bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictive Analytics in Industrial Processes Using LSTM Networks
Authors: Rahul Arulkumaran,  , Dignesh Kumar Khatri  , Viharika Bhimanapati  , Lagan Goel  , Om Goel
Published: September 2024

It is now well acknowledged that predictive analytics is an indispensable instrument for boosting the efficiency and effectiveness of industrial operations. Long Short-Term Memory (LSTM) networks, which are a form of recurrent neural network (RNN), have shown substantial promise among the numerous methodologies that have been used. This is because of its capacity to collect and describe temporal relationships in sequential data sequences. The purpose of this study is to investigate the use of LSTM networks in predictive analytics for industrial processes, with a particular emphasis on the advantages, disadvantages, and uses of these networks in the actual world.
An overview of predictive analytics and the significance of its role in the optimisation of industrial processes is presented at the beginning of the research. The process of analysing previous data to make predictions about future occurrences is known as predictive analytics. This helps companies improve their decision-making processes and their operational efficiency. Industrial processes, which are characterised by data that is complex, dynamic, and time-dependent, may considerably benefit from sophisticated predictive models that are able to manage such complexities.
MATHEMAGIC SQUARE PUZZLE: AN INTERVENTION IN IMPROVING BASIC OPERATION SKILLS ON INTEGERS
Authors: Kervin Cyril L. Cusit  , Johniel T. Angteg  , Jade H. Cellacay  , Faith D. Arabis  , Ivy Joy L. Altizo
Published: September 2024

Basic operation skills on integers are crucial for building a strong mathematical foundation. However, many students in early schooling show poor performance in these fundamental skills. To address this issue, this study aims to assess the effectiveness of using the MatheMagic Square Puzzle as an intervention to enhance integer operation skills among Grade 7 students at Kapalong National High School. The study had a total of 114 students, and it employed quantitative research with a one-group pre-test post-test design and purposive sampling. Results revealed that the overall mean score level of basic operation skills on integers of the experimental group in the pre-test is very low, which is interpreted as it did not meet the expectation. While results in the post-test revealed from the overall mean is average, which is interpreted as satisfactory. Results indicate significant difference between the pre-test and post-test of the experimental group shows that there is a significant difference in the performance levels of the experimental group before and after the intervention. The study revealed a significant improvement in students' ability to solve basic operations on integers. This improvement proved the effectiveness of the MatheMagic Square Puzzle intervention and proved it to be a valuable tool in mathematics education, specifically for teaching integers. The researchers suggest implementing MatheMagic Square Puzzle widely for teaching basic integer operations in Grade 7 due to its effectiveness in improving student performance. They also suggest studying its effectiveness across various grades and mathematical concepts to expand its impact.
KEYWORDS: MatheMagic Square Puzzle, Basic Operation on Integers, Intervention, Grade 7 students, Philippines
ON ONE PROBLEM OF OCCURRENCE IN SOME ARTIN STRUCTURES
Authors:   Moscow Technical University of Communications and Informatics, Moscow, Russia, Dobrynina Irina V. , Manokhin Evgeny V. ,   Tula Branch of the Financial University under the Government of the Russian Federation, Tula, Russia
Published: September 2024

The problem of entering a subgroup is algorithmic, and its solution causes great difficulties in various classes of groups. The same applies to group structures. In this paper, the authors consider the solution of a special case of the general problem of occurrence in the socalled Artin structures. They have the structure of a tree, at the vertices of which there are Artin groups that have an extralarge or woody appearance. Previously, the problem of entering a subgroup generated by a single element was studied for such structures. The authors use methods based on a geometric approach based on the study of diagrams. A special case of the problem of entry is the entry into the socalled parabolic subgroup, that is, a subgroup in which some of the forming elements of the group are removed. The proposed methods make it possible to solve this problem more simply. The solution of the problem considered in the article in Artin groups has not been generally obtained.
APPLICATION OF MACHINE LEARNING IN REAL ESTATE MARKET RESEARCH
Authors:   Graduate student, Assistant, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Tran Hoang Hieu
Published: September 2024

This article discusses the use of machine learning for analysis and forecasting in the residential real estate market. The authors emphasize various machine learning methods, including supervised, unsupervised, and semisupervised learning. These technologies are used to work with real estate data to improve the efficiency of price forecasting, analyzing market trends and optimizing marketing strategies. One of the significant benefits of machine learning is its ability to recognize complex patterns and relationships in large volumes of data, which is invaluable for indepth analysis of the real estate market. The article also discusses the main challenges associated with using this approach, including possible data quality issues and the risks of overfitting models, which can lead to biased analysis results. The author provide specific examples of the successful use of machine learning in this area, demonstrating how these technologies can effectively cope with the task of identifying nonobvious patterns in data. This opens up new perspectives for developing marketing strategies and improving the accuracy of real estate price forecasts. The final part of the article highlights the importance of further research in this area. Particular attention is paid to the need to integrate diverse types of data and develop new algorithms that could improve predictive ability and analytical accuracy in real estate valuations. The author point out the need to continue research to expand the functionality of machine learning, which will make it possible to more fully use its potential in economic and commercial applications in the real estate market.
NUCLEAR INSTALLATIONS DECOMMISSIONING SUPPORTING USING DIGITAL PRODUCTS
Authors:   Candidate of Economic Sciences, Doctoral candidate, Plekhanov Russian University of Economics, Moscow, Russia, Ilyasov Damir F. , Ovchinnikov Ilya D. ,   Postgraduate student, Plekhanov Russian University of Economics, Moscow, Russia, Sergeev Ilya I. ,   Student, Department of Software Engineering, National Research University Higher School of Economics, Moscow, Russia
Published: September 2024

The article discusses the development of a digital product for the decommissioning of nuclear and radiationhazardous facilities at the conceptual level. The need for such development is conditioned by the fulfillment of the requirements for import substitution of software in strategically important sectors of the Russian Federation, the importance of ensuring information security (data in the project is often marked «For official use») and the availability of additional functionality for specific projects that is not provided in other applications. The authors describe the features of nuclear decommissioning projects and form functional requirements for the digital product, proposing architectural patterns. In particular, the clientserver architecture with microservices was chosen for the development of this digital product. Main technologies and methodologies for the clientside application (frontend) include HTML, CSS, React, and FeatureSliced Design. JavaScript and TypeScript languages used to create the frontend of the application. To organize the backend, it is recommended to use Docker, Nest.js, and Node.js. Data storage is handled using the PostgreSQL database and S3 cloud storage. Using the example of one of the modules (Gantt Chart) of the digital product, the methods and libraries used are described in detail. Overall, the combination of these technologies ensures that the digital product is importindependent and meets all the requirements for successful development.
THE MANIFESTATION OF THE NARRATIVE ECONOMY IN THE UNITED STATES: THE IMPACT ON MARKET ACTIVITY AND VOLATILITY
Authors:   Student, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Arzumanov Oleg A. , Dmitriev Nikolai D. ,   Candidate of Economic Sciences, Senior lecturer, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Ungvari Laszlo ,   Doctor of Economics, Professor, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Technical University of Applied Sciences, Wildau, Germany
Published: September 2024

Against the background of growing interest in the role and influence of information noise in economic activity, this study aims to analyze the manifestation of the narrative economy using the example of the United States. The aim of the work is to understand the components of narrative economics and their impact on the market and its participants. This analysis helps to explain which narratives and in which cases incline investors to change their strategies in the market. The object of the study is the growth rate of GDP (economic activity), the profitability of the market and its volatility in the United States. The subject of the study is the influence of narratives on the projected GDP growth rate, profitability and volatility of the US market. The research methodology includes the identification of narratives with a narrative structure using thematic modeling and the use of machine learning methods to identify causeandeffect relationships. Linear regression and machine learning methods, in particular, random forest and XGBoost, were chosen as tools for identifying causeandeffect relationships. The study revealed that narratives have a significant impact on projected GDP growth and economic activity, and there is also a link between market volatility and narratives with an emotional context. However, there is no direct relationship between narratives and market returns. The results obtained may be important for understanding the dynamics of market processes and decisionmaking in the investment sector.
DEVELOPMENT OF RESEARCH IN THE SPHERE OF REAL ESTATE MARKET
Authors:   Graduate student, Assistant, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Tran Hoang Hieu
Published: September 2024

The article analyzes in detail the dynamics and complexity of the real estate market with an emphasis on forecasting methodology and its practical application in an economic context. The main theme is the integration of various forecasting models that predict trends and fluctuations in real estate prices based on a multidisciplinary approach combining economic theory, statistical data and market analysis. First, the basic principles defining the real estate economy, its differences from other sectors in terms of market conditions and consumer behavior patterns are outlined. The importance of location and consumer characteristics in determining the value of the property is emphasized. It is explained how these factors distinguish the real estate market into a separate area of research. The challenges and imperfections of the real estate market, such as lack of competitiveness and inefficiency in comparison with finance, are shown. It is argued that these characteristics require complex predictive models to improve market efficiency and investor decisionmaking. In this context, various statistical and analytical tools that have been improved over the years to improve the accuracy of forecasts in the real estate market are discussed. Theoretical judgments are supplemented by examples and empirical data confirming the effectiveness of models in various economic conditions. The author advocates continuous innovative development and adaptation of forecasting techniques used to analyze the real estate market. The need for a multidisciplinary approach is emphasized, taking into account economic indicators, opinions of market participants and geopolitical factors in forecasts. This comprehensive strategy is presented as key to navigating the complexities of global real estate markets, taking advantage of investment opportunities in an everchanging economic environment.
MANAGING THE EFFECTIVENESS OF DESIGN SOLUTIONS USING THE COMMERCIALIZATION COEFFICIENT
Authors:   St. Petersburg Restoration and Construction Institute, Petrov Mikhail A. , Uskov Vladislav V. ,   St. Petersburg Restoration and Construction Institute
Published: September 2024

The article evaluates the impact of technical and economic indicators of projected residential buildings on the unit costs per square meter of the sold area. The commercialization coefficient (hereinafter Cc) is one of the indicators characterizing the rationality of design decisions. Its purpose is to assess the effectiveness of design solutions in terms of commercial use of the area of a residential building. For this purpose, the Qc for a building as a whole is defined as the ratio of the area of all sold premises to the area of a residential building. Since pricing and cost comparisons in the real estate market are linked to the price of one square meter of the area of the premises being sold, then evaluating the effectiveness of design solutions requires appropriate cost estimates in relation to the unit area of the premises being sold. However, for the purposes of benchmarking construction projects, it is more appropriate to link the cost of erecting a building to a unit area of a residential building, which is the basis for determining the construction volume of a residential building.
Sociological research as a basis for forming a strategy for the spatial development of rural areas
Authors:   Vladimir State University named after A. G. and N. G. Stoletovs, Vladimir, Russia, Kuznetsova Yulia A.
Published: September 2024

The article investigates the theoretical aspects of forming strategies for spatial development of rural areas in the Russian Federation. It notes that contemporary science does not adequately address the sociological factor as one of the main determinants of strategic planning in the context of the country’s rural settlements’ development. Meanwhile, the author substantiates the theoretical and practical significance of public opinion in the development of projects and plans for the spatial development of Russian villages. The influence of the current regulatory legal framework on spatial development on the possibility of civic activity by rural residents in matters of development and modernization of their territories is critically assessed. Based on the analysis of foreign experience in strategic planning of spatial development, the conclusion is made about the necessity of conducting scientific and legal work to develop techniques for collecting and analyzing population opinions, as well as a legal mechanism for incorporating this tool into the strategic planning process in the Russian Federation. An attempt is made to formulate the necessary legislative amendments, and a standardized algorithm for forming spatial development strategies for rural territories is proposed, considering the objective necessity of including sociological interaction tools with the population. It has been concluded that sufficient sociological support for spatial development projects in rural areas can significantly impact the regional economy by accurately allocating resources when planning spatial development activities for villages, identifying problems and needs of specific territories and their residents, stimulating local economic growth through projects designed considering the specifics of rural areas, their strengths, and unique features, improving the quality of life of the population by increasing the necessary infrastructure and access to essential services, reducing migration from rural areas by enhancing the quality of life and providing employment, forming an adaptive mechanism of interaction with the population, and creating sustainable models of spatial development for rural areas.
THE PROGRESS OF RESEARCH IN THE FIELD OF OPTICAL TRANSPARENCY TECHNOLOGY OF BIOLOGICAL TISSUES
Authors:   Grozny State Petroleum Technical University named after Academician M. D. Millionshchikov, Grozny, Russia, Ataeva Aminat A. , Tsurigova Zainap B. ,   Grozny State Petroleum Technical University named after Academician M. D. Millionshchikov, Grozny, Russia, Vakaraeva Malika M. ,   Kadyrov Chechen State University, Grozny, Russia
Published: September 2024

The new optical transparency technology of biological tissues makes opaque biological tissues and organs transparent and complete after processing. The innovation can additionally be combined with optical imaging technology to achieve a three-dimensional fluorescent/absorption image of entire tissues and organs. The know-how has an irreplaceable slicing performance and is a hot spot for research in the field of biomedical photonics. The article discusses the concepts, principles, stages and methods of implementing optical tissue transparency technology, its research status and some results in the field of biomedicine, especially brain science. The advantages and disadvantages of the various parameters of each method are compared. Future proposals, problems and developments in the field of applied research are discussed.
GESTURE CONTROL HUMAN FOLLOWING ROBOT
Authors: Revathi Ms.B. , B. Srinidhi  , Harini I. Sri , N.Devanmukhi
Published: September 2024

A rapidly developing subject of study, humanoid robots has drawn a lot of interest recently and will be crucial to robotics research and numerous applications in the twenty-first century and beyond. A "Human Following Robot" that can communicate and coexist with humans is necessary in our fastpaced environment. These robots may aid people in a variety of scenarios and gather or keep track of specific data related to the human subject thanks to their capacity to follow humans. This article describes a prototype that combines an Arduino Uno with common sensors such an infrared and ultrasonic sensor. The controller is responsible for controlling the motors, while the microprocessor handles all processing. There are several ways to further customize this robot, including via the use of Bluetooth and PixyCamera.
WIRELESS CHARGING STATION FOR EV VEHICLES AND SOLAR PANELS
Authors: Pradeep Sunkari , D.Varshini  , P.Sravya  , P.Vidya  , T.Meenakshi
Published: September 2024

Electric vehicles (EVs) are a new and developing technology in the power and transportation sectors. Regarding the state of the economy and ecology, there are more advantages. The most crucial component of electric vehicles is the charging station, which lowers environmental pollution and the influence of greenhouse gases. Electric Vehicle Supply Equipment is another name for this electric charging station (EVSE). It is made up of both low power and high power. It would be very helpful to build an on-road charging system with a solar panel so that we can charge at any time. We can also drive off-road with connected batteries because the high power is terminated at a fraction of the second charging that can be implemented in an electric vehicle rather than the low power. The photovoltaic (PV) cell's force from sunlight is transferred to the electric vehicle's battery via the application of remote force move technology. Sunoriented boards are thought to build an autonomous force station, so reducing its need on common energy resources. By using the light energy the sun produces, the sunoriented boards generate electrical energy. The energy obtained from the board is transferred to a battery by means of a solarpowered charge regulator, therefore increasing the photovoltaic cell's force output. Due to the wireless connection between the transmitting and receiving coils, DC current is injected into the battery. The battery is automatically switched off from solar power once it is full. As a consequence, electric battery utilization and sustainable mobility are achieved. There is an overview of the charging stations and a discussion of the implications of electric vehicles.
A DEEP LEARNING-BASED APPROACH FOR DETECTING AND CLASSIFYING INAPPROPRIATE CONTENT IN YOUTUBE VIDEOS
Authors: Rajashekhar Mr.V. , Spurthi Y. Sai , Varshitha Y. Soumya , V. Vinshitha
Published: September 2024

There are now billions of videos on YouTube, with most of the viewers being young people. The growth in the quantity of videos has been exponential. To add insult to injury, some unscrupulous users post unsettling animated cartoon films and other material that parents should not allow their children to see. Therefore, social media sites should have a way to filter videos automatically in real time. In order to identify and categorize objectionable video material, this research proposes a new architecture based on deep learning. To do this, the suggested system employs a convolutional neural network (CNN) model named EfficientNet-B7 that has been pre-trained on ImageNet to extract video descriptors. A bidirectional long short-term memory (BiLSTM) network is trained to classify videos into many categories using these characteristics. In order to distribute attention probabilities throughout the network, an attention mechanism is also included after BiLSTM. We test these models using a dataset that has 111,156 cartoon clips tagged by humans from YouTube videos. The experimental findings showed that EfficientNet-BiLSTM achieved a higher accuracy (D=95.30%) than the EfficientNet-BiLSTM framework that was based on the attention mechanism. To continue, when compared to more conventional machine learning classifiers, deep learning ones outperform the pack. With an overall f1 score of D 0.9267, the combination of EfficientNet and BiLSTM, which includes 128 hidden units, achieved state-of-the-art performance. Furthermore, when stacked on top of CNN, BiLSTM outperforms state-of-the-art methods in detecting and classifying children-unsuitable video content because it better grasps the contextual information of video descriptors in network architecture.
A DEEP LEARNING-BASED EFFICIENT FIREARMS MONITORING TECHNIQUE FOR BUILDING SECURE SMART CITIES
Authors: Sajja Mrs. Sri Lavanya , M. Trisha  , N. Alekhya  , N. Sri Latha
Published: September 2024

Any kind of violence is a shame to the world we live in. However, violence still plays a significant role in our society today and claims many innocent lives. Using a gun is one of the traditional methods of violence. Nowadays, firearm-related fatalities are a widespread occurrence. It poses a risk to public safety and presents difficulties for law enforcement. Most of these incidents take place in cities or semi-urban regions. Today, CCTV-based surveillance is widely used by both public and commercial institutions for monitoring and prevention. However, human-based monitoring is error-prone and needs a large number of person-hours as a resource. However, automated smart surveillance is better suited for large-scale and dependable monitoring of violent actions. The primary goal of the study is to demonstrate how deep learning-based methods may be used to identify weaponry, especially rifles. This research employs many detection methods for human face and gun identification, including the newest EfficientDet-based architectures and Faster Region-Based Convolutional Neural Networks (Faster RCNN). The post-processing detection performance of weapons and human faces has been enhanced using an ensemble (stacked) strategy that employs Non-Maximum Suppression, Non-Maximum Weighted, and Weighted Box Fusion techniques. In this study, the comparative outcomes of several detection methods and their ensembles have been addressed experimentally. It facilitates the police's rapid information gathering about the situation and enables them to take prompt preventative action. Additionally, social media videos may be found using the same method for gun-based content recognition. Here, the mean average precisions for the mAP0.5, mAP0.75, and mAP[0.500.95] are 77.02%, 16.40%, and 29.73%, respectively, according to the Weighted Box Fusion-based Ensemble Detection Scheme. Out of all the options tested, the outcomes provide the best performance. The model has undergone extensive testing using movie clips and unidentified test photos. The resulting ensemble schemes are consistently better than the basic models and are adequate.
A MACHINE LEARNING APPROACH USING STATISTICAL MODELS FOR EARLY DETECTION OF CARDIAC ARREST IN NEWBORN BABIES IN THE CARDIAC INTENSIVE CARE UNIT
Authors: ArunaSri Mrs.Bethapudi , Y. Mouna  , S. Akshitha  , V. Samhitha
Published: September 2024

A frightening yet common medical emergency is cardiac arrest in infants who have just been delivered. The greatest care and therapy for these infants can only be provided if detected early. Recent studies have aimed to create reliable diagnostic techniques for early diagnosis of neonatal cardiac arrest by finding possible biomarkers and indications of this condition. Echocardiography, computed tomography, and other imaging modalities may aid in the early diagnosis of cardiac arrest. In order to identify cardiac arrest in newborn newborns in the Cardiac Intensive Care Unit (CICU) early on, this project seeks to construct a Cardiac Machine Learning model (CMLM) utilizing statistical methods. Multiple neonate physiological characteristics were used to identify the cardiac arrest occurrences. Predictive models for cardiac arrest were constructed using statistical modeling approaches, including logistic regression and support vector machines. The suggested methodology will be used in the CICU to facilitate the early identification of neonatal cardiac arrest. With a training (Tr) comparison area, the suggested CMLA achieved a delta-p value of 0.912, an FDR value of 0.894, an OR value of 0.076, a prevalence threshold value of 0.859, and a CSI value of 0.842. The suggested CMLA achieved test-specific values of 0.896 for delta-p, 0.878 for FDR, 0.061 for FOR, 0.844 for prevalence threshold, and 0.827 for CSI in a testing (Ts) comparison range. Babies induced cardiac arrest in the neonatal intensive care unit will have a lower risk of death and morbidity as a result.
An Analytical Study on Challenges of Anganwadi Workers during Post Covid: A Review
Authors: - Kalavati H. Kamble
Published: September 2024

Anganwadi workers provide primary health care as part of India's national health system that is affordable and accessible to the local population. Also, since most of the workers are from the same village, it is easy to trust them, which makes it easier to help people. Anganwadi workers have played a vital role in helping people across the states deal with the pandemic on a grassroots basis. Their contribution to providing basic health care, including immunization and nutrition, to large rural population and combating the pandemic was recognized as ‘unparalleled’ and ‘Commendable’. Meanwhile, the Anganwadi workers also faced many challenges. Present paper showing the challenges and problems faced by Anganwadi Workers during the Post Covid.
Assessing Visceral Fat Percentage with Advancing Age in Women using Bioelectric Impedance Analysis
Authors: - Supriya S Thakur , - Aruna Vinchurkar
Published: September 2024

Obesity and related morbidities are rising globally. This study aims to evaluate the relationship between visceral fat percentage (VF%) and advancing age in 126 female participants aged 20-70 years. These participants underwent anthropometric measurements and Bioelectric Impedance Analysis (BIA). The correlation between VF% and advancing age was 0.42 (P<0.001). BIA is a simple and effective measurement technique for estimating VF%, which can be performed by trained health professionals. This study demonstrated a strong correlation between VF% and advancing age in females.
The Government Expenditure of Education in Ethiopia: Impact and Prospects Ahead
Authors: - Seblewongel Wasihun , - Sure Pulla Rao
Published: September 2024

Ethiopia is not an exception to the rule that government spending on education has a significant influence on a nation's economic progress. The impact of government investment on education on Ethiopia's economic growth is examined in this article. Ethiopia has significantly expanded its educational spending in the last ten years with the goal of raising literacy rates, boosting school enrollment, and advancing the development of human capital overall. Positive results like increased enrollment rates and improved educational access have been a result of this investment, and these are crucial for developing a competent labor force and promoting economic growth. However, a number educational issues, such as poor infrastructure, subpar teachers, and regional differences in resource distribution, affect how beneficial this investment will be. It is observed that government expenditure on education in Ethiopia is significant, there are still areas that require attention in order to maximize its impact on the country's economy. By addressing these challenges and continuing to invest in education, Ethiopia can further enhance its economic potential and promote sustainable development for the future.
Impact of Molecular Identification of Palm leaves on the preservation and conservation of Palm Leaves-Tala patra Manuscripts
Authors: - Ashwini M , - Ramakrishna Bhat K
Published: September 2024

Palm leaves manuscripts preservation is the main target of this research work. Therefore, this research study aimed at molecular identification of palm leaves by DNA Barcoding to assess the potential level on manuscript preservation. This study aims to amplify the rbcL and matK genes in palm leaves collected from different regions of Bangalore. The DNA was isolated by CTAB method and the amplification was done by PCR analysis. DNA barcoding proved to be an efficient tool for proper discrimination of the related species by generating standers that can be used universally. rbcL: A gene found in the chloroplast genome, encoding a large subunit of the enzyme ribulose-bisphosphate carboxylase. matK: Another chloroplast gene coding for maturase K, involved in splicing group II introns.
The discrimination is done by accurately sequencing the standard gene region in a very short time (Hebert et al., 2003). rbcL and matK have been having most recommended and vasty studied DNA barcodes for plants, as they are proved by PWG (Pair wise group) to be potential standardized barcodes for plant DNA barcoding. These barcodes are used to properly identify and discriminate any native or foreign plant species (Maloukh et al., 2017). This work guides us the impact/role of molecular identification-DNA Barcoding of palm leaves on the preservation of Palm leaves manuscripts
Queer Narratives in Indian Cinema : A Comparative Study of Traditional and Modern Depictions" Films Like Taali , Haddi , Super Deluxe , Margarita with a Straw and Aligarh
Authors: - Anindita Dey
Published: September 2024

Indian cinema has historically reflected societal attitudes towards LGBTQ+ identities, with early portrayals often confined to stereotypes and marginal roles. Traditional films frequently depicted queer characters as either comedic caricatures or tragic figures, reinforcing societal biases and limiting authentic representation. This study examines the evolution of queer narratives in Indian cinema, highlighting the significant shift towards more nuanced portrayals in contemporary films. Films such as Taali (2023) and Margarita with a Straw (2014) showcase a move towards depth and empathy, reflecting broader societal changes and greater awareness of LGBTQ+ issues. Taali offers an authentic portrayal of a transgender activist, while Margarita with a Straw provides a ground-breaking depiction of a bisexual woman with a disability. Similarly, Aligarh (2015) and Super Deluxe (2019) demonstrate a departure from superficial portrayals, focusing on the complexities of queer experiences. Despite progress, Bollywood still grapples with outdated stereotypes, underscoring the need for ongoing advocacy and reform. This study emphasizes the importance of these evolving portrayals in fostering a more inclusive cinematic landscape and contributing to societal understanding of LGBTQ+ experiences.
Beyond the Horizon: Understanding Rural Secondary School Dropout through Case Studies
Authors: - Shaweta Miglani , - Raminder Singh
Published: September 2024

Despite numerous initiatives targeted to improve education outcomes, secondary school dropout rates in rural India remain a tenacious challenge. This paper sheds light on the underlying causes of dropout rates in rural areas through a qualitative case study approach. Drawing on in-depth interviews with rural students and their parents, this study examines the interplay of poverty, gender disparities, lack of access to quality education, and social expectations that contribute to students' decisions to leave school. The findings disclose the nuanced and complex ways various dynamics intersect and influence a student's educational trajectory. By exploring the personal, familial, and community factors that shape educational experiences, this study intends to contribute to a more comprehensive understanding of the dropout phenomenon in rural India. The findings have implications for policymakers, educators, and community leaders seeking operative strategies to address this prominent issue.
Weaponization of Social Media – Challenges and Responses
Authors: - Md. Imran Wahab
Published: September 2024

The use of social media as a tool for manipulation poses significant challenges worldwide, affecting public sentiment, intensifying divisions, and endangering democratic systems. This article investigates these issues and examines the responses from governments, tech companies, and civil society.
The swift evolution of social media has changed the way we communicate while also facilitating the rapid dissemination of false information and polarizing narratives, threatening societal unity. Researchers emphasize the impact of algorithms in creating echo chambers and filter bubbles that deepen polarization. Additionally, malicious actors take advantage of these platforms to propagate disinformation, sway elections, and incite violence.
In response, initiatives such as enhanced fact-checking, media literacy programs, and better content moderation by social networks are being implemented. Regulatory actions to promote transparency and accountability are also recommended, alongside international collaboration to combat cross-border online threats. A comprehensive strategy involving technology, regulation, international co-operation and community resilience is essential to protect democratic ideals in our interconnected society.
Experiences of Program Heads in Supervising Teachers: A Phenomenological Study
Authors: - Elton John B. Embodo , - Haydee D. Villanueva
Published: September 2024

The supervision of teachers is essential for ensuring effective teaching methods, ongoing professional growth, and student success. This study explored the experiences of program heads in supervising teachers. It was conducted in a local college in Tangub City, Misamis Occidental. The phenomenological design was used in the study. Eleven program heads served as the participants selected through the purposive sampling technique. The Interview Guide was used as the research instrument. Moustakas’ transcendental phenomenology of data analysis was utilized to analyze the data gathered. Results revealed the following main themes: the critical role of supervision in advancing teacher development and educational excellence, mutual learning and growth, the role of program heads in teacher supervision, overcoming challenges in teacher supervision, and effective communication strategies. Supervision improves teaching and learning quality, which supports professional development. The complex nature of supervisory roles requires adaptive strategies and strong support networks. It is recommended for program heads and teachers to establish open communication to help address the challenges encountered during supervision.
A Juridical Study on the Role of Justice collaborators in the Criminal Justice System for Drug Cases with the Death Penalty Threat
Authors: Nurhadi Syarif , Rahmat Diding , Sudarto Sudarto
Published: September 2024

The increase in drug abuse among adults has been rising significantly. This can be observed through reports in electronic and print media, which daily cover the arrests of drug abusers. Authorities responsible for combating drug abuse include the National Narcotics Agency and the Indonesian National Police. Internationally, there are several conventions governing the use and distribution of narcotics issued by global organizations such as the United Nations, including the Single Convention on Narcotic Drugs 1961 (United Nations Conference for Adoption of a Single Convention on Narcotic Drugs 1961), the Convention on Manufacture and Distribution of Narcotic Drugs (Geneva 1931), and the Convention for the Suppression of Illicit Traffic in Dangerous Drugs (Geneva 1936). Furthermore, it is important to note that drug traffickers involved in the production, import, export, or distribution of Class I and II Narcotics can face the death penalty if the amount of narcotics distributed exceeds certain limits. The death penalty can also be applied to traffickers who engage in activities such as offering narcotics for sale, selling, purchasing, receiving, acting as an intermediary in transactions, exchanging, or delivering Class I and II Narcotics when the quantity exceeds a specified amount. In relation to law enforcement efforts, the term justice collaborator refers to a criminal offender who is willing to cooperate with law enforcement to expose certain organized criminal cases that pose a serious threat. These offenses include corruption, terrorism, narcotics, money laundering, human trafficking, and other organized crimes. In Supreme Court Circular (SEMA) Number 4 of 2011, a justice collaborator is also referred to as a cooperating witness.
Hubungan Pengetahuan Personal Hygiene dan Perilaku Hygiene dengan Kejadian Keputihan
Authors: Novita  , Sukmawati
Published: September 2024

Masalah kesehatan reproduksi perempuan yang buruk telah mencapai 33% dari jumlah total beban penyakit yang diderita para perempuan di dunia salah satunya adalah keputihan. Di Indonesia pada tahun 2011 sebanyak 50% remaja Indonesia mengalami keputihan. Kemudian pada tahun 2012 sebanyak 60% remaja pernah mengalami keputihan, sedangkan tahun 2013 hampir 70% remaja pernah mengalami keputihan.Untuk mengetahui hubungan pengetahuan tentang personal hygiene dan perilaku hygiene dengan kejadian keputihan pada remaja putri di SMA Muhammadiyah 11 Rawamangun periode tahun 2017. Metode penelitian yang digunakan adalah analitik dengan pendekatan cross sectional. Populasi dalam penelitian ini adalah seluruh remaja putri di SMA Muhammadiyah 11 Rawamangun tahun 2017, dengan jumlah sampel 147 orang. Hasil penelitian terdapat 77 responden yang mengalami keputihan dan memiliki pengetahuan kurang tentang personal hygiene, dimana p value = 0,000 artinya ada hubungan antara pengetahuan personal hygiene dengan kejadian keputihan. Pada responden yang memiliki perilaku kurang dan mengalami keputihan sebanyak 74 responden (97,4%), dimana p value= 0,000 artinya ada hubungan antara perilku hygiene dengan kejadian keputihan. Dari hasil penelitian didapatkan adanya hubungan pengetahuan personal hygiene dan perilaku hygiene dengan kejadian keputihan pada remaja putri di SMA Muhammadiyah 11 Rawamangun tahun 2017.
The Integrative roles of Pharmaceutical care Management and Nursing – A Comprehensive Review
Authors:   AL Suwailem Yazeed Abdullah, AL Solami Khalid Aqall, AL Mutairi Hamoud Zayed, AL Mutairi Salma Salem and AL Dossary Bashayer Draan
Published: September 2024

The integration of pharmaceutical care management and nursing plays a critical role in enhancing healthcare delivery, improving patient outcomes, and ensuring medication safety. This review explores the overlapping responsibilities of pharmacists and nurses, highlighting areas where collaboration can bridge gaps in patient care. By examining existing literature and case studies, this article identifies the synergistic benefits of interdisciplinary approaches, such as improved medication adherence, reduced errors, and more holistic patient care. However, challenges to effective integration remain, including communication barriers, differing scopes of practice, and lack of interprofessional education. Strategies to overcome these challenges are discussed, with recommendations for implementing standardized protocols, fostering interprofessional education, and leveraging technology to streamline communication. This review also emphasizes the need for healthcare organizations to adopt collaborative care models that optimize the roles of pharmacists and nurses, ensuring efficient use of resources and enhanced patient safety. The findings suggest that promoting integrative practices can significantly improve healthcare outcomes and patient satisfaction, making a strong case for continued efforts in advancing interdisciplinary collaboration.
AS FINALIDADES DA EDUCAÇÃO NA MODERNIDADE LÍQUIDA
Authors: Jacinto de Castro Lopes Talita , Purificação Marcelo Máximo
Published: September 2024

Neste artigo exploramos os principais conceitos associados à “Modernidade Líquida” como: emancipação, individualidade, tempo/espaço, trabalho e comunidade, bem como o significado de “derretimento dos sólidos”. Fizemos uma análise sucinta sobre quem foi Zygmunt Bauman, nacionalidade, influência, histórico, fases. Também embarcamos na tentativa de diferenciar modernidade sólida e líquida através dos conceitos de Bauman e por fim analisamos as finalidades da escola, segundo a Lei de diretrizes e bases da educação nacional, Lei nº 9.394/1996, tendo como plano de fundo os conceitos do livro Modernidade Líquida.
Implementasi Total Quality Management dinegara berkembang : Studi Literatur
Authors: Mujaddid Mujaddid , Astutik Widi Astutik , Syakia Muflihat  , Muh.Faiz Fitrawan
Published: September 2024

Tujuan dari makalah ini adalah untuk meneliti implementasi Total Quality Management (TQM) di negara-negara berkembang. Penelitian ini terbatas pada studi yang dipublikasikan selama sepuluh tahun terakhir di basis data ScienceDirect. Tinjauan pustaka telah memberikan wawasan terkait implementasi TQM di negara-negara berkembang. Misalnya, di beberapa negara berkembang seperti Malaysia, Turki, Thailand dan India melaporkan bahwa implementasi TQM memiliki dampak positif pada kinerja organisasi. Sementara dalam penelitian lain, beberapa peneliti menunjukkan Critical Success factor (CSF) dari implementasi TQM di Malaysia, Iran, India, Thailand, dan Turki. Dapat disimpulkan bahwa CSF yang paling banyak digunakan dalam implementasi TQM adalah leadership, training, customer-focused, supplier relation, benchmarking, continuous improvement, employee involvement, work culture, information and data management factors.
Simptominis hemorojaus gydymas
Authors: Saladžinskas Žilvinas
Published: September 2024

Hemorojus – tai dažna anorektalinė liga, pasireiškianti simptomais, tokiais kaip kraujavimas, niežulys, skausmas ir hemoroidinių mazgų prolapsas. Daugeliui pacientų pasireiškia lengvi simptomai, kuriuos galima gydyti konservatyviais metodais. Šiame straipsnyje apžvelgiami įvairūs hemorojaus gydymo metodai, įskaitant konservatyvius gydymo būdus (mitybos ir gyvenimo būdo korekciją) bei medikamentinį gydymą. Pagrindinis dėmesys skiriamas vietinių preparatų naudojimui, įskaitant analgetikus, steroidus ir flebotonikus. Straipsnyje taip pat aptariamos ambulatorinės procedūros, tokios kaip hemoroidų perspaudimas elastiniais žiedais ir skleroterapija.
Pagrindinis antioksidantas: kodėl glutationas yra būtinas?
Authors: Čapkauskienė Sandrija , Pudžiuvelytė Lauryna , Stabrauskienė Jolita
Published: September 2024

Glutationas, dažnai vadinamas pagrindiniu natūraliu organizmo antioksidantu, padeda palaikyti ląstelių sveikatą ir kovoti su oksidaciniu stresu. Šis mažos molekulinės masės tripeptidas, sudarytas iš amino rūgščių – glutamato, cisteino ir glicino – labai svarbus detoksikacijos procesams, imuninės sistemos veiklai ir apsaugai nuo oksidacinės pažaidos. Atsižvelgiant į jo reikšmę, labai svarbu palaikyti pakankamą glutationo kiekį organime, siekiant užtikrinti bendrą sveikatą ir užkirsti kelią ligoms.
Deutlich mehr Flexibilität: mobile Cobot-Lösung
Authors: Vollrath Klaus
Published: September 2024

Automationslösungen sind stets Gratwanderungen, die Kompromisse zwischen Produktivität und Einsatz-Flexibilität erfordern. Eine neue Cobot-Variante überzeugt bei wechselnden Aufgabenstellungen und in der Zusammenarbeit von Mensch und Maschine.
Verbesserte HalbleiterInspektion bis 2030
Authors: Menard Bruno
Published: September 2024

Die weltweite Halbleiterknappheit, die im Jahr 2021 begann, prägt weiterhin die Welt. In den USA und in Europa soll massiv in die Elektronikfertigung investiert werden, um die Wettbewerbsfähigkeit zu stärken und Abhängigkeiten zu reduzieren.
Steifere Führungen für Folgeverbundwerkzeuge
Authors: Nobs Stefan
Published: September 2024

Die japanische Firma Ichimura Seisakusho ist Hersteller von elektromechanischen Präzisionsteilen. Die dafür erforderlichen Hochleistungs-Werkzeuge für Folgeverbundpressen werden im eigenen Hause entwickelt, hergestellt sowie stetig optimiert.
THE STUDY OF “INFLUENCE OF ORGANIZATION’S WELLBEING INITIATIVES ON STAFF COMMITMENT” SPECIAL REFERENCE TO A SELECTED STATE UNIVERSITY”
Authors: Mr A SUJENDRAN
Published: September 2024

In the twenty first century every organizations are operating in a very competitive environment. So, Higher Education Institution’s environment (University) is very competitive. In this situation, operational level employee’s job involvement is very important factor for Higher Education Institution’s. Therefore, the aim of this study is to analyze the levels of quality of work life, employee well-being and job involvement at a selected University. This study attempts to find out the relationships among quality of work life, employee wellbeing and job involvement of the University, where the quality of work life and employee wellbeing are independent variables, while the job involvement is the dependent variable. Structured questionnaire is used to collect the data for this study and general information include in part one and research information include in part two. The population of the study is about 310 operational level employees in the University and primary data that will be used for the study of operational level employees who are working using stratified random sampling. The collecting data will be analyzed using unilabiate and bivariate analysis. In accordance with literature review and existing findings, there are literature and empirical knowledge gaps regarding the relationships among quality of work life, employee well – being and job involvement of the Industries. This study will be conducted to fill these gaps at the Eastern University, Sri Lanka.