bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing thermo-physical properties of hybrid nanoparticle-infused RT-54HC organic PCMs using graphene nanoplatelets and multiwall carbon nanotubes
Authors: Islam Anas , Pandey A. K , Sharma Kamal , Bhutto Yasir Ali , Saidur R. , Buddhi D. 
Published: June 2024

Abstract

Phase change materials (PCMs) have emerged as an intriguing option for the storage of thermal energy because of their remarkable capacity to store latent heat. However, the practical application of these materials is hindered by their low thermal conductivity and limited photo-absorbance. For this investigation, graphene nanoplatelets (GNP) and multiwall carbon nanotubes (MWCNT) hybrid nanoparticles were disseminated in RT-54HC organic PCMs at different weight fractions. The nanoparticles were incorporated into the base PCMs using a melt blending technique. Based on the findings, one combination of GNP to MWCNT in a 0.25:0.75 ratio has shown the highest thermal conductivity, with an increase of 30 % (0.28 Wm-1K-1) compared to other hybrid combinations. This breakthrough could potentially open new avenues in the field of thermal energy storage. The chemical stability of the hybrid nanoparticle dispersed composites was assessed through FTIR analysis. In addition, the composites exhibited excellent thermal stability, maintaining their structural integrity even at temperatures as high as 300℃. The melting temperature of the composites also showed minimal variation. Based on the evaluation of latent heat enthalpy, the organic PCM known as base RT-54HC demonstrated a heat storage capacity of 180 J/g. However, the composites exhibited a slight decrease in latent heat with increasing nanoparticle weight fraction. In addition, the composite with added hybrid nanoparticles demonstrated an increase in optical absorbance, accompanied by a decrease in transmissibility. Therefore, the hybrid nano-enhanced composites have demonstrated enhanced thermo-physical properties, making them not only suitable but also highly promising for use in applications with mid-range melting temperatures.
Identification of Diseases in Paddy Crops Using Cnn
Authors: Parasa Gayatri , Arulselvi M. , Razia Shaik 
Published: June 2024

Abstract

In ancient times, agriculture is one of the most predominant occupations of Indian civilizations and it has a great impact in contributing to our country’s economy. Unfortunately, due to several reasons like pests and unpredictable climatic conditions, there has been poor productivity in certain crops, especially paddy. This has been drawn attention towards enhancing the productivity of the paddy crops. Through lots of research, it has been identified that paddy crops are infected by various diseases, and this is one of the reasons that directly affects the overall productivity of the crop. Hence, there emerged an immediate need to take preventive measures and improve the overall productivity rate of paddy crop. In this regard, an Intelligent deep learning algorithm called Convolution Neural Network (CNN) is proposed with an increased structure of 15 layers which predict various diseases that may affect the rice leaves. The developed model efficiency was evaluated in terms of Accuracy, Precision, F-measure, and Recall.
Unveiling the effects of metabolites on the material properties of natural rubber by the integration of metabolomics and material characteristics
Authors: Hiraoka Nobuyuki , Imai Shunsuke , Shioyama Shintaro , Yoneyama Fuminori , Mase Akio , Makita Yuko 
Published: June 2024

Abstract

Natural rubber (NR) is an important material with excellent physical properties. Unlike synthetic rubber from petroleum, NR contains non-rubber components such as proteins, lipids, and metal ions. The non-rubber components are known to affect the properties of NR. In this study, latex samples of Hevea brasiliensis were collected for nine months and their metabolites were comprehensively analyzed by mass spectrometry. NR was made from the same latex samples used for the mass spectrometry, and their vulcanization, tensile and thermal-aging properties were assessed. These results suggest that the metabolite composition in the latex and the NR properties changed seasonally. Correlation analysis between the metabolites and the properties of NR indicated that different metabolites affected different properties. A regression model of NR properties using metabolites as the explanatory variables suggests that about five metabolites need to be considered when examining the relationship between properties and metabolites. This method, which combines comprehensive analysis and characterization of NR, contributes to studies aimed at elucidating how the superior properties of NR are brought about.
Endothelial cell Notch signaling programs cancer-associated fibroblasts to promote tumor immune evasion
Authors: Zhu Yu , Xiang Menglan , Brulois Kevin , Lazarus Nicole , Pan Junliang , Butcher Eugene 
Published: June 2024

Abstract

Stromal cells within the tumor tissue promote immune evasion as a critical strategy for cancer development and progression, but the underlying mechanisms remain poorly understood. In this study, we explore the role of endothelial cells (ECs) in the regulation of the immunosuppressive tumor microenvironment. Using mouse pancreatic ductal adenocarcinoma (PDAC) models, we found that canonical Notch signaling in endothelial cells suppresses the recruitment of antitumor T cells and promotes tumor progression by inhibiting the pro-inflammatory functions of cancer-associated fibroblasts (CAFs). Abrogation of endothelial Notch signaling modulates EC-derived angiocrine factors to enhance the pro-inflammatory activities of CAFs, which drive CXCL9/10-CXCR3-mediated T cell recruitment to inhibit tumor growth. Additionally, abrogation of endothelial Notch unleashed interferon gamma responses in the tumor microenvironment, upregulated PDL1 expression on tumor cells, and sensitized PDAC to PD1-based immunotherapy. Collectively, these data uncover a pivotal role of endothelial cells in shaping the immunosuppressive microenvironment, and suggest the potential of targeting EC-CAF interaction as a novel therapeutic modality to boost antitumor immunity.
Boosting Domain Knowledge Understanding of LLMs through Fine-Tuning with a Novel KNN Algorithm
Authors: Delgaty Shamu , LeBang Ethan 
Published: June 2024

Abstract

Transformer-based architectures have revolutionized natural language processing, demonstrating exceptional capabilities in generating and understanding human-like text. Despite these advancements, challenges persist in enabling models to effectively interpret and generate domain-specific knowledge with high accuracy. The novel integration of a k-nearest neighbour (KNN) algorithm with the GPT-Neo model represents a significant enhancement, specifically designed to improve the model's performance in specialized fields through capturing semantic similarities and contextual nuances inherent in domain-specific data. The research involved fine-tuning the GPT-Neo model with the KNN algorithm, resulting in substantial improvements in accuracy, coherence, and contextual understanding, as evidenced through higher F1, BLEU, and ROUGE scores, alongside reduced perplexity. Ablation studies highlighted the contributions of dynamic weighting schemes, custom distance metrics, and hybrid embeddings to the overall performance gains. The implications of this approach extend to various applications requiring precise domain knowledge interpretation, such as medical diagnostics, legal analysis, and technical support. Future work aims to explore broader domain datasets, integrate additional machine learning algorithms, and further refine the training methodologies to enhance model capabilities.
Impact of COVID-19 Pandemic on the Care of People with Epilepsy and Predictors of Epilepsy Worsening: Aswan/Upper Egypt Hospital-based study
Authors: Khedr Eman M , Haridy Nourelhoda A. , Ahmed Gellan K. , Othman Mohamed Nemr , Elsoghier Abdelrahman S. , Fawal Bastawy M. Al 
Published: June 2024

Abstract

Background:
During the Coronavirus disease pandemic “COVID-19”, epilepsy was one of many chronic neurological diseases in which treatment was neglected. This study aimed to evaluate the impact of the pandemic on people with epilepsy and identify potential predictors of seizure worsening through a face-to-face hospital survey. 245 participants (124 people with epilepsy and 121 people without epilepsy) were recruited and assessed with socio-demographic COVID-19-related questionnaires, the Hamilton Anxiety and Depression scales. Patients with epilepsy also received epilepsy-related questionnaires.
Results:
A significantly higher incidence of COVID-19 infection among people with and without epilepsy. Both groups experienced a similar increase in depression and anxiety during the pandemic compared with prior COVID-19 infection (P = < 0.0001 for each). Around 70% of people with epilepsy reported seizure worsening. Compared with people without worsening epilepsy, a significantly higher incidence of COVID-19 infections, both personally and in family members, that required attendance at health centers and emergency departments was recorded in the people with worsening epilepsy. They faced more medication availability issues than people without worsening and had significantly higher depression but not anxiety scores. Personal COVID-19 infection history, unemployment, work interruptions, and higher pre-COVID seizure frequency emerged as predictors of seizure worsening.
Conclusion
Nearly 70% of people with epilepsy experienced pandemic-related seizures worsening, along with deterioration of mental health. Personal COVID-19 infection, unemployment, work interruption, and higher pre-COVID seizure frequency appear to be predictors of seizure worsening. Mitigating these predictors could strengthen resilience among people with epilepsy during future widespread crises.
Trial registration
clinicaltrials.gov, NCT05205590. Registered 25 October 2021 - Retrospectively registered, https://classic.clinicaltrials.gov/ct2/show/NCT05205590
Optimizing Node Selection in Search Based Multi-Agent Path Finding
Authors: Alam Md. Ahasanul , Mahmud Shekhar , Mamun-Or-Rashid Md. , Khan Md. Mosaddek 
Published: June 2024

Abstract

A Multi-Agent Path Finding (MAPF) problem involves the task of finding paths for multiple agents who want to reach their destinations without obstructing other agents. Although MAPF is essential for numerous real-world applications, finding an optimal solution to this problem is NP-hard. Many approaches have been proposed in the literature, offering sub-optimal solutions to this problem to improve runtime efficiency. Lazy Constraints Addition search for MAPF (LaCAM) is a state-of-the-art sub-optimal MAPF algorithm that employs tree-based lazy successor generation to minimize planning effort. However, the success of the algorithm heavily relies on the effective selection of nodes for expansion. LaCAM employs a fixed heuristic throughout the entire search process, disregarding the agents' preferences or the characteristics of the underlying environment. Nevertheless, experiments with various heuristics indicate that no single heuristic consistently outperforms others across all scenarios. Consequently, in diverse environments, as the number of agents increases, reliance on a single, general heuristic leads to diminished runtime performance. Against this backdrop, with the intent to further speed up the runtime, we propose a novel approach, called eLaCAM, that adaptively selects nodes during the search process considering the current scenario of the environment and agents preferences. We introduce two distinct methods within this approach. The first, eLaCAM-stat, statistically analyses previous results of using different heuristics and selects nodes accordingly. The second method, eLaCAM-ML, employs a Machine Learning (ML) framework to assist in node selection. Our extensive empirical results depict a notable improvement in runtime and a reduction in the search space compared to state-of-the-art MAPF algorithms.
Established and emerging theatre pharmacy services: a scoping review
Authors: McGowan Aisling , Deasy Evelyn , Coyle Mary , O'Connell Juliette 
Published: June 2024

Abstract

Background Pharmacy services impact patients throughout the perioperative journey. Pharmacist activities at surgical pre-assessment clinics and on inpatient wards are well-documented, but services to theatre appear comparatively under-developed. High-risk and high-cost medicines are used routinely in theatre; pharmacists are well-placed to optimise their use and improve patient care.Aim To determine the range, extent and nature of theatre pharmacy services and their outcomes.Method This scoping review was conducted and reported as per the Joanna Briggs Institute methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews. A search was conducted across electronic and grey literature databases to identify pharmacy theatre services. One reviewer screened titles and abstracts and carried out data extraction, with a 10% sample screened by a second reviewer. Two reviewers evaluated full texts. Quality appraisal was undertaken using the Mixed Methods Appraisal Tool.Results Ninety-two publications were included from 3924 search results. Fifty-seven were primary research articles. Most of the included publications described services in the United States of America; the remainder were from Australia, several European countries, Egypt, Morocco, Japan, China and Taiwan. Theatre pharmacy services included medication management and various clinical activities. Outcomes related to cost savings, patient safety and staff satisfaction. Nine of the 57 articles were suitable for quality appraisal. Adherence to quality criteria ranged from 40–100%.Conclusion Evidence for theatre pharmacy services is extensive and varied. Empirical research of high methodological quality is required to assess the outcomes of these services.
Evaluating Abstract Reasoning and Problem-Solving Abilities of Large Language Models Using Raven's Progressive Matrices
Authors: Zhang Chengru , Wang Liuyun 
Published: June 2024

Abstract

Artificial intelligence has rapidly evolved, leading to the development of powerful models capable of performing complex cognitive tasks. Evaluating the cognitive abilities of these models through established human intelligence tests such as Raven's Progressive Matrices (RPM) offers a novel and significant approach to understanding their abstract reasoning capabilities. The study adapted RPM for text-based interactions, enabling the evaluation of Mistral and Llama without human intervention. Results revealed that both models surpass average human performance in overall accuracy, demonstrating their advanced problem-solving skills. However, the analysis also highlighted variability in performance across different types of reasoning tasks, with Llama excelling in sequential pattern recognition and Mistral showing weaknesses in spatial awareness. These findings provide valuable insights into the strengths and limitations of Mistral and Llama, offering a comprehensive understanding of their cognitive abilities and guiding future advancements in artificial intelligence.
Biosensors for Detection of Hepatitis B Virus: Review
Authors: Esfandiari Amir Hossein , Hajipir Farkhani Hadis , Hashemi Javan Zahra , Vojdani Arastoo , Velayati Mahla , Mahaki Hanie , Meshkat Zahra , Manoochehri Hamed , Avan Amir , Tanzadehpanah Hamid 
Published: June 2024

Abstract::
Hepatitis B is still one of the most important infectious diseases among humans,
which is considered a serious threat to their lives. Early diagnosis of this disease
can be an effective measure in stopping the chain of transmission and treatment of the
disease. In this review study, an attempt has been made to explain the use of biosensors
as a fast, high-efficiency, and low-cost method in diagnosis. The biosensors prepared for
hepatitis detection included DNA-based, aptamers-based, protein-based, enzyme-based,
antibody-based, and polymers-based biosensors, each of which had different advantages.
The results of this review showed that almost all introduced biosensors had an acceptable
performance. However, we suggest that aptamers are desirable for biosensing
applications because they can change their structure to properly bind to their target, are
cost-effective to prepare, and are highly sensitive.
Development of a Real-Time Dashboard for Overdose Touchpoints: User-Centered Design Approach
Authors: Salvi Amey , Gillenwater Logan A , Cockrum Brandon P , Wiehe Sarah E , Christian Kaitlyn , Cayton John , Bailey Timothy , Schwartz Katherine , Dir Allyson L , Ray Bradley , Aalsma Matthew C , Reda Khairi 
Published: June 2024

Background
Overdose Fatality Review (OFR) is an important public health tool for shaping overdose prevention strategies in communities. However, OFR teams review only a few cases at a time, which typically represent a small fraction of the total fatalities in their jurisdiction. Such limited review could result in a partial understanding of local overdose patterns, leading to policy recommendations that do not fully address the broader community needs.

Objective
This study explored the potential to enhance conventional OFRs with a data dashboard, incorporating visualizations of touchpoints—events that precede overdoses—to highlight prevention opportunities.

Methods
We conducted 2 focus groups and a survey of OFR experts to characterize their information needs and design a real-time dashboard that tracks and measures decedents’ past interactions with services in Indiana. Experts (N=27) were engaged, yielding insights on essential data features to incorporate and providing feedback to guide the development of visualizations.

Results
The findings highlighted the importance of showing decedents’ interactions with health services (emergency medical services) and the justice system (incarcerations). Emphasis was also placed on maintaining decedent anonymity, particularly in small communities, and the need for training OFR members in data interpretation. The developed dashboard summarizes key touchpoint metrics, including prevalence, interaction frequency, and time intervals between touchpoints and overdoses, with data viewable at the county and state levels. In an initial evaluation, the dashboard was well received for its comprehensive data coverage and its potential for enhancing OFR recommendations and case selection.

Conclusions
The Indiana touchpoints dashboard is the first to display real-time visualizations that link administrative and overdose mortality data across the state. This resource equips local health officials and OFRs with timely, quantitative, and spatiotemporal insights into overdose risk factors in their communities, facilitating data-driven interventions and policy changes. However, fully integrating the dashboard into OFR practices will likely require training teams in data interpretation and decision-making.
PENGGUNAAN DISKRESI OLEH KEPALA DAERAH UNTUK KONSISTENSI PENATAAN RUANG
Authors: Purnama Erma Ekawati , Pramono Retno Widodo Dwi 
Published: June 2024

Abstract
This paper explores the benefits for using discretion on local spatial planning when there is a gap on a system of rules, that must be filled immediately for the local government permit process as an instrument of spatial control for investment. According to Law No. 30 year 2014 on government administration, regional heads can use the discretion. By using empirical legal research, it concludes that the use of the discretion could be possible, and prospectives for improved spatial planning order through establishing urban laws to achieves orderly spatial planning.

Intisari
Penelitian ini menggali manfaat penggunaan diskresi oleh kepala daerah dalam penataan ruang karena ketiadaan RDTR. Undang-Undang Nomor 30 Tahun 2014 tentang Administrasi Pemerintahan memberikan peluang penggunaan diskresi. Melalui metode penelitian empiris, disimpulkan bahwa penggunaan diskresi dapat dilakukan untuk mengatasi permasalahan akibat ketiadaan RDTR, sepanjang lingkup dan tujuan diskresi memenuhi ketentuan dalam Undang-Undang Nomor 30 Tahun 2014, dan bermanfaat dalam hal perbaikan kinerja melalui urban law. Pembahasan praktik diskresi di daerah menggunakan contoh penerbitan Peraturan Bupati Sleman Nomor 63 Tahun 2015 tentang Penghentian Sementara Penerbitan Izin Hotel, Apartemen, dan Kondotel.
OPTIMALISASI PERAN PENEGAK HUKUM DALAM PERLINDUNGAN TERHADAP ANAK-ANAK KORBAN KEKERASAN KOTA PADANG
Authors: Eva Yusnita , Firdaus  , Oktaviani Witia 
Published: June 2024

Abstract
There seems to be an imbalance between regulations and the implementation of the law enforcement process in seeking justice for child victims of violence. The data from 2017 concerning the violence at the children at the municipality of Padang, as reported by the Police Department, reached 115 cases. This trend did not change, as shown by the cases between January and August 2018, when 77 child abuse cases were tabled to the court of the municipality. Only 36 cases in 2017 were submitted to the District Court for legal proceedings. Furthermore, from 2018 to September, only 17 cases were resolved by the District Court. This paper aims to explain the role of law enforcement in optimizing the law to protect the child and strengthen the function of the child protection institution, including DP3AP2KB and LPA. Further, it linked to the efforts that the judges and police have done as vanguards to defend the interests of the children. This study also shows that the role of the law enforcers remains the small function to be done. It is caused by the fact that this institution possessed limited authority. Likewise, the child protection institution carried out advocacy and the institutions did not have any authority to provide some legal advice.

Intisari
Terlihat adanya kesan ketidakseimbangan antara peraturan dan pelaksanaan proses penegakan hukum dalam mencari keadilan bagi anak-anak korban kekerasan. Data kekerasan kepada anak kota Padang tahun 2017 mencapai 115 kasus yang dilaporkan ke Polresta. Kasus kekerasan ini tidak mengalami penurunan sebab data tahun 2018 dari Januari sampai Agustus mencapai 77 kekerasan anak, hanya 36 perkara tahun 2017 yang masuk ke Pengadilan Negeri untuk diproses hukum. Selanjutnya tahun 2018 sampai September hanya 17 perkara yang diselesaikan pihak Pengadilan Negeri. Persoalan di atas menjadi tujuan untuk menjelaskan tentang peranan mereka dalam mengoptimalkan penegakan hukum terhadap perlindungan anak dan hubungannya dengan lembaga-lembaga perlindungan anak seperti DP3AP2KB dan LPA. Selanjutnya juga dikaitkan dengan upaya yang telah dilakukan oleh hakim dan polisi (PPA) sebagai garda terdepan yang membela kepentingan anak sebagai korban kekerasan. Faktanya, peran penegak hukum hanya sebagian kecil yang bisa terlaksana, disebabkan keterbatasan wewenang mereka dalam aturan. Begitu juga dengan lembaga-lembaga perlindungan anak, hanya sekedar melakukan advokasi dan tidak punya kewenangan untuk memberikan pertimbangan hukum.