Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-criteria decision quality optimization as a Scheduling problem

Decision quality under uncertainty is a problem that has been addressed by many researchers. But most of the works dedicated to this problem assume that there is a single quality measure to computation based on the status of an n-tuple of criteria. However, in most of real-world applications the quality is multi-criteria where each criterion captures a dimension of value in the solution. In this paper, we present a decision maker that manipulates the quality as a vector of criteria where the improvement of each criterion is in charge of a progressive processing agent that uses its hierarchy of processing levels to improve the quality of this criterion incrementally. We discuss the problem of optimizing the decision of sequencing processing levels of agents by transforming it to an MDP. We also present the strategy to be adopted when considering the criteria preferences. Finally, we discuss how this approach can be applied to controlling a static set of dependent progressive processing agents where there is no predetermined sequence of agents.
Integration of Spatial Technologies and Semantic Web Technologies for Industrial Archaeology

We propose a method that uses the advancement in spatial technologies from current database systems within the Semantic Web Technologies in order to enrich and to populate the knowledge of a domain defined in an OWL-DL ontology. The results of spatial operations and functions are used to populate and to enrich ontologies with new individuals and new relationships. The advantage of spatial analysis within Semantic Web technologies is the diversity of the functionalities provided by the combination of spatial operations and the rule language of the Semantic Web (SWRL). This method is applied in the industrial archaeology domain in order to enhance the knowledge management.
RESEARCH CONSORTIUM AS COLLECTIVE STRATEGY

Recent management literature on R&D partnerships focuses on relationships between industrial firms or private and public research organizations. This is of particular importance in the context of public policy incentives and socio-economic considerations of innovation. The main research objects are technological partnerships, cooperative strategies, jointventures or strategic alliances. These studies leave unanswered the case of public scientific collaborations, hardly comparable to industrial R&D consortia tackled in abundant specific literature. To better understand this new research object, we consider it as an agglomerate collective strategy through a study case of the ATLAS collaboration, a particle physics experiment at CERN in Geneva, Switzerland. First, we will show that the high stakes of a unique particle physics experiment, well beyond current scientific limits, leads actors to collaborate together and share resources. Secondly, we will show that a loosely coupled institutional framework constitutes the corner stone for the effective functioning of agglomerate collective strategy.
Monte Carlo Simulation of Economic Capital Requirement & Default Protection Premium

This paper presents a simulation framework for measuring and managing the default risk of a loan portfolio. The economic capital requirement is explored for a hypothetical credit portfolio through the dependency of counterparty default on a systematic risk factor. The study employs bivariate standard normal distribution for mapping asset return correlations into default correlations. Monte Carlo simulations are employed to approximate the loss distribution and estimate various risk measures. The analysis performed shows that the Asymptotic Single Risk Factor (ASRF) model is a fast way for generating heavy-tailed credit loss distributions. Further, complete analytic derivation of Basel II-IRB risk weight functions are reported. The paper also comments on the pricing of single-period Portfolio Default Swaps.
Pharmacological Modulation by Shakuyakukanzoto (Shao-Yao-Gan-Cao-Tang) and the Ingredients in Rat Intestinal Smooth Muscle

Shakuyakukanzoto (Shao-Yao-Gan-Cao-Tang), a formulation of Japanese herbal (Kampo) medicines, is composed of Paeoniae Radix and Glycyrrhizae Radix. Effects of Shakuyakukanzoto and the ingredients on rat intestinal tract were examined. Shakuyakukanzoto (0.01 - 0.3 mg/ml) relaxed a carbachol (CCh, 0.3 μM) - induced contraction in a concentration-dependent manner. Both components (Paeoniae radix and Glycyrrhizae radix) also relaxed the CCh-induced contraction. At 0.1 to 1 mM, their constituents (paeoniflorin and glycyrrhetic acid) and the metabolic products (18-α- and 18-β-glycyrrhetinic acids) exerted almost the same actions. The relaxations induced by Shakuyakukanzoto were not modified by 1 μM nicardipine, 10 μM suramin (ATP receptor inhibitor) and several K+ channel inhibitors, but was attenuated by 20 μM IBMX (a phosphodiesterase inhibitor). Also, IBMX inhibited the relaxations induced by paeoniflorin and glycyrrhetic acid, but not by other ingredients. Nicardipine decreased the relaxation of just 18-α-glycyrrhetinic acid. Even in non-treatment with CCh, Shakuyakukanzoto relaxed the intestinal tract. CCh (0.3 μM) elicited spontaneous contractions in 23% specimens, depressed by application of Shakuyakukanzoto. These results indicate that Shakuyakukanzoto causes a remarkable relaxation by the anti-cholinergic and the PDE inhibitory actions, but by minor contribution of Ca2+ channel inhibition. Thus, Shakuyakukanzoto exerts an anti-spasmodic action due to the interaction with pharmacological effects of its ingredients.
HIV-Antiretroviral Therapy Induced Liver, Gastrointestinal, and Pancreatic Injury

The present paper describes possible connections between antiretroviral therapies (ARTs) used to treat human immunodeficiency virus (HIV) infection and adverse drug reactions (ADRs) encountered predominantly in the liver, including hypersensitivity syndrome reactions, as well as throughout the gastrointestinal system, including the pancreas. Highly active antiretroviral therapy (HAART) has a positive influence on the quality of life and longevity in HIV patients, substantially reducing morbidity and mortality in this population. However, HAART produces a spectrum of ADRs. Alcohol consumption can interact with HAART as well as other pharmaceutical agents used for the prevention of opportunistic infections such as pneumonia and tuberculosis. Other coinfections that occur in HIV, such as hepatitis viruses B or C, cytomegalovirus, or herpes simplex virus, further complicate the etiology of HAART-induced ADRs. The aspect of liver pathology including liver structure and function has received little attention and deserves further evaluation. The materials used provide a data-supported approach. They are based on systematic review and analysis of recently published world literature (MedLine search) and the experience of the authors in the specified topic. We conclude that therapeutic and drug monitoring of ART, using laboratory identification of phenotypic susceptibilities, drug interactions with other medications, drug interactions with herbal medicines, and alcohol intake might enable a safer use of this medication.
Modeling Producer Decisions on Land Use in Spatial Continuum

The paper describes how stochastic optimization techniques can be used to model profit maximizing producer behavior in a spatial continuum. The main methodological issues to be addressed are, first, that the representation of optimal allocations in a spatial continuum naturally lead to models that contain integrals over space, and the second that the resulting model tends to have a multi-level structure, i.e. requires solving nested optimization problems because it should combine the profit maximization by individual producers with market clearing at regional level. We specify four regional model that may illustrate the approach. The first determines the optimal output level for factories that emit pollutants which reduce the crop output of neighboring farmers. The main issue is to compute the associated level of compensation to be paid by the factories to the farmers. The second model deals with optimal zoning. It computes the optimal crop routing for farmers who can choose to sell their crop to factories situated at given locations. This is an optimization problem in functional space, which can be reformulated as a dual stochastic optimization problem. In the their model, the farmer has the possibility of routing his crop along different roads or distribution nodes to the various factories for processing. It can describe the optimal choice of distribution centers at given locations, around plants or cities, and produces optimal boundaries for the zones that supply to or buy from these centers. The fourth model deals with the problem optimal land consolidation, distinguishes between consolidation processes with and without side-payments. To each of these four models we associate a decentralized, stochastic quasi-gradient (SQG-)procedure for attaining the global) optimum, which has a natural interpretation as a device for decentralized adaptive planning.
Iron economy in Chlamydomonas reinhardtii

While research on iron nutrition in plants has largely focused on iron-uptake pathways, photosynthetic microbes such as the unicellular green alga Chlamydomonas reinhardtii provide excellent experimental systems for understanding iron metabolism at the subcellular level. Several paradigms in iron homeostasis have been established in this alga, including photosystem remodeling in the chloroplast and preferential retention of some pathways and key iron-dependent proteins in response to suboptimal iron supply. This review presents our current understanding of iron homeostasis in Chlamydomonas, with specific attention on characterized responses to changes in iron supply, like iron-deficiency. An overview of frequently used methods for the investigation of iron-responsive gene expression, physiology and metabolism is also provided, including preparation of media, the effect of cell size, cell density and strain choice on quantitative measurements and methods for the determination of metal content and assessing the effect of iron supply on photosynthetic performance.
Determinants of the wage share: a cross-country comparison using sectoral data

There has been a significant decline in the share of wages in GDP in both developed and developing countries since the 1980s. This paper analyses the determinants of the wage share (labour compensation as a ratio to value added) using sectoral data with country specific estimations for selected OECD countries. We compile a comprehensive sector-level dataset of eight OECD countries (Denmark, France, Germany, Italy, Spain, Sweden, the UK, the US) for the period of 1970 to 2011, which allows us to trace the developments in the wage share across high and low skilled sectors and within manufacturing and service industries. Our findings provide new insights with regard to the drivers of falling wage share. By conducting country specific estimations, we analyse how institutional differences in industrial relations, as well as social security and welfare regimes affect the wage share. Our findings lend strong support to the political economy approach to functional income distribution. Technological change had an impact, especially in Italy, the US and for the total country sample, but the effects are not robust with respect to the use of different specifications and the wage share in most countries in our sample appears to be driven by variables reflecting the bargaining power of labour such as union density, adjusted bargaining coverage and government spending. The relevance of these variables differs considerably across countries, lending support to our approach of country specific estimations. We find that globalisation had a strong impact on the wage share in all countries. The effect of globalisation on the wage share was least strong in Denmark. In Germany, and to a lesser extent in the UK, the effect is due to outward FDI and intermediate import penetration which reflects the impact of international outsourcing practices. Intermediate imports penetrations had no significant impact in Spain while FDI played a smaller role in France and the US. Different institutional variables appear to be relevant for each country. Germany exhibits the most robust positive effect of union density on the wage share. Conversely, collective bargaining coverage, together with social government spending, plays a more important role in France, the UK and the US. Financialisation had the most pronounced effect in the UK and the US, while it appears to be also relevant in Germany. We find mixed results for the effect of personal income inequality on the wage share. However, there is indicative confirmation for a negative effect in Germany, the UK and the US.
Non-negative pre-image in machine learning for pattern recognition

Moreover, in order to have a physical interpretation, some constraints should be incorporated in the signal or image processing technique, such as the non-negativity of the solution. This paper deals with the non-negative pre-image problem in kernel machines, for nonlinear pattern recognition. While kernel machines operate in a feature space, associated to the used kernel function, a pre-image technique is often required to map back features into the input space. We derive a gradient-based algorithm to solve the pre-image problem, and to guarantee the non-negativity of the solution. Its convergence speed is significantly improved due to a weighted stepsize approach. The relevance of the proposed method is demonstrated with experiments on real datasets, where only a couple of iterations are necessary.
Extensible JT Open Tool for prototypical process support, based on OpenSceneGraph and QT

In today's globalized markets, effectivity in the way that product development information is communicated and transparently interpreted by a diversity of divisions and disciplines in an enterprise has an essential impact on the key factors time, cost and quality. Against the background of current activities in the automotive industry, we have conducted a process chain analysis at multiple OEMs and suppliers, analyzing application potentials of JT as the format of origin specifically for CAx processes, such as Digital Mock-Up, Simulation and Downstream production. In this context, a simple application to investigate and manipulate JT data in terms of structure and properties would provide the means for prototypical integration tests. Connecting containers available in the JT Open Toolkit to those provided in the OpenSceneGraph (OSG) graphics toolkit, the fundamentals of such an application were developed and are presented in this paper.
Anticipatory pleasure predicts effective connectivity in the mesolimbic system

Convergent evidence suggests the important role of the mesolimbic pathway in anticipating monetary rewards. However, the underlying mechanism of how the sub-regions interact with each other is still not clearly understood. Using dynamic causal modeling, we constructed a reward-related network for anticipating monetary reward using the Monetary Incentive Delay Task. Twenty-six healthy adolescents (Female/Male = 11/15; age = 18.69 ± 1.35 years; education = 12 ± 1.58 years) participated in the present study. The best-fit network involved the right substantia nigra/ventral tegmental area (SN/VTA), the right nucleus accumbens (NAcc) and the right thalamus, which were all activated during anticipation of monetary gain and loss. The SN/VTA directly activates the NAcc and the thalamus. More importantly, monetary gain modulated the connectivity from the SN/VTA to the NAcc and this was significantly correlated with subjective anticipatory pleasure (r = 0.649, p < 0.001). Our findings suggest that activity in the mesolimbic pathway during the anticipation of monetary reward could to some extent be predicted by subjective anticipatory pleasure.
Local quantum phase transition in the pseudogap Anderson model: scales, scaling and quantum critical dynamics

The pseudogap Anderson impurity model provides a paradigm for understanding local quantum phase transitions, in this case between generalised Fermi liquid (GFL) and degenerate local moment phases. Here we develop a non-perturbative local moment approach to the generic asymmetric model, encompassing all energy scales and interaction strengths and leading thereby to a rich description of the problem. We investigate in particular underlying phase boundaries, the critical behaviour of relevant low-energy scales, and single-particle dynamics embodied in the local spectrum D(ω). Particular attention is given to the resultant universal scaling behaviour of dynamics close to the transition in both the GFL and LM phases, the scale-free physics characteristic of the quantum critical point itself, and the relation between the two.
Fe b 20 18 Ward Identity and Scattering Amplitudes for Nonlinear Sigma Models

We present a Ward identity for nonlinear sigma models using generalized nonlinear shift symmetries, without introducing current algebra or coset space. The Ward identity constrains correlation functions of the sigma model such that the Adler’s zero is guaranteed for S-matrix elements, and gives rise to a subleading single soft theorem that is valid at the quantum level and to all orders in the Goldstone decay constant. For tree amplitudes, the Ward identity leads to a novel BerendsGiele recursion relation as well as an explicit form of the subleading single soft factor. Furthermore, interactions of the cubic biadjoint scalar theory associated with the single soft limit, which was previously discovered using the Cachazo-He-Yuan representation of tree amplitudes, can be seen to emerge from matrix elements of conserved currents corresponding to the generalized shift symmetry.
What matters for life satisfaction among the oldest-old? Evidence from China

Objective The world population is aging rapidly and the well-being of older people is of great interest. Therefore, this study investigates the determinants of life satisfaction among the oldest-old (i.e. individuals aged 80 or over) in China. Materials and methods We use the 2011/2012 Chinese Longitudinal Healthy Longevity Survey data (n = 6530) for this paper. Logistic regression is used to analyse the effects of socio-demographic, economic, health, instrumental activities of daily living, family and community factors on life satisfaction and depression among the oldest-old in China. Results Our analysis confirms the significance of many factors affecting life satisfaction among the oldest-old in China. Factors that are correlated with life satisfaction include respondent’s sex, education, place of residence, self-rated health status, cognitive ability (using mini mental state examination), regular physical examination, perceived relative economic status, access to social security provisions, commercialized insurances, living arrangements, and number of social services available in the community (p<0.05 for all these variables). Although life satisfaction is negatively associated with instrumental activities of daily living (β = -0.068, 95%CI = -.093—.043), and depression (β = -0.463, 95%CI = -.644—.282), the overall effect of self-rated health status is positive (p<0.001). This confirms the primacy of health as the determinant of well-being among the oldest-old. Conclusions Majority of the oldest-old in China rated their life satisfaction as good or very good. Our findings show that health and economic status are by far the most significant predictors of life satisfaction. Our finding on the primacy of health and relative income as determinants of well-being among the oldest-old, and the greater influence of self-rated health status over objective health measures is consistent with the findings of many past studies. Our results suggest that efforts should be directed at enhancing family support as well as health and social service provisions in the community to improve life satisfaction of older people.
Immunomodulation and Anti-Inflammatory Effects of Garlic Compounds

The benefits of garlic to health have been proclaimed for centuries; however, only recently have Allium sativum and its derivatives been proposed as promising candidates for maintaining the homeostasis of the immune system. The complex biochemistry of garlic makes it possible for variations in processing to yield different preparations with differences in final composition and compound proportion. In this review, we assess the most recent experimental results, which indicate that garlic appears to enhance the functioning of the immune system by stimulating certain cell types, such as macrophages, lymphocytes, natural killer (NK) cells, dendritic cells, and eosinophils, by mechanisms including modulation of cytokine secretion, immunoglobulin production, phagocytosis, and macrophage activation. Finally, because immune dysfunction plays an important role in the development and progress of several diseases, we critically examined immunoregulation by garlic extracts and compounds isolated, which can contribute to the treatment and prevention of pathologies such as obesity, metabolic syndrome, cardiovascular disorders, gastric ulcer, and even cancer. We concluded that A. sativum modulates cytokine secretion and that such modulation may provide a mechanism of action for many of their therapeutic effects.
UvA-DARE ( Digital Academic Repository ) Learning compositional semantics for open domain semantic parsing

This paper introduces a new approach to learning compositional semantics for open domain semantic parsing. Our approach is called Dependency-based Semantic Composition using Graphs (DeSCoG) and deviates from existing approaches in several ways. First, we remove the need of the lambda calculus by using a graph-based variant of Discourse Representation Structures to represent semantic building blocks and defining new combinatory operations for our graph structures. Second, we propose a probability model to approximate probability distributions over possible semantic compositions. And third, we use a variant of alignment algorithms from machine translation to learn a lexicon. On the Groningen Meaning Bank (a recently released, large-scale, domain-general, semantically annotated corpus; Basile et al. (2012)), where we preprocess sentences with an existing dependency parser, we achieve results significantly better than the baseline. On Geoquery we obtain performance comparable to semantic parsers that were developed specifically for that domain. Title and Abstract in Vietnamese Học Tổng hợp Ngữ nghĩa cho Phân tích Ngữ nghĩa Miền Mở Bài báo này giới thiệu một phương pháp mới cho học tổng hợp ngữ nghĩa trong phân tích ngữ nghĩa miền mở. Phương pháp của chúng tôi được gọi là Dependency-based Semantic Composition using Graphs (DeSCoG) và khác biệt với các phương pháp có sẵn trên nhiều phương diện. Trước tiên, chúng tôi loại bỏ sự cần thiết của phép tính lambda bằng cách dùng một biến thể dựa trên đồ thị cho Discourse Representation Structure để miêu tả các khối ngữ nghĩa và định nghĩa các phép kết hợp cho những đồ thị này. Thứ hai, chúng tôi đề xuất một mô hình xác suất để xấp xỉ những phân bố xác suất trên các ngữ nghĩa tổng hợp có thể có. Và thứ ba, chúng tôi dùng một biến thể của các thuật toán gióng hàng từ dịch máy để học tập từ vựng. Thực nghiệm trên Groningen Meaning Bank (một ngữ liệu vừa được công bố, lớn, tổng quát, và đã được gán nhãn ngữ nghĩa; Basile et al. (2012)), với các câu được tiền xử lý bằng một bộ phân tích phụ thuộc có sẵn, chúng tôi đạt được kết quả tốt hơn rất nhiều so với phương pháp cơ sở. Đối với Geoquery, chúng tôi có được kết quả tương đương với các bộ phân tích ngữ nghĩa được phát triển cho chính lĩnh vực đó.