Miracle-dz/UniFAR-FTUs huggingface dataset:
The origin of Rhodnius prolixus in Central America

J . P. D U J A R D I N ,1 , 2 M . M U Ñ O Z ,3 T . C H AV E Z , 3 C . P O N C E ,4 J . M O R E N O ,5 and C . J . S C H O F I E L D6 1UMR CNRS-ORSTOM 9926, BP 5045, Montpellier cedex 1, France, 2ORSTOM/IBBA, CP 9214, La Paz, Bolivia, 3Instituto Boliviano de Biologia de Altura, Calle Claudio Sanjinez, La Paz, Bolivia, 4Laboratorio de Referencia de Enfermedad de Chagas y Leishmaniosis, Ministerio de Salud Publica, Apartado 4695, Tegucigalpa, Honduras, 5Facultad de Ciencias Exactas y Naturales, Universidad de Antioquia, Medellin, Colombia and 6Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, U.K.
A review of databases predicting the effects of SNPs in miRNA genes or miRNA-binding sites

Modern precision medicine comprises the knowledge and understanding of individual differences in the genomic sequence of patients to provide tailor-made treatments. Regularly, such variants are considered in coding regions only, and their effects are predicted based on their impact on the amino acid sequence of expressed proteins. However, assessing the effects of variants in noncoding elements, in particular microRNAs (miRNAs) and their binding sites, is important as well, as a single miRNA can influence the expression patterns of many genes at the same time. To analyze the effects of variants in miRNAs and their target sites, several databases storing variant impact predictions have been published. In this review, we will compare the core functionalities and features of these databases and discuss the importance of up-to-date data resources in the context of web applications. Finally, we will outline some recommendations for future developments in the field.
Energy Optimization With Dynamic Task Scheduling Mobile Cloud Computing

The smartphone is a typical cyberphysical system (CPS). It must be low energy consuming and highly reliable to deal with the simple but frequent interactions with the cloud, which constitutes the cloud-integrated CPS. Dynamic voltage scaling (DVS) has emerged as a critical technique to leverage power management by lowering the supply voltage and frequency of processors. In this paper, based on the DVS technique, we propose a novel Energy-aware Dynamic Task Scheduling (EDTS) algorithm to minimize the total energy consumption for smartphones, while satisfying stringent time constraints and the probability constraint for applications. Experimental results indicate that the EDTS algorithm can significantly reduce energy consumption for CPS, as compared to the critical path scheduling method and the parallelism-based scheduling algorithm.
A New System for Continuous Monitoring of Breathing and Kinetic Activity

We present a new system for acquiring simultaneously breathing rate and kinetic activity over a period of twenty-four hours. The system is based on a couple of sensors, which are very light, absolutely noninvasive, and compatible with everyday life. The proposed breathing sensor is cheap and uses a conductive rubber as active material. An analog signal representing the breathing rate is obtained from the sensor's signal, breath by breath, without any averaging or filtering. The kinetic activity sensor is based on a tiny accelerometer whose signal is averaged and filtered, so that both sensors have voltage compatible with a slow data logging.
Identifying the metabolomic fingerprint of high and low flavonoid consumers

Abstract High flavonoid consumption can improve vascular health. Exploring flavonoid–metabolome relationships in population-based settings is challenging, as: (i) there are numerous confounders of the flavonoid–metabolome relationship; and (ii) the set of dependent metabolite variables are inter-related, highly variable and multidimensional. The Metabolite Fingerprint Score has been developed as a means of approaching such data. This study aims to compare its performance with that of more traditional methods, in identifying the metabolomic fingerprint of high and low flavonoid consumers. This study did not aim to identify biomarkers of intake, but rather to explore how systemic metabolism differs in high and low flavonoid consumers. Using liquid chromatography–tandem MS, 174 circulating plasma metabolites were profiled in 584 men and women who had complete flavonoid intake assessment. Participants were randomised to one of two datasets: (a) training dataset, to determine the models for the discrimination variables (n 399); and (b) validation dataset, to test the capacity of the variables to differentiate higher from lower total flavonoid consumers (n 185). The stepwise and full canonical variables did not discriminate in the validation dataset. The Metabolite Fingerprint Score successfully identified a unique pattern of metabolites that discriminated high from low flavonoid consumers in the validation dataset in a multivariate-adjusted setting, and provides insight into the relationship of flavonoids with systemic lipid metabolism. Given increasing use of metabolomics data in dietary association studies, and the difficulty in validating findings using untargeted metabolomics, this paper is of timely importance to the field of nutrition. However, further validation studies are required.
Nakamurella endophytica sp. nov., a novel endophytic actinobacterium isolated from the bark of Kandelia candel.

A Gram-stain-positive, aerobic, coccus-shaped, non-spore-forming actinobacterium, designated strain 2Q3S-4-2T, was isolated from the surface-sterilized bark of Kandelia candel, collected from Cotai Ecological Zones in Macao, PR China. It was tested using a polyphasic approach to determine its taxonomic position. Strain 2Q3S-4-2T grew optimally without NaCl at 28-30 °C and at pH 7.0. Substrate mycelia and aerial mycelia were not formed and no diffusible pigments were observed on the media tested. Phylogenetic analysis, based on 16S rRNA gene sequences, suggested that strain 2Q3S-4-2T belonged to the genus Nakamurella, sharing highest 16S rRNA gene sequence similarity with Nakamurella flavida DS-52T (96.76 %). The DNA G+C content of strain 2Q3S-4-2T was 67.8 mol%. The cell-wall peptidoglycan contained meso-diaminopimelic acid and MK-8(H4) was the predominant menaquinone. The predominant polar lipids were diphosphatidylglycerol, phosphatidylethanolamine, unidentified aminophospholipids and phosphatidylinositol. The major fatty acids were iso-C16 : 0, anteiso-C15 : 0, anteiso-C17 : 0 and C16 : 0. On the basis of the phylogenetic, phenotypic and chemotaxonomic analysis, strain 2Q3S-4-2T represents a novel species of the genus Nakamurella, for which the name Nakamurella endophytica sp. nov. is proposed. The type strain is 2Q3S-4-2T ( = DSM 100722T = CGMCC 4.7308T).
RNA polymerase alpha subunit binding site in positively controlled promoters: a new model for RNA polymerase‐promoter interaction and transcriptional activation in the Escherichia coli ada and aidB genes.

The ada and aidB genes are part of the adaptive response to DNA methylation damage in Escherichia coli. Transcription of the ada and the aidB genes is triggered by binding of the methylated Ada protein (meAda) to a specific sequence located 40–60 base pairs upstream of the transcriptional start, which is internal to an A/T‐rich region. In this report we demonstrate that the Ada binding site is also a binding site for RNA polymerase. RNA polymerase is able to bind the −40 to −60 region of the ada and the aidB promoters in the absence of meAda, and its binding is mediated by the alpha subunit. This region resembles the UP element of the rrnB P1 promoter in location, sequence and mechanism of interaction with RNA polymerase. We discuss the function of UP‐like elements in positively controlled promoters and provide evidence that Ada does not act by enhancing RNA polymerase binding affinity to the promoter region. Instead, Ada stimulates transcription by modifying the nature of the RNA polymerase‐promoter interaction, allowing RNA polymerase to recognize the core promoter −35 and −10 elements in addition to the UP‐like element.
A Mechanistic QSAR Study on the Leishmanicidal Activity of Some 5‐Substituted‐1,3,4‐Thiadiazole Derivatives

Quantitative structure–activity relationship studies help chemist to find chemical facts about the mechanism of action and/or behavior of the system under study. In this study, quantitative structure–activity relationship was employed as a promising tool to investigate some chemical, electronic, and structural features affecting on the antileishmanial activity of 5‐substituted‐1,3,4‐thiadiazole derivatives. A data set, consisting of 21 thiadiazole derivatives with known in vitro leishmanicidal activity, was taken and semi‐empirical AM1 quantum chemical calculation was employed to find the optimum three‐dimensional geometry of the molecules. Multiple linear regression‐based quantitative structure–activity relationship models were obtained between the antileishmanial activity and electronic, chemical, and topological descriptors of the molecules. Model performances and predictivity were evaluated using leave‐one‐out cross‐validation method. The resulted models had good prediction ability (0.83 > q2 > 0.71) and thus they described the structure–activity relationships in a useful manner. It was obtained that LUMO molecular orbital energy represents significant impact on the leishmanicidal activity. This means that the molecules may act on the leishmania parasites through an electron transfer reaction. Further theoretical investigations suggested that one probable mechanism for the activity of the thiadiazole derivatives may be due to the reduction of –NO2 substituents of the molecules to –NO.
Influence of Personal Preferences on Link Dynamics in Social Networks

We study a unique network dataset including periodic surveys and electronic logs of dyadic contacts via smartphones. The participants were a sample of freshmen entering university in the Fall 2011. Their opinions on a variety of political and social issues and lists of activities on campus were regularly recorded at the beginning and end of each semester for the first three years of study. We identify a behavioral network defined by call and text data, and a cognitive network based on friendship nominations in ego-network surveys. Both networks are limited to study participants. Since a wide range of attributes on each node were collected in self-reports, we refer to these networks as attribute-rich networks. We study whether student preferences for certain attributes of friends can predict formation and dissolution of edges in both networks. We introduce a method for computing student preferences for different attributes which we use to predict link formation and dissolution. We then rank these attributes according to their importance for making predictions. We find that personal preferences, in particular political views, and preferences for common activities help predict link formation and dissolution in both the behavioral and cognitive networks.
Remote sensing image reconstruction based on Shearlet transform and total generalized variation regularization

This paper, we propose a method that exploit total generalized variation (TGV) and Shearlet transform for image restoring. The TGV adaptive regularize different image regions at different levels and the Shearlet transform can efficiently represent image anisotropic features such as edges, curves. A new image restoration model combining TGV and Shearlet transform is proposed for image restoration. The proposed model is solved by splitting variables and applying the alternating direction method of multiplier (ADMM). Experimental results show that the proposed algorithm can effectively restore image and improve the quality.
Characteristic analysis of disk type PMLSM with/without skew

This paper deals with the prediction of no-load magnetic field distribution, armature field distribution, flux linkage, and back electromotive force for disk type permanent magnet linear synchronous motor (PMLSM). The open-circuit field distribution is predicted using a two-dimensional (2-D) analytical solution derived in terms of magnetic vector potential. The slotting and skew effect is considered using the relative permeance function. The results are validated extensively by finite element (FE) analyses and experiment results.
Rapidly Adapting Game AI

Current approaches to adaptive game AI require either a high quality of utilised domain knowledge, or a large number of adaptation trials. These requirements hamper the goal of rapidly adapting game AI to changing circumstances. In an alternative, novel approach, domain knowledge is gathered automatically by the game AI, and is immediately (i.e., without trials and without resource-intensive learning) utilised to evoke effective behaviour. In this paper we discuss this approach, called ‘rapidly adaptive game AI’. We perform experiments that apply the approach in an actual video game. From our results we may conclude that rapidly adaptive game AI provides a strong basis for effectively adapting game AI in actual video games.
Statistics of K-groups modulo p for the ring of
integers of a varying quadratic number field

For each odd prime $p$, we conjecture the distribution of the $p$-torsion subgroup of $K_{2n}(\mathcal{O}_F)$ as $F$ ranges over real quadratic fields, or over imaginary quadratic fields. We then prove that the average size of the $3$-torsion subgroup of $K_{2n}(\mathcal{O}_F)$ is as predicted by this conjecture.
Microalbuminuria in pregnancy as a predictor of preeclampsia and eclampsia.

INTRODUCTION Hypertensive disorders of pregnancy are common major complications of pregnancy and are responsible for significant morbidity and mortality in the fetus, the newborn infant and the mother. OBJECTIVES To access if a single estimation of urinary microalbumin at booking would be of value in the prediction of subsequent development of preeclampsia or eclampsia METHODS We studied at booking urinary microalbumin excretion in one hundred healthy normotensive Nigerian pregnant women attending the antenatal clinic and followed them till delivery. The women were grouped into 3 i.e. those with normal, micro and macro albumin excretion during analysis. RESULTS Ninety-three of these patients delivered at UCII, 2 had spontaneous abortions and five delivered elsewhere. At booking, 57 patients (61.3%) had normal albumin excretion and 22 (23.7%) and 14(15%) had microalbuminuria and gross albuminuria respectively. The men urinary albumin excretions for the normal, micro and gross albuminuria groups were 10.2 +/- 8.4, 67.0 +/- 55.2 and 321.4 +/- 14.0 mg/24 hours respectively. There was increased incidence of preeclampsia with an increase in albumin excretion and this was statistically significant (P value < 0.05). No patient developed eclampsia. With single urinary microalbumin excretion estimation at booking, the sensitivity, specificity, positive and negative predictive values of albuminuria were 88.9%, 67.9%, 22.2% and 98.3% respectively. CONCLUSION Urinary microalbumin excretion when used as a single test at booking appeared to predict preeclampsia with a high sensitivity but a low positive predictive value.
The MAI: A Robot for/by Everyone

Humans are dependent upon specific information to fulfill their needs, which suffices their social existence. Due to advancement in technology, humans try to satisfy their social needs through smart devices. However, these devices are not able to completely justify the human needs and humans strive for companionship to combat loneliness. We propose to design a robot (MAI) that can monitor, assist and interact with humans for their better livelihood.
Accurate 3D reconstruction via surface-consistency

We present an algorithm that fuses Multi-view stereo (MVS) and photometric stereo to reconstruct 3D model of objects filmed by multiple cameras under varying illuminations. Firstly, we obtain the surface normal scaled by albedo for each view through photometric stereo techniques. Then, based on the scaled normal, a new correspondence matching method, namely surface-consistency metric, is proposed to acquire accurate 3D positions of pixels through triangulation. After filtering the point cloud, a Poisson surface reconstruction is applied to obtain a watertight mesh. The algorithm has been implemented based on our multi-camera and multi-light acquisition system. We validate the method by complete reconstruction of challenging real objects and show experimentally that this technique can greatly improve on previous MVS results.
Improved Stability Condition for Takagi–Sugeno Fuzzy Systems With Time-Varying Delay

In this paper, the stability analysis problem of Takagi–Sugeno fuzzy systems with time-varying delay is investigated. By utilizing the Wirtinger-based integral inequality and the improved reciprocally convex combination technique, an improved stability condition is derived in terms of linear matrix inequalities. A numerical example is given to demonstrate the efficiency of the obtained result.
Expression of intercellular adhesion molecule‐1 (ICAM‐1) on renal‐cell cancer: Possible significance in host immune responses

In this study we examined the expression of intercellular adhesion molecule‐1 (ICAM‐I) in 28 cases of renal‐cell cancer (RCC). We also examined ICAM‐I expression on RCC cell lines in response to cytokines. Immunohistochemistry revealed frequent expression (23 positive cases among the 28 RCCs) of ICAM‐I in RCC. The molecule was not detected on renal tubular cells as far as could be determined. Furthermore, the number of ICAM‐I‐positive cells in RCC was significantly correlated with the degree of mononuclear cell infiltration, involving mainly T lymphocytes and a smaller number of macrophages bearing the LFA‐I molecule. Expression of ICAM‐I on RCC cell lines was augmented by in vitro treatment with interferon (IFN)‐γ, tumor necrosis factor (TNF)‐α and interleukin‐I (IL‐I)β. These results suggest that the expression of ICAM‐I on RCC might be modified by cytokines produced by tumor‐infiltrating mononuclear cells, and that ICAM‐I expression on RCC might augment the host immune reaction.
Face detection and facial personation prevention by using infrared images

We propose a face recognition system which distinguishes between a person and a face photo from infrared images. The system can detect a facial region robust for background variations because of the characteristic of infrared images. Person-photo distinction is performed by a method based on the photometric stereo. The method can detect a curved photo as well as a flat photo.
Continuous speech recognition in noise using spectral subtraction and HMM adaptation

This paper describes a scheme fur robust speech recognition at very poor signal to noise ratios. It consists of a continuous spectral subtraction (CSS) scheme integrated into a parallel model combination (PMC) compensation framework. In this CSS-PMC scheme, a smoothed estimate of the long term spectrum is continuously calculated and subtracted from the signal. At the same time, the HMMs are compensated using PMC for the signal distortion caused by the CSS stage. The paper presents an evaluation of the CSS-PMC approach using the Noisex 92 database. The results show high recognition performance for very noisy environments. For example, for the Lynx helicopter noise, CSS-PMC gives 97% accuracy at 0 dB SNR. <<ETX>>
On the Identifying Content of Instrument Monotonicity

This paper studies the identifying content of the instrument monotonicity assumption of Imbens and Angrist (1994) on the distribution of potential outcomes in a model with a binary outcome, a binary treatment and an exogenous binary instrument. Specifically, I derive necessary and sufficient conditions on the distribution of the data under which the identified set for the distribution of potential outcomes when the instrument monotonicity assumption is imposed can be a strict subset of that when it is not imposed.
Bacterial colonization of pacifiers of infants with acute otitis media

Abstract The presence of aerobic and facultative anaerobic bacteria on the surface of pacifiers used by children with acute otitis media was investigated. The surface of 40 recently used pacifiers was swabbed after they were allowed to dry for five to six minutes. The swabs were processed quantitatively for the presence of aerobic bacteria. The antibacterial activity of the pacifier material was tested in vitro. Microorganisms were isolated from 21 (52.5 per cent) pacifiers. The number of colonies per pacifier varied between one and 35 (average six). The isolates included eight α-haemolytic streptococci, six Staphylococcus epidermis, five Candida albicans, five α-haemolytic streptococci, three Neisseria spp. and two Staphylococcus aureus. The pacifier material was shown to be inhibitory against S. aureus. This study illustrated that pacifiers do not contain high numbers of organisms and therefore are not likely to serve as a source of persistence of transfer of organisms.
AS/400 64-bit powerPC-compatible processor implementation

An implementation of the 64-bit PowerPC Architecture optimized for the IBM AS/400 commercial environment is described. This 64-bit BiCMOS semicustom implementation runs at a clock rate of 170 MHz. The processor features a 4-way superscalar pipelined fixed point unit which can dispatch and execute up to 4 instructions each cycle, a floating point unit with a peak rate of 500 MFLOPs, 8-Kbyte L0 instruction cache, 256-Kbyte L1 cache, and support for 64-Gbyte of main storage. A 4-way rightly-coupled symmetric multi-processor system is one of several configurations supported by this implementation. <<ETX>>
Semantic Structure and Interpretability of Word Embeddings

Dense word embeddings, which encode meanings of words to low-dimensional vector spaces, have become very popular in natural language processing (NLP) research due to their state-of-the-art performances in many NLP tasks. Word embeddings are substantially successful in capturing semantic relations among words, so a meaningful semantic structure must be present in the respective vector spaces. However, in many cases, this semantic structure is broadly and heterogeneously distributed across the embedding dimensions making interpretation of dimensions a big challenge. In this study, we propose a statistical method to uncover the underlying latent semantic structure in the dense word embeddings. To perform our analysis, we introduce a new dataset (SEMCAT) that contains more than 6500 words semantically grouped under 110 categories. We further propose a method to quantify the interpretability of the word embeddings. The proposed method is a practical alternative to the classical word intrusion test that requires human intervention.