Even if no experimental evidence has been found so far, TeV-scale supersymmetry is still one of the most popular extensions of the Standard Model. This work summarizes some of the most recent results ...on inclusive searches obtained with the ATLAS detector using about 80 fb−1 of data collected in 2015-2017 at a center-of-mass energy s=13TeV. Also prospects on the HL-LHC discovery potential are presented assuming an integrated luminosity of 3000 fb−1 at s=14TeV.
•A new coffee leaves dataset is developed and being made publicly available.•A multi-task framework is proposed to identify and quantify biotic stress.•Different Deep Learning architectures are ...compared showing promising results.
Biotic stress consists of damage to plants through other living organisms. The efficient control of biotic agents such as pests and pathogens (viruses, fungi, bacteria, etc.) is closely related to the concept of agricultural sustainability. Agricultural sustainability promotes the development of new technologies that allow the reduction of environmental impacts, greater accessibility to farmers and, consequently, increased productivity. The use of computer vision with deep learning methods allows the early and correct identification of the stress-causing agent. So, corrective measures can be applied as soon as possible to mitigate the problem. The objective of this work is to design an effective and practical system capable of identifying and estimating the stress severity caused by biotic agents on coffee leaves. The proposed approach consists of a multi-task system based on convolutional neural networks. In addition, we have explored the use of data augmentation techniques to make the system more robust and accurate. Computational experiments performed with the proposed system using the ResNet50 architecture obtained an accuracy of 95.24% for the biotic stress classification and 86.51% for severity estimation. Moreover, it was found that by classifying only the symptoms, the results were greater than 97%. The experimental results indicate that the proposed system might be a suitable tool to assist both experts and farmers in the identification and quantification of biotic stresses in coffee plantations.
Rates of overweight in North American children and adolescents have increased dramatically since the 1970s. Childhood obesity has reached epidemic proportions and calls for prevention and treatment ...programs to reverse this trend have been made. However, the evidence base needed for effective action is still incomplete, especially for childhood obesity prevention programs. This paper focuses on primary prevention of childhood obesity and has three aims: (1) to briefly describe current primary prevention approaches for childhood obesity and the evidence for their impact; (2) to elucidate promising, but untested intervention strategies using an ecological framework and evidence from experimental and epidemiological research on factors influencing children's eating and weight status; and (3) to introduce a multiphase strategy for screening intervention components and building and evaluating potent interventions for childhood obesity. Most childhood obesity prevention programs have focused on school-aged children and have had little success. We suggest that, given these findings, prevention efforts should be expanded to explore other contexts in which children live as possible settings for intervention efforts, including the family and childcare settings. Given that 25% of preschool children are already overweight, intervening with children before school entry should be a priority. A review of experimental research on the developing controls of food intake in infancy and childhood suggests possible intervention strategies, focusing on parenting and aspects of the feeding environment. Epidemiological findings point to even earlier modifiable risk factors, including gestational weight gain, maternal prepregnancy weight, and formula feeding. However, the potential impact of altering these risk factors remains to be evaluated. In response to this problem, we suggest a new, multiphase method for accomplishing this, including screening intervention components, refining intervention designs and confirming component efficacy to build and evaluate potent, optimized interventions.
ABSTRACT
We revisit the joint pricing, supplier selection, and inventory replenishment problem for a single item in a two‐stage system examined by Adeinat and Ventura (2015) and use the logit ...function to model the price‐sensitive demand. This article provides a detailed analysis regarding the shape and properties of the logit demand function. In this context, we propose a two‐stage piecewise‐linear approximation technique to solve the integrated pricing, supplier selection, and inventory replenishment model. Besides, in this research, we provide sufficient justification for the selection of the logit demand function as well as a comparison with other demand functions. A numerical study further suggests the importance of using a precise demand curve to select the set of suppliers, coordinate inventory, and accurately optimize the profit function.
Sustainable transportation refers to low vehicular greenhouse gas (GHG) emissions, energy efficient vehicles, and affordable modes of transportation, including electric and alternative fuel (AF) ...vehicles ...
•A new dynamic supplier selection and inventory model for a serial supply chain is proposed.•Suppliers use a price break and discount scheme that considers order frequency and lead time.•The ...manufacturer achieves minimal purchasing cost by taking advantage of economies of scale.•A second model is proposed where the length of the time period is considered as a variable.•It is shown that the length of the time period affects inventory planning decisions.
A new supplier price break and discount scheme taking into account order frequency and lead time is introduced and incorporated into an integrated inventory planning model for a serial supply chain that minimizes the overall incurred cost including procurement, inventory holding, production, and transportation. A mixed-integer linear programming (MILP) formulation is presented addressing this multi-period, multi-supplier, and multi-stage problem with predetermined time-varying demand for the case of a single product. Then, the length of the time period is considered as a variable. A new MILP formulation is derived when each period of the model is split into multiple sub-periods, and under certain conditions, it is proved that the optimal solution and objective value of the original model form a feasible solution and an upper bound for the derived model. In a numerical example, three scenarios of the derived model are solved where the number of sub-period is set to 2, 3, and 4. The results further show the decrease of the optimal objective value as the length of the time period is shortened. Sufficient evidence demonstrates that the length of the time period has a significant influence on supplier selection, lot sizing allocation, and inventory planning decisions. This poses the necessity of the selection of appropriate length of a time period, considering the trade-off between model complexity and cost savings.
•A pseudo-polynomial algorithm to solve the two-product capacitated dynamic lot-sizing problem is proposed.•The structure of an optimal solution is analyzed with respect to a type of period called ...regeneration period, which is a period where the inventory of one or both products reach zero.•A master problem network is used to determine the location of regeneration periods.•A subproblem network finds an optimal arrangement of orders between consecutive regeneration periods.•Numerical experiments are performed to show the efficiency of the proposed algorithm.•We show how to extend this approach to any number of products.
In this paper, we analyze a two-product multi-period dynamic lot-sizing problem with a fixed capacity constraint in each period. Each product has a known demand in each period that must be satisfied over a finite planning horizon. The aim of this problem is to minimize the overall cost of placing orders and carrying inventory across all periods. The structure of an optimal solution is analyzed with respect to a type of period called regeneration period, which is a period where the inventory of one or both products reach zero. We show that there is an optimal arrangement of placing orders between consecutive regeneration periods. We propose a pseudo-polynomial algorithm to solve the two-product problem. First, we show how the optimal ordering pattern between two consecutive regeneration periods can be solved using a shortest path problem. Then, we explain how the optimal locations for regeneration periods can be found by solving a shortest path problem on a different network, where each arc corresponds to the shortest path in a subproblem network. We then show how this approach can be scaled up to a three-product problem and generalize this technique to any number of products, as long as it is small.
In this work, we study the multi-product dynamic lot-sizing problem with capacity constraints and batch ordering. This problem arises in short to medium range production scheduling for several ...products over a finite number of periods to meet known demand. Each period has a capacity for placing orders, and every order for each product must have a fixed quantity, or batch size, though multiple orders can be placed for each product. We define three mixed-integer linear programming (MILP) models and apply Lagrangian relaxation to formulate the corresponding dual problems by relaxing the capacity constraints. The aim is to identify the dual problem that is the easiest to solve and provides the solution with the smallest duality gap. Subgradient optimisation is applied to solve the preferred Lagrangian dual model, which uses one of two heuristics to find good feasible solutions. We also show that the special case, where the batch sizes for all products are the same, can be modeled as a transportation problem. A set of numerical experiments is designed to compare the performance of the Lagrangian relaxation approach with a commercial MILP solver to identify the version of the subgradient algorithm and the MILP model that provide the best solutions.
The aim of this paper is to solve a multi-period supplier selection and inventory lot-sizing problem with multiple products in a serial supply chain. Compared to previous models proposed in the ...literature, our research incorporates a richer cost structure involving joint replenishment costs for raw material replenishment and production, and a more realistic description of the transportation costs represented as a vector of full-truck load costs for different size trucks. This problem can be displayed graphically as a time-expanded transshipment network defined by nodes and arcs that can be reached by feasible material flows. First, we propose an
integrated
mixed integer linear programming model that minimizes the cost over the entire supply chain for a given planning horizon. The model determines the optimal dynamic supplier selection, inventory lot-sizing, and production schedule simultaneously. Second, a
sequential
approach is proposed to solve the same problem. That is, a production schedule is determined first, and then a supplier selection and replenishment strategy is obtained according to that predetermined schedule. Sensitivity analysis comparing the two approaches is performed. Results show that, even though the integrated approach achieves the minimum cost, the sequential approach may be suitable for solving large-scale instances of the problem as it requires less information sharing and generates a near-optimal solution with shorter implementation time and computational effort.
ABSTRACT
Objective:
Diagnostic criteria for coeliac disease (CD) from the European Society for Paediatric Gastroenterology, Hepatology, and Nutrition (ESPGHAN) were published in 1990. Since then, the ...autoantigen in CD, tissue transglutaminase, has been identified; the perception of CD has changed from that of a rather uncommon enteropathy to a common multiorgan disease strongly dependent on the haplotypes human leukocyte antigen (HLA)‐DQ2 and HLA‐DQ8; and CD‐specific antibody tests have improved.
Methods:
A panel of 17 experts defined CD and developed new diagnostic criteria based on the Delphi process. Two groups of patients were defined with different diagnostic approaches to diagnose CD: children with symptoms suggestive of CD (group 1) and asymptomatic children at increased risk for CD (group 2). The 2004 National Institutes of Health/Agency for Healthcare Research and Quality report and a systematic literature search on antibody tests for CD in paediatric patients covering the years 2004 to 2009 was the basis for the evidence‐based recommendations on CD‐specific antibody testing.
Results:
In group 1, the diagnosis of CD is based on symptoms, positive serology, and histology that is consistent with CD. If immunoglobulin A anti‐tissue transglutaminase type 2 antibody titers are high (>10 times the upper limit of normal), then the option is to diagnose CD without duodenal biopsies by applying a strict protocol with further laboratory tests. In group 2, the diagnosis of CD is based on positive serology and histology. HLA‐DQ2 and HLA‐DQ8 testing is valuable because CD is unlikely if both haplotypes are negative.
Conclusions:
The aim of the new guidelines was to achieve a high diagnostic accuracy and to reduce the burden for patients and their families. The performance of these guidelines in clinical practice should be evaluated prospectively.
PDF
