The present study identified the influence of green advertising and eco-labels on the attitude and environmental awareness of millennials who purchase ecological products in shopping centers in Ecuador. The research was quantitative, correlational and with a cross-sectional design. A total of 430 millennials participated in the study. A 20-question survey was applied in person outside the shopping centers of Quito and Guayaquil - Ecuador. The convergent and discriminant validity of the research model was verified using Confirmatory Factor Analysis (CFA) and Structural Equation Models (SEM). SPSS 20 and AMOS 24 programs were used for statistical analysis. The results show that green advertising influences environmental attitudes (β: 0,245) and awareness (β: 0,110) and specifically influences purchasing behaviour (β: 0,154) for green products. Although eco-labels do not directly influence purchasing behaviour (β: 0,128), they influence the attitudes (β: 0,406) and ecological awareness (β: 0,277) of millennials who buy organic products. This article is one of the first studies to identify the relationship between green advertising elements and green product purchasing behaviors among millennials in a developing country, concluding that marketing strategies based on green advertising and eco-labels have an impact on the attitude and environmental awareness of millennials, but only advertising directly affects purchasing behaviour while eco-labels do not. This research has social implications since it corroborates that millennials are concerned about environmental problems and are willing to contribute to sustainability.

The present research aimed to identify if consumption values influence the attitudes of Millennials who intend to purchase organic products. The research was quantitative, with a correlational scope and a cross-sectional design, and it was conducted on 509 Peruvian millennials. A questionnaire consisting of 23 questions was administered, and responses were quantified using a five-point Likert scale. The results were processed through an Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM) conducted using Statistical Package for Social Sciences 24 and AMOS 24. The study identified that environmental attitudes of Millennials do influence their intentions to purchase organic products, and the antecedents of these attitudes are functional and social values, whereas emotional, conditional, and epistemic values do not. The study confirmed that consumption values, either as a second-order variable or as a single construct, do not influence the attitudes of Millennials who intend to purchase organic products, thus confirming that these dimensions should be measured independently.

Tomato is considered moderately sensitive to salinity, which detracts from the quality and yield of its fruit; therefore, wild populations have been used as a genetic resource. The aim of this research was to identify lines derived from wild tomato populations with tolerance to salinity during the germination and seedling stages. During germination, 52 wild lines and 2 commercial hybrids (Imperial®, Reserva®) were subjected to 150 mM and 0 mM NaCl and evaluated. The test was carried out for 20 days in a germination chamber with constant darkness, temperature of 25±2 °C and relative humidity of 80±4%. At the seedling stage, 22 wild tomato lines with the best performance in the germination test and 2 commercial hybrids (Imperial®, Topanga®) were evaluated for 12 days in a floating raft system. Concentrations of 175 mM and 0 mM NaCl were used. During germination, the saline condition decreased germination percentage (65.2%), speed of germination (88.2%), steam length (72.5%), root length (46.56%), normal plants number (59.5%), stem dry matter (68.78%), root dry matter (61.99%), and total dry matter (67.1%). At the seedling stage, this condition decreased (P<0.05) the aerial part dry matter (46.37%), leaf area (59.35%), root length (42.43%), final plant height (40.24%), and growth rate (71.42%). Seventeen tolerant genotypes were identified at one of both developmental stages, while one genotype showed tolerance at both stages. These results indicate that there are different response mechanisms in each developmental stage. Native tomatoes play an important role in the identification of tolerant genotypes since they can be used as genetic resources for obtaining commercial genotypes with salt tolerance.

Digital twins are an emerging technology that could be harnessed for the digitalization of the industry. Steel industry systems contain a large number of electro-hydraulic components, as proportional valves. An input-output model for a novel water proportional cartridge valve is derived from physical modelling based on fluid mechanics, dynamics, and electrical principles. The valve is a two-stage valve with two 2/2-way water proportional valves as the pilot stage and a marginally stable poppet-type cartridge valve as the main valve. The orifice equation, which is based on Bernoulli principles, is approximated by a polynomial which makes parameter estimation easier and makes modelling possible without measuring pressure of the varying control volume situated in the pilot stage part of the valve. Data were collected when the valve was operating as a component in a closed-loop system as part of a press-mill machine in a steel manufacturing plant. Parameter estimation was made by convex optimization with physical constraints to overcome problems caused by poor system excitation. For comparison, a simple linear model was derived and the least squares method used for parameter estimation. A thorough estimation of the parameters relative errors is presented. The model contains 5 parameters related to the design parameters of the valve. The modelled position output is in good agreement with experimental data for training and test data. The model can be used for real time monitoring of the valve’s status by the model parameters. One of the model parameters varies linearly with production cycles. Thus, aging of the valve can be monitored.

Knowledge of the motivations of managers to practice Corporate Social Responsibility (CSR) is a critical issue for those who promote its adoption. The understanding of these reasons is complicated by the fact that there are different ways of defining this responsibility, raising the question of whether there is any relationship between reasons for adopting it and how to define it. To address this issue, a classification of these reasons was constructed and related to a classification of the different ways of defining CSR. A self-administered questionnaire was applied to a non-probability sample of Social Responsibility managers, which included indicators for both classifications. It was found that these managers present all types of motives, with proactive outweighing reactive motives and that there is a significant degree of correlation between the ways of defining CSR and the reasons for doing so. This suggests that managers present coherence in their objectives (motives) and means (practices of Social Responsibility.

Starch is a biopolymer with wide potential for the generation of new biodegradable packages due to its high availability and low price. However, due to its weak functional properties, it is necessary to limit the interaction of some hydroxyl, and to evaluate blends with other polymers to improve their performance. Glycerol plasticized acetylated corn starch films were developed by the casting method, and the impact of incorporating chitosan (TPS:CH) at various proportions (75:25, 50:50, and 25:75 v/v) was studied. The effect of the chitosan ratios on the films' physical, mechanical, water vapor barrier, and thermal properties was evaluated. Chitosan protonated amino groups promote the formation of intermolecular bonds, improving the tensile strength, the thermal stability, the water adsorption capacity, and the gas barrier of starch films. Where the film composed of TPS25-CH75 was the one that presented the best barrier to water vapor. These composite films are a good option for development of biodegradable packaging.

Scales are widely used in many agricultural applications, ranging from weighing crops at harvest to determine crop yields to regularly weighing animals to determine growth rate. In agricultural research applications, there is a long history of measuring crop water use (evapotranspiration) using a particular type of scale called weighing lysimeters. Typically, weighing lysimeters require very accurate data logging systems that tend to be expensive. Recent developments in open-source technologies, such as micro-controllers and Internet of Things (IoT) platforms, created opportunities for developing effective and affordable ways to monitor crop water use and transmit the data to the Internet in near real-time. Therefore, this study aimed to create an affordable Internet of Things (IoT) scale system to measure crop evapotranspiration. A scale system to monitor crop evapotranspiration was developed consisting of an Arduino-compatible microcontroller with cell phone communication, electronic load cells, an Inter-Integrated Circuit (I2C) multiplexer, and analog-to-digital converters (ADC). The system was powered by a LiPo battery, charged by a small (6 W) solar panel. The IoT scale system was programmed to collect data from the load cells at regular time intervals and send the data to the ThingSpeak.com IoT platform. The system performed successfully during indoor and outdoor experiments conducted in 2023 at the Clemson University Edisto Research and Education Center, Blackville, SC. The results from the experiments showed that the IoT scale system could accurately measure crop evapotranspiration using the weighing lysimeter technique.

Some of the barriers preventing Virtual Reality (VR) from being widely adopted are the cost and unfamiliarity of VR systems. Here we propose that in many cases the specialized controllers shipped with most VR head-mounted displays can be replaced by a regular smartphone, cutting the cost of the system, and allowing users to interact in VR using a device they are already familiar with. To achieve this, we developed SmartVR Pointer, an approach that uses smartphones as a replacement for the specialized controllers for two essential operations in VR: selection and navigation by teleporting. In SmartVR Pointer a camera mounted on the head-mounted display (HMD) is tilted downwards so that it points to where the user will naturally be holding their phone in front of them. SmartVR Pointer supports three selection modalities: tracker-based,gaze-based, and combined/hybrid. In the tracker-based SmartVR pointer selection we use image-based tracking to track a QR code displayed on the phone screen and them map the phone’s position to a pointer shown within the field of view of the camera in the Virtual Environment. In the gaze-based selection modality the user places the pointer using their gaze and taps on the phone for selection. The combined technique is a hybrid between head-gaze-based interaction in VR and smartphone-based Augmented Reality. It allows the user to control a VR pointer that behaves like a mouse pointer by moving their smartphone to select objects within the virtual environment, and to interact with the selected objects using the smartphone’s touch screen. The touchscreen is used for selection and dragging. SmartVR Pointer is simple and requires no calibration and no complex hardware assembly or disassembly. We demonstrate successful interactive applications of SmartVR Pointer in a VR environment with a demo where the user navigates in the virtual environment using teleportation points on the floor and then solves a Tetris-style key-and-lock challenge.

In this article, the evolution in space and in time of the coronavirus pandemic is studied by utilizing a neural network with a self-organizing nature for the spatial analysis of data, and a fuzzy fractal method for capturing the temporal trends of the time series of the countries. Self-organizing neural networks possess the capability for clustering countries in the space domain based on their similar characteristics with respect to their coronavirus cases. In this form enabling finding the countries that are having similar behavior and thus can benefit from utilizing the same methods in fighting the virus propagation. To validate the approach, publicly available datasets of coronavirus cases worldwide have been used. In addition, a fuzzy fractal approach is utilized for the temporal analysis of time series of the countries. Then, a hybrid combination of both the self-organizing maps and the fuzzy fractal approach is proposed for efficient COVID-19 forecasting of the countries. Relevant conclusions have emerged from this study, that may be of great help in putting forward the best possible strategies in fighting the virus pandemic. A lot of the existing works concerned with the Coronavirus have look at the problem mostly from the temporal viewpoint that is of course relevant, but we strongly believe that the combination of both aspects of the problem is relevant to improve the forecasting ability. The most relevant contribution of this article is the proposal of combining neural networks with a self-organizing nature for clustering countries with high similarity and the fuzzy fractal approach for being able to forecast the times series and help in planning control actions for the Coronavirus pandemic.

The demographic history of anatomically modern humans (AMH) involves multiple migration events, population extinctions and genetic adaptations. As genome-wide data from complete genome sequencing becomes increasingly abundant and available even from extinct hominins, new insights of the evolutionary history of our species are discovered. It is currently known that AMH introgressed with archaic hominins once they left the African continent. Current out of African human genomes carry fragments of archaic origin. This review focuses on the fitness consequences of archaic interbreeding in current human populations. We discuss new insights and challenges that researchers face when interpreting the potential impact of introgression on fitness and testing hypotheses about the role of selection within the context of health and disease.

The effect of the addition of maleated polyethylene (MAPE) to compounds of natural rubber (NR) and Teline monspessulana flour (TMF) previously mercerized was investigated. Two factors were analyzed: A. concentration of MAPE with five levels 2; 4; 6; 8; 10 phr (parts per hundred rubber), B. concentration of TMF with two levels 25 and 40 phr. The effect of MAPE on compatibility between NR and HTM was evaluated by tensile testing the compounds. The mixing was performed in a laboratory scale mill. The test tubes were obtained by cutting or die-cutting crosslinked peroxide sheets, these were obtained during the compression molding process. Analysis indicate that the MAPE coupling agent improved the compatibility between HTM and NR, this effect was evidenced by the values of tensile strength and elongation at break. However, the gel content determination indicates that the addition of 10 phr of MAPE crosslinking decreases due to competition with coupling reaction MAPE - HTM.

The objective of this research is to develop an experimental-theoretical analysis about the influence of the cooling medium and the geometry of the welding bead profile in fatigue life and associated parameters with structural integrity of welded joints. A welded joint with cruciform geometry is considered using SMAW, plates in structural steel ASTM A36 HR of 8 mm of thickness and E6013 electrode input. A three-dimensional computational model of the cruciform joint was created using the finite element method. For this model, the surface undulation of the cord and differentiation in the mechanical properties of the fusion zone were considered, the heat-affected zone (HAZ) and base material, respectively. In addition, an initial residual stress field which was established experimentally was considered. The results were a set of analytical expressions for the weld magnification factor Mk. It was found that values for the latter decrease markedly in function of the intensity of the cooling medium used in the post welding cooling phase, mainly due to the effect of the residual compressive stresses. The obtained models of behavior of the weld magnification factor are compared with the results from other researchers with some small differences, mainly due to the inclusion of the cooling effect of the post weld and the variation of the leg of the weld bead. The obtained analytical equations in the present research for Mk can be used in management models of life and structural integrity for this type of welded joint.

Dump design and scheduling are critical elements to effective mine planning, especially if several of them are required in large-scale open pit mines. Infrastructure capital and transportation costs are considerable from an early stage in the mining project, and through the life-of-mine as these dumps gradually become immense structures. Delivered mining rates, as well as certain spatial and physical constraints, provide a set of parameters of mathematical and economic relationship that creates opportunities for modelling and thus facilitates the measuring and optimization of ultimate dump design by using programming and empirical techniques while achieving economic objectives. This paper presents a methodology to model and optimize the design of a mine dump by minimizing the total haulage costs. The proposed methodology consists on: (i) Formulation of a dump model based on a system of equations relying on multiple relevant parameters; (ii) Solves by minimizing the total cost using linear programming and determines a ‘preliminary’ dump design; (iii) Through a series of iterations, modifies the ‘preliminary’ footprint by projecting it to the topography and creates the ultimate dump design. Finally, an example application for a waste rock dump illustrates this methodology.

This work demonstrated the potential of CNC as a substitute for PEG as an additive in ultrafiltration membrane fabrication. Two sets of modified membranes were fabricated using the phase inversion technique with polyethersulfone (PES) as the base polymer, and 1-N-methyl-2 pyrrolidone (NMP) as the solvent. The first set was fabricated with 0.075 wt% CNC, while the second set was fabricated with 2 wt% PEG. All membranes were characterized using SEM, EDX, FTIR, and contact angle measurements. The SEM images were analyzed for surface characteristics using WSxM 5.0 Develop 9.1 software. The membranes were tested, characterized, and compared for their performance in treating both synthetic turbid water and real restaurant Both membranes exhibited improved hydrophilicity, morphology, pore structure, and roughness. Both membranes also exhibited similar water flux for real and synthetic polluted water. However, the membrane prepared with CNC gave the higher turbidity removal and COD removal when raw restaurant water was treated. The membrane compared well with the UF membrane containing 2 wt% PEG in terms of morphology and performance when synthetic turbid water and raw restaurant water were treated.

This paper presents a novel improvement of MuSIASEM (Multiscale Integrated Analysis of the Societal and Ecological Metabolism) by incorporating a new regional analysis of the electricity metabolism across levels. An analysis of Mexico illustrates this toolkit and shows that the industry sector had Economic Energy Intensity (EEI) with 40.3 MWh/MMXN reached a higher value than the commerce and services sector with 0.84 MWh/MMXN. Regarding the Economic Labor Productivity (ELP) indicator (AV/h), the industrial sector with 208.5 TMXN/Kh reached a higher value than the Commercial and services sector with 114.3 TMXN/Kh. With reference to the Exosomatic Metabolic Rate (EMR), the Household sector obtained 59.3 KWh/Kh whereas the paid sector reached 2,486.4 KWh/Kh. Disaggregation of the EMR indicator into economic sectors shows that the Industrial sector obtained 8.4 KWh/Kh and the commercial and services sector reached 0.10 KWh/Kh. The lack of complete data for the agricultural sector does not allow us to calculate EEI, ELP, and EMR indicators accurately. Considering the analysis of indicators by regions, regarding the EEI rate, the Central region had the lowest value with 12.7 MWh/MMXN, followed by the Northeast with 21.4 MWh/MMXN and Western with 29.4 MWh/ MMXN, which means that they require less electricity to produce more added value. In terms of the ELP indicator, it was found regions with higher values were Northeast with 182.3 MMXN/Mh, Central with 177.5 MMXN/Mh, and North with 127 MMXN/Mh, which means that these regions produce more added value per hour of work. About the EMR, it is observed that regions in the northern part of the country had higher values: Northwest with 337 KWh/Kh, Baja California Sur with 334 KWh/Kh, Baja California with 328 KWh/Kh, North with 313 KWh/Kh and Northeast with 274 KWh/Kh, which means that these regions consume more electricity per hour. This innovative approach is useful for governance because it helps to understand and reduce asymmetries across regions, resulting in more social equality and a better economic equilibrium across sectors and regions.

In this review, we aimed to understand the relationship between SARS-CoV-2 infection and preeclampsia severity in infected pregnant women. Pregnant women with SARS- CoV-2 infection have been shown to have a significantly increased risk of maternal death, ICU admission, preterm delivery, and stillbirth compared with those without infection. The risk of preeclampsia also increases in pregnant women infected with SARS-CoV-2, particularly in those with severe symptoms. We emphasize the im-portance of specialized clinical management to prevent poor pregnancy outcomes in this situation. The association between COVID-19 and preeclampsia (PE) is likely due to multiple mechanisms, including the direct effects of the virus on trophoblast function and the arterial wall, acute atherosis, local inflammation leading to pla-cental ischemia, exaggerated inflammatory responses in pregnant women, SARS-CoV-2-related myocardial injury, cytokine storm, and thrombotic microan-giopathy. Emphasis has been placed on the potential impact of COVID-19 on pregnant women, specifically in relation to thrombotic complications, placental dysfunction, and cardiovascular dysfunction. Undoubtedly, one of the diagnostic tools to differentiate between COVID-19-induced preeclampsia-like syndrome and true preeclampsia is the use of biomarkers, such as the sFlt-1/PlGF ratio. We wish to highlight the potential for COVID-19-induced myocardial injury in pregnant women and the associated in-crease in maternal mortality rate. Vaccination against COVID-19 in the general population and in pregnant women in particular, drastically reduced the severity of the disease. There is an urgent need to continue the follow-up of these women and their children to detect the appearance of sequelae of the disease or peristent COVID 19

The applicability of the distance aggregation problem has attracted the interest of many authors. Motivated by this fact, in this paper we face the modular quasi-(pseudo-)metric aggregation problem. We characterize those functions that allow merging a collection of modular quasi-(pseudo-)metrics into a single one. Specifically, a description of such functions in terms of triangle triplets is given and, in addition, the relationship between modular quasi-(pseudo-)metric aggregation functions and modular (pseudo-)metric aggregation functions is discussed. Such characterizations are illustrated with appropriate examples. A few methods to construct modular quasi-(pseudo-)metrics are yielded. Several properties of modular quasi-(pseudo-)metric aggregation functions are explored and used to develop quick tests for discarding candidate functions to aggregate modular quasi-(pseudo-)metrics. Moreover, a characterization of those modular quasi-(pseudo-)metric aggregation functions that preserve modular quasi-(pseudo-)metrics is also provided. Furthermore, the relationship between modular quasi-(pseudo-)metric aggregation functions and quasi-(pseudo-)metric aggregation functions is studied in such a way that significative differences are displayed.

The province of Jaén (Andalusia, Spain), despite being declared the European territory with the largest number of defensive constructions (castles, fortifications, etc.), has few conservation plans, with many remains included on the Red List of Spanish Heritage ly-ing abandoned. This poses a challenge for landscape conservation and the optimal use of the province’s tourism potential. In this paper we present the early implementation of an ongoing methodological approach designed to alleviate this situation. It takes advantage of data from the Sentinel 2A and 2B satellites, HBIM, RPAS, GIS and fieldwork that will be applied across five archaeological case studies. It has been tested for the first time in the village of Magaña. Three main objectives and phases of this methodological approach have been designed: 1. Preparation of an Environmental Risk Chart with which to answer such ques-tions as “How have climate change, anthropic alterations and environmental characteris-tics affected the state of conservation of certain heritage sites?” 2. Preparation of HBIM models to foster monitorisation and conservation policies for the main archaeological remains and improving their protection based on digital and technological tools. 3. Building a Smart Tourism App for mobile devices aimed at promoting smart tourism by digitalising and virtualising tourist itineraries and archaeological remains. Finally, public administrations will be apprised of the need to implement a conservation policy for cultural assets and their surroundings in a simple, quick and cost-effective man-ner.

The province of Jaén (Andalusia, Spain), despite being declared the European territory with the largest number of defensive constructions (castles and fortifications), has few conservation plans, with many remains included on the Red List of Spanish Heritage lying abandoned. This presents a problem for the conservation of the landscape and the optimal use of the province’s tourism potential. Through the study case of Magaña hamlet two actions are proposed to alleviate this situation: The creation of an archaeological and environmental risk chart with which to answer such questions as “How have climate change, anthropic alterations and environmental charac-teristics affected the state of conservation of certain heritage sites?” and to put forward proposals for improving their protection using as a basis digital and technological tools, such as remote sensing (SAR), taking advantage of data from the Sentinel 2A and 2B satellites, HBIM, RPAS and GIS. To foster the promotion of smart tourism by digitalising and virtualising tourist routes and archaeological remains by building a Smart Tourism App for mobile devices. Finally, public administrations will be apprised of the need to implement a conservation policy for cultural as-sets and their surroundings in a simple, quick and cost-effective manner.

Sufficient evidence is currently available to demonstrate the reality of the warming of our planet's climate system. Global warming has different effects on climate at the regional and local levels. The detection of changes in extreme events using instrumental data provides further evidence of such warming and allows for the characterization of its local manifestations. The present study analyzes changes in temperature and precipitation extremes in the Mexican state of Zacatecas using climate change indices developed by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDI). We studied a 40-year period (1976-2015) using annual and seasonal time scales. Maximum and minimum temperature data were used, as well as precipitation statistics from the Mexican climatology database (CLICOM) provided by the Mexican meteorological service. Weather stations with at least 80% of data availability for the selected study period were selected; these databases were subjected to quality control, homogenization, and data filling using Climatol, which runs in the R programming language. These homogenized series were used to obtain daily grides of the three variables at a resolution of 1.3 km. Results reveal important changes in temperature-related indices, such as the increase in maximum temperature and the decrease in minimum temperature. Irregular variability was observed in the case of precipitation, which could be associated with low-frequency oscillations such as the Pacific Decadal Oscillation and the El Niño–Southern Oscillation. The possible impact of these changes in temperature and the increased irregularity of precipitation could have a negative impact on the agricultural sector, especially given that the state of Zacatecas is the largest national bean producer. The most important problems in the short term will be related to the difficulty of adapting to these rapid changes and the new climate scenario, which will pose new challenges in the future.

This study explores into a comprehensive examination of an optical cavity system that integrates Raman and Yb-doped gain media, with a focus on understanding their interactions. The research implies a characterization of each gain medium within the cavity while subjecting them to diverse co-pumping conditions with the other. When the Raman-lasing cavity is co-pumped by exciting the Yb-doped section, the resulting composite laser exhibits significant threshold reductions and there is an optimal co-pumping regime that enhances energy transfer from pump to Stokes. As for the complementary cavity, where the Yb-doped gain is influenced by the co-pumped Raman gain, at moderate pump powers a light-controlling-light behavior phenomenon arises. Within this regime, the 1064-nm signal suppresses the Yb-generated 1115-nm signal, suggesting potential applications in intracavity optical modulation. For higher pump levels, a cooperative effect emerges whereby both lasers mutually enhance each other. Minor variations in the primary 974-nm pump power, even by just a few milliwatts, result in significant capabilities for switching or modulating the Stokes signal. Under these conditions of mutual enhancement, the hybrid optical system validates notable improvements regarding energy transfer efficiency and threshold reduction. This research provides valuable insights into the intricate dynamics of optical cavity systems and reveals promising avenues for applications in advanced optical modulation technologies.

The third trimester of pregnancy is the most critical period for human brain development, during which significant changes occur in the morphology of the brain. The development of sulci and gyri allows considerable increase of the brain surface. In premature childrens, these alterations take place outside the womb that may cause a disruption of the normal brain maturation process. We hypothesize that a normalized atlas of brain maturation with cerebral ultrasound images from birth to term equivalent age will help clinicians assess these changes. This work proposes a semi-automatic GUI platform for segmenting the main cerebral sulci in the clinical setting from ultrasound images. This platform has been obtained from images of a cerebral ultrasound neonatal database images provided by two clinical researchers from the Hospital Sant Joan de Déu in Barcelona, Spain. The primary objective is to provide a user-friendly design platform for clinicians, for running and visualizing an atlas of images validated by medical experts. This GUI offers different segmentation approaches, pre-processing tools, and is friendly designed for running, visualizing images, and segmenting the principal sulci. The presented results are discussed in detail in this paper, providing an exhaustive analysis of the proposed approach’s effectiveness.

Our research team compared the performance of matrix-assisted laser desorption/ionization followed by a time of flight (MALDI-TOF) mass spectrometry and genomic DNA extraction followed by sequencing, assembly and alignment for phylogenetic assessment. We performed these comparisons to determine our methodology’s overall efficacy and accuracy for environmental bacteria. In addition, we collected samples from various contaminated rivers in the Dominican Republic. For both methods, we analyzed these results and reported the main differences between each method.

DNA methylation and other epigenetic factors are important in the pathogenesis of late-onset Alzheimer’s disease (LOAD). Methylenetetrahydrofolate reductase (MTHFR) gene mutations occur in most elderly patients with memory loss. MTHFR is critical for production of S-adenosyl-L-methionine (SAM), the principal methyl donor. A common mutation (1364T/T) of the cystathionine-γ-lyase (CTH) gene affects the enzyme that converts cystathionine to cysteine in the trans-sulfuration pathway causing plasma elevation of total homocysteine (tHcy) or hyperhomocysteinemia – a strong and independent risk factor for cognitive loss and AD. Other causes of hyperhomocysteinemia include aging, nutritional factors, and deficiencies of B vitamins. We emphasize the importance of supplementing vitamin B₁₂ (methylcobalamin), vitamin B₉ (folic acid), vitamin B₆ (pyridoxine), and SAM to patients in early stages of LOAD.

: One of the challenges facing operations management is the design, choice and imple-mentation of action plans adapted to the magnitude of the deviations of the variables of an industrial process. Making conscious and quick decisions is crucial to achieving im-provements in productivity. This will be achieved if the organization's internal and external communication model is strategically designed, considering specific cultural factors and the symmetry or asymmetry required in the communication model. However, how do we organize ourselves and through what channels do we communicate within a production process to generate Big Data that combines data from technologies and the perception, comprehension and projection of experienced humans? Our purpose is to create an operations management model that facilitates the incorporation of technology, allows a prompt response to failures, and promotes the sustainability of processes, without losing sight of its alignment with the organizational strategy. The developed model was implemented in an operations management team, following the guidelines of an action researcher methodology. This resulted in the design of an operations management model and a detailed methodology for its implementation, achieving sig-nificant improvements in the metrics of the current process, making it a success story.

(1) Background: Neglected tropical diseases (NTDs) have been overlooked on the global health agenda and in the priorities of national systems in low- and middle-income countries (LMICs). In 2012, the Sustainable Development Goals (SDGs) were created to ensure healthy lives and promoting well-being for all. This roadmap set out to accelerate work to overcome the global impact of NTDs. Almost a decade has passed since NTDs were re-launched as a global priority. Investment in research and development, as well as the production of scientific literature on NTDs, is expected to have increased significantly. (2) Methods: A bibliometric analysis of the scientific production of Latin America and the Caribbean (LAC) was carried out in relation to 19 endemic NTDs. These data were compared with the scientific production in malaria, tuberculosis and HIV / AIDS. The database available from Thomson Reuters Web of Science (WoS) was used. In addition, the average annual growth percentage was calculated for each disease. (3) Results: In the last decade, the NTDs with the highest number of publications in the world were dengue and leishmaniasis. The United States was the most prolific country in the world in 15 out of 19 NTDs analyzed. In the LAC region, Brazil was the largest contributor for 16 of the 19 NTDs analyzed. Arboviral diseases showed the highest average annual growth. The number of publications for malaria, tuberculosis and HIV /AIDS was considerably higher than for NTDs. The contribution of most LAC countries, especially those considered as LMICs, is inadequate and does not reflect the relevance of NTDs for the public health of the population. (4) Conclusion: This is the first bibliometric analysis to assess the trend of scientific documents on endemic NTDs in LAC. Our results could be used by decision makers both to strengthen investment policies in research and development in NTDs.

In recent years, new metaheuristic algorithms have been developed taking as reference the inspiration on biological and natural phenomena. This nature-inspired approach for algorithm development has been widely used by many researchers in solving optimization problem. These algorithms have been compared with the traditional ones algorithms and have demonstrated to be superior in complex problems. This paper attempts to describe the algorithms based on nature, that are used in fuzzy clustering. We briefly describe the optimization methods, the most cited nature-inspired algorithms published in recent years, authors, networks and relationship of the works, etc. We believe the paper can serve as a basis for analysis of the new are of nature and bio-inspired optimization of fuzzy clustering.

The burdens of malnutrition, protein and micronutrient deficiency, and obesity cause enormous costs to society. Crop nutritional quality has been compromised by the emphasis on edible yield and through the loss of biodiversity due to the introduction of high-yielding uniform cultivars. Heirloom crop cultivars are traditional cultivars grown for a long time (> 50 years), and whose heritage has been preserved by regional, ethnic or family groups. Heirlooms are recognized for their unique appearance, names, uses and historical significance. They are gaining in popularity because of their unique flavors and cultural significance to local cuisine, and their role in sustainable food production for small-scale farmers. As a contrast to modern cultivars, heirlooms may offer a welcome alternative in certain markets. Recently, market channels have emerged for heirloom cultivars in the form of farmer-breeder-chef collaborations and seed savers organizations. There is therefore urgent need to know more about the traits available in heirloom cultivars, particularly for productivity, stress tolerance, proximate composition, sensory quality and flavor. This information is scattered and the intention of this review is to document some of the unique characteristics of heirloom cultivars that may be channeled into breeding programs for developing locally adapted high value cultivars.

Carbon footprint mitigation actions have become a key issue for companies involved in urban freight transport. The electrification of the delivery fleets is one of the crucial sustainable actions carried out. To this end, it is necessary to explore several fleet renewal strategies over a finite planning horizon evaluating different types of electric powertrains for light commercial vehicles. The primary goal of this purpose-built analysis is to assist and boost the fleet managers' decisions when transitioning to alternative-fuelled vans, intending to maximize cost savings and reduce greenhouse gas emissions inventory. The model presented in this work is a Multi-Objective Linear Programming hybrid analysis taking into account the vehicle and energy supply infrastructure costs and the emissions reported in each inventory scope following the Greenhouse Gas Protocol sustainability guidelines. From this perspective, the conducted research offers a novel approximation to fleet management problems enabling a break-down cost analysis and an evaluation of the annual emissions company report. The comprehensive numerical simulations carried out over different study scenarios in Spain demonstrate that the optimization approach does not only show effective fleet renewal strategies but also identifies critical factors that impact the fleet's competitiveness, offering valuable insights for fleet managers and policymakers to meet carbon footprint reductions in a cost-effectively way.

Tetranychid outbreaks have been detected since 2016 in southern highbush blueberries (SHB); however, it was not until 2019 when the southern red mite (SRM), Oligonychus ilicis (Acari: Tetranychidae) was confirmed as the pest causing severe bronzing and stunting, in multiple Florida and Georgia commercial blueberry plantings. There is little known about the management of SRM in SHB and only three miticides (fenazaquin, fenpyroximate, and acequinocyl), have recently been registered for use in SHB between 2019 and 2020. Similarly, there is no knowledge regarding the existence of natural enemies of SRM in SHB. This is the first report of naturally occurring predatory mites (Amblyseius sp. and Neoseiulus ilicis) associated with SRM in SHB. Predatory mites were recorded in treated bushes after evaluating the performance of seven miticides used to manage SRM populations including spiromesifen, acequinocyl, sulfur, sulfur + molasses, bifenazate, fenpyroximate, and fenazaquin. Miticide efficacy was rated based on the number of SRM recorded on collected leaves and plant damage ratings using an arbitrary index (from 0= no bronzing to 4= 100% bronzing). Additionally, the presence or absence of predatory mites per sample was recorded. Fenpyroximate used as the standard miticide, significantly reduced mite numbers seven days after application, as well as acequinocyl and fenazaquin. Only plants treated with fenpyroximate or fenazaquin showed significantly less bronzing compared with the control plants. Overall, fenpyroximate and fenazaquin demonstrated the best performance for managing O. ilicis on SHB and safe to naturally occurring predatory mites. Lastly, the level of growers’ awareness regarding SRM was assessed using surveys in 2020 to design adequate educational materials available to the grower community.

PHA synthases (PhaC) are grouped into four classes based on the kinetics and mechanisms of reaction. The grouping of PhaC enzymes into four classes is dependent on substrate specificity, according to the preference in forming short chain length (scl) or medium chain length (mcl) polymers: class I, class III, and class IV produce scl-PHAs depending on propionate, butyrate, valerate and hexanoate precursors, while class II phaC synthesize mcl-PHAs based on the alkane (C6 to C14) precursors. PHA synthases of class I, in particular PhaC_Cs from Chromobacterium USM2 and PhaC_Cn/RePhaC1 from Cupriavidus necator/R. eutropha, have been analysed and the crystal structures of the C-domains have been determined. PhaC_Cn/RePhaC1 was also studied by small angle X-ray scattering (SAXS) analysis. Models have been proposed for dimerization, catalysis mechanism, substrate recognition and affinity, product formation and product egress route. The assays based on amino acid substitution by mutagenesis have been useful to validate the hypothesis on the role of amino acids in catalysis and in accommodation of bulky substrates, for the synthesis of PHB co-polymers and medium chain length-PHA polymers with optimized chemical properties.

The purpose of this systematic review is to examine the various articles published in the field of neuropsychology of anxiety research in terms of publication type and volume, methodology, and subject matter. The significance of this topic derives from the clinical and functional consequences of cognitive symptoms. Generalized anxiety disorder refers to the cluster of clinical symptoms characterized by predominant anxious anticipation and difficulty controlling worry. In order for the review to be systematic and reproducible, a search of the PsycINFO, Scopus, PubMed, Elsevier databases and an analysis using the PRISMA method are suggested. After analyzing the research data, empirical studies evaluating the clinical neuropsychology of generalized anxiety disorder are discussed.

The KARS gene encodes the aminoacyl-tRNA synthetase (aaRS) which activates and joins the lysin with its corresponding transfer RNA (tRNA), through the ATP-dependent aminoacylation of the amino acid. The KARS gene mutations have been linked to diverse neurologic phenotypes such as: neurosensorial hearing loss, leukodistrophy, microcephaly, developmental delay or regression, peripheral neuropathy, cardiomyopathy, impairment of the mitochondrial respiratory chain, hyperlactatemia, among others. This article presents the case of a Colombian pediatric patient with two pathological missense variants in a compound heterozygous state in the KARS gene.

This paper shows the firsts results of a methodological approach in which Remote Sensing technologies (Satellite imagery and LiDAR) combined with Least Cost Path algorithm on GIS are being tested like tools to overcome locally-based interpretations about populational patterns and communication routes during Flavian municipality in the Comarca de El Condado region. The identification of fourteen hypothetical communication routes between already known archaeological sites thanks to a recent archaeological prospection, and the confirmation of three sections of them and a new archaeological site demonstrate that the combined use of the aforementioned technics has a very useful to delve more deeply, more widely and at a variety of different scales into the relation between the twelve known/selected Early Roman Empire sites and the surrounding landscape in the right bank of Guadalén River. It is expected that, in next phases, this methodological approach will allow us to go deeper in analysing and understanding spatial distribution, exploitation, and interrelation between different Early Roman Empire sites, helping us to fill the aforementioned gaps in our understanding of the archaeological continuum in the region reducing time and costs.

Polyhydroxyalcanoates (PHAs) are biodegradable polymers synthesized in cytoplasmic granules in bacteria, such as Cupriavidus necator (Ralstonia eutropha), Alcaligenes latus, Pseudomonas spp., Comamonas spp. and other species. PHAs accumulation occurs in response to stress conditions, i.e. under high carbon and low nitrogen (24:1 ratio). PHA can be synthesized using recombinant microorganisms (provided with the operon phbA/phbB/phbC), escaping the constrains of nutrient request, except addition of high amount of sugar (glucose, lactose, fructose). In this study; E. coli was genetically modified for PHB production in biofermentors. The production of PHA at industrial scale requires a continuous supplementation of fermentable sugars to support the availability of nutrients and to assess the level of the exponential growth phase; since sugars are required either for bacterial growth either for PHA synthesis and energy storage. The biofermentors need to be run in automated system. Sensors are used at many points in fermentators; in the evaluation of parameters: consumption of sugars; cell density; quantification of PHB synthesis. The need of operational control during the fermentation has prompted us to application of three measurements; one unit linked to a Nanodrop to evaluate OD; one linked to a reaction chamber to measure sugars consumed by enzyme based fluorescence detection; and one for bacteria Nile Blue staining and fluorescence intensity reads. The growth of bacteria on three different plant by-products was monitored and PHB production in four days using a banana by-product feed was optimised. These detectors will make possible to exploit the full potential of bioreactors optimizing the time of use and maximizing the number of bacteria synthesizing PHA.

In this work, we report the magnetocaloric effect (MCE) in a quantum dot corresponding to an electron interacting with an antidot, under the effect of an Aharonov-Bohm flux subjected to a parabolic confinement potential. We use the Bogachek and Landman model, which additionally allows the study of quantum dots with Fock-Darwin energy levels for vanishing antidot radius and flux. We find that the Aharonov-Bohm flux (AB-flux) strongly controls the oscillatory behaviour of the MCE, thus acting as a control parameter for the cooling or heating of the magnetocaloric effect. We propose a way to detect AB-flux by measuring temperature differences.

The aim of this article was to assess how the professional competence of PETs (Physical Education Teachers) can predict student satisfaction in high school and student satisfaction with life itself. In line with these aims, this study was completed as a cross-sectional study, which was carried out in a total 890 Physical Education (PE) students. Of the research group, 50.3% were female and 49.7% were male. Age average was 15.49 years old for females (SD 1.79) and 15.00 years old for males (SD 2.00). The data collection instrument was the Intrinsic Satisfaction Classroom Scale and Satisfaction with Life Scale. The results are presented as descriptive statistics, correlations and structural equation modelling analysis, and they show that the competences of the PE teacher determine in great measure student’s satisfaction with school and with their own personal lives.

Landscape changes based on spectral responses allow showing plant cover changes through diversity, composition, and ecological connectivity. The spatial and temporal vegetation dynamics of the Bijagual Massif from 1986 to 2021 were analyzed as a measure of ecological integrity, conservation, and territory. The covers identified were high open forest (Hof), dense grassland of non-wooded mainland (Dgnm), a mosaic of pastures and crops (Mpc), lagoons (Lag), and bare and degraded lands (Bdl). The Bijagual Massif has 8,574.1 ha. In 1986, Dgnm occupied 42.6% of the total area, followed by Mpc (32.8%) and Hof (24.5%); by 2000, Mpc and Hof increased (43.7 and 28.1%, respectively), while Dgnm decreased (28%); by 2021, Dgnm was restricted to the northeastern zone and continued to decrease (25.2%), Mpc occupied 52.9%, Hof 21.7% and Bdl 0.1%. Of the three fractions of the connectivity probability index, only dPCintra and dPCflux contribute to ecological connectivity. Hof and Dgnm show patches with biota habitat quality and availability. Between 1986 and 2021, Dgnm lost 1,489 ha (41%) and Hof 239.5 ha (11%). Mpc replaced various covers (1,722.2 ha; 38%) in 2021. Bijagual has a valuable biodiversity potential limited by Mpc. Territorial planning and sustainable agroecological and ecotourism proposals are required due to the context of the ecosystems.

The purpose of this study is to bring out a scientometric analysis of the advances of digital transformation in the global banking sector. For this, a background search of the term "Digital Transformation Banking " has been brought out from the Web of Science (Wos) Database, covering records published between 2002 and 2023. A set of 312 publications was identified, which mainly includes a set of 264 academic articles, 29 articles published without cataloging a specific volume of a journal, 9 articles under review, 5 editorial material documents, 4 conference articles, and 1 document is a book chapter. Nowadays the scientific production is low but showing growing development presenting 123 publications and 7,754 citations for the year 2022. Among the scientific production, 43 publications from the Republic of China (8.8%) and 35 publications from Ukraine (7.8%) stand out. ,2%). It is also worth mentioning that the most relevant authors on this topic are Ricardo Palomo, professor and dean of San Pablo University, and Robert J Kauffman, professor at Singapore Management University in terms of influence. Main institutions in terms of scientific production, mainly: the Massachusetts Institute of Technology (MIT) of the United States and the Russian Academy of Sciences of Russia.

Autophagy is an essential mechanism to maintain cellular homeostasis. Besides its role in controlling the quality of cytoplasmic components, it participates in nutrient obtaining and lipid mobilization under stressful conditions. Furthermore, autophagy is involved in the regulation of systemic metabolic, a function mainly performed by neuronal populations of the arcuate nucleus of the hypothalamus. Several studies have shown that blockade of autophagy in these neurons can affect central regulation of metabolism and impact body energy balance. Moreover, hypothalamic autophagy can be altered during obesity. However, neurons are not the only cell type involved in the central regulation of metabolism. Astrocytes, essential cells for brain homeostasis, are key metabolic regulators. They can sense metabolic signals in the hypothalamus and modulate systemic functions as glucose homeostasis and feeding response. Moreover, the response of astrocytes to obesity has been widely studied. Astrocytes are important mediators of brain inflammation and can be affected by increased levels of saturated fatty acids associated to obesity. Although autophagy plays important roles for astrocyte homeostasis and functioning, the contribution of astrocyte autophagy to systemic metabolism has not been analysed. Furthermore, how obesity can impact astrocyte autophagy is poorly understood. More studies are needed in other to understand the contribution of astrocyte autophagy to metabolism.

The interaction of the nervous, immune, and endocrine systems is crucial in the maintenance of homeostasis in vertebrates, and vital in mammals. The spleen is a key organ that regulates the neuroimmunoendocrine system. The Taenia crassiceps mouse system is an excellent experimental model to study the complex host-parasite relationship, particularly sex-associated susceptibility to infection. The aim of the present study was to determine the changes in neurotransmitters, cytokines, sex steroids, and sex-steroid receptors in the spleen of cysticercus-infected male and female mice, and the association of these different components with whole parasite counts. We found that parasite load was higher in female in comparison to male mice. The levels of the neurotransmitter epinephrine were significantly decreased in infected male animals. The expression of IL-2 and IL-4 in the spleen was markedly increased in infected mice; however, the expression of Interleukin (IL)-10 and Interferon (IFN)-γ decreased. We also observed sex-associated differences between non-infected and infected mice. Interestingly, the data show that estradiol levels increased in infected males but decreased in females. Our studies provide evidence that infection leads to changes on neuroimmunoendocrine molecules in the spleen during infection. These changes are dimorphic and impact the establishment, growth, and reproduction of T. crassiceps. Our findings support the key role of the neuroimmune network in determining sex-associated susceptibility to the helminth parasite.

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

The nuclear receptor superfamily comprises a large group of proteins with functions essential for cell signaling, survival and proliferation. There are multiple distinctions between nuclear superfamily classes defined by hallmark differences in function, ligand binding, tissue specificity, and DNA binding. In this review, we utilize the initial classification system, which defines subfamilies based on structure and functional difference. The defining feature of the nuclear receptor superfamily is that these proteins function as transcription factors. The loss of transcriptional regulation or gain of functioning of these receptors is a hallmark in numerous diseases. For example, in prostate cancer the androgen receptor is a primary target for current prostate cancer therapies. Targeted cancer therapies for nuclear hormone receptors have been more feasible than others to develop due to ligand availability and cell permeability of hormones. To better target these receptors, it is critical to understand their structural and functional regulation. Given that late-stage cancers often develop hormone insensitivity, we will explore the strengths and pitfalls of targeting other transcription factors outside of the nuclear receptor superfamily such as the signal transducer and activator of transcription (STAT).

The world is facing an energy crisis. Governments are seeking to provide universal energy access and guarantee energy security while trying to mitigate climate change. One possible solution is energy transitions towards low carbon energy systems. Among other things (physical infrastructure, public policy and regulatory enablers and knowledge and capacities) changes in the energy systems require a well informed and participative citizenship. Within this context the concept of energy literacy appears. Energy literacy is the understanding of how energy is generated, transported, stored, distributed and used, awareness about its environmental and social impacts and the knowledge to use it efficiently in the different sectors of the economy. This paper provides a systematic literature review in the Web of Science’s Core Collection. Most of the work done around energy literacy addresses its evaluation among different groups, particularly students at different levels, and the construction, application and evaluation of tools for improving energy literacy. Other frequently studied issues are the influence of energy literacy in decision making, its drivers and conceptual research about the topic. Energy enables citizens to effectively contribute to energy efficiency and sustainable development, nevertheless energy literacy is not strongly correlated to energy consumption habits.

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.

ZnO films with Ti atoms incorporated (TZO) in a wide range (0-18 at. %) have been grown by reactive co-sputtering on silicon and glass substrates. The influence of the titanium incorporation in the ZnO matrix on the structural and optical characteristics of the samples has been determined by Rutherford backscattering spectroscopy (RBS), X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD). The results indicate that the samples with low Ti content (< 4 at. %) exhibit the wurtzite-like structure, with the Ti+4 ions substitutionally incorporated into the ZnO structure, forming Ti-doped ZnO films. In particular, very low concentration of Ti (<0.9 at. %) leads to a significant increase of the crystallinity of the TZO samples. Higher Ti contents give rise to a progressive amorphization of the wurtzite-like structure so samples with high Ti content (≥18at. %), displays an amorphous structure indicating the XPS analysis a predominance of Ti-O-Zn mixed oxides. The energy gap, obtained from absorption spectrophotometry, increases from 3.2 eV for pure ZnO films to 3.6 eV for those with the highest Ti content. Ti incorporation in the ZnO samples below 0.9 at. % rises both, the blue (380 nm) and green (550 nm) bands of the photoluminescence (PL) emission, thereby indicating a significant improvement of PL efficiency of the samples.

The increasing number of registered road crashes involving cyclists during the last decade, and the high proportion of road crashes resulting in severe injuries and fatalities among cyclists constitutes a global issue for community health, urban development, and sustainability. Nowadays, the incidence of many risk factors for road crashes of cyclists remains largely unexplained. Given the importance of this issue, the present study has been conducted with the aim of determining relationships between infrastructural, human factors and safety outcomes of cyclists. Objectives: This study aimed, first, to examine the relationship between key infrastructural and human factors present in cycling, bicycle-user characteristics, and their self-reported experience with road crashes. And second, to determine whether a set of key infrastructural and human factors may predict their self-reported road crashes. Methods: For this cross-sectional study, a total of 1064 cyclists (38.8% women, 61.2% men; M = 32.8 years of age) from 20 different countries across Europe, South America and North America, participated in an online survey composed of four sections: demographic data and cycling-related factors, human factors, perceptions on infrastructural factors, and road crashes suffered. Results: The results of this study showed significant associations between human factors, infrastructural conditions and self-reported road crashes. Also, a logistic regression model found that self-reported road crashes of cyclists could be predicted through variables such as age, riding intensity, risky behaviors, and problematic user/infrastructure interactions. Conclusions: The results of this study suggest that self-reported road crashes of cyclists are influenced by features related to the user and their interaction with infrastructural characteristics of the road.

We compared the performance of matrix-assisted laser desorption/ionization followed by a time of flight (MALDI-TOF) mass spectrometry and genomic DNA extraction followed by sequencing, assembly, and alignment for phylogenetic assessment (Genomics method). We collected the samples from four contaminated rivers in the Dominican Republic and analyzed MALDI-TOF efficacy and accuracy for identifying bacteria in the samples. We evaluated the results for both methods (MALDI-TOF and Genomics) and reported a similarity percentage between each method's results. The MALDI-TOF method had a 72.41\% of coincidence with the Genomics method. This could have been sequence contamination found in the Genomics method. When it was later filtered, the result's coincidence rate went up to 90\%.

The microstructure of the coating during hot-dip galvanizing under industrial conditions of two structural steels, a low-silicon ASTM A36 steel and a high-silicon Q345B steel, both of commercial quality, have been characterized for industrial-relevant times. For both cases it is noted that the formation of the Fe-Zn phases begins in early stages during the heating of the steel, a situation in which all the phases are in the solid state. The characterization was carried out through traditional metallographic techniques including SEM-EDS and DRX equipment. The evolution in time of the microstructure of both steels is examined, being able to observe that the mechanism by which silicon accelerates the formation of Fe-Zn phases in galvanizing is related to the change in the energy of the interfaces caused by a silicon accumulation in the liquid phase in contact with the ζ layer. These results provided us with a deeper understanding of the phase evolution in the hot-dip galvanizing of high silicon steels.

Development of non-conventional hybrids (NCHs) responds to the demand for the Elotes Occidentales 'EO' race for production of pozole. The effect of: crop cycle (2019, 2020 and 2021) on physical characteristics, flowered grain quality and phytochemical content of two HNC (Pz1 and Pz2) of pozolero maize, as well as the effect of the presence or absence of pedicel, type of pollination (open and controlled, 2019), and progenitor lines (female and male, 2020) on flowered grain quality and content of phytochemical compounds were evaluated. Size, hardness, color, total phenols and anthocyanins in unprocessed grain were determined, and yield, volume and puncture strength in flowered grain. Results were analyzed with a factorial arrangement in a completely randomized design. There were significant differences (p≤0.05) in most of the variables studied by effect of crop cycle and genotype. NCHs had large grains (40 g 100 grains-1), soft endosperm (IF&gt; 60), pink-purple color, and phenol and anthocyanin contents similar to those reported for the 'EO' race. The presence or absence of the pedicel did not affect flowered grain quality. Controlled pollination favored anthocyanin synthesis. The anthocyanin content of NCHs was determined by the female line. Thermal processing reduced anthocyanins by 60%; however, they leached into the flowering broth, so that the pozole made from NCHs improves the nutraceutical value of the pozole, relative to that of pozole made with Cacahuacintle maize.

Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common one has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.

Corneal biomechanics is a hot topic in ophthalmology. The biomechanical properties of the cornea (BMPs) have important implications in the management and diagnosis of corneal diseases such as ectasia and keratoconus. In addition, the characterization of BMPs is crucial to model the predictability of a corneal surgery intervention, the outcomes of refractive surgery or follow-up of corneal diseases. The biomechanical behavior of the cornea is governed by viscoelastic properties that allow, among other structural implications, the damping of excess of intraocular pressure and reduce damage to the optic nerve. Currently, the most versatile and complete methods to measure corneal viscoelasticity are based on air-puff corneal applanation. However, those methods lack the ability to directly measure corneal viscosity. The aim of this work is to propose a new methodology based on the analysis of corneal air-puff measurements through the Standard Linear Solid model (SLSM) to provide analytical expressions to separately calculate the elastic and time-dependent (corneal retardation time and viscosity) properties. The results shown the mean values of elasticity (E), viscosity (Ƞ) and corneal retardation time (τ) in a sample of 200 young and healthy subjects. The influence of elasticity and viscosity on viscoelasticity, high-order corneal aberrations and optical transparency is investigated. Finally, the SLSM fed back from experimental E and Ƞ values was employed to compare the creep-relaxation response between normal, an ocular hypertension patient and Ortho-K user.

Electrical rotating machines like Induction Motors (IMs) are widely used in several industrial applications since their robust elements, provide high efficiency and give versatility in industrial applications. Nevertheless, the occurrence of faults in IMs is inherent to their operating conditions, hence, Inter-turn short-circuit (ITSC) is one of the most common failures that affect IMs and its appearance is due to electrical stresses leads to the degradation of the stator winding insulation. In this regard, this work proposes a diagnosis methodology for the assessment and detection of incipient ITSC in IMs, the proposed method is based on the processing of vibration, stator currents and magnetic stray-flux signals. Certainly, the novelty and contribution include the characterization of different physical magnitudes by estimating a set of statistical time domain features, as well as, their fusion and reduction through the Linear discriminant Analysis technique within a feature-level fusion approach. Furthermore, the fusion and reduction of information from different physical magnitudes leads to perform the automatic fault detection and identification by a simple Neural-Network (NN) structure. The proposed method is evaluated under a complete set of experimental data and the obtained results demonstrate that the fusion of information from different sources (physical magnitudes) allows to improve the accuracy during the detection of ITSC in IMs , the results make this proposal feasible to be incorporated as a part of condition-based maintenance programs in the industry.

This work is mainly focused on improving the differential evolution algorithm with the utilization of shadowed and general type 2 fuzzy systems to dynamically adapt one of the parameters of the evolutionary method. In this case, the mutation parameter is dynamically moved during the evolution process by using a shadowed and general type-2 fuzzy systems. The main idea of this work is to make a performance comparison between using shadowed and general type 2 fuzzy systems as controllers of the mutation parameter in differential evolution. The performance is compared with the problem of optimizing fuzzy controllers for a D.C. Motor. Simulation results show that general type-2 fuzzy systems are better when higher levels of noise are considered in the controller.

There is a disproportionate increase in the incidence of diet-related cardiometabolic disorders in racial and ethnic minority groups. This systematic review examines the extent to which diet-induced changes in health outcomes have been discussed by race or ethnicity in randomized controlled trials recruiting both minority and non-Hispanic White groups. Databases i.e. PubMed, Cochrane library and Web of Science were searched up to November 2019. Studies that discussed effects of defined dietary interventions on health outcomes by racial or ethnic minority group vs. non-Hispanic Whites (n=29) were included in the review. Most studies were conducted in Black vs. White people testing effects of energy restriction, macronutrient modification, sodium reduction, or variations of the Dietary Approaches to Stop Hypertension (DASH) diet on cardiometabolic outcomes. There was limited focus on other minority groups. Evidence suggests greater blood pressure reduction for Black people compared to Whites particularly on DASH (or similar) diets. Overall, there was limited consideration for group-specific eating patterns and diet acceptability in most studies. Adequately powered studies are needed for accurate interpretation of race by diet effects. With emerging precision nutrition initiatives, it is imperative to ensure adequate representation of racial and ethnic subgroups for addressing nutrition-related health disparities.

Introduction: Individuals with gout are at higher risk of developing chronic conditions, such as diabetes, chronic kidney disease (CKD), and cardiovascular diseases. In this study, the association between urate-lowering therapy (ULT) use and the prevalence of these conditions was evaluated. Methods: This observational, cross-sectional pharmacoepidemiologic study used the 2013-2018 biannual cycles of the National Health and Nutrition Examination Survey. The inclusion criteria were adults 30 years of age and older with a diagnosis of gout. The association between ULT treatment status and dyslipidemia, coronary heart disease, heart failure, hypertension, and chronic kidney disease was evaluated, as well as associations with select clinical laboratory biomarkers. Results: Use of ULT was 28.9% (95%CI 24.3%-33.9%). There was no significant association between ULT use and the prevalence of heart failure, coronary heart disease, hypertension, or dyslipidemia (p>0.05). Those on ULT had a lower mean eGFR compared to those not on treatment (68.03 versus 74.74 mL/min/1.73m², p=0.014). LDL- and HDL- and total cholesterol were significantly lower among those receiving ULT treatment (p<0.05). Conclusion: ULT use continues to be low among those with gout. Those on ULT were more likely to be diagnosed with CKD, college graduates and above, older males, and obese. Clinical guidelines conditionally recommend ULTs in co-morbid kidney disease; while our results may reflect guidelines recommendation for ULT use in CKD patients, worsening kidney function while taking ULT is unlikely. Further research is necessary to determine the long-term impact of ULTs on kidney function and cardiovascular biomarkers.

Tissue inhibitors of metalloproteinases (TIMPs) are essential players during tumor progression in various types of cancer, including breast cancer. TIMPs regulate the activity of matrix metallo-proteinases (MMPs) at different levels. However, a dual role for TIMPs in breast carcinogenesis, either promoting or inhibiting tumor progression, has been observed. By a comprehensive bioin-formatics analysis using different databases, we report that of the four TIMPs, only TIMP-1 is overexpressed in tumor breast tissue. However, TIMP-2, TIMP-3, and especially TIMP-4 present lower levels in breast tumor tissue than in normal tissue. Interestingly, high levels of TIMP-1 are associated with shorter survival in breast cancer patients. In contrast, low TIMP-2, TIMP-3, and TIMP-4 levels are associated with poor survival. Function enrichment analysis showed that TIMP-3 has the highest interactions with its target proteins and a higher number of processes re-lated to mammary carcinogenesis. We found differential expression of TIMP-1 concerning TIMP-3 and TIMP-4 in breast cancer and normal tissue. TIMP-4 has a significant relationship with cancer staging, including tumor size, lymph node spread, and metastasis. The correlation between immune cell infiltrates and TIMP expression is of great importance as they provide in-formation on breast cancer diagnosis, prognosis, progression, and response to treatment.

The current study aims to develop a methodology for obtaining topology-optimal structures made of short fiber-reinforced polymers, which include the fluid-structure interaction. Accounting for the molding process during the internal iterations of topology optimization makes it possible to enhance the weight efficiency of structures—a crucial aspect, especially in aerospace. Anisotropy is considered through the fiber orientation tensor, which is modeled by solving the plastic molding equations for non-Newtonian fluids, and then introduced as a variable of the stiffness matrix during the structural analysis. The materials used were non-linearly modeled using an exponential-and-linear hardening law. The evaluation of weight efficiency in structures composed of short-reinforced composite materials using a dimensionless criterion is addressed. Experimental verification was performed to confirm the validity of the developed methodology. The evidence illustrates that considering anisotropy leads to stiffer structures and structural elements should be oriented in the direction of maximal stiffness. The load-carrying factor can be expressed in terms of failure criteria. The presented multidisciplinary methodology can be used to improve the quality of the design of structures made of short fiber-reinforced composites (SFRC) where high stiffness, high strength, and minimum mass are the primary required structural characteristics.

Based on recent contributions regarding the treatment of unsteady hydraulic conditions into the state-of-the-art of scour literature, the theoretically derived probability distribution of bridge scour is introduced. The model is derived assuming a rectangular hydrograph shape with a given duration, and random flood peak following a Gumbel distribution. A model extension for a more complex flood event is also presented, assuming a synthetic exponential hydrograph shape. The mathematical formulation can be extended to any flood-peak probability distribution. The aim of the manuscript is to move forward the current approaches adopted for the bridge design coupling hydrological, hydraulic, and erosional models in a mathematical closed form.

’Lockdown’ periods in response to COVID-19 have provided a unique opportunity to study the impacts of economic activity on environmental pollution (e.g. NO2, aerosols, noise, light). The effects on NO2 and aerosols have been very noticeable and readily demonstrated, but that on light pollution has proven challenging to determine. The main reason for this difficulty is that the primary source of nighttime satellite imagery of the earth is the SNPP-VIIRS/DNB instrument, which acquires data late at night after most human nocturnal activity has already occurred and much associated lighting has been turned off. Here, to analyze the effect of lockdown on urban light emissions, we use ground and satellite data for Granada, Spain, during the COVID-19 induced confinement of the city’s population from March 14 until May 31, 2020. We find a clear decrease in light pollution due both to a decrease in light emissions from the city and to a decrease in anthropogenic aerosol content in the atmosphere which resulted in less light being scattered. A clear correlation between the abundance of PM10 particles and sky brightness is observed, such that the more polluted the atmosphere the brighter the urban night sky. An empirical expression is determined that relates PM10 particle abundance and sky brightness at three different wavelength bands.

Millions of people worldwide have an inadequate intake of selenium (Se) and zinc (Zn), and agronomic biofortification may minimise these problems. To evaluate the efficacy of combined foliar Se and Zn fertilisation in bread making wheat (Triticum aestivum L.), foliar Se (as NaSeO4) and soil and foliar Zn applications (as ZnSO4·7H2O) were tested individually and in all combinations. A 2-year field experiment was established in southern Spain under semiarid Mediterranean conditions, by following a split-split-plot design. The study year (2017/2018, 2018/2019) was considered as the main-plot factor, soil Zn application (50 kg Zn ha-1, nil Zn) as a subplot factor, and foliar application (nil, 10 g Se ha-1, 8 kg Zn ha-1, 10 g Se ha-1 + 8 kg Zn ha-1) as a sub-subplot factor. The best treatment to increase both Zn and Se concentration in both straw, 12.3- and 2.7-fold respectively, and grain, 1.2- and 4.1-fold respectively was the combined foliar application of Zn and Se. This combined Zn and Se application also increased on average the yield of grain, main product of this crop, by almost 26%. Therefore, bread-making wheat seems to be a very suitable crop to be used in biofortification programs with Zn and Se to alleviate their deficiency in both, people when using its grain and livestock when using its straw.

This article focuses on generating an alternative in order to identify traffic officers during driving. This research employed the latest You Only Look Once (YOLO) model, using a six-phase methodology: data collection, data preparation involving resizing and labeling, implementation of various filters to avoid overfitting, model training, prediction evaluation, and result interpretation. The YOLO model was applied across three iterations using a dataset of 1862 images. To enhance training efficiency and detection speed, the graphics processing unit (GPU) acceleration was utilized, further enhancing the experimental process. The results of this study revealed that the YOLOv8x variant produced the most promising results. This proposed model attained a remarkable F1 score of 0.95, bolstered by a confidence score of 0.631, with the potential for an increase to 0.80 in confidence without significantly compromising the F1-score. These findings are poised to make a substantial contribution to the broader research landscape, particularly in advancing the effectiveness of detection models for traffic officers.

Trichomonas vaginalis is an extracellular parasite protozoan that causes human trichomoniasis, a sexually transmitted infection (STI) that affects approximately 200 million people worldwide. The presence of T. vaginalis adhesion to inert substrates has been described in several reports. Still, very few studies on cluster formation and more detailed analyses of the contact regions between the membranes of the parasites in these aggregate formations have not been carried out. We analyzed the formation of parasite monolayers and clusters using high-resolution scanning electron microscopy, transmission electron microscopy, cytochemistry, TEM tomography, and dye injection. Here, we show the formation of a monolayer of tightly adherent cells, epithelium-like, when the parasites are in contact with an inert material. Based on this observation, we analyzed whether this monolayer behaves as an epithelium, analyzing cell junctions, cell communication, and ultrastructural aspects. We also analyzed the cluster formation and the morphological characteristics of parasite aggregation observed in the culture supernatant. We report that monolayer formation differs from cluster formation in many aspects. The monolayers form strong adhesion, whereas the clusters have fragile attachments. There is no fusion or passage of molecules between neighbor-attached cells; there is no need for different strains to form filopodia, cytonemes, and extracellular vesicles during cluster formation.

An exploding demand for processing capabilities related to the emergence of the IoT, AI and big data, has led to the quest for increasingly efficient ways to expeditiously process the rapidly increasing amount of data. These ways include different approaches like improved devices capable of going further in the more Moore path, but also new devices and architectures capable of going beyond Moore and getting more than Moore. Among the solutions being proposed, Stochastic Computing has positioned itself as a very reasonable alternative for low-power, low-area, low-speed, and adjustable precision calculations; four key-points beneficial to edge computing. On the other hand, chaotic circuits and systems appear to be an attractive solution for (low-power, green) secure data transmission in the frame of edge computing and IoT in general. Classical implementations of this class of circuits require intensive and precise calculations. This paper discusses the use of the SC framework for the implementation of nonlinear systems, showing that it can provide results comparable to those of classical integration, with much simpler hardware, paving the way for relevant applications.

: In Chile, most tailings impoundments are in Northern and Central Chile, 20% of them are abandoned. Municipal budgets to manage these environmental liabilities are very limited and the use of native and endemic plant species to remove heavy metals from tailings is a low-cost alternative. Ex-situ phytoremediation experiments were conducted over seven months to evaluate the potential of Lycium chilense and Haplopappus foliosus to remove copper and lead from mine tailings. The results indicate that both species can concentrate high levels of both elements and they present removal efficiencies for Cu close to 50%. The best performance was presented by Haplopappus foliosus, accumulating higher concentrations of both metals than Lycium chilense. Also, it presents a bioconcentration over 1.

This research explored the influence of spatiotemporal variations in phreatic levels and salinity on the patterns and interactions of soil mesofauna communities in a tropical urban coastal wetland. It delineated significant variations in phreatic levels and salinity, with distinct regimes characterizing different habitats and hydroperiods. A total of 120 mesofauna morphotypes across 42 taxa were identified, revealing habitat differences and similarities, and the ecosystem biodiversity. Moderate correlations were established between phreatic levels, salinity, and mesofauna richness and abundance, with habitat type and phreatic level emerging as significant predictors in the regression model. Our findings indicate that shallow phreatic levels in conjunction with oligohaline salinity conditions foster a more favorable abiotic environment, thereby promoting increased biodiversity. The study underscores the dynamic and adaptive nature of mesofauna communities in response to changing environmental conditions, offering valuable insights for effective costal urban wetland management, particularly in the context of multiple stressors such as global and regional climate change, sea level rise, and human activities. The bio-sensor capacity of soil mesofauna emerges as a vital tool for monitoring and facilitating adaptive ecosystem management, thereby ensuring their long-term health and sustainability.

In this work, we report the magnetocaloric effect (MCE) in two systems of non-interactive particles, the first corresponds to the Landau problem case and the second, the case of an electron in a quantum dot subjected to a parabolic confinement potential. In the first scenario, we realize that the effect is totally different from what happens when the degeneration of a single electron confined in a magnetic field is not taken into account. In particular, when the degeneracy of the system is negligible, the magnetocaloric effect cools the system, while in the other case, when the degeneracy is strong, the system heats up. For the second case, we study the competition between the characteristic frequency of the potential trap and the cyclotron frequency to find the optimal region that maximizes the ΔT of the magnetocaloric effect, and due to the strong degeneration of this problem, the results are in coherence with those obtained for the Landau problem. Finally, we consider the case of a transition from a normal MCE to an inverse one and back to normal as a function of temperature. This is due to the competition between the diamagnetic and paramagnetic response when the electron spin in the formulation is included.

Androgen receptor signaling is crucial for prostate cancer growth and is positively regulated in part by intratumoral CYP3A5. As African American (AA) men often carry the wild type CYP3A5 and express high level of CYP3A5 protein, we blocked the wild type CYP3A5 in AA origin prostate cancer cells and tested its effect on androgen receptor signaling. q-PCR based profiler assay identified several AR regulated genes known to regulate AR nuclear translocation, cell cycle progression and cell growth. CYP3A5 processes several commonly prescribed drugs and many of these are CYP3A5 inducers or inhibitors. In this study, we test the effect of these commonly prescribed CYP3A5 inducers/inhibitors on AR signaling. The results show that the CYP3A5 inducers promoted AR nuclear translocation, downstream signaling and cell growth whereas CYP3A5 inhibitors abrogated them. The observed changes in AR activity is specific to alterations in CYP3A5 activity. Both the inducers tested demonstrated increased cell growth of prostate cancer cells, whereas the inhibitors showed reduced cell growth. Further, characterization and utilization of the observation that CYP3A5 inducers and inhibitors alter AR signaling may provide guidance to physicians prescribing CYP3A5 modulating drugs to treat comorbidities in elderly patients undergoing ADT, particularly AA.

Dendroclimatology has gained relevance during the XXI century. We analyze the state of-the-art of dendroclimatology in Latin America during the past 28 years (1990 to 2019), identifying the current state and recent advances in the application of dendroclimatology in this region. We carried out a systematic review in ScienceDirect, Web of Science, and Scopus databases using Boolean operators to logically connect the keywords “dendrochronology,” “dendroclimatology,” “trend,” “climatic variability,” and “climatic variability trend”, for each country. Dendroclimatological research conducted in the region focused on climatic reconstruction and the evaluation of new tree species with dendrochronological potential, which increase in 2010, then there was a gap between 1995 and 1996, later increase to present. Dendroclimatological studies in Latin America have been mainly developed in temperate climate zones (82.4 %) followed by tropical or subtropical areas (17.6 %). Dendroclimatological research in Latin America has provided advances in the study of climate variability by defining response functions of tree rings to climate. The generated information allows for a better understanding of the spatial and temporal dynamics of climatic variability and about its effects on ecosystems and society. We also call for increased dendroclimatological research based on subtropical and tropical forests limited studied until today.

This study proposes a methodology for identifying time intervals in which time-of-use (ToU) energy tariffs can be set. This is achieved by analyzing the variability in electric power demand and esti-mating the potential for demand flexibility. The proposed methodology is as follows: first, data preprocessing is performed, focusing on the organization and cleaning of individual consumption records. Subsequently, the data are processed and classified by using consumption variability analysis and clustering techniques. Then, representative clusters are selected and time intervals are analyzed to identify periods of high electric power consumption variability. This methodology was tested with real data from smart meters in the Colombian electrical system, in which time intervals with potential for settinh ToU tariffs were ultimately identified. This work promotes the implementation of demand response strategies that enhance sustainability and facilitate the transition to a more resilient energy landscape both nationally and internationally. The findings are expected to contribute to the formulation of tariff schemes that encourage con-scious changes in electric energy consumption patterns.

This study introduces an innovative optimization method to identify the optimal configuration of a sparse symmetric 2D array for applications in security, particularly multistatic imaging. Utilizing Genetic Algorithms (GA) in a sophisticated optimization process, the research focuses on achieving the most favorable antenna distribution while mitigating the common issue of secondary lobes in sparse arrays. The main objective is to determine the ideal configuration from specific design parameters, including hardware specifications such as number of radiating elements, minimum spacing, operating frequency range, and image separation distance. The study employs a cost function based on the the point spread function (PSF), the system response to a point source, with the goal of minimizing the secondary lobe levels and maximizing their separation from the main lobe. Advanced simulation algorithms based on Physical Optics (PO) are used to validate the presented methodology and results.

Condition monitoring of bearings is an open issue. The use of the stator current to monitor induction motors has been validated as a very advantageous and practical way to detect several types of faults. Nevertheless, for bearing faults the use of vibrations or sound generally offers better results in the accuracy of the detection although with some disadvantages related to the sensors used for monitoring. To improve the performance of bearing monitoring, it is proposed to take advantage of more information available in the current spectra, beyond the usually employed, incorporating the amplitude of a significant number of sidebands around the first eleven harmonics, growing exponentially the number of fault signatures. This is especially interesting for inverter-fed motors. But, in turn, this leads to the problem of overfitting when applying a classifier to perform the fault diagnosis. To overcome this problem, and still exploit all the useful information available in the spectra, it is proposed to use shrinkage methods, which have been lately proposed in machine learning to solve the overfitting issue when the problem has much more variables than examples to classify. A case study with a motor is shown to prove the validity of the proposal

One of the most important defining characteristics of groundwater quality is pH as it fundamentally controls the amount and chemical form of many organic and inorganic solutes in groundwater. Groundwater data are frequently characterized by a wide degree of variability of the factors which possibly influence pH distribution. For this reason, it is challenging to link the spatio-temporal dynamics of pH to a single environmental factor by the ordinary least squares regression technique of the conditional mean. In this study, quantile regression was used to estimate the response of pH to nine environmental factors (As, Cd, Fe, Mn, Pb, turbidity, electrical conductivity, total dissolved solids and nitrates). Results of 25%, 50%, 75% quantile regression and ordinary least squares (OLS) regression were compared. The standard regression of the conditional means (OLS) underestimated the rates of change of pH due to the selected factors in comparison with the regression quantiles. The effect of arsenic increased for sampling locations with higher pH values (higher quantiles) likewise the influence of Pb and Mn. However, the effects of Cd and Fe decreased for sampling locations in higher quantiles. It can be concluded that these detected heterogeneities would be missed if this study had focused exclusively on the conditional means of the pH values. Consequently, quantile regression provides a more comprehensive account of possible spatio-temporal relationships between environmental covariates in groundwater. This study is one of the first to apply this technique on groundwater systems in sub-Saharan Africa. The approach is useful and interesting and has broad application for other mining environments especially tropical low-income countries where climatic conditions can drive rapid cycling or transformations of pollutants. It is also pertinent to geopolitical contexts where regulatory; monitoring and management capacities are weak and where mining pollution of groundwater largely occur.

This research presents a novel algorithmic implementation to improve the analysis of visually controlled interception and accompanying motor action through the computational application of harmonic ratios and stimulation invariants. Unlike traditional models that focus mainly on psychological aspects, our approach integrates the relevant constructs into a practical mathematical framework. This allows for dynamic prediction of interception points with improved accuracy and real-time perception-action capabilities, essential for applications in neurorehabilitation and virtual reality. Our methodology uses stimulation invariants as key parameters within a mathematical model to quantitatively predict and improve interception outcomes. The results demonstrate the superior performance of our algorithms over conventional methods, confirming their potential for ad-vancing robotic vision systems and adaptive virtual environments. By translating complex theo-ries of visual perception into algorithmic solutions, this study provides innovative ways to im-prove motion perception and interactive systems. This study aims to articulate the complex inter-play of geometry, perception, and technology in understanding and utilizing cross-ratios at infin-ity, emphasizing their practical applications in virtual and augmented reality settings.

Background: COVID-19 made its debut as a pandemic in 2020; since then, more than 607 million cases and at least 6.5 million deaths have been reported worldwide. While the burden of disease has been described, the long-term effects or chronic sequelae are still being described. Objective: To describe the findings of a current systematic review of the long-term effects related to post-COVID-19 sequelae. Design: A systematic review was carried out in which cohort studies, case series, clinical case reports were included, and the PubMed, Scielo, SCOPUS and Web of Science databases were ex-tracted. Information published 2020 to June 1, 2022, was sought. Results: We reviewed 300 manuscripts during the first step of the literature review process. Then 260 abstracts were analyzed. In the end, we included 32 manuscripts: 9 for pulmonary, 6 for cardiac, 2 for renal, 9 for neurological and psychiatric, and 8 for cutaneous sequelae. Conclusion: Studies show that the most common sequelae are those linked to the lungs, followed by skin, cutaneous and psychiatric alterations. Women report a higher incidence of the sequelae, as well as those with comorbidities and severer COVID-19 history. The COVID-19 pandemic has not only caused death and disease since its apparition but has also sickened millions of people around the globe who potentially suffer from serious illnesses that will continue to add to the list of health problems and further burden healthcare systems around the world.

The growing awareness of the biological effects of artificial light on humans has stimulated ample research. It is now widely accepted that asynchrony between artificialand natural light-dark cycles can elicit severe detrimental health effects. New research has been devoted to lighting solutions that dynamically change their color to mimic spectral changes of daylight and to account for human needs. However, in some situations, the visual properties of light must be preserved: For example professional TV video editors and shift workers who must work under standardized lighting conditions to do color correction in post-production. We have investigated the possibility to tune circadian effects using white lights that are spectrally different but nonetheless have similar color coordinates thus appear as a similar white tone. Our simulation results indicate that it is possible to modulate circadian light effects by combining LEDs for neutral white (4000 K), a widely used white tone for indoor lighting in europe. The results also show that the solutions combining single-color LEDs do however not meet the quality criteria from the visual point of view because their color rendering ability decays to unacceptable low levels. Combining narrowband LEDs with a broadband white LED improves the color rendering quality and we show how far circadian light effects can be tuned according to common theoretical models. The aim is to reflect daylight situations with artificial lighting, thus having a high melatonin suppression in the morning and low melatonin suppression in the evening. As a consequence our aim is to show what maximum and minimum circadian effect is possible with the same set of LEDs.

Knowledge of water availability in terms of spatial (i.e., depth) and temporal variability of soil water is essential to describe soil water infiltration and storage processes accurately. Therefore, performing simulations of soil water dynamics can be a valuable tool to evaluate different land uses and their impact on water availability. Consequently, this study aimed to model the volumetric soil water content (θ, cm3 cm-3) under agroforestry systems (AFS) with cocoa. For this purpose, the θ was monitored at different depths (0-20, 20-40, 40-60, 60-80, 80-100 cm) in the soil profile of four plots (20 × 50 m) of cocoa under agroforestry systems. Environmental conditions significantly influenced the water balance of the cocoa crop. There were seven moments when evapotranspiration (ET0) was higher than 5 mm d-1. During those moments, the environment exhibited higher PAR values of 1041 µmol m-2 s-1, very low atmospheric relative humidity (RHa) levels (around 45%), higher ambient temperatures of 32.2 ºC and a vapor pressure deficit of 1.6 kPa whose θ levels reached 0.32 cm3 cm-3 and a water balance of -5.7 mm, which presented negative values during most of the study period. The θ obtained from the HYDRUS-1D model presented a slight bias as a high level of coherence between the observed values, based on the model's goodness-of-fit estimators. The above provides accurate simulations of soil water content at various depths, much-needed information for management schemes for cocoa cultivation under agroforestry systems.

This review delves into the significance of chemical communication in mammals, with an emphasis on the role of the vomeronasal system in sensing pheromone-mediated interactions. The vomeronasal system shapes a variety of social and sexual behaviors, including reproduction, hierarchy formation, maternal bonding, and species recognition. Intriguingly, this system presents a vast degree of evolutionary variability, more so than variations observed in the olfactory system. This adaptive diversity underscores the challenges in studying the vomeronasal system, emphasizing the need for detailed research into its neuroanatomy and functional morphology. This review traverses an array of topics central to our understanding of chemical communication in mammals. We begin with the foundational role and basic concepts of chemocommunication. This is followed by an in-depth exploration of the olfactory systems. Subsequently, the neuroanatomical underpinnings of the vomeronasal system are juxtaposed against those of the olfactory system. Our focus then shifts to an exhaustive study of the sensory element of the vomeronasal system, the vomeronasal organ, and the integrating center of this information, the accessory olfactory bulb. The discussion extends to secondary projections of both the olfactory and vomeronasal systems in the light of the dual olfactory hypothesis. The review culminates with a detailed look at four specific models of vomeronasal system organization belonging to four evolutionarily distinct mammalian families: rodents, marsupials, herpestids, and bovids. These have been meticulously analyzed by the authors, aiming to spotlight the significant morphofunctional differences stemming from the adaptive changes imprinted on the system.

Today, air quality is one of the global concerns that governments are facing. One of the main air pollutants is the particulate matter (PM) that affects human health. This article presents the modeling of a purification system by means of negative air ions (NAIs) for air pollutant removal, using computational intelligence methods. The system uses a high voltage booster output to ionize air molecules from stainless steel electrodes; its particle-capturing efficiency reaches up to 97%. With two devices (5 x 2 x 2.5 cm), 2 trillion negative ions are produced per second, and the particulate matter (PM 2.5) can be reduced from 999 to 0 mg / m3 in a period of approximately 5 to 7 minutes (in a 40 x 40 x 40 cm acrylic chamber). This negative ion generator is a viable and sustainable alternative to reduce polluting emissions, with beneficial effects on human health.

The evolutionary success of land plants largely relies on their ability to cope with constant environmental fluctuations, which negatively impact their reproductive fitness and trigger adaptational responses to biotic and abiotic stresses. In this challenging scenario, comprehensive research efforts so far aimed at depicting the roles of well-known phytohormones, mainly auxins, along with brassinosteroids, jasmonates, and abscisic acid, although the signaling networks coordinating the crosstalk among them remains vaguely understood. Accordingly, this review focuses on the Arabidopsis Amidase Signature (AS) superfamily members, highlighting the hitherto relatively underappreciated functions of AMIDASE1 (AMI1) and FATTY ACID AMIDE HYDROLASE (FAAH), as crucial coordinators of the growth-defense response trade-off by modulating auxin and ABA homeostasis.

In August 2020, the World Health Assembly launched a global initiative to eliminate cervical cancer by 2030, setting three primary targets. One key goal is to achieve a 70% screening coverage rate for cervical cancer, primarily relying on the precise analysis of Papanicolaou (Pap) or digital Pap smears. However, the responsibility of reviewing Pap smear samples to identify potentially cancerous cells primarily falls on pathologists, a task known to be exceptionally challenging and time-consuming. This paper proposes a solution to address the shortage of pathologists for cervical cancer screening. It leverages the OpenAI-GYM API to create a deep reinforcement learning environment utilizing liquid-based Pap smear images. By employing the Proximal Policy Optimization algorithm, autonomous agents navigate Pap smear images, identifying cells with the aid of rewards, penalties, and accumulated experiences. Furthermore, the use of a pre-trained convolutional neuronal network like Res-Net54 enhances the classification of detected cells based on their potential for malignancy. The ultimate goal of this study is to develop a highly efficient, automated Papanicolaou analysis system, ultimately reducing the need for human intervention in regions with limited pathologists.

Three-dimensional matrices are a new strategy used to tackle type I diabetes; a chronic metabolic disease characterized by the destruction of beta pancreatic cells. Type I collagen is an abundant extracellular matrix (ECM), component that has been used to support cell growth. However, pure collagen possesses some difficulties including low stiffness and strength, and high susceptibility to cell-mediated contraction. Therefore, we developed a collagen hydrogel with a poly(ethylene glycol) diacrylate (PEGDA) interpenetrating network (IPN), functionalized with vascular endothelial growth factor (VEGF) to mimic the pancreatic environment for the sustenance of beta-pancreatic cells. We analyzed the physicochemical characteristic of the hydrogels and found that they were successfully synthesized. The mechanical behavior of the hydrogels improved with the addition of VEGF, and the swelling degree and the degradation were stable over time. In addition, it was found that 5 ng/mL VEGF-functionalized collagen/PEGDA IPN hydrogels sustained and enhanced viability, proliferation, respiratory capacity and functionality of beta pancreatic cells. Hence, this is a potential candidate for future preclinical evaluation, which may be favorable for diabetes treatment.

Developed countries have shown a time trend towards a younger age at menarche (AAM), which is associated with increased risk of later obesity and non-communicable diseases. We aimed to assess whether a time trend in AAM with associated disease risk is also present in Mexico. For this, we used data of 30,826 women from the Mexican National Health Survey (2000). Linear and log binomial regression was used for nutritional and disease outcomes, whereas Welch-ANOVA was used to test for a time trend. AAM decreased over time (p < 0.001), with a maximal difference of 0.99 years between the 1920s (13.6 years) and 1980s (12.6 years). AAM (in years) was negatively associated with weight (β = -1.01 kg; 95 % CI -1.006, -1,004) and BMI (β = -1.01 kg/m2; -1.007, -1.006), and positively with height (β = 0.18 cm; 0.112, 0.231). AAM was associated with diabetes (RR = 0.95; 0.93, 0.98) and hypercholesterolemia (RR = 0.93; 0.90, 0.95), but not with hypertension, breast cancer or arthritis. In Mexico, AAM decreased significantly during the 20th century. AAM was inversely associated with adult weight and BMI, and positively with height. Women with a later AAM had a lower risk of diabetes and hypercholesterolemia.

Wildlife monitoring can be time-consuming and expensive, but the fast-developing technologies of uncrewed aerial vehicles, sensors, and machine learning pave the way for automated monitoring. In this study we trained YOLOv5 neural networks to detect Points of Interest, hare (Lepus europaeus), and roe deer (Capreolus capreolus) in thermal aerial footage and proposed a method to manually assess the parameter mean average precision (mAP), compared to the number of actual false positive and false negative detections in a subsample. This showed that a mAP close to 1 for a trained model does not necessarily mean perfect detection and provided a method to gain insights into the parameters affecting the trained models' precision. Furthermore, we provided a basic, conceptual algorithm for implementing real-time object detection in uncrewed aircraft systems equipped with thermal sensors, with high zoom capabilities, and a laser rangefinder. Real-time object detection is becoming an invaluable complementary tool for the monitoring of cryptic and nocturnal animals with the use of thermal sensors.

Breast cancer (BC) is the most common malignancy and the second cause of cancer specific death in women from high-income countries. More than 70% of all breast cancer are hormone receptor-positive BC, and elevated estrogen circulating in blood has been proved to be a strong risk for BC development. This is due to its contribution to enhance proliferation of cancerous cells, angiogenesis and metastasis stimulation and therapy resistance. The estrogen (E) metabolism–gut microbiome axis is functional with underlying individual variations in E levels. It is reasonable that the estrobolome (bacterial genes whose products are capable of metabolizing E) could contribute to the risk of hormone-driven malignancies including BC and may serve as a potential biomarker and target. Gut microbial β -glucuronidase (GUS) enzymes have been suggested to be involved in the estrobolome. Furthermore, bacterial GUS enzymes within the gastrointestinal tract have been postulated to contribute to hormone breast cancer. In this review, we discuss the recent knowledge about the role of GUS enzyme in the pathogenesis of breast cancer. We focus on the role of GUS in (i)-the microbioma and estrogen metabolism, (ii) diet, estrobolome, and the BC development, (iii) other activities of the bacterial β-glucuronidase, and (iv) the new molecular target for BC therapeutic application.

There is an increasing pressure by community and customers forcing companies to insert environmental concerns in their practices. To help companies initiatives, the green bonds market was incepted. Our research question is how to select bonds in a growing billion-dollar market. This paper presents a multi-criteria decision analysis (MCDA) model to enable investors identify opportunities based not only in opinions, but grounded on objective facts. Analytic Hierarchy Process (AHP) and Complex Proportional Assessment (COPRAS) are two MCDA methods applied in this paper. Top-fifteen green bonds ranked by specialized media were assessed with the proposed MCDA model. Criteria included the Environmental Performance Index (EPI) proposed by Yale University, and common financial indicators as assets, risks (β), and dividends. The new AHP–COPRAS rank is compared with another published by specialized media.

Alternative splicing (AS) is a gene regulatory mechanism modulating gene expression in multiple ways. AS is prevalent in all eukaryotes including plants. AS generates two or more mRNAs from the precursor mRNA (pre-mRNA) to regulate transcriptome complexity and proteome diversity. Advances in next-generation sequencing, omics technology and bioinformatics tools, and computational methods provide new opportunities to quantify and visualize AS-based quantitative trait variation associated with plant growth, development, reproduction, and stress tolerance. Domestication, polyploidization and environmental perturbation may evolve novel splicing variants associated with agronomically beneficial traits. To date, pre-mRNAs from many genes are spliced into multiple transcripts that cause phenotypic variation for complex traits, both in model plant Arabidopsis and field crops. Cataloguing and exploiting such variation may provide new paths to enhance climate resilience, resource-use efficiency, productivity, and nutritional quality of staple food crops. This review provides insights into AS variation alongside gene expression analysis to select for novel phenotypic diversity for use in breeding programs. AS contributes to heterosis, enhances plant symbiosis (mycorrhiza and rhizobium), and provides a mechanistic link between the core clock genes and diverse environmental clues.

Inherited retinal dystrophies (IRDs) are a global problem that is largely unaddressed, especially in Africa. Black indigenous Africans are rarely represented in research that develop genetic tests and genetic therapies for IRDs yet their genomes are more diverse. The aim of this literature review is to synthesize information on the IRD genetic research conducted among indigenous black Africans to identify challenges and opportunities for progress. PubMed was searched to identify empirical publications reporting the genetic analysis of IRDs among indigenous Africans. A total of 10 articles were selected for the review. Based on the information in the articles, the main genetic testing methods in use include next-generation, whole exome, and Sanger sequencing. The main IRDs characterized by the genetic tests include retinitis pigmentosa, Leber Congenital Amaurosis, Stagardt disease, and cone dystrophy. Examples of implicated genes include MERTK, GUCY2D, ABCA4, and KCNV2 for the four IRDs respectively. Research activities on the genetics of IRDs are generally scanty in Africa. Even in South Africa and North Africa where some research activities were noted, only a few indigenous black Africans were in the study cohorts. There is an urgent need for genetic research on IRDs, especially in East, Central, and West Africa.

Mine waste rock and drainage pose lasting environmental, social, and economic threats to the mining industry, regulatory agencies, and society as a whole. Mine drainage can be alkaline, neutral, moderately or extremely acidic and contains significant levels of sulfate, dissolved iron, and frequently a variety of heavy metals and metalloids, such as cadmium, lead, arsenic, and selenium. In acid neutralization by carbonate and silicate minerals, a range of secondary minerals can form and possibly scavenge these potentially harmful elements. Apart from the extensively-studied microbial-facilitated sulfide oxidation, the diverse microbial communities present in mine rock and drainage may also participate in the formation, dissolution, and transformation of secondary minerals influencing the mobilization of these metals and metalloids. This article reviews major microbial-mediated geochemical processes occurring in mine rock piles that affect drainage chemistry, with a focus on the role of microorganisms in the formation, dissolution and transformation of secondary minerals. Understanding this is crucial for developing biologically-based measures to deal with contaminant release at the source, i.e., source control.

This study aims to evaluate the land surface temperature (LST) and the thermal characteristics of the Urban Canopy Layer (UCL) of the urban canyon in Avenida Rio Branco in the Central Business District (CBD) of Rio de Janeiro during summer. In order to conduct this evaluation, two methods were employed: 1) TIRS Landsat-8 sensor for data selection and processing (latest generation, 2011-2020); ; 2) field survey using nine sampling points — seven along two mobile transects, one fixed point, and one vertical measurement point, which required the use of a RPA (Remotely Piloted Aircraft). Three categories of analysis were established for the field survey based on the prevailing synoptic situations: stability, instability, and post-instability. The CBD is characterized by extensive areas with surface heat islands, in which temperatures were higher than 38.9°C; the areas with milder LSTs were Campo do Santana, Avenida Rio Branco, and one of the Mixed-Use Zones (Praça Mauá). With respect to Rio Branco Avenue, the LST niches of lowest elevation were derived through building shadowing; however, the orbital data diverged from the observation data of the ten field-study days. In situ data revealed that the characteristics urban morphology of Avenida Rio Branco is susceptible to the formation of heat islands, presenting heat islands of very strong magnitude (over 6.1°C) in atmospheric stability, strong magnitude (4.1-6.0°C) in atmospheric instability, and moderate magnitude (2.1°C-4.0°C) in post-atmospheric instability. Despite the synoptic situation, thermal cores were concentrated at 1 pm. The intersection between Avenida Rio Branco, Rua do Ouvidor, and Praça Mauá stored most of the solar energy received during the day due to the greater sky obstruction caused by the verticalization. Finally, vertical analysis demonstrated the formation of a thermal inversion on the night of the highest mean air temperature (29.5°C), probably, due to the roughness and number of buildings in the urban canyon.

A series of novel substituted isoxazolidine derivatives was synthesized through 1,3-dipolar cycloaddition reactions of α-aryl-N-methyl nitrones with various ethylene moieties, resulting in the formation of isoxazolidine derivatives. The structures of the synthesized compounds were characterized using spectroscopic methods. The [3+2] cycloaddition (32CA) reactions of α-aryl-N-methyl nitrones with diverse ethylene substituents were computed employing Density Functional Theory (DFT) at the B3LYP/6–31G(d) level, upgrading bond parameters. An investigation of the electron localization function (ELF) unveiled the zwitterionic nature of α-aryl-N-methyl nitrones, devoid of pseudoradical or carbenoid centers. Utilization of CDFT indices enabled the prediction of global electronic flux from the strongly nucleophilic α-aryl-N-methyl nitrones to the varied electrophilic ethylene functionalities. Molecular docking and molecular dynamics simulations were conducted on the isoxazolidine derivatives against the EGFR receptor (PDB: 4ZAU). In silico assessment of the synthesized isoxazolidines involved molecular docking, wherein the compound with the highest docking score was subjected to molecular dynamics simulations. Compound 11a, out of the thirty isoxazolidine derivatives, displayed the most substantial binding energy, yielding a g score of -6.57 kcal/mol. These observations highlighted the functional role of amide NH2 and NO2 in the binding process with the target protein, influencing its activity. Furthermore, prediction of ADME drug-likeness properties was performed to identify a suitable candidate.

Topic discovery is finding the main idea of large amounts of textual data. It indicates the recurring topics in the documents, allowing an overview of the texts. Current topic discovery models receive the texts, with or without pre-processing of Natural Language Processing. The processing consists of stopwords removal, text cleaning and normalization (lowercase conversion). A topic discovery model that receives texts with or without processing generates general topics since the input data is many uncategorized texts. The general topics do not offer a detailed overview of the input texts, and manual text categorization is a time-consuming and tedious task. Accordingly, it is necessary to integrate an automatic text classification task in the topic discovery process to obtain specific topics with their top words that contain relevant relationships based on belonging to a class. Text classification performs a word analysis that makes up a document to decide what class or category is being identified; then, integrating the text classification before a topic discovery process will provide latent topics depicted by top words with a high coherence in each topic based on the previously obtained classes. Therefore, this paper exposes a approach that integrates text classification into topic discovery from large amounts of English textual data, such as 20-Newsgroup and Reuters corpora. The text classification is accomplished with a Convolutional Neural Network(CNN) incorporating three embedding models based on semantic relationships. The topic discovery over categorized texts is realized with Latent Dirichlet Analysis(LDA), Probabilistic Latent Semantic Analysis(PLSA), and Latent Semantic Analysis(LSA) algorithms. An evaluation process was performed based on the normalized topic coherence metric. The 20-Newsgroup corpus was classified, and twenty topics with ten top words were discovered for each class, obtaining 0.1723 normalized topic coherence when applying LDA, 0.1622 with LSA, and 0.1716 with PLSA. The Reuters corpus was also classified, obtaining 0.1441 normalized topic coherence when applying the LDA algorithm to obtain 20 topics for each class.

Embedding representation models characterize each word as a vector of numbers with a fixed length. These models have been used in tasks involving text classification, such as recommen- dation and question-answer systems. Semantic relationships are words with a relationship between them providing a complete idea to a text. Therefore, it is hypothesized that an embedding model involving semantic relationships will provide better performance for tasks that use them. This paper presents three embedding models based on semantic relations extracted fromWikipedia to classify texts. The synonym, hyponym, and hyperonym semantic relationships were the ones considered in this work since previous experiments have shown that they are the ones that provide the most semantic knowledge. Lexical-syntactic patterns present in the literature were implemented and subsequently applied to the Wikipedia corpus to obtain the semantic relationships present in it. Several semantic relationships are used in different models: synonymy, hyponym-hyperonym, and a combination of the first two. A convolutional neural network was trained for text classification to evaluate the performance of each model. The results obtained were evaluated with the metrics of precision, accuracy, recall, and F1-measure. The best values obtained with the second model were accuracy of 0.79 for the 20-Newsgroup corpus. F1-measure and recall of 0.87 respectively for the Reuters corpus.

Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with numerous negative impacts in the Chilean salmon farming industry. Although transcriptomic studies of P. salmonis and its host have been performed, dual host-pathogen proteomic approaches during infection are still missing. Considering that gene expression not always corresponds with observed phenotype, and bacteriological culture studies inadequately reflect infection conditions, to improve the existing knowledge for the pathogenicity of P. salmonis we present here a global proteomic profiling of Salmon salar macrophage-like cell cultures infected with P. salmonis LF-89. The proteomic analyses identified several P. salmonis proteins from two temporally different stages of macrophages infection; some of them related to key functions for bacterial survival in other intracellular pathogens. Metabolic differences were observed in early-stage infection bacteria, compared to late-stage infections. Virulence factors related to membrane, LPS and surface component modifications, cell motility, toxins and secretion systems also varied between the infection stages. Pilus proteins, beta-hemolysin and the T6SS were characteristic of the early-infection stage, while fimbria, upregulation of 10 toxins or effector proteins, and the Dot/Icm T4SS were representative of the late-infection stage bacteria. Previously described virulence-related genes in P. salmonis plasmids were identified by proteomic assays during infection in SHK-1 cells, accompanied by an increase of mobile-related elements. By comparing the infected and un-infected proteome of SHK-1 cells, we observed changes in cellular and ROS homeostasis, innate immune response, microtubules and actin cytoskeleton organization and dynamics, alteration in phagosome components, iron transport and metabolism, and amino acids, nucleoside and nucleotide metabolism, together with an overall energy and ATP production alteration. Our global proteomic profiling and the current knowledge of the P. salmonis infection process allowed us to propose a model of the macrophage-P. salmonis interaction.

Frontotemporal lobar degeneration (FTLD) belongs to a heterogeneous group of highly complex neurodegenerative diseases and represents the second cause of presenile dementia in individuals under 65. Frontotemporal-TDP is a subgroup of frontotemporal dementia characterized by the aggregation of abnormal protein deposits, predominantly transactive response DNA-binding protein 43 (TDP-43), in the frontal and temporal brain regions. These deposits lead to progressive degeneration of neurons resulting in cognitive and behavioral impairments. Limbic age-related encephalopathy (LATE) pertains to age-related cognitive decline primarily affecting the limbic system which is crucial for memory, emotions, and learning. Though distinct, emerging research suggests a potential overlap in pathogenic processes, with some cases of limbic encephalopathy displaying TDP-43 pathology. Genetic factors play a pivotal role in both disorders. Mutations in various genes, such as progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72), have been identified as causative in frontotemporal-TDP. Similarly, specific genetic variants have been associated with an increased risk of developing LATE. Understanding these genetic links provides crucial insights into disease mechanisms and the potential for targeted therapies.

In this paper, we revisit the q-states clock model for small systems. We present results for the thermodynamics of the q-states clock model from $q=2$ to $q=20$ for small square lattices $L \times L$, with L ranging from $L=3$ to $L=64$ with free-boundary conditions. Energy, specific heat, entropy and magnetization are measured. We found that the Berezinskii-Kosterlitz-Thouless (BKT)-like transition appears for $q>5$ regardless of lattice size, while the transition at $q=5$ is lost for $L<10$; for $q\leq 4$ the BKT transition is never present. We report the phase diagram in terms of $q$ showing the transition from the ferromagnetic (FM) to the paramagnetic (PM) phases at a critical temperature T$_1$ for small systems which turns into a transition from the FM to the BKT phase for larger systems, while a second phase transition between the BKT and the PM phases occurs at T$_2$. We also show that the magnetic phases are well characterized by the two dimensional (2D) distribution of the magnetization values. We make use of this opportunity to do an information theory analysis of the time series obtained from the Monte Carlo simulations. In particular, we calculate the phenomenological mutability and diversity functions. Diversity characterizes the phase transitions, but the phases are less detectable as $q$ increases. Free boundary conditions are used to better mimic the reality of small systems (far from any thermodynamic limit). The role of size is discussed.

Manual handling tasks, both in daily activities and at work, require high dexterity and the ability to move objects of different shapes and sizes. However, musculoskeletal disorders that can arise due to aging, disabilities, overloading, or strenuous work can impact the natural capabilities of the hand with serious repercussions both in working and daily activities. To address this, researchers have been developing and proving the benefits of wrist exoskeleton., This paper, which is the part II of a study on wrist exoskeletons, presents and summarizes wearable wrist exoskeleton devices conceived for use in rehabilitation, assistance, and occupational fields. Exoskeletons considered within the study are those available either in a prototyping phase or on the market. They can support the human wrist by relieving pain or mitigating fatigue while allowing at least one movement. According to the requirements to be met, the majority have been designed active (80%) for higher force/torque transmission, and soft for better kinematic compliance, ergonomics, and safety (13 devices out of 24, more than 50%). Electric motors (11 devices out of 24, almost 50%) and cable transmission (9 devices out of 24, almost 40%) are the most common due to their simplicity, controllability, safety, power-to-weight ratio, and the possibility of remote actuation. As sensing technologies, position and force sensors are widely used in all devices (almost 90%). The control strategy depends mainly on the application domain: for rehabilitation, CPM (Control Passive Motion) is preferred (35% of the devices), while for assistance and occupational purposes AAN (Assistance-As-Needed) is more suitable (38% of the devices). What emerges from this analysis is that while rehabilitation and training are fields in which exoskeletons have been grown more easily and gained some user acceptance (almost 18 devices of which 4 are available on the market), relatively few devices have been designed for occupational aims (6 of which only 2 are available on the market) due to difficulties in meeting the acceptance and needs of users. In this perspective, as a result of the state-of-the-art analysis, the authors propose a conceptual idea of a portable soft wrist exoskeleton for occupational assistance.

The aim of this study was to determine the relationship between levels of leisure-time sports and physical activity and the stages of change in high school students with goal orientations. Methods: The sample consisted of 2168 students randomly selected to participate in a longitudinal study in Costa Rica (423), Mexico (408) and Spain (1337), with 1052 being boys, 1037 girls and 79 who did not specify sex, aged between 11 and 16 years old (M = 12.49, SD = .81). We used a questionnaire to ask students about their leisure-time sports and physical activity, about stages of change and to measure achievement goals. Results: The results show that students are more active in Costa Rica, most of them being in the stage of active change. Conclusions: We found significant differences in achievement goals in all three countries, which shows that students in active stages have higher values than those in the inactive stage.

The role of foods is shifting from focusing on the provision of energy and basic nutrients to also include bioactive compounds that prevent the development of chronic age-related diseases. Mi-croalgae offer a source of nutritional compounds with important health effects, and have the po-tential for production of health-promoting products, without increasing agricultural land use and negatively impacting the environment. Here we investigate the health effects of microalgal ex-tracts with high levels of the colourless carotenoid phytoene. Phytoene is widely available from dietary sources and can be detected across different tissues in the human body. However, it is usually regarded as a precursor for the synthesis of other carotenoids, rather than a bioactive molecule. We utilised the model organism C. elegans to show that phytoene-rich extracts from Chlorella sorokiniana and Dunaliella bardawil have anti-ageing properties. The extracts protect against oxidative damage and amyloid-β42 proteotoxicity (a major pathology of Alzheimer's disease), and extends lifespan. We show that pure phytoene also has these anti-ageing effects, suggesting that phytoene is a bioactive molecule with positive effects on ageing and longevity.

Forensic assessments may involve the sampling of textile fibers when examining crime scenes. The need to characterize and identify those fibers is crucial as they can provide extensive information relating to a crime, linking a suspect to a location. Fibers in particular may contain issues in terms of both size and quantity of sample, and micro Fourier transform Infrared in attenuated total reflectance mode (micro FTIR-ATR) spectroscopy presents a non-destructive method to identify those fibers. In this study we carried out a rapid forensic assessment via micro FTIR-ATR of sixty textile fibers recovered from twenty white fabrics relying on tape lifting method, in order to discriminate those materials. Two dimensional principal component analysis and radar chart were applied to enhance the visual comparison of the fibers. Results of infrared spectra revealed that the technique allows the discrimination of textile fibers according to their spectral composition (cellulose, polyamide, polyester, or mixture of these composites) and to some characteristics, as number and width of peaks, peak position according to the wavenumber, absorbance index related to peak sharpness, etc. The technique was deemed useful in the forensic assessment of the fibers, presenting rapid and enlightening results.