bluuebunny/crossref_metadata_2025 huggingface dataset:
Restoring Order to Adolescent Eating Disorders: Unveiling Causes, Solutions, and Societal Impacts
Authors: Tang Yuhong
Published: February 2024

This article delves into the complexities of eating disorders, positioning them as substantial mental health concerns rather than mere manifestations of unhealthy dietary preferences. The research contributes valuable insights into the pivotal role played by media in exerting social pressure and shaping body ideals, shedding light on the phenomena of social comparison and the associated social stigma prevalent among adolescents. The profound isolation resulting from nominalization synergistically impacts adolescent body image and susceptibility to appetite disorders. The article also underscores the escalating global prevalence of eating disorders, with a specific focus on their occurrence among adolescents in Singapore. Employing a methodology encompassing interview groups, individual interviews, and expert guidance from psychologists, the research suggests the exploration of media literacy enhancement and the elimination of societal stigma as potential avenues for recovery among individuals grappling with eating disorders. Drawing upon the narratives of recovered patients, the article advocates for heightened awareness within society, emphasizing the imperative to address and actively ameliorate this frequently overlooked social issue.
Research on Cooperation Mode and Evolution Analysis of Huawei Company based on Patent Collaboration Network
Authors: Chen Ziyi , Qiu Jingwen , Liu Ziyu
Published: February 2024

Patents, as a vital tool in open innovation, play a significant role in enabling enterprises to access and utilize external resources, thereby enhancing their competitive advantage. This paper uses Huawei as a case study, employing patent metrics and social network analysis methods to examine the evolution characteristics and attributes of Huawei’s collaboration network. The analysis, based on authorized patent data from the Incopat database, explores Huawei’s collaboration mode. This study aims to provide insights and guidance for Chinese enterprises in the development and management of their patent collaboration networks. The findings reveal that Huawei adopts a mononuclear radiation cooperation mode, primarily industry-university oriented, with a focus on technological proximity.
Biophytum veldkampii– A new record for Tamil Nadu state of India
Authors: Daniel Jisha , Shaju Thankappan , Rajendraprasad Madhavan
Published: February 2024

An interesting specimen of the genus Biophytum (Oxalidaceae) collected from Pechiparai of Kanyakumari district is confirmed as Biophytum veldkampii. This note reports the occurrence of this species in the state of Tamil Nadu as a new record. A detailed description and photo to facilitate field identification of this species are provided here.
Guiding to available parking spots with AR device
Authors: Fu Daowei , Wang Yuxuan , Zhu Yihao
Published: February 2024

Parking congestion has become a pressing issue in urban areas, leading to increased traffic congestion and environmental pollution. This paper presents a comprehensive study on intelligent parking systems aimed at addressing these challenges. The study targets urban drivers, transport authorities and citizens who are affected by parking difficulties and traffic congestion. Intelligent Parking System is a technology-driven solution that aims to optimise parking space utilisation and reduce traffic congestion. It efficiently guides drivers to available parking spaces through real-time data collection and analysis. The study was conducted in Unity3D environment over a period of 2 weeks and covered the phases of system design, development, testing and implementation. The main motivation for this research was to mitigate the negative effects of parking congestion. Intelligent parking systems have the potential to increase traffic efficiency, reduce air pollution and improve the overall quality of life in cities. Server and Unity models were used in the study. Real-time sensors collect parking occupancy data, which is processed to provide real-time parking availability information to drivers via the server. In conclusion, this paper presents an intelligent parking system that can solve the challenges of parking congestion. By utilising server technology and data-driven insights, the project aims to improve the way cities manage parking and contribute to more sustainable urban mobility.
Using data resampling and category weight adjustment to solve sample imbalance
Authors: Leng Zimeng
Published: February 2024

The purpose of this thesis is to investigate the application of artificial intelligence and machine learning in solving the sample imbalance problem. The sample imbalance problem refers to the phenomenon that the number of different categories of samples in the training data varies greatly, resulting in the poor performance of traditional machine learning algorithms on a few categories of samples. To address this problem, this paper proposes a new approach combining data resampling and category weight adjustment strategies. First, the sample distribution of the dataset is adjusted by undersampling and oversampling techniques to balance the number of samples from different categories. Then, during the model training process, different weights are assigned to the samples of different categories so that the model pays more attention to the samples of a few categories. The experimental results show that the method achieves significant performance improvement on multiple datasets. In addition, this paper compares other commonly used methods for solving the sample imbalance problem and analyzes and discusses them in detail. Finally, this study offers a practical solution to the problem of sample imbalance and provides guidance for research in related fields.
Deep learning based multi-target detection for roads
Authors: Jiang Junlin
Published: February 2024

The vehicle target detection algorithm based on deep learning has gradually become a research hotspot in this field. In recent years, with the significant breakthrough of deep learning in the field of target recognition, the vehicle target detection algorithm based on deep learning has gradually become a research hotspot in this field. For the task of vehicle target detection, this paper first briefly introduces the process of traditional target detection algorithms and some optimization methods. It summarizes the development process of YOLO, the current mainstream one-stage vehicle target detection algorithm, and the process of Faster R-CNN, the second-stage vehicle target detection algorithm, and its improvement. Then the characteristics of several types of representative convolutional neural network algorithms are analyzed in chronological development order. Finally, it looks forward to t he future research direction of vehicle target detection algorithms, and also provides new ideas for the optimization of the subsequent vehicle target detection algorithms, which have good engineering application value. Provides algorithmic support for the underlying logic of autonomous driving.
Design and analysis of adaptive control systems: Adaptive control algorithms using machine learning
Authors: Zhou Zikai
Published: February 2024

A growing field of research is the use of adaptive control algorithms with machine learning techniques like Q-learning and SARSA. With prospective applications in robotics, healthcare, and other fields, this interdisciplinary method strives to combine the stability and robustness of conventional control systems with the self-learning skills of reinforcement learning. Making sure that systems are stable and that learning occurs effectively is the main research problem. This paper demonstrates the stability and convergence of existing adaptive control algorithms when integrating with machine learning. There are mainly four primary methods of control algorithms: reinforcement learning, neutral network, support vector machine and deep learning. Reinforcement learning is the main focus of this paper. Data efficiency, robustness, and generalization are the main problems with reinforcement learning. Q-learning and SARSA (State, Action, Reward, State, Action) are two algorithms for reinforcement learning. The research will be done by analyzing these two algorithms based on existing material and the actual application of these two algorithms. SARSA is believed to be more safe as its on-policy methodology, and Q-learning is believed to be more proactive as its off-policy methodology.
Model optimization method based on the MOON algorithm
Authors: Cao Haogang , Dong Chenxin , Zhou Jingyi
Published: February 2024

Federated Learning is a revolutionary approach to machine learning. Its purpose is to enable multiple participants to collaboratively train machine learning models without the need to share local data. The main objective is to address issues related to data privacy and security. In traditional machine learning, data is typically centralized and stored in a single location or on cloud servers for training. However, this centralized training approach carries risks of potential data leakage, especially concerning sensitive and critical information. Industries such as healthcare and finance, which involve sensitive data, place a premium on safeguarding data privacy. Furthermore, in cases where data cannot be easily transferred or is subject to privacy regulations, centralized methods may face limitations. Federated Learning revolutionizes the conventional approach by introducing a decentralized model training process. It maintains data decentralization while achieving collaborative model optimization, greatly enhancing data privacy and security. The MOON algorithm, an integral part of federated learning, contributes to its novelty. As a significant component, the MOON algorithm facilitates new possibilities for federated learning. In this article, the research will elaborate on the MOON algorithm within the context of federated learning. And this article will delve into its description and optimization, elucidating how it enhances federated learning.
The experiment of federated learning algorithm
Authors: Wang Rui
Published: February 2024

As technology advances, concerns regarding data privacy and security have become prominent challenges in machine learning applications. Nevertheless, the introduction of federated learning technology has effectively tackled this concern by concurrently enhancing model performance and preserving data privacy, thereby presenting a more secure and efficient solution within our digital realm. Utilizing discussions about the background of federated learning technology, coupled with pertinent algorithmic procedures and logic, this paper proficiently implements the FedMA algorithm. Additionally, the study performs a comparative analysis of the accuracy and efficiency of the FedMA, FedAvg, FedDyn, and MOON algorithms utilizing the Fashion-MNIST dataset. Moreover, the investigation not only optimizes parameter tuning for the MOON algorithm but also extends experiments to the CIFAR-10 and AGNews datasets, thereby providing additional comparisons of performance and strengths among various federated learning algorithms. In conclusion, the paper provides a comprehensive summary and outlines potential avenues for future research. These insights enhance the comprehension of federated learning and offer valuable guidance to advance and refine its practical applications.
Optimization of 4-bit absolute value detector based on CMOS and PTL
Authors: Han Ju , Jia Yingning , Yang Yuxin
Published: February 2024

This article designed and optimized a 4-bit absolute-value detector mostly using Complementary Metal Oxide Semiconductor (CMOS) static logic and transmission gate logic (PTL). In terms of overall architecture, the implementation of logic circuit functions is primarily separated into two modules, including the absolute value detector and the comparator. This paper identified the critical path of the final detector and conducted research and simplification on it to improve the general functionality of the detector which can compare the value of two numbers. To shorten the delay time in the circuit, this paper reduced the number of components on the crucial path. After calculating, the critical path delay is approximately 61.065 and the initial energy consumption for a minimum path delay is 51.06. To obtain the least amount of delay and energy use, three different techniques were used in this investigation. Ultimately, we found that the circuit optimized using the Changing V_DD and Sizing method was the most efficient. The optimized critical path delay remained around 61.065, and the energy consumption under optimized critical path delay was reduced to 10.845. The final implementation achieved a decrease of 82.2% in energy consumption while maintaining the critical path delay unchanged.
Comparative study of 2FSK and GFSK modulation and demodulation techniques
Authors: Xing Shibo
Published: February 2024

In the digital communication era, efficient data transmission is paramount, spanning applications from mobile communication to satellite systems. Digital modulation, the process of converting digital data into a suitable format for transmission, plays a pivotal role in ensuring reliability and efficiency. This paper delves into the world of digital modulation, specifically focusing on Frequency Shift Keying (FSK) techniques. FSK encodes digital information using different carrier frequencies, making it adaptable and robust, particularly in noisy channels. This paper explores two variants: 2-level Frequency Shift Keying (2FSK) and Gaussian Frequency Shift Keying (GFSK). 2FSKs simplicity and noise tolerance make it ideal for applications like wireless LANs and radio broadcasting. However, it may not be the best choice for high-data-rate applications due to limited bandwidth efficiency. GFSK employs Gaussian filtering to reduce spectral width, enhancing bandwidth efficiency and reducing inter-symbol interference. It finds extensive use in applications like Bluetooth. This paper explores the modulation and demodulation processes for both techniques, emphasizing GFSKs spectral efficiency. Future trends encompass emerging technologies like signal processing and machine learning, reshaping telecommunications and IoT. In conclusion, understanding 2FSK and GFSK modulations nuances aids engineers and researchers. Future endeavors should focus on optimizing GFSKs bandwidth efficiency and bolstering demodulation techniques.
Research on algorithms of machine learning
Authors: Yu Binyan , Zheng Yuanzheng
Published: February 2024

Machine learning has endless application possibilities, with many algorithms worth learning in depth. Different algorithms can be flexibly applied to a variety of vertical fields, such as the most common neural network algorithms for face recognition, garbage classification, picture classification, and other application scenarios image recognition and computer vision, the hottest recent natural language processing and recommendation algorithms for different applications are from it. In the field of financial analysis, the decision tree algorithm and its derivative algorithms such as random forest are the mainstream. As well as support vector machines, naive Bayes, K-nearest neighbor algorithms, and so on. From the traditional regression algorithm to the hottest neural network algorithm. This paper discusses the application principle of the algorithm and lists some corresponding applications. Linear regression, decision trees, supervised learning, etc., while some have been replaced by more powerful and flexible algorithms and methods, by studying and understanding these foundational algorithms in depth, neural network models can be better designed and optimized, and a better understanding of how they work can be obtained.
Overview of the application of artificial intelligence in computer animation
Authors: Huang Zhihong
Published: February 2024

With the flourishing development of artificial intelligence and computer animation technologies, there has been an increasing intersection between these two. In the field of computer animation, the use of artificial intelligence significantly reduces the difficulties in design, production, and post-production processes, which has a massive impact on the entire field. The paper attempts to discuss the relationship between artificial intelligence and computer animation. Not only does the paper elaborate on the related applications of artificial intelligence in various subfields of computer animation, but it also analyzes existing problems and future development trends. The research indicates that AI has achieved significant breakthroughs in computer animation, such as auto-generation of animations, real-time character driving, and emotionally responsive animation creation. However, it also faces challenges like handling interactions in complex scenarios, maintaining realism, and animating high-level abstract concepts. Despite these challenges, it is believed that in the future, AI will further propel the development of computer animation, aiding creators in producing animations that are more vibrant, intricate, and personalized.
Database design for course selection and course grading system
Authors: Liu Donghao
Published: February 2024

In the context of global education, universities and institutions emphasize the importance of proficient academic information management systems. As traditional approaches to course data management become obsolete, there is a growing need to leverage digital transformation for academic management. This paper proposes a novel course database design that centralizes information about subjects, courses, staff, students, buildings, and grades. The database is designed to facilitate the overall academic progress of students by ensuring efficient record keeping, retrieval and updating. The architecture simplifies administrative tasks, underscores the importance of databases in modern educational institutions by providing in-depth student data to support personalized learning, enhance communication among stakeholders, and aid academic research. The conclusion of the experimental test is that a database designer should always ensure they pay attention to avoiding data redundancy and ensuring data diversity when processing data.
A performance study of algorithms and frameworks for federated learning
Authors: Zhang Shuyan
Published: February 2024

Federated learning is a type of distributed machine learning that focuses on solutions for the properties of training data on edge devices as well as the privacy of the training set. Federated learning is a discipline highly relevant to real-world applications, and thus the emphasis on different perspectives requires an adaptation of the federated learning framework. Although almost every newly proposed federated learning algorithm is compared with some existing algorithms, current research on testing comparisons between commonly used federated learning algorithms remains vague and complex. Therefore, the purpose of this paper is to test and compare several federated learning frameworks, including the representative FedAvg, MOON, FedProx, and MOON. Based on revisiting the theory and key steps of these algorithms, an analysis of the performance performance will be conducted, evaluating their advantages for applications. Furthermore, a summary based on the test results will be provided, pointing out possible future challenges as well as research directions.
FPGA-based gesture recognition and voice interaction
Authors: Deng Linhai
Published: February 2024

Human gestures, a fundamental trait, enable human-machine interactions and possibilities in interfaces. Amid technological advancements, gesture recognition research has gained prominence. Gesture recognition possesses merits in sample acquisition and intricate delineation. Delving into its nuances remains significant. Existing techniques leverage PC-based OpenCV and deep learnings computational prowess, showcasing complexity. This scholarly exposition outlines an experimental framework, centered on mobile FPGA for enhanced gesture recognition. The focus lies on DE2-115 as an image discernment base. A 51 microcontroller supports auditory synthesis. Specifically, this paper highlights the DE2-115 FPGA as the foundation for image discernment, while a 51 microcontroller assists in auditory synthesis. Our emphasis lies in recognizing basic gestures, particularly within the rock-paper-scissors taxonomy, to ensure precision and accuracy. This research underscores the potential of FPGA in enabling efficient gesture recognition on mobile platforms. As a result, the experiments conducted in this thesis successfully realize the recognition of simple gestures, such as the numbers 1, 2, 3, and 4, as well as rock-paper-scissors.
Investigating the efficiency and performance gains of FPGA-accelerated Convolutional Neural Networks
Authors: Li Shouyi
Published: February 2024

With the rise of big data and artificial intelligence (AI), Convolutional Neural Networks (CNNs) have become instrumental in numerous applications, from image and speech recognition to natural language processing. However, these networks computational demands often exceed the capabilities of traditional processing units, leading to a search for more effective computing platforms. This research aims to evaluate the potential of Field-Programmable Gate Array (FPGA) technology in accelerating CNN computations, considering FPGAs unique attributes such as reprogrammability, energy efficiency, and custom logic potential. The primary aim of this research is to compare the efficiency and performance of FPGA acceleration of CNNs with conventional processing units like CPUs and GPUs and to explore its potential for future AI applications. This research employs a mixed-methods approach, including an integrated literature review and comparative analysis. This paper reviews state-of-the-art research on FPGA-accelerated CNNs, benchmark performance metrics of FPGA, CPU, and GPU platforms across various CNN models, and compare FPGA-based AI applications with other real-world AI applications. The findings suggest a significant potential for FPGA-accelerated CNNs, particularly in scenarios requiring real-time computation or power-limited environments. However, challenges persist in the areas of development complexity and limited on-chip memory. Future work must focus on surmounting these barriers to unlock the full potential of FPGA-accelerated CNNs.
Classification of brain tumors based on magnetic resonance imaging (MRI) using deep learning models
Authors: Li SiLong
Published: February 2024

Nowadays, With the advancements in medical care and the improvement in global living standards, there has been a continuous increase in the average life expectancy of people around the world, and the aging problem is constantly aggravated, brain tumors have become a growing global health problem. The project aims to use deep learning models to classify magnetic resonance imaging (MRI) images of brain tumors. By constructing convolutional neural network model, image feature extraction and classification are carried out. Data preprocessing, data enhancement, Adaptive Moment Estimation (Adam) are used to improve the model performance, plot the accuracy curve and generate the confusion matrix, and visualize the classification performance of the model. Possible future tasks may include optimizing the model architecture and expanding the exploration of data augmentation techniques to bolster the model's performance, while also further investigating the model's interpretability to understand the internal mechanisms of the model when making predictions. In addition, the project has great application potential, and the model can be applied to the actual clinical assisted diagnosis system, which has good scalability and application prospect. By using deep learning model and related technologies, the accuracy of brain tumor classification can be improved in clinical diagnosis, and better diagnosis and treatment services can be provided for the majority of brain tumor patients.
University major information recommendation based on federated learning
Authors: Song Yuzhao , Wu Yexin , Xue Yanjie
Published: February 2024

This paper focuses on the research of applying federated learning to recommendation systems and proposes a university major recommendation method based on federated learning. Furthermore, an improved knowledge distillation architecture is implemented for university major recommendations. In the collaborative structure of the system based on federated learning, knowledge distillation is used to optimize the recommendation performance. The federated learning algorithm, FedDyn, is employed to aggregate model parameters through weighted averaging, enabling a training mode where only local training data and local models are uploaded to the central server. After reading and studying other papers that apply federated learning to recommendation systems, this paper conducts further speculation and research, aiming to apply relevant knowledge and techniques to establish a system that can recommend specific content to a targeted audience, such as students after the college entrance examination. This includes providing major-related information, predicting students major preferences, and delivering the latest industry news related to specific majors.This paper also categorizes the technologies used in the creation of recommendation systems and compares them into three categories. The study suggests that the recommendation system utilizing knowledge distillation will be more efficient.
Enhancing Airway Assessment with a Secure Hybrid Network-Blockchain System for CT & CBCT Image Evaluation
Authors: Vamsi Krishna Uppalapati , G Srinivasa Rao , Addepalli Lavanya , M Bhavsingh , SD Vidya Sagar , Jaime Lloret Mauri
Published: February 2024

Our investigation explored the intricacies of airway evaluation through Cone-Beam Computed Tomography (CBCT) and Computed Tomography (CT) images. By employing innovative data augmentation strategies, we expanded our dataset significantly, enabling a more comprehensive analysis of airway characteristics. The utility of these techniques was evident in their ability to yield a diverse array of synthetic images, each representing different airway scenarios with high fidelity. A notable outcome of our study was the effective categorization of the initial image as "Class II" under the Mallampati Classification system. The augmented images further enhanced our understanding by exhibiting a spectrum of airway parameters. Moreover, our approach included training a Recurrent Neural Network (RNN) model on a dataset of CT images. This model, fortified with pseudo-labels created via K-means clustering, showcased its proficiency by accurately predicting airway assessment categories in various test scenarios. These results underscore the model's potential as a tool for swift and precise airway evaluation in clinical settings, marking a significant advancement in medical imaging technologies.
Migrant Worker Resource Centre in Tijuana
Authors:   International Labour Organization,
Published: February 2024

It presents the context in which the Tijuana Migrant Worker Resource Centre was created, the services it offers, as well as the steps needed to continue its implementation and reach a greater number of beneficiaries in the Mexico-Central America migration corridor.
Socialization of Tax Procedure for Domestic Taxpayers Receiving Income Abroad in Pulau Pinang Malaysia
Authors: Tarmidi Deden , Setiany Erna , Bin Rahmad Khozaeni , Ali Anees Janee
Published: February 2024

In the era of the global economy, cross-border business activities are widespread, including the urbanisation of citizens abroad, one of which is a member of the Pertubuhan Masyarakat Indonesia (PERMAI) on Penang Island Malaysia both as expatriates, students, entrepreneurs and as a workforce in Malaysia which has an impact on increasing foreign exchange earnings. Specifically, through the Minister of Finance Regulation Number 18 of 2021, the Government of Indonesia has provided direction on how to manage the tax status for domestic taxpayers who work and earn income abroad, or vice versa. However, many taxpayers do not understand their tax status when working and earning income abroad and have the wrong perception that they are at risk of getting a tax bill from the tax authorities in Indonesia, so socialization is needed. This community service activity aims to provide education about tax procedures for Indonesian taxpayers who work and earn income abroad and provide assistance in carrying out procedures according to applicable regulations. This activity was held in Pulau Pinang Malaysia in January 2024 to 75 Indonesians who are domiciled and have income abroad. With the socialization and question and answer method, it was found that all participants did not know the rules and did not understand how the procedure should be before the activity took place. The understanding of the participants increased after the activity, and the majority of participants became vigilant and intended to coordinate with their families in Indonesia regarding their Tax ID Numbers.
Knowledge of eye self-care among secondary school students with myopia attending Nam Dinh Eye Hospital in 2023
Authors: Vu Thi Lung , Do Minh Sinh , Hoang Nang Trong
Published: February 2024

Objective: To describe the knowledge of eye self-care among secondary school students with myopia undergoing examination at Nam Dinh Eye Hospital in 2023.
Methods: The participants were 286 secondary school students (11-14 years old) with myopia examined and treated at Nam Dinh Eye Hospital. A descriptive cross-sectional study design was conducted. The research team developed a survey questionnaire on participants’s knowledge of self-care for myopic eyes, drawing references from various studies on myopia. The total knowledge score is 24 points, the participants had satisfactory knowledge defined as providing at least 70% of the correct answers (≥ 17 points), then the average score of students’ general knowledge of myopic eye self-care would be evaluated.
Results: The average score of the students’ general knowledge of eye self-care was 17.52 ± 2.71 out of 24 points, with 73.1% of the students demonstrating satisfactory general knowledge while 26.9% of the students had unsatisfactory knowledge of eye care.
Conclusion: The participants’ knowledge of self-care for myopic eyes was relatively good. It is necessary to evaluate students’ nearsighted eye self-care practices to have a basis for providing appropriate interventions
Current status of care for patients with tracheostomy among nurses at Thai Binh Provincial general Hospital and some associated factors in 2023
Authors: Pham Thi Thuy , Truong Tuan Anh , Tran Thi Van , Lam Thi Hanh , Bui Thi Lan
Published: February 2024

Objective: To describe the current status of care for patients with tracheostomy at Thai Binh Provincial General Hospital and some related factors.
Research subjects and methods: A cross-sectional study of over 110 visits for each procedure of chest percussion and sputum suction in nursing care of patients with tracheostomy. The assessment scale is based on the procedure issued by the Ministry of Health. The chi-square test was used to identify factors related to the current status of care for patients with tracheostomy.
Results: The practice rate achieving the technique of chest percussion and sputum suction was 35.5% and 81.8%, respectively. The rate of nurses with bachelor’s degrees, and care < 5 nurses/day satisfactorily practice in the technique of chest percussion is higher than the group of nurses with college degree and cared for ≥ 5 patients/day with ORs of 3.25 and 3.06, respectively. The nursing group is ≥ 30 years old, working experience > 10 years, experience in caring for tracheostomy patients > 10 years and number of training participations > 1 time passed the practice of sputum suction technique higher than the remaining nursing group with OR of 7.91; 4.71; 4.71 and 4.44 respectively. This difference is statistically significant with p < 0.05.
Conclusion: The prorpotion of nurses practice satisfactorily the sputum suction technique is relatively high (81.8%), but it is too low with the chest percussion technique (35.5%). There are a number of factors related to percussion technique, including qualifications and the number of patients cared for per day. Some factors related to practicing the sputum suction technique are age, working experience, caring time for tracheostomy patients, and number of training session. Nurses need to pay attention to compliance with technical procedures, especially nurses aged < 30 years old, low qualifications, short working time and rarely participates in training.
EXPLORING THE WISDOM/FOLLY MOTIF IN PROVERBS 9
Authors: Faith Opade Dr. Ochenia
Published: February 2024

The paper explores the wisdom and folly motif within Proverbs 9, delving into the nuance presented in this biblical text. It examines the personifications of Wisdom and Folly as contrasting figures, analysing their respective invitations and the consequences of heeding or disregarding their counsel. This study aims to explore the concept of wisdom/folly motif in Proverbs 9 by engaging in a comprehensive literary analysis of the chapter, dissecting its linguistic and stylistic features and philosophical underpinnings and seeking to uncover the cultural and historical contexts that shaped this timeless allegory. The aim is to understand how the portrayal of wisdom and folly in Proverbs 9 aligns with or challenges prevailing philosophical ideas of the time and how it continues to resonate with contemporary audiences. Through a literary lens, the paper navigates the rich symbolism and rhetorical devices employed in Proverbs 9, shedding light on the moral and practical implications of this ancient wisdom literature.
THE PRINCIPLES OF PASSION AND PURPOSEFUL LEADERSHIP DEVELOPMENT IN RAISING ‘LEADERS OF TOMORROW’ FOR NATION-BUILDING: A STUDY OF DEUTERONOMY 6:1-13
Authors: Umaru Victor
Published: February 2024

This study explores the fundamental tenets of cultivating passionate and purpose-driven leadership, aimed at nurturing the emergence of future leaders pivotal for the advancement of a nation. Focusing on Deuteronomy 6:1-13 as a foundational framework, this research delves into the intricate interplay between passion, purpose, and leadership development. By analyzing the timeless principles embedded in this scripture, the investigation highlights the significance of holistic education, intentional mentorship, and values-based guidance in molding individuals into effective leaders. Through an interdisciplinary approach that merges leadership theories and biblical insights, the study offers valuable insights into fostering a generation of forward-thinking leaders committed to the sustainable growth and prosperity of their nations.
EKKLĒSIO-ACADEMICS IN THE JOHANNINE COMMUNITY AS A PARADIGM IN THE INDIAN CONTEXT
Authors: Thomaskutty Johnson
Published: February 2024

This article develops a new way forward in interpreting the Fourth Gospel by taking into consideration the feelings and aspirations of all levels of people in the Johannine situation. A reader of John can perceive how the narrator facilitates academic thinking and ordinary feelings and aspirations in her or his master plan. With that view in mind, the article elaborates the introductory statements followed by describing the riddling language of the Fourth Gospel, understand the progressive category of people within the Johannine narrative framework, ordinary people within the Johannine context, people’s level of knowledge in John’s community, practice of ekklēsio-academics in John’s community, and doing ekklēsio-academics in India. The article ends with a concluding section.
El discurso de la Unión Europea sobre la sociedad del conocimiento
Authors: Crespo Suárez Eduardo , Serrano Pascual Amparo
Published: February 2024

El discurso acerca de la sociedad del conocimiento y de la información ha sido integrado ypopularizado por las instituciones europeas, y ha sido vinculado al proyecto social europeo. Estediscurso implica, entre otras cuestiones, una redefinición de la cohesión social, que es caracterizadapor un contexto de crisis. Esta crisis se extendería en torno a tres ejes: una crisis de regulacióndel mercado de trabajo, una crisis del desempleo y una crisis de la ciudadanía. El nuevocontrato social planteado en el discurso de las instituciones de la Unión Europea se articula básicamenteen torno a estos tres ejes: frente a la crisis de la regulación del trabajo, el discurso de laflexibilidad del trabajo; frente a la crisis del desempleo, el discurso de la empleabilidad, y frenteal modelo de intervención social basado en los derechos ciudadanos, el discurso de la activacióny la responsabilidad personal.
El fin de la conscripción en Europa
Authors: Ajangiz Rafael
Published: February 2024

Se analizan los últimos cambios habidos en Europa en relación con el servicio militar obligatorioa partir de la constatación de un largo y amplio proceso de declive de los ejércitos de masas.Se presentan y analizan diez indicadores de esa crisis para llegar a la conclusión de que la sociedadcivil, aquí llamada razón democrática, ha ejercido un influjo mucho mayor del que habitualmentese le reconoce en la reciente decisión de varios gobiernos europeos de suprimir tal obligación.En la mayoría de los casos estudiados, aun a pesar de que los gobiernos han sabido pautareste cambio en función de sus prioridades estratégicas, el fin de la conscripción es en realidaduna consecuencia aplazada de la movilización de esa razón democrática. En otros, el caso de Italiay, muy especialmente, España, esa movilización ha forzado un apresurado y problemáticocambio de los planes gubernamentales al respecto. Por fin, la continuidad de esta prestación enalgunos países de nuestro entorno permite entender el fin de la conscripción como una decisiónfacultativa y no una consecuencia obligada de la elección o consolidación del modelo de empleoen las fuerzas armadas.
Teaching fractions at elementary level in the light of Hungarian mathematics textbooks in Romania
Authors: Baranyai Tünde Klára
Published: February 2024

According to the new curriculum in Romania, fractions are introduced in the second grade. The present study analyses Hungarian elementary mathematics textbooks on the topic of fractions focusing on the types of tasks in the textbooks, the significance of representations and the proportion of word problems. Additionally, the paper presents a questionnaire-based research on teachers’ opinion regarding the adequacy and sufficiency of the digital materials and exercises related to fractions in the textbooks.
Subject Classification: 97F40, 97F80, 97U20, 97U50
QUALIFICAÇÃO DA FERRAMENTA FEEDBACK NO PROCESSO AVALIATIVO
Authors: Dias Camilla Lorraine Moreira , Dittz Erika da Silva , Veiga Fernanda Natielle Araújo , Silveira Luana Fátima Alvarenga , Amaral Raquel Vieira do , Xavier Raiane Teixeira
Published: February 2024

Introdução: Ações de planejamento educacional se mostram fundamentais para a prática pedagógica, orientando o trabalho do educador de forma que ele seja um processo contínuo de ação crítico-reflexiva. Objetivo: Relatar a experiência acerca de uma ação educativa sobre o uso do feedback no processo formativo de dois programas de residência (multi e uniprofissional) de um hospital filantrópico de Belo Horizonte, Minas Gerais, Brasil. Relato da experiência: Foram organizados pelas preceptoras dos programas, seis encontros presenciais para desenvolver a ação educativa, dos quais participaram 117 preceptores dos programas da Residência Multiprofissional em Neonatologia e da Residência em Enfermagem Obstétrica. A ação pedagógica foi precedida de um planejamento, a partir de uma necessidade identificada previamente no cotidiano da prática pelas preceptoras. Foi abordado o uso da ferramenta do feedback no processo avaliativo do profissional residente, considerando seus componentes – tempestividade, especificidade, assertividade – e as habilidades de comunicação demandadas no processo educacional, seguidas de simulações de feedbacks inadequado e eficaz. Conclusão: O planejamento da prática educativa possibilitou o alcance dos objetivos de aprendizagem da atividade educativa realizada. Recomenda-se o investimento no planejamento de ações de educação permanente voltadas à preceptoria, pensadas a partir das necessidades vivenciadas pelos profissionais preceptores no cotidiano dos programas de residência em saúde, no sentido de apoiá-los no processo avaliativo e estimular sua participação nas atividades de ensino-aprendizagem-avaliação.
Laboratory Safety Technology with Energy Saving System using IOT
Authors:   MIT Polytechnic ,Yeola, Bodhare T.S
Published: February 2024

Abstract: Internet of Things (IOT) conceptualizes the idea of remotely connecting and monitoring real world objects (things) through the Internet .This concept can be aptly incorporated to make laboratories smarter, safer and automated. This IoT project focuses on building a smart lab safety system which sends alerts to the owner by using Internet in case of any danger and raises an alarm optionally. A safety system needs to be designed to ensure at most safety in the laboratories. Keywords: Automation, Chemical, Hazards, IOT, RFID, Safety.
Interferons during HSV-2 Infection: Immune Regulation
Authors: KUILYA SANTANU
Published: February 2024

Herpes simplex virus type 2 (HSV-2) infection is a prevalent sexually transmitted infection that disproportionately affects women worldwide. Currently, there are no vaccines or curative treatments available, leading to life-long infections. During HSV-2 infection, interferons (IFNs) play a crucial role in the body's antiviral defense. Type I IFNs (IFN-alpha and IFN-beta) and type III IFNs (IFN-lambda) are produced by host cells in response to the virus, alerting neighboring cells to its presence and inducing an antiviral state that limits viral replication and spread. Type III IFNs, produced in epithelial cells, also contribute to controlling viral replication in mucosal tissues. However, HSV-2 has evolved strategies to evade IFN-induced responses, allowing the virus to partially escape the host's immune response, establish latency, and cause recurrent infections. The delicate balance between the host's IFN response and the virus's immune evasion mechanisms determines the outcome of HSV-2 infection. Understanding the intricate interplay between HSV-2 and interferon signalling is critical for developing effective therapies and vaccines to combat this sexually transmitted infection. Keywords: HSV-2, Interferons, Innate immunity, Immune regulation
Gawęda szlachecka i co jeszcze?
Authors: Rambowicz Piotr
Published: February 2024

Michał Kryspin Pawlikowski (1893–1972) należy do najstarszego pokolenia emigrantów, którzy pełnoletniość osiągali jeszcze przed Wielką Wojną lub na jej początku, natomiast okres dwudziestolecia międzywojennego był dla nich czasem rozmaitej aktywności publicznej: politycznej, literackiej czy publicystycznej. Przynależność pokoleniowa i stanowa pisarza do generacji ziemiańskiej, potrafiącej żywą pamięcią świadczyć  o  czasach z końca XIX wieku i pierwszych dziesięcioleci wieku XX, tak istotna dla twórczości wspomnieniowo-gawędowej, którą uprawiał, łączy się ponadto w przypadku Pawlikowskiego ze specyficzną przynależnością geograficzną i polityczną. Ramę terytorialno-historyczną jego przedemigracyjnego życia, z czasów przed odzyskaniem przez Polskę niepodległości, ramę określającą w znacznym stopniu również tematykę późniejszej twórczości literackiej stanowią dawne Kresy Północno-Wschodnie w ostatnim ćwierćwieczu istnienia Imperium Rosyjskiego.
Naśladowanie Chrystusa
Authors: Staroń Ireneusz
Published: February 2024

Krzysztof Koehler pojęcie uchrystusowienia (drogi nawrócenia, która ma prowadzić do upodobnienia człowieka do arcywzoru dobrego życia – Chrystusa) czyni fundamentem swojej filozofii twórczej. W szeregu symboliczno-nastrojowych obrazów szyfruje misterium Kr z y ż a. Biblijne aluzje, metaforyka, tok wierszowy oraz przywoływana przez nie aura tajemniczości często nie pozwalają na dokonanie rozróżnienia pomiędzy pasyjną historią Chrystusa a życiem bohatera. Stąd też poeta nie tworzy apokryfów, lecz aktualizując ewangelijne kody, włącza je we współczesną narrację. W istocie wiersze te dzieją się równocześnie na trzech płaszczyznach czasowych: (1) historycznej (biblijnej), obejmującej powszechnie znane dzieje wędrówki na Golgotę; (2) mistycznej (pozaczasowej i uniwersalnej), w której życie każdego chrześcijanina wplecione jest na poziomie duchowym w dzieje Chrystusa; (3) lirycznej – konkretne „ja” podejmuje trud upodobnienia się do ewangelicznego Mistrza (naśladowanie figuratywne). Przyjrzyjmy się, jak to wygląda w praktyce w wierszach z lat 1993–1998, a więc w barokowo-romantycznych tomach: Nieudana pielgrzymka (1993), Partyzant prawdy (1996) oraz Na krańcu długiego pola (1998).
Kwartalnik Nowy Napis #17
Authors: Urbanowski Maciej , Ciemiera Katarzyna
Published: February 2024

Widzę go, jak prześwituje przez burze z deszczu i burze ze słów. Idzie jak wędrowiec z płachtą na głowie na tle alpejskich szczytów i alpejskich błyskawic z obrazów Caspara Davida Friedricha. Pada deszcz, a on chroni się za zdartym płaszczem ze słów. Jest jesień 1829 roku. Wędrują wraz z Adamem Mickiewiczem i Antonim Edwardem Odyńcem ze Splügen do Chiavenny. Wędrują w drodze do wieczności. O takich wędrowcach przy okazji przemoczonych pończoch wieszcza pisał Jarosław Marek Rymkiewicz w tomie Adam Mickiewicz odjeżdża na żółtym rowerze (2018). Skoro o nich pisał, to był tam wtedy z nimi i nie ma powodu w to wątpić. Gdzie zatem odszedł z tej swojej tutejszej egzystencji 3 lutego 2022 roku? Jak będzie tam, dokąd odszedł? A może należy spytać, co miał na sobie in articulo mortis? Twierdził, że ślady naszej tutejszej egzystencji pozostały w naszych tutejszych przedmiotach. Z wyżej wymienionego tomu esejów wynotowuję zatem: „koszulka śmiertelna stambulska” „to ostatni kawałek tutejszego świata, który Mickiewicz posiadał, kiedy umierał. […] [C]oś, co go w ostatnim momencie dotykało”, „usta istnienia, które całują usta nieistnienia”. Wreszcie – „ostatni pocałunek ostatniej rzeczywistości”. Czym się stał dla Rymkiewicza w lutym onego roku?
„Przepaść nas nie przecina. Przepaść nas otacza”
Authors: Staroń Ireneusz
Published: February 2024

Czy pomyłka zecerska może zrodzić wiersz? Owszem, tak było w przypadku Akrobaty Wisławy Szymborskiej, który ukazał się pierwotnie na łamach „Życia Literackiego” w 1965 roku (nr 33), następnie zaś wszedł do tomu Sto pociech (1967). I choć błąd korektorski nie pojawił się w utworze samej autorki, to stał się istotną inspiracją do myślenia w kategoriach symploki nie tyle jako tropu, ile pewnej filozofii mimesis biorącej swój początek z pism Platona. Jednak zanim przejdziemy do szczegółowego wyjaśnienia tej kwestii, wypada zacytować słowa samej Szymborskiej. Tak o genezie Akrobaty mówiła jego twórczyni:

Pomysł wziął się stąd, że czytałam akurat jakiś tomik wierszy, gdzie wskutek błędu korektorskiego spójnik został umieszczony dwukrotnie, raz na końcu, raz na początku następnego wiersza. Zauważyłam, że to powtórzenie daje efekt jak gdyby huśtania. I wtedy przyszło mi na myśl, żeby napisać wiersz o wysiłku i zarazem lekkości ewolucji akrobatycznych i że właśnie owo balansowanie spójników będzie niejako odpowiednikiem huśtania na trapezie.