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Interface engineering is widely used to enhance the efficiency and stability of photodetectors (PDs). Although fluorine-containing materials are ideal for interface modification, they are seldom used at the NiOx/perovskite interface. This paper reports on the use of Tris(pentafluorophenyl)borane (BCF) and 2,3,5,6-tetrafluoro-7,7,8,8- tetracyanoquinodimethane (F4-TCNQ)-modified NiOx HTL to achieve high-efficiency and high-stability PDs. This study shows that BCF and F4-TCNQ interact to provide better doping ability, form Lewis adducts with Pb2+, and enhance the crystallinity of their perovskites. Interaction with nickel oxide optimizes the Ni3+/Ni2+ ratio, thus improving conductivity and charge transport capability. The F4-TCNQ:BCF modification effectively reduces interface defects, improves carrier mobility, and enhances both the performance and stability of PDs in ambient air. The detector achieves a maximum EQE value of 89.4%, a dark current density of 1.51 × 10−10A cm−2, a detectivity of 6.33 × 1013 Jones, and a LDR of 133.4 dB. Additionally, the interfacially modified device maintains over 90% of its initial performance after one month of storage in ambient air. Our results highlight the importance of F4-TCNQ:BCF interface modification and provide a reference for the further research and development of perovskite devices. [ABSTRACT FROM AUTHOR]

Quantitative structure-activity relationship modeling techniques are widely employed in diverse areas of chemistry, including environmental risk assessment of compounds and virtual screening of drugs. The modeling process entails optimizing the hyper parameters of the model and selecting appropriate molecular descriptors. It is a typical optimization problem with high-dimensional, nonlinear, continuous and discrete variables coexisting. To address this challenge, this paper proposes an enhanced snake optimizer with multiple strategies. First, new food emergence and temperature change mechanisms are introduced to balance the exploration and exploitation. Second, a death and regeneration mechanism is employed to enhance the algorithm's ability to escape from local optima. Third, new formulas for food searching, fighting, mating and eating are designed to simplify the complexity of the algorithm and improve its search efficiency and accuracy. Fourth, the performance of the proposed algorithm is evaluated using the CEC2017 benchmark functions, eight engineering cases with continuous variables, and six feature selection cases with discrete variables. Experimental results demonstrate that the algorithm significantly outperforms comparison algorithms. Finally, the algorithm was applied to quantitative structure-activity relationship modeling for environmental toxicity prediction. Compared with other algorithms, the algorithm can better configure hyper-parameters and select fewer and more effective features for environmental toxicity prediction model. It will be an effective tool to improve the performance of quantitative structure-activity relationship models. • New food emergence and temperature change mechanisms are presented to better balance exploration and exploitation. • Death and regeneration mechanism is adopted to avoid local optima. • The performance of the proposed algorithm is validated in CEC2017, engineering design and feature selection problems. • A joint optimization approach is proposed for quantitative structure-activity relationship modeling. • An environmental toxicity prediction model is obtained by jointly optimizing hyper-parameters and molecular descriptors. [ABSTRACT FROM AUTHOR]

Spiro-OMeTAD is a commonly used hole transport layer (HTL) in perovskite photodetectors (PDs) due to its high glass transition temperature, good solubility in organic solvents, amorphous nature, and better energy level alignment with perovskite layers, etc. However, the unoxidized Spiro-OMeTAD has low electrical conductivity and hole mobility, while air oxidation raises device performance and reproducibility issues. In this study, we successfully achieved early and rapid oxidation of Spiro-OMeTAD by introducing a quantitative amount of manganese dioxide (MnO 2), circumventing the challenges of air oxidation and greatly reducing device preparation time and cost. Additionally, MnO 2 -doped HTLs exhibited significantly improved PD performance, with specific detectivity (D*) increased from 4.36 × 1012 Jones to 4.14 × 1013 Jones. Unpackaged MnO 2 -doped PDs maintained about 81.4 % of the initial EQE value in the glove box after one month, showing remarkable stability. This work demonstrates the feasibility of using MnO 2 as an oxidizing agent for Spiro-OMeTAD and allows us to appreciate the potential of transition metal-based oxides in the oxidation of HTMs. [ABSTRACT FROM AUTHOR]

Change detection (CD) stands out as a pivotal yet challenging task in the interpretation of remote sensing images. Significant developments have been witnessed, particularly with the rapid advancements in deep learning techniques. Nevertheless, challenges such as incomplete detection targets and unsmooth boundaries remain as most CD methods suffer from ineffective feature fusion. Therefore, this paper presents a multi-scale gated fusion network (MSGFNet) to improve the accuracy of CD results. To effectively extract bi-temporal features, the EfficientNetB4 model based on a Siamese network is employed. Subsequently, we propose a multi-scale gated fusion module (MSGFM) that comprises a multi-scale progressive fusion (MSPF) unit and a gated weight adaptive fusion (GWAF) unit, aimed at fusing bi-temporal multi-scale features to maintain boundary details and detect completely changed targets. Finally, we use the simple yet efficient UNet structure to recover the feature maps and predict results. To demonstrate the effectiveness of the MSGFNet, the LEVIR-CD, WHU-CD, and SYSU-CD datasets were utilized, and the MSGFNet achieved F1 scores of 90.86%, 92.46%, and 80.39% on the three datasets, respectively. Furthermore, the low computational costs and small model size have validated the superior performance of the MSGFNet. [ABSTRACT FROM AUTHOR]

Defoliation and accelerating ripening are important measures for cotton mechanization, and judging the time of defoliation and accelerating the ripening and harvest of cotton relies heavily on the boll opening rate, making it a crucial factor to consider. The traditional methods of cotton opening rate determination are time-consuming, labor-intensive, destructive, and not suitable for a wide range of applications. In this study, the relationship between the change rate of the vegetation index obtained by the unmanned aerial vehicle multi-spectrum and the ground boll opening rate was established to realize rapid non-destructive testing of the boll opening rate. The normalized difference vegetation index (NDVI) and green normalized difference vegetation index (GNDVI) had good prediction ability for the boll opening rate. NDVI in the training set had an R2 of 0.912 and rRMSE of 15.387%, and the validation set performance had an R2 of 0.929 and rRMSE of 13.414%. GNDVI in the training set had an R2 of 0.901 and rRMSE of 16.318%, and the validation set performance had an R2 of 0.909 and rRMSE of 15.225%. The accuracies of the models based on GNDVI and NDVI were within the acceptable range. In terms of predictive models, random forests achieve the highest accuracy in predictions. Accurately predicting the cotton boll opening rate can support decision-making for harvest and harvest aid spray timing, as well as provide technical support for crop growth monitoring and precision agriculture. [ABSTRACT FROM AUTHOR]

[Display omitted] Multi-dimensional design and the combination of multiple phases can effectively enhance the dielectric loss properties and multiple reflection effects of absorbers. Herein, a novel multi-dimensional microporous nanostructured composite, melamine sponge (MS) loaded puffed-rice biomass carbon (C) together with bimetallic carbide material Ni 3 ZnC 0.7 (Ni 3 ZnC 0.7 -MS/C) was synthesized by simple vacuum filtration and hydrothermal calcination. The result indicates that small Ni 3 ZnC 0.7 particles with little Ni doping uniformly decorated on the surfaces of the three-dimensional (3D) melamine sponge and puffed rice carbons. The Ni 3 ZnC 0.7 -MS/C composite mixed with paraffin (weight ratio of 1:2) exhibited the best electromagnetic wave (EMW) absorption performance, and the minimum reflection loss (RL min) value of the Ni 3 ZnC 0.7 -MS/C composite reaches −107.7 dB with a matching thickness of 2.78 mm and the maximum effective absorption bandwidth for RL below −10 dB (EAB max) is adjusted to 9.2 GHz at a matching thickness of 4.0 mm. The dipole polarization effect of the N doping and the different interfaces provided by the 3D structure of the MS carbon enhance the conduction loss and interface polarization, while the positive effects of eddy current and resonance caused by Ni 3 ZnC 0.7 effectively improve the microwave absorption performances. This melamine sponge–loaded bimetallic carbon composite exhibited a magnetic/dielectric loss combination, resulting in a high-performance absorber with lightweight, cost-effective and efficient properties. [ABSTRACT FROM AUTHOR]

Concerning the vision of achieving carbon neutral and peak carbon goals, wind energy is extremely important as a renewable and clean energy source. However, existing research ignores the implicit features of the data preprocessing technique and the role of the internal mechanism of the optimization algorithm, making it difficult to achieve high-accuracy prediction. To fill this gap, this study proposes a wind speed forecasting model that combines data denoising techniques, optimization algorithms, and machine learning algorithms. The model discusses the important parameters in the data decomposition technique, determines the best parameter values by comparing the model's performance, and then decomposes and reconstructs the wind speed time series. In addition, a novel optimization algorithm is used to optimize the parameters of the machine learning algorithm using a waiting strategy and an aggressive strategy to improve the effectiveness of the model. Several control experiments were designed and implemented using 10-min wind speed data from three sites in Penglai, Shandong Province. Based on the numerical comparison results and the discussion of the proposed model, it is concluded that the developed model can obtain high accuracy and reliability of wind speed prediction in the short term relative to other comparative models and can have further applications in wind power plants. [ABSTRACT FROM AUTHOR]

The puffed-rice derived carbon@Ni 3 ZnC 0.7 -400 showed RL min of −39.9 dB and the broadest absorption bandwidth of 9.9 GHz. Moreover, the composite showed good performance stability under 400 °C. [Display omitted] • Various puffed-rice derived carbon@Ni 3 ZnC 0.7 composites were prepared by chemical synthesis and annealing. • The puffed-rice derived carbon@Ni 3 ZnC 0.7 -400 mg showed best electrochemical performance. • It showed RL min of −39.9 dB and the broadest absorption bandwidth of 9.9 GHz. • The composite material can be stable at 400 °C and has good performance stability. With the rapidly development of radar detection technology and the increasingly complex application environment in military field and electromagnetic pollution surrounded by electron devices, increasingly demand is needed for electromagnetic wave absorbent materials with high absorption efficiency and thermal stability. Herein, a novel Ni 3 ZnC 0.7 /Ni loaded puffed-rice derived carbon (RNZC) composites are successfully prepared by vacuum filtration of metal-organic frameworks gel precursor together with layered porous-structure carbon and followed by calcination. The Ni 3 ZnC 0.7 particles uniformly decorate on the surface and pores of puffed-rice derived carbon. The puffed-rice derived carbon@Ni 3 ZnC 0.7 /Ni-400 mg (RNZC-4) sample displayed the best electromagnetic wave absorption (EMA) performances among the samples with different Ni 3 ZnC 0.7 loading. The minimum reflection loss (RL min) of the RNZC-4 composite reaches −39.9 dB at 8.6 GHz, while widest effective absorption bandwidth (EAB) of RNZC-4 for RL < −10 dB can reach 9.9 GHz (8.1–18 GHz, 1.49 mm). High porosity and large specific surface area promote the multiple reflection-absorption effect of the incident electromagnetic waves. The Ni 3 ZnC 0.7 nanoparticles provide a large number of interfaces and dipole factors. Analysis reveals that the RNZC-4 remained general stability under 400 °C with formation of a small amount of NiO and ZnO phases. Surprisingly, at such high temperature, the absorbing properties of the material are improved rather than decreased. Obviously, the material still maintains good electromagnetic wave performance at high temperature, and implies that the absorber shows good performance stability. Therefore, our preparations exhibit potential applications under extreme conditions and a new insight for the design and application of bimetallic carbides. [ABSTRACT FROM AUTHOR]

The industrial robot combined with a 3D vision sensor can be flexibly applied to many measurement fields, and repeatability is one of the key performances. When the robot runs for a long period, internal heating and environmental interference are important factors to decrease the repeatability. The traditional solution is to calibrate the robot dynamically and compensate the error based on kinematic model. However, a high redundancy model will increase the measuring time and dynamic error. In this paper, a time-variant model is applied for dynamic error compensation of robot vision measurement system based on an iterative optimization method. Firstly, the initial kinematic model is constructed and calibration spheres are scanned from different poses at regular intervals. Then, the model is extended to full-redundant 42 parameters. After that, a final model with low redundancy is obtained based on a time-variant identification criterion and an iterative optimization method. Finally, the experimental results on the FANUC LR mate 200iD demonstrate that the proposed method can maintain the repeatability within 0.069 mm on an automotive sheet-metal part. [ABSTRACT FROM AUTHOR]

The composite thin film photodetector in this study combines the characteristics of MAPbI 3 material for near-ultraviolet-visible light and PDPP3T:PC71BM material for near-infrared light absorption, resulting in efficient light harvesting. To fabricate high-performance photodetectors, we optimized the photodetector structure, thin film fabrication process, solute concentration, and photoactive layer thickness. Finally, we obtained a photodetector with a broad spectral detection range in the near-ultraviolet-visible-near-infrared (UV–vis–NIR). The detectivity (D*) of our prepared UV–vis–NIR photodetector at 380 nm, 655 nm and 848 nm is 1.24 × 1013 jones, 2.13 × 1013 jones and 1.59 × 1013 jones, respectively. This is one of the best performances among polymer photodetectors reported so far and is comparable to commercial inorganic silicon-based PDs. In addition, the optimal composite thin film photodetector exhibits a fast response speed (t rise /t fall = 109/49 μs), a linear dynamic range of 100 dB, and excellent stability. Furthermore, the PDPP3T:PC71BM active layer can effectively suppress the leakage current in the reverse biased region, which enables the device to obtain an ultra-low dark current density (J dark) of 8.58 × 10−10 A cm−2. This study explores a new avenue for high-performance photodetectors based on mixtures of perovskites and low-bandgap photoactive polymers. [ABSTRACT FROM AUTHOR]

The integrated system with the strapdown inertial navigation system (SINS) and the global positioning system (GPS) is the most popular navigation mode. It has been used in many navigation fields. Before the integrated system works properly, it must determine the initial attitude for SINS. In SINS/GPS-integrated systems, the navigational velocity can be used to carry out the initial alignment when the system is installed in the in-motion vehicle. However, the initial velocity errors are not considered in the current popular in-motion alignment methods for SINS/GPS integration. It is well-known that the initial velocity errors must exist when the initial velocity is obtained from the GPS outputs. In this paper, an improved method was proposed to solve this problem. By analyzing the original observation vectors in the in-motion coarse alignment method, an average operation was used to construct the intermediate vectors, and the new observation vector can be calculated by subtracting the intermediate vector from the original observation vector. Then, the initial velocity errors can be eliminated from the newly constructed observation vector. Thus, the interferences of the initial velocity errors for the initial alignment process can be suppressed. The simulation and field tests are designed to verify the performance of the proposed method. The tests results showed that the proposed method can obtain the higher accurate results than the current methods when the initial velocity is considered. Additionally, the results of the proposed method were similar to the current methods when the initial velocity errors were not considered. This shows that the initial velocity errors were eliminated effectively by the proposed method, and the alignment accuracy were not decreased. [ABSTRACT FROM AUTHOR]

Background: Although the cutaneous involvement of acromegaly has been recognized, the submacroscopical skin changes and the extent of skin thickening of patients remain unclear. Objectives: This study aimed at investigating the clinical cutaneous manifestations, dermoscopic features, and skin thickness revealed by high‐frequency ultrasound (HFUS) of acromegalic patients. Methods: A case‐control observational study was conducted. Patients with acromegaly and controls were prospectively included and received thorough cutaneous examinations to compare the macroscopical and dermoscopic features. The skin thickness measured by HFUS and its correlation with clinical data were also assessed. Results: Thirty‐seven and 26 patients from acromegalic and control group were included, respectively. Clinical skin manifestations were recorded in detail. Under dermoscopy, red structureless area (91.9% vs. 65.4%, p = 0.021), perifollicular orange halo (78.4% vs. 26.9%, p = 0.005), and follicular plug (70.3% vs. 3.9%, p = 0.001) in the facial area, and perifollicular pigmentation (91.9% vs. 23.1%), broom‐head hairs (83.8% vs. 3.9%), honeycomb‐like pigmentation (97.3% vs. 38.46%), widened dermatoglyphics (81.1% vs. 3.9%) at the extremities (p < 0.001) were more prevalent in acromegaly. The mean skin thickness was 4.10 ± 0.48 mm for acromegaly, and 3.55 ± 0.52 mm for controls (p < 0.001) but no correlation with disease duration, adenoma size, and hormone level was found in acromegaly. Conclusions: Submacroscopical skin changes under dermoscopy and skin thickness increase assessed by HFUS can provide clinicians with subtle evidences for early detection of acromegaly and objective parameters for accurate assessment of its skin involvement. [ABSTRACT FROM AUTHOR]

Shoot stem cells act as the source of the aboveground parts of flowering plants. A precise regulatory basis is required to ensure that plant stem cells show the right status during the stages of proliferation, senescence and cell death. Over the past few decades, the genetic circuits controlling stem cell fate, including the regulatory pathways of establishment, maintenance and differentiation, have been largely revealed. However, the morphological changes and molecular mechanisms of the final stages of stem cells, which are represented by senescence and cell death, have been less studied. The senescence and death of shoot stem cells are under the control of a complex series of pathways that integrate multiple internal and external signals. Given the crucial roles of shoot stem cells in influencing plant longevity and crop yields, researchers have attempted to uncover details of stem cell senescence and death. Recent studies indicate that stem cell activity arrest is controlled by the FRUITFULL–APETALA2 pathway and the plant hormones auxin and cytokinin, while the features of senescent and dead shoot apical stem cells have also been described, with dynamic changes in reactive oxygen species implicated in stem cell death. In this review, we highlight the recent breakthroughs that have enriched our understanding of senescence and cell death processes in plant stem cells. [ABSTRACT FROM AUTHOR]

Single crystal (SC) MAPbBr 3 and MAPbCl 3 perovskite are considered promising materials for fabricating high-performance photodetectors (PDs) due to their impressive optoelectronic properties and good chemical stability. Structural modification of PDs is the fundamental solution to improve performance. In this paper, we designed a simple structure diagram considering photoelectric properties and the possibility of epitaxial crystal growth. Then a solution height restriction method (SHR) was used to grow the crystal and make the internal secondary excitation feasible. X-ray rocking curves (XRC) of MAPbBr 3 -SHR SCs show the quality of crystal under this growth method is excellent. X-ray photoelectron spectroscopy (XPS) measurements and Energy-dispersive X-ray spectroscopy (EDS) indicate element diffusion exists in the interface. Photoluminescence spectra (PL) and the photoelectric performance test have proved the existence and validity of the internal secondary excitation of crystals. Based on the above analysis, it was demonstrated that the inner MAPbCl 3 single-crystal enhances the optoelectronic performance of MAPbCl 3 -MAPbBr 3 crystals by the internal secondary excitation effect. [ABSTRACT FROM AUTHOR]

A flat-field correction method is proposed for multiple measured hyperspectral microscopy imaging in this paper. As the most crucial preprocessing process in quantitative microscopic analysis, flat-field correction solves the uneven illumination caused by vignetting in microscopic images, and guarantees the precision of spatial and spectral information in hyperspectral microscopic imaging. In order to carry out flat-field correction and extract uneven illumination among groups of hyperspectral microscopic data containing hundreds of bands simultaneously, two properties of vignetting have been exploited: i) low-rank property is reflected by little information contained in vignetting; ii) local smoothness can be observed as a gradual change in brightness of vignetting, which is typically equivalent to the sparseness in spatial frequency domain. Combining the two properties above, a novel Low Rank Smooth Flat-field Correction (LRSFC) model modified from common orthogonal basis extraction is proposed, while an optimization is solved based on alternating direction multiplier method (ADMM), obtaining a unique flat-field term with low-rank and smooth properties. Qualitative and quantitative experimental assessments indicate that LRSFC does not add extra cell texture to the extracted flat-field term, whose performance appears prior to other state-of-the-art flat-field correction methods. [ABSTRACT FROM AUTHOR]

In perovskite detectors that utilize SnO₂ as an electron transport layer (ETL), the preparation of SnO₂ films using the solution method results in a significant number of defects. Additionally, the presence of nano-aggregates in the aqueous solution of untreated SnO₂ colloids leads to surface unevenness in SnO₂ films prepared using the spin-coating method, which can affect the growth and crystallization of perovskite. Defects and surface unevenness in SnO₂ films affect the performance of perovskite detectors. To further optimize the performance of perovskite detectors, SnO₂ incorporating poly (ethylene glycol) bis (carboxymethyl) ether (PBE) was developed, employing the polymer as a modifier. The results of the study showed that the incorporation of PBE had two effects: 1) the ether oxygen within the PBE forms a coordination bond with SnO₂, thereby reducing oxygen vacancies, and 2) reducing nano-aggregation of SnO₂ colloidal aqueous solutions, obtaining more uniform SnO₂ films, and promoting the growth and crystallization of perovskite. Ultimately, the performance of the optimized device was improved. The external quantum efficiency (EQE) improved from 84.82 % to 89.29 %, the dark current density decreased from 3.27 × 10-⁹ A cm-² to 1.03 × 10-¹⁰ A cm-², the linear dynamic range (LDR) increased from 88.5 to 118.3 dB, and the stability was enhanced. The device maintained 64.9 % of its original efficiency after being stored for 23 days at 25 °C and 20–30 % humidity. • Improving detector performance through simple doping engineering of electron transport measurement layers. • PBE doping passivates SnO 2 defects and reduces SnO 2 film surface roughness to promote perovskite growth and crystallisation. • The device is self-powered, with a D* of up to 7.16×1013 Jones. [ABSTRACT FROM AUTHOR]

A large number of metalworking fluids in industrial manufacturing processes generate high-concentrations of oil mist pollution, which is a typical semi-volatile aerosol and is generally composed of liquid particles and volatile gas components. Long-term exposure to oil mist pollution brings a series of occupational diseases to workers. For the semi-volatile aerosol, the traditional filter sampling method will lead to particle volatilization, which underestimates the concentration of particles and overestimates the concentration of gas. Therefore, this study combined the advantages of the electrostatic method and the Tenax tube adsorption method, to develop a more accurate measurement technology. First, a dichotomous sampler that could efficiently separate the gas and liquid phases of aerosols was optimized through a numerical model, which was validated by literature results. Next, a test table for oil mist sampling was built with a sampler which was fabricated by 3D printing, and the performance of the sampler was evaluated. The results show that the sampling technique can separate the gas and particulate phases of the oil mist efficiently and accurately. Compared with the traditional single sampling methods, the new sampler can better determine the true concentration of oil mist. [ABSTRACT FROM AUTHOR]

As a new type of environmentally friendly adsorbent, biochar has been increasingly applied in water pollution treatment. Herein, a catalyzed and activated biochar adsorbent (CABC) which was derived from hazelnut shell and modified by FeCl 3 and ZnCl 2 was synthesized successfully. The CABC was applied to remove two typical Pharmaceutical and Personal Products (PPCPs), sulfamethoxazole (SMX) and diclofenac (DCF). The CABC obtained high specific surface area of 1413.02 m2/g. The removal rates for SMX and DCF by CABC could reach 97.04 % and 98.65 %, respectively. The adsorption process was consistent with the pseudo-second-order kinetic model and the Langmuir isothermal model, which illustrated that the adsorption process conformed to chemical adsorption and monolayer adsorption. The thermodynamics indicated that the adsorption process was endothermic and could occur spontaneously. After 5 cycles, the CABC still remained a high removal efficiency of 77.7 % and 80.5 % for SMX and DCF, which showed a good reusability. The removal rates of CABC for multiple PPCPs had achieved over 77.7–98.0 %. In different actual wastewater, the removal rates of CABC for SMX and DCF ranged from 56.7 % to 97 %, demonstrating its excellent universality and practical value for utilization. Furthermore, three machine learning models based on Decision Tree, Random Forest and Gradient Boosting Decision Tree algorithm were applied to predict the removal efficiency and determine the relative importance of different influencing factors. The gradient boosting regressor model obtained the best predict performance with R 2 at 0.9806 and 0.9840 for training set and testing set. And the importance analysis had shown that pH was the most important influencing factor with the importance value over 0.35. The adsorption mechanism between CABC and pollutants included pore adsorption, electrostatic interactions, intramolecular hydrogen bonding, the reaction with oxygen-containing functional groups and metal complexation. The prepared biochar adsorbent CABC possessed the potential for PPCPs removing. In addition, the machine learning method can play more and more undeniable role in subsequent water treatment. In future research, machine learning can be used to predict the adsorption performance of materials, enabling targeted design of materials. This will greatly save experimental time and cost losses, and can improve research efficiency. [Display omitted] ● Waste hazelnut shells were transformed into eco-friendly biochar for water treatment. ● The novel biochar effectively removed SMX, DCF and multiple PPCPs. ● Machine learning was used to model and predict the adsorption process. ● The biochar adsorbent exhibited high reusability, low cost in water treatment. [ABSTRACT FROM AUTHOR]

As a new type of environmentally friendly adsorbent, biochar has been increasingly applied in water pollution treatment. Herein, a catalyzed and activated biochar adsorbent (CABC) which was derived from hazelnut shell and modified by FeCl 3 and ZnCl 2 was synthesized successfully. The CABC was applied to remove two typical Pharmaceutical and Personal Products (PPCPs), sulfamethoxazole (SMX) and diclofenac (DCF). The CABC obtained high specific surface area of 1413.02 m2/g. The removal rates for SMX and DCF by CABC could reach 97.04 % and 98.65 %, respectively. The adsorption process was consistent with the pseudo-second-order kinetic model and the Langmuir isothermal model, which illustrated that the adsorption process conformed to chemical adsorption and monolayer adsorption. The thermodynamics indicated that the adsorption process was endothermic and could occur spontaneously. After 5 cycles, the CABC still remained a high removal efficiency of 77.7 % and 80.5 % for SMX and DCF, which showed a good reusability. The removal rates of CABC for multiple PPCPs had achieved over 77.7–98.0 %. In different actual wastewater, the removal rates of CABC for SMX and DCF ranged from 56.7 % to 97 %, demonstrating its excellent universality and practical value for utilization. Furthermore, three machine learning models based on Decision Tree, Random Forest and Gradient Boosting Decision Tree algorithm were applied to predict the removal efficiency and determine the relative importance of different influencing factors. The gradient boosting regressor model obtained the best predict performance with R 2 at 0.9806 and 0.9840 for training set and testing set. And the importance analysis had shown that pH was the most important influencing factor with the importance value over 0.35. The adsorption mechanism between CABC and pollutants included pore adsorption, electrostatic interactions, intramolecular hydrogen bonding, the reaction with oxygen-containing functional groups and metal complexation. The prepared biochar adsorbent CABC possessed the potential for PPCPs removing. In addition, the machine learning method can play more and more undeniable role in subsequent water treatment. In future research, machine learning can be used to predict the adsorption performance of materials, enabling targeted design of materials. This will greatly save experimental time and cost losses, and can improve research efficiency. [Display omitted] ● Waste hazelnut shells were transformed into eco-friendly biochar for water treatment. ● The novel biochar effectively removed SMX, DCF and multiple PPCPs. ● Machine learning was used to model and predict the adsorption process. ● The biochar adsorbent exhibited high reusability, low cost in water treatment. [ABSTRACT FROM AUTHOR]

[Display omitted] • Endo-hydrolytic activity of free dextranase is transformed to exo -hydrolytic after covalent immobilization. • Noncovalent immobilization of dextranase maintains its endo -hydrolysis behavior. • Matching target products generation and separation efficiency can control product molecular weight and mitigate fouling. • A desirable enzyme membrane reactor requires highly active enzyme, strong internal mass transfer and high permselective membrane. • Immobilization is not necessary in enzyme membrane reactor if enzyme has good shear resistance and acceptable stability. Enzyme membrane reactor (EMR) provides an effective strategy for controlling molecular weight (Mw) of oligodextrans. However, the synergistic effect between dextran hydrolysis and product separation as well as continuous operation stability remains still unclear. We observed that covalently immobilized dextranase exhibited more obvious exo -hydrolysis behavior compared to free enzymes probably due to enzyme conformational alterations. Using non-covalently immobilized enzyme, suitable ultrafiltration membrane, optimal substrate/enzyme ratio and matched permeate flux, the yield of the target product reached 62.8%. However, the non-covalently immobilized dextranase exhibited reduced hydrolytic activity and more obvious membrane fouling (caused by high-Mw dextran). When free dextranase with high activity was used together with suitable permeate flux and high shear rate, the yield increased to 72.0%. The obtained EMR maintained stable for 8 h with slight fouling formation because enzymatic hydrolysis and membrane separation were well matched. The polydispersity index of the target product reached 1.3 (analytical grade) following diafiltration purification. [ABSTRACT FROM AUTHOR]

Whole Slide Imaging and Hyperspectral Microscopic Imaging provide great quality data with high spatial and spectral resolution for histopathology. Existing Hyperspectral Whole Slide Imaging systems combine the advantages of the techniques above, thus providing rich information for pathological diagnosis. However, it cannot avoid the problems of slow acquisition speed and mass data storage demand. Inspired by the spectral reconstruction task in computer vision and remote sensing, the Swin-Spectral Transformer U-Net (SSTU) has been developed to reconstruct Hyperspectral Whole Slide images (HWSis) from multiple Hyperspectral Microscopic images (HMis) of small Field of View and Whole Slide images (WSis). The Swin-Spectral Transformer (SST) module in SSTU takes full advantage of Transformer in extracting global attention. Firstly, Swin Transformer is exploited in space domain, which overcomes the high computation cost in Vision Transformer structures, while it maintains the spatial features extracted from WSis. Furthermore, Spectral Transformer is exploited to collect the long-range spectral features in HMis. Combined with the multi-scale encoder-bottleneck-decoder structure of U-Net, SSTU network is formed by sequential and symmetric residual connections of SSTs, which reconstructs a selected area of HWSi from coarse to fine. Qualitative and quantitative experiments prove the performance of SSTU in HWSi reconstruction task superior to other state-of-the-art spectral reconstruction methods. • Hyperspectral Whole Slide Imaging Reconstruction network trained by WSIs and Hyperspectral images within small FOVs. • HWSI Reconstruction within new collected WSI and trained SSTU network. • Spectral and Swin Transformer based U-Net structure. • Solving the collection speed and storage space restriction of real HWSI systems. [ABSTRACT FROM AUTHOR]

Thermosensitive genic male sterile (TGMS) wheat lines are the core of two-line hybrid systems. Understanding the mechanism that regulates male sterility in TGMS wheat lines is helpful for promoting wheat breeding. Several studies have obtained information regarding the mechanisms associated with male sterility at the transcriptional level, but it is not clear how the post-transcriptional process of alternative splicing might contribute to controlling male sterility. In this study, we performed genome-wide analyses of alternative splicing during the meiosis stage in TGMS line BS366 using PacBio and RNA-Seq hybrid sequencing. Cytological observations indicated that cytoskeleton assembly in pollen cells, calcium deposition in pollen and tapetal cells, and vesicle transport in tapetal cells were deficient in BS366. According to our cytological findings, 49 differentially spliced genes were isolated. Moreover, 25 long non-coding RNA targets and three bHLH transcription factors were identified. Weighted gene co-expression network analysis detected four candidate differentially spliced genes that had strong co-relation with the seed setting percentage, which is the direct representation of male sterility in BS366. In this study, we obtained comprehensive data regarding the alternative splicing-mediated regulation of male sterility in TGMS wheat. The candidates identified may provide the molecular basis for an improved understanding of male sterility. [ABSTRACT FROM AUTHOR]

In monocarpic plants, stem cells are fated to die. However, the potential mechanism of stem cell death has remained elusive. Here, we reveal that the levels of two forms of reactive oxygen species (ROS), superoxide anion free radical ( O 2 · − ) and hydrogen peroxide (H2O2), show dynamic changes in the shoot apex during the plant life cycle of Arabidopsis thaliana. We found that the level of O 2 · − decreased and disappeared at four weeks after bolting (WAB), while H2O2 appeared at 3 WAB and showed a burst at 5 WAB. The timing of dynamic changes in O 2 · − and H2O2 was delayed for approximately three weeks in clv3-2, which has a longer lifespan. Moreover, exogenous application of H2O2 inhibited the expression of the stem cell determinant WUSCHEL (WUS) and promoted the expression of the developmentally programmed cell death (dPCD) marker gene ORESARA 1 (ORE1). These results indicate that H2O2 triggers an important signal inducing dPCD in stem cells. Given that O 2 · − plays roles in maintaining WUS expression and stem cell activity, we speculate that the dynamic shift from O 2 · − to H2O2 in the shoot apex results in stem cell death. Our findings provide novel insights for understanding ROS-mediated regulation during plant stem cell death. [ABSTRACT FROM AUTHOR]

Drug-induced liver injury (DILI) is the major cause of clinical trial failure and postmarketing withdrawals of approved drugs. It is very expensive and time-consuming to evaluate hepatotoxicity using animal or cell-based experiments in the early stage of drug development. In this study, an in silico model based on the joint decision-making strategy was developed for DILI assessment using a relatively large dataset of 2608 compounds. Five consensus models were developed with PaDEL descriptors and PubChem, Substructure, Estate, and Klekota–Roth fingerprints, respectively. Submodels for each consensus model were obtained through joint optimization. The parameters and features of each submodel were optimized jointly based on the hybrid quantum particle swarm optimization (HQPSO) algorithm. The application domain (AD) based on the frequency-weighted and distance (FWD)-based method and Tanimoto similarity index showed the wide AD of the qualified consensus models. A joint decision-making model was integrated by the qualified consensus models, and the overwhelming majority principle was used to improve the performance of consensus models. The application scope narrowing caused by the overwhelming majority principle was successfully solved by joint decision-making. The proposed model successfully predicted 99.2% of the compounds in the test set, with an accuracy of 80.0%, a sensitivity of 83.9, and a specificity of 73.3%. For an external validation set containing 390 compounds collected from DILIrank, 98.2% of the compounds were successfully predicted with an accuracy of 79.9%, a sensitivity of 97.1%, and a specificity of 66.0%. Furthermore, 25 privileged substructures responsible for DILI were identified from Substructure, PubChem, and Klekota–Roth fingerprints. These privileged substructures can be regarded as structural alerts in hepatotoxicity evaluation. Compared with the main published studies, our method exhibits certain advantage in data size, transparency, and standardization of the modeling process and accuracy and credibility of prediction results. It is a promising tool for virtual screening in the early stage of drug development. [ABSTRACT FROM AUTHOR]

NiFe2O4‐based ceramic inert anodes for aluminum electrolysis doped with various TiN nanoparticles were prepared by a two‐step cold‐pressing sintering process to investigate how TiN affected the sintering behavior and properties of the composites. The differential scanning calorimetry‐thermogravimetry (DSC‐TG), X‐ray diffraction (XRD), and microstructure analysis results indicated that the Ti and N were evenly distributed in the NiFe2O4 matrix to form a solid solution. The maximum linear shrinkage and linear shrinkage rate were enhanced with the increase of TiN nanoparticles contents, and the sintering activation energy of initial stage was lowered from 382.63 to 279.58 kJ mol−1 with the TiN nanoparticles additive range from 0 to 9 wt%. When the content of TiN nanoparticles was 7 wt%, the relative density, bending strength, and elastic modulus reached their maximum values of 97.24%, 73.88 MPa, and 3.77 GPa, respectively, whereas the minimum static corrosion rate of NiFe2O4‐based ceramic of 0.00114 g cm−2 h−1 was obtained, mainly attributed to the relatively dense and stable microstructure. The electrical conductivity of NiFe2O4‐based ceramics presented a clear ascending trend with increasing TiN nanoparticles content and elevated temperature, attributed to the increased concentration and migration rate of carrier. [ABSTRACT FROM AUTHOR]

Doping dopants are one of the most effective methods which can improve crystallinity, reduce traps, adjust bandgap width of perovskite films and obtain efficient perovskite photodetectors. Chlorine-based dopants have been reported in many literatures, yet their role still remains a mystery. In our study, a typical solution-processed organic–inorganic hybrid perovskite material CH3NH3PbI3 (MAPbI3) was synthesized as the absorption layer for photodetectors and methylammonium chloride (MACl) was selected as dopant. By tuning the incorporation ratios of MACl in the MAPbI3 precursor solutions, bandgap width and trap densities of the MAPbI3 films can be effectively reduced. The crystallinity and morphology of perovskite films were obviously improved, and the photoelectric properties of photodetectors were further enhanced. Ultimately, the optimal device was obtained when the incorporation ratio of MACl reached 1.0 wt%. External quantum efficiency (EQE) of the optimal device exhibited up to 81%, nearly 30% higher than EQE of the device without incorporation. A lower dark current density (Jd) of 8.4 × 10–8 A cm−2 at − 0.1 V bias was obtained because of low trap densities, moreover, due to the suppressed Jd, the optimal device operating at room temperature showed a specific detectivity (D*) of 2.71 × 1012 Jones and a linear dynamic range (LDR) of 104 dB, higher than the D* of 7.03 × 1011 Jones and the LDR of 91 dB of the device without incorporation, respectively. [ABSTRACT FROM AUTHOR]

Guided by the conviction that "Clear waters and green mountains are as good as mountains of gold and silver", China highly values sustainable economic and social development through innovation and Internet technology. Regression analysis is performed to examine the impact of corporate information disclosure environment proxied by the Internet penetration rate on innovation. Leveraging from the city-level Internet penetration rates data in China from 2003 to 2017, this study gets the following findings: (1) Firms headquartered in cities with high Internet penetration rates tend to be more innovative, i.e. they invest more in research and development. (2) This result is supported by several robustness checks, such as alternative measures of key variables, alternative empirical specifications, and tests to mitigate identification concerns. (3) "financing constraint" and "tolerance of innovation failure" are two channels that influence firms' innovative endeavors. (4) Additional tests show that Internet penetration rates facilitate a firm's output efficiency of innovation input, total factor productivity, and human capital environment for innovation. The above conclusions not only enrich the relevant literature on the influencing factors of corporate innovation from the perspective of the firm information disclosure environment but also provide an important reference for further understanding the positive role of macro technology development on social and economic development. [ABSTRACT FROM AUTHOR]

Purpose: To assess the efficacy and side effects of Traditional Chinese Medicine (TCM) in the management of triple negative breast cancer (TNBC). Methods: Full text data on randomized controlled trial (RCT) of TNBC treated with TCM or its combination with Western Medicine (WM) were retrieved from the Chinese biomedical literature database, Chinese periodicals, Chinese Science-Technology periodicals and VP and PubMed. The qualities of the RCTs were evaluated. Revman 5.3 was used to conduct the meta-analysis. Results: A total of 16 RCTs involving 1186 patients were included. Analysis of these RCTs showed significant differences in total effectiveness between WM and TCM or combination of TCM with WM {(OR = 2.63, 95 % CI = 1.37, 5.03), test of the combined effect (Z = 2.91, p ˂ 0.005)}. Conclusion: The results show that TCM is effective in the treatment TNBC. [ABSTRACT FROM AUTHOR]

In the field of robotic automation, achieving high position accuracy in robotic vision systems (RVSs) is a pivotal challenge that directly impacts the efficiency and effectiveness of industrial applications. This study introduces a comprehensive modeling approach that integrates kinematic and joint compliance factors to significantly enhance the position accuracy of a system. In the first place, we develop a unified kinematic model that effectively reduces the complexity and error accumulation associated with the calibration of robotic systems. At the heart of our approach is the formulation of a joint compliance model that meticulously accounts for the intricacies of the joint connector, the external load, and the self-weight of robotic links. By employing a novel 3D rotary laser sensor for precise error measurement and model calibration, our method offers a streamlined and efficient solution for the accurate integration of vision systems into robotic operations. The efficacy of our proposed models is validated through experiments conducted on a FANUC LR Mate 200iD robot, showcasing notable improvements in the position accuracy of robotic vision system. Our findings contribute a framework for the calibration and error compensation of RVS, holding significant potential for advancements in automated tasks requiring high precision. [ABSTRACT FROM AUTHOR]

Nonribosomal peptide synthetases (NRPSs) are multi-modular enzymes involved in the biosynthesis of natural products. Bacillamide C was synthesized by Bacillus atrophaeus C89. A nonribosomal peptide synthetase (NRPS) cluster found in the genome of B. atrophaeus C89 was hypothesized to be responsible for the biosynthesis of bacillamide C using alanine and cysteine as substrates. Here, the structure analysis of adenylation domains based on homologous proteins with known crystal structures indicated locations of the substrate-binding pockets. Molecular docking suggested alanine and cysteine as the potential substrates for the two adenylation domains in the NRPS cluster. Furthermore, biochemical characterization of the purified recombinant adenylation domains proved that alanine and cysteine were the optimum substrates for the two adenylation domains. The results provided the in vitro evidence for the hypothesis that the two adenylation domains in the NRPS of B. atrophaeus C89 preferentially select alanine and cysteine, respectively, as a substrate to synthesize bacillamide C. Furthermore, this study on substrates selectivity of adenylation domains provided basis for rational design of bacillamide analogs. [ABSTRACT FROM AUTHOR]

A ternary composite of Fe 3 O 4 /SnO 2 /rGO has been synthesized via a facile one-step hydrothermal method. In the composite, rGO serves as a conductive and robust matrix, Fe 3 O 4 and SnO 2 nanoparticles are uniformly loaded on the rGO nanosheets without aggregation, due to the space-confine effect of the simultaneous nucleation and growth of Fe 3 O 4 and SnO 2 nanocrystallites. As an anode material for lithium-ion batteries, the Fe 3 O 4 /SnO 2 /rGO nanocomposite exhibited a reversible capacity of 947 mAh g −1 at a current density of 200 mA g −1 in the first cycle, and maintained 831 mAh g −1 after 200 cycles. The cyclic performance and rate capability of the Fe 3 O 4 /SnO 2 /rGO are markedly improved compared with the binary counterparts of FeO x /rGO and SnO x /rGO obtained in the control experiment, as a result of enhanced structural stability and kinetics for charge and Li + transfer due to the synergetic effect in the ternary composite. [ABSTRACT FROM AUTHOR]

Metabolism refers to a series of orderly chemical reactions used to maintain life activities in organisms. In healthy individuals, metabolism remains within a normal range. However, specific diseases can lead to abnormalities in the levels of certain metabolites, causing them to either increase or decrease. Detecting these deviations in metabolite levels can aid in diagnosing a disease. Traditional biological experiments often rely on a lot of manpower to do repeated experiments, which is time consuming and labor intensive. To address this issue, we develop a deep learning model based on the auto-encoder and non-negative matrix factorization named as MDA-AENMF to predict the potential associations between metabolites and diseases. We integrate a variety of similarity networks and then acquire the characteristics of both metabolites and diseases through three specific modules. First, we get the disease characteristics from the five-layer auto-encoder module. Later, in the non-negative matrix factorization module, we extract both the metabolite and disease characteristics. Furthermore, the graph attention auto-encoder module helps us obtain metabolite characteristics. After obtaining the features from three modules, these characteristics are merged into a single, comprehensive feature vector for each metabolite–disease pair. Finally, we send the corresponding feature vector and label to the multi-layer perceptron for training. The experiment demonstrates our area under the receiver operating characteristic curve of 0.975 and area under the precision–recall curve of 0.973 in 5-fold cross-validation, which are superior to those of existing state-of-the-art predictive methods. Through case studies, most of the new associations obtained by MDA-AENMF have been verified, further highlighting the reliability of MDA-AENMF in predicting the potential relationships between metabolites and diseases. [ABSTRACT FROM AUTHOR]

Ambient particulate matter less than 2.5 μm (PM 2.5) and humidity have been considered as two leading determinants of atmospheric visibility. However, quantitative evidence of their independent and interactive effects on visibility is rare at multi-city level. Based on the data of 190 monitoring stations from 182 Chinese cities, the generalized linear model combined with nonlinear smoother was constructed to estimate the station-specific effects of PM 2.5 and relative humidity on visibility. Then, multivariate meta-analysis was used to pool the station-specific estimates. Finally, attributable visibility loss respectively due to PM 2.5 and humidity were calculated. In general, both PM 2.5 and relative humidity were detected to have a significant non-linear negative influence on visibility. Per 1 μg/m3 increase in PM 2.5 was associated with a visibility reduction of 0.232 km and 0.030 km under the level of PM 2.5 below or above 68 μg/m3, respectively. The visibility declined by 0.105 km, 0.254 km, and 0.569 km per 1% increase in relative humidity under low (<58%), middle (58%–85%), and high (>85%) humidity, respectively. Significant interactive effects of PM 2.5 and humidity were observed. The impacts of PM 2.5 on visibility were significantly amplified in days with moderate humidity. However, extremely high humidity could largely attenuate the PM 2.5 -visibility association. The influence of extremely high humidity (like 99%) also consistently declined as the PM 2.5 concentration elevated. From the national perspective, PM 2.5 accounted for a higher proportion of average daily visibility loss than humidity [9.75 km (95%CI: 7.94, 11.57) vs. 7.23 km (95%CI: 5.02, 9.45)]. The relatively mild polluted southern China suffered from similar PM 2.5 -attributable visibility loss with northern China. The findings could provide important information for the prediction and improvement of atmospheric visibility. [Display omitted] • Both PM 2.5 and relative humidity had a negative non-linear effect on visibility. • Humidity between 60 and 80% significantly amplified the impact of PM 2.5 on visibility. • PM 2.5 substantially attenuated the effect of extremely high humidity on visibility. • Daily average visibility loss of 10 km and 7 km were attributed to PM 2.5 and humidity. • Visibility in less polluted but more humid areas also suffered greatly from PM 2.5. [ABSTRACT FROM AUTHOR]

Fe 2 O 3 wrapped by few layered graphene nanosheets composites (Fe 2 O 3 -FLG) have been synthesized via a facile and massive one-step P-milling method, which is effective in reducing the particle size of Fe 2 O 3 and exfoliating the graphite into FLG. The composite shows good electrochemical performance due to the tight wrapping of FLG nanosheets, which is beneficial to electric conductivity and integrity of the electrode. The sample treated under 20 h retains a reversible capacity of 758 mAh g −1 at 200 mA g −1 after 300 cycles, which equals to 88% of its theoretic capacity. With the superior electrochemical performance, Fe 2 O 3 -FLG composites prepared via the P-milling method could be promising as anode materials for high performance lithium-ion batteries. [ABSTRACT FROM AUTHOR]

• This work uses a doped method to develop a low-cost PDs hole transport material with high hole mobility and stability. • The CsI:TBP complex inhibited the agglomeration of Li-TFSI in Spiro-OMeTAD to form HTL with smooth and dense surfaces. • The photodetector exhibits a broadband response from near-ultraviolet to near-infrared, fast response and low dark current. • The EQE, responsivity and detectability of the photodetector are 88%, 0.48 A W−1, and 2.7 × 1013 Jones, respectively. • The EQE of the unpackaged device remained at 98.1% of the initial value after 60 days of storage. Hole transport materials play an essential role in the performance of perovskite detectors (PDs). Therefore, hole transport materials with excellent performance can significantly promote photoinduced holes' extraction rate and mobility. Spiro-OMeTAD, a small organic molecular material, has high solubility and excellent film-forming properties and is ideal for the hole transport layer (HTL) of photodetectors. In this work, a small amount of CsI is introduced into Spiro-OMeTAD together with Li-TFSI and TBP as additives. It is found that CsI and TBP formed a complex, which inhibited the agglomeration of Li-TFSI in Spiro-OMeTAD, thus preventing the rapid evaporation of TBP from leaving some cracks Spiro-OMeTAD. The photodetectors exhibit broadband response from near-ultraviolet to near-infrared (300–800 nm), achieving fast response (rise/fall time is 54.1/10.7 μs) and low dark current density (9.72 ×10−10 A cm−2). The detector can be self-powered at zero bias voltage, the external quantum efficiency (EQE) is 88%, the Responsivity (R) is 0.48 A W−1, and the detectivity (D*) is close to 2.7 × 1013 Jones. When the photovoltaic detector is placed in a nitrogen-filled glove box without special packaging for more than two months, the EQE remains 98.1% of the original. This study provides a simple method for fabricating a large area of high-performance planar PDs. [ABSTRACT FROM AUTHOR]

Observational studies have provided evidence of a correlation between alterations in gut microbiota composition and infertility. However, concrete proof supporting the causal relationship is still lacking. We performed a Mendelian randomization study to assess whether genetically gut microbiota composition influences the risk of infertility. The genetic data pertaining to gut microbiota were obtained from a genome-wide association study meta-analysis, which was conducted among 24 cohorts (18,340 participants) from the international MiBioGen consortium. By the primary method of assessing causality, we have identified 2 family taxa, 2 genus taxa, and 1 order taxa that were linked to a low risk of male infertility, while 1 genus taxa were associated with a high risk of male infertility. Furthermore, we have discovered 6 genus taxa, 1 phylum taxa, 1 class taxa, 1 order taxa, and 1 family taxa that were associated with a low risk of female infertility, while 1 genus taxa were linked to a high risk of female infertility. This study successfully confirmed that there was a causal link between gut microbiota and infertility. The identification of these specific strains through genetic prediction offers a valuable insight for early diagnosis, prevention, and treatment of infertility. [ABSTRACT FROM AUTHOR]

Most patients diagnosed with chronic obstructive pulmonary disease (COPD) present with hallmark features of airway mucus hypersecretion, including cough and expectoration. Airway mucus function as a native immune system of the lung that severs to trap particulate matter and pathogens and allows them to clear from the lung via cough and ciliary transport. Chronic mucus hypersecretion (CMH) is the main factor contributing to the increased risk of morbidity and mortality in specific subsets of COPD patients. It is, therefore, primarily important to develop medications that suppress mucus hypersecretions in these patients. Although there have been some advances in COPD treatment, more work remains to be done to better understand the mechanism underlying airway mucus hypersecretion and seek more effective treatments. This review article discusses the structure and significance of mucus in the lungs focusing on gel-forming mucins and the impacts of CMH in the lungs. Furthermore, we summarize the article with pharmacological and nonpharmacological treatments as well as novel and interventional procedures to control CMH in COPD patients. [ABSTRACT FROM AUTHOR]

Background: Patients with hypertrophic scarring tend to experience recurrence after treatment, which often occurs in areas of the body with high skin tension. Aims: To evaluate better treatments aimed at reducing the risk of scar recurrence in areas of high skin tension. Methods: Patients were randomly divided into the following three treatment groups: botulinum toxin type A (BTA) via dual‐plane micro‐drop injections, triamcinolone acetonide (TAC) suspension, and CO2 via fractional CO2 laser. Interventions were implemented in all three groups once a month for three consecutive sessions. After the final treatment, scarring was evaluated at 1, 3, 6, 12, and 24 months using the Patient and Observer Scar Assessment Scale (POSAS). Results: The 3‐month POSAS score for each scar indicator in the treatment groups was significantly lower than that in the preoperative groups (p < 0.001). The scar score in the TAC group decreased at 3 months and increased thereafter. For other groups, the scar score continually decreased at all time points according to the Patient Scar Assessment Scale. Based on the Observer Scar Assessment Scale, the scar score continuously decreased at all time points in the BTA group; in the TAC group, it decreased at 1 month and increased thereafter; and in the CO2 group, the scar score decreased at 3 months and subsequently stabilized. Conclusions: All three treatment methods were effective. However, the BTA group experienced a reduced risk of scar recurrence and maintained long‐term treatment effects. [ABSTRACT FROM AUTHOR]

Hyperspectral (HS) satellite data have been widely applied in many fields due to its numerous bands. Along with the advantages of high spectral resolution, HS satellite data are still limited by some disadvantages of high acquisition cost, low revisiting capability, and low spatial resolution. Compared with HS satellites, multispectral (MS) satellites have a large number, large width, strong coverage, and high spatial resolution. Therefore, MS data can be used as the input to the spectral reconstruction (SR) to obtain HS data with high temporal resolution. Better HS data can be obtained by spectral reconstructing with these continuous multitemporal data than with single-temporal data. A multitemporal spectral reconstruction network (MTSRN) is proposed in this article, which is used to reconstruct HS images from multitemporal MS images. The proposed MTSRN comprises multiple single-temporal spectral reconstruction networks (STSRN) for extracting temporal features and a multitemporal fusion network (MTFN). The parallel component alternative (PA) post-processing method enhances the physical plausibility of reconstructed HS data. To demonstrate performance of the proposed method in aspects of multitemporal reconstruction, experiments are conducted on four multitemporal HS and MS satellite datasets. The experimental results prove that the proposed MTSRN obtains better SR results compared with the SR method based on single-temporal information. [ABSTRACT FROM AUTHOR]

Simple Summary: Liver receptor homolog-1 (LRH-1) is highly observed in tissues with secretory function, such as the ovaries, suggesting that LRH-1 may play an essential role in the ovarian endocrine. In particular, ovarian granulosa cells (GCs) are the functional cells that produce steroid hormones. The fate of GCs directly affects follicular development or atresia. These effects were lost in granulosa-specific LRH-1-knockout mice, showing that LRH-1 is a central modulator of ovarian function. However, the underlying mechanism LRH-1 in the bovine ovaries remains unclear. We aimed to detect the effect of LRH-1 on steroid hormones in bovine GCs and explore the potential relationship between LRH-1 and the fate of GCs. The results show that LRH-1 was specifically highly expressed in GCs of atretic follicles. Mechanistically, LRH-1 induced the apoptosis of bovine GCs by the progestogen receptor signaling pathway. While this finding provided new ideas for the study of follicular atresia, it also provided a theoretical basis for the clinical diagnosis and treatment for infertility in cow. The purpose of the present investigation was to assess the function of LRH-1 on GCs and the mechanisms involved. Here, LRH- was highly expressed in the bovine GCs of atretic follicles. Treatment with 50 μM of LRH-1 agonist (DLPC) significantly induced the expression of LRH-1 (p < 0.05). In particular, LRH-1 activation blocked the progestogen receptor signaling pathway via downregulating progesterone production and progestogen receptor levels (p < 0.05), but had no effect on 17 beta-estradiol synthesis. Meanwhile, LRH-1 activation promoted the apoptosis of GCs and increased the activity of caspase 3 (p < 0.05). Importantly, upregulating the progestogen receptor signaling pathway with progestogen could attenuate the LRH-1-induced proapoptotic effect. Moreover, treatment with progestogen decreased the activity of the proapoptotic gene caspase 3 and increased the expression of antiapoptotic gene Bcl2 in LRH-1 activated GCs (p < 0.05). Taken together, these results demonstrate that LRH-1 might be dependent on the progestogen receptor signaling pathway to modulate bovine follicular atresia. [ABSTRACT FROM AUTHOR]

Soft sensing technology has been proved to be an effective tool for the online estimation of unmeasured or variables that are difficult to directly measure. The performance of a soft sensor depends heavily on its convergence speed and generalization ability to a great extent. Based on this idea, we propose a new soft sensor model, Isomap-SVR. First, the sample data set is divided into training set and testing set by using self-organizing map (SOM) neural network to ensure the fairness and symmetry of data segmentation. Isometric feature mapping (Isomap) method is used for dimensionality reduction of the model input data, which could not only reduce the structure complexity of the proposed model but speed up learning speed, and then the Support Vector Machine Regression (SVR) is applied to the regression model. A novel bat algorithm based on Cauchy mutation and Lévy flight strategy is used to optimize parameters of Isomap and SVR to improve the accuracy of the proposed model. Finally, the model is applied to the prediction of the temperature of rotary kiln calcination zone, which is difficult to measure directly. The simulation results show that the proposed soft sensor modeling method has higher learning speed and better generalization ability. Compared with other algorithms, this algorithm has obvious advantages and is an effective modeling method. [ABSTRACT FROM AUTHOR]

In the realm of photodetection, there has been growing interest in Ferroelectric/semiconductors heterostructures due to the interfacial charge coupling resulting from ferroelectric polarization. In this study, we created a thin film consisting of alternating layers of Ba 0.86 Ca 0.14 Ti 0.9 Sn 0.1 O 3 and PbZr 0.52 Ti 0.48 O 3 (referred to as BCST/PZT) using a sol-gel growth method on a (0001) GaN/c-sapphire template. Our objective was to examine the impact of these films on the optoelectronic properties of ferroelectric/GaN heterojunctions. Our findings indicate that the BCST/PZT multilayer films possess improved ferroelectric properties. Furthermore, the multilayer structure demonstrates outstanding optoelectronic performance compared to the individual BCST/GaN or PZT/GaN structures, particularly within the 1 V to 3 V bias range. Notably, the multilayer thin film/GaN devices exhibit a responsivity of 121.4 mA/W and a detectivity of 1.44 × 1011 Jones under a 1 V bias voltage. In contrast to other GaN-based materials documented in the literature, our straightforward sol-gel techniques yielded devices exhibiting UV photodetection characteristics that are either comparable to or superior than those reported. • Use the sol-gel method, which is simple and easy to produce large films. • Use of tin and calcium doped barium titanate. • Multilayer BCST/PZT ferroelectric film photodetectors (PDs) have better responsivity (R) and detectivity (D*). • The device shows a significant improvement in photocurrent with 1 V bias applied. [ABSTRACT FROM AUTHOR]

High light intensity as one of the stresses could lead to generation of large amounts of reactive oxygen species (ROS) in plants, resulting in severe plant growth retardation. The photorespiration metabolism plays an important role in producing and removing a variety of ROS, maintaining the dynamic balance of the redox reaction, and preventing photoinhibition. Arabidopsis hydroxypyruvate reductase 1 (HPR1) is a primary metabolic enzyme in the photorespiration cycle. However, the role of HPR1 in plants response to high light is not clear. Here, we found that the expression of HPR1 could be induced by high light intensity. The growth and photosynthetic capacity of hpr1 mutants are seriously affected under high light intensity. The absence of HPR1 suppresses the rates of photorepair of Photosystem II (PSII), aggravates the production of ROS, and accelerates photorespiration rates. Moreover, the activity of ROS scavenging enzymes in the hpr1 mutants is significantly higher. These results indicate that HPR1 is involved in plant response to high light intensity and is essential for maintaining the dynamic balance of ROS and photorespiration. [ABSTRACT FROM AUTHOR]

This study explores the role of SIRT2 in regulating autophagy and its interaction with AMPK in the context of acute liver failure (ALF). This study investigated the effects of SIRT2 and AMPK on autophagy in ALF mice and TAA-induced AML12 cells. The results revealed that the liver tissue in ALF model group had a lot of inflammatory cell infiltration and hepatocytes necrosis, which were reduced by SIRT2 inhibitor AGK2. In comparison to normal group, the level of SIRT2, P62, MDA, TOS in TAA group were significantly increased, which were decreased in AGK2 treatment. Compared with normal group, the expression of P-PRKAA1, Becilin1 and LC3B-II was decreased in TAA group. However, AGK2 enhanced the expression of P-PRKAA1, Becilin1 and LC3B-II in model group. Overexpression of SIRT2 in AML12 cell resulted in decreased P-PRKAA1, Becilin1 and LC3B-II level, enhanced the level of SIRT2, P62, MDA, TOS. Overexpression of PRKAA1 in AML12 cell resulted in decreased SIRT2, TOS and MDA level and triggered more autophagy. In conclusion, the data suggested the link between AMPK and SIRT2, and reveals the important role of AMPK and SIRT2 in autophagy on acute liver failure. [ABSTRACT FROM AUTHOR]

Background: Photosystem II (PSII) is a highly conserved integral-membrane multi-subunit pigment-protein complex. The proteins, pigments, lipids, and ions in PSII need to be assembled precisely to ensure a proper PSII biogenesis. D1 is the main subunit of PSII core reaction center (RC), and is usually synthesized as a precursor D1. D1 maturation by the C-terminal processing protease CtpA is essential for PSII assembly. However, the detailed mechanism about how D1 maturation affects PSII assembly is not clearly elucidated so far. In this study, Arabidopsis thaliana CtpA mutant (atctpa: SALK_056011), which lacks the D1 mature process, was used to investigate the function of this process on PSII assembly in more details. Results: Without the C-terminal processing of precursor D1, PSII assembly, including PSII monomer, dimer, especially PSII supercomplexes (PSII SCs), was largely compromised as reported previously. Western blotting following the BN-2D-SDS PAGE revealed that although the assembly of PSII core proteins D2, CP43 and CP47 was affected by the loss of D1 mature process, the incorporation of CP43 was affected the most, indicated by its most reduced assembly efficiency into PSII SCs. Furthermore, the slower growth of yeast cells which were co-transformed with pD1 and CP43, when compared with the ones co-transformed with mature D1 and CP43, approved the existence of D1 C-terminal tail hindered the interaction efficiency between D1 and CP43, indicating the physiological importance of D1 mature process on the PSII assembly and the healthy growth of the organisms. Conclusions: The knockout Arabidopsis atctpa mutant is a good material to study the unexpected link between D1 maturation and PSII SCs assembly. The loss of D1 maturation mainly affects the incorporation of PSII core protein CP43, an inner antenna binding protein, which functions in the association of LHCII complexes to PSII dimers during the formation of PSII SCs. Our findings here provide detailed supports of the role of D1 maturation during PSII SCs assembly in higher plants. [ABSTRACT FROM AUTHOR]

Highlights • Two modules of nonribosomal peptide synthetase were heterologous expressed and purified. • In vitro set up a biosynthetic reaction system of nonribosomal peptide. • Bacillamide C intermediate- heterocyclic AlaCys thiazole was formed. Abstract Bacillamide C, a potential natural antialgae active compound, is produced by Bacillus atrophaeus C89 derived from marine sponge Dysidea avara. A nonribosomal peptide synthetase (NRPS) cluster is hypothesized to be involved in the biosynthesis of bacillamide C. The NRPS with a domain string of A1-PCP1-Cy-A2-PCP2-C can be divided into three functional modules. After heterologous expression and purification of module A1-PCP1 and module Cy-A2-PCP2, their catalytic activities were biochemically proven in vitro by the reaction with the apo-PCP domain transformed to the holo-PCP domain through a phosphopantetheinyl transferase, ATP, and substrate amino acids. Five– membered heterocyclic AlaCys thiazole with molecular weight of 172.0389 was detected. This proved the formation of the heterocyclic dipeptide AlaCys thiazole , which is considered to be a building block for the biosynthesis of bacillamide. This study provides a basis for further biosynthesis of bacillamides. [ABSTRACT FROM AUTHOR]

Plant–plant interactions play a key role in the function and structure of communities. The combined effect of drought stress and grazing disturbance on shaping plant–plant interactions is still poorly understood, while this combination is common in semiarid ecosystems. Four species including Stipa grandis, which is dominant in the typical steppe, and Stipa krylovii, Artemisia frigida, and Cleistogenes squarrosa, which are dominant species in the S. grandis degraded communities, were selected as study targets. We conducted a competition experiment (uniformly dense monoculture or mixture, respectively) under controlled conditions, including both drought stress and mowing disturbance, and calculated the relative interaction index (RII) of tiller number and RII of biomass for each species under each condition. (a) Under the same condition, the RII of tiller number and that of biomass for the same species usually showed reverse trends. (b) Mowing disturbance rather than drought stress played a negative role in influencing S. grandis' or S. krylovii's RII of tiller number and played a positive role in influencing A. frigida's RII of biomass. (c) Drought stress rather than mowing disturbance played a positive role in influencing C. squarrosa's RII of tiller number. (d) Neighbor species significantly influenced S. grandis' RII of tiller number, S. krylovii's RII of tiller number, A. frigida's RII of tiller number and biomass, and C. squarrosa's RII of biomass. These results could provide an explanation for why S. krylovii, A. frigida, and C. squarrosa can replace S. grandis and become the dominant species when S. grandis communities undergo a process of degradation due to overgrazing or climatic drought in natural communities. The present study provided powerful evidences for species replacement in the typical steppe of Inner Mongolia and elucidated the driving mechanisms of S. grandis communities' retrogressive succession. The combined effect of drought stress and grazing disturbance on shaping plant–plant interactions is the key process of retrogressive succession in Inner Mongolia steppe, China. We conducted a competition experiment to explore how Stipa grandis is replaced by the other three species during the retrogressive succession. (a) Neighbor species could help Stipa krylovii to increase its tiller number but inhibit S. grandis's tiller number under mowing treatment. (b) Mowing disturbance played a positive role in Artemisia frigida expanding in medium–heavy‐degraded region. (c) The higher tolerance to drought stress and lower competitive capacity enabled Cleistogenes squarrosa to be dominant species in heavy‐degraded region but not in stable or light‐degraded region. The present study provided evidences for species replacement in retrogressive succession of S. grandis communities. [ABSTRACT FROM AUTHOR]

• Using F-MSAP measured DNA methylation levels in cartilage (CA) and reserve mesenchyme (RM) cells and tissues. • DNA methylation plays an important role in the fast cartilage of deer antler. • Identified 20 methylated fragments specific to RMCs or the CA. This paper explored using of deer antlers as a model for studying rapid growth and cartilage formation in mammals. The genes and regulatory mechanisms involved in antler chondrogenesis are poorly understood, however, previous research has suggested that DNA methylation played a key role in antler regeneration. By using fluorescence-labeled methylation-sensitive amplified polymorphism (F-MSAP), this study measured DNA methylation levels in cartilage (CA) and reserve mesenchyme (RM) cells and tissues. Results showed that RM cells (RMCs) DNA methylation levels were significantly lower than those of CA, suggesting that DNA demethylation may be involved in antler fast cartilage differentiation. The study also identified 20 methylated fragments specific to RMCs or CA using the methylation-sensitive amplified polymorphism (MSAP) technique and confirmed these findings using southern blot analysis. The data provide the first experimental evidence of a link between epigenetic regulation and rapid cartilage differentiation in antlers. [ABSTRACT FROM AUTHOR]

The chloroplast is a semi-autonomous organelle with a double membrane structure, and its structural stability is a prerequisite for its correct function. Chloroplast development is regulated by known nuclear-encoded chloroplast proteins or proteins encoded within the chloroplast itself. However, the mechanism of chloroplast development regulated by other organelles remains largely unknown. Here, we report that the nuclear-localized DEAD-box RNA helicase 13 (RH13) is essential for chloroplast development in Arabidopsis thaliana. RH13 is widely expressed in tissues and localized to the nucleolus. A homozygous rh13 mutant shows abnormal chloroplast structure and leaf morphogenesis. Proteomic analysis showed that the expression levels of photosynthesis-related proteins in chloroplasts were reduced due to loss of RH13. Furthermore, RNA-sequencing and proteomics data revealed decreases in the expression levels of these chloroplast-related genes, which undergo alternative splicing events in the rh13 mutant. Taken together, we propose that nucleolus-localized RH13 is critical for chloroplast development in Arabidopsis. [ABSTRACT FROM AUTHOR]