Miracle-dz/UniFAR-FTUs huggingface dataset:
Temperament in Infancy Predicts Internalizing and Externalizing Problem Behavior at Age 5 in Children With an Increased Likelihood of Autism Spectrum Disorder

Differences in temperament have been linked to later mental health. Children with autism spectrum disorder (ASD) have an increased likelihood of experiencing such problems, including anxiety, depression, attention deficit/hyperactivity disorder, and oppositional defiant disorder; yet, relations between early temperament and later mental health are not well understood. In this paper, we assess the relationship between temperament in infancy and internalizing and externalizing behavior at age 5, in 178 children at an increased likelihood of being diagnosed with ASD (i.e., younger siblings of children with ASD). Temperament was assessed using the parent-reported Infant Behavior Questionnaire (IBQ) at 6 and 12 months of age and the Toddler Behavior Assessment Questionnaire-Revised (TBAQ-R) at 24 months of age. Mental health problems were assessed using the parent-reported Child Behavior Checklist (CBCL) at age 5. The data were analyzed using hierarchical multiple regressions, with individual temperament subscale scores as single predictor variables (Subscale Score) or temperament profiles using confirmatory factor analyses (Person-Centered Profile) in the first block, Autism Diagnostic Observation Schedule total severity scores at age 3 in the second block, and expressive and receptive language scores (from Mullen Scales of Early Learning) at age 3 in the third block for each model. Three main findings were: (1) 4 of 6 IBQ subscales at both 6 and 12 months significantly predicted internalizing and externalizing problems at age 5; (2) 9 and 8 of 13 TBAQ-R subscales at 24 months significantly predicted internalizing and externalizing problems, respectively, at age 5; and (3) a “sticky attention” temperament profile significantly predicted internalizing problems, whereas a “low-focused” profile significantly predicted externalizing problems, both at age 5. The results of this study support the supposition that temperament is a trans-diagnostic risk factor for later mental health conditions. Exploring temperament profiles and trajectories may illuminate early avenues for prevention in siblings of children with ASD who are at an increased likelihood of experiencing mental health problems, regardless of ASD diagnostic status.
Indoor Pool Game and Substance Abuse as Trajectories to Students’ Academic Procrastination: The Mediation Role of Self-Regulation

Background Over the last decade, indoor pool games (IPGs) and substance abuse (SA) became a remarkable emerging addictive behavior among adolescent university students. With the failure of educational quality and retention of learners, boomerangs around the university local environment in line with the students’ learning culture were not considered in many countries including Ethiopia. Thus, this study aimed to examine the trajectory and contribution of an IPG and SA to students’ academic procrastination (AP) as determinants of quality education. Methods A sequential explanatory mixed-methods design was employed. Self-reporting questionnaires, interview guides, and an observation checklist were used to collect data. All self-reporting items were adapted from previous scales. By using simple random sampling techniques, 237 undergraduate university students were selected for obtaining the quantitative data, and using purposive sampling, 12 interviewees were selected to collect the qualitative data. The SPSS AMOS version 25 was used to compute the multiple mediation path analysis. The Hayes PROCESS macro model was used. Furthermore, the thematic content analysis method was employed for the qualitative data. Results A direct path analysis was established between IPG, SA, and AP. The path analysis model indicated that IPG did not significantly predict AP. Moreover, SA significantly predicted AP. In addition, SR had a partial mediating effect on the relationship between IPG, SA, and AP. Conclusion The study concluded that IPG and substances available around the university local environment found trajectories to students’ AP, which in turn affects the quality of education.
The Neural Mechanism of Long-Term Motor Training Affecting Athletes’ Decision-Making Function: An Activation Likelihood Estimation Meta-Analysis

Decision-making is an advanced cognitive function that promotes information processes in complex motor situations. In recent years, many neuroimaging studies have assessed the effects of long-term motor training on athletes’ brain activity while performing decision-making tasks, but the findings have been inconsistent and a large amount of data has not been quantitatively summarized until now. Therefore, this study aimed to identify the neural mechanism of long-term motor training affecting the decision-making function of athletes by using activation likelihood estimation (ALE) meta-analysis. Altogether, 10 studies were included and comprised a total of 350 people (168 motor experts and 182 novices, 411 activation foci). The ALE meta-analysis showed that more brain regions were activated for novices including the bilateral occipital lobe, left posterior cerebellar lobe, and left middle temporal gyrus (MTG) in decision-making tasks compared to motor experts. Our results possibly suggested the association between long-term motor training and neural efficiency in athletes, which provided a reference for further understanding the neural mechanisms of motor decision-making.
Epidemiological Evidence for Fecal-Oral Transmission of Murine Kobuvirus

Background Murine Kobuvirus (MuKV) is a novel picornavirus of the genus Kobuvirus, and was first identified in the feces of murine rodents in the USA in 2011. There is limited information on the transmission route of MuKV. Thus, we conducted a study to investigate virus detection rates in fecal, serum, throat, and lung tissue samples from murine rodents. Results A total of 413 fecal samples, 385 lung samples, 269 throat swab samples, and 183 serum samples were collected from 413 murine rodents (Rattus norvegicus, Rattus tanezumi, and Rattus rattus) captured in urban Shenzhen. Kobuviruses were detected via RT-PCR. Only fecal samples were positive, with prevalence rates of 34.9% in Rattus norvegicus and 29.4% in Rattus tanezumi. Phylogenetic analysis based on partial 3D and complete VP1 sequence regions indicated that all of the MuKV sequences obtained belonged to Aichivirus A, and were genetically closely related to other MuKVs reported in China, Hungary, and the USA. Twenty-eight full-length MuKV sequences were acquired. Phylogenetic analysis of two sequences randomly selected from the two species (SZ59 and SZ171) indicated that they shared very high nucleotide and amino acid identity with one another (94.0 and 99.3%, respectively), and comparison with human Kobuvirus revealed amino acid identity values of ~80%. Additionally, a sewage-derived sequence shared high similarity with the rat-derived sequences identified in this study, with respective nucleotide and amino acid identity values from 86.5 and 90.7% to 87.2 and 91.1%. Conclusion The results of the current study provide evidence that murine Kobuvirus is transmitted via the fecal-oral route.
Acoustic Mapping of Gas Stored in Sediments of Shallow Aquatic Systems Linked to Methane Production and Ebullition Patterns

Bubble-mediated transport is the predominant pathway of methane emissions from inland waters, which are a globally significant sources of the potent greenhouse gas to the atmosphere. High uncertainties exist in emission estimates due to high spatial and temporal variability. Acoustic methods have been applied for the spatial mapping of ebullition rates by quantification of rising gas bubbles in the water column. However, the high temporal variability of ebullition fluxes can influence estimates of mean emission rates if they are based on reduced surveys. On the other hand, echo sounding has been successfully applied to detect free gas stored in the sediment, which provide insights into the spatial variability of methane production and release. In this study, a subtropical, midsize, mesotrophic drinking water reservoir in Brazil was investigated to address the spatial and temporal variability of free gas stored in the sediment matrix. High spatial resolution maps of gas content in the sediment were estimated from echo-sounding surveys. The gas content was analyzed in relation to water depth, sediment deposition, and organic matter content (OMC) available from previous studies, to investigate its spatial variability. The analysis was further supported by measurements of potential methane production rates, porewater methane concentration, and ebullition flux. The largest gas content (above average) was found at locations with high sediment deposition, and its magnitude depended on the water depth. At shallow water depth (<10 m), high methane production rates support gas-rich sediment, and ebullition is observed to occur rather continuously. At larger water depth (>12 m), the gas stored in the sediment is released episodically during short events. An artificial neural network model was successfully trained to predict the gas content in the sediment as a function of water depth, OMC, and sediment thickness (R 2 = 0.89). Largest discrepancies were observed in the regions with steep slopes and for low areal gas content (<4 L m−2). Although further improvements are proposed, we demonstrate the potential of echo-sounding for gas detection in the sediment, which combined with sediment and water body characteristics provides insights into the processes that regulate methane emissions from inland waters.
Cavitation Influence in 1D Part-load Vortex Models

Residual swirl in the draft tube of Francis turbines may cause annoying low- frequency pulsation of pressure and power output, in particular during part-load operation. A 1D analytical model for these dynamic phenomena would enable simulation by some conventional method for computing hydraulic transients. The proper structure of such a model has implications for the prediction of prototype behaviour based on laboratory tests. The source of excitation as well as the dynamic transmission behaviour of the draft tube flow may both be described either by lumped or distributed parameters. The distributed version contains more information and, due to limited possibilities of identification, some data must be estimated. The distributed cavitation compliance is an example for this dilemma. In recent publications, the customary assumption of a constant wave speed has produced dubious results. The paper presents a more realistic model for distributed compressibility. The measured influence of the Thoma number is applied with the local cavitation factor. This concept is less sensitive to modelling errors and explains both the Thoma and Froude number influence. The possible effect of the normally unknown non-condensable gas content in the vortex cavity is shortly commented. Its measurement in future tests is recommended. It is also recommended to check the available analytical vortex models for possible dispersion effects.
Long-Lasting Desynchronization of Plastic Neuronal Networks by Double-Random Coordinated Reset Stimulation

Hypersynchrony of neuronal activity is associated with several neurological disorders, including essential tremor and Parkinson’s disease (PD). Chronic high-frequency deep brain stimulation (HF DBS) is the standard of care for medically refractory PD. Symptoms may effectively be suppressed by HF DBS, but return shortly after cessation of stimulation. Coordinated reset (CR) stimulation is a theory-based stimulation technique that was designed to specifically counteract neuronal synchrony by desynchronization. During CR, phase-shifted stimuli are delivered to multiple neuronal subpopulations. Computational studies on CR stimulation of plastic neuronal networks revealed long-lasting desynchronization effects obtained by down-regulating abnormal synaptic connectivity. This way, networks are moved into attractors of stable desynchronized states such that stimulation-induced desynchronization persists after cessation of stimulation. Preclinical and clinical studies confirmed corresponding long-lasting therapeutic and desynchronizing effects in PD. As PD symptoms are associated with different pathological synchronous rhythms, stimulation-induced long-lasting desynchronization effects should favorably be robust to variations of the stimulation frequency. Recent computational studies suggested that this robustness can be improved by randomizing the timings of stimulus deliveries. We study the long-lasting effects of CR stimulation with randomized stimulus amplitudes and/or randomized stimulus timing in networks of leaky integrate-and-fire (LIF) neurons with spike-timing-dependent plasticity. Performing computer simulations and analytical calculations, we study long-lasting desynchronization effects of CR with and without randomization of stimulus amplitudes alone, randomization of stimulus times alone as well as the combination of both. Varying the CR stimulation frequency (with respect to the frequency of abnormal target rhythm) and the number of separately stimulated neuronal subpopulations, we reveal parameter regions and related mechanisms where the two qualitatively different randomization mechanisms improve the robustness of long-lasting desynchronization effects of CR. In particular, for clinically relevant parameter ranges double-random CR stimulation, i.e., CR stimulation with the specific combination of stimulus amplitude randomization and stimulus time randomization, may outperform regular CR stimulation with respect to long-lasting desynchronization. In addition, our results provide the first evidence that an effective reduction of the overall stimulation current by stimulus amplitude randomization may improve the frequency robustness of long-lasting therapeutic effects of brain stimulation.
A Prognostic Analysis of the Outcomes in Patients With Anti-γ-Aminobutyric Acid B Receptor Encephalitis

Objective To evaluate neurological function and its influencing factors in patients with anti-γ -aminobutyric acid B receptor (GABABR) encephalitis. Methods This was a clinical cohort study of patients diagnosed with anti-GABABR encephalitis; long-term follow-up was performed by telephone. Clinical factors associated with prognosis were analyzed, including clinical manifestations, laboratory examinations, imaging features, tumor comorbidities and therapeutic responses. Results Twenty-two patients with anti-GABABR encephalitis were evaluated (median age: 55 years). Lung cancer was detected in eight patients. All were with serum tumor markers (mainly NSE), and three of them had additional onconeuronal antibodies. The patients with tumors were older than the patients without tumors and more likely to develop status epilepticus (62.5% vs. 14.3%; p = 0.052), central hypoventilation (50% vs. 7.1%; p = 0.039), and hyponatremia (87.5% vs. 14.3%; p = 0.001). The patients with tumors had higher mortality (87.5% vs. 0%; p < 0.05). Although 92.9% of the patients without tumors became functionally independent (mRS ≤2), sequelae of symptomatic seizures, neuropsychiatric symptoms, and cognitive impairment were still observed in 14.3%, 21.4%, and 21.4% of patients, respectively. Conclusions (1) Elderly patients with anti-GABABR antibodies, especially those with severe symptoms, serum tumor markers, and additional onconeuronal antibodies, should be screened for lung cancer. (2) Anti-GABABR encephalitis with tumors has a poor prognosis. (3) Most patients without tumors achieve self-care, but some still experience remaining neurological deficits.
Combining Coarse-Grained Simulations and Single Molecule Analysis Reveals a Three-State Folding Model of the Guanidine-II Riboswitch

Riboswitch RNAs regulate gene expression by conformational changes induced by environmental conditions and specific ligand binding. The guanidine-II riboswitch is proposed to bind the small molecule guanidinium and to subsequently form a kissing loop interaction between the P1 and P2 hairpins. While an interaction was shown for isolated hairpins in crystallization and electron paramagnetic resonance experiments, an intrastrand kissing loop formation has not been demonstrated. Here, we report the first evidence of this interaction in cis in a ligand and Mg2+ dependent manner. Using single-molecule FRET spectroscopy and detailed structural information from coarse-grained simulations, we observe and characterize three interconvertible states representing an open and kissing loop conformation as well as a novel Mg2+ dependent state for the guanidine-II riboswitch from E. coli. The results further substantiate the proposed switching mechanism and provide detailed insight into the regulation mechanism for the guanidine-II riboswitch class. Combining single molecule experiments and coarse-grained simulations therefore provides a promising perspective in resolving the conformational changes induced by environmental conditions and to yield molecular insights into RNA regulation.
Statistical Analysis and Machine Learning Prediction of Disease Outcomes for COVID-19 and Pneumonia Patients

The Coronavirus Disease 2019 (COVID-19) has spread all over the world and impacted many people’s lives. The characteristics of COVID-19 and other types of pneumonia have both similarities and differences, which confused doctors initially to separate and understand them. Here we presented a retrospective analysis for both COVID-19 and other types of pneumonia by combining the COVID-19 clinical data, eICU and MIMIC-III databases. Machine learning models, including logistic regression, random forest, XGBoost and deep learning neural networks, were developed to predict the severity of COVID-19 infections as well as the mortality of pneumonia patients in intensive care units (ICU). Statistical analysis and feature interpretation, including the analysis of two-level attention mechanisms on both temporal and non-temporal features, were utilized to understand the associations between different clinical variables and disease outcomes. For the COVID-19 data, the XGBoost model obtained the best performance on the test set (AUROC = 1.000 and AUPRC = 0.833). On the MIMIC-III and eICU pneumonia datasets, our deep learning model (Bi-LSTM_Attn) was able to identify clinical variables associated with death of pneumonia patients (AUROC = 0.924 and AUPRC = 0.802 for 24-hour observation window and 12-hour prediction window). The results highlighted clinical indicators, such as the lymphocyte counts, that may help the doctors to predict the disease progression and outcomes for both COVID-19 and other types of pneumonia.
Cross-Sectional Survey of Prophylactic and Metaphylactic Antimicrobial Use in Layer Poultry Farming in Cameroon: A Quantitative Pilot Study

An evaluation of the patterns of antimicrobial use in livestock can help understand the increasing level of antimicrobial resistance worldwide. This study aimed at evaluating antimicrobial usage in modern layer poultry farms in the West Region of Cameroon. In this light, 70 layer poultry farms and 4 veterinary pharmacies were surveyed. Data on antimicrobial use were collected through interviews using a quantitative-frequency questionnaire and consultation of medical records. The four veterinary pharmacies sold a total of 2.8 tons of antimicrobials (active ingredients) during 2011. At the level of farms, 297 kg of antimicrobials (active ingredients) were used in the 50 layer poultry farms surveyed. Tetracycline, sulfonamides, quinolones, and β-lactams (aminopenicillins) were the most sold and used drugs in layer farms. As for treatment indication, metaphylactic (58.1%) and prophylactic (41.9%) treatments were the most observed practices, and nearly all (99%) treatments were administered per os as remedies to respiratory (33.4%) and digestive (24.7%) tract symptoms. Overall, 78.2% of antimicrobials sold in pharmacies and 67.3% used in the farms belonged to the class of critically important antimicrobials of the WHO categorization of antimicrobials according to their importance to human medicine. Doxycycline, sulfonamide, ampicillin, and streptomycin, which have been banned for layer poultry in the production of eggs for human consumption, were still used in Cameroon. The treatment incidences based on the used daily dose (TIUDD) and animal daily dose (TIADD) were 11.59 and 10.45, respectively. In regard to dosage correctness based on the UDD/ADD ratio, aminoglycosides (100%), macrolides (90.6%), and tetracyclines (74.5%) were the most underdosed, while trimethoprim sulfonamides (45.8%) and β-lactams (35.7%) were overdosed. This study highlights an irrational antimicrobial usage in layer poultry farms. Regulation of the use of antimicrobials and the education of farmers on adequate antimicrobial use are essential to preserve the effectiveness of drugs in both humans and animals.
Seismic strengthening of existing RC beam‐column joints by wing walls

Numerous non‐ductile reinforced concrete (RC) buildings with little or no shear reinforcement in beam‐column joints can be found in regions of moderate seismicity. To strengthen such substandard beam‐column joints, this study proposes a method in which RC wing walls are installed beside existing columns, which overcomes the lack of realistic strengthening methods for congested connections in RC buildings. The proposed strengthening mechanism improves the joint moment capacity by utilizing tension and compression acting on the beam–wing wall boundaries; thus, brittle joint hinging failure is prevented. Three 3/4‐scale RC exterior beam‐column joint specimens without shear reinforcement, two of which were strengthened by installing wing walls with different strengthening elements, were fabricated and tested. The test results verified the effectiveness of the proposed strengthening method and the applicability of this method to seismically substandard beam‐column joints. © 2017 The Authors. Earthquake Engineering & Structural Dynamics Published by John Wiley & Sons Ltd.
How to Become a Start-up Capital

Small, young, flexible and informal start-ups represent an appropriate vehicle for new disruptive products and services. The impact of innovation for nations is extremely high; several countries aim to achieve it, but there is a lack of research to support it. Silicon Valley has a glorious reputation thanks to the high concentration of start-ups. Silicon Valley is the most famous, but it is not the only one. Several sources have emphasized the Northern European town Tallinn as one of the European start-up capitals. Many famous start-ups locate or have started their business in Tallinn. Quantitative research was performed among startups in Tallinn, and as a result typical profiles were constructed. The typical founder is a middleaged, well-educated, financially-secure, ambitious male with prior experience. Start-ups have an innovative product and good team, but should have more patents, investments and cooperation with universities. The expected environment has a good tax system, low corruption, SME support policy, high technological base and access to resources.