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Abstract Due to the fact that the vibration and pure rotational Raman signals collected by the temperature and humidity profile lidar were 3–4 orders of magnitude weaker than the Mie scattering signal, they were susceptible to electronic and white noise interference, which seriously affected the system signal-to-noise ratio. In this paper, an improved VMD-WT filtering method was adopted to extract effective signals and denoise. The processing outcome of several filtering algorithms was evaluated, and noisy signals were simulated to confirm the algorithm's efficacy. Based on the quantitative computation of evaluation indicators, such as signal-to-noise ratio, root mean square error, and correlation, the improved VMD-WT algorithm had more significant advantages in indicators such as signal-to-noise ratio. In order to further verify the robustness and adaptability of the proposed algorithm, experimental analysis of the filtering algorithm was conducted on the continuously collected temperature and humidity measured signals. The results demonstrated that the algorithm not only improved the detection range of lidar and suppressed high-altitude noise effectively, but also performed well in processing strong interference signals, like clouds, which led to a significant improvement in the atmospheric optical parameter inversion results. Furthermore, pseudo-color images of aerosols, temperature, and humidity changes over time and space have been used to further illustrate the algorithm's dependability and wide range of potential uses.

Abstract Abnormal cardiac development has been observed in individuals with Cornelia de Lange syndrome (CdLS) due to mutations in genes encoding members of the cohesin complex. However, the precise role of cohesin in heart development remains elusive. In this study, we aimed to elucidate the indispensable role of SMC3, a component of the cohesin complex, in cardiac development and its underlying mechanism. Our investigation revealed that CdLS patients with SMC3 mutations have high rates of congenital heart disease (CHD). We utilized heart-specific Smc3-knockout (SMC3-cKO) mice, which exhibit varying degrees of outflow tract (OFT) abnormalities, to further explore this relationship. Additionally, we identified 16 rare SMC3 variants with potential pathogenicity in individuals with isolated CHD. By employing single-nucleus RNA sequencing and chromosome conformation capture high-throughput genome-wide translocation sequencing, we revealed that Smc3 deletion downregulates the expression of key genes, including Ets2, in OFT cardiac muscle cells by specifically decreasing interactions between super-enhancers (SEs) and promoters. Notably, Ets2-SE-null mice also exhibit delayed OFT development in the heart. Our research revealed a novel role for SMC3 in heart development via the regulation of SE-associated genes, suggesting its potential relevance as a CHD-related gene and providing crucial insights into the molecular basis of cardiac development.

Abstract Given the growing emphasis on energy efficiency, environmental sustainability, and agricultural demand, there’s a pressing need for decentralized and scalable ammonia production. Converting nitrate ions electrochemically, which are commonly found in industrial wastewater and polluted groundwater, into ammonia offers a viable approach for both wastewater treatment and ammonia production yet limited by low producibility and scalability. Here we report a versatile and scalable solution-phase synthesis of high-entropy single-atom nanocages (HESA NCs) in which Fe and other five metals-Co, Cu, Zn, Cd, and In-are isolated via cyano-bridges and coordinated with C and N, respectively. Incorporating and isolating the five metals into the matrix of Fe resulted in Fe-C5 active sites with a minimized symmetry of lattice as well as facilitated water dissociation and thus hydrogenation process. As a result, the Fe-HESA NCs exhibited a high selectivity toward NH3 from the electrocatalytic reduction of nitrate with a Faradaic efficiency of 93.4% while maintaining a high yield rate of 81.4 mg h−1 mg−1.

Abstract The clinical course of COVID-19 is variable and often unpredictable. To test the hypothesis that disease progression and inflammatory responses associate with alterations in the microbiome and metabolome, we analyzed metagenome, metabolome, cytokine, and transcriptome profiles of repeated samples from hospitalized COVID-19 patients and uninfected controls, and leveraged clinical information and post-hoc confounder analysis. Severe COVID-19 was associated with a depletion of beneficial intestinal microbes, whereas oropharyngeal microbiota disturbance was mainly linked to antibiotic use. COVID-19 severity was also associated with enhanced plasma concentrations of kynurenine and reduced levels of several other tryptophan metabolites, lysophosphatidylcholines, and secondary bile acids. Moreover, reduced concentrations of various tryptophan metabolites were associated with depletion of Faecalibacterium, and tryptophan decrease and kynurenine increase were linked to enhanced production of inflammatory cytokines. Collectively, our study identifies correlated microbiome and metabolome alterations as a potential contributor to inflammatory dysregulation in severe COVID-19.

Osteosarcoma is the most common malignant bone tumor without efficient management for improving 5-year event-free survival. Immunotherapy is also limited due to its highly immunosuppressive tumor microenvironment (TME). Pore-forming gasdermins (GSDMs)-mediated pyroptosis has gained increasing concern in reshaping TME, however, the expressions and relationships of GSDMs with osteosarcoma remain unclear. Herein, gasdermin E (GSDME) expression is found to be positively correlated with the prognosis and immune infiltration of osteosarcoma patients, and low GSDME expression was observed. A vector termed as LPAD contains abundant hydroxyl groups for hydrating layer formation was then prepared to deliver the GSDME gene to upregulate protein expression in osteosarcoma for efficient TME reshaping via enhanced pyroptosis induction. Atomistic molecular dynamics simulations analysis proved that the hydroxyl groups increased LPAD hydration abilities by enhancing coulombic interaction. The upregulated GSDME expression together with cleaved caspase-3 provided impressive pyroptosis induction. The pyroptosis further initiated proinflammatory cytokines release, increased immune cell infiltration, activated adaptive immune responses and create a favorable immunogenic hot TME. The study not only confirms the role of GSDME in the immune infiltration and prognosis of osteosarcoma, but also provides a promising strategy for the inhibition of osteosarcoma by pore-forming GSDME gene delivery induced enhanced pyroptosis to reshape the TME of osteosarcoma.

Abstract The range-resolved differential absorption lidar is a high-precision device to measure the concentration of carbon dioxide. This paper provides a system-wide theoretical analysis method for the performance analysis and parameter optimization of the lidar system using the given parameter range. The scattered echo signal, signal-to-noise ratio, and detection sensitivity were simulated by setting assumed parameters with the HITRAN 2020 database and the US 1976 standard atmosphere model to analyze the detection distance and concentration resolution of the lidar system. The effects of the laser energy, repetition frequency, and photodetector noise were also discussed. The wavelength selection near the absorption line is critical because it controls the height region of the highest sensitivity and the demands on frequency stability. Recommendations for the selection of absorption lines are provided in this paper. A quantitative analysis of each error source provided reasonable error ranges.

Abstract Circadian rhythm disorder (CRD) is closely associated with hair regression and shedding, but whether this risk can be transmitted to the offspring is unknown. Whether Pu‐erh tea, with alleviating effects of CRD‐mediated syndrome, can act on the transmission of alopecia risk to offspring is also unproven. Here, we obtained CRD parental mice offspring and found that CRD‐mediated alopecia risk can be transmitted to offspring, especially male offspring. Parental consumption of Pu‐erh tea, especially in females or both parents, reduced the risk of CRD‐mediated alopecia transmitted to offspring by inhibiting subcutaneous fat accumulation (downregulation of Rab18, fat‐specific protein 27 (Fsp27), and perilipin 1 (Plin1)), reducing oxidative stress and inflammation in skin tissue (NADPH oxidase 4 (NOX4)/ nuclear factor kappa‐B (NF‐κB)), balancing androgen and hair growth factor release (hepatocyte growth factor (HGF), vascular endothelial growth factor (VEGF), insulin‐like growth factor 1 (IGF‐1)), and restoring hair follicle DNA repair function (upregulation of Ku70, 8‐Oxoguanine DNA glycosylase 1 (OGG1), and Rad51). Transcriptomic analysis further clarified that the mechanism stemmed from the upregulation of gene expression in pathways such as the Wnt, Hippo, and other signaling pathways.

Abstract Mucus injury associated with goblet cell (GC) depletion constitutes an early event in inflammatory bowel disease (IBD). Using single-cell sequencing to detect critical events in mucus dysfunction, we discover that the Kazal-type serine protease inhibitor SPINK4 is dynamically regulated in colitic intestine in parallel with disease activities. Under chemically induced colitic conditions, the grim status in Spink4-conditional knockout mice is successfully rescued by recombinant murine SPINK4. Notably, its therapeutic potential is synergistic with existing TNF-α inhibitor infliximab in colitis treatment. Mechanistically, SPINK4 promotes GC differentiation using a Kazal-like motif to modulate EGFR-Wnt/β-catenin and -Hippo pathways. Microbiota-derived diacylated lipoprotein Pam2CSK4 triggers SPINK4 production. We also show that monitoring SPINK4 in circulation is a reliable noninvasive technique to distinguish IBD patients from healthy controls and assess disease activity. Thus, SPINK4 serves as a serologic biomarker of IBD and has therapeutic potential for colitis via intrinsic EGFR activation in intestinal homeostasis.

Key components of the existing external meshing dorsal spine plunger-type molding machine were modeled in three dimensions, and the fatigue life analysis of the molding machine spindle was carried out by using Ansys software. Due to the nonlinear mechanical behavior of the material ring mold, and pressure roller in the granulation process, there are a lot of contacts and collisions. Using the linear mechanics model is difficult to analyze. To achieve more accurate and realistic results, an Edem-Ansys joint coupled simulation was carried out for the pressure roller and ring mold engagement process. The results showed that the stress concentration point and fatigue weak region of the spindle occurred at the shaft cross-section, where the stress value should be less than 0.75 F. The maximum stresses and strains in the engagement process of the pressure roller and the ring die body occurred at the engagement point. The maximum values of deformation, stress, and strain were 0.039 mm, 412 MPa, and 0.002 mm/mm, respectively, which are all within the reasonable range and meet the design requirements.

ObjectiveIn response to the problems of high weight and relatively low protective efficiency associated with traditional multicamerate structures (i.e., void compartment-liquid tank-void compartment), this study explores the protective performance of underwater cylindrical protective structures. Methods A numerical model based on an arbitrary Lagrangian-Eulerian (ALE) algorithm is established and verified through a contact explosion case involving a typical structure. On this basis, models of the traditional multicamerate protective structure and cylindrical protective structure are then established. Through numerical simulation, parameters such as maximal stress, strain and energy absorption after underwater contact explosion with the same explosive charge are analyzed, and their respective protective performances obtained.ResultsThe displacement of the defended longitudinal wall of the cylindrical protective structure is smaller than that of the watertight longitudinal wall, which is contrary to the behavior of traditional multicamerate protective structures. Additionally, the energy absorbed by the deck and double bottom is 9.92% less than that of the traditional protective structure, demonstrating a significant advantage in resisting deformation in the vertical direction.ConclusionThe results of this study indicate that the cylindrical protective structure exhibits a lower level of damage under the same charge, providing new insights for the innovative design of underwater protection structures.

IntroductionThis study explores doctors’ and patients’ understandings of citizen journalism on doctor–patient relationship issues. It also examines the communication effect of citizen journalism as a communication platform on doctors and patients who are taking part in the doctor–patient relationship in contemporary China.MethodThis study draws on the analysis of 24 semi-structured interviews with doctors from both publicly funded and privately operated hospital, and nine focus groups which included 36 patients with different socio-economic backgrounds.ResultThe empirical research present the following results: (1) authority and witness are the two key factors to construct the stakeholders’(doctors’ and patients’) awareness and trust of citizen journalist reporting on the doctor–patient relationship issues. (2) stakeholders’ perception on citizen journalism will construct them concern on the uncertain and unfamiliar knowledge during the hospital activities.DiscussionThe interpretation of doctor–patient relationship reports by doctors and patients affects their mutual trust. Authority and witnessing are two key factors that citizen journalists should consider when reporting on doctor–patient relationship news. Doctors from different types of hospitals and patients with different income levels have different understandings of the authority and witnessing of the reported content. Reading the content of doctor–patient conflicts reflected in citizen journalist reports can exacerbate the emotional fluctuations of doctors and patients. After reading these reports, doctors and patients may experience increased anxiety about uncertainty and unfamiliarity in doctor–patient communication.ContributionThis study provides a framework for public health research from the relationship between communication content and audience. It also provides answers from the perspectives of media and stakeholders to investigate the tension in doctor–patient relationships in China.

Abstract 2D polymers have emerged as a highly promising category of nanomaterials, owing to their exceptional properties. However, the understanding of their fracture behavior and failure mechanisms remains still limited, posing challenges to their durability in practical applications. This work presents an in‐depth study of the fracture kinetics of a 2D polyimine film, utilizing in situ tensile testing within a transmission electron microscope (TEM). Employing meticulously optimized transferring and patterning techniques, an elastic strain of ≈6.5% is achieved, corresponding to an elastic modulus of (8.6 ± 2.5) GPa of polycrystalline 2D polyimine thin films. In step‐by‐step fractures, multiple cracking events uncover the initiation and development of side crack near the main crack tip which toughens the 2D film. Simultaneously captured strain evolution through digital image correlation (DIC) analysis and observation on the crack edge confirm the occurrence of transgranular fracture patterns apart from intergranular fracture. A preferred cleavage orientation in transgranular fracture is attributed to the difference in directional flexibility along distinct orientations, which is substantiated by density functional‐based tight binding (DFTB) calculations. These findings construct a comprehensive understanding of intrinsic mechanical properties and fracture behavior of an imine‐linked polymer and provide insights and implications for the rational design of 2D polymers.

Abstract An efficient and facile water dissociation process plays a crucial role in enhancing the activity of alkaline hydrogen evolution reaction (HER). Considering the intricate influence between interfacial water and intermediates in typical catalytic systems, meticulously engineered catalysts should be developed by modulating electron configurations and optimizing surface chemical bonds. Here, a high‐entropy double perovskite (HEDP) electrocatalyst La2(Co1/6Ni1/6Mg1/6Zn1/6Na1/6Li1/6)RuO6, achieving a reduced overpotential of 40.7 mV at 10 mA cm−2 and maintaining exemplary stability over 82 h in a 1 m KOH electrolyte is reported. Advanced spectral characterization and first‐principles calculations elucidate the electron transfer from Ru to Co and Ni positions, facilitated by alkali metal‐induced super‐exchange interaction in high‐entropy crystals. This significantly optimizes hydrogen adsorption energy and lowers the water decomposition barrier. Concurrently, the super‐exchange interaction enhances orbital hybridization and narrows the bandgap, thus improving catalytic efficiency and adsorption capacity while mitigating hysteresis‐driven proton transfer. The high‐entropy framework also ensures structural stability and longevity in alkaline environments. The work provides further insights into the formation mechanisms of HEDP and offers guidelines for discovering advanced, efficient hydrogen evolution catalysts through super‐exchange interaction.

College teacher educators play a crucial role in improving teaching quality and have a significant impact on educational development. They must engage in a process of self-growth to achieve personal development, considering the interaction between individuals and their environment. This process involves deep exploration of their knowledge, skills, and attitudes, as well as an understanding of the broader institutional and cultural contexts. Through self-reflection and continuous learning, college teacher educators can foster personal growth by acquiring new teaching strategies, developing effective communication and interpersonal skills, and cultivating a reflective and adaptive teaching practice. Collaboration with colleagues, engagement with professional communities, and involvement in educational research and innovation are also essential aspects of personal growth. Creating supportive environments that facilitate the continuous development of college teacher educators is crucial for enhanced teaching quality and educational advancement. In this study, an artificial neural network (ANN) was employed to estimate the impact of changes in knowledge and skill development and reflection and continuous learning on the acquisition of new educational strategies, development of communication and interpersonal skills, and reflective and adaptive practice. The ANN's predictions indicate that increasing reflection and continuous learning has a more positive impact on acquiring new educational strategies compared to increasing knowledge and skill development alone. Additionally, when both knowledge and skill development and reflection and continuous learning are combined, it results in substantial growth in the development of communication and interpersonal skills and reflective and adaptive practice. The accuracy of the neural network's predictions was evaluated using linear regression, showing an acceptable level of error when compared to the experimental results.

Background: The Peripherally Inserted Central Catheter (PICC) is a widely used technique for delivering intravenous fluids and medications, especially in critical care units. PICC may induce venous thrombosis (PICC-RVT), which is a frequent and serious complication. In clinical practice, Color Doppler Flow Imaging (CDFI) is regarded as the gold standard for diagnosing PICC-RVT. However, CDFI not only requires prominent time and effort from experienced healthcare professionals, but also relies on the formation and development of PICC-RVT, especially at early stages of PICC-RVT, when PICC-RVT is not apparent. A prognosis tool for PICC-RVT is crucial to bridge the gap between its diagnosis and treatment, especially in resource-limited settings, such as remote healthcare facilities. Objective: Evaluate over 14,885 models from various machine learning techniques to identify an effective prognostic model (referred to as PRAD - PICC-RVT Assessment via Deep-learning) for quantifying the risks associated with PICC-RVT. Methods: To tackle the challenges associated with PICC-RVT diagnosis, we gathered a comprehensive dataset of 5,272 patients from 27 healthcare centers across China. From a pool of 14885 models from various machine learning techniques, we systematically screened a data-driven prognostic model to quantify the risks associated with PICC-RVT. This model aims to provide objective evidence, and facilitate timely interventions. Results: The proposed model displayed exceptional predictive accuracy, achieving an accuracy of 86.4 % and an AUC of 0.837. Based on the prognosis model, we further incorporated a weight analysis to identify the major contributing factors for PICC-RVT risk during catheterization. Albumin levels, primary diagnosis, hemoglobin levels, platelet levels, and education level are emphasized as important risk factors. Conclusions: Our method excels in predicting early PICC-RVT risks, especially in asymptomatic patients. The findings in this paper offers insights into controllable PICC risk factors that could benefit vast patients and reduce disease burden through stratification and early intervention.

Objective The goal of the present research was to evaluate the effectiveness of physical exercise intervention in enhancing psychological well-being and decreasing symptoms of depression among college students, adopting a systematic review and meta-analysis. Methodology The study was performed by searching four databases (PubMed, Embase, Web of Science, and the Cochrane Library) to determine randomized controlled trials (RCTs) exploring the impacts of physical exercise therapies among college students with symptoms of depression. The sequential execution of a meta-analyses, subgroup analyses, and publication bias analyses was accomplished utilizing the software package RevMan version 5.3. Results There were eight articles included. This research demonstrated a significant impact (d = −0.75, P < 0.05), indicating that physical exercise has a substantial impact on decreasing or mitigating depression. The subgroup analyses revealed that interventions involving physical exercise workouts lasting 12 weeks or longer (d = −0.93, P < 0.05), with physical exercise sessions lasting between 30 and 60 min (d = −0.77, P < 0.05), and with physical exercise performed minimum of three times a week (d = −0.90, P < 0.05) were the most effective in reducing symptoms of depression. Conclusion Physical exercise interventions have a beneficial impact on reducing depression among college students. The optimal mode was discovered to be college students participating in each session for a duration of 30 to 60 min, at least three times per week, and for more than 12 weeks. College students are encouraged to cultivate a consistent and long-term physical exercise routine to sustain their physical and mental health.

This study presents a numerical investigation of a novel spiral finned heat exchanger (SFHE). The primary objective is to optimize the heat transfer efficiency of micro gas turbine recuperators by employing a spiral fin model. Through computational simulations (CFD), the study examines the variations in the Colburn j factor and Fanning friction f factor as the spiral fins alter. The results demonstrate that the SFHE exhibits superior heat transfer capacity and overall heat transfer performance compared to wavy fin models. At a Reynolds number of 1000, the JF factor of the spiral fin 35_125 is 70.47 % higher than that of a wavy fin at the same Reynolds number, and 34.03 % higher when the Reynolds number increases to 5000. The study also reveals that the cutting thickness of the top and bottom, denoted as C1, does not significantly impact the variable j, f. However, increasing the cut thickness C2 on the left and right sides results in a more compact model, leading to higher values of f, but the j-factor is almost unchanged. While decreasing the wavelength of the spiral fins can improve heat transfer efficiency, it also increases pressure loss, necessitating careful selection of wavelength for optimal SFHE design.

Due to their extraordinary durability and thermal stability, Epoxy Resin Thermosets (ERTs) are essential in various industries. However, their poor recyclability leads to unacceptable environmental pollution. In this study, Wu et al. successfully synthesized a completely bio-based ERT using lignocellulose-derived building blocks which exhibit outstanding thermal and mechanical properties. Remarkably, these bio-materials degrade via methanolysis without the need of any catalyst, presenting a smart and cost-effective recycling strategy. Furthermore, this approach could be employed for fabricating reusable composites comprising glass fiber and plant fiber, thereby expanding its applications in sustainable transportation, coatings, paints or biomedical devices.

Abstract Background Polypharmacy would increase the risk of adverse drug events and the burden of renal drug excretion among older people. Nevertheless, the association between the number of medication and the risk of chronic kidney disease (CKD) remains controversial. Therefore, this study aims to investigate the association between the number of medication and the incidence of CKD in older people. Methods This study investigates the association between the number of medications and CKD in 2672 elderly people (≥ 65 years older) of the community health service center in southern China between 2019 and 2022. Logistic regression analysis was used to evaluate the relationship between polypharmacy and CKD. Results At baseline, the average age of the study subjects was 71.86 ± 4.60, 61.2% were females, and 53 (2.0%) suffer from polypharmacy. During an average follow-up of 3 years, new-onset CKD developed in 413 (15.5%) participants. Logistic regression analysis revealed that taking a higher number of medications was associated with increase of CKD. Compared with people who didn’t take medication, a higher risk of CKD was observed in the older people who taken more than five medications (OR 3.731, 95% CI 1.988, 7.003), followed by those who take four (OR 1.621, 95% CI 1.041, 2.525), three (OR 1.696, 95% CI 1.178, 2.441), two drugs (OR 1.585, 95% CI 1.167, 2.153), or one drug (OR 1.503, 95% CI 1.097, 2.053). Furthermore, age, systolic blood pressure (SBP), white blood cell (WBC), blood urea nitrogen (BUN) and triglyceride (TG) were also independent risk factors CKD (P

Abstract Background Human hematopoietic organoids have a wide application value for modeling human bone marrow diseases, such as acute hematopoietic radiation injury. However, the manufacturing of human hematopoietic organoids is an unaddressed challenge because of the complexity of hematopoietic tissues. Methods To manufacture hematopoietic organoids, we obtained CD34+ hematopoietic stem and progenitor cells (HSPCs) from human embryonic stem cells (hESCs) using stepwise induction and immunomagnetic bead-sorting. We then mixed these CD34+ HSPCs with niche-related cells in Gelatin-methacryloyl (GelMA) to form a three-dimensional (3D) hematopoietic organoid. Additionally, we investigated the effects of radiation damage and response to granulocyte colony-stimulating factor (G-CSF) in hematopoietic organoids. Results The GelMA hydrogel maintained the undifferentiated state of hESCs-derived HSPCs by reducing intracellular reactive oxygen species (ROS) levels. The established hematopoietic organoids in GelMA with niche-related cells were composed of HSPCs and multilineage blood cells and demonstrated the adherence of hematopoietic cells to niche cells. Notably, these hematopoietic organoids exhibited radiation-induced hematopoietic cell injury effect, including increased intracellular ROS levels, γ-H2AX positive cell percentages, and hematopoietic cell apoptosis percentages. Moreover, G-CSF supplementation in the culture medium significantly improved the survival of HSPCs and enhanced myeloid cell regeneration in these hematopoietic organoids after radiation. Conclusions These findings substantiate the successful manufacture of a preliminary 3D hematopoietic organoid from hESCs-derived HSPCs, which was utilized for modeling hematopoietic radiation injury and assessing the radiation-mitigating effects of G-CSF in vitro. Our study provides opportunities to further aid in the standard and scalable production of hematopoietic organoids for disease modeling and drug testing.

Abstract In order to solve the problems of slow detection speed, large number of parameters and large computational volume of deep learning based gangue target detection method, we propose an improved algorithm for gangue target detection based on Yolov5s. First, the lightweight network EfficientVIT is used as the backbone network to increase the target detection speed. Second, C3_Faster replaces the C3 part in the HEAD module, which reduces the model complexity. once again, the 20 × 20 feature map branch in the Neck region is deleted, which reduces the model complexity; thirdly, the CIOU loss function is replaced by the Mpdiou loss function. The introduction of the SE attention mechanism makes the model pay more attention to critical features to improve detection performance. Experimental results show that the improved model size of the coal gang detection algorithm reduces the compression by 77.8%, the number of parameters by 78.3% the computational cost is reduced by 77.8% and the number of frames is reduced by 30.6%, which can be used as a reference for intelligent coal gangue classification.

Abstract The pressing demand for sustainable energy storage solutions has spurred the burgeoning development of aqueous zinc batteries. However, kinetics-sluggish Zn2+ as the dominant charge carriers in cathodes leads to suboptimal charge-storage capacity and durability of aqueous zinc batteries. Here, we discover that an ultrathin two-dimensional polyimine membrane, featured by dual ion-transport nanochannels and rich proton-conduction groups, facilitates rapid and selective proton passing. Subsequently, a distinctive electrochemistry transition shifting from sluggish Zn2+-dominated to fast-kinetics H+-dominated Faradic reactions is achieved for high-mass-loading cathodes by using the polyimine membrane as an interfacial coating. Notably, the NaV3O8·1.5H2O cathode (10 mg cm−2) with this interfacial coating exhibits an ultrahigh areal capacity of 4.5 mAh cm−2 and a state-of-the-art energy density of 33.8 Wh m−2, along with apparently enhanced cycling stability. Additionally, we showcase the applicability of the interfacial proton-selective coating to different cathodes and aqueous electrolytes, validating its universality for developing reliable aqueous batteries.

This study proposes a battery thermal management system based on L-shaped heat pipes coupled with liquid cooling. Experimental and computational fluid dynamics (CFD) numerical simulation studies have been conducted on the performance of the thermal management system. The thermal performance of three heat dissipation methods including forced air cooling, bottom liquid cooling and heat pipe coupled liquid cooling were compared. The results demonstrate that the coupling system can control the maximum temperature and temperature difference of the module at 30.12°C and 2.02°C at a 3C discharge rate. Compared with forced air cooling and bottom liquid cooling, the maximum temperature was decreased by 30.16% and 17.01% and the temperature difference was decreased by 72.14% and 77.20%, respectively. Studied the impact of factors such as coolant flow rate, the number of liquid-cooled plate channels, and the coolant inlet temperature under different ambient temperatures on the thermal management performance of the coupled system. By monitoring the maximum temperature of the module and the ambient temperature, a method for controlling the flow rate and the inlet temperature of the cooling water has been developed to implement an intermittent liquid cooling strategy for the battery module. Intermittent liquid cooling at various ambient temperatures can obtain similar thermal management performance to continuous liquid cooling, while significantly reducing liquid cooling energy consumption. Compared to continuous liquid cooling, intermittent liquid cooling can reduce energy consumption by a maximum of 97.05% and a minimum of 30.00%.

Abstract The mechanism involved in major depressive disorder (MDD) is well‐studied but the mechanistic origin of the heterogeneous antidepressant effect remains largely unknown. Single‐cell RNA‐sequencing (scRNA‐seq) and assay for transposase‐accessible chromatin using sequencing (ATAC‐seq) on peripheral blood mononuclear cells from 8 healthy individuals and 8 MDD patients before or after 12 weeks of antidepressant treatment is performed. scRNA‐seq analysis reveals a lower proportion of naive T cells, particularly CD4+ naive T cells, in MDD patients compared to controls, and in nonresponders versus responders at the baseline. Flow cytometry data analysis of an independent cohort of 35 patients and 40 healthy individuals confirms the findings. Enrichment analysis of differentially expressed genes indicated obvious immune activation in responders. A specific activated CD4+ naive T population in responders characterized by enhanced mitogen‐activated protein kinases (MAPK) pathway is identified. E‐twenty six (ETS) is proposed as an upstream regulator of the MAPK pathway and heterogeneous differentiation in activated CD4+ naive T population is associated with the response to antidepressant treatment in MDD patients. A distinct immune feature manifested by CD4+ naive T cells during antidepressant treatment in MDD is identified. Collectively, this proposes the molecular mechanism that underlies the heterogeneous antidepressant outcomes for MDD.

Background & Aims: Persistent cholestasis has been associated with poor prognosis after orthotopic liver transplantation. In this study, we aimed to investigate how the accumulation of tauro-beta-muricholic acid (TβMCA), resulting from the reprogramming of bile acid (BA) metabolism during liver ischemia/reperfusion (IR) stress, attenuates liver inflammation. Methods: Ingenuity Pathway Analysis was performed using transcriptome data from a murine hepatic IR model. Three different models of hepatic IR (liver warm IR, bile duct separation-IR, common bile duct ligation-IR) were employed. We generated adeno-associated virus-transfected mice and CD11b-DTR mice to assess the role of BAs in regulating the myeloid S1PR2-GSDMD axis. Hepatic BA levels were analyzed using targeted metabolomics. Finally, the correlation between the reprogramming of BA metabolism and hepatic S1PR2 levels was validated through RNA-seq of human liver transplant biopsies. Results: We found that BA metabolism underwent reprogramming in murine hepatocytes under IR stress, leading to increased synthesis of TβMCA, catalyzed by the enzyme CYP2C70. The levels of hepatic TβMCA were negatively correlated with the severity of hepatic inflammation, as indicated by the serum IL-1β levels. Inhibition of hepatic CYP2C70 resulted in reduced TβMCA production, which subsequently increased serum IL-1β levels and exacerbated IR injury. Moreover, our findings suggested that TβMCA could inhibit canonical inflammasome activation in macrophages and attenuate inflammatory responses in a myeloid-specific S1PR2-GSDMD-dependent manner. Additionally, Gly-βMCA, a derivative of TβMCA, could effectively attenuate inflammatory injury in vivo and inhibit human macrophage pyroptosis in vitro. Conclusions: IR stress orchestrates hepatic BA metabolism to generate TβMCA, which attenuates hepatic inflammatory injury by inhibiting the myeloid S1PR2-GSDMD axis. Bile acids have immunomodulatory functions in liver reperfusion injury that may guide therapeutic strategies. Impact and implications:: Our research reveals that liver ischemia-reperfusion stress triggers reprogramming of bile acid metabolism. This functions as an adaptive mechanism to mitigate inflammatory injury by regulating the S1PR2-GSDMD axis, thereby controlling the release of IL-1β from macrophages. Our results highlight the crucial role of bile acids in regulating hepatocyte-immune cell crosstalk, which demonstrates an immunomodulatory function in liver reperfusion injury that may guide therapeutic strategies targeting bile acids and their receptors.

Abstract Systemic immune monitoring is a crucial clinical tool for disease early diagnosis, prognosis and treatment planning by quantitative analysis of immune cells. However, conventional immune monitoring using flow cytometry faces huge challenges in large-scale sample testing, especially in mass health screenings, because of time-consuming, technical-sensitive and high-cost features. However, the lack of high-performance detection platforms hinders the development of high-throughput immune monitoring technology. To address this bottleneck, we constructed a generally applicable DNA framework signal amplification platform (DSAP) based on post-systematic evolution of ligands by exponential enrichment and DNA tetrahedral framework-structured probe design to achieve high-sensitive detection for diverse immune cells, including CD4+, CD8+ T-lymphocytes, and monocytes (down to 1/100 μl). Based on this advanced detection platform, we present a novel high-throughput immune-cell phenotyping system, DSAP, achieving 30-min one-step immune-cell phenotyping without cell washing and subset analysis and showing comparable accuracy with flow cytometry while significantly reducing detection time and cost. As a proof-of-concept, DSAP demonstrates excellent diagnostic accuracy in immunodeficiency staging for 107 HIV patients (AUC > 0.97) within 30 min, which can be applied in HIV infection monitoring and screening. Therefore, we initially introduced promising DSAP to achieve high-throughput immune monitoring and open robust routes for point-of-care device development.

Abstract Carbon fiber composites are emerging as a promising new biomaterial for chest wall reconstruction implants due to their mechanical properties and biocompatibility. This work evaluates the biomechanics of carbon fiber artificial ribs using finite element analysis and clinical implementation. Static simulations of normal breathing process show the maximum stress on the implant is only 2.83 MPa, far below the material ultimate strength of 60 MPa, indicating the excellent fit for maintaining respiratory function. Dynamic collision simulations demonstrate the artificial rib model could withstand a 4 kg rigid object impact at 2 m/s without fracture. Reconstructing the artificial rib with a human rib in the finite element analysis model increases the overall stress tolerance. The impact force required for fracture increases 48% compared to the artificial rib alone, suggesting improved strength from rib integration. Clinically, 10 of 13 patients receiving the artificial rib implants show no significant loss of pulmonary function based on spirometry tests. Based on our findings, the combined simulations and clinical results validate the strong mechanical performance and biocompatibility of the carbon fiber artificial ribs for chest wall reconstruction under static and dynamic loading while maintaining normal respiratory function.

While chaotic systems have found extensive applications across diverse scientific domains due to their inherent advantages, they often degrade into cyclic patterns when simulated on hardware with limited computational precision. This results in a pronounced decline in properties related to chaotic dynamics. To address this issue, we introduce the delayed exponent coupled chaotic map (DECCM). This model is designed to enhance the chaotic dynamics of the original map, especially at lower computational precisions. Additionally, DECCM can transform any proficient 1-dimensional seed map into an N-dimensional chaotic map. Extensive simulation and performance tests attest to the robust chaotic characteristics of our approach. Furthermore, DECCM holds distinct advantages over premier algorithms, particularly in period analysis experiments. We also introduce various seed maps into DECCM to present 2D and 3D examples, ensuring their generalization through relevant performance evaluations.

Abstract Precipitation forecasting plays an important role in disaster warning, agricultural production, and other fields. To solve this issue, some deep learning methods are proposed to forecast future radar echo images and convert them into rainfall distributions. Prevailing spatiotemporal sequence prediction methods are usually based on a ConvRNN structure that combines a Convolutional Neural Network and Recurrent Neural Network. However, these existing methods ignore the image change prediction, which causes the coherence of the predicted image has deteriorated. Moreover, these approaches mainly focus on complicating model structure to exploit more historical spatiotemporal representations. Nevertheless, they ignore introducing other valuable information to improve predictions. To tackle these two issues, we propose GCMT‐ConvRNN, a multi‐ask framework of ConvRNN. Except for precipitation nowcasting as the main task, it combines the motion field estimation and sub‐regression as auxiliary tasks. In this framework, the motion field estimation task can provide motion information, and the sub‐regression task offers future information. Besides, to reduce the negative transfer between the auxiliary tasks and the main task, we propose a new loss function based on the correlation of gradients in different tasks. The experiments show that all models applied in our framework achieve stable and effective improvement.

In studying the joint object detection and classification problem for facial expression recognition (FER) deploying the YOLOX framework, we introduce a novel feature extractor, called neighborhood coordinate attention Mamba (NCAMamba) to substitute for the original feature extractor in the Feature Pyramid Network (FPN). NCAMamba combines the background information reduction capabilities of Mamba, the local neighborhood relationship understanding of neighborhood attention, and the directional relationship understanding of coordinate attention. The resulting FER-YOLO-NCAMamba model, when applied to two unaligned FER benchmark datasets, RAF-DB and SFEW, obtains significantly improved mean average precision (mAP) scores when compared with those obtained by other state-of-the-art methods. Moreover, in ablation studies, it is found that the NCA module is relatively more important than the Visual State Space (VSS), a version of using Mamba for image processing, and in visualization studies using the grad-CAM method, it reveals that regions around the nose tip are critical to recognizing the expression; if it is too large, it may lead to erroneous prediction, while a small focused region would lead to correct recognition; this may explain why FER of unaligned faces is such a challenging problem.

The mixed signal of respiratory waveform and heartbeat waveform detected by the Laser-Doppler system is processed with an intermediate-frequency (IF) interference filtering method, an enhanced extraction method and a waveform-fixing method. To filter the IF interference signals and the noise scatters in the time-frequency graph, the filtering method based on coefficient of variation (CoV) values and the enhanced curve extraction method based on noise-scatter theory are utilized in vital signal analysis. To decouple the respiratory signal and the heartbeat signal in time domain, the waveform-fixing method based on second-order difference theory is utilized in signal decoupling. This method as an algorithm is applied in the computer simulation and laboratory environments. The results show that the above methods can extract the mixed waveforms and identify the respiratory rates and heart rates in real experimental data. The IF interference signal can be filtered adaptively, and the accuracy of the analyzed rates can be improved to about 95%.

This study explores the in vitro antifungal effects of nerol, a linear acyclic monoterpene alcohol of plant origin, on Fusarium oxysporum, Pestalotiopsis neglecta, and Valsa mali. To further investigate the antifungal mechanism of nerol against F. oxysporum, we examined changes in mycelial morphology and cell membrane integrity-related indices, as well as the activities of antioxidant and pathogenicity-related enzymes. The results demonstrated that nerol exhibited significant concentration-dependent inhibition of mycelial growth in all three fungi, with EC50 values of 0.46 μL/mL for F. oxysporum, 1.81 μL/mL for P. neglecta, and 1.26 μL/mL for V. mali, with the strongest antifungal activity observed against F. oxysporum. Scanning electron microscopy revealed that nerol severely disrupted the mycelial structure of F. oxysporum, causing deformation, swelling, and even rupture. Treatment with 0.04 μL/mL nerol led to significant leakage of soluble proteins and intracellular ions in F. oxysporum, and the Na+/K+-ATPase activity was reduced to 28.02% of the control, indicating enhanced membrane permeability. The elevated levels of hydrogen peroxide and malondialdehyde, along with propidium iodide staining of treated microconidia, further confirmed cell membrane disruption caused by nerol. Additionally, after 12 h of exposure to 0.04 μL/mL nerol, the activity of superoxide dismutase in F. oxysporum decreased to 55.81% of the control, and the activities of catalase and peroxidase were also significantly inhibited. Nerol markedly reduced the activities of pathogenicity-related enzymes, such as endo-1,4-β-D-glucanase, polygalacturonase, and pectin lyase, affecting fungal growth and virulence. In conclusion, nerol disrupts the cell membrane integrity and permeability of F. oxysporum, reduces its virulence, and ultimately inhibits fungal growth, highlighting its potential as an alternative to chemical fungicides for controlling F. oxysporum.

Horizontal well, dissolver, nitrogen, and steam (HDNS) combined flooding is mainly applied to shallow and thin heavy oil reservoirs to enhance oil recovery. Due to the lack of pore-scale mechanism studies, it is impossible to clarify the oil displacement mechanism of each slug in the process combination and the influence of their interaction on enhanced oil recovery (EOR). Therefore, in this study, HDNS combined flooding technology was simulated in a two-dimensional visualization microscopic model, and three viscosity reducer systems and multi-cycle combined flooding processes were considered. In combination with an emulsification and viscosity reduction experiment, two-dimensional microscopic multiphase seepage experiments were carried out to compare the dynamic seepage law and microscopic occurrence state of multiphase fluids in different systems. The results showed that the ability of three viscosity reducers to improve viscosity reduction efficiency in HDNS combined flooding was A > B > C, and their contributions to the recovery reached 65%, 41%, and 30%, respectively. In the system where a high viscosity reduction efficiency was shown by the viscosity reducer, the enhancements of both sweeping efficiency and displacement efficiency were primarily influenced by the viscosity reducer flooding. Steam flooding collaborated to improve displacement efficiency. The thermal insulation characteristics of N2 flooding may not provide a gain effect. In the system where a low viscosity reduction efficiency was shown by the viscosity reducer, the steam flooding was more important, contributing to 57% of the sweeping efficiency. Nitrogen was helpful for expanding the sweep area of the subsequent steam and viscosity reducer, and the gain effect of the thermal insulation steam chamber significantly improved the displacement efficiency of the subsequent steam flooding by 25%. The interaction of each slug in HDNS combined flooding resulted in the additive effect of increasing production. In actual production, it is necessary to optimize the process and screen the viscosity reducer according to the actual conditions of the reservoir and the characteristics of different viscosity reducers.

Background Falls pose a serious health risk for the elderly, particular for those who are living alone. The utilization of WiFi-based fall detection, employing Channel State Information (CSI), emerges as a promising solution due to its non-intrusive nature and privacy preservation. Despite these advantages, the challenge lies in optimizing cross-individual performance for CSI-based methods. Objective This study aimed to develop a resilient real-time fall detection system across individuals utilizing CSI, named TCS-Fall. This method was designed to offer continuous monitoring of activities over an extended timeframe, ensuring accurate and prompt detection of falls. Methods Extensive CSI data on 1800 falls and 2400 daily activities was collected from 20 volunteers. The grouped coefficient of variation of CSI amplitudes were utilized as input features. These features capture signal fluctuations and are input to a convolutional neural network classifier. Cross-individual performance was extensively evaluated using various train/test participant splits. Additionally, a user-friendly CSI data collection and detection tool was developed using PyQT. To achieve real-time performance, data parsing and pre-processing computations were optimized using Numba's just-in-time compilation. Results The proposed TCS-Fall method achieved excellent performance in cross-individual fall detection. On the test set, AUC reached 0.999, no error warning ratio score reached 0. 955 and correct warning ratio score reached of 0.975 when trained with data from only two volunteers. Performance can be further improved to 1.00 when 10 volunteers were included in training data. The optimized data parsing/pre-processing achieved over 20× speedup compared to previous method. The PyQT tool parsed and detected the fall within 100 ms. Conclusions TCS-Fall method enables excellent real-time cross-individual fall detection utilizing WiFi CSI, promising swift alerts and timely assistance to elderly. Additionally, the optimized data processing led to a significant speedup. These results highlight the potential of our approach in enhancing real-time fall detection systems.

Concentration plays an essential role in generating hydroxyl radicals in irradiated nanoenhancer suspensions. In this paper, we used coumarin-3-carboxylic acid as a hydroxyl radical-specific probe to investigate the hydroxyl radical production of different concentration nanodiamonds (NDs) and CeO2 NPs in phosphate-buffered saline under x-ray irradiation. NDs significantly enhanced hydroxyl radical production, and the maximum enhancement of hydroxyl radical production was observed at a concentration of 10 µg/ml, with an enhanced factor of 1.398 ± 0.262. CeO2 NPs can increase and scavenge hydroxyl radicals at different concentration ranges, with the lowest and highest enhanced factors of 0.623 ± 0.069 and 1.738 ± 0.264, respectively. We tested the hydrodynamic diameter at various concentrations to explore the concentration effect further. We found that with increasing concentration, there might be factors, such as hydroxyl radical recombination and nanoparticle agglomeration, that lead to changes in the enhancement factor. Based on the data from previous and present studies, the experimental results indicate that the concentration factor is essential for hydroxyl radical generation in nanoenhancer suspensions under ionizing radiation. We also provide possible mechanisms for enhancing hydroxyl radical production by nanoenhancers in water under ionizing radiation and the decrease in enhancement factor at high concentrations of nanoenhancers.

For a long time, human activities have been prohibited in ecologically protected areas in the Ebinur Lake Wetland National Nature Reserve (ELWNNR). The implementation of total closure is one of the main methods for ecological protection. For arid zones, there is a lack of in-depth research on whether this measure contributes to ecological restoration in the reserve. The Normalized Difference Vegetation Index (NDVI) is considered to be the best indicator for ecological monitoring and has a key role to play in assessing the ecological impacts of total closure. In this study, we used Sentinel-2, Landsat-8, and Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data to select optimal data and utilized Sen slope estimation, Mann-Kendall statistical tests, and the geographical detector model to quantitatively analyze the normalized difference vegetation index (NDVI) dynamics and its driving factors. Results were as follows: (1) The vegetation distribution of the Ebinur Lake Wetland National Nature Reserve (ELWNNR) had obvious spatial heterogeneity, showing low distribution in the middle and high distribution in the surroundings. The correlation coefficients of Landsat-8 and MODIS, Sentinel-2 and MODIS, and Sentinel-2 and Landsat-8 were 0.952, 0.842, and 0.861, respectively. The NDVI calculated from MODIS remote sensing data was higher than the value calculated by Landsat-8 and Sentinel-2 remote sensing images, and Landsat-8 remote sensing data were the most suitable data. (2) NDVI indicated more degraded areas on the whole, but the ecological recovery was obvious in the localized areas where anthropogenic closure was implemented. The ecological environment change was the result of the joint action of man and nature. Man-made intervention will change the local ecological environment, but the overall ecological environment change was still dominated by natural environmental factors. (3) Factors affecting the distribution of NDVI in descending order were as follows: precipitation > evapotranspiration > land use type > elevation > vegetation type > soil type > soil erosion > slope > temperature > slope direction. Precipitation was the main driver of vegetation change in ELWNNR. The synergistic effect of the factors showed two-factor enhancement and nonlinear enhancement, and the combined effect of the driving factors would increase the influence on NDVI.

Summary: Familial Mediterranean fever (FMF) is a periodic fever syndrome caused by variation in MEFV. FMF is known for IL-1β dysregulation, but the innate immune landscape of this disease has not been comprehensively described. Therefore, we studied circulating inflammatory proteins, and the function of monocytes and (albeit less extensively) neutrophils in treated FMF patients in remission. We found that monocyte IL-1β and IL-6 production was enhanced upon stimulation, in concordance with alterations in the plasma inflammatory proteome. We did not observe changes in neutrophil functional assays. Subtle differences in chromatin accessibility and transcriptomics in our small patient cohort further argued for monocyte dysregulation. Together, these observations suggest that the MEFV-mutation-mediated primary immune dysregulation in monocytes leads to chronic inflammation that is subsequently associated with counterregulatory epigenetic/transcriptional changes reminiscent of tolerance. These data increase our understanding of the innate immune changes in FMF, aiding future management of chronic inflammation in these patients.

Immune cell therapy as a revolutionary treatment modality, significantly transformed cancer care. It is a specialized form of immunotherapy that utilizes living immune cells as therapeutic reagents for the treatment of cancer. Unlike traditional drugs, cell therapies are considered “living drugs,” and these products are currently customized and require advanced manufacturing techniques. Although chimeric antigen receptor (CAR)-T cell therapies have received tremendous attention in the industry regarding the treatment of hematologic malignancies, their effectiveness in treating solid tumors is often restricted, leading to the emergence of alternative immune cell therapies. Tumor-infiltrating lymphocytes (TIL) cell therapy, cytokine-induced killer (CIK) cell therapy, dendritic cell (DC) vaccines, and DC/CIK cell therapy are designed to use the body’s natural defense mechanisms to target and eliminate cancer cells, and usually have fewer side effects or risks. On the other hand, cell therapies, such as chimeric antigen receptor-T (CAR-T) cell, T cell receptor (TCR)-T, chimeric antigen receptor-natural killer (CAR-NK), or CAR-macrophages (CAR-M) typically utilize either autologous stem cells, allogeneic or xenogeneic cells, or genetically modified cells, which require higher levels of manipulation and are considered high risk. These high-risk cell therapies typically hold special characteristics in tumor targeting and signal transduction, triggering new anti-tumor immune responses. Recently, significant advances have been achieved in both basic and clinical researches on anti-tumor mechanisms, cell therapy product designs, and technological innovations. With swift technological integration and a high innovation landscape, key future development directions have emerged. To meet the demands of cell therapy technological advancements in treating cancer, we comprehensively and systematically investigate the technological innovation and clinical progress of immune cell therapies in this study. Based on the therapeutic mechanisms and methodological features of immune cell therapies, we analyzed the main technical advantages and clinical transformation risks associated with these therapies. We also analyzed and forecasted the application prospects, providing references for relevant enterprises with the necessary information to make informed decisions regarding their R&D direction selection.

In recent years, PbZrO3 (PZO) films have become favorable electric storage materials due to the unique electric field-induced phase transition behavior, but the severe hysteresis effect leads to low energy storage density and efficiency. In this work, inserting Al2O3 (AO) insulation nanolayers is proposed to tune the polarization behavior of flexible PZO films, anticipating optimization of energy storage performance. The results show that the thickness of the AO nanolayers has a deep influence on the polarization behavior of the PZO films, and PZO/AO/PZO (PAP) sandwiched films with 8 nm AO interlayer deliver relaxor ferroelectric-like polarization instead of antiferroelectric counterpart. To further utilize the AO nanolayers as top/bottom layers, the linear-like polarization and the highest breakdown strength are achieved in the AO/PZO/AO/PZO/AO (APAPA8) multilayer films, leading to both high discharged energy storage density of 35.2 J/cm3 and efficiency of 92.9%, as well as excellent fatigue and bending endurance, good temperatures, and frequency stability. The tunable polarization induced by growing the AO nanolayers makes antiferroelectric PZO films have great potential to be used as energy storage dielectrics.

Due to the complex motion state of biomass raw materials in the granulation process of involute plunger biomass ring mold granulator, it is difficult to analyze by use of a linear mechanical model. Accordingly, a granulation simulation model of molded parts was established by coupling discrete element (DEM) and finite element (FEM) analyses. The stress and strain results of ring die and involute plunger pressure roller were analyzed. On this basis, it can be predicted that for wood pellet materials, when the pressure angle of the involute plunger involute profile is 20°, the ring mold forming hole length-diameter ratio is 4.5, the forming hole diameter is 8 mm, and the hole cone angle is 90°, the compression force on the wood pellet will be maximized at 7.89 KN, the maximum equivalent force at the ring mold forming hole and the root of the involute plunger pressure roller will be 64.2 and 84.5 MPa, respectively, and the maximum deformation will be 0.000327 and 0.000424 mm, which is within permissible limits. The involute plunger roller is more susceptible to fatigue damage compared with the ring die. By contrast, the ring part is more prone to fatigue damage in the case of a ring die.

Abstract Kesterite Cu2ZnSn(S, Se)4 is considered one of the most competitive photovoltaic materials due to its earth-abundant and nontoxic constituent elements, environmental friendliness, and high stability. However, the preparation of high-quality Kesterite absorbers for photovoltaics is still challenging for the uncontrollability and complexity of selenization reactions between metal element precursors and selenium. In this study, we propose a solid-liquid/solid-gas (solid precursor and liquid/vapor Se) synergistic reaction strategy to precisely control the selenization process. By pre-depositing excess liquid selenium, we provide the high chemical potential of selenium to facilitate the direct and rapid formation of the Kesterite phase. The further optimization of selenium condensation and subsequent volatilization enables the efficient removal of organic compounds and thus improves charge transport in the absorber film. As a result, we achieve high-performance Kesterite solar cells with total-area efficiency of 13.6% (certified at 13.44%) and 1.09 cm2-area efficiency of 12.0% (certified at 12.1%).

Abstract The evolution of architectural forms is a significant field of study in modern hybrids of Chinese and foreign architecture. It involves exploring the integration of foreign buildings and their constituent elements into traditional Chinese local culture. The Composite capital is a key component in Western architecture. Research indicates that from the 1920s to 1930s, Composite capital designs in foreign architectural structures within the Jiangsu region exhibited period-specific evolutionary characteristics and variations among different cities. Therefore, the localisation of Composite capitals in Jiangsu is a gradual process. This paper proposes a research methodology combining formal analysis and social analysis to investigate the localisation of Composite capitals in Jiangsu during the modern period. The study yields two main conclusions: (1) Within the same social environment, there are common patterns in the localisation of Composite capital designs among different historical periods, reflecting shared developmental trends influenced by local traditional culture. (2) Different cities in the Jiangsu region, characterised by distinct social environments, exhibit unique patterns in the localisation of Composite capital designs, reflecting regional diversity and providing more possibilities for localisation. This paper investigates the localisation of Composite capital designs in modern Jiangsu and explores the factors that influence the form and value of capital designs, providing a systematic reference for the study of regional architectural localisation in the modern period in China.

Inner Mongolia, a major region in China for growing sugar beet, faces challenges caused by unscientific water and fertilizer management. This mismanagement restricts the improvement of sugar beet yield and quality and exacerbates water waste and environmental pollution. This study aims to evaluate the effects of reduced water and fertilizer on the growth and physiological metabolism of sugar beet taproot. Field experiments were conducted in Ulanqab, Inner Mongolia, in 2022 and 2023, using a split-plot design with three levels each of fertilization and irrigation. The study analyzed the effects of reduced water and fertilizer treatments on fresh taproot weight, respiration rate, energy metabolism, respiratory enzyme activity, and gene expression in sugar beet taproot. It was found that a 10% reduction in fertilizer significantly increased the beet taproot fresh weight. Further research revealed that during the rapid leaf growth phase and the taproot and sugar growth period, a 10% reduction in fertilizer upregulated HK and IDH gene expression and downregulated G6PDH gene expression in the beet taproot. This increased HK and IDH activities, decreased G6PDH activity, enhanced the activity of the EMP-TCA pathway, and inhibited the PPP. Taproot weight was positively correlated with the respiration rate, ATP content, EC, and ATPase, HK, and IDH activities, thereby increasing the taproot growth rate and taproot fresh weight, with an average increase of 4.0% over two years. These findings introduce a novel method for optimizing fertilizer use, particularly beneficial in water-scarce regions. Implementing this strategy could help farmers in western Inner Mongolia and similar areas improve crop yield and sustainability. This study offers new insights into resource-efficient agricultural practices, highlighting the importance of customized fertilization strategies tailored to local environmental conditions.

Due to the influence of geometric factors, the temperature and humidity profile of lidar’s near-field signal was warped when sensing the air environment. In order to perform geometric factor correction on near-field signals, this article proposes different correction solutions for the Mie and Raman scattering channels. Here, the Mie scattering channel used the Raman method to invert the aerosol backscatter coefficient and correct the extinction coefficient in the transition zone. The geometric factor was the ratio of the measured signal to the forward-computed vibration Raman scattering signal. The aerosol optical characteristics were reversed using the corrected echo signal, and the US standard atmospheric model was added to the missing signal in the blind zone, reflecting the aerosol evolution process. The stability and dependability of the proposed algorithm were validated by the consistency between the visibility provided by the Environmental Protection Agency and the visibility acquired via lidar retrieval data. The near-field humidity data were supplemented by the interpolation method in the Raman scattering channel to reflect the water vapor transfer process in the temporal dimension. The measured transmittance curve of the filter, the theoretical normalized spectrum, and the sounding data were used to compute the delay geometric factor. The temperature was retrieved and the near-field signal distortion issue was resolved by applying the corrected quotient of the temperature channel. The proposed algorithm exhibited robustness and universality, enhancing the system’s detection accuracy compared to the temperature and humidity data constantly recorded by the probes in the meteorological gradient tower, which have a high correlation with the lidar observation data. The comparison between lidar data and instrument monitoring data showed that the proposed algorithm could effectively correct distorted echo signals in the transition zone, which was of great value for promoting the application of lidar in the meteorological monitoring of the urban canopy layer.

Reducing resistance to surface friction is challenging in the field of engineering. Natural biological systems have evolved unique functional surfaces or special physiological functions to adapt to their complex environments over centuries. Among these biological wonders, fish, one of the oldest in the vertebrate group, have garnered attention due to their exceptional fluid dynamics capabilities. Fish skin has inspired innovation in reducing surface friction due to its unique structures and material properties. Herein, drawing inspiration from the unique properties of fish scales, a periodic array of fish scales was fabricated by laser ablation on a polished aluminum template. The morphology of the biomimetic fish scale surface was characterized using scanning electron microscopy and a white-light interfering profilometer. Drag reduction performance was measured in a closed circulating water tunnel. The maximum drag reduction was 10.26% at a Reynolds number of 39,532, and the drag reduction performance gradually decreased with an increase in the distance between fish scales. The mechanism of the biomimetic drag reduction surface was analyzed using computational fluid dynamics. Streamwise vortices were generated at the valley of the biomimetic fish scale, replacing sliding friction with rolling friction. These results are expected to provide a foundation for in-depth analysis of the hydrodynamic performance of fish and serve as new inspiration for drag reduction and antifouling.

This paper investigated the inhibitory effect of Sesamol (Ses) on Pestalotiopsis neglecta. The potential inhibitory mechanisms were explored by observing changes in cell morphology, measuring alterations in cell membrane-related indices, as well as energy metabolism-related indices and changes in enzyme activities related to virulence. The results show that Ses completely inhibited the growth of P. neglecta at 600 μg/mL (minimum inhibitory concentration and minimum fungicidal concentration), with an EC50 of 142 ± 13.22 μg/mL. As observed with scanning electron microscopy (SEM) and transmission electron microscopy (TEM), Ses treatment resulted in the breakage and crumpling of P. neglecta cell membrane and organelle lysis. Ergosterol content and the total lipid in P. neglecta treated with 300 μg/mL Ses was 91.52% and 54% of that in the control groups, respectively. In addition, spores were stained, increased leakage of intracellular constituents at 260 nm, and decreased extracellular pH. This suggests damage to the cell membrane integrity and permeability. Furthermore, Ses decreased the ATP levels and key enzymes in the tricarboxylic acid (TCA) cycle, indicating interference with the fungal energy metabolism. Moreover, the activities of polygalacturonase (PG) and endoglucanase (EG) of P. neglecta treated with 300 μg/mL of Ses were only 28.20% and 29.13% of that in the control groups, respectively, indicating that Ses can reduce the virulence of P. neglecta. In conclusion, our results show that Ses should be considered as a potential plant-derived fungicide due to its ability to disrupt the morphology of P. neglecta, damage cell membrane integrity and permeability in P. neglecta, interfere with energy metabolism, and reduce its virulence, ultimately affecting the fungal growth.

With the swift advancement of wearable electronics and artificial intelligence, the integration of electronic devices with the human body has advanced significantly, leading to enhanced real-time health monitoring and remote disease diagnosis. Despite progress in developing stretchable materials with skin-like mechanical properties, there remains a need for materials that also exhibit high optical transparency. Supercapacitors, as promising energy storage devices, offer advantages such as portability, long cycle life, and rapid charge/discharge rates, but achieving high capacity, stretchability, and transparency simultaneously remains challenging. This study combines the stretchable, transparent polymer PEDOT:PSS with MnO2 nanoparticles to develop high-performance, stretchable, and transparent supercapacitors. PEDOT:PSS films were deposited on a PDMS substrate using a spin-coating method, followed by electrochemical deposition of MnO2 nanoparticles. This method ensured that the nanosized MnO2 particles were uniformly distributed, maintaining the transparency and stretchability of PEDOT:PSS. The resulting PEDOT:PSS/MnO2 nanoparticle electrodes were gathered into a symmetric device using a LiCl/PVA gel electrolyte, achieving an areal capacitance of 1.14 mF cm−2 at 71.2% transparency and maintaining 89.92% capacitance after 5000 cycles of 20% strain. This work presents a scalable and economical technique to manufacturing supercapacitors that combine high capacity, transparency, and mechanical stretchability, suggesting potential applications in wearable electronics.

Differential absorption lidar is an advanced tool for investigating tropospheric ozone transport and development. High-quality differential absorption lidar data are the basis for studying the temporal and spatial evolution of ozone pollution. We assessed the quality of the ozone data generated via differential absorption lidar. By correcting the ozone lidar profile in real-time with an atmospheric correction term and comparing the lidar data to ozone data collected using an unmanned aerial vehicle (UAV), we quantified the statistical error of the ozone lidar data in the vertical direction and determined that the data from the two instruments were generally in agreement. To verify the reliability of the ozone lidar system and the atmospheric correction algorithm, we conducted a long-term comparison experiment using data from the Canton Tower. Over the two months, the UAV and lidar data were consistent with one another, which confirmed the viability of the ozone lidar optomechanical structure and the atmospheric correction algorithm, both in real-time and over a given time duration. In addition, we also quantified the relationship between statistical error and signal-to-noise ratio. When the SNR is less than 10, the corresponding statistical error is about 40%. The statistical error was less than 15% when the signal-to-noise ratio was greater than 20, and the statistical error was mostly less than 8% when the signal-to-noise ratio was greater than 40. In general, the statistical error of the differential absorption lidar data was inversely proportional to the signal-to-noise ratio of each echo signal.