bluuebunny/crossref_metadata_2025 huggingface dataset:
The Position of Informed Consent Between Midwives and Patients in Childbirth According to Law Number 17 of 2023 Concerning Health
Authors: Anugrah Maharani , Maulana Siregar Abdul Rahman
Published: May 2024

Medical procedures carried out by midwives often entail uncertainties and un-predictabilities, such as postpartum hemorrhage, shock, or neonatal asphyxia. Patient consent for each medical procedure is an absolute necessity, except in emergency situations. This study aims to analyze the legal relationship between midwives and patients during childbirth and examine the role of informed consent for medical procedures between them in accordance with Law No. 17 of 2023 concerning Health. The research adopts a normative juridical approach, which involves examining legal norms present in legislation, court rulings, and societal legal standards. The data collection method utilized is library research, which involves seeking theoretical foundations and research inquiries. The data includes primary legal materials obtained from Law No. 17 of 2023 concerning Health and other relevant legislation, secondary legal materials sourced from books, documents, legal scholarly works, and the internet, as well as tertiary legal materials providing clarifications regarding primary and secondary legal sources. Justice is the fundamental principle requiring equitable and unbiased information dissemination to all patients. Midwives are expected to refrain from discrimination and provide suitable explanations to every individual. In the realm of justice, healthcare providers hold the responsibility to ensure fair treatment for every patient, irrespective of their social, economic, or cultural backgrounds. Every individual possesses the right to receive clear and comprehensive explanations regarding the forthcoming medical procedures.

Keywords: Informed Consent, Midwife, Patient, Childbirth
Oral Manifestations of Metabolic Disorders -
A Comprehensive Review
Authors: Gopal Saraswathi , B.K. Harini
Published: May 2024

Metabolic disorders encompass a wide range of conditions affecting various biochemical pathways within the human body. While these disorders primarily manifest systemic symptoms, they can also significantly impact oral health and oral cavity structures. This review aims to explore the diverse oral manifestations associated with metabolic disorders, including but not limited to diabetes mellitus, hyperparathyroidism, hypothyroidism, and various storage diseases. These oral manifestations may present as changes in the gingiva, teeth, salivary glands, mucosal tissues, and periodontal tissues. Additionally, metabolic disorders can influence the healing process following oral surgeries and affect dental treatment outcomes. Understanding these oral manifestations is crucial for dental practitioners to provide comprehensive care and collaborate effectively with medical professionals in managing patients with metabolic disorders. This review consolidates existing literature on the topic and underscores the importance in addressing the oral health needs of individuals with metabolic disorders.

Keywords: Metabolic syndrome, Carbohydrate metabolism, porphyria, Amyloidosis, eosinophilic granuloma.
The Legend of Merga Purba Ethnic Batak Karo: A Psychological Study of Literature
Authors: Valentin Sinurat Gabriella Putri , Ginting Rosita , . Herlina
Published: May 2024

This research aims to describe the intrinsic elements and describe the aspects of id, ego, superego in the character of the Legend of Merga Purba Ethnic Batak Karo. The method used in this research is descriptive qualitative method. This research uses Sigmund Freud's psychoanalysis personality theory. Based on the results of the research found, namely: (1) Intrinsic elements in the legend of Merga Purba Ethnic Batak Karo: theme, plot, setting, characterization, point of view, and mandate. (2) In addition, the research also produced the personality structure of id, ego, and superego found in the characters of Merga Purba, King Purba, Dukun Sakti Guru Pakpak Pitu Sedalanen, Angel, Snake and bird, Penghulu Kampung, in the Legend of Merga Purba Ethnic Batak Karo.

Keywords: Merga Purba Legend, Batak Karo Ethnicity, Literary Psychology.
Case Report: EEG Picture in a Patient with Post-Stroke Epilepsy
Authors: Arismunandar Muhammad , Ayu Meidiary Anak Agung
Published: May 2024

Introduction: Epilepsy is a chronic brain disorder that affects people all over the world. Seizures are the most common neurologic symptom in stroke patients. Approximately 10% of all stroke patients have experienced seizures, and post-stroke seizures generally begin several years after the stroke.
Case Illustration: A male patient, 55 years old, Balinese, Kinan, came to the emergency room of Prof. Dr. I.G.N.G. Ngoerah General Hospital with complaints of seizures. The first seizure occurred on December 19, 2021, with a pattern of glancing at the left eye then, followed by full-body twitching, which lasted approximately 5 minutes and stopped on its own. The patient said that before the seizure, the patient was well conscious; during the seizure, the patient was unconscious, and after the seizure, the patient regained consciousness as before the seizure. Then, the seizure repeated the next day (December 20, 2021) with the same pattern and duration, but the patient was not taken for treatment. On physical examination, the patient was alert with vital signs and general physical examination within normal limits. Neurologic examination revealed no focal neurologic deficits. Electroencephalography (EEG) examination showed intermittent slow activity in the left and right fronto-centro-occipital areas. Computed tomography scan (CT-Scan) examination of the head without contrast revealed a hypodense image in the right temporo-parietal lobe. The patient then received anti-epileptic drug (OAE) therapy, OAE therapy given Phenytoin 200 mg every 12 hours intra-orally, Folic Acid 1 mg every 24 hours intra-orally, and anti-platelet and anti-hypertension continued.
Discussion: Post-stroke seizure (PSS) is an episode of convulsion that occurs either single or multiple after a stroke, which is thought to be due to irreversible or reversible brain damage. At the same time, post-stroke epilepsy is convulsions after a stroke that occur at least two revivals without provocation with a distance between revivals of more than 24 hours. PSS classification is divided into early post-stroke seizure, where seizures occur onset two weeks early post-stroke, and late (delayed) post-stroke seizure if seizures occur onset after two weeks post-stroke. Post-stroke seizures' most common electroencephalography (EEG) waves are generalized slow waves, focal slowing, focal sharp and slow waves, and periodic lateralized epileptiform discharges (PLEDs). However, 5.1% of patients have normal EEG. The administration of anti-convulsants to prevent recurrent seizures is recommended by the European Guidelines of The European Stroke Organization. In comparison, prophylaxis is not recommended for patients with post-stroke.

Keywords: Post-stroke Epilepsy, Stroke, Electroencephalography
Equilibrium analysis in game theory using nonlinear functional analysis techniques
Authors: Xiaoqin Li
Published: May 2024

Game theory provides a mathematical framework for analyzing the tactical choices of rational decision makers. The idea of equilibrium, which states that no player has a motivation to change their existing approach given the strategies of other players, is one of the core ideas of game theory. This study examines a type of undirected graph-based distributed quadratic game. The problem of communication topology constraints is presented and nonlinear dynamics with uncertain time-dependent perturbations are present in the participant's dynamics. Based on a high-gain observer approach, a distributed Nash equilibrium (NE) finding technique is given, and the Lyapunov stability theory is used to study the convergence. It represents that every player approximates the positions of their rival players and that there are differences between the NE and the placements of the minor limitation that finally restricts the players. In addition, chattering problems are eliminated since the offered theory's formulation employs the hyperbolic tangent function to control the perturbation rather than the signum function. In an imitation of the oligopoly match, five enterprises manufacture identical materials in a duopoly market framework; this is done to confirm the effectiveness of the recommended strategy. Our results provide novel perspectives and methods for understanding complicated strategic situations, helping to close the gap between mathematical theory and real-world applications.
Research on the Application of Image Processing and Image Recognition Algorithms in Digital Media in Content Editing and Production
Authors: YiJin Wu
Published: May 2024

Image processing and image recognition algorithms are essential to content generation and editing in the digital age. They provide creative ways to improve visual quality, streamline processes, and customize user interfaces. In-depth methods for incorporating cutting-edge image processing and image recognition algorithms into digital media content production and editing workflows are covered in this study. Methods: To maximize visual quality, the research first focuses on pre-processing and improving digital images using the median filtering technique. The Histogram of Oriented Gradients (HOG) technique is applied to locate and identify the objects in images, that enabling customized and interactive content modification. After that, the images are segmented using the watershed approach, and the precise classification of the images is achieved by applying the Mayfly Optimized Spatial Graph Recurrent Neural Network (MOSGRNN), which improves content organization and retrieval.  Results: The results of the experiments demonstrate that the suggested strategy performs well in all aspects of image processing in terms of accuracy (94.91%), recall (92.70%), recognition speed (44 FPS), and f1-score (93.7%). Conclusion: Content production, editing, and delivery across a variety of platforms might be significantly transformed by research on image processing and image recognition algorithms in digital media.
CMOS Based Voltage Reference Designs for Sub - 1V
Authors: Garima Kapur
Published: May 2024

This review paper presents an analysis of the most recent advancements in sub-1V voltage references, addressing the growing demand for ultra-low power consumption and high precision in modern integrated circuits (ICs). Voltage references are critical components in numerous applications, including IoT devices, wearable electronics, and energy-harvesting systems, where power efficiency and accuracy are paramount. It briefly discusses the challenges associated with designing voltage references at such low voltages, such as limited headroom, reduced noise margin, and process variations. Topics include high-order curvature compensation, modified differential pair configurations, and energy-efficient solutions for integrated energy harvesting. These advancements enhance precision and reliability in low-voltage circuits, paving the way for sustainable, low-power electronics and compact devices in the modern digital landscape. It emphasizes the importance of benchmarking different designs against criteria such as power consumption, line regulation, temperature stability, and supply voltage rejection ratio (PSRR). The paper include insights into the state-of-the-art sub-1V voltage reference designs, identification of design trade-offs, and recommendations for future research directions. It underscores the importance of continuous innovation in voltage reference design to address the evolving requirements of ultra-low power electronics. The study here is setting the stage for a detailed analysis of the latest developments in sub-1V voltage references.
ZnCl2 activated Tomato waste derived porous carbon material for high power density for flexible supercapacitor applications
Authors: Yakub Banothu
Published: May 2024

Developing economic and efficient energy storage devices is crucial in the shift towards sustainable energy solutions. Our present work explores the potential of utilizing decayed tomato as a sustainable precursor to produce activated porous carbon electrodes in the construction of supercapacitors. By utilizing the carbonization-activation process and carefully adjusting the preparation parameters, we have achieved an excellent specific surface area (SSA) of 880.33 m2 g-1. This tomato waste char (TWC) predominantly consists of nanopores with a total pore volume of 0.5713 cm3 g-1 and an average pore diameter of about 2.5958 nm. These parameters play a vital role in determining the supercapacitor behavior of the sample. A specific capacitance of 110 F g-1 at 1 mA has been recorded. Furthermore, an energy density of 14.97 Wh kg-1 at 1 mA is observed. This work has reported a high-value power density of about 4163.4 W kg-1 using a symmetric type supercapacitor.
Lrfe: A Novel Local Response Feature Elimination Process for Identification of Lung Cancer Cells
Authors: Chintha Vishnu Vardhana Reddy
Published: May 2024

One of the main causes of cancer-related mortality across the globe is lung cancer.  Early-stage lung cancer frequently exhibits no symptoms, which delays diagnosis until the illness has progressed. Before symptoms manifest, screening and early detection techniques can aid in the early diagnosis and treatment of lung cancer. Many olden research papers have implemented image processing and few latest papers have implemented computer vision techniques to detect lung cancer. Particularly when dealing with minor or subtle anomalies, image processing algorithms may not be able to detect lung cancer lesions with sufficient sensitivity and specificity. It is still difficult to increase the detection algorithms' accuracy and dependability, especially when dealing with early-stage lesions or situations where attributes overlap. It takes a lot of processing power, such as high-performance GPUs and enormous memory capacities, to train deep learning models, particularly large-scale convolutional neural networks (CNNs). In this proposed research, the model pre-processes the images using the ostu and sober filter mechanisms because Otsu's approach adjusts to the features of the input image, including noise, contrast, and lighting fluctuations. It is capable of handling images with varying dynamic ranges and intensity distributions without depending on pre-established threshold settings. When it comes to image noise, the Sobel filter is more resilient than other edge detection methods. It produces clearer edge maps and fewer false detections by determining the gradient magnitude, which amplifies edge information while suppressing noise. The features are extracted using the tuned AlexNet pre-trained model, in AlexNet there is a layer known as “Layer-wise Relevance Propagation”. By giving each pixel or feature in the input image a relevance score, the LRP layer offers fine-grained feature attribution. This makes it possible to analyze in great depth which particular elements or areas of the input image are most important for the network to forecast, which helps to clarify the underlying patterns that the network has learned. At last, the extracted features are further reduced using the enhanced feature elimination method. By iteratively selecting subsets of features based on their importance, RFE helps to identify the most relevant features for the classification task. Integrating RFE with SVM classifiers can lead to improved model performance by focusing on the subset of features that are most discriminative and informative for the classification problem.
Title
Authors: Author1
Published: May 2024

Abstract
A Novel Support Vector Machine based Improved Aquila Optimizer-based Text Mining Mechanism for the Healthcare Applications
Authors: Sultanuddin S. J
Published: May 2024

Social media acts as one of the biggest contributions in every field. In healthcare applications it helps to estimate the quality of the services provided by different hospitals and doctors. Using the text mining technique, the services are analyzed. Several text mining techniques were performed in recent times. However, the effectiveness of text mining in the healthcare field is still a complicated task. Hence, we propose a novel Support Vector Machine (SVM) based Improved Aquilla Optimizer (IAO) algorithm to enhance the text mining from the reviews in the social media. Using this patient can easily evaluate the quality and services of particular clinics and doctors. The work includes the preprocessing of the dataset collected and then discriminative least square regression (DLSR) for the extraction of features from the preprocessed data. Experimental analysis is conducted to analyze the performance of the proposed work. The results are compared with state-of-art works with different performance metrics. Thus, our proposed work can be used to mine the text for the healthcare applications.
NDVI prediction using Machine learning after Geofencing on satellite data of Sugarcane crop
Authors: Mansi Kambli
Published: May 2024

The manual fencing of the crop is too tedious and time-consuming for the farmers. The farmers have to physically see that they are not crossing the boundaries and usually, farmers fight related to the plots. In this paper focus is on the satellite data imagery of Satara district and if geofencing is done for sugarcane crops then monitoring the crop is comparatively easy and analysis can be further done related to sugarcane plots. Geofencing helps then to have the precise data of the farmer and boundaries can be detected to avoid hassles. The Cane plots that have been geofenced can then be labeled according to the plots of the farmers, thus streamlining th classification process. The digitization of the farmer plots is used in this paper and converted into shape files by using GIS which helps to do the further analysis of the crop. Further after doing the pre-processing by using GIS, the Normalized Difference Vegetation Index (NDVI) is predicted prior using Machine learning technique in python. The NDVI actual and predicted for one life cycle of sugarcane is shown in the paper. The NDVI predicted values can be helpful for sustainable agriculture of sugarcane crop in terms of disease detection, cane classification and prediction also. The Machine learning   algorithms can be applied further and the geofencing can be done district wise in future scope along with the vegetation   indices.
Evaluation and Operation of Various DC-DC Converter Topologies with Effective MPPT in a Photovoltaic System
Authors: Vishal G. Jotangiya
Published: May 2024

This article describes the reliable and efficient DC-DC converter for Renewable Energy Sources. The system will function more accurately when the solar panel's irradiance is low. The Maximum Power Point Tracking (MPPT) control algorithm is used to operate the similar system in order to achieve greater efficiency. The characteristics curves for solar panel current v/s voltage (I–V) and power v/s voltage (P–V) are produced by MATLAB simulation. The curves derived from the experiment results are also compared to the simulation curves. A thorough analysis of solar-fed DC–DC converters (Boost, Push-Pull, and Coupled Inductor based converter) is also carried out. The proposed converters are simulated in MATLAB. Simulation results are presented and discussed. Results demonstrate the validity of the models.
The Effect of Data Quality on Decision-Making. A Quasi Experimental Study
Authors: Afnan Alabduljabbar
Published: May 2024

The current study aimed to investigate the relationship between data quality dimensions (completeness and timeliness) and decision-making efficiency. The researcher adopted the quasi-experimental approach to answer the research questions and hypotheses. The study participants consist of 60 subjects, distributed into 2 groups. The first group consisted of 20 sales executives from Saudi beverage manufacturing companies. The other group had 40 participants from Al-Imam university. The study experiment consisted of 4 scenarios, two for each dimension, that give the participants scenarios and ask them to make the best decision based on these data. The scenarios were applied through face-to-face meeting and time to take decisions was recorded by participants. For the first data quality dimension, completeness of data, both groups got scenarios where complete and incomplete data were offered, and they were asked to choose the best available option based on the offered data. For the second dimension, the groups were offered up-to-date data and obsolete data and were asked to choose the best decisions based on the scenarios. The results were analyzed for correlations to check If there is a correlation between the responses of the two groups. The study found strong evidence for a correlational relationship between data quality dimensions and decision-making efficiency at 0.05 and 0.01 significance level for the student and employee groups respectively. The study found that high-quality data leads to both better and faster decisions in both groups. There were no significant differences between occupation, or gender and time taken for making a decision. The current study highlights the importance of data quality dimensions. It urges organizations to use up-to-date data, and complete data sets to base their decisions.
Predicting meltdown situation in Autism and ADHD in real-time through camera using deep learning algorithm.
Authors: Sumbul Alam
Published: May 2024

Neurodevelopmental issues such as Autism spectrum disorder (ASD) and Attention deficit hyperactive disorders (ADHD) are quite prevalent in small children detecting and differentiating them at a very early stage is necessary for the future of the affected children and their parents or care giver. This may require 24 hours of surveillance in level 3 cases in which the affected may experience meltdown situation. It is well known by clinical psychologist that sudden meltdowns are common in autistic children, which makes the situation difficult for the parents or care givers and is also a physical threat to the affected children and people around them as they most likely injure themselves. Research has shown that children diagnosed with autism spectrum disorder display specific behaviors that allow us to predict their violent outbursts. Our aim is to develop a CNN-based system that can identify these kinds of behaviors using real time camera.
In our study, we are trying to make a model that can perform Human Activity Recognition (HAR) in real time. Based on the available training data we have trained our model on a few common pre meltdown actions or gestures creating two classes of dataset. but in future we may take huge number of video frame of different types of gestures (using HMBD51 datasets) to train the algorithm so that it can practically identify the situation in real time and alarm the caregiver before they enter the meltdown situation, this will save the patients from self-inflicted injuries and panic attacks not just in the above mentioned two cases but many other brain disorders. The present model has achieved a training accuracy of 100% ,a satisfactory FPS(Frame processed per Second) and the validation accuracy is slightly increasing in each epoch.
Enhancing Energy Efficiency in Smart Grids through Reinforcement Learning-Based Control Strategies
Authors: Nilam B. Panchal
Published: May 2024

The rapid growth of smart grids has ushered in new opportunities for enhancing energy efficiency through advanced control strategies. This paper explores the potential of reinforcement learning (RL) to improve the energy efficiency of smart grids, focusing on RL-based control strategies. We begin with a comprehensive review of existing technologies, examining a range of architectures and methods used to implement RL in smart grid environments. This review highlights both the benefits and limitations of these approaches, offering a balanced analysis of their effectiveness in addressing the unique challenges of smart grid management. Following this review, we propose a new RL-based control strategy designed to optimize energy efficiency. Our approach leverages the strengths of state-of-the-art RL algorithms while addressing common shortcomings identified in previous work. We evaluate our strategy using a detailed simulation that reflects real-world smart grid scenarios. The results demonstrate significant improvements in energy efficiency compared to traditional control methods. Finally, we discuss best practices for applying RL in smart grids, providing guidelines for researchers and practitioners seeking to implement these strategies. Our recommendations focus on maximizing energy efficiency while ensuring stability and scalability in smart grid systems. Through this work, we aim to contribute to the ongoing development of sustainable and efficient smart grid technologies.
Establishment and Optimization of Security Domain Prevention System in Business Middle Office Based on Choquet Expectation
Authors: Jun Yu
Published: May 2024

With the rapid development of China's national economy, the needs of People's Daily life are increasing, and the demand for various business middle platform security domain prevention is also increasing.At the same time, due to the imbalance of its own resource allocation, it shows the characteristics of "more resources and less load" in the western region.With the gradual popularization of the application of Choquet expectation, a large number of new Choquet expectation algorithms have been incorporated into the security domain prevention system of the business middle platform, and have entered thousands of households.This kind of distributed generation also has its own problems such as difficulties in grid connection, large amount, small environmental pollution, flexible operation mode, and prominent stability problems.Factors such as the interconnection of large-area services, long-distance transmission of AC and DC UHV, and marketization of services make the topology of services more complicated, and the steady-state operation of Choquet services is also closer to the critical stable operation point.At present, the security domain prevention of China's business middle office has become a serious problem.In recent years, there have been several large-scale business middle office security domain incidents around the world.A comprehensive study of the above business middle platform security domain prevention events shows that when the business load is heavy and the business is complex, when the business has a large fault, it will lead to the chain short circuit of the business and serious economic damage.Therefore, combining Choquet expectation to quickly and accurately consider the stability of the service, and combining the new energy characteristics, especially the characteristics of Choquet expectation, is the main problem and problem of the security domain prevention market in the future business.
Various Load Sharing Strategies used in DC Microgrids
Authors: Shilpa K. Patel
Published: May 2024

This paper provides a review of various load sharing strategies used in DC microgrids.  DC microgrids usually utilize parallel connections of DC-DC converters to improve system reliability and flexibility. However, when connecting multiple converters in parallel in a microgrid, the resistance of the cables becomes a critical factor. Unequal load distribution and inadequate voltage control result from cable resistance, leading to the generation of circulating current. The equal load sharing can be achieved by active load sharing and passive load sharing method. These two broad categories encompass a wide range of control schemes. This paper provides a comprehensive analysis of active and passive load sharing strategies, highlighting their advantages and disadvantages. Very Few researchers have explored the influence of cable resistance on load sharing and voltage regulation. Also, the effect of circulating current on the converter is a relatively unknown factor that must be identified and reduced to the greatest extent possible. This paper is a valuable resource for future researchers who are interested in studying load sharing and related control techniques.
Knowledge Hiding of Scientific Research Teams in Colleges and Universities within the Chinese Context
Authors: Jiahui Jin
Published: May 2024

Knowledge hiding is a concept corresponding to knowledge sharing, hindering knowledge integration and innovation of scientific research teams. Study on knowledge hiding is beneficial to improving the innovation ability and performance of scientific research teams. Current research on knowledge hiding behaviors of scientific research teams in colleges and universities within the Chinese context have made new progress, including but not limited to: (1) Characteristics of scientific research teams in colleges and universities within the Chinese context, and the unique knowledge hiding behavior patterns caused by such characteristics; (2) How to effectively measure knowledge hiding behaviors within the Chinese context; (3) Local factors triggering knowledge hiding behaviors; (4) Chinese leadership in scientific research teams; (5) Impact of the unique office culture in China on knowledge hiding behaviors.
《西遊記》民間故事元素拼貼研究——以第九回、第十回為討論重心
Authors: 袁嘉良 袁嘉良
Published: May 2024

《西遊記》作為最具代表性的神魔章回小說，情節常被認為較不具備有機性的連結 ，當中，第九回到第十一回故事主旨為取經隊伍成型，拼貼民間故事用以展延篇幅、推動情節。本文試以觀察這些情節如何被改寫，藉由分析作者如何使用韻文、轉變角色形象，用以證明作者在吸收轉化民間故事時，情節仍不背離《西遊記》取經的主線，而見其精湛的敘事造詣。

 
Rezension von: Jankuhn, Herbert, Vor- und Frühgeschichte
Authors: Huber Hermann , Jankuhn Herbert
Published: May 2024

Herbert Jankuhn: Vor- und Frühgeschichte vom Neolithikum bis zur Völkerwanderung. (Deutsche Agrargeschichte I) Stuttgart: Ulmer 1969. 300 S. Ill. DM 46,-.
Rezension von: Bosl, Karl, Franken um 800
Authors: Taddey Gerhard , Bosl Karl
Published: May 2024

Karl Bosl: Franken um 800. Strukturanalyse einer fränkischen Königsprovinz. 2. erw. Aufl. XII, 210 S. mit 7 Karten. DM 28,-.
Rezension von: Ulshöfer, Kuno, Bilder einer alten Stadt: Schwäbisch Hall
Authors: Wunder Gerd , Ulshöfer Kuno
Published: May 2024

Kuno Ulshöfer: Bilder einer alten Stadt. Schwäbisch Hall. Eppinger 1971. 104 S. DM 42,-
Rezension von: Backes, Heinrich u.a., Bad Mergentheim
Authors: Hampele Walter , Backes Heinrich
Published: May 2024

Bad Mergentheim. Fotografiert von Heinrich Backes. Text von Kuno Ulshöfer. Rottweil: Banholzer (1971). 83 S. DM 15,50.
Rezension von: Ostertag, Fritz-Peter, Weinsberg
Authors: Wunder Gerd , Ostertag Fritz-Peter
Published: May 2024

Weinsberg. Bilder aus seiner Vergangenheit. Hrsg. v. Fritz-Peter Ostertag und Rolf Becker. Weinsberg: W. Röck 1970. 120 S. Ill. DM 11,80.
Rezension von: Schwäbische Lebensläufe Bd. 8, 9, 10
Authors: Wunder Gerd
Published: May 2024

Schwäbische Lebensläufe. (Hrsg. v. Helmut Christmann) Heidenheimer Verlagsanstalt. Je Band DM 9,80.Band 8. Johann Jakob Moser, bearb. v. Siegfried Röder. 1971. 124 S. Band 9. Schwäbische Weltenbummler, bearb. v. Hartmut Sellke. 1971. 144 S. Band 10. Heinrich Seuse, bearb. v. Werner Fiscal. 1971. 160 S.
Rezension von: Schlauch, Rudolf; Schlauch, Ingaruth, Langenburg
Authors: Wunder Gerd , Schlauch Rudolf , Schlauch Ingaruth
Published: May 2024

Rudolf und Ingaruth Schlauch: Langenburg. Herz im Hohenloher Land. Gerabronn: Hohenloher Druck- und Verlagshaus. 1971. 19 S. Ill.
Rezension von: Welchert, Hans-Heinrich, Wanderungen zu den Burgen und Klöstern in Schwaben
Authors: Ulshöfer Kuno , Welchert Hans-Heinrich
Published: May 2024

Hans Heinrich Weichert: Wanderungen zu den Burgen und Klöstern in Schwaben. Tübingen: Wunderlich 1971. 256 S., 16 Tfl., 15 Karten. DM 22,50.
The impact of demographic changes on the economic security of the Republic of Moldova
Authors: Coban Marina
Published: May 2024

This article presents changes in the demographic sphere of the Republic of Moldova, their impact on the economic security of the country as a whole. The most serious threat to the country's economic security is that as the population structure changes as the workforce shrinks (a shrinking and aging population) and welfare costs increase for needy citizens, the economy may slow. The Republic of Moldova at this stage is experiencing problems in the demographic sphere, which reduces the level of economic security. The article presented the main trends in the demographic sphere and their impact on the economic security of the country. Statistical indicators of demographic processes in the Republic of Moldova were analyzed, and conclusions were drawn that in the Republic of Moldova there is a trend towards a decrease in the birth rate, population size, an increase in mortality, and an increase in emigration , which reduces the level of economic development. In this regard, it is necessary to take effective measures to improve the level and quality of life of the population of the Republic of Moldova.
The sustainable economic security through innovations: an integrated model for the Republic of Moldova
Authors: Coretchi Boris
Published: May 2024

This paper holds paramount importance as it presents a pioneering approach to economic development and state security through an economic-mathematical model. Focused on the Republic of Moldova, the author delves into the intricate interplay between innovation, economic progress, and economic security. The paper aims to establish a comprehensive model that integrates these elements, offering a holistic vision for efficient management and the enhancement of economic competitiveness. The originality of this work lies in its thorough analysis of the connections between innovation, economic progress, and economic security specific to the Republic of Moldova. The author introduces an economic-mathematical model, emphasizing the significance of information technologies and scientific leadership in fortifying economic security. Notably, the paper utilizes a fuzzy model based on real data, providing personalized strategies for sustainable economic growth and long-term security.In summary, the integrated model underscores the critical role of adopting and implementing information technologies, equipping institutions with advanced technology, leveraging scientific achievements, and implementing effective personnel policies. These elements are identified as crucial for consolidating the economic security of the Republic of Moldova. The promotion of these key factors is highlighted as a substantial contribution to bolstering institutional effectiveness in the face of economic and security challenges, ultimately supporting sustainable economic growth and ensuring the long-term security of the country.
Risk assessment and hedging as the basis of financial security of the
Authors: Lapitkaia Liudmila
Published: May 2024

Financial security is the basis for the effective development of any economic agent; it is especially important for enterprises, since their financial security underlies the security of both households and the state. This article examines the risks that can lead to the loss of the financial security of an enterprise, which the author classified into: general economic, industry- specific and risks of a particular enterprise. Hedging financial security risks will be most effective if the management of the enterprise evaluates the risks, using the classification proposed by the author. The financial security of an enterprise depends on the financial resources necessary for its normal condition, ensuring their placement and efficient use, financial stability with other legal entities and individuals, solvency and financial stability, as well as on the efficiency of the operating, financial and other activities of the enterprise. By the financial condition one can judge the solvency, liquidity and financial stability of the enterprise. In a market economy, defining the boundaries of an enterprise's financial security is one of the most important economic problems, since insufficient financial stability can lead to a shortage of funds for enterprises, and to their insolvency and, ultimately, bankruptcy, as well as "excessive" stability will slow down development, burdening the enterprise with excess inventories and reserves. Financial security should be considered taking into account the risks that arise both at the level of the economy as a whole, and at the level of the industry and at the level of the enterprise itself.
The current situation with the information security in Ukraine
Authors: Rybalchenko Ludmila
Published: May 2024

The condition in which Ukraine is since 2022 after russia's full scale military invasion, forces us to consider the issue of security in all spheres of life as one of the main components of the state's national security. Conducting informational influence on human consciousness has changed significantly, which is carried out with the use of mass media. The creation of mass information attacks, bots, fakes and other means of influence are effective tools for disorienting the entire society and manipulating people to increase panic. Specially created information resources try to influence in such a way that a person perceives information in the way it is presented and believes it.
The impact of martial law on the organization's information security
Authors: Synytsina Yuliia
Published: May 2024

The article examines the problem of the development of information and analytical activity (IAD) in domestic state and commercial institutions, which leads to the constant improvement of information security issues, which in turn is closely related to issues of economic security. Based on the results of the study, the analysis model was clarified and the practical aspects of the application of neural networks (NN) in the marketing information system (MIS) of the enterprise were clarified with the aim of improving the information system of the enterprise by implementing an intelligent decision support system (IDSS) using a neural network, as well as the concept of modeling the behavior of interacting agents, the basis of which is a three-level structure of modeling subjects and business processes of the contours of the organization's functioning and the security system, based on the modeling of the behavior of antagonistic agents. Modern trends and directions in the field of information security of state and commercial institutions of the present and the near future, which in one form or another use artificial intelligence in their arsenal, are defined, such as EDR / XDR solutions for end hosts, UEBA, SGRC products, Honey Tokens and other developments of the Deception class, IRP (Incident Response), TI- / TH-platforms, etc.
Agile transformation and performing management of IT and cyber security projects, at the government level
Authors: Stefan Marius
Published: May 2024

In an information society in which the quality of life, as well as the prospects for social change and economic development, depend to a greater extent on information and its exploitation, the institutional field of management of IT applications for European funds becomes a matter of national importance, with critical values for national security. Reinventing government can be achieved through digitalization and government computerization, which involves modernizing the current IT infrastructure through specific external funding sources such as European funds, doubled and secured by advanced cyber protection and defense capabilities against possible vulnerabilities or cyber-attacks. Knowledge and scientific information are of enormous importance in the global information society, by: supporting innovation, promoting economic development, making decisions in an efficient and transparent way, at the governmental level and especially for the implementation and use of intelligent technologies in the development of the degree of digitization of public services through financing provided by European funds and the National Recovery and Resilience Plan. In order to move on to building the knowledge society, it is necessary to reduce the digital gap, which accentuates disparities in development, excluding groups and even countries, from the benefit of information and knowledge. The limiting factor in development will be related to the human capacity to assimilate and develop these technologies, to use them in new fields of activity, for new products and services.
Examining The Influence Of Organizational Justice And Workplace Spirituality On Mental Health: Exploring The Interplay Of Interpersonal Trust
Authors: Ai Iman Budiman , Kurnianto Tjahjono Heru , Nurul Qamari Ika
Published: May 2024

This study investigates the intricate dynamics between workplace spirituality, interpersonal trust, organizational justice, and mental well-being within the context of Integrated Islamic Schools (Sekolah Islam Terpadu - SIT) in West Java, Indonesia. Employing a mixed-method approach, combining theoretical and quantitative analyses, data from 261 educators across eight SITs are examined using partial least squares (PLS), structural equation modeling (SEM), and Likert-scale assessment. Results demonstrate the positive influence of organizational justice and workplace spirituality on interpersonal trust, ultimately impacting mental health, with interpersonal trust serving as a mediating factor. These findings underscore the importance of cultivating supportive work environments to enhance educators' well-being and effectiveness. The study contributes to understanding the factors influencing educators' mental health in Islamic educational settings, emphasizing the significance of trust-building strategies in fostering conducive learning environments. Future research endeavors in this realm can inform initiatives aimed at bolstering educator well-being and student outcomes. Theoretical implications highlight the pivotal roles of interpersonal trust, organizational justice, and workplace spirituality in shaping educators' mental health, emphasizing the importance of nurturing spirituality and equitable organizational practices to cultivate trust and enhance well-being. On a practical note, the study underscores the imperative of fostering supportive and fair work environments to promote trust and bolster educators' mental health, offering valuable insights for educators, administrators, and policymakers invested in prioritizing teachers' well-being.
The Impact Of Principle's Transformative Leadership On Organizational Culture, Commitment, Behavior And Performance Productivity
Authors: Dakir Dakir , Fauzi Ahmad , Nurbudiyani Iin , Fatchurahman M. , Qodir Abdul , Amir Amir
Published: May 2024

This study aims to determine the transformation of the principal's leadership style at MTs Palangkaraya City, Central Kalimantan in building organizational culture, performance commitment, performance behavior and employee performance productivity. This study used a quantitative approach with data collection techniques by distributing questionnaires, with a sample of 166 school principals from a total of 210 schools, thus to determine the characteristics of each respondent and variables, this study used descriptive data analysis. Meanwhile, to test the relationship between variables, inferential analysis can be used using the Structural Equation Modeling (SEM) method and the AMOS version 7 approach. The results of this study explain that leadership style transformation is seen as quite effective in dealing with various changes and is believed to be the strongest leadership model (strong leadership), because it can build a healthy organizational culture, performance commitment and performance behavior, so as to increase the productivity of individual performance to be more effective.
Tailoring antidepressant therapy based on genetic profiles
Authors: Al Shammari Yosef Houmid , Al Shammari Homoud Awade , Barak Talal Muhammad bin , Alharbi Bandar Said , Alshammari Saud Tawfiq , Alnais Saleh Abdullah , Aljohani Saeed Awad , Alorf Abdulrahman Abdullah , Alnawmasi Meshari Abdulmajeed , Alshammari Mohammed Awad , Alharbi Majed Farhan , Al Enazi Abdulrahman Gobile , Alamri Abdulelah Mohammed Mubashir
Published: May 2024

Background: Depression is a substantial public health concern that impacts millions of individuals globally. The wide range of symptoms and manifestations of depression emphasizes the need of tailoring treatment methods to each individual, which includes adapting antidepressant prescriptions accordingly. Genetic factors contribute to depression and its association with other psychiatric and non-psychiatric illnesses, highlighting the need of a thorough assessment that encompasses psychopathology, physical health, and genetic variables. Aim of Work: This research aims to highlight the significance of customized therapy in the management of depression, taking into account hereditary variables, metabolic abnormalities, and inflammatory indicators. The research also seeks to emphasize the potential use of genotyping in directing the selection of antidepressants and making dose changes for people with altered metabolism. Methods: The research entails examining previously published works on the genetic factors related to depression, the influence of inflammatory and metabolic abnormalities in its development, and the possible advantages of genotyping in the treatment of antidepressants. The research also examines the incorporation of genetic information, such as the tendency to develop cardio-metabolic illnesses due to several genes, together with non-genetic risk factors to improve treatment results.
Perceptions and Experiences of Academic Advisers and Minoritised Students at a UK University
Authors: Rogerson David , Bosch Sarah , Jacobi Melissa , Tripathi Sweth
Published: May 2024

Academic advising can support students’ academic development and intrapersonal skills whilst fostering a sense of belonging at university. Despite recent advancements in knowledge and practices, it is not clear how best to support minoritised students, who experience outcome differentials and life circumstances that differ from the majority. Following a reciprocal mentoring programme pairing academic staff and minoritised students at a UK university, we explored students’ academic advising experiences. Qualitative data were collected and analysed via framework analysis. The mentoring led to both groups improving relational understanding. Ten themes categorised into three domains (Personal Factors, Institutional Factors and Interplay Between Personal and Institutional Factors) highlighted complex issues that affect students’ day-to-day lives, their ability to engage with academic advising, and factors that affect academic advising practices. Recommendations such as strategies to improve relationships, structured and developmental advising models, and guidance to improve role-specific clarity are provided.