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This study analyzes the effects of COVID-19 confinement on the autonomous learning performance of students in higher education. Using a field experiment with 458 students from three different subjects at Universidad Autónoma de Madrid (Spain), we study the differences in assessments by dividing students into two groups. The first group (control) corresponds to academic years 2017/2018 and 2018/2019. The second group (experimental) corresponds to students from 2019/2020, which is the group of students that had their face-to-face activities interrupted because of the confinement. The results show that there is a significant positive effect of the COVID-19 confinement on students' performance. This effect is also significant in activities that did not change their format when performed after the confinement. We find that this effect is significant both in subjects that increased the number of assessment activities and subjects that did not change the student workload. Additionally, an analysis of students' learning strategies before confinement shows that students did not study on a continuous basis. Based on these results, we conclude that COVID-19 confinement changed students' learning strategies to a more continuous habit, improving their efficiency. For these reasons, better scores in students' assessment are expected due to COVID-19 confinement that can be explained by an improvement in their learning performance.

The present paper reviews the physiological responses of human liver carbohydrate metabolism to physical activity and ingestion of dietary sugars. The liver represents a central link in human carbohydrate metabolism and a mechanistic crux point for the effects of dietary sugars on athletic performance and metabolic health. As a corollary, knowledge regarding physiological responses to sugar ingestion has potential application to either improve endurance performance in athletes, or target metabolic diseases in people who are overweight, obese and/or sedentary. For example, exercise increases whole-body glycogen utilisation, and the breakdown of liver glycogen to maintain blood glucose concentrations becomes increasingly important as exercise intensity increases. Accordingly, prolonged exercise at moderate-to-high exercise intensity results in depletion of liver glycogen stores unless carbohydrate is ingested during exercise. The exercise-induced glycogen deficit can increase insulin sensitivity and blood glucose control, and may result in less hepatic lipid synthesis. Therefore, the induction and maintenance of a glycogen deficit with exercise could be a specific target to improve metabolic health and could be achieved by carbohydrate (sugar) restriction before, during and/or after exercise. Conversely, for athletes, maintaining and restoring these glycogen stores is a priority when competing in events requiring repeated exertion with limited recovery. With this in mind, evidence consistently demonstrates that fructose-containing sugars accelerate post-exercise liver glycogen repletion and could reduce recovery time by as much as half that seen with ingestion of glucose (polymers)-only. Therefore, athletes aiming for rapid recovery in multi-stage events should consider ingesting fructose-containing sugars to accelerate recovery.

Pyrolysis is a feasible solution for environmental problems related to the inadequate disposal of waste tires, as it leads to the recovery of pyrolytic products such as carbon black, liquid fuels and gases. The characteristics of pyrolytic carbon black can be enhanced through chemical activation in order to produce the required properties for its application. In the search to make the waste tire pyrolysis process profitable, new applications of the pyrolytic solid products have been explored, such as for the fabrication of energy-storage devices and precursor in the synthesis of nanomaterials. In this study, waste tires powder was chemically activated using acid (H2SO4) and/or alkali (KOH) to recover pyrolytic carbon black with different characteristics. H2SO4 removed surface impurities more thoroughly, improving the carbon black’s surface area, while KOH increased its oxygen content, which improved the carbon black’s stability in water suspension. Pyrolytic carbon black was fully characterized by elemental analysis, inductively coupled plasma–optical emission spectrometry (ICP-OES), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray diffraction (XRD), N2 adsorption/desorption, scanning electron microscopy–energy-dispersive X-ray spectroscopy (SEM-EDS), dynamic light scattering (DLS), and ζ potential measurement. In addition, the pyrolytic carbon black was used to explore its feasibility as a precursor for the synthesis of carbon dots; synthesized carbon dots were analyzed preliminarily by SEM and with a fluorescence microplate reader, revealing differences in their morphology and fluorescence intensity. The results presented in this study demonstrate the effect of the activating agent on pyrolytic carbon black from waste tires and provide evidence of the feasibility of using waste tires for the synthesis of nanomaterials such as carbon dots.

Metal–organic frameworks (MOFs) possess tuneable properties and a variety of important applications in the areas of catalysis, adsorption, gas storage, and separation, among others. Herein, recent computational studies by density functional theory (DFT) applied for simulations of MOF structure and complex architecture determination, prediction of properties, and computational characterization, including large-scale screening and geometrical properties of hypothetical MOFs, diffusion and adsorption processes in MOFs, are reviewed. DFT calculations have been applied in the MOF area to study chemical stability; mechanical, photophysical, optical, and magnetic properties; photoluminescence; porosity; and semiconductor or metallic character. The prediction of MOF analogs with open-metal sites, studies of chemical bonding and the prediction of energies by quantum mechanics allows reducing experimental efforts in the creation of MOF/polymer membranes, adsorbents for CO2 uptake, separation of C2H2/CH4, C2H2/CO2, and inert gases, radionuclides sequestration, and water adsorption, as well as other promising advances. For the MOF-derived carbons, a lack of profound DFT investigations is currently observed, being mainly restricted to the electrocatalysis area (nitrogen reduction reaction, oxygen evolution reaction, and hydrogen evolution reaction), resulting applications in batteries and other storage devices, CO2 sequestration, and absorbance of organic substances.

Controlling training monotony and monitoring external workload using the Acute:Chronic Workload Ratio (ACWR) is a common practice among elite soccer teams to prevent non-contact injuries. However, recent research has questioned whether ACWR offers sufficient predictive power for injury prevention in elite competition settings. In this paper, we propose a novel feature engineering framework for training load management, inspired by bilinear modeling and signal processing principles. Our method represents external workload variables, derived from GPS data, as discrete time series, which are then integrated into a temporal matrix termed the Footballer Workload Footprint (FWF). We introduce calculus-based techniques—applying integral and differential operations—to derive two representations from the FWF matrix: a cumulative workload matrix ( ∑ T F W F ) generalizing Acute Workload (AW), and a temporal variation matrix ( Δ T F W F ) generalizing Chronic Workload (CW) and formulating the ACWR. Our approach makes traditional workload metrics suitable for modern machine learning. Using real-world data from an elite soccer team competing in LaLiga (Spain’s top division) and UEFA tournaments, we conducted exploratory and confirmatory analyses comparing multivariate models trained on FWF-derived features against those using traditional ACWR calculations. The FWF-based models consistently outperformed baseline methods across key performance metrics—including the Area Under the ROC Curve (ROC-AUC), Precision-Recall AUC (PR-AUC), Geometric Mean (G-Mean), and Accuracy—while reducing Type I and Type II errors. Tested on temporally independent holdout data, our top model performed robustly across all metrics with 95% confidence intervals. Permutation tests revealed a significant association between FWF matrices and injury risk, supporting the empirical validity of our approach. Additionally, we introduce an interpretability framework based on heatmap visualizations of the FWF’s cumulative and temporal variations, enhancing explainability. These findings indicate that our approach offers a robust, interpretable, and generalizable framework for sports science and medical professionals involved in injury prevention and training load monitoring.

With a rising global population and looming water shortages in the U.S., there is a pressing need for water-efficient farming methods. The water needs of potato plants decrease in the late season due to foliage aging and tuber maturation. Therefore, proper late-season irrigation is vital in preventing water waste and maximizing potato profits. This study assessed the feasibility of reducing late-season irrigation to improve crop water productivity (WPc), tuber quality, and economic return. Field trials were planted near Othello, WA, across three years (2018–20). Treatments included five irrigation levels (ILs), 40%, 60%, 80%, 100%, and 120% of modeled evapotranspiration (ET), and five potato cultivars: Alturas, Clearwater Russet, Ranger Russet, Russet Burbank, and Umatilla Russet. Treatments started 100 to 105 days after planting (DAP), approximately 1500 day degrees (at or near peak canopy growth), and ended at vine kill, 150 to 155 DAP. Water from reduced ILs of 40% to 80% ET was more efficiently converted into yield (WPc) for Alturas than higher ILs; however, economic return for all cultivars typically peaked when irrigation was supplied at or above 80% ET. Tuber quality generally improved with a reduction in irrigation level, occasionally at the expense of yield and economic value.

Plant growth-promoting bacteria (PGPB) are soil and rhizosphere bacteria that can benefit plant growth by different mechanisms. The ability of some microorganisms to convert insoluble phosphorus (P) to an accessible form, like orthophosphate, is an important trait in a PGPB for increasing plant yields. In this mini-review, the isolation and characterization of genes involved in mineralization of organic P sources (by the action of enzymes acid phosphatases and phytases), as well as mineral phosphate solubilization, is reviewed. Preliminary results achieved in the engineering of bacterial strains for improving capacity for phosphate solubilization are presented, and application of this knowledge to improving agricultural inoculants is discussed.

Midlobular hepatocytes are proposed to be the most plastic hepatic cell, providing a reservoir for hepatocyte proliferation during homeostasis and regeneration. However, other mechanisms beyond hyperplasia have been little explored and the contribution of other hepatocyte subpopulations to regeneration has been controversial. Thus, re-examining hepatocyte dynamics during regeneration is critical for cell therapy and treatment of liver diseases. Using a mouse model of hepatocyte- and non-hepatocyte- multicolor lineage tracing, we demonstrate that midlobular hepatocytes also undergo hypertrophy in response to chemical, physical, and viral insults. Our study shows that this subpopulation also combats liver impairment after infection with coronavirus. Furthermore, we demonstrate that pericentral hepatocytes also expand in number and size during the repair process and Galectin-9-CD44 pathway may be critical for driving these processes. Notably, we also identified that transdifferentiation and cell fusion during regeneration after severe injury contribute to recover hepatic function. Hepatocytes regenerate the liver after injury, however, the tissue repair mechanisms have been little explored. Here, the authors show that midlobular and pericentral hepatocytes increase their number and size in response to chemical, physical, and viral insults facilitating liver regeneration.

Steringotrema microacetabularis Suriano & Martorelli, 1983 (Fellodistomidae) was described from the flounder Paralichthys orbignyanus. Later, it was redescribed, based on new material from the same host and type locality, and reconsidered as Bacciger microacetabularis (Baccigeridae). The main difference noted in the redescription was the presence of spines on the body. However, the lack of DNA data made confirming the true affiliation of this digenean challenging. New specimens sampled from P. orbignyanus allowed us to sequence the 28S, ITS, and COI genes. Fresh specimens were stained to compare their morphology with the holotype and voucher specimens. The digeneans found correspond with those reported from Mar Chiquita, described as B. microacetabularis (=S. microacetabularis). Genetic analyses clustered the newly sequenced individuals within the Cryptogonimidae, showing relationships with Oligogonotylus manteri, Tabascotrema verai, and Caecincola parvulus (28S); T. verai, Lobosorchis spp., Euryakaina manilensis, and Metadena marina (ITS); and Siphoderina spp. (COI). After comparing the species with cryptogonimids lacking spines in the oral sucker, a new genus, Surianotrema n. gen., is described. This genus increases the number of cryptogonimid genera known in South America to seven – three in freshwater and four in marine environments – with Surianotrema n. gen. being the first to be sequenced. New sequences from other South American cryptogonimids are necessary to better understand the phylogenetic relationships between genera within this family, particularly in South America.

This work presents a methodology integrating Non-Linear Programming (NLP) for multi-objective and multi-period optimization, addressing sustainable waste management and energy conversion challenges. It integrates waste-to-energy (WtE) technologies such as Anaerobic Digestion (AD), Incineration (Inc), Gasification (Gsf), and Pyrolysis (Py), and considers thermochemical, technical, economic, and environmental considerations through rigorous non-linear functions. Using Mexico City as a case study, the model develops waste management strategies that balance environmental and economic aims, considering social impacts. A trade-off solution is proposed to address the conflict between objectives. The economical optimal solution generates 1.79M$ with 954 tons of CO 2 emissions while the environmental one generates 0.91M$ and reduces emissions by 54%, where 40% is due to gasification technology. Moreover, the environmentally optimal solution, with incineration and gasification generates 9500 MWh/day and 5960 MWh/day, respectively, demonstrates the capacity of the model to support sustainable energy strategies. Finally, this work presents an adaptable framework for sustainable waste management decision-making.