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Abstract Intestinal fibrosis is the primary cause of disability in patients with Crohn’s disease (CD), yet effective therapeutic strategies are currently lacking. Here, we report a multiomics analysis of gut microbiota and fecal/blood metabolites of 278 CD patients and 28 healthy controls, identifying characteristic alterations in gut microbiota (e.g., Lachnospiraceae, Ruminococcaceae, Muribaculaceae, Saccharimonadales) and metabolites (e.g., L-aspartic acid, glutamine, ethylmethylacetic acid) in moderate-severe intestinal fibrosis. By integrating multiomics data with magnetic resonance enterography features, putative links between microbial metabolites and intestinal fibrosis-associated morphological alterations were established. These potential associations were mediated by specific combinations of amino acids (e.g., L-aspartic acid), primary bile acids, and glutamine. Finally, we provided causal evidence that L-aspartic acid aggravated intestinal fibrosis both in vitro and in vivo. Overall, we offer a biologically plausible explanation for the hypothesis that gut microbiota and its metabolites promote intestinal fibrosis in CD while also identifying potential targets for therapeutic trials.

Abstract Porcine Epidemic Diarrhea Virus (PEDV) poses a significant threat to neonatal piglets, particularly due to the limited efficacy of existing vaccines and the scarcity of efficacious therapeutic drugs. Gegen Qinlian Decoction (GQD) has been employed for over two millennia in treating infectious diarrhea. Nonetheless, further scrutiny is required to improve the drug’s efficacy and elucidate its underlying mechanisms of action. In this study, a modified GQD (MGQD) was developed and demonstrated its capacity to inhibit the replication of PEDV. Animal trials indicated that MGQD effectively alleviated pathological damage in immune tissues and modulated T-lymphocyte subsets. The integration of network analysis with UHPLC-MS/MS facilitated the identification of active ingredients within MGQD and elucidated the molecular mechanisms underlying its therapeutic effects against PEDV infections. In vitro studies revealed that MGQD significantly impeded PEDV proliferation in IPEC-J2 cells, promoting cellular growth via virucidal activity, inhibition of viral attachment, and disruption of viral biosynthesis. Furthermore, MGQD treatment led to increased expression levels of IFN-α, IFN-β, and IFN-λ3, while concurrently decreasing the expression of TNF-α, thereby enhancing resistance to PEDV infection in IPEC-J2 cells. In conclusion, our findings suggest that MGQD holds promise as a novel antiviral agent for the treatment of PEDV infections.

Abstract Background Teat number is a vital reproductive trait in sows, crucial for providing immunity and nutrition to piglets during lactation. However, “missing heritability” in Single Nucleotide Polymorphism (SNP)-based Genome-Wide Association Studies (GWAS) has led to an increasing focus on structural variations in the genetic analysis of complex biological traits. Results In this study, we generated a comprehensive CNV map in a population of French Yorkshire pigs (n = 644) and identified 429 CNVRs. Notably, 44% (189 CNVRs) of these were detected for the first time. Subsequently, we conducted GWAS for teat number in the French Yorkshire pig population using both 80K chip and its imputed data, as well as a GWAS analysis based on CNV regions (CNVR). Interestingly, 80K chip GWAS identified two SNPs located on Sus scrofa chromosome 5 (SSC5) that were simultaneously associated with Total Teat Number (TTN), Left Teat Number (LTN), and Right Teat Number (RTN). The leading SNP (WU_10.2_5_76130558) explained 3.33%, 2.69%, and 2.67% of the phenotypic variance for TTN, LTN, and RTN, respectively. Moreover, through imputed GWAS, we successfully identified 30 genetic variants associated with TTN located within the 73.22 -73.30 Mb region on SSC5. The two SNPs identified in the 80K chip GWAS were also located in this region. In addition, CNVR-based GWAS revealed three significant CNVRs associated with TTN. Finally, through gene annotation, we pinpointed two candidate genes, TRIM66 and PRICKLE1, which are related to diverse processes such as breast cancer and abnormal vertebral development. Conclusions Our research provides an in-depth analysis of the complex genetic structure underlying teat number, contributing to the genetic enhancement of sows with improved reproductive performance and, ultimately, bolstering the economic benefits of swine production enterprises.

Abstract Hybrid mapping is a powerful approach to efficiently identify and characterize genes regulated through mechanisms in cis. In this study, using reciprocal crosses of the phenotypically divergent Duroc and Lulai pig breeds, we perform a comprehensive multi-omic characterization of regulatory variation across the brain, liver, muscle, and placenta through four developmental stages. We produce one of the largest multi-omic datasets in pigs to date, including 16 whole genome sequenced individuals, as well as 48 whole genome bisulfite sequencing, 168 ATAC-Seq and 168 RNA-Seq samples. We develop a read count-based method to reliably assess allele-specific methylation, chromatin accessibility, and RNA expression. We show that tissue specificity was much stronger than developmental stage specificity in all of DNA methylation, chromatin accessibility, and gene expression. We identify 573 genes showing allele specific expression, including those influenced by parent-of-origin as well as allele genotype effects. We integrate methylation, chromatin accessibility, and gene expression data to show that allele specific expression can be explained in great part by allele specific methylation and/or chromatin accessibility. This study provides a comprehensive characterization of regulatory variation across multiple tissues and developmental stages in pigs.

Abstract Background Nurses face disproportionately high rates of suicidal ideation and non-suicidal self-injury (NSSI). The role of workplace violence, loneliness, and depressive symptoms in exacerbating these issues is poorly understood. This study aims to explore these relationships to inform interventions for improving nurses’ mental health. Methods A cross-sectional study involving 1,774 Chinese nurse staff selected through convenient sampling methods was conducted. Workplace violence, depressive symptoms, and loneliness were assessed using the Chinese versions of the Workplace Violence Scale (WVS), the 9-item Patient Health Questionnaire (PHQ-9), and a three-item loneliness scale, respectively. Participants completed self-report questionnaires anonymously to ensure adherence to ethical standards. Statistical analysis utilized structural equation modeling (SEM) to examine the intricate relationships among variables, thereby elucidating the impact of workplace violence, loneliness, and depressive symptoms on nurses’ suicidal ideation/NSSI outcomes. Results Nurse staff 165 (7.8%) were reported different level of suicidal ideation and 139 (7.8%) participants were reported different level of NSSI. And the final model of workplace violence on suicidal ideation shown a good model fit index (CMIN/DF = 3.482 NFI = 0.969 CFI = 0.977 TLI = 0.955 RFI = 0.938, RMSEA = 0.037 SRMR = 0.035). The pathway of workplace violence to loneliness (β = 0.163, P

Abstract Background Nurses frequently endure elevated levels of psychosocial stress, which often correlates with an increased suicide risk. This study aimed to investigate the impact of latent psychosocial characteristic patterns on suicidal ideation and non-suicidal self-injury among nursing staff. Method Participants were recruited from the Dehong districts of Yunnan province, China, between July 11th and July 26th, 2022. Subgroups were identified using variables linked to suicidal ideation and non-suicidal self-injury, including perceived cognitive deficits, anxiety symptoms, depressive symptoms, resilience, social support, childhood trauma, loneliness, and sleep quality. Measurement tools included the Perceived Deficit Questionnaire-5-item (PDQ-5), Generalized Anxiety Disorder-7 items (GAD-7), Patient Health Questionnaire (PHQ-9), Connor-Davidson Resilience Scale-10 items (CD-RISC10), Multidimensional Scale of Perceived Social Support (MSPSS), Childhood Trauma Questionnaire-Short Form (CTQ-SF), Three-Item Loneliness Scale, and a single-item sleep quality scale. Results Latent profile analysis (LPA) revealed four distinct psychosocial characteristic patterns: “class 1,” “class 2,” “class 3,” and “class 4.” Compared to class 2, individuals in class 1 had a sixfold increased risk of suicidal ideation (OR = 6.59, 95%CI = 4.42–9.81) and a fivefold increased risk of non-suicidal self-injury (OR = 5.13, 95%CI = 3.38–7.78). Similarly, class 4 individuals had twice the risk of suicidal ideation (OR = 2.13, 95%CI = 1.25–3.62) and non-suicidal self-injury (OR = 2.13, 95%CI = 1.25–3.65) compared to class 2. Conversely, class 3 individuals had a lower risk of suicidal ideation (OR = 0.21, 95%CI = 0.11–0.42) and non-suicidal self-injury (OR = 0.15, 95%CI = 0.07–0.36) than class 2. Additionally, divorced/other marital status individuals had a higher risk of suicidal ideation (OR = 2.34, 95%CI = 1.02–5.35) and non-suicidal self-injury (OR = 2.58, 95%CI = 1.01–6.65) compared to married individuals, while unmarried individuals had a lower risk of suicidal ideation (OR = 0.58, 95%CI = 0.37–0.91). Conclusions The study identified eight important psychosocial factors divided into four latent pattern classes. Individuals in “class 1” and “class 4” were more likely to have a higher risk of suicidal ideation and non-suicidal self-injury, while those in “class 3” were more likely to have a lower risk of both outcomes. It is suggested that further research should focus on “class 1” and “class 4” for targeted intervention.

Background: Transmural healing (TH) has emerged as a potential treatment goal for Crohn’s disease (CD). However, further research is needed to confirm its benefits and risk factors associated with TH remain unclear. Objectives: We aimed to assess the value of TH based on magnetic resonance enterography (MRE) in Chinese CD patients regarding the long-term outcomes and its associated factors. Design: Retrospective, observational cohort study. Methods: Patients with CD diagnosed by colonoscopy and MRE examination between 2015 and 2022 were included. All patients were evaluated with endoscopy together with MRE within 6–12 months after baseline and followed up for at least 6 months after evaluation. The primary endpoint was the occurrence of major outcomes during the follow-up, including drug escalation, hospitalization, and surgery. The cumulative probabilities of major outcomes were calculated using Kaplan–Meier survival curves. Logistic regression analyses were used to predict TH within 6–12 months after baseline. Results: A total of 175 patients were included in the study. Of these, 69 (39.4%) patients achieved mucosal healing (MH), but only 34 (19.4%) of them achieved TH. The median follow-up duration was 17.4 months (interquartile range, 11.6–25.5), and major outcomes occurred in 58.3% of patients. A lower occurrence rate of major outcomes was noted in patients who achieved TH than in those who achieved MH only ( p = 0.012). The baseline lymphocyte/C-reactive protein ratio (LCR) [odds ratio (OR), 1.60; 95% confidence interval (CI), 1.02–2.50; p = 0.039] and bowel wall thickness (BWT) (OR, 0.72; 95% CI, 0.59–0.90; p = 0.003) were independent predictors associated with TH. According to multivariate Cox regression analysis, low LCR [hazard ratio (HR), 2.34; 95% CI, 1.51–3.64; p

Abstract Purpose To develop a CT-based radiomics model combining with VAT and bowel features to improve the predictive efficacy of IFX therapy on the basis of bowel model. Methods This retrospective study included 231 CD patients (training cohort, n = 112; internal validation cohort, n = 48; external validation cohort, n = 71) from two tertiary centers. Machine-learning VAT model and bowel model were developed separately to identify CD patients with primary nonresponse to IFX. A comprehensive model incorporating VAT and bowel radiomics features was further established to verify whether CT features extracted from VAT would improve the predictive efficacy of bowel model. Area under the curve (AUC) and decision curve analysis were used to compare the prediction performance. Clinical utility was assessed by integrated differentiation improvement (IDI). Results VAT model and bowel model exhibited comparable performance for identifying patients with primary nonresponse in both internal (AUC: VAT model vs bowel model, 0.737 (95% CI, 0.590–0.854) vs. 0.832 (95% CI, 0.750–0.896)) and external validation cohort [AUC: VAT model vs. bowel model, 0.714 (95% CI, 0.595–0.815) vs. 0.799 (95% CI, 0.687–0.885)), exhibiting a relatively good net benefit. The comprehensive model incorporating VAT into bowel model yielded a satisfactory predictive efficacy in both internal (AUC, 0.840 (95% CI, 0.706–0.930)) and external validation cohort (AUC, 0.833 (95% CI, 0.726–0.911)), significantly better than bowel alone (IDI = 4.2% and 3.7% in internal and external validation cohorts, both p < 0.05). Conclusion VAT has an effect on IFX treatment response. It improves the performance for identification of CD patients at high risk of primary nonresponse to IFX therapy with selected features from RM. Critical relevance statement Our radiomics model (RM) for VAT-bowel analysis captured the pathophysiological changes occurring in VAT and whole bowel lesion, which could help to identify CD patients who would not response to infliximab at the beginning of therapy. Key points • Radiomics signatures with VAT and bowel alone or in combination predicting infliximab efficacy. • VAT features contribute to the prediction of IFX treatment efficacy. • Comprehensive model improved the performance compared with the bowel model alone. Graphical abstract

The poor timeliness of routing has always been an urgent problem in practical operator networks, especially in situations with large-scale networks and multiple network domains. In this article, a pruning idea of routing integrated with Dijkstra’s shortest path searching is utilized to accelerate the process of routing in large-scale multi-domain elastic optical networks (EONs). The layered-graph approach is adopted in the spectrum allocation stage. To this end, an efficient heuristic algorithm is proposed, called “Branch-and-Bound based Routing and Layered Graph based Spectrum Allocation algorithm (BBR-LGSA)”, which is an integrated RSA algorithm. Notably, the significant reduction in algorithm time complexity is not only reflected in the pruning method used in the routing stage but also in the construction of auxiliary graphs during the spectrum allocation stage utilizing the Branch-and-Bound method. Simulation results show that the proposed BBR-LGSA significantly reduces the average running time by nearly 78% with higher spectrum utilization in large-scale multi-domain EONs, compared with benchmark algorithms. In addition, the impact of key parameters on performance comparisons of different algorithms is evaluated.

Abstract Aiming at the problem of crosstalk between microstrip lines, a method of reducing crosstalk by using cross‐shape resonators (CSR) structures is proposed. On the premise of not changing the spacing of microstrip lines, this method adds CSR structures between the coupled microstrip lines to increase the capacitive coupling and thus to suppress the far‐end crosstalk. Based on the analysis of the equivalent circuit of CSR structure, the parameters simulation and verification are carried out by ADS and HFSS software. Through HFSS simulation and physical test of the designed CSR structure, the results show that: the CSR structure can significantly reduce the far‐end crosstalk by about 15 dB in the frequency of 0–10 GHz, and the maximum can reach 43 dB. Compared with 3W crosstalk reduction method and rectangular‐shape resonators crosstalk reduction method, the crosstalk reduction effect is improved.

To solve the problem that how users choose access points in cell-free massive multiple-input multiple-output (CF-mMIMO) network, a prioritized access strategy for poorer users based on channel coefficient ranking was proposed.First, users were evaluated and ranked for their channel quality and stability after channel sensing, and suitable access points were selected in sequence according to the order of the channel state information.Second, considering issues such as users' energy consumption and data security, a federal learning framework was used to enhance user's data privacy and security.Meanwhile, an alternating optimization variables algorithm based on energy consumption optimization was proposed to optimize the multi-dimensional variables, for the purpose of minimizing the total energy consumption of the system.Simulation results show that compared with the traditional user-centric in massive MIMO, the proposed access strategy can improve the average uplink reachable rate of users by 20%, and the uplink rate of users with poor channels can be double improved; in terms of energy consumption optimization, the total energy consumption can be reduced by much more than 50% after optimization.

A new class of bio-composites was developed by utilizing four kinds of lignocellulosic biomass fiber (bagasse, bamboo, rice husk, and rice straw) as filling fibers. Poly-β-hydroxybutyrate (PHB) and poly(butylene succinate) (PBS) in a mixture ratio of 7:3 were used as matrix materials with hot-press molding. The performance of the resulting composites was evaluated by compositional analyses, mechanical analysis, Fourier transform infrared (FTIR) spectroscopy, thermogravimetry, and morphological analysis. The interfacial adhesion, thermal stability, and comprehensive mechanical properties of the alkali treated bamboo/PHB/PBS composite were highest among the four bio-composites. The bending strength, tensile strength, and impact strength for alkali treated bamboo/PHB/PBS composite was 19.82 MPa, 12.97 MPa, and 4.30 kJ/m2, respectively. The thermal stability for NaOH modified bamboo/PHB/PBS composite was slightly superior to the other three composites, with the initial pyrolysis temperature of 248 °C, moderate pyrolysis speed, and the amount of pyrolysis residue (5.81%). The results showed the suitability of biomass fiber and biodegradable polymer for producing environmentally friendly composite materials.

Alkali-treated bagasse fiber was used as a process variable for optimization of the properties of polybutylene succinate/poly(lactic acid)-based biocomposites using Box-Behnken design (BBD) and response surface methodology (RSM). The optimum conditions for three factors, i.e., NaOH-treated bagasse fiber (0.55 to 1.65 g), polybutylene succinate (1.1 to 2.3 g), and poly(lactic acid) (2.2 to 3.4 g) on the bending strength of biocomposite were investigated. The optimum combination was 0.91 g of NaOH-treated bagasse fiber, 1.14 g of polybutylene succinate, and 3.10 g of poly(lactic acid). The bending strength for NaOH-treated bagasse fiber/polybutylene succinate/ poly(lactic acid) composite was 27.0 MPa, which was 26.0% higher than native bagasse fiber-based composite. The composites were also characterized by thermogravimetric analysis, mechanical testing, Fourier transform infrared, scanning electron microscopy, water absorption, and contact angle tests. Results demonstrated that the bending strength, impact strength, and tensile strength of alkali treated bagasse fiber-based biocomposite increased by 26.0%, 15.5%, and 23.3%, separately, compared with native bagasse-based composite after sequential homogenization, compounding, and hot pressing. The hydrophobicity for alkali-treated bagasse fiber/PBS/PLA was also improved. Thus, NaOH-treated biomass materials/biodegradable polymer was judged to be suitable for preparing green composite materials.

Abstract Background Owing to different social background factor in Yunnan-Myanmar Chinese border region, stressful working environment may lead to extra psychological burden among nurse staff in China. However, the prevalence of workplace violence and its effect on psychological characteristics among nurse staff are still unclear. This study aims to explore the effect of workplace violence against psychological health among nurse staff from Yunnan-Myanmar Chinese border region. Methods A cross-sectional survey was conducted among 18 local governmental hospitals in Dehong districts. Participants were 1,774 nurses. Psychosocial characteristics were screened by sleep quality, the 9-item Patient Health Questionnaire for depressive symptoms, the generalized anxiety disorder-7 for anxiety symptoms, the Connor Davidson Resilience Scale – 10 item for resilience, the multidimensional scale of perceived social support for social support, the Chinese version of Work place Violence Scale for workplace violence. Propensity score matching and multivariate linear regression were applied to analyze the data. Results The nurse staff with workplace violence have a higher risk of bad sleep quality (b = -0.883, 95%CI = [-1.171, -0.595]), anxiety symptoms (b = 2.531, 95%CI = [2.031, 3.031]) and depressive symptoms (b = 3.227, 95%CI = [2.635, 3.819]), loneliness (b = 0.683, 95%CI = [0.503, 0.863]), perceived cognitive deficits (b = 1.629, 95%CI = [1.131, 2.127]), poor resilience (b = -2.012, 95%CI = [-2.963, -1.061]), and poor social support (b = -5.659, 95%CI = [-7.307, -4.011]). Conclusions Preventing workplace violence can improve mental health outcomes significantly among nurse staff, including loneliness, perceived cognitive deficits, anxiety symptoms, depressive symptoms, sleep quality, resilience and social support.

Abstract Phased array weather radar (PAWR) for hazardous weather phenomena observation has attracted considerable attention. In this paper, a PAWR simulator for volume scan mode modeling is designed and the volume scan model has been used to evaluate the one-dimensional (1D) PAWR beam pattern characteristics and the effect of scanning mode. Firstly, the three-dimensional weather field has been generated by interpolating spectral moment parameters from next-generation weather radar data (NEXRAD), including reflectivity factor, radial velocity and spectral width. Secondly, based on the parameters of radar system and volume scanning modeling, the relationship between phased array beam characteristics and volume scanning mode is established, which can fully simulate the scanning process of phased array radar at different elevation cuts. Finally, according to the concept of 'scattering center', the time series of each range bin during volume scanning is reconstructed. The performance of the PAWR simulator has been evaluated under typical weather scenario, such as tornadoes and the results indicated the effectiveness and superiority over traditional Doppler weather radar. Simulation examples are provided to illustrate the flexibility and practicability of the PAWR simulator, and the factors affecting its PAWR detection performance are evaluated. The research results represent that reducing the number of linear array elements and increasing the array angle will further exacerbate the degradation of data quality.

Abstract Accurate server traffic prediction can help enterprises formulate network resource allocation strategies in advance and reduce the probability of network congestion. Traditional prediction models ignore the unique data characteristics of server traffic that can be used to optimize the prediction model, so they often cannot meet the long-term and high-precision prediction required by server traffic prediction. To solve this problem, this paper establishes a hybrid model ARIMA-LSTM-CF, which combines the advantages of linear and nonlinear models, as well as the periodic fluctuation characteristics of server traffic data obtained from banks. In addition, this paper also uses the optimized K-means clustering method to extract the traffic data of workdays and non workdays. The results show that the new hybrid model performs better than the single ARIMA and LSTM models in predicting the long-term trend of server traffic. RMSE (root mean square error) and MAE (mean absolute error) are reduced by 50%. R2 score index reached 0.64. The results show that the model can effectively extract the data characteristics of server traffic data, and the model has accurate and stable long-term prediction ability.

Objective: Older people are often considered asexual, but sex is still important for older adults. So, this review aimed to analyze relevant studies on the sexual life of older adults to clarify factors, and provide a basis for their quality of sexual life. Method: A scoping review was performed according to Arksey and O’Malley’s framwork, aiming to identify eligible research studies in PubMed, Web of Science, CINAHL, and PsycINFO, Cochrane Library, and Scopus databases. Peer-reviewed articles published in Chinese or English language from January 2012 to April 2022 were retrieved. All of identified studies were screened, extracted, and analyzed independently by two researchers. Result: A total of 7,374 studies were retrieved, and 13 eligible studies were finally included. The factors affect the sexual quality of life in older adults that included physiological, sociocultural, and health factors and being affected by marital relationships and a lack of relevant knowledge. Conclusion: The factors that affect the quality of old people’s sex life interact and influence each other. Medical and health professionals can assist with the improvement of sexual health.

Background: Low-dose lipopolysaccharide (LPS) protects against early brain injury (EBI) after subarachnoid hemorrhage (SAH). However, the mechanism underlying the neuroprotective roles of low-dose LPS remain largely undefined. Methods: A SAH mice model was established and the pathological changes of brain were evaluated by wet-dry weight method, HE and Nissl staining, and blood-brain barrier (BBB) permeability assay. Cell apoptosis and inflammation were monitored by TUNEL, flow cytometry and ELISA assays. qRT-PCR, immunofluorescence and Western blot were used to detect the expression of microglial polarization-related or oxidative stress-associated markers. Bioinformatics analysis, luciferase and ChIP assays were employed to detect the direct association between FOXO1 and IL-10 promoter. The ubiquitination of FOXO1 in the in vitro SAH model was detected by co-IP. Results: Low-dose LPS alleviated SAH-induced neurological dysfunction, brain edema, BBB disruption, damage in the hippocampus, neuronal apoptosis and inflammation via modulating microglial M1/M2 polarization by IL-10/IL-10R1 signaling. Mechanistic studies showed that FOXO1 acted as a transcriptional activator of IL-10. USP19 mediated the deubiquitination of FOXO1 to activate IL-10/IL-10R1 signaling, thereby regulating microglial M1/M2 polarization. Functional experiments revealed that low-dose LPS upregulated USP19 to modulate microglial M1/M2 polarization via FOXO1/IL-10/IL-10R1 signaling in SAH mice. Conclusion: Low-dose LPS protected against EBI after SAH by modulating microglial M1/M2 polarization via USP19/FOXO1/IL-10/IL-10R1 signaling.

High geo-stresses and complicated geological conditions are two typical characteristics in the traffic tunnel of the tailrace surge chamber at the Shuangjiangkou hydropower station, Southwest China. Rock failures such as spalling and rockbursts induced by excavation were encountered repeatedly in this tunnel. To evaluate the stability of rock mass of the tunnel during excavation, the high-precision microseismic (MS) monitoring technology was introduced. Through analysing the tempo-spatial distribution characteristics of MS events, the main damage areas and their influencing factors were studied. The rock fracturing mechanisms of MS clusters were revealed based on the source parameters of MS events. A three-dimensional model was established to obtain the stress and deformation characteristics of rock mass. Results indicated that the MS events mainly occurred between July 10 and 26, 2017 and the energy release was higher during this period. The main damage areas of rock mass were located at the Stake K0 + 110m–K0 + 170m. Weak structures and multi-cavern effect aggravated rock mass damage subjected to excavation-unloading. Tensile failure was the main fracturing type of rock mass. Rock mass damage influenced by weak structures was especially prominent. The numerical simulation results are consistent with the MS monitoring results. The results could provide significant references for safety evaluation and construction design of similar tunnels.

The objective of this research was to prepare an optimized bio-composite for packaging based on alkali-treated banana pseudo-stem fiber (BPSF), PBAT, and PLA using response surface methodology (RSM). The effects of three factors, i.e., alkali-treated BPSF (0.8 to 2.4 g), PBAT (0.75 to 2.25 g), and PLA (1.6 to 3.2 g) on two dependent variables, i.e., bending strength and tensile strength of bio-composite, were investigated. Box-Behnken design (BBD) provided the combination for an optimum composite, which was 1.15 g of alkali-treated BPSF, 2.09 g of PBAT, and 2.66 g of PLA, respectively. The bending strength and tensile strength for alkali-treated BPSF/PBAT/PLA composite were 32.62 MPa and 30.91 MPa, which was 20.50% and 16.51% higher than native BPSF/PBAT/PLA composite. The bio-composite prepared using the optimized results was further characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetry, scanning electron microscopy (SEM), mechanical testing, contact angles, and water absorption tests. Analyses showed that alkali-treatment could improve the adhesion and compatibility of BPSF in the polymer matrix. These outcomes were associated with the use of treated-BPSF for better mechanical strength and lower hygroscopicity. This result demonstrated that alkali-treated agricultural residue and degradable polymer could be used to prepare composite materials for green packaging application.

Abstract In this paper, an intelligent reflecting surface (IRS) assisted cooperative non‐orthogonal multiple access and mobile edge computing (NOMA‐MEC) system is proposed, where a base station sends signals to users through the virtue of the IRS. When the direct links between the base station and the user are blocked, the offloading tasks will be refracted to the near‐end user through the IRS and forwarded to the remote user, where the near‐end user is equipped with an MEC server working at full duplex or half duplex mode. To evaluate the potential performance of IRS aided cooperative NOMA‐MEC, new closed‐form expressions of the offloading outage probability is deduced for a pair of users. The asymptotic expressions of offloading outage probability are provided in the high signal‐to‐noise ratio regime. Simulation results are presented to substantiate the analyses and demonstrate that: (i) The offloading outage behaviors of IRS‐aided cooperative NOMA‐MEC systems are superior to that of NOMA‐MEC without IRS and IRS‐aided OMA‐MEC; (ii) As the value of parameter Q increases, the IRS‐aided NOMA‐MEC system is capable of achieving the enhanced offloading outage performance; (iii) By comparing with NOMA‐MEC without IRS and IRS‐aided OMA‐MEC, the energy efficiency and system throughput of IRS‐aided NOMA‐MEC has obvious advantages in delay‐limited transmission mode.

Winter wheat is one of the major food crops in China, and timely and effective early-season identification of winter wheat is crucial for crop yield estimation and food security. However, traditional winter wheat mapping is based on post-season identification, which has a lag and relies heavily on sample data. Early-season identification of winter wheat faces the main difficulties of weak remote sensing response of the vegetation signal at the early growth stage, difficulty of acquiring sample data on winter wheat in the current season in real time, interference of crops in the same period, and limited image resolution. In this study, an early-season refined mapping method with winter wheat phenology information as priori knowledge is developed based on the Google Earth Engine cloud platform by using Sentinel-2 time series data as the main data source; these data are automated and highly interpretable. The normalized differential phenology index (NDPI) is adopted to enhance the weak vegetation signal at the early growth stage of winter wheat, and two winter wheat phenology feature enhancement indices based on NDPI, namely, wheat phenology differential index (WPDI) and normalized differential wheat phenology index (NDWPI) are developed. To address the issue of “ different objects with the same spectra characteristics” between winter wheat and garlic, a plastic mulched index (PMI) is established through quantitative spectral analysis based on the differences in early planting patterns between winter wheat and garlic. The identification accuracy of the method is 82.64% and 88.76% in the early overwintering and regreening periods, respectively, These results were consistent with official statistics (R2 = 0.96 and 0.98, respectively). Generalization analysis demonstrated the spatiotemporal transferability of the method across different years and regions. In conclusion, the proposed methodology can obtain highly precise spatial distribution and planting area information of winter wheat 4_6 months before harvest. It provides theoretical and methodological guidance for early crop identification and has good scientific research and application value.

In the research on sustainable mining and environmental preservation, understanding the dynamic behaviour of rock formations in deep, high-stress mining environments is essential. In order to acquire the laws of rock dynamic disaster generation from mining in deep, high-stress environments, this research adopts a multistage and multi-cycle triaxial cyclic loading test to obtain the stress–strain curves and macroscopic deformation characteristics of hard sandstone under different surrounding pressures. The results show that the cumulative damage displacement of hard sandstone under cyclic loading at a certain stress level for the first 3–4 cycles is half of the total damage displacement at that cycle stage, and its peak volumetric strain will increase with the increase. The elastic energy density ratio and dissipation energy density ratio of hard sandstone under cyclic loading show a sinusoidal fluctuation trend, and the fluctuation gradually decreases with the increase in the number of cycles and the increase in the cyclic stress level. Under the cyclic loading of different surrounding pressures, the hard sandstone shows brittle damage characteristics, where the damage form is mainly shear damage with a small amount of tensile damage in low surrounding pressure and the damage form is mainly shear damage, tensile damage, and local compression damage in high surrounding pressure. The study reveals the deformation and damage law, energy evolution, and dissipation characteristics of high-strength hard sandstone. It is essential for the development of mining strategies that minimize the impact on the environment, reduce the dynamic hazards generated by mining, and maximize the efficiency of resource extraction

Abstract Background Obesity is very common in patients with schizophrenia. We aimed to evaluate the influencing factors of obesity in community patients with deficit schizophrenia, to provide implication for schizophrenia management in community. Methods We selected patients with deficit schizophrenia who lived in 10 communities in our city from March 1 to June 30, 2021. The characteristics of included schizophrenia patients were evaluated and analyzed. Pearson correlation analysis was conducted to evaluate the obesity and related characteristics. Logistic regression analyses were conducted to assess the risk factors of obesity in patients with schizophrenia. Results A total of 284 patients with schizophrenia were included, the incidence of obesity in patients with schizophrenia was 56.70%. gender (r = 0.619), waist circumference (r = 0.644), BMI (r = 0.891), diabetes (r = 0.698), FG (r = 0.582), triglyceride (r = 0.618), HDL-C (r = −0.644), LDL-C (r = 0.583), apolipoprotein B (r = 0.595), and PANSS score (r = 0.813) were all correlated with the obesity in patients with schizophrenia (all p

Background: Transmural healing (TH) is a potential therapeutic goal of Crohn’s disease (CD) and is associated with better clinical outcomes. However, few studies have described early TH and its predictors. Objectives: We aimed to evaluate early TH and its predictors using magnetic resonance enterography (MRE) in patients with CD receiving ustekinumab (UST). Design: This was a retrospective observational study. Methods: Patients with active CD treated with UST and their intestinal segments with bowel wall thickness (BWT) ⩽ 3 mm at baseline were included. Clinical characteristics, laboratory indicators, endoscopic manifestations, and MRE indices were evaluated at baseline and week 26 (W26) of the therapy. The following MRE parameters were assessed: BWT, edema, apparent diffusion coefficient (ADC), Clermont score, Magnetic Resonance Index of Activity score, fat stranding, comb sign, and stricture. TH was defined as BWT ⩽ 3 mm without any signs of inflammation (i.e., ulceration, edema, diffusion-weighted hyperintensity, and increased contrast enhancement) at W26. Results: The study included 37 patients with 106 intestinal segments (including 15 proximal small intestines, 33 terminal ilea, and 58 colons). Clinical features, laboratory indicators, endoscopic results, and MRE parameters at W26 were significantly improved after UST treatment in both patient-based and intestinal segment-based analysis. Seven (18.9%) patients and 26 (24.5%) intestinal segments achieved TH at W26. Baseline BWT [odds ratio (OR) = 0.287, 95% confidence interval (CI), 0.090–0.918, p = 0.035] and ADC (OR = 2.997, 95% CI, 1.009–8.908, p = 0.048) predict TH of patients at W26. Baseline ADC (OR = 2.857, 95% CI, 1.285–6.349, p = 0.010) and presence of stenosis (OR = 0.196, 95% CI, 0.052–0.735, p = 0.016) were associated with TH of segments at W26. Conclusion: Early TH assessed by MRE was observed in nearly one-fifth of patients with CD and intestinal segments after UST treatment for 26 weeks. Baseline MRE indices such as BWT and presence of stenosis might negatively predict TH, while ADC might positively predict early TH.

BackgroundMoyamoya disease (MMD) is a rare cerebrovascular disorder with unknown etiology. The underlying pathophysiological mechanism of moyamoya disease remains to be elucidated, but recent studies have increasingly highlighted that abnormal immune response may be a potential trigger for MMD. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) are inflammatory markers that can reflect the immune-inflammation state of the disease.ObjectiveThe purpose of this study was to investigate SII, NLR, and PLR in patients with moyamoya disease.MethodsA total of 154 patients with moyamoya disease (MMD group) and 321 age- and sex-matched healthy subjects (control group) were included in this retrospective case–control study. Complete blood count parameters were assayed to calculate the SII, NLR, and PLR values.ResultsThe SII, NLR, and PLR values in the moyamoya disease group were significantly higher than those in the control group [754 ± 499 vs. 411 ± 205 (P < 0.001), 2.83 ± 1.98 vs. 1.81 ± 0.72 (P < 0.001), and 152 ± 64 vs. 120 ± 42 (P < 0.001), respectively]. The SII in the medium-moyamoya vessels of moyamoya disease was higher than that in the high-moyamoya vessels and low-moyamoya vessels (P = 0.005). Using the receiver operating characteristic (ROC) curve analysis to predict MMD, the highest area under the curve (AUC) was determined for SII (0.76 for SII, 0.69 for NLR, and 0.66 for PLR).ConclusionBased on the results of this study, patients with moyamoya disease admitted for inpatient care due to acute or chronic stroke have significantly higher SII, NLR, and PLR when compared to blood samples drawn from completely healthy controls in a non-emergent outpatient setting. While the findings may suggest that inflammation plays a role in moyamoya disease, further studies are warranted to corroborate such an association. In the middle stage of moyamoya disease, there may be a more intense imbalance of immune inflammation. Further studies are needed to determine whether the SII index contributes to the diagnosis or serves as a potential marker of an inflammatory response in patients with moyamoya disease.

Summary: Background: Visceral adipose tissue (VAT) is involved in the pathogenesis of Crohn's disease (CD). However, data describing its effects on CD progression remain scarce. We developed and validated a VAT-radiomics model (RM) using computed tomography (CT) images to predict disease progression in patients with CD and compared it with a subcutaneous adipose tissue (SAT)-RM. Methods: This retrospective study included 256 patients with CD (training, n = 156; test, n = 100) who underwent baseline CT examinations from June 19, 2015 to June 14, 2020 at three tertiary referral centres (The First Affiliated Hospital of Sun Yat-Sen University, The First Affiliated Hospital of Shantou University Medical College, and The First People's Hospital of Foshan City) in China. Disease progression referred to the development of penetrating or stricturing diseases or the requirement for CD-related surgeries during follow-up. A total of 1130 radiomics features were extracted from VAT on CT in the training cohort, and a machine-learning–based VAT-RM was developed to predict disease progression using selected reproducible features and validated in an external test cohort. Using the same modeling methodology, a SAT-RM was developed and compared with the VAT-RM. Findings: The VAT-RM exhibited satisfactory performance for predicting disease progression in total test cohort (the area under the ROC curve [AUC] = 0.850, 95% confidence Interval [CI] 0.764–0.913, P

Changes in grassland soil organic carbon stock (SOCS) may significantly affect the regional climate and carbon cycle of terrestrial ecosystems. However, how the impact of climate factors on SOCS and the dominant climate factors are regulated by the area scale of grasslands remains unclear. To understand the scale effects of climate on SOCS and how to accurately estimate SOCS at different scales, three area scales were defined by extending grassland types on the basis of meadow, typical and desert grasslands (Scale I (average area 37.22 × 104 km2) included each of these three types of grasslands, Scale II (average area 74.45 × 104 km2) was achieved by a pairwise combination of these three types of grasslands. Scale III (area 111.67 × 104 km2) was an aggregate of these three types of grasslands), the relationship between climate factors (i.e., mean annual precipitation, mean annual temperature, annual maximum temperature, annual minimum temperature, mean annual ground temperature, mean annual humidity, annual sunshine duration, annual maximum depth of accumulated snow, and the number of snow-covered days) and SOCS at the three scales were explored in the grasslands of northern China. Our results indicated that the total SOCS in grasslands at the three scales was ordered as desert grassland

Abstract Aiming at the problem of far‐end crosstalk between microstrip lines, a method to improve crosstalk by using the TL‐shaped defective microstrip structure (DMS) is proposed. This method optimizes the ratio of the capacitive coupling and the inductive coupling between coupled microstrip lines by etching TL‐shaped DMSs on the microstrip lines, reducing the strength of electromagnetic coupling, thereby achieving an improvement in crosstalk. The quantitative equivalent model, S‐parameters, and full‐wave EM simulations are used to analyze the frequency response of the TL‐shaped DMS and crosstalk between the microstrip lines. The results of High Frequency Structure Simulator software simulation and sample texts show that the TL‐shaped DMS can effectively improve the far‐end crosstalk while ensuring the transmission of signals on the microstrip line. In the frequency range of 0–8 GHz, the far‐end crosstalk can be improved by about 11 dB, and the maximum can be improved by 42 dB. Compared with other DMSs, the TL‐shaped DMS has better crosstalk improvement effect and practical application potential.

Abstract Background While anti-tumor necrosis factor alpha (TNF-α) therapy has been proven effective in inflammatory bowel disease (IBD), approximately 40% of patients lose the response. Transmembrane TNF-α (mTNF-α) expression in the intestinal mucosa is correlated with therapeutic efficacy, and quantification of mTNF-α expression is significant for predicting response. However, conventional intravenous application of microbubbles is unable to assess mTNF-α expression in intestinal mucosa. Herein, we proposed intracolic ultrasound molecular imaging with TNF-α-targeted microbubbles (MBTNF-α) to quantitatively detect mTNF-α expression in the intestinal mucosa. Methods MBTNF-α was synthesized via a biotin–streptavidin bridging method. TNF-α-targeted ultrasound imaging was performed by intracolic application of MBTNF-α to detect mTNF-α expression in surgical specimens from a murine model and patients with IBD. Linear regression analyses were performed to confirm the accuracy of quantitative targeted ultrasound imaging. Results On quantitative TNF-α-targeted ultrasound images, a greater signal intensity was observed in the mouse colons with colitis ([1.96 ± 0.45] × 106 a.u.) compared to that of the controls ([0.56 ± 0.21] × 106 a.u., P

Background: While the grading of intestinal fibrosis is closely related to the therapeutic strategy of patients with Crohn’s disease (CD), it has not yet been well resolved. Mesenteric abnormalities are inextricably linked to intestinal fibrosis. Objectives: We aimed to establish an optimal model for assessing intestinal fibrosis using computed tomography enterography (CTE) and clinical markers. Design: A total of 174 patients with CD between January 2014 and June 2020 were included in this retrospective multicentre study. Methods: All patients underwent CTE within 3 months prior to surgery. Intestinal fibrosis was pathologically scored as non-mild or moderate-to-severe. Selected imaging of the intestinal walls and mesentery and/or clinical factors were used to develop the diagnostic models. The area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the discrimination performance of the models. A decision curve analysis was performed to evaluate the clinical usefulness of the models. Results: One-, two-, and three-variable models were identified as possible diagnostic models. Model 1 [mesenteric creeping fat index (MCFI)], Model 2 (mesenteric oedema and MCFI), and Model 3 (mesenteric oedema, MCFI, and disease duration) were established. The AUCs of Model 1 in training and test cohorts 1 and 2 were 0.799, 0.859, and 0.693, respectively; Model 2 was 0.851, 0.833, and 0.757, respectively; and Model 3 was 0.832, 0.821, and 0.850, respectively. We did not observe any significant difference in diagnostic performance between the training and total test cohorts in any model (all p > 0.05). The decision curves showed that Model 3 had the highest net clinical benefit in test cohort 2. The nomogram of this optimal model was constructed by considering the favourable and robust performance of Model 3. Conclusion: A nomogram integrating mesenteric abnormalities on CTE with a clinical marker was optimal for differentiating between non-mild and moderate-to-severe fibrosis in patients with CD.

In this paper, we study the probabilistic Gel’fand N,δ-width of multivariate Sobolev spaces MW2rTd with mixed derivative that are equipped with Gaussian measure μ in LqTd. The sharp asymptotic estimates are determined by employing the discretization method.

Body conformation is the most direct production index, which can fully reflect pig growth status and is closely related to critical economic traits. In this study, we conducted a genome-wide association study (GWAS) on body conformation traits in a population of 1518 Duroc × (Landrace × Yorkshire) commercial pigs. These traits included body length (BL), body height (BH), chest circumference (CC), abdominal circumference (AC), and waist circumference (WC). Both the mixed linear model (MLM) and fixed and random model circulating probability unification (FarmCPU) approaches were employed for the analysis. Our findings revealed 60 significant single nucleotide polymorphisms (SNPs) associated with these body conformation traits in the crossbred pig population. Specifically, sixteen SNPs were significantly associated with BL, three SNPs with BH, thirteen SNPs with CC, twelve SNPs with AC, and sixteen SNPs with WC. Moreover, we identified several promising candidate genes located within the genomic regions associated with body conformation traits. These candidate genes include INTS10, KIRREL3, SOX21, BMP2, MAP4K3, SOD3, FAM160B1, ATL2, SPRED2, SEC16B, and RASAL2. Furthermore, our analysis revealed a novel significant quantitative trait locus (QTL) on SSC7 specifically associated with waist circumference, spanning an 84 kb interval. Overall, the identification of these significant SNPs and potential candidate genes in crossbred commercial pigs enhances our understanding of the genetic basis underlying body conformation traits. Additionally, these findings provide valuable genetic resources for pig breeding programs.

In this article, we give the sharp bounds of probabilistic Kolmogorov N,δ-widths and probabilistic linear N,δ-widths of the multivariate Sobolev space W2A with common smoothness on a Sq norm equipped with the Gaussian measure μ, where A⊂Rd is a finite set. And we obtain the sharp bounds of average width from the results of the probabilistic widths. These results develop the theory of approximation of functions and play important roles in the research of related approximation algorithms for Sobolev spaces.

The number of teats is a crucial reproductive trait with significant economic implications on maternal capacity and litter size. Consequently, improving this trait is essential to facilitate genetic selection for increased litter size. In this study, we performed a genome-wide association study (GWAS) of the number of teats in a three-way crossbred commercial Duroc × (Landrace × Yorkshire) (DLY) pig population comprising 1518 animals genotyped with the 50K BeadChip. Our analysis identified crucial quantitative trait loci (QTL) for the number of teats, containing the ABCD4 and VRTN genes on porcine chromosome 7. Our results establish SNP variants of ABCD4 and VRTN as new molecular markers for improving the number of teats in DLY pigs. Furthermore, the most significant noteworthy single nucleotide polymorphism (SNP) (7_97568284) was identified within the ABCD4 gene, exhibiting a significant association with the total teat number traits. This SNP accounted for a substantial proportion of the genetic variance, explaining 6.64% of the observed variation. These findings reveal a novel gene on SSC7 for the number of teats and provide a deeper understanding of the genetic mechanisms underlying reproductive traits.

Abstract Background HIV/AIDS has transformed into a chronic controllable but not yet curable infectious disease as other chronic diseases to some extent. The additional of so called fourth 90% that included the improved health-related quality of life (HRQoL) for people living with HIV (PLWHIV) required solutions beyond antiretroviral therapy and viral load suppression. This study will explore the role of personality, social economic and prevention strategy effection on HRQoL among people living with HIV/AIDS. Methods A cross-sectional study was conducted among PLWHIV aged more than 16 years old in the 10 municipalities in Yunnan Province, China from October 2019 to May 2020, enrolling total 1997 participants. Individual-level HRQoL data were measured by 12-item Short Form Health Survey (SF-12) and EuroQol Five Dimensions Questionnaire (EQ-5D-5L). We assembled municipal-level data about social economic from Yunnan Statistical Yearbook in 2020 and strategy practice information from the self-evaluation system. We used the principal component analysis to build the social economic and strategy effect on each area respectively and one-way ANOVA was used to perform univariate analysis to identify the predictors with significant differences. Finally we used multi-level model (MLM) to explore the personality, social economic and strategy effects in health-related quality of life among PLWHIV. Results The global score for quality of life measured using EQ-5D-5L had an estimated mean score (standard deviation, SD) of 0.901 ± 0.146. The HRQoL score measured using PCS-12 had an estimated mean score (SD) of 46.62 ± 8.55. The mean MCS-12 score (SD) was estimated to be 47.80 ± 9.71. The area-level predictors explained a proportion of 13.6–17.2% for the between-area variation of the HRQoL scores, regardless of the total HRQoL, physical component and mental component. The impacts of stigma (P

Creeping fat is a specific feature of Crohn’s disease (CD) and is characterized by mesenteric fat wrapping around the intestine. It highly correlates with intestinal transmural inflammation, muscular hypertrophy, fibrosis, and stricture formation. However, the pathogenesis of creeping fat remains unclear. Molecular crosstalk exists between mesenteric fat and the intestine. Indeed, creeping fat contains different types of cells, including adipocytes and immune cells. These cell types can produce various cytokines, fatty acids, and growth factors, which affect the mesenteric fat function and modulate intestinal inflammation and immunity. Moreover, adipocyte progenitors can produce extracellular matrix to adapt to fat expansion. Previous studies have shown that fat fibrosis is an important feature of adipose tissue malfunction and exists in other diseases, including metabolic disorders, cancer, atrial fibrillation, and osteoarthritis. Furthermore, histological sections of CD showed fibrosis in the creeping fat. However, the role of fibrosis in the mesenteric fat of CD is not well understood. In this review, we summarized the possible mechanisms of fat fibrosis and its impact on other diseases. More specifically, we illustrated the role of various cells (adipocyte progenitors, macrophages, mast cells, and group 1 innate lymphoid cells) and molecules (including hypoxia-inducible factor 1-alpha, transforming growth factor-beta, platelet-derived growth factor, and peroxisome proliferator-activated receptor-gamma) in the pathogenesis of fat fibrosis in other diseases to understand the role of creeping fat fibrosis in CD pathogenesis. Future research will provide key information to decipher the role of fat fibrosis in creeping fat formation and intestinal damage, thereby helping us identify novel targets for the diagnosis and treatment of CD.

Potential immune responses resulting from exposure to metal oxide nanoparticles (MeONPs) have been the subject of intensive discussion in the last decade. Despite the extensive use of MeONPs in several applications, their toxic effects on immune cells have rarely been predicted in silico because of the complexity of immune responses and the complicated properties of MeONPs. In the present study, machine learning (ML) methods coupled with high-throughput in vitro bioassays were used to develop models for predicting the toxicity of MeONPs in immune cells. An ML model with a high prediction accuracy (97% and 96% in the training and test sets, respectively) was constructed by resolving the class imbalance problem in training and applying an ensembled algorithm. Further, to verify the model, MeONPs outside the scope of the datasets were selected to examine their cytotoxicity experimentally. The model was validated against independent MeONPs, with an accuracy of 91%. ML methods coupled with intracellular imaging revealed that the toxic ions released in the lysosome were an important determinant of toxicity in immune cells. Furthermore, ζ-potential, electronegativity, and size are crucial factors for predicting nanotoxicity. We believe the established modeling framework will provide useful insights for designing and applying safe nanoparticles and facilitating decision-making for environmental and health protection.

Abstract Dispersal ability is important for the introduction, establishment, and spread of alien plant species. Therefore, determination of the geographical distribution of the dispersal ability of such species, and the relationship between dispersal ability and socio-climatic factors are essential to elucidate the invasion strategies of the alien plant species. Analytic hierarchy process and inventory, risk rank, and dispersal mode data available on Chinese alien plant species were used to determine their dispersal ability, the geographical distribution thereof, and the relationship between socio-climatic factors and dispersal ability. High-risk alien plant species had a higher natural dispersal ability (or several natural dispersal modes) but a lower anthropogenic dispersal ability (or few anthropogenic dispersal modes) than low-risk alien plant species. The geographical distribution of the dispersal ability of the alien plant species showed an inverse relationship with species density. Alien plant species with low dispersal ability (i.e., with fewer dispersal modes and distribution in the southeast) showed a tendency to adapt to environments with mild climates, while those with high dispersal ability (i.e., with more disposal nodes and distribution in the northwest) showed a tendency to adapt to harsh environments. It is essential for land managers and policy makers to understand the geographical distribution of the dispersal ability of alien plant species and their socio-climatic control factors to formulate strategies to control the natural and anthropogenic dispersal of such plants.

Industrial Internet mobile edge computing (MEC) deploys edge servers near base stations to bring computing resources to the edge of industrial networks to meet the energy-saving requirements of Industrial Internet terminal devices. This paper considers a wireless MEC system in an intelligent factory that has multiple edge servers and mobile smart industrial terminal devices. In this paper, the terminal device has the choice of either offloading the task in whole or in part to the edge server, or performing it locally. Through combined optimization of the task offload ratio, number of subcarriers, transmission power, and computing frequency, the system can achieve minimum total energy consumption. A computing offloading and resource allocation approach that combines federated learning (FL) and deep reinforcement learning (DRL) is suggested to address the optimization problem. According to the simulation results, the proposed algorithm displays fast convergence. Compared with baseline algorithms, this algorithm has significant advantages in optimizing the performance of energy consumption.

Percolation experiments were conducted on coal samples with various fracture lengths and inclination angles under different stress conditions using a gravity-loaded rock percolation test device. The goals of these experiments are (1) to improve the technology for protecting water resources while mining coal and (2) to enhance the research on how the size effects of fracture affect seepage. A three-dimensional seepage model was constructed using COMSOL numerical simulation software for larger fracture lengths ranging from 1 to 30 m to investigate the seepage pattern under the coupling of fracture roughness, fracture width, and other factors. Multiple regression analysis was used to investigate the effects of different factors on seepage from large and small fractures independently. The results show that, under laboratory conditions, for fracture lengths 10–70 mm (small length), permeability increases non-linearly with an increase in fracture length, and the overall increase is approximately 1.8 times. Whereas, for fracture lengths of 1–30 m (large length) in the simulation, permeability decreases and then increases with an increase in fracture length, and the overall change is approximately 0.03 times. The permeability varies in three stages (1–8 m obvious change, 8–23 m stabilization, 23–30 m stability) under different fracture lengths, widths, and roughness conditions. Acritical size was found to exist. The effect of fracture length on large length fracture seepage and small length fracture seepage was further verified by parameter sensitivity. The results of this study further reveal the mechanism of fracture seepage under coupling of fracture geometry size stress.

This paper analyzed the performance of an ambient-backscatter-(AmBC)-assisted non-orthogonal multiple access (NOMA) system, where a backscatter device (BD) broadcasts its signal to numerous users. More specifically, the realistic assumptions of imperfect successive interference cancellation (ipSIC) and residual hardware impairments (RHIs) for AmBC–NOMA systems were taken into consideration. We further derived the closed-form and asymptotic expressions of outage probability for the BD and the d-th user. Based on the asymptotic expressions, the diversity orders of the BD and the d-th user were obtained in the high SNR regime. Furthermore, throughput and energy efficiency are further discussed for AmBC-assisted orthogonal multiple access (OMA) systems in the delay-limited transmission model. The numerical results revealed that: (i) AmBC–NOMA systems have the ability to achieve better outage behavior than AmBC–OMA; (ii) due to the existence of the backscatter link, the error floors of outage probability for the BD and the d-th user appear at a high signal-to-noise ratio; (iii) AmBC–NOMA systems are able to achieve higher energy efficiency and throughput than AmBC–OMA systems.

This paper focuses on reducing execution delays of dynamic computing tasks in UAV-assisted fault-prone mobile edge computing (FP-MEC) systems, which combine mobile edge computing (MEC) and network function virtualization (NFV) technologies. FP-MEC is suited to meet Industrial Internet (IIN) requirements such as data privacy, low latency, and low-cost industrial scalability in specific scenarios. However, the reliability of virtual network functions (VNFs) deployed on UAVs could impact system performance. Thus, this paper proposes the dynamic task scheduling optimization algorithm (DTSOA) based on deep reinforcement learning (DRL) for resource allocation design. The formulated execution delay optimization problem is described as an integer linear programming problem and it is an NP-hard problem. To overcome the intractable problem, this paper discretizes it into a series of single-time slot optimization problems. Furthermore, the experimental rigor is improved by constructing a real-time server state update system to calculate the real-time server load situation and crash probability. Theoretical analysis and experiments show that the DTSOA has better application prospects than Q-learning and the recent search method (RSM), and it is closer to the traversal search method (TSM).

An air-to-ground downlink communication network consisting of a reconfigurable intelligent surface (RIS) and unmanned aerial vehicle (UAV) is proposed. In conjunction with a resource allocation strategy, the system’s energy efficiency is improved. Specifically, the UAV equipped with a RIS starts from an initial location, and an energy-efficient unmanned aerial vehicle deployment (EEUD) algorithm is deployed to jointly optimize the UAV trajectory, RIS phase shifts, and BS transmit power, so as to obtain a quasi-optimal deployment location and hence improve the energy efficiency. First, the RIS phase shifts are optimized by using the block coordinate descent (BCD) algorithm to deal with the nonconvex inequality constraint, and then integrated with the Dinkelbach algorithm to address the resource allocation problem of the BS transmit power. Finally, for solving the UAV trajectory optimization problem, the complex objective function is transformed into a convex function, and the optimal UAV flight trajectory is obtained. Our simulation results show that the quasi-optimal deployment location obtained by the EEUD algorithm is superior to other deployment strategies in energy efficiency. Moreover, the instantaneous energy efficiency of the UAVs along the trajectory of searching the deployment location is better than other comparison trajectories. Furthermore, the RIS-assisted multi-user air-to-ground communication network can offer up to 145% improvement in energy efficiency over the traditional amplify-and-forward (AF) relay.

BackgroundTelemedicine plays an important role in the management of inflammatory bowel disease (IBD), particularly during a pandemic such as COVID-19. However, the effectiveness and efficiency of telemedicine in managing IBD are unclear. ObjectiveThis systematic review and meta-analysis aimed to compare the impact of telemedicine with that of standard care on the management of IBD. MethodsWe systematically searched the PubMed, Cochrane Library, EMBASE, Web of Science, and Scopus databases on April 22, 2020. Randomized controlled trials comparing telemedicine with standard care in patients with IBD were included, while conference abstracts, letters, reviews, laboratory studies, and case reports were excluded. The IBD-specific quality of life (QoL), disease activity, and remission rate in patients with IBD were assessed as primary outcomes, and the number of in-person clinic visits per patient, patient satisfaction, psychological outcome, and medication adherence were assessed as secondary outcomes. Review Manage 5.3 and Stata 15.1 were used for data analysis. ResultsA total of 17 randomized controlled trials (2571 participants) were included in this meta-analysis. The telemedicine group had higher IBD-specific QoL than the standard care group (standard mean difference 0.18, 95% CI 0.01 to 0.34; P.03). The number of clinic visits per patient in the telemedicine group was significantly lower than that in the standard care group (standard mean difference −0.71, 95% CI −1.07 to −0.36; P

Abstract In this paper, a non-orthogonal multiple access (NOMA)-based mobile edge computing (MEC) system is proposed, where paired users (the mth user and the nth user) offload tasks to the MEC server under imperfect channel state information (ipCSI) condition. To evaluate the effect on performance under ipCSI condition in NOMA-MEC system, this study derives new exact and asymptotic expressions of the offloading outage probability for two users under ipCSI and perfect channel state information (pCSI) conditions. On the basis of the theoretical derivation, the diversity orders of the nth user under ipCSI and pCSI conditions are zero and n, respectively, while those for the distant user are all zeros. In addition, we also investigate the system throughput and energy efficiency of NOMA-MEC in delay-limited transmission. Numerical results show that (1) the offloading outage behaviors of NOMA-MEC are better than those of time division multiple address (TDMA), (2) the offloading outage performance of paired users under ipCSI is worse than that under pCSI, and (3) the NOMA-MEC system achieves higher throughput and energy efficiency than does the TDMA-MEC system.

Abstract Hydraulic fracturing forms complex hydraulic fracture networks (HFNs) in shale reservoirs and significantly improves the permeability of shale reservoirs. Although rock brittleness is a major factor in determining whether a shale reservoir can be fractured, the relationship between HFNs and rock brittleness remains unclear. To investigate this relationship in a shale reservoir with bedding planes, this paper presents a series of hydraulic fracturing simulations based on a hydromechanically coupled discrete element model. In addition, we analyzed the sensitivity of the difference in rock brittleness to bedding‐plane angle and density. The parameters used in the model were verified by comparing the simulated results with experimental results and a theoretical equation. The results showed that breakdown pressure and injection pressure increased with increasing rock brittleness. The tensile hydraulic fracture of a shale reservoir (THFSR) was always the most abundant type of hydraulic fracture (HF)—almost 2.5 times the sum of the other three types of HFs. The distribution of areas with higher fluid pressure deviated from the direction of the maximum principal stress when the angle between the bedding plane and maximum principal stress directions was large. Upon increasing this bedding‐plane angle, the breakdown pressure and rock brittleness index first decreased and then increased. However, regardless of bedding angle, the relative proportions of the various types of HFs remained essentially constant, and the seepage area expanded in the direction of the maximum principal stress. Increased bedding‐plane density resulted in a gradual increase in the total number of HFs, with significantly fewer of the THFSR type, and the large seepage areas connected with each other. This study thus provides useful information for preparing strategies for hydraulic fracturing.

Abstract In Fucun Coal Mine, the average spacing between the 3upper coal seam (UCS) and 3lower coal seam (LCS) is only 6 m. In the process of mining upper coal, the lower roadway (LR), which is 60 m away from upper pillar, becomes unstable. In order to control the surrounding rock of lower roadway, a physical model experiment and a 3D numerical calculation were performed in this study. The results of physical similarity simulation experiment show that mining of longwall face in UCS will lead to fracturing of key layers at a high elevation (KLHE) far away from the coal seam. The expanded goaf area caused large‐scale fracturing and rotation of the KLHE, which resulted in significant strata pressure behavior in LR. The numerical calculation results show that the LR should be within 19 m of the coal pillar. Finally, a plan which includes a proper location and a supporting system was proposed. The feasibility of the proposed plan is verified by an industrial application.

An unmanned aerial vehicle (UAV) swarm together with a large-scale heterogeneous Internet of Things (IoT) network consisting of macrocells and energy-constrained IoT transmitters (IoT-Ts) is investigated. The UAVs are utilized as flying robot swarms that intelligently transfer energy to the energy-constrained IoT-Ts on the ground. Each IoT-T has an associated IoT device (IoT-D) that is placed at a fixed distance in a random direction. The transmission probability of the energy-constrained IoT-Ts is derived by considering one-slot charging and two-slot charging according to three dimensional (3D) locations, respectively. The coverage probability of each type of IoT-D is investigated. The energy efficiency is derived by considering the transmission power of the active IoT-Ts and the effect of the association biasing factor, and the energy efficiency is also maximized by deploying the optimal density of IoT-Ts. Simulation results are examined to validate the accuracy of our theoretical analysis. Results illustrate the insightful effects of the network parameters, and the helpful guidelines for practical UAV swarms and IoT system design.

Frequency diverse array (FDA) radar have attracted great interests due to the range-angle-dependent transmit beampattern which is different from phased array radar providing only angle-dependent transmit beampattern. In this paper, we firstly proposed a receiver processing strategy based on signal separation method which eliminates the need for employing a bank of bandpass filters at the receiver of FDA radar. In the proposed separation scheme, the received signal at each receiving element was separated into M channels, where M represents the transmitting element number. After time-invariant processing of the separated signal, the angle and range were estimated by two-stage multiple signal classification (MUSIC) algorithm. For velocity estimation, we proposed a novel unambiguous velocity estimation algorithm. This novel algorithm was implemented to calculate the phase of each element and then the differential phase within the adjacent elements is calculated. The velocity of the target was estimated by the differential phase. This mechanism for extending the Nyquist velocity range is that the differential phase of the two adjacent channels has a much smaller variance than the individual channel phase estimated. All estimated parameter performance is verified by analyzing the Cramér-Rao lower bound (CRLB) and the root mean square errors (RMSE).