Millimeter wave antennas have significance for high-speed, high-capacity wireless communication, delivering substantial advantages and an array of applications. This literature review analyzes the historical development, assessment of performance, difficulties with design, and contemporary applications in telecommunications, radar systems, and imaging. It covers the development of technology, especially within the context of 5G and beyond, and focuses at several antenna designs that deal with technical issues including reduction and impedance matching. The review also studies the effect of design on efficiency and bandwidth, identifying research gaps and potential futures, notably in terms of 5G technology. The commitment to develop millimeter wave antenna technology for next-generation wireless networks is evident, underlining the need of continued research and development.

This literature review investigates the importance of simulation and measurement techniques in the development of transmission lines and antennas, which are crucial to the reliability and efficiency of communication system. It emphasizes the necessity of exact measurement and computational approaches for simulating complicated electromagnetic process, which help to optimize designs before physical prototypes are built. The review examines a variety of research articles that offer innovative solutions to improving accuracy in antenna design, scalability and cost challenges in antenna measurements, and crosstalk measurement methods. It also explores how these methodologies affect antenna design parameters such as gain, bandwidth, and radiation patterns, emphasizing the importance of correct modeling to ensure the performance of transmission lines and antennas in modern communication system. The review serves as a valuable reference for guiding future research and technological advancements in these fields.

The emergence of the COVID-19 pandemics prompted a fast development of novel diagnostic methods of the etiologic virus SARS-CoV-2. Methods based on CRISPR-Cas systems have been particularly promising because they can achieve a similar sensitivity and specificity to the golden standard RT-qPCR, especially when coupled to an isothermal pre-amplification step. Furthermore, they have also solved inherent limitations of RT-qPCR that impede its decentralized use and deployment in the field, such as the need for expensive equipment, high cost per reaction, and delivery of results in hours, among others. In this review, we evaluate publicly available methods to detect SARS-CoV-2 that are based on CRISPR-Cas and isothermal amplification. We critically analyze the steps required to obtain a successful result from clinical samples and pinpoint key experimental conditions and parameters that could be optimized or modified to improve clinical and analytical outputs. The COVID outbreak has propelled intensive research in a short time, which is paving the way to develop effective and very promising CRISPR-Cas systems for the precise detection of SARS-CoV-2. This review could also serve as an introductory guide to new labs delving into this technology.

COVID-19 pandemic has affected the public educational sectors in terms of adjustment in educational modalities of instructional delivery, school operations, and policies. With this emerging paradigm shift, teachers' crisis self-efficacy and work commitment are relevant for research. This study's main objective was to determine the significant influence of crisis self-efficacy on the work commitment of public school teachers in Region XI (Davao Region), Philippines, during the COVID-19 pandemic. The sample consisted of 1,340 public school teachers across the Davao Region. The researchers collected the data through adapted questionnaires contextualized to the local setting and administered through online Google forms with appended consent. Mean, standard deviation, Pearson r, and regression analysis were used to analyze data. Results revealed that crisis self-efficacy significantly influences the work commitment of public school teachers during the COVID-19 pandemic. Uncertainty management during this crisis, in particular, best predicts teachers’ work commitment. Data also showed a high level of crisis self-efficacy in terms of action, preventive, achievement and uncertainty management, and high level of teachers’ work commitment in terms of commitment to school, commitment to students, commitment to teaching, and commitment to profession. Correlation results also showed a link between crisis self-efficacy and the work commitment of teachers amid pandemic. Finally, the study concluded with practical recommendations and directions for future research.

If a subject learns about the properties of an alternative under a high state of food deprivation, it will prefer this alternative over a similar one in a later choice test, although the subject is currently under a relative state of satiety. In this experiment, we probe this effect in a delay-discounting task, where the reward of the experienced alternative is progressively delayed. Eight male Wistar rats were trained to respond to an alternative under a high state of deprivation and eight rats under a relative state of satiety. After 20 sessions, their weight was recalibrated to a state of relative satiety. Then, they were exposed to a delay-discounting task where the long-larger alternative was the one used during training. The group that experienced the alternative under a higher level of food deprivation preferred more this alternative, and its preference stayed across time. On the contrary, the group that experienced the alternative under a lower level of food deprivation systematically preferred the small-shorter alternative. Our results support that the reinforcement value may be sensitive to the organism's state at the moment an alternative is experienced for the first time.

Iron Doped TiO₂ nanoparticles (Fe-TiO₂) were synthesized and photocatalitically investigated under high and low fluence values of UV-radiation. The Fe-TiO₂ physical characterization was performed using X-ray Powder Diffraction (XRD), Brunauer-Emmett-Teller (BET) surface area analysis, Transmission Electron Microscope (TEM), Scanning Electron Microscope (SEM), Diffuse Reflectance Spectroscopy (DRS), and X-Ray Photoelectron Spectroscopy (XPS) technique. The XPS evidenced that ferric ion (Fe³⁺) was in the lattice of TiO₂ and co-dopants no intentionally added were also present due to the precursors of the synthetic method. The Fe³⁺ concentration played a key role in the photocatalytic generation of hydroxyl radical (•OH) and estriol (E3) degradation. Fe-TiO₂ materials accomplished E3 degradation, and it was found that the catalyst with 0.3 at. % content of Fe (0.3 Fe-TiO₂) enhanced the photocatalytic activity under low UV-irradiation compared with no intentionally Fe-added TiO₂ (zero-iron TiO₂) and Aeroxide^® TiO₂ P25. Furthermore, the enhanced photocatalytic activity of 0.3 Fe-TiO₂ under low UV-irradiation may have applications when radiation intensity must be controlled, as in medical applications, or when strong UV absorbing species are present in water.

Due to their contribution to human health, the production of healthy snacks has garnered the attention of both the scientific community and the food industry. This study was conducted to determine the suitability of frying and baking processing methods for producing green banana chips using two varieties: Barraganete and Dominico. The aim was to identify a treatment geared towards producing healthy snacks. Initially, the physicochemical properties of the raw materials were analyzed, revealing significant differences in starch, fat, fiber, and protein content. Subsequently, the bananas were processed into baked and fried chips. Multivariate statistical techniques such as ANCOVA, MANOVA, and post-hoc tests were applied to examine the influence of initial characteristics and detect variations attributable to the cooking method. The main findings showed that the initial protein level had a significant covariate effect on the final content in the chips. The Dominico variety generally proved more suitable for making baked chips, retaining higher percentages of protein, starch, fiber, and lower fat content than Barraganete. Baked chips showed significantly lower sodium and fat values than fried ones when differentiated by processing method. The "Dominico + Baked" treatment emerged as the superior alternative, with favourable levels of protein, starch, and low sodium and fat, positioning it as the most suitable for producing a healthy snack.

Abstract: Background: In contrast to conventional definitions, the contemporary conceptualization of adulthood emphasizes psychological characteristics over sociodemographic milestones. Concurrently, there is a growing proposition that individuals' perceptions of adulthood exert a substantial influence on the mental well-being of adolescents and adults. However, empirical examination of this hypothesis has been notably limited to date. Method: This study applied some adulthood markers, and multiple mental health indices (including Well-being, Optimism, Alexithymia, Satisfaction with life, Goldberg's index of mental health, Dark triad, and dimensional personality disorders) to a community sample comprising 1772 individuals in Spain, spanning ages from 16 to 93 years. Results: The findings support the overarching hypothesis, as perceptions of adulthood exhibit significant associations with almost all measured mental health indices, especially with those conforming a factor of Negative emotions. These associations persist even after accounting for age and socioeconomic status, and in alignment with the psychological paradigm of adulthood, they demonstrate stability across different age cohorts. Conclusions: The study establishes that such perceptions of adulthood represent a modifiable factor contributing to positive mental health. The implications of these findings for the formulation of public policies aimed at promoting mental health in the context of adulthood are deliberated, as well as a number of future studies.

Pure monocular 3D reconstruction is an ill-posed problem that has attracted the research community's interest due to the affordability and availability of RGB sensors. SLAM, VO, and SFM are disciplines formulated to solve the 3D reconstruction problem and estimate the camera’s ego-motion, so many methods have been proposed. However, most of these methods were not evaluated in large datasets, under various motion patterns, had not been tested under the same metrics, and most of them had not been evaluated following a taxonomy, making their comparison and selection difficult. In this research, we performed a comparison of ten publicly available SLAM and VO methods following a taxonomy, including one method for each category of the primary taxonomy, three machine learning-based methods, and two updates of the best methods, to identify the advantages and limitations of each category of the taxonomy and test if the addition of machine learning or the updates made on those methods improved them significantly. Thus, we evaluated each algorithm under the TUM-Mono benchmark and performed an inferential statistical analysis to identify significative differences through its metrics. Results determined that sparse-direct methods significantly outperformed the rest of the taxonomy, and fusing them with machine learning techniques significantly improves the performance of geometric-based methods from different perspectives.

The alcoholic fermentation process with agitation/static, followed by the acetic fermentation submerged in banana was evaluated. Kinetics parameters of alcoholic fermentation for the maximum ethanol/glycerol metabolites in agitated process was 29 and 27 h, and in static 47 and 45 h, respectively. For acetic fermentation, the kinetics parameters were medium time of 39.9 h, acetic acid yield of 53.1% and acetic acid productivity of 0.216 g/Lh. Wines from agitated/static process presented 5.73 and 6.81% (v/v) of alcohol content, respectively. Wine obtained by the static process presented higher concentrations of volatile compounds. The vinegar showed 49.2 g/L of acetic acid and the esters concentrations were higher than in wine. The wine and vinegar minerals were consistent with amount observed in the pulp, with an increase in sulphur concentration after alcoholic fermentation and decrease after acetic fermentation. Products showed chemical and composition of sensory and nutritional interest.

Paving blocks are concrete pieces placed in exposed places to the weather, which are sub-jected to loads and wear. Hence, quality control in the manufacture of paving blocks is es-sential to guarantee the properties and durability of the product in construction projects. In Ecuador, the requirements are described in the Ecuadorian technical standard "NTE INEN 3040", and tensile splitting strength is a fundamental requirement to guarantee product quality. It is analyzed using quality control measurements such as dimensions, the weight of the fresh paving block in the vibro-compacted process, and the percentage of water absorption in order to know how the variables influence and manage to predict the tensile splitting strength to avoid product non-conformity in advance, having a timely and better control of the manufacturing process. The data was obtained from a company that can produce 30 000 units per day of rectangular paving blocks with 6 cm thickness. Mul-tivariate models such as multiple linear regression, regression trees, random forests and neural networks are performed to predict the tensile splitting strength variable through two groups of predictors; the first group is the thickness mm, width mm, length mm, mass of fresh paving block g and percentage of water absorption %. The second group of pre-dictor variables is the density of the fresh paving block kg/m3 and the percentage of water absorption %. It is concluded that the multiple linear regression method performs better in predicting the first group of predictor variables with a mean square error (MSE) of 0.110086, followed by the neural network without hidden layers resulting in an MSE of 0.112198. The best method for the second set of predictors was the neural network with-out hidden layers with a mean square error ( MSE ) of 0.112402, closely followed by the multiple linear regression model with an MSE of 0.115044.

The unstable international economic situation is reflected in the supply chain stress, lack or increased cost of some raw materials, fuel or semi-finished products is forcing organizations to perform new optimization initiatives in the utilization of their equipment and assets pointed to obtain the maximum value from them, while maintaining and even improving the quality of their products. The achievement of these objectives involves the reduction or minimization of equipment downtime to maintain the advantage over their competitors and ensure the organization's competitiveness. The intelligent maintenance system (IMS) provides adequate support for decision-making related to equipment maintenance, since poor maintenance results in unplanned stoppages, with the consequent additional cost and increased customer dissatisfaction, and an over-maintenance can result in an additional labor cost, time and the replacement of parts that are in good conditions. The utilization of new tools and technologies introduced by Industry 4.0 offers multiple opportunities for enhancement through communication and computerized data processing, aiming to improve the maintainability of a hydrogen compressor using neural networks based on attention mechanisms combined with linear regression.

In this paper we use the Mellin convolution theorem, which is related to Perron's formula. Also we introduce new explicit formulae for arithmetic function which generalize the explicit formulae of Weil for other arithmetic functions different from the Von-Mangoldt function.

Decapod crustaceans are a very diverse group and have evolved to suit a wide variety of diets. Alpha-amylases enzymes, responsible for starch and glycogen digestion, have been more thoroughly studies in herbivore and omnivore than in carnivorous species. We used information on the α-amylase of a carnivorous lobster as a connecting thread to provide a more comprehensive view of α-amylases across decapods crustaceans. Omnivorous crustaceans such as shrimps, crabs and crayfish present relatively high amylase activity respect to carnivorous. Yet, contradictory results have been obtained and relatively high activity in some carnivores has been suggested to be a remnant trait from ancestor species. Here we provided information sustaining that high enzyme sequence and overall architecture conservation do not allow high changes in activity, and that differences among species may be more related to number of genes and isoforms, as well as transcriptional and secretion regulation. However, recent evolutionary analyses revealed that positive selection might have also occurred among distant lineages with feeding habits as a selection force. Some biochemical features of decapod α-amylases can be related with habitat or gut conditions, while less clear patterns are observed for other enzyme properties. Likewise, while molt cycle variations in α-amylase activity are rather similar among species, clear relationships between activity and diet shifts through development cannot be always observed. Regarding the adaptation of α-amylase to diet, juveniles seem to exhibit more flexibility than larvae, and it has been described variation in α-amylase activity or number of isoforms due to the source of carbohydrate and its level in diets, especially in omnivore species. In the carnivorous lobster, however, no influence of the type of carbohydrate could be observed. Also, lobsters were not able to fine-regulate α-amylase gene expression in spite of large changes in carbohydrate content of diet, while retaining some capacity to adapt α-amylase activity to very low carbohydrate content in the diets. In this review, we raised arguments for the need of more studies on the α-amylases of less studied decapods groups, including carnivorous species which rely more on dietary protein and lipids, to broad our view of α-amylase in decapods crustaceans.

The international literature shows a polarised debate on the impacts of climate change on migration. Some studies find a positive linkage, whereas others find a negative one. It is, without a doubt, a complex process better considered case-specific. There is no available information on the relationship between climate change and migration in Colombia, despite past research exploring each of these subjects independently. This study intends explicitly to investigate this linkage gap. Consequently, this paper's essential contribution is that it builds a bridge between climate change scenarios and migratory science for the first time in Colombia. Despite their limitations, the theoretical and methodological framework suggested by IOM (2009b pp. 86, Section B, Chapter II) is demonstrated in this study to be very valid since it provides a methodology to predict where future flows will occur (based on past evidence). The methodological approaches of SLA and NELM explained in section A in the IV Chapter are also valuable for analysing and approaching this study's conclusions. The primary conclusions of this study indicate that the "Coffee Region," Valle, and Atlantic (or Caribbean Coast) provinces that mainly send emigrants to Spain and the US are the key internal regions responsible for most of the international migration from Colombians. The same areas are especially vulnerable to the impacts of upcoming climate change in the A1B scenario produced by the IDEAM (2010) for 2040 and 2100. Thus, future flows of migrants are expected from these regions (2040-2100). However, issues such as visa requirements or the costs associated with migration constitute international barriers to this flow. The sensitivity of these regions can also be associated with internal migration flows, more armed conflict, and forced displacement in a cyclical process. Theoretically, a resurgence of Colombia's armed conflict and displacement due to climate change can be expected. However, the need for empirical studies in Colombia to support this analysis is imperative and is the most crucial recommendation arising from this study.

In this work, an embroidered textile moisture sensor is presented. The sensor is based on a capacitive interdigitated structure embroidered on a cotton substrate with an embroidery conductor yarn composed by 99% pure silver plated nylon yarn 140/17 dtex. In order to evaluate the sensor sensitivity, the impedance of the sensor has been measured by means of a LCR meter from 20 Hz to 20 kHz on a climatic chamber with a sweep of the relative humidity from 25% to 65% at 20 ºC. The experimental results show a clear and controllable dependence of the sensor impedance with the relative humidity. Moreover, the reproducibility of the sensor performance subject to the manufacturing process variability and washing process is also evaluated. The results show that the manufacturing variability introduce a moisture measurement error up to 4%. The washing process impact on the sensor behavior after applying the first washing cycle implies a sensitivity reduction higher than 14%. Despite these effect, the textile sensor keeps its functionality and can be reused in standard conditions. Therefore, these properties point out the usefulness of the proposed sensor to develop wearable applications on health and fitness scope including the user needs to have a life cycle longer than one-time use

Objectives: In this retrospective observational study, it is intended to establish how the implementation of the use of antimicrobial optimization programs at the hospital and ICU level in a Sincelejo Sucre Clinic has significantly impacted the improvement of the rational use of antibiotics1, due to the alarming situation of increasing antibiotic resistance. Materials and methods: The methodology used was to analyze the Excel database of the Clinic, in such a way that it would allow comparing the pre-PROA and post-PROA data of 4 antibiotics, ceftriaxone3, ciprofloxacin4, meropenem5 and vancomycin6, measured in Daily Dose. defined. Results: According to the DDD values obtained for the 4 antibiotics, a reduction in DDD was identified in the post-Proa period. On the other hand, considering the DDD reported by the WHO for each of the antibiotics, significant differences were verified compared to the DDD obtained in the clinic in the hospitalization and ICU services. Conclusions: In conclusion, in the clinic there was evidence of a reduction in DDD in the post-ASP2 period compared to the pre-PROA period, both in hospitalization and in the ICU, as well as a slight to large effect with Cohen's D.

The receptor tyrosine kinase (EphB4), which produces erythropoietin, was identified as a molecular target for cancer. We identified six peptides as potential inhibitors of EphB4 using an integrated approach combining online bioinformatics tools. According to PeptideRanker, CSM-peptides, SCMTHP, and AcPEP analysis, all peptides are effective against cancer, with the exception of LTAPGQATLPT and VEQNLVPGLK. Furthermore, Toxin-Pred predicts that none of the peptides are toxic, and that only VQLPGWRVFP and TMKGPPDTLQ are potentially allergenic using AllerTop server. PepSite2, HPEPDOCK, and MDockPeP servers were utilized to perform molecular docking, and PacDock was used to examine molecular interactions. The docking score (kcal/mol) range of six promising anticancer peptides against EphB4 was recorded as follows: VQLPGWRVFP (-240.72), FTKDDEWSCFPF (-201.74), SYLPPLSAEVTAK (-177.52), LTAPGQATLPT (-162.23), VEQNLVPGLK (-157.30), TMKGPPDTLQ (-149.67). The main bindings on the allosteric site to VQLPGWRVFP were with R706, S815, R819 and P843 on EphB4. Collectively, our results demonstrated that M. oleifera peptides ameliorate cancer by inhibiting EphB4, and they are promising candidates for the prevention and treatment of cancer.

Recently Palle has investigated the chiral vorticity and Cartan torsion in neutrino asymmetries. In his case he addressed this problem in Goedel s like anisotropic Einstein-Catan cosmology. In this paper we discusse how these ideas applied to sheared Bianchi types I Einstein-Cartan (EC) neutrino amisotropic cosmology, affect the handness of neutrinos in the universe. Actually here a novel concept of the chiral metric is introduced where metric functions also possess two distinct signs as in neutrino flipping or helicity. The axial anomaly equation for neutrinos in the presence of torsion and metric chirality is shown to produce left-handed neutrinos from right-handed torsion. Metric chirality is shown to be able to define how the metric would behave far away of neutrino density. Chiral flipping of the chiral neutrinos in the presence of torsion is also investigated. It is shown that when the chiral torsion is left-handed the chemical chiral potential vanishes as the universe expands.

This study explored the incidence of metaphorical virtual classrooms and interactive learning objects in the interaction of students in online mode. The main objective was to analyze how these digital tools, driven by a set of strategies to promote their use, affect the interaction of students in the virtual classroom system and their derived effects. To this end, the latest version of Moodle was implemented in conjunction with gamification plugins and interactive tools in the higher education institution used as a case study. The methodology consisted of data collection through ordinal instruments applied to the teachers and student performance metrics gathered using a plugin developed to extract accurate metrics of each student's usage and performance through direct queries to the Moodle database and its processing through a neural network. This facilitated the collection of standardized data on the actual metrics of each virtual classroom at the end of the teaching of each subject from both the previous LMS and the newly implemented one. This data was then analyzed using advanced statistical techniques, including Mahalanobis distances, confirmatory factor analysis, and the Wilcoxon signed-rank test. These methods provided a compelling comparison between the old and new systems, revealing significant improvements in the metrics and factors evaluated. The results showed a significant improvement in teachers' perceptions of the usability of the virtual classroom system and an increase in students' academic performance, interaction, progress, and time spent learning in virtual contexts. These results provide solid empirical evidence of the added value of these educational tools as effective strategies for improving student interaction, performance, and motivation in online education.

An accurate, economical, and reliable device for detecting falls in persons ambulating with the assistance of an orthopedic walker is crucially important for the elderly and patients with limited mobility. Existing wearable devices such as wristbands are not designed for walker users, and patients may not wear them at all times. This research proposes a novel idea of attaching an internet-of-things (IoT) device with an inertial measurement unit (IMU) sensor directly to an orthopedic walker to perform real-time fall detection as well as activity logging. A dataset is collected and labeled for walker users in four activities, including idle, motion, step, and fall. Classic machine learning algorithms are evaluated using the dataset by comparing their classification performance. Deep learning with convolutional neural network (CNN) is also explored. Furthermore, the hardware prototype is designed by integrating a low-power microcontroller for onboard machine learning, an IMU sensor, a rechargeable battery, and Bluetooth wireless connectivity. The research results show the promise of improved safety and well-being of walker users.

Based on orbital angular momentum (OAM) properties of Laguerre Gaussian beams LG(p,ℓ), a robust optical encoding model for efficient data transmission applications is designed. This paper presents an optical encoding model based on intensity profile generated by a coherent superposition of two OAM-carrying Laguerre-Gaussian modes and Machine-learning detection method. In the encoding process, the intensity profile for data encoding is generated based on selection of p and ℓ indices, while the decoding process is performed using support vector machine (SVM) algorithm. Two different decoding models based on SVM algorithm are tested to verify the robustness of optical encoding model, finding a BER =10−9 for 10.2dB of signal-to-noise ratio in one of the SVM models.

Background: The extended-spectrum beta-lactamase (ESBL) Klebsiella pneumoniae is one of the leading causes of health-associated infections (HAI), whose antibiotic treatments have been severely reduced. Besides, HAI bacteria may harbor pathogenic factors such as siderophores, enzymes, or capsules, which increase the virulence of these strains. Thus, new therapies such as antimicrobial photodynamic inactivation (aPDI) are needed. Method: A collection of 118 clinical isolates of K. pneumoniae were characterized susceptibility and virulence through the determination of the minimum inhibitory concentration (MIC) of Amk, Cfx, Cfz, Imp, Mer, and Pip-taz, and by PCR, the frequency of the virulence genes, K2, magA, rmpA, entB, ybtS, and allS. Susceptibility to innate immunity, such as human serum, macrophages, and polymorphonuclear cells, was tested. All the strains were tested for sensitivity to the photosensitizer PSIR-3 (4µg/mL) in a 17µW/cm2 for 30 min aPDI. Results: A significantly higher frequency of virulence genes in ESBL than non-ESBL bacteria were observed. The isolates of the genotype K2+, ybtS+, and allS+ display enhanced virulence since they showed higher resistance to human serum as well as to phagocytosis. All strains are susceptible to the aPDI with PSIR-3 decreasing viability in 3log10. The combined treatment with Cfx improved the aPDI to 6log10 for the ESBL strains. The combined treatment is synergistic as it showed an FIC index value of 0.15. Conclusions: The aPDT effectively inhibits clinical isolates of K. pneumoniae, including the more risky strains of ESBL-producing bacteria and the K2+, ybtS+, and allS+ genotype. The aPDI with PSIR-3 is synergistic with Cfx.

In this work, two embroidered textile moisture sensors are characterized with three different conductive yarns. The sensors are based on a capacitive interdigitated structure embroidered on a cotton substrate with an embroidered conductor yarn. The performance comparison of 3 different type of conductive yarns has been addressed. In order to evaluate the sensor sensitivity, the impedance of the sensor has been measured by means of a LCR meter from 20 Hz to 20 kHz on a climatic chamber with a sweep of the relative humidity from 30% to 65% at 20 ºC. The experimental results show a clear and controllable dependence of the sensor impedance with the relative humidity and the used conductor yarns. This dependence points out the optimum conductive yarn to be used to develop wearable applications for moisture measurement.

The search for new food products that promote consumers health has always been of great interest. The dairy industry is perhaps the best example regarding the emergence of new products with claimed health benefits. Cheese whey (CW), the by-product resulting from cheese production, and second cheese whey (SCW), which is the by-product of whey cheese manufacture, have proven to be potential ingredients for the development of food products with improved nutritional characteristics and other functionalities. Nowadays, due to their nutritional quality, whey products have gained a prominent position among healthy food products. However, for long, CW and SCW were usually treated as waste or as animal feed. Due to their high organic content, these by-products can cause serious environmental problems if discarded without appropriate treatment. Small and medium size dairy companies do not have equipment and structure to process whey and second cheese whey. In these cases, generally, they are used for animal feed or discarded without an appropriate treatment, being the cause of several constraints. There are several studies regarding CW valorization and there is a wide range of whey products in the market. However, in the case of SCW remains a lack of studies regarding its nutritional and functional properties, as well as ways to reuse this by-product in order to create economic value and reduce environmental impacts associated to its disposal.

This experimental research presents an easier model for fitting experimental results that can be simulate the dynamical behaviour of a single degree freedom system, SDFS, subjected in a forced vibration in a shaking table. The fractional damping using a Kelvin-Voigt fractional derivative rheological model, KVFRdm, to represent a fractional oscillator and compare with the experimental model.

The Autopoiesis and Cognition Theory (ACT), by Maturana and Varela, based on the notions of Biological Closure and Structural Coupling, is a well-known theory on how to understand biological organization [1, 2, 3]. Although, for example, the Free Energy Principle framework evokes some entailments of autopoiesis in a more formal setting [4, 5]; and ACT has been used in many fields, its impact has been restricted because it lacks quantitative analysis. Here we present a theoretical framework grounded in accepted and well-developed ideas from Mathematics and Physics which advance the understanding of the Principles of Biological Organization under the guidance of Biological Closure and Structural Coupling. The disciplines of Differential Geometry/Topology, Mechanics and Complex Dynamical Systems provide a powerful, elegant, and well-established body of knowledge to support our Biological Organization Principles (BOP) framework. In particular, Stochastic Mechanics and KAM theory (from Kolmogorov, Arnold and Moser theorem) allow us to develop, using the notions of Biological Closure and Structural Coupling, a central core of BOP termed Dynamical Closure Mechanism. Under the proposed framework, a wide variety of bio- logical phenomena can be understood, shedding new light on biological explanations. However, an understanding of biological organization may require the re-evaluation of dogmas on how we think on biology as it seems inescapable that what is needed is an integration of analysis and notions derived from mathematics, physics, and biology to generate a new landscape of ideas.

3D bioprinting holds great promise in the field of regenerative medicine as it can create complex structures in a layer-by-layer manner using cell-laden bioinks, making it possible to imitate native tissues. Current bioinks lack both the high printability and the biocompatibility required in this respect. Hence, the development of bioinks that are capable of both properties is needed. In our previous study, a furfuryl-gelatin based bioink, crosslinkable by visible light, was used for creating mouse mesenchymal stem cell-laden structures with high fidelity. In this study, lattice mesh geometries were printed in a comparative study to test against the properties of a traditional rectangular-sheet. After 3D printing and crosslinking, both structures were analysed for swelling and rheological properties, and their porosity estimated using scanning electron microscopy. Results showed that the lattice structure was relatively more porous but sturdy and exhibited a lower degradation rate compared to the rectangular-sheet. Further, the lattice allowed encapsulation of a greater number of cells, allowing them to proliferate to a greater extent compared to the rectangular-sheet that retained a lesser number of cells initially. All of these results collectively affirmed that the lattice poses as a superior scaffold design for tissue engineering applications.

Industry 4.0 (I4.0) epitomizes the nexus of technological evolution and manufacturing process enhancements, underpinned by four critical pillars: Cyber-Physical Systems (CPS), Digital Twins (DT), the Industrial Internet of Things (IIoT), and Cloud Computing (CC). Through the lens of the German Reference Architectural Model Industrie (RAMI) 4.0, these components are integral to fostering Smart Manufacturing (SM) practices. In conjunction, the Asset Administration Shell (AAS) facilitates seamless inter-company communication and enables adaptability to fluctuating market demands. This paper delves into the structural intricacies of AAS and SM within the RAMI 4.0 framework, unveiling three distinct implementation strategies. Furthermore, it meticulously scrutinizes challenges that hinder the full realization of I4.0 potential, such as interoperability, security concerns, and standardized communication protocols. By examining these models and identifying current barriers, the study illuminates pathways for future research, particularly in enhancing the integration of AAS and SM systems, ensuring robust security measures, and advocating for the development of universal standards. This exploration aims to contribute to the ongoing discourse on I4.0, proposing avenues for advancing manufacturing technologies and operational frameworks in alignment with the principles of RAMI 4.0.

A study of the water quality of the Adolfo López Mateos Reservoir (ALMD) was developed through different indicators from a spatial and seasonal perspective. Variables related to the general characteristics of water quality, trophic level and ecological risk were assessed through the water Quality Index (WQI_NSF-BROWN), Trophic State Index (TSI_CARLSON) and the Ecological Risk Index (RI_HAKANSON). Using data from physical, chemical and biological parameters obtained from four sampling points in the ALMD, the water quality was assessed in each model used. The results indicated that the reservoir presents a water quality classified as “medium” (WQI_NSF-BROWN = 70), where significant variations in the concentrations of some parameters are observed. The reservoir showed a general trophic state classified as “Mesotrophic” (TSI_{GENERAL-AVERAGE} = 43.04). The ecological risk analysis achieved the best classification of the methodology, discarding contamination by heavy metals in surface waters. Through this type of applied methodologies will help as decision making tools in the dam, as well as for application in other dams in the region.

Probabilistic latent semantic analysis is a statistical technique developed for information retrieval and spanned many fields. It yields intuitive and solid results. However, the rigidity of the assumptions and the iterative nature derived from the Expectation-maximization algorithm generate several problems, dividing detractors and enthusiasts. In this manuscript, we first describe the Probabilistic latent semantic analysis. After, we discuss reformulations that attempt to solve these problems. We pay special attention to the works relating Probabilistic latent semantic analysis and the Singular value decomposition Theorem. Also, Probabilistic latent semantic analysis can be the basis for other techniques, such as kernelization or probabilistic transfer learning, and those that extend the descriptive character of the Principal component analysis to an inferential tool and open a window of opportunities.

Summer annual species are the most widely grown crops in the Upper Midwest, but reliance on a summer annual system has led to excessive soil and nutrient loss when crops are not present. Integrating winter rye (Secale cereale L.), known for its hardiness and environmental benefits, into the rotation can address these issues. However, there's limited understanding of the phenotypic diversity in winter rye during key growth stages that overlap with the typical planting dates for corn (Zea mays L.), soybean [Glycine max (L.) Merr], and late-planted crops like dry bean (Phaseolus vulgaris L.). Thus, the objectives of this study were to evaluate changes in biomass accumulation and quality of winter rye and triticale (x Triticosecale Wittmack) cultivars at three growth stages. Twenty cultivars were assessed over the 2014-2015 and 2015-2016 growing seasons across three environments in Minnesota. Winter rye and triticale were harvested for biomass at the tillering, booting, and soft dough growth stages and rye biomass yield and quality [i.e., crude protein, neutral detergent fiber (NDF), and 48-hour digestibility (NDFD)] were determined following harvest. Overall, there was little variation in each parameter among the cultivars within a location and growth stage. NDFD had some variation at the soft dough stage where digestibility ranged from 273 to 324 g kg-1 at the Crookston site and 332 to 406 g kg-1 at the St. Paul site. The lack of difference between cultivars indicates a wide range of choice when selecting a winter rye cultivar.

Sword-duels are interesting, from a game-theoretical perspective, as they correspond to sudden-death interactions between players (i.e., defeat means removal from the game), and where victory/defeat depend on not just skill, but also luck. Analyzing probabilities of victory streaks, given a certain level of self and others' skill, is thus relevant for any application domain that can be modeled in the same way. This paper takes inspiration from Miyamoto Musashi, famously undefeated for 61 duels, and implements a Markov-chain Monte-Carlo simulation approach to evaluate this scenario. Results suggest that a 61 victory streak can be probabilistically observed when skill level is roughly 6.5 times that of the average duelist, and with 95\% confidence when skill level is roughly 1000 times that of the average duelist. More generally, this paper provides a method for determining chances of victory streaks in game-theoretical sudden-death encounters, when both "skill" and "luck" contribute to the outcome of the encounter. Specific scenarios can be modeled by modifying the utilized Markov chain and adjusting sampled distributions as required.

Purpose To analyse diagnostic and therapeutic impact of molecular imaging TNM (miTNM) stage obtained with 18F-DCFPyL versus 18F-Fluorocholine in head to head comparison in biochemical recurrence (BCR) prostate cancer (PCa). Material and methods Patients with BCR PCa after radical treatment with previous 18F-Fluorocholine-PET/CT (negative or oligometastatic disease) were derived to 18F-DCFPyL-PET/CT. Patients were classified attending to: grade group, EAU classification, PSA, PSA doubling time (PSAdt) and PSA velocity (PSAvel). The overall detection rate (DR) and miTNM stage according to PROMISE criteria were assessed for both radiotracers and also correlation (Kappa). The influence of PSA and kinetics on both PET/CT (DR and miTNM) and predictive value of unfavourable kinetics on miTNM were determined. Cut-off PSA, PSAdt and PSAvel values able to predict PET/CT results were determined. Change in miTNM and treatment derived of 18F-DCFPyL information with respect to 18F-Fluorocholine was also evaluated. Results We studied 138 patients. 18F-DCFPyL showed a higher DR than 18F-Fluorocholine (64.5% vs 33.3%). 18F-DCFPyL and 18F-Fluorocholine detected T in 33.3% versus 19.6%, N in 27.5% versus 13.8%, M in 30.4% versus 8.7%. Both tracers DR showed significant associations with PSA and PSAvel. Significant association was only found between miTNM and PSA on 18F-Fluorocholine-PET/CT (p=0.033). For 18F-Fluorocholine and 18F-DCFPyL PET/CT a PSAdt cut-off of 4.09 and 5.59 months, respectively, were able to predict M stage. 18F-DCFPyL changed therapeutic management in 40/138 patients. Conclusion 18F-DCFPyL provides a higher DR and superior miTNM staging than 18F-Fluorocholine in restaging BCR, especially with high PSA and unfavourable PSA kinetics, showing a fair agreement to 18F-Fluorocholine.

In a world filled with uncertainties, Ebb&Flow emerged as a story of convergence, intertwining dementia research, caregiving, and artistic exploration into a tripartite creative knowledge exchange. This study delves into the complexities of uncertainty in dementia care and research through a collaborative project involving artists, researchers, carers, and individuals with lived experience of dementia. Initiated by the Trellis:Arbor program, Ebb&Flow sought to co-created a human space addressing the multifaceted nature of uncertainty. The sea, with its unpredictable nature, served as a guiding metaphor for the project, reflecting the unpredictability of dementia and life. Over three months, through paintings, writings, and digital mediums, participants documented the changing emotions, challenges, and discoveries they encountered daily. The project fostered an environment where uncertainties were openly discussed, building supportive and resilient communities through participatory co-creation and methodological exchange. Key activities included a digital logbook, allowing participants to document and share their experiences of uncertainty, and the creation of the Ebb&Flow card deck—a compilation of personal stories and insights that serve as a legacy of shared experiences. Each card facilitated dialogue, understanding, and connection, bridging gaps between those affected by dementia and the broader community. The project culminated in a final exhibition and sharing event, where participants, researchers, and the public celebrated the journey's outcomes through stories and artworks. Throughout this journey, we observed that embracing uncertainty and fostering empathy through creative collaboration profoundly impacted participants, enhancing empathy and resilience. This project underscores the transformative potential of integrating artistic practices with scientific research to address the emotional and psychological burdens of dementia and research environments. Ebb&Flow demonstrates that even in the face of the unknown, a united community can find strength, solace, and understanding, highlighting the power and beauty of unity in exploring and expressing the multifaceted experiences of dementia and life.

In the field of robotics education, introductory courses would ideally utilize heavy industrial arms for hands-on learning. This would provide students with valuable experience in joint programming, which involves direct control of each joint motor in the arm to accomplish desired path planning and differential movements. This practice requires consideration of the physical dynamics of the arm. However, the use of heavy industrial arms has several drawbacks. They are large and expensive, require specialized maintenance, can pose safety risks, and they typically do not allow for direct control of the joint motors. One solution is to use a small, lightweight, toy-like arm. While these are cost-effective and provide direct access to the joint motors without posing safety risks, their lightweight construction means they exhibit minimal dynamic behavior, which limits their educational value. Another solution involves a robotic arm simulator that uses a virtual arm. However, a virtual arm doesn't offer the same level of hands-on engagement and excitement as a physical arm. We propose a hybrid solution that combines a small physical arm with a virtual arm. This approach provides students with the experience of working with an industrial arm, but without the associated difficulties. We demonstrate how this approach successfully improved the completion rate of joint programming assignments, offering a promising solution for practical robotics education.

Proteins and DNA exhibit key physical chemical properties that make them advantageous for building nanostructures with outstanding features. Both DNA and protein nanotechnology have growth notably and proved to be fertile disciplines. The combination of both types of nanotechnologies is helpful to overcome the individual weaknesses and limitations of each one, paving the way for the continuing diversification of the structural nanotechnologies. Recent studies have implemented a synergistic combination of both biomolecules to assemble unique and sophisticate protein-DNA nanostructures. These hybrid nanostructures are highly programmable and display remarkable features that create new opportunities to build in the nanoscale. This review focuses on the strategies deployed to create hybrid protein-DNA nanostructures. Here, we will discuss strategies such as polymerization, spatial directing and organizing, coating, rigidizing or folding DNA into particular shapes or moving parts. The enrichment of structural DNA nanotechnology by incorporating protein nanotechnology has been clearly demonstrated and still shows a large potential to create useful and advanced materials with cell-like properties or dynamic systems. It can be expected that structural protein-DNA nanotechnology will open new avenues in the fabrication of nano-assemblies with unique functional applications and enrich the toolbox of bionanotechnology.

A nanostructured electrochemical bi-sensor system for analysis of milks has been developed using the Layer by Layer technique. The non-enzymatic sensor [CHI+IL/CuPcS]2, is a layered material containing a negative film of the anionic sulfonated copper phthalocyanine (CuPcS) acting as electrocatalytic material, and a cationic layer containing a mixture of an ionic liquid (IL) (1-butyl-3-methylimidazolium tetrafluoroborate) that enhances the conductivity and chitosan (CHI) that facilitates the enzyme immobilization. The biosensor ([CHI+IL/CuPcS]2-GAO) results from the immobilization of galactose oxidase on the top of the LbL layers. FTIR, UV-vis and AFM have confirmed the proposed structure and cyclic voltammetry has demonstrated the amplification caused by the combination of materials in the film. Sensors have been combined to form an electronic tongue for milk analysis. Principal Component Analysis has revealed the ability of the sensor system to discriminate between milk samples with different lactose content. Using PLS-1 calibration models, correlations have been found between the voltammetric signals and chemical parameters measured by classical methods. PLS-1 models provide excellent correlations with lactose content. Additional information about other components such as fats, proteins and acidity can also be obtained. The method developed is simple and the short response time permits its use in assaying milk samples on-line.

Overweight and Obesity are global health and economic concerns. According to the World Health Organization, the number of individuals with obesity has nearly tripled since 1975. This health issue is currently considered an epidemic, affecting over 1.9 billion adults and 340 million children and adolescents. It contributes to more than 5 million deaths each year and has a global economic burden that will reach $4.32 trillion annually by 2035, according to the World Obesity Federation. This disease can affect every system of the human body and can lead to complications such as metabolic syndrome, diabetes, cancer, dyslipidemia, cardiovascular diseases, and hypertension, among others. Treatment may sometimes include diet, exercise, drugs, and bariatric surgery. Nonetheless, not all people have access to these treatments, and public health strategies consider prevention the most important factor. In this regard, recent investigations are aiming to find alternatives and adjuvants for the treatment of obesity, its prevention, and the reversion of some of its complications, using natural sources of anti-obesogenic compounds like polyphenols, terpenes, alkaloids, saponins, among others. In this review, we gather the most current information using PubMed, Google Scholar, Scopus, Cochrane, and Web of Science. We present and discuss the current information about natural products that have shown anti-obesogenic effects at a molecular level. We also consider the impact of dietary habits and lifestyle in preventing overweight and obesity due to the evidence of the benefits of certain foods and compounds consumed regularly. We discuss mechanisms, pathways, and receptors involved in the modulation of obesity, especially those related to inflammation and oxidative stress linked to this disease, due to the relevance of these two aspects in developing complications.

Background: Xenogenous bone has been proposed as an alternative to overcome the disadvantages of autogenous grafting. The aim of the present study was to study bone dynamics at inlay and onlay xenografts used for bone augmentation applying a ring technique. Methods: The bone at the lateral surface of the mandibular angle of 12 adult male New Zealand White rabbits was exposed bilaterally. The cortical layer received multiple perforations at one side of the mandible and a xenograft block of collagenated cancellous equine bone, 7 mm in diameter and 3 mm in width, was fixed on the prepared surface using an implant (onlay group). On the opposite side, a defect 7 mm in diameter and 3 mm in depth was prepared, the xenograft block was adapted to the defect and fixed with an implant (inlay group). Results: After ten weeks of healing, in the onlay grafts, new bone was mainly formed on the trabeculae surface, reaching in some specimens the most coronal regions of the block. In the inlay grafts, new bone was found arranged on the trabecular surfaces but also occupying the spaces among the trabeculae. The entrance of the defect was often found close at the top of the block by newly formed bone. A higher percentage of new bone was found in the inlay (19.0 ±9.3%) compared to the onlay (10.4 ±7.4%) groups (p=0.031). The mean gain in osseointegration at the implant in relation to the base of the original 3 mm deep defect was 0.95 ±1.05% at the onlay group and 0.78 ±0.71% at the inlay group (p=0.603). Conclusion: The inlay grafts exhibited a higher new bone percentage than the onlay grafts possibly due to the defect conformation that presented more sources for bone formation. The trabecular conformation and the composition of the grafts made possible the expression of the osteoconductive properties of the material used. This resulted, in several specimens, in growth of bone on the graft trabeculae toward the most superior regions in both groups, and in the closure of the coronal entrance of the defects in the inlay group.

The strong couplings among ecological, economic, social and technological processes explains the complexification of human-made systems, and phenomena such as globalization, climate change, the increased urbanization and inequality of human societies, the power of information, and the COVID-19 syndemics. Among complexification’s essential features are non-decomposability, asynchronous behavior, components with many degrees of freedom, increased likelihood of catastrophic events, irreversibility, nonlinear phase spaces with immense combinatorial sizes, and the impossibility of long-term, detailed prediction. Sustainability for complex systems implies enough efficiency to explore and exploit their dynamic phase spaces and enough flexibility to coevolve with their environments. This in turn means solving intractable nonlinear semi-structured dynamic multi-objective optimization problems, with conflicting, incommensurable, non-cooperative objectives and purposes, under dynamic uncertainty, restricted access to materials, energy and information, and a given time horizon, aiming at enhancing the co-evolutionary power of the Biosphere and its human subsystems. Giving the high-stakes, the need for effective, efficient, diverse solutions, their local-global, present-future effects, and their unforeseen short, medium and long-term impacts, achieving sustainable complex systems implies the need for Sustainability-designed Universal Intelligent Agents, harnessing the strong functional coupling between human, artificial and nonhuman biological intelligence in a no-zero-sum game to achieve sustainability.

The Sustainable Development Center of the University of Brasilia is one of the modernist buildings that make up the Darcy Ribeiro campus. The architectural project contains several recommendations for the execution of the flat roof waterproofing system, as well as details for rainwater runoff and drainage, which reveals a certain concern with watertightness. The research seeks to identify the relationship between the pathological manifestations recognized on the roof and the semicircular shape of the building, assessing the state of conservation through the use of damage maps as an analysis tool. The article is based on a field survey using aerophotogrammetry with a drone, the application of vector drawing software for graphic representation and discussion of the possible causes, agents and mechanisms of degradation at work. The results show the importance of mechanical protection for the good performance of the waterproofing system, as well as the need for correct sizing of expansion joints in order to absorb and relieve the stresses caused by hygrothermal variations. The methodology incorporated proved to be effective and economical in diagnosing and monitoring pathological manifestations, making it possible to plan maintenance actions that extend the useful life and preserve the intrinsic characteristics of building systems.

MicroRNAs are small non-coding RNAs that are implicated in several physiological processes such as cell development, proliferation, differentiation, apoptosis, immune response and angiogenesis. In the last couple of decades, several studies on miRNA profiling in OSCC have tried to associate miRNAs with clinical characteristics such as relapse, metastasis, and survival, however, the results have been found to vary considerably, sometimes even being contradictory. The main objective of our study was to analyse and verify miRNA expression in oral squamous cell carcinoma in a Spanish population. Second, we attempted to associate the identified deregulated miRNAs with molecular pathways. 8 Oral Squamous Cell Carcinoma patients and 8 healthy control samples were analysed by a microarray Affymetrix® miRNA 4.1 array plate and validated with 8 more cases using RT-qPCR. Deregulated miRNAs were studied using Diana Tools miRPath 3.0 to associate miRNA targets with molecular pathways. Microarray analysis identified 80 deregulated miRNAs (35 over-expressed and 45 under-expressed). Only miR-497-5p and miR-4417 maintained its deregulated expression after validation with qPCR. Among the molecular pathways in which deregulated miRNAs could be implicated, the most statistically significant pathway was ‘proteoglycans in cancer’. No relationship was found between miR-497-5p or miR-4417 expression and clinical or pathological parameters except of nodular affectation (high miR-4417 expression in patients with nodular affectation, p = 0.035) and radiotherapy (diminished miR-497-5p expression in patients who needed radiotherapy, p = 0.05). We have verified the altered expression of miR-497-5p and miR-4417 in Oral Squamous Cell Carcinoma samples and related the deregulated miRNAs with the ‘proteoglycans in cancer’ pathway.

Background/Objectives: Periodontitis (P), a chronic inflammatory condition that affects the supportive tissues around the teeth, is 3 to 4 times more prevalent in individuals with diabetes mellitus (DM), with a direct correlation between its severity and the levels of glycosylated haemoglobin (HbA1c). This study aimed to evaluate the periodontal clinical parameters following non-surgical periodontal treatment (NSPT) in patients with and without type 2 DM and P. Methods: Forty patients with P were divided into two groups: Group DM/P and Group P. All patients were assessed at baseline, and 90 and 180 days after receiving NSPT. The parameters evaluated included HbA1c levels, plaque index (PI), probing pocket depth (PPD), clinical attachment level (CAL), and bleeding on probing (BoP). Statistical analysis was performed with a significance level set at α = 5%. Results: There were significant differences in HbA1c levels between the DM/P and P groups at baseline, 90, and 180 days, as expected. Importantly, HbA1c levels did not change after NSPT. Group P showed a significant reduction in both PI and BoP values at 90 and 180 days (p < 0.05). In contrast, group DM/P demonstrated a significant increase in the percentage of sites with PPD ≥ 5mm at 180 days (p < 0.05). Additionally, group P exhibited an increase in sites with PPD ≤ 4mm and a decrease in sites with PPD ≥ 5mm at both 90 and 180 days (p < 0.05). Conclusions: Our findings suggest that DM may compromise the effectiveness of NSPT, potentially hindering favorable outcomes during the follow-up period.

The repeated application of herbicides has led to the development of herbicide resistance. Models are useful for identifying key processes and understanding the evolution of resistance. This study developed a spatially explicit model at a landscape scale to examine the dynamics of Lolium rigidum populations in dryland cereal crops and the evolution of herbicide resistance under var-ious management strategies. Resistance evolved rapidly under repeated herbicide use, driven by weed fecundity and herbicide efficacy. Although fitness costs associated with resistant plants re-duced resistance evolution, they did not affect the speed of spread. The most effective strategies to slow resistance involved diversifying cropping sequences (e.g., crop rotation) and the herbicide applications (e.g., rotating different herbicide modes of action). Pollen flow was the main disper-sal vector, with seed dispersal also contributing significantly. Strategies limiting seed dispersal effectively decreased resistance spread. However, the use of a seed-catching device at harvest could unintentionally enrich resistance in the area. It would be beneficial to optimise the move-ment of harvesters between fields. The model presented here is a useful tool that may assist in the exploration of novel management strategies within the context of site-specific weed management at the landscape scale, as well as in the advancement of our understanding of resistance dynamics.

In this study, the physical properties of briquettes produced from two different biomass feedstocks (sawdust and date palm trunk) and different plastic wastes were investigated, without using any external binding agent. The biomass feedstocks were blended with different ratios of two WEEE plastics (halogen-free wire and print circuit boards (PCB)) and automotive shredder residues (ASR). The briquettes production is studied at different waste proportions (10-30%), pressures (22-67 MPa) and temperatures (room-130 ˚C). Physical properties as density and durability rating were measured, usually increasing with temperature. Palm trunk gave better results than sawdust in most cases, due to its moisture content and the extremely fine particles that are easily obtained.

Considerable amounts of agro-industrial by-products are discarded or burnt as fuel every year. However, they can be utilized as a valuable source of fiber, phenolics and other useful compounds such as antioxidants. The profile of beneficial compounds can be affected by genotype, locality, orchard management and productive season, adding or decreasing the bioactive potential of by-products. In this study, hazelnut (Corylus avellana L.) and walnut (Juglans regia L.) nutshells were investigated for their fiber content and antioxidant capacity as valorized by-products for the industry. Determinations (ORAC, TPC and color asses) were performed in hazelnut and walnut orchards located in Southern Chile during three consecutive seasons (2020/21; 2021/22 and 2022/23). Analyses of oxygen radical absorbance capacity (ORAC) in nutshells showed the highest ORAC from both species in the season 2020/21 (3217 µmol TE g1DW for hazelnut shells and 4663 µmol TE g DW1 for walnut shells), while variability in the consecutive seasons was lower for hazelnut than in walnut. Total phenolic content in hazelnut shells was positively correlated with L* (R: 0.883) and E (R: 0.924) during 2020/21 season, also with L* for 2022/23 (R: 0.907). While ORAC was negatively correlated with L* (R: 0.922) in 2021/22. In addition, morphological and structural features of both nutshells examined by Scavenging Electron Microscopy (VP-SEM) and Confocal Scavenging Laser Microscopy (CSLM) revealed differential tissue distribution and accumulation patterns of both cellulose and lignin. On the other hand, photo-colorimetric values were determined for both shells and corresponding seasons, and non-significative differences were found both shells and among seasons Finally, these results provide insight into the physicochemical characteristics of two shell types which should be considered together with antioxidant capacity in their valorization as a residual material.

This paper outlines the ongoing development of a specialised mobile application to address the mental health needs of vulnerable populations in the European Union (EU). Conducted as a mixed-methods research within two EU Science and Technology Cooperation Actions, the study prioritises stakeholder feedback to identify features for initial testing and strategies to improve application uptake, using critical digital health analysis. With a focus on marginalised groups such as refugees, migrants and socio-economically disadvantaged individuals, the application aims to provide an accessible and culturally sensitive platform for mental health support, integrating evidence-based interventions such as cognitive behavioural techniques and mindfulness exercises. Key features include multilingual support, habit tracking, personalised recommendations for support and services, and real-time crisis intervention. Collaboration with stakeholders and ongoing rigorous usability testing are driving the refinement process to ensure usability, acceptability and effectiveness, underscoring the importance of user engagement in technology-based mental health interventions in the EU context and highlighting the importance of collaborative science and technology for societal benefit.

Plastid genomes are in general highly conserved given their slow evolutionary rate, thus large changes in their structure are unusual. However, when specific rearrangements are present, they are often phylogenetically informative. Asteraceae is a highly diverse family whose evolution is long driven by polyploidy (up to 48x) and hybridisation, both processes usually complicating systematic inferences. In this study, we have generated one of the most comprehensive plastome-based phylogenies of family Asteraceae, providing information about the structure, genetic diversity, and repeat composition of these sequences. By comparing the whole plastome sequences obtained, we confirmed the double inversion located in the long single copy region, for most of the species analysed (with the exception of basal tribes), a well-known feature for Asteraceae plastomes. We also show that genome size, gene order and gene content are highly conserved along the family. However, species representative of the basal subfamily Barnadesioideae -as well as in the sister family Calyceraceae - are lacking the pseudogene rps19 located in one inverted repeat. The phylogenomic analysis conducted here, based on 63 protein-coding genes, 30 transfer RNA genes and 21 ribosomal RNA genes from 36 species of Asteraceae, are overall consistent with the general consensus for the family’s phylogeny, while resolving the position of tribe Senecioneae and revealing some incongruences at tribe level between reconstructions based on nuclear and plastid DNA data.

There are different ways to analyse energy absorbance (EA) in the human auditory system. In previous research, we developed a complete finite element model (FEM) of the human auditory system. In this mentioned work, the external auditory canal (EAC), middle ear, and inner ear (spiral cochlea, vestibule, and semi-circular canals) were modelled based on human temporal bone histological sections. Multiple acoustic, structure and fluid-coupled analyses were conducted using the FEM to perform harmonic analyses in the 0.1–10 kHz range. Once the FEM had been validated with published experimental data, the FEM numerical results were used to calculate the EA or energy reflected (ER) by the tympanic membrane. This EA was also measured in clinical audiology tests which were used as a diagnostic parameter. A mathematical approach was developed to calculate the EA and ER, with numerical and experimental results showing adequate correlation up to 1 kHz. Another published FEM had adapted its boundary conditions to replicate experimental results. Here, we recalculated those numerical results by applying the natural boundary conditions of human hearing and found that the results almost totally agreed with our FEM. This boundary problem is frequent and problematic in experimental hearing test protocols: the more invasive they are, the more the results are affected. One of the main objectives of using FEMs is to explore how the experimental test conditions influence the results. Further work will still be required to uncover the relationship between the middle ear structure and EA to clarify how to best use FEMs. Moreover, the FEM boundary conditions must be more representative in future work to ensure their adequate interpretation.

This study focuses on the creation and implementation of a platform to improve personal financial management for scholarship students of the National Program of Scholarships and Educational Credit (Pronabec) in Peru. Using a mixed methodology that combines qualitative and quantitative techniques, the effectiveness and user satisfaction with the platform were evaluated. The results indicated that 50\% of users found the tool useful, 55\% considered it easy to use, 70\% reported a positive impact on their personal budget planning, and 85\% expressed high overall satisfaction. In addition to providing tools for financial recording and analysis, the platform promotes financial education among its users, significantly contributing to improving their financial management skills.

The supply chain has incorporated products by putting them into hair scarfs. This study introduces the use of mini chips in health and beauty products and can reduce fatigue through enhanced sleep patterns. The mini chip could be placed in the scarf and used as a prototype. RFID technology provides the supply chain with specific information that is used to identify products and make communication easier. (Muhammad, et. al. 2013) This paper presents a new tool herein referred to as a scarf prototype which is developed to analyse EMG (electromyogram), ECG (electrocardiography), EEG (electroencephalogram), and EOG (electro-oculogram) signals that focuses in the area of sleep disorders. The mini chips used can be used to determine a solution for sleep disruption by using automated analytics. This could lead to improvement in our understanding of sleep disruption and overall sleep physiology. Automated technology allows repeated measurements, evaluation of sleep patterns, and provide suggestions to improve a person’s quality of sleep. This analysis compares the use of polysomnography and the scarf prototype. The analytics provide models and shows correlation between variables, such as EMG, ECG, EEG, and EOG. This study shows that the results from the scarf prototype is just as reliable as the original method, polysomnography.

Top-down models are defined by hardware architects to provide information on the utilization of the different hardware components. The target is to isolate the users from the complexity of the hardware architecture while giving them insight into how efficiently the code is using the resources. In this paper, we explore the applicability of 4 top-down models defined for different hardware architectures powering state-of-the-art HPC clusters (Intel Skylake, Fujitsu A64FX, IBM Power9, and Huawei Kunpeng 920) and propose a model for AMD Zen 2. We study a parallel CFD code used for scientific production to compare these 5 Top-Down models. We evaluate the level of insight achieved, the clarity of the information, the ease of use, and the conclusions that each one allows us to reach.

Transcriptional regulation constitutes a key step in gene expression regulation. Myocyte enhancer factor 2C (MEF2C) is a transcription factor of MADS box family involved in the early development of several cell types including muscle cells. Over the last decade a novel layer of complexity modulating gene regulation is emerging as non-coding RNAs have been identified, impacting in both transcriptional and post-transcriptional regulation. microRNAs represent the most studied and abundantly expressed subtype of small non-coding RNAs and their functional role have been widely documented. On the other hand, our knowledge on the transcriptional and post-transcriptional regulatory mechanisms that drive microRNA expression is still incipient. We recently demonstrated that MEF2C is able to transactive the long, but not short, regulatory element upstream of miR-23a-miR-27a-miR-24-2 transcriptional start site. However, MEF2C over-expression and silencing, respectively, displayed distinct effects on each of the miR-23a-miR-27a-miR-24-2 mature cluster members, without affecting pri-miRNA expression levels, supporting thus additional MEF2C-driven regulatory mechanisms. Within this study we demonstrated a complex post-transcriptional regulatory mechanisms directed by MEF2C in the regulation of miR-23a-miR-27a-miR-24-2 cluster members, distinctly involving different domains of the MEF2C transcription factor and the physical interaction with pre-miRNAs and RNA interacting proteins such as Ksrp, HnRNPa3 and Ddx17.

The utilization of eco-fonts for office printing is a sustainable, “green” printing concept, which has obvious economic benefits. As a result, it has a significant effect on environmental sustainability. This practice's fundamental problem is the decreased quality of text printed using eco-fonts compared to those printed with regular fonts. The aim of this research is eco-font efficiency estimation, i.e. determination of toner usage reduction level of inkjet-printed documents typed with this font type, as well as estimation of the extent humans perceive differences between text printed with eco-font and the one printed by its “non-eco“ equivalent. Combining the instrumental measuring method and digital image analysis, it was found that this simple principle (eco-font utilization) enables substantial toner usage reduction for an inkjet printing system. At the same time, a visual test showed that the visual experience of text printed using eco-font was sufficient. In addition, awareness of the benefits that eco-font utilization brings, change users’ attitude towards eco-font quality. The concept of removing the black pixel from this commonly used Thai font has a great potential for the sustainability printing process, and this simple solution could be applied to other languages as part of the GIT campaign.

We compare the well known Rayleigh-Ritz variational method (RRVM) with a recently proposed approach based on supersymmetric quantum mechanics and the Gram-Schmidt orthogonalization method (SSQMGS). We apply both procedures to a particular class of double-well harmonic oscillators that had been conveniently chosen for the application of the latter approach. The RRVM eigenvalues converge smoothly from above providing much more accurate results with less computational effort. Present results show that the unproved SSQMGS upper bounds do not hold.

Generative AI has gained enormous interest nowadays due to new applications like chatGPT, DALL E, Stable Difussion and Deep Fake. Particularly DALL E, Stable Difussion and others (Adobe Firefly, ImagineArt...) are able to create images from a text prompt and are also able to recreate real photographs. Due to this fact, intense research has arisen to create new image forensics applications able to distinguish between real captured images and videos and artificial ones. Detecting forgeries made with Deep Fake is one of the most researched issues. This paper is about another kind of forgery detection. The purpose of this research aims to detect photo realistic AI created images versus real photos coming from a physical camera. For this purpose, techniques that perform a pixel level feature extraction are used. First one is Photo Response Non-Uniformity (PRNU). PRNU is a special noise due to imperfections on the camera sensor that is used for source camera identification. The underlying idea is that AI images will have a different PRNU pattern. Second one is Error level analysis (ELA). This is other type of feature extraction traditionally used for detecting image editions. In fact, ELA is being used nowadays by photographers to detect manually AI created images. Both kinds of features are used to train Convolutional Neural Networks to differentiate between AI images and real photographs. Good results are obtained achieving accuracy rates over 95%. Both extraction methods are carefully assessed by computing precision/recall and F1-score measurements.

The enzymatic activities of bacterial isolates have been widely studied, but a spatial distribution of this activity is rarely focused. New antibiotic-producing microorganisms can be discovered in a more efficient manner if spatial statistical techniques are applied to the distribution of the activity of bacterial isolates in different terrains. This study is focused to generate a series of maps illustrating the spatial distribution of different soil parameters and the inhibition against relative-safe pathogens (like Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Salmonella, Pseudomonas fluorencens and Enterobacter cloacae) in an urban park in València (Spain). This spatial data has demonstrated a higher proportion of isolates was specifically allocated. This routine of data presentation is valuable for understanding bacterial population dynamics at a local level.

This paper presents a Multilayer Perceptron and Support Vector Machine algorithms approach to predict the number of COVID19 infections in different countries of America. It intends to serve as a tool for decision-making and tackling the pandemic that the world is currently facing. The models were trained and tested using open data from the European Union repository where a time series of confirmed contagious cases was modeled until May 25, 2020. The hyperparameters as number of neurons per layer were set up using a tabu list algorithm. The countries selected to carry out the study were Brazil, Chile, Colombia, Mexico, Peru and the United States. The metrics used are Pearson's correlation coefficient (CP), Mean Absolute Error (MAE), and Mean Percentage Error (MPE). For the testing stage we obtained the following results: Brazil, CP=0.65, MAE=2508 and MPE=17%; Chile, CP=0.64, MAE=504, MPE=16%; Colombia, CP=0.83, MAE=76, MPE=9%; Mexico, CP=0.77, MAE=231, MPE=9%; Peru, CP=0.76, MAE=686, MPE=18% and the United States of America, CP=0.93, MAE=799, MPE=4%. This resulted in powerful machine learning tools although it is necessary to use specific algorithms depending on the data and the stage of the country’s pandemic.

Asthma is a significant public health concern. This study identified the provinces with the highest morbidity and mortality rates due to asthma among the working-age population (15-69 years) in the Republic of Ecuador. The secondary objective was to explain the possible differences attribut-able to occupational exposure. This nationwide ecological and exploratory study was conducted in 24 provinces between 2016 and 2019. Government databases were used as sources of infor-mation. Standardized rates were calculated for codes the J45 and J46. The hospitalization mor-bidity rate for asthma decreased from 6.51 to 5.76 cases per 100,000 working-age population, and the mortality rate has consistently been low and stable from 0.14 to 0.15 deaths per 100,000 working-age population. Geographic differences between the provinces were evident. The risk of hospitalization and death due to asthma was higher in the Pacific coast (five provinces) and the Andean region (two provinces). The high rates observed in provinces with greater agricultural and industrial development could be the main determinants of national heterogeneity and could act as occupational risk factors. The contribution of occupational hazards in each province should be examined in depth through ad hoc studies. These findings provide valuable information for creating public policies aimed at promoting and safeguarding the respiratory health of the popu-lation, particularly that of workers.

To mitigate pyrethroid resistance in mosquito vectors of emerging and re-emerging human pathogens, there is an urgent need to discover insecticides with novel modes of action. Natural alternatives, such as extracts derived from plants, may serve as substitutes for traditional synthetic insecticides if they prove to be sustainable, cost-effective, and safe for non-target organisms. Hemp (Cannabis sativa) is a sustainable plant known to produce various secondary metabolites with insecticidal properties, including terpenoids and flavonoids. The goal of this study was to assess the larvicidal activity of hemp leaf extract on 1st instar mosquito larvae from both pyrethroid-susceptible (PS) and pyrethroid-resistant (PR) strains of Aedes aegypti Another goal was to identify which components of the extracts were responsible for any observed larvicidal activity. We found that methanol extract of hemp leaves induced similar concentration-dependent larvicidal activity against PS (LC50: 4.4 ppm) and PR (LC50: 4.3 ppm) strains within 48 hours. Partitioning of the dried leaf extract between methanol and revealed that full larvicidal activity was restricted to the methanol fraction. Analysis of this fraction by gas chromatography-mass spectrometry and nuclear magnetic resonance showed it to be dominated by cannabidiol (CBD). Larvicidal assays using authentic CBD confirmed this compound was primarily responsible for the toxicity of hemp leaf extract against both strains. We conclude that hemp leaf extracts and CBD have the potential to serve as viable sources for the development of novel mosquito larvicides.

This paper investigates the effects of air void topology on hydraulic conductivity in asphalt mixtures with porosity in the range 14%-31%. Virtual asphalt pore networks were generated using the Intersected Stacked Air voids (ISA) method, with its parameters being automatically adjusted by the means of a differential evolution optimisation algorithm, and then 3D printed using transparent resin. Permeability tests were conducted on the resin samples to understand the effects of pore topology on hydraulic conductivity. Moreover, the pore networks generated virtually were compared to real asphalt pore networks captured via X-ray Computed Tomography (CT) scans. The optimised ISA method was able to generate realistic 3D pore networks corresponding to those seen in asphalt mixtures in term of visual, topological, statistical and air void shape properties. It was found that, in the range of porous asphalt materials investigated in this research, the high dispersion in hydraulic conductivity at constant air void content is a function of the average air void diameter. Finally, the relationship between average void diameter and the maximum aggregate size and gradation in porous asphalt materials was investigated.

In this paper, the power quality of interconnected microgrids is managed using a Model Predictive Control (MPC) methodology which manipulates the power converters of the microgrids in order to achieve the requirements. The control algorithm is developed for the microgrids working modes: grid-connected, islanded and interconnected. The results and simulations are also applied to the transition between the different working modes. In order to show the potential of the control algorithm, a comparison study is carried out with classical Proportional-Integral Pulse Width Modulation (PI-PWM) based controllers. The proposed control algorithm not only improves the transient response in comparison with classical methods but also shows an optimal behavior in all the working modes, minimizing the harmonics content in current and voltage even with the presence of non-balanced and non-harmonic-free three-phase voltage and current systems

Plant male sterility refers to the failure in the production of fertile pollen. It occurs spontaneously in natural populations and may be caused by genes encoded in the nuclear (genic male sterility; GMS) or mitochondrial (cytoplasmic male sterility; CMS) genomes. This feature has great agronomic value for the production of hybrid seeds and has been widely used in crops, such as corn, rice, wheat, citrus, and several species of the family Solanaceae. Mitochondrial genes determining CMS have been uncovered in a wide range of plant species. The modes of action of CMS have been classified in terms of the effect they produce in the cell, which ultimately leads to a failure in the production of pollen. Male fertility can be restored by nuclear-encoded genes, termed restorer-of-fertility (Rf) factors. CMS from wild plants has been transferred to species of agronomic interest through somatic hybridization. Somatic hybrids have also been produced to generate CMS de novo upon recombination of the mitochondrial genomes of two parental plants or by separating the CMS cytoplasm from the nuclear Rf alleles

In this study, we propose an augmentation method for machine learning based on relabeling data in caregiving and nursing staff indoor localization with Bluetooth Low Energy (BLE) technology. Indoor localization is used to monitor staff to patient assistance in caregiving and to gain insights into workload management. However, improving accuracy is challenging when there is a limited amount of sensor data available for training. In this paper, we propose a data augmentation method to reuse the Received Signal Strength (RSS) from different sensors by relabeling to the sensors with less samples resolving data imbalance. Standard deviation and Kullback-Leibler divergence between minority and majority class are used to measure signal pattern to find matching sensors to relabel. By matching sensors between classes, two variation of relabeling are implemented specifically full and partial matching. The performance is evaluated using real world dataset we collected for five days in a nursing care facility installed with 25 BLE beacons. Random Forest model is utilized for location recognition, and performance is compared using the weighted F1-score to account for class imbalance. By increasing the sensor data with our proposed relabeling method for data augmentation, we achieved higher minority class F1-score as compared to augmentation with Random Sampling, Synthetic Minority Oversampling Technique (SMOTE) and Adaptive Synthetic Sampling (ADASYN). Our proposed method utilizes collected sensor data by leveraging majority class samples. Full matching demonstrated a 6 to 8% improvement from the original baseline overall weighted F1-score.

Annually, an estimated 13-26 million newborns need respiratory support and 2-3 million newborns need extensive resuscitation, defined as chest compression and 100% oxygen with or without epinephrine in the delivery room. Despite such care, there is a high incidence of mortality and short-term neurologic morbidity. The poor prognosis associated with receiving chest compression alone or with medications in the delivery room raises questions as to whether improved cardiopulmonary resuscitation methods specifically tailored to the newborn could improve outcomes. This review discusses the current recommendations, mode of action, different compression to ventilation ratio, continuous chest compression with asynchronous ventilations, chest compression and sustained inflation optimal depth, and oxygen concentration during cardiopulmonary resuscitation.

In this paper, a new anode environmentally friendly for hydrogen production was developed based on 430 stainless steel with an electrodeposited cobalt layer. The novelty of this work is the cobalt source once the electrodeposition bath was obtained from recycling of spent Li-ion batteries cathode with composition LiCoO₂. The electrodeposited cobalt behaves as supercapacitor in KOH 1M. In the linear voltammetry in KOH 1M, when the overpotential reaches 370 mV, the anodic density current for 430 SS/Co is 19 mA cm⁻². Thus, the anode developed in this paper achieves the double of density current with half of production cost if compared with 316SS. Moreover the anode construction described in this paper is an excellent option for Li- ion battery recycling.

In this paper the application of recycled Li-ion batteries spent cathode (LIB-SC) combined with NaHCO₃/H₂O₂ system is presented for the first time in the literature as an alternative for degradation of potentially toxic organic molecules. The model pollutant choice was methylene blue molecule. The spent cathode composition corresponds to LiCoO₂, which was proved by the XRD and EDX. Regarding the decolorization of methylene blue solution, the addition of NaHCO₃ in comparison with only H₂O₂ reduces the complete decolorization time in 96%. This reduction occurs because the radical CO₃ is more stable than OH. In this way, the application the system proposed in this article is aimed at solving two major global problems: the disposal of cell phone batteries and the pollution of liquid effluents.

Background: The conformation of the recipient site for an inlay graft presents an increased contact with the parent bone compared to the onlay graft. This might favor bone growth within the inlay compared to the onlay grafts. Hence, the objective of this study was to compare bone incorporation and remodeling process of xenogeneic en bloc grafts, placed using two bone grafting techniques, i.e., onlay vs. inlay. Methods: In this prospective, randomized, split-mouth study (test and control sides in the same animal), two bone grafting techniques were comparatively evaluated on the lateral aspect of the rabbit mandibles. One side was prepared with perforations (onlay site), whereas the other side was prepared with trephines and drills to obtain a wide (7 mm) standardized recipient site (inlay site). A xenogeneic bone block was fixed in the center with a titanium screw in both sides of the mandible and covered with a collagen membrane. Two healing periods were applied in the study: 2 and 10 weeks of healing. Results: after 2 weeks of healing, the mean percentage of new bone was 10.4% and 23.3% at the onlay and inlay grafts, respectively (p=0.022). After 10 weeks of healing, new bone increased to 13.2% and 25.4%, respectively (p=0.080). In this period of healing, the inlay grafts presented new bone percentage >20% in all regions examined while the onlay graft presented a lower percentage in the most external regions of the graft. Conclusion: The percentage of new bone increased faster and was higher in the inlay compared to the onlay grafts. The composition of the grafts allowed new bone to reach the most peripheral regions in both graft groups, even though it was higher in the inlay group. A marginal closure of the defects by newly formed bone was observed in the inlay group.

This study presents a strategic approach to developing applications focused on implementing Large Language Models using the Langchain framework in Python. Three language models are highlighted: GPT-3.5 (turbo mode), LLaMA 2, and Vicuna 7B, each with their distinctive features and capabilities. The methodology used is described in detail, including data extraction from medical reports using zero-shot prompting data extraction techniques, interaction with language models, and structured storage of results. The performance of the models in data extraction is evaluated, presenting metrics such as precision, recall, and F1 score. The results demonstrate high model capability in extracting information, although areas for improvement are identified, particularly in data extraction precision. In conclusion, the efficacy of the models in extracting information from medical histories is not considerably acknowledged, with an emphasis on the importance of improving precision and increasing the volume of trained data for future research in healthcare digitalization.

Neck lymphangiomas are rare, benign congenital malformations that predominate in childhood. Most present before the age of two. There are no risk factors related to sex, ethnic origin or predominance on either side, and they can occur in any anatomical location, although the most frequent is in the head and neck. The clinical presentation depends on its location. The most frequent symptom is the existence of a painless mass that grows slowly. Available therapeutic tools include surgery, systemic treatment, and injection of sclerosing agents.

In the last years, different biotechnological approaches were developed to reduce the indiscriminate use of chemical fertilizers and pesticides and enhance plant growth and health. The most attractive, safe, and environmentally mild alternatives include those based on plant beneficial microorganisms. After a long period of studies on isolation, selection, and characterisation of plant-beneficial microorganisms, the main lines of research have been oriented to optimising the fermentation processes to produce high-quality and large volumes of biomass/spores and their further formulation. However, further well-structured schemes for improvement of all main steps of the production of bio-formulates should be developed following the ideas based on “healthy soil-healthy plants-healthy humans”.

There is a lack of studies on the level of stress and health of families of workers in road transport. This study aimed to evaluate the perceived stress level and Family Effectiveness of family members of road transport workers. A quantitative study was carried out with family members of road transport workers in the southern region of Brazil. For the data collection, a sociodemographic form, the Perceived Stress Scale (PSS), and the Evaluation of Family Effectiveness Strategies were used. The data were analyzed by simple frequency, Spearman correlation coefficient (ρ) (p < 0.05), and descriptive analysis from the perspective of the Systemic Organization. 49 family members of road transport workers were participants. Perceived stress was higher in family members who had more than nine years of schooling, the targets of Control and Growth were higher in the evaluation of Family Effectiveness. The Control target was also higher in families with more than three people. The Coherence dimension had higher levels in families with health problems and whose income was less than $792.00 US dollars per month. In the Individuation dimension, income over $792.00 had better results. The Maintenance dimension of the system was higher in families whose drivers’ activity was as an intercity driver, as well as in the Stability target. In conclusion, the social factors such as schooling, income, diseases, type of worker activity in road transport, and number of people in the family influenced perceived stress and Family Effectiveness, which demonstrates the need to increase the promotion of health care of the families of road transport workers.

Flowering time is a critical stage for crop development as it regulates the ability of plants to adapt to an environment. To understand the genetic control of flowering time, a genome wide association study (GWAS) was conducted to identify the genomic regions associated with the control of this trait in durum wheat (Triticum durum Desf.). A total of 96 landraces and 288 modern lines were evaluated for days to heading, growing degree days, and accumulated day length at flowering across 13 environments spread across Morocco, Lebanon, Mauritania, and Senegal. These environments were grouped into four pheno-environments based on temperatures, day length and other climatic variables. Genotyping with 35K Axiom array generated 7,652 polymorphic SNPs in addition to 3 KASP markers associated to known flowering genes. In total, 34 significant QTLs were identified in both landraces and modern lines. Some QTLs had strong association with already known regulatory photoperiod genes, Ppd-A and Ppd-B and vernalization genes Vrn-A1, and Vrn3. However, these loci explained only 5 to 20% of variance for days to heading. Seven QTLs overlapped between the two germplasm groups in which Q.ICD.Eps-03 and Q.ICD.Vrn-17 consistently affected flowering time in all the pheno-environments, while Q.ICD.Eps-11 and Q.ICD.Ppd-12 were significant only in two pheno-environments and the combined analysis across all environments. These results help clarify the genetic mechanism controlling flowering time in durum wheat and show some clear distinctions to what is known for common wheat (Triticum aestivum L.)

Synthesis of nickel oxide nanoparticles (NiO NPs) is a low cost and ecofriendly route that brings great benefits over chemical and physical methods of synthesis. Our approach consisted of using aqueous extracts from treated waste of Manihot Esculenta (Cassava) as reducing, stabilizing and capping agents for the synthesis of NiO NPs. The results proved this approach might be a viable alternative. Extracts were mixed during 30 minutes with Ni(NO3)2.6H2O leading to NPs formation. NiO NPs were characterized through FTIR, XRD, TEM and Raman spectroscopy. NiO NPs showed different shapes and sizes around 5-10 nm in agreement with the particle size calculated by XRD Scherrer equation.

Background: Waterborne diseases pose a significant global public health threat, compelling enhanced comprehensive surveillance. This study investigates the current infectious disease and antimicrobial resistance (AMR) surveillance systems, including wastewater and environmental surveillance (WES), in three sub-Saharan African countries: Tanzania, Burkina Faso, and the Democratic Republic of the Congo (DRC). The three countries have their specificities regarding wastewater networks and logistic systems. So, emphasizing the need to strengthen existing disease surveillance, the paper advocates for incorporating WES systems specifically designed for countries' context to monitor waterborne and re-emerging pathogens, as well as AMR.Methods: National workshops were conducted to assess the current clinical and environmental surveillance systems and identify priority pathogens for new environmental monitoring. Data were collected through surveys from experts in academia, research, policy, and healthcare. Results: Prioritized pathogens for WES include waterborne (poliovirus, Salmonella Typhi, Vibrio cholerae), respiratory (influenza A&B, SARS-CoV-2), other (Measles and Rubella, Mycobacterium tuberculosis). Recommended AMR pathogens include drug-resistant Mycobacterium tuberculosis, Salmonella spp., methicillin-resistant Staphylococcus aureus, and extended-spectrum beta-lactamase and carbapenemase-producing E. coli. Tanzania, Burkina Faso, and the DRC employ DHSI2-based centralized electronic systems for clinical data collection, complemented by Excel and paper-based registries. The WES approach is commonly employed for monitoring poliovirus and rarely for AMR and other pathogens. Discussion and conclusions: WES is a valuable tool for early detection of locally circulating human-derived pathogens, aiding in outbreak detection, data-driven epidemic response, and prevention. The availability of WES results underscores the importance of effective sanitation for safeguarding human, animal, and environmental health. WES is a pivotal tool for integrated risk management, preventing waterborne outbreaks, protecting drinking water sources, and ultimately gaining various UN Sustainable Development Goals. The study highlights the importance of customized WES systems in line with each country's context, emphasizing localized approaches for effective monitoring of waterborne pathogens and AMR.

"Hidden hunger", the deficiency of important mineral micronutrients, affects more than 2 billion people globally. Adolescence is unquestionably a period of nutritional risk, given the high nutritional requirements for growth and development, erratic or capricious diets and the increased consumption of snacks. This study applied the rational food design approach to obtain micronutrient-dense biscuits by combining chickpea and rice flours to achieve an optimal nutritional profile, crunchy texture and appealing flavour. The perception of 33 adolescents of the suitability of such biscuits as a mid-morning snack was examined. Four biscuits were formulated, with different ratios of chickpea and rice flours (CF:RF): G100:0, G75:25, G50:50 and G25:75. Nutritional content, baking loss, acoustic-texture and sensory analyses were carried out. On average, the mineral content of biscuits with the CF:RF ratio of 100:0 doubled compared with the 25:75 formula. The dietary reference values for iron, potassium and zinc reached 100% in the biscuits with CF:RF ratios of 50:50, 75:25 and 100:0, respectively. The analysis of mechanical properties revealed that samples G100:0 and G75:25 were harder than the others. Sample G100:0 showed the highest sound pressure level (Smax). Sensory analysis showed that increasing the proportion of CF in the formulation augments the grittiness, hardness, chewiness and crunchiness. Most of the adolescents (72.7%) were habitual snack consumers; 52% awarded scores ≥ 6 to biscuit G50:50 for its overall quality, 24% described its flavour as "biscuit" and 12% as "nutty". However, 55% of the participants could not pinpoint any dominant flavour. In conclusion, it is possible to design nutrient-dense snacks that meet the micronutrient requirements and sensory expectations of adolescents by combining flours naturally rich in micronutrients.

Coronavirus is a disease caused by a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which emerged as a global pandemic in 2019 from Wuhan, China. Since its emergence, it has caused immense suffering to human life, 6.27 million lives have been lost, movement curtailed and social dynamics disrupted. The golden standard for getting samples for SARS-CoV-2 detection is through oral- nasopharyngeal swab, this method of sample collection is invasive and uncomfortable, thus stigmatized the general population, and thereby impeded the progress of controlling the spread through mass testing. Being a contact disease, mechanisms to encourage mass testing is key to reduce the spread. This study thus developed a complimentary sample type to test for SARS-CoV-2, the use of human feces. Fecal samples were collected from 100 asym-symptomatic individuals suspected to be infected with COVID-19, virus RNA was then extracted and profiled through Real Time Polymerase Chain Reaction (RT-qPCR). The antigen rapid diagnostic test revealed high positivity rate of 44%, but the real time polymerase chain reaction results on nasopharyngeal and fecal samples revealed a significant variation, high number of the patients tested positive with stool samples compared to the nasopharyngeal swabs, with 43 and 37%, respectively. SARS-CoV-2 virus was detected in both symptomatic and asymptomatic individuals; however, the symptomatic registered a higher positivity of 25% compared to 20% among the asymptomatic patients. Vaccination only lowered the risk of infection, fully and partially vaccinated lowered the infection level to 10% compared to 20% among the unvaccinated. Finally, gender parity in relation to COVID19 was evaluated, more females (56%) compared to males were recruited in this study, out of which (20; 43.4%) were positive, and 26 (56.6%) were negative based on fecal RT-qPCR outcomes. Based on the outcome of this study, rapid diagnostic test (Ag-RDT) however cheap and or fast does not provide accurate information, moreover, the virus does not stay longer within the Oro-nasopharyngeal region, thus the invalid or negative results, thus use of feces should be adopted as a confirmatory test to ascertain the COVID19 status of an individual.

Electrical Resistance Tomography (ERT) has been used in the literature to monitor the gas-liquid separation. However, the image reconstruction algorithms used in the studies take a considerable amount of time to generate the tomograms, which is far above the time scales of the flow inside the inline separator and, as a consequence, the technique is not fast enough to capture all the rele-vant dynamics of the process, vital for control applications. This article proposes a new strategy based on the physics behind the measurement and simple logics to monitor the separation with a high temporal resolution by minimizing both the amount of data and the calculations required to reconstruct one frame of the flow. To demonstrate its potential, the electronics of an ERT system are used together with a high-speed camera to measure the flow inside an inline swirl separator. For the 16-electrode system used in this study, only 12 measurements are required to reconstruct the whole flow distribution with the proposed algorithm, 10x less than the minimum number of measurements of ERT (120). In terms of computational effort, the technique was shown to be 1000x faster than solving the inverse problem non-iteratively via the Gauss-Newton approach, one of the computationally cheapest techniques available. Therefore, this novel algorithm has the potential to achieve measurement speeds in the order of 104 times the ERT speed in the context of inline swirl separation, pointing to flow measurements at around 10kHz while keeping the aver-age estimation error below 6 mm in the worst case scenario.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction and communication, anxiety, hyperactivity, and restricted interest for specific subjects. In addition to the genetic factors, multiple environmental factors have been related to the development of ASD. Animal models can serve as crucial tools for understanding the complexity of ASD and identifying potential therapeutic strategies. In this study, a chemical model of ASD has been developed in zebrafish by exposing embryos to valproic acid (VPA) from 4 to 48 hours post-fertilization. After the exposure, embryos were transferred to fish water and the effects on behavior and neurotransmitters profile were analyzed at both larval and adult stages. Larvae from VPA-treated embryos showed hyperactivity and decreased visual and vibrational escape responses, as well as an altered neurotransmitters profile, with increased glutamate and decreased acetylcholine and norepinephrine levels. Adults from VPA-treated embryos exhibited impaired social behavior characterized by larger shoal sizes and a decreased interest for their conspecifics. Neurotransmitter analysis revealed a significant decrease in dopamine and GABA levels in the brain. These results support the interest of this model in the study of ASD.

The work and life routine of long-haul truck drivers involves the use of truck stops and rest areas to meet their basic human needs. These extensions of their workspaces while on the road, do not always offer adequate physical structures and services that drivers need for optimal health. Aim: To evaluate long-haul truck drivers’ perceptions about the services of food, safety, physical activity, rest and personal hygiene offered at truck stops and rest areas in Brazil. Method: Quantitative study conducted with long-haul truck drivers from the Southern region of Brazil. For data collection, a sociodemographic questionnaire and a Likert scale on food, rest, personal hygiene, safety and physical activity services were used, offered in general at the truck stops and rest areas along Brazilian roads, from March to August 2023. The data were analyzed with simple frequency descriptive statistics. Results: 175 long-haul truck drivers participated, 70.29% declared that the services of the truck stop and rest areas were charged; more than half (53.59%) of the professionals evaluated the rest service as “good” or “excellent”; the food services, was “good” or “excellent” for 42.24% of the drivers. The spaces for physical activities were the worst evaluated as “bad” or “terrible”, by 41.61%, followed by bathroom service (28.42%) and safety (34.24%), evaluated as “bad” or “terrible”. Conclusions: In the perception of long-haul truck drivers, the rest and feeding services had better evaluations, on the other hand, the services of bathroom, safety and physical activity presented worse evaluations. The perception of drivers demonstrates the lack of investments to improve basic services such as personal hygiene, safe environment and physical exercises, fundamental to the health of the worker, aiming to reduce vulnerability, sedentary lifestyle, and meeting the basic human needs of long-haul truck drivers.

Primary Health Care is crucial in the healthcare system, being the first level of contact with health services for users and patients to take action using the available resources. Patient care units are created to facilitate direct user participation through the circuit of complaints, grievances, and suggestions, allowing the analysis of the population's unmet expectations and needs. To study complaints and grievances regarding the treatment and information received by users in the Santiago and Barbanza healthcare area during the year 2022. A descriptive cross-sectional study was conducted, in which complaints filed by patients in the year 2022 in the Santiago and Barbanza healthcare area were analyzed. A total of 326 users who filed a total of 512 complaints were studied in the year 2022, with 358 (70.0%) related to treatment/information. The mean age was 33.5±16.2 years. 72.4% were women (n=236). A Pearson correlation was performed to establish whether there was a dependence between the number of healthcare visits in both primary care and hospital settings in 2022 and the number of complaints filed in the same year. Pearson correlation coefficient was 0.14; 95% CI (0.02 - 0.27), p=0.012. There is a correlation between the number of consultations and the number of complaints filed. Frequent users are more likely to file a complaint. However, there is no correlation between the number of consultations and the likelihood of filing a complaint regarding treatment/information. Therefore, there seems to be a good relationship between healthcare personnel and users, which impacts patient satisfaction.

This article presents a method that uses a semi-automatic algorithm for the detection and analysis of microcracks in steel test specimens using binarized image analysis. It obtains the length along the crack path in contrast to previous methods that have obtained linear length, thereby achieving a closer approximation to its actual value. Additionally, this method automatically calculates the COD and COA parameters with measurement deviations in micrometres, thus providing greater precision than previous methods proposed to date.

This study analyzed the CO2 capture potential for Parque Natural Regional Serrania de las Quinchas buffer area in Colombia. For this purpose, multitemporal analysis for land covering for years 1989, 2000, 2006, 2011, 2017 and 2021 was made using the Normalized Difference Vegetation Index (NDVI), and Corine Land Cover (CLC) methodology. In the same way, Aboveground Biomass (AGB) was measured for representative parcels by measuring tree’s diameters and heights and applying the adequate allometric models; carbon content in soils was measured too. Results show that dense forest has grown since 1989 and the carbon stock in all the vegetation covers increased by 14,3% from 1989 until 2021, using literature data for tropical humid forests. If measured AGB values obtained in this study are used, the carbon stock average is 3 times this value. Measured carbon average content in AGB was 374,3 Ton C/Ha, well above the average for the content reported for humid tropical forests in Colombia; carbon content in soils was 897,19 Ton/Ha, 2,4 times that found in the AGB. In total, an average of 1271,49 Ton C/Ha (AGB+ soil) was found and a pattern of dense forest recovery was found, but in a more dispersed way than in the past. A very interesting potential for existing forests recovery was found for this area. Strategies for this include the development of sustainable practices, land use management, everything pursuing biodiversity preservation and the participation and leading of the local communities.

The sustainability of Indigenous Socioecological Systems (ISES) faces significant threats from global anthropogenic environmental changes, endangering Indigenous People (IP), who safeguard a substantial portion of the world's natural capital. Indigenous Traditional Food Systems (ITFS) are crucial within ISES, providing not only diverse and nutritious food but also holding cultural, spiritual, and economic significance. Despite embodying sustainable lifestyles, Indigenous voices remain underrepresented in climate and sustainability discussions. Addressing this gap, the research adopts the Political Ecological Theoretical Framework (PETF) to analyze the regulatory impact on the adaptability, resilience, and sustainability of ITFS. Two Indigenous communities, the Karen in Thailand and various groups in the Republic of Sakha (Yakutia) in Russia, serve as case studies. The study aims to establish a theoretical framework integrating Indigenous concerns into policies and regulations, emphasizing self-determination, cultural preservation, and land rights. Findings emphasize the necessity for comprehensive legal frameworks prioritizing Indigenous involvement in climate resilience and sustainability efforts, moving beyond symbolic gestures towards meaningful collaboration and decision-making power. Recognizing Indigenous vulnerability and engaging them as active partners is essential for navigating climate challenges within ISES and ITFS.

In this paper, we introduce a computational procedure that enables autonomous LEO laser trackers endowed with INSs to increase the current accuracy when shooting at middle distant medium-size LEO debris targets. The code is designed for the trackers to throw the targets into the Atmosphere by means of ablations. In case that the targets are eclipsed to the trackers by the Earth, the motions of the trackers and targets are modeled by equations that contain post-Newtonian terms accounting for the curvature of space. Otherwise, when the approaching targets become visible for the trackers, we additionally use more accurate equations, which allow to account for the local bending of the laser beams aimed at the targets. We observe that under certain circumstances the correct shooting configurations that allow to safely and efficiently shoot down the targets, differ from the current estimations by distances that may be larger than the size of many targets. In short, this procedure enables to estimate the optimal shooting instants for any middle distant medium-size LEO debris target.

Myxobacteria feature unique biological characteristics including their capability to glide on surface, undergo different multicellular developmental stages and produce structurally unique natural products such as the catecholate-type siderophores myxochelin A and B. Herein, we report the isolation, structure elucidation and biosynthesis of the new congener myxochelin B-succinate from the terrestrial myxobacterial strain MSr12020, featuring a succinyl decoration at its primary amine group. Myxochelin-B-succinate exhibited antifungal growth inhibition and moderate cytotoxic activity against selected human cancer cell lines. This unique chemical modification of myxochelin B might provide interesting insights for future microbiological studies to understand the biological function and biosynthesis of secondary metabolite succinylation.

Machine learning (ML) has a large capacity to learn and analyze a large volume of data. This study aimed to train different algorithms to discriminate between healthy and pathologic corneal images by evaluating digitally processed spectral-domain optical coherence tomography (SD-OCT) corneal images. A set of 22 SD-OCT images belonging to a random set of corneal pathologies was compared to 71 healthy corneas (control group). A binary classification method was applied; three approaches of ML were used. Once all images were analyzed, representative areas from every digital image were also processed and analyzed for a statistical feature comparison between healthy and pathologic corneas. The best performance was obtained from transfer learning - support vector machine (TL-SVM) (AUROC = 0.94, SPE 88%, SEN 100%) and transfer learning – random forest (TL- RF) method (AUROC = 0.92, SPE 84%, SEN 100%), followed by convolutional neural network (CNN) (AUROC = 0.84, SPE 77%, SEN 91%) and random forest (AUROC = 0.77, SPE 60%, SEN 95%). The highest diagnostic accuracy in classifying corneal images was achieved with the TL-SVM and the TL-RF models. In image classification, CNN was a strong predictor. This pilot experimental study developed a systematic mechanized system to discern pathologic from healthy corneas.

In Tunisia, olive is the most cultivated fruit crop while in the north where rainfall exceeded 400mm.year-1, the olive growing area is in widely extension in marginal soil with high slope gradient. Thus, the inclusion of cover crops is a sustainable solution to increase the ecosystem productivity, improve the soil fertility and oil yields. But, in Tunisia a few study were investigated the effect of legumes cover crop on the olive productivity. Therefore, the aim of this study was to evaluate the short-term (two cropping seasons s 2021 and 2022) effects of different seeded cover crops and soil management practices on the cover crops and soil characteristics, as well as enzymes activities and related microbial diversity. Six intercropping were tested in rainfed olive orchards (cv.Chétoui): Spontaneous vegetation (Spont), Wheat, Vetch, Oat, Fenugreek, mixture Vetch-Oat and compared to control (3 periodic tillage/year without intercropping). During the first cropping season, cover crops were cut as animal feed and only residues were incorporated into the soil. While, during the second year, all cover crops biomass were incorporated into the soil. Results indicate that the dry biomass and carbon uptake were significantly higher in grasses species (Wheat and Oat). But, highest level of nitrogen was found in Fenugreek cover crops. As compared to control, all cover crops including spontaneous vegetation increased soil organic matter and macronutrient level, mainly phosphorus. The most activity of β-glucosidase, phosphatase and arysulphatase was found in the cover crops plot of wheat and oat. In addition, this study improve that the utilization of the carbon sources was dominated by amides, amine and amino-acids in the fenugreek plot; while it was dominated by polymers and carboxylic acids in the case of wheat and oat.

Edible insects can diversify diets, improve livelihoods, contribute to food and nutrition security, and have a smaller ecological impact. European Union has categorized insects as novel food, and recently, in 2021 and 2022, two species: Tenebrio molitor and Acheta domesticus have been authorized for commercialization. Acceptance and perception of food risk derived from insect consumption vary depending on factors impacting insect consumption acceptability, including neophobic tendencies, gender differences, familiarity, and gastronomic perceptions. The aim of this work was to evaluate the perception and acceptance of edible insects by exploring those factors. The study was carried out on higher education students from Universities from Valencia (Spain). Students recognize insects for their high nutritional value, particularly protein content, and have varying knowledge levels about specific nutritional components. In terms of labeling and marketing, removing health and sustainability benefits from packaging can improve consumer responses. Most respondents prefer clear labeling of insect derivatives, quality certification seals, and complete information about insect content. Students consider marketing and knowledge as significant influencers of insect consumption. In summary, the text highlights the multifaceted nature of insect consumption acceptability. These insights offer valuable perspectives on insect consumption dynamics.

The RMA11 water quality model, which has been previously calibrated and validated, was coupled with the RMA10 3D hydrodynamic model to evaluate sanitation scenarios in Buenaventura Bay. The bay receives direct discharge of untreated wastewater from 500,000 people through 695 outlets along the coast. Five different effluent reduction scenarios were proposed and compared based on fecal coliform concentration as an indicator. The areas where values exceed the standard for primary contact were also used to evaluate the scenarios. The model results indicate poor water quality in the bay and how that the situation will become even more severe if immediate action is not taken. The proposed reduction in discharges in stages will have temporarily more severe effects than the current situation, but these will end when the treatment plant becomes operational. However, even with the plant in operation, complete sanitation of the bay cannot be achieved, and further measures must be considered.

In recent years information and communication technologies (ICT) play a significant role in all aspects of modern society and impact socioeconomic development in sectors as education, administration, business, medical care and agriculture. The benefits of such technologies in agriculture can be appreciated only if farmers use them. In order to predict and evaluate the adoption of these new technological tools, the technology acceptance model (TAM) can be a valid aid. The paper measures the potential acceptance of an e-learning tool designed for EU farmers and agricultural entrepreneurs. Starting from a literature review of the technology acceptance model, by analyzing the most commonly used external variables in the fields of e-learning, Agriculture, and Virtual reality, the analysis shows that computer self-efficacy, individual innovativeness, computer anxiety, perceived enjoyment, social norm, content and system quality, experience and facilitating conditions are the most common determinants addressing technology acceptance. Furthermore, findings evidenced that the external variables have a different impact on the two main beliefs of the TAM Model, Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). This study is expected to bring theoretical support for academics when determining the variables to be included in TAM extensions.

Worldwide, hypoxia-related conditions, including cancer, COVID-19, and neuro-degenerative diseases, often lead to multi-organ failure and significant mortality. Oxygen, crucial for cellular function, becomes scarce as levels drop below 10 mmHg (<2% O2), triggering mitochondrial dysregulation and activating hypoxia-induced factors (HiFs). Herein, Oxygen nanoBubbles (OnB), an emerging versatile oxygen de-livery platform, implies to offer a novel approach to address hypoxia-related pathologies. This review explores OnB oxygen delivery strategies and systems, including diffusion, ultrasound, photodynamic, and pH-responsive nanobubbles. It delves into the nanoscale mechanisms of OnB, elucidating their role in mitochondrial metabolism (TFAM, PGC1alpha), hypoxic responses (HiF-1alpha), and their interplay in chronic pathologies including cancer and neurodegenerative disorders, amongst others. By understanding these dynamics and underlying mechanisms, this article aims to contribute to our accruing knowledge of OnB and the developing potential in ameliorating hypoxia- and metabolic stress-related conditions and fostering innovative therapies.

Sensor fusion algorithms and models have been widely used in recent times. Although research evidence has informed the use of sensor fusion models in diverse applications, there is room for improvement, especially in home-based health monitoring applications which require less supervision and technical knowledge of users. The present work compares data mining-based fusion software packages such as RapidMiner Studio, Anaconda, Weka, and Orange, and proposes a data fusion framework suitable for in-home applications. 574 privacy-friendly (binary) images and 1,722 datasets gleaned from thermal and Radar sensing solutions respectively, were fused using the software packages on instances of homogeneous and heterogeneous data aggregation. Experimental results indicated that the proposed fusion framework achieved an average Classification Accuracy of 84.7% and 95.7% on homogeneous and heterogeneous datasets respectively, with the help of data mining and machine learning models such as Naïve Bayes, Decision Tree, Neural Network, Random Forest, Stochastic Gradient Descent, Support Vector Machine, K-Nearest Neighbours and CN2 induction. Further evaluation of the sensor data fusion framework based on cross validation of features indicated average values of 94.4% for Classification Accuracy, 95.7% Precision and 96.4% for Recall.

This study investigates the implementation and evaluation of a university bot designed to improve communication and management of academic events in educational environments. With the rapid evolution of digital technology, bots have emerged as powerful tools with applications in various sectors such as e-commerce, education, and healthcare. In particular, the use of bots in customer service and event management has demonstrated significant benefits by handling frequent inquiries, providing real-time information and assisting with administrative tasks, freeing up human resources for more strategic functions. This project adopted a mixed methodological approach combining qualitative and quantitative methods to assess usability and user satisfaction with the bot. The Usability Scale System (SUS) and the User Experience Questionnaire (UEQ) were used as standard tools to collect data on user perception. The results highlighted a high acceptance of the bot, with an acceptance rate of 90\%, indicating high user interest in using the application. This high acceptance underscores the bot's ability to effectively present the information users are looking for. The bot provides a list of academic events categorized by type, making it easy to find and manage information about grants, conferences, courses and other events. Its design focuses on a friendly and accessible interface that allows direct consultation without the need for conversational interaction. This project contributes to operational optimization in educational environments by providing a practical solution for the management of academic events and offers valuable insights on how to efficiently present information in similar applications. These findings are fundamental for future research and development in the creation of information systems in the educational environment.

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.

Topological data analysis (TDA) is a recent approach for analyzing and interpreting complex data sets, based on ideas a branch of mathematics called algebraic topology. TDA has proven useful to disentangle non-trivial data structure in a broad range of data analytics problems including the study of cardiovascular signals. This review aims to provide an overview of the application of TDA to cardiovascular signals and its potential to enhance the understanding of cardiovascular diseases and their treatment. We first introduce the concept of TDA and its key techniques, including persistent homology, Mapper, and multidimensional scaling. We then discuss the use of TDA in analyzing various cardiovascular signals, including electrocardiography, photoplethysmography, and arterial stiffness. We also discuss the potential of TDA to improve the diagnosis and prognosis of cardiovascular diseases, as well as its limitations and challenges. Finally, we outline future directions for the use of TDA in cardiovascular signal analysis and its potential impact on clinical practice. Overall, TDA has shown great promise as a powerful tool for the analysis of complex cardiovascular signals and may offer significant insights into the understanding and management of cardiovascular diseases.

Rheumatoid arthritis (RA) occurs more frequently in women than in men, and the studies that have addressed clinical and prognostic differences between sexes are scarce and have contradictory results and methodological problems. The present work aims to evaluate sex and gender-related differences in the clinical expression and prognosis of RA as well as the impact on psychosocial variables, coping behavior, and healthcare use and access. By identifying between-sex differences and gender-related outcomes in RA, it may be possible to design tailored therapeutic strategies that consider the differences and unmet needs. Being sex, together with age, the most relevant biomarker and health determinant, a so-called personalized medicine approach to RA must include clear guidance on what to do in case of differences.

In this work Cu2O nanoparticles (NPs) were created in-situ on graphene functionalized with Thermomyces lanuginosus lipase (G@TLL) where site-oriented supported TLL acted as template and binder in the presence of copper salt by tailorable synthesis under mild conditions, producing a heterogeneous catalyst. Cu2O NPs was confirmed by XRD and XPS. The TEM microscopy showed that the nanoparticles were homogeneously distributed over the G@TLL surface with sizes of 53 nm and 165nm. This G@TLL-Cu2O hybrid was successfully used in the degradation of toxic organic compounds such as trichloroethylene (TCE) and Rhodamine B (RhB). In the case of TCE, the hybrid presented a high catalytic capacity, degrading 60 ppm of product in 60 min in aqueous solution and room temperature without the formation of other toxic subproducts. In addition, a TOF value of 7.5 times higher than the unsupported counterpart (TLL-Cu2O) was obtained, demonstrating the improved catalytic efficiency of the system in the solid-phase. The hybrid also presented an excellent catalytic performance for the degradation of Rhodamine B (RhB) obtaining a complete degradation (48ppm) in 50 min in in aqueous solution and room temperature and with the presence of a green oxidant as H2O2.

Ecologists use the net biotic interactions among plants to predict fundamental ecosystem features. Following this approach, ecologists have built a giant body of theory founded on observational evidence. However, due to the limitations that a phenomenological approach raises both in empirical and theoretical studies, an increasing number of scientists claim the need for a mechanistic understanding of plant interaction outcomes, and a few studies have taken such a mechanistic approach. In this synthesis, we propose a modeling framework to study the plant interaction mechanistically. We first establish a conceptual ground to frame plant-plant interactions, and then, we propose to formalize this research line theoretically developing a family of individual-based, spatially-explicit models in which biotic interactions are an emergent property mediated by the interaction between plants’ functional traits and the environment. These models allow researchers to evaluate the strength and sign of biotic interactions under different environmental scenarios and thus constitute a powerful tool to investigate the mechanisms underlying facilitation, species coexistence, or the formation of vegetation spatial patterns.