Development of Microsatellite Markers for Loxosceles devia Gertsch & Mulaik (Araneae: Sicariidae) using Next Generation Sequencing

Brown recluse spiders in the genus Loxosceles are known for causing severe necrotic skin lesions. Despite their impact on human health, very little is known concerning the genetic diversity or population structure of this genus. The development of a suite of molecular markers (microsatellites) would allow us to obtain genetic data and expand the resources available to study Loxosceles devia, the species found throughout south Texas. Microsatellites are long tandem repeats about 1-6 nucleotides long of DNA, also known as simple sequence repeats. Their co-dominant method of inheritance, wide spread distribution across the nuclear genome, ease of scoring, and high mutation rates make microsatellites an ideal molecular marker. Unfortunately, the cost of developing microsatellites has limited their availability until now. The Ion Torrent Personal Genome Machine® was used to shotgun sequence libraries of genomic DNA derived from L. devia. The program MSATCOMMANDER™ was used to identify and design primers for di-, tri-, and tetra- microsatellite repeats from these shotgun sequences. Seventeen microsatellite markers were designed and polymerase chain reaction conditions were optimized for each primer to develop a suite of novel molecular markers for this species

Análisis cuantitativo del precio de la vivienda en Córdoba

El precio de la vivienda en zonas urbanas se analiza con un enfoque de modelos hedónico, en el que se valoran las características que determinan el precio que adquiere este bien en el mercado. Además de definir una serie de índices que tratan de representar características cualitativas de cada finca urbana, se analizan e interpretan los componentes principales con datos muestrales tomados en la ciudad de Córdoba, elaborándose el correspondiente modelo de determinación del precio de una vivienda

Biohydrogen production from diary processing wastewater by anaerobic biofilm reactors

Fermentative hydrogen production was studied in packed bed batch reactors to assess the influence of environmental factors over yield hydrogen production from dairy wastewater. Dried stems of Opuntia imbricata were used as substratum adding a pretreated mixed culture for biofilm formation. Experimental results showed that, yield hydrogen production was significantly affected by initial COD concentration, temperature and dairy wastewater pH. Maximum yield obtained was 12.73 mM H2/g CODc when initial COD concentration was 21.1 g COD, dairy wastewater pH with no adjustment (11.32) and room temperature of 16 ± 3°C. Methane production was completely inhibit at an initial pH of 4 at all temperature studied (final pH 4.06), meanwhile, with an initial pH of 11.32, with exception for 16°C, methanogenic activity was not completely inhibit when final pH was over 5, showing an increase in methane production of 0.35 to 0.75 g CH4/l for 35 to 55°C.Key words: Biofilm, dairy wastewater, hydrogen, Opuntia imbricat

Análisis literario : colección de trozos y composiciones en prosa y verso de los clásicos castellanos

Copia digital. Valladolid : Junta de Castilla y León. Consejería de Cultura y Turismo, 2009-201

El estilo y el lenguaje : discurso leído en la solemne apertura del curso 1884 a 1885 en el Instituto de Segovia

Copia digital. Valladolid : Junta de Castilla y León. Consejería de Cultura y Turismo, 2009-201

Does the Integration of Lean Production and Industry 4.0 in Green Supply Chains Generate a Better Operational Performance?

Purpose – The tightening of environmental measures and policies in various countries around the world is forcing manufacturing companies, particularly those that make up the automotive industry, to improve their production processes, through the implementation of approaches such as lean production and industry 4.0 technologies, to reduce industrial waste. However, the literature indicates that the implementation of lean production and Industry 4.0 does not always lead to an improvement in the level of operational performance. Therefore, this study analyzes the effects of the implementation of lean production practices and Industry 4.0 on a green supply chain and the operational performance of manufacturing companies in the Mexican automotive industry. Methodology/design/approach - A theoretical research framework consisting of six hypotheses was developed and validated by applying PLS-SEM and using a sample of 460 companies from the Mexican automotive industry. Findings - The results show that the level of operational performance of manufacturing companies increases substantially with the implementation of lean production and industry 4.0 practices, as well as a green supply chain. Originality/value - This study contributes to the literature on lean production and Industry 4.0 by providing robust empirical evidence of the positive effects of implementing these approaches on the green supply chain and operational performance of manufacturing companies. Practical implications - Managers of manufacturing companies will be able to use the results of this study to improve their production systems and to demonstrate the effects of these practices on operational performance

Investigating Potential Interventions on disruptive impacts of Industry 4.0 technologies in Circular Supply chains: Evidence from SMEs of an Emerging Economy

As a transversal theme, the intertwining of digitalization and sustainability has crossed all Supply Chains (SCs) levels dealing with widespread environmental and societal concerns. This paper investigates the potential interventions and disruptive impacts that Industry 4.0 technologies may have on pharmaceutical Circular SCs (CSCs). To accomplish this, a novel method involving a literature review and Pythagorean fuzzy-Delphi has initially been employed to identify and screen categorized lists of Industry 4.0 Disruptive Technologies (IDTs) and their impacts on pharmaceutical CSC. Subsequently, the weight of finalized impacts and the performance score of finalized IDTs have simultaneously been measured via a novel version of Pythagorean fuzzy SECA (Simultaneously Evaluation of Criteria and Alternatives). Then, the priority of each intervention for disruptive impacts of Industry 4.0 has been determined via the Hanlon method. This is one of the first papers to provide in-depth insights into advancing the study of the disruptive action of Industry 4.0 technologies cross-fertilizing CE throughout pharmaceutical SCs in the emerging economy of Iran. The results indicate that digital technologies such as Big Data Analytics, Global Positioning Systems, Enterprise Resource Planning, and Digital Platforms are quite available in the Irans' pharmaceutical industry. These technologies, along with four available interventions, e.g., environmental regulations, subsidy, fine, and reward, would facilitate moving towards a lean, agile, resilient, and sustainable supply chain through the efficient utilization of resources, optimized waste management, and substituting the human workforce by machines

Supplier selection for smart supply chain: An adaptive fuzzy-neuro approach

In recent years, companies have experienced international changes that have occurred as a result of technological advances, market globalization, or natural disasters. So, organizations are trying to improve their performance in order to be more competitive. In other words, organizations’ competitiveness highly depends on their suppliers. At present, companies need to consider and include so-called ‘resilience’, ‘sustainability’, and ‘smartness’ in the supplier’s selection to retain a competitive advantage. In this context, the purpose of this paper is to present an intelligent decision-making model for selecting the appropriate suppliers. For doing so, a set of criteria evaluation was determined to respond to the novel era circumstances. The suggested work is helpful for academics as well as professionals as it emphasizes the importance of resilient-sustainable supplier selection in the digital era.N/

Analysing Critical Factors of Strategic Alignment Between Operational Excellence and Industry 4.0 Technologies in Smart Manufacturing

The manufacturing sector is highly competitive and operationally complex. Therefore, the strategic alignment between operational excellence methodologies and Industry 4.0 technologies is one of the issues that need to be addressed. The main aim of the study is to determine the critical factors of strategic alignment between operational excellence methodologies and Industry 4.0 technologies for manufacturing industries and make comparative analyses between automotive, food, and textile industries in terms of strategic alignment between operational excellence methodologies and Industry 4.0 technologies. Firstly, determining the critical factors based on literature review and expert opinions, these criteria are weighted, and Analytical Hierarchy Process is run to calculate the weights of these criteria. Afterwards, the best sector is determined by the Gray Relational Analysis method according to the criteria for the three manufacturing industries selected for the study. As a result of AHP, ‘Infrastructure for Right Methodology, Techniques and Tools, is in the first place, ‘Organizational Strategy, is in the second place, while the third highest critical factor is ‘Capital Investment’. Moreover, based on Gray Relational Analysis results, the automotive industry is determined as the best alternative in terms of strategic alignment between OPEX methodologies and I4.0 technologies. This study is unique in that it is primarily possible to obtain the order of importance within the criteria and to make comparisons between three important manufacturing industries that are important for the economies of the world