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22CrMoH was selected for the gear steel material in this work, and the temperature field change in the scanning electron beam was analyzed to determine the optimal scanning parameters and explored the effect of scanning electron beam pretreatment (Abbreviated as: SEBP) on gas-carburizing (GC) efficiency and organizational properties of gear steel. The results showed that the scanning electron beam caused the material to form a thermally deformed layer 110 μm thick, and it promoted the adsorption of carbon atoms on the surface and their inward diffusion. Under the same gas-carburizing conditions, the carburizing efficiency was improved, and the thickness of the carburized layer increased from 0.78 to 1.09 mm. Furthermore, the hardness of the GC specimens with the SEBP increased from 615 to 638 HV0.05 at 0.1 mm of the sample surface, whereas the hardness of the cross-sectional region decreased gradually, indicating that the scanning electron beam enhanced the adhesion between the carburized layer and matrix zone. A comparative analysis of the microstructures of the GC specimens with and without the SEBP showed that the carbide particles in the surface layer of the samples become smaller and that of volume fraction of residual austenite reduced in size. In terms of the mechanical properties, the surface friction coefficient decreased from 0.87 to 0.46 μ and the GC specimen with the SEBP had a higher cross-sectional hardness gradient. In this way, the amount of wear was reduced from 1.07 to 0.51 mg, which was only 47.7% of the amount of wear of the matrix specimen. [ABSTRACT FROM AUTHOR]

MAPKKs, as one of the main members of the mitogen-activated protein kinase (MAPK) cascade pathway, are located in the middle of the cascade and are involved in many physiological processes of plant growth and development, as well as stress tolerance. Previous studies have found that StMAPKK5 is responsive to drought and salt stress. To further investigate the function and regulatory mechanism of StMAPKK5 in potato stress response, potato variety 'Atlantic' was subjected to drought and NaCl treatments, and the expression of the StMAPKK5 gene was detected by qRT-PCR. StMAPKK5 overexpression and RNA interference-mediated StMAPKK5 knockdown potato plants were constructed. The relative water content, superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) activities, as well as proline (Pro) and malondialdehyde (MDA) contents of plant leaves, were also assayed under drought and NaCl stress. The StMAPKK5 interacting proteins were identified and validated by yeast two-hybrid (Y2H) and bimolecular fluorescence complementation (BiFC). The results showed that the expression of StMAPKK5 was significantly up-regulated under drought and NaCl stress conditions. The StMAPKK5 protein was localized in the nucleus, cytoplasm, and cell membrane. The expression of StMAPKK5 affected the relative water content, the enzymatic activities of SOD, CAT, and POD, and the proline and MDA contents of potatoes under drought and salt stress conditions. These results suggest that StMAPKK5 plays a significant role in regulating drought and salt tolerance in potato crop. Yeast two-hybrid (Y2H) screening identified four interacting proteins: StMYB19, StZFP8, StPUB-like, and StSKIP19. BiFC confirmed the authenticity of the interactions. These findings suggest that StMAPKK5 is crucial for potato growth, development, and response to adversity. [ABSTRACT FROM AUTHOR]

Highlights: What are the main findings? A comprehensive simulation model including particle flow and radiation transfer was developed for a CPC photocatalytic reactor. The ray tracing method was utilized to determine the radiation reaching the surface of the receiving tube, while the discrete ordinates method (DOM) was also employed to solve the radiative transfer equation (RTE), which shows the complete process of solar energy transfer. What is the implication of the main finding? Local volume radiative power absorption (LVRPA) and total radiative power absorption (TRPA) inside the receiving tube was obtained by this study, which is critical data for the photocatalytic reactor. Natural convection with intermittent disturbances is demonstrated to be effective operating mode for the CPC photocatalytic reactor. Compound parabolic concentrator (CPC) photocatalytic reactors are commonly used for photocatalytic water splitting in hydrogen production. This study aimed to gain a better understanding of the physical processes in CPC photocatalytic reactors and provide theoretical support for their design, optimization, and operation. The analysis involved the ray tracing approach, Euler–Euler two-fluid model, and discrete ordinates method (DOM) to study solar radiation transfer and particle flow in the reactor. The distribution of solar radiation on the receiving tube's surface after CPC concentration was obtained by conducting the ray tracing approach. This solar radiation distribution was then coupled into the Euler–Euler two-fluid model to solve for the natural convection flow field, the temperature field, and particle phase volume fraction distribution inside the receiving tube over a period of 120 s. Lastly, the discrete ordinates method (DOM) was used to analyze the transfer of radiation inside the receiving tube at different times, obtaining the distribution of local volume radiative power absorption (LVRPA) and the total radiative power absorption (TRPA) inside the tube. The results showed that the TRPA reached its maximum at 120 s, accounting for 66.61% of the incident solar UV radiation. According to the above results, it could be suggested that adopting an intermittent operation mode in CPC photocatalytic reactors is reasonable and efficient. [ABSTRACT FROM AUTHOR]

Phosphorus (P) stands as a pivotal macroelement in relation to the growth of plants. It plays a significant role in physiological processes, as components of biofilms and nucleotides, and in metabolic activities within plants. The deprivation of phosphorus detrimentally impacts the growth and developmental of plants. However, the rhizosphere's beneficial fungi and bacteria augment the efficacy of phosphorus uptake, participate in the molecular regulation of phosphorus, stimulate physiological alterations in plants, and facilitate signal transmission. In order to give readers a better understanding of the effects and positive roles of soil beneficial fungi and bacteria in regulating plant phosphorus acquisition and transport, this present review introduces the role and influence of rhizosphere microorganisms (fungi and bacteria) in assisting plant phosphorus absorption, and summarizes the key phosphorus transporters found in their interaction with plants. Using mixed microbial populations as composite microbial fertilizers has a positive effect on plants under phosphorus-deficiency conditions. It will be conducive to a better understanding of the mutualistic relationship between fungi, bacteria, and plants to provide a way to reduce the application of phosphorus fertilizers efficiently, and to provide a research background for the development of microbiological fertilizers. [ABSTRACT FROM AUTHOR]

The precision and predictive power of perturbative QCD (pQCD) prediction depends on both a precise, convergent, fixed-order series and a reliable way of estimating the contributions of unknown higher-order (UHO) terms. It has been shown that by applying the principle of maximum conformality (PMC), which applies the renormalization group equation recursively to set the effective magnitude of α s of the process, the remaining conformal coefficients will be well matched with the corresponding α s at each order, leading to a scheme-and-scale invariant and more convergent perturbative series. The PMC series, being satisfied with the standard renormalization group invariance, has a rigorous foundation. Thus it not only can be widely applied to virtually all high-energy hadronic processes, but also can be a reliable platform for estimating UHO contributions. In this paper, by using the total decay width Γ (H → γ γ) which has been calculated up to N4LO QCD corrections, we first derive its PMC series by using the PMC single-scale setting approach and then estimate its unknown N5LO contributions by using a Bayesian analysis. The newly suggested Bayesian-based approach estimates the magnitude of the UHO contributions based on an optimized analysis of the probability density distribution, and the predicted UHO contribution becomes more accurate when more loop terms have been known to tame the probability density function. Using the top-quark pole mass M t = 172.69 GeV and the Higgs mass M H = 125.25 GeV as inputs, we obtain Γ (H → γ γ) = 9.56504 keV , and the estimated N5LO contribution to the total decay width is Δ Γ H = ± 1.65 × 10 − 4 keV for the smallest credible interval of 95.5 % degree of belief. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic caused by the virus SARS-CoV-2 was the greatest global threat to human health in the last three years. The most widely used methodologies for the diagnosis of COVID-19 are quantitative reverse transcription polymerase chain reaction (RT-qPCR) and rapid antigen tests (RATs). PCR is time-consuming and requires specialized instrumentation operated by skilled personnel. In contrast, RATs can be used in-home or at point-of-care but are less sensitive, leading to a higher rate of false negative results. In this work, we describe the development of a disposable, electrochemical, and laser-scribed graphene-based biosensor strips for COVID-19 detection that exploits a split-ester bond ligase system (termed 'EsterLigase') for immobilization of a virus-specific nanobody to maintain the out-of-plane orientation of the probe to ensure the efficacy of the probe-target recognition process. An anti-spike VHH E nanobody, genetically fused with the EsterLigase domain, was used as the specific probe for the spike receptor-binding domain (SP-RBD) protein as the target. The recognition between the two was measured by the change in the charge transfer resistance determined by fitting the electrochemical impedance spectroscopy (EIS) spectra. The developed LSG-based biosensor achieved a linear detection range for the SP-RBD from 150 pM to 15 nM with a sensitivity of 0.0866 [log(M)]−1 and a limit of detection (LOD) of 7.68 pM. [ABSTRACT FROM AUTHOR]

This study aims to address the problem of poor synchronous accuracy when facing a time-varying load in conventional load-sensitive synchronous drive systems. The new electro-hydraulic load-sensitive (EHLS) diverter synchronous drive system was proposed by combining the diverter valve and the EHLS synchronous drive system. The variable pressure margin compensation control was proposed to further improve the system's synchronous control performance. Based on the system control strategy and component mathematical model, the simulation models of the EHLS, EHLS synchronous, and EHLS diverter synchronous drive systems were established using AMESim, respectively, and the synchronous control performance of the systems was obtained. The simulation results show that the EHLS drive system realized the primary functions of the load-sensitive system and could realize the variable load-sensitive pressure margin control. The EHLS synchronous drive system had poor synchronous control accuracy, but variable pressure compensation valve pressure margin control could be realized. The EHLS diverter synchronous drive system effectively improved the system's synchronous control performance and diverter synchronous accuracy by variable pressure margin compensation control. The diverter system diverter error was reduced by 40.8%, and the diverter system after the compensation diverter error was reduced by 52.6% when the multi-way valves were fully opening. The system provides the solution for high-performance hydraulic synchronous drives under severe operating conditions. [ABSTRACT FROM AUTHOR]

Oil crops are the second most cultivated economic crop in the world after food crops, and they are an important source of both edible and industrial oil. The growth of oil crops is limited by biotic and abiotic stresses, which hinder their yield and quality. Among all the agronomic measures, plant growth promoting bacteria (PGPB) play a crucial role in improving the yield, quality, and adaptability of oil crops. In this review, we considered the recent research on the sources of beneficial bacteria and their interactions with and influences on host plants, with a focus on summarizing the important roles and molecular mechanisms of PGPB in promoting growth and resisting biotic and abiotic stresses in oil crops. Finally, we outlined the current opportunities and challenges of microbial strategies for the improvement of the yield, quality, and adaptability of oil crops, providing a theoretical basis for the future use of microbial inoculants in these crops. [ABSTRACT FROM AUTHOR]

Hemorrhagic transformation (HT) is one of the common complications in patients with acute ischemic stroke (AIS). This study aims to investigate the value of different thresholds of Tmax generated from perfusion-weighted MR imaging (PWI) and the apparent diffusion coefficient (ADC) value in the prediction of HT in AIS. A total of 156 AIS patients were enrolled in this study, with 55 patients in the HT group and 101 patients in non-HT group. The clinical baseline data and multi-parametric MRI findings were compared between HT and non-HT groups to identify indicators related to HT. The optimal parameters for predicting HT and the corresponding cutoff values were obtained using the receiver operating characteristic curve analysis of the volumes of ADC < 620 × 10−6 mm2/s and Tmax > 6 s, 8 s, and 10 s. The results showed that the volumes of ADC < 620 × 10−6 mm2/s and Tmax > 6 s, 8 s, and 10 s in the HT group were all significantly larger than that in the non-HT group and were all independent risk factors for HT. Early measurement of the volume of Tmax > 10 s had the highest value, with a cutoff lesion volume of 10.5 mL. [ABSTRACT FROM AUTHOR]

The discrimination of river blockages is very important for the risk assessment of landslide disasters and secondary hazards. Experimental studies and statistical analyses were carried out to explore the formation process and discriminant criteria of river blockages caused by landslides. An adjustable slide chute was designed and built to conduct forty-five landslide experiments. According to the experimental results, river blockage was identified as having six types based on the differences between the water depth and the height of the landslide dam, and the degree of river blockage increased from 70% to 100% as the chute angle, particle size, and landslide volume increased. It is also found that landslide volume controls the landslide dam height and degree of blockage, and particle size and slide angle control both the landslide velocity as it enters the river and the cross-section shape of the landslide dam. To investigate more influence factors, a statistical investigation of 60 real landslide cases was carried out, and it revealed that some geometric attributes related to landslide volume have the highest correlation with river blockage, especially landslide thickness. Finally, an improved probability model was proposed to assess the possibility of complete blockage, and it has overall accuracies of 91.1% and 83.3% when applied to predict experimental landslide cases and real landslide cases, respectively. [ABSTRACT FROM AUTHOR]

Higher standards for reliability and efficiency apply to the connection between vehicle terminals and infrastructure by the fifth-generation mobile communication technology (5G). A vehicle-to-infrastructure system uses a communication system called NR-V2I (New Radio-Vehicle to Infrastructure), which uses Link Adaptation (LA) technology to communicate in constantly changing V2I to increase the efficacy and reliability of V2I information transmission. This paper proposes a Double Deep Q-learning (DDQL) LA scheduling algorithm for optimizing the modulation and coding scheme (MCS) of autonomous driving vehicles in V2I communication. The problem with the Doppler shift and complex fast time-varying channels reducing the reliability of information transmission in V2I scenarios is that they make it less likely that the information will be transmitted accurately. Schedules for autonomous vehicles using Space Division Multiplexing (SDM) and MCS are used in V2I communications. To address the issue of Deep Q-learning (DQL) overestimation in the Q-Network learning process, the approach integrates Deep Neural Network (DNN) and Double Q-Network (DDQN). The findings of this study demonstrate that the suggested algorithm can adapt to complex channel environments with varying vehicle speeds in V2I scenarios and by choosing the best scheduling scheme for V2I road information transmission using a combination of MCS. SDM not only increases the accuracy of the transmission of road safety information but also helps to foster cooperation and communication between vehicle terminals to realize cooperative driving. [ABSTRACT FROM AUTHOR]

Co-doped ZnO thin films have attracted much attention in the field of transparent conductive oxides (TCOs) in solar cells, displays, and other transparent electronics. Unlike conventional single-doped ZnO, co-doped ZnO utilizes two different dopant elements, offering enhanced electrical properties and more controllable optical properties, including transmittance and haze; however, most previous studies focused on the electrical properties, with less attention paid to obtaining high haze using co-doping. Here, we prepare high-haze Ga- and Zr-co-doped ZnO (GZO:Zr or ZGZO) using atmospheric pressure plasma jet (APPJ) systems. We conduct a detailed analysis to examine the interplay between Zr concentrations and film properties. UV-Vis spectroscopy shows a remarkable haze factor increase of 7.19% to 34.8% (+384%) for the films prepared with 2 at% Zr and 8 at% Ga precursor concentrations. EDS analysis reveals Zr accumulation on larger and smaller particles, while SIMS links particle abundance to impurity uptake and altered electrical properties. XPS identifies Zr mainly as ZrO2 because of lattice stress from Zr doping, forming clusters at lattice boundaries and corroborating the SEM findings. Our work presents a new way to fabricate Ga- and Zr-co-doped ZnO for applications that require low electrical resistivity, high visible transparency, and high haze. [ABSTRACT FROM AUTHOR]

Crush syndrome (CS), also known as traumatic rhabdomyolysis, is a syndrome with a wide clinical spectrum; it is caused by external compression, which often occurs in earthquakes, wars, and traffic accidents, especially in large-scale disasters. Crush syndrome is the second leading cause of death after direct trauma in earthquakes. A series of clinical complications caused by crush syndrome, including hyperkalemia, myoglobinuria, and, in particular, acute kidney injury (AKI), is the main cause of death in crush syndrome. The early diagnosis of crush syndrome, the correct evaluation of its severity, and accurate predictions of a poor prognosis can provide personalized suggestions for rescuers to carry out early treatments and reduce mortality. This review summarizes various methods for the diagnostic and predictive evaluation of crush syndrome, including urine dipstick tests for a large number of victims, traditional and emerging biomarkers, imaging-assisted diagnostic methods, and developed evaluation models, with the aim of providing materials for scholars in this research field. [ABSTRACT FROM AUTHOR]

Climate change and anthropogenic activities have had a profound effect on the variation in grassland productivity in the Tibetan Plateau in recent decades. Quantifying the impacts of climatic and anthropogenic variables on grassland productivity is a necessary step in making the management policies of a sustainable grassland ecosystem. Net primary productivity (NPP) is an important part of the terrestrial carbon cycle and can be used to assess vegetation growth. Based on the Carnegie–Ames–Stanford Approach model and statistical analysis method, in this study we estimated the variations in grassland potential NPP (PNPP), actual NPP (ANPP) and human-induced NPP (HNPP) in the Northwest Sichuan Plateau (NWSP) of the Southeast Tibetan Plateau from 2001 to 2020. Also, we assessed the contribution of climatic change and anthropogenic activities to grassland ANPP. The results showed that the average values of grassland ANPP, PNPP and HNPP in the whole NWSP increased at the rates of 3.81, 9.14 and 7.18 g C m−2 a−1, respectively. Grassland ANPP increased in 91.7% of the total area. Climate-oriented impacts led grassland ANPP to increase in 82.6% of the area, and temperature increase was the dominant factor. Additionally, anthropogenic activity was the major reason for the grassland ANPP's decline (5.4% of the total area). Overall, our findings are beneficial for the formulation of practical countermeasures regarding climate change adaption and damaged grassland recovering in the plateau. [ABSTRACT FROM AUTHOR]

Fipronil, a broad-spectrum insecticide, is widely used in agriculture and veterinary practices. Fipronil-induced neurotoxicity and potential adverse effects on humans and aquatic organisms have raised health concerns. Monitoring programs have been implemented globally to assess fipronil residues in food, including fruits, vegetables, and animal products. However, previous exposure assessments have often focused on specific food categories or subsets of items, resulting in limited insights into the overall health risks. Additionally, the large number of non-detect fipronil residues in food has introduced uncertainties in exposure assessment. To address these issues, a probabilistic exposure assessment and dose-response analysis were adopted in this study, considering the sample distribution below the detection limit to better characterize uncertainties and population variability in health risk assessments. The estimated fipronil exposure to the general public ranges from 6.38 × 10−6 ± 0.00017 mg/kg/day to 9.83 × 10−6 ± 0.00034 mg/kg/day. Only one out of 200,000 simulated individuals had a fipronil dose exceeding the probabilistic reference dose (0.048 mg/kg/day, pRfD), which aims to protect 99% of the population with effects less than 10% extra risk. By incorporating uncertainties in exposure and dose-response data, a more comprehensive understanding of the health risks associated with fipronil exposure in the Taiwanese population has been achieved. [ABSTRACT FROM AUTHOR]

The environmental regulatory mechanism underlying the coupling of leaf photosynthesis and transpiration in Artemisia ordosica, a typical desert shrub in China, remains unclear. To understand this mechanism, we measured the net leaf photosynthetic rate (Pn), transpiration rate (E), and stomatal conductance (gs) from May to October 2019 using a portable photosynthesis analyser. Photosynthetically active radiation, air temperature, relative humidity, and soil water content were simultaneously measured. Both E and Pn are positively correlated with gs. Pn and E exhibited a nonlinear quadratic correlation from May to July and a linear correlation in August and September. The changes in the maximum photosynthetic (Pn−max) and carboxylation rates were mainly affected by air temperature and light. Seasonally, Pn−max initially exhibited an increasing trend, peaking in June and then decreasing. Under low temperature and light conditions, Pn−E was linearly correlated and the coupling relationship was stable. Under higher temperatures and radiation, Pn−E exhibited a nonlinear quadratic correlation, and decoupling occurred with increasing temperature and light intensity. The results of this study provide a better understanding of the responses of desert shrub ecosystems to climate change. [ABSTRACT FROM AUTHOR]

To investigate the potential of H2-calponin (CNN2) as a serum biomarker for hepatocellular carcinoma (HCC), this study employed the serological analysis of recombinantly expressed cDNA clone (SEREX) technique to identify the presence of CNN2 antibody in the serum of patients with HCC and other tumors. The CNN2 protein was produced through genetic engineering and used as an antigen to determine the positive rate of serum CNN2 autoantibodies via indirect enzyme-linked immunosorbent assay (ELISA). In addition, the mRNA and protein expressions of CNN2 in cells and tissues were evaluated using RT-PCR, in situ RT-PCR, and immunohistochemistry methods. The HCC group exhibited a significantly higher positive rate of anti-CNN2 antibody (54.8%) compared to gastric cancer (6.5%), lung cancer (3.2%), rectal cancer (9.7%), hepatitis (3.2%), liver cirrhosis (3.2%), and normal tissues (3.1%). The positive rates of CNN2 mRNA in HCC with metastasis, non-metastatic HCC, lung cancer, gastric cancer, nasopharyngeal cancer, liver cirrhosis, and hepatitis were 56.67%, 41.67%, 17.5%, 10.0%, 20.0%, 53.13%, and 41.67%, respectively. Meanwhile, the positive rates of CNN2 protein were 63.33%, 37.5%, 17.5%, 27.5%, 45%, 31.25%, and 20.83%, respectively. The down-regulation of CNN2 could inhibit the migration and invasion of liver cancer cells. CNN2 is a newly identified HCC-associated antigen that is implicated in the migration and invasion of liver cancer cells, making it a promising target for liver cancer therapy. [ABSTRACT FROM AUTHOR]

Wolfberry (Lycium barbarum) is a traditional cash crop in China and is well-known worldwide for its outstanding nutritional and medicinal value. Lycium ruthenicum is a close relative of Lycium barbarum but differs significantly in size, color, flavor and nutritional composition. To date, the metabolic differences between the fruits of the two wolfberry varieties and the genetic basis behind them are unclear. Here, we compared metabolome and transcriptome data of two kinds of wolfberry fruits at five stages of development. Metabolome results show that amino acids, vitamins and flavonoids had the same accumulation pattern in various developmental stages of fruit but that Lycium ruthenicum accumulated more metabolites than Lycium barbarum during the same developmental stage, including L-glutamate, L-proline, L-serine, abscisic acid (ABA), sucrose, thiamine, naringenin and quercetin. Based on the metabolite and gene networks, many key genes that may be involved in the flavonoid synthesis pathway in wolfberry were identified, including PAL, C4H, 4CL, CHS, CHI, F3H, F3'H and FLS. The expression of these genes was significantly higher in Lycium ruthenicum than in Lycium barbarum, indicating that the difference in the expression of these genes was the main reason for the variation in flavonoid accumulation between Lycium barbarum and Lycium ruthenicum. Taken together, our results reveal the genetic basis of the difference in metabolomics between Lycium barbarum and Lycium ruthenicum and provide new insights into the flavonoid synthesis of wolfberry. [ABSTRACT FROM AUTHOR]

The nature of renewable energy resources (RERs), such as wind energy, makes them highly unstable, unpredictable, and intermittent. As a result, they must be optimized to reduce costs and emissions, increase reliability, and also to find the optimal size and location for RERs and energy storage systems (ESSs). Microgrids (MG) can be modified using ESSs to gradually reduce traditional energy use. In order to integrate RERs in a financially viable scheme, ESSs should be sized and operated optimally. The paper presents an enhanced biogeography-driven optimization algorithm for optimizing the operations and sizes of battery ESSs (BESSs) taking into account MGs that experience wind energy penetration in a way that migration rates are adaptively adjusted based on habitat suitability indexes and differential perturbations added to migration operators. An optimization problem was applied to a BESS to determine its depth of discharge and lifespan. This paper considers three different scenarios in using simulations and compares them to existing optimization methods for the purpose of demonstrating the effectiveness of the offered scheme. Out of all the case studies examined, the optimized BESS-linked case study was the least expensive. We also show that a BESS must be of an optimum size to function both economically and healthily. For economic and efficient functioning of MGs, it has been shown that finding the optimum size of the ESS is important and potentially extends battery lifespan. The IBBOA obtained a more precise size for BESS's volume, and the final outcomes are compared in this paper with other methods. [ABSTRACT FROM AUTHOR]

Due to the large wall thickness difference and serious instability in the large-scale ring rolling process, most studies on the feed curve are not suitable for a large-scale ring. The production cost of the large-scale ring is high, and if plastic instability occurs, it will cause a great waste of resources. Therefore, in this study, a staged feed strategy based on the evolution of ring instability is proposed with the objective of controlling the rolling stability of a large-scale ring. Firstly, based on the law of rolling instability evolution, the rolling stage during the rolling process is divided. Secondly, the coordination of all rolling stages is proposed as a factor to design the feed curve. The feed scheme is determined using the central composite design (CCD) method, and then the established mathematical model is applied to obtain the radial feed curves of a large-scale flat ring with a 5 m diameter for different schemes. Next, the designed feed curve was submitted to finite element method (FEM) simulation. According to the FE simulation results, a rolling map for controlling roundness error, eccentricity and vibration is established. Finally, the feed curve in the stable region is input to the FE simulation and the production trial to obtain the results of roundness error, eccentricity and vibration. A comparison of the simulation and production trial results shows that they are in good agreement, which proves the reliability of the feed curve designed based on the stable rolling region in the roll map. Moreover, the machining amount for both the simulation and production trial is below the maximum machined value. [ABSTRACT FROM AUTHOR]

Previous observational studies on the relationship between sleep characteristics and fracture have yielded contradictory results. The goal of this study was to replicate the findings in a large longitudinal cohort and then conduct a Mendelian randomization (MR) analysis to infer the causality between sleep behaviors and fracture risk. Based on data from the China Health and Retirement Longitudinal Study (CHARLS) including 17,708 participants, we found that individuals with short sleep duration (<5 h) (OR [odds ratio] = 1.62, 95% CI: 1.07–2.44) or restless sleep (OR = 1.55, 95% CI: 1.10–2.19) have a higher risk of hip fracture. A U-shaped relationship between nighttime sleep duration and hip fracture risk (p-nonlinear = 0.01) was observed using restricted cubic spline regression analysis. Through joint effect analysis, we found that participants with short sleep duration (<5 h) combined with midday napping could significantly decrease hip fracture incidence. We further inferred the causal relationship between self-reported sleep behaviors and hip fracture using the MR approach. Among four sleep phenotypic parameters (sleep duration, daytime napping, chronotype, and insomnia), we found a modest causal relationship between sleep duration and fracture (OR = 0.69, 95% CI: 0.48 to 0.99, p = 0.04). However, no causal relationship was observed for other sleep traits. In conclusion, our findings suggest that short sleep duration has a potential detrimental effect on hip fracture. Improving sleep patterns is of significance for developing hip fracture preventive strategies in the middle-aged and the elderly populations. [ABSTRACT FROM AUTHOR]

Multi-terminal artificial synaptic devices are promising for building neural morphological networks and manufacturing neural chips. In this study, planar multi-gate InOx-based artificial synaptic transistor was demonstrated by using solution-processed AlOx as an electric double layer (EDL) dielectric with mobile hydrogen protons. The excitatory postsynaptic current (EPSC) was successfully controlled by adjusting amplitude, duration, and interval of the stimulating voltage pulses applied on the planar gates. The EPSC stimulated by multiple inputs shows the property of sublinear summation. As spatial resolution function of the artificial synaptic transistor, the EPSC depends on the presynaptic (planar gate) area and distance to the channel, nonlinearly. The paired-pulse facilitation (PPF), depending on time sequence, demonstrates the temporal resolution function of the multi-gate artificial synaptic transistor. The study shows the potential of planar multi-gate AlOx/InOx EDL transistor as multi-terminal artificial synaptic device. [ABSTRACT FROM AUTHOR]

Based on the data obtained on carbon emissions in Guangdong Province, China, from 1997 to 2019, this study focused on the relationship between energy consumption and population development in Guangdong Province. This study quantitatively analyzed the impact of different population structures and technological progress on carbon emissions in Guangdong Province by establishing an extended model of Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT). The results showed that the population size factor was not as good as the population structure factor for carbon emissions. In addition, different demographic factors affected carbon emissions differently with both positive and negative effects. Finally, relevant policy suggestions were proposed from the perspectives of encouraging the childbearing of appropriate-age residents, optimizing the population structure, reducing the separation of people and households, guiding residents to return to the traditional family model, guiding residents to live a low-carbon life, optimizing industrial institutions, and adjusting the energy consumption structure. [ABSTRACT FROM AUTHOR]

Background: Corneal edema (CE) affects the outcome of phacoemulsification. Effective ways to predict the CE after phacoemulsification are needed. Methods: On the basis of data from patients conforming to the protocol of the AGSPC trial, 17 variables were selected to predict CE after phacoemulsification by constructing a CE nomogram through multivariate logistic regression, which was improved via variable selection with copula entropy. The prediction models were evaluated using predictive accuracy, the area under the receiver operating characteristic curve (AUC), and decision curve analysis (DCA). Results: Data from 178 patients were used to construct prediction models. After copula entropy variable selection, which shifted the variables used for prediction in the CE nomogram from diabetes, best corrected visual acuity (BCVA), lens thickness and cumulative dissipated energy (CDE) to CDE and BCVA in the Copula nomogram, there was no significant change in predictive accuracy (0.9039 vs. 0.9098). There was also no significant difference in AUCs between the CE nomogram and the Copula nomogram (0.9637, 95% CI 0.9329–0.9946 vs. 0.9512, 95% CI 0.9075–0.9949; p = 0.2221). DCA suggested that the Copula nomogram has clinical application. Conclusions: This study obtained a nomogram with good performance to predict CE after phacoemulsification, and showed the improvement of copula entropy for nomogram models. [ABSTRACT FROM AUTHOR]

Considering the complex flow state of the duct flow field in the exhaust system, the structural parameters can significantly impact the internal flow field and noise. This paper takes the noise generated by the duct system under operating conditions as the research object, studies the mechanism of duct noise generation through theoretical analysis, numerical simulation and experimental test, and proposes an optimization design method, that is, to improve the duct structure by adding duct guide vanes. In order to maximize the optimization effect of the guide vane, a multiobjective optimization design of its profile is required, including the parametric expression of the guide vane profile, establishing the design variables and optimization objectives, and establishing the Kriging approximation model. The IMOCS algorithm is used to accurately and efficiently calculate the Pareto front solution to obtain the optimal profile of the duct guide vane and finally improve the noise-reduction performance of the duct system. This paper applies this design method to an integrated stove head duct to verify its accuracy, and prototype tests are conducted according to the optimization results. The test results show that the optimized integrated cooker has improved the outlet flow rate of the whole machine by 1.2 m3/min and reduced the noise by 2.3 dB. [ABSTRACT FROM AUTHOR]

The fluidics system is an indispensable and primary component of phacoemulsification. Both the gravity-fluidics system and active-fluidics system are commonly used in practice. The irrigation pressure of the gravity-fluidics system is determined by the bottle height, which is relatively constant, while the active-fluidics system is paired with a cassette that contains pressure sensors to monitor intraocular pressure changes. The active-fluidics system allows surgeons to preset a target intraocular pressure value, and it replenishes the fluids proactively; thus, the intraocular pressure is consistently maintained near the target value. Under such circumstances, stable intraocular pressure and anterior chamber volume values could be acquired. Research on surgical safety, efficiency and results have reported several strengths of the active-fluidics system. It is also advantageous in some complicated cataract surgeries. However, the system is not widely used at present, mainly due to its low penetration rate and high equipment cost. Some of its updates such as the new Active Sentry handpiece showed potential superiority in laboratory studies recently, but there is still further research to be conducted. This article gives an overview of the mechanism and performance of the active-fluidics system, and it is expected to provide clues for future research. [ABSTRACT FROM AUTHOR]

The failure of insulators may seriously threaten the safe operation of the power system, where the state detection of high-voltage insulators is a must for the normal and safe operation of the power system. Based on the data of insulators in aerial images, this work explored an enhanced particle swarm algorithm to optimize the parameters of the support vector machine. A support vector machine model was therefore established for the identification of the normal and defective states of the insulators. This methodology works with the structure minimization principle of SVM and the characteristics of particle swarm fast optimization. First, the aerial insulator image was segmented as a target by way of the seed region growth based on double-layer cascade morphological improvements, and then, HOG features plus GLCM features were extracted as sample data. Finally, an ameliorated PSO-SVM classifier was designed to realize insulator state identification. Comparisons were made between PSO-SVM and conventional machine learning algorithms, SVM and Random Forest, and an optimization algorithm, Gray Wolf Optimization Support Vector Machine (GWO-SVM), and advanced neural network CNN. The experimental results showed that the performance of the algorithm proposed in this paper touched the top level, where the recognition accuracy rate was 92.11%, the precision rate 90%, the recall rate 94.74%, and the F1-score 92.31%. [ABSTRACT FROM AUTHOR]

The conventional electric loader uses a motor instead of an engine, which aligns with the current energy-saving and emission-reduction trend. However, the motor's speed control performance and overload capacity are under-utilized, and the actuator suffers from the potential energy waste problem of the boom arm. This study proposes a variable pressure margin energy recovery system for the electric loader actuator. It uses a combination of a permanent magnet synchronous motor (PMSM) and a quantitative pump. It can achieve variable pressure margin control and energy recovery through the pressure feedback closed-loop control. AMESim is used to build the simulation model based on the system control strategy, actuator, supercapacitor, and PMSM mathematical mode. Under typical working conditions, the simulation study is conducted on a 50-type wheel loader to obtain cylinder displacement, system energy recovery, and energy-saving performance. The simulation results show that the system is feasible and can effectively reduce energy consumption. Its energy recovery efficiency is 65.4%. The PMSM energy supply is reduced by 28.6% with the variable pressure margin control. It has high energy-saving performance, and the energy-saving efficiency is 38.5%. It provides a reference for research on energy-saving systems for electric construction machinery. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop and validate a near-infrared (NIR) spectroscopy based method for in-line quantification during the second alcohol precipitation process of Astragali radix. In total, 22 calibration experiments were carefully arranged using a Box–Behnken design. Variations in the raw materials, critical process parameters, and environmental temperature were all included in the experimental design. Two independent validation sets were built for method evaluation. Validation set 1 was used for optimization. Different spectral pretreatments were compared using a "trial-and-error" approach. To reduce the calculation times, the full-factorial design was applied to determine the potential optimal combinations. Then, the best parameters for the pretreatment algorithms were compared and selected. Partial least squares (PLS) regression models were obtained with low complexity and good predictive performance. Validation set 2 was used for a thorough validation of the NIR spectroscopy method. Based on the same validation set, traditional chemometric validation and validation using accuracy profiles were conducted and compared. Conventional chemometric parameters were used to obtain the overall predictive capability of the established models; however, these parameters were insufficient for pharmaceutical regulatory requirements. Then, the method was fully validated according to the ICH Q2(R1) guideline and using the accuracy profile approach, which enabled visual and reliable representation of the future performances of the analytical method. The developed method was able to determine content ranges of 8.44–39.8% at 0.541–2.26 mg/mL, 0.118–0.502 mg/mL, 0.220–0.940 mg/mL, 0.106–0.167 mg/mL, 0.484–0.879 mg/mL, and 0.137–0.320 mg/mL for total solid, calycosin glucoside, formononetin glucoside, 9, 10-dimethoxypterocarpan glucopyranoside, 2′-dihydroxy -3′, 4′-dimethoxyisoflavan glucopyranoside, astragloside II, and astragloside IV, respectively. These ranges were specific to the early and middle stages of the second alcohol precipitation process. The method was confirmed to be capable of achieving an in-line prediction with a very acceptable accuracy. The present study demonstrates that accuracy profiles offer a potential approach for the standardization of NIR spectroscopy method validation for traditional Chinese medicines (TCMs). [ABSTRACT FROM AUTHOR]

Aiming at the common problems, such as noise pollution, low contrast, and color distortion in underwater images, and the characteristics of holothurian recognition, such as morphological ambiguity, high similarity with the background, and coexistence of special ecological scenes, this paper proposes an underwater holothurian target-detection algorithm (FA-CenterNet), based on improved CenterNet and scene feature fusion. First, to reduce the model's occupancy of embedded device resources, we use EfficientNet-B3 as the backbone network to reduce the model's Params and FLOPs. At the same time, EfficientNet-B3 increases the depth and width of the model, which improves the accuracy of the model. Then, we design an effective FPT (feature pyramid transformer) combination module to fully focus and mine the information on holothurian ecological scenarios of different scales and spaces (e.g., holothurian spines, reefs, and waterweeds are often present in the same scenario as holothurians). The co-existing scene information can be used as auxiliary features to detect holothurians, which can improve the detection ability of fuzzy and small-sized holothurians. Finally, we add the AFF module to realize the deep fusion of the shallow-detail and high-level semantic features of holothurians. The results show that the method presented in this paper yields better results on the 2020 CURPC underwater target-detection image dataset with an AP50 of 83.43%, Params of 15.90 M, and FLOPs of 25.12 G compared to other methods. In the underwater holothurian-detection task, this method improves the accuracy of detecting holothurians with fuzzy features, a small size, and dense scene. It also achieves a good balance between detection accuracy, Params, and FLOPs, and is suitable for underwater holothurian detection in most situations. [ABSTRACT FROM AUTHOR]

Background: The ability to accurately detect ischemic stroke and predict its neurological recovery is of great clinical value. This study intended to evaluate the performance of whole-brain dynamic radiomics features (DRF) for ischemic stroke detection, neurological impairment assessment, and outcome prediction. Methods: The supervised feature selection (Lasso) and unsupervised feature-selection methods (five-feature dimension-reduction algorithms) were used to generate four experimental groups with DRF in different combinations. Ten machine learning models were used to evaluate their performance by ten-fold cross-validation. Results: In experimental group_A, the best AUCs (0.873 for stroke detection, 0.795 for NIHSS assessment, and 0.818 for outcome prediction) were obtained by outstanding DRF selected by Lasso, and the performance of significant DRF was better than the five-feature dimension-reduction algorithms. The selected outstanding dimension-reduction DRF in experimental group_C obtained a better AUC than dimension-reduction DRF in experimental group_A but were inferior to the outstanding DRF in experimental group_A. When combining the outstanding DRF with each dimension-reduction DRF (experimental group_B), the performance can be improved in ischemic stroke detection (best AUC = 0.899) and NIHSS assessment (best AUC = 0.835) but failed in outcome prediction (best AUC = 0.806). The performance can be further improved when combining outstanding DRF with outstanding dimension-reduction DRF (experimental group_D), achieving the highest AUC scores in all three evaluation items (0.925 for stroke detection, 0.853 for NIHSS assessment, and 0.828 for outcome prediction). By the method in this study, comparing the best AUC of Ft-test in experimental group_A and the best_AUC in experimental group_D, the AUC in stroke detection increased by 19.4% (from 0.731 to 0.925), the AUC in NIHSS assessment increased by 20.1% (from 0.652 to 0.853), and the AUC in prognosis prediction increased by 14.9% (from 0.679 to 0.828). This study provided a potential clinical tool for detailed clinical diagnosis and outcome prediction before treatment. [ABSTRACT FROM AUTHOR]

The conventional loader actuator hydraulic system suffers from the potential energy waste problem of the boom arm. This study proposes a hydraulic control method and control strategy for the energy recovery and regeneration of a hybrid loader arm. When the boom arm drops, the piston side of the boom cylinder charges the accumulator, and the system achieves energy recovery. When the boom arm rises, the accumulator releases hydraulic energy to drive the energy regeneration hydraulic motor to provide energy for the system, and the system achieves energy regeneration. The system's principle analysis and the mathematical model are completed based on Boyle's, Newton's second law, and the flow continuity principle. The simulation model is established using AMESim 2D mechanical library, HCD library, and signal library. Under the typical working condition, 50-type wheel loader numerical simulation research is conducted, and the system cylinder motion characteristics, accumulator charging and discharging performance, system energy recovery, and regeneration performance are obtained. On this basis, energy recovery and regeneration efficiency are selected as optimization objectives. The optimal designs of accumulator and energy regeneration hydraulic motor parameters are carried out to obtain the influence law of accumulator and hydraulic motor parameters on system energy recovery and regeneration, and the energy-saving effect of the system is analyzed. The results show that the optimized parameters effectively improve the system energy recovery and regeneration efficiency and reduce engine fuel consumption. The system provides a reference for designing an energy recovery system and researching the energy-saving technology of loaders. [ABSTRACT FROM AUTHOR]

To automatically and quantitatively evaluate the venous oxygen saturation (SvO2) in cerebral ischemic tissues and explore its value in predicting prognosis. A retrospective study was conducted on 48 AIS patients hospitalized in our hospital from 2015–2018. Based on quantitative susceptibility mapping and perfusion-weighted imaging, this paper measured the cerebral SvO2 in hypoperfusion tissues and its change after intraarterial rt-PA treatment. The cerebral SvO2 in different hypoperfusion regions between the favorable and unfavorable clinical outcome groups was analyzed using an independent t-test. Relationships between cerebral SvO2 and clinical scores were determined using the Pearson correlation coefficient. The receiver operating characteristic process was conducted to evaluate the accuracy of cerebral SvO2 in predicting unfavorable clinical outcomes. Cerebral SvO2 in hypoperfusion (Tmax > 4 and 6 s) was significantly different between the two groups at follow-up (p < 0.05). Cerebral SvO2 and its changes before and after treatment were negatively correlated with clinical scores. The positive predictive value, negative predictive value, accuracy, and area under the curve of the cerebral SvO2 were higher than those predicted by the ischemic core. Therefore, the cerebral SvO2 of hypoperfusion regions was a stronger imaging predictor of unfavorable clinical outcomes after stroke. [ABSTRACT FROM AUTHOR]

This study investigated the quantitative distribution of cerebral venous oxygen saturation (SvO2) based on quantitative sensitivity mapping (QSM) and determined its prognostic value in patients with acute ischemic stroke (AIS). A retrospective study was conducted on 39 hospitalized patients. Reconstructed QSM was used to calculate the cerebral SvO2 of each region of interest (ROI) in the ischemic hemisphere. The intraclass correlation coefficient (ICC) and Bland–Altman analysis were conducted to define the best resolution of the distribution map. The correlation between the cerebral SvO2 in hypoxic regions (SvO2ROI < 0.7) and clinical scores was obtained by Spearman and power analysis. The associations between cerebral SvO2 and unfavorable prognosis were analyzed using multivariate logistic regression. Excellent agreement was found between the cerebral SvO2 in hypoxic regions with a resolution of 7.18 × 7.18 × 1.6 mm3 and asymmetrically prominent cortical veins regions (ICC: 0.879 (admission), ICC: 0.906 (discharge)). The cerebral SvO2 was significantly negative with clinical scores (all |r| > 0.3). The cerebral SvO2 and its changes at discharge were significantly associated with an unfavorable prognosis (OR: 0.812 and 0.866). Therefore, the cerebral SvO2 in hypoxic regions measured by the quantitative distribution map can be used as an indicator for evaluating the early prognosis of AIS. [ABSTRACT FROM AUTHOR]

G-quadruplexes (G4s) have been long considered rare and physiologically unimportant in vitro curiosities, but recent methodological advances have proved their presence and functions in vivo. Moreover, in addition to their functional relevance in bacteria and animals, including humans, their importance has been recently demonstrated in evolutionarily distinct plant species. In this study, we analyzed the genome of Pisum sativum (garden pea, or the so-called green pea), a unique member of the Fabaceae family. Our results showed that this genome contained putative G4 sequences (PQSs). Interestingly, these PQSs were located nonrandomly in the nuclear genome. We also found PQSs in mitochondrial (mt) and chloroplast (cp) DNA, and we experimentally confirmed G4 formation for sequences found in these two organelles. The frequency of PQSs for nuclear DNA was 0.42 PQSs per thousand base pairs (kbp), in the same range as for cpDNA (0.53/kbp), but significantly lower than what was found for mitochondrial DNA (1.58/kbp). In the nuclear genome, PQSs were mainly associated with regulatory regions, including 5′UTRs, and upstream of the rRNA region. In contrast to genomic DNA, PQSs were located around RNA genes in cpDNA and mtDNA. Interestingly, PQSs were also associated with specific transposable elements such as TIR and LTR and around them, pointing to their role in their spreading in nuclear DNA. The nonrandom localization of PQSs uncovered their evolutionary and functional significance in the Pisum sativum genome. [ABSTRACT FROM AUTHOR]

Background: Accurate outcome prediction is of great clinical significance in customizing personalized treatment plans, reducing the situation of poor recovery, and objectively and accurately evaluating the treatment effect. This study intended to evaluate the performance of clinical text information (CTI), radiomics features, and survival features (SurvF) for predicting functional outcomes of patients with ischemic stroke. Methods: SurvF was constructed based on CTI and mRS radiomics features (mRSRF) to improve the prediction of the functional outcome in 3 months (90-day mRS). Ten machine learning models predicted functional outcomes in three situations (2-category, 4-category, and 7-category) using seven feature groups constructed by CTI, mRSRF, and SurvF. Results: For 2-category, ALL (CTI + mRSRF+ SurvF) performed best, with an mAUC of 0.884, mAcc of 0.864, mPre of 0.877, mF1 of 0.86, and mRecall of 0.864. For 4-category, ALL also achieved the best mAuc of 0.787, while CTI + SurvF achieved the best score with mAcc = 0.611, mPre = 0.622, mF1 = 0.595, and mRe-call = 0.611. For 7-category, CTI + SurvF performed best, with an mAuc of 0.788, mPre of 0.519, mAcc of 0.529, mF1 of 0.495, and mRecall of 0.47. Conclusions: The above results indicate that mRSRF + CTI can accurately predict functional outcomes in ischemic stroke patients with proper machine learning models. Moreover, combining SurvF will improve the prediction effect compared with the original features. However, limited by the small sample size, further validation on larger and more varied datasets is necessary. [ABSTRACT FROM AUTHOR]

The δ13C value is regarded as an important indicator for tolerance to drought stress (DS), which is a severe abiotic stress that influences rice productivity. However, exploration of drought-responsive genes (DRGs) related to δ13C regulation is less reported. In this study, we investigated the natural variation in δ13C values in 102 japonica rice accessions. Among them, two rice accessions with contrasting δ13C values, Longdao 10 (LD10, DS-tolerant) and Binxu (BX, DS-sensitive), were used for further analysis. LD10 possesses better drought resistance with 2% lower δ13C values, 35% lower stomatal length and density, 33% lower water loss, and 11% lower stomatal conductance in comparison to BX. Transcriptome analysis shows that there are 2325 and 1378 differentially expressed genes (DEGs) induced by DS in LD10 and BX at the tillering stage, respectively, while there are 1076 and 492 DEGs in LD10 and BX at the graining stage, respectively. In total, 21 overlapped DEGs (defined as DRGs) were identified due to DS effects across two rice accessions over two stages. Among them, the expression levels of six genes, including chloride transporter (CLT1) and photosystem II polypeptide (PSBP), were further tested using qRT-PCR. Furthermore, we found that four methyltransferase genes were upregulated in BX compared to LD10 under DS. Consistently, the methylation levels of CLT1 and PSBP were higher along both promoter and CDS regions for CG, CHG, and CHH types. This study highlights the importance of the expression of these DRGs in response to DS and provides deep insights into DNA methylation-driven gene expression conferring different drought responses in rice. [ABSTRACT FROM AUTHOR]

Thermosensitive hydrogel scaffolds have attracted particular attention in three-dimensional (3D) cell culture. It is very necessary to develop a type of thermosensitive hydrogel material with low shrinkage, and excellent biocompatibility and biodegradability. Here, five types of thermosensitive microgels with different volume phase transition temperature (VPTT) or particle sizes were first synthesized using 2-methyl-2-propenoic acid-2-(2-methoxyethoxy) ethyl ester (MEO2MA) and oligoethylene glycol methyl ether methacrylate (OEGMA) as thermosensitive monomers by free radical polymerization. Their VPTT and particle sizes were investigated by a nanometer particle size meter and an ultraviolet spectrophotometer. The feasibility of using these P(OEGMA-co-MEO2MA) microgels to construct thermosensitive hydrogel by means of the thermal induction method is discussed for the first time. The prepared thermosensitive hydrogel with the optimum performance was screened for in situ embedding and three-dimensional (3D) culture of MCF-7 breast cancer cells. The experimental results of AO/EB and MTT methods indicate that the pioneering scaffold material has prominent biocompatibility, and cells grow rapidly in the 3D scaffold and maintain high proliferative capacity. At the same time, there is also a tendency to aggregate to form multicellular spheres. Therefore, this original P(OEGMA-co-MEO2MA) thermosensitive hydrogel can serve as a highly biocompatible and easily functionalized 3D cell culture platform with great potential in the biomedical area. [ABSTRACT FROM AUTHOR]

Traffic flow forecasting is challenging for us to analyze intricate spatial–temporal dependencies and obtain incomplete information of spatial–temporal connection. Existing frameworks mostly construct spatial and temporal modeling based on a fixed graph structure and given time series. However, a fixed adjacency matrix is limited to learn effective spatial–temporal correlations of the network because it represents incomplete information for missing genuine relation. To solve the difficulty, we design a novel spatial–temporal adaptive fusion graph network (STFAGN) for traffic prediction. First, our model combines fusion convolution layers with a novel adaptive dependency matrix by end-to-end training to capture the hidden spatial-temporal dependency on the data to complete incomplete information. Second, STFAGN could, in parallel, acquire hidden spatial–temporal dependencies by a fusion operation and temporal trend by fast-DTW. Meanwhile, we use ReZero connection as a simple change of deep residual networks to facilitate deep signal propagation and faster converge. Lastly, we conduct comparative experiments on two public traffic network datasets, whose results demonstrate the superiority of our algorithm compared to state-of-the-art baseline types. Ablation experiments also prove the rationality of the framework of STFAGN. [ABSTRACT FROM AUTHOR]

Prussian blue attracts the attention of many researchers as a promising candidate for use in sodium-ion battery cathodes due to its open frameworks and high working potential. However, the interstitial water in its crystal structure and its poor electronic conductivity limits its performance in practical sodium-ion batteries. Here, acid-assisted ball milling synthesis was employed as a versatile method for the production of surface-modified Prussian blue. With (CH3COO)2Fe being used as the raw material, the Prussian blue produced using ball milling synthesis was modified by the carboxyl functional group on its surface, which resulted in lower interstitial water content and enhanced electrochemical cycling performance. In addition, ball milling synthesis provided the as-prepared Prussian blue with a large surface area, improving its electrochemical rate performance. When used as the cathode of sodium-ion batteries, as-prepared Prussian blue delivered a specific capacity of 145.3 mAh g−1 at 0.2 C and 113.7 mAh g−1 at 1 C, maintaining 54.5% of the initial capacity after 1000 cycles at 1 C (1 C = 170 mA g−1). Furthermore, a solid-state sodium-ion battery was mounted, with as-prepared Prussian blue being employed as the cathode and Na metal as the anode, which delivered a high specific capacity of 128.7 mAh g−1 at 0.2 C. The present study put forward an effective solution to overcome the limitations of Prussian blue for its commercial application. [ABSTRACT FROM AUTHOR]

For improving the mechanical strength of controlled release fertilizer (CRF) hydrogels, a novel material of Chlorella was employed as a bio-based filler to prepare chitosan–chlorella hydrogel beads with physical crosslink method. Here, the synthesis mechanism was investigated, and the chitosan–chlorella hydrogel beads exhibited enhanced mechanical stability under centrifugation and sonication than pure chitosan hydrogel beads. Chlorella brought more abundant functional groups to original chitosan hydrogel, hence, chitosan–chlorella hydrogel beads represented greater sensitivity and controllable response to external factors including pH, salt solution, temperature. In distilled water, the hydrogel beads with 40 wt% Chlorella reached the largest water absorption ratio of 42.92 g/g. Moreover, the mechanism and kinetics process of swelling behavior of the chitosan–chlorella hydrogel beads were evaluated, and the loading and releasing of humic acid by the hydrogel beads as a carrier material were pH-dependent and adjustable, which exhibit the potential of chitosan–chlorella hydrogel beads in the field of controlled release carrier biomaterials. [ABSTRACT FROM AUTHOR]

Gel-based ionic conductors are promising candidates for flexible electronics, serving as stretchable sensors or electrodes. However, most of them suffer from a short operating life, low conductivity and rely on an external power supply, limiting their practical application. Herein, we report a stable organogel ionic conductor with high conductivity and self-powering ability. Briefly, lithium trifluoromethanesulfonate, as a conductive salt, provides high conductivity and the poly(1,1-difluoroethylene) layers, as a self-powering system, supply stable energy output under the influence of pressure. Moreover, the proposed conductors withstand long-term and multi-cycle durability tests. The prepared auxiliary training device can withstand the impact of a basketball and detect the impact force, showing potential in passive sensing during practical applications. [ABSTRACT FROM AUTHOR]

Fault detection of Substation Power Transformer by Non-contact measurement is important for the safety of machines, instruments, and human beings. To make non-contact measurement as convenient as possible, it is desirable that efficient algorithms based on AE (acoustic emission) discrimination are developed. This paper presents a system for quick and effective fault detection of substation power transformer, based on AE signals collected by non-contact single microphones. In the experiment, collected data were preprocessed in multiple ways and three machine learning algorithms were designed based on classifiers (Convolutional Neural Network (CNN), support vector machine (SVM), and k-nearest neighbors (KNN) algorithm) trained and tested by a tenfold cross-validation technique. After comparison among the designed classifiers, the results show the two-dimensional principal component analysis (2DPCA) preprocess combined with SVM achieved the best comprehensive effectiveness. [ABSTRACT FROM AUTHOR]

In deep learning-based local stereo matching methods, larger image patches usually bring better stereo matching accuracy. However, it is unrealistic to increase the size of the image patch size without restriction. Arbitrarily extending the patch size will change the local stereo matching method into the global stereo matching method, and the matching accuracy will be saturated. We simplified the existing Siamese convolutional network by reducing the number of network parameters and propose an efficient CNN based structure, namely adaptive deconvolution-based disparity matching net (ADSM net) by adding deconvolution layers to learn how to enlarge the size of input feature map for the following convolution layers. Experimental results on the KITTI2012 and 2015 datasets demonstrate that the proposed method can achieve a good trade-off between accuracy and complexity. [ABSTRACT FROM AUTHOR]

Background: Parkinson’s disease (PD) is typically characterized by impairment of motor function. Gait disturbances similar to those observed in patients with PD can be observed in animals after injection of neurotoxin 6-hydroxydopamine (6-OHDA) to induce unilateral nigrostriatal dopamine depletion. Exercise has been shown to be a promising non-pharmacological approach to reduce the risk of neurodegenerative disease. Methods: In this study, we investigated the long-term effects of voluntary running wheel exercise on gait phenotypes, depression, cognitive, rotational behaviors as well as histology in a 6-OHDA-lesioned rat model of PD. Results: We observed that, when compared with the non-exercise controls, five-week voluntary exercise alleviated and postponed the 6-OHDA-induced gait deficits, including a significantly improved walking speed, step/stride length, base of support and print length. In addition, we found that the non-motor functions, such as novel object recognition and forced swim test, were also ameliorated by voluntary exercise. However, the rotational behavior of the exercise group did not show significant differences when compared with the non-exercise group. Conclusions: We first analyzed the detailed spatiotemporal changes of gait pattern to investigate the potential benefits after long-term exercise in the rat model of PD, which could be useful for future objective assessment of locomotor function in PD or other neurological animal models. Furthermore, these results suggest that short-term voluntary exercise is sufficient to alleviate cognition deficits and depressive behavior in 6-OHDA lesioned rats and long-term treatment reduces the progression of motor symptoms and elevates tyrosine hydroxylase (TH), Brain-derived neurotrophic factor (BDNF), bone marrow tyrosine kinase in chromosome X (BMX) protein expression level without affecting dopaminergic (DA) neuron loss in this PD rat model. [ABSTRACT FROM AUTHOR]

The effects of dolomite powder on the freeze–thaw resistance of C30 and C45 concrete were investigated in this manuscript. Scanning electron microscopy (SEM), the electric flux method, and a freeze–thaw cycle testing machine were used to determine the morphology, chloride penetration resistance, mass loss rate, and relative dynamic elastic modulus ( E r ) of concrete incorporating dolomite powder. Concrete's freeze–thaw resistance improved as the dosage of dolomite powder was increased. After 300 cycles, the mass loss rates of reference specimens of C30 and C45 concrete were 6.71% and 0.14%, respectively, whereas the mass loss rates of C30 and C45 concrete in the presence of dolomite powder at a 50% replacement level were 5.81% and 0.13%, respectively. After 225 cycles, the E r of C30 concrete was 42.57% and 48.56% in the case of dolomite powder at 0 and 50% replacement levels, respectively. Meanwhile, after 300 cycles, the E r of C45 concrete was 67.54% and 71.50% in the case of dolomite powder at 0 and 50% replacement levels, respectively. Accordingly, the structure of dolomite-containing cement-based materials became more compact. Based on the Weibull distribution, a damage model for concrete containing dolomite powder was proposed. It established that concrete treated with dolomite powder had a lower degree of damage than reference specimens when subjected to the same freeze–thaw conditions. [ABSTRACT FROM AUTHOR]

Flavanols, a common class of secondary plant metabolites, exhibit several beneficial health properties by acting as antioxidant, anticarcinogen, cardioprotective, anti-microbial, anti-viral, and neuroprotective agents. Furthermore, some flavanols are considered functional ingredients in dairy products. Based on their structural features and health-promoting functions, flavanols have gained the attention of pharmacologists and botanists worldwide. This review collects and summarizes 121 flavanols comprising four categories: flavan-3-ols, flavan-4-ols, isoflavan-4-ols, and flavan-3,4-ols. The research of the various structural features and pharmacological activities of flavanols and their derivatives aims to lay the groundwork for subsequent research and expect to provide mentality and inspiration for the research. The current study provides a starting point for further research and development. [ABSTRACT FROM AUTHOR]

Promoting oligodendrocyte viability has been proposed as a therapeutic strategy for alleviating many neuronal diseases, such as multiple sclerosis and stroke. However, molecular pathways critical for oligodendrocyte survival under various stresses are still not well known. p53 is a strong tumor suppressor and regulates cell cycle, DNA repair and cell death. Our previous studies have shown that p53 plays an important role in promoting neuronal survival after insults, but its specific role in oligodendrocyte survival is not known. Here, we constructed the mice with oligodendrocyte-specific p53 loss by crossing TRP53flox/flox mice and CNP-cre mice, and found that p53 was dispensable for oligodendrocyte differentiation and myelin formation under physiological condition. In the experimental autoimmune encephalomyelitis (EAE) model, p53 loss of function, specifically in oligodendrocytes, did not affect the EAE disease severity and had no effect on demyelination in the spinal cord of the mice. Interestingly, p53 deficiency in oligodendrocytes significantly attenuated the demyelination of corpus callosum and alleviated the functional impairment of motor coordination and spatial memory in the cuprizone demyelination model. Moreover, the oligodendrocyte-specific loss of p53 provided protection against subcortical white matter damage and mitigated recognition memory impairment in mice in the white matter stroke model. These results suggest that p53 plays different roles in the brain and spinal cord or in response to various stresses. Thus, p53 may be a therapeutic target for oligodendrocyte prevention in specific brain injuries, such as white matter stroke and multiple sclerosis. [ABSTRACT FROM AUTHOR]