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Motivated by recent claims on the potential value of integration in warehouse management, this study evaluates the benefits arising from integrating the planning of order picking and packing processes in e-commerce warehouses. A set of research questions are proposed for exploring various benefits under different operational conditions and an experimental study is designed to answer them. In order to have a concrete model to represent the integrated planning method, a mixed-integer nonlinear programming model is developed, and then compared against a non-integrated variation. The experimental study makes the comparisons by analysing the collected empirical data from a real-life warehouse. Our findings indicate that integrated picking and packing planning can yield improved performance in different aspects under different configurations of objectives, order quantities, order categories or workforce allocation.

The germination and viability of pollen are characteristics required for fecundation when individuals of different or the same species are crossed. For this reason, assessing these parameters in selected individuals to be used in breeding programs will increase the chances for the obtainment of new progeny. In this study, pollen from different accessions of the red-purple tree tomato (Solanum betaceum Cav.) was used: local cultivar (Morado Puntón), two commercial varieties (Large Red and Oratia Red) and six segregants [(Solanum unilobum x Solanum betaceum) x Solanum betaceum]. Three types of flowers were taken (A-day of anthesis, B-one day after anthesis, and C-two days after anthesis). The pollen was conserved in two temperatures (4° and 22° C) and four storage times (0, 5, 10, 20 days). The percentage of germination and pollen viability of the selected individuals were evaluated. It was observed that the commercial materials showed higher germination percentages than the segregants in flower A and B at a temperature of 4 ° C at all storage times, except for the segregants GT7P47 and GT7P48 at the same temperature on day 0. In addition, high percentages of viability were obtained both in flowers A and B, at both temperatures and at all storage times. However, the immediate use of pollen after it is collected is recommended because better germination is achieved. This study is helpful to improve breeding procedures in the initial stages of directed crosses.

The emerging concept of digital twins outlines the pathway towards intelligent buildings. Although abundant building data carries an overwhelming amount of information, if not well exploited, the redundant and irrelevant data dimensions result in the overfitting problem and heavy computational load. Taking the fault detection and diagnosis process for building HVAC systems as the case, this paper adopts a symbolic artificial intelligence technique to identify informative sensory dimensions for building-specific faults by exploring the symbolic representation of labelled time-series. To preserve this ad-hoc temporal knowledge in the digital twin ecosystem, machine-readable fault tags are defined to label corresponding sensor entities. A digital twin data platform is developed to annotate the real-time data with fault tags and produce filtered low-latency data streams associated with a specified tag to automate this process. This paper describes a digital twin-based approach to automatically identify and pick up informative data to support dynamic asset management.

In this investigation, the optimization of mechanical properties with thermal post-processing treatments was analyzed across a wide range of variants. A major aspect of additive manufacturing is the correlation between heat treatments and the effects on the mechanical properties and microstructure of the printed materials. Therefore, the present paper describes a comprehensive overview of post-process heat treatments for Laser Powder Bed Fusion fabricated AlSi10Mg alloy consisting of stress relief anneals at 190 C and 285 C for 2 h, hot isostatic pressing at 515 C for 3 h, hot isostatic pressing + T6 treatment for 6 h, and final aging of each of these conditions at 177 C for up to 1000 h. This has resulted in 40 experimental variants: 20 in the vertical and 20 in the horizontal tensile direction. After tensile testing, the resulting mechanical properties (ultimate tensile strength, yield strength, and elongation) and stress–strain curves are analyzed for comparison between all variants. Ultra-fine cellular, micro dendritic structures (0.6–1.2 μm) along with melt-band structures dominated the asbuilt and stress relief anneal conditions. In contrast, hot isostatic pressing and hot isostatic pressing + T6 conditions were dominated by ~10 μm, equiaxed, recrystallized grain structures and pseudo-eutectic silicon particles with varying sizes and size distributions. Microhardness and fractography results also corresponded to their specific heat treatment and microstructure. The comparison and correlation of the heat treatments are presented to help advance the selection of design strategies for high performance applications.

El artículo analiza la película Leonera de Pablo Trapero. El filme representa la historia de Julia, una mujer joven y embarazada, que ingresaa prisión y debe luchar por ganarse un espacio entre las presas, así como defender el derecho a la crianza de su hijo. A partir de las ideasde vínculo y reciprocidad se explora la forma en que la protagonista construye sus interacciones sociales y afectivas al interior de la prisión.Concluimos que Julia configuró una compleja red de intercambios (servicios, bienes, afectos, sentimientos y corporalidades) que le permitió dar sentido a su experiencia en la cárcel.

Understanding and predicting bacterial behaviour in foods is vital for food safety. Although in the past most food microbiological research was conducted in liquids, it is now known that bacterial behaviour changes fundamentally when grown in structured environments. Furthermore, the bacterial behaviour is also affected by the natural microflora of foods and possible cross-contaminants. These can interact synergistically but can also be used as an antagonistic tool for food safety. The aim of this work is to perform a systematic study on the impact of fat concentrations (FC) on bacterial kinetics, their inter-species interactions, and their sensitivity towards the mild preservation technology of cold atmospheric plasma (CAP) in complex triphasic 3D systems. Building on our biphasic protein/polysaccharide food model (FM), a third fat phase was incorporated into the system (10-60%). Single-cultures of Listeria monocytogenes, Escherichia coli, Pseudomonas aeruginosa and Lactococcus lactis were grown on the surface of the FMs, as well as listerial co-cultures with each of the listed bacterium. A multiscale analysis took place macroscopically (plate count) and microscopically (confocal-laser-scanning-microscopy). Subsequently, the single- and co-cultures grown on the FMs surfaces were treated with CAP. Overall, the macroscopic analysis revealed increased growth of single cultures in comparison to co-cultures, but no significant impact in respect to the tested FCs. However, on the microscopic scale, generally, differences between the FCs were observed. More specifically, the bacterial colony sizes and biofilm formation were increased with increasing FC, more significant in co-cultures than in single-cultures. Due to these microscopic differences, a different level of cell-to-cell and colony-to-colony interaction takes place. This was further demonstrated by the susceptibility and resistance of the single- and co-cultures to the CAP treatment. In conclusion, our results indicate the importance of accounting for the microflora complexity and their interactions in food systems when predicting microbial behaviour and designing food decontamination treatments to ensure food safety.

The Digital Twin (DT) concept is gaining momentum in managing the built environment as a powerful tool to support data-driven decision making. Different open Data Models (DM) can be found in the literature. Each DM addresses the scale and domain applications. However, many DT applications are still based on organization-specific information management processes and proprietary DM, which prevent using the data outside the particular environments. This paper aims to present the process and information management approaches adopted for developing a federated DM supporting the DT applications. The Information Delivery Manual (IDM) process modelling, has been applied adopting a cross-disciplinary and multi-scale methodology. The proposed approach is applied to the West Cambridge Campus Digital Twin research facility, identifying five main phases: Information Requirements (IR) definition, data schemes mapping, conceptual model definition, prototyping, testing and validation. An insight into the BIM-based IR definition, employing the Industry Foundation Classes (IFC) schema is presented. Although additional testing and case studies are required for validation, the methods described in this paper are currently used to explore and develop DT applications at the building and built environment levels.

Ecuador is the main exporter of passion fruit concentrate. Passion fruit production is located in the subtropical areas of the Ecuadorian coast and, due to the geographical location of the country,...

Tree tomato (

Tree tomato (Solanum betaceum Cav.) is an Andean fruit crop that is grown in Ecuador. It is an exceptional source of minerals and vitamins, thus has nutraceutical properties. The objective of this research was to carry out a phytochemical characterization of a breeding population composed of 90 segregants. Pulp (including mesocarp, mucilage, seeds and placenta) was ground and sieved in order to obtain the liquid pulp to be lyophilized for the chemical analyzes. Antioxidants compounds were determined by spectrophotometry and vitamin C by reflectometry. Data were analyzed by principal components, grouping, and variance analyses; in addition, Z Score estimation was carried out to select elite individuals. There was a broad variability in the data obtained for the breeding population, polyphenol content varied from 5.11 to 16.59 mg GAE g−1, flavonoids from 1.24 to 6.70 mg cat g−1, carotenoids from 50.39 to 460.72 µg β-carotene g−1, anthocyanins from 1.06 to 240.49 mg cy-3-glu 100 g−1, antioxidant capacity from 49.51 to 312.30 µm Trolox g−1, and vitamin C from 78.29 to 420.16 mg 100 g−1. It can be concluded that tree tomato is a good source of beneficial biocompounds and has a high antioxidant capacity.

During the execution of business processes involving various organizations, Master Data is usually shared and exchanged. It is necessary to keep appropriate levels of quality in these Master Data in order to prevent problems in the business processes. Organizations can be benefitted from having information about the level of quality of master data along with the master data to support decision about the usage of data in business processes is to include information about the level of quality alongside the Master Data. ISO 8000-1x0 specifies how to add this information to the master data messages. From the clauses stated in the various part of standard we developed a reference architecture, enhanced with big data technologies to better support the management of large datasetsThe main contribution of this paper is a service architecture for Master Data Exchange supporting the requirements stated by the different parts of the standard like the development of a data dictionary with master data terms; a communication protocol; an API to manage the master data messages; and the algorithms in MapReduce to measure the data quality. Data Quality is basic to decide about the suitability of data for intended uses.Master Data are the critical data for the organizations.Master Data exchange is critical for the business process.A Service Arquitecture for Master Data Exchange based on ISO 8000-1x is proposed.Big Data changes the ways to do anything.Big Data Quality Completeness is measure.Big Data Quality Accuracy is measure.The results obtained must be understood in the context of a Big Data project.

Beyond the hype of Big Data, something within business intelligence projects is indeed changing. This is mainly because Big Data is not only about data, but also about a complete conceptual and technological stack including raw and processed data, storage, ways of managing data, processing and analytics. A challenge that becomes even trickier is the management of the quality of the data in Big Data environments. More than ever before the need for assessing the Quality-in-Use gains importance since the real contribution-business value-of data can be only estimated in its context of use. Although there exists different Data Quality models for assessing the quality of regular data, none of them has been adapted to Big Data. To fill this gap, we propose the "3As Data Quality-in-Use model", which is composed of three Data Quality characteristics for assessing the levels of Data Quality-in-Use in Big Data projects: Contextual Adequacy, Operational Adequacy and Temporal Adequacy. The model can be integrated into any sort of Big Data project, as it is independent of any pre-conditions or technologies. The paper shows the way to use the model with a working example. The model accomplishes every challenge related to Data Quality program aimed for Big Data. The main conclusion is that the model can be used as an appropriate way to obtain the Quality-in-Use levels of the input data of the Big Data analysis, and those levels can be understood as indicators of trustworthiness and soundness of the results of the Big Data analysis. Data Quality is basic to decide about the suitability of data for intended uses.A Data Quality-in-Use Model based on ISO/IEC 25012, 25024 is proposed for Big Data.The main concern when assessing the Data Quality-in-Use in Big Data is Adequacy.The model accomplishes all the challenges of a Data Quality program for Big Data.The results obtained must be understood in the context of each Big Data project.

La producción científica en Ecuador ha seguido un patrón similar a la evolución de otros países latinoamericanos, existiendo escasa generación de documentos indexados; pero en los últimos años se ha incrementado. El INIAP ha plasmado los resultados de sus investigaciones en publicaciones técnicas, dípticos, guías, manuales, entre otros. Desde el año 2014 ha tenido un aumento sostenido en su producción científica, debido a nueva reglamentación de acreditación e incentivos a investigadores. El objetivo de la presente investigación fue realizar un análisis de la producción científica del INIAP durante el periodo 2014-2019. Los resultados mostraron un aumentó 3,1 veces durante el periodo analizado, superando el crecimiento latinoamericano en ese mismo tiempo. Se determinó que más del 54% de las publicaciones del INIAP tienen colaboración internacional y el 62% de publicaciones están indexadas en revistas con índice SJR. Estos resultados indican que INIAP ha incrementado su producción y calidad científica en investigación agropecuaria.

Big data is an emerging field of research and many organizations especially governments, business and health care currently use them to make informed decisions. Millions of generated data are unstructured and come in a variety of formats. Nowadays, data technologies make possible to collect and store large and complex amounts of data and then to turn them into meaningful patterns. In higher education, there is limited research into big data despite it would bring opportunities to inform decisions and to identify potential issues related to policies, programs, teaching, learning and research. When learners interact with a digital device (smartphone, tablet or laptop) data about their interactions are easily “logged” and so can be used for further analysis. The trails that students leave behind can be analyzed and could reveal social connections, behaviors, preferences and goals. A large field of research opens to identify patterns and deviations from patterns, addressing some of the key challenges facing higher education. Spanish Universities have deployed different platforms to support teaching and learning. An important part of the teachers still uses the digital environment as a sort of digital photocopy service. However, some teachers make an advanced use of the virtual campus with tasks, exams, wikis and forums and other activities. The Universidad Complutense of Madrid has started some actions to allow the analysis of the students’ interactions and to examine patterns of students’ performance. We describe in this paper one of these pilot experiences focused on Human Histology, a subject in the second year of the Medicine Degree. Three are the main aims of this experience. First of all, to propose a working methodology to gather the data, to define the metrics and to set up the indicators that may be useful to identify patterns in the undergraduate students’ learning. Secondly, to evaluate the results in order to make better decisions that achieve better outcomes. Finally, to reflect on the metrics and indicators that could be useful to measure in other subjects and knowledge areas.

PurposeThe design, construction and deployment of a large virtual campus are a complex issue. Present virtual campuses are made of several software applications that complement e‐learning platforms. In order to develop and maintain such virtual campuses, a complex software engineering infrastructure is needed. This paper aims to analyse the software engineering infrastructure in the virtual campus deployed at the Universidad Complutense de Madrid.Design/methodology/approachThe software engineering infrastructure is analysed from three perspectives: process model; programming language and computer‐aided software engineering tools and design patterns and architecture.FindingsSoftware engineering infrastructure is a key issue in virtual campuses.Originality/valueThe value of the paper is to make our experience available to a wider audience so that organisations interested in the deployment of a large virtual campus can take advantage of our work.

During the execution of business processes involving various organizations, Master Data is usually shared and exchanged. It is necessary to keep appropriate levels of quality in these Master Data, in order to prevent defects and failures in the business processes. A way to support the decision about the usage of data in business processes is to include information about the level of quality alongside the Master Data. ISO/TS 8000 parts 100 to 140, may support the provision of this kind of information in a usable manner. Specifically I8K, a reference implementation from academic sources of the aforementioned standard parts (ISO/TS 8000:100-140), may be used for this objective. Regrettably, I8K is not aimed to support the assessment of large Master Data volumes and does not reach the required efficiency in Big Data surroundings. This paper describe an extension of I8K to resolve those problems of efficiency in Big Data projects.

Eight pathologically proven cases of pineal region tumors examined by computed tomography (CT) were found upon reviewing 11,000 consecutive CT studies at the Massachusetts General Hospital. The CT scan findings of the eight cases are described and related to a pathological classification of pineal tumors.