Miracle-dz/UniFAR-FTUs huggingface dataset:
Species Delimitation using Genome-Wide SNP Data

The multi-species coalescent has provided important progress for evolutionary inferences, including increasing the statistical rigor and objectivity of comparisons among competing species delimitation models. However, Bayesian species delimitation methods typically require brute force integration over gene trees via Markov chain Monte Carlo (MCMC), which introduces a large computation burden and precludes their application to genomic-scale data. Here we combine a recently introduced dynamic programming algorithm for estimating species trees that bypasses MCMC integration over gene trees with sophisticated methods for estimating marginal likelihoods, needed for Bayesian model selection, to provide a rigorous and computationally tractable technique for genome-wide species delimitation. We provide a critical yet simple correction that brings the likelihoods of different species trees, and more importantly their corresponding marginal likelihoods, to the same common denominator, which enables direct and accurate comparisons of competing species delimitation models using Bayes factors. We test this approach, which we call Bayes factor delimitation (*with genomic data; BFD*), using common species delimitation scenarios with computer simulations. Varying the numbers of loci and the number of samples suggest that the approach can distinguish the true model even with few loci and limited samples per species. Misspecification of the prior for population size θ has little impact on support for the true model. We apply the approach to West African forest geckos (Hemidactylus fasciatus complex) using genome-wide SNP data data. This new Bayesian method for species delimitation builds on a growing trend for objective species delimitation methods with explicit model assumptions that are easily tested.
Robust Tomlinson-Harashima precoding for non-regenerative multi-antenna relaying systems

In this paper, we consider the robust transceiver design with Tomlinson-Harashima precoding (THP) for multi-hop amplify-and-forward (AF) multiple-input multiple-output (MIMO) relaying systems. THP is adopted at the source to mitigate the spatial inter-symbol interference and then a joint Bayesian robust design of THP at source, linear forwarding matrices at relays and linear equalizer at destination is proposed. Based on the elegant characteristics of multiplicative convexity and matrix-monotone functions, the optimal structure of the nonlinear transceiver is first derived. Based on the derived structure, the optimization problem is greatly simplified and can be efficiently solved. Finally, the performance advantage of the proposed robust design is assessed by simulation results.
XJSA at SemEval-2017 Task 4: A Deep System for Sentiment Classification in Twitter

This paper describes the XJSA System submission from XJTU. Our system was created for SemEval2017 Task 4 – subtask A which is very popular and fundamental. The system is based on convolutional neural network and word embedding. We used two pre-trained word vectors and adopt a dynamic strategy for k-max pooling.
An ensemble approach for multi-label classification of item click sequences

In this paper, we describe our approach to RecSys 2015 challenge problem. Given a dataset of item click sessions, the problem is to predict whether a session results in a purchase and which items are purchased if the answer is yes. We define a simpler analogous problem where given an item and its session, we try to predict the probability of purchase for the given item. For each session, the predictions result in a set of purchased items or often an empty set. We apply monthly time windows over the dataset. For each item in a session, we engineer features regarding the session, the item properties, and the time window. Then, a balanced random forest classifier is trained to perform predictions on the test set. The dataset is particularly challenging due to privacy-preserving definition of a session, the class imbalance problem, and the volume of data. We report our findings with respect to feature engineering, the choice of sampling schemes, and classifier ensembles. Experimental results together with benefits and shortcomings of the proposed approach are discussed. The solution is efficient and practical in commodity computers.
CautiousBug: a competitive algorithm for sensory-based robot navigation

Bug algorithms are a class of popular algorithms for autonomous robot navigation in unknown environments with local information. Very natural, with low memory requirements, Bug strategies do not yet allow any competitive analysis. The bound on the robot's path changes from scene to scene depending on the obstacles, even though a new obstacle may not alter the length of the shortest path. We propose a new competitive algorithm, CautiousBug, whose competitive factor has an order of O(d/sup m-1/), where d is the length of the optimal path from starting point S to a target point T. m = 2/sup #Min-1/ and #Min denote the number of the distance function isolated local minima points in the given environment. Simulations were performed to study the average competitive factor of the algorithm.
Collaborative Learning Support System in a Classroom Using Ad Hoc Network of Tablet Devices

Having students ask and answer questions among themselves can help deepen their understanding of learning content. Tablet devices are advantageous for such application due to their portability and capability to support not only text but also images and sound. A few elementary schools in Japan have already started introducing tablet devices into the classroom. This requires making some changes to the environment, including providing an access point for the tablets to communicate with each other. To aid in the preparation for computer supported learning, we propose using an ad hoc network of tablet devices to deploy a delay tolerant network with the aim of achieving high message reach ability over intermittent connections. The results of preliminary experiments show that our system can provide a high delivery rate, although its delivery speed is somewhat slow. We also created a practical application using the ad hoc network that students can use to exchange content.
VoiceToModel: an approach to generate requirements models from speech recognition mechanisms

Requirements are typically modelled using some graphical notation with the aid of CASE tools. However, these tools make this activity exclusive to requirements engineers and stakeholders with no accessibility problems, but disabled professionals often have accessibility problems to use tools to build requirements models. Also, accessibility problems can happen to stakeholders in general in a particular context where the use of voice is more convenient (e.g., in a public transport). In this paper, the VoiceToModel framework is proposed to improve the accessibility of the requirements process by effectively integrating a requirements engineer or stakeholder with disabilities during requirements modelling. Through speech recognition, the engineer should be capable of voicing the requirements, which are automatically used to generate requirements models, more specifically goal-oriented models, object models and feature models. Also, the automated framework generates requirements models from speech recognition by firstly defining a grammar where we have the commands to create and modify a model. These commands return a feedback via voice. We show the applicability of the framework through an example and discuss the results of an experiment with 14 participants, including 2 blind people.
Harmonic alternatives to sine-wave speech

Sine-wave speech (SWS) is a three-tone replica of speech, con-ventionally created by matching each constituent sinusoid in amplitude and frequency with the corresponding vocal tract res-onance (formant). We propose an alternative technique where we take a high-quality multicomponent sinusoidal representation and decimate this model so that there are only three components per frame. In contrast to SWS, the resulting signal con-tains only components that were present in the original signal. Consequently it preserves the harmonic ﬁne structure of voiced speech. Perceptual studies indicate that this signal is judged more natural and intelligible than SWS. Furthermore, its tonal artifacts can mostly be eliminated by the introduction of only a few additional components, which leads to an intriguing specu-lation about grouping issues.
Carbohydrates on the surface of urediniospore- and basidiospore-derived infection structures of heteroecious and autoecious rust fungi

summary Nine flucirescein isothiocyanate-labelled lectins with affinity towards different carbohydrates were used to probe the surface carbohydrates of infection structures in vitro, derived from urediniospores and basidiospores of an autoecious rust species, Uromyces viciae-fabae (Pers. J Schroet., and of a heteroecious rust species, Uromyces rumicis (Schum.) Wint. Lectin binding was quantified by measuring fluorescence photometrically. All lectins bound in a characteristic pattern to the infection structures of the respective spore types of each rust fungus. Differences were especially obvious between those infection structures normally produced inside leaf tissue, namely the urediniospore-derived substomatal vesicles with infection hyphae, and the basidiospore-derived intraepidermal vesicles. The dikaryotic stage and the monokaryotic stage of the heteroecious fungus differed mainly in their affinity for the leotins from Bandeira simplicifolin and Lotus tetragonulobus. A statistical analysis comparing the binding of the lectins to infection structures of Two rust fungi suggested that cell surface composition is determined by nuclear condition. The monokaryotic stages of both rust fungi have a higher degree of similarity than the dikaryotic and monokaryotic stages of the same rust fungus.
Assessment of Clinical Pharmacist Management of Lipid-Lowering Therapy in a Primary Care Setting

BACKGROUND: Pharmacists have been shown to positively impact the outcomes of care for treatment of many different kinds of disease states. In particular, pharmacist-run lipid clinics have enjoyed varying degrees of success, depending on the outcome assessed. At our hospital, when a patient is transferred to the pharmacist coordinated lipid clinic, the primary care pharmacist is responsible for ordering and interpreting labs and prescribing and monitoring lipid-altering therapy. OBJECTIVES: This study was designed to assess if there is a statistically significant difference between the magnitude of serum cholesterol reduction for patients receiving lipid-altering pharmacotherapy when clinically trained pharmacists are actively prescribing and adjusting the drug therapy compared to other health care practitioners (usual care). METHODS: Patient records from the hospital computer databases were retrospectively and randomly selected for analysis. Following evaluation for inclusions and exclusions, 41 patient records remained for statistical analysis for the cohort group, and 47 records remained from the group of patients managed by a clinical pharmacist. RESULTS: Management of dyslipidemia by a clinical pharmacist was associated with a significant reduction in overall mean low-density lipoprotein (LDL, 18.5%) compared to the cohort that did not have a clinical pharmacist as the primary manager of dyslipidemia (6.5%, P=0.049). This suggests improved clinical outcomes, defined as greater LDL reduction, when clinical pharmacists participate in lipid management, including drug prescribing. The magnitude reduction in LDL was found to be related to the number of clinical pharmacy visits (11.4% for 1 visit, 23.2% for 2 visits, and 23.7% for greater than3 visits), compared to the usual care group (-11.0%, 18.0%, and 7.4%; statistically significant, P=0.038, for greater than 3 visits only). These results occurred even though the group of dyslipidemic patients managed primarily by a clinical pharmacist contained a statistically greater number of patients with 2 or more risk factors and high-density lipoprotein (HDL) levels less than 40 mg/dL. CONCLUSIONS: Interdisciplinary medical teams that include clinical pharmacists who are actively prescribing and adjusting lipid drug therapy may achieve greater reductions in LDL for patients who have been assessed with multiple risk factors compared to patients managed without clinical pharmacists. Active participation by clinical pharmacists in lipid management for patients with elevated LDL resulted in improved treatment success as measured by the magnitude reduction in LDL. The reduction in LDL was between 5% and 22% per visit greater for patients being treated by clinical pharmacists versus usual care, even in a patient population with more risk factors. These intermediate outcomes may translate into long-term outcomes in fewer cardiovascular events, improved quality of life for patients with dyslipidemia, and lower costs associated with sequelae of dyslipidemias.
HMW1 Is Required for Stability and Localization of HMW2 to the Attachment Organelle of Mycoplasma pneumoniae

ABSTRACT The cytoskeletal proteins HMW1 and HMW2 are components of the terminal organelle of the cell wall-less bacterium Mycoplasma pneumoniae. HMW1 is required for a tapered, filamentous morphology but exhibits accelerated turnover in the absence of HMW2. Here, we report that a reciprocal dependency exists between HMW1 and HMW2, with HMW2 subject to accelerated turnover with the loss of HMW1. Furthermore, the instability of HMW2 correlated with its failure to localize to the attachment organelle. The C-terminal domain of HMW1 is essential for both function and its accelerated turnover in the absence of HMW2. We constructed HMW1 deletion derivatives lacking portions of this domain and examined each for stability and function. The C-terminal 41 residues were particularly important for proper localization and function in cell morphology and P1 localization, but the entire C-terminal domain was required to stabilize HMW2. The significance of these findings in the context of attachment organelle assembly is considered.
A search for scalable evolutionary solutions to the game of MasterMind

MasterMind is a puzzle in which a hidden string of symbols must be discovered by producing query strings which are compared with the hidden one; the result of this comparison (in terms of number of correct positions and colors) is fed back to the player that is trying to crack the code (codebreaker). Methods for solving this puzzle are usually compared in terms of the number of query strings (guesses) made and the total time needed to produce those strings. In this paper we focus on the latter by trying to find a combination of parameters that is, first, uniform and independent of the problem size, and second, adequate to find a fast solution that is, at the same time, good enough. The key to this combination of parameters will be the consistent set size, that is, the maximum number of combinations that are sought before being scored and played as a guess. Having found in previous papers that the consistent set size has an influence on speed, we will concentrate on small sizes and test them through two different scoring methods from literature: most parts and entropy to find out the influence of that parameter on the outcome and which method scales better. With this we try to find out which method and size yield the best results an are effectively able to? find solutions for sizes not approached so far in a reasonable time.
Improving the Lower Bound on the Higher Order Nonlinearity of Boolean Functions With Prescribed Algebraic Immunity

The recent algebraic attacks have received a lot of attention in cryptographic literature. The algebraic immunity of a Boolean function quantifies its resistance to the standard algebraic attacks of the pseudorandom generators using it as a nonlinear filtering or combining function. Very few results have been found concerning its relation with the other cryptographic parameters or with the rth-order nonlinearity. As recalled by Carlet at CRYPTO'06, many papers have illustrated the importance of the r th-order nonlinearity profile (which includes the first-order nonlinearity). The role of this parameter relatively to the currently known attacks has been also shown for block ciphers. Recently, two lower bounds involving the algebraic immunity on the rth-order nonlinearity have been shown by Carlet . None of them improves upon the other one in all situations. In this paper, we prove a new lower bound on the rth-order nonlinearity profile of Boolean functions, given their algebraic immunity, that improves significantly upon one of these lower bounds for all orders and upon the other one for low orders.
The role of organizational capabilities in successful e-business implementation

Purpose – Based on organizational capabilities and information technology implementation literature, this study seeks to propose a research model to examine the influence of organizational capabilities on e‐business implementation success.Design/methodology/approach – Data collected from 202 information systems executives in large Taiwanese organizations were employed to test the relationships between the research model constructs. The results from the structural equation modeling approach provide quite a strong support for the hypothesized relations.Findings – The results showed that certain factors related to organizational learning and knowledge management capabilities are important antecedents of e‐business value.Research limitations/implications – This study did not test all organizational factors, and focused particularly on learning capacity and knowledge capability factors. A knowledge asset must be rare and inimitable to become a source of competitive advantage. Without secure processes, knowledg.
Constitutive Activity at the Cannabinoid CB1 Receptor Is Required for Behavioral Response to Noxious Chemical Stimulation of TRPV1: Antinociceptive Actions of CB1 Inverse Agonists

The potential modulation of TRPV1 nociceptive activity by the CB1 receptor was investigated here using CB1 wild-type (WT) and knock-out (KO) mice as well as selective CB1 inverse agonists. No significant differences were detected in baseline thermal thresholds of ICR, CB1WT or CB1KO mice. Intraplantar capsaicin produced dose- and time-related paw flinch responses in ICR and CB1WT mice and induced plasma extravasation yet minimal responses were seen in CB1KO animals with no apparent differences in TRPV1 channel expression. Capsaicin-evoked CGRP release from spinal cord tissue and capsaicin-evoked action potentials on isolated skin-nerve preparation were significantly decreased in CB1KO mice. Pretreatment with intraplantar galanin and bradykinin, compounds known to sensitize TRPV1 receptors, restored capsaicin-induced flinching in CB1KO mice. The possibility that constitutive activity at the CB1 receptor is required to maintain the TRPV1 receptor in a “sensitized” state was tested using CB1 inverse agonists. The CB1 inverse agonists elicited concentration-related inhibition of capsaicin-induced calcium influx in F-11 cells and produced dose-related inhibition of capsaicin-induced flinching in ICR mice. These data suggest that constitutive activity at the CB1 receptor maintains the TRPV1 channel in a sensitized state responsive to noxious chemical stimuli. Treatment with CB1 inverse agonists may promote desensitization of the channel resulting in antinociceptive actions against chemical stimulus modalities. These studies propose possible therapeutic exploitation of a novel mechanism providing pain relief by CB1 inverse agonists.
The Case for Migratory Priority Inheritance in Linux: Bounded Priority Inversions on Multiprocessors

Linux’s real-time performance crucially depends on priority inheritance because—on uniprocessors—it limits the maximum duration of priority inversion to one critical section per lock while ensuring that tasks remain fully preemptable even when holding locks. Unfortunately, priority inheritance is ineffective on multiprocessors under non-global scheduling (i.e., if some tasks may not execute on every processor) in the sense that it does not prevent unbounded priority inversion in all cases. In fact, as shown in the paper, in a multiprocessor system with priority inheritance, it is possible for a task to suffer from priority inversion as long as in a uniprocessor system without priority inheritance. There is thus currently no predictable locking mechanism suitable for non-global scheduling available in Linux, short of resorting to non-preemptive sections or other latency-increasing mechanisms such as priority boosting. As multicore platforms are becoming more widespread in the embedded domain, this “predictability gap” on multiprocessors limits Linux’s viability as a real-time platform. In this position paper, it is argued that a simple tweak to the priority inheritance algorithm will restore its efficacy on multiprocessors, without breaking POSIX compliance, increasing scheduling latency, or requiring large changes to Linux’s scheduling and locking code. In a nutshell, under the proposed migratory priority inheritance mechanism, inheritance is applied not only to scheduling priorities, but also to processor affinity masks. The need for migratory priority inheritance and its benefits are explained in detail with a sequence of simple examples. Additionally, a prototype implementation within the Linux kernel is described and potential challenges and simplifications are discussed.
Interaction of Nonsteroidal Anti-Inflammatory Drugs with Multidrug Resistance Protein (MRP) 2/ABCC2- and MRP4/ABCC4-Mediated Methotrexate Transport

Methotrexate (MTX) has been used in combination with nonsteroidal anti-inflammatory drugs (NSAIDs) in the treatment of inflammatory diseases as well as malignancies. Especially at high MTX dosages, severe adverse effects with this combination may occur, usually resulting from an impaired renal elimination. It has been shown that the mechanism of this interaction cannot be fully attributed to inhibition of basolateral MTX uptake in renal proximal tubules. Here, we studied the effect of various NSAIDs on MTX transport in membrane vesicles isolated from cells overexpressing the proximal tubular apical efflux transporters human multidrug resistance protein (MRP) 2/ABCC2 and MRP4/ABCC4. MTX was transported by MRP2 and MRP4 with Km values of 480 ± 90 and 220 ± 70 μM, respectively. The inhibitory potency of the NSAIDs was generally higher against MRP4- than MRP2-mediated MTX transport, with therapeutically relevant IC50 values, ranging from approximately 2 μM to 1.8 mM. Salicylate, piroxicam, ibuprofen, naproxen, sulindac, tolmetin, and etodolac inhibited MRP2- and MRP4-mediated MTX transport according to a one-site competition model. In some cases, more complex interaction patterns were observed. Inhibition of MRP4 by diclofenac and MRP2 by indomethacin and ketoprofen followed a two-site competition model. Phenylbutazone stimulated MRP2 and celecoxib MRP4 transport at low concentrations and inhibited both transporters at high concentration. Our data suggest that the inhibition by NSAIDs of renal MTX efflux via MRP2 and MRP4 is a potential new site and mechanism contributing to the overall interaction between these drugs.