Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring aging rates of mice subjected to caloric restriction and genetic disruption of growth hormone signaling

Caloric restriction and genetic disruption of growth hormone signaling have been shown to counteract aging in mice. The effects of these interventions on aging are examined through age-dependent survival or through the increase in age-dependent mortality rates on a logarithmic scale fitted to the Gompertz model. However, these methods have limitations that impede a fully comprehensive disclosure of these effects. Here we examine the effects of these interventions on murine aging through the increase in age-dependent mortality rates on a linear scale without fitting them to a model like the Gompertz model. Whereas these interventions negligibly and non-consistently affected the aging rates when examined through the age-dependent mortality rates on a logarithmic scale, they caused the aging rates to increase at higher ages and to higher levels when examined through the age-dependent mortality rates on a linear scale. These results add to the debate whether these interventions postpone or slow aging and to the understanding of the mechanisms by which they affect aging. Since different methods yield different results, it is worthwhile to compare their results in future research to obtain further insights into the effects of dietary, genetic, and other interventions on the aging of mice and other species.
Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit

We consider a linear stochastic bandit problem where the dimension K of the unknown parameter is larger than the sampling budget n. In such cases, it is in general impossible to derive sub-linear regret bounds since usual linear bandit algorithms have a regret in O(K p n). In this paper we assume that is S sparse, i.e. has at most S non-zero components, and that the space of arms is the unit ball for the jj:jj2 norm. We combine ideas from Compressed Sensing and Bandit Theory and derive an algorithm with a regret bound in O(S p n). We detail an application to the problem of optimizing a function that depends on many variables but among which only a small number of them (initially unknown) are relevant.
De-noising based on wavelet analysis and bayesian estimation for low-dose X-ray CT

Computed Tomography (CT) technology has been widely applied in modern clinical diagnosis. However, the high radiation exposure limits its further application. Low-dose protocol scans have been gradually used in clinics for mass screening due to its lower radiation exposure. Nevertheless, the quality of CT images would be severely decreased by the excessive quantum noise under low x-ray dose circumstances, which may degrade the diagnosis accuracy. This work explores a multiscale approach to reduce the strong noise in low-dose CT sinograms based on analyzing and modeling both the signal and noise in the wavelet domain. Then we develop a denoising method with applying Bayesian analysis to determine adaptive and optimum thresholds for the wavelet coefficients. Experimental results show that the proposed algorithm is effective in removing noise together with maintaining good quality of diagnostic images.
A Saturated Genetic Linkage Map of Autotetraploid Alfalfa (Medicago sativa L.) Developed Using Genotyping-by-Sequencing Is Highly Syntenous with the Medicago truncatula Genome

A genetic linkage map is a valuable tool for quantitative trait locus mapping, map-based gene cloning, comparative mapping, and whole-genome assembly. Alfalfa, one of the most important forage crops in the world, is autotetraploid, allogamous, and highly heterozygous, characteristics that have impeded the construction of a high-density linkage map using traditional genetic marker systems. Using genotyping-by-sequencing (GBS), we constructed low-cost, reasonably high-density linkage maps for both maternal and paternal parental genomes of an autotetraploid alfalfa F1 population. The resulting maps contain 3591 single-nucleotide polymorphism markers on 64 linkage groups across both parents, with an average density of one marker per 1.5 and 1.0 cM for the maternal and paternal haplotype maps, respectively. Chromosome assignments were made based on homology of markers to the M. truncatula genome. Four linkage groups representing the four haplotypes of each alfalfa chromosome were assigned to each of the eight Medicago chromosomes in both the maternal and paternal parents. The alfalfa linkage groups were highly syntenous with M. truncatula, and clearly identified the known translocation between Chromosomes 4 and 8. In addition, a small inversion on Chromosome 1 was identified between M. truncatula and M. sativa. GBS enabled us to develop a saturated linkage map for alfalfa that greatly improved genome coverage relative to previous maps and that will facilitate investigation of genome structure. GBS could be used in breeding populations to accelerate molecular breeding in alfalfa.
IP multicast extensions for mobile internetworking

This paper deals with multicasting in an internetwork with mobile hosts, particularly with regard to mobile-IP and distance vector multicast routing (DVMRP) protocols. When the source of a multicast datagram is a mobile host (MH), the datagram may not reach all group members to which the datagram is addressed, including other mobile hosts. When the source is a static host and the multicast group includes mobile hosts, a mobile group member may receive datagrams in one cell but not in another. Further when a MH enters a cell which contains no other member of the same group, the MH will experience a delay before it starts receiving datagrams addressed to that group. Mobility between campuses which result in a MH acquiring an additional unicast address, also has an effect on multicast routing. We propose enhancements to DVMRP executed at the mobility support routers (MSR) that ensure correct forwarding of multicast datagrams to and from mobile hosts. Our solutions do not require any change at hosts and routers unaware of mobility, i.e. the modifications are limited to MSRs and MHs. We also describe an implementation incorporating a subset of our proposals. Lastly, we show that alternate styles of multicasting or mobile networking, viz. link-state (MOSPF) and IETF proposal, will face similar problems and our proposed solutions are still valid in their context.
A Complexity Trichotomy for the Six-Vertex Model

We prove a complexity classification theorem that divides the six-vertex model on graphs into exactly three types. For every setting of the parameters of the model, the computation of the partition function is precisely: Either (1) solvable in polynomial time for every graph, or (2) #P-hard for general graphs but solvable in polynomial time for planar graphs, or (3) #P-hard even for planar graphs. The classification has an explicit criterion. In addition to matchgates and matchgates-transformable signatures, we discover previously unknown families of planar-tractable partition functions by a non-local connection to #CSP, defined in terms of a "loop space". For the proof of #P-hardness, we introduce the use of Mobius transformations as a powerful new tool to prove that certain complexity reductions succeed in polynomial time.
Application of Support Vector Machines in upper limb motion classification using myoelectric signals

This paper presents a novel support vector machine (SVM) approach to upper limb motion classification using myoelectric signals. The main purpose of this paper is to compare SVM-based classifiers with LDA and MLP. SVM demonstrates exceptional classification accuracy and results in a robust way of limb motion classification with low computational cost. The validity of entropy, as an index to measure correctness of classification, is also examined. Experimental results show that entropy is a reliable measure for online training in myoelectric control systems.
An Ensemble Learning Based Framework for Traditional Chinese Medicine Data Analysis with ICD-10 Labels

Objective. This study aims to establish a model to analyze clinical experience of TCM veteran doctors. We propose an ensemble learning based framework to analyze clinical records with ICD-10 labels information for effective diagnosis and acupoints recommendation. Methods. We propose an ensemble learning framework for the analysis task. A set of base learners composed of decision tree (DT) and support vector machine (SVM) are trained by bootstrapping the training dataset. The base learners are sorted by accuracy and diversity through nondominated sort (NDS) algorithm and combined through a deep ensemble learning strategy. Results. We evaluate the proposed method with comparison to two currently successful methods on a clinical diagnosis dataset with manually labeled ICD-10 information. ICD-10 label annotation and acupoints recommendation are evaluated for three methods. The proposed method achieves an accuracy rate of 88.2% ± 2.8% measured by zero-one loss for the first evaluation session and 79.6% ± 3.6% measured by Hamming loss, which are superior to the other two methods. Conclusion. The proposed ensemble model can effectively model the implied knowledge and experience in historic clinical data records. The computational cost of training a set of base learners is relatively low.
Effectiveness of a Predictive Algorithm in the Prevention of Exercise-Induced Hypoglycemia in Type 1 Diabetes.

BACKGROUND Sensor-augmented pump therapy (SAPT) with a predictive algorithm to suspend insulin delivery has the potential to reduce hypoglycemia, a known obstacle in improving physical activity in patients with type 1 diabetes. The predictive low glucose management (PLGM) system employs a predictive algorithm that suspends basal insulin when hypoglycemia is predicted. The aim of this study was to determine the efficacy of this algorithm in the prevention of exercise-induced hypoglycemia under in-clinic conditions. METHODS This was a randomized, controlled cross-over study in which 25 participants performed 2 consecutive sessions of 30 min of moderate-intensity exercise while on basal continuous subcutaneous insulin infusion on 2 study days: a control day with SAPT alone and an intervention day with SAPT and PLGM. The predictive algorithm suspended basal insulin when sensor glucose was predicted to be below the preset hypoglycemic threshold in 30 min. We tested preset hypoglycemic thresholds of 70 and 80 mg/dL. The primary outcome was the requirement for hypoglycemia treatment (symptomatic hypoglycemia with plasma glucose <63 mg/dL or plasma glucose <50 mg/dL) and was compared in both control and intervention arms. RESULTS Results were analyzed in 19 participants. In the intervention arm with both thresholds, only 6 participants (32%) required treatment for hypoglycemia compared with 17 participants (89%) in the control arm (P = 0.003). In participants with a 2-h pump suspension on intervention days, the plasma glucose was 84 ± 12 and 99 ± 24 mg/dL at thresholds of 70 and 80 mg/dL, respectively. CONCLUSIONS SAPT with PLGM reduced the need for hypoglycemia treatment after moderate-intensity exercise in an in-clinic setting.
Biochemical Identification and Biophysical Characterization of a Channel-Forming Protein fromRhodococcus erythropolis

ABSTRACT Organic solvent extracts of whole cells of the gram-positive bacterium Rhodococcus erythropolis contain a channel-forming protein. It was identified by lipid bilayer experiments and purified to homogeneity by preparative sodium dodecyl sulfate (SDS)-polyacrylamide gel electrophoresis (PAGE). The pure protein had a rather low molecular mass of about 8.4 kDa, as judged by SDS-PAGE. SDS-resistant oligomers with a molecular mass of 67 kDa were also observed, suggesting that the channel is formed by a protein oligomer. The monomer was subjected to partial protein sequencing, and 45 amino acids were resolved. According to the partial sequence, the sequence has no significant homology to known protein sequences. To check whether the channel was indeed localized in the cell wall, the cell wall fraction was separated from the cytoplasmic membrane by sucrose step gradient centrifugation. The highest channel-forming activity was found in the cell wall fraction. The purified protein formed large ion-permeable channels in lipid bilayer membranes with a single-channel conductance of 6.0 nS in 1 M KCl. Zero-current membrane potential measurements with different salts suggested that the channel ofR. erythropolis was highly cation selective because of negative charges localized at the channel mouth. The correction of single-channel conductance data for negatively charged point charges and the Renkin correction factor suggested that the diameter of the cell wall channel is about 2.0 nm. The channel-forming properties of the cell wall channel of R. erythropolis were compared with those of other members of the mycolata. These channels have common features because they form large, water-filled channels that contain net point charges.
Towards a Full-Reference Quality Assessment for Color Images Using Directional Statistics

This paper presents a novel computational model for quantifying the perceptual quality of color images consistently with subjective evaluations. The proposed full-reference color metric, namely, a directional statistics-based color similarity index, is designed to consistently perform well over commonly encountered chromatic and achromatic distortions. In order to accurately predict the visual quality of color images, we make use of local color descriptors extracted from three perceptual color channels: 1) hue; 2) chroma; and 3) lightness. In particular, directional statistical tools are employed to properly process hue data by considering their periodicities. Moreover, two weighting mechanisms are exploited to accurately combine locally measured comparison scores into a final score. Extensive experimentation performed on large-scale databases indicates that the proposed metric is effective across a wide range of chromatic and achromatic distortions, making it better suited for the evaluation and optimization of color image processing algorithms.
Self-Aligned Double and Quadruple Patterning Aware Grid Routing Methods

Although self-aligned double and quadruple patterning (SADP, SAQP) have promising processes for sub-20 nm node advanced technologies and beyond, not all layouts are compatible with them. In advanced technologies, feasible wafer image should be generated effectively by utilizing SADP and SAQP where a wafer image is determined by a selected mandrel pattern. However, predicting a mandrel pattern is not easy since it is different from the wafer image (or target pattern). In this paper, we propose new routing methods for spacer-is-dielectric (SID)-type SADP, SID-type SAQP, and spacer-is-metal (SIM)-type SADP to generate a feasible layout satisfying the connection requirements. Routing algorithms comprising simple connecting and cutting rules are performed on a new grid structure where two (SID-type SADP) or three colors (SID-type SAQP and SIM-type SADP) are assigned alternately to grid-nodes. Then a mandrel pattern is selected without complex coloring or decomposition methods. Also, we try to reduce hotspots (potentially defective regions) by the proposed dummy pattern flipping for SID-type SADP. In experiments, feasible layouts meeting the connection requirements are generated and the effectiveness of the proposed framework is confirmed.
PBIE: A Data Preparation Toolkit Toward Developing a Parsing-Based Information Extraction System

We have developed a toolkit in which an annotation tool, a syntactic tree editor, and an extraction rule editor interact dynamically. Its output can be stored in a database for further use. In the field of biomedicine, there is a critical need for automatic text processing. However, current language processing approaches suffer from insufficient basic data incorporating both human domain expertise and domain-specific language processing capabilities. With the annotation tool presented here, a set of ggold standardsh can be collected, representing what should be extracted. At the same time, any change in annotation can be viewed on an associated syntactic tree. These facilities provide a clear picture of the relationship between the extraction target and the syntactic tree. Underlying sentences can be analyzed with a parser which can be plugged in, or a set of parsed sentences can be used to generate the tree. Extraction rules written with the integrated editor can be applied at once, and their validity can immediately be verified both on the syntactic tree and on the sentence string by coloring the corresponding segments. Thus our toolkit enables the user to efficiently construct parse-based extraction rules. PBIE2 works under Windows 2000/XP and requires Microsoft Internet Explorer 6.0 or higher. The data can be stored in Microsoft Access.
Voice conversion using Artificial Neural Networks

In this paper, we propose to use Artificial Neural Networks (ANN) for voice conversion. We have exploited the mapping abilities of ANN to perform mapping of spectral features of a source speaker to that of a target speaker. A comparative study of voice conversion using ANN and the state-of-the-art Gaussian Mixture Model (GMM) is conducted. The results of voice conversion evaluated using subjective and objective measures confirm that ANNs perform better transformation than GMMs and the quality of the transformed speech is intelligible and has the characteristics of the target speaker.
Effets d’un entraînement neuromoteur et d’un entraînement aérobie sur les fonctions exécutives chez l’enfant

Studies investigating effects of exercise on cognition in animals and human do not permit to clarify if these effects are specific to the type of exercise and if the cognitive gains for a developing brain are global or exclusive to certain cognitive functions. Considering the neuronal circuit between the cerebellum and the dorsolateral prefrontal cortex, we hypothesized that neuromotor training will improve executive functions associated with prefrontal cortex. Since aerobic training positively affected different cognitive functions in previous studies, we hypothesize that this type of exercise will improve executive functions and long-term memory. Three sixth grade classes (mean age = 11.4 years) were randomly assigned to neuromotor (n=20), aerobic (n=19), and control (n=15) conditions. We ensured that the motor training did not stimulate aerobic capacity and that the aerobic intervention was devoid of a motor training component. The exercise sessions for the two training groups consisted in 30 minutes per school day, took place during class time, and lasted for 10 weeks; the control group followed the regular school program. Motor and cognitive tests were administered before and after the intervention. A series of ANOVA’s revealed that neuromotor training enhanced verbal fluency with a marginal effect on verb generation, executive functions related to the fronto-cerebellar circuit, and that aerobic training led to a marginal improvement for verbal fluency. Therefore, our results showed differential improvements in executive functions induced by both neuromotor and aerobic training.
Human Activity and Motion Disorder Recognition: towards smarter Interactive Cognitive Environments

The rise of ubiquitous computing systems in our environment is engendering a strong need for novel approaches of human-computer interaction. Either for extending the existing range of possibilities and services available to people or for providing assistance the ones with limited conditions. Human Activity Recognition (HAR) is playing a central role in this task by offering the input for the development of more interactive and cognitive environments. This has motivated the organization of the ESANN 2013 Special Session in Human Activity and Motion Disorder Recognition and the execution of a competition in HAR. Here, a compilation of the most recent proposals in the area are exposed accompanied by the results of the contest calling for innovative approaches to recognize activities of daily living (ADL) from a recently published data set.
The FLOWERING LOCUS T orthologous gene of Platanus acerifolia is expressed as alternatively spliced forms with distinct spatial and temporal patterns.

The FLOWERING LOCUS T (FT) protein is a likely component of the 'florigen' signal that plays a crucial role in regulating the transition from vegetative to reproductive growth. Here, we report the isolation of full-length cDNAs and the corresponding genomic clones encoding orthologous FT proteins (PaFT) of London plane (Platanus acerifolia Willd). Two genes with high sequence identity were isolated (PaFT1-2), but 34 different transcript products were identified, comprising 21 splice forms produced by alternative splicing of the PaFT pre-mRNAs. Expression of the alternative splicing forms of PaFT varied according to tissue type and developmental stage. PaFT transcripts were detected throughout adult trees, whereas in juvenile trees they were only detected in dormant sub-petiolar buds. In adult trees, levels of the various alternative splicing PaFT forms were related to flower development stage and tree dormancy. Ectopic expression of the archetypal splice form of PaFT-A in tobacco and Arabidopsis developed multiple altered phenotypes, notably early flowering and attenuation of apical dominance. The evidence in this study indicates that complex alternative processing of PaFT transcripts in P. acerifolia may be associated with multiple regulatory roles, including initiation of flowering, flower development, apical dominance, tree dormancy and dormancy release.
Smooth pursuit and visual scanpaths: Independence of two candidate oculomotor risk markers for schizophrenia

Abstract Objectives. Smooth pursuit and visual scanpath deficits are candidate trait markers for schizophrenia. It is not clear whether eye tracking dysfunction (ETD) and atypical scanpath behaviour are the product of the same underlying neurobiological processes. We have examined co-occurrence of ETD and scanpath disturbance in individuals with schizophrenia and healthy volunteers. Methods. Eye movements of individuals with schizophrenia (N = 96) and non-clinical age-matched comparison participants (N = 100) were recorded using non-invasive infrared oculography during smooth pursuit in both predictable (horizontal sinusoid) and less predictable (Lissajous sinusoid) conditions and a free viewing scanpath task. Results. Individuals with schizophrenia demonstrated scanning deficits in both tasks. There was no association between performance measures of smooth pursuit and scene scanpaths in patient or control groups. Odds ratios comparing the likelihood of scanpath dysfunction when ETD was present, and the likelihood of finding scanpath dysfunction when ETD was absent were not significant in patients or controls in either pursuit variant, suggesting that ETD and scanpath dysfunction are independent anomalies in schizophrenia. Conclusion. ETD and scanpath disturbance appear to reflect independent oculomotor or neurocognitive deficits in schizophrenia. Each task may confer unique information about the pathophysiology of psychosis.