bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effects of COVID‐19 measures on the hospitalization of patients with epilepsy and status epilepticus in Thailand: An interrupted time series analysis
Authors: Sirikarn Prapassara , Tiamkao Siriporn , Tiamkao Somsak 
Published: April 2022

AbstractObjectiveTo investigate the effect of Coronavirus disease 2019 (COVID‐19) measures on the hospitalization of patients with epilepsy and status epilepticus (SE).MethodsThis interrupted time series design included data from the Thai Universal Coverage Scheme electronic database between January 2017 and September 2020. The monthly hospitalization rate of epilepsy and SE was calculated by the number of hospitalizations divided by the midyear population. Segmented regression fitted by ordinary least squares (OLS) was used to detect the immediate and overtime effects of COVID‐19 measures on the hospitalization rate.ResultsDuring January 2017 and September 2020, the numbers of epilepsy and SE patients admitted to the hospital were 129 402 and 15 547 episodes, respectively. The monthly trend of the hospitalization rate in epilepsy decreased immediately after the COVID‐19 measure (0.739 per 100 000 population [95% CI: 0.219 to 1.260]). In particular, the number of children declined to 1.178 per 100 000 population, and the number of elderly individuals dropped to 0.467 per 100 000 population, while there was a nonstatistically significant change in SE.SignificanceCOVID‐19 measures reduced the hospital rate in epilepsy, particularly in children and adults. However, there was no change in SE patients.
Probabilistic residual deformation prediction model for rectangular reinforced concrete columns
Authors: Lee Chang Seok , Jeon Jong‐Su 
Published: April 2022

AbstractThis paper presents a probabilistic residual deformation prediction model for estimating the nonlinear response and demolition probability of reinforced concrete structures. An empirical relation between the residual deformation and column physical parameters was formulated from experimental observations. The accuracy of the proposed model was compared to those of three deterministic models available in the literature. The proposed model better represented the central tendency of the observed residual deformations than the prediction of the deterministic models. Nonlinear dynamic analyses using 44 far‐field ground motions on a modern four‐story reinforced concrete building frame are conducted to investigate discrepancies in demolition probability associated with different residual deformation models. The difference between the medians of demolition fragility predicted by the deterministic and probabilistic models was 20–50%, indicating that the probabilistic model has a significantly higher dispersion than that of the deterministic models.
Multipower‐level Q‐learning algorithm for random access in nonorthogonal multiple access massive machine‐type communications systems
Authors: Maciel Ferreira Silva Giovanni , Abrão Taufik 
Published: April 2022

AbstractThe massive machine‐type communications (mMTC) service will be part of new services planned to integrate the beyond fifth generation of wireless communication. In mMTC, thousands of devices sporadically access available resource blocks on the network. In this scenario, the massive random access problem arises when two or more devices collide when selecting the same resource block. There are several techniques to deal with this problem. One of them deploys ‐learning (QL), in which devices store in their ‐table the rewards sent by the central node that indicate the quality of the transmission performed. The device learns which are the best resource blocks to select and transmit in order to avoid collisions. We propose a multipower‐level QL (MPL‐QL) algorithm that uses nonorthogonal multiple access (NOMA) transmit scheme to generate transmission power diversity and allow accommodate more than one device in the same time‐slot as long as the signal‐to‐interference‐plus‐noise ratio (SINR) exceeds a threshold value. The numerical results reveal that the best performance‐complexity trade‐off is obtained by using a higher number of power levels, typically eight levels. The proposed MPL‐QL can deliver better throughput and lower latency when compared to other recent QL‐based algorithms found in the literature.
Insight into the protein degradation during the broad bean fermentation process
Authors: Lin Hongbin , Zhou Binbin , Zhao Jianhua , Liao Shiqi , Han Jinlin , Fang Jiaxing , Liu Ping , Ding Wenwu , Che Zhenming , Xu Min 
Published: April 2022

AbstractBroad bean fermentation is of vital importance in PixianDouban (PXDB) production, as well as a key process for microorganisms to degrade protein, which lays the foundation for the formation of PXDB flavor. In this study, two fungi and bacteria were screened, and their morphology, molecular biology, growth, and enzyme production characteristics were analyzed, and then they were applied to the broad bean fermentation simulation system. The protein, peptide, amino acid, amino nitrogen, and sodium dodecyl sulfate‐polyacrylamide gel electrophoresis (SDS‐PAGE) in the system were evaluated. The results showed that the four microorganisms were Aspergillus oryzae, Aspergillus jensenii, Staphylococcus gallinarum, and Enterobacter hormaeche. Aspergillus oryzae had the highest protease activity at pH 7.0, while the other three strains had better enzyme activity stability under neutral acidic conditions. And the total protein (F1 and F2 were 18.32 g/100 g, 19.15 g/100 g, respectively), peptides (11.79 ± 0.04 mg/g and 12.06 ± 0.04 mg/g), and amino acids (55.12 ± 2.78 mg/g and 54.11 ± 1.97 mg/g) of the fungus experimental groups (F) were higher than the bacterial experimental groups (B). In addition, the enzyme system produced by fungi exhibited a stronger ability for albumin (20 kDa) and glutenin (<30 kDa) deterioration in neutral conditions, while the bacterial enzyme system was more efficient in degrading albumin (<30 kDa) and glutenin (20–30 kDa) in acidic conditions, as indicated by SDS‐PAGE. These findings showed that both bacteria and fungi played an important role in the degradation of protein in different fermentation stages of broad bean fermentation.Practical applicationsThere is a lack of comprehensive understanding of the protein composition and protein degradation mechanism of broad beans in the fermentation stage of PXDB. This research work explored the differences in the degradation of PXDB fermented protein by different microorganisms, and provided a theoretical basis for optimizing the production of PXDB and improving the quality of PXDB.
Use of BIM for the optimized operation of road tunnels: Modelling approach, information requirements, and exemplary implementation
Authors: Vollmann Goetz , Stepien Marcel , Riepe Werner , König Markus , Lehan Anne , Thewes Markus , Wahl Hendrik 
Published: April 2022

AbstractIn the operating phase of a road tunnel, not only maintaining or increasing the availability in the network but the economic optimization regarding the life cycle costs of the structure are also important priorities. A consistent application of the Building Information Modelling (BIM) methodology can theoretically make a useful and targeted contribution, as it provides a complete digital model of the structure with all installed elements and the information required for the operator tasks. In the research project FE https://doi.org/15.0623/2016/RRB ”Building Information Modeling (BIM) in Tunneling,“ the Institute of Tunneling and Construction Management and the Institute of Computing in Engineering (both Ruhr University Bochum) in cooperation with BUNG Ingenieure AG developed the basics for a BIM‐based operating model of road tunnels with funding from the Federal Highway Research Institute commissioned by the Federal Ministry of Transport and Digital Infrastructure. In the article, the results of the research are presented on the basis of specific use cases of a BIM‐based operation and maintenance management.
Potential applications of machine learning for BIM in tunnelling
Authors: Erharter Georg H. , Weil Jonas , Tschuchnigg Franz , Marcher Thomas 
Published: April 2022

AbstractMachine Learning (ML) and Building Information Modelling (BIM) are two topics that are part of a revolutionizing transformation in the construction industry – commonly referred to as digitalization. Being part of the research for artificial intelligence (AI), most of today's ML applications deal with computational processes that try to make sense of data. Automatic rockmass behaviour classification based on tunnel boring machine (TBM) data or tunnel construction site surveillance via closed‐circuit television (CCTV) analysis is an example for applications of ML in tunnelling. BIM describes a new type of planning, including model‐based collaboration and information exchange, which requires well‐organized storage and handling of data – a precondition and valuable source for any automated analysis method like ML. While other sectors of the construction industry have implemented BIM systems successfully, the development in underground engineering is currently at its beginning with multiple actors working towards common standards for semantics, data exchange formats, etc. This article seeks to combine the two fields by giving an overview of the two topics and then points out four potential fields of applications: semantic enrichment and labelling, automation of technical processes, knowledge derivation and online data analysis.
Visual and hearing impairment and their association with depression among middle‐aged and older individuals in India: Evidence from a cross‐sectional study
Authors: Meher Trupti , Gharge Shivani 
Published: April 2022

AbstractObjectiveThe aim of the study was to determine the prevalence and associated factors of visual and hearing impairment as well as to investigate their association with depression among individuals aged 45 and above in India.MethodsThe study utilized data from the Longitudinal Ageing Study in India (LASI) Wave 1, (2017‐18). The total sample size of this study was 65,562 individuals aged 45 and above. Descriptive statistics along with bivariate and multivariable analyses were performed to fulfill the objectives.ResultsThe prevalence of visual impairment in the study population was 32.1 percent, whereas the prevalence of self‐reported hearing impairment was 6.9 percent. In the logistic regression models, both visual impairment [Adjusted odds ratio (AOR)‐1.06; 95% Confidence interval (CI):0.99‐1.14] as well as hearing impairment [AOR‐1.25; 95% CI:1.11‐1.41] were found to be significantly associated with depression. Moreover, individuals with a single impairment were 8 percent [AOR‐1.08; 95% CI: 1.01‐1.16] and individuals with dual impairment were 36 percent [AOR‐1.36; 95% CI:1.13‐1.65] significantly more likely to have depression.ConclusionIndividuals with sensory impairment were more likely to suffer from depression and the risk was significantly higher among individuals with dual impairment. Therefore, clinicians dealing with individuals with sensory impairments must be aware of the likelihood of comorbid depression in order to provide timely screening and treatment.
Regulation of renal calbindin expression during cisplatin‐induced kidney injury
Authors: George Blessy , Szilagyi John T. , Joy Melanie S. , Aleksunes Lauren M. 
Published: April 2022

AbstractSince the discovery of calbindin release into the urine during renal injury, there has been growing interest in the utility of this protein as a biomarker of nephrotoxicity. However, little is known about the intrarenal regulation of the release and expression of this calcium‐regulating protein during kidney injury. We sought to characterize the time‐dependent expression and excretion of the protein calbindin in the distal tubule in comparison to kidney injury molecule‐1 (Kim‐1), a protein in the proximal tubule, in mice treated with cisplatin. Urine, blood, and kidneys were collected from male C57BL/6 mice treated with vehicle or cisplatin (20 mg/kg ip). Urinary concentrations of calbindin and Kim‐1 were elevated by 11.6‐fold and 2.5‐fold, respectively, within 2 days after cisplatin. Circulating creatinine and blood urea nitrogen levels increased in cisplatin‐treated mice by 3 days, confirming the development of acute kidney injury. Time‐dependent decreases in intrarenal calbindin protein were observed on Days 3 and 4 and a 200‐fold upregulation of calbindin (CALB1) and KIM‐1 messenger RNAs (mRNAs) was observed on Day 3. These data suggest that early loss of calbindin protein into the urine along with declines in renal calbindin levels initiates a compensatory induction of mRNA expression at later time points (Days 3 and 4). Understanding the regulation of calbindin during cisplatin nephrotoxicity further enhances its utility as a potential urinary biomarker of kidney damage. The results of the current study support the combined use of a proximal (Kim‐1) and distal tubule (calbindin) marker to phenotype acute kidney injury secondary to cisplatin administration.
Hydrogen storage on flat land materials, opportunities, and challenges: A review study
Authors: Fatima Kaneez , Soomro Amir Mahmood , Rafique Muhammad , Kumar Mahesh 
Published: April 2022

AbstractCurrently, hydrogen (H) is considered as a promising source of energy for future demands. Although, significant work is dedicated to the H production, but its storage is still a substantial challenge. Through this review report, it can be postulated that chemical storage is a suitable technique as compared to physical storage, since in physical storage, it requires higher temperature and pressure for hydrogen storage, whereas smaller amount of temperature and pressure is needed during the chemical process. Furthermore, a detailed review was carried out for hydrogen storage on graphene systems, apart from graphene few novel 2D systems were also studied regarding their application in hydrogen storage. Through detailed survey, it was observed that boron as a surface activating agent for various 2D sheets provides significant H wt% as compared to other impurity atoms used for various 2D sheets. Hence, it can be postulated that boron‐doped systems can be good hydrogen storage agents. Further, transition metal di‐chalcogenides (TMDCs) sheets are rarely used as host sheets for H storage, whereas TM impurities are considered for 2D sheets activation. In addition to above, the advantages and disadvantages of the different 2D systems for hydrogen storage are discussed and compared in a detailed manner.
DNA testing for sickle cell anemia in Africa: Implementation choices for the Democratic Republic of Congo
Authors: Ngole Mamy , Race Valerie , Mbayabo Gloire , Lumbala Paul , Songo Cathy , Lukusa Prosper Tshilobo , Devriendt Koenraad , Matthijs Gert , Lumaka Aimé 
Published: April 2022

AbstractBackgroundHemoglobin‐based tests form the reference diagnostic test for SCA. In limited resource countries, these tests face limitations including cost, low sensitivity due to recurrent transfusions in endemic malaria region, and interference from fetal hemoglobin in neonatal diagnostic. This study aimed at adapting DNA‐based SCA tests to limited resource countries and evaluating the economic benefit.Methods338 participants were recruited in the Democratic Republic of Congo, sorted in 3 cohorts based on venous blood, umbilical cord blood (UCB) and buccal swab sampling. RFLP was performed to identify mutated allele. The feasibility and technical validity of this RFLP was evaluated for specimens collected on DBS cards and on EDTA tubes. RFLP on DBS stored at room temperature was regularly repeated to assess sample conservation. Finally, the cost analysis was performed.ResultsDBS cards yielded identical results to extracted DNA. Repeated testing returned the same result after four years. The DBS‐based test performed on UCB or on buccal swab had a sensitivity and a precision of 100%. Cost comparison indicated that our approach costs half price of the widely used isoelectrofocussing of hemoglobin.ConclusionThe implemented DNA‐based test approach overcomes the limitations faced by hemoglobin‐based tests, while being more affordable. We propose to implement the RFLP test as a first line diagnostic test after transfusion and as second tiers for newborn screening. However, users should be aware that this test is unable to differentiate HbC from HbS or identify other point mutation of gene deletion of HBB gene.
Beneficial effects of melatonin on liver fibrosis: A systematic review of current biological evidence
Authors: San‐Miguel Beatriz , Fernández‐Palanca Paula , Mauriz José L. , Tuñón María J. , González‐Gallego Javier 
Published: April 2022

AbstractHepatic fibrosis is a reversible response to either acute or chronic cellular injury from a wide variety of etiologies, characterized by excessive deposition of extracellular matrix resulting in liver dysfunction and cirrhosis. Melatonin (N‐acetyl‐5‐methoxytryptamine), the main product secreted by the pineal gland, is a multitasking indolamine with important physiological functions such as anti‐inflammatory and antioxidant actions, modulation of circadian rhythms, and immune system enhancement. Among the numerous biological activities of melatonin, its antifibrotic effects have received increasingly more attention. In this study, we performed a systematic review of publications of the last 10 years evaluating the mechanisms of action of melatonin against liver fibrosis. The study protocol was registered at PROSPERO (CRD42022304744). Literature research was performed employing PubMed, Scopus, and Web of Science (WOS) databases, and after screening, 29 articles were included. Results from the selected studies provided denoted the useful actions of melatonin on the development, progression, and evolution of liver fibrosis. Melatonin antifibrotic effects in the liver involved the reduction of profibrogenic markers and modulation of several cellular processes and molecular pathways, mainly acting as an antioxidant and anti‐inflammatory agent. In addition, the indolamine influenced different molecular processes, such as hepatocyte apoptosis, modulation of autophagy and mitophagy, restoration of circadian rhythms, and modulation of microRNAs, among others. Although some limitations have been found regarding variability in the study design, the findings here summarized display the potential role of melatonin in ameliorating the development of liver fibrosis and its possible progression to liver cirrhosis and hepatocarcinoma.
Crowdsourcing the identification of studies for COVID‐19‐related Cochrane Rapid Reviews
Authors: Noel‐Storr Anna , Gartlehner Gerald , Dooley Gordon , Persad Emma , Nussbaumer‐Streit Barbara 
Published: April 2022

AbstractBackgroundUtilisation of crowdsourcing within evidence synthesis has increased over the last decade. Crowdsourcing platform Cochrane Crowd has engaged a global community of 22,000 people from 170 countries. The COVID‐19 pandemic presented an opportunity to engage the community and keep up with the exponential output of COVID‐19 research.AimsTo test whether a crowd could accurately assess study eligibility for reviews under time constraints. Outcome measures: time taken to complete each task, time to produce required training modules, crowd sensitivity, specificity and crowd consensus.MethodsWe created four crowd tasks, corresponding to four Cochrane COVID‐19 Rapid Reviews. The search results of each were uploaded and an interactive training module was developed for each task. Contributors who had participated in another COVID‐19 task were invited to participate. Each task was live for 48‐h. The final inclusion and exclusion decisions made by the core author team were used as the reference standard.ResultsAcross all four reviews 14,299 records were screened by 101 crowd contributors. The crowd completed each screening task within 48‐h for three reviews and in 52 h for one. Sensitivity ranged from 94% to 100%. Four studies, out of a total of 109, were incorrectly rejected by the crowd. However, their absence ultimately would not have altered the conclusions of the reviews. Crowd consensus ranged from 71% to 92% across the four reviews.ConclusionCrowdsourcing can play a valuable role in study identification and offers willing contributors the opportunity to help identify COVID‐19 research for rapid evidence syntheses.
Soil salinity inversion in coastal cotton growing areas: An integration method using satellite‐ground spectral fusion and satellite‐UAV collaboration
Authors: Qi Guanghui , Chang Chunyan , Yang Wei , Zhao Gengxing 
Published: April 2022

AbstractSoil salinity is a crucial factor in agriculture, rising salinity undermines cotton (Gossypium spp.) production in coastal areas of China and damages crops in other countries. In this study, we propose an effective integration method using satellite‐ground spectral fusion and satellite‐unmanned arial vehicle (UAV) collaboration for soil salinity monitoring in cotton growing areas. Firstly, an extreme learning machine (ELM), random forest (RF), and extreme gradient boosting (XGBoost) models were constructed based on UAV images from test areas. The optimal model was selected for soil salinity inversion. Meanwhile, ground imaging hyperspectrum and SENTINEL‐2A multispectral images were differentially fused by nonnegative matrix factorization (NMF). Then, taking the inversion results of UAV as the training sample to build convolutional neural network (CNN) model of the fused SENTINEL‐2A, the soil salinity distribution map of cotton fields in the study area was obtained by inversion, and the satellite‐UAV‐ground integrated inversion of soil salinity in coastal cotton fields was realized. The results showed that the spectrum after satellite‐ground fusion was closer to the original ground hyperspectrum, the fusion improved the correlation between spectrum and soil salinity, and UAV inversion data possessed great potential for the reference data of satellite inversion. The soil salinity obtained by satellite‐UAV‐ground integration approach was highly consistent with the measured salinity in the study area (R2 = 0.805), and the integration approach is suitable for soil salinity inversion in the cotton seedling stage in the coastal area. The satellite‐UAV‐ground integration approach proposed in this study fully tap the advantages of remote sensing data from different platforms and improved the ability to obtain soil salinisation information in large‐scale quantitatively, accurately, and quickly.