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Abstract Interstitial cystitis/bladder pain syndrome (IC/BPS) is a complex chronic pain disorder with an elusive etiology and nonspecific symptoms. Although numerous animal models with phenotypes similar to human disease have been established, no available regimen can consistently alleviate clinical symptoms. This dilemma led us to question whether current animal models adequately represent IC/BPS. We compared four commonly used IC/BPS rat models to determine their diverse histopathological and molecular patterns. Female rats were given single treatments with hydrochloric acid (HCL), acetic acid (AA), protamine sulfate plus lipopolysaccharide (PS + LPS), or cyclophosphamide (CYP) to induce IC/BPS. Bladder sections were stained for histopathologic evaluation, and mRNA expression profiles were examined using next-generation sequencing and gene set analyses. Mast cell counts were significantly higher in the HCL and AA groups than in the PS + LPS, CYP, and control groups, but only the AA group showed significant collagen accumulation. The models differed substantially in terms of their gene ontology and Kyoto encyclopedia of genes and genomes pathways. Our observations suggest that none of these rat models fully reflects the complexity of IC/BPS. We recommend that future studies apply and compare multiple models simultaneously to fully replicate the complicated features of IC/BPS.

Microfluidic is a technology that allows the precise control of fluid in a micro-channel. With its advantages of high throughput and low cost, microfluidic technology has achieved good performance in various fields in recent years. Arthritis is a general term for a variety of joint diseases, which can be clinically manifested as joint pain and swelling, seriously affecting people's physical and mental health. At present, the causes of arthritis disease are still unknown, and existing disease models and treatment methods are still limited, so more treatments need to be developed. Microfluidic organ chip is a cutting-edge technology to build a bionic human organ model, which can reflect the structure and function characteristics of human organs by simulating the physiological environment of tissues and cells in vitro. This paper reviews the application of microfluidic technology in the modeling and treatment of arthritis, hoping to open up a new vision for the study of arthritis.

Psoriasis is an immune system-mediated skin disease identified by the appearance of erythematous as a central symptom. As a recurrent and chronic inflammatory disease, psoriasis is influenced by both genetic and environmental factors and is known to be with no effective cure. Considering a multifaceted etiology of psoriasis, synergistic therapy exhibits great benefits over monotherapy, which becomes common for the treatment of various diseases. Herein, we present the nanozyme microspheres with structural color-coding labels for synergistic therapy of psoriasis. In particular, microsphere hydrogel is fabricated by the edible hydroxypropyl cellulose (HPC), which can generate a photonic liquid crystalline mesophase under lyotropic conditions in solution. Through adjustment of hydrogel components, microspheres endow with different functions, including moisturizing (paraffin), cfDNA scavenging (chitosan), and anti-inflammation (cerium oxide nanozyme). To improve patient convenience, hydrogel drops with different properties are tailored with different vivid structural colors by exploiting the lyotropic behavior of HPC. Of particular note, both in vitro and in vivo experiments have demonstrated the significant therapeutic effects of the encoded structural color microspheres. Green moisturizing microspheres facilitate to relieve dry, flaky skin patches; blue cfDNA scavenging and red anti-inflammatory microspheres significantly reduce skin inflammation. More importantly, combination therapy with encoded microspheres exerted the synergistic effects, including the increased body weight, thicker epidermal layer, and reduced immune activation. Overall, this synergistic treatment offers a promising platform for personalized management of psoriasis and various inflammatory skin diseases.

In the case of resistance-inductance lines in PV station area, the problem of voltage overstep is easy to occur. This article proposes a reactive power compensation control method to improve the voltage stability in the photovoltaic power plant area, which addresses the problem of voltage at the point of common coupling (PCC) exceeding the upper limit due to resistance circuits and exceeding the lower limit due to relatively insufficient reactive power output when the output active power is high. The idea is to achieve dynamic adjustment of PCC voltage by paralleling a static reactive power generator (SVG) at the grid connection point and using a variable droop control method. In addition, a reactive power optimization method based on improved particle swarm optimization (IPSO) algorithm is proposed to address the changes in power flow caused by photovoltaic integration in the distribution network system. The proposed improvement method not only effectively reduces network losses but also significantly improves voltage stability.

IntroductionThe potential neuroprotective and regenerative properties of electrical stimulation (ES) were studied in rhodopsin knockout mice (Rho−/−), a murine model of inherited retinal degeneration. The study focused on assessing the impact of varying ES frequencies on visual functions and photoreceptor cell survival in Rho−/− mice.MethodsTo elucidate the impact of electrical stimulation on cone survival, Rho−/− mice received either sham or transpalpebral ES using biphasic ramp or rectangular waveforms at 100 µA amplitude, starting at six weeks of age. The treatment duration spanned from one to three weeks. The optimal treatment frequency of ES sessions was determined by applying ES every one, two, or three days in three separate groups of Rho−/− mice. The sham group received daily treatments without the application of ES.ResultsOur study revealed significant improvement of visual function in Rho−/− mice following daily or every-other-day noninvasive transpalpebral ES, as evidenced by electroretinogram and optomotor response-based visual behavior assays. Concurrently, assessment of outer nuclear thickness and immunohistochemistry for the cone photoreceptor cell marker PNA demonstrated pronounced increases in the survival of rods and cones and improvement in the morphology of the inner and outer segments.DiscussionThis study underscores the protective effect of non-invasive ES in rhodopsin knockout-induced retinal degenerative disorders, providing a foundation for developing targeted therapeutic interventions for retinitis pigmentosa.

Underground small indoor gymnasiums (USIG) are important public places, it is vital to design and build a very economical and efficient ventilation system for effective closed-loop regulation of temperature and gases concentration at prescribed levels. In the article, the model-based prototype design, establishment and operation were proposed and applied to closed-loop control system of the underground small indoor gymnasiums’ ventilation system (USIGVS). First of all, the extended Multiphysics model was developed through feedback connecting the 3D Multiphysics model of air flow rate, temperature, O2 and CO2 concentration with a 0D proportional-integral-derivative (PID) controller via Neumann boundary condition, hence a close-loop USIGVS was constructed for feedback control of temperature and gases concentration in ping-pong USIG. Simultaneously, a cost function sufficiently representing the design requirement was formulated. Then global parameter sensitivity analysis (GPSA) was applied for sensitivity ranking of parameters including geometric parameters of USIGVS and tunable parameters of PID controller. The GPSA proved that sensitivity ordering of the cost function to each parameter was proportional gain (kp) > derivative gain (kd) > distance from left inlet to bottom (r) > distance from outlet pipe to bottom (d) > integrative gain (ki) > distance from upper inlet pipe to left (h), respectively, and the kp, kd and r was the parameter influencing the cost function the most. The optimal parameters determined by both GPSA and response optimization were kp = 3.17 m4 mol−1 s−1, kd = 1.49 m4 mol−1, r = 2.04 m, d = 3.12 m, ki = 0.37 m4 mol−1 s−2 and h = 3.85 m. Finally, the closed-loop USIGVS prototype with optimal parameters was designed and established through real-time simulation. The real-time operation confirmed that the temperature and gases concentrations were robust maintained at prescribed levels with desired dynamic response characteristics and lower power consumption, and the expected requirements were achieved for the design, establishment and operation of closed-loop USIGVS control system prototype.

The phenomenon of fine particle migration through the voids of the granule skeleton under the seepage force is called suffusion. Relative density, original fine particle content, and gap ratio are thought to play vital roles in the suffusion process. This paper investigates the effect of geometrical characteristics (i.e., original fine particle content, gap ratio, and relative density) on soil structure and mechanical performance (i.e., small strain shear modulus) using the bender element method technique. The small strain shear modulus (G0) is used as a mechanical parameter to evaluate the shear stress transmission of the soil structure along with the erosion process. The comparison between erosion percentage and vertical strain change suggests the alteration in soil fabric after soil erosion. The G0 monitoring results show that packings with a higher original fine particle content have a lower G0 value, whereas the gap ratio and relative density present a positive relationship with G0.

Abstract Effective drugs for the treatment of gastric cancer (GC) are still lacking. Nortriptyline Hydrochloride (NTP), a commonly used antidepressant medication, has been demonstrated by numerous studies to have antitumor effects. This study first validated the ability of NTP to inhibit GC and preliminarily explored its underlying mechanism. To begin with, NTP inhibits the activity of AGS and HGC27 cells (Human-derived GC cells) in a dose-dependent manner, as well as proliferation, cell cycle, and migration. Moreover, NTP induces cell apoptosis by upregulating BAX, BAD, and c-PARP and downregulating PARP and Bcl-2 expression. Furthermore, the mechanism of cell death caused by NTP is closely related to oxidative stress. NTP increases intracellular reactive oxygen species (ROS) and malondialdehyde (MDA) levels, decreasing the mitochondrial membrane potential (MMP) and inducing glucose (GSH) consumption. While the death of GC cells can be partially rescued by ROS inhibitor N-acetylcysteine (NAC). Mechanistically, NTP activates the Kelch-like ECH-associated protein (Keap1)—NF-E2-related factor 2 (Nrf2) pathway, which is an important pathway involved in oxidative stress. RNA sequencing and proteomics analysis further revealed molecular changes at the mRNA and protein levels and provided potential targets and pathways through differential gene expression analysis. In addition, NTP can inhibited tumor growth in nude mouse subcutaneous tumor models constructed respectively using AGS and MFC (mouse-derived GC cells), providing preliminary evidence of its effectiveness in vivo. In conclusion, our study demonstrated that NTP exhibits significant anti-GC activity and is anticipated to be a candidate for drug repurposing.

Abstract Background Green tea has been reported to be potentially protective against the development of cardiovascular disease (CVD). This study aimed to investigate the association between green tea consumption and incident CVD in type 2 diabetes (T2D) patients with overweight/obesity. Methods A total of 4756 Chinese overweight/obese T2D patients were recruited and followed up for 6.27 years. Information on green tea consumption was collected at baseline using interviewer-administered questionnaires. Hazard ratios (HRs) and 95% confidence intervals (CIs) for incident CVD according to green tea consumption were estimated using the Cox proportional hazards model. Results Compared with non-habitual consumers, participants who consumed > 5 g/day of green tea leaves reduced the risk of CVD by 29% (95%CI: 0.55–0.92), stroke by 30% (95%CI: 0.51–0.95) and coronary heart disease (CHD) by 40% (95%CI: 0.40–0.89). Similarly, participants who consumed green tea for ≥ 40 years reduced the risk of CVD by 31% (95%CI: 0.54–0.88), stroke by 33% (95%CI: 0.50–0.90) and CHD by 39% (95%CI: 0.42–0.88). Among participants with 5 g/day of tea leaves and > 40 years of tea consumption were associated with 59% (95%CI: 0.23–0.72) and 57% (95%CI: 0.26–0.74) reduced risk of stroke, respectively. However, among participants with ≥ 5-year history of T2D, > 5 g/day of tea leaves and > 40 years of tea consumption were associated with a 50% (95%CI: 0.30–0.82) and 46% (95%CI: 0.35–0.85) reduced risk of CHD, respectively. Conclusions Green tea consumption is associated with reduced risk of CVD, stroke, and CHD in overweight/obese T2D patients.

Summary: CD8+ T cells are rendered exhausted in tumor and chronic infection. Among heterogeneous exhausted T cells, a subpopulation of progenitor-like (Tpex) cells have been found important for long-term tumor or pathogen control and are also the main responders in immunotherapy. Using an RFP reporter mouse for the orphan nuclear receptor NR4A1, originally characterized as critical in T cell dysfunction, we discover that the reporter is highly expressed in Tpex cells in tumor and chronic infection. Enforced expression of Nr4a1 promotes Tpex cell accumulation, whereas tumor control is improved after Nr4a1 deletion, associated with increased effector function but decreased long-term maintenance of CD8+ T cells. Integrating chromatin immunoprecipitation sequencing (ChIP-seq) and RNA sequencing (RNA-seq) analysis, NR4A1 is found to bind and promote the expression of Tpex-related genes, as well as suppress terminal differentiation-associated genes. This study therefore has identified a key role of NR4A1 in Tpex regulation and provides a promising target for immunotherapy.

BackgroundIt is important to figure out the immunity of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) reinfection to understand the response of humans to viruses. A serological survey for previously infected populations in Jiangsu Province was conducted to compare the antibody level of SARS-CoV-2 in reinfection by Omicron or not.MethodsReinfection with SARS-CoV-2 was defined as an individual being infected again after 90 days of the initial infection. Telephone surveys and face-to-face interviews were implemented to collect information. Experimental and control serum samples were collected from age-sex-matched reinfected and non-reinfected cases, respectively. IgG anti-S and neutralizing antibodies (Nab) concentrations were detected by the Magnetism Particulate Immunochemistry Luminescence Method (MCLIA). Antibody titers were log(2)-transformed and analyzed by a two-tailed Mann–Whitney U test. Subgroup analysis was conducted to explore the relationship between the strain type of primary infection, SARS-Cov-2 vaccination status, and antibody levels. Multivariate linear regression models were used to identify associations between reinfection with IgG and Nab levels.ResultsSix hundred thirty-one individuals were enrolled in this study, including 327 reinfected cases and 304 non-reinfected cases. The reinfection group had higher IgG (5.65 AU/mL vs. 5.22 AU/mL) and Nab (8.02 AU/mL vs. 7.25 AU/mL) levels compared to the non-reinfection group (p

We aimed to investigate the improvement effect of Beclin-1 on the cognitive function of mice with Alzheimer"s disease (AD). Human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) were isolated from neonatal umbilical cord tissues. The cells stably overexpressing Beclin-1 were constructed, and those of passages 5, 10, and 15 were used. Forty-eight AD mice were randomly divided into AD, P5 hUC-MSCs, P15 hUC-MSCs (P15MSCs) and OE Beclin 1-P15 hUC-MSCs (OE Bec-P15MSCs) groups (n=12). Overexpressing Beclin-1 significantly enhanced the proliferation and migration of MSCs of different passages, and reduced G0/G1 arrest. The OE Bec-P15MSCs group had the longest total distance, the shortest time in forced swimming test, and the largest total food consumption in novelty suppressed feeding test. Transplanting hUC-MSCs and overexpressing Beclin-1 significantly reduced Aβ deposition. The expressions of P-tau (Ser396), P-tau (Ser231) and P-tau (Ser235) were significantly inhibited by hUC-MSCs transplantation and Beclin-1 overexpression, especially in the OE Bec- P15MSCs group. Double positive staining of EdU+/DCX+ cells, EdU+/NeuN+ cells and EdU+/Nestin+ cells significantly increased in the OE Bec-P15MSCs group compared to those in other groups (P

Abstract Background In professional ethics-related events, there are various unpleasant and complex ethical issues that require strong moral courage. Our aim is to identify and describe the potential categories of moral courage among nurses and to clarify the coping styles of nurses under different categories. Method A cross-sectional study was conducted using three data collection tools: a self-designed general information questionnaire, a Chinese version of the Moral Courage Scale, and a Trait Coping Style Questionnaire. Three hundred fourteen nurses from a tertiary hospital in Heilongjiang Province, China, were analysed using potential profile analysis, descriptive analysis, and Mann-Whitney U test data. Result The latent profile analysis (LPA) results indicate that the two-profile model is the most suitable and supports the existence of two different moral courage profiles: the low moral courage group (60.51%) and the high moral courage group (39.49%), with a high relative entropy value (0.922). The results point to a good profile solution, and there are significant differences between the two profiles. The Mann-Whitney U-test results showed that the positive coping scores of the high moral courage group were significantly higher than those of the low moral courage group, and the negative coping scores of the high moral courage group were significantly lower than those of the low moral courage group. Conclusion Our results reveal the heterogeneity of moral courage in the nurse sample and indicate that nurses in the high moral courage group tend to choose positive coping styles, while nurses in the low moral courage group are more likely to develop negative coping emotions. This provides important significance and reference value for nursing managers, who can propose customised management plans based on the types of moral courage of the nursing community and the coping styles under different categories.

Carbon sequestration management of plantation forests has become an important topic in the current context of vigorously promoting carbon peaking and carbon neutrality goals and will be the goal and task of the forest industry for a long time. The objective of this study was to explore the applications of genetic algorithm (GA) in both near-optimal thinning regimes at stand level and near-optimal forest management planning at the regional level under the forest management objectives of carbon sequestration. This research integrates a carbon assessment technique with GA optimization to effectively enhance the management of carbon sequestration within plantation forests. Results indicate that the density effect model was an accurate and reliable carbon assessment method (R2 = 0.8701, RMSE = 7.548). The GA optimization approach is efficient in the near-optimal thinning regime and the appropriate forest management planning schedule under the forest management objectives of carbon sequestration. In the research area, the near-optimal carbon sequestration is 38,045.71 t, and in the 15 years from 2016 to 2030, the carbon sequestration of 20 Chinese fir stands should meet the annual thinning constraint condition of not less than 50 t. A near-optimal decision of the carbon sequestration management of plantation forests based on GA provides a theoretical basis and technical support for the compilation of a forest management plan at the stand and regional scales in the plantation operation management of carbon sequestration.

Objective： A surface evaporation concentration device were designed to concentrate thermosensitive feed liquid at low temperature under normal pressure with low energy consumption. Methods： Based on an introduction to the working principle of the device, the basic equations of the device were given. The changes of volumetric evaporation flux and energy saving ratio with flow rate of the feed liquid, feed liquid temperature, sweeping gas flow rate, sweeping gas temperature were calculated and analyzed. Designed an experimental platform and obtained a set of optimal performance parameters through experiments. Results： The results showed that when the flow rate of the feed liquid was 0.02 kg/s, the device had the highest energy saving ratio and higher volumetric evaporation flux; When the temperature of the feed liquid increased from 30 ℃ to 50 ℃, the volumetric evaporation flux increased by 224.68%, but the energy saving ratio decreased by 12.42%; When the sweeping gas flow rate increased from 0.004 kg/s to 0.006 kg/s, the volumetric evaporation flux increased by 23.45%, but the energy saving ratio decreased by 7.74%; When the temperature of the sweeping gas increased from 10 ℃ to 30 ℃, the volumetric evaporation flux decreased by 22.92%, but the energy saving ratio increased by 37.49%; An experimental device was established to test orange juice with a sugar content of 15 °Brix, the results showed that when the feed liquid temperature was 38 ℃ and the sweeping gas temperature was 26 ℃, the volumetric evaporation flux of the device could reach 219 kg/（m3·h）, and the energy saving ratio could reach 3.3.Conclusion： The heat pump assisted random filler surface evaporation device has the characteristics of low temperature concentration under atmospheric pressure and low energy consumption when concentrating thermosensitive feed liquid．

Summary: Preeclampsia (PE) is a hypertensive pregnancy disorder with increased risk of maternal and fetal morbidity and mortality. Abnormal extravillous trophoblast (EVT) development and function is considered to be the underlying cause of PE, but has not been previously modeled in vitro. We previously derived induced pluripotent stem cells (iPSCs) from placentas of PE patients and characterized abnormalities in formation of syncytiotrophoblast and responses to changes in oxygen tension. In this study, we converted these primed iPSC to naïve iPSC, and then derived trophoblast stem cells (TSCs) and EVT to evaluate molecular mechanisms underlying PE. We found that primed (but not naïve) iPSC-derived PE-EVT have reduced surface HLA-G, blunted invasive capacity, and altered EVT-specific gene expression. These abnormalities correlated with promoter hypermethylation of genes associated with the epithelial-mesenchymal transition pathway, specifically in primed-iPSC derived PE-EVT. Our findings indicate that abnormal epigenetic regulation might play a role in PE pathogenesis.

Digital microfluidic biochips (DMFBs) have a significant stride in the applications of medicine and the biochemistry in recent years. DMFBs based on micro-electrode-dot-array (MEDA) architecture, as the next-generation DMFBs, aim to overcome drawbacks of conventional DMFBs, such as droplet size restriction, low accuracy, and poor sensing ability. Since the potential market value of MEDA biochips is vast, it is of paramount importance to explore approaches to protect the intellectual property (IP) of MEDA biochips during the development process. In this paper, an IP authentication strategy based on the multi-PUF applied to MEDA biochips is presented, called bioMPUF, consisting of Delay PUF, Split PUF and Countermeasure. The bioMPUF strategy is designed to enhance the non-linearity between challenges and responses of PUFs, making the challenge–response pairs (CRPs) on the MEDA biochips are difficult to be anticipated, thus thwarting IP piracy attacks. Moreover, based on the easy degradation of MEDA biochip electrodes, a countermeasure is proposed to destroy the availability of piracy chips. Experimental results demonstrate the feasibility of the proposed bioMPUF strategy against the brute force attack and modeling attack.

Background Resolvin D2 (RvD2) has been reported to protect against the development of atherosclerosis in animal models. The objective of this study was to examine the prospective association between plasma RvD2 and the risk of atherosclerotic cardiovascular disease (ASCVD) at the population level. Methods and Results A cohort of 2633 community‐dwelling individuals aged 35–60 years was followed for 8 years in this study. Adjusted hazard ratios and 95% CIs for ASCVD outcomes according to baseline RvD2 levels were calculated using Cox proportional hazards models. Mediation analysis was used to test the indirect effect of serum cholesterol indicators on the association between RvD2 and ASCVD probability. In total, 284 new cases of ASCVD were identified during follow‐up. An inverted U‐shaped association between natural log (ln)‐transformed RvD2 and incident ASCVD was determined, and the threshold value for lnRvD2 was 3.87. Below the threshold, each unit increase in lnRvD2 was associated with a 2.05‐fold increased risk of ASCVD (95% CI, 1.13–3.74; P=0.019). Above the threshold, each unit increase in lnRvD2 was associated with a 36% reduced risk of ASCVD (95% CI, 0.51–0.80; P

Long-range multi-purpose cluster munitions with reconnaissance, identification, strike and evaluation functions are widely used, and a large number of unexploded submunitions will be generated on the surface, which will greatly hinder the battlefield maneuver, deployment and depth attack. Due to its special visual characteristics, surface unexploded submunitions use imaging technology and deep learning technology for long-distance, large-area, non-contact rapid and accurate detection and recognition. This paper introduces the common methods of unexploded submunition detection and their advantages and disadvantages, summarizes the imaging characteristics of unexploded submunitions under different imaging technology conditions and their identification and positioning methods, analyzes the signifi-cant advantages of deep learning in the field of unexploded submunition detection and recognition. Then, a UAV-borne rapid detection, identification and positioning method based on deep learning for surface unexploded submunitions is proposed.

Abstract Aim Rates vary widely across hospitals globally and typically range from 3 to 11 falls per 1000 bed days and as 7–11 in Affiliated Hospital of Nantong University. This study determined to explore contributing factors and poor prognosis of fall in elderly tumour patients in China. Design A cross‐sectional study. Methods 161 older adults were invited to participate in this study and completed a self‐reported questionnaire, took blood tests, and received the exam of musculoskeletal ultrasound. Results Among 161 patients, falls occurred in 41 cases, accounting for 24.8%. 51.6% of older adults suffered from intermediate‐to‐high risk of falls. Fall history, reduced self‐care ability, sleep disturbance, hearing impairment, hyperkyphosis, chronic disease, platelet count, and the thickness of left muscle rectus femoris (LF‐MLT), and left cross‐sectional area (LF‐CSA) were all contributing factors of fall, and higher risk of fall indicating lower quality of life. A fall prediction model was established in this study based on above contributing factors with good prediction efficiency (AUC = 0.920). Patient or public contribution The patient volunteers participated in this study and provided valuable data for the final analysis and the acquisition of conclusion.

【Objective】This study aims to discover members of the Al-activated malate transporter ALMT gene family that may be involved in the growth and development of litchi and to investigate their biological functions.【Method】The physicochemical properties of proteins, subcellular localisation predictions, phylogeny, gene structure, conservative motifs, chromosomal positioning, promoter cis-acting elements, protein structure and expression patterns of litchi ALMT gene family members were systematically analysed using bioinformatics methods, expression of the litchi LcALMTs was analysed by qPCR.【Result】The results showed that the litchi LcALMT gene family has 16 members with CDS lengths ranging from 118 to 803 bp and isoelectric points between 5.16 and 9.07. Subcellular localisation predictions showed that the LcALMTs were all localised to the plasma membrane, and the family was divided into five subclades based on a phylogenetic tree. The number of exons of the LcALMTs ranged from 3 to 10, and four LcALMT genes did not contain any non-coding regions. Chromosomal localisation analysis revealed that LcALMTs was localised on only six of the 15 chromosomes of litchi, and mainly on chromosome 13. Conservative motif analysis revealed that litchi ALMT family members contain both ALMT and ALMT superfamily structural domains. Among the cis-acting elements, light-responsive elements accounted for the largest proportion, followed by hormone-responsive elements. Expression pattern analysis revealed that the expression of Litchi LcALMTs was highly variable in different tissues, with LcALMT5 and LcALMT15 being expressed at high levels in all tissues, the qPCR results showed that the expression level of LcALMT5 was more consistent with the results of the transcriptome.【Conclusion】There are 16 members of the litchi ALMT Gene family, which has a conservative gene structure and protein domain, and there are differences in tissue expression.

Abstract During the COVID-19 lockdown in Shanghai, we found many social exchanges within communities. In this study, we focus on exploring the driving forces behind social exchanges and their impacts on the social solidarity of local communities. Twenty-eight residents of separate communities are interviewed, and grounded theory is applied to have the motivation for social exchanges coded and analyzed. We find that reciprocal and generalized exchanges, rather than negotiated exchanges, occur in most communities. Among these exchanges, the willingness to share is stimulated by the traditional cultural norms taking place in online social groups. Residents will be propelled to carry on exchanges through sentiments cultivated within and to develop the micro social order through interactions in the media space. Social exchanges bring social solidarity to communities and develop it into a noticeable form consisting of functional, emotional, and communal aspects.

Estimating tree height at the national to regional scale is crucial for assessing forest health and forest carbon storage and understanding forest ecosystem processes. It also aids in formulating forest management and restoration policies to mitigate global climate change. Extensive ground-survey data offer a valuable resource for estimating tree height. In tree height estimation modeling, a few comparative studies have examined the effectiveness of global-based versus local-based models, and the spatial heterogeneity of independent variable parameters remains insufficiently explored. This study utilized ~200,000 ground-survey data points covering the entire provincial region to compare the performance of the global-based Ordinary Least Squares (OLS) and Random Forest (RF) model, as well as local-based Geographically Weighted Regression (GWR) model, for predicting the average tree height of Chinese fir forests in Zhejiang Province China. The results showed that the GWR model outperformed both OLS and RF in terms of predictive accuracy, achieving an R-squared (R2) and adjusted R2 of 0.81 and MAE and RMSE of 0.93 and 1.28, respectively. The performance indicated that the local-based GWR held advantages over global-based models, especially in revealing the spatial non-stationarity of forests. Visualization of parameter estimates across independent variables revealed spatial non-stationarity in their impact effects. In mountainous areas with dense forest coverage, the parameter estimates for average age were notably higher, whereas in forests proximate to urban areas, the parameters were comparatively lower. This study demonstrates the effectiveness of large ground-survey data and GWR in tree height estimation modeling at a provincial scale.

Epidemiological studies have shown an association between type 2 diabetes (T2D) and calcific aortic valve stenosis (CAVS), but the potential causal relationship and underlying mechanisms remain unclear. Therefore, we conducted a two-sample and two-step Mendelian randomization (MR) analysis to evaluate the association of T2D with CAVS and the mediating effects of circulating metabolites and blood pressure using genome-wide association study (GWAS) summary statistics. The inverse variance weighted (IVW) method was used for the primary MR analysis, and comprehensive sensitivity analyses were performed to validate the robustness of the results. Our results showed that genetically predicted T2D was associated with increased CAVS risk (OR 1.153, 95% CI 1.096–1.214, p < 0.001), and this association persisted even after adjusting for adiposity traits in multivariable MR analysis. Furthermore, the two-step MR analysis identified 69 of 251 candidate mediators that partially mediated the effect of T2D on CAVS, including total branched-chain amino acids (proportion mediated: 23.29%), valine (17.78%), tyrosine (9.68%), systolic blood pressure (8.72%), the triglyceride group (6.07–11.99%), the fatty acid group (4.78–12.82%), and the cholesterol group (3.64–11.56%). This MR study elucidated the causal impact of T2D on CAVS risk independently of adiposity and identified potential mediators in this association pathways. Our findings shed light on the pathogenesis of CAVS and suggest additional targets for the prevention and intervention of CAVS attributed to T2D.

Metabolomics, especially urine-based studies, offers incredible promise for the discovery and development of clinically impactful biomarkers. However, due to the unique challenges of urine, a highly precise and reproducible workflow for NMR-based urine metabolomics is lacking. Using 1D and 2D non-uniform sampled (NUS) 1H-13C NMR spectroscopy, we systematically explored how changes in hydration or specific gravity (SG) and pH can impact biomarker discovery. Further, we examined additional sources of error in metabolomics studies and identified Navigator molecules that could monitor for those biases. Adjustment of SG to 1.002–1.02 coupled with a dynamic sum-based peak thresholding eliminates false positives associated with urine hydration and reduces variation in chemical shift. We identified Navigator molecules that can effectively monitor for inconsistencies in sample processing, SG, protein contamination, and pH. The workflow described provides quality assurance and quality control tools to generate high-quality urine metabolomics data, which is the first step in biomarker discovery.

This study presents a novel approach for the reuse of uncontaminated fracturing flowback fluids to improve the inhibitory and lubricating properties of water-based drilling fluids (WBFs), curb environmental pollution arising from flowback fluids, and substantially mitigate the expenses associated with WBFs. The experimental design was optimized using orthogonal experiments and range analyses, whereby the modified rubber powder was set at 2.0%, xanthan gum at 0.15%, and a plant phenol to modified complexing agent ratio of 1:0.01. The assessment of the performance evaluation tests indicated that the use of uncontaminated fracturing flowback fluids as the base water can remarkably enhance the inhibitory and lubricating properties of WBFs. Precisely, this approach reduces the linear expansion rate from 62.31% to 21.25%, the reduction rate of extreme pressure lubrication coefficient by 87.98%, and the reduction rate of mud cake sticking factor by 59.86%. This investigation has established the potential environmental and economic benefits of reusing clean fracturing flowback fluids in WBFs.

With the continuous emergence of network and information security challenges, international trade frictions and other issues, the demand for localization, independence and controllability of products is becoming more and more intense. As a result, domestic hardware and software solutions will be gradually adopted to replace foreign solutions for the key control system in the field of rail transit. This paper briefly describes the architecture of the domestic traction and network control system for the standardized subway platform, and focuses on the selection of the hardware and software, such as CPUs, embedded operating systems and graphical development software. It also details the hardware scheme, software structure, and migration and adaptation process of the software and hardware for the traction and network control system, and makes a comparative analysis on the functions and performances of the domestic operating system and VxWorks. Through a series of software functional tests such as verification of traction/electric braking characteristics and networking, conclusions are drawn that the domestic traction and network control system features excellent performance parameters, stable and reliable operation, normal traction/electric braking characteristics, network delay of the system in microseconds, and jitter of the sub-microsecond level, which meet the requirements of the standardized subway platform, and therefore it can be used for 100% localization as an equivalent substitute.

Abstract In this work, the $$\gamma p\rightarrow \phi (1680) p$$ γ p → ϕ ( 1680 ) p reaction is systematically studied based on the two gluon exchange model and the pomeron model. The calculation results show that the total cross section of $$\phi (1680)$$ ϕ ( 1680 ) photoproduction can reach more than 80 nb near the center-of-mass energy $$W=4$$ W = 4 GeV, so it is suggested that JLab and other experiments carry out relevant measurements. Moreover, under the framework of the vector meson dominance assumption, the scattering length of $$\phi (1680)$$ ϕ ( 1680 ) and proton interaction is estimated as $$0.07\pm 0.01$$ 0.07 ± 0.01 fm from the cross sections predicted by the theoretical models, which is on the same order of magnitude as the $$\phi (1020)$$ ϕ ( 1020 ) -p scattering length. In addition, the total cross section, number of events and rapidity distribution of $$\phi (1680)$$ ϕ ( 1680 ) production are predicted at Electron-Ion colliders (EICs) and ultra-peripheral collisions (UPCs) by using eSTARlight and STARlight code. The study of $$\phi (1680)$$ ϕ ( 1680 ) and relevant properties is of enlightening significance in better understanding the strangeonium family spectrum, and provides necessary data support for the future experiment of EICs and UPCs.

Carbon electrode perovskite solar cell has great potential in commercial application based on its low cost, superior stability, and facile fabrication process. However, its performance still lags behind that of devices with gold anode, which greatly attributes to the insufficient charge transport and collection at carbon anode side. Herein, efficient anode buffer contact is built by constructing an organic/inorganic composite hole transport bilayer together with strategic carbon precovering/postcovering anode. Adding a charge selective polythiophene (P3HT) layer between perovskite and nickel oxide (NiOx) can reduce charge transfer recombination loss, inhibit moisture infiltration, and crystallographically protect the perovskite underneath from being corroded by carbon paste. Together with a dense and pin-hole free hole transport layer (HTL)/carbon contact through precovering diluted carbon paste, the modified anode buffer interfaces also promote a facilitated charge collection, thus enhancing the photovoltaic performance of low-cost carbon electrode perovskite solar cells to a state-of-the-art value of 20.8% with an enhanced operational stability. This work provides adaptable and robust anode buffer interfaces for efficient, stable and low cost carbon electrode perovskite cells toward commercialization.

Abstract With the high penetration of distributed generation and gradual increase in loop network structures, existing over‐current protection in distribution networks is difficult to apply. The use of current differential protection has become an ideal solution, and high performance and commercialization of 5G communication provides an effective way to solve the problem of differential protection channel transmission. Aiming at distribution network differential protection based on 5G, this paper adopted an adaptive frequency conversion transmission mechanism to significantly reduce the data flow of differential protection. In terms of protection strategy, the differential allowable signal and the differential protection startup logic are separated, and a novel action method and protection logic suitable for weak infeed distribution networks are proposed. The strategy significantly shortens the protection action time under wireless communication. Furthermore, a comprehensive synchronization scheme using zero‐crossing synchronization of forward sampling points and cycle numbers based on the second pulse signal was established. This scheme can effectively improve the reliability of data synchronization for differential protection. Finally, the method proposed in this study was verified using the dynamic model experiment of real‐time digital simulation (RTDS).

Due to technical barriers and economic costs, malicious circuits, known as hardware Trojans, are easily implanted in the complicated integrated circuit design and manufacturing process, which can lead to many disastrous consequences, such as denial of service, information leakage, performance degradation, etc. Research on how to detecting hardware Trojans has grown into a significantly open issue over the past decade. While, for very large scale integrated circuits, numerous new challenges deserve our full attention, including golden-free chip reference, automatic feature engineering, hardware Trojan localization, and scalable framework. In response to the above challenges, a fine-grained gate-level hardware Trojan detection approach is proposed in this paper, named GateDet, from improving earlier circuit graph modeling to developing a detection framework based on Bidirectional Graph Convolution Networks with a timely information fusion strategy. GateDet achieves automatic feature circuit extraction and further overcomes the original neighborhood limitation of Bidirectional Graph Convolution Network. Moreover, for large-scale training, it comprehensively considers the problems of sample imbalance and boundary network, and develops a circuit directed graph sampling method based on GraphSAINT, which improves the training performance of the directed graph framework. From experiments, GateDet shows high scalability on 24 benchmarks of TrustHub. It could be used to learn about adaptive structural feature extraction for different Trojans simultaneously. Compared to the existing gate-level detections, the fine-grained results of GateDet are more accurate and can be used to track suspicious structures, reducing manual review.

Green synthesis of metal-organic frameworks (MOFs) in water with alleviated environmental influence and reduced cost is an essential step to transfer laboratory MOFs research to industrial application. Switching from the commonly used organic solvents to pure water encounters challenges of the poor solubility of organic linkers, slow reaction kinetics, and the formation of polymorphic products. So far, a universal MOFs synthetic strategy in water system has yet to be developed. This study reports the seed-aided synthesis of eleven MOFs with diverse compositions and structures while pure water serving as solvent. The corresponding reaction temperature and time of using this new strategy were reduced compared with original synthetic approaches, while the products maintain porous structure and high crystallinity. The success of this strategy relies on the addition of parent MOFs as seeds which could promote crystallization process by skipping the time-consuming induction period and avoiding the formation of polymorphic impurities.

Abstract In the quantum chromodynamics, the mass source of the proton is decomposed into four parts by the energy momentum tensor: quark energy term, gluon energy term, quark mass term and trace anomaly term. And the trace anomaly term is the most crucial contribution for studying the internal structure of the proton. In this work, under the definition of the vector meson dominant model, the trace anomaly contribution of the proton is extracted from the experimental data of light vector mesons $$\rho $$ ρ , $$\omega $$ ω and $$\phi $$ ϕ photoproduction at the near-threshold, which are ( $$0.53\pm 0.15$$ 0.53 ± 0.15 ) $$\%$$ % , ( $$1.47\pm 0.48$$ 1.47 ± 0.48 ) $$\%$$ % and ( $$2.73\pm 0.54$$ 2.73 ± 0.54 ) $$\%$$ % , respectively. Further, combined with the results extracted from the heavy vector meson $$J/\psi $$ J / ψ photoproduction, the distribution of the trace anomaly contribution with the vector meson mass is given for the first time. These results may provide important theoretical information for determining the range of the trace anomaly contribution and for further understanding the origin of the proton mass.

The Internet of Vehicles (IoV) has a significant impact on improving traffic efficiency and driving safety. In this paper, we propose an intelligent transportation credit system based on blockchain, and design a crossroad passing smart contract that allows time-sensitive convoys to pass a crossroad earlier by paying traffic tokens for right-of-way trade. Second, this paper formulates the time–cost optimization problem under the premise of protecting the privacy of preceding convoys. Based on game theory with incomplete information, two right-of-way optimal bid strategies are given. Both theoretical analysis and simulation prove that the strategy proposed in this paper effectively reduces the waiting time of time-sensitive vehicles at a crossroad and increases the trade success probability, which, in turn, improves the expected total profit of convoys and achieves Pareto improvement.

The primary feature of Industry 4.0 is MPP (mass personalization production), which requires that consumers’ individual requests are met in large-scale production. Under MPP, there is a multitude of subtasks decomposed from production tasks that are derived from individualized requests, and allocating these subtasks properly brings high economic benefits. However, existing approaches to achieve MPP, such as cloud manufacturing and social manufacturing, generally can not provide customers with deep participation in the entire production cycle, or respond to consumers’ modification needs by a triggered mechanism. Besides, some methods are of centralized architecture, which is vulnerable to single point error and with large cloud load that is not conducive to quickly responding to consumers’ dynamic demand changes. Therefore, this paper proposes a dynamic edge-cloud manufacturing mode for MPP, which can make subtask allocation with high economic benefit through distributed computing and implementing modifications of alternating direction method of multiplier (ADMM) algorithm. Also, it proposes an original improved ADMM algorithm, named Relaxation-Based ADMM algorithm, to increase the optimization speed in large-scale cases. The experimental results show that the proposed method generally obtains a superior solution under a certain iteration count.

ABSTRACT In the situation of mass vaccination against COVID-19, few studies have reported on the early kinetics of specific antibodies (IgG/IgM/IgA) of vaccine breakthrough cases. There is still a lack of epidemiological evidence about the value of serological indicators in the auxiliary diagnosis of COVID-19 infection, especially when the nucleic acid results were undetectable. Omicron breakthrough cases post-inactivated vaccination (n = 456) and COVID-19-naive individuals with two doses of inactivated vaccination (n = 693) were enrolled. Blood samples were collected and tested for SARS-CoV-2 antibody levels based on the magnetic chemiluminescence enzyme immunoassay. Among Omicron breakthrough cases, the serum IgG antibody level was 36.34 Sample/CutOff (S/CO) (95% confidence interval [CI], 31.89 to 40.79) in the acute phase and 88.45 S/CO (95% CI, 82.79 to 94.12) in the recovery phase. Serum IgA can be detected in the first week post-symptom onset (PSO) and showed an almost linear increase within 5 weeks PSO. Compared with those of breakthrough cases, IgG and IgA titers of the postimmune group were much lower (4.70 S/CO and 0.46 S/CO, respectively). Multivariate regression showed that serum IgG and IgA levels in Omicron breakthrough cases were mainly affected by the weeks PSO (P

Digital microfluidic, as an emerging and potential technology, diversifies the biochemical applications platform, such as protein dilution sewage detection. At present, a vast majority of universal cyberphysical digital microfluidic biochips (DMFBs) transmit data through wires via personal computers and microcontrollers (like Arduino), consequently, susceptible to various security threats and with the popularity of wireless devices, losing competitiveness gradually. On the premise that security be ensured first and foremost, calls for wireless portable, safe, and economical DMFBs are imperative to expand their application fields, engage more users, and cater to the trend of future wireless communication. To this end, a new cyber-physical DMFB called PortableLab is proposed in this paper, which guarantees data security through wireless sensors at low cost. After considering the security, computing consumption, and cost, a mobile module is added. In addition, the improved Advanced Encryption Standard (AES) and Cyclic Redundancy Check (CRC) algorithms are utilized to ensure the integrity and confidentiality of data transmission. Ultimately, all the security analysis, cost analysis, and experimental results on multiple protocols demonstrate the feasibility of the proposed PortableLab DMFB in time and space.

In this research, we present a cooperative communication network based on two energy-harvesting (EH) decode-and-forward (DF) relays that contain the harvest-store-use (HSU) architecture and may harvest energy from the surrounding environment by utilizing energy buffers. To improve the performance of this network, an opportunistic routing (OR) algorithm is presented that takes into account channel status information, relay position, and energy buffer status, as well as using the maximal ratio combining (MRC) at the destination to combine the signals received from the source and relays. The theoretical expressions for limiting distribution of energy stored in infinite-size buffers are derived from the discrete-time continuous-state space Markov chain model (DCSMC). In addition, the theoretical expressions for outage probability, throughput, and per-packet time slot cost in the network are obtained utilizing both the limiting distributions of energy buffers and the probabilities of transmitter candidates set. Through numerous simulation results, it is demonstrated that simulation results match with corresponding theoretical results.

As modern vehicles become more intelligent and connected, the number of ECUs and communication interfaces with external networks (such as 3G/4G and Bluetooth) has increased significantly, which raises potential network security risks. Due to the absence of effective security measures, there is a frequent occurrence of cybersecurity incidents targeting vehicles, particularly the in-vehicle CAN bus network. As the main bus in the vehicle, the CAN bus faces important challenges in its safety due to the lack of security mechanisms. Therefore, we propose a CAN bus intrusion detection system based on multiple observation HMM for in-vehicle networks to enhance the security of the vehicle. Specifically, the proposed algorithm builds a multiple observation HMM-based on the ID and data fields of normal CAN bus traffic. According to the established HMMs, we calculate the existence probability of the frame under the defined time window as the detection threshold. When the existence probability of the frame to be detected exceeds the normal threshold range, it is considered abnormal. Furthermore, we establish four common attack models based on the collected real vehicle data and evaluate the performance of the proposed algorithm in these attack scenarios. The experimental results show that the proposed method has better detection performance than other frame-by-frame anomaly detection methods in four attack scenarios.

Traditional liquid-solid extraction methods for the removal of zinc ions (Zn(II)) were generally limited by the leakage of extractant and low extraction capacity. The two-component Pickering emulsion hydrogels (PEHGs) in which the synergistic 2-ethylhexyl hydrogen-2-ethylhexylphosphate/tributyl phosphate (EHEHPA/TBP) was encapsulated in a semi-penetrating polymer network (SIPN) structured hydrogels polyacrylamide/sodium alginate (PAM/SA) were prepared by the Pickering emulsions polymerization route. The PEHGs were characterized by FTIR, SEM, TGA, and tensile mechanical measurements, and their self-healing properties were explored. The adsorption performance of PEHGs on Zn(II) was investigated. The results showed that the encapsulation of the extractant reached 95% due to the hydrogels network and nano-silica (nano-SiO2) particle network in PEHGs-15. The critical crashing pressure of PEHGs-15 was 0.084 MPa, and the adsorption after 3 h of healing was only 86% of the original amount. The maximum adsorption capacity of PEHGs-15 on Zn(II) was 76.51 mg/g at pH 5. The functional groups of SA and EHEHPA/TBP enhanced the adsorption capacity of PEHGs-15 by chelating with Zn(II). After five adsorption-desorption cycles, the adsorption capacity of PEHGs-15 exceeded 85% of the initial one. The excellent mechanical properties, self-healing, and regenerative properties of PEHGs-15 offer the potential to remove Zn(II) from the solution. HIGHLIGHTS The two-component PEHGs based on Pickering emulsions were prepared to remove Zn(II) from the solution.; The introduction of SA and nano-SiO2 resulted in 95% encapsulation of extractants in PEHGs.; The synergistic extractant EHEHPA/TBP and PAM/SA in PEHGs-15 exhibited a high adsorption capacity of 76.51 mg/g for Zn(II).; After five adsorption-desorption cycles, the adsorption capacity of PEHGs-15 exceeded 85% of the initial one.;

Abstract Background Emphasizes the state of academic stress, social support, and self-regulatory fatigue on the physical and mental development of Chinese nursing students, the purpose of this study was to investigate the relationship between these variables and the mediating role of social support in academic stress and self-regulatory fatigue among a group of undergraduate nursing students in Heilongjiang Province, China, in order to provide a theoretical basis for working to reduce nursing students’ self-regulatory fatigue. Methods In this cross-sectional study, 1703 nursing students from various academic years completed the scales of social support, academic stress, and self-regulatory fatigue. In the end, there were 797 valid questionnaires, for a recovery rate of 46.80%. For statistical analysis, the independent t-test, Kruskal Wallis test, and Pearson correlation coefficient were used. In addition, we undertake analyses using structural equation modeling. Results The bulk of nursing students, or 81.4%, are between the ages of 19 and 21. Eighty percent were females. The bulk (93.0%) was comprised of freshmen. Academic stress, social support, and self-regulatory fatigue had total scores of 111.28 ± 29.38, 37.87 ± 6.70, and 45.53 ± 5.55,respectively. Academic stress was correlated with social support and self-regulatory fatigue (all p

Hypergraph, as a generalization of the notions of graph and simplicial complex, has gained a lot of attention in many fields. It is a relatively new mathematical model to describe the high-dimensional structure and geometric shapes of data sets. In this paper,we introduce the neighborhood hypergraph model for graphs and combine the neighborhood hypergraph model with the persistent (embedded) homology of hypergraphs. Given a graph,we can obtain a neighborhood complex introduced by L. Lovász and a filtration of hypergraphs parameterized by aweight function on the power set of the vertex set of the graph. Theweight function can be obtained by the construction fromthe geometric structure of graphs or theweights on the vertices of the graph. We show the persistent theory of such filtrations of hypergraphs. One typical application of the persistent neighborhood hypergraph is to distinguish the planar square structure of cisplatin and transplatin. Another application of persistent neighborhood hypergraph is to describe the structure of small fullerenes such as C20. The bond length and the number of adjacent carbon atoms of a carbon atom can be derived from the persistence diagram. Moreover, our method gives a highly matched stability prediction (with a correlation coefficient 0.9976) of small fullerene molecules.

Using Tianbao banana as the test material, one strain of Fusarium was isolated, purified and identified. Different concentrations (5, 10, 15, 20 mg/mL and 25 mg/mL) of camellia saponin were used to determine the inhibitory effect on Fusarium. The weight loss rate, hardness, soluble solids, titratable acid, respiratory strength and other main quality indicators of bananas treated with different concentrations of camellia saponin (15, 20, 25 mg/mL and 30 mg/mL) at a temperature of 16 ℃ and a relative humidity of 85% under constant temperature and humidity for 25 days were determined to study the effect of camellia saponin on bananas. The results showed that the antibacterial rate of camellia saponin against Fusarium continued to increase as the concentration increased. When the concentration of camellia saponin was 20 mg/mL, the antibacterial rate could reach 86.52%, but when the concentration increased again, the antibacterial rate did not increase significantly. On this basis, the MIC and MBC values of camellia saponin against Fusarium were determined to be 5 mg/mL and 10 mg/mL, respectively. Comprehensive quality indicators showed that the 20 mg/mL concentration of camellia saponin solution had the best preservation effect on post-harvest bananas. When stored for 20 days, compared with the control group (clear water group and positive control group), the weight loss rate was reduced by 48.04% and 51.67%, respectively. Compared with the control group (clear water group), soluble solids delayed the emergence of the peak value. Titratable acid increased by 56.09% and 23.07%, and respiratory intensity increased by 65.68% and 14.82%. On the 10th day of storage, the hardness increased by 13.76% compared with the positive control group. The results of the research are expected to provide certain theoretical and technical support for the preservation of bananas by camellia saponin.

Warm-season O3 pollution has been increasingly frequent worldwide in the past few years, exposing a threat to human health as well as the natural environment. Here, the authors showcase a stable MOF which can not only effectively capture various airborne VOCs, but decompose trace O3 in ambient air.

BackgroundAlthough cellular and animal studies have reported that resolvin D1 (RvD1) and resolvin D2 (RvD2) are mechanisms involved in the development of type 2 diabetes mellitus (T2DM), the impact of RvD1 and RvD2 on the risk of T2DM at a population level remains unclear.MethodsWe included 2755 non-diabetic adults from a community-based cohort in China and followed them for seven years. Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of RvD1 and RvD2 with T2DM probability. Time-dependent receiver operator characteristics (ROC) curve was used to evaluate the predictive performance of RvD1 and RvD2 for the risk of T2DM based on the Chinese CDC T2DM prediction model (CDRS).ResultsA total of 172 incident T2DM cases were identified. Multivariate-adjusted HRs (95% CI) for T2DM across quartiles of RvD1 levels (Q1, Q2, Q3 and Q4) were 1.00, 1.64 (1.03-2.63), 1.80 (1.13-2.86) and 1.61 (1.01-2.57), respectively. Additionally, body mass index (BMI) showed a significant effect modification in the association of RvD1 with incident T2DM (Pinteraction = 0.026). After multivariate adjustment, the HR (95% CI) for T2DM in the fourth compared with the first quartile of RvD2 was 1.94 (95% CI: 1.24-3.03). Time-dependent ROC analysis showed that the area under time-dependent ROC curves of the “CDRS+RvD1+RvD2” model for the 3-, 5- and 7-year risk of T2DM were 0.842, 0.835 and 0.828, respectively.ConclusionsHigher RvD1 and RvD2 levels are associated with a higher risk of T2DM at the population level.

In this work, a dynamic structured light 3D reconstruction method adapted to random phase shift step size is proposed for the problem of dynamic workpiece 3D reconstruction in industrial manufacturing scenes. The method firstly utilizes a structured light sinusoidal grating pattern to match the relative phase shift of the workpieces moving along the perpendicular direction of the stripes on the conveyor belt. Secondly, in order to solve the problem of non-uniform phase shift step length due to external vibration, electromagnetic radiation and other disturbing factors of the conveyor belt and other mechanical devices, the method proposes a dynamic structured light 3D reconstruction model based on RPSNet, which is based on the CycleGAN network model, and uses the AIR2U-net model proposed in this paper as the generator, and the multilayer convolutional neural network CNN as the discriminator to realize the grating map. discriminator to realize the conversion of raster map to depth map. Finally, for the problem that the network model needs a large amount of data for training and it is difficult to collect data in the actual industrial scene, this paper uses the Thing10k dataset, and the dataset made by Blender simulation software for model training. Finally, a higher quality 3D reconstruction of the workpiece is realized.

Electronic tickets (e-tickets) are gradually being adopted as a substitute for paper-based tickets to bring convenience to customers, corporations, and governments. However, their adoption faces a number of practical challenges, such as flexibility, privacy, secure storage, and inability to deploy on IoT devices such as smartphones. These concerns motivate the current research on e-ticket systems, which seeks to ensure the unforgeability and authenticity of e-tickets while simultaneously protecting user privacy. Many existing schemes cannot fully satisfy all these requirements. To improve on the current state-of-the-art solutions, this paper constructs a blockchain-enhanced privacy-preserving e-ticket system for IoT devices, dubbed PriTKT, which is based on blockchain, structure-preserving signatures (SPS), unlinkable redactable signatures (URS), and zero-knowledge proofs (ZKP). It supports flexible policy-based ticket purchasing and ensures user unlinkability. According to the data minimization and revealing principle of GDPR, PriTKT empowers users to selectively disclose subsets of (necessary) attributes to sellers as long as the disclosed attributes satisfy ticket purchasing policies. In addition, benefiting from the decentralization and immutability of blockchain, effective detection and efficient tracing of double spending of e-tickets are supported in PriTKT. Considering the impracticality of existing e-tickets schemes with burdensome ZKPs, we replace them with URS/SPS or efficient ZKP to significantly improve the efficiency of ticket issuing and make it suitable for use on smartphones.

Objective To explore the feasibility of establishing a computer-aided diagnostic model of multi-stained pathological images in patients with non-inflammatory aortic medial degeneration(MD). Methods In this study, pathological sections of aortic surgical specimens for non-inflammatory lesions from patients with thoracic aortic aneurysms and dissections were retrospectively collected at the Beijing Anzhen Hospital, Capital Medical University from July to December 2018. The lesions were scanned under ×400 magnification as whole slide images(WSI) and then annotated by two pathologists. The annotated WSI images were randomly split into training and test sets in a 6:1 ratio. SE-EmbraceNet was used to train the data to construct a multi-classification model for MD of multi-stained pathology images, including intralamellar mucoid extracellular matrix accumulation (MEMA-I), translamellar mucoid extracellular matrix accumulation (MEMA-T), elastic fiber fragmentation and/or loss(EFFL) and smooth muscle cell nuclei loss (SMCNL). The classification effect of the model was evaluated based on the test set data, and the results were expressed in terms of accuracy, sensitivity, precision, and the F1 value. Results Totally 530 pathological slides of non-inflammatory aortic lesion surgical specimens from patients with aortic aneurysm and dissection were included. Extracted 5265 sets of images, each containing 5 stained pathological images of the same lesion site: HE staining, special staining (elastic fiber/VanGieson, Masson, Alcian blue/periodic acid Schiff) and smooth muscle actin staining. There were 4513 sets of training images, including 987 SMCNL, 2013 EFFL, 1337 MEMA-I, and 176 MEMA-T; and 752 test images including 166 SMCNL, 335 EFFL, 222 MEMA-I, and 29 MEMA-T. The overall performance of the model in the test set showed good results, with an accuracy of 96.54%(726/752). The model had the best classification performance for EFFL, with accuracy, sensitivity, precision, and F1 value all ≥98.51%. The model also had a great classification ability for SMCNL, with all evaluated indexes≥97.59%. Conclusion The multi-stained pathology image-based MD classification model constructed in this study has high classification accuracy and good generalization ability, which has the potential to be applied to assist in the diagnosis of the non-inflammatory aortic lesion.