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Clean fire extinguishing systems applicable to the pottery jar liquor warehouse are in demand. In this study, taking 53vol% liquor as the research subject, fire models of various clean fire extinguishing systems comprising water mist, liquid carbon dioxide (LCO2) and liquid nitrogen (LN2) were established using a fire dynamic simulator to determine their fire extinguishing effect. A feasibility assessment of systems was performed under different fire source types, fire source sizes, and ventilation conditions. The fire extinguishing efficiency was analyzed in terms of the fire extinguishing time, oxygen concentration, and space temperature. The results showed that the success rate of the LCO2 and LN2 fire extinguishing systems was 100%, whereas the success rate of the water mist fire extinguishing system was 95%. In terms of reducing the oxygen concentration at the bottom of the space and the temperature in the space, the LCO2 system exhibited the best performance, followed by the LN2 system, and lastly the water mist. Under different ventilation conditions and fire source types, the LCO2 fire extinguishing system was least affected, whereas the effectiveness of the water mist fire extinguishing system reduced under natural ventilation conditions, and the extinguishing efficiency of the LN2 fire extinguishing system was affected by the fire source type. Overall, the LCO2 system presented more advantages in extinguishing fires in pottery jar liquor warehouses and can provide a new idea for the development and application of clean and efficient fire extinguishing systems. [ABSTRACT FROM AUTHOR]

In smart warehouses, logistics robots need to continuously execute tasks, and therefore traditional onetime multi-robot path planning cannot meet practical needs. To address this challenge, we proposed Prejudgment Conflicts Search (SPC) algorithm. The SPC algorithm is divided into two layers: the higher layer allocates tasks to robots based on priority rules, and the lower layer plans paths for these robots with an improved A* algorithm, which includes vertex and edge collision checks during path searching and effectively prevents collisions among robots. We simulated SPC and Conflict-Based Search (CBS) on random maps and warehouse maps. The results show that compared to CBS, SPC provides nearly optimal paths with a significantly reduced computation time. Additionally, as the number of robots increases, SPC exhibits better scalability, offering a practical solution for continuous multi-robot path planning in smart warehouses, with the potential to enhance logistics efficiency. [ABSTRACT FROM AUTHOR]

This paper introduces an multi-compartment open vehicle routing problem with time window (MCOVRPTW) arising in fresh products distribution, which doesn't require the finished service vehicles return to the distribution center. There are three types of fresh products to be delivered by the multi-compartment vehicles, and the objective aims to find the vehicles scheduling scheme with the lowest cost. For this problem, we established a mathematical model in which the capacity constraint of each compartment and time window constraint must be satisfied. Then, we proposed a hybrid genetic algorithm with some local search-based operators, called GA-LS, to solve it. Each individual in initial population was generated by the nearest neighborhood method to obtain highquality initial population. When a child population was built, the local search procedure was executed on each individual in the child population to enhance its quality. Finally, we carried out some experiments to evaluate the effectiveness of the proposed algorithm. According to the results, the proposed algorithm can yield better solutions compared with existing approaches. Meanwhile, the proposed algorithm reveals good stability and convergence. [ABSTRACT FROM AUTHOR]

Herein, the spatial evolution characteristics of high-level Grade A tourist attractions in the Yangtze River Delta (YRD) urban agglomeration, from 2001 to 2021, are studied by comprehensively applying the nearest neighbor index, kernel density analysis, standard deviation ellipse, and spatial autocorrelation. High-level Grade A tourist attractions are investigated using the random forest model as the driving mechanism of the spatial pattern. Results show that 1) the spatial distribution of high-level Class A tourist attractions in the YRD city cluster has grown to be an agglomeration, and the high-density areas have evolved from "point-like dispersion to regiment-like combination," gradually forming a B-shaped core density structure. 2) The spatial distribution comprises an overall "northwest–southeast" direction, a small counterclockwise rotation, the distribution of the center of gravity to the southwest migration, and the center of gravity from the territory of Suzhou City to the territory of Huzhou City. 3) The high-level Class A tourist attractions in the YRD city cluster as a whole show a strong positive spatial correlation, and the significantly clustered areas include three types: high-high (H-H), low-low (L-L), and low-high (L-H). 4) The spatial distribution of high, A-level tourist attractions in the YRD city cluster results from the combined action of the natural environment, resource endowment, socioeconomy, and policy background. Each element has a nonlinear and complex influence on the distribution of scenic spots. [ABSTRACT FROM AUTHOR]

Improving access to HIV/AIDS healthcare services is of great concern to government and policymakers striving to strengthen overall public health. How to reasonably allocate HIV/AIDS healthcare resources and maximize the equality of access to healthcare services across subdistrict areas has become an urgent problem to be solved. However, there is limited research on this topic in China. It is necessary to evaluate spatial accessibility to improve the accessibility and equity of HIV/AIDS healthcare services. In this study, the improved multi-modal two-step floating catchment area (2SFCA) and inverted 2SFCA (i2SFCA) methods are used to measure the spatial accessibility of HIV/AIDS healthcare services and the crowdedness of the healthcare sites in Shandong Province, China. Then, the theoretical supply and the optimal spatial distribution of resources are calculated and visualized by minimizing the accessibility gaps between demand locations. This study showed that the spatial accessibility of HIV/AIDS service resources in Shandong Province was concentrated and unevenly distributed, and the accessibility scores in the marginal areas of prefecture-level cities were significantly lower than those in other areas. Regions with a large number of doctors had significantly higher levels of spatial accessibility. The ART accessibility scores in the southwest of Shandong Province were higher than those in other regions. As the travel friction coefficient increased, the accessibility scores formed an approximately circular cluster distribution centered on the healthcare sites in geographical distribution. More ART drugs needed to be supplied in marginal areas and more doctors were needed to work on HIV/AIDS in urban areas to address the spatial distribution imbalance of HIV/AIDS healthcare services. This study profoundly analyzed the spatial accessibility of HIV/AIDS healthcare services and provided essential references for decision-makers. In addition, it gives a significant exploration for achieving the goal of equal access to HIV/AIDS healthcare services in the future. [ABSTRACT FROM AUTHOR]

The intelligent automated store warehouse (iZMS) research and development project was created to meet the expectations of a modern automatic store. The project concerns the development of the concept and pilot implementation of an automated store warehouse adapted to the autonomous and automatic sales of goods selected by retail chains. One of the aims of the iZMS project is to develop a scalable solution that allows for the simple adaptation of the iZMS to the needs of a potential customer, considering their requirements in terms of the quantity and variety of assortment offered within the iZMS. An important requirement in the use of the iZMS system is minimizing the customer waiting time for purchased products. This problem is related, among others, to the placement of products on the shelves of racks and will be solved in the optimizing process. Running optimization tasks requires a simulator that will mimic the features of a physical device faster than in real time to generate many proposals of the allocation of goods on storage racks in the shortest possible time and choose the best one, guaranteeing the shortest picking time of a representative basket of goods. A numerical simulator was developed to model the physical structures of food storage equipment and then simulate the sales process. Among the results obtained, the most important are the time parameters of individual operations, which will be used to optimize the placement of goods on storage racks. After analyzing the needs resulting from the usage of the iZMS system, we decided to develop a dynamic, deterministic simulator with discrete objects and perform the simulation with a controlled time increment and, in some cases, utilize elements of event-driven simulation, in which the flow of goods is simulated with first-in, first-out (FIFO) queues. Finally, verification of the numerical simulator with a physical model confirmed that it could be employed in optimization processes. [ABSTRACT FROM AUTHOR]

Considering that the determination of fire hazard zones in warehouses is not sufficiently researched and studied, this paper aims to present a new methodological approach concerning the mentioned issue. Based on the COPRAS multi-criteria decision-making method, a new method was developed for the precise determination of potential zones where there is a risk of fire. The advantage of the described method is that it allows the quick and easy determination of all-orientation fire risk zones. The method requires fewer hardware resources compared to the existing ones and enables the display of the warehouse space in the form of a 3D model with calculated fire hazard zones. The mentioned procedure represents the first step when planning the layout and arrangement in the warehouse itself. The effectiveness of the proposed method was confirmed through a suitable numerical example. [ABSTRACT FROM AUTHOR]

China is highly rich in diversity of Begonia, and in which Guangxi Zhuangzu Autonomous Region, following Yunnan province, has the second highest number of Begonia species. As a distribution center of Begonia sect. Coelocentrum, Guangxi already had 58 species recognized in this section. In this paper, Begonia ornithopedata, a new taxon of B. sect. Coelocentrum from southwestern Guangxi is described. With the bird-foot-shape lobed leaves, the new species is easily distinguished from any of other taxa, excepting few similarities only in leaf morphology of B. laminariae Irmsch. and B. circumlobata Hance. Its conservation status is assigned as the Endangered according to The Guidelines for Using the IUCN Red List Categories. [ABSTRACT FROM AUTHOR]

China's policies about reducing carbon emissions mainly focus on saving energy and reducing pollutant emissions. However, the carbon emissions of the logistics industry remain high. Thus, logistics companies should not only reduce distribution costs, but also consider the impact of carbon emissions when planning distribution routes. This paper studies the supermarket delivery distribution route planning problem considering carbon emissions. Aiming at the lowest economic operating cost composed of fixed cost, driving cost, and carbon emission cost, we propose a grey wolf optimized genetic algorithm to generate delivery route plans, where the social rank and hunting behavior of the grey wolf optimization algorithm are integrated into the selection operation of the genetic algorithm. Finally, a real case of a large third-party logistics enterprise in Beijing is studied. The case study results verify the effectiveness and applicability of the model and algorithm. [ABSTRACT FROM AUTHOR]

Aquaculture's role in addressing food security has grown, with a spotlight on Asian carp species. Polyculture, i.e. cultivating multiple fish species in a single system, is being increasingly adopted for its resource efficiency and economic benefits. This practice for Asian fish for food and ornamental purposes is gaining traction in Europe despite their invasive potential. Rising temperatures due to climate change offer an opportunity for thermophilic Asian carps (Hypophthalmichthys molitrix and Aristichthys nobilis). Using GIS modeling (Maxent), we identified the possible settlement of Asian carp in Northern Europe amidst climate change. We analyzed carp global distribution centers, assessed the potential carp spread in Europe, and evaluated their potential suitability for polyculture systems. By 2050, H. molitrix may extend its range to 58–62° N latitude, with a potential 1.7-fold habitat increase, while A. nobilis, which are more heat-tolerant, may move north to 52–58° N latitude, with a 1.3-fold potential increase. Despite the slight ecological differences in their native habitats, niche modeling indicates that these carp can occupy similar niches in Europe (proven statistically). The eventuality of using Asian species for polyculture in Europe presents both opportunities and challenges in the face of a changing climate as long as invasion risks are prevented. Envisaging such polyculture, yet very carefully for the protection of ecosystems, can help food security. [ABSTRACT FROM AUTHOR]

Virus infection is one of the major constraints in garlic production since the viruses are readily accumulated on vegetative propagation material (bulbs). This research aimed to detect garlic common latent virus (GCLV), shallot latent virus (SLV), onion yellow dwarf virus (OYDV), and leek yellow stripe virus (LYSV) infecting local garlic as seed bulb and imported garlic as consumption bulb. Seed bulb samples were obtained from seed breeders in several garlic growing centers in Indonesia. In contrast, consumption bulb samples were obtained from plant quarantine warehouses and three local markets in Bogor. Some bulb samples were used for morphological observations, and some were germinated in the laboratory until the leaves emerged. Leaves were collected for virus detection by RT-PCR using specific primers for GCLV, SLV, OYDV, and LYSV. Seed and consumption bulbs have differences in their morphological characteristics, especially in the type of neck hardness and the size of the bulb diameter. OYDV and LYSV infections were successfully detected in seed and consumption bulbs, while SLV was only found in consumption bulbs. Nucleotide sequence analysis showed that SLV from consumption bulbs formed one group, GCLV from seed bulbs formed one group, while OYDV and LYSV from seed and consumption bulbs were in different groups, indicating that the viruses came from different strains. Further research through high-throughput detection methods and providing virus-free planting material are needed to anticipate the spread of new strains of garlic viruses in Indonesia. [ABSTRACT FROM AUTHOR]

The goods collection and delivery process often relates to distribution logistics problems. The task is to deliver goods from warehouses to customers under specific circumstances. Efforts to optimize the process are largely aimed at reducing overall costs of goods transportation. Among the prominent algorithms for solving the basic type of the delivery (or collection) problem, which includes a single depot and a homogeneous vehicle fleet, is the algorithm developed by Clarke and Wright in 1964. This algorithm minimizes transportation costs by maximizing the savings achieved through merging multiple routes into one. This paper primarily aims to solve the pickup and delivery problem where the goods must be delivered and empty packaging collected in a single process. The request of a customer can be routed from the depot or from another customer. Similarly, the destination of the request may be the depot or another customer. Unlike the original version of the Clarke and Wright algorithm, the initial routes are created to satisfy delivery orders, and therefore, the same customer can occur in multiple routes. Consequently, a situation may arise in which two routes containing one or more common vertices must be combined during the calculation. Furthermore, these vertices need not be the outermost vertices of the routes. This situation cannot be addressed by using the original version of the Clarke and Wright algorithm, and that is why we propose its modification. Merging routes through inner vertices means that the cost savings depend on the configurations of the routes, and therefore, they cannot be calculated a priori. Instead, the dynamic savings matrix must be used. [ABSTRACT FROM AUTHOR]

In order to explore the thermal characteristics and thermal storage performance analysis of energy-saving phase change heat storage materials in buildings, taking the common exterior wall insulation composite wall structure in southwestern China as an example, the influence of insulation board structure thickness design on the total cost of residential air conditioning energy consumption and insulation board cost is studied, thus clarifying the concept and calculation origin of economic insulation thickness. The experimental results show that by drawing mathematical functions of energy consumption cost, total cost, and insulation material cost in the same 2-D co-ordinate, it is intuitively demonstrated that the minimization of total cost can be ensured when the insulation thickness is in an economic state, and the specific economic thickness can be accurately calculated through example data. Therefore, specific measures for improving external wall insulation from refined insulation structure design are proposed. It has been proven that the design of the exterior wall insulation layer structure is an important way to improve the overall energy-saving benefits of building exterior wall insulation. [ABSTRACT FROM AUTHOR]

The author proposes a phase change heat storage component combined with the light wall interior to improve the heat storage performance. Numerical modelling of the composite wall was performed using the finite element program COMSOL connected to Multiphysics simulation, and its accuracy was verified. In order to optimize the use of phase change data and the benefit of phase change temperature, the phase change of the heating device was carried out, and the difference in the development efficiency of the thermal storage performance of the two types of light walls was obtained from the ribs in the thermal phase phase exchanger compared. The results show that the long and thin fins adjust the temperature and flow field changes of the paraffin to the corresponding fin gap and improve the heat transfer rate, 44.8 and 26.3, respectively, the aerated concrete combined wall heat storage and heat release time, added short ribs known need, and the connected wall delay time is not affected by external heat. The mature thermal insulation and thermal insulation time of the polystyrene board composite wall were shortened by 20.8 and 52.9, respectively. Ribs are able to improve heating efficiency and retain heat in the broken walls of polystyrene panels. The author's research can provide a rationale for the design and use of phase change thermal storage. [ABSTRACT FROM AUTHOR]

A model of a single-server queuing-inventory system (QIS) with a limited waiting buffer for consumer customers (c-customers) and catastrophes has been developed. When a catastrophe occurs, all items in the system's warehouse are destroyed, but c-customers in the system are still waiting for replenishment. In addition to c-customers, negative customers (n-customers) are also taken into account, each of which displaces one c-customer (if any). The policy (s, S) is used to replenish stocks. If, when a customer enters, the system warehouse is empty, then, according to Bernoulli's trials, this customer either leaves the system without goods or joins the buffer. The mathematical model of the investigated QIS is constructed in the form of a continuous-time Markov chain (CTMC). Both exact and approximate methods for calculating the steady-state probabilities of constructed CTMCs are proposed and closed-form expressions are obtained for calculating the performance measures. Numerical evaluations are presented, demonstrating the high accuracy of the developed approximate formulas, as well as the behavior of performance measures depending on the input parameters. In addition, an optimization problem is solved to obtain the optimal value of the reorder point to minimize the expected total cost. [ABSTRACT FROM AUTHOR]

Large, powerful corporations were formerly solely and exclusively responsible for supplies, manufacturing, and distribution; however, the supply chain has undergone significant transformations over the last half-century. Almost all supply chain processes are currently outsourced, owing to the initiatives of cutting-edge, contemporary businesses. According to a compilation of studies, analysts, and news sources, the level of risk associated with modern supply chains is considerably higher than the majority of supply chain managers believe. Supply chain vulnerabilities continue to pose a substantial obstacle for a great number of organizations. Neglecting to adequately address these risks—encompassing natural disasters, cyber assaults, acts of terrorism, the credit crisis, pandemic scenarios, and war—could result in substantial reductions in metrics such as profitability, productivity, revenue, and competitive advantage. Unresolved concerns persist with respect to the risk assessment of the supply chain. The purpose of this article is to propose a framework for risk evaluation that can be efficiently applied to the evaluation of hazards within the supply chain. This research study significantly enhances the existing knowledge base by offering supply chain managers a pragmatic tool to evaluate their processes, regardless of the mathematical foundations or the variety of variables utilized in risk assessment. The outcomes of multiple aggregation methods are compared using a case study from an automotive EMS production; the conclusions are validated by risk and FMEA specialists from the same factory. [ABSTRACT FROM AUTHOR]

In the paper, we solved the problems regarding the improvement of the production process of allocating material to the inlet of a production hall using the Plant Simulation software in a selected company. The solved problematics are high costs for the shipping company, elimination of the necessity to transfer the semi-finished product from the external warehouse to the production hall and non-effective layout. We deal with the characteristics of the current state of the production process in the production company and create its model in Plant Simulation. Thereafter we propose solutions that can make that process more efficient. The software enables the comparison of complex production alternatives. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has changed people's shopping habits, causing them to turn to online shopping sites, especially on the internet. In the face of increasing order rates, it has become inevitable for manufacturers and suppliers to produce innovative solutions for collecting orders and delivering them on time. Companies/suppliers who had to use a limited number of manpower due to the pandemic have tried to solve this problem with the use of machinery. In this study, a new low-cost Order Picking and Distribution System application developed for the stages of order picking and distribution in the supply chain is described. This stage of the supply chain is the most problematic, time-consuming and costly. In general, more human resources are used in the proposed solutions. With this application, it is aimed to create a more efficient system in terms of time, manpower, warehouse space and cost. For this purpose, a prototype Order Picking and Distribution System application was designed, manufactured and implemented in real time. [ABSTRACT FROM AUTHOR]

It is important to improve the comprehensive performance of the ductile iron bars (DIBs) for the cylinder block of the extra high pressure hydraulic plunger pump and accelerate the industrial application. In this work, the LZQT600-3 DIBs with the diameter of 145 mm were prepared by the horizontal continuous casting (HCC) process, that is, LZQT600-3 HCCDIBs. The microstructure and room temperature tensile properties of different sections [left-edge (surface layer), left-1/2R (left half of the radius), and the center of the HCCDIBs] were studied. The results show that the spheroidization of LZQT600-3 HCCDIBs matrix from the left-edge, left1/2R to the center is at nodulizing grade II and above. As the cooling rate gradually decreases from surface to the center of the HCCIBs, the number of spheroidized graphite is gradually reduced, the size is gradually increased, the shape factor is decreased, and the pearlite content and lamellate spacing are increased. Along the horizontal direction of the section, the hardness of the material is distributed symmetrically around the center of the HCCDIBs. In the vertical direction, the hardness distribution in the center of the HCCDIBs is asymmetrical due to the gravity during the solidification process. Therefore, the microstructure in the lower part of the section solidifies relatively quickly. The left-edge has the best tensile mechanical properties, and the ultimate tensile strength, yield tensile strength and elongation are 597.3 MPa, 418.5 MPa and 9.6%, respectively. The tensile fracture belongs to the ductile-brittle hybrid fracture. The comprehensive performances of LZQT600-3 HCCDIBs meet the actual application requirements of ultra-high pressure hydraulic plunger pump cylinder. [ABSTRACT FROM AUTHOR]

About half of Luanda's population comprised enslaved people in the mid-nineteenth century. Although scholars have examined the expansion of slavery in Angola after the end of the transatlantic slave trade and the use of slavery to underpin the trade in tropical commodities, the labor performed by enslaved children has been neglected. This study explores the experiences of enslaved children working in Luanda during the era of the so-called "legitimate" commerce in tropical commodities, particularly between 1850 and 1869. It draws upon slave registers, official reports, and the local gazette, the Boletim Oficial de Angola, to analyze the means through which children were enslaved, the tasks they performed, their background, family connections, and daily experiences under enslavement. This paper argues that masters expected enslaved children to perform the same work attributed to enslaved men and women. After all, they saw captives as a productive unit irrespective of their age. [ABSTRACT FROM AUTHOR]

In this research, we establish the novel sin-G class, an innovative and comprehensive class of trigonometric distributions centered on the sine function. A sin-G class analytical approach comprises calculations for the probability density function and reliability indicators. Various estimation methods were presented to estimate the specified model parameters. Applying randomly created datasets and the provided estimating techniques, the behavior of these variables was investigated. Then, the focus is directed toward a specific member of this class, the novel sin-Lomax distribution, which is established with the Lomax distribution serving as the baseline. Exploring the innovative sin-Lomax distribution's inferential characteristics, the constructed distribution is then fitted to real datasets, demonstrating the actual application of the Sin-G class. [ABSTRACT FROM AUTHOR]

Business logistics encompasses the intricate planning, seamless implementation, and precise control of the efficient and effective movement and storage of goods, services, and associated information from their origin to their final consumption point. The strategic placement of facilities is intricately intertwined with business logistics, exerting a direct influence on the efficiency and cost-effectiveness of supply chain operations. In the realm of business logistics, decisions regarding the location of facilities, including warehouses, distribution centers, and manufacturing plants, assume a pivotal role in shaping the overarching logistics strategy. Warehouses, serving as pivotal nodes in the supply chain network, establish crucial links at both local and global markets. They serve as the nexus connecting suppliers and customers across the entire supply chain, thus constituting indispensable elements that significantly impact the overall performance of the supply chain. The optimal location of warehouses is paramount for efficient supply chains, ensuring minimized costs and bigger profits. The decision on warehouse location exerts a profound influence on investment costs, operational expenses, and the distribution strategy of a company, thereby playing a substantial role in elevating customer service levels. Hence, the primary objective of this paper is to propose a novel methodology grounded in the application of the Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA)-Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) methods for determining warehouse locations tailored to a logistics service provider (LSP) operating in the Serbian market. Through the definition of seven evaluation criteria based on a comprehensive literature review and expert insights, this study aims to assess five potential locations. The findings suggest that the proposed model offers great decision support for effectively addressing challenges akin to the one presented in this study. [ABSTRACT FROM AUTHOR]

Recently, multi-agent systems have become widespread as essential technologies for various practical problems. An essential problem in multi-agent systems is collaborative automating picking and delivery operations in warehouses. The warehouse commissioning task involves finding specified items in a warehouse and moving them to a specified location using robots. This task is defined as a spatial task-allocation problem (SPATAP) based on a Markov decision process (MDP). It is considered a decentralized multi-agent system rather than a system that manages and optimizes agents in a central manner. Existing research on SPATAP involving modeling the environment as a MDP and applying Monte Carlo tree searches has shown that this approach is efficient. However, there has not been sufficient research into scenarios in which all agents are provided a common plan despite the fact that their actions are decided independently. Thus, previous studies have not considered cooperative robot behaviors with different goals, and the problem where each robot has different goals has not been studied extensively. In terms of the cooperative element, the item exchange approach has not been considered effectively in previous studies. Therefore, in this paper, we focus on the problem of each robot being assigned a different task to optimize the percentage of picking and delivering items in time in social situations. We propose an action-planning method based on the Monte Carlo tree search and an item-exchange method between agents. We also generate a simulator to evaluate the proposed methods. The results of simulations demonstrate that the achievement rate is improved in small- and medium-sized warehouses. However, the achievement rate did not improve in large warehouses because the average distance from the depot to the items increased. [ABSTRACT FROM AUTHOR]

(1) Background: A current trend observed in the logistics sector is the use of Industry 4.0 tools to improve and enhance the efficiency of cargo handling processes. One of the popular solutions is an augmented reality system that supports operators in everyday tasks. The article aims to present design assumptions for implementing an augmented reality system to support air cargo handling at the warehouse. (2) Methods: Research was carried out based on a five-stage analytical procedure, aiming to analyze the current state and identify the potential for implementing the AR system. The following methods were used to collect data: co-participant observations, process analysis, direct interviews, analysis of internal documentation, and applicable legal regulations. (3) Results: The conducted research allowed for identifying information flows accompanying cargo flows and developing a project to automate selected information flows. The obtained results made it possible to identify operations for which the AR system's implementation will increase their effectiveness and efficiency. (4) Conclusions: The obtained results identified the need to develop a hybrid algorithm for arranging cargo in the warehouse and to build a system supporting self-verification of markings on air cargo. [ABSTRACT FROM AUTHOR]

Given the cross-border e-commerce import tariff and random demands, this study establishes a pricing decision model for cross-border e-commerce dual-channel supply chain, which is composed of domestic manufacturers and overseas retailers, so as to analyze the effects of import tariff and random demand on the pricing, demand and profit of cross-border e-commerce. According to the research, import tariffs have a positive correlation with retailers' retail prices and a negative correlation with manufacturers' direct prices, wholesale prices, demand and profit from direct channels, and profit from retail channels. The export tax rebate policy will lessen the negative effects of import tariffs and maximize the best choices made by manufacturers and retailers. [ABSTRACT FROM AUTHOR]

Uncertain events such as earthquakes, epidemics, and wars have increased the risk of supply chain disruption. Due to the needs of carbon reduction policies and environmental protection, a large number of enterprises have started to produce both traditional and green products. Studying the issue of supply chain disruption for such enterprises has significant practical significance. We have developed a system dynamics model for a substitutable dual product supply chain with two levels of supply sources. Through simulation analysis, we found that (1) supply chain disruption can cause fluctuations in the manufacturer's inventory, and disruptions from second tier suppliers have a higher impact on the manufacturer's inventory than that from primary suppliers. In addition, the disruption of traditional products will cause consumers to flow to the green product market, resulting in a sudden increase in order for green products and components in a short period of time, causing a delayed impact on the inventory of suppliers and manufacturers of green products. (2) The disruption of upstream suppliers in traditional products causes the highest profit losses for all traditional product suppliers, while the disruption of downstream suppliers in green products causes the highest profit losses for the manufacturer and all green product suppliers. (3) From the perspective of the service level, compared to other components, the disruption of critical components in traditional products poses the highest risk of out of stock in the supply chain, while the risk of out-of-stock in the intermediate component of green product is the smallest. (4) Common sense may suggest that the more the suppliers disrupt, the higher the damage of the supply chain. However, due to the ripple effect, this article finds that from the perspectives of profit, inventory, and service level, multisupplier disruption is not necessarily inferior to single supplier disruption. [ABSTRACT FROM AUTHOR]

The lecithocerid genus Woonpaikia Park, 2010 and Woonpaikia angoonae Park, 2010 are newly recorded from China. Woonpaikia similangoonae Yu & Wang, sp. nov. and W. imperspicua Yu & Wang, sp. nov. are described as new to science. Images of adults of the Chinese Woonpaikia species are provided, along with a key to the males of all the known species of Woonpaikia. [ABSTRACT FROM AUTHOR]

Research on systems that imitate the gaze function of human eyes is valuable for the development of humanoid eye intelligent perception. However, the existing systems have some limitations, including the redundancy of servo motors, a lack of camera position adjustment components, and the absence of interest-point-driven binocular cooperative motion-control strategies. In response to these challenges, a novel biomimetic binocular cooperative perception system (BBCPS) was designed and its control was realized. Inspired by the gaze mechanism of human eyes, we designed a simple and flexible biomimetic binocular cooperative perception device (BBCPD). Based on a dynamic analysis, the BBCPD was assembled according to the principle of symmetrical distribution around the center. This enhances braking performance and reduces operating energy consumption, as evidenced by the simulation results. Moreover, we crafted an initial position calibration technique that allows for the calibration and adjustment of the camera pose and servo motor zero-position, to ensure that the state of the BBCPD matches the subsequent control method. Following this, a control method for the BBCPS was developed, combining interest point detection with a motion-control strategy. Specifically, we propose a binocular interest-point extraction method based on frequency-tuned and template-matching algorithms for perceiving interest points. To move an interest point to a principal point, we present a binocular cooperative motion-control strategy. The rotation angles of servo motors were calculated based on the pixel difference between the principal point and the interest point, and PID-controlled servo motors were driven in parallel. Finally, real experiments validated the control performance of the BBCPS, demonstrating that the gaze error was less than three pixels. [ABSTRACT FROM AUTHOR]

The presence of voids can compromise the strength and continuity of downstream products. The Gurson–Tvergaard–Needleman model was utilized to obtain the relevant parameters. A 3D finite element model was then employed to investigate the elimination of voids in a porous free-cutting steel 1215MS during the hot shape rolling process. The center distribution of voids in the billet was considered in the finite element model, and the relationships between the void elimination and the pressure stress in the billet were analyzed. The influences of rolling reduction, rotation speed, and friction between the work roller and billet on the void elimination were also discussed. The results revealed that the pass reduction has a significant influence on the ultimate value of void volume fraction, which is beneficial for better material self-healing during the shape-rolling process. These findings suggest that accurate predictions of void elimination in the workpiece can be achieved using the finite element method for successful simulation of the hot shape rolling process. [ABSTRACT FROM AUTHOR]

The increasing demand for storing various types of goods has led to a raise in the need for storage capacity in warehousing systems. Autonomous vehicle storage and retrieval systems (AVS/RSs) offer high flexibility by allowing different configurations to meet different storage requirements. The system mainly completes operations through elevators and multiple rail-guided vehicles (RGVs). This paper focuses on the scheduling optimization of compound operations in the AVS/RS to improve system performance. Compound operations involve the coordinated execution of both single-command and double-command operations. A mathematical model with compound operations was proposed and effectively decomposed into a horizontal component for RGVs and a vertical counterpart for the elevator, which can represent the operations of one elevator cooperating with multiple RGVs. The goal of this model was to minimize the makespan for compound operations and to determine the optimal operation sequence and path for RGVs. An improved discrete particle swarm optimization (DPSO) algorithm called AGDPSO was proposed to solve the model. The algorithm combines DPSO and a genetic algorithm in an adaptive manner to prevent the algorithm from falling into local optima and relying solely on the initial solution. Through rigorous optimization, optimal parameters for the algorithm were identified. When assessing the performance of our improved algorithm against various counterparts, considering different task durations and racking configurations, our results showed that AGDPSO outperformed the alternatives, proving its effectiveness in enhancing system efficiency for the model. The findings of this study not only contribute to the optimization of AVS/RS but also offer valuable insights for designing more efficient warehouses. By streamlining scheduling, improving operations, and leveraging advanced optimization techniques, we can create a more robust and effective storage and retrieval system. [ABSTRACT FROM AUTHOR]

Cap-and-trade models have been largely studied in the literature when it comes to reducing emissions in a supply chain. In this paper, further pursuing the goal of analyzing the effectiveness of cap-and-trade strategies in reducing emissions in supply chains, we propose a mathematical model for sustainable supply chain management. This optimization program aims at reducing emissions and supply chain costs in an unregulated scenario w.r.t. the cap definition, i.e., trading CO2 is allowed but no formal limit on the CO2 emissions is imposed. Also, we considered an initial budget for technological investments by the facilities in the considered supply chain, allowing plants to reduce their unit production emissions at a different unit production cost. For this model, differently from what exists in the literature, we derive some theoretical conditions guaranteeing that, if obeyed, the emissions over time have a non-increasing trend meaning that decreasing caps over time can be attained with a self-regulated scenario. Computational results show the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

This paper considers a make-to-order production–inventory system that comprises a production facility and an inventory warehouse. Customers arrive at the facility to place an order, and the orders are processed using the first-come-first-served (FCFS) discipline. The warehouse supplies inventory items (raw materials) for the production process, and the warehouse inventory is replenished by internal production. The speed of internal production can be controlled through additional costs. If the inventory level drops to zero, the unmet demand waits in the facility until the inventory is replenished. During the stockout period, newly arriving demand is lost. The stationary joint probability of unmet demands and inventory items is derived, and a cost model is constructed. The optimal control policy for internal production is investigated to minimize the cost per unit time of the system. The experimental results show that such a production speed adjustment could reduce costs by up to 42% compared to the cases without the adjustment. [ABSTRACT FROM AUTHOR]

Last-mile routing refers to the final step in a supply chain, delivering packages from a depot station to the homes of customers. At the level of a single van driver, the task is a traveling salesman problem. But the choice of route may be constrained by warehouse sorting operations, van-loading processes, driver preferences, and other considerations rather than a straightforward minimization of tour length. We propose a simple and efficient penalty-based local search algorithm for route optimization in the presence of such constraints, adopting a technique developed by Helsgaun to extend the Lin–Kernighan–Helsgaun algorithm for the traveling salesman problem to general vehicle routing problems. We apply his technique to handle combinations of constraints obtained from an analysis of historical routing data, enforcing properties that are desired in high-quality solutions. Our code is available under the open-source Massachusetts Institute of Technology license. An earlier version of the code received the $100,000 top prize in the Amazon Last Mile Routing Research Challenge organized in 2021. History: This paper has been accepted for the Transportation Science Special Issue on Machine Learning Methods and Applications in Large-Scale Route Planning Problems. [ABSTRACT FROM AUTHOR]

Eyeing superior operational performance, transportation, and warehousing management, researchers have turned their much‐needed attention to autonomous and IoT‐driven intralogistics systems. Despite its potential, a systematic evaluation of its overall business needs and the criteria for its success at each stage of adoption is missing in the literature. Using the business analysis framework, augmented by the technology adoption model, this study seeks to provide the business context for adopting autonomous and IoT‐driven intralogistics by identifying business requirements and critical success factors for such systems. We thematically analyze 85 recent research articles on autonomous and IoT‐driven intralogistics systems to identify business requirements that are linked to the mission of maximizing operational profit for the warehousing and storage industry. Then, using the identified business requirements as a base, we thematically analyze those 85 research articles again to identify critical success factors at different stages of technology adoption, namely information, analysis, acquisition, and utilization. We use the findings to develop propositions for future researchers. These findings provide a foundation for developing empirical, descriptive, and normative research on adopting and managing these systems for the warehousing and storage industry. [ABSTRACT FROM AUTHOR]

Many online retailers apply scattered (or mixed-shelves) storage in the picking areas of their warehouses. Instead of keeping unit loads together, individual pieces of stock keeping units (SKUs) are stored on various shelves throughout the warehouse. This storage strategy increases the probability that—whatever it is that customers order jointly—somewhere in the warehouse these products will be located in close proximity. Hence, a picker can retrieve them without excessive unproductive walking. The price for this advantage on the picking side, however, is additional effort for the replenishment workers (also denoted as stowers) when restocking the shelves. Instead of moving only a single homogeneous unit load toward an SKU's designated storage position, each stower has to travel along multiple open shelf spaces until all products on the cart are stored on shelves. The resulting stower routing problem is equivalent to the well-known prize collecting traveling salesman problem (PCTSP). While the PCTSP for general graphs is known to be strongly NP -hard, we show that in a warehousing environment, where all open storage positions are located along parallel aisles, it is only binary NP -hard. The special parallel-aisle structure allows us to derive an exact solution algorithm with pseudo-polynomial runtime, which solves even instances with hundreds of open storage positions to proven optimality in just a few seconds. Our computational tests show that the performance gains of an optimized stowing process over the status quo, where stowers operate without decision support, are significant. Especially, when the fill level of a warehouse is high, directing stowers on optimized routes promises huge improvements. History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms – Discrete. Funding: This work was supported by the German Science Foundation/Deutsche Forschungsgemeinschaft (DFG) by the grant "Routing of human and automated order pickers in modern warehouses" (BO 3148/14-1 and BO 1972/2-1). Supplemental Material: The e-companion is available at https://doi.org/10.1287/ijoc.2022.0173. [ABSTRACT FROM AUTHOR]

Purpose: Slotting is one of the main operations in warehouse management. It is based on the efficient allocation of slots for stock-keeping units (SKUs). Order picking and slotting represent a high percentage of total logistics costs; therefore, improving these activities leads to significant savings in overall performance. This paper aims to develop an allocation model integrating SKUs physical variables, warehousing design and operation (dimensions, layout, material handling equipment), and heterogeneous product demand. Design/methodology/approach: The modeling methodology considers two phases. First, an integer linear programming model for warehousing spaces assignment for SKUs considering priority and required orders is developed. Then, the total operation times using different strategies are calculated. Findings: The effectiveness of the model was verified through simulation using historical data. The results showed that the best performance in the total time of the slotting operation is achieved by using the ABC as a criterion for the classification of the SKUs and by sequentially assigning the row, level, column, and section. Practical implications: This approach can be adapted to different industrial sectors and serves as a basis for more robust models regarding the number of constraints or the incorporation of additional warehouse operating parameters. Originality/value: The most important contribution of this work is the development of an adaptable methodology to changes in the operation to improve the efficiency of storage management through slotting. Future work includes other objective functions of sustainable operations and uncertainty treatment techniques. [ABSTRACT FROM AUTHOR]

Purpose: Recently, the complexity of managing warehouses has been amplified significantly due to factors that include increased requests for more frequent and smaller order fulfilment, reduction of operational cost, and improvement of customer experience. Product stock count is a critical process in order to address the aforementioned challenges. This article presents experimental results from the adoption of drones coupled with RFID tags used for real time goods' stock count. Design/methodology/approach: The research methodology adopted combines three different methods, namely Systematic Literature Review (SLR) for identifying parameters that affect the performance of drones in stock count process, survey via questionnaire and interviews to logistics managers to map needs and requirements in warehouse operations, as well as laboratory testing via Design of Experiment (24 full factorial design & ANOVA) methodology to investigate how certain parameters corelate and affect the reading accuracy of RFID tags as well as the time needed by a drone for stock count completion. Findings: The results of the experiments are encouraging, showing that the use of drones coupled with RFID tags may support faster, cost-effective, and safer stock count in warehouses. In both ambient and chilled storage environment a 100% RFID tag reading accuracy was achieved. Less stock-count completion time when compared to manual stock-count was achieved in both cases. Research implications: Understanding the effect of technical and operational parameters of RFID technology in conjunction with unmanned aerial vehicles (UAVs)-drones may have the potential to radically transform the stock count process by considerably increase the efficiency and accuracy of the process. Practical implications: Real-time stock count via drones has significant cost-saving implications for organizations. The elimination of manual stock counting saves operational expenses and increases staff safety. Furthermore, real-time data collection of existing product stock allows managers to efficiently allocate resources, enhancing overall efficiency and performance. Originality/value: This research is among the first studies that aim to present evidence from experimental results that assess the use of drones coupled with RFID technology for real-time stock count. The results from laboratory experiments demonstrate the effect of certain operational parameters, such as drone speed, number of rack levels, and RFID tag location on products, during the execution of the stock count process in terms of RFID reading accuracy and stock-count completion time. [ABSTRACT FROM AUTHOR]

Our study details the development and validation of an orchestrator-controlled robotic network that effectively organizes and manages the activities of multiple robots. The design workflow is based on a model-driven methodology that allows for the independent specification of robot behaviour, which can be successfully refined regardless of the physical architecture. The main focus of this study involves the verification and analysis of robot orchestration by building formal models in a component–port–connector fashion supported by BIP language (behaviour–interaction–priority). The model also helps to study the automated orchestration with the help of a centralized computer tasks manager. The related functional requirements gathered from industrial partners are specified in temporal logic. Statistical model checking is performed to verify the model's correctness, providing a functional assurance to achieve the deployment. Validation is a carry out using a dedicated robotic platform simulator. We demonstrate the capability of the verification artefact for the Brain-IoT (https://cordis.europa.eu/project/id/780089) platform and ways of applying them to potentially complex case studies. [ABSTRACT FROM AUTHOR]

In recent years, global warming and environmental problems have become more serious due to greenhouse gas (GHG) emissions. Harvesting solar energy for production and logistic activities in supply chains, including factories and distribution centers, has been promoted as an effective means to reduce GHG emissions. However, it is difficult to balance the supply and demand of solar energy, owing to its intermittent nature, i.e., the output depends on the daylight and season. Moreover, the use of large-capacity solar power generation systems and batteries incurs higher installation costs. In order to maintain low costs, demand-to-supply management of solar energy, based on appropriate seasonal analysis of power generation and consumption and the capacity planning for power generation and the storage battery, is necessary. In this study, the on-demand cumulative control method is applied to actual power consumption data and solar power generation data estimated at a distribution center. Moreover, the monthly, seasonal, and temporal characteristics of power generation and consumption at the distribution center are analyzed. Additionally, the total amount of power purchased is investigated for solar energy demand-to-supply management. [ABSTRACT FROM AUTHOR]

The research into new approaches to shift from fossil fuels to renewable energy sources (RES) has surged as environmental issues are on the rise, and fossil fuel sources are becoming scarce. The flexibility potential of cold supply systems has been discussed widely in the literature, firstly due to their high share of electricity consumption worldwide and secondly because of their potential to store thermal energy in the form of cold energy. However, finding a clear definition of flexibility and a concise approach for its quantification is still under progress. In this work, a comprehensive definition of the flexibility of energy systems and a novel methodology for its quantification are introduced. The methodology was applied on a cold warehouse with real data regarding its cold energy demand. The cold warehouse was first modeled via oemof, which is a modular open source framework developed in Python 3.8 using a mixed integer linear programming (MILP) optimization approach. The operation optimization of the cold warehouse was conducted for three goals, namely "minimization of electricity costs", "minimization of CO2 emissions", and "minimization of maximum used electric power (peak load minimization)". Additionally, the effect of using different types of refrigeration compressors on the optimized operation of the cold warehouse was investigated. The results suggest that a cold warehouse possesses a high level of flexibility potential, which can be taken advantage of to reduce the electricity cost by up to 50%, the CO2 emissions between 25% to 30%, and the maximum used electric power by 50%. Different compressor types produced very similar results, although their flexibility level may vary. [ABSTRACT FROM AUTHOR]

This paper considers a dual-channel closed-loop supply chain (CLSC) consisting of a manufacturer who wholesales new products through the traditional retail channel and distributes remanufactured products via a direct (online) channel established by himself. Two dynamical Stackelberg game models are developed based on the assumption that the retailer is an adaptive player, and the manufacturer is a bounded rational player who may adopt a delay decision. The existence and locally asymptotic stability of the Nash equilibrium are examined. Moreover, the impacts of key parameters on the complexity characteristics of the models and the performance of chain members are studied by numerical simulation. The results reveal that the excessively fast price adjustment speeds of the manufacturer, the larger consumers' discount perception for the remanufactured products, and the consumers' preference for the direct channel have a strong destabilizing effect on the Nash equilibrium's stability. Furthermore, the delay decision implemented by the manufacturer could be a stabilizing or destabilizing factor for the system. The manufacturer will tolerate a considerable profit reduction while the retailer gains more profits when the dual-channel CLSC system enters periodic cycles and chaotic motions. [ABSTRACT FROM AUTHOR]

Industrial parks, characterized by the clustering of multiple factories and interconnected energy sources, require optimized operational strategies for their Integrated Energy Systems (IES). These strategies not only aim to conserve energy for industrial users but also relieve the burden on the power supply, reducing carbon emissions. In this context, this paper introduces an optimization strategy tailored to clustered factories, considering the incorporation of carbon trading and supply chain integration throughout the entire production process of each factory. First, a workshop model is established for each factory, accompanied by an energy consumption model that accounts for the strict sequencing of the production process and supply chain integration. Furthermore, energy unit models are devised for the IES and then a low-carbon and economically optimized scheduling model is outlined for the IES within the industrial park, aiming to minimize the total operational cost, including the cost of carbon trading. Finally, case studies are conducted within a paper-making industrial park located in the Zhejiang Province. Various scenarios are compared and analyzed. The numerical results underscore the model's economic and low-carbon merits, and it offers technical support for energy conservation and emission reduction in paper-making fields. [ABSTRACT FROM AUTHOR]

Order-picking optimization in a business sustainable competitiveness context is challenging due to prior studies focusing on theoretical model development with unrealistic assumptions in their algorithms and methodological validation, often neglecting practical concerns. This paper improves order-picking operations by employing combinatorial optimization as a travelling salesman problem and class-based dedicated storage models for the ATP company. The paper's originality and novelty lie in bridging the gap between academia and management, presenting an effort to connect theoretical concepts with practical optimization in order-picking warehouse operations in an environment of competitiveness. Realistic data and LINGO software were employed, revealing substantial improvements in the ATP warehouse operations through optimized pick path decisions embedded in warehouse layouts. This paper provides managerial tools for distance traveled optimization in the warehouse that yield competitive edges, enhanced supply chain efficiency and effectiveness, as well as other positive impacts on social, and environmental concerns such as labor safety, customer satisfaction, energy consumption, and CO2 emission. The paper also outlines future research directions to advance warehouse management and address sustainable competitiveness challenges, adding a new dimension to the original research. [ABSTRACT FROM AUTHOR]

Thin-walled structures are a significant and growing portion of engineering construction, with a wide range of applications, including storage vessels, industrial buildings, warehouses, aircraft, automobiles, bridges, ships, and oil rigs. Thin-walled components with minimum thickness without compromising strength and other quality characteristics are the desire of modern industry. Reducing wall thickness not only aids in lowering the cost of production. It also improves the effectiveness of engineering systems, resulting in lower fuel consumption and lower emissions of hazardous gases to the environment. Nowadays, even though thin-walled parts are demanded, the constraints of the production process, quality, and reliability are the concerns of current research and development. The ability to produce parts with intricate geometries and tight dimensional tolerances are important criteria for advanced manufacturing processes. In the early days of society, investment casting was used to produce jewelry, weapons, and statues. In modern industry, investment casting is still used to produce thin-walled and intricate parts such as turbine blades. The current advancements in SLM, which has the capacity to produce thin-walled and intricate parts, have recently attracted attention due to several benefits, such as the supreme degree of design freedom and the viability of tool-free production directly from CAD data. However, the current technological applications of SLM and investment casting are crucial for producing parts at the desired quality and reliability. This review article focuses on comparative studies of SLM and investment casting at the current technology level. The basis of comparison via systematic approach is mechanical characterization; quality in terms of porosity, microstructure, surface roughness and dimensional accuracy; and residual stress. Therefore, the latest open scientific sources published are considered to obtain sufficient literature coverage. Better tensile strength and fine microstructure are found in SLM, while better surface quality, fatigue load resistance, ductility, and residual stress are found in investment casting. The research gap for further investigation is indicated. [ABSTRACT FROM AUTHOR]

An in-depth investigation into Green Supply Chain Management (GSCM) practices is presented, delineating their economic impact. The research applies fuzzy logic within a Multi-Criteria Decision- Making (MCDM) framework to systematize the evaluation and advancement of green practices in supply chains. The integration of fuzzy logic with MCDM is posited to refine the precision of evaluations. The approach centres on the assessment of green suppliers using a linear programming-based fuzzy Multi-Attributive Border Approximation area Comparison (MABAC) method. The study advances the discourse on GSCM by quantifying the economic merits, namely cost efficiency, market productivity enhancement, and brand image improvement. Evidence from practical applications substantiates the dual benefits of GSCM in bolstering environmental sustainability and generating significant economic gains. [ABSTRACT FROM AUTHOR]

Protein oxidation of soybean meal (SBM) during storage may have adverse effects on the intestinal health of laying hens. Moreover, rutin has anti-inflammatory and antioxidant properties which might be used as a feed additive to mitigate the intestinal damage caused by oxidised protein of SBM. This study aimed to investigate the effects of rutin supplementation on intestinal morphology, antioxidant capacity, immunity and caecal microbiota in laying hens fed a diet containing stored SBM. A total of 384 Hy-Line Brown laying hens (220 days) were randomly allocated into four groups with eight replicates of 12 laying hens each according to a 2 × 2 factorial arrangement with 2 types of SBM (FSM: SBM was stored in the cold storage warehouses at −20 °C for 45 days, and was considered as fresh and control SBM; RTSM: SBM was stored in room temperature warehouse (15 °C to 25 °C), average temperature was 20 °C for 45 days) and 2 levels of rutin (0 and 500 mg/kg). The results showed that the RTSM diet decreased the ileal glutathione peroxidase (GSH-Px) activity, the jejunal superoxide dismutase 2 (SOD2) and ileal NAD(P)H: quinone oxidoreductase 1 (NQO1) mRNA expression levels (p < 0.05), and tended to decrease the jejunal superoxide dismutase 1 (SOD1), ileal glutathione peroxidase 1 (GPX1) and increase the jejunal interleukin-1β (IL-1β) and interleukin-4 (IL-4) mRNA expression levels. Dietary rutin decreased the jejunal crypt depth (CD) (p < 0.05), increased the jejunal total antioxidant capacity (T-AOC) and GSH-Px activities (p < 0.05), decreased the content of interferon-γ (IFN-γ) in the jejunum (p < 0.05), and significantly reduced levels of immunoglobulin G (IgG), IL-1β, tumour necrosis factor-α (TNF-α), IFN-γ, and IL-4 in the ileal mucosa (p < 0.05). Dietary rutin increased SOD2, nuclear factor E2-related factor 2 (Nrf2) and NQO1 mRNA expression levels in the jejunum and GPX1, Nrf2 and NQO1 mRNA expression levels in the ileum, and decreased nuclear factor-κB (NF-κB), IL-1β, IFN-γ and IL-4 mRNA expression in the jejunum and NF-κB, IL-1β, TNF-α, IFN-γ and IL-4 mRNA expressions in the ileum. What's more, dietary rutin changed the caecal microbiota. PCoA analysis indicated significant structural differences among four groups (p < 0.05), and SBM × Rutin interactions were found in Actinobacteriota and unclassifiedk_norank_d_ Bacteria at the phylum level (p < 0.05). These results suggested that RTSM had slight adverse effects on the intestinal health, and dietary rutin improved intestinal morphology, exerted antioxidant and anti-inflammatory effects via Nrf2 and NF-κB signal pathways, and changed the composition of caecal microbiota. The RTSM diet has adverse effects on the intestinal health of laying hens compared with the FSM diet. Dietary rutin improved the intestinal health by increasing the intestinal morphology, antioxidant capacity and anti-inflammatory effects. Dietary soybean meal and rutin changed the composition of caecal microbiota. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the effects of rutin on laying performance, egg quality, serum biochemical parameters, serum immunoglobulin, and antioxidant status in laying hens fed a diet containing stored soybean meal (SBM). The dietary treatments used were arranged in a 2 × 2 factorial arrangement with 2 types of SBM (FSM: SBM was stored in the cold storage warehouses at −20 °C for 45 days and was considered as fresh SBM; RTSM: SBM was stored in room temperature warehouse (15 °C to 25 °C), average temperature was 20 °C for 45 days) and 2 levels of rutin (0 and 500 mg/kg). In total, 384 Hy-Line Brown laying hens (220 days of age) were randomly divided into 4 groups with eight replicates. Pre-feeding period was 1 week, and the experiment lasted for 8 weeks. The results showed that the RTSM diet had no effect on laying performance (p > 0.05). Compared with the diet without rutin, diet with 500 mg/kg rutin exhibited a tendency to increase egg mass compared with the diet without rutin (p = 0.096), and there was a trend of interaction effect on average egg weight (p = 0.061). The RTSM diet decreased the egg Haugh unit significantly compared with the FSM diet at the end of 8th week (p < 0.05). Compared with the diet without rutin, dietary rutin supplementation could affect egg quality as evidenced by increased eggshell thickness, albumen height, egg yolk colour at the end of 4th week and increased eggshell strength and eggshell thickness at the end of 8th week (p < 0.05). Furthermore, dietary rutin supplementation increased urea nitrogen, decreased the immunoglobulin M (IgM) content in serum compared with the diet without rutin (p < 0.05). Compared with the diet without rutin, dietary supplementation with rutin improved the total antioxidant capacity in the serum and liver (p < 0.05). The interactions of SBM × Rutin were observed on egg yolk ratio at the end of 8th week, and the urea nitrogen and IgM content in serum. These findings suggested that diet with RTSM had adverse effects on egg quality in laying hens. The RTSM diet negatively impacted egg quality of laying hens over time when compared to the FSM diet. Dietary rutin supplementation could improve the egg quality, and antioxidant capacity of laying hens. Dietary with soybean meal stored in room temperature warehouse reduced egg quality of laying hens. Dietary rutin supplementation improved egg quality and antioxidant capacity of laying hens independent of stored SBM. There was a significant interaction between stored soybean meal and rutin on egg yolk ratio, serum UN and IgM levels. [ABSTRACT FROM AUTHOR]

As consumers' green awareness continues to grow, the level of a product's eco-friendliness and the quality of its marketing have become significant factors in shaping consumers' purchasing decisions. The power structures within the supply chain, as well as corresponding government subsidy policies, are also key elements influencing sustainable strategies for the green supply chain. In a green supply chain comprising one manufacturer and one e-commerce platform, two sales models exist within the online e-commerce platforms: reselling and agency selling. This paper establishes and analyzes three distinct Stackelberg game models, namely: manufacturer-led model without subsidy (bm), manufacturer-led model with subsidy (sm), and platform-led model with subsidy (sp). The results are shown as follows, with the rise of consumers' environmental awareness, more consumers opt for green products, inspiring the manufacturer to increase its optimal greenness and platform to enhance its optimal marketing efforts level. Notably, government subsidies provide a significant stimulus. An increase in the green technology cost coefficient leads to a decline in the manufacturer's profits across all three modes. Intriguingly, the manufacturer's profits are always highest in the sp mode. As the marketing efforts cost coefficient increases, the platform's profits decrease in the bm and sm modes. In contrast, in the sp mode, the platform's profits increase rather than a decrease. The choice of mode primarily depends on the platform's marketing efforts cost coefficient. When this coefficient exceeds a threshold, the platform chooses the sp mode. However, due to the relatively low marketing efficiency in this scenario, the manufacturer prefers the sm mode. For the government, the sp mode involves agency selling, serves as an effective mechanism to redistribute subsidies, thereby yielding the maximum social welfare benefits. Management insights are provided for the manufacturer and platform managers to make decisions about the degree of greenness and marketing efforts level, along with insights for governments to optimize subsidy policies. [ABSTRACT FROM AUTHOR]