The objective of the present study is to evaluate and analyze styles and dimensions of attachment, its possible relations and how they become evident in the people involved in this study, For accomplishing it, a quantitative focus methodology was applied of descriptive type and crosscut, in which 105 Clinical Psychology university career students participated. The CaMir-R questionnaire was applied to evaluate the different styles and dimensions of attachment. In regard to the main found results it can be mentioned that - as much in men as in women -. the disorganized attachment is the most representative, followed by safe attachment. In turn, there exists a significant difference established by gender in these dimensions: family worry, parental permissiveness and infantile traumatism; In addition, as much positive correlations like refusals ones among the renowned dimensions were observed, where bulges out the positive link of self-sufficiency and resentment against the parents with the infantile traumatism. It came to an end that the dependence between the type of relation and the predisposal of offering a sure attachment on behalf of the progenitor, it will generate in the person an atmosphere of satisfaction and a capacity to face the penalties of life everyday.

Prostate cancer is the second leading cause of death in males in America, with advanced prostate cancers exhibiting a 5-year survival rate of only 32%. Castration-resistance is often developed during the course of treatment, though its influences require further understanding. This study explores the human microbiome for its implications in castration-resistance and metastasis in prostate cancer. RNA sequencing data was downloaded for bone and soft tissue biopsies of patients with metastatic castration-resistant prostate cancer. These sequences were mapped to bacterial sequences to yield species-level abundance approximations. Numerous species were found to correlate to the expression of known markers of castration-resistance, including AR, PI3K, and AKT. Castration-resistance-associated signaling pathways were also enriched with these species, including PI3K-AKT signaling and endocrine resistance. For their implications in cancer aggression and metastasis, cancer stem cell markers were further explored for relation to these species. EGFR and SLC3A2 were widely downregulated with greater abundance of most species. Our results suggest that the microbiome is heavily associated with castration-resistance and stemness in prostate cancer. By considering the microbiome’s importance in these factors, we may better understand the highly aggressive and highly invasive nature of prostate cancer, allowing for needed improvement in the treatment of this disease.

The overlap of visual items in data visualization techniques is a known problem aggravated by data volume and available visual space issues. Several methods have been applied to mitigate occlusion in data visualizations, such as Random Jitter, Transparency, Layout Reconfiguration, Focus+Context Techniques, etc. This paper aims to present a comparative study to read visual variables values with partial overlap. The study focuses on categorical data representations varying the percentage limits of partial overlap and the number of distinct values for each visual variable: Hue, Lightness, Saturation, Shape, Text, Orientation, and Texture. A computational application generates random scenarios for a unique visual pattern target to perform location tasks. Each scenario presented the visual items in a grid layout with 160 elements (10 x16), each visual variable had from 3 to 5 distinct values encoded, and the partial overlap percentage applied, represented by a gray square in the center o each grid element, were 0% (control), 50%, 60%, and 70%. Similar to the preliminary tests, the tests conducted in this study involved 48 participants organized into four groups, with 126 tasks per participant, and the application captured the response and time for each task performed. The result analysis indicates that the Hue, Lightness, and Shape visual variables are robust to high percentages of occlusion and gradual increase in encoded visual values. The Text visual variable show promising results for accuracy, and resolution time was a bit higher than the last visual variables mentioned. In contrast, the Texture visual variable presented lower accuracy to high levels of occlusion and more different visual encoding values. At last, the Orientation and Saturation visual variables got the highest error and worst perfomance rates during the tests.

Coccidioidomycosis (Valley Fever) is a disease caused by inhalation of Coccidioides spp. This neglected tropical disease of the Americas has substantial public health impact despite its geographic restriction to desert areas of the southwestern U.S., Mexico, Central and South America. The incidence of this infection in California and Arizona has been increasing over the past fifteen years. The burden of disease in outside the U.S. remains poorly understood. Several large cities are within the endemic region in the U.S. Coccidioidomycosis accounts for 25,000 hospital admissions per year in California. While most cases of coccidioidomycosis resolve spontaneously, up to 40% are severe enough to require anti-fungal treatment, and a significant number disseminate beyond the lungs. Disseminated infection, especially involving the meninges, is fatal without appropriate treatment. Infection with Coccidioides spp. is protective against a second infection, so vaccination seems biologically plausible. This review of efforts to develop a vaccine against coccidioidomycosis focuses on vaccine approaches and the difficulties in identifying protein antigen/adjuvant combinations that protect in experimental mouse models. Although the quest for a vaccine has not yet resulted in a clinically useful product, scientific efforts of vaccine development pave the way for future success.

Pheidole oxyops Forel, 1908 is a generalist ant, which forages actively for plant debris to dead arthropods. In addition, its nest has an entrance that allows the ants gather resources passively by capturing falling preys into the nest. Our objective was to verify if different day periods, temperature and residual soil accumulation (ground pile in the side of nest entrance) could influence the patterns of foraging activity. Foraging activities were registered in the morning, afternoon and twilight. We measured direction and vector of trails, air temperature and humidity during foraging events. Our results showed that foraging routes are independent of residual soil accumulation and other nearby nests. However, air temperature and the time daily period are significant factors to foragers’ exits. Higher air temperatures influenced negatively the exits. In the period of the afternoon, the ants do not show any preference for routes, different from the morning and twilight. In addition, foraging activities were significantly more frequent during twilight period. Leaving the nest at twilight could allow ants foraging in an environment with less exposition to potential predators and competitors. Moreover, it may be also related to opportunism to hunt other nocturnal insects.

Carbonate reservoirs, influenced by depositional and diagenetic processes and characterized by features like faults and vugs that impact storage capacity, require more than traditional Borehole Imaging logs (BHI) for accurate porosity data. This data is essential for geological assessments, production forecasting, and reservoir simulations. This work aims to address this limitation by developing methods to measure and monitor the sustainability of carbonate reservoirs and exploring the application of sustainability principles to their management. The study integrates BHI and conventional logs from two wells to classify porosity-based facies within the Barra Velha Formation (BVF) in the Santos Basin. The methodology involves four steps: (i) analyzing conventional logs; (ii) segmenting BHI logs; (iii) integrating conventional and segmented BHI logs using Self-Organizing Maps (SOM); and (iv) interpreting the resulting classes. Matrix porosity values and non-matrix pore sizes categorize the porosity into four facies (A to D). Facies A has high non-matrix porosity with 14,560 small megapores, 5,419 large megapores, and 271 gigapores (71.9%, 26.76%, and 1.34% of the 20,250 pores, respectively). Facies B shows moderate non-matrix porosity with 8,669 small megapores, 2,642 large megapores, and 33 gigapores (76.42%, 23.29%, and 0.29% of the 11,344 pores, respectively) and medium matrix porosity. Facies C exhibits low non-matrix porosity with 7,749 small megapores, 2,132 large megapores, and 20 gigapores (78.27%, 21.53%, and 0.20% of the 9,901 pores, respectively) and medium matrix porosity. Facies D has low non-matrix porosity with 9,355 small megapores, 2,346 large megapores, and 19 gigapores (79.82%, 20.02%, and 0.16% of the 11,720 pores, respectively) and low matrix porosity. The novelty of this work lies in integrating data from two sources to classify porosity across the Pre-Salt reservoir interval, serving as a proxy for preliminary litho-facies identification without core data. This study advances our understanding of carbonate reservoir sustainability and heterogeneity, offering valuable insights for robust, sustainable reservoir characterization and management in the context of global environmental and geological changes.

In this paper, solar irradiance and wind speed forecasts were performed considering time horizons ranging from 10 min to 60 min, under a 10 min time-step. Global horizontal irradiance (GHI) and wind speed were computed using four forecasting models (Random Forest, k-Nearest Neighbours, Support Vector Regression, and Elastic Net) to compare their performance against two alternative dynamic ensemble methods (windowing and arbitrating). Forecasting models and dynamic forecasting ensembles were implemented in Python for performance evaluation. The performance comparison between the prediction models and the dynamic ensemble methods was carried out by evaluating the RMSE, MAE, R² and MAPE, to evaluate whether the dynamic ensemble forecasting method obtained greater. According to the results obtained windowing dynamic ensemble method was the most efficient among the tested. For the wind speed data, by varying its parameter λ (from 1 to 100), a variable performance profile was obtained, where from λ =1 to λ = 74, windowing proved to be the most efficient, reaching maximum efficiency for λ = 19. Windowing was the best method for the GHI analysis, reaching its best performance for λ = 1. The efficiency gain using windowing was 0.56% when using the wind speed model and 1.96% for GHI.

Microbial populations involved in forming the distinctive precipitates of the S, Fe, Mn, and Ca cycles in the San Diego River watershed reflect an interplay between mineralogy of the rocks in the watershed, sparse rainfall, ground- and surface-water anoxia, and runoff of high sulfate, treated imported water. In the less developed headwaters, Temescal Creek tributary emerges from pyrite-bearing metamorphic rocks, and thus exhibits both an oxidized Fe and reduced S cycle. In the middle reaches, the river moves through developed land where treated, imported high sulfate Colorado River water enters from urban runoff. Mast Park surrounded by caliche-bearing sedimentary rocks is a site where marl is precipitating. Cobbles in riffles in the river are coated black with Mn oxide. When the river encounters deep-seated volcanic bedrock, it wells up to precipitate both Fe and Mn oxides at Old Mission Dam. Then, directly flowing through caliche-laced sedimentary rocks, Birchcreek tributary precipitates tufa. Further downstream, at a site that periodically receives full sunlight, a sulfuretum sets up during the summer when the river is deoxygenated. Such a rich geochemistry results in activity of iron and manganese oxidizing bacteria, sulfur oxidizers and reducers, and cyanobacteria precipitating calcareous marl and tufa.

Although Eulerian approaches are standard in computational acoustics, they are less effective for certain classes of problems like bubble acoustics and combustion noise. A different approach for solving acoustic problems is to compute with individual particles following particle motion. In this paper, a Lagrangian approach to model sound propagation in moving fluid is presented and implemented numerically, using three meshfree methods to solve the Lagrangian acoustic perturbation equations (LAPE) in the time domain. The LAPE split the fluid dynamic equations into a set of hydrodynamic equations for the motion of fluid particles and perturbation equations for the acoustic quantities corresponding to each fluid particle. Then, three meshfree methods, the smoothed particle hydrodynamics (SPH) method, the corrective smoothed particle (CSP) method, and the generalized finite difference (GFD) method, are introduced to solve the LAPE and the linearized LAPE (LLAPE). The SPH and CSP methods are widely used meshfree methods, while the GFD method based on the Taylor series expansion can be easily extended to higher orders. Applications to modeling sound propagation in steady or unsteady fluids in motion are outlined, treating a number of different cases in one and two space dimensions. A comparison of the LAPE and the LLAPE using the three meshfree methods is also presented. The Lagrangian approach shows good agreement with exact solutions. The comparison indicates that the CSP and GFD method exhibit convergence in cases with different background flow. The GFD method is more accurate, while the CSP method can handle higher Courant numbers.

Baía de Todos os Santos is the second largest bay in Brazil and is home to important ecosystems, including estuarine systems and mangroves. However, studies on the seasonal variability of its soil properties and composition are still scarce. For this study, soil and leaf samples were seasonally collected from mangrove forests at four sites (Cacha Prego, Ponta Grossa, Ilha de Maré, and Pitinga), which are representative of different environmental conditions within the BTS. Soil physicochemical properties, soil composition and partition of Fe forms were determined, and analysis of minerals by Scanning Electron Microscope, was performed on soil samples. Isotopic ratios (δ13C, δ15N) were also determined on soil and leaf samples. Soils showed significant spatial and temporal changes affecting both their properties (pH, Eh) and their composition (TOC, pyrite and Fe oxyhydroxide contents). Clear spatial changes were observed in redox potential, significantly affecting the concentrations of the different geochemical forms of Fe, particularly the concentrations of crystalline oxyhydroxydes and pyrite in one of the studied sites. In three of the study sites, pyrite crystals showed clear evidence of degradation associated with sandy soils. Finally, δ13C and N/C ratios in soils seem to suggest a mixed origin of organic matter.

The performance of the presurgical test (preSurg) for temporal lobe epilepsy (TLE) was evaluated via video-electroencephalography (VEEG), electroencephalography (EEG), 99mTc-HmPAO single-photon emission tomography (SPECT) and 1.5 T magnetic resonance imaging (MRI) in a group of 112 men (37.0 ± 1.1 years) and 106 women (39.7 ± 1.1 years) operated on for TLE. The epileptic zone (EZ) was adequately identified to determine whether the patient reached an Engel I grade (EI) at least one year postop. Accuracy was evaluated by the coefficient α, ranging from 3 (when result = EZ) to 2 (result in the same hemisphere as the EZ), 1 (noninformative result) or 0 (EZ in the contralateral hemisphere). The simplicity of diagnosis was defined as the number of preSurg surgeries needed to identify the EZ. EI was obtained in 85.8% of patients even though 42.2% of patients had noninformative MRI results. For preSurg α was (mean ± SEM) = VEEG (2.83 ± 0.04) > MRI (2.14 ± 0.08) > EEG (1.87 ± 0.09) > SPECT (1.71 ± 0.09). The accuracy (combination of sensitivity and specificity) was calculated as follows: VEEG (0.797) > MRI (0.518) > EEG (0.446) > SPECT (0.360). The likelihood positive ratio was greater, and the likelihood negative ratio was lower for VEEG. The most relevant factor for the regression model was VEEG (3.106) > MRI (2.558) > EEG (1.905), and the factors were not significantly related to SPECT. EZs in EI patients with low simplicity were identified mainly by VEEG. A very good postoperative outcome can be obtained even in TLE patients with no lesions on MRI. The VEEG is the most reliable preSurg test and may be the only reliable test for patients with very low simplicity (i.e., difficult).single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

The continuing mutability of the SARS-CoV-2 virus can result in failures of diagnostic assays. To address this, we describe a generalizable bioinformatics-to-biology pipeline developed for calibration and quality assurance of inactivated SARS-COV-2 variant panels provided to Radical Acceleration of Diagnostics programs (RADx)-radical program awardees. Heuristic genetic analysis based on variant-defining mutations demonstrated the lowest genetic variance in the Nucleocapsid protein (Np)- C-terminal domain (CTD) across all SARS-COV-2 variants. We then employed the Shannon entropy method on (Np) sequences collected from the major variants, verifying the CTD with lower entropy (less prone to mutations) than other Np regions. Polyclonal and monoclonal antibodies were raised against this target CTD antigen and used to develop an Enzyme-linked immunoassay (ELISA) test for SARS-CoV-2. Blinded Viral Quality Assurance (VQA) panels comprising of UV-inactivated SARS CoV-2 variants (XBB.1.5, BF.7, BA.1, B.1.617.2, and WA1) and distractor respiratory viruses (CoV 229E, CoV OC43, RSV A2, RSV B, IAV H1N1, and IBV) were assembled by the RADx-rad Diagnostics core and tested using the ELISA described here. The assay tested positive for all variants with high sensitivity (Limit of Detection: 1.72-8.78 ng/mL) and negative for the distractor virus panel. Epitope mapping for the monoclonal antibodies identified a twenty amino acid antigenic peptide on the Np-CTD that an in-silico program also predicted for the highest antigenicity. This work provides a template for a bioinformatics pipeline to select genetic regions with a low propensity for mutation (low Shannon entropy) to develop robust ‘pan-variant’ antigen-based assays for viruses prone to high mutational rates.

Background and Objectives: The Temperament Evaluation of Memphis, Pisa, Paris and San Diego Autoquestionnaire (TEMPS-A) is designed to assess affective temperaments. The short version of TEMPS-A (TEMPS-A-SV) was translated into diverse languages for its broad application in research and clinical settings. However, no study was conducted to validate the Korean version of TEMPS-A-SV among patients with mood disorders. The purpose of this study is to examine the reliability and validity of the TEMPS-A-SV in mood disorder patients of the Korean population. Materials and Methods: In this cross-sectional retrospective study, a total of 715 patients (267 patients with major depressive disorder, 94 patients with bipolar disorder I, and 354 patients with bipolar disorder II) completed the Korean TEMPS-A-SV. Cronbach's alpha and McDonald’s omega was used to assess reliability. Exploratory factor analysis (EFA) was also performed. Spearman's correlation coefficient was used to examine associations between five temperaments. The difference in five temperament scores between gender or diagnosis groups were analyzed, and the correlation between five temperament scores and age were tested. Results: The Korean TEMPS-A-SV displayed good internal consistency (α = 0.65–0.88, ω = 0.66–0.9) and significant correlations between the subscales except one (correlation between hyperthymic and anxious). Using EFA, a two-factor structure was produced: Factor I (cyclothymic, depressive, irritable, and anxious) and Factor II (hyperthymic). The cyclothymic temperament score differed by gender and the anxious temperament score was significantly correlated with age. All the temperaments, except for irritable temperament, showed significant differences between diagnosis groups. Conclusions: Overall, our findings indicate that TEMPS-A-SV is a valid and reliable measure of estimating affective temperaments among Koreans. Our results confirm validity of TEMPS-A-SV among Korean patients with mood disorders. However, more study is required on affective temperaments and associated characteristics in people with mood disorders.

Coronavirus disease 2019 (COVID-19) has detrimental multi-system consequences. Symptoms may appear during the acute phase of infection, but literature on long-term recovery of young adults after mild-to-moderate infection is lacking. Heart rate variability (HRV) allows observation of autonomic nervous system (ANS) modulation post SARS-CoV-2 infection. Additionally, physical activity (PA) helps improve ANS modulation, where investigation of PA influence on ANS recovery is vital to reduce risk and severity of symptoms. Clinicians may use this research to aid development of non-medication interventions. At baseline, 18 control (CT) and 20 post-COVID-19 (PCOV) participants were observed where general amnamnesis was performed, followed by HRV and PA assessment. 10 CT and 7 PCOV subjects returned for follow-up (FU) evaluation 6 weeks after complete immunization (2 doses) and assessments were repeated. Over the follow-up period, decrease in sympathetic (SNS) activity (mean heart rate: p=0.0024, CI=-24.67- -3.26; SNS index: p=0.0068, CI=-2.50- -0.32) and increase in parasympathetic (PNS) activity (mean RR:p=0.0097, CI=33.72-225.51; PNS index: p=0.0091, CI=-0.20-1.47) were observed. At follow-up, HRV was not different between groups (p>0.05). Additionally, no differences were observed in PA between moments and groups. This study provides evidence of ANS recovery after SARS-CoV-2 insult in young adults over a follow-up period, independent of changes in PA.

New proposals for the equation of state of four- and five-dimensional hard-hypersphere mixtures in terms of the equation of state of the corresponding monocomponent hard-hypersphere fluid are introduced. Such proposals (which are constructed in such a way so as to yield the exact third virial coefficient) extend, on the one hand, recent similar formulations for hard-disk and (three-dimensional) hard-sphere mixtures and, on the other hand, two of our previous proposals also linking the mixture equation of state and the one of the monocomponent fluid but unable to reproduce the exact third virial coefficient. The old and new proposals are tested by comparison with published molecular dynamics and Monte Carlo simulation results and their relative merit is evaluated.

The straight leg raise test (SLR) has been proposed to detect increased nerve mechanosensitivity of the lower limbs in individuals with low back pain or leg-related low back pain. However, its validity in the diagnosis of lumbosacral radiculopathy show very variable results. The aim of this study was to analyse the diagnostic validity of the SLR including well defined diagnostic criteria in a sample of participants in phase III with suspicion of lumbar radiculopathy using the nerve conduction studies (NDS) as the reference standard. A phase III diagnostic accuracy study was designed. 142 individuals with suspected lumbosacral radiculopathy referred for NCS participated in the study. Each participant was tested with NCS and SLR. SLR was considered positive using three diagnostic criteria. The sensitivity of the SLR for the criterion 3 was 89.02% (CI 81.65-96.40), the specificity was 25.00% (CI 13.21-36.79), and the +LR and -LR were 1.19 (CI 1.01-1.40) and 0.44 (0.21-0.94), respectively. SLR showed limited validity in the diagnosis of lumbosacral radiculopathy. The incorporation of more objective diagnostic criteria (asymmetry in range of motion or localization of symptoms) improved diagnostic validity but the imprecision of the confidence intervals limited the interpretation of the results.

Injuries of repetitive efforts constitute one of the prime causes of absenteeism in the workplace, have bear a considerable cost for the public health system and can cast doubt on the sustainability of a company. The objective of this paper is to build, in the researchers, the needed knowledge to choose a set of relevant scientific articles about repetitive strain injuries in the poultry meat industry, aiming identify characteristics in those scientific publications that have the potential to contribute on the topic of this paper. The research is characterized as exploratory-descriptive, draws on primary and secondary data sources. The study involves the application of a method for selection and analysis of the selected articles. To this end, the method utilized was the Knowledge Development Process – Constructivist (Proknow-C) as theoretical intervention instrument. Within the process development, it was obtained a portfolio of 16 articles aligned to the research and scientifically recognized with the main periodicals, papers, authors and keywords. The ProKnow-C process allowed identify opportunities in the literature about injuries in the poultry meat industry and showed opportunities for research future. This paper, under the constructivist perspective, presents a structured process to build, in the researcher, the necessary knowledge to identification, selection and analysis of relevant scientific articles relating to research context and, for these articles, find prominences and opportunities for a research theme without similar publications.

Agricultural crops productivity is heavily influenced by the strength of their seeds. Current methods for testing seed vigor, such as the germination rate and tetrazolium test, rely on time-consuming human visual inspections. Computer Vision, a crucial technology in smart production processes, offers an automated alternative and is increasingly applied in digital agriculture processes. Here we propose a method that combines YOLOv8 and morphological analysis of seeds using X-ray images to aid seed quality analysts in classifying seed lots based on their physiological potential. We examined the internal morphology of three seed lots and generated X-ray images to train a YOLOv8-based model with a post-segmentation module. This model assessed various parameters such as the total seed area, area filled by the embryo and endosperm, length, width, and calculated the percentage occupied by the embryo and endosperm in relation to the total seed area. Subsequently, seeds were classified into four categories based on the internal area occupied by the endosperm and embryo. Our findings reveal the robust performance of the YOLOv8 model in segmenting and classifying despite the challenges posed by a relatively small dataset. Notably, the proposed model achieved an impressive accuracy of up to 95.6% in identifying and segmenting the endosperm over 1,500 epochs with just 15 training images. The endosperm/seed area ratio, particularly within the 50-60% range covering over 50% of the samples, emerged as a significant metric for evaluating the viability of seed batches.

(1) Background: The diagnosis of lumbosacral radiculopathy involves anamnesis, assessment of sensitivity and strength, diagnostic imaging—usually magnetic resonance imaging (MRI)—and electrodiagnostic testing (EDX), typically electromyography (EMG) and electroneurography (ENG). MRI evaluates the structures supporting the spinal cord, while EDX evaluates root functionality. The present study aimed to analyze the concordance of MRI and EDX findings in patients with clinically suspected radiculopathy. Additionally, we investigated the comparison between these two reference tests and various clinical variables and questionnaires. (2) Methods: We designed a prospective epidemiological study of consecutive cases with an observational, descriptive, cross-sectional, and double-blind nature following the STROBE guidelines, encompassing 142 patients with clinical suspicion of lumbosacral radiculopathy. (3) Results: Of the sample, 58.5% tested positive for radiculopathy using EDX as the reference test, while 45.8% tested positive using MRI. The comparison between MRI and EDX in the diagnosis of radiculopathy in patients with clinical suspicion was not significant; the overall agreement was 40.8%. Only the years with symptoms were comparatively significant between the positive and negative radiculopathy groups as determined by EDX. (4) Conclusion: The comparison between lumbar radiculopathy diagnoses in patients with clinically suspected pathology using MRI and EDX as diagnostic modalities did not yield statistically significant findings. MRI and EDX are complementary tests assessing different aspects in patients with suspected radiculopathy; degeneration of the structures supporting the spinal cord does not necessarily imply root dysfunction.

Vocational interest inventories are widely used by career counselors to help individuals to make career choices. The most common approach to assess vocational interests is based on verbal or textual stimuli. However, some of them are based on pictorials to overcome reading limits and provide additional information about the working environment and the activities related to a particular job. This article aims to present two studies on the development and first validation of the Multilingual Iconographic Professional Interest Inventory (MIPII) on two samples, one composed of 792 high-school students, and one composed of 366 middle school students. The inventory aimed to assesses the vocational interests of people over 19 areas by illustrations representing 95 jobs, five for each one, combined with their title in six different languages (Arabic, German, English, Spanish, French and Italian in this order). Both illustrations and titles are provided separately in the male and female version on the same page.

In the last four years, the evolution and adoption of blockchain and, more generally, distributed ledger systems have shown the affirmation of many concepts and models with significant differences in system governance and suitable applications. This work aims to update the critical analysis of blockchain technologies carried out by our previous contribution to this journal, extending the focus to distributed ledger components and systems. Starting from the topical concept of decentralization, we introduce concepts and building blocks currently adopted in the available systems centering on their functional aspects and impact on possible applications. We present some conceptual framing tools helpful in the application context, and we will propose the concept of process authenticity, which we will discuss through two use cases: blockchain document dematerialization and e-voting.

Unmanned aerial vehicles serving as air base stations (UAV-BSs) are used in telecommunications, when the network is overloaded or unavailable, providing access to users on the ground. Due to its dynamics of providing access to networks in different altitudes, the electromagnetic signal of UAVs suffers losses along the path, thus facing several problems related to transmission, such as: attenuation, fading and distortion. In this work is proposed a 3D positioning strategy for UAVs, taking into account height, coverage radius and flight energy efficiency. Results show that the proposed algorithm is able to position the UAVs in suboptimal locations, providing network access for mobile users, maximizing the number of connected devices in the UAV-BS and saving energy, thus obtaining better performance than the approaches conventional.

In the recent years, tubular nanostructures have been related with immense advances in various fields of science and technology. Considerable research efforts have been centered on the theoretical prediction and manufacturing of non-carbon nanotubes (NTs), which meet modern requirements for the developing of novel devices and systems. In this context, diatomic inorganic nanotubes formed by atoms of elements from the 13th group of the periodic table (B, Al, Ga, In, Tl) and nitrogen (N), have received much research attention. In the present work, the elastic properties of single-walled boron nitride, aluminium nitride, gallium nitride, indium nitride and thallium nitride nanotubes were numerically evaluated using the nanoscale continuum modelling approach (also called molecular structural mechanics). The elastic properties (rigidities, surface Young´s and shear moduli, and Poisson´s ratio) of nitride nanotubes are discussed with respect to the bond length of the corresponding diatomic hexagonal lattice. The results obtained contribute to a better understanding of the mechanical response of nitride compound-based nanotubes, covering a broad range from the well-studied boron nitride NTs to the hypothetical thallium nitride NTs.

There are complex ethical dilemmas inherent in medicine teaching, particularly in clinical prac-tice involving actual patients. Questions must be raised on fulfilling medical students' training needs while still respecting patients' fundamental rights to autonomy and privacy. We aimed to assess patients' perspectives regarding medical students' involvement in their medical care. An observational, cross-sectional study was developed, and an interview-like questionnaire was ap-plied randomly to patients waiting for a consult/admitted to three distinct departments: General Surgery, Obstetrics/Gynaecology, and Infectious Diseases. Of the 77% interviewed patients who reported previous experiences with medical students, only 59% stated that they were asked for consent for their participation and 28% that students had adequately introduced themselves. Pa-tients from Gynaecology/Obstetrics were the ones who reported lower rates of these practices and were also the ones who were most bothered by students' presence, stating that they would refuse students' participation in the future. Male patients received more explanations than female pa-tients regarding the same matters. 35% of patients stated they would feel more comfortable without the medical students' presence. The study shows a need to pay closer attention to ful-filling patients' fundamental rights.

This article provides insight into flow measurement techniques in water injection wells in oil production fields, with a particular focus on the initial phases of operation. Consequently, the method created by Ramey in 1962, originally intended for estimating the temperature of the injection fluid, has been adapted to calculate the flow rate. In this technique, the calculation This procedure is based on the correlation between the thermal flux formed in the well. The discrepancy between the temperatures of the injected liquid and the geothermal temperature of the reservoir is the main source of the systematic errors in Ramey’s technique. To a lesser extent, but still significant, failure to observe the injection time in a fluid variation also results in an error problem that needs the failure to adhere to the scheduled injection time for a fluid alteration also yields a notable error dilemma that needs to be fixed. The reduction of listed systematic errors is the product of the main part of this article.

Obesity is related to the establishment of chronic inflammation and metabolic diseases, but it can be positively influenced by the regular practice of physical activity. The study aimed to compare the anthropometric, metabolic, and inflammatory parameters of physically active Military Police Officers (MPOs) with those who are less physically active. Sixty male MPOs, low activity (n=28) and physically active (n=32) participated. The following parameters were measured: plasma cytokine levels, C-reactive protein (CRP) levels, circulating glucose triglyceride (TAG) and high-density lipoprotein cholesterol (HDL-C) levels, and plasma glutamic oxalacetate transaminase (GOT), glutamic-pyruvate transaminase (GPT), and gamma-glutamyl transferase (GGT) activities. The physically active group presented lower body fat and reduced TAG and IL-8 levels compared to the low activity group. Moreover, a negative correlation between SPE and SBP, DBP, BPM was detected for the physically active group (p<0.05) but not in the low activity group. Furthermore, the physically active group's work time (WT) values were not correlated with the important metabolic markers SBP, DBP, BPM, GLU, TAG (p>0.05) but could be in the low activity group (p<0.05). These findings highlight the fundamental protective role of physical activity in controlling body composition, subclinical inflammation, and cardiovascular risk in MPOs.

MicroRNAs, short non-protein coding RNAs, are overexpressed in GCTs. Circulating levels of germ cell tumor (GCT)- associated miRNAs, such as miR-371a-3p, can be utilized as efficient and cost-effective alternatives in diagnosing and managing patients presenting with GCTs. This quality of miRNAs has demonstrated favorable performance characteristics as a reliable blood-based biomarker with high diagnostic accuracy compared to current serum tumor markers (STMs) including α-fetoprotein (AFP), beta human chorionic gonadotropin (β-hCG), and lactate dehydrogenase (LDH). The conventional STMs exhibit limited specificity and sensitivity. Potential clinical implications of miRNAs include impact on de-escalating or intensifying treatment, detecting recurrence at earlier stages, and lessening the necessity of cross-sectional imaging or invasive tissue biopsy for non-teratomatous GCTs. Here we also highlight the outstanding issues that must be addressed prior to clinical implementation. Standards for measuring circulating miRNAs and determining ideal cutoff values are essential for integration into current clinical guidelines.

The unusual occurrence and developmental diversity of asexual eukaryotes still remain a puzzle. Despite asexual organisms have a theorized two-fold reproductive advantage over sexuals, asexual lineages are rare among multicellular eukaryotes. Justification of such disparity relies on the consequences of a lack of meiosis, which restricts genotype diversity and adaptation to novel conditions while accelerating the genetic degeneration that drives asexual lineages to an early demise. However, evidence indicates asexuals use different strategies to limit negative consequences of ameiosis, and age estimates show some asexual vertebrates and plants are much older than expected. If rapid extinction is not a factor influencing asexuals lifespan, then why asexuals are not more frequent? Here we review traditional ideas and new data and provide a novel unified evolutionary frame to understand the intriguing nature, developmental diversity and maintenance of asexual lineages. As a rule, de novo formation of a functioning asexual genome requires a unique assemblage combining particular sets of genes or gene states to disrupt cellular mechanisms of meiosis and gametogenesis, and affect discrete components of sexuality to produce clonal or hemiclonal offspring. We highlight two usually overlooked but essential conditions to understand the molecular nature of clonal organisms, i.e. a non-recombinant genomic assemblage retaining modifiers of the sexual program, and a complementation between altered reproductive components. These subtle conditions are the basis for physiologically viable and genetically balanced transitions between generations. Genomic and developmental evidence from asexual animals and plants indicates the lack of complementation of molecular changes in the sexual reproductive program is likely the main cause of asexuals' rarity, and can provide an explanatory frame for the developmental diversity and lability of developmental patterns in some asexuals as well as for the discordant time to extinction estimations.

The enantioselective alpha-amination of 1,3-dicarbonyl compounds has been performed using a catalytic system based on deep eutectic solvents (DES) and chiral 2-amino benzimidazole-derived organocatalysts. This procedure avoids the use of toxic volatile organic compounds (VOCs) as a reaction medium, providing access to highly functionalized chiral molecules, which are important intermediates for the natural product synthesis, in a selective and efficient manner. Furthermore, the reaction can be performed on a large scale and recycling the catalytic system is possible for at least five times, leading to a clean, cheap, simple, and scalable procedure that meets most of the criteria required to be a green and sustainable process.

A new formalism is introduced that makes it possible to elucidate the physical and geometric content of quantum spacetime. It is based in the Minimum Group Representation Principle (MGRP). Within this framework new results for entanglement and geometrical/topological phases are found and implemented in cosmological and black hole space-times. Our main results here are: {\bf(i)} We find the Berry phases for inflation and for the cosmological perturbations and express them in terms of the observables, as the spectral scalar and tensor indices, $n_S$ an $n_T$, and the tensor to scalar ratio $r$. The Berry phase for de Sitter inflation is imaginary with the sign describing the exponential acceleration. {\bf(ii)} The pure entangled states in the minimum group (metaplectic) $Mp(n)$ representation for quantum de Sitter space-time and black holes are found. {\bf(iii)} For entanglement, the relation between the Schmidt type representation and the physical states of the $Mp(n)$ group is found: This is a {\it new non-diagonal} coherent state representation complementary to the known Sudarshan diagonal one. {\bf(iv)} Mean value generators of $Mp(2)$ are related to the adiabatic invariant and topological charge of the spacetime (matrix element of the transition $-\infty < t < \infty$). {\bf(v)} The basic {\it even} and {\it odd} $n$-sectors of the Hilbert space are intrinsic to the quantum spacetime and its discrete levels (in particular continuum for $n \rightarrow \infty$), they do not require any extrinsic generation process as the standard Schrodinger cat states, and are {\it entangled}. {\bf(vi)} The gravity or cosmological domains in one side and another of the Planck scale are {\it entangled}. Examples: The quantum primordial trans-Planckian de Sitter vacuum and the classical late de Sitter vacuum today; the central quantum gravity reqion and the external classical gravity region of black holes. The classical and quantum dual gravity regions of the space-time are entangled. {\bf(vii)} The general classical-quantum gravity duality is associated to the Metaplectic $Mp(n)$ group symmetry which provides the complete full covering of the phase space and of the quantum space-time mapped from it.

This article studies electrostatic fields and potentials in the presence of conductors and point charges under the framework of solving Laplace’s equation with specifi ed boundary conditions. The results demonstrate that many problems posed and solved in elementary electrostatics through various heuristics such as the method of images, can be more rigorously treated under the solution framework of Laplace’s equation.

In his best-selling book An Introduction to Probability Theory and its Applications, W. Feller established a way of ending the St. Petersburg Paradox by the introduction of an entrance fee, and provided it for the case in which the game is played with a fair coin. A natural generalization of his method is to establish the entrance fee for the case in which the probability of head is θ (0 < θ < 1/2). The deduction of those fees is the main result of Section 2. We then propose a Bayesian approach to the problem. When the probability of head is θ (1/2 < θ < 1) the expected gain of the St. Petersburg Game is finite, therefore there is no paradox. However, if one takes θ as a random variable assuming values in (1/2,1) the paradox may hold, what is counter-intuitive. On Section 3 we determine a necessary and sufficient condition for the absence of paradox on the Bayesian approach and on Section 4 we establish the entrance fee for the case in which θ is uniformly distributed in (1/2,1), for in this case there is paradox.

This work deals with the evaluation of adhesive single-lap joints using ultrasonic guided waves. An adhesive bonded lap joint can be modelled as a three-layer system made up of two adherents and an adhesive. The propagation of guided waves in the joint is developed from matrix formulations. The behavior of the different guided wave modes that propagate in the bonded region is characterized and it is found that their relative amplitudes can be estimated based on the properties of the incoming wave that propagates in the non-bonded region. It was verified that the excitation of these modes is ruled by the degree in which the shapes of both modes match each other. A 3D simulation of two aluminium bonded plates using 500 kHz ultrasonic transducers in a pitch and catch configuration was implemented using the Matlab k-Wave toolbox. Scattering effects due to some produced defects located in the bond line of the lap joints were simulated. Experimental setup with some artificial defects produced in the aluminum joints were used in order to compare with the simulated. Qualitative agreement was observed for the two approaches. The observed deviation can be due to the different characteristics of the experimental and simulated defects.

Count data analysis presents unique challenges due to its discrete nature, often exhibiting excessive zeros and overdispersion. To address these complexities, count models, such as Poisson regression and Negative Binomial regression, have been developed, enabling modeling and prediction of count-based phenomena. Additionally, it’s important to notice that zero inflation, a phenomenon commonly observed in count data, requires specialized techniques for robust analysis. This article provides an overview of count data and count models, explores zero inflation, introduces Likelihood Ratio Tests, and explains how the Vuong Test can be used as a model selection criteria. Furthermore, we created a Vuong Test implementation from scratch using the Python programming language. This implementation enhances the accessibility and applicability of the Vuong Test in real-world scenarios, providing a valuable contribution to the academic community, since Python didn’t have an implementation of this statistical test.

The aim of this manuscript is to synthesize and characterize novel silylated Sm3+ and Eu3+ complexes and incorporate them into mesoporous silica nanoparticles (MSNs) and dense silica nanoparticles (DSNs). Sm3+ and Eu3+ ion complexes were chosen for their strong UV-visible emission, deep-red luminescence, and effective interaction with bidentate organic ligands, such as 2-thenoyltrifluoroacetone (tta) and 1,10-phenanthroline (phen). Silylated ligands were employed as coupling agents to form covalent bonds between the complexes and an oxide matrix via a conventional sol-gel process. This approach aims to enhance the thermal stability and photophysical properties of the resulting hybrid material compared to free complexes. The new silylated-bidentate ligand complexes, using tta and phen as organic ligands and 3-chloropropyltriethoxysilane as the silylating agent, were characterized by FTIR, luminescence spectroscopy, and luminescence decay. After incorporation into silica nanoparticles, the hybrid materials were characterized by SEM, TEM, DLS, zeta potential, SAXS, porosity, surface area measurements, luminescence spectroscopy, and MTT assay. The results confirm the successful synthesis of new luminescent silylated complexes with high luminescence intensity and their incorporation into silica nanoparticles.

Recent years have shown that traditional regulatory techniques alone are not effective in achieving behavior change in important fields such as environmental sustainability. Governments all over the world have been progressively including behaviourally informed considerations in policy and law-making with the aim of improving the acceptance and impact of sustainability-oriented measures. This led to the arrival of alternative regulatory tools, such as nudges. The effectiveness of nudges for environmental sustainability (green nudges) has been largely reported but the practical and ethical implications are still largely neglected by academic research. In this contribution, “nudges” are conceptually distinguished from “boosts” and their ethical briefly explained. The analysis is made at the light of the current mostly European and US American academic literature.

Biocontainment techniques for genetically modified yeasts (GMYs) are pivotal due to the importance of these organisms for biotechnological processes and also due to the design of new yeast strains by using synthetic biology tools and technologies. Due to the large genetic modifications that many yeast strains display, it is highly desirable to avoid the leakage of GMY cells into natural environments and, consequently, the spread of synthetic genes and circuits by horizontal or vertical gene transfer mechanisms within the microorganisms. Moreover, it is also desirable to avoid that patented yeast gene technologies spread outside the production facility. In this review, it was evaluated the different biocontainment technologies currently available for GMYs. Interestingly, uniplex-type biocontainment approaches (UTBAs), which relies on nutrient auxotrophies induced by gene mutation or deletion, or the expression of simple kill switches apparatus, are still the major biocontainment approaches still in use with GMY. While bacteria like Escherichia coli account for advanced biocontainment technologies based on synthetic biology and multiplex-type biocontainment approaches (MTBAs), GMYs are distant from this scenario due to many reasons. Thus, a comparison of different UTBAs and MTBAs applied for GMY and genetically engineered microorganisms (GEMs) was made, indicating the major advances of biocontainment techniques for GMYs.

Passiflora cincinnata Mast is a plant popularly used in traditional medicine in northeastern Brazil. The present study aimed to evaluate the anti-lipoperoxidative and anti-α-amylase properties, and cytotoxicity of an extract and fraction of passion fruit leaves (P. cincinnata Mast), as well as the antihyperglecemiant activity of the fraction rich in glycosylated flavonoids and showing low cytotoxicity in rats with a postprandial hyperglycaemia condition. The ethyl acetate fraction (F.ACT) of the P. cincinnata leaves presented the best anti-lipoperoxide properties with TBARs 81.49%, 95.48% and 75.62% lower than AAPH, FeSO₄ and H₂O₂ induced controls, respectively, at 200 μg.mL-1. In addition, it presented an anti-α-amylase potential, with a better ability to inhibit the α-amylase enzyme in comparison to the acarbose control (IC₅₀ 6.49 ± 0.11 and 12.01 ± 0.4 μg.mL-1, respectively). The hydroalcoholic extract of P. cincinnata (ExEt) presented high content of total tannins, flavonoids and flavonols. However, F.ACT had the highest concentration of flavonoids among the fractions studied. HPLC analysis of this fraction revealed the presence of the flavonoids isovitexin, orientin and isoorientin. F.ACT showed low to no cytotoxicity below 150 μg.mL-1. Regarding the post-prandial antihyperglycaemic activity of F.ACT, it was observed at 50 and 100 mg.kg-1.

This article presents and discusses analytical data on the scientific publication record from 1910 to 2020 on two topics: "climate" and "climate change/global warming/climate emergency". The goal is to visualize how the publication record on these two topics has evolved over time, from different classification perspectives (year, country, source and organization). Three hypotheses are tested using data collected from Web of Science and various graphical representations of the data. It is found that research output related to the Earth’s contemporary changing climate overtook that of general climate research in 2011, and the publication ratio has been expanding in the last decade. There are significant differences in the publication countries and sources between the two topics, and conversely less significant differences in terms of organizations publishing these works. Differentiation factors that affect the level of research output and engagement on the climate challenge include: island versus landlocked nations, specialized versus general scientific journals, academic versus institutional organizations. The future of the publication records is discussed, such as the emergence of new terms to refer to the climate challenge, such as “climate emergency”.

The Golgi apparatus (GA) dysfunctions in Parkinson’s Disease (PD), neurodevelopmental disorders (NDDs), cancer, and organelle structural biology (OSB) can provide insights into therapeutic targets, gene therapy, and drug design. Primary defects and fragmentation within the GA are implicated in a wide range of neurodegenerative diseases. GA defects typically result in mislocation of proteins, accumulation of undegraded proteins, and impaired glycosylation of proteins. Inhibition of vesicular trafficking by α-synuclein (aSyn) may affect the dopamine-producing neurons and neuromodulators. GA regulates apoptosis during pathological mechanisms of neurological diseases and could provide new avenues in treatments through translation research. PD patients bearing the hereditary E46K disease mutation manifest the clinical picture of parkinsonism. How do we provide high resolution nanoimages of the GA during disease to capture dysfunction? Could we visualize the aSyn traffic jam between vesicles in the organelles ER and GA? OSB is emerging as a field as more technology advances and is more accessible. Structural studies of the GA will advance the field of neurological disease forward with an in depth understanding of dysfunction, fragmentation, and defects. Discoveries of the GA in PD, NDDs, and cancer would break new ground and provide translational medicine data of these diseases. Future research could be visualizing high angle annular dark field-STEM (HAADF-STEM) tomograms, cryogenic electron tomography (cryo-ET), multiplex correlative light and electron microscopy (cryo-CLEM), nanobody-assisted tissue immunostaining for volumetric EM (NATIVE) and using soft X-ray tomography (SXT) and computational reconstruction of the GA.

Every simplification has the potential to add a systematic error to the measured value. Sometimes, the addition does not render the measurement useless. In the case of oil well flow measurements based on the thermal properties of the fluid in the well, the addition of a systematic error of up to 20% can occur if the variation in the internal energy of the fluid and, most importantly, the transient nature of heat transfer in the completion are not taken into account. This error is a mathematical consequence of the simplifications chosen. To work within the first hours of good operation, given the need for immediate application in a prototype water injection well developed and installed at the UFRN, this article presents an analytical solution for calculating the flow rate by solving the differential equations obtained by applying the principles of mass and heat transfer. As a result, at the cost of greater complexity, the systematic error drops to values of less than 1% in the first two hours of operation of the well, as seen throughout this document.

In winter 2008-2009, Lake Occhito, a strategic multiple-uses reservoir in South Italy, was affected by an extraordinary Planktothrix rubescens bloom. P. rubescens is a filamentous potentially toxic cyanobacterium which has recently colonized many environments in Europe. A number of studies is currently available on the use of remote sensing techniques to monitor different fresh water cyanobacteria species. By contrast no specific applications are available on the remote sensing monitoring of P. rubescens. In this paper we present a specific algorithm, based on Water Leaving Reflectances (WLR) from MERIS data, atmospherically corrected using the Aerosol Optical Thickness (AOT) retrieved by MODIS data, to detect P. rubescens blooms. The high accuracy in AOT data, provided by MOD09 surface reflectance product, at 1km spatial resolution, allowed obtaining a good correlation between the WLR and the P. rubescens chlorophyll-a concentrations measured in the field, through multiple stations fluorometric profiles. A modified Normalized Difference Chlorophyll index (NDCI) algorithm is presented. The performance of the proposed algorithm has been successfully compared with other specific algorithms for turbid productive waters. We demonstrated how important is to verify the spectral behaviour of bio-optical parameters in order to develop an ad hoc algorithm that better performs with respect to standard algorithms.

In modern inverter applications, multilevel converters are used thanks to their capability of reducing the passive fi lter volumes, improving the overall THD, sharing the power sources across the several converter cells, and providing a reconfi guration ability in case of failure. However, increasing the number of cells makes more complex the control of the converter. This article proposes a decentralized control technique based on the use of elementary modular controllers, associated with each converter cell and communicating with their close neighbors to obtain the balancing of the powers they supplied. Each modular controller can be dynamically removed or added to allow reconfi guration of the converter for functional safety purpose. This method is applied to a 240V/3A 5-cells Cascaded Full-Bridge Multilevel Converter. The response of the system to load transients and cell voltage disturbances demonstrates the robustness of the proposed decentralized control method. Thanks to the use of modular controllers, the number of levels of the converter can be extended to the order N without adding complexity to its control.

The purpose of this study is to show an automated laser vision correction (LVC) with the transep-ithelial refractive keratectomy (TransPRK) surgery technique. Since more surgical steps have been automated over the years, we have standardized the TransPRK technique. We have been using it since 2010. This paper aims to illustrate the processes that are readily applicable to automation. To meet the patient's expectations and ensure that the patient has uncorrected visual acuity at least equal to the preoperative corrected vision with glasses, patient selection is crucial in refractive surgical procedures. One major benefit of automating the surgery is that it can be performed in a similar way by each surgeon or laser correction centre, so once the standard and results are good, these can be per-formed by different surgeons.

In the end of April nearly 100 cases of children aged between 6 month and 9 years with Kawasaki like disease were reported (mostly in Europe) probably linked to COVID-19. With the increasing awareness of this condition the number of cases reported is increasing worldwide. We aim to sum up the known data about this new entity based on published data (in a case report, a series of 8 cases and in newspapers and society statement) and using our knowledge of classical Kawasaki disease. It seems to be a post infectious disease with an onset between 2-4 weeks after the infection, probably in genetically predisposed children aged between 6 month to 17 years. A very rough estimation of incidence based on current data from Bergamo, Italy, and New York State and a lot assumption is between 0.016% (95% CI:0.013-0.02%) - 0.31% (95% CI: 0.2-0.47%) of infected children. Clinical signs overlaps with Kawasaki disease in some children, but another feature is prominent gastrointestinal manifestations. For the 9 detailed patients most had incomplete presentation for Kawasaki disease (with a mean 1.7 (+/-1.2) criteria per patient for the 5 non fever criterion) and only one had a classical form. In some cases, presentation is closer to toxic shock syndrome or isolated myocarditis. Persistent fever seems to be constant and biological exploration are consistent with inflammation (elevated CRP, ferritin and D-Dimers). Management is described as supportive and children seem to improve rapidly, but can require cardiac or respiratory support. In date of 11 may 2020 there is 4 deaths confirmed linked to these new entities (1 in UK and 3 in New York). Paediatricians and general practitioners need to be aware of these possible evolution following COVID-19 infection. However it seems to be rare and children are probably still spared from most morbidities and mortality linked to COVID-19 infection .There are need of published detailed cohorts to better delineate these entities.

Background: Elevated fasting plasma glucose and visceral fat area (VFA) is highly prevalent in obese adults. This study investigated the associations between systemic arterial hypertension (SAH) and laboratory, anthropometric, heart rate variability (HRV), and obstructive sleep apnea markers. Methods: Cross-sectional study with 95 obese patients treated at Obesity Treatment and Surgery Center, located in Salvador, BA, Brazil. SAH data were obtained from electronic medical records of patients. To evaluate the association of SAH with the predictor variables, the sample was stratified in Normotense Group (NG) and Hypertensive Group (HG), and laboratory markers, body composition, polysomnography data, and HRV were measured. Results: The average age of the NG was 36.3 ± 10.1 and HG 40.4 ± 10.6 years, 73.7% were women in the NG and 57.9% in HG; 82.4% in HG had insulin resistance. In the multivarious logistics regression model with adjustments age, sex, height, and oxyhemoglobin saturation, SAH was inversely associated with fasting plasma glucose mg/dL (odds ratio [OR] = 0.96; 95% interval confidence [CI] = 0.92 - 0.99) and VFA cm² (OR = 0.98; 95% CI = 0.97 - 0.99). The area under curve the VFA was 0.728; CI 95% (0.620 - 0.836) and fasting plasma glucose 0.693; CI 95% (0.582 - 0.804). Conclusions: Lower VFA and fasting plasma glucose concentrations were inversely associated with SAH. These results indicate opportunities to improve the outcome in obese patients through counseling and clinical interventions.

This work deals with a systematic review of literature data concerning the theme of the integrated approach to occupational health and safety management, with particular reference to the programming of assistance plans, which guide the company's organizational choices also by aiming at the principles of the Total Worker Health. In the current regulatory framework on this issue, the UNI ISO 45001: 2018 standard assumes particular relevance, which defines the dynamic approach to occupational health and safety management systems, paying particular attention to external contextual factors that may influence corporate organizational decisions. The adoption of these systems is not mandatory, but allows companies to fulfill their duties in terms of health and safety at work, through an organizational approach aimed at awareness, involvement and participation of all subjects of the company prevention system, overcoming the phase of the mere technological and prescriptive approach, towards a holistic vision of prevention, which places the person at the center of preventive actions. In this context, the role of institutional networks and socio-economic partnerships assumes particular importance, in the activation of territorial assistance interventions to support companies for the improvement of risk management levels. To this end, the importance of verifying the effectiveness of assistance interventions emerges from the scientific debate, through the use of indicators such as quantitative ones for measuring the performance of all phases of the intervention with particular attention to the effects in terms of improved solutions developed.

The leachate discharges generated in sanitary landfills contain many pollutants that are harmful to the environment; treatments are scarce and should be carried out better. The use of coagulation-flocculation processes has been one of the most widely used, but that; Due to the complexity of the characterization of the leachate, the dosing strategy of coagulants and biopolymers needs to be clarified. Therefore, the present study is carried out to determine the doses of coagulants and biopolymers suitable for coagulation-flocculation processes in the treatment of leachates by using computational models of machine learning techniques such as Artificial Neural Networks (ANN); these allow to decrease the operations of the tests of jars in the laboratory; optimizing resources. Through laboratory experimentation, there are real results of the effectiveness of applying biopolymers in leachate treatments at different concentration levels. The laboratory results were taken as input variables for the algorithms used; after the validation and calibration process, we proceeded to estimate predicted data with the computational model, obtaining predictions of optimal doses for treatment with high statistical adjustment indicators. It is verified that the applied coagulation-flocculation treatments reduce the turbidity values in the leachate and contaminants associated with suspended solids. In this way, the jar tests are optimized so that the operational costs decrease without affecting the results of adequate dosing.

Urban cycling is a sustainable transport mode that cities currently try to expand. However, cities still do not take advantage of geospatial technologies to understand cycling mobility based on the behavioural patterns and difficulties faced by cyclists. This study analyses a geospatial dataset crowdsourced by urban cyclists using an experimental geo-game. About 20 participants per city recorded bicycle trips during one week and, by aggregating them, we found not only the cyclists’ preferred streets but also the frictions faced during cycling. We successfully identified 284 places potentially having frictions: 71 in Münster, Germany; 70 in Castelló, Spain; and 143 in Valletta, Malta. At such places, Participants not only recorded bicycle trips but also segments at lower speeds indicating a deviation from an ideal cycling scenario. We described the potential frictions preventing from bicycle commuting based on the distance to bicycle paths, surrounding infrastructure, and location in the urban area.

Turnovers in the National Football League (NFL) occur whenever a team loses possession of the ball due to a fumble, or an interception. Turnovers disrupt momentum of the offensive team, and represent lost opportunities to advance downfield and score. Teams with a positive differential turnover margin in a given game win $70\%$ of the time. Turnovers are statistically rare events, occurring apparently randomly. These characteristics make them difficult to predict. This investigation advances the hypothesis that turnovers are predictable in NFL football. Machine learning models are developed to learn the concept: At any point within a football game, what is the likelihood that a turnover will be observed on the next play from scrimmage? Results presented suggest evidence to support the working hypothesis. Under certain conditions, both fumbles and interceptions can be anticipated at low false discovery rates (less than $15\%$). This approach may be useful to inform in-game strategies to mitigate the negative consequences of turnovers by an offensive team, or to maximize their probability by a defensive squad.

The specific demands inherent to supply chains built upon large IoT systems, make a must the design of a coordinated framework for cyber resilience provisioning intended to guaranteeing trusted supply chains of ICT systems, built upon distributed, dynamic, potentially insecure and heterogeneous ICT infrastructures. As such, the proposed solution is envisioned to deal with the whole supply chain system components, from the IoT ecosystem to the infrastructure connecting them, addressing security and privacy functionalities related to risks and vulnerabilities management, accountability and mitigation strategies as well as security metrics and evidence-based security assurance. In this paper we present FISHY, as a preliminary designed architecture, designed to orchestrate both existing and beyond state-of-the-art security appliances in composed ICT scenarios and also leveraging capabilities of programmable network and IT infrastructure through seamless orchestration and instantiation of novel security services, both in real-time and proactively. The paper also includes a thorough business analysis to go far beyond the technical benefits of a potential FISHY adoption as well as three real-world use cases where to strongly support the envisioned benefits of a FISHY adoption.

Parkinson's disease (PD) is a degenerative disease that affects approximately 6.1 million and is primarily caused by the loss of dopaminergic neurons. Naphthoquinones have several biological activities explored in the literature, including neuroprotective effects. Therefore, this review shows an overview of natural and synthetic naphthoquinones with neuroprotective effects and with potential for the development of molecules for the treatment of PD. Many examples of natural naphthoquinones, such as shikonin, plumbagin and vitamin K, exerted a neuroprotective effect by preventing oxidative stress, in addition to multiple mechanisms. Synthetic naphthoquinones with inhibitory activity on the P2X7 receptor were also found, leading to a neuroprotective effect on Neuro-2a cells. It was found that naphthazarin can act as inhibitors of the MAO-B enzyme. Vitamin K and synthetic naphthoquinones hybrids with tryptophan or dopamine showed inhibition of the aggregation of α-synuclein. A library of synthetic derivatives of juglone and naphthazarin were able to protect Neuro-2a cells against neurodegenerative effects of neurotoxins. We report many examples of naphthoquinones that act in therapeutic pathways for the treatment of PD. In addition, routes for producing synthetic derivatives were also discussed. With the data presented, 1,4-naphthoquinones can be considered a promising class in the treatment of PD.

Apoptosis, necroptosis, and autophagy are cellular mechanisms by which cells are programmed to die under a wide range of physiological and developmental stimuli. A multitude of protein mediators of programmed cell death have been identified and apoptosis, necroptosis, and autophagy signals have been found to utilize common pathways elucidating the proteins involved. This narrative review focuses on caspase-dependent and caspase-independent programmed cell death systems. Included studies of caspase-dependent programmed cell death include extrinsic pathway apoptotic mechanisms including phosphatidylserine (PS), FAS (APO-1/CD95), Tumor Necrosis Factor (TNF) Receptor type 1 (TNF-R1) and TNF-Related Apoptosis-Inducing Ligand (TRAIL) and intrinsic or mitochondrial pathway such as Cytochrome C, the Bcl-2 family of proteins and Smac/Diablo. The Bcl-2 family has apoptotic mediators Bcl-2-associated X protein (Bax) and Bcl-2 homologous antagonist/killer (Bak), Bcl-2-Interacting Protein BIM (Bim), Bcl-2 agonist of cell death (Bad), Bid, Bcl-2 adenovirus E1B 19kDa-interacting protein 1 NIP3 (Bnip3), BMF, HRK, Noxa and PUMA and anti-apoptotic proteins such as Bcl-2 itself, Mcl-1, Bcl-w, A1, and Bcl-XL. Moreover, caspase-independent programmed cell death pathways include the mitochondrial pathway with the protein mediators Apoptosis Inducing Factor (AIF), and Endonuclease G, the pathways Necroptosis, and Autophagy. Understanding programmed cell death from those reported in this review could shed substantial light on the processes of biological homeostasis. In addition, identifying specific proteins involved in these processes is mandatory to identify molecular biomarkers as well as therapeutic targets. This knowledge could provide the ability to modulate the programmed cell death response and could lead to new therapeutic interventions in a wide range of diseases.

Although sharks have a fundamental role in maintaining the balance of aquatic ecosystems, exerting a great influence at lower levels, their populations are declining worldwide due, to a large extent, to overfishing. Of the 64 species registered in Ecuador, from January to December 2019, 19 species were recorded in Manta from 15455 captured individuals, with the family Carcharhinidae being the family most present in the catches (69.4%), and the most abundant species was Prionace glauca (57.9%). In the case of threatened species, such as Carcharhinus longimanus, Sphyrna lewini and Sphyrna zygaena, a greater presence of immature specimens was observed in landings, suggesting a possible existence of nursery areas. However, information on the composition and biological aspects of shark species in the Ecuadorian Pacific is very scarce. Therefore, research on the characteristics of life history (age, growth and maturity) are of utmost importance for the analysis evolution of the populations that are being exploited, especially in developing countries, where this information is very scarce, causing inadequate management of fishery resources.

SARS-CoV-2 was identified as the pathogenic agent causing the COVID-19 pandemic. Among the proteins codified by this virus, the Spike is one of the most external and exposed. A fragment of the Spike protein, named the Receptor Binding Protein (RBD) interacts with the ACE2 receptors of human cells, allowing the entrance of the viruses. RBD has been proposed as an interesting protein for the development of diagnosis tools, treatment and prevention of the disease. In this work, a method for recombinant RBD production using Pichia pastoris as a cell factory in a Stirred Tank Bioreactor (SRTB) up to 7 L was developed. Using a basal saline medium with glycerol, methanol and compressed air in a four stages procedure, around 500 mg/L of raw yRBD (RBD produced by yeasts) and 206 mg/L of purified (>95%) RBD were obtained. Thereby, the proposed method represents a feasible, simple, scalable and cheap procedure for the obtention of RBD for diagnosis kits and vaccines formulation

Structural health monitoring (SHM) is critical for ensuring the safety of infrastructures like bridges. This article presents a digital twin solution for SHM of railway bridges using low-cost wireless accelerometers and Machine Learning (ML). The system architecture combines edge on-premises computing and cloud analytics to enable efficient real-time monitoring and complete storage of relevant time-history datasets. After train crossings, accelerometers stream raw vibration data, which is processed in the frequency domain and analyzed via machine learning to detect anomalies indicating potential structural issues. The digital twin approach is demonstrated on an in-service railway bridge, where vibration data was collected over two years under normal operating conditions. By learning allowable ranges for vibration patterns, the digital twin model identifies abnormal spectral peaks, suggesting changes in structural integrity. The long-term pilot proves that this affordable SHM system can provide automated and real-time warning of bridge damage and also supports the use of in-house designed sensors of lower-cost and edge computing capabilities than those used in the demonstration. The successful on-premises-cloud hybrid implementation provides a cost effective and scalable model for expanding monitoring to thousands of railway bridges, democratizing SHM to improve safety by avoiding catastrophic failures.

Current consensus diagnostic criteria for vestibular migraine (VM) describes this as an episodic disorder. However, a minority of patients report prolonged (>72h duration) or even persistent VM symptoms, prompting whether a chronic variant of vestibular migraine (CVM) should be introduced to the current classification and how best to define it. Here we summarize current evidence of such a potential chronic variant of VM and critically review previously published proposed definitions for CVM. Potential approaches to establish a diagnostic framework for CVM include a) following the distinction between episodic and chronic migraine headaches; namely, frequent and/or prolonged episodes of VM (but not persistent vertigo or dizziness) in the context of chronic migraine headaches or b) daily dizzy spells over more than 6 months that responded well to prophylactic anti-migraine therapy. A key challenge when defining diagnostic criteria for CVM is how to distinguish it from other chronic vestibular syndromes such as motion sickness, persistent postural-perceptual dizziness (PPPD), and mal-de-débarquement syndrome. Indeed, more than 50% of patients with PPPD and up to 46% with mal-de-débarquement syndrome fulfill diagnostic criteria for episodic migraine headaches, suggesting these disorders may all lie along a spectrum. We propose that when VM becomes persistent, it is best classified as PPPD but that VM and PPPD are not mutually exclusive, such that patients with PPPD need not have features of VM and the triggering event for persistent dizziness may be independent of migraine.

We show that, as in the case of the principle of minimum action in classical and quantum mechanics, there exists an even more general principle in the very fundamental structure of quantum space-time: This is the principle of minimal group that allows to consistently and simultaneously obtain a natural description of the spacetime dynamics and the physical states admissible in it. The theoretical construction is based on the physical states that are average values of the generators of the Metaplectic group Mp(n) , the double covering of SL(2C) in a vector representation, with respect to the coherent states carrying the spin weight. Our main results here are: (i) There exists a connection between the dynamics given by the Metaplectic group symmetry generators and the physical states (mappings of the generators through bilinear combinations of the basic states). (ii) The ground states are coherent states of the Perelomov-Klauder type defined by the action of the Metaplectic group which divide the Hilbert space into even and odd states mutually orthogonal. They carry a spin weight 1/4 and 3/4 respectively from which, two other basic states can be formed. (iii) The physical states, mapped bilinearly with the basic 1/4 and 3/4 spin weight states, plus their symmetric and antisymmetric combinations, have spin contents s = 0, 1/2, 1, 3/2 and 2. (iv) The generators realized with the bosonic variables of the harmonic oscillator introduce a natural supersymmetry and a superspace whose line element is the geometrical Lagrangian of our model. (v) From the line element as operator level, a coherent physical state of spin 2 can be obtained and naturally related to the metric tensor. (vi) The metric tensor is naturally discretized by taking the discrete series given by the basic states (coherent states) in the n number representation, reaching the classical (continuous) space-time for n going to infinity. (vii) There emerges a relation between the eigenvalue of our coherent state metric solution and the black hole area (entropy) as A_{bh}/4 l_{p}^{2} = I alpha I relating the phase space of the metric found g_{ab} and the black hole area A_{bh} through the Planck length l_{p}^{2} and the eigenvalue I alpha I of the coherent states. As a consequence of the lowest level of the quantum discrete space-time spectrum, eg the ground state associated to n = 0 and its characteristic length, there exists a minimum entropy related to the black hole history.

Small non-coding RNAs (sRNAs) are ubiquitously found in the three domains of life playing large-scale roles in gene regulation, transposable element silencing, and defense against foreign elements. While a substantial body of experimental work has been done to uncover function of sRNAs in Bacteria and Eukarya, the functional roles of sRNAs in Archaea are still poorly understood. Recently, high throughput studies using RNA-sequencing revealed that sRNAs are broadly expressed in the Archaea, comprising thousands of transcripts within the transcriptome during non-challenged and stressed conditions. Antisense sRNAs, which overlap a portion of a gene on the opposite strand (cis-acting), are the most abundantly expressed non-coding RNAs and they can be classified based on their binding patterns to mRNAs (3’ UTR, 5’ UTR, CDS-binding). These antisense sRNAs target many genes and pathways, suggesting extensive roles in gene regulation. Intergenic sRNAs are less abundantly expressed and their targets are difficult to find because of a lack of complete overlap between sRNAs and target mRNAs (trans-acting). While many sRNAs have been validated experimentally, a regulatory role has only been reported for very few of them. Further work is needed to elucidate sRNA-RNA binding mechanisms, the molecular determinants of sRNA-mediated regulation, whether protein components are involved, and how sRNAs integrate with complex regulatory networks.

In order to fully perform their functions and be durable, mortars for renders and plasters are requested to have a set of characteristics that can vary with the type of exposure to external environmental actions and the type of substrate. Generally, they need moderate strength, high deformability, some water protection capability, good adhesion to the substrate, and compatibility with the pre-existent materials. The presence of water and its movement inside the pore structure of the mortars are among the most significant causes of degradation. Moreover, several authors consider that the main factors for durability and good performance of lime-based mortars are mostly related with the good quality of the binder and the use of adequate aggregates. This paper intends to study the effect of ageing on the properties and durability of air lime mortars, using aggregates of different mineralogy. For this purpose, different mortars compositions are exposed to an accelerated weathering test under defined conditions. The obtained characteristics are discussed and compared with the results obtained with the same mortars tested in laboratory conditions. The effects of the aggregate type on the durability of mortars seem to be linked to their effects on the mortars porous structure.

This paper analyzes the relationship between corporate social responsibility (CSR) and social impact within the oil industry in an emerging market (Peru). Following the emerging literature on the social impact field, and using the case study methodology, the findings show that the expected positive relationship is diverse depending on several factors. Specifically, the results reveal that companies must focus on community and environmental responsibility, together with stakeholders' involvement to achieve social impact. However, when companies are weak in any of the previous factors, then the social impact is only partially accepted or even withdrawn.

(1) Background: Painful nervus intermedius neuropathy (e.g., geniculate neuralgia) involves continuous or near-continuous pain affecting the distribution of the intermedius nerve(s). The diagnosis of this entity is challenging, particularly when the clinical and demographic features do not resemble the typical presentation of this condition. To the best of our knowledge, only three case reports have described the occurrence of nervus intermedius neuropathy in young patients. (2) Case Description: A 13-year-old female referred to the Orofacial Pain clinic with a complaint of pain located deep in the right ear and mastoid area. The pain was described as a constant throbbing and dull, with an intensity of 7/10 on numerical rating scale, characterized by superimposed brief paroxysms of severe sharp pain. The past treatments included ineffective pharmacological and irreversible surgical approaches. After a comprehensive evaluation, a diagnosis of idiopathic painful nervus intermedius neuropathy was given, which was successfully managed with the use of gabapentin. (3) Conclusions and Practical Implications: The diagnosis and treatment of neuropathic pain affecting the nervus intermedius can be challenging due to the complex nature of the sensory innervation of the ear. The diagnosis can be even more challenging in cases of atypical clinical and demographic presentations, which in turn may result in unsuccessful, unnecessary, and irreversible treatments. Multidisciplinary teams and constant knowledge update are fundamental to provide good quality of care to our patients and to not overlook any relevant signs or symptoms.

In this work, we show that a late fusion approach to multi-modality in sign language recognition improves the overall ability of the model in comparison to the singular approaches of Computer Vision (88.14%) and Leap Motion data classification (72.73%). With a large synchronous dataset of 18 BSL gestures collected from multiple subjects, two deep neural networks are benchmarked and compared to derive a best topology for each. The Vision model is implemented by a CNN and optimised MLP and the Leap Motion model is implemented by an evolutionary optimised deep MLP topology search. Next, the two best networks are fused for synchronised processing which results in a better overall result (94.44%) since complementary features are learnt in addition to the original task. The hypothesis is further supported by application of the three models to a set of completely unseen data where a multi-modality approach achieves the best results relative to the single sensor method. When transfer learning with the weights trained via BSL, all three models outperform standard random weight distribution when classifying ASL, and the best model overall for ASL classification was the transfer learning multi-modality approach which scored 82.55% accuracy.

This review describes the positive effects of growth hormone on the cardiovascular system. We analyze why the vascular endothelium is a real internal secretion gland, whose inflammation is the first step for developing atherosclerosis, as well as the mechanisms by which GH acts on the vascular endothelium improving its dysfunction. We also report how GH acts on coronary arterial disease and heart failure, and on peripheral arterial disease inducing the generation of new collateral vessels able to bypass a major artery occlusion. We include some preliminary data from a trial in which GH or placebo is given to elder people suffering from critical limb ischemia, showing the effects of the hormone on plasma markers of inflammation, and stating that the administration of GH in short periods of time is safe and effective even in diabetic patients. We also analyze how Klotho may have strong relationships with GH, inducing, after being released from the damaged vascular endothelium, the pituitary secretion of GH to repair the damaged tissue. Lastly, we show how GH induces wound healing by increasing the blood flow to the ischemic tissue. In summary, we postulate that short-time GH administration is useful for treating cardiovascular diseases.

Climate changes caused by anthropogenic actions can directly and indirectly affect living beings, including parasites and their hosts. Changes such as water temperature, pH, distribution of nutrients in the aquatic environment are some examples that can interfere with the fish community, whether in open water or in production systems. In this review, we will show how climate change can affect the adaptation of hosts and parasites in the aquatic environment and how these parasites can be used for environmental monitoring.

We study in this work a dilute granular gas immersed in a thermal bath made of smaller particles with nonnegligible masses as compared with the granular ones. The kinetic theory for this system is developed and described by an Enskog--Fokker--Planck equation for the one-particle velocity distribution function. Granular particles are assumed to have inelastic and hard interactions, losing energy in collisions as accounted by a constant coefficient of normal restitution. The interaction with the thermal bath is based on a nonlinear drag force plus a white-noise stochastic force. To get explicit results of the temperature aging and steady states, Maxwellian and first Sonine approximations are developed. The latter takes into account the coupling of the excess kurtosis with the temperature. Theoretical predictions are compared with direct simulation Monte Carlo and event-driven molecular dynamics simulations. While good results for the granular temperature are obtained from the Maxwellian approximation, a much better agreement, especially as inelasticity and drag nonlinearity increase, is found when using the first Sonine approximation. The latter approximation is, additionally, crucial to account for memory effects like Mpemba and Kovacs-like ones.

Western countries are experiencing an increasing aging population, resulting in heightened disability and mobility issues. This trend is expected to escalate in the coming decades. Therefore, ensuring adequate accessibility in collective residential housing –where individuals spend much of their daily lives– is of paramount importance. This paper presents a case study focused on the accessibility of building entrances in collective residential housing in Southeast Spain, specifically in the Region of Murcia. In this region, 9.8% of the population has disabilities, and 15.75% were over 64 years old in 2020. The study began by compiling the relevant national and regional accessibility regulations for existing buildings. Subsequently, extensive fieldwork was conducted, analyzing 150 collective residential housing buildings. Based on this analysis, a set of recommendations to enhance accessibility was formulated for buildings not complying with the regulations. The results are presented and discussed in detail. The most frequent recommendation was the construction of accessible ramps, identified as the primary solution in over 40% of cases, either alone or in conjunction with other measures. In 54% of the cases, multiple interventions were necessary to achieve effective accessibility adaptation. The findings of this study could inform the development of public policies aimed at improving accessibility conditions in urban areas.

This paper addresses the optimal stochastic allocation of Distributed Energy Resources in distribution Networks. Typically, uncertain problems are analyzed in multi-stage formulations including case generation routines, resulting in computationally exhaustive programs. In this article, two probabilistic approaches are proposed resulting in a single-stage, convex, stochastic optimal power flow problem: The Range-Probability Optimization (RPO) and Value-Probability Optimization (VPO). The RPO maximizes probabilities within a range of uncertainty, whilst the VPO optimizes the values of the random variables and maximizes their probabilities. Random variables are modeled with hourly measurements fitted to the logistic distribution. These formulations were tested on two systems and compared against the deterministic case built from expected values. Results indicate that assuming deterministic conditions ends in highly underestimated losses. The RPO showed that by including a ±10 % uncertainty, the losses can be increased up to 40 % with up to −72 % photovoltaic capacity, depending on the system, whereas the VPO resulted in up to 85 % increases in power losses despite PV installations, with 20 % greater probabilities in average. By implementing any of the proposed approaches, it was possible to obtain more probable upper envelopes in the objective, avoiding case generation stages and heuristic methods.

Cooperative organizations try to balance economic viability and Corporate Social Responsibility (CSR) management through strategic policies that involve dialogue, participation and engagement with stakeholders. To measure the impact of CSR management, the electricity sector implements monitoring processes and models, such as the Sustainability Reporting Standards of the Global Reporting Initiative (GRI), which measure contributions to the Sustainable Development Goals (SDGs) of the United Nations 2030 Agenda. This research analyses the strategic management of CSR in the 28 electric cooperatives that market electricity in Spain with the aim of determining their level of commitment to CSR and stakeholder participation in their corporate policies. The analysis is based on the descriptive-exploratory study of the whole population of electric cooperatives. The results indicate that the CSR management of most electric cooperatives is still in an emerging stage within the Value Curve. Importantly, there is a significant percentage of cooperatives that have already advanced towards the consolidating and institutionalized stages. However, most of these social-economy organizations are not developing programs that link their CSR strategies with their priority SDGs and sustainability as commitment to their community.

The fossil record is notorious for being incomplete and distorted, frequently conditioning the type of knowledge that can be extracted from it. In many cases, this often leads to issues when performing complex statistical analyses, such as classification tasks, predictive modelling, and variance analyses, such as those used in Geometric Morphometrics. Here different Generative Adversarial Network architectures are experimented with, testing the effects of sample size and domain dimensionality on model performance. For model evaluation, robust statistical methods were used. Each of the algorithms were observed to produce realistic data. Generative Adversarial Networks using different loss functions produced multidimensional synthetic data significantly equivalent to the original training data. Conditional Generative Adversarial Networks were not as successful. The methods proposed are likely to reduce the impact of sample size and bias on a number of statistical learning applications. While Generative Adversarial Networks are not the solution to all sample-size related issues, combined with other pre-processing steps these limitations may be overcome. This presents a valuable means of augmenting geometric morphometric datasets for greater predictive visualization.

Fiber-cement composites were prepared from cellulosic cotton residue (CCR) arise from sanding process (emerizing). The effect of different concentrations: 0.5% and 1%, and granulometry: thick (retained in a14 mesh sieve) and thin (retained in a 48 mesh sieve) of this residue were evaluated on tensile strength of cement slurries with seven (07) curing days. To characterize the CCR, TGA, FT-IR, SEM and XRD analysis were performed and the residue resistance in an alkaline environment was also evaluated. Splitting tensile strength test, known as Brazilian Test, was used to assess effects of the fibers on the mechanical behavior of cement matrix. Analyzing the results, the CCR proved to be resistant in an alkaline environment, meaning that it can withstand the alkaline environment of cement matrix. The results showed an improvement superior to 17% in tensile strength for 1% of CCR. Therefore, the CCR presents a great application potential in cement pastes used for oil well cementing that requires to increase its tensile strength, once a significant improvement was achieved with a low-residue employee.

Hepatitis C presents a significant global health challenge, necessitating early diagnosis and precise severity classification for timely medical intervention. This study explores the application of machine learning techniques to predict the severity of hepatitis C, leveraging an extensive dataset. Our approach encompasses rigorous data preprocessing, advanced model development, and fine-tuned hyperparameter optimization to ensure accurate and reliable predictions. We evaluated four classification models: Logistic Regression, Random Forest, Gradient Boosting, and Support Vector Machine (SVM), comparing their accuracy in classifying patients. The results showed that the Random Forest and Gradient Boosting models outperformed the others with an accuracy of approximately 93.50%, demonstrating their potential in assisting Hepatitis C diagnosis. Further model enhancements through hyperparameter tuning and feature engineering can improve the precision of Hepatitis C diagnosis, contributing to better patient care.

Accurate estimation of body fat percentage is essential for various health and fitness applications. Traditional methods for measuring body fat, such as underwater weighing, can be costly and inconvenient. In this study, we apply machine learning techniques to predict body fat percentage using easily accessible body measurements and data. The results highlight the effectiveness of regression models in estimating body fat, with Linear Regression, Ridge Regression, and Bayesian Ridge models achieving R-squared scores of approximately 74%, 73%, and 73%, respectively. These models provide a practical and cost-effective solution for individuals and professionals seeking reliable body fat estimates.

This article presents a study on brain tumor detection using the VGG-16 model, a convolutional neural network known for its performance in computer vision tasks. The aim of the study is to classify magnetic resonance imaging (MRI) images and accurately identify the presence of brain tumors. The dataset used consists of brain tumor MRI images, categorized into two classes: "NO" (no tumor) and "YES" (tumor). The methodology involves setting up the environment, importing and preprocessing the data, building the VGG-16 model, and evaluating its performance using metrics such as accuracy, precision, and recall. The results demonstrate an accuracy of approximately 88% on the validation set and 80% on the test set, indicating the potential of the VGG-16 model in supporting healthcare professionals in diagnosing brain tumors. The study contributes to the field of medical image analysis and offers insights into the application of deep learning for brain tumor detection.

This article presents a comparative analysis of three Machine Learning models, namely Logistic Regression, Decision Tree Classifier, and Random Forest Classifier, for prostate cancer detection. The models were trained and evaluated using clinical data, and their performance was assessed using various evaluation metrics. The results show that Logistic Regression achieved the highest accuracy (90%) among the three models, followed by Random Forest Classifier (76.67%) and Decision Tree Classifier (73.33%). Similarly, Logistic Regression demonstrated superior precision (95.65%) and F1 Score (93.62%), indicating its effectiveness in identifying true positive cases. However, the Decision Tree Classifier exhibited higher recall for the negative class (83.33%) compared to the positive class (70.83%), while Random Forest Classifier showed balanced recall for both classes (66.67% for negative and 79.17% for positive). These findings suggest that Logistic Regression outperforms the other models in terms of accuracy and precision, while the Decision Tree Classifier and Random Forest Classifier provide better recall for certain classes. The results highlight the potential of Machine Learning in prostate cancer detection and provide insights for further research and improvement of the models.

In the same manner that there are several statements of the second law of thermodynamics but all of them are equivalent, it is possible that most of the entropic methods applied to the nervous system and brain in particular share a similar outcome, or essence, that helps understand some aspects of the fundamentals of basic neurodynamics. In this short review focused on certain aspects of the entropic metrics some results are examined that indicate the fundamental importance of the natural tendency towards a maximal energy distribution for healthy brain activity and thus cognition to emerge.

An airfoil is the geometric shape of a cross-section of a wing. When it is exposed to the flow of a fluid over its surface, it generates both lift and drag forces through a pressure distribution. Designing an efficient airfoil for aerodynamic applications is a complex challenge in the field of aerodynamic engineering, with the aim of achieving an optimal lift-to-drag ratio. The success of airfoil design hinges on the effective reduction of drag force under specific conditions, while simultaneously attaining the desired lift without encountering significant flow separation, such as boundary layer shedding. Furthermore, the design must adhere to lifting force limitations and meet structural requirements. In the field of airfoil design and optimization, literature review articles provide a valuable resource by offering an overview of the latest advancements in specific areas. These areas encompass a wide range of topics including the design and testing of adaptive geometry wings, such as morphing wing technology as well as the application of shape optimization techniques to enhance airfoil performance. Our goal is to provide researchers with an in-depth review of relevant articles published to date, examining the applied approaches utilized to tackle the complex problem of airfoil design and explore the methodology employed to address it, from a broad perspective on the topic.

Background and Objectives: Blood flow restriction (BFR) has been investigated as an alternative method combined with resistance training or AT to promote different health benefits for older people. Nevertheless, no study analyzed chronic effects of BFR on muscle activation in this population, and in some investigations, the application of BFR has been employed arbitrary pressures, which can be a serious methodological error, both from the results and of the risk to the health of the older. Thus, this study analyzed the effect of 24 weeks of walking with BFR on activation and muscle strength in elderly women with osteoporosis. Materials and Methods: Thirty older women (66.0±4.6 years) performed randomly to one of three training groups: WALK (moderate-intensity walking), WALK+BFR (low-intensity walking with BFR), or BFR (BFR alone). Muscle activation (sEMG) and strength of knee flexors and extensors were measured pre-intervention and after 12 and 24 weeks. Results: Only a trivial effect size (ES) for the WALK+BFR (ES= 0.16) was observed in sEMG of the knee flexors compared to WALK. A moderate effect was observed in sEMG of the knee extensors (ES= 0.65) for the WALK+BFR compared to the WALK. However, adverse effects were found in the strength of the knee flexors for the BFR (ES= −0.86) and WALK+BFR (ES= −0.69) compared to WALK. Adverse and null effects, respectively for the BFR (ES= −0.16) and WALK+BFR (ES= 0.06) groups, were also observed on the strength gain of the knee extensors. Conclusions: Low-intensity walk combined with BFR does not provide relevant chronic effects on strength gain or even limit muscle strength gain, however, due to greater activation of knee extensors over 24 weeks, it is possible to benefit from the use of similar strategies to obtain neuromuscular gains in the long‐term for elderly women with osteopenia and osteoporosis.

The aim of the present study was to investigate whether chronic undernutrition modifies the response to rostafuroxin in juvenile rats. Chronic undernutrition was induced in male rats using a multideficient diet known as Regional Basic Diet (RBD), mimicking alimentary habits in impoverished regions worldwide. Animals were given RBD – or a control/CTRL normal diet for rodents – from weaning to 90 days, and rostafuroxin (1 mg/kg body mass) or vehicle were orally administered during the last 30 days. Undernourished rats became hypertensive at 55–60 days of age (tail-cuff recording). During the last two days, the rats were hosted in metabolic cages to measure food/energy, water, Na+ ingestion, and urinary volume. Blood and kidneys were collected after euthanasia. Rostafuroxin increased food/energy and Na+ intake in CTRL and RBD rats but had opposite effects on Na+ balance (intake minus urinary excretion): negative in CTRL and positive in RBD. The drug normalized the decreased plasma Na+ concentration found in RBD rats, increased urinary volume in RBD but not in CTRL, and decreased and increased urinary Na+ concentration in the RBD and CTRL groups, respectively. Rostafuroxin decreased the ouabain-sensitive (Na++K+)ATPase and increased the ouabain-resistant, furosemide-sensitive Na+-ATPase from proximal tubule cells in both groups, and normalized the systolic blood pressure in RBD without effect in CTRL rats. We conclude that chronic undernutrition modifies the response of blood pressure, caloric metabolism, Na+ distribution in liquid compartments, mobilization of Na+ from non-osmotic compartments, Na+ and water balance, and activity of renal Na+-transporting ATPases to rostafuroxin.

In recent years, news media has been greatly disrupted by the potential of technologically driven approaches in the creation, production, and distribution of news products and services. Artificial intelligence (AI) has emerged from the realm of science fiction and has become a very real tool that can aid society in addressing many issues, including the challenges faced by the news industry. The ubiquity of computing has become apparent and has demonstrated the different approaches that can be achieved using AI. We analyzed the news industry’s AI adoption based on the seven subfields of AI: (i) machine learning; (ii) computer vision (CV); (iii) speech recognition; (iv) natural language processing (NLP); (v) planning, scheduling, and optimization; (vi) expert systems; and (vii) robotics. Our findings suggest that three subfields are being developed more in the news media: machine learning, computer vision, as well as planning, scheduling, and optimization. Other areas have not been fully deployed in the journalistic field. Most AI news projects rely on funds from tech companies such as Google. This limits AI’s potential to a small number of players in the news industry. We make conclusions by providing examples of how these subfields are being developed in journalism and present an agenda for future research.

The health emergency caused by Covid 19 highlighted the food dependency of many cities in the world and Cali and the cities of Valle del Cauca were no exception as they depended on food flows from other regions and countries, so these Entities are part of the corporate food system, to which their rulers delegated food security for their inhabitants. In the same territory and for the last nine years, a second-level organization has been consolidating that brings together 14 peasant agroecological markets and that despite strict confinement measures was able to continue supplying food to consumers in the municipalities of influence that have supported this initiative. The foregoing leads to think that said organization can become a platform for an agroecological food system of regional scope, for which the characteristics that said system should have according to a model based on the principles of agroecology were evaluated.

The growing need for water has pressured society and governments to focus more on preservation, planning and management of this natural resource, in which is fundamental to ecosystems and especially to humans. In this sense, the goal of this study was to analyze the national policy of water resources in Brazil and Italy, figuring out aspects that could promote its improvement, aiming at the preservation of water sources, guaranteeing satisfactory quantity and quality. They were carried out in 2019 by the environmental agencies of both countries, listing the main disciplinary regulations. The results show that although they are countries with different realities, they resemble similarities in managerial aspects of water resources, with legislation addressing qualitative and quantitative aspects of water, with guiding principles, instruments and actions aimed at the defence of this natural resource.

A large diversity of epigenetic factors, such as microRNAs and histones modifications, are known to be capable of regulating gene expression without altering DNA sequence itself. In particular, miR-1 is considered the first essential microRNA in cardiac development. In this study, miR-1 potential role in early cardiac chamber differentiation is analyzed through specific signaling pathways. For this, we performed in chick embryos functional experiments by means of miR-1 microinjections into the posterior cardiac precursors -of both primitive endocardial tubes- committed to sinoatrial region fates. Subsequently, embryos were subjected to whole mount in situ hybridization, immunohistochemistry and RT-qPCR analysis. As a relevant nov-elty, our results revealed that miR-1 increases Tbx5, Gata4 and AMHC1, while this microRNA diminishes Mef2c expression, during early differentiation of cardiac sinoatrial region. Further-more, we observed in this developmental context that miR-1 upregulates CRABPII and RARß, and downregulates CRABPI, which are three crucial factors in retinoic acid signaling pathway. Interestingly, we also noticed that miR-1 directly interacts with HDAC4 and Calmodulin, as well as with Erk2/MAPK1, which are three key factors actively involved in Mef2c regulation. Our study shows, for the first time, a key role of miR-1 as an epigenetic regulator in early differenti-ation of cardiac sinoatrial region through orchestrating opposite actions between retinoic acid and Mef2c, fundamental to properly assign cardiac cells to their respective heart chambers. A better understanding of those molecular mechanisms modulated by miR-1 will definitely help in fields applied to therapy and cardiac regeneration and repair.

With the recent advances in science and technology, more processing capability and data have become available, allowing a more straightforward implementation of data analysis techniques. Fortunately, the available online data storage capacity follows this trend, and vast amounts of data can be stored online freely or at accessible costs. As happens with every evolution (or revolution) in any science field, organizing and sharing this data is essential to contribute to new studies or validate the obtained results quickly. To facilitate this, we must guarantee interoperability between the existing datasets and the developed software, whether commercial or open source. This article explores this issue, analyzing the current initiatives to establish data standards and comparing some of the existing dataset online storage platforms. Through a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, it is possible to understand better the strategy that should be taken to improve the efficiency in this field, which directly depends on the data characteristics.

The paper primarily demonstrates that the three internal triangles formed by connecting any point on a midsegment with the vertices of a generic triangle satisfy the geometric Proof of the Pythagorean theorem in Euclidean geometry. Moreover, this study elucidates the Pythagorean relationships inherent within three-dimensional geometric constructs resulting from the arrangement of three-dimensional spatial triangles. This geometric relationship, akin to a generalized extension of the Pythagorean theorem, unveils a unique spatial region characterized by this harmonious area interrelation among triangles.

‘Arrayana’ mandarin fruits have a short postharvest life and are sensitive to chilling injury (CI) during cold storage. Brassinosteroids (BR) have been used as a sustainable technology to alleviate CI in fruits and improve postharvest quality. This study evaluated the effect of applying the 24-epibrasinolide analogue (EBR), at doses of 5 mg L-1; DI-31 analogue, at 5 and 10 mg L-1; and control, on the main physical and biochemical characteristics of 'Arrayana' mandarin stored at 4°C for 40 days and, subsequently, 7 days at room temperature (shelf life). The application of EBR and DI-31 analogues reduced the appearance of CI in the exocarp of 'Arrayana' mandarin fruits by reducing electrolyte leakage, maintaining membrane integrity, and increasing antioxidant activity and phenol content at the end of cold storage and shelf life. This was especially pronounced with 5 mg L-1 of EBR. Similarly, the BR maintained the postharvest quality of mandarins by reducing weight loss, respiratory intensity and chlorophyll degradation; increasing β-carotene; and maintaining titratable acidity, and soluble solids. Our research reports for the first time CI tolerance in Arrayana mandarin using natural (EBR) and spirostanic (DI-31), analogues and illustrates the tolerance functionality of the DI-31 analog on CI in fruit postharvest.

Principle of memristor presented by Leon Chua and time reversal based non-linear elastic wave spectroscopy (TR-NEWS) which can be applied to acoustic tomography are reviewed. Correlation of acoustic or electromagnetic nonlinear waves and its time reversed wave can produce strong signal. Materials like transducer or biological skin can be assumed to be composed of a large number of small elastic unit: hysteretic elementary unit (HEU), and one can take a HEU as a memristor whose operation depends on time. Relation between TR-NEWS and solitonic wave in fluid, and relation between decomposition of time reversal operator (DORT) and chaotic oscillation are discussed.

Roundabouts need capacity and safety improvements compatible with manual-driven, not only with autonomous vehicles. The signaling and control of roundabouts must evolve and incorporate current technologies. For that, we approach roundabouts as synchronous switches of vehicles. This paper describes Synchronous Roundabouts with Rotating Priorities, a roundabout control system based on vehicle platoons arriving at the roundabout at speed identical to the roundabout and within the time slot assigned to their entry, avoiding conflicts and stops, thus increasing roundabout capacity and safety. Signaling is visual for human drivers and also wireless for connected and autonomous vehicles. We evaluate analytically and with simulations roundabouts of different radius for several values of the average distance between vehicles. Average delays are 28,7 % lower, with negligible dispersion. The capacity improvements depend on design parameters: in our set is moderate for small roundabouts but goes up to 70-100 % for short distances and medium and large roundabouts.

The neural crest, a unique cell population originating from the primitive neural field, has a multi-systemic and structural contribution to vertebrate development. At the cephalic level, the neural crest generates most of the skeletal tissues encasing the developing forebrain and provides the prosencephalon with functional vasculature and meninges. Over the last decade, we have demonstrated that the cephalic neural crest (CNC) exerts an autonomous and prominent control on forebrain and sense organs development. The present paper reviews the primary mechanisms by which CNC can orchestrate vertebrate encephalization. Demonstrating the role of the CNC as an exogenous source of patterning for the forebrain provides a novel conceptual framework with profound implications for understanding neurodevelopment. From a biomedical standpoint, these data suggest that the spectrum of neurocristopathies is broader than expected and that some neurological disorders may stem from CNC dysfunctions.

Senna rugosa is a species found in the Cerrado and used in folk medicine as a vermifuge and in the treatment of poisonous snakebites accidents. In this work, we identified the main secondary metabolites present in ethanolic extracts of the leaves (ELSR) and roots (ERSR) of S. rugosa and evaluated the potential cytoprotective effect against cellular macromolecular damage, as well as the cytotoxic properties of the extracts on the K562 and Jurkat leukemic cell lines. The identification of metabolites was done by liquid chromatography coupled with mass spectrometry. The antioxidant activities were investigated by direct ABTS•+ and DPPH• radical scavenging methods, protection against oxidative damage in proteins and DNA. The cytotoxic properties were investigated against healthy cells, isolated from human peripheral blood (PBMC) and leukemic cell lines. The leaf extract contains catechin, rutin, epigallocatechin derivatives, kaempferol glycosides, luteolin, and dimeric and trimeric procyanidins, while the root extract profile shows obtusichromoneside derivatives, 2-methoxystypandrone, stilbene derivatives, naphthopyranones, and flavanone derivatives. The extracts showed antioxidant activity, with IC50 of 4.86 ± 0.51 µg/mL and 8.33 ± 0.90 µg/mL in the ABTS assay for ELSR and ERSR, respectively. And in the DPPH• assay, the IC50 was 19.98 ± 1.96 µg/mL for ELSR and 13.37 ± 1.05 µg/mL for ERSR. The extracts protected macromolecules against oxidative damage at concentrations of 5 µg/mL. The cytotoxicity test against leukemic strains was observed after 24 and 48 hours of treatment. After 48 h, results against the K562 cell line demonstrate IC50 of 242.54 ± 2.38 µg/mL and 223.00 ± 2.34 µg/mL for ELSR and ERSR , respectively. While against the Jurkat cell line, these extracts showed IC50 of 171.45 ± 2.25 µg/mL and 189.30 ± 2.27 µg/mL, respectively Results on PBMC viability, demonstrate that the extracts showed selectivity for the leukemic cell lines. Together, our results reveal that the leaves and roots of S. rugosa have completely distinct and complex chemical compositions. This study expands the repertoire of identified chemical compounds and underscores their significant pharmacological potential in conditions related to oxidative stress and leukemia.

Today's unstable labor market increasingly requires flexibility and adaptability to cope with the threat of unemployment. It can cause distress in people and have a more significant negative impact on fragile workers, such as migrants. This study aimed to test whether a Career Counseling intervention designed for Migrants (CCfM) can develop Career Adaptability and, therefore, both Work Self-efficacy (WSe) and Job Search Self-efficacy (JSSe) perceptions. It was conducted in Italy and involved a sample of 233 migrants, who were asked to respond to a questionnaire available in three languages (Italian, French, and English). Data analysis showed that an improvement was demonstrated in all the variables considered, namely career adaptability (including concern, control, confidence, and curiosity), WSe, and JSSe, even though the CCfM was not directly designed to increase the last one. In addition, the development of career adaptability explained the increase in migrants' WSe and JSSe, and the initial level of career adaptability was found to explain the increase in WSe due to the initial positive level of curiosity.

This research was carried out with the objective of analyzing the principles of social and solidarity economy in the community funds of the rural sector of Pichincha, Ecuador. Small organizations promote microcredits for local, social and economic development, representing an alternative to those managed by traditional banks. The research was descriptive, non-experimental field research. The population analyzed consisted of 220 community funds, and the size of the representative sample was 49 community organizations that practice solidarity finance. The data were collected through online questionnaires using a Likert scale, and the validity of this approach was judged by experts; the reliability of the instrument obtained was 0.95 using the Cronbach’s alpha method. The results highlight that in these organizations, the following traits prevail: associativity, self-management and organization. However, autonomy and solidarity have a negative valuation, which shows that strategies must be rethought to achieve the empowerment of the financial service. This will allow them to be sustainable and to expand with more benefits that promulgate financial activity and promote structures in rural community networks that promote local development and strengthen deficient principles as a basis for generating a greater benefit to the partners.

Palmitoylethanolamide (PEA) has been prescribed for neuropathic pain for several years. This study is mainly addressed to summarize what has been published on the topic in the last decades, and how appropriate the numerous prescriptions are. Among others, it examines the innovative EquiPEA^® patent, which aims to address obstacles encountered with conventional PEA formulations. EquiPEA^® seems to partially ameliorate the bioavailability and the targeted distribution. It seems to introduce novel advancements that have the potential to enhance the therapeutic effectiveness of PEA in terms of its anti-inflammatory, antioxidant, and analgesic properties. The deep literature analysis aims to examine the potential advantages of this innovative formulation, in the context of several pathological conditions that may benefit from this molecule. In particular, it investigates the potential enhanced bioavailability and targeted delivery system of EquiPEA^®. Also, it tries to understand if it can modernize the field of therapy based on PEA, thus offering a better treatment option for individuals with long-term inflammation, oxidative stress, and neuropathic or mixed pain with a neuropathic component. The study examines the possible impact of EquiPEA^® on personalized medicine strategies and its potential for translation into clinical practice. It analyses the possibilities that EquiPEA^® has in enhancing patient outcomes in a range of central nervous system and inflammatory conditions. This narrative review makes a valuable contribution to the ongoing comprehension of PEA therapy. It establishes a foundation for further exploration in research and potential uses in clinical settings.

Let $\mathcal{N}$ be an arbitrary class of matroids, closed under isomorphism. For $k$ a positive integer, we say that $M \in \mathcal{N}$ is \emph{$k$-minor-irreducible} if $M$ has no minor $N \in \mathcal{N}$ such that $1\leq\left|E\left(M\right)\right|-\left|E\left(N\right)\right|\leq k $. Tutte's Wheels and Whirls Theorem establish that, up to isomorphism, there are only two families of 1-minor-irreducible matroids in the class of 3-connected matroids. More recently, Lemos classified the 3-minor-irreducibles with at least 14 elements in the class of triangle-free 3-connected matroids. Here we prove a local characterization for the 2-minor-irreducible matroids with at least 11 elements in the class of triangle-free 3-connected matroids. This local characterization is used to establish two new families of 2-minor-irreducible matroids in this class.

The growing interest related to the proposal of formal definition of a new geological period that has being called “Anthropocene” has introduced a buzzing dynamics in the scientific community, but its conduct is perhaps due to various interests involved in a discussion that has long surpassed the contours of the so-called “Geosciences”. Themes such as “Climate Change or Drift”, “Global Warming”, “Massive Extinction of Species” and “Loss of bio and geodiversity”, among others, are the wheel of a geomorphogenetic dynamics of anthropocentric origin, which leads the debate. But are the conditions for the formal establishment of a new morphosedimentary cycle following the Meghalayanian (Upper Holocene) Age? This work pursues a line of thought that seeks to answer these and other questions, based on the official position of the institutes that have the scientific competence for the formalization under consideration, and the formal criteria that should be considered for this purpose.

In this article we introduce an extension of the Akash distribution. We use the slash 1 methodology to make the kurtosis of the Akash distribution more flexible. We study the general 2 density of this new distribution, some properties, moments, coefficients of asymmetry and kurtosis. 3 Statistical inference is performed using the methods of moments and maximum likelihood via the 4 EM algorithm. A simulation study is carried out to observe the behavior of the maximum likelihood 5 estimator. An application to a real data set with high kurtosis is considered, where it is shown that 6 the new distribution fits better than other extensions of the Akash distribution.

Unmanned Aerial Vehicles (UAVs) are being increasingly viewed as valuable tools to aid the management of farms. This kind of technology can be particularly useful in the context of extensive cattle farming, as production areas tend to be expansive and animals tend to be more loosely monitored. With the advent of deep learning, and Convolutional Neural Networks (CNNs) in particular, extracting relevant information from aerial images has become more effective. Despite the technological advancements in drone, imaging and machine learning technologies, the application of UAVs for cattle monitoring is far from being thoroughly studied, with many research gaps still remaining. In this context, the objectives of this study were threefold: 1) to determine the highest possible accuracy that could be achieved in the detection of animals of the Canchim breed, which is visually similar to the Nelore breed (\textit{Bos taurus indicus}); 2) to determine the ideal Ground Sample Distance (GSD) for animal detection; 3) to determine the most accurate CNN architecture for this specific problem. The experiments involved 1,853 images containing 8,629 samples of animals, and 15 different CNN architectures were tested. A total of 900 models were trained (15 CNN architectures * 3 spacial resolutions * 2 datasets * 10-fold cross validation), allowing for a deep analysis of the several aspects that impact the detection of cattle using aerial images captured using UAVs. Results revealed that many CNN architectures are robust enough to reliably detect animals in aerial images even under far from ideal conditions, indicating the viability of using UAVs for cattle monitoring.

This research proposes a methodology for minimizing losses in transmission lines (LT), considering the reconfiguration of the architecture of the electrical power system (SEP). The implementation of this methodology redirects the power flow with optimal switching through its LTs to guarantee the stability of the voltage, angle, frequency, and power balance to minimize losses that affect the reliability and quality of the system. Optimal transmission switching (OTS) allows various types of analysis to be carried out, where the loadability of the lines, response times, and operating costs, among others, can be improved. This article proposes to minimize the losses in the transmission lines with the OTS by using AC power flows as a mixed integer nonlinear problem (MINLP). Several test scenarios evaluate the method’s effectiveness, determining the optimal topology for corrective control that optimizes power flows in different situations. It has been proven that this approach reduces losses compared to a base case by 99%, even in the face of N-1 or random contingencies, without losing load, maintaining the same active power dispatch, and finally verifying a strategic increase in dispatch of reactive power to maintain operating parameters within stable limits.

Pediatric interventional cardiology procedures are essential in diagnosing and treating congenital heart disease in children; however, they raise concerns about potential radiation exposure. Managing radiation doses and assessing image quality in angiographs becomes imperative for safe and effective interventions. This systematic review aims to comprehensively analyze the current understanding of physical image quality metrics relevant for characterizing X-ray systems used in fluoroscopy-guided pediatric cardiac interventional procedures, considering the main factors reported in the literature that influence this outcome. A search in Scopus and Web of Science, using relevant keywords and inclusion/exclusion criteria, yielded fourteen relevant articles published between 2000 and 2022. The physical image quality metrics reported were noise, signal-to-noise ratio, contrast, contrast-to-noise ratio, and high contrast spatial resolution. Various factors influencing image quality were investigated, such as polymethyl methacrylate thickness (often used to simulate water equivalent tissue thickness), operation mode, anti-scatter grid presence and tube voltage. Objective evaluations using these metrics ensure impartial assessments for main factors affecting image quality, improving in the characterization fluoroscopic X-ray systems, and aiding informed decisions to safeguard pediatric patients during procedures.

A general framework for inference in dynamical systems is described, based on the language of Bayesian probability theory and making use of the maximum entropy principle. Taking as fundamental the concept of a path, the continuity equation and Cauchy's equation for fluid dynamics arise naturally, while the specific information about the system can be included using the Maximum Caliber (or maximum path entropy) principle.