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Abstract Synthetic micro/nanomotors have been extensively exploited over the past decade to achieve active transportation. This interest is a result of their broad range of potential applications, from environmental remediation to nanomedicine. Nevertheless, it still remains a challenge to build a fast-moving biodegradable polymeric nanomotor. Here we present a light-propelled nanomotor by introducing gold nanoparticles (Au NP) onto biodegradable bowl-shaped polymersomes (stomatocytes) via electrostatic and hydrogen bond interactions. These biodegradable nanomotors show controllable motion and remarkable velocities of up to 125 μm s−1. This unique behavior is explained via a thorough three-dimensional characterization of the nanomotor, particularly the size and the spatial distribution of Au NP, with cryogenic transmission electron microscopy (cryo-TEM) and cryo-electron tomography (cryo-ET). Our in-depth quantitative 3D analysis reveals that the motile features of these nanomotors are caused by the nonuniform distribution of Au NPs on the outer surface of the stomatocyte along the z-axial direction. Their excellent motile features are exploited for active cargo delivery into living cells. This study provides a new approach to develop robust, biodegradable soft nanomotors with application potential in biomedicine.

Objective Defining the distribution of sweet spots in tight reservoirs is the focus of tight oil and gas exploration. Methods Using core observation, thin section identification, X-ray diffraction, homogenization temperature measurements of inclusions, and conventional physical property analysis, the sedimentary characteristics, reservoir characteristics, and diagenesis of Upper Palaeozoic tight sandstones in the Binchang area, southern Ordos Basin were studied in detail.The main controlling factors of reservoir formation were identified and the development model of high-quality reservoirs was established. Results The results show that sedimentary facies are the basis of reservoir formation, and the core beach microfacies of the braided river delta plain have coarse grain sizes, small pore-medium-fine throat pore structures, and relatively good reservoir physical properties. The underwater distributary channel and estuary bar in front of the meandering river delta have fine grain sizes and pore throat structures of micropore-microat throat pore structure, and the reservoir's physical properties are relatively poor. Diagenesis plays an important role in controlling the development and distribution of high-quality reservoirs. Intermittent volcanic tuff is transformed into kaolinite in acidic strata and altered into chlorite sheaths in alkaline strata, which inhibits quartz overgrowth and calcite cementation and protects the reservoir space. The secondary enlargement of quartz is mainly caused by the leaching of SiO2 from mudstone to sandstone.The main reasons for the cementation of calcite roof and floor are the filling of feldspar and the dissolution of cuttings in the middle and late stages of calcite. The microfractures formed by late tectonic transformation have no calcite cementation, which improves the physical properties of the reservoir and plays an adjusting role in the gas reservoir. There are two solution pore development zones near burial depths of 3 750 m and 3 900 m in the Binchang area. The optimal reservoir is the medium-coarse-grained sandstone rich in chlorite mantle formed by the transformation of volcanic tuffaceous matter in the dissolution pore development zone. The sub-optimal reservoir is mainly distributed in the middle and lower parts of the sand body with a greater single-body thickness, cyclicity and no mudstone interval in the dissolution pore development zone.This zone is composed mainly of medium-coarse-grained sandstone lacking chlorite film, calcite cementation and secondary enlargement of quartz are the lowest. Conclusion These research results further increase the understanding of the genesis of the development of high-quality tight sandstone reservoirs in the Upper Palaeozoic, providing important guidance for natural gas exploration and development in this area.

With the electromagnetic environment becoming increasingly complex, it is crucial to address the risk posed by electromagnetic pulse, which critically impairs the performance and reliability of electronic systems based on complementary metal oxide semiconductor (CMOS) image sensors. In this context, research on the failure types of CMOS image sensors in a high-power electromagnetic environment, caused by strong electromagnetic pulses and the rapid evaluation method of interference immunity, has garnered significant interest. This paper conducts electromagnetic pulse simulation experiments on CMOS image sensors to first study their failure types, such as image abnormalities and functional interruption, and then identify the corresponding failure criteria. Furthermore, this study builds on the small sample test evaluation method to investigate the interference threshold of functional interruptions in CMOS image sensors by calculating the failure probability at different field strengths. The obtained data were combined with the Weibull distribution function for fitting, the results of which found the interference threshold to be at 40.4 kV/m. The findings of this study provide a basis for evaluating the survivability of CMOS image sensors and their associated reinforcement technology in high-power electromagnetic environments.

Abstract While strategies such as chemotherapy and immunotherapy have become the first-line standard therapies for patients with advanced or metastatic cancer, acquired resistance is still inevitable in most cases. The introduction of antibody‒drug conjugates (ADCs) provides a novel alternative. ADCs are a new class of anticancer drugs comprising the coupling of antitumor mAbs with cytotoxic drugs. Compared with chemotherapeutic drugs, ADCs have the advantages of good tolerance, accurate target recognition, and small effects on noncancerous cells. ADCs occupy an increasingly important position in the therapeutic field. Currently, there are 13 Food and Drug Administration (FDA)‒approved ADCs and more than 100 ADC drugs at different stages of clinical trials. This review briefly describes the efficacy and safety of FDA-approved ADCs, and discusses the related problems and challenges to provide a reference for clinical work.

Abstract The optimal performance of drug delivery formulations, including polymeric nanoparticles, relies on particle distribution throughout the body and the interactions with biological barriers, particularly mucosal layers, which often limit their potential. A systematic and comprehensive study is presented through a multidisciplinary approach combining conventional and novel techniques for in vitro studies to understand the key molecular interactions between polymeric micelles and mucin. The results shows that polymeric micelles are integrates within the mucin layer, mirroring its viscoelastic properties, evidenced as a dissipation difference of 0.1 ± 0.44, measured by quartz crystal microbalance with dissipation. Surface‐enhanced Raman scattering reveals predominant hydrogen bonding within the mucin's hydrophilic core, while the isothermal titration calorimetry method confirms multiple non‐specific binding sites on the protein backbone. By performing the periodic acid‐Schiff stain assay, a binding amount of 0.20 mg of mucin per milligram of nanoparticles is quantified. Furthermore, motility studies show the surface binding of mucin on the polymeric nanoparticles influencing their Brownian motion. This study sheds light toward the improvement for a better drug delivery formulation and fabrication of optimal nanoparticle colloidal systems, which can advance translational drug delivery technologies into clinical application while enriching the field of surface and colloidal chemistry.

Abstract Background Approximately 50% of breast mucinous carcinomas (MCs) are oval and have the possibility of being misdiagnosed as fibroadenomas (FAs). We aimed to identify the key features that can help differentiate breast MC with an oval shape from FA on ultrasonography (US). Methods Seventy-six MCs from 71 consecutive patients and 50 FAs with an oval shape from 50 consecutive patients were included in our study. All lesions pathologically diagnosed. According to the Breast Imaging Reporting and Data System (BI-RADS), first, the ultrasonographic features of the MCs and FAs were recorded and a final category was assessed. Then, the differences in ultrasonographic characteristics between category 4 A (low-risk group) and category 4B-5 (medium-high- risk group) MCs were identified. Finally, other ultrasonographic features of MC and FA both with an oval shape were compared to determine the key factors for differential diagnosis. The Mann-Whitney test, χ 2 test or Fisher’s exact test was used to compare data between groups. Results MCs with an oval shape (81.2%) and a circumscribed margin (25%) on US were more commonly assessed in the low-risk group (BI-RADS 4 A) than in the medium-high-risk group (BI-RADS 4B-5) (20%, p

In this paper, we investigated an experimental analysis of the degradation caused by low dose rate irradiation in GaN-based high-electron-mobility transistors (HEMTs) with a p-type gate. Combined with experimental frequency-dependent conductance ( $\text{G}_{\mathrm {p}}/\omega)$ analyses and TCAD simulations, it has been demonstrated that the negative shifts in both $\text{I}_{\mathrm {d}}$ - $\text{V}_{\mathrm {gs}}$ and $\text{V}_{\mathrm {th}}$ are primarily due to the formation of donor-like traps near the p-GaN/AlGaN interface, which is a result of the dehydrogenation of pre-existing defects during low dose rate irradiation. Additionally, the results of the TCAD simulations, indicate that the trap-assisted tunneling (TAT) process, which involves the recombination of trap-assisted holes with electrons in the p-GaN layer, may dominate the physical mechanisms responsible for the increase in gate leakage current ( $\text{I}_{\mathrm {g}}$ - $\text{V}_{\mathrm {gs}}$ ). These results may provide a basis for understanding the role of radiation-induced traps on electrical parameters degradations for p-GaN gate HEMTs.

Abstract Precise and timely recognition of hazardous chemical substances is of great significance for safeguarding human health, ecological environment, public security, etc., especially crucial for adopting appropriate disposition measures. Up to now, there remains a practical challenge to sensitively detect and differentiate organic amines with similar chemical structures with intuitive analysis outcomes. Here, a unique optical probe with two electrophilic recognition sites for rapid and ultra‐sensitive ratiometric fluorescence detection of ethylenediamine (EDA) is presented, while producing distinct fluorescence signals to its structural analog. The probe exhibits ppb/nmol level sensitivity to liquidous and gaseous EDA, specific recognition toward EDA without disturbance to up to 28 potential interferents, as well as rapid fluorescence response within 0.2 s. By further combining the portable sensing chip with the convolutional algorithm endowed with image processing, this work cracked the problem of precisely discriminating the target and non‐targets at extremely low concentrations.

The displacement damage effect of 10 MeV proton radiation on a high-speed InGaAs PIN photodiode has been experimentally investigated to evaluate the stability of the device in a space radiation environment. The results show that the dark current and low-frequency noise of the device increase significantly after irradiation, while the capacitance of the device decreases slightly after irradiation, where the spectral response parameters are less affected by irradiation. The increase in dark current is essentially linear with the displacement damage dose. Finally, the effect of proton irradiation on the optical communication system is simulated and the results show that the bit error rate of the system increases with the increase in irradiation fluence, which seriously affects the sensitivity of the optical communication system.

Backdoor attacks have severely threatened deep neural network (DNN) models in the past several years. In backdoor attacks, the attackers try to plant hidden backdoors into DNN models, either in the training or inference stage, to mislead the output of the model when the input contains some specified triggers without affecting the prediction of normal inputs not containing the triggers. As a rapidly developing topic, numerous works on designing various backdoor attacks and developing techniques to defend against such attacks have been proposed in recent years. However, a comprehensive and holistic overview of backdoor attacks and countermeasures is still missing. In this paper, we provide a systematic overview of the design of backdoor attacks and the defense strategies to defend against backdoor attacks, covering the latest published works. We review representative backdoor attacks and defense strategies in both the computer vision domain and other domains, discuss their pros and cons, and make comparisons among them. We outline key challenges to be addressed and potential research directions in the future.

There exist uncertainties in raw material components and distribution parameters in blending process. Considering the dynamic uncertainty of distribution parameters and the dynamic change of raw material inventory, a general closed-loop dynamic blending optimization (CDBO) is proposed. The proposed method consists of both data-driven system and model-based system. In the data-driven system, the feedback optimization problem is reconstructed into a linear regression problem, and the variational Bayesian is proposed to obtain the mean and variance of the distribution. Then, according to the incoming raw materials, the mean value of each distribution parameter is adjusted by expert rules. Last, in the model-based system, blending ratio is obtained by chance-constrained programming. To verify the effectiveness of CDBO, a detailed derivation process of variable Bayesian, expert rule and chance-constrained programming are established for zinc smelting process. Numerical studies and an industrial application for zinc smelting process are presented to demonstrate the advantages of the proposed method. Compared with the manual blending, the volatility index of chemical tests data is greatly reduced and the compliance rates of zinc and lead is increased by 6.7% and 3.3%, respectively.

Abstract In this work, extremely thin silicon-on-insulator field effective transistors (ETSOI FETs) are fabricated with an ultra-thin 3 nm ferroelectric (FE) hafnium zirconium oxides (Hf0.5Zr0.5O2) layer. Furthermore, the subthreshold characteristics of the devices with double gate modulation are investigated extensively. Contributing to the advantages of the back-gate voltage coupling effects, the minimum subthreshold swing (SS) value of a 40 nm ETSOI device could be adjusted from the initial 80.8–50 mV/dec, which shows ultra-steep SS characteristics. To illustrate this electrical character, a simple analytical model based on the transient Miller model is demonstrated. This work shows the feasibility of FE ETSOI FET for ultra-low-power applications with dynamic threshold adjustment.

The advancement of science and technology and the growth of industry have led to an escalating discharge of domestic sewage and industrial wastewater containing dyes. This surge in volume not only incurs higher costs but also exacerbates environmental burdens. However, the benefits of green and reusable catalytic reduction materials within dye processes are still uncertain. Herein, this study utilized the eco-friendly deep eutectic solvent method (DESM) and the chlorite-alkali method (CAM) to prepare a cellulose-composed wood aerogel derived from natural wood for 4-nitrophenol (4-NP) reduction. The life cycle assessment of wood aerogel preparative process showed that the wood aerogel prepared by the one-step DESM method had fewer environmental impacts. The CAM method was used innovatively to make uniform the chemical functional groups of different wood species and various wood maturities. Subsequently, palladium nanoparticles (Pd NPs) were anchored in the skeleton structure of the wood aerogel with the native chemical groups used as a reducing agent to replace external reducing agents, which reduced secondary pollution and prevented the agglomeration of nanoparticles. Results showed that the catalytic reduction efficiency of 4-NP can reach 99.8%, which shows promises for applications in wastewater treatment containing dyes. Moreover, investigation of the advantages of preparation methods of wood aerogel has important implications for helping researchers and producers choose suitable preparation strategies according to demand.

Controlled-release nitrogen fertilizer (CRNF) has been proven to surpass common urea by mitigating nutrient losses, enhancing soil quality, and improving crop productivity. However, the long-term effects of CRNF on soil biological properties are not well understood. Here, a 12-year field experiment was conducted with five treatments: no N fertilizer (PK); the split application of urea at the farmer’s practice rate (FP) and the optimal rate (OPT); the one-time application of CRNF at the same rate as the OPT (CRNF); and a 20% reduced rate of the OPT (0.8CRNF). Soil samples were collected during the maize tasseling and filling stages; high-throughput sequencing and the PICRUSt2 method were employed to determine the bacterial community and its functional potential. The results showed that CRNF significantly increased alkaline hydrolysis N by 14.10% and 9.45% compared to OPT during the tasseling and filling stages, respectively. This increase in soil available N resulted in a significant increase in bacterial diversity of 2.09% and 2.35% compared with the FP and OPT, respectively. The bacterial community in the FP and OPT changed markedly between the tasseling and filling stages, with many bacterial species at the ASV and genus levels showing variations in relative abundance. In contrast, CRNF and 0.8CRNF exhibited stable N-cycling functions, as indicated by the lower variations in nitrate reductase and predicted N-cycling functional genes between the tasseling and filling stages. The obtained results suggest that CRNF application can enhance soil N supply, promote the formation of stable bacterial communities, and maintain stable N-cycling functions.

Summary: Alternative splicing (AS) is a critical mechanism for the aberrant biogenesis of long non-coding RNA (lncRNA). Although the role of Wnt signaling in AS has been implicated, it remains unclear how it mediates lncRNA splicing during cancer progression. Herein, we identify that Wnt3a induces a splicing switch of lncRNA-DGCR5 to generate a short variant (DGCR5-S) that correlates with poor prognosis in esophageal squamous cell carcinoma (ESCC). Upon Wnt3a stimulation, active nuclear β-catenin acts as a co-factor of FUS to facilitate the spliceosome assembly and the generation of DGCR5-S. DGCR5-S inhibits TTP’s anti-inflammatory activity by protecting it from PP2A-mediated dephosphorylation, thus fostering tumor-promoting inflammation. Importantly, synthetic splice-switching oligonucleotides (SSOs) disrupt the splicing switch of DGCR5 and potently suppress ESCC tumor growth. These findings uncover the mechanism for Wnt signaling in lncRNA splicing and suggest that the DGCR5 splicing switch may be a targetable vulnerability in ESCC.

During the use of polyethylene (PE) cable in power systems, electrical tree damages can inevitably occur inside the insulation materials, causing partial discharges and threatening the safety of the power supply. It is difficult to detect the micro damages inside the materials by existing technology, and replacing cables creates a lot of solid waste. The microcapsule self-healing technology derived from bionics can automatically detect and heal micro damages inside the material in time, avoiding accidents and saving resources. In this paper, the self-healing abilities and mechanism of the PE/microcapsule composite materials to the electrical tree damage are studied by means of experiments and simulation. PE/microcapsule composite materials are prepared, and the composite material with 1 wt% microcapsule is demonstrated to have better insulation strength. Microcapsules can attract the development of electric trees and limit their size, while the electrical tree can trigger the self-healing behavior of microcapsules in time. The self-healing behavior can effectively heal the electrical tree branch channel, restore breakdown strength and polarization current, and reverse the deterioration process of the material. Molecular dynamics (MD) simulation confirms that there is good chemical compatibility between the healing product and PE matrix, ensuring a good self-healing effect.

Given the widespread use of wood-based materials and that these materials are often damaged, an abundance of materials have been developed to repair and restore wood. Most of these materials treat the binder and filler as a single system; however, there is yet to be a system that has all the desired properties of an ideal wood-repair composite. Aiming for the goal of creating an ideal wood filler, this study proposed a wood-repair composite that combined epoxy resins, polyether amines, and poplar wood fibers. The materials were selected to mimic the hydrophobicity of lotus leaves and the strong adhesion of mussel proteins. The properties of the designed wood composites were characterized by various testing methods. The prepared fillers were then used to repair damaged poplar wood panels. The mechanical properties of the wood sample repaired with the optimal filler formulation reached 97% of those of the undamaged wood. In summary, the wood composites proposed in this study present a new means of repairing wooden relics, exposed outdoor wooden buildings, and household panels.

Three-dimensional porous carbon materials with moderate heteroatom-doping have been extensively investigated as promising electrode materials for energy storage. In this study, we fabricated a 3D cross-linked chitosan-dicyandiamide-VOSO4 hydrogel using a polymerization process. After pyrolysis at high temperature, 3D porous VOx/N-doped carbon nanosheet hybrids (3D VNCN) were obtained. The unique 3D porous skeleton, abundant doping elements, and presence of VOx 3D VNCN pyrolyzed at 800 °C (3D VNCN-800) ensured excellent electrochemical performance. The 3D VNCN-800 electrode exhibits a maximum specific capacitance of 408.1 F·g−1 at 1 A·g−1 current density and an admirable cycling stability with 96.8% capacitance retention after 5000 cycles. Moreover, an assembled symmetrical supercapacitor based on the 3D VNCN-800 electrode delivers a maximum energy density of 15.6 Wh·Kg−1 at a power density of 600 W·Kg−1. Our study demonstrates a potential guideline for the fabrication of porous carbon materials with 3D structure and abundant heteroatom-doping.

The development of low-cost and high-performance bifunctional electrocatalysts for overall water splitting is still challenging. Herein, we employed a facile electrodeposition method to prepare bifunctional cobalt phosphide for overall water splitting. The needle-like cobalt phosphide (Co-P-1) nanoarray is uniformly distributed on nickel foam. Co-P-1 exhibits excellent electrocatalytic activity for hydrogen evolution reaction (HER, 85 mV at 10 mA/cm2, 60 mV/dec) and oxygen evolution reaction (OER, 294 mV at 50 mA/cm2, 60 mV/dec). The cell-voltage of 1.60 V is found to achieve the current density of 10 mA/cm2 for overall water splitting in the two-electrode system, comparable to that of previously reported Pt/C/NF||RuO2/NF. The excellent electrocatalytic performance can be attributed to the needle-like structure with more active sites, accelerated charge transfer and evolved bubbles’ release. This work can provide new approach to the development of a bifunctional electrocatalyst for overall water splitting.

Lithium batteries incorporating LiFePO4 (LFP) as the cathode material have gained significant attention in recent research. However, the limited electronic and ionic conductivity of LFP poses challenges to its cycling performance and overall efficiency. In this study, we address these issues by synthesizing a series of LiFePO4/carbon (LFP/C) composites through low-temperature carbonization coating of LFP in the presence of Coke as the carbon source. The resulting lithium batteries utilizing LFP/C as the cathode material exhibited impressive discharge specific capacities of 148.35 mA·h/g and 126.74 mA·h/g at 0.1 C and 1 C rates, respectively. Even after 200 cycles of charging and discharging, the capacities remained remarkably high, with values of 93.74% and 97.05% retention, showcasing excellent cycling stability. Notably, the LFP/C composite displayed exceptional rate capability, and capacity retention of 99.27% after cycling at different multiplication rates. These findings underscore the efficacy of in situ low-temperature carbonization capping of LFP with Coke in significantly improving both the cycling stability and rate capability of lithium batteries.

Effects of hot pixels on pixel performance in light and dark environments have been investigated in pinned photodiode 0.18 μm backside illuminated CMOS image sensors irradiated by 10 MeV protons. After exposure to protons, hot pixels and normal pixels are selected from the whole pixel array, and their influences on key parameters are analyzed. Experimental results show that radiation-induced hot pixels have a significant impact on pixel performance in dark environments, such as dark signal nonuniformity, long integration time, and random telegraph signal. Hot pixels are caused by defects with complex structures, i.e., cluster defects. Furthermore, the dark current activation energy result confirms that the defects causing the hot pixels have defect energy levels close to mid-gap.

The research on rapid and efficient detection of microplastics in water is still in its early stages. Fluorescence feature recognition represents an important and innovative approach to microplastic detection. While carbon quantum dots have been widely used in various environmental detection methods, their use for detecting microplastics in water environments has been rarely reported. In this study, N and Cl co-doped carbon quantum dots were synthesized via a hydrothermal method. The heteroatom doping process endowed them with blue luminescence properties, and their adsorption for microplastics was improved through the introduction of positive and negative charges and intermolecular forces. By utilizing a combined mechanism of fluorescence and Rayleigh scattering, the detection of polystyrene microplastics with three different particle sizes was achieved. In the detection process, it exhibits excellent light stability. Notably, the nano-polystyrene exhibited a good nonlinear relationship within the range of 0.01 g/L to 0.001 g/L, with R2 values of 0.923 and 0.980 and a detection limit of 0.4 mg/L. These findings provide a novel approach for the detection of nano microplastics.

Abstract In microservice systems, availability can be ensured through a variety of measures, such as fault tolerance and flow limiting, which are collectively called the flow control. In the current mainstream system design, the flow control rules are usually fixed and set manually, which cannot be dynamically adjusted according to the flow shape. The performance of the system is thus not fully explored. To mitigate this problem, an adaptive dynamic flow control algorithm is proposed. Based on the system's monitoring data and current flow, the algorithm calculates the flow‐limiting threshold in real time, and then it implements fine‐grained service adaptive flow control to improve the resource utilization. Experimental results show that the performance of the adaptive automatic flow control is better than that of the traditional static method on resource utilization.

BackgroundThis study aims to explore the relationship between the lymph nodes examined and survival benefits of postoperative radiotherapy in oral cavity squamous cell carcinoma patients with stage T1-2N1M0.MethodsThis study retrieved patients who underwent dissection of the primary site and neck lymph nodes for pT1-2N1M0 oral cavity squamous cell carcinoma without adverse nodal features from the Surveillance, Epidemiology, and End Results database from 2004 to 2015. Propensity score matching analysis was conducted, and the best cutoff value of the lymph nodes examined was determined by X-tile. Cancer-specific survival was the primary outcome. Univariable and multivariable analyses were performed to assess the relation between postoperative radiotherapy and cancer-specific survival, adjusting for other prognostic factors.ResultsA total of 469 patients were finally enrolled according to our exclusion criteria, and then 119 pairs of patients were matched by propensity score matching analysis. The best cutoff value of the lymph nodes examined was determined by X-tile, stratifying patients into lymph nodes examined ≤16 group and lymph nodes examined >16 group. For the whole matched cohort, the choice of postoperative radiotherapy had no correlation with other factors (all p’s > 0.05), and postoperative radiotherapy made no contribution to a better survival outcome for patients (p = 0.289). After stratified by the lymph nodes examined, in the lymph nodes examined ≤16 group, significantly improved CSS was found for those who undertook postoperative radiotherapy compared to those who just received surgery (unadjusted hazard ratio, 0.541; 95% confidence interval, 0.333–0.878; p = 0.013).ConclusionsOur study revealed that pT1-2N1M0 oral cavity squamous cell carcinoma patients were more likely to benefit from postoperative radiotherapy when unsatisfactory neck dissection was conducted, indicating that the number of lymph nodes examined might be a factor when clinicians do therapeutic planning for early-stage oral cavity squamous cell carcinoma patients.

A long-term annealing experiment was performed using 850 nm vertical-cavity surface-emitting lasers (VCSELs) irradiated with 10 MeV protons. Static parameters such as the threshold current, slope efficiency, and light output power were tested using annealing currents above and below the threshold. The experimental results indicated that these parameters gradually recovered with annealing time, and the degree of recovery was proportional to the annealing current. In addition, curve fitting was performed to obtain the direct relationship between the slope efficiency and annealing current. A comprehensive investigation of the annealing behavior of VCSELs is crucial for device applications in harsh radiation environments.

Rapid growth is one of the most important economic traits in broiler breeding programs. Identifying markers and genes for growth traits may not only benefit marker-assisted selection (MAS)/genomic selection (GS) but also provide important information for understanding the genetic architecture of growth traits in broilers. In the present study, an F2 resource population derived from a cross between the broiler and Baier yellow chicken (a Chinese local breed) was used and body weights from 1 to 12 weeks of age [body weight (BW) 1–BW12)] were measured. A total of 519 F2 birds were genome re-sequenced, and a combination of genome-wide association study (GWAS) and selective sweep analysis was carried out to characterize the genetic architecture affecting chicken body weight comprehensively. As a result, 1,539 SNPs with significant effects on body weights at different weeks of age were identified using a genome-wide efficient mixed-model association (GEMMA) package. These SNPs were distributed on chromosomes 1 and 4. Besides, windows under selection identified for BW1–BW12 varied from 1,581 to 2,265. A total of 42 genes were also identified with significant effects on BW1–BW12 based on both GWAS and selective sweep analysis. Among these genes, diacylglycerol kinase eta (DGKH), deleted in lymphocytic leukemia (DLEU7), forkhead box O17 (FOXO1), karyopherin subunit alpha 3 (KPNA3), calcium binding protein 39 like (CAB39L), potassium voltage-gated channel interacting protein 4 (KCNIP4), and slit guidance ligand 2 (SLIT2) were considered as important genes for broiler growth based on their basic functions. The results of this study may supply important information for understanding the genetic architecture of growth traits in broilers.

Understanding the spatial variations in regional eco-environmental quality and their driving factors is essential for environmental management and protection. However, the lack of quantitative analyses in relevant studies has often hindered the formulation and implementation of effective eco-environmental policies. Taking Minjiang River Basin as an example, we used the remote sensing ecological indices (RSEI) to objectively and quantitatively characterize the eco-environmental quality. We also introduced and compared the maximum entropy (MaxEnt) and the random forest models to identify the critical driving factors. Results showed that the eco-environmental quality of Minjiang River Basin in 2020 was good overall, and the areas with good or excellent eco-environmental quality accounted for 58%. The areas with poor eco-environmental quality were mainly distributed in the periphery of the basin and the riverine areas. Both the MaxEnt and the random forest models were applicable to identify the critical driving factors and indicated that the degrees of landscape fragmentation and drastic land use were the main factors causing spatial variation of eco-environmental quality in the Minjiang River Basin. This study provides a new perspective and method for quantitative analysis of the driving factors of the spatial variations in regional eco-environmental quality for future eco-environmental management and protection.

The optimization of supercapacitive properties in carbon materials derived from cheap and sustainable wood scraps exhibits great application potential. Herein, in support of interfacial groups, polyaniline nanospheres were in situ constructed in the internal pore structure of wood scraps; further, the B and N elements were imported by carbonized and hydrothermal methods. The doped B regulated the species of N doping to improve the electrical conductivity of carbonized wood scraps, and it endowed a certain pseudo-capacitance. Coupled with the fine double-layer capacitance from the hierarchical structures constructed by carbonized nanospheres and wood scrap channels, a high specific capacitance of 406 F g−1 at 0.5 A g−1, high energy density (17.71 Wh kg−1 at 250 W kg−1) and cycle stability (93.04% capacitance retention after 10,000 cycles) were performed simultaneously. This study provided a new strategy to improve the supercapacitive performance of bio-carbon materials in terms of structure and conductance.

The persistent challenge of removing viscous oil on water surfaces continues to pose a major concern and requires immediate attention. Here, a novel solution has been introduced in the form of a superhydrophobic/superoleophilic PDMS/SiO2 aerogel fabric gathering device (SFGD). The SFGD is based on the adhesive and kinematic viscosity properties of oil, enabling self-driven collection of floating oil on the water surface. The SFGD is able to spontaneously capture the floating oil, selectively filter it, and sustainably collect it into its porous fabric interior through the synergistic effects of surface tension, gravity, and liquid pressure. This eliminates the need for auxiliary operations such as pumping, pouring, or squeezing. The SFGD demonstrates exceptional average recovery efficiencies of 94% for oils with viscosities ranging from 10 to 1000 mPa·s at room temperature, including dimethylsilicone oil, soybean oil, and machine oil. With its facile design, ease of fabrication, high recovery efficiency, excellent reclaiming capabilities, and scalability for multiple oil mixtures, the SFGD represents a significant advancement in the separation of immiscible oil/water mixtures of various viscosities and brings the separation process one step closer to practical application.

The effective removal of oxytetracycline hydrochloride (OTC) from the water environment is of great importance. Adsorption as a simple, stable, and cost-effective technology is regarded as an important method for removing OTC. Herein, a low-cost biochar with a developed mesoporous structure was synthesized via pyrolysis of poplar leaf with potassium bicarbonate (KHCO3) as the activator. KHCO3 can endow biochar with abundant mesopores, but excessive KHCO3 cannot continuously promote the formation of mesoporous structures. In comparison with all of the prepared biochars, PKC-4 (biochar with a poplar leaf to KHCO3 mass ratio of 5:4) shows the highest adsorption performance for OTC as it has the largest surface area and richest mesoporous structure. The pseudo-second-order kinetic model and the Freundlich equilibrium model are more consistent with the experimental data, which implies that the adsorption process is multi-mechanism and multi-layered. In addition, the maximum adsorption capacities of biochar are slightly affected by pH changes, different metal ions, and different water matrices. Moreover, the biochar can be regenerated by pyrolysis, and its adsorption capacity only decreases by approximately 6% after four cycles. The adsorption of biochar for OTC is mainly controlled by pore filling, though electrostatic interactions, hydrogen bonding, and π-π interaction are also involved. This study realizes biomass waste recycling and highlights the potential of poplar leaf-based biochar for the adsorption of antibiotics.

We first propose and demonstrate a novel approach for achieving a focused laser differential interferometer (FLDI) system with tunable spatial resolution. The spatial resolution of the FLDI can be adjusted continuously between 83 μm and 382 μm. The density fluctuation of a supersonic shear flow is measured using the FLDI system with a spatial resolution of 182 μm, and the density fluctuations at different locations of the supersonic shear flow are measured and analyzed. The ability to adjust the spatial resolution in this work is of great significance for enhancing the spatial resolution and flexibility of the FLDI system.

Currently, many problems such as variable signal resources, complex execution environments, and low efficiency of scheduling algorithms are faced by heterogeneous signal processing platforms. The task scheduling algorithm is one of the key factors that directly affect the performance of the processing platform. In order to solve the problems of low efficiency of task scheduling algorithms and high computational cost of processors, a heterogeneous platform scheduling algorithm based on the quantum genetic algorithm is proposed in this paper. The algorithm constructs a task scheduling model by using a directed acyclic graph. This paper quantifies the mapping relationship between the quantum genetic algorithm and task scheduling. It corresponds qubits to binary, chromosomes to processor numbers, and individuals to processor scheduling strategies. In this paper, a new way of coding chromosomes using quantum coherence properties is designed to reduce the population size and increase population diversity. Crossover operations are performed on all individuals using full-interference crossover to avoid the results falling into local optimal solutions. The population of slow convergence is solved by implementing mutation operations on populations through quantum rotation gates. In addition, a task pre-ordering stage is designed based on the table scheduling algorithm. The task scheduling priority developed at this stage is used as the reference value for the initial encoding of the population, so that the search space for solutions is reduced. Finally, experiments are conducted using randomly generated task graphs. The algorithm is compared with improved genetic algorithms and existing intelligent scheduling algorithms. The results show that the algorithm can still obtain better results when the number of populations and iterations is small. It is more appropriate for heterogeneous platforms and computation-intensive tasks.

It has been reported that forkhead box D1 (FOXD1) plays an established role in human early embryonic development and is broadly involved in various malignancies. However, there is limited information regarding FOXD1 expression in head and neck squamous cell carcinoma (HNSCC). This present study aimed to explore the clinical significance of FOXD1 in patients with HNSCC. Tissue microarrays of 334 primary HNSCC patients who underwent surgery between 2008 and 2010 at Sun Yat-sen University Cancer Center were investigated by immunohistochemistry regarding FOXD1 expression. χ2 test was used to estimate the relationship of FOXD1 expression with clinicopathologic characteristics. Univariate and multivariate analyses were performed to identify FOXD1 expression as an independent prognostic indicator of overall survival (OS) and disease-free survival (DFS). FOXD1 expression is closely associated with postoperative recurrence. HNSCC patients with high FOXD1 expression have poorer prognoses than the low-expression group (p < 0.05). According to multivariate analysis, FOXD1 was an independent prognostic factor for OS and DFS. The results revealed that FOXD1 could be a prognostic factor for HNSCC and might serve as a potential target for novel therapies.

Abstract KLF3 is a member of the Kruppel‐like factor (KLF) family of transcription factors, and plays an important role in several biological processes, including adipogenesis, erythropoiesis and B‐cell development. The purposes of this study are to search for polymorphisms of KLF3 coding region and to provide functional evidence for abdominal fat in chickens. A total of 168 SNPs in KLF3 coding region were detected in a unique chicken population, the Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF). Of which three single nucleotide polymorphisms (g.3452T > C, g.8663A > G and g.10751G > A) were significantly correlated with abdominal fat weight (AFW) and abdominal fat percentage (AFP) of 329 birds from the 19th generation of NEAUHLF (FDR A (p A is a functional variant that potential would be applied to marker‐assisted selection (MAS) for selective breeding programme.

Forests play an important role in the global carbon cycle, and the growth of forest trees is essential to forest carbon sinks. It is necessary to explore the diameter at breast height (DBH) growth of trees and to quantify the effects of different factors on their growth to predict forest development. This study constructed an individual-tree annual growth-rate model of 41 dominant tree species in China to explore the effects of genetic characteristics and the environment on tree growth and the relationship between forest carbon sink capacity and the geographical environment. The model was estimated and evaluated based on 492,555 samples of 7801 permanent plots (covering 31 provinces in mainland China) and then decomposed into a general annual growth-rate component and an environmental modifier component. The results showed that tree species and size were the dominant factors that affected the growth rate, showing an inverse J-curve trend, and temperature was the most important of all environmental factors. In addition, there was a significant correlation between the potential aboveground carbon sink (PACS) and the geographic growth pattern index (GPI) (Spearman’s = 0.445, p-value

Alkaline pretreatment of herbaceous feedstocks such as corn stover prior to mechanical refining and enzymatic saccharification improves downstream sugar yields by removing acetyl moieties from hemicellulose. However, the relationship between transport phenomena and deacetylation kinetics is virtually unknown for such feedstocks and this pretreatment process. Here, we report the development of an experimentally validated reaction–diffusion model for the deacetylation of corn stover. A tissue-specific transport model is used to estimate transport-independent kinetic rate constants for the reactive extraction of acetate, hemicellulose and lignin from corn stover under representative alkaline conditions (5–7 g L−1 NaOH, 10 wt% solids loadings) and at low to mild temperatures (4–70°C) selected to attenuate individual component extraction rates under differential kinetic regimes. The underlying transport model is based on microstructural characteristics of corn stover derived from statistically meaningful geometric particle and pore measurements. These physical descriptors are incorporated into distinct particle models of the three major anatomical fractions (cobs, husks and stalks) alongside an unsorted, aggregate corn stover particle, capturing average Feret lengths of 917–1239 μm and length-to-width aspect ratios of 1.8–2.9 for this highly heterogeneous feedstock. Individual reaction–diffusion models and their resulting particle model ensembles are used to validate and predict anatomically-specific and bulk feedstock performance under kinetic-controlled vs. diffusion-controlled regimes. In general, deacetylation kinetics and mass transfer processes are predicted to compete on similar time and length scales, emphasizing the significance of intraparticle transport phenomena. Critically, we predict that typical corn stover particles as small as ∼2.3 mm in length are entirely diffusion-limited for acetate extraction, with experimental effectiveness factors calculated to be 0.50 for such processes. Debilitatingly low effectiveness factors of 0.021–0.054 are uncovered for cobs—implying that intraparticle mass transfer resistances may impair observable kinetic measurements of this anatomical fraction by up to 98%. These first-reported quantitative maps of reaction vs. diffusion control link fundamental insights into corn stover anatomy, biopolymer composition, practical size reduction thresholds and their kinetic consequences. These results offer a guidepost for industrial deacetylation reactor design, scale-up and feedstock selection, further establishing deacetylation as a viable biorefinery pretreatment for the conversion of lignocellulosics into value-added fuels and chemicals.

(1) Background: In recent years, Hippophae rhamnoides has been used extensively to prevent desertification in China due to its nitrogen (N) fixation and sand stabilization abilities. However, as a dioecious species, few studies have focused on the sexual dimorphism of H. rhamnoides in response to sand burial, which frequently presents in desertification areas. (2) Methods: In this paper, we explored the ecophysiological responses of female and male saplings of H. rhamnoides under unburied treatment (control) and different sand burial depths (denoted as T33, T67, T90 and T133, corresponding to sand burial depths of 33, 67, 90 and 133 percent of the mean initial height of the saplings, respectively). (3) Results: Compared with unburied controls, the T33 treatment significantly promoted biomass accumulation and photosynthetic capacity, whereas T67 and T90 treatments inhibited biomass and physiological parameters of the two sexes. Deeper sand burial treatments, i.e., T90 and T133, significantly decreased the survival rates of the two sexes. Furthermore, the sex-specific responses of the two sexes of H. rhamnoides were affected by different depths of sand burial. Males had higher levels of stem starch and root sucrose and exhibited a larger increase in root nodule biomass under the T33 treatment, indicating better carbohydrate utilization and N fixation, whereas females showed lower total biomass and fewer root nodules, as well as more inhibition of photosynthetic and chlorophyll fluorescence parameters, water potential and root carbohydrates, indicating more negative effects on females than males under the T67 treatment. (4) Conclusions: We conclude that sex-related response and adaptation to sand burial depths may potentially affect the colonization, sex ratio and ecological function of the two sexes of H. rhamnoides in desertification areas.

As more and more oilfields enter later stages of extraction, demulsification of water-in-oil (W/O) emulsions with high water content has become a challenging problem. To upgrade the current offshore oil treatment process, a compact and efficient demulsification treatment is highly desirable. In this paper, a novel enhanced treatment combining a direct current (DC) electric field and medium coalescence was proposed. Based on this idea, an electric-medium demulsifier was also designed for deep purification of W/O emulsions. The effects of operating conditions, emulsions characteristics and medium bed parameters on demulsification performance were investigated. The enhanced treatment showed better performance compared to electrostatic demulsification and medium coalescence alone, and was especially suitable for treating emulsions with strong emulsification. In short, at U = 3 kV, the demulsification efficiency increased by approximately 30% compared to that at U = 0 kV. This research provided a new approach for the treatment of W/O emulsions that has the advantages of wide operational flexibility, a tolerance for deteriorated characteristics and a rapid and thorough treatment process.

Improving the produced fluid yield is an effective measure for realizing the crude oil production capacity of offshore platforms. However, for offshore platforms employed in production, using the narrow space of the platform to expand the produced water treatment system is a significant problem. In this study, a highly efficient pre-treatment core tube was coupled with the main cavity and secondary cavities (MCSCs) based on a vane-type tubular separator and a cub-mother cyclone. The optimal inlet Reynolds number and processing capacity were determined according to the structure size of the MCSC, and the MCSC was applied to achieve highly efficient pre-treatment of produced water in a heavy oilfield in the Bohai Sea. The comprehensive evaluation indicators FA and FV were better than those used by current technology. When the influent oil content fluctuated around 2000 mg/L (average of 1772.81 mg/L), the oil content in the effluent was stable and below 200 mg/L (average of 106.44 mg/L), and the separation efficiency was nearly 94%. Compared to those of the current corrugated plate interceptor on the platform, the floor space was reduced by more than 60% and the separation efficiency increased by up to 65%.

Mycotoxin contamination in food poses health hazards to humans. Current methods of controlling mycotoxins still have limitations and more effective approaches are needed. During the past decades of years, variable environmental factors have been tested for their influence on mycotoxin production leading to elucidation of a complex regulatory network involved in mycotoxin biosynthesis. These regulators are putative targets for screening molecules that could inhibit mycotoxin synthesis. Here, we summarize the regulatory mechanisms of hierarchical regulators, including pathway-specific regulators, global regulators and epigenetic regulators, on the production of the most critical mycotoxins (aflatoxins, patulin, citrinin, trichothecenes and fumonisins). Future studies on regulation of mycotoxins will provide valuable knowledge for exploring novel methods to inhibit mycotoxin biosynthesis in a more efficient way.

Cyclin D1 is involved in tamoxifen resistance in breast cancer (BC) but how it is regulated is unclear. Here, the authors demonstrate that the LncRNA DILA1 contributes to tamoxifen resistance in breast cancer by binding to Cyclin D1 and preventing its degradation.

Mass production of sustainable biofuels replacing fossil fuels will significantly reduce global greenhouse gas emissions. However, biomass feedstock variability, availability, and affordability pose significant risks for the sustainable production of biofuels in biorefinery plants. To derisk the sustainable production of biofuels, this work investigates the sugar yields and production costs of four different feedstocks as well as their blends, using different pretreatment methods: deacetylation and dilute acid pretreatment (DDA) and deacetylation and mechanical refining pretreatment (DMR). We found that not only feedstock species variability, but also feedstock harvesting techniques have large impacts on both sugar yields and production costs. Single-pass harvested corn stover (SPCS) showed higher sugar yields and lower production costs than multipass harvested corn stover, followed by sorghum and switchgrass. The highest glucose yields of 91% and 95.3%, which corresponds to the lowest sugar production costs of $0.2286/lb. and $0.2490/lb., were observed for SPCS using DDA and DMR, respectively. The difference in sugar yields and production costs due to feedstock variability can be largely mitigated by increasing deacetylation severity, especially in DMR. Higher deacetylation severity resulted in decreased sugar production costs in the case of DMR in contrast to increased costs in the case of DDA. Blending switchgrass and sorghum into corn stover, which can significantly increase the feedstock availability and sustainability, resulted in sugar yields and production costs of roughly the weighted average of those derived from constituent individual feedstocks, respectively. Thus, blending feedstocks of different biomass species is a potential successful strategy for sustainable production of biofuels to replace fossil-derived fuels.

Reintroducing captive giant pandas (Ailuropoda melanoleuca) to the wild is the ultimate goal of their ex situ conservation. Choosing higher fitness candidates to train prior to release is the first step in the giant panda reintroduction program. Disease resistance is one important index of individual fitness and presumed to be related to variation at major histocompatibility complex genes (MHC). Here, we used seven polymorphic functional MHC genes (Aime-C, Aime-I, Aime-L, Aime-DQA1, Aime-DQA2, Aime-DQB1 and Aime-DRB3) and estimate their relationship with Baylisascaris schroederi (Ascarididae) infection in giant panda. We found that DQA1 heterozygous pandas were less frequently infected than homozygotes. The presence of one MHC genotype and one MHC allele were also associated with B. schroederi infection: Aime-C*0203 and Aime-L*08 were both associated with B. schroederi resistance. Our results indicate that both heterozygosity and certain MHC variants are important for panda disease resistance, and should therefore be considered in future reintroduction programs for this species alongside conventional selection criteria (such as physical condition and pedigree-based information).

Moisture variation is extremely relevant for the stability of ecosystems in Central Asia (CA). Therefore, moisture evolution and its potential driving mechanism over the region are always a hot research topic. Although much effort has been devoted to understanding the processes of moisture evolutions in CA during the Quaternary, particularly the Holocene, the associated underlying mechanisms remain in a state of persistent debate. In this study, the granulometry, clay mineral and chroma properties of a loess section (named ZSP section) in the westerlies-dominated Ili Basin, NW China are investigated. With the accelerator mass spectrometry radiocarbon dating (AMS 14C)-based Bayesian age–depth model, we provide a sensitive record of effective moisture evolution since the last glacial maximum (LGM) in the basin, and the results help enhance understanding of the possible driving mechanisms for westerly climate change. Comparisons of clay mineralogy indices shows that the study area is involved in the Northern Hemisphere dust cycle processes as a dust source, and the content of

Forest fires may have devastating consequences for the environment and for human lives. The prediction of forest fires is vital for preventing their occurrence. Currently, there are fewer studies on the prediction of forest fires over longer time scales in China. This is due to the difficulty of forecasting forest fires. There are many factors that have an impact on the occurrence of forest fires. The specific contribution of each factor to the occurrence of forest fires is not clear when using conventional analyses. In this study, we leveraged the excellent performance of artificial intelligence algorithms in fusing data from multiple sources (e.g., fire hotspots, meteorological conditions, terrain, vegetation, and socioeconomic data collected from 2003 to 2016). We have tested several algorithms and, finally, four algorithms were selected for formal data processing. There were an artificial neural network, a radial basis function network, a support-vector machine, and a random forest to identify thirteen major drivers of forest fires in China. The models were evaluated using the five performance indicators of accuracy, precision, recall, f1 value, and area under the curve. We obtained the probability of forest fire occurrence in each province of China using the optimal model. Moreover, the spatial distribution of high-to-low forest fire-prone areas was mapped. The results showed that the prediction accuracies of the four forest fire prediction models were between 75.8% and 89.2%, and the area under the curve (AUC) values were between 0.840 and 0.960. The random forest model had the highest accuracy (89.2%) and AUC value (0.96). It was determined as the best performance model in this study. The prediction results indicate that the areas with high incidences of forest fires are mainly concentrated in north-eastern China (Heilongjiang Province and northern Inner Mongolia Autonomous Region) and south-eastern China (including Fujian Province and Jiangxi Province). In areas at high risk of forest fire, management departments should improve forest fire prevention and control by establishing watch towers and using other monitoring equipment. This study helped in understanding the main drivers of forest fires in China over the period between 2003 and 2016, and determined the best performance model. The spatial distribution of high-to-low forest fire-prone areas maps were produced in order to depict the comprehensive views of China’s forest fire risks in each province. They were expected to form a scientific basis for helping the decision-making of China’s forest fire prevention authorities.

Gut microbiota during early life could influence host fitness in vertebrates. Studies on how gut microbiota colonize the gut in birds using frequent sampling during early developmental stages and how shifts in microbiota diversity influence host growth are lacking. Here, we examine the microbiome profiles of 151 fecal samples from 14 young crested ibis (Nipponia nippon), an endangered bird species, collected longitudinally across 13 time points during the early stages of development and investigated their correlation with host growth. Gut diversity showed a non-linear change during development, which involved multiple colonization and extinction events, mainly associated with Proteobacteria and Firmicutes. Gut microbiota in young crested ibis became more similar with increasing age. In addition, gut microbiota exhibited a strong temporal structure and two specific developmental stages; the beginning of the latter stage coincided with the introduction of fresh loach, with a considerable increase in the relative abundance of Fusobacteria and several Firmicutes, which may be involved in lipid metabolism. Crested ibis chick growth rate was negatively correlated with gut microbiota diversity and negatively associated with the abundance of Halomonadaceae, Streptococci, Corynebacteriaceae, and Dietziaceae. Our findings highlight the importance of frequent sampling when studying microbiome development during early stages of development of vertebrates. The role of microbial diversity in host growth during the early stages of development of birds warrants further investigations.

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement.

In foreground segmentation, it is challenging to construct an effective background model to learn the spatial-temporal representation of the background. Recently, deep learning-based background models (DBMs) with the capability of extracting high-level features have shown remarkable performance. However, the existing state-of-the-art DBMs deal with video segmentation as single-image segmentation and ignore temporal cues in video sequences. To exploit temporal data sufficiently, this paper proposes a multi-input multi-output (MIMO) DBM framework for the first time, which is partially inspired by the binocular summation effect in human eyes. Our framework is an X-shaped network which allows the DBM to track temporal changes in a video sequence. Moreover, each output branch of our model could receive visual signals from two similar input frames simultaneously like the binocular summation mechanism. In addition, our model can be trained end-to-end using only a few training examples without any post-processing. We evaluate our method on the largest dataset for change detection (CDnet 2014) and achieve the state-of-the-art performance by an average overall F-Measure of 0.9920.

Abstract A novel photocatalyst of mesoporous graphitic carbon nitride (g-C3N4) co-doped with Co and Mo (Co/Mo-MCN) has been one-pot synthesized via a simple template-free method; cobalt chloride and molybdenum disulfide were used as the Co and Mo sources, respectively. The characterization results evidently indicate that molybdenum disulfide functions as Mo sources to incorporate Mo atoms in the framework of g-C3N4 and as a catalyst for promoting the decomposition of g-C3N4, resulting in the creation of mesopores. The obtained Co/Mo-MCN exhibited a significant enhancement of the photocatalytic activity in H2 evolution (8.6 times) and Rhodamine B degradation (10.1 times) under visible light irradiation compared to pristine g-C3N4. Furthermore, density functional theory calculations were applied to further understand the photocatalytic enhancement mechanism of the optical absorption properties at the atomic level after Co- or Mo-doping. Finite-difference time-domain simulations were performed to evaluate the effect of the mesopore structures on the light absorption capability. The results revealed that both the bimetal doping and the mesoporous architectures resulted in an enhanced optical absorption; this phenomenon was considered to have played a critical role in the improvement in the photocatalytic performance of Co/Mo-MCN.