Miracle-dz/UniFAR-FTUs huggingface dataset:
Promoting Third Graders’ Executive Functions and Literacy: A Pilot Study Examining the Benefits of Mindfulness vs. Relaxation Training

Research suggested that developing mindfulness skills in children improves proximal outcomes, such as attention and executive functions, as well as distal outcomes, such as academic achievement. Despite empirical evidence supporting this claim, research on the benefits of mindfulness training in child populations is scarce, with some mixed findings in the field. Here, we aimed to fill in this gap, by examining the effects of a mindfulness training on third graders’ proximal and distal outcomes, namely, attention and executive functions (viz., inhibitory control, working memory, and cognitive flexibility) as well as literacy-related achievement (viz., handwriting fluency, text quality, Portuguese grades). These outcomes were measured with behavioral tasks and teacher ratings. Sixty-six Portuguese children were randomly allocated to an experimental group receiving mindfulness training (n = 29) or an active control group receiving relaxation training (n = 37). Both training programs were implemented by psychologists in two 30-min weekly sessions for 8 weeks. All students were assessed before and after the interventions. Three main findings are noteworthy: (a) mindfulness training enhanced teacher-rated cognitive flexibility and a performance-based composite score of executive functions among children with higher pretest scores; (b) relaxation training improved performance-based cognitive flexibility and the composite score of executive functions among children with lower pretest scores; (c) children receiving mindfulness training had higher handwriting fluency and better grades in Portuguese than those receiving relaxation training. These findings provide preliminary evidence on the benefits of mindfulness training in educational settings and highlight the moderating role of baseline performance on those benefits.
High-Frequency Monitoring Reveals Multiple Frequencies of Nitrogen and Carbon Mass Balance Dynamics in a Headwater Stream

The uptake of aquatic nutrients can represent a major pathway for their removal from river ecosystems and is a key control on nitrogen and carbon export from watersheds. Our understanding of temporal variability in nutrient mass balance is incomplete as conventional methods for estimating uptake rates are suited to low-frequency analysis. Here, we utilised hourly streamflow, nitrate (NO3--N) and dissolved organic carbon (DOC) to generate near-continuous estimates of nutrient uptake along a 1 km reach in a headwater catchment with a history of agricultural activity. We identified variability in nutrient mass balance at multiple frequencies. Over seasonal timescales, a shift from nitrate release during spring to uptake during autumn was apparent. In contrast, consistent uptake of DOC was observed across the whole monitoring period (i.e., spring—autumn). Both DOC and nitrate uptake were related significantly to environmental variables (river discharge) and antecedent discharge conditions. DOC:nitrate stoichiometry appeared to be a key control on nitrate uptake rates, yet this coupling weakened from summer to autumn as DOC became more abundant and physical controls become more important. Daily cycles in nutrient uptake were evident and at times the investigated reach acted as a net sink of DOC during the day and a source at night. Short-term impacts of storm events on uptake rates varied seasonally but no consistent changes were observed between pre- and post-event conditions, suggesting aquatic communities were resilient to short-term flow disturbances. For the duration of our study, the reach acted as net sink from the water for DOC (−1.7% of upstream flux) and a net source for nitrate (+2.6%). Even during autumn, when uptake was greatest, mass removal represented <3% of nitrate exported downstream. Our results facilitate new insights into multi-timescale patterns and drivers of stream ecosystem processes, which are essential for developing effective catchment-scale management strategies.
Post-exercise Recovery Methods Focus on Young Soccer Players: A Systematic Review

Background: Prescription of post-match or post-training recovery strategies in young soccer players is a key point to optimize soccer performance. Considering that the effectiveness of recovery strategies may present interindividual variability, scientific evidence-based recovery methods and protocols used in adults are possibly not applicable to young soccer players. Therefore, the current systematic review primarily aimed to present a critical appraisal and summary of the original research articles that have evaluated the effectiveness of recovery strategies in young male soccer players and to provide sufficient knowledge regarding the effectiveness of the recovery methods and strategies. Methodology: A structured search was carried out following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines until November 31, 2020, using the next data bases: WOS, PubMed, Cochrane Library, Evidence Database (PEDro), Evidence Based Medicine (EBM) Search review, EMBASE, and Scopus. There were no filters applied. Results: A total of 638 articles were obtained in the initial search. After the inclusion and exclusion criteria, the final sample was 10 articles focusing on recovery in young male players. Conclusions: Neuromuscular performance can be recovered using WVB but not with SS, and water immersion protocols may also be useful, but their positive effects are not significant, and it is unable to distinguish the best water immersion method; match running performance maintenance may be achieved using water immersion protocols but no other recovery methods have been investigated; EIMD and inflammatory responses could be positively affected when water immersion and AR are applied, although SS seems to be ineffective; perceptual responses also seem to be better with CWI and WVB, but contradictory results have been found when AR is applied, and SS had no positive impact. Finally, it is important to consider that AR strategies may modify HR response and soccer-specific performance.
Prophylactic Erythropoietin for Neuroprotection in Very Preterm Infants: A Meta-Analysis Update

A meta-analysis update of randomized controlled trials investigating recombinant human erythropoietin suggests improved neurodevelopmental outcome in preterm infants. There was substantial heterogeneity, which could be ascribed to a single trial. Exclusion of this trial featuring a high risk of bias abolished heterogeneity and any effects of recombinant human erythropoietin treatment.
TGFβ1 in Cancer-Associated Fibroblasts Is Associated With Progression and Radiosensitivity in Small-Cell Lung Cancer

Objective Small-cell lung cancer (SCLC) is aggressive, with early metastasis. Cytokines secreted by cancer-associated fibroblasts (CAFs) within various tumors influences these features, but the function in particular of TGFβ1 (transforming growth factor beta 1) is controversial and unknown in SCLC. This study explored the influence of TGFβ1 in CAFs on the development, immune microenvironment, and radiotherapy sensitivity of SCLC. Methods SCLC specimens were collected from 90 patients who had received no treatment before surgery. Tumor and tumor stroma were subjected to multiplex immunohistochemistry to quantitate TGFβ1 and other immune factors in CAFs. Cell proliferation and flow cytometry apoptosis assays were used to investigate associations between TGFβ1 and proliferation and radiotherapy sensitivity. The immune factors in tumors were detected by immunohistochemistry in vitro and in vivo (mice). Results TGFβ1 levels on CAFs lower or higher than the median were found, respectively, in 52.2 and 47.8% of patients; overall survival of patients with TGFβ1-high levels (53.9 mo) was significantly longer than that of the TGFβ1-low group (26.9 mo; P = 0.037). The univariate and multivariate analyses indicated that a TGFβ1-high level was an independent predictor of increased survival time. TGFβ1-high levels in CAFs were associated with inhibition of growth, proliferation, antitumor immunity, and enhanced radiotherapeutic sensitivity and tumor immunity of tumor. TGFβ1-low levels promoted tumor cell growth and radiotherapy sensitivity in vivo and in vitro. Conclusion High levels of TGFβ1 in CAFs were associated with longer overall survival in patients with SCLC and enhanced radiotherapy sensitivity.
Sponges With Microbial Symbionts Transform Dissolved Organic Matter and Take Up Organohalides

Seawater dissolved organic matter (DOM) is a large reservoir of carbon composed of a complex and poorly characterized mixture of molecules. Sponges have long been known to consume dissolved organic carbon (DOC) from this mixture, but the role of microbial sponge symbionts in this process is complex, and the molecules involved remain largely unknown. In order to better understand how sponge processing changes seawater DOM, we used untargeted metabolomics to characterize DOM in samples of incurrent and excurrent seawater taken from sponges on the fore-reef off Carrie Bow Cay, Belize, over 2 years. We collected samples from three sponge species each with either high or low microbial abundance (HMA, LMA) to explore the relationship between symbiont abundance and DOM alterations. Analyses revealed that sponges took up metabolites and changed the composition of seawater DOM, but only for the three HMA species, and none of the LMA species, implicating microbial symbionts in this uptake. Using a new mass spectra classification tool, we found that putative compositions of features depleted in the excurrent samples of HMA sponges were similar in both years and were dominated by organic acids and derivatives (74%) and organic nitrogen compounds (19%). Interestingly, HMA sponges also took up halogenated compounds (containing chlorine or bromine), providing evidence of a previously unknown mechanism of halide cycling. The metabolites taken up by HMA sponges may be used as a food source or as building blocks of chemical defenses, selective advantages that may have guided the evolution of microbial symbioses in sponges.
A Longitudinal Study of Mental Wellbeing in Students in Aotearoa New Zealand Who Transitioned Into PhD Study

Journal editorials, career features, and the popular press commonly talk of a graduate student mental health crisis. To date, studies on graduate student mental health have employed cross-sectional designs, limiting any causal conclusions regarding the relationship between entry into graduate study and mental health. Here, we draw on data from a longitudinal study of undergraduate students in Aotearoa New Zealand, allowing us to compare participants who did, and did not, transition into PhD study following the completion of their undergraduate degree. Using multilevel Bayesian regression, we identified a difference in mental wellbeing between those who entered PhD study and those who did not. This difference, however, was largely due to those not entering PhD study displaying an increase in mental wellbeing. Participants that entered PhD study displayed a small decrease in mental wellbeing, with the posterior distribution of the simple effect heavily overlapping zero. This latter finding was orders of magnitude smaller than one might expect based on previous cross-sectional research and provides an important message; that a marked drop in mental health is not an inevitable consequence of entering graduate study.
Enhancing Student Involvement Based on Adoption Mobile Learning Innovation as Interactive Multimedia

The low involvement of students in online learning resulted in a decrease in their academic performance. This research aims to figure out the effect of adopting online learning innovations such as mobile learning (m-learning) on students’ involvement with digital readiness as a mediator. A total of 89 graduate students from all over Indonesia enrolled at Universitas Negeri Yogyakarta participated in the study. To determine the sample, we used purposive sampling. Analysis techniques to test research models used partial least square structural equation model (PLS-SEM) with SmartPLS 3.3. 2 software. The results are significant for digital readiness as a mediator in student perception of the influence of the adoption of m-learning innovation on student engagement. Although students positively perceive that the adoption of m-learning has a positive effect, they must also have strong digital skills to complete their academic work. Besides, they must also be committed to fully engaged in learning activities using m-learning— this finding provides practical implications for improving effective and interactive online learning in college.
A Computational Complexity-Based Method for Predicting Scholars' Ages through Articles' Information

Many scholars have conducted in-depth research on the evaluation and prediction of scholars’ scientific impact and meanwhile discovered various factors that affect the success of scholars. Among all these relevant factors, scholars’ ages have been universally acknowledged as one of the most important factors for it can shed light on many practical issues, e.g., finding supervisors, discovering rising stars, and research funding or award applications. However, due to the inaccessibility or the privacy issues of acquiring scholars’ personal data, there is little research to explore the true ages of scholars currently. Alternatively, scholars’ publications’ information can be obtained through various digital libraries. Inspired by this fact, we propose a novel scholar’s age prediction method based on their articles’ information. Our method first classifies factors that affect scholars’ ages into intuitive and complex types according to their computational complexity and then apply machine learning algorithms to predict the ages of scholars based on these factors. The experimental results on the real dataset demonstrate that our method can effectively predict the true ages of scholars. Given that there is no completely accurate dataset because of the continuous publication of academic papers, we then apply our method on the incomplete dataset. Nevertheless, our method still has high prediction accuracy in such situations.
AQUACOLD: A Novel Crowdsourced Linked Data Question Answering System

Question Answering (QA) systems provide answers to Natural Language (NL) questions posed by humans. The Linked Data (LD) web provides an ideal knowledge base for QA as the framework expresses structure and relationships between data which assist in question parsing. Despite this, recent attempts at NL QA over LD struggle when faced with complex questions due to the challenges in automatically parsingNLintoastructuredquerylanguage, forcingenduserstolearnlanguagessuchasSPARQLwhich can be challenging for those without a technical background. There is a need for a system which returns accurate answers to complex natural language questions over linked data, improving the accessibility of linked data search by abstracting the complexity of SPARQL whilst retaining its expressivity. This work presents AQUACOLD (Aggregated Query Understanding And Construction Over Linked Data) a novel LD QA system which harnesses the power of crowdsourcing to meet this need. AQUACOLD uses query templates built by other users to answer questions which enables the system to handle queries of significant complexity. This paper provides an overview of the system and presents the results of a technical and user evaluation against the QALD-9 benchmark.
Topology Control and Medium Access Control (MAC) Protocol for Wireless Sensor Networks (WSNs) in Cyber-Physical System

The system reachability set is calculated by covering all possible behaviours of the system through a finite number of simulation steps to ensure that the system trajectory stays within a set safety region. In this paper, the theory of the game method is applied to the design of the controller, a very small controller is designed, and good control results are obtained by simulation. The system gradually shows a divergent trend and cannot achieve stable control. A multihop channel reservation Medium Access Control (MAC) protocol based on a parallel mechanism is proposed. The multihop channel reservation mechanism is proposed based on periodic node sleep, and the node uses the reservation frame to make the reservation of the channel and transmits the data according to the reservation information; the parallel mechanism is used to make the reservation information and data transmission simultaneously.
Corrosion behaviour of plasma electrolytic oxidation coated AZ91 Mg alloy: influence of laser surface melting pretreatment

Plasma electrolytic oxidation (PEO) was performed on a laser surface melting (LSM) modified AZ91 Mg alloy. The effect of LSM pre-treatment on the long-term corrosion resistance of the PEO coated AZ91 alloy was evaluated. Results showed that the LSM pretreatment had a negligible effect on the phase composition and microstructure of the PEO coatings. However, after LSM pretreatment, the long-term corrosion resistance of the PEO coated AZ91 alloy revealed a large enhancement. This was mainly ascribed to the improved corrosion resistance of the substrate resulting from the change of microstructure characteristics induced by the LSM treatment. This provided an alternative approach to improve the long-term corrosion resistance of the PEO coated Mg alloy by appropriate surface modified pretreatment of substrates.
Adaptive Integral-Based Robust Q-S Synchronization and Parameter Identification of Nonlinear Hyperchaotic Complex Systems

This communique presents the Q-S synchronization of two nonidentical complex nonlinear hyperchaotic systems with unknown parameters. An adaptive controller based on adaptive integral sliding mode control and parameter update laws are designed to realize the synchronization and parameter identification to a given map vector. The aforementioned strategy’s employment demands the transformation of a system into a specific structure containing a nominal part and some unknown terms (later on, these unknown terms will be computed adaptively). An integral sliding mode controller is used to stabilize the error system by designing nominal control accompanied by compensator control. For chattering suppression, a continuous compensator of smooth nature is used instead of conventional control. The stability of the proposed algorithm is established in an impressive way, using Lyapunov criteria. A numerical simulation is performed to illustrate the validity of the proposed synchronization scheme.
A CNN-Based Mosquito Classification Using Image Transformation of Wingbeat Features

In this paper, a classification of mosquito’s specie is performed using mosquito wingbeats samples obtained by optical sensor. Six world-wide representative species of mosquitos, which are Aedes aegypti, Aedes albopictus, Anopheles arabiensis, Anopheles gambiae and Culex pipiens, Culex quinquefasciatus, are considered for classification. A total of 60,000 samples are divided equally in each specie mentioned above. In total, 25 audio feature extraction algorithms are applied to extract 39 feature values per sample. Further, each audio feature is transformed to a color image, which shows audio features presenting by different pixel values. We used a fully connected neural networks for audio features and a convolutional neural network (CNN) for image dataset generated from audio features. The CNN-based classifier shows 90.75% accuracy, which outperforms the accuracy of 87.18% obtained by the first classifier using directly audio features.
Designing Cuckoo Based Pending Interest Table for CCN Networks

Content Centric Networking (CCN) is a modern architecture that got wide attention in the current researches as a substitutional for the current IP-based architecture. Many studies have been investigated on this novel architecture but only little of them focused on Pending Interest Table (PIT) which is very important component in every CCN router. PIT has fundamental role in packet processing in both upstream process (Interest packets) and downstream process (Data packets). PIT must be fast enough in order to not become an obstruction in the packet processing and also it must be big enough to save a lot of incoming information. In this paper, we suggest a new PIT design and implementation named CF-PIT for CCN router. Our PIT design depends on modifying and utilizing an approximate data structure called Cuckoo filter (CF). Cuckoo filter has ideal characteristics like: high insertion/query/deletion performance, acceptable storage demands and false positive probability which make it with our modification convenient for PIT implementation. The experimental results showed that our CF-PIT design has high performance in different side of views which make it very suitable to be implemented on CCN routers.
MICROFLUIDICS FOR GENETIC CANCER DIAGNOSTICS Microfluidiques pour la détection génétique de cancers

Les microsystèmes d’analyse intégrés, ou μTAS (Micro Total Analysis Systèmes), permettent d’améliorer considérablement la détection de cancers dès les premiers stades d’apparition. En effet, ils interviennent au niveau moléculaire au lieu d’attendre que la maladie ne se manifeste sous forme de tumeurs détectables. Ils offrent également un bien meilleur rendement que les techniques courantes de laboratoire. Ce papier présente le développement d’un microsystème fluidique d’analyse intégré pour la détection et la surveillance génétique de cancer. Des micro-réacteurs fluidiques, placés dans des écoulements liquides d’un macro-dispositif, représentent l’aspect novateur du système développé. Le haut rendement est obtenu par la combinaison de micro-réacteurs évoluant périodiquement en parallèle. Cette approche permet de relever le challenge technologique qu’induit la rencontre des mondes macroscopiques et microscopiques. Parce que les réacteurs sont immergés dans un milieu liquide, la contamination du dispositif et le risque associé à de faux résultats sont minimisés. Ce papier présente une vue d’ensemble sur la génération de micro-gouttes présentées comme les micro-réacteurs, le mélange à micro-échelle de ceux-ci, l’amplification d’ADN par un système fluidique basé sur la PCR et la détection utilisant des techniques optiques.
Synthesis of Some New 1,2,3,4‐Tetrahydropyrimidine‐2‐thione and Their Thiazolo[3,2‐a]pyrimidine, Thiazino and Benzothiazepine Derivatives

The starting N-(2-pyridyl)-6-methyl-4-phenyl-2-thioxo-1,2,3,4-tetrahydropyrimidine-5-carboxamide () was used as a key intermediate for the synthesis of new 1,2,3,4-tetrahydropyrimidine-2-thione and their thiazolo[3,2-a]pyrimidine, thiazino and benzothiazipen derivatives. The reaction of with haloketones in ethanol catalyzed by base afforded the corresponding thiophenopyrimidine and pyrimidothiazipine derivatives . Methylation and formylation of led to the pyrimidine derivatives and , respectively. The preventative compounds were established on the basis of elemental and spectral data.
Water Dissociative Adsorption on NiO(111): Energetics and Structure of the Hydroxylated Surface

The energetics of the reactions of water with metal oxide surfaces are of tremendous interest for catalysis, electrocatalysis, and geochemistry, yet the energy for the dissociative adsorption of water was only previously measured on one well-defined oxide surface, iron oxide. In the present paper, the enthalpy of the dissociative adsorption of water is measured on NiO(111)-2 × 2 at 300 K using single-crystal adsorption calorimetry. The differential heat of dissociative adsorption decreases with coverage from 170 to 117 kJ/mol in the first 0.25 ML of coverage. Water adsorbs molecularly on top of that, with a heat of ∼92 kJ/mol. Density functional theory (DFT) calculations reproduce the measured energies well (all within 17 kJ/mol) and provide insight into the atomic-level structure of the surfaces studied experimentally. They show that the oxygen-terminated O-octo(2 × 2) structure is the most stable NiO(111)-2 × 2 termination and gives reaction energies with water that are more consistent with the calorime.