bluuebunny/crossref_metadata_2025_split huggingface dataset:
OPTIMIZATION OF FIRE STATION LOCATION USING GEOINFORMATION TECHNOLOGIES
Authors: Zakharov Georgy V. , Vasiliev Andrey S. , Filippov Vladimir N. 
Published: September 2024

The article explores the optimization of fire station location using geoinformation technologies. It is proposed an algorithm based on road network analysis to determine optimal fire station location without considering potential road congestion, as fire vehicles are equipped with special signals for priority passage. The study is held using the example of Sterlitamak, utilizing Shapefile (SHP) and Database (DBF) files containing information about road network geometry and intersections. The research involves several key stages: analysis of the original road network, identification of intersections, development of the optimization algorithm, and its testing. The results demonstrate the effectiveness of the proposed method: four optimal centers for fire station placement are successfully identified, three of which correspond to actual fire stations considering a 500 m radius circle around intersections. The proposed algorithm serves as a tool for planning and optimizing fire protection infrastructure in urban areas, based on geographic data analysis. The obtained results can be utilized to enhance the efficiency and responsiveness of emergency response in urban settings.
Epidemiology of acute myocardial infarction in a tertiary hospital in Hadhramout Governorate, Yemen
Authors: Abdul-Raheem Bahishwan  , Yousef Musaab Fahmi 
Published: September 2024

: There is a lack of comprehensive data on the epidemiological characteristics and risk factor profile of adult patients with acute myocardial infarction (AMI) in Yemen. This study aimed to determine the epidemiological characteristics of AMI among adult patients in Hadhramout governorate, Yemen. Aretrospective cross-sectional study was conducted from January 01, 2023, to June 30, 2024, in Hadhramout Modern Hospital, Mukalla, Republic of Yemen. All patients admitted to the hospital with AMI during the study period were included in this study. We recruited 109 patients with AMI, representing 1.3% of all hospital admissions. The mean age of the patients was 61.56±11.02(35-90 years). Male patients accounted for 56% of patients (n=61), and the most common risk factor was diabetes mellitus 89(81.7%). The common clinical presentation was typical chest pain 98(89.9), while 5 patients (4.6%) presented with cardiogenic shock. Two types of AMI were identified: non-ST-elevation MI 29 (26.6%) and ST-elevation MI 80 (73.4%). All patients were admitted to the intensive care unit, and the mean length of hospital stay was 7.84 ± 2.64 (1-13 days). All patients received dual antiplatelet therapy, while 46 patients (42.2%) received streptokinase as intravenous thrombolytics. The in-hospital mortality was 13 (11.9%).AMI represents 1.3% of all hospital admissions in our hospital. It is more commonly seen in males as compared to females with diabetes mellitus being the most commonly associated risk factor. The in-hospital mortality was 13(11.9%) representing 4.2% of all mortality in the hospital during the study period. Our studyhighlights the challenge of prevention and management of AMI in our limited-resources governorate. People should be educated about the risk factors of AMI and a well-equipped cardiac center should be provided in Hadhramout Governorate.
Treatment of Refractory Osteochondral Lesions of the Talus with a Novel Transmalleolar Drilling Technique
Authors: Mullin Edmund P. , Edmonds Eric W. 
Published: September 2024

Case:
A 15-year-old adolescent girl underwent revision surgery for a posteromedial osteochondral lesion of the talus (OLT). To provide anatomic reduction of her lesion, fluoroscopy and ankle arthroscopy facilitated a transmalleolar tunnel for screw fixation. Now, 8 years after surgery, the patient reports high patient satisfaction and pain-free functional use of her ankle.

Conclusion:
A transmalleolar tunnel technique provides an alternative method to treat posteromedial OLT. This minimally invasive procedure allows patients to be spared potential complications from a medial malleolar osteotomy or a posteromedial incision. Most importantly, this case report demonstrates a positive long-term patient outcome.
ChatGPT-4 Knows Its A B C D E but Cannot Cite Its Source
Authors: Ghanem Diane , Zhu Alexander R. , Kagabo Whitney , Osgood Greg , Shafiq Babar 
Published: September 2024

Introduction:
The artificial intelligence language model Chat Generative Pretrained Transformer (ChatGPT) has shown potential as a reliable and accessible educational resource in orthopaedic surgery. Yet, the accuracy of the references behind the provided information remains elusive, which poses a concern for maintaining the integrity of medical content. This study aims to examine the accuracy of the references provided by ChatGPT-4 concerning the Airway, Breathing, Circulation, Disability, Exposure (ABCDE) approach in trauma surgery.

Methods:
Two independent reviewers critically assessed 30 ChatGPT-4–generated references supporting the well-established ABCDE approach to trauma protocol, grading them as 0 (nonexistent), 1 (inaccurate), or 2 (accurate). All discrepancies between the ChatGPT-4 and PubMed references were carefully reviewed and bolded. Cohen's Kappa coefficient was used to examine the agreement of the accuracy scores of the ChatGPT-4–generated references between reviewers. Descriptive statistics were used to summarize the mean reference accuracy scores. To compare the variance of the means across the 5 categories, one-way analysis of variance was used.

Results:
ChatGPT-4 had an average reference accuracy score of 66.7%. Of the 30 references, only 43.3% were accurate and deemed “true” while 56.7% were categorized as “false” (43.3% inaccurate and 13.3% nonexistent). The accuracy was consistent across the 5 trauma protocol categories, with no significant statistical difference (p = 0.437).

Discussion:
With 57% of references being inaccurate or nonexistent, ChatGPT-4 has fallen short in providing reliable and reproducible references—a concerning finding for the safety of using ChatGPT-4 for professional medical decision making without thorough verification. Only if used cautiously, with cross-referencing, can this language model act as an adjunct learning tool that can enhance comprehensiveness as well as knowledge rehearsal and manipulation.
Spatial Quantification of Marine Litter Using Satellite and Drone Data through Empirical and Deep Learning Techniques – A Case Study from India
Authors: P Thanabalan , K Gayathrri , Hidaka Mitsuko , Matsuoka Daisuke , Mishra Pravakar , Dierssen Heidi , Dash S K , Usha Tune , V Ramanamurthy M 
Published: September 2024

Abstract

Marine Litter is a major contaminant in the world's oceans. The mismanaged land-based garbage reaches the marine environment via rivers and creeks. Remote sensing techniques have the potential for detecting, classifying, and quantifying litter patches in the coastal zone. A case study for Chennai metropolitan city beaches attempted to quantify debris using different satellite sensors with specific spectral bands. Equally, the drone can detect and quantify macro litters (> 5 mm) at a relatively better resolution (2 to 2.5 cm). This study was carried out to evaluate the suitability of the drone images for detecting macro litter in the coastal segment. Image-based semantic segmentation deep learning techniques are applied. Estimating litter abundance with the spatial extent of natural and artificial litter on the beaches agrees with ground truth data.
The Impact of Diesel and Various Blends of Biodiesel on Performance, Emissions, and Combustion in DI Diesel Engines
Authors: Veerasamy Arunachalam , Pancharam Naveenchandran , Pandian Balu 
Published: September 2024

Abstract

The rise in consumption, environmental emissions, and the cost of gasoline make energy recovery from trash a top priority. Not only can biodiesel meet energy demands, but it can also reduce greenhouse gas emissions, making it an important source of renewable energy. An experimental study of diesel and many different biodiesel blends was conducted to analyse their performance, emissions, and combustion characteristics. To prepare the emulsified fuel and go on with further experimental work, this effort aimed to identify the optimal biodiesel blends. The results of this paper showed that among all other biodiesel blends with various compositions, Syzygy Cumini (SC) biodiesel, 20% by volume with diesel (SC20), was the best mix. Based on the outcomes of performance, combustion, and emission metrics, it was selected. In comparison to other biodiesel blends, the SC20 biodiesel produced brake thermal efficiency that was nearly as high as that of diesel. With the exception of nitrogen oxide (NOx) emissions, the emission parameters were likewise determined to be lower than those of other biodiesel blends.
Sustainable Processing of Zea Mays peel ash (Methylene adsorbed) biosorbent as a novel green heterogeneous catalyst for biodiesel production
Authors: Prakash Akshay , Manuel Jerold 
Published: September 2024

Abstract

The escalating energy crisis, propelled by extensive fossil fuel consumption, necessitates sustainable and environmentally friendly alternatives. Biodiesel, derived from renewable sources, has emerged as a promising solution. This study explores using methylene blue (M.B., which is a significant water pollutant in several parts of the world) dye-adsorbed biochar, a waste-derived green catalyst, for biodiesel production. The catalyst was synthesized from Zea Mays peels, demonstrating a circular economy approach. The optimization of transesterification reactions is achieved using the Taguchi method, considering factors including reaction time, temperature, catalyst load, and methanol-to-oil ratio. The resulting biodiesel was purified and characterized through various analyses, including Gas Chromatography and Nuclear Magnetic Resonance. Adsorption studies reveal the catalyst's potential, and structural analyses (FESEM, XRD, FTIR) provide insights into its composition. The synthesized biodiesel, identified through GC-MS, exhibited qualities that align with the findings of the literature. Overall, the study presents a sustainable and economically viable pathway for biodiesel production using a novel green catalyst derived from waste resources.
Deep learning segmentation model produces accurate biodiversity predictions at 10 m spatial resolution
Authors: Andermann Tobias , Häggmark Johan , Olsson Patrik , Högström Alice 
Published: September 2024

Abstract

Biodiversity loss is an increasingly intensifying global crisis with significant societal, political, and financial implications. However, our understanding of biodiversity remains limited due to vast data gaps, and the existing data products fail to meet the needs of decision-makers because of their limited accuracy, spatial scale, and resolution. As we approach the short- to medium-term implementation deadlines of major international biodiversity agreements, such as the United Nation's Kunming-Montreal Global Biodiversity Framework and the European biodiversity strategy, there is a pressing need for high-quality data products to guide large-scale conservation prioritization decisions. In this study, we present a novel deep learning segmentation approach for detecting high biodiversity-conservation-value forests using a set of remote sensing data products. This approach has enabled us to produce a national data product of continuous coverage for Sweden, with an unprecedented accuracy of 91% and a high-detail spatial resolution of 10-meter pixel size, significantly advancing on existing approaches. Sweden serves as a good test case for the here developed approach, as it is home to the largest portion of Europe's remaining old-growth forests and is also characterized by robust biodiversity and environmental data availability. Our approach allowed us to map over 50,000 km² of high conservation value forest (HCVF) at high confidence, saving more than 750 years of manual inventory effort and significant financial and personnel resources. With its high accuracy and spatial resolution, our data product offers substantial utility for decision-makers at different administrative scales, and directly addresses the goals set by large international biodiversity conservation plans. While this study focuses on detecting high conservation value forests in Sweden, the presented model serves as a proof-of-concept implementation that can be adapted and applied for modeling other regions and biodiversity metrics.
Is basic training in palliative care sufficient to guarantee the improvement of knowledge and skills in this area? – medical knowledge assessment study
Authors: Monteiro Rita , Ribeiro Hugo , Dourado Marília 
Published: September 2024

Abstract

Background: With the increase in the population needing Palliative Care, it is necessary to increase and improve the supply of this care in Portugal. Throughout doctors' pre-graduate training, there are few learning opportunities in this area, making it necessary to resort to further training to improve the knowledge and skills needed to guide patients at the end of their lives. Studies carried out on doctors and medical students showed a clear need to improve training. Others observed a clear benefit in interns who underwent postgraduate training in the area, in dealing with patients at the end of their lives.
The objective is to evaluate the impact of a basic training action on the palliative care knowledge obtained by medical doctors.
Methods: Observational and cross-sectional study, carried out by sharing a questionnaire with the 204 participants enrolled in the “Intensive Palliative Medicine Course” organized by a group of doctors in November 2021. The questionnaire was completed by participants at three moments of the training (before, immediately after the course and 6 months after the course), which contained questions to assess theoretical knowledge and the skills and abilities obtained.
Results: 209 responses were collected, 93 (45.58%) doctors responded before training, 80 (39.21%) immediately after training and 36 (17.64%) six months after training. After the training, an improvement in knowledge was observed (p=0.014), which does not appear to have persisted six months after the course (p=0.574). However, six months after training, an increase in doctors' confidence in referring patients to Palliative Care Teams or Units (p=0.009) and in medicating patients who may be in the last months of their lives (p=0.005) was observed.
Conclusions: The results of theoretical knowledge in medical areas were worse, so it may be necessary to create more specific training opportunities for the medical profession. An increase in doctors' self-confidence in referring and medicating patients with Palliative Care needs was observed, which may be associated with better medical care provided. It is necessary to carry out more studies to evaluate the impact of combined theoretical and practical training on the knowledge of doctors in PC.
Access to Mental Health Care and Navigating Psychological Distress: A Cross-sectional Study Among Bangladeshi University Students
Authors: Begum Momotaj , Muniruzzaman Md. 
Published: September 2024

Abstract

University students often face high mental health challenges but rarely seek treatment, leading to distress and suicidal behavior. This study addresses this gap by examining the prevalence, risk factors, and accessibility of mental health care among Bangladeshi university students. A total of 267 samples were collected from three different Bangladeshi universities through face-to-face interviews, gathering socio-demographic, health, and behavior variables, along with data using the Kessler Psychological Distress Scale (K10). The results indicate that, approximately just over a quarter reported psychological distress (30.3%). Risk factors for psychological distress among university students included coming from joint families, living in university halls, being financially self-supported, not regularly engaging in religious practices, having insomnia, feeling uncomfortable discussing mental health issues with friends, having moderate social support, and facing significant challenges in overcoming psychological distress. The findings will help in implementing university-based mental health programs, increasing awareness, reducing stigma, enhancing access to professional care, including suicide prevention, and providing baseline data for future research.
Exploring the relationship between Mental Health Issues and Academic Performance of Undergraduate Students in a Ghanaian Tertiary Institution: a cross-sectional study.
Authors: Arthur Andrew , Fraikue Joanne , Adu-Amankwah Bijoux , Ofori Richard , Sekyi Dorcas , Boateng Abena Afrakomah , Asamoah Elsie , Appiah Seth Christopher Yaw 
Published: September 2024

Abstract

Background
Mental health associations with students’ academic outcomes are critical for students’ well-being and excellent performance, particularly among tertiary students in their educational trajectory. This study investigated the relationship between mental health incidence and academic performance among university students in a public university in Ghana. Additionally, we study students’ level of mental health awareness.
Methods
The study adopted a quantitative study with an analytical cross-sectional design. Through the multistage sampling technique, structured questionnaires were administered to 384 undergraduate students at Kwame Nkrumah University of Science and Technology (KNUST). Data management and analysis were performed using SPSS v.27. Descriptive data are presented in tables and reported as frequencies. Inferential analysis was conducted using a multilevel logistic regression model and a p-value of 0.05 was considered to indicate statistical significance.
Results
Severe depression (p = 0.016, ϰ2=0.784) was significantly associated with students’ academic performance. Severe anxiety (p = 0.020, ϰ2=11.700), gender (p = 0.014, ϰ2=5.999) and self-efficacy (p = 0.015, ϰ2=5.939), were found to have a statistically significant association with academic performance (p < 0.05). According the multilevel analysis, females experiencing mental health had reduced likelihood of achieving high academic performance compared to male students (AOR = 0.343, 95% CI = 0.144–0.813, p = 0.015). Severely depressed students (AOR = 0.264, 95% CI = 0.084–0.830, p = 0.23) are significantly less likely to increase their Cumulative Weighted Average (CWA). Self-efficacious students (AOR = 3.325, 95% CI = 1.421–7.784, p = 0.06) were three times more likely to increase their CWA.
Conclusion
Severe depression causes a reduction in students’ academic performance, while high academic self-efficacy among students serves as a protective factor by facilitating an increase in students’ CWA when they encounter mental health issues.
Thickness Accommodation in Earwig Fan Folding
Authors: Kitajima Chisaki , Saito Kazuya , Taiju Yoneda , Nishi Koki , Suehiro Kaoru 
Published: September 2024

Abstract

Origami embodies a traditional aspect of art culture. This technique facilitates the compact folding of deployable structures and improves construction and transportation performance in engineering. While these advantages are attractive, designing deployable structures is complex because it requires consideration of material thickness. Here we introduce the thickness accommodation techniques into the highly efficient folding patterns derived from biomimetic engineering approach. The underlying simple geometrical elements within the complex crease patterns of earwig hindwings were already revealed, and design software was implemented to customize the pattern using an algorithmic design tool. However, the crease pattern has a zero thickness, and the thickness accommodation should be performed for engineering applications as a deployable structure. We propose thickness accommodations for two folding modes with mountain and valley folding line assignments. For each folding mode, the thickness accommodation solves the interference, and we make a model made of thick materials to verify the deployment behavior. The research results represent a further step toward developing biomimetic engineering applications using origami techniques based on the crease patterns of earwig hindwings.
Fe3O4@HA-Cu(OAc)2 nanocomposite as a nanomagnetic water-compatible catalyst for efficient synthesis of 1,2,3-triazoles in water
Authors: Arjmandzadeh Beheshteh , Jafari Abbas Ali 
Published: September 2024

Abstract

A new Humic acid-based nanomagnetic copper(II) composite was prepared and used as an eco-friendly recoverable catalyst for the synthesis of 1,4-disubstituted 1,2,3-triazoles via the three-component click reaction of alkyl halide, sodium azide, and terminal alkyne in good to excellent yield. A simple magnetic copper acetate composite preparation using humic acid, Fe3O4@HA-Cu(OAc)2, was reported and characterized by SEM, TEM, XRD, EDX, VSM, AAS, and FT-IR. The catalyst shows high catalytic potential in a one-pot three-component click reaction for synthesizing 1,2,3-triazoles. The nanomagnetic Fe3O4@HA-Cu(OAc)2 demonstrates highly efficient, stable, compatible with oxygen/water and recyclable copper (II), and cost-effectiveness advantages catalyst. An external magnetic field easily recovers the catalyst, and therefore, time and energy are saved since no filtration or decantation technique was needed. According to high dispersibility in water, nanomagnetic Fe3O4@HA-Cu(OAc)2 can be utilized as a highly efficient catalyst.
Effects of HNTX-VII on Kv4.2 and Kv4.3 and Molecular Determinants of Kv4.3 Interacting with HNTX-VII
Authors: Chen Bo , Hu Zhaotun , Renzhong Chen , Juan He , Zeng Xiongzhi 
Published: September 2024

Abstract

HNTX-VII is a novel peptide isolated and purified from the venom of the Chinese spider Ornithoctonus hainana, with a relative molecular mass of 3830.973 Da. Electrophysiological experiments have demonstrated that HNTX-VII exhibits minimal effects on TTX-S, TTX-R, and delayed rectifier potassium channels on dorsal root ganglia (DRG), as well as on Kv1.4 and Kv4.1. However, it significantly inhibits Kv4.2 and Kv4.3 currents, with IC50 values of 299.6 ± 6.48 nM and 114.5 ± 5.36 nM, respectively, for Kv4.2 and Kv4.3. The sequence of HNTX-VII, determined by Edman degradation, is ECRYWLGTCSKTGDCCSHLSCSPKHGWCVWDWT. Composed of 33 amino acids and containing 3 pairs of disulfide bonds, this molecule represents a typical inhibitor cystine knot (ICK) motif. Furthermore, HNTX-VII alters the kinetic properties of Kv4.2 and Kv4.3 channels by causing corresponding shifts in their steady-state activation, steady-state inactivation, and inactivation recovery curves. To further investigate the molecular mechanism underlying the interaction between HNTX-VII and Kv4.3 channels, 19 mutants in the extracellular loops of the S1-S2 and S3b-S4 segments of the Kv4.3 channel were designed and constructed using site-directed mutagenesis. Electrophysiological techniques were then employed to assess the inhibitory activity of HNTX-VII against these mutants. Notably, the V282A mutant in the S3b-S4 loop exhibited the most significant reduction in sensitivity to HNTX-VII, with an IC50 value 5.37 times that of the wild-type channel. Therefore, it is inferred that the 282nd amino acid in the extracellular loop of S3b-S4 serves as a crucial site for the interaction between HNTX-VII and Kv4.3.