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Currently, age is characterized by implementing business management models based on precarious work and a massive reduction in jobs. This article aims to analyze the degree of happiness perceived in Spanish entrepreneurs, as opposed to that perceived by the employees, and if that happiness is associated with certain sociodemographic variables (such as gender, level of studies, and income level). For this purpose, a brief literature review of the economy of happiness is carried out, considering studies regarding the happiness–entrepreneurship connection over the past few years. With data provided by the Sociological Research Center (C.I.S.) barometer survey, we work in two phases: (1) descriptive and inferential on possible associations between the variables, and (2) the calculation of probabilities through logistic regression. The main result shows that the entrepreneurs with employees are happiest. When the null hypothesis is rejected, the categories that seem to show the most happiness are those with higher education and those in the highest income ranges analyzed. Among the main limitations in this work is the scarcity of bibliographic production on the subject matter of this paper. This paper helps to cover part of this gap.

Segmenting histology images into diagnostically relevant regions is imperative to support timely and reliable decisions by pathologists. To this end, computer-aided techniques have been proposed to delineate relevant regions in scanned histology slides. However, the techniques necessitate task-specific large datasets of annotated pixels, which is tedious, time-consuming, expensive, and infeasible to acquire for many histology tasks. Thus, weakly-supervised semantic segmentation techniques are proposed to utilize weak supervision that is cheaper and quicker to acquire. In this paper, we propose SegGini, a weakly supervised segmentation method using graphs, that can utilize weak multiplex annotations, i.e. inexact and incomplete annotations, to segment arbitrary and large images, scaling from tissue microarray (TMA) to whole slide image (WSI). Formally, SegGini constructs a tissue-graph representation for an input histology image, where the graph nodes depict tissue regions. Then, it performs weakly-supervised segmentation via node classification by using inexact image-level labels, incomplete scribbles, or both. We evaluated SegGini on two public prostate cancer datasets containing TMAs and WSIs. Our method achieved state-of-the-art segmentation performance on both datasets for various annotation settings while being comparable to a pathologist baseline., Comment: 10 pages, 5 figures

Deep learning-based methods are gaining traction in digital pathology, with an increasing number of publications and challenges that aim at easing the work of systematically and exhaustively analyzing tissue slides. These methods often achieve very high accuracies, at the cost of requiring large annotated datasets to train. This requirement is especially difficult to fulfill in the medical field, where expert knowledge is essential. In this paper we focus on nuclei segmentation, which generally requires experienced pathologists to annotate the nuclear areas in gigapixel histological images. We propose an algorithm for instance segmentation that uses pseudo-label segmentations generated automatically from point annotations, as a method to reduce the burden for pathologists. With the generated segmentation masks, the proposed method trains a modified version of HoVer-Net model to achieve instance segmentation. Experimental results show that the proposed method is robust to inaccuracies in point annotations and comparison with Hover-Net trained with fully annotated instance masks shows that a degradation in segmentation performance does not always imply a degradation in higher order tasks such as tissue classification.

Explainability of deep learning methods is imperative to facilitate their clinical adoption in digital pathology. However, popular deep learning methods and explainability techniques (explainers) based on pixel-wise processing disregard biological entities' notion, thus complicating comprehension by pathologists. In this work, we address this by adopting biological entity-based graph processing and graph explainers enabling explanations accessible to pathologists. In this context, a major challenge becomes to discern meaningful explainers, particularly in a standardized and quantifiable fashion. To this end, we propose herein a set of novel quantitative metrics based on statistics of class separability using pathologically measurable concepts to characterize graph explainers. We employ the proposed metrics to evaluate three types of graph explainers, namely the layer-wise relevance propagation, gradient-based saliency, and graph pruning approaches, to explain Cell-Graph representations for Breast Cancer Subtyping. The proposed metrics are also applicable in other domains by using domain-specific intuitive concepts. We validate the qualitative and quantitative findings on the BRACS dataset, a large cohort of breast cancer RoIs, by expert pathologists., Comment: CVPR 2021

Motivation is a basic element of the 'Happiness Management' model at work. Its components are analyzed in the digital era under the Herzberg Theory of the motivational and hygienic factors, to verify if an association between worker sociodemographic profile and these factors is detected, which would allow the managers to "sanitize" them. In a group of companies in Algeciras Bay (Spain) a survey collects the opinions from workers about the issues that have been established as motivational and hygienic factors. It is confirmed that the motivational factors are highly valued. Falsity of the data, fear of being substituted at job, and depersonalization because automation are the most feared topics. An association of worker sociodemographic variables and the level to which some of these fears are manifested is found out. The main originality of this paper lies in the contribution and analysis of new factors, motivational and hygienic, of digital age in workplace, which must be managed., Considerando la motivación como integrante básico de la gestión de la felicidad en el trabajo, se analiza la valoración de determinados componentes de la misma en la era digital a partir del concepto de factor motivacional e higiénico de Herzberg. Se comprobará si existe alguna asociación entre el perfil sociodemográfico del trabajador y ciertos factores a “higienizar”. En una muestra de empresas de la Bahía de Algeciras (España), y mediante cuestionario, se recogen las opiniones de los trabajadores con respecto a dichos componentes. Se confirma que los factores motivacionales propuestos son altamente valorados. La falsedad de datos, el miedo a ser sustituidos en las tareas y la despersonalización del trabajo son las cuestiones más temidas, cuya ausencia hay que procurar. Se percibe, también, asociación de determinadas variables sociodemográficas del trabajador con el grado en que se manifiestan alguno de esos temores. La originalidad principal de este trabajo estriba en que se aportan y analizan factores, motivacionales e higiénicos de nueva aparición en lo laboral, que, como tales, habrán de ser gestionados.

Information retrieval algorithms have changed the way we manage and use various data sources, such as images, music or multimedia collections. First, free text information of documents from varying sources became accessible in addition to structured data in databases, initially for exact search and then for more probabilistic models. Novel approaches enable content-based visual search of images using computerized image analysis making visual image content searchable without requiring high quality manual annotations. Other multimedia data followed such as video and music retrieval, sometimes based on techniques such as extracting objects and classifying genre. 3D (surface) objects and solid textures have also been produced in quickly increasing quantities, for example in medical tomographic imaging. For these two types of 3D information sources, systems have become available to characterize the objects or textures and search for similar visual content in large databases. With 3D moving sequences (i.e., 4D), in particular medical imaging, even higher-dimensional data have become available for analysis and retrieval and currently present many multimedia retrieval challenges. This article systematically reviews current techniques in various fields of 3D and 4D visual information retrieval and analyses the currently dominating application areas. The employed techniques are analysed and regrouped to highlight similarities and complementarities among them in order to guide the choice of optimal approaches for new 3D and 4D retrieval problems. Opportunities for future applications conclude the article. 3D or higher-dimensional visual information retrieval is expected to grow quickly in the coming years and in this respect this article can serve as a basis for designing new applications.

In this paper a theoretical model of sustainable behavior is developed. Through this theoretical model, that we have called Commitment Model Applied to Social Marketing, we propose to establish a relation between the use of social marketing strategies from an integrative perspective and the consumer engagement or commitment. The methodology used has been a literature review about some of the most important social marketing and engagement theories. To explain how to apply the model we have used the case method, through the study of the non profit organization: “Coordinadora de Lucha contra la Droga, Barrio Vivo” (“Coordinator for Combating Drugs, Living Neighborhood”), in Algeciras, a city in the of South-East of the province of Cádiz, in the area denominated Campo de Gibraltar. This area has experienced a dramatic amount of drug consumption by a significant part of its youth population, facilitated by its geographical proximity to North Africa.

The Bag--of--Visual--Words (BoVW) is a visual description technique that aims at shortening the semantic gap by partitioning a low--level feature space into regions of the feature space that potentially correspond to visual concepts and by giving more value to this space. In this paper we present a conceptual analysis of three major properties of language grammar and how they can be adapted to the computer vision and image understanding domain based on the bag of visual words paradigm. Evaluation of the visual grammar shows that a positive impact on classification accuracy and/or descriptor size is obtained when the technique are applied when the proposed techniques are applied.

Epilepsy is a disorder of the brain that can lead to acute crisis and if possible an intervention can help patients. The exact localization of epileptogenic lesions influences the outcome of epilepsy surgery. Magnetic resonance (MR) imaging is clinically used for lesion detection and treatment planning, mainly through simple visual analysis. However, visual inspection in MR imaging can be highly subjective and subtle 3D structural abnormalities can be missclassified or not resected completely during the surgery. In this paper, a measurement of the differences in texture of the cerebral cortex between brain hemispheres is proposed. The 3D Riesz wavelet transform and the Hausdorff distance are used in MR T1 weighted images of the brain. A classification accuracy of 85% is obtained with 10 healthy control subjects and 8 patients with various types of epileptogenic lesions. The proposed quantitative measure of the texture alterations of these lesions allows an objective pre-surgical evaluation of patients undergoing epilepsy surgery.

Content-based medical image retrieval has been proposed as a technique that allows not only for easy access to images from the relevant literature and electronic health records but also for training physicians, for research and clinical decision support. The bag-of-visual-words approach is a widely used technique that tries to shorten the semantic gap by learning meaningful features from the dataset and describing documents and images in terms of the histogram of these features. Visual vocabularies are often redundant, over-complete and noisy. Larger than required vocabularies lead to high-dimensional feature spaces, which present important disadvantages with the curse of dimensionality and computational cost being the most obvious ones. In this work a visual vocabulary pruning technique is presented. It enormously reduces the amount of required words to describe a medical image dataset with no significant effect on the accuracy. Results show that a reduction of up to 90% can be achieved without impact on the system performance. Obtaining a more compact representation of a document enables multimodal description as well as using classifiers requiring low-dimensional representations.

In this paper, a novel 3D retrieval model to retrieve medical volumes using 2D images as input is proposed. The main idea consists of applying a multi-scale detection of saliency of image regions. Then, the 3D volumes with the regions for each of the scales are associated with a set of projections onto the three canonical planes.The 3D shape is indirectly represented by a 2D-shape descriptor so that the 3D-shape matching is transformed into measuring similarity between 2D-shapes. The shape descriptor is defined by the set of the k largest singular values of the 2D images and Euclidean distance between the vector descriptors is used as a similarity measure. The preliminary results obtained on a simple database show promising performance with a mean average precision (MAP) of 0.82 and could allow using the approach as part of a retrieval system in clinical routine.

Partiendo de la normativa preconstitucional, como es la Orden de 29 de marzo de 1974, B.O.E. de 4 de abril, para llegar hasta el Real Decreto Legislativo 2/2011, de 5 de septiembre, por el que se aprueba el Texto Refundido de la Ley de Puertos del Estado y de la Marina Mercante, en este artículo hacemos un repaso sobre la evolución de la normativa en España dentro del sector de la manipulación de mercancías en los puertos españoles, conocido como el sector de la estiba. Éste, que es un sector estratégico dentro de la economía de nuestro país, se caracteriza porque se muestra muy reacio a cambios, sobre todo, desde su parte social. Compro-bamos, además, cómo la legislación evoluciona con la finalidad de inferir un efecto liberalizador en el sector, siguiendo los preceptos de la Unión Europea.

Partiendo de la normativa preconstitucional, como es la Orden de 29 de marzo de 1974, B.O.E. de 4 de abril, para llegar hasta el Real Decreto Legislativo 2/2011, de 5 de septiembre, por el que se aprueba el Texto Refundido de la Ley de Puertos del Estado y de la Marina Mercante, en este artículo hacemos un repaso sobre la evolución de la normativa en España dentro del sector de la manipulación de mercancías en los puertos españoles, conocido como el sector de la estiba. Éste, que es un sector estratégico dentro de la economía de nuestro país, se caracteriza porque se muestra muy reacio a cambios, sobre todo, desde su parte social. Compro-bamos, además, cómo la legislación evoluciona con la finalidad de inferir un efecto liberalizador en el sector, siguiendo los preceptos de la Unión Europea

No son frecuentes los trabajos sobre las necesidades del pequeño empresario, menos aún los referidos a la formación continua dentro de este colectivo. El presente artículo recoge parte de las conclusiones de un estudio de campo sobre formación y cualificación del personal entre las pequeñas empresas de la comarca gaditana del Campo de Gibraltar, una de las dos únicas áreas metropolitanas de Andalucía no basadas en una ciudad capitalina. A través de los resultados de este trabajo de investigación, analizamos determinadas capacidades profesionales, ya sean de carácter técnico, humano o conceptual, y su grado de demanda por parte de los pequeños empresarios. Es decir, testamos lo que dichos empresarios requieren a sus empleados, y, en consecuencia, podríamos deducir que se tratan las competencias que más empleabilidad otorgan a sus trabajadores. En este sentido, han sido las materias técnicas las que han constituido el contenido habitual de las actividades a las que han acudido las pequeñas empresas del Campo de Gibraltar para la formación continua de sus empleados. No obstante, descubrimos que en este estudio los empresarios consultados, sin dejar de reconocer la utilidad de ciertas capacidades técnicas, requieren en mayor medida que éstas un conjunto de habilidades humanas y de tipo conceptual. Si, tal como sostiene la Teoría de los recursos y las capacidades de la empresa, -y es fundamento actual de la Gestión del Conocimiento-, la cualificación del personal puede constituir un elemento clave en la obtención de ventajas competitivas para la organización, y si la formación del trabajador es, por tanto, un instrumento a tal fin, lo primero que debe el empresario considerar es cuáles son las capacidades de las que necesitaría disponer entre sus recursos humanos para lograr esa ventaja, y cuál es el grado en que el personal las alcanzan, para proceder, a continuación, a plantear un proceso formativo que cubra los vacíos hallados. Adicionalmente, diferenciamos tres subgr, There are not many studies about the needs of the small companies, especially those related to professional training in this group. This article contains some of the findings of a research work on training and qualifications of personnel among small businesses in the Cadiz region of Campo de Gibraltar, one of only two metropolitan areas in Andalusia that are not based on a capital city. Through the results of this research we analyze certain skills, whether technical, human and conceptual, and its level of demand from small businesses. I.e., we have tested which employers require to their employees, and thus might deduce that those skills are what give employability to their workers. Technical matters are what have formed the contents of the activities in which small businesses in Campo de Gibraltar have conducted training of its employees. However, this study found that employers consulted, while recognizing the utility of certain technical skills, require especially human and conceptual skills. If, as maintained by the resource-based view of the firm, and is the basis of current Knowledge Management, the personnel can constitute a key element in gaining competitive advantages for the organization, and whether training worker is therefore an instrument for this target, the first thing the employer must consider is what skills need to dispose of its human resources to achieve that advantage, and what is the degree to which staff reach them, to carry on a training process that covers the gaps found. Additionally, we have differentiated three subgroups of firms within the group of small businesses: micro, mini and small businesses, according to size, to check, in a concise manner, how while the firm size increases new skills will be required to workers. In the end, we analyze the capabilities what are provided from the staff in greater degree among the firms questioned, differentiating between the firms which give continuous training to his employees and those that do

Este trabajo desarrolla un método para la búsqueda y selección de un implante para la sustitución de una estructura anatómica dañada. Para ello se ha implementado un sistema de recuperación de imágenes en 3D basado en contenido, por el cual a partir del tratamiento de imágenes radiológicas tridimensionales del paciente, se obtiene una lista de los posibles casos de una base de datos disponible, ordenados por la similitud con el original. El sistema está basado en la extracción de características locales a lo largo de cada modelo, para su incorporación a una base de datos con un motor de búsqueda que selecciona los puntos de afinidad entre el modelo buscado y los propuestos. Posteriormente se realiza una selección de aquellos que comparten, además, características globales.

Epilepsy is a disorder of the brain that can lead to acute crisis and if possible an intervention can help patients. The exact localization of epileptogenic lesions influences the outcome of epilepsy surgery. Magnetic resonance (MR) imaging is clinically used for lesion detection and treatment planning, mainly through simple visual analysis. However, visual inspection in MR imaging can be highly subjective and subtle 3D structural abnormalities can be missclassified or not resected completely during the surgery. In this paper, a measurement of the differences in texture of the cerebral cortex between brain hemispheres is proposed. The 3D Riesz wavelet transform and the Hausdorff distance are used in MR T1 weighted images of the brain. A classification accuracy of 85% is obtained with 10 healthy control subjects and 8 patients with various types of epileptogenic lesions. The proposed quantitative measure of the texture alterations of these lesions allows an objective pre-surgical evaluation of patients undergoing epilepsy surgery.

Content-based medical image retrieval has been proposed as a technique that allows not only for easy access to images from the relevant literature and electronic health records but also for training physicians, for research and clinical decision support. The bag-of-visual-words approach is a widely used technique that tries to shorten the semantic gap by learning meaningful features from the dataset and describing documents and images in terms of the histogram of these features. Visual vocabularies are often redundant, over-complete and noisy. Larger than required vocabularies lead to high-dimensional feature spaces, which present important disadvantages with the curse of dimensionality and computational cost being the most obvious ones. In this work a visual vocabulary pruning technique is presented. It enormously reduces the amount of required words to describe a medical image dataset with no significant effect on the accuracy. Results show that a reduction of up to 90% can be achieved without impact on the system performance. Obtaining a more compact representation of a document enables multimodal description as well as using classifiers requiring low-dimensional representations.

In this paper, a novel 3D retrieval model to retrieve medical volumes using 2D images as input is proposed. The main idea consists of applying a multi-scale detection of saliency of image regions. Then, the 3D volumes with the regions for each of the scales are associated with a set of projections onto the three canonical planes.The 3D shape is indirectly represented by a 2D-shape descriptor so that the 3D-shape matching is transformed into measuring similarity between 2D-shapes. The shape descriptor is defined by the set of the k largest singular values of the 2D images and Euclidean distance between the vector descriptors is used as a similarity measure. The preliminary results obtained on a simple database show promising performance with a mean average precision (MAP) of 0.82 and could allow using the approach as part of a retrieval system in clinical routine.

Information retrieval algorithms have changed the way we manage and use various data sources, such as images, music or multimedia collections. First, free text information of documents from varying sources became accessible in addition to structured data in databases, initially for exact search and then for more probabilistic models. Novel approaches enable content-based visual search of images using computerized image analysis making visual image content searchable without requiring high quality manual annotations. Other multimedia data followed such as video and music retrieval, sometimes based on techniques such as extracting objects and classifying genre. 3D (surface) objects and solid textures have also been produced in quickly increasing quantities, for example in medical tomographic imaging. For these two types of 3D information sources, systems have become available to characterize the objects or textures and search for similar visual content in large databases. With 3D moving sequences (i.e., 4D), in particular medical imaging, even higher-dimensional data have become available for analysis and retrieval and currently present many multimedia retrieval challenges. This article systematically reviews current techniques in various fields of 3D and 4D visual information retrieval and analyses the currently dominating application areas. The employed techniques are analysed and regrouped to highlight similarities and complementarities among them in order to guide the choice of optimal approaches for new 3D and 4D retrieval problems. Opportunities for future applications conclude the article. 3D or higher-dimensional visual information retrieval is expected to grow quickly in the coming years and in this respect this article can serve as a basis for designing new applications.