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Abstract Background Understanding factors associated with antiretroviral treatment (ART) adherence is crucial for ART success among people living with HIV (PLHIV) in the “test and treat” era. Multiple psychosocial factors tend to coexist and have a syndemic effect on ART adherence. We aimed to explore factors associated with ART adherence and the syndemic effect of multiple psychosocial factors on ART adherence among PLHIV newly starting ART in Guangdong Province, China. Methods Newly diagnosed PLHIV from six cities in Guangdong Province were recruited between May 2018 and June 2019, and then followed up from May 2019 to August 2020. Baseline and follow-up data were collected from a questionnaire and the national HIV surveillance system, the follow-up data of which were analyzed in this study. A Center for Adherence Support Evaluation (CASE) index > 10 points was defined as optimal ART adherence, which was measured via participants’ self-reported adherence during follow-up survey. Multivariable logistic regression was used to identify factors associated with ART adherence. Exploratory factor analysis (EFA) and multi-order latent variable structural equation modeling (SEM) were performed to explore the syndemic effect of multiple psychosocial factors on ART adherence. Results A total of 734 (68.53%) follow-up participants were finally included in this study among the 1071 baseline participants, of whom 91.28% (670/734) had self-reported optimal ART adherence. Unemployment (aOR = 1.75, 95%CI: 1.01–3.02), no medication reminder (aOR = 2.28, 95%CI: 1.09–4.74), low medication self-efficacy (aOR = 2.28, 95%CI: 1.27–4.10), low social cohesion (aOR = 1.82, 95%CI: 1.03–3.19), no social participation (aOR = 5.65, 95%CI: 1.71–18.63), and ART side effects (aOR = 0.46, 95%CI: 0.26–0.81) were barriers to optimal ART adherence. The EFA and second-order latent variable SEM showed a linear relationship (standardized coefficient = 0.43, P

Abstract Background Among people living with HIV (PLHIV) on antiretroviral therapy (ART), the mortality of immunological non-responders (INRs) is higher than that of immunological responders (IRs). However, factors associated with immunological non-response following ART are not well documented. Methods We obtained data for HIV patients from the National Free Antiretroviral Treatment Program database in China. Patients were grouped into IRs (CD4 cell count ≥ 350 cells/μl after 24 months’ treatment), immunological incomplete responders (ICRs) (200–350 cells/μl) and INRs (

Sodium ion storage remains relatively unexplored in comparison with well-understood lithium ion storage mechanisms. Here, the authors systematically investigate the surface-redox sodium ion storage properties of anatase titanium dioxide, which delivers excellent rate capability, cycling stability and low overpotentials.

Peritoneal fibrosis (PF) is the main reason leading to declining efficiency and ultrafiltration failure of peritoneum, which restricts the application of peritoneal dialysis (PD). We aimed to investigate the effects and mechanisms of miR-122-5p on the PF. Sprague-Dawley (SD) rats were infused with glucose-based standard PD fluid to establish PF model. HE staining was performed to evaluate the extent of PF. Real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) and fluorescence in situ hybridization (FISH) were performed to measure the expression level of miR-122-5p. Western blot was used to test the expression of transforming growth factor (TGF)-β1, platelet-derived growth factor (PDGF)-A, Fibronectin 1 (FN1), extracellular matrix protein 1 (ECM1), Smad5, α-smooth muscle actin (SMA), collagen type 1(COL-1), Vimentin, E-Cadherin, Wnt1, β-catenin, p-β-catenin, c-Myc, c-Jun, and Cyclin D1. Immunohistochemistry (IHC) staining was used to detect type I collagen alpha 1 (Col1α1), α-SMA, and E-Cadherin expression. We found PF was glucose concentration-dependently enhanced in peritoneum of PD rat. The PD rats showed increased miR-122-5p and decreased Smad5 expression. MiR-122-5p silencing improved PF and epithelial–mesenchymal transition (EMT) process in PD rats. MiR-122-5p silencing attenuated the activity of the Wnt/β-catenin signaling pathway. Importantly, dual-luciferase reporter assay showed Smad5 was a target gene of miR-122-5p. Smad5 overexpression significantly reversed the increases of PF and EMT progression induced by miR-122-5p overexpression. Moreover, miR-122-5p mimic activated Wnt/β-catenin activity, which was blocked by Smad5 overexpression. Overall, present results demonstrated that miR-122-5p overexpression showed a deterioration effect on PD-related PF by targeting Smad5 to activate Wnt/β-catenin pathway.

Pseudocapacitive materials with surface‐redox reactions are capable of realizing high capacities at ultrahigh rates; however, it remains a challenge in the synthesis of active components with high surface area to boost surface‐redox sodiation but restrain side reactions. Herein, a two‐step, topochemical synthesis of 2D mesoporous TiN (2D‐meso‐TiN) with high surface area and rich mesoporosities is presented. It is demonstrated that the sodium‐ion storage mechanism of TiN anode is based on the existence of surficial titanium oxides via redox reactions between Ti4+ and Ti3+. The interconnected, highly conductive 2D‐meso‐TiN with high surface area largely increases the pseudocapacitive capacities, leading to a high capacity of 160/93 mAh g−1 at 0.1/10 A g−1, which is much higher than 2D‐TiN (120/72 mAh g−1) and commercial TiN nanoparticles (57/30 mAh g−1). The surface‐redox (de)sodiation undergoes no destruction of crystalline TiN, which enables high initial coulombic efficiency and long‐term cycles. Furthermore, a novel hybrid sodium‐ion capacitor consisting of 2D‐meso‐TiN anode and Na3V2(PO4)3 cathode is assembled without any presodiation treatments. The hybrid capacitor delivers both high energy density (94 Wh kg−1 at 64 W kg−1) and high power density (38 Wh kg−1 at 4.4 kW kg−1), as well as long cycling stability.

Abstract. Background. With the high prevalence of pre-treatment drug resistance (PDR) and the potential impact to the virological inhibition, the detection of PDR was particularly necessary. This study aimed to determine the prevalence of PDR in Guangdong, China, and its impact on antiretroviral therapy (ART) in treatment-naive HIV patients. Methods. A retrospective cohort study was conducted. A total of 1936 HIV-1–infected treatment-naive patients in the clinic of the infectious department, Guangzhou Eighth People’s Hospital, between August 2018 and December 2019 were assayed for PDR mutations before initiating ART. Patients with PDR mutations (PDR arm) were screened and compared with those without drug-resistant mutations (non-PDR arm). The rate of HIV-1 virologic failure (VF) and CD4+ T-cell counts of the 2 arms were compared at the 96th week after ART to evaluate the impact of PDR on the efficacy of ART. Results. Pretreatment drug resistance was detected in 125 cases (6.46%) from the 1936 enrolled participants, most of which were resistant to non-nucleoside reverse transcriptase inhibitors (64.00%, 80/125). One hundred and eight of 125 completed the follow-up of 96 weeks (PDR arm). In this cohort, 52 patients whose ART regimen containing the resistant drug were grouped as con-PDR arm, and the remaining 56 patients whose ART regimen did not contain the resistant drug were grouped as non- con-PDR arm. A total of 125 patients without PDR were randomly selected as the control group (non-PDR arm), 112 of whom had completed the 96-week follow-up. At the 96th week after ART initiation, 7 patients (6.5%, 7/108) in the PDR arm and 1 patient (0.9%, 1/112) in the non-PDR arm developed VF, exhibiting a significant difference (χ2 = 4.901, P = 0.029). Meanwhile, 3 patients (5.8%, 3/52) in the con-PDR arm developed VF; the rate was also higher than that in the non-PDR arm, but without a significant difference (χ2 = 3.549, P = 0.095). The CD4+ T-cell count in the non-PDR arm increased more than the PDR arm (386.6 vs. 319.1 cells/μL, t = 2.448, P = 0.015) or the con-PDR arm (386.6 vs. 325.1 cells/μL, t = 1.821, P = 0.070) at 12 weeks after ART. However, no significant differences were observed in the CD4+ T-cell count from the 24th week after ART onward. Conclusions. Pretreatment drug resistance was moderately prevalent in Guangdong, China, and could affect the antiretroviral efficacy during a 96-week observation period, indicating the need to closely monitor PDR before ART initiation.

Abstract Background Coinfection with hepatitis C virus (HCV) is common in human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) patients due to shared routes of transmission. We aimed to investigate the characteristics of HCV subgenotypes among HIV/HCV-coinfected patients in Guangdong and explore the molecular transmission networks and related risk factors for HCV strains. Methods Plasma samples were obtained from 356 HIV/HCV-coinfected patients for HCV NS5B region sequencing. A neighbor-joining phylogenetic tree was constructed to affirm HCV subgenotypes. The transmission networks based on maximum likelihood phylogenetic tree were determined by Cluster Picker, and visualized using Cytoscape 3.2.1. Results A total of 302 HCV NS5B sequences were successfully amplified and sequenced from the 356 plasma samples. A neighbor-joining phylogenetic tree based on the 302 NS5B sequences revealed the profile of HCV subgenotypes circulating among HIV/HCV coinfection patients in Guangdong. Two predominant strains were found to be 6a (58.28%, 176/302) and 1b (18.54%, 56/302), followed by 3a (10.93%, 33/302), 3b (6.95%, 21/302), 1a (3.64%, 11/302), 2a (0.99%, 3/302) and 6n (0.66%, 2/302). A molecular transmission network of five major HCV genotypes was constructed, with a clustering rate of 44.04%. The clustering rates of subgenotypes 1a, 3a, 3b, 1b, and 6a were 18.18% (2/11), 42.42%, 52.38%, 48.21%, and 44.89%, respectively. Multivariate logistic regression analysis showed no significant effects from sex, age, transmission route, geographical region, baseline CD4 + T cell count or subgenotype (P > 0.05), except marital status. Married or cohabiting people (compared with unmarried people) had more difficulty forming transmission networks. Conclusions In summary, this study, based on HCV NS5B subgenotypes, revealed the HCV subtype diversity and distribution among HIV/HCV-coinfected patients in Guangdong. Marital status inclined to be the factor influencing HCV transmission networks formation.

Due to the gradual depletion of shallow mineral resources at present, mines are now gradually entering the deep mining stage. To promote the safe and efficient green mining of deep coal resources and sustainable energy development, and to improve the production efficiency of paste filling mining, the research group has performed this study on the green filling mining technology and application of the working face. Taking working face 1241 (3) of the Xieqiao coal mine as the engineering background, the selection and experiment of filling materials were carried out, and the gangue, fly ash and cement produced by the Xieqiao coal mine were used as the filling aggregate. Next, the strength changes before and after paste filling was obtained by theoretical calculation. The strength at the early stage of filling was no less than 0.13 MPa, and that at the late stage of filling was no less than 2 MPa. Based on previous experimental research and theoretical calculation, the mixing pumping process of paste material ratio and the gangue crushing process were determined, and the filling pipeline system was designed. Then, based on the traditional coal mining technology, a filling mining technology of working face was designed and optimized. The field application of the research results shows that after the goaf of the working face had been filled, the ground pressure behavior of the coal wall of the working face was significantly weakened, and the stability of the surrounding rock of the working face was effectively controlled. Therefore, the method achieved good results, effectively controlled the stability of surrounding rock in goaf, and provided a theoretical basis and data support for realizing safe, efficient and green mining of deep coal resources. The results of this study bear important significance and application value.

Abstract Background Transmitted drug resistance (TDR) that affects the effectiveness of the first-line antiretroviral therapy (ART) regimen is becoming prevalent worldwide. However, its prevalence and transmission among HIV-1 treatment-naïve patients in Guangdong, China are rarely reported. We aimed to comprehensively analyze the prevalence of TDR and the transmission clusters of HIV-1 infected persons before ART in Guangdong. Methods The HIV-1 treatment-naïve patients were recruited between January 2018 and December 2018. The HIV-1 pol region was amplified by reverse transcriptional PCR and sequenced by sanger sequencing. Genotypes, surveillance drug resistance mutations (SDRMs) and TDR were analyzed. Genetic transmission clusters among patients were identified by pairwise Tamura-Nei 93 genetic distance, with a threshold of 0.015. Results A total of 2368 (97.17%) HIV-1 pol sequences were successfully amplified and sequenced from the enrolled 2437 patients. CRF07_BC (35.90%, 850/2368), CRF01_AE (35.56%, 842/2368) and CRF55_01B (10.30%, 244/2368) were the main HIV-1 genotypes circulating in Guangdong. Twenty-one SDRMs were identified among fifty-two drug-resistant sequences. The overall prevalence of TDR was 2.20% (52/2368). Among the 2368 patients who underwent sequencing, 8 (0.34%) had TDR to protease inhibitors (PIs), 22 (0.93%) to nucleoside reverse transcriptase inhibitors (NRTIs), and 23 (0.97%) to non-nucleoside reverse transcriptase inhibitors (NNRTIs). Two (0.08%) sequences showed dual-class resistance to both NRTIs and NNRTIs, and no sequences showed triple-class resistance. A total of 1066 (45.02%) sequences were segregated into 194 clusters, ranging from 2 to 414 sequences. In total, 15 (28.85%) of patients with TDR were included in 9 clusters; one cluster contained two TDR sequences with the K103N mutation was observed. Conclusions There is high HIV-1 genetic heterogeneity among patients in Guangdong. Although the overall prevalence of TDR is low, it is still necessary to remain vigilant regarding some important SDRMs.

Late testing and antiretroviral therapy (ART) prevailed among people living with HIV (PLHIV) and impacted the benefit of immediate ART. This study aimed to identify the benefit of the test-and-immediate-treat policy in China, the effect of immediate ART, and the influence of late testing and ART on the whole PLHIV in Guangdong Province, China. We designed two tendency analyses in aggregative form and two cohorts (surveillance and ART cohort) in individuals' perspectives based on the HIV/AIDS Comprehensive Response Information Management System. Two interrupted time series models were conducted for tendency analysis from 2009 to 2018 to explore the all-cause and short-term mortality decrease after the test-and-immediate-treat policy. A time-dependent Cox model was performed for the surveillance cohort from 1992 to 2018 and a joint model was utilized for the ART cohort to identify the effect of immediate ART and the influence of late testing and ART on death. The tendency analysis included 324,914 and 68,679 person-year for all-cause/short-term mortality. A total of 49,289 and 26,287 PLHIV were recruited in the surveillance and ART cohort with 5,557 and 459 deaths, respectively. The short-term mortality dropped from 4.69 cases/100 person-year in January 2009 to 0.35 cases/100 person-year in December 2018 (standardized rate). The all-cause mortality saw a decreasing trend from 1.46 cases/100 person-year in January 2009 to 0.14 cases/100 person-year in December 2018 (standardized rate). The tendency analysis showed a significant short-term mortality slope decrease after the test-and-immediate-treat policy (P = 0.024). From the surveillance cohort, late testing, in general, was a risk factor for all-cause mortality [hazard ratio (HR) = 1.330, 95% CI, 1.250, 1.416]. ART cohort showed higher hazards of all-cause mortality among PLHIV with no late testing, but late ART (HR = 1.690, 95% CI, 1.166, 2.451) and both the late testing and late ART (HR = 1.335, 95% CI, 1.042, 1.710). Immediate ART might decrease the hazard of all-cause death though it is insignificant (HR = 0.923, 95% CI: 0.755, 1.129) in the ART cohort. The test-and-immediate-test policy brought benefit to PLHIV. We should enlarge HIV testing using comprehensive approaches to decrease late testing and ART and increase the benefit of immediate ART.

Background: Integrase strand-transfer inhibitor (INSTI)-containing regimens have gradually been administered in Guangdong Province, China beginning in 2016, and INSTI-related drug resistance (DR) may occur and should be monitored among HIV-1-infected patients. Objective: To investigate the prevalence of INSTI-related resistance among HIV-1-infected individuals in Guangdong and provide evidence for the optimal administration of INSTIs. Methods: This study recruited 1208 HIV-1-infected patients (including 404 ART-naive and 804 ART-experienced patients) between June 2021 and April 2022. The entire integrase gene was amplified from blood plasma. Demographic and epidemiological information were collected. INSTI mutations and susceptibility were interpreted using the Stanford HIV Drug Resistance Database HIVdb program. Results: Of the 1208 enrolled individuals, 2.65% (32/1208) carried at least one INSTI major or accessory drug resistance mutation (DRM), with 1.49% (6/404) being from ART-naive individuals and 3.23% (26/804) from ART-experienced individuals. Among them, seven polymorphic major mutations were detected. Although no INSTI drug resistance was found among treatment-naive patients, seven ART-experienced patients (0.87%, 7/804) carried mutations conferring resistance to INSTIs. Conclusion: The overall prevalence of INSTI DRMs and DR was comparatively low among ART-naive and ART-treated populations in Guangdong; however, INSTI-related polymorphic mutations were observed. Surveillance should be reinforced before transfer to INSTI-containing regimens.

ObjectiveThis study aims to evaluate factors linked to the degree of disability among older adults and explore the relationship between the dietary inflammatory index (DII) and the degree of disability among older adults in southern China.MethodsConducted in two districts of Guangzhou, China, this cross-sectional study included 262 older adults with mild-to-severe disabilities. Disability levels were assessed using the “Assessment Standard for Long-term Care Disability” from the Medical Insurance Bureau, including Activities of Daily Living (ADL), Cognitive Ability, and Sensory Perception and Communication Skills (SPCS). Dietary data were collected via Food Frequency Questionnaire (FFQ) and used to calculate the DII and intake of nutrients (e.g., Protein, Carbohydrate and Fat). A multivariable ordinal logistic regression model was employed to analyze the influence of various factors and the DII on the degree of disability among older adults. Restricted cubic spline and sensitivity analyses were used to assess the association between DII and the degree of disability of the older adult population.ResultsInactivity (never exercising, OR = 8.48, 95% CI = 2.30–31.31) and reduced activity (formerly exercising, OR = 4.85, 95% CI = 1.39–16.96), stroke (OR = 2.78, 95% CI = 1.61–4.80), and dementia (OR = 2.69, 95% CI = 1.26–5.78) were significantly associated with increased disability. After adjusting for confounding factors, a higher DII was linked to a greater degree of disability, with the highest DII quartile showing a notably higher risk (OR = 2.61, 95% CI = 1.21–5.61) compared to the lowest quartile.ConclusionLack of exercise, previous exercise, stroke, and dementia are correlated with increased disability among older adults. Additionally, a higher DII is associated with a more severe degree of disability.

Uniform pore size is essential for molecular sieving in separation membranes. Traditional nanofiltration (NF) polymer membranes struggle with precise structure control due to random chain packing and rapid cross-linking, leading to varied pore sizes and poor molecular discrimination. Covalent organic frameworks (COFs) offer ordered porous structures for enhanced molecular selectivity. We synthesized composite COFs membranes with triphenylamine derivatives through interfacial polymerization, adjusting pore channel functional groups to achieve high water permeance and size-selective molecule retention. The TFB-OMe-TAPA COFs membrane demonstrated sharp rejection profiles, separating solutes of different molecular sizes. A three-stage cascade process was used to fractionate binary molecules with varying charges, achieving a separation factor of 26.7 for heterogeneous charge molecules. This work reveals the selectivity of COF membranes in near-molecular-weight systems, expanding their potential in molecular separations.

The origin of the background carriers in an undoped InAs/GaSb quantum well (QW) at temperatures between 40K and 300K has been investigated using conventional Hall measurements. It is found that the Hall coefficient changes its sign at around 200 K, indicating that both electrons and holes exist in the quantum well. The two-carrier Hall model is thus adopted to analyze the Hall data, which enables the temperature dependence of the carrier density to be obtained. It is found that considerable numbers of holes exist under low temperature conditions (<40 K) in the InAs/GaSb QW, and the hole density is one to two orders higher than that of the electrons within the experimental temperature range. The origin of these low temperature holes and the temperature-dependent behavior of the carrier density over the entire experimental temperature range are then discussed. [ABSTRACT FROM AUTHOR]

Background: Long non-coding RNA taurine-upregulated gene 1 (TUG1) is involved in various cellular processes, but its role in cerebral ischemia–reperfusion injury remains unclear. This study investigated TUG1’s role in regulating the nucleocytoplasmic shuttling of human antigen R (HuR), a key apoptosis regulator under ischemic conditions. Methods: CRISPR-Cas9 technology was used to generate TUG1 knockout Sprague Dawley rats to assess TUG1’s impact on ischemic injury. The infarct area and neuronal apoptosis were evaluated using TUNEL, hematoxylin and eosin (HE), and TTC staining, while behavioral functions were assessed. Immunofluorescence staining with confocal microscopy was employed to examine TUG1-mediated HuR translocation and expression changes in the apoptosis-related proteins COX-2 and Bax. Results: TUG1 knockout rats showed significantly reduced cerebral infarct areas, decreased neuronal apoptosis, and improved neurological functions compared to controls. Immunofluorescence staining revealed that HuR translocation from the nucleus to the cytoplasm was inhibited, leading to decreased COX-2 and Bax expression levels. Conclusions: TUG1 knockout reduces ischemic damage and neuronal apoptosis by inhibiting HuR nucleocytoplasmic shuttling, making TUG1 a potential therapeutic target for ischemic stroke.

Zinc finger proteins (ZFPs) are essential transcription factors in eukaryotes, particularly the extensively studied C2H2 family, which is known for its involvement in various biological processes. This research provides a thorough examination and analysis of the C2H2-ZFP gene family in Flammulina filiformis. Using bioinformatics tools, 58 FfC2H2-ZFP genes spread across 11 chromosomes were identified and scrutinized in detail for their gene structures, protein characteristics, and phylogenetic relationships. The study of phylogenetics and synteny sheds light on the evolutionary relationships among C2H2-ZFPs in F. filiformis and other fungi, revealing a complex evolutionary past. The identification of conserved cis-regulatory elements in the gene promoter regions suggests intricate functionalities, particularly in the developmental and stress response pathways. By utilizing RNA-seq and qRT-PCR techniques, the expression patterns of these genes were explored across different developmental stages and tissues of F. filiformis, unveiling distinct expression profiles. Notably, significant expression variations were observed in the stipe elongation region and pilei of various sizes, indicating potential roles in fruiting body morphogenesis. This study enhances our knowledge of the C2H2-ZFP gene family in F. filiformis and lays the groundwork for future investigations into their regulatory mechanisms and applications in fungal biology and biotechnology.

Trust systems have been widely studied in Internet of Things (IoT). However, there is a little work done on trust management in cross-domain Industrial Internet of Things (IIoT). Many of these models focus mainly or only on trust management in a single administrative domain where trust is evaluated based on the same criteria. In general, different administrative domains adopt different trust models and trust evaluation standards. Due to different trust evaluation standards, trust values from different administrative domain cannot be compared, directly. Therefore, there is a need for a well-defined trust computing scheme for such multi-domain IIoT environment. This paper focuses on the research of cross-domain trust and proposes a cross-domain trust computing scheme “CDTCS”, where trust recommendation value for an IIoT device in a domain can be transferred to a corresponding value in another domain. We analyze CDTCS performance in terms of trust accuracy and resiliency against attacks.

Atmospheric and room-temperature plasma (ARTP) is an efficient microbial mutagenesis method with broad application prospects. Compared to traditional methods, ARTP technology can more effectively induce DNA damage and generate stable mutant strains. It is characterized by its simplicity, cost-effectiveness, and avoidance of hazardous chemicals, presenting a vast potential for application. The ARTP technology is widely used in bacterial, fungal, and microalgal mutagenesis for increasing productivity and improving characteristics. In conclusion, ARTP technology holds significant promise in the field of microbial breeding. Through ARTP technology, we can create mutant strains with specific genetic traits and improved performance, thereby increasing yield, improving quality, and meeting market demands. The field of microbial breeding will witness further innovation and progress with continuous refinement and optimization of ARTP technology.

Trust-based service management in IoT systems, a promising research direction provides an intelligent solution for the identification of appropriate and trustworthy service providers from a huge of number smart nodes providing similar services. An efficient trust-based service ranking scheme (TBSRS) is proposed. The novelty of our design lies in providing accurate trust evaluation and service ranking in the absence of assessment data or presence of untrustworthiness recommendations. TBSRS also addresses the issue about the trustworthiness evaluation of a new service. Service providers are ranking based on the binary fruit fly optimization algorithm in TBSRS. The experimental results demonstrate desirable convergence, accuracy, and resiliency properties of TBSRS, and also demonstrate that TBSRS outperforms Adaptive IoT Trust and IoT-HiTrust in terms of the precision of service selection and other a few performance metrics.

Morels (Morchella spp.) are a kind of rare and precious edible fungus and have been successfully cultivated in many places. Currently, the widespread cultivation of morels poses a significant challenge owing to their demanding environmental requirements. Soil properties and the soil microbiome are thought to play pivotal roles in morel growth. However, it remains unknown what factors exert a decisive influence on morel growth. In this study, soils with different morel yields were studied in nine sites from four locations. The basic soil physical and chemical properties were measured. In addition, the soil microbiome was analyzed using high-throughput metagenomic sequencing. We found that soil pH, nitrogen, carbon and conductivity were key indicators for the impact on microbial communities in soil for cultivating morels. Among these, nitrate was more positively associated with morel yield. The soil microbial diversity was more abundant in the soil with a high morel yield. Moreover, certain unknown archaea might be unfavorable to morel growth. The microbes that perform incomplete denitrification (no step of N2O reduction to N2) and nitrogen fixation were positively and negatively correlated with morel growth, respectively. In summary, morels prefer to live in nutrient-rich soils with a variety of microbes and are supported by nitrate and microbiome components involved in denitrification. The findings elucidate a pivotal mechanism in eliciting morel fructification and provide valuable insights for guiding production practices.

Since the work of detection network (DetNet) by Samuel, Diskin and Wiesel in 2017, deep unfolding for MIMO detection has become a popular topic. We have witnessed significant growth of this topic, wherein various forms of deep unfolding were attempted in the empirical way. DetNet takes insight from the proximal gradient method in terms of the use of the network structure. In this paper, we endeavor to give an explanation of DetNet—in a fundamental way—by drawing connection to a homotopy optimization approach. The intuitive idea of homotopy optimization is to gradually change the optimization landscape, from an easy convex problem to the difficult MIMO detection problem, such that we may follow the solution path to find the optimal MIMO detection solution. We illustrate that DetNet can be interpreted as a homotopy method realized by the proximal gradient method. We also illustrate how this interpretation can be extended to the Frank-Wolfe and ADMM variants of realizing the homotopy optimization approach, which result in new DetNet structures. Numerical results are provided to give insights into how these homotopy-inspired DetNets and their respective non-deep homotopy methods perform.

Lentinula edodes (L. edodes), one of the most popular edible mushrooms in China, is adversely affected by high temperature. Heat shock proteins (HSPs) play a crucial role in regulating the defense responses against the abiotic stresses in L. edodes. Some HSPs in L. edodes have been described previously, but a genome-wide analysis of these proteins is still lacking. Here, the HSP genes across the entire genome of the L. edodes mushroom were identified. The 34 LeHSP genes were subsequently classified into six subfamilies according to their molecular weights and the phylogenetic analysis. Sequence analysis showed that LeHSP proteins from the same subfamily have conserved domains and one to five similar motifs. Except for Chr 5 and 9, 34 LeHSPs genes were distributed on the other eight chromosomes. Three pairs of paralogs were identified because of sequence alignment and were confirmed as arising from segmental duplication. In LeHSPs’ promoters, different numbers of heat shock elements (HSEs) were predicted. The expression profiles of LeHSPs in 18N44 and 18 suggested that the thermo-tolerance of strain 18N44 might be related to high levels of LeHSPs transcript in response to heat stress. The quantitative real-time PCR (qRT-PCR) analysis of the 16 LeHSP genes in strains Le015 and Le027 verified their stress-inducible expression patterns under heat stress. Therefore, these comprehensive findings provide useful in-depth information on the evolution and function of LeHSPs and lay a theoretical foundation in breeding thermotolerant L. edodes varieties.

Abstract Overlapping radio signals recognition is attracting more attention as the development and ubiquitous application of radio technologies. The traditional blind signal separation (BSS) method is mostly not effective when both radio propagation effects and low signal‐to‐noise ratio (SNR) scenarios are taken into consideration. In this letter, joint conformer and CNN model (JCCM) is proposed to separate and recognize the overlapping radio signals which are also unknown by the monitor node. JCCM utilizes the attention mechanism of conformer to encode signal spectrum into feature maps and decodes the feature maps into signal component proportions by perceiving the global and local features through convolutional neural networks (CNN). In addition, a signal preprocessing module is designed including MinPool and AvgPool layers for signal denoising. JCCM is evaluated in terms of signal separation, scaling preservation and principal signal classification experiments. The results show that JCCM has better performance especially in low SNR conditions.

Stroke is an acute cerebrovascular disease that can lead to disability and death. This study aimed to investigate the relationship between socioeconomic status (SES) and stroke. SES was evaluated by two variables: poverty to income ratio (PIR) and education level. In this multi-subject study, we collected data from the National Health and Nutrition Examination Survey (NHANES) database between 2009 and 2018, and finally 22,792 adults (≥20 years old) were included in the study. We proceeded with weighted multivariate logistic regression analysis as well as subgroup analysis. When analyzing the effect of PIR on stroke alone, the results showed that an increase in PIR levels was associated with a decrease in stroke incidence (OR = 0.764 95% CI: (0.711, 0.820), p

Abstract Constructing a functional layer on the surface of commercial membrane (as a substrate) to inhibit the formation of biofilms is an efficient strategy to prepare an antibacterial anion exchange membrane (AEM). Herein, a rechargeable multifunctional anti‐biological system is reported by utilizing the mussel‐inspired L‐dopa connection function on commercial AEMs. Cobalt nanoparticles (Co NPs) and N‐chloramine compounds are deposited on the AEM surface by a two‐step modification procedure. The anti‐biofouling abilities of the membranes are qualitatively and quantitatively analyzed by adopting common Gram‐negative (E. coli) and Gram‐positive (S. aureus & Bacillus) bacteria as model biofouling organisms. The optimized membrane exhibits a high stability concerning the NaCl solution separation performance within 240 min. Meantime, the mechanism of the anti‐adhesion is un‐veiled at an atomic level and molecular dynamics (MD) simulation are conducted to measure the interaction, adsorption energy and average loading by using lipopolysaccharide (LPS) of E. coli. In view of the superior performance of antibacterial surfaces, it is believed that this work could provide a valuable guideline for the design of membrane materials with resistance to biological contamination.

This study focuses on optimizing the mutagenesis process for Morchella eximia (Mel-7) mycelia through atmospheric and room temperature plasma (ARTP) mutation and explores the resultant thermal adaptability and physiological responses of mutant strains. This research demonstrated a clear relationship between ARTP mutagenesis exposure duration and lethality rate, indicating that an exposure time of 40 s resulted in the optimal balance of inducing mutations without causing excessive mortality. Additionally, this study established 43 °C as the ideal screening temperature for identifying mutant strains with enhanced heat resistance, as this temperature significantly challenges the mycelia while allowing thermotolerant strains to be distinguishable. Among the screened mutants, strains L21, L23, L44, and L47 exhibited superior growth and high-temperature tolerance, with notable resilience at 30 °C, highlighting their enhanced adaptability to above-optimal temperatures. Furthermore, this research delved into biochemical responses, including lipid peroxidation and non-enzymatic antioxidant content, highlighting the diverse mechanisms, such as enhanced lipid peroxidation resistance and increased antioxidant content, employed by mutant strains to adapt to temperature fluctuations. The activities of antioxidant enzymes, including peroxidase (POD) and superoxide dismutase (SOD), were shown to be significantly influenced by temperature elevations, illustrating their critical roles in the thermal adaptation of mutant strains. These findings shed light on the importance of considering mutation duration and temperature screening in the development of thermotolerant fungal strains with potential applications in various industries. This study’s breakthrough lies in its comprehensive understanding of the thermal adaptability of Mel-7 mycelia and the identification of promising mutant strains, offering valuable insights for both academic and industrial purposes.

Lentinula edodes, one of the most highly regarded edible mushrooms in China, is susceptible to damage from high temperatures. However, a mutant strain derived from L. edodes, known as Le023M, has shown exceptional thermotolerance. Compared to the original strain Le023, Le023M exhibited accelerated mycelial recovery following heat stress. Through RNA-seq analysis, the majority of differentially expressed genes (DEGs) were found to be associated with functions such as “protein refolding”, “protein unfolding”, “protein folding”, and “response to heat”, all of which are closely linked to heat shock proteins. Furthermore, qRT-PCR results revealed significant accumulation of heat shock-related genes in Le023M under heat stress. GC-MS analysis indicated elevated levels of trehalose, aspartate, and glutamate in Le023M when subjected to heat stress. The highly expressed genes involved in these metabolic pathways were predominantly found in Le023M. Collectively, these findings highlight the following: (i) the crucial role of heat shock proteins (HSPs) in the thermo-resistant mechanisms of Le023M; (ii) the potential of trehalose accumulation in Le023M to enhance mycelium resistance to heat stress; and (iii) the induction of aspartate and glutamate accumulation in response to heat stress. These results shed light on the molecular mechanisms underlying the thermotolerance of Le023M, providing valuable insights for further understanding and improving heat stress response in L. edodes. The findings also highlight the potential applications of Le023M in the cultivation and production of L. edodes under high-temperature conditions.

In the field of livestock management, noncontact pig weight estimation has advanced considerably with the integration of computer vision and sensor technologies. However, real-world agricultural settings present substantial challenges for these estimation techniques, including the impacts of variable lighting and the complexities of measuring pigs in constant motion. To address these issues, we have developed an innovative algorithm, the moving pig weight estimate algorithm based on deep vision (MPWEADV). This algorithm effectively utilizes RGB and depth images to accurately estimate the weight of pigs on the move. The MPWEADV employs the advanced ConvNeXtV2 network for robust feature extraction and integrates a cutting-edge feature fusion module. Supported by a confidence map estimator, this module effectively merges information from both RGB and depth modalities, enhancing the algorithm’s accuracy in determining pig weight. To demonstrate its efficacy, the MPWEADV achieved a root-mean-square error (RMSE) of 4.082 kg and a mean absolute percentage error (MAPE) of 2.383% in our test set. Comparative analyses with models replicating the latest research show the potential of the MPWEADV in unconstrained pig weight estimation practices. Our approach enables real-time assessment of pig conditions, offering valuable data support for grading and adjusting breeding plans, and holds broad prospects for application.

In wireless sensor networks, rotating dominating set is an efficient method for balancing the energy consumption of nodes, and thereby extending the network operational time. This method can be abstracted as $k$ -Lifetime Dominating Set in bipartite graph, that partitions the set of graph vertices representing sensors into $k$ disjoint dominating sets. However, the considered problem has been proven to be NP-hard, and there is no hope of solving it in polynomial time unless P = NP. Existing studies mainly focus on developing approximation or heuristic algorithms, which usually cannot guarantee a solution for a given problem yes instance. In this study, we first propose a randomized algorithm that can generate a solution with guaranteed probability 1- $\varepsilon $ ( $0 < \varepsilon < 1$ ). Using the color coding method, we show that the randomized algorithm can be improved to guarantee the generation of a solution for a given problem yes instance in exponential time. Based on the idea of randomized partition, we further present a more practical centralized greedy algorithm, and then a distributed implementation. Simulation results indicate that the centralized algorithm can efficiently generate optimal solutions for almost all the given problem instances if the partition redundancy is above a certain limit. Compared with existing algorithm, the centralized algorithm increases the number of dominating sets by factors between 0% and 21%.

Mushrooms of the edible and medicinal which are highly nutritious and environmentally friendly crops carry numerous medicinal benefits. For the abundant and high diversity of bioactive metabolites they possess, which are considered to be an important pool of bioresources. The efficient breeding technique is always a challenging task in mushrooms for obtaining better character strains, which are essential for developing healthy products and even consumption. This review comprehensively summarizes the breeding techniques applied to the edible and medicinal mushrooms. Including the traditional mutagenesis method, and even modern gene-editing breeding techniques, the effects of each method, and the comparison of each breeding technique are systematic illustrations. Strategies for mushroom breeding techniques in the future are also discussed in this review paper. With the ongoing sequencing of the mushroom genome, knowledge of the gene background of the strains and functions can be available for developing better markers for gene-editing breeding as CRISPR/Cas9 systems. Combine the metabolism engineering and in-silico tools analysis was the rational design of the novel strains. Modern physical mutagenesis techniques such as the ARTP and the combination of the other physical, and chemical breeding mutagens with cross-breeding techniques or the protoplasts fusion will also lead to superior strains for cultivation and pave the way for higher quality and yield.

BackgroundPatients in minimally conscious state (MCS) exist measurable evidence of consciousness. The frontal lobe is a crucial part of the brain that encodes abstract information and is closely related to the conscious state. We hypothesized that the disturbance of the frontal functional network exists in MCS patients.MethodsWe collected the resting-state functional near-infrared spectroscopy (fNIRS) data of fifteen MCS patients and sixteen age- and gender-matched healthy controls (HC). The Coma Recovery Scale-Revised (CRS-R) scale of MCS patients was also composed. The topology of the frontal functional network was analyzed in two groups.ResultsCompared with HC, the MCS patients showed widely disrupted functional connectivity in the frontal lobe, especially in the frontopolar area and right dorsolateral prefrontal cortex. Moreover, the MCS patients displayed lower clustering coefficient, global efficiency, local efficiency, and higher characteristic path length. In addition, the nodal clustering coefficient and nodal local efficiency in the left frontopolar area and right dorsolateral prefrontal cortex were significantly reduced in MCS patients. Furthermore, the nodal clustering coefficient and nodal local efficiency in the right dorsolateral prefrontal cortex were positively correlated to auditory subscale scores.ConclusionThis study reveals that MCS patients’ frontal functional network is synergistically dysfunctional. And the balance between information separation and integration in the frontal lobe is broken, especially the local information transmission in the prefrontal cortex. These findings help us to understand the pathological mechanism of MCS patients better.

Edible fungus is a large fungus distributed all over the world and used as food and medicine. But people's understanding of edible fungi is not as much as that of ordinary crops, so people have started a number of research on edible fungi in recent years. With the development of science and technology, omics technology has gradually walked into people's vision. Omics technology has high sensitivity and wide application range, which is favored by researchers. The application of omics technology to edible fungus research is a major breakthrough, which has transferred edible fungus research from artificial cultivation to basic research. Now omics technology in edible fungi has been flexibly combined with other research methods, involving multiple studies of edible fungus, such as genetic breeding, growth and development, stress resistance, and the use of special components in edible fungus as pharmaceutical additives. It is believed that in the future, the research of edible fungi will also be brought to a deeper level with the help of omics technology. This paper introduces the application progress of modern omics technology to the study on edible fungi and mentions the application prospect of edible fungi research with the constant development of omics technology, thereby providing ideas for the follow-up in-depth research on edible fungi.

Hypsizygus marmoreus is an edible medicinal mushroom species with a high dietary value. The main purpose of this study was to evaluate the nutritional value, umami taste, and volatile organic compounds (VOCs) of H. marmoreus treated with hot water combined with simulated salivary digestion in vitro. Seafood mushroom (Hm3) had the highest content of moisture, soluble polysaccharides, soluble proteins, and total flavonoids while white Hypsizygus marmoreus (Hm1) had the highest total phenolic content. Moreover, Hm1 had a more noticeable equivalent umami concentration (EUC) value, indicating the umami properties of Hm1 as a food or processing ingredient. Results from E-nose and HS-SPME-GC-MS revealed that the VOCs of Hm1 and brown Hypsizygus marmoreus (Hm2) were relatively similar, which differed substantially from Hm3. Among the 134 VOCs, 24 differential metabolites were identified by OPLS-DA analysis, characterized by VIP > 1, p-value < 0.05, and FC > 2 (pairwise comparisons). Furthermore, 10 biomarkers with VIP > 1 and p-value < 0.05 were identified by PLS-DA analysis based on the total differential metabolites to distinguish different strains of H. marmoreus. These results will benefit future research on the chemistry of H. marmoreus and serve as a guide for breeding, introducing, and using the species more effectively.

Reflective cracking is a common distress of old pavement overlaid with an asphalt layer. The asphalt rubber stress-absorbing membrane interlayer can effectively mitigate and prevent reflective cracking. However, the existing test methods and evaluation indices for the crack resistance of the asphalt rubber stress-absorbing membrane interlayer are insufficient and unsystematic. They do not account for the significant effect of gradation parameters on the crack resistance in a comprehensive way. Therefore, this research aims to explore the impact of gradation parameters on the performance of the asphalt rubber stress-absorbing membrane interlayer. Based on the Chinese and U.S. standards, three kinds of 10 types of gradation were selected, forming a total of seven groups. The asphalt rubber stress-absorbing membrane interlayer was subjected to −10 °C and 15 °C beam bending test, low-temperature semi-circular bend test, crack expansion semi-circular bend test, and overlay test to evaluate its cracking resistance. The correlation and influence law between the key sieve hole method, graded fractal method, and Bayley method parameters of different grades and beam bending test, low-temperature semi-circular bend test, crack expansion semi-circular bend test, and overlay test indexes were quantitatively analyzed by the coefficient of variation and Pearson correlation analysis method. The results showed that the performance of the mixtures with different gradation ranges varied significantly in different tests, as indicated by the maximum difference of 56.07% in stress absorption. This implied that gradation is a critical factor that affects the stress absorption performance of mixes. The different sensitivities of different tests to the parameters of the key sieve method, the graded fractal method, and the Bailey method indicated that the stress absorption performance was affected by a combination of factors. Therefore, in order to evaluate and optimize the stress absorption performance, it was necessary to comprehensively consider the interactions among the parameters of the key sieve method, the graded fractal method, and the Bailey method. The stress absorption performance included crack resistance and crack expansion resistance, which were inversely related and needed to be balanced and optimized during design. The −10 °C beam bending test and crack expansion semi-circular bend tests were more suitable test methods for evaluating stress absorption performance, and maximum flexural–tensile strain, strain energy density, fracture energy, and flexibility index were recommended as evaluation indicators. This research provides a reference for the optimization of the grading design of asphalt rubber stress-absorbing membrane interlayers, and provides test methods and indicators for the evaluation of crack resistance.

Traffic sign detection is an important research direction in the process of intelligent transportation in the Internet era, and plays a crucial role in ensuring traffic safety. The purpose of this research is to propose a traffic-sign-detection algorithm based on the selective kernel attention (SK attention), explicit visual center (EVC), and YOLOv5 model to address the problems of small targets, incomplete detection, and insufficient detection accuracy in natural and complex road situations. First, the feature map with a smaller receptive field in the backbone network is fused with other scale feature maps to increase the small target detection layer. Then, the SK attention mechanism is introduced to extract and weigh features at different scales and levels, enhancing the attention to the target. By fusing the explicit visual center to gather local area features within the layer, the detection effect of small targets is improved. According to the experiment results, the mean average precision (mAP) on the Tsinghua-Tencent Traffic Sign Dataset (TT100K) for the proposed algorithm is 88.5%, which is 4.6% higher than the original model, demonstrating the practicality of the detection of small traffic signs.

Terahertz (THz) noise sources play an irreplaceable role in testing THz devices and evaluating THz application systems, and the flatness of their radio frequency (RF) spectra is an important technical parameter. In this paper, a scheme for generating flat THz noise by mixing multiple filtered incoherent light fields is proposed. A theoretical analysis is conducted to investigate the impact of different spectral linewidths and central wavelength differences of incoherent light fields on the noise power and RF spectrum flatness, and an optimized experimental scheme is obtained. The results show that the proposed method can generate a 280–380 GHz flat THz noise signal with an RF spectrum flatness of ±0.5 dB in simulation and ±2.7 dB in our experiments. This article provides an excellent technical solution to the demand for flat THz noise in the THz field.

Pig counting is an important task in pig sales and breeding supervision. Currently, manual counting is low-efficiency and high-cost and presents challenges in terms of statistical analysis. In response to the difficulties faced in pig part feature detection, the loss of tracking due to rapid movement, and the large counting deviation in pig video tracking and counting research, this paper proposes an improved pig counting algorithm (Mobile Pig Counting Algorithm with YOLOv5xpig and DeepSORTPig (MPC-YD)) based on YOLOv5 + DeepSORT model. The algorithm improves the detection rate of pig body parts by adding two different sizes of SPP networks and using SoftPool instead of MaxPool operations in YOLOv5x. In addition, the algorithm includes a pig reidentification network, a pig-tracking method based on spatial state correction, and a pig counting method based on frame number judgment on the DeepSORT algorithm to improve pig tracking accuracy. Experimental analysis shows that the MPC-YD algorithm achieves an average precision of 99.24% in pig object detection and an accuracy of 85.32% in multitarget pig tracking. In the aisle environment of the slaughterhouse, the MPC-YD algorithm achieves a correlation coefficient (R2) of 98.14% in pig counting from video, and it achieves stable pig counting in a breeding environment. The algorithm has a wide range of application prospects.

In multi-access edge computing (MEC) networks, parallelized service function chains (P-SFCs) can provide low-delay network services for mobile users by deploying virtualized network functions (VNFs) to process user requests in parallel. These VNFs are unreliable due to software faults and server failures. A practical way to address this is to deploy idle backup VNFs (BVNFs) near these active VNFs and activate them when active VNFs fail. However, deploying BVNFs preempts server resources and decreases the number of accepted user requests. Thus, this paper proposes a reliability enhancement approach that uses BVNFs satisfying the delay requirement as active VNFs to form P-SFCs, which contributes to the delay reduction and reliability enhancement. Since the resource capacities of edge servers can only deploy a certain number of P-SFCs and BVNFs, establishing how to deploy the minimum number of P-SFCs and BVNFs to satisfy the delay and reliability requirements of mobile users and maximize the number of accepted user requests is a challenging problem. In this paper, we first model the dynamics of delay and reliability caused by VNF parallelization and BVNFs deployment, then formulate the joint deployment problem of P-SFCs and BVNFs. Next, we design an approximation algorithm to deploy critical VNFs and BVNFs on a target edge server and schedule the data traffic of user requests processed by P-SFCs. Experimental results based on real-world datasets show that our proposed algorithm outperforms two benchmark algorithms in terms of throughput, delay, reliability, and resource utilization.

Chronic cerebral hypoperfusion (CCH) is closely related to vascular cognitive impairment and dementia (VCID) and Alzheimer’s disease (AD). The neuroinflammation involving astrocytes is an important pathogenic mechanism. Along with the advancement of the concept and technology of astrocytic biology, the astrocytes have been increasingly regarded as the key contributors to neurological diseases. It is well known that physical exercise can improve cognitive function. As a safe and effective non-drug treatment, physical exercise has attracted continuous interests in neurological research. In this study, we explored the effects of physical exercise on the response of reactive astrocytes, and its role and mechanism in CCH-induced cognitive impairment. A rat CCH model was established by 2 vessel occlusion (2VO) and the wheel running exercise was used as the intervention. The cognitive function of rats was evaluated by morris water maze and novel object recognition test. The phenotypic polarization and the primary cilia expression of astrocytes were detected by immunofluorescence staining. The activation of MAPKs cascades, including ERK, JNK, and P38 signaling pathways, were detected by western blot. The results showed that physical exercise improved cognitive function of rats 2 months after 2VO, reduced the number of C3/GFAP-positive neurotoxic astrocytes, promoted the expression of S100A10/GFAP-positive neuroprotective astrocytes, and enhanced primary ciliogenesis. Additionally, physical exercise also alleviated the phosphorylation of ERK and JNK proteins induced by CCH. These results indicate that physical exercise can improve the cognitive function of rats with CCH possible by promoting primary ciliogenesis and neuroprotective function of astrocytes. The MAPKs signaling cascade, especially ERK and JNK signaling pathways may be involved in this process.

Abstract Background This study aimed to determine the effect of PKM2 knockout in STZ induced type 1 diabetes mellitus (T1D) mouse models and to explore the possible mechanism. Method PKM2fl/fl C57BL/6 mouse was backcrossed with Ins‐1cre C57BL/6 mouse to generate β‐cell‐specific PKM2 knockout mouse after tamoxifen administration. The expression level of PKM2 in pancreas tissues was detected by quantitative reverse‐transcription polymerase chain reaction and western blot analysis. The blood glucose levels in STZ induced T1D mouse models were measured to validate the establishment of T1D models. The pathological changes of T1D mouse were examined by hematoxylin and eosin. The oxidative stress (OS) and inflammatory response in T1D mouse were determined by measuring the expression levels of malondialdehyde, superoxide dismutase, and 8‐OHdG in pancreatic tissues and the serum levels of interleukin‐6 and tumor necrosis factor‐α. The ability to catabolize glucose was assessed through intraperitoneal glucose tolerance test and insulin tolerance test. Results β‐cell‐specific PKM2 knockout was successfully achieved in PKM2fl/flcre+ mouse. T1D mouse with PKM2 knockdown had decreased blood glucose level and suppressed cell apoptosis. PKM2 knockout in T1D mouse attenuated β cell injury. OS and inflammatory response in T1D mouse with PKM2 knockout were also suppressed compared with T1D mouse without PKM2 knockout. Conclusion PKM2 knockout in T1D mouse can attenuate OS and inflammatory response as well as decrease blood glucose level, suggesting the potential of PKM2 as a drug target for T1D treatment.

The body mass of pigs is an essential indicator of their growth and health. Lately, contactless pig body mass estimation methods based on computer vision technology have gained attention thanks to their potential to improve animal welfare and ensure breeders’ safety. Nonetheless, current methods require pigs to be restrained in a confinement pen, and no study has been conducted in an unconstrained environment. In this study, we develop a pig mass estimation model based on deep learning, capable of estimating body mass without constraints. Our model comprises a Mask R-CNN-based pig instance segmentation algorithm, a Keypoint R-CNN-based pig keypoint detection algorithm and an improved ResNet-based pig mass estimation algorithm that includes multi-branch convolution, depthwise convolution, and an inverted bottleneck to improve accuracy. We constructed a dataset for this study using images and body mass data from 117 pigs. Our model achieved an RMSE of 3.52 kg on the test set, which is lower than that of the pig body mass estimation algorithm with ResNet and ConvNeXt as the backbone network, and the average estimation speed was 0.339 s·frame−1 Our model can evaluate the body quality of pigs in real-time to provide data support for grading and adjusting breeding plans, and has broad application prospects.

In this paper, we study the three-dimensional (3D) trajectory optimization problems of unmanned aerial vehicles (UAV) with a solar energy supply, aiming to provide communication coverage for mobile users on the ground. In general, the higher UAVs fly, the more solar energy they collect, but the smaller the range of coverage they could achieve, and vice versa. How to plan optimal trajectories for UAVs so that more users can be encompassed, while allowing UAVs to collect enough solar energy, is a challenging issue. Moreover, we also consider how geographically fair coverage for each ground user can be achieved. To solve these problems, we designed a multiple solar-powered UAV (SP-UAV) energy consumption model and a fairness model, while designed an observation space, state space, action space, and reward function. Then, we proposed a multiple SP-UAV 3D trajectory optimization algorithm based on deep reinforcement learning (DRL). Our algorithm is able to balance the energy consumption of UAVs to extend the system’s lifetime, while avoiding both collisions and flying out of communication range. Finally, we trained our model through simulation experiments and conducted comparative experiments and analysis based on real network topology data. The results show that our algorithm is superior to the existing typical algorithms in coverage, fairness, and lifetime.