bluuebunny/crossref_metadata_2025 huggingface dataset:
Tindak Tutur Direktif dalam Film “Air Mata di ujung Sajadah” Karya Titien Wattimena
Authors: Syaroh May , Siregar Anggun Luthvita , Manik Carol Shelila , Siregar Debora , Butar-butar Gracia Patunia , Tarigan Laura Debrina , Sinaga Agustini Br. Sinaga , Adha Wirdatul , Puteri Anggia
Published: February 2025

Penelitian ini bertujuan untuk mengetahui tindak tutur direktif yang dituturkan antar tokoh dalam film “Air Mata di Ujung Sajadah” karya Titen Wattimena dan disutradarai oleh Key Mangunsong. Tindak tutur direktif selalu muncul dalam konteks situasi tutur, salah satunya dalam dunia film. Penelitian ini merupakan penelitian kualitatif dengan metode deskriptif. Teknik yang digunakan dalam pengumpulan data adalah teknik simak dan teknik katat untuk memperoleh data penggunaan tindak tutur direktif dalam film dan mencatat data-data yang ditemukan. Berdasarkan temuan, tindak tutur direktif dalam film “Air Mata di Ujung Sajadah” karya Titen Wattimena, ditemukan 19 contoh tindak tutur direktif memerintah, 3 merekomendasikan, 7 menyarankan, 2 mendesak, 2 memaksa, 8 memohon, 6 menasehati, 1 memberi aba-aba , dan 4 contoh arahan memesan.
Analyzing Slang in Social Media
Authors: Ita Rosvita  , Tumbel Maria Celine , Sabata Yusniati N. , Arrasul Abdul Rabbi
Published: February 2025

The purpose of this research was to determine the types of slang and slang that were most used by UMLB students of English education, Eight semesters in social media. This is descriptive qualitative research. This research was conducted by non-participatory observation which is observing social media Facebook and WhatsApp. This research is also done with the documentation of screenshots. Participants of slang users in this research were twenty seven eighth-semester students of English Education Program at UMLB. The result of this research show that there were six types of slang used by the students, those were fresh and creative, flippant, imitative, acronym, clipping, and abbreviation. The number of slang found by the researcher is 74 slangs. 18 slangs for fresh and creative, 11 slangs for flippant, 6 slangs for imitative, 5 slangs for acronym, 13 slangs for clipping, and 21 slangs for abbreviation. Therefore based on the data, abbreviation is the most used slang or often used by UMLB students of English education, eight semesters in social media
The Relevance of The Gothic Concept in The Poem When We Two Parted By George Gordon Byron
Authors: Aryana Nurul Qarimah
Published: February 2025

This study examines the relevance of the Gothic concept in Lord Byron’s poem When We Two Parted. As a Romantic work, the poem emphasizes the primacy of emotion and individual expression, hallmarks of the Romantic era's reaction against neoclassical rationality. The Gothic undertones emerge through the pervasive atmosphere of gloom, sorrow, and haunting recollections, aligning with the genre's thematic focus on trauma and persistent suffering. By situating the poem within the context of Byron's tumultuous personal life and societal transgressions, the study reveals how the poet's intimate experiences of clandestine love and scandal inform the narrative's emotional gravity. Byron's poem reflects these Gothic elements by portraying heartbreak, loss, and the metaphorical "death of love." The analysis highlights how Byron's personal experiences, particularly his controversial relationships, inform the poem's themes of sorrow. Through vivid imagery and emotional depth, When We Two Parted illustrates how Romantic and Gothic elements intertwine, offering a profound exploration of love and loss.
Repetisi sebagai Sarana Pembangun Kepaduan dalam Teks Motivasi di Instagram
Authors: Setyawati Nanik
Published: February 2025

Kehadiran teks motivasi dapat memberi manfaat kepada khalayak luas. Teks motivasi yang padu dapat dibangun melalui sarana repetisi. Tujuan penelitian ini untuk mendeskripsikan wujud repetisi sebagai sarana pembangun kepaduan dalam teks motivasi di Instagram. Penelitian kualitatif ini melakukan pengumpulan data dengan menyimak pemakaian repetisi di Instagram, menyadap, dan dilanjutkan dengan mencatat. Metode agih dan metode padan digunakan untuk menganalisis data. Data yang telah dianalisis disajikan oleh peneliti dengan metode informal. Peneliti berhasil menemukan beberapa jenis repetisi dalam teks motivasi di Instagram, yaitu repetisi tautotes dan repetisi anafora masing-masing berjumlah 6 data, repetisi epizeuksis dan repetisi epistrofa masing-masing dengan 4 data, repetisi mesodiplosis terdapat 2 data; dan repetisi simploke hanya 1 data; sedangkan repetisi epanalepsis dan repetisi anadiplosis tidak ditemukan. Implikasi dari penelitian ini ditujukan kepada para pegiat bahasa agar dapat memanfaatkan repetisi yang tepat guna menjaga kekohesifan dan keestetisan karyanya.
Kata Kunci: repetisi, sarana pembangun kepaduan, teks motivasi, instagram
Students’ Perception on The English Teachers’ Pedagogic Competence at British English School
Authors: Syamsuddin Syamsuddin , Genisa Risma , Ruing Fentry Hernaningsih
Published: February 2025

This study was aiming to analyze the perception of the students on their English teachers’ pedagogical competence who handled the Conversation for Adults Classes at Basic Conversation Level in British English School Makassar. Most of the students at this level still have low English competence and consider that English is difficult. The pedagogic competence of the teachers is related to the success of the learning activities. Therefore, it is required to analyse the teachers’ pedagogic competence based on the students’ perception since this affects to their attitude and actions in learning activities. The population of this study was 100 Adults students of British English School who participated in Basic Conversation Class from January to February 2024. The sample of this study was 50 students taken by using purposive sampling technique. The instrument used in this study is a non-test instrument consisting of 25 items of statements to measure students’ perception on English Teachers’ pedagogical competence. From the data processing, the result of the research was (1) Based on statements, obtained 52% in very good category, 20% in good category, 24% in enough category, 4% in less category, 0% in very less category; (2) Based on indicators, obtained 73.04% good category for learning preparation, 68.35% in good category for presentation of learning materials, 74.8% in good category for learning approach/strategy, 91.87% in very good category for students involvement learning, 70.4% good category for design and do the evaluation and 57.4% in good category for utilize assessment result for quality improvement of learning; (3) overall, the student’s perception on English teachers’ pedagogical competence is 72.64% in good category.
Analisis Konflik Sosial Dalam Novel Santri Pilihan Bunda karya Salsyabila Falensia
Authors: Indriyani Nova , Abror Muchlas
Published: February 2025

Penelitian ini bertujuan untuk: 1) mendeskripsikan bentuk dan penyebab konflik sosial dalam novel Santri Pilihan Bunda berdasarkan teori George Simmel, 2) mendeskripsikan penyelesaian konflik sosial berdasarkan teori George Simmel dan 3) mendeskripsikan dari sisi dampak positif setelah terjadinya konflik sosial berlangsung. Penelitian ini menggunakan penelitian kualitatif deskriptif. Pemerolehan data dilakukan melalui baca simak dilanjutkan dengan teknik catat. Analisis data menggunakan model Miles dan Humberman melalui beberapa tahap: redukasi data, pemaparan data dan penarikan kesimpulan. Berdasarkan teori George Simmel terdiri dari tiga konflik sebagai berikut: 1) konflik kepentingan mempunyai satu bentuk konflik yaitu adu mulut, 2) konflik antar pribadi mempunyai empat bentuk konflik yaitu adu mulut, pengroyokan, sindiran dan ketegangan, dan 3) konflik dalam hubungan Intim mempunyai dua bentuk konflik yaitu adu mulut dan ketegangan. Bentuk penyelesaian konflik berdasarkan teori George Simmel dalam penelitian ada lima: koersi, mediasi, toleransi, konversi dan jalan buntu. Dan juga terdapat dua bentuk dampak positif konflik sosial diantaranya: perubahan perilaku individu dan tambahnya kebersamaan kelompok atau solidaritas.
Inovações e Desafios na Produção Agroindustrial de Alimentos
Authors: Martins Wiaslan Figueiredo , Fernandes Ana Paula Stort , Soares Dayana Silva Batista , Pinto Ellen Godinho , Ribeiro Erlon Alves , Boeno Josianny Alves , Ferreira Suzane Martins , Carvalho Vania Silva
Published: February 2025

Este livro é uma coletânea de trabalhos científicos apresentados durante a VII Semana de Alimentos, realizada pelo Instituto Federal Goiano – Campus Morrinhos. A obra reúne estudos submetidos e aprovados no evento, cada um devidamente identificado por seu DOI, resumo e palavras-chave, evidenciando a diversidade de pesquisas desenvolvidas no campo da produção agroindustrial de alimentos.

Os trabalhos abrangem temas variados, como a análise da cinética de crescimento de microrganismos em filés de carne bovina embalados em atmosfera modificada, a revisão sobre a produção de derivados lácteos a partir de leite de búfala e a modelagem do comportamento de patógenos, como Salmonella spp., sob diferentes condições de armazenamento. Cada capítulo apresenta abordagens metodológicas que ressaltam os desafios e as inovações tecnológicas aplicadas à segurança, qualidade e eficiência dos processos produtivos no setor alimentar.

Orientada a partir da coletânea de trabalhos apresentados no evento, esta publicação serve como um importante registro das discussões técnicas e científicas ocorridas na VII Semana de Alimentos. Ao reunir contribuições relevantes para a agroindústria, o livro se torna uma referência indispensável para profissionais, pesquisadores e estudantes interessados em aprofundar seus conhecimentos e acompanhar as tendências e os desafios atuais na produção de alimentos.
Normativna i
praktična razmatranja zabrane reformatio in peius u kaznenom postupku
Authors: Aljinović Nevena , Bilušić Ivana
Published: February 2025

Zabrana reformatio in peius neizostavna je komponenta vladavine prava, koja počiva na postulatu pravednosti kažnjavanja u obliku jamstva okrivljeniku da žalba podnesena samo u njegovu korist neće rezultirati donošenjem presude na njegovu štetu, odnosno strožom osudom od one na koju je žalba izjavljena. Učinak zabrane dalekosežan je i premašuje okvire pravomoćnosti odluke budući da zabrana reformatio in peius nakon uspostave vrijedi i nakon pravomoćnosti odluke, u postupku u povodu izvanrednih pravnih lijekova izjavljenih u korist osuđenika, sve do konačnosti odluke. Iako iz teksta samog zakona proizlazi da se zabrana reformatio in peius aktivira podnošenjem pravnog lijeka samo u korist okrivljenika, razvidno je da zabrana nastupa u situaciji kada se državni odvjetnik uopće nije žalio na presudu ili se nije žalio u određenom smjeru (premda je uložio žalbu protiv presude). U pravnoj teoriji i sudskoj praksi nesuglasje izaziva opseg primjene zabrane reformatio in peius u žalbenom postupku. Naime, u pravnoj teoriji zastupljeno je stajalište da (samo) podnošenje žalbe na štetu okrivljenika anulira aktivaciju predmetne zabrane, stoga dvojbe pobuđuju situacije kada je pravni lijek, doduše, izjavljen na štetu okrivljenika, ali je odlukom suda odbačen kao nedopušten ili nepravodoban, odnosno odbijen kao neosnovan, ili situacije u kojima je državni odvjetnik podnio žalbu protiv presude, ali je presuda ukinuta po službenoj dužnosti ili u povodu žalbe okrivljenika zbog bitne povrede odredaba kaznenog postupka, čime je žalba državnog odvjetnika postala bespredmetna. Autorice u radu analiziraju normativno uređenje zabrane reformatio in peius u Republici Hrvatskoj, kao i sudsku praksu, napose županijskih sudova, Visokog kaznenog suda Republike Hrvatske i Vrhovnog suda Republike Hrvatske u cilju pronalaženja odgovora na dvojbene situacije koje se pojavljuju u praksi sudova. Ključne riječi: zabrana reformatio in peius, pravo na žalbu, načelo pravičnog postupka, jednakost oružja, zabrana izmjene na gore
Dynamic Multi-Scale Feature Fusion for Robust Sleep Stage Classification Using Single-Channel EEG
Authors: Zhong Jiajun
Published: February 2025

Sleep stage classification is pivotal in evaluating sleep quality and diagnosing sleep-related disorders. Recent advancements in automated single-channel electroencephalogram (EEG)--based classification have gained traction due to their cost-effectiveness and portability. However, the inherent non-stationarity of EEG signals and inter-class imbalance pose significant challenges for model design. This paper proposes MultiScaleSleepNet, an enhanced deep learning architecture that addresses these limitations through dynamic multi-scale feature fusion and residual structural optimizations. Our contributions are threefold: (1) A selective kernel convolution module (SKConv) that dynamically integrates multi-branch convolutional features (kernel sizes: 3, 5, 7) via attention mechanisms to adaptively capture frequency-specific patterns in EEG signals; (2) A residual multi-branch downsampling module that mitigates information loss while preserving high-frequency details for minority-stage classification; (3) Comprehensive experiments on the Sleep-EDF-20 dataset demonstrate superior performance, achieving a macro F1-score (MF1) of 79.6%—a 1.5% improvement over baseline models—with notable gains in classifying the N1 stage (F1-score: 47.0%, +4.4% relative improvement). Quantitative ablation studies validate the efficacy of SKConv and residual connections in enhancing feature discriminability. This study delivers a robust single-channel EEG-based sleep analysis framework, demonstrating significant clinical applicability in resource-constrained settings.
Brain tumor segmentation using deep learning: A Review
Authors: Hou Beibei , Guan Saizong
Published: February 2025

Brain tumor segmentation is a crucial task in medical image analysis, as accurate delineation of tumor regions is vital for clinical diagnosis, treatment planning, and prognosis assessment. Traditional Convolutional Neural Network (CNN)-based models have demonstrated significant success in capturing local features, but they face challenges in modeling global context, which is essential for complex segmentation tasks. This review examines recent advancements in brain tumor segmentation, with a focus on CNNs, Transformers, Mamba, and Graph Neural Networks (GNNs), as well as their hybrid models. This review critically evaluates the strengths and limitations of each approach with respect to architecture, segmentation accuracy, and real-world applicability. Additionally, it addresses key challenges such as computational complexity and data scarcity, and proposes future research directions to enhance the practical use of these methods in clinical settings.
Feature Recognition of Ultrasound Breast Images Based on Improved DSA-U++
Authors: Guan Weichun , Zhang Yuanyuan , Lv Xinshu , Lv Shuyun , Lin Mao , Liu Zhengyang
Published: February 2025

The aim of this project is to recognize features in ultrasound breast images. And an improved DSA-U++ model is proposed based on the image classification task, the traditional U-Net++ in the encoder part in the face of ultrasound images there is a lack of feature extraction, to solve this problem we use Resnet50 as the backbone of the extraction, in order to further enhance the ability of the feature learning, we also introduced the ASPP module, to help capture contextual information at different scales, and a module R-AS is designed to enhance the model multi-scale perception ability. information to enhance the model's multi-scale perception ability and a module R-AS. the output of R-AS after five stages is used as the encoding part of U-Net++, and the feature information extracted by the encoder is reconstructed and enhanced in the decoder part. In order to reduce the computational complexity and the number of parameters, and to maintain a certain feature extraction ability, we replace the traditional convolution in the decoder part of U-Net++ with a depth-separable convolution, which is experimentally validated on the AI Algorithm Elite Challenge dataset, which consists of ultrasound breast images with four features, namely, orientation, edges, calcifications, and shapes, and is trained with the DSA-U++ model. After the DSA-U++ model is trained, it improves on several indexes, not only improving the recognition ability of subtle features in ultrasound breast images, but also effectively improving the performance of image classification.
Research on the Cultivation of Students' Autonomous Learning Ability in Online Learning Environment
Authors: Wang Tiening
Published: February 2025

This paper explores the cultivation of students' autonomous learning ability in an online learning environment. With the rapid development of information technology and the widespread adoption of online education, fostering students' ability to learn independently has become increasingly important. The study examines the concept and characteristics of autonomous learning, analyzes the current state of online learning environments, and investigates factors influencing the development of autonomous learning abilities. Based on theoretical foundations and practical considerations, the paper proposes strategies for cultivating autonomous learning abilities, including optimizing the online learning environment, designing effective teaching strategies, and implementing comprehensive evaluation methods. The research findings provide valuable insights for educators and policymakers seeking to enhance students' autonomous learning capabilities in the digital age.
A multi-type output vehicle circuit system based on CANFD communication control
Authors: Zhai Haotian , Liang Xiyin , Deng Pengfei
Published: February 2025

To address the complex control requirements and system flexibility challenges faced by intelligent vehicles and autonomous driving technology, especially with the significant increase in in-vehicle communication demands, traditional automotive networks such as CAN or LIN have gradually exposed issues with insufficient information exchange speed. This research introduces the more advanced CANFD technology, utilizing a circuit control system based on the STM32 microcontroller with CANFD communication support. By integrating high-performance digital-to-analog converters, the system can generate precise level signals within milliseconds, enabling the control of various analog input devices. Additionally, by using pulse-width modulation (PWM) functionality, efficient control is achieved, improving the system's response speed and flexibility. Meanwhile, a low-frequency wireless communication conversion module connected via serial port enables remote monitoring of key vehicle parameters. This allows for real-time monitoring and fault diagnosis of vehicle operation, providing a reliable solution for the development of intelligent vehicles and autonomous driving technology.
Evolutionary Game Analysis of Enterprise IT Project Management from the Perspective of Technical Debt
Authors: Cui Jingbo
Published: February 2025

Technical debt has become a crucial factor hindering the development of enterprise IT projects, and its management strategy directly affects the success or failure of projects. By constructing a multi-party game model of technical debt management using game theory, this study analyzes the strategic choices and interactions among project managers, development teams, and clients, revealing the evolutionary laws of technical debt. The research shows that a reasonable technical debt management strategy can reduce system maintenance costs by 30% and improve development efficiency by 40%. Case analysis verifies the practicality of the model and provides management suggestions based on game equilibrium. The research findings provide theoretical and practical guidance for technical debt management in enterprise IT projects.
Teaching Reform in University Piano Education by Leveraging Multimedia Technology to Foster Innovation and Performance Skills
Authors: Yang Yang
Published: February 2025

This paper explores the integration of multimedia technology into university piano education, emphasizing its role in fostering innovation and enhancing performance skills. It examines the traditional pedagogical methods and their limitations, followed by an analysis of how multimedia tools-such as virtual simulations, digital sheet music, interactive applications, and online collaboration platforms-enhance learning outcomes. Through empirical data analysis and case studies, the study demonstrates the effectiveness of these technological interventions. The research concludes with recommendations for educators and institutions on best practices for implementing multimedia in piano education.
MsaACPpred: Prediction of Anticancer Peptides Based on Multi-Scale Attention Convolutional Network
Authors: Diao Yanyu , Liu Xueyi
Published: February 2025

Anticancer peptides (ACPs) constitute a family of biologically active peptides with significant anti-tumor activity. These peptides are composed of 5 to 50 amino acid residues and are generally cationic in nature. Through electrostatic interactions, ACPs are able to target and bind to negatively charged cell membranes on the surface of cancer cells, thereby destroying their structure and inducing apoptosis. Given that the process of recognizing ACPs in the laboratory is highly restricted, which is not only costly but also time-consuming and lengthy, this study proposes a computational method for predicting ACPs based on sequence information. The method is designed with three core modules: feature encoding of peptide sequences, deep learning module layers, and a classification prediction layer. Among them, the deep learning module integrates convolutional neural network (CNN), attention mechanism and bidirectional long short-term memory network (BiLSTM), which enhances the learning and analyzing ability of the model. Ultimately, our model achieves 73.1% accuracy while maintaining 77.8% sensitivity and 69.6% specificity.
Plantation forestry research in India: A mini review
Authors: Melkania N. , Arunachalam Kusum
Published: February 2025

Forestry in India presents the history of deforestation and degradation, and on the other the humanized forestation - the plantation forestry. Heavy felling of natural forests during the world wars, especially the second one, replaced natural regeneration-based colonical forestry to human-controlled plantations in the neo-colonical (post-independence) age in a gradient of social, socio-economic and ecological - socioeconomic perspectives in the first, third and eighth Five Year Plans, respectively. This synthesis presents progress in selected aspects of plantation forestry research in India, especially during the last decade and attempts to identify the opportunities for future research to achieve sustainable human-controlled forestry for multiple resource management.
Hvad kan plandata fortælle om planlægning i Danmark?
Authors: Fertner Christian
Published: February 2025

Det danske digitale plandatasystem er blevet etableret som en væsentlig ressource for alle, der arbejder med planlægning. De danske plandata giver indsigt i planlægningen fra de seneste 17 år (og delvis længere tilbage), men en systematisk evaluering af planlægningen baseret på disse data er sjældent gjort.
Perspektiver fra den nationale database kan udgøre en komplementær metode til casestudier for at identificere generelle tendenser i planlægningen, såsom planområdets arealforbrug i forskellige geografier, anvendelser, vi planlægger for, eller temaer, der bliver fremhævet. Udviklingen over tid kan muligvis give indsigt i levetiden af planerne. Artiklen diskuterer analysemulighederne på baggrund af konkrete eksempler.
Knowledge, Attitude, and Practice of Bee Venom Acupuncture Therapy Among Patients in West of Libya
Authors: Somaia Elsaedi  , Amnnah Ahmed  , Ahlam Mohamed  , Ayat Omar  , Shaima Aburas  , Hajer Ali  , Abdulrhman Akasha
Published: February 2025

Apitherapy is an alternate therapy that relies on the usage of honeybee products, most importantly bee venom for the treatment of many human diseases. Bee venom contains several active molecules such as peptides and enzymes that have advantageous potential in treating inflammation and central nervous system diseases. Moreover, bee venom has shown promising benefits against different types of cancer as well as anti-viral activity. This study explores the effects and perceptions of bee venom therapy (BVT) among a selected population in Libya. The research primarily focuses on the demographics of individuals undergoing BVT, the frequency and types of symptoms experienced post-therapy, and the various conditions for which BVT is utilized. A cross-sectional descriptive study of 100 participants using a structured questionnaire on knowledge, attitude scale, and practice was done at three regions in Libya including Tripoli, Gerian & Yefran during Jun and July 2024. A randomized sample size that included a diverse age group and both genders. The data were presented as frequencies and percentages. Excel is used to enter and analyze the data. Results indicated a broad acceptance of BVT, with a majority of participants reporting symptomatic relief for various conditions such as muscular pain, back pain, and nerve-related issues. However, a significant portion of participants also reported common side effects such as swelling and localized pain. The study highlights the necessity for more extensive research to validate the efficacy of BVT and to better understand the long-term impacts and potential risks associated with the therapy.
A Study On Geodesics And Lifespan Of The Rindler-Modified Schwarzschild Black Hole.I. Time-Like Geodesics
Authors: Huo T. , Liu C.
Published: February 2025

We study the time-like geodesics in the spacetime of the Rindler-modified Schwarzschild black hole (RMSBH) with a cosmological constant. We find that for massive particles, whether undergoing radial motion or orbital motion, are unable to escape the black hole. Meanwhile, at larger orbital radii, the cosmological constant significantly modifies the proper velocity of particles. Additionally, we have presented a special solution: if the particle is located on a specific circular orbit, its proper velocity will remain unaffected by the Rindler acceleration. Furthermore, we discuss the stability of circular orbits by employing the Lyapunov exponent, and draw the dividing line between stable and unstable circular orbits.
Исследованы времениподобные геодезические линии в пространственновременной метрике модифицированной Риндлером черной дыры Шварцшильда (RMSBH) с учетом космологической постоянной.
Spectral Variations And Physical Conditions Of By Draconis In The Ultraviolet
Authors: Sanad M. R.
Published: February 2025

We present International Ultraviolet Explorer (IUE) observations during the period (1980 - 1994) of the double lined spectroscopic binary BY Dra to show the spectral behavior and physical conditions in its atmosphere.
Представлены наблюдения IUE спектрально-двойной звезды BY Dra в период с 1980 по 1994 гг. с целью показать спектральное поведение и физические условия в её атмосфере.
A Cosmological Model With Second Law Of Thermodynamics In F(R, T) Gravity
Authors: Tiwari R. K. , Bharali J. , Chetry B. , Beesham A.
Published: February 2025

In the context of f (R, T ) modified gravity theory, we investigate a cosmological model with homogeneous and anisotropic properties, specifically the Locally Rotationally Symmetric (LRS) Bianchi type-I model.
В рамках модифицированной теории гравитации f R, T  исследована космологическая модель с однородными и анизотропными свойствами, в частности, локально вращательно-симметричная (LRS) модель Бьянки типа I.
Isolation of griseofulvin from the endolichenic fungus Cubamyces menziesii (Berk.) Lücking inhabiting Parmotrema rampoddense (Nyl.) Hale
Authors: Tan Mario , dela Cruz Jake Darryn , Magpantay Hilbert , Apurillo Carlo Chris , dela Cruz Thomas Edison
Published: February 2025

Efungi represent valuable sources for the discovery of diverse and biologically relevant natural products with significant applications in pharmaceuticals, agriculture, and industry. In this study, Cubamyces menziesii (Berk.) Lücking, an endolichenic fungus isolated from the lichen Parmotrema rampoddense (Nyl.) Hale, was subjected to extraction and chromatographic purification to obtain griseofulvin (1) and acetyl tributyl citrate (2). The antimicrobial activity of the isolated compounds was assessed using the microtiter plate antimicrobial assay showing 125 – 250 µg/mL minimum inhibitory concentration and minimum bactericidal concentration in Klebsiella pneumoniae ATCC 700603, Pseudomonas aeruginosa ATCC 27853, and Staphylococcus aureus ATCC 25923. This is also the first report of griseofulvin (1), a commercially available antifungal drug, from the genus Cubamyces. The findings highlight the potential of C. menziesii as a promising resource for bioactive compounds, with implications for the development of novel antimicrobial agents for medical and industrial applications.
Best practices for implementing scrum in Jira
Authors: Vududala Santosh Kumar
Published: February 2025

In today’s world software development is a complex process which requires a powerful and adaptive methodology along with framework for managing and completing the projects. Agile methodology is a modern approach which is widely used in the software development. Agile includes different frameworks like Scrum, Kanban, Scaled Agile Framework (SAFe) and Extreme Programming (XP). While each approach has its own specific practices and guidelines, they all share the core principles of Agile and aim to deliver high-quality software efficiently and adaptively. Jira is a project management tool developed by Atlassian which provides robust features to support Scrum practices effectively.
Scrum is an agile framework which widely adopted in software development across different domains. Scrum framework focuses on collaboration between the teams, teamwork, iterative approach, and adaptability. Scrum divides the project work into small manageable units and helps to delivering value incrementally. This paper explores the best practices for implementing Scrum in JIRA to streamline the workflows and boost team productivity.
Enhancing fraud detection and forensic auditing through data-driven techniques for financial integrity and security
Authors: Elumilade Oluwafunmike O. , Ogundeji Ibidapo Abiodun , Achumie Godwin Ozoemenam , Omokhoa Hope Ehiaghe , Omowole Bamidele Michael
Published: February 2025

Financial fraud remains a significant challenge in global economies, threatening the integrity and security of financial systems. Traditional fraud detection and forensic auditing methods often fail to keep pace with increasingly sophisticated fraudulent schemes. This review explores the role of data-driven techniques in enhancing fraud detection and forensic auditing to ensure financial integrity and security. Leveraging advanced technologies such as big data analytics, machine learning (ML), artificial intelligence (AI), blockchain, and robotic process automation (RPA), financial institutions can identify fraudulent activities in real time, improve predictive accuracy, and strengthen risk assessment frameworks. Big data analytics enables the processing of large volumes of financial transactions to detect anomalies and suspicious patterns, while ML algorithms provide adaptive fraud detection by recognizing evolving fraud tactics. AI-powered natural language processing (NLP) enhances forensic investigations by analyzing unstructured financial data, including emails and contracts, for signs of misconduct. Blockchain technology ensures transaction transparency and minimizes risks associated with identity fraud and double spending. Additionally, network analysis techniques improve the detection of fraudulent connections and collusive activities in financial networks. Despite the advantages of data-driven approaches, challenges such as data privacy concerns, implementation costs, and the continuous evolution of fraudulent tactics require adaptive regulatory frameworks and ethical considerations. Successful case studies demonstrate the efficacy of AI-driven fraud detection models in financial institutions, highlighting the importance of integrating data-driven methodologies into forensic auditing. This study emphasizes the need for financial institutions and regulatory bodies to adopt innovative fraud prevention strategies while maintaining compliance with governance and security standards. Future research should focus on developing scalable and interpretable AI models to enhance financial crime mitigation. By integrating advanced analytics with regulatory oversight, financial institutions can reinforce fraud prevention mechanisms and safeguard global financial systems against illicit activities.
Sustainable energy solutions through AI and software engineering: Optimizing resource management in renewable energy systems
Authors: Odunaiya Olusegun Gbenga , Soyombo Oluwatobi Timothy , Ogunsola Olakojo Yusuff
Published: February 2025

Sustainable energy solutions are increasingly critical in addressing global energy demands while minimizing environmental impact. The integration of artificial intelligence (AI) and software engineering plays a transformative role in optimizing resource management within renewable energy systems. This paper explores how AI technologies, including machine learning, predictive analytics, and data-driven modeling, can enhance the efficiency and reliability of renewable energy sources such as solar, wind, and hydroelectric power. By leveraging advanced algorithms, these technologies enable the optimization of energy production, consumption, and distribution, significantly improving overall system performance. One of the primary applications of AI in renewable energy is in forecasting energy generation and demand. Machine learning algorithms analyze historical data and real-time inputs to predict fluctuations in energy production due to weather conditions or seasonal variations. This predictive capability allows for more accurate planning and utilization of resources, ensuring that energysupply aligns with demand. Additionally, AI can optimize grid management by facilitating real-time monitoring and control of distributed energy resources, enhancing grid resilience and reducing energy losses. Furthermore, software engineering methodologies, such as agile development and model-driven engineering, are instrumental in designing and deploying intelligent energy management systems. These systems can automate decision-making processes, enabling rapid responses to changing energy conditions and user demands. The result is a more flexible and responsive energy infrastructure capable of integrating diverse renewable sources while maintaining stability. Despite the promising benefits, challenges remain in the implementation of AI-driven solutions in renewable energy systems. Data privacy concerns, the need for high-quality data, and the potential for algorithmic bias require careful consideration. Addressing these challenges is essential for achieving widespread acceptance and effective deployment. Inconclusion, the convergence of AI and software engineering presents innovative pathways for optimizing resource management in renewable energy systems. By harnessing these technologies, stakeholders can enhance the sustainability and efficiency of energy solutions, contributing to acleaner, more resilient future.
Integrated marketing communication framework for esports brand growth and audience expansion
Authors: Esiri Sidney
Published: February 2025

The rapid expansion of eSports as a mainstream entertainment industry has created the need for a comprehensive Integrated Marketing Communication (IMC) framework to enhance brand growth and audience engagement. This review proposes an IMC model tailored to the unique dynamics of eSports, incorporating digital marketing, sponsorship strategies, event marketing, and community engagement.By integrating multiple communication channels and data-driven decision-making, the framework aims to establish strong brand positioning and maximize audience reach. A key component of the framework is digital and social media marketing, leveraging platforms such as Twitch, YouTube, Discord, and TikTok to enhance audience interaction through influencer collaborations, live streaming, and gamified content. Sponsorship and partnership strategies play a crucial role in brand monetization, attracting both endemic (gaming-related) and non-endemic sponsors through innovative co-branding opportunities. Additionally, event marketing and fan engagement strategies, including in-person tournaments, virtual events, and hybrid experiences, contribute to sustained audience retention. Public relations and community-driven branding efforts help build trust and authenticity, ensuring long-term loyalty among fans. The framework also explores monetization strategies, such as branded merchandise, digital collectibles, and subscription-based content models. By implementing data-driven audience segmentation, eSports organizations can personalize marketing campaigns to different fan demographics, optimizing engagement and conversionrates. Case studies from successful eSports teamsand brands demonstrate the effectiveness of IMC strategies in driving brand equity and market expansion. However, challenges such as content saturation, ad-blocking, and shifting platform preferences must be addressed to ensure sustainable growth. This research highlights the importance of integrating emerging technologies, including artificial intelligence, blockchain, and metaverse branding, to maintain competitive advantage. The proposed IMC framework provides a strategic roadmap for eSports stakeholders seeking to enhance brand visibility, audience engagement, and long-term profitability in a rapidly evolving digital landscape.
Blockchain-Enhanced Financial Transparency: A Conceptual Approach to Reporting and Compliance
Authors: Omowole Bamidele Michael , Omokhoa Hope Ehieghe , Ogundeji Ibidapo Abiodun , Achumie Godwin Ozoemenam
Published: February 2025

The increasing demand for financial transparency and compliance has driven the adoption of innovative technologies to improve reporting systems. This paper proposes a conceptual framework for blockchain-enhanced financial transparency, emphasizing its transformative potential in ensuring accountability, accuracy, and regulatory compliance. Blockchain technology, with its decentralized, immutable, and secure ledger system, offers significant advantages in addressing challenges associated with traditional financial reporting and compliance mechanisms. The proposed framework focuses on integrating blockchain into financial reporting processes to create a tamper-proof environment for data management and transaction validation. Key components include real-time data sharing, automated compliance checks through smart contracts, and enhanced traceability of financial transactions. These features reduce the risks of fraud, errors, and misreporting while increasing stakeholders’ trust in financial disclosures. Additionally, the immutable nature of blockchain ensures an accurate historical record of financial activities, facilitating seamless audits and regulatory reviews. The research also explores the potential for interoperability between blockchain platforms and existing financial systems, enabling seamless integration without disrupting organizational workflows. The use of tokenization for asset representation and reporting simplification is examined, alongside strategies for ensuring scalability and efficiency in blockchain networks. Furthermore, the study highlights the role of artificial intelligence (AI) in analyzing blockchain-stored data to provide actionable insights and enhance decision-making. Challenges such as regulatory uncertainties, technological adoption barriers, and data privacy concerns are critically analyzed. Proposed solutions include developing industry standards, fostering regulatory collaborations, and adopting hybrid blockchain models to balance transparency with confidentiality. The study concludes that blockchain-enhanced financial transparency offers a robust framework for transforming financial reporting and compliance practices. It underscores the need for cross-industry collaboration and strategic investment to harness blockchain’s full potential in creating a secure and transparent financial ecosystem.
Ciclo biológico de Diaspis echinocacti (Bouché,1833) (Hemiptera: Diaspididae) en Tuna Opuntia ficus – indica bajo condiciones de laboratorio
Authors: Rogel Zambrano Guillermo , Marlon Pineda-Escobar , Bayron Cisneros , Esperanza Gia Ajila
Published: February 2025

En la presente investigación se estudió el ciclo biológico de Diaspis echinocacti (Bouché, 1883) (Hemiptera: Diaspididae) además, de otros parámetros biológicos para la hembra adulta, utilizando como hospedero los cladodios de Tuna (Opuntia ficus-indica), bajo condiciones ambientales en el laboratorio de Ecología del Museo de Entomología Klaus Raven Büller de la Universidad Nacional Agraria La Molina (UNALM), durante las estaciones de invierno 21,5 ± 1,5 oC y 70 ± 4% HR (junio a septiembre de 2018) y otoño 27 ± 2 o C y 80 ± 2% HR (marzo a junio de 2019). Se realizó una crianza masal, con el fin de obtener un pie de cría puro, que sirvió para dar inicio a las evaluaciones tanto del ciclo biológico como de otros parámetros biológicos, considerando dos repeticiones para cada época del año. La duración del ciclo biológico para las hembras en invierno fue de 53,05 días y para los machos de 51,05 días; en otoño fue de 39,75 días para las hembras y 37,25 días para los machos. Estos resultados reflejan la influencia de la temperatura en el ciclo biológico de D. echinocacti en otoño y esto es contrariamente en invierno. En referencia a la evaluación de otros parámetros biológicos para la hembra adulta, se registraron: la capacidad de oviposición con un promedio de 120 ± 30 huevos por hembra; ritmo de oviposición de 2 – 6 huevos/hembra/día y su longevidad de 44,75 días para la época de otoño.
Ефективність адаптаційних процесів у зв´язку зі стильовими особливостями життєдіяльності особистості
Authors: Хохліна О. П. , Горбенко С. Л.
Published: February 2025

Психологічна допомога людині в складних ситуаціях передбачає покращення її адаптаційних можливостей, які забезпечують життєстійкість – здатність справлятися з такими ситуаціями, протистояти негативним впливам, повертатися до нормального життя й підтримувати нормальне функціонування, зберігаючи продуктивну активність. У статті наводяться результати теоретико-емпіричного дослідження зв´язку адаптації людини зі стильовими особливостями її життєдіяльності, які розглядаються як детермінанта ефективності цього процесу. Методологічною основою дослідження слугував системно-структурний підхід; методичним інструментарієм - методи аналізу наукових джерел, емпіричні методи опитування, аналізу документації, тестування з використанням стандартизованих психологічних методик вивчення процесу адаптації за низкою визначених показників та методик вивчення стилів діяльності, спілкування й поведінки; методи якісної та кількісної обробки емпіричних даних. Дослідною роботою були охоплено майже 200 осіб. У результаті проведеного емпіричного вивчення проблеми отримано дані щодо наявності та характеру зв´язку адаптованості досліджуваних за показниками самопочуття, активності, настрою, тривожності (особистісної, реактивної, загальної), рівня невротизації, нейротизму, самооцінки і рівня домагань, академічної успішності), з одного боку, та певними стилями життєдіяльності, з іншого, а саме: 1) стилем виконання діяльності (індивідуальним стилем діяльності - підготовчим, виконавчим, змішаним) й рівнем його сформованості; 2) широким спектром стилів спілкування й поведінки, які використовуються у взаємодії субꞌєктів при розвꞌязанні різноманітних завдань, створенні міжособистісних стосунків, передачі інформації та ін. Отримані результати дослідження доводять важливість формування й корекції стильових особливостей життєдіяльності людини з метою підвищення рівня її адаптації і, відповідно, посилення життєстійкості. Перспектива подальшого дослідження проблеми вбачається у розробці психотехнології розвитку життєстійкості людини на основі врахування отриманих результатів щодо звꞌязку ефективності її адаптаційних процесів з певними стильовими особливостями її діяльності, спілкування та поведінки.
Combined microscopic and neuroendoscopic treatment effects on psychological and cognitive outcomes in ruptured intracranial aneurysms
Authors: Shi Li-Ke , Cai Xian-Feng , He Jian-Qing , Wang Yu-Hai
Published: February 2025

BACKGROUND

Intracranial aneurysms, characterized by focal arterial wall dilation, pose significant neurosurgical challenges due to their potential for rupture and hemorrhage, leading to severe clinical outcomes, including fatality. Patients often experience profound psychological and social impacts, such as depression, anxiety, and cognitive impairment, affecting their quality of life. Rapid progression and high mortality necessitate timely intervention. Advances in neurosurgical techniques, including microscopic surgery and neuroendoscopy, offer distinct advantages. Microscopic surgery provides precision and direct visualization, while neuroendoscopy ensures minimally invasive access and reduced tissue trauma. Integrating these methods optimizes treatment efficacy and clinical outcomes.

AIM

To evaluate the impact of combined microscopic and neuroendoscopic techniques on psychological, cognitive outcomes, and quality of life in patients with ruptured intracranial aneurysms.

METHODS

The study focused on 189 patients with intracranial aneurysm rupture and hemorrhage from January 2020 to May 2024 as the objects of observation and analysis. They were randomly divided into a control group (treated with simple microscope surgery, n = 94) and an observation group (treated with microscope combined with neuroendoscopy, n = 95). The treatment effects of the two groups were observed, mainly including depression and anxiety scale scores, cognitive function assessment results and quality of life assessment data.

RESULTS

Before treatment, the depression and anxiety scale scores, cognitive function assessment results and quality of life assessment data of the two groups of patients at different time points were compared, and there was no statistically significant difference (P > 0.05). After microscope combined with neuroendoscopy treatment, the study revealed that the observation group surpassed the control group in alleviating depression and anxiety, accelerating cognitive function recovery, and enhancing quality of life, with these differences being statistically significant (P < 0.05).

CONCLUSION

Surgical treatment combined with microscopy and neuroendoscopy has a significant positive effect on the mental health, cognitive function and overall quality of life of patients with intracranial aneurysm rupture and bleeding, can shorten the operation time and treatment time, and provides a new strategic reference for clinical treatment.