Miracle-dz/UniFAR-FTUs huggingface dataset:
An improved multiphase SPH algorithm with kernel gradient correction for modelling fuel–coolant interaction

Fuel–coolant interaction (FCI) has a pivotal role in the development of core disruptive accident in a sodium-cooled fast reactor. The drastic deformation of multiphase interface in the FCI is hard to deal with in the traditional grid method. In this paper, an improved multiphase smoothed particle hydrodynamics (SPH) algorithm corrected with the kernel gradient correction (KGC) technique is presented for multiphase flow with a large density ratio and complex interfacial behaviors. The density discontinuity across the multiphase interface is described with the use of special volume, which only depends on the position information of adjacent particles. This multiphase SPH algorithm, which is troubled by an unstable and mixed-interface problem under a large density ratio, is significantly improved with the KGC technique. The accuracy and robustness of the improved method are demonstrated in the numerical simulations of the deformation of a square droplet, Rayleigh–Taylor instability, and bubble rising in water. The verified corrected multiphase SPH is applied to simulate the hydrodynamic behaviors of the general FCI and the interaction between fuels coated with stainless steel film and coolant. Boundary layer stripping, Rayleigh–Taylor instability, and Kelvin–Helmholtz instability are observed as important mechanisms of hydraulic fracturing. The fragments’ distribution and the influence of stainless steel film are analyzed. The existence of a stainless steel film has been shown to inhibit breakage.
Meaning in military service among reservists: Measuring the effect of prosocial motivation in a moderated-mediation model

Introduction The meaningful commitment to serve one’s country and the desire to defend others make military service unique compared to other human activities. This is especially true for the army reservists who are typically working in the civilian labor market and serving military for the short-term military training or military missions only. As scholars provide limited insights into the effects and influences of prosocial motivation on meaning in military service, this study contributes to the understanding of direct, mediated, and moderated processes which link prosocial motivation to meaning in military service among reservists. Specifically, the objective of this study was to examine both direct and indirect pathways interconnecting prosocial motivation and meaning in military service. The former is analyzed as a direct effect, while the latter includes the effects of role fit within the military environment, the soldiers’ self-efficacy, as well as the socio-moral climate of military organization—that is, a variable making military service an exceptional activity. Methods This study followed a quantitative method analysis by utilizing a hierarchical regression analysis which revealed direct, moderating, and mediating links between the variables. The analysis was based on a sample of 375 soldiers from the Active Reserve of the Lithuanian Armed Forces, and the data were collected before and after training exercises in one military unit (repeated measures). The effects on providing meaning to military service were evaluated using the following: Occupational Self-Efficacy Scale, Prosocial Motivation Scale, Motivation at Work Scale, and Socio-Moral Climate Scale. Prosocial motivation assumes meaning in military service among reservists through different, yet related, pathways. Results and discussion The direct pathway confirmed that reserve soldiers with higher levels of prosocial motivation experience a higher level of meaning in service. The indirect pathway indicated that role fit mediated this relationship. Following the latter, we found that prosocial motivation was a significant predictor of both role fit and meaning in military service. Finally, we confirmed the moderated-mediation effects of self-efficacy and socio-moral climate in our suggested models. The results can be used to improve training programs for reservists.
Predicting lncRNA-protein interactions with bipartite graph embedding and deep graph neural networks

Background: Long non-coding RNAs (lncRNAs) play crucial roles in numerous biological processes. Investigation of the lncRNA-protein interaction contributes to discovering the undetected molecular functions of lncRNAs. In recent years, increasingly computational approaches have substituted the traditional time-consuming experiments utilized to crack the possible unknown associations. However, significant explorations of the heterogeneity in association prediction between lncRNA and protein are inadequate. It remains challenging to integrate the heterogeneity of lncRNA-protein interactions with graph neural network algorithms. Methods: In this paper, we constructed a deep architecture based on GNN called BiHo-GNN, which is the first to integrate the properties of homogeneous with heterogeneous networks through bipartite graph embedding. Different from previous research, BiHo-GNN can capture the mechanism of molecular association by the data encoder of heterogeneous networks. Meanwhile, we design the process of mutual optimization between homogeneous and heterogeneous networks, which can promote the robustness of BiHo-GNN. Results: We collected four datasets for predicting lncRNA-protein interaction and compared the performance of current prediction models on benchmarking dataset. In comparison with the performance of other models, BiHo-GNN outperforms existing bipartite graph-based methods. Conclusion: Our BiHo-GNN integrates the bipartite graph with homogeneous graph networks. Based on this model structure, the lncRNA-protein interactions and potential associations can be predicted and discovered accurately.
The double-edged sword effects of active social media use on loneliness: The roles of interpersonal satisfaction and fear of missing out

Introduction Social media' impact on loneliness has attracted widespread scholarly attention. One hypothesis is that active social media use (ASMU) is associated with a decrease in loneliness. However, several empirical studies did not find a significant correlation between ASMU and loneliness, and ASMU may even increase loneliness. This study explored the mechanism of the double-edged sword effects of ASMU on loneliness. Methods Data were collected through convenience sampling from three universities in China. A total of 454 Chinese college social media users (Mean age 19.75 ± 1.33; 59.92% female) completed an online questionnaire. Results ASMU was positively related to interpersonal relationship satisfaction, which was negatively related to general trait-fear of missing out (FoMO) and loneliness. Further structural equation modeling (SEM) analysis showed that ASMU could negatively predict loneliness through the mediation pathways of interpersonal satisfaction and “Interpersonal satisfaction → Trait-FoMO. ” At the same time, ASMU was also positively associated with online-specific state-FoMO, which was positively associated with trait-FoMO and loneliness. Further SEM analysis found no mediation effect of state-FoMO between ASMU and loneliness, but state-FoMO and traitFoMO sequentially mediate the relationship between ASMU and loneliness. Discussion This study indicates that ASMU may increase and decrease loneliness. Interpersonal satisfaction and FoMO explained the double-edged mechanism of ASMU on loneliness. These findings contribute to dialectically understanding the effectiveness of active social media use and provide theoretical guidance for promoting the beneficial aspects of social media while weakening its harmful consequences.
Lipidomics and proteomics: An integrative approach for early diagnosis of dementia and Alzheimer’s disease

Alzheimer’s disease (AD) is the most common neurodegenerative disorder and considered to be responsible for majority of worldwide prevalent dementia cases. The number of patients suffering from dementia are estimated to increase up to 115.4 million cases worldwide in 2050. Hence, AD is contemplated to be one of the major healthcare challenge in current era. This disorder is characterized by impairment in various signaling molecules at cellular and nuclear level including aggregation of Aβ protein, tau hyper phosphorylation altered lipid metabolism, metabolites dysregulation, protein intensity alteration etc. Being heterogeneous and multifactorial in nature, the disease do not has any cure or any confirmed diagnosis before the onset of clinical manifestations. Hence, there is a requisite for early diagnosis of AD in order to downturn the progression/risk of the disorder and utilization of newer technologies developed in this field are aimed to provide an extraordinary assistance towards the same. The lipidomics and proteomics constitute large scale study of cellular lipids and proteomes in biological matrices at normal stage or any stage of a disease. The study involves high throughput quantification and detection techniques such as mass spectrometry, liquid chromatography, nuclear mass resonance spectroscopy, fluorescence spectroscopy etc. The early detection of altered levels of lipids and proteins in blood or any other biological matrices could aid in preventing the progression of AD and dementia. Therefore, the present review is designed to focus on the recent techniques and early diagnostic criteria for AD, revealing the role of lipids and proteins in this disease and their assessment through different techniques.
Understanding transitions in exploration profiles of students opting for higher education

Introduction Since previous research on educational career exploration has mainly been cross-sectional and therefore has been unsuccessful in explaining how this process can change during the final year in secondary education before students make the transition to higher education, this study aimed to examine changes over time in the exploration process. A person-centered research perspective was taken to further deepen the understanding of how different exploration tasks jointly combine into meaningful profiles. In this way, this study tried to gain more insight into why some students go through this process successfully and others do not. Four goals guided this study: identifying exploration profiles of students in Fall and Spring of the final year in secondary school based on four decisional tasks (orientation, self-, broad and in-depth exploration), investigating transitions between exploration profiles across these two timepoints, and examining the role which different antecedents (i.e., academic self-efficacy, academic self-concept, motivation, test anxiety, gender, educational track, socio-economic status) play in explaining both profile membership and transitions between profiles. Methods Using self-report questionnaires to measure the exploration tasks and the antecedents in final year students, two cross-sectional samples collected in Fall (n = 9,567) and Spring (n = 7,254), and one longitudinal sample (n = 672) were examined. Results Latent profile analyses identified three exploration profiles at both timepoints: passive, moderately active, and highly active explorers. Latent transition analysis showed the moderately active explorers profile to be the most stable profile, while the passive profile was the most variable profile. Academic self-concept, motivation, test anxiety, and gender had an effect on the initial states, while motivation and test anxiety affected the transition probabilities. For both academic self-concept and motivation, students scoring higher were found to be less present in the passive or the moderately active than in the highly active profile. Furthermore, compared to students who remained in the passive profile, higher levels of motivation were associated with a higher probability to transition to the moderately active profile. Next to that, compared to students who remained in the highly active profile, higher levels of motivation were associated with a lower probability to transition to the moderately active profile. Results on anxiety were inconsistent. Discussion Based on substantial cross-sectional as well as longitudinal data, our findings contribute to a more comprehensive understanding of the explanatory base of important differences in the study choice making process of students opting for higher education. This may ultimately lead to more timely and fitting support for students with different exploration profiles.
Optimal CT perfusion thresholds for core and penumbra in acute posterior circulation infarction

Background At least 20% of strokes involve the posterior circulation (PC). Compared to the anterior circulation, posterior circulation infarction (POCI) are frequently misdiagnosed. CT perfusion (CTP) has advanced stroke care by improving diagnostic accuracy and expanding eligibility for acute therapies. Clinical decisions are predicated upon precise estimates of the ischaemic penumbra and infarct core. Current thresholds for defining core and penumbra are based upon studies of anterior circulation stroke. We aimed to define the optimal CTP thresholds for core and penumbra in POCI. Methods Data were analyzed from 331-patients diagnosed with acute POCI enrolled in the International-stroke-perfusion-registry (INSPIRE). Thirty-nine patients with baseline multimodal-CT with occlusion of a large PC-artery and follow up diffusion weighted MRI at 24–48 h were included. Patients were divided into two-groups based on artery-recanalization on follow-up imaging. Patients with no or complete recanalisation were used for penumbral and infarct-core analysis, respectively. A Receiver operating curve (ROC) analysis was used for voxel-based analysis. Optimality was defined as the CTP parameter and threshold which maximized the area-under-the-curve. Linear regression was used for volume based analysis determining the CTP threshold which resulted in the smallest mean volume difference between the acute perfusion lesion and follow up MRI. Subanalysis of PC-regions was performed. Results Mean transit time (MTT) and delay time (DT) were the best CTP parameters to characterize ischaemic penumbra (AUC = 0.73). Optimal thresholds for penumbra were a DT >1 s and MTT>145%. Delay time (DT) best estimated the infarct core (AUC = 0.74). The optimal core threshold was a DT >1.5 s. The voxel-based analyses indicated CTP was most accurate in the calcarine (Penumbra-AUC = 0.75, Core-AUC = 0.79) and cerebellar regions (Penumbra-AUC = 0.65, Core-AUC = 0.79). For the volume-based analyses, MTT >160% demonstrated best correlation and smallest mean-volume difference between the penumbral estimate and follow-up MRI (R2 = 0.71). MTT >170% resulted in the smallest mean-volume difference between the core estimate and follow-up MRI, but with poor correlation (R2 = 0.11). Conclusion CTP has promising diagnostic utility in POCI. Accuracy of CTP varies by brain region. Optimal thresholds to define penumbra were DT >1 s and MTT >145%. The optimal threshold for core was a DT >1.5 s. However, CTP core volume estimates should be interpreted with caution.
Bacterial volatile organic compounds (VOCs) promote growth and induce metabolic changes in rice

Plant growth-promoting bacteria (PGPB) represent an eco-friendly alternative to reduce the use of chemical products while increasing the productivity of economically important crops. The emission of small gaseous signaling molecules from PGPB named volatile organic compounds (VOCs) has emerged as a promising biotechnological tool to promote biomass accumulation in model plants (especially Arabidopsis thaliana) and a few crops, such as tomato, lettuce, and cucumber. Rice (Oryza sativa) is the most essential food crop for more than half of the world’s population. However, the use of VOCs to improve this crop performance has not yet been investigated. Here, we evaluated the composition and effects of bacterial VOCs on the growth and metabolism of rice. First, we selected bacterial isolates (IAT P4F9 and E.1b) that increased rice dry shoot biomass by up to 83% in co-cultivation assays performed with different durations of time (7 and 12 days). Metabolic profiles of the plants co-cultivated with these isolates and controls (without bacteria and non-promoter bacteria—1003-S-C1) were investigated via 1H nuclear magnetic resonance. The analysis identified metabolites (e.g., amino acids, sugars, and others) with differential abundance between treatments that might play a role in metabolic pathways, such as protein synthesis, signaling, photosynthesis, energy metabolism, and nitrogen assimilation, involved in rice growth promotion. Interestingly, VOCs from IAT P4F9 displayed a more consistent promotion activity and were also able to increase rice dry shoot biomass in vivo. Molecular identification by sequencing the 16S rRNA gene of the isolates IAT P4F9 and E.1b showed a higher identity with Serratia and Achromobacter species, respectively. Lastly, volatilomes of these and two other non-promoter bacteria (1003-S-C1 and Escherichia coli DH5α) were evaluated through headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry. Compounds belonging to different chemical classes, such as benzenoids, ketones, alcohols, sulfide, alkanes, and pyrazines, were identified. One of these VOCs, nonan-2-one, was validated in vitro as a bioactive compound capable of promoting rice growth. Although further analyses are necessary to properly elucidate the molecular mechanisms, our results suggest that these two bacterial isolates are potential candidates as sources for bioproducts, contributing to a more sustainable agriculture.
Omicron COVID-19 variant outcomes and vaccination in non-severe and non-critical patients at admission

The clinical data of patients infected with the Omicron variant virus in Zhejiang Province from January to 14 May 2022 were collected retrospectively. We analyzed the differences in symptoms, clinical categories of COVID-19, length of hospital stay, and time for clearance of Omicron variant viral RNA in the sputum among the groups receiving a different number of vaccine doses. The analysis showed that as the number of vaccine doses increased, the frequency of clinical symptoms, such as fever and fatigue, decreased and the frequency of patients with moderate infections gradually decreased. At the same time, the length of hospital stay was significantly shortened. Based on the multivariate analysis, one vaccine dose [odds ratio (OR): 0.21, 95% confidence interval (CI): 0.08–0.56, p = 0.002], two vaccine doses (OR: 0.54, 95% CI: 0.33–0.88, p = 0.013), and three vaccine doses (OR: 0.40, 95% CI: 0.24–0.64, p < 0.001) shortened the length of hospitalization than those with no vaccination. The persistence of the virus in the sputum was significantly shortened with one vaccine dose (OR: 0.36, 95% CI: 0.15–0.89, p = 0.027), two vaccine doses (OR: 0.46, 95% CI: 0.27–0.78, p = 0.004), and three vaccine doses (OR: 0.38, 95% CI: 0.22–0.64, p < 0.001) than those with no vaccination. Therefore, we concluded that vaccination was an effective way to protect people against infection with the Omicron variant. Indeed, on the premise of the current routine recommendation of vaccination, three vaccines were necessary for people to be protected against the Omicron variant.
Fecal identification markers impact the feline fecal microbiota

Fecal diagnostics are a mainstay of feline medicine, and fecal identification markers help to distinguish individuals in a multi-cat environment. However, the impact of identification markers on the fecal microbiota are unknown. Given the increased interest in using microbiota endpoints to inform diagnosis and treatment, the objective of this study was to examine the effects of orally supplemented glitter and crayon shavings on the feline fecal microbiota (amplicon sequencing of 16S rRNA gene V4 region). Fecal samples were collected daily from six adult cats that were randomized to receive oral supplementation with either glitter or crayon for two weeks, with a two-week washout before receiving the second marker. No adverse effects in response to marker supplementation were seen for any cat, and both markers were readily identifiable in the feces. Microbiota analysis revealed idiosyncratic responses to fecal markers, where changes in community structure in response to glitter or crayon could not be readily discerned. Given these findings, it is not recommended to administered glitter or crayon shavings as a fecal marker when microbiome endpoints are used, however their clinical use with other diagnostics should still be considered.
An Approach to Telerobotic Manipulations

This article introduces three areas of study : 1 telefunctioning; 2 a control method for producing telefunctioning ; and 3 an analysis of human-robot interaction when telefunctioning governs the system behavior. Telefunctioning facilitates the maneuvering of loads by creating a perpetual sense of the load dynamics for the operator. Telefunctioning is defined as a robotic manipulation method in which the dynamic behaviors of the slave robot and the master robot are functions of each other; these junctions are the designer's choice and depend on the application. (In a subclass of telefunctioning currently referred to as telepresence, these functions are specified as unity so that the master and slave variables (e.g., position, velocity) are dynamically equal. ) To produce telefunctioning, this work determines a minimum number of functions relating the robots' variables, and then develops a control architecture which guarantees that the defined functions govern the dynamic behavior of the closed-loop system. The stability of the closed-loop system (i.e., master robot, slave robot, human, and the load being manipulated) is analyzed and sufficient conditions for stability are derived.
Editorial: Immune barrier, viral sanctuaries, and sexual transmission in the male reproductive system

COPYRIGHT © 2023 Zhang, Lu, Cheng and Han. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Editorial PUBLISHED 07 February 2023 DOI 10.3389/fimmu.2023. 1139520