Sole-Mari, G.; Fernandez-Garcia, D.

2017-12-01

Random Walk Particle Tracking (RWPT) coupled with Kernel Density Estimation (KDE) has been recently proposed to simulate reactive transport in porous media. KDE provides an optimal estimation of the area of influence of particles which is a key element to simulate nonlinear chemical reactions. However, several important drawbacks can be identified: (1) the optimal KDE method is computationally intensive and thereby cannot be used at each time step of the simulation; (2) it does not take advantage of the prior information about the physical system and the previous history of the solute plume; (3) even if the kernel is optimal, the relative error in RWPT simulations typically increases over time as the particle density diminishes by dilution. To overcome these problems, we propose an adaptive branching random walk methodology that incorporates the physics, the particle history and maintains accuracy with time. The method allows particles to efficiently split and merge when necessary as well as to optimally adapt their local kernel shape without having to recalculate the kernel size. We illustrate the advantage of the method by simulating complex reactive transport problems in randomly heterogeneous porous media.

Walking velocity and step length adjustments affect knee joint contact forces in healthy weight and obese adults.

PubMed

Milner, Clare E; Meardon, Stacey A; Hawkins, Jillian L; Willson, John D

2018-04-28

Knee osteoarthritis is a major public health problem and adults with obesity are particularly at risk. One approach to alleviating this problem is to reduce the mechanical load at the joint during daily activity. Adjusting temporospatial parameters of walking could mitigate cumulative knee joint mechanical loads. The purpose of this study was to determine how adjustments to velocity and step length affects knee joint loading in healthy weight adults and adults with obesity. We collected three-dimensional gait analysis data on 10 adults with a normal body mass index and 10 adults with obesity during over ground walking in nine different conditions. In addition to preferred velocity and step length, we also conducted combinations of 15% increased and decreased velocity and step length. Peak tibiofemoral joint impulse and knee adduction angular impulse were reduced in the decreased step length conditions in both healthy weight adults (main effect) and those with obesity (interaction effect). Peak knee joint adduction moment was also reduced with decreased step length, and with decreased velocity in both groups. We conclude from these results that adopting shorter step lengths during daily activity and when walking for exercise can reduce mechanical stimuli associated with articular cartilage degenerative processes in adults with and without obesity. Thus, walking with reduced step length may benefit adults at risk for disability due to knee osteoarthritis. Adopting a shorter step length during daily walking activity may reduce knee joint loading and thus benefit those at risk for knee cartilage degeneration. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 9999:XX-XX, 2018. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Walking Wellness. Student Workbook.

ERIC Educational Resources Information Center

Sweetgall, Robert; Neeves, Robert

This comprehensive student text and workbook, for grades four through eight, contains 16 workshop units focusing on walking field trips, aerobic pacing concepts, walking techniques, nutrition, weight control and healthy life-style planning. Co-ordinated homework assignments are included. The appendixes include 10 tips for walking, a calorie chart,…

Geographically weighted regression model on poverty indicator

NASA Astrophysics Data System (ADS)

Slamet, I.; Nugroho, N. F. T. A.; Muslich

2017-12-01

In this research, we applied geographically weighted regression (GWR) for analyzing the poverty in Central Java. We consider Gaussian Kernel as weighted function. The GWR uses the diagonal matrix resulted from calculating kernel Gaussian function as a weighted function in the regression model. The kernel weights is used to handle spatial effects on the data so that a model can be obtained for each location. The purpose of this paper is to model of poverty percentage data in Central Java province using GWR with Gaussian kernel weighted function and to determine the influencing factors in each regency/city in Central Java province. Based on the research, we obtained geographically weighted regression model with Gaussian kernel weighted function on poverty percentage data in Central Java province. We found that percentage of population working as farmers, population growth rate, percentage of households with regular sanitation, and BPJS beneficiaries are the variables that affect the percentage of poverty in Central Java province. In this research, we found the determination coefficient R2 are 68.64%. There are two categories of district which are influenced by different of significance factors.

Aflatoxin contamination of developing corn kernels.

PubMed

Amer, M A

2005-01-01

Preharvest of corn and its contamination with aflatoxin is a serious problem. Some environmental and cultural factors responsible for infection and subsequent aflatoxin production were investigated in this study. Stage of growth and location of kernels on corn ears were found to be one of the important factors in the process of kernel infection with A. flavus & A. parasiticus. The results showed positive correlation between the stage of growth and kernel infection. Treatment of corn with aflatoxin reduced germination, protein and total nitrogen contents. Total and reducing soluble sugar was increase in corn kernels as response to infection. Sucrose and protein content were reduced in case of both pathogens. Shoot system length, seeding fresh weigh and seedling dry weigh was also affected. Both pathogens induced reduction of starch content. Healthy corn seedlings treated with aflatoxin solution were badly affected. Their leaves became yellow then, turned brown with further incubation. Moreover, their total chlorophyll and protein contents showed pronounced decrease. On the other hand, total phenolic compounds were increased. Histopathological studies indicated that A. flavus & A. parasiticus could colonize corn silks and invade developing kernels. Germination of A. flavus spores was occurred and hyphae spread rapidly across the silk, producing extensive growth and lateral branching. Conidiophores and conidia had formed in and on the corn silk. Temperature and relative humidity greatly influenced the growth of A. flavus & A. parasiticus and aflatoxin production.

Influence of the amount of body weight support on lower limb joints' kinematics during treadmill walking at different gait speeds: Reference data on healthy adults to define trajectories for robot assistance.

PubMed

Ferrarin, Maurizio; Rabuffetti, Marco; Geda, Elisabetta; Sirolli, Silvia; Marzegan, Alberto; Bruno, Valentina; Sacco, Katiuscia

2018-06-01

Several robotic devices have been developed for the rehabilitation of treadmill walking in patients with movement disorders due to injuries or diseases of the central nervous system. These robots induce coordinated multi-joint movements aimed at reproducing the physiological walking or stepping patterns. Control strategies developed for robotic locomotor training need a set of predefined lower limb joint angular trajectories as reference input for the control algorithm. Such trajectories are typically taken from normative database of overground unassisted walking. However, it has been demonstrated that gait speed and the amount of body weight support significantly influence joint trajectories during walking. Moreover, both the speed and the level of body weight support must be individually adjusted according to the rehabilitation phase and the residual locomotor abilities of the patient. In this work, 10 healthy participants (age range: 23-48 years) were asked to walk in movement analysis laboratory on a treadmill at five different speeds and four different levels of body weight support; besides, a trial with full body weight support, that is, with the subject suspended on air, was performed at two different cadences. The results confirm that lower limb kinematics during walking is affected by gait speed and by the amount of body weight support, and that on-air stepping is radically different from treadmill walking. Importantly, the results provide normative data in a numerical form to be used as reference trajectories for controlling robot-assisted body weight support walking training. An electronic addendum is provided to easily access to such reference data for different combinations of gait speeds and body weight support levels.

"You've got to walk before you run": positive evaluations of a walking program as part of a gender-sensitized, weight-management program delivered to men through professional football clubs.

PubMed

Hunt, Kate; McCann, Claire; Gray, Cindy M; Mutrie, Nanette; Wyke, Sally

2013-01-01

To explore men's views of a pedometer-based walking program, part of a weight-management intervention delivered through Scottish Premier League football clubs, and the congruence or challenge this poses to masculine identities. Semistructured telephone interviews with a sample of participants in a gender-sensitized, group weight-management program. Interviewing continued until data saturation was reached (n = 29). All men were positive about the context, style of delivery, and content of the broader intervention. These things encouraged men to increase their physical activity (and adopt other behavioral changes) that they may not otherwise have found appealing. The success and acceptability of the walking program resided in three interrelated factors: (a) the utility of pedometers as a technology for motivation, self-monitoring and surveillance, and target setting; (b) the speed with which fitness was regained and weight reduced (enabling men to begin to do more desired forms of physical activity, and so regain visceral, experiential, and pragmatic masculine capital); and (c) bolstering their masculine identities through the receipt of the program in a valued, masculinised context. These data suggest that men will enthusiastically embrace a graduated walking program when the presentation is gender sensitive in context, content, and delivery. Pedometers were viewed as a valuable, reliable technological aid which motivated men and empowered them in self-monitoring of progress toward self-defined goals. Many men experienced the walking program as a means of regaining fitness, thereby enabling them to also regain valued masculine identities and activities, and a step toward regaining a more acceptable masculine body. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Body weight support during robot-assisted walking: influence on the trunk and pelvis kinematics.

PubMed

Swinnen, Eva; Baeyens, Jean-Pierre; Hens, Gerrit; Knaepen, Kristel; Beckwée, David; Michielsen, Marc; Clijsen, Ron; Kerckhofs, Eric

2015-01-01

Efficacy studies concerning robot assisted gait rehabilitation showed limited clinical benefits. A changed kinematic pattern might be responsible for this. Little is known about the kinematics of the trunk and pelvis during robot assisted treadmill walking (RATW). The aim of this study was to assess the trunk and pelvis kinematics of healthy subjects during RATW, with different amounts of body weight support (BWS) compared to regular treadmill walking (TW). Eighteen healthy participants walked on a treadmill, while kinematics were registered by an electromagnetic tracking device. Hereafter, the kinematics of pelvis and trunk were registered during RATW (guidance force 30%) with 0%, 30% and 50% BWS. Compared to TW, RATW showed a decrease in the following trunk movements: axial rotation, anteroposterior flexion, lateral and anteroposterior translation. Besides, a decrease in lateral tilting and all translation of the pelvis was found when comparing RATW with TW. Furthermore, the anteroposterior tilting of the pelvis increased during RATW. In general, there was a decrease in trunk and pelvis movement amplitude during RATW compared with regular TW. Though, it is not known if these changes are responsible for the limited efficacy of robot assisted gait rehabilitation. Further research is indicated.

Body Weight Estimation for Dose-Finding and Health Monitoring of Lying, Standing and Walking Patients Based on RGB-D Data.

PubMed

Pfitzner, Christian; May, Stefan; Nüchter, Andreas

2018-04-24

This paper describes the estimation of the body weight of a person in front of an RGB-D camera. A survey of different methods for body weight estimation based on depth sensors is given. First, an estimation of people standing in front of a camera is presented. Second, an approach based on a stream of depth images is used to obtain the body weight of a person walking towards a sensor. The algorithm first extracts features from a point cloud and forwards them to an artificial neural network (ANN) to obtain an estimation of body weight. Besides the algorithm for the estimation, this paper further presents an open-access dataset based on measurements from a trauma room in a hospital as well as data from visitors of a public event. In total, the dataset contains 439 measurements. The article illustrates the efficiency of the approach with experiments with persons lying down in a hospital, standing persons, and walking persons. Applicable scenarios for the presented algorithm are body weight-related dosing of emergency patients.

Body Weight Estimation for Dose-Finding and Health Monitoring of Lying, Standing and Walking Patients Based on RGB-D Data

PubMed Central

May, Stefan

2018-01-01

This paper describes the estimation of the body weight of a person in front of an RGB-D camera. A survey of different methods for body weight estimation based on depth sensors is given. First, an estimation of people standing in front of a camera is presented. Second, an approach based on a stream of depth images is used to obtain the body weight of a person walking towards a sensor. The algorithm first extracts features from a point cloud and forwards them to an artificial neural network (ANN) to obtain an estimation of body weight. Besides the algorithm for the estimation, this paper further presents an open-access dataset based on measurements from a trauma room in a hospital as well as data from visitors of a public event. In total, the dataset contains 439 measurements. The article illustrates the efficiency of the approach with experiments with persons lying down in a hospital, standing persons, and walking persons. Applicable scenarios for the presented algorithm are body weight-related dosing of emergency patients. PMID:29695098

A self-calibrated angularly continuous 2D GRAPPA kernel for propeller trajectories

PubMed Central

Skare, Stefan; Newbould, Rexford D; Nordell, Anders; Holdsworth, Samantha J; Bammer, Roland

2008-01-01

The k-space readout of propeller-type sequences may be accelerated by the use of parallel imaging (PI). For PROPELLER, the main benefits are reduced blurring due to T2 decay and SAR reduction, while for EPI-based propeller acquisitions such as Turbo-PROP and SAP-EPI, the faster k-space traversal alleviates geometric distortions. In this work, the feasibility of calculating a 2D GRAPPA kernel on only the undersampled propeller blades themselves is explored, using the matching orthogonal undersampled blade. It is shown that the GRAPPA kernel varies slowly across blades, therefore an angularly continuous 2D GRAPPA kernel is proposed, in which the angular variation of the weights is parameterized. This new angularly continuous kernel formulation greatly increases the numerical stability of the GRAPPA weight estimation, allowing the generation of fully sampled diagnostic quality images using only the undersampled propeller data. PMID:19025911

Changes in job strain and subsequent weight gain: a longitudinal study, based on the Danish Nurse Cohort.

PubMed

Vesterlund, Gitte Kingo; Keller, Amélie Cléo; Heitmann, Berit Lilienthal

2018-04-01

Obesity as well as job strain is increasing, and job strain might contribute to weight gain. The objective of the current study was to examine associations between longitudinal alterations in the components of job strain and subsequent weight gain. The study was designed as a prospective cohort study with three questionnaire surveys enabling measurement of job-strain alterations over 6 years and subsequent measurements of weight gain after further 10 years of follow-up. ANCOVA and trend analyses were conducted. Job demands were measured as job busyness and speed, and control as amount of influence. Employed nurses in Denmark. We included a sub-sample of 6188 female nurses from the Danish Nurse Cohort, which consisted of the nurses who participated in surveys in 1993, 1999 and 2009. A linear trend in weight gain was seen in nurses who were often busy in 1999 between those who were rarely v. sometimes v. often busy in 1993 (P=0·03), with the largest weight gain in individuals with sustained high busyness in both years. Loss of influence between 1993 and 1999 was associated with larger subsequent weight gain than sustained high influence (P=0·003) or sustained low influence (P=0·02). For speed, no associations were found. Busyness, speed and influence differed in their relationship to subsequent weight gain. A decrease in job influence and a sustained burden of busyness were most strongly related to subsequent weight gain. Focus on job strain reduction and healthy diet is essential for public health.

Carcass characteristics and meat quality of lambs that are fed diets with palm kernel cake.

PubMed

da Conceição Dos Santos, Rozilda; Gomes, Daiany Iris; Alves, Kaliandra Souza; Mezzomo, Rafael; Oliveira, Luis Rennan Sampaio; Cutrim, Darley Oliveira; Sacramento, Samara Bianca Moraes; de Moura Lima, Elizanne; de Carvalho, Francisco Fernando Ramos

2017-06-01

The aim was to evaluate carcass characteristics, cut yield, and meat quality in lambs that were fed different inclusion levels of palm kernel cake. Forty-five woolless castrated male Santa Inês crossbred sheep with an initial average body weight of 23.16±0.35 kg were used. The experimental design was a completely randomized design with five treatments, with palm kernel cake in the proportions of 0.0%, 7.5%, 15.0%, 22.5%, and 30.0% with nine replications per treatment. After slaughter, the gastrointestinal tract was weighed when it was full, after which it was then emptied. The heart, liver, kidney, pancreas perirenal fat were also collected and weighed. The carcass was split into two identical longitudinal halves and weighed to determine the quantitative and qualitative characteristics. The empty body weight, carcass weight and yield, and fat thickness decreased linearly (p<0.05) as a function of palm kernel inclusion in the diet. There was no difference (p>0.05) for the rib eye area of animals that were fed palm kernel cake. There was a reduction in the commercial cut weight (p<0.05), except for the neck weight. The weights of the heart, liver, kidney fat, small, and large intestine, and gastrointestinal tract decreased. Nevertheless, the gastrointestinal content was greater for animals that were fed increasing levels of cake. For the other organs and viscera, differences were not verified (p>0.05). The sarcomere length decreased linearly (p<0.05), although an effect of the inclusion of palm kernel cake was not observed in other meat quality variables. It is worth noting that the red staining intensity, indicated as A, had a tendency to decrease (p = 0.050). The inclusion of palm kernel cake up to 30% in the diet does not lead to changes in meat quality characteristics, except for sarcomere length. Nevertheless, carcass quantitative characteristics decrease with the use of palm kernel cake.

Carcass characteristics and meat quality of lambs that are fed diets with palm kernel cake

PubMed Central

da Conceição dos Santos, Rozilda; Gomes, Daiany Iris; Alves, Kaliandra Souza; Mezzomo, Rafael; Oliveira, Luis Rennan Sampaio; Cutrim, Darley Oliveira; Sacramento, Samara Bianca Moraes; de Moura Lima, Elizanne; de Carvalho, Francisco Fernando Ramos

2017-01-01

Objective The aim was to evaluate carcass characteristics, cut yield, and meat quality in lambs that were fed different inclusion levels of palm kernel cake. Methods Forty-five woolless castrated male Santa Inês crossbred sheep with an initial average body weight of 23.16±0.35 kg were used. The experimental design was a completely randomized design with five treatments, with palm kernel cake in the proportions of 0.0%, 7.5%, 15.0%, 22.5%, and 30.0% with nine replications per treatment. After slaughter, the gastrointestinal tract was weighed when it was full, after which it was then emptied. The heart, liver, kidney, pancreas perirenal fat were also collected and weighed. The carcass was split into two identical longitudinal halves and weighed to determine the quantitative and qualitative characteristics. Results The empty body weight, carcass weight and yield, and fat thickness decreased linearly (p<0.05) as a function of palm kernel inclusion in the diet. There was no difference (p>0.05) for the rib eye area of animals that were fed palm kernel cake. There was a reduction in the commercial cut weight (p<0.05), except for the neck weight. The weights of the heart, liver, kidney fat, small, and large intestine, and gastrointestinal tract decreased. Nevertheless, the gastrointestinal content was greater for animals that were fed increasing levels of cake. For the other organs and viscera, differences were not verified (p>0.05). The sarcomere length decreased linearly (p<0.05), although an effect of the inclusion of palm kernel cake was not observed in other meat quality variables. It is worth noting that the red staining intensity, indicated as A, had a tendency to decrease (p = 0.050). Conclusion The inclusion of palm kernel cake up to 30% in the diet does not lead to changes in meat quality characteristics, except for sarcomere length. Nevertheless, carcass quantitative characteristics decrease with the use of palm kernel cake. PMID:27857029

Effects of walking or resistance training on weight loss maintenance in obese, middle-aged men: a randomized trial.

PubMed

Borg, P; Kukkonen-Harjula, K; Fogelholm, M; Pasanen, M

2002-05-01

To investigate whether walking or resistance training improves weight maintenance after weight loss when added to dietary counselling. Two months' weight reduction with very-low-energy-diet (VLED) followed by randomization into three groups (control, walking, resistance training) for 6 months' weight maintenance (WM) program and 23 months' unsupervised follow-up. During VLED and WM all groups received similar dietary counselling. The main inclusion criteria were BMI >30 kg/m(2), waist>100 cm and physical inactivity (exercise < or = once a week). Ninety healthy, obese (mean BMI 32.9 kg/m(2) and waist 112.5 cm), 35-50 y-old men started the study and 68 were measured at the end of the study. Weight and body composition assessed by underwater weighing. Exercise diaries and dietary records to assess energy balance. During VLED the mean body weight decreased from 106.0 (s.d. 9.9) kg to 91.7 (9.4) kg. Weight was regained mostly during follow-up and in the end of the study the mean weight in groups was 99.9-102.0 kg. Exercise training did not improve short or long-term weight maintenance when compared to the control group. However, resistance training attenuated the regain of body fat mass during WM (P=0.0l), but not during follow-up. In the combined groups the estimated total energy expenditure (EE) of reported physical activity was associated with less weight regain during WM. EE of 10.1 MJ/week was associated with maintaining weight after weight loss. EE of physical activity tended to decrease after WM in exercise groups due to poor long-term adherence to prescribed exercise. Energy intake seemed to increase during follow-up. Exercise training of moderate dose did not seem to improve long-term weight maintenance because of poor adherence to prescribed exercise.

Motor modules in robot-aided walking

PubMed Central

2012-01-01

Background It is hypothesized that locomotion is achieved by means of rhythm generating networks (central pattern generators) and muscle activation generating networks. This modular organization can be partly identified from the analysis of the muscular activity by means of factorization algorithms. The activity of rhythm generating networks is described by activation signals whilst the muscle intervention generating network is represented by motor modules (muscle synergies). In this study, we extend the analysis of modular organization of walking to the case of robot-aided locomotion, at varying speed and body weight support level. Methods Non Negative Matrix Factorization was applied on surface electromyographic signals of 8 lower limb muscles of healthy subjects walking in gait robotic trainer at different walking velocities (1 to 3km/h) and levels of body weight support (0 to 30%). Results The muscular activity of volunteers could be described by low dimensionality (4 modules), as for overground walking. Moreover, the activation signals during robot-aided walking were bursts of activation timed at specific phases of the gait cycle, underlying an impulsive controller, as also observed in overground walking. This modular organization was consistent across the investigated speeds, body weight support level, and subjects. Conclusions These results indicate that walking in a Lokomat robotic trainer is achieved by similar motor modules and activation signals as overground walking and thus supports the use of robotic training for re-establishing natural walking patterns. PMID:23043818

Body weight supported treadmill training versus traditional training in patients dependent on walking assistance after stroke: a randomized controlled trial.

PubMed

Høyer, Ellen; Jahnsen, Reidun; Stanghelle, Johan Kvalvik; Strand, Liv Inger

2012-01-01

Treadmill training with body weight support (TTBWS) for relearning walking ability after brain damage is an approach under current investigation. Efficiency of this method beyond traditional training is lacking evidence, especially in patients needing walking assistance after stroke. The objective of this study was to investigate change in walking and transfer abilities, comparing TTBWS with traditional walking training. A single-blinded, randomized controlled trial was conducted. Sixty patients referred for multi-disciplinary primary rehabilitation were assigned into one of two intervention groups, one received 30 sessions of TTBWS plus traditional training, the other traditional training alone. Daily training was 1 hr. Outcome measures were Functional Ambulation Categories (FAC), Walking, Functional Independence Measure (FIM); shorter transfer and stairs, 10 m and 6-min walk tests. Substantial improvements in walking and transfer were shown within both groups after 5 and 11 weeks of intervention. Overall no statistical significant differences were found between the groups, but 12 of 17 physical measures tended to show improvements in favour of the treadmill approach. Both training strategies provided significant improvements in the tested activities, suggesting that similar outcomes can be obtained in the two modalities by systematic, intensive and goal directed training.

Who walks? Factors associated with walking behavior in disabled older women with and without self-reported walking difficulty.

PubMed

Simonsick, E M; Guralnik, J M; Fried, L P

1999-06-01

To determine how severity of walking difficulty and sociodemographic, psychosocial, and health-related factors influence walking behavior in disabled older women. Cross-sectional analyses of baseline data from the Women's Health and Aging Study (WHAS). An urban community encompassing 12 contiguous zip code areas in the eastern portion of Baltimore City and part of Baltimore County, Maryland. A total of 920 moderately to severely disabled community-resident women, aged 65 years and older, identified from an age-stratified random sample of Medicare beneficiaries. Walking behavior was defined as minutes walked for exercise and total blocks walked per week. Independent variables included self-reported walking difficulty, sociodemographic factors, psychological status (depression, mastery, anxiety, and cognition), and health-related factors (falls and fear of falling, fatigue, vision and balance problems, weight, smoking, and cane use). Walking at least 8 blocks per week was strongly negatively related to severity of walking difficulty. Independent of difficulty level, older age, black race, fatigue, obesity, and cane use were also negatively associated with walking; living alone and high mastery had a positive association with walking. Even among functionally limited women, sociocultural, psychological, and health-related factors were independently associated with walking behavior. Thus, programs aimed at improving walking ability need to address these factors in addition to walking difficulties to maximize participation and compliance.

Should I Stay or Should I Go? A Habitat-Dependent Dispersal Kernel Improves Prediction of Movement

PubMed Central

Vinatier, Fabrice; Lescourret, Françoise; Duyck, Pierre-François; Martin, Olivier; Senoussi, Rachid; Tixier, Philippe

2011-01-01

The analysis of animal movement within different landscapes may increase our understanding of how landscape features affect the perceptual range of animals. Perceptual range is linked to movement probability of an animal via a dispersal kernel, the latter being generally considered as spatially invariant but could be spatially affected. We hypothesize that spatial plasticity of an animal's dispersal kernel could greatly modify its distribution in time and space. After radio tracking the movements of walking insects (Cosmopolites sordidus) in banana plantations, we considered the movements of individuals as states of a Markov chain whose transition probabilities depended on the habitat characteristics of current and target locations. Combining a likelihood procedure and pattern-oriented modelling, we tested the hypothesis that dispersal kernel depended on habitat features. Our results were consistent with the concept that animal dispersal kernel depends on habitat features. Recognizing the plasticity of animal movement probabilities will provide insight into landscape-level ecological processes. PMID:21765890

Should I stay or should I go? A habitat-dependent dispersal kernel improves prediction of movement.

PubMed

Vinatier, Fabrice; Lescourret, Françoise; Duyck, Pierre-François; Martin, Olivier; Senoussi, Rachid; Tixier, Philippe

2011-01-01

The analysis of animal movement within different landscapes may increase our understanding of how landscape features affect the perceptual range of animals. Perceptual range is linked to movement probability of an animal via a dispersal kernel, the latter being generally considered as spatially invariant but could be spatially affected. We hypothesize that spatial plasticity of an animal's dispersal kernel could greatly modify its distribution in time and space. After radio tracking the movements of walking insects (Cosmopolites sordidus) in banana plantations, we considered the movements of individuals as states of a Markov chain whose transition probabilities depended on the habitat characteristics of current and target locations. Combining a likelihood procedure and pattern-oriented modelling, we tested the hypothesis that dispersal kernel depended on habitat features. Our results were consistent with the concept that animal dispersal kernel depends on habitat features. Recognizing the plasticity of animal movement probabilities will provide insight into landscape-level ecological processes.

Comparison of energy expenditure to walk or run a mile in adult normal weight and overweight men and women.

PubMed

Loftin, Mark; Waddell, Dwight E; Robinson, James H; Owens, Scott G

2010-10-01

We compared the energy expenditure to walk or run a mile in adult normal weight walkers (NWW), overweight walkers (OW), and marathon runners (MR). The sample consisted of 19 NWW, 11 OW, and 20 MR adults. Energy expenditure was measured at preferred walking speed (NWW and OW) and running speed of a recently completed marathon. Body composition was assessed via dual-energy x-ray absorptiometry. Analysis of variance was used to compare groups with the Scheffe's procedure used for post hoc analysis. Multiple regression analysis was used to predict energy expenditure. Results that indicated OW exhibited significantly higher (p < 0.05) mass and fat weight than NWW or MR. Similar values were found between NWW and MR. Absolute energy expenditure to walk or run a mile was similar between groups (NWW 93.9 ± 15.0, OW 98.4 ± 29.9, MR 99.3 ± 10.8 kcal); however, significant differences were noted when energy expenditure was expressed relative to mass (MR > NWW > OW). When energy expenditure was expressed per kilogram of fat-free mass, similar values were found across groups. Multiple regression analysis yielded mass and gender as significant predictors of energy expenditure (R = 0.795, SEE = 10.9 kcal). We suggest that walking is an excellent physical activity for energy expenditure in overweight individuals that are capable of walking without predisposed conditions such as osteoarthritis or cardiovascular risk factors. Moreover, from a practical perspective, our regression equation (kcal = mass (kg) × 0.789 - gender (men = 1, women = 2) × 7.634 + 51.109) allows for the prediction of energy expenditure for a given distance (mile) rather than predicting energy expenditure for a given time (minutes).

FOOT PLACEMENT IN A BODY REFERENCE FRAME DURING WALKING AND ITS RELATIONSHIP TO HEMIPARETIC WALKING PERFORMANCE

PubMed Central

Balasubramanian, Chitralakshmi K.; Neptune, Richard R.; Kautz, Steven A.

2010-01-01

Background Foot placement during walking is closely linked to the body position, yet it is typically quantified relative to the other foot. The purpose of this study was to quantify foot placement patterns relative to body post-stroke and investigate its relationship to hemiparetic walking performance. Methods Thirty-nine participants with hemiparesis walked on a split-belt treadmill at their self-selected speeds and twenty healthy participants walked at matched slow speeds. Anterior-posterior and medial-lateral foot placements (foot center-of-mass) relative to body (pelvis center-of-mass) quantified stepping in body reference frame. Walking performance was quantified using step length asymmetry ratio, percent of paretic propulsion and paretic weight support. Findings Participants with hemiparesis placed their paretic foot further anterior than posterior during walking compared to controls walking at matched slow speeds (p < .05). Participants also placed their paretic foot further lateral relative to pelvis than non-paretic (p < .05). Anterior-posterior asymmetry correlated with step length asymmetry and percent paretic propulsion but some persons revealed differing asymmetry patterns in the translating reference frame. Lateral foot placement asymmetry correlated with paretic weight support (r = .596; p < .001), whereas step widths showed no relation to paretic weight support. Interpretation Post-stroke gait is asymmetric when quantifying foot placement in a body reference frame and this asymmetry related to the hemiparetic walking performance and explained motor control mechanisms beyond those explained by step lengths and step widths alone. We suggest that biomechanical analyses quantifying stepping performance in impaired populations should investigate foot placement in a body reference frame. PMID:20193972

Foot placement in a body reference frame during walking and its relationship to hemiparetic walking performance.

PubMed

Balasubramanian, Chitralakshmi K; Neptune, Richard R; Kautz, Steven A

2010-06-01

Foot placement during walking is closely linked to the body position, yet it is typically quantified relative to the other foot. The purpose of this study was to quantify foot placement patterns relative to body post-stroke and investigate its relationship to hemiparetic walking performance. Thirty-nine participants with hemiparesis walked on a split-belt treadmill at their self-selected speeds and 20 healthy participants walked at matched slow speeds. Anterior-posterior and medial-lateral foot placements (foot center-of-mass) relative to body (pelvis center-of-mass) quantified stepping in body reference frame. Walking performance was quantified using step length asymmetry ratio, percent of paretic propulsion and paretic weight support. Participants with hemiparesis placed their paretic foot further anterior than posterior during walking compared to controls walking at matched slow speeds (P<.05). Participants also placed their paretic foot further lateral relative to pelvis than non-paretic (P<.05). Anterior-posterior asymmetry correlated with step length asymmetry and percent paretic propulsion but some persons revealed differing asymmetry patterns in the translating reference frame. Lateral foot placement asymmetry correlated with paretic weight support (r=.596; P<.001), whereas step widths showed no relation to paretic weight support. Post-stroke gait is asymmetric when quantifying foot placement in a body reference frame and this asymmetry related to the hemiparetic walking performance and explained motor control mechanisms beyond those explained by step lengths and step widths alone. We suggest that biomechanical analyses quantifying stepping performance in impaired populations should investigate foot placement in a body reference frame. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Kernel Machine SNP-set Testing under Multiple Candidate Kernels

PubMed Central

Wu, Michael C.; Maity, Arnab; Lee, Seunggeun; Simmons, Elizabeth M.; Harmon, Quaker E.; Lin, Xinyi; Engel, Stephanie M.; Molldrem, Jeffrey J.; Armistead, Paul M.

2013-01-01

Joint testing for the cumulative effect of multiple single nucleotide polymorphisms grouped on the basis of prior biological knowledge has become a popular and powerful strategy for the analysis of large scale genetic association studies. The kernel machine (KM) testing framework is a useful approach that has been proposed for testing associations between multiple genetic variants and many different types of complex traits by comparing pairwise similarity in phenotype between subjects to pairwise similarity in genotype, with similarity in genotype defined via a kernel function. An advantage of the KM framework is its flexibility: choosing different kernel functions allows for different assumptions concerning the underlying model and can allow for improved power. In practice, it is difficult to know which kernel to use a priori since this depends on the unknown underlying trait architecture and selecting the kernel which gives the lowest p-value can lead to inflated type I error. Therefore, we propose practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures. We demonstrate through simulations and real data applications that the procedures protect the type I error rate and can lead to substantially improved power over poor choices of kernels and only modest differences in power versus using the best candidate kernel. PMID:23471868

Genetic dissection of the maize kernel development process via conditional QTL mapping for three developing kernel-related traits in an immortalized F2 population.

PubMed

Zhang, Zhanhui; Wu, Xiangyuan; Shi, Chaonan; Wang, Rongna; Li, Shengfei; Wang, Zhaohui; Liu, Zonghua; Xue, Yadong; Tang, Guiliang; Tang, Jihua

2016-02-01

Kernel development is an important dynamic trait that determines the final grain yield in maize. To dissect the genetic basis of maize kernel development process, a conditional quantitative trait locus (QTL) analysis was conducted using an immortalized F2 (IF2) population comprising 243 single crosses at two locations over 2 years. Volume (KV) and density (KD) of dried developing kernels, together with kernel weight (KW) at different developmental stages, were used to describe dynamic changes during kernel development. Phenotypic analysis revealed that final KW and KD were determined at DAP22 and KV at DAP29. Unconditional QTL mapping for KW, KV and KD uncovered 97 QTLs at different kernel development stages, of which qKW6b, qKW7a, qKW7b, qKW10b, qKW10c, qKV10a, qKV10b and qKV7 were identified under multiple kernel developmental stages and environments. Among the 26 QTLs detected by conditional QTL mapping, conqKW7a, conqKV7a, conqKV10a, conqKD2, conqKD7 and conqKD8a were conserved between the two mapping methodologies. Furthermore, most of these QTLs were consistent with QTLs and genes for kernel development/grain filling reported in previous studies. These QTLs probably contain major genes associated with the kernel development process, and can be used to improve grain yield and quality through marker-assisted selection.

Gait training with partial body weight support during overground walking for individuals with chronic stroke: a pilot study

PubMed Central

2011-01-01

Background It is not yet established if the use of body weight support (BWS) systems for gait training is effective per se or if it is the combination of BWS and treadmill that improves the locomotion of individuals with gait impairment. This study investigated the effects of gait training on ground level with partial BWS in individuals with stroke during overground walking with no BWS. Methods Twelve individuals with chronic stroke (53.17 ± 7.52 years old) participated of a gait training program with BWS during overground walking, and were evaluated before and after the gait training period. In both evaluations, individuals were videotaped walking at a self-selected comfortable speed with no BWS. Measurements were obtained for mean walking speed, step length, stride length and speed, toe-clearance, durations of total double stance and single-limb support, and minimum and maximum foot, shank, thigh, and trunk segmental angles. Results After gait training, individuals walked faster, with symmetrical steps, longer and faster strides, and increased toe-clearance. Also, they displayed increased rotation of foot, shank, thigh, and trunk segmental angles on both sides of the body. However, the duration of single-limb support remained asymmetrical between each side of the body after gait training. Conclusions Gait training individuals with chronic stroke with BWS during overground walking improved walking in terms of temporal-spatial parameters and segmental angles. This training strategy might be adopted as a safe, specific and promising strategy for gait rehabilitation after stroke. PMID:21864373

Phenolic constituents of shea (Vitellaria paradoxa) kernels.

PubMed

Maranz, Steven; Wiesman, Zeev; Garti, Nissim

2003-10-08

Analysis of the phenolic constituents of shea (Vitellaria paradoxa) kernels by LC-MS revealed eight catechin compounds-gallic acid, catechin, epicatechin, epicatechin gallate, gallocatechin, epigallocatechin, gallocatechin gallate, and epigallocatechin gallate-as well as quercetin and trans-cinnamic acid. The mean kernel content of the eight catechin compounds was 4000 ppm (0.4% of kernel dry weight), with a 2100-9500 ppm range. Comparison of the profiles of the six major catechins from 40 Vitellaria provenances from 10 African countries showed that the relative proportions of these compounds varied from region to region. Gallic acid was the major phenolic compound, comprising an average of 27% of the measured total phenols and exceeding 70% in some populations. Colorimetric analysis (101 samples) of total polyphenols extracted from shea butter into hexane gave an average of 97 ppm, with the values for different provenances varying between 62 and 135 ppm of total polyphenols.

Improved clinical status, quality of life, and walking capacity in Parkinson's disease after body weight-supported high-intensity locomotor training.

PubMed

Rose, Martin H; Løkkegaard, Annemette; Sonne-Holm, Stig; Jensen, Bente R

2013-04-01

To evaluate the effect of body weight-supported progressive high-intensity locomotor training in Parkinson's disease (PD) on (1) clinical status; (2) quality of life; and (3) gait capacity. Open-label, fixed sequence crossover study. University motor control laboratory. Patients (N=13) with idiopathic PD (Hoehn and Yahr stage 2 or 3) and stable medication use. Patients completed an 8-week (3 × 1h/wk) training program on a lower-body positive-pressure treadmill. Body weight support was used to facilitate increased intensity and motor challenges during treadmill training. The training program contained combinations of (1) running and walking intervals, (2) the use of sudden changes (eg, in body weight support and speed), (3) different types of locomotion (eg, chassé, skipping, and jumps), and (4) sprints at 50 percent body weight. The Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS), Parkinson's Disease Questionnaire-39 items (PDQ-39), and the six-minute walk test were conducted 8 weeks before and pre- and posttraining. At the end of training, statistically significant improvements were found in all outcome measures compared with the control period. Total MDS-UPDRS score changed from (mean ± 1SD) 58±18 to 47±18, MDS-UPDRS motor part score changed from 35±10 to 29±12, PDQ-39 summary index score changed from 22±13 to 13±12, and the six-minute walking distance changed from 576±93 to 637±90m. Body weight-supported progressive high-intensity locomotor training is feasible and well tolerated by patients with PD. The training improved clinical status, quality of life, and gait capacity significantly. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Fish consumption and subsequent change in body weight in European women and men.

PubMed

Jakobsen, Marianne U; Dethlefsen, Claus; Due, Karen M; May, Anne M; Romaguera, Dora; Vergnaud, Anne-Claire; Norat, Teresa; Sørensen, Thorkild I A; Halkjær, Jytte; Tjønneland, Anne; Boutron-Ruault, Marie-Christine; Clavel-Chapelon, Francoise; Fagherazzi, Guy; Teucher, Birgit; Kühn, Tilman; Bergmann, Manuela M; Boeing, Heiner; Naska, Androniki; Orfanos, Philippos; Trichopoulou, Antonia; Palli, Domenico; Santucci De Magistris, Maria; Sieri, Sabina; Bueno-de-Mesquita, H B; van der A, Daphne L; Engeset, Dagrun; Hjartåker, Anette; Rodríguez, Laudina; Agudo, Antonio; Molina-Montes, Esther; Huerta, José M; Barricarte, Aurelio; Amiano, Pilar; Manjer, Jonas; Wirfält, Elisabet; Hallmans, Göran; Johansson, Ingegerd; Khaw, Kay-Tee; Wareham, Nicholas J; Key, Timothy J; Chajès, Veronique; Slimani, Nadia; Riboli, Elio; Peeters, Petra H M; Overvad, Kim

2013-01-28

Fish consumption is the major dietary source of EPA and DHA, which according to rodent experiments may reduce body fat mass and prevent obesity. Only a few human studies have investigated the association between fish consumption and body-weight gain. We investigated the association between fish consumption and subsequent change in body weight. Women and men (n 344,757) participating in the European Prospective Investigation into Cancer and Nutrition were followed for a median of 5.0 years. Linear and logistic regression were used to investigate the associations between fish consumption and subsequent change in body weight. Among women, the annual weight change was 5.70 (95 % CI 4.35, 7.06), 2.23 (95 % CI 0.16, 4.31) and 11.12 (95 % CI 8.17, 14.08) g/10 g higher total, lean and fatty fish consumption per d, respectively. The OR of becoming overweight in 5 years among women who were normal weight at enrolment was 1.02 (95 % CI 1.01, 1.02), 1.01 (95 % CI 1.00, 1.02) and 1.02 (95 % CI 1.01, 1.04) g/10 g higher total, lean and fatty consumption per d, respectively. Among men, fish consumption was not statistically significantly associated with weight change. Adjustment for potential over- or underestimation of fish consumption did not systematically change the observed associations, but the 95 % CI became wider. The results in subgroups from analyses stratified by age or BMI at enrolment were not systematically different. In conclusion, the present study suggests that fish consumption has no appreciable association with body-weight gain.

Changes in resting and walking energy expenditure and walking speed during pregnancy in obese women.

PubMed

Byrne, Nuala M; Groves, Ainsley M; McIntyre, H David; Callaway, Leonie K

2011-09-01

Energy-conserving processes reported in undernourished women during pregnancy are a recognized strategy for providing the energy required to support fetal development. Women who are obese before conceiving arguably have sufficient fat stores to support the energy demands of pregnancy without the need to provoke energy-conserving mechanisms. We tested the hypothesis that obese women would show behavioral adaptation [ie, a decrease in self-selected walking (SSW) speed] but not metabolic compensation [ie, a decrease in resting metabolic rate (RMR) or the metabolic cost of walking] during gestation. RMR, SSW speed, metabolic cost of walking, and anthropometric variables were measured in 23 women aged 31 ± 4 y with a BMI (in kg/m(2)) of 33.6 ± 2.5 (mean ± SD) at ≈15 and 30 wk of gestation. RMR was also measured in 2 cohorts of nonpregnant control subjects matched for the age, weight, and height of the pregnant cohort at 15 (n = 23) and 30 (n = 23) wk. Gestational weight gain varied widely (11.3 ± 5.4 kg), and 52% of the women gained more weight than is recommended. RMR increased significantly by an average of 177 ± 176 kcal/d (11 ± 12%; P < 0.0001); however, the within-group variability was large. Both the metabolic cost of walking and SSW speed decreased significantly (P < 0.01). Whereas RMR increased in >80% of the cohort, the net oxygen cost of walking decreased in the same proportion of women. Although the increase in RMR was greater than that explained by weight gain, evidence of both behavioral and biological compensation in the metabolic cost of walking was observed in obese women during gestation. The trial is registered with the Australian Clinical Trials Registry as ACTRN012606000271505.

A framework for optimal kernel-based manifold embedding of medical image data.

PubMed

Zimmer, Veronika A; Lekadir, Karim; Hoogendoorn, Corné; Frangi, Alejandro F; Piella, Gemma

2015-04-01

Kernel-based dimensionality reduction is a widely used technique in medical image analysis. To fully unravel the underlying nonlinear manifold the selection of an adequate kernel function and of its free parameters is critical. In practice, however, the kernel function is generally chosen as Gaussian or polynomial and such standard kernels might not always be optimal for a given image dataset or application. In this paper, we present a study on the effect of the kernel functions in nonlinear manifold embedding of medical image data. To this end, we first carry out a literature review on existing advanced kernels developed in the statistics, machine learning, and signal processing communities. In addition, we implement kernel-based formulations of well-known nonlinear dimensional reduction techniques such as Isomap and Locally Linear Embedding, thus obtaining a unified framework for manifold embedding using kernels. Subsequently, we present a method to automatically choose a kernel function and its associated parameters from a pool of kernel candidates, with the aim to generate the most optimal manifold embeddings. Furthermore, we show how the calculated selection measures can be extended to take into account the spatial relationships in images, or used to combine several kernels to further improve the embedding results. Experiments are then carried out on various synthetic and phantom datasets for numerical assessment of the methods. Furthermore, the workflow is applied to real data that include brain manifolds and multispectral images to demonstrate the importance of the kernel selection in the analysis of high-dimensional medical images. Copyright © 2014 Elsevier Ltd. All rights reserved.

Characterization of non-diffusive transport in plasma turbulence by means of flux-gradient integro-differential kernels

NASA Astrophysics Data System (ADS)

Alcuson, J. A.; Reynolds-Barredo, J. M.; Mier, J. A.; Sanchez, Raul; Del-Castillo-Negrete, Diego; Newman, David E.; Tribaldos, V.

2015-11-01

A method to determine fractional transport exponents in systems dominated by fluid or plasma turbulence is proposed. The method is based on the estimation of the integro-differential kernel that relates values of the fluxes and gradients of the transported field, and its comparison with the family of analytical kernels of the linear fractional transport equation. Although use of this type of kernels has been explored before in this context, the methodology proposed here is rather unique since the connection with specific fractional equations is exploited from the start. The procedure has been designed to be particularly well-suited for application in experimental setups, taking advantage of the fact that kernel determination only requires temporal data of the transported field measured on an Eulerian grid. The simplicity and robustness of the method is tested first by using fabricated data from continuous-time random walk models built with prescribed transport characteristics. Its strengths are then illustrated on numerical Eulerian data gathered from simulations of a magnetically confined turbulent plasma in a near-critical regime, that is known to exhibit superdiffusive radial transport

Effects of virtual reality training using Nintendo Wii and treadmill walking exercise on balance and walking for stroke patients.

PubMed

Bang, Yo-Soon; Son, Kyung Hyun; Kim, Hyun Jin

2016-11-01

[Purpose] The purpose of this study is to investigate the effects of virtual reality training using Nintendo Wii on balance and walking for stroke patients. [Subjects and Methods] Forty stroke patients with stroke were randomly divided into two exercise program groups: virtual reality training (n=20) and treadmill (n=20). The subjects underwent their 40-minute exercise program three times a week for eight weeks. Their balance and walking were measured before and after the complete program. We measured the left/right weight-bearing and the anterior/posterior weight-bearing for balance, as well as stance phase, swing phase, and cadence for walking. [Results] For balance, both groups showed significant differences in the left/right and anterior/posterior weight-bearing, with significant post-program differences between the groups. For walking, there were significant differences in the stance phase, swing phase, and cadence of the virtual reality training group. [Conclusion] The results of this study suggest that virtual reality training providing visual feedback may enable stroke patients to directly adjust their incorrect weight center and shift visually. Virtual reality training may be appropriate for patients who need improved balance and walking ability by inducing their interest for them to perform planned exercises on a consistent basis.

Effects of virtual reality training using Nintendo Wii and treadmill walking exercise on balance and walking for stroke patients

PubMed Central

Bang, Yo-Soon; Son, Kyung Hyun; Kim, Hyun Jin

2016-01-01

[Purpose] The purpose of this study is to investigate the effects of virtual reality training using Nintendo Wii on balance and walking for stroke patients. [Subjects and Methods] Forty stroke patients with stroke were randomly divided into two exercise program groups: virtual reality training (n=20) and treadmill (n=20). The subjects underwent their 40-minute exercise program three times a week for eight weeks. Their balance and walking were measured before and after the complete program. We measured the left/right weight-bearing and the anterior/posterior weight-bearing for balance, as well as stance phase, swing phase, and cadence for walking. [Results] For balance, both groups showed significant differences in the left/right and anterior/posterior weight-bearing, with significant post-program differences between the groups. For walking, there were significant differences in the stance phase, swing phase, and cadence of the virtual reality training group. [Conclusion] The results of this study suggest that virtual reality training providing visual feedback may enable stroke patients to directly adjust their incorrect weight center and shift visually. Virtual reality training may be appropriate for patients who need improved balance and walking ability by inducing their interest for them to perform planned exercises on a consistent basis. PMID:27942130

Broken rice kernels and the kinetics of rice hydration and texture during cooking.

PubMed

Saleh, Mohammed; Meullenet, Jean-Francois

2013-05-01

During rice milling and processing, broken kernels are inevitably present, although to date it has been unclear as to how the presence of broken kernels affects rice hydration and cooked rice texture. Therefore, this work intended to study the effect of broken kernels in a rice sample on rice hydration and texture during cooking. Two medium-grain and two long-grain rice cultivars were harvested, dried and milled, and the broken kernels were separated from unbroken kernels. Broken rice kernels were subsequently combined with unbroken rice kernels forming treatments of 0, 40, 150, 350 or 1000 g kg(-1) broken kernels ratio. Rice samples were then cooked and the moisture content of the cooked rice, the moisture uptake rate, and rice hardness and stickiness were measured. As the amount of broken rice kernels increased, rice sample texture became increasingly softer (P < 0.05) but the unbroken kernels became significantly harder. Moisture content and moisture uptake rate were positively correlated, and cooked rice hardness was negatively correlated to the percentage of broken kernels in rice samples. Differences in the proportions of broken rice in a milled rice sample play a major role in determining the texture properties of cooked rice. Variations in the moisture migration kinetics between broken and unbroken kernels caused faster hydration of the cores of broken rice kernels, with greater starch leach-out during cooking affecting the texture of the cooked rice. The texture of cooked rice can be controlled, to some extent, by varying the proportion of broken kernels in milled rice. © 2012 Society of Chemical Industry.

Proteome analysis of the almond kernel (Prunus dulcis).

PubMed

Li, Shugang; Geng, Fang; Wang, Ping; Lu, Jiankang; Ma, Meihu

2016-08-01

Almond (Prunus dulcis) is a popular tree nut worldwide and offers many benefits to human health. However, the importance of almond kernel proteins in the nutrition and function in human health requires further evaluation. The present study presents a systematic evaluation of the proteins in the almond kernel using proteomic analysis. The nutrient and amino acid content in almond kernels from Xinjiang is similar to that of American varieties; however, Xinjiang varieties have a higher protein content. Two-dimensional electrophoresis analysis demonstrated a wide distribution of molecular weights and isoelectric points of almond kernel proteins. A total of 434 proteins were identified by LC-MS/MS, and most were proteins that were experimentally confirmed for the first time. Gene ontology (GO) analysis of the 434 proteins indicated that proteins involved in primary biological processes including metabolic processes (67.5%), cellular processes (54.1%), and single-organism processes (43.4%), the main molecular function of almond kernel proteins are in catalytic activity (48.0%), binding (45.4%) and structural molecule activity (11.9%), and proteins are primarily distributed in cell (59.9%), organelle (44.9%), and membrane (22.8%). Almond kernel is a source of a wide variety of proteins. This study provides important information contributing to the screening and identification of almond proteins, the understanding of almond protein function, and the development of almond protein products. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Cross-Validation of a Recently Published Equation Predicting Energy Expenditure to Run or Walk a Mile in Normal-Weight and Overweight Adults

ERIC Educational Resources Information Center

Morris, Cody E.; Owens, Scott G.; Waddell, Dwight E.; Bass, Martha A.; Bentley, John P.; Loftin, Mark

2014-01-01

An equation published by Loftin, Waddell, Robinson, and Owens (2010) was cross-validated using ten normal-weight walkers, ten overweight walkers, and ten distance runners. Energy expenditure was measured at preferred walking (normal-weight walker and overweight walkers) or running pace (distance runners) for 5 min and corrected to a mile. Energy…

QTL Mapping of Kernel Number-Related Traits and Validation of One Major QTL for Ear Length in Maize.

PubMed

Huo, Dongao; Ning, Qiang; Shen, Xiaomeng; Liu, Lei; Zhang, Zuxin

2016-01-01

The kernel number is a grain yield component and an important maize breeding goal. Ear length, kernel number per row and ear row number are highly correlated with the kernel number per ear, which eventually determines the ear weight and grain yield. In this study, two sets of F2:3 families developed from two bi-parental crosses sharing one inbred line were used to identify quantitative trait loci (QTL) for four kernel number-related traits: ear length, kernel number per row, ear row number and ear weight. A total of 39 QTLs for the four traits were identified in the two populations. The phenotypic variance explained by a single QTL ranged from 0.4% to 29.5%. Additionally, 14 overlapping QTLs formed 5 QTL clusters on chromosomes 1, 4, 5, 7, and 10. Intriguingly, six QTLs for ear length and kernel number per row overlapped in a region on chromosome 1. This region was designated qEL1.10 and was validated as being simultaneously responsible for ear length, kernel number per row and ear weight in a near isogenic line-derived population, suggesting that qEL1.10 was a pleiotropic QTL with large effects. Furthermore, the performance of hybrids generated by crossing 6 elite inbred lines with two near isogenic lines at qEL1.10 showed the breeding value of qEL1.10 for the improvement of the kernel number and grain yield of maize hybrids. This study provides a basis for further fine mapping, molecular marker-aided breeding and functional studies of kernel number-related traits in maize.

Ongoing walking recovery 2 years after locomotor training in a child with severe incomplete spinal cord injury.

PubMed

Fox, Emily J; Tester, Nicole J; Phadke, Chetan P; Nair, Preeti M; Senesac, Claudia R; Howland, Dena R; Behrman, Andrea L

2010-05-01

The authors previously reported on walking recovery in a nonambulatory child with chronic, severe, incomplete cervical spinal cord injury (SCI) after 76 sessions of locomotor training (LT). Although clinical measures did not predict his recovery, reciprocal patterned leg movements developed, affording recovery of independent walking with a reverse rolling walker. The long-term functional limitations and secondary complications often associated with pediatric-onset SCI necessitate continued follow-up of children with SCI. Therefore, the purpose of this case report is to describe this child's walking function and musculoskeletal growth and development during the 2 years since his participation in an LT program and subsequent walking recovery. Following LT, the child attended elementary school as a full-time ambulator. He was evaluated 1 month (baseline), 1 year, and 2 years after LT. Examination of walking function included measures of walking independence, gait speed and spatiotemporal parameters, gait kinematics, and daily step activity. Growth and development were assessed by tracking his height, weight, incidence of musculoskeletal complications, and gross motor task performance. Over the 2 years, the child continued to ambulate independently with a reverse rolling walker, increasing his fastest gait speed. Spatiotemporal and kinematic features of his walking improved, and daily step activity increased. Height and weight remained on their preinjury trajectory and within age-appropriate norms. The child experienced only minor musculoskeletal complications. Additionally, he gained the ability to use reciprocal patterned leg movements during locomotor tasks such as assisted stair climbing and independent tricycle pedaling. Two years after recovery of walking, this child with incomplete SCI had maintained and improved his walking function and experienced age-appropriate growth and development.

Walking with robot assistance: the influence of body weight support on the trunk and pelvis kinematics.

PubMed

Swinnen, Eva; Baeyens, Jean-Pierre; Knaepen, Kristel; Michielsen, Marc; Hens, Gerrit; Clijsen, Ron; Goossens, Maggie; Buyl, Ronald; Meeusen, Romain; Kerckhofs, Eric

2015-05-01

The goal was to assess in healthy participants the three-dimensional kinematics of the pelvis and the trunk during robot-assisted treadmill walking (RATW) at 0%, 30% and 50% body weight support (BWS), compared with treadmill walking (TW). 18 healthy participants walked (2 kmph) on a treadmill with and without robot assistance (Lokomat; 60% guidance force; 0%, 30% and 50% BWS). After an acclimatisation period (four minutes), trunk and pelvis kinematics were registered in each condition (Polhemus Liberty [240 Hz]). The results were analysed using a repeated measures analysis of variance with Bonferroni correction, with the level of suspension as within-subject factor. During RATW with BWS, there were significantly (1) smaller antero-posterior and lateral translations of the trunk and the pelvis; (2) smaller antero-posterior flexion and axial rotation of the trunk; (3) larger lateral flexion of the trunk; and (4) larger antero-posterior tilting of the pelvis compared with TW. There are significant differences in trunk and pelvis kinematics in healthy persons during TW with and without robot assistance. These data are relevant in gait rehabilitation, relating to normal balance regulation. Additional research is recommended to further assess the influence of robot assistance on human gait. The trunk and pelvis moves in a different way during walking with robot assistance. The data suggest that the change in movement is due to the robot device and the harness of the suspension system more than due to the level of suspension itself.

Ranking support vector machine for multiple kernels output combination in protein-protein interaction extraction from biomedical literature.

PubMed

Yang, Zhihao; Lin, Yuan; Wu, Jiajin; Tang, Nan; Lin, Hongfei; Li, Yanpeng

2011-10-01

Knowledge about protein-protein interactions (PPIs) unveils the molecular mechanisms of biological processes. However, the volume and content of published biomedical literature on protein interactions is expanding rapidly, making it increasingly difficult for interaction database curators to detect and curate protein interaction information manually. We present a multiple kernel learning-based approach for automatic PPI extraction from biomedical literature. The approach combines the following kernels: feature-based, tree, and graph and combines their output with Ranking support vector machine (SVM). Experimental evaluations show that the features in individual kernels are complementary and the kernel combined with Ranking SVM achieves better performance than those of the individual kernels, equal weight combination and optimal weight combination. Our approach can achieve state-of-the-art performance with respect to the comparable evaluations, with 64.88% F-score and 88.02% AUC on the AImed corpus. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Exercise training utilizing body weight-supported treadmill walking with a young adult with cerebral palsy who was non-ambulatory.

PubMed

DiBiasio, Paula A; Lewis, Cynthia L

2012-11-01

The purpose of this case report is to determine the effects of exercise training using body weight-supported treadmill walking (BWSTW) with an 18-year-old male diagnosed with Cerebral palsy (CP) who was non-ambulatory and not receiving physical therapy. Outcome measures included the Pediatric Quality of Life Inventory (PedsQL), the Pediatric Evaluation of Disability Inventory (PEDI), heart rate (HR), rate of perceived exertion, 3-minute walk test and physiological cost index (PCI). BWSTW sessions took place twice a week for 6 weeks with a reduction of approximately 40% of the patient's weight. Over-ground 3-minute walk test distance and PCI were essentially unchanged. BWSTW exercise time increased by 67% with a 43% increase in speed while average working HR decreased by 8%. BWSTW PCI decreased by 26%. PedsQL parent report improved in all domains. PedsQL self-report demonstrated a mild decrease. PEDI showed improvements in self-care and mobility. Exercise utilizing BWSTW resulted in a positive training effect for this young adult with CP who was non-ambulatory. Developing effective and efficient protocols for exercise training utilizing BWSTW may aid in the use of this form of exercise and further quantify outcomes. Ensuring that young adults with CP have safe and feasible options to exercise and be physically active on a regular basis is an important role of a physical therapist.

Effects of Nordic walking and walking on spatiotemporal gait parameters and ground reaction force.

PubMed

Park, Seung Kyu; Yang, Dae Jung; Kang, Yang Hun; Kim, Je Ho; Uhm, Yo Han; Lee, Yong Seon

2015-09-01

[Purpose] The purpose of this study was to investigate the effects of Nordic walking and walking on spatiotemporal gait parameters and ground reaction force. [Subjects] The subjects of this study were 30 young adult males, who were divided into a Nordic walking group of 15 subjects and a walking group of 15 subjects. [Methods] To analyze the spatiotemporal parameters and ground reaction force during walking in the two groups, the six-camera Vicon MX motion analysis system was used. The subjects were asked to walk 12 meters using the more comfortable walking method for them between Nordic walking and walking. After they walked 12 meters more than 10 times, their most natural walking patterns were chosen three times and analyzed. To determine the pole for Nordic walking, each subject's height was multiplied by 0.68. We then measured the spatiotemporal gait parameters and ground reaction force. [Results] Compared with the walking group, the Nordic walking group showed an increase in cadence, stride length, and step length, and a decrease in stride time, step time, and vertical ground reaction force. [Conclusion] The results of this study indicate that Nordic walking increases the stride and can be considered as helping patients with diseases affecting their gait. This demonstrates that Nordic walking is more effective in improving functional capabilities by promoting effective energy use and reducing the lower limb load, because the weight of the upper and lower limbs is dispersed during Nordic walking.

Providing the Fire Risk Map in Forest Area Using a Geographically Weighted Regression Model with Gaussin Kernel and Modis Images, a Case Study: Golestan Province

NASA Astrophysics Data System (ADS)

Shah-Heydari pour, A.; Pahlavani, P.; Bigdeli, B.

2017-09-01

According to the industrialization of cities and the apparent increase in pollutants and greenhouse gases, the importance of forests as the natural lungs of the earth is felt more than ever to clean these pollutants. Annually, a large part of the forests is destroyed due to the lack of timely action during the fire. Knowledge about areas with a high-risk of fire and equipping these areas by constructing access routes and allocating the fire-fighting equipment can help to eliminate the destruction of the forest. In this research, the fire risk of region was forecasted and the risk map of that was provided using MODIS images by applying geographically weighted regression model with Gaussian kernel and ordinary least squares over the effective parameters in forest fire including distance from residential areas, distance from the river, distance from the road, height, slope, aspect, soil type, land use, average temperature, wind speed, and rainfall. After the evaluation, it was found that the geographically weighted regression model with Gaussian kernel forecasted 93.4% of the all fire points properly, however the ordinary least squares method could forecast properly only 66% of the fire points.

Efficient Multiple Kernel Learning Algorithms Using Low-Rank Representation.

PubMed

Niu, Wenjia; Xia, Kewen; Zu, Baokai; Bai, Jianchuan

2017-01-01

Unlike Support Vector Machine (SVM), Multiple Kernel Learning (MKL) allows datasets to be free to choose the useful kernels based on their distribution characteristics rather than a precise one. It has been shown in the literature that MKL holds superior recognition accuracy compared with SVM, however, at the expense of time consuming computations. This creates analytical and computational difficulties in solving MKL algorithms. To overcome this issue, we first develop a novel kernel approximation approach for MKL and then propose an efficient Low-Rank MKL (LR-MKL) algorithm by using the Low-Rank Representation (LRR). It is well-acknowledged that LRR can reduce dimension while retaining the data features under a global low-rank constraint. Furthermore, we redesign the binary-class MKL as the multiclass MKL based on pairwise strategy. Finally, the recognition effect and efficiency of LR-MKL are verified on the datasets Yale, ORL, LSVT, and Digit. Experimental results show that the proposed LR-MKL algorithm is an efficient kernel weights allocation method in MKL and boosts the performance of MKL largely.

Effect of dark, hard, and vitreous kernel content on protein molecular weight distribution and on milling and breadmaking quality characteristics for hard spring wheat samples from diverse growing regions

USDA-ARS?s Scientific Manuscript database

Kernel vitreousness is an important grading characteristic for segregation of sub-classes of hard red spring (HRS) wheat in the U.S. This research investigated the protein molecular weight distribution (MWD), and flour and baking quality characteristics of different HRS wheat market sub-classes. T...

Kernel Abortion in Maize 1

PubMed Central

Hanft, Jonathan M.; Jones, Robert J.

1986-01-01

Kernels cultured in vitro were induced to abort by high temperature (35°C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35°C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth. PMID:16664846

Approximate kernel competitive learning.

PubMed

Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

2015-03-01

Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

Exploring activity-driven network with biased walks

NASA Astrophysics Data System (ADS)

Wang, Yan; Wu, Ding Juan; Lv, Fang; Su, Meng Long

We investigate the concurrent dynamics of biased random walks and the activity-driven network, where the preferential transition probability is in terms of the edge-weighting parameter. We also obtain the analytical expressions for stationary distribution and the coverage function in directed and undirected networks, all of which depend on the weight parameter. Appropriately adjusting this parameter, more effective search strategy can be obtained when compared with the unbiased random walk, whether in directed or undirected networks. Since network weights play a significant role in the diffusion process.

Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery.

PubMed

Feng, Yunlong; Lv, Shao-Gao; Hang, Hanyuan; Suykens, Johan A K

2016-03-01

Kernelized elastic net regularization (KENReg) is a kernelization of the well-known elastic net regularization (Zou & Hastie, 2005). The kernel in KENReg is not required to be a Mercer kernel since it learns from a kernelized dictionary in the coefficient space. Feng, Yang, Zhao, Lv, and Suykens (2014) showed that KENReg has some nice properties including stability, sparseness, and generalization. In this letter, we continue our study on KENReg by conducting a refined learning theory analysis. This letter makes the following three main contributions. First, we present refined error analysis on the generalization performance of KENReg. The main difficulty of analyzing the generalization error of KENReg lies in characterizing the population version of its empirical target function. We overcome this by introducing a weighted Banach space associated with the elastic net regularization. We are then able to conduct elaborated learning theory analysis and obtain fast convergence rates under proper complexity and regularity assumptions. Second, we study the sparse recovery problem in KENReg with fixed design and show that the kernelization may improve the sparse recovery ability compared to the classical elastic net regularization. Finally, we discuss the interplay among different properties of KENReg that include sparseness, stability, and generalization. We show that the stability of KENReg leads to generalization, and its sparseness confidence can be derived from generalization. Moreover, KENReg is stable and can be simultaneously sparse, which makes it attractive theoretically and practically.

Ongoing Walking Recovery 2 Years After Locomotor Training in a Child With Severe Incomplete Spinal Cord Injury

PubMed Central

Fox, Emily J.; Tester, Nicole J.; Phadke, Chetan P.; Nair, Preeti M.; Senesac, Claudia R.; Howland, Dena R.

2010-01-01

Background and Purpose The authors previously reported on walking recovery in a nonambulatory child with chronic, severe, incomplete cervical spinal cord injury (SCI) after 76 sessions of locomotor training (LT). Although clinical measures did not predict his recovery, reciprocal patterned leg movements developed, affording recovery of independent walking with a reverse rolling walker. The long-term functional limitations and secondary complications often associated with pediatric-onset SCI necessitate continued follow-up of children with SCI. Therefore, the purpose of this case report is to describe this child's walking function and musculoskeletal growth and development during the 2 years since his participation in an LT program and subsequent walking recovery. Case Description Following LT, the child attended elementary school as a full-time ambulator. He was evaluated 1 month (baseline), 1 year, and 2 years after LT. Examination of walking function included measures of walking independence, gait speed and spatiotemporal parameters, gait kinematics, and daily step activity. Growth and development were assessed by tracking his height, weight, incidence of musculoskeletal complications, and gross motor task performance. Outcomes Over the 2 years, the child continued to ambulate independently with a reverse rolling walker, increasing his fastest gait speed. Spatiotemporal and kinematic features of his walking improved, and daily step activity increased. Height and weight remained on their preinjury trajectory and within age-appropriate norms. The child experienced only minor musculoskeletal complications. Additionally, he gained the ability to use reciprocal patterned leg movements during locomotor tasks such as assisted stair climbing and independent tricycle pedaling. Conclusions Two years after recovery of walking, this child with incomplete SCI had maintained and improved his walking function and experienced age-appropriate growth and development. PMID:20299409

Phasic-to-tonic shift in trunk muscle activity relative to walking during low-impact weight bearing exercise

NASA Astrophysics Data System (ADS)

Caplan, Nick; Gibbon, Karl; Hibbs, Angela; Evetts, Simon; Debuse, Dorothée

2014-11-01

The aim of this study was to investigate the influence of an exercise device, designed to improve the function of lumbopelvic muscles via low-impact weight-bearing exercise, on electromyographic (EMG) activity of lumbopelvic, including abdominal muscles. Surface EMG activity was collected from lumbar multifidus (LM), erector spinae (ES), internal oblique (IO), external oblique (EO) and rectus abdominis (RA) during overground walking (OW) and exercise device (EX) conditions. During walking, most muscles showed peaks in activity which were not seen during EX. Spinal extensors (LM, ES) were more active in EX. Internal oblique and RA were less active in EX. In EX, LM and ES were active for longer than during OW. Conversely, EO and RA were active for a shorter duration in EX than OW. The exercise device showed a phasic-to-tonic shift in activation of both local and global lumbopelvic muscles and promoted increased activation of spinal extensors in relation to walking. These features could make the exercise device a useful rehabilitative tool for populations with lumbopelvic muscle atrophy and dysfunction, including those recovering from deconditioning due to long-term bed rest and microgravity in astronauts.

Physiological responses and energy cost of walking on the Gait Trainer with and without body weight support in subacute stroke patients

PubMed Central

2014-01-01

Background Robotic-assisted walking after stroke provides intensive task-oriented training. But, despite the growing diffusion of robotic devices little information is available about cardiorespiratory and metabolic responses during electromechanically-assisted repetitive walking exercise. Aim of the study was to determine whether use of an end-effector gait training (GT) machine with body weight support (BWS) would affect physiological responses and energy cost of walking (ECW) in subacute post-stroke hemiplegic patients. Methods Participants: six patients (patient group: PG) with hemiplegia due to stroke (age: 66 ± 15y; time since stroke: 8 ± 3 weeks; four men) and 6 healthy subjects as control group (CG: age, 76 ± 7y; six men). Interventions: overground walking test (OWT) and GT-assisted walking with 0%, 30% and 50% BWS (GT-BWS0%, 30% and 50%). Main Outcome Measures: heart rate (HR), pulmonary ventilation, oxygen consumption, respiratory exchange ratio (RER) and ECW. Results Intervention conditions significantly affected parameter values in steady state (HR: p = 0.005, V’E: p = 0.001, V'O2: p < 0.001) and the interaction condition per group affected ECW (p = 0.002). For PG, the most energy (V’O2 and ECW) demanding conditions were OWT and GT-BWS0%. On the contrary, for CG the least demanding condition was OWT. On the GT, increasing BWS produced a decrease in energy and cardiac demand in both groups. Conclusions In PG, GT-BWS walking resulted in less cardiometabolic demand than overground walking. This suggests that GT-BWS walking training might be safer than overground walking training in subacute stroke patients. PMID:24720844

Physiological responses and energy cost of walking on the Gait Trainer with and without body weight support in subacute stroke patients.

PubMed

Delussu, Anna Sofia; Morone, Giovanni; Iosa, Marco; Bragoni, Maura; Traballesi, Marco; Paolucci, Stefano

2014-04-10

Robotic-assisted walking after stroke provides intensive task-oriented training. But, despite the growing diffusion of robotic devices little information is available about cardiorespiratory and metabolic responses during electromechanically-assisted repetitive walking exercise. Aim of the study was to determine whether use of an end-effector gait training (GT) machine with body weight support (BWS) would affect physiological responses and energy cost of walking (ECW) in subacute post-stroke hemiplegic patients. six patients (patient group: PG) with hemiplegia due to stroke (age: 66 ± 15y; time since stroke: 8 ± 3 weeks; four men) and 6 healthy subjects as control group (CG: age, 76 ± 7y; six men). overground walking test (OWT) and GT-assisted walking with 0%, 30% and 50% BWS (GT-BWS0%, 30% and 50%). heart rate (HR), pulmonary ventilation, oxygen consumption, respiratory exchange ratio (RER) and ECW. Intervention conditions significantly affected parameter values in steady state (HR: p = 0.005, V'E: p = 0.001, V'O2: p < 0.001) and the interaction condition per group affected ECW (p = 0.002). For PG, the most energy (V'O2 and ECW) demanding conditions were OWT and GT-BWS0%. On the contrary, for CG the least demanding condition was OWT. On the GT, increasing BWS produced a decrease in energy and cardiac demand in both groups. In PG, GT-BWS walking resulted in less cardiometabolic demand than overground walking. This suggests that GT-BWS walking training might be safer than overground walking training in subacute stroke patients.

Straight-chain halocarbon forming fluids for TRISO fuel kernel production - Tests with yttria-stabilized zirconia microspheres

NASA Astrophysics Data System (ADS)

Baker, M. P.; King, J. C.; Gorman, B. P.; Braley, J. C.

2015-03-01

Current methods of TRISO fuel kernel production in the United States use a sol-gel process with trichloroethylene (TCE) as the forming fluid. After contact with radioactive materials, the spent TCE becomes a mixed hazardous waste, and high costs are associated with its recycling or disposal. Reducing or eliminating this mixed waste stream would not only benefit the environment, but would also enhance the economics of kernel production. Previous research yielded three candidates for testing as alternatives to TCE: 1-bromotetradecane, 1-chlorooctadecane, and 1-iodododecane. This study considers the production of yttria-stabilized zirconia (YSZ) kernels in silicone oil and the three chosen alternative formation fluids, with subsequent characterization of the produced kernels and used forming fluid. Kernels formed in silicone oil and bromotetradecane were comparable to those produced by previous kernel production efforts, while those produced in chlorooctadecane and iodododecane experienced gelation issues leading to poor kernel formation and geometry.

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach

PubMed Central

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-01-01

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification. PMID:28629202

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.

PubMed

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-06-19

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification.

Classification With Truncated Distance Kernel.

PubMed

Huang, Xiaolin; Suykens, Johan A K; Wang, Shuning; Hornegger, Joachim; Maier, Andreas

2018-05-01

This brief proposes a truncated distance (TL1) kernel, which results in a classifier that is nonlinear in the global region but is linear in each subregion. With this kernel, the subregion structure can be trained using all the training data and local linear classifiers can be established simultaneously. The TL1 kernel has good adaptiveness to nonlinearity and is suitable for problems which require different nonlinearities in different areas. Though the TL1 kernel is not positive semidefinite, some classical kernel learning methods are still applicable which means that the TL1 kernel can be directly used in standard toolboxes by replacing the kernel evaluation. In numerical experiments, the TL1 kernel with a pregiven parameter achieves similar or better performance than the radial basis function kernel with the parameter tuned by cross validation, implying the TL1 kernel a promising nonlinear kernel for classification tasks.

The Genetic Basis of Natural Variation in Kernel Size and Related Traits Using a Four-Way Cross Population in Maize.

PubMed

Chen, Jiafa; Zhang, Luyan; Liu, Songtao; Li, Zhimin; Huang, Rongrong; Li, Yongming; Cheng, Hongliang; Li, Xiantang; Zhou, Bo; Wu, Suowei; Chen, Wei; Wu, Jianyu; Ding, Junqiang

2016-01-01

Kernel size is an important component of grain yield in maize breeding programs. To extend the understanding on the genetic basis of kernel size traits (i.e., kernel length, kernel width and kernel thickness), we developed a set of four-way cross mapping population derived from four maize inbred lines with varied kernel sizes. In the present study, we investigated the genetic basis of natural variation in seed size and other components of maize yield (e.g., hundred kernel weight, number of rows per ear, number of kernels per row). In total, ten QTL affecting kernel size were identified, three of which (two for kernel length and one for kernel width) had stable expression in other components of maize yield. The possible genetic mechanism behind the trade-off of kernel size and yield components was discussed.

The Genetic Basis of Natural Variation in Kernel Size and Related Traits Using a Four-Way Cross Population in Maize

PubMed Central

Liu, Songtao; Li, Zhimin; Huang, Rongrong; Li, Yongming; Cheng, Hongliang; Li, Xiantang; Zhou, Bo; Wu, Suowei; Chen, Wei; Wu, Jianyu; Ding, Junqiang

2016-01-01

Kernel size is an important component of grain yield in maize breeding programs. To extend the understanding on the genetic basis of kernel size traits (i.e., kernel length, kernel width and kernel thickness), we developed a set of four-way cross mapping population derived from four maize inbred lines with varied kernel sizes. In the present study, we investigated the genetic basis of natural variation in seed size and other components of maize yield (e.g., hundred kernel weight, number of rows per ear, number of kernels per row). In total, ten QTL affecting kernel size were identified, three of which (two for kernel length and one for kernel width) had stable expression in other components of maize yield. The possible genetic mechanism behind the trade-off of kernel size and yield components was discussed. PMID:27070143

New mothers' views of weight and exercise.

PubMed

Groth, Susan W; David, Tamala

2008-01-01

To describe the attitudes and preferences of ethnically diverse new mothers on weight and exercise. Exploratory, qualitative study. Forty-nine ethnically diverse women were interviewed during the first year following childbirth regarding beliefs about weight, choices of exercise, walking for exercise, perceived benefits, barriers, and facilitators of exercise. Content analysis techniques were used to analyze the data. Weight was a significant concern for women, although the importance varied by race. New mothers reported that they would like to weigh less, and they endorsed walking for exercise. Common barriers to exercise were children and time constraints; health problems were also seen as a barrier to walking as a form of exercise. Scheduling the walk and having a walking partner were factors that women said would facilitate walking for physical activity during the first year after childbirth. Because new mothers perceive walking as a good form of exercise, nurses can use this information to help them plan a daily walking schedule to aid in weight loss and control postpartum. Nurses should also encourage new mothers to look for a walking partner, especially another new mother or a friend, to help them continue their physical activity during the first year after childbirth.

Intensive aerobic cycling training with lower limb weights in Chinese patients with chronic stroke: discordance between improved cardiovascular fitness and walking ability.

PubMed

Jin, Hong; Jiang, Yibo; Wei, Qin; Wang, Bilei; Ma, Genshan

2012-01-01

To evaluate the effect of aerobic cycling training with lower limb weights on cardiovascular fitness (peak VO(2)) and walking ability in chronic stroke survivors, and to investigate the relationship between changes in these parameters. 133 Chinese patients with chronic hemiparetic stroke (mean age 58 years) were randomized to either 8-week (5×/week) aerobic cycling training with lower limb weights group (n = 68) or a low-intensity overground walking group (n = 65). Peak VO(2), 6-minute walk distance (6MWD), knee muscle strength, balance and spasticity were measured before and after intervention. Cycling training increased peak VO(2) (24% vs. 3%, p < 0.001), 6MWD (2.7% vs. 0.5%, p < 0.001), paretic (11% vs. 1.6%, p < 0.001) and nonparetic knee strength (16% vs. 1.0%, p < 0.001). In the cycling group, percent changes in peak VO(2) were positively associated with those in paretic (r = 0.491, p < 0.001) and nonparetic knee strength (r = 0.432, p < 0.001). Increased 6MWD correlated significantly with improved balance, spasticity and paretic knee strength by the stepwise regression analysis (r(2) = 0.342, p = 0.004), but not fitness gains. The enhanced cardiovascular fitness after aerobic cycling training in Chinese patients with chronic stroke is not associated with the increased walking ability. Unparallel improvements in these parameters related different determinants may have implications for intervention strategy.

QTL Analysis of Kernel-Related Traits in Maize Using an Immortalized F2 Population

PubMed Central

Hu, Yanmin; Li, Weihua; Fu, Zhiyuan; Ding, Dong; Li, Haochuan; Qiao, Mengmeng; Tang, Jihua

2014-01-01

Kernel size and weight are important determinants of grain yield in maize. In this study, multivariate conditional and unconditional quantitative trait loci (QTL), and digenic epistatic analyses were utilized in order to elucidate the genetic basis for these kernel-related traits. Five kernel-related traits, including kernel weight (KW), volume (KV), length (KL), thickness (KT), and width (KWI), were collected from an immortalized F2 (IF2) maize population comprising of 243 crosses performed at two separate locations over a span of two years. A total of 54 unconditional main QTL for these five kernel-related traits were identified, many of which were clustered in chromosomal bins 6.04–6.06, 7.02–7.03, and 10.06–10.07. In addition, qKL3, qKWI6, qKV10a, qKV10b, qKW10a, and qKW7a were detected across multiple environments. Sixteen main QTL were identified for KW conditioned on the other four kernel traits (KL, KWI, KT, and KV). Thirteen main QTL were identified for KV conditioned on three kernel-shape traits. Conditional mapping analysis revealed that KWI and KV had the strongest influence on KW at the individual QTL level, followed by KT, and then KL; KV was mostly strongly influenced by KT, followed by KWI, and was least impacted by KL. Digenic epistatic analysis identified 18 digenic interactions involving 34 loci over the entire genome. However, only a small proportion of them were identical to the main QTL we detected. Additionally, conditional digenic epistatic analysis revealed that the digenic epistasis for KW and KV were entirely determined by their constituent traits. The main QTL identified in this study for determining kernel-related traits with high broad-sense heritability may play important roles during kernel development. Furthermore, digenic interactions were shown to exert relatively large effects on KL (the highest AA and DD effects were 4.6% and 6.7%, respectively) and KT (the highest AA effects were 4.3%). PMID:24586932

Idiopathic toe walking.

PubMed

Oetgen, Matthew E; Peden, Sean

2012-05-01

Toe walking is a bilateral gait abnormality in which a normal heel strike is absent and most weight bearing occurs through the forefoot. This abnormality may not be pathologic in patients aged <2 years, but it is a common reason for referral to an orthopaedic surgeon. Toe walking can be caused by several neurologic and developmental abnormalities and may be the first sign of a global developmental problem. Cases that lack a definitive etiology are categorized as idiopathic. A detailed history, with careful documentation of the developmental history, and a thorough physical examination are required in the child with a primary report of toe walking. Treatment is based on age and the severity of the abnormality. Management includes observation, stretching, casting, bracing, chemodenervation, and surgical lengthening of the gastrocnemius-soleus complex and/or Achilles tendon. An understanding of idiopathic toe walking as well as treatment options and their outcomes can help the physician individualize treatment to achieve optimal results.

Fruit position within the canopy affects kernel lipid composition of hazelnuts.

PubMed

Pannico, Antonio; Cirillo, Chiara; Giaccone, Matteo; Scognamiglio, Pasquale; Romano, Raffaele; Caporaso, Nicola; Sacchi, Raffaele; Basile, Boris

2017-11-01

The aim of this research was to study the variability in kernel composition within the canopy of hazelnut trees. Kernel fresh and dry weight increased linearly with fruit height above the ground. Fat content decreased, while protein and ash content increased, from the bottom to the top layers of the canopy. The level of unsaturation of fatty acids decreased from the bottom to the top of the canopy. Thus, the kernels located in the bottom layers of the canopy appear to be more interesting from a nutritional point of view, but their lipids may be more exposed to oxidation. The content of different phytosterols increased progressively from bottom to top canopy layers. Most of these effects correlated with the pattern in light distribution inside the canopy. The results of this study indicate that fruit position within the canopy is an important factor in determining hazelnut kernel growth and composition. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

The effects of gait training with body weight support (BWS) with no body weight support (no-BWS) in stroke patients.

PubMed

Ullah, Muhammad Asad; Shafi, Hina; Khan, Ghazanfar Ali; Malik, Arshad Nawaz; Amjad, Imran

2017-07-01

The purpose of this study was to measure the clinical outcomes for patients with stroke after gait training with body weight support (BWS) and with no body weight support (no-BWS).Experimental group was trained to walk by a BWS system with overhead harness (BWS group), and Control group was trained with full weight bearing walk on their lower extremities. Treatment session comprised of six weeks training. Treatment outcomes were assessed on the basis of Timed 10 Meter Walk Test, Timed Get Up and Go Test and Dynamic Gait Index. There was a significant (P<0.05) difference in BWS and NBWS for Dynamic Gait Index, Timed Get Up and Go Test, Timed 10 Meter Walk Test (Self-Selected Velocity), and Timed 10 Meter Walk Test (Fast-Velocity). Training of gait in stroke patients while a percentage of their body weight supported by a harness, resulted in better walking abilities than the Training of gait while full weight was placed on patient's lower extremities.

Parental perception of child’s weight status and subsequent BMIz change: the KOALA birth cohort study

PubMed Central

2014-01-01

Background Parents often fail to correctly perceive their children’s weight status, but no studies have examined the association between parental weight status perception and longitudinal BMIz change (BMI standardized to a reference population) at various ages. We investigated whether parents are able to accurately perceive their child’s weight status at age 5. We also investigated predictors of accurate weight status perception. Finally, we investigated the predictive value of accurate weight status perception in explaining children’s longitudinal weight development up to the age of 9, in children who were overweight at the age of 5. Methods We used longitudinal data from the KOALA Birth Cohort Study. At the child’s age of 5 years, parents filled out a questionnaire regarding child and parent characteristics and their perception of their child’s weight status. We calculated the children’s actual weight status from parental reports of weight and height at ages 2, 5, 6, 7, 8, and 9 years. Regression analyses were used to identify factors predicting which parents accurately perceived their child’s weight status. Finally, regression analyses were used to predict subsequent longitudinal BMIz change in overweight children. Results Eighty-five percent of the parents of overweight children underestimated their child’s weight status at age 5. The child’s BMIz at age 2 and 5 were significant positive predictors of accurate weight status perception (vs. underestimation) in normal weight and overweight children. Accurate weight status perception was a predictor of higher future BMI in overweight children, corrected for actual BMI at baseline. Conclusions Children of parents who accurately perceived their child’s weight status had a higher BMI over time, probably making it easier for parents to correctly perceive their child’s overweight. Parental awareness of the child’s overweight as such may not be sufficient for subsequent weight management by the

An efficient diagnosis system for Parkinson's disease using kernel-based extreme learning machine with subtractive clustering features weighting approach.

PubMed

Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Zhao, Xue-Hua

2014-01-01

A novel hybrid method named SCFW-KELM, which integrates effective subtractive clustering features weighting and a fast classifier kernel-based extreme learning machine (KELM), has been introduced for the diagnosis of PD. In the proposed method, SCFW is used as a data preprocessing tool, which aims at decreasing the variance in features of the PD dataset, in order to further improve the diagnostic accuracy of the KELM classifier. The impact of the type of kernel functions on the performance of KELM has been investigated in detail. The efficiency and effectiveness of the proposed method have been rigorously evaluated against the PD dataset in terms of classification accuracy, sensitivity, specificity, area under the receiver operating characteristic (ROC) curve (AUC), f-measure, and kappa statistics value. Experimental results have demonstrated that the proposed SCFW-KELM significantly outperforms SVM-based, KNN-based, and ELM-based approaches and other methods in the literature and achieved highest classification results reported so far via 10-fold cross validation scheme, with the classification accuracy of 99.49%, the sensitivity of 100%, the specificity of 99.39%, AUC of 99.69%, the f-measure value of 0.9964, and kappa value of 0.9867. Promisingly, the proposed method might serve as a new candidate of powerful methods for the diagnosis of PD with excellent performance.

An Efficient Diagnosis System for Parkinson's Disease Using Kernel-Based Extreme Learning Machine with Subtractive Clustering Features Weighting Approach

PubMed Central

Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Zhao, Xue-Hua

2014-01-01

A novel hybrid method named SCFW-KELM, which integrates effective subtractive clustering features weighting and a fast classifier kernel-based extreme learning machine (KELM), has been introduced for the diagnosis of PD. In the proposed method, SCFW is used as a data preprocessing tool, which aims at decreasing the variance in features of the PD dataset, in order to further improve the diagnostic accuracy of the KELM classifier. The impact of the type of kernel functions on the performance of KELM has been investigated in detail. The efficiency and effectiveness of the proposed method have been rigorously evaluated against the PD dataset in terms of classification accuracy, sensitivity, specificity, area under the receiver operating characteristic (ROC) curve (AUC), f-measure, and kappa statistics value. Experimental results have demonstrated that the proposed SCFW-KELM significantly outperforms SVM-based, KNN-based, and ELM-based approaches and other methods in the literature and achieved highest classification results reported so far via 10-fold cross validation scheme, with the classification accuracy of 99.49%, the sensitivity of 100%, the specificity of 99.39%, AUC of 99.69%, the f-measure value of 0.9964, and kappa value of 0.9867. Promisingly, the proposed method might serve as a new candidate of powerful methods for the diagnosis of PD with excellent performance. PMID:25484912

A Fast Reduced Kernel Extreme Learning Machine.

PubMed

Deng, Wan-Yu; Ong, Yew-Soon; Zheng, Qing-Hua

2016-04-01

In this paper, we present a fast and accurate kernel-based supervised algorithm referred to as the Reduced Kernel Extreme Learning Machine (RKELM). In contrast to the work on Support Vector Machine (SVM) or Least Square SVM (LS-SVM), which identifies the support vectors or weight vectors iteratively, the proposed RKELM randomly selects a subset of the available data samples as support vectors (or mapping samples). By avoiding the iterative steps of SVM, significant cost savings in the training process can be readily attained, especially on Big datasets. RKELM is established based on the rigorous proof of universal learning involving reduced kernel-based SLFN. In particular, we prove that RKELM can approximate any nonlinear functions accurately under the condition of support vectors sufficiency. Experimental results on a wide variety of real world small instance size and large instance size applications in the context of binary classification, multi-class problem and regression are then reported to show that RKELM can perform at competitive level of generalized performance as the SVM/LS-SVM at only a fraction of the computational effort incurred. Copyright © 2015 Elsevier Ltd. All rights reserved.

A longitudinal study of childhood obesity, weight status change, and subsequent academic performance in Taiwanese children.

PubMed

Chen, Li-Jung; Fox, Kenneth R; Ku, Po-Wen; Wang, Ching-Hui

2012-09-01

This study examined the association among childhood obesity, weight status change, and subsequent academic performance at 6-year follow-up. First-grade students from one elementary school district in Taichung City, Taiwan were followed for 6 years (N = 409). Academic performance was extracted from the school records at the end of each grade. Weight and height were measured at the beginning of each grade. A weight change variable was created based on each child's weight status difference at grades 1 and 6. A multivariate linear regression model for predicting academic performance at grade 6 was developed with adjustment for individual characteristics and family factors. A latent growth curve (LGC) showed the association between changes in body mass index (BMI) and in academic performance across a 6-year period. BMI in children increased significantly across 6 years. The rate of increase in BMI over 6 years was higher for children with higher baseline BMIs than it was for children with lower baseline BMIs. However, BMI changes were not significantly associated with changes of academic performance. There was no significant relationship between initial obesity or change in weight status and subsequent academic performance. It appears that either being or becoming overweight/obese did not impact academic achievement for these Taiwanese children. © 2012, American School Health Association.

Multiple Kernel Sparse Representation based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension.

PubMed

Zhang, Guoqing; Sun, Huaijiang; Xia, Guiyu; Sun, Quansen

2016-07-07

Sparse representation based classification (SRC) has been developed and shown great potential for real-world application. Based on SRC, Yang et al. [10] devised a SRC steered discriminative projection (SRC-DP) method. However, as a linear algorithm, SRC-DP cannot handle the data with highly nonlinear distribution. Kernel sparse representation-based classifier (KSRC) is a non-linear extension of SRC and can remedy the drawback of SRC. KSRC requires the use of a predetermined kernel function and selection of the kernel function and its parameters is difficult. Recently, multiple kernel learning for SRC (MKL-SRC) [22] has been proposed to learn a kernel from a set of base kernels. However, MKL-SRC only considers the within-class reconstruction residual while ignoring the between-class relationship, when learning the kernel weights. In this paper, we propose a novel multiple kernel sparse representation-based classifier (MKSRC), and then we use it as a criterion to design a multiple kernel sparse representation based orthogonal discriminative projection method (MK-SR-ODP). The proposed algorithm aims at learning a projection matrix and a corresponding kernel from the given base kernels such that in the low dimension subspace the between-class reconstruction residual is maximized and the within-class reconstruction residual is minimized. Furthermore, to achieve a minimum overall loss by performing recognition in the learned low-dimensional subspace, we introduce cost information into the dimensionality reduction method. The solutions for the proposed method can be efficiently found based on trace ratio optimization method [33]. Extensive experimental results demonstrate the superiority of the proposed algorithm when compared with the state-of-the-art methods.

A New Family of Solvable Pearson-Dirichlet Random Walks

NASA Astrophysics Data System (ADS)

Le Caër, Gérard

2011-07-01

An n-step Pearson-Gamma random walk in ℝ d starts at the origin and consists of n independent steps with gamma distributed lengths and uniform orientations. The gamma distribution of each step length has a shape parameter q>0. Constrained random walks of n steps in ℝ d are obtained from the latter walks by imposing that the sum of the step lengths is equal to a fixed value. Simple closed-form expressions were obtained in particular for the distribution of the endpoint of such constrained walks for any d≥ d 0 and any n≥2 when q is either q = d/2 - 1 ( d 0=3) or q= d-1 ( d 0=2) (Le Caër in J. Stat. Phys. 140:728-751, 2010). When the total walk length is chosen, without loss of generality, to be equal to 1, then the constrained step lengths have a Dirichlet distribution whose parameters are all equal to q and the associated walk is thus named a Pearson-Dirichlet random walk. The density of the endpoint position of a n-step planar walk of this type ( n≥2), with q= d=2, was shown recently to be a weighted mixture of 1+ floor( n/2) endpoint densities of planar Pearson-Dirichlet walks with q=1 (Beghin and Orsingher in Stochastics 82:201-229, 2010). The previous result is generalized to any walk space dimension and any number of steps n≥2 when the parameter of the Pearson-Dirichlet random walk is q= d>1. We rely on the connection between an unconstrained random walk and a constrained one, which have both the same n and the same q= d, to obtain a closed-form expression of the endpoint density. The latter is a weighted mixture of 1+ floor( n/2) densities with simple forms, equivalently expressed as a product of a power and a Gauss hypergeometric function. The weights are products of factors which depends both on d and n and Bessel numbers independent of d.

Optimized Kernel Entropy Components.

PubMed

Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau

2017-06-01

This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.

Walking to health.

PubMed

Morris, J N; Hardman, A E

1997-05-01

Walking is a rhythmic, dynamic, aerobic activity of large skeletal muscles that confers the multifarious benefits of this with minimal adverse effects. Walking, faster than customary, and regularly in sufficient quantity into the 'training zone' of over 70% of maximal heart rate, develops and sustains physical fitness: the cardiovascular capacity and endurance (stamina) for bodily work and movement in everyday life that also provides reserves for meeting exceptional demands. Muscles of the legs, limb girdle and lower trunk are strengthened and the flexibility of their cardinal joints preserved; posture and carriage may improve. Any amount of walking, and at any pace, expends energy. Hence the potential, long term, of walking for weight control. Dynamic aerobic exercise, as in walking, enhances a multitude of bodily processes that are inherent in skeletal muscle activity, including the metabolism of high density lipoproteins and insulin/glucose dynamics. Walking is also the most common weight-bearing activity, and there are indications at all ages of an increase in related bone strength. The pleasurable and therapeutic, psychological and social dimensions of walking, whilst evident, have been surprisingly little studied. Nor has an economic assessment of the benefits and costs of walking been attempted. Walking is beneficial through engendering improved fitness and/or greater physiological activity and energy turnover. Two main modes of such action are distinguished as: (i) acute, short term effects of the exercise; and (ii) chronic, cumulative adaptations depending on habitual activity over weeks and months. Walking is often included in studies of exercise in relation to disease but it has seldom been specifically tested. There is, nevertheless, growing evidence of gains in the prevention of heart attack and reduction of total death rates, in the treatment of hypertension, intermittent claudication and musculoskeletal disorders, and in rehabilitation after heart

Obesity does not increase External Mechanical Work per kilogram body mass during Walking

PubMed Central

Browning, Raymond C.; McGowan, Craig P.; Kram, Rodger

2009-01-01

Walking is the most common type of physical activity prescribed for the treatment of obesity. The net metabolic rate during level walking (Watts/kg) is ~10% greater in obese vs. normal weight adults. External mechanical work (Wext) is one of the primary determinants of the metabolic cost of walking, but the effects of obesity on Wext have not been clearly established. The purpose of this study was to compare Wext between obese and normal weight adults across a range of walking speeds. We hypothesized that Wext (J/step) would be greater in obese adults but Wext normalized to body mass would be similar in obese and normal weight adults. We collected right leg three-dimensional ground reaction forces (GRF) while twenty adults (10 obese, BMI=35.6 kg/m2 and 10 normal weight, BMI=22.1 kg/m2) walked on a level, dual-belt force measuring treadmill at six speeds (0.50–1.75 m/s). We used the individual limb method (ILM) to calculate external work done on the center of mass. Absolute Wext (J/step) was greater in obese vs. normal weight adults at each walking speed, but relative Wext (J/step/kg) was similar between the groups. Step frequencies were not different. These results suggest that Wext is not responsible for the greater metabolic cost of walking (W/kg) in moderately obese adults. PMID:19646701

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2014 CFR

2014-01-01

... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2011 CFR

2011-01-01

... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2012 CFR

2012-01-01

... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2013 CFR

2013-01-01

... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

Genetic, Genomic, and Breeding Approaches to Further Explore Kernel Composition Traits and Grain Yield in Maize

ERIC Educational Resources Information Center

Da Silva, Helena Sofia Pereira

2009-01-01

Maize ("Zea mays L.") is a model species well suited for the dissection of complex traits which are often of commercial value. The purpose of this research was to gain a deeper understanding of the genetic control of maize kernel composition traits starch, protein, and oil concentration, and also kernel weight and grain yield. Germplasm with…

UNICOS Kernel Internals Application Development

NASA Technical Reports Server (NTRS)

Caredo, Nicholas; Craw, James M. (Technical Monitor)

1995-01-01

Having an understanding of UNICOS Kernel Internals is valuable information. However, having the knowledge is only half the value. The second half comes with knowing how to use this information and apply it to the development of tools. The kernel contains vast amounts of useful information that can be utilized. This paper discusses the intricacies of developing utilities that utilize kernel information. In addition, algorithms, logic, and code will be discussed for accessing kernel information. Code segments will be provided that demonstrate how to locate and read kernel structures. Types of applications that can utilize kernel information will also be discussed.

Physical activity patterns in morbidly obese and normal-weight women.

PubMed

Kwon, Soyang; Mohammad, Jamal; Samuel, Isaac

2011-01-01

To compare physical activity patterns between morbidly obese and normal-weight women. Daily physical activity of 18 morbidly obese and 7 normal-weight women aged 30-58 years was measured for 2 days using the Intelligent Device for Energy Expenditure and Activity (IDEEA) device. The obese group spent about 2 hr/day less standing and 30 min/day less walking than did the normal-weight group. Time spent standing (standing time) was positively associated with time spent walking (walking time). Age- and walking time-adjusted standing time did not differ according to weight status. Promoting standing may be a strategy to increase walking.

The Crash Intensity Evaluation Using General Centrality Criterions and a Geographically Weighted Regression

NASA Astrophysics Data System (ADS)

Ghadiriyan Arani, M.; Pahlavani, P.; Effati, M.; Noori Alamooti, F.

2017-09-01

Today, one of the social problems influencing on the lives of many people is the road traffic crashes especially the highway ones. In this regard, this paper focuses on highway of capital and the most populous city in the U.S. state of Georgia and the ninth largest metropolitan area in the United States namely Atlanta. Geographically weighted regression and general centrality criteria are the aspects of traffic used for this article. In the first step, in order to estimate of crash intensity, it is needed to extract the dual graph from the status of streets and highways to use general centrality criteria. With the help of the graph produced, the criteria are: Degree, Pageranks, Random walk, Eccentricity, Closeness, Betweenness, Clustering coefficient, Eigenvector, and Straightness. The intensity of crash point is counted for every highway by dividing the number of crashes in that highway to the total number of crashes. Intensity of crash point is calculated for each highway. Then, criteria and crash point were normalized and the correlation between them was calculated to determine the criteria that are not dependent on each other. The proposed hybrid approach is a good way to regression issues because these effective measures result to a more desirable output. R2 values for geographically weighted regression using the Gaussian kernel was 0.539 and also 0.684 was obtained using a triple-core cube. The results showed that the triple-core cube kernel is better for modeling the crash intensity.

Scaling of average weighted shortest path and average receiving time on weighted expanded Koch networks

NASA Astrophysics Data System (ADS)

Wu, Zikai; Hou, Baoyu; Zhang, Hongjuan; Jin, Feng

2014-04-01

Deterministic network models have been attractive media for discussing dynamical processes' dependence on network structural features. On the other hand, the heterogeneity of weights affect dynamical processes taking place on networks. In this paper, we present a family of weighted expanded Koch networks based on Koch networks. They originate from a r-polygon, and each node of current generation produces m r-polygons including the node and whose weighted edges are scaled by factor w in subsequent evolutionary step. We derive closed-form expressions for average weighted shortest path length (AWSP). In large network, AWSP stays bounded with network order growing (0 < w < 1). Then, we focus on a special random walks and trapping issue on the networks. In more detail, we calculate exactly the average receiving time (ART). ART exhibits a sub-linear dependence on network order (0 < w < 1), which implies that nontrivial weighted expanded Koch networks are more efficient than un-weighted expanded Koch networks in receiving information. Besides, efficiency of receiving information at hub nodes is also dependent on parameters m and r. These findings may pave the way for controlling information transportation on general weighted networks.

Carbothermic Synthesis of ~820- m UN Kernels. Investigation of Process Variables

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

Lindemer, Terrence; Silva, Chinthaka M; Henry, Jr, John James

2015-06-01

This report details the continued investigation of process variables involved in converting sol-gel-derived, urainia-carbon microspheres to ~820-μm-dia. UN fuel kernels in flow-through, vertical refractory-metal crucibles at temperatures up to 2123 K. Experiments included calcining of air-dried UO 3-H 2O-C microspheres in Ar and H 2-containing gases, conversion of the resulting UO 2-C kernels to dense UO 2:2UC in the same gases and vacuum, and its conversion in N 2 to in UC 1-xN x. The thermodynamics of the relevant reactions were applied extensively to interpret and control the process variables. Producing the precursor UO 2:2UC kernel of ~96% theoretical densitymore » was required, but its subsequent conversion to UC 1-xN x at 2123 K was not accompanied by sintering and resulted in ~83-86% of theoretical density. Decreasing the UC 1-xN x kernel carbide component via HCN evolution was shown to be quantitatively consistent with present and past experiments and the only useful application of H2 in the entire process.« less

Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection.

PubMed

Wang, Shunfang; Nie, Bing; Yue, Kun; Fei, Yu; Li, Wenjia; Xu, Dongshu

2017-12-15

Kernel discriminant analysis (KDA) is a dimension reduction and classification algorithm based on nonlinear kernel trick, which can be novelly used to treat high-dimensional and complex biological data before undergoing classification processes such as protein subcellular localization. Kernel parameters make a great impact on the performance of the KDA model. Specifically, for KDA with the popular Gaussian kernel, to select the scale parameter is still a challenging problem. Thus, this paper introduces the KDA method and proposes a new method for Gaussian kernel parameter selection depending on the fact that the differences between reconstruction errors of edge normal samples and those of interior normal samples should be maximized for certain suitable kernel parameters. Experiments with various standard data sets of protein subcellular localization show that the overall accuracy of protein classification prediction with KDA is much higher than that without KDA. Meanwhile, the kernel parameter of KDA has a great impact on the efficiency, and the proposed method can produce an optimum parameter, which makes the new algorithm not only perform as effectively as the traditional ones, but also reduce the computational time and thus improve efficiency.

7 CFR 981.7 - Edible kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Edible kernel. 981.7 Section 981.7 Agriculture... Regulating Handling Definitions § 981.7 Edible kernel. Edible kernel means a kernel, piece, or particle of almond kernel that is not inedible. [41 FR 26852, June 30, 1976] ...

Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation

PubMed Central

Sun, Rui; Zhang, Guanghai; Yan, Xiaoxing; Gao, Jun

2016-01-01

Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods. PMID:27537888

Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation.

PubMed

Sun, Rui; Zhang, Guanghai; Yan, Xiaoxing; Gao, Jun

2016-08-16

Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods.

Gait pattern of severely disabled hemiparetic subjects on a new controlled gait trainer as compared to assisted treadmill walking with partial body weight support.

PubMed

Hesse, S; Uhlenbrock, D; Sarkodie-Gyan, T

1999-10-01

To investigate to what extent and with how much therapeutic effort nonambulatory stroke patients could train a gait-like movement on a newly developed, machine-supported gait trainer. Open study comparing the movement on the gait trainer with assisted walking on the treadmill. Motion analysis laboratory of a rehabilitation centre. Fourteen chronic, nonambulatory hemiparetic patients. Complex gait analysis while training on the gait trainer and while walking on the treadmill. Gait kinematics, kinesiological EMG of several lower limb muscles and the required assistance. Patients could train a gait-like movement on the gait trainer, characterized kinematically by a perfect symmetry, larger hip extension during stance, less knee flexion and less ankle plantar flexion during swing as compared to treadmill walking (p <0.01). The pattern and amount of activation of relevant weight-bearing muscles was comparable with an even larger activation of the M. biceps femoris on the gait trainer (p <0.01). The tibialis anterior muscle of the nonaffected side, however, was less activated during swing (p <0.01). Two therapists assisted walking on the treadmill while only one therapist was necessary to help with weight shifting on the new device. The newly developed gait trainer offered severely disabled hemiparetic subjects the possibility of training a gait-like, highly symmetrical movement with a favourable facilitation of relevant anti-gravity muscles. At the same time, the effort required of the therapists was reduced.

The scalable implementation of quantum walks using classical light

NASA Astrophysics Data System (ADS)

Goyal, Sandeep K.; Roux, F. S.; Forbes, Andrew; Konrad, Thomas

2014-02-01

A quantum walk is the quantum analog of the classical random walks. Despite their simple structure they form a universal platform to implement any algorithm of quantum computation. However, it is very hard to realize quantum walks with a sufficient number of iterations in quantum systems due to their sensitivity to environmental influences and subsequent loss of coherence. Here we present a scalable implementation scheme for one-dimensional quantum walks for arbitrary number of steps using the orbital angular momentum modes of classical light beams. Furthermore, we show that using the same setup with a minor adjustment we can also realize electric quantum walks.

A novel prescription pedometer-assisted walking intervention and weight management for Chinese occupational population.

PubMed

Yu, Yingxiang; Lv, Yiran; Yao, Bin; Duan, Liguang; Zhang, Xiaoyuan; Xie, Lan; Chang, Cuiqing

2018-01-01

significantly lower and lifestyle behavior significantly improved (p < 0.05). The prescription pedometer-assisted walking intervention can effectively improve exercise adherence and manage weight. This approach was also effective in controlling the risk factors of weight-related chronic diseases. Chinese Clinical Trial Registry (ChiCTR) ChiCTR-OOh-16010229.

7 CFR 981.8 - Inedible kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.8 Section 981.8 Agriculture... Regulating Handling Definitions § 981.8 Inedible kernel. Inedible kernel means a kernel, piece, or particle of almond kernel with any defect scored as serious damage, or damage due to mold, gum, shrivel, or...

7 CFR 51.1415 - Inedible kernels.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Inedible kernels. 51.1415 Section 51.1415 Agriculture... Standards for Grades of Pecans in the Shell 1 Definitions § 51.1415 Inedible kernels. Inedible kernels means that the kernel or pieces of kernels are rancid, moldy, decayed, injured by insects or otherwise...

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.408 Section 981.408 Agriculture... Administrative Rules and Regulations § 981.408 Inedible kernel. Pursuant to § 981.8, the definition of inedible kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as...

TURBULENCE-INDUCED RELATIVE VELOCITY OF DUST PARTICLES. IV. THE COLLISION KERNEL

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

Pan, Liubin; Padoan, Paolo, E-mail: lpan@cfa.harvard.edu, E-mail: ppadoan@icc.ub.edu

Motivated by its importance for modeling dust particle growth in protoplanetary disks, we study turbulence-induced collision statistics of inertial particles as a function of the particle friction time, τ{sub p}. We show that turbulent clustering significantly enhances the collision rate for particles of similar sizes with τ{sub p} corresponding to the inertial range of the flow. If the friction time, τ{sub p,} {sub h}, of the larger particle is in the inertial range, the collision kernel per unit cross section increases with increasing friction time, τ{sub p,} {sub l}, of the smaller particle and reaches the maximum at τ{sub p,}more » {sub l} = τ{sub p,} {sub h}, where the clustering effect peaks. This feature is not captured by the commonly used kernel formula, which neglects the effect of clustering. We argue that turbulent clustering helps alleviate the bouncing barrier problem for planetesimal formation. We also investigate the collision velocity statistics using a collision-rate weighting factor to account for higher collision frequency for particle pairs with larger relative velocity. For τ{sub p,} {sub h} in the inertial range, the rms relative velocity with collision-rate weighting is found to be invariant with τ{sub p,} {sub l} and scales with τ{sub p,} {sub h} roughly as ∝ τ{sub p,h}{sup 1/2}. The weighting factor favors collisions with larger relative velocity, and including it leads to more destructive and less sticking collisions. We compare two collision kernel formulations based on spherical and cylindrical geometries. The two formulations give consistent results for the collision rate and the collision-rate weighted statistics, except that the spherical formulation predicts more head-on collisions than the cylindrical formulation.« less

The utilization of endopower β in commercial feed which contains palm kernel cake on performance of broiler chicken

NASA Astrophysics Data System (ADS)

Purba, S. S. A.; Tafsin, M.; Ginting, S. P.; Khairani, Y.

2018-02-01

Palm kernel cake is an agricultural waste that can be used as raw material in the preparation of poultry rations. The design used was Completely Randomized Design (CRD) with 5 treatments and 4 replications. Level endopower β used 0 % (R0), 0.02% (R1), 0.04% (R2) and 0.06% (R3). The results showed that R0a and R0b were significantly different from R3 in terms of diet consumption, body weight gain and the conversion ratio The utilization of endopower β in commercial diets containing palm kernel cake in broilers can increase body weight gain, feed consumption, improve feed use efficiency and even energy. It is concluded that utilization endpower β improve performances of broiler chicken fed by diet containing palm kernel cake.

LZW-Kernel: fast kernel utilizing variable length code blocks from LZW compressors for protein sequence classification.

PubMed

Filatov, Gleb; Bauwens, Bruno; Kertész-Farkas, Attila

2018-05-07

Bioinformatics studies often rely on similarity measures between sequence pairs, which often pose a bottleneck in large-scale sequence analysis. Here, we present a new convolutional kernel function for protein sequences called the LZW-Kernel. It is based on code words identified with the Lempel-Ziv-Welch (LZW) universal text compressor. The LZW-Kernel is an alignment-free method, it is always symmetric, is positive, always provides 1.0 for self-similarity and it can directly be used with Support Vector Machines (SVMs) in classification problems, contrary to normalized compression distance (NCD), which often violates the distance metric properties in practice and requires further techniques to be used with SVMs. The LZW-Kernel is a one-pass algorithm, which makes it particularly plausible for big data applications. Our experimental studies on remote protein homology detection and protein classification tasks reveal that the LZW-Kernel closely approaches the performance of the Local Alignment Kernel (LAK) and the SVM-pairwise method combined with Smith-Waterman (SW) scoring at a fraction of the time. Moreover, the LZW-Kernel outperforms the SVM-pairwise method when combined with BLAST scores, which indicates that the LZW code words might be a better basis for similarity measures than local alignment approximations found with BLAST. In addition, the LZW-Kernel outperforms n-gram based mismatch kernels, hidden Markov model based SAM and Fisher kernel, and protein family based PSI-BLAST, among others. Further advantages include the LZW-Kernel's reliance on a simple idea, its ease of implementation, and its high speed, three times faster than BLAST and several magnitudes faster than SW or LAK in our tests. LZW-Kernel is implemented as a standalone C code and is a free open-source program distributed under GPLv3 license and can be downloaded from https://github.com/kfattila/LZW-Kernel. akerteszfarkas@hse.ru. Supplementary data are available at Bioinformatics Online.

Data-Driven Hierarchical Structure Kernel for Multiscale Part-Based Object Recognition

PubMed Central

Wang, Botao; Xiong, Hongkai; Jiang, Xiaoqian; Zheng, Yuan F.

2017-01-01

Detecting generic object categories in images and videos are a fundamental issue in computer vision. However, it faces the challenges from inter and intraclass diversity, as well as distortions caused by viewpoints, poses, deformations, and so on. To solve object variations, this paper constructs a structure kernel and proposes a multiscale part-based model incorporating the discriminative power of kernels. The structure kernel would measure the resemblance of part-based objects in three aspects: 1) the global similarity term to measure the resemblance of the global visual appearance of relevant objects; 2) the part similarity term to measure the resemblance of the visual appearance of distinctive parts; and 3) the spatial similarity term to measure the resemblance of the spatial layout of parts. In essence, the deformation of parts in the structure kernel is penalized in a multiscale space with respect to horizontal displacement, vertical displacement, and scale difference. Part similarities are combined with different weights, which are optimized efficiently to maximize the intraclass similarities and minimize the interclass similarities by the normalized stochastic gradient ascent algorithm. In addition, the parameters of the structure kernel are learned during the training process with regard to the distribution of the data in a more discriminative way. With flexible part sizes on scale and displacement, it can be more robust to the intraclass variations, poses, and viewpoints. Theoretical analysis and experimental evaluations demonstrate that the proposed multiscale part-based representation model with structure kernel exhibits accurate and robust performance, and outperforms state-of-the-art object classification approaches. PMID:24808345

Optimization of fixture layouts of glass laser optics using multiple kernel regression.

PubMed

Su, Jianhua; Cao, Enhua; Qiao, Hong

2014-05-10

We aim to build an integrated fixturing model to describe the structural properties and thermal properties of the support frame of glass laser optics. Therefore, (a) a near global optimal set of clamps can be computed to minimize the surface shape error of the glass laser optic based on the proposed model, and (b) a desired surface shape error can be obtained by adjusting the clamping forces under various environmental temperatures based on the model. To construct the model, we develop a new multiple kernel learning method and call it multiple kernel support vector functional regression. The proposed method uses two layer regressions to group and order the data sources by the weights of the kernels and the factors of the layers. Because of that, the influences of the clamps and the temperature can be evaluated by grouping them into different layers.

Considering causal genes in the genetic dissection of kernel traits in common wheat.

PubMed

Mohler, Volker; Albrecht, Theresa; Castell, Adelheid; Diethelm, Manuela; Schweizer, Günther; Hartl, Lorenz

2016-11-01

Genetic factors controlling thousand-kernel weight (TKW) were characterized for their association with other seed traits, including kernel width, kernel length, ratio of kernel width to kernel length (KW/KL), kernel area, and spike number per m 2 (SN). For this purpose, a genetic map was established utilizing a doubled haploid population derived from a cross between German winter wheat cultivars Pamier and Format. Association studies in a diversity panel of elite cultivars supplemented genetic analysis of kernel traits. In both populations, genomic signatures of 13 candidate genes for TKW and kernel size were analyzed. Major quantitative trait loci (QTL) for TKW were identified on chromosomes 1B, 2A, 2D, and 4D, and their locations coincided with major QTL for kernel size traits, supporting the common belief that TKW is a function of other kernel traits. The QTL on chromosome 2A was associated with TKW candidate gene TaCwi-A1 and the QTL on chromosome 4D was associated with dwarfing gene Rht-D1. A minor QTL for TKW on chromosome 6B coincided with TaGW2-6B. The QTL for kernel dimensions that did not affect TKW were detected on eight chromosomes. A major QTL for KW/KL located at the distal tip of chromosome arm 5AS is being reported for the first time. TaSus1-7A and TaSAP-A1, closely linked to each other on chromosome 7A, could be related to a minor QTL for KW/KL. Genetic analysis of SN confirmed its negative correlation with TKW in this cross. In the diversity panel, TaSus1-7A was associated with TKW. Compared to the Pamier/Format bi-parental population where TaCwi-A1a was associated with higher TKW, the same allele reduced grain yield in the diversity panel, suggesting opposite effects of TaCwi-A1 on these two traits.

Partial Deconvolution with Inaccurate Blur Kernel.

PubMed

Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei

2017-10-17

Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning

Comparison of forward versus backward walking using body weight supported treadmill training in an individual with a spinal cord injury: a single subject design.

PubMed

Moriello, Gabriele; Pathare, Neeti; Cirone, Cono; Pastore, Danielle; Shears, Dacia; Sulehri, Sahira

2014-01-01

Body weight supported treadmill training (BWSTT) is a task-specific intervention that promotes functional locomotion. There is no research evaluating the effect of backward walking (BW) using BWSTT in individuals with spinal cord injury (SCI). The purpose of this single subject design was to examine the differences between forward walking (FW) and BW training using BWSTT in an individual with quadriparesis. The participant was a 57-year-old male with incomplete C3-C6 SCI. An ABABAB design (A = BW; B = FW; each phase = 3 weeks of biweekly sessions) was utilized. Outcome measures included: gait parameters; a timed 4-meter walk; the 5-repetition sit-to-stand test (STST); tandem stance time; and 6-minute walk test (6MWT). Data was analyzed with split level method of trend estimation. Improvements in gait parameters, on the timed 4-meter walk, 6MWT, tandem balance and aerobic endurance were similar with FW and BW training. The only difference between FW and BW training was that BW training resulted in greater improvements in the STST. The results of this study suggest that in this individual backward walking training was advantageous, resulting in improved ability to perform the 5-repetition STST. It is suspected that these changes can be attributed to the differences in muscle activation and task difficulty between FW and BW.

The walking robot project

NASA Technical Reports Server (NTRS)

Williams, P.; Sagraniching, E.; Bennett, M.; Singh, R.

1991-01-01

A walking robot was designed, analyzed, and tested as an intelligent, mobile, and a terrain adaptive system. The robot's design was an application of existing technologies. The design of the six legs modified and combines well understood mechanisms and was optimized for performance, flexibility, and simplicity. The body design incorporated two tripods for walking stability and ease of turning. The electrical hardware design used modularity and distributed processing to drive the motors. The software design used feedback to coordinate the system and simple keystrokes to give commands. The walking machine can be easily adapted to hostile environments such as high radiation zones and alien terrain. The primary goal of the leg design was to create a leg capable of supporting a robot's body and electrical hardware while walking or performing desired tasks, namely those required for planetary exploration. The leg designers intent was to study the maximum amount of flexibility and maneuverability achievable by the simplest and lightest leg design. The main constraints for the leg design were leg kinematics, ease of assembly, degrees of freedom, number of motors, overall size, and weight.

Pollen source effects on growth of kernel structures and embryo chemical compounds in maize.

PubMed

Tanaka, W; Mantese, A I; Maddonni, G A

2009-08-01

Previous studies have reported effects of pollen source on the oil concentration of maize (Zea mays) kernels through modifications to both the embryo/kernel ratio and embryo oil concentration. The present study expands upon previous analyses by addressing pollen source effects on the growth of kernel structures (i.e. pericarp, endosperm and embryo), allocation of embryo chemical constituents (i.e. oil, protein, starch and soluble sugars), and the anatomy and histology of the embryos. Maize kernels with different oil concentration were obtained from pollinations with two parental genotypes of contrasting oil concentration. The dynamics of the growth of kernel structures and allocation of embryo chemical constituents were analysed during the post-flowering period. Mature kernels were dissected to study the anatomy (embryonic axis and scutellum) and histology [cell number and cell size of the scutellums, presence of sub-cellular structures in scutellum tissue (starch granules, oil and protein bodies)] of the embryos. Plants of all crosses exhibited a similar kernel number and kernel weight. Pollen source modified neither the growth period of kernel structures, nor pericarp growth rate. By contrast, pollen source determined a trade-off between embryo and endosperm growth rates, which impacted on the embryo/kernel ratio of mature kernels. Modifications to the embryo size were mediated by scutellum cell number. Pollen source also affected (P < 0.01) allocation of embryo chemical compounds. Negative correlations among embryo oil concentration and those of starch (r = 0.98, P < 0.01) and soluble sugars (r = 0.95, P < 0.05) were found. Coincidently, embryos with low oil concentration had an increased (P < 0.05-0.10) scutellum cell area occupied by starch granules and fewer oil bodies. The effects of pollen source on both embryo/kernel ratio and allocation of embryo chemicals seems to be related to the early established sink strength (i.e. sink size and sink activity) of the

7 CFR 51.2295 - Half kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Half kernel. 51.2295 Section 51.2295 Agriculture... Standards for Shelled English Walnuts (Juglans Regia) Definitions § 51.2295 Half kernel. Half kernel means the separated half of a kernel with not more than one-eighth broken off. ...

Varied overground walking training versus body-weight-supported treadmill training in adults within 1 year of stroke: a randomized controlled trial.

PubMed

DePaul, Vincent G; Wishart, Laurie R; Richardson, Julie; Thabane, Lehana; Ma, Jinhui; Lee, Timothy D

2015-05-01

Although task-related walking training has been recommended after stroke, the theoretical basis, content, and impact of interventions vary across the literature. There is a need for a comparison of different approaches to task-related walking training after stroke. To compare the impact of a motor-learning-science-based overground walking training program with body-weight-supported treadmill training (BWSTT) in ambulatory, community-dwelling adults within 1 year of stroke onset. In this rater-blinded, 1:1 parallel, randomized controlled trial, participants were stratified by baseline gait speed. Participants assigned to the Motor Learning Walking Program (MLWP) practiced various overground walking tasks under the supervision of 1 physiotherapist. Cognitive effort was encouraged through random practice and limited provision of feedback and guidance. The BWSTT program emphasized repetition of the normal gait cycle while supported on a treadmill and assisted by 1 to 3 therapy staff. The primary outcome was comfortable gait speed at postintervention assessment (T2). In total, 71 individuals (mean age = 67.3; standard deviation = 11.6 years) with stroke (mean onset = 20.9 [14.1] weeks) were randomized (MLWP, n = 35; BWSTT, n = 36). There was no significant between-group difference in gait speed at T2 (0.002 m/s; 95% confidence interval [CI] = -0.11, 0.12; P > .05). The MLWP group improved by 0.14 m/s (95% CI = 0.09, 0.19), and the BWSTT group improved by 0.14 m/s (95% CI = 0.08, 0.20). In this sample of community-dwelling adults within 1 year of stroke, a 15-session program of varied overground walking-focused training was not superior to a BWSTT program of equal frequency, duration, and in-session step activity. © The Author(s) 2014.

Oecophylla longinoda (Hymenoptera: Formicidae) Lead to Increased Cashew Kernel Size and Kernel Quality.

PubMed

Anato, F M; Sinzogan, A A C; Offenberg, J; Adandonon, A; Wargui, R B; Deguenon, J M; Ayelo, P M; Vayssières, J-F; Kossou, D K

2017-06-01

Weaver ants, Oecophylla spp., are known to positively affect cashew, Anacardium occidentale L., raw nut yield, but their effects on the kernels have not been reported. We compared nut size and the proportion of marketable kernels between raw nuts collected from trees with and without ants. Raw nuts collected from trees with weaver ants were 2.9% larger than nuts from control trees (i.e., without weaver ants), leading to 14% higher proportion of marketable kernels. On trees with ants, the kernel: raw nut ratio from nuts damaged by formic acid was 4.8% lower compared with nondamaged nuts from the same trees. Weaver ants provided three benefits to cashew production by increasing yields, yielding larger nuts, and by producing greater proportions of marketable kernel mass. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Kernel abortion in maize : I. Carbohydrate concentration patterns and Acid invertase activity of maize kernels induced to abort in vitro.

PubMed

Hanft, J M; Jones, R J

1986-06-01

Kernels cultured in vitro were induced to abort by high temperature (35 degrees C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35 degrees C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth.

An Approximate Approach to Automatic Kernel Selection.

PubMed

Ding, Lizhong; Liao, Shizhong

2016-02-02

Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

Viscozyme L pretreatment on palm kernels improved the aroma of palm kernel oil after kernel roasting.

PubMed

Zhang, Wencan; Leong, Siew Mun; Zhao, Feifei; Zhao, Fangju; Yang, Tiankui; Liu, Shaoquan

2018-05-01

With an interest to enhance the aroma of palm kernel oil (PKO), Viscozyme L, an enzyme complex containing a wide range of carbohydrases, was applied to alter the carbohydrates in palm kernels (PK) to modulate the formation of volatiles upon kernel roasting. After Viscozyme treatment, the content of simple sugars and free amino acids in PK increased by 4.4-fold and 4.5-fold, respectively. After kernel roasting and oil extraction, significantly more 2,5-dimethylfuran, 2-[(methylthio)methyl]-furan, 1-(2-furanyl)-ethanone, 1-(2-furyl)-2-propanone, 5-methyl-2-furancarboxaldehyde and 2-acetyl-5-methylfuran but less 2-furanmethanol and 2-furanmethanol acetate were found in treated PKO; the correlation between their formation and simple sugar profile was estimated by using partial least square regression (PLS1). Obvious differences in pyrroles and Strecker aldehydes were also found between the control and treated PKOs. Principal component analysis (PCA) clearly discriminated the treated PKOs from that of control PKOs on the basis of all volatile compounds. Such changes in volatiles translated into distinct sensory attributes, whereby treated PKO was more caramelic and burnt after aqueous extraction and more nutty, roasty, caramelic and smoky after solvent extraction. Copyright © 2018 Elsevier Ltd. All rights reserved.

Walking performance in people with diabetic neuropathy: benefits and threats.

PubMed

Kanade, R V; van Deursen, R W M; Harding, K; Price, P

2006-08-01

Walking is recommended as an adjunct therapy to diet and medication in diabetic patients, with the aim of improving physical fitness, glycaemic control and body weight reduction. Therefore we evaluated walking activity on the basis of capacity, performance and potential risk of plantar injury in the diabetic population before it can be prescribed safely. Twenty-three subjects with diabetic neuropathy (DMPN) were compared with 23 patients with current diabetic foot ulcers, 16 patients with partial foot amputations and 22 patients with trans-tibial amputations. The capacity for walking was measured using a total heart beat index (THBI). Gait velocity and average daily strides were measured to assess the performance of walking, and its impact on weight-bearing was studied using maximum peak pressure. THBI increased (p<0.01) and gait velocity and daily stride count fell (p<0.001 for both) with progression of foot complications. The maximum peak pressures over the affected foot of patients with diabetic foot ulcers (p<0.05) and partial foot amputations (p<0.01) were higher than in the group with DMPN. On the contralateral side, the diabetic foot ulcer group showed higher maximum peak pressure over the total foot (p<0.05), and patients with partial foot amputations (p<0.01) and trans-tibial amputations (p<0.05) showed higher maximum peak pressure over the heel. Walking capacity and performance decrease with progression of foot complications. Although walking is recommended to improve fitness, it cannot be prescribed in isolation, considering the increased risk of plantar injury. For essential walking we therefore recommend the use of protective footwear. Walking exercise should be supplemented by partial or non-weight-bearing exercises to improve physical fitness in diabetic populations.

Efficient sampling of complex network with modified random walk strategies

NASA Astrophysics Data System (ADS)

Xie, Yunya; Chang, Shuhua; Zhang, Zhipeng; Zhang, Mi; Yang, Lei

2018-02-01

We present two novel random walk strategies, choosing seed node (CSN) random walk and no-retracing (NR) random walk. Different from the classical random walk sampling, the CSN and NR strategies focus on the influences of the seed node choice and path overlap, respectively. Three random walk samplings are applied in the Erdös-Rényi (ER), Barabási-Albert (BA), Watts-Strogatz (WS), and the weighted USAir networks, respectively. Then, the major properties of sampled subnets, such as sampling efficiency, degree distributions, average degree and average clustering coefficient, are studied. The similar conclusions can be reached with these three random walk strategies. Firstly, the networks with small scales and simple structures are conducive to the sampling. Secondly, the average degree and the average clustering coefficient of the sampled subnet tend to the corresponding values of original networks with limited steps. And thirdly, all the degree distributions of the subnets are slightly biased to the high degree side. However, the NR strategy performs better for the average clustering coefficient of the subnet. In the real weighted USAir networks, some obvious characters like the larger clustering coefficient and the fluctuation of degree distribution are reproduced well by these random walk strategies.

7 CFR 51.1441 - Half-kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Half-kernel. 51.1441 Section 51.1441 Agriculture... Standards for Grades of Shelled Pecans Definitions § 51.1441 Half-kernel. Half-kernel means one of the separated halves of an entire pecan kernel with not more than one-eighth of its original volume missing...

Weighted graph cuts without eigenvectors a multilevel approach.

PubMed

Dhillon, Inderjit S; Guan, Yuqiang; Kulis, Brian

2007-11-01

A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods. In this paper, we discuss an equivalence between the objective functions used in these seemingly different methods--in particular, a general weighted kernel k-means objective is mathematically equivalent to a weighted graph clustering objective. We exploit this equivalence to develop a fast, high-quality multilevel algorithm that directly optimizes various weighted graph clustering objectives, such as the popular ratio cut, normalized cut, and ratio association criteria. This eliminates the need for any eigenvector computation for graph clustering problems, which can be prohibitive for very large graphs. Previous multilevel graph partitioning methods, such as Metis, have suffered from the restriction of equal-sized clusters; our multilevel algorithm removes this restriction by using kernel k-means to optimize weighted graph cuts. Experimental results show that our multilevel algorithm outperforms a state-of-the-art spectral clustering algorithm in terms of speed, memory usage, and quality. We demonstrate that our algorithm is applicable to large-scale clustering tasks such as image segmentation, social network analysis and gene network analysis.

An introduction to kernel-based learning algorithms.

PubMed

Müller, K R; Mika, S; Rätsch, G; Tsuda, K; Schölkopf, B

2001-01-01

This paper provides an introduction to support vector machines, kernel Fisher discriminant analysis, and kernel principal component analysis, as examples for successful kernel-based learning methods. We first give a short background about Vapnik-Chervonenkis theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations. We illustrate the usefulness of kernel algorithms by discussing applications such as optical character recognition and DNA analysis.

Classifying Lower Extremity Muscle Fatigue during Walking using Machine Learning and Inertial Sensors

PubMed Central

Zhang, Jian; Lockhart, Thurmon E.; Soangra, Rahul

2013-01-01

Fatigue in lower extremity musculature is associated with decline in postural stability, motor performance and alters normal walking patterns in human subjects. Automated recognition of lower extremity muscle fatigue condition may be advantageous in early detection of fall and injury risks. Supervised machine learning methods such as Support Vector Machines (SVM) have been previously used for classifying healthy and pathological gait patterns and also for separating old and young gait patterns. In this study we explore the classification potential of SVM in recognition of gait patterns utilizing an inertial measurement unit associated with lower extremity muscular fatigue. Both kinematic and kinetic gait patterns of 17 participants (29±11 years) were recorded and analyzed in normal and fatigued state of walking. Lower extremities were fatigued by performance of a squatting exercise until the participants reached 60% of their baseline maximal voluntary exertion level. Feature selection methods were used to classify fatigue and no-fatigue conditions based on temporal and frequency information of the signals. Additionally, influences of three different kernel schemes (i.e., linear, polynomial, and radial basis function) were investigated for SVM classification. The results indicated that lower extremity muscle fatigue condition influenced gait and loading responses. In terms of the SVM classification results, an accuracy of 96% was reached in distinguishing the two gait patterns (fatigue and no-fatigue) within the same subject using the kinematic, time and frequency domain features. It is also found that linear kernel and RBF kernel were equally good to identify intra-individual fatigue characteristics. These results suggest that intra-subject fatigue classification using gait patterns from an inertial sensor holds considerable potential in identifying “at-risk” gait due to muscle fatigue. PMID:24081829

Deciphering drought-induced metabolic responses and regulation in developing maize kernels.

PubMed

Yang, Liming; Fountain, Jake C; Ji, Pingsheng; Ni, Xinzhi; Chen, Sixue; Lee, Robert D; Kemerait, Robert C; Guo, Baozhu

2018-02-12

Drought stress conditions decrease maize growth and yield, and aggravate preharvest aflatoxin contamination. While several studies have been performed on mature kernels responding to drought stress, the metabolic profiles of developing kernels are not as well characterized, particularly in germplasm with contrasting resistance to both drought and mycotoxin contamination. Here, following screening for drought tolerance, a drought-sensitive line, B73, and a drought-tolerant line, Lo964, were selected and stressed beginning at 14 days after pollination. Developing kernels were sampled 7 and 14 days after drought induction (DAI) from both stressed and irrigated plants. Comparative biochemical and metabolomic analyses profiled 409 differentially accumulated metabolites. Multivariate statistics and pathway analyses showed that drought stress induced an accumulation of simple sugars and polyunsaturated fatty acids and a decrease in amines, polyamines and dipeptides in B73. Conversely, sphingolipid, sterol, phenylpropanoid and dipeptide metabolites accumulated in Lo964 under drought stress. Drought stress also resulted in the greater accumulation of reactive oxygen species (ROS) and aflatoxin in kernels of B73 in comparison with Lo964 implying a correlation in their production. Overall, field drought treatments disordered a cascade of normal metabolic programming during development of maize kernels and subsequently caused oxidative stress. The glutathione and urea cycles along with the metabolism of carbohydrates and lipids for osmoprotection, membrane maintenance and antioxidant protection were central among the drought stress responses observed in developing kernels. These results also provide novel targets to enhance host drought tolerance and disease resistance through the use of biotechnologies such as transgenics and genome editing. © 2018 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied

Birth Weight and Subsequent Risk of Cancer

PubMed Central

Spracklen, Cassandra N; Wallace, Robert B; Sealy-Jefferson, Shawnita; Robinson, Jennifer G; Freudenheim, Jo L; Wellons, Melissa F; Saftlas, Audrey F; Snetselaar, Linda G; Manson, JoAnn E; Hou, Lifang; Qi, Lihong; Chlebowski, Rowan T; Ryckman, Kelli K

2014-01-01

Background We aimed to determine the association between self-reported birth weight and incident cancer in the Women’s Health Initiative Observational Study cohort, a large multiethnic cohort of postmenopausal women. Methods 65,850 women reported their birth weight by category (<6 lbs., 6 lbs.–7 lbs. 15 oz., 8 lbs.–9 lbs. 15 oz., and ≥10 lbs.). All self-reported, incident cancers were adjudicated by study staff. We used Cox proportional hazards regression to estimate crude and adjusted hazard ratios (aHR) for associations between birth weight and: 1) all cancer sites combined, 2) gynecologic cancers, and 3) several site-specific cancer sites. Results After adjustments, birth weight was positively associated with the risk of lung cancer (p=0.01), and colon cancer (p=0.04). An inverse trend was observed between birth weight and risk for leukemia (p=0.04). A significant trend was not observed with breast cancer risk (p=0.67); however, women born weighing ≥10 lbs. were less likely to develop breast cancer compared to women born between 6 lbs.–7 lbs. 15 oz (aHR 0.77, 95% CI 0.63, 0.94). Conclusion Birth weight category appears to be significantly associated with the risk of any postmenopausal incident cancer, though the direction of the association varies by cancer type. PMID:25096278

A new discriminative kernel from probabilistic models.

PubMed

Tsuda, Koji; Kawanabe, Motoaki; Rätsch, Gunnar; Sonnenburg, Sören; Müller, Klaus-Robert

2002-10-01

Recently, Jaakkola and Haussler (1999) proposed a method for constructing kernel functions from probabilistic models. Their so-called Fisher kernel has been combined with discriminative classifiers such as support vector machines and applied successfully in, for example, DNA and protein analysis. Whereas the Fisher kernel is calculated from the marginal log-likelihood, we propose the TOP kernel derived; from tangent vectors of posterior log-odds. Furthermore, we develop a theoretical framework on feature extractors from probabilistic models and use it for analyzing the TOP kernel. In experiments, our new discriminative TOP kernel compares favorably to the Fisher kernel.

Obesity history as a predictor of walking limitation at old age.

PubMed

Stenholm, Sari; Rantanen, Taina; Alanen, Erkki; Reunanen, Antti; Sainio, Päivi; Koskinen, Seppo

2007-04-01

To study whether walking limitation at old age is determined by obesity history. In a retrospective longitudinal study based on a representative sample of the Finnish population of 55 years and older (2055 women and 1337 men), maximal walking speed, body mass, and body height were measured in a health examination. Walking limitation was defined as walking speed<1.2 m/s or difficulty in walking 0.5 km. Recalled height at 20 years of age and recalled weight at 20, 30, 40, and 50 years of age were recorded. Subjects who had been obese at the age of 30, 40, or 50 years had almost a 4-fold higher risk of walking limitation compared to non-obese. Obesity duration increased the age- and gender-adjusted risk of walking limitation among those who had been obese since the age of 50 (odds ratio, 4.33; 95% confidence interval, 2.59 to 7.23, n=114), among the obese since the age of 40 [6.01 (2.55 to 14.14), n=39], and among the obese since the age of 30 [8.97 (3.06 to 26.29), n=14]. The risk remained elevated even among those who had previously been obese but lost weight during their midlife or late adulthood [3.15 (1.63 to 6.11), n=71]. Early onset of obesity and obesity duration increased the risk of walking limitation, and the effect was only partially mediated through current BMI and higher risk of obesity-related diseases. Preventing excess weight gain throughout one's life course is an important goal in order to promote good health and functioning in older age.

Kernel Abortion in Maize 1

PubMed Central

Hanft, Jonathan M.; Jones, Robert J.

1986-01-01

This study was designed to compare the uptake and distribution of 14C among fructose, glucose, sucrose, and starch in the cob, pedicel, and endosperm tissues of maize (Zea mays L.) kernels induced to abort by high temperature with those that develop normally. Kernels cultured in vitro at 30 and 35°C were transferred to [14C]sucrose media 10 days after pollination. Kernels cultured at 35°C aborted prior to the onset of linear dry matter accumulation. Significant uptake into the cob, pedicel, and endosperm of radioactivity associated with the soluble and starch fractions of the tissues was detected after 24 hours in culture on labeled media. After 8 days in culture on [14C]sucrose media, 48 and 40% of the radioactivity associated with the cob carbohydrates was found in the reducing sugars at 30 and 35°C, respectively. This indicates that some of the sucrose taken up by the cob tissue was cleaved to fructose and glucose in the cob. Of the total carbohydrates, a higher percentage of label was associated with sucrose and a lower percentage with fructose and glucose in pedicel tissue of kernels cultured at 35°C compared to kernels cultured at 30°C. These results indicate that sucrose was not cleaved to fructose and glucose as rapidly during the unloading process in the pedicel of kernels induced to abort by high temperature. Kernels cultured at 35°C had a much lower proportion of label associated with endosperm starch (29%) than did kernels cultured at 30°C (89%). Kernels cultured at 35°C had a correspondingly higher proportion of 14C in endosperm fructose, glucose, and sucrose. These results indicate that starch synthesis in the endosperm is strongly inhibited in kernels induced to abort by high temperature even though there is an adequate supply of sugar. PMID:16664847

Learning molecular energies using localized graph kernels.

PubMed

Ferré, Grégoire; Haut, Terry; Barros, Kipton

2017-03-21

Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.

Learning molecular energies using localized graph kernels

NASA Astrophysics Data System (ADS)

Ferré, Grégoire; Haut, Terry; Barros, Kipton

2017-03-01

Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.

Local Observed-Score Kernel Equating

ERIC Educational Resources Information Center

Wiberg, Marie; van der Linden, Wim J.; von Davier, Alina A.

2014-01-01

Three local observed-score kernel equating methods that integrate methods from the local equating and kernel equating frameworks are proposed. The new methods were compared with their earlier counterparts with respect to such measures as bias--as defined by Lord's criterion of equity--and percent relative error. The local kernel item response…

Mechanical design of walking machines.

PubMed

Arikawa, Keisuke; Hirose, Shigeo

2007-01-15

The performance of existing actuators, such as electric motors, is very limited, be it power-weight ratio or energy efficiency. In this paper, we discuss the method to design a practical walking machine under this severe constraint with focus on two concepts, the gravitationally decoupled actuation (GDA) and the coupled drive. The GDA decouples the driving system against the gravitational field to suppress generation of negative power and improve energy efficiency. On the other hand, the coupled drive couples the driving system to distribute the output power equally among actuators and maximize the utilization of installed actuator power. First, we depict the GDA and coupled drive in detail. Then, we present actual machines, TITAN-III and VIII, quadruped walking machines designed on the basis of the GDA, and NINJA-I and II, quadruped wall walking machines designed on the basis of the coupled drive. Finally, we discuss walking machines that travel on three-dimensional terrain (3D terrain), which includes the ground, walls and ceiling. Then, we demonstrate with computer simulation that we can selectively leverage GDA and coupled drive by walking posture control.

Joint forces and torques when walking in shallow water.

PubMed

Orselli, Maria Isabel Veras; Duarte, Marcos

2011-04-07

This study reports for the first time an estimation of the internal net joint forces and torques on adults' lower limbs and pelvis when walking in shallow water, taking into account the drag forces generated by the movement of their bodies in the water and the equivalent data when they walk on land. A force plate and a video camera were used to perform a two-dimensional gait analysis at the sagittal plane of 10 healthy young adults walking at comfortable speeds on land and in water at a chest-high level. We estimated the drag force on each body segment and the joint forces and torques at the ankle, knee, and hip of the right side of their bodies using inverse dynamics. The observed subjects' apparent weight in water was about 35% of their weight on land and they were about 2.7 times slower when walking in water. When the subjects walked in water compared with walking on land, there were no differences in the angular displacements but there was a significant reduction in the joint torques which was related to the water's depth. The greatest reduction was observed for the ankle and then the knee and no reduction was observed for the hip. All joint powers were significantly reduced in water. The compressive and shear joint forces were on average about three times lower during walking in water than on land. These quantitative results substantiate the use of water as a safe environment for practicing low-impact exercises, particularly walking. Copyright © 2011 Elsevier Ltd. All rights reserved.

Credit scoring analysis using kernel discriminant

NASA Astrophysics Data System (ADS)

Widiharih, T.; Mukid, M. A.; Mustafid

2018-05-01

Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.

The Use of Cuff Weights for Aquatic Gait Training in People Post-Stroke with Hemiparesis.

PubMed

Nishiyori, Ryota; Lai, Byron; Lee, Do Kyeong; Vrongistinos, Konstantinos; Jung, Taeyou

2016-03-01

This study aimed to examine how spatiotemporal and kinematic gait variables are influenced by the application of a cuff weight during aquatic walking in people post-stroke. The secondary purpose was to compare the differences in gait responses between the placements of cuff weights on the proximal (knee weight) and distal end (ankle weight) of the shank. Twenty-one participants post-stroke with hemiparesis aged 66.3 ± 11.3 years participated in a cross-sectional comparative study. Participants completed two aquatic walking trials at their self-selected maximum walking speed across an 8-m walkway under each of the three conditions: 1) walking with a knee weight; 2) walking with an ankle weight; and 3) walking with no weight. Cuff weights were worn on the paretic leg of each participant. Gait speed, cadence, step width and joint kinematics of the hip, knee and ankle joints were recorded by a customized three-dimensional underwater motion analysis system. Mean aquatic walking speeds significantly increased with the use of cuff weights when compared to walking with no weight. Changes in gait variables were found in the non-paretic leg with the addition of weight, while no significant changes were found in the paretic leg. The results suggest that the use of additional weight can be helpful if the goal of gait training is to improve walking speed of people post-stroke during pool floor walking. However, it is interesting to note that changes in gait variables were not found in the paretic limb where favourable responses were expected to occur. Copyright © 2014 John Wiley & Sons, Ltd.

When Human Walking is a Random Walk

NASA Astrophysics Data System (ADS)

Hausdorff, J. M.

1998-03-01

The complex, hierarchical locomotor system normally does a remarkable job of controlling an inherently unstable, multi-joint system. Nevertheless, the stride interval --- the duration of a gait cycle --- fluctuates from one stride to the next, even under stationary conditions. We used random walk analysis to study the dynamical properties of these fluctuations under normal conditions and how they change with disease and aging. Random walk analysis of the stride-to-stride fluctuations of healthy, young adult men surprisingly reveals a self-similar pattern: fluctuations at one time scale are statistically similar to those at multiple other time scales (Hausdorff et al, J Appl Phsyiol, 1995). To study the stability of this fractal property, we analyzed data obtained from healthy subjects who walked for 1 hour at their usual pace, as well as at slower and faster speeds. The stride interval fluctuations exhibited long-range correlations with power-law decay for up to a thousand strides at all three walking rates. In contrast, during metronomically-paced walking, these long-range correlations disappeared; variations in the stride interval were uncorrelated and non-fractal (Hausdorff et al, J Appl Phsyiol, 1996). To gain insight into the mechanism(s) responsible for this fractal property, we examined the effects of aging and neurological impairment. Using detrended fluctuation analysis (DFA), we computed α, a measure of the degree to which one stride interval is correlated with previous and subsequent intervals over different time scales. α was significantly lower in healthy elderly subjects compared to young adults (p < .003) and in subjects with Huntington's disease, a neuro-degenerative disorder of the central nervous system, compared to disease-free controls (p < 0.005) (Hausdorff et al, J Appl Phsyiol, 1997). α was also significantly related to degree of functional impairment in subjects with Huntington's disease (r=0.78). Recently, we have observed that just as

Average Weighted Receiving Time of Weighted Tetrahedron Koch Networks

NASA Astrophysics Data System (ADS)

Dai, Meifeng; Zhang, Danping; Ye, Dandan; Zhang, Cheng; Li, Lei

2015-07-01

We introduce weighted tetrahedron Koch networks with infinite weight factors, which are generalization of finite ones. The term of weighted time is firstly defined in this literature. The mean weighted first-passing time (MWFPT) and the average weighted receiving time (AWRT) are defined by weighted time accordingly. We study the AWRT with weight-dependent walk. Results show that the AWRT for a nontrivial weight factor sequence grows sublinearly with the network order. To investigate the reason of sublinearity, the average receiving time (ART) for four cases are discussed.

Modeling adaptive kernels from probabilistic phylogenetic trees.

PubMed

Nicotra, Luca; Micheli, Alessio

2009-01-01

Modeling phylogenetic interactions is an open issue in many computational biology problems. In the context of gene function prediction we introduce a class of kernels for structured data leveraging on a hierarchical probabilistic modeling of phylogeny among species. We derive three kernels belonging to this setting: a sufficient statistics kernel, a Fisher kernel, and a probability product kernel. The new kernels are used in the context of support vector machine learning. The kernels adaptivity is obtained through the estimation of the parameters of a tree structured model of evolution using as observed data phylogenetic profiles encoding the presence or absence of specific genes in a set of fully sequenced genomes. We report results obtained in the prediction of the functional class of the proteins of the budding yeast Saccharomyces cerevisae which favorably compare to a standard vector based kernel and to a non-adaptive tree kernel function. A further comparative analysis is performed in order to assess the impact of the different components of the proposed approach. We show that the key features of the proposed kernels are the adaptivity to the input domain and the ability to deal with structured data interpreted through a graphical model representation.

Relationship between asymmetry of quiet standing balance control and walking post-stroke.

PubMed

Hendrickson, Janna; Patterson, Kara K; Inness, Elizabeth L; McIlroy, William E; Mansfield, Avril

2014-01-01

Spatial and temporal gait asymmetry is common after stroke. Such asymmetric gait is inefficient, can contribute to instability and may lead to musculoskeletal injury. However, understanding of the determinants of such gait asymmetry remains incomplete. The current study is focused on revealing if there is a link between asymmetry during the control of standing balance and asymmetry during walking. This study involved review of data from 94 individuals with stroke referred to a gait and balance clinic. Participants completed three tests: (1) walking at their usual pace; (2) quiet standing; and (3) standing with maximal loading of the paretic side. A pressure sensitive mat recorded placement and timing of each footfall during walking. Standing tests were completed on two force plates to evaluate symmetry of weight bearing and contribution of each limb to balance control. Multiple regression was conducted to determine the relationships between symmetry during standing and swing time, stance time, and step length symmetry during walking. Symmetry of antero-posterior balance control and weight bearing were related to swing time and step length symmetry during walking. Weight-bearing symmetry, weight-bearing capacity, and symmetry of antero-posterior balance control were related to stance time symmetry. These associations were independent of underlying lower limb impairment. The results support the hypothesis that impaired ability of the paretic limb to control balance may contribute to gait asymmetry post-stroke. Such work suggests that rehabilitation strategies that increase the contribution of the paretic limb to standing balance control may increase symmetry of walking post-stroke. Copyright © 2013 Elsevier B.V. All rights reserved.

Mean curvature and texture constrained composite weighted random walk algorithm for optic disc segmentation towards glaucoma screening.

PubMed

Panda, Rashmi; Puhan, N B; Panda, Ganapati

2018-02-01

Accurate optic disc (OD) segmentation is an important step in obtaining cup-to-disc ratio-based glaucoma screening using fundus imaging. It is a challenging task because of the subtle OD boundary, blood vessel occlusion and intensity inhomogeneity. In this Letter, the authors propose an improved version of the random walk algorithm for OD segmentation to tackle such challenges. The algorithm incorporates the mean curvature and Gabor texture energy features to define the new composite weight function to compute the edge weights. Unlike the deformable model-based OD segmentation techniques, the proposed algorithm remains unaffected by curve initialisation and local energy minima problem. The effectiveness of the proposed method is verified with DRIVE, DIARETDB1, DRISHTI-GS and MESSIDOR database images using the performance measures such as mean absolute distance, overlapping ratio, dice coefficient, sensitivity, specificity and precision. The obtained OD segmentation results and quantitative performance measures show robustness and superiority of the proposed algorithm in handling the complex challenges in OD segmentation.

The Walking Wellness Teacher's Guide. A Resource Book for Elementary & Middle School Teachers.

ERIC Educational Resources Information Center

Sweetgall, Robert; Neeves, Robert

This teacher's resource guide for implementing a "Walking Wellness" curriculum in grades four through eight offers 16 hands-on workshops. Activities focus on fitness walking, cardiovascular conditioning, nutrition and weight control, walking techniques and posture, stress control, tobacco-free living, and lifestyle planning. The student…

Enhancing performance during inclined loaded walking with a powered ankle-foot exoskeleton.

PubMed

Galle, Samuel; Malcolm, Philippe; Derave, Wim; De Clercq, Dirk

2014-11-01

A simple ankle-foot exoskeleton that assists plantarflexion during push-off can reduce the metabolic power during walking. This suggests that walking performance during a maximal incremental exercise could be improved with an exoskeleton if the exoskeleton is still efficient during maximal exercise intensities. Therefore, we quantified the walking performance during a maximal incremental exercise test with a powered and unpowered exoskeleton: uphill walking with progressively higher weights. Nine female subjects performed two incremental exercise tests with an exoskeleton: 1 day with (powered condition) and another day without (unpowered condition) plantarflexion assistance. Subjects walked on an inclined treadmill (15%) at 5 km h(-1) and 5% of body weight was added every 3 min until exhaustion. At volitional termination no significant differences were found between the powered and unpowered condition for blood lactate concentration (respectively, 7.93 ± 2.49; 8.14 ± 2.24 mmol L(-1)), heart rate (respectively, 190.00 ± 6.50; 191.78 ± 6.50 bpm), Borg score (respectively, 18.57 ± 0.79; 18.93 ± 0.73) and VO₂ peak (respectively, 40.55 ± 2.78; 40.55 ± 3.05 ml min(-1) kg(-1)). Thus, subjects were able to reach the same (near) maximal effort in both conditions. However, subjects continued the exercise test longer in the powered condition and carried 7.07 ± 3.34 kg more weight because of the assistance of the exoskeleton. Our results show that plantarflexion assistance during push-off can increase walking performance during a maximal exercise test as subjects were able to carry more weight. This emphasizes the importance of acting on the ankle joint in assistive devices and the potential of simple ankle-foot exoskeletons for reducing metabolic power and increasing weight carrying capability, even during maximal intensities.

A Longitudinal Study of Childhood Obesity, Weight Status Change, and Subsequent Academic Performance in Taiwanese Children

ERIC Educational Resources Information Center

Chen, Li-Jung; Fox, Kenneth R.; Ku, Po-Wen; Wang, Ching-Hui

2012-01-01

Backround: This study examined the association among childhood obesity, weight status change, and subsequent academic performance at 6-year follow-up. Methods: First-grade students from one elementary school district in Taichung City, Taiwan were followed for 6 years (N = 409). Academic performance was extracted from the school records at the end…

Abiotic stress growth conditions induce different responses in kernel iron concentration across genotypically distinct maize inbred varieties

PubMed Central

Kandianis, Catherine B.; Michenfelder, Abigail S.; Simmons, Susan J.; Grusak, Michael A.; Stapleton, Ann E.

2013-01-01

The improvement of grain nutrient profiles for essential minerals and vitamins through breeding strategies is a target important for agricultural regions where nutrient poor crops like maize contribute a large proportion of the daily caloric intake. Kernel iron concentration in maize exhibits a broad range. However, the magnitude of genotype by environment (GxE) effects on this trait reduces the efficacy and predictability of selection programs, particularly when challenged with abiotic stress such as water and nitrogen limitations. Selection has also been limited by an inverse correlation between kernel iron concentration and the yield component of kernel size in target environments. Using 25 maize inbred lines for which extensive genome sequence data is publicly available, we evaluated the response of kernel iron density and kernel mass to water and nitrogen limitation in a managed field stress experiment using a factorial design. To further understand GxE interactions we used partition analysis to characterize response of kernel iron and weight to abiotic stressors among all genotypes, and observed two patterns: one characterized by higher kernel iron concentrations in control over stress conditions, and another with higher kernel iron concentration under drought and combined stress conditions. Breeding efforts for this nutritional trait could exploit these complementary responses through combinations of favorable allelic variation from these already well-characterized genetic stocks. PMID:24363659

Methods for a Randomized Trial of Weight-Supported Treadmill Training versus Conventional Training for Walking during Inpatient Rehabilitation after Incomplete Traumatic Spinal Cord Injury

PubMed Central

Dobkin, Bruce H.; Apple, David; Barbeau, Hugues; Basso, Michele; Behrman, Andrea; Deforge, Dan; Ditunno, John; Dudley, Gary; Elashoff, Robert; Fugate, Lisa; Harkema, Susan; Saulino, Michael; Scott, Michael

2014-01-01

The authors describe the rationale and methodology for the first prospective, multicenter, randomized clinical trial (RCT) of a task-oriented walking intervention for subjects during early rehabilitation for an acute traumatic spinal cord injury (SCI). The experimental strategy, body weight–supported treadmill training (BWSTT), allows physical therapists to systematically train patients to walk on a treadmill at increasing speeds typical of community ambulation with increasing weight bearing. The therapists provide verbal and tactile cues to facilitate the kinematic, kinetic, and temporal features of walking. Subjects were randomly assigned to a conventional therapy program for mobility versus the same intensity and duration of a combination of BWSTT and over-ground locomotor retraining. Subjects had an incomplete SCI (American Spinal Injury Association grades B, C, and D) from C-4 to T-10 (upper motoneuron group) or from T-11 to L-3 (lower motoneuron group). Within 8 weeks of a SCI, 146 subjects were entered for 12 weeks of intervention. The 2 single-blinded primary outcome measures are the level of independence for ambulation and, for those who are able to walk, the maximal speed for walking 50 feet, tested 6 and 12 months after randomization. The trial’s methodology offers a model for the feasibility of translating neuroscientific experiments into a RCT to develop evidence-based rehabilitation practices. PMID:14503436

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale

PubMed Central

Diao, Yuzhu; Hu, Aqin

2018-01-01

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation. PMID:29498699

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale.

PubMed

Li, Qingsheng; Diao, Yuzhu; Gong, Zaiwu; Hu, Aqin

2018-03-02

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation.

Fast Query-Optimized Kernel-Machine Classification

NASA Technical Reports Server (NTRS)

Mazzoni, Dominic; DeCoste, Dennis

2004-01-01

A recently developed algorithm performs kernel-machine classification via incremental approximate nearest support vectors. The algorithm implements support-vector machines (SVMs) at speeds 10 to 100 times those attainable by use of conventional SVM algorithms. The algorithm offers potential benefits for classification of images, recognition of speech, recognition of handwriting, and diverse other applications in which there are requirements to discern patterns in large sets of data. SVMs constitute a subset of kernel machines (KMs), which have become popular as models for machine learning and, more specifically, for automated classification of input data on the basis of labeled training data. While similar in many ways to k-nearest-neighbors (k-NN) models and artificial neural networks (ANNs), SVMs tend to be more accurate. Using representations that scale only linearly in the numbers of training examples, while exploring nonlinear (kernelized) feature spaces that are exponentially larger than the original input dimensionality, KMs elegantly and practically overcome the classic curse of dimensionality. However, the price that one must pay for the power of KMs is that query-time complexity scales linearly with the number of training examples, making KMs often orders of magnitude more computationally expensive than are ANNs, decision trees, and other popular machine learning alternatives. The present algorithm treats an SVM classifier as a special form of a k-NN. The algorithm is based partly on an empirical observation that one can often achieve the same classification as that of an exact KM by using only small fraction of the nearest support vectors (SVs) of a query. The exact KM output is a weighted sum over the kernel values between the query and the SVs. In this algorithm, the KM output is approximated with a k-NN classifier, the output of which is a weighted sum only over the kernel values involving k selected SVs. Before query time, there are gathered

Reductions in knee joint forces with weight loss are attenuated by gait adaptations in class III obesity.

PubMed

DeVita, Paul; Rider, Patrick; Hortobágyi, Tibor

2016-03-01

A consensus exists that high knee joint forces are a precursor to knee osteoarthritis and weight loss reduces these forces. Because large weight loss also leads to increased step length and walking velocity, knee contact forces may be reduced less than predicted by the magnitude of weight loss. The purpose was to determine the effects of weight loss on knee muscle and joint loads during walking in Class III obese adults. We determined through motion capture, force platform measures and biomechanical modeling the effects of weight loss produced by gastric bypass surgery over one year on knee muscle and joint loads during walking at a standard, controlled velocity and at self-selected walking velocities. Weight loss equaling 412 N or 34% of initial body weight reduced maximum knee compressive force by 824 N or 67% of initial body weight when walking at the controlled velocity. These changes represent a 2:1 reduction in knee force relative to weight loss when walking velocity is constrained to the baseline value. However, behavioral adaptations including increased stride length and walking velocity in the self-selected velocity condition attenuated this effect by ∼50% leading to a 392 N or 32% initial body weight reduction in compressive force in the knee joint. Thus, unconstrained walking elicited approximately 1:1 ratio of reduction in knee force relative to weight loss and is more indicative of walking behavior than the standard velocity condition. In conclusion, massive weight loss produces dramatic reductions in knee forces during walking but when patients stride out and walk faster, these favorable reductions become substantially attenuated. Copyright © 2016 Elsevier B.V. All rights reserved.

Determining the minimum required uranium carbide content for HTGR UCO fuel kernels

DOE PAGES

McMurray, Jacob W.; Lindemer, Terrence B.; Brown, Nicholas R.; ...

2017-03-10

There are three important failure mechanisms that must be controlled in high-temperature gas-cooled reactor (HTGR) fuel for certain higher burnup applications are SiC layer rupture, SiC corrosion by CO, and coating compromise from kernel migration. All are related to high CO pressures stemming from free O generated when uranium present as UO 2 fissions and the O is not subsequently bound by other elements. Furthermore, in the HTGR UCO kernel design, CO buildup from excess O is controlled by the inclusion of additional uranium in the form of a carbide, UC x. An approach for determining the minimum UC xmore » content to ensure negligible CO formation was developed and demonstrated using CALPHAD models and the Serpent 2 reactor physics and depletion analysis tool. Our results are intended to be more accurate than previous estimates by including more nuclear and chemical factors, in particular the effect of transmutation products on the oxygen distribution as the fuel kernel composition evolves with burnup.« less

Learning a peptide-protein binding affinity predictor with kernel ridge regression

PubMed Central

2013-01-01

Background The cellular function of a vast majority of proteins is performed through physical interactions with other biomolecules, which, most of the time, are other proteins. Peptides represent templates of choice for mimicking a secondary structure in order to modulate protein-protein interaction. They are thus an interesting class of therapeutics since they also display strong activity, high selectivity, low toxicity and few drug-drug interactions. Furthermore, predicting peptides that would bind to a specific MHC alleles would be of tremendous benefit to improve vaccine based therapy and possibly generate antibodies with greater affinity. Modern computational methods have the potential to accelerate and lower the cost of drug and vaccine discovery by selecting potential compounds for testing in silico prior to biological validation. Results We propose a specialized string kernel for small bio-molecules, peptides and pseudo-sequences of binding interfaces. The kernel incorporates physico-chemical properties of amino acids and elegantly generalizes eight kernels, comprised of the Oligo, the Weighted Degree, the Blended Spectrum, and the Radial Basis Function. We provide a low complexity dynamic programming algorithm for the exact computation of the kernel and a linear time algorithm for it’s approximation. Combined with kernel ridge regression and SupCK, a novel binding pocket kernel, the proposed kernel yields biologically relevant and good prediction accuracy on the PepX database. For the first time, a machine learning predictor is capable of predicting the binding affinity of any peptide to any protein with reasonable accuracy. The method was also applied to both single-target and pan-specific Major Histocompatibility Complex class II benchmark datasets and three Quantitative Structure Affinity Model benchmark datasets. Conclusion On all benchmarks, our method significantly (p-value ≤ 0.057) outperforms the current state-of-the-art methods at predicting

Chemical and Nutritional Composition of Terminalia ferdinandiana (Kakadu Plum) Kernels: A Novel Nutrition Source

PubMed Central

Netzel, Michael E.; Tinggi, Ujang

2018-01-01

Terminalia ferdinandiana (Kakadu plum) is a native Australian fruit. Industrial processing of T. ferdinandiana fruits into puree generates seeds as a by-product, which are generally discarded. The aim of our present study was to process the seed to separate the kernel and determine its nutritional composition. The proximate, mineral and fatty acid compositions were analysed in this study. Kernels are composed of 35% fat, while proteins account for 32% dry weight (DW). The energy content and fiber were 2065 kJ/100 g and 21.2% DW, respectively. Furthermore, the study showed that kernels were a very rich source of minerals and trace elements, such as potassium (6693 mg/kg), calcium (5385 mg/kg), iron (61 mg/kg) and zinc (60 mg/kg) DW, and had low levels of heavy metals. The fatty acid composition of the kernels consisted of omega-6 fatty acid, linoleic acid (50.2%), monounsaturated oleic acid (29.3%) and two saturated fatty acids namely palmitic acid (12.0%) and stearic acid (7.2%). The results indicate that T. ferdinandiana kernels have the potential to be utilized as a novel protein source for dietary purposes and non-conventional supply of linoleic, palmitic and oleic acids. PMID:29649154

Expression of Fungal diacylglycerol acyltransferase2 Genes to Increase Kernel Oil in Maize[OA

PubMed Central

Oakes, Janette; Brackenridge, Doug; Colletti, Ron; Daley, Maureen; Hawkins, Deborah J.; Xiong, Hui; Mai, Jennifer; Screen, Steve E.; Val, Dale; Lardizabal, Kathryn; Gruys, Ken; Deikman, Jill

2011-01-01

Maize (Zea mays) oil has high value but is only about 4% of the grain by weight. To increase kernel oil content, fungal diacylglycerol acyltransferase2 (DGAT2) genes from Umbelopsis (formerly Mortierella) ramanniana and Neurospora crassa were introduced into maize using an embryo-enhanced promoter. The protein encoded by the N. crassa gene was longer than that of U. ramanniana. It included 353 amino acids that aligned to the U. ramanniana DGAT2A protein and a 243-amino acid sequence at the amino terminus that was unique to the N. crassa DGAT2 protein. Two forms of N. crassa DGAT2 were tested: the predicted full-length protein (L-NcDGAT2) and a shorter form (S-NcDGAT2) that encoded just the sequences that share homology with the U. ramanniana protein. Expression of all three transgenes in maize resulted in small but statistically significant increases in kernel oil. S-NcDGAT2 had the biggest impact on kernel oil, with a 26% (relative) increase in oil in kernels of the best events (inbred). Increases in kernel oil were also obtained in both conventional and high-oil hybrids, and grain yield was not affected by expression of these fungal DGAT2 transgenes. PMID:21245192

Weight regain is related to decreases in physical activity during weight loss.

PubMed

Wang, Xuewen; Lyles, Mary F; You, Tongjian; Berry, Michael J; Rejeski, W Jack; Nicklas, Barbara J

2008-10-01

To examine whether adaptations in physical activity energy expenditure (PAEE) and resting metabolic rate (RMR) during weight loss were associated with future weight regain in overweight/obese, older women. Thirty-four overweight/obese (BMI = 25-40 kg x m(-2)), postmenopausal women underwent a 20-wk weight loss intervention of hypocaloric diet with (low- or high-intensity) or without treadmill walking (weekly caloric deficit was approximately 11,760 kJ), with a subsequent 12-month follow-up. RMR (via indirect calorimetry), PAEE (by RT3 accelerometer), and body composition (by dual-energy x-ray absorptiometry) were measured before and after intervention. Body weight and self-reported information on physical activity were collected after intervention and at 6 and 12 months after intervention. The intervention resulted in decreases in body weight, lean mass, fat mass, percent body fat, RMR, and PAEE (P < 0.001 for all). Weight regain was 2.9 +/- 3.3 kg (-3.1 to +9.2 kg) at 6 months and 5.2 +/- 5.0 kg (-2.3 to +21.7 kg) at 12 months after intervention. The amount of weight regained after 6 and 12 months was inversely associated with decreases in PAEE during the weight loss intervention (r = -0.521, P = 0.002 and r = -0.404, P = 0.018, respectively), such that women with larger declines in PAEE during weight loss experienced greater weight regain during follow-up. Weight regain was not associated with changes in RMR during intervention or with self-reported physical activity during follow-up. This study demonstrates that although both RMR and PAEE decreased during weight loss in postmenopausal women, maintaining high levels of daily physical activity during weight loss may be important to mitigate weight regain after weight loss.

Lower limb joint moment during walking in water.

PubMed

Miyoshi, Tasuku; Shirota, Takashi; Yamamoto, Shin-Ichiro; Nakazawa, Kimitaka; Akai, Masami

2003-11-04

Walking in water is a widely used rehabilitation method for patients with orthopedic disorders or arthritis, based on the belief that the reduction of weight in water makes it a safer medium and prevents secondary injuries of the lower-limb joints. To our knowledge, however, no experimental data on lower-limb joint moment during walking in water is available. The aim of this study was to quantify the joint moments of the ankle, knee, and hip during walking in water in comparison with those on land. Eight healthy volunteers walked on land and in water at a speed comfortable for them. A video-motion analysis system and waterproof force platform were used to obtain kinematic data and to calculate the joint moments. The hip joint moment was shown to be an extension moment almost throughout the stance phase during walking in water, while it changed from an extension- to flexion-direction during walking on land. The knee joint moment had two extension peaks during walking on land, whereas it had only one extension peak, a late one, during walking in water. The ankle joint moment during walking in water was considerably reduced but in the same direction, plantarflexion, as that during walking on land. The joint moments of the hip, knee, and ankle were not merely reduced during walking in water; rather, inter-joint coordination was totally changed.

Effects of the Integration of Dynamic Weight Shifting Training Into Treadmill Training on Walking Function of Children with Cerebral Palsy: A Randomized Controlled Study.

PubMed

Wu, Ming; Kim, Janis; Arora, Pooja; Gaebler-Spira, Deborah J; Zhang, Yunhui

2017-11-01

The aim of the study was to determine whether applying an assistance force to the pelvis and legs during treadmill training can improve walking function in children with cerebral palsy. Twenty-three children with cerebral palsy were randomly assigned to the robotic or treadmill only group. For participants who were assigned to the robotic group, a controlled force was applied to the pelvis and legs during treadmill walking. For participants who were assigned to the treadmill only group, manual assistance was provided as needed. Each participant trained 3 times/wk for 6 wks. Outcome measures included walking speed, 6-min walking distance, and clinical assessment of motor function, which were evaluated before, after training, and 8 wks after the end of training, and were compared between two groups. Significant increases in walking speed and 6-min walking distance were observed after robotic training (P = 0.03), but no significant change was observed after treadmill training only. A greater increase in 6-min walking distance was observed after robotic training than that after treadmill only training (P = 0.01). Applying a controlled force to the pelvis and legs, for facilitating weight-shift and leg swing, respectively, during treadmill training may improve walking speed and endurance in children with cerebral palsy. Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME CME OBJECTIVES: Upon completion of this article, the reader should be able to: (1) discuss the importance of physical activity at the participation level (sports programs) for children with cerebral palsy; (2) contrast the changes in walking ability and endurance for children in GMFCS level I, II and III following sports programs; and (3) identify the impact of higher frequency of sports program attendance over time on walking ability. Advanced ACCREDITATION: The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing

Comparing Alternative Kernels for the Kernel Method of Test Equating: Gaussian, Logistic, and Uniform Kernels. Research Report. ETS RR-08-12

ERIC Educational Resources Information Center

Lee, Yi-Hsuan; von Davier, Alina A.

2008-01-01

The kernel equating method (von Davier, Holland, & Thayer, 2004) is based on a flexible family of equipercentile-like equating functions that use a Gaussian kernel to continuize the discrete score distributions. While the classical equipercentile, or percentile-rank, equating method carries out the continuization step by linear interpolation,…

A ℓ2, 1 norm regularized multi-kernel learning for false positive reduction in Lung nodule CAD.

PubMed

Cao, Peng; Liu, Xiaoli; Zhang, Jian; Li, Wei; Zhao, Dazhe; Huang, Min; Zaiane, Osmar

2017-03-01

The aim of this paper is to describe a novel algorithm for False Positive Reduction in lung nodule Computer Aided Detection(CAD). In this paper, we describes a new CT lung CAD method which aims to detect solid nodules. Specially, we proposed a multi-kernel classifier with a ℓ 2, 1 norm regularizer for heterogeneous feature fusion and selection from the feature subset level, and designed two efficient strategies to optimize the parameters of kernel weights in non-smooth ℓ 2, 1 regularized multiple kernel learning algorithm. The first optimization algorithm adapts a proximal gradient method for solving the ℓ 2, 1 norm of kernel weights, and use an accelerated method based on FISTA; the second one employs an iterative scheme based on an approximate gradient descent method. The results demonstrates that the FISTA-style accelerated proximal descent method is efficient for the ℓ 2, 1 norm formulation of multiple kernel learning with the theoretical guarantee of the convergence rate. Moreover, the experimental results demonstrate the effectiveness of the proposed methods in terms of Geometric mean (G-mean) and Area under the ROC curve (AUC), and significantly outperforms the competing methods. The proposed approach exhibits some remarkable advantages both in heterogeneous feature subsets fusion and classification phases. Compared with the fusion strategies of feature-level and decision level, the proposed ℓ 2, 1 norm multi-kernel learning algorithm is able to accurately fuse the complementary and heterogeneous feature sets, and automatically prune the irrelevant and redundant feature subsets to form a more discriminative feature set, leading a promising classification performance. Moreover, the proposed algorithm consistently outperforms the comparable classification approaches in the literature. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Calcaneal loading during walking and running

NASA Technical Reports Server (NTRS)

Giddings, V. L.; Beaupre, G. S.; Whalen, R. T.; Carter, D. R.

2000-01-01

PURPOSE: This study of the foot uses experimentally measured kinematic and kinetic data with a numerical model to evaluate in vivo calcaneal stresses during walking and running. METHODS: External ground reaction forces (GRF) and kinematic data were measured during walking and running using cineradiography and force plate measurements. A contact-coupled finite element model of the foot was developed to assess the forces acting on the calcaneus during gait. RESULTS: We found that the calculated force-time profiles of the joint contact, ligament, and Achilles tendon forces varied with the time-history curve of the moment about the ankle joint. The model predicted peak talocalcaneal and calcaneocuboid joint loads of 5.4 and 4.2 body weights (BW) during walking and 11.1 and 7.9 BW during running. The maximum predicted Achilles tendon forces were 3.9 and 7.7 BW for walking and running. CONCLUSIONS: Large magnitude forces and calcaneal stresses are generated late in the stance phase, with maximum loads occurring at approximately 70% of the stance phase during walking and at approximately 60% of the stance phase during running, for the gait velocities analyzed. The trajectories of the principal stresses, during both walking and running, corresponded to each other and qualitatively to the calcaneal trabecular architecture.

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Kernel color classification. 51.1403 Section 51.1403... STANDARDS) United States Standards for Grades of Pecans in the Shell 1 Kernel Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be described in terms of the color...

Margin-maximizing feature elimination methods for linear and nonlinear kernel-based discriminant functions.

PubMed

Aksu, Yaman; Miller, David J; Kesidis, George; Yang, Qing X

2010-05-01

Feature selection for classification in high-dimensional spaces can improve generalization, reduce classifier complexity, and identify important, discriminating feature "markers." For support vector machine (SVM) classification, a widely used technique is recursive feature elimination (RFE). We demonstrate that RFE is not consistent with margin maximization, central to the SVM learning approach. We thus propose explicit margin-based feature elimination (MFE) for SVMs and demonstrate both improved margin and improved generalization, compared with RFE. Moreover, for the case of a nonlinear kernel, we show that RFE assumes that the squared weight vector 2-norm is strictly decreasing as features are eliminated. We demonstrate this is not true for the Gaussian kernel and, consequently, RFE may give poor results in this case. MFE for nonlinear kernels gives better margin and generalization. We also present an extension which achieves further margin gains, by optimizing only two degrees of freedom--the hyperplane's intercept and its squared 2-norm--with the weight vector orientation fixed. We finally introduce an extension that allows margin slackness. We compare against several alternatives, including RFE and a linear programming method that embeds feature selection within the classifier design. On high-dimensional gene microarray data sets, University of California at Irvine (UCI) repository data sets, and Alzheimer's disease brain image data, MFE methods give promising results.

[Exoskeleton robot system based on real-time gait analysis for walking assist].

PubMed

Xie, Zheng; Wang, Mingjiang; Huang, Wulong; Yong, Shanshan; Wang, Xin'an

2017-04-01

This paper presents a wearable exoskeleton robot system to realize walking assist function, which oriented toward the patients or the elderly with the mild impairment of leg movement function, due to illness or natural aging. It reduces the loads of hip, knee, ankle and leg muscles during walking by way of weight support. In consideration of the characteristics of the psychological demands and the disease, unlike the weight loss system in the fixed or followed rehabilitation robot, the structure of the proposed exoskeleton robot is artistic, lightweight and portable. The exoskeleton system analyzes the user's gait real-timely by the plantar pressure sensors to divide gait phases, and present different control strategies for each gait phase. The pressure sensors in the seat of the exoskeleton system provide real-time monitoring of the support efforts. And the drive control uses proportion-integral-derivative (PID) control technology for torque control. The total weight of the robot system is about 12.5 kg. The average of the auxiliary support is about 10 kg during standing, and it is about 3 kg during walking. The system showed, in the experiments, a certain effect of weight support, and reduction of the pressure on the lower limbs to walk and stand.

Out-of-Sample Extensions for Non-Parametric Kernel Methods.

PubMed

Pan, Binbin; Chen, Wen-Sheng; Chen, Bo; Xu, Chen; Lai, Jianhuang

2017-02-01

Choosing suitable kernels plays an important role in the performance of kernel methods. Recently, a number of studies were devoted to developing nonparametric kernels. Without assuming any parametric form of the target kernel, nonparametric kernel learning offers a flexible scheme to utilize the information of the data, which may potentially characterize the data similarity better. The kernel methods using nonparametric kernels are referred to as nonparametric kernel methods. However, many nonparametric kernel methods are restricted to transductive learning, where the prediction function is defined only over the data points given beforehand. They have no straightforward extension for the out-of-sample data points, and thus cannot be applied to inductive learning. In this paper, we show how to make the nonparametric kernel methods applicable to inductive learning. The key problem of out-of-sample extension is how to extend the nonparametric kernel matrix to the corresponding kernel function. A regression approach in the hyper reproducing kernel Hilbert space is proposed to solve this problem. Empirical results indicate that the out-of-sample performance is comparable to the in-sample performance in most cases. Experiments on face recognition demonstrate the superiority of our nonparametric kernel method over the state-of-the-art parametric kernel methods.

Major depressive disorder, antidepressant use, and subsequent 2-year weight change patterns in the Netherlands Study of Depression and Anxiety.

PubMed

Gibson-Smith, Deborah; Bot, Mariska; Milaneschi, Yuri; Twisk, Jos W; Visser, Marjolein; Brouwer, Ingeborg A; Penninx, Brenda W J H

2016-02-01

Although depression and obesity are bidirectionally associated, little is known about weight changes following major depressive disorder (MDD). This study compared 2-year weight changes between patients with current MDD (cMDD), patients with remitted MDD (rMDD), and healthy controls. Additionally, we examined the relationship between antidepressant medication use and 2-year weight change. Data from 2,542 adults aged 18-65 y were sourced from the Netherlands Study of Depression and Anxiety. Data were collected at baseline and after 2, 4, and 6 years (September 2004-April 2013). Depression status (DSM-IV criteria for MDD) was established with the Composite International Diagnostic Interview. Subsequent 2-year weight changes were categorized as weight loss (> 5% loss), weight stable (within 5% weight loss or gain), and weight gain (> 5% gain). The association of depression status with subsequent weight change, with weight stable as reference category, was studied by combining all repeated measurements in a mixed multinomial logistical regression model. cMDD, but not rMDD, was significantly associated with both weight gain and weight loss over a 2-year period after adjustment for covariates (odds ratio [OR] = 1.67; 95% confidence interval [CI], 1.37-2.03; P < .001; and OR = 1.27; 95% CI 1.01-1.61; P = .045, respectively). Antidepressant use was associated with weight gain (SSRIs: OR = 1.26; 95% CI, 1.05-1.52; other antidepressants: OR = 1.36; 95% CI, 1.00-1.84; P < .05 for both), but not after considering depression status. Compared to cMDD patients who lost weight, those who gained weight had lower initial weight, were younger, had more comorbid anxiety disorders, and reported poorer quality of mood and reduced appetite as depressive symptoms. Compared to controls, cMDD participants have greater odds of either gaining or losing weight over a 2-year period, regardless of antidepressant use. © Copyright 2015 Physicians Postgraduate Press, Inc.

Computed tomography coronary stent imaging with iterative reconstruction: a trade-off study between medium kernel and sharp kernel.

PubMed

Zhou, Qijing; Jiang, Biao; Dong, Fei; Huang, Peiyu; Liu, Hongtao; Zhang, Minming

2014-01-01

To evaluate the improvement of iterative reconstruction in image space (IRIS) technique in computed tomographic (CT) coronary stent imaging with sharp kernel, and to make a trade-off analysis. Fifty-six patients with 105 stents were examined by 128-slice dual-source CT coronary angiography (CTCA). Images were reconstructed using standard filtered back projection (FBP) and IRIS with both medium kernel and sharp kernel applied. Image noise and the stent diameter were investigated. Image noise was measured both in background vessel and in-stent lumen as objective image evaluation. Image noise score and stent score were performed as subjective image evaluation. The CTCA images reconstructed with IRIS were associated with significant noise reduction compared to that of CTCA images reconstructed using FBP technique in both of background vessel and in-stent lumen (the background noise decreased by approximately 25.4% ± 8.2% in medium kernel (P kernel (P kernel (P kernel (P kernel showed better visualization of the stent struts and in-stent lumen than that with medium kernel. Iterative reconstruction in image space reconstruction can effectively reduce the image noise and improve image quality. The sharp kernel images constructed with iterative reconstruction are considered the optimal images to observe coronary stents in this study.

Endosperm Protein Synthesis and l-[35S]Methionine Incorporation in Maize Kernels Cultured In Vitro1

PubMed Central

Cully, David E.; Gengenbach, Burle G.; Smith, Jane A.; Rubenstein, Irwin; Connelly, James A.; Park, William D.

1984-01-01

This study was conducted to examine protein synthesis and l-[35S] methionine incorporation into the endosperm of Zea mays L. kernels developing in vitro. Two-day-old kernels of the inbred line W64A were placed in culture on a defined medium containing 10 microCuries l-[35S] methionine per milliliter (13 milliCuries per millimole) and harvested at 10, 15, 20, 25, 30, 35, and 40 days after pollination. Cultured kernels attained a final endosperm mass of 120 milligrams compared to 175 milligrams for field-grown controls. Field and cultured kernels had similar concentrations (microgram per milligram endospern) for total protein, albumin plus globulin, zein, and glutelin fractions at most kernel ages. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis and isoelectric focusing patterns for endosperm proteins were similar for field and cultured kernels throughout development. By 15 days, over 70% of the l-[35S]methionine taken up was present in endosperm proteins. Label incorporation visualized by fluorography generally followed the protein intensity of the stained gels. The high methionine content, low molecular weight zeins (i.e. 15 and 9 kilodaltons) were highly labeled. All of the radioactivity in hydrolyzed zein samples was recovered in the methionine peak indicating minimal conversion to l-[35S]cysteine. The procedure described here is suitable for long term culture and labeling experiments in which continued kernel development is required. Images Fig. 2 Fig. 3 Fig. 4 PMID:16663428

Six-minute walk test in children and adolescents with cystic fibrosis.

PubMed

Cunha, Maristela Trevisan; Rozov, Tatiana; de Oliveira, Rosangela Caitano; Jardim, José R

2006-07-01

The 6-min walk test is a simple, rapid, and low-cost method that determines tolerance to exercise. We examined the reproducibility of the 6-min walk test in 16 children with cystic fibrosis (11 female, 5 male; age range, 11.0 +/- 1.9 years). We related the distance walked and the work performed (distance walked x body weight) with nutritional (body mass index and respiratory muscle strength) and clinical (degree of bronchial obstruction and Shwachman score) status. Patients were asked to walk as far as possible upon verbal command on two occasions. There was no statistical difference between distances walked (582.3 +/- 60 and 598.2 +/- 56.8 m, P = 0.31), heart rate, respiratory rate, pulse oxygen saturation, arterial blood pressure, dyspnea, and percentage of maximal heart rate for age in the two tests. Distance walked correlated (Pearson) with maximal expiratory pressure (98.6 +/- 28.1 cmH2O, r = 0.60, P < 0.01), maximal heart rate (157.9 +/- 10.1 bpm, r = 0.59, P < 0.02), Borg dyspnea scale (1.7 +/- 2.4, r = 0.55, P < 0.03), and double product (blood pressure x heart rate; r = 0.59, P < 0.02). The product of distance walked and body weight (work) correlated (Pearson) with height (r = 0.83, P = 0.000), maximal expiratory pressure (r = 0.64, P < 0.01), systolic blood pressure (r = 0.56, P < 0.02), and diastolic blood pressure (r = 0.55, P < 0.03). We conclude that the 6-min walk test is reproducible and easy to perform in children and adolescents with cystic fibrosis. The distance walked was related to the clinical variables studied. Work in the 6-min walk test may be an additional parameter in the determination of physical capacity.

Anisotropic hydrodynamics with a scalar collisional kernel

NASA Astrophysics Data System (ADS)

Almaalol, Dekrayat; Strickland, Michael

2018-04-01

Prior studies of nonequilibrium dynamics using anisotropic hydrodynamics have used the relativistic Anderson-Witting scattering kernel or some variant thereof. In this paper, we make the first study of the impact of using a more realistic scattering kernel. For this purpose, we consider a conformal system undergoing transversally homogenous and boost-invariant Bjorken expansion and take the collisional kernel to be given by the leading order 2 ↔2 scattering kernel in scalar λ ϕ4 . We consider both classical and quantum statistics to assess the impact of Bose enhancement on the dynamics. We also determine the anisotropic nonequilibrium attractor of a system subject to this collisional kernel. We find that, when the near-equilibrium relaxation-times in the Anderson-Witting and scalar collisional kernels are matched, the scalar kernel results in a higher degree of momentum-space anisotropy during the system's evolution, given the same initial conditions. Additionally, we find that taking into account Bose enhancement further increases the dynamically generated momentum-space anisotropy.

Ranking Support Vector Machine with Kernel Approximation

PubMed Central

Dou, Yong

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms. PMID:28293256

Ranking Support Vector Machine with Kernel Approximation.

PubMed

Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Walk well: a randomised controlled trial of a walking intervention for adults with intellectual disabilities: study protocol

PubMed Central

2013-01-01

Background Walking interventions have been shown to have a positive impact on physical activity (PA) levels, health and wellbeing for adult and older adult populations. There has been very little work carried out to explore the effectiveness of walking interventions for adults with intellectual disabilities. This paper will provide details of the Walk Well intervention, designed for adults with intellectual disabilities, and a randomised controlled trial (RCT) to test its effectiveness. Methods/design This study will adopt a RCT design, with participants allocated to the walking intervention group or a waiting list control group. The intervention consists of three PA consultations (baseline, six weeks and 12 weeks) and an individualised 12 week walking programme. A range of measures will be completed by participants at baseline, post intervention (three months from baseline) and at follow up (three months post intervention and six months from baseline). All outcome measures will be collected by a researcher who will be blinded to the study groups. The primary outcome will be steps walked per day, measured using accelerometers. Secondary outcome measures will include time spent in PA per day (across various intensity levels), time spent in sedentary behaviour per day, quality of life, self-efficacy and anthropometric measures to monitor weight change. Discussion Since there are currently no published RCTs of walking interventions for adults with intellectual disabilities, this RCT will examine if a walking intervention can successfully increase PA, health and wellbeing of adults with intellectual disabilities. Trial registration ISRCTN: ISRCTN50494254 PMID:23816316

Rare variant testing across methods and thresholds using the multi-kernel sequence kernel association test (MK-SKAT).

PubMed

Urrutia, Eugene; Lee, Seunggeun; Maity, Arnab; Zhao, Ni; Shen, Judong; Li, Yun; Wu, Michael C

Analysis of rare genetic variants has focused on region-based analysis wherein a subset of the variants within a genomic region is tested for association with a complex trait. Two important practical challenges have emerged. First, it is difficult to choose which test to use. Second, it is unclear which group of variants within a region should be tested. Both depend on the unknown true state of nature. Therefore, we develop the Multi-Kernel SKAT (MK-SKAT) which tests across a range of rare variant tests and groupings. Specifically, we demonstrate that several popular rare variant tests are special cases of the sequence kernel association test which compares pair-wise similarity in trait value to similarity in the rare variant genotypes between subjects as measured through a kernel function. Choosing a particular test is equivalent to choosing a kernel. Similarly, choosing which group of variants to test also reduces to choosing a kernel. Thus, MK-SKAT uses perturbation to test across a range of kernels. Simulations and real data analyses show that our framework controls type I error while maintaining high power across settings: MK-SKAT loses power when compared to the kernel for a particular scenario but has much greater power than poor choices.

Isotemporal Substitution Paradigm for Physical Activity Epidemiology and Weight Change

PubMed Central

Willett, Walter C.; Hu, Frank B.; Ding, Eric L.

2009-01-01

For a fixed amount of time engaged in physical activity, activity choice may affect body weight differently depending partly on other activities’ displacement. Typical models used to evaluate effects of physical activity on body weight do not directly address these substitutions. An isotemporal substitution paradigm was developed as a new analytic model to study the time-substitution effects of one activity for another. In 1991–1997, the authors longitudinally examined the associations of discretionary physical activities, with varying activity displacements, with 6-year weight loss maintenance among 4,558 healthy, premenopausal US women who had previously lost >5% of their weight. Results of isotemporal substitution models indicated widely heterogeneous relations with each physical activity type (P < 0.001) depending on the displaced activities. Notably, whereas 30 minutes/day of brisk walking substituted for 30 minutes/day of jogging/running was associated with weight increase (1.57 kg, 95% confidence interval: 0.33, 2.82), brisk walking was associated with lower weight when substituted for slow walking (−1.14 kg, 95% confidence interval: −1.75, −0.53) and with even lower weight when substituted for TV watching. Similar heterogeneous relations with weight change were found for each activity type (TV watching, slow walking, brisk walking, jogging/running) when displaced by other activities across these various models. The isotemporal substitution paradigm may offer new insights for future public health recommendations. PMID:19584129

Wigner functions defined with Laplace transform kernels.

PubMed

Oh, Se Baek; Petruccelli, Jonathan C; Tian, Lei; Barbastathis, George

2011-10-24

We propose a new Wigner-type phase-space function using Laplace transform kernels--Laplace kernel Wigner function. Whereas momentum variables are real in the traditional Wigner function, the Laplace kernel Wigner function may have complex momentum variables. Due to the property of the Laplace transform, a broader range of signals can be represented in complex phase-space. We show that the Laplace kernel Wigner function exhibits similar properties in the marginals as the traditional Wigner function. As an example, we use the Laplace kernel Wigner function to analyze evanescent waves supported by surface plasmon polariton. © 2011 Optical Society of America

Learning molecular energies using localized graph kernels

DOE PAGES

Ferré, Grégoire; Haut, Terry Scot; Barros, Kipton Marcos

2017-03-21

We report that recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturallymore » incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. Finally, we benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.« less

Learning molecular energies using localized graph kernels

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

Ferré, Grégoire; Haut, Terry Scot; Barros, Kipton Marcos

We report that recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturallymore » incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. Finally, we benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.« less

Relationship between Body Weight of Primiparous Sows during Late Gestation and Subsequent Reproductive Efficiency over Six Parities

PubMed Central

Kim, Jin Soo; Yang, Xiaojian; Baidoo, Samuel Kofi

2016-01-01

The present study investigated the impact of parity 1 gilt body weight during late gestation (d 109) on subsequent reproductive performance of sows and performance of suckling pigs. A total of 2,404 farrowing records over 6 parities were divided into six groups on the basis of body weight (190, 200, 210, 220, 230, and 240 kg) at d 109 of gestation of 585 gilts. Significant effects (p< 0.05) of body weight on sow retention rate was noticed, with the 210 kg group having the lowest culling rate and highest total number of piglets born alive over the 6 parities. With increase of body weight, a linear increase (p<0.05) in losses of body weight and backfat during the lactation period of parity 1 and a linear decrease (p<0.05) in backfat loss for parities 4 and 6 were found. Compared with light sows, heavy sows had higher (p<0.05) litter weight at birth for parities 1 and 2 and at weaning in parity 1. Sow weaning-to-estrus interval of sows was not influenced (p>0.05) by body weight. In conclusion, maintaining optimal body weight during gestation would be beneficial to sows and suckling piglets. PMID:26954198

Walking...A Step in the Right Direction!

MedlinePlus

... For Reporters Meetings & Workshops Follow Us Home Health Information Weight Management Walking: A Step in the Right Direction Related ... at NIDDK Technology Advancement & Transfer Meetings & Workshops Health Information ... Disease Urologic Diseases Endocrine Diseases Diet & Nutrition ...

Influence of non-level walking on pedometer accuracy.

PubMed

Leicht, Anthony S; Crowther, Robert G

2009-05-01

The YAMAX Digiwalker pedometer has been previously confirmed as a valid and reliable monitor during level walking, however, little is known about its accuracy during non-level walking activities or between genders. Subsequently, this study examined the influence of non-level walking and gender on pedometer accuracy. Forty-six healthy adults completed 3-min bouts of treadmill walking at their normal walking pace during 11 inclines (0-10%) while another 123 healthy adults completed walking up and down 47 stairs. During walking, participants wore a YAMAX Digiwalker SW-700 pedometer with the number of steps taken and registered by the pedometer recorded. Pedometer difference (steps registered-steps taken), net error (% of steps taken), absolute error (absolute % of steps taken) and gender were examined by repeated measures two-way ANOVA and Tukey's post hoc tests. During incline walking, pedometer accuracy indices were similar between inclines and gender except for a significantly greater step difference (-7+/-5 steps vs. 1+/-4 steps) and net error (-2.4+/-1.8% for 9% vs. 0.4+/-1.2% for 2%). Step difference and net error were significantly greater during stair descent compared to stair ascent while absolute error was significantly greater during stair ascent compared to stair descent. The current study demonstrated that the YAMAX Digiwalker SW-700 pedometer exhibited good accuracy during incline walking up to 10% while it overestimated steps taken during stair ascent/descent with greater overestimation during stair descent. Stair walking activity should be documented in field studies as the YAMAX Digiwalker SW-700 pedometer overestimates this activity type.

Kinematic responses to changes in walking orientation and gravitational load in Drosophila melanogaster.

PubMed

Mendes, César S; Rajendren, Soumya V; Bartos, Imre; Márka, Szabolcs; Mann, Richard S

2014-01-01

Walking behavior is context-dependent, resulting from the integration of internal and external influences by specialized motor and pre-motor centers. Neuronal programs must be sufficiently flexible to the locomotive challenges inherent in different environments. Although insect studies have contributed substantially to the identification of the components and rules that determine locomotion, we still lack an understanding of how multi-jointed walking insects respond to changes in walking orientation and direction and strength of the gravitational force. In order to answer these questions we measured with high temporal and spatial resolution the kinematic properties of untethered Drosophila during inverted and vertical walking. In addition, we also examined the kinematic responses to increases in gravitational load. We find that animals are capable of shifting their step, spatial and inter-leg parameters in order to cope with more challenging walking conditions. For example, flies walking in an inverted orientation decreased the duration of their swing phase leading to increased contact with the substrate and, as a result, greater stability. We also find that when flies carry additional weight, thereby increasing their gravitational load, some changes in step parameters vary over time, providing evidence for adaptation. However, above a threshold that is between 1 and 2 times their body weight flies display locomotion parameters that suggest they are no longer capable of walking in a coordinated manner. Finally, we find that functional chordotonal organs are required for flies to cope with additional weight, as animals deficient in these proprioceptors display increased sensitivity to load bearing as well as other locomotive defects.

Parsimonious Continuous Time Random Walk Models and Kurtosis for Diffusion in Magnetic Resonance of Biological Tissue

NASA Astrophysics Data System (ADS)

Ingo, Carson; Sui, Yi; Chen, Yufen; Parrish, Todd; Webb, Andrew; Ronen, Itamar

2015-03-01

In this paper, we provide a context for the modeling approaches that have been developed to describe non-Gaussian diffusion behavior, which is ubiquitous in diffusion weighted magnetic resonance imaging of water in biological tissue. Subsequently, we focus on the formalism of the continuous time random walk theory to extract properties of subdiffusion and superdiffusion through novel simplifications of the Mittag-Leffler function. For the case of time-fractional subdiffusion, we compute the kurtosis for the Mittag-Leffler function, which provides both a connection and physical context to the much-used approach of diffusional kurtosis imaging. We provide Monte Carlo simulations to illustrate the concepts of anomalous diffusion as stochastic processes of the random walk. Finally, we demonstrate the clinical utility of the Mittag-Leffler function as a model to describe tissue microstructure through estimations of subdiffusion and kurtosis with diffusion MRI measurements in the brain of a chronic ischemic stroke patient.

Motor modules during adaptation to walking in a powered ankle exoskeleton.

PubMed

Jacobs, Daniel A; Koller, Jeffrey R; Steele, Katherine M; Ferris, Daniel P

2018-01-03

Modules of muscle recruitment can be extracted from electromyography (EMG) during motions, such as walking, running, and swimming, to identify key features of muscle coordination. These features may provide insight into gait adaptation as a result of powered assistance. The aim of this study was to investigate the changes (module size, module timing and weighting patterns) of surface EMG data during assisted and unassisted walking in an powered, myoelectric, ankle-foot orthosis (ankle exoskeleton). Eight healthy subjects wore bilateral ankle exoskeletons and walked at 1.2 m/s on a treadmill. In three training sessions, subjects walked for 40 min in two conditions: unpowered (10 min) and powered (30 min). During each session, we extracted modules of muscle recruitment via nonnegative matrix factorization (NNMF) from the surface EMG signals of ten muscles in the lower limb. We evaluated reconstruction quality for each muscle individually using R 2 and normalized root mean squared error (NRMSE). We hypothesized that the number of modules needed to reconstruct muscle data would be the same between conditions and that there would be greater similarity in module timings than weightings. Across subjects, we found that six modules were sufficient to reconstruct the muscle data for both conditions, suggesting that the number of modules was preserved. The similarity of module timings and weightings between conditions was greater then random chance, indicating that muscle coordination was also preserved. Motor adaptation during walking in the exoskeleton was dominated by changes in the module timings rather than module weightings. The segment number and the session number were significant fixed effects in a linear mixed-effect model for the increase in R 2 with time. Our results show that subjects walking in a exoskeleton preserved the number of modules and the coordination of muscles within the modules across conditions. Training (motor adaptation within the session and

Ideal regularization for learning kernels from labels.

PubMed

Pan, Binbin; Lai, Jianhuang; Shen, Lixin

2014-08-01

In this paper, we propose a new form of regularization that is able to utilize the label information of a data set for learning kernels. The proposed regularization, referred to as ideal regularization, is a linear function of the kernel matrix to be learned. The ideal regularization allows us to develop efficient algorithms to exploit labels. Three applications of the ideal regularization are considered. Firstly, we use the ideal regularization to incorporate the labels into a standard kernel, making the resulting kernel more appropriate for learning tasks. Next, we employ the ideal regularization to learn a data-dependent kernel matrix from an initial kernel matrix (which contains prior similarity information, geometric structures, and labels of the data). Finally, we incorporate the ideal regularization to some state-of-the-art kernel learning problems. With this regularization, these learning problems can be formulated as simpler ones which permit more efficient solvers. Empirical results show that the ideal regularization exploits the labels effectively and efficiently. Copyright © 2014 Elsevier Ltd. All rights reserved.

SEMI-SUPERVISED OBJECT RECOGNITION USING STRUCTURE KERNEL

PubMed Central

Wang, Botao; Xiong, Hongkai; Jiang, Xiaoqian; Ling, Fan

2013-01-01

Object recognition is a fundamental problem in computer vision. Part-based models offer a sparse, flexible representation of objects, but suffer from difficulties in training and often use standard kernels. In this paper, we propose a positive definite kernel called “structure kernel”, which measures the similarity of two part-based represented objects. The structure kernel has three terms: 1) the global term that measures the global visual similarity of two objects; 2) the part term that measures the visual similarity of corresponding parts; 3) the spatial term that measures the spatial similarity of geometric configuration of parts. The contribution of this paper is to generalize the discriminant capability of local kernels to complex part-based object models. Experimental results show that the proposed kernel exhibit higher accuracy than state-of-art approaches using standard kernels. PMID:23666108

The pre-image problem in kernel methods.

PubMed

Kwok, James Tin-yau; Tsang, Ivor Wai-hung

2004-11-01

In this paper, we address the problem of finding the pre-image of a feature vector in the feature space induced by a kernel. This is of central importance in some kernel applications, such as on using kernel principal component analysis (PCA) for image denoising. Unlike the traditional method which relies on nonlinear optimization, our proposed method directly finds the location of the pre-image based on distance constraints in the feature space. It is noniterative, involves only linear algebra and does not suffer from numerical instability or local minimum problems. Evaluations on performing kernel PCA and kernel clustering on the USPS data set show much improved performance.

Exploiting graph kernels for high performance biomedical relation extraction.

PubMed

Panyam, Nagesh C; Verspoor, Karin; Cohn, Trevor; Ramamohanarao, Kotagiri

2018-01-30

Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence. Graph kernels such as the All Path Graph kernel (APG) and Approximate Subgraph Matching (ASM) kernel have been shown to be suitable for classifying general graphs with cycles, such as the enhanced dependency parse graph of a sentence. In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. We present a comparative study of kernel methods for the CID task and also extend our study to the Protein-Protein Interaction (PPI) extraction task, an important biomedical relation extraction task. We discuss novel modifications to the ASM kernel to boost its performance and a method to apply graph kernels for extracting relations expressed in multiple sentences. Our system for CID relation extraction attains an F-score of 60%, without using external knowledge sources or task specific heuristic or rules. In comparison, the state of the art Chemical-Disease Relation Extraction system achieves an F-score of 56% using an ensemble of multiple machine learning methods, which is then boosted to 61% with a rule based system employing task specific post processing rules. For the CID task, graph kernels outperform tree kernels substantially, and the best performance is obtained with APG kernel that attains an F-score of 60%, followed by the ASM kernel at 57%. The performance difference between the ASM and APG kernels for CID sentence level relation extraction is not significant. In our evaluation of ASM for the PPI task, ASM

Correlation and classification of single kernel fluorescence hyperspectral data with aflatoxin concentration in corn kernels inoculated with Aspergillus flavus spores.

PubMed

Yao, H; Hruska, Z; Kincaid, R; Brown, R; Cleveland, T; Bhatnagar, D

2010-05-01

The objective of this study was to examine the relationship between fluorescence emissions of corn kernels inoculated with Aspergillus flavus and aflatoxin contamination levels within the kernels. Aflatoxin contamination in corn has been a long-standing problem plaguing the grain industry with potentially devastating consequences to corn growers. In this study, aflatoxin-contaminated corn kernels were produced through artificial inoculation of corn ears in the field with toxigenic A. flavus spores. The kernel fluorescence emission data were taken with a fluorescence hyperspectral imaging system when corn kernels were excited with ultraviolet light. Raw fluorescence image data were preprocessed and regions of interest in each image were created for all kernels. The regions of interest were used to extract spectral signatures and statistical information. The aflatoxin contamination level of single corn kernels was then chemically measured using affinity column chromatography. A fluorescence peak shift phenomenon was noted among different groups of kernels with different aflatoxin contamination levels. The fluorescence peak shift was found to move more toward the longer wavelength in the blue region for the highly contaminated kernels and toward the shorter wavelengths for the clean kernels. Highly contaminated kernels were also found to have a lower fluorescence peak magnitude compared with the less contaminated kernels. It was also noted that a general negative correlation exists between measured aflatoxin and the fluorescence image bands in the blue and green regions. The correlation coefficients of determination, r(2), was 0.72 for the multiple linear regression model. The multivariate analysis of variance found that the fluorescence means of four aflatoxin groups, <1, 1-20, 20-100, and >or=100 ng g(-1) (parts per billion), were significantly different from each other at the 0.01 level of alpha. Classification accuracy under a two-class schema ranged from 0.84 to

Azadirachtin derivatives from seed kernels of Azadirachta excelsa.

PubMed

Kanokmedhakul, Somdej; Kanokmedhakul, Kwanjai; Prajuabsuk, Thirada; Panichajakul, Sanha; Panyamee, Piyanan; Prabpai, Samran; Kongsaeree, Palangpon

2005-07-01

Three new azadirachtin derivatives, named azadirachtins O-Q (1-3), along with the known azadirachtin B (4), azadirachtin L (5), azadirachtin M (6) 11alpha-azadirachtin H (7), 11beta-azadirachtin H (8), and azadirachtol (9) were isolated from seed kernels of Azadirachta excelsa. Their structures were established by spectroscopic techniques, and the structure of 3 was confirmed by X-ray analysis. Compounds 1-7 and 9 exhibited toxicity to the diamondback moth (Plutella xylostella) with an LD50 of 0.75-1.92 microg/g body weight, in 92 h.

Adaptive kernel function using line transect sampling

NASA Astrophysics Data System (ADS)

Albadareen, Baker; Ismail, Noriszura

2018-04-01

The estimation of f(0) is crucial in the line transect method which is used for estimating population abundance in wildlife survey's. The classical kernel estimator of f(0) has a high negative bias. Our study proposes an adaptation in the kernel function which is shown to be more efficient than the usual kernel estimator. A simulation study is adopted to compare the performance of the proposed estimators with the classical kernel estimators.

Kernel K-Means Sampling for Nyström Approximation.

PubMed

He, Li; Zhang, Hong

2018-05-01

A fundamental problem in Nyström-based kernel matrix approximation is the sampling method by which training set is built. In this paper, we suggest to use kernel -means sampling, which is shown in our works to minimize the upper bound of a matrix approximation error. We first propose a unified kernel matrix approximation framework, which is able to describe most existing Nyström approximations under many popular kernels, including Gaussian kernel and polynomial kernel. We then show that, the matrix approximation error upper bound, in terms of the Frobenius norm, is equal to the -means error of data points in kernel space plus a constant. Thus, the -means centers of data in kernel space, or the kernel -means centers, are the optimal representative points with respect to the Frobenius norm error upper bound. Experimental results, with both Gaussian kernel and polynomial kernel, on real-world data sets and image segmentation tasks show the superiority of the proposed method over the state-of-the-art methods.

7 CFR 51.2125 - Split or broken kernels.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Split or broken kernels. 51.2125 Section 51.2125 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards... kernels. Split or broken kernels means seven-eighths or less of complete whole kernels but which will not...

Robotic Intelligence Kernel: Driver

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

The INL Robotic Intelligence Kernel-Driver is built on top of the RIK-A and implements a dynamic autonomy structure. The RIK-D is used to orchestrate hardware for sensing and action as well as software components for perception, communication, behavior and world modeling into a single cognitive behavior kernel that provides intrinsic intelligence for a wide variety of unmanned ground vehicle systems.

Bell nozzle kernel analysis program

NASA Technical Reports Server (NTRS)

Elliot, J. J.; Stromstra, R. R.

1969-01-01

Bell Nozzle Kernel Analysis Program computes and analyzes the supersonic flowfield in the kernel, or initial expansion region, of a bell or conical nozzle. It analyzes both plane and axisymmetric geometrices for specified gas properties, nozzle throat geometry and input line.

7 CFR 51.2296 - Three-fourths half kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Three-fourths half kernel. 51.2296 Section 51.2296 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards...-fourths half kernel. Three-fourths half kernel means a portion of a half of a kernel which has more than...

Application of kernel method in fluorescence molecular tomography

NASA Astrophysics Data System (ADS)

Zhao, Yue; Baikejiang, Reheman; Li, Changqing

2017-02-01

Reconstruction of fluorescence molecular tomography (FMT) is an ill-posed inverse problem. Anatomical guidance in the FMT reconstruction can improve FMT reconstruction efficiently. We have developed a kernel method to introduce the anatomical guidance into FMT robustly and easily. The kernel method is from machine learning for pattern analysis and is an efficient way to represent anatomical features. For the finite element method based FMT reconstruction, we calculate a kernel function for each finite element node from an anatomical image, such as a micro-CT image. Then the fluorophore concentration at each node is represented by a kernel coefficient vector and the corresponding kernel function. In the FMT forward model, we have a new system matrix by multiplying the sensitivity matrix with the kernel matrix. Thus, the kernel coefficient vector is the unknown to be reconstructed following a standard iterative reconstruction process. We convert the FMT reconstruction problem into the kernel coefficient reconstruction problem. The desired fluorophore concentration at each node can be calculated accordingly. Numerical simulation studies have demonstrated that the proposed kernel-based algorithm can improve the spatial resolution of the reconstructed FMT images. In the proposed kernel method, the anatomical guidance can be obtained directly from the anatomical image and is included in the forward modeling. One of the advantages is that we do not need to segment the anatomical image for the targets and background.

7 CFR 868.254 - Broken kernels determination.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 7 2010-01-01 2010-01-01 false Broken kernels determination. 868.254 Section 868.254 Agriculture Regulations of the Department of Agriculture (Continued) GRAIN INSPECTION, PACKERS AND STOCKYARD... Governing Application of Standards § 868.254 Broken kernels determination. Broken kernels shall be...

Evaluating the Gradient of the Thin Wire Kernel

NASA Technical Reports Server (NTRS)

Wilton, Donald R.; Champagne, Nathan J.

2008-01-01

Recently, a formulation for evaluating the thin wire kernel was developed that employed a change of variable to smooth the kernel integrand, canceling the singularity in the integrand. Hence, the typical expansion of the wire kernel in a series for use in the potential integrals is avoided. The new expression for the kernel is exact and may be used directly to determine the gradient of the wire kernel, which consists of components that are parallel and radial to the wire axis.

Predictive value of age of walking for later motor performance in children with mental retardation.

PubMed

Kokubun, M; Haishi, K; Okuzumi, H; Hosobuchi, T; Koike, T

1996-12-01

The purpose of the present study was to clarify the predictive value of age of walking for later motor performance in children with mental retardation. While paying due attention to other factors, our investigation focused on the relationship between a subject's age of walking, and his or her subsequent beam-walking performance. The subjects were 85 children with mental retardation with an average age of 13 years and 3 months. Beam-walking performance was measured by a procedure developed by the authors. Five low beams (5 cm) which varied in width (12.5, 10, 7.5, 5 and 2.5 cm) were employed. The performance of subjects was scored from zero to five points according to the width of the beam that they were able to walk without falling off. From the results of multiple regression analysis, three independent variables were found to be significantly related to beam-walking performance. The age of walking was the most basic variable: partial correlation coefficient (PCC) = -45; standardized partial regression coefficient (SPRC) = -0.41. The next variable in importance was walking duration (PCC = 0.38; SPRC = 0.31). The autism variable also contributed significantly (PCC = 0.28; SPRC = 0.22). Therefore, within the age range used in the present study, the age of walking in children with mental retardation was thought to have sufficient predictive value, even when the variables which might have possibly affected their subsequent performance were taken into consideration; the earlier the age of walking, the better the beam-walking performance.

Gait Evaluation of Overground Walking and Treadmill Walking Using Compass-Type Walking Model

NASA Astrophysics Data System (ADS)

Nagata, Yousuke; Yamamoto, Masayoshi; Funabiki, Shigeyuki

A treadmill is a useful apparatus for the gait training and evaluation. However, many differences are reported between treadmill and overground walking. Experimental comparisons of the muscle activity of the leg and the heart rate have been carried out. However, the dynamic comparison has not been performed. The dynamic evaluation of the overground walking and the treadmill walking using a compass-type walking model (CTWM) which is a simple bipedal walking model, then their comparison is discussed. It is confirmed that the walking simulation using the CTWM can simulate the difference of that walk, it is clarified that there are the differences of the kick impulse on the ground and the turning impulse of the foot to the variation of the belt speed and then differences are the main factor of two walking.

Association of regular walking and body mass index on metabolic syndrome among an elderly Korean population.

PubMed

Kim, Soonyoung; Kim, Dong-Il

2018-06-01

Aging is associated with increased body fat and lower lean body mass, which leads to increased prevalence of obesity and metabolic syndrome. This study aimed to investigate the association of regular participation in walking and body mass index (BMI) with metabolic syndrome and its 5 criteria in elderly Koreans. A total of 3554 (male = 1581, female = 1973) elderly subjects (age ≥ 65 years), who participated in the Fifth Korea National Health and Nutrition Examination Survey (KNHANES V) were analyzed in this cross-sectional study. Participation in walking activity, BMI, metabolic syndrome and its 5 criteria; waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting glucose (FG) levels, triglyceride (TG) levels, and high-density lipoprotein cholesterol (HDLC) levels, were measured. Subjects were categorized into four groups based on the duration and regularity of their walks and BMI. In the regular walking (≥30 min of continuous walking a day, on ≥5 days a week) and normal weight (BMI < 23 kg/m 2 ) group, WC, SBP, DBP, FG, and TG levels were significantly lower, and HDL-C levels were significantly higher, compared to the non-regular walking and overweight (BMI ≥ 23 kg/m 2 ) group. Furthermore, the odds of metabolic syndrome was 4.36 times higher (Odds ratio [OR]: 4.36, 95% confidence interval [CI]: 3.37-5.63) in the non-regular walking and overweight group than that of the regular walking and normal weight group after controlling for the influence of age, sex, and smoking status. Moreover, The BMI (β = 0.328, R 2  = 0.152) were more contributing factors than Regular walking (β = -0.011) for metabolic syndrome. In conclusions, regular participation in walking activity and implementing weight control may reduce the incidence rate of metabolic syndrome in elderly Koreans, with weight management serving as the greater influences of the two. Copyright © 2018. Published by Elsevier

The immediate effects of robot-assistance on energy consumption and cardiorespiratory load during walking compared to walking without robot-assistance: a systematic review.

PubMed

Lefeber, Nina; Swinnen, Eva; Kerckhofs, Eric

2017-10-01

The integration of sufficient cardiovascular stress into robot-assisted gait (RAG) training could combine the benefits of both RAG and aerobic training. The aim was to summarize literature data on the immediate effects of RAG compared to walking without robot-assistance on metabolic-, cardiorespiratory- and fatigue-related parameters. PubMed and Web of Science were searched for eligible articles till February 2016. Means, SDs and significance values were extracted. Effect sizes were calculated. Fourteen studies were included, concerning 155 participants (85 healthy subjects, 39 stroke and 31 spinal cord injury patients), 9 robots (2 end-effectors, 1 treadmill-based and 6 wearable exoskeletons), and 7 outcome parameters (mostly oxygen consumption and heart rate). Overall, metabolic and cardiorespiratory parameters were lower during RAG compared to walking without robot-assistance (moderate to large effect sizes). In healthy subjects, when no body-weight support (BWS) was provided, RAG with an end-effector device was more energy demanding than walking overground (p > .05, large effect sizes). Generally, results suggest that RAG is less energy-consuming and cardiorespiratory stressful than walking without robot-assistance, but results depend on factors such as robot type, walking speed, BWS and effort. Additional research is needed to draw firm conclusions. Implications for Rehabilitation Awareness of the energy consumption and cardiorespiratory load of robot-assisted gait (RAG) training is important in the rehabilitation of (neurological) patients with impaired cardiorespiratory fitness and patients who are at risk of cardiovascular diseases. On the other hand, the integration of sufficient cardiometabolic stress in RAG training could combine the effects of both RAG and aerobic training. Energy consumption and cardiorespiratory load during walking with robot-assistance seems to depend on factors such as robot type, walking speed, body-weight support or amount of

Associations of dietary protein intake on subsequent decline in muscle mass and physical functions over four years in ambulant older Chinese people.

PubMed

Chan, R; Leung, J; Woo, J; Kwok, T

2014-01-01

To examine the association of dietary protein intake with 4-year change in physical performance measures and muscle mass in Chinese community-dwelling older people aged 65 and older in Hong Kong. Prospective cohort study design. Hong Kong, People's of Republic of China. There were 2,726 (1411 male, 1315 female) community-dwelling older people aged 65 and older. Baseline total, animal and vegetable protein intakes were collected using a validated food frequency questionnaire. Relative protein intake expressed as g/kg body weight was calculated and divided into quartiles for data analysis. Baseline and 4-year physical performance measures (normal and narrow 6-meters walking speed and step length in a 6-meters walk) were measured and 4-year change in appendicular skeletal muscle mass (ASM) from baseline was assessed by dual-energy X-ray absorptiometry. Univariate analysis identified age and sex as significant factors associated with change in physical performance measures or ASM, thus adjustments for these factors were made for subsequent analysis of covariance. Median relative total protein intake was 1.3 g/kg body weight in men and 1.1 g/kg body weight in women. After adjustment for age and sex, relative total protein intake and animal protein intake were not associated with change in physical performance measures and ASM. In contrast, participants in the highest quartile (>0.72 g/kg body weight) of relative vegetable protein intake lost significantly less ASM over 4-year than those in the lowest quartile of relative vegetable protein intake (<=0.40 g/kg body weight) (adjusted mean ± SE: 0.270 ± 0.029 vs. 0.349 ± 0.030 kg, ptrend=0.025). There was no association between relative vegetable protein intake and change in physical performance measures. Higher protein intake from vegetable source was associated with reduced muscle loss in Chinese community-dwelling older people in Hong Kong whereas no association between total and animal protein intake and subsequent

KITTEN Lightweight Kernel 0.1 Beta

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

Pedretti, Kevin; Levenhagen, Michael; Kelly, Suzanne

2007-12-12

The Kitten Lightweight Kernel is a simplified OS (operating system) kernel that is intended to manage a compute node's hardware resources. It provides a set of mechanisms to user-level applications for utilizing hardware resources (e.g., allocating memory, creating processes, accessing the network). Kitten is much simpler than general-purpose OS kernels, such as Linux or Windows, but includes all of the esssential functionality needed to support HPC (high-performance computing) MPI, PGAS and OpenMP applications. Kitten provides unique capabilities such as physically contiguous application memory, transparent large page support, and noise-free tick-less operation, which enable HPC applications to obtain greater efficiency andmore » scalability than with general purpose OS kernels.« less

Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick.

PubMed

Kwak, Nojun

2016-05-20

Recently, the nonlinear projection trick (NPT) was introduced enabling direct computation of coordinates of samples in a reproducing kernel Hilbert space. With NPT, any machine learning algorithm can be extended to a kernel version without relying on the so called kernel trick. However, NPT is inherently difficult to be implemented incrementally because an ever increasing kernel matrix should be treated as additional training samples are introduced. In this paper, an incremental version of the NPT (INPT) is proposed based on the observation that the centerization step in NPT is unnecessary. Because the proposed INPT does not change the coordinates of the old data, the coordinates obtained by INPT can directly be used in any incremental methods to implement a kernel version of the incremental methods. The effectiveness of the INPT is shown by applying it to implement incremental versions of kernel methods such as, kernel singular value decomposition, kernel principal component analysis, and kernel discriminant analysis which are utilized for problems of kernel matrix reconstruction, letter classification, and face image retrieval, respectively.

Fully-Automated High-Throughput NMR System for Screening of Haploid Kernels of Maize (Corn) by Measurement of Oil Content

PubMed Central

Xu, Xiaoping; Huang, Qingming; Chen, Shanshan; Yang, Peiqiang; Chen, Shaojiang; Song, Yiqiao

2016-01-01

One of the modern crop breeding techniques uses doubled haploid plants that contain an identical pair of chromosomes in order to accelerate the breeding process. Rapid haploid identification method is critical for large-scale selections of double haploids. The conventional methods based on the color of the endosperm and embryo seeds are slow, manual and prone to error. On the other hand, there exists a significant difference between diploid and haploid seeds generated by high oil inducer, which makes it possible to use oil content to identify the haploid. This paper describes a fully-automated high-throughput NMR screening system for maize haploid kernel identification. The system is comprised of a sampler unit to select a single kernel to feed for measurement of NMR and weight, and a kernel sorter to distribute the kernel according to the measurement result. Tests of the system show a consistent accuracy of 94% with an average screening time of 4 seconds per kernel. Field test result is described and the directions for future improvement are discussed. PMID:27454427

7 CFR 868.304 - Broken kernels determination.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 7 2011-01-01 2011-01-01 false Broken kernels determination. 868.304 Section 868.304 Agriculture Regulations of the Department of Agriculture (Continued) GRAIN INSPECTION, PACKERS AND STOCKYARD... Application of Standards § 868.304 Broken kernels determination. Broken kernels shall be determined by the use...

7 CFR 868.304 - Broken kernels determination.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 7 2010-01-01 2010-01-01 false Broken kernels determination. 868.304 Section 868.304 Agriculture Regulations of the Department of Agriculture (Continued) GRAIN INSPECTION, PACKERS AND STOCKYARD... Application of Standards § 868.304 Broken kernels determination. Broken kernels shall be determined by the use...

Higher Weight, Lower Education: A Longitudinal Association between Adolescents' Body Mass Index and Their Subsequent Educational Achievement Level?

ERIC Educational Resources Information Center

Larsen, Junilla K.; Kleinjan, Marloes; Engels, Rutger C. M. E.; Fisher, Jennifer O.; Hermans, Roel

2014-01-01

Background: The purpose of this study was to examine the association between adolescents' body mass index (BMI) z-scores and their subsequent level of schooling, extending previous longitudinal research by using objectively measured weight and height data. Methods: A longitudinal study with 3 study waves (1-year intervals) involving 1248 Dutch…

Comparison of a reduced carbohydrate and reduced fat diet for LDL, HDL, and VLDL subclasses during 9-months of weight maintenance subsequent to weight loss.

PubMed

LeCheminant, James D; Smith, Bryan K; Westman, Eric C; Vernon, Mary C; Donnelly, Joseph E

2010-06-01

This study compared LDL, HDL, and VLDL subclasses in overweight or obese adults consuming either a reduced carbohydrate (RC) or reduced fat (RF) weight maintenance diet for 9 months following significant weight loss. Thirty-five (21 RC; 14 RF) overweight or obese middle-aged adults completed a 1-year weight management clinic. Participants met weekly for the first six months and bi-weekly thereafter. Meetings included instruction for diet, physical activity, and behavior change related to weight management. Additionally, participants followed a liquid very low-energy diet of approximately 2092 kJ per day for the first three months of the study. Subsequently, participants followed a dietary plan for nine months that targeted a reduced percentage of carbohydrate (approximately 20%) or fat (approximately 30%) intake and an energy intake level calculated to maintain weight loss. Lipid subclasses using NMR spectroscopy were analyzed prior to weight loss and at multiple intervals during weight maintenance. Body weight change was not significantly different within or between groups during weight maintenance (p>0.05). The RC group showed significant increases in mean LDL size, large LDL, total HDL, large and small HDL, mean VLDL size, and large VLDL during weight maintenance while the RF group showed increases in total HDL, large and small HDL, total VLDL, and large, medium, and small VLDL (p<0.05). Group*time interactions were significant for large and medium VLDL (p>0.05). Some individual lipid subclasses improved in both dietary groups. Large and medium VLDL subclasses increased to a greater extent across weight maintenance in the RF group.

Crutches and children - standing and walking

MedlinePlus

... weight on the armpits can hurt, and your child can get a rash and damage nerves and blood vessels under his arm. Hop forward on the good foot just a little in front of the crutches. ... with the injured leg. Look ahead when walking, not at the feet.

Kernel learning at the first level of inference.

PubMed

Cawley, Gavin C; Talbot, Nicola L C

2014-05-01

Kernel learning methods, whether Bayesian or frequentist, typically involve multiple levels of inference, with the coefficients of the kernel expansion being determined at the first level and the kernel and regularisation parameters carefully tuned at the second level, a process known as model selection. Model selection for kernel machines is commonly performed via optimisation of a suitable model selection criterion, often based on cross-validation or theoretical performance bounds. However, if there are a large number of kernel parameters, as for instance in the case of automatic relevance determination (ARD), there is a substantial risk of over-fitting the model selection criterion, resulting in poor generalisation performance. In this paper we investigate the possibility of learning the kernel, for the Least-Squares Support Vector Machine (LS-SVM) classifier, at the first level of inference, i.e. parameter optimisation. The kernel parameters and the coefficients of the kernel expansion are jointly optimised at the first level of inference, minimising a training criterion with an additional regularisation term acting on the kernel parameters. The key advantage of this approach is that the values of only two regularisation parameters need be determined in model selection, substantially alleviating the problem of over-fitting the model selection criterion. The benefits of this approach are demonstrated using a suite of synthetic and real-world binary classification benchmark problems, where kernel learning at the first level of inference is shown to be statistically superior to the conventional approach, improves on our previous work (Cawley and Talbot, 2007) and is competitive with Multiple Kernel Learning approaches, but with reduced computational expense. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multiple kernels learning-based biological entity relationship extraction method.

PubMed

Dongliang, Xu; Jingchang, Pan; Bailing, Wang

2017-09-20

Automatic extracting protein entity interaction information from biomedical literature can help to build protein relation network and design new drugs. There are more than 20 million literature abstracts included in MEDLINE, which is the most authoritative textual database in the field of biomedicine, and follow an exponential growth over time. This frantic expansion of the biomedical literature can often be difficult to absorb or manually analyze. Thus efficient and automated search engines are necessary to efficiently explore the biomedical literature using text mining techniques. The P, R, and F value of tag graph method in Aimed corpus are 50.82, 69.76, and 58.61%, respectively. The P, R, and F value of tag graph kernel method in other four evaluation corpuses are 2-5% higher than that of all-paths graph kernel. And The P, R and F value of feature kernel and tag graph kernel fuse methods is 53.43, 71.62 and 61.30%, respectively. The P, R and F value of feature kernel and tag graph kernel fuse methods is 55.47, 70.29 and 60.37%, respectively. It indicated that the performance of the two kinds of kernel fusion methods is better than that of simple kernel. In comparison with the all-paths graph kernel method, the tag graph kernel method is superior in terms of overall performance. Experiments show that the performance of the multi-kernels method is better than that of the three separate single-kernel method and the dual-mutually fused kernel method used hereof in five corpus sets.

Required coefficient of friction in the anteroposterior and mediolateral direction during turning at different walking speeds

PubMed Central

Yamaguchi, Takeshi; Suzuki, Akito; Hokkirigawa, Kazuo

2017-01-01

This study investigated the required coefficient of friction (RCOF) and the tangent of center of mass (COM)–center of pressure (COP) angle in the mediolateral (ML) and anteroposterior (AP) directions during turning at different walking speeds. Sixteen healthy young adults (8 males and 8 females) participated in this study. The participants were instructed to conduct trials of straight walking and 90° step and spin turns to the right at each of three self-selected speeds (slow, normal, and fast). The ML and AP directions during turning gait were defined using the orientation of the pelvis to construct a body-fixed reference frame. The RCOF values and COM–COP angle tangent in the ML direction during turning at weight acceptance phase were higher than those during straight walking, and those values increased with increasing walking speed. The ML component of the RCOF and COM–COP tangent values during weight acceptance for step turns were higher than those for spin turns. The mean centripetal force during turning tended to increase with an increase in walking speed and had a strong positive correlation with the RCOF values in the ML direction (R = 0.97 during the weight acceptance phase; R = 0.95 during the push-off phase). Therefore, turning, particularly step turn, is likely to cause lateral slip at weight acceptance because of the increased centripetal force compared with straight walking. Future work should test at-risk population and compare with the present results. PMID:28640853

Required coefficient of friction in the anteroposterior and mediolateral direction during turning at different walking speeds.

PubMed

Yamaguchi, Takeshi; Suzuki, Akito; Hokkirigawa, Kazuo

2017-01-01

This study investigated the required coefficient of friction (RCOF) and the tangent of center of mass (COM)-center of pressure (COP) angle in the mediolateral (ML) and anteroposterior (AP) directions during turning at different walking speeds. Sixteen healthy young adults (8 males and 8 females) participated in this study. The participants were instructed to conduct trials of straight walking and 90° step and spin turns to the right at each of three self-selected speeds (slow, normal, and fast). The ML and AP directions during turning gait were defined using the orientation of the pelvis to construct a body-fixed reference frame. The RCOF values and COM-COP angle tangent in the ML direction during turning at weight acceptance phase were higher than those during straight walking, and those values increased with increasing walking speed. The ML component of the RCOF and COM-COP tangent values during weight acceptance for step turns were higher than those for spin turns. The mean centripetal force during turning tended to increase with an increase in walking speed and had a strong positive correlation with the RCOF values in the ML direction (R = 0.97 during the weight acceptance phase; R = 0.95 during the push-off phase). Therefore, turning, particularly step turn, is likely to cause lateral slip at weight acceptance because of the increased centripetal force compared with straight walking. Future work should test at-risk population and compare with the present results.

Credit scoring analysis using weighted k nearest neighbor

NASA Astrophysics Data System (ADS)

Mukid, M. A.; Widiharih, T.; Rusgiyono, A.; Prahutama, A.

2018-05-01

Credit scoring is a quatitative method to evaluate the credit risk of loan applications. Both statistical methods and artificial intelligence are often used by credit analysts to help them decide whether the applicants are worthy of credit. These methods aim to predict future behavior in terms of credit risk based on past experience of customers with similar characteristics. This paper reviews the weighted k nearest neighbor (WKNN) method for credit assessment by considering the use of some kernels. We use credit data from a private bank in Indonesia. The result shows that the Gaussian kernel and rectangular kernel have a better performance based on the value of percentage corrected classified whose value is 82.4% respectively.

Intake of total, animal and plant protein and subsequent changes in weight or waist circumference in European men and women: the Diogenes project.

PubMed

Halkjær, J; Olsen, A; Overvad, K; Jakobsen, M U; Boeing, H; Buijsse, B; Palli, D; Tognon, G; Du, H; van der A, D L; Forouhi, N G; Wareham, N J; Feskens, E J M; Sørensen, T I A; Tjønneland, A

2011-08-01

As protein is considered to increase thermogenesis and satiety more than other macronutrients, it may have beneficial effects on prevention of weight gain and weight maintenance. The objective of this study is to assess the association between the amount and type of dietary protein, and subsequent changes in weight and waist circumference (WC). 89,432 men and women from five countries participating in European Prospective Investigation into Cancer and Nutrition (EPIC) were followed for a mean of 6.5 years. Associations between the intake of protein or subgroups of protein (from animal and plant sources) and changes in weight (g per year) or WC (cm per year) were investigated using gender and centre-specific multiple regression analyses. Adjustments were made for other baseline dietary factors, baseline anthropometrics, demographic and lifestyle factors and follow-up time. We used random effect meta-analyses to obtain pooled estimates across centres. Higher intake of total protein, and protein from animal sources was associated with subsequent weight gain for both genders, strongest among women, and the association was mainly attributable to protein from red and processed meat and poultry rather than from fish and dairy sources. There was no overall association between intake of plant protein and subsequent changes in weight. No clear overall associations between intakes of total protein or any of the subgroups and changes in WC were present. The associations showed some heterogeneity between centres, but pooling of estimates was still considered justified. A high intake of protein was not found associated with lower weight or waist gain in this observational study. In contrast, protein from food items of animal origin, especially meat and poultry, seemed to be positively associated with long-term weight gain. There were no clear associations for waist changes.

Quality of Public Open Spaces and Recreational Walking

PubMed Central

Gunn, Lucy D.; Christian, Hayley; Francis, Jacinta; Foster, Sarah; Hooper, Paula; Owen, Neville; Giles-Corti, Billie

2015-01-01

Objectives. We examined associations between specific public open space (POS) attributes and recreational walking to local POS. Methods. Between October 2004 and December 2006, 1465 adults of the RESIDential Environments Project, conducted in Perth, Australia, reported whether they walk to a POS for recreation. For each participant, we identified all open spaces larger than 0.8 hectares within 1.6 kilometers from home. On the basis of field audit data, we created 3 scores (presence, count, size-weighted presence) for 19 specific open space attributes. Results. With logistic regression analyses, we found that walking to a POS was associated with the presence of gardens, grassed areas, walking paths, water features, wildlife, amenities, dog-related facilities, and off-leash areas for dogs. It was also associated with the highest number of these attributes in a single open space, but not with the total number of attributes in all POSs within 1.6 kilometers of home. Conclusions. Building 1 high-quality local park may be more effective in promoting recreational walking than is providing many average-quality parks. PMID:26469676

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... generally conforms to the “light” or “light amber” classification, that color classification may be used to... 7 Agriculture 2 2013-01-01 2013-01-01 false Kernel color classification. 51.1403 Section 51.1403... Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be...

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... generally conforms to the “light” or “light amber” classification, that color classification may be used to... 7 Agriculture 2 2014-01-01 2014-01-01 false Kernel color classification. 51.1403 Section 51.1403... Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be...

Evidence-based Kernels: Fundamental Units of Behavioral Influence

PubMed Central

Biglan, Anthony

2008-01-01

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior. PMID:18712600

Integrating the Gradient of the Thin Wire Kernel

NASA Technical Reports Server (NTRS)

Champagne, Nathan J.; Wilton, Donald R.

2008-01-01

A formulation for integrating the gradient of the thin wire kernel is presented. This approach employs a new expression for the gradient of the thin wire kernel derived from a recent technique for numerically evaluating the exact thin wire kernel. This approach should provide essentially arbitrary accuracy and may be used with higher-order elements and basis functions using the procedure described in [4].When the source and observation points are close, the potential integrals over wire segments involving the wire kernel are split into parts to handle the singular behavior of the integrand [1]. The singularity characteristics of the gradient of the wire kernel are different than those of the wire kernel, and the axial and radial components have different singularities. The characteristics of the gradient of the wire kernel are discussed in [2]. To evaluate the near electric and magnetic fields of a wire, the integration of the gradient of the wire kernel needs to be calculated over the source wire. Since the vector bases for current have constant direction on linear wire segments, these integrals reduce to integrals of the form

THERMOS. 30-Group ENDF/B Scattered Kernels

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

McCrosson, F.J.; Finch, D.R.

1973-12-01

These data are 30-group THERMOS thermal scattering kernels for P0 to P5 Legendre orders for every temperature of every material from s(alpha,beta) data stored in the ENDF/B library. These scattering kernels were generated using the FLANGE2 computer code. To test the kernels, the integral properties of each set of kernels were determined by a precision integration of the diffusion length equation and compared to experimental measurements of these properties. In general, the agreement was very good. Details of the methods used and results obtained are contained in the reference. The scattering kernels are organized into a two volume magnetic tapemore » library from which they may be retrieved easily for use in any 30-group THERMOS library.« less

Amygdalin metabolism and effect on reproduction of rats fed apricot kernels.

PubMed

Miller, K W; Anderson, J L; Stoewsand, G S

1981-01-01

Diets containing 10% ground apricot kernels were fed to young and breeding male and female Sprague-Dawley rats. The kernels werE obtained from 35 specific apricot cultivars and divided into groups containing low amygdalin (less than 50 mg cyanide per 100 g), moderate amygdalin (100-200 mg cyanide per 100 g), or high amygdalin (more than 200 mg cyanide per 100 g). Growth of young male rats was greatest in the low- or moderate-amygdalin group which may indicate only that they were more sensitive to the bitter taste of the kernels with high amygdalin contents. In female rats, but not males, liver rhodanese activity and thiocyanate (SCN) blood levels were increased with the high-amygdalin diet, but both male and females efficiently excreted thiocyanate, indicating efficient detoxication and clearance of cyanide hydrolyzed from the dietary amygdalin. No changes in blood chemistry were observed. Although parturition and 3-d survival indices were poor in pups from dams fed a basal semisynthetic diet, offspring of breeding rats fed the high-amygdalin diet for 18 wk had lower 3-d survival indices, lactation indices, and weaning weights than those in the low-amygdalin group. This may indicate that the cyanide present in the milk may not be efficiently detoxified to SCN and excreted by neonates.

Modified kernel-based nonlinear feature extraction.

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

Ma, J.; Perkins, S. J.; Theiler, J. P.

2002-01-01

Feature Extraction (FE) techniques are widely used in many applications to pre-process data in order to reduce the complexity of subsequent processes. A group of Kernel-based nonlinear FE ( H E ) algorithms has attracted much attention due to their high performance. However, a serious limitation that is inherent in these algorithms -- the maximal number of features extracted by them is limited by the number of classes involved -- dramatically degrades their flexibility. Here we propose a modified version of those KFE algorithms (MKFE), This algorithm is developed from a special form of scatter-matrix, whose rank is not determinedmore » by the number of classes involved, and thus breaks the inherent limitation in those KFE algorithms. Experimental results suggest that MKFE algorithm is .especially useful when the training set is small.« less

Effect of the walking speed to the lower limb joint angular displacements, joint moments and ground reaction forces during walking in water.

PubMed

Miyoshi, Tasuku; Shirota, Takashi; Yamamoto, Shin-ichiro; Nakazawa, Kimitaka; Akai, Masami

2004-06-17

The purpose of this study was to compare the changes in ground reaction forces (GRF), joint angular displacements (JAD), joint moments (JM) and electromyographic (EMG) activities that occur during walking at various speeds in water and on land. Fifteen healthy adults participated in this study. In the water experiments, the water depth was adjusted so that body weight was reduced by 80%. A video-motion analysis system and waterproof force platform was used to obtain kinematics and kinetics data and to calculate the JMs. Results revealed that (1) the anterior-posterior GRF patterns differed between walking in water and walking on land, whereas the medio-lateral GRF patterns were similar, (2) the JAD patterns of the hip and ankle were similar between water- and land-walking, whereas the range of motion at the knee joint was lower in water than on land, (3) the JMs in all three joints were lower in water than on land throughout the stance phase, and (4) the hip joint extension moment and hip extensor muscle EMG activity were increased as walking speed increase during walking in water. Rehabilitative water-walking exercise could be designed to incorporate large-muscle activities, especially of the lower-limb extensor muscles, through full joint range of motion and minimization of joint moments.

The Classification of Diabetes Mellitus Using Kernel k-means

NASA Astrophysics Data System (ADS)

Alamsyah, M.; Nafisah, Z.; Prayitno, E.; Afida, A. M.; Imah, E. M.

2018-01-01

Diabetes Mellitus is a metabolic disorder which is characterized by chronicle hypertensive glucose. Automatics detection of diabetes mellitus is still challenging. This study detected diabetes mellitus by using kernel k-Means algorithm. Kernel k-means is an algorithm which was developed from k-means algorithm. Kernel k-means used kernel learning that is able to handle non linear separable data; where it differs with a common k-means. The performance of kernel k-means in detecting diabetes mellitus is also compared with SOM algorithms. The experiment result shows that kernel k-means has good performance and a way much better than SOM.

Relation between random walks and quantum walks

NASA Astrophysics Data System (ADS)

Boettcher, Stefan; Falkner, Stefan; Portugal, Renato

2015-05-01

Based on studies of four specific networks, we conjecture a general relation between the walk dimensions dw of discrete-time random walks and quantum walks with the (self-inverse) Grover coin. In each case, we find that dw of the quantum walk takes on exactly half the value found for the classical random walk on the same geometry. Since walks on homogeneous lattices satisfy this relation trivially, our results for heterogeneous networks suggest that such a relation holds irrespective of whether translational invariance is maintained or not. To develop our results, we extend the renormalization-group analysis (RG) of the stochastic master equation to one with a unitary propagator. As in the classical case, the solution ρ (x ,t ) in space and time of this quantum-walk equation exhibits a scaling collapse for a variable xdw/t in the weak limit, which defines dw and illuminates fundamental aspects of the walk dynamics, e.g., its mean-square displacement. We confirm the collapse for ρ (x ,t ) in each case with extensive numerical simulation. The exact values for dw themselves demonstrate that RG is a powerful complementary approach to study the asymptotics of quantum walks that weak-limit theorems have not been able to access, such as for systems lacking translational symmetries beyond simple trees.

Brain tumor image segmentation using kernel dictionary learning.

PubMed

Jeon Lee; Seung-Jun Kim; Rong Chen; Herskovits, Edward H

2015-08-01

Automated brain tumor image segmentation with high accuracy and reproducibility holds a big potential to enhance the current clinical practice. Dictionary learning (DL) techniques have been applied successfully to various image processing tasks recently. In this work, kernel extensions of the DL approach are adopted. Both reconstructive and discriminative versions of the kernel DL technique are considered, which can efficiently incorporate multi-modal nonlinear feature mappings based on the kernel trick. Our novel discriminative kernel DL formulation allows joint learning of a task-driven kernel-based dictionary and a linear classifier using a K-SVD-type algorithm. The proposed approaches were tested using real brain magnetic resonance (MR) images of patients with high-grade glioma. The obtained preliminary performances are competitive with the state of the art. The discriminative kernel DL approach is seen to reduce computational burden without much sacrifice in performance.

Development of a kernel function for clinical data.

PubMed

Daemen, Anneleen; De Moor, Bart

2009-01-01

For most diseases and examinations, clinical data such as age, gender and medical history guides clinical management, despite the rise of high-throughput technologies. To fully exploit such clinical information, appropriate modeling of relevant parameters is required. As the widely used linear kernel function has several disadvantages when applied to clinical data, we propose a new kernel function specifically developed for this data. This "clinical kernel function" more accurately represents similarities between patients. Evidently, three data sets were studied and significantly better performances were obtained with a Least Squares Support Vector Machine when based on the clinical kernel function compared to the linear kernel function.

Gestational weight gain and subsequent postpartum weight loss among young, low-income, ethnic minority women.

PubMed

Gould Rothberg, Bonnie E; Magriples, Urania; Kershaw, Trace S; Rising, Sharon Schindler; Ickovics, Jeannette R

2011-01-01

Document weight change trajectories that lead to gestational weight gain or postpartum weight loss outside clinical recommendations established by the Institute of Medicine. Women aged 14-25 receiving prenatal care and delivering singleton infants at term (n = 427). Medical record review and 4 structured interviews conducted: second and third trimester, 6- and 12-months postpartum. Longitudinal mixed modeling to evaluate weight change trajectories. Only 22% of participants gained gestational weight within Institute of Medicine guidelines. There were 62% that exceeded maximum recommendations-more common among those overweight/obese (body mass index ≥25.0; P < .0001). 52% retained ≥10 lb 1-year postpartum. Increased weight gain and retention documented among smokers and women with pregnancy-induced hypertension; breastfeeding promoted postpartum weight loss (all P < .02). Body mass index by race interaction suggested healthier outcomes for Latinas (P = .02). Excessive pregnancy weight gain and inadequate postpartum weight loss are highly prevalent among young low-income ethnic minority women. Pregnancy and postpartum are critical junctures for weight management interventions. Copyright © 2011 Mosby, Inc. All rights reserved.

Towards the Geometry of Reproducing Kernels

NASA Astrophysics Data System (ADS)

Galé, J. E.

2010-11-01

It is shown here how one is naturally led to consider a category whose objects are reproducing kernels of Hilbert spaces, and how in this way a differential geometry for such kernels may be settled down.

Application of stochastic weighted algorithms to a multidimensional silica particle model

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

Menz, William J.; Patterson, Robert I.A.; Wagner, Wolfgang

2013-09-01

Highlights: •Stochastic weighted algorithms (SWAs) are developed for a detailed silica model. •An implementation of SWAs with the transition kernel is presented. •The SWAs’ solutions converge to the direct simulation algorithm’s (DSA) solution. •The efficiency of SWAs is evaluated for this multidimensional particle model. •It is shown that SWAs can be used for coagulation problems in industrial systems. -- Abstract: This paper presents a detailed study of the numerical behaviour of stochastic weighted algorithms (SWAs) using the transition regime coagulation kernel and a multidimensional silica particle model. The implementation in the SWAs of the transition regime coagulation kernel and associatedmore » majorant rates is described. The silica particle model of Shekar et al. [S. Shekar, A.J. Smith, W.J. Menz, M. Sander, M. Kraft, A multidimensional population balance model to describe the aerosol synthesis of silica nanoparticles, Journal of Aerosol Science 44 (2012) 83–98] was used in conjunction with this coagulation kernel to study the convergence properties of SWAs with a multidimensional particle model. High precision solutions were calculated with two SWAs and also with the established direct simulation algorithm. These solutions, which were generated using large number of computational particles, showed close agreement. It was thus demonstrated that SWAs can be successfully used with complex coagulation kernels and high dimensional particle models to simulate real-world systems.« less

Biomechanics of stair walking and jumping.

PubMed

Loy, D J; Voloshin, A S

1991-01-01

Physical activities such as stair walking and jumping result in increased dynamic loading on the human musculoskeletal system. Use of light weight, externally attached accelerometers allows for in-vivo monitoring of the shock waves invading the human musculoskeletal system during those activities. Shock waves were measured in four subjects performing stair walking up and down, jumping in place and jumping off a fixed elevation. The results obtained show that walking down a staircase induced shock waves with amplitude of 130% of that observed in walking up stairs and 250% of the shock waves experienced in level gait. The jumping test revealed levels of the shock waves nearly eight times higher than that in level walking. It was also shown that the shock waves invading the human musculoskeletal system may be generated not only by the heel strike, but also by the metatarsal strike. To moderate the risk of degenerative joint disorders four types of viscoelastic insoles were utilized to reduce the impact generated shock waves. The insoles investigated were able to reduce the amplitude of the shock wave by between 9% and 41% depending on the insole type and particular physical activity. The insoles were more effective in the reduction of the heel strike impacts than in the reduction of the metatarsal strike impacts. In all instances, the shock attenuation capacities of the insoles tested were greater in the jumping trials than in the stair walking studies. The insoles were ranked in three groups on the basis of their shock absorbing capacity.

Varied overground walking-task practice versus body-weight-supported treadmill training in ambulatory adults within one year of stroke: a randomized controlled trial protocol.

PubMed

DePaul, Vincent G; Wishart, Laurie R; Richardson, Julie; Lee, Timothy D; Thabane, Lehana

2011-10-21

Although task-oriented training has been shown to improve walking outcomes after stroke, it is not yet clear whether one task-oriented approach is superior to another. The purpose of this study is to compare the effectiveness of the Motor Learning Walking Program (MLWP), a varied overground walking task program consistent with key motor learning principles, to body-weight-supported treadmill training (BWSTT) in community-dwelling, ambulatory, adults within 1 year of stroke. A parallel, randomized controlled trial with stratification by baseline gait speed will be conducted. Allocation will be controlled by a central randomization service and participants will be allocated to the two active intervention groups (1:1) using a permuted block randomization process. Seventy participants will be assigned to one of two 15-session training programs. In MLWP, one physiotherapist will supervise practice of various overground walking tasks. Instructions, feedback, and guidance will be provided in a manner that facilitates self-evaluation and problem solving. In BWSTT, training will emphasize repetition of the normal gait cycle while supported over a treadmill, assisted by up to three physiotherapists. Outcomes will be assessed by a blinded assessor at baseline, post-intervention and at 2-month follow-up. The primary outcome will be post-intervention comfortable gait speed. Secondary outcomes include fast gait speed, walking endurance, balance self-efficacy, participation in community mobility, health-related quality of life, and goal attainment. Groups will be compared using analysis of covariance with baseline gait speed strata as the single covariate. Intention-to-treat analysis will be used. In order to direct clinicians, patients, and other health decision-makers, there is a need for a head-to-head comparison of different approaches to active, task-related walking training after stroke. We hypothesize that outcomes will be optimized through the application of a task

Varied overground walking-task practice versus body-weight-supported treadmill training in ambulatory adults within one year of stroke: a randomized controlled trial protocol

PubMed Central

2011-01-01

Background Although task-oriented training has been shown to improve walking outcomes after stroke, it is not yet clear whether one task-oriented approach is superior to another. The purpose of this study is to compare the effectiveness of the Motor Learning Walking Program (MLWP), a varied overground walking task program consistent with key motor learning principles, to body-weight-supported treadmill training (BWSTT) in community-dwelling, ambulatory, adults within 1 year of stroke. Methods/Design A parallel, randomized controlled trial with stratification by baseline gait speed will be conducted. Allocation will be controlled by a central randomization service and participants will be allocated to the two active intervention groups (1:1) using a permuted block randomization process. Seventy participants will be assigned to one of two 15-session training programs. In MLWP, one physiotherapist will supervise practice of various overground walking tasks. Instructions, feedback, and guidance will be provided in a manner that facilitates self-evaluation and problem solving. In BWSTT, training will emphasize repetition of the normal gait cycle while supported over a treadmill, assisted by up to three physiotherapists. Outcomes will be assessed by a blinded assessor at baseline, post-intervention and at 2-month follow-up. The primary outcome will be post-intervention comfortable gait speed. Secondary outcomes include fast gait speed, walking endurance, balance self-efficacy, participation in community mobility, health-related quality of life, and goal attainment. Groups will be compared using analysis of covariance with baseline gait speed strata as the single covariate. Intention-to-treat analysis will be used. Discussion In order to direct clinicians, patients, and other health decision-makers, there is a need for a head-to-head comparison of different approaches to active, task-related walking training after stroke. We hypothesize that outcomes will be optimized

Ingestion of High Molecular Weight Carbohydrate Enhances Subsequent Repeated Maximal Power: A Randomized Controlled Trial

PubMed Central

Oliver, Jonathan M.; Almada, Anthony L.; Van Eck, Leighsa E.; Shah, Meena; Mitchell, Joel B.; Jones, Margaret T.; Jagim, Andrew R.; Rowlands, David S.

2016-01-01

Athletes in sports demanding repeat maximal work outputs frequently train concurrently utilizing sequential bouts of intense endurance and resistance training sessions. On a daily basis, maximal work within subsequent bouts may be limited by muscle glycogen availability. Recently, the ingestion of a unique high molecular weight (HMW) carbohydrate was found to increase glycogen re-synthesis rate and enhance work output during subsequent endurance exercise, relative to low molecular weight (LMW) carbohydrate ingestion. The effect of the HMW carbohydrate, however, on the performance of intense resistance exercise following prolonged-intense endurance training is unknown. Sixteen resistance trained men (23±3 years; 176.7±9.8 cm; 88.2±8.6 kg) participated in a double-blind, placebo-controlled, randomized 3-way crossover design comprising a muscle-glycogen depleting cycling exercise followed by ingestion of placebo (PLA), or 1.2 g•kg•bw-1 of LMW or HMW carbohydrate solution (10%) with blood sampling for 2-h post-ingestion. Thereafter, participants performed 5 sets of 10 maximal explosive repetitions of back squat (75% of 1RM). Compared to PLA, ingestion of HMW (4.9%, 90%CI 3.8%, 5.9%) and LMW (1.9%, 90%CI 0.8%, 3.0%) carbohydrate solutions substantially increased power output during resistance exercise, with the 3.1% (90% CI 4.3, 2.0%) almost certain additional gain in power after HMW-LMW ingestion attributed to higher movement velocity after force kinematic analysis (HMW-LMW 2.5%, 90%CI 1.4, 3.7%). Both carbohydrate solutions increased post-exercise plasma glucose, glucoregulatory and gut hormones compared to PLA, but differences between carbohydrates were unclear; thus, the underlying mechanism remains to be elucidated. Ingestion of a HMW carbohydrate following prolonged intense endurance exercise provides superior benefits to movement velocity and power output during subsequent repeated maximal explosive resistance exercise. This study was registered with

Ingestion of High Molecular Weight Carbohydrate Enhances Subsequent Repeated Maximal Power: A Randomized Controlled Trial.

PubMed

Oliver, Jonathan M; Almada, Anthony L; Van Eck, Leighsa E; Shah, Meena; Mitchell, Joel B; Jones, Margaret T; Jagim, Andrew R; Rowlands, David S

2016-01-01

Athletes in sports demanding repeat maximal work outputs frequently train concurrently utilizing sequential bouts of intense endurance and resistance training sessions. On a daily basis, maximal work within subsequent bouts may be limited by muscle glycogen availability. Recently, the ingestion of a unique high molecular weight (HMW) carbohydrate was found to increase glycogen re-synthesis rate and enhance work output during subsequent endurance exercise, relative to low molecular weight (LMW) carbohydrate ingestion. The effect of the HMW carbohydrate, however, on the performance of intense resistance exercise following prolonged-intense endurance training is unknown. Sixteen resistance trained men (23±3 years; 176.7±9.8 cm; 88.2±8.6 kg) participated in a double-blind, placebo-controlled, randomized 3-way crossover design comprising a muscle-glycogen depleting cycling exercise followed by ingestion of placebo (PLA), or 1.2 g•kg•bw-1 of LMW or HMW carbohydrate solution (10%) with blood sampling for 2-h post-ingestion. Thereafter, participants performed 5 sets of 10 maximal explosive repetitions of back squat (75% of 1RM). Compared to PLA, ingestion of HMW (4.9%, 90%CI 3.8%, 5.9%) and LMW (1.9%, 90%CI 0.8%, 3.0%) carbohydrate solutions substantially increased power output during resistance exercise, with the 3.1% (90% CI 4.3, 2.0%) almost certain additional gain in power after HMW-LMW ingestion attributed to higher movement velocity after force kinematic analysis (HMW-LMW 2.5%, 90%CI 1.4, 3.7%). Both carbohydrate solutions increased post-exercise plasma glucose, glucoregulatory and gut hormones compared to PLA, but differences between carbohydrates were unclear; thus, the underlying mechanism remains to be elucidated. Ingestion of a HMW carbohydrate following prolonged intense endurance exercise provides superior benefits to movement velocity and power output during subsequent repeated maximal explosive resistance exercise. This study was registered with

Palm kernel cake obtained from biodiesel production in diets for goats: feeding behavior and physiological parameters.

PubMed

de Oliveira, R L; de Carvalho, G G P; Oliveira, R L; Tosto, M S L; Santos, E M; Ribeiro, R D X; Silva, T M; Correia, B R; de Rufino, L M A

2017-10-01

The objective of this study was to evaluate the effects of the inclusion of palm kernel (Elaeis guineensis) cake in diets for goats on feeding behaviors, rectal temperature, and cardiac and respiratory frequencies. Forty crossbred Boer male, non-castrated goats (ten animals per treatment), with an average age of 90 days and an initial body weight of 15.01 ± 1.76 kg, were used. The goats were fed Tifton 85 (Cynodon spp.) hay and palm kernel supplemented at the rates of 0, 7, 14, and 21% of dry matter (DM). The feeding behaviors (rumination, feeding, and idling times) were observed for three 24-h periods. DM and neutral detergent fiber (NDF) intake values were estimated as the difference between the total DM and NDF contents of the feed offered and the total DM and NDF contents of the orts. There was no effect of palm kernel cake inclusion in goat diets on DM intake (P > 0.05). However, palm kernel cake promoted a linear increase (P < 0.05) in NDF intake and time spent feeding and ruminating (min/day; %; period) and a linear decrease in time spent idling. Palm kernel cakes had no effects (P > 0.05) on the chewing, feeding, and rumination efficiency (DM and NDF) or on physiological variables. The use up to 21% palm kernel cake in the diet of crossbred Boer goats maintained the feeding behaviors and did not change the physiological parameters of goats; therefore, its use is recommended in the diet of these animals.

Kernel-PCA data integration with enhanced interpretability

PubMed Central

2014-01-01

Background Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task. Results We analyze the integration of data from several sources of information using kernel PCA, from the point of view of reducing dimensionality. Moreover, we improve the interpretability of kernel PCA by adding to the plot the representation of the input variables that belong to any dataset. In particular, for each input variable or linear combination of input variables, we can represent the direction of maximum growth locally, which allows us to identify those samples with higher/lower values of the variables analyzed. Conclusions The integration of different datasets and the simultaneous representation of samples and variables together give us a better understanding of biological knowledge. PMID:25032747

Changes in Gait over a 30-min Walking Session in Obese Females.

PubMed

Singh, Bhupinder; Vo, Huy; Francis, Shelby L; Janz, Kathleen F; Yack, H John

2017-03-01

This study assessed the biomechanical gait changes in obese and normal-weight female adult subjects after a commonly recommended 30-min walking session. Hip and knee adduction and extensor moments, which are the primary modulators of frontal and sagittal plane load distribution, were hypothesized to increase in obese females after a 30-min walking period, resulting in more stress across the hip and knee joint. Ten obese (37.7 ± 4.8 yr of age, body mass index [BMI] = 36.1 ± 4.2 kg·m) and 10 normal-weight control female subjects (38.1 ± 4.5 yr of age, BMI = 22.6 ± 2.3 kg·m) walked 30 min continuously on the treadmill at their self-selected speed. V˙O2max was estimated using Ebbeling protocol. A three-dimensional pre- and posttreadmill gait analysis was conducted using infrared markers and force plates to calculate hip and knee moments. Knee extensor moments increased in both obese, pretreadmill (0.54 ± 0.28 N·m·kg) to posttreadmill (0.78 ± 0.43 N·m·kg) (P = 0.01), and control subjects, pretreadmill (0.57 ± 0.34 N·m·kg) to posttreadmill (0.80 ± 0.49 N·m·kg) (P = 0.02). Hip extensor moments decreased for both obese and control subjects. Knee adduction moments did not change in either obese or control subjects. Knee extensor and adductor moments showed good to moderate relationships with V˙O2max, but not BMI or waist circumference. Obese and normal-weight subjects experienced an increase in knee extensor moments after 30 min of walking similarly; therefore, clinicians do not need special consideration for obese individuals when recommending 30-min walking sessions. Fitness may be the important factor in judging the implications of exercise on joint mechanics and parameters of a walking program.

Gaussian mass optimization for kernel PCA parameters

NASA Astrophysics Data System (ADS)

Liu, Yong; Wang, Zulin

2011-10-01

This paper proposes a novel kernel parameter optimization method based on Gaussian mass, which aims to overcome the current brute force parameter optimization method in a heuristic way. Generally speaking, the choice of kernel parameter should be tightly related to the target objects while the variance between the samples, the most commonly used kernel parameter, doesn't possess much features of the target, which gives birth to Gaussian mass. Gaussian mass defined in this paper has the property of the invariance of rotation and translation and is capable of depicting the edge, topology and shape information. Simulation results show that Gaussian mass leads a promising heuristic optimization boost up for kernel method. In MNIST handwriting database, the recognition rate improves by 1.6% compared with common kernel method without Gaussian mass optimization. Several promising other directions which Gaussian mass might help are also proposed at the end of the paper.

Reliability and Validity of the International Physical Activity Questionnaire for Assessing Walking

ERIC Educational Resources Information Center

van der Ploeg, Hidde P.; Tudor-Locke, Catrine; Marshall, Alison L.; Craig, Cora; Hagstromer, Maria; Sjostrom, Michael; Bauman, Adrian

2010-01-01

The single most commonly reported physical activity in public health surveys is walking. As evidence accumulates that walking is important for preventing weight gain and reducing the risk of diabetes, there is increased need to capture this behavior in a valid and reliable manner. Although the disadvantages of a self-report methodology are well…

Design of CT reconstruction kernel specifically for clinical lung imaging

NASA Astrophysics Data System (ADS)

Cody, Dianna D.; Hsieh, Jiang; Gladish, Gregory W.

2005-04-01

In this study we developed a new reconstruction kernel specifically for chest CT imaging. An experimental flat-panel CT scanner was used on large dogs to produce 'ground-truth" reference chest CT images. These dogs were also examined using a clinical 16-slice CT scanner. We concluded from the dog images acquired on the clinical scanner that the loss of subtle lung structures was due mostly to the presence of the background noise texture when using currently available reconstruction kernels. This qualitative evaluation of the dog CT images prompted the design of a new recon kernel. This new kernel consisted of the combination of a low-pass and a high-pass kernel to produce a new reconstruction kernel, called the 'Hybrid" kernel. The performance of this Hybrid kernel fell between the two kernels on which it was based, as expected. This Hybrid kernel was also applied to a set of 50 patient data sets; the analysis of these clinical images is underway. We are hopeful that this Hybrid kernel will produce clinical images with an acceptable tradeoff of lung detail, reliable HU, and image noise.

Quantum kernel applications in medicinal chemistry.

PubMed

Huang, Lulu; Massa, Lou

2012-07-01

Progress in the quantum mechanics of biological molecules is being driven by computational advances. The notion of quantum kernels can be introduced to simplify the formalism of quantum mechanics, making it especially suitable for parallel computation of very large biological molecules. The essential idea is to mathematically break large biological molecules into smaller kernels that are calculationally tractable, and then to represent the full molecule by a summation over the kernels. The accuracy of the kernel energy method (KEM) is shown by systematic application to a great variety of molecular types found in biology. These include peptides, proteins, DNA and RNA. Examples are given that explore the KEM across a variety of chemical models, and to the outer limits of energy accuracy and molecular size. KEM represents an advance in quantum biology applicable to problems in medicine and drug design.

Impact of ballistic body armour and load carriage on walking patterns and perceived comfort.

PubMed

Park, Huiju; Branson, Donna; Petrova, Adriana; Peksoz, Semra; Jacobson, Bert; Warren, Aric; Goad, Carla; Kamenidis, Panagiotis

2013-01-01

This study investigated the impact of weight magnitude and distribution of body armour and carrying loads on military personnel's walking patterns and comfort perceptions. Spatio-temporal parameters of walking, plantar pressure and contact area were measured while seven healthy male right-handed military students wore seven different garments of varying weight (0.06, 9, 18 and 27 kg) and load distribution (balanced and unbalanced, on the front and back torso). Higher weight increased the foot contact time with the floor. In particular, weight placement on the non-dominant side of the front torso resulted in the greatest stance phase and double support. Increased plantar pressure and contact area observed during heavier loads entail increased impact forces, which can cause overuse injuries and foot blisters. Participants reported increasingly disagreeable pressure and strain in the shoulder, neck and lower back during heavier weight conditions and unnatural walking while wearing unbalanced weight distributed loads. This study shows the potentially synergistic impact of wearing body armour vest with differential loads on body movement and comfort perception. This study found that soldiers should balance loads, avoiding load placement on the non-dominant side front torso, thus minimising mobility restriction and potential injury risk. Implications for armour vest design modifications can also be found in the results.

Uphill walking: Biomechanical demand on the lower extremities of obese adolescents.

PubMed

Strutzenberger, Gerda; Alexander, Nathalie; Bamboschek, Dominik; Claas, Elisabeth; Langhof, Helmut; Schwameder, Hermann

2017-05-01

The number of obesity prevalence in adolescents is still increasing. Obesity treatment programs typically include physical activity with walking being recommended as appropriate activity, but limited information exists on the demand uphill walking places on the joint loading and power of obese adolescents. Therefore, the purpose of this study was to investigate the effect of different inclinations on step characteristics, sagittal and frontal joint angles, joint moments and joint power of obese adolescents in comparison to their normal-weight peers. Eleven obese (14.5±1.41 years, BMI: 31.1±3.5kg/m 2 ) and eleven normal-weight adolescents (14.3±1.86 years, BMI: 19.0±1.7kg/m 2 ) walked with 1.11m/s on a ramp with two imbedded force plates (AMTI, 1000Hz) at three inclinations (level, 6°, 12°). Kinematic data were collected via an infrared-camera motion system (Vicon, 250Hz). The two-way (inclination, group) ANOVA indicated a significant effect of inclination on almost all variables analysed, with the hip joint being the most affected by inclination, followed by the knee and ankle joint. The obese participants additionally spent less time in swing phase, walked with an increased knee flexion and valgus angle and an increased peak hip flexion and adduction moment. Hip joint power of obese adolescents was especially in the steepest inclination significantly increased compared to their normal-weight peers. Obese adolescents demonstrate increased joint loading compared to their normal-weight peers and in combination with a musculoskeletal malalignment they might be prone to an increased overuse injury risk. Copyright © 2017 Elsevier B.V. All rights reserved.

Generating electricity while walking with loads.

PubMed

Rome, Lawrence C; Flynn, Louis; Goldman, Evan M; Yoo, Taeseung D

2005-09-09

We have developed the suspended-load backpack, which converts mechanical energy from the vertical movement of carried loads (weighing 20 to 38 kilograms) to electricity during normal walking [generating up to 7.4 watts, or a 300-fold increase over previous shoe devices (20 milliwatts)]. Unexpectedly, little extra metabolic energy (as compared to that expended carrying a rigid backpack) is required during electricity generation. This is probably due to a compensatory change in gait or loading regime, which reduces the metabolic power required for walking. This electricity generation can help give field scientists, explorers, and disaster-relief workers freedom from the heavy weight of replacement batteries and thereby extend their ability to operate in remote areas.

An Efficient Method Coupling Kernel Principal Component Analysis with Adjoint-Based Optimal Control and Its Goal-Oriented Extensions

NASA Astrophysics Data System (ADS)

Thimmisetty, C.; Talbot, C.; Tong, C. H.; Chen, X.

2016-12-01

The representativeness of available data poses a significant fundamental challenge to the quantification of uncertainty in geophysical systems. Furthermore, the successful application of machine learning methods to geophysical problems involving data assimilation is inherently constrained by the extent to which obtainable data represent the problem considered. We show how the adjoint method, coupled with optimization based on methods of machine learning, can facilitate the minimization of an objective function defined on a space of significantly reduced dimension. By considering uncertain parameters as constituting a stochastic process, the Karhunen-Loeve expansion and its nonlinear extensions furnish an optimal basis with respect to which optimization using L-BFGS can be carried out. In particular, we demonstrate that kernel PCA can be coupled with adjoint-based optimal control methods to successfully determine the distribution of material parameter values for problems in the context of channelized deformable media governed by the equations of linear elasticity. Since certain subsets of the original data are characterized by different features, the convergence rate of the method in part depends on, and may be limited by, the observations used to furnish the kernel principal component basis. By determining appropriate weights for realizations of the stochastic random field, then, one may accelerate the convergence of the method. To this end, we present a formulation of Weighted PCA combined with a gradient-based means using automatic differentiation to iteratively re-weight observations concurrent with the determination of an optimal reduced set control variables in the feature space. We demonstrate how improvements in the accuracy and computational efficiency of the weighted linear method can be achieved over existing unweighted kernel methods, and discuss nonlinear extensions of the algorithm.

Generalization Performance of Regularized Ranking With Multiscale Kernels.

PubMed

Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

2016-05-01

The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

Multineuron spike train analysis with R-convolution linear combination kernel.

PubMed

Tezuka, Taro

2018-06-01

A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neurons. However, most of these multineuron extensions were carried out in a kernel-specific manner. In this paper, a general framework is proposed for extending any single-neuron spike train kernel to multineuron spike trains, based on the R-convolution kernel. Special subclasses of the proposed R-convolution linear combination kernel are explored. These subclasses have a smaller number of parameters and make optimization tractable when the size of data is limited. The proposed kernel was evaluated using Gaussian process regression for multineuron spike trains recorded from an animal brain. It was compared with the sum kernel and the population Spikernel, which are existing ways of decoding multineuron spike trains using kernels. The results showed that the proposed approach performs better than these kernels and also other commonly used neural decoding methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Kinematics of walking in the hermit crab, Pagurus pollicarus.

PubMed

Chapple, William

2012-03-01

Hermit crabs are decapod crustaceans that have adapted to life in gastropod shells. Among their adaptations are modifications to their thoracic appendages or pereopods. The 4th and 5th pairs are adapted for shell support; walking is performed with the 2nd and 3rd pereopods, with an alternation of diagonal pairs. During stance, the walking legs are rotated backwards in the pitch plane. Two patterns of walking were studied to compare them with walking patterns described for other decapods, a lateral gait, similar to that in many brachyurans, and a forward gait resembling macruran walking. Video sequences of free walking and restrained animals were used to obtain leg segment positions from which joint angles were calculated. Leading legs in a lateral walk generated a power stroke by flexion of MC and PD joints; CB angles often did not change during slow walks. Trailing legs exhibited extension of MC and PD with a slight levation of CB. The two joints, B/IM and CP, are aligned at 90° angles to CB, MC and PD, moving dorso-anteriorly during swing and ventro-posteriorly during stance. A forward step was more complex; during swing the leg was rotated forward (yaw) and vertically (pitch), due to the action of TC. At the beginning of stance, TC started to rotate posteriorly and laterally, CB was depressed, and MC flexed. As stance progressed and the leg was directed laterally, PD and MC extended, so that at the end of stance the dactyl tip was quite posterior. During walks of the animal out of its shell, the legs were extended more anterior-laterally and the animal often toppled over, indicating that during walking in a shell its weight stabilized the animal. An open chain kinematic model in which each segment was approximated as a rectangular solid, the dimensions of which were derived from measurements on animals, was developed to estimate the CM of the animal under different load conditions. CM was normally quite anterior; removal of the chelipeds shifted it caudally

Quantum Walk Schemes for Universal Quantum Computation

NASA Astrophysics Data System (ADS)

Underwood, Michael S.

. The many-particle quantum walk can be viewed as a single quantum walk undergoing perfect state transfer on a larger weighted graph, obtained via equitable partitioning. I extend this formalism to non-simple graphs. Examples of the application of equitable partitioning to the analysis of quantum walks and many-particle quantum systems are discussed.

Evaluation of Biosynthesis, Accumulation and Antioxidant Activityof Vitamin E in Sweet Corn (Zea mays L.) during Kernel Development

PubMed Central

Xie, Lihua; Yu, Yongtao; Mao, Jihua; Liu, Haiying; Hu, Jian Guang; Li, Tong; Guo, Xinbo; Liu, Rui Hai

2017-01-01

Sweet corn kernels were used in this research to study the dynamics of vitamin E, by evaluatingthe expression levels of genes involved in vitamin E synthesis, the accumulation of vitamin E, and the antioxidant activity during the different stage of kernel development. Results showed that expression levels of ZmHPT and ZmTC genes increased, whereas ZmTMT gene dramatically decreased during kernel development. The contents of all the types of vitamin E in sweet corn had a significant upward increase during kernel development, and reached the highest level at 30 days after pollination (DAP). Amongst the eight isomers of vitamin E, the content of γ-tocotrienol was the highest, and increased by 14.9 folds, followed by α-tocopherolwith an increase of 22 folds, and thecontents of isomers γ-tocopherol, α-tocotrienol, δ-tocopherol,δ-tocotrienol, and β-tocopherol were also followed during kernel development. The antioxidant activity of sweet corn during kernel development was increased, and was up to 101.8 ± 22.3 μmol of α-tocopherol equivlent/100 g in fresh weight (FW) at 30 DAP. There was a positive correlation between vitamin E contents and antioxidant activity in sweet corn during the kernel development, and a negative correlation between the expressions of ZmTMT gene and vitamin E contents. These results revealed the relations amongst the content of vitamin E isomers and the gene expression, vitamin E accumulation, and antioxidant activity. The study can provide a harvesting strategy for vitamin E bio-fortification in sweet corn. PMID:29261149

Evaluation of Biosynthesis, Accumulation and Antioxidant Activityof Vitamin E in Sweet Corn (Zea mays L.) during Kernel Development.

PubMed

Xie, Lihua; Yu, Yongtao; Mao, Jihua; Liu, Haiying; Hu, Jian Guang; Li, Tong; Guo, Xinbo; Liu, Rui Hai

2017-12-20

Sweet corn kernels were used in this research to study the dynamics of vitamin E, by evaluatingthe expression levels of genes involved in vitamin E synthesis, the accumulation of vitamin E, and the antioxidant activity during the different stage of kernel development. Results showed that expression levels of Zm HPT and Zm TC genes increased, whereas Zm TMT gene dramatically decreased during kernel development. The contents of all the types of vitamin E in sweet corn had a significant upward increase during kernel development, and reached the highest level at 30 days after pollination (DAP). Amongst the eight isomers of vitamin E, the content of γ-tocotrienol was the highest, and increased by 14.9 folds, followed by α-tocopherolwith an increase of 22 folds, and thecontents of isomers γ-tocopherol, α-tocotrienol, δ-tocopherol,δ-tocotrienol, and β-tocopherol were also followed during kernel development. The antioxidant activity of sweet corn during kernel development was increased, and was up to 101.8 ± 22.3 μmol of α-tocopherol equivlent/100 g in fresh weight (FW) at 30 DAP. There was a positive correlation between vitamin E contents and antioxidant activity in sweet corn during the kernel development, and a negative correlation between the expressions of Zm TMT gene and vitamin E contents. These results revealed the relations amongst the content of vitamin E isomers and the gene expression, vitamin E accumulation, and antioxidant activity. The study can provide a harvesting strategy for vitamin E bio-fortification in sweet corn.

Putting Priors in Mixture Density Mercer Kernels

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

2004-01-01

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains template for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic- algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

Increasing accuracy of dispersal kernels in grid-based population models

USGS Publications Warehouse

Slone, D.H.

2011-01-01

Dispersal kernels in grid-based population models specify the proportion, distance and direction of movements within the model landscape. Spatial errors in dispersal kernels can have large compounding effects on model accuracy. Circular Gaussian and Laplacian dispersal kernels at a range of spatial resolutions were investigated, and methods for minimizing errors caused by the discretizing process were explored. Kernels of progressively smaller sizes relative to the landscape grid size were calculated using cell-integration and cell-center methods. These kernels were convolved repeatedly, and the final distribution was compared with a reference analytical solution. For large Gaussian kernels (σ > 10 cells), the total kernel error was <10 &sup-11; compared to analytical results. Using an invasion model that tracked the time a population took to reach a defined goal, the discrete model results were comparable to the analytical reference. With Gaussian kernels that had σ ≤ 0.12 using the cell integration method, or σ ≤ 0.22 using the cell center method, the kernel error was greater than 10%, which resulted in invasion times that were orders of magnitude different than theoretical results. A goal-seeking routine was developed to adjust the kernels to minimize overall error. With this, corrections for small kernels were found that decreased overall kernel error to <10-11 and invasion time error to <5%.

The Effects of Walking Speed on Tibiofemoral Loading Estimated Via Musculoskeletal Modeling

PubMed Central

Lerner, Zachary F.; Haight, Derek J.; DeMers, Matthew S.; Board, Wayne J.; Browning, Raymond C.

2015-01-01

Net muscle moments (NMMs) have been used as proxy measures of joint loading, but musculoskeletal models can estimate contact forces within joints. The purpose of this study was to use a musculoskeletal model to estimate tibiofemoral forces and to examine the relationship between NMMs and tibiofemoral forces across walking speeds. We collected kinematic, kinetic, and electromyographic data as ten adult participants walked on a dual-belt force-measuring treadmill at 0.75, 1.25, and 1.50 m/s. We scaled a musculoskeletal model to each participant and used OpenSim to calculate the NMMs and muscle forces through inverse dynamics and weighted static optimization, respectively. We determined tibiofemoral forces from the vector sum of intersegmental and muscle forces crossing the knee. Estimated tibiofemoral forces increased with walking speed. Peak early-stance compressive tibiofemoral forces increased 52% as walking speed increased from 0.75 to 1.50 m/s, whereas peak knee extension NMMs increased by 168%. During late stance, peak compressive tibiofemoral forces increased by 18% as speed increased. Although compressive loads at the knee did not increase in direct proportion to NMMs, faster walking resulted in greater compressive forces during weight acceptance and increased compressive and anterior/posterior tibiofemoral loading rates in addition to a greater abduction NMM. PMID:23878264

Modulation of weight off-loading level over body-weight supported locomotion training.

PubMed

Wang, Ping; Low, K H; Lim, Peter A C; McGregor, A H

2011-01-01

With the evolution of robotic systems to facilitate overground walking rehabilitation, it is important to understand the effect of robotic-aided body-weight supported loading on lower limb muscle activity, if we are to optimize neuromotor recovery. To achieve this objective, we have collected and studied electromyography (EMG) data from key muscles in the lower extremity from healthy subjects walking over a wide range of body-weight off-loading levels as provided by a bespoke gait robot. By examining the impact of body-weight off-loading, it was found that muscle activation patterns were sensitive to the level of off-loading. In addition, a large off-loading might introduce disturbance of muscle activation pattern, led to a wider range of motion in terms of dorsiflexion/plantarflexion. Therefore, any future overground training machine should be enhanced to exclude unnecessary effect of body off-loading in securing the sustaining upright posture and providing assist-as-needed BWS over gait rehabilitation. © 2011 IEEE

Decomposition of the polynomial kernel of arbitrary higher spin Dirac operators

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

Eelbode, D., E-mail: David.Eelbode@ua.ac.be; Raeymaekers, T., E-mail: Tim.Raeymaekers@UGent.be; Van der Jeugt, J., E-mail: Joris.VanderJeugt@UGent.be

2015-10-15

In a series of recent papers, we have introduced higher spin Dirac operators, which are generalisations of the classical Dirac operator. Whereas the latter acts on spinor-valued functions, the former acts on functions taking values in arbitrary irreducible half-integer highest weight representations for the spin group. In this paper, we describe how the polynomial kernel spaces of such operators decompose in irreducible representations of the spin group. We will hereby make use of results from representation theory.

Agile Walking Robot

NASA Technical Reports Server (NTRS)

Larimer, Stanley J.; Lisec, Thomas R.; Spiessbach, Andrew J.; Waldron, Kenneth J.

1990-01-01

Proposed agile walking robot operates over rocky, sandy, and sloping terrain. Offers stability and climbing ability superior to other conceptual mobile robots. Equipped with six articulated legs like those of insect, continually feels ground under leg before applying weight to it. If leg sensed unexpected object or failed to make contact with ground at expected point, seeks alternative position within radius of 20 cm. Failing that, robot halts, examines area around foot in detail with laser ranging imager, and replans entire cycle of steps for all legs before proceeding.

An SVM model with hybrid kernels for hydrological time series

NASA Astrophysics Data System (ADS)

Wang, C.; Wang, H.; Zhao, X.; Xie, Q.

2017-12-01

Support Vector Machine (SVM) models have been widely applied to the forecast of climate/weather and its impact on other environmental variables such as hydrologic response to climate/weather. When using SVM, the choice of the kernel function plays the key role. Conventional SVM models mostly use one single type of kernel function, e.g., radial basis kernel function. Provided that there are several featured kernel functions available, each having its own advantages and drawbacks, a combination of these kernel functions may give more flexibility and robustness to SVM approach, making it suitable for a wide range of application scenarios. This paper presents such a linear combination of radial basis kernel and polynomial kernel for the forecast of monthly flowrate in two gaging stations using SVM approach. The results indicate significant improvement in the accuracy of predicted series compared to the approach with either individual kernel function, thus demonstrating the feasibility and advantages of such hybrid kernel approach for SVM applications.

Graph wavelet alignment kernels for drug virtual screening.

PubMed

Smalter, Aaron; Huan, Jun; Lushington, Gerald

2009-06-01

In this paper, we introduce a novel statistical modeling technique for target property prediction, with applications to virtual screening and drug design. In our method, we use graphs to model chemical structures and apply a wavelet analysis of graphs to summarize features capturing graph local topology. We design a novel graph kernel function to utilize the topology features to build predictive models for chemicals via Support Vector Machine classifier. We call the new graph kernel a graph wavelet-alignment kernel. We have evaluated the efficacy of the wavelet-alignment kernel using a set of chemical structure-activity prediction benchmarks. Our results indicate that the use of the kernel function yields performance profiles comparable to, and sometimes exceeding that of the existing state-of-the-art chemical classification approaches. In addition, our results also show that the use of wavelet functions significantly decreases the computational costs for graph kernel computation with more than ten fold speedup.

Small convolution kernels for high-fidelity image restoration

NASA Technical Reports Server (NTRS)

Reichenbach, Stephen E.; Park, Stephen K.

1991-01-01

An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.

Reduced multiple empirical kernel learning machine.

PubMed

Wang, Zhe; Lu, MingZhe; Gao, Daqi

2015-02-01

Multiple kernel learning (MKL) is demonstrated to be flexible and effective in depicting heterogeneous data sources since MKL can introduce multiple kernels rather than a single fixed kernel into applications. However, MKL would get a high time and space complexity in contrast to single kernel learning, which is not expected in real-world applications. Meanwhile, it is known that the kernel mapping ways of MKL generally have two forms including implicit kernel mapping and empirical kernel mapping (EKM), where the latter is less attracted. In this paper, we focus on the MKL with the EKM, and propose a reduced multiple empirical kernel learning machine named RMEKLM for short. To the best of our knowledge, it is the first to reduce both time and space complexity of the MKL with EKM. Different from the existing MKL, the proposed RMEKLM adopts the Gauss Elimination technique to extract a set of feature vectors, which is validated that doing so does not lose much information of the original feature space. Then RMEKLM adopts the extracted feature vectors to span a reduced orthonormal subspace of the feature space, which is visualized in terms of the geometry structure. It can be demonstrated that the spanned subspace is isomorphic to the original feature space, which means that the dot product of two vectors in the original feature space is equal to that of the two corresponding vectors in the generated orthonormal subspace. More importantly, the proposed RMEKLM brings a simpler computation and meanwhile needs a less storage space, especially in the processing of testing. Finally, the experimental results show that RMEKLM owns a much efficient and effective performance in terms of both complexity and classification. The contributions of this paper can be given as follows: (1) by mapping the input space into an orthonormal subspace, the geometry of the generated subspace is visualized; (2) this paper first reduces both the time and space complexity of the EKM-based MKL; (3

Fire-Walking

ERIC Educational Resources Information Center

Willey, David

2010-01-01

This article gives a brief history of fire-walking and then deals with the physics behind fire-walking. The author has performed approximately 50 fire-walks, took the data for the world's hottest fire-walk and was, at one time, a world record holder for the longest fire-walk (www.dwilley.com/HDATLTW/Record_Making_Firewalks.html). He currently…

Enhanced gluten properties in soft kernel durum wheat

USDA-ARS?s Scientific Manuscript database

Soft kernel durum wheat is a relatively recent development (Morris et al. 2011 Crop Sci. 51:114). The soft kernel trait exerts profound effects on kernel texture, flour milling including break flour yield, milling energy, and starch damage, and dough water absorption (DWA). With the caveat of reduce...

First Person Perspective of Seated Participants Over a Walking Virtual Body Leads to Illusory Agency Over the Walking.

PubMed

Kokkinara, Elena; Kilteni, Konstantina; Blom, Kristopher J; Slater, Mel

2016-07-01

Agency, the attribution of authorship to an action of our body, requires the intention to carry out the action, and subsequently a match between its predicted and actual sensory consequences. However, illusory agency can be generated through priming of the action together with perception of bodily action, even when there has been no actual corresponding action. Here we show that participants can have the illusion of agency over the walking of a virtual body even though in reality they are seated and only allowed head movements. The experiment (n = 28) had two factors: Perspective (1PP or 3PP) and Head Sway (Sway or NoSway). Participants in 1PP saw a life-sized virtual body spatially coincident with their own from a first person perspective, or the virtual body from third person perspective (3PP). In the Sway condition the viewpoint included a walking animation, but not in NoSway. The results show strong illusions of body ownership, agency and walking, in the 1PP compared to the 3PP condition, and an enhanced level of arousal while the walking was up a virtual hill. Sway reduced the level of agency. We conclude with a discussion of the results in the light of current theories of agency.

Accelerating the Original Profile Kernel.

PubMed

Hamp, Tobias; Goldberg, Tatyana; Rost, Burkhard

2013-01-01

One of the most accurate multi-class protein classification systems continues to be the profile-based SVM kernel introduced by the Leslie group. Unfortunately, its CPU requirements render it too slow for practical applications of large-scale classification tasks. Here, we introduce several software improvements that enable significant acceleration. Using various non-redundant data sets, we demonstrate that our new implementation reaches a maximal speed-up as high as 14-fold for calculating the same kernel matrix. Some predictions are over 200 times faster and render the kernel as possibly the top contender in a low ratio of speed/performance. Additionally, we explain how to parallelize various computations and provide an integrative program that reduces creating a production-quality classifier to a single program call. The new implementation is available as a Debian package under a free academic license and does not depend on commercial software. For non-Debian based distributions, the source package ships with a traditional Makefile-based installer. Download and installation instructions can be found at https://rostlab.org/owiki/index.php/Fast_Profile_Kernel. Bugs and other issues may be reported at https://rostlab.org/bugzilla3/enter_bug.cgi?product=fastprofkernel.

Common spatial pattern combined with kernel linear discriminate and generalized radial basis function for motor imagery-based brain computer interface applications

NASA Astrophysics Data System (ADS)

Hekmatmanesh, Amin; Jamaloo, Fatemeh; Wu, Huapeng; Handroos, Heikki; Kilpeläinen, Asko

2018-04-01

Brain Computer Interface (BCI) can be a challenge for developing of robotic, prosthesis and human-controlled systems. This work focuses on the implementation of a common spatial pattern (CSP) base algorithm to detect event related desynchronization patterns. Utilizing famous previous work in this area, features are extracted by filter bank with common spatial pattern (FBCSP) method, and then weighted by a sensitive learning vector quantization (SLVQ) algorithm. In the current work, application of the radial basis function (RBF) as a mapping kernel of linear discriminant analysis (KLDA) method on the weighted features, allows the transfer of data into a higher dimension for more discriminated data scattering by RBF kernel. Afterwards, support vector machine (SVM) with generalized radial basis function (GRBF) kernel is employed to improve the efficiency and robustness of the classification. Averagely, 89.60% accuracy and 74.19% robustness are achieved. BCI Competition III, Iva data set is used to evaluate the algorithm for detecting right hand and foot imagery movement patterns. Results show that combination of KLDA with SVM-GRBF classifier makes 8.9% and 14.19% improvements in accuracy and robustness, respectively. For all the subjects, it is concluded that mapping the CSP features into a higher dimension by RBF and utilization GRBF as a kernel of SVM, improve the accuracy and reliability of the proposed method.

21 CFR 176.350 - Tamarind seed kernel powder.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 3 2014-04-01 2014-04-01 false Tamarind seed kernel powder. 176.350 Section 176... Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing, manufacturing, packing, processing, preparing, treating...

End-use quality of soft kernel durum wheat

USDA-ARS?s Scientific Manuscript database

Kernel texture is a major determinant of end-use quality of wheat. Durum wheat has very hard kernels. We developed soft kernel durum wheat via Ph1b-mediated homoeologous recombination. The Hardness locus was transferred from Chinese Spring to Svevo durum wheat via back-crossing. ‘Soft Svevo’ had SKC...

Dietary fiber and subsequent changes in body weight and waist circumference in European men and women.

PubMed

Du, Huaidong; van der A, Daphne L; Boshuizen, Hendriek C; Forouhi, Nita G; Wareham, Nicolas J; Halkjaer, Jytte; Tjønneland, Anne; Overvad, Kim; Jakobsen, Marianne Uhre; Boeing, Heiner; Buijsse, Brian; Masala, Giovanna; Palli, Dominique; Sørensen, Thorkild I A; Saris, Wim H M; Feskens, Edith J M

2010-02-01

Dietary fiber may play a role in obesity prevention. Until now, the role that fiber from different sources plays in weight change had rarely been studied. Our aim was to investigate the association of total dietary fiber, cereal fiber, and fruit and vegetable fiber with changes in weight and waist circumference. We conducted a prospective cohort study with 89,432 European participants, aged 20-78 y, who were free of cancer, cardiovascular disease, and diabetes at baseline and who were followed for an average of 6.5 y. Dietary information was collected by using validated country-specific food-frequency questionnaires. Multiple linear regression analysis was performed in each center studied, and estimates were combined by using random-effects meta-analyses. Adjustments were made for follow-up duration, other dietary variables, and baseline anthropometric, demographic, and lifestyle factors. Total fiber was inversely associated with subsequent weight and waist circumference change. For a 10-g/d higher total fiber intake, the pooled estimate was -39 g/y (95% CI: -71, -7 g/y) for weight change and -0.08 cm/y (95% CI: -0.11, -0.05 cm/y) for waist circumference change. A 10-g/d higher fiber intake from cereals was associated with -77 g/y (95% CI: -127, -26 g/y) weight change and -0.10 cm/y (95% CI: -0.18, -0.02 cm/y) waist circumference change. Fruit and vegetable fiber was not associated with weight change but had a similar association with waist circumference change when compared with intake of total dietary fiber and cereal fiber. Our finding may support a beneficial role of higher intake of dietary fiber, especially cereal fiber, in prevention of body-weight and waist circumference gain.

Deep Restricted Kernel Machines Using Conjugate Feature Duality.

PubMed

Suykens, Johan A K

2017-08-01

The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.

Triso coating development progress for uranium nitride kernels

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

Jolly, Brian C.; Lindemer, Terrence; Terrani, Kurt A.

2015-08-01

In support of fully ceramic matrix (FCM) fuel development [1-2], coating development work is ongoing at the Oak Ridge National Laboratory (ORNL) to produce tri-structural isotropic (TRISO) coated fuel particles with UN kernels [3]. The nitride kernels are used to increase fissile density in these SiC-matrix fuel pellets with details described elsewhere [4]. The advanced gas reactor (AGR) program at ORNL used fluidized bed chemical vapor deposition (FBCVD) techniques for TRISO coating of UCO (two phase mixture of UO2 and UCx) kernels [5]. Similar techniques were employed for coating of the UN kernels, however significant changes in processing conditions weremore » required to maintain acceptable coating properties due to physical property and dimensional differences between the UCO and UN kernels (Table 1).« less

Rollover footwear affects lower limb biomechanics during walking.

PubMed

Forghany, Saeed; Nester, Christopher J; Richards, Barry; Hatton, Anna Lucy; Liu, Anmin

2014-01-01

To investigate the effect of rollover footwear on walking speed, metabolic cost of gait, lower limb kinematics, kinetics, EMG muscle activity and plantar pressure. Twenty subjects (mean age-33.1 years, height-1.71 m, body mass-68.9 kg, BMI 23.6, 12 male) walked in: a flat control footwear; a flat control footwear weighted to match the mass of a rollover shoe; a rollover shoe; MBT footwear. Data relating to metabolic energy and temporal aspects of gait were collected during 6 min of continuous walking, all other data in a gait laboratory. The rollover footwear moved the contact point under the shoe anteriorly during early stance, increasing midfoot pressures. This changed internal ankle dorsiflexion moments to plantarflexion moments earlier, reducing ankle plantarflexion and tibialis anterior activity after initial contact, and increasing calf EMG activity. In mid stance the rollover footwear resulted in a more dorsiflexed ankle position but less ankle movement. During propulsion, the rollover footwear reduced peak ankle dorsiflexion, peak internal plantarflexor ankle moments and the range of ankle plantarflexion. Vertical ground reaction loading rates were increased by the rollover footwear. There were no effects on temporal or energy cost of gait and no effect of elevated shoe weight. Investigating all proposed effects of this footwear concurrently has enabled a more valid investigation of how the footwear effects are interrelated. There were concurrent changes in several aspects of lower limb function, with greatest effects at the foot and ankle, but no change in the metabolic cost of walking. Copyright © 2013 Elsevier B.V. All rights reserved.

21 CFR 176.350 - Tamarind seed kernel powder.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 3 2011-04-01 2011-04-01 false Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing...

21 CFR 176.350 - Tamarind seed kernel powder.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 3 2012-04-01 2012-04-01 false Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing...

21 CFR 176.350 - Tamarind seed kernel powder.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 3 2010-04-01 2009-04-01 true Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing...

21 CFR 176.350 - Tamarind seed kernel powder.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 3 2013-04-01 2013-04-01 false Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing...

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions

NASA Astrophysics Data System (ADS)

Novosad, Philip; Reader, Andrew J.

2016-06-01

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [18F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions.

PubMed

Novosad, Philip; Reader, Andrew J

2016-06-21

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [(18)F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel

Surface-from-gradients without discrete integrability enforcement: A Gaussian kernel approach.

PubMed

Ng, Heung-Sun; Wu, Tai-Pang; Tang, Chi-Keung

2010-11-01

Representative surface reconstruction algorithms taking a gradient field as input enforce the integrability constraint in a discrete manner. While enforcing integrability allows the subsequent integration to produce surface heights, existing algorithms have one or more of the following disadvantages: They can only handle dense per-pixel gradient fields, smooth out sharp features in a partially integrable field, or produce severe surface distortion in the results. In this paper, we present a method which does not enforce discrete integrability and reconstructs a 3D continuous surface from a gradient or a height field, or a combination of both, which can be dense or sparse. The key to our approach is the use of kernel basis functions, which transfer the continuous surface reconstruction problem into high-dimensional space, where a closed-form solution exists. By using the Gaussian kernel, we can derive a straightforward implementation which is able to produce results better than traditional techniques. In general, an important advantage of our kernel-based method is that the method does not suffer discretization and finite approximation, both of which lead to surface distortion, which is typical of Fourier or wavelet bases widely adopted by previous representative approaches. We perform comparisons with classical and recent methods on benchmark as well as challenging data sets to demonstrate that our method produces accurate surface reconstruction that preserves salient and sharp features. The source code and executable of the system are available for downloading.

A dynamic kernel modifier for linux

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

Minnich, R. G.

2002-09-03

Dynamic Kernel Modifier, or DKM, is a kernel module for Linux that allows user-mode programs to modify the execution of functions in the kernel without recompiling or modifying the kernel source in any way. Functions may be traced, either function entry only or function entry and exit; nullified; or replaced with some other function. For the tracing case, function execution results in the activation of a watchpoint. When the watchpoint is activated, the address of the function is logged in a FIFO buffer that is readable by external applications. The watchpoints are time-stamped with the resolution of the processor highmore » resolution timers, which on most modem processors are accurate to a single processor tick. DKM is very similar to earlier systems such as the SunOS trace device or Linux TT. Unlike these two systems, and other similar systems, DKM requires no kernel modifications. DKM allows users to do initial probing of the kernel to look for performance problems, or even to resolve potential problems by turning functions off or replacing them. DKM watchpoints are not without cost: it takes about 200 nanoseconds to make a log entry on an 800 Mhz Pentium-Ill. The overhead numbers are actually competitive with other hardware-based trace systems, although it has less 'Los Alamos National Laboratory is operated by the University of California for the National Nuclear Security Administration of the United States Department of Energy under contract W-7405-ENG-36. accuracy than an In-Circuit Emulator such as the American Arium. Once the user has zeroed in on a problem, other mechanisms with a higher degree of accuracy can be used.« less

Walk Score(TM), Perceived Neighborhood Walkability, and walking in the US.

PubMed

Tuckel, Peter; Milczarski, William

2015-03-01

To investigate both the Walk Score(TM) and a self-reported measure of neighborhood walkability ("Perceived Neighborhood Walkability") as estimators of transport and recreational walking among Americans. The study is based upon a survey of a nationally-representative sample of 1224 American adults. The survey gauged walking for both transport and recreation and included a self-reported measure of neighborhood walkability and each respondent's Walk Score(TM). Binary logistic and linear regression analyses were performed on the data. The Walk Score(TM) is associated with walking for transport, but not recreational walking nor total walking. Perceived Neighborhood Walkability is associated with transport, recreational and total walking. Perceived Neighborhood Walkability captures the experiential nature of walking more than the Walk Score(TM).

Reference equations for 6-min walk test in healthy Indian subjects (25-80 years).

PubMed

Palaniappan Ramanathan, Ramanathan; Chandrasekaran, Baskaran

2014-01-01

Six-min walk test (6MWT), a simple functional capacity evaluation tool used globally to determine the prognosis and effectiveness of any therapeutic/medical intervention. However, variability in reference equations derived from western population (due to racial and ethnicity variations) hinders from adequate use of 6MWT clinically. Further, there are no valid Indian studies that predict reference values for 6-min walk distance (6MWD) in healthy Indian normal. We aimed for framing individualized reference equations for 6MWT in healthy Indian population. Anthropometric variables (age, weight, height, and body mass index (BMI)) and 6-min walk in a 30 m corridor were evaluated in 125 subjects (67 females) in a cross-sectional trial. 6MWD significantly correlated with age (r = -0.29), height (r = 0.393), weight (r = 0.08), and BMI (r = -0.17). The gender specific reference equations for healthy Indian individuals were: (1) Males: 561.022 - (2.507 × age [years]) + (1.505 × weight [kg]) - (0.055 × height [cm]). R (2) = 0.288. (2) Indian females: 30.325 - (0.809 × age [years]) - (2.074 × weight [kg]) + (4.235 × height [cm]). R (2) = 0.272. Though the equations possess a small coefficient of determination and larger standard error estimate, the former applicability to Indian population is justified. These reference equations are probably most appropriate for evaluating the walked capacity of Indian patients with chronic diseases.

Hadamard Kernel SVM with applications for breast cancer outcome predictions.

PubMed

Jiang, Hao; Ching, Wai-Ki; Cheung, Wai-Shun; Hou, Wenpin; Yin, Hong

2017-12-21

Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Kernel SVM for its discriminative power in dealing with small sample pattern recognition problems has attracted a lot attention. But how to select or construct an appropriate kernel for a specified problem still needs further investigation. Here we propose a novel kernel (Hadamard Kernel) in conjunction with Support Vector Machines (SVMs) to address the problem of breast cancer outcome prediction using gene expression data. Hadamard Kernel outperform the classical kernels and correlation kernel in terms of Area under the ROC Curve (AUC) values where a number of real-world data sets are adopted to test the performance of different methods. Hadamard Kernel SVM is effective for breast cancer predictions, either in terms of prognosis or diagnosis. It may benefit patients by guiding therapeutic options. Apart from that, it would be a valuable addition to the current SVM kernel families. We hope it will contribute to the wider biology and related communities.

Kernel Partial Least Squares for Nonlinear Regression and Discrimination

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Clancy, Daniel (Technical Monitor)

2002-01-01

This paper summarizes recent results on applying the method of partial least squares (PLS) in a reproducing kernel Hilbert space (RKHS). A previously proposed kernel PLS regression model was proven to be competitive with other regularized regression methods in RKHS. The family of nonlinear kernel-based PLS models is extended by considering the kernel PLS method for discrimination. Theoretical and experimental results on a two-class discrimination problem indicate usefulness of the method.

Reaching for the Unreachable: Reorganization of Reaching with Walking

PubMed Central

Grzyb, Beata J.; Smith, Linda B.; del Pobil, Angel P.

2015-01-01

Previous research suggests that reaching and walking behaviors may be linked developmentally as reaching changes at the onset of walking. Here we report new evidence on an apparent loss of the distinction between the reachable and nonreachable distances as children start walking. The experiment compared nonwalkers, walkers with help, and independent walkers in a reaching task to targets at varying distances. Reaching attempts, contact, leaning, and communication behaviors were recorded. Most of the children reached for the unreachable objects the first time it was presented. Nonwalkers, however, reached less on the subsequent trials showing clear adjustment of their reaching decisions with the failures. On the contrary, walkers consistently attempted reaches to targets at unreachable distances. We suggest that these reaching errors may result from inappropriate integration of reaching and locomotor actions, attention control and near/far visual space. We propose a reward-mediated model implemented on a NAO humanoid robot that replicates the main results from our study showing an increase in reaching attempts to nonreachable distances after the onset of walking. PMID:26110046

Associations of Maternal Light/Moderate Leisure-Time Walking and Yoga With Offspring Birth Size.

PubMed

Badon, Sylvia E; Littman, Alyson J; Chan, K C Gary; Williams, Michelle A; Enquobahrie, Daniel A

2018-06-01

Although perinatal walking and yoga have been associated with decreased risks of pregnancy complications, associations with offspring birth size have been inconsistent. We investigated associations of prepregnancy and early pregnancy leisure-time light/moderate walking and yoga practice with birth size. Study participants (N = 3687) reported leisure-time physical activity duration (hours per week) in the year before pregnancy and early pregnancy. Birth size was abstracted from medical records. Regression was used to determine mean differences in birth weight, head circumference, and ponderal index. Interaction terms were used to assess effect modification by offspring sex. About one-third of women reported light/moderate leisure-time walking and about 10% reported yoga practice. Women in the highest tertile for prepregnancy (mean: 2.9 h/wk; range: 1.4-20 h/wk) or early pregnancy (mean: 5.9 h/wk; range: 3.1-24 h/wk) light/moderate walking had offspring with 0.9 and 1.5 kg/m 3 greater ponderal index (95% confidence interval, 0.3 to 1.4 and 0.7 to 2.4, respectively) compared with women who reported no light/moderate walking in the same time period. Light/moderate walking was not associated with birth weight or head circumference. Yoga practice was not associated with birth size. Associations were similar by offspring sex. Light/moderate leisure-time walking may be associated with greater offspring ponderal index.

Anthraquinones isolated from the browned Chinese chestnut kernels (Castanea mollissima blume)

NASA Astrophysics Data System (ADS)

Zhang, Y. L.; Qi, J. H.; Qin, L.; Wang, F.; Pang, M. X.

2016-08-01

Anthraquinones (AQS) represent a group of secondary metallic products in plants. AQS are often naturally occurring in plants and microorganisms. In a previous study, we found that AQS were produced by enzymatic browning reaction in Chinese chestnut kernels. To find out whether non-enzymatic browning reaction in the kernels could produce AQS too, AQS were extracted from three groups of chestnut kernels: fresh kernels, non-enzymatic browned kernels, and browned kernels, and the contents of AQS were determined. High performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR) methods were used to identify two compounds of AQS, rehein(1) and emodin(2). AQS were barely exists in the fresh kernels, while both browned kernel groups sample contained a high amount of AQS. Thus, we comfirmed that AQS could be produced during both enzymatic and non-enzymatic browning process. Rhein and emodin were the main components of AQS in the browned kernels.

Limited Transfer of Newly Acquired Movement Patterns across Walking and Running in Humans

PubMed Central

Ogawa, Tetsuya; Kawashima, Noritaka; Ogata, Toru; Nakazawa, Kimitaka

2012-01-01

The two major modes of locomotion in humans, walking and running, may be regarded as a function of different speed (walking as slower and running as faster). Recent results using motor learning tasks in humans, as well as more direct evidence from animal models, advocate for independence in the neural control mechanisms underlying different locomotion tasks. In the current study, we investigated the possible independence of the neural mechanisms underlying human walking and running. Subjects were tested on a split-belt treadmill and adapted to walking or running on an asymmetrically driven treadmill surface. Despite the acquisition of asymmetrical movement patterns in the respective modes, the emergence of asymmetrical movement patterns in the subsequent trials was evident only within the same modes (walking after learning to walk and running after learning to run) and only partial in the opposite modes (walking after learning to run and running after learning to walk) (thus transferred only limitedly across the modes). Further, the storage of the acquired movement pattern in each mode was maintained independently of the opposite mode. Combined, these results provide indirect evidence for independence in the neural control mechanisms underlying the two locomotive modes. PMID:23029490

Performance Characteristics of a Kernel-Space Packet Capture Module

DTIC Science & Technology

2010-03-01

Defense, or the United States Government . AFIT/GCO/ENG/10-03 PERFORMANCE CHARACTERISTICS OF A KERNEL-SPACE PACKET CAPTURE MODULE THESIS Presented to the...3.1.2.3 Prototype. The proof of concept for this research is the design, development, and comparative performance analysis of a kernel level N2d capture...changes to kernel code 5. Can be used for both user-space and kernel-space capture applications in order to control comparative performance analysis to

Anatomically-Aided PET Reconstruction Using the Kernel Method

PubMed Central

Hutchcroft, Will; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

2016-01-01

This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest (ROI) quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization (EM) algorithm. PMID:27541810

Anatomically-aided PET reconstruction using the kernel method.

PubMed

Hutchcroft, Will; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2016-09-21

This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization algorithm.

Anatomically-aided PET reconstruction using the kernel method

NASA Astrophysics Data System (ADS)

Hutchcroft, Will; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

2016-09-01

This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization algorithm.

Human body area factors for radiation exchange analysis: standing and walking postures

NASA Astrophysics Data System (ADS)

Park, Sookuk; Tuller, Stanton E.

2011-09-01

Effective radiation area factors ( f eff) and projected area factors ( f p) of unclothed Caucasians' standing and walking postures used in estimating human radiation exchange with the surrounding environment were determined from a sample of adults in Canada. Several three-dimensional (3D) computer body models were created for standing and walking postures. Only small differences in f eff and f p values for standing posture were found between gender (male or female) and body type (normal- or over-weight). Differences between this study and previous studies were much larger: ≤0.173 in f p and ≤0.101 in f eff. Directionless f p values for walking posture also had only minor differences between genders and positions in a stride. However, the differences of mean directional f p values of the positions dependent on azimuth angles were large enough, ≤0.072, to create important differences in modeled radiation receipt. Differences in f eff values were small: 0.02 between the normal-weight male and female models and up to 0.033 between positions in a stride. Variations of directional f p values depending on solar altitudes for walking posture were narrower than those for standing posture. When both standing and walking postures are considered, the mean f eff value, 0.836, of standing (0.826) and walking (0.846) could be used. However, f p values should be selected carefully because differences between directional and directionless f p values were large enough that they could influence the estimated level of human thermal sensation.

Metabolic and Circulatory Responses to Walking and Jogging in Water.

ERIC Educational Resources Information Center

Evans, Blanch W.

1978-01-01

Water resistance makes running or walking through waist-deep water more strenuous than when performed under normal conditions; however, the buoyancy of the water reduces the stress on weight-bearing muscles and joints. (MM)

Embedded real-time operating system micro kernel design

NASA Astrophysics Data System (ADS)

Cheng, Xiao-hui; Li, Ming-qiang; Wang, Xin-zheng

2005-12-01

Embedded systems usually require a real-time character. Base on an 8051 microcontroller, an embedded real-time operating system micro kernel is proposed consisting of six parts, including a critical section process, task scheduling, interruption handle, semaphore and message mailbox communication, clock managent and memory managent. Distributed CPU and other resources are among tasks rationally according to the importance and urgency. The design proposed here provides the position, definition, function and principle of micro kernel. The kernel runs on the platform of an ATMEL AT89C51 microcontroller. Simulation results prove that the designed micro kernel is stable and reliable and has quick response while operating in an application system.

Effects of underwater treadmill training on leg strength, balance, and walking performance in adults with incomplete spinal cord injury.

PubMed

Stevens, Sandra L; Caputo, Jennifer L; Fuller, Dana K; Morgan, Don W

2015-01-01

To document the effects of underwater treadmill training (UTT) on leg strength, balance, and walking performance in adults with incomplete spinal cord injury (iSCI). Pre-test and post-test design. Exercise physiology laboratory. Adult volunteers with iSCI (n = 11). Participants completed 8 weeks (3 × /week) of UTT. Each training session consisted of three walks performed at a personalized speed, with adequate rest between walks. Body weight support remained constant for each participant and ranged from 29 to 47% of land body weight. Increases in walking speed and duration were staggered and imposed in a gradual and systematic fashion. Lower-extremity strength (LS), balance (BL), preferred and rapid walking speeds (PWS and RWS), 6-minute walk distance (6MWD), and daily step activity (DSA). Significant (P < 0.05) increases were observed in LS (13.1 ± 3.1 to 20.6 ± 5.1 N·kg(-1)), BL (23 ± 11 to 32 ± 13), PWS (0.41 ± 0.27 to 0.55 ± 0.28 m·s(-1)), RWS (0.44 ± 0.31 to 0.71 ± 0.40 m·s(-1)), 6MWD (97 ± 80 to 177 ± 122 m), and DSA (593 ± 782 to 1310 ± 1258 steps) following UTT. Physical function and walking ability were improved in adults with iSCI following a structured program of UTT featuring individualized levels of body weight support and carefully staged increases in speed and duration. From a clinical perspective, these findings highlight the potential of UTT in persons with physical disabilities and diseases that would benefit from weight-supported exercise.

Kernel Temporal Differences for Neural Decoding

PubMed Central

Bae, Jihye; Sanchez Giraldo, Luis G.; Pohlmeyer, Eric A.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2015-01-01

We study the feasibility and capability of the kernel temporal difference (KTD)(λ) algorithm for neural decoding. KTD(λ) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm's convergence can be guaranteed for policy evaluation. The algorithm's nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement). KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithm seeks a proper mapping between a monkey's neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm's capabilities in reinforcement learning brain machine interfaces. PMID:25866504

A randomized trial of functional electrical stimulation for walking in incomplete spinal cord injury: Effects on walking competency

PubMed Central

Kapadia, Naaz; Masani, Kei; Catharine Craven, B.; Giangregorio, Lora M.; Hitzig, Sander L.; Richards, Kieva; Popovic, Milos R.

2014-01-01

Background Multi-channel surface functional electrical stimulation (FES) for walking has been used to improve voluntary walking and balance in individuals with spinal cord injury (SCI). Objective To investigate short- and long-term benefits of 16 weeks of thrice-weekly FES-assisted walking program, while ambulating on a body weight support treadmill and harness system, versus a non-FES exercise program, on improvements in gait and balance in individuals with chronic incomplete traumatic SCI, in a randomized controlled trial design. Methods Individuals with traumatic and chronic (≥18 months) motor incomplete SCI (level C2 to T12, American Spinal Cord Injury Association Impairment Scale C or D) were recruited from an outpatient SCI rehabilitation hospital, and randomized to FES-assisted walking therapy (intervention group) or aerobic and resistance training program (control group). Outcomes were assessed at baseline, and after 4, 6, and 12 months. Gait, balance, spasticity, and functional measures were collected. Results Spinal cord independence measure (SCIM) mobility sub-score improved over time in the intervention group compared with the control group (baseline/12 months: 17.27/21.33 vs. 19.09/17.36, respectively). On all other outcome measures the intervention and control groups had similar improvements. Irrespective of group allocation walking speed, endurance, and balance during ambulation all improved upon completion of therapy, and majority of participants retained these gains at long-term follow-ups. Conclusions Task-oriented training improves walking ability in individuals with incomplete SCI, even in the chronic stage. Further randomized controlled trials, involving a large number of participants are needed, to verify if FES-assisted treadmill training is superior to aerobic and strength training. PMID:25229735

Online selective kernel-based temporal difference learning.

PubMed

Chen, Xingguo; Gao, Yang; Wang, Ruili

2013-12-01

In this paper, an online selective kernel-based temporal difference (OSKTD) learning algorithm is proposed to deal with large scale and/or continuous reinforcement learning problems. OSKTD includes two online procedures: online sparsification and parameter updating for the selective kernel-based value function. A new sparsification method (i.e., a kernel distance-based online sparsification method) is proposed based on selective ensemble learning, which is computationally less complex compared with other sparsification methods. With the proposed sparsification method, the sparsified dictionary of samples is constructed online by checking if a sample needs to be added to the sparsified dictionary. In addition, based on local validity, a selective kernel-based value function is proposed to select the best samples from the sample dictionary for the selective kernel-based value function approximator. The parameters of the selective kernel-based value function are iteratively updated by using the temporal difference (TD) learning algorithm combined with the gradient descent technique. The complexity of the online sparsification procedure in the OSKTD algorithm is O(n). In addition, two typical experiments (Maze and Mountain Car) are used to compare with both traditional and up-to-date O(n) algorithms (GTD, GTD2, and TDC using the kernel-based value function), and the results demonstrate the effectiveness of our proposed algorithm. In the Maze problem, OSKTD converges to an optimal policy and converges faster than both traditional and up-to-date algorithms. In the Mountain Car problem, OSKTD converges, requires less computation time compared with other sparsification methods, gets a better local optima than the traditional algorithms, and converges much faster than the up-to-date algorithms. In addition, OSKTD can reach a competitive ultimate optima compared with the up-to-date algorithms.

Influence of wheat kernel physical properties on the pulverizing process.

PubMed

Dziki, Dariusz; Cacak-Pietrzak, Grażyna; Miś, Antoni; Jończyk, Krzysztof; Gawlik-Dziki, Urszula

2014-10-01

The physical properties of wheat kernel were determined and related to pulverizing performance by correlation analysis. Nineteen samples of wheat cultivars about similar level of protein content (11.2-12.8 % w.b.) and obtained from organic farming system were used for analysis. The kernel (moisture content 10 % w.b.) was pulverized by using the laboratory hammer mill equipped with round holes 1.0 mm screen. The specific grinding energy ranged from 120 kJkg(-1) to 159 kJkg(-1). On the basis of data obtained many of significant correlations (p < 0.05) were found between wheat kernel physical properties and pulverizing process of wheat kernel, especially wheat kernel hardness index (obtained on the basis of Single Kernel Characterization System) and vitreousness significantly and positively correlated with the grinding energy indices and the mass fraction of coarse particles (> 0.5 mm). Among the kernel mechanical properties determined on the basis of uniaxial compression test only the rapture force was correlated with the impact grinding results. The results showed also positive and significant relationships between kernel ash content and grinding energy requirements. On the basis of wheat physical properties the multiple linear regression was proposed for predicting the average particle size of pulverized kernel.

Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS

NASA Astrophysics Data System (ADS)

Tehrany, Mahyat Shafapour; Pradhan, Biswajeet; Jebur, Mustafa Neamah

2014-05-01

Flood is one of the most devastating natural disasters that occur frequently in Terengganu, Malaysia. Recently, ensemble based techniques are getting extremely popular in flood modeling. In this paper, weights-of-evidence (WoE) model was utilized first, to assess the impact of classes of each conditioning factor on flooding through bivariate statistical analysis (BSA). Then, these factors were reclassified using the acquired weights and entered into the support vector machine (SVM) model to evaluate the correlation between flood occurrence and each conditioning factor. Through this integration, the weak point of WoE can be solved and the performance of the SVM will be enhanced. The spatial database included flood inventory, slope, stream power index (SPI), topographic wetness index (TWI), altitude, curvature, distance from the river, geology, rainfall, land use/cover (LULC), and soil type. Four kernel types of SVM (linear kernel (LN), polynomial kernel (PL), radial basis function kernel (RBF), and sigmoid kernel (SIG)) were used to investigate the performance of each kernel type. The efficiency of the new ensemble WoE and SVM method was tested using area under curve (AUC) which measured the prediction and success rates. The validation results proved the strength and efficiency of the ensemble method over the individual methods. The best results were obtained from RBF kernel when compared with the other kernel types. Success rate and prediction rate for ensemble WoE and RBF-SVM method were 96.48% and 95.67% respectively. The proposed ensemble flood susceptibility mapping method could assist researchers and local governments in flood mitigation strategies.

Kernel-based Linux emulation for Plan 9.

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

Minnich, Ronald G.

2010-09-01

CNKemu is a kernel-based system for the 9k variant of the Plan 9 kernel. It is designed to provide transparent binary support for programs compiled for IBM's Compute Node Kernel (CNK) on the Blue Gene series of supercomputers. This support allows users to build applications with the standard Blue Gene toolchain, including C++ and Fortran compilers. While the CNK is not Linux, IBM designed the CNK so that the user interface has much in common with the Linux 2.0 system call interface. The Plan 9 CNK emulator hence provides the foundation of kernel-based Linux system call support on Plan 9.more » In this paper we discuss cnkemu's implementation and some of its more interesting features, such as the ability to easily intermix Plan 9 and Linux system calls.« less

Functional roles of lower-limb joint moments while walking in water.

PubMed

Miyoshi, Tasuku; Shirota, Takashi; Yamamoto, Shin-Ichiro; Nakazawa, Kimitaka; Akai, Masami

2005-02-01

To clarify the functional roles of lower-limb joint moments and their contribution to support and propulsion tasks while walking in water compared with that on land. Sixteen healthy, young subjects walked on land and in water at several different speeds with and without additional loads. Walking in water is a major rehabilitation therapy for patients with orthopedic disorders. However, the functional role of lower-limb joint moments while walking in water is still unclear. Kinematics, electromyographic activities in biceps femoris and gluteus maximums, and ground reaction forces were measured under the following conditions: walking on land and in water at a self-determined pace, slow walking on land, and fast walking in water with or without additional loads (8 kg). The hip, knee, and ankle joint moments were calculated by inverse dynamics. The contribution of the walking speed increased the hip extension moment, and the additional weight increased the ankle plantar flexion and knee extension moment. The major functional role was different in each lower-limb joint muscle. That of the muscle group in the ankle is to support the body against gravity, and that of the muscle group involved in hip extension is to contribute to propulsion. In addition, walking in water not only reduced the joint moments but also completely changed the inter-joint coordination. It is of value for clinicians to be aware that the greater the viscosity of water produces a greater load on the hip joint when fast walking in water.

Excitability Changes in Intracortical Neural Circuits Induced by Differentially Controlled Walking Patterns

PubMed Central

Ito, Tomotaka; Tsubahara, Akio; Shinkoda, Koichi; Yoshimura, Yosuke; Kobara, Kenichi; Osaka, Hiroshi

2015-01-01

Our previous single-pulse transcranial magnetic stimulation (TMS) study revealed that excitability in the motor cortex can be altered by conscious control of walking relative to less conscious normal walking. However, substantial elements and underlying mechanisms for inducing walking-related cortical plasticity are still unknown. Hence, in this study we aimed to examine the characteristics of electromyographic (EMG) recordings obtained during different walking conditions, namely, symmetrical walking (SW), asymmetrical walking 1 (AW1), and asymmetrical walking 2 (AW2), with left to right stance duration ratios of 1:1, 1:2, and 2:1, respectively. Furthermore, we investigated the influence of three types of walking control on subsequent changes in the intracortical neural circuits. Prior to each type of 7-min walking task, EMG analyses of the left tibialis anterior (TA) and soleus (SOL) muscles during walking were performed following approximately 3 min of preparative walking. Paired-pulse TMS was used to measure short-interval intracortical inhibition (SICI) and intracortical facilitation (ICF) in the left TA and SOL at baseline, immediately after the 7-min walking task, and 30 min post-task. EMG activity in the TA was significantly increased during AW1 and AW2 compared to during SW, whereas a significant difference in EMG activity of the SOL was observed only between AW1 and AW2. As for intracortical excitability, there was a significant alteration in SICI in the TA between SW and AW1, but not between SW and AW2. For the same amount of walking exercise, we found that the different methods used to control walking patterns induced different excitability changes in SICI. Our research shows that activation patterns associated with controlled leg muscles can alter post-exercise excitability in intracortical circuits. Therefore, how leg muscles are activated in a clinical setting could influence the outcome of walking in patients with stroke. PMID:25688972

Gradient-based adaptation of general gaussian kernels.

PubMed

Glasmachers, Tobias; Igel, Christian

2005-10-01

Gradient-based optimizing of gaussian kernel functions is considered. The gradient for the adaptation of scaling and rotation of the input space is computed to achieve invariance against linear transformations. This is done by using the exponential map as a parameterization of the kernel parameter manifold. By restricting the optimization to a constant trace subspace, the kernel size can be controlled. This is, for example, useful to prevent overfitting when minimizing radius-margin generalization performance measures. The concepts are demonstrated by training hard margin support vector machines on toy data.

Balance and postural skills in normal-weight and overweight prepubertal boys.

PubMed

Deforche, Benedicte I; Hills, Andrew P; Worringham, Charles J; Davies, Peter S W; Murphy, Alexia J; Bouckaert, Jacques J; De Bourdeaudhuij, Ilse M

2009-01-01

This study investigated differences in balance and postural skills in normal-weight versus overweight prepubertal boys. Fifty-seven 8-10-year-old boys were categorized overweight (N = 25) or normal-weight (N = 32) according to the International Obesity Task Force cut-off points for overweight in children. The Balance Master, a computerized pressure plate system, was used to objectively measure six balance skills: sit-to-stand, walk, step up/over, tandem walk (walking on a line), unilateral stance and limits of stability. In addition, three standardized field tests were employed: standing on one leg on a balance beam, walking heel-to-toe along the beam and the multiple sit-to-stand test. Overweight boys showed poorer performances on several items assessed on the Balance Master. Overweight boys had slower weight transfer (p < 0.05), lower rising index (p < 0.05) and greater sway velocity (p < 0.001) in the sit-to-stand test, greater step width while walking (p < 0.05) and lower speed when walking on a line (p < 0.01) compared with normal-weight counterparts. Performance on the step up/over test, the unilateral stance and the limits of stability were comparable between both groups. On the balance beam, overweight boys could not hold their balance on one leg as long (p < 0.001) and had fewer correct steps in the heel-to-toe test (p < 0.001) than normal-weight boys. Finally, overweight boys were slower in standing up and sitting down five times in the multiple sit-to-stand task (p < 0.01). This study demonstrates that when categorised by body mass index (BMI) level, overweight prepubertal boys displayed lower capacity on several static and dynamic balance and postural skills.

Molecular and cytogenetic characterization of the 5DS-5BS chromosome translocation conditioning soft kernel texture in durum wheat

USDA-ARS?s Scientific Manuscript database

Cultivar ‘Soft Svevo’, a new non-GMO soft durum cultivar with soft kernel texture, was developed through a 5DS(5BS) chromosomal translocation from event. cv. Chinese Spring, and subsequently used to create new soft durum germplasm. The development of Soft Svevo featured the Ph1b-mediated homoeologou...

Gabor-based kernel PCA with fractional power polynomial models for face recognition.

PubMed

Liu, Chengjun

2004-05-01

This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power

[Walking with canes and forearm-crutches (author's transl)].