bluuebunny/crossref_metadata_2025_split huggingface dataset:
Insights into the implementation of a whole genome sequencing report form (SRF) to reduce nosocomial SARS-CoV-2 within UK hospitals: a qualitative process evaluation using normalisation process theory
Authors: Leiser Ruth , McLeod Julie , Mapp Fiona , Stirrup Oliver , Blackstone James , Illingwo Christopher JR , Nebbia Gaia , Price James R , Snell Luke B , Saluja Tranprit , Breuer Judith , Flowers Paul 
Published: July 2023

Abstract

Background
Here we report on a process evaluation conducted as part of a large multisite non-randomised trial of the effectiveness of a whole genome sequence report form (SRF) to reduce nosocomial SARS-CoV-2 through changing infection prevention and control (IPC) behaviours during the COVID − 19 pandemic. We detail how the SRF was implemented across a heterogeneous purposive sub-sample of hospital trial sites (n = 5/14).
Methods
We conducted in-depth interviews from diverse professional staff (N = 39). Inductive thematic analysis initially explored participants’ accounts of implementing the SRF. The resulting data driven themes, concerning the way the SRF was used within sites, were then coded in relation to the key tenets of normalisation process theory (NPT).
Results
Factors that enabled the implementation of the SRF included: elements of the context such as health care professional passion; the existence of whole genome sequencing (WGS) infrastructure; effective communication channels, the creation of new connections across professionals and teams; the integration of SRF-led discussions within pre-existing meetings and the ability of a site to achieve a rapid turnaround time. In contrast, we found factors that constrained the use of the SRF included elements of the context such as the impact of the Alpha-variant overwhelming hospitals. In turn, dealing with COVID-19 breached the limited capacity of infection prevention and control (IPC) to respond to the SRF and ensure its routinisation.
Conclusion
We show preliminary support for the SRF being an acceptable, useable and potentially scalable way of enhancing existing IPC activities. However, the context of both the trial and the alpha wave of COVID-19 limit these insights.
Clinical trial number
https://www.isrctn.com/ISRCTN50212645,
Registration date 20/05/2020
A Modified Clustering Algorithm Based on Fuzzy Clustering (FC) and Modified Grey Wolf Optimization (MGWO)
Authors: C Daniel Nesa Kumar , J Lekha , R Aruna , A Sheela Selvakumari N 
Published: July 2023

Abstract
The goal of a Wireless Sensor Network (WSN) is to extend the life cycle of network and to control topology control. Particle Swarm Optimization is used to pick cluster heads based on Particle Swarm Optimization (PSO). In high-dimensional space, PSO can easily fall into local optimum, results in poor convergence rate when subjected to an iterative process. Proposed technique applies Fuzzy Clustering (FC) for preprocessing and Modified Grey Wolf Optimization to address this problem (MGWO). First, the FC algorithm is used to initialize the clustering process for sensor nodes based on their geographical locations, where each node belonging to a cluster with a given probability, and the count of initial clusters is studied and presented. In addition, the fitness function is created with WSN's energy consumption and distance aspects in mind. Finally, the MGWO is used to determine the CH nodes in hierarchical architecture. Experiments reveal that, when compared to standard methods, the proposed strategy was successful in lowering node mortality and prolonging the network life cycle.
lmprovement of A Searchable Keyword Public Key Encryption Scheme in Cloud Storage
Authors: Zeng Shuhan , Zhou Chuanhao , Dong Yingjie , He Jinlin , Wang Hongwei , Liao Yongjian 
Published: July 2023

Abstract
In big data era, more and more people store their data in some outsourced cloud, but this brings up a problem that how to keep some important and sensitive data from revealing to the curious cloud and malicious ones who aim to steal information. In this case, public-key encryption with keyword search (PEKS) has become an indispensable branch in cryptography. Many great works have been done to contribute this field since then. In 2018, Wu et al (2018) came up with an efficient and secure searchable public key encryption scheme with privacy protection for cloud storage. However, in this paper, we proved that their scheme is not secure under indistinguishability against keyword guessing attack (IND-KGA) by giving two ways to break their scheme. Then we proposed an improved scheme to make it secure and more efficient in some way. And we proved that the proposed scheme is secure under IND-KGA and indistinguishability against chosen keyword attack game (IND-CKA). Finally, in terms of security performance for restricted device data collection, our trapdoor generation algorithm has more advantages.
Deep learning reveals key aspects to help interpret the structure-property relationships of materials
Authors: Dam Hieu-Chi , Vu Tien-Sinh , Ha Minh-Quyet , Nguyen Duong Nguyen , Nguyen Viet-Cuong , Abe Yukihiro , Tran Truyen , Tran Huan , Kino Hiori , Miyake Takashi , Tsuda Koji 
Published: July 2023

Abstract
Deep learning (DL) models currently used for materials research have limitations in providing meaningful information for interpreting predictions and understanding the relationships between structure and material properties. To address this, we propose a DL architecture that incorporates the attention mechanism to predict material properties and gain insights into their structure-property relationships. The proposed architecture is evaluated using four datasets: the QM9 molecule dataset and three in-house-developed computational materials datasets. Train--test--split validations confirm that the models derived from the proposed DL architecture exhibit strong predictive capabilities comparable to those of current state-of-the-art models. Furthermore, comparative validations, based on first-principles calculations, indicate that the degree of attention of the atoms' local structures to the representation of the material structure is critical when interpreting structure-property relationships with respect to physical properties. The properties include molecular orbital energies or formation energies of crystals. Our proposed architecture shows great potential in accelerating material design by predicting material properties and identifying critical features of corresponding structures.
Study on deep learning methods for rockburst risk prediction based on mining-induced seismicity quantification
Authors: Cheng Xianggang , Qiao Wei , He Hu 
Published: July 2023

Abstract
The assessment of rockburst risk (RBR) is the premise of rockburst prevention and control. It is the implementation criterion to guide various rockburst prevention and control measures. The existing static prediction and evaluation methods for RBR cannot be effectively combined with the results of underground dynamic monitoring. This study proposed a mining-induced seismicity information quantification method based on the fractal theory. Deep learning methods are used to construct a deep learning framework of rockburst risk (DLFR) based on the fractal dimension of microseismic information. Gray correlation analysis (GRA), information gain ratio (IGR), and Pearson correlation coefficient are used to screen and compare factors. Statistical evaluation indicators such as macro-F1, accuracy rate, and fitness curve were used to evaluate model performance. Taking Gaojiapu Coal Mine in the Binchang mining area as a case study, the performance of deep learning models such as BP Neural Network (BP), Support Vector Machine (SVM) and its optimized model based on particle swarm optimization (PSO) algorithm under this framework is discussed. The reliability and validity of the research results to verify by comparing the predicted results with the actual results. The research results show that the prediction results of RBR in DLFR are consistent with the actual results, and the model is reliable and effective. The mining-induced seismicity quantification can solve the problem of insufficient training samples for the RBR. With this, different pressure relief measures can be formulated based on the results of the RBR predictions to achieve "graded" precise prevention and control.
Dynamic triggering along the Dead Sea transform uncovers tremor source physics
Authors: Inbal Asaf 
Published: July 2023

Abstract
Tremor signals are weak and emergent, and the physics governing their generation is not well understood. Here, I report on tremor occurring along the Dead Sea Transform (DST), and a microearthquake on the Carmel-Fari'a Fault (CFF), both dynamically triggered by the 2023 Mw7.6 Kahramanmaraş earthquake. The triggered events location coincides with maxima of long-period velocity gradients, concentrated in the CFF-DST intersection and near a CFF fault-jump. Relative to other remotely triggered tremors, the DST tremor is strong and deficient in high-frequency seismic energy. Furthermore, analysis of several triggered tremor episodes suggests that tremors spectral fall-off rates are not universal. I discuss the seismological attributes that may give rise to these observations in the context of two models. In the first, tremor is produced due to inertial vibrations of a frictionally-controlled oscillator, and in the second it is produced by a swarm of Low-Frequency Earthquakes.
Morphological changes of adjacent vertebrae after posterior hemivertebrae resection and unilateral short segment fixation:Retrospective cohort study
Authors: Wang Shixiong , Gao Ze , Zhang Yandong , Xi Fanhui , Guo Weijie , Zhao Sheng , Xue Xuhong 
Published: July 2023

Abstract
Background
To investigate the morphological changes in the adjacent vertebrae in patients with congenital scoliosis caused by hemivertebra treated by posterior hemivertebra resection with unilateral short segment fixation.
Methods
A retrospective cohort study was conducted. From 2000 to 2023, 26 pediatric patients with scoliosis caused by a single hemivertebra were included in our institution. They were treated with posterior hemivertebra resection and unilateral short-segment fixation. The preoperative, postoperative, and final follow-up imaging parameters were measured separately, such as the main curve Cobb angle, correction rate, the height of the convex and concave side of the vertebral body, and bilateral pedicle distance (BLPD). All patients had at least 60 months of follow-up.
Results
The patient was followed up for 68.81 ± 8.11(60–82)months. The preoperative main curve Cobb angle: 36.32°±11.36°, postoperative main curve Cobb angle: 12.29°±7.41°, with a mean correction rate of 66.3%.The main curve Cobb angle at the last follow-up: 12.59°±7.42°, with a loss rate of 2.3%. Preoperative height of proximal vertebral body on convex side: (1.14 ± 0.48) cm,height of proximal vertebral body on concave side: (1.15 ± 0.50) cm, BLPD: (2.58 ± 1.11) cm, height of distal vertebral body in convex side: (1.26 ± 1.89) cm, height of distal vertebral body in concave side: (1.13 ± 0.45) cm, BLPD: (2.83 ± 0.93) cm; Postoperative height of proximal vertebral body in convex side: (1.83 ± 0.49) cm,height of proximal vertebral body in concave side height: (1.58 ± 0.39) cm, BLPD: (2.86 ± 0.77) cm, height of distal vertebral body in convex side: (1.88 ± 0.46) cm,height of distal vertebral body in concave side height: (1.59 ± 0.32) cm, BLPD: (3.31 ± 0.99) cm; At the final follow-up,the height of proximal vertebral body in convex side: (2.01 ± 0.60) cm, height of proximal vertebral body in concave side: (1.89 ± 0.49) cm, BLPD: (3.20 ± 0.78) cm, height of the distal vertebral body in convex side: (2.25 ± 0.50) cm, height of distal vertebral body in concave side: (1.90 ± 0.32) cm, BLPD: (3.58 ± 0.90). The postoperative and final follow-up parameters were significantly difference(P < 0.05) compared with preoperative parameters. No complications such as neurological injury, infection, and internal fixation failure occurred during the follow-up.
Conclusion
Posterior hemivertebrectomy with unilateral short-segment fixation and fusion can effectively remove the factors leading to deformity and correct the spinal alignment. Morphological changes in the vertebrae adjacent to the hemivertebrae are observed on long-term follow-up, with a tendency to from wedge-shaped or irregular-shaped vertebrae to a typical vertebra. It is a safe and effective treatment for congenital scoliosis caused by hemivertebra.
Formation of long-lasting inactive and active multiple tropical cyclone events in the western North Pacific
Authors: Chen Lilan , Gao Jianyun , Li Tim 
Published: July 2023

Abstract
Long-lasting inactive and active multiple tropical cyclone (MTC) events in the western North Pacific (WNP) during July-August 1982-2020 were investigated. It is found that the significant difference between the inactive and active events lies on large-scale circulation conditions and tropical SST anomalies in the Pacific and Indian Ocean. A negative phase of the Pacific Meridional Mode (PMM), an Indian ocean warming and a local suppressed convective phase are associated with the long-lasting inactive MTC events, and vise visa. A further diagnosis of the environmental parameters showed that dynamic parameters such as mid-level vertical motion and the upper-level divergence and thermodynamic parameters such as vertically integrated water vapor content and low-level specific humidity play important roles in regulating the inactive and active MTC events. A separation of interannual and intraseasonal components indicates that the extreme MTC events are influenced by both the timescale motions. While the former is primarily through the SSTA-induced low-level anticyclonic and descent anomalies, the latter is via the fluctuation of the boreal summer atmospheric intraseasonal oscillation.
Bacterial community response to modified-biochar and exogenous fungi inoculation during degradation of oil-contaminated clayey sediment in slurry phase
Authors: Atakpa Edidiong Okokon , Yan Bozhi , Okon Samuel Ukpong , Liu Qing , Zhang Dongdong , Zhang Chunfang 
Published: July 2023

Abstract
Bioremediation strategies for oil-contaminated clayey sediment are still a major environmental concern due to their reluctance to conventional treatment techniques. The main objective of this study was to evaluate the sequential application of modified biochar and exogenous fungus in slurry phase degradation of crude oil-contaminated clayey sediment. Biochar modification using acid and rhamnolipid increased its surface area from 2.544 to 25.378 m2g-1, followed by a corresponding increase in the hydrogen-carbon and oxygen-carbon ratio, indicating improved stability, polarity, and oxygen contents. The maximum TPH removal efficiency of 82.4% was achieved in treatments with the acid-rhamnolipid-treated biochar, followed by a corresponding increase in FDA hydrolysis activity. Furthermore, high-throughput 16S RNA gene sequencing was employed to identify changes in the bacterial community structures of the original sediment and treatments before and after fungal inoculation. This highlighted Proteobacteria as the dominant phylum, followed by Campilobacterota, Bacteroidota, Actinobacteriota, and Desulfobacterota. In addition, it was observed that fungal inoculation promoted the proliferation of some specific TPH-degraders. Specifically, ASVs associated with Hyphomonas adhaerens and Marinobacter mobilis accounted for 77% and 5% of the total degrading populations in treatments where TPH removal was highest. Findings in this study provide valuable insights into the effect of biochar in the treatment of crude oil-contaminated marine sediments, and a better understanding of the fundamental role of exogenous fungus in the proliferation of efficient TPH-degraders towards effective degradation.
A nanoscale view of the origin of boiling and its dynamics
Authors: Gallo Mirko , Magaletti Francesco , Georgoulas Anastasios , Marengo Marco , De Coninck Joel , Casciola Carlo 
Published: July 2023

Abstract
Boiling has the peculiarity of being involved both in frontier technological applications, such as nano cooling, and in everyday life activities, such as food cooking. For that reason, everyone is very familiar with this kind of phase transition. Associated with the empirical knowledge of the process, despite tens of years of scientific exploration, there is yet no adequate physical understanding of the phenomenon and its profound nanoscale origins. Many controversial experimental observations well fit into such a scenario. The lack of fundamental understanding of the process has a great impact on the technological development of thermal science, especially in terms of a quantitative prediction of the physical parameters. The central issue lies in the multiscale and non-equilibrium nature of boiling itself, where nucleation and bubble dynamics must coexist in a single description far from thermodynamic equilibrium and linked to length and time scales, unreachable by the present measurement tools. To date, theory, simulations, and experiments have described the different scales of boiling always compartmentalised and blurred by many uncontrolled parameters. Therefore, a holistic description encompassing the whole aforementioned range of spatial and temporal scales is still lacking, even though strongly desired. Here we show for the first time that a continuum model based on fluctuating hydrodynamics and the diffuse interface approach is able to describe the boiling phenomenon from the stochastic nucleation up to the macroscopic bubble dynamics. The approach covers, with a modest computational cost, the mesoscale area from nano to micrometers, where most of the controversial observations related to the phenomenon originate from. In particular, the role of wettability in the macroscopic observable of boiling is elucidated. In addition, by comparing the ideal case of boiling on ultrasmooth surfaces with a chemically heterogeneous wall, our results will definitively shed light on the puzzling low onset temperatures measured in experiments. Sporadic nanometric spots of hydrophobic wettability will be shown to be enough to trigger the nucleation at low superheat values, significantly reducing the temperature of boiling onset, in line with experimental results. The proposed mesoscale approach constitutes the missing link between macroscopic approaches and molecular dynamics simulations, and will open a breakthrough pathway toward accurate understanding and prediction.
A new tool for identifying giant African snails Lissachatina fulica that reached the hermaphrodite stage
Authors: Patiño-Montoya Angie , Borges Bárbara Luíza , Tidon Rosana 
Published: July 2023

Abstract
The giant African snail Lissachatina fulica (Bowdich, 1822) is a protandrous hermaphrodite gastropod; that is, it develops the male reproductive system first and then the female reproductive system. An individual can lay more than 400 eggs in the same posture, which contributes to its invasive potential. Due to the difficulty in differentiating hermaphrodite individuals, in this study, we evaluated whether the length and shape of the shell contribute to recognizing individuals with female reproductive structures. For this, we classified 104 individuals collected in Brasília (Brazil) according to the presence or absence of an albumin gland and uterus and evaluated the shell length and two indices that reflect its shape in each group. The shell length and two shape indices overlapped between groups. However, the length and one of the indices (how many times the distance between the first suture and the shell aperture fits into the shell width) correctly classified at least 88% of hermaphrodite individuals when applied individually. When these two indicators are adopted simultaneously, the percentage of success in identifying hermaphrodites is greater than 98%. In hermaphroditic individuals, the shell length is generally greater than 5 cm, and the shape index described above is generally less than or equal to 2.1. Our proposal facilitates the recognition of potentially hermaphroditic individuals in the field, thus contributing to the management of this important invasive species.
Rediscover the predictive capacity of B-type natriuretic peptide applied to neonatal ventricular supertachycardia
Authors: Lu Yaheng , Xiong Ying , Wen Yizhou , Yang Yanfeng , Liu Hanmin 
Published: July 2023

Abstract
Background
Supraventricular tachycardia (SVT) is one of the most common non-benign arrhythmias in neonates that could lead to cardiac decompensation. This study investigated early risk factors of acute heart failure (AHF) secondary to SVT in neonates, and explored their value on guiding the selection of efficient anti-arrhythmic treatment.
Methods
A total of 43 newborns with SVT diagnosed and treated between January 2017 and December 2022 were analyzed. According to the presence of AHF after initial restoring SVT to sinus rhythm, newborns were divided into SVT with AHF group and SVT without AHF group, and the clinical data and anti-arrhythmic therapies were analyzed. Risk factors of AHF secondary to SVT in neonates were determined by logistic regression. The cut-off value for predictors of AHF secondary to SVT and demanding of a second line anti-arrhythmic treatment was determined by receiver operating characteristic curve analysis.
Results
Time to initial control of tachycardia > 24h, hyperkalemia, anemia, plasma B-type natriuretic peptide (BNP) were risk factors of AHF secondary to SVT in neonates. BNP exhibited AUC of 0.804 in predicting AHF, and BNP > 2460.5pg/ml (OR 2.281, 95% CI 1.270 ~ 45.399, P = 0.026) was an independent predictor yielded sensitivity of 70.59% and specificity of 84.62%. The neonates with BNP > 2460.5pg/ml (37.5% versus 7.4%, P = 0.037) had a higher demand for a second line anti-arrhythmic treatment to terminate SVT, and the sensitivity and and specificity for BNP in predicting were 75.0%, 71.4%, respectively.
Conclusions
BNP could be used to predict an incident of AHF secondary to SVT and a demand of second line anti-arrhythmic treatment for terminating SVT hastily to prevent decompensation in neonates.