Indoor residual spray (IRS), mainly employing pyrethroid insecticides, is the most common intervention to prevent malaria transmission in many regions of Latin America; the use of long-lasting insecticidal nets (LLINs) has been more limited. Knockdown resistance (kdr) is a well-characterized target-site resistance mechanism associated with pyrethroid and DDT resistance. Most mutations detected in acetylcholinesterase-1 (Ace-1) and voltage-gated sodium channel (VGSC) genes are non-synonymous, resulting in a change of amino acid leading to non-binding of the insecticide. In the present study, we analyzed target-site resistance in Nyssorhynchus darlingi, the primary malaria vector in the Amazon, in multiple malaria endemic localities. We screened 988 wild-caught specimens of Ny. darlingi from three localities in Amazonian Peru and four in Amazonian Brazil. Collections were conducted between 2014-2021. Criteria were Amazonian localities with a recent history as malaria hotspots, primary transmission by Ny. darlingi and the use of both IRS and LLINs as interventions. Fragments of Ace-1 (456 bp) and VGSC (228 bp) were amplified, sequenced and aligned with Ny. darlingi sequences available in GenBank. We detected only synonymous mutations in the frequently reported Ace-1 codon 280 known to confer resistance to organophosphates and carbamates, but detected three non-synonymous mutations in other regions of the gene. Similarly, no mutations linked to insecticide resistance were detected in the frequently reported codon (995) at the S6 segment of domain II of VGSC. The lack of genotypic detection of IR mutations by sequencing the Ace-1 and VGSC genes from multiple Ny. darlingi populations in Brazil and Peru could be associated with low-intensity resistance, or possibly the main resistance mechanism is metabolic.

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.

The content of this paper is a very significant contribution to the heritage regional reconstruction and conservation interventions. The results about the iconographic analysis of the Early-Renaissance frescoes of St. Leocadia Church, in Chaves, in the north-east of Portugal, were presented for the first time. This paper aims to study facial similarity analysis applied to identification of the personages represented in the 1511-1513 mural paintings of the apse of St. Leocadia Church, in Chaves Municipality (North of Portugal) and those ones in the oil paintings by the Proto-Renaissance Portuguese painter Nuno Gonçalves. In this work, it was explored the feasibility of face recognition technologies in answering many ambiguities concerning Manueline stylistic identity and iconography. A proposal was made to identify the characters, fundamental to the meaning of the frescoes. It has been experimentally proved on 7 characters of St. Leocadia Church’s paintings, in comparison with the referred old master portraits. It was used an in-house trained deep face recognition model to extract facial features from images of 15th and 16th century portraits to compare their degree of similarity. It was undertaken facial similarity analysis of the faces in the formidable portrait gallery of the 15th century Portuguese society represented in the Panels of St. Vicent, which has been subject of national and international research for 130 years. On the other, in the oil painting of St. Peter and St. Paul and Infanta St. Joana, of the same old master. The iconographic interpretation of the mural paintings of St. Leocadia, based in the deep facial features of the images, is plausible: a catechetical purpose; the ritual practices of royal ancestor worship in royal portrait apses of the churches; the Portuguese maritime expansion and the macro-imperial ideology of D. Manuel I.

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).

Arthropod-borne viruses belonging to the flavivirus genus possess an enormous relevance in public health. Neotropical non-human primates (NPs) have been proposed to be infected more frequently with flaviviruses due to their arboreal and diurnal habits, their genetic similarity to humans and their relative closeness to humans. However, the only known flavivirus in America that is maintained by sylvatic cycles involving NPs is Yellow Fever virus (YFV), and the NPs role as potential hosts of flaviviruses is still unknown. Here, we examined flavivirus exposure in 86 free range and captive NPs of Costa Rica to evaluate their involvement in flavivirus transmission cycles and their potential as flavivirus hosts. We used a highly-specific micro plaque reduction neutralization test (micro-PRNT) to determine the presence of antibodies against YFV, Dengue virus 1-4 (DENV), Zika virus, West Nile Virus (WNV) and Saint Louis Encephalitis virus (SLEV). We found evidence of seropositive NPs to DENV-1 8.2% (homotypic –3/86, heterotypic – 4/86), SLEV 15.1% (homotypic – 10/86, heterotypic – 2/86), WNV 2.3% (homotypic – 2/86) and 8.1% (7/86) undetermined Flavivirus species. No antibodies against YFV or ZIKV were found. This work provides compelling serological evidence of exposure in NPs of flaviviruses associated with urban cycles, i.e. DENV, and confirms decades of circulation of SLEV in the same environments. Also, the range of years of sampling and the socioeconomic region was statistically significant for the presence of Dengue and Flavivirus undetermined seropositive individuals, respectively. Both the years and socioeconomic regions with greater seroprevalence coincide with the years and socioeconomic regions with high numbers of Dengue human cases for the country. Our work suggests bidirectional? circulation of different flaviviruses between humans and wildlife with public health importance and underscores the necessity of further surveillance for flaviviruses in the humans/wildlife interface in Central America.

Nudibranchs are marine gastropod mollusks that have been extensively studied for their poten-tial to yield new bioactive compounds. This review aims to share data about the chemical and biological activity of extracts and isolated compounds from nudibranchs. The systematic review followed the PRISMA (a systematic review protocol) and covers the studies from the literature published from January 1950 to September 2023, and various scientific databases, including Elsevier, web of science, ACS publications, Taylor and Francis, Wiley Online Library, MDPI, Springer and the Marine Pharmacology website. The results presented are based on the complete set of studies that met our inclusion criteria. Among the selected studies, chemical characteriza-tion was the focus in 79.6% of cases, while biological activity assessment accounted for 20.4%. Ten different types of biological activity assays were performed, with the most frequently studied activities being cytotoxicity (43.6%), antimycobacterial (43.6%), and ichthyotoxic (9.8%) effects. Most positive results obtained from these assays were related to antimycobacterial, cytotoxicity, and ichthyotoxic activities. Eight different types of metabolites were identified, with terpenes be-ing the most prevalent (78.5% of articles), followed by alkaloids (8.1%) and aromatic polyketides (4.7%). Gathering the existing evidence can aid in identifying research gaps and planning future investigations. Our findings indicate that certain nudibranch families, such as Cadlinidae, have received limited attention in terms of studies conducted, yet show promising results in terms of biological activities.

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.

In this study, we successfully obtained a 2Mg-Fe mixture through mechanical alloying (MA) and processed it via accumulative roll bonding (ARB) (MA+ARB). Our primary focus was to analyze the impact of ambient air exposure while also evaluating the processing route. Some powder samples were exposed to air for 12 months before undergoing ARB processing. The Mg samples obtained after ARB processing exhibited a (002)-type texture. Our results demonstrate that all samples, including those processed via ARB, could rapidly absorb hydrogen within a matter of minutes, despite considerable differences in surface area between powders and rolled samples. ARB-processed samples reached approximately 60% of their maximum acquired capacity within just 24 minutes, compared to powders stored for a year which took 36 minutes. Also, the desorption temperatures were lower than those of MgH2. The absorption and desorption kinetics remained fast even after prolonged exposure to air. Although there were minor variations in capacities, our overall findings are promising since scalable techniques such as ARB have the potential to produce hydrogen storage materials that are both safe and cost-effective in a highly competitive market.

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.

High-throughput screening technologies continues to produce large amounts of multiomics data from different populations and cell types for various diseases, such as cancer. However, analysis of such data encounters difficulties due to cancer heterogeneity, further exacerbated by human biological complexity and genomic variability. There is a need to redefine the drug discovery development pipeline, bringing an Artificial Intelligence (AI)-powered informational view that integrates relevant biological information and explores new ways to develop effective anticancer approaches. Here, we show SynPred, an interdisciplinary approach that leverages specifically designed ensembles of AI-algorithms, links omics and biophysical traits to predict synergistic anticancer drug synergy. SynPred exhibits state-of-the-art performance metrics: accuracy – 0.85, precision – 0.77, recall – 0.75, AUROC – 0.82, and F1-score - 0.76 in an independent test set. Moreover, data interpretability was achieved by deploying the most current and robust feature importance approaches. A simple web-based application available online at http://www.moreiralab.com/resources/synpred/ was constructed to predict synergistic anticancer drug combinations requiring only the upload of the two drug SMILES to be tested, allowing easy access by non-expert researchers.

This paper proposes an upper bound for mine productivity and also a simple truck dispatch rule that demonstrates how tight the upper bound can be using simulation. It also proposes a greedy search to approximate the productivity upper bound, which is faster and often exact. Uncertainty is added to the simulation in order to verify how the productivity responds to it. Typically, the productivity upper bound is less tight close to its saturation point as a function of the number of trucks, where adding more trucks only increases queues. Furthermore, more uncertainty in the model typically leads to a less tight upper bound. The results are conducted using real data from an open pit mine in Brazil.

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.

In a software-defined radar (SDR) system, most of the signal processing usually implemented in hardware is implemented by software, thus allowing for higher flexibility and modularity compared to conventional radar systems. However, the majority of SDR demonstrators and proofs-of-concept reported in the open literature so far have been based on simple antenna systems. As a result, the full potentialities of an SDR approach have not been completely exploited yet. In this work, we propose a flexilbe antenna module to be integrated into an active electronically scanning array (AESA) with controlled sidelobe level over a wide angular range, exhibiting polarization reconfigurability with low cross-polarization level and high isolation. For this purpose, analytical and numerically efficient techniques for the synthesis of the aperture distribution and the correct evaluation of the radiating features (e.g., beamwidth, pointing angle, sidelobe levels, etc.) are presented in order to grant a real-time control of the digital beamforming network. A sub-array module demonstrator is fabricated and measured to corroborate the concept.

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.

The primary sources of particulate matter are linked to human activity. Certain particulate emissions, particularly those of a finer nature, can significantly impact human health, making them one of the most concerning pollutants. Ultrafine particles (UFP), which have a diameter of less than 100 nm, are of particular concern due to their impact on human health and the difficulty in controlling them. The concentration of ultrafine particles (UFP) in the workplace is a growing concern and is classified as an emerging risk. Workers may be exposed to UFP through inhalation, skin absorption, ingestion, or a combination of these routes. This study aims to determine the levels of UFP exposure among workers in environments with varying direct particle emission patterns. Measurements were conducted to compare the results with the levels recommended by the WHO. The study monitored industrial workplaces with direct particulate matter emissions, such as a carpentry and a bakery, as well as social sector sites without or almost without direct particle emissions, such as a school and a health clinic. One conclusion drawn from this study is that all tasks and occupations are susceptible to high levels of UFP, exceeding WHO recommended values in virtually all monitored environments. Therefore, monitoring and controlling UFP is crucial. Further in-depth studies on this subject are also necessary..

In 2011, it was reviewed that there is a strong co-occurrence between major depression and chronic fatigue syndrome (CFS), with fatigue and physio-somatic symptoms being key symptoms of depression, and depressive symptoms appearing during the course of CFS. Moreover, the comorbidity between both conditions may in part be explained by activated immune-inflammatory pathways, including increased translocation of Gram-negative bacteria and increased levels of pro-inflammatory cytokines, such as interleukin (IL)-1. Nevertheless, the possible involvement of activated microglia in this comorbidity has remained unclear. This paper aims to review microglial disturbances in major depression, CFS and their comorbidity. A comprehensive literature search was conducted using the PubMed / MEDLINE database to identify studies that are relevant to this current review. Depressed patients present neuroinflammatory alterations, probably related to microglial activation, while animal models show that a microglial response to immune challenges including lipopolysaccharides is accompanied by depressive-like behaviors. Recent evidence from preclinical studies indicate that activated microglia have a key role in the onset of fatigue. In chronic inflammatory conditions, such as infections and senescence, microglia orchestrate an inflammatory microenvironment thereby causing fatigue. In conclusion, based on our review we may posit that shared immune-inflammatory pathways and activated microglia underpin comorbid depression and CFS and that activated microglia are the main orchestrators of this comorbidity. As such, microglial activation and neuro-inflammation may be promising targets to treat the overlapping manifestations of both depression and CFS.

The main objective of this study was to study the effect of occupational stress on turnover intentions, as well as whether this relationship is mediated by burnout levels and moderated by motivation. The sample of this study consisted of 603 participants, all employees of the Portuguese Tax and Customs Authority, which is part of the Ministry of Finance and belongs to the Direct State Administration. The results indicate that occupational stress (with managers, with career and remuneration and with work overload) has a positive and significant effect on turnover intentions and that this relationship is mediated by burnout. Motivation (intrinsic and identified) has a negative and significant effect on turnover intentions. Intrinsic motivation moderates the rela-tionship between occupational stress (with managers, with colleagues, with career and pay and with family problems) and turnover intentions. These results indicate that among the dimensions of occupational stress, the most critical are stress with managers, work overload and career and pay. These are factors that the Direct State Administration should be concerned about in trying to minimize their causes.

A study to produce cellulose nanofibrils (CNF) from Kraft cellulose pulp, an optimal enzyme mixture, was defined using a centroid simplex mixture design. The enzyme blend contains 69% endoglucanase and 31% exoglucanase. The central composite rotational design (CCRD) optimized the CNF production process by achieving a higher crystallinity index. It thus corresponded to a solid loading of 15 g/L and an enzyme loading of 0.974. Using the Segal formula, the crystallinity index (CrI) of CNF was determined by X-ray diffraction to be 80.87%. The average diameter of nanocellulose fibers measured by scanning electron microscopy between 550 - 600 nm for the CNF prepared by enzymatic hydrolysis and between 250 - 300 nm for the CNF produced by enzymatic hydrolysis with the optimal enzyme mixture followed by ultrasonic dispersion. Finally, synergistic interactions between the enzymes involved in nanocellulose production were demonstrated, with Colby factor values greater than one.

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.

The main objective of this review is to determine the main risks that agricultural workers are exposed to during pesticide application, which may have a harmful effect on their health and on public health. This systematic review was based on the PRISMA guidelines. A search for articles was conducted in the Medline/PubMed, ScienceDirect, and Web of Science databases. Fifteen articles were selected considering their assessment of agricultural workers' knowledge, perceptions, attitudes, practices, and behaviours, identifying the main risks and risk factors for disease associated with the unsafe handling of pesticides. The main risk factors identified were age, education, pesticide safety training, farming experience, and contact with other farmers/intermediaries resulting in pesticide access. The most frequent risk behaviours were: application of pesticides without personal protective equipment (PPE), incorrect disposal of empty packaging and waste, and undervaluation of label information, as well as other unsafe practices. A multidisciplinary and more effective training must be delivered in order to enhance pesticide safe usage. This will empower workers to adopt more conscious and safer behaviours while using pesticides.

Thermal camouflage is a highly sought-after technology to increase the survivability of military equipment against infrared (IR) detectors. Recently, two-dimensional (2D) nanomaterials have shown low IR emissivity, widely tunable opto-electronic properties and compatibility with stealth-applications. Among them, graphene and graphene-like materials are the most attractive 2D materials used for thermal camouflage applications. In particular, in multilayer graphene (MLG) charge density can be effectively tuned through sufficiently intense electric fields or through electrolytic gating. Therefore, MLG optical properties, like infrared emissivity and absorbance, can be controlled in a wide range by voltage bias. The large emissivity modulation achievable with this material makes it suitable in the design of thermal dynamic camouflage devices. Generally, the emissivity modulation in the multilayered graphene medium is governed by an intercalation process of non-volatile ionic liquids under a voltage bias. The electrically-driven reduction of emissivity leads to a decrease in the apparent temperature of the surface, which can match that of the background enabling thermal camouflaging. Since this property is common to other graphene-based materials, here we present a review specifically focused on the recent advances in the field of the thermal camouflage properties of graphene in the form of composite film and aerogel structures. A summary of the current understanding of the working principle of thermal camouflage materials, current limitations, and future opportunities is presented and discussed.

Augmented and Virtual Reality have been experiencing a rapidly growth in recent years, but there is not still a deep knowledge on their capabilities and where they could be explored. In that sense, this paper presents a study on the accuracy and repeatability of the Microsoft's HoloLens 2 (Augmented Reality device) and HTC Vive (Virtual Reality device) using an OptiTrack system as ground truth. For the HoloLens 2, the method used was hand tracking, while in HTC Vive, the object tracked was the system's hand controller. A series of tests in different scenarios and situations were performed to explore what could influence the measures. The HTC Vive obtained results in the millimetre scale, while the HoloLens 2 revealed not so accurate measures (around 2 centimetres). Although the difference can seem to be considerable, the fact that HoloLens 2 was tracking the user's hand and not an inherit controller made a huge impact. The results were considered a significant step for the on going project of developing a human-robot interface to program by demonstration an industrial robot using Extended Reality, which shows great potential to succeed based on this data.

Background: Chagas disease is still a neglected disease considered a public health problem. Early diagnosis of cases is important to improve the prognosis of infected patients and prevent transmission. Serological tests are the method of choice for diagnosis. However, two serological tests are currently recommended to confirm positive cases. In this sense, more sensitive and specific serological tests need to be developed to overcome the problems currently faced. This study aimed to develop a new recombinant multiepitope protein for the diagnosis of Chagas disease, hereafter named rTC. Methods: The rTC was constructed based on amino acid sequences from different combinations of Trypanossoma cruzi antigens in the same polypeptide and tested in ELISA for detecting different Chagas disease. Results: rTC1 was able to discriminate between indeterminate (IND) and cardiac (CARD) cases and cross-reactive diseases, and healthy samples, with 96.6% sensitivity and 97.96% specificity, respectively. Conclusion: These data suggest a preliminary study that rTC1 has the po-tential to be tested in future studies against a larger serological panel for the diagnosis of Chagas disease.

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.

Instead of simplified steady-state models, with modern computers, one can solve the complete aero-thermodynamics happening in gas turbine engines. In the present article, we describe a mathematical model and numerical procedure to represent the transient response of a PT6A gas turbine engine operating at off-design conditions. The aero-thermal model consists of a set of algebraic and ordinary differential equations that arise from the application of the mass, linear momentum, angular momentum, and energy balances in each engine's component. The solution code has been developed in Matlab-Simulink using a block-oriented approach. Transient simulations of the PT6A engine start-up have been carried out by changing the original Jet-A1 fuel with biodiesel blends. Time plots of the main thermodynamic variables are shown, especially those regarding the structural integrity of the burner. Numerical results have been validated against reported experimental measurements and GasTurb simulations. The computer model has been capable to predict acceptable fuel blends, such that the real PT6A engine can be substituted to avoid the risk of damaging it.

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%.

The main objective of this investigation was to study the effect of organizational competencies development practices on turnover intentions and whether affective commitment explains this relationship. Another of the study's objectives was to test whether these relationships vary ac-cording to the generation to which the participant belongs. The study sample consisted of 2123 participants working in Portuguese organizations. The results indicate that organizational com-petencies development practices (training, individualized support, and functional rotation) nega-tively and significantly affect turnover intentions and that affective commitment mediates this re-lationship. However, these relationships vary according to the participant's generation. For Gen-eration Y and Generation X, this mediating effect is found in all dimensions of organizational competencies development practices. For the baby boomer generation, there is only a mediating effect of affective commitment in the relationship between individualized support and turnover intentions. These results indicate that human resources should consider the generation to which the participant belongs when implementing competencies development practices.

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.

This research investigates the exposure of plant species to extreme drought events in the Brazilian Atlantic Forest, employing an extensive dataset collected from 205 automatic weather stations across the region. Meteorological indicators derived from hourly data, encompassing precipitation, maximum and minimum air temperature, were utilized to quantify past, current, and future drought conditions. The dataset, comprising 10,299,236 data points, spans a substantial temporal window and exhibits a modest percentage of missing data. Missing data were excluded from analysis, aligning with the decision to refrain from imputation methods due to potential bias. Drought quantification involved the computation of the Aridity Index, the analysis of consecutive hours without precipitation, and the classification of wet and dry days per month. Mann-Kendall trend analysis was applied to assess trends in evapotranspiration and maximum air temperature, considering their significance. The hazard assessment, incorporating environmental factors influencing tree growth dynamics, facilitated the ranking of meteorological indicators to identify regions most exposed to drought events. The results revealed consistent occurrences of extreme rainfall events, indicated by positive outliers in monthly precipitation values. However, significant trends were observed, including an increase in daily maximum temperature and consecutive hours without precipitation, coupled with a decrease in daily precipitation across the Brazilian Atlantic Forest. No significant correlation between vulnerability ranks and weather station latitudes and elevation were found, suggesting geographical location and elevation does not strongly influence observed dryness trends.

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.

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.

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.

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.

Head and neck cancer is the sixth most frequent cancer type. Drug resistance and toxicity are common challenges of the existing therapies, making the development of reliable preclinical models essential for the study of the involved molecular mechanisms as well as for eventual intervention approaches that improve the clinical outcome. Preclinical models of head and neck squamous cell carcinoma have been traditionally based in cell lines and murine models. In this review, we will go over the most frequently used preclinical models, from immortalized-cell and primary tumour cultures in monolayer or 3D, to the currently available animal models. We will scrutinize their efficiency in mimicking the molecular and cellular complexity of head and neck squamous cell carcinoma. Finally, the challenges and opportunities of other envisaged putative approaches, as well as the potential of the preclinical models to further develop customized therapies will be discussed.

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.

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.

Face recognition is a valuable forensic tool for criminal investigators since it certainly helps in identifying individuals in scenarios of criminal activity like fugitives or child sexual abuse. It is, however, a very challenging task as it must be able to handle low-quality images of real world settings and fulfill real time requirements. Deep learning approaches for face detection have proven to be very successful but they require a large computation power and processing time. In this work, we evaluate the speed-accuracy tradeoff of three popular deep-learning-based face detectors on the WIDER Face and UFDD data sets in several CPUs and GPUs. We also develop a regression model capable to estimate the performance, both in terms of processing time and accuracy. We expect this to become a very useful tool for the end user in forensic laboratories in order to estimate the performance for different face detection options. Experimental results showed that the best speed-accuracy tradeoff is achieved with images resized to 50% of the original size in GPUs and images resized to 25% of the original size in CPUs. Moreover, performance can be estimated using multiple linear regression models with a Mean Absolute Error (MAE) of 0.113 what is very promising for the forensic field.

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.

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.

Lattice structures have emerged as promising materials for aerospace structures applications due to their high strength-to-weight ratios, customizable properties, and efficient use of materials. These properties make them at-tractive for use in anti-ice systems, where lightweight and heat exchanging are essential. This paper presents an extensive experimental investigation into mechanical compression properties of lattice trusses fabricated from AlSi10Mg powder alloy, a material commonly used in casted aerospace parts. The truss structures were manufactured using additive manufacturing Selective Laser Melting technique and subjected to uniaxial compressive loading to assess their performance. The results demonstrate that AlSi10Mg lattice trusses exhibit remarkable compressive strength with strong correlations depending upon both topology and cells’ parameters setup. The finding described highlights the potential of AlSi10Mg alloy as a promising material for custom truss fabrication, offering customizable cost-effective and lightweight solutions for aerospace market. The paper also emphasizes the role of additive manufacturing in producing complex structures with pointwise tailored mechanical properties.

Research has shown that emotional states may influence the subjective experience of time. The present study involved 111 healthy adult participants and examined the impact of emotional stimuli on time perception, using a time estimation task with four conditions: in one of the conditions, participants estimated the exposure time of a black screen, wherein the duration could vary be-tween 2 to 7 s (condition without emotional interference); in the other conditions, participants es-timated the exposure time (also ranging from 2 to 7 s) of images that would induce pleasant, un-pleasant, or neutral emotions, to which participants were instructed to focus their attention (pleasant, unpleasant, or neutral emotions). The results showed that participants estimated “shorter” time intervals (underestimation) for pleasant and unpleasant images compared to the condition without interference, but no significant differences were found between the neutral condition and the condition without interference. It is suggested that increased attention to an ex-ternal stimuli, regardless of its emotional valence, produces an underestimated perception of time.

Alcohol effects on hepatic lipid metabolism through various mechanisms, leading synergistically to an accumulation of fatty acids (FA) and triglycerides. Obesity, as well as, the dietary fat [saturated fatty acids (FA) versus poly-unsaturated fatty acids (PUFA)] may modulate the hepatic fat. Alcohol inhibits adenosine monophosphate activated kinase (AMPK). AMPK activates peroxisome proliferators activated receptor a (PPARα) and leads to a decreased activation of sterol regulatory element binding protein 1c (SRABP1c). The inhibition of AMPK, and thus of PPARα results in an inhibition of FAs oxidation. This ß-oxidation is further reduced due to mitochondrial damage induced through cytochrome P4502E1 (CYP2E1) driven oxidative stress. Furthermore, the synthesis of FAs is stimulated through an activation of SHREP1. In addition, alcohol consumption leads to a reduced production of adiponectin in adipocytes due to oxidative stress and to an increased mobilization of FAs from adipose tissue and from the gut as chylomicrons. On the other side, the secretion of FAs via very low density lipoproteins (VLDL) from the liver is inhibited by alcohol. Alcohol also affects signal pathways such as early growth response 1 (Egr-1) associated with the expression of tumour necrosis factor  (TNF), and the mammalian target of rapamycin (mTOR) a key regulator of autophagy. Both have influence the pathogenesis of alcoholic fatty liver. Alcohol-induced gut dysbiosis is contributing to the severity of ALD by increasing metabolism of ethanol in the gut and promoting intestinal dysfunction. Moreover, pathogen associated molecular paterns (PAMPS) via specific Toll-like receptors (TLR) bacterial overgrowth is leading to the translocation of bacteria. Endotoxins, and toxic ethanol metabolites enter the enterohepatic circulation reaching the liver, inducing the activation of the nuclear factor kappa-B (NFB) pathway. Pro-inflammatory cytokines released in the process contribute to inflammation and fibrosis. In addition, cellular apoptosis is inhibited in the favor of necrosis.

In this paper we use the conformable fractional derivative to discuss some fractional linear differential equations with constant coefficients. By applying some similar arguments to the theory of ordinary differential equations, we establish a sufficient condition to guarantee the reliability of solving constant coefficient fractional differential equations by the conformable Laplace transform method. Finally, we analyze the analytical solution for a class of fractional models associated with Logistic model, Von Foerster model and Bertalanffy model is presented graphically for various fractional orders and solution of corresponding classical model is recovered as a particular case.

Myelodysplastic syndromes (MDS) are diseases that occur when blood-producing cells in the bone marrow are damaged; such damage can affect one or more types of blood cells. Common types of MDS are refractory anemia with ring sideroblasts and refractory anemia with excess blasts (MDS-RS and MDS-EB, respectively). This work analyzed the proteomics of the medullary plasma of 10 patients with MDS-RS and MDS-EB compared to healthy control people. Overexpressed proteins that may be potential candidates for biological markers for the evaluation, study, and diagnosis of these diseases have been identified. These samples were subjected to immunodepleting, concentrated, and digested for further analysis by mass spectrometry. The ratios between selected groups and healthy people were calculated. Seven overexpressed proteins in both syndromes were identified as potential biomarker candidates: vitronectin (VTN), (2) fibrinogen (FGA), (3) pregnancy zone protein (PZP), (4) kininogen (KNG1), (5) immunoglobulin lambda chain (IGLL1), (6) complement factor C4b, and (7) hemopexin (HPX). A modified affinity chromatographic column with lectin frutalin (FTL) was used for non-depleted samples. Immunoglobulin M (IgM) was expressed in the samples from both syndromes. Surprisingly, IgM from patients with syndromes was over retained on the frutalin (FTL) column when compared with the control group. We further hypothesized that over retention of this protein by the FTL is due to the presence of α-galactosidic residues in the IgM of MDS-RS and MDS-EB patients. Differential recognition of proteins on non-depleted samples from the use of FTL appears to be a powerful tool for proteomic analysis.

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.

Liposomes have been used for several decades for the encapsulation of drugs and bioactives in cosmetics and cosmeceuticals. On the other hand, the use of these phospholipid vesicles in food applications is more recent and has been increasing significantly in the last ten years. Although in different stages of technological maturity - in the case of cosmetics, many products are on the market - processes to obtain liposomes suitable for the encapsulation and delivery of bioactives are highly expensive, especially aiming at scaling-up. Among the bioactives proposed for cosmetics and food applications, vitamins are the most frequently used. Despite the differences between the administration routes (oral for food and mainly dermal for cosmetics), some challenges are very similar (e.g., stability, bioactive load, average size, increase of drug bioaccessibility and bioavailability). In the present work, a systematic review of the technological advancements in the nanoencapsulation of vitamins using liposomes and related processes was performed; challenges and future perspectives were also discussed in order to underline the advantages of these drug loaded biocompatible nanocarriers for cosmetics and food applications.

This work exclusively focuses on the assessment of the thermal performance of a multifunctional facade panel incorporating PCM in foam layers, recurring to a hot box heat flux meter method to determine the thermal transmittance (U-value). The experimental setup is based on the steady-state approach using climatic chambers, assuring a stable thermal environment. Even small fractions of PCM achieved a small reduction in thermal amplitude. Numerical simulations using Ansys Fluent were developed to evaluate the performance of PCM use over a wide range of temperature boundary conditions and operating modes. These numerical models were calibrated and validated using the results of experimental tests, achieving a correlation factor of 0.9674, thus accurately representing a real-world scenario. The decrement factor (f) was used to analyse the data. It was identified that the efficiency of the panel and size of the optimum region increased with the PCM fraction growth. The simulated behaviour was optimum when the input mean temperature is of 20 °C for a room temperature of between 18-20 °C. The results show the significant potential of the multi-layered panel and the thermal regulator effect of the PCM incorporated on indoor space temperature to reach good thermal comfort levels.

Syphilis continues to be a significant global health concern, and understanding the latest advancements in immunology and pharmacological treatment is crucial for effective disease management. This review article provides an in-depth exploration of these advancements, aiming to contribute to the growing body of knowledge on syphilis research. The epidemiology of syphilis sets the stage for this review, highlighting the persistent burden of the disease worldwide. Current trends and challenges in disease control are discussed, shedding light on the need for comprehensive prevention strategies and improved surveillance systems. The immunological aspects of syphilis are the focus of this review. The intricate interplay between the host immune response and the evasive strategies employed by Treponema pallidum, the causative agent of syphilis, are explored. These include the mechanisms of immune evasion, the role of adaptive and innate immunity, and the development of immune-mediated tissue damage. The article also highlights advancements in diagnostic methods, with emphasis on the importance of accurate and timely detection. From traditional serological tests to the emergence of novel molecular and point-of-care assays, these developments have significantly improved the efficiency and accuracy of syphilis diagnosis. In terms of pharmacological treatment, the review covers the current recommendations and emerging strategies for managing syphilis infections. The challenges posed by antimicrobial resistance are addressed, emphasizing the importance of appropriate treatment regimens and close monitoring of therapeutic efficacy. Looking to the future, this review highlights the potential of vaccine development as a preventive measure against syphilis. Promising vaccine candidates and ongoing research efforts are discussed, offering hope for an effective means of disease prevention. In conclusion, this comprehensive review explores the advancements in syphilis research, from the understanding of immunological complexities to the development of innovative treatment strategies. By collectively advancing our knowledge, we can strive towards better disease management and minimize the impact of syphilis on global public health.

The ironstone outcrops in the rupestrian grasslands, known as cangas, are rich in species of endemic plants. This high endemism and the constant threat because of the area loss and fragmentation make the conservation of the rupestrian grasslands necessary. The rupestrian grasslands that host one of Brazil's largest iron-ore mining areas are Iron Quadrangle. About 89 rare and endangered species of the Iron Quadrangle are exclusive to cangas, including a threatened species Arthrocereus glaziovii. According to the International Union Conservation of Nature (IUCN), this species is considered micro-endemic and endangered and a priority for recovering the Iron Quadrangle's ferruginous rupestrian fields. This work aims to evaluate the potential distribution of A. glaziovii based on abiotic variables and soil elements and characterize the distribution of mining titles that may restrict the areas of occurrence of this species. We used five types of ecological niche model (ENM) algorithms (Bioclim, Domain, MaxEnt, GLM and RandomForest) in two sets of environmental variables for the modeling: 20 climatic variables and 18 edaphic variables. Our results showed that the area of the potential occurrence of A. glaziovii is more extensive and covers areas outside the Iron Quadrangle. However, mining titles currently licensed and in exploration correspond the entire identified area, threatening the species' survival.

In the early 1990s, cyberfeminism emerged as an area of knowledge to discuss the connection between gender and technology. According to UNESCO, women are underrepresented in the field of science, technology, engineering, and mathematics and less than a third of women worldwide work in scientific research and development. However, this number has grown and this reality is constantly changing. In this context, using business intelligence techniques, this study analyzes data from the computer and information and communication technology market to characterize the impact of the performance of women in these areas. It is expected to show that this performance in the highlighted fields is still a challenge in Brazil.

This study aims to precisely characterize the use of magnetoelectric nanoparticles (MENPs) for stimulating peripheral nerves. Numerical methods were employed to quantify the interaction between MENPs and nervous tissue. The influence of MENPs orientation, concentration and distance was assessed in terms of the external potential distribution exerted by the MENPs, the amplification of the exerted MENPs stimulation required to excite the neural fibers and the current injected into the intracellular space. The results highlight the significance of MENPs concentration for stimulation accuracy and efficiency, the impact of MENPs orientation on the electric potential distribution sensed by the nervous tissue, as well as the importance of the MENPs distance over the fibers’ recruitment. Given the considerable variability in the interaction between MENPs and nerves, our research provides a crucial step towards understanding this interaction, offering quantitative support for the application of MENPs in nervous tissue stimulation.

According to previous studies the median raphe region (MRR) is known to contribute significantly to social behavior. Beside serotonin, there are reports of a small population of dopaminergic neu-rons in this region. Dopamine is linked to reward and locomotion, but very little has been known about its role in the MRR. To address that, we first confirmed the presence of dopaminergic cells in the MRR of mice (immunohistochemistry, RT-PCR) and humans (RT-PCR). Next, we used chemogenetic technology in mice containing Cre enzyme under the promoter of the dopamine transporter (DAT). With the help of an adeno-associated virus, artificial receptors were expressed in the dopaminergic cells of the MRR (DAT-MRR). Four weeks later, extensive behavioral charac-terization started 30 minutes after the injection of the artificial ligand (Clozapine-N-Oxide). Stimu-lation of DAT-MRR decreased social interest without influencing aggression and with an increase in social discrimination. Additionally, inhibition of the same cells increased the friendly social be-havior during social interaction test. No behavioral changes were detected in anxiety, memory and locomotion. All in all, dopaminergic cells were present both in the mice and human MRR, and manipulation of dopaminergic neurons of the MRR elicited a specific social response.

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.

The flexitarian diet, which emphasizes a reduction in meat consumption, has been identified as a crucial factor in transitioning to sustainable food systems that can help combat climate change and improve food and nutritional security, particularly in areas where food choices are abundant. Despite Brazil being a major meat producer, meat consumption among Brazilians has been decreasing in recent years, with a growing portion of the population adopting meat-free and meat-reduced dietary models. In this study, we conducted the first non-industry funded scientific investigation of Brazilian flexitarians, with the goal of characterizing their socio-economic and demographic characteristics, motivations for adopting flexitarianism, frequency of animal-based meat consumption, and main substitutes consumed. Data was collected from 1029 self-identified flexitarians in Brazil. Our findings indicate that the flexitarian food model is primarily adopted by women and is motivated by concerns about the environmental impact of meat consumption, personal health, and animal welfare. Flexitarians were found to have a consumption profile that can be divided into three groups: low (consuming meat 36 times a week), medium (consuming meat 7 times a week), and high (consuming meat 4 times a week). The flexitarian meals pattern is characterized by lower consumption of beef (less than 2 times per week) and higher consumption of chicken (3 times per week) and is supplemented by plant-based protein sources and eggs as the main meat substitutes.

The population growth and its needs, has increasingly demanded water resources, requiring managers to adopt mechanisms to guarantee the availability and quality of water from springs. Among the instruments defined by law n. 9433/1997, water charges stand out. In this sense, the objective was to evaluate the evolution of charging for the use of water resources in Brazil, with emphasis on the channel of the Hydrographic Basin of the Paranaíba River. The methodology used was based on two phases, one of reviewing the articles available in Capes journals and the other, consulting the spreadsheets of the Araguari River Basin Agency with information on charges for the use of water within the competence of the Union in the Hydrographic Basin of the Paranaiba River. The results showed that charging for the use of water resources establish a relevant instrument for disciplining and raising financial resources that will enable improvements in the planning and management of water use. It should be noted that irrigation emerges as the main user of the flow captured from the Paranaíba River. However, the main source of funds for charging comes from the public supply. Among the Federation Units, the Federal District proved to be the largest source of contributions for charging the use of the Union's water resources in the Paranaíba River Basin.

Minimally processed fruits undergo changes that need to be controlled. The objective was to evaluate minimally processed papayas, using edible coatings based on chitosan and gelatin through different techniques. The following treatments were applied: control (distilled water), 1% chitosan, 4% gelatin, 1% chitosan + 4% gelatin (blend) and 1% chitosan under 4% gelatin (layer by layer). The infrared spectroscopy (FTIR) of the coatings was analyzed, and fresh mass, firmness, pulp color (L*, a*, b* and Hue angle), pH, titratable acidity, soluble solids, ascorbic acid, phenolic compounds, lycopene, β-carotene, total sugars and catalase from fruits. Gelatin and the layer-by-layer treatment had a positive effect on the conservation of minimally processed papaya. These coatings were able to reduce the loss of fresh mass, maintaining the firmness and orange color of the mesocarp. The treatments showed low SS content during the storage period, few variations in acidity, influencing maturation. Gelatin had a low polyphenol content, the layer-by-layer treatment did not show changes in vitamin C levels. These treatments did not show changes in lycopene and β-carotene levels over the days, showing a small increase in total sugars. Thus, the use of gelatin polymers and undercoat treatment (LBL) is a viable alternative to preserve minimally processed papayas for at least 8 days.

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.

A study on flywheel geometries is presented here with the use of finite element modelling (FEM) simulations. The study analyses the stress behaviour of flywheel rotors subject to the rotational speed that creates the maximum stress that the flywheel can support, and then calculates the rotational energy mass ratio (energy density) for each geometry. The obtained geometry was Gaussian section for the Flywheel rotor. The used material for the simulations is carbon fibre Hexcel UHM 12000. The best results were a rotational speed of ≈279.000 rpm and rotational energy density of ≈ 440 Wh/kg for a single disk, but this keeps the total energy low. To increase the total energy, Flywheels with 2 and 3 rotors were analysed. Then the stability under rotation of these Flywheels were analysed, some instability was found and a solution was presented.

This study adapted and assessed a shortened version of the IAT (Internet Addiction Test) scale completed by young people aged 12 years and older regarding their online behaviors and risk of online addiction. The psychometric qualities of the reduced version - Screening IAT - youth are presented in order to validate its use in the early detection of online addiction. The total sample is composed of 3021 participants being 55.9% female and 44.1% male, with a mean age of x ̅=15 years (σ=3.028), attending junior high school (56.2%), high school (37.8%) and college (5.9%). The procedure included a factorial analysis, in which the total sample was randomly divided into three samples. An exploratory factor analysis was performed with one part of the sample, and a confirmatory factor analysis was performed with the others parts, assessing internal consistency, construct reliability, and discriminant validity. The results indicate that this reduced version of the IAT for young people has good psychometric qualities and can be applied in research and clinical settings. With this version and the parent-teacher version there is a direct contribution to a tripartite assessment of internet addiction risk.

Amidst the rapid urbanization of cities worldwide, there is a pressing need for practical tools to manage and preserve the invaluable architectural heritage contained within them. This research introduces a systematic methodology for digitalizing and interpreting architectural heritage through augmented Reality (AR). The primary goal is to enhance the documentation, preservation, and accessibility of cultural assets, addressing both educational and touristic needs. Focusing on the historic district of Pelourinho in Salvador, Bahia, Brazil, the study showcases how 3D digitalization combined with AR can provide users with an interactive experience with historical structures, bridging the temporal divide. By integrating the digital replicas of historic buildings into a real-time environment, users gain enriched insights into these structures’ history, architecture, and cultural significance. Though the preliminary results underscore the potential of this approach, comprehensive user testing remains an area for future exploration. This paper thus highlights the potential of AR in historical and cultural preservation, suggesting its broader implications for education, tourism, and heritage management.

This study presents results of the sediment yield Watershed of Ribeirão do Pinhal, in the city of Limeira, São Paulo, conducted under three different scenarios of the land use: 1 – land use in 2008, 2 – with reforested protection areas, 3 – the increase sugarcane's areas over grassland and citrus areas. The Soil and Water Assessment Tool (SWAT) was used as a hydro-sedimentological modeling tool to simulate these scenarios. This watershed was divided into five sub-watersheds according to the prevalent use, and adjustments were made in soils database parameters and cultures that are in SWAT, to adapt it to the Brazilian reality. Was used climatological data of eight years (2007-2014) for this modeling. Different sediment yield could be noted in the different types of land use, sub-watersheds and scenarios. The uses that presented higher sediment yield, in ascending order, were: natural vegetation, sugarcane, citrus, annual crop e grassland. Sub-watershed number 2 had the highest sediment yield (~10Mg.ha^-1), while the sub-watershed 5, the lowest (5.51Mg.ha^-1). This remained in the three scenarios. Overall, scenario 2 had the lowest sediment yield (7.74Mg.ha^-1). Scenario 1 had 8.37 Mg.ha^-1 and scenario 3, 8.58Mg.ha^-1. SWAT was considered efficient to simulate the sediment yield by scenarios and by use, combining different thematic and tabular data when performing the necessary adjustments on their original database.

In recent years, novel food is becoming an emerging trend increasingly more demanding in developed countries. Food proteins from vegetables (pulses, legumes, cereals), fungi, bacteria and insects are being researched to introduce them in meat alternatives, beverages, baked products and others. One of the most complex challenges for introducing novel foods on the market is to assure food safety. New alimentary scenarios drive the detection of novel allergens that need to be identified and quantified with the aim of appropriate labelling. Allergenic reactions are mostly caused by proteins of great abundance in foods, most frequently of small molecular mass, glycosylated, water-soluble and with high stability to proteolysis. The most relevant plant and animal food allergens such as lipid transfer proteins, profilins, seed storage proteins, lactoglobulins, caseins, tropomyosins and parvalbumins from fruits, vegetables, nuts, milk, eggs, shellfish, and fish have been investigated. New methods for massive screening in the search of potential allergens must be developed particularly concerning protein databases and other online tools. Moreover, several bioinformatic tools based on sequence alignment, motif identification or 3-D structure predictions should be implemented as well. Finally, targeted proteomics will become a powerful technology for the quantification of these hazardous proteins. The ultimate objective is to build an effective and resilient surveillance network with this cutting-edge technology.

The Geopyörä breakage test uses two counter-rotating wheels to nip and crush rock specimens with a tightly controlled gap between rollers. The force applied and energy consumed during breakage are measured with instrumentation. In contrast to drop weigh test (DWT) methods, the breakage energy is a response to the rock compressive strength and degree of compression, not a controlled test input, such as the kinetic input energy of a falling weight. This paper presents the detailed measures conducted to evaluate the accuracy and precision of energy measurements across various ore types using the Geopyörä device. While force measurement was assessed just for its precision. The outputs are compared directly to the DWT measures of fragmentation at the same energy and fitted A and b parameters. The test reproducibility was evaluated using a Round-Robin methodology, testing several samples in multiple laboratories. The results confirmed that the new test has sufficient accuracy to match DWT results and excellent precision to assure reproducibility.

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 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.

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.

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.

According to a recent study by OpenAI, Open Research, and the University of Pennsylvania, large language models (LLMs) based on artificial intelligence (AI), such as Generative Pretrained Transformers (GPTs), may have potential implications on the job market, specifically regarding job occupations that demand writing or programming skills. The research points out Interpreters and Translators as one of the main job occupations with greater exposure to AI in the US job market (76.5%). This article, following a mixed-methods survey-based research, provides insights into the Portuguese Language Service Providers (LSPs) awareness and knowledge about AI, specifically regarding neural machine translation (NMT) and large language models (LLM), its actual use and usefulness, as well as their potential influence on work performance and labour market. The results show that most professionals are unable to identify if AI and/or automation technologies support the tools that are most used in the profession. The usefulness of AI is essentially low to moderate and the professionals who are less familiar with it and less knowledgeable also demonstrate lack of trust in it. Two thirds of the sample estimate negative or very negative effects of AI in the profession, expressing as main concerns the devaluation and replacement of experts, the reduction of income, and the reconfiguration of the career of translator to mere post-editors.

The research explores the impact of financial indicators on the credit ratings of companies listed on the S&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.

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.

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.

Portugal, in line with the European Union, is aiming for carbon neutrality by 2050 (Net 1 Zero), which implies a transition to sustainable energy sources. Climate change is all too evident, extreme weather periods are occurring in a cyclical manner, with greater brevity to such an extent that the grid operator must deal with production scenarios where it can no longer rely on hydroelectric production given the recurring drought situation. This situation increases dependence on thermal production using natural gas and imports. This has significant economic implications. Portugal has exploited its onshore wind potential, reaching an installed capacity of 5.671 MW by 2022. However, the expansion of onshore wind energy is limited to reinforcing existing infrastructure. To overcome these challenges, it is necessary to expand the exploitation of offshore wind potential that is already underway. This article proposes the location of offshore wind production platforms along the Portuguese coast. This allows for an analysis of offshore production and its optimization according to the minimum cost per MWh in the face of extreme scenarios, i.e., in periods of extreme drought where hydroelectric production capacity is practically non-existent. The model is fed by using market price indications and the amount of energy needed for the following day. Using forecast data, the model adapts offshore wind production for the following day according to the minimization of the average market price. The results of the simulations allow us to conclude that despite the high cost of offshore technology (in deep waters), in extreme climate scenarios, it enables cost reduction and a clear decrease in imports.

The purpose of this study was to examine the impact of fructose consumption during the peri-pubertal period on the later onset of metabolic syndrome in rats. Additionally, the study sought to explore the potential of moderate-intensity physical training as a non-pharmacological approach to mitigate the fructose effects. Male rats, 30 days old, received 10% fructose, and were submitted to concomitant moderate-intensity training until 60 days old. They were divided into 4 groups: sedentary control (SC), sedentary fructose (SF), trained control (TC), and trained fructose (TF). Fructose consumption mainly affected adult animals, resulting in glucose intolerance, increased periepididymal fat, and increased total cholesterol, triglycerides, and insulin levels. Furthermore, these rats exhibited reduced sympathetic nerve activity. The moderate running led to a decrease in periepididymal and retroperitoneal adipose tissue, as well as a reduction in total cholesterol and improved glucose tolerance. Peri-pubertal rats that received combination treatments exhibited lower levels of glucose and insulin during an intraperitoneal glucose tolerance test. The results indicate that 10% fructose supplementation during peripuberty predisposes to metabolic syndrome in adulthood. However, simultaneous moderate-intensity exercise training attenuates these effects and induces positive changes in glycemic homeostasis, lipid metabolism, and autonomic nervous system activity.

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.

This study aimed to determine the impact of a novel formulation of a supplement composed of the natural ingredients: bromelain, quercetin, and Lentinula edodes, on the gut microbiota of healthy adult dogs. Adult healthy female dogs were administered either a placebo (CTR, n = 15) or the supplement (TRT, n=15) over 28 days. Stool samples were collected for 16S rRNA sequencing before supplement administration (T0), at completion of supplement administration (T28), and one week after the end of supplement administration (T35) to characterize changes in the gut microbial communities. QIIME was used to determine both alpha- and beta-diversity and ANCOM-BC was used to identify differences in taxonomic abundances before and after supplementation. We found a significant decrease in overall diversity in CTR group, but no significant differences in overall diversity in the TRT group over time. Furthermore, we found differences in the abundance of several taxa in both CTR and TRT groups but differences in abundance of beneficial bacteria were more pronounced in TRT group. Specifically, we found increases in the abundance of sequences belonging to the genera Bifidobacterium, Lactobacillus, and Pediococcus at T28 in the TRT group with significant increases in Bifidobacterium and Lactobacillus persisting at T35 when compared to T0. Importantly, members of these genera are known to be pro anti-inflammatory and associated with a healthy gut microbiota in dogs. The results of our study show the potential of our supplement to selectively enhance specific beneficial bacterial taxa, offering a targeted approach to modulating the gut microbiome without causing disruptions to the overall equilibrium.

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.

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.

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

Nitric oxide has been implicated in symptoms of ethanol withdrawal in animal models. Zebrafish have been used as models to study neurobehavioral effects of ethanol (EtOH) withdrawal, but the mechanisms associated with these effects are not yet clear. Adult zebrafish were treated with 1% EtOH for 20 min per day for 8 days, injected with the nitric oxide synthase 2 (NOS-2) inhibitor aminoguanidine (50 mg/kg), and allowed to experience withdrawal (WD) in their hometanks for 7 days. EtOH WD increased anxiety-like behavior in the novel tank test, an effect that was blocked by aminoguanidine. EtOH WD also increased brain levels of nitrite, an effect that was partially blocked by aminoguanidine. These results underline a novel mechanism by which NOS-2 controls anxiety-like responses to ethanol withdrawal, with implications for the mechanistic study of symptoms associated with chronic ethanol abuse.

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.

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.

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.

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.

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.

The required processes and steps for making bread include technological and innovative concepts. The current trend is the use of less toxic compounds and green processes. Besides lactic acid bacteria and yeast, other microorganisms with special properties, such as enzymes, new aroma and flavor, exopolysaccharides, and vitamins, among other compounds with beneficial properties, could be added to bread manufacture, improving bread quality and health effects for the consumers. Freeze drying, new encapsulation methods, cryoprotectants, spray drying, fluidized bed drying, and vacuum drying are used for probiotics and microorganism cultures that will be used as starters or biological additives in the fermentation. The same development is observed in the preservation methods, and studies with plant extracts and essential oils have been proposed and introduced, replacing chemical agents, such as propionate, within the clean-label bread formulations concept. Baking science is a growing research line incorporating innovative methods and biological additives.

Medicinal plants are being tested as options to prevent infectious diseases in many countries. Baccharis crispa Spreng. (Asteraceae), is a native medicinal species widely used throughout South America. Our objective was to evaluate the antiviral activity of four wild populations of B. crispa from the province of Córdoba (Argentina) and determine if there is variability between them. The cytotoxicity of the extracts (chlorofom, ethanol and aquose) was evaluated by the neutral red uptake method. Using the plaque-forming unit reduction assay, virucidal and antiviral activity against Herpes Simplex type 1 and Chikungunya viruses were tested. Phytochemical screening of each extract was also performed. Puesto Pedernera (PP) population showed the best antiviral and virucidal effect, standing out the ethanolic extract as the least toxic and with the best inhibitory activity against both viral models. Villa del Parque (VP) population was inactive, regardless of the extract and the virus tested. The results revealed that extracts bioactivities vary significantly depending on the geographic area of collection, with PP and VP populations showing the most significant variability, not only in activity but also in chemical composition. These findings support the potential use of extracts as a source of therapeutic agents against different viruses.

Land degradation and climate change are among the main threats to the sustainability of ecosystems worldwide. Therefore, the restoration of degraded landscapes is essential to maintain the functionality of ecosystems, especially those with greater social, economic and environmental vulnerability. Nevertheless, policy-makers are frequently challenged by deciding on where to prioritize restoration actions, which usually includes to deal with multiple and complex needs under an always short budget. If these decisions are not taken based on proper data and processes, restoration implementation can easily fail. To help decision-makers taking informed decisions on where to implement restoration activities, we have developed a semiautomatic geospatial platform to prioritize areas for restoration activities based on ecological, social and economic variables. This platform takes advantage of the potential to integrate R coding, Google Earth Engine cloud computing and GIS visualization services to generate an interactive geospatial decision-maker tool for restoration. Here, we present a prototype version called "RePlant alpha" which was tested with data from the Central Zone of Chile. This exercise proved that integrating R and GEE was feasible, and that the analysis, with at least six indicators and for a specific region was also feasible to implement even from a personal computer. Therefore, the use of a virtual machine in the cloud with a large number of indicators over large areas is both possible and practical.

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.

With the continuous growth of electric and electronic appliances’ usage, the waste produced with obsolete material (e-waste) has an increasing environmental impact. Also, the production of such appliances bears to increased consumption of natural resources and produces a multitude of toxic and hazardous substances, which typically are not properly treated. One of the approaches that may be adopted to reduce such problems relies on the circularization of the current linear model, commonly adopted in the EEE value chain. This includes recovering eol products and reintroducing its parts, components, or raw materials into the value chain (e.g. semiconductors, circuit boards, raw metals, etc.), thus contributing to a more sustainable value chain. In this article, we present a state-of-art review that focuses on approaches and solutions for the EEE value chain traceability, and analyses the technologies that may be beneficial for promoting and implementing the CE model in this value chain.

As digitalization expands across all sectors, the economic toll of software defects on the U.S. economy reaches up to $2.41 trillion annually. High-profile incidents like the Boeing 787-Max 8 crash have shown the devastating potential of these defects, highlighting the critical importance of software testing within quality assurance frameworks. However, due to its complexity and resource intensity, the exhaustive nature of comprehensive testing often surpasses budget constraints. This research utilizes a machine learning (ML) model to enhance software testing decisions by pinpointing areas most susceptible to defects and optimizing scarce resource allocation. Previous studies have shown promising results using cost-sensitive training to refine ML models, improving predictive accuracy by reducing false negatives through addressing class imbalances in defect prediction datasets. This approach facilitates more targeted and effective testing efforts. Nevertheless, the generalizability of these models across different projects (cross-project) and programming languages (cross-language) remained untested. This study validates the model's applicability across diverse development environments by integrating various datasets from distinct projects into a unified, using a more interpretable ML approach. The results demonstrate that ML can support software testing decisions, enabling teams to identify up to seven times more defective modules with the same testing effort as a benchmark.

Antibody-based passive immunotherapy has been used effectively in the therapy and prophylaxis of infectious diseases. Outbreaks of the emerging viral infections from arthropod-borne viruses (arboviruses) represent a global public health problem due to the rapid spread and urge actions and treatment of the infected individuals to combat them. Preparedness in advance developing antivirals and studies related to the epidemiology could protect us from damages and losses. Immunotherapy based on monoclonal antibodies (mAbs) has shown to be very specific to combat infectious diseases and several illnesses. Recent advances in the mAb discovery techniques allowed the development and approval of a wide number of therapeutic mAbs. This review focuses on the technological approaches available to select neutralizing mAbs for emerging arbovirus infections and outstanding strategies to obtain highly effective and potent mAbs. The characteristics of mAbs developed as prophylactic and therapeutic antiviral agents for the dengue, Zika, chikungunya and West Nile virus are presented, as well as the protective effect verified in animal model studies.