bluuebunny/crossref_metadata_2025 huggingface dataset:
Climate change and reproductive health
Authors: Nazli Hossain
Published: November 2024

Climate change has become a global issue. World HealthOrganization (WHO) has estimated an increase of 250,000 deaths between 2030-2050, due to climate effect. ThoughPakistan does not contribute much to the cause of globalwarming, but suffers enormously due to climate change.The massive floods in 2022, in Sindh and Baluchistan provinces of the country caused tremendous destruction,and people are still unable to recover from these setbacks.The spectrum of climate change includes flood, drought,air pollution, wildfires, heat waves and increase in vectorbornediseases. All of this influence reproductive health. Iteffects both men and women. Pregnant women areincluded in the vulnerable group for these changes.Climate change has been identified as an important causeof maternal and perinatal mortality, as well as involves allaspects of obstetric outcomes. The resultingcomplications include preterm labour and delivery,decrease in gestational length, stillbirth, intrauterinedemise and a high rate of miscarriages. The effect ofclimate change on economy is also well established. With1°C rise in temperature, 12% decrease in global GDP isexpected.
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Water Quality Assessment and Prevalence of Waterborne Diseases within Chikun Local Government Area, Kaduna State-Nigeria
Authors: Ahmad Bello , Pyeng Kurmi Ann
Published: November 2024

Study’s Excerpt

Water quality and the prevalence of waterborne diseases in Chikun Local Government Area, Kaduna State, were assessed.
Microbiological analyses revealed microbial, helminth and protozoan contamination in water sources while Physicochemical analyses revealed heavy metal contamination.
There is a need for enhanced water treatment and community awareness for improving water safety and public health in the region.

Full Abstract
The health and well-being of individuals in a nation are intrinsically tied to the quality of water available for consumption.  Access to high-quality water plays a vital role in supporting proper nutrition, ensuring food security, and preventing waterborne diseases.  Therefore, this study was carried out to assess water quality and prevalence of waterborne diseases within Chikun Local Government Area, Kaduna State.  A cross-sectional study was conducted between January and June 2024.  Data were collected through the administration of questionnaires (400 respondents) and laboratory water analysis.  Water samples were analyzed from various sources involving boreholes, rivers and wells through composite sampling and physicochemical and microbiological analyses.  Results showed samples from Unguwan Maigero and Tricania possessed varying physicochemical properties, while water from Goningora and Nasarawa revealed high turbidity and heavy metal contamination.  Chloride levels were below 500 ppm, and sulphate concentrations ranged from 10.76 to 378.3 ppm.  Sodium levels ranged from 19.5 to 110 mg/l, and potassium levels exceeded the permissible limit in some samples.  Total coliform counts exceeded national limits (zero coliform per 100ml of water), indicating significant microbial contamination.  Parasitological analysis indicated helminths and protozoan contamination in non-borehole sources.  Findings showed 41% prevalence of waterborne diseases with diarrhea and typhoid.  The study indicates that community awareness, appropriate water treatment, surveillance, and monitoring are essentials for assuring the availability and utilisation of safe and high-quality drinking water in Chikun LGA, Kaduna State.
Bioethanol Production from Citrus limon (Citrus) Peel Substrate Using Aspergillus Niger and Saccharomyces Cerevisae
Authors: Baba, H. P.  , Bukar, A.  , Kawo, A. H.
Published: November 2024

Study’s Excerpt

An approach to optimizing bioethanol production from lemon peel waste is presented.
A combination of Aspergillus niger for enzymatic hydrolysis and Saccharomyces cerevisiae for fermentation were employed and specific physicochemical conditions—such as a pH of 3.5, temperature of 30°C, and 96-hour fermentation period—that maximize bioethanol yield and fermentation efficiency were highlighted.
Citrus limon peel has a potential of becoming sustainable bioethanol source that could contributes to renewable energy development.

Full Abstract
The consumption of petroleum products is marred by the inconveniences of environmental pollution and the emission of greenhouse gases, which are responsible for global warming.  Excessive use of fossil fuel has resulted in climate change, the elevation of the greenhouse gas effect, etc., contributing to the search for renewable sources of energy in harmony with the world’s energy needs.  Although bioconversion of lignocellulose residue has received much attention, most plant biomass has not been fully exploited to meet human energy needs.  Among these alternative energy carriers, ethanol receives great attention.   This study aims to determine the optimal conditions for the production of bioethanol from lemon peel using Aspergillus Niger and Saccharomyces cerevisae.  Aspergillus niger and Saccharomyces cerevisiae were isolated using the streak plate method and identified macroscopically and microscopically.  The cellulose hemicellulose and lignin contents of the substrates were determined, and after that, the substrates were pretreated with 5% sulfuric acid and then subjected to enzymatic hydrolysis using Aspergillus niger.  Subsequently, the reducing sugar content of the hydrolysate was determined, followed by fermentation using Saccharomyces cerevisae.  The percentage of bioethanol produced, as well as the fermentation efficiency (%), were calculated.  Analysis of Variance was employed to determine statistically significant differences among the determined parameters.    The cellulose, hemicellulose, and lignin contents of Citrus Limon were found to be 32.00%, 4.99%, and 9.80%.  Pretreatment increased the cellulose content from 23.00% to 32.00%.  The highest reducing sugar content, 6.63 g/L,, was recorded after hydrolysis for 96 hours.  Fermentation using Saccharomyces cerevisae yielded 19.20% of bioethanol from Citrus limon with a fermentation efficiency of 38.42%, respectively.  The Optimum fermentation conditions recorded were a time of 96hrs, pH of 3.5, temperature of 30oC and amount of substrate of 15g.    The combination of these parameters produced a bioethanol yield of (22.90%) and a fermentation efficiency of 44.44%, respectively.  This research revealed the potential of Citrus limon peel waste as a substrate for bioethanol production and optimized the physicochemical parameters for the fermentation.
Design of an Expert System for Student Learning Assessment
Authors: Abo-Hadi Sawsan Hasan , Abo-Hadi Anwar Hasan
Published: November 2024

An expert system has been designed to assess student learning in a manner that aligns with each student's ability level independently, based on modern measurement theory. This approach effectively measures students' actual knowledge levels and is essential for developing assessment tools, which are a cornerstone of education. The expert system records student’s data and interactions, determining the questions to be used to measure their cognitive level based on the obtained responses. Application results demonstrated the impact of the expert system for this type of measurement, providing ability estimates for students comparable to those from traditional tests.
Electronic Stamp Related to Implementation of Electronic Contracts Based on Indonesian Positive Law
Authors: Putri Sherly Ayuna , Cahyadini Amelia , Ramli Tasya Safiranita , Kristiyenda Yoan Shevila
Published: November 2024

Provisions regarding how to carry out stamp in electronic contract transactions often become problematic in themselves. In practice, an electronic contract will be stamped if it faces a special need that requires the contract to be an authentic deed. For example, this is for court requirements, as specified formal requirements and so on. Stamping is carried out by post-stamping, as in Law Number 13 of 1985 or by carrying out a non-digital contract process and affixing a stamp. A breakthrough was made with Law 10 of 2020 concerning Stamp Duty, repealing Law Number 13 of 1985 concerning Stamp Duty. In this provision, there are provisions regarding Electronic Stamps which have good prospects and can increase state revenue in the form of taxes. The research method used in this research is the normative legal method, namely legal research which focuses on a scientific research procedure to find the truth based on legal scientific logic from the normative side. This research discusses how the position of the stamp is related to the terms of the validity of the agreement and what the prospects are for electronic stamp which is starting to be regulated with Law Number 10 of 2020 concerning stamp duty.
DESENVOLVIMENTO DE UM GUIA SEMIOLÓGICO VISUOPERCEPTUAL EM OPTOMETRIA PEDIÁTRICA
Authors: Leal-Silva Leandro , Leandro Oliveira Alves José , Caramantin-Soriano Hilda
Published: November 2024

O estudo visa desenvolver um guia semiológico para a avaliação visual-perceptual em crianças na prática optométrica, buscando uma abordagem que permita diagnósticos mais precoces e intervenções assertivas. Utilizando uma revisão integrativa baseada em publicações dos últimos 10 anos, os resultados enfatizam a importância de identificar marcos do desenvolvimento visual e neurológico nos primeiros anos de vida. Assim, o guia proposto é apresentado como uma ferramenta para aprimorar o diagnóstico e tratamento em optometria pediátrica, promovendo a saúde visual e o desenvolvimento infantil.
КАФЕДРА СПЕЦИАЛЬНОГО ФОРТЕПИАНО: ПРОШЛОЕ, НАСТОЯЩЕЕ, БУДУЩЕЕ (К 80-ЛЕТИЮ КАЗАХСКОЙ НАЦИОНАЛЬНОЙ КОНСЕРВАТОРИИ ИМЕНИ КУРМАНГАЗЫ)
Authors: Сепп Майа , Олексенко Игорь
Published: November 2024

Статья посвящена истории становления кафедры специального фортепиано Казахской национальной консерватории имени Курмангазы, формирование которой происходило в одно время с развитием казахстанской фортепианной школы. В статье выявляются особенности формирования кафедры специального фортепиано Казахской национальной консерватории имени Курмангазы. Авторами предпринимается попытка осмысливания исторического процесса ее формирования. Одним из главных факторов формирования кафедры специального фортепиано рассматривается преемственность исполнительских и педагогических принципов. Авторы применяют исторический подход, с помощью которого прослеживаются истоки, повлиявшие на становление педагогического и исполнительского облика кафедры специального фортепиано, а также системный подход, позволяющий рассмотреть особенности формирования и развития кафедры специального фортепиано Казахской национальной консерватории имени Курмангазы. Особый интерес проявляется к вопросам развития кафедры специального фортепиано Казахской национальной консерватории имени Курмангазы с точки зрения казахстанского музыковедения, отмечается уникальность этого процесса. В ходе исследования были изучены ценные документы, хранящиеся в Архивах Казахской национальной консерватории имени Курмангазы и Новосибирской государственной консерватории им. М. Глинки. Результаты исследования могут быть полезны в процессе обучения как пианистов (исполнителей, исследователей, педагогов), так и музыковедов. Статья содержит таблицу и диаграмму, которые отражают результаты исследования.
Intonational Patterns of Kazakh Culture: From Anthropopractices to Psychotherapy techniques
Authors: Baikuatova Akmaral , Baykuatuly Kurmanbek
Published: November 2024

This study explores the role of intonation in the transformational anthropopractices of Kazakh culture and its psychotherapeutic aspects. Kazakh folklore and ritual practices are rich in musical elements, with intonation playing a central role. Intonation not only serves as a means of conveying cultural and spiritual values, but also acts as a powerful mechanism for psychological regulation and emotional expression.
The aim of this research is to uncover the mechanisms of intonation's impact on the human psyche and its role in maintaining mental equilibrium and inner harmony. Special attention is given to the study of ritual practices where intonation is used to achieve therapeutic effects, such as in “Syngsu”, “Besyk zhyry” and other ritual forms. A comprehensive methodological approach is employed, integrating elements of cultural anthropology, musicology, psychology, and philosophy.
The study identifies key intonational patterns that contribute to psychotherapeutic effects. It is found that certain musical intonations can evoke deep emotional experiences, promoting self-awareness and emotional release. For instance, in rites associated with transitional life stages (birth, marriage, death), intonation helps participants cope with emotional stress and experience these moments more consciously. Intonation is also considered as a means of collective experience and social cohesion. Musical rituals foster a sense of community and mutual understanding, which is particularly significant in the context of traditional Kazakh society. These practices help maintain social structure and cultural identity.
The article highlights the importance of preserving and popularizing the traditional musical practices of Kazakh culture. In contemporary conditions, where mental health is becoming an increasingly pertinent issue, the revival and integration of these practices with modern techniques of music therapy, can serve as an effective means of psychotherapy and spiritual development.
INSTITUTIONAL ART CRITICISM IN 20TH- AND 21ST-CENTURY IN KAZAKHSTAN
Authors: Kobzhanova Svetlana , Kumarbayeva Akzharkyn
Published: November 2024

The independence of Kazakhstan and its state sovereignty became important reforming factors in the new social fabric and worldview of the nation, its culture and art, the main component of which is the replacement of former political ideals and the mythologization of its own past.  In Kazakhstan, official and unofficial art lives side by side and is displayed in various exhibition venues, which avoids a mindset of opposition and allows for art historians and curators to create divisions by preference.
In Kazakhstan, there is a long-overdue need for serious comprehension of, and fixation on, artistic initiatives.  Here, we are not regarding ‘fixation’ as the photography and videography of events; we need something different – analysis of the work of individual researchers, painting a picture of the direction of research and the development of the creative side of art criticism institutions in Kazakhstan.
This article is an attempt to understand the realities of 21st-century Kazakhstani fine art.  It is important to determine the most important institutions and bring the achievements of art criticism in Kazakhstan to the global community, based on the work of individual researchers.  Aiming to grasp and examine the main directions and goals of contemporary art critics, we have discovered the individual directions and themes of leading researchers, which serves as a basis for the revealing the characteristic traits of art criticism in Kazakhstan through the prism of individual knowledge and passions.
An ESG-Compliant Framework for Fraud Detection in Online Payments Using Data Privacy and Machine Learning
Authors: Ahuja Ashutosh
Published: November 2024

Purpose: The purpose of this paper is to analyze the role of machine learning (ML) in fraudulent online payment transaction detection across industries, with a specific focus on integrating Environmental, Social, and Governance (ESG) principles to bring sustainability and ethics in fraud detection.
Methodology: This study reviews the effectiveness of machine learning (ML) techniques in real-time fraud detection, presenting the efficiency of different ML techniques across industries and how those techniques can be modified to apply the principles of ESG. It checks on ethical practices concerning data, compliance with data privacy, and sustainable management, further investigating how effectively ML-driven frameworks can support fraud detection without compromising the standards of ESG.
Findings: The study finds that integrating ESG principles within machine learning frameworks for fraud detection enhances both the effectiveness and ethical alignment of these systems. ML models not only support real-time fraud detection but also reinforce sustainable data management and governance practices, providing businesses with an advanced approach to mitigating cyber risks while upholding ESG commitments.
Unique Contribution to Theory, Practice, and Policy: This paper contributes by advancing ESG-integrated frameworks for fraud detection, offering a sustainable and ethical model for using ML in financial systems. In practice, it provides actionable insights for industries seeking to align fraud prevention with ESG goals. The paper also suggests policy considerations, advocating for stronger ethical standards and data governance in ML applications for fraud detection.
Managing Information Overload in a Pandemic: Influence of Social Media on Vaccine Attitudes in the Digital Age
Authors: Adekunle Yusuf , Ogwezzy-Ndisika Abigail O. , Ibraheem Ismail A.
Published: November 2024

Purpose: This study examined how social media influences public health decisions, focusing on how information overload during a pandemic impacts vaccine hesitancy and acceptance across demographics. It analyzed conflicting vaccine information to understand social media's role in shaping attitudes and identify strategies to mitigate its negative effects.
Methodology: This study employed a multi-stage sampling method to gather data from diverse age groups, education levels, and occupations. This approach combines various techniques at different stages, making it suitable for large, geographically dispersed populations. By segmenting the population into manageable units, multi-stage sampling improves the accuracy, reliability, and representativeness of the data collected.
Findings: The findings reveal that most respondents consider vaccine information on social media unreliable, underscoring the need for greater trust in online discussions. Many feel overwhelmed by conflicting messages, highlighting the necessity for clearer communication. Social media significantly shapes attitudes toward COVID-19 vaccines, with many shifting views after engaging with online content. Additionally, participants report mental health impacts from the constant stream of vaccine information, illustrating information overload.
Unique Contributions to Theory, Policy and Practice: This study advances the information overload model by illustrating how excessive and conflicting vaccine information on social media disrupts comprehension and harms mental health. It emphasizes social media's role in shaping health attitudes and advocates for interdisciplinary approaches that incorporate psychological resilience into public health strategies. Findings highlight the need for regulations against misinformation to improve the credibility of online health information and promote trusted sources, particularly verified health organizations. The study also calls for health literacy initiatives to empower the public in navigating misinformation and suggests strategies for managing information overload through social media disengagement. Targeted initiatives that leverage trusted information sources can effectively combat vaccine hesitancy and boost community engagement in public health campaigns, ultimately improving health outcomes.
Analysis of Factor Affecting Employee Satisfaction in Modern Corporate Sector for Employee Retention
Authors: Pallavi. K  , Mrs Archana JR
Published: November 2024

Data Type: Primary data collected via structured questionnaire.
Survey Factors: Work environment, compensation, career growth, leadership, recognition, and work-life balance.
Methodology: Descriptive research with a sample size of 100 respondents.
Objective: To identify key factors that influence employee satisfaction and its impact on retention in the modern corporate sector.
Data Collection Tool: Google Forms administered survey.
Focus: Investigating how satisfaction drivers affect employee retention strategies in modern organizations
A Comprehensive Review on Accident Detection Using Artificial Intelligence and Machine Learning
Authors: Shrutika Nandanwar  , Shruti Patil  , Swami Patil  , Pranav Zadge
Published: November 2024

This paper reviews the role of Artificial Intelligence (AI) and Machine Learning (ML) in accident detection systems, focusing on the application of image processing techniques and Convolutional Neural Networks (CNNs) to enable detection. Through a comprehensive analysis of recent methodologies, challenges, limitations, and future research directions, this paper aims to provide a detailed understanding of how AI and ML are advancing the field of accident detection
EvPowerStop - Electric Vehicle Station Finder and Slot Scheduler
Authors: Jadhav Prashant  , Bhujbal Pranav  , Kapkar Arpit  , Gayke Krushna  , Prof. Mrs. S. S. Patil
Published: November 2024

With the increasing adoption of electric vehicles (EVs) worldwide, a significant challenge has emerged for EV drivers: locating compatible charging stations in real-time and securing slots for efficient use. The transition to electric mobility has created a demand for seamless infrastructure that supports the dynamic needs of EV drivers. Currently, the lack of centralized information on charging station availability and compatibility with specific vehicles leads to inconveniences and delays, reducing the overall efficiency of electric vehicle usage. This project addresses this gap by developing an EV station finder and slot scheduling application—EV Power Stop—designed to simplify the charging process and ensure that EV drivers can plan their trips with confidence.
The broader context of this work lies in the realm of smart cities and sustainable transportation. As nations push toward carbon-neutral goals, the role of electric vehicles becomes crucial in reducing emissions and lowering dependency on fossil fuels. For this shift to be effective, smart solutions that integrate transportation with infrastructure are vital. This project aligns with the goals of smart urban mobility by offering a system that leverages real-time data to provide EV drivers with the most up-to-date information on charging station availability.
The proposed system uses Flutter as a cross-platform framework for the frontend and Firebase as the backend for managing user data, station information, and slot booking in real-time. APIs like Google Maps are integrated to offer navigational support, ensuring users can easily find and access nearby stations. Key features include user authentication, slot booking, real-time updates on availability, and route guidance. The system is designed with scalability, performance, and security in mind, ensuring that it can handle a growing user base while maintaining quick response times.
Initial testing shows that the app responds within 2 seconds for most user interactions, meets usability standards, and securely manages personal data. Future developments will focus on integrating additional functionalities like iOS support, predictive scheduling, and automated slot management to improve efficiency further. This project demonstrates the potential for integrating real-time systems with urban mobility to enhance the electric vehicle user experience and support broader sustainability goals..
Traffic Sign Detection under Foggy Conditions using Machine Learning
Authors: Sneha Chauhan  , Pradnya Ghule  , Abhijeet Deshmukh  , Onkar Bhagwat
Published: November 2024

Traffic sign detection is crucial for enhancing road safety, especially under adverse weather conditions like fog. This paper explores the challenges of detecting traffic signs in fog and presents an approach that incorporates dehazing techniques to improve detection accuracy. We implement a combination of YOLO (You Only Look Once) and HOG (Histogram of Oriented Gradients) algorithms, evaluating their performance on various datasets. Our findings indicate a significant improvement in detection rates under foggy conditions, suggesting that integrating dehazing techniques can enhance visibility and road safety.
AI-Powered Video and Image Processing for Video Meetings
Authors: Abhishek Mohite  , Gaurang Arora  , Nishant Khanderao  , Ayush Rathod  , Prof. Deepa H Kulkarni
Published: November 2024

The increasing dependence, on meetings has led to a need for advanced technologies that improve communication and teamwork dynamics swiftly evolving video and image processing technologies backed by AI are reshaping the realm of video conferencing by enabling instant enhancements and enhancing interaction quality and usability This research paper delves into how artificial intelligence is being incorporated into video meetings with a focus on practical uses, like real time background blurring and replacement automatic noise reduction facial expression recognition and participant monitoringIn addition, to that we will explore how AI can enhance video quality, compress images and optimize bandwidth. This showcases its ability to decrease delays and enhance video clarity in areas with bandwidth. We will delve into progress in AI algorithms like using learning for recognizing faces utilizing natural language processing, for instant transcription and detecting emotions.
Hybrid Recommendation System for e-Pharmacy
Authors: Aniket Karanje  , Anurag Babar  , Jay Pawar  , Pratik Kshirsagar  , Prof. Mayuri Agrawal
Published: November 2024

In the ever-evolving field of recommendation systems, the importance of providing users with precise and personalized suggestions cannot be understated. This paper delves into the realm of medicine recommendation and explores the use of hybrid recommendation algorithms, combining content-based and collaborative filtering techniques. The study prioritizes content-based recommendation using cosine similarity and Singular Value Decomposition (SVD) while emphasizing their effectiveness in recommending medicines with similar formulae. The proposed hybrid approach leverages a rich dataset from Kaggle and integrates user-friendly features, linking to popular online pharmaceutical platforms. By analyzing the architecture and design, this paper demonstrates the superiority of hybrid filtering in the context of medicine recommendation
Deep Learning Approach for Suspicious Activity Detection from Surveillance Video
Authors: Parth Pradeep Rananaware  , Jayesh Vijay Dhumal  , Anushka Sudhakar Harle  , Prof. D. B. Mane
Published: November 2024

The present generation seeks ways to live their lives free of fear. This often prompts the need for enhanced law enforcement and security systems. Suspicion activity recognition in surveillance footage has become an essential component in modern security systems, focused around the problem of recognizing inappropriate behaviors without too much human time. The advent of deep learning has made an impact in computer vision tasks within such a way the real-time detection by the evaluation of large amounts of video footage becomes realistic. In this context the paper presents a model in which deep learning, particularly Convolutional Neural Networks (CNNs), are utilized for the behavioral pattern recognition from security footage. In addition, it also improves the efficacy of detection and reduces the shortcomings associated with these systems where only the post-event analysis is performed manually or automatically. In this paper, we demonstrate a novel IP model that analyzes live video and performs normal-suspicious–threat triage in real-time. Results indicate the validity of the method in different environmental and illumination conditions. An important objective that this system is designed for is to change the way security is practiced and delivered in today’s intelligent systems providing actionable intelligence and the ability to prevent threats rather than just respond to them making this a high growth opportunity for marketing high-risk and sensitive areas.
Enhanced Security Framework for Multi-Layered Wireless Communication Systems
Authors: Vaishnavi Aradhye  , Aditi Hinge  , Pratham Ingle  , Vedang Khutale  , Prof. Waghole
Published: November 2024

The goal is to predict a Windows machine’s probability of getting infected by various families of malware, based on different properties of that machine. The telemetry data containing these properties and the machine infections was generated by combining heartbeat and threat reports collected by Microsoft’s endpoint protection solution, Windows Defender. Each row in this dataset corresponds to a ma- chine, uniquely identified by a Machine Identifier. Has Detections is the ground truth and indicates that Malware was detected on the machine. Using the information and labels in train.csv, you must predict the value for Has Detections for each machine in test.csv. The sampling methodology used to create this dataset was designed to meet certain business constraints, both in regards to user privacy as well as the time period during which the machine was running. Malware detection is inherently a time-series problem, but it is made complicated by the introduction of new machines, machines that come online and offline, machines that receive patches, machines that receive new operating systems, etc. While the dataset provided here has been roughly split by time, the complications and sampling requirements mentioned above may mean you may see imperfect agreement between your cross validation, public, and private scores! Additionally, this dataset is not representative of Microsoft customers machines in the wild it has been sampled to include a much larger proportion of malware machines
Prognostic Factors for Survival in Patients with Metastatic Colon Carcinoma
Authors: YILMAZ Feride
Published: November 2024

Colorectal cancers are the most common cancers of the gastrointestinal system. They rank third after prostate and lung cancer in men and after breast and lung cancer in women. In Turkiye, colon cancer is the third most common among all cancers. In such cancer, beyond the stage of the disease, there are many biological, molecular, genetic, and tissue-related factors that determine the prognosis. Among these, vascular invasion, the number of affected regional lymph nodes, and the levels of preoperative carcinoembryonic antigen (CEA) are prominent factors. In this study, we investigated the personal, clinical, tumoral, metastatic, and treatment characteristics of metastatic colon cancer (MCC) that may be associated with long survival. This study included the data of 103 patients diagnosed with MCC who were followed at the Medical Oncology Department of Karadeniz Technical University Faculty of Medicine between 2010 and 2016. In univariate analyses, primary surgery (p< 0.001), targeted therapy (p= 0.01), being less than 65 years old (p=0.02), having normal CEA levels (p= 0.03), and not having elevated platelet counts (p= 0.001) were significant factors associated with prolonged survival. Multivariate analysis indicated that survival was longer in patients who underwent primary surgery (p= 0.001, 95% CI: 0.07–0.52) and had normal or low platelet levels at the time of diagnosis (p= 0.001, 95% CI: 1.77–9.16), regardless of other factors. In patients diagnosed with MCC, those who had primary tumor surgery and had normal or low platelet levels at the time of diagnosis had a better prognosis regardless of other factors. Therefore, prognostic factors are important in MCC, and more comprehensive studies are needed on this subject. Keywords: Metastatic colorectal cancer, Survival, Prognostic factors
Predictive Roles of Ki 67 level & mPEPI Score for Neoadjuvant ‘Chemotherapy’ Efficacy in Locally Advanced ER(+)/HER2(-) Breast Cancer
Authors: DOGAN Mutlu
Published: November 2024

Neoadjuvant chemotherapy (NAC) & modified preoperative endocrine prognostic index (mPEPI) score after NAC role is unclear in locally advanced ER+/HER2(-) breast cancer (LA-HnLBC). We aimed to evaluate prognostic & predictive factors including mPEPI score for NAC in LA-HnLBC, retrospectively. 142 LA-HnLBC patients were classified as pCR( n:26) & non-pCR (n: 116) & categorized for PR/ki67/ki67 decline/mPEPI score patients were included. Median age was 53 years. pCR rate was 18.3%. Median ER/PR/ki67 were as 90% / 40% / 40%. Median basal & postoperative ki67 level was 40. pCR group had more T2(73%), grade 3 (69%) & non-pCR had more T3(21%), grade 2(46%) tumors (p= 0.03,p= 0.03). pCR group had lower mPEPI score (3.5 vs 5,p= 0.05). 5y-DFS was 69% (pCR 93.8%,non-pCR 63.4%, p= 0.012). 5y-OS was 77% (pCR 100%,non-pCR 72%, p= 0.018). In univariate analysis, high basal/ postoperative ki67 levels, ki67 decline & mPEPI score were significant poor prognostic factors for DFS (p= 0.01, p< 0.001, p= 0.017, p< 0.001) & OS (p= 0.006, p= 0.003, p= 0.05, p= 0.001) in non-pCR goup. Prognostic cut-offs were as 40 for basal ki67 (DFS & OS), 20 for postoperative ki67 (DFS), 4 for mPEPI (DFS) & 30 for ki67 decline (OS). Favorable prognostic factors were defined as lower basal ki67 level (< 40%) & higher ki67 decline (ki67 <30%) for OS; lower basal ki67 (<40%), po ki 67 (< 20%) & mPEPI score (< 4) for DFS after NAC in LA HnLBC. Different prognostic cut-offs for basal & postoperative ki 67 is striking. mPEPI score may also have prognostic significance after NAC in LA-HnLBC patients. Keywords: ER+/HER2- breast cancer, Locally advanced breast cancer, Luminal-like breast cancer, mPEPI score, Neoadjuvant treatment
Qatar's Foreign Policy
Authors: Kabalan Marwan
Published: November 2024

This study offers an analysis of Qatar’s foreign policy since its independence from Britain in 1971.

Locked between two vying powers, Iran and Saudi Arabia, and lacking the traditional elements of influence in the regional and international state system such as land, human capital, and advanced industry, Qatar nevertheless wields a disproportionately large amount of regional influence with an assertive foreign policy approach. Here, Marwan Kabalan highlights the strategies pursued by the ruling Qatari elite, especially during the last two decades, and delves into the methods Qatar has used to deal with the structural challenges to its foreign policy.

These strategies include financially leveraging its access to crucial resources, such as natural gas, and its manipulation of existing regional frictions. The book also addresses Qatar’s soft power influence – positioning itself as an alternative cultural and intellectual hub in the Arab world, enabling it to take a leading role, particularly as a mediator, in the region. By highlighting Qatar’s foreign policy strategies and outcomes, Kabalan illustrates how the Qatari case challenges key assumptions of international relations theory which assumes that wealthy small powers tend to pursue passive foreign policies, and that structural forces minimize the role of ruling elites in foreign policymaking.
Icon, Libertine, Leader
Authors: White Mark
Published: November 2024

This new biography of JFK offers a comprehensive analysis of the man, the leader, and the cultural icon. Mark White, the leading authority in Britain on JFK, draws on more than 30 years of research to provide a nuanced portrait of one of the most iconic figures in American and world history.John F. Kennedy was a president like no other, with a movie star’s public image and an extraordinary private life. He was no less remarkable politically, with his achievements including the resolution of the 1961 Berlin crisis and the Cuban missile crisis, the Nuclear Test Ban Treaty, and a strong commitment to civil rights.

This book provides what no previous biography has: an in-depth analysis of not only JFK’s political life, particularly his record as a policymaker in the White House, but also his private life, his role as a cultural icon, and what might have happened to a Kennedy presidency had he not been assassinated.

This sophisticated, multi-dimensional biography sheds new light on JFK's life and legacy, and makes a compelling case for why he was the finest president of his generation.
Thinking Nonviolence
Authors: Jahanbegloo Ramin
Published: November 2024

This book presents a solid introduction to nonviolence as a mode of thinking and a mode of life, but also as a strategy of self-defence and social and political transformation."Nonviolence" is a frequently misunderstood, frequently abused term. It can be used in very narrow or broad constructs and can be based on a wide variety of philosophies and practices. The book will examine several of the main currents of nonviolent thought and practice, as approaches that concentrate around the concepts of “struggle” and “resistance”. By focusing on these two concepts, the book will examine the theories and principles of nonviolence as well as the religious and philosophical underpinnings of their commitments. The book dwells on the theoretical discussion of the concept and history of nonviolence as a revolutionary concept for a change in mentalities and realities of our societies. It brings to the forefront the philosophy of nonviolence as it developed from Socrates to Thoreau, Jesus to Dalai Lama. The book covers Gandhi, Mandela, Martin Luther King, Jr. the advocates and practitioners of non-violence in the 20th Century.
Kemanusiaan dan Kearifan Sejarah dalam Pemikiran Pramoedya Ananta Toer
Authors: Pamungkas Ernanto Bayu , Susilo Joko , Mandarani Vidya
Published: November 2024

Bermula dari dikotomi keilmiahan antara sastra dan sejarah, mana yang lebih ilmiah dan hanya sekedar seni, mendorong peneliti untuk mengaitkan keduanya guna membedah karya sastra. Sastra yang bersifat kemanusiaan dan memiliki dimensi personal dan sosial, serta sejarah yang mampu menguatkan muatan sosial dan humanistik sebuah karya menunjukkan bahwa adanya pengaruh keyakinan-keyakinan sejarawan yang ia curahkan untuk memperindah cerita atau menegaskan suatu opini. Pada penelitian kualitatif ini, peneliti akan menyelidiki pemikiran Pramoedya Ananta Toer dan novel-novel sejarahnya melalui kajian historiografi. Dengan demikian, subyektivitas sejarawan akan terlihat dari penulisannya. Objek yang digunakan pada penelitian ini yaitu Tetralogi Buru, yang sarat pesan-pesan kemanusiaan, pengetahuan sejarah dan estetika sastra. Dari hasil pengkajian, peneliti menemukan persoalan kemanusiaan menjadi dasar pemikiran Pram, serta penggambaran gerakan perlawanan mau pun perjuangan yang digambarkan Pram dalam karyanya menguatkan kaitan antara sastra dan sejarah. Dapat ditarik kesimpulan bahwa eksistensi keilmiahan antara sastra dan sejarah bukanlah suatu dikotomi, dan bahkan karya sastra dan pengetahuan sejarah dapat berjalan beriringan dalam membentuk kehidupan kemanusiaan masyarakat yang lebih baik. Karya sastra Pram yang subjektif dan imajinatif justru dapat digunakan sebagai fasilitas pembelajaran sejarah dengan lebih manusiawi.
Strategi Financial Technology dalam Mengatasi Lonjakan Transaksi Lender pada Masa Pandemi Covid 19
Authors: Simatupang Apriani , Siska Elmira
Published: November 2024

Pandemi Covid 19 berdampak pada seluruh kegiatan usaha. Dampak tersebut dirasakan juga pada berbagai lembaga keuangan. Lembaga keuangan semakin melaksanakan kegiatannya dengan basis technology. Lembaga keuangan yang berbasis technology tersebut dinamakan dengan FinTech. Salah satu produk Fintech adalah Peer-to-peer Lending (P2PL). Keberadaan produk P2PL ini sangat membantu dalam memperkuat keuangan inklusif bagi pelaku UMKM (Usaha Mikro Kecil dan Menengah). Adanya P2PL dapat meningkatkan pembiayaan UMKM dan akhirnya akan meningkatkan kinerja usaha UMKM. Adanya pandemic Covid 19 menyebabkan transaksi P2PL mengalami peningkatan. Transaksi Lender meningkat setiap bulannya semenjak pandemic tersebut. Oleh karena itu paper ini bertujuan untuk memaparkan langkah-langkah yang harus dilakukan Fintech dalam mengatasi lonjakan transaksi lender tersebut agar Fintech dapat bertahan, sementara pada periode yang sama produktivitas usaha mengalami penurunan. Desain penelitian yang digunakan dalam analisis ini adalah studi pustaka yaitu dengan mengumpulkan data dokumentasi dari berbagai tulisan. Hasil penelitian dan pembahasan paper ini yakni menunjukkan terdapat tiga hal yang harus dilakukan dalam mengatasi lonjakan transaksi lender agar tidak terjadi kredit macet yakni Pengaturan dan Penerapan Mitigasi Risiko dalam Penyelenggaraan Peer-to-peer Lending, Kewajiban terhadap Penyampaian Laporan SLIK OJK, dan Penerapan Prinsip Kehati-hatian.
Pengembangan Pengelolaan Pariwisata oleh Badan Usaha Milik Desa di Jambi
Authors: Saadah Maratun , Sampoerno M. Norma , Triansyah Zuhri , Chaniago Fransisko
Published: November 2024

Badan Usaha Milik Desa (BUMDes) merupakan instrumen penting dalam mewujudkan otonomi desa yang bermartabat. Keberadaan BUMDes diharapkan bisa menjadi salah satu penopang utama peningkatan pendapatan desa sehingga mampu menyediakan pelayanan publik yang lebih berkualitas. Pengelolaan potensi wisata lokal menjadi salah satu alternatif usaha potensial yang bisa dilakukan oleh BUMDes. Keterlibatan BUMDes dalam pengelolaan pariwisata tidak hanya bertujuan ekonomis, namun sekaligus diharapkan mampu melestarikan dan mengembangkan nilai-nilai kearifan lokal dalam kepariwisataan. Artikel ini menganalisis pola pengembangan pariwisata berkarakter lokal oleh BUMDes di tiga desa yakni Mumpun Baru, Tanjung Lanjut, dan Pendung Talang Genting di Provinsi Jambi. Artikel ditulis berdasarkan hasil penelitian yang dilakukan secara kualitatif di daerah Muaro Jambi, Kerinci dan Merangin dengan metode purposive sampling. Hasil analisis menunjukkan bahwa terdapat beberapa hal yang menjadi ciri dalam pengembangan pariwisata melalui BUMDes yaitu; produk pariwisata, inovasi atau kebaruan dalam pengembangan produk pariwisata, terpeliharanya nilai-nilai kearifan lokal, aspek kelembagaan BUMDes, kontribusi pariwisata terhadap perekonomian masyarakat. Selain itu, pengelolaan pariwisata dengan BUMDes menjadi kunci dalam mendukung tercapainya pariwisata berkelanjutan yang merupakan agenda global negara di seluruh dunia.
A Method to Mitigate Refractive Index Mismatch Artefacts for Scanning Laser Optical Tomography
Authors: Hill Ole
Published: November 2024

SLOT is a volumetric, multi-modal imaging technique. Point-wise illumination with a weakly focused laser beam results in projection images that are reconstructed into tomographic images. The sample is embedded in a refractive index (RI) matched medium, which prevents light refraction at the sample boundary, which would lead to image artifacts. Silicone oil is used as the immersion medium for SLOT. It is toxic, difficult to remove from samples and can interact with the sample in undesirable ways. Using water as an immersion medium would solve these problems. Unfortunately, the refraction between water and the sample leads to artifacts that drastically degrade the quality of the results. This work aims to eliminate the artifacts through a clever post processing of the sinogram by predicting the refraction of each laser beam. The SLOT simulator was programmed for this purpose. It allows the simulation of SLOT measurements with any RI's and the correction of SLOT measurements with an RI mismatch. Simulated and real SLOT measurements are presented and their similarity is evaluated.
Prozessentwicklung zur tribologischen Funktionalisierung von Nutzfahrzeug-Zylinderlaufbuchsen
Authors: Schmidt Christopher
Published: November 2024

Das Einsatzverhalten von tribologisch belasteten Maschinenkomponenten kann durch die gezielte Anpassung ihrer Topographie und Geometrie verbessert werden. In der vorliegenden Arbeit wird dies umgesetzt, indem erstmals durch die neuartige Kombination zweier spanende Fertigungsverfahren tribologisch maßgeschneiderte Schwerlast-Zylinderlaufbuchsen hergestellt werden. Die spanende Bearbeitung der Zylinderlaufbuchsen erfolgt durch Mikrostrukturieren sowie die Kombination mit piezoaktorischem Unrunddrehen. Bei beiden Prozessen werden die Wechsel-wirkungen zu vor- und nachgelagerten Prozessen erforscht, um zum Nachweis der Industrialisierbarkeit eine Demonstratorprozesskette aufzustellen. Abschließend wird der Energiebedarf der spanenden Endbearbeitung tribologisch maßgeschneiderter Zylinderlaufbuchsen untersucht, um die Ressourceneffizienz der neu aufgestellten Prozesskette zu bewerten. Zudem erfolgt eine Validierung der erreichten Reibungs-minderung durch umfassende gefeuerte Motoruntersuchungen an Nutzfahrzeug-zylinderlaufbuchsen verschiedener Baugrößen. Die Kolbengruppenreibung wird um maximal 26 % reduziert, was den Kraftstoffverbrauch um 1 % senkt. Der Energiebedarf der Endbearbeitung wird um 34 % gesenkt.
https://aircconline.com/csit/papers/vol14/csit141901.pdf
Authors: Yu Claire , Wu Joshua
Published: November 2024

Students feel overwhelmed in the college process, whether it be due to the inability to find college tours or feeling lost on what they want to pursue in education and where to pursue it. Through our application, CollegeMatcher, we aim to resolve such feelings of aimlessness by providing accessible resources of information and conveying the campus experience for a multitude of universities in America, as well as guiding the student to a higher education home based on their interests and capabilities. We utilize web scraping and API connections (including Google Maps and OpenAI) to retrieve data for each university, including its buildings and images. The application page that provides personalized recommendations of universities integrates with an OpenAI trained chatbot (through its API) in addition to user-inputted data. This application will help students find the university and path of education that best suits them, allowing for the future discovery of passions and pursuits.
Smart Kitchen Management: Enhancing Food Inventory Control and Waste Reduction Through AI-Owered Image Processing and Data Integration
Authors: Lu Xiangning , Sun Yu
Published: November 2024

This paper presents the design and evaluation of a mobile application aimed at optimizing food inventory management and reducing food waste [1][4]. The application integrates several key features, including a food classification engine powered by the Gemini Image Processing Engine, a waste index calculation, and personalized recipe suggestions [2]. Experiments were conducted to assess the accuracy of the image processing engine under various conditions and the reliability of the waste index calculation based on user input data. The results showed that while the application performs well under optimal conditions, its accuracy and effectiveness can be affected by poor image quality and incomplete data. The paper discusses these findings and proposes improvements to address the identified limitations. Ultimately, the application provides a comprehensive and user-friendly tool for managing food resources, with the potential to significantly reduce waste and promote sustainability in households [3].
Quantifying Credit Risk in Lending Industry: A Monte Carlo Simulation Approach
Authors: M. Durojaiye Olalekan , K. Sahi Ramanjit
Published: November 2024

The loan data simulated with Monte Carlo approach and analyzed in the research work provides valuableinsights into the borrowers’ financial positions and loan performance. Debt-To-Income ratio (DTI) was calculated and we identified 141 (57.8%) loans that were at high risk of default. We then adopted a risk-based pricing (RBP) to mitigate the risk of default by assigning higher interest rates to riskier loans by taking into consideration some parameters like credit score and risk premium. The analysis revealed that a higher DTI is associated with a higher risk of default, and a higher RBP is associated with a higher interest rate. Therefore, it is essential to use these metrics when assessing loan applications to ensure a healthy loan portfolio. This research can be used to inform loan officers, risk analysts, and other stakeholders involved in the lending process.