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Calcium (Ca2+), a second messenger, plays a crucial role in plant growth and development as well as in responding to biotic and abiotic stresses. In this work, we explored the role of exogenous calcium in alleviating cold stress and examined the relationship between calcium chloride (CaCl2) and calcium channel blockers, lanthanum chloride (LaCl3), in tea plants under cold stress at the physiological and transcriptional levels. Exogenous Ca2+ partially offsets the negative impacts of cold stress which increased the tolerance of tea plants by significantly raising the photochemical efficiency of PSII, protective enzyme activities, and the ABA content, which reduced the relative electrical conductivity (REC) level and the malondialdehyde (MDA) concentration. At the transcriptome level, exogenous Ca2+ significantly enhanced the expression of key genes involved in cold response pathways. Nevertheless, LaCl3 treatment not only significantly inhibited the activities of antioxidant enzymes including superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT), but also increased cold damage. This study aims to provide essential insight into the role of exogenous Ca2+ in tea plants responding to cold stress, and to better understand the molecular mechanisms that facilitate Ca-mediated cold tolerance. [ABSTRACT FROM AUTHOR]

Compared to conventional energy sources, wind power is a clean energy source with high intermittence and uncertainty. As a system that converts wind energy into electricity, wind farms inevitably face severe reliability issues. In this paper, based on reliability theory, a new reliability modeling method for wind farms is proposed. Firstly, a belief reliability model for wind farms is constructed. Then, a power generation model based on two-directional rotor equivalent wind speed is established to represent the wind farm performance in the belief reliability model. Finally, several numerical studies are conducted to verify the power generation model under different wind speeds and directions, to demonstrate the belief reliability model with different levels of uncertainty, and to compare the belief reliability considering two-directional rotor equivalent wind speed with other methods. [ABSTRACT FROM AUTHOR]

A specialized hoe opener was engineered for no-till systems to apply substantial amounts of wheat seeds and granular fertilizers, effectively suppressing early stage weeds. This distinctive hoe opener plants wheat seeds within a 120 mm wide horizontal band, positioning granular fertilizers precisely at the band's center, all accomplished in a single pass. Notably, the design excels at covering the fertilizer with soil aggregates, compacting it through a wheat separator, and concurrently depositing wheat seeds from above. Our primary research objectives centered on achieving a consistent seedbed post-fertilizer application and ensuring a uniform distribution of wheat seeds within the horizontal band. The DEM (Discrete Element Method) was exploited to optimize the hoe opener's parameters. Through extensive simulations and comparisons with experimental outcomes, an optimal wing orifice AB length of 60 mm was identified, effectively covering granular fertilizers with soil aggregates and achieving compaction through the wheat separator. Furthermore, parameters of the wheat seed separator's hump were fine-tuned using the Box–Behnken algorithm, resulting in an optimal dimension of 40 mm for the top radius (A), 140 degrees for the top angle (B), and 90 mm for the bottom length (C). [ABSTRACT FROM AUTHOR]

To detect the moisture of dried Goji (Lycium barbarum L.) berries nondestructively, a near-infrared (NIR) hyperspectral imager was used for experiments. NIR hyperspectral data were obtained and processed by standard normal variate (SNV) calculation using the MATLAB software v.R2016a. On the basis of the actual moisture of dried Goji berries, the predicted moisture was obtained based on the partial least squares (PLS) algorithm and a prediction model for the moisture of dried goji berries was established. It was found that the moisture of dried Goji berries was responsive to the NIR hyperspectral imager. The established prediction model could accurately predict the moisture of dried goji berries, and its R2-value was 0.9981. The results provide a theoretical basis for the design of non-destructive moisture-detecting equipment for dried Goji berries. [ABSTRACT FROM AUTHOR]

Simple Summary: ACSL4 is an enzyme involved in the intracellular conversion of long-chain fatty acids and coenzyme A into fatty-acid coenzymes. It plays a vital role in various biological processes, including maintaining cell membrane structure, energy metabolism, and lipid metabolism. Recent studies have shed light on the involvement of ACSL4 in cell death pathways, autophagy regulation, and the development of human diseases. These findings position ACSL4 as a potential therapeutic target. This review provides an overview of the fundamental structure and mechanisms regulating ACSL4 at both the gene and protein levels, emphasizing its diverse biological functions. Additionally, we discuss the role of ACSL4 in different regulated cell death modalities, including apoptosis and ferroptosis, as well as its involvement in autophagosome formation. Furthermore, we explore potential modulators targeting ACSL4 and emphasize the importance of further research to comprehensively understand the clinical impact of ACSL4 in regulating various pathological conditions. By addressing concerns regarding the systemic impact of therapeutic approaches targeting ACSL4, we aim to pave the way for the development of effective treatments for human diseases. Lipid metabolism, cell death, and autophagy are interconnected processes in cells. Dysregulation of lipid metabolism can lead to cell death, such as via ferroptosis and apoptosis, while lipids also play a crucial role in the regulation of autophagosome formation. An increased autophagic response not only promotes cell survival but also causes cell death depending on the context, especially when selectively degrading antioxidant proteins or organelles that promote ferroptosis. ACSL4 is an enzyme that catalyzes the formation of long-chain acyl-CoA molecules, which are important intermediates in the biosynthesis of various types of lipids. ACSL4 is found in many tissues and is particularly abundant in the brain, liver, and adipose tissue. Dysregulation of ACSL4 is linked to a variety of diseases, including cancer, neurodegenerative disorders, cardiovascular disease, acute kidney injury, and metabolic disorders (such as obesity and non-alcoholic fatty liver disease). In this review, we introduce the structure, function, and regulation of ACSL4; discuss its role in apoptosis, ferroptosis, and autophagy; summarize its pathological function; and explore the potential implications of targeting ACSL4 in the treatment of various diseases. [ABSTRACT FROM AUTHOR]

To explore the mixed traffic characteristics of vehicles and aircraft on the airport surface and solve the problem of real-time conflict detection at key intersections. According to the actual taxiing procedures and airport control rules in China, this paper focus on abstracting the mixed motion process of aircraft and vehicles in the maneuvering area, defining the convergent cross-safety operation scenario. To quantify the driver's attention to safety separation and the degree of conservatism in adjusting speed, the vehicle deceleration rate and acceleration rate are defined with α as the exponent. Under the same spacing, the vehicle deceleration rate is directly proportional to α, and α is named the vehicle safety sensitivity. At the same time, the rules of speed change of vehicles and aircraft will be designed, and a convergent operation model of aircraft and vehicles will be proposed. Based on real-time speed and separation dynamic assessment of safety and efficiency under different traffic strategies, the computer simulation results show that vehicle safety sensitivity and deceleration rules determine the sequence of vehicles and aircraft when they are passing through in the short term and can affect the proportion of mixed traffic flow in the long run. The safety probability of vehicles passing the intersection first is negatively correlated with vehicle safety sensitivity, while the safety probability of aircraft passing the intersection first is correlated positively with vehicle safety sensitivity. The efficiency of passing without conflict with mixed traffic has an inverse relationship with vehicle safety sensitivity. When the vehicle safety sensitivity takes the value in the interval [0.4, 0.6], a mixed traffic flow with higher safety and efficiency, better stability, and a balanced ratio of locomotives can be obtained. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the effects of a biological nitrification inhibitor on nitrous oxide emission and rice yield quality in paddy soils and its effects on denitrifying the bacteria of nosZ, nirK, and nirS types. Two treatments were performed: (1) using a local conventional fertilizer as the control CK; (2) using the partial application of a conventional fertilizer + biological nitrification inhibitor as SW. N2O emission was measured using gas chromatography; qPCR amplification was performed using primers for the targeted functional genes, nosZ, nirS, and nirK, and denitrifying functional gene abundance and denitrifying microbial community structure were analyzed using fluorescence quantification and high–throughput sequencing, respectively. The results reveal that the biological nitrification inhibitor resulted in a 41.83% reduction in N2O, relative to the normal fertilizer treatment. Meanwhile, rice yield increased by 15.45% and related quality indexes were also improved. This can promote the reproduction of bacteria with the nosZ gene while inhibiting the growth of bacteria with nirS and nirK genes. The core bacteria, Nitrosospira, Rhodanobacter, Bradyrhizobium, Tardiphaga, Rhodopseudomonas, and Paracoccus, positively correlated with N2O emissions, while core bacteria Azospirillum, Burkholderia, and Mesorhizobium negatively correlated with N2O emissions. Therefore, the application of a biological nitrification inhibitor could be an effective measure to promote rice yield and quality, reduce N2O emissions, and affect key denitrifying bacteria. [ABSTRACT FROM AUTHOR]

As a maintenance strategy to reduce unexpected failures and enable safe operation, condition-based maintenance (CBM) has been widely used in recent years. The maintenance decision criteria of CBM in the literature mostly originate from statistical failure data or degradation states, few of which can directly and effectively reflect the current state and analyze condition monitoring data, maintenance measures, and reliability together at the same time. In this paper, we introduce the performance margin as a decision criterion of CBM. We propose a condition-based maintenance optimization method using performance margin. Considering a CBM optimization problem for a degrading and periodically inspected component, a newly developed performance margin degradation model is established when three different maintenance measures become involved. Maintenance measure effect factors, maintenance decision vectors, and maintenance measure threshold vectors are developed to update the degradation model. And to build a maintenance optimization model, both cost and loss related to maintenance decision problems and reliability obtained by performance margin have been taken into consideration. Finally, a numerical example is provided to illustrate the proposed optimization method. [ABSTRACT FROM AUTHOR]

This paper copes with a joint Location-Allocation-Inventory problem in a three-echelon base-level spare part support system with epistemic uncertainty in uncertain demands of bases. The aim of the paper is to propose an optimization model under the uncertainty theory to minimize the total cost, which integrates crucial characterizations of the inventory control decisions and the location-allocation scheme arrangement under a periodic review order-up-to-S (T, S) policy. Uncertainty theory is introduced in this paper to characterize epistemic uncertainty, where demands are treated as uncertain variables and stockout loss is represented by value-at-risk in uncertain measurement. To solve the original uncertain optimization model, an equivalent deterministic model is derived and addressed by an improved bilevel genetic algorithm. Moreover, the proposed models and algorithm are encoded into numerical examples for supply chain programming. The results highlight the applicability of the model and the algorithm's effectiveness in approaching the optimal solution compared with traditional genetic algorithm. Sensitivity analyses are further made for the impacts of review time and inventory capacity on different cost components. [ABSTRACT FROM AUTHOR]

Regulated cell death (RCD) is a signal-controlled process that not only eliminates infected, damaged, or aged cells but is also implicated in a variety of pathological conditions. The process of RCD is regulated by intracellular proteins that undergo varying levels of post-translational modifications, including mono- or polyubiquitination. Functionally, ubiquitination can affect protein abundance, localization, and activity. Like other post-translational modifications, ubiquitination is a dynamic and reversible process mediated by deubiquitinases, a large class of proteases that cleave ubiquitin from proteins and other substrates. The balance between ubiquitination and deubiquitination machinery determines cell fate under stressful conditions. Here, we review the latest advances in our understanding of the role of deubiquitinases in regulating the main types of RCD, including apoptosis, necroptosis, pyroptosis, and ferroptosis. This knowledge may contribute to identifying new protein degradation-related prognostic markers and therapeutic targets for human disease. [ABSTRACT FROM AUTHOR]

As an important Ca2+ sensor, calmodulin (CaM) and calmodulin-like protein (CML) play core roles in plant growth, development, and response to environmental stimuli. The CaM/CML gene family has been well characterized in various plant species, such as Arabidopsis thaliana, rice, and tomato; however, in the tea plant, the CaM/CML gene family has not been systematically and comprehensively characterized. In the present study, a total of 5 CsCaM and 60 CsCML proteins were identified from the tea plant genome, which were unevenly distributed on the 14 chromosomes of the tea plant. All the proteins contained two to four EF-hand domains. Meanwhile, an integrated analysis of physicochemical properties, sequence structure, motif identification, phylogeny, gene duplication, promoter cis-elements, and RNA-seq expression profiles in the CsCaM/CML gene family was performed. Transcriptome analysis revealed that CsCaM/CMLs were differentially expressed in different tissues of the tea plant, suggesting their potential roles in plant growth and development. The expression profiles associated with various stress treatments revealed that CsCaM/CML genes were involved in a wide range of abiotic factors, including cold and drought stress. Quantitative real-time PCR (qRT-PCR) was also used to validate the differences in expression under abiotic stress. Overall, these findings enhanced our understanding of CsCaM/CML genes and provided useful information for further research into their molecular functions in abiotic stress response, and in multiple physiological processes in the tea plant. [ABSTRACT FROM AUTHOR]

This paper investigates the stabilization for stochastic coupled Kuramoto oscillators (SCKOs) via nonlinear distributed feedback control. An original nonlinear distributed feedback control with the advantages of fast response, no steady-state deviation, and easy implementation is designed to stabilize SCKOs. With the help of the Lyapunov method and stochastic analysis skills, some novel sufficient conditions guaranteeing the stochastic stability for SCKOs are provided by constructing a new and suitable Lyapunov function for SCKOs. Finally, a numerical example is given to illustrate the effectiveness and applicability of the theoretical result. [ABSTRACT FROM AUTHOR]

A general sampling problem can be described by an Ellsberg urn, which is a mathematical model that assumes that balls are randomly drawn from an urn with an uncertain numbers of colored balls. This means that the Ellsberg urn is essentially an intricate model with simultaneous randomness and epistemic uncertainty, and this is the core problem discussed in this paper. Since practical sampling is usually processed in an intricate environment, the solution for an equivalent mathematical problem is necessary. Suppose an Ellsberg urn contains three unknown numbers of colored balls (i.e., a two-degrees-of-freedom Ellsberg urn), and three balls are randomly drawn from the urn. Compared to the published papers, this paper first constructs a chance space with two-dimensional uncertainty space and three-dimensional probability space to rigorously calculate the color distributions for those drawn balls by uncertainty theory, probability theory, and chance theory. Moreover, it is interesting to find that all cases of the drawn balls are symmetric in such a specific situation of a sample problem with epistemic uncertainty. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method for construction component classification by designing a feature-based deep learning network to tackle the automation problem in construction digitization. Although scholars have proposed a variety of ways to achieve the use of deep learning to classify point clouds, there are few practical engineering applications in the construction industry. However, in the process of building digitization, the level of manual participation has significantly reduced the efficiency of digitization and increased the application restrictions. To address this problem, we propose a robust classification method using deep learning networks, which is combined with traditional shape features for the point cloud of construction components. The proposed method starts with local and global feature extraction, where global features processed by the neural network and the traditional shape features are processed separately. Then, we generate a feature map and perform deep convolution to achieve feature fusion. Finally, experiments are designed to prove the efficiency of the proposed method based on the construction dataset we establish. This paper fills in the lack of deep learning applications of point clouds in construction component classification. Additionally, this paper provides a feasible solution to improve the construction digitization efficiency and provides an available dataset for future work. [ABSTRACT FROM AUTHOR]

The pilot is the main person in charge of taxiing safety while moving on the airport surface. The visual separation and speed adjustment are directly related to safety and efficiency of airport surface operation. According to the actual taxiing procedures and airport control rules in China, this paper proposes a novel microscopic simulation model based on the pilots' visual separation. This model is also built by refining the aircraft taxiing procedures at intersections. The observation range, the separation judgment, pilots' visual distance, rate of proximity and the intention for speed governing are discussed as parameters in the model. The rules for aircraft separation judgment, pilots' autonomous speed governing, and position updates are also set up and discussed. The proposed simulation can accurately simulate the acceleration and deceleration intentions under different motion trends while reproducing the motion process including the following acceleration, following deceleration and delayed deceleration caused by separation changes. The results demonstrate that the number of conflicts can be reduced to 50% based on visual separation adjustment of 50 s when the convergence angle is 30°. The pilot's visual distance is inversely proportional to the fluctuation range of the speed of the rear aircraft, the proximity rate of the front and rear aircraft and the probability of conflict. The simulation results of this model conform to the actual taxiing routes and control rules, which provides technical support for improving the safety level of airport surface operation and presents certain reference value and practicability. [ABSTRACT FROM AUTHOR]

Epistemic uncertainties, caused by data asymmetry and deficiencies, exist in resilience evaluation. Especially in the system design process, it is difficult to obtain enough data for system resilience evaluation and improvement. Mathematics methods, such as evidence theory and Bayesian theory, have been used in the resilience evaluation for systems with epistemic uncertainty. However, these methods are based on subjective information and may lead to an interval expansion problem in the calculation. Therefore, the problem of how to quantify epistemic uncertainty in the resilience evaluation is not well solved. In this paper, we propose a new resilience measure based on uncertainty theory, a new branch of mathematics that is viewed as appropriate for modeling epistemic uncertainty. In our method, resilience is defined as an uncertainty measure that is the belief degree of a system's behavior after disruptions that can achieve the predetermined goal. Then, a resilience evaluation method is provided based on the operation law in uncertainty theory. To design a resilient system, an uncertain programming model is given, and a genetic algorithm is applied to find an optimal design to develop a resilient system with the minimal cost. Finally, road networks are used as a case study. The results show that our method can effectively reduce cost and ensure network resilience. [ABSTRACT FROM AUTHOR]

Listeria monocytogenes is a major foodborne pathogen that can cause listeriosis in humans and animals. Andrographolide is known as a natural antibiotic and exhibits good antibacterial activity. We aimed to investigate the effect of andrographolide on two quorum-sensing (QS) systems, LuxS/AI-2 and Agr/AIP of L. monocytogenes, as well as QS-controlled phenotypes in this study. Our results showed that neither luxS expression nor AI-2 production was affected by andrographolide. Nevertheless, andrographolide significantly reduced the expression levels of the agr genes and the activity of the agr promoter P2. Results from the crystal violet staining method, confocal laser scanning microscopy (CLSM), and field emission scanning electron microscopy (FE-SEM) demonstrated that andrographolide remarkably inhibited the biofilm-forming ability of L. monocytogenes 10403S. The preformed biofilms were eradicated when exposed to andrographolide, and reduced surviving cells were also observed in treated biofilms. L. monocytogenes treated with andrographolide exhibited decreased ability to secrete LLO and adhere to and invade Caco-2 cells. Therefore, andrographolide is a potential QS inhibitor by targeting the Agr QS system to reduce biofilm formation and virulence of L. monocytogenes. [ABSTRACT FROM AUTHOR]

Resilience, the ability of a system to withstand disruptions and quickly return to a normal state, is essential for a low-Earth-orbit satellite communication system (LEO-SCS), as its large number of satellites, may encounter various disturbances. As a developing system with asymmetrical and insufficient data, it is with both aleatory and epistemic uncertainties, which renders existing resilience measures inapplicable. This paper utilizes uncertainty theory to define belief instantaneous availability, based on which a new resilience measure for the LEO-SCS is proposed. As the resilience is mainly determined by the dynamic and uncertain characteristics of an LEO-SCS, an uncertain satellite network evolution model is developed to describe its operating patterns, and an evaluation method is proposed to estimate its resilience. To illustrate our proposed uncertain theory-based resilience evaluation method, an LEO-SCS case with 48 satellites is studied, and its resilience values under different backup strategies are compared to assist in system design decisions. [ABSTRACT FROM AUTHOR]

Decision time, also known as choice reaction time, has been frequently discussed in the field of psychology. The Hick–Hyman Law (HHL) has been a fundamental model that has revealed the quantitative relationship between the mean choice reaction time of human and the information entropy of stimuli. However, the HHL is only focused on rule-based behavior in which rules for selecting response according to stimulus are certain and neglects to model the knowledge-based behavior in which choices are uncertain and influenced by human belief. In this article, we explored the decision time related to one basic knowledge-based behavior—uncertain binary choice, where selections of response are determined by human belief degrees but not by stimuli uncertainties. Two experiments were conducted: one for verifying the HHL and the other for uncertain binary choice. The former (experiment) demonstrated the effectiveness of the HHL, and the latter one indicated that there is an exponential relationship existing between decision time and entropy of belief degree in uncertain binary choice. Moreover, data obtained from both experiments showed that the disturbance term of decision time should not be seen as probabilistic as existing studies have assumed, which highlighted the necessity and advantage of uncertain regression analysis. [ABSTRACT FROM AUTHOR]

Gleditsia sinensis Lam. is a woody species that can tolerate various drought conditions and has been widely used in all aspects of life, including medicine, food, cleaning products, and landscaping. However, few reports have focused on the regulatory mechanism of the drought response in G. sinensis. To understand the metabolic basis of the Gleditsia sinensis drought response, different tissues were subjected to a rehydration/dehydration treatment and subsequently analyzed using untargeted and targeted metabolomics profiling depending on gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass (LC-MS) analytical platforms, respectively. Eight sugars, twelve amino acids, and twenty phenolic compounds were characterized. Metabolites showing a significant increase or decrease under drought stress were considered to be the key metabolites of interest for a better understanding of the drought tolerance mechanisms. The GC-MS-identified compounds were shown to undergo tissue-specific regulation in response to drought stress. Moreover, the C6C3C6 and C6C3 structures were identified by LC-MS as phenolic metabolites, which revealed their drought-response association. Significant physiological parameters were measured, including overall plant development, and the results showed that antioxidant systems could not be completely restored, but photosynthetic parameters could be recovered. The results of this research provide insight into biochemical component information mechanism of drought resistance in G. sinensis. [ABSTRACT FROM AUTHOR]

With the development of intelligent manufacturing technology, the material handling system (MHS) faces larger resilience challenges that threaten the sustainability of the system. To evaluate system resilience, the disturbance that the system may experience and the system response need to be identified in advance. This paper proposes a systematic and innovative approach to performing resilience-related disturbance analysis, i.e., disturbance mode and effects analysis (DMEA). Using this method, the possible disturbance modes, their occurrence probabilities, and the quantitative effects on system performance can be collected in a bottom-up process, and the information can be applied to further resilience quantification. Moreover, a quantitative system resilience evaluation framework for the MHS based on DMEA and the Monte Carlo method is presented. Production is defined as the key performance index of the system and is monitored to reflect the resilience behavior of the system after the disturbance occurs. The resilience of a tire tread handing system is quantified in our case study, and the results show the effectiveness of our DMEA-based resilience evaluation method. We also find that a reasonable system configuration and maintenance strategy can effectively improve system resilience, and a trade-off can be made between resilience and cost. [ABSTRACT FROM AUTHOR]