Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperative behavior acquisition in multi robots environment by reinforcement learning based on action selection level

In a multi robots environment, the overlap of actions selected by each robot makes the acquisition of cooperation behaviors less efficient. So we propose an approach to determine the action selection priority level based on which the cooperative behaviors can be well controlled. First, we define eight levels for the action selection priority, which can be correspondingly mapped to eight subspaces of actions. Then by the local potential field method the action selection priority level for each robot is calculated and thus its action subspace is obtained. Third, reinforcement learning (RL) is employed to choose a proper action for each robot in its action subspace. Finally we have applied the proposed method to a soccer playing situation and the efficiency was verified by the results of both the computer simulation and real experiments.
Usability Patterns in Software Architecture

Over the years the software engineering community has increasingly realized the important role software architecture plays in fulfilling the quality requirements of a system. Practice shows that for current software systems, most usability issues are still only detected during testing and deployment. To improve the usability of a software system, usability patterns can be applied. However, too often software systems prove to be inflexible towards such modifications which lead to potentially prohibitively high costs for implementing them afterwards. The reason for this shortcoming is that the software architecture of a system restricts certain usability patterns from being implemented after implementation. Several of these usability patterns are “architecture sensitive”, such modifications are costly to implement due through their structural impact on the system. Our research has identified several usability patterns that require architectural support. We argue the importance of the relation between usability and software architecture. Software engineers and usability engineers should be aware of the importance of this relation. The framework which illustrates this relation can be used as a source to inform architecture design for usability.
Oblivion Tracking: Towards a Probabilistic Working Memory Model for the Adaptation of Systems to Alzheimer Patients

We introduce a new probabilistic working memory (WM) model that we intend to use to automatically personalize user interfaces with respect to Alzheimer patients' declining WM capacity. WM is the part of the human memory responsible for the conscious short-term storing and manipulation of information. It is known to be extremely limited and to be one of the strongest factors that impact individual differences in cognitive abilities. In particular, individuals suffering from Alzheimer's disease have significantly impaired WM capacities that worsen as the disease progresses. As a use case for our model, we describe a system that is designed to help patients with Alzheimer's disease choose the music track they would like to listen to from a given playlist. We discuss how our WM model could be used to adapt this system to each patient's disease progression in time and the consequent deterioration of her WM capacity.
Performance evaluation of the PowerPC 620 microarchitecture

The PowerPC 620 microprocessor is the most recent and performance leading member of the PowerPC family. The 64-bit PowerPC 620 microprocessor employs a two-phase branch prediction scheme, dynamic renaming for all the register files, distributed multi-entry reservation stations, true out-of-order execution by six execution units, and a completion buffer for ensuring precise exceptions. This paper presents an instruction-level performance evaluation of the 620 microarchitecture. A performance simulator is developed using the VMW (visualization-based microarchitecture workbench) retargetable framework. The VMW-based simulator accurately models the microarchitecture down to the machine cycle level. Extensive trace-driven simulation is performed using the SPEC92 benchmarks. Detailed quantitative analyses of the effectiveness of all key microarchitecture features are presented.
Numerical modelling of the coupling of thermal and photoelectric effects for the photovoltaic modules under low concentration. (Modélisation numérique du couplage thermique-photoélectrique pour des modules photovoltaïques sous faible concentration)

The poor utilisation of the inter-row irradiation limits the production of photovoltaic (PV) modules. The "Aleph" project explores the potential of adding inter-row planar reflectors to increase the system yield, and defines clear rules for optimal settings of such systems in a given location and under a given climate. This work presents a multiphysics model of the system, numerical simulations of its behaviour, and the comparison with experimental data. Two PV module technologies are tested: amorphous silicon (a-Si) and polycrystalline silicon (p-Si). The experimental data show significant gains in produced energy brought by the reflectors. The gains are higher for a-Si modules compared to p-Si. The modelling work combines a Monte-Carlo ray-tracing optical model (EDStaR), a photo-electric model (SPICE), and an empirical thermal model. The complete model is calibrated with measurements using an evolutionary algorithm. Once calibrated, the model demonstrates good performance in predicting the module power output as a function of atmospheric and irradiance data.
Antidiabetic medications and mortality reduction: a shift from surrogate to clinical endpoints

journals.sagepub. com/home/tae 173 It was widely believed that antidiabetic medications should improve the macrovascular (such as mortality and myocardial infarction) as well as microvascular endpoints (such as retinopathy and nephropathy) by virtue of improved glycemic control and consequently a reduction of glycated haemoglobin (HbA1C). Therefore, the United States Food and Drug Administration (US FDA) initially considered the reduction of HbA1c as the basis of approval of antidiabetic medications. HbA1c is a surrogate endpoint where it acts as a marker for diabetes control and as for every other endpoint, it is important to demonstrate that it actually correlates with the clinical endpoints and patient safety.
Blast Effector Proteins May Pave the Way for Hyphal Invasion

The rice blast fungus ( Magnaporthe oryzae ) is an economically important pathogen that infects rice, wheat, and other cereal crops. The fungus enters leaves via dome-shaped appressoria that develop from germinated spores and forms invasive hyphae (IH) that undergo pseudohyphal growth inside the
Coxa Magna Following Surgical Treatment of Congenital Hip Dislocation

We studied coxa magna after operative treatment of congenital dislocation of the hip, including incidence, relationship to treatment, and influence of coxa magna on the acetabulum. Coxa magna was defined as a femoral head with a horizontal diameter at least 15% greater than the symmetrical position on the opposite side. Coxa magna developed in 16 hips (33%). The mean increase was 20.9% (range 15–30%). Three factors correlated with coxa magna: femoral osteotomy (100%), open reduction (75%), and operation at a younger age (mean 15.6 vs. 35.8 months). Four of the 16 hips developed coxa magna following Type 1 avascular necrosis; no other growth deformities appeared. At follow-up, the acetabular indices and the center edge angles were not statistically different between the coxa magna and the control groups. One must avoid confusing coxa magna with hip subluxation or inadequate reduction, of which the latter requires appropriate treatment. Coxa magna gives a good hip if a concentric, congruous reduction is obtained, providing the acetabulum has enough growth potential for remodeling.
Nonadditive effects in the partitioning behavior of various aliphatic and aromatic molecules

Predicting the partition behavior of bifunctional molecules from their molecular structure is a challenge because the combination of two or more functional groups often has nonadditive effects. Data presented here and in the literature reveal that isomers of bifunctional compounds can exhibit partition constants that differ by several orders of magnitude. These effects are not limited to compounds with intramolecular H‐bonds. For aliphatic molecules, large effects are found for diones and diesters but not for dioles. For aromatic molecules, large effects are found for compounds with intramolecular H‐bonds and also for p‐isomers with a strong delocalisation of π‐electrons over both functional groups as in p‐nitroaniline and p‐nitrophenol. Interestingly, these nonadditive effects apply not only to the specific interactions but also to the van der Waals interactions of a molecule. This diversity of possible nonadditive effects makes it difficult to predict partitioning of such polyfunctional molecules. Our results suggest that successful models require either an extensive number of correction factors or a quantum chemical approach. Predicting partitioning of bifunctional molecules to environmental systems might face an additional complication. Unlike with solvents, steric limitations of natural phases may prevent them from forming multiple H‐bonds with bifunctional molecules. Our experimental results, however, indicate that this situation does not occur, as the H‐bond‐interaction behavior of bifunctional molecules in humic matter and on quartz was the same as it was in various solvent systems.
Accuracies and Contrasts of Models of the Diffusion-Weighted-Dependent Attenuation of the MRI Signal at Intermediate b-values

The diffusion-weighted-dependent attenuation of the MRI signal E(b) is extremely sensitive to microstructural features. The aim of this study was to determine which mathematical model of the E(b) signal most accurately describes it in the brain. The models compared were the monoexponential model, the stretched exponential model, the truncated cumulant expansion (TCE) model, the biexponential model, and the triexponential model. Acquisition was performed with nine b-values up to 2500 s/mm2 in 12 healthy volunteers. The goodness-of-fit was studied with F-tests and with the Akaike information criterion. Tissue contrasts were differentiated with a multiple comparison corrected nonparametric analysis of variance. F-test showed that the TCE model was better than the biexponential model in gray and white matter. Corrected Akaike information criterion showed that the TCE model has the best accuracy and produced the most reliable contrasts in white matter among all models studied. In conclusion, the TCE model was found to be the best model to infer the microstructural properties of brain tissue.
Computing Generalized Specificity

Most formalisms for representing common-sense knowledge allow incomplete and potentially inconsistent information. When strong negation is also allowed, contradictory conclusions can arise. A criterion for deciding between them is needed. The aim of this paper is to investigate an inherent and autonomous comparison criterion, based on specificity as defined in [POO 85, SIM 92]. In contrast to other approaches, we consider not only defeasible, but also strict knowledge. Our criterion is context-sensitive, i. e. , preference among defeasible rules is determined dynamically during the dialectical analysis. We show how specificity can be defined in terms of two different approaches: activation sets and derivation trees. This allows us to get a syntactic criterion that can be implemented in a computationally attractive way. The resulting definitions may be applied in general rulebased formalisms. We present theorems linking both characterizations. Finally we discuss other frameworks for defeasible reasoning in which preference handling is considered explicitly.
Sensitive PCR Method for Detection of Escherichia coli 0157:H7 and Other Shiga toxin-producing Bacteria in Ground Meat

and Implications Sensitivity of a polymerase chain reaction (PCR) procedure was evaluated for Escherichia coli O157:H7 and Shiga toxin gene (stx) detection in ground beef and ground pork at contamination levels of 0.14, 1.4, and 14 colony forming units per gram (CFU/g) of meat. The PCR procedure, developed during our previous research, amplifies three target genes simultaneously: uidA that is specific for E. coli O157:H7, and stx1 and stx2, the genes for Shiga toxins 1 and 2, respectively. Detection of the uidA gene by the PCR was 91% sensitive in beef and 55% sensitive in pork, and 90% and 71% sensitive for stx gene detection in beef and pork, respectively. In comparison, detection of E. coli O157:H7 by culture, done simultaneously with PCR, was 53% sensitive in beef and 11% sensitive in pork. Results indicate that this PCR procedure is a rapid and sensitive method for STEC and E. coli O157:H7 detection in meat at contamination levels less than 1 CFU/g.
Microvascular density and vascular endothelial growth factor and osteopontin expression during the implantation window in a controlled ovarian hyperstimulation rat model

Vascular endothelial growth factor (VEGF) and osteopontin (OPN) are suggested to facilitate angiogenesis and vascular remodeling in endometrial receptivity. Determination of the endometrial microvascular density (MVD) is the commonest method used to indirectly assess the levels of vasculogenesis and angiogenesis; however, the associations among VEGF, OPN and MVD remain unclear. Controlled ovarian hyperstimulation (COH) with the gonadotrophin-releasing hormone agonist-long protocol may impair endometrial receptivity, and Traditional Chinese Medicine (TCM) may exert therapeutic effects to relieve this impairment. The aim of the present study was to investigate the effects of COH on implantation biology and pregnancy outcome, and to explore the potential therapeutic role of the TCM Zi Dan Yin (ZDY). Female Sprague Dawley rats were divided into four groups: Control, COH, ZDY and COH + ZDY. On days 3, 4 and 5 of pregnancy (D3, D4 and D5, respectively), endometrial MVD was measured with cluster of differentiation 34 immunohistochemical detection, and VEGF and OPN protein and mRNA expression was detected through western blotting and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis. On D10, the average number of implantation sites was observed. Subsequent to conceiving and bearing newborn rats, the number of live births from each group was recorded. COH was shown to have adverse effects on implantation and pregnancy outcome. The MVD was found to be significantly increased in the COH group compared with that in the control, ZDY and COH+ZDY groups. The results of the protein and RT-qPCR analysis of VEGF and OPN revealed the same trend. Conversely, ZDY reversed the changes in endometrial MVD, VEGF and OPN, and was indicated to improve uterine receptivity and pregnancy outcome. No significant difference was observed among the control, ZDY and COH + ZDY groups. In conclusion, since the results for MVD and VEGF and OPN expression were consistent, MVD could be used as an alternative approach to identify the period of receptivity in rats.
fMRI Data Analysis with Dynamic Causal Modeling and Bayesian Networks

Brain, an amazing organ of human body comprises electrical signal that can be helpful for interaction between various brain regions. Functional Magnetic resonance Imaging (fMRI) is a specialized type of Magnetic Resonance Imaging scan. Though nature of fMRI data posses various challenges in the analysis. But, even after all challenges too, it is used as an effective method to diagnose various disease and the relationships between various brain regions. In this paper, we have proposed a model that will result a better fMRI data analysis. The effective interactions among the brain regions can be explored using dynamic causal modeling (DCM) that will help us to understand the functionality of brain up to some extent. Bayesian networks can be used for causal discovery purpose in support with markov blanket which can be evaluated with the help of evaluation metrics.
STIM1–Ca2+ signaling modulates automaticity of the mouse sinoatrial node

Significance Each heartbeat originates in the sinoatrial node (SAN), a collection of specialized cardiomyocytes (SANCs), which exhibit rhythmic action potentials and spontaneous Ca2+ transients. We have found that the Ca2+ sensor protein stromal interaction molecule 1 (STIM1) is enriched in the SANCs. Here we show that STIM1 Ca2+ signaling is important in SANCs to maintain the Ca2+ content of intracellular Ca2+ stores and that this contributes to maintaining the regular sinus rhythm of the heart. Cardiac pacemaking is governed by specialized cardiomyocytes located in the sinoatrial node (SAN). SAN cells (SANCs) integrate voltage-gated currents from channels on the membrane surface (membrane clock) with rhythmic Ca2+ release from internal Ca2+ stores (Ca2+ clock) to adjust heart rate to meet hemodynamic demand. Here, we report that stromal interaction molecule 1 (STIM1) and Orai1 channels, key components of store-operated Ca2+ entry, are selectively expressed in SANCs. Cardiac-specific deletion of STIM1 in mice resulted in depletion of sarcoplasmic reticulum (SR) Ca2+ stores of SANCs and led to SAN dysfunction, as was evident by a reduction in heart rate, sinus arrest, and an exaggerated autonomic response to cholinergic signaling. Moreover, STIM1 influenced SAN function by regulating ionic fluxes in SANCs, including activation of a store-operated Ca2+ current, a reduction in L-type Ca2+ current, and enhancing the activities of Na+/Ca2+ exchanger. In conclusion, these studies reveal that STIM1 is a multifunctional regulator of Ca2+ dynamics in SANCs that links SR Ca2+ store content with electrical events occurring in the plasma membrane, thereby contributing to automaticity of the SAN.
Performance Dependence on Width-to-Length Ratio of Si Cap/SiGe Channel MOSFETs

This paper measures the n- and p-MOSFETs fabricated through 65-nm high- k/metal gate CMOSFET process flow. The [110] channels of the Si cap on SiGe with different width (W) and length (L) ratios were compared with Si-only channels. The results show that a high W-L ratio in the [110] n-channel can alleviate the degradation of biaxial compressive stress. Meanwhile, a low W-L ratio in the p-channel can improve the performance; however, the ratio should at least be below two in this paper. The dominance of the longitudinal or transverse configurations successfully explains this phenomenon because of the reliance of the different levels of piezoresistance coefficient on the channel orientation. The threshold voltage shifts versus the W-L ratio in the p-channel is in agreement with the result. The result is verified by a quantitative current comparison at a high bias in the n-/p-channels between the strained SiGe and Si-only channels, which shows that an extreme W-L ratio in the original biaxially strained SiGe channel can result in longitudinal or transverse strain, thereby leading to different levels of performance degradation/improvement.
Statistical Shape and Probability Prior Model for Automatic Prostate Segmentation

Accurate prostate segmentation in Trans Rectal Ultra Sound (TRUS) images is an important step in different clinical applications. However, the development of computer aided automatic prostate segmentation in TRUS images is a challenging task due to low contrast, heterogeneous intensity distribution inside the prostate region, imaging artifacts like shadow, and speckle. Significant variations in prostate shape, size and contrast between the datasets pose further challenges to achieve an accurate segmentation. In this paper we propose to use graph cuts in a Bayesian framework for automatic initialization and propagate multiple mean parametric models derived from principal component analysis of shape and posterior probability information of the prostate region to segment the prostate. The proposed framework achieves a mean Dice similarity coefficient value of 0.974±0.006, mean mean absolute distance value of 0.49±0.20 mm and mean Hausdorff distance of 1.24±0.56 mm when validated with 23 datasets in a leave-one-patient-out validation framework.
Strategies for a Successful Anatomic Pathology Subspecialty Workgroup

From 1990 to present, 14 liver pathologists and 2 clinical hepatologists from 9 countries have met annually to hold thematic 2.5-day meetings centered on case-based discussion. The goal of these meetings has been to identify gaps in knowledge in our field and fuel scholarly effort to address these gaps. The founding principles were worldwide representation, good representation of women, compatibility of participants, commitment to stable membership and regular attendance, mutual education and friendship, and free exchange of ideas. A summary report of the 2.5-day meeting constituted an enduring document that captured the free flow of ideas discussed. These ideas were open to all participants for the pursuit of scholarship back at their home institutions. However, any idea borne out of an Elves meeting merits open invitation for other Elves to participate in, using established standards for meaningful coauthorship. Over 26 consecutive meetings (1990-2015), themes covered the breadth of liver pathology. With retirement of 2 individuals, resignation of 3, and death of 1, six new members were nominated and voted into membership. Over these same 26 years, active members published 2025 articles indexed in PubMEd Central under the topic “liver;” 3% of these articles represented collaborations between members. This international group represents a successful model in a subspecialty of anatomic pathology for open exchange of ideas, mutual education, and generation of topics worthy of scholarly investigation. We conclude that a self-selected group of subspecialty pathologists can meet successfully over 26 years, maintain a high state of engagement through each annual meeting, self-renew as a result of retirement or resignation, and provide a creative stimulus for highly productive academic careers.
Multi-provider service negotiation and contracting in network virtualization

Network virtualization environment (VNE) affords great business flexibility to the customers and the providers as multiple providers can jointly support a customer's virtual network. Under the current network model, a group of Infrastructure Providers (InPs) peer with each other to provide a packaged deal. Such a business arrangement is not customer-driven, does not promote fair market competition and does not ensure cost minimization. Furthermore, the on-demand nature of virtual networks requires efficient and automated service negotiation and contracting. In this paper, we present V-Mart. To the InPs, V-Mart offers an environment to participate in a faithful and fair competition over the VN resources; and to the SPs, it offers a customer-driven virtual resource partitioning and contracting engine. V-Mart uses a two-stage Vickrey auction model that is strategy-proof, flexible to diverse InP pricing models, and functions over heterogenous multi-commodity market that characterizes the NVE. Through analysis and simulation we show the flexibility and effectiveness of V-Mart.