Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Characterization of Insertion and Deletion Variation in Chicken Using Next Generation Sequencing

Insertion and deletion (INDEL) is one of the main events contributing to genetic and phenotypic diversity, which receives less attention than SNP and large structural variation. To gain a better knowledge of INDEL variation in chicken genome, we applied next generation sequencing on 12 diverse chicken breeds at an average effective depth of 8.6. Over 1.3 million non-redundant short INDELs (1–49 bp) were obtained, the vast majority (92.48%) of which were novel. Follow-up validation assays confirmed that most (88.00%) of the randomly selected INDELs represent true variations. The majority (95.76%) of INDELs were less than 10 bp. Both the detected number and affected bases were larger for deletions than insertions. In total, INDELs covered 3.8 Mbp, corresponding to 0.36% of the chicken genome. The average genomic INDEL density was estimated as 0.49 per kb. INDELs were ubiquitous and distributed in a non-uniform fashion across chromosomes, with lower INDEL density in micro-chromosomes than in others, and some functional regions like exons and UTRs were prone to less INDELs than introns and intergenic regions. Nearly 620,253 INDELs fell in genic regions, 1,765 (0.28%) of which located in exons, spanning 1,358 (7.56%) unique Ensembl genes. Many of them are associated with economically important traits and some are the homologues of human disease-related genes. We demonstrate that sequencing multiple individuals at a medium depth offers a promising way for reliable identification of INDELs. The coding INDELs are valuable candidates for further elucidation of the association between genotypes and phenotypes. The chicken INDELs revealed by our study can be useful for future studies, including development of INDEL markers, construction of high density linkage map, INDEL arrays design, and hopefully, molecular breeding programs in chicken.
Very high power 1310nm InP single mode distributed feed back laser diode with reduced linewidth

High power single mode InGaAsP/InP DFB laser diodes with narrow linewidth and emitting near 1310nm are key devices for Analog transmission and Sensor applications since they can be rugged and compact sources more suited to harsh environment than solid-state or fiber-based lasers. Typically, the useful output power of DFB sources is limited to about 100mW when sub-MHz linewidth is required Ref [1] by the so-called "re-broadening effect" which causes the spectral linewidth to increase due to spatial-hole burning and other effects. We report here sub-MHz linewidth at output power levels exceeding 500mW resulting from cavity design that successfully addresses the concerns of linewidth re-broadening. Single-frequency operation can be maintained from threshold to the high power operating point without mode hops.
Activity Prediction Based on Tme Series Forcasting

Activity recognition is a crucial step in automaticassistance for elderly and disabled people, such asAlzheimer’s patients. The large number of activities ofdaily living (ADLs) that these persons are used to per-forming as well as their inability, sometimes, to start anactivity make the recognition process difficult, if not im-possible. To adress such problems, we propose a time-based activity prediction approch as a preliminary stepto activity recognition. Not only it will facilitate therecognition, but it will also rank activities according totheir occurrence probabilities at every time interval. Inthis paper, after detecting activities models, we imple-ment and validate an activity prediction process using atime series framework.
MicroRNA–Mediated Repression of the Seed Maturation Program during Vegetative Development in Arabidopsis

The seed maturation program only occurs during late embryogenesis, and repression of the program is pivotal for seedling development. However, the mechanism through which this repression is achieved in vegetative tissues is poorly understood. Here we report a microRNA (miRNA)–mediated repression mechanism operating in leaves. To understand the repression of the embryonic program in seedlings, we have conducted a genetic screen using a seed maturation gene reporter transgenic line in Arabidopsis (Arabidopsis thaliana) for the isolation of mutants that ectopically express seed maturation genes in leaves. One of the mutants identified from the screen is a weak allele of ARGONAUTE1 (AGO1) that encodes an effector protein for small RNAs. We first show that it is the defect in the accumulation of miRNAs rather than other small RNAs that causes the ectopic seed gene expression in ago1. We then demonstrate that overexpression of miR166 suppresses the derepression of the seed gene reporter in ago1 and that, conversely, the specific loss of miR166 causes ectopic expression of seed maturation genes. Further, we show that ectopic expression of miR166 targets, type III homeodomain-leucine zipper (HD-ZIPIII) genes PHABULOSA (PHB) and PHAVOLUTA (PHV), is sufficient to activate seed maturation genes in vegetative tissues. Lastly, we show that PHB binds the promoter of LEAFY COTYLEDON2 (LEC2), which encodes a master regulator of seed maturation. Therefore, this study establishes a core module composed of a miRNA, its target genes (PHB and PHV), and the direct target of PHB (LEC2) as an underlying mechanism that keeps the seed maturation program off during vegetative development.
A neural model for heading detection from optic flow

This paper describes a neural model developed for comput- ing heading from optic flow caused by 3D translational egomotion. The model uses the distributed representation of optic flow directions in cor- tical areas MT and MSTd. Model MSTd cells are selective for specific di- rections of visual motion and have large receptive fields covering approx- imately a quarter of the visual field at different retinal positions. The es- timation of heading is computed in a polar framework by combining the activation of all MSTd cells in a geometrically motivated and biological plausible manner. In our implementation optic flow fields were generated from motion of a simulated camera in a static environment. We analysed the detection error by comparing estimated heading with the ground truth defined by the given camera motion. The results show that the described neural approach provides a robust detection method. We demonstrate that movements inducing radial flow patterns (forward movements) are detected more accurately than motions inducing laminar flow fields (e.g. sideward movements), consistent with psychophysical findings. Most im- portant is that the described properties are a consequence of simple geo- metrical constraints defined by the spatial arrangement of MSTd cells.
Modeling of path loss for ultrawide band body-centric wireless communications

This paper presents the characterization of the path loss in ultrawide band body area networks. A Measurement campaign was performed in the anechoic chamber and in an indoor environment for comparison. The propagation along the front part of the body was analyzed, and the effect of the body movements on the signal strength was investigated. The results demonstrated that the normal distribution provides the best fit for modeling the path loss.
Selective Inhibition by Ethanol of Mitochondrial Calcium Influx Mediated by Uncoupling Protein-2 in Relation to N-Methyl-D-Aspartate Cytotoxicity in Cultured Neurons

Background We have shown the involvement of mitochondrial uncoupling protein-2 (UCP2) in the cytotoxicity by N-methyl-D-aspartate receptor (NMDAR) through a mechanism relevant to the increased mitochondrial Ca2+ levels in HEK293 cells with acquired NMDAR channels. Here, we evaluated pharmacological profiles of ethanol on the NMDA-induced increase in mitochondrial Ca2+ levels in cultured murine neocortical neurons. Methodology/Principal Findings In neurons exposed to glutamate or NMDA, a significant increase was seen in mitochondrial Ca2+ levels determined by Rhod-2 at concentrations of 0.1 to 100 µM. Further addition of 250 mM ethanol significantly inhibited the increase by glutamate and NMDA in Rhod-2 fluorescence, while similarly potent inhibition of the NMDA-induced increase was seen after exposure to ethanol at 50 to 250 mM in cultured neurons. Lentiviral overexpression of UCP2 significantly accelerated the increase by NMDA in Rhod-2 fluorescence in neurons, without affecting Fluo-3 fluorescence for intracellular Ca2+ levels. In neurons overexpressing UCP2, exposure to ethanol resulted in significantly more effective inhibition of the NMDA-induced increase in mitochondrial free Ca2+ levels than in those without UCP2 overexpression, despite a similarly efficient increase in intracellular Ca2+ levels irrespective of UCP2 overexpression. Overexpression of UCP2 significantly increased the number of dead cells in a manner prevented by ethanol in neurons exposed to glutamate. In HEK293 cells with NMDAR containing GluN2B subunit, more efficient inhibition was similarly induced by ethanol at 50 and 250 mM on the NMDA-induced increase in mitochondrial Ca2+ levels than in those with GluN2A subunit. Decreased protein levels of GluN2B, but not GluN2A, subunit were seen in immunoprecipitates with UCP2 from neurons with brief exposure to ethanol at concentrations over 50 mM. Conclusions/Significance Ethanol could inhibit the interaction between UCP2 and NMDAR channels to prevent the mitochondrial Ca2+ incorporation and cell death after NMDAR activation in neurons.
ENVELOPE MODELS FOR PARSIMONIOUS AND EFFICIENT MULTIVARIATE LINEAR REGRESSION

We propose a new parsimonious version of the classical multivariate nor- mal linear model, yielding a maximum likelihood estimator (MLE) that is asymp- totically less variable than the MLE based on the usual model. Our approach is based on the construction of a link between the mean function and the covariance matrix, using the minimal reducing subspace of the latter that accommodates the former. This leads to a multivariate regression model that we call the envelope model, where the number of parameters is maximally reduced. The MLE from the envelope model can be substantially less variable than the usual MLE, especially when the mean function varies in directions that are orthogonal to the directions of maximum variation for the covariance matrix.
Electrical Reorientation of Liquid Crystal within Silicon Macropore for Photonic Devices

We present the simulation results for the local director distribution of a nematic liquid crystal (NLC) confined inside cylindrical macropores of porous silicon (PS). The Frank free energy approach is used to describe the equilibrium configuration of the NLC in porous media. The influence of the molecular anchoring strength and of an externally applied electric field is investigated. Bruggeman approximation is used while calculating the effective refractive index of each layer in a PS multilayer structure. The reflectivity spectrum of the latter is simulated using the transfer matrix approach. Electrical tuning of a NLC-PS optical microcavity designed for resonance at lambda = 1330 nm is demonstrated. Tuning range varies from 8.5 nm up to 16 nm for weak and strong surface anchoring conditions, respectively.
Lean Body Mass Predicts Long-Term Survival in Chinese Patients on Peritoneal Dialysis

Background Reduced lean body mass (LBM) is one of the main indicators in malnutrition inflammation syndrome among patients on dialysis. However, the influence of LBM on peritoneal dialysis (PD) patients’ outcomes and the factors related to increasing LBM are seldom reported. Methods We enrolled 103 incident PD patients between 2002 and 2003, and followed them until December 2011. Clinical characteristics, PD-associated parameters, residual renal function, and serum chemistry profiles of each patient were collected at 1 month and 1 year after initiating PD. LBM was estimated using creatinine index corrected with body weight. Multiple linear regression analysis, Kaplan–Meier survival analysis, and Cox regression proportional hazard analysis were used to define independent variables and compare survival between groups. Results Using the median LBM value (70% for men and 64% for women), patients were divided into group 1 (n = 52; low LBM) and group 2 (n = 51; high LBM). Group 1 patients had higher rates of peritonitis (1.6 vs. 1.1/100 patient months; p<0.05) and hospitalization (14.6 vs. 9.7/100 patient months; p<0.05). Group 1 patients also had shorter overall survival and technique survival (p<0.01). Each percentage point increase in LBM reduced the hazard ratio for mortality by 8% after adjustment for diabetes, age, sex, and body mass index (BMI). Changes in residual renal function and protein catabolic rate were independently associated with changes in LBM in the first year of PD. Conclusions LBM serves as a good parameter in addition to BMI to predict the survival of patients on PD. Preserving residual renal function and increasing protein intake can increase LBM.
Performance evaluation of Multiple Target Tracking in the absence of reference data

Evaluating the performance of Multiple Target Tracking algorithms is a crucial requirement for the design and validation of different applications. Most of the available evaluation metrics require knowledge about the true state of the estimated situation. However, in most practical applications, such reference data are not available. Thus, a system of performance evaluation metrics which do not require reference data is proposed in this paper. The presented measures evaluate the detection performance, accuracy, and quality of the system output. The approach is evaluated based on simulated data and demonstrated on the example of an automotive tracking application.
Nonlinear Processes in Geophysics Intermittent heating of the solar corona by MHD turbulence

As the dissipation mechanisms considered for the heating of the solar corona would be sufficiently efficient only in the presence of small scales, turbulence is thought to be a key player in the coronal heating processes: it allows indeed to transfer energy from the large scales to these small scales. While Direct numerical simulations which have been performed to investigate the properties of magnetohydrodynamic turbulence in the corona have provided interesting results, they are limited to small Reynolds numbers. We present here a model of coronal loop turbulence involving shell-models and Alfv́ en waves propagation, allowing the much faster computation of spectra and turbulence statistics at higher Reynolds numbers. We also present first results of the forward-modelling of spectroscopic observables in the UV.
Linux Software Router: Data Plane Optimization and Performance Evaluation

Recent technological advances give a good chance to reach really effective results in the field of open Internet equipments, also called Open Routers (ORs). Some initiatives have been activated since the last few years to investigate the OR and related issues. But despite these activities, large interesting areas still require a deeper investigation. This work tries to give a contribution by reporting the results of an in-depth activity of optimization and testing realized on a PC Open Router architecture based on Linux software and COTS hardware. The main target of this paper has been the forwarding performance evaluation of different OR Linux-based software architectures. This analysis has been performed with both external (throughput and latencies) and internal (profiling) measurements. In particular, for what concerns the external measurements, a set of RFC2544 compliant tests has been proposed and analyzed.
Refactoring and Publishing WS-BPEL Processes to Obtain More Partners

WS-BPEL processes can facilitate service discovery when the services have multiple interfaces in certain order. Current approaches derive the abstract WS-BPEL processes directly from the corresponding executable ones by hiding or omitting the internal activities. However, these simple approaches may prevent the services from being found by valuable potential partners at service discovery stage. To address this problem, we propose a novel approach to refactoring the executable and abstract WS-BPEL processes for service discovery. We show the application of our approach through a typical travel agency service.
Theoretical and Methodological Approaches to Understanding Human Migration Patterns and their Utility in Forensic Human Identification Cases

Human migration patterns are of interest to scientists representing many fields. Theories have been posited to explain modern human evolutionary expansion, the diversity of human culture, and the motivational factors underlying an individual or group decision to migrate. Although the research question and subsequent approach may vary between disciplines, one thread is ubiquitous throughout most migration studies: why do humans migrate and what is the result of such an event? While the determination of individual attributes such as age, sex, and ancestry is often integral to migration studies, the positive identification of human remains is usually irrelevant. However, the positive identification of a deceased is paramount to a forensic investigation in which human remains have been recovered and must be identified. What role, if any, might the study of human movement patterns play in the interpretation of evidence associated with unidentified human remains? Due to increasing global mobility in the world's populations, it is not inconceivable that an individual might die far away from his or her home. If positive identification cannot immediately be made, investigators may consider various theories as to how or why a deceased ended up in a particular geographic location. While scientific evidence influences the direction of forensic investigations, qualitative evaluation can be an important component of evidence interpretation. This review explores several modern human migration theories and the methodologies utilized to identify evidence of human migratory movement before addressing the practical application of migration theory to forensic cases requiring the identification of human remains.
An Optimal Algorithm for Computer-Aided Design of Key Type Constraints

The paper defines entity, relationship, attribute, structural function, and constraint concepts in the framework of the Elementary Mathematical Data Model. A sound and complete algorithm for computer-aided design of key type constraints, which starts with a possibly non-empty set of keys for any object set, and aimed at hopefully completing it with all other existing keys is then introduced and discussed. Finally, this algorithm is proved to be optimal, as it asks db designers the minimum possible number of questions. By simply replacing object sets with relations and mappings with attributes, this proposed algorithm could be used in the Relational Data Model too.
A Decentralized Approach to Network Coding Based on Learning

Network coding is used to efficiently transmit information in a network from source nodes to sink nodes through intermediate nodes. It has been shown that linear coding is sufficient to achieve the multicast network capacity. In this paper, we introduce a method to design capacity achieving network codes based on reinforcement learning and makes using the market theory concepts. We demonstrate that the proposed algorithm is decentralized and polynomial time complex; while it constructs the codes much faster than other random methods with the same complexity order, especially in large networks with small field sizes. Furthermore, the proposed algorithm is robust to link failures and is used to reduce the number of encoding nodes in the network.
Hop, a Language for Programming the Web 2.0

Hop is a new higher-order language designed for programming interactive web applications such as web agendas, web galleries, music players, etc. It exposes a programming model based on two computation levels. The first one is in charge of executing the logic of an application while the second one is in charge of executing the graphical user interface. Hop separates the logic and the graphical user interface but it packages them together and it supports strong collaboration between the two engines. The two execution flows communicate through function calls and event loops. Both ends can initiate communications. The paper presents the main constructions of Hop. It sketches its implementation and it presents an example of a simple web application written in Hop.
Adaptive digital slope compensation for peak current mode control

Peak current mode control as well as digital control offers a number of benefits. Therefore it is an interesting approach to combine these two techniques in one control structure. Based on microcontrollers with on-chip comparators, this combination is realizable with very low effort. In order to eliminate the drawbacks of peak current mode control, a slope compensation has to be added. This paper presents such a slope compensation implemented on a microcontroller not using an analog ramp signal but instead pre-calculating the desired comparator switch-off threshold. In contrast to conventional analog control, adaptive algorithms can be used to maintain optimal slope compensation over a wide operating range. Problems that occur in practice due to reverse recovery current spike and computing time can be handled with simple measures. The effectiveness of the proposed digital slope compensation is verified by experimental results.
Error-related negativities elicited by monetary loss and cues that predict loss

Event-related potential studies have reported error-related negativity following both error commission and feedback indicating errors or monetary loss. The present study examined whether error-related negativities could be elicited by a predictive cue presented prior to both the decision and subsequent feedback in a gambling task. Participants were presented with a cue that indicated the probability of reward on the upcoming trial (0, 50, and 100%). Results showed a negative deflection in the event-related potential in response to loss cues compared with win cues; this waveform shared a similar latency and morphology with the traditional feedback error-related negativity.
Interactive functional specificity of the stress and immune responses: the ying, the yang, and the defense against 2 major classes of bacteria.

Received 2 May 2005; accepted 11 May 2005; electronically published 15 July 2005. Potential conflicts of interest: none reported. Reprints or correspondence: Dr. George P. Chrousos, First Department of Pediatrics, Athens University Medical School, Children’s Hospital Aghia Sophia, 115 27 Athens, Greece (chrousge@med.uoa.gr). The Journal of Infectious Diseases 2005;192:551–5 This article is in the public domain, and no copyright is claimed. 0022-1899/2005/19204-0001 The stress and immune systems play crucial roles in maintaining homeostasis [1, 2]. The former is relatively nonspecific, in the sense that it is activated by any threat to general homeostasis—including immune threats, when that threat exceeds a certain threshold—whereas the latter is relatively specific, in the sense that it is primarily activated when injurious agents come into contact with the tissues of the organism. During the past few decades, it has become apparent that the stress and immune systems extensively interact with each other, influencing each other’s activity, with the purpose of the successful defense against and adaptation of the organism to injurious agents. The study by Straub et al. [3] in this issue of the Journal of Infectious Diseases examines and eloquently describes the interaction of the stress and immune systems with regard to the powerful influence of the stress system on the quality of the defense of the organism against gram-negative versus gram-positive bacteria. This study highlights several key concepts that pertain to the interaction of these 2 systems that are important to review.