The aim of this study was to identify differentially expressed genes, biological processes and metabolic pathways related to adipogenesis and lipogenesis in calves receiving different diets during the cow-calf phase. Forty-eight uncastrated F1 Angus × Nellore males were randomly assigned to two treatments from 30 days of age to weaning: no creep feeding (G1) or creep feeding (G2). After weaning, the animals were feedlot finished for 180 days and fed a single diet containing 12.6% forage and 87.4% corn-based concentrate. Longissimus thoracis muscle samples were collected by biopsy at weaning for transcriptome analysis by RNA-Seq and at slaughter for the measurement of intramuscular fat content (IMF) and marbling score (MS). Animals of G2 had 17.2% and 14.0% higher IMF and MS, respectively (P < 0.05). We identified 947 differentially expressed genes (log2 fold change 0.5; FDR 5%); of these, 504 were up-regulated and 443 were down-regulated in G2. Part of the genes up-regulated in G2 were related to PPAR signaling (PPARA, SLC27A1, FABP3, and DBI), unsaturated fatty acid synthesis (FADS1, FADS2, SCD, and SCD5), and fatty acid metabolism (FASN, FADS1, FADS2, SCD, and SCD5). Regarding biological processes, the genes up-regulated in G2 were related to cholesterol biosynthesis (EBP, CYP51A1, DHCR24, and LSS), unsaturated fatty acid biosynthesis (FADS2, SCD, SCD5, and FADS1), and insulin sensitivity (INSIG1 and LPIN2). Cow-calf supplementation positively affected energy metabolism and lipid biosynthesis, and thus favored the deposition of marbling fat during the postweaning period. Here it was shown, in an unprecedented way, by analyzing the transcriptome, genes, pathways and enriched processes due to the use of creep feeding.

The relationship between religion and politics is a constant in the history of humanity. In the specific case of Western culture, it is possible to trace an archeology of the political as an effect of theological-political devices (essentially Christian-inspired). If we add to this the evolution of politics, in modern times, towards biopolitics, then the relationship focuses on very concrete topics. This is the case of the immunological process – from a personal, social, and philosophical perspective – thoroughly analyzed by Italian philosopher Roberto Esposito. In the context of his philosophical immunology, the place of religion is mainly archaeological and is interpreted critically. This article also aims to critically analyze his position, proposing a reading close to his thought but which is, at the same time, somewhat different.

Chronic wounds remain a major challenge in healthcare, with conventional dressings often leading to infections and lacking advanced healing capabilities. This study evaluated the wound healing potential of NIMO-CH, a cellulose hydrogel derived from nipa fronds and enriched with indigenous microorganisms, particularly Lacticaseibacillus paracasei BCRC-16100. Using ICR mice with excisional wounds, three treatments were compared: no treatment, NIMO-CH, and DuoDERM. Results showed that NIMO-CH and DuoDERM both achieved 100% wound closure, with NIMO-CH-treated wounds showing complete healing with hair growth by day 18-20, while untreated wounds healed by day 20. Minimal scarring was observed in both NIMO-CH and DuoDERM groups. Histological analysis confirmed similar healing processes, including granulation tissue formation and moderate inflammatory responses, with no significant differences in collagen fiber orientation. Furthermore, genome sequencing revealed that Lacticaseibacillus paracasei BCRC-16100 contained genes sodA and gsiC, responsible for coding enzymes necessary for the wound healing process. These results suggest that NIMO-CH could be an effective alternative for wound care applications.

Bacterial infections pose a serious threat to human health, and the overuse of antibiotics has led to the rise of multidrug-resistant bacteria. Numerous current wound dressings, which may cause skin irritation or allergies are insufficient in handling large wounds, often leading to infections. This highlights the need for better antibacterial materials. Nypa fruticans (Nipa palm), native to Southeast Asia, has long been utilized for various purposes because of its multiple benefits such as its antimicrobial properties, presence of probiotics, and high cellulose content. This study evaluates the use of cellulose hydrogel from nipa fronds, loaded with probiotics (ProbioGel), as an antimicrobial agent to prevent infections. The study involved an in-vitro assay using the Kirby-Bauer method to evaluate the gel’s antimicrobial properties against common wound pathogens. Additionally, whole genome sequencing and promoter analysis were done to identify genes supporting their biochemical properties. The results showed ProbioGel exhibited significant antimicrobial activity against Staphylococcus aureus, Escherichia coli, Staphylococcus epidermidis, and Candida albicans due to the presence of genes encoding lysozyme, carnobacteriocin B2, and fatty acid ABC transporter ATP binding in the Lacticaseibacillus paracasei BCRC-16100. This study highlighted the potential of ProbioGel as an innovative and effective antimicrobial and anti-infection agent for wound care. The discovery of genes in the probiotic strain responsible for encoding antimicrobial peptides further supports its therapeutic potential.

Probiotics are microorganisms infused in products for health benefits including acceleration of nutrient digestion, however, it is also important to ensure the safety prior to incorporation. Here, we present evidence of the ability of two probiotic isolates,Lacticaseibacillus paracasei BCRC-16100 and Lacticaseibacillus paracasei ZFM54, in the (1) enhancement of carbohydrate digestion, (2) tolerance to stress, and (3) antibiotic resistance. Approaches include whole genome sequence (WGS) analysis and bioactivity assays. WGS revealed genes suggesting the ability of the two isolates to promote carbohydrate digestion, tolerance to stress and antibiotic resistance. Carbohydrate digestive ability was confirmed through a biochemical assay where the two isolates cause glucose release from starch. The two isolates also showed versatility in a range of temperature and alcohol concentration. For antibiotic resistance particularly on vancomycin, there are three mechanisms namely transporter control, transcriptional regulation, and efflux pump. Furthermore, promoter and transposable element analysis showed that some of the active antibiotic resistant (AbR) genes can be laterally transferred. Altogether, we show the potential of two probiotic isolates to be incorporated in products for improved carbohydrate digestion and the need to address the removal of active and mobile antibiotic resistance genes that may compromise safety.

The development of an equipment starts from an effective design activity. The concept selection process is an activity that is entailed in the design stage and its relevance in the design process cannot be overemphasized because it informs the choice of optimal conceptual design from a set of alternative design. Hence, there is a need to accrue efforts to the concept selection process because of its importance. This article presents the identification of optimal conceptual design as a Multicriteria decision making model by assessing the suitability of Fuzzy Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS). The Fuzzy MARCOS model was developed to access four alternative conceptual designs of briquetting machines considering eight design features with several sub features. The fuzzy MARCOS model was able to rank the conceptual designs and the results obtained from the decision analysis showed that the Fuzzy MARCOS model was able to rank the designs based on their performance and the final values of the overall utility function. The overall utility function is a based on the utility degree of the conceptual design alternatives in terms of the best and worst designs identified by the model. The utility degree created a platform for comparison on how the design alternatives varies from the best and worst design.

The main purpose of this paper is to present a system to detect extrusion failures in Fused Deposition Modelling (FDM) 3D printers by sensing that the filament is moving forward properly. After several years using these kind of machines, authors detected that there is not any system to detect the main problem in FDM machines. Authors thought in different sensors and used the Weighted Objectives Method, one of the most common evaluation methods, for comparing design concepts based on an overall value per design concept. Taking into account the obtained scores of each specification, the best choice for this work is the optical encoder. Once the sensor is chosen, it is necessary to design de part where it will be installed without interfering with the normal function of the machine. To do it, photogrammetry scanning methodology was employed. The developed device perfectly detects the advance of the filament without affecting the normal operation of the machine. Also, it is achieved the primary objective of the system, avoiding loss of material, energy and mechanical wear, keeping the premise of making a low-cost product that does not significantly increase the cost of the machine. This development has made it possible to use the printer with remains coil filament, which were not spent because they were not sufficient to complete an impression and also printing models in two colours with only one extruder.

Abstract: The aim of the present study was to identify the age and sex-related associations between marital status with PA and TV time. We used data from Vigitel, an annual telephone survey started in 2006 in Brazil. We applied a complex sample logistic regression model to estimate the odds for PA and TV time comparing marital statuses according to age and sex subgroups, independent of obesity, hypertension, diabetes, self-assessed poor health, and smoking. Our sample included 561,837 individuals with a TV time > 3 h/day (prevalence = 25.2%) and PA > 150 min/week (prevalence = 35%). Compared to single individuals, married men and women were less likely to watch TV more than 3 h/day in participants > 30 years old. When compared to single, married participants were less likely to do more than 150 min of PA/week at younger age groups. Married women older than 40 years were more likely to do more than 150 min of PA/week than the single ones, while there were no differences among married men by age group. In conclusion, married individuals are less likely to spend more than 3 hours a day watching TV than single individuals. Single men and women were more likely to do more than 150 min of PA/week at younger age groups and married women older than 40 years were more likely to do 150 min of PA/week than single women.

Background: This study aimed to analyze the psychometric properties of the Brief-COPE Inventory and to determine its concurrent validity by exploring its association with perceived stress in Peruvian nurses. Methods: Psychometric study carried out in 434 Peruvian nurses to determine the psychometric properties by confirmatory factor analysis. Three stepwise variable selection regression models were implemented. Results: The three-factor of the Brief-COPE Inventory reported adequate fit (root mean square error of approximation = 0.052, standardized root mean square = 0.068, and both the comparative fit index and the Tucker–Lewis index = 0.95). Likewise, we found that its factors are correlated (p < 0.001) and that there is adequate reliability (ω= 0.90). Moreover, nurses showed a medium level of perceived stress and the following associated factors: sex, having received stress management training, fear of COVID-19, and problem-focused coping strategies (p < 0.05). Conclusion: This study proved that Brief-COPE Inventory is a valid tool for measuring coping strategies in Peruvian nurses because it has a good fit to the model, excellent reliability, and concurrent validity with perceived stress. However, further studies are required to evaluate its validity according to the nursing professionals’ perceived areas of performance.

We study the nonlinear absorptive and dispersive optical properties of molecular systems immersed in a thermal reservoir interacting with a Four-wave Mixing (FWM) signal. Residual spin-orbit Hamiltonians are considered in order to take into account the internal structure of the molecule. As system parameters in the dissipation processes, transverse and longitudinal relaxation times are considered for stochastic solute-solvent interaction processes. The intramolecular coupling effects on the optical responses are studied using a molecule model consisting of two coupled harmonic curves of electronic energies with displaced minima in nuclear energies and positions. In this study, it was considered the complete frequency space is considered through the pump-probe detuning, not restricting the derivations to only maximums of population oscillations. This approach opens the possibility of studying the behavior of optical responses, which is very useful in experimental design. Our results indicate the sensitivity of the optical responses to parameters of the molecular structure as well as to those derived from the photonic process of FWM signal generation.

The development of language and communication patterns has been significantly impacted by the internet's quick advancement. The ability to instantly communicate globally and engage with people of different linguistic origins is one of the main advantages of using the internet. Internet use has significant positive effects on language growth, but it also brings with it drawbacks that need to be addressed. Online communication's casual atmosphere can occasionally cause grammar norms to deteriorate and non-standard language patterns to proliferate. With the information stated in this paper, the aim now is to collect literature on the benefits of internet usage and the evolution of language to provide substantive information in regard to this matter. In order to assist students in navigating the complexity of Internet communication, educational institutions should incorporate digital literacy into their curricula. This involves upholding strict requirements for traditional language proficiency while teaching students how to use digital technologies efficiently. The Internet should be used to support the revitalization and preservation of endangered languages. This can entail setting up community forums, digital archives, and online learning portals where language users can interact and exchange resources.

In this work, optimal consumption and investment strategies are derived for risk-averse investors under the 4/2 stochastic volatility class of models. We work under an expected utility (EUT) framework and consider a Constant Relative Risk Aversion (CRRA) investor, who might also be ambiguity-averse. The corresponding Hamilton-Jacobi-Bellman (HJB) and HJB-Isaacs (HJBI) equations are solved in closed-form for a subset of the parametric space and under some restrictions on the portfolio setting, for complete markets. Conditions for proper changes of measure and well defined solutions are provided. These are the first analytical solutions for the 4/2 stochastic volatility model and the embedded 3/2 model for the type of excess returns established in .

Several studies have already demonstrated the relationship between the loss of natural habitats and the incidence of diseases caused by vectors, such as dengue, which is an acute fever disease, considered a serious public health problem. The aim of the present study was to analyze the relationship between land use changes between 2009 and 2019 and the occurrence of dengue fever in 2015 and 2019 by municipality, using the state of Minas Gerais as a case study. For this, secondary data obtained from openly available sources were used. Natural vegetation cover data were obtained from the MAPBiomas platform and dengue occurrence data from the Ministry of Health, in addition to socioeconomic indicators from the Brazilian Institute for Geography and Statistics. Between 2015 and 2019, 1,255,731 cases of dengue were recorded throughout the state of Minas Gerais, ranging from 0 to 227 per thousand inhabitants between municipalities. The occurrence of dengue was distributed throughout all regions of Minas Gerais, affected by climatic and socioeconomic aspects. In general, municipalities with net loss of natural vegetation, predominantly located in the Cerrado biome, had the highest number of dengue cases in the studied period. Despite the significant positive relationship between these two variables, three of the eight socioeconomic parameters analyzed also affected the occurrence of dengue: population density, human development index (both positively) and Gini inequality index (negatively). These results indicate that, contrary to expectations, municipalities with better social conditions had more dengue cases. Our study indicates that natural vegetation is, directly or indirectly, involved in the ecosystem service of dengue control, despite the occurrence of this disease being affected by multiple factors that interact in a complex way. Thus, policies towards reducing deforestation must be complemented by a continuous investment in public health policies and reduction of social inequalities to efficiently control dengue fever.

The intricate mechanisms of the immune response elicited by vaccines and the interplay between the immune system and the central nervous system (CNS) are poorly understood. This review explores these mechanisms, emphasizing the interplay between the immune system and the central nervous system (CNS). A critical aspect is the examination of how vaccine-induced immune responses can interact with the CNS, influencing neuroinflammation and neuroimmune interactions. Furthermore, the link between vaccination and persistent symptoms observed in long-COVID patients is discussed. Vaccination initiates a complex cascade of events, starting with the production of specific proteins, such as S1/S2 spike proteins, leading to robust immune activation in the axillary lymph nodes. The role of macrophages and antigen-presenting cells (APCs) in cytokine production, antigen presentation, and the stimulation of B and T cells highlights the sophistication of the adaptive immune response. The migration of immune cell-derived exosomes to the brain plays a dynamic role in CNS inflammation, neurodegenerative processes and long COVID. On the other hand, the prolonged presence of viral and vaccine-derived spike proteins may contribute to the complex pathophysiology of Long-COVID, shedding light on the delicate balance between beneficial immune responses and possible adverse neurological outcomes of vaccination. It is worth rigorous monitoring and further research to understand the mechanisms of neuroinflammation and the persistence of spike proteins and their long-term effects on the brain, emphasising the importance of a nuanced approach to vaccine safety and efficacy in the context of COVID-19 and beyond.Principio del formulario

The knowledge of COVID-19 impact on the human body has increased rapidly. Although many people recover from COVID-19, some continue to experience persistent symptoms that have been identified as Long COVID. This condition can have a severe impact on quality of life, and it remains a significant concern for medical professionals and researchers. One of the key components of the SARS-CoV-2 virus that enables it to enter human cells is the spike (S) protein. Recent studies have revealed a complex network of interactions between G proteins, spike (S) protein, and the Renin-Angiotensin System (RAS) may be responsible, at least in part, for long COVID. SARS-CoV-2 can also affect the brain, leading to neurological symptoms such as confusion, memory loss, and fatigue. Increasing evidence suggests that COVID-19 is not just a respiratory illness since it is likely that the virus could influence signal transduction pathways such as G-protein-coupled receptor (GPCR), among others, in the brain, either directly or indirectly, affecting neural functions. These interactions with the spike (S) protein and RAS, alongside the brain, are complex and require deep research to understand their implications for Long COVID-19 manifestation fully. While recent research has shed light on the complex interactions between G proteins, spike (S) protein, the brain, and the angiotensin system, this article explores these interconnected pathways and their implications for long COVID-19 manifestations. The present review summarises current research on different molecular mechanisms in Long COVID pathophysiology and may help identify possible targets or new strategies for the diagnosis and treatment.

With the Sendai Framework (2015-2030) and the Paris Agreement (2015), the UN has been promoting at a global level, the priority objectives to protect the life and well-being of people, these documents of global consensus have scheduled in several countries, an extensive list of actions of responsibilities and commitments to the environment, to address natural disasters among those of greatest impact earthquakes and floods and among earthquakes (seismic activity). The materialization of the disaster is a natural or human-induced event, it manifests itself in permanent changes in society and by its origin it is classified as natural, anthropogenic (anthropogenic) and mixed, creating a worldwide problematic situation of immediate reaction. The attention and alert in the scientific community have been adding efforts, but in a disorganized way, with limited human and material resources and with globalized strategies still to be improved. The literature review of disaster risk management due to seismic activity, from 2008 to 2023, allows us to have updated information to identify the factors and deepen them, with the understanding, comprehension, and multidisciplinary knowledge. The selected researches that mention the factors (elements) that influence risk management of natural disasters due to seismic activity (RMNDDSA) allow us to know the advances and spaces to approach them, which constitutes the motivation to study the twenty-four (24) factors present in this type of disasters. The selected research articles indicate important advances that associate disaster risk management (DRM) and communication technology (ICTs). The technological means mentioned are well received and accepted by society, capable of detecting and communicating in real time seismic activity worldwide, with the help of social mobile networks, technological platforms, Twitter, Facebook, and others.

The global craft beer market is witnessing substantial growth, with a particular spotlight on sour beers. These unique brews are created through lactic fermentation initiated by lactic acid bacteria (LAB). However, the presence of hops, renowned for their antimicrobial properties, can pose a limitation within the realm of sour beer production. This research aims to explore and assess the potential of sour beer as a probiotic beverage. It involves a comparative analysis of the viability of Lacticaseibacillus paracasei subsp. paracasei F19 (F19) and 431 (L431) in a sour beer with an International Bitterness Unit (IBU) value of 26.65, alongside examining the ex-pression of genes such as horA, horB, horC, hitA, bsrA, and recA, which are associated with hop resistance. The study encompasses the development of two formulations of sour beers characterized by both high hop content and a robust probiotic count (8.44 – 8.77 log CFU/mL). The findings suggest that both probiotic strains of F19 and L431, are well-suited to produce sour beers with elevated hop levels, demonstrating excellent stability. Notably, the expression of genes responsible for hops resistance exhibited distinct modulation patterns among the two strains. It appears that a higher concentration of bsrA, as observed in strain L431, may be more effective in mitigating the effects of hop-related stress, potentially surpassing the combined expression of horA and bsrA. Nonetheless, further research is essential to validate this observation in gene expression. F19 and L431 emerge as promising candidates for the development of sour beers with increased hop intensity.

In this research work, we examined the decomposition mechanisms of N-substituted diacetamides. We focused on the substituent effect on the nitrogen lone pair electron delocalization, withdrawing and electron donor groups. DFT functionals used included: B1LYP, B3PW91, CAMB3LYP, LC-BLYP, and X3LYP. Dispersion functions gd3bj were applied when necessary to improve non-covalent interactions in the transition state. Pople with higher angular moments and def2-TZVP basis sets were also applied and were crucial for obtaining consistent thermodynamic parameters. The proposed mechanism involves a six-membered transition state with the extraction of an α hydrogen. Several conformers of N-diacetamides were used to account for the decrease in entropy in the transition state in the rate-determining state. All calculations, including Natural Bond Orbital (NBO) analyses, were performed using the Gaussian16 computational package and its GaussView 6.0 visualizer, along with VMD and GNUPLOT software. The isosurfaces and IBSI indexes were calculated using MultiWFN and IGMPlot, respectively.

This research aims to introduce a model, SectraBank, designed to mitigate cyber fraud attacks, specifically targeting SIM Swapping and Fake App schemes in mobile banking users. A quantitative methodology with an experimental design was meticulously employed to examine the rise of cyber fraud within mobile banking. The study involved a sample of 100 professionals with advanced knowledge in Information and Communication Technologies (ICTs). Surveys were utilized to measure awareness of threats and perceptions of security before and after the implementation of the proposed model. SectraBank leverages unique user identifiers such as fingerprint authentication and the International Mobile Equipment Identity (IMEI) number, in addition to geolocation and One Time Passwords (OTP) for validating electronic transactions in mobile banking. The effectiveness of the proposed model was notable, achieving a 96.1% efficacy rate in mitigating Fake App attacks and a 90.2% success rate in countering SIM Swapping attacks. These findings underscore the potential of SectraBank as a robust solution to enhance cybersecurity measures in the realm of mobile banking.

Mexico has a great diversity of cacti, however, many of their fruits have not been studied in greater depth. Several bioactive compounds available in cacti juices extract have demonstrated nutraceutical properties. Two cactus species are interesting for their biologically active pigments, which are chico (Pachycereus weberi (J. M.Coult.) Backeb)) and jiotilla (Escontria chiotilla (Weber) Rose)). Hence, the goal of this work was to evaluate the bioactive entities, i.e., betalains, total phenolic, vitamin C, antioxidant activity, and mineral content in the extract of the above-mentioned P. weberi and E. chiotilla. Then, clarified extracts were evaluated for their antioxidant activity and cytotoxicity (cancer cell lines) potentialities. Based on the obtained results, Chico fruit extract was found to be a good source of vitamin C (27.19±1.95 mg L-Ascorbic acid/100g fresh sample). Moreover, chico extract resulted in a high concentration of micronutrients, i.e., potassium (517.75±16.78 mg/100 g) and zinc (2.46±0.65 mg/100 g). On the other hand, Jiotilla has a high content of biologically active pigment, i.e., betaxanthins (4.17±0.35 mg/g dry sample). The antioxidant activities of clarified extracts of chico and jiotilla were 80.01±5.10 and 280.88±7.62 (DPPH method), respectively. From the cytotoxicity perspective against cancer cell lines, i.e., CaCo-2, MCF-7, HepG2, and PC-3, the clarified extracts of chico showed cytotoxicity in CaCo-2 (49.7±0.01) and MCF-7 (45.56±0.05). Normal fibroblast cell line (NIH/3T3) was used as a control for comparison purposes. While, jiotilla extract had cytotoxicity against HepG2 (47.31±0.03) and PC-3 (53.65±0.04). These results demonstrated that Chico and jiotilla are good resources of biologically active constituents with nutraceuticals potentialities.

This short paper reveals a simple methodology to create local-correlation models suitable for the closed-form pricing of multi-asset financial derivatives. The multivariate models are built to ensure two conditions, first, marginals follow desirable processes, e.g. we choose the Geometric Brownian Motion (GBM), popular for stock prices. Second, the payoff of the derivative should follow a desired one dimensional process. These conditions lead to a specific choice of the dependence structure, in the form of a local-correlation model. Two popular multi-asset options are entertained, a spread option and a basket option.

Background. Shoulder in CrossFit should have a balance between mobility and stability. Glenohumeral internal rotation deficit and posterior shoulder stiffness are risk factors for overhead shoulder injury. Objective. To determine the effectiveness of instrument assisted soft tissue mobilization and horizontal adduction stretch in CrossFit practitioners’ shoulders. Methods: Twenty-one regular CrossFitters were allocated to experimental (stretching with isometric contraction and instrument assisted soft tissue mobilization) or control group (instrument assisted soft tissue mobilization). Each session lasted 5 minutes, 2 days a week, over a period of 4 weeks. Shoulder internal rotation and horizontal adduction (digital inclinometer), and posterior shoulder stretch perception (Park scale) were evaluated. Shapiro-Wilk test was used to analyze the distribution of the sample. Parametric student's t-test was used to obtain the intragroup differences. The inter- and intra-rater differences were calculated using a repeated measures ANOVA. Results. Changes were found in the experimental group following intervention (p < 0.05), and when comparing baseline and follow-up assessments (p < .05) in all variables. Significant differences were found in the control group following intervention (p < 0.05), in right horizontal adduction and left internal rotation. When comparing perception of internal rotation and horizontal adduction in both groups in the three assessments significant differences were found. Conclusions. Instrument assisted soft tissue mobilization can improve shoulder horizontal adduction and internal rotation. An instrument-assisted soft tissue mobilization technique yields the same results alone as those achieved in combination with post-isometric stretch with shoulder adduction.

Configurable process models are frequently used to represent business workflows and other discrete event systems among different branches of large organizations: they unify commonalities shared by all branches and describe their differences, at the same time. The configuration of such models is usually done manually, which is challenging. On the one hand, when the number of configurable nodes in the configurable process model grows, the size of the search space increases exponentially. On the other hand, the person performing the configuration may lack the holistic perspective to make the right choice for all configurable nodes at the same time, since choices influence each other. Nowadays, information systems that support the execution of business processes create event data reflecting how processes are performed. In this article, we propose three strategies (based on exhaustive search, genetic algorithms, and greedy heuristic) that use event data to automatically derive a process model from a configurable process model that better represents the characteristics of the process in a specific branch. These strategies have been implemented in our proposed framework, and tested in both business-like event logs as recorded in a higher educational ERP system, and a real case scenario involving a set of Dutch municipalities.

After the ban on tributyltin-based antifouling paints, DCOIT (4,5-Dichloro-2-octylisothiazol-3(2H)-one) became one of the most used antifouling biocides. DCOIT is a pseudo-persistent contaminant in port areas and is toxic to non-target species, but its ability to bioaccumulate and be transferred along the trophic chain remains unknown. This study aimed to preliminarily investigate the bioaccumulation, trophic transfer, and biomagnification of DCOIT and SiNC-DCOIT (DCOIT immobilized in silica mesoporous nanocapsules) from the microalga Tetraselmis chuii to the mussel Mytilus galloprovincialis during exposure experiments considering 24 h of uptake followed by 72 h depuration. Mussels rapidly internalized and metabolized both DCOIT and SiNC-DCOIT. The predator-prey biomagnification factors (BMFTL) suggested that both forms of the biocide can be trophically transferred, with higher concentrations of DCOIT and SiNC-DCOIT in mussels than in microalgae (BMFTL &gt; 1). However, the bioaccumulation and bioconcentration factors indicated a low bioaccumulation capability in the short term, suggesting that the depuration rate overcomes the uptake. Our findings contribute to the development of environmental risk assessments for DCOIT and SiNC-DCOIT, but do not exclude the possibility of DCOIT bioaccumulation in the long-term in areas with constant input of DCOIT. Further studies are needed to understand these processes under continuous exposure scenarios to DCOIT.

The Western ‘discovery’ of Japanese cinema in the 1950s prompted scholars to articulate essentialist visions understanding its singularities as a result of its isolation from the rest of the World and its close links to local aesthetic and philosophical traditions. Recent approaches however, have evidenced the limitations of this paradigm of ‘national cinema’. Higson (1989) opened a critical discussion on the existing consumption, text andproduction-based approaches to this concept. This article draws on Higson´s contribution and calls into question traditional theorising of Japanese film as a national cinema. Contradictions are illustrated by assessing the other side of the ‘discovery’ of Japanese cinema: certain gendaigeki works that succeeded at the domestic box office while jidaigeki burst into European film festivals. The Taiyōzoku and subsequent Mukokuseki Action created a new postwar iconography by adapting codes of representation from Hollywood youth and western films. This article does not attempt to deny the uniqueness of this film culture, but rather seeks to highlight the need to reformulate the paradigm of national cinema in the Japanese case, and illustrate the sense in which it was created from outside, failing to recognise its reach transnational intertextuality.

In the context of energy conversion from renewable sources to distribution grids (insulated or not), a converter is often required to transfer energy from a low voltage source, towards three-phase grids. This paper presents the HW design, the simulation results and the conversion performance of a CSI converter intended to interface low voltages renevable sources to three-phase grids. The main focus of this paper is to obtain the best performance in terms of voltage increase towards the output stage while maximizing the conversion efficiency. In comparison with the currently used energy conversion systems for small photovoltaic systems, hereafter some solutions were adopted to level and maximize the energy flow from the source to the DC-link and improve the quality of current supplied in terms of harmonic distortion. The proposed system is composed of two conversion stages: the first, voltage-to-current, the second current-to-current via a three-phase CSI bridge modulated with SVM technique. The stages are not completely decoupled from an electrical point of view, therefore, in order to mitigate the effects of these interactions, synchronization strategies have been adopted.

The natural history of COVID-19 caused by SARS-CoV-2 is extremely variable, ranging from asymptomatic infection, to pneumonia, and to complications eventually fatal. We propose here the first model, explaining how the outcome of first, crucial 10-15 days after infection, hangs on the balance between the cumulative dose of viral exposure and the efficacy of the local innate immune response (natural IgA and IgM antibodies, MBL). If SARS-CoV-2 runs the blockade of this innate immunity and spreads from the upper airways to the alveoli in the early phases of the infections, it can replicate with no local resistance, causing pneumonia and releasing high amounts of antigens. The delayed and strong adaptive immune response (high affinity IgM and IgG antibodies) that follows, causes severe inflammation and triggers mediator cascades (complement, coagulation, and cytokine storm) leading to complications often requiring intensive therapy and being, in some patients, fatal. Strenuous exercise and high flow air in the incubation days and early stages of COVID-19, facilitates direct penetration of the virus to the lower airways and the alveoli, without impacting on the airway’s mucosae covered by neutralizing antibodies. This allows the virus to bypass the efficient immune barrier of the upper airways mucosa in young and healthy athletes. In conclusion, whether the virus or the adaptative immune response reach the lungs first, is a crucial factor deciding the fate of the patient. This “quantitative and time-sequence dependent” model has several implications for prevention, diagnosis, and therapy of COVID-19.

The effect of legumes adapted to a temperate climate on gas production kinetics, enteric methane, and rumen fermentation in vitro was evaluated. The species studied were Acacia dealbatha, Acacia melanoxylon, Albizzia lopantha, Lupinus pubescens, Inga insignes, Senna multiglandulosa and Tecoma stans. The effective degradation of the dry matter was estimated, the in vitro gas production was measured up to 120 hours of incubation, and the production of enteric methane, VFAs, and ammonia were measured at 24 hours. Dry matter, organic matter, ash, crude protein, neutral detergent fiber, acid detergent fiber, and acid detergent lignin were evaluated. The content of total phenols and condensed tannins was quantified. To determine digestibility, the samples were incubated for up to 120 hours. I. insignes presented a higher dry matter content and a high crude protein content. L. pubescens presented low dry matter digestibility. The neutral detergent fiber content was higher in I. insignes and with a higher value in dry matter digestibility and lower content of total phenols and condensed tannins. While S. multiglandulosa showed low detergent acid fiber content. The acid detergent lignin value was higher in I. insignes and lower in L. pubescens. In vitro gas and enteric methane production was higher in L. pubescens. propionic acid and ammonia they were higher in S. multiglandulosa. It is concluded that the amount of secondary compounds affects methane production, compromises digestibility and rumen kinetics of the legumes studied.

The orchid genus Brachystele Schltr. comprises 20 species distributed from Mexico to Argentina; 10 are found in Brazil. Anatomical studies of Orchidoideae Lindl. have been scarce, and the anatomy and histochemistry of Brachystele are still largely unknown. We characterized the vegetative organs of B. guayanensis (Lindl.) Schltr. using standard anatomical and histochemical microtechniques. Brachystele guayanensis was observed to display the anatomical characters commonly found in the vegetative organs of representatives of the Orchidaceae and Orchidoideae (including a uniseriate epidermis, thin cuticle, amphistomatic leaves, anomocytic, diacytic and tetracytic stomata, a homogeneous mesophyll, collateral vascular bundles, rhizomes with pericyclic fibers, roots with velamen, uniseriate exodermis, endodermis and pericycle). Histochemical tests confirmed the presence of lignin, proteins, and alkaloids, the lipidic nature of the cuticle, starch grains stored in spiranthosomes in the roots, and the composition of the raphides. Alkaloids were observed in great abundance, especially in the roots, and may have potentially useful medicinal activities, as has been observed in groups phylogenetically related to Brachystele.

We present an open-source Star Tracker (ST) for Attitude Determination. Our implementation makes use of open source software of common usage in astronomy running on a Raspberry Pi 2 platform. The developed platform is open and available for parties interested in further development. Evaluation of the system showed that the ST is suitable for Cubesats of 2U or larger. The ST platform is capable of solving the Lost-In-Space (LIS) problem. Currently, the average accuracy reached of the algorithm is close to 5 seconds of arc with an average processing time of 75 seconds. However, a average accuracy of about 3 minutes of arc can be reached with 35 seconds in average processing time. We also describe the evaluation procedure, the found conclusions of this procedure, in particular the section of the algorithm where most of the processing time is spent and other possible source of errors not included in this study.

The era of digital technology has brought about a substantial shift in language development, especially for younger generations who have grown up surrounded by it. Language development is impacted by digital media exposure in both positive and bad ways. Positively, users can interact with a variety of linguistic communities across the globe by using digital platforms, which offer a wealth of options for linguistic exposure and practice. This exposure can promote imaginative language use, increase vocabulary, and improve reading comprehension. Since the brevity and informality of digital communication frequently stress speed over correctness, there are worries that digital media could encourage shallow communication, shorter attention spans, and a deterioration in professional writing skills. This paper aims to gather literature about language development in the digital age. In order to make sure that technical breakthroughs support language development, standards for the responsible and balanced use of digital media in educational settings must also be developed. Teachers can better support their students' language development in a constantly changing digital environment by remaining knowledgeable and flexible.

The paper presents the main experimental capabilities of the automatic system for the study of the interaction between porous media and atmosphere. This system is one of the possible variants of patent 2-241-477. The paper shows the result of a drying and wetting study of a tailings sample. The sample is 32 cm in height and 29 cm in diameter. The saturation and drying process was carried out at 26 degrees Celsius at the sample surface, an air velocity of 2 m/s and a relative humidity of 60%. The recharge applied to the column surface was 0.3 cm3/cm2/minute. The results show the effectiveness of the system in controlling the spatial-temporal variation of different physical properties of the porous medium in the vertical and surface profile. The controlled variables include volumetric water content, suction, relative humidity, sample weight variation due to recharge or drying, shrinkage, temperature, etc. The experiment shows how the tailings saturate very quickly but dry very slowly. Tailings consolidation occurs in the drying and wetting processes, being higher in the first one.

This work is a generalization of the Lopez-Ruiz, Mancini and Calbet (LMC); and Shiner, Davison and Landsberg (SDL) complexity measures, considering that the state of a system or process is represented by a dynamical variable during a certain time interval. As the two complexity measures are based on the calculation of informational entropy, an equivalent information source is defined and, as time passes, the individual information associated to the measured parameter is the seed to calculate instantaneous LMC and SDL measures. To show how the methodology works, an example with economic data is presented.

The mechanisms underlying the establishment of asymmetric structures during development remain elusive. The wing of Drosophila is asymmetric along the Anterior-Posterior (AP) axis, despite that its growth signals that drive its growth are presumably symmetric. Here, we investigated the contribution of cell recruitment, a process that drives wing fate differentiation in Drosophila, to the asymmetric shape and pattern of the adult wing. Genetic impairment of cell recruitment results in a significant reduction in adult wing asymmetry, primarily affecting the region between longitudinal vein 5 and the wing margin (L5-M). Morphometric analysis reveals that the lack of cell recruitment results in a more symmetric wing with respect to the AP, suggesting a contribution of cell recruitment to the establishment of asymmetry in the adult wing. A close examination of the expression of the wing selector gene vestigial (vg) in wing disc does not support this hypothesis. However, the circularity of the Vg pattern significantly increase in recruitment-impaired wing disc, suggesting that while the decrease of the L5-M region in the adult wing may not be attributed to cell recruitment, it could contribute to the overall asymmetry of the adult wing. We conclude that cell recruitment, a widespread mechanism that participates in growth and patterning of several developing systems, could drive, at least partially, the asymmetric shape of the Drosophila wing.

There are increasing calls in education for deeper integration of disciplines and better preparation for the personal and job challenges of a fast-changing and smarter society. Thus, we need to search for new effective didactic strategies. However, current classrooms are isolated. They practically never connect. This hinders the exchange of ideas. It inhibits imitation and recombination, the basic blocks of cultural evolution and innovation. In this paper, we analyze online inter-class tournaments. These are lessons where entire elementary or middle school classes interconnect synchronously and play an educational game. These are new types of academic activities, and only possible thanks to digital communication technology. In this paper, we examine four online tournaments, we analyze how feasible it is to carry them out and the benefits they bring. One tournament is for teaching machine learning and statistics. The second one teaches the conservation of momentum in physics and an engineering optimization challenge. The third tournament is for learning to solve word problems. The fourth one is for teaching natural and sexual selection along with developing statistical and population thinking. We found that these inter-class tournaments are feasible to implement in schools and that they are a promising mechanism to facilitate imitation, recombination, and innovation of teaching strategies.

The potential of biological consortia designed for laccase production and dye treatment is discussed in this review. The poor yields in laccase production and low efficiency in dye decolorization of monoculture-based treatments has encouraged the use of designed biological consortia. A consortium is a system where the growth of two or more organisms, chosen to improve a particular bioprocess, is induced in the same medium. Chemical and natural mediators are being replaced by consortia for the production of laccases because, in addition to being less toxic, they induce new enzyme isoforms and lead to high laccase yields. On the other hand, consortia act synergistically in the decolorization of azo dyes through the enzymes they produce, so overall degradation is improved. Designed consortia are an attractive alternative still in development that could provide new biotechnological tools for the treatment of textile effluents.

By defining a constant probabilistic orbit of and iterated functions, the stability dynamics of these functions in possible interactions through connectivity provides the formation of a dynamic fixed point as a metric space between both iterated functions. The presence of a dynamic fixed point identifies qualitatively phases of iteration time lengths and interaction orbits of the event. Qualitative results show that the greater the average distance from one of the functions to the fixed point of the other (all possible solutions), the higher the iteration expression on time (false asymptotic effect) of one of the functions and in the opposite hand, the lower the average distance, the higher orbit’s interactions proximity between iterated functions (stability). This feature reveals asymptotic (well-defined) behavior between functions f and g within a well-defined Lyapunov stability.

Geopolymers, made from aluminosilicate raw materials, offer significant environmental advantages over conventional concrete (CC) mixes. This study explores the compressive strength, setting time, and durability of geopolymer concrete (GPC) cylinders, some of which include an additional ordinary portland cement (OPC) mix. Consistent material composition and testing methods are emphasized to achieve reliable results. MATLAB was utilized to develop and assess a neural network model predicting the compressive strength of GPC based on key variables. The model was validated using 16 experimental samples and 1047 samples from various studies. The performance plot displayed the Mean Squared Error (MSE) over iterations, identifying the best training performance at epoch 658 with an MSE of 5.3408. The Error Histogram highlighted distribution errors between predicted and actual compressive strength values, with the highest range from -1.015 to 0.3587, meaning that the predicted values were mostly within a small margin of error from the actual values. This narrow error range indicates that the ANN model has high accuracy in its predictions, as most errors are small and clustered around zero, demonstrating reliable performance in estimating compressive strength. Regression analysis showed varying correlation coefficients (training set R=0.98373, test set R=0.88164, and whole set R=0.96982), indicating adequate predictive accuracy. The results demonstrate that properly trained neural networks can effectively predict the compressive strength of GPC, highlighting its potential as a sustainable construction material.

Polyolefin fibre reinforced concrete (PFRC) has become an attractive alternative to steel for the reinforcement of concrete elements mainly due to its chemical stability and the residual strengths that can be reached with lower weights. The use of polyolefin fibres can meet the requirements in the standards, although the main constitutive relations are based on the experience with steel fibres. Therefore, the structural contributions of the fibres should be assessed by inverse analysis. In this study, the fibre dosage has been fixed at 6kg/m³ and both self-compacting concrete and conventional concrete have been used to compare the influence of the positioning of the fibres. An idealized homogeneous distribution of the fibres with such fibres crossing from side to side of the specimen has been added to self-compacting concrete. The experimental results of three-point bending tests on notched specimens have been reproduced by using the cohesive crack approach. Hence, the constitutive relations were found. The significance of this research relies on the verification of the formulations found to build the constitutive relations. Moreover, with these results it is possible to establish the higher threshold of the performance of PFRC and the difficulties of limiting the first unloading branch typical of fracture tests of PFRC.

Centropomus undecimalis (common snook, sergeant fish or robalo) and Centropomus parallelus (fat snook, smallscale fat snook, little snook or chucumite) have tropical and subtropical wide distribution from southern Florida (Gulf of Mexico) to southern Brazil (Rio Grande do Sul) waters, and due the value of their flesh, these species have been explored with predatory fishing, generating a deficiency for their conservation. Adequate conservation of this species depends on population genetic parameters. Thus, in this study, we used microsatellite markers to investigate the genetic variability and the genetic characterization of C. undecimalis and C. parallelus populations, identifying if the citations species are geographically connected, using 10 loci of microsatellites, bringing strategies of management, sustainability, and conservation for species citations, and providing genetic subsidies needed to be used in breeding programs for snooks. Microsatellite molecular genetic markers were efficient in the study of the genetic variability of the samples of C. parallelus and C. undecimalis, resulting in data on the genetic structuring of these populations, thus aiding in their management and conservation. The data presented may provide subsidies for future use in programs aimed at animal breeding of sea bass, establishing tools for use in fish farming. In addition, despite being two species that are not on the endangered list, we can observe that there are genetic differences between the studied populations of the same species.

The Canal of Aragon and Catalonia (CAC) is 134 km long and irrigates 105,000 ha (131 irrigation user communities) and it is own by the River Ebro’s Water Agency. The aqueducts are located between km 67 and 71 of the canal and were designed by the Civil Engineer Félix de los Ríos Martín in 1907. The cross-section of both aqueducts, Coll de Foix and Capedevila, was extended within the framework of the project by Fernando Hué Herrero in 1962 in order to reach design flows of 26.1 m3/s and 25.7 m3/s, respectively. The structural performance of the aqueducts has been satisfactory, nevertheless the hydraulic capacity has reduced over the years. As a result, the irrigation user communities have expressed the need to extend the cross-section of the aqueducts to meet the irrigation demands. Given the age of the structure and the different design considerations at the time, it is paramount to verify the structural reliability of the aqueducts in the new load configuration. Therefore, the objective of the paper is to present the structural safety analysis conducted and describe the new extended cross-section for both aqueducts (maintaining the original structural typology).

The revolutionary idea of complementary intelligence involves a unique strategy in which artificial intelligence (AI) works with human cognitive abilities embodied by natural intelligence (NI), creating a harmonious partnership instead of engaging in a competitive relationship. This innovative concept can potentially revolutionize how we approach scientific research and discovery. This cutting-edge process capitalizes on pooling the vast information from various distinct and autonomous sources to generate forecasts that frequently outshine human perspectives by significant margins, leading to groundbreaking advancements in scientific development based on hybrid intelligence. Multilayer networks extend traditional network theory to adjacent layers linked through copula nodes. Artificial intelligence, with its retrieval capacity to collect and interpret big data, sharply increases the number of nodes and their linking interpretation. This process, amplified by multilayer networks, dramatically improves the scalability of the networked ecosystem. Multilayer networks can represent NI and AI in complementary hyperplanes, connecting them with copula nodes and edge properties. Thus, it is possible to measure the interaction of NI and AI, assessing their scalable value co-creation properties. This study examines the interaction of NI and AI with an innovative and multidisciplinary approach. A theoretical framework of these related concepts precedes practical insights for possible applications in future research.

Several methods have been tried to estimate air temperature using satellite imagery. In this paper, the results of two machine learning algorithms, Support Vector Machine and Random Forest, are compared with Multivariate Linear Regression, TVX and Ordinary kriging. Several geographic, remote sensing and time variables are used as predictors. The validation is carried out using four different statistics on a daily basis allowing the use of ANOVA to compare the results. The main conclusion is that Random Forest with residual kriging produces the best results (R$^2$=0.612 $\pm$ 0.019, NSE=0.578 $\pm$ 0.025, RMSE=1.068 $\pm$ 0.027, PBIAS=-0.172 $\pm$ 0.046), whereas TVX produces the least accurate results. The environmental conditions in the study area are not really suited to TVX, moreover this method only takes into account satellite data. On the other hand, regression methods (Support Vector Machine, Random Forest and Multivariate Linear Regression) use several parameters that are easily calculated from a Digital Elevation Model, adding very little difficulty to the use of satellite data alone. The most important variables in the Random Forest Model were satellite temperature, potential irradiation and cdayt, a cosine transformation of the julian day.

In 2015, the Self-Action Leadership Theory—a qualitative, nomological expansion of self-leadership theory rooted in atmospheric and astronomical metaphor aimed at expanding the personal freedom of individuals, organizations, and nations by bolstering the existential growth of individuals through a series of Maslow-esque stages of holistic, personal development. This article introduces an accompanying, practitioner-based Model of Self-Action Leadership (SAL) aimed at the implicit enhancement of a holistic range of administrative processes through explicit training, mentoring, and coaching in the model’s general and universally-applicable principles and practices. The SAL model produces an original construct of personal leadership practice that builds upon the extant self-leadership academic canon, which dates back to 1983 (Manz, 1983). It also provides an analogue to four of the five core processes of Project Management by positioning a self-action leader (an individual) as the ongoing “project” at hand. The SAL Model is rooted in action research and was developed through a variety of self-oriented, action research projects in conjunction with a comprehensive, qualitative, analytical autoethnographic study of a scholar’s life experiences.

The Convective Rainfall Rate from Cloud Physical Properties (CRPh) for Meteosat Second Generation Satellites is a day-only precipitation algorithm developed at the Spanish Meteorological Agency (AEMET) for EUMETSAT’ Satellite Application Facility in support to Nowcasting and Very Short Range Forecasting (NWC SAF). It is therefore mainly intended to provide input for monitoring and near-real-time forecasts for the next few hours. This paper critically discusses the theoretical basis of the algorithm with special emphasis in the empirical values and assumptions in the microphysics of precipitation and compares the performances of the CRPh with its antecessor, the Convective Rainfall Rate algorithm (CRR), using an object-based method. The analyses show that AEMET’s CRPh is physically consistent and that outperforms the CRR. The applicability of the algorithm for nowcasting and the challenges to evolve the product to an all-day algorithm are also presented.

In this article, we give a brief review of the origin of the neutrino mass in some interesting non-linear supersymmetric models with R-symmetry. These models are able to address and solve the most important problems of the particle physics and provide mechanisms for neutrino mass generation and their mixing parameters in agreement with the current experimental data. Their prediction could be experimentally tested in the near future by collider experiments.

Dual-energy CT (DECT) imaging has broadened the potential of CT imaging by offering multiple postprocessing datasets with a single acquisition at more than one energy level. DECT shows profound capabilities to improve diagnosis based on its superior material differentiation and its quantitative value. However, the potential of dual energy imaging remains relatively untapped, possibly due to its intricate workflow and intrinsic technical limitations of DECT. Knowing the clinical advantages of dual-energy imaging and recognizing its limitations and pitfalls is neces-sary for an appropriate clinical use. The aims of this paper are to review physical and technical basis of DECT acquisition and analysis, to discuss advantages and limitations of DECT in dif-ferent clinical scenarios, to review technical constraints in material labeling and quantification, and to evaluate cutting-edge applications of DECT imaging, including artificial intelligence, qualitative and quantitative imaging biomarkers, and DECT-derived radiomics and radioge-nomics

The heat and matter transfer during glucose catabolism in living systems and their relation with entropy production are a challenging subject of the classical thermodynamics applied to biology. In this respect, an analogy between mechanics and thermodynamics has been performed via the definition of the entropy density acceleration expressed by the time derivative of the rate of entropy density and related to heat and matter transfer in minimum living systems. Cells are regarded as open thermodynamic systems that exchange heat and matter resulting from irreversible processes with the intercellular environment. Prigogine’s minimum energy dissipation principle is reformulated using the notion of entropy density acceleration applied to glucose catabolism. It is shown that, for out-of-equilibrium states, the calculated entropy density acceleration is finite and negative and approaches as a function of time a zero value at global thermodynamic equilibrium for heat and matter transfer independently of the cell type and the metabolic pathway. These results could be important for a deeper understanding of entropy generation and its correlation with heat transfer in cell biology with special regard to glucose catabolism representing the prototype of irreversible reactions and a crucial metabolic pathway in stem cells and cancer stem cells.

Plant-parasitic nematodes cause expressive annual yield losses to worldwide agricultural production. Most cultivated plants have no known resistance against nematodes and the few bearing a resistance gene can be overcome by certain species. The chemical methods that have been deployed to control nematodes were largely banned from use due to their poor specificity and high toxicity. Hence, there is an urgent need for the development of cleaner and more specific control methods. Recent advances in nematode genomics, including in phytoparasitic species, provide an unprecedented opportunity to identify genes and functions specific to these pests. Using phylogenomics, we compared 61 nematode genomes, including 16 for plant-parasitic species and identified more than 24,000 protein families specific to these parasites. In the genome of Meloidogyne incognita, one of the most devastating plant parasites, we found ca. 10,000 proteins with orthologs restricted only to phytoparasitic species and no further homology in protein databases. Among these phytoparasites-specific proteins, ca. 1,000 shared the same properties as known secreted effectors involved in essential parasitic functions. Of those, 68 were novel and showed strong expression during the endophytic phase of the nematode life cycle, based on both RNA-seq and RT-qPCR analyses. Besides effector candidates, transcription-related and neuro-perception functions were enriched in phytoparasites-specific proteins, revealing interesting targets for nematode control methods. This phylogenomics analysis, constitutes an unprecedented resource for the further understanding of the genetic basis of nematode adaptation to phytoparasitism and for the development of more efficient control methods.

This study addresses the problem of accurately predicting azimuth and elevation angles of signals impinging on an antenna array employing Machine Learning (ML). Using the information obtained at a receiving system when a transmitter’s signal hits it, a Decision Tree (DT) model is trained to estimate azimuth and elevation angles simultaneously. Simulation results demonstrate the robustness of the proposed DT-based method, showcasing its ability to predict the Direction of Arrival (DOA) in diverse conditions beyond the ones present in the training dataset, i.e., the results display the model’s generalization capability. Additionally, the comparative analysis reveals that DT-based DOA estimation outperforms the state-of-the-art MUltiple SIgnal Classification (MUSIC) algorithm, establishing DTs as competitive alternatives for DOA estimation in signal reception systems.

Background/aim: Sexual harassment has become a serious social and public health problem in adolescence, causing adverse effects on mental health. Nevertheless, some behaviours arise that, due to their characteristics, might be misinterpreted as sexual harassment. A field study, a survey with a non-probabilistic accidental sampling, was designed in order to estimate the prevalence of sexual harassment victimization in the Spanish adolescent population, as well as to quantify the harms. Method: 1028 Spanish adolescents, 54.3% females and 45.7% males, aged 13-17 years (M = 15.21, SD = 1.03), responded to a diagnostic measure of sexual harassment victimization and an inventory measure of internalizing and externalizing Mental Health Problems (MHPs). Results: The results showed a significant prevalence of diagnosed sexual harassment victimization of school-aged adolescents, 24.1%, 95% [.215, 267], with adverse effects on internalizing and externalizing MHPs. As for the internalizing MHPs, the results showed moderate adverse effects on depression, anxiety, somatic burns, posttraumatic symptoms, and obsessive-compulsive symptoms; and mild adverse effects on social anxiety. With regard to externalizing MHPs, the results revealed moderate adverse effects on hyperactivity-impulsivity, anger control and antisocial behaviour; and mild adverse effects on attention problems, aggression and defiant behaviour. In addition, it was corroborated that sexual harassment victimization affects adolescent females to a greater extent, with the effect being significantly greater in internalizing than in externalizing MHPs. Conclusions: The results obtained are discussed and future lines of research and intervention are proposed to promote the implementation of prevention and intervention programs that address this phenomenon and, in turn, improve the physical, psychological, and social well-being of adolescents.

Companies have been increasing the amount of data that they collect from their systems and processes, considering the decrease in the cost of memory and storage technologies in recent years. The emergence of technologies such as Big Data, Cloud Computing, E-Science, and the growing complexity of information systems made evident that traceability and provenance are promising approaches. Provenance has been successfully used in complex domains, like health sciences, chemical industries, and scientific computing, considering that these areas require a comprehensive semantic traceability mechanism. Based on these, we investigate the use of provenance in the context of Software Process (SP) and introduce a novel approach based on provenance concepts to model and represent SP data. It addresses SP provenance data capturing, storing, new information inferencing and visualization. The main contribution of our approach is PROV-SwProcess, a provenance model to deal with the specificities of SP and its ability in supporting process managers to deal with vast amounts of execution data during the process analysis and data-driven decision-making. A set of analysis possibilities were derived from this model, using SP goals and questions. A case study was conducted in collaboration with a software development company to instantiate the PROV-SwProcess model (using the proposed approach) with real-word process data. This study showed that 87.5% of the analysis possibilities using real data was correct and can assist in decision-making, while 62.5% of them are not possible to be performed by the process manager using his currently dashboard or process management tool.

This work aimed to synthesize new N-rich triazole compounds. In this article we describe the synthesis of three different 1,2,4-triazole-based systems starting from 1,3-diaminoguanidine hydrochloride monohydrate. The structure of the obtained crystals was established by single-crystal X-Ray diffraction. The high nitrogen content of the synthetized compounds makes them building blocks for the application in the High-Energy-Density material science.

The climate and its changes are major risk factors for agricultural activities because agricultural systems are highly affected by climatic factors such as temperature, rain, humidity, wind, and solar radiation. While some agricultural areas of the world are irrigated, the vast majority rely on natural rainfall patterns. Farmers will consume more water as a result of climate change and experience less water availability, resulting in a decrease in production capacity. As one of the most important natural phenomena affecting agricultural productivity, drought is a limiting environment for plant growth. The response of plants to water stress is complex and involves coordination between gene expression and its integration with hormones. It has been shown that bacteria have mechanisms to reduce water stress in these plant species and promote greater growth. The underlined mechanism involves root-to-shoot phenotypic changes in growth rate, architecture, hydraulic conductivity, water conservation, plant cell protection, and damage restoration through integrating phytohormones modulation, stress-induced enzymatic apparatus, and metabolites. This review demonstrates how plant growth-promoting bacteria can mitigate negative effects associated with water stress in plants and provide examples of technology conversion in agroecosystems.

The European Union's recent decision to renew the authorization for the use of glyphosate until 15 December 2033 stimulates the scientific discussion all around the world regarding its toxicity or otherwise for humans. Glyphosate is a chemical used by millions of tons in the last 50 years worldwide to drying weeds in cultivated fields, greenhouses, roadsides. Concern has been raised in many quarters about the possible presence in the food chain and the consequent adverse effects on health: both aspects that argue in favor of toxicity and those that instead may indicate limited toxicity of glyphosate are here discussed. The great debate that has been generated requires further investigations and field measurements to understand its fate once dispersed in the environment and its concentration in the food chain. Hence the need for validated analytical methods that are available to analysts in the field. In the present review, methods for the analytical determination of glyphosate and its main metabolite, AMPA, are discussed, with a specific focus on chromatographic techniques applied to cereal products. The experimental procedures are explained in any detail, including cleanup, derivatization, and instrumental conditions to give the laboratories involved enough information to proceed with the implementation of this line of analysis. The prevalent chromatographic methods used are LC-MS/MS, GC-MS/SIM, and GC-MS/MS but sufficient indications are also given to those laboratories that wish to use the simpler HPLC-FLD, HPLC-UV, GC-NPD or GC-FPD techniques for screening purposes. Concentrations from literature measured in wheat, corn, barley, rye, oats, soybean, and cereal-based foods are reported together with the regulatory status in various parts of the world and the accumulation mechanism. As for the accumulation in cereals, available data show that glyphosate tends to accumulate more in wholemeal flours than in refined ones, that its concentration in the product strictly depends on the treatment period (the closer it is to the time of harvesting, the higher the concentration) and that in cold climates the herbicide tends to persist in the soil for a long time.

We report a photonic-based radio frequency (RF) arbitrary waveform generator (AWG) using a soliton crystal micro-comb source with a free spectral range (FSR) of 48.9 GHz. The comb source provides over 80 wavelengths, or channels, that we use to successfully achieve arbitrary waveform shapes including square waveforms with a tunable duty ratio ranging from 10% to 90%, sawtooth waveforms with a tunable slope ratio of 0.2 to 1, and a symmetric concave quadratic chirp waveform with an instantaneous frequency of sub GHz. We achieve good agreement between theory and experiment, validating the effectiveness of this approach towards realizing high-performance, broad bandwidth, nearly user-defined RF waveform generation.

We report a broadband radio frequency (RF) channelizer with up to 92 channels using a coherent microcomb source. A soliton crystal microcomb, generated by a 49 GHz micro-ring resonator (MRR), is used as a multi-wavelength source. Due to its ultra-low comb spacing, up to 92 wavelengths are available in the C band, yielding a broad operation bandwidth. Another high-Q MRR is employed as a passive optical periodic filter to slice the RF spectrum with a high resolution of 121.4 MHz. We experimentally achieve an instantaneous RF operation bandwidth of 8.08 GHz and verify RF channelization up to 17.55 GHz via thermal tuning. Our approach is a significant step towards the monolithically integrated photonic RF receivers with reduced complexity, size, and unprecedented performance, which is important for wide RF applications ranging from broadband analog signal processing to digital-compatible signal detection.

Despite being stored at 113 K and atmospheric pressure, LNG cold potential is not exploited to reduce green ships’ energy needs. An innovative system based on three Organic Ranking Cycles integrated into the regasification equipment is proposed to produce additional power and recover cooling energy from condensers. A first-law analysis identified ethylene and ethane as suitable working fluids for the first and the second ORC making available freshwater and ice. Propane, ammonia and propylene could be arbitrarily employed in the third ORC for air-conditioning. An environmental analysis that combines exergy efficiency, ecological indices and hazard aspects for marine environment and ship’s passengers, indicated propylene as safer and more environmentally friendly. The exergy analysis confirms more than 20% of the LNG potential can be recovered from every cycle to produce a net clean power of 76 kW, whereas 270 kW can be saved by recovering condensers' cooling power to satisfy some ship needs. Assuming the sailing mode, a limitation of 162 kg in LNG consumptions was determined, avoiding the emission of 1584 kg of CO2 per day. Marine thermal pollution is reduced by 3.5 times by recovering the working fluids' condensation heat for the LNG pre-heating.

We have modelled the energy consumption of prototype and real buildings under present and future climatic conditions with the EnergyPlus model to develop a better understanding of the relationship between changing climate conditions and energy demand. We have produced detailed meteorological information with 50 meters of spatial resolution through dynamical downscaling process combining regional, urban and computational fluid dynamics models which include the effects of the buildings on urban wind patterns. The city of Madrid has been chosen for our experiment. The impact on energy demand and their respective economic cost are calculated for year 2100 versus 2011 based on two IPCC climate scenarios, RCP 4.5 (stabilization of emissions) and RCP 8.5 (not reduction of emissions). Findings show that climate change will have a significant impact on the energy demand for buildings. Space heating demand will be increased by the RCP 4.5 and cooling demand will be increased for the RCP 8.5 in the analysed buildings.

A numerical approach for generating a limited number of water demand scenarios and estimating their occurrence probabilities in a Water Distribution Network (WDN) is proposed. This approach makes use of the demand scaling laws in order to consider the natural variability and spatial correlation of nodal consumptions. The scaling laws are employed to determine the statistics of nodal consumption as a function of the number of users and the main statistical features of the unitary user's demand. Besides, consumption at each node is considered to follow a Gamma probability distribution. A high number of groups of cross-correlated demands, i.e., scenarios, for the entire network were generated using Latin Hypercube Sampling (LHS) and the numerical procedure proposed by Iman and Conover. The Kantorovich distance is used to reduce the number of scenarios and estimate their corresponding probabilities, while keeping the statistical information on nodal consumptions. By hydraulic simulation, the whole number of generated demand scenarios was used to obtain a corresponding number of pressure scenarios on which the same reduction procedure was applied. The probabilities of the reduced scenarios of pressure were compared with the corresponding probabilities of demand.

In the last decade several projects have been developed for the digitization and semantization of cultural heritage data. They were developed to preserve and maintain this heritage, but bringing it closer to all types of users and allowing access to this information to other sectors such as tourism, education, etc. In these developments, web technologies are combined, along with the use of knowledge graphs and interactive visualisation tools. Although remarkably interesting projects have been developed, in those projects, the data visualization tools are usually focused on the project context. This makes it difficult to reuse these jobs. Additionally, there are peculiarities of cultural heritage data considered with little depth, such as uncertainty, spatial and temporal granularity, as well as other aspects, such as relationships between data. In this article, these problems are described and based on other works such as VUMO or VISO, the design of an ontology that formalizes how to visualise this information is proposed, considering these problems. In addition, the development of a platform that allows the visualisation of this information through a web application and its evaluation of its use in projects such as SILKNOW, or Arxiu Valencià del Disseny is exposed

This paper seeks to optimize the mechanical and durability properties of ultra-high performance concrete (UHPC). To meet this objective, concrete specimens were manufactured by using 1,100 kg/m3 of binder, water/binder ratio 0.20, silica sand and last generation of superplasticizer. Silica fume, metakaolin and two types of nano silica were used for improving the performances of the concrete. Additional mixtures included 13mm long OL steel fibers. Compressive strength, electrical resistivity, mercury intrusion porosimetry tests and differential and thermogravimetric thermal analysis were carried out. The binary combination of nano silica and metakaolin, and the ternary combination of nano silica with metakaolin and silica fume, led to the best performances of the UHPC, both mechanical and durable performances.

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

In the southeastern coast of Brazil, the bays of Ilha Grande and Sepetiba are linked by the Ilha Grande Channel, where remarkably vigorous currents have been consistently observed. The sheer intensity of these currents defies a simple explanation through tidal forcing alone, prompting researchers to delve into potential influences such as basin resonance and the baroclinic effect. This study aims to elucidate the role of remote meteorological effects within this complex hydrodynamic system. A numerical approach with a coastal model nested within an ocean model was employed, enabling an in-depth examination of the intricate interplay between meteorological and tidal forcings. The study revealed a significant finding: the lag in signal propagation plays a pivotal role in determining how these signals impact the dynamics of the bays. The astronomical signal exhibits a minimal lag along the coast (1 minute), and leads to water level differences between the sea and the coastline, resulting in the generation of tidal currents at the bay entrances. On the other hand, the remote meteorological signal, with a stronger signal lag along the coast (4.92 hours), leads to the creation of water level difference between the bay’s entrances, inducing significant fluxes along the narrow Ilha Grande Channel.

The combined effects of the thermal processing (i.e., sterilisation treatment) and the prior frozen storage time (3 or 6 months at –18 ºC) on the quality loss in canned Atlantic horse mackerel (Trachurus trachurus) were determined. Thus, the sterilisation step led to a remarkable (p&lt;0.05) formation in canned fish muscle of fluorescent compounds, free fatty acids (FFAs) and trimethylamine and to an increase of the L* and b* colour parameters; meantime, a decrease (p&lt;0.05) of the total ω3 FA/total ω6 FA ratio and the a* colour value were detected. The prior frozen storage period led to an increased (p&lt;0.05) lipid oxidation (peroxide, thiobarbituric acid reactive substance and fluorescent compound formation) and hydrolysis (FFA formation) development and to increased L* and b* colour values in the corresponding canned samples; additionally, a lower (p&lt;0.05) polyene index and phospholipid content were observed in canned fish previously subjected to frozen storage. In most indices, physico-chemical changes related to quality loss were found higher if the previous storage period was increased. According to the marked effects of the sterilisation step and the prior frozen storage period, optimisation of such processing conditions is recommended to maximise the quality of canned horse mackerel.

Interoperable multilayer networks are pivotal and transformative in public digital health. They not only enhance the delivery of healthcare services but also contribute significantly to improving public health outcomes. Through better accessibility, efficiency, and data-driven decision-making, these networks are revolutionizing how we approach public health. The seamless data exchange and integration they facilitate across different healthcare systems and providers can lead to substantial cost savings for public healthcare systems. These networks pave the way for a more efficient and effective healthcare system by reducing redundancies, optimizing resource allocation, and minimizing unnecessary procedures. This study combines the pressing issues of public digital health with the innovative interpretation of multilayer network theory, proposing practical solutions that inspire academics and practitioners alike.Public digital health is not just about improving care access and patient engagement. It is also about ensuring the financial sustainability of our healthcare systems. Innovative multilayer network analysis is critical in this game, improving interoperability and reducing spatial and temporal constraints. These networks streamline processes and improve efficiency by easing complex interactions within healthcare systems. This process, in turn, allows healthcare providers to deliver high-quality care at a lower cost, transforming, whenever possible, in-patients and out-patients into home-patients. Networks are a cornerstone and a beacon of hope for transforming public digital health. They are increasing the Value for Money and enhancing a patient-centric approach, making us optimistic about the future of healthcare.This study shows that revolutionizing digital healthcare methodologies has a profound impact on crucial elements like resilience, interoperability, and patient well-being within public health. The enhancement of interoperability facilitates the smooth flow of data exchange across various platforms and healthcare providers, fostering improved collaboration and decision-making processes and elevating the safety of patients.

The search for growth and sustainability in any organization largely depends on its ability to carry out digital transformation and agility processes. These processes are essential to adapt to an increasingly changing and competitive business environment, allowing companies to be more efficient and effective in creating an unbreakable bond with their customers. This manuscript addresses the importance of detecting and eliminating anti-patterns in organizational culture for a successful digital and agile transformation. During the early stages of the transformation process, prejudices and paradigms rooted in the organization can become an obstacle to change. The goal of this writing is to offer a practical guide for leaders and teams in organizations seeking successful cultural transformation. Effective strategies are proposed to overcome the challenges faced by organizations during this early stage. In summary, the key steps to be followed in the initial stages of digital transformation with agility are described, including the importance of establishing strong leadership, defining a clear vision and scope of the transformational process, among others. A set of recommendations will be provided to overcome recurring anti-patterns, such as lack of stakeholder participation and commitment, lack of proper planning, and confusion of roles and responsibilities.

Despite decreasing anthropogenic mercury (Hg) emissions in Europe and the banning and restriction of many persistent organic pollutants (POPs) under the Stockholm Convention, Mediterranean marine mammals still have one of the highest body burdens of persistent pollutants in the world. Moreover, the Mediterranean basin is one of the most sensitive to climate change, with likely changes in the biogeochemical cycle and bioavailability of Hg, primary productivity, and the length and composition of pelagic food webs. The availability of food resources for marine mammals is also affected by widespread overfishing and the increasing number of alien species colonizing the basin. After reporting the most recent findings on the biogeochemical cycle of Hg in the Mediterranean Sea and the physico-chemical and bio-ecological factors determining its exceptional bioaccumulation in odontocetes, this review discusses possible future changes in the bioavailability of the metal. Recent ocean-atmosphere-land models predict that in mid-latitude seas, water warming (which in the Mediterranean is 20% faster than the global average) is likely to decrease the solubility of Hg and favor the escape of the metal to the atmosphere. However, the basin has been affected for thousands of years by natural and anthropogenic inputs of metals, and climate change with sea level rise (3.6 ± 0.3 mm year-1 in the last two decades) and the frequency of extreme weather events will likely remobilize large amount of legacy Hg from soils, riverine and coastal sediments. Moreover, possible changes in pelagic food webs and food availability could determine dietary shifts and lower growth rates in Mediterranean cetaceans, increasing their Hg body burden. Although adult marine mammals have evolved the ability to detoxify monomethylmercury (MMHg) and store the metal in the liver and other organs as insoluble Hg-Se crystals, in Mediterranean populations more exposed to the metal, this process can deplete the biological pool of Se, increasing their susceptibility to infectious diseases and autoimmune disorders. Mediterranean mammals are also among the most exposed in the world to legacy POPs, micro- and nanoplastics and contaminants of emerging interest. Concomitant exposure to these synthetic chemicals may pose a much more serious threat than the Se depletion. Unfortunately, as shown by literature data summarized in this review, the most exposed populations are those living in the NW basin, the main feeding and reproductive area for most Mediterranean cetaceans, declared a sanctuary for their protection since the 2002. Thus, while emphasizing the adoption of all available approaches to mitigate anthropogenic pressure with fishing and maritime traffic, it is recommended to direct future research efforts towards the assessment of possible biological effects, at individual and population level, of chronic and simultaneous exposure to Hg, legacy POPs, contaminants of emerging interest and microplastics.

Humulus lupulus, or hops, is a vital ingredient in brewing, contributing bitterness, flavor, and aroma. The female plants produce strobiles rich in essential oils and acids, along with bioactive compounds like polyphenols, humulene, and myrcene, which offer health benefits. This study examined the aromatic profiles of five hop varieties grown in Brazil versus their countries of origin. Fifty grams of pelletized hops from each strain were collected and analyzed using HS-SPME/GC-MS to identify volatile compounds, followed by statistical analysis with PLS-DA and ANOVA. The study identified 330 volatile compounds and found significant aromatic differences among hops from different regions. For instance, H. Mittelfrüher grown in Brazil has a fruity and herbaceous profile, while the German-grown variety is more herbal and spicy. Similar variations were noted in Magnum, Nugget, Saaz, and Sorachi Ace varieties. The findings underscore the impact of terroir on hop aromatic profiles, with Brazilian-grown hops displaying distinct profiles compared to their counterparts from their countries of origin, including variations in aromatic notes and α-acid content.

With the term neuroinflammation has defined the typical inflammatory response of the brain closely related to the onset of many neurological diseases. Neuroinflammation is well known, but its mechanisms and pathways are not entirely comprehended. Currently, some progress has been achieved through many efforts and research. Consequently, new cellular and molecular mecha-nisms, diverse from conventional ones, are emerging. In listing some of those that will be the sub-ject of our description and discussion, essential are the important role of peripheral and infiltrated monocytes and clonotypic cells, alterations in gut/brain axis, dysregulation of the apelinergic sys-tem, as well as changes in the endothelial glycocalyx of blood-brain barrier, variation in expres-sion of some genes and levels of the encoding molecules by microRNAs (miRNAs), or other epige-netic factors and distinctive transcriptional factors, as well as the role of autophagy, ferroptosis, sex differences and modifications in the circadian cycle. Such mentioned mechanisms can add significant pieces in understanding the complex etiological puzzle of neuroinflammation. In addi-tion, they could represent biomarkers and targets of neurodegenerative diseases, in increase in our old populations.

This study investigates the integration of natural intelligence (NI) and artificial intelligence (AI) within traditional firms, proposing a multilayer network framework to enhance economic value. The research explores the central question: How can the integration of NI and AI, facilitated by copula nodes, drive economic value creation in digitized firms? Through empirical testing across multiple industries—namely manufacturing, retail, and finance—the study evaluates the cost-benefit improvements associated with AI adoption. The findings reveal substantial efficiency gains, improved decision-making, and notable cost reductions, validating the proposed model's predictions. The study emphasizes the critical role of copula nodes in optimizing interactions between NI and AI, ensuring that their integration yields maximum economic benefits. By providing a novel framework for quantifying AI's economic impact within digitized firms, this research fills a significant gap in the literature on multilayer networks and intelligent systems. The practical implications are profound, offering a strategic pathway for firms to enhance profitability and competitiveness in the digital age.

Audio recording in classrooms is a common practice in educational research, with applications ranging from detecting classroom activities to analysing student behaviour. Previous research has employed neural networks for classroom activity detection and speaker role identification. However, these recordings are often affected by background noise that can hinder further analysis, and the literature has only sought to identify noise with general filters and not specifically designed for classrooms. Although the use of high-end microphones and environmental monitoring can mitigate this problem, these solutions can be costly and potentially disruptive to the natural classroom environment. In this context, we propose the development of a neural network model that can specifically detect and filter out background noise in classroom recordings. This model would allow the use of lower quality recordings without compromising analysis capability, thus facilitating data collection in natural educational environments and reducing the costs associated with high-end recording equipment.

Background: This study aimed to explore the association between the emotional impact of COVID-19 and emotional eating and the risk of alcohol use disorder among Peruvian health science students. Methods: We conducted a cross-sectional analytical study in which an online questionnaire was administered to 456 health science interns from four cities in Peru. We used the COVID-19 Emotional Impact Profile questionnaire, Mindful Eating Questionnaire, and Alcohol Use Disorders Identification Test. Spearman’s correlations were calculated and two multiple linear regression models were developed. Results: 68.4% of the participants were emotional eaters and 8.6% reported low-risk levels of alcohol use disorder. Based on the results of the first model, the overall emotional impact of COVID-19, being overweight or obese, depression and anxiety levels, and living with only one parent were factors associated with emotional eating. The results of the second model showed that the level of depression, living with just one parent, living alone, sex, and number of months as an intern were factors associated with the risk of alcohol use disorder. Conclusion: To reduce emotional eating and the risk of alcohol use disorder among interns, universities should implement interventions aimed at reducing the emotional impact of COVID-19 and provide nutritional counseling.

Size effect on plain concrete specimens is well known and can be correctly captured when performing numerical simulations by using a well characterised softening function, but in the case of fibre reinforced concrete this is not directly applicable, since an only diagram cannot capture the material behaviour on elements with different size due to dependence of the orientation factor of the fibres with the size of the specimen. In previous works, the use of a trilinear softening diagram proved to be very convenient for reproducing fracture of polyolefin fibre reinforced concrete elements, but only if it is previously adapted for each specimen size. In this work, a predictive methodology is used to reproduce fracture of polyolefin fibre reinforced concrete specimens of different sizes under three-point bending. Fracture is reproduced by means of a well known embedded cohesive model, with a trilinear softening function that is defined specifically for each specimen size. The fundamental points of these softening functions are defined a priori by using empirical expressions proposed in past works, based on an extensive experimental background. Therefore, the numerical results are obtained in a predictive manner, and then compared with a previous experimental campaign, showing that this approach properly captures the size effect, although some values of the fundamental points in the trilinear diagram could be defined more accurately.

This manuscript explores the significance of continuous improvement in software development and digital product management, highlighting its role in addressing challenges and achieving superior results in today's dynamic business landscape. Drawing on Lean Thinking and Agile principles, the paper emphasizes the importance of customer focus, multidisciplinary collaboration, respect for people, inspection and adaptation, experimentation, incremental delivery, and continuous feedback in driving continuous improvement. It identifies key problems associated with the lack of continuous improvement, including quality issues, stagnation, inefficiency, lack of learning, lack of participation and collaboration, and lack of adaptability. To overcome these challenges, the paper proposes a solution that leverages agile events and interactions, such as sprint retrospectives and daily scrum meetings, and introduces a "kaizen board" as a visual tool to manage and monitor the continuous improvement process. The manuscript highlights the benefits of continuous improvement in terms of quality enhancement, efficiency gains, improved customer satisfaction, and adaptability to change. It stresses the need for fostering a culture of learning and constant adaptation, and provides insights on applying continuous improvement across different dimensions: product, process, team, and culture. The paper concludes by emphasizing the significance of commitment and active participation from all team members for achieving sustainable progress and success in digital transformation efforts.

Micro-combs [1-4] - optical frequency combs generated by integrated micro-cavity resonators – offer the full potential of their bulk counterparts [5,6], but in an integrated footprint. The discovery of temporal soliton states (DKS – dissipative Kerr solitons) [4,7-11] as a means of mode-locking micro-combs has enabled breakthroughs in many fields including spectroscopy [12,13], microwave photonics [14], frequency synthesis [15], optical ranging [16,17], quantum sources [18,19], metrology [20,21] and more. One of their most promising applications has been optical fibre communications where they have enabled massively parallel ultrahigh capacity multiplexed data transmission [22,23]. Here, by using a new and powerful class of micro-comb called “soliton crystals” [11], we achieve unprecedented data transmission over standard optical fibre using a single integrated chip source. We demonstrate a line rate of 44.2 Terabits per second (Tb/s) using the telecommunications C-band at 1550nm with a spectral efficiency – a critically important performance metric - of 10.4 bits/s/Hz. Soliton crystals exhibit robust and stable generation and operation as well as a high intrinsic efficiency that, together with a low soliton micro-comb spacing of 48.9 GHz enable the use of a very high coherent data modulation format of 64 QAM (quadrature amplitude modulated). We demonstrate error free transmission over 75 km of standard optical fibre in the laboratory as well as in a field trial over an installed metropolitan optical fibre network. These experiments were greatly aided by the ability of the soliton crystals to operate without stabilization or feedback control. This work demonstrates the capability of optical soliton crystal micro-combs to perform in demanding and practical optical communications networks.

We demonstrate a photonic RF integrator based on an integrated soliton crystal micro-comb source. By multicasting and progressively delaying the input RF signal using a transversal structure, the input RF signal is integrated discretely. Up to 81 wavelengths are provided by the microcomb source, which enable a large integration time window of ~6.8 ns, together with a time resolution as fast as ~84 ps. We perform signal integration of a diverse range of input RF signals including Gaussian pulses with varying time widths, dual pulses with varying time intervals and a square waveform. The experimental results show good agreement with theory. These results verify our microcomb-based integrator as a competitive approach for RF signal integration with high performance and potentially lower cost and footprint.

The chemistry and electrochemistry basic fields have been active since the last two decades of the past century studying how surface modification of electrodes by coating with conductive films enhances their activity and performance. In the light of the development of alternative sustainable ways of energy storage and carbon dioxide conversion by electrochemical processes, these research studies have jumped in the 21st century to more applied fields such as chemical engineering, energy and environmental science and engineering. The huge amount of literature on experimental works dealing with the development of CO2 electroreduction processes addresses electrocatalyst development. Membranes can help understanding and controlling the mass transport limitations of current electrodes and reactors designs. The present bibliometric review addresses the papers published in the 21st century regarding membrane coated electrodes and electrocatalysts to enhance electrochemical reactor performance and viability with a special focus on the urgent issue of carbon dioxide capture and utilization.

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

The fermentation of syngas is an attractive technology that can be integrated with gasification of lignocellulosic biomass. The coupling of these two technologies allows for treating a great variety of raw materials. Lignin usually hinders microbial fermentations; thus, the thermal decomposition of the whole material into small molecules allows for the production of fuels and other types of molecules using syngas as substrate, a process performed at mild conditions. Syngas contains mainly hydrogen, carbon monoxide and carbon dioxide in varying proportions. These gases have a low volumetric energy density, resulting more interesting its conversion into higher energy density molecules. Syngas can be transformed by microorganisms, thus avoiding the use of expensive catalysts, which may be subject to poisoning. However, the fermentation is not free of suffering from inhibitory problems. The presence of trace components in syngas may cause a decrease in fermentation yields or cause a complete cessation of bacteria growth. The presence of tar and hydrogen cyanide are just examples of this fermentation's challenges. Syngas cleaning impairs significant restrictions in technology deployment. The technology may seem promising, but it is still far from large-scale application due to several aspects that still need to find a practical solution.

Purpose: This research compared the dissociated phoria at near and distance fixation in free space using three techniques: the Howell test, alternate Cover test, and Thorington test. Methods: 220 healthy Mexican children (age 5.06-17.11) participated in this study. Phorias were quantified at both distances using each test, from the least to the most disruptive. The stereopsis degree and near point of convergence (break/recovery) were analyzed to understand their role on the visual system's sensorimotor balance. Results: For the exophoria/esophoria at near, the alternate Cover and Thorington tests showed similar values. The exophoria at distance, was similar with the alternate Cover and Howell tests, while esophoria, with the alternate Cover and Thorington tests. The break value and near exophoria relates to each other and affect the stereopsis degree, whereas age is associated with the stereopsis degree and break value. Conclusions: The analysis revealed that alternate Cover and Thorington tests can substitute one another, but not with the Howell test. The test's specific dissociation method may explain these results. Analyzing the binocular visual system provides information about its sensorimotor balance and fragility when faced to the technique’s degree of dissociation.

This work proposes a metaheuristic-based approach for hyperparameter selection in a multilayer perceptron to classify electromyographic signals. The main goal of the study is to improve the performance of the model by optimizing four important hyperparameters: the number of neurons, the learning rate, the epochs, and the training batches. The approach proposed in this work shows that hyperparameter optimization using particle swarm optimization and gray wolf optimizer significantly improves the performance of a multilayer perceptron for classifying EMG motion signals. The final model achieved an average classification rate of 93% for the validation phases. The results obtained are promising and suggest that the proposed approach may be helpful for the optimization of deep learning models in other signal processing applications.

The practice of spatial econometrics revolves around a weighting matrix, which is often supplied by the user on previous knowledge. This is the so called $\mathbf{W}$ issue. Probably, the aprioristic approach is not the best solution although, nowadays, there few alternatives for the user. Our contribution focuses on the problem of selecting a $\mathbf{W}$ matrix from among a finite set of matrices, all of them considerer appropriate for the case. We develop a new and simple method based on the Entropy corresponding to the distribution of probability estimated for the data. Other alternatives, which are common in current applied work, are also reviewed. The paper includes a large Monte Carlo to calibrate the effectiveness of our approach compared to the others. A well-known case study is also included.

We consider an evolutionary model of social coordination in a 2x2 game where two groups of players prefer to coordinate on different actions. Players can pay a cost to learn their opponent's group: if they pay it, they can condition their actions on the groups. We assess the stability of outcomes in the long-run using stochastic stability analysis. We find that three elements matter for the equilibrium selection: the group size, the strength of preferences, and the information's cost. If the cost is too high, players never learn the group of their opponents in the long-run. If one group is stronger in preferences for its favorite action than the other, or its size is sufficiently large compared to the other group, every player plays that group's favorite action. If both groups are strong enough in preferences, or if none of the group's size is large enough, players play their favorite actions and miscoordinate in inter-group interactions. Lower levels of the cost favor coordination. Indeed, when the cost is low, in inside-group interactions, players always coordinate on their favorite action, while in inter-group interactions, they coordinate on the favorite action of the group that is stronger in preferences or large enough.

The Steepest Descent (or Ascent) algorithm is one of the most widely used algorithms in Science, Technology, Engineering, and Mathematics (STEM). However, this powerful mathematical tool is neither taught nor even mentioned in K12 education. We study whether it is feasible for elementary school students to learn this algorithm, while also aligning with the standard school curriculum. We also look at whether it can be used to create enriching activities connected to children’s real-life experiences, thus enhancing the integration of STEM and fostering Computational Thinking. To address these questions, we conducted an empirical study in two phases. In the first phase, we tested the feasibility with teachers. In a face-to-face professional development work-shop with 457 mathematics teachers actively participating using an online platform, we found that after a 10-minute introduction they could successfully apply the algorithm and use it in a couple of models. They were also able to complete two complex and novel tasks: selecting models and adjusting the parameters of a model that uses the steepest descent algorithm. In a second phase, we tested the feasibility with 90 fourth graders from 3 low Socioeconomic Status (SES) schools. Using the same introduction and posing the same questions, we found that they were able to understand the algorithm and successfully complete the tasks on the online platform. Additionally, we found that close to 75% of the students completed the two complex modeling tasks and performed similarly to the teachers.

The Steepest Descent (or Ascent) algorithm is one of the most widely used algorithms in Science, Technology, Engineering, and Mathematics (STEM). However, this powerful mathematical tool is neither taught nor even mentioned in K12 education. We study whether it is feasible for elementary school students to learn this algorithm, while also aligning with the standard school curriculum. We also look at whether it can be used to create enriching activities connected to children’s real-life experiences, thus enhancing the integration of STEM and fostering Computational Thinking. To address these questions, we conducted an empirical study in two phases. In the first phase, we tested the feasibility with teachers. In a face-to-face professional development work-shop with 457 mathematics teachers actively participating using an online platform, we found that after a 10-minute introduction they could successfully apply the algorithm and use it in a couple of models. They were also able to complete two complex and novel tasks: selecting models and adjusting the parameters of a model that uses the steepest descent algorithm. In a second phase, we tested the feasibility with 90 fourth graders from 3 low Socioeconomic Status (SES) schools. Using the same introduction and posing the same questions, we found that they were able to understand the algorithm and successfully complete the tasks on the online platform. Additionally, we found that close to 75% of the students completed the two complex modeling tasks and performed similarly to the teachers.

We explores the relational, dynamic elements of Complex Buildings, a type of architecture designed to incubate uses, located in urban areas with high housing density. The uses of Complex Buildings concern different elements, including the network of agents using or managing them, the environment, and the activities and functions that take place occasionally, temporarily or permanently. Data was gathered through ethnographic research lasting 6 months and a chronotopian approach was used to describe time and space. We analyzed and discussed the interaction of the elements of Complex Buildings through a cellular automaton model, a computational method that simulates the growth of complex systems. It was used here to generate patterns that suggest configurations of uses that can optimize management and therefore increase economic and social capital. The cellular automaton model was also used to develop an abstraction of the Centquatre, a public cultural center in Paris. This center is a good example of a Complex Building, being based on a public-private partnership and having an architectural configuration designed to host a wide range of art, social and productive activities. The building includes a large central space used as an urban public area open to different types of people. The importance of this case study lies in its capacity to produce economic value by combining different uses, and also by welcoming different people to the public space. Regarding the building as a living organism, the cellular automaton model reveals the determinant nature of the concepts of configuration, compatibility of uses and economic value generated by the presence of people. We argue that this approach makes it possible to show that the space-time design and public space dimensions are determinant factors in Complex Buildings.

The purpose of this work was analysing the compaction of a cohesive material using different DEM simulators to determine the equivalent contact models and identify how some parameters of the simulations affect the compaction results (maximum force and compacts appearance) and computational costs. For that purpose, three cohesion contact models were tested (‘linear cohesion’ in EDEM; ‘SJKR’ and ‘SJKR2’ in LIGGGHTS). The influence of the particle size distribution (PSD) on the results was also investigated. Further assessments were performed on the effect of selecting different timesteps, using distinct conversion tolerances for exporting the 3D models to STL files and moving the punch with different speeds. Consequently, it was possible to determine that a timestep equal to a 10% Rayleigh timestep, a conversion tolerance of 0.01 mm and a punch speed of 0.2 m/s are adequate for simulating the compaction process using the contact models in this work. In addition, the results determined that the maximum force was influenced by the PSD because of the rearrangement of the particles. The PSD was also related to the computational cost because of the number of simulated particles and their sizes. Finally, an equivalence was found between the linear cohesion and SJKR2 contact models

As a consequence of the global sanitary crisis in early 2020, universities had to tackle with a sudden shift in their teaching-learning strategies so that the preset competences could be fulfilled. This study presents the learning outcomes of the tasks implemented, student experiences and feedback, as well as some reflections from the instructors with a holistic perspective of the courses due to the measures and adaptations adopted. Six courses taught at Civil Engineering degrees of three universities, two from Spain and one from Peru, are analyzed. The teaching and evaluation strategies are described and some reflections are made by comparing the student’s performance with the previous course. Although the shift to online learning had to be made from day to day, with no time for preparation, the experience has proved that online learning can be beneficial in some aspects and have probably come to stay, although some others are difficult to replace with respect to face-to-face learning, especially students’ engagement and motivation.

Numerous studies on evaporative cooling systems have been conducted globally, but there is a scarcity of investigations in eastern Africa. The few studies undertaken in this region have primarily focused on their application in food storage and preservation, rather than for building purpose. The goal of this study is to review the most recent advancements in evaporative cooling technology, which would be relevant in eastern Ethiopia and could provide adequate cooling, give adequate thermal comfort, use less energy, and minimize environmental effect in hot and dry areas. There aren't many studies on evaporative cooling systems for building applications in Eastern Africa as a whole, thus this review has taken into account studies conducted in regions with climates similar to eastern Ethiopia. This study covers the classification, operation, and performance of evaporative cooling systems in hot and dry climate. Evaporative cooling systems work well in hot and dry climates, as revealed by this review study.

COVID-19 was a terrible worldwide pandemic that caused a global public health crisis, with numerous deaths and a severe economic depression. To suppress the spread of COVID-19 and initiate patient isolation and contact tracing to reduce its effect, early diagnosis was required, with real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test being the most widely used. However, the RT-PCR test was sometimes found to be lengthy and inaccurate and; for that reason, in many cases of severe complications of COVID-19 pneumonia, chest screening with radiography imaging was preferred. In this paper, we carried out a study for COVID-19 detection from computed tomography images, and compared the obtained results using deep learning (DL) and support vector machine (SVM). The findings showed that, despite the excellent results shown by deep learning, the accuracy in predicting COVID-19 using SVM, in the presence of small databases, was slightly higher than DL. The execution time using SVM was also shorter

The textile and clothing (T&amp;C) industry, despite its significant contribution to the European economy, is one of the most polluting industries globally. Therefore, the EU's Green Deal has identified the T&amp;C sector as a strategic area for allocating public funding and transitioning towards a circular economy (CE). In this context, the “Circular Design for Natural Fibers” project, financed by the PNRR MICS “Made in Italy Circolare e Sostenibile” programme, focuses on enhancing the use of natural fibrous material, related by-products and waste from local production chains. In the research, a crucial aspect is the evaluation of the effectiveness of circularity through life cycle approaches, such as LCA, LCC, S-LCA and LCSA, for environmental, economic and social sustainability evaluation, respectively. A systematic review was carried out, to provide a synthesis of the available scientific evidence regarding the life cycle approaches in the international/national context within the production, processing, and post-consumer supply chains of natural fibers. The study identifies gaps in the literature on life cycle evaluation approaches for natural fibers. Specifically, the LCA approach appears preponderant compared to the others. The paper offers insights for researchers and professionals interested in improving the sustainability of natural fiber production processes and the evaluation of their overall sustainability.

This paper investigates pseudo-polymorphism in 2-pyridylmethoxy derivatives of p-tert-butylcalix[4]arene (PyC4), p-tert-butyldihomooxa-calix[4]arenes (PyHOC4), and p-tert-butylhexahomotrioxacalix[3]arenes (PyHO3C3), presenting 11 crystal structures with 15 crystallographically independent molecules. The macrocycle of PyC4 is smaller and less flexible with respect to those of PyHOC4 and PyHO3C3 and in solution, the cone conformation of these three molecules exhibit different point symmetries: C4, Cs and C3, respectively. A correlation is observed between the macrocycle's structural rigidity and the number of pseudo-polymorphs formed. The more rigid PyC4 displays a higher number (6) of pseudo-polymorphs compared to PyHOC4 and PyHO3C3, which exhibit a smaller number of crystalline forms (3 and 2, respectively). The X-ray structures obtained show that the conformation of the macrorings is primarily influenced by the presence of an acetonitrile guest molecule within the cavity, with limited impact from crystal packing and intermolecular cocrystallized solvent molecules. Notably, both calix[4]arene derivatives produce host-guest complex with acetonitrile, while the most flexible and less aromatic PyHO3C3 do not give crystals with acetonitrile as guest. Intertwined 1D and 2D solvent channel networks were observed in the PyHOC4-hexane and in the PyHO3C3-H2O-MeOH crystal structures, respectively, while the other pseudopolymorphs of PyHOC4 and PyHO3C3 and all PyC4 crystal forms exhibit a closely packed crystal structures without open channels.

Fibre reinforced cementitious materials (FRC) have become an attractive alternative for structural applications. Among such FRC, steel and polyolefin fibre reinforced concrete and glass fibre reinforced concrete are the most used ones. However, in order to exploit the properties of such materials structural designers need constitutive relations that reproduce FRC fracture behaviour accurately. This contribution analyses the suitability of multilinear softening functions combined with a cohesive crack approach for reproducing the fracture behaviour of the FRC previously mentioned. The implementation performed accurately simulates the fracture behaviour while being versatile, robust and efficient from a numerical point of view.

The permeation of dioxin-like pollutants, namely, chlorinated dibenzodioxins and dibenzofurans, through lipid membranes has been simulated using classic molecular dynamics (CMD) combined with the umbrella sampling approach. The most toxic forms of chlorinated dibenzodioxin and dibenzofuran, 2,3,7,8-tetrachloro-p-dibenzodioxin (TCDD) and 2,3,7,8-tetrachlorodibenzofuran (TCDF), and a dioleyl-phosphatidylcholine (DOPC) lipid membrane of 50 Å wide have been chosen for our study. The free energy profile shows the penetration process is largely favoured thermodynamically (DG≈-12 kcal/mol), with a progressively decrease of the free energy until reaching the energy minima at distances of 8Å and 9.5Å from the centre of the membrane for, respectively, TCDD and TCDF. At the centre of the membrane, both molecules display subtle local maxima with free energy differences of 0.5 and 1 kcal/mol with respect to the energy minima for TCDD and TCDF, respectively. Furthermore, the intermolecular interactions between the molecules and the lipid membrane have been characterized at the minima and the local maxima using hybrid quantum mechanics/molecular mechanics energy decomposition analysis (QM/MM-EDA). Total interaction energies of -17.5 and -16.5 kcal/mol have been found at the energy minima for TCDD and TCDF, respectively. In both cases, the dispersion forces govern the molecule-membrane interactions, no significant changes have been found at the local maxima, in agreement with the classical free energy profile. The small differences found in the results obtained for TCDD and TCDF point out the adsorption and diffusion processes through the cell membrane are not related to the different toxicity shown by these pollutants.

The article analyzes Bernoulli 's binary sequences in representation of empirical events about the distribution of natural resources and population sizes. Considering the event as a nonlinear system, and consisting of two dependent random variables, with memory and probabilities in maximum finite or infinite lengths, constant and equal to ½ for both variables (stationary process). The expressions of the possible trajectories remain constant in sequences that are repeated alternating the presence or absence of one of the variables at each iteration (asymmetric). There are constant oscillations in the event except if the variables X₁ and X₂ are regulated as a function of time Y. It is observed that the variables X₁ and X₂ assume in time T_k → ∞ specific behaviors (geometric variable) that can be used as management tools for random systems. In this way, the article seeks to know from this analyzes, the maximum entropy of information in the system by a theoretical view and how to model resources distribution or containment in the given problem.

Cities require flexible and participatory planning methodologies to address complex and evolving urban challenges. In Italy, the legislative framework is defined at the Regional level, according to the National laws and jurisprudence. The Lombardy region introduced the Planning Document (PD) in the Territorial Government Plan (PGT), as a strategic tool capable of adapting to changes. Based on a strategic vision, this document is useful to guide concrete actions for urban transformation, actively involving stakeholders, including citizens. The PD has the role to translate the political program into an urban planning design. So, the role it has is both technical and political. The political dimension is usually deepened in the strategic component of the document. Following the formation process of the whole city plan, the authors define the key strategies in the PD for a healthier urban future for the city of Voghera. It emerges as a balanced urban development that combines economic growth, environmental preservation, and community well-being. In the paper the authors synthesize the Voghera’s PD as an example of strategic planning that interacts with the practical planning actions and that guides both the public and the private decisions about the city development towards a healthier city.

In manufacturing chatter is an unwanted phenomenon that can lead to product quality reduction and tool wear. Real time chatter detection is key to preventing these issues and improving overall machining efficiency. In this paper we propose an unsupervised chatter detection method using autoencoders (AE) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm that uses internal signals of Computer Numerical Control (CNC) machines. The proposed method starts by using an AE to extract features from raw internal signals collected from CNC machines. This step reduces the dimensionality of the data and captures the underlying patterns of chatter. Then the extracted features are fed into DBSCAN clustering algorithm which is a density based algorithm that groups similar data points and identifies outliers. We tested the proposed method with real world data collected from various CNC machines. The results show that our unsupervised chatter detection method has high accuracy, precision and recall, can detect chatter and distinguish it from normal machining. Also the method is robust to noise and can adapt to dynamic machining conditions. In summary our work presents an unsupervised chatter detection method using AE and DBSCAN clustering that uses internal signals of CNC machines. This method is a reliable and efficient solution for real time chatter detection so manufacturers can improve product quality, optimize machining process and reduce tool wear during machining.

This article proposes a monitoring system that allows to track transitions between different stages in the berry harvesting process (berry picking, waiting for transport, transport, and arrival to the packing) solely using information from temperature and vibration sensors located in the basket. The monitoring system assumes a characterization of the process based on Hidden Markov Models and uses the Viterbi algorithm to perform inference and estimate the most likely state trajectory. The obtained state trajectory estimate is then used to compute a potential damage indicator in real-time. The proposed methodology does not require information about the weight of the basket to identify each of the different stages, which makes it effective and more efficient than other alternatives available in the industry.

Despite the advancements in evidence-based medicine, many hospitals still maintain high rates of patients undergoing prolonged preoperative fasting. The goal of this study is to determine the prevalence of prolonged fasting time among patients undergoing elective surgeries at a Brazilian university hospital and its associations with clinical and sociodemographic variables. This cross-sectional study was conducted between May and November 2019 and included patients of all ages undergoing elective surgeries. Out of the 293 patients analyzed, 64.2% were male, with ages ranging from 1 to 85 years, and 93.9% were classified as ASA I or II. The prevalence of preoperative fasting exceeding 8 hours was 89.4%. An average fasting time exceeding 11 hours was observed across all age groups. Patients who underwent procedures in the afternoon had an average fasting time that was 16% longer than those in the morning period (13.84 vs. 11.92, p<0.001). Surgery time (r=0.134, p<0.03) and anesthesia times (r=0.121, p<0.04) demonstrated a weak correlation with fasting time. Despite the international consensus on preoperative fasting time, our study demonstrated low adherence to current recommendations. Therefore, healthcare professionals should ensure the comprehension of fasting guidelines, and further studies should aim to identify effective solutions to mitigate prolonged fasting.