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Tomography has had an important impact on the physical, biological, and medical sciences. To date, most tomographic applications have been focused on 3D scalar reconstructions. However, in some crucial applications, vector tomography is required to reconstruct 3D vector fields such as the electric and magnetic fields. Over the years, several vector tomography methods have been developed. Here, we present the mathematical foundation and algorithmic implementation of REal Space Iterative REconstruction for Vector tomography, termed RESIRE-V. RESIRE-V uses multiple tilt series of projections and iterates between the projections and a 3D reconstruction. Each iteration consists of a forward step using the Radon transform and a backward step using its transpose, then updates the object via gradient descent. Incorporating with a 3D support constraint, the algorithm iteratively minimizes an error metric, defined as the difference between the measured and calculated projections. The algorithm can also be used to refine the tilt angles and further improve the 3D reconstruction. To validate RESIRE-V, we first apply it to a simulated data set of the 3D magnetization vector field, consisting of two orthogonal tilt series, each with a missing wedge. Our quantitative analysis shows that the three components of the reconstructed magnetization vector field agree well with the ground-truth counterparts. We then use RESIRE-V to reconstruct the 3D magnetization vector field of a ferromagnetic meta-lattice consisting of three tilt series. Our 3D vector reconstruction reveals the existence of topological magnetic defects with positive and negative charges. We expect that RESIRE-V can be incorporated into different imaging modalities as a general vector tomography method. To make the algorithm accessible to a broad user community, we have made our RESIRE-V MATLAB source codes and the data freely available at https://github.com/minhpham0309/RESIRE-V .

The precision of stereopsis and vergence are ultimately limited by internal binocular disparity noise. Here we propose an equivalent noise model with both global and local internal disparity noises to provide a unified explanation of both absolute and relative disparity thresholds. To test this model, we developed a psychophysical procedure to measure the equivalent internal disparity noise by adding external disparity noise to random-Gabor-patch stereograms. We used the method of constant stimuli to measure the minimum and maximum disparity thresholds (Dmin and Dmax) for both absolute and relative disparity. Consistent with previous studies, we found that Dmin thresholds are substantially worse for absolute disparity than for relative disparity. We tested three relative disparity mechanisms: (1) the difference between the monocular separations of targets projecting to the two eyes; (2) the direct measurement of relative disparity; and (3) the difference of absolute disparities of targets. Computing the difference of absolute disparities when detecting relative disparity, Mechanism 3 cancels global noise, resulting in a much lower relative Dmin threshold, and provides a reasonable fit to the experimental data. We also found that the presence of as much as 2400 arcsec of external disparity noise does not appear to affect the Dmax threshold. This observation suggests that Dmax is implicated in a mechanism that disregards the disparity variance of individual items, relying instead on the average disparity across all items, supporting the depth model proposed in our previous study (Ding & Levi, 2021), which posits distinct mechanisms governing Dmin and Dmax thresholds.

Abstract Single-layer isophorone diisocyanate (IPDI) are one of the most popular self-healing microcapsules but suffers from low shell strength, poor heat resistance, stability and aging properties. In this paper, IPDI microcapsules were encapsulated into double-layer phenolic (PF)/polyurethane (PU) by a two-step process involving interfacial polymerization and in-situ polymerization. The prepared microcapsule composites were comprehensively characterized for their physical and chemical properties using optical microanalysis, scanning electron microscope, Fourier transform infrared spectroscopy, thermal gravimetric analysis and depth-sensing indentation analysis. Compared with the single-layer PU-IPDI microcapsule counterpart, the mechanical performance, thermal resistance, aging property and environmental stability of double-layer PF/PU-IPDI microcapsules were significantly improved. The epoxy coating was enhanced with the incorporation of 10 wt.% PF/PU-IPDI microcapsules, whose self-healing performance was evaluated by scratch corrosion test. The results demonstrated successful repair of coating scratches, along with the absence of corrosion on the coated steel substrate soaked in a 10 wt.% NaCl solution for 7 days. By comparing the tensile strength of epoxy coating before and after crack formation, it could be found that the self-healing efficiency was 57.9% when loaded with 10 wt.% of PF/PU-IPDI microcapsules in coating. This study highlights that the rational design of double-layer microcapsules integrated into the epoxy coating matrix could provide excellent anti-corrosion and self-healing properties.

Abstract The marine ecological red lines (MERLs) is an institutional innovation of the Chinese government to seek a balance between ecological protection and social development. China’s MERLs was designated in 2017, but there are problems such as insufficient consideration of areas of high ecological importance and lack of convergence with marine functional zoning. This paper carries out the adjustment of the MERLs in China by constructing the methods of marine ecological importance assessment and human activities disposal assessment, and the results show that after the adjustment, the type and distribution pattern of China’s MERLs is more reasonable, the areas of high ecological importance in the MERLs increases significantly, the intensity of human activities in the MERLs declines significantly, and the unification with the use of marine space is realized. China’s adjustment of the MERLs is based on scientific assessment and realizes the coordination of development and protection, which can provide a reference for global marine ecological protection.

Abstract Few studies have focused on the risk factors for necrotizing enterocolitis (NEC) in small for gestational age (SGA) infants. The aim of this study was to identify the risk factors for NEC in SGA newborns. This study included consecutive SGA neonates admitted to a tertiary hospital in Jiangxi Province, China from Jan 2008 to Dec 2022. Patients with NEC (Bell’s stage ≥ II) were assigned to the NEC group. Gestational age- and birth weight-matched non-NEC infants born during the same period at the same hospital were assigned to the control group. The risk factors associated with NEC were analyzed with univariate and logistic regression models. During the study period, 2,912 SGA infants were enrolled, 150 (5.15%) of whom developed NEC. In total, 143 patients and 143 controls were included in the NEC and control groups, respectively. Logistic regression analysis revealed that sepsis (OR 2.399, 95% CI 1.271–4.527, P = 0.007) and anemia (OR 2.214, 95% CI 1.166–4.204, P = 0.015) might increase the incidence of NEC in SGA infants and that prophylactic administration of probiotics (OR 0.492, 95% CI 0.303–0.799, P = 0.004) was a protective factor against NEC. Therefore, sepsis, anemia and a lack of probiotic use are independent risk factors for NEC in SGA infants.

Abstract The aim of this study was to investigate the overall effects of phototherapy on biopterin (BH4), neopterin (BH2), tryptophan (Trp), and behavioral neuroinflammatory reaction in patients with post-stroke depression. There involved a total of 100 hospitalized patients with post-stroke depression at our hospital from February 2021 to December 2022. The participants enrolled were randomly assigned to either the control group or the experimental group. The control group received routine treatment, including medication and psychological support, while the experimental group received 30 min of phototherapy daily for 8 weeks. All participantsvoluntarily participated in the study and provided informed consent. Baseline characteristics of the patients were statistically analyzed. The severity of depressive symptoms was evaluated using the hamilton depression scale (HAMD) and the beck depression inventory (BDI). Levels of amino acid neurotransmitters, including gamma-aminobutyric acid (GABA), aspartic acid (Asp), and glutamic acid (Glu), were measured using radioimmunoassay. Plasma levels of neuroinflammatory factors, such as TNF-α, IL-6, and IL-1β were, determined using ELISA. Plasma levels of BH4, BH2, and Trp were detected by HPLC. Levels of SOD, GPx, CAT, and MDA in plasma were measured using corresponding kits and colorimetry. Quality of life was assessed using the SF-36 scale. There were no differences in baseline characteristic between the two groups (P > 0.05). The HAMD and BDI scores in the experimental group were lower than those in the control group (P

Abstract There is no reliable causal evidence for the effect of statins on diabetic nephropathy (DN) and diabetic retinopathy (DR), and the results of previous observational studies are contradictory. Genetic variants linked to low-density lipoprotein cholesterol (LDL-C) from a UK biobank genome-wide association study and located within a 100kb window around HMGCR were used to proxy statins, comparing with PCSK9 inhibitors (control). DN and DR genome-wide association study summary statistics were obtained from the FinnGen study. Secondary MR analyses and NHANES cross-sectional data were used for validation. Drug-target Mendelian randomization (MR) was applied to investigate the association between the genetically proxied inhibition of HMGCR and PCSK9 with DN and DR, p

Abstract This study explores disparities and opportunities in healthcare information provided by AI chatbots. We focused on recommendations for adjuvant therapy in endometrial cancer, analyzing responses across four regions (Indonesia, Nigeria, Taiwan, USA) and three platforms (Bard, Bing, ChatGPT-3.5). Utilizing previously published cases, we asked identical questions to chatbots from each location within a 24-h window. Responses were evaluated in a double-blinded manner on relevance, clarity, depth, focus, and coherence by ten experts in endometrial cancer. Our analysis revealed significant variations across different countries/regions (p

Abstract Nutrition is a limiting feature of species evolution. The differences in nutritional requirements are the evolutionary result of differential adaptations to environmental changes, explaining differences in their ecological traits. Cnaphalocrocis medinalis and Cnaphalocrocis exigua, two related species of rice leaffolders, have similar morphology and feeding properties but different migration and overwintering behaviors. However, it is unclear whether they have evolved adult nutritional differentiation traits to coexist. To explore this issue, this study examined the effects of carbohydrates and amino acids on their reproductive and demographic parameters. The findings indicate that carbohydrate intake prolonged the longevity and population growth of two rice leaffolders, but amino acid intake promoted egg hatching only. However, nutrient deficiency made it impossible for C. medinalis to reproduce successfully and survive, but it did not affect C. exigua. The population expansion and survival of migratory C. medinalis relied on adult nutritional intake. Conversely, the nutrients necessary for C. exigua overwintering activity mostly came from the storage of larvae. The difference in nutritional requirements for population growth and survival between the two rice leaffolders partially explained their differences in migration and overwintering.

Abstract Diffusion Kurtosis Imaging (DKI)-derived metrics are recognized as indicators of maturation in neonates with low-grade germinal matrix and intraventricular hemorrhage (GMH-IVH). However, it is not yet known if these factors are associated with neurodevelopmental outcomes. The objective of this study was to acquire DKI-derived metrics in neonates with low-grade GMH-IVH, and to demonstrate their association with later neurodevelopmental outcomes. In this prospective study, neonates with low-grade GMH-IVH and control neonates were recruited, and DKI were performed between January 2020 and March 2021. These neonates underwent the Bayley Scales of Infant Development test at 18 months of age. Mean kurtosis (MK), radial kurtosis (RK) and gray matter values were measured. Spearman correlation analyses were conducted for the measured values and neurodevelopmental outcome scores. Forty controls (18 males, average gestational age (GA) 30 weeks ± 1.3, corrected GA at MRI scan 38 weeks ± 1) and thirty neonates with low-grade GMH-IVH (13 males, average GA 30 weeks ± 1.5, corrected GA at MRI scan 38 weeks ± 1). Neonates with low-grade GMH-IVH exhibited lower MK and RK values in the PLIC and the thalamus (P

Abstract The potential long-term effects of anesthesia on cognitive development, especially in neonates and infants, have raised concerns. However, our understanding of its underlying mechanisms and effective treatments is still limited. In this study, we found that early exposure to isoflurane (ISO) impaired fear memory retrieval, which was reversed by dexmedetomidine (DEX) pre-treatment. Measurement of c-fos expression revealed that ISO exposure significantly increased neuronal activation in the zona incerta (ZI). Fiber photometry recording showed that ZI neurons from ISO mice displayed enhanced calcium activity during retrieval of fear memory compared to the control group, while DEX treatment reduced this enhanced calcium activity. Chemogenetic inhibition of ZI neurons effectively rescued the impairments caused by ISO exposure. These findings suggest that the ZI may play a pivotal role in mediating the cognitive effects of anesthetics, offering a potential therapeutic target for preventing anesthesia-related cognitive impairments.

Abstract Many patients with diabetes struggle with post-meal high blood glucose due to missed or untimely meal-related insulin doses. To address this challenge, our research aims to: (1) study mealtime patterns in patients with type 1 diabetes using wearable insulin pump data, and (2) develop personalized models for predicting future mealtimes to support timely insulin dose administration. Using two independent datasets with over 45,000 meal logs from 82 patients with diabetes, we find that the majority of people ( $$\sim$$ ∼ 60%) have irregular and inconsistent mealtime patterns that change notably through the course of each day and across months in their own historical data. We also show the feasibility of predicting future mealtimes with personalized LSTM-based models that achieve an average F1 score of > 95% with less than 0.25 false positives per day. Our research lays the groundwork for developing a meal prediction system that can nudge patients with diabetes to administer bolus insulin doses before meal consumption to reduce the occurrence of post-meal high blood glucose.

Abstract Programming cell signaling during T-cell activation represents a simple strategy for improving the potency of therapeutic T-cell products. Stim-R technology (Lyell Immunopharma) is a customizable, degradable synthetic cell biomimetic that emulates physiologic, cell-like presentation of signal molecules to control T-cell activation. A breadth of Stim-R formulations with different anti-CD3/anti-CD28 (αCD3/αCD28) antibody densities and stoichiometries were screened for their effects on multiple metrics of T-cell function. We identified an optimized formulation that produced receptor tyrosine kinase-like orphan receptor 1 (ROR1)-targeted chimeric antigen receptor (CAR) T cells with enhanced persistence and polyfunctionality in vitro, as assessed in repeat-stimulation assays, compared with a benchmark product generated using a conventional T-cell–activating reagent. In transcriptomic analyses, CAR T cells activated with Stim-R technology showed downregulation of exhaustion-associated gene sets and retained a unique subset of stem-like cells with effector-associated gene signatures following repeated exposure to tumor cells. Compared with the benchmark product, CAR T cells activated using the optimized Stim-R technology formulation exhibited higher peak expansion, prolonged persistence, and improved tumor control in a solid tumor xenograft model. Enhancing T-cell products with Stim-R technology during T-cell activation may help improve therapeutic efficacy against solid tumors.

Abstract This study aimed to compare the effects of a 6-week upper body plyometric training (UBPT) on maximal strength and anaerobic power performance of male and female subjects. Forty collegiate physically active male and female subjects participated in the study and were assigned to either UBPT group (M-UBPT, n = 10, F-UBPT, n = 10) or control group (M-CON, n = 10; F-CON, n = 10). The training groups performed 6 weeks of progressive overload UBPT three times per week using six exercises and were evaluated for upper-body anaerobic power and maximal strength, 3-kg medicine ball throw (MBT), push-up endurance, and reaction time at pre- and post-intervention. After the training intervention, the M-CON and F-CON groups did not show significant (p > 0.05) changes in the variables, while both the M-UBPT and F-UBPT groups demonstrated significant (p = 0.001) medium to very large improvements in their performance as follows: maximal strength (effect size [ES] = 0.55, 0.92), MBT (ES = 1.96, 0.89) peak power output (ES = 2.31, 1.52), mean power output (ES = 2.19, 1.11), push-up endurance (ES = 1.26, 0.70), and reaction time (ES = − 2.16, − 1.56), respectively. Nevertheless, the male group experienced more significant improvements in the MBT (p = 0.001), peak (p = 0.001) and mean power output (p = 0.01), as well as reaction time (p = 0.01) compared to the female group when utilizing UBPT. In conclusion, it is imperative to take sex into account as a crucial factor when incorporating UBPT, particularly if the objective is to enhance anaerobic power output, muscular power, and reaction time.

Abstract In this study, we successfully established a novel gallbladder cancer cell line, designated as GBC-X1, derived from a primary tumor of a gallbladder cancer patient. By comprehensively analyzing the cell line’s phenotype, molecular characteristics, biomarkers, and histological characteristics, we confirmed that GBC-X1 serves as a valuable model for investigating the pathogenesis of gallbladder cancer and developing therapeutic agents. GBC-X1 has been continuously cultured for one year, with over 60 stable passages. Morphologically, GBC-X1 exhibits typical features of epithelial tumors. The population doubling time of GBC-X1 is 32 h. STR analysis validated a high consistency between GBC-X1 and the patient’s primary tumor. Karyotype analysis revealed an abnormal hypertetraploid karyotype for GBC-X1, characterized by representative karyotypes of 98, XXXX del (4) p (12) del (5) p (21) der (10). Under suspension culture conditions, GBC-X1 efficiently forms tumor balls, while subcutaneous inoculation of GBC-X1 cells into NXG mice leads to xenograft formation with a rate of 80%. Drug sensitivity testing demonstrated that GBC-X1 is resistant to oxaliplatin and sensitive to 5-FU, gemcitabine, and paclitaxel. Immunohistochemistry revealed positive expression of CK7, CK19, E-cadherin, MMP-2, CD44, SOX2, and TP53 in GBC-X1 cells, weak positive expression of Vimentin, and a Ki67 positive rate of 35%. Our research highlights GBC-X1 as a novel gallbladder cancer cell line and emphasizes its potential as an effective experimental model for investigating the pathogenesis of gallbladder cancer and drug development.

Abstract The escalating frequency of environmental pollution incidents has raised significant concerns regarding the potential health impacts of pollutant fluctuations. Consequently, a comprehensive study on the role of pollutants in the prevalence of viral hepatitis is indispensable for the advancement of innovative prevention strategies. Monthly incidence rates of viral hepatitis from 2005 to 2020 were sourced from the Chinese Center for Disease Control and Prevention Infectious Disease Surveillance Information System. Pollution data spanning 2014–2020 were obtained from the National Oceanic and Atmospheric Administration (NOAA), encompassing pollutants such as CO, NO2, and O3. Time series analysis models, including seasonal auto-regressive integrated moving average (SARIMA), Holt-Winters model, and Generalized Additive Model (GAM), were employed to explore prediction and synergistic effects related to viral hepatitis. Spearman correlation analysis was utilized to identify pollutants suitable for inclusion in these models. Concurrently, machine learning (ML) algorithms were leveraged to refine the prediction of environmental pollutant levels. Finally, a weighted quantile sum (WQS) regression framework was developed to evaluate the singular and combined impacts of pollutants on viral hepatitis cases across different demographics, age groups, and environmental strata. The incidence of viral hepatitis in Beijing exhibited a declining trend, primarily characterized by HBV and HCV types. In predicting hepatitis prevalence trends, the Holt-Winters additive seasonal model outperformed the SARIMA multiplicative model ((1,1,0) (2,1,0) [12]). In the prediction of environmental pollutants, the SVM model demonstrated superior performance over the GPR model, particularly with Polynomial and Besseldot kernel functions. The combined pollutant risk effect on viral hepatitis was quantified as βWQS (95% CI) = 0.066 (0.018, 0.114). Among different groups, PM2.5 emerged as the most sensitive risk factor, notably impacting patients with HCV and HEV, as well as individuals aged 35–64. CO predominantly affected HAV patients, showing a risk effect of βWQS (95% CI) = − 0.0355 (− 0.0695, − 0.0016). Lower levels of PM2.5 and PM10 were associated with heightened risk of viral hepatitis incidence with a lag of five months, whereas elevated levels of PM2.5 (100–120 μg/m3) and CO correlated with increased hepatitis incidence risk with a lag of six months. The Holt-Winters model outperformed the SARIMA model in predicting the incidence of viral hepatitis. Among machine learning algorithms, SVM and GPR models demonstrated superior performance for analyzing pollutant data. Patients infected with HAV and HEV were primarily influenced by PM10 and CO, whereas SO2 and PM2.5 significantly impacted others. Individuals aged 35–64 years appeared particularly susceptible to these pollutants. Mixed pollutant exposures were found to affect the development of viral hepatitis with a notable lag of 5–6 months. These findings underscore the importance of long-term monitoring of pollutants in relation to viral hepatitis incidence.

Abstract Porcine pasteurellosis is an infectious disease caused by Pasteurella multocida (P. multocida), which seriously endangers the healthy development of pig breeding industry. Early detection of disease transmission in animals is a crucial early warning for humans. Therefore, predicting risk areas for disease is essential for public health authorities to adopt preventive measures and control strategies against diseases. In this study, we developed a predictive model based on multi-criteria decision analysis (MCDA) and assessed risk areas for porcine pasteurellosis in the Chinese mainland. By using principal component analysis, the weights of seven spatial risk factors were determined. Fuzzy membership function was used to standardize all risk factors, and weight linear combination was used to create a risk map. The sensitivity of the risk map was analyzed by calculating the mean of absolute change rates of risk factors, as well as calculating an uncertainty map. The results showed that risk areas for porcine pasteurellosis were predicted to be locate in the south-central of the Chinese mainland, including Sichuan, Chongqing, Guangdong, and Guangxi. The maximum standard deviation of the uncertain map was less than 0.01and the ROC results showed that the prediction model has moderate predictive performance with the area under the curve (AUC) value of 0.80 (95% CI 0.75–0.84). Based on the above process, MCDA was combined with WebGIS technology to construct a system for predicting risk areas of porcine pasteurellosis. Risk factor data was directly linked to the developed model, providing decision support for disease prevention and control through monthly updates.

Abstract A sense of belonging to a community is a dimension of subjective well-being that is of growing population health interest. We evaluated sex-stratified associations between community belonging and risk of avoidable hospitalization. Adult men and women from the Canadian Community Health Survey (2000–2014) were asked to rate their sense of community belonging (N = 456,415) and were also linked to acute inpatient hospitalizations to 31 March 2018. We used Cox proportional hazards models to assess the association between community belonging and time to hospitalization related to ambulatory care sensitive conditions (ACSCs) and adjusted for a range of sociodemographic, health, and behavioural confounders. Compared to those who reported intermediate levels of belonging, both very weak and very strong sense of belonging were associated with greater risk of avoidable hospitalization for women (HR 1.29, 95% CI 1.12, 1.47, very weak; HR 1.15, 95% CI 1.03, 1.27, very strong), but not for men (HR 1.12, 95% CI 0.97, 1.29, very weak; HR 1.08, 95% CI 0.98, 1.19, very strong). This study suggests that community belonging is associated with risk of ACSC hospitalization for women and provides a foundation for further research on community belonging and population health.

Abstract Bridge construction collapse is one of the most common bridge safety accidents. At present, evaluation results are often affected by the ability and experience of the assessor. Therefore, it is difficult to quickly, accurately and effectively evaluate the risk in the process of bridge construction. Moreover, key factors that can prevent accidents can hardly find from the existing bridge construction safety management and evaluation method. This paper analyzes and classifies the artificial and environmental risk factors that affect the bridge construction stage, and establishes 26 risk factors in 5 categories according to the characteristics of bridge construction and the actual situation of the project. Random forest (RF) algorithm is a non-parametric machine learning method based on decision tree, which does not need to be scored by experts in advance and avoids the influence of subjective factors. Compared with other analysis methods, random forest algorithm has the advantages of accurate and robust risk assessment results. Based on the advantages of random forest algorithm and the characteristics of bridge construction risk, this paper uses random forest algorithm to evaluate the bridge construction risk, and ranks the importance of indicators, and identify the index that has a greater influence on the risk. In order to verify the applicability and feasibility of the proposed method, a typical urban complex pedestrian bridge was taken as an example for actual engineering evaluation and verification. The results obtained are basically consistent with the actual risk assessment results of the pedestrian bridge.

Abstract Primary dysmenorrhea (PD) is a common global health concern. However, limited studies explored the association between soft drinks intake and PD among female undergraduates in China. To determine the association between soft drinks (carbonated soft drinks, etc.) as well coffee intake and the incidence/severity of PD among female undergraduates in China. We performed a cross-sectional study among 1809 female undergraduates in China from September 29, 2020 to October 22, 2020. The demographic information and menstrual information of the participants were collected by a self-administrated questionnaire. Chi-square test, ANOVA test, and logistic regression test were used to investigate the association between soft drinks intake and the incidence/severity of PD. We also conducted stratification analysis among different locations (rural or urban). The prevalence of PD was 47.1% (n = 852). There were 221 (25.9%) participants suffered from severe pain. In the participants with PD, the OR of carbonated soft drinks intake was 1.244 (95% CI 1.010–1.533). Among the participants with PD from rural areas, the OR of carbonated soft drinks intake was 1.402 (95% CI 1.045–1.881), compared with the non-carbonated soft drink group. In the participants with moderate and severe PD, the OR of coffee intake was 0.451 (95% CI 0.228–0.892), compared with the non-coffee-drinking group. There was a significant association between carbonated soft drinks intake frequency and the severity of PD (P

Abstract Optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) have the potential application in evaluating pathological structural change of the optic nerve. We aimed to evaluate the value of the OCT and OCTA parameters of the optic disk and macular in differentiating early chronic primary angle-closure glaucoma (CPACG) and early pituitary adenoma (PA) in case of mild visual field defects (the mean defect (MD) > 6 dB). The results showed that regarding OCTA parameters, CPACG patients had lower retinal blood flow density of most layers of the optic disk and macular than PA patients. Regarding OCT parameters, CPACG patients had thinner circumpapillary retinal nerve fiber layer (CP-RNFL) in all quadrants and average CP-RNFL, ganglion cell layer (GCL) and macular ganglion cell complex (GCC) in each quadrant of macular inner and outer rings, and inner plexus layer (IPL) of macular inner ring, superior-outer ring and temporal-outer ring than PA patients. The Z test indicated that OCTA parameters and OCT parameters had similar value in the diagnosis of disease. In conclusion, in the case of similar visual field damage, early CPACG patients have smaller blood flow density and thinner optic disk and macular than early PA. OCTA has similar performance to OCT in diagnosing CPACG and PA.

Abstract The blockage and the deformation and failure of the ore pass walls constitute two major problems in applying the ore passes in mines. These problems, which affect the normal operation of mine production, have attracted widespread attention worldwide. The labeled-particle layers method based on numerical simulation was used to investigate the flow characteristics of the ore-rock bulk in the ore pass under different eccentric distances of the ore-drawing port center and ore pass centerline. Moreover, the overpressure coefficient and overpressure number are used to evaluate the degree of damage to the ore-pass wall. The results show that: (1) During the ore drawing process under different eccentricities, the flow patterns of the topmost labeled-particle layers in the ore pass are always in a “—” shaped distribution, and the other layers in the ore pass gradually transition from a “—” shape to a “U” shaped distribution, and then gradually to a “V” shape closer to the drawing funnel; (2) in the range of the ore-drawing funnel, the flow pattern of the ore-rock bulk gradually changes from an upright “V” shape to an italic “V” shape with increasing eccentricity and tip slants to the drawing port, and is less affected in the shaft; and (3) the dynamic lateral pressure caused by the ore-rock flow mainly acts on the lower part of the storage section. When the eccentricity is 0.5 m, the maximum overpressure coefficient and overpressure times are the smallest, leading to the lowest damage degree of the ore pass wall.

Abstract The identification and classification of various phenotypic features of Auricularia cornea fruit bodies are crucial for quality grading and breeding efforts. The phenotypic features of Auricularia cornea fruit bodies encompass size, number, shape, color, pigmentation, and damage. These phenotypic features are distributed across various views of the fruit bodies, making the task of achieving both rapid and accurate identification and classification challenging. This paper proposes a novel multi-view multi-label fast network that integrates two different views of the Auricularia cornea fruiting body, enabling rapid and precise identification and classification of six phenotypic features simultaneously. Initially, a multi-view feature extraction model based on partial convolution was constructed. This model incorporates channel attention mechanisms to achieve rapid phenotypic feature extraction of the Auricularia cornea fruiting body. Subsequently, an efficient multi-task classifier was designed, based on class-specific residual attention, to ensure accurate classification of phenotypic features. Finally, task weights were dynamically adjusted based on heteroscedastic uncertainty, reducing the training complexity of the multi-task classification. The proposed network achieved a classification accuracy of 94.66% and an inference speed of 11.9 ms on an image dataset of dried Auricularia cornea fruiting bodies with three views and six labels. The results demonstrate that the proposed network can efficiently and accurately identify and classify all phenotypic features of Auricularia cornea.

Abstract With the increase in high-rise buildings in cities, public flue exhaust systems have a direct impact on residential air quality and the living environment. Although existing studies have analyzed the problems in public flue exhaust systems through computational fluid dynamics (CFD) numerical simulations and experimental tests, these studies often lack an in-depth exploration of the specific impacts of individual components in the system. To solve this problem, this study not only thoroughly analyzes the key components in the public flue system, such as branch pipes, check valves, and tee pipes, but also develops a parametric public flue simulation system software based on C# and verifies the accuracy of the simulation through experiments. The study first determines the key parameters affecting the comprehensive resistance coefficient of the branch pipe, check valve, tee pipe, and other components through CFD simulation and experimental testing. Subsequently, a visualization program is developed using the C# language, which can quickly simulate and visualize the flow changes in the flue according to different building parameters such as the number of floors, height of floors, and size of the flue. The results confirm that the program can efficiently predict the flow distribution under different design options, providing a practical tool for the optimal design and performance evaluation of public flues, which is important for improving the air quality of the living environment.

Abstract Human activities have profound impacts on land use and the supply–demand balance of ecosystem services (ESs). Various activities, such as urban construction, urban and rural planning, and inter-basin water transfer projects, continuously reshape land use patterns. This is a case study of the Anhui section of the Yangtze-Huaihe Water Diversion Project. Data from 2000, 2010, and 2020 is analyzed. Additionally, the patch-generating land use simulation (PLUS) model is utilized to quantify the specific impacts of the water diversion project construction on the supply and demand of ESs. The results indicate that the comprehensive dynamic attitude of land use during the project construction period significantly increased, rising from 0.16 to 13.79%, and mainly affected forest, water areas, construction land, and unused land. Specifically, the construction of the project led to significant changes in water purification, biodiversity, and, especially, hydrological regulation services. Additionally, the migration of residents significantly impacted the demand for ESs. The study also found a significant correlation between land use changes and the balance of ES supply and demand: the proportion of cultivated land and construction land is positively correlated with the balance, while the proportion of forest, grassland, and water areas is negatively correlated. This study provides empirical data for understanding the environmental and socio-economic impacts of large-scale water diversion projects and offers a scientific basis for local mitigation and control of adverse impacts. Through quantitative analysis and model prediction, this research effectively bridges the gap between theory and practice, providing important references for sustainable regional development.

Abstract Episodic memory is essential for forming and retaining personal experiences, representing a fundamental aspect of human cognition. Traditional studies of episodic memory have typically used static analysis methods, viewing the brain as an unchanging entity and overlooking its dynamic properties over time. In this study, we utilized dynamic functional connectivity analysis on fMRI data from healthy adults performing an episodic memory task. We quantified integration and recruitment metrics and examined their correlation with memory performance using Pearson correlation. During encoding, integration across the entire brain, especially within the frontoparietal subnetwork, was significantly correlated with memory performance. During retrieval, recruitment becomes significantly associated with memory performance in visual subnetwork, somatomotor subnetwork, and ventral attention subnetwork. At the nodal level, a significant negative correlation was observed between memory scores and integration of the anterior cingulate gyrus, precentral gyrus, and inferior frontal gyrus within the frontoparietal network during encoding task. During retrieval task, a significant negative correlation was found between memory scores and recruitment in the left progranular cortex and right transverse gyral ventral, whereas positive correlations were seen in the right posterior inferior temporal, left middle temporal, right frontal operculum, and left operculum nodes. Moreover, the dynamic reconfiguration of the functional network was predictive of predict memory performance, as demonstrated by a significant correlation between actual and predicted memory scores. These findings advance our understanding network mechanisms underlying memory processes and developing intervention approaches for memory-related disorders as they shed light on critical factors involved in cognitive processes and provide a deeper understanding of the underlying mechanisms driving cognitive function.

Abstract With the rapid advancement of drone technology and the growing applications in the field of drone engineering, the demand for precise and efficient path planning in complex and dynamic environments has become increasingly important. Traditional algorithms struggle with complex terrain, obstacles, and weather changes, often falling into local optima. This study introduces an Improved Crown Porcupine Optimizer (ICPO) for drone path planning, which enables drones to better avoid obstacles, optimize flight paths, and reduce energy consumption. Inspired by porcupines' defense mechanisms, a visuo-auditory synergy perspective is adopted, improving early convergence by balancing visual and auditory defenses. The study also employs a good point set population initialization strategy to enhance diversity and eliminates the traditional population reduction mechanism. To avoid local optima in later stages, a novel periodic retreat strategy inspired by porcupines' precise defenses is introduced for better position updates. Analysis on the IEEE CEC2022 test set shows that ICPO almost reaches the optimal value, demonstrating robustness and stability. In complex mountainous terrain, ICPO achieved optimal values of 778.1775 and 954.0118; in urban terrain, 366.2789 and 910.1682 and ranked first among the compared algorithms, proving its effectiveness and reliability in drone delivery path planning. Looking ahead, the ICPO will provide greater efficiency and safety for drone path planning in navigating complex environments.

Abstract The aim of this study was to explore the related factors linked to the development and infectivity of tuberculosis. This was achieved by comparing the clinical characteristics of patients with pulmonary tuberculosis (TB) who tested positive in smear Mycobacterium tuberculosis tests with this who tested negative in smear mycobacterium tests but positive in sputum Gene Xpert tests. We gathered clinical data of 1612 recently hospitalized patients diagnosed with pulmonary tuberculosis who tested positive either in sputum Gene-Xpert test or sputum smear Mycobacterium tuberculosis tests. The data was collected from January 1, 2018 to August 5, 2023, at Sichuan Provincial People's Hospital. We conducted separately analyzes and comparisons of the clinical characteristics between the two groups of patients, aiming to discussed the related factors influencing the development and infectivity of tuberculosis. In comparison to the GeneXpert positive group, the sputum smear positive group exhibited a higher proportion of elderly patients (aged 75–89) and individuals classified as underweight (BMI