Search Results (60)

Due to the complexity of shipyards’ operating scenes and the inconsistency of ship parts’ type and size, current sorting operations for ship parts mainly rely on laborers, resulting in weak control over the production process and key nodes. With the gradual advancement of intelligent manufacturing technology in the shipbuilding process, the trend of machines replacing humans is obvious. In order to promote the automation of the sorting process, intelligent scene recognition and route planning algorithms are needed. In this work, we introduce a localization method based on a laser line profile sensor and ship parts layout analysis algorithm, aiming at obtaining the information needed for sorting route planning. In addition, a heuristic-based route planning algorithm is proposed to solve the built mathematical model of the ship part sorting process. The proposed method can optimize the sorting order of parts, realize stable stacking, shorten sorting distance (taking about 490 m for 43 parts), and thereby improve operation efficiency. These results show that the proposed approach can make intelligent and comprehensible sorting route planning for the ship parts layout. Full article

Time Division Multiplexing Passive Optical Networks (TDM-PONs) serve as a key enabler for the evolution of broadband access network infrastructure. As TDM-PONs adapt to support 6G networks, reducing energy consumption becomes increasingly critical. Sleep modes have been widely adopted as an effective energy-saving solution. However, their use can introduce delays that compromise performance. This issue becomes especially problematic in 6G PONs, where ultra-low latency and stringent service requirements leave minimal tolerance for delay-related inefficiencies. In this paper, we propose a novel sleep synchronization mechanism for both single and multiple TDM-PONs, allowing Optical Network Units (ONUs) to join one or more sleep/wake-up groups based on the service type and delay tolerance. Our practical design framework incorporates delay-based grouping and existing sleep modes to address the operational complexities of multi-PON systems while remaining fully compatible with current PON standards. The simulation results show that our approach satisfies the requirements of delay-sensitive traffic and achieves up to 37% energy savings. Compared to baseline methods such as adaptive scheduling and fixed-interval cyclic sleep, it offers a 15–20% improvement in the energy–delay trade-off. These results demonstrate the potential for near-term deployment of 6G PONs and lay the foundation for more advanced, delay-aware energy management strategies in next-generation optical access networks. Full article

Background/Objectives: The whole cell pertussis vaccine was introduced in the United States in the 1940s and switched to the acellular pertussis vaccine partially in 1992 and completely in 1997. This study examines the relationship between the resurgence of pertussis in the United States and the change in the type of pertussis vaccines. Methods: Pertussis cases from 1922 to 2024 were obtained from the CDC’s national notifiable disease surveillance system, and vaccination coverage was obtained from the WHO. A trend analysis and Pearson’s correlation test were conducted between the incidence of cases and the coverage of the third and fourth doses of the pertussis vaccine. An ANOVA test and multivariable linear regression were performed to assess the association between the type of vaccine and the number of pertussis cases. Results: The number of cases increased from 4083 in 1992 to 35,435 in 2024, with cyclical outbreaks in 2010, 2012–2014, and 2024. The third and fourth doses of pertussis vaccine coverage had mild and moderate correlations with the number of pertussis cases. The vaccine type had a significant association with the number of pertussis cases and stayed significant after adjusting for vaccination coverage. Conclusions: The switch in pertussis vaccine has impacted the epidemiology of pertussis outbreaks in the United States. A combination of factors, such as different types of immune response to vaccines, waning of immunity, and selection of non-vaccine bacterial strains, may explain the observed results. Further research on newer, improved vaccinations or alternative schedules in children needs to be conducted to address the resurgence of pertussis in this study. Full article

This study presents a novel, two-stage algorithm that minimizes the number of machines and operators required to produce multiple product types repeatedly in cyclic scheduling. Our algorithm treats the problem of minimum machines as a bin packing problem (BPP), and the problem of determining the number of operators required is also modeled as the BPP, but with constraints. The BPP is NP-hard, but with suitable heuristic algorithms, the proposed model allocates multiple product types to machines and multiple machines to operators without overlapping setup times (machine interference). The production schedule on each machine is represented as a circle (donut). By using lower bounds, it is possible to assess whether the number of machines required by our model is optimal; if not, the optimality gap can be quantified. The algorithm has been validated using real-world data from an industrial facility producing 17 types of products. The results of our algorithm led to significant cost savings and improved scheduling performance. The outcomes demonstrate the effectiveness of the proposed algorithm in optimizing resource utilization by reducing the number of machines and operators required. Although this study focuses on a manufacturing system, the model can also be applied to other contexts. Full article

We study the use of a homogeneous fleet of drones to design an unattended persistent drone-based patrolling system for vast circular areas. The drones follow flight missions supported by auxiliary on-ground charging stations, whose location and number must be determined. To this end, we first present a mixed integer non-linear programming model for defining cyclic schedules of drone flights considering the selection of the drone model from a set of candidate drone platforms. By imposing a minimum acceptable time between consecutive visits to any perimeter point, the objective consists of minimizing the total surveillance system deployment cost. The solution provides the best platform, the location of base stations, and the number of drones needed to monitor the perimeter, as well as the flight mission for each drone. We test five commercial platforms in six different scenarios whose radios vary between 1196 and 1696 m. In five of them, the MD4-100 Microdrones model achieves the lower cost solution, with values of EUR 66,800 and 83,500 for Scenarios 1 and 2 and EUR 116,900 for Scenarios 3, 4 and 5, improving its rivals in average percentages that vary between 8.46% and 70.40%. In Scenario number 6, the lower cost solution is provided by the TARTOT-500 model, with a total cost of EUR 168,000, improving by 20% the solution provided by the MD4-100. After obtaining the optimal solution, to evaluate the system robustness, we propose a discrete event simulation model incorporating uncertain flight times taking into account the possibility of accelerated depletion of drones’ Lithium-Ion polymer (Li-Po) batteries. Overall, our research investigates how various factors—such as the number of drones in the fleet and the division of the perimeter into sectors—impact the reliability of the system. Using Scenario number 3, our tests demonstrate that under a risk of battery failures of 2.5% and three UAVs per station, the surveillance system reaches a global percentage of punctually patrolled sectors of 92.6% and limits the number of delayed sectors (the relay UAV reaches the perimeter slightly above the required time, but it positively re-establishes the cyclic pattern for patrolling) to only a 5.6%. Our findings provide valuable insights for designing more robust and cost-effective drone patrol systems capable of operating autonomously over large planning horizons. Full article

(1) Background: The combination of venetoclax and hypomethylating agents (HMAs) is a standard first-line regimen for acute myeloid leukemia (AML) patients unfit for intensive chemotherapy. Since venetoclax-HMAs are usually administered until progression and delayed hematologic recovery is one of the limiting toxicities, cyclic administration including 7–14-day breaks is recommended. However, whether longer venetoclax schedules lead to higher response rates and how venetoclax pharmacokinetics correlate with toxicity and efficacy remains unclarified. In this single-center retrospective study, we analyzed how venetoclax plasma levels and treatment duration impact hematologic toxicity and treatment responses. (2) Methods: We analyzed the safety and efficacy of venetoclax-HMA combination regimens in a cohort of AML patients unfit for intensive chemotherapy treated at our institution between June 2020 and September 2023. The primary endpoint was the correlation between venetoclax plasma levels or administration schedule with hematologic recovery after the first cycle. Secondary endpoints included the following clinical outcomes: correlation with complete response (CR) status, progression-free survival, and overall survival. (3) Results: Within our cohort of 75 AML patients, we found no correlation between venetoclax plasma peak and trough levels, or venetoclax treatment duration (≤ or >14 days), and hematologic toxicity. Patients receiving shorter venetoclax schedules (≤14 days) had similar CR rates compared to patients treated with longer schedules. (4) Conclusions: Our results suggest that shorter (≤14 days) venetoclax schedules may have no negative impact on tumor responses in AML patients receiving venetoclax and HMA combinations. However, prospective validation studies would be required to confirm these findings. Full article

In the field of manufacturing, complex products with a tree structure often naturally exhibit asymmetric characteristics due to the uniqueness of their constituent elements and hierarchical relationships. In the production scheduling of such small-batch and multi-variety products, due to the influence of process constraints, many pieces of equipment will be idle for a long time in the production process. This increases the makespan of production and reduces the utilization rate of the equipment. Aiming at improving this situation, a resource cooperative scheduling algorithm is proposed to dynamically adjust the idle time of equipment: the integrated scheduling algorithm with dynamic adjustment of machine idle time based on an improved semi-numerical algorithm (ISA_DA). This algorithm adopts the critical path chain and the optimal scheduling strategy. On this basis, an adjustment strategy based on the semi-numerical algorithm considering the backward movement of the process is proposed, which improves the strength of the close connection of the process and the strength of parallel processing. Experimental results show that the effect of the proposed algorithm is better than the comparison algorithms: the hierarchical scheduling order algorithm and the process tree cyclic decomposition algorithm. It can increase the equipment utilization rate by 10% and 11.5%, respectively, and reduce the makespan by 28.6%. These experimental results strongly prove that the proposed algorithm can effectively reduce the total processing time and improve the production efficiency, whether it is for complex products with a symmetric structure or asymmetric structure. Full article

The Haidian District was, historically, rich in water resources. However, with urban development, the groundwater levels have declined, and most rivers have lost their ecological baseflows. To restore the aquatic ecosystems, the district has implemented a cyclic water network and advanced water replenishment projects. Nonetheless, the existing replenishment strategies face challenges, such as an insufficient scientific basis, lack of data, and high energy consumption. There is an urgent need to develop a scientifically robust ecological water replenishment system and optimize pump station scheduling to enhance water resource management efficiency. This study addresses the ecological water replenishment needs of seasonal rivers by integrating the Literature method, Rainfall-Runoff method, and R2cross method to develop a comprehensive approach for calculating the ecological flow and water depth. The proposed method simultaneously meets the ecological functionality and landscape requirements of seasonal rivers. Additionally, the SWMM model is employed to design intelligent pump station scheduling rules, optimizing the replenishment efficiency and energy consumption. Through field measurements and data collection, the ecological water demands of the river channels in different areas are assessed. Using a hydrodynamic model, the dynamic variations in the ecological flow and water depth are simulated. For the Cuihu, Daoxianghu, and Yongfeng areas, this study reveals that the current replenishment volume is insufficient to meet the landscape and ecological needs of the rivers. Most rivers require a 20–30% increase in water levels, with the Dazhai qu needing a substantial rise from 0.17 m to 0.3 m, representing an increase of 76%. Additionally, the results demonstrate that intelligent pump station scheduling can significantly reduce operating costs and energy consumption by dynamically adjusting the replenishment timing and flow rates. This approach optimizes the intervals between equipment activation and deactivation, thereby balancing ecological and energy-saving goals. This research not only provides technical support for the precise calculation of ecological replenishment volumes and the intelligent management of pump stations, but also offers scientific references for water resource management in similar regions. The findings will enhance the ecological functions and landscape quality of the rivers in the Haidian District while promoting refined and intelligent regional water resource management. Moreover, this study presents innovative solutions and theoretical foundations for water resource regulation under the backdrop of climate change. Full article

Earth’s rotation around its axis has pressured its inhabitants to adapt to 24 h cycles of day and night. Humans adapted their own circadian rhythms to the Earth’s rhythms with a light-aligned awake–sleep cycle. As a consequence, metabolism undergoes drastic changes throughout the circadian cycle and needs plasticity to cope with opposing conditions in the day (when there is an increase in energy demands and food availability), and during the night (when prolonged fasting couples with cyclic changes in the energy demands across the sleep stages). In the last century, human behavior changed dramatically with a disregard for the natural circadian cycles. This misalignment in sleep and eating schedules strongly modulates the metabolism and energy homeostasis, favoring the development of obesity, metabolic syndrome, and metabolic dysfunction-associated steatotic liver disease (MASLD). This review summarizes the effects of circadian disruption, with a particular focus on the feeding and sleep cycles in the development of MASLD and hepatocellular carcinoma. Full article

The intelligent monitoring of road surveillance videos is a crucial tool for detecting and predicting traffic anomalies, swiftly identifying road safety risks, rapidly addressing potential hazards, and preventing accidents or secondary incidents. With the vast number of surveillance cameras in operation, conducting traditional real-time video analysis across all cameras at once requires substantial computational resources. Alternatively, methods that employ periodic camera patrol analysis frequently overlook a significant number of anomalous traffic events, thereby hindering the effectiveness of traffic event detection. To overcome these challenges, this paper introduces a heuristic optimal scheduling approach designed to enhance traffic event detection efficiency while operating within limited computational resources. This method leverages historical data and prior knowledge to compute a weighted event feature value for each camera, providing a quantitative measure of its detection efficiency. To optimize resource allocation, a cyclic elimination mechanism is implemented to exclude low-performing cameras, enabling the dynamic reallocation of resources to higher-performing cameras, thereby enhancing overall detection performance. Finally, the effectiveness of the proposed method is validated through a case study conducted in a representative region of a major metropolitan city in China. The results revealed a substantial improvement in traffic event detection efficiency, with increases of 40%, 28%, 17%, and 28% across different time periods when compared to the pre-optimized state. Furthermore, the proposed method outperformed existing resource scheduling algorithms in terms of average load degree, load balance degree, and higher computational resource utilization. By avoiding the common issues of resource wastage and insufficiency often found in static allocation models, this approach offers greater flexibility and adaptability in computational resource scheduling, thereby effectively addressing the practical demands of traffic anomaly detection and early warning systems. Full article

Time-sensitive networking (TSN) is a kind of network communication technology applied in fields such as industrial internet and intelligent transportation, capable of meeting the application requirements for precise time synchronization and low-latency deterministic forwarding. In TSN, cyclic queuing and forwarding (CQF) is a traffic shaping mechanism that has been extensively discussed in the recent literature, which allows the delay of time-triggered (TT) flow to be definite and easily calculable. In this paper, two algorithms are designed to tackle the start time planning issue with the CQF mechanism, namely the flow–path–offset joint scheduling (FPOJS) algorithm and congestion-aware scheduling algorithm, to improve the scheduling success ratio of TT flows. The FPOJS algorithm, which adopts a novel scheduling object—a combination of flow, path, and offset—implements scheduling in descending order of a well-designed priority that considers the resource capacity and resource requirements of ports. The congestion-aware scheduling algorithm identifies and optimizes congested ports during scheduling and substantially improves the scheduling success ratio by dynamically configuring port resources. The experimental results demonstrate that the FPOJS algorithm achieves a 39% improvement in the scheduling success ratio over the naive algorithm, 13% over the Tabu-ITP algorithm, and 10% over the MSS algorithm. Moreover, the algorithm exhibits a higher scheduling success ratio under large-scale TSN. Full article

High-throughput screening systems are robotic cells that automatically scan and analyze thousands of biochemical samples and reagents in real time. The problem under consideration is to find an optimal cyclic schedule of robot moves that ensures maximum cell performance. To address this issue, we proposed a new efficient version of the parametric PERT/CPM project management method that works in conjunction with a combinatorial subalgorithm capable of rejecting unfeasible schedules. The main result obtained is that the new fast PERT/CPM method finds optimal robust schedules for solving large size problems in strongly polynomial time, which cannot be achieved using existing algorithms. Full article

Both radiation and cancer therapeutic vaccine research are more than 100 years old, and their potential is likely underexplored. Antiangiogenics, nanoparticle targeting, and immune modulators are some other established anticancer therapies. In the meantime, immunotherapy usage is gaining momentum in clinical applications. This article proposes the concept of a pulsed/intermittent/cyclical endothelial-sparing single-dose in situ vaccination (ISVRT) schedule distinguishable from the standard therapeutic stereotactic body radiotherapy (SBRT) and stereotactic radiosurgery (SRS) plans. This ISVRT schedule can repeatedly generate tumor-specific neoantigens and epitopes for primary and immune modulation effects, augment supplementary immune enhancement techniques, activate long-term memory cells, avoid extracellular matrix fibrosis, and essentially synchronize with the vascular normalized immunity cycle. The core mechanisms of ISVRT impacting in situ vaccination would be optimizing cascading antigenicity and adjuvanticity. The present proposed hypothesis can be validated using the algorithm presented. The indications for the proposed concept are locally progressing/metastatic cancers that have failed standard therapies. Immunotherapy/targeted therapy, chemotherapy, antiangiogenics, and vascular–lymphatic normalization are integral to such an approach. Full article

Time-Sensitive Networking (TSN) is a set of Ethernet standards aimed to improve determinism in packet delivery for converged networks. The main goal is to provide mechanisms that enable low and predictable transmission latency and high availability for demanding applications such as real-time audio/video streaming, automotive, and industrial control. To provide the required guarantees, TSN integrates different traffic shaping mechanisms including 802.1Qbv, 802.1Qch, and 802.1Qcr, allowing for the coexistence of different traffic classes with different priorities on the same network. Achieving the required quality of service (QoS) level needs proper selection and configuration of shaping mechanisms, which is difficult due to the diversity in the requirements of the coexisting streams under the presence of potential end-system-induced jitter. This paper discusses the suitability of the TSN traffic shaping mechanisms for the different traffic types, analyzes the TSN network configuration problem, i.e., finds the optimal path and shaper configurations for all TSN elements in the network to provide the required QoS, discusses the goals, constraints, and challenges of time-aware scheduling, and elaborates on the evaluation criteria of both the network-wide schedules and the scheduling algorithms that derive the configurations to present a common ground for comparison between the different approaches. Finally, we analyze the evolution of the scheduling task, identify shortcomings, and suggest future research directions. Full article

Isolated deep infiltrating endometriosis (DIE) of sacral nerve roots or major pelvic nerves, including the sciatic nerve, is considered to be extremely rare. Due to the overlap with sciatica symptoms, the diagnosis of sciatica DIE is difficult yet crucial, as it results in permanent neural damage if left untreated. We report a case of a 45-year-old woman who experienced a three-year-long and recently exacerbating pain in her right leg, accompanied by a tingling sensation and weakness in her right leg and foot, with difficulty walking. In between regular menstrual bleedings, when her aforementioned symptoms worsened, she had been experiencing mild 10-day extra-cyclical bleeding. Her neurologist’s, orthopedist’s, and gynecological examinations were unremarkable. Magnetic resonance imaging (MRI) showed an infiltrative lesion on the right sciatic nerve that was immunohistochemically confirmed to be endometriosis. The patient was treated with gonadotropin-releasing hormone analogues (GnRHa), which led to a significantly diminished size of the lesion on the control MRI, and endometriosis remission was obtained. For persistent mild, but cyclical, pain and muscle weakness, continuous progestagnes were administered, with advice for physical therapy provided for her neuro-muscle rehabilitation and a scheduled check-up in 6 months. Full article