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The delayed product differentiation (DPD) recently rose as a hybrid production strategy able to overcome the main limits of make to stock (MTS) and make to order (MTO), guaranteeing the management of high variety and keeping low storage cost and quick response time by using the so-called product platforms. These platforms are a set of sub-systems forming a common structure from which a set of derivative variants can be efficiently produced. Platforms are manufactured and stocked following an MTS strategy. Then, they are customized into different variants, following an MTO strategy. Current literature proposes methods for platform design mainly using optimization techniques, which usually have a high computational complexity for efficiently managing real-size industrial instances in the modern mass customization era. Hence, efficient algorithms need to be developed to manage the product platforms design for such instances. To fill this gap, this paper proposes a two-step methodology for product platforms design and assessment in high-variety manufacturing. The design step involves the use of a novel modified algorithm for solving the longest common subsequence (LCS) problem and of the k-medoids clustering for the identification of the platform structure and the assignment of the variants to the platforms. The platforms are then assessed against a set of industrial and market metrics, i.e. the MTS cost, the variety, the customer responsiveness, and the variants production cost. The evaluation of the platform set against such a combined set of drivers enhancing both company and market perspectives is missing in the literature. A real case study dealing with the manufacturing of a family of valves exemplifies the efficiency of the methodology in supporting companies in managing high-variety to best balance the proposed metrics.

In the last years, in industry, the adoption of effective microclimate strategies for the improvement of the indoor air quality (IAQ) has been considered an important topic for its effects on the workers' health and safety, but it is recently more relevant than ever in the light of the current coronavirus pandemic. The ongoing coronavirus pandemic is moving the scientific community's attention to the study of new microclimate strategies to reduce the transmission of respiratory viruses within industrial settings. Experimental studies showed that increased ventilation and controlled relative humidity levels influence the buoyancy of the expiratory clouds ejected during human respiratory. The result is a reduced contamination range of the suspended droplets containing the respiratory viruses. The existing literature outlines eight Indoor Environmental Quality (IEQ) factors impacting occupants' health and well-being. Among these, IAQ and thermal comfort rise as the most influential ones. The Italian National Institute of Health recently defined a set of strategic implementation measures to improve the IAQ in industrial environments and, ultimately, contain the transmission of the SARS-CoV-2. Moreover, the World Health Organization recommends an increase in the ventilation rate of industrial environments through natural aeration or artificial ventilation. However, these microclimatic variations may cause thermal stress, discomfort and other adverse effects on workers' health and safety. As the literature lacks studies reviewing the effects of these microclimatic strategies, this paper aims to investigate their impact on the well-being and productivity of industrial workers. At the same time, this work is also of interest to industries as it analyses the technologies adopted in the industry to improve IEQ. The findings of this paper describe the critical contents of mid-long term strategies for reducing the transmission of respiratory infections, as the common seasonal flu and the recent coronavirus disease 2019 (COVID-19).

In the last decades, the energy consumption increases due to several factors such as the economic and population growth and the climate change. Both the rapid depletion of the fossil fuels and the rising concern on the environmental issues make the renewable energy sources (RESs), e.g. solar, wind, etc., a promising alternative with the aim to produce low-carbon heat and electricity. Within this energy transition scenario, several countries, by promoting new government policies, make efforts to encourage their diffusion. Such sources allow achieving multiple environmental and financial goals, e.g. the reduction of the greenhouse effect, lower costs, high efficiency and the opportunity to provide electricity to remote areas. For these reasons, the scientific literature focuses on supporting hybrid renewable energy systems (HRESs). Such systems integrate one or more RESs and a backup source, e.g. diesel, oil, natural gas, etc. or the electric grid, and they often include an energy storage (ES) system. HRESs join the strengths of each power source and they try to reduce the impact of their weaknesses. The aim of this paper is to revise the literature on HRESs for power generation, identifying the main technologies and facilities for both on-grid and offgrid applications, considering different operative and geo-climate scenarios and different users. The scope, i.e. research question, is to categorise the developed models and approaches by considering different KPIs identifying feasibility limits, best practices and suitable directions for future research.

This paper addresses the so-called integrated process planning and scheduling (IPPS) problem in a reconfigurable manufacturing environment. Process planning and scheduling are two important and complex functions in manufacturing. To reduce the problem complexity, they are considered sequentially by traditional approaches. In this paper, we consider the simultaneous integration of both functions by developing a heuristic approach to solve the IPPS problem in a reconfigurable environment. Reconfigurable manufacturing systems (RMSs) comprise of a set of machines distinguished by multiple working configurations and tools. Each machine can perform a certain number of operations based on its configurations and their availability. The purpose of the proposed heuristic approach is to find the best assignment of operations to machines while considering process-quality. Finally, to demonstrate the approach applicability, an illustrative numerical example is presented and the results discussed.

Nowadays, manufacturing environment is characterized by the necessity of customized flexibility as well as responding rapidly and cost-effectively to changing market demands while minimizing impacts on environment and society. To reach these goals, a key paradigm called sustainable manufacturing can be coupled with reconfigurable manufacturing systems (RMSs). The coupling of RMS characteristics and sustainability concerns is a basis to develop a new generation of sustainable production systems. This paper outlines sustainability in a reconfigurable environment from an energy consumption point of view. A nonlinear mathematical model is developed to optimize the energy consumption of a RMS through a redefinition of its core characteristics-modularity and integrability. The objective is to minimize the energy consumption of the system by selecting the most suitable modular machines from a set of candidate machines. The optimization problem is addressed using an exhaustive search heuristic. Finally, the applicability of the proposed approach is illustrated through a simple numerical example and the discussion of the obtained results.

Made available in DSpace on 2022-04-28T17:21:35Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-07-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Company Finacier of Studies and Projects (FINEP) Context. Exercise and anabolic steroids are anticipated to promote fat mass reduction and so decrease the number of comorbidities related to excessive weight. Objective. The aim of this study was to verify the influence of aerobic exercise and the use of steroids on the accumulation of adipose tissue and on the biochemical limitations of Wistar rats nourished by a hypercaloric diet. Methods. Forty, young male Wistar rats were split into four groups: obese control (n=10), obese under treatment (n=10), obese under aerobic exercise (n=10) and obese under aerobic exercise and treatment (n=10). All animals were fed with a hypercaloric diet and animals under treatment received intramuscular testosterone. Body (weight and visceral fat) and blood (lipidogram, glucose, and liver enzymes) parameters were assessed. Results. The group treated with aerobic exercise and testosterone revealed a reduction in body weight and visceral, perirenal, retroperitoneal and epididymal fats, accompanied by the blood levels of glucose, lactate, LDLcholesterol, HDL-cholesterol, and lactate dehydrogenase; following high-intensity physical activity. Conclusion. The results support the theory that the combination of steroids and physical activity reduce side-effects of androgenic-anabolic hormones and convey benefits to some constraints. Univ Fed Acre, Postgrad Program Hlth Sci Western Amazon, Rio Branco, AC, Brazil Coll Meta, Rio Branco, Acre, Brazil Univ Fed Acre, Med Hlth & Sports Sci Ctr, Rio Branco, Brazil Univ Fed Uberlandia, Inst Biotechnol, Uberlandia, MG, Brazil Univ Fed Acre, Postgrad Program Sanit & Sustainable Anim Prod We, Rio Branco, AC, Brazil Sao Paulo State Univ, UNESP, Av Hygino Muzzi Filho 737, BR-17525900 Marilia, SP, Brazil Sao Paulo State Univ, UNESP, Av Hygino Muzzi Filho 737, BR-17525900 Marilia, SP, Brazil

International audience

In modern industry, companies adopt Lean Management (LM) to increase efficiency and productivity and to reduce wastes and no-value added activities. In parallel, according to the international regulations, rising attention is toward Green Management (GM) to minimize environmental emissions. Despite the most of the existing literature contributions focuses on such two topics separately, an emerging trend analyzes the integration and relationships between LM and GM. This paper follows this stream and addresses the integration between LM and GM in the greedy energy industry, i.e. industry using machines characterized by time and energy consuming phase-in and switch-off setup times. These times represent low-value added activities because production is off and significant CO2 emissions take place. In this paper, an original bi-objective model minimizes the environmental emissions generated by the overall process, i.e. the green objective function, and the cumulative stock in terms of gap between the production rate and the customer demand, i.e. the lean objective function, matching the Just-in-Time (JIT) principles aiming at producing what the customers need, when needed. The model application to a study-case gets emission reduction and good market demand matching.

We studied HLA class I (HLA-A, -B) and class II (HLA-DRB1, -DQB1) allele groups and alleles by PCR-SSP based typing in a total of 15,318 mixed ancestry Mexicans from all the states of the country divided into 78 sample sets, providing information regarding allelic and haplotypic frequencies and their linkage disequilibrium, as well as admixture estimates and genetic substructure. We identified the presence of 4268 unique HLA extended haplotypes across Mexico and find that the ten most frequent (HF > 1%) HLA haplotypes with significant linkage disequilibrium (Δ’≥0.1) in Mexico (accounting for 20% of the haplotypic diversity of the country) are of primarily Native American ancestry (A*02~B*39~DRB1*04~DQB1*03:02, A*02~B*35~DRB1*08~DQB1*04, A*68~B*39~DRB1*04~DQB1*03:02, A*02~B*35~DRB1*04~DQB1*03:02, A*24~B*39~DRB1*14~DQB1*03:01, A*24~B*35~DRB1*04~DQB1*03:02, A*24~B*39~DRB1*04~DQB1*03:02, A*02~B*40:02~DRB1*04~DQB1*03:02, A*68~B*35~DRB1*04~DQB1*03:02, A*02~B*15:01~DRB1*04~DQB1*03:02). Admixture estimates obtained by a maximum likelihood method using HLA-A/-B/-DRB1 as genetic estimators revealed that the main genetic components in Mexico as a whole are Native American (ranging from 37.8% in the northern part of the country to 81.5% in the southeastern region) and European (ranging from 11.5% in the southeast to 62.6% in northern Mexico). African admixture ranged from 0.0 to 12.7% not following any specific pattern. We were able to detect three major immunogenetic clusters correlating with genetic diversity and differential admixture within Mexico: North, Central and Southeast, which is in accordance with previous reports using genome-wide data. Our findings provide insights into the population immunogenetic substructure of the whole country and add to the knowledge of mixed ancestry Latin American population genetics, important for disease association studies, detection of demographic signatures on population variation and improved allocation of public health resources. Fil: Barquera, Rodrigo. Max Planck Institute For The Science Of Human History; Alemania. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; México Fil: Hernández Zaragoza, Diana Iraíz. Técnicas Genéticas Aplicadas A la Clínica (tgac); México. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; México Fil: Bravo Acevedo, Alicia. Instituto Mexicano del Seguro Social; México Fil: Arrieta Bolaños, Esteban. Universitat Essen; Alemania Fil: Clayton, Stephen. Max Planck Institute For The Science Of Human History; Alemania Fil: Acuña Alonzo, Víctor. Instituto Nacional de Antropología E Historia, Mexico; México Fil: Martínez Álvarez, Julio César. Instituto Mexicano del Seguro Social; México Fil: López Gil, Concepción. Instituto Mexicano del Seguro Social; México Fil: Adalid Sáinz, Carmen. Instituto Mexicano del Seguro Social; México Fil: Vega Martínez, María del Rosario. Hospital Central Sur de Alta Especialidad; México Fil: Escobedo Ruíz, Araceli. Instituto Mexicano del Seguro Social; México Fil: Juárez Cortés, Eva Dolores. Instituto Mexicano del Seguro Social; México Fil: Immel, Alexander. Max Planck Institute For The Science Of Human History; Alemania. Christian Albrechts Universitat Zu Kiel; Alemania Fil: Pacheco Ubaldo, Hanna. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; México Fil: González Medina, Liliana. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; México Fil: Lona Sánchez, Abraham. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; México Fil: Lara Riegos, Julio. Universidad Autónoma de Yucatán; México Fil: Sánchez Fernández, María Guadalupe de Jesús. Instituto Mexicano del Seguro Social; México Fil: Díaz López, Rosario. Hospital Central Militar, Mexico City; México Fil: Guizar López, Gregorio Ulises. Hospital Central Militar, Mexico City; México Fil: Medina Escobedo, Carolina Elizabeth. Instituto Mexicano del Seguro Social; México Fil: Arrazola García, María Araceli. Instituto Mexicano del Seguro Social; México Fil: Montiel Hernández, Gustavo Daniel. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; México Fil: Hernández Hernández, Ofelia. Técnicas Genéticas Aplicadas a la Clínica ; México Fil: Ramos de la Cruz, Flor del Rocío. Instituto Mexicano del Seguro Social; México Fil: Juárez Nicolás, Francisco. Instituto Nacional de Pediatría; México Fil: Pantoja Torres, Jorge Arturo. Instituto Mexicano del Seguro Social; México Fil: Rodríguez Munguía, Tirzo Jesús. Hospital General Norberto Treviño Zapata; México Fil: Juárez Barreto, Vicencio. Hospital Infantil de Mexico Federico Gomez; México Fil: Gonzalez-Jose, Rolando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; Argentina

Mixed-model Flexible Manufacturing Systems (FMSs) and, more recently, Reconfigurable Manufacturing Systems (RMSs) are widely studied as diffuse solutions for complex production environments, targeting variable markets and highly dynamic production plans. Their design and management are challenging both in new plants and for plant-redesign actions. In this field, the literature suggests the adoption of cellular configurations as effective solutions. These configurations partition the FMS and RMS machines into manufacturing cells and assign the working parts to the cells to reduce the so-called intercellular flows, causing costs and inbound congestions. This paper advances the current literature presenting and applying an optimal linear programming cost model for the redesign of mixed-model FMS/RMS cellular production environments. The model goes beyond the widely studied partitioning of the FMSs among the cells and it best balances machine relocations and redundancies, the production area layout optimization and the intercellular flow reduction. The major industrial operative constraints are included in the model together with a reference case study to exemplify its advantages toward the standard approaches.