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Abstract Flash Joule heating (FJH) is an emerging and profitable technology for converting inexhaustible biomass into flash graphene (FG). However, it is challenging to produce biomass FG continuously due to the lack of an integrated device. Furthermore, the high-carbon footprint induced by both excessive energy allocation for massive pyrolytic volatiles release and carbon black utilization in alternating current-FJH (AC-FJH) reaction exacerbates this challenge. Here, we create an integrated automatic system with energy requirement-oriented allocation to achieve continuous biomass FG production with a much lower carbon footprint. The programmable logic controller flexibly coordinated the FJH modular components to realize the turnover of biomass FG production. Furthermore, we propose pyrolysis-FJH nexus to achieve biomass FG production. Initially, we utilize pyrolysis to release biomass pyrolytic volatiles, and subsequently carry out the FJH reaction to focus on optimizing the FG structure. Importantly, biochar with appropriate resistance is self-sufficient to initiate the FJH reaction. Accordingly, the medium-temperature biochar-based FG production without carbon black utilization exhibited low carbon emission (1.9 g CO2-eq g−1 graphene), equivalent to a reduction of up to ~86.1% compared to biomass-based FG production. Undoubtedly, this integrated automatic system assisted by pyrolysis-FJH nexus can facilitate biomass FG into a broad spectrum of applications.

Abstract The primary methods of assessing the reliability of distribution networks comprise analytic and simulation methods. However, both approaches require the identification and computation of network topology, which precludes their expression in explicit, continuous functions, consequently impeding the incorporation of reliability constraints into planning and operational optimization models. To tackle this restriction, the present work puts forth a novel linear‐programming‐based reliability assessment method that is mathematically formulated, considering distribution automation (DA) and distributed generations (DGs), consisting of both conventional and renewable energy sources. In this paper, the clustering method and the scenario‐based method are used to model DGs. Next, a mixed integer linear programming (MILP) model, considering the DA and DGs with the System Average Interruption Duration Index (SAIDI) as the optimization objective, is proposed. Finally, the feasibility and effectiveness of the proposed method are verified in a 37‐node distribution network system.

The vibration tests were carried out using a 162kW wheeled tractor to evaluate the Whole-body vibration while the tractor working in the field, driving on concrete road and in-parking state. The tractor ride comfort was analyzed using the joint weighted acceleration of seat surface vibration from 1 to 80 Hz as the evaluation indicator, according to ISO2631 standard suggestions. During field work, the combined acceleration of the driver’s whole body vibration is 1.39, and the subjective feeling is extremely uncomfortable. Based on the multi-body dynamics analysis software, a tractor dynamics simulation model including the seat, cab mounts, chassis, tyre and road coupling system was established. By changing the model parameters, the influence of the tractor driver’s whole body vibration under the condition of the artificial test track was further analyzed. The analysis shows that the factors that have a greater impact on the driver’s whole body vibration when driving on the artificial runway are the vertical stiffness of the tyre, the vertical stiffness of the seat suspension, and the damping coefficient of the tyre.

The production of green hydrogen by water splitting from renewable energy is of great significance for achieving sustainable energy development. Alkaline water electrolysis (AWE) is the most economical and feasible route at present due to its earth-abundant catalysts, but it is desirable and crucial to improve the efficiency and purity of hydrogen production. Hydrogen production purity and energy consumption affect the fluctuation range of input power and economy respectively. In this paper, an electrolyzer with independent fluid flow path (IFP) is designed, which improves the problem of shutting current, hydrogen purity and hydrogen production efficiency. It has the characteristics of bipolar plate, zero gap and IFP. A test platform was built to verify its performance. The results showed that the IFP structure significantly improved the purity of hydrogen production, and the energy efficiency value increased by more than 3.29%.

Abstract Iron-based catalysts are promising candidates for advanced oxidation process-based wastewater remediation. However, the preparation of these materials often involves complex and energy intensive syntheses. Further, due to the inherent limitations of the preparation conditions, it is challenging to realise the full potential of the catalyst. Herein, we develop an iron-based nanomaterial catalyst via soft carbon assisted flash joule heating (FJH). FJH involves rapid temperature increase, electric shock, and cooling, the process simultaneously transforms a low-grade iron mineral (FeS) and soft carbon into an electron rich nano Fe0/FeS heterostructure embedded in thin-bedded graphene. The process is energy efficient and consumes 34 times less energy than conventional pyrolysis. Density functional theory calculations indicate that the electron delocalization of the FJH-derived heterostructure improves its binding ability with peroxydisulfate via bidentate binuclear model, thereby enhancing ·OH yield for organics mineralization. The Fe-based nanomaterial catalyst exhibits strong catalytic performance over a wide pH range. Similar catalysts can be prepared using other commonly available iron precursors. Finally, we also present a strategy for continuous and automated production of the iron-based nanomaterial catalysts.

The return of straw and manure to agricultural fields can impact soil organic carbon (SOC) and biological properties. However, there is a lack of research on how to use swine manure, maize straw, and various conditioners together affects soil bacterial and fungal populations. This study aimed to investigate six treatments, namely, only maize straw (S00), maize straw combined with swine manure (S0Z), maize straw combined with biochar and swine manure (SCZ), maize straw combined with boron slag and swine manure (SBZ), maize straw combined with biological agent and swine manure (SJZ), and maize straw combined with bio-organic fertilizer and swine manure (SFZ). The results showed that after the two-year return, all treatments increased the SOC content in 2023, which was 12.55–26.89% higher than S00. And the SCZ treatment significantly increased the soil organic carbon (SOC), dissolved organic carbon (DOC), easily oxidizable carbon (EOC), particulate organic carbon (POC), and microbial biomass carbon (MBC) content by 26.89%, 25.44%, 56.88%, 16.08%, and 43.54%, compared to S00. A redundancy analysis (RDA) showed that the continuous application of manure, maize straw, and conditioners has a positive impact on the diversity and abundance of soil microbial communities, enhancing the accumulation of soil carbon. Furthermore, our research revealed that soil fungi exhibited higher sensitivity in soil carbon composition following the addition of manure, straw, and conditioners to agricultural fields than bacteria. In conclusion, the addition of different conditioners to the fields is beneficial to biodiversity conservation from the perspective of achieving soil carbon storage and soil protection. Our findings suggested that the combination of maize straw, biochar, and swine manure was been proven to be the most effective treatment for increasing labile organic carbon fractions and enhancing the microbial community.

A microgrid is a promising small-scale power generation and distribution system. The selling prices of wind turbine equipment (WT), photovoltaic generation equipment (PV), and battery energy storage equipment (BES) have a significant impact on microgrid profits, which, in turn, affects the planning capacity of renewable energy. However, existing research has not yet conducted in-depth modeling and analysis for different kinds of energy generation electricity prices. This paper proposes an optimal capacity planning method for wind-photovoltaic-storage equipment, considering different energy selling incomes in microgrids. Stochastic characteristics of renewable energy (WT and PV), selling prices of different types of energy, and timing coupling characteristic are considered in the proposed model. In addition, the configuration capacities of WT, PV, and BES are modeled as discrete decision variables, according to the type of specific equipment. The comprehensive life cycle cost (LCC) is considered an objective function. It can be found that the proposed collaborative capacity planning model is a mathematical programming problem with complex nonlinear constraints and integer variables. To solve this problem, a cultural gray wolf optimization algorithm (CGWO) is applied in this paper. The proposed method’s efficiency, convergence, superiority, and effectiveness are verified through a case study. Moreover, the impact of different new energy sales prices on capacity planning results is also revealed in the article.

Aerospace bearings need to withstand the low-temperature environment of space, which will cause changes in the internal lubrication state of the bearings. This article aims to assess the traction properties of aerospace lubricants under low-temperature micro-oil droplet (hereinafter referred to as ‘micro-oil’) supply conditions, and provide a lubrication theoretical basis for studying the motion characteristics of aerospace bearings in a low-temperature environment. An experimental study on the low-temperature micro-oil traction properties of high-speed bearing lubricants was conducted on a specially designed aerospace bearing lubricant traction characteristic tester. A modified Herschel–Bulkley model (modified H–B model) was presented based on test data analysis, and the fitting results were compared with the Tevaarwerk–Johnson model (T–J model). The findings demonstrated that the traction coefficient of this lubricant decreased at a higher load and entrainment velocity, and decreased with a decreasing inlet oil temperature from 0 °C to −50 °C. The modified H–B model accurately fitted the test data and was suitable for the engineering traction coefficient calculation of lubricants and high viscosities at low temperatures. This paper can provide fundamental information for analyzing aerospace bearing friction torque variation.

To overcome the limitations of the hybrid tractor bumping tests, which include extended cycle times, high costs, and impracticality for single-part reliability verification, this study focuses on the exhaust system mounting bracket of a hybrid tractor. A novel approach that combines multi-objective particle swarm optimization (MOPSO) and wavelet decomposition algorithms was employed to enhance the reconstruction of shock vibration signals. This approach aims to enable the efficient acquisition of input signals for subsequent shaker table testing. The methodology involves a systematic evaluation of the spectral correlation between the original signal and the reconstructed signal at the stent’s response position, along with signal compression time. These parameters collectively constitute the objective function. The multi-objective particle swarm optimization algorithm is then deployed to explore a range of crucial parameters, including wavelet basic functions, the number of wavelet decomposition layers, and the selection of wavelet components. This exhaustive exploration identifies an optimized signal reconstruction method that accurately represents shock vibration loads. Upon rigorous screening based on our defined objectives, the optimal solution vector was determined, which includes the utilization of the dB10 wavelet basic function, employing a 12-layer wavelet decomposition, and selecting wavelet components a12 and d3~d11. This specific configuration enables the retention of 95% of the damage coefficients while significantly compressing the test time to just 46% of the original signal duration. The implications of our findings are substantial as the reconstructed signal obtained through our optimized approach can be readily applied to shaker excitation. This innovation results in a notable reduction in test cycle time and associated costs, making it particularly valuable for engineering applications, especially in tractor design and testing.

The noise level in a tractor cab directly affects the driving experience. Reducing the noise level in a tractor cab is an important means of improving the image of the product brand and protecting the physical and psychological health of employees. To reduce medium- and low-frequency noise in a tractor cab, the influence of the installation of coupled resonance acoustic materials (CRAMs) on tractor driver ear noise is investigated in this study. Theories for sound absorption by perforated plates and sound insulation by thin membranes are used to design a CRAM composed of a perforated plate, elastic membrane and additional mass. The acoustic impedance and sound absorption coefficient of the CRAM are obtained by an equivalent circuit method, and the resonance frequency of a local resonance system composed of an elastic membrane and additional mass is calculated. The effects of different hole diameters and porosities of the perforated plate on the CRAM sound absorption coefficient are compared. The results of tests performed using impedance tubes over a wide frequency range of 50 Hz~1600 Hz show that the maximum sound absorption coefficient is 0.99 and several transmission loss peaks of 15 dB~26 dB. Measurement of the acoustic response of the CRAM installed on the cab front panel shows that an ear noise reduction of approximately 1.3 dB(A) for a tractor working speed of 2200 rpm. The results show that the designed CRAM has a relatively good effect on reducing driver ear noise over a wide frequency band and is a feasible scheme for noise reduction in a tractor cab.

Long-term exposure to high levels of vibration and noise can have detrimental effects on the health of tractor drivers. This study aimed to evaluate the subjective comfort experienced by drivers operating large-horsepower tractors. A total of 10 tractors sourced from 5 different manufacturers were subjected to testing. The assessment encompassed three operational conditions, namely, idle, maximum torque, and rated power. Objective measurements, including A-weighted sound pressure level (A-SPL), loudness, sharpness, roughness, articulation index (AI), hand vibration, and seat vibration, were collected. Additionally, subjective comfort evaluations were carried out using a paired comparison test. To predict the subjective comfort of tractor drivers, a novel prediction model was developed by employing a simulated annealing (SA) algorithm to optimize a backpropagation neural network (BPNN). The model successfully achieved accurate predictions of subjective comfort, yielding a maximum prediction error of 4.4%. The study findings revealed that vibration had a more pronounced impact on driver comfort in environments with lower-amplitude noise, whereas high-decibel noise exerted a masking effect on vibration-induced discomfort. In conclusion, the SA-BPNN model, utilizing A-SPL, loudness, sharpness, roughness, AI, hand vibration, and seat vibration as objective parameters, effectively predicted the subjective comfort of tractor drivers. This discovery holds significant implications for tractor manufacturers, who can employ the model to optimize the design of tractor cabs and enhance driver comfort.

PurposeMacrophage polarization plays an essential role in the tumor microenvironment of brain tumors. However, the role of tumor-associated macrophages (TAMs) in medulloblastoma still remains controversial. Thus, we investigated the distribution of macrophages in medulloblastoma tissues and analyzed the association of TAM recruitment and medulloblastoma patients’ outcomes.MethodsWe obtained a total of 71 paraffin sections from patients with medulloblastoma, and detected the activated phenotype (M1/M2) by monoclonal antibodies for CD68, HLA-DR and CD163 with multiple fluorescence immunohistochemistry method. The number of polarized macrophages was quantified using the InForm software. Outcomes were analyzed according to clinical data and quantified macrophage data.ResultsThe study revealed that TAMs were significantly higher in sonic hedgehog (SHH) medulloblastoma than in other subgroups, and M1 macrophages in metastatic group were significantly higher than those in non-metastatic group. A Kaplan-Meier survival analysis and multivariate Cox regression model showed the correlation of high percentage of total macrophages (P = 0.038, HR = 0.241) and M1 macrophages (P = 0.034, HR = 0.333) with good 5-year progression-free survival (PFS); however, M2 macrophages had no correlation with survival of medulloblastoma patients (P> 0.05).ConclusionHigh percentage of total macrophages and M1 macrophages are correlated with good outcome of medulloblastoma patients. TAMs might be a target of therapy.

A series of ultra-toughened sustainable blends were prepared from poly(lactic acid) (PLA) and bromobutyl rubber-based ionomers (i-BIIRs) via reactive blending, in which dicumyl peroxide (DCP) and Joncryl®ADR-4440 (ADR) were used as reactive blending additives. The miscibility, phase morphology and mechanical property of the PLA/i-BIIRs blends were thoroughly investigated through DMA, SEM, tensile and impact tests. The influence of different ionic groups and the effects of DCP and ADR on the compatibility between the phases, phase structure and mechanical properties were analyzed. The introduction of the imidazolium-based ionic groups and the reactive agents enable the i-BIIRs play multiple roles as effective compatibilizers and toughening agents, leading to improved interfacial compatibility and high toughness of the blends. The mechanical properties test showed that the PLA/i-BIIRs blends exhibit excellent toughness: impact strength and the elongation at break of AR-OH(30)+AD reached 95 kJ/m2 and 286%, respectively. The impact fracture surface showed the large-scale plastic deformation of the PLA matrix in the blends, resulting in greatly absorbing the impact energy. The results proved that simultaneously applying reactive blend and multiple intermolecular interactions methods is an effective toughening strategy for toughening modification of the PLA blends.

Abstract Medulloblastoma (MB) is the most common type of brain malignancy in children. Molecular profiling has become an important component to select patients for therapeutic approaches, allowing for personalized therapy. In this study, we successfully identified detectable levels of tumor-derived cell-free DNA (cfDNA) in cerebrospinal fluid (CSF) samples of patients with MB. Furthermore, cfDNA from CSF can interrogate for tumor-associated molecular clues. MB-associated alterations from CSF, tumor, and post-chemotherapy plasma were compared by deep sequencing on next-generation sequencing platform. Shared alterations exist between CSF and matched tumor tissues. More alternations were detected in circulating tumor DNA from CSF than those in genomic DNA from primary tumor. It was feasible to detect MB-associated mutations in plasma of patients treated with chemotherapy. Collectively, CSF supernatant can be used to monitor genomic alterations, as a superior technique as long as tumor-derived cfDNA can be isolated from CSF successfully.

Obstacle avoidance operations of tractors can cause parts of land to be unavailable for planting crops, which represents a reduction in land utilization. However, land utilization is significant to the increase in agricultural productivity. Traditional obstacle avoidance path planning methods mostly focus on automatic tractor navigation with small errors, ignoring the decrease in land utilization due to obstacle avoidance operations. To address the problem, this paper proposed an obstacle avoidance path planning method based on the Genetic Algorithm (GA) and Bezier curve. In this paper, a third-order Bezier curve was used to plot the obstacle avoidance path, and the range of control points for the third-order Bezier curve was determined according to the global path and the location of the obstacle. To target the navigation error and land utilization problems, GA was used to search for the optimal point from the selection range of the control point under multiple constraints for automatic tractor navigation such as the obstacle collision avoidance, the minimum turning radius, and the maximum turning angle. Finally, the optimal obstacle avoidance path was determined based on the selected control points to minimize the navigation error and maximize land utilization. The algorithm proposed in this paper was compared with existing methods and the results showed that it has generally favorable performance on obstacle avoidance path planning.

Using photovoltaic (PV) energy to produce hydrogen through water electrolysis is an environmentally friendly approach that results in no contamination, making hydrogen a completely clean energy source. Alkaline water electrolysis (AWE) is an excellent method of hydrogen production due to its long service life, low cost, and high reliability. However, the fast fluctuations of photovoltaic power cannot integrate well with alkaline water electrolyzers. As a solution to the issues caused by the fluctuating power, a hydrogen production system comprising a photovoltaic array, a battery, and an alkaline electrolyzer, along with an electrical control strategy and energy management strategy is proposed. The energy management strategy takes into account the predicted PV power for the upcoming hour and determines the power flow accordingly. By analyzing the characteristics of PV panels and alkaline water electrolyzers and imposing the proposed strategy, this system offers an effective means of producing hydrogen while minimizing energy consumption and reducing damage to the electrolyzer. The proposed strategy has been validated under various scenarios through simulations. In addition, the system’s robustness was demonstrated by its ability to perform well despite inaccuracies in the predicted PV power.

Three dimensional (3D) geological model is frequently used to represent the geological conditions of the subsurface. The generalized triangular prism (GTP) model designed for borehole sampling data is a spatial data model that could retain the internal connection between the three adjacent boreholes and distinguish between the bedding and cross-bedding directions, which is proper for accurate 3D geological modeling. The traditional building method cannot consider two factors: the borehole distance is usually longer than the stratigraphic thickness, and the top and the bottom surface have different accuracy at the same time. In this study, we describe the new interpolation method for the GTP 3D geological model to improve the model accuracy with sparse borehole data. Firstly, definition and calculation method of the GTP model smoothness are proposed to measure the model smoothness and accuracy degree, which are used to decide whether the GTP voxel requires interpolation. Secondly, the virtual borehole design and calculation method for the GTP voxel subdivision in terms of the GTP geometric smoothness are discussed in detail. Finally, the GTP adaptive interpolation can be performed through the GTP voxel subdivision and the geometric optimization rebuilding. This method could adaptively interpolate the existing GTP model by local updating without changing the GTP model structure, it has high efficiency compared to the classical method. In addition, the feasibility and accuracy of this method could be proven by the actual case. The study will provide a new and reliable interpolation method for the GTP model, and it is also conducive to economic geology related research.

Introduction Chronic heart failure (CHF) is a leading cause of deaths induced by cardiovascular disease. This study aimed to investigate the protective effects of emodin in CHF rats and explore the related mechanisms. Material and methods A total of 56 Wistar rats were used to construct CHF model using the coronary artery ligation. The effects of emodin on cardiac function and inflammation were analyzed in the CHF rats. Expression of miR-26b-5p in the CHF model before and after emodin treatment was estimated by quantitative real-time polymerase chain reaction. The effects of miR-26b-5p on cardiac function and inflammation were also assessed, and its target gene was predicted and confirmed in rat cardiomyocyte H9c2. Results Emodin treatment could significant improve the cardiac function and inflammation evidenced by the increased increased ejection fraction (EF), fractional shortening (FS), left ventricular systolic pressure (LVSP) and maximum of the first differentiation of left ventricular pressure (+LV dP/dtmax) and decreased atrial natriuretic peptide (ANP), brain natriuretic peptide (BNP), left ventricular end diastolic pressure (LVEDP), interleukin (IL)-6, tumor necrosis factor α (TNF-α) levels. Expression of miR-26b-5p was downregulated in the CHF rats (CHF 0.442 ±0.131 vs. Sham 1.044 ±0.160), and this suppressive effect was rescued by emodin (Emodin 0.902 ±0.132 vs. CHF 0.442 ±0.131). The overexpression of miR-26b-5p in CHF rats led to improved cardiac function and inflammatory response. In addition, the emodin-induced increased EF, FS, LVSP and +LV dP/dtmax and decreased ANP, BNP, LVEDP, IL-6 and TNF-α were all abrogated by the knockdown of miR-26b-5p. The target prediction results revealed that PTEN was a target gene of miR-26b-5p in H9c2 cells. Conclusions All the results indicated that emodin serves a protective role in CHF via regulation of the miR-26b-5p/PTEN pathway. Emodin may be an effective therapeutic agent for CHF treatment.

REV7 has emerged as a critical regulator of DNA double-strand breaks repair. Here, the authors show that REV7 is crucial for both antibody class switch recombination and somatic hypermutation in activated B cells, in addition to their survival upon AID-deamination.

This research aimed to establish an effective storage method to maintain the quality of processed sea cucumbers. In this study, sea cucumbers were stored by various methods including the storage of live sea cucumbers (seawater treatment, oxygen treatment, and ascorbic acid treatment) and the storage of dead sea cucumbers (frozen treatment). The sea cucumber quality was monitored after storage and boiling. The weightlessness rate and WHC of the frozen group increased to 86.96% ± 0.83% and 93.29% ± 0.32%, respectively. Frozen sea cucumbers shrunk with the meat’s textural properties deteriorated. During the live sea cucumber storage, the tissue protein degraded from day 3 to day 7 which led to the promotion of TVB-N. Among these, the oxygen group showed the smallest TVB-N increase from day 0 (3.78 ± 0.60 mg 100 g−1) to day 7 (10.40 ± 0.12 mg 100 g−1). The oxygen group exhibited the most moderate change in weightlessness rate (4.24% ± 0.45%) and the most moderate texture parameters decline, such as the hardness of 32.52%, chewiness of 78.98 ± 5.10 N, and adhesion of 0.84 ± 0.00. The oxygen method showed the best condition of sea cucumber after 5 days of storage.

Indoor localization problems are difficult due to that the information, such as WLAN and GPS, cannot achieve enough precision for indoor issues. This paper presents a novel indoor localization algorithm, GeoLoc, with uncertainty eliminate based on fusion of acceleration, angular rate, and magnetic field sensor data. The algorithm can be deployed in edge devices to overcome the problems of insufficient computing resources and long delay caused by high complexity of location calculation. Firstly, the magnetic map is built and magnetic values are matched. Secondly, orientation updating and position selection are iteratively executed using the fusion data, which gradually reduce uncertainty of orientation. Then, we filter the trajectory from a path set. By gradually reducing uncertainty, GeoLoc can bring a high positioning precision and a smooth trajectory. In addition, this method has an advantage in that it does not rely on any infrastructure such as base stations and beacons. It solves the common problems regarding the non-uniqueness of the geomagnetic fingerprint and the deviation of the sensor measurement. The experimental results show that our algorithm achieves an accuracy of less than 2.5 m in indoor environment, and the positioning results are relatively stable. It meets the basic requirements of indoor location-based services (LBSs).

Introduction: Chronic heart failure (CHF) is a leading cause of deaths induced by cardiovascular disease. This study aimed to investigate the protective effects of emodin in CHF rats and explore the related mechanisms. Material and methods: A total of 56 Wistar rats were used to construct CHF model using the coronary artery ligation. The effects of emodin on cardiac function and inflammation were analyzed in the CHF rats. Expression of miR-26b-5p in the CHF model before and after emodin treatment was estimated by quantitative real-time polymerase chain reaction. The effects of miR-26b-5p on cardiac function and inflammation were also assessed, and its target gene was predicted and confirmed in rat cardiomyocyte H9c2. Results: Emodin treatment could significant improve the cardiac function and inflammation evidenced by the increased increased ejection fraction (EF), fractional shortening (FS), left ventricular systolic pressure (LVSP) and maximum of the first differentiation of left ventricular pressure (+LV dP/dtmax) and decreased atrial natriuretic peptide (ANP), brain natriuretic peptide (BNP), left ventricular end diastolic pressure (LVEDP), interleukin (IL)-6, tumor necrosis factor α (TNF-α) levels. Expression of miR-26b-5p was downregulated in the CHF rats (CHF 0.442 ±0.131 vs. Sham 1.044 ±0.160), and this suppressive effect was rescued by emodin (Emodin 0.902 ±0.132 vs. CHF 0.442 ±0.131). The overexpression of miR-26b-5p in CHF rats led to improved cardiac function and inflammatory response. In addition, the emodin-induced increased EF, FS, LVSP and +LV dP/dtmax and decreased ANP, BNP, LVEDP, IL-6 and TNF-α were all abrogated by the knockdown of miR-26b-5p. The target prediction results revealed that PTEN was a target gene of miR-26b-5p in H9c2 cells. Conclusions: All the results indicated that emodin serves a protective role in CHF via regulation of the miR-26b-5p/PTEN pathway. Emodin may be an effective therapeutic agent for CHF treatment. [ABSTRACT FROM AUTHOR]

While photoredox catalysis presents exciting avenues for molecular transformations, balancing optimal photochemical and materials properties can be challenging. Here, the authors prepare carbon-coated In2O3 nanoparticles as recoverable photocatalysts for arylboronic acid oxidative hydroxylation.

Abstract Background Surfactin is a cyclic lipopeptide that is of great industrial use owing to its extraordinary surfactant power and antimicrobial, antiviral, and antitumor activities. Surfactin is synthesized by a condensation reaction in microbes, which uses fatty acids and four kinds of amino acids (l-glutamate, l-aspartate, l-leucine and l-valine) as precursors. Surfactin biosynthesis could be improved by increasing the supply of fatty acids; however, the effect of the regulation of amino acid metabolism on surfactin production was not yet clear. Results In this study, we aimed to improve surfactin production in B. subtilis by repressing the genes on the branch metabolic pathways of amino acid biosynthesis using CRISPRi technology. First, 20 genes were inhibited individually, resulting in 2.5- to 627-fold decreases in transcriptional level as determined by RT-qPCR. Among the 20 recombinant strains, 16 strains obtained higher surfactin titres than that produced by the parent BS168NU-Sd strain (the surfactin production of BS168NU-Sd with only dCas9 but no sgRNA expression was 0.17 g/L). In particular, the strains in which the yrpC, racE or murC genes were inhibited individually produced 0.54, 0.41, or 0.42 g/L surfactin, respectively. All three genes are related to the metabolism of l-glutamate, whose acylation is the first step in the surfactin condensation reaction. Furthermore, these three genes were repressed in combination, and the strain with co-inhibition of yrpC and racE produced 0.75 g/L surfactin, which was 4.69-fold higher than that of the parent strain. In addition, the inhibition of bkdAA and bkdAB, which are related to the metabolism of l-leucine and l-valine, not only improved surfactin production but also increased the proportion of the C14 isoform. Conclusions This study, to the best of our knowledge for the first time, systematically probed the regulatory effect of increasing the supply of amino acids on surfactin production. It provided an effective strategy and a new perspective for systematic studies on surfactin and other amino acid-derived chemicals.

Abstract Porous structures offer highly accessible surfaces and rich pores, which facilitate the exposure of numerous active sites for photocatalytic reactions, leading to excellent performances. Recently, metal–organic frameworks (MOFs) have been considered ideal precursors for well-designed semiconductors with porous structures and/or heterostructures, which have shown enhanced photocatalytic activities. In this review, we summarize the recent development of porous structures, such as metal oxides and metal sulfides, and their heterostructures, derived from MOF-based materials as catalysts for various light-driven energy-/environment-related reactions, including water splitting, CO2 reduction, organic redox reaction, and pollution degradation. A summary and outlook section is also included.

In order to deal with the problem of environmental pollution and energy consumption, developing clean and renewable energy to maintain the sustainable development of society has become an urgent matter for human beings. Therefore, distributed generation (DG) is widely concerned by engineers. However, the output of DG is generally random and intermittent. When it is connected to different locations, different capacities and different types of power grids, the safe and stable operation of the power system will be affected to different degrees. When selecting the optimal DG access scheme, power grid planners must consider the influence of capacity, type and location to ensure a safer, more stable, more reliable and more efficient power grid operation. Therefore, this paper proposes an objective function considering integrated power losses, voltage profile and pollution emission, and swarm moth flame optimization algorithm (SMFO) is used to solve. Finally, based on IEEE-33 bus, the effectiveness of the proposed algorithm is verified.

Accurate and reliable photovoltaic (PV) cell parameter identification is critical to simulation analysis, maximum output power harvest, and optimal control of PV systems. However, inherent high-nonlinear and multi-modal characteristics usually result in thorny obstacles to hinder conventional optimization methods to obtain a fast and satisfactory performance. In this study, a novel bio-inspired grouped beetle antennae search (GBAS) algorithm is devised to effectively identify unknown parameters of three different PV models, i.e., single diode model (SDM), double diode model (DDM), and triple diode model (TDM). Compared against beetle antennae search (BAS) algorithm, optimization efficiency of GBAS algorithm is markedly enhanced based on a cooperative searching group that consists of multiple individuals rather than a single beetle. Besides, a dynamic balance mechanism between local exploitation and global exploration is designed to increase the probability for a higher quality optimum. Comprehensive case studies demonstrate that GBAS algorithm can outperform other advanced meta-heuristic algorithms in both optimization precision and stability for estimating PV cell parameters, e.g., standard deviation (SD) of root mean square error (RMSE) obtained by GBAS algorithm is 64.34% smaller than the best value obtained by other algorithms in SDM, 61.86% smaller than that in DDM.

At present, urban traffic congestion is a common problem of urban development in China. Therefore, China’s government issued the policy of opening the gated communities in 2016, hoping to alleviate traffic pressure to some extent. But, at present, the quantitative empirical research on the effect of the policy implementation is less and more idealistic. In order to complete the leap from research on local isolated traffic capacity of static gated communities to research on global coupling traffic capacity of dynamic multilayer network and, to a certain extent, reflect the innovation of the research model and method, we make a quantitative analysis of the effect of the policy more consistent with the actual situation, which provides a quantitative management basis for the implementation of the policy. Based on literature review, this paper carried out two stages of research. Stage one consists of constructing traffic capacity assessment model—Road Capacity Assessment (RCA) model based on BPR (Bureau of Public Roads) impedance function from a simple local static perspective. Considering the factors such as delay of signalized intersection and travel time, through modeling analysis and empirical test, it is found that about 12% of local traffic capacity can be improved after open community. Stage two consists of constructing a global capacity model based on multilayer complex network coupling from the perspective of complex global dynamics. Considering the various network nodes of pedestrians, nonmotor vehicles, and other factors, we construct a multilayer complex network and dynamic superposition coupling. The empirical data show that the overall traffic capacity of the open community is improved by at least 11.3%. Finally, it can be concluded that a significant increase in the global traffic capacity of complex urban road networks means that the losses caused by traffic congestion will be reduced. In some first-tier cities, the direct monthly income of the open-gated community is as high as 230 million yuan, not to mention its overall economic, social, and environmental benefits.

With the update and iteration of Internet technology, the socialized Q&A (question-and-answer) platform realizes the cross-border dissemination of knowledge with the main purpose of disseminating and sharing knowledge. Zhihu, as a knowledge-sharing platform that relies on the user-generated content model to maintain operation and the strong willingness of users to share knowledge, plays a key role in the development of the community. Currently, social Q&A platforms are facing problems such as low user participation rate and gradual decrease in the number of active users. It is very important and urgent to explore the factors that affect users’ willingness to share knowledge. In response to this problem, this paper builds a theoretical model of the factors that are affecting users’ willingness to share knowledge and uses questionnaire research methods to conduct research design and collect sample data and uses methods such as correlation analysis and structural equation modeling to verify the model and hypothesis. The research results show that the theoretical model of planned behavior has strong explanatory power and self-efficacy and material rewards have a positive effect on knowledge-sharing attitudes. Finally, according to some research results, this paper shows that, with the change of time, young people have different needs for knowledge sharing than before, while realizing self-worth through sharing experience, and we also hope to protect own interests and hope that there are more factors to encourage more users to share their knowledge and experience. Therefore, we propose that the platform can use incentive mechanisms to promote knowledge sharing while helping sharers realize their self-worth, improve the existing functions of the platform, or carry out activities to encourage users to participate, so as to achieve the purpose of knowledge sharing and maintain the operation of the Zhihu platform.

This article, titled "Editorial: Necroptosis: from bench to bedside," explores the role of necroptosis, a programmed cell death pathway, in human diseases and potential therapeutic approaches. The article highlights the interactions between necroptosis and the immune system, as well as its involvement in inflammatory diseases such as skin inflammation, Inflammatory Bowel Disease, pancreatitis, and Multiple Sclerosis. The authors also discuss the regulation of necroptosis by TNF Receptor Interacting Kinase 1 (RIPK1) and the potential for targeting RIPK1 in the treatment of various inflammatory conditions. The article includes in-depth reviews of the pathophysiological mechanisms of necroptosis in Idiopathic Inflammatory Myopathies and gastrointestinal diseases, as well as the role of RIPK1 in neuroinflammation and neurodegenerative diseases. The authors conclude by emphasizing the need for further research and the development of therapeutic strategies targeting the necroptotic machinery. [Extracted from the article]

Karst cave collapse usually occurs during the process of drilling and reservoir development. Karst cave collapse increases drilling risk and seriously affects oil production. In order to reveal the collapse mechanism of karst caves in fractured-vuggy reservoirs in Tahe oil field, rock mechanic experiments and numerical simulation studies were conducted. In rock mechanic experiments, three types of rock mechanics tests (uniaxial compression, triaxial compression, and Brazilian splitting) were carried out to obtain the basic rock mechanics parameters. In numerical simulation studies, the collapse conditions of a single karst cave and a cave system were studied. Numerical simulation results indicate that for a single karst cave, the size and geometrical features of karst caves are the main factors influencing collapse condition. For a cave system, a combination pattern and distance between caves are two main factors affecting collapse condition. In order to facilitate the application of these research results, the authors present formulas for calculating the critical conditions of karst cave collapse by means of multivariate linear regression method. The calculation formulas and prediction chart were verified as consistent with actual field results. The research results in this paper have great theoretical and practical value for revealing the mechanism of karst cave collapse in fractured-vuggy carbonate reservoirs.

Necroptosis is a type of programmed cell death executed through the plasma membrane disruption by mixed lineage kinase domain-like protein (MLKL). Previous studies have revealed that an N-terminal four-helix bundle domain (NBD) of MLKL is the executioner domain for the membrane permeabilization, which is auto-inhibited by the first brace helix (H6). After necroptosis initiation, this inhibitory brace helix detaches and the NBD can integrate into the membrane, and hence leads to necroptotic cell death. However, how the NBD is released and induces membrane rupture is poorly understood. Here, we reconstituted MLKL2–154 into membrane mimetic bicelles and observed the structure disruption and membrane release of the first brace helix that is regulated by negatively charged phospholipids in a dose-dependent manner. Using molecular dynamics simulation we found that the brace region in an isolated, auto-inhibited MLKL2–154 becomes intrinsically disordered in solution after 7 ns dynamic motion. Further investigations demonstrated that a cluster of arginines in the C-terminus of MLKL2–154 is important for the molecular conformational switch. Functional mutagenesis showed that mutating these arginines to glutamates hindered the membrane disruption of full-length MLKL and thus inhibited the necroptotic cell death. These findings suggest that the brace helix also plays an active role in MLKL regulation, rather than an auto-inhibitory domain.

Abstract Background The microbial fuel cell (MFC) is a green and sustainable technology for electricity energy harvest from biomass, in which exoelectrogens use metabolism and extracellular electron transfer pathways for the conversion of chemical energy into electricity. However, Shewanella oneidensis MR-1, one of the most well-known exoelectrogens, could not use xylose (a key pentose derived from hydrolysis of lignocellulosic biomass) for cell growth and power generation, which limited greatly its practical applications. Results Herein, to enable S. oneidensis to directly utilize xylose as the sole carbon source for bioelectricity production in MFCs, we used synthetic biology strategies to successfully construct four genetically engineered S. oneidensis (namely XE, GE, XS, and GS) by assembling one of the xylose transporters (from Candida intermedia and Clostridium acetobutylicum) with one of intracellular xylose metabolic pathways (the isomerase pathway from Escherichia coli and the oxidoreductase pathway from Scheffersomyces stipites), respectively. We found that among these engineered S. oneidensis strains, the strain GS (i.e. harbouring Gxf1 gene encoding the xylose facilitator from C. intermedi, and XYL1, XYL2, and XKS1 genes encoding the xylose oxidoreductase pathway from S. stipites) was able to generate the highest power density, enabling a maximum electricity power density of 2.1 ± 0.1 mW/m2. Conclusion To the best of our knowledge, this was the first report on the rationally designed Shewanella that could use xylose as the sole carbon source and electron donor to produce electricity. The synthetic biology strategies developed in this study could be further extended to rationally engineer other exoelectrogens for lignocellulosic biomass utilization to generate electricity power.

The interest of the high internal phase (HIP) gel-in-oil concept for the development of emulsions with original aesthetic qualities was highlighted some years ago. Manufactured using a sustainable cold process, these emulsions were characterized by a fresh skin contact and triggered similar emollience to classical emulsions and cream gels with half the oil concentration. However, the factors governing the emulsion structure have not been thoroughly clarified. Composition factors (i.e., the essential structural materials and concentration of the internal gel phase) and the preparation procedure (i.e., emulsification mode and agitation procedure) have been investigated on a standard HIP gel-in-oil emulsion. Their influence on the creation, structure, and stability of gel-in-oil emulsions was determined by conventional observations, stability tests, and rheology experiments, from low to high shear conditions (rotational controlled stress/strain rheometer). Limitations and critical factors such as characteristics of the gel phase and a required dose of emulsifier were highlighted. An emulsification mixing procedure with medium shear using an anchor provided the best results. In addition, conventional conductivity monitoring combined with rheology experiments detected early indicators of the risk of destabilization soon after manufacturing. Precise recommendations to obtain stable HIP gel-in-oil emulsions, characterized by highly stable elastic structure, could be defined. [ABSTRACT FROM AUTHOR]

A new sea urchin polysaccharide (SUP) was extracted from the gonad of sea urchin (Strongylocentrotus intermedius), and its bioactivity to synergistically enhance the functionality of bone morphogenetic protein-2 (BMP-2) induced osteoblastic differentiation was characterized. Results showed that the SUP is homogenous with an average molecular weight of 4.4 kDa, and it is mainly composed of mannose with a small number of glucose and N-acetylglucosamine, with a backbone of alternating 1, 4-D-Man and 1, 3-D-Man residues. The SUP was shown to synergistically enhance BMP-2 induced osteoblastic differentiation in C2C12 myoblast cells, evidenced by a significant increase in the activity of alkaline phosphatase (ALP), when the concentration of the SUP was higher than 10 µg/mL. The elevated ALP activity was also confirmed by histochemical staining of C2C12 myoblast cells. These results suggest that the SUP can promote bone regeneration and may serve as a functional food supplement for bone health.