Uncertain Duration Research Articles

Redesigning Fellowship Curriculum Amidst The Covid-19 Pandemic: Our Shared Experiences

The COVID-19 pandemic has created innumerable challenges for medical professionals, including the need to balance clinical obligations with the continued need to provide a valuable and well-rounded educational experience for our medical trainees. Indeed, trainees at all levels have expressed concerns regarding the impact of COVID-19 on their education (1,2). Given the uncertain duration of this pandemic, it is important to begin sharing best practices to optimize trainees’ educational experiences during this time.

O acesso de pessoas com doenças crônicas não transmissíveis à Rede de Atenção à Saúde em pequenos municípios

As doenças crônicas apresentam início gradual, com duração longa ou incerta e geralmente têm múltiplas causas, contemplando uma categoria vasta de agravos e exigindo reorganizações do sistema de saúde. A rede de atenção à saúde das pessoas com doenças crônicas busca promover a atenção integral e ampliação das ações de promoção à saúde e de prevenção do aparecimento de complicações. Este estudo objetivou analisar o acesso das pessoas com doenças crônicas não transmissíveis aos serviços de saúde, comparando a oferta de atendimentos e procedimentos em dois pequenos municípios da Região de Saúde 29, do Rio Grande do Sul (RS), com os parâmetros estabelecidos pela Portaria 1.631/2015. Trata-se de um estudo transversal e exploratório, com base em documentos das Secretarias Municipais de Saúde e entrevistas com gestores e informantes-chave de dois municípios do RS. Verificou-se que não há dificuldade de acesso aos serviços de saúde na atenção básica; porém, a oferta de assistência na média e alta complexidade é insuficiente, dificultando o acesso do usuário e induzindo sua participação financeira no custeio do diagnóstico e tratamento. Concluiu-se que é necessário ampliar a oferta de atendimentos de média e alta complexidade, no que se refere às doenças crônicas, cabendo aos três entes federativos estabelecer mecanismos de garantia de acesso a estes serviços, bem como uma regulação qualificada.

Reorganization of the endoscopic activity of Cancer Institutes during phase II of the Covid-19 emergency

After the lockdown during the emergency phase of the Covid-19 pandemic, we have to deal with phase 2, a period of uncertain duration, with a controlled and progressive return to normalization, in which we need to reconcile our work and our movements with the presence of the virus on our territory. Digestive endoscopic activity is a high-risk transmission procedure for Covid-19. The measures put in place to protect healthcare personnel and patients are stressful and “time-consuming” and lead to a reduction in the number of endoscopic procedures that can be performed. In this scenario, the Oncological Institutes are forced to make a rigorous selection of patients to undergo endoscopic examinations and treatments, according to lists of exceptional priorities, in order to guarantee cancer patients and subjects at high risk of developing digestive tumors, a preferential diagnostic and therapeutic process, protected from contagion risks. For this purpose, cuts and postponing times of endoscopic performances are here proposed, which go beyond the guidelines of scientific societies and have little evidences in the literature. These changes should be applied limited to this exceptional period and in proportion to the capacity of each operating unit in order to meet the demands of the patients.

Integrating reliability and resilience to support the transition from passive distribution grids to islanding microgrids

Reliability and resilience are the main drivers for the transition of distribution networks from passive systems to active microgrids; as such, quantifying the potential benefits of microgrids in the design phase can support the transition of passive distribution networks into microgrids. To support this transition, this paper presents a mathematical optimization model which integrates techno-economic, resilience and reliability objectives. Storage and distributed generation are optionally installed to complement renewable generation, enabling the microgrid to supply priority demands during stochastic islanding events with uncertain duration. Islanding due to external events is combined with a detailed model of internal faults for comprehensive quantification and optimization of microgrid resilience and reliability. Minimizing the interruption costs yields optimal capacities and placements of distributed energy resources and new lines for reconfiguration. The proposed method produces microgrid designs with up to 95% reliability and resilience gain and moderate cost increase in two benchmark distribution networks using data from the United States Department of Energy. The developed methodology is scalable to large networks owing to the tailored Column-and-Constraint-Generation approach, reducing the computational time by 92% compared to state-of-the-art Benders decomposition for a 123 bus network.

A Two-Stage Service Migration Algorithm in Parked Vehicle Edge Computing for Internet of Things.

Parked vehicle edge computing (PVEC) utilizes both idle resources in parked vehicles (PVs) and roadside units (RSUs) as service providers (SPs) to improve the performance of vehicular internet of things (IoT). However, it is difficult to make optimal service migration decisions in PVEC networks due to the uncertain parking duration and resources heterogeneity of PVs. In this paper, we formulate the service migration of all the vehicles as an optimization problem with the objective of minimizing the average latency. We propose a two-stage service migration algorithm for PVEC networks, which divides the original problem into the service migration between SPs and the serving PV selection in parking lots. The service migration between SPs is transformed to an online problem based on Lyapunov optimization, where the expected parking duration of PVs is utilized. A modified Hungarian algorithm is proposed to select the PVs for migration. A series of simulation experiments based on the real-world vehicle traces are conducted to verify the superior performance of the proposed two-stage service migration (SEA) algorithm as compared with the state-of- art solutions.

Immigration Detention and Habeas Corpus: Positive Developments and Missed Opportunities in Chhina

In Canada (Public Safety and Emergency Preparedness) v Chhina (“Chhina”), a majority of the Supreme Court of Canada found that immigration detainees in detention of lengthy and uncertain duration may access habeas corpus relief at provincial superior courts. The majority held that the detention review scheme under the governing statute did not accord as broad and advantageous protection as that provided by habeas corpus. The author argues that Chhina is a positive development with missed opportunities. The Supreme Court laudably clarified the case law and narrowed the exception that previously barred immigration detainees from seeking any form of habeas corpus relief. Further, in finding that the governing detention review scheme is not as broad and advantageous as habeas corpus, the majority adopted a pragmatic approach and focused on how detention reviews are conducted, not on how they ought to be performed. Notwithstanding these strengths, the majority missed an opportunity to resolve the conflicting case law on three common issues that arise when detainees in lengthy immigration detention file habeas corpus petitions: (i) determining when a detention becomes unduly lengthy such that it is unlawful; (ii) developing a singular approach to calculating the duration of detention; and (iii) establishing the proper weight that should be ascribed to detainee cooperation in habeas corpus applications. Moreover, in omitting substantive discussions of the broader context surrounding immigration detention, the majority missed a valuable opportunity to fully shine the light on the shortcomings of immigration detention and in the process potentially usher in systemic changes.

Immigration Detention and Habeas Corpus

In Canada (Public Safety and Emergency Preparedness) v Chhina (“Chhina”), a majority of the Supreme Court of Canada found that immigration detainees in detention of lengthy and uncertain duration may access habeas corpus relief at provincial superior courts. The majority held that the detention review scheme under the governing statute did not accord as broad and advantageous protection as that provided by habeas corpus. The author argues that Chhina is a positive development with missed opportunities. The Supreme Court laudably clarified the case law and narrowed the exception that previously barred immigration detainees from seeking any form of habeas corpus relief. Further, in finding that the governing detention review scheme is not as broad and advantageous as habeas corpus, the majority adopted a pragmatic approach and focused on how detention reviews are conducted, not on how they ought to be performed. Notwithstanding these strengths, the majority missed an opportunity to resolve the conflicting case law on three common issues that arise when detainees in lengthy immigration detention file habeas corpus petitions: (i) determining when a detention becomes unduly lengthy such that it is unlawful; (ii) developing a singular approach to calculating the duration of detention; and (iii) establishing the proper weight that should be ascribed to detainee cooperation in habeas corpus applications. Moreover, in omitting substantive discussions of the broader context surrounding immigration detention, the majority missed a valuable opportunity to fully shine the light on the shortcomings of immigration detention and in the process potentially usher in systemic changes.

A Multi-PR Heuristic for Distributed Multi-Project Scheduling With Uncertain Duration

Multiple projects are often managed and run in a decentralized setting. In this paper, considering the uncertainty in project implementation, we study the distributed multi-project scheduling problem with uncertain duration. A multi-PR heuristic (MPR-H) is then proposed to dynamically coordinate the global resource conflicts while minimizing the expected total tardiness cost. Three priority rules based on current known information are also proposed and incorporated in our approach. We further consider the opportunistic behaviour of self-interested agents and design a payment negotiation process which is added to the MPR-H. In this paper, we then evaluate the performance of the MPR-H on the benchmark dataset MPSPLIB. The computational results confirm that MPR-H achieves significant improvements in comparison with several state-of-the-art distributed/centralized algorithms. The proposed algorithm also provides the senior manager with an efficient method to allocate global resources for large-size and strong conflicting instances under various activity duration distributions. Besides, we show that multi-projects with relative slack global resource constraints are more affected by the change of uncertainty. By analyzing the strategic behaviour of the agents in problems with two projects, we also show that in our MPR-H with payment negotiation approach, rational agents have to behave truthfully that is the dominant-strategy equilibrium leading to high-quality results.

Динамика информационных поисковых запросов о COVID-19 на этапе самоизоляции

Objective. Studying the dynamics of information search queries in the situation of experiencing an objective global threat-the spread of COVID-19. Background. The pandemic situation is specific because of its universality, uncertain duration and weak predictability of disease manifestations, which suggests the cumulative nature of this stressor. The uniqueness of its socio-psychological consequences is determined by the experience of self-isolation in a virtual space. The dynamics of search queries in large random samples may reflect both the reaction of the population to the statements of power subjects, and the presence of certain mechanisms of emotional self-regulation. Study design. We analyzed search queries thematically related to the spread of COVID-19 and the introduction of self-isolation mode: 5 million search queries were randomly selected from the database, 1 million for each of the analyzed time intervals. Participants. The study was conducted on users of the Yandex search engine. Methods. Quantitative methods of the Data Mining class were used for data collection. Qualitative methods of the Data Mining class and contextual analysis were used for data analysis. Microsoft Excel tools were used for statistical code processing. Results. The number of information requests on the topic of the pandemic increased sharply after V. Putin’s first address, and then steadily decreased, but the overall picture of the content dynamics of search queries, depending on official statements of the authorities, was not observed; requests about the current level of morbidity are constantly presented to the greatest extent, and to the minimum-about the possibilities of psychological assistance and the state of the Russian economy. During the whole time of the study the contents of the Internet search shifted towards positive emotional information. Conclusions. To the maximum extent, the relationship between the experience of a pandemic and self-isolation with the nature of search queries manifests itself at the initial stages and tends to decrease in the future. The dynamics of the content of requests is ambiguously related to official statements of power subjects, influenced by the effect of counter-regulation.

Resilience-Driven Modeling, Operation and Assessment for a Hybrid AC/DC Microgrid

High-impact and low-probability extreme events can cause severe damage to power systems, especially for distribution systems. Microgrids (MGs) with distributed generation resources provide a viable solution for local load survivability via islanding schemes during extreme events. Recently, much research has focused on resilience-driven modeling and operations of MGs. In this paper, a resilience-driven operational model incorporating two operational modes (grid-connected and islanded) and detailed technical characteristics, such as voltage-related operational constraints, is developed for the resilience enhancement of a hybrid AC/DC MG. A detailed AC optimal power flow (OPF) algorithm is employed to model operational constraints and the power exchange between AC and DC subgrids. Preventive power importing is utilized for better preparedness before extreme events and demand response is employed to reduce load shedding during emergency mode. Existing literature on resilience assessment is reviewed and a modified multi-phase curve is proposed to fully represent the influence of limited generation resources and uncertain event duration on resilience. Extensive case studies capturing the distinction of critical loads and non-critical loads and two types of contingencies (multiple line faults and interrupted connection between AC subgrid and DC subgrid) are conducted to demonstrate the effectiveness of the proposed resilience strategy on protecting critical loads and reducing total load shedding. Particularly, a sensitivity analysis considering different event occurrence time has been simulated to capture, in a simple but rather effective way, the effect of the uncertainty surrounding event occurrence.

A two-step stochastic approach for operating rooms scheduling in multi-resource environment

Planning and scheduling of operating rooms (ORs) is important for hospitals to improve efficiency and achieve high quality of service. Due to significant uncertainty in surgery durations, scheduling of ORs can be very challenging. In this paper, surgical case scheduling problem with uncertain duration of surgeries in multi resource environment is investigated. We present a two-stage stochastic mixed-integer programming model, named SOS, with the objective of total ORs idle time and overtime. Also, in this paper a two-step approach is proposed for solving the model based on the L-shaped algorithm. Proposing the model in a multi resources environment with considering real-life limitations in academic hospitals and developing an approach for solving this stochastic model efficiently form the main contributions of this paper. The model is evaluated through several numerical experiments based on real data from Hasheminejad Kidney Center (HKC) in Iran. The solutions of SOS are compared with the deterministic solutions in several real instances. Numerical results show that SOS enjoys a better performance in 97% of the cases. Furthermore, the results of comparing with actual schedules applied in HKC reveal a notable reduction of OR idle time and over time which illustrate the efficiency of the proposed model in practice.

Prevalence of chronic wet cough and protracted bacterial bronchitis in Aboriginal children.

BackgroundChronic wet cough, the most common symptom of a disease spectrum that encompasses protracted bacterial bronchitis (PBB) and bronchiectasis, is common among Aboriginal children. In the absence of any community prevalence data, and with the high burden of respiratory disease and the European Respiratory Society task force's recommendation to identify disease burden, we determined the prevalence of chronic wet cough and PBB in young Aboriginal children in four remote communities in north Western Australia.MethodsA whole-population, prospective study was conducted. Aboriginal children aged ≤7 years were clinically assessed for chronic wet cough by paediatric respiratory clinicians between July 2018 and May 2019. Where children had a wet cough but parents reported a short or uncertain cough duration, children were followed up 1 month later. A medical record audit 6 weeks to 3 months later was used to determine those children with chronic wet cough who had PBB (based on response to antibiotics).ResultsOf the 203 children, 191 (94%; median age 3.5 years, range 0–7 years) were enrolled. At the initial visit, chronic wet cough was present in 21 (11%), absent in 143 (75%) and unknown in 27 (14%). By follow-up, the total prevalence of chronic wet cough was 13% (95% CI 8–19%) and 10% (95% CI 7–17%) for PBB. Chronic wet cough was more common in the two communities with unsealed roads (19%) compared to the two with sealed roads (7%).ConclusionGiven the relatively high prevalence, strategies to address reasons for and treatment of chronic wet cough and PBB in young Aboriginal children in remote north Western Australia are required.

Crowdfunding via Revenue-Sharing Contracts

Problem definition: We analyze a new model of crowdfunding recently introduced by Bolstr, Localstake, and Startwise. A platform acts as a matchmaker between a firm needing funds and a crowd of investors willing to provide capital. After the firm is funded, it pays back the investors using revenue-sharing contracts, with a prespecified investment multiple (investors will receive [Formula: see text] dollars for every dollar invested) and a revenue-sharing proportion, over an investment horizon of uncertain duration. Academic/practical relevance: We analyze the revenue-sharing contract approach to crowdfunding, and we assist the firm to determine its optimal contract parameters to maximize its expected net present value (NPV) subject to investor participation constraints and platform fees. Methodology: A natural multiperiod formulation for the firm’s problem results in an intractable stochastic optimization model, which we approximate using a deterministic model. In the approximation model, we use a cash buffer for dealing with cash flow uncertainties; we are able to solve the approximation model analytically. Results: Parametrized on real data from Bolstr campaigns, our approximation solutions give an NPV in the stochastic problem that is within 0.2% of the simulation-based optimal NPV for all levels of cash flow uncertainty. We compare revenue-sharing contracts with equity crowdfunding and observe that the former result in higher NPVs and comparable bankruptcy probabilities. We also compare revenue-sharing contracts with fixed rate loans and find that, for most cases considered, revenue-sharing contracts provide a higher NPV and a lower probability of bankruptcy than a fixed rate loan. We also show that these benefits are more significant for firms with higher levels of cash flow uncertainty. Managerial implications: Revenue-sharing contracts are a novel approach to crowdfunding, and we show that are superior to other financing models.

A multi-objective optimization approach to project scheduling with resiliency criteria under uncertain activity duration

Uncertainty is one of the main parts of the project management environment that can strongly affect the project objectives and cause unpredictable delays. This study presents a multi-objective optimization approach for constructing resilient project schedules under resource constraints to cope with uncertain activity durations. In this paper, the concept of resilient project scheduling is defined to measure the ability of schedules to deal with duration disruption. Since the direct evaluation of resiliency is computationally complicated and time-consuming, a new surrogate resilience measure is introduced. The proposed resiliency criteria measure the floating of activities and the risks associated with the completion of the project. Furthermore, a new model based on a combination of time buffer and float allocation approach is developed. To extend existing project scheduling models with uncertainty, general precedence relationships between activities have been considered. To validate the proposed approach, the construction project of a combined cycle power plant is used as a case study. Due to a large number of project activities in this case study, the non-dominated sorting genetic algorithm (NSGA II) has been used to solve the problem. The results of solving the mathematical model using the proposed method are assessed through extensive simulation experiments and compared with those of the baseline schedule. The results show that by taking the proposed resiliency measure and the optimal allocation of buffer time to activities, the project completed at the same duration with higher reliability.

Jump and Volatility Risk Premia:‎ Empirical Estimations Following Tail Events

We estimate post-jump volatility-decay risk premia as the predictable ‎difference between periods of high and low diffusive volatility. By ‎constructing straddle portfolios after positive and negative jumps occur, we ‎show that the gains that these hedged options' portfolios yield compensate ‎investors for the uncertain magnitude and duration of volatility decay, as well ‎as for vega exposure. This paper adds to the literature by distinguishing ‎between the premia after positive versus negative jumps, and by exploring ‎premia patterns over time. In particular, we find that GARCH(1,1) is an ‎inefficient identifier of jumps, and show that Hampel [1971] is a superior ‎procedure. ‎

Resource Allocation and Task Offloading for Heterogeneous Real-Time Tasks With Uncertain Duration Time in a Fog Queueing System

Fog computing has become the primary infrastructure on the Internet for improving the quality of service. We consider a fog queueing system with limited infrastructure resources to accommodate real-time tasks with heterogeneities in task types and execution deadlines. Owing to the uncertain execution duration, such a fog system should jointly consider fog resource allocation and a task offloading to satisfy the deadline requirements. To consider the task heterogeneity, a parallel virtual queue model is applied to buffer each type of task in a separate queue. Subsequently, we use a framework, including three parallel algorithms, namely, offloading, buffering, and resource allocation, to improve resource allocation balance, throughput, and task completion ratio. The task offloading is decided according to the task urgencies in terms of the laxity times, which accounts for the deadline, estimated execution time, and transmission delay to the cloud. The buffering process rearranges the arriving tasks based on their laxity time and the estimated task execution time at the fog tier. The resource allocation uses an adaptive queue weight based on the Lyapunov drift to avoid task starvation that may lead to a long queueing delay for tasks with long execution time. The simulation results indicate that our proposed policies can avoid task starvation and yields a tradeoff between high throughput and a high task completion ratio.

Payoff Distribution in a Multi-Company Extraction Game with Uncertain Duration

A nonrenewable resource extraction game model is analyzed in a differential game theory framework with random duration. If the cumulative distribution function (c.d.f.) of the final time is discontinuous, the related subgames are differentiated based on the position of the initial instant with respect to the jump. We investigate properties of optimal trajectories and of imputation distribution procedures if the game is played cooperatively.

Optimization of Project Schedules in the Critical-Chain Project-Management Max-Plus-Linear Framework

Focusing on projects with uncertain task duration times, we aim to minimize the makespan of a project under the framework of the critical-chain project management approach. In existing frameworks, no attention has been paid to optimality under the “good enough” goal. However, in situations where there are only limited available resources, it is clear that the processing sequence of tasks greatly affects the makespan of the project. Hence, we structure an optimization problem to obtain an exact optimal solution. A discrete algebraic system called max-plus algebra plays is key to calculate the objective-function value. We adhere to seek an exact solution, for which a branch-and-bound technique is relied upon. Through numerical experiments, we find that the computation time highly depends on the structure of precedence constraints and assignment of resources. The developed solver is able to obtain an optimal solution within practical time standards if the number of tasks is not greater than 20.

Coordinating overseas and local sourcing through a capacitated expediting transportation policy

We consider an assembly system that adopts both overseas sourcing and local sourcing for different components. Local sourcing has a short and deterministic lead-time. Overseas sourcing can be divided into two stages and each stage has uncertain transportation duration. A capacitated expediting service could be adopted after first-stage transportation. In this study, we derive an optimal expediting policy for overseas sourcing and an optimal responsive sourcing policy for local sourcing. In addition, we discuss the impacts of lead-time volatility and the decision of safety lead-time, which are relevant in implementing the expediting service.

Determination of Input Parameters of the Neural Network Model, Intended for Phoneme Recognition of a Voice Signal in the Systems of Distance Learning

The article is devoted to the problem of voice signals recognition means introduction in the system of distance learning. The results of the conducted research determine the prospects of neural network means of phoneme recognition. It is also shown that the main diculties of creation of the neural network model, intended for recognition of phonemes in the system of distance learning, are connected with the uncertain duration of a phoneme-like element. Due to this reason for recognition of phonemes, it is impossible to use the most eective type of neural network model on the basis of a multilayered perceptron, at which the number of input parameters is a xed value. To mitigate this shortcoming, the procedure, allowing to transform the non-stationary digitized voice signal to the xed quantity of mel-cepstral coecients, which are the basis for calculation of input parameters of the neural network model, is developed. In contrast to the known ones, the possibility of linear scaling of phoneme- like elements is available in the procedure. The number of computer experiments conrmed expediency of the fact that the use of the oered coding procedure of input parameters provides the acceptable accuracy of neural network recognition of phonemes under near-natural conditions of the distance learning system. Moreover, the prospects of further research in the eld of development of neural network means of phoneme recognition of a voice signal in the system of distance learning is connected with an increase in admissible noise level. Besides, the adaptation of the oered procedure to various natural languages, as well as to other applied tasks, for instance, a problem of biometric authentication in the banking sector, is also of great interest.