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As transcription factors derived from transposase, FAR-RED IMPAIRED RESPONSE1 (FAR1) and its homolog FHY3 play crucial roles in the regulation of light signaling and various stress responses by coordinating the expression of downstream target genes. Despite the extensive investigation of the FAR1/FHY3 family in Arabidopsis thaliana and other species, a comprehensive examination of these genes in maize has not been conducted thus far. In this study, we employed a genomic mining approach to identify 16 ZmFAR1 genes in the maize inbred line B73, which were further classified into five subgroups based on their phylogenetic relationships. The present study characterized the predicted polypeptide sequences, molecular weights, isoelectric points, chromosomal distribution, gene structure, conserved motifs, subcellular localizations, phylogenetic relationships, and cis-regulatory elements of all members belonging to the ZmFAR1 family. Furthermore, the tissue-specific expression of the 16 ZmFAR1 genes was analyzed using RNA-seq, and their expression patterns under far-red light conditions were validated in the ear and tassel through qRT-qPCR. The observed highly temporal and spatial expression patterns of these ZmFAR1 genes were likely associated with their specific functional capabilities under different light conditions. Further analysis revealed that six ZmFAR1 genes (ZmFAR1-1, ZmFAR1-10, ZmFAR1-11, ZmFAR1-12, ZmFAR1-14, and ZmFAR1-15) exhibited a response to simulated shading treatment and actively contributed to the development of maize ears. Through the integration of expression quantitative trait loci (eQTL) analyses and population genetics, we identified the presence of potential causal variations in ZmFAR1-14 and ZmFAR1-9, which play a crucial role in regulating the kernel row number and kernel volume weight, respectively. In summary, this study represents the initial identification and characterization of ZmFAR1 family members in maize, uncovering the functional variation in candidate regulatory genes associated with the improvement of significant agronomic traits during modern maize breeding.

The flow characteristics of methane and water in sedimentary layers are important factors that affect the beneficial exploitation of marine hydrates. To study the influencing factors of methane drive-off water processes in porous media, we constructed nonhomogeneous geometric models using MATLAB 2020a random distribution functions. We developed a mathematical model of gas–water two-phase flow based on the Navier–Stokes equation. The gas-driven water processes in porous media were described using the level-set method and solved through the finite element method. We investigated the effects of the nonhomogeneous structure of pore media, wettability, and repulsion rate on gas-driven water channeling. The nonhomogeneity of the pore medium is the most critical factor influencing the flow. The size of the throat within the hydrophilic environment determines the level of difficulty of gas-driven water flow. In regions with a high concentration of narrow passages, the formation of extensive air-locked areas is more likely, leading to a decrease in the efficiency of the flow channel. In the gas–water drive process, water saturation changes over time according to a negative exponential function relationship. The more hydrophilic the pore medium, the more difficult the gas-phase drive becomes, and this correlation is particularly noticeable at higher drive rates. The significant pressure differentials caused by the high drive-off velocities lead to quicker methane breakthroughs. Instantaneous flow rates at narrow throats can be up to two orders of magnitude higher than average. Additionally, there is a susceptibility to vortex flow in the area where the throat connects to the orifice. The results of this study can enhance our understanding of gas–water two-phase flow in porous media and help commercialize the exploitation of clean energy in the deep ocean.

Foodborne mycotoxins (FBMTs) are toxins produced by food itself or during processing and transportation that pose an enormous threat to public health security. However, traditional instrumental and chemical methods for detecting toxins have shortcomings, such as high operational difficulty, time consumption, and high cost, that limit their large-scale applications. In recent years, aptamer-based biosensors have become a new tool for food safety risk assessment and monitoring due to their high affinity, good specificity, and fast response. In this review, we focus on the progress of single-mode and dual-mode aptasensors in basic research and device applications over recent years. Furthermore, we also point out some problems in the current detection strategies, with the aim of stimulating future toxin detection systems for a transition toward ease of operation and rapid detection.

A low-cost method for the simultaneous extraction of alkaloids and water-insoluble flavonoids and esters from Coptis chinensis Franch. (Abbrev. C. chinensis) was explored to provide a reference for the production of green plant-based preparations and traditional Chinese medicine formula granules. A combined extraction method with the deep eutectic solvents (DESs) of choline chloride and urea (molar mass ratio of 1:2) and organic solvent ethanol was used, supplemented by ultrasonic-assisted extraction (ultrasonic power: 150 W; ultrasonic temperature: 60 °C; treatment time: 15 min). The extraction efficiency of the 50% DES (choline chloride and urea) aqueous solution for berberine, palmatine, jatrorrhizine, and magnoflorine was found to be the highest and was superior to traditional ultrasonic extraction and water bath reflux extraction methods. Furthermore, the flavonoids and esters from C. chinensis residue were extracted using ethanol. The results from high-performance liquid chromatography and gas chromatography–mass spectrometry indicated a high extraction efficiency overall.

Fusarium head blight (FHB) is a plant disease caused by various species of the Fusarium fungus. One of the major concerns associated with Fusarium spp. is their ability to produce mycotoxins. Mycotoxin contamination in small grain cereals is a risk to human and animal health and leads to major economic losses. A reliable site-specific precise Fusarium spp. infection early warning model is, therefore, needed to ensure food and feed safety by the early detection of contamination hotspots, enabling effective and efficient fungicide applications, and providing FHB prevention management advice. Such precision farming techniques contribute to environmentally friendly production and sustainable agriculture. This study developed a predictive model, Sága, for on-site FHB detection in wheat using imaging spectroscopy and deep learning. Data were collected from an experimental field in 2021 including (1) an experimental field inoculated with Fusarium spp. (52.5 m × 3 m) and (2) a control field (52.5 m × 3 m) not inoculated with Fusarium spp. and sprayed with fungicides. Imaging spectroscopy data (hyperspectral images) were collected from both the experimental and control fields with the ground truth of Fusarium-infected ear and healthy ear, respectively. Deep learning approaches (pretrained YOLOv5 and DeepMAC on Global Wheat Head Detection (GWHD) dataset) were used to segment wheat ears and XGBoost was used to analyze the hyperspectral information related to the wheat ears and make predictions of Fusarium-infected wheat ear and healthy wheat ear. The results showed that deep learning methods can automatically detect and segment the ears of wheat by applying pretrained models. The predictive model can accurately detect infected areas in a wheat field, achieving mean accuracy and F1 scores exceeding 89%. The proposed model, Sága, could facilitate the early detection of Fusarium spp. to increase the fungicide use efficiency and limit mycotoxin contamination.

Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn) is a crop of significant interest due to its nutritional value and resilience to drought conditions. However, drought, particularly following flowering, is a major factor contributing to yield reduction. This research employed two distinct Tartary buckwheat genotypes to investigate the effects of post-anthesis drought on growth and physicochemical characteristics. The study aimed to elucidate the response of Tartary buckwheat to drought stress. The findings indicated that post-anthesis drought adversely impacted the growth, morphology, and biomass accumulation of Tartary buckwheat. Drought stress enhanced the maximum photosynthetic capacity (Fv/Fm) and light protection ability (NPQ) of the ‘Xiqiao-2’ genotype. In response to drought stress, ‘Dingku-1’ and ‘Xiqiao-2’ maintained osmotic balance by accumulating soluble sugars and proline, respectively. Notably, ‘Xiqiao-2’ exhibited elevated levels of flavonoids and polyphenols in its leaves, which helped mitigate oxidative damage caused by drought. Furthermore, rewatering after a brief drought period significantly improved plant height, stem diameter, and biomass accumulation in ‘Dingku-1’. Overall, ‘Xiqiao-2’ demonstrated greater long-term tolerance to post-anthesis drought, while ‘Dingku-1’ was less adversely affected by short-term post-anthesis drought.

Accurate prediction of reservoir landslide displacements is crucial for early warning and hazard prevention. Current machine learning (ML) paradigms for predicting landslide displacement demonstrate superior performance, while often relying on various feature engineering techniques, such as decomposing into different temporal lags and feature selection. This study investigates the impact of various feature selection techniques on the performance of ML algorithms for landslide displacement prediction. The Shuping and Baishuihe landslides in China’s Three Gorges Reservoir Area are used to comprehensively benchmark four prevalent ML algorithms. Both static ML models, including backpropagation neural network (BPNN), support vector machine (SVM), and dynamic models, such as long short-term memory (LSTM), and gated recurrent unit (GRU), are included. Each ML model is evaluated under three feature engineering techniques: raw multivariate time series, and feature selection under maximal information coefficient-partial autocorrelation function (MIC-PACF), or grey relational analysis-PACF (GRA-PACF). The results demonstrate that appropriate feature selection methods could significantly improve the performance of static ML models. In contrast, dynamic models effectively leverage inherent capabilities in capturing temporal dynamics within raw multivariate time series, seeing marginal gains with extensive feature engineering compared to no feature selection strategy. The optimal feature selection approach varies based on the ML model and specific landslide, highlighting the importance of case-specific assessments. The findings in this study offer guidance on integrating feature selection techniques with different machine learning models to maximize the robustness and generalizability of data-driven landslide displacement prediction frameworks.

In China, the Liaodong Peninsula is an important growing area for blueberries because of the high organic matter content in the soil, the abundance of light, and the large temperature difference between day and night. However, the low temperature and relative humidity of the air during the winter and early spring in the Liaodong Peninsula are the main reasons for the damage to blueberry plants. Here, we documented the transcriptome and proteome dynamics in response to cold stress in three blueberry cultivars (‘Northland’, ‘Bluecrop’, and ‘Berkeley’). Functional enrichment analysis indicated that many differentially expressed genes (DEGs) and differentially abundant proteins (DAPs) were mainly involved in the pathways of protein processing in the endoplasmic reticulum, the glutathione metabolism pathway, and ribosomes. We identified 12,747 transcription factors (TFs) distributed in 20 families. Based on our findings, we speculated that cold tolerance development was caused by the expression of calcium-related genes (CDPKs and CMLs), glutathione proteins, and TFs (NAC, WRKY, and ERF). Our investigation found that three cultivars experienced cold damage when exposed to temperatures between −9 °C and −15 °C in the field. Therefore, the cold resistance of blueberries during overwintering should not only resist the influence of low temperatures but also complex environmental factors such as strong winds and low relative humidity in the air. The order of cold resistance strength in the three blueberry cultivars was ‘Berkeley’, ‘Bluecrop’, and ‘Northland’. These results provide a comprehensive profile of the response to cold stress, which has the potential to be used as a selection marker for programs to improve cold tolerance in blueberries.

This prospective crossover study aimed to investigate the effect of binaural beat therapy music on soccer player performance. Between July 2023 and December 2023, 45 athletes (31 females/14 males, mean age = 20.47 ± 0.99) wore Bluetooth earphones through which one of the following was given during initial 20 min warm-up exercises before undergoing repeated sprint ability tests: no music/fast-tempo music/fast-tempo music with background binaural beat therapy music. Heart rate change after warm-up exercises/repeated sprint ability (RSA) tests and the time to finish RSA tests were recorded. Despite no significant difference in heart rate increase after warm-up between the two genders regardless of intervention, larger increases after RSA tests were found in males following any of the three interventions (all p < 0.01) with the most notable difference observed after fast-tempo music (p < 0.0001). A significant effect size (r = 0.2) correlated with fast-tempo music during warm-up in either gender. Binaural beat therapy music during warm-up reached a significant effect size only when all participants were considered, suggesting limited benefits.

Steel structures with light weight, high rigidity, and easy assembly have become the first choice for large-span complex building materials. At the same time, transparent materials are widely used for the sake of practicality and aesthetics. However, steel structures will be deformed due to changes in temperature, which will affect the accuracy of closure. The components are restricted from free deformation as a result of multiple statically indeterminate structures. A safety hazard will occur if the residual temperature stress is not released. At present, the strain law of open-air steel structures caused by temperature change is still unclear, and the corresponding temperature–strain model has not been established. This paper is based on the third-phase reconstruction and expansion project of Taiyuan Wusu Airport in Xiaodian District, Taiyuan City, Shanxi Province (37°45′ N, 112°38′ E, average altitude of 774 m), winter long time series temperature measured data, deduced daily temperature change laws, and the established relationship model between air temperature and steel surface temperature. Based on the measured data of long-term stress and strain in winter, the strain law of open-air steel columns under temperature change is discussed. According to the results, the air temperature can be utilized to determine the strain of the open-air steel column during winter. The determination coefficient of the temperature–stress model can reach 0.868, and the radial bending stress caused by the change in daily temperature cannot be ignored, accounting for 15.7% of the radial stress at the same time, which can provide a reference for stress calculations of similar structures.

Bog bilberry (Vaccinium uliginosum L.) is considered a highly valued non-wood forest product (NWFP) species with edible and medicinal uses in East Asia. It grows in the northeastern forests of China, where stand attributes and structure jointly determine its population characteristics and individuals’ growth. Mapping the regional distributions of its population characteristics can be beneficial in the management of its natural resources, and this mapping should be predicted using machine learning modeling to obtain accurate results. In this study, a total of 60 stands were randomly chosen and screened to investigate natural bog bilberry populations in the eastern mountains of Heilongjiang and Jilin provinces in northeastern China. Individual height, canopy cover area, and fresh weight all increased in stands at higher latitudes, and shoot height was also higher in the eastern stands. The rootstock grove density showed a polynomial quadratic distribution pattern along increasing topographical gradients, resulting in a minimum density of 0.43–0.52 groves m−2 in stands in the southern part (44.3016° N, 129.4558° E) of Heilongjiang. Multivariate linear regression indicated that the bog bilberry density was depressed by host forest tree species diversity; this was assessed using both the Simpson and Shannon–Wiener indices, which also showed polynomial quadratic distribution patterns (with a modeling minimum of 0.27 and a maximum of 1.21, respectively) in response to the increase in latitude. Structural equation models identified positive contributions of tree diameter at breast height and latitude to shoot height and a negative contribution of longitude to the bog bilberry canopy area. Random forest modeling indicated that dense populations with heavy individuals were distributed in eastern Heilongjiang, and large-canopy individuals were distributed in Mudanjiang and Tonghua. In conclusion, bog bilberry populations showed better attributes in northeastern stands where host forest trees had low species diversity, but the dominant species had strong trunks.

Increased usage of selective laser sintering (SLS) for the production of end-use functional components has generated a requirement of developing new materials and process improvements to improve the applicability of this technique. This article discusses a novel process wherein carbon black was applied to the surface of TPU powder to reduce the laser reflectivity during the SLS process. The printing was carried out with a preheating temperature of 75 °C, laser energy density of 0.028 J/mm2, incorporating a 0.4 wt % addition of carbon black to the TPU powder, and controlling the powder layer thickness at 125 μm. The mixed powder, after printing, shows a reflectivity of 13.81%, accompanied by the highest average density of 1.09 g/cm3, hardness of 78 A, tensile strength of 7.9 MPa, and elongation at break was 364.9%. Compared to commercial TPU powder, which lacks the carbon black coating, the reflectance decreased by 1.78%, mechanical properties improved by 33.9%, and there was a notable reduction in the porosity of the sintered product.

Remote patient-monitoring systems are helpful since they can provide timely and effective healthcare facilities. Such online telemedicine is usually achieved with the help of sophisticated and advanced wearable sensor technologies. The modern type of wearable connected devices enable the monitoring of vital sign parameters such as: heart rate variability (HRV) also known as electrocardiogram (ECG), blood pressure (BLP), Respiratory rate and body temperature, blood pressure (BLP), respiratory rate, and body temperature. The ubiquitous problem of wearable devices is their power demand for signal transmission; such devices require frequent battery charging, which causes serious limitations to the continuous monitoring of vital data. To overcome this, the current study provides a primary report on collecting kinetic energy from daily human activities for monitoring vital human signs. The harvested energy is used to sustain the battery autonomy of wearable devices, which allows for a longer monitoring time of vital data. This study proposes a novel type of stress- or exercise-monitoring ECG device based on a microcontroller (PIC18F4550) and a Wi-Fi device (ESP8266), which is cost-effective and enables real-time monitoring of heart rate in the cloud during normal daily activities. In order to achieve both portability and maximum power, the harvester has a small structure and low friction. Neodymium magnets were chosen for their high magnetic strength, versatility, and compact size. Due to the non-linear magnetic force interaction of the magnets, the non-linear part of the dynamic equation has an inverse quadratic form. Electromechanical damping is considered in this study, and the quadratic non-linearity is approximated using MacLaurin expansion, which enables us to find the law of motion for general case studies using classical methods for dynamic equations and the suitable parameters for the harvester. The oscillations are enabled by applying an initial force, and there is a loss of energy due to the electromechanical damping. A typical numerical application is computed with Matlab 2015 software, and an ODE45 solver is used to verify the accuracy of the method.

In this paper, based on Meyerhof’s theory of homogeneous foundation, the limit equilibrium analysis method and unified logarithmic spiral sliding surface assumption are used to derive the theoretical formula for the ultimate bearing capacity of a layered foundation when the foundation is completely rough. It should be noted that this formula is only applicable to strip foundations of upper soft clay and lower sandy soil. In addition, a comparative analysis is conducted between theoretical formulas and semiempirical formulas for layered foundations. On the basis of verifying the reliability of the theoretical formula results, numerical simulation is carried out to further explore and analyze the influence of the width to depth ratio of the foundation, the strength parameters of the double-layer soil, and the thickness of the upper soft soil on the bearing capacity of the foundation. Research has shown that the formula for the bearing capacity of a layered foundation derived in this paper has a certain degree of error compared to Meyerhof’s semiempirical formula, but it is in good agreement with numerical simulation results and Hansen’s weighted average method results. The ratio of the width to depth of the foundation, the ratio of the cohesive force of the double-layer soil, and the tangent ratio of the internal friction angle have a significant positive correlation with the ultimate bearing capacity of the foundation. The increase in thickness of the overlying cohesive soil has a negative impact on the ultimate bearing capacity of the foundation, and the thicker the soil, the smaller the foundation’s bearing capacity.

Due to the limited availability of fault samples and the expensive nature of marking fault samples in Electric Multiple Unit (EMU) gearbox monitoring data, a study was conducted to simulate the degradation process of key components in the CRH5 gearbox using rigid–flexible coupling dynamics. Vibration acceleration data from the simulation were utilized to create a six-dimensional hybrid feature domain representing the degradation process. By leveraging the capabilities of the Hidden Markov Model (HMM) for handling hidden transitive probabilities in temporal data and Gated Recurrent Unit (GRU) for addressing long-distance and high-dependence temporal data, a GRU-HMM fault prediction model was developed. This model was validated using monitoring data and the six-dimensional hybrid feature domain from the CRH5 gearbox and compared against actual maintenance records. The findings indicated that the GRU-HMM fault prediction model can effectively recognize the degradation patterns of multiple components, offering higher accuracy in fault prediction compared to traditional models. These research outcomes are expected to optimize EMU maintenance schedules based on usage conditions, enhance EMU utilization rates, and reduce operational and maintenance costs, thereby providing valuable theoretical support.

The WRKY gene family is a key transcription factor family for plant development and the stress response. However, few studies have investigated the WRKY gene family in Chinese rose (Rosa chinensis). In this study, 68 RcWRKY genes were identified from the Chinese rose genome and classified into three primary groups and five subgroups based on the structural and phylogenetic characteristics. The analysis of the conserved domains, motifs, and gene structure revealed that the RcWRKY genes within the same group had the same exon–intron organization and composition. Chromosome mapping and gene duplication revealed that the RcWRKY genes were randomly dispersed across seven chromosomes. Fragment duplication and refined selection may have influenced the evolution of the WRKY gene family in Chinese rose. The cis-acting elements in the WRKY promoter region revealed that the RcWRKY genes contained numerous abiotic stress response elements. The results of qRT-PCR revealed that the expression of RcWRKY was tissue-specific, with high expression being observed under drought, heat, and salt stress. Notably, RcWRKY49′s expression increased more than fivefold following salt stress, indicating that it is a crucial gene mediating the salt stress response of Chinese rose. These findings shed light on the regulatory role of RcWRKY in the growth and development of Chinese rose, and they serve as a foundation for future molecular breeding programs and gene discovery.

NASH (non-alcoholic steatohepatitis) is a severe liver disease characterized by hepatic chronic inflammation that can be associated with the gut microbiota. In this study, we explored the therapeutic effect of Gynostemma pentaphyllum extract (GPE), a Chinese herbal extract, on methionine- and choline-deficient (MCD) diet-induced NASH mice. Based on the peak area, the top ten compounds in GPE were hydroxylinolenic acid, rutin, hydroxylinoleic acid, vanillic acid, methyl vanillate, quercetin, pheophorbide A, protocatechuic acid, aurantiamide acetate, and iso-rhamnetin. We found that four weeks of GPE treatment alleviated hepatic confluent zone inflammation, hepatocyte lipid accumulation, and lipid peroxidation in the mouse model. According to the 16S rRNA gene V3–V4 region sequencing of the colonic contents, the gut microbiota structure of the mice was significantly changed after GPE supplementation. Especially, GPE enriched the abundance of potentially beneficial bacteria such as Akkerrmansia and decreased the abundance of opportunistic pathogens such as Klebsiella. Moreover, RNA sequencing revealed that the GPE group showed an anti-inflammatory liver characterized by the repression of the NF-kappa B signaling pathway compared with the MCD group. Ingenuity Pathway Analysis (IPA) also showed that GPE downregulated the pathogen-induced cytokine storm pathway, which was associated with inflammation. A high dose of GPE (HGPE) significantly downregulated the expression levels of the tumor necrosis factor-α (TNF-α), myeloid differentiation factor 88 (Myd88), cluster of differentiation 14 (CD14), and Toll-like receptor 4 (TLR4) genes, as verified by real-time quantitative PCR (RT-qPCR). Our results suggested that the therapeutic potential of GPE for NASH mice may be related to improvements in the intestinal microenvironment and a reduction in liver inflammation.

Officers on Watch (OOWs) of the ship’s bridge play a vital role in maritime navigation safety, monitoring the ship’s navigational status, and ensuring maritime safety. The status of inactive watch officers, such as fatigued driving and negligence on lookout, is one of the main causes of accidents. Intelligent technology for real-time perception and state evaluation of ship OOWs significantly reduces accidents caused by human factors. The traditional computer vision method is difficult to adapt to the complex environment of a ship bridge, and carries strong privacy risks. With the development of Internet of Things technology, sensing technology based on ubiquitous Wi-Fi devices provides a new way to accurately monitor the status of ship OOWs. In this paper, we use commercial off-the-shelf (COTS) Wi-Fi devices to propose a ship driving activity state detection method based on beamforming feedback information (BFI). Using wireless sensing data to sense the number of OOWs and their driving behavior realizes low-cost and high-precision detection of the behavioral status of the ship’s bridge watchkeeper. Experiments were conducted in a ship-driving simulation laboratory and on a real-world Yangtze River cruise ship. The experimental results demonstrate that our proposed method achieves 92.4% and 98.1% accuracy for tracking active status and estimating the number of OOWs, respectively.

In order to study the adsorption process and adsorption characteristics of shale oil at the macro scale, the isothermal adsorption experiments of illite and kerogen on a heptadecane (oil phase) solution were carried out by infrared spectrophotometry and gas chromatography–mass spectrometry. Based on the adsorption isotherm model and adsorption thermodynamic model, the characteristics of heptadecane adsorbed by illite and kerogen at different temperatures and oily solution concentrations were studied. The experimental results show that the concentration and temperature of the alkane solution help to enhance the adsorption and increase the saturated adsorption capacity. The difference is that the concentration will have a certain effect on the adsorption rate, while the temperature will not. Based on the three adsorption isotherm models, it was found that Langmuir and Freundlich were more suitable for describing the adsorption process of the heptadecane solution by illite and kerogen, and the adsorption characteristics of heptadecane molecules at different temperatures and adsorbents were evaluated. Heating leads to an increase in the collision efficiency between adsorbate molecules and adsorbents, thereby accelerating the migration rate of alkanes. Therefore, increasing temperature helps to enhance the adsorption capacity of rocks and increase the saturated adsorption capacity of minerals. The research results clarify the adsorption characteristics of shale oil heavy components from the macro level and fill the research gap in the application of solid–liquid isothermal adsorption physical experiments on the adsorption and occurrence of shale oil.

Single-shot dual-wavelength interferometry offers a promising avenue for surface profile measurement of dynamic objects. However, current techniques employing pixel multiplexing or color cameras encounter challenges such as complex optical alignment, limited measurement range, and difficulty in measuring rough surfaces. To address these issues, this study presents a novel approach to single-shot dual-wavelength interferometry. By utilizing separated polarization illumination and detection, along with a monochromatic polarization camera and two slightly different wavelengths, this method enables the simultaneous recording of two frames of separated interferometric patterns. This approach facilitates straightforward optical alignment, expands measurement ranges, accelerates data acquisition, and simplifies data processing for dual-wavelength interferometry. Consequently, it enables online shape measurement of large dynamic samples with rough surfaces.

Rabies virus (RABV) is a neurotropic virus that causes fatal neurological disease, raising serious public health issues and attracting extensive attention in society. To elucidate the molecular mechanism of RABV-induced neuronal damage, we used hematoxylin–eosin staining, transmission electron microscopy, transcriptomics analysis, and immune response factor testing to investigate RABV-infected neurons. We successfully isolated the neurons from murine brains. The specificity of the isolated neurons was identified by a monoclonal antibody, and the viability of the neurons was 83.53–95.0%. We confirmed that RABV infection induced serious damage to the neurons according to histochemistry and transmission electron microscope (TEM) scanning. In addition, the transcriptomics analysis suggested that multiple genes related to the pyroptosis pathway were significantly upregulated, including gasdermin D (Gsdmd), Nlrp3, caspase-1, and IL-1β, as well as the chemokine genes Ccl2, Ccl3, Ccl4, Ccl5, Ccl7, Ccl12, and Cxcl10. We next verified this finding in the brains of mice infected with the rRC-HL, GX074, and challenge virus standard strain-24 (CVS-24) strains of RABV. Importantly, we found that the expression level of the Gsdmd protein was significantly upregulated in the neurons infected with different RABV strains and ranged from 691.1 to 5764.96 pg/mL, while the basal level of mock-infected neurons was less than 100 pg/mL. Taken together, our findings suggest that Gsdmd-induced pyroptosis is involved in the neuron damage caused by RABV infection.

In response to the inefficiencies and high costs associated with manual buoy inspection, this paper presents the design and testing of an Autonomous Navigation Unmanned Surface Vehicle (USV) tailored for this purpose. The research is structured into three main components: Firstly, the hardware framework and communication system of the USV are detailed, incorporating the Robot Operating System (ROS) and additional nodes to meet practical requirements. Furthermore, a buoy tracking system utilizing the Kernelized Correlation Filter (KCF) algorithm is introduced. Secondly, buoy image training is conducted using the YOLOv7 object detection algorithm, establishing a robust model for accurate buoy state recognition. Finally, an improved Line-of-Sight (LOS) method for USV path tracking, assuming the presence of an attraction potential field around the inspected buoy, is proposed to enable a comprehensive 360-degree inspection. Experimental testing includes validation of buoy image target tracking and detection, assessment of USV autonomous navigation and obstacle avoidance capabilities, and evaluation of the enhanced LOS path tracking algorithm. The results demonstrate the USV’s efficacy in conducting practical buoy inspection missions. This research contributes insights and advancements to the fields of maritime patrol and routine buoy inspections.

Space–time adaptive processing (STAP) is an effective technology in clutter suppression and moving target detection for airborne radar. When working in the heterogeneous environment, the number of training samples that satisfy independent and identically distributed (IID) conditions is insufficient, making it difficult to ensure the estimation accuracy of the clutter plus noise covariance matrix for traditional STAP methods. Sparse recovery–based STAP (SR–STAP) methods have received widespread attention in the past few years. The accurate estimation of the clutter plus noise covariance matrix can be achieved using only a few training samples. The iterative adaptive approach (IAA) can quickly and accurately estimate the power spectrum, but applying this method directly to the STAP method cannot produce good performance. In this paper, a fast IAA–based SR–STAP method is proposed. Based on the weighted l1 problem, the IAA spectrum is used as a weighted term to obtain a good approximation. In order to obtain an analytical solution, we use the weighted l2 norm to approximate the weighted l1 norm without loss of performance. Compared with the IAA–STAP method, the proposed method is more robust to errors. Moreover, the proposed method has a fast computational speed. The effectiveness of the proposed method is demonstrated by simulations.

At present, most studies use the direct method to analyze the oscillation problem of modern power systems. However, these studies often only simplify the external characteristics of the wind turbine and lack an in-depth understanding of its internal refined energy structure. In this paper, based on the direct-drive permanent magnetic synchronous generator’s detailed model (D-PMSG), combined with the dynamic energy of its port, layers of analysis are performed on the wind turbine’s internal connections, and a detailed model of the energy structure is created. Then, the interaction mechanism of each control link in the wind turbine is analyzed by combining the energy function of the wind turbine with the improved perturbation method. Finally, this paper constructs a sub-synchronous oscillation (SSO) scenario of weak damping and a forcing type and proves the accuracy and effectiveness of the traceability method based on the refined energy of D-PMSG. This traceability method based on refined energy is expected to provide a new solution to the stability problem caused by the integration of new energy.

Meat color traits directly influence consumer acceptability and purchasing decisions. Nevertheless, there is a paucity of comprehensive investigation into the genetic mechanisms underlying meat color traits in pigs. Utilizing genome-wide association studies (GWAS) on five meat color traits and the detection of selection signatures in pig breeds exhibiting distinct meat color characteristics, we identified a promising candidate SNP, 6_69103754, exhibiting varying allele frequencies among pigs with different meat color characteristics. This SNP has the potential to affect the redness and chroma index values of pork. Moreover, transcriptome-wide association studies (TWAS) analysis revealed the expression of candidate genes associated with meat color traits in specific tissues. Notably, the largest number of candidate genes were observed from transcripts derived from adipose, liver, lung, spleen tissues, and macrophage cell type, indicating their crucial role in meat color development. Several shared genes associated with redness, yellowness, and chroma indices traits were identified, including RINL in adipose tissue, ENSSSCG00000034844 and ITIH1 in liver tissue, TPX2 and MFAP2 in lung tissue, and ZBTB17, FAM131C, KIFC3, NTPCR, and ENGSSSCG00000045605 in spleen tissue. Furthermore, single-cell enrichment analysis revealed a significant association between the immune system and meat color. This finding underscores the significance of the immune system associated with meat color. Overall, our study provides a comprehensive analysis of the genetic mechanisms underlying meat color traits, offering valuable insights for future breeding efforts aimed at improving meat quality.

Heat shock proteins (HSPs) play important roles in plant stress resistance, but it is not clear whether small molecular HSPs (sHSPs) are involved in the cold stress resistance of lily flowers. In this study, we cloned LbHSP17.9 and found that its expression was up-regulated under cold stress. When LbHSP17.9 was silenced (TRV2::LbHSP17.9) using virus-induced gene silencing in cut lily flowers, the content of malondialdehyde was increased under 4 °C stress treatment. The catalase (CAT) activity in TRV2::LbHSP17.9 was significantly lower than in TRV2 in the first 7 days, and the peroxidase (POD) activity in TRV2::LbHSP17.9 was significantly lower than in TRV2 after 4 days of 4 °C stress. Further analysis showed that the transcription levels of LbCu/ZnSOD, LbMnSOD and LbCAT in TRV2::LbHSP17.9 were lower than those of TRV2 under 4 °C stress. When LbHSP17.9 was overexpressed in lily petal disks, the OE-LbHSP17.9 disks faded later than the controls at 4 °C and the relative conductivity decreased significantly. Overexpression of LbHSP17.9 in Arabidopsis thaliana resulted in fewer injury symptoms and lower MDA content than wild type under 4 °C stress. Therefore, we speculate that LbHSP17.9 can improve the resistance of lily flowers to cold stress.

This study pioneered a non-destructive testing approach to evaluating the physicochemical properties of golden passion fruit by developing a platform to analyze the fruit’s electrical characteristics. By using dielectric properties, the method accurately predicted the soluble solids content (SSC), Acidity and pulp percentage (PP) in passion fruit. The investigation entailed measuring the relative dielectric constant (ε′) and dielectric loss factor (ε″) for 192 samples across a spectrum of 34 frequencies from 0.05 to 100 kHz. The analysis revealed that with increasing frequency and fruit maturity, both ε′ and ε″ showed a declining trend. Moreover, there was a discernible correlation between the fruit’s physicochemical indicators and dielectric properties. In refining the dataset, 12 outliers were removed using the Local Outlier Factor (LOF) algorithm. The study employed various advanced feature extraction techniques, including Recursive Feature Elimination with Cross-Validation (RFECV), Permutation Importance based on Random Forest Regression (PI-RF), Permutation Importance based on Linear Regression (PI-LR) and Genetic Algorithm (GA). All the variables and the selected variables after screening were used as inputs to build Extreme Gradient Boosting (XGBoost) and Categorical Boosting (Cat-Boost) models to predict the SSC, Acidity and PP in passion fruit. The results indicate that the PI-RF-XGBoost model demonstrated superior performance in predicting both the SSC (R2 = 0.9240, RMSE = 0.2595) and the PP (R2 = 0.9092, RMSE = 0.0014) of passion fruit. Meanwhile, the GA-CatBoost model exhibited the best performance in predicting Acidity (R2 = 0.9471, RMSE = 0.1237). In addition, for the well-performing algorithms, the selected features are mainly concentrated within the frequency range of 0.05–6 kHz, which is consistent with the frequency range highly correlated with the dielectric properties and quality indicators. It is feasible to predict the quality indicators of fruit by detecting their low-frequency dielectric properties. This research offers significant insights and a valuable reference for non-destructive testing methods in assessing the quality of golden passion fruit.

Alcoholic liver disease (ALD) is the main factor that induces liver-related death worldwide and represents a common chronic hepatopathy resulting from binge or chronic alcohol consumption. This work focused on revealing the role and molecular mechanism of nodakenin (NK) in ALD associated with hepatic inflammation and lipid metabolism through the regulation of Nur77-P2X7r signaling. In this study, an ALD model was constructed through chronic feeding of Lieber–DeCarli control solution with or without NK treatment. Ethanol (EtOH) or NK was administered to AML-12 cells, after which Nur77 was silenced. HepG2 cells were exposed to ethanol (EtOH) and subsequently treated with recombinant Nur77 (rNur77). Mouse peritoneal macrophages (MPMs) were treated with lipopolysaccharide/adenosine triphosphate (LPS/ATP) and NK, resulting in the generation of conditioned media. In vivo, histopathological alterations were markedly alleviated by NK, accompanied by reductions in serum triglyceride (TG), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) levels and the modulation of Lipin-1, SREBP1, and Nur77 levels in comparison to the EtOH-exposed group (p < 0.001). Additionally, NK reduced the production of P2X7r and NLRP3. NK markedly upregulated Nur77, inhibited P2X7r and Lipin-1, and promoted the function of Cytosporone B, a Nur77 agonist (p < 0.001). Moreover, Nur77 deficiency weakened the regulatory effect of NK on P2X7r and Lipin-1 inhibition (p < 0.001). In NK-exposed MPMs, cleaved caspase-1 and mature IL-1β expression decreased following LPS/ATP treatment (p < 0.001). NK also decreased inflammatory-factor production in primary hepatocytes stimulated with MPM supernatant. NK ameliorated ETOH-induced ALD through a reduction in inflammation and lipogenesis factors, which was likely related to Nur77 activation. Hence, NK is a potential therapeutic approach to ALD.

Legubicin, a novel prodrug based on doxorubicin, has both albumin-binding and legumain-activating properties. The aim of this study was to develop and validate a UHPLC-MS/MS method for investigating the in vivo pharmacokinetics and tissue distribution profiles of legubicin in rats and tumor-bearing mice following intravenous administration, and to compare this prodrug with the positive control drug doxorubicin. The study employed a UHLC-MS/MS method to determine the levels of albumin-bound of legubicin and two metabolites (free Leu-DOX and DOX) in plasma, tumor, and tissue samples. This method was validated for good selectivity, high sensitivity, excellent extraction recovery, and short run time. The results showed that legubicin was present in the circulation in vivo mainly in a protein-bound form with larger AUC values and lower clearance and distribution, and essentially released small amounts of doxorubicin. Compared to administration of equimolar doses of doxorubicin, legubicin showed increased exposure of the active drug in the tumor and decreased the level of the active drug in the heart and kidney. This study provides valuable information on the pharmacokinetics and tissue distribution of legubicin, implicating its potential as a novel and effective drug candidate for anti-cancer therapies.

This study investigated the influence of Fe content on the microstructure and mechanical properties of Ti–6Al–4V(TC4) + 25Ti alloys prepared by low-energy-density direct energy deposition (DED) technology. With the incorporation of the Fe elements, the α-Ti phases exhibited significant changes in size and morphology, while the numerous β-Ti phases and some triclinic-Ti precipitates were retained. With the refinement of the α-Ti phase, retainment of the β-Ti phase and the presence of triclinic-Ti precipitates, the mechanical properties of DED samples can be significantly improved compared with DED TC4 alloys. The room-temperature mechanical property tests showed that the ultimate tensile strength (UTS) of 3Fe + TC4 + 25Ti achieved 1298.64 ± 5.26 MPa with an elongation of 4.82% ± 0.20%, and the maximum elongation of 1Fe + TC4 + 25Ti reached 10.82% ± 0.82% with a UTS of 1076.95 ± 11.69 MPa. The strengthening mechanism of DED Ti-Al-V-Fe alloys were further discussed, providing new insights into the microstructure control and the composition design of additive manufacturing of Ti alloys.

This study analyzed the differences in ozone (O3) sensitivity in four different urban areas in China from February 2019 to January 2020 based on data on various near-surface pollutants from passive multi-axis differential optical absorption spectroscopy (MAX-DOAS) sites and nearby China National Environmental Monitoring Center (CNEMC) sites. Across the four cities, the nitrogen dioxide (NO2) and formaldehyde (HCHO) concentrations varied seasonally. Xianghe consistently displayed the lowest NO2 levels, suggesting reduced emissions compared to other cities. Guangzhou, a city with a robust economy and a high level of vehicle ownership, exhibited higher concentrations in spring. Summer brought elevated HCHO levels in Guangzhou, Xianghe, and Shenyang due to intensified photochemical processes. Autumn and winter showed higher HCHO concentrations in Guangzhou and Xianghe compared to Lanzhou and Shenyang. Overall, Guangzhou recorded the highest annual averages, due to its developed economy, while Xianghe’s lower NO2 levels were offset by the elevated HCHO due to higher O3 values. The analysis delved into primary and secondary HCHO sources across seasons and used carbon monoxide (CO) and O3 data. Xianghe showcased the dominance of secondary sources in summer and autumn, while Lanzhou was characterized by primary dominance throughout the year. Shenyang mirrored Xianghe’s evolution due to industrial emissions. In Guangzhou, due to the high levels of vehicular traffic and sunlight conditions, secondary sources predominantly influenced HCHO concentrations. These findings highlight the interplay between primary and secondary emissions in diverse urban settings. This study explored O3 sensitivity variations across seasons. Xianghe exhibited a balanced distribution among volatile organic compound (VOC)-limited conditions, nitrogen oxide (NOx)-limited conditions, and transitional influences. Lanzhou was mainly affected by VOC-limited conditions in winter and NOx-limited conditions in other seasons. Shenyang’s sensitivity varied with the seasons and was primarily influenced by transitions between VOCs and NOx in autumn and NOx-limited conditions otherwise. Guangzhou experienced varied influences. During periods of high O3 pollution, all regions were affected by NOx-limited conditions, indicating the necessity of NOx monitoring in these areas, especially during summer in all regions and during autumn in Xianghe and Guangzhou.

Adolescent Idiopathic Scoliosis is a 3D spinal deformity commonly characterized by serial radiographs. Patients with AIS may have increased average radiation exposure compared to unaffected patients and thus may be implicated with a modest increase in cancer risk. To minimize lifetime radiation exposure, alternative imaging modalities such as surface topography are being explored. Surface topography (ST) uses a camera to map anatomic landmarks of the spine and contours of the back to create software-generated spine models. ST has previously shown good correlation to radiographic measures. In this study, we sought to use ST in the creation of a risk stratification model. A total of 38 patients met the inclusion criteria for curve progression prediction. Scoliotic curves were classified as progressing, stabilized, or improving, and a predictive model was created using the proportional odds logistic modeling. The results showed that surface topography was able to moderately appraise scoliosis curvatures when compared to radiographs. The predictive model, using demographic and surface topography measurements, was able to account for 86.9% of the variability in the future Cobb angle. Additionally, attempts at classification of curve progression, stabilization, or improvement were accurately predicted 27/38 times, 71%. These results provide a basis for the creation of a clinical tool in the tracking and prediction of scoliosis progression in order to reduce the number of X-rays required.

Recent works have experimentally proven that metal matrix composites (MMCs) with network architecture present improved strength–ductility match. It is envisaged that the performance of architecturally designed composites is particularly sensitive to reinforcement strength. Here, reinforcing particles with various fracture strengths were introduced in numerical models of composites with network particle distribution. The results revealed that a low particle strength (1 GPa) led to early-stage failure and brittle fracture. Nevertheless, a high particle strength (5 GPa) delayed the failure behavior and led to ductile fracture at the SiC/Al–Al macro-interface areas. Therefore, the ultimate tensile strengths (UTS) of the network SiC/Al composites increased from 290 to 385 MPa, with rising particle strength from 1 to 5 GPa. Based on the composite property, different particle fracture threshold strengths existed for homogeneous (~2.7 GPa) and network (~3.7 GPa) composites. The higher threshold strength in network composites was related to the increased stress concentration induced by network architecture. Unfortunately, the real fracture strength of the commercial SiC particle is 1–2 GPa, implying that it is possible to select a high-strength particle necessary for efficient network architecture design.

In this paper, an improved robust line-of-sight (RLOS) guidance-based fuzzy sliding mode controller is presented to control underactuated ships to conduct the cooperative maritime search operation under the presented improved creeping line search method. First, considering that the ship cannot perform turning with corners, an improved creeping line search method is presented by integrating the Bezier method into the traditional creeping line search method to smooth the transition points with corners and employing the cubic spline interpolation method to generate continuous reference paths. Second, an improved RLOS guidance method is presented for the first time by exploring the idea of robust adaptive control to mitigate the chattering effect of the RLOS guidance. Third, the fuzzy logic system with approximate ability is integrated into the design of sliding mode controller to handle unknown nonlinear model dynamics and environmental disturbances. Finally, an improved RLOS guidance-based fuzzy sliding mode controller is presented. The closed-loop stability is guaranteed by the Lyapunov theorem. Comparative simulations are conducted to illustrate the advantages and verify the effectiveness of the presented method.

Oral squamous cell carcinoma (OSCC) is a prevalent type of oral cancer. While therapeutic innovations have made strides, radioresistance persists as a significant hindrance in OSCC treatment. Despite identifying numerous targets that could potentially suppress the oncogenic attributes of OSCC, the exploration of oncogenic protein kinases for cancer therapy remains limited. Consequently, the functions of many kinase proteins in OSCC continue to be largely undetermined. In this research, we aim to disclose protein kinases that target OSCC and elaborate their roles and molecular mechanisms. Through the examination of the kinome library of radiotherapy-resistant/sensitive OSCC cell lines (HN12 and SAS), we identified a key gene, the tyrosine phosphorylation-regulated kinase 3 (DYRK3), a member of the DYRK family. We developed an in vitro cell model, composed of radiation-resistant OSCC, to scrutinize the clinical implications and contributions of DYRK3 and phosphoribosylaminoimidazole carboxylase and phosphoribosylaminoimidazolesuccinocarboxamide synthase (PAICS) signaling in OSCC. This investigation involves bioinformatics and human tissue arrays. We seek to comprehend the role of DYRK3 and PAICS signaling in the development of OSCC and its resistance to radiotherapy. Various in vitro assays are utilized to reveal the essential molecular mechanism behind radiotherapy resistance in connection with the DYRK3 and PAICS interaction. In our study, we quantified the concentrations of DYRK3 and PAICS proteins and tracked the expression levels of key pluripotency markers, particularly PPAT. Furthermore, we extended our investigation to include an analysis of Glut-1, a gene recognized for its linkage to radioresistance in oral squamous cell carcinoma (OSCC). Furthermore, we conducted an in vivo study to affirm the impact of DYRK3 and PAICS on tumor growth and radiotherapy resistance, focusing particularly on the role of DYRK3 in the radiotherapy resistance pathway. This focus leads us to identify new therapeutic agents that can combat radiotherapy resistance by inhibiting DYRK3 (GSK-626616). Our in vitro models showed that inhibiting PAICS disrupts purinosome formation and influences the survival rate of radiation-resistant OSCC cell lines. These outcomes underscore the pivotal role of the DYRK3/PAICS axis in directing OSCC radiotherapy resistance pathways and, as a result, influencing OSCC progression or therapy resistance. Our findings also reveal a significant correlation between DYRK3 expression and the PAICS enzyme in OSCC radiotherapy resistance.

The surface morphology of a buffer template is an important factor in the heteroepitaxial integration of optoelectronic devices with a significant lattice mismatch. In this work, InP-based long-wave infrared (~8 µm) emitting quantum cascade lasers with active region designs lattice-matched to InP were grown on GaAs and Si substrates employing InAlGaAs step-graded metamorphic buffer layers, as a means to assess the impact of surface roughness on device performance. A room-temperature pulsed-operation lasing with a relatively good device performance was obtained on a Si template, even with a large RMS roughness of 17.1 nm over 100 µm2. Such results demonstrate that intersubband-operating devices are highly tolerant to large RMS surface roughness, even in the presence of a high residual dislocation density.

The Global Navigation Satellite System Occultation Sounder II (GNOS-II) payload onboard the Chinese Fengyun-3E (FY-3E) satellite is the world’s first operational spaceborne mission that can utilize reflected signals from multiple navigation systems for Earth remote sensing. The satellite was launched into an 836-km early-morning polar orbit on 5 July 2021. Different GNSS signals show different characteristics in the observations and thus require different calibration methods. With an average data latency of less than 3 h, many near real-time applications are possible. This article first introduces the FY-3E/GNOS-II mission and instrument design, then describes the extensive calibration methods for the multi-GNSS measurements, and finally presents application results in the remote sensing of ocean surface winds, land soil moisture and sea ice extent. Especially, the ocean surface wind product has been used in operational applications such as assimilation in the numerical weather prediction model and monitoring of tropical cyclones. Currently, GNOS-II has been carried by FY-3E, FY-3F (launched in August 2023) and FY-3G (launched in April 2023). It will be also carried by future follow-on FY series and a more complete multi-GNSS reflectometry constellation will be established.

Screening and identifying the active compounds in foods are important for the development and utilization of functional foods. In this study, the anti-enteritis activity of ethanol extract from Camellia oleifera oil (PECS) was quickly evaluated using a Smurf Drosophila model and the metabolomics approach, combined with molecular docking techniques, were performed to rapidly screen and identify compounds with potential anti-enteritis activity in PECS. PECS showed good anti-enteritis activity and inhibited the activity of 5-lipoxygenase (LOX), cyclooxygenase 2 (COX-2) and inducible nitric oxide synthase (iNOS). In particular, wighteone and p-octopamine were newly identified in C. oleifera oil and were proven to have good anti-enteritis activity. The inhibitory activity of kaempferitrin (IC50 = 0.365 mmol L−1) was higher than that of wighteone (IC50 = 0.424 mmol L−1) and p-octopamine (IC50 = 0.402 mmol L−1). Of note, the IC50 value of salazosulfapyridine was 0.810 mmol L−1. Inhibition of LOX activity is likely one of the anti-enteritis mechanisms of PECS. These new findings lay the foundation for further investigations into the underlying mechanisms of anti-enteritis activity in C. oleifera oil.

Self-powered biomedical devices, which are the new vision of Internet Of Things (IOT) healthcare, are facing many technical and application challenges. Many research works have reported biomedical devices and self-powered applications for healthcare, along with various strategies to improve the monitoring time of self-powered devices or to eliminate the dependence on electrochemical batteries. However, none of these works have especially assessed the development and application of healthcare devices in an African context. This article provides a comprehensive review of self-powered devices in the biomedical research field, introduces their applications for healthcare, evaluates their status in Africa by providing a thorough review of existing biomedical device initiatives and available financial and scientific cooperation institutions in Africa for the biomedical research field, and highlights general challenges for implementing self-powered biomedical devices and particular challenges related to developing countries. The future perspectives of the aforementioned research field are provided, as well as an architecture for improving this research field in developing countries.

There has been over half a century since the discovery of hepatitis B virus (HBV) to now, but approximately 300 million patients with chronic hepatitis B (CHB) still live in the world, resulting in about one million deaths every year. Although currently approved antivirals (e.g., nucleoside analogues) are effective at reducing HBV replication, they have almost no impact on the existing HBV covalently closed circular DNA (cccDNA) reservoir. HBV cccDNA is a critical obstacle to the complete elimination of the virus via antiviral therapy. The true cure of HBV infection requires the eradication of viral cccDNA from HBV-infected cells; thus, the development of new agents directly or indirectly targeting HBV cccDNA is urgently needed due to the limitations of current available drugs against HBV infection. In this regard, it is the major focus of current anti-HBV research worldwide via different mechanisms to either inactivate/inhibit (functional cure) or eliminate (complete cure) HBV cccDNA. Therefore, this review discussed and summarized recent advances and challenges in efforts to inactivate/silence or eliminate viral cccDNA using anti-HBV agents from different sources, such as small molecules (including epigenetic drugs) and polypeptides/proteins, and siRNA or gene-editing approaches targeting/attenuating HBV cccDNA via different mechanisms, as well as future directions that may be considered in efforts to truly cure chronic HBV infection. In conclusion, no breakthrough has been made yet in attenuating HBV cccDNA, although a number of candidates have advanced into the phase of clinical trials. Furthermore, the overwhelming majority of the candidates function to indirectly target HBV cccDNA. No outstanding candidate directly targets HBV cccDNA. Relatively speaking, CCC_R08 and nitazoxanide may be some of the most promising agents to clear HBV infection in small molecule compounds. Additionally, CRISPR-Cas9 systems can directly target HBV cccDNA for decay and demonstrate significant anti-HBV activity. Consequently, gene-editing approaches targeting HBV cccDNA may be one of the most promising means to achieve the core goal of anti-HBV therapeutic strategies. In short, more basic studies on HBV infection need to be carried out to overcome these challenges.

Due to the difference of industrialization degree and meteorological conditions, there are obvious differences in the composition of air pollution between islands and inland areas. With Zhoushan (ZS) and Nanjing (NJ) representing islands and inland cities in the Yangtze River Delta, the differences in vertical distribution of atmospheric components were investigated. A combination of multi-axial differential optical absorption spectroscopy (MAX-DOAS), weather research and forecasting (WRF), and potential source contribution function (PSCF) models were used to obtain vertical distribution data for aerosols, nitrogen dioxide (NO2) and formaldehyde (HCHO), meteorological factors, and pollution sources in summer 2019. The findings indicate that, except for the aerosol extinction coefficient (AE), the atmospheric composition at the ZS site was not significantly stratified. However, the AE, NO2, and HCHO at NJ all displayed a decreasing trend with altitude. Here is the interesting finding that the ZS site has a higher AE value than the NJ site, while NJ displays higher NO2 and HCHO columns than the ZS site. This discrepancy was primarily attributable to Zhoushan City’s extremely low traffic emissions when compared to inland cities. In addition, HCHO in the YRD region was significantly affected by human activities. Analysis of potential pollution sources found that regional transport contributed to differences in atmospheric composition at different altitudes in different regions. Aerosols, NO2, and HCHO in Nanjing were significantly affected by transport in inland areas. Aerosols in Zhoushan were easily affected by transport in the Yellow Sea and East China Sea, and NO2 and HCHO were significantly affected by transport contributions from surrounding areas in inland areas. The study strongly suggests that land and sea breezes play an important role in the vertical distribution of aerosols over island regions.

Under the control of the Montreal Protocol and its amendments, hydrofluorocarbons (HCFCs) are used as temporary substitutes for ozone-depleting substances, such as chlorofluorocarbons, and are regulated for consumption and production. China plans to phase out HCFCs by 2030, and HCFC-22 (CHClF2) is currently the most abundant HCFC in the atmosphere. This study measures the vertical profiles and total columns of atmospheric HCFC-22 from January 2017 to December 2022, based on the mid-infrared solar spectra recorded by the ground-based high-resolution Fourier transform infrared (FTIR) spectrometer at the Hefei remote sensing station. The HCFC-22 total columns over Hefei increased from 2017–2018 and gradually decreased in 2018–2022, with an annual variation rate of 5.98% and −1.02% ± 0.02%, respectively. Compared with the ACE-FTS satellite independent dataset, the FTIR data indicate good consistency with the ACE-FTS data at a 5–25 km altitude, with an average relative difference of −4.38 ± 0.83% between the vertical profiles. HCFC-22 emissions in the Yangtze River Delta from 2017 to 2022 are estimated, derived from measured total columns combined with the Lagrangian transport model and the Bayesian inversion technique. In the Yangtze River Delta, HCFC-22 emissions were high in 2017, with a value of 33.3 ± 16.8 kt, and decreased from 2018 to 2022, with a minimum of 27.3 ± 13.6 kt in 2022 during the observations.

The problem of two-dimensional irregular packing involves the arrangement of objects with diverse shapes and sizes within a given area. This challenge arises across various industrial sectors, where effective packing optimization can yield cost savings, enhanced productivity, and reduced material waste. Existing methods for addressing the two-dimensional irregular packing problem encounter several challenges, such as limited computing resources, a prolonged solving time, and the propensity to converge to local optima. To address this issue, this study proposes a hybrid algorithm called the GA-LP algorithm to optimize the two-dimensional irregular packing problem in the manufacturing industry. The algorithm combines the global search capability of a genetic algorithm with the precise solving characteristics of linear programming. Matheuristics merges the advantages of metaheuristics, such as genetic algorithms, and mathematical programming, such as linear programming. The algorithm employs the no-fit-polygon technique along with the bottom-left and lowest-gravity center mixing placement strategies to acquire an initial solution via the utilization of a genetic algorithm. The algorithm then optimizes the solution obtained by the genetic algorithm using linear programming to obtain the final packing result. Experimental results, drawn from a real case involving the European Special Interest Group on Cutting and Packing (ESICUP) demonstrate that the GA-LP algorithm outperforms two hybrid algorithms from the relevant literature. Compared with recent methods, this algorithm can increase the best and average utilization rates by up to 5.89% and 4.02%, respectively, with important implications for improving work quality in areas such as packing and cutting.

This study focuses on the utilization of Aspergillus flavus(M-3) for the bioleaching mercury from coal, offering an alternative and environmentally to its clean utilization. The fungus was isolated from the soil near a high mercury coal mine in Lao Ying Shan (LYS), Guizhou. Utilizing direct mercury analysis, X-ray diffraction (XRD), and Fourier Transform-Infrared (FT-IR) analysis techniques, the transformation of mercury speciation, mineral components, and organic groups in the coal were analyzed before and after the bioleaching process. The findings of the study illustrated that the fungus M-3 exhibited a remarkable capacity for coal bioliquefaction and mercury leaching from LYS coal. Following a 15-day bioleaching process, a remarkable mercury leaching rate of 83.79% was achieved. Various forms of mercury speciation, including residue, organic matter, sulfide-bound, oxide-bound, exchangeable, and carbonate-bound forms, were released from the coal, with leaching rates ranging from 80.41% to 92.60%. XRD analysis indicated that the M-3 strain facilitated the dissolution of coal pyrite and the degradation of macromolecules, effectively loosening the coal structure. FT-IR analysis of raw and residual coal demonstrated the breakdown of the aromatic ring structure and introduced oxygen-containing functional groups by M-3. Overall, this study highlights the efficacy of bioliquefying coal using Aspergillus flavus (M-3) as a method for clean coal utilization while simultaneously bioleaching mercury.

The accurate measurement of river velocity is essential due to its multifaceted significance. In response to this demand, remote measurement techniques have emerged, including large-scale particle image velocimetry (LSPIV), which can be implemented through cameras or unmanned aerial vehicles (UAVs). This study conducted water surface velocity measurements in the Xihu River, situated in Miaoli County, Taiwan. These measurements were subjected to analysis using five distinct algorithms (PIVlab, Fudaa-LSPIV, OpenPIV, KLT-IV, and STIV) and were compared with surface velocity radar (SVR) results. In the quest for identifying the optimal parameter configuration, it was found that an IA size of 32 pixels × 32 pixels, an image acquisition frequency of 12 frames per second (fps), and a pixel size of 20.5 mm/pixel consistently yielded the lowest values for mean error (ME) and root mean squared error (RMSE) in the performance of Fudaa-LSPIV. Among these algorithms, Fudaa-LSPIV consistently demonstrated the lowest mean error (ME) and root mean squared error (RMSE) values. Additionally, it exhibited the highest coefficient of determination (R2 = 0.8053). Subsequent investigations employing Fudaa-LSPIV delved into the impact of various water surface velocity calculation parameters. These experiments revealed that alterations in the size of the interrogation area (IA), image acquisition frequency, and pixel size significantly influenced water surface velocity. This parameter set was subsequently employed in an experiment exploring the incorporation of artificial particles in image velocimetry analysis. The results indicated that the introduction of artificial particles had a discernible impact on the calculation of surface water velocity. Inclusion of these artificial particles enhanced the capability of Fudaa-LSPIV to detect patterns on the water surface.

Urban air pollution has become a regional environmental problem. In order to explore whether island areas were affected by the urban development of surrounding areas, in this paper, we systematically study the vertical distribution characteristics of atmospheric components, meteorological drivers, potential pollution sources, and the population health risks of fine particulate matter in island cities in China. The vertical profiles of three atmospheric pollutants (aerosols, NO2, and HCHO) in the lower troposphere of Huaniao Island in the East China Sea (ECS) were obtained using ground-based multi-axial differential optical absorption spectroscopy (MAX-DOAS). The results show that the aerosol extinction coefficients, NO2, and HCHO were primarily distributed at altitudes below 1 km, and the atmospheric pollutants in Zhoushan were obviously affected by high-altitude transfer. The main meteorological driving factors of aerosols, NO2, and HCHO were different at different altitudes. The key factor contributing to the high column concentrations of NO2 and HCHO in the upper air (greater than 400 m) was the transport of pollutants brought about by changes in wind speed. By exploring the main potential sources of atmospheric pollutants, it was found that the main sources of aerosols, NO2, and HCHO are coastal cities in the Yangtze River Delta, including southeast Zhejiang Province, southeast Fujian Province, Shanghai, ECS, and the Yellow Sea. Compared with aerosols and HCHO, local primary emissions are an important source of NO2, which are mainly related to industrial activities in Zhoushan Port. In addition, using the expose-response function model, the number of attributable cases of PM2.5 air pollution in Zhoushan City in 2019 accounted for 6.58% of the total population. This study enriches our understanding of the vertical distribution characteristics of atmospheric composition and health risk assessment on Chinese islands.

The mechanisms of rape straw biochar that affect the fixation of cadmium (Cd) in paddy soil by influencing redox of iron and sulfur are unclear. Several anaerobic incubation experiments were carried out using Cd-contaminated paddy soils (LY and ZZ). Rape straw biochar at pyrolysis temperatures of 450 °C (LRSB) and 800 °C (HRSB) was selected as the soil remediation agent. The electron exchange capacity and electrical conductivity were higher in HRSB than those in LRSB. The lower pe + pH in HRSB enhanced Fe oxide reduction, with a maximum increase in Fe2+ of 46.0% in ZZ. Compared to treatment without biochar (CK), the poorly crystallized Fe oxide (Feo) in HRSB increased by 16.8% in ZZ. This induced Cd bound to Fe, and Mn oxides fraction (Fe-Mn Cd) increased by 42.5%. The SO42−-S content in LRSB was 4.6 times that of HRSB. LRSB addition increased acid-volatile sulfide by 46.4% and 48.9% in LY and ZZ soils, respectively, compared to CK. This resulted in an increase in sulfide’s contribution to Cd fixation, with values rising from 24.2% to 37.8% in LY and 19.1% to 29.8% in ZZ. Overall, LRSB reduced Cd mobility by forming more sulfide, while HRSB increased Fe-Mn Cd by increasing Feo.

A novel Gram-stain-negative, facultatively anaerobic, and non-motile bacterial strain, designated SDUM287046T, was isolated from the coastal sediments of Jingzi Port of Weihai, China. Cells of strain SDUM287046T were rod-shaped with widths of 0.4–0.5 μm and lengths of 0.7–1.4 μm and could produce flexirubin-type pigments. Optimum growth of strain SDUM287046T occurred at 33–35 °C, pH 7.0, and with 2% (w/v) NaCl. Oxidase activity was negative, but catalase activity was positive. Phylogenetic analysis based on 16S rRNA gene sequence revealed that strain SDUM287046T was most closely related to Aequorivita aquimaris D-24T (98.3%). The main cellular fatty acids were iso-C15:0, anteiso-C15:0, iso-C17:0 3–OH, and summed feature 9 (comprised of iso-C17:1 ω9c and/or C16:0 10-methyl). The sole respiratory quinone was MK-6. The polar lipids consisted of phosphatidylethanolamine (PE), one aminolipid (AL), three unidentified glycolipids (GL), and three unidentified lipids (L). The DNA G + C content was 39.3 mol%. According to the integrated results of phylogenetic, physiological, biochemical, and chemotaxonomic characteristics, we propose that strain SDUM287046T represents a novel species of the genus Aequorivita, for which the name Aequorivita aurantiaca sp. nov. is proposed. The type strain is SDUM287046T (=KCTC 92754T = MCCC 1H01418T). Comparative genomic analysis showed that the 16 Aequorivita species shared 1453 core genes and differed mainly in amino acid metabolism, cofactor metabolism, and vitamin metabolism. Biogeographic distribution analysis indicated that the marine environments were the primary habitat of Aequorivita bacteria.

Head and neck cancer (HNC) is a prevalent malignancy with a poor prognosis, necessitating the identification of prognostic biomarkers to guide management. The geriatric nutritional risk index (GNRI), calculated from serum albumin and body weight, may predict survival in patients with HNC. We performed a systematic review and meta-analysis to clarify this relationship. Databases were searched for studies examining the association between pretreatment GNRI and overall survival in patients with HNC. Ten studies with 2793 patients were included. Meta-analysis demonstrated that low GNRI was associated with significantly worse overall survival compared to high GNRI (hazard ratio [HR]:2.84, 95% CI 2.07–3.91, p < 0.00001). Older age (HR:1.73; 95% CI, 1.35–2.22; p < 0.0001), male sex (HR:1.7; 95% CI, 1.12–2.6; p = 0.01), advanced tumor stage (HR: 2.5; 95% CI, 1.72–3.63; p < 0.00001), and higher T-/N-stage (HR = 1.69 and 1.98, respectively) were also predictive of unfavorable outcomes. The GNRI had the highest HR, suggesting potent predictive ability. Despite limitations, including retrospective design and potential publication bias, our study indicates that low pretreatment GNRI predicts poor overall survival in patients with HNC. The GNRI is an inexpensive, routinely available biomarker that could improve prognostication and guide management decisions. Additional research is warranted to validate these findings.

The climate is changing in Europe: average temperatures are increasing, and so is the frequency of extreme weather events. Climate change has a severe impact on areas suitable for growing certain crops and on food safety, for example, affecting the occurrence of the aflatoxin contamination of maize. The aim of this study was to obtain insights into the impact of climate change on possible changes in land use in Europe, particularly in areas suitable for maize cultivation, and on the probability of the mycotoxin contamination of maize in order to give directions for long-term adaptation to climate change. By combining a land use model and a mycotoxin prediction model, the suitability of land for maize cultivation and the probability of aflatoxin contamination were estimated for suitable areas in Europe, comparing the current climate with the 2050 scenario. In 2050, the occurrence of aflatoxin contamination in Europe is predicted to severely increase, especially in Central and Southern Europe. More northern regions, presently unsuitable for maize cultivation, will become suitable for maize cultivation in 2050. In the baseline scenario, most regions suitable for maize cultivation have a low probability of aflatoxin contamination, whereas in 2050, about half of the regions suitable for maize cultivation have a medium to high probability of aflatoxin contamination. Regions for safely growing maize for human consumption will shift from the southern to the northern half of Europe.