Miracle-dz/UniFAR-FTUs huggingface dataset:
A Soft Constraints-Based Approach for Reconciliation of Non-Functional Requirements in Web Services-Based Multi-Agent Systems

Over the last years agents have proved to be a powerful mechanism for solving a range of problem sets. In order to fully leverage their power in a multi-agent environment with heterogeneous participants, the establishment of barrier-free communication between different parties is of prime concern. In particular, such an environment may consist of numerous entities, based on different implementations and with different nonfunctional requirements (NFRs), e.g. encryption key length or latency. Currently, interoperability between the involved parties in multi-agent systems is limited as there is no established way of elaborating a common set of NFRs. In this paper, we outline a Web services-based architecture addressing this issue of interoperability in multi-agent systems. Furthermore, we introduce a soft constraints-based approach for modeling and reconciling the NFRs. In particular, Web services serve as a tool for establishing an open system providing reliable communication between a variety of agent implementations and possible non-agent based entities while lacking the limitations of Agent Communication Languages (ACLs), which are asynchronous in nature and closed in implementation. In this way, Web services enable the desired level of openness and robustness needed for maximum interoperability. Adding a soft constraints-based approach to the Web services agent layer provides an extensible and flexible mechanism for the reconciliation of interdependent NFRs. We present a prototype implementation of an open, Web services-based framework optimizing unary soft constraints in a pareto optimal way and therefore enabling barrier-free communication in a multi-agent scenario. Due to its open nature, the framework is applicable to any heterogeneous environment in need of reconciling NFRs. To illustrate its functioning, we briefly demonstrate the framework in the potential use case of a Demand Driven Supply Network (DDSN).
金融危機のミクロ経済分析 = Microeconomic analysis of financial crises

第１部 金融危機の要因と銀行行動（不良債権問題はなぜ長期化したのか；不良債権問題はどのように解消されたのか；銀行の合併は効率性と健全性を改善させたか） 第２部 金融危機と実体経済（銀行の健全性は中小企業の設備投資に影響するか；金融危機はマクロ経済の生産性を低下させるか） 第３部 金融危機と経済政策（銀行のバランスシートは金融政策の有効性に影響するか；金融政策は企業の流動性制約に影響するか；日米の金融危機から得られる教訓は何か）
Exercise Induces Cortical Plasticity after Neonatal Spinal Cord Injury in the Rat

Exercise-induced cortical plasticity is associated with improved functional outcome after brain or nerve injury. Exercise also improves functional outcomes after spinal cord injury, but its effects on cortical plasticity are not known. The goal of this investigation was to study the effect of moderate exercise (treadmill locomotion, 3 min/d, 5 d/week) on the somatotopic organization of forelimb and hindlimb somatosensory cortex (SI) after neonatal thoracic transection. We used adult rats spinalized as neonates because some of these animals develop weight-supported stepping, and, therefore, the relationship between cortical plasticity and stepping could also be examined. Acute, single-neuron mapping was used to determine the percentage of cortical cells responding to cutaneous forelimb stimulation in normal, spinalized, and exercised spinalized rats. Multiple single-neuron recording from arrays of chronically implanted microwires examined the magnitude of response of these cells in normal and exercised spinalized rats. Our results show that exercise not only increased the percentage of responding cells in the hindlimb SI but also increased the magnitude of the response of these cells. This increase in response magnitude was correlated with behavioral outcome measures. In the forelimb SI, neonatal transection reduced the percentage of responding cells to forelimb stimulation, but exercise reversed this loss. This restoration in the percentage of responding cells after exercise was accompanied by an increase in their response magnitude. Therefore, the increase in responsiveness of hindlimb SI to forelimb stimulation after neonatal transection and exercise may be due, in part, to the effect of exercise on the forelimb SI.
Enhanced or Reduced Fetal Growth Induced by Embryo Transfer into Smaller or Larger Breeds Alters Post-Natal Growth and Metabolism in Pre-Weaning Horses

In equids, placentation is diffuse and nutrient supply to the fetus is determined by uterine size. This correlates with maternal size and affects intra-uterine development and subsequent post-natal growth, as well as insulin sensitivity in the newborn. Long-term effects remain to be described. In this study, fetal growth was enhanced or restricted through ET using pony (P), saddlebred (S) and draft (D) horses. Control P-P (n = 21) and S-S (n = 28) pregnancies were obtained by AI. Enhanced and restricted pregnancies were obtained by transferring P or S embryos into D mares (P-D, n = 6 and S-D, n = 8) or S embryos into P mares (S-P, n = 6), respectively. Control and experimental foals were raised by their dams and recipient mothers, respectively. Weight gain, growth hormones and glucose homeostasis were investigated in the foals from birth to weaning. Fetal growth was enhanced in P-D and these foals remained consistently heavier, with reduced T3 concentrations until weaning compared to P-P. P-D had lower fasting glucose from days 30 to 200 and higher insulin secretion than P-P after IVGTT on day 3. Euglycemic clamps in the immediate post-weaning period revealed no difference in insulin sensitivity between P-D and P-P. Fetal growth was restricted in S-P and these foals remained consistently lighter until weaning compared to S-D, with elevated T3 concentrations in the newborn compared to S-S. S-P exhibited higher fasting glycemia than S-S and S-D from days 30 to 200. They had higher maximum increment in plasma glucose than S-D after IVGTT on day 3 and clamps on day 200 demonstrated higher insulin sensitivity compared to S-D. Neither the restricted nor the enhanced fetal environment affected IGF-1 concentrations. Thus, enhanced and restricted fetal and post-natal environments had combined effects that persisted until weaning. They induced different adaptive responses in post-natal glucose metabolism: an early insulin-resistance was induced in enhanced P-D, while S-P developed increased insulin sensitivity.
Determinants of Householdsâ€™ Overdue Loans in Romania

The paperâ€™s target is to identify macroeconomic and financial variables that are relevant for the evolution and forecassting of the householdâ€™s overdue loans in Romania. By employing vector autoregression and systems of ecuations using the SUR methodology, the authors are trying to respond to the following questions: (1) Which are the lags and the individual intensities of the macroeconomic relevant indicators when affecting the household overdue loans rate? ; (2) What are the characteristics of the loans reimbursement behavior in case of shocks on the labor, monetary, goods and services markets? The empirical analysis is based on monthly data which allows for assessing the quality of household loan repayment, both in terms of number of overdue loans and in terms of overdue loan volumes. The relevant explanatory variables were used in various configurations and lags for constructing several macroeconomic credit risk models.
Identification of Seroreactive Proteins of Leptospira interrogans Serovar Copenhageni Using a High-Density Protein Microarray Approach

Background Leptospirosis is a widespread zoonotic disease worldwide. The lack of an adequate laboratory test is a major barrier for diagnosis, especially during the early stages of illness, when antibiotic therapy is most effective. Therefore, there is a critical need for an efficient diagnostic test for this life threatening disease. Methodology In order to identify new targets that could be used as diagnostic makers for leptopirosis, we constructed a protein microarray chip comprising 61% of Leptospira interrogans proteome and investigated the IgG response from 274 individuals, including 80 acute-phase, 80 convalescent-phase patients and 114 healthy control subjects from regions with endemic, high endemic, and no endemic transmission of leptospirosis. A nitrocellulose line blot assay was performed to validate the accuracy of the protein microarray results. Principal findings We found 16 antigens that can discriminate between acute cases and healthy individuals from a region with high endemic transmission of leptospirosis, and 18 antigens that distinguish convalescent cases. Some of the antigens identified in this study, such as LipL32, the non-identical domains of the Lig proteins, GroEL, and Loa22 are already known to be recognized by sera from human patients, thus serving as proof-of-concept for the serodiagnostic antigen discovery approach. Several novel antigens were identified, including the hypothetical protein LIC10215 which showed good sensitivity and specificity rates for both acute- and convalescent-phase patients. Conclusions Our study is the first large-scale evaluation of immunodominant antigens associated with naturally acquired leptospiral infection, and novel as well as known serodiagnostic leptospiral antigens that are recognized by antibodies in the sera of leptospirosis cases were identified. The novel antigens identified here may have potential use in both the development of new tests and the improvement of currently available assays for diagnosing this neglected tropical disease. Further research is needed to assess the utility of these antigens in more deployable diagnostic platforms.
Sparse sound field decomposition using group sparse Bayesian learning

A sparse sound field decomposition method is proposed. Sound field decomposition is the foundation of the various acoustic signal processing applications and enables the estimation of the entire sound field from pressure measurements. The plane wave decomposition, i.e., spatial Fourier analysis, of the sound field has been widely used; however, artifacts originating from spatial aliasing occur above the spatial Nyquist frequency. We have proposed a sparse sound field decomposition method based on a generative model as a sum of monopole source and plane wave components in the context of sound field recording and reproduction. For more accurate and robust decomposition, we propose three different group sparse signal models based on physical properties and a decomposition algorithm by extending sparse Bayesian learning. In simulation experiments, the accuracy of sparse decomposition was improved compared with that of current methods.
Analysis of a bias effect in a tree-based variable importance measure

The research in the field of data mining has widely addressed the problem of variable selection and several variable importance measures have been proposed in the literature. This paper deals with a frequently used variable importance measure defined in the context of decision trees and tree-based ensemble models like Random Forests and Treeboost. The aim of this paper is to show the existence of a bias effect in this importance measure and to discuss its potentially dangerous effects on variable selection. In addition, a heuristic correction strategy is proposed.
Exploring many task computing in scientific workflows

One of the main advantages of using a scientific workflow management system (SWfMS) to orchestrate data flows among scientific activities is to control and register the whole workflow execution. The execution of activities within a workflow with high performance computing (HPC) presents challenges in SWfMS execution control. Current solutions leave the scheduling to the HPC queue system. Since the workflow execution engine does not run on remote clusters, SWfMS are not aware of the parallel strategy of the workflow execution. Consequently, remote execution control and provenance registry of the parallel activities is very limited from the SWfMS side. This work presents a set of components to be included on the workflow specification of any SWMfS to control parallelization of activities as MTC. In addition, these components can gather provenance data during remote workflow execution. Through these MTC components, the parallelization strategy can be registered and reused, and provenance data can be uniformly queried. We have evaluated our approach by performing parameter sweep parallelization in solving the incompressible 3D Navier-Stokes equations. Experimental results show the performance gains with the additional benefits of distributed provenance support.
A Kind of Improved AdaBoost Algorithm

AdaBoost algorithm is a kind of very important feature classification machine learning algorithm, But if difficult samples exist in the training samples, with the iterative Nurnber increasing, this easily leads to degeneration Phenomenon, and reduces the generalization ability of the classifier. In view of the face detection under complex background degeneration appeared problem, This article Proposes LWE-AdaBoost algorithm which can limit weight expansion, the experimental results indicate that the LWE-AdaBoost algorithm can restrain the recurrence of degeneration Phenomenon well.
Testing the randomness in the sky-distribution of gamma-ray bursts

We have studied the complete randomness of the angular distribution of gamma-ray bursts (GRBs) detected by the Burst and Transient Source Experiment (BATSE). Because GRBs seem to be a mixture of objects of different physical nature, we divided the BATSE sample into five subsamples (short1, short2, intermediate, long1, long2) based on their durations and peak fluxes, and we studied the angular distributions separately. We used three methods, Voronoi tesselation, minimal spanning tree and multifractal spectra, to search for non-randomness in the subsamples. To investigate the eventual non-randomness in the subsamples, we defined 13 test variables (nine from the Voronoi tesselation, three from the minimal spanning tree and one from the multifractal spectrum). Assuming that the point patterns obtained from the BATSE subsamples are fully random, we made Monte Carlo simulations taking into account the BATSE's sky-exposure function. The Monte Carlo simulations enabled us to test the null hypothesis (i.e. that the angular distributions are fully random). We tested the randomness using a binomial test and by introducing squared Euclidean distances in the parameter space of the test variables. We concluded that the short1 and short2 groups deviate significantly (99.90 and 99.98 per cent, respectively) from the full randomness in the distribution of the squared Euclidean distances; however, this is not the case for the long samples. For the intermediate group, the squared Euclidean distances also give a significant deviation (98.51 per cent).
Making the Uncontrollable Seem Controllable: the Role of Action in the Illusion of Control

It is well known that certain variables can bias judgements about the perceived contingency between an action and an outcome, making them depart from the normative predictions. For instance, previous studies have proven that the activity level or probability of responding, P(R), is a crucial variable that can affect these judgements in objectively noncontingent situations. A possible account for the P(R) effect is based on the differential exposure to actual contingencies during the training phase, which is in turn presumably produced by individual differences in participants' P(R). The current two experiments replicate the P(R) effect in a free-response paradigm, and show that participants' judgements are better predicted by P(R) than by the actual contingency to which they expose themselves. Besides, both experiments converge with previous empirical data, showing a persistent bias that does not vanish as training proceeds. These findings contrast with the preasymptotic and transitory effect predicted by several theoretical models.
Adapting Paper Prototyping Techniques for Interactive Workspaces

Low-fidelity paper prototyping is a well-known and effective technique for expressing, communicating, and evaluating design ideas for interactive systems [8]. This technique enables and encourages rapid iteration on a design, which can lead to significant usability improvements with minimal investment of time and resources. In our work, we have sought to bring the benefits of paper prototyping to the design of user interfaces for interactive workspaces. The term interactive workspace refers to a pervasive computing environment in which multiple independent devices are networked through a distributed infrastructure. An interactive workspace can be formed by instrumenting a fixed physical workspace (e.g., [4, 9]) or by networking an ad-hoc collection of devices (e.g., [6]).
Finite Element Computations of KPP Front Speeds in Random Shear Flows in Cylinders ∗

We study the Kolmogorov-Petrovsky-Piskunov (KPP) minimal front speeds in spatially random shear flows in cylinders of various cross sections based on variational principle and an associated elliptic eigenvalue problem. We compare a standard finite element method and a two-scale finite element method in random front speed computations. The two-scale method iterates solutions between coarse and fine meshes, and reduces the cost of the eigenvalue computation to that of a boundary value problem while maintaining the accuracy. The two-scale method saves computing time and provides accurate enough solutions. In case of square and elliptical cross sections, our simulation shows that larger aspect ratios of domain cross sections increase the average front speeds in agreement with an asymptotic theory.
Group Oriented Deniable Authentication Protocol

Deniable authenticated protocol is a new cryptographic authentication protocol that enables an intended receiver to identify the source of a given message without being able to prove the identity of the sender to a third party. Therefore, it can be applied to many practical situations. Over the past years, plenty of deniable authentication protocols have been put forth. In this paper, based on the elliptic curve cryptosystem, we would like to propose a novel group oriented deniable authentication protocol. In our proposed protocol, the number of the senders reaches the qualified threshold value, and then these senders can send a deniable authentication message to an intended receiver
A Novel Approach for Intelligent Robot Path Planning

Path planning of Robot is one of the challenging fields in the area of Robotics research. In this paper, we proposed a novel algorithm to find path between starting and ending position for an intelligent system. An intelligent system is considered to be a device/robot having an antenna connected with sensor-detector system. The proposed algorithm is based on Neural Network training concept. The considered neural network is Adapti ve to the knowledge bases. However, implementation of this algorithm is slight ly expensive due to hardware it r equires. From detailed analysis, it can be proved that the resulted path of this algorithm is efficient.
HER2 Expression in Fine Needle Aspirates of Lymph Nodes Detected by Preoperative Axillary Ultrasound in Breast Cancer Patients

The purpose of this study was to assess the usefulness of HER2 levels in ultrasonographically guided fine-needle aspiration biopsy (US-FNA) aspirates of axillary lymph nodes (ALNs) in the determination of lymph node metastasis or the characterization of primary breast cancer, and to correlate the HER2 levels in US-FNA aspirates (FNA-HER2s) of metastatic ALNs with the HER2 statuses of corresponding primary breast cancers. An institutional review board approved the study. Between January and October 2010, 164 patients with 167 ALNs examined by US-FNA were included. FNA-HER2s of ALNs were measured by chemiluminescence immunoassay, and they were correlated with cytologic/final diagnoses. Receiver operating characteristics (ROC) curve analysis was performed to evaluate the diagnostic ability to differentiate benign and metastatic ALNs. Additionally, FNA-HER2s of metastatic ALNs were correlated with HER2 status and other clinicopathologic variables of the primary breast cancers. Among the 167 ALNs, 138 were metastatic and 29 were benign. The mean FNA-HER2 (6.3 ng/ml) of metastatic ALNs was higher than that of benign ALNs. All 29 benign ALNs showed no measurable value of FNA-HER2 (0.0 ng/ml). The area under the ROC curves of FNA-HER2 of ALNs was 0.679 for the diagnosis of ALN metastasis. The FNA-HER2 statuses of 108 metastatic ALNs (79.4%) were concordant with the HER2 statuses of the corresponding primary breast cancers. In a subgroup analysis of HER2-positive cancers with ALN metastasis, distant metastasis was significantly associated with FNA-HER2-negativity of metastatic ALNs (P = 0.04). Although FNA-HER2 of ALNs did not improve the diagnostic performance of FNA cytology in preoperative diagnosis of ALN metastasis of overall patients, FNA-HER2-positive metastatic ALNs were significantly associated with HER2-positivity of primary breast cancers. Additionally, FNA-HER2 analysis of ALN may help to develop more personalized treatment protocol for breast cancer patients by determining the concordance or discordance of HER2 status between primary cancers and metastatic ALNs.
Injection efficiency of DI and CTIA readout integrated circuit

Advanced hybrid infrared focal plane arrays (IRFPA) consist of a semiconductor photodetector chip which is bump-bonded to a silicon CMOS readout integrated circuit (ROIC) chip generally containing a reset integrator preamp to accumulate detector photon-induced current over a fixed integration time. A number of readout structures have been developed for different system applications and concerns, among which the direct injection (DI) and the capacitor feedback transimpedance amplifier (CTIA) are popularly used. The structures and performances, especially injection efficiency, of DI and CTIA are respectively discussed and compared. The DI enables an ultralow power consumption and has a high injection efficiency at large background photocurrent, while the CTIA has a comparatively higher power dissipation and higher injection efficiency at low background photocurrent.
Hyperbolic Discounting, Reference Dependence and Its Implications for the Housing Market

The influential work of Genesove and Mayer (2001) uses loss aversion theory to explain several puzzling behaviors in the housing market. In this study, we present an alternative theory, which does not require an asymmetric value function, to observe the same "loss aversion" behavior. Specifically, this paper presents a model in which a reference-dependent home seller has a symmetric value function, but faces an inter-temporal decision problem. Furthermore, the framework presented in this paper also helps explain the positive price-volume relationship and price dispersion effect, two observations that are well-documented in the housing market.
Computer-aided grading of lymphangioleiomyomatosis (LAM) using HRCT

Lymphangioleiomyomatosis (LAM) is a multisystem disorder associated with proliferation of smooth muscle-like cells, which leads to destruction of lung parenchyma. Subjective grading of LAM on HRCT is imprecise and can be arduous especially in cases with severe involvement. We propose a computer-aided evaluation system that grades LAM involvement based on analysis of lung texture patterns. A committee of support vector machines is employed for classification. The system was tested on 36 patients. The computer grade demonstrates good correlation with subjective radiologist grade (R=0.91, p¿0.0001) and pulmonary functional tests (R=0.85, p¿0.0001). The grade also provides precise progression assessment of disease over time.