Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Predictive Factors of Empyema in Children with Parapneumonic Pleural Effusion

Background Empyema is a complication of bacterial pneumonia which has a particular importance due to its significant morbidity and mortality in children. The aim of this study was to investigate the prognostic factors of empyema in children with parapneumonic pleural effusion. Materials and Methods: This retrospective cross-sectional study investigated all patients under 14 years old with parapneumonic pleural effusion associated with community-acquired pneumonia (CAP) who were hospitalized in Tabriz Children's Hospital, Tabriz, Iran, between March 2016 and March 2020 (4 years). Demographic and clinical characteristics were collected via medical records of patients and assessed as possible factors for empyema. These included: pre-treatments with ibuprofen, antibiotic therapy before admission, duration of the disease, underling diseases, fever, tachycardia, tachypnea, and also some paraclinical variables such as leukocytosis, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), acidosis, blood, and pleural fluid culture results. Results: Empyema associated with parapneumonic pleural effusion was detected in 47 patients (41.2%) of 114 hospitalized children. Based on logistic regression modeling, ibuprofen consumption history (OR = 7.16; 95% CI: 1.35-37.80; p = 0.02), tachypnea (OR = 17.13; 95% CI: 1.63- 179.90; p = 0.01), and leukocytosis (OR= 5.66; 95% CI: 2.10-15.24; p = 0.003) had a significant relationship with empyema occurrence. Conclusion Based on the findings of this study, the history of ibuprofen use, tachypnea, and leukocytosis were predictive factors for empyema in children with parapneumonic pleural effusion as a result of community-acquired pneumonia.
Phenotypic, molecular and pathogenic characterization of Phlyctema vagabunda, causal agent of olive leprosy

Olive leprosy, caused by the fungus Phlyctema vagabunda, is a classic fruit rot disease widespread in the Mediterranean basin. From 2009 to 2013, new disease symptoms consisting of small circular necrotic leaf lesions, coin branch canker and shoot dieback were observed in Spanish and Portuguese olive orchards showing intense defoliation. Phlyctema-like anamorphs were consistently isolated from symptomatic leaves and shoots. Representative isolates from affected leaves, shoots and fruits were characterized based on morphology of colonies and conidia, optimum growth temperature and comparison of DNA sequence data from four regions: ITS, tub-2, MIT and rpb2. In addition, pathogenicity tests were performed on apple and olive fruits, and on branches and leaves of olive trees. Maximum mycelial growth rate ranged between 0.54 and 0.73 mm day−1. Conidia produced on inoculated apple fruits showed slight differences in morphology among the representative fungal isolates evaluated. Phylogenetic analysis clustered all of the Phlyctema-like isolates in the same clade,identifying them as Phlyctema vagabunda. On fruits, influence of wounding, ripening and cultivar resistance was studied, with cv. Blanqueta being the most susceptible cultivar. On branches, mycelial-plug inoculation method reproduced olive leprosy symptoms and caused shoot dieback. On leaves, Koch′s postulates were fulfilled and the pathogen caused characteristic necrotic spots and plant defoliation. This is the first time that the pathogenicity of Ph. vagabunda in olive leaves has been demonstrated. This article is protected by copyright. All rights reserved.
Bayesian Learning-Based Doubly-Selective Sparse Channel Estimation for Millimeter Wave Hybrid MIMO-FBMC-OQAM Systems

We design and analyse filter bank multicarrier (FBMC) offset quadrature amplitude modulation (OQAM)-based millimeter wave (mmWave) hybrid multiple-input multiple-output (MIMO) systems. Furthermore, a novel channel estimation model is conceived for quasi-static mmWave hybrid MIMO-FBMC-OQAM (mmH-MFO) systems that reconfigures the radio-frequency (RF) circuitry during the transmission of zero symbols. Subsequently, a Bayesian learning (BL) technique is proposed for sparse channel estimation, which relies on multiple measurement vectors combined with selective subcarrier grouping for enhanced estimation. Additionally, an online BL based Kalman filter (OBL-KF) is designed for sparse channel tracking in doubly-selective mmH-MFO systems. Then the Bayesian Cramér-Rao lower bounds (BCRLBs) are derived for characterizing the performance of the proposed frequency-selective and doubly-selective channel estimation techniques. Finally, a limited feedback based algorithm relying on beamspace channel estimates is proposed for hybrid precoder/combiner design. The accuracy of our analytical results is confirmed by our simulation results.
Advances in flowering phenology across the Northern Hemisphere are explained by functional traits

Aim: Numerous studies have reported changes in first flowering day (FFD-changes) in response to changes in climate. However, regarding the direction (advances versus delays) and the intensity (number of days/decade) of FFD-changes, species show differences even when observed in the same location. Here, we examine the extent to which plant traits can explain observed differences in the response of flowering phenology in trees, shrubs, herbs and grasses. Location: Eighteen sites distributed over the Northern Hemisphere. Methods: We compiled data from the literature on FFD-changes over recent decades for 562 species (648 observations). We related FFD-changes to predictor variables associated with (a) changes in climate, (b) local site conditions and (c) traits. Results: Of all FDD-changes, 80.4% were FFD-advances, 69.9% not exceeding 5 days/decade, and 10.5% exceeding 5 days/decade, whereas 19.6% reported delays. The intensity of FFD-advances could be explained by several predictor variables from all three groups (a–c). The importance of these variables differed between the growth forms. Overall, decreasing precipitation was more important than increasing temperature in explaining FFD-advances. FFD-advances were strongest in polar tundra and in dry and warm habitats. Traits related to competition and growth rate, like plant height, specific leaf area and leaf dry matter content, had substantial explanatory power in the models. Traits had the highest overall importance in trees and grasses. In herbs they were of equal importance with changes in climate. In shrubs, variables related to site conditions best explained the intensity of FFD-advances. Main conclusions: Plant traits are important to understand species-specific and growth form-specific differences in phenological responses to climatic changes. Hence, in future observations and predictions of plant phenology, traits should be taken into consideration, especially those related to competition and growth rate, as they improve our understanding of adaptations leading to phenological changes.
Study of Clear Air Turbulence Related to Tropopause Folding over the Romanian Airspace

Clear air turbulence (CAT) poses a significant threat to aviation. CAT usually occurs in the lower stratosphere and the upper troposphere. It is generally associated with large scale waves, mountain waves, jet streams, upper-level fronts and tropopause folds. Aircraft can experience CAT when flying in proximity of a tropopause fold. To better understand and diagnose tropopause fold- associated CAT we selected a series of cases from among those reported by pilots between June 2017 and December 2018 in the Romanian airspace. Data on turbulence were used in conjunction with meteorological data, satellite imagery, and vertical profiles. Additionally, a set of indices as Ellrod, horizontal temperature gradient, Dutton, and Brown were computed to diagnose CAT associated with tropopause folding. These indices were also analyzed to test the physics mechanisms that may explain the occurrence of severe turbulence. Results show that out of the 420 cases announced by pilots, severe turbulence was reported in 80 cases of which 13 were associated with tropopause folding.
AP-4 mediated ATG9A sorting underlies axonal and autophagosome biogenesis defects in a mouse model of AP-4 deficiency syndrome

Adaptor protein (AP) complexes have critical roles in transmembrane protein sorting. AP-4 remains poorly understood in the brain despite its loss of function leading to a hereditary spastic paraplegia termed AP-4 deficiency syndrome. Here we demonstrate that knockout (KO) of AP-4 in a mouse model leads to thinning of the corpus callosum and ventricular enlargement, anatomical defects previously described in patients. At the cellular level, we find that AP-4 KO leads to defects in axonal extension and branching, in addition to aberrant distal swellings. Interestingly, we show that ATG9A, a key protein in autophagosome maturation, is critically dependent on AP-4 for its sorting from the trans-golgi network. Failure of AP-4 mediated ATG9A sorting results in its dramatic retention in the trans-golgi network in vitro and in vivo leading to a specific reduction of the axonal pool of ATG9A. As a result, autophagosome biogenesis is aberrant in the axon of AP-4 deficient neurons. The specific alteration to axonal integrity and axonal autophagosome maturation in AP-4 knockout neurons may underpin the pathology of AP-4 deficiency.
Thinking Through Transfer: Examining How Community College Students Make Transfer Decisions

Objective: For many students, community college is a convenient first step toward a bachelor’s degree. Yet, although more than 80% of those who enroll in community colleges intend to transfer to a 4-year institution, fewer than 35% do so within 6 years. Quantitative data reveal the presence of a transfer gap and there is extensive research on college choice for high school students, but little qualitative research has been done to examine the transfer process for community college students to identify what drives their decisions. Method: In this article, we draw on interviews with 58 community college students in Texas to examine how they made transfer decisions. Results: We find that their decision-making and transfer pathways were complex and nonlinear in ways that were particular to the uncertainty of the community college context. For a subset of students, we identify minor hurdles that could derail their decision-making, lengthen their timelines to transfer, or lead to a failure to transfer. Contribution: By illuminating student pathways to transfer using qualitative research, our work identifies potential areas where policy and practice could strengthen transfer to improve student outcomes.
Core RxLR Effectors in Phytopathogenic Oomycetes: A promising Way to Breeding for Durable Resistance in Plants?

Phytopathogenic oomycetes are known to infect a host plant successfully due to their ability to secrete a set of protein effectors. Of interest to many researchers are effectors with the N-terminal RxLR motif (Arginine-any amino acid-Leucine-Arginine). Owing to the genome sequencing, we can now comprehend the high level of diversity among oomycete effectors, and similarly, their conservation within and among species core RxLR effectors (CREs). Currently, there are a couple of putative CREs that have been identified in oomycetes. The functional characterization of these CREs proposes their virulence role with the potential of targeting central cellular processes that are conserved across diverse plant species. This could be harnessed in engineering plants for broad-spectrum and durable resistance.
ASYMPTOTIC ANALYSIS OF PERES’ ALGORITHM FOR RANDOM NUMBER GENERATION

von Neumann [(1951). Various techniques used in connection with random digits. National Bureau of Standards Applied Math Series 12: 36–38] introduced a simple algorithm for generating independent unbiased random bits by tossing a (possibly) biased coin with unknown bias. While his algorithm fails to attain the entropy bound, Peres [(1992). Iterating von Neumann's procedure for extracting random bits. The Annals of Statistics 20(1): 590–597] showed that the entropy bound can be attained asymptotically by iterating von Neumann's algorithm. Let $b(n,p)$ denote the expected number of unbiased bits generated when Peres’ algorithm is applied to an input sequence consisting of the outcomes of $n$ tosses of the coin with bias $p$. With $p=1/2$, the coin is unbiased and the input sequence consists of $n$ unbiased bits, so that $n-b(n,1/2)$ may be referred to as the cost incurred by Peres’ algorithm when not knowing $p=1/2$. We show that $\lim _{n\to \infty }\log [n-b(n,1/2)]/\log n =\theta =\log [(1+\sqrt {5})/2]$ (where $\log$ is the logarithm to base $2$), which together with limited numerical results suggests that $n-b(n,1/2)$ may be a regularly varying sequence of index $\theta$. (A positive sequence $\{L(n)\}$ is said to be regularly varying of index $\theta$ if $\lim _{n\to \infty }L(\lfloor \lambda n\rfloor )/L(n)=\lambda ^\theta$ for all $\lambda > 0$, where $\lfloor x\rfloor$ denotes the largest integer not exceeding $x$. ) Some open problems on the asymptotic behavior of $nh(p)-b(n,p)$ are briefly discussed where $h(p)=-p\log p- (1-p)\log (1-p)$ denotes the Shannon entropy of a random bit with bias $p$.
Study on inhibitors from acid pretreatment of corn stalk on ethanol fermentation by alcohol yeast

The inhibitory effects of the main inhibitors formed during acid pretreatment of corn stalk were studied through ethanol fermentations of model substrates and hydrolysates from corn stalk by alcohol yeast. Experimental results showed that the tested inhibitors had no significant effect on ethanol fermentations when they were added separately at a concentration according to analysis results from hydrolysate of corn stalk. However, when they were added as a mixture, the inhibitory effects became obvious. With the increase of concentration, there was a delay in ethanol productivity. But complete inhibition was observed at 5.0 g L−1 furfural, 10.0 g L−1 acetic acid, 7.0 g L−1 ferulic acid, and 7.0 g L−1p-coumaric acid, respectively. The inhibitory effect decreased in the order: furfural > acetic acid > ferulic acid > p-coumaric acid > HMF. These results suggest that a high concentration of inhibitor has a strong negative influence on ethanol fermentation, but the inhibiting abilities of various inhibitors are different.
Adaptive compliant controller for space robot stabilization in post-capture phase

Safety and reliability are the primary prerequisites of space robotic manipulation. Due to the inaccurate inertial parameters of the tumbling target, tracking the desired trajectory directly will lead to the build up of large contact force and torque and damage the grasping point. The measurement noise in the contact wrenches will disturb the application of compliant stabilization strategy, and lead to mission failure. In order to coordinate the desired motion and contact, a compliant stabilization is required for realistic application. However, the measurement noise in the measured contact will disturb the application of compliant control scheme. According to these facts, herein, an adaptive compliant stabilization control scheme is proposed for a safe and reliable stabilization process. With the reference of the unsafe desired motion, a safe admittance motion is generated with an adaptive stiffness virtual spring. In consideration of the parameter selection and the presence of the contact wrenches measurement noise, a neural network-based coordinated adaptive impedance tracking controller is designed to track the safe motion and consume the transmitted energy from the tumbling target at the same time. With the benefit of the combination of the admittance motion and the coordinated adaptive impedance tracking controller, interactions at the grasping point can be controlled and the target can be stabilized under the influence of the measurement noise in the contact wrenches. Furthermore, safety and reliability of the proposed control scheme are validated via digital simulations.
Biom: A Biometric Currency a New Approach to Banking

Our modern financial system traces its origin to the ancient Babylonian banking system. The same fractional lending idea that is used today was used by merchants in the regions of ancient Babylonia, Assyria and Sumeria around 2000 BC. Later, the idea found its way to ancient Greece, the Roman Empire, China, India and then to us. The fractional lending concept was not the fruit of scientific research like what is done in other scientific endeavors where most of the best ideas are the result of a long process of trial and error. Is it not time to rethink the way we do banking in this digital age and try other ideas? The last 40 years of cryptographic research culminated with the creation of Bitcoin currency system in 2009. We would like to expand on this and introduce three ideas to help rethink the banking system of the 21 st century: 1) the concept of a biometric currency, 2) the concept of being your own bank and issue your own loans with zero-interest rate 3) and redefining the fractional reserve lending. We propose a biometric currency concept that will enable people to self finance and to safely store their money in their hands. Contrary to cryptocurrencies that are issued by blockchain miners and Fiat currencies that are issued by bankers, Biom will be issued by everyone. The goal is to create from human life a precious asset like Gold that will benefit all.
End-to-End Neural Matching for Semantic Location Prediction of Tweets

The impressive increasing availability of social media posts has given rise to considerable research challenges. This article is concerned with the problem of semantic location prediction of geotagged tweets. The underlying task is to associate to a social media post, the focal spatial object, if any (e.g., Place Of Interest POI), it topically focuses on. Although relevant for a number of applications such as POI recommendation, this problem has not so far received the attention it deserves. In previous work, the problem has mainly been tackled by means of language models that rely on costly probability estimation of word relevance across spatial regions. We propose the Spatially-aware Geotext Matching (SGM) model, which relies on a neural network learning framework. The model combines exact word-word-local interaction matching signals with semantic global tweet-POI interaction matching signals. The local interactions are built over kernel spatial word distributions that allow revealing spatially driven word pair similarity patterns. The global interactions consider the strength of the interaction between the tweet and the POI from both the spatial and semantic perspectives. Experimental results on two real-world datasets demonstrate the effectiveness of our proposed SGM model compared to state-of-the-art baselines including language models and traditional neural interaction-based models.
Construction of Auxotrophic Strains of Candida albicans Clinical Strains

Candida albicans is a yeast commonly found in the gastrointestinal and genitourinary tracts of healthy individuals. Although part of the normal human microbiome, C. albicans can be problematic to certain populations such as individuals with compromised immune systems or those taking broad-spectrum antibiotics. C. albicans is the cause of diaper rash, thrush, vaginal yeast infections, and is a leading cause of systemic infections in hospitals. The focus of C. albicans research has almost entirely been focused on a single strain background, SC5314, found in clade I. This research will contribute to a larger project to delete several marker genes (URA3, LEU2, ARG4, HIS1) that are commonly used for C. albicans genetics in order to create mutant strains. These genetic tools can then be used to compare and better understand the pathogenesis and antifungal drug response across the four major clades that, along with clade I containing SC5314, cause most C. albicans infections in the United States.
Development of efficient D-lactic acid-producing Saccharomyces cerevisiae strains by evolutionary and rational metabolic engineering

Development of efficient D-lactic acidproducing Saccharomyces cerevisiae strains by evolutionary and rational metabolic engineering Seung-Ho Baek School of Chemical and Biological Engineering The Graduate School Seoul National University There is an increasing demand for microbial production of optically pure lactic acid (LA) as a monomer for biodegradable poly lactic acid (PLA). Saccharomyces cerevisiae, having high acid tolerance, has emerged as a promising LA-producing host. In this dissertation, efficient D-LA-producing strains of S. cerevisiae were developed using rational metabolic engineering and adaptive evolution. Firstly, to generate D-LA-producing strain, highly stereospecific D-lactate dehydrogenase gene (ldhA, designated Lm.ldhA) from Leuconostoc mesenteroides subsp. mesenteroides ATCC 8293 was selected and expressed in S. cerevisiae
Understanding L2 Speech Production : Implications for Teaching Speaking in EFL Classroom

As communicative competence has become a primary goal of English education in many Asian contexts, EFL curricula increasingly focus on students’ speaking performance. Considering the demands of cultivating competent L2 speakers, this study investigates factors associated with L2 speaking performance in a Korean EFL college classroom setting. Fifty-one students enrolled in a basic English speaking course participated. They completed five tasks measuring two linguistic variables (i.e., learners’ perception of segmental and suprasegmental features), a cognitive variable (i.e., short-term memory), and two language ability variables (i.e., listening comprehension ability and vocabulary size). They also completed a production task (i.e., picture narration). The results indicate that sensitivity to suprasegmental features (e.g., pause, stress, and intonation) and listening ability are associated with the quality of the learners’ spontaneous speech production, while sensitivity to segmental information (e.g., minimal pairs), short-term memory, and vocabulary size are not. These findings suggest the importance of explicit instruction in suprasegmental features to improve L2 production as well as perception ability, and that integrating listening and speaking instruction in L2 curricula may be the most effective means of improving learners’ speech.
Estudo relacional entre gênero e rendimento escolar de alunos do Ensino Fundamental e Médio de Brasília-Brasil

Este estudo se propõe descobrir relações entre gênero e rendimento escolar, composto em especial por valores de metas acadêmicas (3 fatores psicossociais não-cognitivos), de uma amostra de alunos de 11 a 17 anos inseridos na rede de ensino fundamental II e médio de Brasília-DF, capital do Brasil. A pesquisa se inscreveu em uma perspectiva motivacional, que se sustenta em um desenho transversal descritivo e correlacional com metodologia qualitativa e quantitativa. Se aplicou o Questionário de Metas Acadêmicas de Hayamizu e Weiner (1991). Descreveu-se e aplicou, empiricamente, a um grupo de alunos dos gêneros masculino e feminino. Foi possível demonstrar que não existiram correlações entre as variáveis devido à normalidade estatística da amostra. No entanto, os resultados da descrição fazem supor impactos positivos em metas de aprendizagem e metas de obtenção, pelo alto nível de pontuação obtido na descrição da amostra e pela consistência dos dados, e impactos negativos em metas de reforço social. O fato mais chamativo foi a contradição encontrada com os resultados obtidos por Cominetti e Ruiz (1997), que se baseiam em sustentar que o fator gênero ajuda a modular as relações com o rendimento escolar. Esta pesquisa contribui cientificamente com novos elementos às literaturas sobre o assunto.