bluuebunny/crossref_metadata_2025 huggingface dataset:
Synergistic Bond Properties of Different Deformed Steel Fibers Embedded in Mortars Wet-Sieved from Self-Compacting SFRC
Authors: Ding Xinxin , Geng Haibin , Zhao Minglei , Chen Zhen , Li Jie
Published: November 2021

Reliable bond of steel fiber in concrete is a key problem relating to the reinforcing effect of steel fiber on concrete matrix and for the guide in significance for the optimal design of the geometry and mechanical properties of steel fiber. In this paper, on the basis of multi-indices of evaluation for the bond properties of single hooked-end steel fiber, the indices for the evaluation of synergistic bond properties of different deformed steel fibers are proposed. The pull-out tests were carried out for different deformed steel fibers embedded in mortar wet-sieved from self-compacting SFRC with manufactured sand. Fourteen types of steel fibers were used, including six hooked-end, two crimped, four indentation, one milling, and one large-end. The bond strength, bond energy, and bond toughness of single and per unit weight steel fiber were evaluated with the correspondence to the loading status of cracking resistance, normal serviceability, and ultimate bearing capacity of concrete. Results show that the deformed steel fibers presented different bond behaviors, hooked-end, and crimped steel fibers with circular cross-sections and a tensile strength of higher than 1150 MPa have excellent effects of strengthening, energy dissipation, and toughening capacity on self-compacting concrete with a cubic compressive strength of 60 MPa at normal serviceability and ultimate bearing capacity. Indentation, milling, and large-end steel fibers are more suitable for reinforcing the concrete strength due to the rigid bond before concrete cracking. The synergistic working of steel fibers with concrete matrix should be concerned to realize the effects of only or simultaneously reinforcing the strength and toughness of concrete.
Assignments as Influential Factor to Improve the Prediction of Student Performance in Online Courses
Authors: Esteban Aurora , Romero Cristóbal , Zafra Amelia
Published: November 2021

Studies on the prediction of student success in distance learning have explored mainly demographics factors and student interactions with the virtual learning environments. However, it is remarkable that a very limited number of studies use information about the assignments submitted by students as influential factor to predict their academic achievement. This paper aims to explore the real importance of assignment information for solving students’ performance prediction in distance learning and evaluate the beneficial effect of including this information. We investigate and compare this factor and its potential from two information representation approaches: the traditional representation based on single instances and a more flexible representation based on Multiple Instance Learning (MIL), focus on handle weakly labeled data. A comparative study is carried out using the Open University Learning Analytics dataset, one of the most important public datasets in education provided by one of the greatest online universities of United Kingdom. The study includes a wide set of different types of machine learning algorithms addressed from the two data representation commented, showing that algorithms using only information about assignments with a representation based on MIL can outperform more than 20% the accuracy with respect to a representation based on single instance learning. Thus, it is concluded that applying an appropriate representation that eliminates the sparseness of data allows to show the relevance of a factor, such as the assignments submitted, not widely used to date to predict students’ academic performance. Moreover, a comparison with previous works on the same dataset and problem shows that predictive models based on MIL using only assignments information obtain competitive results compared to previous studies that include other factors to predict students performance.
Laser–Accelerated Plasma–Propulsion System
Authors: Palla Daniele , Cristoforetti Gabriele
Published: November 2021

In this paper, the laser-accelerated plasma–propulsion system (LAPPS) for a spacecraft is revisited. Starting from the general properties of relativistic propellants, the relations between specific impulse, engine thrust and rocket dynamics have been obtained. The specific impulse is defined in terms of the relativistic velocity of the propellant using the Walter’s parameterization, which is a suitable and general formalism for closed–cycle engines. Finally, the laser-driven acceleration of light ions via Target Normal Sheath Acceleration (TNSA) is discussed as a thruster. We find that LAPPS is capable of an impressive specific impulse Isp in the 105 s range for a laser intensity I0≃1021W/cm2. The limit of Isp≲104 s, which characterizes most of the other plasma-based space electric propulsion systems, can be obtained with a relatively low laser intensity of I0≳1019W/cm2. Finally, at fixed laser energy, the engine thrust can be larger by a factor 102 with respect to previous estimates, making the LAPPS potentially capable of thrust-power ratios in the N/MW range.
Understanding Customers’ Transport Services with Topic Clustering and Sentiment Analysis
Authors: Moreno Alejandro , Iglesias Carlos A.
Published: November 2021

The recent increase in user interaction with social media has completely changed the way customers communicate their opinions, questions, and concerns to brands. For this reason, many companies have established on the top of their agendas the necessity of analyzing the high amounts of user-generated content data in social networks. These analyses are helping brands to understand their customers’ experiences as well as for maintaining a competitive advantage in the sector. Due to this fact, this study aims to analyze and characterize the public opinions from the messages posted by Twitter users while addressing customer services. For this purpose, this study carried out a content analysis of a customer service platform. We extracted the general users’ viewpoints and sentiments of each of the discussed topics by using a wide range of techniques, such as topic modeling, document clustering, and opinion mining algorithms. For training these systems and drawing conclusions, a dataset containing tweets from the English-speaking customers addressing the @Uber_Support platform during the year 2020 has been used.
Design Method Using Response Surface Model for CFRP Corrugated Structure under Quasistatic Crushing
Authors: Gomi Tetsuya , Ayuzawa Shotaro , Urushiyama Yuta , Misaji Kazuhito , Takahashi Susumu , Motoyama Keiichi , Suzuki Kosuke
Published: November 2021

The development of a carbon-fiber-reinforced plastic (CFRP) part is carried out by utilizing many experimental results in deciding the design. For this reason, the development period of a CFRP structure is long and an obstacle for commercialization. In this paper, multiple regression analysis is used to derive a response surface that estimates the generated load using the shape parameters of a corrugated collision energy absorbing structure to shorten the development period. To obtain the response surface, we conducted a quasistatic crushing experiment by using the length of linear portions (pitch) and the number of stacks (thickness) of a corrugated shape as parameters. When progressive crushing mode is observed, energy absorption efficiency decreases with the increase in pitch, and increases with the increase in the number of stacks. To discuss how energy absorption efficiency changes, a comparison examination is conducted using the derived response surfaces. Results indicate that specifications with high energy absorption efficiency can be accurately selected using the response surface of primary expression. In addition, differences in deformation mode were due to the influence of the stress at the corner portion of a part.
Determination of Thermodynamic Parameters of Polylactic Acid by Thermogravimetry under Pyrolysis Conditions
Authors: Palmay Paul , Mora Melissa , Barzallo Diego , Bruno Joan Carles
Published: November 2021

In the present study, the thermodynamic parameters of Polylactic Acid (PLA) under conditions of thermal degradation were determined. The PLA material, previously sampled and characterized, was analyzed by dynamic thermogravimetry (TG) at heating rates of 5, 10 and 15 °C min−1 with a nitrogen flow of 20 mL min−1 from a temperature of 25 to 900 °C. The data were treated using isoconversional kinetic models to obtain the activation energy and the pre-exponential factor of each model. To fit the DTG curves, the Arrhenius equation was used applying the Contraction Sphere reaction model: two-dimensional phase limit reaction (R2). The thermodynamic parameters such as enthalpy, Gibbs free energy and entropy were determined from the kinetic parameters of suitable models for each heating rate after statistical validation and comparison with other studies. The results showed that as the heating rate increases, the degradation temperature also increases, while the activation energy, enthalpy and pre-exponential factor decrease. According to the value of ∆G (171.65 kJ mol−1), PLA has a significant potential to be used as a raw material to produce bioenergy/biofuels by pyrolysis.
Tyrosol, at the Concentration Found in Maltese Extra Virgin Olive Oil, Induces HL-60 Differentiation towards the Monocyte lineage
Authors: Gatt Lucienne , Saliba David G. , Schembri-Wismayer Pierre , Zammit-Mangion Marion
Published: November 2021

Tyrosol is a phenolic found in extra virgin olive oil (EVOO). In a Maltese monocultivar EVOO, it was present at a concentration of 9.23 ppm. The HL-60 acute myeloid leukaemia cell line, which can be differentiated to both monocytes and neutrophils, was exposed to tyrosol at this concentration and analysed for evidence of differentiation and effects of cytotoxicity. The polyphenol induced a 1.93-fold increase in cellular oxidative activity (p-value 0.044) and enhanced surface expression of CD11b and CD14. This indicates that tyrosol induces monocytic-like differentiation. An RNA-seq analysis confirmed the upregulation of monocyte genes and the loss of neutrophil genes concomitant with the bi-potential promyelocyte precursor moving down the monocytic pathway. A cell cycle analysis showed an accumulation of cells in the Sub G0/G1 phase following tyrosol exposure for 5 days, which coincided with an increase in apoptotic and necrotic markers. This indicates differentiation followed by cell death, unlike the positive monocyte differentiation control PMA. This selective cytotoxic effect following differentiation indicates therapeutic potential against leukaemia.
A Feature-Independent Hyper-Heuristic Approach for Solving the Knapsack Problem
Authors: Sánchez-Díaz Xavier , Ortiz-Bayliss José Carlos , Amaya Ivan , Cruz-Duarte Jorge M. , Conant-Pablos Santiago Enrique , Terashima-Marín Hugo
Published: November 2021

Recent years have witnessed a growing interest in automatic learning mechanisms and applications. The concept of hyper-heuristics, algorithms that either select among existing algorithms or generate new ones, holds high relevance in this matter. Current research suggests that, under certain circumstances, hyper-heuristics outperform single heuristics when evaluated in isolation. When hyper-heuristics are selected among existing algorithms, they map problem states into suitable solvers. Unfortunately, identifying the features that accurately describe the problem state—and thus allow for a proper mapping—requires plenty of domain-specific knowledge, which is not always available. This work proposes a simple yet effective hyper-heuristic model that does not rely on problem features to produce such a mapping. The model defines a fixed sequence of heuristics that improves the solving process of knapsack problems. This research comprises an analysis of feature-independent hyper-heuristic performance under different learning conditions and different problem sets.
Experimental Study on the Behavior of Polyurethane Springs for Compression Members
Authors: Ju Young Hun , Hu Jong Wan
Published: November 2021

In this study, the characteristics of the compression behavior of polyurethane springs that can be used as compression members of seismic devices, such as dampers and seismic isolators, were identified, and the effect of the design variables on the performance points of polyurethane springs was investigated. Compressive stiffness and specimen size were set as the design variables of the polyurethane spring, and the performance indicators were set as maximum force, residual strain, and energy dissipation. A total of 40 specimens with different conditions were fabricated and a cyclic loading test was performed to obtain the force-displacement curve of the polyurethane spring and to check the performance indicator. Significant strength degradation was confirmed after the first cycle by repeated loading, and it was confirmed that compressive stiffness and size demonstrated a linear proportional relationship with maximum force. In addition, the design variables did not make a significant change to the recovered strain, including residual strain, and residual strain of about 1% to 3% occurred. Energy dissipation showed a tendency to decrease by about 60% with strength degradation after the first cycle, and this also demonstrated no relationship with the design variables. Finally, the relationship between the design variables and performance indicators set in this study was reviewed and suggestions are presented for developing a simple design formula for polyurethane springs.
Decentralized Multi-Agent Control of a Manipulator in Continuous Task Learning
Authors: Shahid Asad Ali , Sesin Jorge Said Vidal , Pecioski Damjan , Braghin Francesco , Piga Dario , Roveda Loris
Published: November 2021

Many real-world tasks require multiple agents to work together. When talking about multiple agents in robotics, it is usually referenced to multiple manipulators in collaboration to solve a given task, where each one is controlled by a single agent. However, due to the increasing development of modular and re-configurable robots, it is also important to investigate the possibility of implementing multi-agent controllers that learn how to manage the manipulator’s degrees of freedom (DoF) in separated clusters for the execution of a given application (e.g., being able to face faults or, partially, new kinematics configurations). Within this context, this paper focuses on the decentralization of the robot control action learning and (re)execution considering a generic multi-DoF manipulator. Indeed, the proposed framework employs a multi-agent paradigm and investigates how such a framework impacts the control action learning process. Multiple variations of the multi-agent framework have been proposed and tested in this research, comparing the achieved performance w.r.t. a centralized (i.e., single-agent) control action learning framework, previously proposed by some of the authors. As a case study, a manipulation task (i.e., grasping and lifting) of an unknown object (to the robot controller) has been considered for validation, employing a Franka EMIKA panda robot. The MuJoCo environment has been employed to implement and test the proposed multi-agent framework. The achieved results show that the proposed decentralized approach is capable of accelerating the learning process at the beginning with respect to the single-agent framework while also reducing the computational effort. In fact, when decentralizing the controller, it is shown that the number of variables involved in the action space can be efficiently separated into several groups and several agents. This simplifies the original complex problem into multiple ones, efficiently improving the task learning process.
Detecting Small Size Mass Loading Using Transversely Coupled SAW Resonator
Authors: You Ran , Liu Jiuling , Liu Minghua , Zhang Yuxiang , Chen Zhiyuan , He Shitang
Published: November 2021

In the detection of small size mass loading, such as a single cell, a micro droplet or an aerosol particle, the sensors with longitudinally coupled surface acoustic wave resonator (LC-SAWR) structure can hardly avoid waveform distortions. The relative size of mass loading to the sensitive surface of the detector is the main factor affecting the response of LC-SAWR. The smaller the relative size, the worse the waveform distortion. In order to avoid influences from the mass loading’s size, in this paper, a transversely coupled SAW resonator (TC-SAWR) was proposed in order to achieve high performance in sensing small size mass loadings. For the design and simulation of TC-SAWR, the two-dimensional coupling of model (2D-COM) theory and finite element method (FEM) were used in this work. In the experiment, SiO2 was deposited on the sensor’s surface as a small size mass loading. The results from simulation and experiment mutually demonstrated the advantage of TC-SAWR to conquer waveform distortion in the detection of small size mass loading.
Autonomous Driving Robot That Drives and Returns along a Planned Route in Underground Mines by Recognizing Road Signs
Authors: Kim Heonmoo , Choi Yosoon
Published: November 2021

In this study, an autonomous driving robot that drives and returns along a planned route in an underground mine tunnel was developed using a machine-vision-based road sign recognition algorithm. The robot was designed to recognize road signs at the intersection of a tunnel using a geometric matching algorithm of machine vision, and the autonomous driving mode was switched according to the shape of the road sign to drive the robot according to the planned route. The autonomous driving mode recognized the shape of the tunnel using the distance data from the LiDAR sensor; it was designed to drive while maintaining a fixed distance from the centerline or one wall of the tunnel. A machine-vision-based road sign recognition system and an autonomous driving robot for underground mines were used in a field experiment. The results reveal that all road signs were accurately recognized, and the average matching score was 979.14 out of 1000, confirming stable driving along the planned route.
Lossless Compression of Sensor Signals Using an Untrained Multi-Channel Recurrent Neural Predictor
Authors: Chen Qianhao , Wu Wenqi , Luo Wei
Published: November 2021

The use of sensor applications has been steadily increasing, leading to an urgent need for efficient data compression techniques to facilitate the storage, transmission, and processing of digital signals generated by sensors. Unlike other sequential data such as text sequences, sensor signals have more complex statistical characteristics. Specifically, in every signal point, each bit, which corresponds to a specific precision scale, follows its own conditional distribution depending on its history and even other bits. Therefore, applying existing general-purpose data compressors usually leads to a relatively low compression ratio, since these compressors do not fully exploit such internal features. What is worse, partitioning a bit stream into groups with a preset size will sometimes break the integrity of each signal point. In this paper, we present a lossless data compressor dedicated to compressing sensor signals which is built upon a novel recurrent neural architecture named multi-channel recurrent unit (MCRU). Each channel in the proposed MCRU models a specific precision range of each signal point without breaking data integrity. During compressing and decompressing, the mirrored network will be trained on observed data; thus, no pre-training is needed. The superiority of our approach over other compressors is demonstrated experimentally on various types of sensor signals.
Metal-Organic Frameworks Characterization via Inverse Pulse Gas Chromatography
Authors: Yusuf Kareem , Shekhah Osama , ALOthman Zeid , Eddaoudi Mohamed
Published: November 2021

The desire to customize the properties of a material through complete control over both its chemical and architectural structure has created a constant and persistent need for efficient and convenient characterization techniques. Inverse gas chromatography (IGC) is considered a useful characterization method for probing the material’s surface properties, like its enthalpies of adsorption, which are the key stimulus components for their adsorption performance. Here, we conclusively review the significance of a less common application of the IGC technique for the physicochemical characterization of metal-organic frameworks (MOFs), which are an innovative subclass of porous materials with matchless properties in terms of structure design and properties. This review focuses on the fundamental theory and instrumentation of IGC as well as its most significant applications in the field of MOF characterization to shed more light on this unique technique.
Reservoir Characterisation of High-Pressure, High-Temperature Zone of Malay Basin Using Seismic Inversion and Artificial Neural Network Approach
Authors: Yazmyradova Gulbahar , Hassan Nik Nur Anis Amalina Nik Mohd , Salleh Nur Farhana , Hermana Maman , Soleimani Hassan
Published: November 2021

The growing demand for hydrocarbons has driven the exploration of riskier prospects in depths, pressures, and temperatures. Substantial volumes of hydrocarbons lie within deep formations, classified as high pressure, high temperature (HPHT) zone. This study aims to delineate hydrocarbon potential in the HPHT zone of the Malay Basin through the integrated application of rock physics analysis, pre-stack seismic inversion, and artificial neural network (ANN). The zones of interest lie within Sepat Field, located offshore Peninsular Malaysia, focusing on the HPHT area in Group H. The rock physics technique involves the cross-plotting of rock properties, which helps to differentiate the lithology of sand and shale and discriminates the fluid into water and hydrocarbon. The P-impedance, S-impedance, Vp/Vs ratio, density, scaled inverse quality factor of P (SQp), and scaled inverse quality factor of S (SQs) volumes are generated from pre-stack seismic inversion of 3D seismic data. The obtained volumes demonstrate spatial variations of values within the zone of interest, indicating hydrocarbon accumulation. Furthermore, the ANN model is successfully trained, tested, and validated using 3D elastic properties as input, to predict porosity volume. Finally, the trained neural network is applied to the entire reservoir volume to attain a 3D porosity model. The results reveal that rock physics study, pre-stack seismic inversion, and ANN approach helps to recognize reservoir rock and fluids in the HPHT zone.
Establishment and Application of a Monitoring Strategy for Living Modified Cotton in Natural Environments in South Korea
Authors: Lim Hye Song , Kim Il Ryong , Lee Sunghyeon , Choi Wonkyun , Yoon A-Mi , Lee Jung Ro
Published: November 2021

Cotton (Gossypium hirsutum L.) is grown worldwide for its natural hollow fibers and is used as cattle feed. Living modified (LM) cotton is not cultivated in South Korea and must be imported for food, feed, and processing. From 2009 to 2013, the Ministry of Environment (MOE) and the National Institute of Ecology (NIE) conducted a natural environment monitoring and post-management initiative for living modified organisms (LMOs) in some areas to reduce the likelihood of harmful effects caused by unintentionally discharged LMOs during transportation and use. In this study, we adopted a new strategy to identify unintentionally released LM cotton plants nationwide from 2014 to 2018. A total of 451 suspicious cotton samples were collected from 3921 survey sites. Among them, we identified 255 LM cotton plants, of which approximately 72.2% had transgenic herbicide and insecticide traits. The majority of the samples were collected from the roadside along transportation routes and from stockbreeding farms. This study establishes an LMO safety management system to efficiently maintain conservation efforts in South Korea. Our findings suggest that these efforts may play a key role in safely transporting, using, and managing approved LMOs, as well as in regulating unintentionally released LMOs, in order to preserve the natural ecosystem of South Korea.
Some New Post-Quantum Integral Inequalities Involving Twice (p, q)-Differentiable ψ-Preinvex Functions and Applications
Authors: Vivas-Cortez Miguel , Awan Muhammad Uzair , Talib Sadia , Kashuri Artion , Noor Muhammad Aslam
Published: November 2021

The main motivation of this article is derive a new post-quantum integral identity using twice (p, q)-differentiable functions. Using the identity as an auxiliary result, we will obtain some new variants of Hermite–Hadamard’s inequality essentially via the class of ψ-preinvex functions. To support our results, we offer some applications to a special means of positive real numbers and twice (p, q)-differentiable functions that are in absolute value bounded as well.
The Rigging Technique for Null Hypersurfaces
Authors: Gutiérrez Manuel , Olea Benjamín
Published: November 2021

Starting from the main definitions, we review the rigging technique for null hypersurfaces theory and most of its main properties. We make some applications to illustrate it. On the one hand, we show how we can use it to show properties of null hypersurfaces, with emphasis in null cones, totally geodesic, totally umbilic, and compact null hypersurfaces. On the other hand, we show the interplay with the ambient space, including its influence in causality theory.
Foundations of Engineering Mathematics Applied for Fluid Flows
Authors: Chashechkin Yuli D.
Published: November 2021

Based on a brief historical excursion, a list of principles is formulated which substantiates the choice of axioms and methods for studying nature. The axiomatics of fluid flows are based on conservation laws in the frames of engineering mathematics and technical physics. In the theory of fluid flows within the continuous medium model, a key role for the total energy is distinguished. To describe a fluid flow, a system of fundamental equations is chosen, supplemented by the equations of the state for the Gibbs potential and the medium density. The system is supplemented by the physically based initial and boundary conditions and analyzed, taking into account the compatibility condition. The complete solutions constructed describe both the structure and dynamics of non-stationary flows. The classification of structural components, including waves, ligaments, and vortices, is given on the basis of the complete solutions of the linearized system. The results of compatible theoretical and experimental studies are compared for the cases of potential and actual homogeneous and stratified fluid flow past an arbitrarily oriented plate. The importance of studying the transfer and transformation processes of energy components is illustrated by the description of the fine structures of flows formed by a free-falling drop coalescing with a target fluid at rest.
Hybrid Method for Simulation of a Fractional COVID-19 Model with Real Case Application
Authors: Din Anwarud , Khan Amir , Zeb Anwar , Sidi Ammi Moulay Rchid , Tilioua Mouhcine , Torres Delfim F. M.
Published: November 2021

In this research, we provide a mathematical analysis for the novel coronavirus responsible for COVID-19, which continues to be a big source of threat for humanity. Our fractional-order analysis is carried out using a non-singular kernel type operator known as the Atangana-Baleanu-Caputo (ABC) derivative. We parametrize the model adopting available information of the disease from Pakistan in the period 9 April to 2 June 2020. We obtain the required solution with the help of a hybrid method, which is a combination of the decomposition method and the Laplace transform. Furthermore, a sensitivity analysis is carried out to evaluate the parameters that are more sensitive to the basic reproduction number of the model. Our results are compared with the real data of Pakistan and numerical plots are presented at various fractional orders.
Responses of the Soil Microbial Community to Salinity Stress in Maize Fields
Authors: Hou Yaling , Zeng Wenzhi , Hou Menglu , Wang Zhao , Luo Ying , Lei Guoqing , Zhou Bo , Huang Jiesheng
Published: November 2021

To investigate the diversity and structure of soil bacterial and fungal communities in saline soils, soil samples with three increasing salinity levels (S1, S2 and S3) were collected from a maize field in Yanqi, Xinjiang Province, China. The results showed that the K+, Na+, Ca2+ and Mg2+ values in the bulk soil were higher than those in the rhizosphere soil, with significant differences in S2 and S3 (p < 0.05). The enzyme activities of alkaline phosphatase (ALP), invertase, urease and catalase (CAT) were lower in the bulk soil than those in the rhizosphere. Principal coordinate analysis (PCoA) demonstrated that the soil microbial community structure exhibited significant differences between different salinized soils (p < 0.001). Data implied that the fungi were more susceptible to salinity stress than the bacteria based on the Shannon and Chao1 indexes. Mantel tests identified Ca2+, available phosphorus (AP), saturated electrical conductivity (ECe) and available kalium (AK) as the dominant environmental factors correlated with bacterial community structures (p < 0.001); and AP, urease, Ca2+ and ECe as the dominant factors correlated with fungal community structures (p < 0.001). The relative abundances of Firmicutes and Bacteroidetes showed positive correlations with the salinity gradient. Our findings regarding the bacteria having positive correlations with the level of salinization might be a useful biological indicator of microorganisms in saline soils.
Assessment of Anthropometric Indices for Optimal Cut-Offs for Obesity Screening in a South African Adolescent Population
Authors: Engwa Godwill Azeh , Schmid-Zalaudek Karin , Anye Chungag , Letswalo Boitumelo P. , Anye Paul Chungag , Mungamba Muhau Muhulo , Sewani-Rusike Constance Rufaro , Goswami Nandu , Nkeh-Chungag Benedicta Ngwenchi
Published: November 2021

The assessment of obesity in sub-Saharan Africa relies on cut-offs established from western populations. This study assessed anthropometric indices to determine optimal cut-off values for obesity screening in the South African adolescent population. A cross-sectional study involving 1144 (796 females and 348 males) adolescents aged 11–17 years from the Eastern Cape Province of South African was conducted. Anthropometric parameters were measured. Receiver operating characteristic (ROC) analysis was performed to assess the sensitivity and specificity of obesity screening tools and establish cut-offs. The optimal cut-offs for obesity in the cohort using waist-to-height ratio (WHtR) as reference were: neck circumference (NC) = 30.6 cm, mid-upper arm circumference (MUAC) = 25.9 cm, waist circumference (WC) = 75.1 cm, hip circumference (HC) = 92.15 cm and body mass index percentile (pBMI) = p85.2th. The new pBMI cut-off value at p85.2th improved the sensitivity of the test by approximately 30% compared to the CDC recommended BMI percentile (pBMIr) of p95.0th. When pBMI was used as reference, the optimal cut-offs in the cohort were: WHtR = 0.481, NC = 30.95 cm, MUAC = 27.95 cm, WC = 76.1 cm and HC = 95.75 cm. The WHtR optimal cut-off of 0.481 was close to the recommended cut-off value of 0.5. The predicted prevalence of obesity obtained using cut-offs from ROC analysis was higher than those from recommended references. All cut-off values for the various anthropometric measures generally increased with age for all percentile ranges. This study reveals a lower pBMI cut-off value, different from the CDC recommended cut-off, for screening obesity in a South African adolescent population. The study has established that the optimal pBMI cut-off for obesity screening may be ethnic-specific.
Soil Fungal Community Composition Correlates with Site-Specific Abiotic Factors, Tree Community Structure, and Forest Age in Regenerating Tropical Rainforests
Authors: Adamo Irene , Ortiz-Malavasi Edgar , Chazdon Robin , Chaverri Priscila , ter Steege Hans , Geml József
Published: November 2021

Successional dynamics of plants and animals during tropical forest regeneration have been thoroughly studied, while fungal compositional dynamics during tropical forest succession remain unknown, despite the crucial roles of fungi in ecological processes. We combined tree data and soil fungal DNA metabarcoding data to compare richness and community composition along secondary forest succession in Costa Rica and assessed the potential roles of abiotic factors influencing them. We found a strong coupling of tree and soil fungal community structure in wet tropical primary and regenerating secondary forests. Forest age, edaphic variables, and regional differences in climatic conditions all had significant effects on tree and fungal richness and community composition in all functional groups. Furthermore, we observed larger site-to-site compositional differences and greater influence of edaphic and climatic factors in secondary than in primary forests. The results suggest greater environmental heterogeneity and greater stochasticity in community assembly in the early stages of secondary forest succession and a certain convergence on a set of taxa with a competitive advantage in the more persisting environmental conditions in old-growth forests. Our work provides unprecedented insights into the successional dynamics of fungal communities during secondary tropical forest succession.
Proteasome Inhibition Is an Effective Treatment Strategy for Microsporidia Infection in Honey Bees
Authors: Huntsman Emily M. , Cho Rachel M. , Kogan Helen V. , McNamara-Bordewick Nora K. , Tomko Robert J. , Snow Jonathan W.
Published: November 2021

The microsporidia Nosema ceranae is an obligate intracellular parasite that causes honey bee mortality and contributes to colony collapse. Fumagillin is presently the only pharmacological control for N. ceranae infections in honey bees. Resistance is already emerging, and alternative controls are critically needed. Nosema spp. exhibit increased sensitivity to heat shock, a common proteotoxic stress. Thus, we hypothesized that targeting the Nosema proteasome, the major protease removing misfolded proteins, might be effective against N. ceranae infections in honey bees. Nosema genome analysis and molecular modeling revealed an unexpectedly compact proteasome apparently lacking multiple canonical subunits, but with highly conserved proteolytic active sites expected to be receptive to FDA-approved proteasome inhibitors. Indeed, N. ceranae were strikingly sensitive to pharmacological disruption of proteasome function at doses that were well tolerated by honey bees. Thus, proteasome inhibition is a novel candidate treatment strategy for microsporidia infection in honey bees.
The Influence of Oxidative Stress on Neurological Outcomes in Spontaneous Intracerebral Hemorrhage
Authors: Masomi-Bornwasser Julia , Kurz Elena , Frenz Christina , Schmitt Jan , Wesp Dominik M. A. , König Jochem , Lotz Johannes , Ringel Florian , Kerz Thomas , Krenzlin Harald , Keric Naureen
Published: November 2021

Spontaneous intracerebral hemorrhage (ICH) causes, besides the primary brain injury, a secondary brain injury (SBI), which is induced, amongst other things, by oxidative stress (OS) and inflammation, determining the patient’s outcome. This study aims to assess the impact of OS in plasma and cerebrospinal fluid (CSF) on clinical outcomes in patients with ICH. A total of 19 ICH (volume > 30 cc) patients and 29 control patients were included. From day one until seven, blood and CSF samples were obtained, and ICH volume was calculated. OS markers, like malondialdehyde (MDA), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), glutathione-sulfhydryl (GSH), and the total antioxidant status (TAS) were measured. Clinical data on treatment and outcome were determined. Patients with mRS ≤ 4 showed significantly elevated SOD and GSH-Px levels in plasma compared to patients with poor CO (p = 0.004; p = 0.002). Initial increased TAS in plasma and increased MDA in CSF were linked to an unfavorable outcome after six months (p = 0.06, r = 0.45; p = 0.05, r = 0.44). A higher ICH volume was associated with a worse outcome at week six (p = 0.04, r = 0.47). OS plays a significant role in SBI. Larger ICHs, elevated MDA in CSF, and TAS in plasma were associated with a detrimental outcome, whereas higher plasma-SOD and -GSH-Px were associated with a favorable outcome.
Using Graphene-Based Biosensors to Detect Dopamine for Efficient Parkinson’s Disease Diagnostics
Authors: Kujawska Małgorzata , Bhardwaj Sheetal K. , Mishra Yogendra Kumar , Kaushik Ajeet
Published: November 2021

Parkinson’s disease (PD) is a neurodegenerative disease in which the neurotransmitter dopamine (DA) depletes due to the progressive loss of nigrostriatal neurons. Therefore, DA measurement might be a useful diagnostic tool for targeting the early stages of PD, as well as helping to optimize DA replacement therapy. Moreover, DA sensing appears to be a useful analytical tool in complex biological systems in PD studies. To support the feasibility of this concept, this mini-review explores the currently developed graphene-based biosensors dedicated to DA detection. We discuss various graphene modifications designed for high-performance DA sensing electrodes alongside their analytical performances and interference studies, which we listed based on their limit of detection in biological samples. Moreover, graphene-based biosensors for optical DA detection are also presented herein. Regarding clinical relevance, we explored the development trends of graphene-based electrochemical sensing of DA as they relate to point-of-care testing suitable for the site-of-location diagnostics needed for personalized PD management. In this field, the biosensors are developed into smartphone-connected systems for intelligent disease management. However, we highlighted that the focus should be on the clinical utility rather than analytical and technical performance.
Influence of «Spectolak extra» on the growth rate of post-weaned pigs
Authors: Pshenichnaya E. A. , Ermolova E. M.
Published: November 2021

Post-weaned pigs are affected by such stressful situations as weaning and switching to another diet, participation in the life of a new group of animals, getting used to a new place of residence, the struggle of piglets for the establishment of hierarchical subordination. All of the above factors lead to a weakening of the immunity of piglets and the appearance of deep physiological changes in the digestive organs. The purpose of the research work was to study the influence of the skimmed milk replacer “Spectolak extra” on the growth rate of post-weaned pigls. Scientific and economic experiment was carried out on the basis of OOO “Agrofirma Ariant”, which is located in the Chelyabinsk region. The object of research was compound feed intended for post-weaning pigs, skimmed milk replacer “Spectolak extra” and post-weaned pigs themselves. The selection of postweaned pigs into groups has been carried out on the principle of pairs of analogues grown under the same feeding and housing conditions. Two groups of piglets with 15 heads in each group have been formed. “Spectolak extra” was added to the compound feed for post-weaned pigs at a dose of 4 kg per 100 kg of compound feed, which softens the transition from mother’s milk to vegetable feed. “Spectolak extra” consists of 67 % of dairy components, as well as micro – and macroelements, vitamins and amino acids in its composition. It has been found that for the entire period of the experiment, i.e. before the animals reached the age of 4 months, the piglets of the experimental group had an absolute live weight gain 34,4 kg, which was more by 3,7 kg or 9,4 % (P < 0,001) than in the control group. The average daily gain in live weight in the experimental group was also higher by 80 g or 20,0 % (P < 0,001) and it was in average 480 g.
Algorithm for calculation of reliability indicators based on monitoring of technical condition parameters
Authors: Kostomakhin M. N. , Voronov A. N.
Published: November 2021

Material by definition of local indicators of reliability of self-propelled farm vehicles, on the basis of monitoring of the controlled resource parameters used for definition of technical condition of the equipment is presented in article. The main dependences when calculating local indicators of a resource are given, examinees of cars/knots/interfaces.
Nanoscale tribological materials
Authors: Selyutin G. E. , Dunaev A. V.
Published: November 2021

The results of the development and testing of nanodiamond triboactive from Krasnoyarsk Institute of chemistry and chemical technology, Krasnoyarsk Institute of Biophysics together with "RealDzerjinsk", as well as the results of the development of the new triboactive based on nano carbon fibers. It is proved that in contrast to pure nanodiamond powders imported nanomaterials explosion technologies graphite represent pseudoalpina nanoparticles surrounded by a carbon shell. Saturating them various peripheral organic compounds can be sedimentary stable carbon clusters, working at friction in oil is not for mechanism sergiovanni, and the mechanism of chemisorption and polymerization components triborate. A new, more technologically advanced and cheaper tribological material GRAF SB on the basis of on nano carbon fibers, are no less effective nanodiamond, only works on mechanism of adsorption and chemisorption.
Rancang Bangun Tempat Sampah Dengan Sistem Memilah Jenis Sampah Basah, Kering dan Logam Menggunakan Atmega328P
Authors: Nugroho Hendre Setio
Published: November 2021

Sampah tentunya menjadi masalah pada kehidupan setiap hari, dari jenis sampah yang berbeda, volume sampah yang sangat bervariasi hingga permasalahan sampah masih sering dibarkan menumpuk pada tempat sampah sehingga dapat menimbulkan penyakit tertentu ketika sampah dibiarkan menumpuk. Tujuan dari penelitian ini adalah agar jenis sampah yang dibuang tidak menyatu dalam satu tempat sampah lagi dan sampah tidak lagi dibiarkan menumpuk ketika tempat sampah sudah penuh. Penelitian kali ini akan menggunakan ATmega328P sebagai pengatur dalam keseluruhan proses kerja alat, magnet elektromagnetik sementara untuk memilah sampah logam sedangkan sensor touch digunakan sebagai pemilah sampah basah atau kering. Magnet elektromagnetik sementara yang digunakan mampu mengangkat beban sampah logam seberat maksimal 1,9kg, sedangkan sensor touch yang digunakan pada penelitian ini dapat memilah sampah basah atau sampah kering karena sensor touch memiliki output analog. Output analog dari sampah basah berada pada range 2.5 â€“ 209 dan untuk output analog sampah kering berada pada range 210 â€“ 224. Conveyor pada penelitian kali ini berfungsi sebagai tempat menjatuhkan sampah dan menghantarkan sampah pada tempat sampah yang berbeda. Nilai keberhasilan dari keseluruhan sistem yang dibuat pada penelitian kali ini adalah sebesar 79%.
Sistem Penghitung Skor Otomatis Pada Olahraga Menembak Menggunakan Metode Analisis Blob Berbasis Matlab
Authors: Dharma Hazel Rasendriya
Published: November 2021

Abstrak – Olahraga menembak merupakan olahraga ketangkasan karena olahraga ini memerlukan tingkat fokus dan ketelitian yang tinggi. Saat ini penghitungan skor pada olahraga menembak masih menggunakan cara manual sehingga membutuhkan tenaga petugas dan waktu yang lebih lama dalam penghitungan skor. Sistem Penghitung Skor Otomatis (PSO) pada olahraga menembak bertujuan untuk mengklasifikasi citra sasaran tembak dan citra jejak peluru hingga mengkalkulasikan jumlah skor yang di dapat. Sistem pengolahan citra sendiri menggunakan bahasa pemrograman Matlab untuk mendeteksi citra pada sasaran tembak. Prinsip utama metode analisis blob adalah mendeteksi kumpulan pixel dengan warna yang sama dibandingkan dengan latar belakangnya agar dapat mendeteksi low-level dalam suatu objek dua dimensi. Dari tahap pengujian diperoleh hasil persentase keberhasilan sistem dalam menghitung skor sebesar 92%. Dibandingkan dengan cara penghitungan manual/visual yang masih dilakukan oleh petugas, Sistem PSO lebih efektif dalam melakukan perhitungan skor pada olahraga menembak.
Dolgan Destancılık Geleneği ve Dolgan Destanlarındaki Farklı Bir Kahraman: Atın Oğlu Atalamii Bahadır
Authors: DURANLI Muvaffak
Published: November 2021

Destan metninin en belirgin özelliği, toplumun bütün olumlu değer yargılarını taşıyan, bir “rol model” niteliğinde algılanabilecek olumlu bir baş kahraman içermesidir. Kahramanlık olgusunun geçmişte hemen hemen her toplumda erkekle özdeşleşmesinden dolayı destan kahramanlarının çoğu erkek kahramanlardan oluşsa da pek çok kültürde sınırlı sayıda kadın destan kahramanı da yer almaktadır. İster erkek ister kadın olsun kahraman, toplumunun inancı, yaşama biçimi ve olumlu kabul edilebilecek bütün değer yargıları ile bütünleşmiştir. O iyi, güçlü, sadık, adaletlidir. Onu tanımlayan her sıfat, destanı dinleyeni ve okuyanı etkileme amacına hizmet eder.Bu sıfatların etkileme düzeyi toplumun değer yargıları ile bağlantılı olduğu ölçüde artmaktadır. Kahraman soylu, zengin bir aileden olabileceği gibi, fakir, fakat önemsenen bir köke de sahip olabilir. Mitlerde tanrısal köklerle bağlantılı olan kahramanların varlığı söz konusuyken destanlarda da benzer şekilde kutsal bir hayvanın soyundan gelen kahramanlar vardır. Bu ise kahramanı insanüstü özelliklerle donatmanın bir yolu olarak değerlendirilebilir. Atın Oğlu Atalamii Bahadır adlı Dolgan destanında kahraman bir atın oğludur. Kahramanın kökünün bir insandan değil, bir attan gelmiş olması Dolgan inanç sistemi ile bağlantılıdır. Dolgan inanç sisteminde göre, Tanrı/ Tanrıların yeryüzü için yarattıkları ilk canlı attır. Bu attan at- insan, ondan da insan yaratılmıştır. Bu makalede Dolganlar, Dolgan destan anlatıcılığı ve Dolganlar arasından farklı tarihlerde derlenmiş Atın Oğlu Atalamii Bahadır adlı destanın belirleyici özellikleri ve kahramanın mitolojik motiflerle nasıl güçlendirildiği ele alınacaktır.
Inclusión y diferenciación de la educación secundaria para jóvenes y adultos en Argentina. Un análisis sobre la especificidad de la oferta del Plan FinEs II
Authors: Olivares Julián
Published: November 2021

El presente artículo tiene como objetivo abordar la especificidad de la oferta del Plan de Finalización de Estudios Primarios y Secundarios para Jóvenes y Adultos II, más conocido como FinEs II, en Argentina. Para ello se avanza a través de distintos niveles de análisis, tomando en cuenta las determinaciones de la expansión de la educación secundaria en el país, para luego observar la normativa general que regula la política educativa estudiada a nivel nacional y en la provincia de Buenos Aires (donde más desarrollo tuvo el programa), las particularidades de su diseño curricular y sus diferencias con otras ofertas secundarias para jóvenes y adultos, las características de los espacios de cursada, así como también de las formas que asume el trabajo de docentes y referentes de las sedes.