Miracle-dz/UniFAR-FTUs huggingface dataset:
Regression genetic programming for estimating trend end in foreign exchange market

Most forecasting algorithms use a physical time scale for studying price movement in financial markets, making the flow of physical time discontinuous. The use of a physical time scale can make companies oblivious to significant activities in the market, which poses a risk. Directional changes is a different and newer approach, which uses an event-based time scale. This approach summarises data into alternating trends called upward directional change and downward directional change. Each of these trends are further dismembered into directional change (DC) event and overshoot (OS) event. We present a genetic programming (GP) algorithm that evolves equations that express linear and non-linear relationships between the length of DC and OS events in a given dataset. This allows us to have an expectation when a trend will reverse, which can lead to increased profitability. This novel trend reversal estimation approach is then used as part of a DC-based trading strategy. We aim to appraise whether the new knowledge can lead to greater excess return. We assess the efficiency of the modified trading strategy on 250 different directional changes datasets from five different thresholds and five different currency pairs, consisting of intraday data from the foreign exchange (Forex) spot market. Results show that our algorithm is able to return profitable trading strategies and statistically outperform state-of-the-art financial trading strategies, such as technical analysis, buy and hold and other DC-based trading strategies.
miR-370 mimic inhibits replication of Japanese encephalitis virus in glioblastoma cells

Japanese encephalitis (JE) is one of the most severe viral infections of the central nervous system. No effective treatment for JE currently exists, because its pathogenesis remains largely unknown. The present study was designed to screen the potential microRNAs (miRNAs) involved in JE. Glioblastoma cells were collected, after being infected with the Japanese encephalitis virus (JEV). Total miRNAs were extracted and analyzed using an miRNA chip. One of the most severely affected miRNAs was selected, and the role of miR-370 in JEV infection was investigated. Cell viability and apoptosis of the host cells were evaluated. JEV replication was detected via analysis of gene E expression. Real-time polymerase chain reaction was used to determine the levels of endogenous miR-370 and expression of innate immunity-related genes. Following JEV infection, 114 miRNAs were affected, as evidenced by the miRNA chip. Among them, 30 miRNAs were upregulated and 84 were downregulated. The changes observed in five miRNAs were confirmed by real-time polymerase chain reaction. One of the significantly downregulated miRNAs was miR-370. Therefore, miR-370 mimic was transfected into the cells, following which the levels of endogenous miR-370 were significantly elevated. Concurrently, JEV replication was significantly reduced 24 hours after transfection of miR-370 mimic. Functionally, miR-370 mimic mitigated both JEV-induced apoptosis and the inhibition of host cell proliferation. Following JEV infection, interferon-β and nuclear factor-kappa B were upregulated, whereas miR-370 mimic prevented the upregulation of the genes induced by JEV infection. The present study demonstrated that miR-370 expression in host cells is downregulated following JEV infection, which further mediates innate immunity-related gene expression. Taken together, miR-370 mimic might be useful to prevent viral replication and infection-induced host cell injury.
Conversion of Sensory Signals into Motor Commands in Primary Motor Cortex

Movement triggered by sensory stimuli requires that the networks generating the motor commands receive an adequate driving input, which, in general, is a transformed version of the initial sensory signal. We investigated the nature of this transformation in a task in which monkeys categorize the speed of tactile stimuli as either low or high, reaching for one of two pushbuttons to indicate their choice. Extracellular recordings from primary motor cortex revealed two types of neurons selective for the speed categories: ones that fire at higher rates for low versus high speeds, and others that do the opposite. These differential responses are task-specific; no firing rate modulation was seen when identical arm movements were triggered by visual cues or when stimuli were delivered passively. Analyses using decoding and modeling techniques produced two main results. First, the neurons accurately encode the chosen category; an observer measuring their responses can exhibit a psychophysical performance during categorization identical to the monkey’s. Second, by analyzing separately the trials in which hits and errors were scored, it is possible to distinguish purely sensory activity from activity exclusively related to arm motion. The recorded responses did not match either of these alternatives but were consistent with a model in which the category-tuned neurons are the link between the output of the sensory categorization process and the motor command used to indicate the animal’s decision. Thus, the observed activity seems to encode a preprocessed version of the sensory stimulus and to participate in driving the arm motion.
Implementing an ALCRP(D) ABox Reasoner - Progress Report

: This paper presents a progress report on the implementation of an ALCRP ( D ) ABox reasoner and a knowledge representation framework. We present an ALC ABox reasoner which has been constructed for providing a basis for an optimized ALCRP ( D ) implementation. We compare the implementation with the concept consistency reasoner FaCT which sets the standard in current DL implementations.
Resistance to Infection by Subgroups B, D, and E Avian Sarcoma and Leukosis Viruses Is Explained by a Premature Stop Codon within a Resistance Allele of the tvb Receptor Gene

ABSTRACT Here we present the first molecular characterization of the defect associated with an avian sarcoma and leukosis virus (ASLV) receptor resistance allele, tvb r. We show that resistance to infection by subgroups B, D, and E ASLV is explained by the presence of a single base pair mutation that distinguishes this allele from tvb s1, an allele which encodes a receptor for all three viral subgroups. This mutation generates an in-frame stop codon that is predicted to lead to the production of a severely truncated protein.
The WOSP Model: Balanced Information System Design and Evaluation

IS researchers may wonder why computing advances often confound expectations. The leisure society, the paperless office, and programmer decline are just a few predictions that didn’t happen. If current expectations are to be any more accurate, we must learn from experience. As we create e-systems to rival ourselves, and networks to match society, the problem may be a limited view of system performance. The Technology Acceptance Model (TAM) sees performance as functionality plus usability. The Web Of System Performance (WOSP) model presented in this paper extends TAM to include other requirements common in performance research literature. WOSP is a theoretical framework for the balanced design and evaluation of advanced information systems, as now being created on the Internet and elsewhere. It analyses performance via four fundamental system elements: boundary, internal structure, effectors and receptors. Each can be designed for opportunity or risk, giving eight performance goals, whose design tension comprises a “web” of performance. It explains why advances sometimes “bite back”, and need creative system requirements integration. The theory applies to hardware, software, cognitive, or social system levels, but as each level is a different “world”, it cannot be instantiated across levels. The WOSP model should interest those designing or evaluating advanced software systems.
Perceptual and Acoustic Differences between Aging Voice and Dysphonic Voice

This study aimed to investigate the differences between dysphonic and aging voice from perceptual and acoustic perspectives. Ten listeners listened to 64 voice stimuli collected from 32 Cantonese subjects to determine whether they were dysphonic or non-dysphonic under two testing conditions, one with age information of each speaker given and the other without age information provided. The perceptual analysis showed that when age information was provided the listeners judged more older female subjects to have nondysphonic voice than when no age information was given. Therefore, the perceptual voice qualities previously perceived as dysphonic might be reconsidered as normal aging when age of speaker was known. In addition, more older subjects were judged as dysphonic than the young adult. The presence of aging that resulted in increase judgment of dysphonic again suggests the aging voice and dysphonic voice were found to be similar perceptually. Voice stimuli from the young dysphonic subjects and older subjects with normal voice were compared on the measures of five acoustic measures including mean fundamental frequency (Hz), standard deviation of fundamental frequency (Hz), jitter (%), shimmer (dB), and noise to harmonic ratio. However, the present study failed to show the similarity between aging voice and dysphonic voice on acoustic measures based on qualitative description.
Finite‐element modeling of trabecular bone: Comparison with mechanical testing and determination of tissue modulus

We combined three techniques—mechanical testing, three‐dimensional imaging, and finite‐element modeling—to distinguish between the contributions of architecture and tissue modulus to mechanical function in human trabecular bone. The objectives of this study were 2‐fold. The first was to assess the accuracy of micromechanical modeling of trabecular bone using high‐contrast x‐ray images of the trabecular architecture. The second was to combine finite‐element calculations with mechanical testing to infer an average tissue modulus for the specimen. Specimens from five human L1 vertebrae were mechanically tested along the three anatomic axes. The specimens were then imaged by synchrotron x‐ray tomography, and the elastic moduli of each specimen were calculated from the tomographic image by finite‐element modeling. We found that 23‐μm tomographic images resolved sufficient structural detail such that the calculated anisotropy in the elastic modulus was within the uncertainties of the experimental measurements in all cases. The tissue modulus of each specimen was then estimated by comparing the calculated mean stiffness of the specimen, averaged over the three anatomical directions, with the experimental measurement. The absolute values of the experimental elastic constants could be fitted, again within the uncertainties of the experimental measure‐ments, by a single tissue modulus of 6.6 GPa, which was the average tissue modulus of the five specimens. These observations suggest that a combination of mechanical testing, three‐dimensional imaging, and finite‐element modeling might enable the physiological variations in tissue moduli to be determined as a function of age and gender.
Multiple DNA and protein sequence alignment based on segment-to-segment comparison.

In this paper, a new way to think about, and to construct, pairwise as well as multiple alignments of DNA and protein sequences is proposed. Rather than forcing alignments to either align single residues or to introduce gaps by defining an alignment as a path running right from the source up to the sink in the associated dot-matrix diagram, we propose to consider alignments as consistent equivalence relations defined on the set of all positions occurring in all sequences under consideration. We also propose constructing alignments from whole segments exhibiting highly significant overall similarity rather than by aligning individual residues. Consequently, we present an alignment algorithm that (i) is based on segment-to-segment comparison instead of the commonly used residue-to-residue comparison and which (ii) avoids the well-known difficulties concerning the choice of appropriate gap penalties: gaps are not treated explicity, but remain as those parts of the sequences that do not belong to any of the aligned segments. Finally, we discuss the application of our algorithm to two test examples and compare it with commonly used alignment methods. As a first example, we aligned a set of 11 DNA sequences coding for functional helix-loop-helix proteins. Though the sequences show only low overall similarity, our program correctly aligned all of the 11 functional sites, which was a unique result among the methods tested. As a by-product, the reading frames of the sequences were identified. Next, we aligned a set of ribonuclease H proteins and compared our results with alignments produced by other programs as reported by McClure et al. [McClure, M. A. , Vasi, T. K. & Fitch, W. M. (1994) Mol. Biol. Evol. 11, 571-592]. Our program was one of the best scoring programs. However, in contrast to other methods, our protein alignments are independent of user-defined parameters.
Eating Behavior and Social Interactions from Adolescence to Adulthood

This paper analyzes the importance of social ties for eating behavior of US youth. We propose a novel approach that addresses identification of social endogenous effects. We overcome the problem of measuring the separate impact of endogenous and contextual effects on individual Body Mass Index (BMI) in a dynamic linear-in-means model, where individual- and group-specifi? c unobservable effects are controlled for. We show that the main drivers of eating behavior are habituation and imitation effects. Imitation effects explain most of the variation in BMI of individuals who were normal-weight and overweight during adolescence. Obese adolescents, instead, become future obese adults through wrong habits enforced by imitative behavior.
One-class support vector machine based undersampling: Application to churn prediction and insurance fraud detection

In this paper, we propose One Class support vector machine (OCSVM) based undersampling. To demonstrate the effectiveness of the proposed methodology, we worked on Automobile Insurance fraud dataset and Credit card customer churn dataset taken from literature. We employed Decision Tree (DT), Support Vector Machine (SVM), Logistic Regression (LR), Probabilistic Neural Network (PNN) and Group Method of Data Handling (GMDH) for classification purpose. We observed significant improvement with respect to the Area Under Receiver Operating Characteristic Curve (AUC) over other techniques. For automobile insurance dataset, undersampling with the sigmoid kernel yielded AUC of 7605 when compared with Sundar kumar and Ravi, Vasu and Ravi, Farquad [9,12,47] with respect to Decision tree, while for Credit card customer churn dataset, undersampling with the radial basis kernel (proposed method) yielded significant performance with respect to DT (AUC 8506.5). We preferred DT over SVM (AUC 8728.5) as there is no statistically significant difference between them. Finally, we recommend DT over other classifiers as it also yields "if-then" rules, while achieving high AUC.
African-American Women:

This article argues that African-American women are not a homogeneous group. An attempt to categorize them will therefore establish that there are differences within the group as well as between African-Americans women and other groups of women. African-American women continue to be victims of racial oppression, sex discrimination and class stratification. Historical and contemporary forces which shape the lives of African-American women will be identified.
Screen for Chemical Modulators of Autophagy Reveals Novel Therapeutic Inhibitors of mTORC1 Signaling

Background Mammalian target of rapamycin complex 1 (mTORC1) is a protein kinase that relays nutrient availability signals to control numerous cellular functions including autophagy, a process of cellular self-eating activated by nutrient depletion. Addressing the therapeutic potential of modulating mTORC1 signaling and autophagy in human disease requires active chemicals with pharmacologically desirable properties. Methodology/Principal Findings Using an automated cell-based assay, we screened a collection of >3,500 chemicals and identified three approved drugs (perhexiline, niclosamide, amiodarone) and one pharmacological reagent (rottlerin) capable of rapidly increasing autophagosome content. Biochemical assays showed that the four compounds stimulate autophagy and inhibit mTORC1 signaling in cells maintained in nutrient-rich conditions. The compounds did not inhibit mTORC2, which also contains mTOR as a catalytic subunit, suggesting that they do not inhibit mTOR catalytic activity but rather inhibit signaling to mTORC1. mTORC1 inhibition and autophagosome accumulation induced by perhexiline, niclosamide or rottlerin were rapidly reversed upon drug withdrawal whereas amiodarone inhibited mTORC1 essentially irreversibly. TSC2, a negative regulator of mTORC1, was required for inhibition of mTORC1 signaling by rottlerin but not for mTORC1 inhibition by perhexiline, niclosamide and amiodarone. Transient exposure of immortalized mouse embryo fibroblasts to these drugs was not toxic in nutrient-rich conditions but led to rapid cell death by apoptosis in starvation conditions, by a mechanism determined in large part by the tuberous sclerosis complex protein TSC2, an upstream regulator of mTORC1. By contrast, transient exposure to the mTORC1 inhibitor rapamycin caused essentially irreversible mTORC1 inhibition, sustained inhibition of cell growth and no selective cell killing in starvation. Conclusion/Significance The observation that drugs already approved for human use can reversibly inhibit mTORC1 and stimulate autophagy should greatly facilitate the preclinical and clinical testing of mTORC1 inhibition for indications such as tuberous sclerosis, diabetes, cardiovascular disease and cancer.
LQP controller design for generic whole body motion

This paper deals with robotic control through optimization tools, as Linear Quadratic Program (LQP). This method allows whole-body control, takes account contacts between the robot and the environment, and achieves tasks simultaneously. Each task can have a priority level, so hierarchy is possible. The method is applied on a virtual robot Icub, designed from the real one.
Predicting death from kala-azar: construction, development, and validation of a score set and accompanying software.

INTRODUCTION Early identification of patients at higher risk of progressing to severe disease and death is crucial for implementing therapeutic and preventive measures; this could reduce the morbidity and mortality from kala-azar. We describe a score set composed of four scales in addition to software for quick assessment of the probability of death from kala-azar at the point of care. METHODS: Data from 883 patients diagnosed between September 2005 and August 2008 were used to derive the score set, and data from 1,031 patients diagnosed between September 2008 and November 2013 were used to validate the models. Stepwise logistic regression analyses were used to derive the optimal multivariate prediction models. Model performance was assessed by its discriminatory accuracy. A computational specialist system (Kala-Cal(r)) was developed to speed up the calculation of the probability of death based on clinical scores. RESULTS: The clinical prediction score showed high discrimination (area under the curve [AUC] 0.90) for distinguishing death from survival for children ≤2 years old. Performance improved after adding laboratory variables (AUC 0.93). The clinical score showed equivalent discrimination (AUC 0.89) for older children and adults, which also improved after including laboratory data (AUC 0.92). The score set also showed a high, although lower, discrimination when applied to the validation cohort. CONCLUSIONS: This score set and Kala-Cal(r) software may help identify individuals with the greatest probability of death. The associated software may speed up the calculation of the probability of death based on clinical scores and assist physicians in decision-making.
Advanced techniques in real-time hair rendering and simulation

Hair rendering and simulation have always been challenging tasks, especially in real-time. Due to their high computational demands, they have been vastly omitted in real-time applications and studied by a relatively small group of graphics researchers and programmers. With recent advancements in both graphics hardware and software methods, real-time hair rendering and simulation are now possible with reasonable performance and quality. However, achieving acceptable levels of performance and quality requires specific expertise and experience in real-time hair rendering. The aim of this course is to bring the accumulated knowledge in research and technology demos to real world software such as video games and other commercial or research oriented real-time applications. We begin with explaining the fundamental techniques for real-time hair rendering and then present alternative approaches along with tips and tricks to achieve better performance and/or quality. We also provide an overview of various hair simulation techniques and present implementation details of the most efficient techniques suitable for real-time applications. Moreover, we provide example source codes as a part of our lecture notes.
Plaggie: GNU-licensed source code plagiarism detection engine for Java exercises

A source code plagiarism detection engine Plaggie is presented. It is a stand-alone Java application that can be used to check Java programming exercises. Plaggie's functionality is similar with previously published JPlag web service but unlike JPlag, Plaggie must be installed locally and its source code is open. Apparently, Plaggie is the only open-source plagiarism detection engine for Java exercises.
Multi-HDP: A Non Parametric Bayesian Model for Tensor Factorization

Matrix factorization algorithms are frequently used in the machine leaming community to find low dimensional representations of data. We introduce a novel generative Bayesian probabilistic model for unsupervised matrix and tensor factorization. The model consists of several interacting LDA models, one for each modality. We describe an efficient collapsed Gibbs sampler for inference. We also derive the non-parametric form of the model where interacting LDA models are replaced with interacting HDP models. Experiments demonstrate that the model is useful for prediction of missing data with two or more modalities as well as learning the latent structure in the data.
Resolution of Transverse Electron Beam Measurements Using Optical Transition Radiation

In the plasma wakefield acceleration experiment E-167, optical transition radiation is used to measure the transverse profile of the electron bunches before and after the plasma acceleration. The distribution of the electric field from a single electron does not give a point-like distribution on the detector, but has a certain extension. Additionally, the resolution of the imaging system is affected by aberrations. The transverse profile of the bunch is thus convolved with a point spread function (PSF). Algorithms that deconvolve the image can help to improve the resolution. Imaged test patterns are used to determine the modulation transfer function of the lens. From this, the PSF can be reconstructed. The Lucy-Richardson algorithm is used to deconvolute this PSF from test images.