A Hybrid Genetic Algorithm to Solve a Logt-Sizing and Scheduling Problem

Abstract: This paper reports a lot-sizing and scheduling problem, which minimizes inventory and backlog costs on m parallel machines with sequence-dependent set-up times over t periods. Problem solutions are represented as product subsets ordered and/or unordered for each machine m at each period t. The optimal lot sizes are determined applying a linear program. A genetic algorithm searches either over ordered or over unordered subsets (which are implicitly ordered using a fast ATSP-type heuristic) to identify an overall optimal solution. Initial computational results are presented, comparing the speed and solution quality of the ordered and unordered genetic algorithm approaches.

Modeling height-diameter relationship in pinus pinaster ait. in the forest intervention zone of Lomba, NE-Portugal

In this work, the relationship between diameter at breast height (d) and total height (h) of individual-tree was modeled with the aim to establish provisory height-diameter (h-d) equations for maritime pine (Pinus pinaster Ait.) stands in the Lomba ZIF, Northeast Portugal. Using data collected locally, several local and generalized h-d equations from the literature were tested and adaptations were also considered. Model fitting was conducted by using usual nonlinear least squares (nls) methods. The best local and generalized models selected, were also tested as mixed models applying a first-order conditional expectation (FOCE) approximation procedure and maximum likelihood methods to estimate fixed and random effects. For the calibration of the mixed models and in order to be consistent with the fitting procedure, the FOCE method was also used to test different sampling designs. The results showed that the local h-d equations with two parameters performed better than the analogous models with three parameters. However a unique set of parameter values for the local model can not be used to all maritime pine stands in Lomba ZIF and thus, a generalized model including covariates from the stand, in addition to d, was necessary to obtain an adequate predictive performance. No evident superiority of the generalized mixed model in comparison to the generalized model with nonlinear least squares parameters estimates was observed. On the other hand, in the case of the local model, the predictive performance greatly improved when random effects were included. The results showed that the mixed model based in the local h-d equation selected is a viable alternative for estimating h if variables from the stand are not available. Moreover, it was observed that it is possible to obtain an adequate calibrated response using only 2 to 5 additional h-d measurements in quantile (or random) trees from the distribution of d in the plot (stand). Balancing sampling effort, accuracy and straightforwardness in practical applications, the generalized model from nls fit is recommended. Examples of applications of the selected generalized equation to the forest management are presented, namely how to use it to complete missing information from forest inventory and also showing how such an equation can be incorporated in a stand-level decision support system that aims to optimize the forest management for the maximization of wood volume production in Lomba ZIF maritime pine stands.

Implementation and Validation of a Self-Consumption Maximization Energy Management Strategy in a Vanadium Redox Flow BIPV Demonstrator

This paper presents the results of the implementation of a self-consumption maximization strategy tested in a real-scale Vanadium Redox Flow Battery (VRFB) (5 kW, 60 kWh) and Building Integrated Photovoltaics (BIPV) demonstrator (6.74 kWp). The tested energy management strategy aims to maximize the consumption of energy generated by a BIPV system through the usage of a battery. Whenever possible, the residual load is either stored in the battery to be used later or is supplied by the energy stored previously. The strategy was tested over seven days in a real-scale VRF battery to assess the validity of this battery to implement BIPV-focused energy management strategies. The results show that it was possible to obtain a self-consumption ratio of 100.0%, and that 75.6% of the energy consumed was provided by PV power. The VRFB was able to perform the strategy, although it was noticed that the available power (either to charge or discharge) varied with the state of charge.

Cell surface Glut1 levels distinguish human CD4 and CD8 T lymphocyte subsets with distinct effector functions

International audience

Self-ordered pointing as a test of working memory in typically developing children

The self-ordered pointing test (SOPT; Petrides & Milner, 1982) is a test of non-spatial executive working memory requiring the ability to generate and monitor a sequence of responses. Although used with developmental clinical populations there are few normative data against which to compare atypical performance. Typically developing children (5!11 years) and young adults performed two versions of the SOPT, one using pictures of familiar objects and the other hard-to-verbalise abstract designs. Performance improved with age but the children did not reach adult levels of performance. Participants of all ages found the object condition easier than the abstract condition, suggesting that verbal processes are utilised by the SOPT. However, performance on the task was largely independent from verbal and nonverbal cognitive ability. Overall the results suggest that the SOPT is a sensitive measure of executive working memory.

Mathematical Programming Models for Influence Maximization on Social Networks

In this dissertation, we apply mathematical programming techniques (i.e., integer programming and polyhedral combinatorics) to develop exact approaches for influence maximization on social networks. We study four combinatorial optimization problems that deal with maximizing influence at minimum cost over a social network. To our knowl- edge, all previous work to date involving influence maximization problems has focused on heuristics and approximation. We start with the following viral marketing problem that has attracted a significant amount of interest from the computer science literature. Given a social network, find a target set of customers to seed with a product. Then, a cascade will be caused by these initial adopters and other people start to adopt this product due to the influence they re- ceive from earlier adopters. The idea is to find the minimum cost that results in the entire network adopting the product. We first study a problem called the Weighted Target Set Selection (WTSS) Prob- lem. In the WTSS problem, the diffusion can take place over as many time periods as needed and a free product is given out to the individuals in the target set. Restricting the number of time periods that the diffusion takes place over to be one, we obtain a problem called the Positive Influence Dominating Set (PIDS) problem. Next, incorporating partial incentives, we consider a problem called the Least Cost Influence Problem (LCIP). The fourth problem studied is the One Time Period Least Cost Influence Problem (1TPLCIP) which is identical to the LCIP except that we restrict the number of time periods that the diffusion takes place over to be one. We apply a common research paradigm to each of these four problems. First, we work on special graphs: trees and cycles. Based on the insights we obtain from special graphs, we develop efficient methods for general graphs. On trees, first, we propose a polynomial time algorithm. More importantly, we present a tight and compact extended formulation. We also project the extended formulation onto the space of the natural vari- ables that gives the polytope on trees. Next, building upon the result for trees---we derive the polytope on cycles for the WTSS problem; as well as a polynomial time algorithm on cycles. This leads to our contribution on general graphs. For the WTSS problem and the LCIP, using the observation that the influence propagation network must be a directed acyclic graph (DAG), the strong formulation for trees can be embedded into a formulation on general graphs. We use this to design and implement a branch-and-cut approach for the WTSS problem and the LCIP. In our computational study, we are able to obtain high quality solutions for random graph instances with up to 10,000 nodes and 20,000 edges (40,000 arcs) within a reasonable amount of time.

Synthesis of Ordered Mesoporous Carbon Materials by Dry Etching

A novel synthesis method for ordered mesoporous carbons is presented. The inverse replication of a silica template was achieved using the carbonization of sucrose within mesoporous KIT-6. Instead of liquid acid etching, as in classical nanocasting, a novel dry chlorine etching procedure for template removal is presented for the first time. The resultant ordered mesostructured carbon material outperforms carbons obtained by conventional hard templating with respect to high specific micro- and mesopore volumes (0.6 and 1.6 cm3 g−1, respectively), due to the presence of a hierarchical pore system. A high specific surface area of 1671 m2 g−1 was achieved, rendering this synthesis route a highly convenient method to produce ordered mesoporous carbons.

Ordered mesoporous titanium oxide for thin film microbatteries with enhanced lithium storage

A 3D mesoporous TiO2 material with well-developed mesostructure is prepared in the form of a binder-free thin (100 nm) film and studied as potential candidate for the negative electrode in lithium microbatteries. By appropriate thermal treatments, the selected crystal structure (anatase, rutile, or amorphous), and micro-/mesostructure of the materials was obtained. The effects of voltage window and prelithiation treatment improved first cycle reversibility up to 86% and capacity retention of 90% over 100 cycles. After a prolonged intercalation of lithium ions in ordered mesoporous TiO2 appeared small particles assigned to Li2Ti2O4 with cubic structure as observed from ex-situ TEM micrographs. This study highlights the flexibility of the potential window to which the electrode can operate. Maximum capacity values over 100 cycles of 470 μA h cm−2 μm−1 and 177 μA h cm−2 μm−1 are obtained for voltage ranges of 0.1–2.6 V and 1.0–2.6 V, respectively. The observed values are between 6 and 2 times higher than those obtained for films with 600 nm (80 μA h cm−2 μm−1) and 900 nm (92 μA h cm−2 μm−1) lengths. This indicates that 100 nm thin TiO2 films with high accessibility show finite-length type diffusion which is interesting for this particular application.

Demonstration of (In, Ga)N/GaN Core-Shell Micro Light-Emitting Diodes Grown by Molecular Beam Epitaxy on Ordered MOVPE GaN Pillars

This work reports on the growth of (In, Ga)N core−shell micro pillars by plasma-assisted molecular beam epitaxy using an ordered array of GaN cores grown by metal organic vapor phase epitaxy as a template. Upon (In, Ga)N growth, core−shell structures with emission at around 3.0 eV are formed. Further, the fabrication of a core−shell pin structure is demonstrated.

Evaluation of the pathogenetic role of cellular subsets of the Follicular Lymphoma Microenvironment

Follicular lymphoma (FL) is a B cell neoplasm, composed of follicle center cells, that accounts for about 20% of all lymphomas, with the highest incidence reported in the USA and western Europe. FL has been considered a virtually incurable disease, with a high response rate alternated with frequent post-therapy relapses or progression towards more aggressive lymphomas. Due to the extreme variability in outcome, many efforts were made to predict prognosis, the need for therapy, and the likelihood of evolution. Even if clinical scores turned out to be robust and easy to use in clinical practice for patient risk stratification, marked heterogeneity in outcome remains within each group and further insights into the biology of FL are needed. The genome-wide approach underscored the pivotal role of the FL microenvironment in the evolution of the disease. In 2004, a landmark study by Dave et al. first described the microenvironment impact on tumor biology. By gene expression profiling they identified two different immune response signatures, involving T-cells and macrophages which seemed to independently predict FL outcome, but their exact is not completely understood and different studies led to variable results. Subsequently, many workgroups identified in amount and distribution pattern of these different cell subsets features which can impact prognosis, this leading to hypothesizing the use of these parameters as surrogate markers of the molecular signature. We aimed to assess the possible contributions of micro-environmental components to FL transformation or progression, its relevance as a prognostic/predictive tool, and its potential role as an innovative therapeutic target. We used immunohistochemical techniques, focusing specifically on macrophages and T-cells subsets, and then found correlations between the presence, proportions, and distribution of these reactive cells and the clinical outcomes leading to the future development of a reliable tool for upfront risk stratification of patients affected by FL.

Unsupervised reinforcement learning via state entropy maximization

Reinforcement Learning (RL) provides a powerful framework to address sequential decision-making problems in which the transition dynamics is unknown or too complex to be represented. The RL approach is based on speculating what is the best decision to make given sample estimates obtained from previous interactions, a recipe that led to several breakthroughs in various domains, ranging from game playing to robotics. Despite their success, current RL methods hardly generalize from one task to another, and achieving the kind of generalization obtained through unsupervised pre-training in non-sequential problems seems unthinkable. Unsupervised RL has recently emerged as a way to improve generalization of RL methods. Just as its non-sequential counterpart, the unsupervised RL framework comprises two phases: An unsupervised pre-training phase, in which the agent interacts with the environment without external feedback, and a supervised fine-tuning phase, in which the agent aims to efficiently solve a task in the same environment by exploiting the knowledge acquired during pre-training. In this thesis, we study unsupervised RL via state entropy maximization, in which the agent makes use of the unsupervised interactions to pre-train a policy that maximizes the entropy of its induced state distribution. First, we provide a theoretical characterization of the learning problem by considering a convex RL formulation that subsumes state entropy maximization. Our analysis shows that maximizing the state entropy in finite trials is inherently harder than RL. Then, we study the state entropy maximization problem from an optimization perspective. Especially, we show that the primal formulation of the corresponding optimization problem can be (approximately) addressed through tractable linear programs. Finally, we provide the first practical methodologies for state entropy maximization in complex domains, both when the pre-training takes place in a single environment as well as multiple environments.

Direct Visualization Of The Action Of Triton X-100 On Giant Vesicles Of Erythrocyte Membrane Lipids.

The raft hypothesis proposes that microdomains enriched in sphingolipids, cholesterol, and specific proteins are transiently formed to accomplish important cellular tasks. Equivocally, detergent-resistant membranes were initially assumed to be identical to membrane rafts, because of similarities between their compositions. In fact, the impact of detergents in membrane organization is still controversial. Here, we use phase contrast and fluorescence microscopy to observe giant unilamellar vesicles (GUVs) made of erythrocyte membrane lipids (erythro-GUVs) when exposed to the detergent Triton X-100 (TX-100). We clearly show that TX-100 has a restructuring action on biomembranes. Contact with TX-100 readily induces domain formation on the previously homogeneous membrane of erythro-GUVs at physiological and room temperatures. The shape and dynamics of the formed domains point to liquid-ordered/liquid-disordered (Lo/Ld) phase separation, typically found in raft-like ternary lipid mixtures. The Ld domains are then separated from the original vesicle and completely solubilized by TX-100. The insoluble vesicle left, in the Lo phase, represents around 2/3 of the original vesicle surface at room temperature and decreases to almost 1/2 at physiological temperature. This chain of events could be entirely reproduced with biomimetic GUVs of a simple ternary lipid mixture, 2:1:2 POPC/SM/chol (phosphatidylcholine/sphyngomyelin/cholesterol), showing that this behavior will arise because of fundamental physicochemical properties of simple lipid mixtures. This work provides direct visualization of TX-100-induced domain formation followed by selective (Ld phase) solubilization in a model system with a complex biological lipid composition.

What Is The Best Indication For Single-incision Ophira Mini Sling? Insights From A 2-year Follow-up International Multicentric Study.

The Ophira Mini Sling System involves anchoring a midurethral, low-tension tape to the obturator internus muscles bilaterally at the level of the tendinous arc. Success rates in different subsets of patients are still to be defined. This work aims to identify which factors influence the 2-year outcomes of this treatment. Analysis was based on data from a multicenter study. Endpoints for analysis included objective measurements: 1-h pad-weight (PWT), and cough stress test (CST), and questionnaires: International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF) and Urinary Distress Inventory (UDI)-6. A logistic regression analysis evaluated possible risk factors for failure. In all, 124 female patients with stress urinary incontinence (SUI) underwent treatment with the Ophira procedure. All patients completed 1 year of follow-up, and 95 complied with the 2-year evaluation. Longitudinal analysis showed no significant differences between results at 1 and 2 years. The 2-year overall objective results were 81 (85.3%) patients dry, six (6.3%) improved, and eight (8.4%) incontinent. A multivariate analysis revealed that previous anti-incontinence surgery was the only factor that significantly influenced surgical outcomes. Two years after treatment, women with previous failed surgeries had an odds ratio (OR) for treatment failure (based on PWT) of 4.0 [95% confidence interval (CI) 1.02-15.57). The Ophira procedure is an effective option for SUI treatment, with durable good results. Previous surgeries were identified as the only significant risk factor, though previously operated patients showed an acceptable success rate.

Emergent Antiferromagnetism Out Of The Hidden-order" State In Uru2si2: High Magnetic Field Nuclear Magnetic Resonance To 40 T."

Very high field (29)Si-NMR measurements using a fully (29)Si-enriched URu(2)Si(2) single crystal were carried out in order to microscopically investigate the hidden order (HO) state and adjacent magnetic phases in the high field limit. At the lowest measured temperature of 0.4 K, a clear anomaly reflecting a Fermi surface instability near 22 T inside the HO state is detected by the (29)Si shift, (29)K(c). Moreover, a strong enhancement of (29)K(c) develops near a critical field H(c) ≃ 35.6 T, and the ^{29}Si-NMR signal disappears suddenly at H(c), indicating the total suppression of the HO state. Nevertheless, a weak and shifted (29)Si-NMR signal reappears for fields higher than H(c) at 4.2 K, providing evidence for a magnetic structure within the magnetic phase caused by the Ising-type anisotropy of the uranium ordered moments.

Cd8+ Tumour-infiltrating Lymphocytes And Cox2 Expression May Predict Relapse In Differentiated Thyroid Cancer.

There is an increasing rate of papillary thyroid carcinomas that may never progress to cause symptoms or death. Predicting outcome and determining tumour aggressiveness could help diminish the number of patients submitted to aggressive treatments. We aimed to evaluate whether markers of the immune system response and of tumour-associated inflammation could predict outcome of differentiated thyroid cancer (DTC) patients. Retrospective cohort study. We studied 399 consecutive patients, including 325 papillary and 74 follicular thyroid carcinomas. Immune cell markers were evaluated using immunohistochemistry, including tumour-associated macrophages (CD68) and subsets of tumour-infiltrating lymphocytes (TIL), such as CD3, CD4, CD8, CD16, CD20, CD45RO, GRANZYME B, CD69 and CD25. We also investigated the expression of cyclooxygenase 2 (COX2) in tumour cells and the presence of concurrent lymphocytic infiltration characterizing chronic thyroiditis. Concurrent lymphocytic infiltration characterizing chronic thyroiditis was observed in 29% of the cases. Among all the immunological parameters evaluated, only the enrichment of CD8+ lymphocytes (P = 0·001) and expression of COX2 (P =0·01) were associated with recurrence. A multivariate model analysis identified CD8+ TIL/COX2 as independent risk factor for recurrence. A multivariate analysis using Cox's proportional-hazards model adjusted for the presence of concurrent chronic thyroiditis demonstrated that the presence of concurrent chronic thyroiditis had no effect on prognostic prediction mediated by CD8+ TIL and COX2. In conclusion, we suggest the use of a relatively simple pathology tool to help select cases that may benefit of a more aggressive approach sparing the majority of patients from unnecessary procedures.