bluuebunny/crossref_metadata_2025_split huggingface dataset:
A trustworthy and reliable multi-keyword search inblockchain-assisted cloud-edge storage
Authors: Liu Xingchen , Zhang Shaohui , Huang Haiping , Malekian Reza 
Published: August 2023

Abstract
Edge computing has low transmission delay and unites more agile interconnected devices spread acrossgeographies, which enables cloud-edge storage more suitable for distributed data sharing. This paper proposes a trustworthy and reliable multi-keyword search (TRMS) in blockchain-assisted cloud-edgestorage, where data users can choose a faster search based on edge servers or a wider search based on cloud servers. To acquire trustworthy search results and find reliable servers, the blockchain-based smart contract is introduced in our scheme, which will execute the search algorithm and update the score-based trust management model. In this way, search results and trust scores will be published and recorded on the blockchain. By checking search results, data users can judge whether the returned documents are top-k documents. Based on the trust management model, we can punish the malicious behavior of search servers, while data users can choose more reliable servers based on trust scores. To improve efficiency, we design a threshold-based depth-first search algorithm. Security analysis and extensive experiments are conducted to prove the security and efficiency of the proposed scheme.
Evaluation of Tp-e interval and Tp-e/QT ratio in dermatomyositis and analysis of their relationship with inflammation
Authors: Wang Hui , Lin Ping , Wang Yiwen 
Published: August 2023

Abstract
Objective.
Dermatomyositis(DM) is a chronic multi-systemic inflammatory rheumatic disorder. Malignant arrhythmia are the leading cause of morbidity and mortality in patients withDM. The Tp-e interval and Tp-e/QT ratio have been accepted as new markers for the assessment of myocardial repolarization and ventricular arrhythmogenesis. The aim of this study was to evaluate ventricular repolarization by using Tp-e interval and Tp-e/QT ratio in patients with DM, and to assess the relation with inflammation.
Methods.
This study included 281 DM patients (180 females, 101 males; mean age 52.73 ± 15.80 years) and 281 control subjects (180 females, 101 males; mean age 53.38 ± 15.72 years). QTc, Tp–e interval and Tp–e/QT ratio were measured from the 12-lead ECG. The plasma level of blood routine test, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) were measured. These parameters were compared between groups.
Results.
No statistically significant difference was found between two groups in terms of basic characteristics. In electrocardiographic parameters analysis, QTc, Tp–e interval and Tp–e/QT ratio were significantly increased in DM patients compared the control group (441.44 ± 26.62 ms vs 422.72 ± 11.7 ms and 104.16 ± 24.34 ms vs 77.23 ± 16.25 ms and 0.27 ± 0.06 ms vs 0.20 ± 0.04 ms, all P value < 0.001). Tp–e interval and Tp–e/QT were positively correlated with NLR, CRP, and ESR (all P value < 0.001).
Conclusion.
Our study demonstrated that QTc, Tp-e interval, and Tp-e/QT ratio were increased in DM patients. Also, the Tp–e interval and Tp–e/QT ratio were positively correlated with the level of NLR, CRP, and ESR.
High levels of NfL, GFAP, TAU and UCH-L1 as potential predictor biomarkers of severity and lethality in acute COVID-19
Authors: Salvio Andreza Lemos , Fernandes Renan Amphilophio , Ferreira Helena França Alcaraz , Duarte Larissa Araujo , Gutman Elisa Gouvea , Raposo-Vedovi Jessica Vasques , Filho Carlos Henrique Ferreira Ramos , Coelho Wagner Luis da Costa Nunes Pimentel , Passos Giselle Fazzioni , Andraus Maria Emília Cosenza , Gonçalves João Paulo da Costa , Cavalcanti Marta Guimarães , Amaro Marisa Pimentel , Kader Rafael , Medronho Roberto de Andrade , Figueiredo Cláudia Pinto , Amado-Leon Luciane Almeida , Alves-Leon Soniza 
Published: August 2023

Abstract
Few studies showed that neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), total tubulin associated unit (TAU), and ubiquitin carboxy-terminal hydrolase-L1 (UCH-L1) may be related to neurological manifestations and severity during and after SARS-CoV-2 infection. The objective of this work was to investigate the relationship among nervous system biomarkers (NfL, TAU, GFAP and UCH-L1) and viral loads with heterogeneous outcomes in a cohort of severe COVID-19 patients admitted in Intensive Care Unit (ICU) of a university hospital. For that, 108 subjects were recruited within the first five days at ICU. In parallel, 18 mild COVID-19 patients were enrolled. Severe COVID-19 group was divided between “deceased” and “survivor”. All subjects were positive for SARS-CoV-2 detection. NfL, total TAU, GFAP and UCH-L1 quantification in plasma was performed using SIMOA SR-X platform. Of 108 severe patients (mean age 62.92 years old; male: 49.08%; female: 50.92%). Among them, thirty-six (33.33%) presented neurological manifestation and forty-one (37.96%) died. All four biomarkers – GFAP, NfL, TAU and UCH-L1 – were significantly higher among deceased patients in comparison to survivors (p < 0.05). Analyzing biochemical biomarkers, higher Ferritin Peak levels was related to death (p < 0.0001). In multivariate analysis, GFAP, NfL, TAU, UCH-L1 and Ferritin Peak were correlated to death. Regarding SARS-CoV-2 viral load, no statistical difference was observed for any group. Thus, Ferritin, NFL, GFAP, TAU and UCH-L1 are early biomarkers of severity and lethality of SARS-COV-2 infection and may be important tools for therapeutic decision-making in the acute phase of disease.
Thermocapillary Convection Of Evaporating Thin Nanofluid Layer In A Rectangular Cavity
Authors: Tao Yuequn , Liu Qiusheng , Qin Jun , Zhu Zhiqiang 
Published: August 2023

Abstract
Thermocapillary convection of nanofluid with evaporating phase change interface occurs in a variety of industrial processes such as micro/nano fabrication, ink-jet printing, and thin film coatings, etc. Previous studies have mostly focused on the phenomena of thermocapillary convection in pure fluids without phase change. This paper reports the first fundamental experimental work on thermocapillary flow of nanofluid thin liquid layer under effect of evaporation. This research focuses on the behavior of volatile thin nanofluid liquid layer in a rectangular test cell under the effects of horizontal temperature gradient. The buoyancy effect can be ignored inside this thin liquid layer, which is similar to the results in microgravity condition. HEE7200 and HFE7200-Al2O3 nanofluid are used as working fluid to analyze the effect of nanoparticles addition. The results indicate that the linear relationship between the thickness of the liquid layer and the duration of evaporation does not change by nanoparticles addition. HFE7200-Al2O3 nanofluid always has higher evaporation rate than its base fluid in the temperature difference range of 2.98 to 13.92℃. The critical Marangoni number for nanofluid is lower than that of pure fluid, which indicates that nanoparticles addition promotes the flow pattern transition.
Build an accurate 3D geometrical model of a soft knife profile of abrasive water jet
Authors: Chen Ming , Zhang Shijin , Wu Yuqiang , Wang Hongxia 
Published: August 2023

Abstract
Virtual machining simulation is becoming a must-have or an important tool currently in traditional machining process. With it, a series of trial machining can be avoided. However, the situation is different for high-energy-beam cutting. Till now, there is no accurate virtual cutting simulation tool which could simulate the physical cutting process accurately. As a soft knife, whose shape is changing dynamically, it is a big challenge to accurately define the tool shape and build an accurate 3D geometrical model as a virtual model for simulation. Aiming at abrasive water jet (AWJ) machining, a new method to build a soft knife profile based on energy distribution analysis has been explored in this paper. Through 3D point cloud data of kerf profile, a 3D model of the abrasive water jet profile has been built under different working conditions. To evaluate the effectiveness of the self-defined tool shape, the compensation strategy based on 3D AWJ profile has been carried out in the actual cutting process. The results show that 3D AWJ profile is beneficial to improve the machining accuracy. And this method can be extended to other high-energy-beam cutting tools such as laser and plasma.
Approaches for accelerating synchronization between photosensitive neurons in a coupled memory delay system
Authors: Zhou Shu , Huang Guodong , Zhu Rui , Wang Yunhai , Chai Yuan 
Published: August 2023

Abstract
After being stimulated by external light, photoreceptor cells in the retina produce action potentials, which are then transmitted to the visual center to create vision. Reduced vision and even blindness can result from changes in photoreceptor cells. The most cutting-edge treatment available right now is to implant electronic chips to replace the damaged photoreceptor cells. Therefore, it is crucial to understand the biophysical processes that the photoreceptor cell goes through. However, the pertinent biophysical mechanisms are still not entirely understood. This study adds phototube to the FitzHugh Nagumo (FHN) model, builds a light-dependent neuron model by using phototube's photosensitive properties, and proposes a coupled photosensitive neuron model. The effects of synaptic connection between neurons, information transmission delay, external stimulation, electromagnetic effects generated by the memristors, and noise stimulation on the synchronization of the neuronal system are all fully taken into account by the model. The outcomes of the experiment suggest that these variables regulate the speed and stability of synchronization. In an effort to develop a theoretical foundation for the treatment of visual problems, the results of the numerical simulation serve as a certain point of reference for research into the biophysical mechanisms of photosensitive neurons.
Bullying Victimization among in-School Adolescents in Sierra Leone: A cross-sectional Analysis of the 2017 Sierra Leone Global School-Based Health Survey.
Authors: Osborne Augustus , James Peter Bai , Bangura Camilla , Williams Samuel Maxwell Tom , Kangbai Jia Bainga , Lebbie Aiah 
Published: August 2023

Abstract
Background
Adolescent bullying victimization is recognized as a public health and mental health problem in many countries. However, data on bullying victimization's prevalence and risk factors is scarce in sub-Saharan Africa Sierra Leone. This research aimed to determine bullying victimization prevalence and its associated factors among Sierra Leonean school-going adolescents.
Methods
The Sierra Leone 2017 Global School-based Health Survey (GSHS) dataset was analyzed. The outcome variable was the respondent's self-report of bullying victimization ("How many days in the previous 30 days were you bullied?"). Descriptive, Pearson chi-square and binary logistic regression analyses were conducted. The regression analysis yielded adjusted odds ratios (aOR) with 95% confidence intervals (CIs) and a significance level of p 0.05.
Results
Bullying victimization was prevalent among 48.7% of the in-school adolescents. Adolescents who drank alcohol [aOR = 2.48, 95% CI = 1.50–4.10], who reported feelings of loneliness [aOR = 1.51, 95% CI = 1.07–2.14] and who had attempted suicide [aOR = 1.72, 95% CI = 1.03–2.87] were also more likely to be bullied. Also, school truancy [aOR = 1.53, 95% CI = 1.24–1.88] among teenagers was associated with an increased risk of being bullied.
Conclusions
Our findings suggest that bullying is a widespread problem among Sierra Leonean school-aged youth, and alcohol drinking, loneliness, suicide attempt and school truancy are potential risk factors. In light of the aforementioned causes of bullying in schools, policymakers and school administrators in Sierra Leone need to develop and execute anti-bullying policies and initiatives that target the underlying risk factors of bullying among teenagers.
Imaging artifacts and quality evaluation with ultrawide-field swept-source OCTA in diabetic retinopathy
Authors: Wang Xiang-ning , Li Shuting , Cai Xuan , Li Tingting , Long Da , Wu Qiang 
Published: August 2023

Abstract
Background: To evaluate the prevalence and types of artifacts in ultrawide-field swept-source optical coherence tomography angiography (SS-OCTA) scans of diabetic retinopathy (DR) patients.
Methods: This study was a prospective, observational study conducted from May 2022 to October 2022. Participants comprised individuals with proliferative diabetic retinopathy (PDR), nonproliferative diabetic retinopathy (NPDR), no diabetic retinopathy, and healthy controls. SS-OCTA imaging was performed, and a 5-scan composite with a larger field of view (23.5 mm * 17.5 mm) was captured using built-in software. Two experienced ophthalmologists analyzed the images independently, and the image quality and artifact prevalence were recorded and analyzed.
Results: The study included 70 eyes (16 with PDR, 24 with NPDR, 12 eyes of diabetic patients without DR, and 18 healthy eyes) in 70 subjects. The most prevalent artifacts were loss of signal in 63 eyes (90%) and displacement artifact and masking artifact in 43 eyes (61.4%). Patients with more severe stages of DR had higher artifact scores (P<0.05). Multivariate regression analysis indicated that DR severity was the most important factor influencing artifact scores (P<0.05).
Conclusions: In OCTA photos, various artifacts arise at different frequencies. It is crucial to qualitatively evaluate the images to ensure their quality. The results demonstrate that DR severity has a significant correlation with artifact scores.
Unraveling the Interplay Between Root Exudates, Microbiota, and Rhizosheath Formation in Pearl Millet
Authors: Alahmad Abdelrahman , Harir Mourad , Fochesato Sylvain , Tulumello Joris , Walker Alesia , Barakat Mohamed , Ndour Papa Mamadou Sitor , Schmitt-Kopplin Philippe , Cournac Laurent , Laplaze Laurent , Heulin Thierry , Achouak Wafa 
Published: August 2023

Abstract
Background
The rhizosheath, a cohesive soil layer firmly adhering to plant roots, plays a vital role in facilitating water and mineral uptake. In pearl millet, rhizosheath formation is genetically controlled and influenced by root exudates. Here, we investigated the impact of root exudates on the microbiota composition, interactions, and assembly processes, and rhizosheath structure in pearl millet using four distinct lines with contrasting soil aggregation abilities.
Results
Utilizing 16S rRNA gene and ITS metabarcoding for microbiota profiling, coupled with FTICR-MS metabonomic analysis of metabolite composition in distinct plant compartments and root exudates, we revealed substantial disparities in microbial diversity and interaction networks. The ß-NTI analysis highlighted bacterial rhizosphere turnover driven primarily by deterministic processes, showcasing prevalent homogeneous selection in root tissue and RAS. Conversely, fungal communities were more influenced by stochastic processes. In bulk soil assembly, a combination of deterministic and stochastic mechanisms shapes composition, with deterministic factors exerting a more pronounced role. Metabolic profiles across shoots, roots, and root-adhering soil (RAS) in different pearl millet lines mirrored their soil aggregation levels, emphasizing the impact of inherent plant traits on microbiota composition and unique metabolic profiles in root tissues and exudates. Notably, exclusive presence of antimicrobial compounds, including DIMBOA and H-DIMBOA, emerged in root exudates and roots of low aggregation lines.
Conclusions
This research underscores the pivotal influence of root exudates in shaping the root-associated microbiota composition across pearl millet lines, entwined with their soil aggregation capacities. These findings underscore the interconnectedness of root exudates and microbiota, which jointly shape rhizosheath structure, deepening insights into plant-microbe interactions and ecological processes shaping rhizosphere microbial communities. Deciphering plant-microbe interactions and their contribution to soil aggregation and microbiota dynamics holds promise for the advancement of sustainable agricultural strategies.
Analysis of the carbon effect of high-standard basic farmland based on the whole life cycle
Authors: Li Xuemei , He Ying , Fu Yanhua , Wang Yajie 
Published: August 2023

Abstract
Based on the whole life cycle theory, the carbon effect of three different sizes of high-standard basic farmland construction projects is measured and analysed, and the results show that (1) the carbon emissions generated during the construction of high-standard basic farmland projects and the carbon absorption capacity at the later stage are different for projects of different sizes. (2) The carbon emissions of different scales of high-standard basic farmland projects will increase during the construction stage. (3) The results of carbon effect changes in the later operation and management stage show that the high-standard basic farmland construction projects will help reduce the carbon emissions of the field ecosystem where the farmland is located and increase its carbon sink capacity after the completion of construction, and the effect is more obvious in larger projects. (4) The emission reduction and carbon sequestration capacity of the farmland after remediation are improved to different degrees, which is more conducive to the ecological development of agricultural production and ecological environmental protection in the relevant areas.
Research on Utilization Technology of Waste Heat from Dead Steam in Nuclear Power Plant
Authors: Zhang Ming , Zhang Shoujie , Ge Yunzheng 
Published: August 2023

Abstract
Based on the waste status of exhausted steam waste heat in nuclear power plant conventional island, schemes to generate electricity by extracting waste heat from steam are proposed. Through the design and research of power generation scheme based on waste heat of exhausted steam, design and analysis of turbine, analysis of scheme applicability, the feasibility of using exhausted steam for power generation is discussed. Final studies show that, according to the characteristics of exhausted steam, the steam power generation or Rankine cycle of organic working medium method can be used to build the waste heat utilization system.
Tumor-to-Tumor Spread: A Case Report and Literature Review of Renal Cell Carcinoma Metastasis into Thyroid Cancer
Authors: Gawlik Cassidy , Lane Jason , Horattas Mark 
Published: August 2023

Abstract
Tumor-to-tumor metastasis is a rare, yet important entity. Patients with a history of renal cell carcinoma (RCC) may have tumor deposits to the thyroid gland preceding or following their initial cancer diagnosis for many years. The diagnosis can be challenging, and clinicians must remain suspicious of a newly found thyroid nodule in a patient with a history of RCC. In this review, we report a case of a patient with RCC who was incidentally found to have a thyroid nodule on surveillance imaging found to be consistent with tumor-to-tumor metastasis from RCC into papillary thyroid carcinoma. It is imperative to consider this diagnosis as the thyroid is the most common site of spread, and treatment with partial or total thyroidectomy has led to improved survival.
A Novel Saliva-Based miRNA Profile to Diagnose and Predict Oral Cancer
Authors: Punyadeera Chamindie , Balakittnen Jaikrishna , Weeramange Chameera Ekanayake , Wallace Daniel F. , Duijf Pascal H.G. , Cristino Alexandre S. , Hartel Gunter , Barrero Roberto A. , Taheri Touraj , Kenny Liz , Vasani Sarju , Batstone Martin , Breik Omar 
Published: August 2023

Abstract
Oral cancer (OC) is the most common form of head and neck cancer. Despite the high incidence and unfavourable patient outcomes, currently, there are no biomarkers for the early detection of OC. This study aims to discover, develop, and validate a novel saliva-based microRNA signature for early diagnosis and prediction of OC risk in oral potentially malignant disorders (OPMD).
The Cancer Genome Atlas (TCGA) miRNA sequencing data and small RNA sequencing data of saliva samples were used to discover differentially expressed miRNAs. Identified miRNAs were validated in saliva samples of OC (n=50), OPMD (n=52), and controls (n=60) using quantitative real-time PCR.
Eight differentially expressed miRNAs (miR-7-5p, miR-10b-5p, miR-182-5p, miR-215-5p, miR-431-5p, miR-486-3p, miR-3614-5p, and miR-4707-3p) were identified in the discovery phase and were validated. The efficiency of our eight-miRNA signature to discriminate OC and controls was: Area Under Curve (AUC): 0.954, sensitivity: 86%, specificity: 90%, positive predictive value (PPV): 87.8% and negative predictive value (NPV): 88.5% whereas between OC and OPMD was: AUC: 0.911, sensitivity: 90%, specificity: 82.7%, PPV: 74.2% and NPV: 89.6%. We have developed a risk probability score to predict the development of OC in OPMD patients.
We established a salivary miRNA signature that can aid in diagnosing and predicting OC, revolutionizing the management of patients with OPMD. Together, our results shed new light on the management of OC by salivary miRNAs to the clinical utility of using miRNAs derived from saliva samples.
Machine learning-based decision support system for the prognostication of neurological outcome in the successfully resuscitated OHCA patient
Authors: Lee Kwang-Sig , Park Sang-Hyun , Lee Sung Woo , Kim Su Jin 
Published: August 2023

Abstract

Background
This study uses machine learning and multi-center registry data for analyzing the determinants of favorable neurological outcome in the out-of-hospital cardiac arrest (OHCA) patient and developing its decision support systems for various subgroups.
Methods
Data came from Korean Cardiac Arrest Research Consortium registry with 2679 OHCA patients aged 18 or more with the return of spontaneous circulation (ROSC). The dependent variable was favorable neurological outcome (Cerebral Performance Category scores 1–2) and 68 independent variables were included, e.g., first monitored rhythm, in-hospital cardiopulmonary resuscitation (CPR) duration and post-ROSC pH. The random forest was used for identifying major determinants of favorable neurological outcome and developing its decision support systems for various subgroups stratified by major variables.
Results
Based on random forest variable importance, major determinants of OHCA outcome were in-hospital CPR duration (0.0824), in-hospital electrocardiogram on emergency room arrival (0.0692), post-ROSC pH (0.0579), prehospital ROSC before emergency room arrival (0.0565), coronary angiography (0.0527), age (0.0415), first monitored rhythm (EMS) (0.0402), first monitored rhythm (community) (0.0401), early coronary angiography within 24 hours (0.0304) and scene arrival to CPR stop (0.0301). It was also found that patients can be divided to 6 subgroups in terms of prehospital ROSC and first monitored rhythm (EMS) and that a decision tree can be developed as a decision support system for each subgroup to find its effective cut-off points regarding in-hospital CPR duration, post-ROSC pH, age and hemoglobin.
Conclusions
We identified the major determinants of favorable neurological outcome in successfully resuscitated OHCA patients using machine learning. This study demonstrated the strengths of the random forest as an effective decision support system for each stratified subgroup (prehospital ROSC and first monitored rhythm by EMS) to find its own optimal cut-off points for major in-hospital variables (in-hospital CPR duration, post-ROSC pH, age and hemoglobin).