In this paper, we define and investigate modified p-Leonardo, p-Leonardo-Lucas and p-Leonardo sequences as special cases of the generalized Leonardo sequence. We present Binet's formulas, generating functions, Simson formulas, and the summation formulas for these sequences. Moreover, we give some identities and matrices related with these sequences. Furthermore, we show that there are close relations between modified p-Leonardo, p-Leonardo-Lucas, p-Leonardo numbers and Fibonacci, Lucas numbers.

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.

Sports are framed within the context of the Olympic spirit and are, therefore, within the vision and mission of the Olympic Committee, aimed at “building a better world”. This is identified as a fundamental value and sustainability is therefore explicitly considered to be a “working principle” of this. In this research an analysis of the performance of professional European football teams publicly listed on stock markets, restating the income statements according to the Value-Added perspective is carried out. This takes into account the effective sustainable contribution in the distribution of added value with reference to the human, structural, debt, infrastructural, and risk capitals of these organisations. The Value-Added Statement is considered as a part of the broader CSR Reporting and can be traced back to the late 1970s. However, it is in widespread contemporary use and is regarded as being both a credible and a tested measure. In this paper, the authors apply a slightly modified and simplified version of this tool to these publicly listed European football clubs as a proxy for wider professional sport. This research demonstrates that, although professional sports clubs are profit-oriented, the distribution of wealth generated by the added value is unbalanced. In most cases, at least in financial terms, shareholders are the most disadvantaged and athletes are the most rewarded.

Although advertising literacy leads to critical thinking in the face of advertising, but so far, no action has been taken in Iran regarding a tool to measure this type of literacy. And after the investigations, it was determined that although much research has been done on advertising, but the lack of appropriate measurement tools to measure the level of advertising literacy is clearly evident. Therefore, this research provides a valid tool for measuring advertising literacy from students' perspective. In this study, referring to the dimensions of advertising literacy from the perspective of Malmelin (2010) and the views of related professors, a questionnaire was developed and to determine the validity of the structure, confirmatory factor analysis was used. In this study, the statistical population was high school students, considering the impact of advertising in this age range; finally, a tool with four dimensions of informational literacy, aesthetic literacy, rhetorical literacy and promotional literacy was obtained. According to the confirmation of this tool in the present study, it can be used to examine the status of items, their order and prioritization from the perspective of the mentioned population.

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.

This study explores the impact of regular physical exercise on the quality of life and body image among Para-athletes, emphasizing the necessity of such activities for physical, social, and psychological health. This qualitative study employs content analysis and ethnomethodology to evaluate seven Para-athletes from the Navy's Paralympic Project, using focus group interviews to assess their perceptions. The findings reveal that participation in structured sports programs positively influences body image and quality of life, leading to improved performance in training, social interactions, and competitive events. The analysis suggests that motivation and self-esteem are fundamental to the sporting success of Paralympic athletes. Both external and internal motivations are crucial for sustaining athletic careers and overcoming challenges. Self-esteem enables athletes to remain confident in their abilities, even after setbacks.

The aim of this paper is to analyze the five grand parks in Dubai, United Arab Emirates (UAE) and provide a geoprocessing approach to different aspects such as sport, health, leisure, recreation, and public wellbeing. The study uses a hybrid of qualitative and quantitative approach as methodology. Sustainability offerings, accessibility for people of determination and special needs, typology and the geolocations of the grand parks plays crucial role in residents’ wellbeing. The paper concludes with recommendations for Dubai government to design new and innovative approaches to manage wellbeing of urban public places into the leisure environment for residents.

ClinVar is a web platform that stores around 774k curated entries, which allows exploring genetic variants and their associations with complex phenotypes. A partial set of ClinVar’s genetic associations were reported with conflict of interpretation or uncertain clinical impact significance, which currently challenges clinicians and geneticists. Here, we evaluate the performance of data pre-processing methods combined with classical prediction methods, such as Naive Bayes, Random Forest, and Support Vector Machine to build a meta-prediction model aiming to improve genetic pathogenicity interpretation. Models were trained with ClinVar data (September 2020), and genetic variants were annotated with eight functional impact predictors catalogued with SnpEff/SnpSift (v4.3). A 10-fold cross-validation strategy was performed for evaluation by accuracy, F1-Score, Receiver Operating Characteristic, Area Under Curve. The best meta-prediction model raises by combining one-hot encoding with tree-based classifiers as Random Forest, which shows Area Under Curve ≥ 0,93. We predict pathogenicity for 109k genetic variants, which were found labeled as uncertain significance or conflict of interpretation. Additionally, we implemented AmazonForest (https://www.lghm.ufpa.br/amazonforest), a web tool to query data for a set of 5k variants that were predicted with high pathogenic probability (RFprob >= 0.9).

Leonardo da Vinci (1452-1519) is considered one of the greatest geniuses of the Renaissance. His studies developed advanced ideas for his time, even in its most unknown aspects, such as: architecture, urban planning and restoration. He never studied formally, but he learned everything due to his method of observation, the study of other treatises and especially the group of artists with whom he collaborated. After the study of its codices a great interest and knowledge is detected, related to the design, the structural calculation, the materials and the constructive systems, in such a way that their proposals influenced the architecture of the Renaissance, through the work of other authors of your time. The purpose of this article is to make a critical analysis of its excellent architectural proposal in the cupola of the Duomo of Milan and the reasons why it was not carried out under its name. This proposal is included within a discipline in which it has never been recognized as such, but which demonstrated the same qualities as in other fields where it is recognized prestigiously.

In mobile robotics, laser scanners have a wide spectrum of indoor and outdoor applications, both in structured and unstructured environments, due its accuracy and precision. Most works that use this sensor have their own data representation and their own case-specific modeling strategies, and no common formalism is adopted. To address this issue, this manuscript presents an analytical approach for identification and localization of objects using a 2D LiDARs Our main contribution lies in formally defining laser sensor measurements and their representation, the identification of objects, their main properties and their location in a scene. We validate our proposal with experiments in generic semi-structured environments common in autonomous navigation, and we demonstrate its feasibility on multiple object detection and identification, following strictly its analytical representation. Finally, our proposal further encourages and facilitates the design, modeling and implementation of other applications that use laser scanners as a distance sensor.

The calibration of three-dimensional (3D) coordinates in augmented reality (AR) systems is a complex activity. It involves the recognition of environmental characteristics and technology that models the 3D space of the device, determining its position and orientation. In the industrial environment, it is common for AR applications to cover large spaces, making it difficult to maintain attributes such as precision and accuracy. The set of sensors and mapping algorithms available in HoloLens stimulate the development of virtual reality (VR) applications, in particular localization techniques. This study proposes calibration models of the 3D coordinates of the HoloLens for indoor industrial environments. The performance of tests in a relevant environment provides data necessary to evaluate the performance of the proposed models in terms of precision and accuracy in determining point coordinates in the study environment. The results show improvements in determining the axes that define the 3D space, with a direct influence on the position of the points observed in the experiment

Over the past few decades, the growth of the urban population has been remarkable. Nowadays, 50% of the population lives in urban areas, and forecasts point that by 2050 this number will reach 70%. Today, 64% of all travel made is within urban environments and the total amount of urban kilometers traveled is expected to triple by 2050. Thus, seeking novel solutions for urban mobility becomes paramount for 21st century society. In this work, we discuss the performance of vehicular networks. We consider the metric Delta Network. The Delta Network characterizes the connectivity of the vehicular network through the percentage of travel time in which vehicles are connected to roadside units. This article reviews the concept of Delta Network and extends its study through the presentation of a general heuristic based on the definition of scores to identify the areas of the road network that should receive coverage. After defining the general heuristic, we show how small changes in the score computation can generate very distinct (and interesting) patterns of coverage, each one suited to a given scenario. In order to exemplify such behavior, we propose three deployment strategies based on simply changing the computation of scores. The results show that the strategies derived from the general heuristic are very interesting, all of them deploying roadside units in a circle pattern around the traffic epicenter.

The use of optical fibers is increasing in modern aircraft because it helps solve challenges of size, weight, communication, and reliability in new aircraft generation. This work describes a video and power transmission system using optical fibers (PoF) for in-flight entertainment (IFE) system application. We present the benefits and the limitations of this application, and we perform two practical experiments to demonstrate their performance. It used off-the-shelf devices in the experiments, such as one 15-W semiconductor laser operating at 808 nm, GaAs photovoltaic converters, optical transmitters and receivers, and video monitors. The power and video signals were transmitted using two 50-m multimode fibers. In addition, we proposed and tested two types of energy transformation units (ETU), which are responsible for supplying electrical energy to the IFE video monitor and the optical fiber receiver.

This paper presents a study on the influence of the frequency variation of a nonlinear1 control allocation technique execution, developed by the author [1], named by Fast Control2 Allocation (FCA) for the Quadrotor Tilt-Rotor (QTR) aircraft. Then, through Software In The3 Loop (SITL) simulation, the proposed work considers the use of Gazebo, QGroundControl, and4 Matlab applications, where different frequencies of the FCA can be implemented separated in5 Matlab, always analyzing the QTR stability conditions from the virtual environment performed in6 Gazebo. TheresultsshowedthattheFCAneedsatleast200HzoffrequencyfortheQTRsafeflight7 conditions, i. e., 2 times smaller than the main control loop frequency, 400 Hz. Lower frequencies8 than this one would case instability or crashes during the QTR Operation.

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.

This article presents a combined route and path planning strategy to guide Skid-Steer Mobile Robots (SSMRs) in scheduled harvest tasks within expansive crop rows with complex terrain conditions. The proposed strategy integrates: i) a global planning algorithm based on the Traveling Salesman Problem under the Capacitated Vehicle Routing approach and Optimization Routing (OR-tools from Google) to prioritize harvesting positions by minimum path length, unexplored harvest points, and vehicle payload capacity, and ii) a local planning strategy using Informed Rapidly-exploring Random Tree (IRRT*) to coordinate scheduled harvesting points while avoiding low-traction terrain obstacles. The global approach generates an ordered queue of harvesting locations, maximizing the crop yield in a workspace map. In the second stage, the IRRT* planner avoids potential obstacles, including farm layout and slippery terrain. The path planning scheme incorporates a traversability model and a motion model of SSMRs to meet kinematic constraints. Experimental results in a generic fruit orchard demonstrated the effectiveness of the proposed strategy. In particular, the IRRT* algorithm outperformed RRT and RRT* with 96.1% and 97.6% smoother paths, respectively. The IRRT* also showed improved navigation efficiency, avoiding obstacles and slippage zones, making it suitable for precision agriculture.

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.

Exercises for lower trapezius (LT) often use overhead positions, causing compressive forces to the subacromial space. Scapular retraction would be an alternative to activate LT muscle. Electromyography of infraspinatus (IS), upper (UT) and LT was recorded during scapular retraction under progressive adduction loads of 42 participants, divided in 2 groups: with (SP, n=26) and without shoulder pain (nSP, n=16). The adduction loads of 20, 30, 40 and 50% of the maximal voluntary contraction were applied using a load cell. Normalized electromyography and the ratio between UT and LT (UT:LT) were used for statistical analysis. No differences were observed between groups, but a condition effect occurred for all muscles: UT showed higher values at 50% vs. 20% (p=0.004); LT showed higher values on 40% and 50% (p=0.001; 0.006). Higher values for IS were noted at 40% (vs 20%; p=0.04), and at 50% (vs. 20%; p=0.001, vs. 30%, p=0.001; vs. 40%; p=0.001). UT:LT showed lower values at 50% (vs. 20%; p=0.001, and vs. 30%; p=0.016). Scapular retraction with adduction loads at 40-50% is an alternative to overhead exercises aiming to activate the LT and the IS muscles. The exercise ensures higher levels of LT and IS excitation, without increasing UT excitation.

This study was conducted with the objective of investigating the enrichment of weaned piglet diets with organic selenium (proteinate selenium) and inorganic selenium (sodium selenite) with two addition levels (0.15 and 0.30 mg/kg). A total of 40 piglets (20 castrated males and 20 females) weaned at 28 days of age with an average initial weight of 6.60±1.06 kg were used. The treatments were: Control diet (Control diet); Selenium-enriched control diet proteinate with 0.15 mg/kg of selenium added (SeOrg-0.15); Selenium-enriched control diet proteinate with 0.30 mg/kg of selenium added (SeOrg-0.30); Control diet enriched with sodium selenite with 0.15 mg/kg of selenium added (SeInorg-0.15); and Control diet enriched with sodium selenite with 0.30 mg/kg of selenium added (SeInorg-0.30). The presence of selenium in the control diet came from the ingredients and the mineral supplement. The following data were analyzed: productive performance; digestibility of nutrients and energy; morphometry and intestinal integrity; serum biochemical parameters; and gene expression of selenoproteins in intestinal epithelium and liver tissue of piglets. The SeOrg-0.30 treatment caused a reduction (P

Purpose: This study aimed to evaluate the nanomechanical properties and chemical composition of restorative materials and dental surfaces using different toothpastes. Methods: Enamel (n=60) and dentin (n=60) bovine blocks were obtained and restored using resin-modified glass ionomer cement (RMGIC, n=30) or composite resin (CR, n=30) to form the dentin adjacent to RMGIC (DRMGIC), enamel adjacent to RMGIC (ERMGIC), dentin adjacent to CR (DCR), and enamel adjacent to CR (ECR). After restoration, one hemiface of each specimen was coated with an acid-resistant varnish to create the control (C) and eroded (E) sides (erosion: 5 days, 4 × 2 min/day; 1% citric acid / abrasion: 2 × 15 s followed by immersion on slurries 2 min). Three toothpastes were used: without fluoride (WF; n=10), sodium fluoride (NaF; n=10), and stannous fluoride (SnF2; n=10). The specimens were analyzed for nanohardness (H), elastic modulus (Er), and chemical composition using energy-dispersive X-ray spectroscopy (EDS) and Raman microscopy. Data were analyzed using ANOVA two-way repeated measures and Tukey’s test (α = 0.05). Results: The NaF presented lower values of H for DRMGIC-C, with a statistical difference for WF (p < 0.05). SnF2 resulted in lower Er values for ERMGIC-E and RMGIC-E than WF and NaF (p < 0.05). WF showed lower calcium and phosphorus concentrations for DCR-E than other types of toothpastes (p < 0.05). Only stannous-based toothpaste damaged the elasticity of eroded glass ionomer restorations performed in enamel. Toothpastes with fluoride was capable for maintaining main chemical elements of dentin adjacent to restorative materials under challenge conditions.

Two distinct measures of information, connected respectively to the amplitude and phase of the wave function of a particle, are proposed. There are relations between the time derivatives of these two measures and their gradients on the configuration space, which are equivalent to the wave equation. The information related to the amplitude measures the strength of the potential coupling of the particle (which is itself aspatial) with each volume of its configuration space, i.e. its tendency to participate in an interaction localized in a region of ordinary physical space corresponding to that volume. The information connected to the phase is that required to obtain the time evolution of the particle as a persistent entity starting from a random succession of bits. It can be considered as the information provided by conservation principles. The meaning of the so-called "quantum potential" in this context is briefly discussed.

This study analyzes the correlation between the lifetime and the rest energy of the unstable particle states with a lifetime greater than the zeptosecond (10⁻²¹ s), using data available from the Particle Data Group. This set of states seems to be divided into three groups, in each of which the two quantities can be correlated through a remarkably accurate power law. Although this fact does not represent anything new compared to the predictions of the Standard Model, it nevertheless reveals an unexpected order structure in the set of particle decays, emerging from such predictions.

Hymenaea courbaril is an endangered species, promising to reforestation programs and mainly explored as a wood source. The available information concerning long-term storage methods, seed recalcitrance, parental, and substrate influence is scarce. This study focused on the seed behavior according to population origin and during one-year storage, also testing the efficiency of the low-temperature conservation. Variations between the uncertainty indexes were found to the studied populations after long-term storage. There was no significant loss of the germination potential in consequence of the prolonged storage period. Although, older seeds promoted gradually greater delayed germination. Germination speed, synchrony, and uncertainty indexes were substantially different between the -20° conservation and control. H. courbaril seeds are capable of long-term storage without losing their germination potential, indicating an orthodox behavior.

Climate change related increases in frequency and intensity of heatwaves affect viticulture, leading to losses in yield and grape quality. We assessed whether canopy architecture manipulation mitigates the effects of summer stress in a Mediterranean vineyard. Muscat of Alexandria grapevines were monitored during 2019-2020. Two canopy shoot positioning treatments were applied: Vertical shoot positioning (VSP); and Modulated shoot positioning (MSP), the west side upper foliage released to promote partial shoot leaning, shading the clusters. Clusters were sampled at pea size (PS), veraison (VER) and full maturation (FM). Measurements included rachis anatomy and hydraulic conductance, and aquaporins (AQP) and stress-related genes expression in cluster tissues. Results show significant seasonal and interannual differences in Kh and vascular anatomy. At VER, Krachis , Krachis+pedicels, and xylem diameter decreased but were unaffected by treatments. The Phloem/Xylem ratio was either increased (2019) or reduced (2020) in MSP, compared to VSP. Most AQP were down-regulated at FM in pedicels, and up-regulated at VER in pulp. A potential maturation shift in MSP was observed, confirmed by the up-regulation of several stress-related genes in all tissues. The study pinpoints the role of canopy architecture in berry water relations and stress response during ripening.

: In our previous work we had developed an hxt-null Saccharomyces cerevisiae strain displaying high xylose reductase, xylitol dehydrogenase and xylulokinase activities that proved to be useful as a chassis strain to study new xylose transporters, as SsXUT1 from Scheffersomyces stipitis. Spathaspora passalidarum and Spathaspora arborariae have in their genomes genes with high sequence similarity (78-80%) to SsXUT1. To characterize these putative transporter genes (SpXUT1 and SaXUT1, respectively) they were expressed in the same chassis strain as SsXUT1. Surprisingly, the cloned genes could not restore the ability to grow in several monosaccharides tested, although the strains expressing the SsXUT1 and SpXUT1 permeases, after growth on maltose, showed the presence of 14C-glucose and 14C-xylose transport activity. An important feature of these permeases is that SsXUT1 lacks lysine residues in its N-terminal domain with high-confidence ubiquitinylation potential, and has only one at the C-terminal domain, while the SpXUT1 transporter had several of such residues at its C-terminal domain. When the SpXUT1 gene was cloned in a truncated version lacking such lysine residues, the permease allowed grow on glucose or xylose, and even promoted xylose fermentation by the hxt-null strain. In another approach, we deleted two arrestins known to be involved in sugar transporter ubiquitinylation and endocytosis (ROD1 and ROG3), but only the rog3Δ strain allowed modest growth on these sugars. Taken together, these results suggest that to allow efficient sugar transporter expression in S. cerevisiae the lysines involved in transporter endocytosis should be removed from the sequence of the permease.

The purpose of this article is to draw attention to the challenges faced by business organizations implementing sustainable solutions in the United Arab Emirates (UAE) and the wider Gulf Coast Countries (GCC) region. To this end, our study examines an academic theory supporting the implementation of responsible solutions to the market. Ultimately, the authors hope to inspire the reader to consider what he or she can do to ameliorate the existing challenges encountered by sustainable businesses. The analysis presented in this article implies that in recent markets, the implementation of the sustainability theory is essential for further development. The research project contributes to the increase of knowledge about corporate and organizational challenges related to running a responsible business, as well as challenges related to the application of environmental, social and economic aspects of sustainable business practices. The research is currently limited to conceptual analysis, literature review and a survey conducted during the Sustainability Week 2019 in Abu Dhabi, United Arab Emirates. Nevertheless, this is the first stage of the research project conducted by the research team in cooperation with enterprises that implement responsible solutions in many global markets, and in UAE market. The scope of the first stage of the study was limited to the analysis of data clarifying the concept of the model specified in the research. To prove the validity of the model it will be implemented and tested in cooperation with organizations participating in the research.

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.

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.

The exact, non perturbative, response theory developed within the field of nonequilibrium molecular dynamics, also known as TTCF (Transient Time Correlation Function) applies to quite general dynamical systems. Its key element is called dissipation function, because it represents the power dissipated by external fields acting on the particle system of interest, whose coupling with the environment is given by deterministic thermostats. This theory has been initially developed for time independent external perturbations, and then it has been extended to time dependent perturbations. It has also been applied to dynamical systems of different nature, and to oscillator models undergoing phase transitions, which cannot be treated withe.g. linear response theory. The present work includes time dependent stochastic perturbations, in the theory, using the Karhunen-Loeve theorem. This leads to three different investigations of a given process. One in which a single realization of the stochastic coefficients is fixed, and averages are taken only over the initial conditions, as in a deterministic process. In the second, the initial condition is fixed, and averages are taken with respect to the distribution of stochastic coefficients. In the last investigations, one averages over both initial conditions and stochastic coefficients. We conclude illustrating the applicability of the resulting exact response theory with simple examples.

The double nature, wave and corpuscular, of the material particles is usually considered incomprehensible as it cannot be represented visually. It is proposed to the student, in the introductory courses, as a fact justified by quantum interference experiments of which, however, no further analysis is possible. In this note we propose a description of the wave function in terms of a simple electrical analogy, which reproduces at least some of its essential properties. The aim we propose is to provide a cognitive representation of an analogical type: starting from a classical context (electrical circuits) and introducing in an appropriate way the notions of "wave" and "particle", we show how typically quantum properties such as delocalization and entanglement emerge in a natural, understandable and intuitive way.

Research on Traffic Light Recognition (TLR) has grown in recent years, primarily driven by the growing interest in autonomous vehicles development. Machine Learning algorithms have been widely used to that purpose. Mainstream approaches, however, require large amount of data to properly work, and as a consequence, a lot of computational resources. In this paper we propose the use of Expert Instruction (IE) as a mechanism to reduce the amount of data required to provide accurate ML models for TLR. Given an image of the exterior scene taken from the inside of the vehicle, we stand the hypothesis that the picture of a traffic light is more likely to appear in the central and upper regions of the image. Frequency Maps of traffic light location were thus constructed to confirm this hypothesis. The frequency maps are the result of a manual effort of human experts in annotating each image with the coordinates of the region where the traffic light appears. Results show that EI increased the accuracy obtained by the classification algorithm in two different image datasets by at least 15%. Evaluation rates achieved by the inclusion of EI were also higher in further experiments, including traffic light detection followed by classification by the trained algorithm. The inclusion of EI in the PCANet achieved a precision of 83% and recall of 73% against 75.3% and 51.1%, respectively, of its counterpart. We finally presents a prototype of a TLR Device with that expert model embedded to assist drivers. The TLR uses a smartphone as a camera and processing unit. To show the feasibility of the apparatus, a dataset was obtained in real time usage and tested in an Adaptive Background Suppression Filter (AdaBSF) and Support Vector Machines (SVMs) algorithm to detect and recognize traffic lights. Results show precision of 100% and recall of 65%.

Indoor scene recognition and semantic information can be helpful for social robots. Recently, in the field of indoor scene recognition, researchers have incorporated object-level information and shown improved performances. This paper demonstrates that scene recognition can be performed solely using object-level information in line with these advances. A state-of-the-art object detection model was trained to detect objects typically found in indoor environments and then used to detect objects in scene data. These predicted objects were then used as features to predict room categories. This paper successfully combines approaches conventionally used in computer vision (YOLO) and Term Frequency-Inverse Document Frequency (TF-IDF). These approaches could be further helpful in the field of embodied research and dynamic scene classification, which we elaborate on.

Harmonic resonances are part of the Power Quality (PQ) problems of electrified railways and have serious consequences for the continuity of service and integrity of components in terms of overvoltage stress. The interaction between Traction Power Stations (TPSs) and trains that causes line resonances is briefly reviewed showing the dependence on infrastructure conditions. The objective is real-time monitoring of resonance conditions seen first of all from the onboard panto-graph interface, but it is equally applicable at TPS terminals. Voltage and current spectra, and de-rived impedance and power spectra, are analyzed proposing compact and efficient methods based on Short-Time Fourier Transform, suitable for real-time implementation with the hardware avail-able for energy metering and harmonic interference monitoring. The methods are tested by sweeping long recordings taken at some European railways, covering cases of longer and shorter supply sections, with a range of resonance frequencies of about one decade. They give insight into the spectral behavior of resonances, their dependency on position and change over time, and criteria to recognize genuine infrastructure resonances from rolling stock emissions.

This study explores an eco-friendly approach to synthesizing silver nanoparticles (AgNPs) using soybean leaf extracts, employing a reaction with silver nitrate at 65°C for 2.5 h. Optimal results were achieved at extract concentrations of 3.12 and 6.25 mg leaf mL-1, termed 3.12AgNP and 6.25AgNP, respectively. UV-Vis spectrophotometric analysis between 350-550 nm exhibited a peak at 410-430 nm, along with a color transition in the suspensions from pale yellow to brown, indicating successful synthesis. Dynamic light scattering (DLS) further delineated favorable properties of these AgNPs, including nanometric dimensions (73–104 nm), negative charge, and moderate polydispersity, portraying stable and reproducible synthesis reactions. The bioreduction mechanism, possibly expedited by leaf extract constituents such as amino acids, phenolic acids, and polysaccharides, remains to be fully elucidated. Notably, the study underscored the potent nematicidal effectiveness of the biosynthesized AgNPs, especially 6.25AgNP, against Pratylenchus brachyurus, a common plant parasitic nematode in tropical soybean cultivation regions. In vitro tests illustrated significant nematicidal activity at concentrations above 25 µmol L-1, while in vivo experiments displayed pronounced nematode population diminishment in plant roots, particularly with a 6.25AgNP rhizosphere application at concentrations of 500 µmol L-1 or twice at 250 µmol L-1, attaining a reproduction factor below 1 without any morphological nematode alterations. The research highlights the potential of 6.25AgNPs derived from soybean leaf extracts in forging sustainable nematicidal solutions, marking a significant stride towards eco-friendly phytonematode management in soybean cultivation. This novel methodology signals a promising avenue in harnessing botanical resources for nematode control, propelling a greener agricultural horizon.

Macromolecular crystallography at cryogenic temperatures has so far provided the majority of the experimental evidence that underpins the determination of the atomic structures of proteins and other biomolecular assemblies by means of single crystal X-ray diffraction experiments. One of the core limitations of the current methods is that crystal samples degrade as they are subject to X-rays, and two broad groups of effects are observed: global and specific damage. While the currently successful approach is to operate outside the range where global damage is observed, specific damage is not well understood and may lead to poor interpretation of the chemistry and biology of the system under study. In this work, we present a phenomenological model in which specific damage is understood as the result of a single process, the steady excitation of crystal electrons caused by X-ray absorption, which acts as a trigger for the bulk effects that manifest themselves in the form of global damage and obscure the interpretation of chemical information from XFEL and synchrotron structural research.

In this article, it is demonstrated that if the zeta function does not have a sequence of zeros whose real part converges to 1, then it cannot have any zeros in the critical strip, showing that the Riemann Hypothesis is false.

This research was conducted on the Maribaya Timur school community in Lembang Subdistrict, West Bandung Regency, Indonesia, which is an active community in the area that is threatened by the potential for earthquake disasters due to the active Lembang fault. Disaster risk reduction efforts are pursued through increasing school-based preparedness that involves members of the school community, surrounding communities and various institutions that are associated with reducing the risk of school-based earthquake. Increasing preparedness against earthquakes focuses more on aspects of capacity building of school communities in reducing disaster risk, while aspects of vulnerability and threats have not been the focus of disaster risk reduction. The steps taken refer to the element of preparedness by aligning with the conditions, needs and potential that exist in the school community. Theoretically, if the school community has preparedness to face an earthquake disaster, the risk of earthquake disaster in the school community will be reduced so that it can minimize losses, victims and suffering that will be caused by the earthquake disaster.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), an RNA virus, is responsible for coronavirus disease 2019 (COVID-19) pandemic of 2020. Experimental evidence suggests that microRNA can mediate an intracellular defence mechanism against some RNA viruses. The purpose of this study was to identify microRNA with predicted binding sites in the SARS-CoV-2 genome, compare these to their microRNA expression profiles in lung epithelial tissue and make inference towards possible roles for microRNA in mitigating coronavirus infection. We hypothesize that high expression of specific coronavirus-targeting microRNA in lung epithelia may protect against infection and viral propagation, conversely low expression may confer susceptibility to infection. We have identified 128 human microRNA with potential to target the SARS-CoV-2 genome, most of which have very low expression in lung epithelia. Six of these 128 microRNA are differentially expressed upon in vitro infection of SARS-CoV-2. Twenty-eight and 23 microRNA also target the SARS-CoV and MERS-CoV, respectively. In addition, 48 and 32 microRNA are commonly identified in two other studies. Further research into identifying bona fide coronavirus targeting microRNA will be useful in understanding the importance of microRNA as cellular defence mechanism against pathogenic coronavirus infections.

This work focused on the evaluation of some machine learning (ML) models and their application in e-health, using intermediate nodes within an Internet of Things (IoT) platform used for heartbeat anomaly detection. For the evaluation of ML models, a set of statistical validation metrics was selected. These metrics were applied in the training, testing and validation phases of the models. The results obtained can determine relevant factors for the selection of ML models, either based on the statistical and intrinsic efficiency of the ML models, or on their suitability to be implemented in intermediate nodes within an IoT platform. the more Lightweight models such as Simple Linear Regression, Logistic Regression, and K Nearest Neighbors, could easily operate in intermediate nodes, and they are models that require low processing and storage to work. In conclusion, the approach for intermediate nodes of Internet of Things platforms using cognitive networks decreases the processing cost in cloud computing and transfers it to the fog layer.

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.

Urban planning is recognized as an interaction between the state and society, which aims to articulate public policies in the territory, facilitating their administration in favor of greater development and well-being of society. However, this interaction becomes complex because consumption demands increase, and the needs of the community exceed the capacity of the urban ecosystem to supply them, hindering its sustainable functionality. With this panorama, it becomes relevant to study urban planning from a sustainable environmental planning perspective, based on four topics: urban planning, sustainability, resilience and smart cities. The methodology used is based on a bibliometric study through a PRISMA adjustment to 87 articles, supported by VOSviewer® to construct and visualize the co-occurrence networks of important terms extracted from a body of scientific literature. The main result is to consider cities with a complex systems approach that works like a gear, that is, there is a connective element between inter- and intra-urban processes. This relationship is the key factor that allows understanding their synchronization, stating that the deepening of each of these topics is crucial to the ideal of a territorial administration through time scales, by means of adaptive cycles, allowing to provide new tools to concepts such as carrying capacity and the measurement of the environmental footprint.

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.

Ozonated oil has several benefits for humans, as it contributes to numerous interventions, maintaining the quality of life and the well-being of individuals. Being a natural product, it has few or almost no side effects. Thus, the study aimed to verify the sensitivity and/or resistance of fixed o “Ozonated” and “Non-Ozonated” oils from Mauritia flexuosa (Buriti), Carapa guaianensis (Andiroba) and essential “Ozonated” oils from Menta piperita (Mint), Eugenia caryophyllus (Clove) in different concentrations, against internationally known bacteria from the American Type Culture Collection – ATCC, comparing with the “Non-Ozonated” versions of the respective oils, using the Agar diffusion technique. Thus, it is evident that the ozonation of the fixed oils of Buriti and Andiroba, as well as the essential oils of Mint and Clove, provided significant results, although they were statistically different. The Buriti and Andiroba oil were ineffective in inhibiting microorganisms. On the other hand, the essential oil of Mint and Clove obtained similar activity of inhibition of microorganisms. With regard to Ozonation, the Essential Oil of “Ozonated” Clove provided greater activity than the “Non-Ozonated” one, which inhibited only one tested microorganism, in addition to producing changes in its chemical composition, requiring individualized studies for the ozonation of each essential oil.

The research explores the impact of financial indicators on the credit ratings of companies listed on the S&amp;P 500, employing a Sys-GMM Model to address endogeneity concerns. The study investigated three independent variables categorized as market and survival factors alongside with seven control variables sourced from leverage, liquidity, interest coverage, profitability, market, survival, and macroeconomic domains. The sample comprised 2398 observations from Capital IQ Pro, spanning nine years (2013 to 2021) and encompassing 240 public companies. The findings suggest that neither Tobin's Q (TQ) and Total Shareholder Return (TSR) lack significant correlations with credit ratings, implying that stock market performance and total shareholder return do not directly impact credit ratings. In contrast, the Altman Z-score (AZS) emerged as a significant predictor, indicating its importance in assessing credit risk. These insights enhance understanding of financial indicators' impact on credit ratings, aiding financial institutions and companies in prudent lending and financing decisions.

Breast cancer represents the most common neoplasm worldwide. Viral infections are involved with carcinogenesis, especially those caused by oncogenic Human Papillomavirus (HPV) genotypes. The relationship between HPV and various types of cancer, such as breast and lung, still requires further studies. After infection with HPV, there is a remodeling of the tumor microenvironment, providing a post-infection alteration with immunosuppressive characteristics. This study evaluated the role of HPV in breast adenocarcinoma cell lineage (MDA-MB-231), transfected with the HPV16 E5, E6, and E7 oncogenes and co-cultured with PBMCs. Immunophenotyping was performed. There was an increase in CD4+ T cells number when compared with non-transfected and transfected MDA-MB-231, especially the Treg profile. Moreover, proinflammatory intracellular cytokines, such as IFN-γ, TNF-α, and IL-17 were impaired by transfected cells and a decrease in the cytolytic ac-tivity of the CD8+ and CD56+ lymphocytes was also observed in the presence of HPV oncogenes, mainly with E6 and E7 in NK and TCD8+ cells. In conclusion, MDA-MB-231 breast cell lineage transfected with HPV oncogenes can downregulate the number and function of lymphocytes and monocytes.

Among many other themes, Leonardo da Vinci’s Manuscript B contains several drawings of centrally planned churches, some of which are represented using a plan view paired with a bird’s-eye view. The use of a bird’s-eye instead of an elevation represents an innovative depiction technique, which allows to combine the immediacy of the perspective view with the measurability of the façades, and therefore to describe the three-dimensionality of the buildings. To understand the reasons behind the use of this original technique, the edifices’ shape and classify them we decided to use 3D digital reconstruction techniques, for their ability to avoid misunderstandings in the reconstruction process and in the results. This article describes the method to create the digital models of sixteen churches. A Visual programming language (VPL) script was used as 3D base for modelling the churches achieved from a classification code expressing the aggregative rules of the churches. Then, the geometric process for the construction of the plan and its relationship with the elevation measures was studied for each church. Finally, this information was used for the completion of the 3D models, distinguishing more output variants each time there was an inconsistency between plan and perspective view, a variability of one architectural element or an uncertainty.

All neurological diseases have their pathological progress influenced by microglial cells, which react to insults with multiple morphofunctional phenotypes. However, the complete morphological spectrum of the reactive microglia, revealed by the three-dimensional microscopic reconstruction, has not been explored in detail in virus limbic encephalitis. Here, we used anatomical series of brain sections from a previous study using Piry arbovirus encephalitis, expanding the original investigation to CA1/CA2. The morphological response of the homeostatic and reactive microglia was investigated 8 days after infection. The hierarchical cluster and linear discriminant function analysis of multimodal morphometric features allowed to distinguish between the microglial morphology of infected individuals and controls. In order to represent more broadly the morphological spectrum of the microglia of each cluster, representative cells of the homeostatic and reactive microglia were chosen, using the sum of the distances of each cell in relation to all the others. Overall, the multivariate statistical analysis showed that the reactive microglia of infected animals have more complex trees and thicker branches, that cover a larger volume of tissue than the microglia of control animals. With this approach a more reliable representation of the microglia dispersion in the Euclidean space, would be closer to the spectrum of morphotypes of the control and infected groups, and help to avoid hiding the morphological kaleidoscope of surveillant and reactive microglia. As form precedes function in nature, our findings are a good starting point for future research with integrative approaches to microglia form and function.

All neurological diseases have their pathological progress influenced by microglial cells, which react to insults with multiple morphofunctional phenotypes. However, the complete morphological spectrum of the reactive microglia, revealed by the three-dimensional microscopic reconstruction, has not been explored in detail in virus limbic encephalitis. Here, we used anatomical series of brain sections from a previous study using Piry arbovirus encephalitis, expanding the original investigation to CA1/CA2. The morphological response of the homeostatic and reactive microglia was investigated 8 days after infection. The hierarchical cluster and linear discriminant function analysis of multimodal morphometric features allowed to distinguish between the microglial morphology of infected individuals and controls. In order to represent more broadly the morphological spectrum of the microglia of each cluster, representative cells of the homeostatic and reactive microglia were chosen, using the sum of the distances of each cell in relation to all the others. Overall, the multivariate statistical analysis showed that the reactive microglia of infected animals have more complex trees and thicker branches, that cover a larger volume of tissue than the microglia of control animals. With this approach a more reliable representation of the microglia dispersion in the Euclidean space, would be closer to the spectrum of morphotypes of the control and infected groups, and help to avoid hiding the morphological kaleidoscope of surveillant and reactive microglia. As form precedes function in nature, our findings are a good starting point for future research with integrative approaches to microglia form and function.

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.

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.

A theoretical description of quantum jumps at the level of elementary particles is proposed, based on a micro-cosmological interpretation of their de Broglie phase. The third quantization formalism proposed in current literature for the description of baby universes in quantum cosmology is used here to describe the breakdown of unitarity in the transition from the pre-jump to the post-jump wave function. The corpuscular aspect manifested by the particle in the micro-interaction that originates the jump is represented by a pair of evanescent "micro-universes", respectively pre- and post-jump, connected by a wormhole. The latter represents the actual implementation of the interaction that leads to the projection on the outgoing state; this interaction is always local, even when the selected outgoing state is entangled. Therefore, the decoherence which leads to the emergence of classicality is originated by the same fundamental interactions of the Standard Model involved in the unitary evolution of the wave function. The objective nature of the reduction process admits implications on the possibility of using the formalism in the cosmological context, which are briefly discussed.

This paper explores an event-based version of quantum mechanics which differs from the commonly accepted one, even though the usual elements of quantum formalism, e.g., the Hilbert space, are maintained. This version introduces as primary element the occurrence of micro-events induced by usual physical (mechanical, electromagnetic and so on) interactions. These micro-events correspond to state reductions and are identified with quantum jumps, already introduced by Bohr in his atomic model and experimentally well established today. Macroscopic bodies are defined as clusters of jumps; the emergence of classicality thus becomes understandable and time honoured paradoxes can be solved. In particular, we discuss the cat paradox in this context. Quantum jumps are described as temporal localizations of physical quantities; if the information associated with these localizations has to be finite, two time scales spontaneously appear: an upper cosmological scale and a lower scale of elementary "particles''. This allows the interpretation of the Bekenstein limit like a particular informational constraint on the manifestation of a micro-event in the cosmos it belongs. The topic appears relevant in relation to recent discussions on possible spatiotemporal constraints on quantum computing.

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.

Soiling accumulated on a photovoltaic (PV) module can significantly reduce the transmittance of the cover glass, resulting in power losses and consequent economic losses. Natural atmospheric parameters influence the accumulation of soiling at the various geographic locations. In this paper, the approaches and outcomes of the research studies on either indoor (simulator-based) or outdoor (field-based) PV soiling have been thoroughly reviewed. Different parameters depicted for the power loss of PV modules are analyzed individually and presented. Moreover, this study delves into a detailed examination of the key factors influencing dust depositions on PV modules in various geographical regions, with a particular focus on their relationship with climatic conditions. This way, probable future research directions to quantify soiling losses are identified. In addition, different loss prevention and mitigation techniques are also reviewed. This makes it possible to highlight effective strategies and pinpoint potential future research lines in these areas.

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 aim was to evaluate levels of compassion fatigue in nursing professionals working in complex care units of a Brazilian university hospital. A cross-sectional, descriptive, and correlational study was carried out with nursing workers from complex care units of a University Hospital. Data were collected in the second half of 2019, in the pre-pandemic period of COVID-19, using the Brazilian version of the Professional Quality of Life Scale (ProQoL-BR). A total of 146 individuals partici-pated, including 41 (28.1%) nurses, 92 (63.0%) nursing technicians and 13 (8.9%) nursing assis-tants. It was observed that 26.1% presented high level of compassion satisfaction. For 17.5% there was level of burnout and 49.7%, medium level of burnout; and 22.0% with high and 46.1% with medium level of secondary traumatic stress. Twenty-eight (19.2%) professionals had compassion fatigue, of which 16 (57.1%) were nursing technicians. There is a high percentage of professionals with medium and high rates of burnout and secondary traumatic stress, a fact that is reinforced by the presence of compassion fatigue in almost one fifth of the studied individuals. These results highlights how much the health of these workers can be affected by living with traumatic patient experiences.

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.

This paper investigates if Corporate Social Responsibility (CSR) reports published by a selected group of Nordic companies are aligned with the Global Reporting Initiative (GRI) standards. To achieve this goal, several natural language processing, and text mining techniques were implemented and tested. We extracted strings, corpus, and hybrid semantic similarities from the reports and evaluated the models through the intrinsic assessment methodology. A quantitative ranking score based on index matching was developed to complement the semantic valuation. The final results show that Latent Semantic Analysis (LSA) and Global Vectors for Word Representation (GloVE) are the best methods for our study. Our findings will open the door to the automatic evaluation of sustainability reports which could have a strong impact on the environment.

Documenting cultural heritage by using artificial intelligence (AI) is crucial for preserving the memory of the past and a key point for future knowledge. However, modern AI technologies make use of statistical learners that lead to self-empiricist logic, which, unlike human minds, use learned non-symbolic representations. Nevertheless, it seems that it is not the right way to progress in AI. If we want to rely on AI for these tasks, it is essential to understand what lies behind these models. Among the ways to discover AI there are the senses and the intellect. We could consider AI as an intelligence. Intelligence has an essence, but we do not know whether it can be considered “something” or “someone”. Important issues in the analysis of AI concern the structure of symbols -operations with which the intellectual solution is carried out- and the search for strategic reference points, aspiring to create models with human-like intelligence. For many years, humans, seeing language as innate, have carried out symbolic theories. Everything seems to have skipped with the advent of Machine Learning. In this paper, after a long analysis of history, the rule-based and the learning-based vision, we propose KERMIT as a unit of investigation for a possible meeting point between the different learning theories. Finally, we propose a new vision of knowledge in AI models based on a combination of rules, learning and human knowledge.

Cultivating research competencies facilitated by the use of technology in the university is crucial to boost acquisition of knowledge, educational innovation, and successful professional development. The objective of this article is to analyze the evolution and characteristics of scientific production that has had the greatest impact on the momentum of investigative competencies and their articulation within technological scenarios. Applying various selection criteria in the Scopus database, we utilized systematic, bibliometric mapping as a methodological strategy in which 250 articles related to the topic were identified, then analyzed with the semantic analysis software VOSViewer. The results indicate that there is an emerging line of research on the subject since 2016 and point to the underdevelopment of lines that associate research skills with digital literacy, information literacy, digital libraries databases, and the development of critical thinking.

The present study aims to analyze scientific production about technological cooperation networks in biotechnology sector, based on bibliometrics network analysis. We used the Gephi software to identify groups of partnerships, proving that the cooperation relationship is a practice used, re-sulting technological development. Findings identify that in the path for new resources that com-plement skills and competences universities are an important player in this cooperative ecosystem, and The United States is a large hub, with an extensive network of global cooperation. A strong role of its researchers in the publication of scientific articles in cooperation is highlighted. This study contributes to the advancement of the discussion about cooperative networks, as well as to the development of policies aimed at the biotechnology sector advancements

We improved a magnetic scanning microscope for measuring the magnetic properties of minerals in thin sections of geological samples at submillimeter scales. The microscope is comprised of a 200 µm diameter Hall sensor that is 142 µm from the sample; an electromagnet capable of applying to the sample up to 500 mT dc magnetic fields over a 40 mm diameter region; a second Hall sensor arranged in a gradiometric configuration to cancel the background signal applied by the electromagnet and reduce overall noise in the system; a custom-designed electronics to bias the sensors and provide adjustment for background signal cancelation; and a scanning XY stage with micrometer resolution. Our system achieves a spatial resolution of 220 µm with noise at 6.0 Hz of »300 nT_rms/(Hz)^1/2 in an unshielded environment. The magnetic moment sensitivity is 1.3 × 10⁻¹¹ Am².^1/2 We successfully measured the representative magnetization of a geological sample using an alternative model that takes into account the sample geometry and identified different micrometric characteristics in the sample slice.

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.

The protection of grapevine from the diseases is now particularly focused on the development of environmentally friendly strategies. Although sulphur is not in itself a toxic substance, a large use towards powdery mildew, in organic vineyards especially, may cause problems to environment, health and safety of viticultural workers and plant phytotoxicity. The activity on powdery mildew of sulphur applied at doses reduced up to 50% in tank mixtures with silicates and Equisetum arvense based products, never tested on grapevine, was assessed. Two-year trials were carried out applying the products every 7-9 days in the period of greatest risk for spring ascosporic infections, in two organic vineyards in the Abruzzo region, Italy. The effectiveness towards the disease of the mixtures was demonstrated, often to a greater extent than that of full-dose sulphur, normally used in the vineyards. Furthermore, in vines treated with the mixtures, increases in yield quantity and quality, such as higher contents of soluble solids and lower levels of total acidity, have been shown. Due to the strong efficacy demonstrated on the leaves, silicon-based products + sulphur mixtures can also be recommended in eradicative applications, aimed at reducing the inoculum of the disease. The great activity of the mixtures demonstrated in this study suggests confirmation through further investigations on different cultivars and vine-growing areas at different levels of infection, also testing the effectiveness of individual silicon products against the disease.

Cocoa beans of the CCN-51 clone harvested in the Tumaco region (Nariño, Colombia) were fermented following four different treatments: (1) spontaneously (at room temperature for 120 h) in traditional conditions (Control); (2) traditional processing with a pre-drying (sun-dried for 24 h) treatment (PD); (3) with fermentation (for 120 h) after inoculation of a yeast starter culture (YS); and (4) including both treatments, pre-drying and yeast inoculation (PD+YS). Chemical composition, fatty acids, total polyphenol, methylxanthines (theobromine and caffeine) and lactic acid content of cocoa beans were determined. Chemical and fatty acid composition and theobromine content were not affected by the different fermentation treatment applied. When analysing total polyphenol content, YS and PD+YS treatments significantly increased the content of these compounds at the end of the fermentation process, while PD treatment decreased the caffeine content of cocoa beans. Finally, lactic acid content decreased as a consequence of both inoculation of yeast starter and mainly the pre-drying treatment. In conclusion, solar pre-drying in the open air and the inoculation of a yeast starter treatments could improve the final quality of coca beans.

Weeds are unwanted and invasive plants that proliferate and compete for resources such as space, water, nutrients, and sunlight, affecting the quality and productivity of the desired crops. Weed detection is crucial for the application of precision agriculture methods and for this purpose machine learning techniques can be used, specifically convolutional neural networks (CNN). This study focuses on the search for CNN architectures and technology used to detect and identify weeds in different crops; 61 articles applying CNN architectures and technology were analyzed in the last five years (2019-2023). The results show the used of different devices to acquire the image for training, such as digital cameras, smartphones, and drone cameras. Additionally, the YOLO family and algorithms are the most widely adopted architectures, followed by VGG, ResNet, Faster R-CNN, AlexNet, and MobileNet, respectively. This study provides an update on CNNs that will serve as a starting point for researchers wishing to implement these weed detection and identification techniques.

Rhizophora mangle L. is a well-known medicinal plant found in mangroves worldwide used to treatment diabetes. This study evaluated the chemical composition of the acetonic extract from Rhizophora mangle barks (AERM), by HPLC-PDA and FIA-ESI-IT-MS/MS and the effects on high-fat diet induced obesity in mice and its mechanism of action by gene expression of inflammatory markers (Pparg, Ppara, Srebf1, Cd36, Tnf, Ccl2, Lep, Il10, Il6, Fasn, 18s). High-fat diet fed mice during 12 weeks was used as model of obesity and associated alterations. The results were very satisfactory, the extract, rich in polyphenolic compounds, flavonoids and phenolic acids, displayed intense antioxidant activity in vitro (608 µmol Trolox/g), and showed excellent activity against non-alcoholic fatty liver disease (NAFLD) and reverse insulin resistance in a model of diet-induced obesity. We can registered a modulatory effect of AERM in liver PPAR-γ mRNA expression associated to an important inhibition of CD36 mRNA expression suggesting that AERM induces the down regulation of CD36 mRNA via PPAR-gamma inhibition. These results support the traditional knowledge about the use of R. mangle for the treatment of type 2 diabetes and reveal the potential of AERM for the treatment of NAFLD and management of obesity and comorbidities.

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.

Sleep-disordered breathing is a significant problem affecting the pediatric population. These conditions can affect sleep quality and significantly affect children's overall health and well-being. Difficulties in social interaction, communication, and repetitive behavioral patterns characterize autism spectrum disorder. Sleep disturbances are common in children with ASD. This literature review aims to gather and analyze available studies on the relationship between SDB and children with autism spectrum disorder. We comprehensively searched the literature using major search engines (PubMed, Scopus, and Web of Science). After removing duplicates, we extracted a total of 96 records. We selected 19 studies for inclusion after a thorough title and abstract screening process. A total of 7 articles were ultimately included. This review has analyzed the relationship between autism spectrum disorder and sleep-disordered breathing, particularly Obstructive Sleep Apnea, highlighting an intriguing web of complex associations. Some studies involving children have demonstrated a significant association between autism spectrum disorder and the presence of Obstructive Sleep Apnea. Furthermore, a heightened risk of developing sleep disturbances, including sleep-disordered breathing, has emerged in children with autism. The risk and prevalence of obesity are increasing in pediatric subjects with autism spectrum disorder. Obesity has been identified as a predictive factor for Sleep-disordered breathing, and Body Mass Index can directly correlate with Obstructive Sleep Apnea in these children. Adenotonsillectomy has proven to be pivotal in improving behavioral issues in autism spectrum disorder children with obstructive Sleep Apnea. In conclusion, this review underscores the complexity of the interplay between autism spectrum disorder and sleep-disordered breathing, emphasizing the importance of further research to understand underlying mechanisms and develop optimal therapeutic and preventative approaches to enhance sleep quality and overall health in children with autism spectrum disorder.

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.

Cyber-physical Systems involve the creation, continuous updating and monitoring of virtual replicas that closely mirror their physical counterparts. These virtual representations are fed by real-time data from sensors, Internet of Things (IoT) devices and other sources, enabling a dynamic and accurate reflection of the state of the physical system. This emphasizes the importance of data synchronization, visualization and interaction within virtual environments as a means to improve decision-making, training, maintenance and overall operational efficiency. This paper presents a novel approach to a cyber-physical system to harness the power of Industry 4.0, Digital Twin technology, Virtual Reality (VR) and 3D SCADA in the context of monitoring and optimizing an olive mill. In conclusion, this paper presents a methodology that leverages digital twins and virtual reality to create an immersive, data-driven simulation and monitoring system for an olive mill. The proposed CPS takes data from the physical environment through the existing sensors and measurement elements in the olive mill, concentrates them and exposes them to the virtual environment through the Open Platform Communication United Architecture (OPC-UA) protocol, thus establishing a bidirectional and real-time communication. Furthermore, in the proposed virtual environment, the digital twin is interfaced with the 3D SCADA system, allowing it to create virtual models of the process. This innovative approach has the potential to revolutionize the olive oil industry by improving operational efficiency, product quality and sustainability, while optimizing maintenance practices.

Abdominal aortic aneurysm (AAA) represents an important public health problem with a prevalence between 1.3% and 12.5%. Several population-based randomized trials have evaluated ultrasound screening for AAA providing evidence of a reduction in aneurysm-related mortality in the screened population. The aim of our study was to perform a systematic review and meta-analysis of the risk factors for AAA. We conducted a systematic review of observational studies and we performed a meta-analysis that evaluated the following risk factors: gender, smoking habits, hypertension, diabetes mellitus, Coronary Artery Disease and family history of AAA. Abdominal aortic aneurysm prevalence is higher in smokers and in males. It is important to underline that all countries, where AAA screening was set up, had high income level and the majority belong to Western Europe (United Kingdom, Sweden, Italy, Poland, Spain and Belgium). Abdominal aortic aneurysm screening is fundamental for public health. It would avoid deaths, ruptures, and emergency surgical interventions if abdominal aortic aneurysm was diagnosed early in the population target for screening.

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.

Human endogenous retroviruses (HERV) are remnants of ancient retroviral infections that, over millions of years, became integrated into the human genome. While normally inactive, environmental stimuli such as infections have contributed to the transcriptional reactivation of HERV promoting pathological conditions including the development of autoimmunity, neurodegenerative disease and cancer. What infections then trigger HERV activation? Mycobacterium avium subspecies paratuberculosis (MAP) is a pluripotent driver of human disease. Aside from granulomatous diseases Crohn’s, sarcoidosis and Blau syndrome, MAP is associated with autoimmune disease: type one diabetes (T1D), multiple sclerosis (MS), rheumatoid arthritis and autoimmune thyroiditis. MAP is also associated with Parkinson’s disease. Autoimmune diabetes, multiple sclerosis and rheumatoid arthritis are the diseases with the strongest MAP/HERV association. There are several other diseases associated with HERV activation including diseases whose epidemiology and/or pathology would prompt speculation for a causal role of MAP. These include non-solar uveal melanoma, colon cancer, glioblastoma and amyotrophic lateral sclerosis (ALS). This article further points to MAP infection as a contributor to autoimmunity, neurodegenerative disease and cancer via unsilencing of HERV. We examine the link between the ever-increasing number of MAP- associated diseases, the MAP/HERV intersection with these diverse medical conditions and propose treatment opportunities based upon this association.

We select four important waves of new entrants that knocked on the door of European electricity markets to illustrate how market rules need to be continuously adapted to allow new entrants to come in and push innovation forward. The new entrants that we selected are utilities venturing into neighbouring markets after establishing a strong position in their home market, utility-scale renewables project developers, asset-light software companies aggregating the assets of smaller consumers and producers, and different types of communities. We show that well-intentioned rules designed for certain types of market participants can (unintentionally) become obstacles for new entrants. We conclude that the evolution of market rules illustrates the importance of dynamic regulation. At the start of the liberalisation process the view was that we would deregulate or re-regulate the sector after which the role of regulators could be reduced. But their role has only increased. New players might also present new risks that require intervention by regulators.

Although most biological processes are characterized by a strong temporal asymmetry, several popular mathematical models neglect this issue. Maximum entropy methods provide a principled way of addressing time irreversibility, which leverages powerful results and ideas from the3literature of non-equilibrium statistical mechanics. This article provides a comprehensive overview of these issues, with a focus in the case of spike train statistics. We provide a detailed account of the5mathematical foundations and work out examples to illustrate the key concepts and results from non-equilibrium statistical mechanics

We hypothesized that biofilm production occurs on stainless steel when incubated with tissue specimens in thioglycolate broth media (TBM). In a diabetic foot infection (DFI) cohort, applying the Kirschner wire and conventional methods were more sensitive than applying only the latter (CI 90%; 0.167 versus 0.375).

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.

Introduction: maxillary hypoplasia and mandibular asymmetry may be corrected with orthognathic surgery at the completion of growth. Many patients require segmental Le Fort I osteotomies to obtain the most stable results. Unfortunately, if Invisalign is chosen for pre-surgical preparation, ClinCheck © software does not allow for prediction when these complex surgeries are planned. The objective of this paper was to show the potential of aligners beyond its software in most complex cases like multiple-piece maxillary osteotomies in cleft and non-cleft patients. Method: Thirteen patients who underwent pre-surgical treatment with clear aligners-Invisalign (study group) were matched in terms of diagnosis, surgical procedure, and orthodontic complexity with thirteen patients treated using fixed appliances (control group). A technique based on simple superimposition was devised to enhance the software for creating a suitable occlusion for segmental pre-surgical treatments. Virtual curves following the lower arch were employed to guide the correct pre-surgical positions of the upper teeth. The amount of impressions required in both groups to achieve satisfactory pre-surgical alignment of the segmented arches was compared. Results: one or no refinement phase were needed in the Invisalign group to reach an acceptable pre-surgical occlusion while the amount of pre-surgical impressions taken in order to reach adequate coordination with fixed appliance treatment was slightly higher. The average overall treatment duration did not show a statistically significant variation between the groups. Conclusions: it appears that clear aligner could serve as an effective treatment for individuals with skeletal discrepancies, including cleft and craniofacial anomalies, necessitating segmental Le Fort I osteotomies when aided by the suggested superimposition approach during digital pre-surgical movement simulations. More sophisticated softwares will certainly be implemented in the future.

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.

The aim was to analyze the coping strategies used by primary health care (PHC) professionals. A cross-sectional, descriptive-analytical study was conducted with professionals working in primary health care units in São José do Rio Preto, a large city in the interior of São Paulo, Brazil. For data collection we used an instrument developed by the researchers, containing sociodemographic and professional variables, as well as the Problem Coping Modes Scale (EMEP). We evaluated 333 PHC professionals. A difference was observed between the scores of the four coping strategies (p<0.001), with the highest score for the problem-focused strategy (3.8) and the lowest score for the emotion-focused strategy (2.4). Physicians had the lowest scores in coping strategies focused on religious practices/fantastical thinking (p<0.001) and pursuit of social support (p=0.045), while community health agents had the highest scores in these coping strategies). Professionals working in PHC have different coping strategies for the problems and stressful situations experienced in the work environment. These strategies can involve more positive attitudes focused on confrontation and problem solving, to emotional responses that involve attitudes of avoidance and denial that involve attitudes of avoidance and denial of the problem.

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.

Generating early warning signals of reduced resilience in ecosystems is crucial for conservation and management endeavors. However, the practical implications of such early warning signal systems are still limited by the lack of data and uncertainties associated with predicting complex systems such as ecosystems. This research aims to investigate the feasibility of developing an early warning system capable of identifying an upcoming critical transition within mangrove forest ecosystems. Using time series analysis of remote sensing images, the resilience of mangrove forests was explored across two distinct study sites. One site (Qeshm Island) has been adversely affected by land-use and land-cover changes, while the other (Gabrik) serves as a reference ecosystem. The study uses data from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite to quantify three remotely sensed indices: the Normalized Difference Vegetation Index (NDVI), the Modified Normalized Difference Water Index (MNDWI), and the Modified Vegetation Water Ratio (MVWR). In addition, Landsat data has been used to explore temporal alterations in land-use and land cover. To identify early warning signals, indicators such as autocorrelation (acf(1)), standard deviation (SD), and skewness (SK) are applied. The findings indicate a signal of reduced resilience by a significant increase in NDVI statistical metrics (acf(1): 0.50, SD: 0.9). Although MNDWI showed significant early warning signals in Qeshm Island (acf(1); 0.86, SD: 0.90), it provided a false alarm in the reference study site. MVWR failed to generate early warning signals of reduced resilience (acf(1); -0.100, SD: -0.07, SK: -0.21). Land-use land-cover change may explain reduced resilience in the forests. This study not only emphasizes the potential of remote sensing in monitoring the state of mangrove forests but also contributes to advancing our understanding of ecosystem dynamics. The findings of this study can be integrated with ecosystem management tools to enhance the effectiveness of conservation efforts aimed at safeguarding mangroves. This is the first report of the successful application of remote sensing in generating early warning signals of reduced resilience within mangrove forests in the Middle East.

Divergences have become a very useful tool for measuring similarity (or dissimilarity) between probability distributions. Depending on the field of application a more appropriate measure may be necessary. In this paper we introduce a family of divergences we call gamma-divergences. They are based on the convexity property of the functions that generate them. We demonstrate that these divergences verify all the usually required properties, and we extend them to weighted probability distribution. We investigate their properties in the context of kernel theory. Finally, we apply our findings to the analysis of simulated and real time series.

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.

For the agricultural sector to develop sustainably in the future, progress toward more environmentally friendly technologies and methods is crucial. It is necessary to increase output while reducing the demand for energy, agrochemicals, and water resources. Although greenhouses can be utilized successfully for this purpose, significant technical advancements are required, especially when it comes to heating, to lower the use of fossil fuels and boost energy efficiency. Infrared waves and microwaves, for instance, can warm plants without having to heat the entire greenhouse volume, which takes a significant amount of energy to compensate for heat loss to the outdoor environment. In this paper, through a thorough examination of the state of the art, a general overview of novel greenhouse heating systems based on radiation is reported. First, infrared heating of greenhouses is analyzed, then the strengths and weaknesses of microwave and dielectric heating are discussed, and finally the use of microwaves for soil sterilization is examined. All outcomes suggest these irradiation-based technologies can contribute significantly to an agriculture that is energetically sustainable.

Many manufacturing sectors require high surface finishing. After machining operations such as milling or drilling, undesirable burrs or insufficient edge finishing may be generated. For decades, many finishing processes have been handmade-basis; this fact is accentuated when dealing with complex geometries especially for high value-added parts. In recent years, it’s a tendency of trying to automate as far as possible this kind of processes, repeatability and time/money savings are main purposes. Based on that idea, the aim of this work is to check new tools and strategies for finishing aeronautical parts, especially critical engine parts made on Inconel 718, a very ductile nickel alloy. Automating edge finishing of chamfered holes is a complicated but really important goal. In this paper, flexible abrasive tools were used for this purpose. A complete study of different abrasive possibilities was carried out, mainly focusing on roughness analysis and final edge results obtained.

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.

We consider open non-twist Hamiltonian systems represented by an area-preserving two-dimensional map describing incompressible planar flows in the reference frame of a propagating wave, and possessing exits through which map orbits can escape. The corresponding escape basins have a fractal nature that can be revealed by the so-called basin entropy, a novel concept developed to quantify final-state uncertainty in dynamical systems. Since the map considered violates locally the twist condition, there is a shearless barrier that prevents global chaotic transport. In this paper we show that it is possible to determine the shearless barrier breakup by considering the variation of the escape basin entropy with a tunable parameter.

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.

Studies involving vortex in hybrid superconducting devices and their interaction with different components inside the sample are an important issue to reach higher values of their critical parameters in superconducting materials. The vortex distribution on each side of sample with different fundamental parameters, such as temperature T, penetration depth λ, coherence length ξ, electron mass m and the order parameter Ψ, may help to improve the superconducting properties. Thus, in this work, we used the modified Ginzburg-Landau theory to investigate hybrid superconductor (HS), but also to provide a highly tunable and adjustable theoretical tool to theoretically explain the experimental results involving HS, in order to study the vortex behaviour in superconductors of mesoscopic dimensions with extremely differences among their fundamentals parameters. Therefore, we evaluated the influence of HS on vortex configuration and their effects in the field-dependent magnetization. The results show that the during the increment of applied magnetic field H the diamagnetic response of HS, Meissner effect, include additional jumps of magnetization while diamagnetism continues its increase in the sample. In addition, the differences among parameters, create an interface between both components, two different magnitudes of supercurrent and vortex sizes producing a lower degradation of local superconductivity, which increase the upper critical field. On the other hand, this type HS with differences of parameters on both sides can be used to control the vortex movement in the selected superconducting region sample with more accuracy.

As an option to deal with the insulin-dependent disease, a recent commuted PD control strategy is designed and carefully analyzed for different clinic diabetic patients. This controller approach is mainly conceived to stabilize the glucose blood concentration in a diabetic patient around its basal value, hence avoiding extreme situations such as hypoglycemia and hyperglycemia. This control strategy receives two inputs carefully tuned to actuate when the measured variable is out of a prescribed healthy zone. Therefore, one of these variables is invoked to decrease the glucose concentration to insulin injection, and the other is employed to increase the glucose absorption, both by using a proper PD controller. According to our numerical experiments, our controller approach performs well, even when there is an external disturbance in the controlled system.

The importance of measuring sustainability in tourism has been significantly advancing in recent years, following the need to manage the impact of tourism on territories and hosting communities. It was further boosted by the pandemic, where sustainability has been defined as one of the central elements to restart global tourism. The ETIS model, developed by the European Commission, is a point of reference based on self-assessment, data collection and analysis by the destinations themselves. The application of ETIS toolkit has faced many challenges, especially at sub-national level, mostly related to the lack of available and updated data to feed the model. The hypothesis explored by the authors is to solve the implementation issues, developing an indicator based on the use of the Sentiment Analysis to frame e-reputation and tourism satisfaction, and further combining it with other open data sources. The Tourism Sustainability Index (TSI) can provide a scalable and geo-referenced evaluation of tourism sustainability, measuring the four pillars and sub-components referenced to ETIS criteria, applicable to any tourism destination. Results show that the TSI can be seen as a consistent and valid tool for destinations to analyze sustainability, monitor its evolution through time periods and sub-areas, and compare it to other benchmark or competitive areas.