bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Microbiome After Bail-out: Testing Individual Polyps from Pocillopora verrucosa as Models for Coral Microbiology Studies
Authors: CARDOSO PEDRO , VILLELA HELENA , DÍAZ-RÚA RUBEN , BARNO ADAM , PEIXOTO RAQUEL 
Published: April 2024

Abstract
Micro-scale in vitro models are essential for the study of model organisms in highly reproducible and controlled environments. Coral research grapples with a substantial knowledge gap on micro-scale processes underlying symbiotic interactions and holobiont health, which could be addressed through the use of models adapted to microscopic studies. Individual coral polyps separated from their colonies through an acute stress-induced bail-out process have been suggested in the past as miniaturized models to study the coral holobiont. However, changes in the microbiome associated with these polyps after bail-out are still not completely understood. An aquarium experiment was therefore performed to monitor the diversity and composition of microbes of bailed-out polyps of Pocillopora verrucosa alongside their parental fragments over time. Our findings revealed no significant microbiome differences immediately following bail-out, with 80% of microbial members persisting for up to two weeks, decreasing slightly to 60% in the third week. Notably, despite a reduction in shared Amplicon Sequence Variants (ASVs), the dominant bacterial taxa's relative abundance stayed consistent across both the source fragments and bailed-out polyps for up to three weeks. This consistency underscores the potential of using micropropagates as valuable tools for microbiological research in corals. Further enhancements in polyp settlement techniques may refine these models, bolstering our capacity for comprehensive coral microbiome studies.
Design and experiment of automatic grasping manipulator for side-mounted garbage truck
Authors: Meng Xiangyan , Sun Qun , Liu Mingxian , He Shisheng , Ren Fuguo , Liu Qianglin 
Published: April 2024

Abstract
At present, for the garbage collection, high labor intensity, mechanization, automation and low level of intelligence, for the existing garbage collection mode, garbage collection and transportation facilities and technologies have been unable to quickly and timely meet the increasing demand for garbage. Aiming at the problems of unstable structure, garbage leakage and trash can destruction in the current garbage truck manipulator, this paper designs a hydraulic lever tandem drive clean and jerk type turning mechanism. To solve the problem of destroying the trash can, this paper installs a spoke-type pressure sensor on the clamp mechanism, and uses the pressure sensor to accurately measure the shrinkage of the clamp hydraulic rod, so as to effectively reduce the damage to the trash can.
Reliability of High-Performance Monolayer MoS2 Transistors on Scaled High-κ HfO2
Authors: Chen Zhihong , Lan Hao-Yu , Yang Shao-Heng , Tripathi Rahul , Appenzeller Joerg 
Published: April 2024

Abstract

The successful integration of ultrathin high-κ insulators is essential for the advancement of ultra-scaled field-effect transistors (FETs) based on two-dimensional (2D) semiconductors in future technology nodes. However, defects within the high-κ stack or at the interfaces can significantly degrade the performance of these “interface-only” devices, raising questions regarding their long-term reliability. Here, we study the reliability of monolayer MoS2 FETs on ultra-thin high-κ HfO2. Interestingly, we observe a two-stage threshold voltage shift (ΔVTH) under positive bias temperature stress (PBTS) and hot carrier degradation (HCD), attributed to electron trapping in preexisting traps and the generation of hydrogen-assisted donor traps within the gate oxide. In contrast, devices fabricated on exfoliated hBN lack this two-stage ΔVTH, implying such donor trap generation is induced by atomic-layer-deposition (ALD) processes used in HfO2-based devices. Refining the ALD process emerges as a key strategy for enhancing the stability of 2D FETs to meet silicon CMOS standards.
The preoperative prognostic nutritional index is a prognostic indicator of postoperative pulmonary complications in patients with gynecological cancer
Authors: Jo Woo-Young , Seo Jeong-Hwa , Choi Seungeun , Kim Hee-Soo , Kim Yoon Jung 
Published: April 2024

Abstract
The prognostic nutritional index (PNI) reflects systemic inflammation and nutritional status. This study aimed to evaluate the predicting ability of the preoperative PNI regarding postoperative pulmonary complications (PPCs) in patients with gynecological cancer. Demographic, laboratory, and clinical data were retrospectively collected from 4887 patients who underwent gynecological cancer surgery. Preoperative PNIs were calculated from serum albumin levels and total lymphocyte counts. Primary outcome was PPCs, a composite outcome including acute respiratory distress syndrome, pneumonia, atelectasis, pleural effusion, and pneumothorax within postoperative day 15. An optimal cut-off value of 49.4 for the PNI score was determined using the receiver operating characteristic curve. The study used the stabilized inverse probability of treatment weighting (IPTW) method to reduce bias and compare between the high (n = 2898.5) and low PNI groups (n = 1290.4). The incidence of PPCs is significantly higher in the low PNI group than in the high PNI group (8.9% vs 17.0%, p < 0.001). In the multivariate logistic regression model after IPTW adjustment, a low preoperative PNI was an independent predictor of PPCs (odds ratio [95% confidence interval] 1.93 [1.53, 2.43], p < 0.001). Low preoperative PNIs are associated with PPCs in patients undergoing surgery for gynecologic cancer.
Femtosecond laser multiple pulse-induced thermochemical copper precipitation from glyoxylic acid copper complex ink with surfactant
Authors: Ha Nam Phuong , Ohishi Tomoji , Mizoshiri Mizue 
Published: March 2024

Abstract

This paper presents copper (Cu) precipitation from a surfactant-added glyoxylic acid copper (GACu) complex ink through femtosecond laser multiple pulse-induced thermochemical precipitation to realize high resolution Cu direct writing. The influence of the surfactant (n-decanoylsarcosine sodium, NDSS) on the nonlinear absorption properties of GACu complex ink was explored. NDSS addition did not affect the molecule binding and single-photon absorption properties of GACu complex ink. However, nonlinear optical absorptions evaluated via the open aperture z-scan method revealed differences between the NDSS-added and non-added GACu complex inks upon femtosecond laser pulse irradiation. These findings imply that Cu nanoparticles were produced from the GACu complex ink through nucleation and surfactant-mediated growth, and these nanoparticles within the ink led to the saturable absorption of the subsequently irradiated pulses. Furthermore, by irradiating the pulses at repetition frequency of 5 MHz and a pulse number of 2×104, a minimum dot diameter of 1.6 µm was attained with NDSS-added ink, matching the laser spot diameter, without excessive precipitation due to thermal diffusion. This fundamental comprehension of the effects of the surfactant NDSS and pulse numbers on the Cu precipitation process can be applied to the direct writing of various materials.
Fluoride impairs vascular smooth muscle cells via disrupting amino acids metabolism
Authors: Li Yan , Yang Ru-Ru , Li Xin-Ying , Liu Wei-Wei , Zhao Yi-Ming , Zu Ming-Man , Gao Yi-Hong , Huo Min-Qi , Jiang Yu-Ting , Li Bingyun 
Published: April 2024

Abstract
Given the insidious and high-fatality nature of cardiovascular diseases (CVDs), the emergence of fluoride as a newly identified risk factor demands serious consideration alongside traditional risk factors. While vascular smooth muscle cells (VSMCs) play a pivotal role in the progression of CVDs, the toxicological impact of fluoride on VSMCs remains largely uncharted. In this study, fluoride aggravated the pathological damage of rat aorta in vivo. Then rat VSMC lines (A7R5) were exposed to fluoride with concentration ranging from 0 to 1200 μmol/L over a 24-hour period, revealing a dose-dependent inhibition of cell proliferation and migration. The further metabolomic analysis showed alterations in metabolite profiles induced by fluoride exposure, notably decreasing organic acids and lipid molecules level. Additionally, gene network analysis underscored the frequency of fluoride's interference with amino acids metabolism, potentially impacting the tricarboxylic acid (TCA) cycle. Our results also highlighted the ATP-binding cassette (ABC) transporters pathway as a central element in VSMC impairment. Moreover, we observed a dose-dependent increase in osteopontin (OPN) and α-smooth muscle actin (α-SMA) mRNA level and a dose-dependent decrease in ABC subfamily C member 1 (ABCC1) and bestrophin 1 (BEST1) mRNA level. These findings advance our understanding of fluoride as a CVD risk factor and its influence on VSMCs and metabolic pathways, warranting further investigation into this emerging risk factor.
Single- Versus Multi-Fraction Spine Stereotactic Radiosurgery (ALL-STAR) for Patients with Spinal Metastases: a Randomized Phase III Trial
Authors: Pratapneni Aniket , Klebaner Daniella , Soltys Scott Gerard , Rahimy Elham , Gibbs Iris Catrice , Chang Steven Daniel , Li Gordon , Gephart Melanie Hayden , Veeravagu Anand , Szalkowski Gregory Arthur , Gu Xuejun , Wang Lei , Chuang Cynthia , Liu Lianli , Jackson Scott , Skerchak Jillian Adele , Huang Kelly Zhe , Wong Samantha , Brown Eleanor , Pollom Erqi Liu 
Published: April 2024

Abstract

Background: For patients with spine metastases, stereotactic radiosurgery (SRS) provides excellent local control and pain response. Despite increasing use of this treatment modality, there is no consensus on the optimal dose and fractionation of spine SRS for efficacy and toxicity. We have initiated a phase III randomized trial that compares two dose regimens with similar biological equivalent dose (BED) to determine the isolated effect of SRS fractionation on local control.
Methods: Patients with one to three cervical, thoracic, or lumbar spine metastases spanning no more than two contiguous vertebral levels in need of radiation will be eligible for enrollment. Patients will be assigned 1:1 to receive either 22 Gy in 1 fraction or 28 Gy in 2 fractions. Biased coin randomization will be used to minimize the size difference between arms, and randomization will incorporate the following strata: gastrointestinal histology (yes/no), paraspinal tissue extension (yes/no), epidural compression (low-/high-grade), and number of sites treated (one to three).
The primary endpoint is one-year local control, defined per Spine Response Assessment in Neuro-Oncology (SPINO) criteria. The secondary endpoints include patient-reported health-related quality of life (HRQOL), pain associated with the treated site, vertebral compression fracture (VCF), and two-year local control. Patients will be followed for these outcomes at one to two weeks, one month, three months, and six months after treatment, and every six months thereafter until 24 months after treatment.
Discussion: The studies published thus far comparing the single- and multi-fraction SRS are lacking long-term local control outcomes and are limited by selection bias as well as single-fraction arms with higher BED, which is correlated with improved local control. Our study will compare one-year local control in patients treated with 28 Gy in 2 fractions and the biologically equivalent single-fraction dose of 22 Gy. We will additionally compare the two arms with respect to two-year local control, pain response, adverse events, VCF, and HRQOL.
Machine Learning Models for Point-of-Care Diagnostics of Acute Kidney Injury
Authors: Chen Chun-You , Chang Te-I , Chen Cheng-Hsien , Hsu Shih-Chang , Chu Yen-Ling , Huang Nai-Jen , Sue Yuh-Mou , Chen Tso-Hsiao , Lin Feng-Yen , Shih Chun-Ming , Huang Po-Hsun , Hsieh Hui-Ling , Liu Chung-Te 
Published: April 2024

Abstract

Background
Computerized diagnostic algorithms could achieve early detection of acute kidney injury (AKI) only with available baseline serum creatinine (SCr). To tackle with this weakness, we tried to construct a machine learning model for AKI diagnosis based on point-of-care clinical features regardless of baseline SCr.
Methods
Patients with SCr > 1.3 mg/dL were recruited retrospectively from Wan Fang Hospital, Taipei. A Dataset A (n = 2,846) was used as the training dataset and a Dataset B (n = 1,331) was used as the testing dataset. Point-of-care features, including laboratory data and physical readings, were inputted into machine learning models. The repeated machine learning models randomly used 70% and 30% of Dataset A as training dataset and testing dataset for 1,000 rounds, respectively. The single machine learning models used Dataset A as training dataset and Dataset B as testing dataset. A computerized algorithm for AKI diagnosis based on 1.5x increase in SCr and clinician’s AKI diagnosis compared to machine learning models.
Results
The repeated machine learning models showed accuracy of 0.65 to 0.69. The single machine learning models showed accuracy of 0.53 to 0.74. The computerized algorithm show accuracy of 0.86 to 0.95. Clinician’s diagnosis showed accuracy of 0.52 to 0.57. The clinical features with leading impact on model output included blood lymphocyte, white blood cell, platelet, SCr, aspartate aminotransferase, systolic blood pressure, and pulse rate.
Conclusions
The machine learning models were able to diagnose AKI in the context of absent baseline SCr and showed superior accuracy than clinicians have.
Deep Neural Networks Hydrologic and Hydraulic Modeling in Flood Hazard Analysis
Authors: Hawamdeh Alaa , Tarawneh Anwar , Sharrab Yousef , Al-Fraihat Dimah 
Published: April 2024

Abstract
Natural disasters can be devastating to the environment and natural resources. Flood inundation mapping and hydraulic modeling are essential to forecast critical flood information, including flood depth and water surface height. In this research, several factors that influence floods were studied. These factors include the intensity of the rainstorm, the depth of precipitation, soil types, geologic settings, and topographic features. Furthermore, the research carried out hydraulic modeling of storm flows for 50- and 100-Year return periods and estimated that the water depth in Wadi Al Wala could reach 15m at 50 years of storm and 25m at 100 return years of storms. A DNN model is developed with good accuracy to predict flood flow based on historical records from 1980 to 2018 meteorological data. The goal of this research is to improve flood prediction, and risk assessment with the use of DNN integrated with hydrological and hydraulic models.
Security &amp; Driver Assistance In VANET Using Edge Computing
Authors: Managuli Manjunath , Managuli Sangamesh 
Published: April 2024

Abstract
The research introduces a priority-based fog computing model designed to mitigate delay and latency challenges in connected vehicles within smart cities. This model utilizes VANET (Vehicular Ad-hoc Networks) and fog computing as intermediaries between vehicles and the cloud, providing processing, storage, and networking capabilities. The goal is to establish a smart and autonomous transportation system, leveraging Cellular Vehicle-to-Everything (C-V2X) connectivity and roadside units (RSUs) for various vehicular applications. To enhance task processing efficiency, the research proposes an efficacy utility and a knapsack-based task scheduling algorithm for fog servers located near RSUs. The results indicate that the 0/1 Knapsack algorithm is the most effective of the four algorithms considered, as it maximizes total priority while considering both the priority and size of tasks. Overall, this research contributes to the advancement of a smart and autonomous transportation system by addressing the experiments related to delay and latency in fog adding and VANET.
Foot Pressure Classification and Feature Extraction Based on Multiple Fusion Algorithms
Authors: Bai Xiaotian , Hou Xiao , Song Yiling , Tang Zhengyan , Huo Hongfeng , Liu Jingmin 
Published: April 2024

Abstract
Objective
Using multiple fusion algorithms to optimize the classification and feature extraction of foot pressure during walking stance phase in healthy people, and explore the diversity of foot pressure distribution.
Methods
243 healthy young male individuals was studied to collect data on plantar impulse and maximum pressure indices from ten distinct regions of the foot during walking. Principal component analysis was utilized to reduce the dimensionality of the data. Optimized clustering and feature extraction algorithms categorized the foot pressure characteristics and extracted key indicators. Classification discriminant functions were developed using linear discriminant analysis. Analysis of variance compared the differences in features between various foot pressure distribution patterns.
Results
Three types of foot pressure distribution were identified by multiple fusion algorithms, and four indicators were extracted, including impulses of Toe1, Meta1, Meta5 and Midfoot. The average accuracy rates of original data and cross-validation were 89.70% and 88.50%. Based on one-way analysis of variance, the distribution types were ultimately determined as Thumb Extension Type, Midfoot-Lateral Forefoot Push-off Type, and Normal Type.
Conclusion
Foot pressure distribution during walking in healthy people can be categorized into Thumb Extension Type, Midfoot-Lateral Forefoot Push-off Type, and Normal Type. Among them, the impulses around the first metatarsophalangeal joint region, fifth metatarsal bone region and midfoot region showed better classification performance. It is recommended that future studies combine the current findings and use prospective studies to further analyze the relationship between gait characteristics and sports injuries.
High-order accuracy identification framework for stochastic differential equation with Gaussian white noise
Authors: Wang Bochen , Wang Liang , Peng Jiahui , Dong Shuangqi , Xu Wei 
Published: April 2024

Abstract

This paper presents a high-order accuracy data-driven identification framework for stochastic differential equation (SDE) with the Gaussian white noise. The framework improves the accuracy in discovering SDE from the data collected at low frequencies. It first approximates the increment of data as a one-step mapping. The truncated terms of the approximation are the higher order terms of the time step of the collected data. Therefore, the mapping can approximate the data collected with large time steps, i.e., low frequencies with high-order accuracy. Then, the framework approximates the mapping as the Fourier series with a high rate of convergence, which is called the double-even extended series. In this way, we can approximate the average change of SDE with high accuracy and do not need knowledge about the change. After determining the coefficients of the Fourier series from data, the new framework finds an accurate approximation of the SDE. We apply the new framework to achieve the identification of an SD oscillator and a glycolytic oscillation. The new framework accurately discovers the SDEs from data collected at low frequencies, e.g., 4 HZ and 2.5 HZ. Identified SDEs can accurately predict stochastic responses. To the best of the authors' knowledge, the frequency is much lower than existing SDE identification methods.
A diffusion-reaction synergism model for concrete carbonation: Combined effects of calcium leaching and temperature
Authors: Mo Rui , Wang Jing-xiang , Wu Ling-jun 
Published: March 2024

Abstract

The deterioration behavior caused by carbonization can reduce the durability of concrete structures. This study established a diffusion-reaction synergism model of concrete carbonation depth considering calcium leaching and temperature field, and predicted the influence of calcium leaching process and temperature on the carbonation resistance of concrete. Specifically, calcium leaching is described using solid-liquid equilibrium curves. The model was validated using published experimental data. The effects of calcium leaching, temperature, and concrete water saturation on carbonation are analyzed. The results show that the calcium leaching effect has a strong influence on the carbonation of concrete, so future models need to include it.
Pregnancy Entails a U-Shaped Trajectory in Human Brain Structure Linked to Hormones and Maternal Attachment
Authors: Servin-Barthet Camila , Martínez-García Magdalena , Paternina-Die María , Marcos-Vidal Luis , de Blas Daniel Martín , Soler Anna , Khymenets Olha , Bergé Daniel , Casals Gemma , Prats Pilar , Pozo Óscar , Pretus Clara , Carmona Susana , Vilarroya Oscar 
Published: March 2024

Abstract

Growing evidence places the gestational period as a unique moment of heightened neuroplasticity in adult life. In this longitudinal study, we unveiled a U-shaped trajectory in gray matter (GM) volume, which dips in late pregnancy and partially recovers during postpartum. These changes were most prominent in brain regions associated with the Default Mode and Frontoparietal Network, which also showed an increased global efficiency and density connectivity. The U-shaped trajectory was predominantly linked to gestational factors, as it was only present in gestational mothers and correlated with fluctuations in estrogens over time. Finally, the mother’s mental health status mediated the relationship between postpartum GM volume recovery and maternal attachment at six months postpartum. This research sheds light on the complex interplay between hormones, brain development, and behavior during the transition to motherhood. It addresses a significant knowledge gap in the neuroscience of human pregnancy and opens new possibilities for interventions aimed at enhancing maternal health and well-being.
Evaluation and detection capabilities of the ultrasonic examination procedure established by AWS D1.1 and D1.5 Codes
Authors: Arias Paula A. Cortés , Barrada Jorge E. Giraldo 
Published: April 2024

Abstract
This study aimed to quantitatively determine the detection and evaluation capabilities of the ultrasonic procedure established by the American Welding Society in AWS D1.1 and D1.5 for the examination of welded steel bridges and buildings. Several reference steel blocks were manufactured employing ASTM A709 Grade 50W steel and including artificial reflectors with various shapes and dimensions, as follows: (1) with two types of planar artificial reflectors (Notches and Flat Bottom Holes), and (2) with one type of volumetric reflector (Side-Drilled Holes). The reflectors were manufactured in four sizes (0.5, 1, 3, and 5 mm), and were manually examined with a pulse-echo ultrasound equipment as follows: using the prescribed AWS procedure (Experiment 0), changing the crystal size (Experiment 1), and changing the frequency (Experiment 2). These modifications can induce changes in the detection and evaluation capabilities. Eight examination tests were performed for each type and size of artificial reflector, including variations in examination angle (45°, 60°, and 70°), as follows: two sound distances (first and second leg), two scanning levels, and two trials, for a total of 1224 measurements. Among the most important results, we found that the examination procedure prescribed by the AWS has good detection capability, which is not altered by changes in transducer frequency or crystal size. Nevertheless, this procedure has a poor ability to evaluate reflectors regardless of their size or type. In sum, with this methodology, it is almost impossible to determine, in a reliable way, the “severity” of natural discontinuities in welds or artificial reflectors.