Photocatalytic degradation plays a crucial role in wastewater treatment, and the key to achieving high efficiency is to develop photocatalytic systems that possess excellent light absorption, carrier separation efficiency, and surface-active sites. Among various photocatalytic systems, S-type heterojunctions have shown remarkable potential for efficient degradation. This work delves into construction of S-type heterojunctions of ternary indium metal sulfide and bismuth ferrite nanofibers with introduction of sulfur vacancy defects and morphology modifications to enhance the photocatalytic degradation performance. Through the impregnation method, BiFeO₃/Zn₂S₄ heterojunction materials were synthesized and optimized30% BiFeO₃/Zn₂S₄ heterojunction exhibited superior photocatalytic performance with higher sulfur vacancy concentration than Zn₂S₄. The in-situ XPS results demonstrate that the electrons between Zn₂S₄ and BFO are transferred via S-Scheme, and after modification, Zn₂S₄ has a more favorable surface morphology for electron transport, and its flower-like structure interacts with the nanofibers of BFO, which has a further enhancement of the reaction efficiency for degrading pollutants. This exceptional material demonstrated a remarkable 99% degradation of Evans blue within 45 min and a significant 68% degradation of ciprofloxacin within 90 min. This work provides a feasible idea for developing photocatalysts to deal with the problem of polluted water resources under practical conditions.

The interfacial mechanics and electrical properties of the SiC reinforced copper matrix composites were studied via the first principles method. The work of adhesion (Wad) and the interfacial energies were calculated to evaluate the stabilities of the SiC/Cu interfacial models. The carbon terminated (CT)-SiC/Cu interfaces were predicted more stable than those of the silicon terminated (ST)-SiC/Cu from the results of the Wad and interfacial energies. The interfacial electron properties of SiC/Cu were studied via the charge density distribution, charge density difference, electron localized functions and partial density of the state. The covalent C-Cu bonds were formed based on the results of the electron properties, which further explained the fact that the interfaces of the CT-SiC/Cu are stable than those of the ST-SiC/Cu. The interfacial mechanics of the SiC/Cu were investigated via the interfacial fracture toughness and ultimate tensile stress, and the results indicate that both CT- and ST-SiC/Cu interfaces are hard to fracture. The ultimate tensile stress of the CT-SiC/Cu is nearly 23GPa, which is smaller than those of the ST-SiC/Cu of 25 GPa. The strains corresponding to their ultimate tensile stresses of the CT- and ST-SiC/Cu are about 0.28 and 0.26, respectively. The higher strains of CT-SiC/Cu indicate their stronger plastic properties on the interfaces of the composites.

Monin-Obukhov similarity theory (MOST) overestimates wind shear in some atmospheric stable conditions, i.e. Richardson number $R_f<0.25$. The overestimated wind shear that leads to an under-predicted friction wind speed and a lower ambient turbulence intensity for a given hub-height reference wind speed and a given roughness length, could influence wake modeling of a wind turbine. This work investigates the side effects of the breakdown of MOST on wake modeling under stable conditions and makes some modifications to the flow similarity functions to eliminate these side effects. Based on a field measurement in a wind farm, we firstly show that MOST predicts a larger wind shear for the atmospheric stability parameter $\zeta>0.1$ and proposes new flow similarity functions without constraining $R_f$ to limit the overestimated wind shear by MOST. Next, different turbulence models based on MOST and a modified one based on the new similarity functions are investigated through numerical simulations. These turbulence models are combined with the actuator disk model (AD) and Reynolds-averaged Navier–Stokes equations (RANS) to model wind turbine wakes under stable conditions. As compared to measurements, numerical results show that turbulence models based on MOST result in larger wake deficits and slower wake recovery rate with a square root of the mean-squared-error (RSME) of wake deficit in the range of 0.07-0.18. This overestimated wake effect is improved by applying the new similarity functions and the RSME of wake deficit is averagely reduced by 0.05. Finally, we check the role of the under-predicted turbulence intensity playing in the larger wake deficit predicted by models based MOST. Additional numerical simulations using the modified turbulence model are carried out, in which the roughness length is reduced to impose a hub-height ambient turbulence intensity equivalent to the MOST case. Simulation results show that reducing turbulence intensity enhances wake effects, however, it cannot reproduce the large wake deficit predicted by models based on MOST, which suggests that the overestimated wake effect by MOST could be also related to the overestimated wind shear.

The adaptive identification method developed to evaluate the parameters of the Bouc-Wen hysteresis (BWH). The adaptive approach based on the use of adaptive observers. We synthesize adaptive identification algorithms using the second Lyapunov method. The boundedness of adaptive system processes shown in coordinate and parametric spaces. We prove exponential dissipativity of processes in an adaptive system. Estimating method proposed for signaling uncertainty in the system.

Atmospheric stability affects wind turbine wakes significantly. High-fidelity approaches such as large eddy simulations (LES) with the actuator line (AL) model which predicts detailed wake structures, fail to be applied in wind farm engineering applications due to its expensive cost. In order to make wind farm simulations computationally affordable, this paper proposes a new actuator disk model (AD) based on the blade element method (BEM) and combined with Reynolds-averaged Navier–Stokes equations (RANS) to model turbine wakes under different atmospheric stability conditions. In the proposed model, the upstream reference velocity is firstly estimated from the disk averaged velocity based on the one-dimensional momentum theory, and then is used to evaluate the rotor speed to calculate blade element forces. Flow similarity functions based on field measurement are applied to limit wind shear under strongly stable conditions, and turbulence source terms are added to take the buoyant-driven effects into consideration. Results from the new AD model are compared with field measurements and results from the AD model based on the thrust coefficient, the BEM-AD model with classical similarity functions and a high-fidelity LES approach. The results show that the proposed method is better in simulating wakes under various atmospheric stability conditions than the other AD models and has a similar performance to the high-fidelity LES approach however in much lower computational cost.

This study was conducted to determine the dynamic effects of dietary crude protein (CP) intake on nitrogen (N) balance, ileal amino acid digestibility, and gene expression levels of digestive enzymes at three stages in pigs. In Experiment 1, 18 growing pigs (average body weight (BW) = 9.5 kg) were randomly assigned to one of three treatments (n = 6/treatment group), including normal (20% CP), low (17% CP), and very low (14% CP) protein intake. In Experiment 2, 18 growing pigs (average BW = 30 kg) were allotted randomly to one of three treatments (n = 6/treatment group), including normal (18% CP), low (15% CP), and very low (12% CP) protein intake. In Experiment 3, 18 growing pigs (average BW = 45 kg) were assigned randomly to one of three treatments (n = 6/treatment group), including normal (16% CP), low (13% CP), and very low (10% CP) protein intake. Growing pigs fed the 14% CP and 17% CP diets had lower final BW (P < 0.05) and average daily gain (ADG) (P < 0.05) compared to pigs fed the 20% CP diet. Reducing the dietary CP level from 20 to 14% decreased urinary N excretion by 52.8% (P < 0.001) in Experiment 1. Reducing the dietary CP level from 18 to 12% decreased urinary N excretion by 55.3% (P < 0.001) and reduced fecal N excretion by 34% (P < 0.05) in Experiment 2. Reducing the dietary CP level from 16 to 10% decreased urinary N excretion by 56.4% (P < 0.001) and fecal N excretion by 47.1% (P < 0.001) in Experiment 3. Pigs fed the very low (14%, 12%, and 10% CP) diets showed higher digestibility for CP (P < 0.05), His (P < 0.05), Ile (P < 0.05), Phe (P < 0.05), Thr (P < 0.05), Trp (P < 0.05), Glu (P < 0.05), and Ser (P < 0.05) compared to pigs fed the normal (20%, 18%, and 16% CP) diets among the three experiments. Pigs fed the very low (14%, 12%, and 10% CP) diets showed higher mRNA levels for chymotrypsin C (P < 0.01 in Experiment 1 and 2; P < 0.05 in Experiment 3) compared to pigs fed the normal (20%, 18%, and 16% CP) diets among the three experiments. These results indicated that a reduction in dietary CP by 6% limited the growth performance of growing pigs, and a reduction of dietary CP by 3% supplemented with essential amino acids could reduce the excretion of N into the environment without affecting weight gain.

A typical solid-state quantum sensor can be developed based on negatively charged nitrogen-vacancy (NV-) centers in diamond. The electron spin state of NV- can be controlled and read at room temperature. Through optical detection magnetic resonance (ODMR) technology, temperature measurement inside living cells can be achieved at the nanoscale. The key to ODMR technology is to apply microwave resonance to manipulate the electron spin state of NV-. Therefore, the microwave field characteristics formed near the NV- have a crucial impact on the sensitivity of ODMR measurement. This article mainly focuses on the temperature situation in cellular applications, and simulates the influence of structural parameters of double open loop resonant (DOLR) microwave antennas and broadband large-area (BLA) microwave antennas on the microwave field’s resonance frequency, quality factor Q, magnetic field strength, uniformity, etc. The parameters are optimized to have sufficient bandwidth, high signal-to-noise ratio, low power loss, and high magnetic field strength in the temperature range of 36 ℃ to 42.5 ℃. Finally, the ODMR spectra are used for effect comparison, and the signal-to-noise ratio and Q values of the ODMR spectra are compared when using different antennas. We have provided an optimization method for the design of microwave antennas and it is concluded that the DOLR microwave antenna is more suitable for living cell temperature measurement in our study.

The bilateral trade relationship between PRC and ASEAN is close. As early as 2012, China has been the largest trading partner of ASEAN, and ASEAN has also taken the place of the United States as PRC’s second largest trading partner in 2019.This paper uses the theory of ecological population evolution, selects the total import and export volume of PRC and the ten ASEAN countries from 2000 to 2019 as the data sample, studies the bilateral trade relations between PRC and the ten ASEAN countries, analyzes the competition and symbiotic relationship of bilateral trade between PRC and the ten ASEAN countries and the possibility of trade friction according to the results, and proposes corresponding improvement strategies. According to the results of the population evolution competition model, China has a competitive relationship with Indonesia, Malaysia, the Philippines, Singapore and Thailand, which is most likely to cause trade friction. China has a biased relationship with Brunei, Cambodia, Laos, Myanmar and Vietnam, which is more likely to cause trade friction. On this basis, in order to further strengthen the trade relations between PRC and the ten ASEAN countries, this paper puts forward policy suggestions on improving infrastructure, strengthening independent innovation, seeking cooperation fields and actively investing abroad.

This study provides an in-depth examination of the binary system of n-Nonadecane and 1-Octadecanol, representative of plant cuticular waxes. It emphasizes the crystallization and phase transitions in this hydrocarbon mixture. Using Differential Scanning Calorimetry (DSC) and Fourier Transform Infrared (FTIR) spectroscopy, the research uncovers detailed thermal properties and phase behaviors. The findings reveal the distinct phase transitions and enthalpy changes of each component in the binary system. This research is significant for its implications in under-standing the structural properties of plant waxes. Such insights are crucial for enhancing the effi-ciency of fertilizer and pesticide absorption in plant leaves, with broad applications in bionics and materials science. This study not only furthers the understanding of identifying specific phase transitions for each compound, facing challenges in detecting subtle changes using DSC. The re-search enhances understanding of plant cuticle waxes through FTIR analysis, revealing intricate molecular interactions and structural complexities. but also opens avenues for improved agri-cultural practices and material engineering, potentially influencing future innovations in these fields.

Synthetic Aperture Radar (SAR) is an active sensor that uses microwave for sense, it is unrestricted by weather and illumination conditions, and it can observe targets all day and weather. Aircraft targets are important monitoring objects in military and civilian fields, and how to efficiently detect and recognize aircraft targets is an important topic in the field of SAR image interpretation. Based on the features of SAR images, such as complex background, high resolution, and multi-scale, we proposed an improved method based on YOLOv5s. Firstly, this paper proposed the structure of the multi-scale receptive field and channel attention fusion, which is applied to the shallow layer of the backbone of YOLOv5s, it can adjust the weights of the multi-scale receptive field during the training process to enhance the extraction ability of feature information. Secondly, we proposed four de-coupled detection heads to replace the original part in YOLOv5s, which can improve the efficiency and accuracy of SAR image interpretation for small targets. Thirdly, in the case of the limited amount of SAR images, this paper proposed multi methods of data augmentation, which can enhance the diversity and generalization of the network. Fourthly, this paper proposed the K-means++ to re-place the original K-means to improve the network convergence speed and detection accuracy. Finally, Experiments demonstrate that the improved YOLOv5s can enhance the accuracy of SAR image interpretation by 9.3%, and the accuracy of small targets is improved more obviously, reaching 13.1%.

Magnesium ions play an important immune-regulatory role during bone repair. For this study, we prepared micro-nano bioactive glass containing magnesium, which can release magnesium, silicon, and calcium ions and has a positive impact on osteogenic differentiation and vascular regeneration. In this study, MgMNBG was compounded and combined with PLGA and PCL for 3D printing. Afterwards, the physicochemical properties and bone repair performance of the scaffolds were evaluated through in vitro and in vivo experiments. We also investigated the effects of MgMNBG on osteogenic differentiation, immune regulation, and vascular regeneration. The results showed that MgMNBG can inhibit inflammation and promote osteogenesis and angiogenesis by regulating macrophages. PLGA/PCL/MgMNBG scaffolds have good osteogenic and angiogenic effects, and the composite scaffolds have excellent bone repair performance and potential application value.

Micro-gyroscopes based on the Coriolis principle are widely employed in inertial navigation, motion control, and vibration analysis applications. This paper presents our main contributions which include a novel dual-frame optomechanical gyroscope, a unique photonic crystal cavity design, and advanced numerical simulation and optimization methods. The proposed design utilizes an optical cavity formed between dual oscillating frames, whereby input rotation induces a measurable phase shift via optomechanical coupling. Actuation of the frames is achieved electrostatically via an interdigitated comb-drive design. Through theoretical modeling based on cavity optomechanics and finite element simulation, the operating principle and performance parameters are evaluated in detail. Results indicate an expected angular rate sensitivity of 22.8 mV/°/s and angle random walk of 7.1×10-5 °/h1/2, representing superior precision than to existing micro-electromechanical systems gyroscopes of comparable scale. Detailed analysis of the optomechanical transduction mechanism suggests this dual-frame approach could enable angular vibration detection with resolution exceeding state-of-the-art solutions.

Curcumin is the main secondary metabolites of Curcuma longa and other Curcuma spp, and has been reported to have some potential in preventing and treating some physiological disorders. This study investigated the effect curcumin in inhibiting high-fat diet and streptozotocin (STZ)-induced hyperglycemia and hyperlipidemia in rats. Twenty-six male Sprague-Dawley (SD) rats (170-190 g) were randomly divided into a standard food pellet diet group (Control group), a high-fat diet and streptozotocin group (HF+STZ group), and a high-fat diet combined with curcumin and STZ group (HF+ Cur +STZ group). Compared with the HF+STZ group, the HF+Cur+STZ group exhibited significantly reduced fasting blood glucose (FBG), total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), alanine aminotransferase (AST) and aspartate transaminase (ALT) levels, and liver coefficients; in the livers of these rats, the expression of malondialdehyde (MDA) and Bax was downregulated, whereas that of superoxide dismutase (SOD) and Bcl-2 was upregulated. Moreover, the liver histology of these rats was improved and resembled that of the control rats. These results suggest that curcumin prevents high-fat diet and STZ-induced hyperglycemia and hyperlipidemia, mainly via anti-oxidant and anti-apoptotic mechanisms in the liver.

Salmonella infections can lead to intestinal inflammation and metabolic disorders in birds. However, whether ARA metabolism is involved in Salmonella-induced intestinal inflammation remains unclear. This experiment investigated the changes in cecal flora and arachidonic acid (ARA) metabolism in Hainan Wenchang chickens infected with S. Typhimurium using 16s rDNA sequencing and targeted metabolomics. The results showed that the levels of ARA metabolites were increased in the cecum tissue of Wenchang chickens after infection with S. Typhimurium, including prostaglandin E2, prostaglandin F2α, lipoxin A4, ±8(9)-EET, ±11(12)-EET, and ±8,9-DiHETrE. The content of key enzymes for ARA production and metabolism (PLA2 and COX-2) in chicken cecum tissues was increased after S. Typhimurium infection. The relative mRNA levels of inflammatory factors were also increased after infection, including IFN-γ, TGF-β1, IL-4, and IL-6. In HD11 cells, the use of a cyclooxygenase (COX) inhibitor reduced the increased levels of COX-2 and PGF2α induced by S. Typhimurium infection and effectively reduced the inflammatory response. In addition, the number of beneficial genera (e.g., Bifidobacterium, Lactobacillus, and Odorobacterium) in the cecum of Wenchang chickens was significantly reduced after infection with S. Typhimurium. In this study, we revealed the structure of the cecal flora of Wenchang chickens infected with S. Typhimurium and demonstrated that S. Typhimurium can mediate the onset and development of intestinal inflammation through the activation of the metabolic pathway of ARA cyclooxygenase in Wenchang chickens. The results can provide data support and theoretical support for the prevention and control of avian salmonellosis.

Potato tubers are susceptible to wounding during post-harvest processes, leading to quality decline, perishability and large economic losses. In this study, the potato cultivar, ‘Longshu No.7’, was foliar-sprayed with 3% chitosan (w/v) three times during the pre-harvest period after flowering to evaluate the effect of foliar spraying with chitosan on suberization processing at wounds of harvested potato tubers. Our results demonstrate that foliar-sprayed with chitosan significantly reduced wound-induced fresh weight loss and dry rot disease index by 37.34% and 41.60% on the 28 day after wounding, respectively. Foliar-sprayed with chitosan accelerated the deposition of suberin polyphenolics and lignin at the wound sites of potato tubers with the formation of thicker cell layers. This occurred with increased localized activities of key enzymes in the suberin polyphenolics and lignin pathways, including phenylalanine ammonia lyase, 4-coumaryl-coenzyme A ligase, cinnamyl alcohol dehydrogenase and peroxidase (33.90–64.32%), as well as the contents of cinnamic acid, sinapic acid, flavonoids, lignins and total phenolics (19.70–23.46%) at wound sites of potato tubers on the 7 day after wounding. Our results indicated that foliar application of chitosan accelerated wound-induced suberization of potato tubers and could mitigate post-harvest product damages.

The transforming growth factor-β (TGF-β), in which overexpression have been associated with various diseases, has become an attractive molecular target for the treatment of cancers. Three series of 3-substituted-4-(quinoxalin-6-yl) pyrazoles 14a–h, 15a–h, 16a–h, 22a, 22b, 22d, 23a, 23b, 23d, 24b, and 24d were synthesized and evaluated for their activin receptor-like kinase 5 (ALK5) and p38α mitogen activated protein (MAP) kinase inhibitory activity in an enzymatic assays. Among these compounds, the most active compound 16f inhibited ALK5 phosphorylation with an IC₅₀ value of 0.28 µM, with 98% inhibition at 10 µM. Compound 16f also had good selectivity index of >35 against p38α MAP kinase, with 9.0-fold more selective than clinical candidate, compound 3 (LY-2157299). Molecular docking study was performed to identify the mechanism of action of the synthesized compounds and their good binding interactions were observed. ADMET prediction of good active compounds showed that these ones possess good pharmacokinetics and drug-likeness behavior.

Macrobrachium rosenbergii is a valuable freshwater prawn in Asian aquaculture. In recent years, a new symptom that was generally called as ‘white head’ caused high mortality in M. rosenbergii farms in China. Samples of M. rosenbergii, M. nipponense, Procambarus clarkii, M. superbum, Penaeus vannamei, and Cladocera from a farm suffering from ‘white head’ in Jiangsu Province were collected and analyzed in this study. Pathogen detection showed that all samples were positive for Shrimp hemocyte iridescent virus (SHIV). Histopathological examination revealed dark eosinophilic inclusions and pyknosis in hematopoietic tissue, hepatopancreas and gills of M. rosenbergii and M. nipponense. Blue signals of in situ DIG-labeled LAMP (ISDL) appeared in hematopoietic tissue, hemocytes, hepatopancreatic sinus, and antennal gland. TEM of ultrathin sections showed a large number of SHIV particles with a mean diameter about 157.9 nm. The virogenic stromata and budding virions were observed in hematopoietic cells. Quantitative detection by TaqMan probe based real-time PCR of different tissues in natural infected M. rosenbergii showed that hematopoietic tissue contained the highest SHIV load with a relative abundance of (25.4±16.9)%. Hepatopancreas and muscle contained the lowest SHIV load with a relative abundance at (2.44±1.24)% and (2.44±2.16)%, respectively. Above results verified that SHIV is the pathogen causing ‘white head’ in M. rosenbergii, and M. nipponense and Pr. clarkii are also the susceptible species of SHIV.

Results showed that mulberry leaves could significantly reduce backfat thickness (P&lt;0.05) and increase intramuscular fat (IMF) content (P&lt;0.05). Lipidomics analysis showed that mulberry leaves improved lipid profile composition and increased the proportion of triglycerides (TG). Interestingly, IMF content was positively correlated with acyl C18:2 and negatively correlated with C18:1 of differential TGs. In addition, cecal microbiological analysis showed that mulberry leaves could increase the abundance of bacteria such as UCG−005, Muribaculaceae_norank, Prevotellaceae_NK3B31_group, Limosilactobacillus, and so on. At the same time improve the L-tyrosine-baton rouge ester, Oleic acid methyl ester, 21-deoxycortisol, N-acetyldihydrosphingosine, Mulberrin relative abundance. In this study, we found that mulberry leaves could extremely significantly increasing the mRNA relative expression of lipoprotein lipase (LPL), fatty acid-binding protein 4 (FABP4) and peroxisome proliferators-activated receptor γ (PPARγ) in muscle (P＜0.01), significantly increasing mRNA relative expression of diacylglycerol acyltransferase 1 (DGAT1) (P＜0.05) and significantly decreasing the mRNA relative expression of acetyl CoA carboxylase (ACC) (P＜0.05), and aignificantly upregulated hormone-sensitive triglyceride lipase (HSL), peroxisome proliferators-activated receptor α (PPARα) mRNA relative expression (P＜0.05) in backfat. In addition mulberry leaves could increased serum leptin and adiponectin (P＜0.01). Ultimately lead to up-regulation of IMF and down-regulation of backfat.

Analyzing horse behavior is crucial for assessing training quality, particularly in accurately identifying actions like standing, walking, and running. Research has been conducted both domestically and internationally in this regard; however, challenges persist, including reliance on single sensors, poor real-time performance, and low identification accuracy. In view of these challenges, this study investigated real-time identification of horse behavior based on wearable devices. The system, centered around a microcontroller and utilizing a 4G network as a carrier, employs multi-axis IMU sensors as input sources to perceive horse posture. The study proposed a behavior classification method based on analysis of acceleration thresholds. The method consists primarily of two sequential stages: first, the resultant acceleration interval counting method, which employs a nonlinear segmentation approach for initial behavior classification; and second, the statistical analysis of variance parameters between segments, which when coupled with multi-level threshold processing, achieves a refined classification. Experimental results indicated that the interval counting method alone achieved an accuracy of 87.55%, while for the variance analysis method alone the accuracy was 90.87%. The proposed method, comprising the two stages, reached a classification accuracy of 91.57%, underpinning its usefulness in supporting future equine research.

The increasing prevalence of obesity and sedentary lifestyles has led to an increased incidence of metabolic syndrome (MetS) worldwide. In Taiwan, middle-aged women are at a greater risk of MetS, type 2 diabetes, and cardiovascular disease than men are because they have more subcutaneous fat and larger waist circumferences compared to men with equal visceral fat levels. This study investigated the effects of calorie restriction supplemented with fish oil (CRF) in middle-aged women with MetS. For 12 weeks, 75 eligible participants were randomly assigned either calorie restriction (CR) or CRF. Both dietary intervention groups were further divided into two age groups: ≤45 and >45 years. The changes in MetS severity, inflammatory status, iron status, and red blood cell fatty acid profile were evaluated. Seventy-one participants completed the trial. Both dietary interventions significantly ameliorated MetS and improved the participants’ inflammatory status. CR significantly increased total iron binding capacity, whereas CRF increased hepcidin levels. Furthermore, CRF significantly increased the n-6/n-3 and arachidonic acid/docosahexaenoic acid ratios. In conclusion, CR and CRF improved the anthropometric and MetS characteristics of early-middle aged women, including body weight, blood glucose levels, triglyceride levels, as well as the scores for the homeostasis model assessment of insulin resistance and quantitative insulin sensitivity cheque index. Dietary intervention was more effective in >45-year-old women than ≤45-year-old women.

Ischemic stroke is one of the most disabling diseases and a leading cause of death globally. Despite advances in medical care, the global burden of stroke continues to grow, as no effective treatments to limit or reverse ischemic injury to the brain are available. However, recent preclinical findings have revealed the potential role of transient receptor potential cation 6 (TRPC6) channels as endogenous protectors of neuronal tissue. Activating TRPC6 in various cerebral ischemia models has been found to prevent neuronal death, whereas blocking TRPC6 enhances sensitivity to ischemia. Evidence has shown that Ca2+ influx through TRPC6 activates cAMP response element-binding protein (CREB), an important transcription factor linked to neuronal survival. Additionally, TRPC6 activation may counter excitotoxic damage resulting from glutamate release by attenuating the activity of NMDA receptors of neurons by posttranslational means. Unresolved though, are the roles of TRPC6 channels in non-neuronal cells such as astrocytes and endothelial cells. Moreover, TRPC6 channels may have detrimental effects on the blood-brain barrier, although their exact role in neurovascular coupling requires further investigation. This review discusses evidence-based cell-specific aspects of TRPC6 in the brain to assess the potential targets for ischemic stroke management.

The article delves into the intricate phase transitions of 1-Octadecanol and n-Nonadecane within a binary system, unveiling dynamic structural changes under varying conditions. Through Fouri-er-transform infrared (FTIR) analysis, specific molecular vibrations were identified, shedding light on the molecular composition and interactions. The study highlights the challenges in detecting subtle phase transitions and emphasizes the individuality of molecular behaviours in closely related compounds. The findings underscore the complexity of phase transitions in binary systems and advocate for a nuanced approach to studying molecular structures and behaviours. Addi-tionally, the research contributes valuable insights into the molecular dynamics of Organic Polymer Functional Adsorption Materials, offering implications for synthetic waxy layers in plant epidermis.

The integration of metal nanoparticles and solid carriers can achieve ideal stability, high load and good conductivity. In this work, copper nanoparticles (Cu NPs) were sequentially deposited on a cobalt metal-organic framework (Co-MOF) by bonding with exposed imino groups, followed by a reduction reaction to prepare a new Cu@Co-MOF composite. Cu@Co-MOF acts as a non-enzymatic electrochemical sensor to detect glucose (Glu) in an alkaline medium. The composite working electrode of Cu@Co-MOF/GCE (GCE = glassy carbon electrode) improves the electrocatalytic activity for Glu oxidation. Cu@Co-MOF/GCE shows excellent electrocatalytic performances in Glu concentration ranging 0.005~1.8 mmol∙L⁻¹ (mM): the sensitivities are 282.89 μA∙mM⁻¹∙cm⁻² in 0.005-0.4 mM Glu and 113.15 μA∙mM⁻¹∙cm⁻² in 0.4-1.8 mM Glu respectively with low detection limit of 1.6 μM (S/N = 3) and high selectivity and stability.

Environmental decentralization (ED), or the allocation of environmental protection affairs and responsibilities among various administrative authorities, affects the effectiveness of environmental regulation in promoting green total factor productivity (GTFP). Based on panel data of 30 Chinese provinces from 2001 to 2015, this paper employs dynamic panel models to test the effects of environmental regulations (environmental protection investment, ENV; pollutant discharge fees, PDF) on GTFP, with or without being influenced by ED. Without the impact of ED, GTFP is significantly inhibited by ENV while significantly promoted by PDF. Considering the impact of ED, with the strengthening of ED, the negative effects of ENV on GTFP is significant; contrarily, the positive effects of PDF on GTFP is significant; improving provincial ED adds negative effects of ENV, while reduces the positive effects of PDF; increasing prefectural ED reduces negative effects of ENV; expanding county-level ED adds the positive effects of PDF. Therefore, to boost GTFP growth, prefectural environmental protection authorities should have more autonomy in ENV, while the county-level should have more autonomy in PDF.

Glioblastoma (GBM) is the most common malignant brain tumor in adults. Despite advancements in treatment, the prognosis for patients with GBM remains poor due to its aggressive nature and resistance to therapy. CRISPR-based genetic screening has emerged as a powerful tool for identifying genes crucial for tumor progression and treatment resistance, offering promising targets for tumor therapy. In this review, we provide an overview of the recent advancements in CRISPR-based genetic screening approaches and their applications in GBM. We highlight how these approaches have been used to uncover genetic determinants of GBM progression and susceptibility to various therapies. Furthermore, we discuss ongoing challenges and future directions of CRISPR-based screening methods in advancing GBM research.

This paper focuses on robust multi-criteria traffic network equilibrium problems with path capacity constraints. The concepts of robust vector equilibrium and robust vector equilibrium with respect to worst case are introduced, respectively. To generate a subset of robust vector equilibrium, an equivalent min-max optimization problem is constructed. In addition, a direct search algorithm, in which the step size without derivatives and redundant parameters, for solving this min-max problem is proposed. To find a subset of robust vector equilibrium with respect to worst case, an equivalent smoothing optimization problem based on a variant version of ReLU activation function is established. Numerical experiments are also presented to expound the advantages of the algorithms.

In this paper, the distributed formation tracking control problem of quadrotor unmanned aerial vehicles (UAVs) is considered. Adaptive backstepping technology is used to design flight control schemes for quadrotor UAVs. For the position subsystem, a distributed robust formation tracking control scheme is developed to achieve formation flight of quadrotor UAVs and track the desired flight trajectory. For the attitude subsystem, an adaptive disturbance rejection control scheme is proposed to achieve attitude stabilization during UAV flight under uncertain disturbances. Compared with the existing results, the novelty of this paper is that the proposed formation control scheme does not require the use of the quadrotor model parameters. Finally, a quadrotor UAV swarm system is used to verify the effectiveness of the proposed control scheme.

Poverty alleviation is a hallmark of post-revolution Chinese policymaking. Since 1978, the Communist Party of China (CPC) has implemented successive waves of poverty alleviation policies whose effects have become the focus of an ever-increasing body of academic literature. This paper reviews this diverse but limited literature that evaluates the impact of the CPC’s poverty reduction programs through four major channels, namely fiscal investment programs, social safety nets, rural governance on the village-, county- and provincial level, and the relocation of rural populations from destitute regions. This paper aims to synthesize results and evaluate whether and how the abovementioned poverty alleviation programs have had distinct positive or negative impacts on regional development outcomes. Furthermore, I highlight contradictions in empirical findings to motivate the discussion about contextual importance when designing and implementing future poverty alleviation programs. Finally, I suggest that an exhaustive and critical appraisal of the empirical strategies used in this literature would further the development and application of more accurate and informative methodologies.

This study primarily investigates the effect of fly ash (FA) content on the mechanical properties and hydration performance of alkali-activated ground granulated blast furnace slag cements (AAGC), and compares the related properties with ordinary Portland cement (OPC). Additionally, the study examined the hydration products, thermal analysis, MIP, SEM, chemically bound water, and pH values of AAGC. The compressive strength of AAGC showed a retrogression phenomenon from 3 to 28 days, with the 14-day and 28-day compressive strengths of AAGC being higher than those of OPC. The AAGC with 20% FA content exhibits the highest 28-day compressive strength (75 MPa). The hydration heat release rate curved of OPC and AAGC can be divided into the initial induction period, induction period, acceleration period, deceleration period and steady period. As FA content increases, the 28-day pore volume of AAGC increased while pH values and chemically bound water decrease. SEM images of AAGC with low FA content showed more microcracks.

We explored the trends and the diversity of the mortality and risk factors of age-standardized cardiovascular diseases (CVD) and cerebrovascular disease (CBD) from 2000 to 2020 in five advanced Asian countries, including China, Japan, Singapore, South Korea, and Taiwan. Data were obtained from the Global Burden of Disease (GBD) report. Overall, the CVD mortality rates decreased gradually in all five Asian countries. Singapore had the highest rates before 2011, but Taiwan replaced Singapore as the nation of the highest mortality rates after 2012. Additionally, South Korea had the highest CBD mortality rates before 2016, while Taiwan experienced a peak in 2011 and remained high thereafter. The absolute difference (AD) and relative difference (RD) for CVD mortality rates showed clear declining trends in all five countries, with South Korea and China displaying the highest reductions, respectively. It is noteworthy that overweight and obesity exhibited an increasing trend in all these five Asian countries, with China demonstrating the highest AD and RD. Except for Taiwan, where a negative association of r=-0.732 was observed, CVD mortality was positively associated with CBD, hypertension, and DM mortality in all other four countries, therefore, further investigation into these relationships are needed.

It is well established that the reaction cycles involving some halogenated alkanes (so-called ozone-depleting substances, ODS) contribute to the depletion of ozone in the stratosphere, thus causing the Montreal Protocol (initially signed in 1987) and later amendments. The Protocol called for the scheduled phase-out of ODS, including chlorofluorocarbons (CFC), hydrochloro-fluorocarbons (HCFC), carbon tetrachloride (CCl4), halon, methyl chloroform (CH3CCl3), me-thyl chloride (CH3Cl), and even hydrofluorocarbons (HFCs). In view of the urgent importance of ozone layer protection to the globally ecological environment, the Taiwan government took regulatory actions on reducing ODS consumption since 1993 by the joint-venture of the central competent authorities. Under the regulatory requirements and the industry’s efforts by adopt-ing the alternatives to ODS and abatement technologies, the phase-out of some ODS (i.e., CFC, CCl4, halon, and CH3CCl3) have been achieved prior to 2010. The consumptions of HCFCs and methyl chloride have been significantly declined over the past three decades (1993-2022). However, HFC emission indicated a V-type variation during the period. Due to the local pro-duction and extensive use of HFC in Taiwan, its emissions increased from 663 kilotons of carbon dioxide equivalents (CO2eq) in 1993 to 2,330 kilotons of CO2eq in 2001, and then decreased to 373 kilotons of CO2eq in 2011. Since then, the emissions of HFC largely used as the alternatives to ODS showed an upward trend, increasing to 1,555 kilotons of CO2eq in 2022. To be in compliance with the Kigali Amendment (KA-2015) to the Montreal Protocol for mitigating global warming, the Taiwan government has taken regulatory actions in reducing the consumption of some HFC substances with high global warming potential (GWP) under the authorization of the Climate Change Response Act in 2023, aiming at the baseline consumption in 2024 by 80 % reduction by 2045.

Pancreatitis and alcoholic pancreatitis are serious health concerns, and there is an urgent need for effective treatment strategies. Alcohol is a known etiological factor for pancreatitis, including acute pancreatitis (AP) and chronic pancreatitis (CP). Excessive alcohol consumption induces many pathological stress responses; of particular note is endoplasmic reticulum (ER) stress and adaptive unfolded protein response (UPR). ER stress results from the accumulation of unfolded/misfolded protein in the ER and is implicated in the pathogenesis of alcoholic pancreatitis. Here we summarize the possible mechanisms by which ER stress contributes to alcoholic pancreatitis. We also discuss potential approaches targeting ER stress and UPR for developing novel therapeutic strategies for the disease.

In order to study the effects of irradiation on the physicochemical properties and digestion behavior of chickpea protein, chickpea protein concentrate (CPC) was treated with electron beam irradiation (EBI) at doses of 5, 10, 15 and 20 kGy, respectively. After irradiation, protein solubility first increased at 10 kGy and 15 kGy, and then decreased at higher dose of 20 kGy. This was supported by SDS-PAGE where the intensity of major protein bands first increased and then decreased. Increased does of EBI generally led to greater oxidative modification of proteins in CPC, indicated by reduced sulfhydryls and increased carbonyls. In addition, protein structure was modified by EBI shown by Fourier transform infrared spectroscopy analysis where α-helix generally decreased and β-sheet increased. Although the protein digestibility was not significantly affected by EBI, the peptidomic analysis of the digests revealed significant difference among CPC irradiated with varying doses. A total of 337 peptides were identified from CPC irradiated with 0 kGy, 10 kGy and 20 kGy, respectively, with 18 overlapping peptides and 60, 29 and 40 peptides specific to the groups of 0, 10 and 20 kGy respectively. Theoretical calculation showed that the distribution of peptide length, hydrophobicity, net charge, and C-terminal residues were affected by irradiation. The 2, 2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging activity showed a marginal decrease with increasing dose of irradiation. In conclusion, EBI led to oxidative modification and structural changes of the chickpea protein, which subsequently affected the physicochemical properties of peptides obtained from in-vitro digestion of CPC despite of similar digestibility.

The adulteration of goat milk powder occurs frequently, cattle-derived and soybean-derived ingredients are common adulterants in goat milk powder. However, simultaneously and rapidly detecting cattle-derived and soybean-derived components is still a challenge. high throughput and efficient screening method for adulteration detection is need. In this study, a rapid method was developed to detect the adulteration of common cattle-derived and soybean-derived components simultaneously in goat milk powder by combining the CRISPR/ Cas12a system with recombinant polymerase amplification (RPA). A dual DNA extraction method was employed, primers and crRNA for dual detection were designed and screened, and a series of condition optimizations were carried out in this experiment. The optimized assay can rapidly detect cattle-derived and soybean-derived components in 40 min. The detection limits of both cattle-derived and soybean-derived components were 1% (w/w) for the mixed adulteration models. The established method was applied into a blind survey of 55 commercially available goat milk powder products. The results showed that 36.36% of the samples contained cattle-derived or soybean-derived ingredients, which revealed the noticeable adulteration situation in the goat milk powder market. This study realizes a fast flow of dual extraction, dual amplification and dual detection of cattle-derived and soybean-derived components in goat milk powder for the first time. It can be used for high-throughput and high-efficiency on-site primary screening of goat milk powder adulterants, and provide a technical reference for combating with food adulteration.

Regeneration of biological tissues in medicine is challenging, and 3D bioprinting offers an innovative way to create functional multicellular tissues. One common way in bioprinting is bioink which is one type of the cell-loaded hydrogel. For clinical application, however, the bioprinting still suffers from satisfactory performance, e.g. in vascularization, effective antibacterial, immunomodulation and regulation of collagen deposition. Many studies have incorporated different bioactive materials into the 3D printed scaffolds to optimize the bioprinting. Here, we review a variety of additives added to the 3D bioprinting hydrogel. The underlying mechanisms and methodology for biological regeneration are important and will provide useful basis for future research.

The ever deepening population aging has brought opportunities and challenges to the continued expansion of tourism consumption in China. In this article, the impact of population aging on household tourism consumption was studied from both theoretical and empirical aspects. First, the micro mechanisms of the impact of population aging on household tourism consumption were analyzed, which include economic condition mechanism, intergenerational care mechanism, health status mechanism and Internet use mechanism. Subsequently, the impact of population aging on household tourism consumption and its impact mechanisms were tested, and the heterogeneity analysis was conducted, by using the data of China Family Panel Studies (CFPS) from 2014, 2016 and 2018. The main conclusions of the article are as follows: (1) Population aging has a significant negative impact on household tourism consumption, and a series of robustness test results such as endogenous treatment support this finding. (2) The results of the impact mechanism test show that population aging has a negative mediating effect on household tourism consumption by reducing household economic conditions. The moderating effect of intergenerational care on the effect of population aging on household tourism consumption is insignificant. Health status of the elderly and Internet use have a significant positive moderating effect on the impact of population aging on household tourism consumption. (3) The results of the heterogeneity analysis show that the negative impact of population aging on household tourism consumption in urban areas is greater than that in rural areas, and the negative impact of population aging on household tourism consumption of families with the old-old elderly is greater than that of falimies with the young-old elderly. The conclusions of this article provide important references for activating tourism consumption in China in the context of population aging.

With the rapid development of global offshore wind power, the demand for offshore wind power operation and maintenance is also increasing. Wisdomization of offshore wind farms is a practical need to improve the operation level and benefit of offshore wind farms. This paper first introduces the current development situation and characteristics of global offshore wind power, and expounds the current situation and main challenges of offshore wind power operation and maintenance market. Therefore, our paper discusses the innovation of offshore wind power operation and maintenance from the aspects of operation and maintenance management of offshore wind power, monitoring and analysis technology of units, far-reaching wind field monitoring and operation and maintenance risks. Then, combined with information technology and lean management concept, a smart operation and maintenance management platform for wind farms in far-reaching sea areas is built to explore centralized and intelligent operation and maintenance management mode, improve operation and maintenance efficiency of wind farms in far-reaching sea areas, and minimize operation and maintenance costs. Finally, through the research on the characteristics of 5G technology, combined with the practical experience of operation and maintenance, and in view of the characteristics of offshore wind farms, we analyze and propose several typical application scenarios of 5G technology in the intelligent operation and maintenance of offshore wind farms, which provides a new solution for the efficient operation and maintenance of offshore wind farms.

Many research work has demonstrated that taken the Combined Cooling Heating and Power system (CCHP) as the core equipment, the integrated energy system (IES) can bring obvious benefit to energy efficiency, CO2 emission reduction and operation economy in urban areas. Compared with isolated IES, integrated energy micro-grid (IEMG) which is formed by connecting multiple regions IES together, through distribution and thermal network, can further improve the reliability, flexibility, cleanliness and economy of regional energy supply. Based on the existing IES model, this paper describes the basic structure of IEMG and built a IEMG planning model. The planning based on the mixed integer linear programming, and economically construction planning scheme are calculated by using known electricity, heating and cooling loads information and the given multiple equipment selection schemes. At last, the model is validated by a case study. The results show that the application of IEMG can effectively improve the economy of regional energy supply.

Network Embedding (NE) is an important method to learn the representations of network via a low-dimensional space. Conventional NE models focus on capturing the structure information and semantic information of vertices while neglecting such information for edges. In this work, we propose a novel NE model named BimoNet to capture both the structure and semantic information of edges. BimoNet is composed of two parts, i.e., the bi-mode embedding part and the deep neural network part. For bi-mode embedding part, the first mode named add-mode is used to express the entity-shared features of edges and the second mode named subtract-mode is employed to represent the entity-specific features of edges. These features actually reflect the semantic information. For deep neural network part, we firstly regard the edges in a network as nodes, and the vertices as links, which will not change the overall structure of the whole network. Then we take the nodes' adjacent matrix as the input of the deep neural network as it can obtain similar representations for nodes with similar structure. Afterwards, by jointly optimizing the objective function of these two parts, BimoNet could preserve both the semantic and structure information of edges. In experiments, we evaluate BimoNet on three real-world datasets and task of relation extraction, and BimoNet is demonstrated to outperform state-of-the-art baseline models consistently and significantly.

Macadamia nut plantings in China are expanding year by year. In order to further promote the superior varieties, this study analyzed the effects of different varieties of rootstock and scion on the survival rate as well as the effects of 18 different ratios of substrate composition on seedling growth were analyzed. The results showed that: The survival rate of HAES788 varieties as rootstock and Guire No.1 as scion was the highest, reaching 96%. The optimal grafting time in December was better than that in March. Substrate formulations 12, 13, 15 and 16 had agglomerated soil and well-developed root systems compared to the controls. Plant height, stem diameter, leaf length, leaf width, and dry weight of aboveground and underground parts were significantly higher than those of the control. In addition, the substrate formulations 12, 13, 15 and 16 significantly improved the organic matter, total nitrogen, and total potassium content of the substrate soils, but little on total phosphorus content. All in all, macadamia grafting times are best in December, with HAES788 and Guire No.1 being the best rootstock and scion. Substrate formulations 12, 13, 15 and 16 are the optimal formula. This study provides a solid foundation to produce high-quality macadamia seedlings.

In this study, Brillouin optical time-domain analysis (BOTDA) sensing technology was utilized for monitoring settlement in a similarity model of a highway subgrade. As contact winding cannot be used for an optical fiber that is buried directly in soil, uncoupling between. the fiber and the soil can occur. Thus, an optical-fiber-embedded beam (OFEB) was developed, and a method for measuring and calculating the beam deformation was proposed. A calibration test and a test on a similarity model of a subgrade were carried out to investigate the applicability and monitoring accuracy of the OFEB. It was concluded that the OFEB can accurately measure beam deflection, where the maximum relative error between measurements by the optical fiber and a displacement transducer was approximately 5%. The OFEB was embedded directly into a similarity model of a subgrade to monitor settlement. The deflection deformation of the OFEB was found to be close to the subgrade settlement over a certain settlement range with a relative error below 8.1%. Thus, the OFEB can be used to realize measure large-range distributed settlement in a subgrade. A numerical simulation was performed to identify appropriate beam dimensions and material design parameters, thereby extending the measurement range before decoupling of the OFEB and soil occurs. The enhancement of the measurement range and accuracy of the OFEB based on the preliminary experiments carried out in this study enables further investigation of settlement monitoring.

With the rapid development of the Internet of Things, massive amounts of data will be generated at the network edge, resulting in increased latency of the traditional cloud computing model. Cloud service providers deploy edge servers near the users to improve the quality of service. Due to the large scale of networks, the inefficiency of edge server deployment and task scheduling will result in excessive latency and severe workload imbalance among edge servers. In this paper, we propose a Server Deployment and Task Scheduling (SDTS) framework in multi-edge collaborative computing, which can effectively reduce latency and ensure workload balancing. First, a metropolitan area network (MAN) is divided into dense candidate regions (DCRs) based on the density characteristics of mobile end devices, and then servers are deployed independently in each sub-region. Then, a two-step clustering algorithm is designed to deploy servers as close as possible to the mobile devices. Finally, a task scheduling algorithm is presented based on an edge scheduling layer in DCRs, which can leverage collaboration between edge servers to improve the performance of the entire edge computing system. The experimental results based on the Cellular Base Station (CBS) dataset of Shanghai Telecom indicate that the proposed approach outperforms several representative strategies in terms of latency and workload balancing.

Coal is an important resource that is closely related to people’s lives and has an irreplaceable role. However, coal mine safety accidents occur from time to time in the process of working underground. To this end, this paper proposes a coal mine environmental safety early warning model to detect abnormalities and ensure worker safety in a timely manner by assessing the underground climate environment. In this paper, the support vector machine (SVM) parameters are optimized using an improved artificial hummingbird algorithm (IAHA), and its safety level is classified by combining various environmental parameters. To address the problems of insufficient global exploration capability and slow convergence of the artificial hummingbird algorithm during iterations, a strategy incorporating Tent chaos mapping and backward learning is used to initialize the population, a Levy flight strategy is introduced to improve the search capability during the guided foraging phase, and then the simplex method is introduced to replace the worst value before the end of each iteration of the algorithm. The IAHA-SVM safety warning model was established using the improved algorithm to classify and predict the safety of the coal mine environment into four classes. Finally, the performance of the IAHA algorithm and the IAHA-SVM model are simulated separately. The simulation results show that the convergence speed and the search accuracy of the IAHA algorithm are improved, and the performance of the IAHA-SVM model has a significant improvement.

We review recent progress in high-speed orbital angular momentum (OAM) multiplexed free-space optical communication systems. The outdoor atmospheric turbulence is emulated by an indoor turbulence emulator, which is based on split-step beam propagation method. Adaptive optics, channel coding, Huffman coding combined with LDPC coding, and spatial offset are used for turbulence mitigation; while OAM multiplexing and wavelength-division multiplexing (WDM) are applied to boost aggregate capacity.

The bridge crane is often used in a complex environment, often subject to interference of all loads. Some uncertainties factors often have an inevitable impact on its swing. So the force situation of the bridge crane during a working cycle is analyzed, and a three-dimensional dynamic mathematical model of the bridge crane is built. Through the simulation analysis of the model under the action of driving force and wind load, the change law of the swing angle of the bridge crane is studied. Then, the fuzzy control theory is used to determine the control parameter in the anti sway control process. The position, swing angle deviation and deviation rate of the bridge crane are taken as the input, and the parameter correction is obtained after the fuzzification by using the center of gravity method, the anti sway fuzzy control system of the bridge crane is designed and simulated. The research results show that the fuzzy PID anti sway controller can not only improve the adaptability of the control system, but also overcome the large overshoot, quickly restrain the swing, and effectively realize the anti sway function of the bridge crane.

The three-pronged sliding universal coupling is a new kind of three-pronged coupling. To study its kinematic and dynamic characteristics, directional cosine matrices are utilized as tools to analyze the coordinate systems by establishing simplified geometric models and corresponding motions. Through the analysis of the motions of the input and output shafts and employing the method of single-force element, a set of equilibrium equations for the forces acting on the output shaft and the input shaft are formulated for solution analysis. The research indicates that during the rotation process, there exists a small angular difference between the input shaft and the intermediate shaft, demonstrating the quasi-constant angular velocity characteristics of the new tripod sliding universal coupling. The curves of the forces and torques acting on each component of the coupling approximate sinusoidal curves. The optimal operating angle range for the new tripod universal coupling is at angle , during which the system exhibits good transmission and mechanical performance.

Co-integration and Causality was built to conduct studies on causality relation between carbon intensity and coal consumption leading to providing important basis for the transition to a low carbon economy. The EG two-step method was performed to study the relation between carbon intensity and coal consumption of China during 1990-2015 and the co-integration and Granger test was constructed to build up the co-integration and error correction models for analysis of the interaction between carbon intensity and coal consumption. The results showed that in long term there is a stable co-integration relation and a positive correlation between carbon intensity and coal consumption; whereas fluctuations exist in short term and there is a one-way Granger causality of carbon intensity with respect to coal consumption.

A major problem in the post-inversion geophysical interpretation is the extraction of geological information from inverted physical property models, which do not necessarily represent all underlying geological features. No matter how accurate the inversions are, each inverted physical property model is sensitive to limited aspects of subsurface geology and is insensitive to other geological features that are otherwise detectable with complementary physical property models. Therefore, specific parts of the geological model can be reconstructed from different physical property models. To show how this reconstruction works, we simulated a complex geological system that comprises an original layered earth model that has passed several geological deformations and alteration overprints. Linear combination of complex geological features comprised three physical property distributions: Electrical resistivity, induced polarization chargeability, and magnetic susceptibility models. This study proposes a multivariate feature extraction approach to extract information about the underlying geological features comprising the bulk physical properties. We evaluated our method in numerical simulations and compared three feature extraction algorithms to see the tolerance of each method to the geological artifacts and noises. We show that the fast-independent component analysis (fast-ICA) algorithm by negentropy maximization is a robust method in the geological feature extraction that can handle the added unknown geological noises. The post-inversion physical properties are also used to reconstruct the underlying geological sources. We show that the sharpness of the inverted images is an important constraint on the feature extraction process. Our method successfully separates geological features in multiple 3D physical property models. This methodology is reproducible for any number of lithologies and physical property combinations and can recover the latent geological features, including the background geological patterns from overprints of chemical alteration.

Dry eye syndrome (DES) has become increasingly prevalent due to the prolonged use of digital devices in modern society. Individual supplementation with lutein or docosahexaenoic acid (DHA) demonstrated potential benefits for eye health. This study aimed to investigate the effects of lutein plus DHA complex supplementation on DES, visual function, and memory in healthy individuals. Thirty-four participants, aged 40~60 years, received lutein/DHA complex supplements (containing 10 mg free-form lutein, 200 mg DHA, 30 mg red algae extract (astaxanthin), phosphatidylserine, and vitamin A) for 12 weeks. Ophthalmological examinations and memory tests were carried out, and a questionnaire was administered at weeks 0, 6, and 12 of the study. After 12 weeks of the intervention, the tear break-up time had significantly increased, and intraocular pressure (IOP) had significantly decreased. This suggests that lutein/DHA complex supplementation may reduce the IOP and offer potential benefits for DES, as indicated by improved tear stability.

The utilization of primary school buildings is multifaceted, primarily due to the high occupancy density, varying thermal preferences among occupants, diverse indoor activities (such as walking, sports, and conversation), and a constant flow of individuals entering and exiting the building. This results in frequent opening and closing of external windows and doors and fluctuations in internal heat gain. Consequently, frequent interactions between the indoor and outdoor microenvironments lead to energy losses. This study conducts a comprehensive literature review on building energy loss stemming from occupant behavior and the interactions between indoor and outdoor microenvironments. Furthermore, it proposes a dynamic real-time monitoring system based on a computer data capture and visualization platform foundation for building energy loss. The research methods include data crawling, data association rule mining, and data association analysis. The research findings yield a universally applicable and informative building energy-saving design theory based on extensive data analysis. Additionally, the system presents information on occupants' behavior and the microclimate data of indoor and outdoor environments on a computer screen, facilitating human-machine communication and enabling timely adjustments to design strategies for new buildings and operation and maintenance strategies for existing buildings.

The key issue in the post-genomic era is how to systematically describe the association between small molecule transcripts or translations inside cells. With the rapid development of high-throughput “omics” technologies, the achieved ability to detect and characterize molecules with other molecule targets opens up the possibility of investigating the relationships between different molecules from a global perspective. In this article, a Molecular Associations Network(MAN) is constructed and comprehensively analyzed by integrating the associations among miRNA, lncRNA, protein, drug, and disease, in which any kind of potential associations can be predicted. More specifically, each node in MAN can be represented as a vector by combining two kinds of information including the attributes of the node itself (e.g. sequences of ncRNAs and proteins, semantics of diseases and molecular fingerprints of drugs) and the manner of the node in the complex network (associations with other nodes). Random Forest classifier is trained to classify and predict new interactions or associations between biomolecules. In the experiment, the proposed method achieves a superb performance with 0.9735 AUC in 5-fold cross-validation, which show that the proposed method can provide new insight for exploration of the molecular mechanisms of disease and valuable clues for disease treatment.

Background: The COVID-19 outbreak has accelerated the huge difference between medical care and disease prevention in Chinese medical institutions. This study aimed to investigated the relationship between the symbiotic units, environments, models, and effects of the integration of medical and disease prevention. Methods: This cross-sectional study involved 762 employees of public hospitals in 11 cities in Zhejiang Province by random stratified sampling. We analyzed the influence paths of elements in the mechanism of integration of medical and disease prevention and the mediating effect of symbiotic models among symbiotic units, symbiotic environments, and effects for on this integration. Results: The path coefficient of symbiotic unit on the symbiosis model was 0.46 (p&lt;.001), the path coefficient of symbiotic environment on symbiosis model was 0.52 (p&lt;.001). The path coefficient of the symbiotic unit and environment was 0.91 (p&lt;.001). The symbiotic models exhibited a partial mediation effect between symbiotic units and the effect of this integration. Sobel test = 3.27, β = 0.152, and the mediating effect accounted for 34.6%. Conclusions: It is suggested that Health policy-makers and public hospital managers should provide sufficient symbiotic units, establish collaborative symbiotic models, and improve the effects of integration of medical and disease prevention in public hospitals.

Earth observation satellites can capture images of specific areas in Earth's orbit based on user requirements. Despite the high demand for satellite imagery, satellites remain a scarce resource. When there are many observation tasks that are large and dense, they may interfere with each other due to satellite mobility. To address this issue, a multi-satellite scheduling algorithm based on a task merging mechanism has been proposed. This paper proposes a two-stage approach to the problem: task merging phase and merging task scheduling phase. The task merging phase introduces two methods based on Mean Shift and Complete Graph to generate the merging task set. In the merging task scheduling phase, a multi-satellite scheduling algorithm based on merging tasks is employed to solve the problem. Finally, certain measurement experiments suggest the effectiveness of the algorithm.

Autophagy is a highly conserved self-degradation process involving the degradation and recycling of cellular components and organelles. Although the involvement of autophagy in metabolic changes during fruit ripening has been preliminarily demonstrated, the variations in autophagic flux and specific functional roles in fruit ripening remain to be elucidated. In this study, we analyzed the occurrence of autophagy during tomato fruit ripening. The results revealed differential expression of SlATG8 family member during tomato fruit ripening. Transmission electron microscopy observations and dansylcadaverine (MDC) staining confirmed the presence of autophagy at the cellular level in tomato fruits. Furthermore, the overexpression of SlATG8f induced the formation of autophagosomes, increased autophagic flux within tomato fruits, effectively enhanced the expression of ATG8 proteins during the color transition phase of fruit ripening, thereby promoting tomato fruit maturation. This overexpression also led to the accumulation of vitamin C (VC) and soluble solids while reducing acidity in the fruit. Collectively, our findings highlight the pivotal role of SlATG8f in enhancing tomato fruit ripening, providing insights into the mechanistic involvement of autophagy in this process. This research contributes to a better understanding of key factors regulating tomato fruit quality and offers a theoretical basis for tomato variety improvement.

Questions：SAP in mountainous cities of China serve as crucial carriers for species and wild food, constituting potential green infrastructure. These patches should be recognized as locally specific resources. This study investigates the transformation characteristics of the landscape patterns of SAP, along with their elements, across urban-rural gradients, providing foundational support for the planning of conservation and utilization strategies. Location: Yongchuan area of Chongqing in southwest China. Methods: The study investigated urban-rural gradient-based transformation of SAP. A four-direction transect space was selected and divided into uniform sample squares. Fragstats 4.3 calculated the landscape index of SAP, and Spearman correlation coefficients in SPSS were used to evaluate the influence of landform and artificial factors on agroforestry patch transformation. Results: 1) Patch area (PA), Plaque density (PD), and CLUMPY of SAP systematically transform, showing increased SAP areas and higher connectivity with greater distance from the city, resulting in reduced patch fragmentation. However, Edge density (ED) and Largest plaque index (LPI) exhibit irregular transformation patterns. 2) With increased distance from the city, woodland patch area and connectivity increase, leading to decreased fragmentation, dispersal, and lower fractal dimensions. Conversely, Cultivated land follows the opposite trend. garden land patch area, fractal dimension, fragmentation, and dispersal all increase, while connectivity decreases. 3) Landscape pattern transformations of SPA are significantly influenced by artificial factors. Woodland patches are influenced similarly by landform and artificial factors. In contrast, cultivated land and garden land patches are more significantly impacted by artificial factors. Conclusions: SAP exhibit differentiated conservation and utilization measures across urban-rural gradients. Small patches located far from urban centers may benefit from systematic conservation measures to prevent further fragmentation and erosion in peri-urban areas.

The research fills the policy research gap for the women entrepreneurship and sustainability performance for examining key successful factors. Previous women entrepreneurship research fails to offer policy recommendations. The research purpose is to investigate these factors affect women entrepreneurship capabilities and sustainability performance by using SEM analysis and making policy recommendation. This research employs online and mail survey and obtains 175 women entrepreneur sample. The study finds that family support and motivation have positive effect on women entrepreneurship capabilities and sustainability performance. Barriers have no effect on performance. Hopefully, the research can provide the guidance to contribute to women’s entrepreneurship opportunities for achieving SDGs. Policy recommendation and managerial implication are discussed in the article.

The application of Virtual Reality in a driving simulation is not novel, yet little is known about the use of this technology by senior populations. The effects of age, sex, control device (joystick or handlebar), and task type on wayfinding proficiency using a virtual reality (VR) driving simulation were explored. The driving experimental model involved 96 randomly recruited participants, including 48 young people and 48 seniors (split evenly by gender in each group). The experimental results and statistical analyses indicate that in a VR driving scenario task type significantly affected VR driving performance. Navigational scores were significantly higher for the straight (easy) task than for the curved (difficult) task. The aging effect was the main reason for significant and interacting effects of sex and control device. It was found that interactions between age and sex difference indicated that the young group exhibited better wayfinding performance than the senior group, and in the young group males had better performance than females. Similarly, interactions between age and control device indicated that the handlebar control device type resulted in better performance than the joystick device in the young group, but no difference was found in the senior group due to age or learning effects. Findings provide an understanding of the evaluation of the interface designs of navigational support systems, taking into consideration any effects of age, sex, control device, and task type within three-dimensional VR games and driving systems. With a VR driving simulator, seniors can test drive inaccessible products, such as electric bicycles or cars, using a computer at home.

Improper disposal of waste plastic has caused serious ecological and environmental pollution problems. Transforming plastics into high value-added chemicals can not only achieve efficient recycling of waste plastics, but also an effective way to control white pollution. The catalyst selectively breaks the C-C bond of polyolefin plastic under heat treatment and converts it into liquid fuel, thus realizing sustainable recycling of plastics and has a good development prospect. This review provides a detailed overview of the current development of catalytic pyrolysis, catalytic hydrolysis, solvent decomposition and supercritical hydrothermal liquefaction for cracking plastics to make fuel oil. The reaction mechanism, influencing factors and promoting effects of catalysts in various degradation technologies are analyzed and summarized and the latest proposed tandem reaction for degrading plastics is briefly introduced. Finally, some optimization paths of waste plastic pyrolysis to fuel oil technology are proposed: synergies between mixed raw materials, in-depth exploration of catalysts, design and manufacture of reactors that match the pyrolysis technology. All these are important research directions for promoting the industrialization of plastic pyrolysis to fuel oil.

Dry eye disease (DED) is one of the most common eye diseases. There is at least one DED patient in almost every five people. AI-based research methods increasingly become the focus of DED diagnosis research. This study utilizes a systematic review method on DED AI-based diagnosis. 2112 unduplicated records are extracted from Google Scholar, Web of Science (WOS), PubMed, China National Knowledge Infrastructure (CNKI), and Scopus databases. The most contributed countries, institutions, authors, journals, references, and disciplines are recognized. Keyword distribution and hot topics are identified. Popular databases of ophthalmic images, videos, and electronic demographic medical records are discussed. The DED diagnosis, classification, and grading criteria are identified. The major diagnosing methods are clustered, compared, and investigated. Findings show that diagnosing method research could be classified into three categories based on the relationship between AI techniques, which are (1) ground truth and/or comparable standards for AI DED diagnosis (TBUT, S Ⅰ T, TMH, and OSDI), (2) potential methods for AI-based methods have a great advantage(DED detection based on meibometry Images, CASPs, IVCM Images, OCT Images, blink videos and ultrasonic imaging), (3) and the potential direction and supplemented methods for AI-based DED detection (DED detections based on tear osmolarity, proteomic analysis, TCM and demographic information). AI-based approaches based on digital ophthalmologic images play an important role in early screening. Challenges and future perspectives are discussed at the end of this article, academically and practically.

The fusion of "innovation theory" and "ecology" gave birth to a large number of studies on "innovation ecology", which mainly studies how to build an industrial ecological chain at the regional level, focusing on self-evolution, achieving ecological balance, and enabling the regional economy to take the path of sustainable innovation. This type of research borrows a lot of concepts from ecology, and very vividly describes the competition and cooperation relationships formed by various agents in the innovation system, laying a good foundation for qualitative analysis of the inherent dynamics of innovation development. However, many studies focus on the analogous description of ecosystems and economic systems, lacking scientifically and rigorously quantitative empirical research as a support. This paper uses network-based indicators such as degree, cluster coefficient, and betweenness centrality to measure the function and position of high-tech enterprises in the Z-Park in a business environment, so as to clarify the socio-economic meaning of the topological structure of the regional innovation system. On this basis, it provides theoretical references for regional innovation development and sustainable development policy formulation.

Various sudden shifts in financial market conditions over the past decades have demonstrated the significant impact of market structural breaks on firms' credit behavior. To characterize such effect quantitatively, we develop a continuous-time modulated Markov model for firms' credit rating transitions with the possibility of market structural breaks. The model takes a semi-parametric multiplicative regression form, in which the effects of firms' observable covariates and macroeconomic variables are represented parametrically and nonparametrically, respectively, and the frailty effects of unobserved firm-specific and market-wide variables are incorporated via the integration form of the model assumption. We further develop a mixtured-estimating-equation approach to make inference on the effect of market variations, baseline intensities of all firms' credit rating transitions, and rating transition intensities for each individual firm. We then use the developed model and inference procedure to analyze the monthly credit rating of U.S. firms from January 1986 to December 2012, and study the effect of market structural breaks on firms' credit rating transitions.

Concrete cracks and local damage can affect the bond performance between concrete and steel bars, thereby reducing the durability of reinforced concrete structures. Compared with general concrete crack repair methods, biomineralization repair not only has effective bonding capabilities but is also particularly environmentally friendly. In view of this, this study aimed to apply biomineralization technology to repair damaged fiber-reinforced lightweight aggregate concrete (LWAC). Two groups of LWAC specimens were prepared. The control group used lightweight aggregates (LWAs) without bacterial spores and nutrient sources, and the experimental group used LWAs containing bacterial spores and nutrient sources. These specimens were first subjected to compression tests and pull-out tests, respectively, and thus were damaged. After the damaged specimen healed itself in different ways for 28 days, secondary compression and pull-out tests were conducted. The self-healing method of the control group involved placing the specimens in an incubator. The experimental group was further divided into experimental group I and experimental group II. The self-healing method of experimental group I was the same as that of the control group. The self-healing method of experimental group II involved soaking the specimen in a mixed solution of urea and calcium acetate for two days, and then taking it out and placing it in an incubator for two days, with a cycle of four days. The test results showed that, compared with the control group specimens, the relative bond strength ratio of the experimental group II specimens increased by 17.9%. Moreover, the EDS and XRD analysis results confirmed that the precipitate formed at the crack was calcium carbonate, which improved the compressive strength and bond strength after self-healing. This indicates that the biomineralization maintenance method used in experimental group II is more effective.

Technology can be seen everywhere and has been integrated into our lives.We are always using technology and enjoying the convenience brought by technology. However, physical retailers and e-commerce companies are also gradually adopting advanced technologies. Technology improves the purchasing environment and purchasing experience. Virtual reality and augmented reality have been hotly discussed in recent years. Technology, although virtual reality and augmented reality technology have not yet matured, it can be said that they will in the future It has great development potential. Virtual reality and augmented reality are also beginning to sprout in the retail industry. However, research on the acceptance of the use of virtual reality and augmented reality in the apparel shopping process is still lacking because This study explores how usefulness, ease of use, hedonicity, customer experience, customer engagement and satisfaction. To influence customer loyalty, this study adopted questionnaire survey and convenience sampling methods, and collected a total of 308 valid questionnaires. The analysis method used confirmatory factor analysis and structural equation model to verify the research hypothesis relationship. The results of this study found. Hedonic has a significant impact on customer loyalty, while usefulness, ease of use, customer experience, customer engagement and satisfaction Satisfaction does not have a significant impact on customer loyalty. This study explains the academic contribution of the research results. The practical implications in marketing are put forward, and specific suggestions and directions for future research are given.

The pathogenicity of grapevine geminivirus A (GGVA), a recently identified DNA virus, to grapevine plants remains largely unclear. Here, we report a new GGVA isolate (named GGVAQN) obtained from grapevine ‘Queen Nina’ plants with severe disease symptoms; the infectious clone of GGVAQN (pXT-GGVAQN) was also constructed. Infection assays indicated that Nicotiana benthamiana plants inoculated with GGVAQN display upward leaf curling and chlorotic mottling symptoms. Direct injection of Agrobacterium tumefaciens cells carrying pXT-GGVAQN into roots of in vitro-grown ‘Red Globe’ grape plantlets by syringe led to systemic infection with GGVAQN, and the plants exhibited chlorotic mottling symptoms on their upper leaves, and downward curling, interveinal yellowing, and leaf-margin necrosis symptoms on their lower leaves. Our results provide insights into the pathogenicity of GGVA, and a simple and efficient inoculation method to deliver infectious viral clones to woody perennial plants.

Text CAPTCHAs are crucial security measures employed on global websites to deter unauthorized intrusions. The presence of anti-attack features incorporated into text CAPTCHAs limits the effectiveness of breaking them, despite CAPTCHA recognition being an effective method for assessing their security. This study introduces a novel color augmentation technique called Variational Color Shift (VCS) to boost the recognition accuracy of different networks. VCS generates a color shift range of every input image and then resamples the image within that range to generate a new image, thus expanding the number of samples of the original dataset to improve training effectiveness. In contrast to Random Color Shift (RCS) which treats the color offsets as hyperparameters, VCS uses the estimated offsets to reparametrize the points sampling from the unit uniform distribution to reconstruct new image pixels, which makes the offsets learnable. To reduce the computational effort of VCS, we also propose two variants of VCS: Sim-VCS and Dilated-VCS. In addition, to solve the overfitting problem caused by many disturbances in CAPTCHAs, we propose an Auto Encoder (AE) based on a Large Separable Kernel Attention (AE-LSKA) to replace the convolutional module in the text CAPTCHA recognizer. This new module employs an AE) to compress the interference while expanding the receptive field using Large Separable Kernel Attention (LSKA), which reduces the impact of local interference on the model training and improves the overall perception of characters. The experimental results show that the recognition rate of the model after integrating the AE-LSKA module is improved by at least 15 percentage points on both M-CAPTCHA and P-CAPTCHA datasets. In addition, experimental results demonstrate that color augmentation using VCS is more effective in enhancing recognition.

The demand for precise indoor localization services is steadily increasing. Among various methods, fingerprint-based indoor localization has become a popular choice due to its exceptional accuracy, cost-effectiveness, and ease of implementation. However, its performance degrades significantly as a result of multipath signal attenuation and environmental changes. In this paper, we propose an indoor localization method based on fingerprints using self-attention and long short-term memory (LSTM). By integrating a self-attention mechanism and LSTM network, the proposed method exhibits outstanding positioning accuracy and robustness in diverse experimental environments. The performance of the proposed method is evaluated under two different experimental scenarios, which involve 2D and 3D moving trajectories, respectively. The experimental results demonstrate that our approach achieves an average localization error of 1.76 m and 2.83 m in the respective scenarios, outperforming the existing state-of-the-art methods by 42.67% and 31.64%.

Bisphenol A (BPA) has been identified as one of endocrine disrupting chemicals (EDCs). Due to its massive production (over 700,000 tons per year) and the extensive use of BPA-based plastics (i.e., polycarbonate and epoxy resin) in Taiwan, it was thus included into a toxic substance by the Ministry of Environment. This work surveyed the updated information about the production of BPA and its environmental distributions in Taiwan over the past decade. Furthermore, the regulatory strategies and countermeasures for managing the environmental risks of BPA by the Taiwan government were summarized to show the cross-ministerial efforts under the relevant acts, including the Toxic and Concerned Chemical Substances Control Act (TCCSCA), the Food Sanitation Management Act (FSMA) and the Commodity Inspection Act (CIA). The findings showed that most of the monitoring data showed far below the acceptable risks. However, the people may pose an adverse threat to the aquatic environment and human health via ecological and food chains. In addition, some countermeasures were further recommended to echo the international actions on environmental endocrine disruptors in recent years.

Background: Alzheimer's disease (AD) is a leading cause of dementia, significantly influenced by the Apolipoprotein E4 (APOE4) gene and gender. This study aims to use machine learning (ML) algorithms to predict brain age and assess AD risk by considering the effects of APOE4 genotype and gender. Methods: We collected brain volumetric MRI data and medical records from 1100 cognitively unimpaired individuals and 602 AD patients. We applied three ML regression models—XGBoost, Random Forest (RF), and Linear Regression (LR)—to predict brain age. Additionally, we introduced two novel metrics, Brain Age Difference (BAD) and Integrated Difference (ID), to evaluate model performance and analyze the influence of APOE4 genotype and gender on brain aging. Results: AD patients displayed significantly older brain ages compared to their chronological ages, with BADs ranging from 6.5 to 10 years. The RF model outperformed both XGBoost and LR in terms of accuracy, delivering higher ID values and more precise predictions. Comparing APOE4 carriers with non-carriers, the models showed enhanced ID values and consistent brain age predictions, improving overall performance. Gender-specific analyses indicated slight enhancements, with models performing equally well on both genders. It indicates that APOE4 may be a more robust predictor of brain age than gender. Conclusion: Robust ML models for brain age prediction can be pivotal in the early detection of AD risk via MRI brain structural imaging, especially for APOE4 carriers. Such early identification may facilitate timely preventive interventions for AD.

According to many research groups, high glucose induces over production of superoxide anions, and reactive oxygen species (ROS) in general is the link between high glucose levels and the toxicities seen at cellular levels. Respiratory complex anomalies could lead to the production of ROS. Calcium [Ca2+], at physiological levels serves as a second messenger in many physiological functions. Accordingly, mitochondrial calcium [Ca2+]m overload leads to ROS production which could be lethal to the mitochondria through various mechanisms. The F1F0-ATPase (ATP syn-thase or complex V) is the enzyme that is responsible for catalyzing the final step of oxidative phosphorylation. It does so by coupling the translocation of protons in the mitochondrial in-termembrane space and shuttling them to the mitochondrial matrix for ATP synthesis to take place. Mitochondrial complex V T8993G mutation specifically blocks the translocation of protons across the intermembrane space thereby blocking ATP synthesis leading to Neuropathy, Ataxia and Retinitis Pigmentosa Syndromes (NARP). This study seeks to explore the possibility of [Ca2+]m overload mediating the pathological roles of high glucose in defective respiratory chain mediated mitochondrial stress. The NARP cybrids are the in vitro experimental models for the cells with F1FO-ATPase defects, these cells harbor 98% of mtDNA T8993G mutation. Their coun-terparts 143B osteosarcoma cell lines are the parental cell lines used for comparisons. We uncov-ered that, NARP cells mediated and enhanced the death of the cells (apoptosis) when incubated with hydrogen peroxide (H2O2) and high glucose respectively as depicted by the MTT assay of cell viability. Furthermore, using the fluorescence probe-coupled laser scanning confocal imag-ing microscopy, NARP cells significantly enabled mitochondrial reactive oxygen species (mROS) formation and enhanced the depolarization of the mitochondrial membrane potential (ΔΨm). Elucidating the mechanisms of sugar enhanced toxicity on mitochondria would help in the fu-ture to alleviate the symptoms of patients associated with (NARP) syndromes.

This study presents an exploration into identifying the interactions between ocean waves and the continental margin in the origination of double-frequency (DF, 0.1-0.5 Hz) microseisms recorded at 33 stations across East Coast of USA (ECUSA) during a ten-day period of ordinary ocean wave climate. Daily primary vibration directions are calculated in three frequency bands and projected as great circles passing through each station. In each band, the great circles from all stations exhibit largest spatial density primarily near the continental slope in the western North Atlantic Ocean. Generation mechanisms of three DF microseism events are explored by comparing temporal and spatial variations of the DF microseisms with the migration patterns of ocean wave fronts in Wavewatch III hindcasts. Correlation analyses are conducted by comparing the frequency compositions of and calculating the correlation coefficients between the DF microseisms and the ocean waves recorded at selected buoys. The observations and analyses lead to a hypothesis that the continental slope causes wave reflection, generating low frequency DF energy and that the continental shelf is where high frequency DF energy is mainly generated in ECUSA. The hypothesis is supported by the primary vibration directions being mainly perpendicular to the strike of the continental slope.

To evaluate the relative importance of IGF-I expression in various cell types for endochon-dral ossification, we quantified the trabecular bone at the secondary spongiosa and epiphysis of the distal femur in 8-12-week-old male mice with a global knockout of the Igf-I gene as well as conditional deletion of the Igf-I gene in osteoblasts, chondrocytes, osteo-blasts/chondrocytes, and their corresponding control wild type littermates. The osteoblast-, chondrocyte- and osteoblast/chondrocyte-specific Igf-I conditional knockout mice were generated by crossing Igf-I floxed mice with Cre transgenic mice in which Cre expression is under the control of Col1α2 or Col2α1 promoter. We found that global disruption of Igf-I resulted in 80% and 70% reduction in bone size, which is defined as total volume, at the secondary spongiosa and epiphysis of the distal femur, respectively. Abrogation of Igf-I in Col1α2-producing osteoblasts, but not Col2α1-producing chondrocytes, decreased bone size by 25% at both the secondary spongiosa and epiphysis while deletion of the Igf-I globally or specifically in osteoblasts or chondrocytes reduced trabecular bone mass by 25%. By contrast, global Igf-I knockout but not conditional knockout of Igf-I in osteoblasts and/or chondrocytes reduced trabecular bone mass in the epiphysis. The reduced trabecu-lar bone mass at the secondary spongiosa in osteoblast- and/or chondrocyte-specific Igf-I conditional knockout mice is caused by reduced trabecular number and increased trabec-ular separation. Immunohistochemistry studies revealed that expression levels of chon-drocyte (COL10, MMP13) and osteoblast (BSP) markers were reduced in the secondary spongiosa and the epiphyses in the global Igf-I knockout mice. Our data indicate that local and endocrine IGF-I actions in bone are pleiotropic and dependent on cell type as well as the bone compartment where IGF-I acts.

The raw material purchasing (RMP) problem is to determine the purchasing quantities of raw materials in given periods or cycles. Raw material purchasing optimization is crucial for large-scale steel plants because it is closely related to the supply of raw materials and cost savings. The raw material purchasing of large-scale steel enterprises is characterized by many varieties, large quantities, and high costs. The RMP objective is to minimize the total purchasing cost consisting of the price of raw materials, purchasing set-up costs, and inventory costs and meet product demand. We present a mixed integer linear programming (MILP) model and a column generation (CG) solution for the resulting optimization problem. The column generation algorithm is the generalization of the branch & bound algorithm with solving the linear programming (LP) relaxation of MILP using column generation (CG), and its advantage is to handle large-sized MILPs. Experimental results show the effectiveness and efficiency of the solution.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Construction using earth materials demonstrates ecological sustainability using locally sourced natural materials and environmentally friendly demolition methods. In this study, the environmental impact of adding cement to soil materials for rammed-earth farmhouse construction in rural China was investigated and comparatively simulated using the One Click LCA database, focusing on the conflict between sustainability objectives and the practical aspects of cement addition. By analyzing how the addition of cement aligns with local construction practices and by addressing the debate surrounding the inclusion of cement in rammed earth construction, our objective is to provide insights into achieving a balance between the environmental impact and the pragmatic considerations of using cement in earthen building practices. Three local structure scenarios are evaluated via simulations: a cement-stabilized rammed earth wall, a fired brick wall, and a localized reinforced concrete frame structure. The quantitative environmental impacts are assessed, and the qualitative differences in adaptation, economic sustainability, and other factors are examined in the context of present-day development in rural China. The results show that the use of cement-stabilized rammed earth wall-supported structures is associated with higher embodied carbon emissions compared to structures supported by reinforced concrete frames and enclosed by brick walls; however, these emissions are lower than those for brick wall-supported structures, while effectively meeting the structural requirements. In addition, the use of cement-stabilized earth for perimeter walls simplifies material management and disposal throughout the building's life cycle, and the cost-effectiveness of cement has been found to be substantially greater than that of reinforced concrete frames and brick structures, improving economic viability and social acceptability, especially among low-income communities in rural areas.

A finite element model of 100m X-BOW polar exploration cruise is established. The entire ship frequency response analysis was carried out, comparing the simulated values with the test values, the maximum error is 22%, but only 0.24mm/s difference, the error can be ignored from the perspective of comfort, therefore, the simulation results meet the requirements of engineering accuracy and verify the effectiveness of the model. According to the solution method for global modal equivalent mass, combing the spatial distribution principle of local modal mass, the method for solving the equivalent mass of a single local mode in mixed mode is proposed, the equivalent mass of the local vibration region of 100m X-BOW polar exploration cruise ship is solved by this method, tuned mass dampers mass ratio parameters are calculated using the equivalent mass. According to the analysis, tuned mass dampers has 31dB vibration absorption effect at 13.4Hz when the mass ratio is 0.05, it also has certain control effect at 10Hz and 18.8Hz, the control effect is 3dB and 2dB respectively, the overall control frequency band is flat and robust.

This article puts forward the bi-matrix games with crisp parametric payoffs based on interval value function approach. We conclude that the equilibrium solution of the game model can converted into optimal solutions of the pair of the non-linear optimization problem. Finally, experiment results show the efficiency of the model.

With the COVID-19 pandemic now ongoing for close to a year, people all over the world are still waiting for a vaccine to become available. The initial focus of accelerated global research and development efforts to bring a vaccine to market as soon as possible was on novel platform technologies that promised speed but had limited history in the clinic. In contrast, recombinant protein vaccines, with numerous examples in the clinic for many years, missed out on the early wave of investments from government and industry. Emerging data are now surfacing suggesting that recombinant protein vaccines indeed might offer an advantage or complement to the nucleic acid or viral vector vaccines that will likely reach the clinic faster. Here, we summarize the current public information on the nature and on the development status of recombinant subunit antigens and adjuvants targeting SARS-CoV-2 infections.

A number of challenging combinatorial optimization problems in logistics, transportations, aeronautics, and astronautics can be modeled as orienteering problems (OPs). To address the classic OP and its real-world variants, a parallel adaptive local-search algorithm based on competition and evolution (Palace) is proposed in this paper. In this algorithm, the parallelism runs proper local-search metaheuristics and operators to obtain the population per generation; then the competition grades those metaheuristics and operators to highlight the outperforming and eliminate the underperforming; also, the evolution explores large solution space and reproduces the best solutions for next generation. In this manner, the parallelism, competition, and evolution are organized in an easy-to-use algorithm and enable the expansibility, adaptivity, and exploration abilities, respectively. The Palace is examined on the classic and real-world Benchmarks about the OP, the time-dependent/independent OP with time windows, and the unmanned aerial vehicle and agile earth observation satellite planning. As a result, the Palace shows good performance in applicability and effectiveness in comparison with the state-of-the-art algorithms.

Blast, caused by Magnaporthe oryzae, is one of the most destructive diseases affecting rice production. Understanding population dynamics of the pathogen avirulence genes is pre-required for breeding and then deploying new cultivars carrying promising resistance genes. The divergence and population structure of AvrPii was dissected in the populations of southern (Guangdong, Hunan, and Guizhou) and northern (Jilin, Liaoning, and Heilongjiang) China, via population genetic and evolutionary approaches. The evolutionary divergence between a known haplotype AvrPii-J and a novel one AvrPii-C was demonstrated by haplotype-specific amplicon-based sequencing and genetic transformation. The different avirulent performances of a set of seven haplotype-chimeric mutants suggested that the integrity of the full-length gene structures is crucial to express functionality of individual haplotypes. The population structure of the AvrPii family was shaped by balancing, purifying, and positive selection pressures in the Chinese populations. The AvrPii-J was recognized as the wild type that emerged before rice domestication. Considering higher frequencies of avirulent isolates were detected in Hunan, Guizhou, and Liaoning, the cognate resistance gene Pii could be continuously served as a basic and critical resistance resource in such regions. The unique population structures of the AvrPii family found in China have significant implications for understanding how the AvrPii family has kept an artful balance and purify among its members (haplotypes) those keenly interact with the cognate resistance gene under gene-for-gene relationships.

The present paper investigates numerically the resistance at full-scale of a zero-emission, high-speed catamaran in both deep and shallow water, with the Froude number ranging from 0.2 to 0.8. The numerical methods are validated by two means: a) comparison with available model tests; b) a blind validation using two different flow solvers. The resistance, sinkage and trim of the catamaran, as well as the wave pattern, longitudinal wave cuts and cross-flow fields, are examined. The total resistance curve in deep water shows a continuous increase with the Froude number while in shallow water, a hump is witnessed near the critical speed. This difference is mainly caused by the pressure component of total resistance, which is significantly affected by the interaction between the wave systems created by the demihulls. The pressure resistance in deep water is maximised at a Froude number around 0.58, whereas the peak in shallow water is achieved near the critical speed (Froude number ≈ 0.3). Insight into the underlying physics is obtained by analysing the wave creation between the demihulls. Profoundly different wave patterns within the inner region are observed in deep and shallow water. Specifically, in deep water, both crests and troughs are generated and moved astern as the increase of the Froude number. The maximum pressure resistance is accomplished when the secondary trough is created at the stern, leading to the largest trim angle. In contrast, the catamaran generates a critical wave normal to the advance direction in shallow water, which significantly elevates the bow and creates the highest trim angle as well as pressure resistance. Moreover, significant wave elevations are observed between the demihulls at supercritical speeds in shallow water which may affect the decision for the location of the wet deck.

Auto checkout has received more and more attention in recent years and this system automatically generates a shopping bill by identifying the picture of the products purchased by the customers. However, the system is challenged by the domain adaptation problem, where each image of the training set contains only one commodity, whereas the test set is a collection of multiple commodities. The existing solution to this problem is to resynthesize the training images to enhance the training set. Then the composite images are rendered using CycleGAN to make the image distribution of the training set and the test set more similar. However, we find that the detection boxes given by the ground truth of the common dataset contain a large part of the background area, the area will affect the training process as noise. To solve this problem, we propose a mask data priming method. Specifically, we redo the large scale Retail Product Checkout (RPC) dataset and add segmentation annotation information to each item in the training set image based on the original dataset using pixel-level annotation. Secondly, a new network structure is proposed in which we train the network using joint learning of detectors and counters, and fine-tune the detection network by filtering out suitable images from the test set. Experiments on the RPC dataset have shown that our method yields better results. we used an approach that reached 81.87% compared to 56.68% for the baseline approach which demonstrates that pixel-level information helps to improve the detection results of the network.

In this paper, we propose a novel network representation learning model TransPath to encode heterogeneous information networks (HINs). Traditional network representation learning models aim to learn the embeddings of a homogeneous network. TransPath is able to capture the rich semantic and structure information of a HIN via meta-paths. We take advantage of the concept of translation mechanism in knowledge graph which regards a meta-path, instead of an edge, as a translating operation from the first node to the last node. Moreover, we propose a user-guided meta-path sampling strategy which takes users' preference as a guidance, which could explore the semantics of a path more precisely, and meanwhile improve model efficiency via the avoidance of other noisy and meaningless meta-paths. We evaluate our model on two large-scale real-world datasets DBLP and YELP, and two benchmark tasks similarity search and node classification. We observe that TransPath outperforms other state-of-the-art baselines consistently and significantly.

The electronic structural evolution of LLM-105 crystal and the (101) plane of LLM-105 crystal under different pressures is investigated by the density functional theory (DFT) calculations and the surface properties of seven low-Miller-index planes of LLM-105 crystal were investigated in this study. The result demonstrates that the surface energy of (101) plane of LLM-105 is much smaller when compared with other low-Miller-index planes of LLM-105.In order to further investigate the stability of crystal structure and (101) plane of LLM-105 under different pressures, a series of pressures ranged from 0 GPa to 55 GPa were applied during the DFT calculation, and the result shows that the electronic structures of LLM-105 crystal and the (101) plane changed with the increase of external pressure and the evolution process of (101) plane is different from that of LLM-105 crystal structure.

Skeletal muscle atrophy is one of the major side effects of high dose or sustained usage of glucocorticoids. Pyroptosis is a novel form of pro-inflammatory programmed cell death that may contribute to skeletal muscle injury. Trimetazidine, a well-known anti-anginal agent, can also improve skeletal muscle performance both in human and mice. We here showed that dexamethasone induced atrophy, evidenced by the increase of muscle atrophy F-box (Atrogin-1) and muscle ring finger 1 (MuRF1) expression , and the decrease of myotube diameter in C2C12 myotubes. Dexamethasone also induced pyroptosis, indicated by upregulated pyroptosis-related protein NLRP3, Caspase-1 and GSDMD. Knockdown of NLRP3 or GSDMD attenuated dexamethasone-induced myotube pyroptosis and atrophy. Trimetazidine administration ameliorated dexamethasone-induced muscle atrophy both in vivo and in vitro. Moreover, trimetazidine improved exercise tolerance, as evidenced by increased running distance and running time, as well as increased skeletal muscle mass in dexamethasone-treated mice. Mechanically, trimetazidine could reverse dexamethasone-induced activation of pyroptosis both in C2C12 myotubes and in mice. Taken together, our present study demonstrated that NLRP3/GSDMD pathway-mediated pyroptosis was involved in dexamethasone-induced skeletal muscle atrophy. Trimetazidine could partially alleviate dexamethasone-induced skeletal muscle atrophy, and increase the diameter of C2C12 myotubes via inhibiting pyroptosis. Thus, trimetazidine might be a potential therapeutic compound for the prevention of muscle atrophy in glucocorticoid-treated patients.

Enterovirus 71 (EV71) is an etiological agent of hand foot and mouth disease and can also cause neurological complications in young children. However, there are no approved drugs to treat EV71 infections. In this study, we conducted an antiviral drug screening by using a Food and Drug Administration (FDA)-approved drug library. We identified five drugs that showed dose-dependent inhibition of viral replication. Sertraline was further characterized because it exhibited the most potent antiviral activity with the highest selectivity index among the five hits. The antiviral activity of sertraline was noted for other EV serotypes. The drug’s antiviral effect is not likely associated with its approved indications as an antidepressant and its mode-of-action as a selective serotonin reuptake inhibitor. The time-of-addition assay revealed that sertraline inhibited an EV71 infection at the entry stage. We also showed that sertraline partitioned into acidic compartments, such as endolysosomes, to neutralize the low pH levels. In agreement with the findings, the antiviral effect of sertraline could be relieved greatly by exposing virus-infected cells to extracellular low-pH culture media. Together, we have identified an FDA-approved antidepressant with the new indication for the broad-spectrum EV inhibition by blocking viral entry through the alkalization of the endolysosomal route.

A SARS-CoV receptor-binding domain (RBD) recombinant protein was developed and manufactured under current good manufacturing practices in 2016. The protein known as RBD219-N1 when formulated on Alhydrogel®, induced high-level neutralizing antibodies and protective immunity with minimal immunopathology in mice after a homologous virus challenge with SARS-CoV (MA15 strain). In this report, we examined published evidence in support of whether the SARS-CoV RBD219-N1 could be repurposed as a heterologous vaccine against Coronavirus Infectious Disease (COVID)-19. Our findings include evidence that convalescent serum from SARS-CoV patients can neutralize SARS-CoV-2. Additionally, a review of published studies using monoclonal antibodies (mAbs) raised against SARS-CoV RBD and that neutralize the SARS-CoV virus in vitro, finds that some of these mAbs bind to the receptor-binding motif (RBM) within the RBD, while others bind to domains outside this region within RBD. This information is relevant and supports the possibility of developing a heterologous SARS-CoV RBD vaccine against COVID-19, especially due to the finding that the overall high amino acid similarity (82%) between SARS-CoV and SARS-CoV-2 spike and RBD domains is not reflected in RBM region (59%). However, the high similarity (94%) in the region outside of RBM offers the potential of conserved neutralizing epitopes between both viruses.

In order to solve the problem of feature extraction of underwater acoustic signals in complex ocean environment, a new method for feature extraction from ship radiated noise is presented based on empirical mode decomposition theory and permutation entropy. It analyzes the separability for permutation entropies of the intrinsic mode functions of three types of ship radiated noise signals, and discusses the permutation entropy of the intrinsic mode function with the highest energy. In this study, ship radiated noise signals measured from three types of ships are decomposed into a set of intrinsic mode functions with empirical mode decomposition method. Then, the permutation entropies of all intrinsic mode functions are calculated with appropriate parameters. The permutation entropies are obviously different in the intrinsic mode functions with the highest energy, thus, the permutation entropy of the intrinsic mode function with the highest energy is regarded as a new characteristic parameter to extract the feature of ship radiated noise. After that, the characteristic parameters, namely, the energy difference between high and low frequency, permutation entropy, and multi-scale permutation entropy, are compared with the permutation entropy of the intrinsic mode function with the highest energy. It is discovered that the four characteristic parameters are at the same level for similar ships, however, there are differences in the parameters for different types of ships. The results demonstrate that the permutation entropy of the intrinsic mode function with the highest energy is better in separability as the characteristic parameter than the other three parameters by comparing their fluctuation ranges and the average values of the four characteristic parameters. Hence, the feature of ship radiated noise can be extracted efficiently with the method.

3D Zernike moments based on 3D Zernike polynomials have been successfully applied to the field of voxelized 3D shape retrieval and have attracted more attention in biomedical image processing. As the order of 3D Zernike moments increases, both computational efficiency and numerical accuracy decrease. Due to this phenomenon, a more efficient and stable method for computing high-order 3D Zernike moments was proposed in this study. The proposed recursive formula for computing 3D Zernike radial polynomials combines the recursive calculation of spherical harmonics to develop a voxel-based algorithm for the calculation of 3D Zernike moments. The algorithm was applied to the 3D shape Michelangelo's David with a size of 150×150×150 voxels. As compared to the method without additional acceleration, the proposed method uses a group action of order sixteen orthogonal group and saving unnecessary iterations, the factor of speed-up is 56.783±3.999 when the order of Zernike moments is between 10 and 450. The proposed method also obtained an accurate reconstructed shape with the error rate (normalized mean square error) of 0.00 (4.17×10^-3) when the reconstruction was computed for all moments up to order 450.

This paper studied the dynamic characteristics of the deployment process of the replaceable interface mast and the vibration generated at the end of the mast. The interface is discretized by the absolute nodal coordinate thin shell element with gradient reduction, and the three-dimensional motion of the reconfigurable rigid body module is described by the natural coordinate method. The dynamic equations of the interface and the reconfigurable module without external constraints are established by the principle of virtual work. Finally, the dynamic models of each part are assembled into the dynamic model of the mast system deployment process through the system constraint equation. According to the established dynamic model of the mast system deployment process, the dynamic behavior changes of the replaceable interface mast are analyzed. At the same time, the differences in the deployment behavior of the replaceable interface mast under different system configuration schemes, flexible interface geometric parameters, and different driving laws are studied and compared. It provides guidance for the scheme configuration of the mast system, the structural design of the interface, and the deployment motion planning of the mast. According to the physical prototype and the assembly of the mast system model, the deployment process of the replaceable interface mast is experimentally analyzed. It shows that the established dynamic model of the mast system can correctly analyze the dynamic characteristics of the deployment behavior of the replaceable interface mast, which provides a reference for the design and behavior analysis of the mast system.

In recent years, applying deep learning to solve physics problems has attracted much attention. Data-driven deep learning methods produce operators that can learn solutions to the whole system of partial differential equations. However, the existing methods are only evaluated on simple flow equations (e.g., Burger's equation), and only consider the generalization ability on different initial conditions. In this paper, we construct CFDBench, a benchmark with four classic problems in computational fluid dynamics (CFD): lid-driven cavity flow, laminar boundary layer flow in circular tubes, dam flows through the steps, and periodic Karman vortex street. Each flow problem includes data with various boundary conditions, fluid physical properties, and domain geometries. Compared to existing datasets, the advantages of CFDBench are (1) comprehensive. It contains common physical parameters such as velocity, pressure, and cavity fraction. (2) realistic. It is very suitable for deep learning solutions of fluid mechanics equations. (3) challenging. It has a certain learning difficulty, prompting to find models with strong learning ability. (4) standardized. CFDBench facilitates a comprehensive and fair comparison of different deep learning methods for CFD. We make appropriate modifications to popular deep neural networks to apply them to CFDBench and enable the accommodation of more changing inputs. The evaluation on CFDBench reveals some new shortcomings of existing works and we propose possible directions for solving such problems.

Microbiota-based strategies are a novel auxiliary therapeutic and preventative way of moderating chronic kidney disease. Lactobacillus mixture (Lm) was previously demonstrated to exert a renal-protective function in the CKD mice model. The efficacy of probiotics in pet foods is a relatively new area of study, and thus verifying the potential health benefits is necessary. This study evaluated the efficacy of Lm treats in feline CKD and elucidated the mechanisms underlying host-microbe interactions. CKD cats (2 and 3 stages) were administrated probiotic pet treats daily (10 g) for 8 weeks. The results demonstrated that during the eight weeks of Lm administration, creatinine was reduced or maintained in all cats with CKD. Similarly, gut-derived uremic toxins (GDUT), IS, and TMAO were significantly downregulated in the serum (confidence intervals = 90%). The life quality of the cats also improved. Feline gut microbiome data, KEGG pathway, and renal function indicator analyses revealed the possible mechanisms involved in modulating CKD feline microbial composition. Further regulation of the microbial functions in amino acid metabolism after Lm administration contributed to downregulating deleterious IS, PCS, and TMAO. The current study provides potential adjuvant therapeutic insights into probiotic pet foods or treats for pets with CKD.

The multi-modal data fusion method based on IA-net and CHMM technical proposed is designed to solve the problem that the incompleteness of target behavior information in complex family environment leads to the low accuracy of human behavior recognition.The two improved neural networks(STA-ResNet50、STA-GoogleNet)are combined with LSTM to form two IA-Nets respectively to extract RGB and skeleton modal behavior features in video. The two modal feature sequences are input CHMM to construct the probability fusion model of multi-modal behavior recognition.The experimental results show that the human behavior recognition model proposed in this paper has higher accuracy than the previous fusion methods on HMDB51 and UCF101 datasets. New contributions: attention mechanism is introduced to improve the efficiency of video target feature extraction and utilization. A skeleton based feature extraction framework is proposed, which can be used for human behavior recognition in complex environment. In the field of human behavior recognition, probability theory and neural network are cleverly combined and applied, which provides a new method for multi-modal information fusion.

BACKGROUND: Qu-aroma is a critical quality indicator for medium-high temperature Daqu (MT-Daqu), significantly influencing the aroma profile of strong-aroma Baijiu (SAB). SAB is produced across various regions in China, each with unique environmental conditions and production techniques. These regional differences are likely to cause variations in the Qu-aroma of MT-Daqu. Despite this, comprehensive research on the variations in Qu-aroma across different regions has been lacking. This study aims to address this gap by utilizing Gas Chromatography-Olfactometry-Mass Spectrometry (GC-O-MS) and electronic nose (E-nose) technology, combined with sensory evaluation, to analyze the differences in Qu-aroma characteristics and volatile compound profiles of MT-Daqu from seven distinct production areas.RESULTS: Sensory analysis identified seven broad aroma categories and 25 specific aromas characterizing the Qu-aroma of MT-Daqu samples. Chen aroma and roasted aroma were notably more prevalent in MT-Daqu samples from Sichuan compared to those from other regions (P < 0.05), while the fermentation aroma was less prominent in Sichuan samples. In total, 123 volatile compounds were detected in MT-Daqu, with 46 classified as aroma-active compounds. Among these, 21 aroma-active compounds were identified as markers distinguishing Sichuan MT-Daqu from those produced in non-Sichuan regions, showing significant differences in their concentrations (P < 0.05). Additionally, six major aroma-active compounds-ethyl isovalerate, ethyl heptanoate, hexanal, 1-nonanal, (E)-2,4-decadienal, and 2,3-dimethyl-5-ethylpyrazine-were found to significantly contribute to the aroma differences between Sichuan and non-Sichuan MT-Daqu.CONCLUSION: This study delineates the distinct Qu-aroma characteristics of MT-Daqu from various SAB production areas and identifies the aroma-active compounds responsible for these differences. The insights gained from this research offer valuable guidance for optimizing flavor profiles in MT-Daqu production, potentially enhancing the overall quality and regional distinctiveness of the product.

Sinojackia Hu. comprises five to eight Chinese endemic species with high ornamental and medicinal value. However, the generic limits, interspecific relationships and evolutionary history of the genus remain unresolved. In this study, we newly sequenced and assembled three plastomes of S. oblongicarpa and compared them with those of the other congeneric species to explore the taxonomic delimitation of the species and the evolutionary history of the genus. Plastomes structure of Sinojackia species were extremely conserved in terms of number of genes, sequence length and GC content. Codon usage patterns revealed that natural selection may be the main factor shaping codon usage bias. Our phylogenetic tree shows that Sinojackia is monophyletic and can be divided into two clades. Sinojackia oblongicarpa as a distinct species is supported for it is distantly related to S. sarcocarpa. The evolutionary analysis of morphological features indicates that woody mesocarp is an ancestral feature, while mesocarp undeveloped, spongy and fleshy are the later derived. Sinojackia originated in Central-Southeast China during the early Miocene. In this period, it experienced elevated diversification and migrated from the Central-Southeast China to Hunan Province and Sichuan Province with the development of the Asian monsoon and East Asian flora. Sinojackia experienced elevated diversification at intraspecies levels that mainly occurred in the Quaternary. Glacial-interglacial interactions with the monsoon climate may provide favorable expansion conditions for Sinojackia on a small-scale.

This letter presents a dual-frequency terahertz amplitude modulator based on a cross-shaped structure and U-shaped metal patches. Its structural unit is a typical metal-substrate structure. The top metal consists of a cross-shaped structure and U-shaped metal patches, and the bottom substrate layer is made of quartz. Amplitude modulation is achieved by adjusting the temperature of the vanadium dioxide (VO2) patches. The modulation depth can be approximately 75%. The mechanism of the resonance frequency is explained by the equivalent circuit model. The proposed structure shows good amplitude modulation capability at different incidence and azimuth angles by changing the location of the VO2 patches. The dual-frequency terahertz amplitude modulator can be used in terahertz communication, imaging, etc.

Adipose-derived stem cells (ADSCs) were suggested for treating degenerative osteoarthritis, suppressing inflammatory responses, and repairing damaged soft tissues. Moreover, the ADSCs have the potential to undergo self-renewal and differentiate into bone, tendon, cartilage, and ligament. Recently, investigation of the self-renewal and differentiation of the ADSCs becomes an attractive area. In this work, a pneumatic microdevice has been developed to study the gene expression of the ADSCs after the stimulation of multi-axial tensile strain. The ADSCs were cultured on the microdevice and experienced multi-axial tensile strain during a 3-day culture course. Self-renewal and differentiation abilities were investigated by mRNA expressions of NANOG, SOX2, OCT4, SOX9, PPAR-γ, and RUNX2. The result showed that the genes related self-renewal were significantly up-regulated after the tensile stimulation. Higher proliferation ratio of the ADSCs was also shown by cell viability assay. The microdevice provides a promising platform for cell-based study under mechanical tensile stimulation.

This paper examines certain implications from the literature on Tiebout’s model of local gov-ernment service provision, particularly Hamilton’s extension of the model to include local control of land use and property taxation. Our empirical analysis focuses on the use of fiscal zoning to lower property tax rates, a topic that has not been addressed in the extensive Tiebout literature. Using data for over 100 municipalities in the Miami, Florida, metropolitan area, we specify property tax rates as a function of fiscal zoning measures, other municipal characteristics, and tax mimicking. We conclude that single-family zoning is by far the most important variable ex-plaining municipal property tax rates.

Controlling surface-protein interaction during wastewater treatment is the key motivation for developing functionally modified membranes. A new biocatalytic thermo-responsive poly(vinylidene fluoride)(PVDF)/nylon-6,6/poly(N-isopropylacrylamide)(PNIPAAm) ultrafiltration membrane was fabricated to achieve dual functionality of protein-digestion and thermo-responsive self-cleaning. The PVDF/nylon-6,6/PNIPAAm composite membranes were constructed by integrating a hydrophobic PVDF cast layer and hydrophilic nylon-6,6/PNIPAAm nanofiber layer where trypsin enzymes were covalently immobilized. The immobilization density of enzymes on the membrane surface decreased with increasing PNIPAAm concentration, due to the decreased number of amine functional sites. Through a ultrafiltration study using a model solution containing BSA/NaCl/CaCl₂, the PNIPAAm containing biocatalytic membranes demonstrated a combined effect of enzymatic and thermo-switchable self-cleaning. The membrane without PNIPAAm revealed superior fouling resistance and self-cleaning with an R_PD of 22%, compared to membranes with 2 and 4 wt% PNIPAAm with 26% and 33% R_PD, respectively, after an intermediate temperature cleaning at 50°C, indicating that higher enzyme density offers more efficient self-cleaning than the combined effect of enzyme and PNIPAAm at low concentration. The conformational volume phase transition of PNIPAAm did not affect the stability of immobilized trypsin on membrane surface. Such novel surface engineering design offer a promising route to severe surface-protein contamination remediation in food and wastewater applications.

Automatic target detection of remote sensing images (RSI) plays an important role in military reconnaissance, disaster monitoring, and target rescue. The core task of remote sensing target detection is to judge the target categories and complete precise location. However, the existing target detection algorithms have limited accuracy and weak generalization capability for remote sensing images with complex backgrounds. To achieve accurate detection of different categories targets in remote sensing images, this study presents a novel feature enhancement single shot multibox detector (FESSD) algorithm for remote sensing target detection. The FESSD introduces feature enhancement module and attention mechanism into the convolution neural networks (CNN) model, which can effectively enhance the feature extraction ability and nonlinear relationship between different convolution features. Specifically, the feature enhancement module is used to extract the multi-scale feature information, and enhance the model nonlinear learning ability; the self-learning attention mechanism (SAM) is used to expand the convolution kernel local receptive field, which makes the model extract more valuable features. In addition, the nonlinear relationship between different convolution features is enhanced using the feature pyramid attention mechanism (PAM). The advantage of FESSD over other state-of-the-art target detection methods is validated by experiments on the presented seven-class target detection dataset (SD-RSI) and the public DIOR dataset.

The composition, structure and functionalities of prolamins from highland barley was investigated. These parameters of was compared with the widely applied prolamins (zein). There are more charged and hydrophilic amino acids in prolamins from highland barley than zein. The molecu-lar weight of prolamins from highland barley were between 30 to 63 kDa, which was larger than zein (20 to 24 kDa). β-turn helices is the main secondary structure in prolamins from highland barley, while α-helical structure is the main secondary structure in zein. The water holding capacity, thermal stability, emulsifying capacity and stability of prolamins from highland barley is quite lager than zein, while opposite results can be observed for oil absorption capacity. The diameter of fibers prepared with prolamins from highland barley was almost 6 times that of zein, while ribbon structures rather than fibers were formed by prolamins from highland barley. The results would provide the guidance for application of prolamins from highland barley.