bluuebunny/crossref_metadata_2025 huggingface dataset:
From Rate Regulation to Financial Control: Accounting and Public Policy at the Interstate Commerce Commission, 1887–1933
Authors: Miranti, Jr. Paul J. , Collier Deirdre M. , Palmon Dan
Published: September 2023

This paper focuses on the Interstate Commerce Commission’s (ICC’s) application of accounting to achieve public policy goals for the U.S. railroad industry. The ICC began in 1887 with a mandate to ensure competition in the transportation industry, with rate oversight as one tool. During the Progressive Era, from 1901 to 1921, the ICC used accounting to ensure rate equity; a second implicit goal was to reduce the rail industry’s informational asymmetries to investors, morphing over time to ensuring a reasonable return to investors. In the 1920s, the ICC used accounting to reduce securities speculation, facilitate regional rail consolidation, and govern industry finance. This accounting-based model of regulation continued until the Great Depression of the 1930s, when new economic circumstances called into question the ICC’s ability to serve the most pressing public policy concerns. The technologies used by the ICC, however, continued to be exploited by other regulatory bodies.
Hyperparameter Tunning and Feature Selection Methods for Malware Detection
Authors: KAVALCI YILMAZ Esra , BAKIR Halit
Published: September 2023

Smartphones have started to take an essential place in every aspect of our lives with the developing technology. All kinds of transactions, from daily routine work to business meetings, payments, and personal transactions, started to be done via smartphones. Therefore, there is a significant amount of very important user information stored in these devices which makes them a target for malware developers. For these reasons, machine learning (ML) methods have been used to detect malicious software on android devices quickly and reliably. In this study, a machine learning-based Android malware detection system has been developed, optimized, and tested. To this end, firstly, the data in the dataset has been balanced with 3 different methods namely SMOTE, SMOTETomek and ClusterCentroids. Afterward, the obtained results have been tried to be optimized by using different feature selection approaches including mRMR, Mutual Information, Select From Model, and Select k Best. Finally, the most two successful methods from the five tested ML algorithms (i.e. RF, SVM, LR, XGBoost, and ETC) have been tuned using GridSearch, Random Search, and Bayesian Optimization algorithms in order to investigate the effects of hyperparameter tuning on the performance of ML algorithms.
A review: Usage of Different Technologies of Electrical Energy Storage System Coupled Hybrid Power System
Authors: SAİB Samia , BAYINDIR Ramazan , VADİ Seyfettin
Published: September 2023

Energy storage system is becoming crucial in the electric power system. It can response to economic, environmental, geopolitical and technological considerations. Energy storage system has a great role to covering energy for power electric system as renewable energy source, improves energy efficiency and promotes the integration of variable renewable energies, brings security and flexibility to networks, control and regulation. Several studies have been focused on different energy storage technologies connected to various hybrid energy systems to supply power to the grid /load. Almost of these recent papers have been mentioned the performance and the utility of storage system in term of management, control, cost, lifetime. For this reason, an overview is offered in this paper including hybrid energy system and using various energy storage technologies to generate electric power in the aim to clarify the use of diverse storage technologies from several sides as energy management strategy, control and optimization problems. A comparative study is made to demonstrate more the analysis of this paper.
The Complicated Relationship between Cancer Disease and Viral Infection: Facts and Understanding
Authors: BAR Hassan
Published: September 2023

Environmental, lifestyle, host-related, infectious, and genetic factors have all been connected to the oncogenic process. Knowing what causes cancer and what variables increase one's risk is crucial for targeting screening and prevention efforts towards high-risk populations. Infectious agents have been identified as a significant preventable risk factor for cancer among various other risk factors. Among this cohort, viruses are the predominant etiological agents implicated in the pathogenesis of neoplastic disorders in humans.
Physiotherapy and Cardiopulmonary Rehabilitation Approaches in SARS-CoV-2 Infection
Authors: Y Artik
Published: September 2023

An arising of infectious outbreaks lately December of 2019 has been reported as pneumonia of unknown cause appeared in Wuhan city, China which called SARS-CoV-2. Globally, 12 July 2023, there have been 767.972.961 confirmed cases of COVID-19, including 6.950.655 deaths, reported by WHO. As of 8 July 2023, a total of 13.474.185.140 vaccine doses have been administered. In 2013, the number of people has been died from cardiovascular disease more than 17.3 million and representing an increase from 1990 of 40.8%. Evaluating the effects on cardiopulmonary physiology has an important place among the parameters of the COVID-19 pandemic affecting public health. For this reason, we evaluated physiotherapy and rehabilitation approaches as a for CBRN threats and disaster risk management policies by associating cardiopulmonary physiology with the effects of the COVID-19 (SARS-CoV-2) pandemic
The Influence of Psychophysical Preparation of Pregnant Women on the Outcome of Childbirth and Postpartum Recovery
Authors: Geko Nura , Imamović Fahira , Hadžimuratović Emina , Ovčina Amer , Marjanović Marijan , Marušić Jasmina , Tomić Darko , Đido Vedran
Published: September 2023

The psychophysical preparation program for pregnant women includes physical exercises and theoretical lectures aimed at preparing the pregnant woman for childbirth and that the benefits far outweigh the risks. Exercise is an essential element of pregnancy, and OB-GYNs and other obstetric care providers should encourage their patients to continue or begin exercise. The aim of this work is to understand the impact of psychophysical preparation of pregnant women on health during and after pregnancy, birth outcomes and postpartum recovery. Twenty scientific research papers/articles including 5517 respondents were reviewed, based on databases: Web of Science, EBSCO, Scopus, Medline, PubMed, ScienceDirect, Google Scholar, and others. Works published from 2017-2022 were reviewed. The results of this study show that pregnant women who attended the program of psychophysical preparation for childbirth had a chance to experience childbirth in a more beautiful light, to be prepared, so that they would go to the maternity hospital with less fear, how to use breathing techniques during childbirth, and how to have the easiest and most beautiful childbirth without the use of drugs and interventions. Pregnant women had significantly more positive outcomes of childbirth as well as postpartum recovery and mental health. Psychological support and education have positive outcomes on the mental health of pregnant women because they reduce fear of the unknown and reduce the risk of postpartum depression. Higher rates of intact perineum, reduction of episiotomy and less damage of perineal tears are recorded. The preparation itself significantly affects the outcome of the test subjects’ births, where vaginal births are much more common, and the rate of instrumental methods of birth and caesarean section is reduced. A positive outcome was recorded during postpartum recovery.
Features of measurement uncertainty evaluation during calibration of digital ohmmeters
Authors: Zakharov Igor , Semenikhin Valerii , Zakharov Oleksandr , Shevchenko Svitlana
Published: September 2023

The scheme for transferring the size of the unit of resistance during the calibration of digital ohmmeters at direct current is considered. The procedure for the measurement uncertainty evaluation is described: recording the measurement model and its refinement, evaluation of input and measured values, evaluation of standard uncertainties of the input and measured values, evaluation of the expanded uncertainty. The refined model includes the dependence of the resistance of the reference resistor on temperature and a correction to the drift of the resistance value of the reference resistor since its last calibration. To evaluate the expanded uncertainty, the kurtosis method was used. An uncertainty budget has been made, including the kurtosis of input and measured values. The use of the Excel package makes it possible to implement, based on this budget, a program for automation of measurement uncertainty calculations. An example of the measurement uncertainty evaluation during the calibration of a digital ohmmeter of type 2318 at a point of 1 mOhm using an electrical resistance coil R310 with an accuracy class of 0.01 is considered. The influence of nonlinearity of the measurement model on the estimates of the numerical value of the measurand and its combined standard uncertainty is studied. To verify the results, the distribution law of the measurand was modelled by the Monte Carlo method. An algorithm for determining the expanded uncertainty using the NIST Uncertainty Machine web application for the missing confidence level of 0.9545 is proposed. The comparison of the results of the measurement uncertainty evaluation by the kurtosis and Monte Carlo methods has shown their good agreement.
Validity of instruments for assessment of scientific literacy and critical thinking of students based on multiple intelligence in acid-base material
Authors: Rahayu Wigati Muji , M. Noer Asmadi , Anwar Lenny
Published: September 2023

This research aims to create an assessment tool to evaluate students' scientific reading comprehension and critical thinking ability based on multiple intelligences on acid-base materials and to determine the validity of this study rating tool. The research methodology uses the Borg and Gal research and development model. This research phase continues into the development phase. The assessment instrument developed in this study consists of sixteen items of description test questions that refer to science literacy indicators consisting of four indicators are science as a body of knowledge; science as a way of investigation; science as a way of thinking; and the interaction of science, technology and society. Then the assessment instrument refers to critical thinking which consists of five indicators: providing a simple explanation, building basic skills, inference, providing further explanation, and developing strategies and tactics. This assessment instrument is based on multiple intelligences consisting of five types of intelligence: logical-mathematical, verbal-linguistic, visual-spatial, rhythmic-musical, and naturalistic. The validation of this assessment instrument is carried out by five validators. Validation by material experts is measured using the Guttman scale. Validity according to experts, namely aspects of material, language, and construction, obtained on average expert validation ranges from 90,33 – 94,7% and 16 questions are declared valid. Assessment instruments have been developed to be useful as a measure of a student's creative thinking ability.
Tensor products of infinite dimensional modules in the BGG category of a quantized simple Lie algebra of type ADE
Authors: WEİ Zhaoting
Published: September 2023

We consider the BGG category $\O$ of a quantized universal enveloping algebra $U_q(\mathfrak{g})$. It is well-known that $M\otimes N\in \O$ if $M$ or $N$ is finite dimensional. When $\mathfrak{g}$ is simple and of type ADE, we prove in this paper that $M\otimes N\notin \O$ if $M$ and $N$ are both infinite dimensional.
Research on information visualization for digital media design methodology based on big data technology
Authors: Zhang Ruhe , Zhao Lu , Wang Xiaochen
Published: September 2023

Information visualization is one of the important contents of digital media design, and they have a mutually complementary relationship. This paper combines the realistic background of the big data era and makes a more comprehensive introduction to the theoretical study of data visualization, including visual perception, visualization functions, judgment indexes, and principles. Secondly, by collecting the time series data, anomaly detection is carried out in the pre-processing stage, while the ring test is divided into a short-term ring and a long-term ring because the time series carries the property of time succession. Finally, anomaly detection is performed by its statistical features, which include distribution, moving average, exponential smoothing, standard deviation, and mean, whose values are equivalent to observing single-dimensional data when the sample data distribution is used as a perspective. The results show that through the comparative analysis of data visualization and traditional mathematical statistics, the correlation coefficients of information visualization for digital media design are between 0.8003 and 0.8129, while the traditional statistical methods for digital media design are only between 0.5038 and 0.5523. The information visualization proposed in this paper is better for digital media design to convey the art expressed by data and deeper mining analysis of spatiotemporal data.
Research on the physical training of athletes in ice and snow sports based on big data
Authors: Jiang Xiangzhi , Qu Xinyi
Published: September 2023

Through big data technology, we analyze the effect of functional fitness training on the physical quality of cross-country skiers and explore a scientific training method suitable for cross-country skiers. The MCDM-Apriori algorithm is proposed based on matrix compression, partitioning, and subsumption to solve the problem that the Apriori algorithm continuously generates the candidate set of intermediate processes during the operation and scans the original database several times, which causes huge consumption to the computer. The HDWA-Kmeans algorithm was used to analyze the effect of experimental training on the physical quality of athletes before and after the training, and the MCDM-Apriori algorithm was used to analyze the quality of functional movements to demonstrate the effect of functional training on the physical quality of cross-country skiers. In the physical quality comparison, the increase of 15 quality indexes in the experimental group was greater than that in the control group except for the push-up strength exhaustion, in which the increase of 49.91% and 54.05% in the experimental group of single-leg squat left and single-leg squat right, respectively. The increase in the quality of movement screening indexes compared with the experimental group, except for the deep squat, all other movements were increased to varying degrees, including a 20.77% increase in quadriceps rotation stability, while the increase in the control group was much worse than the experimental group. The results indicate that the functional training method and the training intensity and volume are consistent with and adapted to the physical training needs and physical characteristics of the athletes in the experimental group.
A study on the management of big data technology in financial decision-making of enterprise cloud accounting
Authors: Zhang Pei
Published: September 2023

Exploring the effectiveness of the application of big data technology in financial decision management of enterprise cloud accounting is to help better enterprises achieve economic growth and sustainable development. In this paper, a decision tree algorithm based on information gain and attribute dependency is jointly analyzed under big data technology using attribute dependency of rough set theory, attribute parsimony algorithm, and information gain of ID3 algorithm. The analysis of enterprise cloud accounting and financial decision-making is explained, including the process and content. The data analysis of financial decision management of WK Group, BL Real Estate, and LD Holdings is carried out using a decision tree algorithm. In terms of financing structure, debt financing mainly consists of long-term borrowings, short-term borrowings, and bonds payable, accounting for 66.06%, 21.18%, and 12.76%, respectively. In terms of gearing ratio, the average ratios of WK Group, BL Real Estate, and LD Holdings are 76.6%, 81.54%, and 80.05%, respectively. It shows that the decision tree algorithm based on information gain and attribute dependency can effectively perform corporate financial decision management analysis and visualize the company’s sustainable development strategy through the data.
Research on digital transformation innovation of the exhibition industry in the era of big data
Authors: Zhang Jieli
Published: September 2023

The changing world situation has put the requirement of digital transformation to the traditional exhibition industry. In this paper, we propose a big data-based exhibition exhibit recommendation system, which adopts the improved ALS collaborative filtering algorithm as an offline recommendation and combines window-based real-time TopN recommendation with dynamic perception-based exhibit recommendation as a real-time recommendation algorithm. Then, the big data-based recommendation system is applied to the digital transformation of the exhibition industry to analyze its impact on exhibition-viewing efficiency, exhibition service evaluation, and digital evaluation of exhibition projects. The impact assessment of digitally transformed exhibitions is 0.737 on average, which is 10.61% higher than that of exhibitions in traditional mode. The assessment of the degree of digital application is 0.778 on average, which is 12.59% higher than that of the exhibitions in the traditional mode. The average evaluation of exhibit specialization is 0.872, which is 17.69% higher than that of the traditional model. The research based on big data can provide references and case studies for the digital transformation of traditional exhibition enterprises and help the whole industry chain of the exhibition industry to carry out digital transformation.
Coupling research of Confucianism and Chinese philosophy based on data mining model
Authors: Ba Wenze
Published: September 2023

Confucianism is a cultural school guided by Confucianism, which is of great significance to the development of Chinese philosophy. This paper first introduces the steps of the outlier data mining algorithm of weighted deep forest, describes the construction method of weighted deep forest, divides the data into several different dimensions, and enters the random forest training in turn. Then outlier detection is introduced, dividing the data into classes with different densities and calculating their local isolation factors and outlier data. Then the algorithm’s performance is tested, and finally, the influence of Confucianism on Chinese philosophy and the main position of Confucian philosophy in the history of Chinese philosophy is analyzed. In terms of algorithm performance, the number T of different decision trees has an impact on AUC. When the number T of subtrees is 50, the AUC value starts to converge, and when the number T is 100 and 200, the AUC value of the algorithm is close to 1. In terms of the influence of Confucianism on Chinese philosophy, 75% of the people think that Confucianism Confucianism is precocious and has enriched the connotation and promoted the evolution of Chinese philosophy. Confucianism is an essential part of the Chinese philosophical calendar, advancing Chinese philosophy and moral culture.
Research on brand operation strategy of integrating traditional culture into the modern tourism industry based on big data analysis
Authors: Zhao Xiang , Wei Jinchan , Chen Jiaping
Published: September 2023

The rich traditional culture is an inexhaustible treasure trove of resources for the brand operation of the modern tourism industry. This paper proposes an improved method for the LDA model of text big data mining, optimizing the topic representation of LDA by introducing the Topic2Vec model, optimizing the probability calculation of generated words by combining the original Dilley distribution and Bernoulli distribution and optimizing the assignment of topic words in the Gibbs adoption process of LDA model with the help of likelihood function. Then, the big data of tourism brand design text, promotion, and cultural products are mined and analyzed based on the improved LFV-LDA model. In the design of tourism brands focusing on traditional culture, the frequency of the keyword “pattern” was the highest, accounting for 8.20%. In brand promotion, the most distributed channel from 2017 to 2021 was a live broadcast, and the growth rate in 2020 and 2021 reached 22.71% and 36.29%. Regarding traditional cultural and creative products, tourism cultural and creative products have maintained a high growth momentum from 2012 to 2021, with an average annual growth rate of 154.25%. Based on the analysis of big data, it can guide the operation of tourism industry brands in all aspects, such as design, promotion, and landing, and give full play to the value connotation of traditional culture.
The Fit of Constructivist Teaching Theory and Foreign Language Teaching Reform in the Background of the Internet Era
Authors: Deng Ting
Published: September 2023

The development of the fit between constructivist teaching theory and foreign language teaching is explored to improve learners’ language proficiency and comprehensive application skills effectively. This paper discusses a constructivist teaching model in the Internet era, using the fruit fly algorithm to optimize the kernel function of support vector machines and then constructing an FOA-SVM classification analysis model. The FOA-SVM model was used to analyze the fit data of the foreign language culture introduction teaching model based on constructivist teaching theory, including teaching principles and teaching practices. Regarding teaching principles, 55.69% of the students thought that the appropriateness principle was the best for the constructivist teaching theory to fit foreign language teaching. In terms of teaching practice, students’ learning attitude, learning initiative, learning ability, language ability, and application ability increased by 65.55%, 71.94%, 62.23%, 62.22%, and 78.42%, respectively. This shows that the integration and development of constructivist teaching theory and foreign language teaching should be based on the principle of appropriateness, and the use of a foreign language culture introduction mode of teaching is conducive to improving students’ learning attitudes and initiatives.
Heritage development of traditional culture in folk art education based on the decentralized Internet
Authors: Cui Yuting , Yu Xuanli
Published: September 2023

Folk art education is an important way to inherit and develop traditional culture. In this paper, the cascade propagation of typical decentralized Internet-social networks is modeled as a propagation dynamic graph model, and an enhanced graph-aware neural network is proposed through the analysis of the learning process of neural graph networks. A further recurrent graph-aware neural network is proposed for the characteristics of information dissemination in the decentralized Internet, and the transmission and development of traditional culture in folk art education are analyzed based on this network model. In folk art education, the most common type of traditional culture dissemination is ink painting, accounting for 20.32%, which is 6.91%, 12.35%, and 14.86% higher than other types, respectively. From 2014 to 2021, the percentage of Internet-based communication media increased from 12.47% to 24.78%, an increase of 12.31 percentage points. The analysis based on the decentralized Internet can accurately extract the characteristics of traditional culture integrated into folk art education, which helps to inherit further and promote the excellent traditional culture.
A study on the application of creative writing in literature teaching based on multiple linear regression algorithm
Authors: Zhang Qingbo
Published: September 2023

Under the background of the big data era, the rapid development of the Internet has driven the development of the education field. The traditional creative writing teaching is hardly suitable for the new curriculum reform requirements, prompting the rapid rise of creative writing and being highly recognized by the National Education Bureau. This paper applies creative writing based on multiple linear regression algorithms, i.e., teaching literature and education. Firstly, we understand the formula and principle of multiple linear regression algorithm, establish multiple linear models, extract and matrix students’ characteristic data, collect students’ data when learning on the online platform, pre-process the collected data, and analyze the performance and behavior of creative writing based on the end element linear regression algorithm. The results show that the number of clustering centers and visits are linearly correlated with the student’s grades, final overall grades, and test scores and that the student’s grades eventually improved to above 90. This study identifies the extent to which learning behaviors impact students’ final grades, allowing teachers to refine their teaching methods by selecting the learning styles that have a greater impact on students’ final grades among the many online platform student activities. It is conducive to improving cultural literacy and creative writing skills and has historical significance for developing Chinese literature and education.
Teaching reform and innovation of vocational development and employment guidance courses in colleges and universities based on random forest model
Authors: Lu Xi , Wei La
Published: September 2023

The current employment situation of graduates is serious and complicated, and employment work is very difficult. Furthermore, the employment quality of college graduates is an important reflection of the quality of education teaching and talent cultivation in higher education. Using big data to provide all-round and multi-perspective feedback on employment quality can find the direction of efforts to improve employment quality further, provide an important reference basis for schools to adjust the layout of majors, make development plans, reform education teaching, optimize career guidance courses and optimize enrollment policies and measures, and effectively promote universities to fulfill better their historical mission of serving the society. This paper extracts features for a series of school behavior data of students and carries out feature selection through appropriate methods. Specifically, the construction problem of the traditional random forest model is analyzed, and a new model is proposed by combining it with a decision tree algorithm; then, the model is constructed and adjusted by grid parameters to ensure the accuracy of the model, and finally, the model is compared and analyzed. The research shows that the accuracy of the RF prediction model using standard features is 0.702, and the LSTM prediction model using only temporal features is only 0.683. In contrast, the prediction accuracy of the model in this paper reaches 0.805. Therefore, the prediction accuracy of the model based on the decision tree algorithm is much higher than the other two, which is effective for optimizing the teaching of career development and employment guidance courses in colleges and universities, thus can improve the education and management-related to career planning and career guidance in schools.
Origin of potassium-bearing tourmalines of the Kumdy-Kolsky deposit (Kokchetav massif, Northern Kazakhstan): Study of Mineral inclusions
Authors: Korsakov A. V. , Musiyachenko K. A. , Mikhailenko D. S. , Demin S. P.
Published: September 2023

Research subject. Mineral inclusions in potassium-bearing tourmaline crystals of the Kumdy-Kol microdiamond deposit. Aim. To reconstruct PT conditions for the origin of potassium-bearing tourmalines. Materials and methods. Mineral analysis and element mapping were performed using an X-ray spectral microanalyzer. Raman spectroscopy was used to detect the C and SiO2 polymorphs. Results. For the first time, diamond inclusions were identified in tourmalines with the potassium content ranging from 1.0 to 1.6 wt %. In addition, diamond-bearing zircon was detected in tourmaline crystals, with the K2O content below the detection limit. Previously, diamond inclusions had been exclusively identified only within the most potassium-rich cores of tourmaline crystals, which were approved as a new end member referred to as maruyamaite. Similar to the previous studies, the Kfs inclusions were recognized in both marumaite crystals and tourmaline crystals, with a variable content of potassium. Conclusions. The obtained findings indicate that high-pressure conditions may not be necessary for the formation of potassium-rich tourmaline. The chemical composition of the fluid is most likely to be the main factor controlling the appearance of tourmalines with an unusual composition.
Exploring the Impact of Big Bang-Big Crunch Algorithm Parameters on Welded Beam Design Problem Resolution
Authors: Almufti Saman M.
Published: September 2023

A Metaheuristic Optimization is a group of algorithms that are widely studied and employed in the scientific literature. Typically, metaheuristics algorithms utilize stochastic operators that make each iteration unique, and they frequently contain controlling parameters that have an impact on the convergence process since their impacts are mostly neglected in most optimization literature, making it difficult to draw conclusions. This paper introduced the Big Bang-Big Crunch (BB-BC) metaheuristic algorithm to evaluate the performance of a metaheuristic algorithm in relation to its control parameter. It also demonstrates the effects of varying the values of BB-BC in solving. The "Welded Beam Design problem" is a well-known engineering optimization problem that is classified as a Single-Objective Constrained Optimization issue. Multiple starting parameter values for the BB-BC are evaluated as part of the experimental findings. This is done in an attempt to find the algorithm's optimal starting settings. The lowest, maximum, and mean values of the penalized objective functions are then computed. Finally, the BB-BC results are compared with various metaheuristics algorithms.
Efektifitas Pemberian Hasil Rekomendasi Penyelidikan Komnas HAM Terhadap Dugaan Pelanggaran HAM Kepada Lembaga Negara
Authors: Morfi Rini Fitria , Arfiani Arfiani , Amsari Feri
Published: September 2023

Human rights are the basis of a country in forming all provisions in the life of the nation and state which are the natural rights of every human being. The establishment of the National Human Rights Commission as an independent institution, is also based on Article 28 of the 1945 Constitution of the Republic of Indonesia which confirms that; protecting, promoting, upholding and fulfilling human rights is the responsibility of the state. This article analyzes one of the functions of Komnas HAM, namely having the authority to investigate alleged cases of human rights violations and issuing recommendations based on the investigation. The purpose of this article is to find out the effectiveness of providing state institutions with the results of investigation recommendations by the National Human Rights Commission on alleged human rights violations. This article uses a research method. This type of empirical juridical research. The results of the study found that first, according to Law Number 39 of 1999 concerning Human Rights and Law Number 26 of 2000 concerning Human Rights Courts that in protecting and guaranteeing human rights, the National Human Rights Commission has a role and function of reviewing , research, counseling, monitoring, mediation, and has the authority to investigate alleged cases of gross human rights violations, as well as issue recommendations afterward. Second, the recommendations issued by Komnas HAM after the investigation was carried out were public law acts because they resulted in a legal relationship between Komnas HAM and the Government as the recipient of the recommendations and the substance of Komnas HAM's recommendations regarding the existence of a case of human rights violations and various solutions in its settlement as well as the results of recommendations issued by Komnas HAM does not have binding and coercive legal force like court decisions which have executorial value. For this reason, some recommendations from the National Commission on Human Rights were followed up by the target state agencies, some were not.
Analisis Putusan Perkara Anak Pelaku Tindak Pidana Eksploitasi Secara Ekonomi Dan Seksual Terhadap Anak Secara Online (Studi Putusan No.6/Pid.Sus-Anak/2020/Pn.Pdg)
Authors: Elpasya Ivandro , Nelwitis Nelwitis , Afrizal Riki
Published: September 2023

This paper is a case study with case number 6/Pid.Sus-Anak/2020/Pn.Pdg which has permanent legal force. In this decision, the child is the perpetrator of the crime of economic and sexual exploitation of children. Juridically in Article 70 of the SPPA Law, the personal circumstances of the child, or the circumstances at the time of the act or what happened later can be used as a basis for the judge's consideration not to impose imprisonment. However, in this decision the judge imposed a prison sentence on the child. The problem formulations discussed in this paper are: 1. How is the judge's consideration in imposing a criminal judgment against the child who is the perpetrator of the criminal offense of Economic and Sexual Exploitation of Children (Decision Number 6/Pid.Sus-Anak/2020/Pn.Pdg)? 2. Is the Judge's Decision Number 6/Pid.Sus-Anak/2020/Pn.Pdg. in accordance with the Purpose of Punishment of Children? The legal research method used is normative juridical with a problem approach, namely, case, statutory and conceptual approaches. This research is descriptive analytical, data collection techniques with document studies or literature studies. In the legal analysis of case settlement, according to the author, the child should not have been sentenced to imprisonment because first, the child had not previously committed a criminal offense, second, the child was cooperative and polite during the trial and the consequences of the incident hindered the child's growth and development. Judge Decision Number 2/Pid.Sus-Anak/2019/Pn.Pdg is not in accordance with the objectives of punishment in general, which are more precisely regulated in the SPPA Law because it emphasizes restitution to the original state rather than retaliation, and the use of imprisonment or detention as a last resort or as an ultimum remedium.
Desempenho cognitivo e escolar em crianças com transtorno de déficit de atenção e hiperatividade (TDAH)
Authors: Simão Adriana Nobre de Paula , Ciasca Sylvia Maria
Published: September 2023

O Transtorno de Déficit de Atenção e Hiperatividade é um transtorno de conduta é crônico, com substrato biológico muito importante, não devido a uma única causa, apresenta forte base genética e é formado por um grupo heterogêneo de crianças. Inclui crianças com inteligência normal, que apresentam dificuldades significativas para se adequar em termos de comportamento e/ou aprendizagem às normas esperadas para sua idade. Sendo dividido em três subtipos denominados como Subtipo Desatento,  Subtipo Hiperativo/Impulsivo e Subtipo Combinado. O objetivo deste trabalho foi caracterizar o desempenho cognitivo, de funções corticais superiores e escolar. Utilizando como instrumento de avaliação o WISC Ill, TLN-Ce TDE. Foram avaliadas 13 crianças, com idade média de 9 anos, sendo a sua maioria do sexo masculino, frequentando o ensino fundamental da rede publicada região de Campinas. Como resultado, o grupo apresenta desempenho cognitivo dentro da média, com melhor resultado nos índices fatoriais de organização perceptual e compreensão verba. Na avaliação das funções corticais tiveram pior desempenho nas áreas cadêmicas, ritmo e habilidade tátil. Na avaliação de desempenho escolar apresentou dificuldade em escrita, aritmética e leitura.
AME Psiquiatria: um ano de funcionamento
Authors: Araujo Filho Gerardo Maria de , Yamaguchi Luciana Mayumi , Laranjeira Ronaldo Ramos , Amino Denise , Silveira Ana Stella Azevedo , Tamai Sérgio
Published: September 2023

Introdução: AME Psiquiatria Vila Maria e sua contribuição para a assistência à saúde mental: dados do primeiro ano de funcionamento. Objetivo: Apresentar o ambulatório médico de especialidades (AME) Psiquiatria Vila Maria e reportar os dados do primeiro ano de funcionamento e suas contribuições à assistência em saúde mental para a Zona Norte da cidade de São Paulo. Método: Foi realizada uma revisão dos dados referentes ao número de atendimentos, unidades de referência, área de abrangência, número de profissionais, atividades de extensão e pesquisa e aceitação geral da unidade pelos usuários no referido período de funcionamento. Resultados: O AME Psiquiatria Vila Maria, primeiro AME de São Paulo, é referência para toda a Zona Norte de São Paulo, que abrange uma área de 295,3 km2 e uma população de 2.214.654 habitantes. Em seu primeiro ano de funcionamento, realizou 26.352 atendimentos médicos e 21.385 não-médicos, conta atualmente com 127 profissionais, realiza atividades de extensão e pesquisa e conta com 97% de aceitação geral da unidade pelos usuários. Conclusão: O modelo de saúde mental atualmente vigente no Brasil apresenta uma série de desafios à sociedade brasileira. A Associação Brasileira de Psiquiatria tem participado dessa discussão, propondo a criação de serviços que possam atender mais adequadamente as necessidades da população brasileira. Nesse contexto, o AME Psiquiatria tem contribuido, em seu primeiro ano de funcionamento, para a melhora na qualidade da assistência à saúde mental em sua área de atuação.
Demonstrating Autonomy for Complex Space Missions: A Europa Lander Mission Autonomy Prototype
Authors: Wagner Caleb , Mauceri Cecilia , Twu Philip , Marchetti Yuliya , Russino Joseph , Aguilar Dustin , Rabideau Gregg , Tepsuporn Scott , Chien Steve , Reeves Glenn
Published: September 2023

There is a desire for robotic spacecraft to perform exploration in unknown, dynamic environments. The Europa Lander Mission Concept is one such mission that needs to deal with an extremely limited lifetime and energy supply, manage intermittent communications with long blackouts, face numerous environmental dangers, and ultimately take place too far from Earth to rely on human control. No missions to date have operated with the required level of autonomy and under the same level of communication constraints, uncertainty, and mission concept complexity as this mission. As a result, the viability of the autonomy must be demonstrated before it will be trusted with mission-critical planning. In this paper, we present an autonomous software prototype that can demonstrate and test the ability of different planners and executives to carry out complex, science-centric missions with limited interventions from humans. The prototype uses a hierarchical utility model that is used to maximize both the amount of expected science return as well as the number of mission objectives imposed by the ground. We demonstrate how this system handles some of the autonomous tasks expected of complex space missions such as decision making, in-situ data acquisition and analysis, data prioritization, resource management, and failure response handling in both simulation and on actual hardware. Through several scenario-based experiments we show how different planners and executives can meet the challenges of the Europa Lander Mission Concept. We also demonstrate that this system can be used in concert with a hardware prototype for autonomy field tests.
The Effects of Internal and External Risk Factors in Forensic Social Workers’ Experience of Secondary Traumatic Stress
Authors: Mashego Baatseba Babra , Boshoff Pieter , Fourie Erika
Published: September 2023

Forensic social workers are vulnerable to secondary traumatic stress due to their direct exposure to trauma narratives from sexually abused children. They face the unique challenge of distinguishing between their roles as expert witnesses and therapists. However, research on the risk factors for secondary traumatic stress in forensic social workers is frequently disregarded both internationally and in South Africa. The purpose of this study was to look at the effect of internal and external risk factors on secondary traumatic stress symptoms among forensic social workers. An all-inclusive voluntary sample method was used to include all trained forensic social workers with a master’s degree in forensic practice who graduated from a recognised South African university between 2006 and 2019. The study used a quantitative cross-sectional descriptive design and data was collected using Google Forms, which was distributed via email. IBM SPSS version 27 was used to analyse the data. Internal factors such as race and relationship status as well as external factors such as clinical supervision, social support, and exposure to traumatic experiences were found to have varied effects on secondary traumatic stress symptoms in the study.
Refractory seizure in a neonate with severe hypernatraemic dehydration – A case report
Authors: Venkatesh H. A.
Published: September 2023

Hypernatraemic dehydration is a common clinical condition seen in neonates especially when they lose weight by more than 10%. Such neonates should be carefully followed up for rising sodium levels and need to be encouraged adequate feeding to prevent complications. Term-appropriate neonate born to a non-consanguineous couple with an uneventful perinatal period was brought to the paediatric emergency room on day 15 of life with multiple seizures and was diagnosed with hypernatraemic dehydration. Her brain imaging demonstrated sagittal venous thrombosis with intraventricular haemorrhage and parenchymal bleeding with infarct. She was managed with respiratory support and fluid management. Parents were counselled regarding the guarded prognosis. She was discharged against medical advice.
Awake craniotomy for fenestration of motor cortex neuroglial cyst: A case report
Authors: Hamzah Abdulaziz , Ashqar Alaa Adel , Alshanqiti Maryam , Lary Ahmed , Samkari Alaa
Published: September 2023

Background:

Neuroglial cysts (NCs) are uncommon benign cysts covered by an epithelial layer, accounting for <1% of all intracranial cysts. The optimal management approach for these cysts remains a subject of debate. Given their rarity, management principles used for arachnoid cysts can be applied to NCs.

Case Description:

We present a case of a 35-year-old male without prior medical history, who presented to the neurosurgery clinic with complaints of absence seizures. A neurological examination revealed subtle weakness in the left upper limb. Brain magnetic resonance imaging demonstrated a large cystic lesion in the posterior frontal and anterior parietal lobes of the right hemisphere. The patient underwent an awake craniotomy, during which a cystoventricular fenestration was performed on the motor cortex cyst. Histopathological examination confirmed the diagnosis of NC. At the 4-month follow-up, the patient experienced complete recovery, with normal strength (5/5) in all limbs and absence of seizure remission.

Conclusion:

This case highlights the successful use of awake craniotomy for the fenestration of an NC in the motor cortex. Given the rarity of NCs, there is no consensus on the optimal treatment strategy. However, in this particular case, the patient achieved complete recovery without any new neurological deficits following the procedure.
Investigation of the Relationship Between the Levels of Leisure Time Satisfaction and Passion in Sports Who Exercise Individuals Fitness
Authors: DOKUZOĞLU Gökhan , SAĞIROĞLU İsa , ÇEVİK Ali
Published: September 2023

This study aimed to reveal the relationship between the leisure satisfaction levels of individuals who do fitness exercises and their passion levels in sports. The study group of the research consisted of individuals who did fitness exercises in Aydın in 2023. 259 individuals voluntarily participated in the study. In the study, demographic information was used as a data collection tool in the first part, and in the second part, the "Passion in Sport Scale" developed by Sigmundsson et al., (2020) and adapted into Turkish by Özdayı et al., (2021), and the "Leisure Time Satisfaction Scale" developed by Beard and Ragheb (1980) and adapted into Turkish by Gökçe and Orhan (2011) were used. In statistical terms, frequency analysis, reliability coefficient calculations, pearson correlation analysis, simple regression analysis, t test and anova analysis were performed. There was a statistically significant difference (p<0.05) between the variables of leisure satisfaction and weekly exercise duration and sports experience of the participants, and a statistically significant difference was detected between passion in sports and age, weekly exercise time and sports experience variables (p<0.05). It has been concluded that individuals who do fitness exercises have a significant and positive effect on their leisure satisfaction.
Problems and possibilities for developing the risk concept of technical systems
Authors: Лепихин А.М. , Лещенко В.В. , Махутов Н.А.
Published: September 2023

Дан краткий анализ развития концепций риска аварий технических систем. На основе концепции минимизации стоимости жизненного цикла предложена новая трактовка риска технических систем, включающая потери как от аварий, так и от нарушений работоспособного состояния. Рассмотрены задачи оценки риска в предлагаемой формулировке. Ввиду ограниченности возможностей аналитических методов оценки риска основное внимание акцентируется на использовании методов Монте-Карло. Рассмотрены возможности оценок риска на основе статистических данных об авариях и нарушениях работоспособности. В качестве примера выполнены оценки риска аварий наземных и морских подводных трубопроводных систем с учетом нарушений работоспособности. Показано, что предлагаемый подход дает более высокие оценки риска по сравнению с традиционным подходом

The article gives a brief analysis for development of the concepts for risk analysis of accidents in technical systems. The new interpretation of the risk of technical systems is proposed, including both losses from accidents and losses from violations of the working condition and based on the concept of minimizing the cost of the life cycle. The problems of risk assessment in the proposed formulation are considered. The main attention is paid to the prospects of risk assessments using Monte Carlo methods due to the limited capabilities of analytical methods for risk assessment. The capabilities of risk assessments based on statistical data on accidents and malfunctions are considered. The assessments of the risk of accidents and malfunctions of onshore and offshore underwater pipeline systems are carried out. It is shown that the proposed approach gives higher risk estimates compared to the traditional approach