bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing Smart Home Security and Privacy: Integrating Blockchain and Machine Learning
Authors: Sheng Jianwen
Published: November 2024

Abstract. A smart home is a type of home device connected through the Internet of Things (IoT) technology. With the rapid development of IoT applied to smart homes, this brings great convenience to people and also raises some privacy and security issues. As IoT collects privacy and a large amount of data about users that may be stolen by unscrupulous people through some cyberattacks, people are beginning to pay more and more attention to the security of the smart home. Blockchain is a distributed database technology that stores data in the form of blocks and uses cryptographic methods to ensure the security and integrity of the data. And mechanical learning can detect some network attacks. This study proposes a smart home architecture that integrates blockchain technology and mechanical learning. Combining blockchain technology, machine learning, and smart homes can effectively identify some cyber attacks while ensuring privacy and security so that people can take appropriate measures.
The Approaches to Predict Stock Prices by Random Forest
Authors: Sun Zelin
Published: November 2024

Abstract. People are always curious about how to predict the stock prices, various type of prediction tools are introduced to help people explore the trend of the stock price movement. With the development of the machine learning, there are more and more models and methods that we can use to predict the stock prices, while Random Forest, a typical machine learning algorithm, will be discussed in this article to examine its performance in the stock market. The data utilized in this study is sourced from Yahoo Finance, with several additional indicators computed and incorporated into feature set of the Random Forest model. To evaluate its performance, a comparison between the Random Forest model and the simple linear regression model is going to be conducted, which is a considerably basic model and serves as a benchmark for the minimum returns individuals can expect. The RMSE and MAPE will be compared firstly, which can help us assess which model demonstrates superior predictive accuracy, while the ROI derived from the strategy based on these models predictions will serve as a measure of their practical performance in the stock market. Collectively, this data will substantiate that Random Forest is indeed an effective model that is capable of assisting individuals in achieving greater profits.
Implementation of Deep Learning in Computer Version
Authors: Guo Zhiyuan
Published: November 2024

Abstract. Artificial intelligence's deep learning (DL) sector has revolutionized image processing, particularly in the area of autonomous driving. As deep learning and convolutional neural networks in particular, i.e., progresses and becomes more and more superior to traditional methods for object detection and semantic segmentation, applications of deep learning in autonomous driving are becoming increasingly prominent. This study investigates several deep learning models, including Transformers, Recurrent Neural Networks and Convolutional Neural Networks, with a focus on their usage in real-time vehicle trajectory prediction, item detection, and scene analysis. Principal findings show that while RNNs and LSTMs improve temporal tasks like traffic predictions, CNNs are still able to evaluate high-dimensional video data for real-time object detection. When accelerated by FPGA, recent Transformer models, such Vision Transformers (ViT), offer better accuracy in picture categorization and real-time object detection, particularly in complex driving circumstances. Despite these improvements, issues like processing costs and model robustness in adverse environments persist. Subsequent investigations aim to improve the generality and efficiency of the model for real-world uses. These results demonstrate how deep learning can be utilized in a novel way to increase the effectiveness and safety of autonomous cars.
Leveraging AI and Machine Learning Models for Enhanced Efficiency in Renewable Energy Systems
Authors: Wen Xin , Shen Qi , Wang Shikai , Zhang Haodong
Published: November 2024

Abstract. Artificial intelligence (AI) and machine learning (ML) have great potential in the management and optimization of renewable energy systems, through more in-depth AI-assisted analysis of store demand in the energy system, and through active learning models for energy optimization and scheduling. Among them, artificial intelligence and active learning can be combined to improve the utilization efficiency of renewable energy in a high range. In particular, recurrent neural network RNN and long- and short-term memory network LSTM in active learning can be used to predict energy and power demand, so as to achieve more effective intelligent power management and system optimization. Two of these models have their own advantages. LSTM and other active learning models can optimize the long-term dependence of traditional time series models and provide more efficient and accurate prediction model results for wind power forecasting and management and other renewable energy forecasting tasks. This study shows that compared with the traditional model, the LSTM model has a high advantage in processing long-term relationships and complex time series data, and the prediction results are more accurate and obvious. Through the dual combination of artificial intelligence and machine learning for renewable energy, this study provides theory, support and certain experimental guidance for the innovation of global energy systems, so as to make certain contributions to the development of renewable energy.
Prediction of Underwater Airworthiness Zone Based on GA-BP Neural Network
Authors: Zhao Chunsi , Huang Binghao , Li Shushi , Peng Feng , Duan Junyan , Guo Li
Published: November 2024

Abstract. The classification and prediction technology of adaptation zones for underwater navigation and positioning is of strategic significance. Gravity anomaly occurs due to the uneven density distribution inside the Earth, leading to a difference between the observed and theoretical normal gravity values. Areas with significant gravity anomaly changes enable high-precision positioning for navigation systems, while relatively flat changes result in lower positioning accuracy. Thus, establishing an adaptive zone classification prediction model applicable to various regions is crucial for ensuring the navigation accuracy of underwater vehicles. This article uses genetic algorithm to improve the robustness and convergence speed of BP neural network, establishes a GA-BP neural network underwater navigation adaptation zone prediction model, and obtains good gravity anomaly prediction effect. Based on this result, the adaptation zone can be predicted.
A Review of the Limitations of Language Models in NLP
Authors: Zhang Xuantong , Li Binyu
Published: November 2024

Abstract. In the field of Natural Language Processing (NLP), large neural language models have successfully been applied to a variety of tasks, including machine translation and reading comprehension. These models often learn the structure of language (such as grammar and semantics) by predicting the next word or character. However, there's an overly optimistic assessment of the current state of natural language understanding, which assumes that models can handle text at a semantic level. This article primarily explores the successes of large neural language models (such as BERT and GPT-2) in numerous tasks that require the understanding of linguistic meaning in the domain of NLP. Language models trained purely on form cannot learn meaning, as understanding meaning involves the relationship between linguistic form and non-linguistic communicative intent. The article aims to guide scientific research in the field of Natural Language Understanding (NLU) by clearly distinguishing the concepts of form and meaning. The learning, generalization, and other capabilities of different models under various attributes show significant differences, suggesting that a combination of different models and properties can achieve unexpected results. The simple learning combinations of some models may offer new insights into the understanding of linguistic meaning by models.
Artificial Intelligence and Its Transformative Impact on Modern Politics
Authors: Li Jinhan
Published: November 2024

Abstract. Since the advent of artificial intelligence (AI) with the Turing test and the Dartmouth Conference, AI has continued to evolve. This evolution has encompassed the introduction of cybernetics, big data, and machine training. However, as the development of artificial intelligence becomes more sophisticated, several issues have begun to emerge. This paper examines the increasing influence of artificial intelligence (AI) in the political sphere over time, specifically examines how AI is being used in the political process, including applications such as sentiment analysis, targeted advertising, and more. It also considers the challenges that have emerged alongside the development of AI, including those related to privacy, voter manipulation, and the transparency of the political process. The paper presents case studies of the 2016 US presidential election and the 2019 Indian general election, which demonstrate how artificial intelligence is exerting a significant influence on democratic political processes, and concludes that as AI becomes increasingly beneficial to human society, concerns are emerging regarding regulations, ethics, political involvement, and other issues. The research addressed the issue of maintaining democratic integrity in politics while advancing artificial intelligence, which offers numerous benefits for modern politics. The paper calls for implementing regulatory policies that would prevent the unethical involvement of artificial intelligence in politics. Additionally, it emphasizes the importance of ensuring that the advantages of artificial intelligence are utilized effectively and fully in the modern political landscape.
Privacy by Design in Machine Learning Data Collection: An Experiment on Enhancing User Experience
Authors: Xu Yang , Liu Yingchia , Wu Jiang , Zhan Xiaoan
Published: November 2024

Abstract. With the development of artificial intelligence (AI) technology, predictive analytics and data-driven decision making are becoming increasingly common across industries. While the widespread use of AI has brought many conveniences, it has also led to profound discussions about user privacy and data protection. This study aims to explore the application of privacy protection design principles to machine learning data collection and its impact on user experience. The study found that embedding privacy protection measures early in system design can significantly reduce privacy management vulnerabilities and enhance users' trust and satisfaction with the system. This study provides theoretical support and practical guidance for privacy protection in machine learning data analysis and provides a feasible design framework for future user experience optimization.
Advancing Wireless Network: The Role of C-RAN in 5G and Beyond
Authors: Sheng Xiaolong
Published: November 2024

Abstract: The rapid evolution of mobile communication technologies, particularly with the transition from 5G to 6G, has heightened the demand for higher data capacity, lower latency, and improved network reliability. Traditional Distributed Radio Access Networks (D-RAN) struggle to meet these requirements, creating a gap that has led to the adoption of Cloud Radio Access Network (C-RAN) as the mainstream deployment model. The approach involves a combination of literature review and technological evaluation to assess the scalability and security challenges posed by C-RAN. Simulation models were employed to evaluate the performance of Wavelength Division Multiplexing (WDM) and Free Space Optical (FSO)- millimeter-wave (mmWave) integration in terms of network resilience and resource optimization. Despite its advantages, such as enhanced spectral efficiency and reduced energy consumption, C-RAN faces significant challenges related to high fiber-optic infrastructure demands and complex data processing requirements. The findings highlight C-RANs potential to meet the needs of 6G networks by optimizing resource allocation and enhancing network resilience. However, further advancements are required to overcome existing scalability and security issues. These insights underline C-RANs pivotal role in the future of wireless communication, driving the evolution toward autonomous and highly adaptive network architectures in 6G, capable of meeting future communication demands.
Lightweight Research on Wireless Charging System for Unmanned Aerial Vehicles Based on High Efficiency
Authors: Sheng Kaichen
Published: November 2024

Abstract: Unmanned aerial vehicles (UAVs) are characterized by safety, flexibility, and economy, and are widely used in many fields. At present, due to the limitation of UAV loads and the bottleneck of battery technology, UAVs can't carry out missions for a long time. The wireless charging system for UAVs has the advantages of safety, flexibility, automation, and environmental adaptability, so it has gained wide attention. Electromagnetic induction wireless energy transmission system is a system that transmits electrical energy through a magnetic field, and in electromagnetic induction wireless energy transmission system, it is necessary to reach the goals of lightweight, high efficiency, anti-skewing, and modularization. In order to achieve the goals of high efficiency and anti-deviation, this paper adopts three sets of series-connected rounded rectangular coils as the transmitting stage to improve the charging efficiency and anti-deviation ability; in order to achieve the goal of lightweight, this paper reduces the weight by changing the material of the magnetic core, and using the annulus core amorphous alloy core; in order to achieve the goal of modularity, this paper designs to carry multiple sets of receiving coils, which can be switched on and off according to the demand in order to satisfy the different power requirements. Finally, a bilateral LCC compensation topology network is established to control the input and output currents to achieve the design goal. The method proposed in this paper helps to realize the automatic charging of UAV and improve the endurance of UAV, so as to enhance the working hours and inspection range of UAV, and make UAV capable of doing more work.
A Novel Deep Convolutional Network Based on Transfer Learning for Lung Image Disease Diagnosis
Authors: Feng Shuo , Wu Ximei , Li Lixian
Published: November 2024

In this study, a deep learning model based on transfer learning is proposed, which uses the pre-trained ResNet50 architecture to automatically classify X-ray images of normal, bacterial and viral pneumonia. In the experimental process, after 20 rounds of training, the accuracy of the model is close to 100% in both the verification set and the test set. The changes of loss function and accuracy curve show that the model learns and converges rapidly, and the performance of verification set is consistent with that of training set, and there is no obvious over-fitting phenomenon. In addition, the classification results are further verified by confusion matrix and classification report, which shows that the classification accuracy of the model on three types of pneumonia is extremely high, with an overall accuracy rate of 99.6%, and the accuracy rate, recall rate and F1 score are close to 1.00. Although there is slight misclassification in a small number of samples of bacterial and viral pneumonia, the overall results show that the model has strong robustness and generalization ability in medical image classification tasks. The research results show that the model performs well in pneumonia classification, which provides an important reference for future medical image analysis and automatic diagnosis.
BiLipschitz homogeneous hyperbolic nets
Authors: Bishop Christopher J.
Published: November 2024

We answer a question of Itai Benjamini by showing there is a \(K< \infty\) so that for any \(\epsilon >0\), there exist \(\epsilon\)-dense discrete sets in the hyperbolic disk that are homogeneous with respect to \(K\)-biLipschitz maps of the disk to itself. However, this is not true for \(K\) close to \(1\); in that case, every \(K\)-biLipschitz homogeneous discrete set must omit a disk of hyperbolic radius \(\epsilon(K)>0\). For \(K=1\), this is a consequence of the Margulis lemma for discrete groups of hyperbolic isometries.
Peran Komunikasi Verbal dan Nonverbal Dalam Dukungan Sosial Teman Sebaya Terhadap Resiliensi Mahasiswa
Authors: Anhar Anhar , Tasya Tasya , Selviana Selviana , Tanjung Karina
Published: November 2024

This study examines the role of verbal and non-verbal communication in peer social support and its impact on student resilience, an area that is still rarely studied. Academic and social challenges during lectures demand high resilience, and peer support is believed to strengthen this resilience. This study uses a quantitative approach and survey method, data from 15-20 students of various study programs at the Balikpapan College of Economics was collected through an online questionnaire covering aspects of demography, communication, and resilience. The analysis of the research data was carried out in a descriptive manner. The results showed that verbal communication, such as motivation, as well as non-verbal communication, such as eye contact, were significant in supporting resilience. The combination of these two forms of communication helps students cope with academic stress. These findings propose a communication-based mentoring program in educational institutions to improve student resilience and psychological well-being
Pengaruh Penerapan Model Project Based Learning Terhadap Hasil Belajar Siswa pada Mata Pelajaran Biologi Kelas X di SMA Negeri 1 Sutera
Authors: Mailanda Aqsa , Hidayati Abna , Zen Zelhendri , Kurnia Reni
Published: November 2024

This article discusses the effect of the application of the Project Based Learning (PBL) model on student learning outcomes in biology subjects. The research method used is quantitative with a quasi-experimental design. This research was conducted in a high school by involving a group of students who were divided into two groups, namely an experimental group that applied the PBL model and a control group that used conventional methods. The instruments used are tests, observations, and questionnaires. The resulting data was analyzed using descriptive statistical tests and t-tests. The results showed that the application of PBL significantly improved students' understanding of biology concepts, critical thinking skills, and learning motivation. These findings indicate that PBL can be an effective alternative in teaching biology, increasing student engagement, and resulting in more meaningful learning
Peningkatan Minat Baca Peserta Didik Melalui Program Literasi di SDN Sidokare 1 Sidoarjo
Authors: Firmansyah Alfian , El-Yunusi Muhammad Yusron
Published: November 2024

Reading interest is one of the key factors in developing learners' literacy skills. A literacy program can be one solution to this problem that not only focuses on teaching reading but also creates an atmosphere that supports reading interest. The purpose of the study was to find out how much impact the school literacy program has on students' interest in reading at SDN Sidokare 1 Sidoarjo. This research uses qualitative research methods with the target of Principals, Teachers and students in the environment of SDN Sidokare 1 Sidoarjo with data collection techniques through interviews, observation and documentation through recording and collecting data from the subject of observation. Based on the results of the research, the school library program has a positive impact on students' interest in reading. There are obstacles faced by limited resources, both in the form of books, facilities and infrastructure, technology and qualified educators. School efforts in dealing with these obstacles by providing socialization, adding facilities and infrastructure and collaborating with related agencies (regional library office) to support the activeness of students' interest in reading at SDN SIdokare 1.
A review on Diversity, Mechanism of Action and Evolutionary Significance of Antimicrobial Peptides
Authors: Muhammad Noor , Ansar Waiza , Ullah Arif , Liaqat Iram , Nazir Zahid
Published: November 2024

Antimicrobial peptides (AMPs) are small, evolutionarily main peptides that widely exist in rich diversity across nature and play a significant role in the innate immunity of various taxa from invertebrates to vertebrates. They are equally targeted as the newest discovered antibiotics against various prokaryotes, including bacteria, viruses, fungi, and parasites. AMPs show broad-spectrum potential with high efficacy and low toxicity via in vivo studies. Undoubtedly, this also confers their specific mechanism of action (MOA) and unique but distinct structures. Already, many studies have reported that AMPs possess diverse MOA against various pathogenic microbes. AMPs also encourage the cells to enhance wound healing, programmed cell death, angiogenesis, and produce chemokines. However, the associated risk is the evolution of resistance to AMPs could lead to possible danger to inherent immunity. From an evolutionary perspective, they are usually considered nonspecific with redundant functions due to the fact that they are easily duplicated and produce pseudogenes, thus showing less evolution at the primary amino acid level. However, the microbial resistance risk against conventional antibiotics can be minimized by using AMPs efficiently and sustainably. Understanding the nature and evolution of AMPs will be beneficial as well. The current review focused on antimicrobial peptides' diversity, history, MOA, and evolutionary significance.
Խմբավարի «Տասը պատվիրանքները». Կոմիտասի մտորումները դիրիժորական արվեստի շուրջ
Authors: Հարությունյան Լիլիթ
Published: November 2024

Կոմիտաս Վարդապետի ձեռագրային ժառանգությունը մշտապես գտնվել է հայկական երաժշտատեսական մտքի ականավոր ներկայացուցիչների ուշադրության կենտրոնում և դարձել է հայ երաժշտագիտության կարևոր ճյուղերից մեկի՝ կոմիտասագիտության զարգացման հիմնական շարժառիթը ։ Բացի բուն ձեռագրային ֆոնդից՝ Երևանի Եղիշե Չարենցի անվան գրականության և արվեստի թանգարանում պահվում է նաև Կոմիտասի անձնական գրադարանը, որի միավորների զգալի քանակություն ևս պարունակում է Կոմիտասի ձեռագիր նշումներ ։ Երբեմն դրանք միայն ընդգծումներ են, կարճ թարգմանություններ կամ նկատողություններ գրքի տեքստի վերաբերյալ, բայց երբեմն էլ հանդիպում են ծավալուն մտքեր, որոնք առատորեն շարադրված են հենց գրքի լուսանցքներում:
Komitas Vardapet’s manuscripts have always been at the center of attention of prominent Armenian musicologists and have become the main motive for the development of one of the important branches of Armenian musicology, Komitas studies. In addition to the actual manuscript fund, the Yeghishe Charents Museum of Literature and Art in Yerevan houses Komitas’s personal library, a significant number of units of which contain Komitas’s handwritten notes. Sometimes they are only highlights, short translations or remarks about the text of the book, but sometimes there are extensive thoughts that are abundantly written in the margins of the book itself.
THE CORRELATION BETWEEN HUMBLENESS AND GRACE (SEEN AS EMPOWERMENT) ILLUSTRATED IN THREE BIBLICAL EXAMPLES
Authors: MIHAI Delia Doina
Published: November 2024

For a long time in the Church’s tumultuous history, legalism was equated with the unbiblical attempt of some believers to “earn” their salvation through good deeds, to which they added all sorts of “salvation”-charged rituals, thus adding to what Christ had already done for them (and, consequently, for all of us) at the Cross. This pattern of faith-based-on-good-works often places a strong emphasis on the external or formal elements, expanding them into normative rules, followed by severe discipline for those who don’t live up to its standards. Beyond the mere doctrinal issues, however, the so-called “legalism” also contains a practical, implicit aspect, which characterizes the attitude of those well-intentioned (yet immature) Christians, who –out of their inner weaknesses or even sincere desire to be as productive as possible –focus on reaching certain standards of holiness and service that turn the walk1with Jesus into a “religious marathon”: ‘Driven to do more and more to gain a shadow of acceptance, many among God’s children are restless, fearful, guilt-ridden slaves.’2But what if there could be another way? A way in which we can rest while doing His will? (In other words, entering into “His rest” and resting from “our works”, as the biblical author states in Hebrews 4:10...)
NATURE AND DIVINITY IN THE SELECTED POEMS OF K. SAREEN RAJ: A CRITICAL STUDY
Authors: Hussain Dr. M. D. , Hafeez Unnisa Dr. Fatima
Published: November 2024

What is life without nature, the beauty, the splendor that gives us joy and keeps us moving ? Nature is nothing but the reflection of the almighty God, whose presence is felt everywhere. Nature poems celebrate the beauty and complexity of the natural environment, often portraying landscapes, seasons, and wildlife with vivid imagery and emotional depth. They explore concepts of growth, renewal, and decay, mirroring the cycles of life observed in the natural world. They evoke sensory experiences, inviting readers to immerse themselves in the sights, sounds, and textures of the natural world. Through descriptive language and metaphors, the poets capture the essence of mountains, forests, rivers, and skies, portraying them as both majestic and serene. Themes in nature poetry encompass a wide range of emotions and ideas. The present article titled, “Nature and Divinity in the Selected Poems of K. Sareen Raj: A Critical Study” explores the nature poems written by K. Sareen Raj, from the book titled, “Canopy of Heaven,” a collection of poems. The article studies the poems “Under the Canopy of Heaven”, “The Quiet Land”, “The Moon”, “The Yellow Garden”, and “A Winter Morning”. It studies the major themes of Sareen Raj’s selected poems, most importantly the mystical element of the divine presence in nature. It critically analyzes the poems and sheds light on the significant aspects of the poems. An attempt is made to understand the harmony, balance found in nature and its significance in human life.
Potential use of virtual reality technologies for opioid use disorder treatment
Authors: Garett Renee , Young Sean D.
Published: November 2024

The opioid epidemic is a serious national public health crisis. Although effective medications are available to treat opioid use disorder, there are low rates of uptake and treatment retention. To mitigate these problems, novel engineering devices, such as using virtual reality (VR), warrant examination. Certain opioid use disorder (OUD) populations may especially benefit from virtual reality to assist with treatment initiation and retention, such as incarcerated persons living in pre-release facilities, adolescents and young adults, and patients of methadone treatment facilities. However, prior to implementing VR in research and the community, issues such as side effects (e.g., VR-related nausea) need to be considered. This manuscript provides a brief review, identifies potential OUD-related populations that might most benefit from VR, and discusses considerations needing addressing prior to widescale implementation of VR for OUD.
An analytical view on Unmanned Aircraft Systems
Authors: Sharma Arunima
Published: November 2024

Unmanned Aircraft Systems (UAS) is a booming technology with a future perspective and does have a huge potential to transfigure warfare and enable up-to-date civilian applications. It furthermore matures in a technological way as to be impinged into the civil society. In 2010, the importance of scientific applications in the respective field was demonstrated by DOD in the contemporary years. In recent years, UAS has played an integral role in a number of missions that are public, like law enforcement, which is local, board surveillance, weather monitoring, wildlife surveys, and military training. UAS do force some challenges that are numbered as lacking a pilot who is on-board in order to see and hence avoid supplemental aircraft, and furthermore, the extensive discrepancy in the missions related to UAS, and in order to implement the operations in the NextGen time frame impinged in NAS, the capabilities of the respective topic must be communicated. The applications of UAS are numbered as Ariel Mapping and Meteorology, intelligence, remote sensing, surveillance and reconnaissance, environmental monitoring and agriculture, border security, security applications and law enforcement, counter insurgency, electronic attacks, attack strikes, communication relays, target identification, and designation. Via this survey paper, it can be concluded that UAS is emerging as a valuable and helpful technology having tremendous potential for revolting warfare and enabling new applications w.r.t the UAS field.
Adaptive beamforming approach for secure communication in 5G network
Authors: Sharma Arunima
Published: November 2024

The beamforming approach has been emerging as a very important concept for next generation networks. In addition to the improved channel capacity, spectral efficiency, energy efficiency, secrecy rate and secrecy outage probability, the upcoming fifth generation network mainly aims at enhancing the parameters of the channel for secure communication. In this paper, we have implied the allocation of resource blocks adaptively using HMM with a beamforming approach in an intruded network. A system model for secure communication in an intruded network has been discussed using a beamforming approach with the main motive being to provide a security scenario to the data which is transmitted over an unsecured channel in a network. In addition to this we have used the approach of HMM for allocating the resource blocks to the users which have been demanded and applied in order to avoid the intrusion and wastage of resource blocks.
Impact of Mpox on Children's Health: A Comprehensive Overview
Authors: Andariska Ni Made Gita
Published: November 2024

Mpox (formerly monkey pox) is an emerging zoonotic disease caused by infection with the Mpox virus, which affects both humans and animals. The disease is usually self-limiting, but severe illness can occur in certain groups especially children, and people who are immunocompromised or pregnant. In recent years, rapid globalization, population movement and deepening trade networks have contributed to the international spread of Mpox, resulting in outbreaks in various countries around the world. Based on information from previous outbreaks, children may be more susceptible to severe manifestations of the disease, leading to sepsis, encephalitis, and even death or long-term disability. In addition, the reports recommends that babies born to mothers who had Mpox virus while pregnant should be properly monitored in specialized care facilities. This overview presents a thorough review of Mpox, including its transmission patterns, epidemiology and pathogenesis. This review aims to provide updated information about Mpox virus for designing better treatment.
Enhancing retrieval performance of embedding models via fine-tuning on synthetic data in RAG chatbot for Vietnamese military science domain
Authors: Nguyen Xuan Bac  , Luu Van Sang  , Nguyen Duc Vuong  , Luong Quoc Le  , Dang Duc Thinh
Published: November 2024

Retrieval-Augmented Generation (RAG) is a technology that combines information retrieval with large language models, enabling chatbots to provide accurate answers by querying relevant documents from a data repository before generating responses. While RAG chatbot has demonstrated effectiveness in many applications, there are still limitations in specialized Vietnamese data domains, particularly in the military science field. To address this challenge, this paper proposes a framework for fine-tuning embedding models using synthetic datasets generated by ChatGPT to enhance retrieval performance in a Q&A application focused on the history of the Institute of Information Technology (IoIT). Our approach evaluates 11 popular embedding models and shows a significant average improvement of 18.15% in the MAP@K metric. The resulting IoIT history Q&A chatbot, developed with fine-tuned embedding models and the Vietnamese language model Vistral-7B, outperforms chatbots utilizing OpenAI's embedding models and ChatGPT. These findings highlight the potential of RAG chatbot technology for advancing information retrieval applications in specialized fields like military science.
A novel eight-way power combiner on suspended substrate stripline for Ku-band applications
Authors: Pham Thanh Cong  , Vu Le Ha  , Luong Duy Manh
Published: November 2024

This work proposes a novel 8-way power combiner implemented using suspended substrate stripline technology for Ku-band applications. The equivalent circuit of the design is analyzed to obtain parameters for the physical realization of the structure. The combiner is well matched at both input and output ports with VSWR better than 1.6:1, achieves low insertion loss of less than 1dB and isolation of more than 16.8 dB over the range from 12 GHz to 18 GHz. The structure is also able to handle high thermal dissipated power due to its housing, hence, suitable to find application in high power-amplifier subsystems.
Green synthesis of selenium nanoparticles using aloe leaf extract and evaluation of acute toxicity of materials
Authors: Le Minh Tri  , Vu Tri Thien
Published: November 2024

The element selenium (Se) is of great importance in many fields, such as physics, chemistry, and biology. Selenium is also an important trace element, which has a great influence on biological systems due to its antioxidant, anticancer and antiviral activities. Selenium deficiency can lead to a number of serious diseases such as cancer, cardiovascular disease, immune disorders, or cause immunosuppression. Selenium nanoparticles are much more biologically active than other forms of selenium that exist in the form of inorganic salts or in organic compounds. In this paper, selenium nanoparticles are synthesized using a green method using aloe vera leaf extract which acts as a reducing agent and dispersion stabilizer. The properties of the post-synthetic materials analyzed by UV-vis spectroscopy, selected area diffraction (SAED), scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive X-ray spectroscopy (EDX), X-ray photoelectron spectroscopy (XPS) showed that the synthesized selenium nanoparticles were in the range of 30 - 70 nm. The results of the assessment of acute toxicity in rats showed a lethal concentration (50% death of mice) of 10,374 mg/kg.
Comparative study of living donor kidney transplants: Right vs left
Authors: Khan Taqi , Ahmad Nadeem , Iqbal Qaisar , Hassan Muneeb , Asnath Lajward , Khan Naveed , Shakeel Sajid
Published: November 2024

BACKGROUND

Transplant teams often hesitate to use the right kidney (RK) in living donor (LD) transplants due to the complexities of anastomosing the short, thin-walled right renal veins, which can potentially lead to graft loss or graft dysfunction. Nevertheless, circumstances may arise where selecting the RK over the left kidney (LK) is unavoidable. Consequently, it is crucial to thoroughly examine the implications of such a choice on the overall transplant outcome.

AIM

To compare transplant outcomes between recipients of RK and LK while examining the factors that influence these outcomes.

METHODS

We retrospectively analyzed data from adult patients who received LD kidney transplants involving meticulous patient selection and surgical techniques at our center from January 2020 to December 2023. We included all kidney donors who were over 18, fit to donate, and had undergone diethylenetriamine pentaacetic acid split function and/or computed tomography based volumetry. The variables examined comprised donor and recipient demographics, and outcome measures included technical graft loss (TGL), delayed or slow graft function (SGF), and post-transplant serum creatinine (SC) trends. We used a logistic regression model to assess the likelihood of adverse outcomes considering the donor kidney side.

RESULTS

Of the 250 transplants performed during the period, 56 (22%) were RKs. The recipient demographics and transplant factors were comparable for the right and LKs, except that the donor warm and cold ischemia time were shorter for RKs. TGL and SGF each occurred in 2% (n = 1) of RKs and 0.5% (n = 1) of LKs, the difference being insignificant. These complications, however, were not related to the venous anastomosis. One RK (2%) developed delayed graft function after 48 hours, which was attributable to postoperative hypoxia rather than the surgical technique. The post-transplant SC trend and mean SC at the last follow-up were similar across both kidney sides.

CONCLUSION

The donor kidney side has little impact on post-transplant adverse events and graft function in LD transplants, provided that careful patient selection and precise surgical techniques are employed.
Large-for-size syndrome prophylaxis in infant liver recipients with low body mass
Authors: Semash Konstantin , Dzhanbekov Timur
Published: November 2024

Transplantation of the left lateral section (LLS) of the liver is now an established practice for treating advanced diffuse and unresectable focal liver diseases in children, with variants of the LLS primarily used in infants. However, the surgical challenge of matching the size of an adult donor's graft to the volume of a child's abdomen remains significant. This review explores historical developments, various approaches to measuring the required functional liver mass, and techniques to prevent complications associated with large-for-size grafts in infants.
Insights into gastrointestinal manifestation of human immunodeficiency virus: A narrative review
Authors: Moliya Pratiksha , Singh Anmol , Singh Navdeep , Kumar Vikash , Sohal Aalam
Published: November 2024

Human immunodeficiency virus (HIV) modifies CD4-positive cells, resulting in immunodeficiency and a wide range of gastrointestinal (GI) manifestations. The burden of HIV-related GI illnesses has significantly evolved with the widespread use of antiretroviral therapy (ART). While ART has effectively reduced the occurrence of opportunistic infections, it has led to an increase in therapy-related GI illnesses. Common esophageal conditions in HIV patients include gastroesophageal reflux disease, idiopathic esophageal ulcers, herpes simplex virus, cytomegalovirus (CMV), and candidal esophagitis. Kaposi’s sarcoma, a hallmark of acquired immunodeficiency syndrome, may affect the entire GI system. Gastritis and peptic ulcer disease are also frequently seen in patients with HIV. Diarrhea, often linked to both opportunistic infections and ART, requires careful evaluation. Bloody diarrhea, often a sign of colitis caused by bacterial infections such as Shigella or Clostridium difficile, is prevalent. Small bowel lymphoma, although rare, is increasing in prevalence. Anorectal disorders, including proctitis, fissures, and anal squamous cell carcinoma, are particularly relevant in homosexual men, underlining the importance of timely diagnosis. This review comprehensively explores the epidemiology, pathogenesis, and treatment considerations for the various GI disorders associated with HIV, highlighting the importance of accurate diagnosis and effective treatment to improve outcomes for HIV-infected patients.
Convergence of COVID-19 and recurrent stroke: In-hospital mortality risks explored
Authors: Nagoba Basavraj S , Dhotre Shree V , Gavkare Ajay M , Mumbre Sachin S , Dhotre Pradnya S
Published: November 2024

This editorial comments on the article by Desai et al , which investigates the impact of coronavirus disease 2019 (COVID-19) on in-hospital mortality among patients with recurrent stroke using data from the 2020 National Inpatient Sample. The findings reveal significantly higher mortality rates in COVID-19-positive patients compared to non-COVID-19 patients, particularly among middle-aged individuals, males, and ethnic minorities. This editorial explores the underlying mechanisms contributing to these outcomes and discusses the clinical implications for targeted management strategies in high-risk groups. The results emphasize the need for comprehensive approaches to mitigate the heightened risks faced by recurrent stroke patients during the COVID-19 pandemic.
Review on Semi-Autonomous Robots for Satellite Maintenance and Refueling
Authors: Chandru P A , Gutierrez Arianne , Valenzuela Cynthia , Shetty Poorvi , Kumar Shristy
Published: November 2024

As the number of satellites in Earth's orbit
continues to grow, the need for efficient satellite servicing
solutions becomes increasingly pressing. Currently, about
9,900 satellites are in orbit, with over 3,300 of these being
inactive, posing a threat as space debris. Traditional methods
for satellite maintenance and refueling are complex,
expensive, and risky. The development of semi-autonomous
robots, powered by advancements in artificial intelligence
and robotics, presents a more efficient alternative. These
robots can perform complex maintenance and refueling tasks
with minimal human intervention, reducing costs and risks
associated with satellite servicing. This paper investigates the
design, technological advancements, and operational
strategies behind these robots, and how they can mitigate
space debris while enhancing the sustainability of satellite
operations.
Key Words: Maintenance, Satellites, Refuelling, Robots.
Analisis Strategi Pengelolaan Dana Kampung
Authors: Iek Mesak , Maray Luis Zadrak , Iek Anselmus S. P.
Published: November 2024

Tujuan penelitian ini untuk menganalisis tingkat kepatuhan implementasi UU No. 6 tahun 2014, dan pasal 100 PP No. 43 Tahun 2014 pada aparat kampung, menganalisis manfaat dana kampung bagi masyarakat, dan menganalisis kendala-kendala yang dihadapi dalam mengelola dana Kampung di Distrik Aitinyo Utara. Tahun anggaran yang di telusuri yaitu tahun 2019-2021. Penelitian ini dilaksanakan pada 12 kampung pada Distrik Aitinyo Utara Kabupaten Maybrat Provinsi Papua Barat. Teknik pengambilan sampel menggunakan metode purposive sampling dengan pertimbangan tertentu yaitu aparat kampung dan masyarakat kampung yang memahami proses perencanaan dan pelaksanan pembangunan kampung. Alat analisi yang digunakan adalah analisis deskriptif. Hasil penelitian menunjukkan bahwa alokasi dana kampung pada 12 kampung distrik Aitinyo Utara kurang patuh pada regulasi, terbukti dengan dana desa sebelum tahun 2020 semuanya digunakan untuk pembangunan fisik, namun sejak tahun 2020 – 2021 alokasi dana desa sudah mengarah kepada tingkat kepatuhan, walaupun belum patuh 100 persen. Alokasi untuk peningkatan kapasitas SDM aparat kampung mulai dianggarkan di tahun 2022. Alokasi dana kampung pada 12 kampung di Distrik Aitinyo Utara persentasenya sama yaitu 40 persen untuk Bantuan Langsung Tunai, 20 persen untuk ketahanan pangan, 8 persen untuk penanganan covid-19 dan 25 persen untuk kebutuhan tidak terduga. Pengelolaan Dana Kampung memberi manfaat yang sangat besar bagi masyarakat di Distrik Aitinyo Utara, namun belum maksimal.Kendala yang dihadapi dalam pengelolaan dana kampung pada 12 kampung yaitu beberapa kampung kurang transparan dalam pengelolaan dana kampung karena hanya dilakukan oleh kepala kampung dan bendahara, hal ini terjadi sebagai akibat dari bendahara selalu diangkat berkisar “keluarga dalam”. Hal lainnya yaitu kepala kampung dari “keturunan bobot” sangat berpengaruh pada pengelolaaan dana kampung yang sangat tertutup.
Perlindungan Hukum terhadap Debitur Pemilik Jaminan dalam Penyelesaian Sengketa Lelang Hak Tanggungan Apabila Kreditur Beritikad Tidak Baik
Authors: Prasetyo Bony , Hartana Hartana , Nyoman Tio Rae G.
Published: November 2024

Sengketa lelang hak tanggungan sering kali terjadi akibat eksekusi yang dilakukan secara melawan hukum oleh kreditur. Hal ini menimbulkan kebutuhan akan perlindungan hukum yang tepat bagi debitur. Penelitian ini bertujuan untuk menganalisis penerapan perlindungan hukum dalam penyelesaian sengketa lelang hak tanggungan serta untuk mengidentifikasi tantangan yang dihadapi debitur akibat tindakan kreditur yang beritikad tidak baik. Metode penelitian yang digunakan adalah pendekatan yuridis normatif, yang meliputi studi terhadap peraturan perundang-undangan yang berlaku serta analisis kasus-kasus yang relevan melalui telaah putusan pengadilan. Hasil penelitian menunjukkan bahwa hukum nasional Indonesia belum secara jelas mengatur penyelesaian sengketa eksekusi lelang yang dilakukan secara melawan hukum. Selain itu, terdapat ketidakseragaman dalam putusan pengadilan terkait sengketa ini. Penelitian ini menyimpulkan bahwa diperlukan perbaikan dalam regulasi hukum pertanahan dan perbankan untuk memberikan perlindungan yang lebih baik bagi debitur. Rekomendasi juga diberikan untuk menyusun panduan yang jelas bagi hakim dalam menangani sengketa lelang hak tanggungan.
Del desplazarse en la noche
Authors: Berardi Pedro
Published: November 2024

Rondas nocturnas… propone, a la vez que se cifra en, los pliegues de una cartografía del cine argentino que habilita los desbordes. Sobre los marcos de posibilidades que configuraron los momentos de la modernidad cinematográfica, situados a comienzos de los años 60 y en las dos décadas que enmarcaron el cambio de siglo —por sus aparentes rupturas estéticas e innovaciones del lenguaje propiciadas por la renovación técnica—, indaga en las eclosiones de la sexualidad y sus variantes representaciones visuales, desde una mirada que pone énfasis en las múltiples tensiones que permearon también al gesto de hacerlas visibles.
Una maldición irremediable
Authors: Echave Emilio
Published: November 2024

Título: El Escuerzo
Año: 2023
Duración: 91´
Director: Augusto Sinay 
Guion: Augusto Sinay
Producción: Damián Carretero Seisdedos
Dirección de Fotografía: Martín Heredia Troncoso
Dirección de Sonido: Patricia Tosco
Música Original: Tomas Leonhardt
Datos editoriales #12
Authors: Siragusa Cristina
Published: November 2024

Información y equipo editorial de Revista Toma Uno, número 12, (2024): "Audiovisualidades, naturaleza y afectos".
Rethinking Bodily Expression in Human-Robot Communication: Insights from Sculpture.
Authors: Dunstan Belinda J , Hoffman Guy
Published: November 2024

Sculpture offers a centuries-long tradition of techniques for expressing emotion and movement in a static form. Insights from this field present an opportunity to design robots that express not only through movement, but also via dynamic cues in their static positions. Such cues can suggest motion potential, emotion, and character. This paper presents three principles identified in sculpture techniques that can be applied to robot design: (a) depicting exposure and protection of emotional pivot points in the body, (b) weight distribution, and (c) the revelation of movement mechanisms and tension through flexible skins. We employ the first two of these principles in an interactive design and motion control environment to demonstrate the potential for application to the design of social collaborative robots. We illustrate the third principle via a robot design that uses a flexible fabric skin stretched over rigid and elastic actuation elements. Using insights from sculpture can promote the design of robots from a transdisciplinary perspective by increasing the readability of robot intent and affect even when the robot is not actively moving.