bluuebunny/crossref_metadata_2025 huggingface dataset:
Ecological and Human Health Risk Assessment of Heavy Metals by Consuming the Aquatic Plant Species Near an Electronic Waste Open Dumpsite in Thailand
Authors: Parkpoom Thitima , Intamat Somsak , Phoonaploy Uraiwan , Neeratanaphan Lamyai
Published: July 2022

Heavy metals from electronic waste (e-waste) accumulate in the environment and can affect human health. The purpose of this study was to determine As, Cd, Cr and Pb concentrations in water, sediment and three species of edible aquatic plants (Ottelia alismoides, Ipomoea aquatic and Marsilea crenata) near an e-waste open dumpsite. Samples were collected from six sampling points surrounding an e-waste open dumpsite and heavy metal concentrations were analyzed by inductively coupled plasma optical emission spectrometry (ICP-OES). Bioaccumulation factors (BAFs), estimated daily intake (EDI), hazard quotient (HQ), hazard index (HI) and carcinogenic risk (CR) were evaluated in the plants. The Pb concentration in the water samples exceeded the quality standard. The order of the heavy metal concentrations in the sediment was Pb>Cr>As >Cd, and these concentrations were within the limits of the quality standard. The order of the heavy metal concentrations in O. alismoides, I. aquatic and M. crenata was Cr>Pb>As>Cd, Pb>Cr>As>Cd and Pb>Cr>As>Cd, respectively. The concentrations of As, Cd, Cr and Pb in O. alismoides and As, Cr and Pb in I. aquatic and M. crenata exceeded the quality standard of food consumption. Most of the BAF values of the heavy metals in O. alismoides were more than one, but in I. aquatic and M. crenata, they were less than one. The order of the EDI values in O. alismoides, I. aquatic and M. crenata was Cr>Pb>As>Cd, Pb>Cr>As>Cd and Cr>As>Pb >Cd, respectively. The HQ values were greater than one for As, Cd and Pb in O. alismoides; Pb in I. aquatic; and As and Pb in M. crenata. The HQ and CR values show that the consumption of edible plants from an e-waste open dumpsite is a human health risk.
Era of The COVID-19 Pandemic: Ewuh Pakewuh Culture and Its Role on The Behavior of Someone in Debt, Based on Social Norms
Authors: Santoso Aprih , Rawi Rais Dera Pua , Ma'ruf M. Hasan
Published: July 2022

The purpose of this study was to examine the effect of social norms on the behavior of a person in debt for small entrepreneurs in the city of Semarang in the era of the COVID-19 PANDEMI, with ewuh paewuh culture as a moderating variable. The population of this study includes all small entrepreneurs who take credit from the Wibawa in the city of Semarang, amounting to 3950 people. The number of samples is 100 people (based on the Slovin formula). The sample selection method is purposive sampling, with the following criteria: 1) small entrepreneurs taking debts for the first time. 2) Small entrepreneurs are married and still have dependents for school children. The results of this study indicate that social norms influence the behavior of a person in debt for small entrepreneurs in Semarang City during the COVID-19 PANDEMIC era and the ewuh pakewuh culture is able to moderate the relationship between the influence of social norms on this behavior.
Transformational Leadership and Organizational Commitments to Performance of State Civilians in the Local Government of East Luwu District
Authors: Sismiati Sismiati , Sulaiman Syarifuddin , Mochamad Yudi
Published: July 2022

This study aims to determine and analyze the effect of transformational leadership and organizational commitment on the performance of the state civil apparatus in the East Luwu Regency. This type of research is explanatory research that explains the effect of the independent variables on the dependent variable. This paper uses a quantitative approach in the form of statistical results to test the research hypothesis. This research was conducted in Luwu Raya Regency. The population in this study were all state civil servants in the local government of East Luwu Regency as many as 7,682 people. Determination of the number of samples using the Slovin approach, resulting in a total sample of 100 people. Sampling using an accidental sampling method. The analytical technique used in this research is multiple linear regression analysis. The results showed that simultaneously all independent variables (transformational leadership and organizational commitment) had a positive and significant effect on the performance of the state civil apparatus. The transformational leadership has a dominant effect on the performance of the state civil apparatus compared to the organizational commitment variable.
Effect of Employee Characteristics and Organizational Culture on Employee Performance Mediated By Motivation
Authors: Tj Hery Winoto
Published: July 2022

Human resources are important factors that need to be considered by companies, with superior human resources, the company has the potential to achieve its goals effectively and efficiently. Besides that, the company can also win the competition and expand its business. This study aims to analyze the effect of employee characteristics and organizational culture on employee performance with motivation as a mediating variable. Using the purposive sampling technique, the respondents obtained are 125 employees of PT Nuansa Bumi. The technique used in analyzing the data in this research is Non-Probability sampling using SmartPLS tools. The results obtained from this study are that employee characteristics and organizational culture positively affect employee performance. Employee characteristics and organizational culture mediated by motivational ​​variable also positively affect employee performance.
The Effect of Customer Trust, Lifestyle, and Attitude on the Online Buying Decision
Authors: Saparso S.
Published: July 2022

The internet is essential for business. It is because all people apply this connection to do their online activities, for example, buying. Therefore, many online platforms appear to facilitate it. The research about the decision to buy online and its determinants is numerous. In this study, three determinants want to get investigated: trust, lifestyle, and attitude. By employing the undergraduate management students in Universitas Kristen Krida Wacana as population and stratified random sampling as the method to take the samples, this study has the goal to examine these three effects on the decision to purchase online. Before testing the effect of trust, lifestyle, and attitude on the online buying decision, the data collected from the online survey get validated first by the confirmatory factor analysis. Then, the reliability test by the Cronbach Alpha analysis becomes the following step. Furthermore, after examining the statistical hypotheses by the structural equation based on variance, this study reveals that trust does not affect the online purchasing decision. However, lifestyle and attitude become the determinant with a positive sign. It implies that the platform has to be able to provide a safe transaction to raise the trust of the customer to buy online, the sellers have to assure the fits of products offered and delivery time promised.
Co-combustion of Sewage Sludge in the Coal-Fired Heating Plant
Authors: Hlaváček Ondřej
Published: July 2022

Due to greening of production of electricity and heat some owners of heating plant are changing their fuel mix from fossil fuels to biomass one. The stabilized sewage sludge is in this biomass category as well. New Czech national legislation limits are stricter in parameters of biological activity, so the owners of water treatment plant are looking for new utilization of their stabilized sludge. There are some possibilities in combustion or co-combustion of this sludge in currently heating plant.
The article describes the trial test of stabilized sludge combustion on heating plant technology. The heating plant is originally designed for combustion of brown coal. The stabilized sludge was produced at the municipal wastewater treatment plant, from where it was transported to low-temperature (78 °C) drying technology, from where it was transported in granular form to the heating plant in Mladá Boleslav. The fuel mixture of trial test was in energetic ratio of 23% dried sludge and 77% brown coal. The sludge was transported into the boilers by pneumatic conveying, which is used in normal operation for conveying pelletized phytomass. The result shows an increase in SO2 emissions from the original 189.91 mg∙m-3 to 407.98 mg∙m-3 and an increase in NOx emissions from 148.45 mg∙m-3 to 181.46 mg∙m-3. There were also detected increasing NH3 emissions due to reac-tion of control system in SNCR technology od decreasing of NOx emissions. The trial test was done during full op-eration of the heating plant. During the test there was also a lower steam production, from originally 38.17 kg∙s-1 to 34.44 kg∙s-1, which is related to the lower LHV compared to the reference fuel. There were no major operation problems, except higher dustiness during unloading of sludge.
Finally, the Czech legislative problems associated with the combustion of stabilized sewage sludge are mentioned. In the current system, the sludge is established as waste, which forbids the combustion of it in conventional heating plants, even though all emission legislative limits are complied with. Nowadays the Ministry of the Environment of the Czech Republic is working on new regulation, which will determine new category of solid alternative fuels and it will be solution of this situation.
Artificial-Intelligence-Based Maintenance Scheduling for Complex Systems with Multiple Dependencies
Authors: Nguyen Van-Thai , Do Phuc , Voisin Alexandre
Published: July 2022

Maintenance planning for complex systems has still been a challenging problem. Firstly, integrating multiple dependency types into maintenance models makes them more realistic, however, more complicated to solve and analyze. Secondly, the number of maintenance decision variables needed to be optimized increases rapidly in the number of components, causing computational expensive for optimization algorithms. To face these issues, this thesis aims to incorporate multiple kinds of dependencies into maintenance models as well as to take advantage of recent advances in artificial intelligence field to effectively optimize maintenance polices for large-scale multi-component systems.
Physics Informed Self Supervised Learning For Fault Diagnostics and Prognostics in the Context of Sparse and Noisy Data
Authors: Deng Weikun , Nguyen Khanh T. P. , Medjaher Kamal
Published: July 2022

Sparse & noisy monitoring data leads to numerous challenges in prognostic and health management (PHM). Big data volume but poor quality with scarce healthy states information limits the performance of training machine learning (ML) and physics-based failure modeling. To address these challenges, this thesis aims to develop a new hybrid PHM framework with the ability to autonomously discover and exploit incomplete implicit physics knowledge in sparse & noisy monitoring data, providing a solution for deep physics knowledge-ML fusion by physics-informed machine learning algorithms. In addition, the developed hybrid framework also applies the self-supervised learning paradigm to significantly improve the learning performance under uncertain, sparse, and noisy data with lower requirements for specialist area knowledge. The performance of the developed algorithms will be investigated on the sparse and noise data generated by simulation data sets, public benchmark data sets, and the PHM platform to demonstrate its applicability.
Combining Knowledge and Deep Learning for Prognostics and Health Management
Authors: Radtke Maximilian-Peter , Bock Jürgen
Published: July 2022

In the recent past deep learning approaches have achieved remarkable results in the area of Prognostics and Health Management (PHM). These algorithms rely on large amounts of data, which is often not available, and produce outputs, which are hard to interpret. Before the broad success of deep learning machine faults were often classified using domain expert knowledge based on experience and physical models. In comparison, these approaches only require small amounts of data and produce highly interpretable results. On the downside, however, they struggle to predict unexpected patterns hidden in data. This research aims to combine knowledge and deep learning to increase accuracy, robustness and interpretability of current models.
Novel Graph-Based Features for Bearing Fault Diagnosis: Two Aspects of Time Series Structure
Authors: Lee Sangho , Son Youngdoo , Choi Chihyeon
Published: July 2022

The feature-based methods for bearing fault diagnosis in prognostics and health management have been achieved satisfactory performances because of their robustness to noise and reduced dimension by pre-defined features. However, widely employed time- and frequency-domain features are insufficient to recognize the global pattern that indicates the structure of a time-series instance. In this paper, we propose two novel graph-based features which reflect the connection strength and degree of time series, respectively. First, we construct a graph of which an edge is defined as the Euclidean distance between each pair of time steps to measure the strengths of connections between the nodes. The other graph is constructed by the visibility algorithm, which converts a time series into a complex network to reflect the degrees of connections. Then, we calculate the Frobenius norms of the adjacency matrices of both graphs and use them as features for bearing fault diagnosis. To verify the proposed features, we performed several experiments with both synthetic and real datasets. From the synthetic datasets, it is observed that the changes in amplitudes and frequencies are detected by the features for the connection strength and degree, respectively. In addition, the proposed features also well-separate the distributions of each bearing state, including normal and several fault types, and show significant performance improvement as applied to the fault diagnosis task.
Novel Metrics to Evaluate Probabilistic Remaining Useful Life Prognostics with Applications to Turbofan Engines
Authors: De Pater Ingeborg , Mitici Mihaela
Published: July 2022

Well-established metrics such as the Root Mean Square Error or the Mean Absolute Error are not suitable to evaluate estimated distributions of the Remaining Useful Life (i.e., probabilistic prognostics). We therefore propose novel metrics to evaluate the quality of probabilistic Remaining Useful Life prognostics. We estimate the distribution of the Remaining Useful Life of turbofan engines using a Convolutional Neural Network with Monte Carlo dropout. The accuracy and sharpness of the obtained probabilistic prognostics are evaluated using the Continuous Ranked Probability Score (CRPS) and weighted CRPS. The reliability of the obtained probabilistic prognostics is evaluated using the α-Coverage and the Reliability Score. The results show that the estimated distributions of the Remaining Useful Life of turbofan engines are accurate, reliable and sharp when using a Convolutional Neural Network with Monte Carlo dropout. In general, the proposed metrics are suitable to evaluate the accuracy, sharpness and reliability of probabilistic Remaining Useful Life prognostics.
Noise-Robust Representation for Fault Identification with Limited Data via Data Augmentation
Authors: Taghiyarrenani Zahra , Berenji Amirhossein
Published: July 2022

Noise will be unavoidably present in the data collected from physical environments, regardless of how sophisticated the measurement equipment is. Furthermore, collecting enough faulty data is a challenge since operating industrial machines in faulty modes not only has severe consequences to the machine health, but also may affect collateral machinery critically, from health state point of view. In this paper, we propose a method of denoising with limited data for the purpose of fault identification. In addition, our method is capable of removing multiple levels of noise simultaneously. For this purpose, inspired by unsupervised contrastive learning, we first augment the data with multiple levels of noise. Later, we construct a new feature representation using Contrastive Loss. The last step is building a classifier on top of the learned representation; this classifier can detect various faults in noisy environments. The experiments on the SOUTHEAST UNIVERSITY (SEU) dataset of bearings confirm that our method can simultaneously remove multiple noise levels.
Case-study Led Investigation of Explainable AI (XAI) to Support Deployment of Prognostics in the industry
Authors: Amin Omnia , Brown Blair , Stephen Bruce , McArthur Stephen
Published: July 2022

Civil nuclear generation plant must maximise it’s operational uptime in order to maintain it’s viability. With aging plant and heavily regulated operating constraints, monitoring is commonplace, but identifying health indicators to pre-empt disruptive faults is challenging owing to the volumes of data involved. Machine learning (ML) models are increasingly deployed in prognostics and health management (PHM) systems in various industrial applications, however, many of these are black box models that provide good performance but little or no insight into how predictions are reached. In nuclear generation, there is significant regulatory oversight and therefore a necessity to explain decisions based on outputs from predictive models. These explanations can then enable stakeholders to trust these outputs, satisfy regulatory bodies and subsequently make more effective operational decisions. How ML model outputs convey explanations to stakeholders is important, so these explanations must be in human (and technical domain related) understandable terms. Consequently, stakeholders can rapidly interpret, then trust predictions better, and will be able to act on them more effectively. The main contributions of this paper are: 1. introduce XAI into the PHM of industrial assets and provide a novel set of algorithms that translate the explanations produced by SHAP to text-based human-interpretable explanations; and 2. consider the context of these explanations as intended for application to prognostics of critical assets in industrial applications. The use of XAI will not only help in understanding how these ML models work, but also describe the most important features contributing to predicted degradation of the nuclear generation asset.
Automating Critical Surface Identification and Damage Detection Using Deep Learning and Perspective Projection Methods
Authors: Vadisala Gautam Kumar , Rawat Anurag Singh , Dubey Abhishek , Chin Gareth Yen Ket , Abreu Fabio
Published: July 2022

With an increased collection of data, assessing the health of an asset and designing recommendations or executing response actions via prognostics and health management (PHM) has made great advances. These actions can be corrective or preventive depending upon the risk of failure or the cost of repair. As downhole testing tools operate in extreme environments, they are subjected to conditions like elevated temperature, shocks, vibrations, and pressures. The dump mandrels used in the process are prone to wear and tear like scratches, pits, and corrosion, which may cause operational failure. If these damages and their degree goes undetected and no remedial actions are taken, possibilities of non-productive time (NPT) and financial losses increase drastically. This paper aims to develop a fitness inspector which uses Computer Vision and Deep Learning to identify critical surfaces of these tools and the damage within them. This will help the Subject Matter Experts (SMEs) by replacing the qualified workforce provided by them and reducing the time consumed to gauge the health status of all the tools as the diagnosis can be made in real-time.
Experimental Validation of Multi-fidelity Models for Prognostics of Electromechanical Actuators
Authors: Baldo Leonardo , Berri Pier Carlo , Dalla Vedova Matteo D. L. , Maggiore Paolo
Published: July 2022

The growing adoption of electrical energy as a secondary form of onboard power leads to an increase of electromechanical actuators (EMAs) use in aerospace applications. Therefore, innovative prognostic and diagnostic methodologies are becoming a fundamental tool to early identify faults propagation, prevent performance degradation, and ensure an acceptable level of safety and reliability of the system. Furthermore, prognostics entails further advantages, including a better ability to plan the maintenance of the various equipment, manage the warehouse and maintenance personnel, and a reduction in system management costs.
Frequently, such approaches require the development of typologies of numerical models capable of simulating the performance of the EMA with different levels of fidelity: monitoring models, suitably simplified to combine speed and accuracy with reduced computational costs, and high fidelity models (and high computational intensity), to generate databases, develop predictive algorithms and train machine learning surrogates. Because of this, the authors developed a high-fidelity multi-domain numerical model (HF) capable of accounting for a variety of physical phenomena and gradual failures in the EMA, as well as a low-fidelity counterpart (LF). This simplified model is derived by the HF and intended for monitoring applications. While maintaining a low computing cost, LF is fault sensitive and can simulate the system position, speed, and equivalent phase currents.
These models have been validated using a dedicated EMA test bench, designed and implemented by authors. The HF model can simulate the operation of the actuator in nominal conditions as well as in the presence of incipient mechanical faults, such as a variation in friction and an increase of backlash in the reduction gearbox.
Comparing the preliminary results highlights satisfactory consistency between the experimental test bench and the two numerical models proposed by the authors.
Approach to Condition Monitoring of BLDC Motors with Experimentally Validated Simulation Data
Authors: Weigert Max
Published: July 2022

Due to their compact design and low number of wear parts, Brushless Direct Current (BLDC) motors are ideally suited for use in unmanned aerial vehicles (UAVs). In view of the growing areas of application and the increasing complexity of unmanned flight missions, the need for suitable safety mechanisms for the operation of technical components, such as BLDC motors, in unmanned aircraft drive trains is also increasing. The integration of redundant components analogous to manned aviation is often not possible for smaller unmanned aerial vehicles for weight reasons. Therefore, online-capable dynamic diagnosis and prognosis methods for monitoring safety-critical components of unmanned aircraft are subject of ongoing research.
One major challenge in the development of data based condition monitoring approaches for safety critical components is the availability of operational data of degraded components. This often leads to an unbalanced database without sufficient information on components’ degradation behavior.
In the presented work, this problem is approached by combining bench testing and simulation models. On a test rig, common degradation effects are recreated by targeted manipulation. This allows for a safe and expressive data acquisition of the components’ behavior. In order to reduce the material and time required to build up a sufficient database for condition monitoring with experimental data, the observable effects are replicated in a simulation. This provides the opportunity to create a large database with slight variations in simulation parameters and incorporated noise in the simulation.
The BLDC motor manipulation on the test rig includes mechanical, electrical and magnetic manipulation. The effects of the manipulation are analyzed and their representation by parameters in the corresponding simulation is derived. The model is built in MATLAB Simulink and replicates both the electrical and physical behavior of the motor, as well as its commutation behavior.
The established simulation data shall be used as a balanced dataset on which condition monitoring algorithms can be trained. This will allow for the comparison of various data based condition monitoring methods in the future. A remaining challenge lies in the time behavior of the analyzed degradation, which has not yet been explored in depth. The proposed approach might also be applied to further unmanned aerial vehicle components, such as servo motors.
Toward Runtime Assurance of Complex Systems with AI Components
Authors: He Yuning , Schumann Johann , Yu Huafeng
Published: July 2022

AI components (e.g., Deep Neural Networks) are increasingly used in safety-relevant aerospace applications. Rigorous Verification and Validation (V&V) is mandatory for such components, yet V&V techniques for DNNs are still in their infancy and can often only provide relatively weak guarantees. In this paper, we will present a runtime-monitoring architecture, which combines the advanced statistical analysis framework SYSAI (System Analysis using Statistical AI) with temporal and probabilistic runtime monitoring carried out by R2U2 (Realizable, Responsive, and Unobtrusive Unit). We will present initial results of our tool set and architecture on a case study, a DNN-based autonomous centerline tracking system (ACT).
Long Horizon Anomaly Prediction in Multivariate Time Series with Causal Autoencoders
Authors: Asres Mulugeta Weldezgina , Cummings Grace , Khukhunaishvili Aleko , Parygin Pavel , Cooper Seth I. , Yu David , Dittmann Jay , Omlin Christian W.
Published: July 2022

Predictive maintenance is essential for complex industrial systems to foresee anomalies before major system faults or ultimate breakdown. However, the existing efforts on Industry 4.0 predictive monitoring are directed at semi-supervised anomaly detection with limited robustness for large systems, which are often accompanied by uncleaned and unlabeled data. We address the challenge of predicting anomalies through data-driven end-to-end deep learning models using early warning symptoms on multivariate time series sensor data. We introduce AnoP, a long multi-timestep anomaly prediction system based on unsupervised attention-based causal residual networks, to raise alerts for anomaly prevention. The experimental evaluation on large data sets from detector health monitoring of the Hadron Calorimeter of the CMS Experiment at LHC CERN demonstrates the promising efficacy of the proposed approach. AnoP predicted around 60% of the anomalies up to seven days ahead, and the majority of the missed anomalies are abnormalities with unpredictable noisy-like behavior. Moreover, it has discovered previously unknown anomalies in the calorimeter’s sensors.
Domain Analysis to assess the sustainability of construction projects using Semantic Technologies
Authors: Silva Cristiano Geraldo Teixeira , Bax Marcello Peixoto
Published: July 2022

A avaliação de projetos de construção visa medir o quão sustentáveis ​​são os ambientes construídos e isso é importante para salvar o meio ambiente de uma deterioração crescente. Porém, a maioria das tarefas de avaliação são realizadas em ferramentas diferentes, em todas as fases da construção e até manualmente, consumindo tempo e aumentando a possibilidade de erros. O problema de pesquisa é verificar como o uso de tecnologias semânticas representaria uma alternativa vantajosa, em relação ao estado da arte, para analisar, sistematizar e organizar informações do domínio dos projetos de construção, acelerando o processo de avaliação. São apresentados os conceitos por trás de um experimento que emprega tecnologias semânticas e uma ontologia de domínio para integrar dados de projetos BIM (Building Information Modeling) e outros dados tabulares externos ao projeto para automatizar as tarefas de certificação LEED (Leadership in Energy and Environmental Design). Para produzir o protótipo deste experimento, dados de um projeto BIM e dados tabulados abertos da cidade de Belo Horizonte são semanticamente anotados e um gráfico de conhecimento é gerado em formato RDF. Depois de integrados ao gráfico, os dados são usados ​​para avaliar os critérios de certificação por meio de consultas. Os resultados sugerem que a análise de domínio associada às tecnologias semânticas promove a extensibilidade conceitual dos elementos construtivos, possibilitando sua integração com bases de conhecimento externas. Outra vantagem é a organização conceitual dos dados com o objetivo de melhorar as tarefas de recuperação de informações relevantes.
Influence of personal and occupational stressors on job performance of library staff in private universities in Oyo State, Nigeria
Authors: Oyadeyi Adekunle Emmanuel , Fasola Omobolanle Seri , Oladokun Taofeek Abiodun
Published: July 2022

The study investigated the influence of personal and occupational stressors on job performance of library staff in private universities in Oyo State, Nigeria. A survey research method was adopted in the conduct of this study. The population of the study includes all library staff in private universities in Oyo State, Nigeria using total enumeration sampling technique. Questionnaire was the major instrument used for data collection. The data collected was analyzed using table of frequency, percentage counts and mean analysis. The study’s findings revealed a significant correlation between personal stress, job stress and job performance. According to the findings, underachieving, financial problem, resentment, job insecurity, relationship and health issues are stress stimulants that contribute to personal stress among library personnel in private universities in Oyo State. While disrespect from library users, poor working conditions, working overtime, work overload, and using personal resources to work constitute major occupational stressors for library staff.  These stressors are significantly correlated with absenteeism, low productivity, resignation, lateness, sleeplessness and alcoholism
Competência em Informação e os Idosos
Authors: Do Amaral Oliveira Gardin Daniela , Alcará Adriana
Published: July 2022

Esta investigação se propôs a identificar e conhecer os trabalhos científicos, suas abordagens e aprofundamentos, bem como as grandes áreas neles contempladas dos últimos cinco anos, acerca da competência em informação do público idoso. Caracteriza-se como uma investigação de tipo bibliográfica e exploratória, com abordagem qualitativa. Para seu desenvolvimento foi realizada consulta às bases de dados do Portal de Periódicos da Capes e do Google Acadêmico que resultaram em 22 trabalhos internacionais e nacionais, analisados sob a perspectiva da quantidade, abordagens, objetivos, palavras-chave, descritores e áreas de discussão, entre outras particularidades. Concluiu-se que a competência em informação no contexto dos idosos tem alcançado uma pequena, porém constante visibilidade nas pesquisas científicas e que há uma prevalência de estudos que a associam à utilização de ferramentas da tecnologia de informação e comunicação e ao campo da literacia em saúde dos idosos. Por fim, sugeriu-se o implemento de estudos que abranjam outros contextos do sujeito idoso, como por exemplo sob a perspectiva de aprendizado constante, das habilidades, de reflexão crítica acerca da realidade, da manutenção de sua atividade laboral e de protagonismo do sujeito idoso na conquista de direitos e do exercício da cidadania na sociedade da informação e do conhecimento.
The Influence Of Corporate Governance On Integrated Reporting Disclosure Moderated By Type Auditor
Authors: Afifah Hasnaul , Surwanti Arni , Sotya Pamungkas Wihandaru
Published: July 2022

The objective of this research is to the influence of independent board members, board size, female board, type of auditor to independent board members as a moderating variable on IRD The sample in this study was the LQ45 Non-Banking on Indonesia Stock Exchange in 2016-2020 period with a purposive sampling technique. The analytical tool used was Eviews 10 (x64). The result is independent board members have a positive effect and negative significant on IRD, board size have a positive effect on IRD, female board have a no effect on IRD, and type of auditor no strengthens independent board members on IRD
O elemento da vontade nos fenômenos complexos
Authors: Becker Silvério
Published: July 2022

O presente texto é a tradução do décimo segundo capítulo da obra Doctrine of the Will (Doutrina da Vontade), de Asa Mahan (1799-1889), publicado originalmente em 1845. Nele, Mahan defende que, embora a Inteligência e a Sensibilidade dos agentes morais sejam, em si mesmas, destituídas de liberdade, e por conseguinte, de moralidade, a Vontade possui um controle indireto sobre essas faculdades na vasta medida em que elas apresentam objetos para sua ação em diferentes direções. Assim, quando influenciados pela Vontade – seja direta ou indiretamente - os fenômenos das outras faculdades da mente constituem fenômenos complexos da mente humana, e possuem caráter moral. Segundo Mahan, as ações externas, assim como os estados da Inteligência e da Sensibilidade, quando são requeridos ou proibidos pela lei moral, ou pela Revelação, são requeridos ou proibidos por serem o resultado natural e necessário de intenções corretas ou erradas. Nesses casos, os requerimentos e as proibições se referem às causas desses atos ou estados, ou seja, à ação da Vontade da qual eles resultam necessariamente. Na apresentação de suas proposições, Mahan usa argumentos relacionados à ação da Vontade em direção às propensões naturais, como emoções desejos e anelos; e às afeições religiosas, como o arrependimento, o amor e a fé. Ele também defende que as afeiçoes religiosas requeridas pela lei moral são atos voluntários da mente e não meros estados da sensibilidade ou meras convicções da Inteligência.
Unidade e multiplicidade na constituição do corpo político em Thomas Hobbes: uma leitura do Elements of Law e do Leviathan
Authors: Mattos Delmo
Published: July 2022

O objetivo desse artigo consiste em discutir as relações entre multidão e povo para a constituição da teoria da representação proposta por Thomas Hobbes. Para tanto, direcionam-se as discussões para o âmbito das obras Elements of Law e Leviathan, pelas quais se reconstitui a trajetória argumentativa que dispensa os elementos da pluralidade das vontades para o âmbito da sua unidade. Evidencia-se, portanto, uma evolução argumentativa no que concerne à ideia de unidade e representação entre as duas obras de Hobbes. Para tanto, discute-se a aquisição da unidade das vontades como um elemento indispensável para o estabelecimento da pessoa artificial. Como consequência, demonstra-se que a teoria da representação está condicionada à constituição de uma vontade única, pela qual se estabelecem as premissas da redução do múltiplo ao uno, cuja consequência é o surgimento da concepção de autorização, fundamental ao núcleo da representatividade política.
Perspectives on human beings in chinese philosophy and its historical significance to the cause of educational innovation in Vietnam currently
Authors: Quyet Nguyen Thi
Published: July 2022

China is known as a cradle of human civilization. Since ancient times, this place has achieved many brilliant development achievements in all fields of social life, especially philosophy. During the process of formation and development, Chinese philosophy has taken people and human-related issues as the object of study. Theories on people are very rich and diverse in order to clarify the human issues in many different aspects. Chinese philosophic viewpoints on people are widespread, affecting and influencing many other countries in the region, including Vietnam. The article uses the methodology of the materialistic dialectics with principles of comprehensiveness, development, specific history and methods of comparison, analysis and synthesis to clarify the basic contents of the human issue in ancient Chinese philosophy, thereby, drawing its historical significance for the cause of current educational innovation in Vietnam through the development of policies on detecting, fostering, training and employing talents; focusing on moral education, considering moral education as the basic task of all educational processes; promoting the particularly important role of the teacher in the entire educational process; and building a rich and lively system of teaching methods to achieve the highest efficiency in the educational process.
К ИСТОРИИ И МИКРОТОПОНИМИИ СЕЛА ШЕРДЫ-МОХК (ШИРДА-МОХК)
Authors: Усаев А.А. , Усаева А.А.
Published: July 2022

В статье рассматривается краткая история села Шерды-Мохк Веденского района Чеченской Республики, основанного представителями общества ширдой (ширди). Рассмотренная история и география Шерды-Мохк позволяет ознакомиться с общей историей и географическим местоположением данного селения. Рассматриваются версии по происхождению названия тайпа ширдой. Упоминается личность Ширдалха (связывается с областью Нашха); рассматриваются микротопонимы Шерды-Мохк, связанные с исторической территорией Ширдойской общины; исследованы и указаны топонимы (гидронимы, дримонимы, ойконимы, оронимы и т.д) селения и их некоторые этимологии.
СВОЙСТВА РЕБЕР И ДИАГОНАЛЕЙ СОВЕРШЕННОГО КУБОИДА
Authors: Салтамигов М.А. , Магомедов И.А.
Published: July 2022

Поиск кубоида, все 7 основных величин которого являются целыми числами, является одной из старых проблем в математике. Часто предлагается свести эту задачу к решению сложных диофантовых уравнений. Однако пока решить данное уравнение не удалось никому. Также существует метод грубого перебора всех возможных ребер данного кубоида. Однако при переборе всех чисел до 3*1012 не было найдено ни одного совершенного кубоида. В данной статье будет собрана информация о некоторых свойствах ребер и диагоналей примитивного совершенного кубоида с доказательствами. Эта информация позволит улучшить алгоритмы поиска этого кубоида или же стать фундаментом для нахождения новых свойств его величин.
КРИМИНАЛЬНЫЙ АНТИГОСУДАРСТВЕННЫЙ ЭКСТРЕМИЗМ: УГОЛОВНО-ПРАВОВЫЕ И КРИМИНОЛОГИЧЕСКИЕ АСПЕКТЫ
Authors: Ибрагимова Э.С.
Published: July 2022

Одной из важных проблем для России и для всего мирового сообщества в целом на сегодняшний день является экстремизм. Это обусловлено, прежде всего, глубинными экономическими, политическими, межнациональными противоречиями, устойчивыми кризисами в политической и социально-экономической сферах, системной нестабильностью, внешними вызовами и угрозами. Разжигая межгрупповые конфликты, экстремизм создает реальную угрозу для общественной безопасности и целостности государства. Поэтому для любого государства крайне важным является принятие мер, направленных на противодействие экстремизму. В статье рассмотрены теоретические и уголовно-правовые аспекты антигосударственного экстремизма, а также деятельность законодательства по противодействию экстремизму.
МИКРОБИОЛОГИЧЕСКАЯ ХАРАКТЕРИСТИКА БАКТЕРИЙ РОДА SERRATIA
Authors: Дохтукаева С.-М.М. , Сулумов С.-М.М. , Эскирханова А.С.
Published: July 2022

На сегодняшний день проблеме изучения бактерий рода Serratia как представителей энтеробактерий не уделяется должного внимания несмотря на то, что серрации часто являются причиной гнойно- воспалительных, урологических, гинекологических и кишечных заболеваний [2, 3]. Также инфекционные процессы, вызванные этими бактериями, нередко развиваются у детей раннего возраста, онкологических больных, и являются причиной внутрибольничных инфекций [4, 5]. Например, S.entomophilas может вызвать оппортунистические инфекции у ослабленных лиц, часто выявляется после инвазивных процедур. В медицинских учреждениях возбудитель может передаваться через руки персонала. Довольно часто S.ficcaria и S.fonticola контаминируют различные растворы для внутривенного введения. Значение серраций в патологии человека и животных до конца не выяснено.
ЦВЕТОЧНАЯ СИМВОЛИКА: ВИДЫ И ЗНАЧЕНИЕ В ЖИЗНИ И КУЛЬТУРЕ НАРОДОВ
Authors: Темаева Х.Н.
Published: July 2022

В ХХ столетии «язык цветов» часто попадал в поле интереса языковедов и литературоведов. Данный феномен стал объектом научного исследования литературоведов и языковедов. Научные работы были посвящены изучению семантики цветочной темы. Проблема селама на материале русской поэзии поэтов ХХ века изучалась фрагментарно и изредка появлялась в научных трудах исследователей. Каждый цветок наделен неповторимым характером, имеет свое лицо. Какие цветы часто встречаются в текстах? И что они символизируют, какую информацию несут читателю? В данном исследовании сделана попытка ответить на эти вопросы. В данной статье показана этимологическая обусловленность названий цветов в связи с особенностями языка, культуры, истории народа; рассмотрена степень изученности флористики и идейной сущности цветочных образов. Проведенное исследование позволило обобщить информацию о гуманитарных и естественнонаучных исследованиях цветочных образов, о месте цветов в древних и современных философиях и в культурной символике. Проведенная работа позволила определить роль архетипа «цветок» в мифах и легендах разных народов.
НЕВЕРБАЛЬНАЯ КОММУНИКАЦИЯ ПРИ ОБУЧЕНИИ ИНОСТРАННОМУ ЯЗЫКУ
Authors: Дзейтова Х.Б. , Махмудов Т.-А.А.
Published: July 2022

В статье рассматриваются некоторые особенности невербальной и паравербальной коммуникации при обучении иностранному языку. Коммуникация делится на лингвистические и внелингвистические аспекты. При изучении иностранного языка предпочтение отдается словесности перед жестикуляцией. В соответствии с возникшими трудностями в преподавании и обучении педагоги и лингвисты вводят новый подход, который облегчает понимание и передачу информации учащимся; преподавание жестов в качестве целевой задачи рассматривается как метод обучения, а не как средство обучения.
РОЛЬ КОММУНИКАТИВНОЙ КОМПЕТЕНЦИИ В ИЗУЧЕНИИ ИНОСТРАННОГО ЯЗЫКА
Authors: Мунгашева М.С.
Published: July 2022

Данная статья посвящена рассмотрению иноязычной коммуникативной компетенции. Подчеркивается необходимость выбора подходящей методики изучения иностранного языка с целью освоения коммуникативной компетенции. Приводится схема компонентов иноязычной коммуникативной компетенции, в рамках которой следует выделять три основных – языковой, речевой и социокультурный. Каждый из них предполагает деление на подкатегории, формирование которых способствует овладению иноязычной коммуникативной компетенции в целом.
ASSESSMENT OF THE SECURITY OF THE NATIONAL ECONOMY OF VIETNAM IN THE IMPLEMENTATION OF A REGIONAL COMPREHENSIVE ECONOMIC PARTNERSHIP. PART 1: ECONOMIC PATRONAGE OF THE GOVERNMENT AND THE STATE BANK OF SOCIALIST REPUBLIC OF VIETNAM
Authors:   Institute of the Far East of the Russian Academy of Sciences, Russian Academy of National Economy and Public Service under the President of Russia, Gordienko Dmitry V.
Published: July 2022

In the context of the intensification of the struggle for leadership between the United States and China and the “turn of Russia to the East”, the task of assessing the security of the national economies of the states of East Asia and other countries of the world in the implementation of global integration projects becomes especially relevant. Vietnam’s participation in the implementation of the Comprehensive Regional Partnership makes it necessary to assess the security of the country’s national economy from external and internal threats. This paper analyzes the prospects for the socio-economic development of Vietnam, as well as its participation in the implementation of the Comprehensive Regional Partnership. The methodological approach is to calculate the normalized indicators of the security of the national economy of Vietnam, which characterize various forms of ensuring its economic security. The proposed approach within the framework of various forms of ensuring the economic security of Vietnam makes it possible to substantiate recommendations for participation in global integration projects of Russia and other countries of East Asia. The results of assessing the security of the national economy of Vietnam in the framework of various forms of ensuring its economic security in the context of anti-Russian sanctions, the intensification of the struggle for leadership between the US and China in the context of relations between the countries of the “strategic triangle” Russia-China-USA can be used to substantiate recommendations to the leadership of our country. It is concluded that the Russian Federation and Vietnam are important strategic partners for each other.
CREDIT RISK ASSESSMENT MODELS AT THE BEHAVIOR-SCORING STAGE
Authors:   Financial University under the Government of Russia, Rozhina Viktoria D.
Published: July 2022

Credit risk management is one of the most important tasks in banking risk management. Credit risk is the possibility of financial losses if the borrower fails to fulfill its obligations in a timely manner and in full, in particular as a result of a delay or non-repayment of a payment on a banking product. This article is devoted to the search for optimal methods for assessing the main component of the credit risk model - the probability of default of the borrower (PD) at the stage of building behavioral models. The paper considers two blocks of mathematical models - quantitative and classification. The object of the study is a portfolio of homogeneous loans of a commercial bank, the subject is the dynamics of the exit of the considered contracts into default. As an effective approach, the author proposes an integrated method for introducing the forecast result obtained using migration matrices as a new variable for the scoring model. Namely, revealing the depth of delinquency, upon reaching which borrowers do not improve the quality of the loan, as a separate predictor that helps to improve the scoring result.
FEATURES OF ASSESSING THE VALUE OF BANKS IN THE MODERN MARKET IN RUSSIA
Authors:   Bauman Moscow State Technical University, Moscow, Russia, Gritsik Polina A. , Volkova Maria V. ,   Bauman Moscow State Technical University, Moscow, Russia
Published: July 2022

The article discusses the key concepts on the practice of bank valuation, the basics and factors influencing this valuation. It is determined that the assessment of the value of a financial institution is influenced by the state of the external environment and economic circumstances, including banking legislation and internal management. The features of the bank valuation method using the discounted cash flow model for dividends are disclosed. The stages of calculating the value of the company are determined. The factors that have the greatest impact on the assessment of a financial company are identified.
MAIN DIRECTIONS OF RISK MANAGEMENT DEVELOPMENT IN THE DIGITAL ECONOMY
Authors:   Saint-Petersburg State University of Aerospace Instrumentation, St. Petersburg, Russia, Makarenko Evgeny A.
Published: July 2022

The article considers the problems of the development of digitalization in the modern world and the problems that this trend brings to society. The key areas in which changes are taking place related to the digitalization of processes are considered and structured, using the example of the activities of insurance companies. Such a factor as a change in the value of quality and volume of information is considered in detail. The main problems of growth in conditions of instability in both the economic and political fields, both in Russia and around the world, are systematized. Conclusions and proposals are made on the directions of reforming the system of economic relations for the sustainable development of the information environment.