Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of SVM in Financial Research

Based on the structural risk minimization, support vector machine is a new method of data mining. Since it has effectively solved complicated problems of classification and prediction, it has been widely used in many cross-disciplinary fields. This paper has reviewed and analyzed SVM’s application to the classification and prediction in the financial field. It has a promising future of applying to company's credit rating, early warning, stock prices forecast and so on. However, we hold that the correct selection of kernel and different sub-assembly function, as well as parameters, is the key point to optimize the application of SVM.
Effect of Dehydroepiandrosterone Administration in Patients with Poor Ovarian Response According to the Bologna Criteria

Background Dehydroepiandrosterone (DHEA) is now widely used as an adjuvant to IVF treatment protocols in poor responders. However, clinical evidence for DHEA on improvement of ovarian response and IVF outcome is still limited, the validity of the results of the earlier studies, especially the varied inclusion criteria, is a subject of debate. Recently, the ESHRE Working Group developed a new definition, the Bologna criteria. The aim of the current study was to investigate the potential effect of DHEA treatment on in vitro fertilization (IVF) outcome of poor ovarian responders that fulfill the Bologna criteria. Methods This study investigated 386 poor ovarian responders that fulfill the Bologna criteria. Patients underwent IVF-ET treatment with the GnRH antagonist protocol. The study group contained 189 patients, who received 75 mg of DHEA daily (25 mg three times daily) before the IVF cycle. The control group was composed of 197 patients who received infertility treatment, but did not receive DHEA. The IVF outcome parameters in each group were compared. Results The study and control groups did not show statistically significant differences in terms of patient demographics characteristics, mean numbers of oocytes retrieved, mature oocytes, fertilization rate, cleavage rate, or embryo availability. While the DHEA group demonstrated significantly higher implantation rates (18.7% vs. 10.1%; P<0.01) and ongoing PRs (26.7% vs. 15.8%; P<0.05) as compared with the control. Conclusions DHEA pre-treatment does not significantly increase oocyte yield. However, the ongoing PRs in this subgroup of women are significantly higher after DHEA administration, suggesting that DHEA may increase IVF results by improving oocyte and embryo quality.
Protection against Dengue Virus Infection in Mice by Administration of Antibodies against Modified Nonstructural Protein 1

Background Infection with dengue virus (DENV) may cause life-threatening disease with thrombocytopenia and vascular leakage which are related to dysfunction of platelets and endothelial cells. We previously showed that antibodies (Abs) against DENV nonstructural protein 1 (NS1) cross-react with human platelets and endothelial cells, leading to functional disturbances. Based on sequence homology analysis, the C-terminal region of DENV NS1 protein contains cross-reactive epitopes. For safety in vaccine development, the cross-reactive epitopes of DENV NS1 protein should be deleted or modified. Methodology/Principal Findings We tested the protective effects of Abs against full-length DENV NS1, NS1 lacking the C-terminal amino acids (a.a.) 271-352 (designated ΔC NS1), and chimeric DJ NS1 consisting of N-terminal DENV NS1 (a.a. 1-270) and C-terminal Japanese encephalitis virus NS1 (a.a. 271-352). The anti-ΔC NS1 and anti-DJ NS1 Abs showed a lower binding activity to endothelial cells and platelets than that of anti-DENV NS1 Abs. Passive immunization with anti-ΔC NS1 and anti-DJ NS1 Abs reduced DENV-induced prolonged mouse tail bleeding time. Treatment with anti-DENV NS1, anti-ΔC NS1 and anti-DJ NS1 Abs reduced local skin hemorrhage, controlled the viral load of DENV infection in vivo, synergized with complement to inhibit viral replication in vitro, as well as abolished DENV-induced macrophage infiltration to the site of skin inoculation. Moreover, active immunization with modified NS1 protein, but not with unmodified DENV NS1 protein, reduced DENV-induced prolonged bleeding time, local skin hemorrhage, and viral load. Conclusions/Significance These results support the idea that modified NS1 proteins may represent an improved strategy for safe and effective vaccine development against DENV infection.
Downregulation of cystathionine β‐synthase and cystathionine γ‐lyase expression stimulates inflammation in kidney ischemia–reperfusion injury

Inflammation plays a critical role in kidney ischemia–reperfusion injury but mechanisms of increased proinflammatory cytokine expression are not completely understood. Kidney has a high expression of cystathionine‐β‐synthase (CBS) and cystathionine‐γ‐lyase (CSE) that can synthesize hydrogen sulfide. CBE and CSE are also responsible for the synthesis of cysteine, an essential precursor for glutathione, an antioxidant. Reduced hydrogen sulfide and glutathione production is associated with multiple organ injury. Although pro‐ and anti‐inflammatory effects of hydrogen sulfide have been reported, its role in ischemia–reperfusion‐induced inflammation in the kidney has not been well addressed. The aim of this study was to investigate the effect of CBS and CSE‐mediated hydrogen sulfide and glutathione production on kidney inflammatory response and the mechanism involved. The left kidney of Sprague‐Dawley rat was subjected to 45‐min ischemia followed by reperfusion for 24 h. Ischemia–reperfusion caused a significant decrease in CBS and CSE mRNA and protein levels with a concomitant reduction of glutathione and hydrogen sulfide production in the kidney while the expression of proinflammatory cytokine expression (MCP‐1, IL‐6) was elevated. Hypoxia–reoxygenation of proximal tubular cells led to a decrease in CBS and CSE expression and an increase in proinflammatory cytokine expression. Supplementation of glutathione or hydrogen sulfide donor (NaHS) effectively attenuated cytokine expression in tubular cells. These results suggested that ischemia–reperfusion impaired CBS and CSE‐mediated glutathione and hydrogen sulfide production in the kidney, which augmented the expression of proinflammatory cytokines. Regulation of CBS and CSE expression may be therapeutically relevant in alleviating ischemia–reperfusion‐induced inflammation and improving kidney function.
Watching Players: An Exploration of Media Enjoyment on Twitch

Video game streaming platforms have reached high popularity within the last years. As one of these popular platforms, Twitch provides users with the opportunity to participate in several gaming situations: They can simultaneously watch in-game actions, the streamer playing the game, and additionally, they can interact with the streamer and other viewers by using the chat. In an online survey, the current study explored how individuals (N = 548) experience media enjoyment when using Twitch. Findings indicate that social aspects of using Twitch predominantly contribute to enjoyment. Approaches toward the phenomenon of video game streaming as well as implications for research on the usage of second screens and Social TV are discussed.
DOWNLINK AND UPLINK CAPACITY ENHANCEMENT IN POWERCONTROLLED CELLULAR

I. ABSTRACT The joint power control and base station assignment for downlink is considered in this paper. We present an algorithm that nds a feasible joint base assignment and power control in the downlink which uses the base assignment that is computed by the joint algorithm in the uplink. We show that under some conditions the algorithm also minimizes the sum of downlink powers. Interestingly , there is not always a Pareto optimal power vector for the joint problem in the downlink as is the case in the uplink. This fact is demonstrated through a counter example. The objective of power control in wireless networks is to minimize transmitted powers subject to maintaining the link quality by keeping the signal to noise ratio (SNR) above a threshold called minimum protection ratio. The power allocation and base station assignment can be integrated to attain higher capacity and achieve smaller allocated powers. In a network with power control capability , as the mobiles move or new calls arrive, the reassignment of mobiles to base stations helps to nd a feasible power allocation and provides a framework for handoo. In 1], 2] the combined base station assignment and power allocation was proposed for uplink. In those papers , algorithms were proposed to achieve the optimal base assignment and power allocation such that the mobile powers are minimal among all feasible assignments. In 3] it has been observed that for xed assignment the feasibility of uplink and downlink are equivalent. In this paper we consider the joint power control and base station assignment for downlink. It is interesting to note that unlike the xed assignment, in the joint problem the uplink and downlink are substantially diierent. While in the uplink there is a Pareto optimal solution for the power control and base station assignment, this is not the case for the downlink. We will demonstrate this fact through a counter example. Regarding the joint problem in the downlink we will show that the sequence of base station assignment for the joint uplink power control and base station assignment converges to a feasible assignment for the downlink. We use the same iterations to update the downlink power, and we will prove that this algorithm converges to a feasible downlink power allocation and base station assignment when there exists any. We will also show that when the interference is only due to thermal noise and cochannels, …
Recursive sparse recovery in large but structured noise — Part 2

We study the problem of recursively recovering a time sequence of sparse vectors, S<sub>t</sub>, from measurements M<sub>t</sub> := S<sub>t</sub> + L<sub>t</sub> that are corrupted by structured noise L<sub>t</sub> which is dense and can have large magnitude. The structure that we require is that L<sub>t</sub> should lie in a low dimensional subspace that is either fixed or changes “slowly enough” and the eigenvalues of its covariance matrix are “clustered”. We do not assume any model on the sequence of sparse vectors. Their support sets and their nonzero element values may be either independent or correlated over time (usually in many applications they are correlated). The only thing required is that there be some support change every so often. We introduce a novel solution approach called Recursive Projected Compressive Sensing with cluster-PCA (ReProCS-cPCA) that addresses some of the limitations of earlier work. Under mild assumptions, we show that, with high probability, ReProCS-cPCA can exactly recover the support set of S<sub>t</sub> at all times; and the reconstruction errors of both S<sub>t</sub> and L<sub>t</sub> are upper bounded by a time-invariant and small value.
The GENiC Architecture for Integrated Data Centre Energy Management

We present an architecture for integrated data centre energy management developed in the EC funded GENiC project. The architecture was devised to create a platform that can integrate functions for workload management, cooling, power management and control of heat recovery for future, highly efficient data centres. The architecture is based on a distributed systems approach that allows the integration of components developed by several entities through defined interfaces and data formats. We also present use cases for the architecture, a brief description of the project's prototypical implementation, evaluation metrics and some lessons learned.
Glycemic behavior in patients with type 2 diabetes during a short period of a combined training program

Aim: The present study investigated the behavior of glycemia in subjects with type 2 diabetes (T2DM) during 36 sessions of a combined training program. Methods: This is a single arm clinical study with 20 patients with T2DM submitted to combined exercise training (strength and aerobic exercise). The sessions occurred on alternate days, 3x/week, lasting ~ 80 minutes, totaling ~ 240 minutes/week, for 12 weeks, over a total of 36 sessions. Capillary glycemia was measured before and 10 to 15 minutes after the end of each combined exercise session. Results: There was a significant reduction (p<0.05) in glycemia after application of the combined training program in 27 (75%) of the 36 sessions. Regarding the maintenance of this reduction after about 48 hours, no significant differences were identified (p>0.05). When investigating the cumulative effect of the 36 sessions of combined training program on capillary glycemia, no significant differences were observed (p>0.05). Conclusion: Glycemia exhibits a behavior of reduction immediately after concurrent strength and aerobic training programs in patients with T2DM. However, the immediate reduction of glycemia is not maintained until 48 hours, nor is there a cumulative effect of the 36 training sessions on baseline glycemia.
Mesh parameter optimization for images colorization scheme

Colorization is a process of adding color to a monochrome image or movie. In order to color the grayscale images and minimize the amount of human labor required. Welsh is to transfer color to a grayscale image from a color image. Though the method is simple and easy to realize, the shortcoming is that the speed is relatively slow, and may get the wrong color because of the wrong compare. The methods of Levin and Yatziv color a image only need people to annotate the image with a few color scribbles. In image painting systems, the underlying surface parameterization is fixed during the painting process. Such a parameterization is not sensitive to the frequency spectrum of the color signal introduced by painting strokes. To associate the regions of higher color signal variation with more texture samples, re-parameterization according to user strokes at interactive rates is necessary. It provides a method to produce re-parameterization scheme to solve above problems. The results can demonstrate our method that is convenient and practical.
Formal transformation of ontology axioms to application domain rules

Transformation rules can be defined in two ways -- theoretical and empirical. A theoretical-based definition of transformation is a formal way to prove and verify some theory. Therefore, it is precise, the likelihood of errors is reduced, it is easier to tell where it is wrong and correct it, and the quality of specification of the transformation can be improved. The disadvantage is the lack of knowledge about the theoretical-based approach. An empirical-based definition of transformation is informal and based on practice. Therefore, we can be sure that the transformation will work. However, sometimes it is impossible to verify some theory on practice or the cost of verification is too high. In this paper authors investigate the possibility of ontology axioms transformation to application domain rules using theoretical and empirical aspects.
MADmap: A MASSIVELY PARALLEL MAXIMUM LIKELIHOOD COSMIC MICROWAVE BACKGROUND MAP-MAKER

MADmap is a software application used to produce maximum likelihood images of the sky from time-ordered data which include correlated noise, such as those gathered by cosmic microwave background (CMB) experiments. It works efficiently on platforms ranging from small workstations to the most massively parallel supercomputers. Map-making is a critical step in the analysis of all CMB data sets, and the maximum likelihood approach is the most accurate and widely applicable algorithm; however, it is a computationally challenging task. This challenge will only increase with the next generation of ground-based, balloon-borne, and satellite CMB polarization experiments. The faintness of the B-mode signal that these experiments seek to measure requires them to gather enormous data sets. MADmap is already being run on up to O(1011) time samples, O(108) pixels, and O(104) cores, with ongoing work to scale to the next generation of data sets and supercomputers. We describe MADmap's algorithm based around a preconditioned conjugate gradient solver, fast Fourier transforms, and sparse matrix operations. We highlight MADmap's ability to address problems typically encountered in the analysis of realistic CMB data sets and describe its application to simulations of the Planck and EBEX experiments. The massively parallel and distributed implementation is detailed and scaling complexities are given for the resources required. MADmap is capable of analyzing the largest data sets now being collected on computing resources currently available, and we argue that, given Moore's Law, MADmap will be capable of reducing the most massive projected data sets.
Knowledge-Based Scientific Discovery in Geological Databases

A framework for knowledge-based scientific discovery in geological databases has been developed. The discovery process consists of two main steps: context definition and equation derivation. Context definition properly defines and formulates homogeneous regions, each of which is likely to produce a unique and meaningful analytic formula for the goal variable. Clustering techniques and a suite of visualization and interpretation routines make up a tool box that assists the context definition task. Within each context, muiti-variable regression analysis is conducted to derive analytic equations between the goal variable and a set of relevant independent variables, starting with one or more of the initial base models. Domain knowledge, plus a heuristic search technique called component plus residual plots dynamically guide the equation refinement process. The methodology has been applied to derive porosity equations for data collected from oil fields in the Alaska Basin. Preliminary results demonstrate the effectiveness of this methodology.
Blade: A Data Center Garbage Collector

An increasing number of high-performance distributed systems are written in garbage collected languages. This removes a large class of harmful bugs from these systems. However, it also introduces high tail-latency do to garbage collection pause times. We address this problem through a new technique of garbage collection avoidance which we call Blade. Blade is an API between the collector and application developer that allows developers to leverage existing failure recovery mechanisms in distributed systems to coordinate collection and bound the latency impact. We describe Blade and implement it for the Go programming language. We also investigate two different systems that utilize Blade, a HTTP load-balancer and the Raft consensus algorithm. For the load-balancer, we eliminate any latency introduced by the garbage collector, for Raft, we bound the latency impact to a single network round-trip, (48 {\mu}s in our setup). In both cases, latency at the tail using Blade is up to three orders of magnitude better.
Facebook Linked Data via the Graph API

Facebook's Graph API is an API for accessing objects and connections in Facebook's social graph. To give some idea of the enormity of the social graph underlying Facebook, it was recently announced that Facebook has 901 million users, and the social graph consists of many types beyond just users. Until recently, the Graph API provided data to applications in only a JSON format. In 2011, an effort was undertaken to provide the same data in a semantically-enriched, RDF format containing Linked Data URIs. This was achieved by implementing a flexible and robust translation of the JSON output to a Turtle output. This paper describes the associated design decisions, the resulting Linked Data for objects in the social graph, and known issues.
Blind Recognition Algorithm of Turbo Codes for Communication Intelligence Systems

Turbo codes are widely used in land and space radio communication systems, and because of complexity of structure, are custom in military communication systems. In electronic warfare, COMINT systems make attempt to recognize codes by blind ways. In this Paper, the algorithm is proposed for blind recognition of turbo code parameters like code kind, code-word length, code rate, length of interleaver and delay blocks number of convolution code. The algorithm calculations volume is0.5L 3 +1.25L, therefore it is suitable for real time systems.
TRECO: Dynamic technology remapping for timing Engineering Change Orders

Due to the increasing IC design complexity, Engineering Change Orders (ECOs) have become a necessary technique to resolve late-found functional and/or timing deficiencies. To fix timing violations, the principles of gate sizing and buffer insertion are commonly used in post-mask ECO. These techniques however may not be powerful enough, especially when spare cells are inserted in a way of striking a balance between functional and timing repair capabilities. We propose a post-mask ECO technique, called TRECO, to remedy timing violations based on technology remapping, which supports functional ECO as well. Unlike conventional technology mapping, TRECO performs technology mapping with respect to a limited set of spare cells and confronts dynamic changes of wiring cost incurred by different spare-cell selections. With a pre-computed lookup table of representative circuit templates, TRECO iteratively performs technology remapping to restructure timing critical sub-circuits until no timing violation remains. Experimental results on five industrial designs show the effectiveness of TRECO in ECO timing optimization.
A Semantic Scattering Model for the Automatic Interpretation of Genitives

This paper addresses the automatic classification of the semantic relations expressed by the English genitives. A learning model is introduced based on the statistical analysis of the distribution of genitives' semantic relations on a large corpus. The semantic and contextual features of the genitive's noun phrase constituents play a key role in the identification of the semantic relation. The algorithm was tested on a corpus of approximately 2,000 sentences and achieved an accuracy of 79%, far better than 44% accuracy obtained with C5.0, or 43% obtained with a Naive Bayes algorithm, or 27% accuracy with a Support Vector Machines learner on the same corpus.
The heart-gut axis: new target for atherosclerosis and congestive heart failure therapy

The human gut microbiota has been identified as a possible novel risk factor for cardiovascular disease. The intestinal microbiome plays a role in the pathogenesis of atherosclerosis and heart failure. Even though studies in rodents suggested that gut microbes may affect the risk of heart disease, this link has not been shown in humans. In the present study, we review several potential mechanisms by which the gut microbiome and bacterial translocation are associated with the development of cardiac disorders making them potential targets for novel therapeutic measures for these conditions. Modulation of the gut microbiota as a mechanism for altering the pathogenesis of disorders is an area of growing interest. Alteration in the gut microbiota is being explored as a method of reducing risk factors associated with cardiac diseases.