Globally, non-communicable diseases like hypertension are on the rise, existing concurrently with the human immunodeficiency virus (HIV) in populations, especially those in low- to middle-income countries. The introduction of antiretroviral treatment (ART) for people living with HIV was welcomed with great enthu-siasm across populations. A cross-sectional study of 100 purposively selected adult participants on an-tiretroviral treatment living in the OR Tambo district was conducted to determine factors associated with treatment outcomes among patients living with HIV and hypertension comorbidity. The data was analyzed using the Statistical Package for Social Sciences, with a p-value of 0.05 considered significant. A total of 86% of the female population, with a mean age of 39.76, was studied. Participants with improved viral load and CD4 cell count after initiation of ART increased from 63% to 68% and 74% to 90%, respectively whilst viral load suppression increased from 45.1% to 90.2%. Hypertension post-ART initiation increased from 9% to 34%, exacerbated by smoking (12%), alcohol (14%), vegetable consumption (39%), skipping breakfast (50%), sugar use (62%), and vigorous physical activity (12%). The onset of hypertension was linked to the start of ART, and risky behaviors influenced treatment outcomes. Primordial prevention, like strong health promotion inter-ventions for risk factors, is needed to improve life expectancy.

In this contribution a new configuration of a DC-DC Boost and Buck-Boost converters is proposed to track sinusoidal signals exactly, with zero tracking error. The stage is conformed by two DC-DC converters connected to the same load, this is, they are not connected in cascade. To track exactly the sinusoidal reference the control scheme is base on the indirect control algorithm and the harmonic balance method. The proposed algorithm considers a second control input with the end of cancel out the second harmonic, this second harmonic is produced by the non linearity of the model and must be cancelled since there must be a single frequency in the output. The result is such that the converters can track sinusoidal signals with exactly zero error, some numerical results are presented to corroborate the proposal.

Fifty bull calves of the Continental × British crossbred (147.0 ± 1.67 kg body weight, BW) were used in a completely randomized design to investigate the effect varying levels and duration of calcium propionate (CaPr) supplementation on the growth performance, body fat reserves, serum metabolites, and hemogram of high-risk newly received stocker calves. These calves were individually housed and fed a received-diet for 56 d. The calves received the following treatments: 1) No CaPr (CTL), 2) 20 g CaPr/calf/d, 3) 40 g CaPr/calf/d, 4) 60 g CaPr/calf/d, and 5) 80 g CaPr/calf/d, during 14, 28, 42 and 56 d the after arrival. The supplementation with 20 g CaPr from 28 to 56 d after arrival increases average daily gain (ADG) and BW (p < 0.05), and DMI is not affected (p > 0.05). This is reflected at 28 d with increases (p < 0.05) in ADG:DMI ratio and longissimus muscle area (LMA), and at 56 d in back fat thickness (BFT) y fat thickness at the rump (FTR). Also, with 20 g, blood urea nitrogen decreased (p < 0.05); and increases were observed in the activity of gamma glutamyltransferase, monocytes (quadratic trend, p < 0.07) and granulocytes% (quadratic effect, p < 0.03). However, as the level of CaPr increased during the first 14 d after arrival, daily water intake, creatinine, total cholesterol, mean corpuscular hemoglobin concentration (linear effect, p < 0.05), globulin, calcium and mean corpuscular volume (linear trend, p = 0.08) increased, while alkaline phosphatase (linear trend, p = 0.07) and lymphocytes (linear effect, p = 0.05) decreased. Finally, the different levels of CaPr supplementation did not produce any significant effects or differences (p > 0.05), in the remaining serum metabolites and hemogram (p > 0.05). Ultimately, the inclusion of 20 g CaPr/calf/d in the diet for 28 d in newly received stocker calves increases ADG, ADG:DMI ratio and LMA. If extended to 42 or 56 d, the increases in ADG persist, but there is also a rise in body fat reserves (BFT and FTR) at the expense of a reduction in ADG:DMI ratio. Furthermore, the different supplementation levels did not impact the reference range for most serum metabolites or the health of stocker calves.

We study the possibility of determining the octant of the neutrino mixing angle 23, that is, whether 23 > 45 or 23 < 45, in long baseline neutrino experiments. Here we numerically derived the sensitivity limits within which these experiments can determine, by measuring the probability of the  ! e transitions, the octant of 23 with a 5 certainty. The interference of the CP violation angle  with these limits, as well as the effects of the baseline length and the run-time ratio of neutrino and antineutrino modes of the beam have been analyzed.

Let G be a graph with n vertices and let 1; 2; : : : ; n be the eigenvalues of Randic matrix. The Randic Estrada index of G is REE(G) = Ón i=1 ei . In this paper, we establish lower and upper bounds for Randic index in terms of graph invariants such as the number of vertices and eigenvalues of graphs and improve some previously published lower bounds.

This article explores the synergies and progression of feminism towards a comprehensive, emancipatory and sustainable policy from a theoretical point of view, particularly from a radical gender focus, suggesting the masculinist theory as a complement in the fight against the patriarchal-capitalist system, whose greatest achievement was to use a ‘feminist rhetoric’ with no feminist content, which implies a hidden reconfiguration, even more patriarchal, of the geographical borders of countries from the notion of State-nations to the entrepreneurial-nations. A theoretical model is proposed to analyse the adoption and compliance feminist behaviour in order to identify the uncompliant and unsustainable behaviour, that is, the friendly machismo or feminism light. Finally, in a preliminary manner, the foundations of a new masculinist theory and policy will be listed as a necessary step towards a deeply feminist and radical emancipatory policy.

This article analyses from a post-Marxist view, particularly, an ecological and gender-oriented perspective, the perception and attitudes of the Mexican people by gender, political affiliation and income level towards such current environmental issues as global warming, water shortage, water pollution and the influence of economic growth on the environment, among others. It highlights the influence of political ideology on the environment and of gender awareness on conservation and a more positive attitude towards ecological issues, despite women having usually been excluded from the administrative and decision-making arenas. A new theoretical model is proposed related to the Responsibility Footprints, a new concept more critical than the neoliberal Corporate Social Responsibility. The data for this study come from the 2012 International Social Survey Program. The results analysed brought to light some relevant questions for designing public policies that will greatly bolster initiatives to prompt better female professional involvement in the conservation of natural resources.

The objective of this study was to analyze the effects of a pulmonary telerehabilitation (TR) program in young adults with post-COVID-19 syndrome. The information of sixteen students' medical files were analyzed and allocated to one of two groups (control=CG/experimental=EG). Twelve TR sessions were performed distantly and asynchronously at the EG patients' homes during 4-weeks. The program included diaphragmatic pattern breathing and aerobic exercises. The parameters: i) vital signs (oxygen saturation "SpO2", heart rate "HR", respiratory rate "RR" and blood pressure "BP"; ii) physical capacity “Sit-to-stand test”; iii) cardiorespiratory capacity “6-Minute Walk Test”; and iv) perceived effort "Borg scale" were assessed in both groups. The statistical analyses showed a significant decrease of RR and HR (p < 0.012) accompanied by a significant increase in SpO2 (p < 0.042), physical (p < 0.012) and respiratory (p < 0.028) capacity. The perceived effort decreased significantly in both groups (CG: p < 0.006; EG p < 0.001) only for physical but not for cardiorespiratory capacity (p < 0.106). There were no statistical changes registered in BP (p > 0.05). The current study suggests that a TR program that involves breathing and aerobics exercises is feasible and effective in treating post-COVID-19 syndrome in young patients.

Abstract The modified Bessel function (MBF) of the first kind is a fundamental special function in mathematics with applications in a large number of areas. When the order of this function is integer, it has an integral representation which includes the exponential of the cosine function. Here we generalize this MBF to include a fractional parameter, such that the exponential in the previously mentioned integral is replaced by a Mittag-Leffler function. The necessity for this generalization arises from a problem of communication in networks. We find the power series representation of the fractional MBF of the first kind, as well as some differential properties. We give some examples of its utility in graph/networks analysis and mention some fundamental open problems for further investigation.

The aim of this work was to describe the physiological limitations induced under drought conditions in young sweet orange trees, including the crop capability to recuperate its physiological status once re-watering, and after a water withholding. The trial was conducted during two consecutive months (July and August) in two-years old sweet orange trees. Three irrigation treatments were arranged: A full irrigation treatment; (FI); a low-frequency deficit-irrigation treatment (LFDI); and a sustained-deficit irrigation (SDI) treatment. The obtained results showed that for Stem values below -1.5 MPa, significant decreases in gas exchange rates, evidencing diffusive limitations to drought stress. Additionally, there was evidence of increased osmolyte synthesis, compatible as a defensive response to prevent oxidative damage. Likewise, the isohydric behaviour observed also resulted in significant decreases in gs even for moderate stress situations. In addition, it was observed that in the LFDI treatment, the stress levels reached caused a significant increase in the levels of Pro and MDA, which were not equal to those detected in FI during the recovery periods, which leads us to assume that potential values below -1.8 MPa would be causing significant oxidative damage with no capacity for subsequent recovery, and probably affecting the final yield.

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

This work presents an analytical methodology to predict meat juiciness (discriminant semi-quantitative analysis using groups of intervals of intramuscular fat) and intramuscular fat (regression analysis) in Longissimus thoracis et lumborum (LTL) muscle of Bísaro pigs using as independent variables the animal carcass weight and parameters from color and image analysis. These are non-invasive and non-destructive techniques which allow development of rapid, easy and inexpensive methodologies to evaluate pork meat quality in a slaughterhouse. The proposed predictive supervised multivariate models were non-linear. Discriminant mixture analysis to evaluate meat juiciness by classified samples into three groups—0.6 to 1.1%; 1.25 to 1.5%; and, greater than 1.5%. The obtained model allowed 100% of correct classifications (92% in cross-validation with seven-folds with five repetitions). Polynomial support vector machine regression to determine the intramuscular fat presented R2 and RMSE values of 0.88 and 0.12, respectively in cross-validation with seven-folds with five repetitions. This quantitative model (model’s polynomial kernel optimized to degree of three with a scale factor of 0.1 and a cost value of one) presented R2 and RSE values of 0.999 and 0.04, respectively. The overall predictive results demonstrated the relevance of photographic image and color measurements of the muscle to evaluate the intramuscular fat, rarther than the usual time-consuming and expensive chemical analysis.

This study analyzes oral supplement of molecular iodine (I2) alone and in combination with the neoadjuvant therapy 5-fluorouracil/epirubicin/cyclophosphamide or taxotere/epirubicin (FEC/TE) in women with Early (stage II) and Advanced (stage III) breast cancer. In the Early group, 30 women were treated with I2 (5 mg/day) or placebo (colored water) for 7–35 days before surgery. For the Advanced group, 30 patients received I2 or placebo along with FEC/TE treatment. After surgery, all patients received FEC/TE + I2 for 170 days. I2 supplementation showed a significant attenuation of the side effects and absence of tumor chemoresistance. Control, I2, FEC/TE, and FEC/TE+I2 groups exhibit response rate of 0, 33%, 73%, and 100%, respectively, and a pathologic complete response of 18%, and 36% in the last two groups. Five-year disease-free survival rate was significantly higher in patients with I2 supplement before and after surgery compared to those receiving the supplement only after surgery (82% vs. 46%). I2-treated tumors exhibit less invasive potential, and significant increases in apoptosis, estrogen receptor expression, and immune cell infiltration. Transcriptomic analysis indicated activation of the antitumoral immune response. The results led us to register a phase III clinical trial analyzing chemotherapy + I2 treatment for advanced breast cancer.

A substantial body of phenomenological and theoretical work over the last few years strengthens the possibility that the vacuum energy density (VED) of the universe is dynamical, and in particular that it adopts the `running vacuum model' (RVM) form, in which the VED evolves mildly as $\delta \rho_{\rm vac}(H)\sim \nu_{\rm eff} m_{\rm Pl}^2{\cal O}\left(H^2\right)$, where $H$ is the Hubble rate and $\nu_{\rm eff}$ is a (small) free parameter. This dynamical scenario is grounded on recent studies of quantum field theory (QFT) in curved spacetime and also on string theory. It turns out that what we call the `cosmological constant', $\Lambda$, is no longer a rigid parameter but the nearly sustained value of $8\pi G(H)\rho_{\rm vac}(H)$ around (any) given epoch $H(t)$, where $G(H)$ is the gravitational coupling, which can also be very mildly running (logarithmically). Of particular interest is the possibility suggested in past works that such a running may help to cure the cosmological tensions afflicting the $\Lambda$CDM. In the current study, we reanalyze it in full and we find it becomes further buttressed. Using the modern cosmological data, namely a compilation of the latest SNIa+BAO+$H(z)$+LSS+CMB observations, we probe to which extent the RVM provides a quality fit better than the concordance $\Lambda$CDM model, paying particular emphasis on its impact on the $\sigma_8$ and $H_0$ tensions. We utilize the Einstein-Boltzmann system solver \texttt{CLASS} and the Monte Carlo sampler \texttt{MontePython} for the statistical analysis, as well as the statistical DIC criterion to compare the running vacuum against the rigid vacuum ($\nu_{\rm eff} = 0$). On fundamental grounds, $\nu_{\rm eff}$ receives contributions from all the quantized matter fields in FLRW spacetime. We show that with a tiny amount of vacuum dynamics ($|\nu_{\rm eff}|\ll 1$) the global fit can improve significantly with respect to the $\CC$CDM and the mentioned tensions may subside to inconspicuous levels.

Wildfires are important sources of landscape change in Mediterranean environments, creating large patches of natural habitats (i.e., scrublands) inside protected areas, whereas woodland patches remained at the border in the vicinity of human settlements. Landscape patterns resulting from these gradients influence habitat suitability for mesocarnivores regarding food and shelter. In winter and summer 2019, we sampled 16 independent line-transects of four camera traps each (for a total of 64 cameras), covering the main habitats of the study area (woodlands, scrublands, and crops). Cameras were baited to compensate for low detectability of target species, and mesocarnivore contacts were analyzed by means of GLMMs and occupancy models. We hypothesized that Mediterranean mesocarnivores were constrained by two opposing forces, pushing them living in semi-natural but highly fragmented and heterogeneous landscapes created by humans, or living in natural but less suitable and continuous habitats created by fire regimes. In the former case, mesocarnivores will find protection against predators and resting sites in forests, as well as improved food opportunities in crops and urban areas, despite the possible interference with humans and their pets. Potential cascading effects linked to ecological roles of Mediterranean mesocarnivores on the succession of Mediterranean landscapes would imply longer-term effects of human disturbance on landscape trends.

In this study, the values of the interfacial energies of seven different polymer-water systems obtained by Sessile Drop Accelerometry (SDACC) are compared with the values obtained by the Young’s-equation-based Owens-Wendt method. The SDACC laboratory instrument –a combination of a drop shape analyzer with high-speed camera and a microgravity tower- and the evaluation algorithms, are designed to measure the interfacial energies as a function of the geometrical changes of a sessile droplet shape due to the effect of “switching off” gravity during the experiment. The method bases on Thermodynamics of Interfaces and differs from the conventional aproach of the two hundred-years-old Young’s equation in that it assumes a thermodynamic equilibrium between interfaces, rather than a balance of forces on a point of the solid-liquid-gas contour line. A comparison of the mathematical model that supports the SDACC method with the widely accepted Young`s equation is discussed in detail in this study.

A new method, the sessile drop accelerometry (SDACC) for the study and measurement of the interfacial energies of solid-liquid-gas systems, is tested and discussed in this study. The laboratory instrument and technique –a combination of a drop shape analyzer with high-speed camera and a laboratory drop tower- and the evaluation algorithms, were designed to calculate the interfacial energies as a function of the geometrical changes of a sessile droplet shape due to the effect of “switching off” gravity during the experiment. The method bases on the thermodynamic equilibrium of the system interfaces and not on the balance of bi-dimensional tensions on the solid-liquid-gas contour line. A comparison of the mathematical model that supports the method with the widely accepted Young`s equation is discussed in this study.

This study examined how practice distribution schedules influenced accuracy and efficacy in the tennis serve. 24 recreational players were randomized into two experimental groups. Both groups carried out 4 series of 10 services per session during 12 sessions. Massed practice group did not rested between services and rested 10 seconds between series. Distributed practice group rested 10 seconds between services and 30 seconds between series. The accuracy and efficacy were registered and computed based on the 2D digitalization. The learning and retention were tested in a post-test and retention test. The learning program increased the efficacy in the post-test in both groups (p =.001 massed group; p =.015 distributed group). On the retest, the group of massed practice decreased efficacy (p =.021). In accuracy, the group of massed practice reduced its performance in the post-test (p =.015). The effects of the program on the accuracy in the retention test were not observed. It is concluded that this type of sports learning programs, applied at a recreational level, can provide a rigorous approach that contributes with guarantees to the learning of tennis.

This analytical cross-sectional study was designed to evaluate the association between glycemic control and peripheral arterial disease in patients with diabetic foot with more than ten years of evolution of diabetes mellitus who attended the diabetic foot outpatient clinic of the Guillermo Almenara National Hospital between June 2015 and February 2017. Glycosylated hemoglobin (HbA1C) and ankle-brachial index (ABI) were used to diagnose glycemic control and peripheral arterial disease, respectively. A generalized Poisson log-linear regression model was used to calculate the crude (cPR) and adjusted (aPR) prevalence ratios, with 95% confidence intervals, and a significance level of p < 0.05. 226 patients were included in the study, finding 23% (n=52) with good glycemic control, and 44.7% (n=101) with peripheral arterial disease. The adjusted model found statistically significant associations for glycemic control, age, and sedentary lifestyle with peripheral arterial disease. Compared with patients with good glycemic control, those with poor glycemic control had a 34% higher probability of presenting peripheral arterial disease (aPR: 1.34, 95%CI: 1.01-1.79, p=0.045). The prevalence of good glycemic control in the population with diabetic foot is low. Poor glycemic control was found to be independently associated with the presence of peripheral arterial disease.

In this study, the unsteady Reynolds-averaged Navier-Stokes (URANS) equations are employed in conjunction with the Menter Shear Stress Transport (SST)-Scale-Adaptive Simulation (SAS) turbulence model in compressible flow, unstructured mesh and complex geometry. Whereas, other scale-resolving approaches in space and time, such as Direct Numerical Simulation (DNS) and Large-Eddy Simulation (LES), supply more comprehensive information about the turbulent energy spectra of the fluctuating component of the flow; however, previously mentioned avenues imply computationally intensive situations, usually performed over structured meshes and relatively simply geometries. In contrast, the SAS approach is designed according to “physically” prescribed length scales of the flow. More precisely, it operates by locally comparing the length scale of the modelled turbulence to the von Karman length scale (which is prescribed according to local fluid velocity derivatives and depends on the grid point distribution in the computational domain). This length scale ratio allows the flow to dynamically adjust the local eddy viscosity in order to better capture the large scale motions (LSM) in unsteady regions of URANS simulations. While SAS may be constrained to model only low flow frequencies or waivenumbers (i.e., LSM), its versatility and computational low-cost make it attractive to obtain a quick first insight of the flow physics; particularly, in those situations dominated by strong flow unsteadiness. The selected numerical application is the well-known M219 three-dimensional rectangular acoustic cavity from the literature at two different freestream Mach numbers, M∞ (0.85 and 1.35) and a length-to-depth ratio of 5:1. Thus, we consider the “deep configuration" in experiments by Henshaw. The SST-SAS model has demonstrated a satisfactory compromise between simplicity, accuracy and flow physics description.

Burkholderia are a group of Gram-negative bacteria that can cause a variety of diseases in at-risk populations. B. pseudomallei and B. mallei, the etiological agents of melioidosis and glanders, respectively, are the two clinically relevant members of the B. pseudomallei complex (Bpc). The development of vaccines against Bpc species has been accelerated in recent years, resulting in numerous promising subunits and glycoconjugate vaccines incorporating a variety of antigens. However, a second group of pathogenic Burkholderia species exists known as the Burkholderia cepacia complex (Bcc), a group of opportunistic bacteria which tend to affect individuals with weakened immunity or cystic fibrosis. To date there have been few attempts to develop vaccines to Bcc species. Therefore, the primary goal of this review is to provide a broad overview of the various subunit antigens that have been tested in Bpc species, their protective efficacy, study limitations, and known or suspected mechanisms of protection. Then, we assess the reviewed Bpc antigens for their amino acid sequence conservation to homologous proteins found in Bcc species. We propose that protective Bpc antigens with a high degree of Bpc-to-Bcc sequence conservation could serve as components of a pan-Burkholderia vaccine capable of protecting against both disease-causing groups.

Power converters with coupled inductors are very promising due to the high efficiency and high voltage gain. Apart from the aforementioned advantages, the boost-flyback converter reduces the voltage stress on the semiconductors. However, to obtain good performance with high voltage gains, the controller must include two control loops (current and voltage), and a compensation ramp. One of the most used control techniques for power converters is the peak current-mode control with compensation ramp. However, in the case of a boost-flyback converter there is no mathematical expression in the literature, to compute the slope of the compensation ramp. In this paper, a formula to compute the slope of the compensation ramp is proposed in such a way that a stable period-1 orbit is obtained. This formula is based on the values of the circuit parameters, such as inductances, capacitances, input voltage, switching frequency and includes some assumptions related to internal resistances, output voltages, and some other electrical properties related with the physical construction of the circuit. The formula is verified numerically using the saltation matrix and experimentally using a test circuit.

We consider two abstract systems of parabolic-hyperbolic type that model thermoelastic problems. We study the influence of the physical constants and the initial data on the nonexistence of global solutions that in our framework are produced by the blow-up in finite time of the norm of the solution in the phase space. We employ a differential inequality to find sufficient conditions that produce the blow-up. To that end, we construct a set that is positive invariant for any positive value of the initial energy. As a result we found that the coupling with the parabolic equation stabilizes the system, as well as the damping term in the hyperbolic equation. Moreover, for any pair of positive values $(\xi,\epsilon)$, there exist initial data such that the corresponding solution with initial energy $\xi$ blows-up at a finite time less than $\epsilon$. Our purpose is to improve results previously published in the literature.

Hot air frying is a new method of frying food, where the use of a small amount of oil is optional but recommended. The objective of this review was to know the state of the art of hot air frying technology, focusing on trends, and thus obtain new ideas for future work in this area of food. In conclusion, the availability of advanced devices will increase the demand for hot air fryers as demonstrated by the trend generating a great economic and social impact. This new technology not only provides health benefits, but also has environmental advantages. In addition, work focusing on food (i.e. tortilla chips, plantain chips, eggs and meats) is recommended, since there are not enough studies on the subject. Currently, research is being conducted on home fryers, so the use of fryers and their impact at the industrial level is a developing area that will require further research.

In recent years, the use of gamified systems in education has increased due to the growing empirical evidence of their usefulness in improving motivation and participation in learning processes. In order to take advantage of the opportunities for improvement in education presented by gamification, plus the decision to create gamified systems in higher education, this article investigates the willingness of student teachers to learn with gamified systems. The research method is quantitative with validated instruments to measure: 1) student perception of gamification; 2) player profile; and 3) screen time, with an n=569 student teachers from the fifteen regions of Chile. The results show that students prefer to learn with gamified systems than in a traditional way with a significant difference (Wilcoxon z= -18.86, p < 0.01). There are significant positive and negative relationships in correspondence with the Gamer Profile. However, as a finding, a negative relationship was found between the number of hours spent playing video games and the perception of learning through gamified systems. In conclusion, Chilean student teachers present a favorable disposition to teacher training with gamified systems. However, the disposition varies in relation to the number of hours spent playing video games.

The consumer’s acceptability of hamburgers elaborated with the flank of culling cows in which the content of salt or fat had been partially replaced was studied. A mixture of potassium chloride, potassium ferrocyanide and sodium ferrocyanide was used as substitutes for the salt. Oat flakes or a mixture of chia and flax seeds were used as substitutes for the fat. The hamburgers were tasted by 34 consumers. Consumers did not detect significant differences between the control and the rest of the formulations. Neither the gender nor the age of the consumers influenced the sensory appraisal. However, many comments regarding texture failures were recorded. Therefore, the substitution of salt and / or fat in the composition of hamburgers made with the flank of cows is a viable alternative for the commercialization of these pieces of low commercial value as long as the texture of the same is adjusted to resemble it to the control.

Gait is a basic cognitive propositive action that has been shown to be altered in late stages of neurodegenerative dementias. Nevertheless, alterations are less clear in mild forms of dementia, and the potential use of gait analysis as a biomarker of initial cognitive decline has hitherto mostly been neglected. We here report the results of a study of gait kinematic time series for two groups of patients (Mild Cognitive Impairment and mild Alzheimer's disease) and a group of matched control subjects. Two metrics based on permutation patterns are considered, respectively measuring the complexity and irreversibility of the time series. Results indicate that kinematic disorganisation is present at early phases of cognitive impairment; in addition, they depict a rich scenario, in which some joint movements display an increased complexity and irreversibility, while others a marked decrease. Beyond their potential use as biomarkers, complexity and irreversibility metrics can open a new door towards the understanding of the role of the nervous system in gait, as well as its adaptation and compensatory mechanisms.

Laser Cladding is one of the leading processes within Additive Manufacturing technologies, a fact which has concentrated an important amount of effort on its development. In regard to the latter, the current study aims to summarize the influence of the most relevant process parameters in the laser cladding processing of single and compound volumes (solid forms) made from AISI 316L stainless steel powders and using a coaxial nozzle for deposition. Process speed, applied laser power and powder flow are considered to be the main variables affecting laser cladding in single clads, meanwhile overlap percentage and overlapping strategy become also relevant when dealing with multiple clads. By means of setting appropriate values of each process parameter, the main goal of this paper is to develop a processing window in which a good metallurgical bond between the delivered powder and substrate is obtained, trying simultaneously to maintain processing times in their lowest value possible. Conventional metallography techniques were performed on the cross sections of the laser tracks to measure the effective dimensions of clads for dilution analysis, height and width for the values of overlap between contiguous clads and layers, and also to analyze them for physical defects such as porosity and cracks. The resulting solid piece was 8 mm high at 800 mm/min.

This study aims to identify the model that best approximates the credit spread that should be fixed on debt instruments issued by both public and private companies, considering the particularities of the Mexican market. Five models were analyzed: Merton's [1], those proposed by Denzler et al., the one presented in this paper, which includes the conformable derivatives, taking as a reference the change of variable made by Morales-Bañuelos et al., and the Corporate Default Risk Model (DRSK) for Publics Firms of Bloomberg [4]. The required financial information was obtained from the Bloomberg platform, from which the probabilities of default, credit spreads, and credit ratings for each company in the sample under the model (DRSK) were extracted directly. Likewise, the program developed by Moody's K.M.V. was used to obtain the EDF (Expected Default Frequencies). It was concluded that the Modified Merton model approximates to a greater extent the credit spreads that fix on a prime rate on the loans granted to the Mexican non-financial companies.

In this work, we apply ensemble formalism to a geometric agents model to study the effect of saving propensity in a system with money, credit, and debt. We calculate the partition function to obtain the total money of the system, with which we give an interpretation of the economic temperature in terms of the different payment methods available to the agents. We observe an interplay between the fraction of money that agents can save and the debt that can be financed. We also observe that the system’s entropy increases as the saved proportion increases and increases, even more, when debt is present.

Rapid SARS-CoV-2 self-tests have the potential to expand access to COVID-19 testing and improve community-level case detection, particularly in resource-constrained countries such as Kenya. However, prior to their introduction, their acceptability must be assessed. This qualitative study explored key decision-takers’ values towards SARS-CoV-2 self-testing in Kenya. Healthcare workers, representatives of civil society, and potential implementors from Mombasa and Taita-Taveta were selected as decision-takers. Semi-structured interviews and focus group discussions were used to collect data on their values towards self-testing. A thematic analysis approach was applied. Most informants considered that the Kenyan public is equipped to accept and use self-testing safely as an approach to help to reduce workload at public healthcare facilities, and know one’s COVID-19 status in a private manner. The informants emphasized the need to provide counselling to end-users, to support those needing to self-isolate, and to engage different civil society stakeholders in information provision on self-testing. Fear of stigma and of forced isolation were noted as potential deterrents to self-testing uptake for some individuals. In conclusion, there is high acceptability of self-testing in Kenya among decision-takers. However, enhanced education, counselling, and addressing deterrents to testing would be helpful to ensure effective use of SARS-CoV-2 self-testing in Kenya.

We demonstrate that the black hole evaporation can be modelled as a process where one symmetry of the system is spontaneously broken continuously. We then identify three free-parameters of the system. The sign of one of the free-parameters, governs whether the particles emitted by the black-hole are fermions or bosons. The present model explains why the Black Hole evaporation process is so universal. Interestingly, this universality emerges naturally inside certain modifications of gravity.

Climate change is expected to increase the occurrence of droughts with the hydrology in alpine systems being largely determined by snow dynamics. In this paper we propose a methodology to assess the impact of climate change on both meteorological and hydrological droughts taking into account the dynamics of the snow cover area (SCA). We will also analyse the correlation between these types of droughts. We have generated ensembles of local climate scenarios based on regional climate models (RCMs) representative of potential future conditions. We have considered several sources of uncertainty: different historical climate databases, simulations obtained with several RCMs, and some statistical downscaling techniques. We then used a stochastic weather generator (SWG) to generate multiple climatic series preserving the characteristics of the ensemble scenario. These were simulated within a cellular automata (CA) model to generate multiple SCA future series. They were used to calculate multiple series of meteorological drought indices, the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)) and a novel hydrological drought index (Standardized Snow Cover Index (SSCI)). A linear correlation analysis was applied to both types of drought to analyse how they propagate and the time delay between them. We applied the proposed methodology to the Sierra Nevada (southern Spain) where we estimated a general increase in meteorological and hydrological drought magnitude and duration for the horizon 2071-2100 under the RCP 8.5 emission scenario. The SCA droughts also revealed a significant increase in drought intensity. The meteorological drought propagation to SCA droughts is reflected in an immediate or short time (1 month), obtaining significant correlations in lower accumulation periods of drought indices (3 and 6 months). This will allow us to obtain information about meteorological drought from SCA deficits and vice versa.

Auto-labeling is one of the main challenges in 3D vehicle detection. Auto-labeled datasets can be used to identify objects in LiDAR data, which is a challenging task due to the large size of the dataset. In this work, we propose a novel methodology to generate new 3D based auto-labeling datasets with a different point of view setup than the one used in the most recognized datasets (KITTI, WAYMO, etc.). The performance of the methodology has been further demonstrated with the development of our own dataset with the auto-generated labels and tested under boundary conditions on a bridge in a fixed position. The proposed methodology is based on the YOLO model trained with the KITTI dataset. From a camera-LiDAR sensory fusion, it is intended to auto-label new datasets while maintaining the consistency of the Ground Truth. The main contribution of this work is a novel methodology to auto-label autonomous driving datasets using YOLO as the main labelling system. The performance of this approach is measured retraining the contrast models of the KITTI benchmark.

This brief communication intends to develop critical thinking on the development at different levels that could be evaluated in the well-being of humans from the local development towards a global scale or planetary point of view. Therefore it was presented and discussed how Artificial Intelligence tools could provide important contributions and influence in the design of critical thinking to develop ideas and insights within Research as well as funding for technology transfer. In this context it should be highlighted that the generation of funding and economy for sustainability that it should be based on critical thinking and analysis of what is need it from the close surrounding towards longer distances as well as in the inversed direction. In this regard, the main axes that support it are based on the importance of entailment of individuals in their close surrounding as well as to longer physical distances and cultural differences. An in this context it should be highlighted the existence of large diversity and varied Multicultural differences. These factors could affect the developments of technology, education; level, and quality of life. Thus the Economical and development indexes could be largely varied and different between them. For this reason it should highlighted the local development within shortened times by interacting to receive or provide materials with aggregated value or non-tangible values. Therefore, it could be accelerated the process of improvement in a targeted field looking for average homogeneous development everywhere. And there, it is where the link-up and transfer strategies of technology and education by creation of varied strategies in communication media. As for example the communication plays an important role to transfer knowledge within the different social status and imagining the development of thinking that later it will be the basis for the next generation of technology. By this manner, it could be coupled different levels of educations degrees by a factor in common related with curiosity and open minds to learn, work, and live together in the context of developments of new smart manners of living where economy and new encrypted currency are involucred and provide by different manners sustainability. In these perspectives the development and education at the University and higher degrees taking into account the transmission of important factors such as; i) entailment , ii) development of knowledge, and iii) transference, is fundamental. Finally, it should be highlighted the particular need of good human relationships, emotional intelligence, and diplomacy to afford from the simplest challenges to the higher ones.

Since December 2019, the coronavirus disease (COVID-19) has rapidly spread worldwide. The Mexican government has implemented public safety measures to minimize the spread of the virus. In this paper, the authors use statistical models in two stages to estimate the total number of coronavirus (COVID-19) cases per day at the state and national level in Mexico. Two types of models are proposed: first, a polynomial model of the growth for the first part of the outbreak until the inflection point of the pandemic curve and then a second nonlinear growth model is used to estimate the middle and the end of the outbreak. Model selection will be performed using Vuong’s test. The proposed models show overall fit similar to predictive models (e.g. time series, and machine learning); however, the interpretation of parameters is less complex for decision-makers and the residuals follow the expected distribution when fitting the models without autocorrelation being an issue.

Abstract: Fanconi anemia (FA), a chromosomal instability syndrome, is caused by inherited pathogenic variants in any of 22 FANC genes, that cooperate in the FA/BRCA pathway. This pathway regulates the repair of DNA interstrand crosslinks (ICLs) through homologous recombination. In FA proper repair of ICLs is impaired, and accumulation of toxic DNA double strand breaks occurs. In order to repair this type of DNA damage, FA cells activate alternative error-prone DNA repair pathways, that may lead to the formation of gross structural chromosome aberrations of which radial figures are the hallmark of FA and their segregation during cell division are the origin of subsequent aberrations like translocations, dicentrics and acentric fragments. The deficiency in DNA repair has pleiotropic consequences in the phenotype of patients with FA, including developmental alterations, bone marrow failure and an extreme risk to develop cancer. The mechanisms leading to the physical abnormalities during embryonic development have not been clearly elucidated, however FA has features of premature aging with chronic inflammation mediated by pro-inflammatory cytokines, that results in tissue attrition, selection of malignant clones and cancer onset. Moreover, the effect of the FA/BRCA pathway in germinal cells, evidenced by infertility in patients with FA attests of chromosomal instability and cell death also occurring in the germinal compartment.

The objective of the present study is to evaluate and analyze styles and dimensions of attachment, its possible relations and how they become evident in the people involved in this study, For accomplishing it, a quantitative focus methodology was applied of descriptive type and crosscut, in which 105 Clinical Psychology university career students participated. The CaMir-R questionnaire was applied to evaluate the different styles and dimensions of attachment. In regard to the main found results it can be mentioned that - as much in men as in women -. the disorganized attachment is the most representative, followed by safe attachment. In turn, there exists a significant difference established by gender in these dimensions: family worry, parental permissiveness and infantile traumatism; In addition, as much positive correlations like refusals ones among the renowned dimensions were observed, where bulges out the positive link of self-sufficiency and resentment against the parents with the infantile traumatism. It came to an end that the dependence between the type of relation and the predisposal of offering a sure attachment on behalf of the progenitor, it will generate in the person an atmosphere of satisfaction and a capacity to face the penalties of life everyday.

In this paper we focus on an implicit assumption in the BSM framework that limits the scope of market network connections to seeking gains in the currency basis, i.e., on trading strategies between the numeraire and the stock and between the numeraire and the option, separately. We relax this assumption and derive the equivalent of the standard BSM approach under a more general market network framework in order to assess its implications. In doing so, we find that it is not possible to hedge the implicit option that allows one to directly trade the option and stock. This represents a potential challenge to the BSM framework, since the missing market network connection provides a potentially useful mechanism for risk-bearing portfolio managers to alter their portfolios.

Patients with schizophrenia (SCZ) are at high risk of cardiovascular disease (CVD) due to an inherited predisposition, a sedentary life style and the use of antipsychotic medications. Several approaches have been taken to minimize this risk but results continue to be unsatisfactory. A potential alternative is prescribing Selective Serotonin Reuptake Inhibitors (SSRIs). SSRIs decrease platelet aggregation and reduce the risk of coronary heart disease in patients with depression. We therefore aim to investigate whether there is evidence that supports the use of SSRIs to reduce the risk for CVD in SCZ. A systematic review of the literature revealed five published reports relating to the impact of SSRIs on CV risk in SCZ. Three trials assessed the influence on metabolic parameters of fluvoxamine when combined with clozapine. Two of those studies found improvements with fluvoxamine. Of the other two reports, one indicates SSRIs as a group caused minimal but statistically significant increments in total cholesterol, LDL and triglyceride. The second report suggests that when SSRIs are combined with antipsychotics, the metabolic impact depends on the antipsychotic prescribed. While there are promising results, further studies are needed to establish the impact of SSRIs on CV risk in SCZ.

The patterns of food consumption in general and those of meat, in particular, are constantly changing. These changes are due not only to socio-economic and cultural trends that affect the whole society but also to the specific lifestyles of consumer groups. Due to the importance of consumer lifestyle, the objectives of this study were i) to identify the profiles of lamb meat consumers according to their orientation toward convenience, as defined by their eating and cooking habits; ii) to characterize these profiles according to their socio-economic characteristics and their preferences regarding the intrinsic and extrinsic quality signals of lamb meat; and iii) to analyze the willingness to pay for lamb confit. In this study, four types of consumers have been differentiated according to their lifestyles related to lamb consumption. These groups, due to their characteristics, could be called "Gourmet", "Disinterested", "Conservative" and "Basic". The Gourmet group has characteristics that make it especially interesting to market a product such as lamb confit; however, this group is unaware of this product. Therefore, a possible strategy to expand the commercialization of light lamb and the confit product would be guided marketing to this niche market.

This review provides insight into the role that obesity, but especially mediators of the adipose tissue, have in both renal disease and transplantation. In particular, we focus on the functions of leptin and adiponectin, inflammatory mediators with widely known clinical implications, as well as on the role of arachidonic acid-derived eicosanoid metabolites. These latter compounds, epoxyeicosatrienoic (EETs) and hydroxyeicosatetraenoic (HETEs) acids, which modulate the liberation of cytokines in the adipose tissue, are generated in the epoxygenase pathway of arachidonic biotransformation via CYP450 enzymes. There is accumulating evidence suggesting that EETs and HETEs may have a critical role in the onset and outcome of chronic kidney disease and renal transplantation. Finally, we also discuss the reported effect that the presence of genetic variants in leptin, adiponectin, EETs and HETEs-related genes may cause in renal patients and recipients. The levels of cytokines of the adipose tissue and related compounds play a remarkable role in both renal disease and transplant. Accordingly, novel therapeutic strategies are being developed based on the modulation of their concentrations in patients with various diseases.

In this paper the attention is focused on the analysis and the optimization of energy flows in networked systems via a fluid-dynamic model. In particular, a cost functional that represents a term proportional to the kinetic energy of an energy system is studied. First, the functional is optimized for a simple network having a unique node, with an incoming arc and two outgoing ones. The optimization deals with distribution coefficients and explicit solutions are found. Then, the global optimization is obtained using the local optimal parameters at the various nodes of the system. Considering the case study of an energy hub, interesting results are obtained for the whole network, proving the correctness of the proposed approach.

The performance of the presurgical test (preSurg) for temporal lobe epilepsy (TLE) was evaluated via video-electroencephalography (VEEG), electroencephalography (EEG), 99mTc-HmPAO single-photon emission tomography (SPECT) and 1.5 T magnetic resonance imaging (MRI) in a group of 112 men (37.0 ± 1.1 years) and 106 women (39.7 ± 1.1 years) operated on for TLE. The epileptic zone (EZ) was adequately identified to determine whether the patient reached an Engel I grade (EI) at least one year postop. Accuracy was evaluated by the coefficient α, ranging from 3 (when result = EZ) to 2 (result in the same hemisphere as the EZ), 1 (noninformative result) or 0 (EZ in the contralateral hemisphere). The simplicity of diagnosis was defined as the number of preSurg surgeries needed to identify the EZ. EI was obtained in 85.8% of patients even though 42.2% of patients had noninformative MRI results. For preSurg α was (mean ± SEM) = VEEG (2.83 ± 0.04) &gt; MRI (2.14 ± 0.08) &gt; EEG (1.87 ± 0.09) &gt; SPECT (1.71 ± 0.09). The accuracy (combination of sensitivity and specificity) was calculated as follows: VEEG (0.797) &gt; MRI (0.518) &gt; EEG (0.446) &gt; SPECT (0.360). The likelihood positive ratio was greater, and the likelihood negative ratio was lower for VEEG. The most relevant factor for the regression model was VEEG (3.106) &gt; MRI (2.558) &gt; EEG (1.905), and the factors were not significantly related to SPECT. EZs in EI patients with low simplicity were identified mainly by VEEG. A very good postoperative outcome can be obtained even in TLE patients with no lesions on MRI. The VEEG is the most reliable preSurg test and may be the only reliable test for patients with very low simplicity (i.e., difficult).single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Introduction: Studies of the socio-economic function of entrepreneurship have emphasized the critical role that entrepreneurial competence and its implementation play at different stages of the education system. In this paper, we seek to determine the entrepreneurial interest of Spanish youth aged between 15 to 18 years of age, who find themselves in the state-regulated education system, at an initial stage in the development of entrepreneurship. A previously validated ad hoc questionnaire was applied through simple random sampling to 1,764 students at a secondary school in Spain. The analysis is done with Artificial Neural Networks (ANN), a technique that reduces the high dimensionality of data through Cooperative Maximum Likelihood Hebbian Learning (CMLHL), applying neurocomputational methods to the educational sciences. Spanish youth expressed a medium level of interest in entrepreneurship. Analysis with ANN shows that education in entrepreneurial competence is an influential aspect of interest in entrepreneurship. As conclusion, educational and curricular reforms must be undertaken to promote the development of entrepreneurial competence at various stages of compulsory education to increase interest in entrepreneurship.

In this work, we introduce a scalable and efficient GPU-accelerated methodology for volumetric particle advection and finite-time Lyapunov exponent (FTLE) calculation, focusing on the analysis of Lagrangian Coherent Structures (LCS) in large-scale Direct Numerical Simulation (DNS) datasets across incompressible, supersonic, and hypersonic flow regimes. LCS play a significant role in turbulent boundary layer analysis, and our proposed methodology offers valuable insights into their behavior in various flow conditions. Our novel owning-cell locator method enables efficient, constant-time cell search, and the algorithm draws inspiration from classical search algorithms and modern multi-level approaches in numerical linear algebra. The proposed method is implemented for both multi-core CPUs and Nvidia GPUs, demonstrating strong scaling up to 32,768 CPU cores and up to 62 Nvidia V100 GPUs. By decoupling particle advection from other problems, we achieve modularity and extensibility, resulting in consistent parallel efficiency across different architectures. Our methodology was applied to calculate and visualize the FTLE on four turbulent boundary layers at different Reynolds and Mach numbers, revealing that coherent structures grow more isotropic proportional to the Mach number, and their inclination angle varies along the streamwise direction. We also observed increased anisotropy and FTLE organization at lower Reynolds numbers, with structures retaining coherency along both spanwise and streamwise directions. Additionally, we demonstrated the impact of lower temporal frequency sampling by upscaling with an efficient linear upsampler, preserving general trends with only 10% of the required storage. In summary, we present a particle search scheme for particle advection workloads in the context of visualizing LCS via FTLE that exhibits strong scaling performance and efficiency at scale. Our proposed algorithm is applicable across various domains requiring efficient search algorithms in large structured domains. While this manuscript focuses on the methodology and its application to LCS, an in-depth study of the physics and compressibility effects in LCS candidates will be explored in a future publication.

Corruption is a legal and moral contravention that generates great concern among nations due to its erosive effects on economic growth, democracy, governance, social equity and the integrity of culture. Therefore, it is necessary to know more about the multiple variables that produce and maintain this phenomenon. This article reports the results of an experimental investigation that sought to provide elements of judgment on the influence of the structure of personal values ​​on the willingness to bribe. For this, 12 couples of young university students of both sexes interacted through a game that simulated a relationship between a corrupter and a corruptible agent, with the help of a real-time communication system, mediated by an online platform, which allowed instant and bidirectional interaction. The couples were randomly constituted and played with each other under double blind. However, the interacting members of the dyad could share values ​​or vary in their axiological structure in such a way that, while one of them could manifest anti-corruption principles, the other's commitment was not so obvious. The results confirm the importance of the axiological structure of people in the facilitation or containment of the corrupt behavior. This article also reflects on the theoretical connotations of the relationships shown.

This review provides a snapshot of chronic bacterial infections through the lens of Burkholderia pseudomallei; detailing its ability to establish multi-nucleated giant cells (MNGC) within the host, leading to the formation of pyogranulomatous lesions. We explore the role of MNGC in melioidosis disease progression and pathology by comparing the similarities and differences of melioidosis to tuberculosis, outlining the concerted events in pathogenesis that lead to MNGC formation, discussing the factors that influence MNGC formation and how they fit into clinical findings reported in chronic cases. Finally, we speculate about future models and techniques that can be used to delineate the mechanisms of MNGC formation and function.

The hybrid system is analyzed and optimized to produce electric energy in Non-Interconnected Zones in the Colombian Caribbean region, contributing both to the improvement in the reduction of greenhouse gas emissions and to the rational use of energy. A comparative analysis of the performance of these systems was carried using a dynamic model in real wind and solar data. The model is integrated by a Southwest Wind Power Inc. wind turbine. AIR 403, a proton exchange fuel cell (PEM), an electrolyze, a solar panel and a charge regulator based on PID controllers to manipulate oxygen and hydrogen flows in the cell. The transient responses of the cell voltage, current, and power were obtained for the demand of 200 W for changes in solar radiation and wind speed for all days of the year 2013 in the Ernesto Cortissoz airport, Puerto Bolívar, Alfonso Lopez airport and Simon Bolívar airport, by regulating the flow of hydrogen and oxygen into the fuel cell. The maximum contribution of power generation from the fuel cell was presented for the Simon Bolívar airport in November with a value of 158,358W (9.45%). A multi-objective design optimization under a Pareto front is presented for each place studied to minimize the Levelized Cost of Energy and CO₂ emission, where the objective variables are the number of panel and stack in the PV system and PEM.

Increasingly, systems biology is gaining relevance in basic and applied research. The combination of computational biology with wet lab produces a synergy that results in an exponential increase in knowledge of biological systems. The study of microorganisms such as Staphylococcus epidermidis RP62A enables the researcher to understand better its metabolic network, which allows the design of effective strategies to treat infections caused by this species or others. S. epidermidis is the second cause of infection in patients with joint implants, so treating its proliferation seems vital for public health. There are different approaches to the analysis of metabolic networks. Flux Balance Analysis (FBA) is one of the most widespread streams. It allows the study of large metabolic networks, their structural properties, the optimization of metabolic flux, and the search for intervention strategies to modify the state of the metabolic network. This work presents the validation of the Staphylococcus epidermidis RP62A metabolic network model elaborated by Díaz-Calvo et al.. Then, we elaborate further on the network analysis’s essential reactions, classifying them. Finally, we introduce some proposals to intervene in the network and design knock-outs.

This study examines the effects and durability of postural exercise on gait kinematics in people with intellectual and developmental disabilities (IDD). Thirty-four men with mild IDD were assigned to either the training group (n = 19) or the control group (n = 15). The TG performed the intervention over 8 weeks, 3 days/week, 1 h/day. The results indicated that the intervention program had a significant effect on some variables of gait. Also, in the TG between post-test and follow-up, there was no significant difference, which indicated that gait variables were maintained by the TG one month after the end of the program. This study provides evidence that postural exercises can be used as an effective intervention for improving gait in individuals with IDD.

The search of DNA polymorphisms useful for the genetic improvement of dairy farm animals lasts more than 40 years with relevant findings in cattle for milk traits, where the best combination of alleles for dairy processing have been found in casein genes and in the DGAT1. Nowadays, similar results are not reached yet in river buffaloes despite advanced genomic technologies and accurate phenotype records are available. The aim of the present study was to investigate and validate in a larger buffalo population the effect on six milk traits of four single nucleotide polymorphisms (SNP) in the CSN1S1, CSN3, SCD and LPL genes, previously reported to be associated with or affect dairy traits in smaller populations often belonging to one farm. A total of 800 buffaloes were genotyped. Daily milk yield (dMY, kg), protein yield (dPY, kg) and fat yields (dFY, kg), fat and protein contents (dFP, % and dPP, %), somatic cell count (SCC, 103cell/ml) and urea (mg/dl) were individually recorded in each month for the whole lactation from 2010 to 2021. A total of 15,742 individual milk test day records (2,496 lactations) were available on 680 buffalo cows with 3.6±1.7 parity (from 1 to 13) and 6.1±1.2 test day records per lactation on average. Three out four SNP in CSN1S1, CSN3 and LPL were associated with at least one of analyzed traits. In particular, the CSN1S1 (AJ005430:c.578C&gt;T) gave favorable associations with all yield traits (dMY, p=0.022; dPY, p=0.014 ; dFY, p=0.029) and SCS (p=0.032), whereas the CSN3 (HQ677596: c.536C&gt;T) positively associated with SCS (p=0.005) and milk urea (p=0.04). Favorable effect on dMY (p=0.028), dFP (p=0.027) and dPP (p=0.050) were observed for the LPL. Conversely, SCD did not show any association with milk traits. This is the first example of confirmation study carried out in the Mediterranean river buffalo for genes of economic interest in dairy field and it represents a very important indication for the preselection of young bulls destined to breeding programs in the view of a more sustainable dairy production.

The Practicum is regarded as a fundamental aspect of the training of prospective teachers. In addition, digital tools are increasingly used to enrich a traditional face-to-face experience. However, the technological exploitation of augmented reality (AR) by undergraduate students studying early childhood and primary education is low. A Systematic Literature Review (SLR) on the use of augmented reality (AR) in teacher training was conducted. Based on the overarching objectives of the ERASMUS+ project, entitled Digital Practicum 3.0 Exploring Augmented Reality, Remote Classrooms, and Virtual Learning to Enrich and Expand Preservice Teacher Education Preparation (2020-1-ES01-KA226-HE- 096120), the ultimate purpose of this study was to assess whether the use of this resource favors learning and expertise. Two main results are prominent. First, it is noteworthy how the use of this digital technology is limited, given the scarcity of studies. Second, the research studies available focus largely on the benefits of the use of AR in teacher education at a theoretical level. Thus, future research needs to further explore the use of AR in teacher training specially focused on the student teachers’ learning processes.

The growing concern about climate change and global warming has driven greater involvement of international organizations, countries, companies, and society in general in acting and ensur-ing the life of our planet and the sustainability of future generations. Sustainability and finance are two concepts that are intertwined through sustainable finance, serving as an instrument that guides financial resources towards achieving sustainable development. Sustainability allows companies to identify risks and opportunities, being responsible for measuring their social, envi-ronmental, and economic impact under a multi-stakeholder approach. One of the three main cri-teria of sustainability is corporate governance, and the main corporate governance body is the board of directors, where the composition of the board and its supervision and monitoring func-tions improve the ESG performance. A relevant aspect within the board of directors is the ade-quate balance of gender diversity on the board, becoming an aspect regulated by laws and cor-porate governance code. This article develops the main concepts related to sustainability, sus-tainable finance and corporate governance describing the current situation of these topics and their relationship, creating a conceptual framework that allows identifying topics necessary for further empirical research and the implication of regulation in the scope of ESG issues.

Two new systematic authentication codes based on the Gray map over a Galois ring are introduced. The first introduced code attains optimal impersonation and substitution probabilities. The second code improves space sizes but it does not attain optimal probabilities. Besides it is conditioned to the existence of a special class of bent maps on Galois rings.

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

We report recent enhancements of the online atomic database at the Ohio State University, NORAD-Atomic-Data, that provides various parameters for radiative and collisional atomic processes dominant in astrophysical plasma. NORAD stands for Nahar Osu RADiative. The database belongs to the data sources, especially for the latest works, of the international collaborations of the Opacity Project and the Iron Project. The contents of the database are calculated values for energies, oscillator strengths, radiative decay rates, lifetimes, cross sections for photoionization, electron-ion recombination cross sections and recombination rate coefficients. We have recently expanded NORAD-Atomic-Data with several enhancements over those reported earlier. They are as follows. i) We continue to add energy levels, transition parameters, cross sections for atoms and ions with their publications. ii) Recently added radiative atomic data contains significant amount of transition data for photo-absorption spectral features corresponding to x-ray resonance fluorescence effect, prominent wavelength regions of bio-signature elements, such as phosphorus ions, and emission bumps of heavy elements, such as of lanthanides, that may be created in a kilonova event. We are including iii) collisional data for electron-impact-excitation, iv) experimental data for energies and oscillator strengths for line formation, v) experimental cross sections for photoionization that can be applied for benchmarking and other applications, and vi) introduction of a web-based interactive feature to calculate spectral line ratios at various plasma temperature and density diagnostics, starting with our recently published data for P II. We presented summary description of theoretical backgrounds for the computed data in the earlier paper. With introduction of experimental results, we present summary description of measurement of high resolution photoionization cross sections at Advanced Light Source of LBNL synchrotron set-up and briefly discuss other set-ups. These additions should make NORAD-Atomic-Data more versatile for various applications. For brevity, we provide information on the extensions and avoid repetition of data description of the original paper.

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

The electronic structure of 7/9-AGNR superlattices with up to eight unit cells has been studied by means of state of the art Density Functional Theory (DFT) and also by two model Hamiltonians, the first one including only local interactions (Hubbard model, Hu) while the second one is extended to allow long-range Coulomb interactions (Pariser, Parr and Pople model, PPP). Both are solved within mean field approximation. At this approximation level, our calculations show that 7/9 interfaces are better described by spin non-polarized solutions than by spin-polarized wavefunctions. Consequently, both Hu and PPP Hamiltonians lead to electronic structures characterized by a gap at the Fermi level that diminishes as the size of the system increases. DFT results show similar trends although a detailed analysis of the density of states around the Fermi level shows quantitative differences with both Hu and PPP models. Before improving model Hamiltonians, we interpret the electronic structure obtained by DFT in terms of bands of topological states: topological states localized at the system edges and extended bulk topological states which interact between them due to the long-range Coulomb terms of Hamiltonian. After careful analysis of the interaction among topological sates, we find that the discrepancy between ab initio and model Hamiltonians can be resolved considering a screened long-range interaction that is implemented adding an exponential cutoff to the interaction term of PPP model. In this way, an adjusted cutoff distance λ = 2 allows a good recovery of DFT results. In view of this, we conclude that the correct description of the density of states around the Fermi level (Dirac point) needs the inclusion of long-range interactions well beyond Hubbard model but not completely unscreened as is the case for the PPP model.

The COVID-19 pandemic affected the perinatal emotional landscape in Italy, a country with high mortality and strict lockdown. This study explored the emotions and challenges of pregnant and post-partum women during the pandemic, using AI-based mixed-methods. The study analyzed 1774 women from the national survey COVID-ASSESS: 1136 pregnant and 638 post-partum. The survey had qualitative questions on emotions and feelings related to birth, communication with healthcare professionals, media, and peers and family. We used natural language processing and machine learning to classify emotions, identify themes, and extract citations from the data. Fear and anxiety replaced joy as dominant emotions during the pandemic: trust and joy decreased by 49.3% and 36.4%, respectively, while sadness and fear increased by 52.3% and 49.3%, respectively. The pandemic also induced loneliness, isolation, frustration, and anger. Women faced challenges related to birth, communication with HCPs, media, and peers and family. They also used coping strategies such as self-care, news limitation, and tried to cultivate gratitude and hope. The study provides a comprehensive exploration of the perinatal emotional landscape of Italian women during the pandemic. The findings underscore the significant psychological impact of the pandemic, and also highlights women’s resilience and coping strategies.

Most research on colostrum quality and colostrum management focuses on maternal IgG transfer to the newborn calf. However, in addition to being a source of antibodies, colostrum has other components that influence passive immune transfer, nutrition, gut maturation, and thermoregulation. In this review, the constituents in the bovine colostrum, as well as their variation, are explored and it is discussed the biological role of colostrum on the newborn calf. Protein is the nutrient in higher concentration and fat is the nutrient with the most variation. There is a pronounced amplitude in the total solids content of colostrum, but the average concentration does not vary much between studies (24.7%). Bovine colostrum major components can vary with several factors, such as the region, season, breed, dry period length, and nutritional aspects of the dam. Bioactive components, cells, and microbiome variability are less understood, besides IgG. Regardless, they play crucial distinct roles in the physiological development of the newborn. However, a multi-interactive effect between these components, cells, and microorganisms is more likely to occur. Recently researched components in colostrum like miRNA, nucleo(t)sides, the milk fat globule membrane, oligosaccharides, minor proteins, and the microbiome are examples of promising interest areas of study.

Aberrant expression of the tight junction protein claudin 6 (CLDN6) is a hallmark of gastric can-cer progression. Its expression is regulated by the transcription factor CREB. But in H. pylo-ri-induced gastric cancer there is no information regarding what transcription factors in-duce/upregulate the expression of CLDN6. We aimed to identify if CREB and YY1 regulate the expression of CLDN6 and the site where they bind to the promoter sequence. Bioinformatics analysis, H. pylori LPS, YY1 and CREB silencing, western blot, luciferase assays, and chromatin immunoprecipitation experiments were performed using the gastric adenocarcinoma cell line AGS. A gen reporter assay suggested that the initial 2000 bp contains the regulatory sequence as-sociated with CLDN6 transcription; the luciferase assay demonstrated three different regions with transcriptional activity, but the -901 to -1421 bp region displayed the maximal transcrip-tional activity in response to LPS. Fragment 1279-1421 showed CREB and surprisingly YY1 oc-cupancy. Sequential ChIP experiments confirmed that YY1 and CREB interact in the 1279-1421 region. Our results suggest that CLDN6 expression is regulated by the binding of YY1 and CREB in the 901-1421 enhancer in which a non-described interaction of YY1 with CREB was established in the 1279-1421 region.

A model for enabling the production of lower carbon cement paste is proposed in this research. The model is based on predicting the strength of cement pastes with partial replacement of wheat straw ash (WSA) and silica fume (SF), two major wastes of agricultural and industrial production. The model is set up based on response surface methodology and Box-Behnken design, and included a suite of mechanical tests with distinct replacements following a micro an meso characterization. The model shows capability for predicting strength of any cement paste, including partial substitution of WSA and/or SF at any combination level with excellent accuracy, which is verified with three validation mixtures demonstrating maximum errors of less than 6% at the three ages. The analysis of the response surface evidences that any cement replacement in the range of 0-20% WSA and above 5% SF allows the reduction of the carbon footprint by maximizing the incorporation of both wastes. The proposed model can be used by setting the required strength of cement paste and calculating the maximum possible replacement, which should contribute to making the construction industry more sustainable by utilizing local waste.

This work proposes a methodology for the design, development, optimisation, and evaluation of amorphous rosuvastatin calcium tablets (BCS class II drug). The main goal was to ensure rapid disintegration and high dissolution rate of the active ingredient, thus enhancing its bioavailability. The design started from a careful selection of excipients, which due to their characteristics and proportions within the formulation allowed the use of their properties such as fluidity or granulometric distribution. The formulation was characterised using scanning electron microscopy (SEM), differential scanning calorimetry (DSC), thermogravimetry (TGA), Fourier transform infrared spectroscopy (FT-IR) and powder X-ray diffraction (PXRD) methods. The galenic SeDeM methodology was used to establish the profile of the active ingredient-excipient mixture and guarantee its suitability for producing tablets by the direct compression method. The results demonstrate that the amorphous rosuvastatin calcium tablets formulation developed made it possible to obtain cost-effective tablets by direct compression with optimal pharmacotechnical characteristics that showed a remarkable disintegration and dissolution rate. The manufactured tablets complied with the pharmacopoeia guidelines regarding uniformity of weight, tablet hardness, thickness, friability, in vitro disintegration time and dissolution profile.

Lung cancer represents the most common form of cancer accounting for 1.8 million deaths globally in 2020.The 5-year relative survival rate for lung cancer is lower than many other leading cancer types. Over the last decade the treatment for advanced and metastatic non small cell lung cancer have dramatically improved due to the development of immune checkpoint inhibitors and the identification of targetable driver mutations. Recently, potentially effective inhibitors of a hitherto untargetable oncogenic driver mutation in NSCLC, Kirsten Rat Sarcoma (KRAS) have been developed. KRAS mutations are found in 20-25% of NSCLC and represent the most frequent mutation. The mutation is almost exclusively detected in adenocarcinoma and is found among smokers 90% of the time. Along with the development of new drugs that have been showing promising activity, resistance mechanisms have begun to be clarified. The aim of this review is to unwrap the biology of KRAS in NSCLC with a specific focus on primary and secondary resistance mechanisms and their possible clinical implications.

As entrepreneurial interest is believed to represent a causal factor increasing entrepreneurship, research has begun to explore how family systems affect youth entrepreneurial interests. In the present study, we attempt to identify different types of family influence on the entrepreneurial interests of young people. A questionnaire was used to obtain data from 1,633 Spanish youths, who were 15 to 18 years old, and another questionnaire was used to obtain data from 839 parents. Principal Component Analysis identified unique family types and revealed that they have differential associations to entrepreneurial interest among youths. These findings reaffirm the influence of family on the entrepreneurial ecosystem and the promotion of an entrepreneurial family cuture. This study further suggests that early attention should focus on the detection of entrepreneurial interest among youths so that actions can be implemented in the families of low-interest youths to incentivize an entrepreneurial family culture.

Non-linear loads in circuits cause the appearance of harmonic disturbances both in voltage and current. In order to minimize the effects of these disturbances and, therefore, to control over the flow of electricity between the source and the load, they are often used passive or active filters. Nevertheless, determining the type of filter and the characteristics of their elements is not a trivial task. In fact, the development of algorithms for calculating the parameters of filters is still an open question. This paper analyzes the use of genetic algorithms to maximize the power factor compensation in non-sinusoidal circuits using passive filters, while concepts of geometric algebra theory are used to represent the flow of power in the circuits. According to the results obtained in different case studies, it can be concluded that the genetic algorithm obtain high quality solutions that could be generalized to similar problems of any dimension.

Roundabouts need capacity and safety improvements compatible with manual-driven, not only with autonomous vehicles. The signaling and control of roundabouts must evolve and incorporate current technologies. For that, we approach roundabouts as synchronous switches of vehicles. This paper describes Synchronous Roundabouts with Rotating Priorities, a roundabout control system based on vehicle platoons arriving at the roundabout at speed identical to the roundabout and within the time slot assigned to their entry, avoiding conflicts and stops, thus increasing roundabout capacity and safety. Signaling is visual for human drivers and also wireless for connected and autonomous vehicles. We evaluate analytically and with simulations roundabouts of different radius for several values of the average distance between vehicles. Average delays are 28,7 % lower, with negligible dispersion. The capacity improvements depend on design parameters: in our set is moderate for small roundabouts but goes up to 70-100 % for short distances and medium and large roundabouts.

The purpose of this paper is to provide a structural review of the progress made on detection and localization of leaks in pipelines by using approaches based on the Kalman filter. This is, to the best of our knowledge, the first review on the t opic. In particular, it is the first to try to draw the attention of the leak detection community to the important contributions that use the Kalman filter as the core of a computational pipeline monitoring system. Without being exhaustive, we try to gather the results from different research groups and present them in a unified fashion. For this reason, we propose a classification of the current approaches based on the Kalman filter. For each of the existing approaches within this classification, the basic concepts, fundamental results, and relations with the other approaches are discussed in detail. The review starts from a short summary of basic concepts about state observers. Then, a brief history of the use of the Kalman filter for diagnosing leaks is described by mentioning the most outstanding approaches. At last, we briefly discuss some emerging research problems, such as the leak detection in pipelines transporting heavy oils, and we discuss the main challenges and some open problems.

The number of disputes related to water that reach courts in Chile has increased in the last decades, the topics of these disputes have become more complex, and the current conflict resolution system has not been able to adjust to this situation. This study analyses colonial texts from water-related conflicts that were addressed at the Royal Hearings in Santiago (1691-1800) and from the Cabildo gatherings (1541-1802), using an adaptation of the Institutional Analysis and Development framework. The research shows a strong institutional system surrounding conflict resolution during colonial times, with nested schemes and empowered figures appointed in leading roles. However, a lack of equity and inclusion of all actors is also visible, reducing its legitimacy. At present, the increasing value of water and a sense of distrust in the institutional system have led to longer and more complex conflict resolution processes. Here, learning from past times about the empowerment of the institutional system for solving water disputes could be useful. An increased support towards initial conflict resolution mechanisms, giving space for local knowledge and generating stronger participation in these initial steps, could also be a lesson for the future.

Direct yaw moment control (DYC) is an effective way to alter the behaviour of electric cars with independent drives. Controlling the torque applied to each wheel can improve the handling performance of a vehicle making it safer andfaster on a race track. The state-of-the-art literature covers the comparison of various controllers (PID, LPV, LQR, SMC, etc.) using ISO manoeuvres. However, more advanced comparison on important characteristics of the controllers performance is missed, such as the robustness of the controllers under changes in the vehicle model, steering behaviour, use of the friction circle and, ultimately, lap time on a track. In this study, we have compared the controllers according to some of the aforementioned parameters on a modelled race car. Interestingly, best lap times are not provided by perfect neutral or close-to-neutral behaviour of the vehicle, but rather by allowing certain deviations from the target yaw rate. In addition, a modified PID controller showed that its performance is comparable to other more complex control techniques such as MPC.

The so-called Born-Huang ansatz is a fundamental tool in the context of ab-initio molecular dynamics, viz., it allows to effectively separate fast and slow degrees of freedom and thus treating electrons and nuclei at different mathematical footings. Here we consider the use of a Born-Huang-like expansion of the three-dimensional time-dependent Schr\"odinger equation to separate transport and confinement degrees of freedom in electron transport problems that involve geometrical constrictions. The resulting scheme consists of an eigenstate problem for the confinement degrees of freedom (in the transverse direction) whose solution constitutes the input for the propagation of a set of coupled one-dimensional equations of motion for the transport degree of freedom (in the longitudinal direction). This technique achieves quantitative accuracy using an order less computational resources than the full dimensional simulation for a prototypical two-dimensional constriction.

Pilots can be one of the factors in many air traffic accidents. When one or both pilots are impaired (e.g. fatigue, drunk), disabled, capable but wrong-headed, don’t have sufficient training, distracted, miscommunicate with the air traffic controller, or follow wrong instructions from the air traffic controller, the risk of accident will increase dramatically. In some of these cases, the risk can be mitigated by using big data and machine learning. The system will collect and analyze large amount of data about the state of the aircraft, e.g., the flight path, the immediate environment around the aircraft, the weather and terrain information, and the pilots’ input to control the aircraft. Additional sensors such as eye tracking devices and biological monitor can also be added to determine the condition of the pilots. If the pilots’ input do not match proper reaction to the situation or the pilots are impaired, the learning machine will first provide an advisory to the pilots. If both pilots are impaired or incapable, a warning will be sent to the flight attendants and air traffic controllers so that they can take appropriate actions. The learning machine will be trained by both accident database and an automatic training system.

In the recent years, tubular nanostructures have been related with immense advances in various fields of science and technology. Considerable research efforts have been centered on the theoretical prediction and manufacturing of non-carbon nanotubes (NTs), which meet modern requirements for the developing of novel devices and systems. In this context, diatomic inorganic nanotubes formed by atoms of elements from the 13th group of the periodic table (B, Al, Ga, In, Tl) and nitrogen (N), have received much research attention. In the present work, the elastic properties of single-walled boron nitride, aluminium nitride, gallium nitride, indium nitride and thallium nitride nanotubes were numerically evaluated using the nanoscale continuum modelling approach (also called molecular structural mechanics). The elastic properties (rigidities, surface Young´s and shear moduli, and Poisson´s ratio) of nitride nanotubes are discussed with respect to the bond length of the corresponding diatomic hexagonal lattice. The results obtained contribute to a better understanding of the mechanical response of nitride compound-based nanotubes, covering a broad range from the well-studied boron nitride NTs to the hypothetical thallium nitride NTs.

Franklinite-Zincochromite-Gahnite solid solutions have been prepared by ceramic or coprecipitation method and its pigmenting capacity as cool ceramic pigments in different glazes (double and single firing frits and porcelain frit) was studied. XRD, UV-Vis-NIR diffuse reflectance, CIEL*a*b* colour analysis, bandgap measurement and the photocatalytic activity over the Orange II azoic dye were carried out for the characterization of samples. Following criteria of high red colouring capacity and high NIR reflectance at minimum Cr amount, Zn(Fe1.8Cr0.2), Zn(Al1.5Cr0.5) and Zn(Al1.3Cr0.5Fe0.2)O4 turn out to be the optimal compositions for an intense reddish cool pigment. All powders show a direct semiconductor behaviour with bandgap around 2 eV, falling in the visible range (620 nm), and according to literature, the associated photocatalytic activity over Orange II with visible light irradiation is moderate in all cases, but the Franklinite-Zincochromite Zn(Fe1.8Cr0.2) stands out.

In the framework of maritime surveillance, vessel detection techniques based on spaceborne Synthetic Aperture Radar (SAR) images have promoted extensive applications for the effective understanding of unlawful activities at sea. The paper deal with this topic presenting a novel approach exploiting a cascade application of a pre-screening, and discrimination phase. The latter leverage the SAR spectrum by means of sub-looks analysis. For the first time, the method has been validated with experiments on multi-frequency (C-, X-, and L-band) SAR images. For a future syngergic exploitation of more SAR missions, the developed dataset, composed of Sentinel-1, SAOCOM and COSMO-SkyMed images, is comprehensive of multiple images gathered over the same area with short time lag (below 15 minutes). Finally, the diversified processing chains and the results for each mission product and scenarios are discussed. Being the first dataset of SLC (Single Look Complex) SAR multi-frequency data, the present work intends to encourage additional research in this promising field of research.

The volume of vehicular traffic in large cities has increased in recent years, the devices that collect vehicular GPS data such as cameras, GPS receivers and others generate millions of records at every instant of time generating problems in processing and storage of these data which becomes important for researchers. Intelligent Transportation Systems perform vehicle monitoring and control by collecting GPS trajectories, this large volume of information is necessary to have an optimal storage process. Its processing by means of compression techniques and simplification algorithms allow to reduce the necessary storage space. This paper presents a GPS trajectory simplification algorithm that considers noise reduction, point simplification and analysis of road network information. The results obtained on two data sets from the cities of California and Beijing are satisfactory, achieving a higher compression ratio without affecting data quality

High-level performance in mountain sports would be unlikely unless different emotional factors are taken into account through the analysis of psychological characteristics such as mood, resilience or motivation, among many others. In this study, 788 people with a sports degree from the Spanish Federation of Mountain Sports and Climbing (FEDME) participated, 75.3% are men and 24.5% are women. The mean age of the participants was 49.8 years (±12.8), ranging from 18 to 76 years. The Wong Law Emotional Intelligence Scale (WLEIS-S), the RS-14 Resilience Scale and the Satisfaction with Life Scale (SWLS) instrument were used. The aim of this research was to determine the relationship between the dimensions of emotional intelligence, resilience and life satisfaction. The results showed a relationship between several of the dimensions from the instruments used (p<.01). In terms of gender, higher scores were found for women than for men. The regression model shows that both the dimensions of emotional intelligence [Appraisal of own emotions (β=.104; p<.001); Use of emotions (β=.30; p&lt;.001); Emotional Regulation (β=.103; p<.001)] and resilience [Personal competence (β=.402; p<.001)], are predictors of greater life satisfaction, with 44.1% positively explained by the regression model. Further proposals should extend the results obtained with the analysis of more sports modalities and provide evidence that would complement those extracted in this research.

The calculation of power flow in power systems with the presence of harmonics has been properly studied in the scientific literature. However, power flow calculation considering interharmonic components is still an open question. Traditional methods based on the IEEE1459 standard have proven to be valid and accurate only for linear and sinusoidal systems, but have been criticized for non-linear and non-sinusoidal systems because they are not able to explain correctly the current and voltage interactions beyond the active power. This paper proposes the use of a novel mathematical framework called geometric algebra (GA) to study the power flow considering the interaction of current and voltage harmonics and interharmonics. The use of GA enables the precise determination of the direction and magnitude of the total and single active power flow for each component, as well as other power elements related to the non-active power due to cross interaction. Moreover, this paper makes a novel contribution to the definition of interharmonics in geometric algebra space that has not been done before. To test the validity of the method, both linear and non-linear circuits are proposed and solved by applying voltages and currents with harmonic and interharmonic components. The results obtained show that power flow can be analyzed under the prism of the principle of energy conservation (PoCoE) in a way that allows a better understanding of the power spectrum due to the interaction of harmonics and interharmonics of voltage and current.

Metabolic Syndrome (MetS) is a serious condition that significantly increases the risk of cardiovascular diseases and the severity of type 2 diabetes, also impacting on the development and evolution of other chronic diseases. Predicting metabolic syndrome is a complex task due to the multifactorial nature of this condition, which involves a combination of various risk factors such as abdominal obesity, insulin resistance, dyslipidemia, and hypertension. The complex interplay of these factors makes it challenging to predict the syndrome. Both genetic predisposition and environmental factors also contribute to the development of metabolic syndrome. Metabolic syndrome affects diverse populations with different ethnicities, lifestyles, and socioeconomic backgrounds. Prediction models, in addition, need to account for population heterogeneity and consider variations in risk factors across different groups. The present study analyzed data from participants in a cohort from Mexico City to identify key risk factors in men and women, addressing the presence of unbalanced data. In order to tackle the issues posed by data imbalance data, SMOTE and ADASYN were applied to assess significant differences in the selection of risk factors for MetS prediction. Random Forest and RPART models using ADASYN and SMOTE demonstrated better performance, achieving a balanced accuracy of approximately 87%. In women, they highlighted sleep quality, anxiety factors, tobacco consumption, and nutritional components. In the case of men, stronger associations were identified with the social development index and factors related to gout in parents.

Pancreatic neuroendocrine tumor (P-NET) is a rare neoplasm originating in the neuroendocrine system. Carcinoid syndrome occurs in approximately 19% of patients with functional P-NETs, typically when liver metastases occur. NETs diagnosis is frequently late, along with symptoms related to hormone hypersecretion. We described the case of a patient with a low-grade non-functional P-NET, but with a typical clinical presentation of a carcinoid syndrome; moreover, we reviewed the literature regarding this topic. An 81-year-old male was admitted to our Department of Internal Medicine at Cannizzaro Hospital (Catania, Italy) because of the onset of abdominal pain with nausea, loose stools and episodic flushing. Firstly, an abdominal contrast-enhanced CT scan showed a small pancreatic hypervascular mass; then a gallium-68 DOTATOC integrated PET/CT revealed an elevated expression of SSTR receptors. Serum Chromogranin A and urinary 5-HIAA measurements resulted negative. Given the small size of the lesion (8 mm), we preferred to perform an endoscopic ultrasonography (EUS) with fine-needle biopsy (EUS-FNB), allowing the diagnosis of low-grade (G1) non-functional P-NET (NF-P-NET). Surgery was waived, while a follow-up strategy was chosen. Early recognition of P-NETs, although rare, is necessary to improve patient’s survival. EUS-FNB should be the protocol of choice for an early characterization of these tumors.

The automation of welding processes requires the use of automated systems and equipment, in many cases industrial robotic systems, to carry out welding processes that previously required human intervention. Automation in the industry offers numerous advantages, such as increased efficiency and productivity, cost reduction, improved product quality, increased flexibility and safety, and greater adaptability of companies to market changes. The field of welding automation is currently undergoing a period of profound changes due to a combination of technological, regulatory, and economic factors worldwide. Nowadays, the most relevant aspect of the welding industry is to meet customer requirements by satisfying their needs. To achieve this, the automation of the welding process through sensors and control algorithms ensures the quality of the parts and prevents errors such as porosity, unfused areas, deformations, excessive heat, etc. This paper proposes an intelligent and adaptive system based on the measurement of welding joints using laser scanning and the subsequent analysis of the obtained point cloud to adapt the welding trajectories.

This study involved a comprehensive examination of sensory attributes in Bísaro dry-cured loins, including odor, androsterone, scatol, color, fat color, hardness, juiciness, chewiness, flavor intensity, and flavor persistence. Analysis of 40 samples revealed a wide variation in these attributes, ensuring a robust margin for multivariate calibration purposes. The respective near-infrared (NIR) spectra unveil distinct peaks associated with significant components such as protein, lipid, and water. Support Vector Regression (SVR) models were methodically calibrated for all sensory attributes, with optimal results using multiplicative scattering correction pre-treatment, MinMax normalization, and radial base kernel (non-linear SVR model). The predictive models exhibited acceptable results, characterized by R-squared values close to 1 (0.9616 - 0.9955) and low RMSE values (0.0400 – 0.1031). The prediction set's relative standard deviation (RSD) remained under 5%. Comparisons with prior research revealed significant improvements in prediction accuracy, particularly when considering attributes like pig aroma, hardness, fat color, and flavor intensity. This research underscores the potential of advanced analytical techniques to improve the precision of sensory evaluations in food quality assessment.

Mn-promoted bulk iron catalysts with high specific surface area (82-211 m2.g-1) were synthesized by coprecipitation followed by drying under supercritical conditions. The catalysts were tested in the CO2 hydrogenation reaction. The Mn-promoted iron catalysts showed better textural properties than the bare Fe2O3 catalyst, allowing better dispersion of the active phase, easier reduction of iron oxide, better carburization of iron oxides and higher catalytic activity than the bare Fe2O3 catalyst. The best activity results were obtained by catalyst promotion with a very low amount of Mn (Mn/Fe ratio of 0.05). Upon steady-state conditions (T=340 ºC, total pressure of 20 bar and H2/CO2=3), this catalyst showed high CO2 conversion (44.2%) and selectivity to C2-C4 hydrocarbons (68%, olefin to paraffin ratio of 0.54), while the selectivity to C5+ hydrocarbons, CH4 and CO was about 3.2, 38.5 and 5%, respectively. A close correlation was found between catalyst textural properties and CO2 conversion. The most active MnFe-0.05 catalyst shows high stability during 72 h of reaction related to low amount of soft coke formation and catalyst activation through the formation of χ-Fe5C2 phase during the on-stream reaction.

Concurrent Optical and Magnetic Stimulation (COMS) combines extremely low frequency electromagnetic and light stimulation modalities for enhanced wound healing. In this report, we investigated the potential mechanistic synergism between magnetic and light components by comparing their individual and combined cellular responses. Although each individual stimulation mode was capable of stimulating cell proliferation, magnetic fields exposure alone produced greater proliferation enhancement than light alone, yet their combined effects of were supra-additive of the individual responses. Reactive oxygen species were incrementally reduced by exposure to light, magnetics fields and their combination, where statistical significance was ultimately achieved. On the other hand, ATP production was significantly enhanced in response to magnetic exposure alone or in combination with light. These results suggest that mitochondrial respiratory efficiency was preferentially improved by the combination of the two stimuli. Protein expression related to cell proliferation was preferentially enhanced by the combinatory COMS modality as were the protein levels of the TRPC1 cation channel previously implicated as part of a calcium-mitochondrial signaling axis invoked by electromagnetic exposure and involved in proliferation. These results corroborate that light facilitates functional synergism with magnetic fields that ultimately impinge on mitochondria-dependent developmental responses. The aminoglycoside antibiotics (AGAs) have been previously shown to antagonize TRPC1-mediated magnetotransduction. Streptomycin applied during the exposure to any of the stimulation modes reduced proliferation enhancement, whereas streptomycin added after the exposure did not. Notably, the COMS modality and magnetic field exposure were capable of partially overcoming streptomycin antagonism of proliferation, whereas light alone was not. Transductional antagonism of combinatorial photon-electromagnetic effects by streptomycin thus aligns with previous studies showing that the AGAs block TRPC1-mediated magnetotransduction when applied during exposure. The prophylactic usage of the AGAs (neomycin) should be avoided during COMS therapy to maintain clinical efficacy and would be a common concern with most other electromagnetic regenerative paradigms.

Despite the efforts made to stop the tuberculosis (TB) epidemic, it still remains one of the leading causes of death from an infectious disease. Previous work in the group uncovered a new family of amides which showed promising activities against Mycobacterium tuberculosis. A closer look at the literature showed that these compounds are structurally related to the DNB family of DprE1 inhibitors, so, we decided to study a wide range of substituted amides and determine their activity, focusing on unexplored structures related to the dinitrobenzamides (DNB) found in the literature. To synthesize our library of compounds we started from 3,5-dinitrobenzoic acid to form the nitroaromatic core that is characteristic of the DNB’s, to which we then added linear or cyclic amine moieties. Additionally, the impact of terminal aromatic moieties was also assessed for some derivatives, via an ether, ester, or amide bond. In order to obtain the desired derivatives, multiple synthetic approaches were used, mainly focused on nucleophilic addition/elimination reactions, SN2 reactions and Mitsunobu reactions. The activity was impacted mainly by two structural features, the addition of an aromatic moiety as a terminal group and the type of the linker. The most interesting compounds exhibited activities comparable to isoniazid and DNB1. Computational studies were also performed aimed at understanding their possible interactions with DprE1. The most active compounds are a good starting point for further development, and we plan to study an extended family of compounds based in those structures.

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.

Prior work has suggested that discrimination and immigration-related stress may impede mental health care seeking and utilization among Latinx populations. These effects may be more nuanced as both discrimination and immigration-related stress may increase symptomology, particularly posttraumatic stress disorder (PTSD) and depression. Both symptoms may in turn prompt attempts to seek care. The current study examined the direct effects of discrimination and immigration-related stress on care access, as well as potentially indirect effects with PTSD and depression symptoms as mediators. Interviews and online surveys were completed with 234 Latinx residents of the Midwest assessing everyday discrimination, discrimination in healthcare, PTSD symptoms, depression symptoms, current mental health utilization, and previous unsuccessful attempts to seek care. Direct effects of discrimination and immigration-related stress were largely unrelated to care access variables. Discrimination in healthcare settings predicted both unsuccessful attempts to seek care and current use, but this effect was positive. The indirect effect was largely supported, but only for PTSD symptoms and not depression. Results indicate further investigation is necessary to understand the direct effects of discrimination on care access. Further, discrimination and immigration-related stress may indirectly prompt attempts to seek mental health care.

In this systematic review of the literature on using Machine Learning (ML) for credit risk prediction, we raise the need for financial institutions to use AI and ML to assess credit risk, analyzing large volumes of information. We posed research questions about algorithms, metrics, results, data sets, variables, and related limitations in predicting credit risk. We searched renowned databases to answer them and identified 52 relevant studies with the credit industry microfinance. Challenges and approaches in credit risk prediction using ML models we identified, difficulties with the implemented models such as the black box model, the need for explanatory artificial intelligence, the importance of selecting relevant features, addressing multicollinearity, and the problem of the imbalance in the input data. By answering the questions, we identified that the Boosted Category is the most researched family of ML models; the most commonly used metrics for evaluation are Area Under Curve (AUC), Accuracy (ACC), Recall, precision measure F1 (F1), and Precision; Research mainly uses public data sets to compare models, and private ones to generate new knowledge when applied to the real world. The most significant limitation identified is the representativeness of reality, and the variables primarily used in the microcredit industry are related data to the demographic, the operation, and payment behavior. This study aims to guide the developers of credit risk management tools and software towards the existing offer of ML methods, metrics, and techniques used to forecast it, thereby minimizing possible losses due to default and guiding risk appetite.

To improve the voltage gain of step-up converters, cascaded technique is considered as a possible solution in this paper. By considering the concept of cascading two Z-source networks in a conventional boost converter, the converter takes the advantages of both impedance source and cascaded converters. However, by applying some modifications, the proposed converter provides high voltage gain while the voltage stress of switch and diodes are still low. Moreover, the low input current ripple of the converter makes it absolutely appropriate for photovoltaic applications in order to expand the lifetime of PV panels. After analyzing the operation principles of the proposed converter, simulation and experimental results of a 100W prototype are presented to verify the proposed converter performance.

Future cyber-physical systems may extend over broad geographical areas, like cities or regions, thus requiring the deployment of large real-time networks. A strategy to guarantee predictable communication over such networks is to synthesize an offline time-triggered communication schedule. However, this synthesis problem is computationally hard (NP-complete), and existing approaches do not scale satisfactorily to the required network sizes. This article presents a segmented offline synthesis method which substantially reduces this limitation, being able to generate time-triggered schedules for large hybrid (wired and wireless) networks. We also present a series of algorithms and optimizations that increase the performance and compactness of the obtained schedules while solving some of the problems inherent to segmented approaches. We evaluate our approach on a set of realistic large-size multi-hop networks, significantly larger than those considered in the existing literature. The results show that our segmentation reduces the synthesis time up to two orders of magnitude.

A The agri-food sector is in full renovation, continuously demanding new systems that allow farmers to facilitate their work. Efficient agricultural practices are essential for increasing farm profitability. Efficient agricultural practices can be increased by understanding and managing water neeeds. However, real-time monitoring of water needs is currently slow, and irrigation decisions are based on previous data or physical evidence. Furthermore, the prices of automatic systems for collecting data from several sources (soil and climate) are expensive and the autonomy is very low. Emerging Internet of Things (IoT) technologies such as wireless sensor networks can be used to collect vast amounts of data recorded via apps. By means of an LPWAN communication the farmer can know in real time the state of his crops thanks to a large number of sensors connected wirelessly and distributed across his farm. This paper presents a low consumption solution based on LoRaWAN technology. The wireless sensor node, called BoX, exhibits very low power since it has been optimized both in terms of hardware and software. The result is a higher degree of autonomy than commercial motes. That will allow the farmer to have all the information necessary to achieve an efficient management of his crops with full autonomy.

The use of the voice of the customer as a main input to guide decision making towards customer centricity strategies has become a necessity for companies. This research proposes a structured method of textual processing using the KDD (Knowledge Discovery Databases) methodology applied to the tweets of users of Colombian public sector companies, through the analysis of temporal sentiments and topic modeling to identify the areas in which actions should be taken to improve the perception of service. To fulfill such purpose, tweets from January to June 2022 are processed, followed by a temporal analysis of the evolution of the sentiment based on 3 enriched dictionaries; after, the LDA (Linear Discriminant Analysis) algorithm is implemented to find the areas with ailment for the user, in addition to propose a method to homologate the CIER (Comisión de Integración Energética Regional) survey. Finally, metrics are detailed to follow up the perception of the service. It is concluded that for the Acueducto the topic with the highest number of complaints is related to "Water truck request", for Enel "Servide Outages" and for Vanti: " Case solution and request information". Also, the homologation of 3 of the 5 pillars on which the CIER survey is based is presented.

Social networks have become the scenario with the greatest potential for the circulation of disinformation, hence there is a growing interest in understanding how this type of information is spread, especially in relation to the mechanisms used by disinformation agents such as bots, trolls, among others. In this scenario, the potential of bots to facilitate the spread of disinformation is recognised, however, the analysis of how they do this is still in its initial stages. Taking into consideration what was previously stated, this paper aimed to model and simulate scenarios of disinformation propagation in social networks caused by bots based on the dynamics of this mechanism documented in the literature. For achieving the purpose, System dynamics was used as the main modelling technique. The results present a mathematical model, as far as disinformation by this mechanism is concerned, and the simulations carried out against the increase in the rate of activation and deactivation of bots. Thus, the preponderant role of social networks in controlling disinformation through this mechanism, and the potential of bots to affect citizens, is recognised.

Zero-Knowledge Proofs ZKP provide a reliable option to verify that a claim is true without giving detailed information other than the answer. A classical example is provided by the ZKP based in the Graph Isomorphism problem (GI), where a prover must convince the verifier that he knows an isomorphism between two isomorphic graphs without publishing the bijection. We design a novel ZKP exploiting the NP-hard problem of finding the algebraic ideal of a multivariate polynomial set, and consequently resistant to quantum computer attacks. Since this polynomial set is obtained considering instances of GI, we guarantee that the protocol is at least as secure as the GI based protocol.

Nowadays, there are implemented devices whose purpose is to perform massive computations by saving resources at the time they reduce the latency of arithmetic operations. These devices are usually GPUs, FPGAs and other specialised devices such as "Coral". Neural networks, digital filters and numerical simulators take advantage of the massively parallel operations of such devices. One way to reduce the amount of resources used is to limit the size of the registers that store data. This has led to the proliferation of numeric formats with a length of less than 32 bits, known as short floating point or SFP. We have developed several SFP’s for use in our neural network accelerator design, allowing for different levels of accuracy. We use a 16-bit format for data transfer and different formats can be used simultaneously for internal operations. The internal operations can be performed in 16-bit, 20-bit and 24-bit. The use of registers larger than 16-bit allows the preservation of fractional information while increasing precision. By leveraging some of the FPGA’s arithmetic resources, our design outperforms designs implemented from scratch and is competitive with specialized arithmetic circuits already implemented in the FPGA.

This paper shows a method for pipeline leak detection using a transient-based method with MATLAB® functions. The simulation of a pipeline systems in the time domain are very complex. In the case of the dissipative model, transfer functions are hyperbolic Bessel functions. Simulating a pipeline system in the frequency domain using a dissipative model we could find an approximate transfer function with equal frequency domain response to in order get the pipeline system's time domain response. The method described in this paper can be used to detect, by comparison, to detect a leak in a pipeline system model.

Salinity is a significant abiotic stress factor for ornamental plants cultivated in greenhouses, as they are supplied with fertilizers over a long period of time. It causes drastic yield losses in com-mercially important ornamentals such as Gerbera jamesonii, whose cut flowers rank fifth in the global flower trade. In the current study, pretreatment of G. jamesonii plants (white and yellow flowering varieties) with optimum concentrations of thiourea (1.0 mM, 5.0 mM & 10.0 mM) in-duced plant salt-tolerance. Gerberas pretreated with thiourea (5.0 mM), when exposed to NaCl (200mM), showed no signs of plant stress or phenotypic abnormalities, as seen in gerberas ex-posed to NaCl without thiourea pretreatment. Moreover, thiourea application significantly pro-moted plant growth as evidenced by increases in fresh and dry leaf weight, relative water con-tent, total protein content, free proline content, and chlorophyll. A decrease in H2O2 and MDA content and an increase in antioxidant enzymes superoxide dismutase, catalase, ascorbate perox-idase, glutathione reductase, and peroxidase activity indicate minimal cellular damage in gerberas treated with thiourea. Thus, spraying leaves with thiourea (5.0 mM) could help gerbera plants overcome the deleterious effects of salt stress during repeated fertilization in nethouses. In addi-tion to alleviating salt stress, thiourea can also be used as a biofertilizer. This could also be ex-tended to other ornamental species to promote sustainable development of the floriculture indus-try.

People who suffer a mild traumatic brain injury (mTBI) have heterogeneous symptoms and disease trajectories, which make it difficult to precisely diagnose and assess complications long-term. Insufficient information is available regarding how to precisely diagnose and assess mTBI. This study identified and compared deficits in cognitive, psychosocial, visual functions, and balance performance between college students with and without histories of mTBI. Global DNA methylation ratio (5-mC%) in blood was also compared as a peripheral epigenetic marker. Twenty-five volunteers participated in this pilot study, including 11 mTBI cases (27.3% females; mean age of 28.7 years, SD=5.92) and 14 healthy controls (64.3% females; mean age of 22.0, SD=4.13). All the participants were assessed for cognitive (by NIH toolbox—executive function, memory, and processing speed), psychological (by PROMIS—depression, anxiety, and sleep disturbances), visual function (by King-Devick and binocular accommodative tests), postural balance performance (by a force plate), and blood 5-mC% (global methylation) levels. Students with mTBI reported significantly poorer episodic memory, severe anxiety, and more sleep disturbance problems. They also had higher blood 5-mC% level (all p’s<.05). No significant differences were found in visual function and postural balance. These findings validate changes in cognitive, psychosocial, and global DNA methylation long after mTBI.

We propose a new binary formulation of the Travelling Salesman Problem (TSP), with which we overcame the best formulation of the Vehicle Routing Problem (VRP) in terms of the minimum number of necessary variables. Furthermore, we present a detailed study of the constraints used and compare our model (GPS) with other frequent formulations (MTZ and native formulation). Finally, we have carried out a coherence and efficiency check of the proposed formulation by running it on a quantum annealing computer, D-Wave\_2000Q6.