Column generation for a multitrip vehicle routing problem with time windows, driver work hours, and heterogeneous fleet

This study addresses a vehicle routing problem with time windows, accessibility restrictions on customers, and a fleet that is heterogeneous with regard to capacity and average speed. A vehicle can performmultiple routes per day, all starting and ending at a single depot, and it is assigned to a single driverwhose totalwork hours are limited.Acolumn generation algorithmis proposed.The column generation pricing subproblem requires a specific elementary shortest path problem with resource constraints algorithm to address the possibility for each vehicle performingmultiple routes per day and to address the need to set the workday’s start time within the planning horizon. A constructive heuristic and a metaheuristic based on tabu search are also developed to find good solutions.

Optimal Code Set Selection and Security Issues in Spectral Phase-Encoded Time Spreading (SPECTS) OCDMA Systems

In this paper, we perform a thorough analysis of a spectral phase-encoded time spreading optical code division multiple access (SPECTS-OCDMA) system based on Walsh-Hadamard (W-H) codes aiming not only at finding optimal code-set selections but also at assessing its loss of security due to crosstalk. We prove that an inadequate choice of codes can make the crosstalk between active users to become large enough so as to cause the data from the user of interest to be detected by other user. The proposed algorithm for code optimization targets code sets that produce minimum bit error rate (BER) among all codes for a specific number of simultaneous users. This methodology allows us to find optimal code sets for any OCDMA system, regardless the code family used and the number of active users. This procedure is crucial for circumventing the unexpected lack of security due to crosstalk. We also show that a SPECTS-OCDMA system based on W-H 32(64) fundamentally limits the number of simultaneous users to 4(8) with no security violation due to crosstalk. More importantly, we prove that only a small fraction of the available code sets is actually immune to crosstalk with acceptable BER (<10(-9)) i.e., approximately 0.5% for W-H 32 with four simultaneous users, and about 1 x 10(-4)% for W-H 64 with eight simultaneous users.

Optimal mean-variance control for discrete-time linear systems with Markovian jumps and multiplicative noises

In this paper, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noises under two criteria. The first one is an unconstrained mean-variance trade-off performance criterion along the time, and the second one is a minimum variance criterion along the time with constraints on the expected output. We present explicit conditions for the existence of an optimal control strategy for the problems, generalizing previous results in the literature. We conclude the paper by presenting a numerical example of a multi-period portfolio selection problem with regime switching in which it is desired to minimize the sum of the variances of the portfolio along the time under the restriction of keeping the expected value of the portfolio greater than some minimum values specified by the investor. (C) 2011 Elsevier Ltd. All rights reserved.

Integrated pulp and paper mill planning and scheduling

This article describes a real-world production planning and scheduling problem occurring at an integrated pulp and paper mill (P&P) which manufactures paper for cardboard out of produced pulp. During the cooking of wood chips in the digester, two by-products are produced: the pulp itself (virgin fibers) and the waste stream known as black liquor. The former is then mixed with recycled fibers and processed in a paper machine. Here, due to significant sequence-dependent setups in paper type changeovers, sizing and sequencing of lots have to be made simultaneously in order to efficiently use capacity. The latter is converted into electrical energy using a set of evaporators, recovery boilers and counter-pressure turbines. The planning challenge is then to synchronize the material flow as it moves through the pulp and paper mills, and energy plant, maximizing customer demand (as backlogging is allowed), and minimizing operation costs. Due to the intensive capital feature of P&P, the output of the digester must be maximized. As the production bottleneck is not fixed, to tackle this problem we propose a new model that integrates the critical production units associated to the pulp and paper mills, and energy plant for the first time. Simple stochastic mixed integer programming based local search heuristics are developed to obtain good feasible solutions for the problem. The benefits of integrating the three stages are discussed. The proposed approaches are tested on real-world data. Our work may help P&P companies to increase their competitiveness and reactiveness in dealing with demand pattern oscillations. (C) 2012 Elsevier Ltd. All rights reserved.

Toward the optimal dose metric in continuous renal replacement therapy

Purpose: There is no consensus on the optimal method to measure delivered dialysis dose in patients with acute kidney injury (AKI). The use of direct dialysate-side quantification of dose in preference to the use of formal blood-based urea kinetic modeling and simplified blood urea nitrogen (BUN) methods has been recommended for dose assessment in critically-ill patients with AKI. We evaluate six different blood-side and dialysate-side methods for dose quantification. Methods: We examined data from 52 critically-ill patients with AKI requiring dialysis. All patients were treated with pre-dilution CWHDF and regional citrate anticoagulation. Delivered dose was calculated using blood-side and dialysis-side kinetics. Filter function was assessed during the entire course of therapy by calculating BUN to dialysis fluid urea nitrogen (FUN) ratios q/12 hours. Results: Median daily treatment time was 1,413 min (1,260-1,440). The median observed effluent volume per treatment was 2,355 mL/h (2,060-2,863) (p<0.001). Urea mass removal rate was 13.0 +/- 7.6 mg/min. Both EKR (r(2)=0.250; p<0.001) and K-D (r(2)=0.409; p<0.001) showed a good correlation with actual solute removal. EKR and K-D presented a decline in their values that was related to the decrease in filter function assessed by the FUN/BUN ratio. Conclusions: Effluent rate (ml/kg/h) can only empirically provide an estimated of dose in CRRT. For clinical practice, we recommend that the delivered dose should be measured and expressed as K-D. EKR also constitutes a good method for dose comparisons over time and across modalities.

Optimal Timing for Assessment of Tumor Response to Neoadjuvant Chemoradiation in Patients With Rectal Cancer: Do All Patients Benefit From Waiting Longer Than 6 Weeks?

Purpose: To estimate the metabolic activity of rectal cancers at 6 and 12 weeks after completion of chemoradiation therapy (CRT) by 2-[fluorine-18] fluoro-2-deoxy-D-glucose-labeled positron emission tomography/computed tomography ([18 FDG] PET/CT) imaging and correlate with response to CRT. Methods and Materials: Patients with cT2-4N0-2M0 distal rectal adenocarcinoma treated with long-course neoadjuvant CRT (54 Gy, 5-fluouracil-based) were prospectively studied (ClinicalTrials. org identifier NCT00254683). All patients underwent 3 PET/CT studies (at baseline and 6 and 12 weeks fromCRT completion). Clinical assessment was at 12 weeks. Maximal standard uptakevalue (SUVmax) of the primary tumor wasmeasured and recorded at eachPET/CTstudy after 1 h (early) and3 h (late) from 18 FDGinjection. Patientswith an increase in early SUVmax between 6 and 12 weeks were considered " bad" responders and the others as "good" responders. Results: Ninety-one patients were included; 46 patients (51%) were "bad" responders, whereas 45 (49%) patients were " good" responders. " Bad" responders were less likely to develop complete clinical response (6.5% vs. 37.8%, respectively; PZ. 001), less likely to develop significant histological tumor regression (complete or near-complete pathological response; 16% vs. 45%, respectively; PZ. 008) and exhibited greater final tumor dimension (4.3cmvs. 3.3cm; PZ. 03). Decrease between early (1 h) and late (3 h) SUVmax at 6-week PET/CTwas a significant predictor of " good" response (accuracy of 67%). Conclusions: Patients who developed an increase in SUVmax after 6 weeks were less likely to develop significant tumor downstaging. Early-late SUVmax variation at 6-week PET/CT may help identify these patients and allow tailored selection of CRT-surgery intervals for individual patients. (C) 2012 Elsevier Inc.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Determination of decimal reduction time (D value) of chemical agents used in hospitals for disinfection purposes

Abstract Background Prior to the selection of disinfectants for low, intermediate and high (sterilizing) levels, the decimal reduction time, D-value, for the most common and persistent bacteria identified at a health care facility should be determined. Methods The D-value was determined by inoculating 100 mL of disinfecting solution with 1 mL of a bacterial suspension (104 – 105 CFU/mL for vegetative and spore forms). At regular intervals, 1 mL aliquots of this mixture were transferred to 8 mL of growth media containing a neutralizing agent, and incubated at optimal conditions for the microorganism. Results The highest D-values for various bacteria were determined for the following solutions: (i) 0.1% sodium dichloroisocyanurate (pH 7.0) – E. coli and A. calcoaceticus (D = 5.9 min); (ii) sodium hypochlorite (pH 7.0) at 0.025% for B. stearothermophilus (D = 24 min), E. coli and E. cloacae (D = 7.5 min); at 0.05% for B. stearothermophilus (D = 9.4 min) and E. coli (D = 6.1 min) and 0.1% for B. stearothermophilus (D = 3.5 min) and B. subtilis (D = 3.2 min); (iii) 2.0% glutaraldehyde (pH 7.4) – B. stearothermophilus, B. subtilis (D = 25 min) and E. coli (D = 7.1 min); (iv) 0.5% formaldehyde (pH 6.5) – B. subtilis (D = 11.8 min), B. stearothermophilus (D = 10.9 min) and A. calcoaceticus (D = 5.2 min); (v) 2.0% chlorhexidine (pH 6.2) – B. stearothermophilus (D = 9.1 min), and at 0.4% for E. cloacae (D = 8.3 min); (vi) 1.0% Minncare® (peracetic acid and hydrogen peroxide, pH 2.3) – B. stearothermophilus (D = 9.1 min) and E. coli (D = 6.7 min). Conclusions The suspension studies were an indication of the disinfectant efficacy on a surface. The data in this study reflect the formulations used and may vary from product to product. The expected effectiveness from the studied formulations showed that the tested agents can be recommended for surface disinfection as stated in present guidelines and emphasizes the importance and need to develop routine and novel programs to evaluate product utility.

Influence of psychosocial risk factors on the trajectory of mental health problems from childhood to adolescence: a longitudinal study

Background Longitudinal epidemiological studies involving child/adolescent mental health problems are scarce in developing countries, particularly in regions characterized by adverse living conditions. We examined the influence of psychosocial factors on the trajectory of child/adolescent mental health problems (CAMHP) over time. Methods A population-based sample of 6- to 13-year-olds with CAMHP was followed-up from 2002–2003 (Time 1/T1) to 2007–2008 (Time 2/T2), with 86 out of 124 eligible children/adolescents at T1 being reassessed at T2 (sample loss: 30.6%). Outcome: CAMHP at T2 according to the Child Behavior Checklist/CBCL’s total problem scale. Psychosocial factors: T1 variables (child/adolescent’s age, family socioeconomic status); trajectory of variables from T1 to T2 (child/adolescent exposure to severe physical punishment, mother exposure to severe physical marital violence, maternal anxiety/depression); and T2 variables (maternal education, child/adolescent’s social support and pro-social activities). Results Multivariate analysis identified two risk factors for child/adolescent MHP at T2: aggravation of child/adolescent physical punishment and aggravation of maternal anxiety/depression. Conclusions The current study shows the importance of considering child/adolescent physical punishment and maternal anxiety/depression in intervention models and mental health care policies.

A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.