Local Intensification Research Articles

DQL-assisted competitive evolutionary algorithm for energy-aware robust flexible job shop scheduling under unexpected disruptions

Energy-aware scheduling has emerged as a well-defined research topic for achieving sustainable development. However, unexpected disruptions in workshop pose several challenges to the manufacturing process, causing the original schedules to become non-optimal or even infeasible, resulting in significant energy waste. Consequently, it is necessary to investigate the robust scheduling problem with energy-awareness. The energy-efficient robust flexible job shop scheduling problem (ERFJSP) aims to simultaneously optimize scheduling efficiency, total energy consumption, and robustness. A two-stage mixed-integer linear programming model considering machine breakdown and job insertion is formulated in this paper for the first time. To solve this problem, a double Q-learning (DQL)-assisted competitive evolutionary algorithm (DQCEA) is proposed. In DQCEA, a heuristic initialization strategy is first designed, which allows it to obtain high-quality and diverse solutions. Subsequently, a multi-objective competitive mechanism is proposed to classify search individuals into inferiors and superiors. Moreover, an inferior-pushing and superior-pulling-based crossover is designed for inferior members, facilitating knowledge transfer within the population and enhancing global diversification capability. Meanwhile, a hyper-mutation operator is devised for superior members, which incorporates eight search strategies to improve local intensification ability. Furthermore, DQL is employed to learn and recommend the most suitable strategy for each superior individual. Finally, extensive experiments are carried out to evaluate the correctness of the formulated MILP model and the performance of DQCEA. Experimental analysis confirms that DQCEA effectively provides promising schedules under different scenarios, demonstrating its reliability in addressing unexpected disruption challenges.

A Dynamical Interpretation of the Intensification of the Winter North Atlantic Jet Stream in Reanalysis

Abstract Jet streams play an important role in determining weather variability and extremes. A better understanding of the mechanisms driving long-term changes in the jet is essential to successfully anticipate extreme meteorological events. This study analyzes the intensification trend of the North Atlantic jet using the ERA5 reanalysis and investigates the dynamical mechanisms involved. The results highlight the importance of an increase in diabatic heating in the free troposphere below the jet entrance over the Gulf Stream sector. This change in diabatic heating modifies the jet directly and produces a local intensification and a slight poleward shift. A two-dimensional frontal-geostrophic model illustrates this mechanism by considering the enhanced diabatic heating associated with the baroclinic growth of extratropical cyclones. The change in diabatic heating also affects the jet indirectly by increasing the mean baroclinicity and subsequent eddy momentum flux convergence. This indirect mechanism has also an effect downstream, where there is an acceleration of the jet core and reduced westerlies along the flanks, reducing the width of the jet. An idealized warming experiment confirms this mechanism by determining the jet response downstream of an idealized land–sea contrast. Finally, using a single-model ensemble of fully coupled climate simulations, we show that the differences in the evolution of the North Atlantic jet are related to the latitude of the increase in baroclinicity, which has a large spread. What emerges from the model hierarchy is a consistent dynamical chain of mechanisms associated with the intensification trend of the North Atlantic jet stream.

Impact of damaged housing on the performance of field aged composite High Voltage Insulators

Composite High Voltage Insulators (HVIs) are lightweight, inexpensive, and offer superior pollution performance. Consequently, they have replaced ceramic HVIs in highly contaminating coastal and desert regions. However, they are prone to degradation in harsh environments. In this paper, we assess the performance of three identical field-aged 380 kV composite HVIs with a service life of twelve years near the western coastal region of the Kingdom of Saudi Arabia. The housing of all the HVIs showed widespread damage, including cracks on sheds and shanks, partially or fully broken sheds, and rusted end fittings. The changes in morphology and material composition were assessed through SEM and EDX. An electrical breakdown test in the presence of steam fog revealed lowered withstand strength. Electric field distribution, a key design criterion for an HVI, was studied using the Finite Element Model (FEM) of the insulator bearing physical defects. The results reveal localized electric field intensification caused by all types of defects, notably smaller and narrower ones. Our findings indicate that while physical defects in HVIs can cause localized electric field intensification, they are not a significant concern unless accompanied by severe hydrophobicity loss, compromised electrical withstand levels, or extensive erosion exposing the fiberglass rod and jeopardizing mechanical stability.

Co-optimization of the operation and energy for AGVs considering battery-swapping in automated container terminals

Since the number of containers in automated container terminals (ACTs) has been growing, the operation of ACT relies on a large amount of electric power, which comes from the terminal energy system. As the main horizontal transportation equipment in ACTs, the scheduling of automated guided vehicles (AGVs) has become increasingly important. Even though AGV scheduling has been studied, the battery-swapping procedure is often overlooked, which hinders operation efficiency and the usage of renewable energy. We propose a co-optimization problem of the operation and energy for AGVs considering battery-swapping in this paper. A multi-objective model is constructed to minimize the makespan of AGVs and the operation and maintenance cost of energy system. In addition, we create a discrete multi-objective whale optimization algorithm to address this co-optimization problem. A load-balancing-based method for population initialization is developed to make the distribution of solutions more uniform in this algorithm. With the two-dimensional matrix encoding scheme, an individual right-shifted method is proposed for decoding. The best solution is assessed and selected through a fitness evaluation mechanism based on fuzzy correlation entropy. The bubble-net attack based on opposition-based learning is implemented to enhance the capacity for local intensification. Numerous tests confirm that the proposed method can guarantee the operation efficiency, lower the total cost of the energy system, and promote sustainable development in ACTs.

Strain-Dependent Assessment of Powassan Virus Transmission to Ixodes scapularis Ticks.

Powassan virus (POWV) is an emerging tick-borne encephalitic virus in Lyme disease-endemic sites in North America. Due to range expansion and local intensification of blacklegged tick vector (Ixodes scapularis) populations in the northeastern and upper midwestern U.S., human encephalitis cases are increasingly being reported. A better understanding of the transmission cycle between POWV and ticks is required in order to better predict and understand their public health burden. Recent phylogeographic analyses of POWV have identified geographical structuring, with well-defined northeastern and midwestern clades of the lineage II subtype. The extent that geographic and genetically defined sublineages differ in their ability to infect and be transmitted by blacklegged ticks is unclear. Accordingly, we determined whether there are strain-dependent differences in the transmission of POWV to ticks at multiple life stages. Five recent, low-passage POWV isolates were used to measure aspects of vector competence, using viremic and artificial infection methods. Infection rates in experimental ticks remained consistent between all five isolates tested, resulting in a 12-20% infection rate and some differences in viral load. We confirm that these differences are likely not due to differences in host viremia. Our results demonstrate that blacklegged ticks are susceptible to, and capable of transmitting, all tested strains and suggest that the tick-virus association is stable across diverse viral genotypes.

Origin and current activity of the Jiaocheng ground fissure, a 48 km long fissure in northern China

Since the mid to late 20th century, several regions in Northern China have had to contend with ground fissure disasters, with the FenWei basin and North China Plain being clear examples. The Jiaocheng ground fissure, which spans a total of 48 km in the FenWei basin, has caused severe damage to infrastructure along its path. In recent years, the local activity of the Jiaocheng ground fissure has worsened. Field investigations, mapping, trenching, geophysical surveys and other methods have been used to determine the origin mechanism and current activity characteristics of the Jiaocheng fissure. The Jiaocheng ground fissure has a general orientation stretching 48 km in the NE-NEE direction, inclining towards the SE. The Jiaocheng ground fissure involves horizontal tension and vertical dislocation, with segmented activity on the surface, with the most intense activity observed in the northern Qingxu section. In profile, it displays characteristics of synsedimentary faults and primary-secondary fissure combinations. The activity of the Jiaocheng fault underlies the occurrence of the Jiaocheng ground fissure. Over-extraction of groundwater has exacerbated the fissure activity. Recently, the Jiaocheng ground fissure has displayed localized intensification and the emergence of new fissures stretching towards the north. This has been linked to heightened tectonic activity in the northern region of the Taiyuan basin.

Patterns of Treatment Failure in Primary Central Nervous System Lymphoma.

Progression of PCNSL remains a challenge with salvage therapies, including the risk of substantial morbidity and mortality. We report patterns of first tumor progression to inform opportunities for improvement. This is an institutional retrospective review from 2002 to 2021 of 95 consecutive patients with pathologically confirmed PCNSL, of whom 29 experienced progressive disease. Kaplan-Meier method, log-rank test, and Cox proportional hazard models are used to characterize associations of patient, tumor, and treatment variables with LC, PFS, and patterns of first failure. Most patients were below 65 years old (62%) with KPS >70 (64%) and negative CSF cytology (70%). In 70 patients with MRIs, the median tumor volume was 12.6 mL (range: 0.5 to 67.8 mL). After a median follow-up of 11 months, 1-year PFS was 48% and 1-year LC was 80%. Of the 29 patients with progression, 24% were distant only, 17% were distant and local, and 59% were local only. On MVA, LC was associated with age (HR: 1.08/y, P =0.02), KPS (HR: 0.10, P =0.02), completion of >6 cycles of HD-MTX (HR: 0.10, P <0.01), and use of intrathecal chemotherapy (HR: 0.03, P <0.01). On UVA, local only first failure trended to be increased with >14 mL tumors (OR: 5.06, P =0.08) with 1-year LC 83% (<14 mL) versus 64% (>14mL). There were no significant associations with LC and WBRT ( P =0.37), Rituximab ( P =0.12), or attempted gross total resection ( P =0.72). Our findings reaffirm the importance of systemic and intrathecal therapies for local control in PCNSL. However, bulky tumors trend to fail locally, warranting further investigation about the role of local therapies or systemic therapy intensification.

A matheuristic-based multi-objective evolutionary algorithm for flexible assembly jobs shop scheduling problem in cellular manufacture

The flexible assembly job shop scheduling problem (FAJSP) and its extensions have received increased attention. However, multi-objective FAJSP in cellular manufacture (FAJSP-CM), a real-world extension of FAJSP with important applications in the mass customization of complex products, is barely considered in most previous studies. Hence, this study first addresses the multi-objective FAJSP-CM problem via a mixed-integer linear programming model (MILP). Then, a matheuristic-based multi-objective evolutionary algorithm (MMOEA), with a matheuristic decoding method, knowledge-guided initialization and learning-based local intensification method, is presented to efficiently tackle the FAJSP-CM problem in polynomial-time. The matheuristic decoding method, which hybrids a decomposition linear programming model (D-LP) that can quickly and optimally allocate the execution times of all operations, to search for the optimal solution in a specific space. The knowledge-guided initialization is extended to get a high-quality and great-diversity initial population for accelerated convergence. Meanwhile, the learning-based local intensification method is developed to adaptively coordinate five problem-specific local search operators to enhance the exploitation ability of the MMOEA algorithm. Finally, comprehensive experiments based on 720 instances are conducted to evaluate the proposed MILP model and MMOEA algorithm. The results of the first experiments illustrate the MILP model can obtain the Pareto solutions of small-scale instances. The remaining experiments demonstrate that the proposed MMOEA algorithm outperforms its competitors by 0.21 and 0.72 in hypervolume ratio and coverage indictors, along with approximately a 25 % improvement in success rate.

Intensifikasi Pajak Hiburan Oleh Badan Pendapatan Daerah (BAPENDA) Kabupaten Bandung Barat

Taxes are the largest component of the state's revenue source, so taxes have a crucial role in the Indonesian economy. The government in each year always strives so that tax revenue can always increase. This research is motivated by the realisation of entertainment tax revenue that did not reach the target in 2019, 2021 and 2022. The purpose of this study is to describe the efforts of Entertainment Tax intensification by the Regional Revenue Agency (Bapenda) of West Bandung Regency to increase entertainment tax revenue in West Bandung Regency. This research was conducted in West Bandung Regency, namely at the Regional Revenue Agency (BAPENDA) of West Bandung Regency. This research uses a qualitative descriptive method. The data collection techniques used are observation, interviews, and documentation. The data source of this research is primary data derived from the results of observations and interviews. Secondary data include tax and local tax revenue realisation, target data and realisation of entertainment tax revenue, and the number of entertainment taxpayers in West Bandung Regency. The main theory in this research is the theory of Local Tax Intensification from Kustiawan (2010). The results of this study indicate that the entertainment tax intensification activities of West Bandung Regency are still not well implemented and there are several obstacles. The obstacles that occur in this entertainment tax intensification activity are the lack of staff and limited human resources.

Investigating the Effects of Various Soil Amendments on Forages Production in the Field

An initial investigation into the utilization of recycled plant and animal residues as soil amendments (SAs), including compost, biochar, and soil conditioner, was conducted using alfalfa crops. This study evaluated the impact of SAs on alfalfa seed germination, resulting in an 87% germination rate for biochar, 82% for soil conditioner, and 82% for compost. In comparison, untreated seeds displayed a 78% germination rate. After successful germination, the SAs were employed to enhance soil health, with a focus on water conservation and increased forage yield. The study used sandy-textured soil with moderate alkalinity, very slight salinity, slight calcareousness, and high permeability. The germination trial confirmed that SAs usage did not hinder seed germination, even for salt-sensitive crops like alfalfa. Two field experiments were carried out in Al-Wafra, using different application rates of compost, biochar, and soil conditioner at 5, 7.5, and 10 tons per hectare. The results highlighted the positive impact of SAs application on increasing forage production, with varying degrees of enhancement, and confirmed a 40% reduction in water usage compared to treatment without SAs but under 100% irrigation (100% ETc). In conclusion, SAs show promising potential for local forages intensification and water conservation.

A Novel Artificial Electric Field Algorithm for Solving Global Optimization and Real-World Engineering Problems.

The Artificial Electric Field Algorithm (AEFA) stands out as a physics-inspired metaheuristic, drawing inspiration from Coulomb's law and electrostatic force; however, while AEFA has demonstrated efficacy, it can face challenges such as convergence issues and suboptimal solutions, especially in high-dimensional problems. To overcome these challenges, this paper introduces a modified version of AEFA, named mAEFA, which leverages the capabilities of Lévy flights, simulated annealing, and the Adaptive s-best Mutation and Natural Survivor Method (NSM) mechanisms. While Lévy flights enhance exploration potential and simulated annealing improves search exploitation, the Adaptive s-best Mutation and Natural Survivor Method (NSM) mechanisms are employed to add more diversity. The integration of these mechanisms in AEFA aims to expand its search space, enhance exploration potential, avoid local optima, and achieve improved performance, robustness, and a more equitable equilibrium between local intensification and global diversification. In this study, a comprehensive assessment of mAEFA is carried out, employing a combination of quantitative and qualitative measures, on a diverse range of 29 intricate CEC'17 constraint benchmarks that exhibit different characteristics. The practical compatibility of the proposed mAEFA is evaluated on five engineering benchmark problems derived from the civil, mechanical, and industrial engineering domains. Results from the mAEFA algorithm are compared with those from seven recently introduced metaheuristic algorithms using widely adopted statistical metrics. The mAEFA algorithm outperforms the LCA algorithm in all 29 CEC'17 test functions with 100% superiority and shows better results than SAO, GOA, CHIO, PSO, GSA, and AEFA in 96.6%, 96.6%, 93.1%, 86.2%, 82.8%, and 58.6% of test cases, respectively. In three out of five engineering design problems, mAEFA outperforms all the compared algorithms, securing second place in the remaining two problems. Results across all optimization problems highlight the effectiveness and robustness of mAEFA compared to baseline metaheuristics. The suggested enhancements in AEFA have proven effective, establishing competitiveness in diverse optimization problems.

Enhanced photocatalytic performance of Bi2MoO6 via strain engineering through collaborative optimization of indium doping and oxygen vacancies

Investigating lattice strain manipulation as an emerging strategy for improved photocatalysis, we introduce lattice strain into Bi2MoO6 nanosheets through synergistic indium doping and oxygen vacancies (OVs). Structural analysis reveals distinct compressive and tensile effects induced by indium doping and OVs, respectively, leading to localized lattice strain intensification. The optimized photocatalyst displays significantly enhanced tetracycline, ciprofloxacin, oxytetracycline, and norfloxacin removal activity due to increased active sites and improved charge carrier separation efficiency induced by lattice strain. Elucidation of tetracycline cleavage pathways and assessment of intermediate molecule toxicity are presented. This collaborative approach, merging doping and OVs for lattice strain induction, provides crucial insights for advancing bismuth-based photocatalysts.

A Reinforcement-Learning-Based 3-D Estimation of Distribution Algorithm for Fuzzy Distributed Hybrid Flow-Shop Scheduling Considering On-Time-Delivery.

With the increasing level of mass-customization and globalization of competition, environmentally friendly production scheduling for distributed manufacturing considering customer satisfaction has received growing attention. Meanwhile, uncertain scheduling is becoming a force to be considered within intelligent manufacturing industries. However, little research has been found that surveyed the uncertain distributed scheduling considering both energy consumption and customer satisfaction. In this article, the fuzzy distributed hybrid flow-shop scheduling problem considering on-time delivery (FDHFSP-OTD) is addressed, and a 3-D estimation of distribution algorithm (EDA) with reinforcement learning (RL) is proposed to minimize the makespan and total energy consumption while maximizing delivery accuracy. First, two heuristics and a random method are designed and used cooperatively for initialization. Next, an EDA with a 3-D probability matrix is innovated to generate offspring. Then, a biased decoding method based on Q -learning is proposed to adjust the direction of evolution self-adaptively. Moreover, a local intensification strategy is employed for further enhancement of elite solutions. The effect of major parameters is analyzed and the best combination of values is determined through extensive experiments. The numerical results prove the effectiveness of each specially designed strategy and method, and the comparisons with existing algorithms demonstrate the high-potential of the 3D-EDA/RL in solving the FDHFSP-OTD.

Characterizing First Events in LA-NSCLC Patients Treated with Chemoradiotherapy

Definitive chemoradiotherapy (CRT) is a standard treatment for locally advanced non-small cell lung cancer (LA-NSCLC). After treatment, patients are at risk for local disease recurrence, developing new sites of disease, and death without disease recurrence. Here, we characterize the rates of these events in a modern patient cohort and explore risk factors for each event. The hypothesis is that these rates and risk factors will better inform treatment strategies for local intensification and systemic therapy. We reviewed patients who underwent staging PET/CT and were treated for LA-NSCLC with definitive CRT at our institution between 2010 and 2022. Competing risks analyses were performed to calculate rates of disease progression and death without disease progression. Competing risks analyses were repeated after dividing disease progression into in-field recurrence versus out-of-field progression and after subdividing in-field recurrences into progression of high-risk (large) tumors or lymph nodes (defined as having metabolic tumor volume [MTV] >20 cc on staging PET/CT) versus progression of low-risk (small) tumors or lymph nodes. Predictors of each event type were identified using univariate and multivariable Fine and Gray competing risks regressions. A total of 210 patients met inclusion criteria, and the median follow-up duration is 43 months. Median age was 68 (IQR 60 to 74), and 77% of patients had ECOG performance status 0-1. Median progression-free survival and overall survival durations are 13 and 40 months, respectively. The 3-year cumulative incidence rate (CIR) of disease progression was 58%, and the 3-year CIR of death without disease progression was 18%. The 3-year CIR for out-of-field disease progression was 44%, and the 3-year CIR for in-field recurrence was 14%. The 3-year CIR for in-field recurrence of high-risk lesions was 11%, and the 3-year CIR for low-risk lesions was 4%. Multivariable analyses examining predictors of out-of-field progression revealed two statistically significant factors: total disease burden on PET (SHR 1.03 per 10 cc, p = 0.013) and durvalumab receipt (SHR 0.60, p = 0.031). Multivariable analyses also revealed two predictors of death without disease progression: age (SHR 1.06 per year, p = 0.018) and ECOG performance status (SHR 1.81, p = 0.012). For LA-NSCLC patients treated with definitive CRT, we found that developing new sites of disease is the most common first event, followed by death without disease recurrence. In-field disease recurrence is relatively uncommon, particularly when treating relatively small tumors and lymph nodes. These findings may inform prioritization of strategies to improve systemic therapy, intensify local therapy, and minimize treatment-related toxicity.

Potential for climate change driven spatial mismatches between apple crops and their wild bee pollinators at a continental scale

Visitation by wild bee species alongside managed pollinators is necessary to ensure consistent yields and fruit quality in apple fields. Wild bee species are vulnerable to several environmental changes. Climate change is expected to lead to broad-scale changes to wild bee distributions that will impact the service they provide as crop pollinators. We modelled selected wild bee species known to be important for apple production in Europe and we quantified the shifts in distribution range for these key apple-pollinating bee species (KABS) under three climate‌ change scenarios (RCP 2.6, 4.5 and 8.5) for 2041–2060 and 2061–2080. We compared species distribution maps (after the expected range changes) to the distribution of areas with suitable habitat for apple orchards and with national apple production statistics to estimate potential pollination service at the landscape scale. Overall, ‌KABS are widespread species found across Europe and while most species have projected range contractions, these contractions are limited (∼10% loss). Only under the worst-case climate change scenario (RCP8.5) do we project range contractions over 50% and only under RCP8.5 is the average loss of overlap between suitable apple conditions and KABS likely to decrease by over 10%. However, range contractions at the southern limit of many species’ ranges mean that the potential impact of climate change on apple pollination is not evenly shared between apple producing countries; France and Italy for example are projected to have high range loss of KABS and loss in potential pollination service. Climate change is not the only threat to apple pollination and future pollination deficits will also depend on local orchard intensification and ecological infrastructure. Key changes to intensive, commercial apple orchards towards a more agroecological approach are needed to maintain a diverse wild bee community and apple production in areas that may become climatically unsuitable in the future.

Mesoscale Factors Contributing to the Extreme Rainstorm on 20 July 2021 in Zhengzhou, China, as Revealed by Rapid Update 4DVar Analysis

Abstract The purpose of this study is to diagnose mesoscale factors responsible for the formation and development of an extreme rainstorm that occurred on 20 July 2021 in Zhengzhou, China. The rainstorm produced 201.9 mm of rainfall in 1 h, breaking the record of mainland China for 1-h rainfall accumulation in the past 73 years. Using 2-km continuously cycled analyses with 6-min updates that were produced by assimilating observations from radar and dense surface networks with a four-dimensional variational (4DVar) data assimilation system, we illustrate that the modification of environmental easterlies by three mesoscale disturbances played a critical role in the development of the rainstorm. Among the three systems, a mesobeta-scale low pressure system (mesolow) that developed from an inverted trough southwest of Zhengzhou was key to the formation and intensification of the rainstorm. We show that the rainstorm formed via sequential merging of three convective cells, which initiated along the convergence bands in the mesolow. Further, we present evidence to suggest that the mesolow and two terrain-influenced flows near the Taihang Mountains north of Zhengzhou, including a barrier jet and a downslope flow, contributed to the local intensification of the rainstorm and the intense 1-h rainfall. The three mesoscale features coexisted near Zhengzhou in the several hours before the extreme 1-h rainfall and enhanced local wind convergence and moisture transport synergistically. Our analysis also indicated that the strong midlevel south/southwesterly winds from the mesolow along with the gravity-current-modified low-level northeasterly barrier jet enhanced the vertical wind shear, which provided favorable local environment supporting the severe rainstorm.

A knowledge-based NSGA-II algorithm for multi-objective hot rolling production scheduling under flexible time-of-use electricity pricing

With the increasing demand and shortage of energy, the iron and steel industry has focused on achieving low-carbon and smart manufacturing. This study investigates an energy-oriented scheduling problem arising from hot rolling production under flexible time-of-use (TOU) electricity tariffs, where the electric power comes from both the enterprise-owned power plant and the state-owned power grid. First, we model the studied scheduling problem as a multi-objective prize-collecting vehicle routing problem with special constraints. This model selects slabs from the order pool and sequences them to form rolling units, aiming to simultaneously minimize the transition costs in specifications, penalty costs, and electricity costs. Next, we develop a knowledge-based NSGA-II algorithm (KB-NSGA-II) by introducing a self-adaptive recombination procedure and a shortest path search (SPS)-based local intensification procedure. Furthermore, the comparative experimental results indicate that the KB-NSGA-II outperforms other competing algorithms in terms of the following indicators: (1) the hypervolume indicator is improved by approximately 57%; (2) the Spacing indicator is decreased by approximately 40%; and (3) the success ratio indicator of KB-NSGA-II is at least 60% higher than that of other competing algorithms. Finally, we apply a multi-criteria decision-making method named VIKOR to a case study under flexible TOU pricing strategies. These comparison results and the case study confirm that the KB-NSGA-II algorithm obtained better computational performance than the other competing algorithms and provided more flexible solutions under TOU pricing.

On the effects of surface waviness upon catalytic steam reforming of methane in micro-structured reactors - a computational study

The effects of wavy channels upon steam methane reforming in catalytic micro-structured reactors, using Nickle as the catalyst, are investigated numerically. Laminar, three-dimensional models of reacting flows, with heterogeneous chemistry, are developed and applied to micro-structured reactors with different wave patterns on their internal walls. It is observed that introduction of surface waves on the walls of reactor, can significantly alter production and consumption of H2 and CH4. This is shown to be due to large fluctuations in convective mass and heat transfer, induced by the surface waviness. In particular, it is shown that separation and reattachment of concentration and thermal boundary layers and the subsequent modifications in Sherwood and Nusselt number can significantly affect the catalytic processes over the walls of reactor. A major local intensification of catalytic processes is observed where Sherwood and Nusselt number are maximised. Similarly, the catalytic process becomes highly inefficient in places with minimal Sherwood (and Nusselt) number. The analyses further reveal that a strategic discrete coating of wavy walls with the catalyst can substantially improve the performance of microstructure. For example, by coating only 25% of the surface area of wavy walls, CH4 conversion rate and selectivity per coated surface area increase by 459% and 308% compared to those of an equivalent fully coated straight channel. This implies the possibility of developing highly efficient and cost-effective catalytic micro-reactors for production of hydrogen from methane.

Phase III study of local or systemic therapy intensification directed by PET in prostate cancer patients with post-prostatectomy biochemical recurrence (INDICATE): ECOG-ACRIN EA8191.

TPS5118 Background: Salvage radiation therapy (sRT) to the prostate bed and pelvic nodes with short-term androgen deprivation therapy (STAD) is considered a standard of care (SOC) salvage therapy (ST) paradigm for prostate cancer (PC) patients (pts) with post-prostatectomy (RP) biochemical recurrence (BCR). PET imaging with recently FDA-approved agents in this setting (18F-Fluciclovine, 18F-DCFPyL and 68Ga-PSMA-11), have shown improved accuracy for detection of metastases not identified with conventional imaging (CIM). Given the greater sensitivity and specificity of PET, its findings are being increasingly but variably applied to justify modification or omission of SOC therapies without high-level evidence of clinical benefit. PET may help identify candidates for different treatment intensification approaches. In metastatic prostate cancer, metastasis-directed RT (MDT) has been used to avoid or delay systemic therapy in men with oligometastatic disease. Apalutamide (Apa) is an androgen receptor signaling inhibitor that has been shown to improve outcomes when added to ADT in mCSPC. This study will evaluate whether patients with PET-detected lesions outside the pelvis will benefit from addition of MDT to treatment intensification with STAD/Apa, and whether patients with no PET-detected lesions outside the pelvis will benefit from addition of Apa to standard sRT/STAD. Methods: PC pts with post-RP BCR (PSA &gt; 0.5ng/mL; &gt; 0.2ng/mL if first detectable within 12 mos of RP) and no extrapelvic metastases on CIM who are candidates for SOC ST (sRT to prostate bed and pelvic nodes with STAD) are eligible. Pts will undergo SOC baseline PET using a FDA-approved tracer. Based on institutional clinical interpretation of the SOC PET, pts will be placed in Cohort 1 (PET-negative) or 2 (PET-positive for extra-pelvic metastases). Cohort 1 will be randomized to SOC ST +/- Apa for 6 months and Cohort 2 will be randomized to SOC ST and Apa +/- MDT to PET-positive lesions. The primary endpoint is PFS, defined as time from randomization to radiographic progression on CIM, symptomatic disease or death, whichever occurs first. Primary objectives are to evaluate whether addition of Apa to SOC ST and addition of MDT to SOC ST and Apa could prolong PFS in Cohorts 1 and 2, respectively. For Cohort 1, 480 pts will be randomized with 85% power to distinguish a 5-year PFS rate of 90% (Apa arm) vs. 80% (SOC arm) using one-sided stratified logrank test with type I error of 0.025. For Cohort 2, 324 pts will be randomized with 85% power to distinguish a 5-year PFS rate of 76.5% in the experimental arm from 61.5% in the control arm. Secondary endpoints include overall and event-free survival, toxicity, PET progression and quality of life. Clinical trial registry number: NCT04423211. Clinical trial information: NCT04423211 .

Ship traffic optimization method for solving the approach channel and lock co-scheduling problem of the Three Gorges Dam on the Yangzi River

Since the demands of waterway transport on the Yangzi River have been growing in recent years, traffic congestion at Three Gorges Dam (TGD) has become a very serious issue, which leads to long waiting time as well as environmental pollution. To improve the efficiency of the ship traffic scheduling, this paper investigates an approach channel and lock co-scheduling problem of the TGD on the Yangzi River. A new mathematical model is presented to optimize the lock chamber utilization rate, average waiting time and total energy consumption of ships, simultaneously. To solve this problem, a multi-objective metaheuristic algorithm (MOMA) based on fuzzy correlation entropy is proposed. In the algorithm, with a ship sequence encoding scheme, a pre-grouping panning approach is firstly designed for decoding. Then, a fitness evaluation mechanism using fuzzy correlation entropy is adopted to assess the solutions. Finally, an adaptive local reinforcement search strategy is introduced to improve local intensification ability. Various simulation experiments are carried out based on the real historical data at TGD. Computational results demonstrate the applicability and effectiveness of proposed MOMA. The result of this study is very useful for TGD to improve the ship traffic efficiency and save energy.