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A three-bin moving average window (3B-MAW) model was proposed and compared with the work-based window method (WB-WM) to investigate the on-road emission characteristics of heavy-duty vehicles. The invalid data of remote monitoring were mainly composed of the NOx sensor’s abnormal data and the uploaded data after the engine shutdown. In the 3B-MAW model, each data was attributed to one, two or three bins. The percentage of the three bins were linked to the vehicle’s real driving conditions. In order to gain the emission calculation accuracy and a smaller scale of required data, the value of the four main parameters, i.e., the minimum window number, the window width, the first cut-off and the second cut-off are set around 2 400 s, 300 s, 6% and 20%, respectively. Since the window power is no longer required, the 3B-MAW method is able to capture the low load emission characteristics more effectively, compared to the WB-WM. Therefore, the 3B-MAW method is a more appreciate approach to analyse on-road random driving conditions.

This paper addresses the multiorder open-dimension three-dimensional rectangular packing problem (3D-MOSB-ODRPP), which involves packing rectangular items from multiple orders into a single, size-adjustable container. We propose a novel metaheuristic approach combining a genetic algorithm with the Gurobi solver. The algorithm incorporates a lower neighborhood search strategy and is underpinned by a mathematical model representing the multiorder open-dimension packing scenario. Extensive experiments validate the effectiveness of the proposed approach. The LNSGA algorithm outperforms Gurobi and the traditional genetic algorithm in solution quality and computational efficiency. For small-scale instances, LNSGA achieves optimal values in most cases. LNSGA demonstrates significant optimization improvements over Gurobi and the genetic algorithm for large-scale instances. The superior performance is attributed to the effective integration of the lower neighborhood search mechanism and the Gurobi solver. This study offers valuable insights for optimizing the packing process in e-commerce warehousing and logistics operations. [ABSTRACT FROM AUTHOR]

The increasingly usage of Intensive shelves, greatly increase the utilization of storage space, but also is more demanding on order picking time . Based on the storage layout of intensive mobile shelves, this paper combines the time cost of shelf movement with the moving distance under the guidance of seeking global optimum. Transform the single order picking process into TSP problem, while considering the picking process. The waiting cost of the order, and the minimum of the picking cost and the waiting cost of the whole batch of orders requiring shelf movement, to establish a two-stage mathematical model of the order picking order. Then, the algorithm for solving the model is designed, and the simulation is carried out by numerical examples to illustrate the law and characteristics of the problem more vividly, in order to provide reference and reference for the order picking activities of intensive mobile shelves.

Order picking is a crucial operation in the storage industry, with a significant impact on storage efficiency and cost. Responding quickly to customer demands and shortening picking time is crucial given the random nature of order arrival times and quantities. This paper presents a study on the order-picking process in a distribution center, employing a "parts-to-picker" system, based on dynamic order batching and task optimization. Firstly, dynamic arriving orders with uncertain information are transformed into static picking orders with known information. A new method of the hybrid time window is proposed by combining fixed and variable time windows, and an order consolidation batch strategy is established with the aim of minimizing the number of target shelves for picking. A heuristic algorithm is designed to select a shelf selection model, taking into account the constraint condition that the goods on the shelf can meet the demand of the selection list. Subsequently, task division of multi-AGV is carried out on the shelf to be picked, and the matching between the target shelf and the AGVs, as well as the order of the AGVs to complete the task of picking, is determined. A scheduling strategy model is constructed to consider the task completion time as the incorporation of moving time, queuing time, and picking time, with the shortest task completion time as the objective function and AGV task selection as the decision variable. The improved ant colony algorithm is employed to solve the problem. The average response time of the order batching algorithm based on a hybrid time window is 4.87 s, showing an improvement of 22.20% and 40.2% compared to fixed and variable time windows, respectively. The convergence efficiency of the improved ant colony algorithm in AGV task allocation is improved four-fold, with a better convergence effect. By pre-selecting the nearest picking station for the AGVs, the multi-AGV picking system can increase the queuing time. Therefore, optimizing the static picking station selection and dynamically selecting the picking station queue based on the queuing situation are proposed. The Flexsim simulation results show that the queue-waiting and picking completion times are reduced to 34% of the original, thus improving the flexibility of the queuing process and enhancing picking efficiency. [ABSTRACT FROM AUTHOR]

Aiming at the multibox 3D packing problem of heterogeneous extrudable items in e-commerce retail department stores, the optimization goal is to select appropriate packaging materials for packing all items in the order. On this basis, the number of packaging materials used is the least and the space utilization rate is high. A heuristic algorithm is designed. Firstly, the items are sorted in descending order according to volume, and then the items are boxed according to the rule of "layer generation." In order to verify the feasibility and effectiveness of the algorithm, the data provided by a large domestic e-commerce platform are used to analyse and compare the space utilization of packaging materials under the conditions of no extrusion operation and extrusion operation. The feasibility and effectiveness of the algorithm in the packaging and delivery link in the storage field of e-commerce retail department stores are proved. [ABSTRACT FROM AUTHOR]

In China, where in-use heavy-duty diesel vehicles producing NOx and particulate emissions for air pollution are required to undergo emission spot inspection at check stations, it is significant to adopt a simple method to evaluate emissions due to traffic jams, especially in big cities. To realize convenient vehicle emission spot inspection, this paper investigates the effects of exhaust temperature on the Selective Catalytic Reduction (SCR) de-NOx conversion efficiency and presents a method for evaluating the SCR operation state based on ammonia storage characteristics. The paper proposes a real-road driving test procedure and verifies it by measuring NOx from a heavy-duty diesel vehicle in an on-road driving test. The results show that the SCR de-NOx efficiency experiences three operation states. In state I, SCR works and injects urea, resulting in high de-NOx efficiency (>90%); state III occurs during the cold, starting with the lowest de-NOx efficiency (<50%) due to a lack of NH3; and state II is a transition stage caused by the ammonia storage, with a certain conversion efficiency (50–90%) when SCR de-NOx efficiency linearly relates to exhaust temperature. Whether the SCR works normally can be judged based on the SCRs operation states. This method is simple and easy to implement in different SCR operation states, and it is effective and repeatable. [ABSTRACT FROM AUTHOR]

The routing strategy for order picking is an important factor in the efficiency of warehouse picking, and improvements to the warehouse layout provide more routing options for picking. The number of storage locations to be visited during the picking operation also has an impact on the selection of routing strategies. In order to achieve an effective improvement in the efficiency of picking operations in warehouse distribution centers, this paper focuses on the leaf warehouse layout based on the previous single-command operation strategy and extends it to study the multi-command operation strategy, in which three heuristic routing strategies, the S-shape, the return, and the composite, are introduced to solve the walking distance problem of picking operations, with the study of the selection of the routing strategy for different numbers of storage locations to be visited. Based on the distance equation between any two storage locations to be visited in the leaf layout warehouse, travel distance models corresponding to the three routing strategies in the picking operation are constructed, and the cuckoo search algorithm is introduced to solve and calculate the travel distance of the composite strategies for the experiments. In addition, the computational experiments of the three path strategies are carried out according to the different numbers of storage locations to be visited in the picking operation. By analyzing the numerical results, we find that the composite strategy has the best overall results among the three routing strategies, with the average values of optimization rates exceeding 30% (the S-shape) and 40% (the return), respectively. At the same time, the return strategy outperforms the S-shape strategy when the number of locations to be visited is less than seven. As the number of locations to be visited increases, the S-shape strategy gradually outperforms the return strategy. From a managerial and practical perspective, compared to the single-command operation strategy that is the focus of the current research, the multi-command operation strategy we studied is more relevant to the actual situation of order merging picking in warehouses and can effectively improve the efficiency of picking operations, the competitiveness of enterprises, and customer satisfaction of e-commerce enterprises. [ABSTRACT FROM AUTHOR]

In order to explore the application of robots in intelligent supply-chain and digital logistics, and to achieve efficient operation, energy conservation, and emission reduction in the field of warehousing and sorting, we conducted research in the field of unmanned sorting and automated warehousing. Under the guidance of the theory of sustainable development, the ESG (Environmental Social Governance) goals in the social aspect are realized through digital technology in the storage field. In the picking process of warehousing, efficient and accurate cargo identification is the premise to ensure the accuracy and timeliness of intelligent robot operation. According to the driving and grasping methods of different robot arms, the image recognition model of arbitrarily shaped objects is established by using a convolution neural network (CNN) on the basis of simulating a human hand grasping objects. The model updates the loss function value and global step size by exponential decay and moving average, realizes the identification and classification of goods, and obtains the running dynamics of the program in real time by using visual tools. In addition, combined with the different characteristics of the data set, such as shape, size, surface material, brittleness, weight, among others, different intelligent grab solutions are selected for different types of goods to realize the automatic picking of goods of any shape in the picking list. Through the application of intelligent item grabbing in the storage field, it lays a foundation for the construction of an intelligent supply-chain system, and provides a new research perspective for cooperative robots (COBOT) in the field of logistics warehousing. [ABSTRACT FROM AUTHOR]

Wearable medical devices rely on the human body to form a small LAN around the human body, called body area network (BAN). Users can use these devices to monitor the changes of various body indicators in real time. The physiological data involved in this process belongs to personal privacy. Therefore, the security requirements of BAN are relatively high, and its current research focus is on authentication mechanisms. To meet the requirements of security and resource consumption of BAN, this paper proposes a lightweight identity authentication mechanism that meets the characteristics of BAN resource constraints. Based on the characteristics of BAN, a simple and mature star topology structure is applied to establish the network model of BAN. For the human body in normal situations and emergencies, the corresponding authentication mechanism and encryption and decryption method of physiological data are designed by using the physical unclonable function (PUF) and cloud database, physiological data, and cross-correlation algorithm. Furthermore, the formal and informal security analysis of the designed authentication mechanism proves that the authentication mechanism designed in this paper has certain security, and the lightweight authentication mechanism is simulated and evaluated. The experimental results show that compared with the benchmarking mechanism, the authentication mechanism designed in this paper solves more security problems and has certain advantages in terms of calculation cost, communication cost, and energy cost. [ABSTRACT FROM AUTHOR]

The utilization of a storage space can be considerably improved by using dense mobile racks. However, it is necessary to perform an optimisation study on the order picking to reduce the time cost as much as possible. According to the channel location information that needs to be sorted, the multiple orders are divided into different batches by using hierarchical clustering. On this basis, a mathematical model for the virtual order clusters formed in the batches is established to optimize the order cluster picking and rack position movement, with the minimum picking time as the objective. For this model, a hybrid genetic algorithm is designed, and the characteristics of the different examples and solution algorithms are further analysed to provide a reference for the solution of the order picking optimisation problem in a dense mobile rack warehouse. [ABSTRACT FROM AUTHOR]

Listeria ivanovii (LI) possesses a facultative intracellular life cycle in macrophages and non-professional phagocytes thus making it a potential novel vaccine vector. We have developed a genome site-specific integration system as a universal tool for constructing the live LI-based vaccines. Using this system, the porcine reproductive and respiratory syndrome virus (PRRSV) orf5 and orf6 genes, coding for PRRSV membrane-associated protein GP5 and M, respectively, were integrated into the LI genome. Genome PCR and sequencing results showed that the orf5 or orf6 gene had been integrated into the LI genome downstream of orfXYZ or mpl gene. Western blot analysis of the non-secreted and secreted bacterial protein samples showed the expression and secretion of GP5 or M protein from the recombinant LI strains. The secretion of the heterologous proteins is a key step for bacterial vaccine vectors to deliver the antigens to the immune system to stimulate antigen-specific immune responses. Therefore, this integration system may be a potential tool for constructing novel vaccines using live LI as vector. © 2014 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Order picking is the part with the highest proportion of operation cost and time in the warehouse. The characteristics of small-batch and multi-frequency current orders reduce the applicability of the traditional layout in the warehouse. Besides this, the improvement of the layout will also affect the picking path, such as the Chevron warehouse layout, and at present, there is a lack of research on order picking with multiple picking locations under non-traditional layouts. In order to minimize the order picking cost and time, and expand the research in this field, this paper selects the Chevron layout to design and describe the warehouse layout, constructs the picking walking distance model of Return-type, S-type and Mixed-type path strategies in the random storage Chevron layout warehouse, and uses the Cuckoo Search (CS) algorithm to solve the picking walking distance generated by the Mixed-type path. Compared with the existing single-command order picking research, the order picking problem of multi picking locations is more suitable for the reality of e-commerce warehouses. Moreover, numerical experiments are carried out on the above three path strategies to study the impact of different walking paths on the picking walking distance, and the performance of different path strategies is evaluated by comparing the order picking walking distance with the different number of locations to be picked. The results show that, among the three path strategies, the Mixed-type path strategy is better than the Return-type path strategy, and the average optimization proportion is higher than 20%. When the number of locations to be picked is less than 36, the Mixed-type path is better than the S-type path. With the increase of the number of locations to be picked, the Mixed-type path is gradually worse than the S-type path. When the number of locations to be picked is less than 5, the Return-type path is better than the S-type path. With the increase of the number of locations to be picked in the order, the S-type path is gradually better than the Return-type path. [ABSTRACT FROM AUTHOR]

In the field of e-commerce warehousing, maximizing the utilization of packing bins is a fundamental goal for all major logistics enterprises. However, determining the appropriate size of packing bins poses a practical challenge for many logistics companies. Given the limited research on the open-size 3D bin packing problem as well as the high complexity and lengthy computation time of existing models, this study focuses on optimizing multiple-bin sizes within the e-commerce context. Building upon existing research, we propose a hybrid integer programming model, denoted as the three dimensional multiple option dimensional rectangular packing problem (3D-MODRPP), to address the multiple-bin size 3D bin packing problem. Additionally, we leverage well-established hardware and software technologies to propose a 3D bin packing system capable of accommodating multiple bin types with open dimensions. To reduce the complexity of the model and the number of constraints, we introduce a novel assumption method for 0-1 integer variables in the overlap and rotation constraints. By applying this approach, we significantly streamline the computational complexity associated with the model calculations. Furthermore, we refine the dataset by developing a customized version based on the classical Three-Dimensional One-Size Dependent Rectangular Packing Problem (3D-ODRPP) dataset, leading to improved outcomes. Through comprehensive analysis of the research results, our model exhibits remarkable advancements in addressing the strong heterogeneous bin packing problem, the weak heterogeneous bin packing problem, the actual bin packing problem, and the bin packing problem with multiple bin types and open sizes. Specifically, it significantly reduces model complexity and computation time and increases space utilization. The system designed in this study paves the way for practical applications based on the proposed model, providing researchers with broader research prospects and directions to expand the scope of investigation in the field of 3D bin packing. Consequently, this system contributes to solving complex 3D packing problems, reducing space waste, and enhancing transportation efficiency., Competing Interests: The authors declare there are no competing interests., (©2023 Yang et al.)

Polybrominated diphenyl ethers (PBDEs) are ubiquitous environmental pollutants that accumulate to high levels in human populations that are subject to occupational or regional industry exposure. PBDEs have been shown to affect human neuronal, endocrine and reproductive systems, but their effect on the immune system is not well understood. In this study, experimental adult mice were intragastrically administered 2,2',3,3',4,4',5,5',6,6'-decabromodiphenyl ether (BDE-209) at doses of 8, 80 or 800 mg/kg of body weight (bw) at 2-day intervals. Our results showed that continuous exposure to BDE-209 resulted in high levels of BDE-209 in the plasma that approached the levels found in people who work in professions with high risks of PDBE exposure. Reduced leukocytes, decreased cytokine (IFN-γ, IL-2 and TNF-α) production and lower CD8 T-cell proliferation were observed in the mice exposed to BDE-209. Additionally, mice with long-term BDE-209 exposure had lower numbers of antigen-specific CD8 T cells after immunization with recombinant Listeria monocytogenes expressing ovalbumin (rLm-OVA) and the OVA-specific CD8 T cells had reduced functionality. Taken together, our study demonstrates that continuous BDE-209 exposure causes adverse effects on the number and functionality of immune cells in adult mice.