bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractCandida 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

AbstractThe 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

AbstractZearalenone (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

AbstractBackgroundTransitions 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.MethodsThis 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.ResultsCounterattacks 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.ConclusionTransitions 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

Abstract
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

AbstractThis 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

AbstractPermeability 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

AbstractThe 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

AbstractThe 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

AbstractAccurate 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

Abstract
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

Abstract
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

ZusammenfassungDie 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

AbstractIn 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.