bluuebunny/crossref_metadata_2025_split huggingface dataset:
Circadian regulation of muscle growth independent of locomotor activity
Authors: Kelu Jeffrey J. , Pipalia Tapan G. , Hughes Simon M. 
Published: November 2020

Significance
A long-standing question, particularly in physiotherapy and sports medicine, is whether time of day affects muscle metabolism and hence growth, either intrinsically or in response to exercise or nutrition. Answers would help to identify the best time of day to exercise, build muscle, and prevent aging- or disease-related sarcopenia. Here, we address this question in live zebrafish myotome in vivo, without interference from other circadian oscillations such as locomotor activity and food intake. We show that active muscle anabolizes more in the day and grows faster, while catabolizing more at night and growing slower. Such day/night differences remain in inactive muscle but disappear after clock disruption. We conclude that muscles display circadian differences in growth independent of activity and feeding.
Local conformal autoencoder for standardized data coordinates
Authors: Peterfreund Erez , Lindenbaum Ofir , Dietrich Felix , Bertalan Tom , Gavish Matan , Kevrekidis Ioannis G. , Coifman Ronald R. 
Published: November 2020

Significance
A fundamental issue in empirical science is the ability to calibrate between different types of measurements/observations of the same phenomenon. This naturally suggests the selection of canonical variables, in the spirit of principal components, to enable matching/calibration among different observation modalities/instruments. We develop a method for extracting standardized, nonlinear, intrinsic coordinates from measured data, leading to a generalized isometric embedding of the observations. This is achieved through a local burst data acquisition strategy that allows us to capture the local z-scored structure. We implement this method using a local conformal autoencoder architecture and illustrate it computationally. The proposed embedding is fast, parallelizable, easy to implement using existing open-source neural network implementations and exhibits surprising interpolation and extrapolation capabilities.
Bumblebees perceive the spatial layout of their environment in relation to their body size and form to minimize inflight collisions
Authors: Ravi Sridhar , Siesenop Tim , Bertrand Olivier , Li Liang , Doussot Charlotte , Warren William H. , Combes Stacey A. , Egelhaaf Martin 
Published: November 2020

Significance
Like many other animals, including humans, insects frequently move through densely cluttered environments to perform activities critical for their survival, such as foraging. Vertebrates avoid collisions by perceiving their surroundings in relation to their body size and form, but it is unknown whether insects, with much smaller brains, possess such skills. We discovered that flying bumblebees judge the gap between obstacles relative to their wingspan and reorient themselves to fly sideways through tight spaces. Our findings suggest that bees too evaluate the affordance of their surroundings and account for their own size and form to safely navigate through complex environments. This facet of insect flight poses questions about the neural requisites for perception of self-size in animals.
Izhma Komi in Western Siberia
Authors: Kashkin Egor , Muravyev Nikita 
Published: November 2020

Abstract
This paper considers contact-induced change in Izhma Komi
subdialects spoken in Western Siberia. We focus on the interaction of Izhma
Komi, first, with Russian and, second, with the indigenous Siberian
languages (Nenets and to a lesser extent Khanty). The main emphasis is on
the phenomena of pattern borrowing at various language levels, which mostly
remained beyond previous studies. For instance, these include the borrowing of some phonotactic patterns, the copying of polysemy patterns, and changes in the
properties of some grammatical constructions. We discuss how in each case
the degree of contact-induced change depends on the sociolinguistic
situation.
Investigating bottom-quark Yukawa interaction at Higgs factory *
Authors: Bi Qi , Chai Kangyu , Gao Jun , Liu Yiming , Zhang Hao 
Published: November 2020

Abstract
Measuring the fermion Yukawa coupling constants is important for understanding the origin of the fermion masses and their relationship with spontaneously electroweak symmetry breaking. In contrast, some new physics (NP) models change the Lorentz structure of the Yukawa interactions between standard model (SM) fermions and the SM-like Higgs boson, even in their decoupling limit. Thus, the precise measurement of the fermion Yukawa interactions is a powerful tool of NP searching in the decoupling limit. In this work, we show the possibility of investigating the Lorentz structure of the bottom-quark Yukawa interaction with the 125 GeV SM-like Higgs boson for future

colliders.
Implications of axion-like particles from the Fermi-LAT and H.E.S.S. observations of PG 1553+113 and PKS 2155−304 *
Authors: Guo Jun-Guang , Li Hai-Jun , Bi Xiao-Jun , Lin Su-Jie , Yin Peng-Fei 
Published: November 2020

Abstract
We investigate the axion-like particle (ALP)-photon oscillation effect in the high-energy

-ray spectra of PG 1553+113 and PKS 2155−304 measured by Fermi-LAT and H.E.S.S. The choice of extragalactic background light (EBL) model, which induces the attenuation effect in observed

-ray spectra, affects the ALP implications. For the ordinary EBL model that prefers a null hypothesis, we set constraints on the ALP-photon coupling constant at 95% C.L. as

for the ALP mass

neV. We also consider the CIBER observation of the cosmic infrared radiation, which shows an excess at wavelengths of

m after the substraction of foregrounds. High-energy gamma-rays from extragalactic sources at high redshifts would suffer from a more significant attenuation effect caused by this excess. In this case, we find that the ALP-photon oscillation would improve the fit to the observed spectra of PKS 2155−304 and PG 1553+113 and find a favored parameter region at 95% C.L..
Study of underwater topography change with measurement and analysis
Authors: Iwakami Satoshi , Tamega Masahiko , Sanada Masahide , Mohri Michiaki , Iwakami Yoshitaka , Jimbo Shuji , Watanabe Masaji 
Published: November 2020

Abstract
Techniques developed in previous studies were applied to positional data and depth data concerning underwater topography of a reservoir. The Gauss-Krüger projection was applied to horizontal coordinates of positional data. The horizontal coordinates and the vertical coordinate yielded a curve in an underwater topography. A surface containing the curve was obtained by a fixed point iteration. Numerical results for two time periods were compared.
Analysis of User Satisfaction on Corona.Jakarta.go.id Website: Use Webqual Method 4.0
Authors: Titiani Fakihotun , Erni  , Riana Dwiza , Budihartanti Cahyani , Rahmatullah Syaifur , Tutupoly Taransa Agasya 
Published: November 2020

Abstract
The Corona.jakarta.go.id website is a website owned by the Jakarta city government as a provider of information related to Covid-19, the website contains data on the distribution of Covid-19 throughout Indonesia and specifically Jakarta, as well as appeals to the public and other information for overcoming Covid-19 in Indonesia. Indonesia is experiencing a pandemic Corona Virus or Covid-19, many websites are built as a form of government contribution to the response of Covid-19. As one of the websites which is a place for information related to Covid-19, of course many people access the website, with the information presented on the website, the website user satisfaction research is carried out by distributing questionnaires to the public. From the description of the problem, a Corona.jakarta.go.id website quality measurement is carried out using the Webqual 4.0 method whose aim is to find out the Webqual variables that affect user satisfaction, from the Webqual 4.0 indicators what needs to be improved for and provide recommendations improvement. Based on the results of a survey of 109 respondents obtained the value of R square for the variable user satisfaction by 0.448 or 44.8% through linear relationships, while the value of the remaining 0.552 or 55.2%, influenced by other variables outside this study.
Method for Calculating Children’s Parenting and Self-Concept towards Student’s Environmental Behaviour Using Correlational Approach
Authors: Sarkawi Dahlia , Lawu Suparman Hi , Oktaviani Anggi , Priadi Agus , Yuniasih Idah 
Published: November 2020

Abstract
The purpose of this study is to find the correlation among three variables namely children’s parenting and self-concept to increase students’ environmental behaviour on college students of Office Administration and Business Administration of Universitas Bina Sarana Informatika in Central Jakarta. Research and Development is chosen by involving 120 college students. The data were collected through participant observation using questionnaires. The data searched by the researcher using correlational approach with survey technique. The research findings showed that (1) the correlation between children’s parenting and students’ environment behaviour is positive and significant with the result of correlation is 0,327, (2) the correlation between self-concept and students’ environmental behaviour is positive and significant with the result of correlation is 0,360, and (3) the correlation both children’s parenting and self-concept is positive and significant with the result of contributed 0,253 towards environmental behaviour.
Influence Of Overload Information About COVID-19 Pandemic On Internet For Psychological Illnesses And Behavioral Intentions To Continue Searching For Information
Authors: Fadhilah N M , Fauziah S , Riana D , Eko A , Yulianto A , Sulthon B M 
Published: November 2020

Abstract
Information about COVID-19 is now very easily accessed on the Internet, even too much. The phenomenon of excessive information obtained can also be linked to psychological illnesses and obtain information retrieval. this article conducts research about information overload about the psychology of information seekers and their protection. The study used the TAM method with SEM tools with 380 respondents. The results of the study show that excessive online information about COVID-19 has a positive influence on the psyche and affects the relationship of information seekers not to continue the search results.
The Application of Power Business Intelligence in Analyzing the Availability of Rental Units
Authors: Andriansyah D , Nulhakim L 
Published: November 2020

Abstract
The availability of rental units in the field of vehicle rental services is the most important thing that must be given special attention by company management in order to provide good service to customers related to unit information. Sometimes unit information available in the field is different from what is recorded in the system, resulting in misinformation. For example, a unit that is supposed to be ready for rental, but in the system status the unit has not changed from its last status which causes the unit cannot be ordered by the customer. Errors are still found in the recording of repair units so that it needs to be adjusted to the status of the unit so that the unit can be rented immediately. Besides the lack of supervision of employees who record or update the status of the unit in the system makes the data pull system is not the same as the existing manual data. To reduce these errors, management requests that information on the availability of units be displayed in the form of a dashboard so that they can display the status of units from various categories simultaneously. This study uses literature study and experimental methods which consist of four stages, namely collecting data, pre-processing data, visualizing, and analyzing data. The purpose of this research is to build a dashboard using Power Business Intelligence (BI) that can display rental unit availability information from various categories based on certain parameters.
TAM Method and Acceptance of COVID-19 Website Users in Indonesia
Authors: Kurniasih A , Santoso A K , Riana D , Kadafi A R , Dari W , Husin A I 
Published: November 2020

Abstract
The world facing a hard time during this time since the presence of coronavirus (COVID-19). Public can monitor and update the information related the virus and its spread during this time through the internet, Indonesian Mobile website. The purpose of this research is to analyze the factors that influence people’s acceptance of the website the using the Technology Acceptance Model (TAM) method. Five constructs of the TAM research model used are Perceived Usefulness, Perceived Ease of Use, Attitude Towards Use, Intentions of Use Behavior and Use of Actual Systems. Data obtained using an online questionnaire from Google Form. Valid questionnaire data is processed using the SmartPLS 3 application using three structural analysis models, namely external model analysis, inner model analysis, and hypothesis testing. The results showed that of all the hypotheses studied and obtained in each hypothesis can be stated significantly and proven acceptable.
Detecting Alzheimer’s Disease by The Decision Tree Methods Based On Particle Swarm Optimization
Authors: Saputra R A , Agustina C , Puspitasari D , Ramanda R , Warjiyono  , Pribadi D , Lisnawanty  , Indriani K 
Published: November 2020

Abstract
In this study aims to determine the classification of Alzheimer’s disease, this disease is a dangerous disease that can eliminate memory loss and can even result in a loss of ability to remember. For this reason, early detection of this disease is needed so that it can prepare for medical treatment. In this study the proposed method is to compare several decision tree methods with feature or attribute selection using the Particle Swarm Optimization (PSO) algorithm with the Alzheimer OASIS 2 dataset: Longitudinal Data from kaggle.com. The results of experiments with ten-fold cross validation, by testing the decision tree algorithm before the feature or attribute selection is performed, the highest accuracy value is obtained from the random forest algorithm with a value of 91.15%. The feature selection process is carried out using the PSO algorithm and the experiment is repeated using the Decision tree, the PSO-based random forest algorithm has the highest accuracy value of 93.56% with a kappa value of 0.884. Feature or attribute selection using the PSO algorithm is proven to be able to improve the accuracy of the decision tree algorithm, and is included in the algorithm with a very good range of values.
The Implementation of the MFEP (Multi Factor Evaluation Process) Method In Determining the Learning Model
Authors: Warnilah Ai Ilah , Purnia Dini Silvi , Adiwisastra Miftah Farid , Sutisna Herlan , Ratningsih  , Ardianto Rian 
Published: November 2020

Abstract
The success of every generation of children is the hope of the success of the education world. The role of educators especially teachers has an important role in achieving the success of their students then a teacher must have a strategy in developing the learning system. A system approach is needed by using specific learning models, in order to help the teacher design the learning system. With the selection of the right learning model is one of the factors that support the success of the learning system. One factor of student achievement is less than the maximum is the application of learning models that are not appropriate, the selection of learning models still using manual systems makes the learning models applied less precise and appropriate. The purpose of this study is to determine the decision support system in determining learning models including cooperative learning models, problem based learning models, contextual learning models, Direct learning models, with the aim to assist teachers in determining the appropriate learning model to be applied in teaching and learning activities. The method applied is using the MFEP (Multi Factor Evaluation Process) method., by determining and giving subjective / intuitive assessments on factors / criteria that are very influential on indicators / alternatives and ranking systems to find out the alternative with the highest value. The results of this study cooperative learning models are highly recommended in the learning process in determining the level of success of students with a value of 6.18
Dynamic Model for Determining Disaster Evacuation Locations with Game Theory
Authors: Safii M. , Efendi Syahril , Zarlis Muhammad , Mawengkang Herman 
Published: November 2020

Abstract
Disaster management can be grouped into three stages with several activities that can be carried out starting from pre-disaster, during emergency response and post-disaster. In the pre-disaster stage one of which is mitigation, which is a series of efforts to reduce disaster risk, both through physical development and awareness raising and capacity to face the threat of disaster. In mitigation one important factor is about evacuation. Evacuation locations in disaster transportation management are urgently needed for an effective evacuation process. Evacuation location determination is a benchmark in handling evacuation that can minimize the impact of losses from the disaster. To determine the evacuation location dynamically using game theory can solve the problem by providing several alternative locations by showing the dominant factor in the variables in the selection of the evacuation site. Game theory will use pure and mixed strategies to provide the most optimum choice of criteria. With this method will produce a decision support system to determine the optimal evacuation location or safe area in disaster mitigation
Similarity Approach Based to Customer Behavior for Trade Business Metrics
Authors: Elveny Marischa , Nasution Mahyuddin KM , Zarlis Muhammad , Zamzami Elviawaty Muisa 
Published: November 2020

Abstract
Data mining is a process of mining data in very large amounts of data. The purpose of this data mining is to extract and identify data for the sake of certain information related to a large database. To find user behavior based on competing merchants, the similarity of several objects is needed. Similarity involves the process of characterizing each object or describing in detail the features of the object. In the process it produces the naming and weighting of the characteristics of objects so as to provide a way to measure their similarity. The way is determined by placing a comparison of what is the same and what is different from the two objects. The results achieved in the form of similarity methods to look for customer behavior in a competitive merchant. The purpose of this study is set out in a simple knowledge base in the form of information to find relationships and models. With this research it is expected to produce new standard models and paradigms that can be used in accordance with the needs of industry and society.
Analysis of Seismic Hazard Prediction Using Non Parametric Conic Multivariate Adaptive Regression Splines (C-Mars) Methods
Authors: Priyanto Dadang , Zarlis Muhammad , Mawengkang Herman , Efendi Syahril 
Published: November 2020

Abstract
The data mining process requires a data set that can be used in determining a number of specific patterns to gain new knowledge. Large data sets (Big data) require special methods to get effective results. Included in this study are using big data related to the earthquake in Lombok. Earthquake research, especially in Lombok, is needed because Lombok is on three active plates in Indonesia, so that the danger of earthquake damage can be minimized. Earthquake data obtained from the Geophysical Station (BMKG) of Mataram has different characteristics and is complex, an appropriate method is needed, namely by detecting a non-parametric method with the Multivariate Adaptive Regression Spline (MARS). The use of the backward stepwise algorithm with the Conical Quadratic Programming (CQP) framework of MARS, referred to as CMARS (Conic Multivariate Adaptive Regression Splines), is used for optimizing the results. The conclusions of this study are 1. A mathematical model with a total of 12 basis functions (BF) has contributed to the prediction analysis of the PGA dependent variable. 2. Contributions of the influence of independent variables on the PGA value are the epicenter distance (R

e

pi) of 100% and the Magnitude (Mw) of 31.08608%, while the temperature of the incident location (SUHU) of 5.48525% and depth (Depth) of 3,52988%. 3. Acquired areas that have earthquake hazard levels in the order of the most vulnerable are Malaka, Genggelang, Tegal Maja, Senggigi and Mangsit.
An Application of Mask Detector For Prevent Covid-19 in Public Services Area
Authors: Henderi  , Rafika Ageng Setiani , Spits Warnar Harco Leslie Hendric , Saputra Meldi Anggara 
Published: November 2020

Abstract
Coronavirus disease (COVID-19) that has entered Indonesia made the government impose large-scale social restrictions to reduce the spread of the coronavirus. As the increase in patients confirmed positive, the government continues to appeal and ask the Indonesian to use masks. Whether it is a healthy people or those who are sick. This appeal is in line with the recommendations of the World Health Organization (WHO) in preventing the spread of COVID-19. Therefore it is necessary to develop tools for monitor people who have not used masks in public service areas in real-time. We develop an application of mask detection using a camera that functions as photo and video input and connected to Speed Maix Bit microprocessor to process data and display it to the LCD. We purposed the tools to solve the problems regarding people who were not used masks or not immediately to minimize the spread of COVID-19. Our final experiment demonstrates that the application highly detects people using masks or not in the public area. This study contributed to the conception, design system, and rules-based for application of mask detector to prevent Covid-19.
High Accuracy in Forex Predictions Using the Neural Network Method Based on Particle Swarm Optimization
Authors: Nuraeni Nia , Astuti Puji , Irnawati Oky , Darwati Ida , Harmoko Danang Dwi 
Published: November 2020

Abstract
In forex trading, trader has to predict the risk in forex transaction and how to gain or increase the profits based on analysis. The purpose of this study is to predict the value of the USD against the IDR by comparing the neural network method with the neural network method based on Particle Swarm Optimization (PSO) to find out which level of accuracy is higher. This method was chosen by the author after reading several previous studies using PSO-based Neural Networks showing a higher level of accuracy compared to using Neural Networks without PSO-based. From the results of the study it was found that predictions using Neural Networks strengthened with PSO resulted in very high accuracy.