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The complexity corresponding to the industrial projects and their management are concepts whose interest is increasing. The structural complexity derives directly from the main characteristics of c...

The quantification of the SARS-CoV-2 RNA load in wastewater has emerged as a useful tool to monitor COVID–19 outbreaks in the community. This approach was implemented in the metropolitan area of A Coruña (NW Spain), where wastewater from a treatment plant was analyzed to track the epidemic dynamics in a population of 369,098 inhabitants. Viral load detected in the wastewater and the epidemiological data from A Coruña health system served as main sources for statistical models developing. Regression models described here allowed us to estimate the number of infected people (R2 = 0.9), including symptomatic and asymptomatic individuals. These models have helped to understand the real magnitude of the epidemic in a population at any given time and have been used as an effective early warning tool for predicting outbreaks in A Coruña municipality. The methodology of the present work could be used to develop a similar wastewater-based epidemiological model to track the evolution of the COVID–19 epidemic anywhere in the world where centralized water-based sanitation systems exist., Graphical abstract Unlabelled Image

[Abstract] This work proposes a green material for artificial reefs to be placed in Galicia (northwest Spain) taking into account the principles of circular economy and sustainability of the ecosystem. New concrete formulations for marine applications, based on cement and/or sand replacement by mussel shells, are analyzed in terms of resistance to abrasion. The interest lies in the importance of the canning industry of Galicia, which generates important quantities of shell residues with negative environmental consequences. Currently, the tests to determine the abrasion erosion resistance of concrete on hydraulic structures involve large and complex devices. According to this, an experimental test has been proposed to estimate and compare the wear resistance of these concretes and, consequently, to analyze the environmental performance of these structures. First, a numerical analysis validated with experimental data was conducted to design the test. Subsequently, experimental tests were performed using a slurry tank in which samples with conventional cement and sand were partially replaced by mussel shell. The abrasive erosion effect of concrete components was analyzed by monitoring the mass loss. It shows an asymptotic trend with respect to time that has been modeled by Generalized Additive Model (GAM) and nonlinear regression models. The results were compared to concrete containing only conventional cement and sand. Replacing sand and/or cement by different proportions of mussel shells has not significantly reduced the resistance of concrete against erosive degradation, except for the case where a high amount of sand (20 wt.%) is replaced. Its resistance against the erosive abrasion is increased, losing between 0.1072 and 0.0310 wt.% lower than common concrete. In all the remaining cases (replacements of the 5–10 wt.% of sand and cement), the effect of mussel replacement on erosive degradation is not significant. These results encourage the use of mussel shells in the composition of concrete, taking into account that we obtain the same degradation properties, even more so considering an important residue in the canning industry (and part of the seabed) that can be valorized. This research was funded by Xunta de Galicia through the project CN-10MMA003CT. This study was also funded through the collaboration agreement between Xunta de Galicia (Convenio de colaboración entre a Xunta de Galicia, a Universidade da Coruña e a Fundación da Universidade da Coruña para dar continuidade ao Proxecto de investigación de arrecife artificial—PROARR), Universidade da Coruña and the Universidade da Coruña Foundation (FUAC) to give continuity to the previous project. The research of Javier Tarrío-Saavedra has been supported by MINECO grant MTM2017-82724-R, Ministerio de Ciencia e Innovación grant PID2020-113578RB-100, and by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2020-14 and Centro de Investigación del Sistema universitario de Galicia ED431G2019/01), all of them through the ERDF Xunta de Galicia; 10MMA003CT Xunta de Galicia; ED431C-2020-14 Xunta de Galicia; ED431G2019/01

In some industrial sectors such as naval construction, the use of adhesives is still limited to some specific applications. However, shipbuilders, academia and classification societies are cooperating to expand the field of certificated applications of adhesive joints. As a part of a validation study, thermal and rheological studies of the curing process and of the cured adhesives should be included. While a neat glass transition and other relaxation processes can be normally identified by ramp temperature tests performed both on a differential scanning calorimeter or on a rheometer, there are some adhesive systems in which several glass transitions or melting or crystallization processes overlap. Applying a thermal treatment to delete the thermal history and conditioning are common practices to clarify what happens in complex systems. However, although that practices usually help, there are still some complexities due to overlapping processes that cannot be easily understood. An important point of this work is to show how differential scanning calorimetry and rheology complement to each other in order to demonstrate several thermal relaxations and to obtain a better understanding of the cure process. The use of two different techniques along with a careful election of the setup parameter values allows to better interpret the thermal events. In addition, thermogravimetry helps to understand some rheological behaviors. In the end, this work shows how a good insight of the adhesive properties can be obtained by means of the combined use of DSC, rheology and TG.

In response to an increased reliance on bigger, Neopanamax-sized vessels for shipping, the Panama Canal has been expanded. Whilst the way that vessels transit the newly expanded canal has stayed the same, maneuvering operations have changed. As a result, transit times have been affected. In accordance with the size and cargo of vessels, canal navigation rules restrict how access channels (Culebra Cut, Gatun Lake, and seaways) and new locks (Cocoli and Agua Clara) are used. Larger sized, Neopanamax vessels will benefit most from the expanded canal. Since the canal opened on 26 June 2016, data on transit times have been gathered. With these data, a thorough statistical analysis should be carried out. The most influential variables on overall time in transit (TET), such as pilot skill and Culebra Cut or Gatun Lake transit times, are identified. Formulae based on multivariate linear regression can be extracted that will make it possible to establish a conductive methodology for estimating the transit time of a Neopanamax vessel. Taking into account the results of the statistical analysis, a proposal is included for improving Neopanamax traffic management, with views to reduce the TET, from a transit policy point of view. This is the first work in scientific literature that analyzes in detail, from qualitative and statistical approaches, the total time in transit through the set of navigable routes and locks that compose the new expanded Panama Canal.

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG [Abstract] Piloting in the Panama Canal is exceptional as, due to its importance, the functions of the captains of vessels are taken over by pilots. Hence, prior to inauguration of the expanded canal, a limited number of pilots experienced on the existing canal were certified for the transit of Neopanamax vessels by means of planned and innovative individual learning. After this organisational training through operative training, with the implementation of the expanded canal in June 2016, the routine training started. Hence the learning curve in the performance of these manoeuvres will represent the growing skill acquired by both the pilots and the organisation. Given that the learning effect is measurable, this paper has the dual objective of determining two curve models: the organisation operative learning curve model and the routine learning curve model for pilots performing transit manoeuvres in the expanded Panama Canal waterways and the Cocolí and Agua Clara locks. Manoeuvre times in locks and transit in the whole of the canal were followed up continuously in the first 42 months of operation. The research of Salvador Naya and Javier Tarrío has been supported by MINECO grant MTM2017-82724-R, and by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2020-14 and Centro de Investigación del Sistema universitario de Galicia ED431G 2019/01), all of them through the ERDF. This work has been funded in part by Project 1-FACINA of the International Maritime University of Panama (UMIP). Xunta de Galicia; ED431C-2020-14 Xunta de Galicia; ED431G 2019/01 Universidad Marítima Internacional de Panamá; Project 1-FACINA

[Abstract] A kinetic model is proposed to fit isothermal thermogravimetric data obtained from cellulose in an inert atmosphere at different temperatures. The method used here to evaluate the model involves two steps: (1) fitting of single time-derivative thermogravimetric curves (DTG) obtained at different temperatures versus time, and (2) fitting of the rate parameter values obtained at different temperatures versus temperature. The first step makes use of derivative of logistic functions. For the second step, the dependence of the rate factor on temperature is evaluated. That separation of the curve fitting from the analysis of the rate factor resulted to be very flexible since it proved to work for previous crystallization studies and now for thermal degradation of cellulose Ministerio de Asuntos Económicos y Transformación Digital; MTM2017-82724-R Xunta de Galicia; ED431C-2020-14 Xunta de Galicia; ED431G 2019/01

The quantification of the SARS-CoV-2 load in wastewater has emerged as a useful method to monitor COVID-19 outbreaks in the community. This approach was implemented in the metropolitan area of A Coruña (NW Spain), where wastewater from the treatment plant of Bens was analyzed to track the epidemic’s dynamic in a population of 369,098 inhabitants. We developed statistical regression models that allowed us to estimate the number of infected people from the viral load detected in the wastewater with a reliability close to 90%. This is the first wastewater-based epidemiological model that could potentially be adapted to track the evolution of the COVID-19 epidemic anywhere in the world, monitoring both symptomatic and asymptomatic individuals. It can help to understand with a high degree of reliability the true magnitude of the epidemic in a place at any given time and can be used as an effective early warning tool for predicting outbreaks.

The analysis of thermal processes associated to the curing of adhesives and the study of mechanical behavior once cured, provide key information to choose the best option for any specific application. The proposed methodology for the curing characterization, based on thermal analysis and rheology, is described through the comparison of three commercial adhesives. The experimental techniques used here are Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC) and Rheology. TGA provides information about the thermal stability and filler content, DSC allows the evaluation of some thermal events associated to the cure reaction and to thermal changes of the cured material when subjected to temperature changes. Rheology complements the information of the thermal transformations from a mechanical point of view. Thus, the curing reaction can be tracked through the elastic modulus (mainly the storage modulus), the phase angle and the gap. In addition, it is also shown that although DSC is of no use to study the curing of moisture curable adhesives, it is a very convenient method to evaluate the low temperature glass transition of amorphous systems.

This study proposes a control chart based on functional data to detect anomalies and estimate the normal output of industrial processes and services such as those related to the energy efficiency domain. Companies providing statistical consultancy services in the fields of energy efficiency, heating, ventilation and air conditioning (HVAC), installation and control, and big data for buildings, have been striving to solve the problem of automatic anomaly detection in buildings controlled by sensors. Given the functional nature of the critical to quality (CTQ) variables, this study proposed a new functional data analysis (FDA) control chart method based on the concept of data depth. Specifically, it developed a control methodology, including the Phase I and II control charts. It is based on the calculation of the depth of functional data, the identification of outliers by smooth bootstrap resampling and the customization of nonparametric rank control charts. A comprehensive simulation study, comprising scenarios defined with different degrees of dependence between curves, was conducted to evaluate the control procedure. The proposed statistical process control procedure was also applied to detect energy efficiency anomalies in the stores of a textile company in the Panama City. In this case, energy consumption has been defined as the CTQ variable of the HVAC system. Briefly, the proposed methodology, which combines FDA and multivariate techniques, adapts the concept of the control chart based on a specific case of functional data and thereby presents a novel alternative for controlling facilities in which the data are obtained by continuous monitoring, as is the case with a great deal of process in the framework of Industry 4.0.

The pilotage in the Panama Canal (PC) is unique due to the importance it acquires; in fact, the pilot relieves the captain in his/her duties during the transit. This exceptional nature has meant that prior to the commissioning of the expanded canal; a small group of experienced pilots of the existing Canal was enabled for the transit of Neopanamax ships through a planned and innovative learning.

The appearance of new gas extraction technologies has led to surplus production in the United States (Gulf of Mexico). At the same time, energy consumption in Asia has increased significantly and Japan has introduced important changes to its post-Fukushima energy policies. Taken together, these factors have resulted in an imbalance in production and consumption between the Atlantic and Pacific Maritime Areas. Over the same period of time, the Panama Canal expansion opened, permitting transit by liquefied natural gas vessels for the first time. These developments are reflected in the current order book for liquefied natural gas carriers, which is composed entirely of ships in the new Neopanamax category. The canal transit fees and new propulsion systems for these ships—dual fuel diesel electric and electronically controlled gas injection—significantly impact the price of cargo at the destination. This study conducts a sensitivity analysis of the variables for transportation costs in order to determine the expanded Canal’s competitive position. In addition, the study uses a Monte Carlo simulation to obtain the most representative values for total cost based on factors such as the type of propulsion and fuel as well as the distance traveled. The analysis clearly demonstrates the competitiveness of exporting liquefied natural gas via the Panama Canal from terminals in the Gulf of Mexico and the Caribbean to consumers in Asia, as well as the competitiveness of the canal itself versus alternative routes. With respect to propulsion systems, the study demonstrates the greater competitive advantage of electronically controlled gas injection propulsion.

In this paper we present an R package with routines to perform Interlaboratory Studies (ILS). The aim of the ILS package is to detect laboratories that provide not consistent results, working simultaneously with different test materials, from the perspective of the Univariate Data Analysis and the Functional Data Analysis (FDA). The ILS package estimates the Mandel's h and k scalar statistics, based on the ASTM E691 and ISO 5725-2 standards, to identify laboratories that provide significantly different results. Cochran and Grubbs tests to evaluate the presence of outliers are also available. In addition, Analysis of Variance (ANOVA) techniques are provided, both for the cases of fixed and random effects, including confidence intervals for the parameters. One of the novelties of this package is the incorporation of tools to perform an ILS from a functional data analysis approach. Accordingly, the functional nature of the data obtained by experimental techniques corresponding to analytical chemistry, applied physics and engineering applications (spectra, thermograms, and sensor signals, among others) is taking into account by implementing the functional extensions of Mandel's h and k statistics. For this purpose, the ILS package also estimates the functional statistics H ( t ) and K ( t ) , as well as the d H and d K test statistic, which are used to evaluate the repeatability and reproducibility hypotheses where the critical c h and c k values are estimated by using a bootstrap algorithm.

Purpose This work shows an effective methodology to evaluate the dynamic viscoelastic behavior of silicones for application in podiatry. The aim is to characterize, compare their viscoelastic properties according to the dynamic stresses they can be presumably subjected when used in podiatry orthotic applications. These results provide a deeper insight which extends the previous creep-recovery results to the world of dynamic stresses developed in physical activity. In this context, it shoulod be taken into account that an orthoses can subjected to a set of static and dynamic shear and compressive forces. Methods Two different podiatric silicones, Blanda-blanda and Master, from Herbitas, are characterized by dynamic rheological methods. Three kinds of rheological tests are considered: shear stress sweep, compression frequency sweep and shear frequency sweep, all the three with simultaneous control of the static force at three different levels. The static force represents a static load like that produced by the weight of a human body on a shoe insole. In a practical sense, dynamic stresses are related to physical activity and are needed to evaluate the frequency effect on the viscoelastic behavior of the material. It is considered that the dynamic stresses can be applied in compression and shear since, in practice, the way the stresses are applied in real life depends on the orthoses geometry and its exact location with respect to the foot and shoe. The effects of static and dynamic loads are individualized and compared to each other through the relations between the elastic constants for isotropic materials. Conclusions The overall proposed experimental methodology can provide very insightful information for better selection of materials in podiatry applications. This study focuses on the rheological characterization to choose the right silicone for each podiatric application, taking into account the dynamic viscoelastic requirements associated to the physical activity of user. Accordingly, one soft and one hard silicones of common use in podiatry were tested. Each of the two silicones exhibit not only different moduli values, but also, a different kind of dependence of the dynamic moduli with respect to the static load. In the case of the soft sample a linear trend is observed but in the case of of the hard one the dependence is of the power law type. Moreover, these samples exhibit very different Poisson's coefficient values for compression stresses lower than 20 kPa, and almost the same values for stresses above 40 kPa. That different dependence of the Poisson's ratio on the static load should also be taken into account for material selection in customized podiatry applications, where static and dynamic loads are strongly dependent on the individual weight and activity.

espanolEl principal objetivo de este trabajo es averiguar en que medida el hecho de que una empresa sea exportadora tiene consecuencias sobre su rendimiento. El caso de estudio, elaborado a partir de la base de datos ARDAN, se encuadra dentro de la region espanola de Galicia. El periodo temporal comprende desde el ano 2002 hasta 2013. La muestra recoge unicamente PYMEs. El analisis empirico parte de un conjunto de variables empresariales ligadas a la gestion, a factores fijos como la localizacion, y a la coyuntura economica. Los resultados obtenidos con las tecnicas de analisis aplicadas no son concluyentes y queda el camino abierto a nuevas investigaciones. EnglishThe main objective of this work is to find out to what extent the fact that a company is an exporter has consequences on its performance. The case study, developed from ARDAN database, is focused on the Spanish region of Galicia. The temporary period covers from 2002 to 2013. The sample includes only SMEs. The empirical analysis starts from a set of business variables linked to management, fixed factors such as location and to the economic situation. The results obtained with the analytical techniques applied are not conclusive and the way is open to new investigations.

The Panama Canal (PC) expansion will have an impact on trading patterns and the manner in which goods are transported around the world. Once the third set of locks at the Canal began their operation, it was clear that the way in which vessels transited the canal and their maximum dimensions were going to change. As such, the expanded Canal will undoubtedly mean that a new kind of vessel will come into existence. In terms of dimensions, these Neopanamax ships will be adapted to how the locks operate. However, this effect will not be the same across the full range of traffic. After the first transit on 26 June 2016, it was possible to obtain access to transit data for Neopanamax ships. A thorough statistical study of these new datasets would involve analysing how these new locks impact the vessel size and seaborne transport.

Functional data analysis (FDA) alternatives, based on the classical Mandel h and k statistics, are proposed to identify the laboratories that supply inconsistent results in interlaboratory studies (ILS). ILS is the procedure performed by a number of laboratories to test the precision of an analytical method, to measure the proficiency of laboratories in implementing an analytical procedure, to certify reference materials, and to evaluate a new experimental standard. The use of outlier tests, such as h and k Mandel statistics proposed by the ASTM E691, is crucial to assess these aims, estimating inter- and intra-laboratory data position and variability from a univariate point of view. Considering that experimental results obtained in analytical sciences are often functional, the use of FDA techniques can prevent the loss of important data information. The FDA approaches of h and k statistics are presented and point-wise obtained to deal with functional experimental data. Both functional statistics are estimated for each laboratory, their functional critical limits are obtained by bootstrap resampling, and new FDA versions of h and k graphics are presented. Real and synthetic thermogravimetric data are utilized to assess the good performance of the proposed FDA h and k statistics and their advantages with respect to the univariate approach.

Galicia's Rias face the challenge of solving key environmental issues. Fishing activities involving certain species are in decline and this trend has a negative impact on socio-economic contexts. Therefore, environmentally friendly technologies must be developed to protect and regenerate biodiversity; this biodiversity generates environmental wealth and socio-economic stability for the future. Installing green artificial reefs along the Galician coast is proposed as an effective option for marine biodiversity conservation; research has been carried out on their production. Here the proposal is to replace concrete aggregates with reused, lifeless waste materials from processes in the shipbuilding, fishing and shellfish industries. The statistical survey provides evidence to support the use of mussel shells since they offer compressive strength and water absorption, similar to what the sand in concrete provides.

With mid-depth trawling techniques, the number of fishing grounds available increases. In turn, the vessel can have a greater workload, as it has to control and direct its activity towards different species depending on the use of mid- or deep-sea equipment. However, specific equipment for each depth has to be used and this equipment influences the fishing manoeuvre. A new piece of auxiliary equipment comes into play to haul and store the net: the net winch. The aim of this study is to determine the most suitable net winch for each of the various vessels, fishing grounds and fishing modalities of the Spanish trawling fishing fleet. For each fishing ground, vessel size and target species, a relationship will be established with the net winch design parameters: fishing reel capacity, traction and operation speed.

The Panama Canal (PC) has recently been in the world spotlight. In August 2014, it celebrated 100 years of uninterrupted service and, in June 2016, the expansion project for the canal was inaugurated. The final project involved building a third set of locks. Once the canal started to operate, it could be seen that the way in which vessels transited the canal remained the same. However, the dimensions of locks and their revised operating procedures have had an effect on vessel size and the manoeuvres for the larger vessels. After the first transit on 26 June 2016, it was possible to have access to data on the new lockage systems for Neopanamax ships. The thorough statistical study of these new datasets (composed of Analysis of Variance (ANOVA), multivariate regression and statistical quality control techniques) has shown the main drivers of transit time across the Cocolí and Agua Clara locks. It has also made it possible to test the learning curve of Panama Canal pilots in the newly expanded canal. The effects of pilot training on the time it takes to transit through the locks, direction of entry in each lock, the type of vessel, vessel dimensions and the use of different types of manoeuvres have been analysed. The results are used to characterise and help optimise the performance of this new and unique lock system.

In this paper, a case study of performing a reliable statistical procedure to evaluate the quality of HVAC systems in buildings using data retrieved from an ad hoc big data web energy platform is presented. The proposed methodology based on statistical quality control (SQC) is used to analyze the real state of thermal comfort and energy efficiency of the offices of the company FRIDAMA (Spain) in a reliable way. Non-conformities or alarms, and the actual assignable causes of these out of control states are detected. The capability to meet specification requirements is also analyzed. Tools and packages implemented in the open-source R software are employed to apply the different procedures. First, this study proposes to fit ARIMA time series models to CTQ variables. Then, the application of Shewhart and EWMA control charts to the time series residuals is proposed to control and monitor thermal comfort and energy consumption in buildings. Once thermal comfort and consumption variability are estimated, the implementation of capability indexes for autocorrelated variables is proposed to calculate the degree to which standards specifications are met. According with case study results, the proposed methodology has detected real anomalies in HVAC installation, helping to detect assignable causes and to make appropriate decisions. One of the goals is to perform and describe step by step this statistical procedure in order to be replicated by practitioners in a better way.

A port&rsquo, s operating capacity and the economic performance of its concessions are intimately related to the quality of its operational conditions. This paper presents an analytical methodology for estimating the movements of a moored vessel based on field measurements and forecast data, specifically including ship dimensions and meteorological and maritime conditions. The methodology was tested and validated in the Outer Port of Punta Langosteira, A Coru&ntilde, a, Spain. It was determined that the significant wave height outside the port, and the ratio of the vessel&rsquo, s length divided by its beam (L/B), are the variables that most influence movements. Furthermore, heave and surge are the movements with a better value of the coefficient of determination (R2 values of 0.71 and 0.67, respectively), the sway (R2 = 0.30) and roll (R2 = 0.27) being the worst when using the available forecast variables of the Outer Port of Punta Langosteira. Despite their low R2 values, sway and roll models are able to estimate the main trends of these movements. The obtained estimators provide good predictions with assumable error values (root mean square error&mdash, RMSE and mean absolute error&mdash, MAE), showing their potential application as a predictive tool. Finally, as a consequence, the A Coru&ntilde, a Port Authority has included the results of the methodology in its port management system allowing them to predict moored vessel behavior in the port.

[Abstract] This work proposes a method based on image analysis and machine and statistical learning to model and estimate osteocyte growth (in type I collagen scaffolds for bone regeneration systems) and the collagen degradation degree due to cellular growth. To achieve these aims, the mass of collagen -subjected to the action of osteocyte growth and differentiation from stem cells- was measured on 3 days during each of 2 months, under conditions simulating a tissue in the human body. In addition, optical microscopy was applied to obtain information about cellular growth, cellular differentiation, and collagen degradation. Our first contribution consists of the application of a supervised classification random forest algorithm to image texture features (the structure tensor and entropy) for estimating the different regions of interest in an image obtained by optical microscopy: the extracellular matrix, collagen, and image background, and nuclei. Then, extracellular-matrix and collagen regions of interest were determined by the extraction of features related to the progression of the cellular growth and collagen degradation (e.g., mean area of objects and the mode of an intensity histogram). Finally, these critical features were statistically modeled depending on time via nonparametric and parametric linear and nonlinear models such as those based on logistic functions. Namely, the parametric logistic mixture models provided a way to identify and model the degradation due to biological activity by estimating the corresponding proportion of mass loss. The relation between osteocyte growth and differentiation from stem cells, on the one hand, and collagen degradation, on the other hand, was determined too and modeled through analysis of image objects’ circularity and area, in addition to collagen mass loss. This set of imaging techniques, machine learning procedures, and statistical tools allowed us to characterize and parameterize type I collagen biodegradation when collagen acts as a scaffold in bone regeneration tasks. Namely, the parametric logistic mixture models provided a way to identify and model the degradation due to biological activity and thus to estimate the corresponding proportion of mass loss. Moreover, the proposed methodology can help to estimate the degradation degree of scaffolds from the information obtained by optical microscopy. Ministerio de Asuntos Económicos y Transformación Digital; MTM2014-52876-R Ministerio de Asuntos Económicos y Transformación Digital; MTM2017-82724-R Xunta de Galicia; ED431C-2016-015 Xunta de Galicia; ED431G/01

Seabed classification in coastal environments is usually accomplished using multivariate methods applied to acoustic features from corrected or uncorrected echoes. This paper presents a comparative study of alternative statistical tools based on time series clustering and non-hierarchical clustering methods for functional data. This allows us to consider the entire acoustic signal without information reduction and assess performance using data acquired in a controlled environment with three different seabed types. The methods considered are used to both analyse the classification power of the recorded echoes and identify the most significant portions of signal. Fil: Tarrío Saavedra, Javier. Universidad da Coruña; España Fil: Sanchez Carnero, Noela Belen. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; Argentina Fil: Prieto, Andrés. Universidad da Coruña; España

This chapter aims to contrast if internationalization is a key element to explain the performance of a company, especially focusing on small and medium-size entreprises (SMEs), and to identify if a business model (BM) based on exports leads to more successful companies. There is a broad theoretical body and a representative set of methodological approaches in this area of knowledge; however, the conclusions reached are very different and in many cases hardly comparable, being limited to a specific temporal and geographical scope. For the purpose of giving a step further in the investigation of BM based on exports, the SMEs from the Autonomous Community of Galicia (Spain) are analyzed through an exploratory research over the 2002-2013 period. The empirical analysis takes into account a range of firm variables linked to both firm management and fixed factors, such as the type of sector, the location, and the economic situation.

A crankshaft is a mechanical component of an engine that performs a conversion of an alternative movement of a piston in a rotational motion of a shaft. It is a critical part and one of the most expensive of an engine. Defects in crankshafts may imply serious failures and, consequently, possible injuries and high costs. Therefore, the manufacture quality is of primordial importance for security and economic reasons. Nowadays, the quality control of crankshafts manufactured by forging in the automotive industry consists, among others, in inspecting them at the final process, using a magnetic particle procedure. This slow and highly stressful technique depends on operators and consumes many human resources, time, and space. This paper presents a methodology to automatically detect defective crankshafts. The proposed procedure is based on digital image analysis techniques, to extract a set of representative features from crankshaft images. Statistical techniques for supervised classification are used to classify the images into defective or not. The experimental results demonstrated the good performance of the proposed method with a classification accuracy over 99%, a 10% higher than the one obtained by manual inspection. Therefore, working time and personnel required for this task can be reduced when using this automated procedure.

[Abstract] The R package qcr for Statistical Quality Control (SQC) is introduced and described. It includes a comprehensive set of univariate and multivariate SQC tools that completes and increases the SQC techniques available in R. Apart from integrating different R packages devoted to SQC (qcc, MSQC), qcr provides nonparametric tools that are highly useful when Gaussian assumption is not met. This package computes standard univariate control charts for individual measurements, (Formula presented), S, R, p, np, c, u, EWMA, and CUSUM. In addition, it includes functions to perform multivariate control charts such as Hotelling T2, MEWMA and MCUSUM. As representative features, multivariate nonparametric alternatives based on data depth are implemented in this package: r, Q and S control charts. The qcr library also estimates the most complete set of capability indices from first to the fourth generation, covering the nonparametric alternatives, and performing the corresponding capability analysis graphical outputs, including the process capability plots. Moreover, Phase I and II control charts for functional data are included. The work of Salvador Naya, Javier Tarrío-Saavedra, Miguel Flores and Rubén Fernández-Casal has been supported by MINECO grant MTM2017-82724-R, and by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2020-14 and Centro de Investigación del Sistema universitario de Galicia ED431G 2019/01), all of them through the ERDF. The research of Miguel Flores has been partially supported by Grant PII-DM-002-2016 of Escuela Politécnica Nacional of Ecuador. In addition, the research of Javier Tarrío-Saavedra has been also founded by the eCOAR project (PC18/03) of CITIC Xunta de Galicia; ED431C-2020-14 Xunta de Galicia; ED431G 2019/01 Escuela Politécnica Nacional de Ecuador; PII-DM-002-2016

In offshore activities, it is necessary for the floating equipment extracting raw materials to reach and maintain a static position along the seabed. Increasingly crucial in these operations is a new type of auxiliary vessel: the anchor handling and supply. While this work is being carried out, the deck gear related to towing and anchor handling – secondary and tugger winches, as well as capstans – play a key role on the anchor handling and supply. To estimate the vessels capacity for taking part in towing and anchor handling tasks, one can turn to the concept of the pull number as the sum total of the traction for this equipment. Linear regression, non-linear and semi-parametric generalised and additive models are adjusted around a broad data base about state-of-the-art vessels. This makes it possible to estimate their value, using as a starting point the vessels main dimensions and power. From this estimate, the traction values for the main and anchor handling winches can be determined. The next step is to propose a way of calculating the traction needed by the secondary, capstan and towing winches assisting the manoeuvre. This study provides procedures and statistical models that can help determine the traction of the towing and anchor handling winches for the anchor handling and supply. These depend on the traction obtained in Bollard Pull testing. The analysis proposed here involves dimensioning the key equipment used on these kinds of vessels so that valuable design information is obtained.

The aim of this study is to statistically identify and distinguish wood samples corresponding to different areas of annual rings in trees of temperate regions, using the corresponding thermogravimetric (TG) and their first TG derivative (DTG) curves, and specifically to verify whether late and early wood chestnut samples are different with statistical significance, taking into account their TG and DTG curves. These significant differences are sought by applying statistical procedures based on functional data analysis (FDA), such as the functional ANOVA and the FDA classification methods. Each TG curve is firstly smoothed using the local polynomial regression estimator, and its first derivative is estimated. Then, functional ANOVA based on random projections (RP) is used to identify significant differences between TG or DTG curves of early and late wood samples. In order to know the extent of the differences between early and late wood samples, they are discriminated (and the correct classification proportion obtained) by employing a kernel nonparametric functional data analysis technique, based on the Bayes' rule, as well as functional generalized linear models and functional generalized additive models, allowing to classify materials using more than one type of thermal curves simultaneously. The results are compared with those obtained using some classical multivariate supervised classification methods: linear discriminant analysis, naive Bayes (NBC) and quadratic classification (QDA). The partial least squares (PLS) dimension reduction procedure was previously applied to the TG curves in order to employ these multivariate methods. The application of RP ANOVA shows significant differences between late and early wood regarding mass loss and mass loss rate under combustion. The use of PLS multivariate methods or FDA classification approaches applied to the TG and DTG curves allows to distinguish very accurately between late and early wood. The proposed method could be applied to other species to identify thermooxidative differences, combined with other experimental methods to find their chemical and physical causes.

En este trabajo, se proponen dos nuevos índices de capacidad robustos para detectar la influencia de los factores que pueden causar grandes desviaciones de las especificaciones técnicas del proceso. El comportamiento de estos nuevos índices se analizó mediante la comparación de su rendimiento con respecto a otras medidas de capacidad ampliamente estudiados en la literatura. El trabajo tiene como objetivo investigar la robustez de estos nuevos índices de capacidad bajo la presencia de valores extremos y de falta de normalidad. Para este propósito, se aplicaron técnicas de remuestreo Bootstrap para detectar la verdadera capacidad potencial de un proceso a través de los métodos de inferencia estadística. La precisión de los índices propuestos es discutida por medio de resultados numéricos con un ejemplo de datos reales. Robustness of process capability measurements is a very important matter in statistical quality control. In this paper, two new classes of capability measurements are studied as robust mechanisms to detect the influence of factors that may cause large departures from the process’ engineering specifications. The behavior of the new indices was analyzed by comparing their performance to other capability measures that have been widely studied in literature. The paper aims to investigate the robustness of the new capability ratios under the presence of outliers and a lack of normality. For this purpose, bootstrap techniques were applied to detect the true potential capability of a process via statistical inference methods. The accuracies of the proposed indices are discussed by means of numerical results from a real data example.

[Abstract] This methodology permits to simulate the performance of different Poly(D,L-lactide-co-glycolide) copolymer formulations (PDLGA) in the human body, to identify the more influencing variables on hydrolytic degradation and, thus, to estimate biopolymer degradation level. The PDLGA characteristic degradation trends, caused by hydrolysis processes, have been studied to define their future biomedical applications as dental scaffolds. For this purpose, the mass loss, pH, glass transition temperature (Tg) and absorbed water mass of the different biopolymers have been obtained from samples into a phosphate-buffered saline solution (PBS) with initial pH of 7.4, at 37°C (human body conditions). The mass loss has been defined as the variable that characterize the biopolymer degradation level. Its dependence relationship with respect to time, pH and biopolymer formulation has been modelled using statistical learning tools. Namely, generalized additive models (GAM) and nonlinear mixed-effects regression with logistic and asymptotic functions have been applied. GAM model provides information about the relevant variables and the parametric functions that relate mass loss, pH and time. Mixed effects are introduced to model and estimate the degradation properties, and to compare the PDLGA biopolymer populations. The degradation path for each polymer formulation has been estimated and compared with respect to the others for helping to use the proper polymer for each specific medical application, performing selection criteria. It was found that the mass loss differences in PDLGA copolymers are strongly related with the way the pH decay versus time, due to carboxylic acid groups formation. This may occur in those environments in which the degradation products remain relatively confined with the non degraded mass. This is the case emulated with the present experimental procedure. The results show that PDLGA polymers degradation degree, in terms of half life and degradation rate, is increasing when acid termination is included, when DL-lactide molar ratio is reduced, decreasing the midpoint viscosity, or when glycolide is not included. Xunta de Galicia; ED431G/012016-2019 Xunta de Galicia; ED431C2016-015 Ministerio de Economía y Competitividad; MTM2014-52876-R

Yachting uses the boat, in navigation and anchored, to develop different leisure activities. In this use the vessel remains static a great deal of the time of its total use, which constitutes a notable difference with respect to merchant activity. Maintaining the safe condition of the vessel at anchorage is not easy for the crew due to multiple factors: navigation with reduced crews and/or lack of crew professionalism/experience, tiredness after long navigation, ignorance of the area, or simply lack of attention during this time. These circumstances can be increased when the crew decide to anchor to rest or spend the night and the meteorological conditions vary without adapting the anchorage of the boat to this new situation. The objective of the work is the description of the results of the EAS project in which a system for the automatization and supervision of the anchorage maneuver has been developed. The system is designed to assist the crew in the anchorage by means of partial automation of the maneuver. During the stay at the anchorage area, the system passes to a situation of permanent surveillance that allows the detection of dangerous situations of dragging the anchor, alerting the crew, and recommending an action.

This work proposes the use of statistical methodologies based on unsupervised classification for the automatic identification of seabed types in coastal areas. For this purpose, acoustic data obtained by means of a simple beam echo sounder (at 200 kHz) coupled to a small ship have been used as discriminant features. Each of the resulting acoustic curves has been preprocessed through the application of time corrections (elongation of the echo with depth), power (attenuation of the wave with distance), and ping length (deformation of the echo due to distance), with the aim of eliminating its dependence with respect to depth. The experimental data have been obtained in a controlled environment in the region of Cabo de Palos (Murcia, Spain), studying three different types of bottom: sandy, sandy with sparse vegetation, and rock. The statistical techniques adapted and applied to this particular case belong to the cluster classification from time series. In fact, taking into account that in actual identification problems the existing fund classes are not known in advance, the problem of identification has been addressed through an unsupervised classification perspective based on the previous calculation of dissimilarity matrices and the application of hierarchical cluster classification methods. The results obtained, correctly identifying 93% of the total funds—with little confusion between their classes—support the use of automatic classification techniques in this area for the correct characterization of the seabed.