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Background: Previous studies have shown that catastrophizing and avoiding pain increase suffering and disability of patients with fibromyalgia (FM). Acceptance and Commitment Therapy (ACT) has demonstrated good results in the treatment of chronic pain. Method: This study applies a group ACT therapy for women with fibromyalgia, focusing on therapeutic components, such as acceptance, defusion, and personal values. An experimental design with control group was used; 57 women diagnosed with FM participated in this study (25 in the ACT group and 32 in the control group). The ACT group received five intervention sessions. Psychological symptoms, perceived health, mindfulness, catastrophic thinking, and cognitive fusion were evaluated at pre- and post-treatment and at six-month follow-up. Results: The results showed that the ACT group had significantly better results in mental health, social role and functioning, anxiety, depression, somatization, and obsession-compulsion, less catastrophic thinking, and improved capacity for mindfulness at six-month follow-up. Conclusions: The results are discussed in the light of previous interventions.

Abstract Background Developmental dyslexia is characterized by reading and writing deficits that persist into adulthood. Dyslexia is strongly associated with academic underachievement, as well as impulsive, compulsive, and criminal behaviors. The aims of this study were to investigate impulsive or compulsive reading comprehension, analyzing the differences in reading errors between two distinct groups —one with Antisocial Personality Disorder (ASPD) and another with Obsessive–Compulsive Personality Disorder (OCPD) and examine their correlation with criminal behavior within a prison population. Methods We gathered data from 194 participants: 81 with ASPD and 113 with OCPD from a prison center. Participants took part in interviews to gather data on demographic, criminal, and behavioral data. Additionally, the participants underwent various assessments, including the International Examination for Personality Disorders; Symptom Inventory, and Battery for the Assessment of Reading Processes in Secondary and High School – Revised. Results Our analysis revealed differences in reading skills between the ASPD and OCPD groups. Specifically, the OCPD group showed poorer performance on lexical selection, semantic categorization, grammar structures, grammatical judgements, and expository comprehension when compared with the ASPD group. Conversely, the OCPD group obtained higher scores on narrative comprehension relative to the ASPD group. Conclusions The OCPD group showed slow lexical-phonological coding and phonological activation.

Background/Objectives: In a previous study, we described elevated anti-Anisakis IgG levels in septic patients in relation to disease severity. In this study, our objective was to analyze the evolution of anti-Anisakis immunoglobulins in septic patients during hospital admission and their association with αβ and γδ T cell subsets. Methods: We recruited 80 subjects: 40 patients with sepsis and 40 controls. αβ and γδ T cells were analyzed using flow cytometry. Apoptosis was also assessed, and anti-Anisakis antibodies were measured by ELISA in the sera of patients with sepsis and controls. Results: In the second analysis (7–10 after sepsis evolution), an increase in all specific antibody isotypes was identified in individuals with septic shock, except IgE. The levels of anti-Anisakis IgG and IgA were higher in the subjects with sepsis in the first analysis and continued to increase in the second analysis compared with the healthy control subjects. There was an increase in anti-Anisakis IgG and IgA levels in surviving patients and an increase in IgA levels in non-surviving patients. A rise in specific IgG and IgE levels was noted in the second analysis of patients with sepsis with αβ CD3+ T cell deficiency. Patients without γδ T cell deficiency had increased anti-Anisakis IgA levels 7–10 days after admission. Conclusions: Our results suggest a previous infection by Anisakis that could be involved in the subsequent septic process and be related to patients who have negative cultures in which the pathogen causing sepsis has not been identified.

Hedgerow cultivation systems have revolutionized olive growing in recent years because of the mechanization of harvesting. Initially applied under irrigated conditions, its use has now extended to rainfed cultivation. However, there is limited information on the behavior of olive cultivars in hedgerow growing systems under rainfed conditions, which is a crucial issue in the context of climate change. To fill this knowledge gap, a rainfed cultivar trial was planted in 2020 in Southern Spain to compare ‘Arbequina’, ‘Arbosana’, ‘Koroneiki’, and ‘Sikitita’, under such growing conditions. One of the most important traits in low-water environments is the canopy growth. Because traditional canopy measurements are costly in terms of time and effort, the use of light detection and ranging (LiDAR) sensor onboard an uncrewed aerial vehicle (UAV) was tested. Statistical analyses of data collected in November 2022 and January 2023 revealed high correlations between UAV-LiDAR metrics and field measurements for height, projected area, and crown volume, based on validation with measurements from 36 trees. These results provide a solid basis for future research and practical applications in rainfed olive growing, while highlighting the potential of UAV-LiDAR technology to characterize tree canopy structure efficiently.

Background: Adolescents who identify as sexual minorities often face social stigmatisation, which can lead to increased adversity and a higher risk of suicidal behaviours. However, there are also protective factors that may promote resilience to these risk behaviours. This study aims to identify factors that predict resilience in sexual minority adolescents with high suicidal vulnerability. Methods: The study sample comprised 78 self-reported LGBTIQ+ adolescents aged between 13 and 18 years old (M = 16.11, SD = 1.56) who had previously attempted suicide. They completed several psychosocial instruments to measure risk and protective variables related to suicidal vulnerability. Results: Entrapment was found to be the most predictive risk variable for suicide attempts. However, protective variables promoting resilience were also found, such as adequate parental communication, life satisfaction, and cognitive reframing. Discussion: The findings related to prevention of suicide attempts are discussed and we highlight the urgent need to enhance certain internal and contextual protective factors to promote resilience in the face of suicidal vulnerability in certain clinical subpopulations exposed to highly adverse situations.

Background: The COVID-19 pandemic is the biggest global health problem in the last hundred years. The efficacy of the vaccine to protect against severe disease is estimated to be 70–95% according to the studies carried out, although there are aspects of the immune response to the vaccine that remain unclear. Methods: Humoral and cellular immunity after the administration of three doses of the Pfizer–BioNTech and Oxford AstraZeneca vaccines against SARS-CoV-2 over one year and the appearance of post-vaccination COVID-19 were studied. SARS-CoV-2 IgG and IgA antibodies, αβ and γδ T-cell subsets, and their differentiation stages and apoptosis were analyzed. Results: Anti-SARS-CoV-2 IgG and IgA antibodies showed a progressive increase throughout the duration of the study. This increase was the greatest after the third dose. The highest levels were observed in subjects who had anti-SARS-CoV-2 antibodies prior to vaccination. There was an increase in CD4+ αβ, CD8+ γδ and TEM CD8+ γδ T cells, and a decrease in apoptosis in CD4+ CD8+ and CD56+ αβ and γδ T cells. Post-vaccination SARS-CoV-2 infection was greater than 60%. The symptoms of COVID-19 were very mild and were related to a γδ T cell deficit, specifically CD8+ TEMRA and CD56+ γδ TEM, as well as lower pre-vaccine apoptosis levels. Conclusions: The results unveil the important role of γδ T cells in SARS-CoV-2-vaccine-mediated protection from the disease.

Background In psychopathologies characterized by compulsive decision-making, core impairments include cognitive inflexibility and excessive sensitivity to rewards. It has been posited that traits shared by nonclinical individuals and psychiatric patients could help explain the pathogenesis of compulsive decision-making. Methods To investigate whether cognitive inflexibility predisposes nonclinical individuals to poor choices and hyper-reactivity to reward, we recruited people with high and low scores for cognitive persistence and used the Iowa Gambling Task to assess decision-making and cardiac reactivity to monetary gains/losses. Results As is frequently observed in psychophysiological research, the data indicated discrepancies among self-reports, behavior, and physiology. Cognitive inflexibility was not related to worse performance; however, monetary gains, in line with the literature, prompted marked cardiac accelerations. Consistent with our research goal, only inflexible participants showed large cardiac accelerations during the largest monetary wins. Discussion Taken together, the data confirm an association between cognitive persistence and physiological reward sensitivity in a nonclinical population. The findings are in line with recent theories on the development of compulsive behaviors that consider cognitive inflexibility as a transdiagnostic impairment and predisposing factor for excessive reactivity to rewards, and might act both as a preexisting individual trait and drug-induced deficit.

Abstract Malnutrition is frequent in hemodialysis (HD) patients. Nutritional deficiencies may negatively impact quality of life (QOL). This study examines the utility of the Malnutrition-Inflammation Score (MIS) in detecting nutritional risk (NR) and assesses the correlation between nutritional status and QOL in dialysis patients upon starting a nutritional intervention program (NIP). One hundred and twenty patients were included in this cross-sectional study. The MIS was used to detect NR and the Kidney Disease Quality of Life (KDQOL-SF) instrument version 1.2 was used to assess QOL. 62% of patients were found to be at NR (MIS > 5). Nutritional status was significantly correlated with all generic QOL sub-scales. On a multiple linear regression analysis, malnutrition showed the highest level of explanation in the Kidney Disease Summary Component which explained 28.9% of the variance; the Physical Component Summary which explained 33% of the variance; and the Mental Component Summary which explained 21.5% of the variance. Malnutrition was found to be the most significant predictor of impaired scores on the KDQOL-SF. The use of MIS to identify patients at NR and a nutritional assessment to detect malnutrition in its early stages are important given the effects a NIP can have on improving QOL in HD patients.

Musculoskeletal disorders (MSD) are a frequent reason for consultation and the main cause of disability in population. Electromyographic biofeedback or myofeedback (MF) is a promising treatment in rehabilitation, although studies supporting its benefits in MSD have declined in recent years. The objective of this review was to describe the efficacy of MF in function recovery, strength increase and muscle relaxation in MSD. Randomized clinical trials (RCTs) were identified in Pubmed, Scopus, Web of Science, Cinahl and Science Direct databases dated September 2, 2021. Four independent researchers reviewed articles titles and abstracts to determine their eligibility. Risk of bias and articles quality was assessed using Rob2 tool (Cochrane) and PEDro scale. Functionality improvement, strength increase, and muscle relaxation were considered as main outcome. Search strategy yielded 160 articles after eliminating duplicates, reducing to 26 when selection criteria were applied. Articles were classified in strengthening (n=16) and muscle relaxation (n=10) according to MF therapeutic aim. Eighteen articles were rated as low risk of bias (69.22%) and an average internal validity of 6 points was obtained. Studies show improvements in functionality, strength increase and pain reduction with statistical significance when MF were complemented with therapeutic exercises or other physical agents modalities (p

ABSTRACT OBJECTIVE To expose visibility of the health concerns of sexual and gender minority groups in Chile, as well as to provide a platform to advocate for policies that support the health and well-being of sexual and gender minority people in the country. METHODS The health conditions and risk factors of participants identified as sexual and gender minority were compared to those identified as cisgender heterosexual using data from the 2016-2017 National Health Survey. RESULTS Despite reporting higher self-rated health than heterosexual men, gay men had a higher risk of lifetime diagnosis of sexually transmitted infections. Compared to heterosexual women, the prevalence of depression was higher among bisexual women, who were also less likely to have been tested for HIV. Moreover, transgender participants were more likely to report depression and worse self-rated health than cisgender heterosexual participants. CONCLUSION Small sample sizes of sexual and gender minority subgroups might have obscured some differences that would have been observable in larger samples. Despite this, we found statistically significant sexual and/or gender identity differences in several health areas, especially mental, sexual, and overall health.

The ethical imperative voiced by colleagues from the Universidad Católica de Chile stresses the urgency of providing universal access to healthcare services on a global scale because health is a social good and a social right. On the one hand, health systems should promote innovations because they will contribute to greater sustainability and foster the sharing of health benefits to the different communities in the world. On the other hand, in healthcare practice, it is necessary to create more inclusive models of care that reach out to larger sectors of the population. Finally, interdisciplinary work is necessary to provide comprehensive care, considering the social determinants of health in the diverse social contexts where people live.

Abstract Background Almond is an emerging crop due to the health benefits of almond consumption including nutritional, anti-inflammatory, and hypocholesterolaemia properties. Traditional almond producers were concentrated in California, Australia, and Mediterranean countries. However, almond is currently present in more than 50 countries due to breeding programs have modernized almond orchards by developing new varieties with improved traits related to late flowering (to reduce the risk of damage caused by late frosts) and tree architecture. Almond tree architecture and flowering are acquired and evaluated through intensive field labour for breeders. Flowering detection has traditionally been a very challenging objective. To our knowledge, there is no published information about monitoring of the tree flowering dynamics of a crop at the field scale by using color information from photogrammetric 3D point clouds and OBIA. As an alternative, a procedure based on the generation of colored photogrammetric point clouds using a low cost (RGB) camera on-board an unmanned aerial vehicle (UAV), and an semi-automatic object based image analysis (OBIA) algorithm was created for monitoring the flower density and flowering period of every almond tree in the framework of two almond phenotypic trials with different planting dates. Results Our method was useful for detecting the phenotypic variability of every almond variety by mapping and quantifying every tree height and volume as well as the flowering dynamics and flower density. There was a high level of agreement among the tree height, flower density, and blooming calendar derived from our procedure on both fields with the ones created from on-ground measured data. Some of the almond varieties showed a significant linear fit between its crown volume and their yield. Conclusions Our findings could help breeders and researchers to reduce the gap between phenomics and genomics by generating accurate almond tree information in an efficient, non-destructive, and inexpensive way. The method described is also useful for data mining to select the most promising accessions, making it possible to assess specific multi-criteria ranking varieties, which are one of the main tools for breeders.

Research has found links between academic failure and criminal offending and suggest that many incarcerated young people have experienced significant behavioral and learning problems in school, which could result in criminal outcomes and poor academic performance. The objective of this study was to analyse writing disorders in impulsive and compulsive prisoners. The sample was composed of 194 male prisoners, of which 81 had been diagnosed with Antisocial Personality Disorder and 113 with Obsessive Compulsive Personality Disorder. Male participants were recruited at the Granada Prison Center. They completed the Demographic, Crime, and Institutional Behavior Interview; the International Personality Disorder Examination (IPDE); The Symptom Checklist (SCL-90-R) and Assessment Battery of Writing Processes (PROESC in its Spanish acronym). We found that prisoners with writing disorders generally have difficulties in the skills necessary to write properly due to impulsive and compulsive behavior.

There is increasing evidence that executive functions have significative effects on nicotine abuse. An unresolved challenge for smoking cessation interventions is the detection of factors associated with nicotine use. In order to understand how cognition is affected by nicotine abuse, this study was designed to determine the relationship between years of smoking addiction and several variables of executive functions. The sample was composed of 174 smokers, whose age ranged between 27 and 69 years old (M = 47.44; SD = 8.48). Smokers were assessed at baseline with measures of cognitive inhibition [Go/No Go Task and Five Digit Test (FDT)], updating [Visual Search and Attention Test (VSAT) and Letter-Number Sequencing (WAIS IV)] and shifting [Delay Discounting Task (DDT) and Iowa Gambling Task (IGT)] while the outcome measure was years of smoking. The linear regression and correlation analysis highlighting that the variable which has the strongest association with years of smoking is updating. Multivariate analysis of variance (MANCOVA) followed by Tukey post-hoc tests revealed significant differences such that heavy smoking indicated worse performance than light smoking on updating tasks. These findings report the ability of working memory to predict years of smoking and suggest that cigarette packaging warning may experience a loss of effectiveness in heavy smokers.

Co-occurrence of drug misuse with other dysregulated behaviors is common. This study was aimed at exploring the associations between the risk of presenting a clinically relevant condition involving non-substance-related addictive or dysregulated behaviors (as measured by the MultiCAGE CAD-4 screening), and cannabis abuse/dependence (CAST/SDS) scores, and the role of gender therein. Participants were recruited using stratified probabilistic sampling at the University of Granada. Mann-Whitney’s U tests were used to compare male and female students in SDS and CAST scores. Associations between gender and MultiCAGE scores were estimated using the γ ordinal correlation index, and tested with χ2. For each MultiCAGE dimension, a Poisson-family mixed-effects model was built with either SDS or CAST as the main input variable, while controlling for nicotine and alcohol dependence, and relevant sociodemographic variables. Incidence rate ratios (IRR) were computed for SDS/CAST effects, and the significance threshold was family-wise Bonferroni-corrected. Gender differences were significant for cannabis dependence/abuse and all MultiCAGE scores for non-substance-related conditions, with males showing higher risk scores for excessive gambling, excessive internet use, excessive video gaming, and hypersexuality, and females presenting higher scores in dysregulated eating and compulsive buying. Cannabis dependence and abuse were significantly associated with a higher risk of problematic video gaming. These associations were mostly driven by males. Importantly, although risk of problematic video gaming was specifically associated with cannabis abuse/dependence, there was only a weak non-significant association between problematic video gaming and alcohol use scores. Risk of alcohol use problems, in turn, was strongly associated with all other non-substance-related problems (problematic gambling, excessive Internet use, dysregulated eating, compulsive buying, and hypersexuality). These differential associations can cast light on the etiological similarities and dissimilarities between problematic substance use and putative addictive behaviors not involving drugs.

Information such as the prevalence and frequency of criminal behaviour is difficult to estimate using standard survey techniques because of the tendency of respondents to withhold or misrepresent information. Social desirability bias is a significant threat to the validity of self-reported data, especially when supplied by persons such as sexual offenders or those convicted of theft or substance abuse. The randomized response approach is an alternative to the standard interview method and offers great potential for researchers in the field of criminal justice. By means of a survey of 792 prison inmates, incorporating both indirect and direct response techniques, we investigate if the prison population also has problems recognizing their participation in criminal acts such as theft, illicit drug use, violence against property, reckless driving and arson. Our research findings suggest that self-reported criminal behaviour among a prison population is affected by social desirability bias and that the behaviour considered is significantly associated with the severity of obsessive-compulsive symptoms. The results also demonstrate the inadequacy of traditional, yet widely used, direct questioning methods, and the great potential for indirect questioning techniques to advance policy formation and evaluation in the field of criminal behaviour.

Abstract Background Most people who make the transition to renal replacement therapy (RRT) are treated with a fixed dose thrice-weekly hemodialysis réegimen, without considering their residual kidney function (RKF). Recent papers inform us that incremental hemodialysis is associated with preservation of RKF, whenever compared with conventional hemodialysis. The objective of the present controlled randomized trial (RCT) is to determine if start HD with one sessions per week (1-Wk/HD), it is associated with better patient survival and other safety parameters. Methods/design IHDIP is a multicenter RCT experimental open trial. It is randomized in a 1:1 ratio and controlled through usual clinical practice, with a low intervention level and non-commercial. It includes 152 incident patients older than 18 years, with a RRF of ≥4 ml/min/1.73 m2, measured by renal clearance of urea (KrU). The intervention group includes 76 patients who will start with incremental HD (1-Wk/HD). The control group includes 76 patients who will start with thrice-weekly hemodialysis régimen. The primary outcome is assessing the survival rate, while the secondary outcomes are the morbidity rate, the clinical parameters, the quality of life and the efficiency. Discussion This study will enable to know the number of sessions a patient should receive when starting HD, depending on his RRF. The potentially important clinical and financial implications of incremental hemodialysis warrant this RCT. Trial registration U.S. National Institutes of Health, ClinicalTrials.gov. Number: NCT03239808, completed 13/04/2017. Sponsor: Foundation for Training and Research of Health Professionals of Extremadura.

Introduction: Progressive haemodialysis (HD) is a starting regime for renal replacement therapy (RRT) adapted to each patient's necessities. It is mainly conditioned by the residual renal function (RRF). The frequency of sessions with which patients start HD (one or two sessions per week), is lower than that for conventional HD (three times per week). Such frequency is increased (from one to two sessions, and from two to three sessions) as the RRF declines. Methodology/Design: IHDIP is a multicentre randomized experimental open trial. It is randomized in a 1:1 ratio and controlled through usual clinical practice, with a low intervention level and non-commercial. It includes 152 patients older than 18 years with chronic renal disease stage 5 and start HD as RRT, with an RRF of ≥4 ml/min/1.73 m2, measured by renal clearance of urea (KrU). The intervention group includes 76 patients who will start with one session of HD per week (progressive HD). The control group includes 76 patients who will start with three sessions per week (conventional HD). The primary purpose is assessing the survival rate, while the secondary purposes are the morbidity rate (hospital admissions), the clinical parameters, the quality of life and the efficiency. Discussion: This study will enable us to know, with the highest level of scientific evidence, the number of sessions a patient should receive when starting the HD treatment, depending on his/her RRF. Trial registration: Registered at the U.S. National Institutes of Health, ClinicalTrials.gov under the number NCT03239808. Resumen: Introducción: La hemodiálisis (HD) progresiva es una modalidad de inicio del tratamiento renal sustitutivo adaptada a las necesidades individuales de cada paciente. Está condicionada fundamentalmente por la función renal residual (FRR). En ella, la frecuencia de sesiones con las que el paciente inicia HD (una o 2 sesiones por semana) es menor que en la HD convencional (3 por semana). Dicha frecuencia aumenta (de una a 2, y de 2 a 3) con el declinar de la FRR. Metodología/diseño: DiPPI es un estudio abierto, multicéntrico, experimental, aleatorizado 1:1 y controlado con procedimiento de práctica clínica habitual, de bajo nivel de intervención y no comercial. Incluye 152 pacientes mayores de 18 años, con enfermedad renal crónica estadio 5, que inician HD como tratamiento renal sustitutivo; y la FRR, medida por aclaramiento renal de urea (KrU) es ≥4 ml/min/1,73 m2. El estudio se basa en un grupo de intervención con 76 pacientes que iniciarán HD con una sola sesión por semana (modalidad progresiva) y un grupo control con 76 pacientes que comenzarán con 3 sesiones por semana. El objetivo primario es evaluar la supervivencia y los objetivos secundarios son la morbilidad (hospitalizaciones), los parámetros clínicos habituales, la calidad de vida y la eficiencia. Discusión: Este estudio permitirá conocer, con la máxima evidencia científica, cuántas sesiones debe recibir un paciente al inicio del tratamiento con HD, dependiendo de su FRR. Registro: Registrado en U.S. National Institutes of Health, ClinicalTrials.gov con número NCT03239808. Keywords: Chronic renal failure, Incremental haemodialysis, Progressive haemodialysis, Randomized clinical trial, Palabras clave: Insuficiencia renal crónica, Hemodiálisis incremental, Hemodiálisis progresiva, Estudio aleatorizado controlado

Resumen: Introducción: La hemodiálisis (HD) progresiva es una modalidad de inicio del tratamiento renal sustitutivo adaptada a las necesidades individuales de cada paciente. Está condicionada fundamentalmente por la función renal residual (FRR). En ella, la frecuencia de sesiones con las que el paciente inicia HD (una o 2 sesiones por semana) es menor que en la HD convencional (3 por semana). Dicha frecuencia aumenta (de una a 2, y de 2 a 3) con el declinar de la FRR. Metodología/diseño: DiPPI es un estudio abierto, multicéntrico, experimental, aleatorizado 1:1 y controlado con procedimiento de práctica clínica habitual, de bajo nivel de intervención y no comercial. Incluye 152 pacientes mayores de 18 años, con enfermedad renal crónica estadio 5, que inician HD como tratamiento renal sustitutivo; y la FRR, medida por aclaramiento renal de urea (KrU) es ≥ 4 ml/min/1,73 m2. El estudio se basa en un grupo de intervención con 76 pacientes que iniciarán HD con una sola sesión por semana (modalidad progresiva) y un grupo control con 76 pacientes que comenzarán con 3 sesiones por semana. El objetivo primario es evaluar la supervivencia y los objetivos secundarios son la morbilidad (hospitalizaciones), los parámetros clínicos habituales, la calidad de vida y la eficiencia. Discusión: Este estudio permitirá conocer, con la máxima evidencia científica, cuántas sesiones debe recibir un paciente al inicio del tratamiento con HD, dependiendo de su FRR. Registro: Registrado en U.S. National Institutes of Health, ClinicalTrials.gov con número NCT03239808. Abstract: Introduction: Progressive haemodialysis (HD) is a starting regime for renal replacement therapy (RRT) adapted to each patient's necessities. It is mainly conditioned by the residual renal function (RRF). The frequency of sessions with which patients start HD (one or two sessions per week), is lower than that for conventional HD (three times per week). Such frequency is increased (from one to two sessions, and from two to three sessions) as the RRF declines. Methodology/Design: IHDIP is a multicentre randomised experimental open trial. It is randomised in a 1:1 ratio and controlled through usual clinical practice, with a low intervention level and non-commercial. It includes 152 patients older than 18 years with chronic renal disease stage 5 and start HD as RRT, with an RRF of ≥ 4 ml/min/1.73 m2, measured by renal clearance of urea (KrU). The intervention group includes 76 patients who will start with one session of HD per week (progressive HD). The control group includes 76 patients who will start with three sessions per week (conventional HD). The primary purpose is assessing the survival rate, while the secondary purposes are the morbidity rate (hospital admissions), the clinical parameters, the quality of life and the efficiency. Discussion: This study will enable us to know, with the highest level of scientific evidence, the number of sessions a patient should receive when starting the HD treatment, depending on his/her RRF. Trial registration: Registered at the U.S. National Institutes of Health, ClinicalTrials.gov under the number NCT03239808. Palabras clave: Insuficiencia renal crónica, Hemodiálisis incremental, Hemodiálisis progresiva, Estudio aleatorizado controlado, Keywords: Chronic renal failure, Incremental haemodialysis, Progressive haemodialysis, Randomized clinical trial

Poplar is considered one of the forest crops with greatest potential for lignocellulose production, so rapid and non-destructive measurements of tree growth (in terms of height and biomass) is essential to estimate productivity of poplar plantations. As an alternative to tedious and costly manual sampling of poplar trees, this study evaluated the ability of UAV technology to monitor a one-year-old poplar plantation (with trees 4.3 meters high, on average), and specifically, to assess tree height and estimate dry biomass from spectral information (based on the Normalized Difference Vegetation Index, NDVI) and Digital Surface Models (DSM). We used an UAV flying at 100 m altitude over an experimental poplar plantation of 95 × 60 m2 (3350 trees approx.), and collected remote sensing images with a conventional visible-light camera for the generation of the DSM and a multi-spectral camera for the calculation of NDVI. Prior to the DSM generation, several adjustments of image enhancement were tested, which improved DSM accuracy by 19–21%. Next, UAV-based data (i.e., tree height, NDVI, and the result of fusing these variables) were evaluated with a validation set of 48 tree-rows by applying correlation and linear regression analysis. Correlation between actual and DSM-based tree heights was acceptable (R2 = 0.599 and RMSE = 0.21 cm), although DSM did not detect the narrow apexes in the top of the poplar trees (1 m length, on average), which led to notable underestimates. Linear regression equations for tree dry biomass showed the highest correlation with NDVI × Tree-height (R2 = 0.540 and RMSE = 0.23 kg/m2) and the lowest correlation with NDVI (R2 = 0.247 and RMSE = 0.29 kg/m2). The best results were used to determine the distribution of the trees according to their dry biomass, providing information about potential productivity of the entire poplar plantation by applying a fast and non-destructive procedure.

Downregulation of the T cell system has been proposed as a mechanism to block immunity in colonic cancer (CC). However, little has been studied about circulating αβ and γδ T cells and their immunological status in newly diagnosed patients. The aim of this study was to characterize the αβ and γδ T cell subsets in peripheral blood of patients with CC matched with healthy volunteers. In this prospective case-control study, blood samples were obtained from 96 patients with newly diagnosed treatment-naïve infiltrating colonic adenocarcinoma and 48 healthy volunteers. Pathological report at surgery was obtained from all CC patients. A significant decrease in CD3+ γδ T cells and CD3+CD8+ γδ T cells (p

The need for the olive farm modernization have encouraged the research of more efficient crop management strategies through cross-breeding programs to release new olive cultivars more suitable for mechanization and use in intensive orchards, with high quality production and resistance to biotic and abiotic stresses. The advancement of breeding programs are hampered by the lack of efficient phenotyping methods to quickly and accurately acquire crop traits such as morphological attributes (tree vigor and vegetative growth habits), which are key to identify desirable genotypes as early as possible. In this context, an UAV-based high-throughput system for olive breeding program applications was developed to extract tree traits in large-scale phenotyping studies under field conditions. The system consisted of UAV-flight configurations, in terms of flight altitude and image overlaps, and a novel, automatic, and accurate object-based image analysis (OBIA) algorithm based on point clouds, which was evaluated in two experimental trials in the framework of a table olive breeding program, with the aim to determine the earliest date for suitable quantifying of tree architectural traits. Two training systems (intensive and hedgerow) were evaluated at two very early stages of tree growth: 15 and 27 months after planting. Digital Terrain Models (DTMs) were automatically and accurately generated by the algorithm as well as every olive tree identified, independently of the training system and tree age. The architectural traits, specially tree height and crown area, were estimated with high accuracy in the second flight campaign, i.e. 27 months after planting. Differences in the quality of 3D crown reconstruction were found for the growth patterns derived from each training system. These key phenotyping traits could be used in several olive breeding programs, as well as to address some agronomical goals. In addition, this system is cost and time optimized, so that requested architectural traits could be provided in the same day as UAV flights. This high-throughput system may solve the actual bottleneck of plant phenotyping of “linking genotype and phenotype,” considered a major challenge for crop research in the 21st century, and bring forward the crucial time of decision making for breeders.

Significant advances in weed mapping from unmanned aerial platforms have been achieved in recent years. The detection of weed location has made possible the generation of site specific weed treatments to reduce the use of herbicides according to weed cover maps. However, the characterization of weed infestations should not be limited to the location of weed stands, but should also be able to distinguish the types of weeds to allow the best possible choice of herbicide treatment to be applied. A first step in this direction should be the discrimination between broad-leaved (dicotyledonous) and grass (monocotyledonous) weeds. Considering the advances in weed detection based on images acquired by unmanned aerial vehicles, and the ability of neural networks to solve hard classification problems in remote sensing, these technologies have been merged in this study with the aim of exploring their potential for broadleaf and grass weed detection in wide-row herbaceous crops such as sunflower and cotton. Overall accuracies of around 80% were obtained in both crops, with user accuracy for broad-leaved and grass weeds around 75% and 65%, respectively. These results confirm the potential of the presented combination of technologies for improving the characterization of different weed infestations, which would allow the generation of timely and adequate herbicide treatment maps according to groups of weeds.

Yield prediction is crucial for the management of harvest and scheduling wine production operations. Traditional yield prediction methods rely on manual sampling and are time-consuming, making it difficult to handle the intrinsic spatial variability of vineyards. There have been significant advances in automatic yield estimation in vineyards from on-ground imagery, but terrestrial platforms have some limitations since they can cause soil compaction and have problems on sloping and ploughed land. The analysis of photogrammetric point clouds generated with unmanned aerial vehicles (UAV) imagery has shown its potential in the characterization of woody crops, and the point color analysis has been used for the detection of flowers in almond trees. For these reasons, the main objective of this work was to develop an unsupervised and automated workflow for detection of grape clusters in red grapevine varieties using UAV photogrammetric point clouds and color indices. As leaf occlusion is recognized as a major challenge in fruit detection, the influence of partial leaf removal in the accuracy of the workflow was assessed. UAV flights were performed over two commercial vineyards with different grape varieties in 2019 and 2020, and the photogrammetric point clouds generated from these flights were analyzed using an automatic and unsupervised algorithm developed using free software. The proposed methodology achieved R2 values higher than 0.75 between the harvest weight and the projected area of the points classified as grapes in vines when partial two-sided removal treatment, and an R2 of 0.82 was achieved in one of the datasets for vines with untouched full canopy. The accuracy achieved in grape detection opens the door to yield prediction in red grape vineyards. This would allow the creation of yield estimation maps that will ease the implementation of precision viticulture practices. To the authors’ knowledge, this is the first time that UAV photogrammetric point clouds have been used for grape clusters detection.

Assessing the spatial distribution of weeds within a field is a key step to the success of site-specific weed management strategies. Centaurea diluta (knapweed) is an emerging weed that is causing a major agronomic problem in southern and central Spain because of its large size, the difficulty of controlling it, and its high competitive ability. The main objectives of this study were to examine the spatial variability of C. diluta density in two wheat fields by multivariate geostatistical methods using unmanned aerial vehicle (UAV) imagery as secondary information and to delineate potential control zones for site-specific treatments based on occurrence probability maps of weed infestation. The primary variable was obtained by grid weed density field samplings, and the secondary variables were derived from UAV imagery acquired the same day as the weed field surveys. Kriging and cokriging with UAV-derived variables that displayed a strong correlation with weed density were used to compare C. diluta density mapping performance. The accuracy of the predictions was assessed by cross-validation. Cokriging with UAV-derived secondary variables generated more accurate weed density maps with a lower RMSE compare with kriging and cokriging with RVI, NDVI, ExR, and ExR(2) (the best methods for the prediction of knapweed density). Cokriged estimates were used to generate probability maps for risk assessment when implementing site-specific weed control by indicator kriging. This multivariate geostatistical approach enabled the delineation of winter wheat fields into two zones for different prescription treatments according to the C. diluta density and the economic threshold.

Canopy management operations, such as shoot thinning, leaf removal, and shoot trimming, are among the most relevant agricultural practices in viticulture. However, the supervision of these tasks demands a visual inspection of the whole vineyard, which is time-consuming and laborious. The application of photogrammetric techniques to images acquired with an Unmanned Aerial Vehicle (UAV) has proved to be an efficient way to measure woody crops canopy. Consequently, the objective of this work was to determine whether the use of UAV photogrammetry allows the detection of canopy management operations. A UAV equipped with an RGB digital camera was used to acquire images with high overlap over different canopy management experiments in four vineyards with the aim of characterizing vine dimensions before and after shoot thinning, leaf removal, and shoot trimming operations. The images were processed to generate photogrammetric point clouds of every vine that were analyzed using a fully automated object-based image analysis algorithm. Two approaches were tested in the analysis of the UAV derived data: (1) to determine whether the comparison of the vine dimensions before and after the treatments allowed the detection of the canopy management operations; and (2) to study the vine dimensions after the operations and assess the possibility of detecting these operations using only the data from the flight after them. The first approach successfully detected the canopy management. Regarding the second approach, significant differences in the vine dimensions after the treatments were detected in all the experiments, and the vines under the shoot trimming treatment could be easily and accurately detected based on a fixed threshold.

The perennial and stoloniferous weed, Cynodon dactylon (L.) Pers. (bermudagrass), is a serious problem in vineyards. The spectral similarity between bermudagrass and grapevines makes discrimination of the two species, based solely on spectral information from multi-band imaging sensor, unfeasible. However, that challenge can be overcome by use of object-based image analysis (OBIA) and ultra-high spatial resolution Unmanned Aerial Vehicle (UAV) images. This research aimed to automatically, accurately, and rapidly map bermudagrass and design maps for its management. Aerial images of two vineyards were captured using two multispectral cameras (RGB and RGNIR) attached to a UAV. First, spectral analysis was performed to select the optimum vegetation index (VI) for bermudagrass discrimination from bare soil. Then, the VI-based OBIA algorithm developed for each camera automatically mapped the grapevines, bermudagrass, and bare soil (accuracies greater than 97.7%). Finally, site-specific management maps were generated. Combining UAV imagery and a robust OBIA algorithm allowed the automatic mapping of bermudagrass. Analysis of the classified area made it possible to quantify grapevine growth and revealed expansion of bermudagrass infested areas. The generated bermudagrass maps could help farmers improve weed control through a well-programmed strategy. Therefore, the developed OBIA algorithm offers valuable geo-spatial information for designing site-specific bermudagrass management strategies leading farmers to potentially reduce herbicide use as well as optimize fuel, field operating time, and costs.

Mobile phone addiction has attracted much attention recently and is showing similarity to other substance use disorders. Because no studies on mobile phone addiction had yet been conducted in Spain, we developed and validated a questionnaire (Cuestionario de Abuso del Teléfono Móvil, ATeMo) to measure mobile phone abuse among young adults in Spanish. The ATeMo questionnaire was designed based on relevant DSM-5 diagnostic criteria and included craving as a diagnostic symptom. Using stratified sampling, the ATeMo questionnaire was administered to 856 students (mean age 21, 62% women). The MULTICAGE questionnaire was administered to assess history of drug abuse and addiction. Using confirmatory factor analysis, we found evidence for the construct validity of the following factors: Craving, Loss of Control, Negative Life Consequences, and Withdrawal Syndrome, and their association with a second order factor related to mobile phone abuse. The four ATeMO factors were also associated with alcoholism, internet use, and compulsive buying. Important gender differences were found that should be considered when studying mobile phone addictions. The ATeMo is a valid and reliable instrument that can be used in further research on mobile phone abuse.

This article describes the technical specifications and configuration of a multirotor unmanned aerial vehicle (UAV) to acquire remote images using a six-band multispectral sensor. Several flight missions were programmed as follows: three flight altitudes (60, 80 and 100 m), two flight modes (stop and cruising modes) and two ground control point (GCP) settings were considered to analyze the influence of these parameters on the spatial resolution and spectral discrimination of multispectral orthomosaicked images obtained using Pix4Dmapper. Moreover, it is also necessary to consider the area to be covered or the flight duration according to any flight mission programmed. The effect of the combination of all these parameters on the spatial resolution and spectral discrimination of the orthomosaicks is presented. Spectral discrimination has been evaluated for a specific agronomical purpose: to use the UAV remote images for the detection of bare soil and vegetation (crop and weeds) for in-season site-specific weed management. These results show that a balance between spatial resolution and spectral discrimination is needed to optimize the mission planning and image processing to achieve every agronomic objective. In this way, users do not have to sacrifice flying at low altitudes to cover the whole area of interest completely.

Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights.

In order to optimize the application of herbicides in weed-crop systems, accurate and timely weed maps of the crop-field are required. In this context, this investigation quantified the efficacy and limitations of remote images collected with an unmanned aerial vehicle (UAV) for early detection of weed seedlings. The ability to discriminate weeds was significantly affected by the imagery spectral (type of camera), spatial (flight altitude) and temporal (the date of the study) resolutions. The colour-infrared images captured at 40 m and 50 days after sowing (date 2), when plants had 5–6 true leaves, had the highest weed detection accuracy (up to 91%). At this flight altitude, the images captured before date 2 had slightly better results than the images captured later. However, this trend changed in the visible-light images captured at 60 m and higher, which had notably better results on date 3 (57 days after sowing) because of the larger size of the weed plants. Our results showed the requirements on spectral and spatial resolutions needed to generate a suitable weed map early in the growing season, as well as the best moment for the UAV image acquisition, with the ultimate objective of applying site-specific weed management operations.

Remote sensing applied in the digital transformation of agriculture and, more particularly, in precision viticulture offers methods to map field spatial variability to support site-specific management strategies; these can be based on crop canopy characteristics such as the row height or vegetation cover fraction, requiring accurate three-dimensional (3D) information. To derive canopy information, a set of dense 3D point clouds was generated using photogrammetric techniques on images acquired by an RGB sensor onboard an unmanned aerial vehicle (UAV) in two testing vineyards on two different dates. In addition to the geometry, each point also stores information from the RGB color model, which was used to discriminate between vegetation and bare soil. To the best of our knowledge, the new methodology herein presented consisting of linking point clouds with their spectral information had not previously been applied to automatically estimate vine height. Therefore, the novelty of this work is based on the application of color vegetation indices in point clouds for the automatic detection and classification of points representing vegetation and the later ability to determine the height of vines using as a reference the heights of the points classified as soil. Results from on-ground measurements of the heights of individual grapevines were compared with the estimated heights from the UAV point cloud, showing high determination coefficients (R² > 0.87) and low root-mean-square error (0.070 m). This methodology offers new capabilities for the use of RGB sensors onboard UAV platforms as a tool for precision viticulture and digitizing applications.

The strategic management of agricultural lands involves crop field monitoring each year. Crop discrimination via remote sensing is a complex task, especially if different crops have a similar spectral response and cropping pattern. In such cases, crop identification could be improved by combining object-based image analysis and advanced machine learning methods. In this investigation, we evaluated the C4.5 decision tree, logistic regression (LR), support vector machine (SVM) and multilayer perceptron (MLP) neural network methods, both as single classifiers and combined in a hierarchical classification, for the mapping of nine major summer crops (both woody and herbaceous) from ASTER satellite images captured in two different dates. Each method was built with different combinations of spectral and textural features obtained after the segmentation of the remote images in an object-based framework. As single classifiers, MLP and SVM obtained maximum overall accuracy of 88%, slightly higher than LR (86%) and notably higher than C4.5 (79%). The SVM+SVM classifier (best method) improved these results to 89%. In most cases, the hierarchical classifiers considerably increased the accuracy of the most poorly classified class (minimum sensitivity). The SVM+SVM method offered a significant improvement in classification accuracy for all of the studied crops compared to the conventional decision tree classifier, ranging between 4% for safflower and 29% for corn, which suggests the application of object-based image analysis and advanced machine learning methods in complex crop classification tasks.

Decisional Balance and Processes of Change are generally addressed in motivational interventions for the treatment of cannabis use disorders. However, specific aspects of these multifaceted constructs, with greater relevance for severe cannabis users, need to be ascertained to enable better interventions. This study aimed to compare the different facets of decisional balance and processes of change between mild and severe cannabis users in a community-based sample of young undergraduates. Thirty-one severe cannabis users and 31 mild cannabis users, indicated with the Severity of Dependence Scale, were assessed using the Decisional Balance Questionnaire (DBQ) and the Processes of Change Questionnaire (PCQ). We found that severe cannabis users had higher scores in the DBQ dimensions of Utilitarian Gains for the Self, Utilitarian Gains for Significant Others, and Self-approval, as well as in the total subscale of Gains but not Losses. The group of severe cannabis users also had higher scores in the PCQ dimensions of Self-revaluations and Counter-conditioning. Our results pinpoint specific dimensions of Decisional Balance and Processes of Change that are endorsed by severe cannabis users. This knowledge could be applied to inform motivational interventions targeting severe cannabis users.

This paper aims to evaluate the spatial persistence of wild oat patches in four wheat fields over time to determine the economic feasibility of using late-season wild oat maps for early site-specific weed management (SSWM) next season. The spatial persistence of wild oat patches was analyzed by three tests: land use change detection between years, spatial autocorrelation, and analysis of spreading distance. The temporal trend of wild oat patch distribution showed a clear persistence and a generalized increase in the infested area, with a noticeable level of weed aggregation and a tendency in the new weed patches to emerge close to older ones. To economically evaluate the SSWM, five simulations in four agronomic scenarios, varying wheat yields and losses due to wild oat, were conducted. When yield losses due to wild oat were minimal and for any of the expected wheat yields, some SSWM simulations were more economically profitable than the overall application in most of the fields. Nevertheless, when the yield losses due to wild oat were maximal, all SSWM simulations were less profitable than overall treatment in all the analyzed fields. Although the economic profit variations achieved with SSWM treatments were modest, any of the site-specific treatments tested are preferred to herbicide broadcast over the entire field, in order to reduce herbicide and environmental pollution.

Precision viticulture has arisen in recent years as a new approach in grape production. It is based on assessing field spatial variability and implementing site-specific management strategies, which can require georeferenced information of the three dimensional (3D) grapevine canopy structure as one of the input data. The 3D structure of vineyard fields can be generated applying photogrammetric techniques to aerial images collected with Unmanned Aerial Vehicles (UAVs), although processing the large amount of crop data embedded in 3D models is currently a bottleneck of this technology. To solve this limitation, a novel and robust object-based image analysis (OBIA) procedure based on Digital Surface Model (DSM) was developed for 3D grapevine characterization. The significance of this work relies on the developed OBIA algorithm which is fully automatic and self-adaptive to different crop-field conditions, classifying grapevines, and row gap (missing vine plants), and computing vine dimensions without any user intervention. The results obtained in three testing fields on two different dates showed high accuracy in the classification of grapevine area and row gaps, as well as minor errors in the estimates of grapevine height. In addition, this algorithm computed the position, projected area, and volume of every grapevine in the field, which increases the potential of this UAV- and OBIA-based technology as a tool for site-specific crop management applications.

El objetivo de este estudio teórico es destacar las posibilidades aplicadas de la Teoría de los Marcos Relacionales (RFT) en el ámbito clínico. En primer lugar, describiremos de manera muy breve algunos de los principales conceptos técnicos de la teoría (por ejemplo, los conceptos de transformación de funciones y de operante generalizada). Posteriormente, propondremos cuatro causas por las cuales se generan los problemas psicológicos derivadas de una aproximación a la psicopatología humana generada desde la RFT. Dichas causas tienen que ver con los contextos verbales de la literalidad, la formación de categorías y por consiguiente la evaluación y comparación, el contexto de la búsqueda de coherencia y de dar razones y finalmente con el control de los eventos privados. Por último, se expondrán las amplias implicaciones clínicas de los conceptos de contexto relacional y contexto funcional, usando ejemplos clínicos relevantes y clasificando diferentes terapias en función de cual es su objetivo principal: la alteración del contexto funcional o del contexto relacional de redes relacionales.

En las últimas décadas, las agencias financieras internacionales han destacado la importancia de las políticas públicas como dispositivo teórico y metodológico frente a la administración pública centralizada. En el discurso de estos organismos, la participación social y la descentralización son los ejes principales, mientras que desde una postura crítica, se aprecia como una forma de apropiación de las demandas de la sociedad para la preservación del poder de forma centralizada. En este marco, se analizan y discuten algunas modificaciones en el Estado mexicano como las reformas al art. 115 constitucional y la Ley para el Desarrollo Rural Sustentable (ldrs). Asimismo, esto se relaciona con los actores institucionales y de la ruralidad del municipio de San Blas, para reflexionar sobre las limitaciones y las posibilidades municipales en la definición de políticas para el desarrollo rural.

En este artículo se discute sobre la relación entre la esquizofrenia y la personalidad, esta relación es compleja y se puede estudiar desde diferentes perspectivas y modelos. Parece que diversos rasgos de personalidad como altos niveles de neuroticismo y bajos niveles de extraversión (Berenbaum y Fujita, 1994) y altos niveles de evitación del daño (HA) y bajos de autodirección (SD) (Guillem, Bicu, Semkovska y Debruile, 2002), pueden actuar como factores de vulnerabilidad para la esquizofrenia. También, se han relacionado algunos rasgos con síntoma esquizofrénicos, lo que puede ayudar a explicar la heterogeneidad observada en esta enfermedad. Pero son necesarios más estudios para averiguar qué características de personalidad actúan más como factores presdisponentes y cuáles forman parte de la reacción a la enfermedad

Este estudio de revisión tiene como objetivo proveer una visión general de la evolución y situación actual de las unidades de cuidados paliativos. Además, se clarifica el concepto de enfermedad terminal, así como los objetivos de la actuación terapéutica en dichas condiciones. Tales objetivos se llevan a cabo por un equipo multidisciplinar que requiere formación y atención específica, entre quienes el psicólogo tiene un importante papel en relación con el bienestar emocional del paciente y su familia. Finalmente, se reflexiona en relación con las dificultades que encuentran los profesionales para realizar su trabajo, así como sobre la necesidad de estudios en los que se ofrezcan descripciones sistemáticas de la intervención integral en medicina paliativa.

Objective: To describe an outbreak of acute gastroenteritis in the population, occurred in June and July 2002.Design: A descriptive, case-control study.Location: Rural population of 1.323 inhabitants, living in Granada.Population and sample: It affected about 200 persons. 32 cases and 32 controls were selected.Intervention: An epidemiological survey was run, taking into account variables of time and person (age, sex, drinking water intake and clinical pattern of the disease antecedent. We investigated the different independents variables. A contingency tables, hypothesis X2 test, calculation of the unprocessed and subsequently adjusted Odds Ratio (IC 95%) were carried out using logic regression.Results: No significant differences were found in the sex variable and consumption of water. The epidemic curve no showed a rapid onset. In the adjusted Odds Ratio calculation the clinical pattern of disease antecedent showed causal relationship values (adjusted Odds Ratio=5,32; IC-95% 1,23-22,93; p=0,025). The inspection of the water network no showed deficient. Patient stool samples no were sent for analysis.Conclusions: This study has not detected disease-causing agent, however, it’s spread through person-to-person contact.Objetivo: Describir un cuadro de gastroenteritis aguda de base poblacional ocurrido a durante los meses de junio y mediados de julio del año 2002.Diseño: Estudio descriptivo y de casos-control.Emplazamiento: Población rural de 1.323 habitantes (1-1-2001) de la provincia de Granada.Población y muestra: De unos 200 enfermos se recogieron 34 casos y los mismos controles.Intervenciones: Mediante encuesta epidemiológica se investiga la relación entre la enfermedad y distintas variables independientes: características personales (edad, sexo, consumo agua y antecedentes de enfermedad) y tiempo. Se realizó tablas de contingencia y test de hipótesis χ2 y el cálculo de OR cruda y posteriormente ajustada (IC al 95%) utilizando regresión logística.Resultados: No se observaron diferencias significativas en la variable sexo y de consumo de cualquier tipo de agua (red y embotellada). La curva epidémica no refleja un comienzo explosivo. En el cálculo de la OR ajustada destaca la relación causal los antecedentes familiares de padecer la enfermedad (OR ajustada= 5,32; IC-95% 1,23- 22,93; p=0,025). La inspección de la red de agua estaba bien y no se remitieron muestras de heces de enfermos para su análisis.Conclusiones: Se trata de un brote de gastroenteritis aguda de base poblacional, de etiología desconocida y con mecanismo de transmisión de persona a persona.

El personal sanitario se enfrenta frecuentemente a situaciones de vida y muerte. Su trabajo puede ser física y emocionalmente agotador. El estrés que se deriva de este contexto implica el desarrollo de problemas conductuales como burnout y otros problemas de salud y psicológicos (ansiedad, depresión, etc.). En la actualidad esta temática es importante ya que afecta a la moral y bienestar psicológico de los trabajadores, a la calidad y tratamiento que se proporciona a los pacientes y, por último, puede tener una influencia fuerte en el funcionamiento administrativo de los servicios sanitarios. En este trabajo teórico se presenta una revisión del concepto de burnout, las variables de las que depende, las medidas más utilizadas, las consecuencias del mismo y las estrategias de intervención que se han desarrollado para prevenir y tratar este problema. Finalmente, se realiza una propuesta de análisis conceptual del burnout como un ejemplo de evitación experiencial, así como de sus implicaciones en el tratamiento.

Accurate and timely detection of weeds between and within crop rows in the early growth stage is considered one of the main challenges in site-specific weed management (SSWM). In this context, a robust and innovative automatic object-based image analysis (OBIA) algorithm was developed on Unmanned Aerial Vehicle (UAV) images to design early post-emergence prescription maps. This novel algorithm makes the major contribution. The OBIA algorithm combined Digital Surface Models (DSMs), orthomosaics and machine learning techniques (Random Forest, RF). OBIA-based plant heights were accurately estimated and used as a feature in the automatic sample selection by the RF classifier; this was the second research contribution. RF randomly selected a class balanced training set, obtained the optimum features values and classified the image, requiring no manual training, making this procedure time-efficient and more accurate, since it removes errors due to a subjective manual task. The ability to discriminate weeds was significantly affected by the imagery spatial resolution and weed density, making the use of higher spatial resolution images more suitable. Finally, prescription maps for in-season post-emergence SSWM were created based on the weed maps—the third research contribution—which could help farmers in decision-making to optimize crop management by rationalization of the herbicide application. The short time involved in the process (image capture and analysis) would allow timely weed control during critical periods, crucial for preventing yield loss.

The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status and crop production. However, these variables are mostly estimated after a time-consuming and hard field work and applying equations that treat the trees as geometric solids, which produce inconsistent results. As an alternative, this work presents an innovative procedure for computing the 3-dimensional geometric features of individual trees and tree-rows by applying two consecutive phases: 1) generation of Digital Surface Models with Unmanned Aerial Vehicle (UAV) technology and 2) use of object-based image analysis techniques. Our UAV-based procedure produced successful results both in single-tree and in tree-row plantations, reporting up to 97% accuracy on area quantification and minimal deviations compared to in-field estimations of tree heights and crown volumes. The maps generated could be used to understand the linkages between tree grown and field-related factors or to optimize crop management operations in the context of precision agriculture with relevant agro-environmental implications.

AIMS:Temperament and impulsivity are powerful predictors of addiction treatment outcomes. However, a comprehensive assessment of these features has not been examined in relation to smoking cessation outcomes. METHODS:Naturalistic prospective study. Treatment-seeking smokers (n = 140) were recruited as they engaged in an occupational health clinic providing smoking cessation treatment between 2009 and 2013. Participants were assessed at baseline with measures of temperament (Temperament and Character Inventory), trait impulsivity (Barratt Impulsivity Scale), and cognitive impulsivity (Go/No Go, Delay Discounting and Iowa Gambling Task). The outcome measure was treatment status, coded as "dropout" versus "relapse" versus "abstinence" at 3, 6, and 12 months endpoints. Participants were telephonically contacted and reminded of follow-up face to face assessments at each endpoint. The participants that failed to answer the phone calls or self-reported discontinuation of treatment and failed to attend the upcoming follow-up session were coded as dropouts. The participants that self-reported continuing treatment, and successfully attended the upcoming follow-up session were coded as either "relapse" or "abstinence", based on the results of smoking behavior self-reports cross-validated with co-oximetry hemoglobin levels. Multinomial regression models were conducted to test whether temperament and impulsivity measures predicted dropout and relapse relative to abstinence outcomes. RESULTS:Higher scores on temperament dimensions of novelty seeking and reward dependence predicted poorer retention across endpoints, whereas only higher scores on persistence predicted greater relapse. Higher scores on the trait dimension of non-planning impulsivity but not performance on cognitive impulsivity predicted poorer retention. Higher non-planning impulsivity and poorer performance in the Iowa Gambling Task predicted greater relapse at 3 and 6 months and 6 months respectively. CONCLUSION:Temperament measures, and specifically novelty seeking and reward dependence, predict smoking cessation treatment retention, whereas persistence, non-planning impulsivity and poor decision-making predict smoking relapse.

Para quienes ejercemos el oficio de historiadores constituye una labor cotidiana el manejo de diversas fuentes históricas como las bibliográficas, las publicaciones periódicas y, especialmente, los documentos de archivo a los que se les atribuye una función probatoria fundamental. Actualmente es notable la ampliación y diversidad de las fuentes para el trabajo histórico cuya validez es aceptada, entre las que han alcanzado un lugar de privilegio en tiempos recientes las orales, lo que implica la aplicación de técnicas adecuadas a su naturaleza. Sin embargo, ¿cuántas veces nos hemos preguntado cuáles son los fundamentos teóricos de este oficio? Sin dudas, la historia requiere del trabajo empírico para el estudio de un proceso, coyuntura o acontecimiento específico, es decir, la investigación histórica concreta tiene sus requerimientos en la indagación de lo factual, pero esto resulta insuficiente si no partimos de conocer las características y bases teóricas del área del saber a la que nos dedicamos.

A new aerial platform has risen recently for image acquisition, the Unmanned Aerial Vehicle (UAV). This article describes the technical specifications and configuration of a UAV used to capture remote images for early season site- specific weed management (ESSWM). Image spatial and spectral properties required for weed seedling discrimination were also evaluated. Two different sensors, a still visible camera and a six-band multispectral camera, and three flight altitudes (30, 60 and 100 m) were tested over a naturally infested sunflower field. The main phases of the UAV workflow were the following: 1) mission planning, 2) UAV flight and image acquisition, and 3) image pre-processing. Three different aspects were needed to plan the route: flight area, camera specifications and UAV tasks. The pre-processing phase included the correct alignment of the six bands of the multispectral imagery and the orthorectification and mosaicking of the individual images captured in each flight. The image pixel size, area covered by each image and flight timing were very sensitive to flight altitude. At a lower altitude, the UAV captured images of finer spatial resolution, although the number of images needed to cover the whole field may be a limiting factor due to the energy required for a greater flight length and computational requirements for the further mosaicking process. Spectral differences between weeds, crop and bare soil were significant in the vegetation indices studied (Excess Green Index, Normalised Green-Red Difference Index and Normalised Difference Vegetation Index), mainly at a 30 m altitude. However, greater spectral separability was obtained between vegetation and bare soil with the index NDVI. These results suggest that an agreement among spectral and spatial resolutions is needed to optimise the flight mission according to every agronomical objective as affected by the size of the smaller object to be discriminated (weed plants or weed patches).

The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a weed map in an experimental maize field in Spain. The OBIA procedure combines several contextual, hierarchical and object-based features and consists of three consecutive phases: 1) classification of crop rows by application of a dynamic and auto-adaptive classification approach, 2) discrimination of crops and weeds on the basis of their relative positions with reference to the crop rows, and 3) generation of a weed infestation map in a grid structure. The estimation of weed coverage from the image analysis yielded satisfactory results. The relationship of estimated versus observed weed densities had a coefficient of determination of r(2)=0.89 and a root mean square error of 0.02. A map of three categories of weed coverage was produced with 86% of overall accuracy. In the experimental field, the area free of weeds was 23%, and the area with low weed coverage (

In the context of detection of weeds in crops for site-specific weed control, on-ground spectral reflectance measurements are the first step to determine the potential of remote spectral data to classify weeds and crops. Field studies were conducted for four years at different locations in Spain. We aimed to distinguish cruciferous weeds in wheat and broad bean crops, using hyperspectral and multispectral readings in the visible and near-infrared spectrum. To identify differences in reflectance between cruciferous weeds, we applied three classification methods: stepwise discriminant (STEPDISC) analysis and two neural networks, specifically, multilayer perceptron (MLP) and radial basis function (RBF). Hyperspectral and multispectral signatures of cruciferous weeds, and wheat and broad bean crops can be classified using STEPDISC analysis, and MLP and RBF neural networks with different success, being the MLP model the most accurate with 100%, or higher than 98.1%, of classification performance for all the years. Classification accuracy from hyperspectral signatures was similar to that from multispectral and spectral indices, suggesting that little advantage would be obtained by using more expensive airborne hyperspectral imagery. Therefore, for next investigations, we recommend using multispectral remote imagery to explore whether they can potentially discriminate these weeds and crops.

Objetivo: Describir un cuadro de gastroenteritis aguda de base poblacional ocurrido a durante los meses de junio y mediados de julio del año 2002. Diseño: Estudio descriptivo y de casos-control. Emplazamiento: Población rural de 1.323 habitantes (1-1-2001) de la provincia de Granada. Población y muestra: De unos 200 enfermos se recogieron 34 casos y los mismos controles. Intervenciones: Mediante encuesta epidemiológica se investiga la relación entre la enfermedad y distintas variables independientes: características personales (edad, sexo, consumo agua y antecedentes de enfermedad) y tiempo. Se realizó tablas de contingencia y test de hipótesis χ2 y el cálculo de OR cruda y posteriormente ajustada (IC al 95%) utilizando regresión logística. Resultados: No se observaron diferencias significativas en la variable sexo y de consumo de cualquier tipo de agua (red y embotellada). La curva epidémica no refleja un comienzo explosivo. En el cálculo de la OR ajustada destaca la relación causal los antecedentes familiares de padecer la enfermedad (OR ajustada= 5,32; IC-95% 1,23- 22,93; p=0,025). La inspección de la red de agua estaba bien y no se remitieron muestras de heces de enfermos para su análisis. Conclusiones: Se trata de un brote de gastroenteritis aguda de base poblacional, de etiología desconocida y con mecanismo de transmisión de persona a persona.