Miracle-dz/UniFAR-FTUs huggingface dataset:
Acute Effects on Physical Performance Measures after 45 Min of Official Competition in Youth Soccer Players

(1) Background: An improved understanding of soccer players’ match-related physical performance and recovery may help conditioning programs and re-warm up strategies to increase team performance during official competitions. Therefore, the aim of this study was to analyze the acute effects of 45 min of official competition (first half in matches) on physical performance variables in U-16 youth soccer players. (2) Methods: 20 male soccer players (age: 14.4 ± 0.5 years; height: 1.70 ± 0.05 cm; body mass: 65.1 ± 11.6 kg) were recruited to participate in this study. Data was collected from five official matches. Participants performed the assessments in two stages of each match: after the pre-match warm-up and after the first half. Tests included rate of perceived exertion (RPE), 30-m sprint and countermovement (CMJ). (3) Results: Statistically significant differences were found (p < 0.001) when the measurements prior to the game were compared with those recorded after half time across all variables. Effect sizes (ES) were very large for RPE (ES = 1.82), moderate for 30-m sprint times (ES = 0.64) and small for CMJ (ES = −0.25). (4) Conclusions: After 45 min of official competition, our results suggest that U-16 soccer players demonstrated a reduction in sprint and jump performance, in addition to a higher RPE. Hence, this information could be useful when designing re-warming strategies that can be performed before the second half.
Cloning And Analysis Of The Nile Tilapia Toll-Like Receptor Type 5 Mrna Sequence

Toll-like receptors (TLRs), which detect infections in vertebrates, are the most thoroughly understood innate immune receptors. However, bony fish’s TLRs shows distinct features and substantial diversity, which are likely originated from the variation in evolutionary history of fish and the distinct environments that they life in. there are a limited data about the structure of the fish immune system. Our work aimed to identify and clone and sequence the Nile tilapia TLR5 for the first time as a model for freshwater fish species. The full-length sequence of Nile tilapia (Oreochromis niloticus) TLR-5 receptor has been identified, where it consisted of 2661 nucleotides. The consensus cDNA sequence showed 81% identity with the sequence from Takifugu rubripes, 77% identity with the sequence form Japanese flounder, and 75% identity with the sequence from Japanese medaka, which confirmed that the new sequence is considered probably homologous to fish TLR-5. The predicted protein structure encoded by the Nile tilapia TLR-5 mRNA composed of 887 amino acids, beginning with signal peptide as ATG, like other functional fish TLR-5 sequences. Analysis of the deduced amino acid sequence indicated that Nile tilapia TLR-5 has typical structural features and contains the main components of proteins in the TLR family. Our results reveal a complete and functional Nile tilapia TLR-5 that is orthologous to other vertebrate receptors.
Scandinavian Forest Economics No. 44, 2012 Proceedings of the Biennial Meeting of the Scandinavian Society of Forest Economics Hyytiälä, Finland, May 2012

The purpose of this study is to explore how companies in the Finnish, Swedish and Norwegian wood products value-chains currently employ environmental performance measures (EPMs) in their communication and to study the existence of strategic element in the use of EPMs. The primary data for this study was collected by conducting 41 thematic interviews in 2011 in the three countries and was analyzed using theory-driven thematization. According to our results the most important EPMs in this context are forest certificates and the key stakeholders targeted are customers, suppliers and environmental authorities.
BIOLOGICAL INDICATORS OF ORAL LACTOBACILLI IN WOMEN OF FERTILE AGE: NORMAL AND CAVITIES

Scientists have been researching for a long time, where they have found evidence of a connection between “Lactobacillus Caries”. According to the results of some countries, the qualitative and quantitative composition of lactoflora of the oral cavity is already known in the norm and case of diseases caused by disbiotic conditions of the mouth. This article presents the results of the quantitative and qualitative composition of oral lactoflora of women of fertile age, the state of biological properties of each particular representative and their impact on cavities formation, which can explain the microbiological etiology of cavities. Each of the following indicators was statistically processed and compared with the results of foreign countries.
Distributed Utility Maximization From the Edge in IP Networks

To improve bandwidth sharing in IP networks, load balancing and rate control are key traffic engineering ingredients. In this context, we propose a fully distributed load balancing and rate allocation mechanism that operates only from the edge. Each access router is able to determine target rates over multiple paths for different traffic aggregates based on already available link state information and, some small and optional, information received from other edge devices. Our distributed utility maximization solution provides a feasible rate allocation at each iteration with diminishing returns. Through numerical results on a variety of instances, we show that it converges to near optimal solutions after a few iterations. Thanks to packet-level simulations on an SD-WAN scenario, we also show that it can well prioritize traffic over centralized and legacy solutions.
HETEROGENEOUS GRAPH-BASED USER-SPECIFIC REVIEW HETEROGENEOUS GRAPH-BASED USER-SPECIFIC REVIEW HELPFULNESS PREDICTION HELPFULNESS PREDICTION

With the popularity of e-commerce and review websites, it is becoming increasingly important to identify the helpfulness of reviews. However, existing works on predicting reviews’ helpfulness have three major issues: (i) the correlation between helpfulness and features from review text is not clear yet, although many standard features are proposed, (ii) the relations between users, reviews and products have not been considered, (iii) the eﬀectiveness of the existing approaches have not been systematically compared. To address these challenges, we ﬁrst analyze the correlation between standard features and review helpfulness that are widely used in other work. Based on this analysis, we propose an end-to-end neural network architecture, the Global-Local Heterogeneous Graph Neural Networks (GL-HGNN). It consists of the graph construction and learning nodes representations both globally and locally. The graph is composed of three types of nodes including users, reviews and products, as well as four link types to build connections among these nodes. To better learn the feature representations, we employ a global graph neural network (GNN) branch and a local GNN branch on the whole graph and associated subgraphs to capture graph structure and information propagation. Finally, we provide an empirical comparison with traditional machine learning models training on hand-crafted features as well as four state-of-the-art deep learning models on eight Amazon product categories.
Cloud Database Tuning with Reinforcement Learning

In database management systems (DBMSs), especially cloud DBMSs, conﬁgura-tion tuning is one of the key factors that inﬂuence database performance. For a long period of time, the tuning job of databases is done by experienced database administrators (DBAs), which is time-consuming and sub-optimal. Recently, with the development of machine learning, automatic tuning tool starts to play a signiﬁcant role in DBMSs. Among all the learning-based methods, reinforcement learning has the greatest potentiality to ﬁnd the optimal or near-optimal conﬁguration. There are already some reinforcement learning applications in database tuning, nonetheless, none of them provide fully executable code. In this project, we implement an independent version of auto-tuner to re-produce the current works on MySQL. Based on a careful design of the system, our code can be easily applied to other databases like JDB, LevelDB, etc. We believe it will beneﬁt a lot to those database administrators who know a lot about databases but lack the knowledge of reinforcement learning. The code is available at https://github.com/ChaokunChang/GDBTuner . The 5 minutes video can be found at Google Drive 1 .
Parameterizing the Outflow from a Central Black Hole in Dwarf Spheroidal Galaxies: A 3D Hydrodynamic Simulation

Large galaxies harbor massive central black holes and their feedback exerts a substantial impact on their evolution. Recently, observations have suggested that dwarf galaxies might host black holes in their centers, but with lower masses (intermediate-mass black holes—IMBHs). The impact of IMBHs on the evolution of dwarf spheroidal galaxies (dSphs), however, has so far not been properly analyzed. In this work, we investigate the effects of an outflow from an IMBH on gas dynamics in dSphs by means of noncosmological, three-dimensional hydrodynamic simulations, letting the galactic gas distribution evolve over 3 Gyr under the influence of the IMBH’s outflow and supernova feedback. All simulations have a numerical resolution of 20.0 pc cell−1. Two scenarios are considered to infer differences in the propagation of the outflow, one with a homogeneous interstellar medium (ISM) and another one with inhomogeneities caused by supernova feedback. A minimal initial speed and a minimal initial density are required for the outflow to propagate, with the values depending on the conditions of the medium. In an unperturbed medium, the outflow propagates freely in both directions with the same velocity (lower than the initial one), removing a small fraction of gas from the galaxy (the exact fraction depends on the initial physical conditions of the outflow). However, in an inhomogeneous ISM, the impact of the outflow is substantially reduced, and its contribution to the removal of gas from the galaxy is almost negligible.
Signal transducer and activator of transcription 1 gene polymorphism in Indonesian river buffalo

One of the genetic superiority of river buffalo can be seen from the genes controlling milk production. One of the well known genes that can control milk production in river buffalo is Signal Transducer and Activator of Transcription 1 (STAT 1). This study was conducted to identify the STAT 1 gene polymorphisms in river buffaloes in Indonesia. A total of 36 head of water buffalo including bulls (12) and calves (24) were collected Lembang Artificial Insemination Center, North Sumatra Artificial Insemination Center, BPTU-HPT Siborongborong, Deli Serdang District, and Medan District. Hair samples from each individual were collected for obtaining DNA samples. The amplification was carried out to obtain STAT1 partial sequence covering intron 9 to intron 11. This study found the G23549C and the T24011C loci polymorphism in Indonesian river buffalo for the first time. Both loci were polymorphic in both bulls and calves population. The polymoprhism information found in this study suggests that the STAT1 gene has the potential to be used as a genetic marker for buffalo milk production. Further studies are needed to prove this hypothesis.
Investigations into growth of whistlers with energy of energetic electrons

Runaway electrons have great significance in fusion plasmas as they are considered to be responsible for the excitation of instabilities and for damage to the first wall components. The threshold for the generation of the runaway electron population in tokamaks strongly depends on the toroidal magnetic field and bulk electron temperature. The presence of these runaway electrons with a critical density and magnetic field value are correlated with the magnetosonic whistler activity. The Rosenbluth condition applies to the destabilization of upper hybrid modes, that remains mostly stable in large-scale tokamaks like Joint European Tokamakand International Thermonuclear Experimental reactor. On the other hand, whistlers with a frequency in the lower hybrid range are more likely to be destabilized in a lower magnetic field and temperature, along with the whistlers’ excitation threshold. The process of destabilization of whistlers by energetic electrons thus has a finite overlap between fusion and basic plasma devices, and the outcome from the latter can be scalable to fusion machines. We report that in the linear large volume plasma device, the destabilization of quasi-longitudinal whistlers, driven by the reflected particles from the mirror, takes place in the bulk plasma region i.e. away from the mirror in the energetic belt region, and follows the frequency ordering of 40kHz<ωr/2π<80kHz . Our explanation involves an alternate limit of quasi-linear analysis, commonly employed for recovering the instability threshold of runaways scattering off whistlers in fusion plasmas, and the growth rate due to the reflected particle is proportional to the inverse square root of electron temperature, where the reflected particle fraction is \frac{{K{n_0}}}{{4{B_0}T_{\text{e}}^{0.5}}}$? > nrn0>Kn04B0Te0.5 (Sharma and Vlahos 1984 Astrophys. J. 280 405). The measurements required to obtain the energy scaling of runaway electrons with whistler instability are critical for large devices but remain scarce. We have emphasized the analytic correlation between the two regimes in these investigations.
Risk management of chilli supply chains using weighted failure mode effect analysis

Chilli supply chain is very vulnerable to risk due to scattered production centre, large number of actors along supply chain. Hence, risk management of chilli supply chain is very crucial to be executed in order to reduce the losses received by farmers and traders. The study aims to (i) identify and assess supply chain risks, and (2) arrange efforts to manage risks in the chilli supply chain. Weighted Failure Mode Effect Analysis (WFMEA) enriched by Analytical Hierarchy Process (AHP) was implemented to evaluate high-risk priorities and to manage those risks. The results showed that risk in marketing chain got the highest priority to be controlled since the greatest potential failure occurred in this channel with the weighted Risk Priority Number about 647.3. Risk indicators in this channel were cashless payment, major harvesting, and price fluctuations. Strategies to manage those risks were the provision of storage warehouses, planting time arrangements, bailout funds for cash purchase, harvest and post-harvest technology and farm capital loan. Government supports was required for providing the small-scale storage, home scale ozonation technology to extent the chilli shelf life and improve the product quality as well as policies on accessible farmer’s credit with farming guarantee system.
DNA isolation and amplification of Dryobalanops oblongifolia DREY and Dryobalanops lanceolata BURCK

Dryobalanops belong to a member of Dipterocarpaceae, which has a high economic value. Due to illegal harvesting for its wood, the population tends to decrease every year, so rapid conservation effort was needed. D. oblongifolia and D. lanceolata were important members of dryobalanops, which have listed as endangered (EN), according to IUCN. This study aims to provide information on the DNA isolation and amplification process. This data was needed as basic information for further research, such as genetic diversity, population genetics, phylogeny studies, or biogeography aspects. DNA isolation was performed using the CTAB method (Cetyl Trimethyl Ammonium Bromide). The amplification process was performed with three barcode markers those were trnL-trnF, rbcL, and matK. The results of DNA isolation showed quite good DNA yield. Amplified DNA using all primers showed successfully with an annealing temperature of 490C for matK, 500C for trnL-trnF, and 550 C for rbcL.
Compact and Wide Bandwidth Microstrip Patch Antenna for 5G Millimeter Wave Technology: Design and Analysis

In this paper, a compact microstrip patch antenna for 5G Millimeter wave technology has been proposed. By developing wide bandwidth characteristics, long ranges of data transfer are covered with better quality of signal transmission in 5G communication system. Modification of antenna element; patch width structured has influenced the frequency bandwidth. The design, analysis and optimization of the proposed work along with parametric analysis were performed using CST Microwave Studio. A microstrip patch antenna has been designed with high bandwidth millimeter wave, compact dimension, consistent radiation patterns and relatively higher gain at 28 GHz (mm-wave) band. FR-4 substrate has been employed in this work with a dielectric constant value of 4.3, thickness value of 1.6 mm and loss tangent value of 0.025. The proposed antenna has achieved high bandwidth which is 14.674 GHz with a reflection coefficient of -40.14 dB, Voltage Standing Wave Ratio (VSWR) value of 1.1098 dB and maximum gain of 5.29 dB with high directivity of 7.465 dBi. The antenna results of this work proved to be useful in fulfilling the requirements of wider bandwidth and higher gain particularly at 28 GHz for 5G applications.
Marketing efficiency of red chilli pepper in North Sumatera Province

This study aims to analyse the marketing of red chili pepper using price efficiency analysis. The data used is secondary data, namely time series data of monthly red chili pepper prices at the level of farmers, intermediate traders, wholesalers, retailers and consumers during 2015 to 2019. Data processing was carried out using quantitative descriptive analysis. Based on the results of the price efficiency analysis conclude that in the short and long term the red chili pepper market at the farm level is strongly intermediate traders, wholesalers, retailers and consumers. This can be seen from the IMC value which is smaller than 1 and the coefficient b2 which is greater than 0.05. This integration shows the marketing of red chilies in North Sumatra is efficient when viewed from price efficiency.
Seedling-stage screening method for tolerance of upland rice genotypes to low pH stress

One of the causes of generally low upland rice productivity in Indonesia is low fertility and soil pH. The use of genotypes with high yielding capacity and tolerant of acid soils can increase rice productivity. This study aimed to develop an early and efficient selection method, to determine rice genotypes tolerant to low pH. This research was conducted using a seed germination technique on rice paper medium with varied acidity level (pH 6.5, 5.5 and 4.5). Research data on the germination test showed that germination variables: growth uniformity, relative growth rate, vigour index, T50, and root length can be used as early indicators for determining rice genotypes tolerant to low pH. Research data showed that genotype Pae Huko is relatively more tolerant to low pH than the other three tested genotypes. Pae Huko had the highest values for relative growth rate, growth uniformity, vigour index, and T50 of 92.12%, 87%, 73.3, and 1.6 days, respectively. It had also the highest root length of 14.27 cm. The results give an indication that the method can be used as an early screening for determining tolerant rice genotypes to low pH. Further test (glasshouse experiment) is required to confirm the current results.
Characterizing the Effects of Calcium and Prebiotic Fiber on Human Gut Microbiota Composition and Function Using a Randomized Crossover Design—A Feasibility Study

Consumption of prebiotic inulin has been found to increase calcium absorption, which may protect against gut diseases such as colorectal cancer. This dietary relation may be modulated by compositional changes in the gut microbiota; however, no human study has addressed this hypothesis. We determined the feasibility of a randomized crossover trial to evaluate the effect of three interventions (combined calcium and inulin supplementation, calcium supplementation alone, and inulin supplementation alone) on the intestinal microbiota composition and function. We conducted a 16-week pilot study in 12 healthy adults who consumed the three interventions in a random sequence. Participants provided fecal and blood samples before and after each intervention. Each intervention period lasted four weeks and was flanked by one-week washout periods. 16S ribosomal RNA sequencing and quantification of short chain fatty acids (SCFA) was determined in fecal samples. Systemic lipopolysaccharide binding protein (LBP) was quantified in serum. Of the 12 individuals assigned to an intervention sequence, seven completed the study. Reasons for dropout included time (n = 3), gastrointestinal discomfort (n = 1), and moving (n = 1). Overall, participants reported positive attitudes towards the protocol (n = 9) but were unsatisfied by the practicalities of supplement consumption (44%) and experienced digestive discomfort (56%). We found no appreciable differences in microbial composition, SCFA concentration, nor LBP concentrations when comparing intervention periods. In conclusion, an intervention study using a randomized crossover design with calcium and a prebiotic fiber is feasible. Improvements of our study design include using a lower dose prebiotic fiber supplement and a larger sample size.
Using Markov Decision Processes for Medical Resource Allocation Decisions

This paper discusses an optimized approach to decision making in regards to resource allocation within health care systems and the medical industry. Decision making in medical resource management is often sequential and uncertain in nature. Markov Decision Processes (MDPs) are used to model decision-making in sequential environments and can be used as a technique for solving decision problems. MDPs allow a decision holder, to make the best possible decisions in the environment they inhabit, which changed state in response to choices of action made by the agent. We will be describing our MDP model and illustrating the performance of our design with data focusing on health care professionals as well as medical supplies. We will be analyzing our evaluations and offer a promising approach towards an optimal policy focusing on increased measures of health. We will also discuss the challenges in addressing complex resource allocation problems that arise in healthcare settings
Rice Plant Infection Recognition using Deep Neural Network Systems

In this work, identification of diseases present in the plant of rice is carried out using methods of Deep Neural Network. So as to achieve image accession, a dataset having 2212 leaf images with different diseases is used. In this work, the entire dataset is divided into two classes in which class 1 contains the healthy leaves and the other class contains infected leaves. The identification is done using VGG-19, LeNet5, and MobileNet-V2predefined Convolutional Neural Network (CNN) models that own a fixed number of Convolutional layers and also the layers that are connected completely also known as fully connected layers. The architecture is designed as per the details for the LeNet5 model while for the other two methods that is MobileNet-V2 and VGG-19, the architecture is directly imported from some predefined libraries which are ready to use, and further, they are used according to the author’s requirement. Once the experiment was completed successfully, it was observed that the accuracy achieved of VGG-19, LeNet5, and MobileNet-V2 was 77.09 %, 76.63 %, and 76.92 %respectively.