Terminal Conditions Research Articles

Branch-and-price for routing with probabilistic customers

We study the Vehicle Routing Problem with Probabilistic Customers (VRP-PC), a two-stage optimization model, which is a fundamental building block within the broad family of stochastic routing problems. This problem is mainly motivated by logistics distribution networks in which customers receive frequent delivery services, and by the last mile problem faced by companies such as UPS and FedEx. In a first stage before customer service requests realize, a dispatcher determines a set of vehicle routes serving all potential customer locations. In a second stage occurring after observing all customer requests, vehicles execute planned routes skipping all locations of customers not requiring service. The objective is to minimize the expected vehicle travel cost assuming known customer realization probabilities. We propose a column generation framework to solve the VRP-PC to a given optimality tolerance. Specifically, we present two novel algorithms, one that under-approximates a solution’s expected cost, and another that uses its exact expected cost. Each algorithm is equipped with a route pricing mechanism that iteratively improves the approximation precision of a route’s reduced cost; this produces fast route insertions at the start of the algorithm and reaches termination conditions at the end of the execution. Compared to branch-and-cut algorithms for arc-based formulations, our framework can more readily incorporate sequence-dependent constraints, which are typically required in routing problems. We provide a priori and a posteriori performance guarantees for these algorithms, and demonstrate their effectiveness via a computational study on instances with realization probabilities ranging from 0.5 to 0.9.

Sen1 and Rrm3 ensure permissive topological conditions for replication termination

Replication forks terminate at TERs and telomeres. Forks that converge or encounter transcription generate topological stress. Combining genetics, genomics, and transmission electron microscopy, we find that Rrm3hPif1 and Sen1hSenataxin helicases assist termination at TERs; Sen1 specifically acts at telomeres. rrm3 and sen1 genetically interact and fail to terminate replication, exhibiting fragility at termination zones (TERs) and telomeres. sen1rrm3 accumulates RNA-DNA hybrids and X-shaped gapped or reversed converging forks at TERs; sen1, but not rrm3, builds up RNA polymerase II (RNPII) at TERs and telomeres. Rrm3 and Sen1 restrain Top1 and Top2 activities, preventing toxic accumulation of positive supercoil at TERs and telomeres. We suggest that Rrm3 and Sen1 coordinate the activities of Top1 and Top2 when forks encounter transcription head on or codirectionally, respectively, thus preventing the slowing down of DNA and RNA polymerases. Hence Rrm3 and Sen1 are indispensable to generate permissive topological conditions for replication termination.

Robust backward linear-quadratic differential game and team: A soft-constraint analysis

The robust design with model uncertainty is an extensively investigated research issue but traditionally focuses on forward stochastic system for which the initial condition is given as a priori. This paper makes a systematic continuation of this issue but in backward linear-quadratic context. That is, the state dynamics is evolved by a linear backward stochastic differential equation with terminal condition being specified, and cost functionals to be optimized are of quadratic forms. Three types of dynamic backward decisions, are introduced in both game and team setting in presence of drift uncertainty (disturbance). Specifically, in (Stackelberg) game setting, both cases for the follower or leader with unknown disturbance are discussed respectively; whereas in the team setting, the case with disturbance unknown to the leader is highlighted. For each of these three types, corresponding robust backward strategies are designed and associated optimal values for either leader or follower are given.

Five Phases Algorithm: A Novel Meta-heuristic Algorithm and Its Application on Economic Load Dispatch Problem

<p>A new meta-heuristic algorithm named the five phases algorithm (FPA) is presented in this paper. The proposed method is inspired by the five phases theory in traditional Chinese thought. FPA updates agents based on the generating and overcoming strategy as well as learning strategy from the agent with the same label. FPA has a simple structure but excellent performance. It also does not have any predefined control parameters, only two general parameters including population size and terminal condition are required. This provides flexibility to users to solve different optimization problems. For global optimization, 10 test functions from the CEC2019 test suite are used to evaluate the performance of FPA. The experimental results confirm that FPA is better than the 6 state-of-the-art algorithms including particle swarm optimization (PSO), grey wolf optimizer (GWO), multi-verse optimizer (MVO), differential evolution (DE), backtracking search algorithm (BSA), and slime mould algorithm (SMA). Furthermore, FPA is applied to solve the Economic Load Dispatch (ELD) from the real power system problem. The experiments give that the minimum cost of power system operation obtained by the proposed FPA is more competitive than the 14 counterparts. The source codes of this algorithm can be found in https://ww2.mathworks.cn/matlabcentral/fileexchange/118215-five-phases-algorithm-fpa.</p> <p> </p>

(Анти)санкционные оговорки в международных коммерческих контрактах

The article provides analysis of sanctions clauses in international commercial contracts. Such clauses are intended to regulate actions of the parties in the event of sanctions and corresponding legal consequences. In comparison to classic force majeure clauses sanctions clauses have a number of advantages and may serve several interrelated purposes, including securing compliance by the parties with mandatory rules that impose restrictions on certain economic activity, adaptation of the contract to new circumstances in the event of economic sanctions, regulation of termination of the contract, as well as the distribution of risks and costs incurred by the parties in connection with this. The authors explore the structure of sanctions clauses and their provisions, which cause difficulties in practice, diverse approaches to determining the scope of sanctions clauses in the context of extraterritorial sanctions and blocking statutes, different threshold for sanctions risks that activate the clause, spectrum of options to secure adaptation of contract provisions depending on the specifics of the sanctions regimes, standards of due care and endeavours that are expected from parties in the context of sanctions, conditions for termination of contracts and possibilities for the distribution of costs incurred, including the payment of indemnity. The article also discusses validity of sanctions clauses, their relationship with overriding mandatory rules and norms preventing circumvention of the law, considers the risks of asymmetric and disparity provisions. Particular emphasis is placed on the relationship of sanctions clauses with other sections of international contracts, in particular applicable law and dispute resolution clauses.

Doubly reflected BSDEs with stochastic quadratic growth: Around the predictable obstacles

We prove the existence of maximal (and minimal) solution for one-dimensional generalized doubly reflected backward stochastic differential equation (RBSDE for short) with irregular barriers and stochastic quadratic growth, for which the solution Y has to remain between two rcll barriers L and U on [0,T[, and its left limit Y− has to stay respectively above and below two predictable barriers l and u on ]0,T]. This is done without assuming any P−integrability conditions and under weaker assumptions on the input data. In particular, we construct a maximal solution for such a RBSDE when the terminal condition ξ is only FT−measurable and the driver f is continuous with general growth with respect to the variable y and stochastic quadratic growth with respect to the variable z.Our result is based on a (generalized) penalization method. This method allows us find an equivalent form to our original RBSDE where its solution has to remain between two new rcll reflecting barriers Y¯ and Y̲ which are, roughly speaking, the limit of the penalizing equations driven by the dominating conditions assumed on the coefficients.A standard and equivalent form to our initial RBSDE as well as a characterization of the solution Y as a generalized Snell envelope of some given predictable process l are also given.

Constructive–destructive heuristics for the Safe Set Problem

The Weighted Safe Set Problem aims to determine in an undirected graph a subset of vertices such that the weights of the connected components they induce exceed the weights of the adjacent components induced by the complementary subset. We tackle the problem with various approaches based on randomised constructive and destructive procedures, comparing them with each other and with the only other existing heuristic approach, that is a randomised destructive heuristic. The experiments concern all the available benchmark instances (random graphs up to 60 vertices), but also new benchmark instances with larger size and different topologies, namely random, small-world, regular, planar, grid and real-world graphs up to 300 vertices. Dense random graphs, in fact, appear to become progressively easier to solve as their size grows. On the other instances, the best performance is obtained by combining a randomised constructive procedure, a deterministic destructive procedure, and delayed termination conditions that allow a deeper exploration of the feasible region.

Kinetic and Kinematic Analysis of Gait Termination: A Comparison between Planned and Unplanned Conditions

Purpose: Gait termination (GT) is the transition from steady-state walking to a complete stop, occurring under planned gait termination (PGT) or unplanned gait termination (UGT) conditions. This study aimed to investigate the biomechanical differences between PGT and UGT, which could help develop therapeutic interventions for individuals experiencing difficulty with GT. Methods: Twenty healthy adults performed three walking trials, followed by PGT and UGT trials. Gait termination was analyzed in three phases as follows: Phase 1 (pre-stopping), Phase 2 (initial stopping phase), and Phase 3 (terminal stopping phase). Spatiotemporal, kinematic, and kinetic data during each phase were compared between conditions. Results: The GT time and GT step length were significantly different between the PGT and UGT trials. Ankle range of motion (ROM) demonstrated significant differences in Phase 1, with the PGT having a slightly lower ankle ROM than the UGT. In Phase 2, the hip, knee, and ankle ROM exhibited significant differences between the conditions. Finally, in Phase 3, UGT showed reduced hip ROM but increased knee ROM and kinetic parameters compared to PGT. Conclusion: Our results indicate that the ankle joint primarily contributes to deceleration during the initial preparation for generating braking force during PGT. Conversely, UGT reveals disrupted kinesthetic control due to instability, leading to a preference for a hip and knee strategy to absorb force and control the center of mass for a safe and rapid GT in response to unexpected stimuli. These findings provide valuable insights into the biomechanical mechanisms underlying body stability during GT and may contribute to the development of effective rehabilitation strategies for individuals with gait impairment.

Coordinate Fault Ride-Through Strategy for Connection of Offshore Wind Farms Using Voltage Source-Converter-Based High-Voltage Direct-Current Transmission under Single Polar Fault.

In a system where wind farms are connected to the grid via a bipolar flexible DC transmission, the occurrence of a short-time fault at one of the poles results in the active power emitted by the wind farm being transmitted through the non-faulty pole. This condition leads to an overcurrent in the DC system, thereby causing the wind turbine to disconnect from the grid. Addressing this issue, this paper presents a novel coordinated fault ride-through strategy for flexible DC transmission systems and wind farms, which eliminates the need for additional communication equipment. The proposed strategy leverages the power characteristics of the doubly fed induction generator (DFIG) under different terminal voltage conditions. By considering the safety constraints of both the wind turbine and the DC system, as well as optimizing the active power output during wind farm faults, the strategy establishes guidelines for the wind farm bus voltage and the crowbar switch signal. Moreover, it harnesses the power regulation capability of the DFIG rotor-side crowbar circuit to enable fault ride-through in the presence of single-pole short-time faults in the DC system. Simulation results demonstrate that the proposed coordinated control strategy effectively mitigates overcurrent in the non-faulty pole of flexible DC transmission during fault conditions.

PREMIUMS CALCULATION OF TERMINAL ILLNESS INSURANCE

One related type of critical illness insurance is Long Term Care (LTC) Insurance. This study discusses the calculation of LTC insurance premiums with an annuity as a rider benefit. The benefit is included the cost of insurance care when diagnosed with a critical illness with a terminal condition or death because of any reason. The types of critical illnesses used in this study are cancer, heart disease, stroke, and diabetes mellitus. The data used are in the form of Indonesia's mortality table, and data on the prevalence of critical illness patients with terminal illness conditions. The net annual premium value in this study was obtained through the results of the multiple-state model determination of the transition probabilities of 10 states. The transition probability of an insured candidate is obtained from the prevalence of critical illness patients and the prevalence of mortality. Based on the case study, the amount of net annual premium that must be paid by an insured female aged years in good health is for the protection period and the payment period is years. The cost of insurance premiums for the male insured is greater than for the female insured. The higher the interest rate used, the smaller the net single premium that must be paid. The younger the age when registering the policy, the smaller the premium that must be paid. The longer the coverage period, the greater the premium that must be paid. This result is expected to be a recommendation for the prospective insured to adjust the suitable premium.

Factorized Doubling Algorithm for Large-Scale High-Ranked Riccati Equations in Fractional System

In real-life control problems, such as power systems, there are large-scale high-ranked discrete-time algebraic Riccati equations (DAREs) from fractional systems that require stabilizing solutions. However, these solutions are no longer numerically low-rank, which creates difficulties in computation and storage. Fortunately, the potential structures of the state matrix in these systems (e.g., being banded-plus-low-rank) could be beneficial for large-scale computation. In this paper, a factorized structure-preserving doubling algorithm (FSDA) is developed under the assumptions that the non-linear and constant terms are positive semidefinite and banded-plus-low-rank. The detailed iteration scheme and a deflation process for FSDA are analyzed. Additionally, a technique of partial truncation and compression is introduced to reduce the dimensions of the low-rank factors. The computation of residual and the termination condition of the structured version are also redesigned. Illustrative numerical examples show that the proposed FSDA outperforms SDA with hierarchical matrices toolbox (SDA_HODLR) on CPU time for large-scale problems.

Resonator Arrays for Linear Position Sensors

A contactless position sensor based on an array of magnetically coupled resonators and an external single coil cell is discussed for both stationary and dynamic applications. The simple structure allows the sensor to be adapted to the system in which it is installed and can be used to detect the positions of objects in motion that bear an external resonator coil that does not necessitate a supply. By exploiting the unique behaviour of the array input impedance, it is possible to identify the position of the external resonator by exciting the first array cell with an external voltage source and measuring the resulting input current. The system is robust and suitable for application in harsh environments. The sensitivity of the measured input impedance to the space variation is adjustable with the definition of the array geometry and is analysed. Different configurations of the array and external resonator are considered, and the effects of various termination conditions and the resulting factor of merit after changing the coil resistance are discussed. The proposed procedure is numerically validated for an array of ten identical magnetically coupled resonators with 15 cm side lengths. Simulations carried out for a distance of up to 20 cm show that, with a quality factor lower than 100 and optimal terminations of both the array and external coil, it is possible to detect the position of the latter.

Competence for physician-assisted death of patients with mental disorders: theoretical and practical considerations

Physician-assisted death (PAD) of patients whose suffering does not stem from terminal conditions has become more prevalent during the last few decades. This paper is focused on decision-making competence for...

Whose Life Is It Anyway? Medical Aid in Dying and Its Legal, Medical, and Ethical Conundrums

Whose Life Is It Anyway? Medical Aid in Dying and Its Legal, Medical, and Ethical Conundrums

A Probability-Based Zero-Block Early Termination Algorithm for QSHVC

To seamlessly adapt to time-varying network bandwidths, the Quality Scalable High-Efficiency Video Coding (QSHVC) is developed. However, its coding process is overly complex, and this seriously limits its wide applications in real-time environments. Therefore, it is of great significance to study fast coding algorithms for QSHVC. In this paper, we propose a novel probability-based zero-block early termination algorithm for QSHVC. First, we observed that the generated residual coefficients follow the Laplace distribution if a CU is accurately predicted. According to this observation, we derive the sum of squared differences based All-Zero Block (AZB) decision condition. Second, we develop the Hadamard Transform (HT)-based zero-valued quantized coefficient decision condition to obtain zero-valued quantized coefficients and the corresponding Partial-Zero Block (PZB). Third, the probability of each coding mode and coding depth being chosen as the best ones are combined with both AZBs and PZBs to derive the probability-based early termination condition. The experimental results show that the proposed algorithm can improve the average coding speed by 79.85% with a 0.34% decrease in BDBR.

Numerical Method for Multi-Dimensional Coupled Forward-Backward Stochastic Differential Equations Based on Fractional Fourier Fast Transform

Forward-backward stochastic differential equations (FBSDEs) have received more and more attention in the past two decades. FBSDEs can be applied to many fields, such as economics and finance, engineering control, population dynamics analysis, and so on. In most cases, FBSDEs are nonlinear and high-dimensional and cannot be obtained as analytic solutions. Therefore, it is necessary and important to design their numerical approximation methods. In this paper, a novel numerical method of multi-dimensional coupled FBSDEs is proposed based on a fractional Fourier fast transform (FrFFT) algorithm, which is used to compute the Fourier and inverse Fourier transforms. For the forward component of FBSDEs, time discretization is used as well as the backward equation to yield a recursive system with terminal conditions. For the numerical experiments to be successful, three types of numerical methods were used to solve the problem, which ensured the efficiency and speed of computation. Finally, the numerical methods for different examples are verified.

The Metabolic Profile of Young, Watered Chickpea Plants Can Be Used as a Biomarker to Predict Seed Number under Terminal Drought.

Chickpea is the second-most-cultivated legume globally, with India and Australia being the two largest producers. In both of these locations, the crop is sown on residual summer soil moisture and left to grow on progressively depleting water content, finally maturing under terminal drought conditions. The metabolic profile of plants is commonly, correlatively associated with performance or stress responses, e.g., the accumulation of osmoprotective metabolites during cold stress. In animals and humans, metabolites are also prognostically used to predict the likelihood of an event (usually a disease) before it occurs, e.g., blood cholesterol and heart disease. We sought to discover metabolic biomarkers in chickpea that could be used to predict grain yield traits under terminal drought, from the leaf tissue of young, watered, healthy plants. The metabolic profile (GC-MS and enzyme assays) of field-grown chickpea leaves was analysed over two growing seasons, and then predictive modelling was applied to associate the most strongly correlated metabolites with the final seed number plant-1. Pinitol (negatively), sucrose (negatively) and GABA (positively) were significantly correlated with seed number in both years of study. The feature selection algorithm of the model selected a larger range of metabolites including carbohydrates, sugar alcohols and GABA. The correlation between the predicted seed number and actual seed number was R2 adj = 0.62, demonstrating that the metabolic profile could be used to predict a complex trait with a high degree of accuracy. A previously unknown association between D-pinitol and hundred-kernel weight was also discovered and may provide a single metabolic marker with which to predict large seeded chickpea varieties from new crosses. The use of metabolic biomarkers could be used by breeders to identify superior-performing genotypes before maturity is reached.

Negotiation mechanism of carbon emission quota trading process

Carbon emission quota trading is an effective method for realizing carbon neutrality. Negotiation can help to effectively resolve the differences and conflicts among the trading parties in the carbon emission quota trading process. For researching the negotiation mechanism of carbon emission quota trade, we construct the agent negotiation model that introduces the risk appetite of negotiator and Bayesian algorithm. And then, the negotiation protocol is analyzed, including offer tactics, negotiation unity and termination condition. The experimental studies are given to simulate the negotiation of carbon emission quota trading process for demonstrating the validity of the negotiation model and tactics. This study demonstrates the impact of risk appetite on negotiation in the carbon emission quota trading. And can help to improve negotiation efficiency, achieve win-win and accurate matching among the trading parties of carbon emission quota.

Instantaneous and Averaged Volatility in Two-Side Filtration Model of Financial Asset Pricing

A two-factor approach to asset pricing based on averaged historical and instantaneous volatility defined by a marginal investor’s beliefs and herding behaviour is proposed. For the two-side filtration, backward SDE-defined stochastic dynamics under the risk-neutral probability measure is determined by a target price distribution at given horizon with parameters averaged over a subset of active market agents. For the current price at market equilibrium and instantaneous volatility, the distribution of acceptable price of risk is obtained. The found implied volatility dependencies on strike and maturity are corresponding to the historical data for options by <xref>Carr and Wu (2016)</xref>. The liquidity discount for bonds and options is derived. A generalized solution for the FBSDE and a partial solution for the stochastic terminal conditions are found. The developed two-factor approach is well-suited to deep learning pricing algorithms.

Stochastic Framework for Optimal Control of Planetary Reentry Trajectories Under Multilevel Uncertainties

We present a novel stochastic optimal control framework that accounts for various types of uncertainties, with application to reentry trajectory planning. The formulation of the optimal trajectory control problem is presented in the context of an indirect method where a functional objective associated with the terminal vehicle speed is to be minimized. Uncertain input parameters in the optimal trajectory control model, including aerodynamic parameters and initial and terminal conditions, are modeled as aleatory random variables, while the statistical parameters of these aleatory distributions are themselves random variables. The parametric and model uncertainties are simultaneously propagated through an extended polynomial chaos expansion (EPCE) formalism. Several metrics are described to evaluate response statistics and presented as insightful tools for robust decision making. Specifically, the response probability density function (PDF) reflecting influence of both epistemic and aleatory uncertainties is obtained. By sampling over the random variables representing model error, an ensemble of response PDFs is generated and the associated failure probability is estimated as a random variable with its own polynomial chaos expansion. Besides, the sensitivity index functions of response PDF with respect to the statistical parameters are evaluated. Coupling parametric and model uncertainties within the EPCE framework leads to a robust and efficient paradigm for multilevel uncertainty propagation and PDF characterization in general optimal control problems.