bluuebunny/crossref_metadata_2025 huggingface dataset:
The Aerob and Anaerob Performance Beta-Alanine Supplement and Ergogenic Aid Using to the Power Output Variables in Cyclists: A Cohort Studies Random Model Effect
Authors: Kahraman Yeliz
Published: August 2021

: Supplement the use of ergogenic aids in cyclist’s directly have been improved the body metabolism and hemodynamic factors that are micro supplement in chancing reactions on the body muscle mass and limb muscle. Mostly knowing that, muscle power development progressive fast glycolytic and short time oxidative systems reactions. Sport competition intervals, therefore, during periods has been used specific drinks supported to cyclists. But, be obtained during should be long race times. Athletes directly needed some drug and fluid intake to prevented from metabolic breakdown rapidly the dynamic physiologic performance factors. Beta-alanine supplementation can be direct muscle performance development affects the anaerobic metabolism and capacity. It should be de-termined how the cyclists will use the competitive and training period intervals can increase the cyclists specific sprint and endurance race performance. Science cyclist International Road doses will be created in which, intervals can random effectively the investigate. This study random a cohort studies is examined the effects of beta-alanine supplementation on aerobic and anaerobic power output in specific cyclists. Therefore, we have been databases PubMed, Scopus and Medline initial search 10 August 2020 were created prospective effect the quality of bias work concluded effect size (ES) 95% confidence interval (CI) were used in participant. Participations (N=66) have age range 25 to 38 of the using beta-alanine in training periods to endurance muscle performance, aerobic power, anaerobic power, and sprint time trials. As a result of beta-alanine improved an-aerobic and aerobic power output on 4-week time-dependent trial performance condition. Signifi-cant values are obtained level factor alpha <0.05 and p-value analysis pre-post interactive stand-ardization.
A Note on Stokes Approximations to Leray Solutions of the Incompressible Navier-Stokes Equations in Rn
Authors: Rigelo Joyce Cristina , Zingano Janaina Pires , Zingano Paulo Ricardo
Published: August 2021

In the early 1980s it was well established that Leray solutions of the unforced Navier-Stokes equations in Rn decay in energy norm for large time. With the works of T. Miyakawa, M. Schonbek and others it is now known that the energy decay rate cannot in general be any faster than t^-(n+2)/4 and is typically much slower. In contrast, we show in this note that, given an arbitrary Leray solution u(.,t), the difference of any two Stokes approximations to the Navier-Stokes flow u(.,t) will always decay at least as fast as t^-(n+2)/4, no matter how slow the decay of || u(.,t) ||_L2 might happen to be.
Comparative Study and Overview of Field-oriented Control Techniques for 6-phase PMSM
Authors: Furmanik Marek , Gorel Lukáš , Konvičný Daniel , Rafajdus Pavol
Published: August 2021

The paper interprets a comparison of two mostly used techniques of a field-oriented control for 6-phase electric drives, with their pros and cons, as well as their differences in construction and behaviour. Both of these approaches have been realized. Frequency and step responses analysis have been demonstrated with a 6-phase permanent magnet synchronous machine. Experimental results have been compared with simulations based on a mathematical model.
Difficulty Manipulation and Feedback Strategies on Performance During a Novel Fine Motor Coordination Task
Authors: Elghoul Yousri , Bahri Fatma , Trabelsi Khaled , Chtourou Hamdi , Frikha Mohamed , Clark Cain C.T. , Glenn Jordan M. , Bragazzi Nicola , Souissi Nizar
Published: August 2021

Improving the acquisition and retention of a new motor skill is of great importance. The present study (i) investigated the effects of difficulty manipulation strategies (gradual difficulty), combined with different modalities of feedback (FB) frequency on performance accuracy and consistency when learning a novel fine motor coordination task, and (ii) examined relationships between novel fine motor task performance and executive function (EF), working memory (WM), and perceived difficulty (PD). Thirty-six, right-handed, novice physical education students volunteered to participate in this study. Participants were divided into three progressive difficulty groups (PDG), 100% visual FB (FB1), 50% FB (FB2), and 33% FB (FB3). Progressive difficulty was increased by the manipulation of the distance to the target; 2 m, 2.37 m, and 3.56 m. Three FB modalities were investigated (i.e.: 100% visual FB (100% FB), 50% reduced feedback condition (50% RFB), and 33% reduced feedback conditions (33% RFB)). Performance assessments were conducted following familiarization, acquisition, and retention learning phases. Two stress-conditions of dart throws were investigated (i.e.: free condition (FC) and time pressure condition (TPC)). After the learning intervention, data showed that, under the free condition, the 100% FB group had a significant improvement in accuracy during all learning phases. Under time pressure condition, for the 50% RFB and the 33% RFB group, the measured variable (accuracy and consistency) showed a significant linear improvement in performance. The association between the percentage of RFB frequencies and the task difficulty (50% group) may be a more appropriate and manageable cognitive load compared to the 33% RFB and the 100% FB group. The present findings could have practical implications for practitioners because, while strategies are clearly necessary for improving learning, the efficacy of the process appears to be essentially based on the characteristics of the learners.
θ∗-Weak Contractions and Discontinuity at the Fixed Point With Applications to Matrix and Integral Equations
Authors: Perveen Atiya , Alfaqih Waleed , Sessa Salvatore , Imdad Mohammad
Published: August 2021

In this paper, the notion of θ∗-weak contraction is introduced, which is utilized to prove some fixed point results. These results are helpful to give a positive response to certain open question raised by Kannan [Amer. Math. Monthly 76:1969] and Rhoades [Contemp. Math. 72:1988] on the existence of contractive definition which does not force the mapping to be continuous at the fixed point. Some illustrative examples are also given to support our results. As applications of our result, we investigate the existence and uniqueness of a solution of non-linear matrix equations and integral equations of Volterra type as well.
Adverse Drug Reaction Reports Containing AMR-Relevant MedDRA Terms in the Dutch Pharmacovigilance Database
Authors: Habarugira Jean Marie Vianney , Harmark Linda , Figueras Albert
Published: August 2021

(1) Background: Antimicrobial resistance (AMR) requires urgent multidisciplinary solutions, and Pharmacovigilance (PV) has the potential to strengthen current antimicrobial stewardship (AMS) strategies. This study aimed to characterise AMR-relevant adverse drug reaction (ADR) reports submitted to The Netherlands Pharmacovigilance Centre (Lareb); (2) Methods: We carried out a descriptive analysis of ADR reports submitted to Lareb, coded with AMR-relevant MedDRA Preferred Terms (PTs).; (3) Results: Between 1998 and Jan 2019, 252 AMR-relevant ADR reports were submitted to Lareb. The most frequent antibiotics were tobramycin (n=89; 35%), colistin (n=30; 11,9%), ciprofloxacin (n=16; 6,35%), doxycycline (n=14; 5,5%) and aztreonam (n=12; 4,76%). The most frequently used PTs were drug ineffective (n=71; 28%), pathogen resistance (n=14; 5%) and drug resistance (n=13; 13%). A total of 119 reports (74%) suggested use-related issues. Watch antibiotics were in 54% of the reports and Reserve antibiotics were in 19%. In the Watch group, “Off label use” and “Product use in unapproved indication” were the most frequent PTs and majority of reports on Reserve antibiotics were coded as “Off label”. (4) Conclusions: Addressing AMR using the PV methods will provide an opportunity for PV expansion and could encourage further investment in both in AMS programs and PV systems.
The impact of Artificial Intelligence on Data System Security: A Literature Review
Authors: Rosário Albérico Travassos , Raimundo Ricardo
Published: August 2021

Diverse forms of artificial intelligence (AI in further text) are at the forefront of triggering digital security innovations, based on the threats that are arising in this post COVID world. On the one hand, companies are experiencing difficulty in dealing with security challenges with regard to a variety of issues ranging from system openness, decision making, quality control and web domain, just to mention a few. On the other hand, in the last decade, research has focused on security capabilities based on tools such as platform complacency, intelligent trees, modeling methods and outage management systems, in an effort to understanding the interplay between AI and those issues. The dependence on the emergence of AI in running industries and shaping the education, transports and health sectors is now well known in literature. AI is increasingly employed in managing data security across economic sectors. Thus, a literature review of AI and system secu-rity within the current digital society is opportune. This paper aims at identifying research trends in the field through a Systematic Bibliometric Literature Review (LRSB) of research on AI and system security. The review entails 77 articles published in Scopus® database, presenting up-to-date knowledge on the topic. The LRSB results were synthesized across current research subthemes. Findings are presented. The originality of the paper relies on its LRSB method, together with extant review of articles that have not been categorized so far. Implications for future re-search are suggested.
Inclination Estimates from Off-Axis GRB Afterglow Modelling
Authors: Lamb Gavin P. , Fernandez Joseph J. , Hayes Fergus , Kong Albert K. H. , Lin En-Tzu , Tanvir Nial R. , Hendry Martin , Heng Ik Siong , Saha Surojit , Veitch John
Published: August 2021

For gravitational wave (GW) detected neutron star mergers, one of the leading candidates for electromagnetic (EM) counterparts is the afterglow from an ultra-relativistic jet. Where this afterglow is observed, it will likely be viewed off-axis, such as the afterglow following GW170817/GRB 170817A. The temporal behaviour of an off-axis observed GRB afterglow can be used to reveal the lateral jet structure, and statistical model fits can put constraints on the various model free-parameters. Amongst these parameters is the inclination of the system to the line of sight. Along with the GW detection, the afterglow modelling provides the best constraint on the inclination to the line-of-sight and can improve the estimates of cosmological parameters e.g. the Hubble constant, from GW-EM events. However, modelling of the afterglow depends on the assumed jet structure and, often overlooked, the effects of lateral spreading. Here we show how the inclusion of lateral spreading in the afterglow models can affect the estimated inclination of GW-EM events.
Precision Rock Excavation: Beyond Controlled Blasting and Line Drilling
Authors: Cardu Marilena , Saltarin Simone , Todaro Carmine , Deangeli Chiara
Published: August 2021

The strictness of the result of an excavation, whether mechanical or by means of explosives, is naturally conditioned by the objective, and therefore by the type of technique applied to achieve it. To attain the best results in terms of rock breakage and respect of the final profile, it’s important to evaluate the excavation specific energy and its optimization. This research focuses on evaluating the effects of different techniques on the quality of final walls in open-pit and underground operations. Different geometries and configurations can be applied to both quarrying and tunnelling blasts. The research is aimed to push contour blasts to their limits, and the main aspects are discussed in order to improve the blast parameters in the daily practice.
Artscience, STEAM, SciArt, SEAD and Much More: Multiple Names for a Complex and Transdisciplinary Research Field
Authors: Silveira Joao
Published: August 2021

This article explores the lack of unanimity regarding the nomenclature used to refer to the field of research that explores the intersection between art and science. A series of examples of nomenclatures and the context in which they are applied are listed and referenced. The diverse terminology reflects the heterogeneity, transdisciplinarity, and complexity of a research field in full expansion.
Utilizing Hybrid Feature Extraction, Tree-Based Learning and Data-Lightweight Model Re-Training for Accurate Short-Term and Day-Ahead Residential Load Forecasting
Authors: Ioakimidis Christos S , Bezas Napoleon , Timplalexis Christos , Salamanis Athanasios I. , Karapatsias Vasileios , Ioannidis Dimosthenis , Kehagias Dionysios , Tzovaras Dimitrios
Published: August 2021

Residential load forecasting is one of the most important tasks of the overall supply management process in electrical grids, since it enables smart grid services such as demand response (DR). Hence, several approaches for accurate residential load forecasting have been proposed in the relevant literature. However, most of the existing methods focus on the forecasting performance and neglect other aspects of the problem like training time and model size (i.e. memory usage). In this paper, we introduce a new model for both short-term and day-ahead residential load forecasting. The model synthesizes an heterogeneous feature set, which is constituted by both automatically-selected lagged values from the load time series and manually-extracted temporal features. Then, the tree-based algorithm light gradient boosting machine (LGBM) is fed with the constructed feature set and used as a regression model. Finally, a data-lightweight strategy is used for retraining the proposed model, which leads to both high forecasting accuracy and low training times. The proposed model has been extensively evaluated on a large real-world residential load dataset. The experimental results indicate that the proposed model achieves both higher forecasting performance and lower training times and model sizes compared to state-of-the-art solutions.
Protective Factors and Teachers’ Risk to Burnout during the Covid-19 Pandemic. Do Kolb’s Educator Roles Matter? - A Cluster Analysis
Authors: Răducu Camelia-Mădălina , Stănculescu Elena
Published: August 2021

Teacher burnout has been revealed to be one of the most common negative consequence of the COVID-19 pandemic The purpose of this study was to identify distinct psychological resources and burnout risk profiles of teachers and to examine their association with Kolb’s Educator Roles and the professional experience. Methods: The survey data were collected from 330 preschool and primary school (84 males, Mage = 38.3, SD = 9.14) teachers using a convenience sampling method. Results: The two-step cluster analysis revealed two distinct profiles. The first profile, ‘High psychological resources, no burnout risk’, was characterised by absent symptoms of burnout and increased levels of well-being, self-control, and positive emotionality. The second profile, ‘Moderate psychological resources, mild burnout’, was associated with medium levels of well-being, self-control and positive emotionality accompanied by mild burnout. Our findings highlighted that cluster 1 had a significantly higher score for the Facilitator role and cluster 2 for the Expert and Coach roles. In addition, teachers with less professional experience were more likely to belong to cluster 1, taking into account their good skills on digital literacy. Conclusions: These findings help to provide new insights into the explanation of teacher burnout and the design of intervention programmes.
Genetic and Epigenetic Variations of SARS-Cov-2 and Host Genes and Their Impact in Covid-19 Pandemic
Authors: Meethal Muhammed Elayadeth , Naseef Punnoth Poonkuzhi , Kuruniyan Mohamed Saheer , Abdulla Mansoor C , Ollakkod Shyju , Ebrahim Shahul , Varma Godavarma Girish
Published: August 2021

The global COVID-19 pandemic claiming global spread continues to evolve, now to the verge of a third wave of outbreak possibly caused by the novel variants of concern of severe acute respiratory syndrome corona virus-2 (SARS-CoV-2). The test positivity rate (TPR) and case fatal-ity rate (CFR) have increased steeply in the second wave of COVID-19 compared to the first. From the example of Kerala, a state in southern India, positivity increased from 1.33% at the peak of wave one in 10th June 2020 to 13.45% during 10th June 2021 in the second wave of pandemic. SARS-CoV-2 is an enveloped single-stranded RNA virus. Angiotensin-Converting Enzyme-2 (ACE-2) is a trans membrane surface protein present on multiple types of cells in the human body to which the viral spike protein attaches. Genetic variations in the SARS-CoV-2 and ACE2 receptor can affect the transmission, clinical manifestations, mortality and the efficacy of drugs and vaccines for COVID-19. Mutations are the primary cause of genetic variations. Given the high TPR and CFR, it is necessary to understand the variations of SARS-CoV-2 and cellular receptors of SARS-CoV-2 at the molecular level. In this review, we summarize the impact of genetic and ep-igenetic variations in determining COVID-19 pathogenesis and disease outcome.
Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions
Authors: Sarker Iqbal H.
Published: August 2021

Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is nowadays considered as a core technology of today's Fourth Industrial Revolution (4IR or Industry 4.0). Due to its learning capabilities from data, DL technology originated from artificial neural network (ANN), has become a hot topic in the context of computing, and is widely applied in various application areas like healthcare, visual recognition, cybersecurity, and many more. However, building an appropriate DL model is a challenging task, due to the dynamic nature and variations in real-world problems and data. Moreover, the lack of core understanding turns DL methods into black-box machines that hamper development at the standard level. This article presents a structured and comprehensive view on DL techniques including a taxonomy considering various types of real-world tasks like supervised or unsupervised. In our taxonomy, we take into account deep networks for supervised or discriminative learning, unsupervised or generative learning as well as hybrid learning and relevant others. We also summarize real-world application areas where deep learning techniques can be used. Finally, we point out ten potential aspects for future generation DL modeling with research directions. Overall, this article aims to draw a big picture on DL modeling that can be used as a reference guide for both academia and industry professionals.
Quantifying and Linking Sustainable Land - Water - Energy - Food Nexus Resources and Livelihoods of Local Community in Ethiopia
Authors: Wolde Zinabu , Wei Wu , Ketema Haile , Karikari Benjamin
Published: August 2021

The sustainable management of Land - Water - Energy - Food (LWEF) nexus requires an envi-ronmental characterization that allows the comparison of complex interlinkages between nexus resources and livelihoods. This complexity makes this characterization difficult coupled with limited study in quantifying sustainability of LWEF nexus and its linkage with livelihood. Therefore, the present study aimed to investigate the link between sustainable LWEF nexus and livelihoods. We used analytical hierarchy process and pairwise comparison matrix in combina-tion with weighting model. The result of composite LWEF nexus index was 0.083 representing, low sustainability. This could be linked with nexus resources consumption, use, and manage-ment. From the analysis of the weight of land, water, energy and food nexus resources, the highest weight was observed for food. The focus of on food production only shows no clear synergy on provisioning, supporting or regulating nexus resources to address livelihoods. The result further showed that LWEF nexus resources have strong correlation with livelihoods. This was evidenced by social (r>0.8, P<0.01), natural (r>0.3, P<0.05) and physical (r>0.6, P<0.01) liveli-hood indicators showed strong positive correlation with LWEF nexus resources. From this re-sults, it was observed that managing nexus resources not only provide a significant contribution to achieve sustainable LWEF nexus, but also be effective for enhancing livelihood through food security. This could be attained by strong evidence based policy to ensure sustainable use of nexus resources. The results provided by this study would serve as the foundation for future study, policy formulation and implementation.
Predicting Fatigue in Long Duration Mountain Events with a Single Sensor and Deep Learning Model
Authors: Russell Brian , McDaid Andrew , Toscano William , Hume Patria
Published: August 2021

Aim: To determine whether an AI model and single sensor measuring acceleration and ECG could model cognitive and physical fatigue for a self-paced trail run. Methods: A field-based protocol of continuous fatigue repeated hourly induced physical (~45 minutes) and cognitive (~10 minutes) fatigue on one healthy participant. Physical load was a 3.8 km, 200 m vertical gain, trail run with acceleration and electrocardiogram (ECG) data collected using a single sensor. Cognitive load was a Multi Attribute Test Battery (MATB) and separate assessment battery including the Finger Tap Test (FTT), Stroop, Trail Making A and B, Spatial Memory, Paced Visual Serial Addition Test (PVSAT), and a vertical jump. A fatigue prediction model was implemented using a Convolutional Neural Network (CNN). Results: When the fatigue test battery results were compared for sensitivity to the protocol load, FTT right hand (R2 0.71) and Jump Height (R2 0.78) were the most sensitive while the other tests were less sensitive (R2 values Stroop 0.49, Trail Making A 0.29, Trail Making B 0.05, PVSAT 0.03, spatial memory 0.003). Best prediction results were achieved with a rolling average of 200 predictions (102.4 s), during set activity types, mean absolute error for ‘walk up’ (MAE200 12.5%) and range of absolute error for ‘run down‘ (RAE200 16.7%). Conclusion: We were able to measure cognitive and physical fatigue using a single wearable sensor during a practical field protocol including contextual factors in conjunction with a neural network model. This research has practical application to fatigue research in the field.
Optimal Type 2 Diabetes Mellitus Management and Active Ageing
Authors: Calabrese Alessia Maria , Calsolaro Valeria , Rogani Sara , Okoye Chukwuma , Caraccio Nadia , Fabio Monzani
Published: August 2021

Type two diabetes mellitus (T2DM) represents a chronic condition with increasing prevalence worldwide among the older population. T2DM condition increases the risk of micro and macro-vascular complications as well as the risk of geriatric syndromes as falls, fractures and cognitive impairment. The management of T2DM in the older population represents a challenge for the cli-nician, and a Comprehensive Geriatric Assessment should always be prioritized, in order to tailor the glycate haemoglobin target according to functional and cognitive status comorbidities, life ex-pectancy and type of therapy. According to the most recent guidelines, older adults with T2DM should be cathegorized in three groups: healthy patients with good functional status, patients with complications and reduced functionality and patients at the end of life; for each group the target for the glycemic control is different, also according to the type of treatment drug. The therapeutic ap-proach should always begin with lifestyle changes; after that, several lines of therapies are available, with different mechanism of action and potential effect other than glucose level reduction. Partic-ular interest is growing around sodium-glucose cotransporter-2 inhibitors, due to their effect on the cardiovascular system. In this review we evaluate the therapeutic options available for the treat-ment of older diabetic patients, to ensure a correct treatment approach
Analysis of Accommodation Gain of Presbyopia Eye after Laser Ablation (or Shrinkage) of Sclera via Lens Reshaping and Anterior Shift
Authors: Lin Jui-Teng
Published: August 2021

Purpose: To derive and provide analytic formulas for accommodative gain of presbyopia eyes. via sclera ablation and/or thermal shrinkage such that lens is reshaped an/or its positon is shifted. New mechanisms are also proposed. Study Design: To increased accommodation of presbyopia. Place and Duration of Study: New Taipei City, Taiwan, between June, 2021 and July, 2021. Methodology: Accommodation gain is calculated by a 4-component theory, in which the rate functions are derived by an effective eye model for the change of anterior curvature of the lens and its anterior shift. The measured data of accommodative response of the lens versus the lens curvature change and anterior shift are analyzed. The measured net change of the posterior vitreal zonules (PVZ) length and the space between the ciliary body and lens (CLS) during the accommodation are also analyzed. Results: The accommodative gain (AG) is mainly due the change of lens anterior curvature and its anterior shift. The AG per diopter change of the reshaped lens is 0.62 to 0.68 by our formulas, comparing to the measured average value M'=0.69. The efficacy of LASA (or AG) is proportional to the amount of scleral tissue removed (or shrinkaged), such that more space is produced for the change of PVZ and CLS from a UCS to AS for accommodation. Conclusion: The AG is proportional to the amount of scleral tissue removed (or shrinkaged), such that more space is produced for the change of PVZ and CLS from a UCS to AS for accommodation.
Nanosensors Based on Structural Memory Carbon Nanodots for Ag+ Fluorescence Determination
Authors: Zhou Xi , Cao Yufeng , Zhou Xinji , Xu Lina , Zhang Daihui , Wang Chunpeng , Chu Fuxiang , Qian Tao
Published: August 2021

Ag+ pollution is great of harm to the human body and the biology. Therefore, it is an urgent need to develop inexpensive and accurate detection methods. Herein, lignin-derived structural memory carbon nanodots (CSM-dots) with outstanding fluorescence property were fabricated via a green method, which reserve functional and structural units of the precursor molecules. The CSM-dots could specifically bind Ag+, accompanied with a remarkable fluorescence quenching response. This “turn-off” fluorescence behavior was used for Ag+ determination in a linear range of 5-290 μM with the detection limit as low as 500 nM. Furthermore, the finding showed that this sensing nano-platform was successfully used for Ag+ determination in real samples and intracellular imaging, showing great potential in biological and environmental monitoring applications.
Resource Allocation Schemes For 5G Network: A Systematic Review
Authors: Kamal Muhammad Ayoub , Raza Hafiz Wahab , Alam Muhammad Mansoor , Mazliham M.S.
Published: August 2021

Fifth Generation (5G) communication technology is intended to offer higher data rates, outstanding user exposure, power consumption, and extremely short latency. Such cellular networks will implement a diverse multi-layer model comprising of device-to-device networks, macro-cells, and dissimilar categories of small-cells to assist customers with desired quality-of-service (QoS). This multi-layer model affects several studies that confront utilizing interference management and resource allocation in 5G networks. With the growing need and the lack of resources, the resource distribution problem desires to be focused capably to accomplish the traffic and to enhance network working. One of the utmost serious problems is to alleviate the jamming from the network in support of having a better QoS. However, there are limited review papers written on resource distribution, there is no particularize and organized review carry out in 5G resource allocation. Hence, this article covers and evaluates the argument using a classification of existing developing resource allocation schemes in 5G thoroughly by classifying the schemes to enhance the service quality. This survey comprises the discussion based on metrics used to evaluate the performance. It would also permit ahead beyond evidence on resource allocation methods in 5G and empowers the scholars to meet the present research areas to focus on.
Implicit aspects of the National Common Curricular Base: some implications in the current context
Authors: Eça Antoniclebio Cavalcante , Nunes Claudio Pinto
Published: August 2021

This work consists of analyzing and discussing some aspects that are implicit in the Common Base National Curriculum - BNCC, which was approved by the National Education Council and approved by the MEC, initially in the year 2017 with early childhood education and, later, in 2018, high school. Based on a bibliographic and documentary research, it was possible to identify that the BNCC, when approved and ratified on different dates when related to the teaching stages, members of basic education, demonstrated to have a certain fragmentation, opposing the critical conception of rights, objectives of learning and development, as provided for by law. It is concluded, therefore, that the implications implicit in this official document, dated and published in the context of a political-ideological, economic and social crisis, consequently have been unfolding and strengthening the precariousness and the dismantling of Brazilian education, requiring a wide opening of debates and discussions for new possibilities of changes in the structure and current conjuncture of the country.
Taste Learning in Insular Cortex: Plasticity Is Influenced by Experience Type
Authors:   ,   University of Tennessee Health Science Center, Staszko Stephanie
Published: August 2021

The gustatory cortex (GC) has long been studied as the main cortical area encoding taste stimuli and likely integrates sensory, visceral, and emotional information to guide taste-related behaviors. However, our understanding of cortical taste coding on a single-cell level has only become clear in recent years. The anatomical location of GC on the lateral and ventral surface of the brain makes it difficult to target with traditional imaging methods. Thus, much of what we know about cortical taste coding and cortical taste plasticity has been derived either from multiunit electrode recordings or anesthetized imaging experiments, techniques which lack the ability to reliably track neurons over time. To address this limitation, we use miniaturized microendoscope (miniscope) imaging of the calcium indicator GCaMP6s to investigate how cortical taste coding changes with different types of experience. In a basic taste experience paradigm, in which animals consume taste stimuli based on innate taste preferences, we address the question of how novelty and familiarity of taste stimuli effect cortical coding. Using multiday cell tracking, we find two populations of neurons: a stable population encoding taste quality information, and a transient cell population whose activity correlates with the animal's behavioral state. We use the associative learning paradigm conditioned taste aversion (CTA) to show changes in the transient cell population depend upon experience type. With basic experience, the number of transient cells decreases as animals become familiar with taste stimuli and the behavioral task. After increasing situational salience using CTA, the number of transient cells increases to levels seen during novel taste exposure. This research demonstrates a clear role for novelty and familiarity in population responses to taste stimuli in GC, and suggests an overall implication for these effects in cortical coding of sensory stimuli.
Pengaruh Kecerdasan Naturalis Terhadap Pro Environmental Behavior
Authors: Afifah Kamila Nur , Putrawan I Made , Vivanti Diana
Published: August 2021

Environmental problems have occurred in various regions. This problem is a problem that must be solved by many parties, including students. Pro Environmental Behavior is needed by someone to improve environmental quality. Naturalistic intelligence is one of the factors affecting Pro Environmental Behavior. This study aims to determine the naturalistic intelligence factor towards the pro environmental behavior. This study involved 48 students in Jakarta as randomly selected samples. There are two instruments that had been developed to measure these variables. Each of these instruments has a reliability of 0.852 and 0.376. Data has been analyzed by T test. The results showed that there was a difference in the average score of the pro-environmental behavior of students who had high and low naturalistic intelligence at É‘ = 0.3 (1.1). These results mean that there is an effect of naturalistic intelligence on the pro environmental behavior. Therefore, in increasing the pro-environmental behavior of students, factors such as naturalist intelligence can be considered.
Faktor Yang Memengaruhi Perilaku Peduli Lingkungan: Pengembangan Model Menggunakan Theory of Planned Behavior dan Norm Activation Model
Authors: Simanungkalit Ika Pratiwi , Hadining Aulia Fashanah , Kusnadi Kusnadi
Published: August 2021

Permasalahan Sungai Citarum menjadi salah satu wujud pencemaran lingkungan yang sampai saat ini belum teratasi sepenuhnya, bahkan kondisi Sungai Citarum mendapatkan predikat sungai paling tercemar di dunia. Salah satu faktor penyebab yaitu pola perilaku masyarakat terhadap pembuangan limbah domestik tanpa pengolahan yang menambah beban pencemaran di Sungai Citarum. Program Citarum Harum menjadi salah satu solusi untuk mengatasi permasalahan pencemaran Sungai Citarum yang dalam pelaksanaannya membutuhkan partisipasi dan kontribusi masyarakat. Keterlibatan peran serta kepedulian masyarakat menjadi kunci kesuksesan implementasi program Citarum Harum. Peran serta kepedulian masyarakat untuk memutuskan berkontribusi dalam suatu program peduli lingkungan terkait dengan bagaimana perilaku masyarakat tersebut terhadap obyeknya. Penelitian ini bertujuan untuk mengembangkan model dari Theory of Planned Behavior (TPB) dan Norm Activation Model guna menentukan faktor-faktor signifikan yang dapat memengaruhi perilaku pro-lingkungan seseorang dalam program Citarum Harum. Model yang diterapkan adalah gabungan Theory of Planned Behavior dan Norm Activation Model, dengan mengusulkan kerangka kerja yang lebih komprehensif dan tepat. Tahapan pengembangan model dari literatur sebelumnya diaplikasikan dengan menggunakan enam hipotesis. Tahap selanjutnya dari penelitian ini adalah melakukan survei untuk mengoperasionalisasikan dan menguji secara empiris model menggunakan metode yang ada sesuai dengan objek dan metode penelitian.
The role of Islamic Corporate Social Responsibility in building corporate image to increase customer loyalty
Authors: Hasan Irmayanti , Farida Lailatul , Kholilah Kholilah
Published: August 2021

This research aims to determine the influence of Islamic Corporate Social Responsibility and Corporate Image on Customer Loyalty. The research was conducted by sending questionnaires to sharia banking customers in Malang. There were 100 respondents to the study. This research is quantitative. The analysis technique used is Partial Least Square. The results showed that Islamic Corporate Social Responsibility affects Corporate Image and Customer Loyalty. This study successfully proved that CSR activities carried out by Sharia banking can increase customers' trust in Sharia banking. Besides, the survey results also showed that corporate image could not mediate ICSR's influence on customer loyalty because many customers do not know CSR activities done by Sharia banking. This study's limitations were question items in the questionnaire that did not pass the validity and reality test and a relatively small number of respondents. Further research can use question items that better describe the variables used, and analysis can be done on sharia banking customers throughout Indonesia so that the results can be more generalized.
The effect of skill and incentives on employee performance at RSUD Dr. Soekardjo Tasikmalaya
Authors: Qotrotul Rida , Adnansyah Ilham , Nugraha Nugi Mohammad
Published: August 2021

This research aims to determine the skills, incentives, and performance of employees at RSUD Dr. Soekardjo Tasikmalaya and to find out how much influence skills and incentives have on employee performance at Dr. Soekardjo Tasikmalaya for the period 2014-2018. The research used is the quantitative method. The sample used in this study were employees who worked at RSUD Dr. Soekardjo Tasikmalaya. Data processing was performed using Multiple Linear Regression, Correlation Analysis, and hypothesis testing. Based on the results of the study, it can be concluded that there is an influence between skills on the performance of the employees of Dr. Soekardjo Tasikmalaya and there is an influence between the provision of incentives on employee performance at Dr. Soekardjo Tasikmalaya. There is a simultaneous influence between skills and the provision of incentives on employee performance at Dr. Soekardjo Tasikmalaya
SENSORY RESPONSE OF WET NOODLES WITH SUBSTITUTION OF SUPER RED DRAGON FRUIT (Hylocereus costaricensis) PEEL
Authors: Yuliani Yuliani , Parlindungan Alberth , Marwati Marwati , Candra Krishna Purnawan
Published: August 2021

Innovation in increasing the wet noodles performance was conducted by substituting super red dragon fruit (pitaya) peel (DFP) puree to get DFP wet noodles that have red color and rich in fiber. Wheat flour (WF) was substituted with super red DFP puree in a portion of 0-20%. A single factor experiment arranged in Completely Randomized Design with four replications for each treatment was conducted. Hedonic and quality hedonic properties for color, aroma, texture, and taste were determined. Data were analyzed by the Friedman test continued by the Wilcoxon Sign Rank test. The DFP wet noodle with DFP puree substitution of 10% gave the best hedonic sensory response for overall acceptability with the properties of like for color, texture, and taste, but rather like for aroma. The DFP wet noodles have hedonic quality properties of a light reddish color, slightly scented of dragon fruit peel with a texture of rather hard and rather taste of DFP. The fiber content of the DFP wet noodles was 0.135 ± 0.003%.
Water-Oil Displacement in Shale: New Insights from a Comparative Study Integrating Imbibition Tests and Multiscale Imaging
Authors: Peng Sheng , Shevchenko Pavel , Periwal Priyanka , Reed Robert M.
Published: August 2021

Water-oil displacement is an important process that occurs in a shale matrix after hydraulic fracturing and in water-based enhanced oil recovery. Current understanding of this displacement process is limited because of the complicated pore structure and surface properties in shale. In this work, this process and its controlling factors are investigated through a comparative study of three shale samples that have different types of pore systems and wettability. An integrated method of imbibition and multiscale imaging was applied, and a modified oleic tracer that can better represent oil flow was used in imbibition testing and micro-computed tomography (CT) imaging. Scanning electron microscope (SEM) pore characterization was then performed under high magnification with guidance from the micro-CT images showing the changes caused by oil or water imbibition. New insights were obtained on the importance of both wettability and pore size effect on oil recovery and the distribution of residual oil after water-oil displacement. Connectivity of pores with different wettability is also discussed based on 3D analysis and SEM pore characterization. Collectively, these new findings improve the understanding of the complicated process of water-oil displacement and the role of influencing factors. Important implications for improved oil recovery strategy in shale are discussed for different types of reservoir rocks. The integrated imaging and imbibition technique provides a new path for further investigation of improved oil recovery in shale.
Improved Well-Control Progressive Optimization with Generalized Barycentric Coordinates and Manifold Mapping
Authors: Echeverría Ciaurri D. , Moreno Beltrán G. A. , Camacho Navarro J. , Prada Mejía J. A.
Published: August 2021

Well-control management is nowadays frequently approached by means of mathematical optimization. However, in many practical situations the optimization algorithms used are still computationally expensive. In this paper, we present progressive optimization (PO), a simulator-nonintrusive four-stage methodology to accelerate optimal search substantially in well-control applications.

The first stage of PO comprises a global exploration of the search space using design of experiments (DOEs). Thereafter, in the second stage, a fast-to-evaluate proxy model is constructed with the points considered in the experimental design. This proxy is based on generalized barycentric coordinates (GBCs), a generalization of the concept of barycentric coordinates used within a triangle. GBCs can be especially suited to problems in which nonlinearities are not strong, as is the case often for well-control optimization. This fact is supported by the good performance in these types of optimization problems of techniques that rely strongly on linearity assumptions, such as trajectory piecewise linearization, a procedure that is not always applicable due to its simulator-intrusive nature. In the third stage, the precision of the proxy model is iteratively improved and the enhanced surrogate model is reoptimized by means of manifold mapping (MM), a method that combines models with different levels of accuracy. MM has solid theoretical foundations and leads to efficient optimization schemes in multiple engineering disciplines. The final and fourth stage aims at additional improvement, resorting to direct optimization of the best solution from the previous stages. Nonlinear (operational) constraints are handled in PO with the filter method. The optimal search may be finalized earlier than at the fourth stage whenever the solution obtained is of satisfactory quality.

PO is tested on two waterflooding problems built upon a synthetic model previously studied in well-control optimization literature. In these problems, which have 120 and 40 well controls and include nonlinear constraints, we observe for PO reductions in computational cost, for solutions of comparable quality, of approximately 30% and 50% with respect to Hooke-Jeeves direct search (HJDS), which, in turn, outperforms particle swarm optimization (PSO). HJDS and PSO are simulator-nonintrusive algorithms that usually perform well in optimization for oilfield operations.

The novel concepts of GBC and MM within the framework of the PO paradigm can be extremely helpful for practitioners to efficiently deal with optimized well-control management. Savings of 50% in computing cost may be translated in practice into days of computations for just a single field and optimization run.
Would High-Dose Corticosteroid Adjuvant To Multimodal Cocktail Periarticular Injection Contribute To Prolonged Pain Control and Better Recovery After Total Knee Arthroplasty?: Study Protocol for a Double-Blinded, Randomized, and Placebo-Controlled Trial
Authors: Zhong Chengfan , He Rong , Lu Xiaomin , Zhong Lilun , Lin Ding-Kun , Liu Jun , Da Guo
Published: August 2021

Background

Enhanced recovery after total knee arthroplasty (TKA) has been suggested to enhance postoperative recovery. The use of multimodal cocktail periarticular injection (MCPI) to control the pain of TKA has gained wide acceptance. MCPI containing corticosteroids is believed to be an effective solution because of its local anti-inflammatory effects and ability to reduce the local stress response postoperatively. However, there is conflicting evidence about its benefits. This trial aims to compare MCPI containing a high dose of corticosteroid, MCPI containing anormal dose of corticosteroid, and MCPI without a corticosteroid during TKA to assess the effectiveness of MCPI containing corticosteroid in postoperative pain relief, functional improvement, rescue analgesia and side effects. This will provide evidence regarding the effectiveness of high-dose corticosteroids on prolonged pain control and better recovery after total knee arthroplasty.
Methods/design

This trial is a double-blinded randomized, placebo-controlled study. A total of 234 patients will be randomized into 3 groups to receive a high dose of betamethasone MCPI (group H), a normal dose of betamethasone MCPI (group N), and a nonbetamethasone MCPI (group C). the following indexes will be recorded and analyzed: knee pain at rest and bending at 90° at 6 h, 24 h, 48 h, 72 h, 5 days, 14 days, and 30 days after surgery; 1-minute walking ability and circumference around patella at 2, 4, 7, 14, and 30 days after surgery; HSS score at 14 and 30 days after surgery; C-reactive protein and blood sedimentation as well as blood sugar at 2, 4, 7, 14, 30 days after surgery; additional morphine analgesics consumption; and side effects.
Discussion

The results from this study will provide clinical evidence on the effectiveness of MCPI-containing corticosteroids in postoperative pain relief, functional improvement, rescue analgesia, and side effects as well as evidence on the efficacy of high-dose corticosteroids for leading to prolonged pain control and better recovery after TKA.
Trial registration

Chinese Clinical Trial Registry ChiCTR2000038671. Registered on 27 September 2020
Shaping Lightwaves in Time and Frequency for Optical Fiber Communication
Authors: Cho Junho , Chen Xi , Raybon Greg , Che Di , Burrows Ellsworth , Olsson Samuel , Tkach Robert
Published: August 2021

In optical communications, sphere shaping is used to limit the energy of lightwaves to within a certain value over a period. This minimizes the energy required to contain information, allowing the rate of information transmission to approach the theoretical limit if the transmission medium is linear. In optical fiber, however, the sphere shaping induces Kerr nonlinearity in a peculiar way that makes analysis of transmission performance difficult, potentially lowering the communications capacity. In this article, we show how the impact of sphere shaping on Kerr nonlinearity varies with the chromatic dispersion and the structure of shaped lightwaves in time and frequency, and give insights into why the structure matters. As a practical consequence, by optimally controlling the structure of lightwaves in time and frequency, it is experimentally demonstrated that the information rate can be increased by up to 25% in low-dispersion channels on a 2824-km dispersion-managed wavelength-division multiplexed optical fiber link.
Large-Scale Modeling of Solum Thickness Based on the Local Topographic Attributes of Ground and Bedrock Surfaces
Authors: Khanifar Javad , Khademalrasoul Ataallah
Published: August 2021

This study was aimed to address the importance of neighborhood scale and using bedrock topography in the soil-landscape modeling in a low-relief large region. For this study, local topographic attributes (slopes and curvatures) of the ground surface (DTM) and bedrock surface (DBM) were derived at five different neighborhood sizes (3×3, 9×9, 15×15, 21×21, and 27×27). Afterward, the topographic attributes were used for multivariate adaptive regression splines (MARS) modeling of solum thickness. The results demonstrate that there are statistical differences among DTM and DBM morphometric variables and their correlation to solum thickness. The MARS analyses revealed that the neighborhood scale could remarkably affect the soil–landscape modeling. We developed a powerful MARS model for predicting soil thickness relying on the multi-scale geomorphometric analysis (R2= 83%; RMSE= 12.70 cm). The MARS fitted model based on DBM topographic attributes calculated at a neighborhood scale of 9×9 has the highest accuracy in the prediction of solum thickness compared to other DBM models (R2 = 61%; RMSE = 19cm). This study suggests that bedrock topography can be potentially utilized in soil-related research, but this idea still needs further investigations.