Search Results (887)

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

For aircraft departure, which is a process of multi-resource coordination, strict time limitations, and complex condition constraints, the optimization of taxi-out time prediction is critical for enhancing airport surface operational efficiency, optimizing runway slot utilization, and reducing aircraft ground delay and fuel consumption. By combining aircraft taxi path and network traffic flow features, a refined airport road-level transport network model is constructed to accurately characterize the taxi path topology and node-edge attributes. On this basis, two new micro-features are introduced: estimated taxi time and the number of handovers. Experimental results show that after the introduction of the micro-features, the prediction accuracy of the taxi-out time prediction model within the error of 1 min increases from 49.29% to 54.41%, and the prediction accuracy within the error of 5 min reaches 99.42%. This method effectively addresses the limitations of traditional models that focus solely on the overall taxiing process while neglecting microscopic airfield network dynamics and time consumption during control handover procedures. The method can be integrated into the Airport Collaborative Decision Making (A-CDM) system to provide minute-level support for departure taxi-out time prediction, thereby providing a more precise and operationally aligned temporal benchmark for intelligent apron operations scheduling, aircraft sequencing optimization, and other collaborative decision making processes. Full article

This field study describes the successful implementation and evaluation of a Polymer-free Delayed Acid System, a next-generation acid retarder system that is chemically superior to traditional emulsified acid systems with an amphoteric-based surfactant. It is a polymer-free system that stimulates ultra-tight carbonate reservoirs in extreme sour and high-temperature conditions. The candidate well, located in an onshore gulf region field, for a major oil and gas company demonstrated chronically unstable production behavior for over two years, with test volumes fluctuating unpredictably between 200 and 400 barrels of oil per day. This indicated severe near-wellbore damage, high skin, and limited matrix permeability (<0.3 mD). The well was chosen for a pilot trial of the Polymer-free Delayed Acid System technology after a thorough formation study, which included mineralogical characterization and capillary diagnostics. The innovative acid retarder formulation, designed for deep matrix penetration and controlled acid–rock reaction, uses intrinsic encapsulation kinetics to significantly increase the acid’s reactivity, allowing it to bypass damaged zones, minimize acid leak-off, and initiate dominant wormhole propagation into the tight formation. The stimulation procedure began with a custom pre-flush designed to change nanoscale wettability and interfacial tension, so increasing acid displacement and assuring effective contact with the formation rock. Real-time injectivity testing and operational data collecting were performed prior to, during, and following the acid job, with pre-stimulation injectivity peaking at 1.2 bpm, indicating poor formation conductivity. Treatment with the Polymer-free Delayed Acid System resulted in a 592% increase in post-stimulation injectivity, indicating significant increases in near-wellbore permeability and successful propagation. However, a substantial operational difficulty arose: the well remained shut down for more than two months following the acid stimulation work due to surface infrastructure delays, notably the scheduling and execution of a flowline cleanup campaign. This lengthy closure slowed immediate flowback analysis and impeded direct assessment of treatment performance because production could not be tracked in real time. Despite this, once the surface system was operational and the well was open to flow, a structured production testing program was carried out over four quarterly intervals. The well regularly produced at an average stable rate of 500 bbl/day, more than doubling pre-treatment performance and demonstrating the long-term effectiveness and mechanical durability of the acid-induced wormhole network. Despite the post-job shut-in, the Polymer-free Delayed Acid System maintained the stimulating impact even under non-ideal settings, demonstrating its robustness. The Polymer-free Delayed Acid System outperforms conventional emulsified acid systems, giving better control over acid placement and reactivity, especially under severe reservoir conditions with bottomhole temperatures reaching 200 °F. This project offers a field-proven methodology that combines advanced chemical engineering, formation-specific design, and live diagnostics, as well as a scalable blueprint for unlocking hydrocarbon potential in similarly complicated, low-permeability reservoirs. Full article

To meet the escalating demands of massive data transmission, the next generation of wireless networks will leverage the multi-access edge computing (MEC) architecture coupled with multi-access transmission technologies to enhance communication resource utilization. This paper presents queue stability-constrained reinforcement learning algorithms designed to optimize the transmission control mechanism in MEC systems to improve both throughput and reliability. We propose an analytical framework to model the queue stability. To increase transmission performance while maintaining queue stability, queueing delay model is designed to analyze the packet scheduling process by using the M/M/c queueing model and estimate the expected packet queueing delay. To handle the time-varying network environment, we introduce a queue stability constraint into the reinforcement learning reward function to jointly optimize latency and queue stability. The reinforcement learning algorithm is deployed at the MEC server to reduce the workload of central cloud servers. Simulation results validate that the proposed algorithm effectively controls queueing delay and average queue length while improving packet transmission success rates in dynamic MEC environments. Full article

Battery-powered automatic guided vehicles (B-AGVs) serve as crucial horizontal transportation equipment in terminals and significantly impact the terminal transportation efficiency. Imbalanced B-AGV availability during terminal peak and off-peak periods is driven by dynamic vessel arrivals. We propose a flexible dual-threshold charging (FDTC) strategy synchronized with vessel dynamics. Unlike the static threshold charging (STC) strategy, FDTC dynamically adjusts its charging thresholds based on terminal workload intensity. And we develop a collaborative B-AGV scheduling and routing optimization model incorporating FDTC. A tailored Dijkstra-Partition neighborhood search (Dijkstra-Pns) algorithm is designed to resolve the problem in alignment with practical scenarios. Compared to the STC strategy, FDTC strategy significantly reduces the maximum B-AGV running time and decreases conflict waiting delays and charging times by 25.04% and 24.41%, respectively. Moreover, FDTC slashes quay crane (QC) waiting time by 40.78%, substantially boosting overall terminal operational efficiency. Full article

Background: Relapsed/refractory acute myeloid leukemia (R/R AML) remains a therapeutic challenge due to disease heterogeneity, resistance mechanisms, and poor tolerability to intensive regimens. Venetoclax (VEN), a BCL-2 inhibitor, has shown promise in combination with hypomethylating agents (HMAs), but data on response timing in the R/R setting are limited. The aim of this study was to assess the efficacy, safety, and kinetics of response to HMA-VEN therapy in a real-world cohort of R/R AML patients, with particular focus on early versus late responders. Methods: This prospective single-center study included 33 adult patients with R/R AML treated with VEN plus either azacitidine (AZA) or decitabine (DEC) from 2018 to 2021. The primary endpoint was the composite complete remission (cCR) rate and the rate of early and late response, respectively, occurring within two cycles of therapy or later; secondary endpoints included overall survival (OS), relapse-free survival (RFS), time to relapse (TTR), and safety. Results: The cCR was 58%, with complete remission (CR) or CR with incomplete recovery (CRi) achieved in 52% of patients. Median OS was 9 months. No significant differences in OS or TTR were observed between early (≤2 cycles) and late (>2 cycles) responders. Eight responders (42%) underwent allogeneic hematopoietic stem cell transplantation (HSCT), with comparable transplant rates in both groups of responders. Toxicity was manageable. Grade 3–4 neutropenia occurred in all patients, and febrile neutropenia occurred in 44% of patients. An Eastern Cooperative Oncology Group (ECOG) score >2 was associated with inferior response and shorter treatment duration. Conclusions: HMA-VEN therapy is effective and safe in R/R AML, including for patients with delayed responses. The absence of a prognostic disadvantage for late responders supports flexible treatment schedules and suggests that the continuation of therapy may be beneficial even without early blast clearance. Tailored approaches based on performance status and comorbidities are warranted, and future studies should incorporate minimal residual disease (MRD)-based monitoring to refine response assessment. Full article

Autonomous vehicles and intelligent traffic transportation are widely investigated for road networks. Context-aware traffic light scheduling algorithms determine signal phases by analyzing the real-time characteristics and contextual information of competing traffic flows. The context of traffic flows mainly considers the existence of regular, emergency, or heavy vehicles. This is an important factor in setting the phases of the traffic light schedule and assigning a high priority for emergency vehicles to pass through the signalized intersection first. VANET technology, through its communication capabilities and the exchange of data packets among moving vehicles, is utilized to collect real-time traffic information for the analyzed road scenarios. This introduces an attractive environment for hackers, intruders, and criminals to deceive drivers and intelligent infrastructure by manipulating the transmitted packets. This consequently leads to the deployment of less efficient traffic light scheduling algorithms. Therefore, ensuring secure communications between traveling vehicles and verifying the integrity of transmitted data are crucial. In this work, we investigate the possible attacks on the integrity of transferred messages and vehicles’ identities and their effects on the traffic light schedules. Then, a new secure context-aware traffic light scheduling system is proposed that guarantees the integrity of transmitted messages and verifies the vehicles’ identities. Finally, a comprehensive series of experiments were performed to assess the proposed secure system in comparison to the absence of security mechanisms within a simulated road intersection. We can infer from the experimental study that attacks on the integrity of vehicles have different effects on the efficiency of the scheduling algorithm. The throughput of the signalized intersection and the waiting delay time of traveling vehicles are highly affected parameters. Full article

Background/Objectives: Pseudohypoparathyroidism (PHP) is a group of genetic disorders characterized by end-organ resistance to multiple hormones, short stature, brachydactyly, subcutaneous ossifications, obesity, and developmental delays. The tissue specific imprinting of GNAS in the hypothalamus may lead to different eating behavior phenotypes in maternally inherited (PHP1A, PHP1B) vs. paternally inherited (PPHP) variants. In this exploratory study, we aimed to evaluate differences in eating behaviors in a cohort of patients with PHP1A, PPHP and PHP1B. Methods: Assessments included caregiver-reported measures (hyperphagia questionnaire, children’s eating behavior questionnaire, child feeding questionnaire) and self-reported measures (three factor eating behavior questionnaire). Results: A total of 58 patients with PHP1A, 13 patients with PPHP and 10 patients with PHP1B contributed data, along with 124 obese pediatric controls. An increased risk of obesity was found in PHP1A vs. PPHP (adult body mass index (BMI) 39.8 ± 8.7 vs. 30.2 ± 7.4 kg/m², p = 0.03). Parents reported significantly earlier onset of interest in food in children with PHP1A (2.0 ± 2.3 years) and PHP1B (1.1 ± 1.3 years) compared with controls (5.2 ± 3.2 years, p < 0.001). Measures of hyperphagia, satiety and other feeding behaviors were all similar to controls. The highest hyperphagia questionnaire scores were seen prior to adolescence. In a multi-year, longitudinal assessment of 11 pediatric patients with PHP1A, hyperphagia scores were stable and 25% showed an improvement in symptoms. Conclusion: Patients with PHP1A/1B may have hyperphagia symptoms from a young age but they do not worsen over time. Patients may overeat when allowed access to food, but do not usually have disruptive food seeking behaviors. Early diagnosis can give clinicians the opportunity to provide anticipatory diagnosis on the increased risk of obesity in PHP1A/1B and need for scheduled meals and controlled portions. Further studies with larger cohorts are needed to confirm these findings. Full article

Background/Objectives: Radical cystectomy performed via midline laparotomy is associated with substantial postoperative pain, frequently necessitating a high opioid consumption, which may impair immune function and delay recovery. The rectus sheath block (RSB) is widely used as part of multimodal analgesia to enhance postoperative pain control; however, the duration of analgesia is limited when using single-injection techniques. Dexamethasone has increasingly been used as a perineural adjuvant to prolong the effects of peripheral nerve blocks and enhance analgesia. This randomized controlled trial evaluated whether adding perineural dexamethasone to an RSB improves analgesic efficacy in patients undergoing a radical cystectomy. Methods: Fifty-two adult patients scheduled for radical cystectomy were randomly assigned to receive an ultrasound-guided bilateral RSB with either 0.25% ropivacaine alone or 0.25% ropivacaine combined with 4 mg dexamethasone per side after skin closure. Postoperative pain was assessed using a numeric rating scale (NRS) at 3, 6, 12, 18, 24, and 48 h following surgery. Cumulative intravenous patient-controlled analgesia (IV-PCA) in terms of fentanyl consumption and the incidence of rebound pain—defined as an increase in the NRS from ≤3 to ≥7 within 24 h after the block administration—were also recorded. Results: The dexamethasone group exhibited significantly reduced cumulative fentanyl consumption. Pain scores were consistently lower in the dexamethasone group compared with the ropivacaine-only group at all time points except 3 h postoperatively. The incidence of rebound pain was also substantially lower in the dexamethasone group. Conclusions: Perineural dexamethasone as an adjuvant to an RSB provides effective and prolonged analgesia, reduces opioid requirements, and lowers rebound pain incidence in patients undergoing a radical cystectomy. Full article

Risk management is crucial in engineering projects, especially in highly complex environments like petrochemical plants producing polyvinyl chloride (PVC). This study proposes a tailored risk management model, using analytic hierarchy process (AHP) and linear regression analysis, alongside MS Excel and IBM SPSS^® version 23, to identify, assess, and prioritize key risks. Surveys and interviews revealed seven management factors (budget, schedule, safety, productivity, contracting, quality, and environment) and 18 critical risks, including design errors and procurement delays. The model quantifies risk impacts, provides a regression equation for risk classification, and supports effective mitigation strategies. Based on this model, decision-making can be facilitated for the implementation of effective mitigation strategies. It also promotes continuous improvement, optimizing economic resources and minimizing environmental impacts, addressing a research gap in Colombia’s petrochemical sector and paving the way for broader industrial applications. Full article

The terminal maneuvering area (TMA) serves as a critical transition zone between upper enroute airways and airports, representing one of the most complex regions for managing high volumes of arrival and departure traffic. This paper presents the multi-route TMA scheduling problem as an optimization challenge aimed at optimizing TMA interventions, such as rerouting, speed control, time-based metering, dynamic minimum time separation, and holding procedures; the objective function minimizes schedule deviations and the accumulated holding time. Furthermore, the problem is formulated as a mixed-integer linear program (MILP) to facilitate finding solutions. A rolling horizon control (RHC) dynamic optimization framework is also introduced to decompose the large-scale problem into manageable subproblems for iterative resolution. To demonstrate the applicability and effectiveness of the proposed scheduling models, a hub airport—Chengdu Tianfu International Airport (ICAO code: ZUTF) in the Cheng-Yu Metroplex—is selected for validation. Numerical analyses confirm the superiority of the proposed models, which are expected to reduce aircraft delays, shorten airborne and holding times, and improve airspace resource utilization. This study provides intelligent decision support and engineering design ideas for the macroscopic-level collaborative optimization framework of the Integrated Arrival–Departure and Surface (IADS) system. Full article

Under the scenario of global climate warming, meteorological risks affecting sunflower cultivation in Xinjiang’s 10th Division were investigated by developing a meteorological-growth coupling model. Field experiments were conducted at three representative stations (A1–A3) during 2023–2024 to assess temperature and precipitation impacts on yield and quality traits among sunflower cultivars with varying maturation periods. The main findings were: (1) Early-maturing cultivar B1 (RH3146) exhibited superior adaptation at low-temperature station A1, achieving 12% higher plant height and an 18% yield increase compared to regional averages. (2) At thermally variable station A2 (daily average temperature fluctuation ± 8 °C, precipitation CV = 25%), the late-maturing cultivar B3 showed enhanced stress resilience, achieving 35.6% grain crude fat content (15% greater than mid-maturing B2) along with 8–10% increases in seed setting rate and 100-grain weight. These improvements were potentially due to optimized photoassimilated allocation and activation of stress-responsive genes. (3) At station A3, characterized by high thermal-humidity variability (CV > 15%) during grain filling, B3 experienced a 15-day delay in maturation and a 3% reduction in ripeness. Two principal mitigation strategies are recommended: preferential selection of early-to-mid maturing cultivars in regions with thermal-humidity CV > 10%, improving yield stability by 23%, and optimization of sowing schedules based on accumulated temperature-precipitation modeling, reducing meteorological losses by 15%. These evidence-based recommendations provide critical insights for climate-resilient cultivar selection and precision agricultural management in meteorologically vulnerable agroecosystems. Full article

By assuming that both travel and departure time are normally distributed variables, a multi-objective stochastic optimization model for the multi-airport flight cooperative scheduling problem (MAFCSP) with CvaR of travel and departure time is firstly proposed. Herein, conflicts of flights from different airports at the same waypoint can be avoided by simultaneously assigning an optimal route to each flight between the airport and waypoint and determining its practical departure time. Furthermore, several real-world constraints, including the safe interval between any two aircraft at the same waypoint and the maximum allowable delay for each flight, have been incorporated into the proposed model. The primary objective is minimization of both total carbon emissions and delay times for all flights across all airports. A feasible set of non-dominated solutions were obtained using a two-stage heuristic approach-based NSGA-II. Finally, we present a case study of four airports and three waypoints in the Beijing–Tianjin–Hebei region of China to test our study. Full article

The construction industry is one of the largest contributors to the world economy. However, the level of automation and digitalization in the construction industry is still at its infancy in comparison with other industries due to the complex nature and the large size of construction projects. Meanwhile, construction projects are prone to cost overruns and schedule delays due to the adoption of traditional progress monitoring techniques to retrieve progress on-site, having indoor activities participating with an accountable ratio of these works. Improvements in deep learning and Computer Vision (CV) algorithms provide promising results in detecting objects in real time. Also, researchers have investigated the probability of using CV as a tool to create a Digital Twin (DT) for construction sites. This paper proposes a model utilizing the state-of-the-art YOLOv8 algorithm to monitor the progress of bricklaying activities, automatically extracting and analyzing real-time data from construction sites. The detected data is then integrated into a 3D Building Information Model (BIM), which serves as a DT, allowing project managers to visualize, track, and compare the actual progress of bricklaying with the planned schedule. By incorporating this technology, the model aims to enhance accuracy in progress monitoring, reduce human error, and enable real-time updates to project timelines, contributing to more efficient project management and timely completion. Full article

Traditional project scheduling tools like Gantt charts struggle with dynamic adjustments and real-time optimization in complex construction projects, leading to inefficiencies and delays. This study addresses this challenge by proposing a dynamic optimization framework that integrates Building Information Modeling (BIM) and Artificial Intelligence (AI) to enhance schedule management. The framework comprises three layers: a data layer for collecting BIM and real-time site data, an analysis layer powered by AI algorithms for predictive analytics and optimization, and an application layer for visualizing progress and supporting decision-making. Through a case study on a large-scale water reservoir tunnel project in China, the framework demonstrated significant improvements in identifying schedule risks, optimizing resource allocation, and enabling real-time adjustments. Key innovations include a 4-in-1 Network Diagram Engine and a Blueprint Engine, which facilitate intuitive progress monitoring and automated task management. However, limitations in personnel skill matching, interface complexity, and mobile system performance were identified. This research advances the theoretical foundation of BIM-AI integration and provides practical insights for improving scheduling efficiency and project outcomes in the construction industry. Future work should focus on enhancing human resource management modules and refining system usability for broader adoption. Full article