bluuebunny/crossref_metadata_2025 huggingface dataset:
COMMUNITY PARTICIPATION IN THE 2022 REGIONAL ELECTIONS IN BANDAR SETIA VILLAGE, PERCUT SEI TUAN DISTRICT, DELI SERDANG REGENCY, NORTH SUMATRA PROVINCE
Authors: Stepani Gabriella , Sitorus Kapita , Ivanna Julia
Published: August 2024

The election of regional heads in Indonesia is a direct mandate of the reform movement in 1998. The election of regional heads is part of local democracy, which to realize good democracy, the implementation that can be carried out is the election of regional heads. This aims to channel the aspirations of the community to exercise their voting rights. The election of Regional Heads that is carried out directly can increase the participation of the community. However, it is not uncommon for many people to not care about the election of regional heads. Most of them are apathetic and do not find out about the future leader they will choose. This can happen because the prospective leaders promise a lot of things that can attract the attention of the public but are not implemented correctly. So that the community is disappointed and does not want to know anymore about how the leader will lead them in the future. This analysis is to find out the participation of the community in carrying out local democracy through the election of regional heads. This study uses a qualitative descriptive method. Qualitative research is an approach used to understand the phenomena experienced by the research subject, for example motivation, perception, action, and so on.
Profiles of Patients with Low Back Pain Caused by Disc Herniation in the Neurology Outpatient Clinic of Dr. Soetomo General Academic Hospital Surabaya during the Period of 2021
Authors: Agindra Bani , Hidayati Hanik Badriyah , Widhiyanto Lukas , Herawati Lilik
Published: August 2024

Highlight:

The degenerative process plays a dual role, both protecting from and causing disc herniation.
Men have a quicker degeneration rate at a younger age, while women have a quicker rate at an older age.
Occupational factors such as physical workload, repetition, bending, and sitting periods all contribute to disc herniation.

 
ABSTRACT
Introduction: Low back pain (LBP) refers to a sensation of pain or discomfort occurring in the region between the lowest costal and gluteal crease, with or without leg pain. Damage to the annulus fibrosus causes disc herniation, allowing the nucleus pulposus to herniate into the spinal canal. In less than 5% of cases, LBP is caused by disc herniation. Objective: This study examined the profiles of individuals with herniated LBP discs and related factors at Dr. Soetomo General Academic Hospital Surabaya. Methods: The study was conducted at Dr. Soetomo General Academic Hospital Surabaya using secondary data from medical records, which was then analyzed using descriptive statistics. Results: Fifty-eight LBP patients with herniated discs were enrolled in this study. The patient sample ranged from 23 to 74 years old, with a mean of 47,98±14,92. The majority of patients (29.3%) were 31–40 years old. Male and female prevalence rates were the same. Employees have the highest percentage of any occupation group, with 56.9%. Conclusion: Some of the findings clarify previous studies. Age, gender, and occupation were all linked to the occurrence of either LBP or disc herniation. However, our data cannot indicate whether or not these factors contribute to the occurrence of LBP and disc herniation. Therefore, more research is required to understand these factors and their relation to disc herniation and LBP.
The Incidence and Characteristics of Dermatophytosis in Boarding School Students in Bandar Sei-Kijang, Pelalawan, Riau Province, Indonesia
Authors: Maryanti Esy , Inayah  , Enny Lestari  , Ade Wirdayanto  , Namira Syafira Nihla , Robiatul Adawiyah
Published: August 2024

Background: Indonesia is a tropical country with high humidity and temperatures, making dermatophytosis a persistent health issue. Dermatophytoses are superficial mycoses caused by dermatophytes affecting the skin, hair, and nails. Also known as tinea infections. Purpose: To determine the incidence of dermatophytosis and types of dermatophytosis among boarding school students in Sei-Kijang, Pelalawan, Riau Province. It was conducted from August 2023 until October 2023. Methods:  This research is a simple descriptive study with a cross-sectional design. The aim of the study was to detect dermatophytes in the skin lesions. Dermatophytosis examination was carried out by microscopic examination of skin scrapings with 10-20% potassium hydroxide (KOH) and fungal culture using Sabouraud’s dextrose agar and then examined with a light microscope (lactophenol cotton blue staining). Result: In this study, there were 339 research subjects with 51% male students and 49% female students with an average age of 14.3 years. This study found that the incidence of dermatophytosis was 4.1%, with male students in the 10 to 14-year-old age group having a higher infection rate (71%) than female students. The incidence of tinea corporis was 64.3%, followed by tinea cruris, tinea pedis, and tinea faciei, depending on the type of dermatophytosis. Tinea capitis and tinea unguium were not found. Conclusions: This study demonstrates a high incidence of dermatophytosis, tinea corporis being the predominant type among boarding school students in Bandar Sei-Kijang.
The Validity of Point-of-Care Test (POCT) Lateral Flow Immunochromatographic Assay (LFIA) Candida albicans for the Diagnosis of Vulvovaginal Candidiasis
Authors: Puspitasari Monika , Retno Pudjiati Satiti , Sri Siswati Agnes
Published: August 2024

Background: Vulvovaginal candidiasis is one of the most common causes of complaints of vaginal discharge, which is mostly caused by Candida albicans. The common diagnosis of vulvovaginal candidiasis is microscopic and culture examination. However, the availability of examinations is limited at the private clinic, and for culture examinations, the cost is high and results take several days. The point-of-care test (POCT) lateral flow immunochromatographic assay (LFIA) is a tool that can detect Candida albicans antigens, but this diagnostic test has never been carried out in Indonesia. Purpose: to know the validity of POCT LFIA Candida albicans for the diagnosis of vulvovaginal candidiasis caused by Candida albicans in women with complaints of vaginal discharge. Methods: Cross-sectional observational study with a diagnostic test design, using vaginal discharge samples. Vaginal discharge samples were subjected to POCT LFIA examination with the Medomic Candida albicans/ Trichomonas vaginalis/ Gardnerella vaginalis Antigen Combo Test KitÒ and Candida spp culture. Result: POCT LFIA Candida albicans had a sensitivity of 100%, specificity of 89.9%, accuracy of 90.32 %, LR (+) 9, LR (-) 0, PPV 50%, and NPV 100% against Candida spp. culture. Conclusion: The POCT LFIA Candida albicans can be used to diagnose vulvovaginal candidiasis caused by Candida albicans in women who complain of vaginal discharge.
Enhancing liver surgery and transplantation: the role of 3D printing and virtual reality
Authors: Kasai Meidai , Aihara Tsukasa , Yamanaka Naoki
Published: August 2024

This review explores the significant advancements in liver surgery and transplantation, particularly focusing on the integration of 3D printing and virtual reality (VR) technologies. The core objective is to enhance preoperative planning, simulation, and intraoperative navigation. The review discusses several studies that underscore the accuracy and utility of 3D printed models derived from medical imaging, which are instrumental in identifying small liver lesions, improving surgical education, and facilitating patient comprehension. Additionally, the role of VR in surgical simulation is examined, highlighting its superiority in tumor identification and its potential in training systems. While clinical outcomes data suggest a need for further randomized trials to establish the impact on surgical efficiency and recovery, the review also touches upon the promising future of augmented reality (AR) for intraoperative guidance and liver segment identification, with prospects of artificial intelligence (AI) integration. The conclusion underscores the importance of continued clinical evidence and technological advancements for wider adoption in liver surgery and transplantation.
Questioning Sexual Diversity in Andre Aciman’s Call Me by Your Name and Brent Hartinger’s Geography Club
Authors: Pramesti Tri , Litaay Adeline Grace Mariana
Published: August 2024

This paper discusses sexual diversity exposed in Andre Aciman’s Call Me by Your Name and Brent Hartinger’s Geography Club.  Both novels tell stories about sexual orientation and its impact on the daily lives of the main characters, who are high school students. In Call Me by Your Name, Aciman depicted Elio as a teenager who admires people of the same sex, and in Geography Club, Russell Middle Brook disguises his sexual orientation because he is gay. Using Sociology of Literature as an approach, more specifically queer theory as a means of carrying out queer criticism, this research aims to discuss sexual diversity exposed in these two fictions. It also talks about the heteronormative pressures experienced by the two figures above during their high school years as students who had different sexual orientations. The research results show that although schools and society always emphasize diversity, sexual diversity is not yet accepted. The heteronormative pressure that the experience of Elio and Russel comes from their close environments, such as parents, friends, and school. Elio and Russel need to keep their true sexual identities because showing sexual diversity for high school students is taboo. They also have to keep their sexual orientation to safeguard their lives from rejection and bullying. Selecting the two novels as the data sources helps to understand each text individually and acknowledge how different authors approach similar themes.
Slogans and Posters on Instagram for 2024 Legislative Candidates as Junior High Indonesian Language Learning Media: A Teun Van Dijk's Microstructure Study
Authors: Wardana Muhammad Aditya Wisnu , Rakhmawati Ani , Suhita Raheni
Published: August 2024

This study aims to analyze the critical discourse analysis of microstructure aspects contained in the slogans and Instagram posters of legislative candidates in 2024. The data source of this research is based on Hapri Sianturi's Instagram social media for legislative candidates in 2024 (https://www.instagram.com/haprisianturi/) by observing the linguistic aspects of Instagram posts and the language of Instagram captions. This research uses the critical discourse analysis framework of Teun van Dijk's model to explore the microstructure in the slogans and Instagram posts of legislative candidates in 2024. The research used a qualitative approach and listening method with listening and recording techniques for the data collection. Then, interviews and field observations were conducted at SMP Negeri 1 Surakarta and SMP Negeri 4 Surakarta to determine the relevance of teaching media. The results of research and discussion show that the microstructure aspects of the 2024 legislative candidate Hapri Sianturi are complete. Critical discourse analysis research on posters and slogans of legislative candidates is relevant to learning at the 8th-grade junior high school level using the independent curriculum on the material of Advertising Texts, Slogans, and Posters.
A Syntactic Analysis of Constituent Structure in Sentences Written by EFL Students
Authors: Sari Lilis Indah , Bochari Siska , Usman Sriati , Hastini Hastini
Published: August 2024

This research aims to determine which student uses the most dominant conjunction, what students use the most difficult conjunction and why they have difficulty using correlative and coordinating conjunctions in their sentences. The population of this research was the 4th-semester students of the English education study program at Tadulako University. The sample was selected using a simple random sampling technique, and there were 151 4th-semester students. The researcher used a quantitative description. The data of this research used a test and questionnaire. The results of the data analysis show that (1) the most dominant conjunction used by the students was coordinating conjunction, especially conjunction “and” (2) the most difficult conjunction utilized by the students was correlative conjunction, namely conjunction “both…and”, the frequency of conjunction “both…and”, (3) there are two factors influencing the students in using coordinating and correlative conjunctions which are internal factor and external factor. The internal factors are: the students rarely improve their knowledge about conjunctions; The students are not interested in the material about conjunctions; The students do not understand the function of conjunctions; The students do not understand about lexical categories. The external factors are: There is no motivation from lecturers or teachers for students to learn the conjunctions; The lecturers or the teachers do not explain clearly the material of conjunctions.
Risk Management Analysis Using The AS/NZS 4360:2004 Method On Boilers At PT. Dharmapala Successful Business Cilacap
Authors: Rakhmawati Nita Sofia
Published: August 2024

Boiler merupakan salah satu alat dengan berbagai potensi bahaya. Potensi bahaya tersebut dapat berasal dari tahapan pengoperasian maupun pada tahapan perawatan. Untuk mencegah terjadinya risiko yang dapat terjadi, di perlukan managemen risiko yang tepat. Salah satu yang dapat digunakan yaitu managemen risiko metode AS/NZS 4360:2004. Tujuan penelitian ini yaitu melakukan analisis risiko dengan metode AS /NZS 4360-2004 pada boiler di PT. Dharmapala Usaha Sukses Cilacap. Penelitian ini merupakan penelitian kualitatif analitik, dengan menggunakan 3 informan antara lain pimpinan, pengawaas dan pekerja. Penelitian di lakukan dengan wawancara dan observasi berpedoman lembar wawancara dan lembar observasi komponen boiler, yang di analisis yaitu pada tahap pengoperasian dan perawatan boiler. Analisis dilakukan dengan metode triangulasi. Hasil penelitian menunjukan terdapat potensi bahaya yang dapat menyebabkan risk level high pada aktivitas pengoperasian yaitu pengisian bahan bakar dan perawatan boiler yaitu aktivitas pengecekan belt conveyor. Risiko yang dapat terjadi adalah kematian akibat kebakaran. Upaya pengendalian yang sudah dilakukan perusahaan di antaranya memasang cyclone, serta dilakukan inspeksi. Peneliti menyarankan perusahaan dapat melakukan pengecekan rutin temperatur batu bara dan memasang safety sign pada area yang berbahaya.
Growth Performance of Clown Anemonefish (Amphiprion ocellaris) in Maluku at Optimum Salinity
Authors: Fitrinawati Henny , Syahailatua Diana Yulanda , Utami Endang Sri
Published: August 2024

Clown anemonefish (Amphiprion ocellaris) is one of the most popular ornamental coral reefs. The marine ornamental fish trade has increased fishing pressure. It has a considerable impact on the clown anemonefish's declining population. The ability of each fish species to tolerate the salinity is a vital consideration in aquaculture marine organisms as it gives information on primary environmental necessities. This study aimed to analyze the clown anemonefish growth performance by modifying different salinity levels through survival rate, specific growth rate, and feed conversion ratio parameters. The experiment was conducted with a Completely Randomized Design (CRD) to investigate the effect of salinity on clown anemonefish growth performance with six treatments (24, 26, 28, 30, 32, and 35 ppt) and three replications. Water quality parameters in this study observed include pH, temperature, and dissolved oxygen. The clown anemonefish reared with six different salinity treatments for 30 days showed that there was a significantly different effect on SGR (p value = 0.007) but no significant differences in FCR (p value = 0.189) and survival rates (p value = 0.458). The considerable effect of salinity on specific growth rates explains that the amount of energy used in the osmoregulation process disrupts a portion of growth energy. The optimal growth performance of clown anemonefish was in a 24 ppt salinity treatment, accompanied by other water quality parameters such as temperature, dissolved oxygen, and pH, which ranged from 26.5 – 32oC; 4.9 - 5.6 ppm; and 7.9 - 8.2, respectively.Keywords: Amphiprion ocellaris, clown anemonefish, growth performance, salinity
Chondrogenic Cancer Grading by combining Machine and Deep Learning with Raman Spectra of Histopathological Tissues
Authors: Lazzini Gianmarco , D’Acunto Mario
Published: August 2024

The present paper explored the possibility of discriminating between different malignant degrees of Chondrosarcoma (CS), a diffused bone tumor, and Enchondroma (EC), its benign version, through an approach based on the coupling between Confocal Raman Microscopy (CRM) and Machine Learning (ML) techniques. Recently, Raman Spectroscopy has proven to be a powerful tool for a complete grading of CS by distinguishing between grade 1, 2 and 3, and to distinguish CS from EC. In this paper, we tested some models, belonging either to ML or to the sub-type called Deep Learning (DL), showing excellent classification performances, especially the DL algorithms, with classification accuracy approaching to 100%, making the models promising for future implementations of Raman spectroscopy when applied to oncology diagnosis. In turn, we highlighted how some proper ML models result in worse classification performances but better resolution of specific chemical target compounds, possible candidate to become malignant markers, with relevant implication for a correct diagnosis.
Advancements in Wireless Power Transfer (WPT) Technologies Enhanced by AI for Next-Generation Applications
Authors: ISLAM MD. SUZON
Published: August 2024

The two combined technologies WPT and AI still have huge prospects for several industries such as consumer electronics and industry. This paper looks at the recent developments in WPT, particularly concerning AI-improved efficiency, range, and reliability. AI-driven also works to control power, manage device alignment, and test when maintenance is necessary, this makes powering smarter and more efficient. Accuracy is given by deploying machine learning and computer vision, and on the other hand, the maintenance procedure is done through predictions. Furthermore, the ability of the management system to include the use of AI in power regulation enables the control of consumption based on the load. In this study, the positive future effect of AI is discussed concerning improvements in WPT technologies, which is paramount in subsequent applications. Based on the results, it is essential to continue the investigation of the topic within this interdisciplinary science to advance existing problems and discover novel possibilities for evolution. Data based on experiments shows a significant improvement in the efficiency of information transfer where AI is used with rates up to 25% higher than those using the traditional ways. Additionally, advanced maintenance forecasting algorithms improve system availability by cutting down on 30% of the downtimes when applied in real-life applications of AI technology. The study also looks at the possibilities of the outlook to the future including emergence of the distributed artificial intelligence for autonomous WPT network, and additional potential of quantum computing for the use to improve the algorithm. This indicates that there is a new era for the convergence of WPT and AI to enhance the progress of power transfer system in conditions of elegant, efficient, and robust.
Exploring the Adoption of Cloud-Based Supply Chain Management Solutions
Authors: Wilson George , Brown William , Johnson Oliver
Published: August 2024

The adoption of cloud-based supply chain management (SCM) solutions represents a transformative shift in how organizations manage their supply chains, offering significant advantages in terms of cost efficiency, flexibility, real-time data access, and the integration of advanced technologies. This study explores the multifaceted impacts of cloud-based SCM systems, focusing on both their benefits and the challenges encountered during their implementation. Through an in-depth analysis of interview and case study data, the research reveals that cloud-based solutions enable organizations to reduce capital and operational expenditures substantially while providing the scalability necessary to adapt to fluctuating demands. Real-time access to data enhances visibility and decision-making, and the incorporation of advanced technologies such as artificial intelligence and machine learning improves predictive analytics and process optimization. However, the study also identifies several critical challenges associated with the adoption of cloud-based SCM solutions. Key issues include data security concerns, integration difficulties with legacy systems, and the complexities of managing organizational change. Effective implementation requires meticulous planning, comprehensive training, and strategic vendor management to address these challenges successfully. The research highlights the importance of robust security measures, thorough integration strategies, and effective change management practices in overcoming these obstacles. The strategic outcomes of adopting cloud-based SCM solutions include improved operational efficiency, enhanced inventory management, and increased customer satisfaction. Additionally, organizations gain a competitive edge through better supplier coordination and greater responsiveness to market changes. Overall, the study demonstrates that while cloud-based SCM solutions offer substantial benefits, their successful adoption hinges on effectively managing associated challenges and leveraging their transformative potential.
Predictive Assessment and Compressive Strength Test of Geopolymer Concrete Mix as a Partial Replacement to Conventional Concrete Mix with Artificial Neural Network Application
Authors: Labiano Hannah Beatrix D. , Cruz Ian Rovic P. , Quizon Lanz Ghranyel C. , Marcos Christ John L.
Published: August 2024

Geopolymers, made from aluminosilicate raw materials, offer significant environmental advantages over conventional concrete (CC) mixes. This study explores the compressive strength, setting time, and durability of geopolymer concrete (GPC) cylinders, some of which include an additional ordinary portland cement (OPC) mix. Consistent material composition and testing methods are emphasized to achieve reliable results. MATLAB was utilized to develop and assess a neural network model predicting the compressive strength of GPC based on key variables. The model was validated using 16 experimental samples and 1047 samples from various studies. The performance plot displayed the Mean Squared Error (MSE) over iterations, identifying the best training performance at epoch 658 with an MSE of 5.3408. The Error Histogram highlighted distribution errors between predicted and actual compressive strength values, with the highest range from -1.015 to 0.3587, meaning that the predicted values were mostly within a small margin of error from the actual values. This narrow error range indicates that the ANN model has high accuracy in its predictions, as most errors are small and clustered around zero, demonstrating reliable performance in estimating compressive strength. Regression analysis showed varying correlation coefficients (training set R=0.98373, test set R=0.88164, and whole set R=0.96982), indicating adequate predictive accuracy. The results demonstrate that properly trained neural networks can effectively predict the compressive strength of GPC, highlighting its potential as a sustainable construction material.
An Expanded Molecular and Systems Toolbox for Imaging, Mapping, and Controlling Local Translation
Authors: Onchan Warunya , Attakitbancha Chadaporn , Uttamapinant Chayasith
Published: August 2024

Localized protein translation occurs through trafficking of mRNAs and protein translation machineries to different compartments of the cell, leading to rapid on-site synthesis of proteins in response to signaling cues. The spatiotemporally precise nature of the local translation process necessitates continual developments of technologies reviewed herein to visualize and map biomolecular components and the translation process with better spatial and temporal resolution, and with fewer artifacts. We also discuss approaches to control local translation, which can serve as a design paradigm for subcellular genetic devices for eukaryotic synthetic biology.
Using mHealth Technology to Evaluate Daily Symptom Burden Among Adult Survivors of Childhood Cancer: A Feasibility Study
Authors: Howell Kristen E. , Baedke Jessica L. , Bagherzadeh Farideh , McDonald Aaron , Nathan Paul C. , Ness Kirsten K. , Hudson Melissa M. , Armstrong Gregory T. , Yasui Yutaka , Huang I-Chan
Published: August 2024

Background: Cancer therapies predispose survivors to a high symptom burden. This study utilized mobile health (mHealth) technology to assess the feasibility of collecting daily symptoms from adult survivors of childhood cancer and evaluate symptom fluctuation and associations with future health-related quality-of-life (HRQOL).
Methods: A prospective study using an mHealth platform to distribute a 20-item cancer-related symptom survey (5 consecutive days each month) and an HRQOL survey (the day after symptom survey) over 3 consecutive months to participants from the Childhood Cancer Survivor Study. PROMIS-29 Profile and Neuro-QOL assessed HRQOL. Daily symptom burden was calculated by summing the severity (mild, moderate, or severe) of 20 symptoms. Univariate linear mixed-effects models analyzed total, person-to-person, day-to-day, and month-to-month variability for the burden of 20 individual symptoms. Multivariable linear regression analyzed the association between daily symptom burden in the first month and HRQOL in the third month, adjusting covariates.
Results: Out of the 60 survivors invited, 41 participated in this study (68% enrollment rate); 83% reported their symptoms ≥3 times and 95% reported HRQOL, both in each week across 3 months. Variability of daily symptom burden differed from person-to-person (74%), day-to-day (18%), and month-to-month (8%). Higher first-month symptom burden was associated with poorer HRQOL related to anxiety (regression coefficient: 6.56; 95%CI: 4.10-9.02), depression (6.32; 95%CI: 3.18-9.47), fatigue (7.93; 95%CI: 5.11-10.80), sleep (6.07; 95%CI: 3.43-8.70), pain (5.16; 95%CI: 2.11-8.22), and cognitive function (-6.89; 95%CI: -10.00 to -3.79) in the third month.
Conclusion: Daily assessment reveals fluctuations in symptomology, and higher symptom burden was associated with poorer HRQOL in the future. Utilizing mHealth technology for daily symptom assessment improves our understanding of symptom dynamics and sources of variability.
Coating of Refractory Surfaces with Fine TiO2 Particles via Gas‐Dynamic Cold Spraying
Authors: Aleksieieva Olha , Bozoglu Mustafa , Tretiakov Pavlo , Toporov Andrii , Antonyuk Sergiy
Published: August 2024

Refractory materials are used worldwide in process equipment. However, gaseous and liquid process products penetrate the surface layer, and deep into the volume of refractories destructing rather expensive constructions complicated to repair. To address this challenge, there is a need to develop protective coatings for refractory that can limit the penetration of working media and extend their operational lifespan. In this work, the application of gas-dynamic cold spraying (CGDS) to produce a coating on the refractory using fine titanium dioxide (TiO2) particles is explored. These particles are accelerated within a nitrogen flow, passing through a Laval nozzle, and then sprayed onto a fireclay surface. The mechanisms of particle deposition and layer formation on porous surfaces through experiments and numerical simulations were investigated. The geometry of a typical refractory pore was determined, which was then incorporated into Computational Fluid Dynamics (CFD) simulations to model the cold spraying process of porous substrates. As a result, the influence of the particle size on its velocity and angle of penetration into pores was established. Experimental findings demonstrate the effective closure of pores and the formation of a particle layer on the refractory surface. Furthermore, the nanoindentation tests for the refractory samples showcase capabilities for checking coating thickness for porous materials.
A Comparative Analysis of Key Features for Tracing the Causes of Abnormal Electricity Prices in Market Environments
Authors: Dai Siting , Wu Wenmin , Zhang Xiaolong , Hong Weixin , Li Yan
Published: August 2024

Electricity price signal is a direct reflection of the attributes of electric power commodities, but due to the influence of market supply and demand, power producers' offer, line capacity and other factors, electricity price signals often show a variety of abnormal forms. The identification and traceability of abnormal tariff signals is an important daily work of power trading centers at all levels. However, at present, it is common to rely on manual experience to analyze the causes of abnormal tariffs, which is inefficient and difficult to ensure the objective and scientific traceability of abnormal tariff causes. Since different types of abnormal tariff signals are caused by different dominant factors, if the key features of abnormal tariffs can be classified and matched, the identification efficiency can be effectively improved. For this reason, this paper proposes a traceability method of abnormal tariffs based on the comparison analysis of key features. First of all, based on the characteristics of historical tariff data, this paper completes the classification of tariff spike magnitude anomaly and tariff mean value anomaly, further establishes the key features of each type of abnormal tariff signal based on principal component analysis, and finally calculates the influence degree of each element within the key features one by one based on alternative algorithms, and then realizes the screening and traceability of the causes of abnormal tariffs based on the importance of the degree of influence ordering. The effectiveness of the proposed method has been verified in a large number of examples constructed based on the actual data of the electricity market, and the average correctness rate of the proposed method for the traceability of the causes of the average value and spike anomalies of the electricity price reaches more than 85%, which can reduce the labor cost in the process of the traceability of the causes of the anomalous electricity price.
Lightweight Optic Disc and Optic Cup Segmentation Based on MobileNetv3 Convolutional Neural Network
Authors: Chen Yuanqiong , Liu Zhijie , Meng Yujia , Li Jianfeng
Published: August 2024

Glaucoma, a global leading cause of blindness, necessitates accurate segmentation of the optic disc (OD) and optic cup (OC) for effective screening. However, existing segmentation methods based on convolutional neural networks (CNNs) suffer from high computational complexity and long inference times. In this paper, we propose an end-to-end segmentation method for the OD and OC using a lightweight MobileNetv3 as the feature extraction network. Our approach incorporates boundary branches and an adversarial learning network to achieve multi-label segmentation of the OD and OC. We evaluate the proposed method on three publicly available datasets: Drishti-GS, RIM-ONE-r3, and REFUGE. The experimental results demonstrate segmentation accuracies of 0.974/0.900, 0.966/0.875, and 0.962/0.880 for the OD and OC on the respective datasets, while significantly reducing inference time.
Innovative Air Preconditioning Method for Accurate Particulate Matter Sensing in Humid Environments
Authors: Kunić Zdravko , Mršić Leo , Đambić Goran , Ražov Tomislav
Published: August 2024

This paper addresses the challenges of improving the accuracy of low-cost particulate matter sensors (LCPMS) under high humidity conditions. Such weather conditions often lead to the overestimation of particle counts due to hygroscopic particle growth, resulting in a potential public concern, although most of the detected particles consist of just water. The paper presents an innovative design for an indicative air-quality measuring station that integrates the particulate matter sensor with a preconditioning subsystem designed to mitigate the impact of humidity. The preconditioning subsystem works by heating the incoming air, effectively reducing the relative humidity and preventing the hygroscopic growth of particles before they reach the sensor.
To validate the effectiveness of this approach, parallel measurements were conducted using both preconditioned and non-preconditioned sensors over a period of 19 weeks. The data was analyzed to compare the performance of the sensors in terms of accuracy for PM1, PM2.5, and PM10 particles. The results demonstrated a significant improvement in measurement accuracy for the preconditioned sensor, especially in environments with high relative humidity. When the conditions were too severe and both sensors started measuring incorrect values, the preconditioned sensor measured values were closer to the actual values. Also, the period of measuring incorrect values was shorter with the preconditioned sensor.
The results suggest that the implementation of air preconditioning subsystems in LCPMS can provide a cost-effective solution to overcome humidity-related inaccuracies, thereby improving the overall quality of measured air pollution data.
Mechanical Behaviour of Breast Tissue: An In-Depth Systematic Review
Authors: Semakane Letlhogonolo , Mohan Turup Pandurangan , Ngwangwa Harry , Pandelani Thanyani , Nemavhola Fulufhelo
Published: August 2024

The breast holds significant importance in women's lactation process. The breast has diverse tissues such as glandular, Cooper’s ligament, lactiferous ducts, adipose, muscles, and skin with various mechanical properties. Most soft tissues exhibit nonlinear, viscoelastic, and anisotropic mechanical behaviour. Stiffness is one of the commonly used mechanical properties for measuring mechanical behaviour in soft tissues. However, this is typically used in simplifying cases where analysis is limited to within the linear elastic region. Young’s modulus is the prevailing measure for quantifying stiffness in tissues. This systematic review examines commonly used techniques for mechanically characterising breast soft tissues to close the gap in the literature. Additionally, this systematic review summarises the mechanical behaviour of the breast tissues available in the literature and highlights the uncovered areas to understand the mechanical behaviour of breast tissues fully. These include a) more mechanical behaviour studies, allowing more accurate modelling for other applications, b) Viscoelastic analysis studies, and c) mechanical analysis on other breast tissues, such as the lactiferous duct, also known as the milk duct. The data obtained in the review can be used as inputs in computational models to analyse the behaviour of the breast tissues.
Indoor Air Quality Management in Dubai: Assessing the Efficacy of Air Purifiers, Photocatalysts, and Window Ventilation in Reducing HCHO
Authors: Jung Chuloh , Alshamasi Shams Mohammed
Published: August 2024

This study investigates the characteristics of formaldehyde (HCHO) concentration and its reduction in newly constructed apartment buildings in Dubai. It addresses the significant health risks of high HCHO levels due to poor ventilation and extensive use of VOC-emitting materials. The research explores the effectiveness of various mitigation strategies, including air purifiers, photocatalyst applications, and window ventilation, in the living room, master bedroom (MBR), Room 1, and Room 2. HCHO concentrations were measured under different conditions: sealed windows, operation of an air purifier with a VOCs filter, and the application of a photocatalyst. The study followed a quantitative approach, recording real-time HCHO levels over 24 hours. Results indicated that sealing windows led to HCHO concentrations surpassing the domestic standard of 0.1 ppm, with the MBR recording the highest concentration at 0.73 ppm. The air purifier showed minimal impact within the first 8 hours but achieved an 18% reduction after 24 hours of operation. Applying a photocatalyst to room surfaces resulted in a 50% reduction in HCHO levels. Ventilation through window openings significantly improved air exchange rates, with the air exchange per hour (ACH) increasing proportionally with window opening size. Smaller rooms with larger window-to-volume ratios, such as Room 1 and Room 2, maintained HCHO concentrations below the WHO standard of 0.1 ppm with partial window openings. The study concludes that window ventilation is the most effective strategy for reducing HCHO concentrations, highlighting the importance of integrating comprehensive ventilation designs in modern residential buildings to ensure healthier indoor environments in Dubai.
Determining 1:1 Charge Stoichiometry and Rheological Characterization for pH Induced Chitosan-Albizia procera Complex Coacervate Xerogels
Authors: Roy Dr. Partha Sarathi
Published: August 2024

Abstract: In order to explore new options for colon targeting, this study designs new polyelectrolyte complex (PEC) coacervate xerogels of chitosan (Ch) with Albizia procera (AP). It was determined by potentiometric titration tests that a 1:5 Ch/AP weight ratio was necessary for 1:1 charge stoichiometry. Rheological characterizations experiments were carried out for the pH independent coacervates and 1:5 coacervate was found to be having the highest G/ value in the strain sweep experiment. In the frequency sweep experiments the coacervate (1:5) with the highest storage modulus (G/) values was produced at pH 4.5.
Dynamics of Mammarenavirus Wenzhouense Acute Infection in the Rodent Rattus norvegicus
Authors: Du ShanShan , Deng XueFei , Huang Xiaoxia , Liu TieZhu , Li Aqian , Wang Qin , Tian TingTing , Li Chuan , Zheng ZhangQi , Lin QiHan , Li ZhuoWei , Wang Shiwen , Li Jiandong
Published: August 2024

Mammarenavirus Wenzhouense (WENV) is broadly distributed in Asia, while the he dynamics process of WENV infection remains unclear. A field derived strain of WENV was used to inoculate Sprague-Dawley (SD) rats by intramuscular injection, the process of virus infection was de-tected by controlling time for 28 days. Viral RNA became detectable in the blood at 3 d pi, and remained detectable for about 12 d. In most organ tissues, viral RNA peaked at 7 d pi, then began to decline by 14 d, however remained detectable in intestine and brain tissues at 21 and 28 d pi. Virus shedding had been detected from fecal samples for 5 days from 6 to 11 d pi using qRT-PCR, and was recovered from feces collected at 8 d pi. Horizontal contact infection occurred among cage-mates at 14 and 21 d pi. Antibodies against the nucleocapsid were detected at 5 dpi, next increased and persisted until the end of experiment. The results enabled to discriminate the kinetic of viremic response, virus shedding in feces and horizontal transmission, as well as the potential sites for WENV replication or maintenance of the virus in nature.
Design and Analysis of off -Grid PV/Diesel System for Small Scale Factory Located in Wadi Rum, Jordan Using Homer Software
Authors: Alghweri Mohammad , AL-Khataybeh Ruba
Published: August 2024

The fuel prices are increasing nowadays, causing a burden on the power system. From this, diesel generators that are still in use, must be hybridized with renewable energy (RE) to levelized the overall projects costs. This study aims to schedule an operation of a hybrid system photovoltaic (PV)/ diesel in a remote area which located in Wadi Rum district in Jordan to serve factory load in addition to obtain the best economical system combination that can serve the needs of a continuous electrical load without any interruption. Based on the results of the analysis using HOMER software, the configuration in the system will be a combination between PV modules, and diesel generator. The hybrid system has met the target for electricity production which is documented in upcoming sections.
Erbil Citadel as a Brand for the City, The Role of Residents Awareness and Perceptions
Authors: Ali Haval Sami , Khayat Mahmood Ahmed Bakr
Published: August 2024

The branding of cities through their historical and cultural assets has become a pivotal strategy in urban development and tourism. This study focuses on Erbil Citadel, a UNESCO World Heritage Site, and its potential as a brand for Erbil, a city with a rich historical backdrop and flourishing urban landscape. The study aimed to explore the perceptions of Erbil's residents regarding the cultural significance of the Citadel and its potential as a city brand. A mixed-method survey questionnaire was conducted, collecting data from around 440 residents through both manual distribution around the Citadel and an online platform. The findings were analysed using SPSS to provide both descriptive and inferential statistical insights.
4D Printing: Advancements and Applications: Research in the Emerging Field of 4D Printing
Authors: Egon Axel , Bell Chris , Shad Ralph
Published: August 2024

4D printing represents an innovative evolution of 3D printing technologies, incorporating time as a fourth dimension to create objects that can transform and adapt over time in response to environmental stimuli. This emerging field has shown significant advancements in materials science, design principles, and applications. Recent research focuses on developing responsive materials such as shape-memory polymers, hydrogels, and composites that can undergo controlled transformations in reaction to changes in temperature, humidity, or other external factors. The advancements in 4D printing have led to a wide array of applications, including self-healing structures, adaptive medical devices, and dynamic architectural components. This abstract examines the latest progress in 4D printing technologies, highlighting key advancements in material development and design strategies. It explores various case studies that demonstrate the practical implementation of 4D-printed objects across different sectors. Furthermore, the abstract discusses the challenges faced by researchers, including material limitations, scalability issues, and the need for standardized testing methods. The potential future directions of 4D printing are also considered, emphasizing the need for interdisciplinary collaboration to overcome current limitations and expand the range of applications. This research underscores the transformative potential of 4D printing in creating intelligent and adaptable systems, offering significant benefits across industries from healthcare to construction.
Additive Manufacturing in Medical Applications
Authors: Egon Axel , Bell Chris , Shad Ralph
Published: August 2024

Additive Manufacturing (AM), commonly known as 3D printing, has revolutionized various industries, including the medical field. This technology enables the creation of complex structures layer by layer, offering unprecedented customization and precision. In medical applications, AM has proven transformative in producing patient-specific implants, prosthetics, and anatomical models, facilitating better surgical planning and outcomes. Additionally, it has shown promise in bioprinting, where cells and biomaterials are used to create tissue-like structures for regenerative medicine. The ability to rapidly prototype and manufacture medical devices reduces time and costs, and enhances personalized patient care. This abstract explores the diverse applications, benefits, and challenges of AM in the medical sector, highlighting its potential to revolutionize healthcare and improve patient outcomes.
Additive Manufacturing for Complex Geometries
Authors: Egon Axel , Bell Chris , Shad Ralph
Published: August 2024

Additive manufacturing (AM), commonly known as 3D printing, has revolutionized the production of complex geometries that were once challenging or impossible to achieve through traditional manufacturing techniques. This paper investigates the capabilities of additive manufacturing in producing intricate designs, focusing on the unique advantages and potential applications across various industries. Additive manufacturing enables the creation of complex geometries by adding material layer by layer, allowing for greater design freedom and the ability to produce structures with intricate internal features, complex curves, and lightweight lattice structures. This capability is particularly advantageous in fields such as aerospace, biomedical, and automotive, where weight reduction, customization, and the integration of complex internal channels are critical. The study explores various additive manufacturing technologies, including stereolithography (SLA), selective laser sintering (SLS), and fused deposition modeling (FDM), highlighting their specific strengths and limitations in producing complex geometries. Factors such as material properties, resolution, surface finish, and build size are analyzed to determine the suitability of different AM processes for specific applications. Additionally, the research delves into the design considerations and software tools that facilitate the creation of complex geometries in AM, including generative design and topology optimization. These tools leverage the design freedom offered by AM to optimize structures for weight, strength, and functionality, pushing the boundaries of what is possible in product design. The paper concludes with an examination of the challenges and future directions in the field, such as improving material properties, reducing production costs, and enhancing the accuracy and reliability of AM processes. The potential of additive manufacturing to revolutionize the production of complex geometries is underscored, emphasizing its growing importance in modern manufacturing and its role in enabling innovative solutions across various industries. This abstract provides an overview of the potential and challenges of additive manufacturing for producing complex geometries, suitable for an academic paper or report. If you need more specific information or have a different focus, feel free to ask!
Impact of Additive Manufacturing on Supply Chain Management
Authors: Egon Axel , Bell Chris , Shad Ralph
Published: August 2024

Additive manufacturing (AM), commonly known as 3D printing, has emerged as a transformative technology in supply chain management (SCM). This abstract explores how AM influences various aspects of SCM, including inventory management, production processes, and logistics. By enabling on-demand production and reducing reliance on traditional manufacturing methods, AM minimizes inventory costs and enhances customization capabilities. It also facilitates localized production, which can reduce lead times and transportation costs. The integration of AM into SCM fosters greater flexibility and resilience, allowing businesses to respond more swiftly to market changes and disruptions. This study highlights both the opportunities and challenges associated with adopting AM, emphasizing the need for strategic adjustments to fully leverage its potential in modern supply chains.