bluuebunny/crossref_metadata_2025 huggingface dataset:
S3DR-Det: A Rotating Target Detection Model for High Aspect Ratio Shipwreck Targets in Side-Scan Sonar Images
Authors: Ma Quanhong , Jin Shaohua , Bian Gang , Cui Yang , Liu Guoqing , Wang Yihan
Published: January 2025

The characteristics of multi-directional rotation and high aspect ratio of targets such as shipwrecks lead to low detection accuracy and difficulty localizing existing detection models for this target type. Through our research, we design three main inconsistencies in rotating target detection compared to traditional target detection, i.e., inconsistency between target and anchor frame, inconsistency between classification features and regression features, and inconsistency between rotating frame quality and label assignment strategy. In this paper, to address the discrepancies in the above three aspects, we propose the Side-scan Sonar Dynamic Rotating Target Detector (S3DR-Det), which is a model with a dynamic rotational convolution (DRC) module designed to effectively gather rotating targets’ high-quality features during the model’s feature extraction phase, a feature decoupling module (FDM) designed to distinguish between the various features needed for regression and classification in the detection phase, and a dynamic label assignment strategy based on spatial matching prior information (S-A) specific to rotating targets in the training phase, which can more reasonably and accurately classify positive and negative samples. The three modules not only solve the problems unique to each stage but are also highly coupled to solve the difficulties of target detection caused by the multi-direction and high aspect ratio of the target in the side-scan sonar image. Our model achieves an average accuracy (AP) of 89.68% on the SSUTD dataset and 90.19% on the DNASI dataset. These results indicate that our model has excellent detection performance.
Array Three-Dimensional SAR Imaging via Composite Low-Rank and Sparse Prior
Authors: Yang Zhiliang , Wang Yangyang , Zhang Chudi , Zhan Xu , Sun Guohao , Liu Yuxuan , Mao Yuru
Published: January 2025

Array three-dimensional (3D) synthetic aperture radar (SAR) imaging has been used for 3D modeling of urban buildings and diagnosis of target scattering characteristics, and represents one of the significant directions in SAR development in recent years. However, sparse driven 3D imaging methods usually only capture the sparse features of the imaging scene, which can result in the loss of the structural information of the target and cause bias effects, affecting the imaging quality. To address this issue, we propose a novel array 3D SAR imaging method based on composite sparse and low-rank prior (SLRP), which can achieve high-quality imaging even with limited observation data. Firstly, an imaging optimization model based on composite SLRP is established, which captures both sparse and low-rank features simultaneously by combining non-convex regularization functions and improved nuclear norm (INN), reducing bias effects during the imaging process and improving imaging accuracy. Then, the framework that integrates variable splitting and alternative minimization (VSAM) is presented to solve the imaging optimization problem, which is suitable for high-dimensional imaging scenes. Finally, the performance of the method is validated through extensive simulation and real data experiments. The results indicate that the proposed method can significantly improve imaging quality with limited observational data.
Interannual Variability and Trends in Extreme Precipitation in Dronning Maud Land, East Antarctica
Authors: Yu Lejiang , Zhong Shiyuan , Jagovkina Svetlana , Sui Cuijuan , Sun Bo
Published: January 2025

This study examines the trends and interannual variability of extreme precipitation in Antarctica, using six decades (1963–2023) of daily precipitation data from Russia’s Novolazarevskaya Station in East Antarctica. The results reveal declining trends in both the annual number of extreme precipitation days and the total amount of extreme precipitation, as well as a decreasing ratio of extreme to total annual precipitation. These trends are linked to changes in northward water vapor flux and enhanced downward atmospheric motion. The synoptic pattern driving extreme precipitation events is characterized by a dipole of negative and positive height anomalies to the west and east of the station, respectively, which directs southward water vapor flux into the region. Interannual variability in extreme precipitation days shows a significant correlation with the Niño 3.4 index during the austral winter semester (May–October). This relationship, weak before 1992, strengthened significantly afterward due to shifting wave patterns induced by tropical Pacific sea surface temperature anomalies. These findings shed light on how large-scale atmospheric circulation and tropical-extratropical teleconnections shape Antarctic precipitation patterns, with potential implications for ice sheet stability and regional climate variability.
Internal Integrated Temperature Sensor for Lithium-Ion Batteries
Authors: Yang Pengfei , Su Kai , Weng Shijie , Han Jiang , Zhang Qian , Li Zhiqiang , Peng Xiaoli , Xiang Yong
Published: January 2025

Lithium-ion batteries represent a significant component of the field of energy storage, with a diverse range of applications in consumer electronics, portable devices, and numerous other fields. In view of the growing concerns about the safety of batteries, it is of the utmost importance to develop a sensor that is capable of accurately monitoring the internal temperature of lithium-ion batteries. External sensors are subject to the necessity for additional space and ancillary equipment. Moreover, external sensors cannot accurately measure internal battery temperature due to packaging material interference, causing a temperature discrepancy between the interior and surface. Consequently, this study presents an integrated temperature sensor within the battery, based on PT1000 resistance temperature detector (RTD). The sensor is integrated with the anode via a flexible printed circuit (FPC), simplifying the assembly process. The PT1000 RTD microsensor’s temperature is linearly related to resistance (R = 3.71T + 1003.86). It measures about 15 °C temperature difference inside/outside the battery. On short-circuit, the battery’s internal temperature rises to 27 °C in 10 s and 32 °C in 20 s, measured by the sensor. A battery with the PT1000 sensor retains 89.8% capacity under 2 C, similar to the normal battery. Furthermore, a PT1000 temperature array sensor was designed and employed to enable precise monitoring and localization of internal temperature variations.
A Review of Miniature Radio Transmitters for Wildlife Tracking
Authors: Toledo Sivan
Published: January 2025

This article surveys the literature on miniature radio transmitters designed to track free-ranging wild animals using emitter-localization techniques. The articles covers the topics of power sources used in such transmitters, including miniature batteries and energy harvesting, techniques for generating the transmitted radio-frequency carrier, techniques for creating short radio pulses and more general on–off schedules, modulation in modern wildlife-tracking transmitters, construction, manufacturing, and tuning techniques, and recent trends in this area. The article also describes the recreation of the first successful wildlife-tracking transmitter, a nontrivial invention that had a profound impact on wildlife ecology, and explores its behavior.
Research on Sensitivity Improvement Methods for RTD Fluxgates Based on Feedback-Driven Stochastic Resonance with PSO
Authors: Wang Rui , Pang Na , Guo Haibo , Hu Xu , Li Guo , Li Fei
Published: January 2025

With the wide application of Residence Time Difference (RTD) fluxgate sensors in Unmanned Aerial Vehicle (UAV) aeromagnetic measurements, the requirements for their measurement accuracy are increasing. The core characteristics of the RTD fluxgate sensor limit its sensitivity; the high-permeability soft magnetic core is especially easily interfered with by the input noise. In this paper, based on the study of the excitation signal and input noise characteristics, the stochastic resonance is proposed to be realized by adding feedback by taking advantage of the high hysteresis loop rectangular ratio, low coercivity and bistability characteristics of the soft magnetic material core. Simulink is used to construct the sensor model of odd polynomial feedback control, and the Particle Swarm Optimization (PSO) algorithm is used to optimize the coefficients of the feedback function so that the sensor reaches a resonance state, thus reducing the noise interference and improving the sensitivity of the sensor. The simulation results show that optimizing the odd polynomial feedback coefficients with PSO enables the sensor to reach a resonance state, improving sensitivity by at least 23.5%, effectively enhancing sensor performance and laying a foundation for advancements in UAV aeromagnetic measurement technology.
Improving Industrial Quality Control: A Transfer Learning Approach to Surface Defect Detection
Authors: Semitela Ângela , Pereira Miguel , Completo António , Lau Nuno , Santos José P.
Published: January 2025

To automate the quality control of painted surfaces of heating devices, an automatic defect detection and classification system was developed by combining deflectometry and bright light-based illumination on the image acquisition, deep learning models for the classification of non-defective (OK) and defective (NOK) surfaces that fused dual-modal information at the decision level, and an online network for information dispatching and visualization. Three decision-making algorithms were tested for implementation: a new model built and trained from scratch and transfer learning of pre-trained networks (ResNet-50 and Inception V3). The results revealed that the two illumination modes employed widened the type of defects that could be identified with this system, while maintaining its lower computational complexity by performing multi-modal fusion at the decision level. Furthermore, the pre-trained networks achieved higher accuracies on defect classification compared to the self-built network, with ResNet-50 displaying higher accuracy. The inspection system consistently obtained fast and accurate surface classifications because it imposed OK classification on models trained with images from both illumination modes. The obtained surface information was then successfully sent to a server to be forwarded to a graphical user interface for visualization. The developed system showed considerable robustness, demonstrating its potential as an efficient tool for industrial quality control.
Classification and Monitoring of Salt Marsh Vegetation in the Yellow River Delta Based on Multi-Source Remote Sensing Data Fusion
Authors: Xu Ran , Fan Yanguo , Fan Bowen , Feng Guangyue , Li Ruotong
Published: January 2025

Salt marsh vegetation in the Yellow River Delta, including Phragmites australis (P. australis), Suaeda salsa (S. salsa), and Tamarix chinensis (T. chinensis), is essential for the stability of wetland ecosystems. In recent years, salt marsh vegetation has experienced severe degradation, which is primarily due to invasive species and human activities. Therefore, the accurate monitoring of the spatial distribution of these vegetation types is critical for the ecological protection and restoration of the Yellow River Delta. This study proposes a multi-source remote sensing data fusion method based on Sentinel-1 and Sentinel-2 imagery, integrating the temporal characteristics of optical and SAR (synthetic aperture radar) data for the classification mapping of salt marsh vegetation in the Yellow River Delta. Phenological and polarization features were extracted to capture vegetation characteristics. A random forest algorithm was then applied to evaluate the impact of different feature combinations on classification accuracy. Combining optical and SAR time-series data significantly enhanced classification accuracy, particularly in differentiating P. australis, S. salsa, and T. chinensis. The integration of phenological features, polarization ratio, and polarization difference achieved a classification accuracy of 93.51% with a Kappa coefficient of 0.917, outperforming the use of individual data sources.
Virtual Node-Driven Cloud–Edge Collaborative Resource Scheduling for Surveillance with Visual Sensors
Authors: Gu Xinyang , Duan Zhansheng , Ye Guangyuan , Chang Zhenjun
Published: January 2025

For public security purposes, distributed surveillance systems are widely deployed in key areas. These systems comprise visual sensors, edge computing boxes, and cloud servers. Resource scheduling algorithms are critical to ensure such systems’ robustness and efficiency. They balance workloads and need to meet real-time monitoring and emergency response requirements. Existing works have primarily focused on optimizing Quality of Service (QoS), latency, and energy consumption in edge computing under resource constraints. However, the issue of task congestion due to insufficient physical resources has been rarely investigated. In this paper, we tackle the challenges posed by large workloads and limited resources in the context of surveillance with visual sensors. First, we introduce the concept of virtual nodes for managing resource shortages, referred to as virtual node-driven resource scheduling. Then, we propose a convex-objective integer linear programming (ILP) model based on this concept and demonstrate its efficiency. Additionally, we propose three alternative virtual node-driven scheduling algorithms, the extension of a random algorithm, a genetic algorithm, and a heuristic algorithm, respectively. These algorithms serve as benchmarks for comparison with the proposed ILP model. Experimental results show that all the scheduling algorithms can effectively address the challenge of offloading multiple priority tasks under resource constraints. Furthermore, the ILP model shows the best scheduling performance among them.
An Independent Suspension and Trafficability Analysis for an Unmanned Ground Platform
Authors: Li Jianying , Xie Yinghong , Huo Yongwang
Published: January 2025

The objective of this paper was to investigate and design a novel vertical- and horizontal-arm independent suspension system aimed at enhancing the autonomous obstacle-crossing capabilities of unmanned ground platforms in complex, unstructured environments such as mountainous regions, hills, and mining areas. By thoroughly considering factors such as the suspension structure design, changes in the centroid position, distribution of driving forces, and dynamic stability analysis, we proposed an innovative suspension structure. An unmanned ground platform model equipped with this suspension system was developed using ADAMS and MATLAB/Simulink. Subsequently, a joint simulation was conducted to validate the performance of the suspension system. The results indicated that the unmanned ground platform could successfully traverse vertical steps up to 370 mm high and trenches measuring up to 600 mm wide. Furthermore, when confronted with intricate obstacles including vertical barriers, trenches, and side slopes, the platform demonstrated exceptional traversing capabilities. In conclusion, the proposed suspension system significantly enhances both the obstacle-surmounting ability and the terrain adaptability of unmanned ground platforms while providing crucial technical support for their deployment in complex unstructured environments.
Characterization of Spatial Cognitive EEG Signals Using Normalized Adjusted Permutation Conditional Mutual Information
Authors: Wan Xianglong , Sun Yue , Wu Zhenzhen , Wen Dong
Published: January 2025

Spatial cognitive ability, a fundamental domain within the human cognitive system, involves the perception, interpretation, and manipulation of spatial environments. This study introduces a new EEG feature extraction algorithm, Normalized Adjusted Permutation Conditional Mutual Information (NAPCMI), to improve the accuracy of spatial cognition assessments. By capturing the symmetry and temporal dependencies within EEG signals during spatial cognition tasks, NAPCMI enhances the ability to extract relevant features. The study validates NAPCMI using a BCI-VR spatial cognition assessment system, incorporating gesture recognition. Results demonstrate that NAPCMI outperforms traditional methods in feature extraction, highlighting its potential for advancing the understanding and assessment of spatial cognitive abilities. The findings also emphasize the significance of specific EEG frequency bands, such as Delta and Beta1, in spatial cognition tasks, further validating NAPCMI’s effectiveness.
Behavior Safety Decision-Making Based on Deep Deterministic Policy Gradient and Its Verification Method
Authors: Zhu Yi , Li Zexin , Wang Jinyong , Zhao Ying , Li Miaoer
Published: January 2025

As an emerging mode of transportation, autonomous vehicles are increasingly attracting widespread attention. To address the issues of the traditional reinforcement learning algorithm, which only considers discrete actions within the system and cannot ensure the safety of decision-making, this paper proposes a behavior decision-making method based on the deep deterministic policy gradient. Firstly, to enable autonomous vehicles to drive as close to the center of the road as possible while sensitively avoiding surrounding obstacles, the reward function for reinforcement learning is constructed by comprehensively considering road boundaries and nearby vehicles. We account for the symmetry of the road by calculating the distances between the vehicle and both the left and right road boundaries, ensuring that the vehicle remains centered within the road. Secondly, to ensure the safety of decision-making, the safety constraints in autonomous driving scenarios are described using probabilistic computation tree logic, and the scenario is modeled as a stochastic hybrid automaton. Finally, the model is verified by the statistical model checker UPPAAL. The above method enables autonomous vehicles not only to independently acquire driving skills across diverse driving environments but also significantly enhances their obstacle avoidance capabilities, thereby ensuring driving safety.
Matching Polynomials of Symmetric, Semisymmetric, Double Group Graphs, Polyacenes, Wheels, Fans, and Symmetric Solids in Third and Higher Dimensions
Authors: Balasubramanian Krishnan
Published: January 2025

The primary objective of this study is the computation of the matching polynomials of a number of symmetric, semisymmetric, double group graphs, and solids in third and higher dimensions. Such computations of matching polynomials are extremely challenging problems due to the computational and combinatorial complexity of the problem. We also consider a series of recursive graphs possessing symmetries such as D2h-polyacenes, wheels, and fans. The double group graphs of the Möbius types, which find applications in chemically interesting topologies and stereochemistry, are considered for the matching polynomials. Hence, the present study features a number of vertex- or edge-transitive regular graphs, Archimedean solids, truncated polyhedra, prisms, and 4D and 5D polyhedra. Such polyhedral and Möbius graphs present stereochemically and topologically interesting applications, including in chirality, isomerization reactions, and dynamic stereochemistry. The matching polynomials of these systems are shown to contain interesting combinatorics, including Stirling numbers of both kinds, Lucas polynomials, toroidal tree-rooted map sequences, and Hermite, Laguerre, Chebychev, and other orthogonal polynomials.
The Mechanism of Entrepreneurial Resource Bricolage on Entrepreneurial Behavior in Underdeveloped Regions
Authors: Ouyang Sheng , Luo Linji , Chen Kaili , Liu Zhaoyang
Published: January 2025

Entrepreneurial resources are crucial to the success of ventures in underdeveloped regions. Leveraging limited resources to enhance entrepreneurial effectiveness and contribute to poverty alleviation through entrepreneurship has attracted significant academic interest. In this study, a conceptual model is developed, incorporating resource bricolage, entrepreneurial involvement, entrepreneurial action learning, and entrepreneurial behavior. Through an empirical analysis of data collected from 230 startup founders in the Wuling Mountain Area, the results indicate that resource bricolage positively influences entrepreneurial behavior, while entrepreneurial involvement partially mediates the relationship between resource bricolage and entrepreneurial behavior. However, the findings also suggest that entrepreneurial action learning negatively moderates the relationship between resource bricolage and entrepreneurial involvement and that entrepreneurial involvement exerts a significant moderated mediation effect on the relationship between resource bricolage and entrepreneurial behavior. This study advances our understanding of resource bricolage and its implication for the resource environment in underdeveloped regions, providing valuable insights into how entrepreneurs can effectively adapt to resource-constrained settings.
An Investigation of Infrared Small Target Detection by Using the SPT–YOLO Technique
Authors: Qi Yongjun , Yang Shaohua , Jia Zhengzheng , Song Yuanmeng , Zhu Jie , Liu Xin , Zheng Hongxing
Published: January 2025

To detect and recognize small-size and submerged complex background targets in infrared images, we combine a dynamic receptive field fusion strategy and a multi-scale feature fusion mechanism to improve the detection performance of small targets significantly. The space-to-depth convolution module is introduced as a downsampling layer in the backbone first and achieves the same sampling effect. More detailed information is retained at the same time. Thus, the model’s detection capability for small targets has been enhanced. Then, the pyramid level 2 feature map with minimum receptive field and maximum resolution is added to the neck, which reduces the loss of positional information during feature sampling. Furthermore, x-small detection heads are added, the understanding of the overall characteristics and structure of the target is enhanced much more, and the representation and localization of small targets have been improved. Finally, the cross-entropy loss function in the original network model is replaced by an adaptive threshold focal loss function, forcing the model to allocate more attention to target features. The above methods are based on a public tool, the eighth version of You Only Look Once (YOLO) improved, it is named SPT–YOLO (SPDConv + P2 + Adaptive Threshold + YOLOV8s) in this paper. Some experiments on datasets such as infrared small object detection (IR-SOD) and infrared small target detection 1K(IRSTD-1K), etc. have been executed to verify the proposed algorithm; and the mean average precision of 94.0% and 69% under the condition of threshold at 0.5 and over a range from 0.5 to 0.95 is obtained, respectively. The results show that the proposed method achieves the best performance of infrared small target detection compared to existing methods.
Effectiveness of the Federal ‘Clean Air’ Project to Improve Air Quality in the Most Polluted Russian Cities
Authors: Gordeev Roman V. , Pyzhev Anton I. , Syrtsova Ekaterina A.
Published: January 2025

An unavoidable adverse consequence of industrial development is the contamination of urban atmospheres. Deterioration of air quality leads to a decrease in the quality of life of the population, creates a lot of risks of serious diseases, and threatens to increase life expectancy. This phenomenon is particularly evident in many large Russian cities, where historically a powerful industry has developed. In recent decades, the Russian government has acknowledged environmental remediation as a pivotal priority for the National Development Goals. The dedicated funding from the National ‘Ecology’ Project in 2018–2024 allowed for large-scale public and private investments to address the problem of improving the air quality of urban areas in Russia. What is the effectiveness of this spending? In this article, we answer this question by analyzing the effectiveness of the Federal ‘Clean Air’ Project, part of the National ‘Ecology’ Project, which aimed to improve air quality in 12 of the most polluted Russian cities. We show that the project’s key performance indicators (KPIs) underwent significant changes over the 2018–2024 period. The emissions reduction target was lowered from 22% to 20%, the methodology for measuring pollution was revised, and new targets were set. One of the main reasons for this was the suboptimal quality of the data on which the initial plan was based. As a result, the revised emissions estimates produced by the project were found to exceed not only the target benchmarks but also the baseline. The planned targets are largely on track, and it is likely that the target of a 20% reduction in emissions from the 2017 baseline will be met. However, the link between the KPIs and the improvement in urban air quality is questionable. The initial phase of the ‘Clean Air’ Project was a valuable first step, particularly in establishing an air quality monitoring network and conducting detailed pollution assessments in 12 cities. However, to further improve project performance, it is essential to base project KPIs on estimates of air pollution-related health damage and economic losses.
Prediction of Flood Processes Based on General Unit Hydrograph
Authors: Xu Nuo , Sun Yingjun , Sun Yizhi , Sun Zhilin , Geng Fang
Published: January 2025

The general unit hydrograph (GUH), recently established by Guo, represents the most advanced hydrograph model today, but how to implement it with hydrologic data is another story. In this work, an effective initial value-based method for estimating the parameters in the GUH model is proposed and applied to the analysis of flood processes. In contrast to the flood-rainfall united fitting method, which heavily depends on the flood records and has a broad range of parameter variations, which makes it practically intractable, the initial value-based method enables the calculation of model parameters directly from the measured rainstorm data and greatly enriches the discharge dataset so that more accurate prediction of flood processes becomes achievable. From the data collected from several watersheds, we find that smaller-shape parameters usually indicate a multi-peak flood process, and the rainfall patterns have a significant impact on flood peaks. These results provide a reliable approach for the prediction of floods in streams with scarce discharge data. Additionally, it is observed that the peak time lags have a notable increase from the southwest to the northeast of Zhejiang.
Efficiency of Microalgae Employment in Nutrient Removal (Nitrogen and Phosphorous) from Municipal Wastewater
Authors: Popa Marcel Daniel , Simionov Ira-Adeline , Petrea Stefan Mihai , Georgescu Puiu-Lucian , Ifrim George Adrian , Iticescu Catalina
Published: January 2025

Growing population, industrialisation, and demand for resources put pressure on the delicate balance of the planet’s ecosystems. From alternative sources of energy, healthier foods, cleaner water, and an overall more sustainable economy, the integration of microalgae in various industries, that otherwise are based on practices that hurt the environment, could be a successful solution. To reach that goal, further research is required on the complex relationship between microalgae and growth parameters (temperature, light intensity and spectrum, nutrient distribution, inhibiting factors, and so on). The scientific community successfully used microalgae to produce healthier foods, pigments, biofuel, animal fodder, methods for sequestering heavy metals, toxic compounds from water, and much more. In this review article, we approach the use of microalgae in municipal wastewater treatment, mainly for using nitrogen and phosphorous present in water as nutrients. Data were collected from articles published in the last 7 years (2018–2024). The results show that microalgae are very efficient at using N and P compounds from wastewater, as well as carbon, converting them in high-value substances (proteins, lipids, carbohydrates, etc.) with further applications in multiple industries.
RASIO MONOSIT LIMFOSIT SEBAGAI PREDIKTOR KEPARAHAN NEFROPATI DIABETIK PADA PASIEN DIABETES MELITUS TIPE 2
Authors: Bernando Andri , Siregar Jelita , Syafril Santi
Published: January 2025

Diabetic nephropathy is a complication that often occurs in diabetics. In this disease, there is damage to the kidney filter, known as the glomerulus. Due to glomerular damage, diabetic nephropathy is closely related to the mechanism of inflammation. The Monocyte-Lymphocyte Ratio is a relatively new marker of inflammation. This study aims to explore the significance of the prediction of the Monocyte-Lymphocyte Ratio as a predictor of the severity of diabetic nephropathy in Type 2 Diabetes Mellitus (DMT2) patients at H. Adam Malik Hospital, Medan. The research was conducted using the cross-section method. This study took blood samples from 44 patients with type 2 diabetes mellitus with diabetic nephropathy, 22 patients with macroalbuminuria, and 22 patients with microalbuminuria. Then blood was drawn from the vein, and the Monocyte-Lymphocyte Ratio was assessed in all patients. In this study, the average MLR for all patients was 0.41±0.037. There was a significant difference between MLR values ​​in diabetic nephropathy patients with macroalbuminuria compared to diabetic nephropathy patients with microalbuminuria (p<0.001). The optimal cut-off value of MLR in predicting diabetic nephropathy with macroalbuminuria and microalbuminuria was 0.37 with a specificity of 81.8% and a sensitivity of 81.8%. The MLR value in type 2 diabetic patients with diabetic nephropathy can be used as a prognostic factor for the incidence of microalbuminuria and macroalbuminuria.
Nursing Care for Homeless Patients with Hemorrhagic Stroke at A Public Hospital
Authors: Dwivania Agatha Tunjung , Ernawati Ernawati , Zendrato Mey Lona Verawaty , Marpaung Yosi Marin
Published: January 2025

A hemorrhagic stroke occurs when a blood vessel in the brain bursts, causing bleeding in the brain tissue. A hemorrhagic stroke can have a significant impact on the patient. Family support has been shown to influence the success of treatment for hemorrhagic stroke patients. Therefore, Family support is substantial and linked to achieving patient independence. Homeless stroke patients typically receive minimal care and have high mortality rates. This paper aims to review the implementation of care for homeless patients with hemorrhagic stroke in a public hospital in Jakarta. This article is a case report of a homeless 65-year-old man with decreased consciousness who was diagnosed with hemorrhagic stroke. The data were obtained by physical assessment. Several diagnostic tests were performed, including CT scan, MRI, and blood tests. A student nurse working one shift per day provided nursing care for three days. The patient had limb paralysis and drowsiness. The priority diagnoses were ineffective cerebral tissue perfusion, impaired physical mobility, and deficits in self-care. Nursing care focuses on the patient's consciousness and fulfilling basic needs. After 3 days of care, the patient was still unconscious. However, there were no symptoms of increased intracranial pressure. Family participation is necessary for the care of patients with hemorrhagic stroke. The nurse's role as a caregiver becomes primary and crucial for homeless patients who have no family.
The Relationship between Knowledge with Attitudes of College Students towards the HPV Vaccine
Authors: Seo Jordhy Kevin Christoper , Neri Heliana , Maturan Ameylia Martesi , Cathryne Joice , Debby Chryest
Published: January 2025

Cervical cancer is the second-deadliest disease in the world for women after breast cancer. Many women who have cervical cancer, when found, have already entered the final stage, making it difficult to cure. Cervical cancer can prevented by using the human papilloma vaccine, but many women do not vaccinate because they lack knowledge and information. Based on the results of interviews with 20 female students, 18 did not know about the human papilloma vaccine, and 4 had a history of cervical cancer in their family. This study aimed to determine the relationship between the knowledge and attitude of female students towards the human papillomavirus vaccine at faculty teachers college Pelita Harapan University. This research method uses a cross-sectional approach with 101 students as a sample, and the sampling technique used is purposive sampling. The results of data analysis using the Chi-Square test showed a p-value of 0.002 (p<0.005). In conclusion, there is a relationship between the knowledge and attitude of female students toward the human papillomavirus vaccine. Further research will research factors related to attitudes towards the human papillomavirus vaccine other than knowledge.
Female Students’ Knowledge and Behavior in Relation to Breast Examination
Authors: Damayanti S Febrina , Budiawan Mawar Julia , Banggapian Onying , Cathryne Joice , Sihaloho Shinta Marina Josephina Putri
Published: January 2025

Further research will be conducted on the factors that influence the realization examination. Breast cancer is a major global health problem and the highest cause of death among women because many women who suffer from breast cancer are found in the final stage, making it difficult to cure. Breast self-examination is a preventive measure that is done independently to detect early changes in the breast, but even though it can be done by yourself, many women rarely do it. Based on an initial survey of 20 female students, 11 did not know the meaning of breast self-examination, 15 did not know how to do breast self-examination, and 3 had a family history of breast cancer. The purpose of this study was to determine the relationship between knowledge and behavior of female students regarding breast self-examination at the Faculty of Economics and Business at one of the universities in Banten. Purposive sampling is the sampling strategy utilized in this study, which employs cross-sectional sampling with a sample of 88 female students. The Chi-Square test results for the data analysis revealed a p-value of 0.272 (p < 0.05). In summary, there is no correlation between knowledge and the behavior of female students in breast self-examination. Further research will be conducted to determine the factors that influence breast self-examination.
Effect of Lower Extremity Range of Motion (ROM) Exercise on Improving Blood Circulation
Authors: Basri Basri , Arlis Arlis , Yongki Phan
Published: January 2025

Range of Motion Exercise (ROM) are used to increase peripheral perfusion with the aim of facilitating adequate oxygen diffusion and adequate supply of nutrients to the wound area and for the process of repairing wound tissue in the legs of diabetes mellitus patients. The aims to determine the effect of lower extremity range of motion (ROM) training on improving blood circulation in the legs of patients with type 2 diabetes mellitus at Aceh Singkil District Hospital. This Study design uses quasi experimental using a one group pre-test post-test design approach. The Study sample was 35 respondents. Data were analyzed using the Wilcoxon sign rank test. The results of the study showed that there was a significant effect on the blood circulation in the legs of type 2 diabetes mellitus patients before and after being given lower extremity Range of Motion (ROM) training with a value of p = 0.000, the average value before lower extremity ROM training was 1.28 with a minimum value of 1.00 and maximum 2.00. and after being given lower extremity ROM exercises the average value was 1.94 with a minimum value of 1.00 and a maximum value of 2.00. From the results of this Study, it is hoped that nurses at Aceh Singkil District Hospital can apply lower extremity exercises to reduce the risk of complications from peripheral vascular disease, especially in diabetes mellitus sufferers.
Bay Leaf Juice (Syzygium Polyanthum) And Lavender Leaf Juice (Lavandula Angustifolia) As Ae. Aegypti Adult Mosquito Control
Authors: Pakpahan Eka Lolita Eliyanti , Pane Putri Yunita
Published: January 2025

Dengue fever cases in Indonesia, with a total of 71,633 cases as of July 2020, where Medan City experienced a 20% increase in cases in 2020. The main vector of dengue fever is Ae. Aegypti, usually prefers to suck human blood rather than animals (arthrophilic) and is usually active during the day. One way to control Ae. Aegypti mosquitoes is to break the mosquito life cycle by using insecticides. Reports from the Medan City Health Office and several studies have found an increase in cases due to the resistance of Ae. Aegypti mosquitoes to chemical insecticides. This resistance prevents mosquitoes from dying but has an impact on public health. People tend to use insecticides with the active ingredient Cypermethrin, which if used for a long time can cause problems with the upper respiratory tract, skin and eye irritation. Therefore, natural insecticides are needed that are relatively safe for humans and environmentally friendly, such as bay leaf juice (Syzygium Polyanthum) and Lavender Leaf Juice (Lavandula Angustifolia). The purpose of this study was to obtain a natural insecticide formula that can be found in the community environment and can be used by the community because it is cheap, easy and efficient and does not interfere with public health. This type of research is experimental, with the design of The Post Test Only Controlled Group Design. The population in this study was Ae. Aegypti mosquitoes located in the Jalan Durung area of ​​Medan City. The sample in this study was 20 adult Ae. Aegypti mosquitoes in each of the 3 treatments and 2 controls, namely negative control (Aquades) and positive control (Cypermethrin) totaling ± 640. The results of the study that have been obtained are that there is a statistically significant effect on the number of mosquitoes that died between the Bay Leaf Juice (Syzygium Polyanthum) group and the Lavender Leaf Juice (Lavandula Angustifolia) group.
Keywords: Ae. Aegypti; Insecticide; Bay Leaf (Syzygium Polyanthum); Lavender Leaf (Lavandula Angustifolia).
Profilaxia pré-exposição ao HIV em Pelotas: resultados iniciais da implementação no SUS
Authors: Queiroz Vinicius Kaiser
Published: January 2025

O Brasil lidera novos casos de HIV na América Latina, e Pelotas/RS apresenta uma taxa de infecção superior à média nacional. A profilaxia pré-exposição ao HIV (PrEP) foi introduzida pelo SUS em 2019, como parte da estratégia de prevenção combinada, nesse sentido o presente estudo busca avaliar essa implantação. Foi realizado um estudo descritivo que utilizou dados do painel de monitoramento da PrEP, de março de 2019 a junho de 2020, em Pelotas, analisando o perfil dos usuários e o uso de preservativos, parceiros, adesão e efeitos adversos. Obteve-se que 59 pessoas iniciaram a PrEP, 47% interromperam o uso. A maioria era branca (90,32%), HSH (80,25%) e com alta escolaridade (87,10%). Notando-se um aumento de parcerias sexuais e diminuição no uso regular de preservativos. Dessa maneira, observou que a PrEP é eficaz e esta em ampla implementação no município de Pelotas/RS, mas populações vulneráveis, como negros e transexuais, têm menor acesso. Assim, é essencial promover maior conscientização e melhorar o acesso a esses grupos para reduzir a incidência de HIV.
Efeitos adversos no tratamento da hanseníase: uma revisão sistemática
Authors: Espanhol Harley Araujo , Hamada João Pedro Castelo Branco , Antonio Gabriel Lucas Navarro , Abreu Marilda Aparecida Milanez Morgado de
Published: January 2025

Introdução: A hanseníase é uma doença infecciosa crônica causada pelo Mycobacterium leprae, que afeta a pele, os nervos periféricos e outros órgãos. O diagnóstico clínico da doença é baseado em lesões cutâneas com perda sensorial e pode ser confirmado por testes histopatológicos e sorológicos. A transmissão ocorre principalmente pelo trato respiratório superior e os pacientes multibacilares são considerados a principal fonte de infecção. O tratamento da hanseníase é feito com poliquimioterapia (PQT), que consiste no uso de rifampicina, clofazimina e dapsona. A PQT tem sido eficaz na eliminação da bactéria, mas não reverte os danos nervosos. No entanto, a terapia pode causar efeitos colaterais, como anemia hemolítica, dermatite esfoliativa, reações de hipersensibilidade, descoloração da pele intolerância gastrointestinal e interações medicamentosas. A vigilância dos efeitos adversos é essencial para prevenir complicações e garantir a adesão ao tratamento. O abandono do tratamento é preocupante, pois pode levar à recidiva da doença, resistência aos medicamentos e complicações crônicas. Objetivo: Realizar revisão de estudos que demonstrem de maneira científica os efeitos adversos das drogas utilizadas no tratamento da hanseníase para auxiliar no progresso do tratamento melhorando a adesão ao mesmo. Metodologia: Essa revisão sistemática foi realizada obtendo os estudos randomizados que abordam o tratamento e seus efeitos colaterais em pacientes com hanseníase, das bases de dados da Embase, Cochrane Library, LILACs e PubMed e de acordo com os itens de relatório preferidos para Revisões Sistemáticas (PRISMA 2020).
Ancilostomíase, anemia ferropriva e hemorragia digestiva: um relato de caso
Authors: Rossignoli Raphael Augusto , Antonelli Laíza Leite , Guedes Rachel Leite , Pires Henrique Fernandes de Moura , Bezerra João Vitor Rodrigues , Gabriel Stefania Burjack
Published: January 2025

A ancilostomíase é uma infecção parasitária intestinal prevalente em regiões tropicais e subtropicais e uma das principais manifestações clínicas da doença é a anemia, devido à perda crônica de sangue intestinal por fixação dos vermes adultos à mucosa e submucosa dos intestinos. Os autores relatam o caso de um paciente de 30 anos de idade, com histórico de dependência química, atendido em unidade de pronto atendimento devido a anemia severa decorrente de hematoquezia. O diagnóstico de ancilostomíase (Ancylostoma duodenale) foi confirmado após a detecção de vermes na endoscopia digestiva alta. O paciente foi tratado com terapia antiparasitária e suporte clínico com melhora rápida dos sintomas. O caso enfatiza a importância do controle da ancilostomíase como problema de saúde pública e ressalta os desafios quanto ao diagnóstico e o tratamento desta parasitose que, muitas vezes é simples, econômica e eficaz.
The Use of Artificial Intelligence in Film Promotion
Authors: Čábyová Ľudmila
Published: January 2025

The paper is based on the theoretical foundations of promotion with a focus and promotion of the film. It characterizes the possibilities of promotion within film marketing through various tools and techniques. The objective of the contribution is to identify the benefits of using artificial intelligence (AI) in optimizing marketing strategies and personalizing content in film promotion. The author explores the potential of using artificial intelligence (AI) to streamline marketing strategies within film promotion through the creation of personalized, interactive and technologically advanced campaigns. Based on the analysis of secondary data and case studies, author offers several successful examples of the use of AI in film promotion and analyses the added value that AI brings to the field. The paper provides insights into the strategic application of AI to maximize the effectiveness of film marketing activities and offers direction for future developments in this rapidly changing field. By analysing the use of artificial intelligence (AI) in film promotion, the paper aims to identify its benefits in optimizing marketing strategies and personalizing content, as well as its impact on campaign effectiveness and audience engagement. The findings highlight the importance of balancing the automation that AI brings with human creativity for the need to maintain the cultural and emotional depth of film marketing outputs.
Perfil discente do Curso Jardins Amigos da Fauna, Escola Municipal de Jardinagem, Prefeitura do Município de São Paulo
Authors: Silva Linda Lacerda da , Brischi Ana Maria , Beloni Thiago , Lacerda Luciene L. , Roncatti Nicolle W
Published: January 2025

O curso Jardins Amigos da Fauna foi criado em 2018, na Escola Municipal de Jardinagem, da Prefeitura do Município de São Paulo, para ensinar noções básicas de: morfologia floral, polinização, fecundação, morfologia e dispersão de frutos e sementes, nomenclatura biológica, plantio e paisagismo, visando abrigar e alimentar a fauna silvestre do Município de São Paulo, auxiliar na escolha da espécie vegetal, enfatizando-se plantas nativas. Os objetivos foram os de ensinar, sensibilizar, criar agentes multiplicadores e conhecer o perfil dos alunos para o aprimoramento do curso. Ministraram-se aulas teóricas e práticas. Grande parte dos alunos era novata (67,57%), de faixa etária ampla, de 19 a 60 anos, sendo que a maioria era do sexo feminino (72,33%) e vindos da zona Sul (33,33%). A maioria dos alunos (23) respondeu que escolheu fazer o curso por razões pessoais. Estes resultados correspondem com aqueles encontrados na literatura, em cursos de paisagismo, nos quais há um número maior de mulheres participantes, com ampla faixa etária, e as motivações para fazer o curso são, predominantemente, pessoais.
Humanities and Unification Education for Unification
Authors:   Public Policy Research Institute, Korea University, Kim Sang Bum
Published: January 2025

This paper explores the essential meaning and direction of unification education aimed at achieving peaceful unification on the Korean Peninsula. The author argues that unification education should present a clear vision of peaceful unification and systematically teach it to students. To this end, the paper proposes an integrated approach grounded in ‘Humanities for Unification,’ emphasizing a balanced teaching of universal values such as freedom, human rights, and democracy, alongside the necessity of unification.
The paper also explores the challenges of current unification education from three perspectives: the tangled issues of unification education, the problem of neutrality, and the concept of ‘halfway unification education,’ while seeking alternatives to address these challenges. The author particularly emphasizes the use of the humanities as a theoretical toolkit to encourage students to autonomously reflect on and explore unification issues, advocating for teaching methods that cultivate emotional empathy and a practical commitment to unification. It emphasizes the need for unification education to be respected as an independent field while actively interacting with democratic citizenship education, peace education, and global citizenship education. Additionally, the paper highlights the importance of academically distinguishing between the concept of unification and its justification.
In conclusion, the paper asserts that unification education must inspire students to perceive unification as both an ‘irresistible and inevitable’ goal. It highlights the need to cultivate civic competencies that empower students to actively participate in the unification process. To achieve this, unification education should offer concrete and context-rich narratives, providing students with meaningful and experiential learning opportunities.