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Abstract Using ultrasound findings and clinical characteristics, we constructed and validated a new nomogram for distinguishing epididymal tuberculosis from nontuberculous epididymitis, both of which share similar symptoms. We retrospectively examined data of patients with epididymal tuberculosis and nontuberculous epididymitis hospitalized between January 1, 2013, and March 31, 2023. Eligible patients were randomly assigned to derivation and validation cohorts (ratio, 7:3). We drew a nomogram to construct a diagnostic model through multivariate logistic regression and visualize the model. We used concordance index, calibration plots, and decision curve analysis to assess the discrimination, calibration, and clinical usefulness of the nomogram, respectively. In this study, 136 participants had epididymal tuberculosis and 79 had nontuberculous epididymitis. Five variables—C-reactive protein level, elevated scrotal skin temperature, nodular lesion, chronic infection, and scrotal skin ulceration—were significant and used to construct the nomogram. Concordance indices of the derivation and validation cohorts were 0.95 and 0.96, respectively (95% confidence intervals, 0.91–0.98 and 0.92–1.00, respectively). Decision curve analysis of this nomogram revealed that it helped differentiate epididymal tuberculosis from nontuberculous epididymitis. This nomogram may help clinicians distinguish between epididymal tuberculosis and nontuberculous epididymitis, thereby increasing diagnosis accuracy.

Our research is dedicated to combating HIV by targeting its Matrix (MA) domain, which is crucial for viral assembly and replication. This strategy specifically aims to interrupt early-stage infection and deter drug resistance by focusing on this essential domain. Due to the MA domain’s conservation across different HIV strains, our approach promises broad-spectrum efficacy, which is particularly crucial in regions marked by significant genetic diversity and resistance issues. In our study, we introduce CNP0269688, a natural product that exhibits high affinity for the HIV-1 Matrix. Through detailed molecular dynamics simulations, we have assessed the compound’s structural stability and interaction dynamics, particularly its potential to hinder Protein-tRNA interactions. This analysis lays the groundwork for future experimental investigations. Our efforts are steps toward enhancing HIV treatment, reducing viral transmission, and curbing drug resistance, with the ultimate aim of controlling and eradicating the pandemic, thereby contributing significantly to public health and scientific advancement.

Abstract Precise energy management in distribution power system requires high‐precision time synchronization among large‐scale deployed devices. Multiple clock sources‐based time synchronization possesses advantages of reliability, high precision, and robustness, but still faces several challenges such as coupling between time synchronization error and delay, as well as different timescales between clock source and clock weight optimization. In this paper, a multi‐clock source time synchronization model is constructed and a problem is formulated to minimize the synchronization error and delay through jointly optimizing large‐timescale clock source selection and small‐timescale weight selection. A reinforcement learning‐based multi‐timescale multi‐clock source time synchronization algorithm named RL‐M2 is proposed to solve the formulated problem from a learning perspective. Besides, a lossless switching method is proposed to address the switching problem for multiple clock sources. Simulation results demonstrate the superior performance of RL‐M2 and the lossless switching method in time synchronization delay and error.

The Erdaopuzi section in the Baishan area of Jilin Province, northeast China, contains abundant late Tremadoc graptolites. However, there are some taxonomic controversies regarding the characters of the hand specimens that are difficult to identify. In this paper, we present our restudy of isolated graptolites from acid residue and discuss the taxonomic problems of the subgenus Clonograptus (Neoclonograptus) Zhao and Zhang. Four genera and six species were identified, including Adelograptus tenellus (Linnarsson), Ancoragraptus gracilis (Zhao and Zhang), Dictyonema sp., Psigraptus jacksoni Rickards and Stait, Psigraptus lenzi Jackson, Psigraptus arcticus Jackson. According to the significant evolution of morphological characters, two graptolite zones (from bottom to top) can be identified in ascending order in the study area, i.e. Adelograptus Zone and the Psigraptus Zone.

Abstract Background Breast cancer is the most common malignant tumor that threatens women's health. Attention has been paid on the study of long- non-coding RNA (lncRNA) in breast cancer. However, the specific mechanism remains not clear. Methods In this study, we explored the role of lncRNA BC069792 in breast cancer. In vitro and in vivo functional experiments were carried out in cell culture and mouse models. High-throughput next-generation sequencing technology and real-time fluorescence quantitative PCR technology were used to evaluate differentially expressed genes and mRNA expression, Western blot and immunohistochemical staining were used to detect protein expression. RNA immunoprecipitation assay and dual-luciferase activity assay were used to evaluate the competing endogenous RNAs (ceRNA), and rescue and mutation experiments were used for verification. Results We found that lncRNA BC069792 was expressed at a low level in breast cancer tissues, and significantly decreased in breast cancer with high pathological grade, lymph node metastasis and high Ki-67 index groups. Moreover, BC069792 inhibited the proliferation, invasion and metastasis of breast cancer cells in vitro and in vivo. Mechanically, BC069792 acts as a molecular sponge to adsorb hsa-miR-658 and hsa-miR-4739, to up-regulate the protein expression of Potassium Voltage-Gated Channel Q4 (KCNQ4), inhibits the activities of JAK2 and p-AKT, and plays a role in inhibiting breast cancer growth. Conclusions LncRNA BC069792 plays the role of tumor suppressor gene in breast cancer and is a new diagnostic index and therapeutic target in breast cancer.

Abstract Carbon footprint monitoring provides significant basis for computing facilities to improve the computing efficiency and reduce the energy cost, which can enable low/zero carbon computing and facilitate the construction of sustainable cites. Massive sensing devices access to 5G base station to transmit collected carbon emission data, which requires intelligent access management. Fast uplink grant possesses the advantages of reducing signalling overhead and access conflicts while facing the problems of incomplete information and difficulty in guaranteeing priority constraint. This paper examines, the maximum access queuing delay minimization problem is formulated under the long‐term service priority constraint and the short‐term access management constraint. First, Lyapunov optimization is leveraged to decouple the long‐term service priority constraint and short‐term access management optimization, and decompose the long‐term stochastic optimization problem into a series of short‐term deterministic problems. Then, a priority‐aware deep Q‐network (DQN)‐based fast uplink grant access management (PDAC) algorithm is proposed to achieve intelligent access management with differentiated service priority requirements. PDAC utilizes DQN to handle non‐convex high‐dimensional optimization problem with service priority constraint to achieve intelligent access management and priority awareness. Simulation results demonstrate that PDAC outperforms the existing algorithms in access queuing delay, buffer queue backlog, and priority deficit fluctuation.

Background: The association between soy product consumption and cancer risk varies among studies. Therefore, this comprehensive meta-analysis of observational studies examines the association between soy product consumption and total cancer risk. Methods: This study was conducted following the PRISMA guidelines. Up to October 2023, all eligible published studies were searched through PubMed and Web of Science databases. Results: A total of 52 studies on soy product consumption were included in this meta-analysis (17 cohort studies and 35 case–control studies). High consumption of total soy products (RR: 0.69; 95% CI: 0.60, 0.80), tofu (RR: 0.78; 95% CI: 0.70, 0.86), and soymilk (RR: 0.75; 95% CI: 0.60, 0.93) were associated with reduced total cancer risk. No association was found between high consumption of fermented soy products (RR: 1.18; 95% CI: 0.95, 1.47), non-fermented soy products (RR: 0.95; 95% CI: 0.77, 1.18), soy paste (RR: 1.00; 95% CI: 0.88, 1.14), miso soup (RR: 0.99; 95% CI: 0.87, 1.12), or natto (RR: 0.96; 95% CI: 0.82, 1.11) and cancer risk. A 54 g per day increment of total soy products reduced cancer risk by 11%, a 61 g per day increment of tofu reduced cancer risk by 12%, and a 23 g per day increment of soymilk reduced cancer risk by 28%, while none of the other soy products were associated with cancer risk. Conclusion: Our findings suggest that high total soy product consumption, especially soymilk and tofu, is associated with lower cancer risk. More prospective cohort studies are still needed to confirm the causal relationship between soy product consumption and cancer risk.

The multi-mode communication network provides communication support for the collection, transmission, and processing of energy regulation data and the training of energy regulation models for smart buildings.Digital twin can provide state estimation of computing resources and channel characteristics, assist in the multi-mode communication resource optimization management, and improve the training precision of energy regulation models.However, the digital twin-assisted multi-mode communication resource management of smart buildings still face challenges such as large training error of energy regulation model, coupling of multi-timescale resource allocation, and contradictions between training precision improvement of energy regulation model and energy consumption optimization.Aiming at the above challenges, a multi-timescale communication resource management optimization algorithm based on digital twin and empirical matching learning was proposed.The weighted sum of global model loss function and energy consumption was minimized by jointly optimizing the large-timescale gateway selection and small-timescale channel allocation and power control.Simulation results show that the proposed algorithm can improve the performance of weighted sum of global model loss function and energy consumption, ensure the precise energy regulation requirement and promote the low-carbon operation of smart buildings.

Objective: We aimed to investigate the use of core needle biopsy (CNB) in epididymal tuberculosis (TB) diagnosis. Methods: We analyzed 41 samples collected between January 1, 2018, and January 31, 2021, from patients who underwent CNB for suspected epididymal TB. All specimens were examined using histopathological examination and the Xpert Mycobacterium tuberculosis bacilli/rifampicin (MTB/RIF) assay. We analyzed the examination results to determine the application value of CNB in epididymal TB diagnosis and evaluate its safety. Results: According to the comprehensive reference standard established in this study, 37 of the 41 patients had epididymal TB and four patients had chronic epididymitis. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve of histopathological examination were 86.49% (71.23-95.46%), 100.00% (39.76-100.00%), 100.00% (89.11-100.00%), 44.44% (13.70-78.80%), and 0.93 (0.81-0.99), respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve of the Xpert MTB/RIF assay were 62.16% (44.76-77.54%), 100.00% (39.76-100.00%), 100.00% (85.18-100.00%), 22.22% (6.41-47.76%), and 0.81 (0.66-0.92), respectively. No postoperative complication attained a Clavien–Dindo classification grade of >2. Conclusion: CNB was useful in diagnosing epididymal TB. Therefore, we recommend using CNB as a sample collection tool for diagnosing epididymal TB.

The construction process is a dynamic one, and the complexity of the working conditions and the high level of uncertainty make the construction industry the third most dangerous industry after mining and agriculture. And since the construction industry is vital to the development of a country, safety during construction is of particular importance. A great deal of research, studies and practices have been conducted to reduce potential risks and improve worker efficiency during the construction process. In recent years, with the rapid development of cognitive neuroscience and the integration of medical technology, various wearable monitoring devices have been widely used in the field of building construction for real-time monitoring of workers’ physical and mental conditions. Among them, the application of EEG (electroencephalogram) in the building construction process enables researchers to gain insight into the physical and mental state of construction workers while performing construction tasks. This paper introduces EEG technology and portable EEG monitoring equipment and summarizes its application in monitoring workers’ adverse reactions (emotion, fatigue, psychological burden, and vigilance) and construction hazard identification during the process of construction in recent years, which provides future EEG research in the field of building construction and construction site safety management.

Celadons were prepared in the reducing atmosphere with purple clay and other natural elements. Different concentrations of silicon powder, silicon carbide, and tin dioxide were used as auxiliary reducing agents to investigate their effects on celadons. The results showed that the brightness value of celadons increased and subsequently declined when Si and SiC were introduced, and the glaze color gradually shifted from yellowish-green to bluish-green. On the other hand, samples with SnO2 had an opaque yellowish-green tint. According to XPS data, the reducing ability of SiC was added, followed by Si and SnO2. The structural colors of samples containing Si, SnO2, and without reducing agents were weak. Otherwise, celadons with SiC could yield blue structural colors conforming to the “Rayleigh scattering” effect. In conclusion, the reducing atmosphere raised the quantity of Fe2+ in celadons, resulting in blue colors, and additives created a variety of chemical and structural color coupling effects, leading to different aesthetic effects.

The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune severity index (SII), and prognostic nutritional index (PNI) are associated with the prognosis of gastric, lung, and breast cancers. However, the predictive value of pathological complete response (pCR) rates in patients with breast cancer treated with neoadjuvant chemotherapy (NAC) remains unclear. This retrospective study explored the correlation between each index and the efficacy of neoadjuvant chemotherapy in patients with breast cancer and assessed the relationship between changes before and after neoadjuvant chemotherapy. We enrolled 95 patients with locally advanced breast cancer who received neoadjuvant therapy for breast cancer at the Second Affiliated Hospital of Fujian Medical University from April 2020 to April 2022. Based on postoperative pathology, patients were divided into pCR and non-pCR groups. Between-group differences and efficacy prediction ability of NLR, PLR, SII, and PNI were analyzed. Patient characteristics and changes in NLR, PLR, SII, and PNI before and after neoadjuvant chemotherapy (NAC) were compared between groups. Patients were divided into two groups according to the optimal diagnostic thresholds of the SII before treatment. Between-group differences in terms of neoadjuvant therapy efficacy and patient characteristics were evaluated. The pCR exhibited significantly lower ER (χ2 = 10.227, P = 0.001), PR (χ2 = 3.568, P = 0.049), pretreatment NLR (χ2 = 24.930, P

Long non-coding RNAs (LncRNAs) have already been taken as critical regulatory molecules in breast carcinoma (BC). Besides, the progression of BC is closely associated with the immune system. However, the relationship between lncRNAs and the tumor immune system in BC has not been fully studied. LncRNA KRT19P3 has been reported to inhibit the progression of gastric cancer. In the present study, we first discovered that KRT19P3 was downregulated in BC tissues compared with para cancer tissue. Then we showed that KRT19P3 could be used as a marker to differentiate BC from para cancer tissue. Increased expression of KRT19P3 markedly inhibited the proliferation, migration, and invasion rate of BC cells in vitro and tumor growth of BC in vivo. Conversely, KRT19P3 knockdown by siRNA markedly promoted the proliferation, migration, and invasion rate of BC cells after being transfected. Comparison of clinical parameters showed an inverse relationship between the expression of KRT19P3 and pathological grade. Furthermore, immunohistochemistry (IHC) was applied to reveal the positive rate of the expression of Ki-67, programmed death-ligand 1 (PD-L1), and CD8 in BC tissues. Correlation analysis showed that Ki-67 and PD-L1 were inversely proportional to KRT19P3 but CD8 was directly proportional to KRT19P3. In conclusion, this study demonstrated that lncRNA KRT19P3 inhibits BC progression, and may affect the expression of PD-L1 in BC, which in turn affects CD8+ T (CD8 positive Cytotoxic T lymphocyte) cells in the immune microenvironment.

In this study, the fracture propagation characteristics and associated mechanisms of coal are investigated by using computed tomography (CT) observation and image-based simulation. The spatial distribution and the structural morphology of original fractures provide significant influences on the failure behavior of fractured coal. The fractures with small dip angles and large openings result in more-obvious fracture closure and stable propagation stages, while failure pattern is more sensitive to those with large dip angles. The coal tends to experience brittle failure, which transits from a splitting to mixed-splitting faulting mode because of the difference in original fracture distribution. The final failure fracture network originates mainly from the propagation of original fractures, driven by localized tensile stress. Fracture interaction and mineral influence tend to increase the complexity in the failure fracture network. Moreover, image-based numerical models are established on the basis of CT reconstruction, where the spatial distribution and the structural morphology of original fractures are properly considered. Numerical modeling reproduces similar stress–strain responses and failure fracture networks to that observed in the experiment. The predicted distribution of tensile stress shows a similar evolution trend to the failure fracture network, implying that the fracture propagation of coal is dominated by tensile failure. Shear cracks emerge mainly after the large fracture running through the coal sample has been formed.

Understanding the pattern of species extinction risk is key to biodiversity conservation. Previous studies showed extinction risk correlates strongly with taxon species richness. However, there is no consistent conclusion to this hypothesis, and patterns differ among different taxonomic groups. Here, we collated lists of vascular plant and terrestrial vertebrate species information on their threatened status in Yunnan Province and performed the first systematical analysis to test the relationship between the proportion of threatened or extinct species and species richness at the family-level of the two above taxa in Yunnan Province, China. We found that extinction risk was not randomly distributed among families and the estimated extinction risk was higher among closer phylogenetic families than expected by chance. Moreover, there were significant negative correlations between extinction risk and family size in vascular plants and terrestrial vertebrates. Our results suggest that family size is a good predictor of extinction risk and extinction risk is related to evolutionary history at family-level among vascular plants and terrestrial vertebrates in Yunnan.

Vehicular edge computing has emerged as a promising technology to accommodate the tremendous demand for data storage and computational resources in vehicular networks. By processing the massive workload tasks in the proximity of vehicles, the quality of service can be guaranteed. However, how to determine the task offloading strategy under various constraints of resource and delay is still an open issue. In this paper, we study the task offloading problem from a matching perspective and aim to optimize the total network delay. The task offloading delay model is derived based on three different velocity models, i.e., a constant velocity model, vehicle-following model, and traveling-time statistical model. Next, we propose a pricing-based one-to-one matching algorithm and pricing-based one-to-many matching algorithms for the task offloading. The proposed algorithm is validated based on three different simulation scenarios, i.e., straight road, the urban road with the traffic light, and crooked road, which are extracted from the realistic road topologies in Beijing and Guangdong, China. The simulation results confirm that significant delay decreasing can be achieved by the proposed algorithm.

In computer vision, convolutional networks (CNNs) often adopt pooling to enlarge receptive field which has the advantage of low computational complexity. However, pooling can cause information loss and thus is detrimental to further operations such as features extraction and analysis. Recently, dilated filter has been proposed to tradeoff between receptive field size and efficiency. But the accompanying gridding effect can cause a sparse sampling of input images with checkerboard patterns. To address this problem, in this paper, we propose a novel multi-level wavelet CNN (MWCNN) model to achieve a better tradeoff between receptive field size and computational efficiency. The core idea is to embed wavelet transform into CNN architecture to reduce the resolution of feature maps while at the same time, increasing receptive field. Specifically, MWCNN for image restoration is based on U-Net architecture, and inverse wavelet transform (IWT) is deployed to reconstruct the high resolution (HR) feature maps. The proposed MWCNN can also be viewed as an improvement of dilated filter and a generalization of average pooling and can be applied to not only image restoration tasks, but also any CNNs requiring a pooling operation. The experimental results demonstrate the effectiveness of the proposed MWCNN for tasks, such as image denoising, single image super-resolution, JPEG image artifacts removal and object classification.

Deep mining has become the normal state of coal mining; compared with the mine with shallow buried depth, the consequent high level of in situ stress and complex distribution have brought severe threats to the stability of the stope and the surrounding rock of the roadway. In this research, taking the 121304 working face of Kouzidong Mine as the engineering background, the characteristics of mining-induced stress distribution under complex in situ stress environment in deep mining are analyzed by using on-site measurement of the original rock stress and mining stress, establishing a theoretical model centered on the middle section of the working face, and establishing large-scale numerical calculation models for different advancing directions. It was found that under deep mining conditions, the maximum stress of the original rock is 25.12 MPa, and the direction is vertical. The advanced influence range of mining stress is about 150 m, and the abutment pressure presents a three-peak distribution characteristic in front of the working face. The research results provide important theoretical guiding value for guiding the mining of coal mines with similar geological conditions.

As one of the largest inland megacities in Northwest (NW) China, Xi’an has been facing serious regional haze frequently, especially during winter. The composition of aerosols in Xi’an is highly complex due to its unique basinal topography and unique meteorological conditions. In this study, we characterized the morphology, size, and composition of individual aerosol particles collected during regional haze events at an urban site in Xi’an using Transmission Electron Microscopy (TEM) coupled with Energy-Dispersive X-ray Spectrometry (EDX). Six types of particles were identified based on their morphology and chemical composition, including organic (41.88%), sulfate (32.36%), soot (8.33%), mineral (7.91%), K-rich (5.13%), and fly ash particles (4.49%). These results demonstrate that the organic particles made a larger contribution to haze formation than the secondary inorganic particles during the sampling period. Size distribution and dominance suggest that organic and sulfate particles exert major control on the variation trends of particle size in haze. The coating thickness of organic-cored particles was about 369 nm and that of sulfate-cored particles was about 322 nm, implying that the organic particles were more aged than the sulfate particles. The results presented in this study provide further insights into understanding haze particle formation.

Abstract The synergistic effect of conventional flame-retardant elements and graphene has received extensive attention in the development of a new class of flame retardants. Compared to covalent modification, the non-covalent strategy is simpler and expeditious and entirely preserves the original quality of graphene. Thus, non-covalently functionalized graphene oxide (FGO) with a phosphorus–nitrogen compound was successfully prepared via a one-pot process in this study. Polyethyleneimine and FGO were alternatively deposited on the surface of a poly(vinyl alcohol) (PVA) film via layer-by-layer assembly driven by electrostatic interaction, imparting excellent flame retardancy to the coated PVA film. The multilayer FGO-based coating formed a protective shield encapsulating the PVA matrix, effectively blocking the transfer of heat and mass during combustion. The coated PVA has a higher initial decomposition temperature of about 260 °C and a nearly 60% reduction in total heat release than neat PVA does. Our results may have a promising prospect for flame-retardant polymers.

Hippuris vulgaris is an aquatic perennial herb distributed worldwide. In this research, the complete chloroplast genome of H. vulgaris was sequenced and assembled. Its complete genome size was 152,698 bp in length. The typical quadripartite structure was shown, which contained a large single-copy region (82,940 bp), a small single-copy region (18,262 bp), and a pair of inverted repeat regions (25,748 bp). The CG content of this genome was 37.6%. A total of 114 genes have been identified in the genome, including 80 protein-coding genes, 30 tRNA genes, and 4 rRNA genes. In addition, 18 genes possessed at least one intron. The phylogenetic analysis indicated that H. vulgaris was nested in Plantaginaceae with 100% bootstrap value and was a sister to Digitalis, Plantago, Hemiphragma, Veronica and Veronicastrum.

Abstract A novel hybrid flame retardant combining graphene oxide (GO) with long-chain phosphaphenanthrene was fabricated via surface grafting reaction. Taking advantageous of the double barrier effects, including the physical shield contributed by graphene nanoplates during the initial stage and the chemical char contributed by phosphaphenanthrene during the later stage, greatly decreased the release rate of decomposed volatiles from the resin, as well as minimized the release of oxygen and combustion heat. Hence, such hybrid flame retardant can overcome the shortcomings of early acid catalyzed degradation effects caused by conventional flame retardants containing phosphorus. Satisfactory flame retardance was achieved (UL94 V-0 rating) with only 4% addition of the hybrid flame retardant to the epoxy resin laminate. Due to the long-chain and bulky phosphaphenanthrene groups, the interlayer attractive forces of the modified GO were effectively weakened, thus favoring the exfoliation and dispersion of graphene sheets. As a result, the incorporation of the flame retardant slightly enhanced the mechanical properties of the polymer composites, rather than deteriorating them, as occurs with traditional additive flame retardants. As a potential application for graphene, it is believed that the reported hybrid flame retardant has promising future prospect.

Detecting forest degradation from satellite observation data is of great significance in revealing the process of decreasing forest quality and giving a better understanding of regional or global carbon emissions and their feedbacks with climate changes. In this paper, a quick and applicable approach was developed for monitoring forest degradation in the Three-North Forest Shelterbelt in China from multi-scale remote sensing data. Firstly, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Ratio Vegetation Index (RVI), Leaf Area Index (LAI), Fraction of Photosynthetically Active Radiation (FPAR) and Net Primary Production (NPP) from remote sensing data were selected as the indicators to describe forest degradation. Then multi-scale forest degradation maps were obtained by adopting a new classification method using time series MODerate Resolution Imaging Spectroradiometer (MODIS) and Landsat Enhanced Thematic Mapper Plus (ETM+) images, and were validated with ground survey data. At last, the criteria and indicators for monitoring forest degradation from remote sensing data were discussed, and the uncertainly of the method was analyzed. Results of this paper indicated that multi-scale remote sensing data have great potential in detecting regional forest degradation.

Molar tooth structures are common in early- to mid-Proterozoic carbonates but extremely rare in rocks younger than 750 Ma. Here, the authors show molar tooth carbonate formation is related to benthic methane fluxes.