Performance of two transferred modules in the Lagunera Region: Water relations

Water policy / Performance / Privatization / Irrigation systems / Operations / Maintenance / Irrigation efficiency / Water users' associations / Water rights / Water allocation / Water supply / Water distribution

Human resource practices and performance in small Spanish wineries, and their evolution with age and size

This research aims to cover the existing gap in knowledge regarding human resource management practices in winery businesses. Three of the most important practices in this field - recruitment and selection, training and development, and remuneration - and their relationship with performance in small family and non-family wineries as well as the differences in those businesses' behaviours according to their age and size were analysed. The analysis was based on a 2016 database containing 339 Spanish wine sector SMEs, and a multivariate Bayesian regression methodology was applied. The results demonstrate a lower level of human resource management practices in small family businesses and a stronger relationship with performance than in non-family businesses. The results also show that human resource management varies according to the age and size of the company, indicating an inverted U-shaped relationship with size. On the one hand, these results highlight the importance of human resource practices in the environment of a small winery. These practices have not usually been considered as drivers of performance in small family firms. On the other hand, the results can be useful for the managers of such firms, both in the wine industry and in general, as they highlight the human resource practices that could improve the performance of those entities. The paper contributes to filling the existing gap in the literature related to small family businesses. Esta pesquisa visa cobrir a lacuna existente no conhecimento sobre práticas de gestão de recursos humanos em empresas vinícolas. Foram analisadas três das práticas mais importantes neste campo - recrutamento e seleção, treino e desenvolvimento, e remuneração - e sua relação com o desempenho em pequenas adegas, familiares e não familiares, bem como as diferenças no comportamento dessas empresas de acordo com a sua idade e a sua dimensão. A análise foi baseada num banco de dados de 2016 contendo 339 PME do setor vinícola espanhol, tendo sido aplicada a metodologia de regressão bayesiana multivariada. Os resultados demonstram um nível mais baixo de práticas de gestão de recursos humanos em pequenas empresas familiares e uma relação mais forte com o desempenho do que em empresas não familiares. Relatam também que a gestão de recursos humanos varia de acordo com a idade e a dimensão da empresa, encontrando uma relação em U invertido com a dimensão. Por um lado, estes resultados destacam a importância das práticas de recursos humanos no ambiente de uma pequena adega. Estas práticas não têm sido geralmente consideradas como motores de desempenho em pequenas empresas familiares. Por outro lado, os resultados podem ser úteis para os gerentes de tais empresas, tanto na indústria do vinho como na indústria em geral, pois destacam as práticas de recursos humanos que podem melhorar o desempenho dessas entidades. O artigo contribui para preencher a lacuna existente na literatura relativamente às pequenas empresas familiares

The competitive advantage in business, capabilities and strategy. What general performance factors are found in the Spanish wine industry?

The wine sector in Europe has undergone a major change of trend in recent years, especially in Spain. On the one hand, the surface area has been reduced, but the production has been maintained by restructurings and improvements made in exploitation techniques. On the other hand, consumption has diminished causing a significant increase in competition. The Spanish wine sector is formed mainly by small and medium-sized firm, which is representative of the size of existing companies in Europe. This article aims to analyze the relationships between the competitive strategy, resources and capabilities of the firms, analyzing their technological and managerial capabilities, with business performance. 339 companies of the wine sector in Spain have been studied, differentiating between individual firms, cooperatives and mercantile companies. The results reveal that resources and capabilities along with strategies define competitive advantage, but their relationship and importance is different for each type of company

¿Es posible llevar al aula los resultados de una investigación?

En este trabajo se presentan resultados de una investigación realizada sobre ideas previas de alumnos de licenciatura, relacionadas con el enlace químico. Estos resultados condujeron a la elaboración de un libro para docentes de bachillerato y licenciatura, que recoge los resultados de la investigación y aporta fundamentos teóricos y propuestas para promover el cambio conceptual, en el tema referido. Se describen algunas de las aportaciones más innovadoras, contenidas en el libro, para mejorar el aprendizaje del tema en bachillerato y licenciatura

Reliable prediction of difficult airway for tracheal intubation from patient preoperative photographs by machine learning methods

Background: Estimating the risk of a difficult tracheal intubation should help clinicians in better anaesthesia planning, to maximize patient safety. Routine bedside screenings suffer from low sensitivity. Objective: To develop and evaluate machine learning (ML) and deep learning (DL) algorithms for the reliable prediction of intubation risk, using information about airway morphology. Methods: Observational, prospective cohort study enrolling $n$=623 patients who underwent tracheal intubation: 53/623 difficult cases (prevalence 8.51%). First, we used our previously validated deep convolutional neural network (DCNN) to extract 2D image coordinates for 27 + 13 relevant anatomical landmarks in two preoperative photos (frontal and lateral views). Here we propose a method to determine the 3D pose of the camera with respect to the patient and to obtain the 3D world coordinates of these landmarks. Then we compute a novel set of $d_M$=59 morphological features (distances, areas, angles and ratios), engineered with our anaesthesiologists to characterize each individual's airway anatomy towards prediction. Subsequently, here we propose four ad hoc ML pipelines for difficult intubation prognosis, each with four stages: feature scaling, imputation, resampling for imbalanced learning, and binary classification (Logistic Regression, Support Vector Machines, Random Forests and eXtreme Gradient Boosting). These compound ML pipelines were fed with the $d_M$=59 morphological features, alongside $d_D$=7 demographic variables. Here we trained them with automatic hyperparameter tuning (Bayesian search) and probability calibration (Platt scaling). In addition, we developed an ad hoc multi-input DCNN to estimate the intubation risk directly from each pair of photographs, i.e. without any intermediate morphological description. Performance was evaluated using optimal Bayesian decision theory. It was compared against experts' judgement and against state-of-the-art methods (three clinical formulae, four ML, four DL models). Results: Our four ad hoc ML pipelines with engineered morphological features achieved similar discrimination capabilities: median AUCs between 0.746 and 0.766. They significantly outperformed both expert judgement and all state-of-the-art methods (highest AUC at 0.716). Conversely, our multi-input DCNN yielded low performance due to overfitting. This same behaviour occurred for the state-of-the-art DL algorithms. Overall, the best method was our XGB pipeline, with the fewest false negatives at the optimal Bayesian decision threshold. Conclusions: We proposed and validated ML models to assist clinicians in anaesthesia planning, providing a reliable calibrated estimate of airway intubation risk, which outperformed expert assessments and state-of-the-art methods. Our novel set of engineered features succeeded in providing informative descriptions for prognosis

Development of machine learning system for airway prediction from facial image with mobile device

Goals: A reliable prognostic tool for a difficult airway (DA) may enhance patients’ safety during orotracheal intubation by decreasing unanticipated DAs. We aim to examine the applicability of an Artificial Intelligence-Deep Learning (AI-DL) algorithm to measure airway’s anatomy, and to predict DA based on published models. Materials and methods: Observational prospective cohort study with n=503 patients recruited at Galdakao-Usansolo and Basurto University Hospitals (Biscay, Spain) between 2018 and 2020. Two pre-operative photos for each patient were collected: a frontal view, in which patients were instructed to open their mouth completely; and a lateral view, with head in vertical ex tension. Smartphones with general-purpose cameras were used, and a cue card was added to the scene as reference. Patients’ medical records were logged. After intubation, HAN score and IDS-ASA criteria for intubation difficulty [1] were collected. Our anaesthesiology team defined a set of relevant orofacial landmarks, whereas our data-science team developed an AI-DL algorithm, trained to identify locate them automatically within the images. In a previous evaluation, the system achieved an accuracy comparable to the consensus of two human annotators [2]. Landmark positions output by the AI-DL method were subsequently used by the system to ex tract two anatomical measurements: thyromental distance and interincisor gap. Finally, these two were integrated into a published model for DA prognosis: Naguib et al. 2006 [3], which also employed patients’ height and Mallampati score. Results and discussion: The estimated incidence of DA was 6.36% (32 out of 503 patients) according to the IDS-ASA criteria. Naguib’s model, when used in combination with our automatic AI-DL based measurements, achieved 53.12% sensitivity and 79.83% specificity; compared to clinicians’ subjective assessment, who obtained 25.00% sensitivity and 93.63% specificity. Conclusion(s): In this work, we evaluated an AI-DL method to predict DA for intubation, with two pre-operative photos and Naguib’s model. Our results complemented expert judgements’ predictive ability in terms of sensitivity, substantially lowering false negatives; at the expense of a restrained loss in specificity (false positives). Thus, our proposal may provide anaesthesiologists with an automatic, objective and accessible decision support tool for the prognosis of DAs

Espondilitis tuberculosa no es una metástasis vertebral: diagnóstico diferencial y tratamiento quirúrgico. A propósito de un caso

Presentamos el caso de una paciente con dorsalgia y clínica neurológica de varios meses de evolución que ante las pruebas de imagen fue erróneamente diagnosticada de metástasis vertebral sin confirmación previa con biopsia. El deterioro progresivo neurológico y las nuevas pruebas de imagen confirmaron el diagnóstico de tuberculosis vertebral. La paciente fue tratada mediante curetaje, desbridamiento, fusión intersomática y osteosíntesis anterior además del tratamiento médico. Hubo una recuperación neurológica de la función sensitiva, motora y esfinteriana prácticamente completa al mes de la intervención. Tras 20 meses de evolución la paciente está asintomática sin evidencia de progresión de la enfermedadWe report a patient with back pain and neurological symptoms several months of evolution to the test image was wrongly diagnosed with spinal metastases without prior confirmation with biopsy. The progressive deterioration of neurological and new imaging confirmed the diagnosis of spinal tuberculosis. The patient was treated by curettage, debridement, anterior interbody fusion and internal fixation in addition to medical treatment. There neurological recovery of sensory function, motor and sphincter almost complete month after the intervention. After 20 months of evolution, the patient is asymptomatic without evidence of disease progressio

Association between olfactory dysfunction and mood disturbances with objective and subjective cognitive deficits in long-COVID

Background and purposeThe coronavirus disease 2019 (COVID-19) has been associated with olfactory dysfunction. The persistent symptoms of anosmia or hyposmia were associated in previous studies with the development of memory impairment and mood disturbances. We aimed to investigate the association between the chronicity of reported olfactory dysfunction and subjective and objective cognitive performance in long-COVID patients and to explore whether their emotional symptoms are related to their cognition.MethodsOne hundred twenty-eight long-COVID participants were recruited. Reported symptomatology, subjective memory complaints, anxiety and depression symptomatology, and trait-anxiety were assessed. Subjective memory complaints and mood disturbances were compared among groups of participants with olfactory dysfunction as an acute (AOD), persistent (POD), or nonexistent (NOD) symptom. Seventy-six of the volunteers also participated in a face-to-face session to assess their objective performance on tests of general cognitive function and verbal declarative memory. Objective cognitive performance and mood disturbances were compared among the AOD, POD, and NOD groups.ResultsThe subjective memory complaints and the anxiety and depression symptoms were similar among the groups, but the score in general cognitive function was lower in the participants with symptoms of acute olfactory dysfunction than in those with no olfactory symptoms at any time. Participants’ memory complaints were positively related to their emotional symptoms. The relationship between depressive symptomatology and memory complaints interacted with the olfactory dysfunction, as it only occurred in the participants without symptoms of olfactory dysfunction. Depressive symptomatology and acute olfactory symptoms were negatively associated with general cognitive function and delayed memory performance. The months elapsed from diagnosis to assessment also predicted delayed memory performance. Anxious symptomatology was negatively associated with the immediate ability to recall verbal information in participants who did not present olfactory dysfunction in the acute phase of the infection.ConclusionOlfactory dysfunction in the acute phase of the infection by COVID-19 is related to cognitive deficits in objective tests, and mood disturbances are associated with self-reported and objective memory. These findings may contribute to further understanding the neuropsychological and emotional aspects of long-COVID

First report of neocosmospora falciformis Causing Wilt and Root Rot of Muskmelon in Spain

‘Cantaloupe’ and ‘Piel de Sapo’ are melon (Cucumis melo L.) varieties cultivated in Spain. In 2018, during a pathogens survey in experimental fields of Valencia and Alicante provinces (southeast Spain), wilt and root rot of melon plants were detected in grafted and ungrafted plants. Disease incidence ranged from 10% (Alicante) to 45% (Valencia). Symptoms included yellowing and wilting of leaves, rotting at the stem base and upper root, and collapse of the entire plant. Samplings were conducted from severely decayed and dead plants. Fragments (0.5 to 1 cm) from rotted lower stems and roots were surface disinfected for 1 min in 1.5% NaOCl, washed twice with sterilized distilled water, and plated onto potato dextrose agar (PDA) with streptomycin sulfate (0.5 g/liter). Plates were incubated at 25°C in the dark for 3 to 5 days. Mycelia resembling Fusarium were isolated and characterized by morphological and molecular methods. Based on their adpressed beige mycelia, growth in concentric rings, and absence of sporodochia, colonies growing on PDA and Spezieller Nährstoffarmer agar were preliminary identified as belonging to the Fusarium solani species complex. On PDA, colonies were white-greyish to pale-cream growing in concentric rings with beige reverse after 6 days. No sporodochia were observed. Macroconidia were slender, falcate, hyaline, ..