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To explain the use of concept mapping in a study about family members’ experiences in taking care of people with cancer.

Direct release of inorganic compounds Cu (II) and Zn (II) into water bodies can disrupt ecosystems. Using microalgae biosorbent Tetraselmis chuii (T. chuii) is a promising approach for removing these metals from wastewater. This study investigated the effect of blue light on the absorption of Cu (II) and Zn (II) by analyzing the contact time and initial concentration. Statistical analysis (MANOVA) revealed differences in the biosorption process due to the contact time and Cu (II) concentration (P

The perceived disadvantage faced by high school students from rural areas in pursuing higher education is often associated with the fact that these areas are by default affected by socio-economic disadvantages. The analysis of the results from the high school baccalaureate examination for Romania, which is mandatory for admission to higher education, and which plays a major role in ranking the applicants, shows the potential outcomes of the university admission policy targeting high school baccalaureate holders from rural areas. Under different scenarios, this can lead to either targeted admission places being allocated to students that would have been otherwise successfully admitted by competing on general admission places or could have helped students from other disadvantaged backgrounds. These results may help as a basis for guiding policy designs that can better target admission places for students from disadvantaged backgrounds.

Climate change and increasing global temperatures have increased the frequency and intensity of forest fires, making fire risk evaluation increasingly important. This study aims to improve the accuracy of predicting forest fuel drought conditions (Drought Code) by using the XGBoost algorithm optimized with RandomizedSearchCV. The research methods include collecting data related to forest fires, preprocessing data to ensure quality and consistency, and using RandomizedSearchCV for XGBoost hyperparameter optimization. The results showed that the optimized XGBoost model resulted in a decrease in Mean Squared Error (MSE) and an increase in R-squared value compared to the default model. The optimized model achieved an MSE of 0.0210 and R2 of 0.9820 on the test data, indicating significantly improved prediction accuracy for forest fuel drought conditions. These findings emphasize the importance of hyperparameter optimization in improving the accuracy of predictive models for forest fire risk assessment.

Evidence-based practices (EBPs) have been taught to students by identifying the best evidence/evidence from research results. However, the experiences of Indonesian nurse preceptors in helping students implement research findings have not been explored thoroughly. This study aimed to explore Indonesian nurse preceptors in guiding nursing students to use research findings.

BackgroundThe ability to prioritize people living with HIV (PLWH) by risk of future transmissions could aid public health officials in optimizing epidemiological intervention. While methods exist to perform such prioritization based on molecular data, their effectiveness and accuracy are poorly understood, and it is unclear how one can directly compare the accuracy of different methods. We introduce SEPIA (Simulation-based Evaluation of PrIoritization Algorithms), a novel simulation-based framework for determining the effectiveness of prioritization algorithms. SEPIA expands upon prior related work by defining novel metrics of effectiveness with which to compare prioritization techniques, as well as by creating a simulation-based tool with which to perform such effectiveness comparisons. Under several metrics of effectiveness that we propose, we compare two existing prioritization approaches: one phylogenetic (ProACT) and one distance-based (growth of HIV-TRACE transmission clusters).ResultsUsing all proposed metrics, ProACT consistently slightly outperformed the transmission cluster growth approach. However, both methods consistently performed just marginally better than random, suggesting that there is significant room for improvement in prioritization tools.ConclusionWe hope that, by providing ways to quantify the effectiveness of prioritization methods in simulation, SEPIA will aid researchers in developing novel risk prioritization tools for PLWH.

Cancer has one of the highest disease mortality rates. Families are very important in the treatment of people with cancer. By using a phenomenological design, this study aimed to explore the experience of families in caring for a person with cancer and to identify the needs of these families.

Abstract While perovskite solar cells have reached competitive efficiency values during the last decade, stability issues remain a critical challenge to be addressed for pushing this technology towards commercialisation. In this study, we analyse a large homogeneous dataset of Maximum Power Point Tracking (MPPT) operational ageing data that we collected with a custom-built High-throughput Ageing System in the past 3 years. In total, 2,245 MPPT ageing curves are analysed which were obtained under controlled conditions (continuous illumination, controlled temperature and atmosphere) from devices comprising various lead-halide perovskite absorbers, charge selective layers, contact layers, and architectures. In a high-level statistical analysis, we find a correlation between the maximum reached power conversion efficiency (PCE) and the relative PCE loss observed after 150-hours of ageing, with more efficient cells statistically also showing higher stability. Additionally, using the unsupervised machine learning method self-organising map, we cluster this dataset based on the degradation curve shapes. We find a correlation between the frequency of particular shapes of degradation curves and the maximum reached PCE.

Purpose: This study aimed to explore nursing lecturers' experiences of online teaching and learning during the coronavirus disease 2019 (COVID-19) pandemic. The COVID-19 policy on social and physical distancing urges nursing lecturers to provide online teaching delivery for their students using both synchronous and asynchronous methods. However, the experiences of nursing lecturers providing online teaching delivery in the era of COVID-19 are yet unknown. Design/methodology/approach: The authors used an interpretive phenomenological analysis study design. Participants were seven nursing lecturers, with whom we conducted in-depth interviews using semi structured questions through telephone calls or video conferences. Interpretive phenomenology analysis was adopted to analyse the generated data. Findings: The core theme of this current study is that of becoming accustomed to online teaching delivery. The main theme is supported by three sub-themes, which are being comfortable with the technology, difficulties and how to overcome them and caring for students to explain the online teaching experiences of nursing lecturers. Originality/value: The results of this study demonstrate that familiarity with technology is critical for lecturers to facilitate their online teaching. There is a need for further enhancement of technology and application usage to improve the quality of nursing lecturers' teaching methods and ensure the provision of theory and nursing skill competency to students.

Tuberculosis is a critical issue in a community, and the rising number of cases can be attributed the development and evolution of the bacteria responsible. As part of independent nursing actions, educational intervention is a solution to improve prevention and treatment success at the family and community levels. This study aimed to determine the factors for Tuberculosis transmission. This research was a correlation study with a cross-sectional design, involving a sample of 100 participants selected through purposive sampling. Independent variables for the present study include age, gender, occupation, diabetes record, body mass index (BMI), and level of knowledge. Meanwhile, the dependent variable in this study is the risk of transmission. This observation used a questionnaire with chi-square and logistic regression analysis. The result showed that families with a thin body mass index had a lower likelihood of carrying out infectious behavior (p=0.000). Most respondents have a high level of knowledge and a low potential for infectious behavior. In fact, a good education system, it will allow someone to be independently trained to change behaviors and attitudes for the better.

This paper quantitatively analyzes how policy responses to the COVID-19 pandemic should differ in developing countries. To do so we build an incomplete-markets macroeconomic model with heterogeneous agents and epidemiological dynamics that features several of the key distinctions between advanced and developing economies germane to the pandemic. We focus in particular on differences in: age structure, fiscal capacity, healthcare capacity, informality, and the frequency of contacts between individuals at home, work, school and other locations. The model predicts that blanket lockdowns are less effective in developing countries, saving fewer lives per unit of lost GDP. In contrast, age-specific policies are even more effective, since they focus scarce public funds on shielding the smaller population of older individuals. School closures are also more effective at saving lives in developing countries, providing a greater reduction in secondary transmissions between children and older adults at home.

Research background. The consumption of whole grain cereal flour contributes to increased intake of dietary fibre and phenolic compounds beneficial to human health. However, whole grain flour also has some disadvantages, such as poor baking properties and lower technological quality. Applying ultrasonic and hydrothermal treatments can provide new opportunities to modify and improve the baking and biofunctionality of flour as well as the quality of baked goods. Experimental approach. The whole grain flour samples of six wheat varieties with different amylose content were studied. The original chemical composition and viscosity profiles of the flour were determined. The flour samples were subjected to ultrasonic treatment at a frequency of 30 kHz and temperature of 40 °C for 10 min and hydrothermal treatment on a magnetic stirrer with heating for 3 min after reaching the boiling point. The treatments were carried out to determine their influence on the studied digestible and antioxidant properties of the flour. A multistep in vitro enzymatic digestibility protocol simulating the digestion process in the human gastrointestinal tract was applied to the untreated and treated whole grain flour samples. Total free phenolic compound content and total antioxidant capacity were also determined. Results and conclusions. Hydrothermal treatment had a positive effect on the digestibility of the whole grain flour, especially in waxy wheat genotypes compared to those with high amylose content, due to the formation of resistant starch. The hydrothermal treatment had an overall negative effect on the antioxidant capacity of the flour samples, while ultrasonic treatment generally increased the analytical values of total free phenolic compounds by enhancing their extractability. These findings can provide valuable information for the development of new whole wheat foods. Novelty and scientific contribution. To the best of our knowledge, this type of study of the effects of ultrasound and hydrothermal treatment on the digestibility and antioxidant properties has not yet been performed on whole wheat flour with different amylose content. Waxy and high-amylose wheat varieties are considered novel raw materials because of their unique properties in bread making, such as improved bread texture and increased dietary fibre content. §Paper was presented at the 11th Central European Congress on Food and Nutrition CEFood2022, Čatež ob Savi, Slovenia, 27-30 September 2022

BackgroundTo date, there are no large studies delineating the clinical correlates of “pure” essential tremor (ET) according to its new definition.MethodsFrom the ITAlian tremor Network (TITAN) database, we extracted data from patients with a diagnosis of “pure” ET and excluded those with other tremor classifications, including ET-plus, focal, and task-specific tremor, which were formerly considered parts of the ET spectrum.ResultsOut of 653 subjects recruited in the TITAN study by January 2022, the data of 208 (31.8%) “pure” ET patients (86M/122F) were analyzed. The distribution of age at onset was found to be bimodal. The proportion of familial cases by the age-at-onset class of 20 years showed significant differences, with sporadic cases representing the large majority of the class with an age at onset above 60 years. Patients with a positive family history of tremor had a younger onset and were more likely to have leg involvement than sporadic patients despite a similar disease duration. Early-onset and late-onset cases were different in terms of tremor distribution at onset and tremor severity, likely as a function of longer disease duration, yet without differences in terms of quality of life, which suggests a relatively benign progression. Treatment patterns and outcomes revealed that up to 40% of the sample was unsatisfied with the current pharmacological options.DiscussionThe findings reported in the study provide new insights, especially with regard to a possible inversed sex distribution, and to the genetic backgrounds of “pure” ET, given that familial cases were evenly distributed across age-at-onset classes of 20 years. Deep clinical profiling of “pure” ET, for instance, according to age at onset, might increase the clinical value of this syndrome in identifying pathogenetic hypotheses and therapeutic strategies.

Plastic waste is now a major environmental problem worldwide, and it has worsened in the last few years. Scientists are studying how much plastic is in the environment, how dangerous it is, and how to learn it. This study looked at research papers on microplastics’ effects on plants listed by Scopus from 2011 to 2022. The goal was to see how this body of knowledge has grown and expanded over time and guess what it will do. The authors used the VOSviewer package and Scopus analytics for the bibliometric study. A total of 380 manuscripts, written by 159 authors, were taken out. Much study is being done on particle size, quantity, bioaccumulation, and environmental and community effects. Rillig, M.C., Das Berlin-Brandenburgisches Institut für Biodiversitatsforschung, Germany, is thought to be the most productive and often-cited researcher. The Ministry of Education China is the most essential printing house. China is the leader in terms of the number of papers and study partnerships. It is best to look at the International Journal of Pharmaceutics.

The role of the alkali metal cations in halide perovskite solar cells is not well understood. Using synchrotron-based nano-x-ray fluorescence and complementary measurements, we found that the halide distribution becomes homogenized upon addition of cesium iodide, either alone or with rubidium iodide, for substoichiometric, stoichiometric, and overstoichiometric preparations, where the lead halide is varied with respect to organic halide precursors. Halide homogenization coincides with long-lived charge carrier decays, spatially homogeneous carrier dynamics (as visualized by ultrafast microscopy), and improved photovoltaic device performance. We found that rubidium and potassium phase-segregate in highly concentrated clusters. Alkali metals are beneficial at low concentrations, where they homogenize the halide distribution, but at higher concentrations, they form recombination-active second-phase clusters.

Given the advent of Industry 4.0 and the importance of labour-based automation in ensuring competitiveness at the firm, regional cluster, or country level, the paper aims to explore, for the first time, the features of several estimates of occupational/labour automation and to assess the potential risks associated with it. A comparative analysis of the most well-established estimates of labour automation, the Occupational Information Network (O*NET) degree of automation estimates and Frey and Osborne’s future probabilities of automation was carried out to see whether, and to what extent, these estimates are compatible. Results show significant distributional differences between them, which are quantified into automation-triggered disruption risks at the occupational level, as current levels of labour automation are, in some cases, well below their future estimates. Work context features were used to derive a typology of occupations, which can explain up to one-third of the current, and up to half of the future levels of labour automation. Finally, we identified which occupations and occupational groups are likely to be affected by the highest risk of automation-induced displacement and estimated the magnitude of different disruption classes. Conclusions are compatible with other economywide assessments of the impact of labour automation on the workforce, thus being valuable inputs for corporate strategy, decision-makers and human resource planners as they address a growing need for quantitative insights useful for adapting the labour force structure, workers’ skills, and the task content of occupations to the competitiveness requirements related to the process of digitization in the Industry 4.0 context.