bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a Reference Spatiotemporal Gait Data Set for Indian Subjects: A Pilot Study
Authors: Ramnani Raj , Mukul Pooja , Jain Siddhant , Tripathi Abhishek 
Published: October 2016

1.AbstractInterpretation of pathological gait has, for decades, offered insight into amputee anomalies and diseases such as cerebral palsy. Gait analysis has been actively used at the Bhagwan Mahaveer Viklang Sahatya Samiti for such purposes. The normative gait data used to compare data obtained from amputees, however, has been collected from laboratories under dissimilar conditions, skewing interpretation. Spatiotemporal gait parameters were extractedfrom 43 male Indian subjects using a 7.5m walkway and theBTS Bioengineering GAITLABsetup. Working under the hypothesis that a lack of cross-cultural validity was somewhat responsible for variations in normative gait, we attempted to develop a region-specific data set for use at the headquarters of the Jaipur Foot Organization Bhagwan Mahaveer Viklang Sahatya Samiti (BMVSS). Stratified random sampling was used to recruit subjects and measures were taken to ensure minimal effects of extraneous variables. Statistical analysis was performed on obtained data using one-way analysis of variance (ANOVA) to gauge the effect age and ethnicity had on normative values of the parameters investigated. We found statistically significant p-values for a few spatiotemporal parameters in the analysis of variance for both age and ethnicity. While the results were much less significant than initially hypothesized, the study proved an efficient way to create a normative gait data set exclusively for use at the gait laboratory of the Jaipur Foot Organization, thereby eliminating potential erroneous interpretation of pathological gait when comparing said gait to normative gait data obtained in laboratories under dissimilar conditions.
A Probabilistic Approach To The Diagnosis Of Obstructive Sleep Apnea
Authors: Ramnani Raj , Tripathi Anshul 
Published: October 2016

AbstractIn a novel approach to diagnose Obstructive Sleep Apnea, electronic components including an Arduino Mega, a Bluetooth Transceiver, an accelerometer, and a air-quality sensor, were put together to create a wearable that would detect the frequency of apnea events, diagnose the disorder, and sound an alarm when necessary. A primary consideration was to make the mechanism accessible and affordable, and in doing so, lower the number of cases of Obstructive Sleep Apnea that go undiagnosed due to the cost and inconvenience associated with the traditional diagnosis method—a Polysomnogram. Bluetooth capability was an additional consideration so that the device would transmit data directly to an android smartphone, eliminating the need for an additional output mechanism. The total cost of the device, quite surprisingly, did not exceed $30, and therein rendered the device an accessible, affordable mechanism for diagnosis. Tests of the device on diagnosed patients yielded data consistent with the diagnosis, with a few false positives as a result of the excessive sensitivity of the sensors.
Reconstructing cell cycle and disease progression using deep learning
Authors: Eulenberg Philipp , Köhler Niklas , Blasi Thomas , Filby Andrew , Carpenter Anne E. , Rees Paul , Theis Fabian J. , Wolf F. Alexander 
Published: October 2016

AbstractWe show that deep convolutional neural networks combined with non-linear dimension reduction enable reconstructing biological processes based on raw image data. We demonstrate this by recon-structing the cell cycle of Jurkat cells and disease progression in diabetic retinopathy. In further analysis of Jurkat cells, we detect and separate a subpopulation of dead cells in an unsupervised manner and, in classifying discrete cell cycle stages, we reach a 6-fold reduction in error rate compared to a recent approach based on boosting on image features. In contrast to previous methods, deep learning based predictions are fast enough for on-the-fly analysis in an imaging flow cytometer.
FIDDLE: An integrative deep learning framework for functional genomic data inference
Authors: Eser Umet , Churchman L. Stirling 
Published: October 2016

AbstractNumerous advances in sequencing technologies have revolutionized genomics through generating many types of genomic functional data. Statistical tools have been developed to analyze individual data types, but there lack strategies to integrate disparate datasets under a unified framework. Moreover, most analysis techniques heavily rely on feature selection and data preprocessing which increase the difficulty of addressing biological questions through the integration of multiple datasets. Here, we introduce FIDDLE (Flexible Integration of Data with Deep LEarning) an open source data-agnostic flexible integrative framework that learns a unified representation from multiple data types to infer another data type. As a case study, we use multipleSaccharomyces cerevisiaegenomic datasets to predict global transcription start sites (TSS) through the simulation of TSS-seq data. We demonstrate that a type of data can be inferred from other sources of data types without manually specifying the relevant features and preprocessing. We show that models built from multiple genome-wide datasets perform profoundly better than models built from individual datasets. Thus FIDDLE learns the complex synergistic relationship within individual datasets and, importantly, across datasets.
Refinement of intraperitoneal injection of sodium pentobarbital for euthanasia in laboratory rats (Rattus norvegicus)
Authors: Zatroch K , Knight CG , Reimer JN , Pang DSJ 
Published: October 2016

AbstractBackgroundThe Canadian Council on Animal Care and American Veterinary Medical Association classify intraperitoneal (IP) pentobarbital as an acceptable euthanasia method in rats. However, federal guidelines do not exist for a recommended dose or volume and IP euthanasia has been described as unreliable, with misinjections leading to variable success in ensuring a timely death. The aims of this study were to assess and improve efficacy and consistency of IP euthanasia.MethodsIn a randomized, blinded study, 51 adult female Sprague-Dawley rats (170-495 g) received one of four treatments: low-dose low-volume (LL) IP pentobarbital (n = 13, 200 mg/kg pentobarbital), low-dose high-volume (LH) IP pentobarbital (n = 14, 200 mg/kg diluted 1:3 with phosphate buffered saline), high-dose high-volume (HH, n = 14, 800 mg/kg pentobarbital), or saline. Times to loss of righting reflex (LORR) and cessation of heartbeat (CHB) were recorded. To identify misinjections, necropsy examinations were performed on all rats. Video recordings of LL and HH groups were analyzed for pain-associated behaviors. Between-group comparisons were performed with 1-way ANOVA and Games-Howell post hoc tests. Variability for CHB was assessed by coefficient of variation (CV) calculation.ResultsThe fastest euthanasia method (CHB) was HH (283.7 ± 38 s), compared with LL (485.8 ± 140.7 s, p = 0.002) and LH (347.7 ± 72.0 s, p = 0.039). Values for CV were: HH, 13.4%; LH, 20.7%; LL, 29.0%. LORR time was longest in LL (139.5 ± 29.6 s), compared with HH (111.6 ± 19.7 s, p = 0.046) and LH (104.2 ± 19.3 s, p = 0.01). Misinjections occurred in 15.7% (8/51) of euthanasia attempts. Pain-associated behavior incidence ranged from 36% (LL) to 46% (HH).ConclusionThese data illustrate refinement of this euthanasia technique. Both dose and volume contribute to speed of death with IP pentobarbital and an increase in volume alone does not significantly reduce variability. The proportion of misinjections was similar to that of previous studies.AbbreviationsLLlow-dose low-volumeLHlow-dose high-volumeHHhigh-dose high-volumeLORRloss of righting reflexCHBcessation of heartbeatGITgastrointestinal tractCVcoefficient of variation
FISH-ing for captured contacts: towards reconciling FISH and 3C
Authors: Fudenberg Geoff , Imakaev Maxim 
Published: October 2016

AbstractDeciphering how the one-dimensional information encoded in a genomic sequence is read out in three-dimensions is a pressing contemporary challenge. Chromosome conformation capture (3C) and fluorescence in-situ hybridization (FISH) are two popular technologies that provide important links between genomic sequence and 3D chromosome organization. However, how to integrate views from 3C, or genome-wide Hi-C, and FISH is far from solved. We first discuss what each of these methods measure by reconsidering available matched experimental data for Hi-C and FISH. Using polymer simulations, we then demonstrate that contact frequency is distinct from average spatial distance. We show this distinction can create a seemingly-paradoxical relationship between 3C and FISH. Finally, we consider how the measurement of specific interactions between chromosomal loci might be differentially affected by the two technologies. Together, our results have implications for future attempts to cross-validate and integrate 3C and FISH, as well as for developing models of chromosomes.
The Divisive-Normalization Model of V1 Neurons: A Comprehensive Comparison of Physiological Data and Model Predictions
Authors: Sawada Tadamasa , Petrov Alexander A. 
Published: October 2016

AbstractThe physiological responses of simple and complex cells in the primary visual cortex (V1) have been studied extensively and modeled at different levels. At the functional level, the divisive normalization model (DNM, Heeger, 1992) has accounted for a wide range of single-cell recordings in terms of a combination of linear filtering, nonlinear rectification, and divisive normalization. We propose standardizing the formulation of the DNM and implementing it in software that takes static grayscale images as inputs and produces firing-rate responses as outputs. We also review a comprehensive suite of 30 empirical phenomena and report a series of simulation experiments that qualitatively replicate dozens of key experiments with a standard parameter set consistent with physiological measurements. This systematic approach identifies novel falsifiable predictions of the DNM. We show how the model simultaneously satisfies the conflicting desiderata of flexibility and falsifiability. Our key idea is that, while adjustable parameters are needed to accommodate the diversity across neurons, they must be fixed for a given individual neuron. This requirement introduces falsifiable constraints when this single neuron is probed with multiple stimuli. We also present mathematical analyses and simulation experiments that explicate some of these constraints.
Asexual but not clonal: evolutionary processes in populations with automictic reproduction
Authors: Engelstädter Jan 
Published: October 2016

AbstractMany parthenogenetically reproducing animals produce offspring not clonally but through different mechanisms collectively referred to as automixis. Here, meiosis proceeds normally but is followed by the fusion of meiotic products that restores diploidy. This mechanism typically leads to a reduction in heterozygosity among the offspring compared to the mother. Following a derivation of the rate at which heterozygosity is lost at one and two loci, depending on the number of crossovers between loci and centromere, a number of models are developed to gain a better understanding of basic evolutionary processes in automictic populations. Analytical results are obtained for the expected equilibrium neutral genetic diversity, mutation-selection balance, selection with overdominance, the rate of spread of beneficial mutations, and selection on crossover rates. These results are complemented by numerical investigations elucidating how associative overdominance (two off-phase deleterious mutations at linked loci behaving like an overdominant locus) can in some cases maintain heterozygosity for prolonged times, and how clonal interference affects adaptation in automictic populations. These results suggest that although automictic populations are expected to suffer from the lack of gene shuffling with other individuals, they are nevertheless in some respects superior to both clonal and outbreeding sexual populations in the way they respond to beneficial and deleterious mutations. Implications for related genetic systems such as intratetrad mating, clonal reproduction, selfing as well as different forms of mixed sexual and automictic reproduction are discussed.
Rapid evolution of female-biased genes among four species ofAnophelesmalaria mosquitoes
Authors: Papa Francesco , Windbichler Nikolai , Waterhouse Robert M. , Cagnetti Alessia , D’Amato Rocco , Presampieri Tania , Lawniczak Mara K. N. , Nolan Tony , Papathanos Philippos Aris 
Published: October 2016

AbstractUnderstanding how phenotypic differences between males and females arise from the sex-biased expression of nearly identical genomes can often reveal important insights into the biology and evolution of a species. AmongAnophelesmosquito species, these phenotypic differences include vectorial capacity, as it is only females that blood feed and thus transmit human malaria. Here, we use RNA-seq data from multiple tissues of four vectors spanning theAnophelesphylogeny to explore the genomic and evolutionary properties of sex-biased genes. We find that in these mosquitoes, in contrast to what has been found in many other organisms, female-biased genes are more rapidly evolving in sequence, expression, and genic turnover, than male-biased genes. Our results suggests that this atypical pattern may be due to the combination of sex-specific life history challenges encountered by females, such as blood feeding. Furthermore, female propensity to only mate once in nature in male swarms likely diminishes sexual selection of post-reproductive traits related to sperm competition among males. We also develop a comparative framework to systematically explore tissue- and sex-specific splicing, to document its conservation throughout the genus and identify a set of candidate genes for future functional analyses of sex-specific isoform usage. Finally, our data reveals that the deficit of male-biased genes on the X chromosomes inAnophelesis a conserved feature in this genus and can be directly attributed to chromosome-wide transcriptional regulation that demasculinizes the X in male reproductive tissues.
Flexibility and design: conformational heterogeneity along the evolutionary trajectory of a redesigned ubiquitin
Authors: Biel Justin T. , Thompson Michael C. , Cunningham Christian N. , Corn Jacob E. , Fraser James S. 
Published: October 2016

SummaryAlthough protein design has been used to introduce new functions, designed variants generally only function as well as natural proteins after rounds of laboratory evolution. One possibility for this pattern is that designed mutants frequently sample nonfunctional conformations. To test this idea, we exploited advances in multiconformer modeling of room temperature X-ray data collection on redesigned ubiquitin variants selected for increasing binding affinity to the deubiquitinase USP7. Initial core mutations disrupt natural packing and lead to increased flexibility. Additional, experimentally selected mutations quenched conformational heterogeneity through new stabilizing interactions. Stabilizing interactions, such as cation-pi stacking and ordered waters, which are not included in standard protein design energy functions, can create specific interactions that have long range effects on flexibility across the protein. Our results suggest that increasing flexibility may be a useful strategy to escape local minima during initial directed evolution and protein design steps when creating new functions.
Improving power for rare variant tests by integrating external controls
Authors: Lee Seunggeun , Kim Sehee , Fuchsberger Christian 
Published: October 2016

AbstractDue to the drop in sequencing cost, the number of sequenced genomes is increasing rapidly. To improve power of rare variant tests, these sequenced samples could be used as external control samples in addition to control samples from the study itself. However, when using external controls, possible batch effects due to the use of different sequencing platforms or genotype calling pipelines can dramatically increase type I error rates. To address this, we propose novel summary statistics-based single and gene- or region-based rare-variant tests that allow the integration of external controls while controlling for type I error. Our approach is based on the insight that batch effects on a given variant can be assessed by comparing odds ratio estimates using internal controls only vs. using combined control samples of internal and external controls. From simulation experiments and the analysis of data from age related macular degeneration and type 2 diabetes studies, we demonstrate that our method can substantially improve power while controlling for type I error rate.
Challenging the Raunkiaeran shortfall and the consequences of using imputed databases
Authors: Jardim Lucas , Bini Luis Mauricio , Felizola Diniz-Filho José Alexandre , Villalobos Fabricio 
Published: October 2016

SummaryGiven the prevalence of missing data on species’ traits – Raunkiaeran shorfall — and its importance for theoretical and empirical investigations, several methods have been proposed to fill sparse databases. Despite its advantages, imputation of missing data can introduce biases. Here, we evaluate the bias in descriptive statistics, model parameters, and phylogenetic signal estimation from imputed databases under different missing and imputing scenarios.We simulated coalescent phylogenies and traits under Brownian Motion and different Ornstein-Uhlenbeck evolutionary models. Missing values were created using three scenarios: missing completely at random, missing at random but phylogenetically structured and missing at random but correlated with some other variable. We considered four methods for handling missing data: delete missing values, imputation based on observed mean trait value, Phylogenetic Eigenvectors Maps and Multiple Imputation by Chained Equations. Finally, we assessed estimation errors of descriptive statistics (mean, variance), regression coefficient, Moran’s correlogram and Blomberg’s K of imputed traits.We found that percentage of missing data, missing mechanisms, Ornstein-Uhlenbeck strength and handling methods were important to define estimation errors. When data were missing completely at random, descriptive statistics were well estimated but Moran’s correlogram and Blomberg’s K were not well estimated, depending on handling methods. We also found that handling methods performed worse when data were missing at random, but phylogenetically structured. In this case adding phylogenetic information provided better estimates. Although the error caused by imputation was correlated with estimation errors, we found that such relationship is not linear with estimation errors getting larger as the imputation error increases.Imputed trait databases could bias ecological and evolutionary analyses. We advise researchers to share their raw data along with their imputed database, flagging imputed data and providing information on the imputation process. Thus, users can and should consider the pattern of missing data and then look for the best method to overcome this problem. In addition, we suggest the development of phylogenetic methods that consider imputation uncertainty, phylogenetic autocorrelation and preserve the level of phylogenetic signal of the original data.
Modeling duration of FSA operating and farm ownership loan guarantees
Authors: Long Deng , Ahrendsen Bruce L. , L. Dixon Bruce , B. Dodson Charles 
Published: October 2016

Purpose
The purpose of this paper is to identify determinants of feasible outcome events (expired with no loss, settled for loss, still performing) and time to event of Farm Service Agency (FSA) operating and farm ownership (FO) loan guarantees.

Design/methodology/approach
Data on 19,126 FSA guaranteed loans, which were made by various lenders to farmers who have limited ability to obtain loans from normal sources without the Federal guarantee, were collected. Cox proportional hazards models for operating loans (OLs) and FO loans are estimated to identify borrower characteristics, loan characteristics, lender types, and farm and macroeconomic environment factors that influence guarantee outcomes.

Findings
Loans with different characteristics (loan amount, loan term, lender type, region originated) and assistance programs (Beginning Farmer, Interest Assistance) have differing guarantee outcomes. Contemporaneous variables, in particular delinquency status, have a significant impact on guarantee outcomes.

Research limitations/implications
All loans were originated in calendar years 2004 and 2005. Since FO loans may have as long as 40 year terms, results are not as robust for FO loans as for OLs.

Practical implications
Different loan characteristics and macroeconomic conditions significantly influence the occurrence of possible guarantee outcomes and time to the outcomes.

Originality/value
Guaranteed loans are the primary method of government credit assistance to US farm operators. Data on individual borrowers have been difficult to obtain for much of the life of the guaranteed program because loan applications are held privately. This study provides insight on how various factors drive guarantee performance which is useful to policy makers trying to increase guaranteed loan program efficiency.
Does credit market inefficiency affect technology adoption? Evidence from Sub-Saharan Africa
Authors: Abdallah Abdul-Hanan 
Published: October 2016

PurposeThe purpose of this paper is to investigate factors affecting the adoption of agricultural technologies in Sub-Saharan Africa, specifically the role of credit market inefficiency in adoption of agricultural technologies in the region.Design/methodology/approachMost importantly, the paper applies a 2SLS model on a unique data set on nine agrarian countries from Sub-Saharan Africa’s intensification of food crops agriculture (Afrint) to provide evidence on how credit market inefficiency affects adoption of technologies in the sub region.FindingsThe study finds that the relationship between credit and technology adoption is one-way causal relation (i.e. credit access leads to technology adoption) as opposed to a two-way relation (i.e. mutual dependent relation). Further, the results indicate that credit market inefficiency can be a major barrier to the adoption of yield enhancing technologies in Sub-Saharan Africa. Further, the study showed mixed results for household variables. The results give credence to studies that highlight the importance of infrastructure and risk control in the adoption of new technologies.Research limitations/implicationsThe study is limited to only nine countries in Sub-Saharan Africa. Thus, the findings and interpretations should be considered as such. Further, there is the need for further research that considers all the region so as to establish whether or not there is a relationship between credit market inefficiencies and technology adoption in the region.Practical implicationsThe policy implication is that microfinance institutions should consider scaling up their credit services to ensure that more households benefit from it, and in so doing technology adoption will be enhanced.Originality/valueThe main contribution of the study lies in its use of a unique data set from Sub-Saharan Africa’s intensification of food crops agriculture (Afrint) to investigation relationship between credit market inefficiency and technology adoption.