bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utilization of the Google Earth Engine for the evaluation of daily soil temperature derived from Global Land Data Assimilation System in two different depths over a semiarid region
Authors: Akbari Abolghasem , Rajabi Jaghargh Majid , Abu Samah Azizan , Peter Cox Jonathan , Gholamzadeh Mojtaba , Araghi Alireza , Saco Patricia M. , Khosravi Khabat 
Published: July 2024

AbstractThe Google Earth Engine (GEE) was used to investigate the performance of the Global Land Data Assimilation System (GLDAS) soil temperature (ST) data against observed ST from 13 synoptic stations over a semiarid region in Iran. Three‐hourly ST data were collected and analyzed in two depths (0–10 cm; 40–100 cm) and 5 years. In each depth, GLDAS‐Noah ST data were evaluated for daily minimum, maximum, and average ST (i.e., Tmin, Tmax, and Tavg). Based on the correlation coefficient, Kling–Gupta Efficiency, and Nash–Sutcliffe Efficiency the overall performance of the GLDAS‐Noah is 0.96, 0.66, and 0.79 for Tmin; 0.97, 0.84, and 0.89 for Tavg; and 0.95, 0.89, and 0.89 for Tmax, respectively in the first layer. Likewise, 0.97, 0.85, and 0.86 for Tmin; 0.97, 0.77, and 0.80 for Tavg; and 0.97, 0.69, and 0.69 for Tmax are obtained in the second layer. However, there is a significant negative bias which tends to underestimate ST in the two investigated layers, given by an average bias over all the stations analyzed of −24%, −12%, and −5% for Tmin, Tavg, and Tmax in the first layer, and average bias of −8%, −13%, and −17% for Tmin, Tavg, and Tmax in the second layer. This study reveals that GLDAS‐Noah‐derived ST can be used in arid regions where little or no observation data is available. Moreover, GEE performed as an advanced geospatial processing tool in regional scale analysis of ST in different layers.
Novel compound heterozygous variants in MARVELD2 causing autosomal recessive hearing loss in two Chinese families
Authors: Shi Xinyu , Liu Xiaozhou , Zong Yanjun , Zhao Zhengdong , Sun Yu 
Published: July 2024

AbstractBackgroundHereditary hearing loss is an important component of congenital hearing loss. MARVELD2 (OMIM ID:610572), located in the DFNB49 locus, which encodes a tight junction protein tricellulin playing an important role in the sensory epithelial barrier of the inner ear, may contribute to nonsyndromic autosomal recessive hereditary hearing loss.MethodsTwo Han Chinese pedigrees with hearing loss underwent clinical and genetic analyses. Variants were detected by targeted next‐generation sequencing and sequencing data were compared with the Human Genome Reference (GRCh 37/hg 19) to identify mutant genes and loci. Furthermore, online tools such as RDDC, SpliceAI, and REVEL were used to predict risks from different variants.ResultsBoth two probands failed neonatal hearing screening and were diagnosed with sensorineural hearing loss. A total of 3 mutations were detected in the two families, c.1331+1G>A, c.1325A>G, and c.782G>A. According to ACMG/AMP guidelines, they were judged to be pathogenic, uncertain significance, and uncertain significance, respectively.ConclusionsThese findings contribute to a better understanding of the relationship between different variants of MARVELD2 and hearing. This could further expand the spectrum of deafness gene mutations and contribute to deafness patient management and genetic counseling.
Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN): An introduction to the Urinary Urgency Phenotyping Protocol LURN II
Authors: Cameron Anne P. , Yang Claire C. , Bradley Catherine S. , Griffith James W. , Kirkali Ziya , Clemens J. Quentin , Kreder Karl J. , Kenton Kimberly S. , Andreev Victor P. , Amundsen Cindy L. , Jelovsek J. Eric , Helfand Brian T. , Lai H. Henry ,   the LURN Study Group
Published: July 2024

AbstractAimsThe Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) is undertaking a new cohort study in LURN II including cases and controls.MethodsThis new cohort was enrolled to specifically study urinary urgency and urgency urinary incontinence, lower urinary tract symptoms (LUTSs) that are often difficult to treat due to a lack of understanding of their phenotypes and pathophysiologies.ResultsThis paper will focus on the motivation for the second iteration of LURN and highlight the new research techniques and plans for more thorough phenotyping of this population.ConclusionsThis paper will outline the gaps in understanding in treating LUTSs, specifically urinary urgency.
Privacy Preservation of Large Language Models in the Metaverse Era: Research Frontiers, Categorical Comparisons, and Future Directions
Authors: Huang Dabin , Ge Mengyu , Xiang Kunlan , Zhang Xiaolei , Yang Haomiao 
Published: July 2024

ABSTRACTLarge language models (LLMs), with their billions to trillions of parameters, excel in natural language processing, machine translation, dialog systems, and text summarization. These capabilities are increasingly pivotal in the metaverse, where they can enhance virtual interactions and environments. However, their extensive use, particularly in the metaverse's immersive platforms, raises significant privacy concerns. This paper analyzes existing privacy issues in LLMs, vital for both traditional and metaverse applications, and examines protection techniques across the entire life cycle of these models, from training to user deployment. We delve into cryptography, embedding layer encoding, differential privacy and its variants, and adversarial networks, highlighting their relevance in the metaverse context. Specifically, we explore technologies like homomorphic encryption and secure multiparty computation, which are essential for metaverse security. Our discussion on Gaussian differential privacy, Renyi differential privacy, Edgeworth accounting, and the generation of adversarial samples and loss functions emphasizes their importance in the metaverse's dynamic and interactive environments. Lastly, the paper discusses the current research status and future challenges in the security of LLMs within and beyond the metaverse, emphasizing urgent problems and potential areas for exploration.
Role of uric acid in neurodegenerative diseases, focusing on Alzheimer and Parkinson disease: A new perspective
Authors: Alrouji Mohammed , Al‐kuraishy Hayder M. , Al‐Gareeb Ali I. , Alshammari Mohammed S. , Alexiou Athanasios , Papadakis Marios , Bahaa Mostafa M. , Batiha Gaber El‐Saber 
Published: July 2024

AbstractNeurodegenerative diseases (NDs) such as Alzheimer disease (AD) and Parkinson disease (PD) are group of diseases affecting the central nervous system (CNS) characterized by progressive neurodegenerations and cognitive impairment. Findings from different studies highlighted the beneficial and detrimental effects of serum uric acid on the development and progression of NDs. Therefore, this mini‐review aims to discuss the beneficial and detrimental effects of uric on NDs. The neuroprotective effect of uric acid is mainly related to the antioxidant effect of uric acid which alleviates oxidative stress‐induced neurodegeneration in AD and PD. However, long‐term effect of hyperuricemia prompts for the development and progression of cognitive impairment. Hyperuricemia is associated with cognitive impairment and dementia, and gout increases dementia risk. In addition, hyperuricemia can cause cerebral vascular injury which is a risk factor for vascular dementia and cognitive impairment. Taken together, the relationship between uric acid and NDs risk remains conflicting. Hence, preclinical and clinical studies are indicated in this regard.
Enhanced lithium‐ion battery state‐of‐charge estimation for Electric Vehicles using the AOA‐DNN approach
Authors: Thangaraj Kokilavani , Indiran Rajarajeswari , Ananth Vasantharaj , Raman Mohan 
Published: July 2024

AbstractElectric vehicles (EVs) battery management systems (BMSs) rely on exact state of charge (SoC) estimations to guarantee efficient and safe operation. Lithium‐ion batteries (LIBs) are favored for EVs due to their extended lifespan, high energy density, and minimal self‐discharge and high voltage. To address these issues, this research propose a LIB SoC prediction based on an actual BMS in EVs. The main objective is improving SoC of LIB. The proposed hybrid strategy is the combined performance of both the dynamic neural networks (DNN) and arithmetic optimization algorithm (AOA). Commonly it is named as DNN‐AOA technique. The SoC of Lithium‐ion batteries are predicted using the DNN approach. The proposed AOA is used to optimize the weight parameter of DNN to enhance prediction accuracy and reliability. By then, the operational MATLAB platform has adopted the proposed framework, and existing procedures are used to compute its execution. The proposed method demonstrates superior existing like Bayesian network (DBN), random vector functional link neural network (RVFLNN) and Gaussian progress regression (GPR). The proposed method yields a lower error value of 0.1 and a higher accuracy value of 98% compared with other existing methods.
Predicting Tracheostomy Need on Admission to the Intensive Care Unit—A Multicenter Machine Learning Analysis
Authors: Nguyen Matthew , Amanian Ameen , Wei Meihan , Prisman Eitan , Mendez‐Tellez Pedro Alejandro 
Published: July 2024

AbstractObjectiveIt is difficult to predict which mechanically ventilated patients will ultimately require a tracheostomy which further predisposes them to unnecessary spontaneous breathing trials, additional time on the ventilator, increased costs, and further ventilation‐related complications such as subglottic stenosis. In this study, we aimed to develop a machine learning tool to predict which patients need a tracheostomy at the onset of admission to the intensive care unit (ICU).Study DesignRetrospective Cohort Study.SettingMulticenter Study of 335 Intensive Care Units between 2014 and 2015.MethodsThe eICU Collaborative Research Database (eICU‐CRD) was utilized to obtain the patient cohort. Inclusion criteria included: (1) Age >18 years and (2) ICU admission requiring mechanical ventilation. The primary outcome of interest included tracheostomy assessed via a binary classification model. Models included logistic regression (LR), random forest (RF), and Extreme Gradient Boosting (XGBoost).ResultsOf 38,508 invasively mechanically ventilated patients, 1605 patients underwent a tracheostomy. The XGBoost, RF, and LR models had fair performances at an AUROC 0.794, 0.780, and 0.775 respectively. Limiting the XGBoost model to 20 features out of 331, a minimal reduction in performance was observed with an AUROC of 0.778. Using Shapley Additive Explanations, the top features were an admission diagnosis of pneumonia or sepsis and comorbidity of chronic respiratory failure.ConclusionsOur machine learning model accurately predicts the probability that a patient will eventually require a tracheostomy upon ICU admission, and upon prospective validation, we have the potential to institute earlier interventions and reduce the complications of prolonged ventilation.
Numerical and experimental study on anisotropic heat transfer behaviors of quartz fabric composite preforms: Multiple micro‐scale models method
Authors: Wu Hui , Wang Xi , Peng Haoyue , Ding Xiang , Du Peijian , Han Zian , Gao Xiaoping , Xu Peng , Zhu Xianfeng 
Published: July 2024

AbstractThis paper presents a comprehensive study on anisotropic heat transmission behaviors in quartz fiber fabrics. Considering the random distribution characteristic of fibers within the yarn, an innovative two‐scale finite element method (tFEM) is introduced, incorporating multiple micro‐scale fiber models (MMFM) based on scanning electron microscope (SEM) observations. MMFM are divided into 8 distinct models to capture intricate fiber arrangements. The macro‐scale fabric model is constructed based on the geometric structure analysis by Micro‐CT technology. Both micro‐ and macro‐scale models are assembled with the air matrix to form the two‐phase composite model. The Hot‐Disk thermal analysis instrument is applied to measure the anisotropic thermal conductivity (ATC). Numerical results from MMFM shows more excellent agreements with the experimental ones at 3D orthogonal directions of fabrics, i.e., the error rates of the thermal conductivity in the warp, weft and thickness directions between numerical and experimental methods are all less than 3%, which indicates the tFEM including MMFM in this paper is more accurate than the tFEM including OSMFM. In addition, the temperature distribution and heat transmission differences due to fiber arrangements are simulated and illustrated through the MMFM. Afterwards, temperature drop and isothermal characteristics are demonstrated in this study.Highlights
Effects of fiber arrangements on steady heat transfer behaviors at micro‐scale are illustrated.
Isothermal and temperature‐drop characteristics at micro‐ and macro‐scale are simulated and studied.
The transverse isotropy of thermal conductivity at micro‐scale and the anisotropy of that at macro‐scale are revealed.
The Reliability of Ultrasound Markers in Identifying Fetuses With a Life‐Limiting Skeletal Dysplasia
Authors: Crane Haley M. , Schindewolf Erica , Burrill Natalie , Debari Suzanne , Khalek Nahla , Paidas Teefey Christina , Soni Shelly , Coleman Beverly , Moldenhauer Julie S. , Gebb Juliana 
Published: July 2024

ABSTRACTObjectiveTo determine the diagnostic performance of ultrasound markers associated with life‐limiting fetal skeletal dysplasia in a fortified cohort.MethodsRetrospective review from 2013 to 2023 of pregnancies with suspected fetal skeletal dysplasia. Ultrasound evaluation included measurements predictive of a life‐limiting dysplasia: thoracic circumference/abdominal circumference (TC/AC) < 0.6, femur length/abdominal circumference (FL/AC) < 0.16, and thoracic circumference (TC) < 2.5th percentile. Demographics, ultrasound findings, genetic testing, and fetal/neonatal outcome were reviewed.ResultsOf 96 fetuses with complete outcome data, 47 (49%) had a non‐life‐limiting dysplasia and 49 (51%) had a life‐limiting dysplasia. 22 (23%) had no life‐limiting markers, 42 (44%) had one, 27 (28%) had two, and 5 (5%) had three. FL/AC < 0.16 and TC < 2.5th percentile were associated with life‐limiting dysplasia (p < 0.001; p < 0.001), while TC/AC < 0.6 was rare and did not reach statistical significance (p = 0.056). The positive predictive value (PPV) for predicting life‐limiting dysplasia increased from 50% to 78% to 100% with one, two, or three markers. The PPV of the two life‐limiting markers was significantly higher in those diagnosed at < versus ≥ 28 weeks (90% vs. 43%, p = 0.02) but the analysis was limited by small numbers in the ≥ 28 weeks cohort. The negative predictive value of no life‐limiting markers was 91%.ConclusionsIn our cohort, the presence of two life‐limiting ultrasound markers prior to 28 weeks was highly suggestive of a life‐limiting dysplasia, whereas the absence of life‐limiting markers was strongly associated with a non‐life‐limiting dysplasia throughout gestation. Nonetheless, individual markers had a poor predictive value of lethality, and a life‐limiting diagnosis ≥ 28 weeks is challenging based on ultrasound markers alone. This highlights the importance of integrating thorough sonography, genetic testing, and balanced parental counseling.
Bio‐composite using polyhydroxyalkanoates and sustainable nanofillers derived from cellulose nanofibers and its application for an environmentally friendly packaging material
Authors: Jo Jaemin , Koo Bonwook 
Published: July 2024

AbstractPolyhydroxyalkanoates (PHA) is a carbon neutral material that contributes to reducing greenhouse gas emissions due to manufactured from biomass and easily degraded by the enzymatic effects of microorganisms in the natural environment. However, PHA exhibits poorer mechanical properties and processability compared with petroleum‐based plastics. This study used cellulose nanofiber (CNF) to improve limit of PHA. Moreover, CNF was silylated to reduce polarity difference with PHA and enhance the dispersibility of nanocellulose at PHA. At a result, the silylation process was successfully performed by Si‐CH3 stretching peaks in Fourier transform infrared spectroscopy spectra and hydrophobicity of TEOS‐MTES‐CNF (TECNF) was confirmed by observed water contact angle (147°). In addition, nanostructure of TECNF was maintained during silylation and drying process through field emission scanning electron microscopy. Moreover, the PHA/TECNF composite showed enhanced processability, and tensile strength was increase almost 37% (0.52 MPa) compared with PHA. Oxygen transmission rates (300 cc/m2۰day) and single lap shear strength (225 kPa) were determined to be at least equivalent or superior to those of commercial packaging materials. Therefore, TECNF could be considered as a reinforcing agent, nucleating agent, and plasticizer in PHA. Also, this composite has possibilities to using as environmentally friendly packaging materials.
Quantitative structure‐property relationshiptechniques for predicting carbon dioxide solubility in ionic liquids using machine learning methods
Authors: Benmouloud Widad , Euldji Imane , Si‐Moussa Cherif , Benkortbi Othmane 
Published: July 2024

AbstractIonic liquids (ILs) are considered unique and attractive types of solvents with great potential to capture carbon dioxide (CO2) and reduce its emissions into the atmosphere. On the other hand, carrying out experimental measurements of CO2solubility for each new IL is time‐consuming and expensive. Whereas, the possible combinations of cations and anions are numerous. Therefore, the preparation and design of such processes requires simple and accurate models to predict the solubility of CO2as a greenhouse gas. In the present study, two different models, namely: artificial neural network (ANN) and support vector machine optimized with dragonfly algorithm (DA‐SVM) were used in order to establish a quantitative structure–property relationship (QSPR) between the molecular structures of cations and anions and the CO2solubility. More than 10 116 CO2solubility data measured in various ionic liquids (ILs) at different temperatures and pressures were collected. 13 significant PaDEL descriptors (E2M, MATS8S, TDB6I, TDB1S, ATSC4V, MATS8M, ATSC7V, Gats2S, Gats5S, Gats5C, ATSC6V, DE, and Lobmax), temperature and pressure were considered as the model input data. For the test set data (2023 data point), the estimated mean absolute error (MAE) andR2for the ANN model are of 0.0195 and 0.9828 and 0.0219 and 0.9745 for the DA‐SVM model. The results obtained showed that both models can reliably predict the solubility of CO2in ILs with a slight superiority of the ANN model. Examination of sensitivity and outlier diagnosis examinations confirmed that the QSPR model optimized using the ANN algorithm is better suited to correlate and predict this property.
The Impact of HIV Upon the PCI Results: A Systematic Review and Meta‐Analysis
Authors: El‐Qushayri Amr Ehab , Hashan Mohammad Rashidul , Alam Md Mahfuj , Khan Muhammad Sanowar , Alqahtani Nasser G. 
Published: July 2024

ABSTRACTThe aim of this systematic review and meta‐analysis was to comprehensively evaluate the latest evidences and summarise the impact of HIV on PCI outcomes. A PRISMA guided literature search was conducted on 14 February 2024 in Web of Science, PubMed, Virtual Health Library, Google Scholar and Scopus. We searched with the term ‘(“percutaneous coronary intervention” OR “PCI”) AND (“human immunodeficiency virus” OR “HIV” OR “acquired immunodeficiency syndrome” OR “AIDS”)’ after selecting the keywords from randomly chosen included papers. We included 8 papers of 781 screened records. HIV (+) patients had significant in‐hospital, 1‐year and overall (event at the last follow up point) all‐cause mortality compared to HIV (−) group (OR: 1.73, 95%CI: 1.57–1.90, p < 0.01), (OR: 1.39, 95%CI: 1.07–1.81, p = 0.01) and (OR: 1.69, 95%CI: 1.55–1.85, p < 0.01), respectively. HIV (+) patients had significantly higher odds of developing MACE (OR: 1.35, 95%CI: 1.12–1.62, p = 0.001) compared to the HIV (−) group. No differences between both groups were detected regarding in‐hospital and overall CV mortality, TVR, TLR, post‐PCI TIMI grade 3 flow, cerebrovascular accidents and recurrent coronary events (p > 0.05). Our study revealed that people with HIV who underwent PCI in this modern era may have worse short and long‐term PCI outcomes. This finding highlights the need for specialised cardiovascular care protocols for the HIV population. However, enhanced clinical management and preventative measures are imperative to improve PCI success rates in patients with HIV.
55‐1: A Novel Modeling & Compensation Algorithm for Medium‐Term Image Sticking on AMOLED Display
Authors: Lin Xuan-Yong , Su Shang-Yu , Pai Feng-Ting , Lin Ching-Chun 
Published: July 2024

In this paper, we discuss the different type of image sticking(IS) and propose a novel algorithm for improving medium‐term IS on AMOLED display. This method could not only solve the IS effect on traditional display but also the multi‐areas frame rate (MAFR) display.For future OLED power‐saving applications, the application of MAFR becomes increasingly important. This involves categorizing the same display into high and low refresh rate zones based on display usage efficiency. When the display remains static for a period and then switches, the issue of display retention may arise. Our experimental results confirms that IS can be quantified into a model, and the algorithm is used for real‐time compensation to reduce the retention issues.
P‐105: Micro LED Total Repair Solutions for Display Application: EHD Printing, 1‐by‐1 Transfer, and Functional Nano‐ink material
Authors: Nguyen Vudat , Lee Hyungdong , Jeon Kwangsun , Son Wonil , Joung Jaewoo , Byun Doyoung 
Published: July 2024

In recent years, micro‐LED technology has become crucial for high‐definition AR/VR displays and large TVs. ENJET addresses production challenges with a specialized bonder machine, employing EHD Printing, 1‐by‐1 transfer for precise, defect‐free micro‐LED production.This work demonstrated dispensing up to 7 µm conductive bond dots via EHD inkjet printing, achieving a placement precision of 1.5 µm in both x and y directions.
P‐108: High conductivity transparent electrode with In2O3 – ZnO periodic structure and gradient oxygen concentration
Authors: Akhmedov Akhmed , Asvarov Abil , Murliev Eldar , Belyaev Victor , Abduev Aslan 
Published: July 2024

Multilayer structures based on the In‐Zn‐O (IZO) system with modulated oxygen doping have been developed as a TCF (transparent conductive film) alternative to ITO or IGZO layers in the LC and OLED displays. The minimum resistivity (3.37 Ohm*cm) and the maximum concentration of free charge carriers correspond to the layers synthesized in an atmosphere of pure argon, while the maximum mobility (39.18 cm2/V*s) corresponds to the layers synthesized in the atmosphere of both argon and oxygen 99.6%/0.4% mixture. Thin‐film periodic structures with gradient modulation of oxygen content in thickness have been fabricated by periodically changing the oxygen concentration in the composition of the working gas during spraying at a substrate temperature of 100 °C. The structures consist of alternating layers with a high concentration of free charge carriers and layers with high mobility. As a result of the single layers' thicknesses optimization the thin‐film periodic structures with a minimum resistivity of 2.89 Ohm*cm have been made. The resistivity is lower than in homogeneous layers of the same composition. The alternation of layers of optimal thickness provides high carrier mobility, it is inherent to layers synthesized in the atmosphere of 99.6/0.4 argon and oxygen mixture at high concentration. The mobility value is close to the value achieved in the layers synthesized in the pure argon atmosphere.This material provides fabrication of high quality, stable and low cost transparent electrodes or TFT layers with performances corresponding to parameters of traditional materials.