New methods for new needs? Analysis of the study plans in Social Work from the perspective of graduates: the case of the University of La Laguna

The purpose of the research is to analyze the opinions of the graduates in Social Work of the University of La Laguna about their Study Plan, in order that it can serve to evaluate, improve and update this and other curricula of the discipline in other university centres. This work has a descriptive quantitative method and used a questionnaire for data collection, with 102 participants and statistical treatment with SPSS. The main results show a great demand to adjust, firstly, the teaching methods of the teaching staff to the new needs of their students, and secondly, the subjects and contents with the current social realities. Likewise, it points towards a disconnection between university-society, reflected in the problems derived from curricular practices and the application of workshops with external professionals and real practical cases as two of the favourites activities as content of practical classes. Therefore, studies in Social Work in Spain must remain in constant review so as not to be outdated, since social reality, its object of study and analysis, is an element in constant change.

How causal is a reciprocal effect? Contrasting traditional and new methods to investigate the reciprocal effects model of self-concept and achievement

The relationship between students’ subject-specific academic self-concept and their academic achievement is one of the most widely researched topics in educational psychology. A large body of this research has considered cross-lagged panel models (CLPMs), oftentimes synonymously referred to as reciprocal effects models (REMs), as a gold standard to investigate the causal relations between the two variables and has reported evidence for a reciprocal relationship between self-concept and achievement. However, more recent methodological research questioned the plausibility of assumptions that need to be satisfied in order to interpret results from traditional CLPMs causally. In this substantive-methodological synergy, we aimed at contrasting traditional and more recently developed methods to investigate reciprocal effects of students’ academic self-concept and achievement. Specifically, we compared results from CLPMs, from full forward CLPMs (FF-CLPMs), and from random intercept CLPMs (RI-CLPMs) with two weighting approaches developed to study causal effects of continuous treatment variables. To estimate these different models, we used rich longitudinal data of N = 3,757 students from lower secondary schools in Germany. Results from CLPMs, FF-CLPMs, and weighting methods support the reciprocal effects model, particularly when considering math self-concept and grades. In contrast, results from the RI-CLPMs were less consistent. Implications from our study for the interpretation of effects from the different models and methods as well as for school motivation theory are discussed.

A Blueprint for Ocean Literacy: EU4Ocean

In this paper, we discuss the importance of the efficient communication of science results to citizens across the world. In order for people to absorb information, we need to understand the principles and apply the best available means to facilitate the process of increasing global awareness of the changes. This explicitly applies to the verification of how we appeal to people with respect to various environmental issues and, hence, how we can modernize the educational approaches to challenge the global change. We state that, in order to follow the philosophy of sustainable development goals with respect to ocean issues, we need an attractive alternative to the existing areas of consumption. We also state that the ocean issues are at the core of any process aiming to secure sustainability. New methods and tools of education and scientific communication, especially those which are offered by non-formal approaches, are necessary, and we present here some of the activities of the EU4Ocean coalition as best practice examples.

Multi-Omics Analysis of Lipid Metabolism for a Marine Probiotic Meyerozyma guilliermondii GXDK6 Under High NaCl Stress

Investigating microbial lipid regulation contributes to understanding the lipid-dependent signal transduction process of cells and helps to improve the sensitivity of microorganisms to environmental factors by interfering with lipid metabolism, thus beneficial for constructing advanced cell factories of novel molecular drugs. Integrated omics technology was used to systematically reveal the lipid metabolism mechanism of a marine Meyerozyma guilliermondii GXDK6 under high NaCl stress and test the sensitivity of GXDK6 to antibiotics when its lipid metabolism transformed. The omics data showed that when GXDK6 perceived 10% NaCl stress, the expression of AYR1 and NADPH-dependent 1-acyldihydroxyacetone phosphate reductase was inhibited, which weaken the budding and proliferation of cell membranes. This finding was further validated by decreased 64.39% of OD600 under 10% NaCl stress when compared with salt-free stress. In addition, salt stress promoted a large intracellular accumulation of glycerol, which was also verified by exogenous addition of glycerol. Moreover, NaCl stress remarkably inhibited the expression of drug target proteins (such as lanosterol 14-alpha demethylase), thereby increasing sensitivity to fluconazole. This study provided new insights into the molecular mechanism involved in the regulation of lipid metabolism in Meyerozyma guilliermondii strain and contributed to developing new methods to improve the effectiveness of killing fungi with lower antibiotics.

Predictive stochastic analysis of massive filter-based electrochemical reaction networks

Chemical reaction networks (CRNs) are powerful tools for obtaining mechanistic insight into complex reactive processes. However, they are limited in their applicability where reaction mechanisms are not well understood and products are unknown. Here we report new methods of CRN generation and analysis that overcome these limitations. By constructing CRNs using filters rather than templates, we can capture species and reactions that are unintuitive but fundamentally reasonable. The resulting massive CRNs can then be interrogated via stochastic methods, revealing thermodynamically bounded reaction pathways to species of interest and automatically identifying network products. We apply this methodology to study solid-electrolyte interphase (SEI) formation in Li-ion batteries, generating a CRN with ~86,000,000 reactions. Our methods automatically recover SEI products from the literature and predict previously unknown species. We validate their formation mechanisms using first-principles calculations, discovering novel kinetically accessible molecules. This methodology enables the de novo exploration of vast chemical spaces, with the potential for diverse applications across thermochemistry, electrochemistry, and photochemistry.

Rigid Sets and Coherent Sets in Realistic Ocean Flows

This paper focuses on the extractions of Lagrangian Coherent Sets from realistic velocity fields obtained from ocean data and simulations, each of which can be highly resolved and non volume-preserving. We introduce two novel methods for computing two formulations of such sets. First, we propose a new “diffeomorphism-based” criterion to extract “rigid sets”, defined as sets over which the flow map acts approximately as a rigid transformation. Second, we develop a matrix-free methodology that provides a simple and efficient framework to compute “coherent sets” with operator methods. Both new methods and their resulting rigid sets and coherent sets are illustrated and compared using three numerically simulated flow examples, including a high-resolution realistic, submesoscale to large-scale dynamic ocean current field in the Palau Island region of the western Pacific Ocean.

Laser Reconstruction of Spinal Discs Experiments and Clinic

Degenerative disease of the intervertebral discs (DDD) is currently a serious problem facing the world community. The surgical methods and conservative therapy used today, unfortunately, do not stop the pathological process, but serve as a palliative method that temporarily relieves pain and improves the patient’s quality of life. Therefore, at present, there is an active search for new methods of treating DDD. Among new techniques of treatment, biological methods, and minimally invasive surgery, including the use of laser radiation, which, depending on the laser parameters, can cause ablative or modifying effects on the disc tissue, have acquired considerable interest. Here, we analyze a new approach to solving the DDD problem: laser tissue modification. This review of publications is focused on the studies of the physicochemical foundations and clinical applications of a new method of laser reconstruction of intervertebral discs. Thermomechanical action of laser radiation modifies tissue and leads to its regeneration as well as to a long-term restoration of disc functions, elimination of pain and the return of patients to normal life.

COVID-19 vaccination breakthrough infections in a real-world setting: Using community reporters to evaluate vaccine effectiveness

Background COVID-19 has highlighted the need for new methods of pharmacovigilance. Here we use community volunteers to obtain systematic information on vaccine effectiveness and the nature and severity of breakthrough infections. Methods Between December 15, 2020 to September 16, 2021, 10,412 unpaid community-based participants reported the following information to an on-line registry: COVID-19 test results, vaccination (Pfizer, Moderna, or Johnson & Johnson), COVID-19 symptoms and perceived severity using a 4-point scale. COVID-19 infections were described for those who were 1) fully vaccinated, 2) partially vaccinated (received first of two dose vaccines or were <14 days post-final dose), or 3) unvaccinated. Results Of 8,554 who were vaccinated, COVID-19 infections were reported by 74 (1.0%) of those who were fully vaccinated and 198 (2.3%) of those who were partially vaccinated. Among the 74 participants who reported a breakthrough infection after full vaccination, the median time to reported positive test result was 104.5 days (Interquartile range: 77-135 days), with no difference among vaccine manufactures. One quarter (25.7%) of breakthrough infections in the fully vaccinated cases were asymptomatic. More than 97% of fully vaccinated participants reported no moderate/severe symptoms compared to 89.3% of the unvaccinated cases; and only 1.4% of fully vaccinated participants reported experiencing at least 3 moderate to severe symptoms compared to 7.8% in the unvaccinated. Conclusion Person-generated health data, also referred to as patient-reported outcomes, is a useful resource for quantifying breakthrough infections and their severity, showing here that fully vaccinated participants report no or very mild COVID-19 symptoms.