We investigated fabrication of neodymium doped thin film optical waveguide-based devices as potential active sources for planar integrated optics. Liquid-phase epitaxial growth was used to fabricate neodymium-doped yttrium aluminum borate films on compatible lattice-matched un-doped yttrium aluminum borate substrates. We observed the refractive index contrast of the doped and un-doped crystal layers by differential interference contrast microscopy. In addition, characterization by X-ray powder diffraction, optical absorption and luminescence spectra demonstrated the crystal quality and uniformity and optical guiding of the resulting thin films.

The field of controlled polymerization is growing and evolving at unprecedented rates, facilitating polymer scientists to engineer the structure and property of polymer materials for a variety of applications. However, the lack of degradability, particularly in vinyl polymers, is a general concern for not only environmental sustainability but also biomedical applications. In recent years, there has been a significant effort to develop reversible polymerization approaches in those well-established controlled polymerization systems. Reversible polymerization typically involves two steps including (i) forward polymerization which converts small monomers into macromolecules, and (ii) depolymerization capable of regenerating original monomers. Furthermore, recycled monomers can be repolymerized into new polymers. In this perspective, we highlight recent developments of reversible polymerization in those controlled polymerization systems and offer insight into the promise and utility of reversible polymerization systems. More importantly, the current challenges and future directions to solve those problems are discussed. We hope this perspective can serve as an “initiator” to promote continuing innovations in this fairly new area.

The water resources carrying capacity (WRCC) system comprises multiple complex and nonlinear interactions related to society, economy, water resources and the water environment. A full understanding of its internal mechanism is conducive to the further improvement of the regional WRCC. This article focuses on the temporal and spatial variability of WRCC to explore a method of dynamic successive assessment. Firstly, the Pressure-State-Response (PSR)framework is used to develop a systematic and causal indicator system. Then, The Variable Fuzzy Pattern Recognition (VFPR) model and an analytic hierarchy process-entropy (AHP-E) model are combined to successively and dynamically assess WRCC. The proposed method is applied to the dynamic successive assessment of WRCC in Hebei Province, and it is obtained that the poor water resources carrying capacity in Hebei Province is mainly due to the basic attribute of the decision of the water resources shortage, but Hebei Province actively adopts a variety of measures to save water and pressurize mining, which makes the province's water resources carrying capacity have a tendency to become better gradually. At the same time, the system dynamics model (SD) of water resources carrying capacity based on the analysis of the model structure was established. Moreover, three scenarios were designed, including existing continuation, high-efficiency water-saving, cross-regional water transfer and coordinated development, each scenario divided into high and low-speed economic development and population growth schemes, then total 6 schemes between 2023 and 2030 were simulated and predicted respectively. The results indicate that if the current development model is adopted, the water resource carrying capacity will continue to maintain low levels. It was concluded that the high-speed development of economy and population, the efficient water conservation and inter-basin transfer scenario (scenario 2 with high-speed) is the best choice for sustainable development of water resources and social economy in Hebei.

Transcranial direct current stimulation (tDCS) is acknowledged for its non-invasive modulation of neuronal activity in psychiatric disorders. However, its application in insomnia research yields varied outcomes depending on different tDCS types and patient conditions. Our primary objective is to elucidate its efficiency and uncover the underlying mechanisms in insomnia treatment. We hypothesized that anodal prefrontal cortex stimulation activates glutaminergic projections from the infralimbic cortex (IL) to ventrolateral preoptic area (VLPO) to promote sleep. After administering 0.06 mA of electrical currents for 8 minutes, our results indicate significant non-rapid eye movement (NREM) enhancement in naïve mice within the initial 3 hours post-stimulation, persisting up to 16-24 hours. In the insomnia group, tDCS enhanced NREM sleep bout numbers during acute stress response and improved NREM and REM sleep duration in subsequent acute insomnia. Sleep quality, assessed through NREM delta powers, remains unaffected. Interference of the IL-VLPO pathway, utilizing designer receptors exclusively activated by designer drugs (DREADDs) with the cre-DIO system, partially blocked tDCS's sleep improvement in stress-induced insomnia. This study elucidated that the activation of the IL-VLPO pathway mediates tDCS's effect on stress-induced insomnia. These findings support the understanding of tDCS effects on sleep disturbances, providing valuable insights for future research and clinical applications in sleep therapy.

Global warming may increase the potential evapotranspiration (Etp), thereby affecting the amount of clean water resources available in a region. In this study, the systematic biases in temperature outputs of 24 global climate models (GCMs) under 3 emission scenarios are corrected by using 8 bias correction methods. The trend of Etp in Yangzi River Delta in the 21st century is projected by using 4 Etp calculation formulas. The uncertainty of the projections is estimated and decomposed by using multi-way analysis of variance. The influence of uncertainty on the projected change signal is quantified by using the signal-to-noise ratio. The results show that, relative to the reference period (1971~2000), the annual mean daily Etp in Yangzi River Delta will increase by 0.14~0.17mm/d during the period 2021~2050 and by 0.21~0.41mm/d during the period 2061~2090, respectively. During 2021~2050, the uncertainty of Etp increase projections is dominantly contributed by the main effects of GCM (63%) and Etp calculation formula (24%). During 2061~2090, it is mainly contributed by the main effect of GCM (36%), followed by the main effects of emission scenario (34%) and Etp calculation formula (18%). The increase projections of Etp are generally reliable and robust during the two projection periods.

Excessive body fat is a major contributor to obesity, which is related to high blood, total cholesterol and triglycerides. Lemons (Citrus limon) are renowned for their antioxidant and lipid-lowering properties. First, Sugar-free fermentation demonstrated better results lower sugar content and was identified as the preferred fermentation method. Next, the effect of two doses of sugar-free fermented lemon peel juice (SF-FLPJ) on obesity was investigated. Sprague Dawley (male rats) were randomly divided into 4 groups and fed a standard feed or high-fat diet (HFD) to induce fatness for eight weeks. The two groups of rats fed an HFD were administered SF-FLPJ at 0.45 or 0.9 g/kg body weight daily for eight weeks. The obese rats administered 0.9 g/kg (body weight/day) of SF-FLPJ exhibited significant reductions in body fat mass and percentage; they also had lower blood cholesterol and triglyceride levels than the other groups. Additionally, the rats displayed diminished liver fat accumulation. The results suggest that SF-FLPJ can be a supplement in managing body fat, contributing positively to addressing obesity within the context of health management, and reduce obesity-associated issues.

Low-loss photonic waveguides in lithium niobate offer versatile functionality as nonlinear frequency converters, switches, and modulators for integrated optics. Combining the flexibility of laser processing with liquid phase epitaxy we have fabricated and characterized lithium niobate channel waveguides on lithium niobate and lithium tantalate. We used liquid phase epitaxy with K2O flux on laser-machined lithium niobate and lithium tantalate substrates. The laser-driven rapid-prototyping technique can be programmed to give machined features of various sizes, and liquid phase epitaxy produces high quality single-crystal, lithium niobate channels. The surface roughness of the lithium niobate channels on a lithium tantalate substrate was measured to be 90 nm. The lithium niobate channel waveguides exhibit propagation losses of 0.26 ± 0.04 dB/mm at a wavelength of 633 nm. Second harmonic generation at 980 nm was demonstrated using the channel waveguides, indicating that these waveguides retain their nonlinear optical properties.

The therapeutic effects of volatile anesthetics on mental diseases, particularly schizophrenia, have gained considerable interest. Although isoflurane is a commonly used volatile anesthetic, there’s no more evidence that it could work on treating schizophrenia. Here, we discovered that inhaling isoflurane at low concentrations might reverse the behavioral phenotypes of schizophrenia caused by MK801, such as hyperlocomotion, pre-pulse inhibition impairment, and working memory loss. Isoflurane also helped recovering adult neurogenesis and synaptic plasticity impairments in the dentate gyrus (DG) induced by MK801. To better understand the mechanism, we discovered that isoflurane could reverse the reduction of parvalbumin (PV)-positive GABAergic interneuron (PVI) number and the aberration of NRG1-ErbB4 signaling in the DG; however, isoflurane could not reverse the schizophrenia-related phenotypes caused by PVI ablation, indicating that PVI are necessary for the therapeutic effect of isoflurane. Interestingly, isoflurane could reverse phenotypes caused by blocking PVIs GABA release in the DG, indicating the therapeutic impact is independent of PVI GABA release. Our research revealed that isoflurane might be used to treat schizophrenia, possibly through PVI in the DG.

Rapid urbanization has led to many ecological problems such as landscape fragmentation, decreased landscape connectivity, and decreased biodiversity. Building an ecological security pattern is an important way to ensure ecological security and maintain sustainable urban development. Harbin is an important large-scale city in northeastern China, and the urban central district of Harbin is used as the study area. Ecological sensitivity assessment, MSPA, gravity model, landscape connectivity assessment and MCR model were used to extract ecological source areas, ecological corridors and ecological nodes in the study area to construct and optimize the ecological security pattern. Research shows that: A total of 23 ecological source areas were identified, mainly located along the Songhua River in the central part of the study area and in the mountain forest areas within the A-cheng District in the southeastern part of the study area. 48 ecological corridors were extracted, mainly in Daowai District, A-cheng District and the eastern part of Xiangfang District. There are 8 important ecological corridors and 10 important connecting corridors. 61 ecological nodes of the first level and 65 ecological nodes of the second level were extracted. High, higher, medium, lower and low security areas were classified based on the minimum cumulative resistance surface, with the highest proportion of high ecological security areas accounting for 45.75% of the study area. 65 ecological breakpoints were extracted and restoration measures were proposed. Finally, The structure of the ecological security pattern optimization of "two axes, two belts and four areas" is proposed, and corresponding ecological management measures are put forward. The experimental system of this study can provide new ideas for the construction of ecological security patterns in other regions and provide scientific support for the ecological sustainable development of similar urban areas.

Objective: This study investigated the effects of an easily implemented 8-week program centered around jump rope exercise (JRE) on executive function among children with ADHD. Methods: Using the Stroop Color Word Test to assess inhibitory control, the n-back task (1- and 2-back) to assess working memory, and task switching to assess cognitive flexibility. Results: After the intervention, there were within-group effects only for the experimental group, with higher accuracy on the 1-back working memory task (t= -2.79，p= 0.011< 0.05，Cohen’s d= 0.60) and on task switching after compared with before the JRE intervention (t= -4.00，p=0.01<0.05，Cohen’s d= 0.85), but with no change in reaction time. There was no significant within-group difference on the Stroop test (P> 0.05). Additionally, there were no between-group effects as assessed by one-way analyses of variance. Conclusion: 8-week program focused on JRE improved two aspects of executive function, working memory and cognitive flexibility, with no significant effect on a third aspect, inhibitory control, among children with ADHD aged 7 to 12 years.

Calcareous sand deposits are widely distributed along the shoreline in ropical and subtropical regions. Microbially induced calcite precipitation treatment (MICP) is a relatively new method to improve the stiffness and strength of the soil. Little is known about the small-strain shear modulus and damping ratio of MICP-treated calcareous sand, which are two crucial parameters for the prediction of the dynamic behavior of soil. A series of resonant column tests are performed to investigate the dynamic performance of MICP-treated calcareous sand, with special attention paid to the influence of treatment duration and confining stress on the stiffness and damping characteristics. The relationship between the initial dynamic shear modulus and unconfined compressive strength is analyzed. Additionally, the empirical equations of the reference shear strain between treatment duration and confining stress are given. The G/G0 of MICP-cemented calcareous sand presents a higher strain sensitivity than that of untreated sand, and its attenuation pattern can be described by Hardin-Drnevich model. The σc has an apparent effect on the degradation characteristics of the dynamic shear modulus of MICP-treated calcareous sand with a low cementation level, however, its effect decreases with the increasing treatment duration. The relationship between the reference shear strain and the treatment duration and confining stress can be described by a power and a linear formula, respectively.

Vascular calcification (VC) is associated with increased cardiovascular risks in patients with chronic kidney disease (CKD). Sodium-glucose cotransporter 2 inhibitors, like empagliflozin, can improve cardiovascular and renal outcomes. We assessed the expression of Runt-related transcription factor 2 (Runx2), interleukin (IL)-1β, IL-6, AMP-activated protein kinase (AMPK), nuclear factor erythroid-2-related factor (Nrf2), and heme oxygenase 1 (HO-1) in inorganic phosphate–induced VC in mouse VSMCs to investigate the mechanisms underlying empagliflozin’s therapeutic effects. We evaluated biochemical parameters, mean artery pressure (MAP), pulse wave velocity (PWV), transcutaneous glomerular filtration rate (GFR), and histology in an in vivo mouse model with VC induced by an oral high-phosphorus diet following a 5/6 nephrectomy in ApoE−/− mice. Compared to the control group, empagliflozin-treated mice showed significant reductions in blood glucose, MAP, PWV, and calcification, as well as increased calcium and GFR levels. Empagliflozin inhibited osteogenic trans-differentiation by decreasing inflammatory cytokine expression and increasing AMPK, Nrf2, and HO-1 levels. Empagliflozin mitigates high phosphate–induced calcification in mouse VSMCs through the Nrf2/HO-1 anti-inflammatory pathway by activating AMPK. Animal experiments suggested that empagliflozin reduces VC in CKD ApoE−/− mice on a high-phosphate diet.

In our previous study, a novel barrier processing on a porous low-dielectric constant (low-k) film was developed: an ultrathin Mn oxide on a nitrogen-stuffed porous carbon-doped organosilica film (p-SiOCH(N)) as a barrier of the Cu film was fabricated. To form a better barrier Mn₂O_3-xN film, an additional annealing at 450°C was implemented. In this study, the electrical characteristics and reliability of this integrated Cu/Mn₂O_3-xN/p-SiOCH(N)/Si structure is investigated. The proposed Cu/Mn₂O_3-xN/p-SiOCH(N)/Si capacitors exhibited poor dielectric breakdown characteristics in the as-fabricted stage, although, less degradation was found after thermal stress. Moreover, its time-dependence-dielectric-breakdown electric-field acceleration factor slightly increased after thermal stress, leading to a larger dielectric lifetime in a low electric-field as compared to other MIS capacitors. Furthermore, its Cu barrier ability under electrical or thermal stress was improved. As a consequent, the proposed Cu/Mn₂O_3-xN/p-SiCOH(N) scheme is a promising integrity for back-end-of-line interconnects.

In view of the problem that the output thrust of solenoid actuator is affected by various factors and is difficult to calculate in actual working conditions, this paper proposes a semi-analytical model constructed by magnetic field subdomain method with internal and external boundary conditions in cylindrical coordinate system for calculation, and the general solution equations of magnetic vector potential for each subdomain are derived and solved by MATLAB. Taking a push-pull electromagnet as an example, the finite element simulation and experimental comparative analysis are carried out. The correctness and applicable conditions of the subdomain method are illustrated by comparing the gradient plot of magnetic vector potential, inductance curve and electromagnetic force. By calculating the output thrust after considering the core gravity, spring force and electromagnetic force, it is shown that this method has the advantage of computational flexibility compared with the finite element method, and it is easier to write special algorithms according to various working conditions to calculate the important parameters in engineering applications.

Different toll collection types of vehicles and different distribution of tollbooths lead to the toll plaza diverging area becoming a typical vehicle weaving area with frequent crossing behaviors and conflicts on highways. This study aims to identify contributing factors to conflict risks of four vehicle-following patterns in a toll plaza diverging area by developing random parameters ordered logit models with heterogeneity in means and variances. The model can flexibly capture the unobserved heterogeneity of the contributing factors in different vehicle-following patterns. Real-world vehicle trajectory data obtained from the toll plaza diverging area in Nanjing, China, are used for model estimation. The results show that vehicle-following patterns with the same toll collection types have higher percentage of severe conflict risks. The average acceleration of the following vehicles, lane marking indicator, the initial lanes and lane-changes of vehicles are significantly associated with the collision risk levels. The standard deviation of surrogate safety measures of all vehicles in sub-segments are found differ significantly between vehicle-following patterns. Furthermore, a series of likelihood ratio tests are adopted to test the spatial dependence in sub-segments of the diverging area. The findings of this study could provide valuable information for safety improvement in toll plazas.

A single-crystal of ytterbium-doped “mixed” yttrium-lutetium aluminium garnet with a stoichiometric composition of (Y0.601Lu0.233Yb0.166)3Al5O12 was grown by the Czochralski method and its structure, vibronic, spectroscopic and laser properties were studied. The stimulated-emission cross-section for Yb3+ ions was maximized to 2.53×10-20 cm2 at 1031 nm, the emission bandwidth is ~8 nm and the reabsorption-free luminescence lifetime of the 2F5/2 state is 1.063 ms. Pumped at 941 nm, the Yb-laser generated a maximum output power of 1.04 W at 1.03 and 1.05 μm with a high slope efficiency of 76.4% and a laser threshold of 76 mW. A continuous wavelength tuning over a range of 51.6 nm (1026.4 - 1078.0 nm) was also achieved. Power scaling is achieved using a 969 nm-diode pumped microchip cavity. A maximum output power of ~9 W is obtained at 1.05 μm with a slope efficiency of 76% and with an almost circular laser beam profile.

Abstract: Unusual methane emission and spontaneous combustion of coal induced by the air leakage are both hazards during mining. The most common practice has been to improve mine safety is sealing the mining fractures. In this paper, the methane and geology, coal spontaneous combustion characteristics and the coexistence of methane emission and spontaneous combustion of coal were analyzed. The preparation system of inorganic solidified foam (ISF) in field applications is studied and the working principle of generating device consists of foam generator and mixer was expounded. The technical plan of site construction is that the foam fluids was injected to respectively seal the mining fractures behind hydraulic supports, the cavities of air return corner, and the fractures nearby the coal pillar. After the foam fluids injection, the two stress values in the coal pillar eventually maintained above 15.5Mpa and 13Mpa, respectively. It indicated that the ISF can enhance the bearing stress ability of the coal pillar by transforming the stress state from two dimensional to three dimensional. The methane concentration in the air return corner and air return roadway declined significantly to 0.63% and 0.25%. The differential pressure inside and outside of the 4301(1) goaf fluctuated between -100pa to 150pa and the concentration of CO and O2 declined to 9ppm and 6%. The CO concentration in the air return corner finally reached a stable level of 6ppm. What that all means, the foam fluids can seal the air leakage and inhibit spontaneous combustion of coal effectively.

Patients with lean NAFLD make up an increasing subset of liver diseases. The association between lean NAFLD and feutin-A, which serves as a hepatokine and adipokine, has never been examined. Our study aimed to explore the association of serum fetuin-A among lean and nonlean patients. The study comprised 606 adults from the community, stratified into lean or nonlean (BMI </≥ 24 kg/m2) and NAFLD or non-NAFLD (scoring of ultrasonographic fatty liver indicator, US-FLI ≥ 2/<2). Multivariate logistic regression analyses were performed to estimate the odds ratio of having NAFLD among the tertiles of fetuin-A after adjustment. The least square means were computed by general linear models to estimate marginal means of the serum fetuin-A concentrations in relation to the NAFLD groups. The OR of having NAFLD for the highest versus the lowest tertile of fetuin-A was 2.62 (95% CI: 1.72-3.98; P for trend<0.001). Stratifying by BMI, the OR of having lean NAFLD for the highest versus the lowest tertile of fetuin-A was 2.09 (95% CI: 1.09-3.98; P for trend 0.026), while nonlean NAFLD had no significant association with the fetuin-A gradient after adjustments. Fetuin-A was positively associated with lean NAFLD after adjusting for central obesity and insulin resistance.

The purpose of this study was to arrange a green roof on a sheet metal house to achieve winter heat preservation and summer thermal insulation using different plants and soil media, and to maintain the advantage of cost-saving and quick installation of sheet metal houses. In terms of the research method, the roof insulation, heat preservation and plant growth index were tested. Plants were grown in 10 container-type green roofs on the sheet metal house roof, and the physical environment of the building was monitored for one year. Five containers of commercially-available culture soil and five containers of sustainable composite were used as the media for growing five kinds of plants, respectively. The control group only had a sheet metal house roof. There were 11 experimental modules for testing whether the green roofs had thermal insulation, heat preservation and plant growth effects on a general sheet metal house. The results showed that, regarding the thermal insulation benefit assessment, the Sedum acre cv. robustum of green roof Groups B to D caused the temperature to be 38.29°C lower than the surface of the simple sheet metal house roof in August, showing a temperature difference of 54%.

Osteoporosis is a common problem in orthopedic medicine, and it has become an important medical issue in orthopedics as Taiwan is gradually becoming an aging society. In the diagnosis of osteoporosis, the bone mineral density (BMD) derived from dual-energy X-ray absorptiometry (DXA) is the main criterion for orthopedic diagnosis of osteoporosis, but due to the high cost of this equipment and the lower penetration rate of the equipment compared to the X-ray images, the problem of osteoporosis has not been effectively solved for many people who suffer from osteoporosis, however, at present, in clinical diagnosis, doctors are not yet able to accurately interpret X-ray images for osteoporosis manually, and must rely on the data obtained from DXA. In recent years, with the continuous development of artificial intelligence, especially in machine learning and deep learning, significant progress has been made in image recognition. Therefore, it is worthwhile to revisit whether it is possible to use a convolutional neural network model to read a hip X-ray image and then predict the patient's BMD. In this study, we proposed a hip X-ray image segmentation model and a hip X-ray image recognition classification model. First, we used the U-Net model as a framework to segment the femoral neck, greater trochanter, wards triangle, and the total hip in the hip X-ray images. We then performed image matting and data augmentation. Finally, we constructed a predictive model for osteoporosis using deep learning algorithms. In the segmentation experiments, we used intersection over union (IoU) as the evaluation metric for image segmentation, and both the U-Net and U-Net++ models achieved segmentation results greater than or equal to 0.5. In the classification experiments, using the T-score as the classification basis, the total hip using the DenseNet121 model has the highest accuracy of 74%.

To realize fast and effective synthetic aperture radar (SAR) deception jamming, a high-quality SAR deception jamming template library can be generated by performing sample augmentation on SAR deception jamming templates. However, current sample augmentation schemes of SAR deception jamming templates face certain problems. First, the authenticity of templates is low due to the lack of speckle noise. Second, the generated templates have low similarity to the target and shadow areas of the input templates. To solve these problems, this study proposes a sample augmentation scheme based on generative adversarial networks, which can generate a high-quality library of SAR deception jamming templates with shadows. The proposed scheme solves the two aforementioned problems from the following aspects. First, the influence of the speckle noise is considered in the network to avoid the problem of reduced authenticity in generated images. Second, a channel attention mechanism module is used to improve the network's learning ability of shadow features, which improves the similarity between the generated template and the shadow area in the input template. Finally, the proposed scheme and the SinGAN scheme are compared regarding the equivalent numbers of looks and the structural similarity between the target and shadow in the sample augmentation results. The comparison results demonstrate that, compared to the templates generated by the SinGAN scheme, those generated by the proposed scheme have targets and shadow features similar to those of the original image, and can incorporate speckle noise characteristics, resulting in higher authenticity, which helps to achieve fast and effective SAR deception jamming.

Globally, the use of whole-cell matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) in clinical microbiology laboratories has increased considerably. With the rapid growth of artificial intelligence technology, there is an increasing number of areas devoted to solving problems by implementing machine learning-based methods. Applying the use of artificial intelligence to the analysis of the massive amount of information obtained in the mass spectrum derived from MALDI-TOF MS should be a breakthrough in clinical microbiology. Specifically, it would facilitate a more rapid and accurate strain typing or antibiotic susceptibility test (AST) based on whole-cell MALDI-TOF MS spectra, and hence, it is a promising solution. Even though the reproducibility of peaks could result in some critical problems, computational methods have been developed to address this issue. Therefore, clinical microbiologists are able to perform strain typing or an AST as smoothly and easily as identifying species by using MALDI-TOF MS and artificial intelligence.

Soil is an extremely significant resource for human survival, and agglomerates, as the basic unit of soil structure, not only enhance soil fertility and control the biological validity of nutrients, but also strengthen the soil's erosion resistance. The mass application of fertilizers may have a significant impact on crop growth and soil structure, and the rational application and dispensing of fertilizers will be an urgent issue to be addressed. Therefore, the effect of fertilizer application on the stability of water-stable soil aggregates needs to be studied under different meteorological and soil conditions to draw more general and feasible conclusions. Our Meta-analysis of data from 220 of 56 published studies found that fertilizer application increased mean weight diameter (MWD) by an average of 18% compared to the no-fertilizer treatment. Among the nitrogen (N), phosphate (P), and organic (OM) fertilizer treatments, the organic fertilizer treatment had a greater stimulatory effect on MWD (26%). Among the different fertilizer levels, low level of phosphorus (<40kg·hm-2·yr-1), high level of N (>120kg·hm-2·yr-1), and low level of organic fertilizer (<5000kg·hm-2·yr-1) increased MWD by 19%, 14%, and 41% respectively. Across soil types and land use types, the response to MWD was positive for red soils and paddy fields, and the stimulatory effect of organic fertilizer was more significant compared to chemical fertilizer. The regression model showed that the response ratio of MWD was negatively correlated with the response ratio of soil pH and bulk density (BD), and positively correlated with the response ratio of soil organic carbon (SOC) and microbial mass carbon (MBC). Meanwhile, the PLS-SEM model showed that average annual temperature was the main factor affecting the stability of soil aggregates, and the average annual rainfall is the secondary factor. Therefore, this study found that the long-term use of organic fertilizers in place of some chemical fertilizers was more effective than chemical fertilizer alone. Temperature and rainfall have greater effects on the response of fertilizer to soil aggregate stability.

Aging and obesity make humans more prone to cardiovascular and metabolic syndrome diseases, leading to several serious health conditions, including dyslipidemia, high blood pressure, and sleep disturbance. Hyperlipidemia means elevated blood lipid levels, including cholesterol and triglycerides. This study aimed to explore the hypolipidemic effect of fermented citrus lemon juice using a hyperlipidemic hamster model. Sugar-free lemon juice’s fermentation was optimized, and the characteristics of fresh and fermented lemon juice (FLJ) were evaluated and compared. In addition, tests were conducted to determine the appropriate hamster feed for the functional animal tests. Then, experiments were conducted to evaluate the hypolipidemic effect of the FLJ, which contained polyphenols and superoxide dismutase-like activity, on a hyperlipidemic hamster model. This study’s pre-fermentation efficiency evaluation found that 21–30 days of bacterial DMS32004 and DMS32005 fermentation of fresh lemon juice provided the best fermentation benefits. In addition, the fermentation evaluation showed that a sugar-free fermentation method provided FLJ with the best benefits. Results showed that the absorption and utilization efficiency of FLJ was higher compared with the unfermented lemon juice. After six weeks of feeding, the total cholesterol and triglyceride values in the blood and liver of the FLJ treatment groups were de-creased compared with the high-fat diet (HFD) group. In addition, the blood low-density lipoprotein cholesterol levels were significantly reduced in the FLJ treatment groups compared with the HFD group. In contrast, the blood high-density lipoprotein to low-density lipoprotein cholesterol ratio increased considerably in the FLJ treatment groups, and the total to high-density lipoprotein ratio was significantly lower than in the HFD group. Compared with the HFD group, the total cholesterol content in the FLJ treatment groups’ feces increased significantly. This study demonstrated that the sugar-free fermentation method and fermentation cycle management provided FLJ with the potential to regulate blood lipids. Further research and verification will be carried out to isolate specific substances from the FLJ and identify their mechanisms of action.

Dry intrusion is an important mid-latitude atmosphere phenomenon within the upper troposphere and lower stratosphere. It is always found to be related to the cyclogenesis, rainstorm, as well as convection generation and precipitation enhancement. Since the atmosphere environment for any of these above-mentioned weather is terribly complicated, those preexisting popular schemes which takes no account of water vapor may not suitable for detecting the dry intrusion related to these weathers. With regard to the merits and demerits of the current preexisting schemes, a new scheme based on Fengyun-2E geo-stationary satellite data is presented in this study to detect the atmospheric dry intrusion. The scheme is set up based on the statistical relationship between water vapor at high level troposphere, the general moist potential vorticity, ozone concentration and upper-level jet. After using the total amount of ozone and ozone profile operational products retrieved by Fengyun-3 Polar Orbiting Meteorological Satellites and the potential vorticity calculated by ECMWF Interim data for validation, this scheme is applied to analyze two typical middle-latitude weather processes. One is the famous Beijing extreme rainfall of 21 July 2012 and the other is a hailstorm occurred on the eastern China during March 19, 2014. A good application effect in both cases suggests that our new method of detecting dry intrusion is feasible and can be helpful in middle-latitude disastrous weather monitoring and forecasting.

G protein-coupled receptor 15 (GPR15, also known as BOB) is an extensively studied orphan GPCR involving HIV infection, colonic inflammation and smoking-related diseases. Recently, GPR15 was deorphanized and its corresponding natural ligand demonstrated an ability of inhibiting cancer cell growth. However, no study reported the potential role of GPR15 in a pan-cancer manner. Using large-scale publicly available data from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases, we found that GPR15 expression is significantly lower in colon adenocarcinoma (COAD) than in normal tissues. And among 33 cancer types, GPR15 expression is significantly correlated with the prognoses of COAD, neck squamous carcinoma (HNSC), lung adenocarcinoma (LUAD) positively and stomach adenocarcinoma (STAD) negatively. This study also revealed that commonly upregulated gene set in the high GPR15 expression group (stratified via median) of COAD, HNSC, LUAD and STAD are enriched in immune systems, indicating that GPR15 might be considered as a potential target for cancer immunotherapy. Furthermore, we modelled the 3D structure of GPR15 and conducted the structure-based virtual screening. The top 8 hits compounds were screened and then subjected to molecular dynamics (MD) simulation for stability analysis. Our study provided novel insights into the role of GPR15 in a pan-cancer manner and discovered a potential hit compound for GPR15 antagonists.

The utilization of tempered blast furnace (BF) slag through the direct fiber forming process to create high-value thermal insulation materials offers a dual benefit: it efficiently harnesses the latent heat within unused slag and substantially enhances the value of blast-furnace slag utilization. However, gauging the melting properties of iron slag under high temperatures is a challenge. In this study, we explore the melting behavior of SiO2 within a high-temperature molten pool. We employ dynamic visual data (video stream) captured via a non-contact charge coupled device (CCD) video recording system to extract SiO2 contours through image processing. The change in image centroid characteristics is used to establish a convolution function relationship, and MATLAB's traversal search algorithm determines SiO2's centroid position. Given that SiO2 is proportionate to crucible pixels, the area of SiO2 is calculated through pixel statistics within these contours. Subsequently, we propose a new indirect method to process image information, yielding SiO2 volume and mass at different time points. An exponential fitting yields the melting rate function of SiO2. Finally, we compare this indirect method with shape from shading (SFS), quantitative characterization, and dimensional analysis techniques. We also discuss the strengths and limitations of each method. Our findings reveal that the indirect solution method presented here boasts straightforward calculation steps and imposes minimal image format requirements. This research provides theoretical and technical support for blast-furnace slag's direct fiber forming process.

The aim of this study was to examine oxidative stress and low level of alpha-1-antitrypsin (A1AT) in primary Sjögren's syndrome (pSS), and evaluate the associated autoreactivity against unmodified and their 4-hydroxy-2-nonenal (HNE)-modified peptides with pSS. Two differentially expressed proteins, alpha-1-acid glycoprotein 1 (A1AG1) and A1AT, exhibited 2-fold differences, and their HNE modifications were identified by depleted-albumin and immunoglobulin G (IgG) serum protein, in-solution digestion, in-gel digestion, and nano-LC-MS/MS from pSS patients and age-matched healthy controls (HCs). Furthermore, levels of proteins, confirmation of HNE modifications, HNE-protein adducts and autoreactivity against unmodified and their HNE-modified peptides were further validated. Levels of the HNE-protein adduct and A1AG1 were significantly higher in pSS patients than HCs, but levels of A1AT were significantly lower in pSS patients compared to HCs. Only the HNE modification of A1AT was confirmed. Further, concentrations of anti-A1AT^50-63 IgG and anti-A1AT^50-63 HNE IgA were significantly lower in pSS patients than HCs. Our study suggests that elevated HNE-protein adduct, oxidative stress, level [odds ratio (OR) 4.877, p = 0.003], lowered A1AT level (OR 3.910, p = 0.010) and a decreased level of anti-A1AT^50-63 IgG (OR 3.360, p = 0.010) showed an increased risk in pSS patients compared to HCs, respectively.

There is no doubt that seagrass beds constitute one of the most productive ecosystems in shallow coastal waters. Despite this, picoplankton in seagrass ecosystems has received relatively little attention. The purpose of this study was to compare picoplankton growth and mortality rates between seagrass and unvegetated habitats using chamber incubations. We tested two main hypotheses: (i) incubation with seagrass would result in higher bacterial growth rates due to increased DOM release from seagrass photosynthesis, and (ii) Synechococcus spp. would be lower in the presence of seagrass due to competition for inorganic nutrients. Our results showed bacterial growth rates of 2.31 and 2.44 d–1 without and with seagrass, respectively. In seagrass chambers, bacterial growth was higher than that in non-seagrass chambers, suggesting that organic carbon coming from the seagrass community may support bacterial production. Furthermore, we observed a negative Synechococcus spp. growth rate (-0.9 d–1) in the seagrass treatment, likely reflecting nutrient competition with the seagrass. Small-scale chambers proved to be a useful tool for studying the factors controlling spatial and temporal patterns of picoplankton across different habitats. Furthermore, future studies should examine picoplankton growth over a wider range of spatial scales in seagrass beds and adjacent unvegetated sediment.

3D printing is a non-traditional additive manufacturing process. It is different from the traditional subtractive manufacturing process. It offers exceptional rapid prototyping capabilities and results that traditional subtractive manufacturing methods cannot attain, especially in applications involving curved or intricately shaped components. Despite its advantages, metal 3D printing will face porosity, warpage, and surface roughness issues. These issues will affect the future practical application of the parts indirectly, for example, the structural strength and the parts assembly ca-pability. Therefore, this study compares the qualities of the warpage, weight, and surface rough-ness after milling and grinding processes under the same materials (316L stainless steel) between general rolled steel and 3D additive steel. Experimental results show that 3D printing parts are approximately 13% to 14% lighter than the general rolled steel. The surface roughness performance of 3D printing steel is better than general rolled steel under the same material after milling or grinding processing. The hardness of the 3D printing steel is better than that of the gen-eral rolled steel. The research verifies that 3D additive manufacturing can use surface processing to optimize surface performance and achieve the functions of lightness and hardness.

Semi-continuous data are very common in the social science and economics. In this paper, a Bayesian variable selection procedure is developed to assess the influence of exogenous factors including observed and unobserved on the semi-continuous data. Our formulation is based on the two-part latent variable model with polytomous response. We consider two schemes for the penalties of regression coefficients and factor loadings: the Bayesian spike and slab bimodal prior and the Bayesian lasso prior. Within the Bayesian framework, we implement Markov Chains Monte Carlo sampling method to conduct posterior inference. To facilitate posterior sampling, we recast the logistic model in part one as the norm-like mixture model. Gibbs sampler is designed to draw observations from the posterior. Our empirical results show that with suitable hyper-parameters, the spike and slab bimodal method slightly outperforms the Bayesian lasso in the current analysis. Finally, a real example related to the China household finance survey is analyzed to illustrate the application of the methodology.. .

The most recent National Research Council Nutrient Requirements for Sheep and Goats was published in 2007, one of the most consequential nutrient requirement recommendations for sheep and goats in the world. It is pertinent to continue the refinement and discussion of nutrient utilization and requirements for the purposes of enhancing the efficiency of production systems, maximizing resource economy, and minimizing the carbon footprint, among others. Progress has been made in the estimation of energy and protein requirements in sheep and goats, mainly utilizing empirical feeding experimentation, comparative slaughter technique and minimum endogenous loss method. In sheep, newer estimates of energy and protein requirements for maintenance and growth and partial efficiencies had been reported since 2007. There were suggestions that energy and protein requirements could have been affected by breed, wool growth, gender and size; with these reported values being similar or lower than the recommended values in international feeding systems such as NRC, ARC, INRA and AFRC. In goats, energy and protein requirements for growing goats were reported to be either higher or lower than the established recommendations, depending upon meat or dairy breeds. Effect of gender on energy requirement appeared to be related to the stage of growth or degree of maturity. Newer data also suggested that the guidelines of the major feeding systems for the entire growth phase may not be adequate for non-pregnant and non-lactating pubertal females. In multiparous pregnant goats, energy and protein requirements for maintenance did not appear to be affected by days of pregnancy, but efficiencies of metabolizable energy and metabolizable protein utilization for pregnancy were. There were suggestions that that metabolizable protein synthesis in the rumen can be predicted from energy intake using combined equations that encompass both sheep and goats, but more data on goats were called for to account for specific differences in nutrition. In addition to sulfur, there has been progress made on the estimation of maintenance and growth requirements of calcium, phosphorus, potassium and magnesium in goats, with suggestions on the consideration of gender and breed differences. Species, level of Intake, genotype, mature size, age, gender, body composition, use of tissue energy, activity, season, and acclimatization continue to be important considerations for the estimation of nutrient requirements in sheep and goats, with emerging factors such as climate change, heat stress, parasitism and secondary plant compounds. Model equations and partial efficiencies used by NRC to predict energy and protein requirements for maintenance, growth, lactation, and fiber have been highlighted and discussed for the purpose of a more focus discussion and refinement for the future. Potential and limitation of both traditional and emerging methodologies in determining the nutrient requirements in sheep and goats were discussed. To justify the research investment, emerging methodologies such as nutrigenomics will have to be linked more directly to the improvement of production efficiency via more precise prediction of nutrient requirement.

In mesoscale eddies, chemical properties and biological composition are different from those in surrounding water, due to their unique physical processes. It is unclear how physical-biological coupling occurs in warm-core eddies, particularly since no study has examined the relationship between bacteria and viruses. The purpose of the present study was to examine the influence of anticyclonic warm eddy on the relationship between bacterial and viral abundances as well as viral activity (viral production) in different depths. In the core of warm eddy, bacterial abundance (0.48 to 2.82 ×105 cells mL−1) fluctuated less than that of the outside eddy (1.12 to 7.03×105 cells mL−1). In particular, there was four-folds higher of viral-bacterial abundance ratio (VBR) estimated within the eddy below DCM than the outside eddy. We suggest that prevailing physical forces with downwelling at the center of the anticyclonic warm eddy, viruses can also be transmitted into the deep ocean directly through adsorption on particulate organic matter during sinking. Overall, our findings provide valuable insights into the interaction between bacterial and viral communities and their ecological mechanism within the warm eddy.

Natural montane peatlands generally are not a significant source of nitrous oxide (N₂O) due to environment limitation including phosphorus (P) scarcity and temperature lowness. Phosphorus enrichment and warming caused by global change are altering this limitation, likely to increase the source function of N₂O. However, the combined effects of P addition and warming on N₂O fluxes and biotic/abiotic factor in peatlands are still uncertain. To address this, we investigated the long-term (12 yrs) effects of P addition (5 and 10 kg ha^-1 yr^-1) and its interaction with warming on N₂O fluxes in a peatland. The results showed that although long-term P addition did not significantly affect the source/sink function of N₂O in the peatland, it stimulated enzyme activities, promoted peat decomposition. However, warming amplified the effect of P addition to increase N₂O emissions by stimulating enzyme activities and changing soil stoichiometry, even turned the peatland into a significant source of N₂O with an emission of approximate 100 g m^-2 during the growing season. Our study suggests that P enrichment under the current background of global warming will enhance the possibility of strong N₂O emissions in montane peatlands, which may increase the risk to further aggravate global warming.

Metal plasmonic nanostructures have promising applications in biosensing due to their ability to facilitate light-matter interaction. However, the damping of the metal leads to a wide full width at half maximum (FWHM) spectrum and results which restricts its sensing capabilities. In this research, we present a novel non-full-metal nanostructure, namely indium-tin oxide (ITO)-Au nanodisk arrays consisting of top ITO nanodisk arrays and a bottom gold layer, and compare the coupling mode with the full-metal nanodisk arrays. The FWHM of proposed ITO-Au nanodisk array reduces to one fifth of that all metal nanodisk arrays, which is generated mode-coupling by surface plasmon modes at metal interfaces with magnetic resonance mode. Furthermore, the thickness variation of nanodisks has no impact on the sensing performance of this ITO-based nanostructure, ensuring excellent tolerance during preparation. We fabricated both structures by using template transfer and vacuum deposition techniques and calibrated their sensing performances by detect Immunoglobulin G (IgG) protein molecules. Both theoretical and experimental results demonstrate that ITO-Au nanodisk arrays provide an effective solution for biosensing applications.

Cholangiocarcinoma is the most common primary malignant tumor of the bile duct. The current standard first-line treatment for advanced or metastatic cholangiocarcinoma is gemcitabine and cisplatin. However, few effective treatment choices exist for refractory cholangiocarcinoma, and additional therapeutic drugs are urgently required. Our previous work demonstrated that the ALDH isoform 1A3 plays a vital role in the malignant behavior of cholangiocarcinoma and may serve as a new therapeutic target. In this study, we found a positive correlation between ALDH1A3 protein expression levels and cell migration abilities of three cholangiocarcinoma cell lines, which was verified using ALDH1A3-overexpressing and ALDH1A3-knockdown clones. We also used ALDH1A3-high and ALDH1A3-low populations of cholangiocarcinoma cell lines from the Library of Integrated Network-based Cellular Signatures (LINCS) program and assessed the effects of ruxolitinib, a commercially available JAK2 inhibitor. Ruxolitinib had a higher cytotoxic effect when combined with gemcitabine. Furthermore, the nuclear translocation STAT1 and STAT3 heterodimers were markedly diminished by ruxolitinib treatment, possibly resulting in decreased ALDH1A3 activation. Notably, ruxolitinib alone or combined with gemcitabine led to significantly reduced tumor size and weight. Collectively, our studies suggest that ruxolitinib might suppress the ALDH1A3 activation through the JAK2/STAT1/3 pathway in cholangiocarcinoma, and trials should be undertaken to evaluate its efficacy in clinical therapy.

The Internet use has become an integral part of daily life, adolescents are especially at a higher risk to develop problematic Internet use (PIU). Although one of the most well-known comorbid conditions of PIU is sleep disturbance, little is known about the sex disparity in this association. This school-based survey in students of grades 7-9 was conducted to estimate the prevalence of PIU and sleep disturbance among Chinese adolescents, to test the association between PIU and sleep disturbance, and to investigate the role of the child’s sex in this association. A two-stage stratified cluster sampling method was used to recruit participants, and a two-level logistic regression models were fitted. The mean Internet addiction test scores was 37.2 (SD: 13.2), and 15.5% (736) met the criteria for PIU. After adjusting for control variables, problematic Internet users were at a higher risk of sleep disturbance (adjusted odds ratio=2.41, 95% CI=2.07-3.19). Sex-stratified analyses also demonstrated that association was greater in girls than boys. In this respect, paying more attention to the sleep patterns of adolescents who report excessive Internet use is recommended, and this early identification may be of practical importance for schools, parents, and adolescents themselves.

In order to the effect of hydrated phase change materials on suppressing coal spontaneous combustion, the thermogravimetric experiment and reaction activation energy analysis experiment were used to explore the changes of combustion characteristic, parameters characteristic temperature and activating energy of gas coal, long flame coal, meagre coal, and lean coal before and after adding hydrated phase change materials. The research results showed that hydrated phase change materials increased the coal samples’characteristic temperature point and have effective inhibitory effects on different stages of oxidation process.However, the effect was best at low temperatures, as hydrated phase change materials undergo phase change and absorb heat when heated at low temperatures, isolating coal from contact with oxygen. The activating energy increased by 1.138 KJmol-1～23.048 KJmol-1 and the mass loss reduced by 1.6%～9.3% after the inhibition of the coal sample,indicating that the oxidation rate of various coal samples can be slowed down and the spontaneous combustion can be suppressed by using hydrated phase change materials.At the same time, this material can also reduce the combustibility index of meagre coal and lean coal, as well as the comprehensive combustion index and maximum loss rate of long flame coal and gas coal.

The quality of healthcare services is a very important indicator of social welfare in developed and emerging countries. Good quality levels are critical to ensuring patient safety, improving health outcomes, increasing patient satisfaction, optimizing resource utilization, and meeting regulatory requirements. The stable and sustainable operation of medical institutions urgently requires the establishment of a reliable and effective medical quality performance evaluation platform. However, the complexity of the evaluation process, involving numerous evaluators and the consideration of different subjective and objective criteria, poses significant challenges and essentially constitutes a group multi-criteria decision-making problem. This article uses the overall medical environment of the institution, medical service attitude, medical security, administrative service measures, etc. as measurement standards to deal with this challenge. It proposes a medical service quality measurement model suitable for both qualitative and quantitative analysis. In view of the heterogeneity of information, the two-tuple fuzzy language calculation method is introduced to enable evaluators to skillfully manage diverse information and effectively avoid potential information omission problems in the subjective evaluation integration process. The effectiveness and feasibility of the model were demonstrated by applying it to the operational framework of a medical institution in central Taiwan.

Aluminum wire is a common material for wire bonding due to its resistance to oxidation and low price. It does not melt when becoming a free air ball (FAB) during the electronic flame-off (EFO) process with wettability, and is applied by wedge bonding. This study used 20μm Zn-Coated Al-0.5wt.%Si (ZAS) wires to improve the FAB shape after the EFO process, while maintaining stability of the mechanical properties, including the interface bonding strength and hardness. In order to test circuit stability after ball bonding, the current-tensile test was performed. During the experiment, it was found that 80nm ZAS with wire bonding has lower resistance and higher fusing current. For the bias tensile test, the thicker Zn film diffused into the Al-Si matrix easily, after which the strength was reduced. The ball-bond interfaces had no change in their condition before and after the bias. Accordingly, ZAS could be a promising candidate for ball bonding in the future.

Soarinho Alkaline Intrusion, southeastern Brazil, makes part of the Serra do Mar Igneous Province, and it is composed of alkali feldspar syenite, alkali feldspar trachyte, quartz syenite, and mon-zonite. Geochemical and geochronological analysis of the Soarinho were compared with data from its neighbors Rio Bonito and Tanguá. Zircon U-Pb Laser Ablation ages show that Soarinho is youngest than Rio Bonito and Tanguá. Ages obtained from the monzonite (60 ± 2 Ma), alkali feldspar syenite (58 ± 2 Ma), and quartz syenite (58 ± 2 Ma) are indistinguishable within error. Petrographic and geochemical data show a clear contrast among Soarinho, Rio Bonito, Tanguá, and Lu-Hf isotopic data for the three alkaline intrusions (all negative), point to some similarities in their sources. The data suggest an enriched mantle source for Soarinho; however, an older con-tinental crust contribution cannot be discarded.

This study aimed to overcome the difficulty of conducting the horizontal-well cavity leaching test in the field and to investigate the long-term stability of the horizontal-well salt-cavity natural gas storage. The simulation test design is combined with the similarity theory to study the cavity expansion characteristics and the influence law of cavity leaching parameters. Through the design of a rubber hose connection, an integrated closed test system for multi-stage horizontal-well cavity leaching and brine drainage was built. The test system also realises the repeatable backward movement of the injection well during the test. A similarity simulation of the test design was carried out, and the test platform was constructed to carry out multi-stage horizontal-well leaching tests with a nitrogen cushion. In the horizontal-well leaching tests with a nitrogen cushion, the influence laws of the well spacing, flow rate and liquid level position on cavity expansion were investigated. Based on the morphological characteristics of the horizontal-well cavity, a numerical model of the horizontal-well salt cavity was developed, which reflects the real cavity morphology leached in the test. The long-term stability of the horizontal-well salt-cavity natural gas storage under different internal pressures was investigated through numerical simulation.

Cancer immunotherapy reaches a remarkable achievement in various cancer types and brings new possibilities to improve cancer patients’ long-term survival. However, outcomes vary from case to case, and the present protocol benefits a small fraction of patients. One notable factor is the tumor microenvironment, especially the immune cell components, that may reflect the immune response's status quo on site. Thus, understanding the content of infiltrating immune cells in tumors is not only for research interesting but also a crucial subject toward precision medicine. We implement an algorithm for resolving relative proportions of twenty-one immune cell subclasses from a human tissue profiled transcriptome by microarray technology to reach the goal above. By selecting gene features and then adopting ?-Support Vector Regression, we can construct a deconvolution model and resolve the immune cell context. The excellent consistency between the estimated values and the correct immune-cell composition further demonstrates this approach provides a more natural alternative to revealing samples' immune cell content and reliable results like recent single-cell technologies. Based on this algorithm, the web-based deconvolution tool implemented named mySORT provides a user-friendly interface for estimating the immune cell content by uploading gene expression profiling. We also present comprehensive visualization 2D/3D plots in mySORT so that users can easily make a comparison between different samples. Finally, we synthesized pseudo-bulk expression data from single-cell transcriptomic datasets of 17 melanoma and 16 head and neck cancer patients. The deconvolution results of microarray-based data in the previous study and synthetic pseudo-bulk data all proved the excellent performance of mySORT. We believe that mySORT can help researchers in all fields easily understand complex immune microenvironment. The website of mySORT is freely accessible on https://symbiosis.iis.sinica.edu.tw/mySORT/.

Small peptides (SPs), ranging from 5 to 100 amino acids, play integral roles in plants due to their diverse functions. Despite their low abundance and small molecular weight, SPs intricately regulate critical aspects of plant life, including cell division, growth, differentiation, flowering, fruiting, maturation, and stress responses. As vital mediators of intercellular signaling, SPs have garnered significant attention in plant biology research. This comprehensive review delves into SPs' structure, classification, and identification, providing a detailed understanding of their significance. Additionally, we summarize recent findings on the biological functions and signaling pathways of prominent SPs that regulate plant growth and development. The review also offers a forward-looking perspective on future research directions in peptide signaling pathways.

This work is devoted to physical vapor deposition synthesis, and characterisation of bismuth and lutetium-substituted ferrite-garnet thin-film materials for magneto-optic (MO) applications. The properties of garnet thin films sputtered using a target of nominal composition type Bi_0.9Lu_1.85Y_0.25Fe_4.0Ga₁O₁₂ are studied. By measuring the optical transmission spectra at room temperature, the optical constants and the accurate film thicknesses can be evaluated using Swanepoel’s envelope method. The refractive index data are found to be matching very closely to these derived from Cauchy’s dispersion formula for the entire spectral range between 300-2500 nm. The optical absorption coefficient and the extinction coefficient data are studied for both the as-deposited and annealed garnet thin-film samples. A new approach is applied for accurately deriving the optical constants data simultaneously with the physical layer thickness, using a combination approach employing custom-built spectrum-fitting software in conjunction with Swanepoel’s envelope method. MO properties, such as specific Faraday rotation, MO figure of merit and MO swing factor are also investigated for several annealed garnet-phase films.

Color image binarization plays a pivotal role in image preprocessing work, significantly impacting subsequent tasks, particularly in text recognition. This paper concentrates on Document Image Binarization (DIB), aiming to separate a image into foreground (text) and background (non-text content). Through a thorough analysis of conventional and deep learning-based approaches, we conclude that prevailing DIB methods leverage deep learning technology. Furthermore, we explore the receptive fields pre- and post-network training to underscore the Transformer model's advantages. Subsequently, we introduce a lightweight model based on the U-Net structure, enhanced with the Mobile ViT module to better capture global information features in document images. Given its adeptness at learning both local and global features, our proposed model exhibits superior performance on two standard datasets (DIBCO2012 and DIBCO2017) compared to state-of-the-art methods. Notably, our proposed DIB method presents a straightforward end-to-end model devoid of additional image preprocessing or post-processing. Moreover, its parameter count is less than a quarter of the HIP'23 model, which achives best results on three datasets(DIBCO2012, DIBCO2017 and DIBCO2018). Finally, two sets of ablation experiments were conducted to verify the effectiveness of the proposed binarization model.

In the recent decade, Building Information Modelling (BIM) has widely been adopted in the Architecture, Engineering and Construction (AEC) industry and completely upended the way we build. While BIM continues gain momentum in the industry, it has also attracted increasing attentions from researchers. However, most of the current study focuses on reviewing BIM for management, BIM for green building, BIM for infrastructure and BIM for Facilities Management (FM). There are few studies about Global BIM review and to discuss their complex inter-connections. In this study, we adopted a scientometric analysis method to review global BIM research from 2004-2019. A total of 1455 scholarly bibliographic records obtained from Web of Science Core Collection databased were established for the analysis. This study has identified the top productive and influential researchers, research institutes, regions/countries, subject categories and journals in the BIM field. In addition, 11 clusters of Global BIM research were also identified including construction project, green BIM, construction safety planning, automated IFC-based workflow and so on. Authors distinguished 11 clusters of global BIM research into 3 stages, namely formulating stage, accelerating stage and transforming stage. Furthermore, authors reviewed the BIM policy of Singapore and observed there is a co-production relationship between evolution of BIM policy and global BIM research. These findings provide valuable information for researchers, practitioners and policy makers by visualizing the current progress in the research field of BIM and highlighting future research needs.

Major depressive disorder (MDD) is one of the most prevalent and disabling mental disorders worldwide. Among the symptoms of MDD, sleep disturbance such as insomnia is prominent and the first reason patients may seek professional help. However, the underlying pathophysiology of this comorbidity is still elusive. Recently, genome-wide association studies (GWAS) have begun to unveil the genetic background of several psychiatric disorders, including MDD and insomnia. Identifying the shared genomic risk loci between comorbid psychiatric disorders could be a valuable strategy to understand their comorbidity. This study seeks to identify the shared genes and biological pathways between MDD and insomnia based on their shared genetic variants. First, we performed a meta-analysis based on the GWAS summary statistics of MDD and insomnia obtained from Psychiatric Genomics Consortium and UK Biobank, respectively. Next, we associated shared genetic variants to genes using two gene mapping strategies: (a) positional mapping based on genomic proximity and (b) expression quantitative trait loci (eQTL) mapping based on gene expression linkage across multiple tissues. As a result, a total of 719 shared genes were identified. Over half (51%) of them are protein-coding genes. Functional enrichment analysis shows that the most enriched biological pathways are related to epigenetic modification, sensory perception, and immunologic signatures. We also identified druggable targets using a network approach. Together these results may provide insights into understanding the genetic predisposition and underlying biological pathways of comorbid MDD and insomnia symptoms.

With the advancement of technology, signal modulation types are becoming increasingly diverse and complex. The phenomenon of signal time-frequency overlap during transmission poses significant challenges for the classification and recognition of mixed signals, including poor recognition capabilities and low generality. This paper presents a recognition model for fine-grained analysis of mixed signal characteristics, proposing a Geometry Coordinate attention mechanism and introducing a low-rank bilinear pooling module to more effectively extract signal features for classification. The model employs a residual neural network as its backbone architecture and utilizes the Geometry Coordinate attention mechanism for time-frequency weighted analysis based on information geometry theory. This analysis targets multiple-scale features within the architecture, producing time-frequency weighted features of the signal. These weighted features are further analyzed through a low-rank bilinear pooling module, combined with the backbone features, to achieve fine-grained feature fusion. This results in a fused feature vector for mixed signal classification. Experiments were conducted on a simulated dataset comprising 39,600 mixed signal time-frequency plots. The model was benchmarked against a baseline using a residual neural network. The experimental outcomes demonstrated an improvement of 9% in the exact match ratio and 5% in the Hamming score. These results indicate that the proposed model significantly enhances the recognition capability and generalizability of mixed signal classification.

The accompanying mechanical behavior during the flow of ore-rock dispersion is an important factor leading to the instability and failure of the orepass in the ore storage section. It is of great significance to accurately understand the instability characteristics of the well wall in the ore section, during the ore drawing process by understanding the flow characteristics and internal mechanical transfer mechanism of ore-rock dispersion. Using the discrete element method to analyze the flow characteristics, contact compactness, stress distribution characteristics and contact force probability distribution of the ore-rock dispersion, it realizes the quantitative characterization of the damage degree of ore-rock flow, and reveals the damage mechanism of mine storage wall. The results show that: (1) The friction between ore-rock particles, between ore-rock and well wall is an important reason for the change of the macroscopic flow form of ore-rock from “one” to “V” type. (2) The compactness and stress concentration of ores are increasing with the increase of storage depth, which is shown that with the increase of storage depth, the greater the probability of well wall instability. (3) The probability distribution of contact force strength between particles decreases exponentially in the whole process of ore drawing, in which the strong chain plays a major role in the stability of the dispersion system. (4) The number of overpressure and the overpressure coefficient can be used to quantitatively characterize the wall damage degree under the action of ore-rock flow. The dynamic side pressure decreases periodically in the form of exponential fluctuations, and the dynamic load formed by the ore-rock flow mainly played a role in the lower area of the ore storage section.

Plants do need a fixed proportion of carbon (C), nitrogen (N) and phosphorus (P) elements to maintain normal metabolic activities. The P fertilizers are widely used to supplement nutrients in subtropical plantations. Stoichiometric homeostasis reflects the strategy of plants to cope with various environments (including P fertilizer supply rate). It is thus of great significance to understand C:N:P stoichiometry in the plant-litter-soil system under P addition and stoichiometric homeostasis of plant tissues for fertilization management of slash pine (Pinus elliottii Engelm) plantations. We measured the C, N and P contents in root, branch, needle, litter and soil in slash pine plantations fertilized with four treatments - P1 (25 kg P ha−1 yr−1), P2 (50 kg P ha−1 yr−1), P3 (100 kg P ha−1 yr−1), and a control (CK) in subtropical China and calculated stoichiometric homeostasis of plant tissues. Results showed that P addition increased the capacity of needle to obtain C, N and P elements and altered the C:N:P stoichiometry of plant tissues, as well promoted the accumulation of C and P elements in soil, but had no significant effect on soil stoichiometry. The nutrient contents of needle and branch were higher than those of root and litter, indicating that slash pine was more inclined to allocate nutrient to the aboveground tissues. The stoichiometric homeostasis of C, N and P among plant tissues was ranked as follows: root > branch > needle, and homeostasis of nutrient elements in the needle was C > N > P. This indicated that the C, N and P stoichiometric homeostasis was various among plant tissues and elements types under P addition. These findings suggest P addition would alleviate the P limitation of slash pine growth in subtropical regions. In the future, long-term observation experiments should be conducted and the trade-off between P addition rates and economic and ecological benefits should be considered.

This paper designed a new type of generator, transgenerator, that integrates the wind turbine and flywheel into one system, aiming to make the flywheel distributed energy storage (FDES) more modular and scalable than the conventional FDES. The transgenerator is a three-member dual-mechanical-port (DMP) machine with two rotating members (inner and outer rotors) and one stationary member (stator). The transgenerator-flywheel system is introduced with the system configuration, transgenerator overview, flywheel operation principle and power management strategies, and control system. Simulations are performed in MATLAB/ Simulink to verify the system viability, including control system verification and the flywheel storage performance evaluation. Results show that the inner and outer rotors can be controlled independently with accurate and fast control response, and the grid-side control works properly. The flywheel performs well with considerable charging power and storage capacity.

This research focuses on the Hopf bifurcation occurring at a singular point with high-order degeneracy in a class of three-dimensional systems. Based on center manifold theorem, by expanding the technique for determining singular point values of degenerate singularities in two-dimensional systems, the formal series method to determine the singular point values at the high-order degenerate critical point is discussed. Furthermore, a class of specific three-dimensional differential systems with high-order degenerate singularities is explored. By computing the singular point values and determining center conditions, we proved that a minimum of 5 small-amplitude limit cycles in the vicinity of the origin. This research provides new perspectives on the center problem and limit cycle bifurcation in high-dimensional systems with high-order degenerate singular points.

While considering the sensitivity over the parameter optimization, it is essential to determine which parameters have the most significant implications on model performance. This study focuses on the baseflow recession constant as one of the independent basin parameters to forecast low flows, perform hydrograph analysis, and calibrate rainfall-runoff models for significant improvement. Prior studies examined that the optimization of data adjustment parameters can improve the hydrological model performance and determine the minimum acceptable data length for data scarce regions using the Xinanjaing model. However, it is essential to pay special attention to the sensitivity of the recession constant, which can also impact the model performance during the data scarcity. Therefore, this study extends the research to comprehend the recession constant sensitivity over data adjustment parameters in the shorter datasets leading to more reliable parameter estimation. In terms of that, this study explores how recession constant affects hydrological parameter estimation on annual scale while keeping data adjustment parameters constant in continuous hydrological modeling, employing the Xinanjiang (XAJ) model as a case study. This study considered two approaches of recession constant (cg); (i) assessing the relationship between cg and the data adjustment parameter (Cep), for the 28-year datasets, (ii) investigating the significant impacts of the sensitivity of cg over Cep in shorter datasets which can affect the estimation of the acceptable minimum data length in the data scarce basins. The study underscores the importance of the recession constant sensitivity for reliable continuous hydrological model predictions, especially in data-scared areas. The study’s outcomes enhance the understanding of the importance of parameter sensitivity and its relationship in conceptual hydrological modeling during the data limitations.

Background: Previous in vitro and in vivo studies have demonstrated that storage of cooked rice at 4 °C for 24 h and reheating to 65 °C significantly reduced starch digestibility and postprandial glycaemic responses. Moreover, the effect was greater for parboiled rice compared to other rice varieties commonly consumed in New Zealand. This study aimed to evaluate consumer preferences of related sensory attributes and consumer acceptability of several rice varieties freshly cooked or reheated. Method: Sixty-four consumers volunteered and recorded on Visual Analoge Scales their preference and acceptability of freshly prepared or cold-stored and reheated medium grain white, medium grain brown and parboiled rice. Results: All six rice samples were accepted by participants (average 54%). Reheated parboiled rice and reheated medium grain brown rice were both accepted by participants as a preferred staple meal compared to other rice samples. Among all rice samples, the sweetness and the flavour of freshly cooked warm medium-grain white rice were less preferred (scored 42.1% and 45.0% respectively) compared with other samples (P = 0.05). Participants who prepared and consumed brown rice at home regularly (more than 10 times per month), preferred the reheated brown rice (73.8% (67.4, 80.2)) and reheated parboiled rice (74.3% (67.9, 80.7)) (P < 0.001). Conclusions: It is suggested that reheated parboiled rice, with the lowest starch digestibility and glycaemic impact (both in vitro glucose release and in vivo glucose response) could be accepted as a healthier alternative for the daily staple meal.

Liquid-liquid phase separation (LLPS) of proteins has been found ubiquitously in eukaryotic cells, critical in the controlling of many biological processes through forming a temporary condensed phase with different bimolecular components. TDP-43 is recruited to stress granules in cells and is the main component of TDP-43 granules and proteinaceous amyloid inclusions in patients with amyotrophic lateral sclerosis (ALS). TDP-43 low complexity domain (LCD) is able to demix in solution forming the protein condensed droplets. The molecular interactions regulating its LLPS were investigated at the protein fusion equilibrium stage, where the droplets stopped growing. We found the molecules in the droplet were still liquid-like but with enhanced intermolecular helix-helix interaction in the LCD. The protein would start to aggregate after about 200 minutes of lag time and aggregate slower than at the condition when the protein does not phase separate or the molecules have a reduced intermolecular helical interaction. A structural transition intermediate towards protein aggregation was also discovered involving a decrease of the intermolecular helix-helix interaction and a reduction in the helicity. Therefore, LLPS and the intermolecular helical interaction could help maintain the stability of TDP-43 LCD.

Combining Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) spectra data and artificial intelligence (AI) has been introduced for rapid prediction on antibiotic susceptibility test (AST) of S. aureus. Based on the AI predictive probability, the cases with probabilities between low and high cut-offs are defined as “grey zone”. We aimed to investigate the underlying reasons of unconfident (grey zone) or wrong predictive AST. A total 479 S. aureus isolates were collected, analyzed by MALDI-TOF, and AST prediction, standard AST were obtained in a tertiary medical center. The predictions were categorized into the correct prediction group, wrong prediction group, and grey zone group. We analyzed the association between the predictive results and the demographic data, spectral data, and strain types. For MRSA, larger cefoxitin zone size was found in the wrong prediction group. MLST of the MRSA isolates in the grey zone group revealed that uncommon strain types composed 80%. Amid MSSA isolates in the grey zone group, the majority (60%) was composed of over 10 different strain types. In predicting AST based on MALDI-TOF AI, uncommon strains and high diversity would contribute to suboptimal predictive performance.

High dimensional statistical analysis for the yield of large-scale circuits is quite difficult due to expensive simulations, especially for the memory circuits with high sigma requirement (e.g., SRAM). In this paper, we developed an efficient sparse additive model to substitute simulations. To fit high sigma region accurately, the modeling center is moved to near failure boundary searched by scaling the shape of sampling function. To solve the model efficiently, the process variables are grouped by standard cells so that the model can be solved by our developed blockwise greedy algorithm. The experiments on the 28nm memory circuits validate that our method achieves high accuracy and efficiency compared with other state-of-art works.

Over the past decades, overweight and obesity has become a global epidemic and the leading threat for death. To prevent the serious risk, an overweight or obese individual must apply a long-term weight-management strategy to control food intake and physical activities, which is however, not easy. Recently, with the advances of information technology, more and more people can use wearable devices and smartphones to obtain physical activity information, while they can also access various health-related information from Internet online social networks (OSNs). Nevertheless, there is a lack of an integrated approach that can combine these two methods in an efficient way. In this paper, we address this issue and propose a novel mobile-social framework for health recognition and recommendation, namely, H-Rec². The main ideas of H-Rec² include (1) to recognize the individual's health status using smartphone as a general platform, and (2) to recommend physical activity and food intake based on personal health information, life science principles, and health-related information obtained from OSNs. To demonstrate the potentials of the H-Rec² framework, we develop a prototype that consists of four important components: (1) an activity recognition module that senses physical activity using accelerometer, (2) a health status modeling module that applies a novel algorithm to generate personalized health status index, (3) a restaurant information collection module that collects relevant information from OSN, and (4) a restaurant recommendation module that provides personalized and context-aware recommendation. To evaluate the prototype, we conduct both objective and subjective experiments, which confirm the performance and effectiveness of the proposed system.

Predators are dependent on the capture of prey to meet their energetic and nutritive requirements, imposing a regime of predation risk. Consequently, prey experience both consumptive and non-consumptive effects. Non-consumptive effects may manifest through altered growth and ontogenetic trajectories of prey species, a dynamic modulated by olfactory or other sensory cues from predators. Bactrocera dorsalis Hendel represents a great invasive threat to global horticulture. While earlier research has primarily centered on the consumptive interactions between B. dorsalis and its natural enemies, the potential consequences of non-consumptive interactions on the development of B. dorsalis have been overlooked. In this study, we investigated the impact of predation risk effects, induced by both visual exposure to the predatory mantis Hierodula patellifera Serville and its associated odor, on the life history traits of B. dorsalis. Female B. dorsalis demonstrated reduced development time in the presence of isolated H. patellifera or H. patellifera odor, yet evidenced significantly increased fecundity. Conversely, males displayed no significant change in development time. Additionally, neither female nor male body weight at death was significantly influenced by predation risk from isolated predators or predator odor. These results indicated adaptive developmental strategies of B. dorsalis when faced with risks from predators and highlight the important role of predator odor, which has the potential to lay the groundwork for improving biological control efforts and innovative approaches within pest control.

Objective: To use the ancient and modern medical record cloud platform (V2.3.5) to organize and explore the medication patterns of the "Three Causes, Extremity, and One Disease Syndrome Formula" by Chen Wuxuan, and to summarize its therapeutic ideas. Method: Collect and organize the "San Yin Si Tian Fang" in the "San Yin Ji Yi Zheng Fang Lun", and use the modern medical record cloud platform (V2.3.5) to conduct medication frequency statistical analysis, cluster analysis, and complex network analysis. As a result, a total of 16 Chinese herbal medicines were collected in the "Three Causes, Extreme and One Disease Syndrome Formula", involving 75 traditional Chinese medicines. Statistical analysis showed that roasted licorice was the most commonly used, followed by Pinellia ternata, papaya, ginger, and Poria cocos; Medications mainly include warm drugs, sweet and pungent flavors, as well as drugs that promote lung and spleen meridians. Cluster analysis can divide the above-mentioned traditional Chinese medicine into two groups, with specific grouping as follows. Group 1: ginger, white peony, aconite, papaya, and achyranthes bidentata; Group 2: roasted licorice, poria cocos, dried ginger, pinellia ternata, and green peel. Conclusion: The characteristics of the 16 prescriptions are biased towards Xin Gan Wen, emphasizing the regulation of the spleen and stomach, which may be related to the common use of prescription by doctors in the Song Dynasty and the tendency towards warm and dry medication.

The broad emission bump in the electromagnetic spectra observed following the detection of gravitational waves created during the kilonova event of merger of two neutron stars in August 2017, GW170817, has been linked to the heavy elements of lanthanides (Z=57-71), and a new understanding of creation of heavy elements in the r-process. The initial spectral emission bump has a wavelength range of 3000 - 7000 \AA, thus covering the region of ultraviolet (UV) to optical (O) wavelengths, and is similar to those seen for lanthanides. Most lanthanides have large number of closely lying energy levels which introduce extensive sets of radiative transitions which often form broad region of lines of significant strength. The current study explores these broad features through photoabsorption spectroscopy of 25 lanthanides ions, Ho I-III, Er I-IV, Tm I-V, Yb I-VI and Lu I-VII. With excitations only to a few orbitals up beyond the ground configurations, we find most of these ions cover large number of bound levels with open $4f$ orbital and produce tens to about hundred thousands lines that may form one or multiple broad features in X-ray to UV, O, and infrared (IR) regions. Spectrum of each of 25 ions is presented indicating presence, shape and wavelength region of the features. Accuracy of atomic data to interpret the merger spectra has been a outstanding problem. The present study aims at providing improved atomic data for energies and transition parameters obtained using relativistic Breit-Pauli approximation implemented in the atomic structure code SUPERSTRUCTURE. The present data have been benchmarked with available experimental data for energies and transition parameters. The study finds that number of ions under the present study are possible contributors of the emission bump of GW170817. All atomic data will be made available online at NORAD-Atomic-Data database.

Accurate and reliable mid-long runoff prediction (MLTRP) is of great importance in water re-sources management. However the MLTRP is not suitable in each basin and how to evaluate the applicability of MLTRP is still a question. Therefore, the total mutual information (TMI) index is developed in this study based on the predictor selection method using mutual information (MI) and partial MI (PMI). The relationship between the TMI and the predictive performance of five models is analyzed by applying five models in 222 forecasting scenarios in Australia. The results over 222 forecasting scenarios demonstrate that, compared with the MI, the developed TMI index can better represent the available information in the predictors, and has more significant negative correlation with the RRMSE with the correlation coefficient between -0.62 and -0.85. This means the model's predictive performance will become better along with the increase of TMI, and there-fore the developed TMI index can be used to evaluate the applicability of MLTRP. When TMI is more than 0.1, the available information in the predictors can support the construction of MLTRP models. In addition, the TMI is used to partly explain the difference of predictive performance among five models. In general, the complex models, which can better utilize the contained infor-mation, are more sensitive to the TMI, and have more significant improvement in terms of predic-tive performance along with the increase of TMI. This research can provide support for the study of MLTRP.

In recent decades, with the ever-growing scale of video data, near-duplicate videos continue to emerge. Data quality issue caused by near-duplicate videos is becoming more and more prominent, which has affected the application of normal videos. Although current studies on near-duplicate video detection can be helpful to uncover data quality issues for videos, they still lack a process of automatic merging for the video data represented by high-dimensional features, which are difficult to automatically clean the near-duplicate videos to improve data quality for video datasets. At present, there are few studies on near-duplicate video data cleaning. The existing studies have the sensitive problems of video data orderliness and clustering initial center under a condition that prior distribution is unknown, which seriously affect the accuracy of near-duplicate video data cleaning. To address the above issues, an automatic near-duplicate video data cleaning method based on a consistent feature hash ring is proposed in this paper. First, a residual network with convolutional block attention modules, a long short-term memory deep network, and an attention model are integrated to construct an RCLA deep network with the multi-headed attention mechanism to extract spatiotemporal features of video data. Then, a consistent feature hash ring is constructed, which can effectively alleviate the sensitivity of video data orderliness while providing a condition of near-duplicate video merging. To reduce the sensitivity of the initial cluster centers to results of near-duplicate video cleansing, an optimized feature distance-means clustering algorithm is constructed by utilizing a mountain peak function on a consistent feature hash ring, which can implement automatic cleaning of near-duplicate video data. Finally, experiments are conducted based on a commonly used dataset named CC_WEB_VIDEO and a coal mining video dataset. Compared with some existing works, simulation results demonstrate that the performance of the proposed method.

Amid the swift progression of the global automobile industry, the aspiration for lightweight vehicle design has surfaced as a crucial approach to boost fuel efficiency and curtail environmental impact. The objective of this study revolves around achieving holistic optimization of vehicle structure via detailed scrutiny of vehicle process characteristics, amalgamated with a Back Propagation neural network (BPNN) optimized by a genetic algorithm (GA) and a topology optimization (TO) method.The process initiates with an examination of the vehicle's technical characteristics, succeeded by an optimization protocol that couples GA with BPNN. This exhaustive optimization procedure derives the best-fit values of design parameters and identifies the globally optimal lightweight design approach. Subsequently, a comprehensive structural optimization is actualized by modifying the topological distribution of the structure.A simulation experiment of the conceptual car body beam skeleton is conducted as a conclusive step, and the anti-collision capacity of the car body beam skeleton is assessed by measuring deformation intrusion. The findings reveal that in the vehicle topology optimization, a comparative analysis of pre and post-optimization results indicates an improved topological density across diverse sections. The topological density of the vehicle's frontal structure escalates from 0.75 to 0.8. Following optimization, the stiffness assessment records a marginal increase (within the range of 0.02–0.05), implying that the lightweight design does not compromise the general rigidity of the structure.The optimized body structure manifests superior crashworthiness in the crash test: the deformation intrusion diminishes by 27% in front-end collisions. In side impacts, the deformation and intrusion at critical points are reduced by 13.15% to 10% respectively. The comprehensive method proposed herein proves to be an efficient strategy to actualize the lightweight design of vehicles.

We study the Gaudin models with gl(1|1) symmetry that are twisted by a diagonal matrix and defined on tensor products of polynomial evaluation gl(1|1)[t]-modules, extending all the results of to the twisted case. Namely, we give an explicit description of the algebra of Hamiltonians (Gaudin Hamiltonians) acting on tensor products of polynomial evaluation gl(1|1)[t]-modules and show that there exists a bijection between common eigenvectors (up to proportionality) of the algebra of Hamiltonians and monic divisors of an explicit polynomial written in terms of the highest weights and evaluation parameters. In particular, our result implies that each common eigenspace of the algebra of Hamiltonians has dimension one. We also give dimensions of the generalized eigenspaces.

On the basis of the force and safety factor analysis of traditional retaining wall, a new analytical method of force and displacement of slope is suggested, the numerical theoretical solution of the stress distribution of the sliding body can be obtained under the conditions, which the stresses distribution are satisfied with the differential equilibrium equations, the boundary conditions, the compatibility equation and the macroscopic equilibrium equations. The interface stresses between the sliding body and the retaining wall are continuous, the theoretical solution of retaining wall stress distributions can be gotten, while the stress differential equilibrium equation, the compatibility equation, macroscopic force and moment balance equations are satisfied. The strain and displacement solutions can be obtained by using Duncan Chang and Hooke constitutive equations for the slope and the retaining wall respectively. The transfer station of landfill in the Guandukou Town of Badong County is taken as an example, the results of the sliding body and retaining wall analysis show: The stress and strain solutions of a slope and a retaining wall can be obtained by the proposed method, the forces between the retaining wall and the sliding body include shear stress and normal stress, and the stress distributions change with the deformation of the sliding body, the shape and material of retaining wall can be optimized according to the calculation results，it is feasible for the proposed analysis method of slope with retaining wall design to be run many years.

Inflammasomes are multiprotein complexes that activate inflammatory responses by inducing pyroptosis and secretion of pro-inflammatory cytokines. Along with many previous studies on inflammatory responses and diseases induced by canonical inflammasomes, an increasing number of studies have demonstrated that non-canonical inflammasomes, such as mouse caspase-11 and human caspase-4 inflammasomes, are emerging key players in inflammatory responses and various diseases. Flavonoids are natural bioactive compounds found in plants, fruits, vegetables, and teas and have pharmacological properties in a wide range of human diseases. Many studies have successfully demonstrated that flavonoids play an anti-inflammatory role and ameliorate many inflammatory diseases by inhibiting canonical inflammasomes. Others have demonstrated the anti-inflammatory roles of flavonoids in inflammatory responses and various diseases, with a new mechanism by which flavonoids inhibit non-canonical inflammasomes. This review discusses recent studies that have investigated the anti-inflammatory roles and pharmacological properties of flavonoids in inflammatory responses and diseases induced by non-canonical inflammasomes and further provides insight into developing flavonoid-based therapeutics as potential nutraceuticals against human inflammatory diseases.

Background: Globally, hot cooked refined rice is consumed in large quantities and is a major contributor to dietary glycaemic load. This study aimed to compare the glycaemic potency of hot and cold stored parboiled rice to widely available medium grain white rice. Method: Twenty-eight healthy volunteers participated in a three treatment experiment where postprandial blood glucose was measured over 120 minutes after consumption of 140g of rice. Three rice samples were freshly cooked medium-grain white rice, freshly cooked parboiled rice, and parboiled rice stored overnight at 4 ºC. All rice was served warm at 65 ºC. Chewing time was recorded. Results: The 24-hours cold-stored and reheated parboiled rice resulted in a 42% and 12% lower blood glucose concentration trajectory than freshly cooked medium-grain white rice and freshly cooked parboiled rice. Chewing time for 10g cold stored parboiled rice was 6 seconds (25%) longer and was considered more palatable, visually appealing and better tasting than freshly cooked medium grain (all P<0.05). Conclusions:. For regular consumers of rice reheating cooked rice after cold storage would lower the dietary glycaemic load and long term may reduce risk for type 2 and gestational diabetes. More trials are needed to identify the significance.

Abstract: Bacillus subtilis fmb60, which has broad-spectrum antimicrobial activities was isolated from plant straw compost. A hybrid NRPS/PKS cluster was screened from the genome. Sixteen secondary metabolites produced by the gene cluster were isolated and identified using LC-HRMS and NMR. Three lipoamides D–F (1-3) and two amicoumacin derivatives, amicoumacins D, E (4, 5), were identified, and are reported here for the first time. Lipoamides D–F exhibited strong antibacterial activities against harmful foodborne bacteria, with the MIC ranging from 6.25 to 25 µg/mL. Amicoumacin E scavenged 38.8% of ABTS+ radicals at 1 mg/mL. Direct cloning and heterologous expression of the NRPS/PKS and ace gene cluster identified its importance for the biosynthesis of amicoumacins. This study demonstrated that there is a high potential for biocontrol utilization of B. subtilis fmb60, and genome mining for clusters of secondary metabolites of B. subtilis fmb60 has revealed a greater biosynthetic potential for the production of novel natural products than previously anticipated.

Health issues of children with intellectual disabilities (ID) have gained significant attention as a key focus of China health goals. This study aimed to compare the differences in displacement skills and problem behaviors among children with varying degrees and types of ID, while also exploring their relationship. The study included 90 participants who were children with ID and had completed TGMD-2 displacement skills and Strengths and Difficulties Questionnaire (SDQ) assessments. Covariance, partial correlation, and multiple linear regression analyses were conducted to examine the differences and correlations between these factors. The findings revealed that higher severity of intellectual disability was associated with lower scores in locomotor skills and increased manifestation of problem behaviors. Notably, there were significant variations in locomotor skills and problem behaviors among children with different types of intellectual disabilities. There is a positive correlation between locomotor skills and problem behaviors in children with intellectual disabilities, where locomotor skills can predict the occurrence of problem behaviors. In Conclusion, the research confirms that the development of locomotor skills can have a positive impact on the accompanying problem behaviors of children with developmental disabilities.

In autonomous driving systems, high-speed and real-time image processing, along with object recognition, are crucial technologies. This paper builds upon the research achievements in in-dustrial item sorting systems and proposes an object recognition and sorting system for auton-omous driving. In industrial sorting lines, goods sorting robots often need to work at high speeds to efficiently sort large volumes of items. This poses a challenge to the robot's real-time vision and sorting capabilities, making it both practical and economically viable to implement a real-time and low-cost sorting system in a real-world industrial sorting line. Existing sorting systems have limitations such as high cost, high computing resource consumption, and high power consump-tion. These issues lead to the fact that existing sorting systems are typically used only in large industrial plants. In this paper, we design a high-speed, low-cost, low-resource-consumption FPGA (Field-Programmable Gate Array) based item sorting system that achieves similar perfor-mance to current mainstream sorting systems at a lower cost and consumption than existing sorting systems. The recognition part employs a morphological recognition method, which segments the image using a frame difference algorithm and then extracts the color and shape features of the items. To handle sorting, a six-degree-of-freedom robotic arm is introduced in the sorting segment. The improved cubic B-spline interpolation algorithm is employed to plan the motion trajectory and consequently control the robotic arm to execute the corresponding actions. Through a series of experiments, this system achieves an average recognition delay of 25.26ms, ensures smooth operation of the gripping motion trajectory, minimizes resource consumption, and reduces implementation costs.

Vibration signal analysis is regarded as a fundamental approach in diagnosing faults in rolling bearings, and recent advancements have shown notable progress in this domain. However, the presence of substantial background noise often results in the masking of these fault signals, posing a significant challenge for researchers. In response, an Adaptive Denoising Autoencoder (ADAE) approach is proposed in this paper. The data representations are learned by the encoder through convolutional layers, while the data reconstruction is performed by the decoder using deconvolutional layers. Both the encoder and decoder incorporate adaptive shrinkage units to simulate denoising functions, effectively removing interfering information while preserving sensitive fault features. Additionally, dropout regularization is applied to sparsify the network and prevent overfitting, thereby enhancing the overall expressive power of the model. To further enhance ADAE's noise resistance, shortcut connections are added. Evaluation using publicly available datasets under scenarios with known and unknown noise demonstrates that ADAE effectively enhances the signal-to-noise ratio in strongly noisy backgrounds, facilitating accurate diagnosis of faults in rolling bearings.

Laser-targeted weeding methods further enhance the sustainable development of green agriculture, with one key technology being the improvement of weed localization accuracy. Here, we propose an improved YOLOv8 instance segmentation based on bidirectional feature fusion and deformable convolution (BFFDC-YOLOv8-seg) to address the challenges of insufficient weed localization accuracy in complex environments with resource-limited laser weeding devices. Initially, by training on extensive datasets of plant images, the most appropriate model scale and training weights are determined, facilitating the development of a lightweight network. Subsequently, the introduction of the Bidirectional Feature Pyramid Network (BiFPN) during feature fusion effectively prevents the omission of weeds. Lastly, the use of Dynamic Snake Convolution (DSConv) to replace some convolutional kernels enhances flexibility, benefiting the segmentation of weeds with elongated stems and irregular edges. Experimental results indicate that the BFFDC-YOLOv8-seg model achieves a 4.9% increase in precision, an 8.1% increase in recall rate, and a 2.8% increase in mAP50 value to 98.8% on a vegetable weed dataset compared to the original model. It also shows improved mAP50 over other typical segmentation models such as Mask R-CNN, YOLOv5-seg, and YOLOv7-seg by 10.8%, 13.4%, and 1.8%, respectively. Furthermore, the model achieves a detection speed of 24.8 FPS on the Jetson Orin nano standalone device, with a model size of 6.8MB that balances between size and accuracy. The model meets the requirements for real-time precise weed segmentation, suitable for complex vegetable field environments and resource-limited laser weeding devices.

The rapid development of China’s textile industry leads to consumption and pollution of large volumes of water. Therefore, the textile industry has been the focus of water conservation and waste reduction in China’s 13th Five-Year Plan (2016–2020). The premise of sustainable development is to achieve decoupling of economic growth from water consumption and wastewater discharge. In this work, changes in blue water (water consumption), grey water (water pollutants), and water footprints of the textile industry from 2001 to 2014 were calculated. The relationship between water footprint and economic growth was then examined using the Tapio decoupling model. Furthermore, factors influencing water footprint were determined through logarithmic mean Divisia index (LMDI) method. Results show that the water footprint of China’s textile industry has strongly decoupled for five years (2002, 2006, 2008, 2011, and 2013) and weakly decoupled for four years (2002, 2007, 2009, and 2010). A decoupling trend occurred during 2001–2014, but a steady stage of decoupling has not been achieved yet. Based on the decomposition analysis, the total water footprint is mainly increased by production scale and inhibited by the technology. In addition, the effect of industrial structure adjustment is relatively weak.

Innovative interventions in the planning and design of stair and escalator facilities call for understanding their effects on stair use. This study considers five planning variables for the twinned stair and escalator facilities–stair pitch and width, angle of deviation, height and separating distance. Public sites were identified in 8 commercial districts in Beijing. Facilities (n=21) presenting heterogeneously across variables were sampled for simultaneous up and down pedestrian counts in 18 5-minute video segments middays, for a total of 1464 counts. Stair width accounts for 20% of the variance in ascending rate and 10% in descending. Plan angle accounts for 2% in ascending and 5% in descending, while pitch accounts for 1% in ascending and 5% in descending. The study confirms the effects of layout and design of stairway and escalator facilities on facility choice. The results point directly to interventions in support of higher stair-climbing rates.

The rapid urbanization in China has significantly contributed to the vast expansion of urban built-up areas. Precisely extracting and monitoring these areas is crucial for understanding and optimizing the developmental process and spatial attributes of smart, compact cities. However, most existing studies tend to focus narrowly on a single city or global scale with a single dimension, often ignoring mesoscale analysis across multiple urban agglomerations. In contrast, our study employs GIS and image processing techniques to integrate multi-source data for the identification of built-up areas. We specifically compare and analyze two representative urban agglomerations in China: the Yangtze River Delta (YRD) in the east and the Chengdu-Chongqing (CC) region in the west. We use different methods to extract built-up areas from socio-economic factors, natural surfaces, and traffic network dimensions. Additionally, we utilize a high-precision built-up area dataset of China as a reference for verification and comparison. Our findings reveal several significant insights: (1) The multi-source data fusion approach effectively enhances the extraction of built-up areas within urban agglomerations, achieving higher accuracy than previously employed methods. (2) Our research methodology performs particularly well in the CC urban agglomeration. The average precision rate in CC is 96.03%, while the average precision rate in YRD is lower at 80.33%. This study provides an objective and accurate assessment of distribution characteristics and internal spatial structure of built-up areas within urban agglomerations. This method offers a new perspective for identifying and monitoring built-up areas in Chinese urban agglomerations.

The Shule River Basin (SRB) is a typical arid area in northwest China with a fragile ecology. Un-derstanding vegetation dynamics and its response to climate change and human activities provides essential information for ecological and environmental resource management. This study extracted fractional vegetation coverage (FVC) data from 2000 to 2019 using the Google Earth Engine plat-form and Landsat satellite images, employing trend analysis and other methods to examine spati-otemporal changes in vegetation in the SRB. Additionally, partial correlation and residual analysis were utilized to explore the response of FVC to climate change and human activities. The main results were as follows: (1) The regional average FVC in the SRB showed a significant upward trend from 2000 to 2019, increasing by 1.3 × 10−3 y–1. The area within 1 km of roads experienced a higher increase of 3 × 10−3 y–1, while the roadless areas experienced a lower increase of 1.1 × 10−3 y–1. Road construction from 2004 to 2006 significantly reduced the FVC within 200 meters of the roads. FVC spatial heterogeneity in the SRB is significant. (2) Partial correlation analysis shows that FVC has a strong positive correlation with precipitation and surface water area, with correlation coefficients of 0.575 and 0.744, respectively. There is a weak negative correlation between FVC and land surface temperature (LST). FVC changes are more influenced by precipitation than by LST. (3) Compared to climate factors, human activities have a greater impact on vegetation dynamics in the SRB. The contributions of climate change to vegetation recovery are increasing. (4) The area changes of dif-ferent land types are closely related to climate factors and human activities, reflecting their impact on vegetation. These results provide valuable information for ecosystem restoration and environ-mental protection in the SRB.

Epitaxial lithium ferrite (LiFe5O8) films with different thicknesses have been successfully fabricated on SrTiO3 (001) substrates by magnetron sputtering deposition technique. The microstructural and magnetic properties are characterized by advanced transmission electron microscope and magnetic measurement device. It was found that the formation of structural defects can be influenced by the thickness of the film. Apart from the misfit dislocations, the orientation domains form in thinner film and twin boundaries appear in thicker film, respectively, contributing to the misfit strain relaxation in the heterosystem. The magnetic measurement shows that the thinner films have enhanced magnetization and a relatively lower coercive field compared with the thicker films containing the antiferromagnetic twin boundaries. Our results provide a way for tuning the microstructure and magnetic properties of lithium ferrite films by changing the film thickness.

Hydrogen is considered as an ideal substitute to the traditional fossil fuels because of its widespread sources, high calorific value of combustion, and zero carbon emissions. The electrocatalytic water-splitting to produce hydrogen is also deemed to be the best approach, however, it is a challenge to make high-efficient and low-cost electrocatalysts. Single-atom catalysts (SACs) are considered the most promising candidate to replace the traditional noble-metal catalysts. Compared with SACs, the dual-atom catalysts (DACs) are of greater attraction including higher metal loading, more versatile active sites, and excellent catalytic activity. In the review, several general synthetic strategies and structural characterization methods of DACs are introduced, and the mechanisms of hydrogen evolution reaction (HER) and oxygen evolution reactions (OER) are discussed. The authors hope that the review has given some insights and inspiration to the researchers about DACs in electrocatalytic water-splitting.

Demethyleneberberine is an active component extracted from the Chinese herbal drug Cortex Phellodendri. It is also a metabolite of the berberine in animals and humans. However, the pharmacokinetics, tissue distribution and excretion of demethyleneberberine have not been reported. The present study aimed to investigate the pharmacokinetic parameters of demethyleneberberine by developing a method of high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). The detection was performed by using positive ion electrospray ionization in multiple reaction monitoring mode. The MS/MS ion transitions were monitored at m/z 324.4→308.3 for demethyleneberberine and 465.5→350.3 for IS. After oral administration of demethyleneberberine in rats and mice, the pharmacokinetics, tissue distribution, and excretion of desmethylberberine in rats and mice were comparatively studied for the first time. The plasma concentration of desmethylberberine reached its peak within 5 min after oral administration in both rats and mice. The bioavailability of rats and mice was comparable, ranging from 4.47% to 5.94%, higher than that of berberine. The total excretion of desmethylberberine in urine, feces and bile is 7.28~9.77%. These findings provide valuable insights into the pharmacological and clinical research on desmethylberberine.

In order to investigate the relationship between government policy, the service and design of rural crowdsourcing spaces, the self-efficacy of returning youth, and the innovation performance of businesses, this study focuses on gathering data by distributing questionnaires to returning youth in rural crowdsourcing spaces and developing a structural model. The results demonstrate how important government policies are in encouraging youth entrepreneurship in their local communities. It has the potential to enhance both the development of rural crowdsourcing spaces and the self-efficacy of young entrepreneurs, thereby enhancing the innovative capabilities of local entrepreneurial businesses. Therefore, in order to encourage economic development in rural areas, the government should improve pertinent support measures.

Viruses can induce the fusion of infected and neighboring cells, leading to the formation of syncytia. Cell-cell fusion is mediated by viral fusion proteins on the plasma membrane of infected cells that interact with cellular receptors on neighboring cells. Viruses use this mechanism to spread rapidly to adjacent cells or escape host immunity. For some viruses, syncytium formation is a hallmark of infection and a known pathogenicity factor. For others, the role of syncytium formation in viral dissemination and pathogenicity remains poorly understood. Human cytomegalovirus (HCMV) is an important cause of morbidity and mortality in transplant patients and the leading cause of congenital infections. Clinical HCMV isolates have broad cell tropism but differ in their ability to induce cell-cell fusions, and little is known about the molecular determinants. We developed a system to analyze HCMV glycoprotein B (gB) variants in a defined genetic background. HCMV strains TB40/E and TR were used as vectors to compare the fusogenicity of six gB variants from congenitally infected fetuses with those from three laboratory strains. Five of them conferred the ability to induce fusion of MRC-5 human embryonic lung fibroblasts to one or both backbone strains, as determined by a split GFP-luciferase reporter system. The same gB variants were not sufficient to induce syncytia in infected ARPE-19 epithelial cells, suggesting that additional factors are involved. The system described here allows a systematic comparison of the fusogenicity of viral envelope glycoproteins and may help to clarify whether fusion-promoting variants are associated with increased pathogenicity.

Excretory-secretory products (ESPs) are the main research targets for investigating the hosts and helminths interaction. Parasitic worms can migrate to parasitic sites and avoid the host immune response by secreting this product. Angiostrongylus cantonensisis an important food-borne zoonotic parasite that causes severe neuropathological damage and symptoms, including eosinophilic meningitis or meningoencephalitis in humans. Benzaldehydes are organic compounds composed of a benzene ring and formyl substituents. This compound has anti-inflammatory and antioxidation properties. Previous studies showed that 3-hydroxybenzaldehyde (3-HBA) and 4-hydroxybenzaldehyde (4-HBA) can reduce apoptosis in A. cantonensis ESPs treated astrocytes. These results on the protective effect underlying benzaldehyde have primarily focused on cell survival. The study was designed to investigate the molecular mechanisms of endoplasmic reticulum stress (ER stress) and oxidative stress in astrocytes in A. cantonensis ESPs treated astrocytes and to evaluate the therapeutic consequent of 3-HBA and 4-HBA. First, we initially established the RNA-seq dataset in each group, including Normal, ESPs, ESPs+3-HBA, and ESPs+4-HBA. We also found that benzaldehyde (3-HBA and 4-HBA) can stimulate astrocytes to express ER stress-related molecules after ESP treatment. The level of oxidative stress could also be decreased in astrocytes by elevating antioxidant activity and reducing ROS generation. These results suggested that benzaldehyde may be a potential therapeutic compound for human angiostrongyliasis to support brain cell survival by inducing the expression levels of ER stress- and oxidative stress-related pathway.

With the gradual improvement of coal mining efficiency, the disturbance of groundwater system caused by the high-intensity mining mode also increases, which is a more severe challenge to the prevention of mine safety and the protection of water resources in mining areas. How to accurately describe the dynamic changes of the groundwater system under mining and quantitatively predict mine water inflow is a major problem in the current research. Based on the full analysis of the response characteristics of groundwater system to the extraction disturbance, this paper forms a kind of method to establish a mine hydrogeological conceptual model that can accurately represent the water inrush process, and uses the MODFLOW non-structural division grid to accurately characterize the formation structure, and finally make accurate water inflow prediction. Taking the Caojiatan Coal Mine in Shaanxi Province, China as an example, a numerical model of unstructured mine water inrush was established for the first time, and the changes of water inflow source and water inflow intensity were quantitatively evaluated. Compared with the traditional water inflow prediction method, it is found that the prediction accuracy is improved by 12%~17% by detailing the response characteristics of complex groundwater system under high-strength coal seam mining conditions. The method is of great significance and promotion value for the comprehensive understanding of the disturbance characteristics of human underground engineering activities, such as coal mining, on the groundwater system, and for accurately predicting water inflow.

In coastal areas around the world, seagrass meadows play a crucial ecological and economic role. A large amount of seagrass beds dominates primary production and contributes to the high secondary productivity of this ecosystem. The microbial loop (consuming bacterial biomass by grazers and using seagrass-derived detritus by bacteria) may be an important mechanism for transferring seagrass-derived organic matter to the aquatic food chain. This study aims to improve our understanding of how bacterial growth and mortality (grazing and viral lysis rates) differ in seagrass and adjacent unvegetated meadow habitats. We found that viral lysis and grazing caused similar mortality rates of bacteria in a seagrass environment during the summer. It has been found, however, that bacterial production is controlled by the availability of resources (bottom-up control) and is cycled within the bacteria-virus-DOC loop in adjacent unvegetated waters. Our study region may be affected by this shift in organic matter fate and cycling.

Agriculture is an industry that heavily relies on the environment. The increasing frequency of ex-treme disasters attributable to climate change has adversely affected agricultural land and dis-rupted the stability of the supply of agricultural products. Therefore, we implemented a research program focused on current strategies for adapting to agricultural meteorological disasters. The primary goal was to actively promote disaster prevention information and techniques through information platforms and applications and to provide refined forecasting and an early warning system to enhance preparedness for and recovery from agricultural disasters. This initiative can transform passive mitigation into dynamic action by disseminating crucial information to farmers. We integrated meteorological data and crop characteristics to develop disaster prevention strate-gies for the predisaster, during-disaster, and postdisaster stages to empower farmers to implement autonomous disaster prevention, ensuring their profitability and minimizing the impact of disas-ters. This paper presents an agricultural disaster prevention system involving cross-disciplinary collaboration to establish an early warning system for crop disasters. However, the effectiveness of the early warning system relies on the availability of complete meteorological and crop infor-mation, necessitating high-density agricultural meteorological stations, refined weather forecast services, historical crop damage data, and ongoing research and development on disaster preven-tion technology. In the system, a diversified social media interface is used to provide local farmers with weather forecast information. When impending disasters are identified, the platform acti-vates disaster prevention measures to reduce agricultural losses. This article paper introduces Taiwan’s agricultural disaster prevention system as a complete disaster prevention strategy.

Mass hauling operations play central roles in construction projects. They typically use many haulers that consume large amounts of energy and emit significant quantities of CO₂. However, practical methods for estimating the energy consumption and CO₂ emissions of such operations during project planning are lacking. This paper presents a detailed model for estimating the energy consumption and CO₂ emissions of mass haulers that integrates the mass hauling plan with a set of predictive equations. The mass hauling plan is generated using a planning program such as DynaRoad in conjunction with data on the productivity of selected haulers and the amount of material to be hauled during cutting, filling, borrowing, and disposal operations. This plan is then used as input for estimating the energy consumption and CO₂ emissions of the selected hauling fleet. The proposed model will help planners to assess the energy and environmental performance of mass hauling plans, and to select hauler and fleet configurations that will minimize these quantities. The model was applied in a case study, demonstrating that it can reliably predict energy consumption, CO₂ emissions, and hauler productivity as functions of the hauling distance for individual haulers and entire hauling fleets.

Water quality forecasting is increasingly significant for agricultural management and environmental protection. Enormous amounts of water quality data are increasingly being collected by advanced sensors, which leads to an interest in using data-driven models for predicting trends in water quality. However, the unpredictable background noises introduced during water quality monitoring seriously degrade the performance of those models. Meanwhile, artificial neural networks (ANN) with feed-forward architecture lack the capability of maintaining and utilizing the accumulated temporal information, which leads to biased predictions in processing time series data. Hence, we propose a water quality predictive model based on a combination of Kernal Principal Component Analysis (kPCA) and Recurrent Neural Network (RNN) to forecast the trend of dissolved oxygen. Water quality variables are reconstructed based on kPCA method, which aims to reduce the noise from the raw sensory data and preserve actionable information. With the RNN's recurrent connections, our model can make use of the previous information in predicting the trend in the future. Data collected from Burnett River, Australia was applied to evaluate our kPCA-RNN model. The kPCA-RNN model achieved R2 scores up to 0.908, 0.823 and 0.671 for predicting the concentration of dissolved oxygen in the upcoming 1, 2 and 3 hours, respectively. Compared to current data-driven methods like ANN and SVR, the predictive accuracy of the kPCA-RNN model was at least 8 %, 17 % and 21 % better than the comparative models in these 3 cases. The study demonstrates the effectiveness of the kPAC-RNN modeling technique in predicting water quality variables with noisy sensory data.

By repeated unloading and loading of the excavation dynamic and static loads, repeated train dynamic and static loads of multi-factors, the underpass tunnel, cross tunnel engineering influence area rock layer, the existing tunnel structure of the three constitutes a multifaceted structure, multi-factor interaction system. Existing tunnels into the prediction theory model of the new tunnel excavation process of dynamic and static loads, dynamic and static loads of existing tunnels are mostly analyzed individually, the results of synergistic analysis needs to be improved. Based on the theory of the current layer method, the paper comprehensively considers the stiffness of the existing tunnel, the stiffness of the new tunnel, the excavation method load and the existing tunnel load, coupled with Peck's empirical formula, the theoretical model of deformation prediction for excavation of a two-lane highway tunnel under the tunnel through the existing railroad is proposed, and verified and optimized by numerical calculations and monitoring data, which proves the applicability and reliability of the theoretical model in the similar strata and the project promotion.

The research on the excavation mechanical properties of underpass tunnels has already had certain results, but fewer of them consider the effects of dynamic and static loads on the excavation mechanical properties of underground tunnels at the same time, especially the lack of research cases of double-line highway tunnels with angled underpasses of existing railway tunnels. In this paper, based on the tunnel project of the new double-line Shiqian Highway Tunnel passing under the Hurong Railway at an oblique angle, the mechanical parameters of the rock body in the cross-tunneling area under the influence of static and dynamic load coupling are obtained by using the disturbance quantification coefficients and the Hoek-Brown criterion based on the method of over-advanced geological prediction and the investigation of the surrounding rock on the palisade face, and the engineering-scale finite element model is constructed and the mechanical characteristics of the excavation in the tunnel of the double-lane highway tunnel passing under the existing railroad under the influence of the static and dynamic loads are analyzed. The results show that: the new tunnel rock movement law for the top of the arch sinking, bottom plate bulging, side wall to move outward, the height and width of the arch and bottom plate arch with the tunnel excavation and increase, the side wall rock displacement effect is smaller; left and right lines of the tunnel disturbed area of the rule of change is similar; the existing tunnel bottom plate displacement is more than the top plate and the left and right side walls by the excavation of the time step influence is larger. Typical profile displacement is mainly determined by the distance from the excavation surface; the new tunnel in the four types of calculation conditions of the rock disturbance angle is the same; the existing tunnel roof and side wall Von Mises stress extreme occurs in the tunnel structure, the bottom plate there are pressure relief and pressure-bearing areas; based on the displacement control criteria, the recommended upper and lower step blasting method.

To estimate the degree of quantum entanglement, it is important to understand the statistical behavior of functions of spectrum of density matrices such as von Neumann entropy, quantum purity, and entanglement capacity. These entangle- ment metrics over different generic state ensembles have been studied intensively in the literature. As an alternative metric, in this work we study sum of square root spectrum of density matrices, which is relevant to negativity and fidelity in quantum information processing. In particular, we derive the exact mean and vari- ance of sum of square root spectrum over the Bures-Hall generic state ensemble extending known results obtained recently over the Hilbert-Schmidt ensemble.

The intense motion of a ship can greatly impacts the comfort of crew members and the safety of the vessel. Therefore, accurately estimating and predicting ship attitudes has become an important issue. This paper introduces the latest development in functional deep learning model called DeepOnet. It takes wave height as input and ship motion as output, using a cause-to-result prediction approach. The modeling data used in this study is sourced from publicly available experimental data from the Iowa Institute of Hydraulic Research. Firstly, parameters system tuning was conducted for the neural network's hyperparameters to determine the appropriate combination of parameters. Secondly, the DeepOnet model for wave height and multi-degree-of-freedom motion was established, and the influence of increasing time steps on prediction accuracy was examined. Finally, a comparison was made between the DeepOnet model and the classical time series model LSTM. It was found that the DeepOnet model had a 10-fold improvement in accuracy for roll and heave attitudes. Moreover, as the forecast duration increased, the advantage of DeepOnet showed a trend of strengthening. As a functional prediction model, DeepOnet provides a new promising tool for very short-term prediction of ship motion.

Wound healing is a complex, dynamic process involving the coordinated interaction of diverse cell types, growth factors, cytokines, and extracellular matrix components. Despite emerging evidence highlighting their importance, dermal sheath cells remain a largely overlooked aspect of wound healing research. This review explores the multifunctional roles of dermal sheath cells in various phases of wound healing, including modulating inflammation, aiding in proliferation, and contributing to extracellular matrix remodeling. Special attention is devoted to the paracrine effects of dermal sheath cells and their role in fibrosis, highlighting their potential in improving healing outcomes, especially in differentiating between hairy and non-hairy skin sites. By drawing connections between dermal sheath cells activity and wound healing outcomes, this work proposes new insights into the mechanisms of tissue regeneration and repair, marking a step forward in our understanding of wound healing processes.

Despite UAV multi-target detection exhibits considerable developmental potential worldwide, it suffers distinct challenges compared with traditional tasks in this field. These challenges include insufficient feature extraction capabilities for small targets, limited capabilities for multi-dimensional feature fusion, as well as constraints on hardware computation parameters. Especially in mission scenarios such as disaster detection, these challenges will be further amplified. Consequently, this paper introduces SSE-YOLO, an innovative YOLO framework algorithm specially designed to address these challenges. To enhance the model's feature extraction capability, we employ the SPDConv module to replace the original Conv in the backbone section, utilizing depth-separable convolution instead of traditional convolution pooling. Concurrently, we eliminate the SPPF module at the bottom and address a new Separate Kernel Attention Pyramid Pooling (SKAPP) module, substantially enhancing the feature fusion capability at the model's core. Moreover, to address the challenge of multi-dimensional feature fusion, we replace the Concat module of the neck and head with E-BiFPN, transmitting feature information from the backbone to the lower network through four CBS blocks, which effectively resolves the issue of lost contextual information in the model. Meanwhile, SSE-YOLO undergoes ablation experiments on the VisDrone2019 dataset to evaluate its effectiveness against alternative methods, and experimental results illustrate the model's exceptional precision in detecting UAV targets. In comparison to models with comparable experimental accuracy, SSE-YOLO requires remarkably fewer parameters. On the VisDrone2019-DET-test-dev dataset, SSE-YOLO enhances mAP by 17.3%, with a 42.5% reduction in the parameter amounts. Therefore, the proposed method effectively tackles the challenge of reconciling low parameters and high accuracy, presenting a novel pathway for deep learning-based UAV multi-target detection.

Incremental stability analysis for time-delay systems has attracted more and more attentions for its contemporary applications in transportation processes, population dynamics, economics, satellite positions, etc. This paper researches criteria on v(t)-incremental stability, which is defined to demonstrate the convergence rate for incremental stability, for time-delay systems. Firstly, the sufficient conditions for v(t)-incremental stability for time-delay systems with continuous right-hands are studied, and several corollaries for specific cases are provided. As for time-delay systems with discontinuous right-hands, after expounding the relevant conditions for the existence and uniqueness of the Filippov solution, by using approximation methods, sufficient conditions for v(t)-incremental stability are obtained. The conclusions are applied to linear switched time-delay systems and Hopfield neural network system with composite right-hand afterwards.

Background Dietary guidelines typically recommend limiting the intake of fresh red meat, yet evidence linking red meat consumption with adverse health outcomes is inconsistent. Objective To assess the level of evidence from existing systematic reviews and meta-analyses and analyze the association between high consumption of red meat and cancer risk and adverse health outcomes. Methods Eight databases were searched to collect systematic reviews and meta-analyses from database inception to December 2022. Two independent reviewers screened and extracted data and used the AMSTAR 2 tool to evaluate methodological quality of the included studies. Meta-analysis was conducted using STATA 17.0. Results A total of 18 studies were included, of which 5 were rated as high quality, 4 as medium quality, 6 as low quality, and 3 as extremely low quality. Of the 9 SRs/MAs included, primary studies with overlap were identified, and 14 studies were eventually included. The meta-analysis results showed that compared with the lowest intake of red meat, the highest intake of red meat was associated with an increased risk of colorectal cancer (OR 1.21, 95% CI 1.07-1.37), gastric cancer (OR 1.37, 95% CI 1.18-1.59), non-Hodgkin's lymphoma (OR 1.10.95% CI 1.02-1.19), stroke (RR 1.11, 95% CI 1.03-1.20), type 2 diabetes (RR 1.19 95% CI 1.04-1.37), and ischemic heart disease (RR 1.09, 95% CI 1.06-1.12), as well as a negative effect on total cholesterol (WMD 0.264, 95% CI 0.144-0.383), triglycerides (WMD -0.181, 95% CI -0.349 to -0.013), low-density lipoprotein (WMD 0.198, 95% CI 0.065-0.330), and high-density lipoprotein (WMD -0.065, 95% CI -0.109 to -0.020). However, the associations with breast cancer (RR 1.05 95% CI 1.00-1.11), glycemic control (WMD 0.040, 95% CI 0.049-0.129), and changes in body weight status [overweight (β 0.89, 95% CI 0.48-1.64); obesity (β 1.06, 95% CI 0.30-3.71)] were not significant. Conclusions This comprehensive umbrella review suggests that high consumption of red meat may increase the risk of colorectal cancer, gastric cancer, non-Hodgkin lymphoma, stroke, type 2 diabetes, and cardiovascular disease, and that reducing red meat intake is a key modifiable dietary factor for reducing risk. However, there was no significant correlation with breast cancer, kidney stones, age-related eye disease or changes in body weight.

Three new compounds (1, 11 and 12), together with 32 known ones, were isolated from the root bark of Morus alba L. using various chromatographic methods. The structures of the undescribed compounds were elucidated based on 1D, 2D NMR and HRESIMS data analysis, while the known ones were identified by comparison of their spectroscopic data with those reported in the literature. All the isolates were evaluated for their cytotoxic activities against human gastric cancer HGC27 cells by CCK-8 assay. Among them, compounds 5, 8, 10 and 30 exhibited cytotoxic activities on HGC27 cells with IC50 values of 10.24 ± 0.89 μM, 28.94 ± 0.72 μM, 6.08 ± 0.34 μM and 33.76 ± 2.64 μM, respectively. Furthermore, compound 10 was confirmed to reduce proliferation ability, increase apoptosis rate and inhibit cell migration pathway by annexin V/PI double staining experiment, transwell experiment and western blot analysis.

The rapid development of multicopters has led to many security problems. In order to prevent multicopters from invading restricted areas or famous buildings, an Anti-UAV Defense System (AUDS) has been developed and become a research topic of interest. Topics under research in relation to this include electromagnetic interference guns for unmanned aerial vehicles (UAVs), high-energy laser guns, US military net warheads, and AUDSs with net guns. However, these AUDSs use either manual aiming or expensive radar to track UAVs. This paper proposes a dual-axis rotary platform with UAV automatic tracking. The tracking platform uses visual image processing technology to track and lock the dynamic displacement of a UAV. When a target UAV is locked, the system uses a nine-axis attitude meter and laser rangefinders to measure its flight altitude and calculates its longitude and latitude coordinates through sphere coordinates to provide UAV monitoring for further defense or attack missions. Tracking tests of UAV flights in the air were carried out using a DJI MAVIC UAV at a height of 30 meters to 100 meters. It was set up for UAV image capture and visual recognition for tracking under various weather conditions by a thermal imager and a full-color camera respectively. When there was no cloud during the daytime, the images captured by the thermal imager and full-color camera provide a high-quality image recognition result. However, under dark weather, black clouds will emit radiant energy and seriously affect the capture of images by a thermal imager. When there is no cloud at night, the thermal imager performs well in UAV image capture. When the UAV is tracked and locked, the system can effectively obtain the flight altitude and longitude and latitude coordinate values.

To study the feasibility and effect of compounding lignin and its derivatives to improve expansive soil, the physical properties, mechanical properties, and microstructure of the improved soil mixed with calcium lignosulfonate alone, calcium lignosulfonate and lignin fibers were investigated through indoor experiments and electron microscope scanning. Select samples with better performance for water stability tests, and discuss the improvement mechanism of expansive soil by combining macroscopic mechanical changes with microstructural characteristics. The research results show that the addition of calcium lignosulfonate can reduce the water content of the soil and enhance its strength of the soil. The overall performance is the best when the calcium lignosulfonate content is 3%. 3% calcium lignosulfonate compounded with 1.5% lignin fiber has the best all-around performance; the composite improved soil has a better pore-filling effect, the whole is more compact, and the connection between particles significantly enhances the strength, which greatly inhibits the development of cracks good water stability. Lignin and its derivatives compound improved expansive soil have better effect than traditional improvement methods, and have no pollution to the environment, which can provide a particular reference for engineering practice