Scheduling Period Research Articles

A Social Media Survey of US Adolescent Preferences for Menstrual Bleeding Patterns

Study ObjectiveAssess preferences for menstrual pattern and acceptability and knowledge about safety of induced amenorrhea among adolescents and young adults MethodsWe conducted a cross-sectional online survey of U.S. residents aged 14-24 years at least one-year post-menarche. Online recruitment was via the social media platform “TikTok” on a teen reproductive health channel. Survey questions focused on menstrual history, menstrual pattern preferences, and demographics. The primary outcome was the proportion of post-menstrual individuals who would prefer amenorrhea versus scheduled bleeding. ResultsFrom 5,113 potential respondents who accessed the eligibility screening, 3,001 completed surveys and met inclusion criteria. Most were age 14-18 (63.7%), distributed proportionally among all U.S. Census Regions. When asked if they could pick their period-bleeding style without any permanent impacts, almost three-quarters chose no bleeding at all (amenorrhea; 71.5%) compared to scheduled periods; 28.5%). However, 63.7% agreed or were uncertain when faced with the statement: “It might be unsafe if hormone medications stop your period-bleeding.” After adjusting for age, gender expression, race, religion, heavy bleeding, and frequent bleeding, factors associated with preference for amenorrhea versus regular bleeding were younger age, masculine gender expression, white race, and non-Christian religious background. Baseline bleeding amount and frequency were not associated with preference for amenorrhea. ConclusionsMore than two-thirds of U.S. adolescents and young adults indicated a preference for medication-induced amenorrhea if the method was assured to not have any permanent effects on the body, despite highly prevalent misconceptions about health and safety.

Interference Avoidance through Periodic UAV Scheduling in RIS-Aided UAV Cluster Communications

This article investigates the transmission of downlink control signals for multiple unmanned aerial vehicle (UAV) clusters in collaborative search and rescue operations in mountainous environments. In this scenario, a reconfigurable intelligent surface (RIS) mounted on the UAV is utilized to overcome obstacles between the ground base station (BS) and UAVs. By leveraging the fixed channel of the RIS to the BS, the line-of-sight (LoS) path characteristics of the air-to-air channel, and the position information of the UAV, the RIS forms a directional beam by adjusting the RIS coefficient, which points towards UAVs in the cluster. To ensure low delay in control signaling and UAV state transmission, we adopt semi-persistent scheduling (SPS), which allocates pre-specified periodic intervals to each UAV for the formation of corresponding RIS coefficients. The allocation of time slots is constrained by the transmission intervals required by different UAVs and the number of RISs available. We propose a time slot scheduling scheme for UAVs to reduce inter-cluster interference caused by RIS beams. The time slot allocation problem is formulated as a combinatorial optimization problem. To solve this problem, we first propose an intuitive greedy scheme called local interference minimization (LIM). Building upon the LIM scheme, we propose a rollout-based algorithm called rollout interference minimization (RIM). Through simulation, we compare the LIM and RIM schemes with the benchmark scheduling scheme. The results demonstrate that our proposed scheme significantly reduces interference between UAV clusters while satisfying the conditions of periodic transmission and RIS quantity constraints.

CO2 Emission-Constrained Short-Term Unit Commitment Problem Using Shuffled Frog Leaping Algorithm

The increasing concerns about greenhouse gas emissions have made it necessary to incorporate environmental constraints in the operation of power systems. The CO2 emission-constrained short-term unit commitment problem (CSCUCP) is a multiobjective optimization problem that involves minimizing both the cost of operation and the CO2 emissions. This paper proposes an integer-coded shuffled frog-leaping algorithm (SFLA) to minimize both total CO2 emissions and operating costs for the unit commitment problem (UCP) over a one-day scheduling period. The SFLA is inspired by the natural food-searching behavior of frogs. The proposed method aims to determine the optimal start-up and shut-down times for generating units to meet fluctuating loads while minimizing operating costs and CO2 emissions. The method takes into account fuel costs, start-up and shut-down costs, and maintenance costs while satisfying various constraints. The study uses the IEEE 39 bus with a 10-unit test system, and the results are related to conventional methods. The proposed method consistently produces lower CO2 emissions and total operating costs compared to the existing methods.

Periodic timetabling with integrated track choice for railway construction sites

We propose a mixed-integer linear programming model to generate and optimize periodic timetables with integrated track choice in the context of railway construction sites. When a section of a railway network becomes unavailable, the nearby areas are typically operated close to their capacity limits, and hence carefully modeling headways and allowing flexible routings becomes vital. We therefore discuss first how to integrate headway constraints into the Periodic Event Scheduling Problem (PESP) that do not only prevent overtaking, but also guarantee conflict-free timetables in general and particularly inside stations. Secondly, we introduce a turn-sensitive event-activity network, which is able to integrate routing alternatives for turnarounds at stations, e.g., turning at a platform vs. at a pocket track for metro-like systems. We propose several model formulations to include track choice, and finally evaluate them on six real construction site scenarios on the S-Bahn Berlin network.

Online Bipartite Matching with Reusable Resources

We study the classic online bipartite matching problem with a twist: off-line vertices, called resources, are reusable. In particular, when a resource is matched to an online vertex, it is unavailable for a deterministic time duration d, after which it becomes available again for a rematch. Thus, a resource can be matched to many different online vertices over a period of time. Whereas recent work on the problem has resolved the asymptotic case in which we have large starting inventory (i.e., many copies) of every resource, we consider the (more general) case of unit inventory and give the first algorithms that are provably better than the naïve greedy approach, which has a competitive ratio of (exactly) 0.5. Our first algorithm, which achieves a competitive ratio of 0.589, generalizes the classic RANKING algorithm for online bipartite matching of nonreusable resources (Karp et al. 1990) by reranking resources independently over time. Whereas reranking resources frequently has the same worst case performance as greedy, we show that reranking intermittently on a periodic schedule succeeds in addressing reusability of resources and performs significantly better than greedy in the worst case. Our second algorithm, which achieves a competitive ratio of 0.505, is a primal-dual randomized algorithm that works by suggesting up to two resources as candidate matches for every online vertex and then breaking the tie to make the final matching selection in a randomized correlated fashion over time. As a key component of our algorithm, we suitably adapt and extend the powerful technique of online correlated selection (Fahrbach et al. 2020) to reusable resources in order to induce negative correlation in our tie-breaking step and beat the competitive ratio of 0.5. Both of our results also extend to the case in which off-line vertices have weights. Funding: R. Niazadeh’s research is supported by the Asness Junior Faculty Fellowship at The University of Chicago Booth School of Business.

Deep reinforcement learning-based approach for dynamic disassembly scheduling of end-of-life products with stimuli-activated self-disassembly

Remanufacturing is one of the most critical strategies for end-of-life product management to promote a circular economy; however, it has been seen very limited implementation due to the labor-intensive and time-consuming disassembly processes for component retrieval. The newly emerged 4D printing technology enables the fabrication of stimuli-responsive reconfigurable structures, outlining new ways to achieve non-destructive and simultaneous self-disassembly of components with different geometry. However, large uncertainties and increased process dynamics have also emerged directly pertaining to the real-time scheduling in disassembly lines with self-disassembly workstations, which the existing scheduling methods are not equipped to handle. In this study, a constrained multi-agent deep reinforcement learning approach is proposed to maximize the disassembly profit by dynamically changing the batch mixing ratios of different-sized components in self-disassembly workstations and adapting real-time scheduling to stochastic product quality, changes in operational sequences, and self-disassembly failures. The proposed approach is validated on a disassembly line for hand pulse detectors that contain heat-activated self-disassembly components. Numerical results show that the proposed achieves stable convergence under uncertainties, and the implementation of a dynamic batch mixing scheme in self-disassembly operations yields a substantial improvement in disassembly profit over the scheduling period. In addition, sensitivity analyses are conducted to evaluate the impacts of system uncertainties on the profitability of the disassembly line.

Introducing TimPassLib – A Library for Integrated Periodic Timetabling and Passenger Routing

Classic models to derive a timetable for public transport often face a chicken-and-egg situation: A good timetable should offer passengers routes with small travel times, but the route choice of passengers depends on the timetable. While models that fix passenger routes were frequently considered in the literature, integrated models that simultaneously optimize timetables and passenger routes have seen increasing attention lately. This creates a growing need for a set of instances that allows to test and compare new algorithmic developments for the integrated problem. Our paper addresses this requirement by presenting TimPassLib, a new benchmark library of instances for integrated periodic timetabling and passenger routing.

Replay attack detection and mitigation for cyber–physical systems via RADIR algorithm with encryption scheduling

This paper investigates the security state estimation issue facing replay attacks in confidential cyber–physical systems. Smart sensor equipped with a power harvester transmits critical measurements to the remote estimator over wireless networks, in which the transmission modes include encrypted and normal. In order to complete the persistent threats, the adversary launches multi-stage discontinuous replay attacks to compromise the estimation process. In virtue of the designed label detection scheme, we transform attack detection into encryption scheduling optimization under the constraint of sensor energy harvesting and acquire a rigorous relationship between detection probability, attack duration, and encryption ratio. Different from most existing studies only focusing on attack detection, the localization of replay interval measured by detection immediacy is also analyzed. Subsequently, the optimal periodic encryption scheduling strategy is given to maximally determine the attack interval by adopting an optimization-based approach. Further, a complete algorithm of replay attack detection, isolation, and recovery (RADIR) is designed to minimize deterioration from multi-stage attacks, which can guarantee the estimated performance of the system as much as possible. Finally, the unmanned ground vehicle system is applied to validate the theoretical results, where the dataset of replay attacks is obtained by capturing the normal operation data of a moving vehicle. Also, we compare the optimal encryption strategy designed in this paper with general centralized and random scheduling strategies.

Calculation of the Timing of the Replacement of Relay Equipment for Railway Automation and Telemechanic

In 2021, at the Obukhovo station of the Oktyabrskaya railway. testing of the technology for counting the number of operations of relay equipment began. The results of testing the technology at the Obukhovo station showed that relay equipment with a high intensity of operation generates faster the standard number of operations specified in the technical specifications for the equipment. Relay equipment with a high intensity of operation needs to be replaced earlier than the scheduled period, and equipment with a low intensity of operation needs to be replaced less often than the scheduled period. The routine method of replacing relay equipment does not take into account the intensity of its work. The article proposes a scientific approach that allows you to manage the resource of the relay equipment of railway automation and telemechanic at the stage of its operation based on the calculation of the timing of its replacement. To calculate the timing of the replacement of relay equipment, objective data on the values of their actual number of operations are used. The article proposes the calculation of the timing of the replacement of relay equipment based on its characteristics, service life under technical conditions, scheduled terms in the instructions, and the intensity of its work. The calculation of the cost of failure and maintenance of relay equipment over the entire service life is given to determine the optimal replacement period for relay equipment, for which the replacement period occurs earlier than the scheduled period. The calculation of the timing of the replacement of relay equipment makes it possible to switch from the scheduled maintenance method to maintenance based on the actual state and ensure the transition to address planning. This will reduce labor costs for maintenance and the risk of relay equipment failures.

Real-Time Fixed Priority Scheduling Synthesis using Affine DataFlow Graphs: from Theory to Practice

The major drawback of using static schedules to execute dataflow applications is their high inflexibility. In real-time systems, periodic schedules make it easier to assert safety guarantees and to decrease the schedule size, but their characteristics remain hard to compute. This article presents an approach to automatically generate fixed priority schedules from a dataflow specification. To do so, precedence dependencies between actors in the dataflow graphs are abstracted, as well as the task periods, by using affine relations . This abstraction allows us to synthesize schedules efficiently considering two main objectives: the maximization of throughput and the minimization of buffer sizes. Given a dataflow graph to execute in a real-time environment, we transform it into an Affine DataFlow Graph (ADFG) and compute the task priorities, their mapping, the number of delays in the buffers, and the buffer sizes. This article is the first to present an overview of both theoretical and practical aspects of ADFG. On the theoretical side, it presents corrections and improvements on the fixed priority case. On the practical side, benchmark evaluations demonstrate the robustness and maturity of the approach that our scheduling synthesizer implements. Synthesized schedules are evaluated by using scheduling simulation and real-time implementation. Last but not least, the synthesized periods reach the optimal throughput if enough processors are available, and most of the time the periods reach the maximal processor utilization factor in the uni-processor case. Moreover, execution time of the synthesis is about only one second for the main proposed algorithms.

Radiological characterization for the disposal of a decommissioned LHC external beam dump at CERN

During the last Long Shutdown, a scheduled maintenance period between physics runs, the two Large Hadron Collider (LHC) beam dumps were replaced with upgraded spares modules. It was then decided to conduct an in-house autopsy and a post-irradiation examination of the removed dumps to extract information essential for the 3rd LHC physics run and to aid the design of new generations of beam dumps able to cope with future upgrades of the LHC. The need for a postmortem analysis of the dump cores opened the opportunity to combine the autopsy with processes required for the disposal of the dumps as radioactive waste at a dedicated disposal facility in France. This had a direct impact in terms of overall optimization of the interventions (postmortem analysis and prepackaging) to be performed on the dump as well as in terms of minimizing of the radiological risk (ALARA), by reducing the exposure of the personnel by combining two interventions in one. The characterization of the dump as radioactive waste was performed by means of state-of-the-art Monte Carlo and analytical techniques verified experimentally via a series of dedicated radiochemical (using liquid scintillation) analyses, conducted in-house and in external specialized laboratories. Based on these results, the dumps will be disposed of as intermediate–medium-level (FMA-VC) waste at the ANDRA CSA repository in France.

Impact of reflex locomotion and the Bobath concept on clinical and biomolecular parameters in people with multiple sclerosis: study protocol for a randomized controlled trial.

Multiple sclerosis (MS) is a progressive disease with a fluctuating and unpredictable course that has no curative treatment at present. One of its main characteristics is the variety of signs and symptoms that produce a high percentage of patients who present alterations in balance and gait during the development of the disease, decreased muscle strength, spasticity, or decreased pimax. Rehabilitative therapy, especially physiotherapy, is the main course of the treatment of these alterations using reflex locomotion and the Bobath concept as a form of kinesitherapy that activates the preorganized circuits of the central nervous system. The objective of this study is to evaluate the reflex locomotion and Bobath concept effects on balance, spasticity, reaction time, respiratory parameters, and lacrimal biomolecular markers. This is a randomized controlled trial on the effectiveness of two neurorehabilitation techniques in patients with multiple sclerosis conducted at the University of Salamanca. The research will take place at the Faculty of Nursing and Physiotherapy, University of Salamanca. The study will be conducted from June 2023 to June 2024. The reflex locomotion group will receive individual sessions of therapy (n = 27), and the Bobath concept group (n = 27) will receive the same number of sessions. Both groups will receive two sessions per week for 12 months. The measurement variables will be the Berg Balance Scale, the Tardieu Scale, the Cognitfit Program, Maximum Inspiratory Pressure, and Lacrimal Biomarkers. This study has been approved by the Ethics Committee of the University of Salamanca on March 2023 (ref: 896). The main limitations of this study are the selection and number of patients, the delay in implementing the therapy within the initially scheduled period, inadequate sample collection, and inadequate sample processing. ClinicalTrials.gov; identifier: NCT05558683.

High Engagement in Care in a Pediatric Medical Home for Children Impacted By Parental Substance Use.

The opioid epidemic has heavily affected adults of childbearing age, leading to thousands of children impacted by parental substance use. Few programs provide longitudinal support to these children. This article describes an innovative pediatric medical home model for substance-impacted children and their families, at an urban safety-net hospital. The team-based program directly serves children, and also devotes significant resources to parental health and recovery. In the program's first 3 years, 95% of enrollees were engaged in care, meeting the American Academy of Pediatrics' recommended periodicity schedule for preventive health visits. On-time receipt of childhood vaccines ranged from 95% (pneumococcal conjugate) to 100% (human papilloma virus). The program's high engagement in care shows promise in engaging vulnerable families over time. Future work should explore how to engage children from more diverse backgrounds, and should examine whether the model impacts other indicators of health and well-being for children impacted by parental substance use.

Optimal periodic sensor scheduling for minimizing communication rate under LQG constraint

This paper is concerned with the optimal sensor periodic scheduling for minimizing communication rate under LQG constraint. A novel two-parameter model is proposed to characterize periodic scheduling schemes. Closed-form expressions of the optimal two parameters are derived by linear programming theory. The minimum communication rate is also found based on the optimal two parameters. Simultaneously, optimal periodic scheduling schemes are constructed for the sensor under LQG constraint. Finally, one numerical example shows the efficiency of our design method.

Fuzzy robust flexible programming with [formula omitted] measure for electric sustainable supply chain

Electricity as a source of energy, is one of the most essential part in our life. In recent time, it is noted that the temperature of earth increases in compare to the previous years. It is caused due to burning of the conventional energy sources such as gas, oil, and coal from thermal power plant and other sources, which brings about global warming. Bases on this fact, we propose a multi-objective mixed-integer programming model to design an electric sustainable supply chain network by considering resiliency and responsiveness. In order to formulate the environmental issues, a power-to-gas (P2G) technology is considered as an environment-friendly system. The presence of P2G can reduce the carbon level and it has some major advantages, i.e., it collects carbon dioxide (CO2) from thermal power plant and then converts CO2 to hydrogen (H2) with the help of water (H2O) and methane (CH4) gas. The drawbacks in addressing the uncertainty of the parameters are overcome by proposing a novel fuzzy robust flexible programming approach based on Me measure. Thereafter, a new approach namely, multi-choice conic goal programming with utility function is introduced to solve the proposed multi-objective model. Damodar Valley Corporation (DVC) in India is considered as a case study about electric network that envisages the sustainable issues of an electric supply chain. Finally, experimental results show that one bio-fuel plant, one photovoltaic plant, one air turbine plant, and two mixed-cycle power plants are build at the end of the scheduled period.

Mars: Near-Optimal Throughput with Shallow Buffers in Reconfigurable Datacenter Networks

The performance of large-scale computing systems often critically depends on high-performance communication networks. Dynamically reconfigurable topologies, e.g., based on optical circuit switches, are emerging as an innovative new technology to deal with the explosive growth of datacenter traffic. Specifically, periodic reconfigurable datacenter networks (RDCNs) such as RotorNet (SIGCOMM 2017), Opera (NSDI 2020) and Sirius (SIGCOMM 2020) have been shown to provide high throughput, by emulating a complete graph through fast periodic circuit switch scheduling. However, to achieve such a high throughput, existing reconfigurable network designs pay a high price: in terms of potentially high delays, but also, as we show as a first contribution in this paper, in terms of the high buffer requirements. In particular, we show that under buffer constraints, emulating the high-throughput complete graph is infeasible at scale, and we uncover a spectrum of unvisited and attractive alternative RDCNs, which emulate regular graphs, but with lower node degree than the complete graph. We present Mars, a periodic reconfigurable topology which emulates a d-regular graph with near-optimal throughput. In particular, we systematically analyze how the degree~d can be optimized for throughput given the available buffer and delay tolerance of the datacenter. We further show empirically that Mars achieves higher throughput compared to existing systems when buffer sizes are bounded.

Forward and Line-Based Cycle Bases for Periodic Timetabling

The optimization of periodic timetables is an indispensable planning task in public transport. Although the periodic event scheduling problem (PESP) provides an elegant mathematical formulation of the periodic timetabling problem that led to many insights for primal heuristics, it is notoriously hard to solve to optimality. One reason is that for the standard mixed-integer linear programming formulations, linear programming relaxations are weak, and the integer variables are of pure technical nature and in general do not correlate with the objective value. While the first problem has been addressed by developing several families of cutting planes, we focus on the second aspect. We discuss integral forward cycle bases as a concept to compute improved dual bounds for PESP instances. To this end, we develop the theory of forward cycle bases on general digraphs. Specifically for the application of timetabling, we devise a generic procedure to construct line-based event-activity networks and give a simple recipe for an integral forward cycle basis on such networks. Finally, we analyze the 16 railway instances of the benchmark library PESPlib, match them to the line-based structure, and use forward cycle bases to compute better dual bounds for 14 out of the 16 instances.

Systemic thrombolysis in patients with acute stroke and active cancer: a systematic review and meta-analysis.

Cancer patients frequently have concomitant cerebrovascular diseases, which significantly worsen their prognosis. Prospective studies validating intravenous thrombolysis (IVT) safety profile in patients with acute ischemic stroke and active cancer are still lacking. Therefore, we aimed to evaluate IVT's efficacy and safety profile in acute ischemic stroke patients with comorbid active cancer. We included in a meta-analysis all relevant published studies, including patients with acute ischemic stroke with or without active cancer and receiving IVT, according to recommendations for IVT treatment for acute ischemic stroke. The primary outcomes were: any intracerebral hemorrhage, all-cause mortality, and good functional outcome reported as modified Rankin Scale (mRS) ≤ 2 at the end of the scheduled follow-up period. We included 11 studies in the meta-analysis. IVT was not associated with a significant increase in the incidence of intracerebral hemorrhage (OR 1.35; 95% CI 0.85-2.14; I2 76%), nor with a significant increase in death for any cause (OR 1.26; 95% CI 0.91-1.75; I2 71%); furthermore, IVT did not influence mRS between cancer and non-active cancer stroke patients (OR 0.72; 95% CI 0.35-1.49; I2 59%). IVT seems safe and effective in patients with ischemic stroke and concomitant cancer. Due to the low overall quality of the evidence, high-quality randomized controlled trials with adequate sample sizes are needed.

Надійність і безпека стартових комплексів ракет-носіїв

This paper is concerned with the reliability and safety of launch complexes. The problems to be solved in launch complex reliability evaluation are identified: calculations of the probability of no-failure operation of passive redundancy systems with equal- and nonequal-reliability elements, reliability analysis for replacement redundancy with integer multiplicity and unloaded reserve; calculations of the probability of no-failure operation of the launch complex components in launch preparation, and calculations of the reliability indices of a component part as a whole and a comparison of the calculated reliability indices with the specification requirements. Since a launch complex consists both of renewable elements and of nonrenewable ones, the reliability indices must be calculated so that one may evaluate the reliability both of individual elements and of a system of different-type elements as a whole. These indices are characterized by the nonfailure operation time and recovery time distributions and show the probability of а serviceable state or a failure state of an element and a system. On condition that the nonfailure operation time and the recovery time can be described by the Weibull distribution, expressions are obtained for the availability factor, i.e., the probability of the launch complex being operative at an arbitrary time, except for scheduled periods during which the launch complex is not envisaged for use. Launch complex safety is evaluated by the probability of hazards, the identification of main ways to mitigate their consequences, and account for weight of the consequences of possible hazards in service. Launch complex safety indices are identified. It is shown that safety must be evaluated using indices suitable for the practical solution of problems of the justification and assurance of specified safety requirements against possible threats in the development of launch complexes. The adopted safety index is the probability that each hazard that occurs in a certain time will be eliminated. A renewal process is used to describe a random number of hazard occurrences. To determine the hazard frequency, it is recommended to use statistical data on launch complex accident rate and reliability, logical methods of event tree and fault tree analysis, accident simulation models, and expert judgments.

A zone-based optical intra-vehicle backbone network architecture with dynamic slot scheduling

As Ethernet has a large bandwidth capacity, it is commonly proposed as a backbone for future intra-vehicle networks. However, satisfying the severe hardware reliability requirements of intra-vehicle networks while providing high-bandwidth and low latency by Ethernet may be costly. As a solution, we propose a novel optical intra-vehicle backbone network architecture that may have a lower cost and higher reliability in terms of hardware when compared to Ethernet. However, unlike traditional optical Ethernet architectures, only a single master node has transmitter laser diodes in the backbone of our architecture, so the gateway nodes cannot generate and send packets to the backbone links directly. As the gateways cannot inform the master node and request a slot when they have a new packet to send, a slot scheduling algorithm with polling is necessary to detect and transfer the new packets in the gateways, which may cause higher transmission delays compared to Ethernet. In this paper, we present our optical intra-vehicle backbone network architecture and propose two slot scheduling algorithms. We show that using a dynamic slot scheduling algorithm decreases packet delays when compared to fixed periodic slot scheduling in our architecture. We also evaluate the total delays including traffic shaping and processing delays in an optical TSN Ethernet backbone architecture as a reference. We show that the extra delays due to slot scheduling in our architecture may be negligibly low when compared with traffic shaping and processing delays.