bluuebunny/crossref_metadata_2025 huggingface dataset:
From Linear to Circular: A Comprehensive SWOT Analysis of India’s Circular Economy Potential
Authors: Kumar Anil
Published: February 2025

The conventional linear "take-make-dispose" approach has exacerbated the problems of environmental degradation and climate change by accelerating resource depletion, increasing greenhouse gas emissions, and producing a large amount of solid waste (Ellen MacArthur Foundation, 2013). An efficient substitute for the linear economy paradigm is the circular economy model. It fosters sustainable economic growth through effective resource-saving techniques like recycling, remanufacturing, industrial symbiosis etc. This SWOT analysis focuses on a comprehensive study of the Circular Economy in India and aims to provide policy recommendations for improving Circular Economy practices in India. It is backed by a systematic study of policy documents, data analysis, and literature as well as comparative assessments employing case studies from around the globe, based on information obtained from authentic sources. The findings of this research work suggest that while the circular economy paradigm has enormous potential to transform India due to technical improvements, foreign investments, and other factors, it is also threatened by various obstacles such as cultural barriers and market instabilities. However, focused efforts and targeted interventions would be needed to overcome these barriers.
Variation Of Native Arabic Speakers' Responses To The Question Kaifa Haluk On YouTube Media: A Sociolinguistic Study/ Variasi Jawaban Penutur Asli Arab terhadap Pertanyaan Kaifa Haluk Di Media YouTube: Kajian Sosiolinguistik
Authors: Lillahi Wahdah Dainunah , Tamarisa Syarova Ilvi , Tatang
Published: February 2025

This study examines the variation in native Arabic speakers' responses to the question kaifa haluk/ كيف حالك (How are you?) in the context of communication on the YouTube platform, specifically through the Iday Adventurer channel. The study aims to describe the forms of responses given by native Arabic speakers and to analyze the social factors influencing language choices, such as the use of formal language (fusha) and everyday language (’amiyah dialect). Data were collected using the Video Content Analysis (VCA) technique, which involves converting spoken interactions in videos into text data for qualitative analysis. The findings show a range of responses tailored to social context and the relationships between speakers, generally influenced by factors such as age, educational background, and the closeness of social ties. This study concludes that digital communication, particularly on YouTube, reflects rich sociolinguistic dynamics, where native Arabic speakers adjust their language choices according to situational and social backgrounds. This research provides additional insight into Arabic language variation on social media and the role of social context in the use of informal and formal language in the digital realm.
Authority control of Arabic persons names in the union catalog of Egyptian Universities Libraries Consortium (EULC): an evaluative study
Authors: Hassan Ibrahim
Published: February 2025

The study aims to monitor the reality of  the Authority control of Arabic names in the Union Catalog of Egyptian Universities Libraries Consortium (EULC), in terms of identifying the rules and mechanisms used when drafting Arabic persons names entries in the bibliographic records on the Future Library System (FLS), the procedures that cataloguers perform when drafting Arabic names entries, the extent of their ability to carry out the Arabic names reference control process in bibliographic records and create reference records on the future system, and identifying the obstacles and issues that they face when drafting Arabic names entries and proposals.
One of the most prominent findings of the study, there is no unified nor standardized policies and practices for catalogers rely when drafting entries for Arabic persons names in the bibliographic records in the Union Catalog, as the drafting process depends on catalogers’ diligence, whether or not they possess the skills, without relying on an already existing authority file.
The study also recommended that the necessity of developing work tools and policies that are applied to train and qualify catalogers on working in the Union Catalog in accordance with modern trends in the field, and not to pay attention to quantity at the expense of quality.
Consent as Friction
Authors: Guggenberger Nikolas
Published: February 2025

The leading technology platforms generate several hundred billion dollars annually in revenue through algorithmically personalized advertising—with pernicious effects on our privacy, mental health, and democracy. To fuel their data-hungry algorithms, these platforms have long conditioned access to their services on far-reaching authorizations, embedded in boilerplate terms, to extract their users’ data. Until recently, privacy-sensitive alternatives were unavailable—even for a premium. Users faced a stark choice: submit to surveillance or forgo digital participation. I term this business practice “surveillance by adhesion.”
     In July 2023, however, the European Court of Justice ruled in Meta Platforms Inc. v. Bundeskartellamt that surveillance by adhesion violated the European Union’s General Data Protection Regulation. To comply with the EU’s new regulatory paradigm, the leading (predominantly American) platforms must fundamentally revise their business models by either abandoning personalized advertising or obtaining individuals’ informed consent. In practice, the EU’s stringent guardrails—which mandate providing users with “real choice” beyond mere consent pop-ups and granular control—may render user consent so onerous to secure, precarious to sustain, restrictive to operationalize, and prone to litigation that they undermine the commercial viability of personalized advertising. Rather than empowering users to exercise control over their data, the consent mechanism may thus manifest as a vehicle for welcome friction, prompting a shift toward less invasive contextual advertising.
     Building on these insights, this Article contends that U.S. policymakers and regulators should, and indeed can, likewise leverage consent as friction to undermine the economic viability of personalized advertising and other harmful surveillance-driven business models. This approach offers a pragmatic alternative to failed notions of user control over data, especially as democratic data governance too often remains beyond reach. Although the EU’s new regulatory paradigm offers one model, there are multiple avenues to harness consent as a source of friction across different legal contexts. In fact, state-level biometric privacy laws exemplify this strategy’s efficacy domestically. Their qualified consent requirements have thrown so much sand in the gears of biometric data collection and use that several leading technology companies have refrained from launching intrusive facial recognition applications altogether. By adopting this friction-based strategy, the Federal Trade Commission and state privacy enforcers can effectively establish potent data usage limitations.
The Role of Epigenetics in Plant Development and Adaptation: A Comprehensive Molecular and Ecological Perspective
Authors:   Freelance Writer, Mumbai, India, Kajrolkar Amita
Published: February 2025

Epigenetics has revolutionized ideas on plant genetics and development by introducing mechanisms beyond the immediate genetic systems. Unlike the concept of fixed genetic methodology, epigenetics is mobile, with inheritable modulations in gene expression without affecting the genetic code. Such changes are DNA methylation, histone modifications, and non-coding RNAs that collectively allow plants to respond to both environmental stimuli and developmental signals in a dynamic manner.1,2 As protective caps for TEs, modulators of gene expression, and general guardians of genome integrity, epigenetic regulations offer plants indispensable resources for phenotypic flexibility and robustness.3,4 In plants, epigenetic regulation emphasizes developmental steps such as embryogenesis, flowering period, and organogenesis. For example, during embryogenesis, DNA methylation and specific histone modifications coordinatively regulate cell fate determination.5 Furthermore, histone marks lead to the silencing of Flowering Locus C (FLC) to ensure that plants flower when environmental conditions are favorable.6 Likewise, siRNAs and miRNAs serve as stress response modulations that involve targeted transcript and chromatin sites for modification.7 Thus, one can note that plants can ‘remember’ stress through epigenetic modifications, more of which will be said below. Epigenetic imprints formed due to developmentally important stresses, like drought or heat, can be passed on to other generations, enabling them to handle the like conditions better. They established this phenomenon to show that epigenetics plays an evolutionary significance in plants.8,9 Moreover, epigenetics controls plant resistance genes to some abiotic stresses, including pathogen attacks, by activating defense-
related genes or suppressing invasive genes through RNA silencing pathways.10 Nevertheless, epigenetics is more than a biological phenomenon; it is an agroeconomic and biotechnological innovation in disguise, including research about ­epigenetically modified weather-resistant crops, epigenetically improving hybrid stress using memory, and applying its components to eco-oriented practices.11,12
Although basic epigenetic techniques include recombinant DNA techniques, which have been in use for some time now, recent innovations in genome editing technologies, especially CRISPR-based epigenetic tools, have brought closer the ability to engineer epigenetic modification at near molecular level as described by Gao & Chen13 and Mo & colleagues14 using these innovations solutions to complex global problems which include food security and loss of biodiversity.45,46

Altogether, epigenetics provides valuable information about the interaction between plant’s genomes and their environment. This ­integration has allowed it to revolutionize agricultural practices and address other ecological issues affecting plant systems in an area of tremendous environmental change.
Evidence based risk reduction recommendations for people at risk or with breast cancer-related lymphedema.
Authors: Brunelle Cheryl , Hunley Julie H.
Published: February 2025

"The Pathways Editorial Board is pleased to promote recently published research along various lymphedema-related themes from the 2023 ACS - LANA Summit, “Forward Momentum - Future Steps in Lymphedema Management.” This is the first of a series of interviews with some of the authors who were involved, discussing the process, but more importantly, soliciting their ideas of how to translate this new knowledge into clinical practice. This article presents new evidence-based risk reduction recommendations for individuals at risk of or living with breast cancer-related lymphedema (BCRL). Based on extensive research and expert consensus, the recommendations clarify which daily precautions are supported by scientific evidence and distinguish between guidance for at-risk individuals versus those already diagnosed with BCRL. Key findings include the impact of blood pressure measurements, injections, skin care, exercise, and travel on lymphedema risk. The article also highlights efforts to disseminate these guidelines to clinicians, patients, and healthcare organizations, aiming to replace outdated precautionary advice with clear, research-backed recommendations. The ultimate goal is to enhance patient education, clinical practice, and long-term management of BCRL.
In the trenches. A provincial advocacy story.
Authors: Chandler Christine
Published: February 2025

The British Columbia Lymphedema Association (BCLA) conducted a patient survey and established a committee to advocate for funding compression garments for all lymphedema patients. Their efforts led to the submission of a comprehensive application to the B. C. Ministry of Health, now under review. The BCLA continues to focus on early diagnosis and public awareness initiatives while exploring regional clinic proposals.
Infection and skin trauma incrementally increase the risk of breast cancer-related lymphedema.
Authors: Fu Mei Rosemary
Published: February 2025

This article explores the impact of daily-living activities on the risk of breast cancer-related lymphedema (BCLE), a condition affecting 5–20% of breast cancer survivors. A large cross-sectional study of 567 patients, published in Annals of Surgical Oncology, examined various risk factors, revealing that infection, cuts/scratches, sunburn, burns, and insect bites significantly increase the odds of developing BCLE. Conversely, carrying a shoulder bag on the affected arm may have a protective effect. The findings emphasize the importance of self-care and skin protection strategies to mitigate risk. While complete avoidance of daily-living risks is impractical, proactive skin care and injury prevention techniques can help manage BCLE risk. The study underscores the need for further prospective research to validate these findings and guide patient education.
Estudio DFT de los Mecanismos de Interacción de los Fármacos Clopidogrel y Clonidina
Authors: Ocampo Cárdenas Breyner , Dodero Gabriela , Noseda Grau Emilia , Simonetti Sandra
Published: February 2025

En este estudio, se investigan las interacciones entre los fármacos clopidogrel y clonidina. La clonidina se utiliza para tratar la hipertensión arterial mediante la disminución de la frecuencia cardíaca y la relajación de los vasos sanguíneos, para que la sangre pueda fluir más fácilmente a través del cuerpo. El clopidogrel es un agente antiplaquetario que inhibe la formación de coágulos en la enfermedad arterial coronaria, enfermedad vascular periférica y enfermedad cerebrovascular. Estos fármacos administrados en combinación podrían mejorar el tratamiento de la hipertensión arterial. Se identifican sitios activos del principio activo (API) del clopidogrel y la clonidina. El análisis se centra en la energía, las propiedades electrónicas y en los mecanismos de interacción entre ambos fármacos. Para llevar a cabo este estudio, se utiliza el software Gaussian 09. El análisis proporciona información valiosa para su aplicación en el desarrollo de polipíldoras cardiovasculares.
Software para la Evaluación de la Influencia de la Formulación de Elementos Finitos en la Simulación del Comportamiento de Estructuras Simples - Parte 2
Authors: Zera Santiago , López Daniel E. , Leiva Carlos J.
Published: February 2025

El uso de software basado en el Método de los Elementos Finitos (MEF) requiere conocer los distintos tipos de elementos y las variables implícitas en su formulación, como la discretización del campo incógnita, las funciones de forma, el esquema de integración numérica y la compatibilidad interelemental. El MEF es el método más utilizado para análisis estructural en diversas ramas de la ingeniería. Sin embargo, sus usuarios no siempre tienen en cuenta las variables involucradas ni la influencia que las mismas pueden tener en los resultados. En parte, esto se debe a que el software disponible no siempre permite interactuar con ellas. En este trabajo se describe un software desarrollado por los autores para la enseñanza del MEF que permite la interacción con estas variables para la evaluación de su influencia en los resultados de simulaciones estructurales. En la primera parte (S. Zera et al., Mecánica Computacional, 42:1587–1596, (2023)) se presentaron las capacidades del software para estudiar estructuras bidimensionales bajo estados planos de tensión y deformación y placas sometidas a flexión. En esta segunda parte se extienden sus capacidades para el estudio de estructuras de cáscara.
Performance metrics analysis: Evaluating machine learning models in the detection of cloud-based DDoS
Authors: Alozie Chisom Elizabeth
Published: February 2025

Tables 10 and 11 show the performance metric result of this experiment. The metrics used to evaluate the machine learning models are accuracy, precision, recall, f1-score, and computation time on new datasets and open-source datasets as shown in Tables 10 and 11. An 80:20 split of the overall dataset was used for the Model building where 80% was used for training and 20% was used for validation and testing. The objective of the evaluation is to assess the effectiveness of DDoS datasets in terms of their ability to detect DDoS attacks in the cloud system. The results demonstrate that the new dataset performed very well, achieving a 100% accuracy rate with Random Forest, SVM, Decision tree, and KNN, and then 98% with Naïve Bayes. An F1 score (measure) of 100% on all models except NB with 98%. This indicates that a model trained with a newly generated dataset performs very well, as it correctly predicts threats (precision) and captures all relevant cases of malicious traffic (recall) at a 100% rate in RF, DT, and KNN, 99% on SVM and NB with a 97% rate. On the other hand, the CSE-CIC-IDS2018 dataset was used for training a larger sample size since time constrain could not allow the generation of such a sample size in the new dataset. The RF, DT and KNN achieved 100% accuracy followed by NB at 99% and the SVM performs the lowest with an accuracy of 95%. as shown in table 11. It depicts that the CSE-CIC-IDS2018 dataset is a very good data source for the detection of DDoS on a cloud network.
Refugiados ante as dificuldades de reconhecimento da igualdade entre os povos e o desrespeito à cidadania e aos direitos fundamentais pelos estados
Authors:   Pontifícia Universidade Católica de São Paulo, Gonçalves Antonio Baptista
Published: February 2025

Os refugiados não escolhem sair de suas casas e de seus países por melhores condições econômicas, nem por empregos mais qualificados com maiores remunerações ou incremento na qualidade de vida, mas sim porque lutam por sobreviver e o fazem devido à necessidade, e ainda, não raro, deixam familiares e entes queridos para trás. A acolhida pelos Estados não é pacífica: intolerância, xenofobia, desrespeito e humilhações são alguns dos percalços a serem enfrentados. O Estado deveria conferir condições mínimas aos refugiados e respeitar sua cidadania e a igualdade dos povos, e conferir os direitos tidos como fundamentais. Na prática, os desafios ainda são muitos, e resistir para continuar a viver é o maior deles.
东西方绘画透视法差异及其在插画创作中的融合
Authors: 蒋礼
Published: February 2025

本论文探讨东西方绘画透视法的差异及其在现代插画创作中的融合应用。透视法作为艺术创作中的重要技术手段，不仅影响画作的空间表现力，还深刻反映了不同文化背景下的审美观念与价值取向。东方绘画中，传统透视法以散点透视为主，强调表现画面意境与神韵，弱化物理空间的准确性，注重画面整体的抒情性和流动性，如中国水墨画的表现技法。西方绘画自文艺复兴时期开始，通过透视法数学化、规则化的发展，建立了一套包括单点透视、双点透视及多点透视等系统化理论，尤其强调真实空间的再现，使得绘画作品在视觉上更具立体感。东西方透视法历经岁月碰撞与交流，逐渐在现代插画中实现了一定程度的融合，插画作品的创意形式不断演变，透视法的多样化呈现成为可能。本文通过对当代插画中融合实例的分析，探讨东西方透视法融合的可能路径及对插画创作的积极影响。本研究旨在为艺术创作者提供一种视角、理论基础以及实际应用的方法，助力插画领域在全球化背景下的创新性创作。
The influence of Management Information Systems (MISs) on the performance of the Public Procurement and Disposal of Public Assets Authority (PPDA)
Authors:   , Akiror Mary
Published: February 2025

The study sought to investigate the influence of Management Information Systems (MISs) on the performance of the Public Procurement and Disposal of Public Assets Authority (PPDA). Data was collected from 100 respondents, using self administered questionnaires and analyzed using the Statistical Package for Social Sciences (SPSS V.17). The findings substantiate that MISs was an integral part in promoting efficiency in organizational work processes. This implies that when management is committed to development and implementation of the MISs, this would promote effectiveness and efficiency in the PPDA’s performance. This is justification that MIS was paramount in improving organizational efficiency. The findings on objective two revealed that MIS had a positive significant effect on service delivery. The positive influence of MIS on service delivery is justification that to attain reliable, responsive, tangible, empathy and assurance during service delivery, there was need to have line managers and employees appreciate the role of MIS at the PPDA. The findings confirmed that MIS was a determining factor of information quality which is an implication that management’s willingness to develop a fully fledged MIS at the PPDA would enhance information quality at the PPDA and also result into production of accurate, reliable and relevant information. The study recommends that the management of PPDA should draw a lot of emphasis on MIS as this would greatly enhance the performance of the PPDA. This should be supported by effective and efficient governance structures which promote MIS among stakeholders in the procurement sector. On the other hand, PPDA should advocate for the production of accurate, relevant and reliable information through the use of the MIS that can be used by the different stakeholders. Considering that the study indicated a significant positive correlation between MIS and organizational performance, greater attention must be given to the perceptions held by the PPDA staff, PDEs and providers in relation to the MIS. Stakeholders in the procurement sector should undertake training of the employees in the use of MIS as this will help in developing their perceptions of usefulness and ease of use. This in turn will greatly influence service delivery in the sector. Staff need the assurance that by using the MIS option they will achieve greater job performance, save time, money and complete a given task better, than it would have otherwise been. From the findings, it is further recommended that in order to realize effective capacity utilization of the MIS, there should be a move from use of ICTs for elementary work such as word processing and integrate the current systems with customized electronic information management programmes which promote organizational performance. Management should consider putting in place a fully fledged customized MIS system which will coordinate the creation, management, maintenance and disposal of records.
The contribution of motivation to employee performance case study: World Vision Uganda, Karamoja region
Authors:   ,   Uganda Martyrs University, Akol Mary Hellen
Published: February 2025

The study sought to establish the relationship between motivation and employee performance a case study of World Vision Uganda, Karamoja Region. The study was guided by three objectives and these included the following; to assess the types of motivation that exists in the organization, to assess the effectiveness of motivation on staff performance and to examine the relationship between Motivation and organizational performance of staff in World Vision. The study was conducted using both quantitative and qualitative approach using survey, correlation and case study as research design. The research relied also on documentary review, structured interview, questionnaire research methods and techniques. The study population comprised a total of 60 employees and the sample size of the study was 52 which was determined using the sloven’s formula, n= N/1+Ne2 . Respondents were selected using simple random and purposive sampling. Data was analyzed using SPSS package to come up with complete research findings and statistics that enabled interpretation of results. The analysis from the empirical findings showed that tangible motivation was the most ranked factor for all the respondents that made up the sample survey. However a study from previous researchers used in this study showed that different results could be obtained from a bigger sample size or geographical location of the organization. This study therefore can be seen as an introduction to a more detailed study to be carried by future researchers on the field of employee’s motivation. The researcher also found out that many respondents performed well after being motivated although others disagreed that their performance was dependent on motivation. . However, the study found that motivation attributes to the variation in the performance of employees with a beta of 47.5% (0.475) and the remaining 52.5% is attributed to other factors other than motivation. It was also noted that there is a strong positive relationship between motivation and employee performance and the relationship is significant (r =.475, p<0.01). There was also a strong relationship between motivation and employee performance. However, the findings, recommendations and conclusions of the study revealed a strong relationship between motivation and employee performance. The study recommends additional research to be carried out to gain a continuous view, insight and knowledge of what motivates employees to perform best on their jobs. Employee motivation even after some 50years of research continues to be one of the problems and challenges facing organizations today. Furthermore factors such as technological advances, globalization, retrenchments etc leave employees with an uncertain future this is because most organizations today do not guarantee life employment’s for their employees as it was the case before
Impact of Adoption of Business Excellence Framework on Organizational Performance: A Systematic Review of the Literature and Development of Conceptual Model
Authors: P M Krishnan ,   Research Scholar, XIME Research Centre, Affiliated to University of Mysore, Bhatta NMK ,   Professor & Dean (Research) Xavier Institute of Management & Entrepreneurship, Bangalore (Formerly Professor IIM
Published: February 2025

Since 1987, many business excellence frameworks (BEFs) have been developed, post the launch
of the “Malcolm Baldrige National Quality Award and Baldrige Excellence Framework”. BFFs are
considered transformational tools to drive the current performance and sustainably secure future
growth. This study explored the effectiveness of the adoption of BEFs in improving organizational
performance and determined whether the adoption of BEFs is triggered by a desire to win a national
award or as an initiative for organizational transformation. Considering that many changes have
occurred in the excellence framework over the past 15 years, this study focused on the literature
published after 2005. Using the PRISMA framework, the authors shortlisted 53 papers for this
study. Many studies indicated that the framework was primarily used for the recognition process
of the national-level award program, and organizations considered the process of winning the
award as a destination instead of a significant milestone in the excellence journey. Moreover, this
study determined that insufficient data were presented in the available literature to investigate
the impact of adopting a BEF on organizations. Rigorous requirements of the award program and
complexity in understanding abstract-level requirements were the major reasons for not initiating
the adoption of the BEF for organizational transformation. Based on the findings of this systematic
literature survey, a conceptual model was established to understand triggers for BEF adoption and
the roadmap leading to organizational impact. Researchers in the future may use this model for
examining the effect of BEFs adoption organizational Performance and transformation.
Precautionary Screening for Covid-19
Authors:   PESS Modern College of Engineering, Pune, Maharashtra, India, Deshpande Meghana , Chavan Pratima , Kamathe Rupali , Joshi Kalyani , Ankolekar Shraddha , Bhusari Kahini , Bhagat Akshada
Published: February 2025

The Internet of Things (IoT) is a field that has been utilized to enable remote monitoring and control of home appliances. Automated system is required to develop to save a life of every individual and to stop spread of disease. In this paper real time implementation of face mask and temperature detection system implemented using Raspberry Pi 3 along with some additional features such as servo motor controlled door opening. For face mask recognition, deep leaning methodology used. The Convolution Neural Network is used for detection of face mask. If a face mask is worn and the temperature is below the designated threshold, the door will be unlocked. Conversely, if a face mask is not worn or the temperature exceeds the threshold, a buzzer will sound. The proposed system successfully achieves the results for precision 98 and recalls 99 values.
Deep Learning for Improved Breast
Cancer Detection: ResNet-50 vs VGG16
Authors:   Ph, A Patil Rupali , V Dixit V
Published: February 2025

Breast cancer continues to pose a major global health challenge, underscoring the need for advanced detection and classification methods for mammograms. This study examines the effectiveness of ResNet-50 and VGG16 models in detecting and classifying multiview mammograms. Early and accurate detection of breast cancer is essential for improving patient outcomes and reducing mortality rates. Our approach began with the preparation of mammography images using various image processing techniques, including transfer learning and median filtering. The processed images were then used to train ResNet-50 and VGG16 models for detection and classification tasks. Our experiments demonstrated impressive performance, achieving an accuracy of 96 and an F1 score of 94.66 on the Digital Database for Screening Mammography (DDSM) datasets. These results underscore the potential of deep learning models, particularly ResNet-50, in effectively detecting and classifying multiview mammograms.
MSRTC Bus Automation
Authors:   Assistant Professor, D Y Patil International University, DYPIEMR, Akurdi, Pune, Maharashtra, India, Shinde Sandhya , Wayadande Suchita , Shinde Shrawni , Gurav Raj
Published: February 2025

The MSRTC Bus Automation and Emergency Alert System is a comprehensive solution designed to enhance public security and safety within the Maharashtra State Road Transport Corporation (MSRTC) bus fleet. This smart assistance system encompasses features to mitigate risks such as rash driving, with accident detection and monitoring capabilities. Utilizing GPS technology and an intuitive Android application, users can conveniently track bus locations in real-time. In addition to providing real-time tracking, the system facilitates emergency alerts to hospitals, police stations, and bus depots, ensuring swift response in critical situations. With a focus on user-friendliness and intelligent features, this system aims to optimize public transport, catering to the needs of Smart Cities and promoting efficient and safe travel for passengers.
Advanced and Automatic Smart Street
Light using Dimming Control and
Motion Sensor
Authors:   Assistant Professor, Electronics and Telecommunication Engineering Department, DY Patil College of Engineering, Akurdi, Pune, Maharashtra, India, Shere Vivekanand , Barshikar Mrunmayee , Jangle Aditi , Desai Omkar
Published: February 2025

Our project for developing a Advanced and Automatic LED street light system with dimming control and smart sensor is reviewed. In this project, the street light system, in which lights on when needed and light-off when not needed. Currently, in the whole world, enormous electric energy is consumed by the street lamps, which are automatically turn on when it becomes dark and automatically turn off when it becomes bright. This is the huge waste of energy in the whole world and should be changed. Our smart street light system consists of a LED light, a brightness sensor, a motion sensor, and a short-distance communication network. The lights turn on before pedestrians and vehicles come and turn off or reduce power when there is no one. It will be difficult for pedestrians and drivers of vehicles to distinguish our smart street lamps and the conventional street lights, since our street lamps all turn on before they come. The present status and the future prospects of our smart start light project will be reviewed.
Advancements in Deep Learning for
Alzheimers Disease Diagnosis: A
Comprehensive Review
Authors:   Ph, S Bhosale Sonali , V Dixit Vaibhav
Published: February 2025

This research aims to advance the diagnosis and management of Alzheimer's disease (AD) by leveraging deep learning methodologies, providing a comprehensive quantitative evaluation of their efficacy compared to traditional machine learning models. A thorough literature review was conducted, focusing on the application of deep learning techniques in AD diagnosis. The study examined various biomarkers and datasets utilized in the field, evaluating their contributions to the accuracy and reliability of diagnostic models. The analysis encompassed both natural language processing and computer vision approaches, highlighting recent trends and innovations. Deep learning models demonstrated superior accuracy in diagnosing AD compared to conventional machine learning techniques. The quantitative analysis revealed significant improvements in early detection and diagnostic precision, showcasing the potential of these advanced methodologies. Despite the advancements, several challenges, such as data variability and model interpretability, were identified, indicating areas for further research. Comparative analysis with existing diagnostic approaches underscored the advancements in accuracy and reliability achieved through deep learning. The novelty of this research lies in its detailed quantitative assessment of deep learning techniques for AD diagnosis, providing a robust foundation for future advancements. Unlike conventional studies, this work offers a comprehensive numerical justification of the efficacy of deep learning models. The integration of diverse biomarkers and datasets, combined with the superior diagnostic performance, sets this study apart, highlighting the potential for significant improvements in AD diagnosis and management through continued innovation in deep learning methodologies.
Sentiment Analysis
Authors:   PG student, Department of Electronics and Telecommunication, Trinity College of Engineering  Research, Kondhawa Budruk, Pune, 411048, Maharashtra, India, Zore Soniya , Bhosale Amol , Chavan Pratibha
Published: February 2025

Social media platforms like Twitter have become a rich source of real-time data and public sentiment. Analysing sentiment on Twitter is essential for various applications, from brand monitoring to political analysis. This work focuses on Twitter sentiment analysis, employing natural language processing (NLP) techniques to categorize tweets as positive, negative, or neutral. We collect a large dataset of tweets, pre-process the text, and train machine learning models to predict sentiment. Our goal is to provide insights into public sentiment on various topics, trends, and events, which can be valuable for decision-makers in diverse domains.
Geo-Environmental Assessment: Evidence from Geotechnical and Chemical Insight for Irrigation Purpose, Nigeria
Authors: Ibrahim Ibrahim O
Published: February 2025

Aim of Study: Climate change constitute a serious challenge to food security globally. Its impact on food production has been alarming and this study aim to address the severe environmental problem linked to soil and weather variability condition.
Methodology: Selected exploratory pits within the study area for Geotechnical and chemical assessment were bored to elucidate the area for irrigation design that will serve the plantation. This study was done by getting ditch cutting samples at defined coordinates of the area. This facilitated better and deeper insight into the soil composition of the area.
Findings: The facies consisted of silty-sandy soil with some clayey-sandy soil and the area was thus noted more for its non-plastic property using Atterbergs test. Compaction analysis revealed maximum dry density that varied between 1263.0 kg/m3-1627.2kg/m3and Optimum moisture content that varied between 11.1% to 15.0. Compression Index used in determining the settlement potential of the fine-grained clay/silt material of the study area recorded 6.2 x 10-4 of P3 sample to 8.6 x 10-4 in P5 sample. Coefficient of volume compressibility (mv) varied 6.1 x 10-4 to 8.6 x 10-4.More importantly, Sulphate, Nitrate, Bicarbonate and Chloride have respectively shown a good area to enhance sugarcane plantation.
Conclusions: The area is tectonically stable as no tremor has been reported with underground water potential that can supplement the water need for irrigation of the proposed plantation. Chemical analysis of the soil has revealed its good for sugarcane plantation. Thus, study concluded that the soil of the study area is suitable for such purpose with Pad and Strip foundational footing recommendation.
Mapping Melancholy : Sentiment Analysis of Emotional Trends in Victorian Literature
Authors:   Assistant Professor, Government College Poogal, Bikaner, Tamanna Tamanna
Published: February 2025

Through a mixed-methods lens that pairs computational sentiment analysis with historical literary criticism, this paper investigates the complex relationship between emotional expression and socio-cultural context in Victorian literature. Centralizing the inescapable theme of melancholy, the study analyzes a representative corpus of Victorian texts through modern text-mining techniques—namely, application of sentiment lexicons, tokenization, and normalization. The session explores some fundamental aspects of the spatial and temporal dynamics of melancholic expressions with the help of digital mapping tools, especially concerning Victorian London. On a qualitative level, close readings demonstrate the subtle narrative strategies employed in the work that elicit melancholy; on a quantitative level, statistically significant trends in sentiment distribution crucially track with important historical events and socio-political changes
Comprehensive genomic and functional analysis of Leuconostoc lactic acid bacteria in alcohol and acetaldehyde metabolism
Authors: Gwak Joo-Han , Choi Yun Ji , Ayub Hina , Seol Min Kyeong , Kim Hongik , Jung Man-Young
Published: February 2025

Alcohol consumption can lead to the accumulation of harmful metabolites, such as acetaldehyde, contributing to various adverse health effects, including hangovers and liver damage. This study presents a comprehensive genomic and functional analysis of Leuconostoc suionicum VITA-PB2, a lactic acid bacterial strain isolated from kimchi, to elucidate its role in enhancing alcohol and acetaldehyde metabolism. Genomic characterization revealed key genes encoding alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH), providing insights into the metabolic capabilities of strain VITA-PB2. Phylogenomic analyses confirmed its taxonomic classification and genetic similarity to other Leuconostoc species. Functional validation through in vitro and in vivo experiments demonstrated superior ethanol and acetaldehyde decomposition abilities of strain VITA-PB2, with significant reductions in blood ethanol and acetaldehyde levels observed in rats administered with the strain. Further analysis indicated that while hepatic ADH activity did not significantly increase; however, ALDH expression was elevated. This suggests that the microbial ADH of strain VITA-PB2 contributed to ethanol breakdown, while both microbial and host ALDH facilitated acetaldehyde detoxification. These findings highlight the potential of strain VITA-PB2 as a functional probiotic for mitigating the toxic effects of alcohol consumption.
Functional importance of Ser323 in cysteine desulfhydrase and cystathionine gamma-lyase MccB of Staphylococcus aureus
Authors: Lee Dukwon , Lee Hyojeong , Byun Kyumi , Park Eun-Su , Ha Nam-Chul
Published: February 2025

Pyridoxal 5'-phosphate (PLP)-dependent enzymes participate in various reactions involved in methionine and cysteine metabolism. The representative foodborne pathogen Staphylococcus aureus expresses the PLP-dependent enzyme MccB, which exhibits both cystathionine gamma-lyase (CGL) and cysteine desulfhydrase activities. In this study, we investigated the role of Ser323 in MccB, a conserved residue in many PLP-dependent enzymes in the transsulfuration pathway. Our findings reveal that Ser323 forms a hydrogen bond with the catalytic lysine in the absence of PLP, and upon internal aldimine formation, PLP-bound lysine is repositioned away from Ser323. Substituting Ser323 with alanine abolishes the enzymatic activity, similar to mutations at the catalytic lysine site. Spectroscopic analysis suggests that Ser323 is essential for the rapid formation of the internal aldimine with lysine in wild-type MccB. This study highlights the crucial role of Ser323 in catalysis, with broader implications for other PLP-dependent enzymes, and enhances our understanding of the molecular mechanisms involved in the selective control of foodborne pathogenic bacteria.
Humanização No Atendimento À Saúde Centrado No Paciente
Authors: Batista Rodrigo de Aguiar Santos , Barros Carolina Ferreira , Linhares José Augusto de Souza , Lopes Maria Rita Feijão , Filho Manoel Borges dos Santos , Silva Fábio Casagrande Jobim da , Santiago Áthila Silveira , Juncá Beatriz Chaves Nani , Catani Bárbara Suelen , Oliveira Lisandra Campos de
Published: February 2025

Este estudo teve como objetivo analisar as práticas de humanização no atendimento à saúde centrado no paciente, destacando a interdisciplinaridade e as estratégias institucionais que favorecem a construção de uma assistência mais integral. Trata-se de uma revisão narrativa da literatura, realizada entre janeiro e fevereiro de 2025, por meio de busca sistemática nas bases de dados SciELO, PubMed e Google Scholar. Os descritores utilizados foram combinados por operadores booleanos, resultando na seleção de 10 estudos publicados entre 2019 e 2024, que atenderam aos critérios de inclusão e exclusão previamente estabelecidos. A análise dos estudos revelou que a humanização transcende a perspectiva biológica e demanda uma abordagem ampliada, que contemple a escuta ativa, a valorização da subjetividade e o fortalecimento dos vínculos entre profissionais e pacientes. Observou-se também que a articulação interdisciplinar potencializa práticas humanizadoras, mas ainda enfrenta desafios estruturais no contexto institucional. As principais limitações do estudo referem-se à natureza narrativa da revisão e à seleção restrita a publicações em português e inglês. Recomenda-se a realização de estudos empíricos para aprofundar as investigações sobre o impacto das práticas humanizadoras nos serviços de saúde.
Efeitos Neuroprotetores Da Lactação Materna: Uma Investigação Sobre A Prevalência De TDAH
Authors: Faria Ana Cláudia Gambarotto Diogo de , Oliveira Celine Silva de , Vockes Victoria Vieira , Rufino Maria Paula Penha , Santos Evelyn Larissa Viana , Cruz Maria Yasmin Ribeiro da , Holanda Francisca Maria Portela Peres de , Castro Lucélia da Cunha , Torres Beatriz Lainy Penha Marques , Lima Jaine Magalhães Paz de
Published: February 2025

O presente estudo teve como principal objetivo identificar a relação entre o aleitamento materno e o índice de sintomas relacionados ao Transtorno de Déficit de Atenção/Hiperatividade (TDAH), isso por meio de revisão sistemática seguindo os princípios PRISMA e utilizando a estratégia PICO, assim, foram analisados dez estudos publicados entre os anos de 2019 e 2024. Os artigos apontam para uma correlação positiva entre maior período de lactação materna exclusiva e menores taxas de diagnósticos de TDAH, melhor neurodesenvolvimento e menos sintomas associados a desatenção e hiperatividade. O leite materno é fonte rica em nutrientes importantes para o crescimento saudável, como ácidos graxos poli-insaturados e piridoxal, que promovem mielinização neuronal e consequente desenvolvimento cognitivo. Barreiras biopsicossociais, como retorno ao ambiente laboral e falta de rede de apoio diminuem o período de amamentação, trazendo prejuízos à mãe e ao filho. Conclui-se que o aleitamento deve ser incentivado, pois além de melhorar o desenvolvimento físico infantil, promove o neurodesenvolvimento e previne sintomas de transtornos comportamentais a longo prazo, como é o caso do Transtorno de Déficit de Atenção/Hiperatividade.
Private Rooms in Peer-to-Peer Accommodation: Employing Machine Learning to Determine Revenue Drivers
Authors:   Kozminski University, Poland, Kiczmachowska Ewa E.
Published: February 2025

Purpose: The goal of this study was to identify the performance determinants of private rooms offered via peer-to-peer accommodation (P2PA) platforms.

Design/methodology/approach: Based on property level data of Airbnb, the applications of machine learning clustering and artificial neural networks methods were proposed to identify the performance determinants of private room performance defined as yearly revenue.

Findings: The results indicate that the most important revenue determinants were maximum number of guests, number of photos, number of bathrooms, location, and cancellation policy, as well as high availability of the property throughout the year. The highest revenues were achieved by 2–3 person rooms with at least two bathrooms, 4-person rooms, or rooms located around the Central Railway Station. However, properties with at least 2 bathrooms tend to deliver high revenue, regardless of location. Furthermore, a sufficient number of photos and a flexible cancellation policy could offset location disadvantages and deliver higher revenues in distant vs. central locations.

Research limitations/implications: The limitations of this study are that it covered only one destination during a 12-month period, which encompasses yearly seasonality, but might include some exceptional events. Replication for other destinations (urban or non-urban) or timeframes would be valuable future research recommendations.

Originality/value: This study adds threefold to the P2PA performance determinants stream. First, it offers an application of machine learning methods to identify property and host features and behaviours that contribute to high performance. Second, as opposite to the majority of available research, it defines performance as revenue rather than price. Third, building on the hedonic price theory, it sheds light on how to manage a complex offer for private rooms in P2PA, in contrast to entire homes/apartments that researchers have focused on to date.
Detection of concha bullosa using deep learning models in cone-beam computed tomography images: a feasibility study
Authors: Shetty Shishir , Mubarak Auwalu Saleh , David Leena R , Jouhari Mhd Omar Al , Talaat Wael , Kawas Sausan Al , Al-Rawi Natheer , Shetty Sunaina , Shetty Mamatha , Ozsahin Dilber Uzun
Published: February 2025

Background: Pneumatization of turbinates, also known as concha bullosa (CB), is associated with nasal septal deviation and sinonasal pathologies. This study aims to evaluate the performance of deep learning models in detecting CB in coronal cone-beam computed tomography (CBCT) images.Methods: Standardized coronal images were obtained from 203 CBCT scans (83 with CB and 119 without CB) from the radiology archives of a dental teaching hospital. These scans underwent preprocessing through a hybridized contrast enhancement (CE) method using discrete wavelet transform (DWT). Of the 203 CBCT images, 162 were randomly assigned to the training set and 41 to the testing set. Initially, the images were enhanced using a CE technique before being input into pre-trained deep learning models, namely ResNet50, ResNet101, and MobileNet. The features extracted by each model were then flattened and input into a random forest (RF) classifier. In the subsequent phase, the CE technique was refined by incorporating DWT.Results: CE-DWT-ResNet101-RF demonstrated the highest performance, achieving an accuracy of 91.7% and an area under the curve (AUC) of 98%. In contrast, CE-MobileNet-RF recorded the lowest accuracy at 82.46% and an AUC of 92%. The highest precision, recall, and F1 score (all 92%) were observed for CE-DWT-ResNet101-RF.Conclusion: Deep learning models demonstrated high accuracy in detecting CB in CBCT images. However, to confirm these results, further studies involving larger sample sizes and various deep learning models are required.