232 research outputs found

    An MPCC Formulation and Its Smooth Solution Algorithm for Continuous Network Design Problem

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    Continuous network design problem (CNDP) is searching for a transportation network configuration to minimize the sum of the total system travel time and the investment cost of link capacity expansions by considering that the travellers follow a traditional Wardrop user equilibrium (UE) to choose their routes. In this paper, the CNDP model can be formulated as mathematical programs with complementarity constraints (MPCC) by describing UE as a non-linear complementarity problem (NCP). To address the difficulty resulting from complementarity constraints in MPCC, they are substituted by the Fischer-Burmeister (FB) function, which can be smoothed by the introduction of the smoothing parameter. Therefore, the MPCC can be transformed into a well-behaved non-linear program (NLP) by replacing the complementarity constraints with a smooth equation. Consequently, the solver such as LINDOGLOBAL in GAMS can be used to solve the smooth approximate NLP to obtain the solution to MPCC for modelling CNDP. The numerical experiments on the example from the literature demonstrate that the proposed algorithm is feasible.</p

    An MPCC Formulation and Its Smooth Solution Algorithm for Continuous Network Design Problem

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    Continuous network design problem (CNDP) is searching for a transportation network configuration to minimize the sum of the total system travel time and the investment cost of link capacity expansions by considering that the travellers follow a traditional Wardrop user equilibrium (UE) to choose their routes. In this paper, the CNDP model can be formulated as mathematical programs with complementarity constraints (MPCC) by describing UE as a non-linear complementarity problem (NCP). To address the difficulty resulting from complementarity constraints in MPCC, they are substituted by the Fischer-Burmeister (FB) function, which can be smoothed by the introduction of the smoothing parameter. Therefore, the MPCC can be transformed into a well-behaved non-linear program (NLP) by replacing the complementarity constraints with a smooth equation. Consequently, the solver such as LINDOGLOBAL in GAMS can be used to solve the smooth approximate NLP to obtain the solution to MPCC for modelling CNDP. The numerical experiments on the example from the literature demonstrate that the proposed algorithm is feasible.</p

    Predicting peritoneal carcinomatosis of gastric cancer: A simple model to exempt low-risk patients from unnecessary staging laparoscopy

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    BackgroundPeritoneal carcinomatosis (PC) of gastric cancer indicates a poor outcome and is mainly diagnosed by staging laparoscopy (SL). This study was designed to develop a risk stratification model based on the number of risk factors to exempt low-risk patients from unnecessary SL.MethodsThis was a retrospective cohort study based on a single institution between January 2015 and December 2019. SL is indicated for patients of advanced locoregional stage, and clinicopathologic characteristics of 535 consecutive patients were included. PC-associated variables were identified by logistic regression analysis. A risk stratification model based on the number of risk factors was constructed, and we defined its predictive value with a receiver operating characteristic (ROC) curve and negative predictive value.ResultsIn total, 15.9% of included patients were found to have PC during SL. Borrmann type IV, elevated CA125, and tumour diameter ≥5 cm were independent risk factors of PC. These three factors combined with cT4 were selected as predictive factors, and the number of predictive variables was significantly related to the possibility of PC (2.0%, 12.8%, 20.0%, 54.2%, and 100%, respectively). When the cutoff value is more than one predictive factor, the negative predictive value is 98.0%, with an area under the curve of 0.780. This model could exempt 29.8% of unnecessary SL compared to the indication of the current NCCN guideline.ConclusionsWe constructed a simple model to predict the probability of PC using the number of predictive factors. It is recommended that patients without any of these factors should be exempt from SL

    Stable trajectory planning and energy-efficience control allocation of lane change maneuver for autonomous electric vehicle

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    Purpose - The purpose of this paper is to investigate problems in performing stable lane changes and to find a solution to reduce energy consumption of autonomous electric vehicles. Design/methodology/approach - An optimization algorithm, model predictive control (MPC) and Karush–Kuhn–Tucker (KKT) conditions are adopted to resolve the problems of obtaining optimal lane time, tracking dynamic reference and energy-efficient allocation. In this paper, the dynamic constraints of vehicles during lane change are first established based on the longitudinal and lateral force coupling characteristics and the nominal reference trajectory. Then, by optimizing the lane change time, the yaw rate and lateral acceleration that connect with the lane change time are limed. Furthermore, to assure the dynamic properties of autonomous vehicles, the real system inputs under the restraints are obtained by using the MPC method. Based on the gained inputs and the efficient map of brushless direct-current in-wheel motors (BLDC IWMs), the nonlinear cost function which combines vehicle dynamic and energy consumption is given and the KKT-based method is adopted. Findings - The effectiveness of the proposed control system is verified by numerical simulations. Consequently, the proposed control system can successfully achieve stable trajectory planning, which means that the yaw rate and longitudinal and lateral acceleration of vehicle are within stability boundaries, which accomplishes accurate tracking control and decreases obvious energy consumption. Originality/value - This paper proposes a solution to simultaneously satisfy stable lane change maneuvering and reduction of energy consumption for autonomous electric vehicles. Different from previous path planning researches in which only the geometric constraints are involved, this paper considers vehicle dynamics, and stability boundaries are established in path planning to ensure the feasibility of the generated reference path

    CENet: A Cabinet Environmental Sensing Network

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    For data center cooling and intelligent substation systems, real time cabinet environmental monitoring is a strong requirement. Monitoring data, such as temperature, humidity, and noise, is important for operators to manage the facilities in cabinets. We here propose a sensing network, called CENet, which is energy efficient and reliable for cabinet environmental monitoring. CENet achieves above 93% reliable data yield and sends fewer beacons compared to periodic beaconing. It does so through a data-aided routing protocol. In addition, based on B-MAC, we propose a scheduling scheme to increase the lifetime of the network by reducing unnecessary message snooping and channel listening, thus it is more energy efficient than B-MAC. The performance of CENet is evaluated by simulations and experiments

    Asymmetric Somatic Hybridization Affects Synonymous Codon Usage Bias in Wheat

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    Asymmetric somatic hybridization is an efficient strategy for crop breeding by introducing exogenous chromatin fragments, which leads to whole genomic shock and local chromosomal shock that induces genome-wide genetic variation including indel (insertion and deletion) and nucleotide substitution. Nucleotide substitution causes synonymous codon usage bias (SCUB), an indicator of genomic mutation and natural selection. However, how asymmetric somatic hybridization affects SCUB has not been addressed. Here, we explored this issue by comparing expressed sequence tags of a common wheat cultivar and its asymmetric somatic hybrid line. Asymmetric somatic hybridization affected SCUB and promoted the bias to A- and T-ending synonymous codon (SCs). SCUB frequencies in chromosomes introgressed with exogenous fragments were comparable to those in chromosomes without exogenous fragments, showing that exogenous fragments had no local chromosomal effect. Asymmetric somatic hybridization affected SCUB frequencies in indel-flanking sequences more strongly than in non-flanking sequences, and this stronger effect was present in both chromosomes with and without exogenous fragments. DNA methylation-driven SCUB shift was more pronounced than other SC pairs. SCUB shift was similar among seven groups of allelic chromosomes as well as three sub-genomes. Our work demonstrates that the SCUB shift induced by asymmetric somatic hybridization is attributed to the whole genomic shock, and DNA methylation is a putative force of SCUB shift during asymmetric somatic hybridization. Asymmetric somatic hybridization provides an available method for deepening the nature of SCUB shift and genetic variation induced by genomic shock
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