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Nowadays, electricity is a basic commodity necessary for the well-being of any modern society. Due to the growth in electricity consumption in recent years, mainly in large cities, electricity forecasting is key to the management of an efficient, sustainable and safe smart grid for the consumer. In this work, a deep neural network is proposed to address the electricity consumption forecasting in the short-term, namely, a long short-term memory (LSTM) network due to its ability to deal with sequential data such as time-series data. First, the optimal values for certain hyper-parameters have been obtained by a random search and a metaheuristic, called coronavirus optimization algorithm (CVOA), based on the propagation of the SARS-Cov-2 virus. Then, the optimal LSTM has been applied to predict the electricity demand with 4-h forecast horizon. Results using Spanish electricity data during nine years and half measured with 10-min frequency are presented and discussed. Finally, the performance of the proposed LSTM using random search and the LSTM using CVOA is compared, on the one hand, with that of recently published deep neural networks (such as a deep feed-forward neural network optimized with a grid search) and temporal fusion transformers optimized with a sampling algorithm, and, on the other hand, with traditional machine learning techniques, such as a linear regression, decision trees and tree-based ensemble techniques (gradient-boosted trees and random forest), achieving the smallest prediction error below 1.5%.

Background Despite growing interest in treatment strategies that limit oxygen exposure in ICU patients, no studies have compared conservative oxygen with standard oxygen in postsurgical patients with sepsis/septic shock, although there are indications that it may improve outcomes. It has been proven that high partial pressure of oxygen in arterial blood (PaO 2 ) reduces the rate of surgical-wound infections and mortality in patients under major surgery. The aim of this study is to examine whether PaO 2 is associated with risk of death in adult patients with sepsis/septic shock after major surgery. Methods We performed a secondary analysis of a prospective observational study in 454 patients who underwent major surgery admitted into a single ICU. Patients were stratified in two groups whether they had hyperoxemia, defined as PaO 2  > 100 mmHg ( n  = 216), or PaO 2  ≤ 100 mmHg ( n  = 238) at the day of sepsis/septic shock onset according to SEPSIS-3 criteria maintained during 48 h. Primary end-point was 90-day mortality after diagnosis of sepsis. Secondary endpoints were ICU length of stay and time to extubation. Results In patients with PaO 2  ≤ 100 mmHg, we found prolonged mechanical ventilation (2 [8] vs. 1 [4] days, p  < 0.001), higher ICU stay (8 [13] vs. 5 [9] days, p  < 0.001), higher organ dysfunction as assessed by SOFA score (9 [3] vs. 7 [5], p  < 0.001), higher prevalence of septic shock (200/238, 84.0% vs 145/216) 67.1%, p  < 0.001), and higher 90-day mortality (37.0% [88] vs. 25.5% [55], p  = 0.008). Hyperoxemia was associated with higher probability of 90-day survival in a multivariate analysis (OR 0.61, 95%CI: 0.39–0.95, p  = 0.029), independent of age, chronic renal failure, procalcitonin levels, and APACHE II score > 19. These findings were confirmed when patients with severe hypoxemia at the time of study inclusion were excluded. Conclusions Oxygenation with a PaO 2 above 100 mmHg was independently associated with lower 90-day mortality, shorter ICU stay and intubation time in critically ill postsurgical sepsis/septic shock patients. Our findings open a new venue for designing clinical trials to evaluate the boundaries of PaO 2 in postsurgical patients with severe infections.

The objective of this study was to analyze the perceived barriers to dual career success and athletic identity of student-athletes according to disability type and level of professionalization. The final sample consisted of 203 student-athletes with disabilities from five European countries. The questionnaires used were ESTPORT, EBBS and AIMS. Depending on disability type, it was found that student-athletes with hearing and physical impairment showed the highest difficulty in reconciling sports and studies (p = 0.001); that student-athletes with a hearing impairment showed the highest score in the barrier ‘the cost of education is high’ (p = 0.023); that student-athletes with a physical impairment had the highest scores in the barrier ‘Exercise tires me’ (p = 0.013); that student-athletes with cerebral palsy showed the highest scores in the barrier ‘I do not have enough university/educational institution support’ (p = 0.014) and ‘Exercise facilities do not have convenient timetables for me’ (p = 0.001). Depending on sports professionalization level, semi-professional student-athletes showed the highest values in the barrier ‘the university/educational institution is far from my training center’ (p = 0.040); while professional student-athletes had the highest score in the barrier ‘exercise takes too much time from family responsibilities’ (p = 0.034). In most of the variables related to identity as athletes, professional student-athletes showed the highest values, followed by semi-professional athletes (p = 0.043- < 0.001). In conclusion, the self-perception of barriers is quite relevant, with differences arising from disability type and level of professionalization, whereas the identity as an athlete is only different according to the level of professionalization.

Background/Objectives: Cardiovascular disease (CVD) remains the leading cause of death worldwide, and the effectiveness of statin therapy is critically dependent on patient adherence and persistence. The aim of this study was to evaluate adherence and persistence in newly started and previously treated statin patients, with reference to cardiovascular prevention. Methods: A retrospective cohort study was conducted to assess adherence and persistence in newly started and previously treated statin patients. Patients aged 18 years or older with a statin claim from 1 January 2021 to 31 December 2023 were included. Adherence was defined as a Medication Possession Rate (MPR) of 80% or greater. Persistence was defined as the time between the index date and treatment discontinuation. Binary logistic regression and Cox proportional hazard regression were used to analyze factors influencing adherence and persistence, respectively. Kaplan–Meier survival analysis was used to compare persistence between both cohorts. Results: Of the 411,956 patients on statins, 81.21% were adherent, with higher rates in the previously treated statin patients (83.05% vs. 73.73%; p = 0.001). Statin persistence decreased from 92.65% at 3 months to 78.28% at 12 months, with higher persistence rates in previously treated statin patients. Previously treated statin patients were more likely to be adherent (AOR: 1.29) and persistent (AHR: 2.08) than those newly started on statins. In secondary prevention patients, adherence was higher in the previously treated cohort (88.09% vs. 79.77%; p = 0.001) than in the newly started cohort (80.52% vs. 71.38%; p = 0.001). Similar results were observed for persistence; 82.97% vs. 81.65% (p = 0.001) and 65.08% vs. 61.57% (p = 0.001), respectively. Conclusions: Adherence and persistence to statins were higher in previously treated patients than in newly started patients, especially for secondary cardiovascular prevention. New strategies are needed to improve medication adherence and persistence in patients with poor cardiovascular prognosis.

We prove the existence of equilibrium states for partially hyperbolic endomorphisms with one-dimensional center bundle. We also prove, regarding a class of potentials, the uniqueness of such measures for endomorphisms defined on the 2-torus that: have a linear model as a factor; and with the condition that this measure gives zero weight to the set where the conjugacy with the linear model fails to be invertible. In particular, we obtain the uniqueness of the measure of maximal entropy. For the n -torus, the uniqueness in the case with one-dimensional center holds for absolutely partially hyperbolic maps with additional hypotheses on the invariant leaves, namely, dynamical coherence and quasi-isometry. We provide an example satisfying these hypotheses.

The increasing demand for sustainable and environmentally friendly materials has prompted intensive research into developing bioplastics as viable alternatives to conventional petroleum-derived plastics. Here, we report a novel approach to bioplastic production by employing plant extract-based solvents to partially dissolve cellulose, a fundamental biopolymer precursor. Using plant-derived solvents addresses concerns surrounding the environmental impact of traditional solvent-based processes, as per the principles of green chemistry. Using computational screening, some natural products were identified from the integrated database resource MEGx. Six natural sources were selected based on their molecular weight, high pKa, and chemical classification. Thin-layer chromatography (TLC) and column chromatography confirmed the presence of molecules in the extracts. Bioplastics were prepared with 1, 3, 6, 10, and 15 wt.% plant extract concentrations. Control samples without conventional dissolved and positive controls were also studied to compare their properties with novel bioplastics. Chemical characterization and biodegradability tests were performed. Degradation in water and soil tests for 35 days showed that the biodegradability of the bioplastics with natural extracts at higher concentrations was faster than that of the control samples. By day 35, bioplastics containing 15 wt.% of the D1 W extract showed rapid degradation, with higher weight loss compared with the conventional controls. The positive control (C4), containing NaOH and glycerol, degraded more slowly than the plant extract-based formulations. Also, the test indicated that the natural dissolvent’s influence on the water uptake of the material produced a better performance than the control samples. The surfaces of the bioplastic formulations were analyzed using a scanning electron microscope (SEM) at different magnifications. The findings presented here hold promise for advancing the field of bioplastics and contributing to the sustainable utilization of plant resources for eco-friendly material production.

The first wave of the COVID-19 pandemic collapsed the hospitals in Castile and Leon (Spain). An analysis of the clinical characteristics, drug therapies and principal outcome predictors in the COVID-19 hospitalized patients from 1 March to 31 May 2020 is presented through a population-based registry study. Hospital stay variables, ventilation mode data and clinical outcomes were observed. In Castile and Leon hospitals, 7307 COVID-19 patients were admitted, with 57.05% being male and a median of 76 years. The mortality rate was 24.43%, with a high incidence of severe acute respiratory syndrome (SARS) (14.03%) and acute kidney injury (AKI) (10.87%). The most used medicines were antibiotics (90.83%), antimalarials (42.63%), steroids (44.37%) and antivirals, such as lopinavir/ritonavir (42.63%). The use of tocilizumab (9.37%) and anti-SIRS (systemic inflammatory response syndrome) medicines (7.34%) were remarkable. Fundamentally, death occurred more likely over 65 years of age (OR: 9.05). In addition, the need for ventilation was associated with a higher probability of death (OR: 3.59), SARS (OR: 5.14) and AKI (OR: 2.31). The drug-use pattern had been modified throughout the COVID-19 first wave. Multiple factors, such as age, gender and the need for mechanical ventilation, were related to the worst evolution prognosis of the disease.

Background Pectum excavatum is a congenital thoracic alteration that can present important physiological alterations depending on the severity of the case. The Nuss procedure is a minimally invasive technique for managing chest wall deformity, in which there is a risk of perioperative complications. Case presentation This article presents the case of a 16-year-old patient who underwent placement of a Nuss bar and suffered intraoperative and postoperative cardiorespiratory arrest. Conclusions it is important to consider the possible early and late complications scenarios as well as their treatment in patients with pectum excavatum scheduled for a Nuss procedure.

The Atacama Desert, the driest of its kind on Earth, hosts a number of unique geological and geochemical features that make it unlike any other environment on the planet. Considering its location on the western border of South America, between 17 and 28 °S, its climate has been characterized as arid to hyperarid for at least the past 10 million years. Notably dry climatic conditions of the Atacama Desert have been related to uplift of the Andes and are believed to have played an important role in the development of the most distinctive features of this desert, including: (i) nitrates and iodine deposits in the Central Depression, (ii) secondary enrichment in porphyry copper deposits in the Precordillera, (iii) Li enrichment in salt flats of the Altiplano, and (iv) life in extreme habitats. The geology and physiography of the Atacama Desert have been largely shaped by the convergent margin present since the Mesozoic era. The geochemistry of surface materials is related to rock geochemistry (Co, Cr, Fe, Mn, V, and Zn), salt flats, and evaporite compositions in endorheic basins (As, B, and Li), in addition to anthropogenic activities (Cu, Mo, and Pb). The composition of surface water is highly variable, nonetheless in general it presents a circumneutral pH with higher conductivity and total dissolved solids in brines. Major water constituents, with the exception of HCO3−, are generally related to the increase of salinity, and despite the fact that trace elements are not well-documented, surface waters of the Atacama Desert are enriched in As, B, and Li when compared to the average respective concentrations in rivers worldwide.

With an increasing prevalence, dementia is one of the most disabling diseases among the elderly. Impaired cognitive function and behavioral and psychological symptoms predispose patients to medication non-adherence, resulting in increased morbidity, mortality, and healthcare costs. The aim of this study was to estimate the prevalence of non-adherence to antidementia medications and to identify the main predictors. A population-based registry study was conducted in 2022 in Castile and Leon, Spain. A total of 17,563 patients with dementia were included. The medication possession ratio (MPR) was used as an indirect method to measure adherence. The cut-off point for determining that a patient was nonadherent was 80% of MPR. Multivariate logistic regression was used to identify predictors of nonadherence based on sociodemographic and health-related variables. In 2022, 6.2% of the population over 80 years old used antidementia medications. Of these patients, 70% were women, 28.15% were institutionalized, and over 90% were polymedicated and had multiple prescribers. The most used medicines were donepezil (43.49%), rivastigmine (36.84%), and memantine (30.7%). The combined use of an acetylcholinesterase inhibitor plus memantine was relevant (13.33%). Men were less adherent than women, and the prevalence of non-adherence decreased with age. The medication associated with the highest prevalence of non-adherence was rivastigmine (19%), followed by donepezil (17%) and memantine (13.23%). Institutionalized patients (13%) and patients on combination therapy (13.29%) had the lowest prevalence of non-adherence. Protective factors against non-adherence include institutionalization, polymedication, use of memantine or combination therapy, and comorbid mental illness. In Castile and Leon, one in six patients were non-adherent to antidementia medications. Younger male patients with cardiometabolic disease are more likely to be non-adherent to antidementia medications. On the other hand, institutionalization is a protective factor against non-adherence, but still 10% of nursing home patients are non-adherent to antidementia medications.