bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhanced YOLOv8 Ship Detection Empower UnmannedSurface Vehicles for Advanced Maritime Surveillance
Authors: HAIJOUB Abdelilah , HATIM Anas , HAMMIA Slama , ELOUALKADI Ahmed , CHOUGDALI Khalid , ARIOUA Mounir 
Published: May 2024

Abstract

The evolution of maritime surveillance is sig-nificantly marked by the incorporation of Artificial In-telligence and machine learning into Unmanned SurfaceVehicles (USVs). This paper presents a an AI methodfor detecting and tracking unmanned surface vehicles,specifically leveraging an enhanced version of YOLOv8,fine-tuned for maritime surveillance needs. Deployedon the NVIDIA Jetson TX2 platform, the system fea-tures an innovative architecture and perception mod-ule optimized for real-time operations and energy effi-ciency. Demonstrating superior detection accuracy witha mean Average Precision (mAP) of 0.99 and achievingan operational speed of 17.99 FPS, all while maintain-ing energy consumption at just 5.61 joules. The remark-able balance between accuracy, processing speed, and energy efficiency underscores the potential of this sys-tem to significantly advance maritime safety, security,and environmental monitoring.
Real-Time Cloud Computing of GNSS Measurements from Smartphones and Mobile Devices for Enhanced Positioning and Navigation
Authors: Olcina Jorge Hernández , Julián Ana Belén Anquela , Furones Ángel Esteban Martín 
Published: May 2024

Abstract

In recent years, Global Navigation Satellite Systems (GNSSs) have become integral to our daily lives because of their precise positioning and navigation capabilities. Widespread use of smartphones equipped with GNSS receivers results in the generation of a huge amount of positioning data. Therefore, real-time cloud computing has emerged as a promising approach to effectively leverage this wealth of location information. In this study, we developed an Android application that captures raw GNSS data from smartphones, leverages cloud computing resources, calculates the position of the device, and returns the computed solution to the user. Integration of cloud-based processing not only conserves the device resources but also enables real-time position calculation, paving the way for enhanced location-based applications and services.
Dolutegravir Disrupts Mouse Blood-Brain Barrier by Inducing Endoplasmic Reticulum Stress
Authors: Huang Chang , Qu Qing Rui , Hoque Md. Tozammel , Bendayan Reina 
Published: May 2024

Abstract

Background
Dolutegravir (DTG) - based antiretroviral therapy is the contemporary first-line therapy to treat HIV infection. Despite its efficacy, mounting evidence has suggested a higher risk of neuropsychiatric adverse effect (NPAE) associated with DTG use with a limited understanding of the underlying mechanisms. Our laboratory has previously reported a toxic effect of DTG comparable to efavirenz in disrupting the blood-brain barrier (BBB) integrity in vitro and in vivo. The current study aimed to investigate, in vitro, the potential mechanisms involved in DTG toxicity.
Methods
Primary cultures of mouse brain microvascular endothelial cells were used as a robust rodent BBB cell model. The cells were treated with DTG at therapeutic relevant concentrations (2500, 3500, 5000 ng/ml) for 3–48 h with or without the presence of three endoplasmic reticulum (ER) sensor inhibitors (GSK2606414, 4µ8c, 4PBA). RNA-sequencing, qPCR, western blot analysis and cell stress assays (Ca2+ flux, H2DCFDA, TMRE, MTT) were performed.
Results
Our initial Gene Ontology (GO) analysis of RNA-Sequencing data revealed an enriched transcriptome signature of ER stress pathway in DTG treated cells. We further demonstrated that therapeutic concentrations of DTG significantly activated the ER stress sensor proteins (PERK, IRE1, p-IRE1) and downstream ER stress markers (eIF2α, p-eIF2α, Hspa5, Atf4, Ddit3, Ppp1r15a, Xbp1, spliced-Xbp1). In addition, DTG treatment resulted in a transient Ca2+ flux, an aberrant mitochondrial membrane potential, and a significant increase in reactive oxygen species in primary cultures of mouse brain microvascular endothelial cells. Furthermore, we found that prior cell treatment with 4PBA (a broad-spectrum ER stress inhibitor) significantly rescued DTG-induced downregulation of tight junction proteins (Zo-1, Ocln, Cldn5), whereas GSK2606414 (a PERK inhibitor) elicited the greatest protective effect on DTG-induced elevation of pro-inflammatory cytokines and chemokines (Il6, Il23a, Il12b, Cxcl1, Cxcl2).
Conclusions
The current study provides valuable insights into DTG toxicological cell mechanisms, which may serve as a potential explanation of DTG-associated NPAEs in the clinic.
Effect of random noise behaviour on the properties of forcing nonlinear Maccari’s model structures
Authors: Alhazmi Hadil , Bajri Sanaa A. , El-Shewy E. K. , Abdelrahman Mahmoud A.E. 
Published: May 2024

Abstract

This article analyses and examine the nonlinear Maccari’s equations with noise term using the powerful sub-equation mathematical approach. Several significant solitary and rational solutions have been provided. These solutions are crucial in a number of fields, such as superfluid, optical fibre communication, and space-confined plasma waves. The effects of model parameters on the obtained solutions features have been discussed. The randomness parameter affects the envelope, soli-tonic structures, and energy properties. It was reported that by raising the random parameter, Brownian isolated driving shock waves with random amplitude were produced. Finally, the method described here may be applied to many nonlinear systems and new energy trends in natural science.
AMS Subject Classification (2010): 34A34, 60G05, 60H15, 35Q60
Unraveling Developmental Dynamics and Triterpene Saponin Biosynthesis in Panax notoginseng Stem Apices by Single-Cell Transcriptomics
Authors: Liu Mei , Yang Lifang , Guo Junda , Wang Hanye , Yu Saiying , Wang Panpan , Yang Ye , Huang Luqi , Cui Xiuming , Liu Yuan 
Published: May 2024

Abstract

Background
Panax notoginseng is often regarded as the foremost blood-nourishing herb due to its rich content of triterpene saponins, which possess various pharmacological activities. The transcriptional regulatory mechanisms governing stem apex development and the expression of its major component, triterpene saponins, remain poorly understood.
Results
In this study, we constructed a single-cell transcriptome atlas of stem apices, and the cells were divided into seven major cell types, comprising a total of 14 subclusters. Subsequently, we analyzed the developmental trajectory patterns and gene expression features of stem apices and inferred relevant transcription factors associated with stem apex development. We discovered potential key transcription factors, PTI5 and IDD12, involved in the early development of stem apices. Additionally, we investigated the expression and regulation of the triterpene saponin synthesis pathway in stem apices.
Conclusions
Therefore, the aim of this study is to elucidate the developmental trajectory of P. notoginseng stem apices and identify key transcription factors, opening a new avenue for future research of Panax genus.
An Investigation of GNSS RO Data Pattern for Climate Change Monitoring and Analysis over Africa
Authors: Sa’i Ibrahim Usman , Aleem Kamorudeen , Musa Tajul Ariffin , Youngu Terwase Tosin , Obadaki Yusuf , Anom Wan Aris , Nasara Mohammed Abdu 
Published: May 2024

Abstract

Climate change monitoring and analysis is a critical aspect that involves the consideration of both spatial and temporal dimensions. Improved spatial distribution of the Global Navigation Satellite System (GNSS) ground-based Continuous Operating Reference (COR) stations can lead to enhanced results when coupled with a continuous flow of data over time. In Africa, a significant number of COR stations do not operate continuously and lack collocation with meteorological sensors essential for climate studies. Consequently, Africa faces challenges related to inadequate spatial distribution and temporal data flow from GNSS ground-based stations, impacting climate change monitoring and analysis. This research delves into the pattern of GNSS Radio Occultation (RO) data across Africa, addressing the limitations of the GNSS ground-based data for climate change research. The spatial analysis employed Ripley's F, G, K, and L-functions, along with calculations of nearest neighbour and Kernel density. The analysis yielded a Moran's P-value of 0.001 and a Moran's I-value approaching 1.0. For temporal analysis, the study investigated the data availability period of selected GNSS RO missions. Additionally, it examined seasonal temperature variations from May 2001 to May 2023, showcasing alignment with findings from other researchers worldwide, Hence, this study suggests the utilization of GNSS RO missions/campaigns like METOP and COSMIC owing to their superior spatial and temporal resolution.
Push-Pull Carbazole-Based Dyes: Synthesis, Strong Ultrafast Nonlinear Optical Response, and Effective Photoinitiation for Multiphoton Lithography
Authors: Stavrou Michalis , Zyla Gordon , Ladika Dimitra , Dumur Frederic , Farsari Maria , Gray David 
Published: May 2024

Abstract

The present work reports on the ultrafast nonlinear optical (NLO) properties of a series of D-π-Α and D-A push-pull carbazole-based dyes and establishes a correlation between these properties and their efficiency for potential photonic and optoelectronic applications, such as multiphoton lithography (MPL). The ultrafast NLO properties of the studied dyes are determined by two distinct experimental techniques, Z-scan and pump-probe optical Kerr effect (OKE), employing 246 fs laser pulses at 515 nm. The results indicate that chemical functionalization of the carbazole moiety with various strong electron-donating and/or electron-withdrawing groups, such as benzene, styrene, 4-bromostyrene, nitrobenzene, trimethyl isocyanurate, methyl, and indane-1,3-dione, can result in a controlled and significant enhancement of the NLO absorptive and refractive responses. In the context of potential applications, the efficiency of carbazole-based organic materials as photoinitiators (PIs) for MPL applications is demonstrated. The fabricated woodpile microstructure using chemically functionalized carbazole as a PI demonstrates improvements in both resolution and MPL efficiency compared to that using unfunctionalized carbazole as a PI. This attributed to efficient charge transfer resulting from chemical functionalization, which leads to a substantial increase (approximately one order of magnitude) in the values of the imaginary part of the second-order hyperpolarizability (Imγ) and the two-photon absorption cross section (σ). The achieved resolution of 280 nm is comparable to that obtained with other widely used PIs in MPL applications. Additionally, owing to strong NLO refraction and Kerr signal of the studied functionalized carbazole, they also exhibit promise as candidates for all-optical switching applications in telecommunications, optical computing, data processing, etc.
Network Pharmacology Approach: Analysing Pathways in Breast Cancer
Authors: Bobade Ishwari , Badhe Pravin , Mali Prof. Prashant 
Published: May 2024

Abstract

Breast cancer is the most commonly occurring cancer in women. However, the efficacy and utility of the available drug therapies are limited. The objective of the present study was to determine the genes and molecular pathways associated with breast cancer by using computational tools. In this study, we used text mining and GeneCodis to mine genes which were highly related to breast cancer. Protein‑protein interaction (PPI) analysis was performed by using STRING and Cytoscape. In this present study, about 166 entries were taken from uniport database of breast cancer. After deleting the duplicate genes only 7 genes were selected for the gene ontology analysis. GO analysis showed that there were 80 pathways related to the Biological Process (BP) and 10 KEGG pathways obtained. Using STRING database three key target proteins were obtained(BRCA1, BRCA2 and RBBP6 ).To visualize the interaction between the target proteins Cytoscape 3.7.1 software were used. The degree and betweenness were measured using centiscape app. In conclusion, investigating candidate medications that target the genes or pathways relevant to breast cancer using in silico text mining and pathway analysis technologies.
Identifying challenging barriers to farmers' adaptation to climate change in Bo district, Sierra Leone: A review
Authors: Alie Morie Elogima Kendekpa , Yateh Mohamed , Bavumiragira Jean Pierre , Liao Zhenliang 
Published: May 2024

ABSTRACT

The global trend of climate change presents substantial obstacles to the agricultural sector in Africa, impacting farmers’ livelihoods and jeopardizing food security. Sierra Leone, similarly to numerous other African nations, confronts substantial obstacles in effectively responding to the consequences of climate change, with a special emphasis on the agricultural domain. The article examines the formidable obstacles farmers face in Sierra Leone as they strive to adjust to the impacts of climate change. A detailed literature review and empirical evidence identify four main barriers: economic, knowledge and information, institutional and policy, and social and cultural aspects. Farmers face economic problems investing in adaptable technologies and recovering from climate-related losses due to restricted financial resources, financial institution availability, and insurance coverage. Limited access to reliable climate data and scientific research hinders informed decision-making and adaptive strategy prioritization. Institutional and policy challenges, including limited institutional capacity for climate change adaptation planning and implementation and policy gaps and inconsistencies, hinder farmers’ climate adaptation efforts. Social and cultural variables, including traditional attitudes and traditions, also resist change and impede climate-resilient actions. Financial support, targeted extension services, farmer-to-farmer learning, enhanced institutions, policy integration into agricultural policies, and community engagement are suggested.
Green infrastructure layout based on a dynamic operation feature of drainage systems
Authors: Shen Chen , Dong Xin , Wang Luyao , Wang Xinhao 
Published: May 2024

ABSTRACT

Increasingly frequent urban floods strain the traditional grey infrastructure, overwhelming the capacity of drainage networks and causing challenges in managing stormwater. The heavy precipitation leads to flooding and damage to drainage systems. Consequently, efficient mitigation strategies for flooding have been researched deeply. Green infrastructure (GI) has proved to be effective in responding the increasing risk of flood and alleviate pressure on drainage systems. However, as the primary infrastructure of stormwater management, there is still a lack of attention to the dynamic operation feature of urban sewer systems during precipitation events. To fill this gap, we proposed a novel approach that integrates hydraulic characteristics and the topological structure of a sewer network system. This approach aims to identify influential nodes, which contribute to the connectivity of the sewer network amidst dynamic changes in inflow during precipitation events. Furthermore, we adopted rain barrels to serve as exemplars of GI, and 14 GI layout schemes are produced based on the different ranks of influential nodes. Implementing GI measures on both poorly performing and well-performing nodes can yield distinct benefits in mitigating node flooding. This approach provides a new perspective for stormwater management, establishing effective synergy between GI and the drainage system.
Comparison of Doppler Imaging and Microvascular Imaging in Cervical Lymph
Node Blood Flow Analysis
Authors: Yang Zhanghui , Cai Jinhua , Wang Yu , Shu Lilu , Liu Wenjun , Wang Zhiwei 
Published: May 2024

Abstract::
Cervical lymph node metastasis is an important determinant of cancer stage and the selection of an appropriate treatment plan for patients with
head and neck cancer. Therefore, metastatic cervical lymph nodes should be effectively differentiated from lymphoma, tuberculous lymphadenitis,
and other benign lymphadenopathies. The aim of this work is to describe the performance of Doppler ultrasound and superb microvascular imaging
(SMI) in evaluating blood flow information of cervical lymph nodes. In addition, the features of flow imaging in metastatic lymph nodes,
lymphoma, and tuberculous lymphadenitis were described. Compared with Doppler ultrasound, SMI, the latest blood flow imaging technology,
could detect more blood flow signals because the sensitivity, specificity, and accuracy of SMI in the diagnosis of cervical lymph node disease were
higher. This article summarizes the value of Doppler ultrasound and SMI in evaluating cervical lymph node diseases and focuses on the diagnostic
performance of SMI.
Reviewing the Impact of Machine Learning on Disease Diagnosis and Prognosis: A Comprehensive Analysis
Authors: Chandan Radha Raman , Singh Jagendra , Ravi Vinayakumar , Shivahare Basu Dev , Alahmadi Tahani Jaser , Singh Prabhishek , Diwakar Manoj 
Published: May 2024

Aim
This study aimed to explore how machine learning algorithms can enhance medical diagnostics through the analysis of illness imagery and patient data, assessing their effectiveness and potential to improve diagnostic accuracy and early disease detection.

Background
This study highlights the critical role of machine learning in healthcare, particularly in medical diagnostics. By leveraging advanced algorithms to analyse medical data and images, machine learning enhances disease detection and diagnosis, contributing significantly to improved patient outcomes and the advancement of precision medicine.

Objective
The objective of this study was to thoroughly analyse and evaluate the efficacy of machine learning algorithms in medical diagnostics, focusing on their application in interpreting illness images and patient data. The goal was to ascertain the algorithms' accuracy in disease diagnosis and prognosis, aiming to demonstrate their potential in revolutionizing healthcare through improved diagnostic precision and early disease detection.

Methods
A systematic approach has been used in this study to evaluate machine learning algorithms' effectiveness in diagnosing diseases from medical images and data. It involved selecting pertinent datasets, applying and comparing models, like SVM and K-nearest neighbors, and assessing their diagnostic accuracy and performance, aiming to identify the most effective methodologies in medical diagnostics.

Results
The results have highlighted the varying accuracy of machine learning algorithms in medical diagnostics, with a focus on the performance of models, such as SVM and K-nearest neighbors. A comparative analysis has illustrated the differential effectiveness of these algorithms across various diseases and datasets, underscoring their potential to enhance healthcare diagnostics.

Conclusion
The study has concluded that machine learning algorithms have significantly improved medical diagnostics, offering varied effectiveness across different conditions. Their potential to revolutionize healthcare is evident, with enhanced diagnostic accuracy and efficiency. Ongoing research and clinical application are essential to harness these technologies' full benefits.
Evaluasi Data Curah Hujan Satelit ERA-5 pada Berbagai Periode Data Hujan di Sub DAS Bodor.
Authors: Sitepu Haniyah , Harisuseno Donny , Fidari Jadfan 
Published: May 2024

Data curah hujan merupakan data yang sangat penting dalam pengelolaan sumber daya air, sehingga dibutuhkan data curah hujan yang baik, akurat, runtut dan panjang. Namun, ketersediaan data curah hujan di Indonesia masih kurang baik. Persebaran stasiun yang tidak merata, serta banyaknya terjadi kehilangan data, terutama pada daerah-daerah terpencil. Salah satu alternatif untuk menyelesaikan permasalahan kekurangan data tersebut adalah dengan memanfaatkan data dari satelit curah hujan. Dalam menggunakan data curah hujan satelit, harus dilakukan evaluasi terlebih dahulu. Penelitian ini dilakukan untuk mengevaluasi keandalan satelit ERA-5 pada periode bulanan, 15-harian, dan 10-harian di Sub DAS Bodor. Evaluasi dilakukan menggunakan 3 parameter statistik yaitu NSE, RSR, dan r. Hasil evaluasi menunjukkan bahwa satelit ERA-5 memiliki nilai paling andal pada periode bulanan di Sub DAS Bodor (NSE: 0,904; RSR: 0,310; r: 0,952), disusul oleh periode 15-harian (NSE: 0,754; RSR: 0,496; r: 0,875), dan periode 10-harian (NSE: 0,588; RSR: 0,642; r: 0,774).
Digital Behavior Change Intervention Designs for Habit Formation: Systematic Review
Authors: Zhu Yujie , Long Yonghao , Wang Hailiang , Lee Kun Pyo , Zhang Lie , Wang Stephen Jia 
Published: May 2024

Background
With the development of emerging technologies, digital behavior change interventions (DBCIs) help to maintain regular physical activity in daily life.

Objective
To comprehensively understand the design implementations of habit formation techniques in current DBCIs, a systematic review was conducted to investigate the implementations of behavior change techniques, types of habit formation techniques, and design strategies in current DBCIs.

Methods
The process of this review followed the PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) guidelines. A total of 4 databases were systematically searched from 2012 to 2022, which included Web of Science, Scopus, ACM Digital Library, and PubMed. The inclusion criteria encompassed studies that used digital tools for physical activity, examined behavior change intervention techniques, and were written in English.

Results
A total of 41 identiﬁed research articles were included in this review. The results show that the most applied behavior change techniques were the self-monitoring of behavior, goal setting, and prompts and cues. Moreover, habit formation techniques were identified and developed based on intentions, cues, and positive reinforcement. Commonly used methods included automatic monitoring, descriptive feedback, general guidelines, self-set goals, time-based cues, and virtual rewards.

Conclusions
A total of 32 commonly design strategies of habit formation techniques were summarized and mapped to the proposed conceptual framework, which was categorized into target-mediated (generalization and personalization) and technology-mediated interactions (explicitness and implicitness). Most of the existing studies use the explicit interaction, aligning with the personalized habit formation techniques in the design strategies of DBCIs. However, implicit interaction design strategies are lacking in the reviewed studies. The proposed conceptual framework and potential solutions can serve as guidelines for designing strategies aimed at habit formation within DBCIs.
Diagnostics and Treatment of Peptic Ulcer in Adults (Clinical Guidelines of the Russian Gastroenterological Association, the Russian Society of Colorectal Surgeons, the Russian Endoscopic Society and the Scientific Society for the Clinical Study of Human Microbiome)
Authors: Ivashkin V. Т. , Mayev I. V. , Tsarkov Р. V. , Korolev М. Р. , Andreev D. N. , Baranskaya Е. К. , Bordin D. S. , Burkov S. G. , Derinov А. А. , Efetov S. К. , Lapina Т. L. , Pavlov Р. V. , Pirogov S. S. , Poluektova Е. А. , Tkachev А. V. , Trukhmanov А. S. , Uljanin А. I. , Fedorov Е. D. , Sheptulin А. А. 
Published: May 2024

Aim. The guidelines set out the modern methods of diagnostics and treatment of peptic ulcer and are created for gastroenterologists, primary care physicians, general practitioners, surgeons, endoscopists.Key points. The clinical guidelines contain modern views on the etiology and pathogenesis of peptic ulcer, its clinical features, methods of laboratory and instrumental diagnostics, the main approaches to conservative and surgical treatment. They include the criteria for assessment of the quality of medical care, the algorithm of the doctor's actions, as well as information for the patient.Conclusion. Knowledge of modern methods of diagnostics and therapy of peptic ulcers will contribute to improving the results of its treatment.