The human serotonin transporter (hSERT) terminates neurotransmission by removing serotonin from the synaptic cleft, which is an essential process plays an important role in depression. In addition to substrate serotonin, hSERT is also the target of drugs of abuse like cocaine and clinically used antidepressants such as escitalopram and paroxetine. To date, few studies attempt to investigate the unbinding mechanism underlying the orthosteric and allosteric modulation of hSERT. The high-resolution X-ray structure of hSERT resolved recently enables us to theoretically study the unbinding of the above four ligands against the S1 or S2 site of hSERT, by means of molecular docking, molecular dynamics (MD) and potential of mean force (PMF) simulations. We proved that for either the S1 or S2 site, the other three ligands (cocaine, escitalopram and paroxetine) are much more favorable than the original substrate serotonin, whether in kinetics along the unbinding pathways or in thermodynamics at the equilibrium states. Furthermore, the S1 site is much more favorable than the S2 site, for each ligand. Interestingly, inspection revealed that there are ~ 3Å lengths between the allosteric site of serotonin and cocaine, and an unseen un-binding pathway for escitalopram at the S1 site except for verification of the broadest trail.

Semisolid casting can provide excellent castings, but the nature of the pore-forming mechanisms has not been properly clarified. In the current communication, it was suggested that hydrogen precipitated during slurry making might have a decisive role in the formation of both gas and shrinkage porosity. Intensive stirring at the end of the slurry making process may act as a degassing step. Without the intense stirring, structures of primary slurry particles form around the hydrogen pores, strongly affecting pore formation and feeding during the intensification stage.

During the smelting process of AOD furnace, the unbalanced reaction of material will lead to the occurrence of splashing. It will not only damage the smelting equipment, but also seriously injure the personnel. In this study, first, the information of liquid level, audio information, and vibration information are detected by multiple sensors respectively. Then, the fused information is used to forecast the splashing. Finally, the multitasking fuzzy controller is used to suppress splashing. The results show that the method of forecasting and suppressing splashing can accurately forecast and achieve rapid suppression. Thus, the efficiency of smelting can be improved.

In the paper, the authors establish two identities to express the generating function of the Chebyshev polynomials of the second kind and its higher order derivatives in terms of the generating function and its derivatives each other, deduce an explicit formula and an identities for the Chebyshev polynomials of the second kind, derive the inverse of an integer, unit, and lower triangular matrix, present several identities of the Catalan numbers, and give some remarks on the closely related results including connections of the Catalan numbers respectively with the Chebyshev polynomials, the central Delannoy numbers, and the Fibonacci polynomials.

The dust originating from the extinct lake of the Aral Sea poses a considerable threat to the sur-rounding communities and ecosystems. The accurate location of these wind erosion areas is an essential prerequisite for controlling sand and dust activity. However, few relevant indicators re-ported in the current study can accurately describe and measure wind erosion intensity. A novel wind erosion intensity (WEI) of a resolution unit was defined in this paper based on the deformation due to the wind erosion in this resolution unit. We also derived the relationship between WEI and soil InSAR temporal decorrelation (ITD). The ITD is usually caused by the surface change over time, which is very suitable for describing wind erosion. However, within one resolution unit, the ITD signal usually includes soil and vegetation contributions, and few studies are referred to this. Therefore, we proposed an ITD decomposition model (ITDDM) to decompose the ITD signal of a resolution unit. The least-squares method (LSM) based on singular value decomposition (SVD) is used to estimate the ITD of soil (SITD) within a resolution unit. We verified the results qualitatively by the landscape photos, which can reflect the actual conditions of the soil. At last, the WEI of the Aral Sea from June 23, 2020, to July 05, 2020, was mapped. The results confirmed that (1) Based on the ITDDM model, the SITD can be accurately estimated by the LSM method, (2) the Aral Sea is experiencing severe wind erosion, and (3) The middle, northeast, and southeast bare areas of the South Aral Sea are where salt dust storms may occur.

Flavin-dependent monooxygenases (FMOs) have made substantial influence as catalysts for monooxygenation reactions, impacting diverse field such as drug metabolism, environmental studies, and natural product synthesis. Their application in biocatalysis boasts several advantages over conventional chemical catalysis, such as heightened selectivity, safety, sustainability, and eco-friendliness. In the realm of biomedicine, FMOs are pivotal in antibiotic research, modulating natural products, antimicrobial agents, and pathways involved in drug synthesis. They're also underscored as potential pharmaceutical targets, pivotal in disease progression and viable for therapeutic intervention. Additionally, FMOs play a substantial role in environmental science, especially in pesticide processing and plant vitality. Their involvement in biosynthesizing compounds like polyethers, tropolones, and ω-hydroxy fatty acids, with remarkable regio- and stereoselectivity, renders them indispensable in drug discovery and development. As our comprehension of FMOs' catalytic mechanisms and structures advances, coupled with cutting-edge biotechnologies like computational design and directed evolution, FMOs are poised to occupy an increasingly significant role in both scientific exploration and industrial applications.

Moso bamboo is famous for fast growing and biomass accumulation, as well as high annual output for timber and bamboo shoots. These high outputs require high nutrient inputs to maintain and improve stand productivity. Soil nitrogen (N), phosphorus (P) and potassium (K) are important micronutrients for plant growth and productivity. Due to high variability of soils, analysing spatial patterns of soil N, P and K stocks is necessary for scientific nutrient management in Moso bamboo forests. In this study, soils were sampled from 138 locations across Yong’an City and ordinary kriging was applied for spatial interpolation of soil N, P and K stocks. Soil N stock showed a strong spatial dependence while soil N and P stocks presented a moderate spatial dependence, indicating soil N was mainly controlled by intrinsic factors while soil N and P stocks were controlled by both intrinsic and extrinsic factors. Different spatial patterns were observed for soil N, P and K stocks across the whole study area, indicating that fertilizations with different ratios of N:P:K should be applied for different sites to maintain and improve stand productivity. The total soil N, P and K stocks within 0-60 cm were 0.624, 0.020 and 0.583 Tg, respectively.

The Urban heat island (UHI) effect has evolved into one of the key environmental problems affecting urban ecological environment and sustainable development. Based on 52 Urban Thermal Heat spots (UTHSs) with significant differences between land use structure and UGI spatial layout within the influence range of UHI in Shanghai, Landsat-8/9 satellite images were used to construct a high-dimensional data set reflecting the impact of built environment components on urban thermal environment. Descriptive statistical analysis was used to analyze the spatial difference qualitatively. Using stepwise regression model and partial least square regression (PLSR) model, the complex response relationship between UGI pattern differentiation and urban thermal environment in three spatial stratification ranges of UTHSs was quantitatively analyzed. Overall, the statistical explanatory power of the partial least square regression PLSR model is due to the stepwise regression model. The PLSR model points out that moderately increasing the average building height, CA, PLAND, LSI and LPI play a positive role in inhibiting/slowing down the growth of LST (land surface temperature), and the cooling effect of index weights decreases in order. However, the interaction effects of CA×Cohesion×AI×LPI and PLAND×CA×Cohesion×AI×LPI exert relatively small weight on the cooling effect, and according to the results, suggestions such as UGI structure and urban construction layout optimization can effectively alleviate the urban heat island effect are proposed.

In order to explore the effect of fertilization patterns on the growth of rapeseed seedlings under waterlogging stress, three fertilization patterns (conventional fertilization, supplemental organic fertilization, and supplemental microbial fertilization) were set up using the variety Xiangyou 708 as the material, and waterlogging treatment was carried out during the seedling stage of rapeseed. The effects of fertilization patterns on the growth of rapeseed seedlings and rhizosphere microorganisms under waterlogging stress were investigated. The results showed that all three fertilization patterns exhibited that waterlogging stress inhibited the growth of rapeseed seedlings, inhibited root activity, and changed the structure of rhizosphere bacterial colonies. However, supplemental organic fertilization and microbial fertilization could better promote the growth of rapeseed seedlings, reduce the impact of waterlogging stress on the growth of rapeseed seedlings, and accelerate the recovery of rapeseed seedlings after waterlogging stress. In addition, supplemental microbial fertilization could also change the structure of rhizosphere bacterial colonies. Under normal water supply, supplemental organic fertilization enriched P_Bacteroidota, P_Actinobacteriota, P_Chloroflexi, and G_Flavisolibacter in the rhizosphere soil of rapeseed, while supplemental microbial fertilization enriched P_Bacteroidota and G_Flavisolibacter in the rhizosphere soil of rapeseed. After 7 days of waterlogging treatment, supplemental organic fertilization enriched P_Verrucomicrobiota in the rhizosphere soil of rapeseed, while supplemental microbial fertilization enriched P_Actinobacteriota, G_SC-I-84, and G_Ellin6067 in the rhizosphere soil of rapeseed. The enrichment of these bacteria may be related to the growth promotion and waterlogging tolerance of rapeseed. This study provides evidence that microbial fertilizer and organic fertilizer can promote the growth of rapeseed and enhance its waterlogging tolerance, as well as evidence that some rhizosphere microorganisms have a potential role in promoting the growth and waterlogging tolerance of rapeseed.

This general review assesses the impact of physical exercise on oxidative and nitrosative stress and the counteractive role of antioxidants, drawing from a systematic literature search up to March 2024 in databases like PubMed and Web of Science. The review highlights studies on the effect of exercise on the production of reactive oxygen species (ROS) and reactive nitrogen species (RNS) and antioxidant responses in both human and animal models based on rigorous inclusion and exclusion criteria. Due to the variety of exercise types and participants' characteristics, a narrative synthesis approach was adopted. The findings indicate that moderate exercise boosts antioxidant defenses, known as hormesis, whereas excessive physical activity may increase oxidative and nitrosative damage. The review also explores the complex effects of antioxidant supplementation, revealing that while natural dietary antioxidants support health, high-dose supplements could potentially hinder positive adaptations to exercise. Recommendations for athletes and the general active population highlight the importance of balancing exercise and dietary intake to optimize health benefits. The review concludes with a call for more detailed research on tailored exercise and nutrition plans to dissect these intricate relationships further.

In order to maintain the best conditions of the building from the first day of opening, explorations of office buildings in the world investigated the approaches of optimizing the building operation and property facilities, whereas building managers often have trouble prioritizing improvements toward their sustainable objectives. The challenge is due to numerous equipment types in the building, which has various durability in years and represents users’ different feelings of importance and satisfaction. When faced with multiple improvement projects, building managers are often unable to determine the order of implementation.Hence, this research applies the Analytic Hierarchy Process (AHP) using TAIPEI 101 Tower as a case study to explore the key factors affecting tenants’ willingness to lease office buildings by distributing questionnaires to real estate experts. By filtering out key indicators related to property facilities that users care about, this study used Importance and Satisfaction Analysis (IS Analysis) to identify items that need urgent improvement. The research revealed that air conditioning is the top priority for improvement through empirical evaluation and weight ranking. This study hopes to establish an evaluation model for facility improvements to help clarify the prioritization and defeat limited resources to projects effectively, which is helpful for sustainable property management.

To prepare an edible coating with a good preservative effect on sweet cherries, carboxymethyl chitosan (CMCS) and gelatin (GL) were selected as the film-forming matrix in this experiment, and CaCl2 and ascorbic acid (AA) were added as crosslinking agents and antioxidants, respectively. First, the film was prepared by the casting method, and the film formula with better mechanical and barrier performance was filtered out by one-factor and response surface optimization test, and the differences in the preservation effect of different film formulations (CMCS-GL, CaCl2- CMCS-GL, AA -CaCl2- CMCS-GL) on sweet cherries were compared. and then the different film formulations were compared. The difference in film formulation on the preservation effect of sweet cherries was investigated. The results showed that the optimal formulation for an edible film based on CMCS-GL with good performance was CMCS: GL (w:w)=2:1, with the additional amount of 1% glycerol, 2% CaCl2, 0.1% Tween-20, 2% AA, the tensile strength, elongation at break, oxygen permeability and water vapor permeability of the film obtained with this formula were: 16.28 MPa, 71.46%, 1.39×10-12 g- cm/(cm2-s-Pa), 5.10×10-11 cm3-cm/(m2-s-Pa), respectively. In the preservation of sweet cherries, all three film formulations effectively reduced the rotting rate and weight loss during storage while preserving the high hardness and skin color of the fruit. Among them, the formulation AA -CaCl2- CMCS-GL showed the best preservation effect and can be used as a new method for postharvest preservation of sweet cherries.

The calculation of the exact value of the square root of 2 is requested. In order to obtain its infinite value, A new concept is proposed where the accumulations of the infinitely many of finity is indicated by the change in direction which means that there is a jump from finity to infinity .The meaningless for an infinite number with a decimal point is indicated by this jump because any decimal number only have meanings within a finite range values and there is only an infinite integer quantity that can not be operated by algorithms like operations of multiplication，division,addition, and subtraction . The final result of the change in direction is two quantity where the second quantity and the first quantity extend in parallel line and never intersect and the second quantity represent the size of the first quantity. The first quantity is the infinitely great that can't be talked about anything outside of it and can compress any quantities outside of it to nothing and it is the exact value of the square root of 2 .

Abstract Although we know something about single cell neuromuscular junction, It is still mysterious how multiple skeletal muscle cells coordinate to complete the intricate spatial curve movement. Here I propose a hypothesis that skeletal muscle cell populations with action potentials are alligned according to a curved manifolds on space(a curved shape on space) and the skeletal muscle also moves according to this corresponding shape(manifolds) when an specific motor nerve impulses are transmitted. the action potential of motor nerve fibers has the characteristics of time curve manifold and this time manifold curve of motor nerve fibers come from visual cortex in which a spatial geometric manifolds are formed within the synaptic connection of neurons. This spatial geometric manifolds of the synaptic connection of neurons orginate from spatial geometric manifolds in outside nature that are transmitted to brain through the cone cells and ganglion cells of the retina.Further,the essence of life is that life is an object that can move autonomously and the essence of life's autonomous movement is the movement of proteins. theoretically, due to the infinite diversity of geometric manifold shapes in nature, the arrangement and combination of 20 amino acids should have infinite diversity, and the geometric manifold formed by protein three-dimensional spatial structure should also have infinite diversity.

An approximate calculation of the spatial characteristics on finite range is required, so one quantitative continuum represents the accumulation of infinite great quantities is artificially divided it into smaller and camparable parts in which calculus operation can be applied .This operation is defined as Theorem 1 in which infinity is not involved, there is a camparable finity is constantly (forever) approaching and not reaching infinity, and only staying within a finite range. Theorem 1 can exist in this paper as a new mathematical basis for physics. Because the essence of all physical quantities is size comparison, and the size comparison relation of matter can only be space/time, so relation formula space/time is the only expression of the concept of matter, all physical quantities are applicable to this expression, each different physical quantity is a multi-dimensional representation of this expression. A new mass energy formula is aslo derived from this paper.

Abstract Unlike accelerated motion or curvalinear motion,a nonlinear motion state(non-inertial system) can be described by differential equations or the other algebric equations in axiom 2, the accelerated motion in axiom 3 can be considered to be described by using the equation of the linear and curvilinear process of the continuum extending to infinitely distance.Further, this linear and curvilinear process of the continuum is a quantitative continuum in essence as a unity of infinitely quantities and infinitely dimensions at infinite distance (infinity) relative to all orientations in which we exist. These indicates that an accelerated motion accumulates continuously started from a finite quantities, leaping to transit from finite to infinite quantities by an infinitely great accelerating force.

Single-phase-to-ground fault in non-effectively grounded systems poses serious public safety concern. Along with increasing deployment of low-voltage (LV) sensors, new opportunities and ways are created for solving this traditional problem in distribution systems. A new approach, identifying primary single-phase-to-ground line fault and locating it through measurement data from smart sensors deployed in the secondary side of distribution transformers, is proposed in this paper. When a fault occurs in primary distribution feeder, the transient aerial mode voltage (AMV) of each LV smart sensor is calculated. The fault line can be identified by an abrupt change value of AMV at LV side. Next, by finding the position of the maximum value of this AMV from LV sensors on the fault line, the fault location can be pinpointed to two neighboring distribution transformers. The proposed method has been proven to be efficient and reliable by simulation studies.

Complex illumination condition is one of the most critical challenging problems for practical face recognition. In this paper, we propose a novel method to improve the illumination invariants for solving this challenge. Firstly, a new method based on the Lambert reflectance model is proposed to extract illumination invariant, which is less insensitive to complex illumination variations. Secondly, in order to repair the defects caused by process of illumination invariants extraction, Fast Mean Filter is utilized to smooth and remove noise. Lastly, for raising the richness of information in output image, a nonlinear normalization transformation is proposed. Compared with the state-of-the-arts, experimental results show that the proposed method can extract more robust illumination invariants. Apart from it, the richness of information in processed image is greater and superior performance in face recognition rate is superior.

We estimated the daily intakes of chlorpyrifos and cypermethrin via ingestion of indoor dust and outdoor soils using the Stochastic Human Exposure and Dose Simulation Model on a probabilistic approach for Taiwan’s homes. Variable information for the daily intake estimation, such as concentration, ingestion rate, body weight, was adopted from previous studies. Monte Carlo simulation was performed with 1,000,000 iterations to simulate a single daily intake, which was shown in terms of percentage of the Acceptable Daily Intake (ADI) of either insecticide. The daily intakes were minimal with a 99% probability; at 99.9th percentile, however, the total intakes leaped to 13.1% and 20.0% of the respective ADIs of chlorpyrifos and cypermethrin. The sensitivity analysis indicated that concentration was the most determinant variable. Compared to the data of daily intakes via dietary ingestion of vegetables derived from a previous study, the estimated intakes by this study were considerable at the highest percentile, which referred to insecticide residues few days after insecticide application. Consequently, the non-dietary ingestion exposure to either insecticide was negligible in most cases; nevertheless, for those with indoor insecticide applications, the daily intakes for young children could be of concern. Frequently home cleaning is recommended to reduce the exposure.

Aflatoxin biosynthesis is correlated with oxidative stress and is proposed to function as a secondary defense mechanism to redundant intracellular reactive oxygen species (ROS). We find that the antioxidant gallic acid inhibits aflatoxin formation and growth in A. flavus in a dose-dependent manner. Global expression analysis (RNA-Seq) of gallic acid treated A. flavus showed that 0.8% (w/v) gallic acid revealed two possible routes of aflatoxin inhibition. Gallic acid significantly inhibited the expression of farB, encoding a transcription factor that participates in peroxisomal fatty acid β oxidation, a fundamental contributor to aflatoxin production. Secondly, the carbon repression regulator encoding gene creA was significantly down regulated by gallic acid treatment. CreA is necessary for aflatoxin synthesis and aflatoxin biosynthesis genes were significantly downregulated in DcreA mutants. In addition, the results of antioxidant enzyme activities and the lipid oxidation levels coupled with RNA-Seq data of antioxidant genes indicated that gallic acid may reduce oxidative stress through the glutathione- and thioredoxin-dependent systems in A. flavus.

Bearings are widely used in various types of electrical machinery and equipment. As their core components, failures will often cause serious consequences . At present, most methods of parameter adjustment are still manual adjustment of parameters. This adjustment method is susceptible to prior knowledge and easy to fall into the local optimal solution, failing to obtain the global optimal solution and requires a lot of resources.Therefore, this paper proposes a new method of bearing fault diagnosis based on wavelet packet transform and convolutional neural network optimized by simulated annealing algorithm.The experimental results show that the method proposed in this paper has a more accurate effect in feature extraction and fault classification compared with traditional bearing fault diagnosis methods. At the same time, compared with the traditional artificial neural network parameter adjustment, this paper introduces the simulated annealing algorithm to automatically adjust the parameters of the neural network, thereby obtaining an adaptive bearing fault diagnosis method. To verify the effectiveness of the method, the Case Western Reserve University bearing database was used for testing, and the traditional intelligent bearing fault diagnosis method was compared. The results show that the method proposed in this paper has good results in bearing fault diagnosis. Provides a new way of thinking in the field of bearing fault diagnosis in parameter adjustment and fault classification algorithms

This paper considers the Hermitian solutions of a new system of commutative quaternion matrix equations, we establish both necessary and sufficient conditions for the existence of solutions. Furthermore, we derive an explicit general expression when it is solvable. To illustrate our main findings, we present two numerical algorithms and examples in this paper.

Most of existing fuzzy forecasting models partition historical training time series into fuzzy time series and build fuzzy-trend logical relationship groups to generate forecasting rules. The determination process of intervals is complex and uncertainty. In this paper, we present a novel fuzzy forecasting model based on high-order fuzzy-fluctuation trends and the fuzzy-fluctuation logical relationships of the training time series. Firstly, we compare each data with the data of its previous day in historical training time series to generate a new fluctuation trend time series(FTTS). Then, fuzzify the FTTS into fuzzy-fluctuation time series(FFTS) according to the up, equal or down range and orientation of the fluctuations. Since the relationship between historical FFTS and the fluctuation trend of future is nonlinear, Particle Swarm Optimization (PSO) algorithm is employed to estimate the required parameters. Finally, use the acquired parameters to forecast the future fluctuations. In order to compare the performance of the proposed model with that of the other models, we apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) time series datasets. The experimental results and the comparison results show that the proposed method can be successfully applied in stock market forecasting or such kinds of time series. We also apply the proposed method to forecast Shanghai Stock Exchange Composite Index (SHSECI) to verify its effectiveness and universality.

In wireless sensor networks (WSNs), each sensor node can estimate the global parameter from the local data in distributed manner. This paper proposed a robust diffusion estimation algorithm based on minimum error entropy criterion with self-adjusting step-size, which are referred to as diffusion MEE-SAS (DMEE-SAS) algorithm. The DMEE-SAS algorithm has fast speed of convergence and is robust against non-Gaussian noise in the measurements. The detailed performance analysis of the DMEE-SAS algorithm is performed. By combining the DMEE-SAS with diffusion minimum error entropy (DMEE) algorithms, an Improving DMEE-SAS algorithm is proposed, in non-stationary environment where tracking is very important. The Improving DMEE-SAS algorithm can avoid insensitivity of the DMEE-SAS algorithm due to the small effective step-size near the optimal estimator, and obtain a fast convergence speed. Numerical simulations are given to verify the effectiveness and advantages of these proposed algorithms.

This study examines the DCMA concerning the future risk of the water security status. We considered three risk factors: population growth, economic growth, and natural water supply demand differences. In the risk analysis part, we consulted with experts from several sectors including academia, Non-Governmental Organization (NGOs), and industry, to predict that the probability of future water stresses in high, medium, and low scenarios are 0.73, 0.24, and 0.03, respectively. In the decision analysis part, we adopted two Multiple Criteria Decision Analysis (MCDA) approaches that include Multiple Attribute Value Theory (MAVT) and Analytic Hierarchy Process (AHP) methods to evaluate the best alternative decision to alleviate future water stresses in the DCMA. The sensitivity analysis demonstrates the best option closely connects to the weighting scheme of the criteria considered in the framework. This study provides a valuable risk and decision analysis framework to analyze the water security status associated with the future water supply and demand gap decrease caused by three risk factors: population growth, climate change, and natural water supply.

Image segmentation is the process of partitioning an image into multiple segments where the goal is to simplify the representation of the image and make the image more meaningful and easier to analyze. In particular, semantic segmentation is an approach of detecting the classes of objects, based on each pixel. In the past, most semantic segmentation models were for only one single style, such as urban street views, medical images, or even Manga. In this paper, we proposed a semantic segmentation model called Dual-Pyramid Wide Residual Network (DPWRN) to solve the segmentation for cross-style datasets, which is suitable for diverse segmentation applications. The DPWRN integrated the Pyramid of Kernel paralleled with Dilation (PKD) and Multi-Feature Fusion (MFF) to improve the accuracy of segmentation. To evaluate the generalization of the DPWRN and its superiority over most state-of-the-art models, three datasets with completely different styles are tested in the experiments. Finally, the DPWRN verified its generalization and also showed its superiority over most state-of-the-art models.

Given the recent advances in information technology, speed has become an important requirement in data transmission. Given that an LED (light emitting diode) can turn on and off several thousand or even millions of times per second, then LiFi (light fidelity) technology has strong advantages over WiFi (wireless fidelity) in terms of speed. In this research project, a consortium involving an academic institution decided to evaluate the maturity of LiFi technology and design a demonstrator that could be integrated in a vehicle via an intra-vehicle data transmission system. The demonstrator is to implement a two-way LiFi communication between the reading light of a vehicle and a portable device such as a tablet or smartphone. The nomadic device must display, via an interface, data in real time. The data is RNT (Digital Terrestrial Radio) and TNT (Digital Terrestrial Television) provided by an in-house antenna. LiFi depends on optical technology. The optical characteristics have significant influences on the system. The paper shows ways to improve the system’s throughput, communication range, and reception area. By replacing the reading light with a more powerful one with better optical characteristics, the communication range and reception area improve. By using symmetrical power supply, the throughput improves. Likewise, by using optical filters that eliminate noise, the throughput also improves. We have demonstrated that LiFi data transmission in the vehicle is feasible; low-definition videos were successfully transmitted. The paper acknowledges that there are still various avenues for this work’s improvement.

The purpose of interdisciplinary communication during the early architectural design stage is to achieve the early integration of knowledge in different professional fields, which can help architects to choose correct design development strategies during the early architectural design stage. However, because there is too little information at the early design stage, and design solutions are still rapidly changing and developing, the uncertainties at this stage make it difficult for consultants in other disciplines to provide their views and analysis. In spite of this situation, the emergence of generative modeling is changing design procedures and methods of communication and cooperation for architectural teams, and has brought about a shift in the way architects transmit design information from "what" (declarative information) to "how" (procedural information). Generative modeling is like an aircraft's dashboard: It can provide a basis for interdisciplinary communication, provide interdisciplinary knowledge packages, and bring about a shift in interdisciplinary communication that will reduce the architectural team's communication needs and cost. This study uses a real design case to show the feasibility of generative modeling. Employing generative modeling as a basis, architects can enhance the efficiency of design change and multi-disciplinary communication during the early design stage, integrate specialized knowledge in relevant fields, use this knowledge to formulate design criteria for the next stage, and effectively transmit design decisions. As a consequence, the changes to the cost structure of design revisions and communication between different disciplines has initiated a paradigm shift toward multi-disciplinary communication in architectural design.

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.

A novel scheme that can simultaneously measure the Doppler frequency shift (DFS) and angle of arrival (AOA) of microwave signals is proposed. At the signal receiving unit (SRU), two echo signals and the reference signal are modulated by a Sagnac loop structure and sent to the central station (CS) for processing. At the CS, two low-frequency electrical signals are generated after polarization control and photoelectric conversion. The DFS without direction ambiguity and wide AOA measurement can be real-time acquired by monitoring the frequency and power of the two low-frequency electrical signals. In the simulation, an unambiguous DFS measurement with errors of ±3×10-3 Hz and a -90° to 90° AOA measurement range with errors of less than ±0.5° are realized. The safety and robustness of the system to environmental disturbance are improved, and it is more suitable for the modern electronic warfare system.

The oscillating heat pipe (OHP) is a new member in the family of heat pipes, and it has great potential applications in energy conservation. However, the fluid flow and heat transfer in the OHP as well as the fundamental effects of inner diameter on them have not been fully understood, which are essential to the design and optimization of the OHP in real applications. Therefore, by combining the high-speed visualization method and infrared thermal imaging technique, the fluid flow and thermal performance in the OHPs with inner diameters of 1, 2 and 3 mm are presented and analyzed. The results indicate that three fluid flow motions, including small oscillation, bulk oscillation and circulation, coexist or, respectively, exist alone with the increasing heating load under different inner diameters, with three flow patterns occurring in the OHPs, viz. bubbly flow, slug flow and annular flow. These fluid flow motions are closely correlated with the heat and mass transfer performance in the OHPs, which can be reflected by the characteristics of infrared thermal images of condensers. The decrease in the inner diameter increases the frictional flow resistance and capillary instability while restricting the nucleate boiling in OHPs, which leads to a smaller proportion of bubbly flow, a larger proportion of short slug flow, a poorer thermal performance, and easier dry-out of working fluid. In addition, when compared with the 2 mm OHP, the increasing role of gravity induces the thermosyphon effect and weakens the 'bubble pumping' action, which results in a little smaller and bigger thermal resistances of 3 mm OHP under small and bulk oscillation of working fluid, respectively.

This study uses machine learning to predict the convergence results of the Duffing equation with and without damping. The Duffing equation represents a nonlinear second-order differential equation with interesting behavior in undamped free vibration and forced vibration with damping. Convergence alternates randomly between 1 and -1 in undamped free vibration, depending on initial conditions. For forced vibration with damping, multiple factors influence vibration patterns. We utilize the fourth-order Runge-Kutta method to collect convergence results for both conditions. Machine learning techniques, specifically the long short term memory (LSTM) and LSTM-Neural Network (LSTM-NN) method, are employed to predict these convergence values. The LSTM-NN model is a hybrid approach that combines the LSTM method with the addition of hidden layers of neurons. Both the LSTM and LSTM-NN models are thoroughly explored and analyzed in this research. The research process involves three stages: data preprocessing, training, and verification. The results show that the LSTM-NN model becomes more adept at predicting binary datasets, boasting an impressive accuracy of up to 98%. However, when it comes to predicting multiple solutions, the traditional LSTM method outperforms the LSTM-NN approach.

Thrombosis is the pathological clot formation under abnormal hemodynamic conditions, which can result in vascular obstruction, causing ischemic strokes and myocardial infarction. Thrombus growth under moderate to low shear (<1000 s^-1) relies on platelet activation and coagulation. Thrombosis at elevated high shear rates (>10,000 s-1) is predominantly driven by unactivated platelet binding and aggregating mediated by von Willebrand factor (VWF), while platelet activation and coagulation are secondary in supporting and reinforcing the thrombus. Given the molecular and cellular level information it can access, multiscale computational modelling informed by biology can provide new pathphysiological mechanisms that are otherwise not accessible experimentally, holding promise for novel first-principle-based therapeutics. In this review, we summarize the key aspects of platelet biorheology and mechanobiology, focusing on the molecular and cellular scale events and how they build up to thrombosis through platelet adhesion and aggregation in the presence or absence of platelet activation. In particular, we highlight recent advancements in multiscale modeling of platelet biorheology and mechanobiology and how they can lead to better prediction and quantification of thrombus formation, exemplifying the exciting paradigm of digital medicine.

Applied talent is not only a builder of human civilization but also a promoter of economic development. They not only need systematic and solid engineering theoretical knowledge but also rich engineering practical experience. Applied undergraduate colleges are the cradle for cultivating applied talent and shoulder the important mission of cultivating various types of applied talent for society. With the rapid development of higher education, the number of applied undergraduate institutions has sharply increased, but the quality of applied talent cultivated by them has shown a significant decline, which greatly restricts the pace of industrial development in the world. This article proposes a new concept of promoting the "three certificates" (graduation certificate, degree certificate, and skill certificate) education model in applied undergraduate colleges, which is of great significance for the country to cultivate composite talents with the ability of "product design, production management, and product processing" at the same time.

The hospital indoor environment plays a significant role in shaping the microbial exposures that humans encounter. Resistance to antibiotics is one of the mechanisms employed by bacteria to develop resilience against stress in indoor environments. The extensive usage of antibiotics has been a key factor in driving changes in the ecological function of antibiotic resistance genes (ARGs) and their acquisition by pathogenic bacteria. By integrating the 16S rRNA Illumina sequencing and high throughput-qPCR approaches with water and air dust samples across seven departments at Peking University Shenzhen Hospital, China, this study yielded intriguing findings regarding the department-specific variation, transmission, and correlation of bacteria, ARGs and MGEs within the hospital indoor environment. One notable observation was that the seasonal variation played a vital role in shaping the bacterial composition in the overall hospital indoor environment across seven studied departments. Nevertheless, a similar significant seasonal impact was only observed in the blood test room and emergency departments, rather than in the other five departments. Another intriguing finding was the correlation between ARGs and MGEs abundance. This correlation was evident in the overall hospital indoor environment, which was conversely not found in the emergency, pneumology and gynecology departments. Additionally, while there was no significant relationship that occurred between bacterial communities and ARGs/MGEs within the hospital, the gynecology department demonstrated a close link between bacterial communities and the presence of ARGs/MGEs. Notably, the gynecology department also stood out as an important source of bacteria and ARGs/MGEs for other departments. This study underscores the need for careful surveillance and monitoring of antibiotic resistance, particularly in Legionella spp. in man-made water systems. The findings also show the importance of monitoring and understanding the genetic elements such as Tp614 involved in gene transfer and recombination, as well as their impact on antimicrobial treatment efficacy.

The fusion of machine learning, biomedical, and bioengineering research offers novel ways to understand, diagnose, and treat various health conditions. However, the complexities of biomedical and bioengineering data, coupled with the intricate process of developing and deploying machine learning solutions, often pose significant challenges to researchers in these fields. We introduce a new Automatic Semantic Machine Learning Microservice Framework (AIMS) that addresses these challenges by automating key aspects of the machine learning pipeline, from data preprocessing to model evaluation. Our proposed framework emphasizes model interpretability, the integration of domain knowledge, and the efficient handling of biomedical data. Furthermore, it incorporates self-supervised knowledge learning strategies, enabling the automatic generation, optimization, and continuous adaptation of machine learning models in response to new tasks and data. We illustrate the potential of our framework through three case studies in biomedical research, showcasing its capacity to streamline research processes, improve scientific exploration quality, and provide a foundation for significant breakthroughs.

Coal gasification with carbon dioxide is a process for generating clean gaseous fuels and relieving greenhouse effect. Zhundong coal has high alkali and alkali earth metals (AAEMs) content, medium volatile and low ash in nature. Isothermal CO₂ gasification of char derived from Zhundong coal (R-char) and char from acid washing R-char (AR-char) are performed in thermo-gravimetric analyzer (TGA). The effect of AAEMs is investigated on the gasification behavior in the range of temperatures 1073 K to 1273 K. The carbon conversion increases rapidly with increasing reaction temperature and CO₂ concentration. R-char has high gasification rate and carbon conversion compared with AR-char. The accuracy of the free-model approach for calculating activation energy at different conversions is validated by compared with different kinetic models (volume reaction model, distributed activation energy model). Moreover, R-char gasification with CO₂ shows a compensation effect as the Arrhenius parameters (EA and k0) increase or decrease simultaneously.

Chromosome elimination resulting in haploids is achieved by rapid loss of chromosomes from one parent during zygote stage, and is an important procedure to produce doubled haploid (DH) lines in plants. During crosses between an emasculated wheat (Triticum aestivum L.) and a maize (Zea mays L.) as pollen donor, the complete loss of maize chromosomes results in wheat haploid embryos. Through embryo rescue and chromosome doubling process, pure lines with stable traits can be quickly obtained. We here term it as the maize-obligated wheat doubled haploids (mowDH). Although this technology is not new, it remains a practical approach to date. In order to optimize and improve this technology, and to achieve its maximum potential in the winter wheat area of China, this paper reviews the previous and on-going research, proposes a technical scheme for production of wheat DH lines via the maize pollen induction, and presents outlooks on DH research and its application in wheat breeding.

In this paper, we shall introduce the interval-valued spatial error model. Based on the idea of least square method of single-valued case, we give the parameter estimator for interval-valued spatial error model. The theoretical properties of the proposed estimator are proved. Finally, we give the numerical analysis and a real example.

Transition between free-surface and pressurized flows is an crucial phenomenon in many hydraulic systems, including water distribution systems, urban drainage systems, etc. During the transition, the force exerted on the structures changes drastically, thus it is meaningful to simulate this process. However, severe numerical oscillations are widely observed behind filling-bores, causing unphysical pressure variations and even computation failure. In this paper, some oscillation-suppressing approaches are reviewed and evaluated on a benchmark model. Then a new oscillation-suppressing approach is proposed to admit numerical viscosity when the water surface is at proximity of conduct roof which has first order accuracy. This approach adds numerical viscosity when water surface is at the proximity of conduct roof. It can sufficiently suppress numerical oscillations under an acoustic wave speed of 1000m/s and is simple to apply. In comparison with two experiments, the simulation results of this method show good agreement and little numerical oscillations. The results in this paper can help readers to choose an appropriate oscillation-suppressing method to improve the robustness and accuracy of flow regime transition simulations.

The theory of heterogeneous nucleation was initially developed as a part of condensed matter physics and later it was used as an important engineering tool to design metallurgical processes. The success leads to wide applications of the theory in metallurgical practice. For example, engineering heterogeneous nucleation in ductile iron has been used to reduce shrinkage defects, suppress cementite formation, and modify size and shape of micro-structural constituencies. This demonstrates how theoretical knowledge could benefit industry practice. This overview aims to summarize the authors’ published studies in co-authorship with colleagues and students, which covered different aspects of engineering heterogeneous nucleation in multiphase cast alloys. Several approaches for engineering heterogeneous nucleation using thermodynamic simulation and practical methods for improving efficiency of nucleation using co-precipitation technique and a local transient melt supersaturation were suggested. Automated Scanning Electron Microscopy Energy-Dispersive-X-ray (SEM/EDX) analysis and a high-resolution Transmission Electron Microscopy (TEM) were used to verify simulation predictions. Practical examples of controlling micro-porosity shrinkage in cast irons with spheroidal graphite are presented to illustrate the power of engineering heterogenous nucleation. The authors appreciate the great efforts that the co-authors have made on the original, overviewed articles here.

This paper presents a multifunctional reflective digital metasurface of arbitrary base based on voltage tunable liquid crystal (LC). The reflective digital metamaterial can be multiplexed for different desirable functions by properly biasing the LC for different code patterns. Simulation results of three significant functions, beam steering with a steering elevation angle 27° at 75 GHz, RCS reduction of at least 15dB along the incident direction, and beam shaping with different beam shapes have been presented to prove the concept.

Arc sensors have been used in seam tracking and widely studied since the 80s; commercial arc sensing products for T and V shaped grooves have been developed. However, it is difficult to use these arc sensors in narrow gap welding because arc stability and sensing accuracy are not satisfactory. Pulse gas melting arc welding (P-GMAW) has been successfully applied in narrow gap welding and all position welding processes, so it is worthwhile to research P-GMAW arc sensing technology. In this paper, we derived a linear mathematical P-GMAW model for arc sensing, and the assumptions for the model are verified through experiments and finite element methods. Finally, the linear characteristics of the mathematical model were investigated. In torch height changing experiments, uphill experiments, and groove angle changing experiments the P-GMAW arc signals all satisfied the linear rules. In addition, the faster the welding speed, the higher the arc signal sensitivities; the smaller the groove angle, the greater the arc sensitivities. The arc signal variation rate needs to be modified according to the welding power, groove angles, and swing or rotate speed.

This paper addresses the effect of both microstructure and relative humidity on the long-term creep properties of sustainable calcium carbonate (CaCO₃) cements. Those can be prepared by mixing amorphous calcium carbonate and vaterite with water. A larger starting amount of vaterite, X_V, within the mixture design gives a higher elasticity and resistance to the specimens due to the larger overall bridging area within the newly formed calcite crystals. Regarding creep properties for a given relative humidity, the amplitude of creep strain decreases with X_V, and makes the relation between the elastic modulus, E, and hardness, H, of the samples to be linear with the contact creep modulus, C. On the other hand, for a given composition, the amplitude of creep increases with the relative humidity, making the contact creep modulus, Ci, to rise exponentially with the elastic modulus, E, and hardness, H, of the specimens. The most probable creep mechanisms for this kind of cement seem to be a combination of microcraking in the early stages and dissolution and reprecipitation of calcite in the long-term (also known as pressure solution theory). The presence of water in pores with increasing relative humidity might enhance the local dissolution of calcite, and hence the creep amplitude.

This is the fourth part of [6] on the existence of K¨ahler Einstein metrics of the general type I almost homogeneous manifolds of cohomogeneity one. We actually carry out all the results in [8] to the type I cases. In part II [14], we obtained a lot of new K¨ahler-Einstein manifolds as well as Fano manifolds without K¨ahler-Einstein metrics. In particular, by applying Theorem 15 therein, we have complete results in the Theorems 3 and 4 in that paper. However, we only have some partial results in Theorem 5 there. In this note, we shall give a report of recent progress on the Fano manifolds Nn,m when n > 15 and N′n,m when n > 4. We actually give two nice pictures for these two classes of manifolds. See our Theorems 1 and 2 in the last section. Moreover, we post two conjectures. Once we could solve these two conjectures, the question for these two classes of manifolds would be completely solved. With applying our results to the canonical circle bundles we also obtain Sasakian manifolds with or without Sasakian-Einstein metrics. That also give some open Calabi-Yau manifolds.

We investigate and discuss in detail the structure of the restricted singular value decomposition for a tensor triplet under t-product (T-RSVD). The algorithm is provided with a numerical example illustrating the main result. For applications, we consider color image watermarking processing with T-RSVD.

Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided.

During choriogenesis in insects, chorion (eggshell) is formed by surrounding follicular epithelial cells in ovarioles. However, the regulatory endocrine factor(s) activating choriogenesis and the chemical components on eggshell deserve further exploration. In two representative Coleopterans, a Coccinellid Henosepilachna vigintioctopunctata and a Chrysomelid Leptinotarsa decemlineata, genes encoding the 20-hydroxyecdysone (20E) receptor heterodimer, ecdysone receptor (EcR) and ultraspiracle (USP), and two chitin biosynthesis enzymes UDP-N-acetylglucosamine pyrophosphorylase (UAP) and chitin synthase (ChS1), were highly expressed in ovaries of the young females. RNA interference (RNAi)-aided knockdown of either HvEcR or Hvusp in H. vigintioctopunctata inhibited oviposition, suppressed the expression of HvChS1, and lessened the positive signal of Calcofluor staining on the chorions, which suggests the reduction of a chitin-like substance (CLS) deposited on eggshells. Similarly, RNAi of LdEcR or Ldusp in L. decemlineata constrained oviposition, decreased the expression of LdUAP1 and LdChS1, and declined CLS contents in the resultant ovaries. Knockdown of LdUAP1 or LdChS1 caused similar defective phenotypes, i.e., reduced oviposition and CLS contents in the L. decemlineata ovaries. These results, for the first time, indicate that 20E signaling activates choriogenesis in two Coleopteran species. Moreover, our findings propose the deposition of a CLS on the chorions.

Some researchers in Taiwan argue that the current mechanism by which government subsidies are allocated for smart city demonstration projects warrants improvement. A comprehensive literature review determined that the development potential of smart cities should be prioritized in site selection for such demonstration projects. This study developed an evaluation framework on the basis of multi-criteria evaluation methods to enable the identification of suitable smart community demonstration sites. Evaluation criteria were first identified through the Delphi method. Next, the weights of each criterion were derived through the analytic hierarchy process. Furthermore, the capability of the proposed evaluation model was determined through simulation testing.

Quantitative and qualitative fuzzy measures have been proposed to hesitant fuzzy sets (HFSs) from different points. However, few of the existing HFSs fuzzy measures refer to the grey relational analysis (GRA) theory. Actually, the GRA theory is very useful in the fuzzy measure domain, which has been developed for such the intuitionistic fuzzy sets. Therefore, in this paper, we apply the GRA theory to the HFSs and interval-valued hesitant fuzzy sets (IVHFS) domain. We propose the HFSs grey relational degree, HFSs slope grey relational degree, HFSs synthetic grey relational degree and IVHFSs grey relational degree, which describe the closeness, the variation tendency and both the closeness and variation tendency of HFSs and closeness of IVHFSs, respectively, greatly enriching the fuzzy measures of HFSs. Furthermore, with the help of the TOPSIS method, we develop the grey relational based MADM methodology to solve the HFSs and IVHFSs MADM problems. Finally, combined with two practical MADM examples about energy policy selection with HFSs information and emergency management evaluation with IVHFSs information, we obtain the most desirable decision results, and compared with the previous methods, the validity, effectiveness and accuracy of the proposed grey relational degree for HFSs and IVHFSs are demonstrated in detail.

Erosion caused by the repeated impact of particles on a substance surface is a usual wear method resulting in gradual and continual loss of objects. It is a crucial problem in several modern industries because their surfaces are frequently subjected to destructive erosive situations. Polymers and their hybrid materials include several applications to be used as a coating in the form of powder for different applications. This review paper aims to provide extensive information on the erosion behavior of thermoset and thermoplastic neat resin and their hybrid materials composites. Focus is specifically paid to highlight the influence of properties of selected materials, impingnation parameters such as incident Angle of erodent, impact velocity of erodent, erodent nature, and the erosion mechanism. The review further extends the information about the erosion techniques and numerical simulation methods used for wear studies of surfaces. An investigation has been carried out for researchers to explore the selection of materials and methods in terms of conditions and parameters to meet the current and future needs and challenges for the protection of surfaces of the advanced industries. During review according to the findings achieved from the literature of the past fifty years, it has been noted that the thermoplastic nature of the composite is a key component to determine the anti-wear properties, the composites with lower glass transition, higher ductility, and greater crystallinity can provide better protection to erosion in advance surface applications.

This paper proposes a new approach for multi-focus images fusion based on Region Mosaicing on Contrast Pyramids (REMCP). A density-based region growing method is developed to construct a focused region mask for multi-focus images. The segmented focused region mask is decomposed into a mask pyramid, which is then used for supervised region mosaicking on a contrast pyramid. In this way, the focus measurement and the continuity of focused regions are incorporated and the pixel level pyramid fusion is improved at the region level. Objective and subjective experiments show that the proposed REMCP is more robust to noise than compared algorithms and can fully preserves the focus information of the multi-focus images meanwhile reducing distortions of the fused images.

Nowadays the relationship between planning land use and actual land use is not so clear in general. A lot of efforts have been put in the failures of regulation for the expansion of construction land. However, it still lacks an integrated approach to study the effectiveness of land use regulation in terms of different land use types. Furthermore, the existing evaluation of land use plan mainly focuses on a general level, a detailed research on the regulation effectiveness of each construction land use type is absent. Therefore, this research tries to evaluate regulation effectiveness of land use plan, which takes Cangwu country, Guangxi Province as an example. The finding by analysis is that the total area of construction land expansion was about 3494.73 ha, nearly 1.1 times of the plan quota. Moreover, the effectiveness differs greatly in various construction land use types. Town, industrial/mining sites can be well regulated through the quota of land use plan. While, the quota regulation system is not as effective for other type of construction land. Thus, we suggest to improve the regulation effectiveness of construction land through different plan instruments.

The anti-inflammatory effect of ginsenoside Rh2 (GRh2) is one of the most important ginsenosides. The purpose of this study is to identify the anti-inflammatory and antioxidant effects of GRh2 after LPS challenge lung injury animal model. GRh2 reduced LPS-induced NO, TNF-α, IL-1, IL-4, IL-6 and IL-10 productions in lung tissues. GRh2 treatment decreased the histological alterations in the lung tissues and BALF protein content and total cells number also diminished in LPS-induced lung injury mice. Moreover, GRh2 blocked iNOS, COX-2, the phosphorylation of IκB-α, ERK, JNK, p38, Raf-1 and MEK protein expression which is corresponded to the growth of HO-1, Nrf-2, catalase, SOD and GPx expressions in LPS-induce lung injury. An experimental study has suggested that GRh2 has provided with anti-inflammatory effects in vivo, and its potential therapeutic efficacy in major anterior segment lung diseases.

Primary urethral malignancies are rare in clinical practice and elderly female are prone to suffer. The cause of PUC is unknown and may be related to long-term chronic inflammation, infection, sexual intercourse, pregnancy and irritation of the urethra. Incipient symptom of PUC is not distinctness and can easily lead to misdiagnosis. The final diagnosis relied on transvaginal ultrasound-guided mass biopsy and urethral biopsy. Early tumor treatment is mainly based on surgical resection. For advanced tumors, it is recommended to adopt a comprehensive treatment plan combining surgery, radiotherapy and chemotherapy We report this case with the aim of bringing attention to that primary urethral cancer progresses rapidly and has a poor prognosis, it is urged to call for a need of diagnostic and treatment specification.

Visual data on the geographic distribution of carbon storage helps policy maker to formulate countermeasures on global warming. However, Taiwan, as an island showing diversity in climate and topography, had lacked valid visual data in distribution of forest carbon storage between the last to forest surveys (1993-2015). This study established a model to achieve an estimation that capable to demonstrate the distribution of forest carbon storage. This model uses land use, stand morphology, carbon conversion coefficient databases accordingly for 51 types of major forest in Taiwan. An estimation on 2006 was conducted and shows an overall carbon storage of 165.65 Mt C, with forest carbon storage per unit area of 71.56 t C ha–1, where natural forests and plantations respectively contributed of 114.15 Mt C (68.9%) and 51.50 Mt C (31.1%). By assuming no change in land use type, the carbon sequestration from 2006 to 2007 by the 51 forest types was estimated to be 5.21 Mt C yr–1 using historical tree growth and mortality rates. The result reflects the reality of the land use status and event of coverage shifting with time by combining to the two forest surveys in Taiwan.

BACKGROUND. The aims of this study was to compare differences in daytime sleepiness between genders and qualification levels in a cohort university Chinese soccer player under 0 Covid policy restrictions in the urban area of Shanghai. METHODS. 491 questionnaires of Epworth Sleepiness Scales (ESS) were compiled online by males and females Soccer Students (SS), Semi-professional players (SP) and professional players (PP) during the ongoing measures of Shanghai lockdown. ANOVA was performed for players levels and gender. RESULTS. Significant differences were found between the 3 levels and between males and females. PP showed a very low score in the ESS (5,97) well below the threshold of 8, while SS and SP showed an ESS score above the threshold. Female showed higher scores than males. CONCLUSIONS. This study present the first data on sleepiness in Chinese soccer players of different level of qualification in a lockdown condition. Professional players has been less affected by lockdown measures than SS and SP. We can hypothesize the reasons resides in the more ordered lifestyle of PP in comparison to SS and SP, which mitigated the effects of the lockdown. Measures to improve sleep in females’ soccer player should be adopted.

Leaf variegation pale yellowing is observed in the Calcineurin B-Like-Interacting Protein Kinase14 (CIPK14) overexpression line (oeCIPK14) and double knockout WHIRLY1/WHIRLY3 (why1/3) lines of Arabidopsis, the distribution of WHIRLY1 (WHY1) protein between plastids and the nucleus are affected by the phosphorylation of WHY1 by CIPK14. To elucidate the coregulation of CIPK14 and WHIRLY1/WHIRLY3 mediated leaf pale yellowing, a differential proteomic analysis is conducted between the oeCIPK14 variegated (oeCIPK14-var) line, why1/3 variegated (why1/3-var) line and wild type (WT). More than 800 protein spots are distinguished on each gel, 67 differential abundance proteins (DAPs) are identified by matrix-assisted laser desorption ionization-time of flight/time of flight mass spectrometry (MALDI-TOF/TOF-MS), of which, 34 DAPs are in the oeCIPK14-var, 33 DAPs are in the why1/3-var compared to WT. Five overlapping proteins differentially change both in the oeCIPK14-var and in the why1/3-var. They are ATP-dependent Clp protease proteolytic subunit-related protein 3 (ClpR3), Ribulose bisphosphate carboxylase large chain (RBL), Beta-amylase 3 (BAM3), Ribosome-recycling factor (RRF), Ribulose bisphosphate carboxylase small chain (RBS). Bioinformatics analysis show that most of DAPs are involved in photosynthesis, defense and antioxidation pathway, protein metabolism, amino acid metabolism, energy metabolism, malate biosynthesis, lipid metabolism and transcription. Thus, the photosystem parameters are measured that the content of chlorophyll, the photochemical efficiency of PSⅡ (Fv/Fm), and electron transport rates (ETR) decrease in the why1/3-var and oeCIPK14-var, but the non-photochemical quenching (NPQ) increases. Both mutants show high sensitivity to strong light. Based on the annotation of DAPs from both why1/3-var and oeCIPK14-var lines, we conclude that CIPK14 phosphorylation mediated WHY1 deficiency in plastids is related to impairment of protein metabolism leading to chloroplast dysfunction.

To win a taekwondo competition, more points must be scored, and the key to scoring points is to improve the motor performance of the kick. The wing kick is an offensive and defensive maneuver. Core stability appears to be important for improving athletic performance, but the specific relationship and effect of core stability on athletic performance in the aerial phase of taekwondo is unclear. The aim of this study was to investigate the relationship between core stability and athletic performance in taekwondo in order to provide appropriate theoretical support for training and to help coaches and athletes to improve athletic performance. A total of 16 subjects (height: 167.34±9.2 cm; weight: 61±8.96 kg; age: 24.7±3.25 years) were studied. Data were captured using 13 infrared cameras at 120Hz, kinematic and kinetic data were captured using a motivated motion capture system, and the data were exported to Visual3D in order to calculate the execution time of the aerial phase, the angular momentum of the left lower extremity, and MVC analysis of the EMG using EMG works. The core stability level of the subjects were measured using the Sahrmann Core Stability Test (SCST) to correlate with the other data, and then the subjects were grouped according to their core stability levels and the data from both groups were analyzed with t-tests. Results During the double fly lifting of aerial segments, SCST levels showed a very strong negative correlation with execution time (r= -0.739) and there was a statistically significant difference in execution time between high and low SCST levels (p &lt; 0.001), and the desired negative correlation was also seen in lower limb angular momentum X-axis (thigh r= -0.6294, shank r= -0.536, foot r= -0.6175), especially in the X-axis. The left rectus femoris (LRF) data had greater activation in the low SCST group(p=0.0019*). Through this experiment, we found that athletes with high core stability had faster execution times, lower angular momentum, and higher core muscle activation. Therefore, we conclude that incorporating core stability training into taekwondo training has the potential to improve kicking performance.

Defect recognition in ballastless track structures, based on distributed acoustic sensors (DASs), was researched in order to improve detection efficiency and ensure the safe operation of trains on high-speed railways. A line in southern China was selected, and equipment was installed and debugged to collect the signals of trains and events along it. Track vibration signals were extracted by identifying a train track, denoising, framing and labeling to build a defect dataset. Time–frequency-domain statistical features, wavelet packet energy spectra and the MFCCs of vibration signals were extracted to form a multi-dimensional vector. An XGBoost model was trained and its accuracy reached 89.34%. A time-domain residual network (ResNet) that would expand the receptive field and test the accuracies obtained from convolution kernels of different sizes was proposed, and its accuracy reached 94.82%. In conclusion, both methods showed good performance with the built dataset. Additionally, the ResNet delivered more effective detection of DAS signals compared to conventional feature engineering methods.

Chronic hepatitis B infection remains a significant worldwide health burden, placing persons at risk for hepatocellular cancer and hepatic fibrosis. Chronic hepatitis B virus (CHB) infection is characterized by elevated levels of immunosuppressive regulatory T cells (Tregs), which can inhibit the function of effector T cells and lead to an insufficient immune clearance response against HBV in the host. Theoretically, suppression of Treg functionality and percentage could increase anti-HBV reactivity in CHB-infected patients, although this has not yet been explored. We attempted to enhance our previously established anti-CHB protocol utilizing the GM-CSF+IFN-α+rHBVvac regimen (GMI-HBVac) by incorporating Mafosfamide (MAF), which has been utilized in anticancer therapy in the past. Intravenous administration of MAF to rAAV8-1.3HBV-infected mice resulted in a dose-dependent reduction of Tregs in the blood, rebounding to pretreatment levels 10 days later. To determine the efficacy of anti-CHB, 2ug/ml MAF was combined with the GMI-HBVac in an HBV-infected animal model as an anti-Treg treatment. When rAAV8-1.3HBV-infected mice were immunized with MAF+GMI-HBVac, peripheral blood Tregs decreased significantly, leading to dendritic cell activation, HBV-specific T cell proliferation, and upregulation of IFN-gamma producing CD8+T cells. In addition, MAF+GMI-HBVac vaccination stimulates T cell infiltration in HBV-infected liver. These conditions may contribute to an enhanced immune response and the clearance of HBV-associated antigens, including serum HBsAg, serum HBcAg, and HBcAg+ hepatocytes. Overall, this is the first indication that MAF was utilized as an adjuvant to deplete Tregs and paired with GMI-HBVac as a unique therapeutic vaccine regimen against established CHB mice to produce a functional cure, as seen by the remarkable clearance of HBsAg.

Stem cells are undifferentiated cells which can give rise to any types of cells in our body. Hence, they have been utilized for various applications such as drug testing and disease modeling. However, for the successful of those applications, the survival and differentiation of stem cells into specialized lineages should be well controlled. Growth factors and chemical agents are the most common signals to promote the proliferation and differentiation of stem cells. However, those approaches holds several drawbacks such as the negative side effects, degradation or denaturation, and expensive. To address such limitations, nanomaterials have been recently used as a better approach for controlling stem cells behaviors. Graphene oxide is the derivative of graphene, the first 2D materials in the world. Recently, due to its extraordinary properties and great biological effects on stem cells, many scientists around the world have utilized graphene oxide to enhance the differentiation potential of stem cells. In this mini review, we highlight the key advances about the effects of graphene oxide on controlling stem cell growth and various types of stem cell differentiation. We also discuss the possible molecular mechanisms of graphene oxide in controlling stem cell growth and differentiation.

Depression is the most common chronic mental illness and is characterized by low mood, insomnia, and affective disorders. However, the pathological mechanisms of depression remain unclear. Numerous studies have suggested that the ghrelin/GHSR system may be involved in the pathophysiologic process of depression. Ghrelin plays a dual role in the experimental animals, increasing depressed behavior and decreasing anxiety. By combining several neuropeptides and traditional neurotransmitter systems to construct neural networks, it modifies signals connected to depression. The present review emphasizes the role of ghrelin in neuritogenesis, astrocyte protection, inflammatory factor production, and endocrine disruption in depression. Furthermore, ghrelin/GHSR can activate multiple signaling pathways to produce antidepressant effects, including cAMP/CREB/BDNF, PI3K/Akt, Jak2/STAT3, and p38-MAPK. Given the antidepressant effects of ghrelin/GHSR1a system, it is expected to become a potential therapeutic target for the treatment of depression.

The impact of the agriculture net carbon effect is crucial for climate change mitigation, yet research on this topic in China is currently insufficient. In this study, the carbon balance ratio (CBR) is used to characterise the net carbon effect of agriculture, and the spatial Durbin model and threshold regression model were used to empirically analyse the CBR with a sample of 30 provincial-level regions in China from 2004 to 2019. The aim was to investigate the mechanism of the influence of the land management scale (SCALE) of farming on the CBR. The results of the study indicate that national farming generally has a net sink effect, with large changes in interannual fluctuations; the expansion of SCALE has an obvious role in increasing sinks and reducing emissions, and has a positive spatial spillover effect on CBR, with significant spatial heterogeneity. Furthermore, as the SCALE expands, the direction of the influence of rural residents’ income and education level on CBR changes in the opposite direction, showing a significant non-linear relationship characteristic. However, in most areas, the SCALE threshold has not yet been reached, suggesting that the improvement in education levels can still offset the negative impact of economic income growth in the short term. The study recommends paying attention to the role of farmers’ human capital, changing production methods, and implementing carbon peaking and carbon neutrality goals to enhance the net sink effect of the farming industry, which would be achieved by increasing land management scale.

This narrative review critically evaluates the multidimensional impacts of team sports on student wellness through the Wellness Wheel framework, encompassing physical, emotional, intellectual, social, spiritual, occupational, and environmental well-being. Methodologically, the review synthesizes empirical studies, systematic reviews, and meta-analyses from the last 20 years, extracted from databases such as PubMed, PsycINFO, Scopus, Web of Science, and Google Scholar, to construct a comprehensive understanding of how team sports contribute to holistic student development. Our findings highlight team sports as a vital component of educational and wellness programs, significantly enhancing not just physical health but also emotional stability, cognitive performance, social skills, spiritual enrichment, and environmental awareness. The review underscores the necessity of integrating team sports into educational curricula to promote a balanced and comprehensive approach to student well-being. It also identifies existing gaps in literature, particularly the need for further research on enhancing inclusivity and accessibility in team sports, ensuring that all students can benefit from their wide-ranging impacts. This study advocates for strategic initiatives to incorporate team sports in educational settings, emphasizing their essential role in cultivating a well-rounded, healthy, and inclusive student body.

The Mine Internet of Things (MIoT), as a key technology for reconstructing post-disaster communication networks, enables to realize the safety monitoring and controlling of the affected roadway. However, due to the challenging underground mine environment, the MIoT suffers from severe signal attenuation, vulnerable nodes, and limited energy, which result in low network reliability of the post-disaster MIoT. To improve the transmission reliability as well as to reduce energy consumption, a directional-area-forwarding-based energy-efficient opportunistic routing (DEOR) for the post-disaster MIoT is proposed. DEOR defines a forwarding zone (FZ) for each node to route packets toward the sink. The candidate forwarding set (CFS) is constructed by the nodes within the FZ that satisfy the energy constraint and the neighboring node degree constraint. The nodes in CFS are prioritized based on the routing quality evaluation by taking the local attributes of nodes into consideration, such as the directional angle, transmission distance, and residual energy. DEOR adopts a recovery mechanism to address the issue of void nodes. The simulation results validate that the proposed DEOR outperforms ORR, OBRN and ECSOR in terms of energy consumption, average hop count, packet delivery rate, and network lifetime.

Prime period sequences can serve as the fundamental tool to construct arbitrary composite period sequences. This is a review study of prime period perfect Gaussian integer sequence (PGIS). When cyclic group {1,2,…,N−1} can be partitioned into k cosets, where N=kf+1 is an odd prime number, the construction of a degree-(k+1) PGIS can be derived from either matching the flat magnitude spectrum criterion or making the sequence with ideal periodic autocorrelation function (PACF). This is a systematic approach of prime period N=kf+1 PGIS construction, and is applied to construct PGISs with degrees 1, 2, 3 and 5. However, for degrees larger than 3, matching either the flat magnitude spectrum or achieving the ideal PACF encounters a great challenge of solving a system of nonlinear constraint equations. To deal with this problem, the correlation and convolution operations can be applied upon PGIS of lower degrees to generate new PGIS with degree-4 and other higher degrees, e.g., 6, 7, 10, 11, 12, 14, 20 and 21 in this paper. In this convolution based scheme, both degree and pattern of a PGIS vary and can be indeterminant, which is rather nonsystematic compared with the systematic approach. The combination of systematic and nonsystematic schemes contributes the great efficiency for constructing abundant PGISs with various degrees and patterns for the associated applications.

The primary measure of the quality of sea surface temperature (SST) fields obtained from satellite-borne infrared sensors has been the bias and variance of matchups with co-located in-situ values. Because such matchups tend to be widely separated, these bias and variance estimates are not necessarily a good measure of small scale (several pixels) gradients in these fields because one of the primary contributors to the uncertainty in satellite retrievals is atmospheric contamination, which tends to have large spatial scales compared with the pixel separation of infrared sensors. Hence, there is not a good measure to use in selecting SST fields appropriate for the study of submesoscale processes and, in particular, of processes associated with near-surface fronts, both of which have recently seen a rapid increase in interest. In this study, two methods are examined to address this problem, one based on spectra of the SST data and the other on their variograms. To evaluate the methods, instrument noise was estimated in Level-2 VIIRS and AVHRR SST fields of the Sargasso Sea. The two methods provided very nearly identical results for AVHRR: along-scan values of approximately 0.18 K for both day and night and along-track values of 0.21 K also for day and night. By contrast, the instrument noise estimated for VIIRS varied by method, scan geometry and day-night. Specifically, daytime, along-scan (along-track), spectral estimates were found to be approximately 0.05 K (0.08 K) and the corresponding nighttime values of 0.02 K (0.03 K). Daytime estimates based on the variogram were found to be 0.08 K (0.10 K) with the corresponding nighttime values of 0.04 K (0.06 K). Taken together: AVHRR instrument noise is significantly larger than VIIRS instrument noise, along-track noise is larger than along-scan noise and daytime levels are higher than nighttime levels. Given the similarity of results and the less stringent preprocessing requirements, the variogram is the preferred method although there is a suggestion that this approach overestimates the noise for high quality data in dynamically quiet regions. Finally, simulations of the impact of noise on the determination of SST gradients show that on average the gradient magnitude for typical ocean gradients will be accurately estimated with VIIRS but substantially overestimated with AVHRR.

Biodiversity plays an important role in maintaining the ecological balance of the earth. The study of traditional knowledge related to biological resources is a hot issue in the field of international biodiversity conservation. Xishuangbanna is a key area of biodiversity and a cultural hotspot of international significance. According to the Technical Regulation for Classification, Investigation, and Inventory of Traditional Knowledge Relating to Biological Diversity issued by the Ministry of Ecology and Environment, we investigated and catalogued the traditional knowledge related to biodiversity of the Jino people who have lived in Xishuangbanna for generations, and collected 490 entries of traditional knowledge related to biodiversity of the Jino people. Drawing on the traditional knowledge diversity index calculation method proposed by Wang Guoping, the overall traditional knowledge α-diversity index of the Jino people is 0.63, indicating that the richness of the traditional knowledge of the Jinuo people is relatively high. The traditional culture related to biodiversity, the traditional knowledge related to agricultural genetic resources, and the traditional technology related to the sustainable utilization of biological resources are relatively rich and diverse. The diversity index is 0.86, 0.82 and 0.79 respectively. In addition, Xishuangbanna has invested a lot of energy in biodiversity protection, including the establishment of nature reserves, botanical gardens, zoos, ecological tea gardens and other species reserves, the promulgation of laws and policies related to biodiversity protection, and has achieved remarkable results in in-situ protection and ex-situ protection. On the basis of analyzing the progress and achievements of biodiversity conservation in Xishuangbanna, this study points out that Xishuangbanna faces challenges such as the loss of traditional knowledge, insufficient conservation efforts, and great changes in land use, and puts forward corresponding suggestions.

Diffuse cavernous hemangioma of the rectum (DCHR) is a rare benign lesion of vascular malformation. According to previous studies, the most reported major symptoms of DCHR are recurrent painless rectal bleeding or iron deficiency anemia[1][2][3][4][5][6]. We present a case of an 8Y11M boy who was diagnosed with DCHR by MRI. The patient underwent Laparoscopic-assisted transanal distal sigmoidectomy and sigmoido-anal anastomosis（Laparoscopic Swenson Procedure）, and recovered well. After the operation, the child had short-term fecal incontinence and loose stools, which returned to normal after half a year. Regardless of age and symptoms, early and correct diagnosis and treatment of DCHR and postoperative restoration of normal anal function are necessary. Laparoscopic Swenson procedure may be a good option for the treatment of DCHR.

Group-IV GeSn photodetectors (PDs) compatible with standard complementary metal-oxide-semiconductor (CMOS) processing have emerged as a new and non-toxic infrared detection technology to enable a wide range of infrared applications. The performance of GeSn PDs is highly dependent on the Sn composition and operation temperature. Here, we develop theoretical models to establish a simple rule of thumb, namely “GeSn-rule 23”, to describe GeSn PDs’ dark current density in terms of operation temperature, cutoff wavelength, and Sn composition. In addition, analysis of GeSn PDs’ performance shows that the responsivity, detectivity, and bandwidth are highly dependent on operation temperature. This rule provides a simple and convenient indicator for device developers to estimate the device performance at various conditions for practical applications.

An electrocardiograph (ECG) reflects the health of the human heart and is used to help diagnose arrhythmia and myocardial infarction(MI) in clinical practice. Early diagnosis of arrhythmia helps implement preventive measures and plays a crucial role in saving a patient's life. With the increasing demand of clinicians for ECG analysis technology, intelligent detection and diagnosis of ECG signals has become a more efficient means to assist physicians in diagnosing cardiovascular diseases. This paper introduces an ECG diagnosis approach based on an ensemble deep learning combination of CNN(convolutional neural network) and SLAP(stacked-long short term memory architecture for prediction) architecture. ECG data is denoised and further divided into single heartbeats to achieve data standardization and sample diversity. Adam optimizer and BCEwithlogitsloss multi-classification loss function were used to enhance the model effect, and the system achieved the classification effect of 99.3% average accuracy, 99.0% F1-value, and 99.2% sensitivity in MIT-BIH standard database classification. It also shows good generalization ability on the Tianchi data set.

This work aimed to study the thermal and crystalline properties of poly (1,4-phenylene sulfide)@carbon char nanocomposites. Coagulation-processed nanocomposites of polyphenylene sulfide were prepared using synthesized mesoporous nanocarbon of coconut shell as reinforcement. The mesoporous reinforcement was synthesized using a facile carbonization method. The investigation of the properties of nanocarbon was done by SAP, XRD, and FESEM analysis. The research was further propagated via the synthesis of nanocomposite by the addition of characterized nanofiller into poly (1,4-phenylene sulfide) at five different combinations. The coagulation method was utilized for the nanocomposite formation. The obtained nanocomposite was analyzed using FTIR, TGA, DSC, and FESEM analysis. The BET surface area and average pore volume of bio-carbon prepared from coconut shell residue were calculated to be 1517 m2/g and 2.51 nm respectively. The addition of nanocarbon to poly (1,4-phenylene sulfide) has led to an increase in thermal stability and crystallinity up to 6% loading of filler. The minimum achievable glass transition temperature is for 6 % doping of filler into the polymer matrix. It was established that the thermal, morphological, and crystalline properties have been tailored by synthesizing their nanocomposites with mesoporous bio-nanocarbon obtained from coconut shells. So, the loading of filler into poly (1,4-phenylene sulfide) can be optimized to enhance its thermoplastic properties for surface applications.

Dual quaternions have wide applications in automatic differentiation, computer graphics, mechanics and others. Due to its application in control theory, the matrix equation AXB=C has been extensively studied. However, there is currently limited information on matrix equation AXB=C over the dual quaternion algebra. In this paper, we provide the necessary and sufficient conditions for the solvability of the dual quaternion matrix equation AXB=C, and present the expression for the general solution when it is solvable. As an application, we derive the ϕ-Hermitian solutions for the dual quaternion matrix equation AXAϕ=C, where the ϕ-Hermitian extends the concepts of Hermiticity and η-Hermiticity. Lastly, we present a numerical example to verify the main research results of this paper.

The objective of this study is to design an optimal model predictive control (MPC) strategy using manipulated variables to control the production of a sufficient amount of hydrogen through low temperature autothermal reforming of dimethyl ether (DME), a reforming reaction performed using PdO/ZnO/γ-Al2O3 catalysts coated on honeycomb cordierite ceramics. Experiments and simulation have verified that the optimal activity temperature of the catalyst is 400 °C, and the hydrogen volume fraction in syngas is over 43%. In the implementation of the hydrogen production system, the MPC controller can precisely determine the feed rates of DME, high-purity air, and water based on the space state equation of the reformer, to achieve the anti-disturbance of the reformer temperature. Thus, the reduction of hydrogen yield and sintering of the catalyst as a result of overheating are prevented. As the static and dynamic performance of hydrogen production exhibits excellent tracking of the setpoints, an autonomous, automated, and reliable continuous system was designed to meet the desired hydrogen demand situation. This study shows that an autonomous, automated, and reliable continuous hydrogen production reforming system can be designed to actively respond to the on-board hydrogen usage situation.

Regeneratively cooled scramjet has already been successfully verified as propulsion device for hypersonic vehicle. As a result, dynamic process of flow and heat transfer in cooling channel is commonly occurred which may bring hazard and control difficulties for scramjet. To study transient flow and heat transfer process in cooling channel, a dynamic numerical model is established. Dynamic characteristics of flow and heat transfer under different conditions are calculated and discussed, which includes change of inlet fuel mass flow, heat flux and pressure working conditions. Results show that stable time of cooling channel outlet fuel temperature is related to the change rate of inlet mass flow and heat flux. The stable time of outlet fuel temperature under heat flux decreasing working conditions are about 12.5 s. The initial response of working pressure fluctuation will lead to fuel temperature fluctuation, which has little effect on wall temperature.

The calcium-sensing receptor (CAS), as a chloroplast thylakoid membrane protein, involved in the process of [Ca2+] ext-induced [Ca2+]cyt increase (CICI) in the plant. However, the underlying mechanism regulating this process is lacking. Furthermore, recent evidence suggests that CAS may perform additional roles in the plant. Here, we provide an update covering the multiple roles of CAS in stomatal movement regulation and calcium signaling in the plant. We also analysis the possible phosphorylation mechanism of CAS by light and discuss the role of CAS in abiotic stress (drought, salt stress) and biotic stresses (plant immune signaling). Finally, we provide a perspective for future experiments which are required to fill gaps in our understanding of the biological function of CAS in the plant.

Marek’s disease (MD) is an important neoplastic disease caused by serotype 1 Marek's disease virus (MDV-1), which results in severe economic losses worldwide. Despite vaccination practices that have controlled the MD epidemic, current increasing MD-suspected cases indicate the persistent viral infections circulating among vaccinated chicken farms in many countries. However, the lack of available information about phylogeny and molecular characterization of circulating MDV-1 field strains in Taiwan reveals a potential risk in MD outbreaks. This study investigated the genetic characteristics of 18 MDV-1 isolates obtained from 17 vaccinated chicken flocks in Taiwan between 2018 and 2020. Based on the sequences of the meq oncogene, phylogenetic analysis demonstrated that the circulating Taiwanese MDV-1 field strains were predominantly in a single cluster that showed high similarity with strains/isolates from countries of East Asian region. Because the isolated strains were obtained from CVI988/Rispens vaccinated chicken flocks and the molecular characteristics of the Meq oncoprotein showed the features like vvMDV and vv+MDV strains, the circulating Taiwanese MDV-1 field strains may have higher virulence compared with vvMDV pathotype. In conclusion, the presented data demonstrate the circulation of hypervirulent MDV-1 strains in Taiwan and highlight the importance of routine surveillance and precaution strategies in response to the emergence of enhanced virulent MDV-1.

Periodontitis is a progressive and inflammatory oral disease and results in the damage of the supporting tissues of teeth. Peroxiredoxin6 (PRDX6) is an antioxidant enzyme and has been identified as a regulator in redox balance. This study aimed to investigate whether PRDX6 could protect human gingival fibroblasts (HGFs) from lipopolysaccharide (LPS) induced inflammation and its mechanisms. Here, both inflamed and non-inflamed human gingival tissues were collected to assess the expression of PRDX6 and NRF2 by Immunohistochemistry and Western blotting. Furthermore, HGFs were stimulated with LPS, MJ33 (PRDX6 phospholipase A2 inhibitor), or ML385 (NRF2 inhibitor). The expression levels of inflammatory cytokines were measured by RT-qPCR and ELISA, and reactive oxygen species (ROS) was detected using DCFH-DA. PRDX6 was downregulated in inflamed gingival tissues. In HGFs, LPS induced inflammatory cytokines and ROS was upregulated in PRDX6 knockdown cells. Furthermore, co-treatment with MJ33 alleviated LPS-induced inflammatory cytokines and ROS, while inhibiting NRF2 upregulated those in HGFs. Therefore, this study provided a new mechanistic insight that PRDX6, regulated by the NRF2 signaling, alleviates LPS- induced periodontitis in human gingival fibroblasts.

Cs2NaInCl6 double perovskites, which have excellent photoelectric conversion properties and are non-toxic and lead-free, have recently attracted much attention. In particular, double perovskite quantum dots (QDs) are considered to be a promising material for optoelectronic device applications. Ligands such as oleic acid (OA) and oleylamine (OAm) are essential for the synthesis of perovskite QDs, but their roles on double perovskite QDs are not yet clear. In this study, we have investigated the binding of OA and OAm to Cs2NaInCl6 QDs through FTIR and NMR and their effects on the surface defect reduction and stability improvement for Cs2NaInCl6 QDs. We found that only OAm was bound to the QD surfaces while OA was not. The OAm has a great effect on photoluminescence quantum yield (PLQY) improvement by passivate the QD surface defects. The stability of the QDs was also investigated, and it was shown that OA played a significant role in the stability of the QDs. Our findings provide critical insights into the roles of the ligands for photophysical properties and stability of lead-free double perovskite QDs.

Schizophrenia (SCZ) is a severe mental disorder that may result in hallucinations, delusions, and extremely disordered thinking. How each cell type in the brain contributes to SCZ occurrence is still unclear. Here, we leveraged the human dorsolateral prefrontal cortex bulk RNA-seq data, then used the RNA-seq deconvolution algorithm CIBERSORTx to generate SCZ brain single-cell RNA-seq data for a comprehensive analysis to understand SCZ-associated brain cell types and gene expression changes. Firstly, we observed that the proportions of brain cell types in SCZ differed from normal samples. Among these cell types, astrocyte, pericyte, and PAX6 cells were found to have a higher proportion in SCZ patients (astrocyte: SCZ = 0.163, Control = 0.145, P.adj = 4.9×10-4; pericyte: SCZ = 0.057, Control = 0.066, P.adj = 1.1×10-4; PAX6 : SCZ = 0.014, Control = 0.011, P.adj = 0.014), while the L5/6_IT_CAR3 cells and LAMP5 cells are the exact opposite (L5/6_IT_Car3 : SCZ = 0.102, Control = 0.108, P.adj = 0.016; LAMP5 : SCZ = 0.057, Control = 0.066, P.adj = 2.2×10-6). Next, we investigated gene expression in cell types and functional pathways in SCZ. We observed chemical synaptic transmission dysregulation in two types of GABAergic neurons (PVALB and LAMP5), and immune reaction involvement in GABAergic neurons (SST) and non-neuronal cell types (endothelial and oligodendrocyte). Furthermore, we observed that some differential expression genes from bulk RNA-seq displayed cell-type-specific abnormal in the expression of molecules in SCZ. Finally, the cell types with the SCZ-related transcriptomic changes could be considered to belong to the same module since we observed two major similar coordinated transcriptomic changes across these cell types. Together, our results offer novel insights into cellular heterogeneity and the molecular mechanisms underlying SCZ.

Transition-metal-free synthesis of 4-pyrones via TfOH-promoted nucleophilic addition/cyclization of diynones and water has been developed. This transformation is simple, atom economical and environmentally benign, providing rapid and efficient access to substituted 4-pyrones.

The optimization of the production process of metal mines has been traditionally driven only by economic benefits while ignoring resource efficiency. However, it has become increasingly aware of the importance of resource efficiency since mineral resource reserves continue to decrease while the demand continues to grow. To better utilize the mineral resources for sustainable development, this paper proposes a multi-objective optimization model of the production process of metal mines considering both economic benefits and resource efficiency. Specifically, the goals of the proposed model are to maximize the profit and resource utilization rate. Then, the fast and elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) is used to optimize the multi-objective optimization model. The proposed model has been applied to the optimization of the production process of a stage in the Huogeqi Copper Mine. The optimization results provide a set of Pareto-optimal solutions that can meet varying needs of decision makers. Moreover, compared with those of the current production indicators, the profit and resource utilization rate of some points in the optimization results can increase respectively by 2.99% and 2.64%. Additionally, the effects of the decision variables (geological cut-off grade, minimum industrial grade and loss ratio) on objective functions (profit and resource utilization rate) were discussed using variance analysis. The sensitivities of the Pareto-optimal solutions to the unit copper concentrate price were studied. The results show that the Pareto-optimal solutions at higher profits (with lower resource utilization rates) are more sensitive to the unit copper concentrate prices than those obtained in regions with lower profits.

The electromagnetic inference is an issue from decades, where working for a better shielding material is still on-going. The purpose of this study is to review the existing methods in the formation of graphene, metal and polymer-based composites. Study indicates that in graphene and metal-based composites, the utilization of alternating deposition method showed the highest shielding effectiveness, whereas, in polymer-based composite, the utilization of chemical vapor deposition method showed highest shielding effectiveness. However, this review reveals that still there is a gap in the literature in terms of the selection of the method. Although there are various available methods which researchers adopt as per their convenience, none of the studies makes a comparison of the methods to form a similar composite. Therefore, as a future gap researcher needs to adopt various methods to form a single composite and then make a comparison of shielding effectiveness. This act will be useful for future researchers to select the appropriate method.

This paper is aimed at studying the temporal evolution of the surface displacements occurred over the past few years in the ocean-reclaimed platforms of the Shanghai megacity (China), which are mainly ascribable to consolidation processes of large dredger fills and alluvial deposits. With respect to previous analyses carried out over the same area, this work provides a joint multi-platform differential interferometry synthetic aperture radar (DInSAR) analysis, based on the application of the advanced Small BAseline Subset (SBAS) algorithm. This led us to retrieve long-term deformation time-series that are helpful for a better understanding of the on-going deformation phenomena. To this aim, we have exploited two sequences of SAR data collected by the ASAR/ENVISAT and by the COSMO-SkyMed (CSK) sensors, respectively, spanning the whole time period from 2007 to 2016. Unfortunately, the large time gap (of about three years) existing between the available ASAR/ENVISAT and CSK datasets gave rise to additional difficulties for their combination. Nevertheless, this problem has been faced by benefiting from the knowledge of a time-dependent model describing the temporal evolution of the expected deformations affecting the Shanghai ocean-reclaimed platforms.

Ultraviolet (UV) radiation has both harmful and beneficial effects on human health. It can cause skin damage and cancer, but also provides the primary source of vitamin D. Additionally, UV radiation affects energy metabolism in mice with metabolic diseases and has protective effects on hypertension and cardiovascular diseases.Metabolic Syndrome is a collection of metabolic dysfunctions such as dyslipidemia, hypertension, hyperglycemia, abdominal/central obesity, and insulin resistance. Chronic UVR exposure suppressed obesity and type 2 diabetes in high-fat diet-fed mice, while vitamin D supplementation did not replicate these effects. On the other hand, topical application of nitric oxide (NO) donors replicated UV effects on mice, and NO scavengers prevented the positive impact of UV. UVR may prevent the development of obesity and metabolic syndrome through mechanisms that depend on UVR-induced NO, not vitamin D. Exposure to sunshine has a protective impact on blood pressure and cardiovascular disease. Although lower vitamin D concentration is linked to increased hypertension and the incidence of CVD, oral vitamin D supplementation does not decrease blood pressure or the risk of CVD, indicating that vitamin D may not mediate the beneficial effects of sun exposure. Instead, NO plays a crucial role as an endogenous vasodilator, produced by the vascular endothelium. Solar UVA may release nitrogen oxides from skin storage into the bloodstream, lowering blood pressure and cardiovascular mortality.In conclusion, UVR exposure could be a promising non-pharmacological intervention for metabolic syndrome, hypertension, and CVD prevention, and NO may play a crucial role in mediating these effects. Further research is needed to explore the precise mechanisms and identify the optimal doses and exposure times of UVR.

A series of novel N-n-butyl-1,8-naphthalimide derivatives were synthesized via a three-step reaction involving nucleophilic substitution and acylation. All of the compounds were characterized by IR, ¹H NMR, ¹³C NMR, MS, and elemental analysis, and the crystal structure of N-n-butyl-4-[N’,N’-bis(2`,4`-dichlorobenzoyl)ethylamino]-1,8-naphthalimide was determined. The π-π stacking interactions and hydrogen bonds between the two molecular core planes (naphthalimide ring) and the van der Waals forces between the flexible n-butyl groups resulted in a 3D long-chain structure. The UV-vis and fluorescence properties of the title compounds were investigated. The results indicated that the monosubstituted 1,8-naphthalimide derivatives bearing an electron-donating group on the benzene ring or a structure with a larger conjugative effect exhibited enhanced fluorescence properties.

Newly build offshore wind farms (OWFs) render a collision risk between ships and installations. The paper proposed a real-time traffic monitoring method based on machine vision and deep learning technology to improve the efficiency and accuracy of the traffic monitoring system in the vicinity of offshore wind farms. Specifically, the method employs real automatic identification system (AIS) data to train a machine vision model, which is then used to identify passing ships in OWF waters. Furthermore, the system utilizes stereo vision techniques to track and locate the positions of passing ships. The method is tested in offshore water in China to validate its reliability. The results prove that the system sensitively detects the dynamic information of the passing ships, such as the distance between ships and OWFs, ship speed and course. Overall, this study provides a novel approach to enhancing the safety of OWFs, which is increasingly important as the number of such installations continues to grow. By employing advanced machine vision and deep learning techniques, the proposed monitoring system offers an effective means of improving the accuracy and efficiency of ship monitoring in challenging offshore environments.

Serine is widely involved in antioxidant synthesis, immune response, and fat metabolism. However, it remains unclear whether dietary serine supplementation affects fat deposition in the skeletal muscles of pigs. Thus, we explored the effects of dietary serine supplementation on growth performance, meat quality, and composition of gut microbes and their metabolites in growing-finishing pigs. Forty-eight boars weighing approximately 20 kg were fed either a basal diet or a basal diet supplemented with 0.15% serine. The results showed that dietary serine increased the daily weight gain and improved the antioxidant ability of pigs, as indicated by the decreased malondialdehyde content and increased glutathione and superoxide dismutase content. Pigs supplemented with serine had better meat quality, as shown by the lower drip loss and higher IMF content. Furthermore, dietary serine increased the relative abundance of Streptococcus and Lactobacillus and decreased the relative abundance of Clostridium_sensu_stricto_1 and Terrisporobacter. Differential microbial metabolites were mostly enriched in metabolic pathways related to lipid synthesis, such as alpha-linolenic acid metabolism and steroid hormone biosynthesis. Correlation analysis showed that the altered metabolites were closely related to the intestinal microbiota. In conclusion, our results suggested that serine serves as a potential additive for improving meat quality in growing-finishing pigs.

Formaldehyde (HCHO) is one of the most important carcinogenic air contaminants. However, the lack of global surface concentration of HCHO monitoring is currently hindering research on outdoor HCHO pollution. Traditional methods are either restricted to small areas or data- demanding for a global scale of research. To alleviate this issue, we adopted neural networks to estimate surface HCHO concentration with confidence intervals in 2019, where HCHO vertical column density data from TROPOMI, in-situ data from HAPs (harmful air pollutants) monitoring network and ATom mission are utilized. Our result shows that the global surface HCHO average concentration is 2.30 μg/m3. Furthermore, in terms of regions, the concentration in Amazon Basin, Northern China, South-east Asia, Bay of Bengal, Central and Western Africa are among the highest. The results from our study provides a first dataset of the global surface HCHO concentration. In addition, the derived confidence interval of surface HCHO concentration adds an extra layer for the confidence to our results. As a pioneer work in adopting confidence interval estimation into AI-driven atmospheric pollutant research and the first global HCHO surface distribution dataset, our paper will pave the way for the rigorous study on global ambient HCHO health risk and economic loss, thus providing a basis for pollutant controlling policies worldwide.

Soil erosion due to soil erosion is an important ecological impact factor. In order to further explore the impact and contribution of soil and water conservation measures on sand production and transport in the watershed, and also to provide a reference for soil erosion control, soil and water conservation and ecological environmental protection in the Yellow River Basin. In this paper, based on the measured data from the Henan Soil and Water Conservation Observatory in the Yellow River Basin, we select appropriate equations for quantifying soil erosion factor to calculate the rainfall erosion, topography, soil, vegetation and soil conservation measures in the basin, and then analyse the changes in soil erosion factor and the actual benefits of soil conservation measures in the basin. The results show that there is an increasing trend in the rainfall erosion force factor R in the Yellow River Basin; Soil erosion can be K value made the vertical loess > yellow clunamon soil, the overall change shows a decreasing trend, indicating that erosion control has produced results and that attention should be paid to erosion control in the lithosol region in the future; Since the slope lengths of the runoff plots are laid out consistently with the same LS values for both topographic factors, soil erosion is severely increased when the slope exceeds 20°. The C value of natural vegetation is small, while the C value of bare land is large. The authorities should continue to promote the return of farmland to forests and grasses and pay attention to the self-regulation and restoration of ecosystems; There is an overall decreasing trend in the P value of the soil and water conservation measures factor, the soil and water conservation measures have been effective in providing good protection.

With increasing demand from unmanned driving and robotics, more attention has been paid to point cloud-based 3D object accurate detection technology. However, due to the sparseness and irregularity of the point cloud, the most critical problem is how to utilize the relevant features more efficiently. In this paper, we proposed a point-based object detection enhancement network to improve the detection accuracy in the 3D scenes understanding based on the distance features. Firstly, the distance features are extracted from the raw point sets and fused with the raw features about reflectivity of the point cloud to maximizing the use of information in point cloud. Secondly, we enhanced the distance features and raw features that we collectively refer to them as self-features of the key points in Set Abstraction (SA) layers with the self-attention mechanism, so that the foreground points can be better distinguished from the background points. Finally, we revised the group aggregation module in SA layers to enhance the feature aggregation effect of key points. We conducted experiments on the KITTI dataset and nuScenes dataset and the results show the enhancement method proposed in this paper has excellent performance.

Abstract: Image aesthetic assessment (IAA) with neural attention has made significant progress due to its effectiveness in object recognition. Current studies have shown that the features learned by convolutional neural networks (CNN) at different learning stages indicate meaningful information. The shallow feature contains the low-level information of images and the deep feature perceives the image semantics and themes. Inspired by this, we propose a visual enhancement network with feature fusion (FF-VEN). It consists of two sub-modules, the visual enhancement module (VE module) and the shallow and deep feature fusion module (SDFF module). The former uses an adaptive filter in the spatial domain to simulate human eyes according to the region of interest (ROI) extracted by neural feedback. The latter not only takes out the shallow feature and the deep feature by transverse connection, but also uses a feature fusion unit (FFU) to fuse the pooled features together with the aim of information contribution maximization. Experiments on standard AVA dataset and Photo.net dataset show the effectiveness of FF-VEN.

Quantitative structure-activity relationship (QSAR) model is adopted to study the relationship between the chemical and physical properties of various substances and the structure. Through QSAR studies, the internal relationship between the invisible structure and the activity can be obtained. In this paper, a novel chaos-enhanced accelerate particle swarm algorithm (CAPSO) is proposed, which is used to molecular descriptors screening and optimization of the weights of back propagation artificial neural network (BP ANN). Then, the QSAR model based on CAPSO and BP ANN is put forward, hereinafter referred to as CAPSO BP ANN model. The prediction experiment showed that the CAPSO algorithm is a reliable method for screening molecular descriptors and the five molecular descriptors obtained by CAPSO algorithm could well characterize the molecular structure of each compound in pKa prediction. The experimental results also showed the CAPSO BP ANN model has a good performance in predicting the pKa values of various compounds, the absolute mean relative error, root mean square error, and square correlation coefficient are respectively 0.5364, 0.0632, and 0.9438, indicating the higher prediction accuracy and correlation. The proposed hybrid intelligent model can be applied in all kinds of engineering design, prediction of physical and chemical properties and intelligent calculation.

The escalating frequency and severity of global wildfires necessitate an in-depth understanding and monitoring of wildfire smoke impacts, specifically its contribution to fine particulate matter (PM2.5). We propose a data-fusion method to study wildfire contribution to PM2.5 using satellite-derived smoke plume indicators and PM2.5 monitoring data. Our study incorporates two types of monitoring data, the high-quality but sparse Air Quality System (AQS) stations and the abundant but less accurate PurpleAir (PA) sensors that are gaining popularity among citizen scientists. We propose a multi-resolution spatiotemporal model specified in the spectral domain to calibrate the PA sensors against accurate AQS measurements, and leverage the two networks to estimate wildfire contribution to PM2.5 in California in 2020 and 2021. A Bayesian approach is taken to incorporate all uncertainties and our prior intuition that the dependence between networks, as well as the accuracy of PA network, vary by frequency. We find that 1% to 3% increase in PM2.5 concentration due to wildfire smoke, and that leveraging PA sensors improves accuracy.

Nowadays, we use social networks such as Twitter, Facebook, WeChat and Weibo as means to communicate with each other and get to know others. Gradually social networks has become indispensable in our everyday life, and we cannot absolutely imagine what the daily life would be like without social networks. Through social networks, we can access friends' opinions and behaviors easily and are influenced by them in turn. Thus, an effective algorithm to find the top-K influential nodes (the problem of influence maximization) in the social network is critical for various downstream tasks such as viral marketing, anticipating natural hazards, reducing gang violence, public opinion supervision etc. Solving the problem of influence maximization in real-world propagation scenarios often involves estimating influence strength (influence probability between two nodes), which cannot directly observed. To estimate influence strength, conventional approaches propose various humanly-devised rules to extract features of user interactions, the effectiveness of which heavily depends on domain expert knowledge. Besides, they are often applicable for special scenarios or specific diffusion models. Consequently, they are difficult to be generalized into different scenarios, diffusion models and even domains. Inspired by the powerful ability of neural networks in the field of representation learning, we design a deep hierarchical network embedding model HGE to map nodes (with attributes) into latent space automatically. In general, HGE takes an attributed social network as the input for learning latent network representation of each node, incorporating hierarchical community structure, node attributes and general network structure into a unified deep generative framework. Then, with the leaned latent representation of each node, we propose a HGE-GA algorithm to predict influence strength and compute the top-K influential nodes through a greedy-based maximization algorithm. Extensive experiments on real-world attributed networks demonstrate the outstanding superiority of the proposed HGE model and HGE-GA algorithm compared with the state-of-the-art methods, verifying the effectiveness of the proposed model and algorithm.

The Loess Plateau is an important region for vegetation restoration in China, however, changes in soil organic carbon (SOC), soil nutrients, and stoichiometry after restoration in this vulnerable ecoregion are not well understood. Typical restoration types, including orchardland (OL), grassland (GL), shrubland (SL), and forestland (FL) were chosen to examine changes in the stocks and stoichiometry of SOC, soil total nitrogen (TN), and soil total phosphorus (TP) at different soil depths and recovery times. Results showed that SOC stocks first increased and then stabilized in OL, GL, and SL at 0–30 cm depth, while in FL, stocks gradually increased. Soil TN stocks first increased and then decreased in OL, SL, and FL with vegetation age at 0–30 cm depth, while soil TP stocks showed little variation between restoration types. In the later stages of restoration, the stocks of SOC and soil TN at 0–30 cm soil depth were still lower than those in natural grassland (NG) and natural forest (NF). The overall C:N, C:P, and N:P ratios increased with vegetation age. Additionally, the SOC, soil TN and soil TP stocks, and C:N, C:P, and N:P ratios decreased with soil depth. The FL had the highest rate of change in SOC and soil TN stocks, at 0-10 cm soil depth. These results indicate a complex response of SOC, soil TN, and soil TP stocks and stoichiometry to vegetation restoration, which could have important implications for understanding C, N, and P changes and nutrient limitations after vegetation restoration.

Today, we are all threatened by an unprecedented pandemic: COVID-19. How different is it from other coronaviruses? Will it be attenuated or become more virulent? Which animals may be its original host? In this study, we analyzed 377 publicly available complete genome sequences for the COVID-19 virus, the previously known flu-causing coronaviruses (HCov-229E, HCov-OC43, HCov-NL63 and HCov-HKU1) and the lethal, pathogenic P3/P4 viruses, SARS, MERS, Victoria, Lassa, Yamagata, Ebola, and Dengue. We found strong similarities between the current circulating COVID-19 and SARS and MERS, as well as COVID-19 in rhinolophines and pangolins. On the contrary, COVID-19 shares little similarity with the flu-causing coronaviruses and the other P3/P4 viruses. Strikingly, we observed divergence of COVID-19 strains isolated from human hosts has steadily increased from December 2019 to March 2020, suggesting COVID-19 is actively evolving in human hosts. From all existing human COVID-19 genome sequences, we calculated the first common model that represents the shared sequences of the human COVID-19 strains, which provides important information for vaccine and antibody development. Geographic and time-course analysis of the evolutionary trees of the human COVID-19 reveals possibly heterogeneous evolutional paths among strains from 21 countries. This finding has important implications to the management of COVID-19 and the development of vaccines.

Our aim was to evaluate efficacy and safety of 30mL CaO alone or plus Asc in bowel preparation before colonoscopy. Two hundred and forty six patients were allocated randomly to ingest 2L PEG with 30mL CaO, 1L PEG with 30mL CaO plus 5g Asc, or 3L PEG. We used Boston Bowel Preparation Scale (BBPS) to evaluate bowel preparation efficacy. We also determined other outcomes such as procedure time, polyp or adenoma detection rate and adverse events (AEs). Of 282 patients recruited, 36 were excluded. Groups were matched for baseline characteristics except weight (P = 0.020) and body mass index (BMI) (P = 0.003). Patient’s satisfaction were higher in 2L PEG-CaO (P = 0.016) and 1L PEG-CaO-Asc groups (P = 0·017). Patients’ compliance was 67.5%, 71.4% and 80.5% in 3L PEG, 2L PEG-CaO and 1L PEG-CaO-Asc groups (P = 0.014). Adequate bowel preparation rate was 75%, 78.57% and 53.66% in 3L PEG, 2L PEG-CaO and 1L PEG-CaO-Asc groups (P = 0.021). There were no differences in terms of remaining outcomes. Despite an increase in patients’ satisfaction and compliance, 1L PEG-CaO-Asc significantly decreased adequate bowel preparation rate. However, 2L PEG-CaO improved the patients' satisfaction and compliance and increased adequate bowel preparation rate.

We have designed cell penetrating peptides that target the leucine zipper transcription factors ATF5, CE-BPB and CEBPD and that promote apoptotic death of a wide range of cancer cell types, but not normal cells, in vitro and in vivo. While such peptides have the potential for clinical application, their mechanisms of action are not fully understood. Here, we show that one such peptide, Dpep, compromises glucose uptake and glycolysis in a cell-context-dependent manner (in about 2/3 of cancer lines assessed). These actions are dependent on induction of tumor suppressor TXNIP (thioredoxin interacting protein) mRNA and protein. Knockdown studies show that TXNIP significantly contributes to apoptotic death in those cancer cells in which it is induced by Dpep. The metabolic actions of Dpep on glycolysis led us to explore combinations of Dpep with clinically approved drugs metformin and atovaquone that inhibit oxidative phosphorylation and that are in trials for cancer treatment. Dpep showed additive to synergistic activities in all lines tested. In summary, we find that Dpep induces TXNIP in a cell-context-dependent manner that in turn sup-presses glucose uptake and glycolysis and contributes to apoptotic death of a range of cancer cells.