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Semantic segmentation of medical images presents an enormous potential for diagnosis and surgery. However, achieving precise results involves designing and training complex Deep Learning (DL) models specifically for this task, which is only available to some. SAM is a model developed by Meta capable of segmenting objects present in virtually any type of image. This paper showcases SAM’s robustness and exceptional performance in medical image segmentation, even in the absence of direct training on these image types (lung Computed Tomographies (CTs) and chest X-rays, in particular). Additionally, it achieves this impressive outcome while requiring minimal user intervention. Although the dataset used to train SAM does not contain a single sample of both medical image types, processing a popular dataset comprised of $\mathrm {20 }$ volumes with a total of $\mathrm {3520 }$ slices using the ViT-L version of the model yields an average Jaccard index of $\mathrm {91.45 \%}$ and an average Dice score of $\mathrm {94.95 \%}$ . The same version of the model achieves a $\mathrm {93.19 \%}$ Dice score and a $\mathrm {87.45 \%}$ Jaccard index when segmenting a frequently-used chest X-ray dataset. The values obtained are above the $\mathrm {70 \%}$ mark recommended in the literature, and close to state-of-the art models developed specifically for medical segmentation. These results are achieved without user interaction by providing the model with positive prompts based on the masks of the dataset used and a negative prompt located in the center of bounding box that contains the masks.

BackgroundX (previously known as “Twitter”) serves as a platform for open discussions on mental health, providing an avenue for scrutinizing public perspectives regarding psychiatry, psychology and their associated professionals.ObjectiveTo analyze the conversations happening on X about psychiatrists, psychologists, and their respective disciplines to understand how the public perception of these professionals and specialties has evolved over the last 15 years.MethodsWe collected and analyzed all tweets posted in English or Spanish between 2007 and 2023 referring to psychiatry, psychology, neurology, mental health, psychiatrist, psychologist, or neurologist using advance topic modelling and sentiment analysis.ResultsA total of 403,767 tweets were analyzed, 155,217 (38%) were in English and 248,550 (62%) in Spanish. Tweets about mental health and mental health professionals and disciplines showed a consistent volume between 2011 and 2016, followed by a gradual increase from 2016 through 2022. The proportion of tweets discussing mental health doubled from 2016 to 2022, increasing from 20% to 67% in Spanish and from 15% to 45% in English. Several differences were observed on the volume of tweets overtime depending on the language they were written. Users associated each term with varied topics, such as seeking for help and recommendation for therapy, self-help resources, medication and side effects, suicide prevention, mental health in times of crisis, among others. The number of tweets mentioning these topics increased by 5-10% from 2016 to 2022, indicating a growing interest among the population. Emotional analysis showed most of the topics were associated with fear and anger.ConclusionThe increasing trend in discussions about mental health and the related professionals and disciplines over time may signify an elevated collective awareness of mental health. Gaining insights into the topics around these matters and user’s corresponding emotions towards them presents an opportunity to combat the stigma surrounding mental health more effectively.

Introduction: Single-nucleotide polymorphism (SNP) rs9939609 in the FTO gene has been associated with dietary intake and appetite traits, mainly in participants with obesity; however, it remains widely unexplored in normal weight participants. Thus, the aims of this study were (1) to compare the changes in subjective appetite sensations, ghrelin, and insulin concentrations according to the SNP rs9939609 T>A in FTO and (2) to compare dietary intake between rs9939609 genotype groups in normal weight young participants. Methods: We conducted a quasi-experimental study involving 88 normal weight participants to analyze subjective perception of appetite, hormonal response for hunger and satiety, and dietary intake according to the rs9939609 SNP. Participants received a standardized single breakfast. Visual analogue scales (VAS) were utilized for assessing the subjective perception of appetite at fasting and immediately after breakfast and at 30, 60, 90, and 120 min postprandially. Glucose, lipid profile, ghrelin, and insulin were measured at fasting and at 120 min after breakfast. Dietary intake was assessed with a 3-day food record. The SNP was determined by allelic discrimination with TaqMan probes. To compare dietetic, biochemical, and the subjective appetite sensations, Student t test, ANCOVA test, and the repeated measures ANOVA were used. The linear regression model and the linear mixed model were used for the association analysis. Pearson correlation was used to test the correlation between two quantitative variables. Results: A total of 88 people participated, 81.8% were female, with a mean body mass index of 21.8 ± 2.0 kg/m2 and a mean age of 20.6 ± 2.0. Genotype frequencies of the rs9939609 SNP were 52% for the TT allele and 48% for the TA/AA. The subjective perception of appetite named hunger, fullness, satiety, desire to eat, and prospective food consumption were similar between genotypes of the rs9939609. Participants with the TA/AA genotype showed a higher intake of added sugar (p = 0.039) than TT participants. No differences were found in ghrelin, insulin, glucose, or lipid parameters between genotypes. Conclusion: Carriers of the A allele from FTO gene SNP rs9939609 may have an increased preference for foods, specifically for added sugars.

To effectively combat the re-infestation of boll weevils (Anthonomus grandis L.) in cotton fields, it is necessary to address the detection of volunteer cotton (VC) plants (Gossypium hirsutum L.) in rotation crops such as corn (Zea mays L.) and sorghum (Sorghum bicolor L.). The current practice involves manual field scouting at the field edges, which often leads to the oversight of VC plants growing in the middle of fields alongside corn and sorghum. As these VC plants reach the pinhead squaring stage (5–6 leaves), they can become hosts for boll weevil pests. Consequently, it becomes crucial to detect, locate, and accurately spot-spray these plants with appropriate chemicals. This paper focuses on the application of YOLOv5m to detect and locate VC plants during the tasseling (VT) growth stage of cornfields. Our results demonstrate that VC plants can be detected with a mean average precision (mAP) of 79% at an Intersection over Union (IoU) of 50% and a classification accuracy of 78% on images sized 1207 × 923 pixels. The average detection inference speed is 47 frames per second (FPS) on the NVIDIA Tesla P100 GPU-16 GB and 0.4 FPS on the NVIDIA Jetson TX2 GPU, which underscores the relevance and impact of detection speed on the feasibility of real-time applications. Additionally, we show the application of a customized unmanned aircraft system (UAS) for spot-spray applications through simulation based on the developed computer vision (CV) algorithm. This UAS-based approach enables the near-real-time detection and mitigation of VC plants in corn fields, with near-real-time defined as approximately 0.02 s per frame on the NVIDIA Tesla P100 GPU and 2.5 s per frame on the NVIDIA Jetson TX2 GPU, thereby offering an efficient management solution for controlling boll weevil pests.

Abstract Despite exponential growth in ecological data availability, broader interoperability amongst datasets is needed to unlock the potential of open access. Our understanding of the interface of demography and functional traits is well-positioned to benefit from such interoperability. Here, we introduce MOSAIC, an open-access trait database that unlocks the demographic potential stored in the COMADRE, COMPADRE, and PADRINO open-access databases. MOSAIC data were digitised and curated through a combination of existing datasets and new trait records sourced from primary literature. In its first release, MOSAIC (v. 1.0.0) includes 14 trait fields for 300 animal and plant species: biomass, height, growth determination, regeneration, sexual dimorphism, mating system, hermaphrodism, sequential hermaphrodism, dispersal capacity, type of dispersal, mode of dispersal, dispersal classes, volancy, and aquatic habitat dependency. MOSAIC includes species-level phylogenies for 1,359 species and population-specific climate data. We identify how database integration can improve our understanding of traits well-quantified in existing repositories and those that are poorly quantified (e.g., growth determination, modularity). MOSAIC highlights emerging challenges associated with standardising databases and demographic measures.

The study focuses on identifying and understanding the ecological dynamics of Triatoma breyeri in Bolivia. Morphological identification and molecular analysis using gene fragments (COI, CytB and 16S) confirms T. breyeri's presence and its relation to other species. The species has been consistently found in the Estancia-Mataral-La Palma region since 2010 but has not spread to other regions in Bolivia. The region of occurrence is a small characteristic dry inter-Andean valley. A MaxEnt model suggests part of the Bolivian Montane Dry Forest ecoregion serves as a unique habitat within its range. The infrequent presence in Bolivia and the distance from its main range in Argentina suggest recent accidental introduction, possibly through human transport. Further research is needed to comprehend its persistence in this small area of Bolivia.

The severity of the pandemic and its consequences on health and social care systems were quite diverse and devastating. COVID-19 was associated with an increased risk of neurological and neuropsychiatric disorders after SARS-CoV-2 infection. We did a cross-sectional study of 3 months post-COVID consequences of 178 Cuban subjects. Our study has a unique CUBAN COVID-19 cohort of hospitalized COVID-19 patients and healthy subjects. We constructed a latent variable for pre-health conditions (PHC) through Item Response Theory (IRT) and for post-COVID neuropsychiatric symptoms (Post-COVID-NPS) through Factor Analysis (FA). There seems to be a potential causal relationship between determinants of CIBD and post-COVID-NPS in hospitalized COVID-19 patients. The causal relationships accessed by Structural Equation Modeling (SEM) revealed that PHC (p < 0.001) and pre-COVID cognitive impairments (p < 0.001) affect the severity of COVID-19 patients. The severity of COVID-19 eventually results in enhanced post-COVID-NPS (p < 0.001), even after adjusting for confounders (age, sex, and pre-COVID-NPS). The highest loadings in PHC were for cardiovascular diseases, immunological disorders, high blood pressure, and diabetes. On the other hand, sex (p < 0.001) and pre-COVID-NPS including neuroticism (p < 0.001), psychosis (p = 0.005), cognition (p = 0.036), and addiction (p < 0.001) were significantly associated with post-COVID-NPS. The most common neuropsychiatric symptom with the highest loadings includes pain, fatigue syndrome, autonomic dysfunctionalities, cardiovascular disorders, and neurological symptoms. Compared to healthy people, COVID-19 patients with pre-health comorbidities or pre-neuropsychiatric conditions will have a high risk of getting severe COVID-19 and long-term post-COVID neuropsychiatric consequences. Our study provides substantial evidence to highlight the need for a complete neuropsychiatric follow-up on COVID-19 patients (with severe illness) and survivors (asymptomatic patients who recovered).

Unmanned aircraft systems (UAS), commonly referred to as drones, are an emerging technology that has changed the way many industries conduct business. Precision agriculture is one industry that has consistently been predicted to be a major locus of innovation for UAS. However, this has not been the case globally. The agricultural aircraft sector in the United States is used as a case study here to consider different metrics to evaluate UAS adoption, including a proposed metric, the normalized UAS adoption index. In aggregate, UAS operators only make up 5% of the number of agricultural aircraft operators. However, the annual number of new UAS operators exceeded that of manned aircraft operators in 2022. When used on a state-by-state basis, the normalized UAS adoption index shows that there are regional differences in UAS adoption with western and eastern states having higher UAS adoption rates while central states have significantly lower UAS adoption rates. This has implications for UAS operators, manufacturers, and regulators as this industry continues to develop at a rapid pace.

Abstract Background The interest in the relationship between brain damage and social cognition has increased in recent years. The objectives of the present study were the following: (1) to evaluate and compare emotional facial recognition and subjective emotional experience in patients who have suffered a single ischemic stroke in the right hemisphere (RH) and in healthy people, (2) to analyze the relationship between both variables in both groups of subjects, and (3) to analyze the association between the cerebral location of the stroke and these two variables. Methods Emotional facial recognition and the subjective emotional experience of 41 patients who had suffered a single ischemic stroke in the RH and 45 volunteers without previous cerebrovascular pathology were evaluated. Results Brain damaged patients performed lower in facial emotional recognition and had a less intense subjective emotional response to social content stimuli compared to healthy subjects. Likewise, among patients with RH ischemic stroke, we observed negative associations between facial recognition of surprise and reactivity to unpleasant images, and positive associations between recognition of disgust and reactivity to pleasant images. Finally, patients with damage in the caudate nucleus of the RH presented a deficit in the recognition of happiness and sadness, and those with damage in the frontal lobe exhibited a deficit in the recognition of surprise, compared to those injured in other brain areas. Conclusions Emotional facial recognition and subjective emotional experience are affected in patients who have suffered a single ischemic stroke in the RH. Professionals caring for stroke patients should improve their understanding of the general condition of affected persons and their environment, assess for risk of depression, and facilitate their adaptation to work, family, and social environments.

Abstract Background Aggression is observed across the animal kingdom, and benefits animals in a number of ways to increase fitness and promote survival. While aggressive behaviors vary widely across populations and can evolve as an adaptation to a particular environment, the complexity of aggressive behaviors presents a challenge to studying the evolution of aggression. The Mexican tetra, Astyanax mexicanus exists as an aggressive river-dwelling surface form and multiple populations of a blind cave form, some of which exhibit reduced aggression, providing the opportunity to investigate how evolution shapes aggressive behaviors. Results To define how aggressive behaviors evolve, we performed a high-resolution analysis of multiple social behaviors that occur during aggressive interactions in A. mexicanus. We found that many of the aggression-associated behaviors observed in surface-surface aggressive encounters were reduced or lost in Pachón cavefish. Interestingly, one behavior, circling, was observed more often in cavefish, suggesting evolution of a shift in the types of social behaviors exhibited by cavefish. Further, detailed analysis revealed substantive differences in aggression-related sub-behaviors in independently evolved cavefish populations, suggesting independent evolution of reduced aggression between cave populations. We found that many aggressive behaviors are still present when surface fish fight in the dark, suggesting that these reductions in aggression-associated and escape-associated behaviors in cavefish are likely independent of loss of vision in this species. Further, levels of aggression within populations were largely independent of type of opponent (cave vs. surface) or individual stress levels, measured through quantifying stress-like behaviors, suggesting these behaviors are hardwired and not reflective of population-specific changes in other cave-evolved traits. Conclusion These results reveal that loss of aggression in cavefish evolved through the loss of multiple aggression-associated behaviors and raise the possibility that independent genetic mechanisms underlie changes in each behavior within populations and across populations. Taken together, these findings reveal the complexity of evolution of social behaviors and establish A. mexicanus as a model for investigating the evolutionary and genetic basis of aggressive behavior.

Abstract Vaccine development for Plasmodium vivax, an important human relapsing malaria, is lagging behind. In the case of the most deadly human malaria P. falciparum, unprecedented high levels of protection have been obtained by immunization with live sporozoites under accompanying chemoprophylaxis, which prevents the onset of blood-stage malaria. Such an approach has not been fully evaluated for relapsing malaria. Here, in the P. cynomolgi-rhesus macaque model for relapsing malaria, we employ the parasites’ natural relapsing phenotype to self-boost the immune response against liver-stage parasites, following a single-shot high-dose live sporozoite vaccination. This approach resulted in sterile protection against homologous sporozoite challenge in three out of four animals in the group that was also exposed for several days to blood stages during primary infection and relapses. One out of four animals in the group that received continuous chemoprophylaxis to abort blood-stage exposure was also protected from sporozoite challenge. Although obtained in a small number of animals as part of a Proof-of-Concept study, these results suggest that limited blood-stage parasite exposure may augment protection in this model. We anticipate our data are a starting point for further research into correlates of protection and extrapolation of the single-shot approach to develop efficacious malaria vaccines against relapsing human malaria.

Abstract A better understanding of schizophrenia subtypes is necessary to stratify the patients according to clinical attributes. To explore the genomic architecture of schizophrenia symptomatology, we analyzed blood co-expression modules and their association with clinical data from patients in remission after a first episode of schizophrenia. In total, 91 participants of the 2EPS project were included. Gene expression was assessed using the Clariom S Human Array. Weighted-gene co-expression network analysis (WGCNA) was applied to identify modules of co-expressed genes and to test its correlation with global functioning, clinical symptomatology, and premorbid adjustment. Among the 25 modules identified, six modules were significantly correlated with clinical data. These modules could be clustered in two groups according to their correlation with clinical data. Hub genes in each group showing overlap with risk genes for schizophrenia were enriched in biological processes related to metabolic processes, regulation of gene expression, cellular localization and protein transport, immune processes, and neurotrophin pathways. Our results indicate that modules with significant associations with clinical data showed overlap with gene sets previously identified in differential gene-expression analysis in brain, indicating that peripheral tissues could reveal pathogenic mechanisms. Hub genes involved in these modules revealed multiple signaling pathways previously related to schizophrenia, which may represent the complex interplay in the pathological mechanisms behind the disease. These genes could represent potential targets for the development of peripheral biomarkers underlying illness traits in clinical remission stages after a first episode of schizophrenia.

The n-3 polyunsaturated fatty acids (PUFAs) can reduce inflammatory markers and may therefore be useful in obesity management. The aim of this study was to analyze the effect of supplementation with n-3 PUFAs on total fatty acid profile in red blood cells (RBCs), as well as biochemical and inflammatory markers, in subjects with obesity. The study consisted in a randomized placebo-controlled, double-blind clinical trial involving 41 subjects with obesity during a 4-month follow-up. Individuals were randomly assigned to two groups: n-3 PUFA supplementation (1.5 g fish oil) and placebo (1.5 g sunflower oil). Anthropometric, biochemical, dietetic, cytokine and total fatty acid profiles in RBCs were measured. Both groups increased their PUFA intake and DHA incorporation in RBCs. However, the placebo group showed a reduction in serum IL-8 and MCP-1 at the end of the study. A multiple linear regression model adjusted by body fat mass and sex showed that an increase in DHA in RBCs decreased the serum IL-8 levels in both study groups at the end of the study. Our results highlight the role of dietary DHA and n-3 supplementation usefulness in exerting beneficial anti-inflammatory effects.

The feral or volunteer cotton (VC) plants when reach the pinhead squaring phase (5–6 leaf stage) can act as hosts for the boll weevil (Anthonomus grandis L.) pests. The Texas Boll Weevil Eradication Program (TBWEP) employs people to locate and eliminate VC plants growing by the side of roads or fields with rotation crops but the ones growing in the middle of fields remain undetected. In this paper, we demonstrate the application of computer vision (CV) algorithm based on You Only Look Once version 5 (YOLOv5) for detecting VC plants growing in the middle of corn fields at three different growth stages (V3, V6 and VT) using unmanned aircraft systems (UAS) remote sensing imagery. All the four variants of YOLOv5 (s, m, l, and x) were used and their performances were compared based on classification accuracy, mean average precision (mAP) and F1-score. It was found that YOLOv5s could detect VC plants with maximum classification accuracy of 98% and mAP of 96.3% at V6 stage of corn while YOLOv5s and YOLOv5m resulted in the lowest classification accuracy of 85% and YOLOv5m and YOLOv5l had the least mAP of 86.5% at VT stage on images of size 416 × 416 pixels. The developed CV algorithm has the potential to effectively detect and locate VC plants growing in the middle of corn fields as well as expedite the management aspects of TBWEP.

Background Schizophrenia is a complex disorder involving deficits in both cognitive and emotional processes. Specifically, a marked deficit in cognitive control has been found, which seems to increase when dealing with emotional information. Aims With the aim of exploring the possible common links behind cognitive and emotional deficits, two versions of the emotional Stroop task were administered. Method In the cognitive-emotional task, participants had to name the ink colour (while ignoring the meaning) of emotional words. In contrast, the emotional-emotional task consisted of emotional words superimposed on emotional faces, and the participants had to indicate the emotional valence of the faces. Fifty-eight participants (29 in-patients diagnosed with schizophrenia and 29 controls) took part in the study. Results Patients and controls showed similar response times in the cognitive-emotional task; however, patients were significantly slower than controls in the emotional-emotional task. This result supports the idea that patients show a more pronounced impairment in conflict modulation with emotional content. Besides, no significant correlations between the tasks and positive or negative symptoms were found. This would indicate that deficits are relatively independent of the clinical status of patients. However, a significant correlation between the emotional-emotional task and cognitive symptoms was found. Conclusions These findings suggest a restricted capacity of patients with schizophrenia to deal with the attentional demands arising from emotional stimuli.

First episode of psychosis (FEP) patients display a wide variety of metabolic disturbances at onset, which might underlie these patients’ increased morbidity and early mortality. Glycemic abnormalities have been previously related to pharmacological agents; however, recent research highlights the impact of early life events. Birth weight (BW), an indirect marker of the fetal environment, has been related to glucose abnormalities in the general population over time. We aim to evaluate if BW correlates with glucose values in a sample of FEP patients treated with different antipsychotics. Two hundred and thirty-six patients were included and evaluated for clinical and metabolic variables at baseline and at 2, 6, 12, and 24 months of follow-up. Pearson correlations and linear mixed model analysis were conducted to analyze the data. Antipsychotic treatment was grouped due to its metabolic risk profile. In our sample of FEP patients, BW was negatively correlated with glucose values at 24 months of follow-up [r=-0.167, p=0.037]. BW showed a trend towards significance in the association with glucose values over the 24-month period (F=3.22; p=0.073) despite other confounders such as age, time, sex, body mass index, antipsychotic type, and chlorpromazine dosage. This finding suggests that BW is involved in the evolution of glucose values over time in a cohort of patients with an FEP, independently of the type of pharmacological agent used in treatment. Our results highlight the importance of early life events in the later metabolic outcome of patients.

Delusions are one of the most classical symptoms described in schizophrenia. However, despite delusions are often emotionally charged, they have been investigated using tasks involving non-affective material, such as the Beads task. In this study we compared 30 patients with schizophrenia experiencing delusions with 32 matched controls in their pattern of responses to two versions of the Beads task within a Bayesian framework. The two versions of the Beads task consisted of one emotional and one neutral, both with ratios of beads of 60:40 and 80:20, considered, respectively, as the “difficult” and “easy” variants of the task. Results indicate that patients showed a greater deviation from the normative model, especially in the 60:40 ratio, suggesting that more inaccurate probability estimations are more likely to occur under uncertainty conditions. Additionally, both patients and controls showed a greater deviation in the emotional version of the task, providing evidence of a reasoning bias modulated by the content of the stimuli. Finally, a positive correlation between patients’ deviation and delusional symptomatology was found. Impairments in the 60:40 ratio with emotional content was related to the amount of disruption in life caused by delusions. These results contribute to the understanding of how cognitive mechanisms interact with characteristics of the task (i.e., ambiguity and content) in the context of delusional thinking. These findings might be used to inform improved intervention programs in the domain of inferential reasoning.

BackgroundDeficits in psychosocial functioning are present in the early stages of psychosis. Several factors, such as premorbid adjustment, neurocognitive performance, and cognitive reserve (CR), potentially influence functionality. Sex differences are observed in individuals with psychosis in multiple domains. Nonetheless, few studies have explored the predictive factors of poor functioning according to sex in first-episode psychosis (FEP). This study aimed to explore sex differences, examine changes, and identify predictors of functioning according to sex after onset.Materials and methodsThe initial sample comprised 588 individuals. However, only adults with non-affective FEP (n = 247, 161 males and 86 females) and healthy controls (n = 224, 142 males and 82 females) were included. A comprehensive assessment including functional, neuropsychological, and clinical scales was performed at baseline and at 2-year follow-up. A linear regression model was used to determine the predictors of functioning at 2-year follow-up.ResultsFEP improved their functionality at follow-up (67.4% of both males and females). In males, longer duration of untreated psychosis (β = 0.328, p = 0.003) and worse premorbid adjustment (β = 0.256, p = 0.023) were associated with impaired functioning at 2-year follow-up, while in females processing speed (β = 0.403, p = 0.003), executive function (β = 0.299, p = 0.020) and CR (β = −0.307, p = 0.012) were significantly associated with functioning.ConclusionOur data indicate that predictors of functioning at 2-year follow-up in the FEP group differ according to sex. Therefore, treatment and preventative efforts may be adjusted taking sex into account. Males may benefit from functional remediation at early stages. Conversely, in females, early interventions centered on CR enhancement and cognitive rehabilitation may be recommended.

This paper explores the key factors influencing mental health professionals' behavioral intention to adopt virtual humans as a means of affect recognition training. Therapies targeting social cognition deficits are in high demand given that these deficits are related to a loss of functioning and quality of life in several neuropsychiatric conditions such as schizophrenia, autism spectrum disorders, affective disorders, and acquired brain injury. Therefore, developing new therapies would greatly improve the quality of life of this large cohort of patients. A questionnaire based on the second revision of the Unified Theory of Acceptance and Use of Technology (UTAUT2) questionnaire was used for this study. One hundred and twenty-four mental health professionals responded to the questionnaire after viewing a video presentation of the system. The results confirmed that mental health professionals showed a positive intention to use virtual reality tools to train affect recognition, as they allow manipulation of social interaction with patients. Further studies should be conducted with therapists from other countries to reach more conclusions.

Plastic shopping bags are often discarded as litter and can be carried away from roadsides and become tangled on cotton plants in farm fields. This rubbish plastic can end up in the cotton at the gin if not removed before harvest. These bags may not only cause problems in the ginning process but might also become embedded in cotton fibers, reducing the quality and marketable value. Therefore, detecting, locating, and removing the bags before the cotton is harvested is required. Manually detecting and locating these bags in cotton fields is a tedious, time-consuming, and costly process. To solve this, this paper shows the application of YOLOv5 to detect white and brown colored plastic bags tangled at three different heights in cotton plants (bottom, middle, top) using Unmanned Aircraft Systems (UAS)-acquired Red, Green, Blue (RGB) images. It was found that an average white and brown bag could be detected at 92.35% and 77.87% accuracies and a mean average precision (mAP) of 87.68%. Similarly, the trained YOLOv5 model, on average, could detect 94.25% of the top, 49.58% of the middle, and only 5% of the bottom bags. It was also found that both the color of the bags (p < 0.001) and their height on cotton plants (p < 0.0001) had a significant effect on detection accuracy. The findings reported in this paper can help in the autonomous detection of plastic contaminants in cotton fields and potentially speed up the mitigation efforts, thereby reducing the amount of contaminants in cotton gins.

Objective To measure plasma levels of malondialdehyde (MDA), a marker of oxidative stress (OS), in patients with major depressive disorder (MDD) compared with healthy control (HC) subjects in order to determine if it is a possible biomarker of depression. Methods This prospective cross-sectional study enrolled patients with MDD and HC subjects. The plasma levels of MDA were measured using a commercially-available colorimetric assay. Results A total of 30 patients with MDD and 20 HC subjects with similar sex, age and body mass index distribution were enrolled in the study. Patients with MDD had significantly higher plasma levels of MDA than the HC subjects. Receiver operating characteristic curve analysis for plasma MDA levels in patients with MDD demonstrated an area under the curve of 0.9767. Conclusion The findings of this current study provide further evidence of the role pathophysiological relevance of OS and MDA in MDD. This study provides the basis for the use of MDA as a biomarker for MDD.

Abstract Plasmodium falciparum apical membrane antigen 1 (PfAMA1) is a candidate malaria vaccine antigen expressed on merozoites and sporozoites. PfAMA1’s polymorphic nature impacts vaccine-induced protection. To address polymorphism, three Diversity Covering (DiCo) protein sequences were designed and tested in a staggered phase Ia/b trial. A cohort of malaria-naive adults received PfAMA1-DiCo adjuvanted with Alhydrogel® or GLA-SE and a cohort of malaria-exposed adults received placebo or GLA-SE adjuvanted PfAMA1 DiCo at weeks 0, 4 and 26. IgG and GIA levels measured 4 weeks after the third vaccination are similar in malaria-naive volunteers and placebo-immunised malaria-exposed adults, and have a similar breadth. Vaccination of malaria-exposed adults results in significant antibody level increases to the DiCo variants, but not to naturally occurring PfAMA1 variants. Moreover, GIA levels do not increase following vaccination. Future research will need to focus on stronger adjuvants and/or adapted vaccination regimens, to induce potentially protective responses in the target group of the vaccine.

High levels of school dropout are a major burden on the educational and professional development of a country’s inhabitants. A country’s prosperity depends, among other factors, on its ability to produce higher education graduates capable of moving a country forward. To alleviate the dropout problem, more and more institutions are turning to the possibilities that artificial intelligence can provide to predict dropout as early as possible. The difficulty of accessing personal data and privacy issues that it entails force the institutions to rely on the Academic Data of their students to create accurate and reliable predictive systems. This work focuses on creating the best possible predictive model based solely on academic data, and accordingly, its capacity to infer knowledge must be maximised. Thus, Feature Engineering and Instance Engineering techniques such as dealing with redundancy, significance of the features, correlation, cardinality features, missing values, creation or elimination of features, data fusion, removal of unuseful instances, binning, resampling, normalisation, or encoding are applied in detail before the construction of well-known models such as Gradient Boosting, Random Forest, and Support Vector Machine along with an Ensemble of them at different stages: prior to enrolment, at the end of the first semester, at the end of the second semester, at the end of the third semester, and at the end of the fourth semester. Through the construction of these predictive models that serve as inputs to a decision support system, the application of effective dropout prevention policies can be applied.

Background: Even though excessive adipose tissue is related to chronic metabolic disturbances, not all subjects with excess weight (EW) display metabolic alterations, and not all normal-weight (NW) subjects have a metabolically healthy (MH) phenotype, probably due to gene-environment interactions. The aim of this study was to investigate the interaction effects of ADIPOQ and PPARG genetic variants in NW and EW individuals with different metabolic phenotypes. Methods: Data on 345 adults from western Mexico were analyzed. The individuals were classified into NW and EW groups according to body mass index, and were categorized as MH or metabolically unhealthy (MUH), considering homeostatic model assessment insulin resistance (HOMA-IR) and National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) cut-off points for glucose, triglycerides, high-density lipoprotein cholesterol, and blood pressure. Subjects with ≤1 altered parameter were classified as MH. The single nucleotide polymorphisms (SNPs) –11377C>G, –11391G>A, +45T>G, and +276G>T for ADIPOQ and Pro12Ala for PPARG were analyzed by allelic discrimination. High-molecular-weight adiponectin isoform levels were measured by ELISA. Results: Lower serum adiponectin levels were associated with the MUH phenotype in EW subjects. NW subjects with the GG or TG genotype for the +45T>G SNP had reduced odds of the MUH phenotype. Individuals who carried two copies of the GG haplotype at the –11391G>A and –11377C>G SNPs for ADIPOQ had lower serum adiponectin levels than those with zero copies. Conclusion: In this population, lower serum adiponectin levels were found in the EW-MUH phenotype, and no differences were observed between the NW-MH and the EW-MH phenotype. In addition, the +45T>G SNP was associated with reduced odds of the MUH phenotype.

El objetivo del estudio consistió en evaluar el impacto de la Escuela de Directores (EDCE) en la calidad de los aprendizajes, medidos por medio de los resultados en las Pruebas Nacionales de octavo grado del nivel básico (hoy segundo grado del secundario) de República Dominicana. El estudio se fundamentó en el enfoque cuantitativo, caracterizado por la medición numérica y análisis mediante el uso de técnicas estadísticas. Se tomó una muestra de 400 centros educativos, en la que la mitad (200) era dirigida por egresados de la EDCE y tomada, aleatoriamente, de las primeras cohortes del programa, capacitadas en el 2012 y 2013. La otra mitad de la muestra se tomó de manera intencional, siendo cada centro el más próximo a cada uno de los primeros. Los centros dirigidos por egresados de la EDCE, conformaron el grupo experimental y el segundo, el grupo control. Se realizó un análisis comparativo de los resultados de Pruebas Nacionales entre el período 2011 y 2016 de ambos grupos. Los resultados indicaron que en el año escolar 2011-2012, el rendimiento del estudiantado, en el grupo experimental, mostraba similitud con el del grupo control. En cada año siguiente, se observó un mayor y ascendente rendimiento en los centros educativos que conformaron el grupo experimental. Se concluyó que el estudiantado de centros educativos dirigidos por egresados de la EDCE, tiene mejor aprendizaje que el estudiantado de centros educativos dirigidos por otros directores.

Higher Education plays a principal role in the changing and complex world of today, and there has been rapid growth in the scientific literature dedicated to predicting students' academic success or risk of dropout thanks to advances in Data Mining techniques. Degrees such as Computer Science in particular are in ever greater demand. Although the number of students has increased, the number graduating is still not enough to provide society with as many as it requires. This study contributes to reversing this situation by introducing an approach that not only predicts the dropout risk or students' performance but takes action to help both students and educational institutions. The focus is on maximizing graduation rates by constructing a Recommender System to assist students with their selection of subjects. In particular, the challenge is addressed of constructing reliable Recommender Systems on the basis of data which are both sparse and few in quantity, imbalanced, and anonymized, and which might have been stored under imperfect conditions. This approach is successfully applied to create a Recommender System using a real-world dataset from a public Spanish university containing performance data of a Computer Science degree course, demonstrating its successful application in real environments. The construction of a support system based on that approach is described, its results are evaluated, and its implications for students' academic achievement, and for institutions' graduation rates are discussed. Through the construction of this decision support system for students, we intend to increase the graduation rates and lower the dropout rate.

Background: Antipsychotic medications are the first-line treatment for schizophrenia. However, non-adherence is frequent despite its negative impact on the course of the illness. In response, we aimed to investigate social media posts about antipsychotics to better understand the online environment in this regard.Methods: We collected tweets containing mentions of antipsychotic medications posted between January 1st 2019 and October 31st 2020. The content of each tweet and the characteristics of the users were analyzed as well as the number of retweets and likes generated.Results: Twitter users, especially those identified as patients, showed an interest in antipsychotic medications, mainly focusing on the topics of sexual dysfunction and sedation. Interestingly, paliperidone, despite being among one of the newest antipsychotics, accounted for a low number of tweets and did not generate much interest. Conversely, retweet and like ratios were higher in those tweets asking for or offering help, in those posted by institutions and in those mentioning cognitive complaints. Moreover, health professionals did not have a strong presence in tweet postings, nor did medical institutions. Finally, trivialization was frequently observed.Conclusion: This analysis of tweets about antipsychotic medications provides insights into experiences and opinions related to this treatment. Twitter user perspectives therefore constitute a valuable input that may help to improve clinicians' knowledge of antipsychotic medications and their communication with patients regarding this treatment.

Grasshoppers are integral parts of rangeland ecosystems but also have the potential to reach population densities high enough (outbreaks) to cause serious economic damage from forage loss and affect adjacent crops. The objective of this study was to investigate the efficacy of treating grasshopper population hotspots with a liquid insecticide using a remotely piloted aerial application system (RPAAS), as opposed to fixed-wing aircraft, which is the most common method currently in use. A liquid insecticide, Sevin XLR PLUS (containing carbaryl), was applied on replicated 4.05-hectare (10-acre) plots with an RPAAS on a ranch in New Mexico. Our results demonstrated that Sevin XLR PLUS significantly suppressed grasshopper populations over a 14-day period (normalized population reduction was 79.11 ± 8.35% SEM) and quite rapidly (mostly by day 3) compared to untreated controls. These results are comparable to those achieved with fixed-wing aircraft. The RPAAS covered the whole test area in a single flight in approximately 5 min, making these population hotspot treatment applications relatively rapid, potentially more cost-effective, and more targeted in comparison to fixed-wing aircraft. Before adoption as an application method option, further research is recommended on using an RPAAS to cover larger areas in combination with using diflubenzuron-based insecticides, which are often preferred.

Abstract Background Concerns about financial sustainability of health systems have promoted the adoption of risk-sharing agreements. Nevertheless, few insights have been derived, due to their confidentiality. The purpose of this study is to analyze to what extent these agreements have been implemented in Spain and the importance of several clinical and management variables concerning their use. We also explore whether risk-sharing agreements promote the adoption of personalized medicine. We give a descriptive analysis based on a questionnaire sent to members of the Spanish Society of Hospital Pharmacy, asking about the implementation of risk-sharing contracts in their hospitals. Results There were 80 replies. Implementation of risk-sharing agreements was high (90%), being oncology, neurology, dermatology and infectious diseases the main specialties. The most relevant variables were the number of units of medication per year (89%) in price-volume agreements, and the efficacy and uncertainty of treatments (over 75%) in pay-for-performance agreements. Price-volume agreements were suitable for both conventional and personalized medicine and pay-for-performance more specific for personalized medicine. Paying for performance promotes genetic testing (85%). Conclusions The results suggest health authorities should encourage the assessment of financial and health outcomes of real-world contracts of conventional and personalized medicine to better know the variables influencing their use.

The use of workflows to manage business or administrative process has been increasing since the end of the past century. Administrative workflows proved useful in large companies and public institutions with strict hierarchical organizations. In order to use them adequately in different areas or departments of a hierarchical organization, they must be adapted to their particular conditions while complying with the general regulations of the process established at the top level. Any department of an organization can add activities, can remove them, and can choose concrete users to perform them and to set the data managed in the activities, as long as the adapted process does not fail to comply with the restrictions established at the generic level. This problem, called hierarchical adaptation problem, also implies establishing the appropriate measures to implement when the general regulation is changed. Such measures must maintain the consistency among the different levels by means of the propagation of the changes to all the adapted processes. To solve this problem, this paper presents the hierarchical adaptation method, which is an ontology-based method to define the rules to satisfy by a generic adaptable workflow. Additionally, it establishes the rules to satisfy the adaptations of the specification ontology. Moreover, it provides the operations facilitating both adaptations of administrative workflows and propagations of changes.

Immune-mediated inflammatory diseases (IMIDs) represent a large group of diseases (Crohn’s, ulcerative colitis, psoriasis, lupus, and rheumatoid arthritis) evidenced by systemic inflammation and multiorgan involvement. IMIDs result in a reduced quality of life and an economic burden for individuals, health care systems, and countries. In this brief descriptive review, we will focus on some of the common biological pathways of these diseases from the point of view of psychoneuroimmunoendocrinology (PNIE). PNIE consists of four medical disciplines (psychology, nervous system, immune system, and endocrine system), which are key drivers behind the health–disease concept that a human being functions as a unit. We examine these drivers and emphasize the need for integrative treatments that addresses the disease from a psychosomatic point of view.

Abstract Background Exacerbations of chronic obstructive pulmonary disease (COPD) are associated with loss of lung function and poor outcomes for patients. However, there are limited data on the time course of changes in forced expiratory volume in 1 s (FEV1) preceding the first reported symptom and after the start of an exacerbation. Methods WISDOM was a multinational, randomized, double-blind, active-controlled, 52-week study in patients with severe-to-very severe COPD. Patients received triple therapy (long-acting muscarinic antagonist and long-acting β2-agonist/inhaled corticosteroid [ICS]) for 6 weeks, and were randomized to continue triple therapy or stepwise withdrawal of the ICS (dual bronchodilator group). After suitable training, patients performed daily spirometry at home using a portable, battery-operated spirometer. In the present post hoc analysis, patients who continued to perform daily home spirometry and completed at least one measurement per week for a 56-day period before and after the start of a moderate or severe exacerbation were included. Missing values were imputed by linear interpolation (intermittent), backfilling (beginning) or carry forward (end). Exacerbation onset was the first day of a reported symptom of exacerbation. Results Eight hundred and eighty-eight patients in the WISDOM study had a moderate/severe exacerbation after the complete ICS withdrawal visit; 360 of them contributed at least one FEV1 measure per week for the 8 weeks before and after the event and are included in this analysis. Mean daily FEV1 began to decline from approximately 2 weeks before the onset of symptoms of an exacerbation, dropping from 0.907 L (mean Days − 56 to − 36 before the exacerbation) to 0.860 L on the first day of the exacerbation. After the exacerbation, mean FEV1 improved but did not return to pre-exacerbation levels (mean Days 36–56 after the exacerbation, 0.875 L). The pattern of FEV1 changes around exacerbations was similar in the triple therapy and dual bronchodilator groups, and a similar pattern was seen in moderate and severe exacerbations when analysed separately. Conclusions Mean lung function starts to decline prior to the first reported symptoms of an exacerbation, and does not recover to pre-exacerbation levels 8 weeks after the event. Trial registration WISDOM (ClinicalTrials.gov number, NCT00975195).

The role of the cannabinoid receptor 2 (CNR2) is still poorly described in sensory epithelia. We found strong cnr2 expression in hair cells (HCs) of the inner ear and the lateral line (LL), a superficial sensory structure in fish. Next, we demonstrated that sensory synapses in HCs were severely perturbed in larvae lacking cnr2. Appearance and distribution of presynaptic ribbons and calcium channels (Cav1.3) were profoundly altered in mutant animals. Clustering of membrane-associated guanylate kinase (MAGUK) in post-synaptic densities (PSDs) was also heavily affected, suggesting a role for cnr2 for maintaining the sensory synapse. Furthermore, vesicular trafficking in HCs was strongly perturbed suggesting a retrograde action of the endocannabinoid system (ECs) via cnr2 that was modulating HC mechanotransduction. We found similar perturbations in retinal ribbon synapses. Finally, we showed that larval swimming behaviors after sound and light stimulations were significantly different in mutant animals. Thus, we propose that cnr2 is critical for the processing of sensory information in the developing larva.

Abstract Objective We aim to explore the differential presence of symptoms of anxiety, depression, and acute stress between men and women during the COVID‐19 outbreak, and to study the relationship between these symptoms and two environmental variables, coexistence, and violence. Methods We conducted a cross‐sectional study starting on March 29 to April 5, 2020, based on a national online survey using snowball sampling techniques. Symptoms of anxiety (Hamilton Anxiety Scale), depression (Beck Depression Inventory), and acute stress (Acute Stress Disorder Inventory) were assessed. Differences in the presence of symptoms and the relationship of coexistence and domestic violence were evaluated from a gender perspective. Results Men showed significant lower mean (SD) in anxiety, depression, and acute stress levels than women [HARS, 14.1 (9.8) versus. 18.4 (10.2), F = 56.2, p

The ability to recognise facial emotions is essential for successful social interaction. The most common stimuli used when evaluating this ability are photographs. Although these stimuli have proved to be valid, they do not offer the level of realism that virtual humans have achieved. The objective of the present paper is the validation of a new set of dynamic virtual faces (DVFs) that mimic the six basic emotions plus the neutral expression. The faces are prepared to be observed with low and high dynamism, and from front and side views. For this purpose, 204 healthy participants, stratified by gender, age and education level, were recruited for assessing their facial affect recognition with the set of DVFs. The accuracy in responses was compared with the already validated Penn Emotion Recognition Test (ER-40). The results showed that DVFs were as valid as standardised natural faces for accurately recreating human-like facial expressions. The overall accuracy in the identification of emotions was higher for the DVFs (88.25%) than for the ER-40 faces (82.60%). The percentage of hits of each DVF emotion was high, especially for neutral expression and happiness emotion. No statistically significant differences were discovered regarding gender. Nor were significant differences found between younger adults and adults over 60 years. Moreover, there is an increase of hits for avatar faces showing a greater dynamism, as well as front views of the DVFs compared to their profile presentations. DVFs are as valid as standardised natural faces for accurately recreating human-like facial expressions of emotions.

The hepatopulmonary syndrome (HPS) is defined by the presence of pulmonary gas exchange abnormalities due to intrapulmonary vascular dilatations in patients with chronic liver disease. Changes in DNA methylation reflect the genomic variation. Since liver transplant (LT) reverts HPS we hypothesized that it may be associated with specific liver epigenetic changes. Thus, the aim of this study was to investigate the role of the liver epigenome in patients with HPS. We extracted DNA from paraffin embedded liver tissue samples from 10 patients with HPS and 10 age-, sex- and MELD (Model for End-stage Liver Disease)-matched controls. DNA methylation was determined using the 850K array (Illumina). Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify modules related to defining physiologic characteristics of HPS. Only 12 out of the 20 liver biopsies (7 HPS and 5 controls) had sufficient quality to be analyzed. None of the 802,688 DNA probes analyzed in the case control comparison achieved a significant False Discovery Rate (FDR). WGCNA identified 5 co-methylated gene-modules associated to HPS markers, mainly related to nervous and neuroendocrine system, apoptotic processes, gut bacterial translocation, angiogenesis and vascular remodeling ontologies. To conclude, HPS is associated with nervous/neuroendocrine system and vascular remodeling related liver epigenetic changes.

Background: Childhood maltreatment (CM) is thought to play a key role in the etiology and course of psychotic disorders (PD). In addition, CM is related to neurobiological and clinical characteristics that can lead to poor social functioning. However, the extent to which CM and social functioning are directly associated in individuals with PD, is unclear. Therefore, we aim to systematically review the literature to provide an estimate on the strength of the association between CM and different domains of social functioning in PD and to summarize potential moderators and mediators of this association. Methods and analysis: To identify relevant studies, we will systematically search the following databases: Pubmed (Medline), PsycInfo, Embase, Web of Science (Core Collection), and Pilots (trauma), manually search reference lists and contact experts in the field. Studies will be included if they investigate and report on the association between CM (exposure) and social functioning (outcome) in adults with PD. Two independent reviewers will screen titles, abstracts and full texts according to eligibility criteria, perform data extraction and assess study quality according to a modified version of the Newcastle–Ottawa Scale. Analysis: Effect estimates will be pooled in a meta-analysis. Heterogeneity and publication bias will be assessed and the effects of potential moderators (genetic factors, type of diagnosis, duration of illness, type of CM and age at the time of CM exposure) will be analyzed using meta-regressions. Candidate moderators and mediators (neurocognition, cognitive schemas, comorbidities, stress sensitivity, attachment) will be also examined qualitatively. Ethics and dissemination: Because this review will make use of already published data, ethical approval will not be sought. This work has the potential to inform upcoming investigations on the association between the exposure to CM in PD and social functioning. PROSPERO registration number CRD42020175244.

Major depressive disorder (MDD) is an incapacitating condition characterized by loss of interest, anhedonia and low mood, which affects almost 4% of people worldwide. With rising prevalence, it is considered a public health issue that affects economic productivity and heavily increases health costs alone or as a comorbidity for other pandemic non-communicable diseases (such as obesity, cardiovascular disease, diabetes, inflammatory bowel diseases, etc.). What is even more noteworthy is the double number of women suffering from MDD compared to men. In fact, this sex-related ratio has been contemplated since men and women have different sexual hormone oscillations, where women meet significant changes depending on the age range and moment of life (menstruation, premenstruation, pregnancy, postpartum, menopause…), which seem to be associated with susceptibility to depressive symptoms. For instance, a decreased estrogen level promotes decreased activation of serotonin transporters. Nevertheless, sexual hormones are not the only triggers that alter neurotransmission of monoamines and other neuropeptides. Actually, different dietary habits and/or nutritional requirements for specific moments of life severely affect MDD pathophysiology in women. In this context, the present review aims to descriptively collect information regarding the role of malnutrition in MDD onset and course, focusing on female patient and especially macro- and micronutrient deficiencies (amino acids, ω3 polyunsaturated fatty acids (ω3 PUFAs), folate, vitamin B12, vitamin D, minerals…), besides providing evidence for future nutritional intervention programs with a sex-gender perspective that hopefully improves mental health and quality of life in women.

Miconia is a highly invasive plant species with incipient plants occupying remote areas of Hawaiian watersheds. Management of these incipient plants is integral to current containment strategies. Herbicide Ballistic Technology (HBT) has been used for 8 years from helicopters as a precision approach to target individual plants. We have developed a prototype HBT applicator integrated onto an unmanned aircraft system, HBT-UAS, which offers the same precision approach with a semi-automated flight plan. Inclusion of the HBT payload resulted in statistically significant deviations from programmed flight plans compared to the unencumbered UAS, but the effect size was lower than that observed for different stages of flight. The additional payload of the HBT-UAS resulted in a large reduction in available flight time resulting a limited range of 22 m. The projectile spread of the HBT-UAS, within a 2–10 m range, had a maximum CEP of 1.87–5.58 cm. The most substantial limitation of the current prototype HBT-UAS is the available flight time. The use of larger capacity UAS and potential for beyond visual line of sight operations would result in a substantial improvement in the serviceable area and utility of the HBT-UAS for containment of invasive plants.

Dural arteriovenous fistulas (dAVFs) in the anterior cranial fossa represent only 10% of all dAVFs. Anterior fossa or ethmoidal dAVFs have a unique angioarchitecture, with cortical vein drainage, associated with a significant risk of hemorrhage. Treatment of ethmoidal dAVFs is challenging due to the ethmoidal artery origin and branch of the ophthalmic artery (OpA), which makes this lesion a difficult target for endovascular route.We present management of a 59-year-old female with a recent history of migraine. Angiography demonstrated bilateral supply with shunting directly into the superior sagittal sinus (SSS) at its origin adjacent to the crista galli via ethmoidal arteries arising from both OpA, and a 5 mm basilar tip aneurysm projecting postero-superiorly. Since the fistula had a higher risk of hemorrhage, aneurysm occlusion was deferred for treatment at a later time. Endovascular occlusion of the dAVF was not feasible due to the high risk of catherization of OpA, and the patient agreed to microsurgical treatment. A bifrontal craniotomy with ligation of SSS in its proximal third was required to allow access to the crista galli. After occlusion of the arterial feeders, clips were placed to occlude the origin of SSS and avoid fistula recurrence. The patient was discharged without complications, and post-operative angiography showed complete occlusion of the fistula and no further shunting into the SSS. This facilitated future antiplatelet therapy for endovascular treatment of the basilar aneurysm. Keywords: Dural arteriovenous fistula, Ethmoidal arteries, Bifrontal approach

El presente proyecto tiene como objetivo la selección de un aerogenerador de baja potencia para el abastecimiento energético de una casa-tipo, situada en un lugar aislado de la Patagonia Argentina. Con tal fin, se ejecutó un relevamiento de la potencia instalada en el hogar y el consumo estimado del mismo, como así también un análisis del recurso eólico en la zona, tomando mediciones periódicas de la velocidad del viento, velocidad de ráfagas y dirección mediante una estación meteorológica instalada en el lugar. Los datos obtenidos fueron procesados para calcular el potencial eólico y seleccionar a partir de ellos, el aerogenerador.

Timely, accurate maps of invasive plant species are critical for making appropriate management decisions to eliminate emerging target populations or contain infestations. High-resolution aerial imagery is routinely used to map, monitor, and detect invasive plant populations. While conventional image interpretation involving human analysts is straightforward, it can require high demands for time and resources to produce useful intelligence. We compared the performance of human analysts with a custom Retinanet-based deep convolutional neural network (DNN) for detecting individual miconia (Miconia calvescens DC) plants, using high-resolution unmanned aerial system (UAS) imagery collected over lowland tropical forests in Hawai’i. Human analysts (n = 38) examined imagery at three linear scrolling speeds (100, 200 and 300 px/s), achieving miconia detection recalls of 74 ± 3%, 60 ± 3%, and 50 ± 3%, respectively. The DNN achieved 83 ± 3% recall and completed the image analysis in 1% of the time of the fastest scrolling speed tested. Human analysts could discriminate large miconia leaf clusters better than isolated individual leaves, while the DNN detection efficacy was independent of leaf cluster size. Optically, the contrast in the red and green color channels and all three (i.e., red, green, and blue) signal to clutter ratios (SCR) were significant factors for human detection, while only the red channel contrast, and the red and green SCRs were significant factors for the DNN. A linear cost analysis estimated the operational use of a DNN to be more cost effective than human photo interpretation when the cumulative search area exceeds a minimum area. For invasive species like miconia, which can stochastically spread propagules across thousands of ha, the DNN provides a more efficient option for detecting incipient, immature miconia across large expanses of forested canopy. Increasing operational capacity for large-scale surveillance with a DNN-based image analysis workflow can provide more rapid comprehension of invasive plant abundance and distribution in forested watersheds and may become strategically vital to containing these invasions.

Abstract Background A 12-week, double-blind, parallel, multi-center randomized controlled trial in 316 adult patients with major depressive disorder (MDD) was conducted to evaluate the effectiveness of pharmacogenetic (PGx) testing for drug therapy guidance. Methods Patients with a CGI-S ≥ 4 and requiring antidepressant medication de novo or changes in their medication regime were recruited at 18 Spanish public hospitals, genotyped with a commercial PGx panel (Neuropharmagen®), and randomized to PGx-guided treatment (n = 155) or treatment as usual (TAU, control group, n = 161), using a computer-generated random list that locked or unlocked psychiatrist access to the results of the PGx panel depending on group allocation. The primary endpoint was the proportion of patients achieving a sustained response (Patient Global Impression of Improvement, PGI-I ≤ 2) within the 12-week follow-up. Patients and interviewers collecting the PGI-I ratings were blinded to group allocation. Between-group differences were evaluated using χ2-test or t-test, as per data type. Results Two hundred eighty patients were available for analysis at the end of the 12-week follow-up (PGx n = 136, TAU n = 144). A difference in sustained response within the study period (primary outcome) was not observed (38.5% vs 34.4%, p = 0.4735; OR = 1.19 [95%CI 0.74-1.92]), but the PGx-guided treatment group had a higher responder rate compared to TAU at 12 weeks (47.8% vs 36.1%, p = 0.0476; OR = 1.62 [95%CI 1.00-2.61]), and this difference increased after removing subjects in the PGx-guided group when clinicians explicitly reported not to follow the test recommendations (51.3% vs 36.1%, p = 0.0135; OR = 1.86 [95%CI 1.13-3.05]). Effects were more consistent in patients with 1–3 failed drug trials. In subjects reporting side effects burden at baseline, odds of achieving a better tolerability (Frequency, Intensity and Burden of Side Effects Rating Burden subscore ≤2) were higher in the PGx-guided group than in controls at 6 weeks and maintained at 12 weeks (68.5% vs 51.4%, p = 0.0260; OR = 2.06 [95%CI 1.09-3.89]). Conclusions PGx-guided treatment resulted in significant improvement of MDD patient’s response at 12 weeks, dependent on the number of previously failed medication trials, but not on sustained response during the study period. Burden of side effects was also significantly reduced. Trial registration European Clinical Trials Database 2013-002228-18 , registration date September 16, 2013; ClinicalTrials.gov NCT02529462 , retrospectively registered: August 19, 2015.

Purpose: The aim of the research was to examine if adolescents can develop abilities of democratic interaction through Community Theatre. Design/methodology: Firstly, two instruments were applied, a questionnaire covering socio-moral problems, of the students and a Questionnaire, covering the Educational Ideologies of the professors. Then, a theatrical intervention was realized at middle-school students in Aguascalientes City, based on the objectives of the formation of Citizenship as stated at the National Curriculum. Findings: Students themselves stated a change in their attitude during the intervention, which was also observed and registered at the field diary and at the written evaluations. For this reason, we claim that Community theater could be used as a transdisciplinary method for teaching democratic skills, as it creates a public sphere where the students can develop democratic behavior. Research limitations: Further studies on the subject are required, especially concerning the time and the sample as the research had a two-month duration and was conducted at a limited population. Practical implications: The contribution of this project was the introduction of Community Theatre at the service of the Citizenship Education, promoting the artistic education as a means of the formal education in the search for personal and social democratic development and could be considered in an educational reform.

BackgroundImpairments in social cognition have been described in several psychiatric and neurological disorders. Given the importance of the relationship between social cognition and functioning and quality of life in these disorders, there is a growing interest in social cognition remediation interventions. The aim of this study was to carry out a systematic mapping review to describe the state of the art in social cognition training and remediation interventions.MethodsPublications from 2006 to 2016 on social cognition interventions were reviewed in four databases: Scopus, PsycINFO, PubMed and Embase. From the initial result set of 3229 publications, a final total of 241 publications were selected.ResultsThe study revealed an increasing interest in social cognition remediation interventions, especially in the fields of psychiatry and psychology, with a gradual growth in the number of publications. These were frequently published in high impact factor journals and underpinned by robust scientific evidence. Most studies were conducted on schizophrenia, followed by autism spectrum disorders. Theory of mind and emotional processing were the focus of most interventions, whilst a limited number of studies addressed attributional bias and social perception. Targeted interventions in social cognition were the most frequent practice in the selected papers, followed by non-specific treatment interventions and broad-based interventions.ConclusionsResearch in social cognition remediation interventions is growing. Further studies are needed on attributional bias and social perception remediation programs, while the comparative efficacy of different interventions also remains unclear.

Neck circumference (NC) and wrist circumference (WrC) have been proposed as practical and inexpensive tools with the capacity to indicate metabolic alterations to some extent. Nevertheless, their application in the pediatric population is relatively recent. Thus, the aim of this scoping review was to review and analyze the reported evidence regarding the correlation of NC and WrC with metabolic alterations in the pediatric stage. The literature search was performed in January 2021 in seven indexes and databases. A total of 26 articles published between 2011 and 2020 were included. Most significant results were grouped into three categories: serum lipid profile, glucose homeostasis, and blood pressure. The parameter that showed the most significant results regardless of the anthropometric indicator analyzed for association was blood pressure. In contrast, total cholesterol and LDL-cholesterol showed non-significant associations along with conflicting results. We conclude that the use of NC and WrC, in addition to other well-established indicators, could facilitate the identification of metabolic alterations, specifically in plasma insulin and blood pressure. In fact, further studies are required to address the potential use of NC and WrC as predictors of early metabolic alterations, especially in countries with a fast-growing prevalence in obesity.

The identification of a new generation of adaptive strategies for deep brain stimulation (DBS) will require the development of mixed hardware–software systems for testing and implementing such controllers clinically. Towards this aim, introducing an operating system (OS) that provides high-level features (multitasking, hardware abstraction, and dynamic operation) as the core element of adaptive deep brain stimulation (aDBS) controllers could expand the capabilities and development speed of new control strategies. However, such software frameworks also introduce substantial power consumption overhead that could render this solution unfeasible for implantable devices. To address this, in this work four techniques to reduce this overhead are proposed and evaluated: a tick-less idle operation mode, reduced and dynamic sampling, buffered read mode, and duty cycling. A dual threshold adaptive deep brain stimulation algorithm for suppressing pathological oscillatory neural activity was implemented along with the proposed energy saving techniques on an energy-efficient OS, YetiOS, running on a STM32L476RE microcontroller. The system was then tested using an emulation environment coupled to a mean field model of the parkinsonian basal ganglia to simulate local field potential (LFPs) which acted as a biomarker for the controller. The OS-based controller alone introduced a power consumption overhead of 10.03 mW for a sampling rate of 1 kHz. This was reduced to 12 μW by applying the proposed tick-less idle mode, dynamic sampling, buffered read and duty cycling techniques. The OS-based controller using the proposed methods can facilitate rapid and flexible testing and implementation of new control methods. Furthermore, the approach has the potential to become a central element in future implantable devices to enable energy-efficient implementation of a wide range of control algorithms across different neurological conditions and hardware platforms.

Background: Recently, an emerging flavivirus, Usutu virus (USUV), has caused an epidemic among birds in Europe, resulting in a massive die-off in Eurasian blackbirds. Currently found only in Europe and Africa, it can be envisioned that Usutu virus will follow the path of other flaviviruses, like West Nile virus and Zika virus, and will spread via its mosquito vectors and bird hosts to other parts of the world. Several cases of human infections by Usutu virus have already been published. Anticipating this spread, development of an efficacious vaccine would be highly desirable. Method: This study describes the production in E. coli, purification, and refolding of a partial USUV envelope protein. Prior to immunization, the protein was characterized using size exclusion chromatography, transmission electron microscopy and dynamic light scattering, showing the limited presence of virus-like structures, indicating that the protein solution is probably a mixture of mono and multimeric envelope proteins. Results: Immunizations of two rabbits with the refolded E-protein fraction, mixed with a strong adjuvant, resulted in the generation of neutralizing antibodies, as evidenced in an in vitro assay. Discussion: The way forward towards a subunit vaccine against Usutu virus infection is discussed.