bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of deep learning models in contactless human motion detection system for next generation healthcare
Authors: Song Yukai , Taylor William , Ge Yao , Usman Muhammad , Imran Muhammad Ali , Abbasi Qammer H. 
Published: December 2022

AbstractRecent decades have witnessed the growing importance of human motion detection systems based on artificial intelligence (AI). The growing interest in human motion detection systems is the advantages of automation in the monitoring of patients remotely and giving warnings to doctors promptly. Currently, wearable devices are frequently used for human motion detection systems. However, such devices have several limitations, such as the elderly not wearing devices due to lack of comfort or forgetfulness and/or battery limitations. To overcome the problems of wearable devices, we propose an AI-driven human motion detection system (deep learning-based system) using channel state information (CSI) extracted from Radio Frequency (RF) signals. The main contribution of this paper is to improve the performance of the deep learning models through techniques, including structure modification and dimension reduction of the original data. In this work, We firstly collected the CSI data with the center frequency 5.32 GHz and implemented the structure of the basic deep learning network in our previous work. After that, we changed the basic deep learning network by increasing the depth, increasing the width, adapting some advanced network structures, and reducing dimensions. After finishing those modifications, we observed the results and analyzed how to further improve the deep learning performance of this contactless AI-enabled human motion detection system. It can be found that reducing the dimension of the original data can work better than modifying the structure of the deep learning model.
Predicting multipotency of human adult stem cells derived from various donors through deep learning
Authors: Kim Hyeonji , Park Keonhyeok , Yon Jung-Min , Kim Sung Won , Lee Soo Young , Jeong Iljoo , Jang Jinah , Lee Seungchul , Cho Dong-Woo 
Published: December 2022

AbstractAdult stem cell-based therapeutic approaches have great potential in regenerative medicine because of their immunoregulatory properties and multidifferentiation capacity. Nevertheless, the outcomes of stem cell‑based therapies to date have shown inconsistent efficacy owing to donor variation, thwarting the expectation of clinical effects. However, such donor dependency has been elucidated by biological consequences that current research could not predict. Here, we introduce cellular morphology-based prediction to determine the multipotency rate of human nasal turbinate stem cells (hNTSCs), aiming to predict the differentiation rate of keratocyte progenitors. We characterized the overall genes and morphologies of hNTSCs from five donors and compared stemness-related properties, including multipotency and specific lineages, using mRNA sequencing. It was demonstrated that transformation factors affecting the principal components were highly related to cell morphology. We then performed a convolutional neural network-based analysis, which enabled us to assess the multipotency level of each cell group based on their morphologies with 85.98% accuracy. Surprisingly, the trend in expression levels after ex vivo differentiation matched well with the deep learning prediction. These results suggest that AI‑assisted cellular behavioral prediction can be utilized to perform quantitative, non-invasive, single-cell, and multimarker characterizations of live stem cells for improved quality control in clinical cell therapies.
Adaptive driver following model that integrates perception process and driving behavior
Authors: Piao Changhao , Li Kexin , Yu Qifan , Shi Junren 
Published: December 2022

AbstractIn order to meet the personalized needs of Chinese intelligent vehicles and improve the satisfaction and acceptance of human–computer interaction and collaboration in domestic intelligent vehicles. In this paper, we design an adaptive longitudinal following model that integrates the perceptual perturbation process and driver characteristics for simulating driver following behavior and studying the variability of driver following behavior. Firstly, for the independence and randomness of driver perception process, a set of random variables conforming to Wiener process is introduced to simulate the perception process of speed and following distance of the vehicle in front; secondly, for the characteristic differences of different drivers' following behavior, a driver characteristic parameter identification algorithm is designed to identify the expected collision time distance and following distance parameters of different drivers, and the identified parameters will be used for Again, a sliding mode control system based on fuzzy switching gain adjustment is designed to simulate the driver following control system. The results show that the designed following model recognizes the driver's characteristics well and can better simulate the driver's following behavior, and the following index is relatively improved by 80%.
Hybridization and diversity of aquatic macrophyte Sparganium L. (Typhaceae) as revealed by high-throughput nrDNA sequencing
Authors: Belyakov Evgeny A. , Mikhaylova Yulia V. , Machs Eduard M. , Zhurbenko Peter M. , Rodionov Aleksandr V. 
Published: December 2022

AbstractSparganiumis an emergent aquatic macrophyte widely spread in temperate and subtropical zones. Taxa of this genus feature high phenotypic plasticity and can produce interspecific hybrids. By means of high-throughput sequencing of the internal transcribed spacer (ITS1) of 35S rDNA, the status of 15 EurasianSparganiumspecies and subspecies was clarified and the role of hybridization events in the recent evolution of the genus was investigated. It has been shown that a number of species such asS. angustifolium, S. fallaxandS. subglobosumhave homogenized rDNA represented by one major ribotype. The rDNA of other taxa is represented by two or more major ribotypes. Species with high rDNA heterogeneity are apparently of hybrid origin. Based on the differences in rDNA patterns, intraspecific diversity was identified inS. probatovaeandS. emersum. Thus, we have concluded thatSparganiumhas extensive interspecific hybridization at the subgenus level, and there may also be occasional hybridization between species from different subgenera.
Skeletal muscle transcriptome is affected by age in severely burned mice
Authors: Song Juquan , Widen Steven G. , Wolf Steven E. , EI Ayadi Amina 
Published: December 2022

AbstractSevere burn results in muscle wasting affecting quality of life in both children and adults. Biologic metabolic profiles are noticeably distinctive in childhood. We posit that muscle gene expression profiles are differentially regulated in response to severe burns in young animals. Twelve C57BL6 male mice, including young (5 weeks-old) and adults (11 weeks-old), received either scald burn, or sham procedure. Mouse muscle tissue was harvested 24 h later for Next Generation Sequence analysis. Our results showed 662 downregulated and 450 upregulated genes in gastrocnemius of young mice compared to adults without injury. After injury, we found 74/75 downregulated genes and 107/128 upregulated genes in both burned groups compared to respective uninjured age groups. VEGFA-VEGFR2, focal adhesion, and nuclear receptor meta-pathways were the top 3 gene pathways undergoing a differential change in response to age. Of note, the proteasome degradation pathway showed the most similar changes in both adult and young burned animals. This study demonstrates the characteristic profile of gene expression in skeletal muscle in young and adult burned mice. Prominent age effects were revealed in transcriptional levels with increased alterations of genes, miRNAs, pathways, and interactions.
Automated BIM-based structural design and cost optimization model for reinforced concrete buildings
Authors: Sherif Mohamed , Nassar Khaled , Hosny Ossama , Safar Sherif , Abotaleb Ibrahim 
Published: December 2022

AbstractThe process of optimizing building designs requires developing several architectural and structural layout alternatives. Traditionally, limited number of design iterations can be conducted manually, which is time consuming and results in non-optimum designs in terms of limited functionality or high costs. The goal of this research is to develop an advanced Building Information Modeling (BIM) model for automating and optimizing design of building layouts and structural elements to reach minimum construction cost while abiding by the functionality constraints of the architectural design. The developed model integrates concepts from structural design, BIM modeling, and computer programming into one advanced optimization framework. The model was tested and validated in 11 case studies and is found to reduce the structural materials cost by up to 15% per floor without compromising the defined space requirements.
Molecular and metabolic alterations of 2,3-dihydroquinazolin-4(1H)-one derivatives in prostate cancer cell lines
Authors: Dahabiyeh Lina A. , Hourani Wafa , Darwish Wesam , Hudaib Farah , Abu-Irmaileh Bashaer , Deb Pran Kishore , Venugopala Katharigatta N. , Mohanlall Viresh , Abu-Dahab Rana , Semreen Mohammad H. , Bustanji Yasser 
Published: December 2022

AbstractProstate cancer (PC) is the second most common tumor in males worldwide. The lack of effective medication and the development of multidrug resistance towards current chemotherapeutic agents urge the need to discover novel compounds and therapeutic targets for PC. Herein, seven synthesized 2,3-dihydroquinazolin-4(1H)-one analogues were evaluated for their anticancer activity against PC3 and DU145 cancer cell lines using MTT, scratch-wound healing, adhesion and invasion assays. Besides, a liquid chromatography mass spectrometry (LC–MS)-based metabolomics approach was followed to identify the biochemical pathways altered in DU145 cancer cells upon exposure to dihydroquinazolin derivatives. The seven compounds showed sufficient cytotoxicity and significantly suppressed DU145 and PC3 migration after 48 and 72 h. C2 and C5 had the most potent effect with IC50 < 15 µM and significantly inhibited PC cell adhesion and invasion. Metabolomics revealed that C5 disturbed the level of metabolites involved in essential processes for cancer cell proliferation, progression and growth including energy production, redox homeostasis, amino acids and polyamine metabolisms and choline phospholipid metabolism. The data presented herein highlighted the importance of these compounds as potential anticancer agents particularly C5, and pointed to the promising role of metabolomics as a new analytical approach to investigate the antiproliferative activity of synthesized compounds and identify new therapeutic targets.
A new method for hosting and sharing MATLAB Web App
Authors: Ren Ruijie , Sun Xiang-e , Hu Lin 
Published: December 2022

AbstractCurrently, using MATLAB Web App Server to deploy MATLAB Web applications for hosting and sharing interactive Web applications involves the following problems: slow loading of applications, incompatibility with some browser versions, and various shortcomings of deployment tools, such as poor scalability and difficulty in optimizing black boxes. These problems adversely affect the user experience. To address this situation, we propose the use of front-end technology to design application layouts and build an application hosting platform with front-end and back-end separation using Nginx and Python. This method is shown to be simple and efficient, and it can successfully overcome the aforementioned problems while providing new ideas for hosting and sharing.
The combined effects of temperature and salinity on the digestion and respiration metabolism of Pinctada fucata
Authors: Yang Jingru , Fu Zhengyi , Ma Zhenhua , Yu Gang 
Published: December 2022

AbstractThe combined effects of temperature and salinity on the digestion and respiration metabolism of Pinctada fucata were evaluated via response surface methodology and box-benhnken design under laboratory condition. Results indicated that the primary and secondary effects of salinity and temperature had significant effects on amylase (AMS) of P. fucata (P < 0.05)., The digestive enzyme reached the maximum activity when temperature was 26 °C. The AMS and trypsin (TRYP) increased at first, and then decreased with increasing temperature. The Lipase (LPS) was positively correlated with either salinity or temperature. Salinity had no significant effect on TRYP as a primary effect (P > 0.05), but had a significant effect on TRYP as a secondary effect (P < 0.01). These effects were completely opposite to the effect of temperature on pepsin (PEP) as primary and secondary effects. The combined effects of salinity and temperature on AMS, TRYP and PEP were significant (P < 0.01), but had no significant effect on LPS (P > 0.05). The primary, secondary and interaction effects of salinity had significant effects on NKA (Na+-K+-ATPase) of P. fucata (P < 0.05), and NKA presented a U-shaped distribution with increasing salinity. The quadratic and interactive effects of temperature had a significant effect on AKP (P < 0.05), and AKP showed a U-shaped distribution with increasing temperature. Lactate dehydrogenase (LDH) activity decreased at first, and then increased when temperature and salinity changed from 20 to 30 °C and 23–33 ‰, respectively. The expression of GPX gene affected by temperature in gills may be delayed compared with that in hepatopancreas, and its expression is tissue-specific. The appropriate digestion and respiratory metabolism index models were established under the combined temperature and salinity conditions. The optimization results showed that the optimal combination of temperature and salinity was 26.288 °C/28.272‰. The desirability was 0.832. Results from the present study will provide a theoretical reference for shellfish culture affected by environmental interactions and the establishment of related index models.
Effects of substituting agro-industrial by-products for soybean meal on beef cattle feed utilization and rumen fermentation
Authors: Suriyapha Chaichana , Suntara Chanon , Wanapat Metha , Cherdthong Anusorn 
Published: December 2022

AbstractThe purpose of the present investigation was to detect the effect of replacement of soybean meal (SBM) with citric waste fermented yeast waste (CWYW) as an alternative protein source of portentous substances in a concentrate mixture diet of beef cattle on intake, digestibility, ruminal fermentation, plasma urea-nitrogen, energy partitioning, and nitrogen balance. Four Thai-native beef bulls (170 ± 10.0 kg of initial body weight) were randomly allocated to a 4 × 4 Latin square design. The dietary treatments were four levels of CWYW replacing SBM in a concentrated diet at ratios of 0, 33, 67, and 100%. SBM was added to the concentrate diet at a dose of 150 g/kg DM. All cattle were offered ad libitum rice straw and the concentrate diet at 5 g/kg of body weight. The study was composed of four periods, each lasting for 21 days. The findings demonstrated that there was no difference in total dry matter intake, nutritional intake, or digestibility between treatments (p > 0.05). When CWYW replaced SBM at 100% after 4 h of feeding, ruminal pH, ammonia nitrogen, plasma urea nitrogen, and bacterial population were highest (p < 0.05). Volatile fatty acids and energy partitioning were not different (p > 0.05) among dietary treatments. Urinary nitrogen excretion was greatest (p < 0.05) for cattle fed CWYW to replace SBM at 100% of the concentrate. However, nitrogen absorption and retention for Thai-native cattle were similar (p > 0.05) among treatments. In conclusion, CWYW may be utilized as a substitute for SBM as a source of protein in Thai-native beef cattle without having an adverse impact on feed utilization, rumen fermentation characteristics, or blood metabolites.
Brazilin from Caesalpinia sappan inhibits viral infection against PRRSV via CD163ΔSRCR5 MARC-145 cells: an in silico and in vitro studies
Authors: Arjin Chaiwat , Tateing Suriya , Potapohn Nuttha , Arunorat Jirapat , Pringproa Kidsadagon , Lumsangkul Chompunut , Seel-audom Mintra , Ruksiriwanich Warintorn , Sringarm Korawan 
Published: December 2022

AbstractThis research aimed to identify bioactive compounds from Caesalpinia sappan extract that function as novel porcine reproductive and respiratory syndrome virus (PRRSV) infection inhibitors by computational molecular screening. We obtained a set of small-molecule compounds predicted to target the scavenger receptor cysteine-rich domain 5 (SRCR5) of CD163. In addition, the functions of positive hits were assessed and verified utilizing an in vitro antiviral activity assay with PRRSV-infected MARC-145 cells. Combining molecular docking with the results of binding affinity and ligand conformation, it was found that brazilin had the highest binding energy with the SRCR5 receptor compared to catechin and epicatechin (− 5.8, − 5.5, and − 5.1 kcal/mol, respectively). In terms of molecular mechanics, the binding free energy between the SRCR5 receptor was − 15.71 kcal/mol based on the Poisson-Boltzmann surface area of brazilin. In addition, PRRSV infection in MARC-145 cells was significantly inhibited by brazilin compared to the control (virus titer, 4.10 vs. 9.25 TCID50/mL, respectively). Moreover, brazilin successfully limited the number of PRRSV RNA copies in MARC-145 cells as determined by RT-qPCR. By inhibiting the PRRSV-CD163 interaction with brazilin from Caesalpinia sappan, it may be possible to prevent PRRSV infection in pigs, as suggested by this research.
Outcome in early vs late intubation among COVID-19 patients with acute respiratory distress syndrome: an updated systematic review and meta-analysis
Authors: Ridjab Denio A. , Ivan Ignatius , Budiman Fanny , Juzar Dafsah A. 
Published: December 2022

AbstractTiming of endotracheal intubation in COVID-19 patients with acute respiratory distress syndrome (ARDS) remains controversial regarding its risk and benefit in patient outcomes. Our study aims to elucidate early versus late intubation outcomes among COVID-19 patients with ARDS. A protocol of this study is registered at the international prospective register of systematic reviews (PROSPERO) (CRD42021230272). We report our systematic review based on PRISMA and MOOSE guidelines. We searched the Cochrane Library, EBSCOhost, EMBASE, Grey Literature Report, OpenGrey, ProQuest, PubMed, and ScienceDirect from inception until 4 December 2021. Titles and abstracts were reviewed for their relevance. The risk of bias in each study was evaluated using the risk of bias in non-randomised studies-of interventions (ROBINS-I) guideline. Trial sequential analysis is done to elucidate firm evidence. We retrieved 20 observational studies that assessed an intervention (early vs. late intubation). Meta-analysis for in-hospital mortality reduction showed 119 fewer deaths per 1000 patients in early intubation. Early intubation reduces 2.81 days of ICU length of stay (LOS) and 2.12 days of ventilation duration. Benefits for mortality and ICU LOS reduction were based on studies with low to moderate risk of bias while ventilation duration was based on low disease burden setting. According to the contextualized approach, the benefit of mortality reduction showed a trivial effect, while ICU LOS and ventilation duration showed a small effect. GRADE certainty of evidence for mortality reduction in early intubation is moderate. The certainty of evidence for ICU length of stay, ventilation duration, ventilator-free days, and continuous renal replacement therapy are very low. This updated systematic review provided new evidence that early intubation might provide benefits in treating COVID-19 patients with ARDS. The benefits of early intubation appear to have an important but small effect based on contextualized approach for ICU LOS and ventilation duration. In reducing in-hospital mortality, the early intubation effect was present but only trivial based on contextualized approach. TSA showed that more studies are needed to elucidate firmer evidence.
H2S and SO2 detectability in hot Jupiters
Authors: Polman J. , Waters L. B. F. M. , Min M. , Miguel Y. , Khorshid N. 
Published: December 2022

Context. The high cosmic abundance, the intermediate volatility, and the chemical properties of sulphur allow sulphur-bearing species to be used as tracers of the chemical processes in the atmospheres of hot Jupiter exoplanets. Nevertheless, despite their properties and relevance as tracers of the giant planets’ formation histories, little attention has been paid to these species in the context of hot Jupiter atmospheres.
Aims. In this paper, we provide an overview of the abundances of sulphur-bearing species in hot Jupiter atmospheres under different conditions and explore their observability.
Methods. We used the photochemical kinetics code VULCAN to model hot Jupiter atmospheric disequilibrium chemistry. Transmission spectra for these atmospheres were created using the modelling framework ARCiS. We varied model parameters such as the diffusion coefficient Kzz, and we studied the importance of photochemistry on the resulting mixing ratios. Furthermore, we varied the chemical composition of the atmosphere by increasing the metallicity from solar to ten times solar. We also explored different C/O ratios.
Results. We find that H2S and SO2 are the best candidates for detection between 1 and 10 μm, using a spectral resolution that is representative of the instruments on board the James Webb Space Telescope (JWST). H2S is easiest to detect at an equilibrium temperature of ~1500 K, and with C/O ratios between 0.7 and 0.9, with the ideal value increasing slightly for increasing metallicity. SO2 is most likely to be detected at an equilibrium temperature of ~1000 K at low C/O ratios and high metallicities. Nevertheless, among these two molecules, we expect SO2 detection to be more common, as it is detectable in scenarios more favoured by formation models.
Conclusions. We conclude that H2S and SO2 will most likely be detected in the coming years with the JWST, and that the detection of these species will provide information on atmospheric processes and planet formation scenarios.
Existence of variational solutions to nonlocal evolution equationsviaconvex minimization
Authors: Prasad Harsh , Tewary Vivek 
Published: December 2022

We prove existence of variational solutions for a class of nonlocal evolution equations whose prototype is the double phase equation[see formula in PDF]The approach of minimization of parameter-dependent convex functionals over space-time trajectories requires only appropriate convexity and coercivity assumptions on the nonlocal operator. As the parameter tends to zero, we recover variational solutions. Under further growth conditions, these variational solutions are global weak solutions. Further, this provides a direct minimization approach to approximation of nonlocal evolution equations.