bluuebunny/crossref_metadata_2025 huggingface dataset:
Method of quantitative assessment of changes in “critical” levels of elastic-strength parameters of epoxy polymers in the process of natural climatic aging
Authors: Nizina T.A. , Nizin D.R. , Kanaeva N.S.
Published: January 2024

The method for quantitative analysis of the kinetics of damage accumulation in the structure of series of polymer samples at stretching is proposed. The proposed approach is to calculate the fractality indices of time series by means of a minimum coverage method, followed by a failure frequency analysis, while increasing the levels of applied stresses and relative deformations. Epoxy polymer based on ED-20 resin hardened by Etal-1460 hardener, was selected as the object of the study. The results of the study of changes in elastic-strength indicators and levels of “critical” stresses and relative elongation in the stretching of epoxy polymer during the natural climate impact are presented.
Investigation of the impacts of the thickness of the composite material on the temperature regime of energy-saving fencing of the outer wall with closed vertical wind channels
Authors: Zhangabay Nurlan
Published: January 2024

The proposes of investigation are the energy-saving facade structures with closed vertical canals, which were analyzed in ANSYS medium with finite elemental technique. An analysis of temperature lag of designed structures with vertical closed canals evidenced that contraction in frost protection material volume from 0.08 m3 to 0.055 m3 per 1 m2 gives rise to significant contraction in the temperature lag of outer shells in case with a heat directing shield up to 24.55%, and in case without a heat directing shield up to 26.9%. An analysis was also made of the heat directing shield influence on the temperature lag of a new structure, which evidenced that in case of the heat directing shield in vertical closed canals, the structure’s efficiency in terms of temperature lag value increases up to 20%, depending on external climate conditions. Since energy saving is the main problem all over the world, the investigation data can be realized in buildings’ design, construction, reconstruction, with a view to save heat release rate. At the same time, the use of the developed structures with a heat-reflecting screen with closed vertical channels leads to an increase in the temperature lag indicator, depending on external climatic conditions, by 8.5-20%.
Generalized assessment of region environmental state based on mathematico-cartographic modeling with GIS
Authors: Belogurov V.
Published: January 2024

The developed methodology features an uneven distribution of indicator parameters in classes, based on principles of regulation and ecological laws. The problem is solved by the innovative method of mathematico-cartographic modeling, based on GIS-technology using the Geostatistical Analysis ArcGIS. All models are tested according to the Belogurov's RR-criterion of model suitability. Among the many logistic functions, the one for which the rules for the allocation of 5 classes are established, is selected. Mathematical analysis of the expression for the logistic curve made it possible to propose the new authors expression for its description. It contains such parameters as the values of the middle and width of the increasing section of this curve and its maximum value. This set is more visible and convenient for assessing the environmental state. It also corresponds to the typical pollution levels accepted by the Hydro meteorological Service: high and extremely high pollution levels. The maximum efforts and means to improve on the environmental state will be devoted to the first signs of high pollution, preventing the transition from class 2 to class 3. A well-reasoned concept of creating systems for monitoring dangerous trends and managing enterprises in accordance with mining safety conditions has been developed.
Challenges and obstacles to recognizing Artificial Intelligence as a new economic actor
Authors: Abasov Mir Faraj Ali
Published: January 2024

The article offers an in-depth analysis of the role of Artificial Intelligence (AI) in terms of the development of a new Economic Formation. Amid the transformation of classical economic-political systems, a new acting image of the modern formation of digitalism - its new economic actor - Artificial Intellect - emerges. The term “economic agent” is defined, and a comparative historical analysis of applicants for the role of the second economic agent in the history of mankind is made. The author, for the first time relying on the comparative and deductive method of research, provides arguments for the possible emergence of a new economic actor on Earth. And again, for the first time, four main groups of Problems and Obstacles from the Human Community on the path to the recognition of AI as a new economic actor are classified and described. Along with classifying and describing the issues, the author also identifies possible ways to overcome the obstacles and recognize AI as a new economic actor. A wide range of sciences, from economics to philosophy, are involved in solving these problems. Special attention is paid to the elements of psychological and emotional perception of Artificial Intelligence by society.
Development of models for managing the population mass service system in a bank
Authors: Soma Guedes , Kopanitsa Georgy
Published: January 2024

This paper presents models for evaluating the effectiveness of management tasks in Public Service Systems (PSSs), a mathematical model based on the analytical hierarchy process method for distributing elderly and conflicting customers along routes to a specific operator based on the emotional state and age of a customer. The models were trained and tested on the AffectNet and Adience datasets with four classes [angry, happy, neutral, sad] and [6-20, 25-30, 42-48, 60-98]. The accuracy of these models after training achieved in this study was compared with the results described in the scientific papers published in the Scopus Database. According to the experimental data obtained, the first and second developed models achieved validation accuracy of 76.30% and 75.1%, respectively.
Information technologies and their impact on electronic marketing
Authors: Al-Ababneh Hassan Ali
Published: January 2024

The main theoretical hypotheses for studying the characteristics of the influence of information technology on electronic marketing are considered. Using methodological analysis and scientific synthesis, the key components of the strategy and the main trends in the modification of electronic marketing are identified. It is substantiated that the introduction of innovative business management tools in order to optimize business processes and increase profitability leads to a change in the marketing strategy. The influence of information technology on the main trends in changes in electronic marketing has been revealed. The main channels of electronic marketing are argued using information technologies, on the basis of which the main tools of electronic marketing are structured. Methodological approaches to economic and mathematical forecasting of trends in electronic marketing modification under the influence of information technology have been developed, with justification of costs and profitability of implementation. The results obtained and scenarios for forecasting long-term trends in the modification of electronic marketing under the influence of information technology for the next 5 years can be applied in practice when strategically planning a company's marketing.
Assessing and managing risks in the oil and gas industry with machine learning and digital technologies
Authors: Kuleshov V.V. , Aygumov T.G. , Zolkin A.L. , Saradzheva O.V.
Published: January 2024

This article aims to provide a comprehensive overview of the current use of machine learning and digital technologies for risk assessment and management in the oil and gas industry. A comprehensive methodology was used, including a literature review, data collection from academic journals, industry reports, and online sources, data analysis using machine learning algorithms, and results interpretation. The results from the study provide valuable insights into the use of machine learning and digital technologies for risk management, including the effectiveness of machine learning algorithms for modeling and predicting risks and the benefits of IoT and blockchain technology for data collection and analysis. The study highlights that the use of these technologies has the potential to significantly enhance the effectiveness of risk management in the oil and gas industry, but more research is needed to fully understand the benefits and limitations of these approaches and to identify best practices for implementation.
Methods of applying matrices in creating models of group pursuit
Authors: Dubanov A.A.
Published: January 2024

The article deals with the application of matrix modeling to the group pursuit of objects. The article applies matrix modeling to the group pursuit of objects based on models of actual objects' behavior and can be used in simulation modeling packages, virtual simulation of game processes, or transport logistics processes. The results of the article may be in demand in creating virtual reality models of delivery of postal goods by drones in creating an optimized hub - network. The author proposes to consider the model of group pursuit of multiple targets. Methods of pursuit by individual subjects are various modifications of methods of parallel approach, pursuit, and proportional approach. The author constructed a matrix reflecting the number of chasers and the number of targets. The conducted research contains a model of group pursuit of a set of targets. The model contains optimization based on the least time of simultaneous achievement of goals. These results are in the certificate of registration of programs for computers. Objectives assume that in the method of dynamic programming of matrices of distribution of pursuers, we will construct the matrix at each discrete moment, because the number of pursuers and objectives, and their strategies can change at any moment. The methods of forming matrices of distribution of pursuers and goals can be in demand in the design of virtual reality systems for game tasks. Such tasks simulate the process of group pursuit, running away, and evasion. The method of dynamic programming for the distribution matrix of pursuers on targets will allow us to move to an automated distribution process with optimization according to the specified parameters.
Control of a neural network for the operation of small aircraft for agricultural purposes
Authors: Osintsev Konstantin , Karelin Aleksandr , Isaev Viktor
Published: January 2024

We will discuss the impact of various parameters, such as network size and complexity, on accuracy, speed, and efficiency, as well as ways to optimize them. We also analyze the use of deep learning algorithms to detect and classify objects and adjust the navigation of small agricultural aircraft depending on the environment. We also highlight the importance of data preprocessing and how it can be used to improve the accuracy and speed of deep learning algorithms. Finally, we will discuss how deep learning can be used to automate certain tasks, such as detecting and repairing leaks or anomalies, as well as the use of aircraft from other fields, in the field of agriculture.
Approximate solution of non-local boundary value problems for a loaded hyperbolic equation with two fractional differentiation operators
Authors: Beshtokov Murat
Published: January 2024

Nonlocal boundary value problems for the loaded hyperbolic type equation with two fractional differentiation operators are studied. Using the method of energy inequalities for various relations between the orders of the fractional derivative (α, β), a priori estimates in differential and difference interpretations are obtained for the solution of the problem under consideration,which imply the uniqueness and stability of the solution with respect to the initial data and the right-hand side, as well as the convergence of the solution of the difference problem to the solution of the original differential problem at the rate equal to the of approximation.
B-FEF-blockchain based framework to exchange files
Authors: Varfolomeev Alexander , Al-Farhani Liwa
Published: January 2024

Blockchain-based systems have proven to be efficient and capable of resolving the majority of security issues relating to exchange transactions in the system. As a result, it became necessary to move away from the problems of the existence of third parties in the system with an important level of trust; a decentralized method of transferring digital files was created. In this paper we present B-FEF-Blockchain Based Framework to Exchange Files. This solution uses IPFS and the Ethereum blockchain. The suggested method offers irreversible and irreversible records of the transmission and reception of documents. In the work system, it is available to all participants who have successfully registered and depending on the smart contract offered by Ethereum blockchain to start sending and receiving documents according to available applications or needs. In the end, the results of the B-FEF model showed that a single transaction costs about 0.387020062 Ether, that is, it showed a positive side in terms of the total cost rate. Also, in comparison with the methods previously presented in five of the previous researches and based on assessments based on eight basic criteria, the analyses supported our claim that the proposed model fulfills all these criteria. As for the basic trio of confidentiality, integrity and availability analysis, the proposed model proved to meet these fundamentals.
Neural network algorithms optimizing the development of residential neighborhoods
Authors: Prokhorov Vitalii , Salnikov Viktor , Pridvizhkin Stanislav
Published: January 2024

Modern urban planning involves the creation of a comfortable living environment. The success of new neighborhoods depends on factors such as size, location, services, and transport accessibility. However, issues such as project cost and feasibility often limit innovative urban development projects. A systematic analysis, including a morphological approach, can reveal the complexities of such projects. To optimize the efficiency of construction, the project documentation contains input parameters for calculations. Calculations of economic efficiency should take into account the phasing of the project and the stages of the life cycle. To evaluate the effectiveness of a neighborhood, fuzzy logic is used to process parameters such as the attractiveness of the neighborhood. This research focuses on creating a model of a residential neighborhood using neural network algorithms to optimize economic efficiency by adjusting the parameters of design, construction and operation, taking into account the specifics of the life cycle of a construction and investment project. The article suggests the use of neural network algorithms to improve the development of residential neighborhoods, presenting the appropriate model and discussing its features. The relevance and possibilities of developing this approach in the context of planning new neighborhoods are highlighted.
Ecosystems of smart territories: cartographic and economic analysis tools
Authors: Chelak Igor , Popov Evgenij , Skvortsov Maksim
Published: January 2024

In economics, the ecosystem approach becomes the main method of analysing large communities. In this paper, the object of research is the ecosystem of a smart territory (smart ecosystem, i-ecosystem). The subject of the study is economic relations based on the analysis of the results of mapping the ecosystem of a smart territory. We single out economic analysis as the main tool of ecosystem management. The synthesis of mapping the ecosystem of a smart territory and various methods of its analysis allows us to identify key growth points and promising directions of ecosystem dynamics. The problem of the study is the lack of systematization of the directions of ecosystem economic analysis. The purpose of the study is to systematize the directions of economic analysis based on the results of mapping the ecosystem of a smart territory. Logical and systematic methods of research allowed to conduct a content analysis of scientific papers. The research algorithm includes a review of previous studies, formulation of the research problem, systematization of the directions of economic analysis of the ecosystem of a smart territory. The methodological foundation of the research is represented by the system concept, the paradigm of sustainable development, and the ESG approach. The result of the work was a table on the directions of economic analysis of the ecosystem of the smart territory.
Synthesis and study of the antifungal activity of 1-(2-cyanophenyl)-3-heterylureas
Authors: Dunaeva Kristina , Baratova Daria , Kalinina Tatiana , Glukhareva Tatiana
Published: January 2024

In the treatment and prevention of fungal infections of plants, along with fungicides, inducers of systemic plant resistance, also called elicitors, have become particularly important in recent years. In this work, a method was developed for the synthesis of new 3,4-dichloroisothiazol-5-yl and 4-methyl-1,2,3-thiadiazol-5-yl ureas 1,2, containing a 2-cyanophenyl substituent, structurally similar to a known synthetic elicitors isotianil and tiadinil. The protective properties of the obtained compounds on cucumber and pepper leaves infected with B. cinerea, as well as their fungicidal properties against B. cinerea, were studied. It has been established that disubstituted ureas 1,2 exhibit very low fungicidal activity against this fungus, about 11%. At the same time, study on plant leaves showed that compound 2 effectively inhibited the development of gray mold on both cucumber and pepper leaves with an inhibition rate of more than 90%, which was similar to tiadinil. Compound 1 was effective only on cucumber leaves (96.50±0.01%). Isotianil in the experiment showed an average degree of protection – 62.48±1.04% on cucumber leaves and 56.50±1.29% on pepper leaves.
Ways to ensure environmental standards when harmful gaseous substances are released into the atmosphere from drainage networks based on modeling their operation
Authors: Orlov V. , Melnik O.
Published: January 2024

The issues of physical and mathematical modeling of the operation of a pressure-free drainage pipeline made of polymer material and ceramics are studied in order to prevent negative environmental consequences when harmful and toxic gases are released into the atmosphere of cities from the drainage network. Studies of the dynamics of changes in hydraulic and aerodynamic parameters during the flow of liquid and gas in the subsurface space of a ceramic pipeline are presented. An algorithm for solving the problem based on the calculation of hydrodynamic similarity criteria describing the phenomena of mass transfer as a result of forced air convection by using a mechanical ventilation system of aggressive airborne droplet mass over a water surface is compiled. Based on the results of the operation of a special automated calculation program, the total mass of harmful gases released from the water into the subsurface space of the pipeline, the time of removal of hydrogen sulfide entering the subsurface space in concentrations significantly exceeding their maximum permissible values in the city atmosphere, as well as the time of removal of gaseous substances depending on the filling of water in the gravity pipeline are determined.
Risk management in safety standards and environmental management issues of housing construction
Authors: Larionov Arkadij , Smirnova Elena
Published: January 2024

At present, the threat of technogenesis is not weakening despite the measures taken to reduce the levels of negative impact on the environment. In this regard, the authors analyze the standardization of risk management as an effective tool for monitoring the safety of not only design decisions in housing construction, but also any economic activity. The article discusses the safety aspects set out in Russian standards (GOSTs) and international guidelines. The analyzed regulatory documentation answers the question of how to achieve an acceptable level of risk. The basic concepts of risk assessment are given. There are positive changes in state standards in the safety area. Federal Law N7 regulates the leadership of the employer, and not his responsibility. As part of the improvement of environmental management for housing construction, the use of certain penalties, interest fines and forfeits looks quite natural. The main goal of the international standard ISO 14001 is not to point out the need for managers to have leadership qualities as the main factor in ensuring environmental safety for the construction industry, but to form a responsible attitude towards the environment and natural resources as the most important asset of economic activity. The article raises the issue that risk analysts cannot be fully guided by domestic standards due to their lack of development and inconsistency with the universal international documents ISO 31000:2018 "Risk management - Guidelines" and ISO 14001:2016 "Environmental management systems". A special risk assessment approach should be developed that describes the interaction of various scenarios, which will provide an increased environmental and economic effect in the field of housing construction safety.
Desalination and heating of water in heat pumps in the agro-industrial complex
Authors: Solomin Evgeny , Antonova Kseniya , Bolkov Yaroslav
Published: January 2024

Evaporators are widely used in the chemical industry for processes such as distillation, concentration and crystallization. Heat pumps can be used in purpose to increase the efficiency of these processes by using the low-grade heat of the secondary vapors of liquid matter from the last effect of the apparatus. Heat pumps have the capacity to substantially reduce energy consumption in the chemical industry compared to more customary warming techniques, as they necessitate less energy to run. This can reduce the overall energy consumption of the chemical process and help reduce emissions.
Evaporation and desalination using a solar concentrator in an agricultural complex
Authors: Dudkin Maksim , Vasilev Kirill , Kovalyov Anton
Published: January 2024

The purpose of the article is to study boiling and distilling water using solar concentrator, the actual application and profitability of using such a method of liquid evaporation. The use of various modern types of technologies makes it possible to purify water as efficiently as possible, while avoiding the decomposition of compounds. The different configurations of boiling by means of solar concentrator allow meeting different forms of application. Such configuration changes include different types of lenses, as well as different shapes and sizes of the solar concentrator itself, the use of mirror arrays that can be configured in such a way as to direct sunlight to one point to achieve high temperatures.
Methods of air distant control for cadastral works in an agrocomplex
Authors: Mamazhonov Abdulaziz , Sobolkin Sergey , nyakova Olga Kor
Published: January 2024

consider the technical-theoretical side of the work of neural networks on examples get acquainted with different methods of landing and understand their features, their possibilities and disadvantages compared to the standard methods of using manned vehicles. We will tell you about the method of improving the work of neural networks. We will introduce you to the features and importance of using air vehicles in rural industries and local supply organizations in order to improve the quality and speed of work.
Comparison of the K-Means method with and without Principal Component Analysis (PCA) in predicting employee resignation
Authors: Binanto Iwan , Tumanggor Andrianto
Published: January 2024

Employees are individuals who work for a company or organization and receive a salary. Employees are the most important assets that need to be effectively managed by the company in order to maximize their contribution. However, many employees feel dissatisfied with the outcomes of their contributions to the company, as they do not receive the expected rewards. This study utilizes a dataset from Kaggle.com, consisting of a total of 14,999 data rows with 10 attributes. In the first experiment, the dataset was reduced using PCA before applying the K-means clustering method. In the second experiment, the dataset is directly fed into the K-means clustering method without PCA. To evaluate the clusters in the K-means method, this study applies the sum of squared error (SSE) method and the silhouette coefficient method to determine the optimal clusters. The study concludes that there are two dominant factors, last_evaluation and average_monthly_hours, that contribute to employees resigning from a company. The SSE evaluation indicates that both methods have an elbow point at 3 clusters, suggesting that dividing the data into more than 3 clusters does not provide significant additional information. The silhouette coefficient evaluation shows that K-means without PCA obtain the best silhouette coefficient value of 0.5674, while K-means with PCA obtain a silhouette coefficient value of 0.5491. Although K-means with PCA have the advantage of reducing the dimensionality of the dataset, they have a longer execution time compared to K-means without PCA, with an execution time of 181.53 seconds for K-means with PCA and 95.84 seconds for K-means without PCA.
Environmental management for car accident precaution and remote notification
Authors: Reinaldy Gerardo , Rhatodirdjo Angka Peter , Gunadhi Albert , Pranjoto Hartono , Yuliati  , Sitepu Rasional
Published: January 2024

Cars have been utilized as reliable means of transportation beyond the capacity of motorcycles. However, the misuse and abuse of these vehicles through unsafe practices like speeding and reckless driving poses a great risk that results in accidents – and sometimes – with casualties. In such unfortunate circumstances, the importance of prompt accident notification is extremely important for the driver. This notification should encompass vital accident details and precise location information. Thus, the implementation of a comprehensive system for accident warnings and the remote transmission of accident data emerges as an imperative safety measure. In this system, accidents are assessed based on the vehicle's slope relative to the road and speed. The vehicle's slope is measured using ultrasonic sensor, which calculates the ground clearance distance at two different locations of the vehicles. The two sensors will provide warning when there is a difference of more than 3 cm. Speed is measured using GPS, with the limit set at 90 km/h. If crashed occurs, Airbag Sensor gives logic ‘1’, then GPS will take current coordinates and date of the accident, then sends it via SIM800L in SMS format to registered number. Thus, the dangerous condition signed by 4,7 cm difference marked by Red LED and formed 7o angles which caused by excessive maneuver while GPS has 95% accuracy with speedometer. Thus, this voice output sure be great while quiet environment which output quality is 45dB at conversation environment.
Classification of delivery type of pregnant women using support vector machine
Authors: Chelsea Maria Yubela , Rosa Paulina H. Prima
Published: January 2024

One of the ways to reduce maternal mortality is by diagnosing childbirth to find out whether a mother will give birth normally or not so that appropriate treatment can be done. This study aims to improve maternal safety and health by classifying delivery type of pregnant women, either Caesarean or normal types, using the Support Vector Machine method. The dataset used in this study was taken from a hospital in 2020. It consists of 25 attributes and 302 records that include information about the health conditions of pregnant women and babies. Several experiments were performed towards the dataset with and without balancing. Three types of SVM kernels, namely Linear, RBF, and Polynomial kernels, were then implemented to classify the dataset using several variations of parameters of C, gamma, and degree. The validation was performed using several k-fold cross validations. The results of this study show that the highest accuracy is 92.98% at 5-fold cross validation using the RBF kernel with parameters C = 10 and gamma = 1. The performances of the three SVM kernels varied depending on the type of data used.
Numerical investigation on the effect of blunt body deflector on darieus turbine performance
Authors: Rofi’i Ahmad Syafiq , Aulia Aditia , Fadri Muhammad Ferry , Syarif Muhammad Haidar , Rahman Elvira Rosmawati , Haryadi Gunawan Dwi
Published: January 2024

One of the renewable energy source that is abundant but has not been used optimally is wind energy. Roads are currently the main transportation infrastructure along with the increasing number of motorized vehicles. Wind is one of the best renewable energy sources that can be utilized on the highway where it can be used as a power source to drive the Vertical Axis Wind Turbine (VAWT). Darrieus type turbines can operate at low wind speeds and do not require a specific wind direction. However, the installation of this wind turbine on the highway can be hampered due to the presence of highway light poles. We simulate a light pole as a blunt object placed in front of the turbine which will then be observed for the ratio of torque produced to compare the performance of the turbine with a blunt body and without a blunt body. This study aims to determine the effect of the diameter ratio and distance between the turbine and the blunt object on the torque generated on the rotor. This research uses CFD simulation on NACA 4415 foil. The results showed that placing a blunt object in front of the Darrieus turbine increased the turbine torque. The most optimal increase in torque is obtained at a distance of 700 mm with a blunt body diameter of 0.6 DT or 0.3 DT which can increase the torque output of the turbine.
Machine learning based modeling for estimating solar power generation
Authors: Uddin Nur , Purwanto Edi , Nugraha Hari
Published: January 2024

The solar power plant is a rapidly growing renewable energy source that has a potential role in reducing climate change and replacing fossil fuels. Estimation of the power generated by a solar power plant is required to determine the energy supply. Unfortunately, the solar power generated is highly uncertain due to highly dependence to nature, such as solar radiation and weather. This makes the estimation of solar power generation to be very difficult. This study presents a development of machine learning to model a solar power plant for estimating the generated power. The machine learning is developed by implementing the k-NN algorithm. A data set of power generated in a solar power plant is applied to build the machine learning. The development resulted in a machine learning that models the solar power plant. Simulation test result show the machine learning was able to estimate the solar power generated with an accuracy of 69.6%. The developed model is very useful to estimate potential of solar power resource in a region. The developed model is very useful in feasibility studies to estimate the potential of solar power resources in an area.
Assessing the effectiveness of agricultural policies on development: A systematic literature review from diverse countries
Authors: Guindo Tidiane , Hak Muhamad Bai’ul
Published: January 2024

This research strives to evaluate the efficacy of farm-related policies in promoting development by conducting a global analysis across diverse nations. The assessment seeks to distill invaluable insights through a comparative examination of agricultural policies implemented in various countries. The research employs a systematic literature review as its methodology. This comprehensive review systematically scrutinizes the impact of agricultural policies on development, with a specific focus on a carefully chosen set of countries: Mali, Cameroon, South Africa, Indonesia, Vietnam, the United States, European nations, and Brazil. The study encapsulates the lessons gleaned from these nations' experiences in bolstering their agricultural sectors to achieve objectives such as economic advancement, food security, environmental responsibility, poverty reduction, and rural community development. By synthesizing and contrasting findings from a multitude of studies, this research strives to furnish a holistic comprehension of the outcome of agricultural policies on development outcomes. Through a nuanced analysis pertaining to the strengths and weaknesses of these countries' agricultural policies in the context of development, this research seeks to offer useful understandings to shape future policy decisions and further the cause of agricultural development on a global scale.
Readiness assessment of lean six sigma implementation in the manufacturing industry as a way to ensure sustainability
Authors: Dewi Fransisca Candra , Hartanti Lusia Permata Sari , Dewi Dian Retno Sari , Mulyono Julius , Mulyana Ig. Jaka
Published: January 2024

Lean Six Sigma (LSS) is a strategy to overcome the problems that occur to improve the efficiency and effectiveness of the company through the elimination of variation and waste. efficiency and effectiveness will ensure the sustainability of the company. Several factors affect the success of LSS implementation in the company. Therefore, to be successful in LSS implementation, an assessment is needed to measure the level of LSS readiness (Lean Six Sigma Readiness/LESIRE). This article discusses the measurement of the readiness level of the plastic industry in Indonesia in the implementation of LSS. In addition to measuring the level of readiness, this article also discusses what important factors must be prepared in advance to be ready for LSS implementation. Data was collected by distributing questionnaires and processed using the fuzzy method. Factors that influence success consist of 5 enablers, 19 criteria, and 55 attributes. The results showed that the industry studied was categorized as Almost Ready. Attributes that need to be improved to increase LSS readiness are company initiatives in development, learning processes in development, improving workforce skills, customer-focused organizations or companies, strategic and visionary leadership, responsibility, authority and communication, planning, feedback loop design, eliminating waste, high impact of customer satisfaction, and technology improvement.
Un cas de péricardite hémorragique aseptique idiopathique chez une vache Prim’Holstein de 3 ans
Authors: Collin Floriane
Published: January 2024

Une vache Prim’Holstein de 3 ans, est référée le 17/11/2022 aux hôpitaux de médecine des animaux d’élevage d’Oniris pour suspicion de péricardite traumatique par corps étranger évoluant. Les signes évoluent depuis un mois et demi, avec dans un premier temps une chute en lait et un avortement à 7 mois de gestation. L’examen clinique met en évidence des signes marqués d’insuffisance cardiaque congestive droite, une atténuation bilatérale des bruits cardiaques, une matité des bruits respiratoires à droite crânio-ventralement, une diarrhée liquide malodorante sans éléments figurés et des signes de douleur ou d’inconfort.

Une échocardiographie révèle un épanchement péricardique anéchogène, de 10 cm de profondeur et une tamponnade. La mise en place d’un drain péricardique permet l’écoulement progressif de 5,5 litres d’un épanchement hémorragique inodore. Les analyses cytologiques et bactériologiques mettent en évidence un exsudat de type hémopéricarde inflammatoire aseptique pouvant correspondre à une péricardite idiopathique ou un traumatisme vasculaire au niveau du péricarde. Une échographie pulmonaire met en évidence un épanchement pleural focal anéchogène en portion crânio-ventrale à droite. L’analyse révèle un exsudat aseptique compatible avec une insuffisance cardiaque droite.

L’évolution est favorable : augmentation de l’appétit, disparition de la diarrhée en 3 jours, et réduction des signes d’insuffisance cardiaque droite après 10 jours. Les contrôles échocardiographiques montrent un épanchement stable de 2 cm de profondeur et une disparition de la tamponnade. Après un gain d’environ 30 kg, la vache est abattue, avec absence de saisie.
Direct-Acting Oral Anticoagulants in patients at extremes of body weight: a review of pharmacological considerations and clinical implications
Authors: Talerico Rosa , Pola Roberto , Klok Frederikus Albertus , Huisman Menno Volkert
Published: January 2024

Patients at extremes of body weight are underrepresented in randomized controlled trials of direct-acting oral anticoagulants (DOACs). Therefore, their optimal anticoagulant treatment remains a topic of debate.

The aim of this narrative review is to summarize the evidence on the pharmacokinetic and pharmacodynamic profile of DOACs for treating patients at extremes of body weight in venous thromboembolism (VTE) and in the prevention of cardioembolic stroke in nonvalvular atrial fibrillation (NVAF). A literature search was conducted in the main bibliographic databases, and the most relevant reviews and original articles on the topic were selected.

Although data in these patient groups are limited, apixaban and rivaroxaban show a favorable pharmacokinetic and pharmacodynamic profile in obese VTE treatment and NVAF patients and, in the case of apixaban, also in underweight patients. In particular, these drugs demonstrated comparable efficacy and safety to standard therapy. Very few data were available for dabigatran and edoxaban; the latter drug was safer at a lower dose, mainly in underweight patients.

Our findings are in line with the last International Society of Haemostasis and Thrombosis position paper and European Heart Rhythm Association 2021 practical guide, suggesting the use of apixaban and rivaroxaban in morbidly obese patients (>120 kg or body mass index ≥40 kg/m2) and the reduced dosage of edoxaban in low-weight patients. Future studies should focus on large populations of patients at extremes of body weights to acquire more clinical and pharmacokinetic evidence on all available DOACs, especially those currently less investigated.
Comparative analysis of single-crater parameters in ultrasonic-assisted and unassisted micro-EDM of Ti6Al4V using discharge plasma imaging
Authors: Raza Sohaib , Nirala Chandrakant
Published: January 2024

Ultrasonic-assisted micro-electro-discharge machining (μEDM) has the potential to enhance processing responses such as material removal rate (MRR) and surface finish. To understand the reasons for this enhancement, the physical mechanisms responsible for the individual discharges and the craters that they form need to be explored. This work examines features of craters formed by single discharges at various parameter values in both conventional and ultrasonic-assisted μEDM of Ti6Al4V. High-speed imaging of the plasma channel is performed, and data on the individual discharges are captured in real-time. A 2D axisymmetric model using finite element software is established to model crater formation. On the basis of simulation and experimental results, a comparative study is then carried out to examine the effects of ultrasonic vibrational assistance on crater geometry. For every set of μEDM parameters, the crater diameter and depth from a single discharge are found to be higher in ultrasonic-assisted μEDM than in conventional μEDM. The improved crater geometry and the reduced bulge formation at the crater edges are attributed to the increased melt pool velocity and temperature predicted by the model.
Completing the perspectives on cell migration with mechanobiology
Authors: Lange Katherine De
Published: January 2024

Mechanobiology holds the key to answering many unresolved questions on cell migration.
Investigation of thermoelectric and magnetotransport properties of single crystalline Bi2Se3 topological insulator
Authors: Singha Pintu , Das Subarna , Rana Nabakumar , Mukherjee Suchandra , Chatterjee Souvik , Bandyopadhyay Sudipta , Banerjee Aritra
Published: January 2024

The realization of remarkable thermoelectric (TE) properties in a novel single-crystalline quantum material is a topic of prime interest in the field of thermoelectricity. It necessitates a proper understanding of transport properties under magnetic field and magnetic properties at low field. We report polarized Raman spectroscopic study, TE properties, and magneto-resistance (MR) along with magnetic characterization of single-crystalline Bi2Se3. Polarized Raman spectrum confirms the strong polarization effect of A1g1 and A1g2 phonon modes, which verifies the anisotropic nature of the Bi2Se3 single crystal. Magnetization measurement along the in-plane direction of single crystal divulges a cusp-like paramagnetic response in susceptibility plot, indicating the presence of topological surface states (TSSs) in the material. In-depth MR studies performed in different configurations also confirm the presence of anisotropy in the single-crystalline Bi2Se3 sample. A sharp rise in MR value near zero magnetic field and low-temperature regime manifests a weak anti-localization (WAL) effect, depicting the quantum origin of the conductivity behavior at low temperature. Moreover, in-plane magneto-conductivity data at low-temperature (up to 5 K) and low-field region (≤15 kOe) confirm the dominance of the WAL effect (due to TSS) with a negligible bulk contribution. Quantum oscillation (SdH) in magneto-transport data also exhibits the signature of TSS. Additionally, an exceptional TE power factor of ∼950 μW m−1 K−2 at 300 K is achieved, which is one of the highest values reported for pristine Bi2Se3. Our findings pave the way for designing single crystals, which give dual advantages of being a good TE material along with a topological insulator bearing potential application.
A numerical study of the influence of the wave reflection on the hydrodynamic characteristics of a cylinder with moonpool
Authors: Han Jian , Zhang Xinshu
Published: January 2024

We develop a new numerical model based on eigenfunction matching method and the method of images to investigate the influence of tank wall reflection on the hydrodynamic behaviors of a cylinder with moonpool, which is defined as an opening from the deck to the bottom of a floating structure or ship. The new numerical model is first validated by comparing its results to experimental data in the existing literature and WaveAnalysisMIT results and then is used to analyze the effects of different tank widths on the heave radiation and diffraction problems. When the tank is not too narrow, the results only show a significant difference from those in open water around the transverse sloshing frequencies of the tank, i.e., when the tank width is an integer times the wavelength. It is noticed that the reflection effects induce spikes of the amplitude of free-surface elevations at the center of the moonpool in the radiation problem but induce troughs in the diffraction problem. This is explained by estimating the phase of the waves in moonpool induced by the wall reflections. For the narrow tank that does not allow transverse sloshing in the given frequencies, the results deviate from those in open water in a width range of frequencies. The free-surface elevations outside the cylinder are also investigated.
Learning the stable and metastable phase diagram to accelerate the discovery of metastable phases of boron
Authors: Balasubramanian Karthik , Banik Suvo , Manna Sukriti , Srinivasan Srilok , Sankaranarayanan Subramanian K. R. S.
Published: January 2024

Boron, an element of captivating chemical intricacy, has been surrounded by controversies ever since its discovery in 1808. The complexities of boron stem from its unique position between metals and insulators in the Periodic Table. Recent computational studies have shed light on some of the stable boron allotropes. However, the demand for multifunctionality necessitates the need to go beyond the stable phases into the realm of metastability and explore the potentially vast but elusive metastable phases of boron. Traditional search for stable phases of materials has focused on identifying materials with the lowest enthalpy. Here, we introduce a workflow that uses reinforcement learning coupled with decision trees, such as Monte Carlo tree search, to search for stable and metastable boron phases, with enthalpy as the objective. We discover new boron metastable phases and construct a phase diagram that locates their phase space (T, P) at different levels of metastability (ΔG) from the ground state and provides useful information on the domains of relative stability of the various stable and metastable boron phases.
Photoluminescence enhancement from hot nitrogen-ion implanted Si quantum dots embedded within SiO2 layer
Authors: Mizuno Tomohisa , Murakawa Koki
Published: January 2024

Using the novel process of hot N+-ion implantation at 800 °C into Si quantum dots (Si-QDs) with approximately 3.2 nm fabricated by hot Si+-ion implantation into an SiO2 layer and post-Ar annealing, we experimentally demonstrated that the photoluminescence intensity (IPL) of the Si-QDs increased with increasing N+-ion dose (DN+). Post-N2 high-temperature annealing without hot N+-ion implantation, as a reference process, also increased the IPL of Si-QDs, because N atoms trapped within Si-QDs, which was evaluated by secondary ion mass spectrometry, terminate the dangling bonds within Si-QDs and at the Si/SiO2 interface. Additionally, the IPL of Si-QDs showed the maximum value at the optimal DN+ of 5 × 1015 cm−2, which was 1.4-fold higher than that observed without hot N+-ion implantation. With a short post-annealing time (<60 min), the increase in IPL owing to N+-ion implantation was considerably larger than that caused by N2 annealing, which is likely due to the efficiency of the termination of the dangling bonds of the Si-QDs by the N+-ions. This is an advantage of the hot N+-ion implantation technique. Forming gas annealing after furnace annealing also induced a larger IPL than that observed before forming gas annealing. However, the maximum IPL observed after forming gas annealing was completely independent of the conditions of furnace annealing and DN+. This suggests that the perfect termination of the dangling bonds of the Si-QDs may be realized via forming gas annealing after furnace annealing.
Sand particle characterization and identification in annular multiphase flow using an intelligent method
Authors: Wang Kai , Tian Jiaqi , Chang Ziang , Qin Min , Fu Guangming , Lu Jiaqi , Yang Kui
Published: January 2024

The intelligent recognition and monitoring of sand particles in annular multiphase flow are of paramount importance for the safe production of high-yield gas wells. In this study, an experiment based on a uniaxial vibration method was initially designed to collect collision response signals between sand particles and the pipe wall. Utilizing wavelet packet analysis, the identification and classification of sand-carrying signals in the liquid film and gas core regions were first achieved. The results indicate that the excitation frequency range for sand-carrying signals impacting the pipe wall in the liquid film region was 19.2–38.4 kHz, while in the gas core region, it was 38.4–51.2 kHz. Finally, convolutional neural network (CNN) models, support vector machine (SVM) models, and CNN-SVM models were constructed to characterize and identify sand particles in annular multiphase flow. The results show that the CNN-SVM model improved the accuracy of sand-carrying data recognition by 2.0% compared to CNN and by 5.6% compared to SVM for gas core region data, and by 1.8% compared to CNN and by 8.6% compared to SVM for liquid film region data. Consequently, this research offers a high-accuracy recognition and classification method for sand particles in the gas core and liquid film regions of annular multiphase flow.