bluuebunny/crossref_metadata_2025 huggingface dataset:
The key-roles of the expert during classroom discussions aimed at fostering formative assessment processes through the use of digital technologies
Authors: Cusi Annalisa , Morselli Francesca
Published: April 2024

We study the experts’ practices developed with the support of digital technologies (DT), when they take aware in-the-moment decisions during classroom discussions to promote the development of effective formative assessment (FA) processes. In this investigation, we complement a macro-analysis of paradigmatic examples of classroom activities, focused on the functionalities of DT and on the implemented FA strategies, with a micro-analysis, developed with reference to a theoretical construct useful for interpreting and analysing expert teachers’ roles during classroom discussions (the Model of Aware and Effective Attitudes and Behaviours, MAEAB). More specifically, we explore how the expert uses DT to empower these roles with the aim of promoting FA processes. This study has two implications: (1) at the theoretical level, the study will introduce a model aimed at characterising the ways in which the expert can promote FA during classroom discussions when they are mediated by the use of DT; (2) at the pragmatic level, the use of this model to analyse paradigmatic examples from teaching experiments will introduce potential guidelines for teacher professional development aimed at promoting teachers’ autonomous use of DT to carry out effective FA practices.
Arme Kinder und ihre Familien
Authors: Klundt Michael
Published: April 2024

In dem Beitrag geht es um mediale und politische Diskurse über Kinderarmut und über Konzepte zu einer Kindergrundsicherung. Problematisiert werden zunächst Vorgehensweisen verschiedener armuts-verzerrender Varianten in Medien und Wissenschaft sowie Ursachen mit Anlässen verwechselnde Armutsbetrachtungen einiger Forscher_innen und Journalist_innen. Ebenso untersucht der Beitrag die Frage, wie und warum bisherige Maßnahmen gegen Kinderarmut offensichtlich nicht erfolgreich gewirkt haben und, was nun z. B. mit der von der Bundesregierung versprochenen Kindergrundsicherung geplant und zu erwarten ist. Schließlich soll ergründet werden, welche Maßnahmen notwendig wären, um Kinderarmut wirklich abzubauen.
Detecting the Impact of Academics Self-Citations: Fi-Score
Authors: Fiorillo Luca
Published: April 2024

The academic landscape has witnessed significant transformations in recent years, primarily attributed to advancements in IT tools, which have advantages and drawbacks in the world of publications. The transition from traditional university library searches to the digital era, with access to various information sources such as Pubmed, Scopus, Web of Science and Google Scholar, has revolutionized research practices. Thanks to technology, researchers, academics and students now enjoy rapid and vast information access, facilitating quicker manuscript preparation and boosting bibliometric parameters. To identify authors “self-distorted” bibliometric parameters, different indices following the Hirsch index (h-index) (based on citations) have been proposed. The new “fi-score” evaluates the reliability of citation counts for individual authors and validates the accuracy of their h-index, comparing the number of citations to the h-index value to highlight value that is not within the norm and probably influenced or distorted by authors themselves. It examines how authors’ citations impact their h-index, although they are not self-citing. The study calculated the fi-score on a sample of 194,983 researchers. It shows that the average value of the fi-score is 25.03 and that a maximum value admissible as good must not exceed 32. The fi-score complements existing indexes, shedding light on the actual scientific impact of researchers. In conclusion, bibliometric parameters have evolved significantly, offering valuable insights into researchers’ contributions. The fi-score emerges as a promising new metric, providing a more comprehensive and unbiased evaluation of scholarly impact. By accounting for the influence of citations and self-citations, the fi-score addresses the limitations of traditional indices, empowering academic communities to recognize better and acknowledge individual contributions.
Predicting psychological need satisfaction and frustration from early maladaptive schemas and DSM-5 and ICD-11 personality traits
Authors: Thimm Jens C.
Published: April 2024

The satisfaction of basic psychological needs is closely connected with an individual’s well-being and mental health. The purpose of the present study was to examine the associations of persistent and pervasive negative cognitions about oneself and others (early maladaptive schemas) and pathological personality traits (DSM-5 and ICD-11 personality traits) with the satisfaction and frustration of basic psychological needs. To this aim, self-report measures of psychological need satisfaction (Basic Psychological Need Satisfaction and Frustration Scale), early maladaptive schemas (Young Schema Questionnaire – Short Form 3), and pathological personality traits (Modified Personality Inventory for DSM-5 and ICD-11 – Brief Form Plus), were administered in a community sample (N = 322, Mage = 35.3 years, SDage = 12.5 years, 66% female). The data were analyzed using correlation analysis, linear regression analysis, and a machine-learning approach (XGBoost). The results showed strong negative relationships of early maladaptive schemas and pathological personality traits with the satisfaction and frustration of the needs for autonomy, relatedness, and competence, especially the disconnection/rejection and impaired autonomy/performance schema domains and the pathological personality traits of negative affectivity and detachment. Early maladaptive schemas predicted the frustration of the psychological needs for relatedness and competence above pathological personality traits. The study findings add to the understanding of current psychological need satisfaction.
Relationship among sleep quality, quality of life and academic self-efficacy of university students
Authors: Aydin Funda , Aydin Aylin
Published: April 2024

This study aimed to explore the interconnections among quality-of-life, sleep quality, and academic self-efficacy as loads of researches have indicated a correlation between these elements, suggesting that they are intricately linked. The current investigation delved into the reciprocal relationships between these concepts, examining their bidirectional correlations with 410 students (Female = 267, Male = 143), (M = 22.04, SD = 3.367), and the findings indicated an interrelationship among the quality-of-life, academic self-efficacy, and sleep quality of university students. The results of the study revealed a continuous positive significant relationship between all sub-categories of the quality of life and academic self-efficacy (r = .396, p < .01) which is a novel result in the field. Another novel result is that decreasing sleep quality is associated with low academic self-efficacy (r=-.121, p < .01). Studies in the field were supported with this study in terms of revealing the existing correlation between quality of life and sleep quality measured with Richards – Campbell Sleep Scale (r = .341, p < .01) and Pittsburgh Sleep Quality Index (r = .439, p < .01) both of which indicate a relationship between an increasing sleep quality and high quality of life. On the other hand, the quality of life and sleep quality are found to be significant predictors of academic self-efficacy which is an important contributing result to the field (R2 = 0.226, p < .0,01), (R2 = 0.015, p < .0,05). These results must be taken into account when the role of sleep quality and quality-of-life on academic life of individuals is researched.
Impacts of family functioning on social avoidance and distress among people with disabilities: a moderated mediating model
Authors: Fengbo Liu , Ning Li , Yue Xi
Published: April 2024

This study has conducted a questionnaire survey on 600 people with disabilities and 600 healthy people, compared their psychological characteristics, and examined the mediating effects of perceived social support and happiness on the relationship between family functioning and social avoidance and distress among people with disabilities, as well as whether this process is moderated by self-esteem. The results reveal that there are significant differences between people with disabilities and healthy people in terms of happiness and self-esteem; perceived social support and happiness have multiple mediating effects on the relationship between family functioning of people with disabilities and their social avoidance and distress; and the mediating effect of perceived social support is moderated by self-esteem, and self-esteem moderates the latter half path of the mediating process of family functioning - perceived social support - social avoidance and distress. Therefore, the impacts of family functioning of people with disabilities on their social avoidance and distress is a moderated mediating model. The findings from the study are of theoretical and practical significance for improving social skills of people with disabilities.
Exploring the Therapeutic Potential of Scorpion-Derived Css54 Peptide Against Candida albicans
Authors: Park Jonggwan , Kim Hyeongsun , Kang Da Dam , Park Yoonkyung
Published: April 2024

Candida albicans (C. albicans) is one of the most common opportunistic fungi worldwide, which is associated with a high mortality rate. Despite treatment, C. albicans remains the leading cause of life-threatening invasive infections. Consequently, antimicrobial peptides (AMPs) are potential alternatives as antifungal agents with excellent antifungal activity. We previously reported that Css54, found in the venom of Centrurodies suffusus suffusus (C. s. suffusus) showed antibacterial activity against zoonotic bacteria. However, the antifungal activity of Css54 has not yet been elucidated. The objective of this study was to identify the antifungal activity of Css54 against C. albicans and analyze its mechanism. Css54 showed high antifungal activity against C. albicans. Css54 also inhibited biofilm formation in fluconazole-resistant fungi. The antifungal mechanism of action of Css54 was investigated using membrane-related assays, including the membrane depolarization assay and analysis of the membrane integrity of C. albicans after treatment with Css54. Css54 induced reactive oxygen species (ROS) production in C. albicans, which affected its antifungal activity. Our results indicate that Css54 causes membrane damage in C. albicans, highlighting its value as a potential therapeutic agent against C. albicans infection.
Harbour porpoise (Phocoena phocoena) in the Wadden Sea World Heritage Site and requirements for trilateral monitoring
Authors: Scheidat Meike , Vrooman Jip , Teilmann Jonas , Baltzer Johannes , Bie Thøstesen Charlotte , Diederichs Britta , Dietz Rune , Geelhoed Steve C. V. , Gilles Anita , IJsseldijk Lonneke L. , Keijl Guido O. , Nabe-Nielsen Jacob , Ruser Andreas , Schnitzler Joseph , Sveegaard Signe , Siebert Ursula
Published: April 2024

The harbour porpoise (Phocoena phocoena) is considered part of the ‘Outstanding Universal Value’ characterising the Wadden Sea World Heritage Site (WS WHS). The Trilateral Wadden Sea Plan aims to preserve the conservation status of the Trilateral Wadden Sea Cooperation Area, encompassing the WS WHS. The plan has specified two conservation targets for the harbour porpoise: (1) viable stocks and a natural reproduction capacity and (2) conservation of habitat quality for its conservation. To assess the current occurrence of the harbour porpoise in the Wadden Sea area, we collated and analysed data from regional and national research projects using telemetry, aerial surveys, strandings and passive acoustic monitoring, obtained over the years 1990–2020. The results illustrate that porpoises occur in both offshore and intertidal waters, showing seasonal movements and changes in local occurrence over time. Some porpoises displayed limited home ranges throughout the year, suggesting a possible residency for some of the animals using the Wadden Sea area. We also showed that methods, frequency and spatial coverage of monitoring activities vary among the countries Denmark, Germany and the Netherlands. We discuss the suitability of the different methods both regarding the challenges of monitoring in the complex Wadden Sea habitat as well as their ability to target the conservation aims of the WHS. We give several recommendations to assess the status of the species to meet the identified conservation aims.
Estrogenic, androgenic, and genotoxic activities of zearalenone and deoxynivalenol in in vitro bioassays including exogenous metabolic activation
Authors: Yu Maria , Oskarsson Agneta , Alexander Jan , Lundqvist Johan
Published: April 2024

Zearalenone (ZEN) and deoxynivalenol (DON) and their derivatives are well-known mycotoxins, which can occur not only in crops but also in water bodies, including drinking water sources. In vitro bioassays can be used to detect biological effects of hazardous compounds in water. To this, when studying biological effects and toxicity in vitro, metabolism is important to consider. In this study, ZEN, α-zearalenol (α-ZEL), DON, 3-acetyl DON, and 15-acetyl DON were evaluated in vitro for hormone receptor–mediated effects (estrogen receptor [ER] and androgen receptor [AR]) and genotoxicity (micronucleus assay) in the presence of an exogenous metabolic activation system (MAS). The ER bioassay proved to be a highly sensitive method to detect low concentrations of the ZEN compounds (EC10 values of 31.4 pM for ZEN, 3.59 pM for α-ZEL) in aqueous solutions. In the presence of the MAS, reduced estrogenic effects were observed for both ZEN compounds (EC10 values of 6.47 × 103 pM for ZEN, 1.55 × 102 pM for α-ZEL). Of the DON compounds, only 3-acetyl DON was estrogenic (EC10 of 0.31 µM), and the effect was removed in the presence of the MAS. Anti-androgenic effects of the ZEN compounds and androgenic effects of the DON compounds were detected in the micromolar range. No induction of genotoxicity was detected for ZEN or DON in the presence of the MAS. Our study highlighted that inclusion of exogenous MAS is a useful tool to detect biological effects of metabolites in in vitro bioassays.
Decoding the complexities of transitions in football: a comprehensive narrative review
Authors: Eusebio Pedro , Prieto-González Pablo , Marcelino Rui
Published: April 2024

Background

Transitions in football are pivotal moments in the game, carrying significant tactical and strategic implications. Despite the lack of a consensus on the exact definition and duration of transitions, their importance is evident in the analysis of football matches. Clear connections exist between performance indicators, team play styles, and specific game moments. The evolution of game analysis, facilitated by technology employing spatial, optical, and motion sensors, has heightened the recognition of transition actions.

Methods

This narrative review synthesizes perspectives on transitions from various authors and investigates how these perspectives have evolved over time. By utilizing real-time analysis through advanced technology, the review aims to offer a comprehensive understanding of transitions in football.

Results

Counterattacks are identified as a key outcome emerging from transitions, affirming existing literature suggesting that each transition prompts a response from the opposing team. The review underscores the need to objectively define the dichotomy of transitions in terms of the moment of play and style of play, mitigating overlap and confusion.

Conclusion

Transitions are complex phenomena occurring independently of ball possession. Understanding their classification, determinants, and outcomes is crucial for optimizing team performance. By shedding light on the multifaceted nature of transitions, this review contributes to a more nuanced comprehension of this critical aspect of football strategy.
The Path Innovation of Regional Economic Growth: Data Analysis Based on China
Authors: Zhang Jing , Teng Tangwei , Wang Tingting , Zeng Gang
Published: April 2024

Innovative development to some extent overcomes the path-dependent characteristics of knowledge proximity, and the diversity and complexity of regional knowledge and technology foster regional economic growth. This study constructs a dynamic mechanism for maximizing the enterprise profit to explore the conditions enabling regions that can achieve knowledge accumulation and technological leapfrogging. Utilizing the fitness landscape methodology based on customs data from 30 provinces in China and employing genetic algorithms, we analyze two modes of enterprises with similar and different initial conditions under varying leapfrogging scenarios. By applying profit maximization rules within the fitness landscape of the product space, we examine how to promote regional industrial transformation and upgrade. The results indicate that a larger leap range in the production of products by enterprises, reflecting stronger innovative capabilities, significantly enhances the region’s ability for industrial transformation and upgrade. There is a strong positive relationship between the initial industrial foundation and regional economic development. When regions share a similar industrial base, the complexity of regional knowledge becomes more critical. Therefore, an increase in the foundational development of industries and technology-intensive products can enhance the potential for regional path innovation. Past research has primarily been based on the path dependence theory, emphasizing that the most crucial aspect for underdeveloped economies is the accumulation and development of foundational capabilities. However, our study contends that, for emerging economies, it is crucial to enhance the diversity and complexity of knowledge and technology. Particularly, it is essential to, based on a comprehensive understanding of their own strengths, open up new areas and new arenas in development, continually shaping new growth drivers and new strengths. This emerges as a significant factor in regional growth and leapfrog development.
Reforming Inspection of Childcare Provision: Lessons from Israel
Authors: Moshel Smadar
Published: April 2024

This study explores the impact of transitioning from structural quality to process quality in the regulation of Early Childhood Education and Care (ECEC) for children aged birth to 3 years on the professional identity of inspectors. The research centers on a pilot program led by the Day Care Division at the Ministry of Welfare in Israel, which aimed to reform the inspection of day care facilities in the country. The methodology involves conducting 24 interviews with day care inspectors who participated in the pilot program, tracing their evolving understanding of their professional identity and their adaptation to the new regulatory model. The study's findings reveal that inspectors' professional identity comprises five key aspects: source of authority, inspection methods, superintendent's skill set, role perception, and their perception of the regulated entities. Inspectors are compelled to redefine their professional identity in response to changes in the regulatory model. In conclusion, this research underscores the intricate nature of inspectors' roles during periods of regulatory transformation. Shifting toward a process-oriented ECEC regulation necessitates the development of a new professional identity for inspectors. This shift presents them with heightened ethical dilemmas and exposes them to the risk of regulatory capture.
Reservoir rock typing for optimum permeability prediction of Nubia formation in October Field, Gulf of Suez, Egypt
Authors: Kassab Mohamed A. , Abbas Ali E. , Osman Ihab A. , Eid Ahmed A.
Published: April 2024

Permeability prediction and distribution is very critical for reservoir modeling process. The conventional method for obtaining permeability data is from cores, which is a very costly method. Therefore, it is usual to pay attention to logs for calculating permeability where it has massive limitations regarding this step. The aim of this study is to use unique artificial intelligence (AI) algorithms to tackle this challenge and predict permeability in the studied wells using conventional logs and routine core analysis results of the core plugs as an input to predict the permeability in non-cored intervals using extreme gradient boosting algorithm (XGB). This led to promising results as per theR2correlation coefficient. TheR2correlation coefficient between the predicted and actual permeability was 0.73 when using the porosity measured from core plugs and 0.51 when using the porosity calculated from logs. This study presents the use of machine-learning extreme gradient boosting algorithm in permeability prediction. To our knowledge, this algorithm has not been used in this formation and field before. In addition, the machine-learning model established is uniquely simple and convenient as only four commonly available logs are required as inputs, it even provides reliable results even if one of the required logs for input is synthesized due to its unavailability.
Numerical simulation of multi-field coupling in geothermal reservoir heat extraction of enhanced geothermal systems
Authors: Zeng Zhi , Shen Weijun , Wang Mingcang , Li Zhiyu , Wang Xiangyang , Ding Jianghui
Published: April 2024

The coupled analysis of multi-field heat and mass transfer in geothermal reservoirs is a pivotal concern within the realm of geothermal rock exploitation. It holds significant implications for the assessment of thermal energy capacity and the formulation of reservoir optimization strategies in the context of geothermal rock resources. Parameters governing production, along with fracture network characteristics (such as injection well temperature, injection well pressure, fracture width, and fracture network density), exert an influence on enhanced geothermal systems (EGS) heat production. In this study, aiming to comprehend the dynamic heat generation of EGS during prolonged exploitation, a coupling of various fields including permeation within the rock formations of geothermal reservoirs and the deformation of these rocks was achieved. In this study, we formulated the governing equations for the temperature field, stress field, and permeability field within the geothermal reservoir rock. Subsequently, we conducted numerical simulations to investigate the heat transfer process in an enhanced geothermal system. We analyzed the effects of injection well temperature, injection well pressure, primary fracture width, and secondary fracture density on the temperature distribution within the reservoir and the thermal power output of the production well. The research findings underscore that ill-conceived exploitation schemes markedly accelerate the thermal breakthrough rate of production wells, resulting in a diminished rate of geothermal resource extraction from the geothermal reservoir rock. Variations in influent well temperature and secondary fracture density exhibit an approximately linear impact on the output from production wells. Crucially, injection well pressure and primary fracture width emerge as pivotal factors influencing reservoir output response, with excessive widening of primary fractures leading to premature thermal breakthrough in production wells.
Multi-objective optimization of parameters design based on genetic algorithm in annulus aerated dual gradient drilling
Authors: Li Qian , Zhang Xiaolin , Yin Hu
Published: April 2024

The optimization of drilling parameters is crucial for resolving the drilling problems in low-pressure and leaky formations using the annulus aerated dual gradient drilling technology. However, the previous studies have mostly focused on engineering applications and wellbore fluid flow models, with less emphasis on parameter optimization. This paper combines the wellbore multiphase flow model with genetic algorithms for the first time, proposing a key parameter optimization method for annulus aerated dual gradient drilling based on genetic algorithms. The study investigates the impact of selection operators on the performance of genetic algorithms and compares genetic algorithms with PSO algorithm and SAA. The results indicate that the convergence and stability of genetic algorithms can be improved by enhancing the selection operators. Compared to the gas–liquid ratio parameter optimization method, the IRSGA optimization method reduces the cost coefficient by 36.46%. Through comparative analysis of different optimization methods, the IRSGA demonstrates over 95% accuracy in large-scale computations. The research findings contribute to the optimization of parameters design under low-cost conditions and are of significant importance for promoting the use of this technology to address the serious issue of lost circulation in drilling technology.
Automated real-time prediction of geological formation tops during drilling operations: an applied machine learning solution for the Norwegian Continental Shelf
Authors: Elahifar Behzad , Hosseini Erfan
Published: April 2024

Accurate prediction of geological formation tops is a crucial task for optimizing hydrocarbon exploration and production activities. This research investigates and conducts a comprehensive comparative analysis of several advanced machine learning approaches tailored for the critical application of geological formation top prediction within the complex Norwegian Continental Shelf (NCS) region. The study evaluates and benchmarks the performance of four prominent machine learning models: Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Random Forest ensemble method, and Multi-Layer Perceptron (MLP) neural network. To facilitate a rigorous assessment, the models are extensively evaluated across two distinct datasets - a dedicated test dataset and a blind dataset independent for validation. The evaluation criteria revolve around quantifying the models' predictive accuracy in successfully classifying multiple geological formation top types. Additionally, the study employs the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm as a baseline benchmarking technique to contextualize the relative performance of the machine learning models against a conventional clustering approach. Leveraging two model-agnostic feature importance analysis techniques - Permutation Feature Importance (PFI) and Shapley Additive exPlanations (SHAP), the investigation identifies and ranks the most influential input variables driving the predictive capabilities of the models. The comprehensive analysis unveils the MLP neural network model as the top-performing approach, achieving remarkable predictive accuracy with a perfect score of 0.99 on the blind validation dataset, surpassing the other machine learning techniques as well as the DBSCAN benchmark. However, the SVM model attains superior performance on the initial test dataset, with an accuracy of 0.99. Intriguingly, the PFI and SHAP analyses converge in consistently pinpointing depth (DEPT), revolution per minute (RPM), and Hook-load (HKLD) as the three most impactful parameters influencing model predictions across the different algorithms. These findings underscore the potential of sophisticated machine learning methodologies, particularly neural network-based models, to significantly enhance the accuracy of geological formation top prediction within the geologically complex NCS region. However, the study emphasizes the necessity for further extensive testing on larger datasets to validate the generalizability of the high performance observed. Overall, this research delivers an exhaustive comparative evaluation of state-of-the-art machine learning techniques, offering critical insights to guide the optimal selection, development, and real-world deployment of accurate and reliable predictive modeling strategies tailored for hydrocarbon exploration and reservoir characterization endeavors in the NCS.

Graphical abstract
Lactic acid production from different sources of organic solid waste: evaluation of the inoculum type and operational optimization
Authors: Villanueva-Galindo Edith , Pérez-Rangel Marisol , Moreno-Andrade Iván
Published: April 2024

This work aimed to evaluate the effect of the sources of organic solid waste on lactic acid (HLa) production. Organic fractions from cafeteria (CW), market (MW), and recycling plant (RW) wastes were used as substrates. HLa production during the self-fermentation of CW, MW, and RW, as well as during the fermentation of each substrate with anaerobic sludge (CW + sludge, MW + sludge, and RW + sludge), was evaluated in batch tests at 37 °C, initial pH of 6.5, and 150 rpm. Subsequently, the initial pH and substrate concentration of self-fermentation of CW were optimized using a central composite design. The highest HLa production was observed in the self-fermentation of CW, where several Lactobacillus species predominated in the microbial community. The higher value of HLa production using CW (20.7 g/L) was obtained at a pH of 7.29 and 115.5 gVS/L. In the optimization tests, Lactobacillus and Weissella spp. were identified as the dominant lactic acid bacteria; however, only Lactobacillus species were associated with the highest HLa production.
The agreement between bronchoalveolar lavage, bronchial wash and sputum culture: a retrospective study
Authors: Post Anne-Eva , Bathoorn Erik , Postma Douwe F. , Slebos Dirk-Jan , Akkerman Onno W.
Published: April 2024

Purpose

Bronchoalveolar lavage is commonly used in clinical practice for unresolved pneumonia. However, bronchoalveolar lavage is not suitable for all patients as it is an invasive procedure and can worsen oxygenation. The diagnostic value of bronchial wash and sputum has been debated extensively over the years. In this study, we aim to compare the diagnostic value in several pathogens of bronchoalveolar lavage and bronchial wash, and secondarily bronchoalveolar lavage and sputum.

Methods

We retrospectively included all adult patients in our hospital who underwent bronchoalveolar lavage, bronchial wash, and where sputum sampling was done between January 1st of 2018 and December 31st of 2021. The intraclass correlation coefficient was computed for the three tests.

Results

In total, 308 patients were included. We found a level of correlation of 0.819 and 0.865, respectively, between bronchoalveolar lavage and bronchial wash for two pathogens: Staphylococcus aureus and Pseudomonas aeruginosa. For Stenotrophomonas maltophilia and Aspergillus fumigatus, we found an intraclass correlation coefficient of 0.568 and 0.624, respectively. Between bronchoalveolar lavage and sputum, we found varying levels of agreement.

Conclusion

Our study shows reasonably well agreement levels between bronchoalveolar lavage and bronchial wash, suggesting that bronchial wash could potentially be an alternative to bronchoalveolar lavage.
Probleme und Potenziale der Forschungsinfrastrukturförderung in Deutschland am Beispiel des Fachinformationsdienstes Politikwissenschaft
Authors: Czolkoß-Hettwer Michael , Lein Paula , Mayr Philipp
Published: April 2024

Die Forschungsinfrastrukturförderung in Deutschland ist, wie die Forschungsförderung insgesamt, stark auf Projekte orientiert und von Drittmitteln abhängig. Diese Konstellation birgt einerseits Potenziale, zum Beispiel für technische Innovationen zur Anpassung an den digitalen Wandel. Andererseits bringt diese Ausgangslage auch Probleme mit sich, vor allem im Hinblick auf einen nachhaltigen Betrieb der Forschungsinfrastruktureinrichtungen und die großen Herausforderungen von Open Science. Der vorliegende Beitrag beleuchtet diese Konstellation anhand des Beispiels des DFG-geförderten Fachinformationsdienstes (FID) Politikwissenschaft – Pollux und fragt danach, welche Rolle Forschende für die Weiterentwicklung der Forschungsinfrastruktur spielen können.
An Approach to Distributed Systems from Orderings and Representability
Authors: Estevan Asier
Published: April 2024

In the present paper, we propose a new approach on ‘distributed systems’: the processes are represented through total orders and the communications are characterized by means of biorders. The resulting distributed systems capture situations met in various fields (such as computer science, economics and decision theory). We investigate questions associated to the numerical representability of order structures, relating concepts of economics and computing to each other. The concept of ‘quasi-finite partial orders’ is introduced as a finite family of chains with a communication between them. The representability of this kind of structure is studied, achieving a construction method for a finite (continuous) Richter–Peleg multi-utility representation.
Assessment of Plant-Growth Promoting Potential of Bacteria Isolated from Amazonian Black Pepper Roots
Authors: da Silva Anderson Moraes , da Cruz Paula Neves Patrick , Costa Sávio Souza , Silva Artur , Schneider Maria Paula Cruz , das Graças Diego Assis , da Silva Joyce Kelly do Rosário , Baraúna Rafael Azevedo
Published: April 2024

Purpose: In the Amazon, farmers use chemical fertilizers on a large scale to meet the nutritional requirements of some crops. Plant-growth promoting bacteria (PGPB) offer a sustainable alternative to enhance crop productivity. This study aimed to prospect novel PGPB from Amazonian black pepper (Piper nigrum L.) roots. Methods: Bacterial isolates were obtained from plant roots, evaluated for their biofertilizing potential, and the most promising strain was selected for genome sequencing. Taxonomic classification was based on 16 S rRNA gene sequencing. ACC deaminase activity, phosphate solubilization, and nitrogen fixation were assessed. Genome sequencing was performed using the Ion GeneStudio S5 platform. Results: The 20 isolates were affiliated to Enterobacter (7 isolates), Klebsiella (4 isolates), Kosakonia (5 isolates), Bacillus (2 isolates), and two unclassified bacteria. Seven isolates were positive for ACC deaminase activity, while four were positive for the presence of the nifH gene. Nitrogenase gene was found only in Kosakonia isolates. Ninety isolates were able to solubilize phosphate. The isolate Pn16 was the most promising and presented a genome of 6,432,985 bp, GC content of 55%, 6,465 Coding Sequences, 10 Symbiotic Islands, 28 biosynthetic gene clusters, and several genes involved in plant-growth promotion such as phoU-pstSCAB-phoBR, oqxAB, ipdC, speADEGF, nifHDK. Conclusions: We were able to isolate a bacterium with potential for biofertilization. Based on phylogeny and Average Nucleotide Identity, we propose the classification of the Pn16 isolate as Kosakonia pseudosacchari Pn16.
Urinary thymidine dimer excretion reflects personal ultraviolet radiation exposure levels
Authors: Lerche Catharina Margrethe , Frederiksen Nynne Johanne Sahl , Thorsteinsson Ida Schwarz , Køster Brian , Nybo Lars , Flouris Andreas D. , Heydenreich Jakob , Philipsen Peter Alshede , Hædersdal Merete , Wulf Hans Christian , Granborg Jonatan Riber
Published: April 2024

Exposure to ultraviolet radiation (UVR) leads to skin DNA damage, specifically in the form of cyclobutane pyrimidine dimers, with thymidine dimers being the most common. Quantifying these dimers can indicate the extent of DNA damage resulting from UVR exposure. Here, a new liquid chromatography-mass spectrometry (LC–MS) method was used to quantify thymidine dimers in the urine after a temporary increase in real-life UVR exposure. Healthy Danish volunteers (n = 27) experienced increased UVR exposure during a winter vacation. Individual exposure, assessed via personally worn electronic UVR dosimeters, revealed a mean exposure level of 32.9 standard erythema doses (SEDs) during the last week of vacation. Morning urine thymidine dimer concentrations were markedly elevated both 1 and 2 days post-vacation, and individual thymidine dimer levels correlated with UVR exposure during the last week of the vacation. The strongest correlation with erythema-weighted personal UVR exposure (Power model, r2 = 0.64, p < 0.001) was observed when both morning urine samples were combined to measure 48-h thymidine dimer excretion, whereas 24-h excretion based on a single sample provided a weaker correlation (Power model, r2 = 0.55, p < 0.001). Sex, age, and skin phototype had no significant effect on these correlations. For the first time, urinary thymidine dimer excretion was quantified by LC–MS to evaluate the effect of a temporary increase in personal UVR exposure in a real-life setting. The high sensitivity to elevated UVR exposure and correlation between urinary excretion and measured SED suggest that this approach may be used to quantify DNA damage and repair and to evaluate photoprevention strategies.

Graphical abstract
Study of Nano-Powell-Erying fluid flow past a porous stretching sheet by the effects of MHD, thermal and mass convective boundary conditions
Authors: Gundagani Murali , Babu N. V. N. , Gadially Deepa , Bhati S. M. , Ch Sanjay , Nirmala Kasturi V.
Published: April 2024

The object of this research is to examine the combined effects of mass and thermal Biot numbers on the properties of a Powell-Erying fluid flow that is two-dimensional, constant, viscous, incompressible, and non-Newtonian. In the direction of the flow is an extending sheet encircled by a porous medium. Further consideration is given to the existence of a chemical reaction, thermophoresis, Brownian motion, and velocity lapse, among other factors. Utilizing the Powell-Erying Cauchy non-Newtonian model, the viscoelastic effect is accounted for. When establishing concentration and temperature boundary conditions, thermal and mass Biot numbers are incorporated. By utilizing graphs, one can examine the impacts of a variety of engineering parameters on concentration profiles, velocity, and temperature. This is accomplished through the implementation of numerical solutions derived via the Runge–Kutta method. By utilizing graphs, one can examine the impacts of a variety of engineering parameters on concentration profiles, velocity, and temperature. This is accomplished through the implementation of numerical solutions derived via the Runge–Kutta method. Furthermore, the Nusselt number, Skin-friction, and Sherwood number coefficients are evaluated and shown in a tabular format utilizing the same parameters. In the end, the numerical outcomes obtained from this investigation are substantiated and considered to be highly consistent with the findings that were previously documented.
A Manta-Ray Hill Climbing Vision Transformer Model for Predicting Ischemic Stroke Outcome
Authors: Sarhan Amany M. , Saif Dina , Elshennawy Nada M.
Published: April 2024

An ischemic stroke attack can cause permanent damage to healthy brain tissue, leading to a permanent loss of motor or sensory function. It can also result in disability or death if not diagnosed and treated promptly. Early prediction of the outcome of the first stroke, such as disability or death, can help many patients by administering appropriate medications to save their lives. Additionally, early prediction of a recurrent stroke within 14 days of the initial stroke can contribute to prevent its recurrence. This paper first proposes a modified Manta-Ray Foraging Optimizer (MMRFO) to enhance the characteristics of the MRFO technique. This approach is based on incorporating the Hill Climbing methodology into the original MRFO in order to improve the exploitation phase, which is responsible for locating the promising zone in the search area. The proposed approach is then utilized to determine the appropriate hyperparameters of the Vision Transformer(ViT) model to predict stroke outcomes prior to its occurrence. To transform categorical data to numerical values, an ASCII encoder module is included. In the feature selection step, the Harris Hawk Optimization approach (HHO) is used to identify the most important elements that may define the stroke. A comparative study has been performed to confirm the effectiveness of the proposed methodology. The results demonstrate that the proposed technique with a Vision Transformer achieves superior results compared to state-of-the-art algorithms. The accuracy of the proposed technique was improved to 87% for the first dataset and 83% for the second, which is clearly superior to that of the other models and earlier research.
Preprocessed Spectral Clustering with Higher Connectivity for Robustness in Real-World Applications
Authors: Sadjadi Fatemeh , Torra Vicenç , Jamshidi Mina
Published: April 2024

This paper introduces a novel model for spectral clustering to solve the problem of poor connectivity among points within the same cluster as this can negatively impact the performance of spectral clustering. The proposed method leverages both sparsity and connectivity properties within each cluster to find a consensus similarity matrix. More precisely, the proposed approach considers paths of varying lengths in the graph, computing a similarity matrix for each path, and generating a cluster for each path. By combining these clusters using multi-view spectral clustering, the method produces clusters of good quality and robustness when there are outliers and noise. The extracted multiple independent views from different paths in the graph are integrated into a consensus graph. The performance of the proposed method is evaluated on various benchmark datasets and compared to state-of-the-art techniques.
Dynamic Patterns and Predominance of Respiratory Pathogens Post-COVID-19: Insights from a Two-Year Analysis
Authors: AlBahrani Salma , AlZahrani Samira Jamaan , Al-Maqati Thekra N. , Almehbash Atheer , Alshammari Anfal , Bujlai Refan , Ba Taweel Sarah , Almasabi Fares , AlAmari Abdullah , Al-Tawfiq Jaffar A.
Published: April 2024

Introduction

Respiratory tract infections (RTIs) stand out as the most frequent causes leading to visits to the emergency department and hospitalizations. This study aims to assess the types and prevalence of respiratory infections across two years following the end of the COVID-19 pandemic.

Methods

Patients presenting with an influenza-like illness (ILI) were tested using multiplex RT-PCR (QIAstat-Dx, Qiagen). The multiplexed RT- PCR test detects 21 respiratory viruses and bacteria.

Results

During the study period, PCR test was done on a total of 1,790 samples were tested, and 712 (40%) were positive for a total of 796 pathogens. The mean age (± SD) of the participants was 20.1 ± 28.4 years in 2022 and 21.9 ± 27.6 years in 2023. Among the detected pathogens, the most prevalent were Rhinovirus/Enterovirus 222 (12.4%), followed by RSV A&B (103 cases, 5.7%), and H1N1 Influenza (77 cases, 4.3%). Additionally,  Influenza A/B constituted 172 (9.6%) while parainfluenza constituted (58, 3.2%). SARS-CoV-2 was identified in 3.97% of the samples. Over the two-year period, the monthly pattern of the identified pathogens exhibited fluctuations in the prevalence. Furthermore, variations were observed in the detected pathogens across different age groups.

Conclusion

In addition to adding significant knowledge to the field of respiratory viral infections, this study emphasizes the necessity of ongoing research and surveillance for the detection and characterization of respiratory viruses, particularly those with the potential for emergence. Such studies would also require setting up a strategy for genotyping and/or sequencing of viruses.
A Neural Network Method for Inversion of Turbulence Strength
Authors: Yin Weishi , Zhang Baoyin , Meng Pinchao , Zhou Linhua , Qi Dequan
Published: April 2024

Accurate inversion of atmospheric turbulence strength is a challenging problem in modern turbulence research due to its practical significance. Inspired by transfer learning, we propose a new neural network method consisting of convolution and pooling modules for the atmospheric turbulence strength inversion problem. Its input is the intensity image of the beam and its output is the refractive index structure constant characterizing the atmospheric turbulence strength. We evaluate the inversion performance of the neural network at different beams. Meanwhile, to enhance the generalisation of the network, we mix data sets from different turbulence environments to construct new data sets. Additionally, the inverted atmospheric turbulence strength is used as a priori information to help identify turbulent targets. Experimental results demonstrate the effectiveness of our proposed method.
Unlocking the cosmos: evaluating the efficacy of augmented reality in secondary education astronomy instruction
Authors: Ferrari Enzo , Teijón Pablo Herrero , Ruiz Camilo
Published: April 2024

Augmented Reality (AR) is now being used in education across various subjects. The number of AR applications has increased with the popularity of smartphones. In this study, we explore the use of AR-based apps for teaching astronomy in the last four years of secondary education in Spain. The study includes an experimental group and a control group to show the benefits of using AR in the classroom. We conducted a pretest-posttest design, with a knowledge questionnaire given before and after the teaching period. 130 students aged 12 to 16, from a secondary school in Spain were divided into four groups, each having a control and an experimental group. The experimental group showed significant improvement in academic performance through the use of AR. This research aligns with previous studies, confirming that the use of AR makes Science, Technology, Engineering, and Mathematics (STEM) learning more engaging compared to traditional teaching methods.
Early Beringian Traditions: Functioning and Economy of the Stone Toolkit from Swan Point CZ4b, Alaska
Authors: Gauvrit Roux Eugénie , Gómez Coutouly Yan Axel , Holmes Charles E. , Hirasawa Yu
Published: April 2024

The pressure knapping technique develops circa 25,000 cal BP in Northeast Asia and excels at producing highly standardized microblades. Microblade pressure knapping spreads throughout most of Northeast Asia up to the Russian Arctic, and Alaska, in areas where the human presence was unknown. Swan Point CZ4b is the earliest uncontested evidence of human occupation of Alaska, at around 14,000 cal BP. It yields a pressure microblade component produced with the Yubetsu method, which is widespread in Northeast Asia during the Late Glacial period. Through the techno-functional analysis of 634 lithic pieces from this site, this study seeks to identify the techno-economical purposes for which the Yubetsu method was implemented. Data show that the microblade production system is related to an economy based on the planning of future needs, which is visible through blanks standardization, their overproduction, their functional versatility, and the segmentation of part of the chaîne opératoire. This expresses the efficiency and economic value of the microblade production system. The flexible use of pressure microblades identified at Swan Point CZ4b is also found in Japan, Korea, Kamchatka, and the North Baikal region, suggesting that their modes of use accompany the spread of early microblade pressure knapping over an immense territory across Beringia.
More Than an Intermediary: James Bannerman and Colonial Space-Making on the Nineteenth-Century Gold Coast
Authors: von Hesse Hermann W.
Published: April 2024

Scholars have emphasized the importance and autonomy of African intermediaries in European imperial projects. However, intermediaries have not been studied as founders of (proto) colonial administrations. Between 1840 and 1874, the inchoate British establishment on the Gold Coast was largely a project of Anglo-African merchants, rooted in their political visions of “progress.” Merchants like James Bannerman provided infrastructure, institutions, and material form to the administration and intended it as a force for development. Ultimately, the British administration exercised its hegemony through Euro-African infrastructures, spaces, and ideas. Consequently, merchants like Bannerman undermined their local networks, rulers, and dependents who opposed British domination.