Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Success in Machine Translation

The performance of machine translation systems varies greatly depending on the source and target languages involved. Determining the contribution of different characteristics of language pairs on system performance is key to knowing what aspects of machine translation to improve and which are irrelevant. This paper investigates the effect of different explanatory variables on the performance of a phrase-based system for 110 European language pairs. We show that three factors are strong predictors of performance in isolation: the amount of reordering, the morphological complexity of the target language and the historical relatedness of the two languages. Together, these factors contribute 75% to the variability of the performance of the system.
Predicting CD4 counts in HIV-infected Brazilian individuals: a model based on the World Health Organization staging system.

CD4 cell counts are one of the best available surrogate markers for disease progression; they are widely used laboratory parameters in clinical trials and commonly used indicators for the introduction of primary prophylaxis and antiretroviral therapy. However, measurement is too expensive to be done in most developing countries. The objective of this study was to derive a model for prediction of CD4 counts < 200 cells/mm3 based on the proposed World Health Organization (WHO) staging system for HIV infection and widely available laboratory parameters. One hundred and six consecutive patients enrolled in a prospective cohort study who were not taking anti-HIV drugs or prophylaxis for opportunistic infections were included. Blood tests were performed within 72 h of the outpatient visit. Lymphocyte phenotyping was done by flow cytometry. Two models based on the WHO staging system, hematocrit and total lymphocyte counts, were developed. The two models had sensitivity > 90% and specificity > 83%. These results indicate that the combined use of simple clinical and laboratory parameters can predict CD4 counts < 200 cells/mm3 with high sensitivity and specificity. Similar studies should be conducted in other countries. Should our findings be confirmed, intervention strategies based on this model of potential universal applicability should be devised and validated.
NetTopo: Beyond Simulator and Visualizer for Wireless Sensor Networks

Deploying real WSN testbed provides a realistic testing environment, and allows users to get more accurate test results. However, deploying real testbed is highly constrained by the available budget when the test needs a large scale WSN environment. By leveraging the advantages of both simulators and real testbed, an approach that integrates simulation environment and testbed can effectively solve both scalability and accuracy issues. In this paper, we present NetTopo for providing both simulation and visualization functions to assist the investigation of algorithms in WSNs. Two case studies are described to prove the effectiveness of NetTopo.
A 128-Channel 6mW Wireless Neural Recording IC with On-the-Fly Spike Sorting and UWB Tansmitter

The chip is composed of eight 16-channel front-end blocks, data serializing circuits, a DSP for on-chip spike sorting, digital MUX, encoder, UWB TX, and bias generators. The chip operates in one of the two modes. In sorting mode, a selected channel is connected to the on-the-fly spike sorting block and the extracted features of the spikes are transmitted for off-chip classification. In streaming mode, all the sampled data from the 128 channels are recorded and transmitted without any additional processing.
Mechanical control of the directional stepping dynamics of the kinesin motor

Among the multiple steps constituting the kinesin mechanochemical cycle, one of the most interesting events is observed when kinesins move an 8-nm step from one microtubule (MT)-binding site to another. The stepping motion that occurs within a relatively short time scale (≈100 μs) is, however, beyond the resolution of current experiments. Therefore, a basic understanding to the real-time dynamics within the 8-nm step is still lacking. For instance, the rate of power stroke (or conformational change) that leads to the undocked-to-docked transition of neck-linker is not known, and the existence of a substep during the 8-nm step still remains a controversial issue in the kinesin community. By using explicit structures of the kinesin dimer and the MT consisting of 13 protofilaments, we study the stepping dynamics with varying rates of power stroke (kp). We estimate that kp−1 ≲ 20 μs to avoid a substep in an averaged time trace. For a slow power stroke with kp−1 > 20 μs, the averaged time trace shows a substep that implies the existence of a transient intermediate, which is reminiscent of a recent single-molecule experiment at high resolution. We identify the intermediate as a conformation in which the tethered head is trapped in the sideway binding site of the neighboring protofilament. We also find a partial unfolding (cracking) of the binding motifs occurring at the transition state ensemble along the pathways before binding between the kinesin and MT.
Mate sampling and choosiness in the sand goby

To date, mate choice studies have mostly focused on establishing which mates are chosen or how the choices are performed. Here, we combined these two approaches by empirically testing how latency to mate is affected by various search costs, variation in mate quality and female quality in the sand goby (Pomatoschistus minutus). Our results show that females adjust their mating behaviour according to the costs and benefits of the choice situation. Specifically, they mated sooner when access to males was delayed and when the presence of other females presented a mate sampling cost. We also found a positive link between size variation among potential mating partners and spawning delay in some (but not all) experimental conditions. By contrast, we did not find the number of available males or the females' own body size (‘quality’) to affect mating latency. Finally, female mating behaviour varied significantly between years. These findings are notable for demonstrating that (i) mate sampling time is particularly sensitive to costs and, to a lesser degree, to variation among mate candidates, (ii) females' mating behaviour is sensitive to qualitative rather than to quantitative variation in their environment, and (iii) a snapshot view may describe mate sampling behaviour unreliably.
Fuzzy sliding mode control of a finger of a humanoid robot hand

Abstract: The motion control problem for the finger of a humanoid robot hand is investigated. First, the index finger of the human hand is dynamically modelled as a kinematic chain of cylindrical links. During construction of the model, special attention is given to determining bone dimensions and masses that are similar to the real human hand. After the kinematic and dynamic analysis of the model, in order to ensure that the finger model tracks its desired trajectory during a closing motion, a fuzzy sliding mode controller is applied to the finger model. In this controller, a fuzzy logic algorithm is used in order to tune the control gain of the sliding mode controller; thus, an adaptive controller is obtained. Finally, numerical results, which include a performance comparison of the proposed fuzzy sliding mode controller and a conventional sliding mode controller, are presented. The results demonstrate that the proposed control method can be used to perform the desired motion task for humanoid robot hands efficiently.
Spatial Memory Structures for Sensor-Guided Robot Navigation

Although evolutionary algorithms o er an attractive and versatile approach to the automated design of behavior and control structures for mobile robots, they cannot anticipate the detailed structure of speci c environments that the robot might have to deal with. Robots must thus possess mechanisms to adapt to the environments they encounter. In particular, mobile robots need stuctures for building and using spatial maps to aid in the successful exploration and navigation of a-priori unknown environments. This paper proposes a biologically inspired computational model for the acquisition and use of spatial memory structures for mobile robot navigation. Preliminary experimental results indicate that the proposed mechanisms can be e ectively exploited by evolution in the design of high-performance robots.
Possible targets of therapy for catecholaminergic polymorphic ventricular tachycardia. - Insight from a theoretical model -.

BACKGROUND Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a serious disease with a high mortality but its management is limited. The aim of this study was to investigate specific target sites for therapy in order to find potential management strategies for CPVT. METHODS AND RESULTS The mutant Ryanodine receptor 2 (RyR2) with reduced stored-overloaded-induced Ca²⁺ release (SOICR) threshold was incorporated into the Luo-Rudy dynamic (LRd) cell model to elucidate the underlying pathologies of CPVT. The simulations reveal that β-adrenergic stimulation increased the Ca²⁺ load in cardiac myocyte, which facilitates spontaneous SR Ca²⁺ leakage, resulting in triggered arrhythmias. Varied blockade (from 0% to 90%) in specific ion channels, including the Na⁺/Ca²⁺ exchanger (I(NaCa)), fast Na⁺ channel (I(Na)), RyR2 receptor (I(rel)), Ca²⁺-ATPase (SERCA) (I(up)) or L-type Ca²⁺channel (I(Ca(L))),was performed to simulate the action of specific drugs on target sites. Blockade of the I(NaCa) (≤ 10% blockade), in contrast to the I(up) (≤ 30% blockade), I(Ca(L)) and I(Na) (≤40% blockade), and followed by I(rel) (≤ 80% blockade), was most effective in suppressing the triggered arrhythmias in CPVT. Specifically, dual blockade of I(Ca(L))/I(up), I(Na)/I(rel) or I(Ca(L))/I(rel) had a synergistic effect in CPVT management. CONCLUSIONS Blockade of I(NaCa) appears to be the most efficacious target for CPVT management. Dual blockade of I(Ca(L))/I(up), I(Na)/I(rel) or I(Ca(L))/I(rel) has a synergistic effect in CPVT treatment.
Early Ordovician island arc of Qimantag Mountain,eastern Kunlun:Evidences from geochemistry,Sm-Nd isotope and geochronology of intermediate-basic igneous rocks

Intermediate-basic igneous rocks, including hornblende gabbros, basalts, diorites and andesites, were found in Qimantag Group of Yaziquan area, west of Qimantag Mountain. The main geochemistry and isotope characteristics are as follows; (1) basic igneous rocks show SiO(2) 47.93% similar to 50.54%, MgO 3.40% similar to 6.24% and total Fe(FeO(T)) 11.24% similar to 14.10%, belonging to tholeiitic rocks; intermediate rocks are of SiO(2) 51.5% similar to 59.59%, MgO 2.05 similar to 6.42%, total Fe(FeO(T)) 5.65% similar to 9.38%, belonging to tholeiitic and calc-alkalic rocks; (2) REE patterns show that both basic and intermediate igneous rocks are enriched in LREEs, with (La/Yb), = 1.44 similar to 11.69; (3) Enriched in LILEs (like Sr, Ba, Th, U) and depleted in HFSEs (P, Zr, Ti), especially Nb and Ta negative anomaly; (4) epsilon(Nd) (t = 480Ma) is from +1.1 to +7.9, showing that they were contaminated with subducted crustal materials. The characteristics above show that these intermediate-basic igneous rocks formed in an island arc setting. Zircon U-Pb dating for a dimite sample yields ages of 480 +/- 3Ma, representing the rock forming age. Indicating that the Qimantag oceanic basin already exist in Early Ordovician and began subducting then, leading to the formation of island arc igneous rocks in Yaziquan.
Antibiotic susceptibility of planktonic‐ and biofilm‐grown staphylococci isolated from implant‐associated infections: should MBEC and nature of biofilm formation replace MIC?

Purpose. The purpose of this study was to develop an alternative, more clinically relevant approach to susceptibility reporting for implant‐associated infections. Using 20 staphylococcal isolates, isolated from clinical implant infections, the majority (85%) demonstrated biofilm‐forming capabilities. A significantly increased minimum biofilm eradication concentration (MBEC) compared to minimum inhibitory concentration (MIC) breakpoint was obtained, with MBEC values greater than 256 &mgr;g ml−1 for the majority of bacteria. Such a vast increase was also demonstrated for isolates defined as negligible biofilm formers via crystal violet staining, likely due to the high protein content of biofilms, as confirmed by proteinase‐K treatment. Methodology. This study employed a variety of techniques to assess MIC and MBEC of the isolates tested. In addition, the nature of bacterial biofilm across a range of clinical isolates was investigated using crystal violet staining, sodium metaperiodate and proteinase‐K treatment, and PCR analysis. Results/Key findings. Infection of medical implants is associated with increased rates of infection and increased bacterial tolerance to antibiotic strategies. Clinical significance is due to the presence of pathogens attached to biomaterial surfaces enclosed in an extracellular polymeric matrix termed the biofilm. This article highlights the importance of defining the clinical susceptibility of implant‐associated infections in vitro using methods that are relevant to the biofilm phenotype in vivo, and highlights how current planktonic‐based antimicrobial susceptibility tests are often misleading. Conclusion. The use of biofilm‐relevant susceptibility tests would improve patient outcomes by enabling correct antimicrobial regimens to be rapidly identified, reducing treatment failure and halting the spread of antimicrobial‐resistant strains.
Nonparametric Bayesian Variable Selection With Applications to Multiple Quantitative Trait Loci Mapping With Epistasis and Gene–Environment Interaction

The joint action of multiple genes is an important source of variation for complex traits and human diseases. However, mapping genes with epistatic effects and gene–environment interactions is a difficult problem because of relatively small sample sizes and very large parameter spaces for quantitative trait locus models that include such interactions. Here we present a nonparametric Bayesian method to map multiple quantitative trait loci (QTL) by considering epistatic and gene–environment interactions. The proposed method is not restricted to pairwise interactions among genes, as is typically done in parametric QTL analysis. Rather than modeling each main and interaction term explicitly, our nonparametric Bayesian method measures the importance of each QTL, irrespective of whether it is mostly due to a main effect or due to some interaction effect(s), via an unspecified function of the genotypes at all candidate QTL. A Gaussian process prior is assigned to this unknown function. In addition to the candidate QTL, nongenetic factors and covariates, such as age, gender, and environmental conditions, can also be included in the unspecified function. The importance of each genetic factor (QTL) and each nongenetic factor/covariate included in the function is estimated by a single hyperparameter, which enters the covariance function and captures any main or interaction effect associated with a given factor/covariate. An initial evaluation of the performance of the proposed method is obtained via analysis of simulated and real data.
Analysis of a glycinergic inhibitory pathway in the cat retina

Incubation of cat retinas with 3H-glycine in vitro, followed by horizontal sectioning and autoradiography, showed labeling of 10–12% of bipolar cells and 45% of amacrine cells. To ascertain the effects of glycine-accumulating bipolar and amacrine cells on the response properties of retinal ganglion cells, in vivo iontophoretic studies were performed in the cat eye. Glycine inhibited all ganglion cells, and this action was blocked by strychnine. Aminophosphonobutyric acid (APB) suppressed ON-ganglion cells, but activated OFF-ganglion cells. The influence of APB upon OFF-ganglion cells could be completely blocked by strychnine. In the mudpuppy, APB suppressed ON-bipolar cells without affecting OFF-bipolar cells and without direct effects on other retinal neurons (Slaughter and Miller, 1981, 1985). If APB has the same mode of action in the cat retina, the present results suggest a glycinergic inhibitory input of the ON-channel upon OFF-ganglion cells.
P 300-based Brain Computer Interface Mouse with Genetically-optimised Analogue Control

In this paper we propose a BCI mouse based on the manipulation of P300 waves in EEG signals. The system is analogue in that at no point a binary decision is made as to whether or not a P300 was actually produced in response to the stimuli. Instead, the 2–D motion of the pointer on the screen, using a novel BCI paradigm, was controlled by directly combining the amplitudes of the output produced by a filter in the presence of different stimuli. This filter and the features to be combined within it are optimised by an evolutionary algorithm. In the paper we illustrate our approach, describe our system, and report the results of the testing and validation of the system with 6 participants. The results are very promising, with all 6 participants being able to control the mouse with excellent accuracy only minutes after wearing the electrode cap despite their having no previous training with this system.
The future is here: A review of foresight systems in anxiety and depression

Cognitive models of anxiety and depression have long suggested a central role for future-oriented thinking in these disorders. Experimental studies suggest that anxiety and depression are characterised by distinct future-oriented thinking profiles, and that these profiles are markedly different from those of asymptomatic adults. In this paper, we review these profiles and propose two explanatory models marked by two different neurocognitive systems. The Reconstructive Memory Model emphasises a role for emotionally driven learning and retrieval in episodic foresight (i.e., the construction of future-oriented scenarios), and the Valuation Model proposes that an overweighing of risk and uncertainty estimates can be invoked to explain the future-oriented thought patterns. We consider the effectiveness of interventions aimed at altering such thought patterns. We suggest that future research aimed at elucidating the neurobiological underpinnings of future-oriented thinking in anxiety and depression can play an important role in advancing development of effective biological and psychosocial interventions for these disorders.
Leveraging relational autocorrelation with latent group models

The presence of autocorrelation provides a strong motivation for using relational learning and inference techniques. Autocorrelation is a statistical dependence between the values of the same variable on related entities and is a nearly ubiquitous characteristic of relational data sets. Recent research has explored the use of collective inference techniques to exploit this phenomenon. These techniques achieve significant performance gains by modeling observed correlations among class labels of related instances, but the models fail to capture a frequent cause of autocorrelation - the presence of underlying groups that influence the attributes on a set of entities. We propose a latent group model (LGM) for relational data, which discovers and exploits the hidden structures responsible for the observed autocorrelation among class labels. Modeling the latent group structure improves model performance, increases inference efficiency, and enhances our understanding of the datasets. We evaluate performance on three relational classification tasks and show that LGM outperforms models that ignore latent group structure, particularly when there is little information with which to seed inference.
Modeling of Speaking Rate Influences on Mandarin Speech Prosody and Its Application to Speaking Rate-controlled TTS

A new data-driven approach to building a speaking rate-dependent hierarchical prosodic model (SR-HPM), directly from a large prosody-unlabeled speech database containing utterances of various speaking rates, to describe the influences of speaking rate on Mandarin speech prosody is proposed. It is an extended version of the existing HPM model which contains 12 sub-models to describe various relationships of prosodic-acoustic features of speech signal, linguistic features of the associated text, and prosodic tags representing the prosodic structure of speech. Two main modifications are suggested. One is designing proper normalization functions from the statistics of the whole database to compensate the influences of speaking rate on all prosodic-acoustic features. Another is modifying the HPM training to let its parameters be speaking-rate dependent. Experimental results on a large Mandarin read speech corpus showed that the parameters of the SR-HPM together with these feature normalization functions interpreted the effects of speaking rate on Mandarin speech prosody very well. An application of the SR-HPM to design and implement a speaking rate-controlled Mandarin TTS system is demonstrated. The system can generate natural synthetic speech for any given speaking rate in a wide range of 3.4-6.8 syllables/sec. Two subjective tests, MOS and preference test, were conducted to compare the proposed system with the popular HTS system. The MOS scores of the proposed system were in the range of 3.58-3.83 for eight different speaking rates, while they were in 3.09-3.43 for HTS. Besides, the proposed system had higher preference scores (49.8%-79.6%) than those (9.8%-30.7%) of HTS. This confirmed the effectiveness of the speaking rate control method of the proposed TTS system.
Homocysteine levels in patients with risk factors for atherosclerosis

Background: Abundant epidemiological evidence has demonstrated that the presence of mild to moderate hyperhomocysteinemia is an independent risk factor for atherosclerosis in the coronary, cerebral, and peripheral vasculature, and for vascular disease, including coronary disease. It has been demonstrated that plasma total homocysteine level is a strong predictor of mortality in patients with angiographically confirmed coronary artery disease.
Drug use data, drug use theories and drug use policies in the United States: a combinatorial lack of connections.

and economic adversity play in shaping illicit drug demand. It is remarkable and disappointing that no existing model of demand provides information on the factors that cause individuals to make transitions between various levels of drug use [8]. To fully understand this process and the phenomena described by Caulkins et al. [1] we need large-scale longitudinal studies of drug use. That would allow us to chart the movements of individuals through various stages of drug use and examine the factors associated with these movements. If ADAM is to be abandoned, it is to be hoped that a suitable large-scale longitudinal survey of drug use will take its place.
Bioclimatic Characteristics of Recreational Zones – Important Component of the Passport of the Health Resort – Tourist Potential of Georgia

მოყვანილია საკურორტო-ტურისტული პოტენციალის პასპორტის ძირითადი მაჩვენებლების აღწერილობა. განსაკუთრებული ყურადღება ეთმობა ბიოკლიმატურ პარამეტრებს. მოყვანილია პრაქტიკული მაგალითები აღნიშნული პარამეტრების გამოყენებისა საქართველოს ზოგიერთი საკურორტო-ტურისტული რაიონების ბიოკლიმატური პირობების შესაფასებლად.