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Climate change is increasing the frequency and severity of short-term (~1 y) drought events-the most common duration of drought-globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function-aboveground net primary production (ANPP)-was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.

Abstract: Meridional circulation regulates the Sun’s interior dynamics and magnetism. While it is well accepted that meridional flows are poleward at the Sun’s surface, helioseismic observations have yet to provide a definitive answer for the depth at which those flows return to the equator, or the number of circulation cells in depth. Here, we explore the observability of multiple circulation cells stacked in radius. Specifically, we examine the seismic signature of several meridional flow profiles by convolving time–distance averaging kernels with mean flows obtained from a suite of 3D hydrodynamic simulations. At mid and high latitudes, we find that weak flow structures in the deep convection zone can be obscured by signals from the much stronger surface flows. This contamination of 1–2 m s−1 is caused by extended side lobes in the averaging kernels, which produce a spurious equatorward signal with flow speeds that are 1 order of magnitude stronger than the original flow speeds in the simulations. At low latitudes, the flows in the deep layers of the simulations are stronger (>2 m s−1) and multiple cells across the convection zone can produce a sufficiently strong signal to survive the convolution process. Now that meridional flows can be measured over two decades of data, the uncertainties arising from convective noise have fallen to a level where they are comparable in magnitude to the systematic biases caused by nonlocal features in the averaging kernels. Hence, these systematic errors are beginning to influence current helioseismic deductions and need broader consideration.

Toughening polymers has attracted significant interest. Traditionally, polymer toughness is enhanced by constructing polymer networks or introducing sacrificial bonds into the chains between crosslink points. These strategies, though, introduce pronounced energy dissipation and associated heat, both of which are undesirable under long-term cyclic loading, for example at the interface of implants in the human body. By incorporating single-chain nanoparticles (SCNPs) into linear polymer chains to generate all-polymer nanocomposites (APNCs), we have been able to achieve high strength, high toughness with low energy dissipation. Using a combination of simulation and experimental results, we are advancing a “SCNPs effect” where tightly cross-linked SCNPs produce a modulus contrast to achieve strengthening and toughening. Benefitting from the soft interface, the penetrable and deformable SCNPs cause the surrounding polymer chains to move in concert, significantly reducing the interfacial friction to achieve low energy dissipation. The intramolecular cross-linking of the SCNPs and adhesion between the SCNPs and polymer matrix are critical for realizing such high-performance systems. Based on a Gaussian regression model and back propagation (BP) neural network, the mechanical strength can be predicted and is supported by simulations. The APNC concept described can be applied to elastomers and gels, broadening its utilization in high-cycle and low-dissipation applications, like soft robots, flexible sensors and cartilage replacements, and artificial heart valves.

Abstract Previous studies have pointed to a potential link between Obstructive Sleep Apnea (OSA) and gastrointestinal diseases, suggesting that this relationship might be influenced by the presence of Metabolic Syndrome. However, the exact role of these factors in determining gastrointestinal diseases has not been thoroughly explored. In our study, we utilized data from the Genome-wide Association Studies (GWAS) database, focusing on OSA, metabolic syndrome characteristics such as Body Mass Index (BMI), waist circumference, triglycerides, cholesterol, hypertension, type 2 diabetes, and common gastrointestinal diseases including chronic gastritis, gastric ulcers, irritable bowel syndrome, colorectal cancer, inflammatory bowel disease, cholecystitis, nonalcoholic fatty liver, and dyspepsia. By applying Single-variable and Multi-variable Mendelian randomization methods, we aimed to assess the correlation between OSA and gastrointestinal diseases and investigate whether this correlation is influenced by metabolic syndrome. Our findings revealed a strong association between OSA and an increased risk of chronic gastritis, gastric ulcers, inflammatory bowel disease, and nonalcoholic fatty liver disease. No significant connections were found with irritable bowel syndrome, colorectal cancer, cholecystitis, or dyspepsia. Additionally, OSA was linked to metabolic syndrome traits like BMI, waist circumference, triglycerides, hypertension, and type 2 diabetes. Further analysis showed that BMI, triglycerides, and hypertension were causally related to inflammatory bowel disease; BMI, waist circumference, hypertension, and type 2 diabetes to nonalcoholic fatty liver disease; and triglycerides, hypertension, and type 2 diabetes to chronic gastritis. The multivariable analysis indicated that hypertension mediates the relationship between OSA and chronic gastritis; BMI, triglycerides, and hypertension mediate the link between OSA and inflammatory bowel disease; and waist circumference mediates the connection between OSA and nonalcoholic fatty liver disease. To wrap up, this finding helps us understand how these issues might be related and stresses the role of metabolic syndrome in preventing them, which could lessen their effect on health.

Privacy protection plays a crucial role in recommender systems as it helps to protect users’ sensitive information from disclosure risks. Recent recommendation unlearning has attracted increasing attention as an effective method of privacy protection. Existing methods often partition data into sub-partitions before training to enhance model training efficiency. However, simply partitioning interactions into sub-partitions can disrupt the integrity of user-item relationships and reduce the availability of data. In addition, the presence of false-positive noise in sub-partitions with implicit feedback can interfere with model training, preventing it from accurately capturing users’ true preferences. To address these challenges, a recommendation unlearning algorithm combining fuzzy clustering and adaptive denoising (FDRU) is proposed. Firstly, fuzzy clustering determines membership by calculating cosine distances between samples and various cluster centers, subsequently dividing the training dataset into several sub-partitions. Then, FDRU designs an adaptive denoising algorithm that dynamically eliminates false positive noise in sub-partitions based on thresholds. Finally, it utilizes dynamic weighted aggregation of sub-models for prediction and top-N recommendations. In order to assess the performance of the proposed algorithm, extensive experiments are carried out on three public datasets. Experimental results indicate that FDRU outperforms other benchmark algorithms on Recall and NDCG.

Changes of wind barrier angles exert significant effect on the occurrence of low oxygen gas in the upper corner. Taking the 100510 working face of a mine in Shanxi Province as example, this study uses Ansys Fluent software to build a gas migration model of the working face to simulate the occurrence patterns of low oxygen gas in the upper corner under different wind barrier angles, and verifies the model through field measurement. Results show that setting wind barrier could increase wind speed in the upper corner, which offers a solution to the low oxygen problem in upper corner. The optimal treatment of low oxygen in the upper corner is realized with wind barrier angle set at 60° at the position 5m away from the return air channeling. This study provides implications for solutions to the low oxygen issue in the upper corner and thereby ensure safety production.

Abstract Background Several tetraspanin (TSPAN) proteins have been implicated in tumorigenesis and disease progression. However, the precise function of tetraspanin 6 (TSPAN6) in glioma remains unclear. Methods Integrated raw data from the Tumor Genome Atlas (TCGA) and Gene Expression Profiling (GEO) databases were processed using R4.2.1. Bioinformatic methods were used to analyze the gene expression levels of TSPAN6 in both glioma and normal brain tissues, correlating them with clinical characteristics. Additionally, the predictive value of TSPAN6 in relation to the immune checkpoint blockade (ICB) therapy response was assessed. In vitro experiments were conducted to investigate the effects of TSPAN6 knockdown on glioma cell proliferation, migration, cell cycle regulation, and macrophage recruitment. Results TSPAN6 expression was significantly upregulated in glioma tissues compared to normal tissues. Elevated TSPAN6 expression is strongly correlated with unfavorable clinical characteristics in gliomas. Bioinformatic analyses revealed a significant correlation between elevated TSPAN6 expression and reduced overall survival. Additionally, TSPAN6 was co-expressed with several immune checkpoint genes and revealed a prognostic value in the context of ICB therapy. Functional enrichment analysis revealed the involvement of TSPAN6 in cell-cycle regulation. Furthermore, TSPAN6 expression positively correlated with macrophage and neutrophil infiltration. In vitro experiments confirmed that the downregulation of TSPAN6 inhibited U251 cell proliferation, disrupted the cell cycle, diminished migratory capabilities, and reduced the recruitment of macrophages. Conclusion Our findings emphasize its potential as both a diagnostic and therapeutic target as well as a predictor of immune therapy response in gliomas.

Abstract Topological crystalline insulators are known to support multiple Majorana zero modes (MZMs) at a single vortex, their hybridization is forbidden by a magnetic mirror symmetry M T $M_{T}$ . Due to the limited energy resolution of scanning tunneling microscopes and the very small energy spacing of trivial bound states, it remains challenging to directly probe and demonstrate the existence of multiple MZMs. In this work, we propose to demonstrate the existence of MZMs by studying the hybridization of multiple MZMs in a symmetry breaking field. The different responses of trivial bound states and MZMs can be inferred from their spatial distribution in a vortex. However, the theoretical simulations are very demanding since it requires an extremely large system in real space. By utilizing the kernel polynomial method, we can efficiently simulate large lattices with over 108 orbitals to compute the local density of states which bridges the gap between theoretical studies based on minimal models and experimental measurements. We show that the spatial distribution of MZMs and trivial vortex bound states differs drastically in tilted magnetic fields. The zero-bias peak elongates when the magnetic field preserves M T $M_{T}$ , while it splits when M T $M_{T}$ is broken, giving rise to an anisotropic magnetic response. Since the bulk of SnTe are metallic, we also study the robustness of MZMs against the bulk states, and clarify when can the MZMs produce a pronounced anisotropic magnetic response.

Abstract Many large-scale regularized inverse problems in imaging such as image restoration and reconstruction can be modeled as a generic objective function involves sum of nonsmooth but proximable terms, which are usually linear-operator-coupled. For the solution of these problems, a parallel linearized alternating direction method of multipliers (PLADMM) is proposed in this paper. At each step of the proposed algorithm, the proximity operators of the nondifferential terms are called individually. This leads to a highly parallel algorithm structure, where most sub-steps can be simultaneously solved. Profiting from the linearization step, the linear inverse operation is excluded. The convergence property of the proposed method is analyzed. The image deblurring, inpainting, and pMRI reconstruction experiments show that the proposed method has vast applicable vistas. Compared with the state-of-the-art methods, such as PADMM [21], FTVD-v4 [22], PPDS [33], FUSL [8], LADM [36], and ALADMM [27], it gains competitive results both in terms of quantitative indicators, such as PSNR or SSIM, and in terms of visual impression.

Abstract This paper presents a rule‐based energy management system (EMS) designed for a standalone DC microgrid incorporating solar photovoltaic (PV), fuel cell, battery energy storage system (BESS), and electric vehicle. The unpredictable nature of renewable energy sources and the instability of loads pose challenges for maintaining DC bus voltages and power‐sharing arrangements, impacting the microgrid's smooth operation. The proposed EMS aims to ensure power balance between generation and demand, mitigating vulnerabilities of the DC bus to voltage instability caused by fluctuations from both the load and source sides. This is achieved through an autonomous DC bus voltage stabilization strategy, involving the maintenance of a nominal state of energy (SoE) for the BESS and hydrogen fuel consumption for the fuel cell within predefined lower and upper limits. By regulating these two factors, the EMS algorithm facilitates optimal performance of the PV, battery, and fuel cell components. Consequently, the EMS provides decision‐making instructions to each individual energy source, ensuring efficient operation under various conditions. The effectiveness of the proposed EMS is evaluated through hardware‐based testing on a DC microgrid and simulations in the MATLAB Simulink environment across multiple operating scenarios.

Abstract The quest to understand the molecular mechanisms of tumour metastasis and identify pivotal biomarkers for cancer therapy is increasing in importance. Single-omics analyses, constrained by their focus on a single biological layer, cannot fully elucidate the complexities of tumour molecular profiles and can thus overlook crucial molecular targets. In response to this limitation, we developed a multiobjective recommendation system (RJH-Metastasis 1.0) anchored in a multiomics knowledge graph to integrate genome, transcriptome, and proteome data and corroborative literature evidence and then conducted comprehensive analyses of colorectal cancer with liver metastasis (CRCLM). A total of 25 key genes significantly associated with CRCLM were recommended by our system, and GNB1, GATAD2A, GBP2, MACROD1, and EIF5B were further highlighted. Specifically, GNB1 presented fewer mutations but elevated RNA transcription and protein expression in CRCLM patients. The role of GNB1 in promoting the malignant behaviours of colon cancer cells was demonstrated via in vitro and in vivo studies. Aberrant expression of GNB1 could be regulated by METTL1-driven m7G modification. METTL1 knockdown decreased m7G modification in the 3’ UTR of GNB1, increasing its mRNA transcription and translation during liver metastasis. Furthermore, GNB1 induced the formation of an immunosuppressive microenvironment by promoting the CLEC2C-KLRB1 interaction between memory B cells and KLRB1+PD-1+CD8+ cells. GNB1 expression and the efficacy of PD-1 antibody-based treatment in CRCLM patients were significantly correlated. In summary, our recommendation system can be used for effective exploration of key molecules in colorectal cancer, among which GNB1 was identified as a critical CRCLM promoter and immunotherapy biomarker in colorectal cancer patients.

Abstract The explosion in foundation poses a significant threat to people and buildings. Currently, a unified empirical prediction formula for crater in calcareous foundation has not been established. In this paper, analyzed the types and sizes of explosion crater with different scaled burial depths through field tests and numerical simulation. In field tests, revealed the influence of scaled burial depth on the type and size of explosion crater and obtained the critical scaled burial depth for three different types of explosion craters, namely ejecta-type crater, collapse-type crater and covert explosion. Through the Smooth Particle Hydrodynamic-Finite Element Method (SPH-FEM) coupling algorithm, studied the movement trajectory of sand particles around the explosive at the moment of explosion in detail. Based on the field tests and numerical simulation results, it was found that calcareous sand has a smaller specific gravity due to its own characteristics, and the size of the explosion crater is larger than that of quartz sand at the same scaled burial depth. Obtained an empirical formula for crater in calcareous sand. Which can quickly predict the size of explosion crater and provide calculation basis for explosion resistant design in calcareous sand foundations.

Abstract Background CHRDL1 belongs to a novel class of mRNA molecules. Nonetheless, the specific biological functions and underlying mechanisms of CHRDL1 in oral squamous cell carcinoma (OSCC) remain largely unexplored. Methods RT-qPCR and immunohistochemical staining were employed to assess the mRNA and protein expression levels of the MED29 gene in clinical samples of OSCC. Additionally, RT-qPCR and Western Blot analyses were conducted to investigate the mRNA and protein expression levels of the MED29 gene specifically in OSCC. The impact of MED29 on epithelial-mesenchymal transition (EMT), invasion, and migration of OSCC was evaluated through scratch assay, transwell assay, and immunofluorescence staining. Furthermore, wound healing assay and Transwell assay were utilized to examine whether CHRDL1 influences the malignant behavior of OSCC by modulating MED29 in vitro. The regulatory role of CHRDL1 on MED29 was further elucidated in vivo through a tail vein lung metastasis model in nude mice. Results MED29 expression was elevated in tumor tissues of OSCC patients compared with adjacent cancer tissues. Moreover, in CAL27 and SCC25 cell lines, MED29 was upregulated and associated with increased cell migration and invasion abilities. Overexpression of MED29 facilitated EMT in OSCC cell lines, whereas knockdown of MED29 impeded EMT, resulting in diminished cell migration and invasion capacities. CHRDL1 exerted inhibitory effects on the expression of MED29, thereby suppressing EMT progression and consequently restraining the invasion and migration of OSCC cells. Furthermore, CHRDL1 mediated the inhibition of migration of OSCC cell lines to the OSCC through its regulation of MED29. Conclusions MED29 facilitated the epithelial-mesenchymal transition process in OSCC, thereby promoting migration and invasion. On the other hand, CHRDL1 exerted inhibitory effects on the invasion and metastasis of OSCC by suppressing MED29 through the inhibition of the MAPK signaling pathway.

Abstract Infrared images of sensitive targets are difficult to obtain and cannot meet the design and training needs of target detection and tracking algorithms for mobile platforms such as aircraft. This paper proposes an image translation algorithm TransImg, which can achieve visible light image translation to the infrared domain to enrich the dataset. First, the algorithm designed a generator structure consisting of a deep residual connected encoder and a region perception feature fusion module to enhance feature learning, thereby avoiding issues such as generating infrared images with insufficient details in the transfer task. Afterward, a multi-scale discriminator and a composite loss function were designed to further improve the transfer effect. Finally, an automatic mixed-precision training strategy was designed for the overall migration algorithm architecture to accelerate the training and generation of infrared images. Experiments have shown that the image translation algorithm TransImg has good algorithm accuracy, and the infrared image generated by visible light image translation has richer texture details, faster generation speed, and lower video memory consumption, and the performance exceeds the mainstream traditional algorithm, and the generated images can meet the requirements of target detection and tracking algorithms design and training for mobile platforms such as aircraft.

In situ regeneration is a promising strategy for constructing tissue engineering heart valves (TEHVs). Currently, the decellularized heart valve (DHV) is extensively employed as a TEHV scaffold. Nevertheless, DHV exhibits limited blood compatibility and notable difficulties in endothelialization, resulting in thrombosis and graft failure. The red blood cell membrane (RBCM) exhibits excellent biocompatibility and prolonged circulation stability and is extensively applied in the camouflage of nanoparticles for drug delivery; however, there is no report on its application for large-scale modification of decellularized extracellular matrix (ECM). For the first time, we utilized a layer-by-layer assembling strategy to immobilize RBCM on the surface of DHV and construct an innovative TEHV scaffold. Our findings demonstrated that the scaffold significantly improved the hemocompatibility of DHV by effectively preventing plasma protein adsorption, activated platelet adhesion, and erythrocyte aggregation, and induced macrophage polarization toward the M2 phenotype in vitro. Moreover, RBCM modification significantly enhanced the mechanical properties and enzymatic stability of DHV. The rat models of subcutaneous embedding and abdominal aorta implantation showed that the scaffold regulated the polarization of macrophages into the anti-inflammatory and pro-modeling M2 phenotype and promoted endothelialization and ECM remodeling in the early stage without thrombosis and calcification. The novel TEHV exhibits excellent performance and can overcome the limitations of commonly used clinical prostheses.

We prepared biocompatible and environment-friendly zinc oxide nanoparticles (ZnO NPs) with upconversion properties and catalase-like nanozyme activity. Photodynamic therapy (PDT) application is severely limited by the poor penetration of UV–Visible light and a hypoxic tumor environment. Here, we used ZnO NPs as a carrier for the photosensitizer chlorin e6 (Ce6) to construct zinc oxide–chlorin e6 nanoparticles (ZnO-Ce6 NPs), simultaneously addressing both problems. In terms of penetration, ZnO NPs convert 808 nm near-infrared light into 401 nm visible light to excite Ce6, achieving deep-penetrating photodynamic therapy under long-wavelength light. Interestingly, the ability to emit short-wavelength light under long-wavelength light is usually observed in upconversion nanoparticles. As nanozymes, ZnO NPs can catalyze the decomposition of hydrogen peroxide in tumors, providing oxygen for photodynamic action and relieving hypoxia. The enhanced photodynamic action produces a large amount of reactive oxygen species, which overactivate autophagy and trigger immunogenic cell death (ICD), leading to antitumor immunotherapy. In addition, even in the absence of light, ZnO and ZnO-Ce6 NPs can induce ferroptosis of tumor cells and exert antitumor effects.

Abstract Background Pneumocystis jirovecii pneumonia (PcP) is an opportunistic infection associated with immunocompromised patients. The development of novel immunotherapies has promoted the incidence of PcP. This study describes the clinical course and outcome of PcP in chimeric antigen receptor (CAR) T cell recipients with hematological malignancies. Methods This is a retrospective case series of CAR-T recipients diagnosed with PcP in our center. The cases were all confirmed by metagenomic next-generation sequencing of clinical samples. The demographic, clinical, and outcome data were retrieved from the patients’ medical charts and electronic medical record system. Results In total, 8 cases of PcP were identified. The underlying malignancies included T-acute lymphoblastic leukemia (ALL) (n = 1), diffuse large B cell lymphoma (DLBCL) (n = 4), and B-ALL (n = 3). One patient received short-term sulfamethoxazole-trimethoprim (SMZ-TMP) while the others had no prophylaxis. Four patients had neutropenia/lymphopenia at the diagnosis of PcP, and two patients had immunosuppressants within one month before PcP manifestation. The median time from CAR-T infusion to PcP diagnosis was 98.5 days (range 52–251). Seven patients recovered from PcP after proper management while one died of septic shock. Conclusion PcP can occur after different CAR-T product, and the long-term depletion of immune cells seems to be related to PcP. SMZ-TMP is effective in this setting. More real-world experience of CAR-T therapy is required to assess the incidence and outcome of PcP in this population.

Abstract Background Poor working postures in morning care operations contribute significantly to work-related muscle fatigue and low back pain among ICU (Intensive Care Unit, ICU) nurses. However,there are few field studies on the relationship between Poor working postures and work-related muscle fatigue, low back pain among ICU nurses. Objective This study aims to assess the frequency and degree of posture hazards associated with poor working postures during morning care operations of ICU nurses. Methods Two ICUs in a Grade-A tertiary hospital in Hunan Province were randomly selected for the field study in May–June 2021 research. The image data of the participating nurses’ morning care work postures were collected by observation method and image recording method, and the postural hazard level was assessed by the two-person interpretation method of the work posture analysis system. The mean and standard deviation, frequency and percentage were used for the basic statistical description, and the general linear model multivariate Hotelling’s T 2 test was used to calculate the Hotelling’s T 2 and F statistics to explore the pattern of change in the postural hazard score curves. Results A total of 45 nurses were observed during morning care operations, resulting in 47.8 h of video data and 34,428 effective static operation posture pictures. Among these pictures, 21,166 (61.5%) depicted poor working postures. Nurses spent up to 7 min and 30 s maintaining a challenging posture during oral care, with the highest postural hazard score (M = 2.2, SD = 0.3) observed during defecation care. Each patient requires a total of 25–30 min of oral care per day.The Hotelling’s T 2 test indicated that the change curve of the postural hazard score in each step revealed the largest second-order F value, F = 52.931, P

Abstract Background Schizophrenia is a complex neuropsychiatric disorder. Growing evidence indicates that the activation of the inflammatory response system with interleukin (IL)-2, IL-4, IL-8, IL-10, and tumor necrosis factor-alpha (TNF-α) plays an important role in the pathogenesis of schizophrenia,. However, clinical data on cytokine levels in patients with schizophrenia treated with antipsychotics are inconsistent or inconclusive. In this study, we have examined inflammatory factors’ alterations and their relationship to changes in clinical symptoms before and after olanzapine treatment of drug-naive patients with first-episode schizophrenia. Methods We recruited 142 hospitalized patients with first-episode schizophrenia as a study group; blood samples were collected, and the patients were assessed for clinical symptoms at baseline and after 6 weeks of olanzapine treatment. One hundred individuals with no history of mental illness were also recruited as healthy controls. Blood samples were collected, and the serum levels of IL-2, IL-4, IL-8, IL-10, and TNF-α were determined using an enzyme cycling assay. The severity of clinical symptoms was assessed according to the Positive and Negative Syndrome Scale (PANSS). Results Individuals with schizophrenia had lower IL-8 levels and higher IL-10 levels than healthy controls (P

Abstract Hole-conductor-free printable mesoscopic perovskite solar cells (p-MPSCs) have attracted widespread attention for their low cost, up-scalability, and exceptional stability. However, the high defect density of perovskite and the absence of interfacial barrier layer between perovskite and carbon electrode cause profound open-circuit voltage (V OC) loss, which results in uncompetitive power conversion efficiency (PCE). Herein, an anion-cation synergy of decylammonium sulfate (DA2SO4) is utilized for suppressing V OC loss of p-MPSCs via a facile post-treatment method. DA+ cations transform the perovskite adjacent to carbon electrode into wide-bandgap 2D perovskite for blocking electrons, while the SO4 2− anions interact with undercoordinated lead centers for reducing defect density. As a result, the modified device delivers an enhanced PCE from 17.78% to 19.59%, with an improved V OC from 0.98 V to 1.06 V. Meanwhile, the modified device without any encapsulation exhibits excellent moisture stability with the PCE remained almost 99% of the initial value after 528 h aging in 75% RH air at room temperature.

Abstract Digital transformation (DX) has become an important strategy for the sustainable development of traditional manufacturers. However, the impact of DX on the environment is still inconclusive, and whether it is beneficial for manufacturers to reduce total carbon emissions remains to be examined. Therefore, based on the carbon cap-and-trade policy, this paper employs a game-theoretic model to study the DX strategies of duopolistic manufacturers and to explore the influence of low-carbon policy on these strategies. Additionally, we compare the total carbon emissions before and after DX implementation by manufacturers, discussing the environmental implications of DX. And we innovatively segment the market into two scenarios: one with a low digital technology level and the other with a high digital technology level. Our research demonstrates that the appropriate DX strategy can not only boost manufacturers’ profits but also enhance their ability to withstand external shocks. In the scenario with a high level of digital technology, manufacturers can achieve greater profits and are more likely to reduce total carbon emissions, resulting in a win-win situation. Sensitivity analysis reveals that an increase in carbon trading prices encourages manufacturers to ramp up their investments, ultimately driving comprehensive DX. This study not only provides decision-making guidance for the DX of manufacturers, but also provides a direction for the government to promote DX and achieve carbon neutralization.

Digital in-line holographic microscopy (DIHM) is a widely used interference technique for real-time reconstruction of living cells’ morphological information with large space-bandwidth product and compact setup. However, the need for a larger pixel size of detector to improve imaging photosensitivity, field-of-view, and signal-to-noise ratio often leads to the loss of sub-pixel information and limited pixel resolution. Additionally, the twin-image appearing in the reconstruction severely degrades the quality of the reconstructed image. The deep learning (DL) approach has emerged as a powerful tool for phase retrieval in DIHM, effectively addressing these challenges. However, most DL-based strategies are data-driven or end-to-end net approaches, suffering from excessive data dependency and limited generalization ability. Herein, a novel multi-prior physics-enhanced neural network with pixel super-resolution (MPPN-PSR) for phase retrieval of DIHM is proposed. It encapsulates the physical model prior, sparsity prior and deep image prior in an untrained deep neural network. The effectiveness and feasibility of MPPN-PSR are demonstrated by comparing it with other traditional and learning-based phase retrieval methods. With the capabilities of pixel super-resolution, twin-image elimination and high-throughput jointly from a single-shot intensity measurement, the proposed DIHM approach is expected to be widely adopted in biomedical workflow and industrial measurement.

ObjectiveTo analyze the whole-genome characteristics of four coxsackievirus B5 (CVB5) strains isolated in Yunnan province, China in 2022. MethodsPrimers were designed to amplify and sequence the whole genome of CVB5 isolates. The whole genome was amplified in segments, and sequenced using the "primer walking" method. Sequence splicing and assembly were performed. Genetic characteristics of the CVB5 strains were analyzed using software such as MEGA 7.0, Simplot 3.5.1, and DNAStar 7.1. ResultsBased on VP1 and whole-genome phylogenetic analysis, all four CVB5 isolates belonged to genotype C. Compared with the prototype strain, multiple amino acid mutations occurred in the VP1 region of the four strains. Phylogenetic analysis of P1, P2, and P3 regions and Simplot recombination analysis showed that the CVB5 isolates in this study may have undergone recombination with multiple enterovirus B strains. ConclusionThe four CVB5 strains isolated from clinical samples of hand, foot and mouth disease (HFMD) patients in Kunming, Yunnan province in 2022 all belonged to genotype C.

Abstract Background The prevalence of clinically diagnosed depressive disorders (DD) in Chinese left-behind children (LBC) remains unknown. We aim to estimate the prevalence of DD, discuss the associations between DD and self-harm (SH) behaviors in a large representative sample of Chinese LBCs chosen from Yunnan province. Methods A total of 5462 LBCs were selected from the most recent datasets of the Mental Health Survey for Children and Adolescents in Yunnan (MHSCAY), a mega population-based two-phase cross-sectional survey. Weighted prevalence rates and designed Logistic regression were adopted to estimate the prevalence of DD and the association between DD and SH. Results The weighted prevalence of lifetime and current DD were 4.22% (95% CI: 3.13-6.00%) and 3.84% (95% CI: 2.85-5.00%) in Chinese LBCs. Higher lifetime and current DD prevalence rates were observed in girls and those reported adverse parental marital status and SH behaviors. The absence of DD was associated with significantly decreased odds of SH behavior (OR = 0.06), repetitive SH (OR = 0.09), using multiple SH methods (OR = 0.09), and severe SH (OR = 0.15). Subsequently performed stratified analyses identified prominent effect modification by sex and age, as a stronger association between DD and SH was found in girls (OR = 0.02 versus OR = 0.07 in boys) and younger adolescents (OR = 0.08 versus OR = 0.22 in older adolescents). Conclusion The prevalence of DD was high in Chinese LBCs. DD was associated with prominently increased risk of SH behaviors in LBCs. Attention and intervention are needed in this vulnerable population.

Abstract Moso bamboo (Phyllostachys edulis), an ecologically and economically important forest species in East Asia, plays vital roles in carbon sequestration and climate change mitigation. However, intensifying climate change threatens moso bamboo survival. Here we generate high-quality haplotype-based pangenome assemblies for 16 representative moso bamboo accessions and integrated these assemblies with 427 previously resequenced accessions. Characterization of the haplotype-based pangenome reveals extensive genetic variation, predominantly between haplotypes rather than within accessions. Many genes with allele-specific expression patterns are implicated in climate responses. Integrating spatiotemporal climate data reveals more than 1050 variations associated with pivotal climate factors, including temperature and precipitation. Climate-associated variations enable the prediction of increased genetic risk across the northern and western regions of China under future emissions scenarios, underscoring the threats posed by rising temperatures. Our integrated haplotype-based pangenome elucidates moso bamboo’s local climate adaptation mechanisms and provides critical genomic resources for addressing intensifying climate pressures on this essential bamboo. More broadly, this study demonstrates the power of long-read sequencing in dissecting adaptive traits in climate-sensitive species, advancing evolutionary knowledge to support conservation.

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.

In order to obtain endophytic selenium-rich yeast from Lycium barbarum with strong ability producing alcohol and aroma, and then promote the selenium-rich fermentation products and improve the flavor, this study took the endophytic yeast of L. barbarum stored in the laboratory as experimental materials, and the yeast with strong selenium-rich ability was obtained through the initial screening of selenium-resistant method and red selenium methods. Atmospheric room temperature plasma (ARTP) technology was used to obtain mutant strains and through TTC medium, Duchenne tubule fermentation, alcohol production, ester and acid production, tolerance and other experiments to screen out the target strains of aroma enhancement and high alcohol production. The content of selenium in yeast cell and fermentation liquid was determined by hydride generation atomic fluorescence spectrometry. The results showed that M1 Saccharomyces cerevisiae and M16 Clavispora lusitaniae were obtained by primary selenium screening, the mutagenic strain M1-5 of S. cerevisiae with higher alcohol production capacity and the mutagenic strain M16-28 of C. lusitaniae with higher aroma production capacity were obtained through ARTP mutagenesis. The alcohol production capacity of M1-5 increased by 38.07% compared with M1, and the ester production capacity of M16-28 increased by 107.62% compared with M16, and the genetic stability was good. The selenium contents in the intracellular and fermentation broth of the M1-5 strains were 204.8 and 1158 μg/L, respectively, and in M16-28 were 666.45μg/L and 1830 μg/L, respectively. Therefore, the selenium enrichment capacity of M16-28 was higher than that of M1-5, and the selenium content of fermentation liquid was extremely significantly higher than that of yeast cells (P

Abstract Persistent subretinal fluid (PSF) after scleral bucking of rhegmatogenous retinal detachment may delay recovery and affect the final visual quality, but with no effective treatment. This study firstly investigated the safety and efficacy of 577 nm yellow subthreshold micropulse laser (SML) on PSF after scleral bucking surgery. This double-masked randomized clinical trial was conducted from December 2020 to October 2022 at Chongqing Aier Eye Hospital. Participants with PSF last for 1 month after scleral bucking surgery with break closed and retina reattachment were recruitment. These participants were treated by 577 nm yellow SML or sham treatment. Funduscopy, optical coherence tomography (OCT) volume change, best corrected vision acuity (BCVA) and visual field test were evaluated for six mouths follow-up. A total of 24 participants were randomized into SML group or Sham group equally. Compared with Sham group, the OCT volume within 6 mm of macular fovea was significantly less in SML group 6 months after therapy (P = 0.048). There were no statistically significant differences of OCT volume at 1, 2 and 3 months from baseline between groups. BCVA of ETDRS letters had no statistically significant difference. Pattern Standard Deviation amelioration (P = 0.039) had statistically significance in SML group compared with Sham group. There were no complications in the 2 groups. These preliminary findings suggest that 577 nm yellow SML therapy could accelerate PSF absorption after scleral bucking surgery. Trial registration: Chinese Clinical Trial Registry No. ChiCTR2000037838, 02/09/2020, https://www.chictr.org.cn/showproj.html?proj=51885 .