Miracle-dz/UniFAR-FTUs huggingface dataset:
Citation Semantic Based Approaches to Identify Article Quality

Analyzing the structure of research articles and the relationship between the articles has always been important in bibliometrics research area. One of the methods for analyzing articles is by its citation. Normally researchers rank the article based on the citation count. But this quantity based evaluation is not sufficient due to various citation types like Random citation, Guest citation. Our paper aims in providing a new method to rate a research paper based on its citation quality. In order to find the citation quality, three different semantic related processes are used: Citation classification, Citation Sentiment Analysis, Content Relevancy. This work analyzes some challenges found in citing a research paper. We have proposed methods to figure out the valid citations for research paper and thereby found quality of the research paper.
A new beamforming approach for the localisation of event related potentials

The ERP signals describe the concentrated electrical activity of the brain in response to an external event. ERPs exhibit variations in latency, strength and location between various instances of the same event. Also, different population groups can show similarities in the characteristics of their ERPs and this fact is used by clinicians in diagnosis and monitoring of some specific psychiatric diseases. In this paper, we model the ERP components as transient spikes and use them as reference signals. We employ a novel localisation procedure utilising spatial notch filters and the information from the modelled ERP. The algorithm accurately localises the ERP sources within a noisy environment.
Toward a general theory of names: binding and scope

High-level formalisms for reasoning about names and binding such as de Bruijn indices, various flavors of higher-order abstract syntax, the Theory of Contexts, and nominal abstract syntax address only one relatively restrictive form of scoping: namely, unary lexical scoping, in which the scope of a (single) bound name is a subtree of the abstract syntax tree (possibly with other subtrees removed due to shadowing). Many languages exhibit binding or renaming structure that does not fit this mold. Examples include binding transitions in the π-calculus; unique identifiers in contexts, memory heaps, and XML documents; declaration scoping in modules and namespaces; anonymous identifiers in automata, type schemes, and Horn clauses; and pattern matching and mutual recursion constructs in functional languages. In these cases, it appears necessary to either rearrange the abstract syntax so that lexical scoping can be used, or revert to first-order techniques.The purpose of this paper is to catalogue these "exotic" binding, renaming, and structural congruence situations; to argue that lexical scoping-based syntax techniques are sometimes either inappropriate or incapable of assisting in such situations; and to outline techniques for formalizing and proving properties of languages with more general forms of renaming and other structural congruences.
A comparison of methods for player clustering via behavioral telemetry

The analysis of user behavior in digital games has been aided by the introduction of user telemetry in game development, which provides unprecedented access to quantitative data on user behavior from the installed game clients of the entire population of players. Player behavior telemetry datasets can be exceptionally complex, with features recorded for a varying population of users over a temporal segment that can reach years in duration. Categorization of behaviors, whether through descriptive methods (e.g. segmention) or unsupervised/supervised learning techniques, is valuable for finding patterns in the behavioral data, and developing profiles that are actionable to game developers. There are numerous methods for unsupervised clustering of user behavior, e.g. k-means/c-means, Non-negative Matrix Factorization, or Principal Component Analysis. Although all yield behavior categorizations, interpretation of the resulting categories in terms of actual play behavior can be difficult if not impossible. In this paper, a range of unsupervised techniques are applied together with Archetypal Analysis to develop behavioral clusters from playtime data of 70,014 World of Warcraft players, covering a five year interval. The techniques are evaluated with respect to their ability to develop actionable behavioral profiles from the dataset.
Systematic Momentum

This paper provides evidence that momentum is a systematic phenomenon. We first show that there is essentially no diversification effect in the volatility of momentum profits when momentum strategies are applied to increasingly larger samples of stocks. Further, using the frequency domain component method to decompose stock returns, we find that stocks’ response to a few dynamic systematic factors can explain both the level and the variability of momentum profits. The results are robust to variations in momentum strategies and estimation procedures. Our finding supports a rational explanation of the momentum effect. We also examine the relationship between the estimated dynamic factors and several observable economic factors. JEL Classification: G12
Nonlinear Dynamic System Identification Based on Multiobjectively Selected RBF Networks

In this paper, nonlinear dynamic system identification by using multiobjectively selected RBF network is considered. RBF networks are widely used as a model structure for nonlinear systems. The determination of its structure that is the number of basis functions is prior important step in system identification, and the tradeoff between model complexity and accuracy exists in this problem. By using multiobjective evolutionary algorithms, the candidates of the RBF network structure are obtained in the sense of Pareto optimality. We discuss an application to system identification by using such RBF networks having Pareto optimal structures. Some numerical simulations for nonlinear dynamic systems are carried out to show the applicability of the proposed approach.
Low-Latency Real-Time Meeting Recognition and Understanding Using Distant Microphones and Omni-Directional Camera

This paper presents our real-time meeting analyzer for monitoring conversations in an ongoing group meeting. The goal of the system is to recognize automatically “who is speaking what” in an online manner for meeting assistance. Our system continuously captures the utterances and face poses of each speaker using a microphone array and an omni-directional camera positioned at the center of the meeting table. Through a series of advanced audio processing operations, an overlapping speech signal is enhanced and the components are separated into individual speaker's channels. Then the utterances are sequentially transcribed by our speech recognizer with low latency. In parallel with speech recognition, the activity of each participant (e.g., speaking, laughing, watching someone) and the circumstances of the meeting (e.g., topic, activeness, casualness) are detected and displayed on a browser together with the transcripts. In this paper, we describe our techniques and our attempt to achieve the low-latency monitoring of meetings, and we show our experimental results for real-time meeting transcription.
Load Balancing Strategies for Parallel SAMR Algorithms

Highly resolved numerical solutions of partial dierential equations are important in many areas of science and technology. Only adaptive mesh refinement methods reduce the necessary work suciently, allowing the calculation of realistic problems. Block-structured methods are well-suited for the time-explicit computation of largescale dynamical problems, but still require parallelization on distributed systems. Unfortunately, assigning tasks in a load-balanced manner is even more dicult than for unstructured mesh refinement techniques. Therefore the application-specific load-balancing problem is analyzed more deeply in order to adapt and integrate existing strategies and libraries. Common approaches decompose the work domain into smaller parts and assign them to processors using workload data, geometric information and neighborhood relationship. Especially, the input generated for graph partitioning algorithms has great influence on the quality of the results and thus is examined more closely.
Parallel Sequence Analysis under Three Load Balancing Strategies

Retrieving homologous sequences from existing databases is very important for the biomedical research community. In this project, we implemented four sequence alignment algorithms (general gap penalty, affine gap penalty, general gap penalty with mid-point and affine gap penalty with midpoint) to look for nearly optimum aligned sequences in the database for nucleic acid sequences (i.e. DNA/RNA sequences). We use MPI, which is a MIMD programming interface, to achieve parallelism. Our focus in this project is to achieve good load balancing strategies. Three load balancing strategies, including static assignment, dynamic assignment and semi-dynamic assignment, are implemented to divide and assign sequences in the database to different processors. And the semi-dynamic assignment strategy is the highlight. It is designed by us to achieve better load balancing than pure static and dynamic load balancing strategies. We also compare the performance of these three load balancing strategies.
Distributed application tamper detection via continuous software updates

We present a new general technique for protecting clients in distributed systems against Remote Man-at-the-end (R-MATE) attacks. Such attacks occur in settings where an adversary has physical access to an untrusted client device and can obtain an advantage from tampering with the hardware itself or the software it contains. In our system, the trusted server overwhelms the analytical abilities of the untrusted client by continuously and automatically generating and pushing to him diverse client code variants. The diversity subsystem employs a set of primitive code transformations that provide an ever-changing attack target for the adversary, making tampering difficult without this being detected by the server.
Toward a Framework in Cloudlet-Based Architecture for a Real-Time Predictional Model

In this paper we present a framework based on prediction model for users in smart living environment. Users need to be able to get access to all available services continuously without performance or memory constraints, regardless of their physical location and mobility. To satisfy this need, we propose the use of cloudlets acting as distributed cloud resources with specific ranges of influence, and a real-time processing framework that will track the events and preferences of end consumers, predict their potential requirements, and give recommendations in order to optimize the resource utilization and service response time.
Vascular Endothelium Derived Endothelin-1 Is Required for Normal Heart Function after Chronic Pressure Overload in Mice

Background Endothelin-1 participates in the pathophysiology of heart failure. The reasons for the lack of beneficial effect of endothelin antagonists in heart failure patients remain however speculative. The anti-apoptotic properties of ET-1 on cardiomyocytes could be a reasonable explanation. We therefore hypothesized that blocking the pro-apoptotic TNF-α pathway using pentoxifylline could prevent the deleterious effect of the lack of ET-1 in a model for heart failure. Methods We performed transaortic constriction (TAC) in vascular endothelial cells specific ET-1 deficient (VEETKO) and wild type (WT) mice (n = 5–9) and treated them with pentoxifylline for twelve weeks. Results TAC induced a cardiac hypertrophy in VEETKO and WT mice but a reduction of fractional shortening could be detected by echocardiography in VEETKO mice only. Cardiomyocyte diameter was significantly increased by TAC in VEETKO mice only. Pentoxifylline treatment prevented cardiac hypertrophy and reduction of fractional shortening in VEETKO mice but decreased fractional shortening in WT mice. Collagen deposition and number of apoptotic cells remained stable between the groups as did TNF-α, caspase-3 and caspase-8 messenger RNA expression levels. TAC surgery enhanced ANP, BNP and bcl2 expression. Pentoxifylline treatment reduced expression levels of BNP, bcl2 and bax. Conclusions Lack of endothelial ET-1 worsened the impact of TAC-induced pressure overload on cardiac function, indicating the crucial role of ET-1 for normal cardiac function under stress. Moreover, we put in light a TNF-α-independent beneficial effect of pentoxifylline in the VEETKO mice suggesting a therapeutic potential for pentoxifylline in a subpopulation of heart failure patients at higher risk.
Epithelium-dependent extracellular matrix synthesis in transforming growth factor-beta 1-growth-inhibited mouse mammary gland

Exogenous transforming growth factor beta (TGF-beta 1) was shown in earlier studies to reversibly inhibit mouse mammary ductal growth. Using small plastic implants to treat regions of developing mammary glands in situ, we now report that TGF-beta 1 growth inhibition is associated with an ectopic accumulation of type I collagen messenger RNA and protein, as well as the glycosaminoglycan, chondroitin sulfate. Both macromolecules are normal components of the ductal extracellular matrix, which, under the influence of exogenous TGF-beta 1, became unusually concentrated immediately adjacent to the epithelial cells at the tip of the ductal growth points, the end buds. Stimulation of extracellular matrix was confined to aggregations of connective tissue cells around affected end buds and was not present around the TGF-beta 1 implants themselves, indicating that the matrix effect was epithelium dependent. Ectopic matrix synthesis was specific for TGF-beta 1 insofar as it was absent at ducts treated with other growth inhibitors, or at ducts undergoing normal involution in response to endogenous regulatory processes. These findings are consistent with the matrix-stimulating properties of TGF-beta 1 reported for other systems, but differ in their strict dependence upon epithelium. A possible role for endogenous TGF-beta 1 in modulating a mammary epithelium-stroma interaction is suggested.
Individuals With Type 2 Diabetes Mellitus Are at an Increased Risk of Gout But This Is Not Due to Diabetes

AbstractThe relationship between type 2 diabetes and gout is complex. The objective of this study was to understand the role of diabetes itself and its comorbidities within the association between type 2 diabetes and gout.We conducted a retrospective cohort study using the UK Clinical Practice Research Datalink (CPRD) GOLD. Persons with type 2 diabetes were identified as persons on a noninsulin antidiabetic drug (NIAD) between 2004 and 2012, and were matched to 1 control based on age, sex, and general practice. We estimated gout risk in NIAD users using Cox regression analysis. All analyses were stratified for sex.In total, 221,117 NIAD users were identified. NIAD users had an increased risk of gout (hazard ratio (HR) 1.48; 95% CI 1.41–1.54). This association was stronger in women (HR 2.23; 95% CI 2.07–2.41) compared with men (HR 1.19; 95% CI 1.13–1.26). After adjustments for BMI, eGFR, hypertension, renal transplantation, diuretics, statins, low-dose aspirin, ciclosporin, and tacrolimus, the risk disappeared in women (HR 1.01; 95% CI 0.92–1.11) and reversed in men (HR 0.61; 95% CI 0.58–0.66) (P for interaction <0.001). When stratifying gout risk according to HbA1c in male and female NIAD users, we found an inverse association between raising HbA1c and incident gout in men only. Further adjustment gave similar results.Individuals with type 2 diabetes are at increased risk of gout. This is not due to diabetes itself, but to the comorbid conditions. Diabetes itself is apparently associated with a decreased risk of gout, especially in men.
A versatile low-jitter PLL in 90-nm CMOS for SerDes transmitter clocking

A low-jitter charge-pump PLL is built in 90-nm CMOS for 1-10 Gb/s SerDes transmitter clocking. The PLL employs a programmable dual-path loop filter with integrating path and novel resistorless proportional path that can be independently controlled and accurately modeled for flexible setting of closed-loop bandwidth and peaking. Frequency is synthesized using an area-efficient LC-VCO with helical inductors and inversion-mode nFET varactors for 45% tuning range. The PLL exhibits 0.81 ps rms jitter at 10.0 Gb/s. Technology considerations for improving design manufacturability, tuning range, and jitter performance are addressed.
The Relation Between Financial and Housing Wealth of Dutch Households

We analyze households' joint investment decisions for financial wealth and homes.In our bivariate censored regression model with endogenous switching, fixed costs or transaction costs are captured by a threshold that has to be passed before the purchase.The model allows for spill-over effects of a binding threshold for one asset on the demand for the other asset.We find that tenure choice affects the level of financial wealth.Our results do not support the view that people first accumulate financial wealth before acquiring homes.This can be due to the absence of down payment constraints in the Netherlands.
An Algorithm of Mining Exceptions in High Dimensional Data Cube

Existing algorithms of mining exceptions in high dimension data cube often require users to fix out one or more thresholds beforehand to judge whether a data point is an exception, and different thresholds will lead to different efficiency. To overcome this problem, we propose a new definition of exception, interval exception, which can help users find the exceptions in data cell fast and efficiently without any threshold users given. This method computes reference range of a point firstly according to regression parameters, and then considers whether it is an interval exception by comparing its absolute value of residual to reference range. Performance study shows that the method is practical and effective.
University of Pennsylvania Working Papers in Linguistics Discourse like in Quebec English Discourse like in Quebec English Discourse like in Quebec English

This study considers the spread of discourse like in Quebec English. Although several previous studies have examined the pragmatic functions and rate of use of like as a discourse marker, few consider its interaction with the syntactic structure and most focus solely on English-dominant communities. Thus, while D' Arcy (2005) has shown that this discourse feature is spreading systematically throughout the syntactic structure in apparent time in Toronto, it is unknown whether its evolution is as advanced in communities such as Quebec, where English is a minority language, isolated from mainstream varieties. We analyze the rate of use of discourse like in three distinct structural contexts (CP, DP, and vP) by 39 native English speakers from the Quebec English Corpus (Poplack, et al., 2006). Speakers from both Montreal and Quebec City were included in this study since the degree of isolation from mainstream English is arguably greater in the latter. Internal grammatical factors and external factors are also analyzed. The results show that while both Quebec City and Montreal speakers exhibit substantially lower rates than Toronto speakers in their use of like in each of the structural contexts examined, the internal conditioning of like in Quebec English is practically identical to that in Toronto English. These findings only partially support the hypothesis that these speakers' isolation from mainstream English causes them to lag behind in ongoing change and highlight the complexity involved in the exploration of such a widespread and multifaceted phenomenon.
Genetic Variation of Human Cytochrome P450 Reductase as a Potential Biomarker for Mitomycin C-Induced Cytotoxicity

The importance of genetic variation in clinical response to various drugs is now well recognized. Identification of genetic biomarkers that can predict efficacy and toxicity of chemotherapeutic drugs in cancer patients holds great promise in treatment improvement and cost reduction. Mitomycin C (MMC) is a common anticancer drug used for the treatment of numerous types of tumors. Metabolism-mediated activation, by either one-electron or two-electron reduction, plays a critical role in the chemotherapeutic action of MMC. NADPH-cytochrome P450 (oxido)reductase (POR) is a major enzyme responsible for MMC activation through the one-electron reductive pathway, which leads to the production of semiquinone anion radicals and subsequent DNA damage in the cells. Recently, a total of six naturally occurring human POR variants with single amino acid changes (Y181D, A287P, R457H, V492E, C569Y, and V608F) have been identified. Although the catalytic efficiency of these variants in reduction of cytochrome c was reported to be altered, their capability in activating MMC, a direct substrate of POR, has not been examined. In the present study, we demonstrated that except for the C569Y variant, MMC-induced toxicity assayed as cell viability and proliferative capability was significantly decreased in the Flp-In Chinese hamster ovary cells stably expressing all the other POR variants in comparison with the cells expressing wild-type human POR. Cells expressing the V608F and Y181D variants had a complete loss of the capability to activate MMC. Our finding suggests that these functional POR genetic variations may serve as a potential biomarker to predict the chemotherapeutic response to MMC.
LBP based on multi wavelet sub-bands feature extraction used for face recognition

The strategy of extracting discriminant features from a face image is immensely important to accurate face recognition. This paper proposes a feature extraction algorithm based on wavelets and local binary patterns (LBPs). The proposed method decomposes a face image into multiple sub-bands of frequencies using wavelet transform. Each sub-band in the wavelet domain is divided into non-overlapping sub-regions. Then LBP histograms based on the traditional 8-neighbour sampling points are extracted from the approximation sub-band, whilst 4-neighbour sampling points are used to extract LBPHs from detail sub-bands. Finally, all LBPHs are concatenated into a single feature histogram to effectively represent the face image. Euclidean distance is used to measure the similarity of different feature histograms and the final recognition is performed by the nearest-neighbour classifier. The above strategy was tested on two publicly available face databases (Yale and ORL) using different scenarios and different combination of sub-bands. Results show that the proposed method outperforms the traditional LBP based features.
Evaluation of the estrogenic effects of dietary perinatal Trifolium pratense

This study was designed to investigate the potential estrogenic effects of perinatal dietary phytoestrogens on the rat uterus. Pregnant rats were divided to three groups provided the following diets: (1) rat chow, (2) rat chow with 7.5% Trifolium (T.) pratense, or (3) rat chow supplemented with 17β-estradiol (0.5 mg/kg). The dams in each group were kept on the same diet during pregnancy and lactation. Female offspring were euthanized on day 21 at which time body and organ weights were recorded and tissue samples were taken for histology. Immunohistochemistry was performed to detect estrogen receptor alpha (ERα) and progesterone receptor (PR) levels. Our results revealed estrogen-like biological effects of perinatal T. pratense exposure. Relative uterus and ovary weights in the experimental groups were increased compared to control. The number of uterine glands and luminal epithelium heights were also increased. However, there were no statistically significant changes detected in the immunostaining intensity of ERα and PR between the groups.