bluuebunny/crossref_metadata_2025 huggingface dataset:
Analisis Keadilan Substantif dalam Putusan Kasasi Terkait Tindak Pidana Kehutanan
Authors: Desi Optapia  , Dona Raisa Monica  , Fristia Berdian Tamza
Published: February 2025

Forests play an important role in supporting the lives of Indonesian and even international communities. However, the problem of forestry crimes today is a fairly complicated problem to overcome. This is due to, among other things, the lack of regional boundaries, low intensity and effectiveness of patrol/supervision, very limited and unprofessional forest security personnel and facilities, weak coordination among law enforcement officers, weak law enforcement against violators and the lack of perception from community members themselves of the importance of forest resources for all mankind. Supreme Court Decision Number 121 K/PID.SUS-LH/2024 is the focus of this study, because it highlights the challenges and complexities in law enforcement against perpetrators of forestry crimes. In this regard, there are problems related to legal uncertainty, differences in legal interpretation, and the complexity of cases that influence judges' decisions at the cassation level. The problem in this study is how is the basis for the judge's considerations in sentencing perpetrators of forestry crimes and whether the decisions given are in accordance with the principles of substantive justice. This research method is carried out using a normative juridical approach and an empirical juridical approach. The data used are primary data and secondary data. The data collection procedure in writing this research is by means of literature and field studies. Data analysis uses qualitative analysis.
Analisis Tindak Tutur Ilokusi Video “Sex Education” pada Saluran YouTube Neuron
Authors: Savira Nailil Hana  , Rizna Asticka  , Noufal Azmi Widianto  , Esti Maurilla  , Firas Abid Zidan  , Asep Purwo Yudi Utomo  , Amilia Buana Dewi Islamy  , Rina Rina
Published: February 2025

Humans as social creatures need language as a communication tool to share thoughts, feelings, and information. Language is a complex social phenomenon that is influenced by culture and social context. Pragmatics, which is a branch of linguistics that studies meaning in context, focuses on speech acts as a basic element in communication. This study aims to analyze the illocutionary speech acts (directive, expressive, commissive, declarative, and representative) that often appear on Neuron's YouTube channel, especially on playlists related to sex education. This research uses descriptive qualitative method and pragmatics theoretical approach, and collects data through literature study by referring to various scientific literatures relevant to the topic discussed. The focus of the study is to analyze the illocutionary speech acts in sex education videos on Neuron's YouTube channel, which discuss important issues such as HIV/AIDS, contraception, and transgender. Of the six videos in the “Sex Education” playlist analyzed, 91 illocutionary speech acts were found, consisting of 28 directive speech acts, 8 expressive speech acts, 11 commissive speech acts, 15 declarative speech acts, and 29 representational speech acts. This research is expected to provide insight into the use of illocutionary speech acts in Neuron's YouTube channel playlist and help viewers understand the messages conveyed in these sex education videos.
Edukasi dengan Pendekatan Self-Directed Learning untuk Meningkatkan Pengetahuan dan Keterampilan Diabetesi dalam Pencegahan Ulkus Diabetikum
Authors: Ainul Yaqin Salam  , Ana Fitria Nusantara
Published: February 2025

Diabetes mellitus (DM) can cause serious complications, including impaired peripheral tissue perfusion that risks diabetic ulcers and amputation. The Self-Directed Learning (SDL) approach is an effective self-education strategy in improving the understanding and skills of DM patients in preventing these complications. This community service program aims to improve the understanding and skills of lower extremity care in DM patients through education and hands-on training. Activities include counseling, foot self-examination, and proper foot care practices. Evaluation results showed significant improvement in participants' understanding of diabetic ulcer prevention, awareness in maintaining blood sugar levels, and selection of appropriate footwear. In addition, skills in foot self-examination, proper nail trimming, and moisturizer application also improved. The SDL approach proved effective in increasing participants' engagement in the learning process, so they were more motivated to apply the knowledge gained in their daily lives. This program indicates that SDL-based education can be an effective strategy in improving the foot health of people with DM and preventing serious complications.
Recipient Feasibility Decision Support System Micro Small Medium Business Assistance Use Method Analytic Hierarchy Process and Simple Additives Weighting
Authors: Abdullah Dahlan , Erliana Cut Ita , Bintoro Andik , Hartono Hartono , Ikhwani Muhammad , Nazaruddin Nazaruddin
Published: February 2025

Study This aims To determine the eligibility of MSME assistance recipients with the method AHP (Analytic Hierarchy Process) And SAW (Simple Additives weighting). The AHP method is used to determine the weight of each criterion. Meanwhile, SAW is used To determine the rank selection of beneficiaries. This is very important for Indonesia's economy during the crisis, Where MSME's own Power stands to face a crisis economy. Criteria used in a way This uses six measures: type of business, Amount of power Work, turnover per month, amount of assets, sector MSME, And sector business. Decision support systems are designed to support someone who must make certain decisions. That is, interactive, Flexible, Data quality, and Expert Procedure. Study System Supporters Decision Appropriateness Recipient Help Business Micro Community Use Analytic Hierarchy Process (AHP) and Simple Additive Methods weighting (SAW), Study This done in Subdistrict Intersection Three Regency Pidie Aceh Province to facilitate the Selection of Eligibility of Government Assistance Recipients For Build a business Micro Society. Testing is done in this study, namely black box testing. Results Testing black box shows that the system can walk with Good by function, with results calculation method AHP and results calculation method SAW in determining eligibility selection MSME aid recipients. The results of the level of accuracy testing on the AHP and SAW methods with six criteria and alternatives the requirements is 75%.
GLCM and PSNR Analysis of Woven Fabric Images Made from Natural Dyes Due to Sunlight Exposure
Authors: Batarius Patrisius , Santoso Albertus Joko , Sinlae Alfry Aristo Jansen
Published: February 2025

Traditional woven fabrics generally use natural dyes that come from the local area. Natural dyes are often considered low quality if exposed to sunlight. This study aims to analyze the effect of sunlight on the image of woven fabrics made from natural dyes. The natural dyes used come from noni (Morinda citrofolia L), which produces a red color; Tarum (Indigofera tinctoria L), which produces a blue-black color; and corn starch juice, which produces a white color. A thread made of cotton is dipped and cooked to produce the desired color. The analysis is done by comparing the value of GLCM (Grey Lever Co-Coruent Matrix) features, changes in the value of Mean Square Error (MSE), and Peak Signal Noise Ratio (PSNR) with the original image. The original image is taken before the woven fabric is dried in the sun. The changing image is taken after the woven fabric is dried in the sun with variations in drying times. The drying time of woven fabric is 1 hour. Sun drying starts from 09:00 to 14:00. The distance between the original and sun-dried images is 30 cm. The original image and the sun-dried image went through cropping and resizing the image to be the same size. The grayscale image type is used for the GLCM, MSE, and PSNR comparison process. The image size used is 128x128 for woven fabric images with three kinds of colors (white, red, and blue) and 256x256 pixels for images with white color. The results showed that the quality of the images produced at drying hours of 09.00-10.00 to 14.00-15.00 tended to be low, with a significant difference between the original image and the changed image. The lowest point of quality lies in the drying time of 12.00-13.00 and 13.00-14.00. For the GLCM features, the sun-dried image at 14.00-15.00 has a homogeneity value close to the original value. For contrast features, the image dried at 10.00-11.00 has a contrast value that is close to the original image contrast value. This shows the smaller the difference in pixel intensity in the image.
Enhancement of Secure Hospital Healthcare Monitoring System Based–Software Defined Network (SDN) with Machine Learning
Authors: Ahmed Sarah Shihab , Shakir Huda Rashid
Published: February 2025

Handling delicate and crucial knowledge by healthcare providers requires security measures to prevent unapproved use. Software-defined networks (SDNs) are extensively used in medical facilities to ensure resource efficiency, security, and superior network management and management. Despite these advantages, SDNs present a significant threat from various assaults due to the sensitivity  of patient information. Our work's primary goal is to propose a global connection between SDN technology and machine learning-based assaults in healthcare. This paper aims to draw attention to a few relevant options. Additionally, we give a framework using software-defined network principles that illustrate linkages between a collection of people, each of whom has a Nano network residing within their bodies, and medical providers via the local network of a medical center. In health care, the initiative is sometimes called an issue of machine learning assault systems and amenities. The current possibilities for machine learning cyberattacks on the medical industry are quite promising. It is also highly well-liked because of its capacity to identify and assess. From a single instrument to the enormous amounts of data gathered, this evolution radically changes how we approach medicine. This work uses a range of ML approaches and attacks to test MLCAH (Machine Learning-based Cyber Attacks Healthcare). For every combination of machine learning methods and assaults, an efficiency assessment highlights the benefits and drawbacks of different algorithms for defending against a specific assault.
Implementation of Word Trends Using a Machine Learning Approach with TF-IDF and Latent Dirichlet Allocation
Authors: Rifaldi Dianda , Fadlil Abdul , Herman -
Published: February 2025

In today's technological age, the prevalence of social media has become ubiquitous, facilitating the easy dissemination of information and communication. This has led to the uploading of various content, including opinions on mental health, particularly in Indonesia. Mental health refers to an individual's emotional, psychological, and social well-being, commonly affecting individuals from adolescence to adulthood. This research utilized Twitter data on mental health issues gathered from October to November 2022, employing TF-IDF and Latent Dirichlet Allocation (LDA) to conduct topic modeling for word trend analysis based on user-generated content. The sentiment analysis concept was used to label text as either negative or positive sentiment. Subsequently, TF-IDF weighed the word frequency in the documents/tweets, categorizing the data based on the resulting sentiments. Manual labeling ensured accuracy, avoiding potential errors from libraries provided in the Indonesian language. Employing these two topic modeling techniques, conclusions were drawn for each concept, aiming to identify word trends, mainly focusing on mental health discourse within Twitter user-generated content. Results indicated the synchronicity of the keyword 'mental health' with word trends generated by LDA. At the same time, TF-IDF produced word trends based on positive and negative labels, revealing commonly used terms by Twitter users to express these concerns. Furthermore, subsequent research can be experimented by comparing topic modeling techniques using Latent Semantic Allocation (LSA), Probabilistic Latent Semantic Analysis (pLSA), and Hierarchical Dirichlet Process (HDP), where LSA and pLSA present approaches closely aligned with LDA.
A Thorough Review of Vehicle Detection and Distance Estimation Using Deep Learning in Autonomous Cars
Authors: Rahmat Muhammad Abdillah , Indrabayu Indrabayu , Achmad Andani , Salam Andi Ejah Umraeni
Published: February 2025

Autonomous vehicle technologies are rapidly advancing, and one key factor contributing to this progress is the enhanced precision in vehicle detection and distance calculation. Deep Learning Networks (DLNs) have emerged as powerful tools to address this challenge, offering remarkable capabilities in accurately detecting and estimating vehicle positions. This study comprehensively reviews DLN applications for vehicle detection and distance estimation. It examines prominent DLN models such as YOLO, R-CNN, and SSD, evaluating their performance on widely used datasets such as KITTI, PASCAL VOC, and COCO. Analysis results indicate that YOLOv5, developed by Farid et al. achieves the highest accuracy level with a mAP (mean Average Precision) of 99.92%. Yang et al. showcased that YOLOv5 performs exceptionally in detection and distance estimation tasks, with a mAP of 96.4% and a low mean relative error (MRE) of 10.81% for distance estimation. These achievements highlight the potential of DLNs to enhance the accuracy and reliability of vehicle detection systems in autonomous vehicles. The study also emphasizes the importance of backbone architectures like DarkNet 53 and ResNet in determining model efficiency. The choice of the appropriate model depends on the specific task requirements, with some models prioritizing real-time detection and others prioritizing accuracy. In conclusion, developing DLN-based methods is crucial in advancing autonomous vehicle technology. Research and development remain crucial in ensuring road safety and efficiency as autonomous vehicles become more common in transportation systems.
2.5D Face Recognition System using EfficientNet with Various Optimizers
Authors: Teo Min-Er , Chong Lee-Ying , Chong Siew-Chin , Goh Pey-Yun
Published: February 2025

Face recognition has emerged as the most common biometric technique for checking a person's authenticity in various applications. The depth characteristic that exists in 2.5D data, also known as depth image, is utilized by the 2.5D facial recognition algorithm to supply additional details, strengthening the system's precision and durability. A deep learning approach-based 2.5D facial recognition system is proposed in this research. The accuracy of 2.5D face recognition could be enhanced by integrating depth data with deep learning approaches. Besides, optimizers in the deep learning approach act as a function for adjusting the properties, like learning rates and weights in the neural network, which can minimize the overall loss of the system and further enhance performance. In this paper, several experiments have been conducted in two versions of EfficientNet architectures, such as EfficientNetB1 and EfficientNetB4, using different optimizers, including Adam, Nadam, Adamax, RMSProp, etc. Various optimizers are compared to find the most suitable optimizer for the system. The Face Recognition Grand Challenge version 2 (FRGC v2.0) database was utilized in this research. This research aims to increase the 2.5D face recognition system’s effectiveness and efficiency by implementing deep learning approaches. Based on the experimental result, a deep learning algorithm enhances the system's accuracy rate. It also proves that the EffifientNetB4, using Adam optimizer, gained the highest accuracy rate at 97.93%.
Deep Learning-based Utility Pole Safety Assessment from Visual Data
Authors: Abbas M. Elsayed Mohamed , Hashim Noramiza , Abdul Rahman Abdul Aziz , Alhayek Mohamed
Published: February 2025

Utility poles are crucial infrastructure components, and efficiently assessing the safety of these structures and ensuring they adhere to the clearance guidelines, which specify the minimum distance between the pole and any surrounding objects, remains a challenge; the current manual inspection process is time-consuming, costly, and often subjective. This work proposes an automated deep learning-inspired solution to improve utility pole detection and measure the clearance distance. The biggest challenge was the lack of a comprehensive pole dataset; therefore, we collected a dataset containing utility poles in varied backgrounds, environments, and conditions. We compared data augmentation techniques and employed them to address the limited dataset size. The proposed approach consists of two main stages: pole detection and differentiation and pole distance measurement. The first stage is a comparison of multiple object detection models on our utility pole dataset; we used the results from the best-performing model to estimate the distance between the two pole objects. The results show that our pipeline with the YOLOv8 model outperforms SSD and achieves 83% accuracy in classifying pole compliance. The system can accurately detect and estimate clearance violations even with limited data. The success of the pipeline opens opportunities for future research; obtaining depth by using additional sensors or deep learning models could enhance the detection module. Scaling the approach to large utility pole networks while retaining real-time performance could lead to improved autonomous infrastructure maintenance.
A Model for Enhancing Pattern Recognition in Clinical Narrative Datasets through Text-Based Feature Selection and SHAP Technique
Authors: Dalhatu Sirajo Muhammad , Azmi Murad Masrah Azrifah
Published: February 2025

Clinical narratives contain crucial patient information for predicting cardiac failure. Accurate and timely cardiac failure recognition (CFR) significantly impacts patient outcomes but faces challenges like limited dataset sizes, feature space sparsity, and underutilization of vital sign data. This study addresses these issues by developing a methodology to improve CFR accuracy and interpretability within clinical narratives. Four datasets—the Framingham Heart Study, Heart Disease from Kaggle, Cleveland Heart Disease, and Heart Failure Clinical Records—undergo preprocessing, including handling missing values, removing duplicates, scaling, encoding categorical variables, and transforming unstructured data using natural language processing (NLP). Various feature selection methods (Chi-Squared, Forward Selection, L1 Regularization) are used to identify influential features for CFR, and the SHapley Additive exPlanations (SHAP) technique is integrated to improve interpretability. Support Vector Machine (SVM), Logistic Regression (LR), and Random Forest (RF) models are trained and evaluated. Performance was evaluated using accuracy, precision, recall, f1-score, and area under the receiver operating characteristic curve (AUC-ROC). Results indicate that L1 Regularization with LR and Chi-Squared with RF perform best for specific datasets. The final model, combining all datasets with Forward Selection and RF, achieves high accuracy (91%), precision (87%), recall (97%), f1-score (91%), and AUC-ROC (94%). This study concludes that advanced text-based feature selection and SHAP interpretability significantly enhance CFR model accuracy and transparency, aiding clinical decision-making. Future research should incorporate more diverse datasets, explore advanced NLP techniques, and validate models in various clinical settings to enhance robustness and applicability.
Evaluating Law Enforcement Efficiency in Incestuous Rape Cases: A Systematic Literature Review Using Data Envelopment Analysis
Authors:   University of Southeastern Philippines, Lerios Hamlet
Published: February 2025

This systematic literature review evaluates the efficiency of law enforcement agencies in managing incestuous rape cases, employing Data Envelopment Analysis (DEA) as a methodological framework. Incestuous rape, a profound violation of individual autonomy and familial trust, remains significantly underreported and poses unique challenges for law enforcement due to its sensitive nature. The review synthesizes findings from 43 studies published since 2015, focusing on resource allocation, case management practices, and judicial outcomes. Key themes identified include police efficiency and performance, sexual assault case management, investigation of incest and child abuse, police perceptions of victim credibility, collaboration and resource allocation, and legal and policy frameworks. The findings reveal systemic inefficiencies, including biases in victim credibility assessments and inadequate resource allocation, which hinder effective case resolution. The review underscores the necessity for law enforcement agencies to adopt victim-centered approaches, enhance training, and foster collaboration with external agencies to improve outcomes for victims of incestuous rape. Ultimately, this research aims to contribute to the discourse on enhancing law enforcement responses to sexual violence, advocating for evidence-based recommendations to optimize practices and policies in this critical area.
The Role of AI and Automation in Revolutionizing the Modern Medical Environment: A Systematic Review
Authors: Asiri Hanan Mofareh Ahmed , Al Muhmal Mofareh Hassan Mohammed , Asiri Sara Mofareh Ahmed , Jali Asim Mohammed Ali , Assiri Tahani Ahmed Mohammed , Al Murayh Hussain Ali Saleh , Algamsh Abdullah Hussain , abutaleb Ohood Mohammed Yahya
Published: February 2025

Background: The integration of Artificial Intelligence (AI) and automation in healthcare has emerged as a transformative force, reshaping the modern medical environment. These technologies promise to enhance operational efficiency, improve diagnostic accuracy, and optimize patient care. However, their adoption also raises ethical, technical, and operational challenges. Objective: This systematic review aims to explore the impact of AI and automation on the healthcare sector, focusing on their applications, benefits, challenges, and future potential. Methods: A systematic search was conducted across major databases, including PubMed, Scopus, and Web of Science, to identify peer-reviewed studies published between 2016 and 2024. Studies were selected based on their relevance to AI and automation in medical environments, using predefined inclusion and exclusion criteria. Data were extracted and analyzed to identify key themes. Results: The review identified significant advancements in AI-driven diagnostics, robotic-assisted surgeries, workflow automation, and predictive analytics. These technologies have demonstrated measurable improvements in clinical outcomes, operational efficiency, and cost reduction. However, challenges such as data privacy, ethical concerns, and integration issues persist. Conclusion: AI and automation are revolutionizing healthcare by streamlining processes, enhancing patient outcomes, and addressing resource limitations. Despite current challenges, their potential to transform the medical environment is undeniable. Further research and multidisciplinary collaboration are essential to overcome barriers and fully harness these technologies.
Enhancing Critical Thinking Skills: Exploring Generative AI-enabled Cognitive Offload Instruction in English Essay Writing
Authors: Hong Hui , Viriyavejakul Chantana , Vate-U-Lan Poonsri
Published: February 2025

This study explores the integration of Generative AI technology for cognitive offloading in the context of English essay writing, with the aim of promoting inclusive and equitable quality education. Focusing on how AI-assisted cognitive offload instruction enhances students' critical thinking skills, the research adopts a quantitative approach, collecting data from 240 first-year English majors across four colleges through purposive sampling. Statistical analysis reveals that the implementation of Generative AI-enabled Cognitive Offload instruction significantly improves students' critical thinking skills in essay writing. This instructional strategies and specific practices fosters the development of analytical thinking, problem-solving, and effective communication, creating an educational environment that supports originality, critical thought, and responsible writing practices. The findings contribute to the growing body of literature on the role of AI in educational settings, highlighting the potential of AI-assisted cognitive offloading to advance critical thinking and writing skills through structured instructional design.
Enhancing Cultural Value Propagation in Lanna Artisan Patterning through Educational Intervention in Northern Thailand
Authors: Suwanreang Chanankarn , thongsuk Jessada , Jun-on Nipa
Published: February 2025

Lanna craftsmanship, renowned for its intricate patterns and deep cultural significance, faces challenges due to globalization, urbanization, and declining interest among younger generations. This research explores how intervening Lanna artisan techniques into extra-curricular activities in secondary school influences students' skill development in traditional craftsmanship, enhances their sense of cultural belonging, and fosters the creation of culturally authentic and innovative product designs. This participatory action research (PAR) involved collaboration between three local artisans as experts, 12 educators, and 25 students from four schools to develop and implement a culturally responsive intervention. The results showed changes in students' patterning skills, cultural belonging awareness, and product design outcomes. These changes developed different enhancements of students' cultural propagation, including transformation in their perceptions of cultural arts, expansion of their cultural literacy, development of their responsibility and commitment to cultural preservation, and renovation of cultural sustainability and community impact.
会计师事务所在企业破产管理中的定位及相关财税处理案例研究
Authors: 李丹丹  , 王剑  , 罗元元
Published: February 2025

李丹丹，王剑，罗元元
湖北注协行业课题组，湖北华仁致远会计师事务所（普通合伙），湖北襄阳
摘要：2007年6月1日，《中华人民共和国企业破产法》正式实施。依据该法规定，破产管理人由人民法院指定。在当前经济下行与疫情影响的双重背景下，企业破产现象日益增多，会计师事务所在企业破产管理中的重要性愈发凸显。根据法律规定，管理人可以由有关部门、机构的人员组成的清算组，或者依法设立的律师事务所、会计师事务所、破产清算事务所等社会中介机构担任。随着营商环境的不断优化以及破产制度的逐步健全，破产事务也越来越多。会计师事务所作为提供破产管理和财税服务的专业机构，对其定位进行深入研究梳理显得尤为必要。此外，本文还结合案例对破产管理环节的财税处理展开研究，旨在为会计师事务所从事破产清算财税工作提供参考，从而更好地发挥破产重整在化解企业债务危机、优化资源配置以及维护社会稳定中的积极作用。
中国数字普惠金融时空格局动态演化及驱动力分析
Authors: 金莹  , 王征兵
Published: February 2025

金莹1,2，王征兵1,*
1.西北农林科技大学经济管理学院，陕西杨凌；
2.甘肃农业大学财经学院，甘肃兰州
摘要：基于2011—2020年全国大陆31个省域层面数字普惠金融发展指数，运用探索性空间数据分析法、Kernel密度估计、趋势面和地理加权回归（GWR）模型，探究中国数字普惠金融的时空格局、演进趋势及驱动因素。研究发现：①中国省域数字普惠金融发展整体存在明显的空间集聚性，在增速方面表现为“西部较快、中东部缓慢”的态势；②省域间数字普惠金融具有显著的空间自相关性，聚类方式以低低、高高集聚区为主；③东、中、西部整体差异较大，长期趋于稳态收敛发展；④数字普惠金融的发展离不开经济发展水平、传统金融发展水平、第三产业发展水平、政府干预程度、互联网发展水平、收入水平、人口密度和受教育水平等因素的影响，但影响方向和程度在不同年份、不同区域差异性明显。最后，依据实证结论提出相关政策启示，以期促进各地区数字普惠金融的协同发展。
新质生产力赋能县域发展的对策研究——以衢州龙游县为例
Authors: 刘畅  , 毕书磊
Published: February 2025

刘畅1，毕书磊2,*
1. 衢州职业技术学院，中国衢州；
2. 布达佩斯经济大学，匈牙利布达佩斯
摘要：在大力发展新质生产力的背景下，本文探讨了龙游县域经济发展中新质生产力的内在逻辑与对策建议。通过分析新质生产力对龙游县域经济的重要性，文章提出了加大科技创新投入、推动产业转型升级、强化人才支撑等对策建议。同时，文章还强调了文化传承与创新、绿色发展在县域可持续发展中的关键作用。龙游县的新质生产力发展实践为县域经济转型升级和可持续发展提供了宝贵经验和启示。
基于区块链技术的畜禽育种产学研协同机制研究
Authors: 姜梦琪  , 冯晓春  , 冯晓春  , 乔迪  , 王天宇  , 阮俊虎
Published: February 2025

姜梦琪，冯晓春，乔迪，王天宇，阮俊虎*
西北农林科技大学经济管理学院，陕西咸阳
摘要：在当前畜禽种业发展取得显著成绩但仍面临技术创新“卡脖子”问题的背景下，本文深度剖析了畜禽育种产学研协同模式存在的问题，特别是企业与高校、科研院所之间合作松散、信息交流不充分的问题。针对这些问题，本文进而提出了基于区块链技术的创新解决方案。该方案的核心在于构建一个信息共享平台，旨在打破信息壁垒，促进育种企业、高校和科研院所之间的深度合作与交流。具体而言，该方案通过利用区块链的去中心化、去信任、可溯源和防篡改等特性，有效解决当前产学研协同模式中的信息壁垒、互信困难以及知识产权保护这三个主要问题，最终实现了畜禽育种市场需求与科研成果的有效对接，加速了畜禽育种科研成果的转化，并为区块链在农业领域的其他应用提供了参考。
Ziemie nadnarwiańskie w planach operacyjnych Polski i Niemiec w roku 1939
Authors: Rzepniewski Andrzej
Published: February 2025

Obchodzona w roku 1989 50 rocznica września skierowała myśl Polaków — zwłaszcza najstarszego pokolenia — ku tej katastrofie naszych nowożytnych dziejów, w wyniku której utraciliśmy odzyskaną niespełna 21 lat wcześniej niepodległość. Również ziemie nadnarwiańskie, wzdłuż których rozwinął się nasz front północny — podzieliły los całego państwa. W zależności od położenia operacyjnego niektóre powiaty, niektóre miasta ucierpiały mocno zarówno w wyniku walk naziemnych, jak i barbarzyńskich nalotów powietrznych, pozostałe zaś, położone na uboczu kierunków uderzeń Wehrmachtu — przetrwały wojnę wrześniową w nieco lepszym stanie. Wszystko zależało od ich roli w planach operacyjnych obu stron, zwłaszcza w planie „Fali Weiss". Od niego zatem wypadnie rozpocząć naszą analizę.
Wspomnienia wojenne 1939 roku
Authors: Ciszewski Henryk
Published: February 2025

W 1938 roku nastąpiła reorganizacja wojska w Wojciechowicach. 5 Pułk Ułanów Zasławskich pozostał bez zmian, natomiast 12 Dywizjon Artylerii Konnej im. Józefa Bema, który mieścił się tam, gdzie obecnie znajdują się Ostołęckie Zakłady Celulozowo-Papiernicze, częściowo został przeniesiony do Białegostoku.
5 Pułk Ułanów Zasławskich w walkach o niepodległość
Authors: Kruszewski Tadeusz
Published: February 2025

5 pułk ułanów był jednym z pierwszych oddziałów, które zaczęły się formować w niepodległej Polsce w pamiętnych dniach listopadowych. Oficerowie pułku, na czele z ppłk. Sochaczewskim, wyrwawszy się z twierdzy w Brześciu nad Bugiem natychmiast pośpieszyli do Warszawy. Dnia 13 listopada 1918 r. ppłk Sochaczewski zameldował się u Komendanta Piłsudskiego, a już 14 listopada, na mocy rozkazu szefa sztabu generalnego, rozpoczął formowanie 5 pułku ułanów z miejscem postoju w Mińsku Mazowieckim. W Mińsku znajdował się szwadron kawalerii polskiej tzw. „Polskiego Wehrmachtu", zorganizowany jeszcze przez Niemców. Oficerowie tego szwadronu, pochodzący z 2 pułku ułanów II Brygady Legionów, zostali wcieleni do organizującego się 5 pułku.
 
Skan artykułu udostępniony z zasobów prowadzonego przez Muzeum Historii Polski repozytorium BazHum.
Ostrołęczanie okresu II Rzeczypospolitej
Authors: Parzych Czesław
Published: February 2025

W dziejach Ostrołęki, jak i każdego miasta, najważniejszą rolę zawsze odgrywali ludzie. Ich aktywność, zdolność i pasja działania tworzyły oblicze i klimat miasta, nadawały barwę i kształt wielu różnym dziedzinom życia.
Zapis jest próbą przypomnienia niektórych z grona ostrołęczan, ocalenia ich od niepamięci. Szczupłość miejsca zmusza mnie do pominięcia wielu zasłużonych rodaków, którzy na pamięć zasługują.
HAIR & SCALP DISORDERS BOOK ONE
Authors:   EUROPEAN WELLNESS ACADEMY, Chan Mike , Alvin Glen , Sison Antonio , Jamora Maria Jasmin
Published: February 2025

This textbook of trichology is a valuable resource for all students, from undergraduate to postgraduate, as well as clinicians. It is comprehensive in its coverage of hair physiology and diseases, with illustrations and pictures to make reading it an enjoyable experience. This textbook fulfils the requirements of medical students with basic science issues. At the same time, clinicians will find it an ideal companion as its content is concise and easy to refer to, while postgraduate students will thrive on its up-to-date data and facts from hair and scalp research. The clinical chapters cover all common and rare diseases in all age groups. The book incorporates various therapeutic modalities, including integrative medicine, cell therapy psychotherapy, and conventional medicine. The chapters are written in a simplified, crisp, practical, and user-friendly style, with many illustrations and classical photographs exhibiting features of selected diseases.
Interest in trichology is developing rapidly, with many doctors and aestheticians establishing exclusive trichology clinics. The volume of patients concerned with hair condition and appearance is ever-increasing. The interest and enthusiasm in this subject continue to grow substantially. Therefore, all dermatology and aesthetic medicine stakeholders must furnish and update themselves in the field of hair and hair diseases. Renowned authors with expertise in trichology have shared their knowledge and experience to make this book a success.
Internal Communication Patterns in Improving Employee Performance in Macro Planning
Authors: Howay Fenelon , Zulaikha Zulaikha , Abror Dhimam
Published: February 2025

This study aims to analyze the communication patterns applied in the Macro Planning Division of BAPPERIDA, West Papua Province to improve the effectiveness of internal communication. This study uses a descriptive qualitative approach that focuses on understanding employee behavior, perceptions, and motivations in the context of the organization. The subjects of the study consisted of employees in the Macro Planning Division of BAPPERIDA who were selected through purposive sampling based on their competencies and roles. Data collection was carried out through in-depth interviews, direct observation, and documentation studies. The results of the study indicate that internal communication in the Macro Planning Division of BAPPERIDA is running well, which is reflected in the improvement of work quality, punctuality, initiative, ability, and smooth interaction between leaders and staff. Employees have completed planning tasks, such as RKPD, RAP, and RPJMD, although there are some minor obstacles faced. Supporting factors for employee performance include discipline, understanding of tasks, and punctuality in completing work. In addition, the leadership communication approach that emphasizes good coordination and active problem-solving also facilitates task completion. This study concludes that effective communication is an important factor in achieving organizational success, with no significant obstacles found thanks to established internal communication practices. These findings underscore the importance of effective communication in optimizing organizational performance, increasing employee productivity, and creating more solid working relationships within the organization.
MODEL BISNIS TOKO JAMU KARYA SUBUR
Authors: Rossiana Cendra Kasih  , Hadi Ismanto
Published: February 2025

This research aims to analyze the business model of the Jamu Karya Subur Shop using the Business Model Canvas (BMC) approach. Toko Jamu Karya Subur is a micro and small industry operating in the field of traditional herbal medicine, which has been operating since 2002. This research is motivated by the challenges faced by Toko Jamu Karya Subur, such as limited reach of information to customers and low competitiveness in the digital era. The research method used is qualitative phenomenological, which aims to understand the subjective experiences of owners and customers. Data collection was carried out through interviews, observation and documentation. Research subjects consisted of shop owners, franchise partners and customers. The research results show that the Jamu Karya Subur Shop has great potential to develop, but there needs to be innovation in marketing strategy and product development. The analysis results show that key elements in BMC, such as key partners, channels and customer relationships, are the main focus in developing business models. Toko Jamu Karya Subur's key partners include suppliers of herbal raw materials and distribution partners who can help expand the marketing network. The channels currently used are still limited to word of mouth promotion, so it is necessary to develop digital marketing channels to reach wider customers. Apart from that, customer relationships need to be improved through better service and the use of social media as a means of communication with customers. This research makes a significant contribution to the development of the Jamu Karya Subur Shop business model and provides recommendations for other micro and small businesses to pay attention to innovation and marketing strategies in facing competition in the digital era. By implementing BMC, it is hoped that Jamu Karya Subur Shop can increase its competitiveness and expand the market, so that it can continue to contribute to the local economy.
STRATEGI PENGEMBANGAN USAHA MELALUI BUSINESS MODEL CANVAS UD. JAYANTI
Authors: Fittrotun Nur Afidah  , Hadi Ismanto
Published: February 2025

This research aims to analyze UD's business development strategy. Jayanti through the Business Model Canvas (BMC) approach. UD. Jayanti is a Micro and Small Industry (IMK) which operates in the field of household equipment production, experiencing problems with shortages of raw material stock for cake brush strings, direct selling promotions, and sales through agents and not through customers. The method used is qualitative with a phenomenological approach, with data collection techniques in the form of interviews, observation and recording. The focus of this research is on three elements of BMC, namely Customer Segment, Customer Relationship, and Key Partner. Customer Segment Analysis is to group customers based on characteristics and behavior which focuses on UD problems. Jayanti sells directly through non-customer agents. Customer Relationship is a company interaction strategy with customers to build mutually beneficial relationships which focus on UD problems. Jayanti promotes direct selling, and Key Partner Elements, namely parties who collaborate with the company who focus on UD problems. Jayanti is short of stock of raw materials for cake brush strings. UD. Jayanti also implements business development strategies, namely product strategy, price strategy, location strategy and promotion strategy. The research results show that the product strategy, namely UD. Jayanti produces various household appliances that must remain relevant by understanding consumer characteristics and preferences which can increase customer satisfaction. Pricing strategy by implementing flexible prices, for example by providing discounts for large purchases or loyalty programs for regular customers. The location strategy is UD. Jayanti needs to ensure that products are easily accessible to customers by utilizing online platforms for sales. Promotional strategies, namely collaboration with influencers or local media, can help introduce products to a wider audience.
War, Colonization, and Language Evolution: Tracing Linguistic Shifts in Global History
Authors: Galandarova Aytan
Published: February 2025

This study investigates the intertwined roles of war and colonization in driving language evolution, focusing on the ways in which historical conflicts and colonial encounters have reshaped linguistic systems. By examining pivotal case studies—including the Norman Conquest, 20th-century conflicts, and colonial language imposition in various regions—the research reveals how power dynamics, cultural exchange, and forced linguistic contact contribute to shifts in vocabulary, syntax, and identity. Employing a multi-method approach that combines comparative historical analysis, corpus-based investigation, and qualitative case studies, the study highlights both the rapid lexical integration observed during wartime and the more gradual processes of creolization and pidgin formation that emerge in colonized settings. The findings underscore the dual nature of language as both a repository of cultural memory and a tool for negotiating social identity, offering valuable insights for contemporary language policy and cultural preservation efforts. This work aims to enrich our understanding of language change by situating it within the broader context of historical events, thereby contributing to ongoing discussions in historical linguistics and sociolinguistics.
Speech Acts and Hidden Meaning: A Journey into Pragmatics
Authors: Babazade Yasin
Published: February 2025

This article examines the core principles of pragmatics, focusing on how speech acts and hidden meanings guide communication across diverse contexts. It explores John Austin and John Searle’s foundational work on speech acts—locutionary, illocutionary, and perlocutionary—demonstrating how utterances perform actions beyond mere information exchange. The discussion then turns to implicature, introduced by H. P. Grice, highlighting the ways in which inferred meanings depend on shared knowledge and context. By integrating cultural considerations, the article underscores how pragmatic competence shapes both cross-cultural understanding and effective discourse. Practical applications include challenges in translation, advances in artificial intelligence, and strategies in media and political communication. Ultimately, the study affirms that pragmatics offers crucial insights into the power of language to form relationships, shape societies, and influence global interaction.
O papel das Entidades de Assistência Técnica e Extensão no Desenvolvimento Rural: ênfase no caso de Rondônia
Authors: Andrade Wilson Silva , Andrade Lenyldo Santana , Lima Wagner Soares de
Published: February 2025

O desenvolvimento rural sustentável é um desafio estratégico no Brasil, onde a agricultura familiar exerce papel central na segurança alimentar e na geração de renda. Este estudo tem como foco a EMATER-RO, entidade de assistência técnica e extensão rural do Estado de Rondônia, buscando identificar sua contribuição para o fortalecimento da agricultura familiar e as práticas sustentáveis, bem como as barreiras que limitam sua eficácia. O problema central reside na necessidade de maior integração entre a EMATER-RO e as políticas públicas, além das limitações de recursos financeiros e logísticos.A pesquisa adota uma abordagem qualitativa descritiva e um diagnóstico institucional, com base em revisão bibliográfica e análise documental de fontes oficiais, como o Relatório PROATER 2018 e publicações governamentais. As obras de autores como Figueiredo e Moraes (2010), Tavárez (2020) e Santos (2022) fornecem embasamento teórico sobre assistência técnica, sustentabilidade e segurança alimentar no contexto rural brasileiro.Os resultados revelam que a EMATER-RO desempenha um papel essencial no desenvolvimento rural de Rondônia, atuando na capacitação técnica de agricultores, na promoção do associativismo e cooperativismo e na implementação de práticas agroecológicas que fortalecem a produção familiar e conservam o meio ambiente. Contudo, desafios como a escassez de recursos financeiros, a falta de profissionais qualificados e a necessidade de maior articulação com políticas públicas permanecem. Recomenda-se a ampliação do financiamento, o uso de tecnologias digitais e o fortalecimento de parcerias interinstitucionais. Conclui-se que o fortalecimento da EMATER-RO é essencial para potencializar os resultados das políticas rurais, promover a resiliência da agricultura familiar e consolidar o desenvolvimento sustentável no estado.
Estabilidad y competitividad en la Unión Monetaria Europea
Authors:   Universitat Autònoma de Barcelona, Brunet Cid Ferran
Published: February 2025

Un déficit estructural de competitividad y unas políticas díscolas han causado una grave inestabilidad financiera en ciertos países de la zona euro, llevándolos a situaciones límite. Más aún, la propia Unión Europea padece ahora un elevado riesgo sistémico, económico y político. En este artículo se analizan las condiciones que generaron esta grave situación: a) las estructuras económicas y de ciertos Estados miembros; b) el carácter no óptimo de la zona euro; c) las políticas despilfarradoras de ciertos gobiernos e instituciones; y d) el déficit de gobernanza económica europea. Para afrontar los riesgos y retos de algunos Estados y a la propia Unión se necesitan nuevos y sólidos mecanismos para la estabilización financiera, así como protocolos detallados para la sostenibilidad fiscal y las reformas estructurales.
Política regional y cohesión europea: perspectivas 2014-2020
Authors:   Universidad de Alcalá, Mancha Navarro Tomás , Gallo Rivera María Teresa ,   Universidad de Alcalá
Published: February 2025

La parsimonia de la política regional europea desde su creación sufrió un impulso muy notable con la reforma de 1988 y con el inicio del proceso de integración monetaria, para posteriormente detenerse, primero, con las dificultades presupuestarias ligadas al cumplimiento de los criterios de Maastricht que llevó a una congelación de los recursos financieros destinados a la misma; y, posteriormente con su vinculación a los objetivos de la denominada Estrategia de Lisboa, que han desdibujado y complicado su funcionamiento y sus resultados. En el actual contexto de crisis económica, el devenir de la política regional para el futuro inmediato (2014-2020) se prevé –a la vista de los planteamientos conocidos de la Comisión Europea– complejo y con más sombras que luces, máxime si tenemos en cuenta que de nuevo se le liga a la denominada Estrategia 2020. Así se aleja en buena medida de lo que debiera constituir su objetivo primordial: la cohesión económica y social en el seno de una Unión ampliada a 27 países, prestando una especial atención a la reducción de las desigualdades regionales.
Un balance de la política de cohesión europea en Euskadi
Authors:   Gobierno Vasco, Varela Alonso José Antonio
Published: February 2025

Este artículo estudia la aplicación de la Política de Cohesión Regional de la Unión Europea en la Comunidad Autónoma Vasca (CAV). Comienza recordando los iniciales apoyos del FEDER y a partir de entonces recorre, uno por uno, los distintos periodos de programación plurianual. Estima el alcance de la experiencia vasca en el proceso de integración comunitaria, pero también examina la difícil, en ocasiones imposible, compatibilidad del interés regional con el estatal. Se pone de manifiesto cómo los intereses de una región en declive industrial (País Vasco) en un «país de cohesión» (España) no han estado entre las prioridades. Aunque actualmente en la UE todas las regiones son beneficiarias de la política regional comunitaria, la política estructural para las regiones más desarrolladas parece enfocarse hacia el impulso de sus capacidades de arrastre económico. Los acuerdos para el periodo 2014- 2020 darán su medida.
Stability and competitiveness in the European Monetary Union
Authors:   Universitat Autònoma de Barcelona, Brunet Cid Ferran
Published: February 2025

Structural non-competiveness and unruly policies have provoked severe financial instability and put certain euro zone countries in a shocking situation. Indeed, the entire European Union is at economic and political systemic risk. In this paper we shall analyze the coinciding conditions which helped generate this perfect and fatal storm: a) the structures of the European economy and of some Member States; b) the non-optimal currency zone that is the euro area; c) the profligate policies of certain governments and institutions; and d) the deficit in European economic governance. Newer and tougher mechanisms for European financial stability and detailed government measures for budget sustainability and structural reforms need to be most effective to be able to address the risks and challenges many States, and the Union itself, are facing.
Análisis de los determinantes de la transparencia en Responsabilidad Social Corporativa desde la perspectiva del buen gobierno
Authors:   Universidad de León, Cabeza García Laura , Fernández Gago Roberto ,   Universidad de León, Matilla Fernández Lorena ,   Universidad de León
Published: February 2025

Este trabajo estudia la relación existente entre el gobierno corporativo y la transparencia en materia de responsabilidad social corporativa (RSC). Se utiliza una muestra de 38 empresas españolas cotizadas en el IBEX35 en el periodo 2005-2010 y un modelo donde se consideran conjuntamente variables relativas a la estructura de propiedad y al Consejo de administración. Los análisis de regresión realizados mediante un pool de datos utilizando la opción cluster concluyen que son las variables relativas al Consejo de administración las que influyen de manera significativa en la transparencia en RSC. En concreto, cuanto mayor sea el número de mujeres miembros del Consejo y cuanto menor sea el tamaño del Consejo de administración, mayor será la transparencia de las empresas sobre las actividades de naturaleza social que llevan a cabo.