bluuebunny/crossref_metadata_2025 huggingface dataset:
ĐÁNH GIÁ THỰC TRẠNG PHÂN BỐ, GÂY TRỒNG PHÁT TRIỂN CÂY GIỔI ĂN HẠT (Michelia tonkinensis A.Chev.) TRÊN ĐỊA BÀN TỈNH LÀO CAI
Authors: Vu Quy Dong , Nguyễn Xuân Đài , Trần Văn Cao , Lê Thị Thu Hằng
Published: October 2024

Cây Giổi ăn hạt chưa được đầu tư gây trồng có bài bản ở địa bàn tỉnh Lào Cai. Một số huyện đã có các mô hình tập trung nhưng chưa nhiều, đa phần là các cây trồng phân tán trong vườn hộ, nguồn giống không được kiểm soát. Người dân hầu như không chăm sóc thường xuyên cũng như bón phân trong quá trình trồng và chăm sóc cây Giổi ăn hạt. Cây Giổi ăn hạt đã cho thu hoạch quả đều thuộc mô hình trồng phân tán trong vườn hộ và có thời gian trồng hầu hết từ 20 năm trở lên. Việc thu hái, sơ chế và bảo quản hạt giống được áp dụng theo kinh nghiệm của người dân. Kết quả phân tích, so sánh hàm lượng tinh dầu và thành phần các chất bay hơi trong mẫu hạt Giổi tại tỉnh Lào Cai khi so sánh với 2 tỉnh Hòa Bình và Phú Thọ cho thấy chất lượng tinh dầu hạt giổi tại 3 tỉnh không có khác biệt quá lớn. Cây Giổi ăn hạt trồng tại Lào Cai có biên độ phân bố khá rộng, phù hợp với nhiều loại điều kiện địa hình, khí hậu, thổ nhưỡng khác nhau. Các mô hình trồng tập trung Giổi ăn hạt bằng phương thức trồng thuần loài phổ biến ở tuổi 2 đến tuổi 13. Các chỉ tiêu sinh trưởng tương đối đồng đều và ổn định. Tuy nhiên, việc các hộ dân hầu như không áp dụng bón phân trong quá trình trồng và chăm sóc đã làm tốc độ sinh trưởng và phát triển của cây Giổi ăn hạt tương đối chậm. Nhìn chung, tỉnh Lào Cai có điều kiện và tiềm năng gây trồng và phát triển cây Giổi ăn hạt rất lớn. Tuy nhiên, việc chưa được đầu tư nghiên cứu bài bản cũng như chưa được quan tâm, chăm sóc đúng mức là trở ngại rất lớn đến sự phát triển loài cây này tại địa phương. Do vậy, việc tăng số lần chăm sóc cũng như áp dụng bón phân cho cây là rất cần thiết để đảm bảo khả năng phát triển của các mô hình trồng Giổi ăn hạt tại tỉnh Lào Cai trong tương lai.
The Development of Interactive Learning Media for Islamic Religious Education in Elementary Schools in Indonesia
Authors: Susanto Happy , Marpuah Siti , Sudarmadi  , Erwahyudin Devid Dwi , Wahyuni Nani
Published: October 2024

In today’s digital era, conventional teaching methods often fail to captivate students, making interactive media a promising solution. Interactive media combines visual, audio, and participatory elements, providing a more engaging and effective learning experience. The development process includes analyzing student needs and curriculum, selecting appropriate technology, creating interactive content, conducting trials, and evaluating effectiveness. This study uses a qualitative approach. Primary data sources in qualitative research are the words of the interview results obtained from primary data including respondents from teachers and students in SDMT Ponorogo. Data collection is carried out by means of snowball sampling. The data collection technique in this study is through observation, in-depth interviews and documentation. The data obtained during the study, both primary and secondary data are then processed and analyzed using Miles and Huberman model. The validity test of data in qualitative research includes tests, credibility, transferability, dependability, and confirmability. The article highlights the benefits of interactive media, including increased student motivation, improved understanding of abstract religious concepts, and the development of critical thinking skills. This approach not only modernizes religious education but also ensures that students remain interested and actively involved in learning. Through proper testing and implementation, interactive media can significantly enhance the quality of Islamic Religious Education at SDMT Ponorogo. The developed media, which consists of animated videos, interactive quizzes, and educational games, is able to make the learning process more engaging and increase student engagement.
Pemberdayaan Masyarakat Peduli Lingkungan Melalui Teknologi Pengolahan Minyak Jelantah Menjadi Lilin Wangi
Authors: Maulidah Rifaatul , Sulistyaningsih Dwi , Sujarwanto Eko , Sumantri Agus
Published: October 2024

Masyarakat Desa Pawindan Kecamatan Ciamis, telah memiliki kesadaran akan pentingnya menjaga kelestarian lingkungan. Tampak dari program-program yang digagas oleh Kampung Keluarga Berencana (KB) Magot dan Kelompok Usaha Peningkatan Pendapatan Keluarga Sejahtera (UPPKS) Flamboyan seperti program “Selamatkan Lingkungan Hidup” yang menerapkan misi “Halaman Dirumat jeung Pipir Diurus”. Namun sayangnya informasi teknologi pengolahan sampah untuk menjadi barang bernilai guna belum sampai, terutama terkait teknik pengolahan minyak jelantah. Maka dari itu pengenalan teknologi tersebut penting untuk disampaikan oleh tim pelaksana melalui kegiatan Pengabdian bagi Masyarakat (PbM). Kegiatan ini bertujuan untuk menerapkan Teknologi Tepat Guna (TTG) pengolahan minyak jelantah menjadi lilin wangi yang bermanfaat dan bernilai ekonomis. Kegiatan ini merupakan solusi yang dipilih oleh tim pelaksana bersama mitra untuk memberikan tambahan pengetahuan serta keterampilan dalam memanfaatkan bahan limbah menjadi sebuah produk bernilai guna. Metode yang digunakan dalam kegiatan pelatihan adalah metode ceramah, diskusi tanya-jawab, kemudian dilanjutkan dengan demonstrasi dan praktik pengolahan minyak jelantah menjadi lilin wangi. Hasil kegiatan menunjukkan adanya pengetahuan baru bagi Masyarakat Desa Pawindan tentang pengolahan minyak jelantah menjadi lilin wangi. Diperoleh pula data respon peserta sebelum dan setelah mengikuti kegiatan yang menunjukkan adanya minat positif masyarakat untuk memanfatkan teknologi tersebut. Kedepannya program ini diharapkan dapat membantu masyarakat khususnya di Desa Pawindan Kecamatan Ciamis untuk terus menjaga kelestarian lingkungan dan memperoleh keterampilan baru
Perancangan Sistem Informasi Akademik Dengan Menggunakan Metode Rapid Application Development (RAD) Berbasis Website
Authors: Gilang Dwi Fahri Harahap  , Muhammad Khaibar Putra Adithia  , Saiful Amir  , Mardiah
Published: October 2024

The education system in Indonesia is experiencing rapid development characterised by an increase in the number of schools, students, and the complexity of the teaching and learning process. To manage academic data that includes information on students, teachers, grades, attendance, and class schedules, schools need to improve the quality of their services. Education is an important aspect of the country's development, and in this context, Academic Information System (AIS) plays a vital role in supporting administration and management in educational institutions. This research focuses on SMP NU Medan, where the need for an efficient and integrated AIS is increasingly urgent to improve the quality of education services. With the rapid development of information technology, the Rapid Application Development (RAD) method is the right choice because it allows rapid and iterative application development. In addition, Web-based AIS provides wide accessibility for education stakeholders, including making it easier for prospective students to access information and register online. The case study at SMP NU Medan provides a strong foundation for this research by identifying specific needs and coming up with solutions that are relevant and can be implemented immediately. This research aims to design, implement, and evaluate a Web-based AIS using the RAD method, so that it can make a positive contribution in improving the efficiency, accuracy, and quality of service of the school.
EFEKTIVITAS KONSUMSI AIR PUTIH TERHADAP RISIKO DEHIDRASI BERDASARKAN URIN PADA MAHASISWA KEPERAWATAN TOMOHON
Authors: Rachman Fernando , Walanda Irwan , Rumagit Selvie
Published: October 2024

Dehidrasi merupakan dimana kondisi tubuh kekurangan cairan, apabila tidak di tangani segera mungkin dapat mengakibatkan gangguan kesehatan. Penelitan ini bertujuan untuk mengidentifikasi jumlah konsumsi air putih dalam sehari pada mahasiswa keperawatan Universitas Sariputra Indonesia Tomohon yang di lakukan pada bulan maret 2022. Penelitian ini menggunakan metode kuantitatif dengan desain cross sectional. Dengan pengambilan data proposive sampling, populasi 240 mahasiswa, sampel 103 responden mahasiswa keperawatan semester II, IV dan VI dengan menggunakan kuisioner. Variabel Independen adalah konsumsi air putih dan Dependen adalah risiko dehidrasi berdasarkan warna urin. Instrument yang digunakan lembar observasi, spearmen rho digunakan untuk menganalisa data. Hasil uji statistic didapatkan P value=0,000 < a =0.05, maka HO diterima dan Ha ditolak. Kesimpulan dalam penelitian ini terdapat hubungan kuat pada kunsumsi air putih dan resiko dehidrasi.
ANALISIS FAKTOR YANG MEMPENGARUHI TINGKAT KECEMASAN PADA IBU HAMIL TRIMESTER III DALAM MENGHADAPI PERSALINAN DI MASA PANDEMI COVID-19
Authors: Sariowan Gladys , Tandipajung Tinneke , Timmerman Ellen
Published: October 2024

Kecemasan saat hamil banyak dialami oleh ibu hamil karena kurangnya pengetahuan dan dukungan dari keluarga, masyarakat, dan lingkungan. Beban psikologis ibu hamil lebih banyak terjadi pada kehamilan trimester III, dan banyak ibu hamil yang mengalami persalinan abnormal yang bahkan mengakibatkan kematian ibu dan janin. Tujuan penelitian ini adalah untuk mengetahui hubungan pendidikan ibu, usia ibu, paritas ibu dan dukungan keluarga dengan tingkat kecemasan pada ibu hamil trimester III di RS GMIM Bethesda Tomohon. Desain penelitian yang digunakan adalah Cross Sectional, sampel dalam penelitian ini adalah 58 orang, dari total populasi 68 orang. Pengambilan sampel menggunakan purposive sampling. Teknik pengumpulan data yang digunakan adalah kuesioner yang telah diuji validitas dan reliabilitasnya dengan dukungan keluarga alpha cronbach 0,869 kecemasan 0,761. Analisis univariat berupa distribusi frekuensi. Hasil analisis bivariat melalui uji chi-square dilanjutkan dengan uji Regresi Logistik menunjukkan signifikansi 0,024 < = 0,05 artinya pendidikan ibu berhubungan dengan tingkat kecemasan, sehingga H1 diterima. Melalui uji chi-square didapatkan signifikansi 0,035 < = 0,05 yang artinya umur ibu berhubungan dengan tingkat kecemasan sehingga H1 diterima. Melalui uji chi square signifikansi 0,047 < = 0,05 yang berarti paritas berhubungan dengan tingkat kecemasan sehingga H1 diterima. Melalui uji chi square signifikansi 0,015 < = 0,05 05 yang artinya dukungan keluarga berhubungan dengan tingkat kecemasan sehingga H1 diterima. Dengan demikian dapat disimpulkan bahwa ada hubungan antara pendidikan ibu, usia ibu, paritas ibu dan dukungan keluarga dengan tingkat kecemasan pada ibu hamil trimester III di RS GMIM Bethesda Tomohon.
EFEKTIVITAS TERAPI RELAKSASI OTOT PROGRESIF TERHADAP TEKANAN DARAH PADA LANSIA HIPERTENSI
Authors: Pantouw Angreany , Rondonuwu Peeki , Adam Anggela
Published: October 2024

Hipertensi  merupakan  salah  satu  masalah  kesehatan dengan  prevalensi yang cukup tinggi  dan  terus  meningkat. Salah satu upaya penanganan pada penderita hipertensi yaitu dengan cara terapi relaksasi otot progresif. Terapi ini mudah dilakukan, tidak memiliki efek samping, membuat tubuh menjadi rileks dan pikiran menjadi tenang. Tujuan penelitian ini adalah untuk mengetahui Efektivitas Relaksasi Otot Progresif Terhadap Tekanan Darah pada lansia hipertensi di RSU GMIM Bethesda Tomohon. Jenis penelitian ini adalah penelitian Quasi Eksperimen yaitu One Group Pre-Posttest Design. Sampel dalam penelitian ini adalah lansia hipertensi berjumlah 57 responden dengan teknik total sampling menggunakan kuisioner, data yang diperoleh dianalisa dengan uji Wilcoxon. Hasil yang diperoleh bahwa terapi sebelum dan sesudah terapi relaksasi otot progresif diperoleh dengan nilai hitung signifikan (p)  =  0,00 < α = 0,01  dengan Z hitung = -5,604 yang menunjukan ada pengaruh relaksasi  otot  progresif  terhadap  tekanan  darah  pada  lansia  hipertensi  di  RSU  GMIM  Bethesda  Tomohon. Terapi relaksasi otot progresif sangat tepat diberikan pada lansia hipertensi karena dapat menjaga tekanan darah agar tetap stabil.
Towards the Effective Utilisation of Influencer Marketing in Nigeria
Authors: Olanrewaju Ayishat
Published: October 2024

Advances in technology and the increased use of social media have made brands' usage of influencer marketing more widespread. Social media users no longer want to hear only from brands; they also want to listen to what others say about the brands and what their favourite influencers say. However, if brands do not understand how to utilise influencer marketing effectively, they cannot harness its benefits and minimise its drawbacks. Therefore, this position paper explored how organisations can gain desired results from well-planned influencer marketing efforts. It used the desk research methodology to gather secondary data on this subject matter. It discovered that organisations stand to benefit significantly from intentional and strategic influencer marketing campaigns if they consider several crucial factors such as the loyalty the influencer garners, how the influencer can persuade their audience, source credibility, content congruence, trustworthiness, values alignment, content informative value, content entertainment value, and the like. It was recommended that before working with influencers, organisations should be clear on their brand values and objectives to derive desired results. They should also develop influencer marketing guides, be more strategic and intentional when selecting influencers, and develop systems to monitor influencer marketing efforts effectively.
Leveraging Marketing Techniques for Disseminating Malaria Messages in Northern Nigeria: A Case Study
Authors: Mary Abah
Published: October 2024

Malaria intervention in Northern Nigeria had several gaps because transmission of the disease was aggravated by the warm weather which promoted mosquito breeding, and social determinants like malnutrition, which weakened immune systems, making people more vulnerable to illness. This study examined the application of marketing principles within the Community-led Monitoring (CLM) project, a Global Fund initiative to improve malaria interventions. CLM, among other things, was a development, health communication project that employed principles of marketing to communicate malaria prevention and treatment in some communities across Nigeria. The study used Social Cognitive Theory to analyse how health communication and community engagement influenced behaviour change. The CLM project used the four Ps of marketing – product, price, place, and promotion - to address gaps in existing interventions that focused on preventing and treating malaria. The results showed that the project empowered communities, leading to improved health systems driven by community members. This integration of marketing and health communication effectively mobilised community action and achieved positive health outcomes. Thus, the research demonstrated the potential of combining marketing strategies with health communication to combat important public health issues such as malaria. Considering the CLM model's success, incorporating marketing principles in health communication was recommended.
Exploring the Power of Images and Videos in Visual Storytelling and Content Marketing: Airtel Ovajara as a Paradigm
Authors: Onyekuru Joyce
Published: October 2024

This study examined the significant power of images and videos in visual storytelling and content marketing using Airtel Ovajara as a paradigm. In today’s digitally saturated landscape, the inability of content marketers to capture attention, convey complex ideas, and build brand authenticity using good images and videos has left some businesses in constant battle for audience/customer acceptability. Employing the Consumer behaviour theory which provided insights into the psychological processes that influence consumer responses to images and videos in visual storytelling, the paper explored the strategic ways in which Airtel Ovajara used images and videos to craft compelling narratives that not only showcased the brand but also fostered genuine connections with customers. The study adopted the mixed research methodology of content analysis and Key Persons Interviews (KPI) to understand the common themes, strategies and elements that position Airtel Ovajara’s visual storytelling as a successful marketing strategy. The use of images and videos as part of this strategy has revolutionized how brands engage with consumers, offering a dynamic way to communicate messages and evoke emotions. The study recommended a valuable insight into the strategic use of visual content to build stronger connections with audiences, demonstrating that effective visual communication was key to contemporary marketing.
Digital twin for healthcare, finance, agriculture, retail, manufacturing, energy, and transportation industry 4.0, 5.0, and society 5.0
Authors: Rane Nitin Liladhar , Shirke Shweta
Published: October 2024

Digital twins, virtual replicas of physical systems, combine real-time data, advanced analytics led by Artificial Intelligence (AI) to improve operations, forecast failure and create new products. Digital twins add value to manufacturing processes using smart automation in the industry 4.0 era and this aids predictive maintenance, real-time monitoring, and integration of Internet of things (IoT) devices. This results in more throughput, less down time and saves a bundle of money. Automation is easing transitions into Industry 5.0, where digital twins will further human-machine collaboration through individualized manufacturing and worker safety. With AI and robotics, digital twins can adaptively learn and interact between users and machines, enabling a high-rate of innovation and customization. If the concept of digital twins can be further broadened to social systems., such as individual people and industrial systems in Society 4.0 becoming part of Society 5.0, this eventually leads to a concept of Society 5.0. Healthcare applications includes digital twins of human patients for personalized medicine and continuous health monitoring and predictive maintenance of health. In addition, digital twins help to improve environmental sustainability by simulating ecosystems and forecasting the effects of global climate change for strategic planning on wildlife conservation. Digital Twins in association with AI, IoT, Big Data analytics catapult the road from Industry 4.0 to Society 5.0 The integration of these systems not just improve industrial productivity, rather it also helps the society to uplift their living standards and contribute to building a sustainable and smart future.
Role of machine learning and deep learning in advancing generative artificial intelligence such as ChatGPT
Authors: Rane Nitin Liladhar , Mallick Suraj Kumar , Kaya Ömer , Rane Jayesh
Published: October 2024

The advancement of machine learning (ML) and deep learning (DL) has greatly accelerated the progress of generative artificial intelligence (GAI) models such as ChatGPT, transforming multiple industries through improved human-machine communication. This study investigates how ML and DL are crucial for the development of GAI, with a specific emphasis on their architectures, methods, and uses that have propelled its advancement. Cutting-edge models, especially transformer-based designs, have shown remarkable abilities in natural language processing (NLP), allowing for the creation of coherent, contextually appropriate, and human-like text. The combination of large quantities of data and advanced algorithms like reinforcement learning and unsupervised learning has improved these models, making them better at comprehending and producing language with incredible precision. Further, the progress in computer speed and the access to vast amounts of data have accelerated the development of GAI, enabling the training of models with billions of parameters. This study outlines the various ways ChatGPT can be used in customer service, content creation, and education, underscoring its ability to enhance human productivity and creativity. It also focuses on the ethical aspects and difficulties related to GAI, such as reducing bias, ensuring transparency, and responsibly deploying AI. This research offers a thorough examination of how ML and DL are influencing generative AI's future through analyzing recent trends and advancements, leading to the development of smarter and more interactive systems.
Impact of ChatGPT and similar generative artificial intelligence on several business sectors: Applications, opportunities, challenges, and future prospects
Authors: Rane Jayesh , Kaya Ömer , Mallick Suraj Kumar , Rane Nitin Liladhar
Published: October 2024

This review highlights the applications, opportunities, challenges, and future prospects of ChatGPT, an AI language model, as it looks at its transformative impact across multiple business sectors. ChatGPT's ability to automate procedures, improve decision-making, and improve customer interactions has led to its widespread adoption in sectors like marketing, customer service, healthcare, finance, and education. ChatGPT simplifies customer service processes by providing round-the-clock assistance and customized solutions. By producing content at scale and analyzing customer sentiment, it has also completely transformed marketing. ChatGPT helps with administrative work and patient management in the healthcare industry. In the finance industry, it improves operations, risk management, and fraud detection. Nevertheless, there are obstacles that businesses must overcome in order to implement ChatGPT. Security, data privacy, and the moral application of AI continue to be major concerns. Other difficulties include the possibility of false information spreading, opaque AI decision-making, and job displacement. Moreover, in order to fully utilize the potential of the technology, businesses must make infrastructure and training investments.
Artificial intelligence and big data analytics for the advancement of industry 4.0, 5.0, and society 5.0
Authors: Rane Nitin Liladhar , Kaya Ömer , Rane Jayesh
Published: October 2024

The tidal wave of data created by connected devices and cyber-physical systems in an Industry 4.0 environment is utilized via advanced analytics to drive manufacturing efficiency, improve predictive maintenance, and empower real-time actions. The potential of big data analytics with artificial intelligence (AI) to transform the industrial landscape lies in its ability to enable the processing of enormous troves of data, revealing hidden patterns and trends that open up a range of avenues to enable industrial operations that are smarter and more responsive. Big data is equally important as moving forward to Industry 5.0. This phase focuses more on human-centric ways and human-machine collaboration matters here. This shift is supported by big data analytics which produces clever intelligence in systems that are complementary to human capabilities. With the analysis of vast pools of data, these systems can augment the way humans decide, create, and solve problems. In Society 5.0, big data analytics is an essential for super-smart society where digital transformation pervades virtually every life. Personalized services in healthcare, education, transportation, urban planning, public safety, sustainable development. It is essential to produce accessible machine learning (ML) tools that can meet the needs of both people and communities, unlocking broader economic benefits as well as enhancing overall quality of life. In a future where the volumes of data collected through the Internet of Things (IoT), introduction of file types that allows more data to be stored for adopting the big data analytics stack to the enterprises applications to provide resiliency and agility in a data driven world.
Machine learning and deep learning: Methods, techniques, applications, challenges, and future research opportunities
Authors: Patil Dimple , Rane Nitin Liladhar , Desai Pravin , Rane Jayesh
Published: October 2024

Machine learning (ML) and deep learning (DL) have significantly transformed various sectors through automation and extracting insights from vast datasets, while recent advancements have highlighted the potential of integrating these technologies for enhanced performance. This research reviews the latest methodologies and hybrid approaches in ML and DL, such as ensemble learning, transfer learning, and novel architectures that blend their capabilities. The synergy between ML's robust decision frameworks and DL's hierarchical feature extraction enables more accurate, efficient, and scalable applications, particularly in fields like natural language processing, computer vision, healthcare, and financial modeling. This review also addresses key challenges in ML and DL, including high computational demands, data privacy, and issues with model interpretability and transparency. It explores the future potential of emerging trends like quantum computing convergence, edge AI for real-time low-power processing, and improvements in hybrid model integration. Ethical considerations in deploying these technologies are emphasized, especially in sensitive fields. Ultimately, this review aims to provide a comprehensive understanding of the current state of ML and DL, offering valuable insights for researchers, practitioners, and policymakers.
Factors Affecting Logistics Performance Metrics in Logistics Industry: Case of Kuehne+Nagel Logistics Company
Authors: Hussein Dima Talaso , Mutoka Felister
Published: October 2024

The purpose of this study was to determine the role of logistics metrics on logistics performance measurement in the Kenyan logistics industry; a case study of Kuehne Nagel logistic company. The specific objectives were to determine the role of logistics cost, logistics quality, logistics productivity, and logistics cycle-time on logistics performance measurement in Kuehne Nagel logistic company. The study was anchored on the SCOR model, resource-based view, theory of constraints and transactions theory. The study adopted a descriptive research design. The study target population was 72 managers comprising of top, middle and supervisory level managers. A census of all the managers was done. The study used questionnaires to collect data. A multivariate regression model was used to link the independent variables with the dependent variable. The study findings indicated that logistics cost and logistics metrics performance are negatively and significantly associated. the results further indicated that logistics quality, logistics productivity and logistics cycle-time had positive and significant association with logistics metrics performance the regression results showed that there is a negatively significant relationship between logistics cost and logistics metrics performance. Further, results indicate that there is positively significant relationship between logistics quality, logistics productivity, logistics cycle-time and logistics metrics performance. Based on the findings, the study concluded that there is negative and significant relationship between logistics cost and logistics metrics performance. Further, the study concluded that there is a positive and significant relationship between quality, productivity, cycle-time and logistics metrics performance. From the findings, the study recommended that logistic companies should find ways of reducing their logistics cost, since it affects their performance; should adopt measures towards improving the quality of their services; should invest in improving their productivity; and lastly logistic firms should adopt efficient time management systems. This will ensure maximum utilization of time as a resource.
Prevalence of anxiety and depression among hirsutism patients in Herat city
Authors: Kakar Ramzia , Joya Shafiq Ahmad
Published: October 2024

Background/Aim: Hirsutism induces mental illnesses such as depression and anxiety, so it is important to know the prevalence of these diseases in societies. The aim of this study was to determine the prevalence of anxiety and depression in patients with hirsutism in Herat city.
Material and methods: One hundred and thirty-eight patients with hirsutism were participated in the study. This study was conducted over one year (from August 1, 2018, to the end of July 2019) in Herat city of Afghanistan. The Ferriman-Gallwey scale is used for diagnosis and determining the severity of hirsutism, the Hospital Anxiety and Depression Scale (HADS) for diagnosis and severity assessment of depression and anxiety, a questionnaire for patients sociodemographic study, and the IBM program SPSS Statistics for analyzing the data.
Results: Anxiety (85 cases (61.5%)) was more prevalent among the study population than depression (73 cases (52.8%)). Anxiety was present in 7 cases (5.0%) of illiterate patients, 41 cases (29.7%) of school level, and 37 cases (26.8%) with higher education levels. Depression was present in 5.0% of illiterate, 23.9% of patients with the school level, and 23.9% of patients with a high level of education.
Conclusion: Despite the high prevalence of depression and anxiety in patients with hirsutism, there was no evidence to suggest a relationship between hirsutism and the high prevalence of depression and anxiety. We recommend further studies on the prevalence of depression and anxiety among the general population in Herat city.
Keywords: Anxiety, Depression, Ferriman-Gallwey scale, Hirsutism, Prevalence
Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language
Authors: Hong Zhuoqiao , Wang Haocheng , Zada Zaid , Gazula Harshvardhan , Turner David , Aubrey Bobbi , Niekerken Leonard , Doyle Werner , Devore Sasha , Dugan Patricia , Friedman Daniel , Devinsky Orrin , Flinker Adeen , Hasson Uri , Nastase Samuel A , Goldstein Ariel
Published: October 2024

Recent research has used large language models (LLMs) to study the neural basis of naturalistic language processing in the human brain. LLMs have rapidly grown in complexity, leading to improved language processing capabilities. However, neuroscience researchers haven’t kept up with the quick progress in LLM development. Here, we utilized several families of transformer-based LLMs to investigate the relationship between model size and their ability to capture linguistic information in the human brain. Crucially, a subset of LLMs were trained on a fixed training set, enabling us to dissociate model size from architecture and training set size. We used electrocorticography (ECoG) to measure neural activity in epilepsy patients while they listened to a 30-minute naturalistic audio story. We fit electrode-wise encoding models using contextual embeddings extracted from each hidden layer of the LLMs to predict word-level neural signals. In line with prior work, we found that larger LLMs better capture the structure of natural language and better predict neural activity. We also found a log-linear relationship where the encoding performance peaks in relatively earlier layers as model size increases. We also observed variations in the best-performing layer across different brain regions, corresponding to an organized language processing hierarchy.
Decoding contextual influences on auditory perception from primary auditory cortex
Authors: Englitz Bernard , Akram Sahar , Elhilali Mounya , Shamma Shihab
Published: October 2024

Perception can be highly dependent on stimulus context, but whether and how sensory areas encode the context remains uncertain. We used an ambiguous auditory stimulus - a tritone pair - to investigate the neural activity associated with a preceding contextual stimulus that strongly influenced the tritone pair’s perception: either as an ascending or a descending step in pitch.We recorded single-unit responses from a population of auditory cortical cells in awake ferrets listening to the tritone pairs preceded by the contextual stimulus. We find that the responses adapt locally to the contextual stimulus, consistent with human MEG recordings from the auditory cortex under the same conditions. Decoding the population responses demonstrates that cells responding to pitch-class-changes are able to predict well the context-sensitive percept of the tritone pairs. Conversely, decoding the individual pitch-class representations and taking their distance in the circular Shepard tone space predicts the
opposite
of the percept. The various percepts can be readily captured and explained by a neural model of cortical activity based on populations of adapting, pitch-class and pitch-class-direction cells, aligned with the neurophysiological responses.Together, these decoding and model results suggest that contextual influences on perception may well be already encoded at the level of the primary sensory cortices, reflecting basic neural response properties commonly found in these areas.
Spatial and temporal coordination of Duox/TrpA1/Dh31 and IMD pathways is required for the efficient elimination of pathogenic bacteria in the intestine of Drosophila larvae
Authors: Tleiss Fatima , Montanari Martina , Milleville Romane , Pierre Olivier , Royet Julien , Osman Dani , Gallet Armel , Kurz C Léopold
Published: October 2024

Multiple gut antimicrobial mechanisms are coordinated in space and time to efficiently fight foodborne pathogens. In
Drosophila melanogaster
, production of reactive oxygen species (ROS) and antimicrobial peptides (AMPs) together with intestinal cell renewal play a key role in eliminating gut microbes. A complementary mechanism would be to isolate and treat pathogenic bacteria while allowing colonization by commensals. Using real-time imaging to follow the fate of ingested bacteria, we demonstrate that while commensal
Lactiplantibacillus plantarum
freely circulate within the intestinal lumen, pathogenic strains such as
Erwinia carotovora
or
Bacillus thuringiensis
, are blocked in the anterior midgut where they are rapidly eliminated by antimicrobial peptides. This sequestration of pathogenic bacteria in the anterior midgut requires the Duox enzyme in enterocytes, and both TrpA1 and Dh31 in enteroendocrine cells. Supplementing larval food with hCGRP, the human homolog of Dh31, is sufficient to block the bacteria, suggesting the existence of a conserved mechanism. While the IMD pathway is essential for eliminating the trapped bacteria, it is dispensable for the blockage. Genetic manipulations impairing bacterial compartmentalization result in abnormal colonization of posterior midgut regions by pathogenic bacteria. Despite a functional IMD pathway, this ectopic colonization leads to bacterial proliferation and larval death, demonstrating the critical role of bacteria anterior sequestration in larval defense. Our study reveals a temporal orchestration during which pathogenic bacteria, but not innocuous, are confined in the anterior part of the midgut in which they are eliminated in an IMD pathway dependent manner.
Mitigating adversarial manipulation in LLMs: a prompt-based approach to counter Jailbreak attacks (Prompt-G)
Authors: Pingua Bhagyajit , Murmu Deepak , Kandpal Meenakshi , Rautaray Jyotirmayee , Mishra Pranati , Barik Rabindra Kumar , Saikia Manob Jyoti
Published: October 2024

Large language models (LLMs) have become transformative tools in areas like text generation, natural language processing, and conversational AI. However, their widespread use introduces security risks, such as jailbreak attacks, which exploit LLM’s vulnerabilities to manipulate outputs or extract sensitive information. Malicious actors can use LLMs to spread misinformation, manipulate public opinion, and promote harmful ideologies, raising ethical concerns. Balancing safety and accuracy require carefully weighing potential risks against benefits. Prompt Guarding (Prompt-G) addresses these challenges by using vector databases and embedding techniques to assess the credibility of generated text, enabling real-time detection and filtering of malicious content. We collected and analyzed a dataset of Self Reminder attacks to identify and mitigate jailbreak attacks, ensuring that the LLM generates safe and accurate responses. In various attack scenarios, Prompt-G significantly reduced jailbreak success rates and effectively identified prompts that caused confusion or distraction in the LLM. Integrating our model with Llama 2 13B chat reduced the attack success rate (ASR) to 2.08%. The source code is available at: https://doi.org/10.5281/zenodo.13501821.
Simulation of Summer Groundnut for Yield and Yield Attributing Traits Using CROPGRO-Peanut Model
Authors: Mote B. M. , Pandey Vyas , Kumar Neeraj
Published: October 2024

Field experiments were carried out at College farm, B. A. College of Agriculture, Anand Agricultural University, Anand. The DSSAT v 4.6 CROPGRO-Peanut model was used to predict the phenology of groundnut crop under combinations of three sowing dates and four groundnut cultivars. The model was calibrated with a 2015 dataset of growth and phenological parameters for estimating the genetic coefficients of all four cultivar and was validated with a 2016 dataset of the same parameters. Result found that the model was able to reasonably simulate the pod yield, kernel yield and haulm yield with per cent error ranging (± 10.06) between observed and simulated value for all cultivars under different sowing dates Simulations of yield and yield attributing characters using the calibrated model were found to be quite accurate.
Mathematical Model for Antimicrobial Resistance Transmission Dynamics in Hospitals
Authors: Oraro Fredrick , Ambogo David , Opiyo Richard
Published: October 2024

In this study, we formulate and analyze a mathematical model to describe the possible transmission routes of Antimicrobial Resistance (A.M.R) in a hospital setting. We have examined the significant means of transmission of resistance in hospitals and found that the significant means of transmission is the use of antibiotics and through the contamination by health care workers. It has been shown that the resistance free equilibrium point is locally asymptotically stable. We have also shown that the model has a unique positive endemic equilibrium point which is locally asymptotically stable.
Agricultural Valorization of Treated Effluent from Korhogo Wastewater Treatment Plant
Authors: Salomon KOUAKOU Yao , Brahima SEYHI , Lucas KONAN N’da
Published: October 2024

Aims: The main objective is to evaluate the effluents of Korhogo’s wastewater treatment plant for irrigation and fertilization in agriculture.
Study Design: Characterization of outlet treated wastewaters has been firstly done. Then their suitability for irrigation has been determined and finally their fertilizing power has been assessed.
Place and Duration of Study: Department of geosciences, Korhogo’s wastewater treatment plant and laboratory. Sampling and analyses were carried out in January 2023, before agricultural field implementation started in February 2023.
Methodology: Firstly, Physico-chemical and microbiological analyses, allowed characterization of outlet treated wastewaters. A determination of their suitability for irrigation was then done through Sodium Adsorption Ratio calculation and water classification with Diagram of Richards. An assessment of their fertilizing capacity was finally carried out using these waters for irrigating and fertilizing crop plots (3x2 m), and consisting of determining firstly their biodegradability index, then their nutrient contents (Nitrogen, Phosphorus and potassium), and the influence of their use on crop development and yield.
Results: The results show that several parameters meet standards for discharge of treated wastewater except total nitrogen, suspended matters and total phosphorus (67.67 mg/l, 271.33 mg/l and 18.30 mg/l). Sodium Adsorption Ratio (SAR) value=3.78 and C3S1 class indicate that these treated effluents can be used for irrigation without salinization risk. As fertilizer, treated effluents brought to crops respectively 603 kg/ha of nitrogen, 162 kg/ha of phosphorus and 99 kg/ha of potassium for maize; and 368.5 kg/ha of nitrogen, 99 kg/ha of phosphorus and 60.5 kg/ha of potassium respectively for Okra. A yield of 12.2 kg of fresh maize and 3.15 kg of fresh okra was obtained for the plot irrigated by treated effluents, compared with 4.80 kg of fresh maize and 0.36 kg of fresh okra for the plot irrigated by well water.
Conclusion: This study has shown that outlet treated wastewater from Korhogo’s wastewater treatment plant is suitable for crops irrigation, contains sufficient nutrients enhancing crops development and yield.
Prevalence of Hepatitis E Virus Infection among Blood Donors in a Tertiary Healthcare Facility in Osun State, Nigeria
Authors: Bejide Ifeoluwa O , Alao Jude O , Komolafe Isaac O
Published: October 2024

Hepatitis E virus (HEV) is currently the most common cause of viral hepatitis in developing countries. While prospective blood donors are routinely screened for HIV, Hepatitis B and C globally in endemic areas, HEV is not included in the protocol, despite the increase in global prevalence of HEV. Till date, only a handful of studies exist on the prevalence of HEV in Nigeria. The aim of this study was to fill this knowledge gap by determining the prevalence of HEV among blood donors at the LAUTECH Teaching Hospital, Osogbo, Osun State, Nigeria. A total of 102 consenting individuals were enrolled into the study between ages 20 and 55. A volume of 5ml blood sample was collected, and the serum harvested, stored at 20°C until ready for analysis. A double antibody sandwich HEV ELISA was performed to analyze the sera in duplicate for HEV antigen, using an ELISA Kit. Of the 102 samples analyzed, 15 (14.7%) tested positive for HEV antigen, confirming the presence of HEV infection among blood donors in the study population.
There was significant association between HEV seropositivity and contact with animals (P=0.010) and alcohol consumption (P=0.000), which means there was a higher chance of donors who consumed alcohol or have had contact with animals to get infected with HEV. However, age, educational status, occupation and gender did not show any statistically significant association with HEV infection. The prevalence of HEV seropositivity was high (14.7%) and a cause for concern as HEV continues to be a major public health issue especially in developing countries.
Effect of Land Configuration and Vermicompost on Hardening Status of Gaillardia pulchella under Micro-climate Conditions
Authors: Ahirwar G.K , Chauhan Somil Singh , Kushwah Bhavya , Kushwah Divya , Verma Diksha , Mukati Deepak , Hammad Shivam , Kushwah Vinayak
Published: October 2024

Gaillardia (Gaillardia pulchella Foug), commonly known as the blanket flower, is a herbaceous perennial renowned for its vibrant, daisy-like flowers. This paper provides a thorough examination of G. pulchella, encompassing its botanical characteristics, hardening configuration, and ecological significance. The present study investigates the impact of land configuration and vermicompost application on the growth metrics of Gaillardia pulchella, and discuss how different configurations affect microclimate conditions and plant acclimatization. By evaluating different land configurations and vermicompost treatments, this research aims to optimize cultivation practices for enhancing the plant’s growth performance, floral quality, and overall yield. The findings provide insights into sustainable agricultural practices for improving the productivity and aesthetic value of G. pulchella. The present results suggest that the flat, ridge and furrow and raised bed configuration, particularly with 75% vermicompost with (33.53, 34.44 and 42.70) is optimal for cultivating Gaillardia flowers. However, minimum plant height was observed under the control plot (24.56, 17.77 and 31.72) cm for all three bed types. The maximum number of leaves count treatment were maximum (83.40, 81.46 and 99.26) with 50% vermicompost under flat, ridge and furrow and raised bed configuration. Number of new shoots per plant at hardening was found maximum (8.66, 9.33 and 9.23) under 50% vermicompost. Moreover, the survival percentage (%) were also found maximum (83.40, 81.46 and 99.26) under 50% vermicompost. It may be concluded that by assessing different land configurations and vermicompost treatments which influences the hardening process characterized by plant acclimatization to environmental stress which ultimate the research aims to enhance the resilience and establishment of G. pulchella in controlled environments.
Perilaku Laju Keausan dan Kekerasan Komposit Epoksi yang Diperkuat dengan Serat Gelas dan Partikel Bambu
Authors: Sunardi Sunardi , Hamdi Shafnur , Saefuloh Iman , Sudrajad Agung , Ula Shofiatul , Fawaid Moh.
Published: October 2024

Penggunaan material organik dalam komposit mengalami perkembangan yang sangat menarik. Kondisi ini tidak dapat dipisahkan dari semakin menguatnya isu lingkungan. Pembatasan penggunaan bahan-bahan yang dapat mencemari lingkungan harus dilakukan untuk menjaga itu keberlanjutan. Partikel yang dilepaskan dari komposit, sebagai debris keausan harus aman untuk kesehatan dan lingkungan. Kontribusi penelitian ini adalah eksplorasi material ramah lingkungan untuk aplikasi kampas rem di bidang otomotif. Penelitian ini menggunakan partikel bambu dan seng sebagai filler, serat kaca sebagai penguat komposit, dan epoksi sebagai matriks yang mengikat semua itu gabungan material. Pembuatan sampel dilakukan dengan menggunakan kompaksi dingin dengan tekanan yang berbeda-beda, yaitu 20, 30, dan 40 MPa. Proses selanjutnya adalah curing dengan memanaskan sampel di dalam oven listrik pada suhu 150 °C selama 1 jam. Hasil ekperimen menunjukkan bahwa kompaksi memiliki pengaruh signifikan terhadap performa komposit yang dihasilkan. Pada tekanan kompaksi 20 MPa menghasilkan densitas 1,58 g/cm3, kekerasan 15,30 BHN, dan laju keausan 6,16 x 10-6 g/mm2.s. Pada tekanan kompaksi 30 MPa menghasilkan densitas 1,62 g/cm3, kekerasan 16,33 BHN, dan laju keausan 5,66 x 10-6 g/mm2.s, sedangkan pada tekanan kompaksi 40 MPa memiliki densitas, kekerasan dan laju keausan masing-masing adalah 1,66 g/cm3, 17,67 BHN, dan 5,48 x 10-6 g/mm2.s. Densitas, kekerasan, dan ketahanan aus material mengalami peningkatan seiring dengan tekanan kompaksi pada saat proses manufaktur.
Empreendedorismo Coletivo: O Desenvolvimento Local Promovido Pelo Cooperativismo Feminino
Authors: Guimarães Amanda Rebeca Monteiro , Fontão Bruna Guimarães , Filho Wlademir Leite Correia , Maduro Márcia Ribeiro , Lima Orlem Pinheiro De
Published: October 2024

O empreendedorismo feminino é uma força crescente em todo o mundo, contribuindo significativamente para o desenvolvimento econômico e social. Este artigo destacou a importância do empoderamento feminino por meio do empreendedorismo, evidenciando como as mulheres assumiram papéis de liderança e criaram impacto em diversas áreas, por intermédio do cooperativismo, um modelo que enfatiza a colaboração, a igualdade e a solidariedade, oferecendo às mulheres uma ataforma para unir forças, compartilhar recursos e conhecimentos, e alcançar objetivos comuns. Ao se envolverem em cooperativas, as mulheres não apenas fortaleceram suas próprias capacidades empreendedoras, mas também contribuíram para o desenvolvimento sustentável de suas comunidades. Por meio de pesquisas bibliográficas e apresentação de gráficos e informações quantitativas, ex orou-se como o cooperativismo pode am ificar o impacto do empreendedorismo feminino, proporcionando um ambiente propício para o crescimento pessoal e profissional das mulheres, ao mesmo tempo em que promoveu a equidade de gênero e o progresso socioeconômico