bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neoliberal Agendas in English Language Education in Urban Latin America: The Case of Medellín, Colombia
Authors: Sucerquia Paula Andrea Echeverri , Rúa Cristian Andrés Medina 
Published: August 2024

Abstract
In this article we discuss the findings of a diagnostic study of (foreign and native) language use in the department of Antioquia, in the Northwest region of Colombia; we specifically focus on the findings pertaining to the largest urban area of the department, Medellín, along with its metropolis. We discuss how the current development agenda, centered around turning the city into a technological and business hub, intertwined with a bilingualism program, poses challenges to language education. In addition, we discuss how city development plans that have an effect on education are influenced by neoliberal discourses centered on ideas of economic development and competition.
Unlocking the Potential of Algae for Heavy Metal Remediation
Authors: Machado Avryl Anna , Valiaparampil Jithu George , M Lavanya 
Published: August 2024

AbstractAlgae have emerged as a promising approach for the removal of heavy metals from wastewater due to their low-cost, efficient, and eco-friendly characteristics. The unique structural and biochemical properties of algae enable them to remove heavy metals from wastewater using various mechanisms, including physical adsorption, ion exchange, complexation, precipitation, phycoremediation, and bioaccumulation. Algal modification techniques such as pre-treatment, immobilization, and genetic modification are also discussed as means of enhancing the efficiency and specificity of heavy metal removal. Additionally, the regeneration of algal biomass is presented as a sustainable solution to the issue of algal disposal.
Die Erziehungswissenschaft der Gegenwart im Spiegel ihrer Theorierezeption
Authors: Vogel Katharina 
Published: August 2024

ZusammenfassungDer Beitrag gibt einen empirischen Überblick über die Rezeption von Theorien in der Erziehungswissenschaft der Gegenwart und jüngeren Vergangenheit. Dazu werden über einen Zeitraum von zehn Jahren (2007–2016) Zeitschriftenbeiträge aus einschlägigen Fachzeitschriften voll- und halbautomatisiert analysiert, in denen Theorien explizit benannt werden. Diese Ergebnisse sollen einen Einblick in die Theorieentwicklung der Disziplin geben und dabei nicht nur prominente Theoretiker*innen und Theoriebezugsfelder, sondern auch erziehungswissenschaftliche Theorie-Rezeptionslogiken identifizieren. Dabei wird deutlich, dass die Disziplin nach wie vor nicht auf eine eigenständige Theorieproduktion zurückgreift, sondern überwiegend fremddisziplinäre Theorien rezipiert.
Erziehungswissenschaft seit 1990: Reduktion, Segmentierung, Identitätsprobleme – Vom Bedeutungsverlust einer Disziplin
Authors: Tenorth Heinz-Elmar 
Published: August 2024

ZusammenfassungDer Beitrag untersucht die Sozialgestalt der Erziehungswissenschaft seit der Vereinigung 1990, die als historische Zäsur auch deshalb gilt, weil sie eine lange Phase distanzierter Selbstbeobachtung der Disziplin markiert. Gestützt auf Indikatoren zur Infrastruktur der Disziplin im Hochschulsystem, auf ihre Stellung in der außeruniversitären Forschung sowie in der evaluativen Beobachtung und angesichts der Nachfrage nach erziehungswissenschaftlicher Expertise wird insgesamt ein Bedeutungsverlust der Disziplin konstatiert, weil die Erziehungswissenschaft sich weder akademisch mit Professoren noch im Wissenschaftssystem insgesamt als eigenständige Forschungskraft behaupten kann.
Group formation based on extraversion and prior knowledge: a randomized controlled study in higher education online
Authors: Mueller Adrienne , Konert Johannes , Röpke René , Genc Ömer , Bellhäuser Henrik 
Published: August 2024

AbstractThe study investigates how the 2×2 configuration of homogeneous and heterogeneous distributions of extraversion and prior knowledge influences group outcomes, including satisfaction, performance, and stability. Based on the standard deviation of extraversion and prior knowledge, groups were established to test experimentally, what form of grouping leads to best outcomes. The randomized controlled trial took place in the context of an online course with 355 prospective students, working in 82 groups. The two characteristics extraversion and prior knowledge were distributed algorithmically, either homogeneously or heterogeneously. Results showed no superiority of heterogeneous formation, yet there were systematic interaction effects by the experimental group formation on satisfaction and performance. Due to the increasing relevance of online groupwork, explorative results are reported and integrated. Ideas for future research on group formation as an important influencing factor are discussed. Findings supports knowledge about cooperative online learning by optimizing the selection of group members using a therefore implemented algorithm.
The Composting of Water Hyacinth: A Life Cycle Assessment Perspective
Authors: Serafini Laís Fabiana , Arrobas Margarida , Rodrigues Manuel Ângelo , Feliciano Manuel , Miguens Filomena , Oliveira Verónica , Santos Daniela , Tuesta Jose Luis Diaz De , Gonçalves Artur 
Published: August 2024

Abstract
Water hyacinth is an invasive species that causes eutrophication in lentic waters. While mechanical removal is effective, it generates hazardous waste with biological contamination risk. Composting is a safe waste treatment option, inhibiting seeds and yielding agriculturally suitable compost. Life cycle assessment evaluated the environmental impacts of six composting piles using eight different by-products (potato peel, cattle manure, wood chip, rice straw, potato leftovers, olive pomace and biochar), all formulations containing water hyacinth. The worst environmental performances were the M2 pile (water hyacinth + olive pomace + cattle manure + potato leftovers) which achieved the highest AP (47.33 kg SO2 eq.) and EP (10.56 kg PO4³− eq.), while M3 (water hyacinth + olive pomace + rice straw + potato leftovers) had the highest GWP (816.51 kg CO2 eq.) and OLD (2.99E-11 kg R11 eq.). The biological composting process contributed the most to the overall increase in the impact categories for all piles due to air emissions (CH4 and N2O). M3 and M5 (water hyacinth + wood chip) had the worst performance in fossil fuel consumption due to distances travelled from by-products and energy use in the maintenance of composting piles. Concerning packaging, Big Bags with polypropylene had a greater impact than polyethylene bags (50 kg capacity). Evaluating the potential avoidance of mineral fertilisers, M3 compost showed potential for reducing TSP fertiliser production by 46%. Overall, M4, which incorporated a mixture of water hyacinth, olive pomace, wood chips and biochar, was the most favourable option from an environmental point of view.
Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage: The Role of the Complement and Innate Immune System
Authors: Provencio Jose Javier , Inkelas Sonya , Vergouwen Mervyn D. I. 
Published: August 2024

Abstract
Specific inflammatory pathways are important in the development of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage. Understanding the specific pathways of inflammation may be critical for finding new treatments. Evidence is accumulating that innate inflammatory cells and proteins play a more important role than cells of the adaptive inflammatory system. In this work, we review the evidence from clinical and preclinical data regarding which cells of the immune system play a role in DCI with particular emphasis on the bone-marrow-derived cells monocytes and neutrophils and the brain parenchymal microglia. In addition, we will review the evidence that complement proteins, a non-cellular part of the innate immune system, play a role in the development of DCI.
Application of a multivariate approach to the study of chemometric and sensory profiles of cookies fortified with brewers’ spent grain
Authors: Baiano Antonietta , Fiore Anna , Rutigliano Mariacinzia , Gatta Barbara la 
Published: August 2024

AbstractThis work was aimed to investigate the effects of three factors on cookie quality: brewers’ spent grain (BSG) composition [65% malted barley and 35% of unmalted durum (DA) or soft (RI), or emmer (EM) wheats]; geographical origin of the cereals used in brewing (Daunia or Salento); and percentages of BSG in cookie formulation (30 or 40%). A control made of 100% Manitoba flour was produced. Statistical analyses were performed to evaluate the effects of those factors (Analysis of Variance), the possibility to distinguish the various types of cookies (Principal Component Analysis), and the relationships among variables (Pearson Correlation Analysis).The single and interactive effects of the three factors were significant for almost all variables. Cookies with 40% EM spent grains showed the highest ash, dietary fibre, and total phenolic contents but cookies with 30% DA or RI spent grains received the highest overall quality scores due to the higher intensity of their fresh baked flavour and their lower hardness and fibrousness. Based on the nutritional and sensory characteristics, cookies fortified with RI and DA were the best to consume. Although few physicochemical differences can be attributed to geographical origin, a slightly higher overall sensory score was assigned to those produced with Salento cereals. Principal Component Analysis showed a clear separation between the control made of 100% Manitoba flour and the group of fortified cookies. Among the latter, the cookies produced with RI and DA spent grains were indistinguishable from each other due to their similar quality characteristics.
Temporal forecasting by converting stochastic behaviour into a stable pattern in electric grid
Authors: Qashou Akram , Yousef Sufian , Hazzaa Firas , Aziz Kahtan 
Published: August 2024

AbstractThe malfunction variables of power stations are related to the areas of weather, physical structure, control, and load behavior. To predict temporal power failure is difficult due to their unpredictable characteristics. As high accuracy is normally required, the estimation of failures of short-term temporal prediction is highly difficult. This study presents a method for converting stochastic behavior into a stable pattern, which can subsequently be used in a short-term estimator. For this conversion, K-means clustering is employed, followed by long-short-term memory and gated recurrent unit algorithms are used to perform the short-term estimation. The environment, the operation, and the generated signal factors are all simulated using mathematical models. Weather parameters and load samples have been collected as part of a dataset. Monte-Carlo simulation using MATLAB programming has been used to conduct experimental estimation of failures. The estimated failures of the experiment are then compared with the actual system temporal failures and found to be in good match. Therefore, to address the gap in knowledge for any future power grid estimated failures, the achieved results in this paper form good basis for a testbed to estimate any grid future failures.
Evaluating machine learning models in predicting GRI drought indicators (case study: Ajabshir area)
Authors: Faramarzpour Mahtab , Saremi Ali , Khosrojerdi Amir , Babazadeh Hossain 
Published: August 2024

AbstractExamining the condition of groundwater resources and the impact of droughts is valuable for effective water resources management. Today, machine learning (ML) models are recognized as one of the useful tools in time series predictions. In this study, the groundwater condition of one of the most important aquifers in northwest Iran was investigated using MODFLOW, followed by estimating the groundwater resource index (GRI) utilizing the multivariate adaptive regression spline (MARS) and least squares support vector regression (LSSVR) for a period between 2001 and 2019. Meteorological and hydrological drought indicators along with precipitation and flow rate were used as input variables for prediction. The simulation results revealed a groundwater level decrease since the aquifer withdrawal amount is more than the recharge amount. Besides, results showed that there is a limited interaction between surface water and groundwater resources, mainly caused by the decrease in the river flow and aquifer groundwater level drop. Both ML models performed well in GRI estimation, using groundwater flow, streamflow drought index, standardized precipitation index, and runoff as input variables. The performance of the MARS model with RMSE, MAE, and NSE error evaluation criteria of 0.37, − 0.19, and 0.83, respectively, exerted slightly better results than LSSVR with RMSE, MAE, and NSE of 0.48, − 0.06, and 0.80, respectively. The findings reveal the appropriate performance of both models in forecasting drought indicators, highlighting the necessity of using ML models in hydrology and drought prediction problems.
Analyzing digital propaganda and conflict rhetoric: a study on Russia’s bot-driven campaigns and counter-narratives during the Ukraine crisis
Authors: Marigliano Rebecca , Ng Lynnette Hui Xian , Carley Kathleen M. 
Published: August 2024

Abstract
The dissemination of disinformation has become a formidable weapon, with nation-states exploiting social media platforms to engineer narratives favorable to their geopolitical interests. This study delved into Russia’s orchestrated disinformation campaign, in three times periods of the 2022 Russian-Ukraine War: its incursion, its midpoint and the Ukrainian Kherson counteroffensive. This period is marked by a sophisticated blend of bot-driven strategies to mold online discourse. Utilizing a dataset derived from Twitter, the research examines how Russia leveraged automated agents to advance its political narrative, shedding light on the global implications of such digital warfare and the swift emergence of counter-narratives to thwart the disinformation campaign. This paper introduces a methodological framework that adopts a multiple-analysis model approach, initially harnessing unsupervised learning techniques, with TweetBERT for topic modeling, to dissect disinformation dissemination within the dataset. Utilizing Moral Foundation Theory and the BEND Framework, this paper dissects social-cyber interactions in maneuver warfare, thereby understanding the evolution of bot tactics employed by Russia and its counterparts within the Russian-Ukraine crisis. The findings highlight the instrumental role of bots in amplifying political narratives and manipulating public opinion, with distinct strategies in narrative and community maneuvers identified through the BEND framework. Moral Foundation Theory reveals how moral justifications were embedded in these narratives, showcasing the complexity of digital propaganda and its impact on public perception and geopolitical dynamics. The study shows how pro-Russian bots were used to foster a narrative of protection and necessity, thereby seeking to legitimize Russia’s actions in Ukraine whilst degrading both NATO and Ukraine’s actions. Simultaneously, the study explores the resilient counter-narratives of pro-Ukraine forces, revealing their strategic use of social media platforms to counteract Russian disinformation, foster global solidarity, and uphold democratic narratives. These efforts highlight the emerging role of social media as a digital battleground for narrative supremacy, where both sides leverage information warfare tactics to sway public opinion.
Purification and immobilization of β-glucosidase using surface modified mesoporous silica Santa Barbara Amorphous 15 for eco-friendly preparation of sagittatoside A
Authors: Yang Ya-Ya , Jing Shun-Li , Shao Jia-Li , Chen Ji-Xuan , Zhang Wei-Feng , Wan Si-Yuan , Shen Yu-Ping , Yang Huan , Yu Wei 
Published: August 2024

AbstractFunctionalized mesoporous materials have become a promising carrier for enzyme immobilization. In this study, Santa Barbara Amorphous 15 (SBA-15) was modified by N-aminoethyl-γ-aminopropyl trimethoxy (R). R-SBA-15 was employed to purify and immobilize recombinant β-glucosidase from Terrabacter ginsenosidimutans (BgpA) in one step for the first time. Optimum pH of the constructed R-SBA-15@BgpA were 7.0, and it has 20 ℃ higher optimal temperature than free enzyme. Relative activity of R-SBA-15@BgpA still retained > 70% at 42 ℃ after 8-h incubation. The investigation on organic reagent resistance revealed that the immobilized enzyme can maintain strong stability in 15% DMSO. In leaching test and evaluation of storage stability, only trace amount of protein was detected in buffer of the immobilized enzyme after storage at 4 ℃ for 33 days, and the immobilized BgpA still maintained > 50% relative activity. It also demonstrated good reusability, with 76.1% relative activity remaining after fourteen successive enzymatic hydrolyses of epimedin A to sagittatoside A. The newly proposed strategy is an effective approach for the purification and immobilization of BgpA concurrently. In addition, R-SBA-15@BgpA was demonstrated to have high efficiency and stability in this application, suggesting its great feasibility and potential to produce bioactive compounds such as secondary glycosides or aglycones from natural products.
Graphical Abstract
Micro-scale screening of genetically modified Fusarium fujikuroi strain extends the apicidin family
Authors: Fischle Alica , Lutsch Mika , Hübner Florian , Schäker-Hübner Linda , Schürmann Lina , Hansen Finn K. , Kalinina Svetlana A. 
Published: August 2024

AbstractApicidins are a class of naturally occurring cyclic tetrapeptides produced by few strains within the Fusarium genus. These secondary metabolites have gained significant attention due to their antiprotozoal activity through HDAC inhibition, thereby highlighting their potential for the treatment of malaria. Predominantly, apicidins have been isolated from Fusarium semitectum, offering a deep insight into the biosynthetic pathway responsible for their formation. A similar biosynthetic gene cluster has also been identified in the rice pathogenic fungus F. fujikuroi, leading the discovery of three additional apicidins through genetic manipulation. Routine mass spectrometric screening of these compound-producing strains revealed another metabolite structurally related to previously studied apicidins. By optimizing culture conditions and developing an effective isolation method, we obtained a highly pure substance, whose chemical structure was fully elucidated using NMR and HRMS fragmentation. Further studies were conducted to determine cytotoxicity, antimalarial activity, and HDAC inhibitory activity of this new secondary metabolite alongside the previously known apicidins. This work not only expands the apicidin class with a new member but also provides extensive insights and comparative analysis of apicidin-like substances produced by F. fujikuroi.
Graphical Abstract
A Comprehensive Review of the Non-operative Management of Traumatic Rib Fractures
Authors: Hemati Kaveh , Gray Andrew T. , Agrawal Ashish 
Published: August 2024

Abstract
Purpose of Review
This review summarizes current literature on the non-operative management of traumatic rib fractures, including risk assessment scores, respiratory therapy, and multimodal and regional analgesia.

Recent Findings
Rib fractures are associated with significant morbidity and mortality, especially in elderly patients. Risk assessment scores, such as the Pain Inspiration Cough (PIC) score, allow for early identification and dynamic assessment of those at risk for ICU admission or increased length of stay. Incentive spirometry is both prognostic and therapeutic for patients with rib fractures, while high flow nasal cannula and non-invasive ventilation strategies lack robust evidence. Multimodal analgesia regimens have been associated with significant reductions in opioid exposure and pain scores. Epidural and regional anesthesia remain common analgesic modalities to decrease unplanned intubation and ICU admission especially in elderly patients.

Summary
Optimizing pulmonary hygiene and analgesia regimens remain the primary evidence-based goals of management for patients with rib fractures.
Imperfect discrimination, similarity, and stochastic transitivity
Authors: Caliari Daniele 
Published: August 2024

AbstractWe study the relationship between imperfect discrimination, similarity, and stochastic transitivity in generalized versions of Perturbed Utility (Fudenberg et al. in Econometrica 83(6):2371–2409, 2015) and Fechnerian models (Debreu in Econometrica 26(3):440–444, 1958). We show that these models are equivalent and that, within them, the properties of a similarity function can characterize all notions of stochastic transitivity (as Weak, Moderate, and Strong). Specifically, He and Natenzon (Am Econ Rev Insights 6(2):176–195, 2024) have recently shown that choice probabilities are moderately transitive if and only if the similarity function is a metric. We provide a counterpoint and show that unless choice probabilities are strongly transitive, the similarity function can violate the triangle inequality.
Combining Forward-Looking Expenditure Targets and Fixed OPEX-CAPEX Shares for a Future-Proof Infrastructure Regulation: the ROSS Approach in Italy
Authors: Bovera Filippo , Schiavo Luca Lo , Vailati Riccardo 
Published: August 2024

Abstract
Purpose of Review
Decarbonization of many energy sectors is led by a process of “new electrification”, which poses great challenges to achieve in parallel a timely and cost-effective development of electricity networks. It becomes thus fundamental to assess the best approach on how to successfully regulate new investments in power grids, addressing their development in the general interest of consumers.

Recent Findings
Over the last twenty years, many researchers and practitioners highlighted the bias towards capital intensive investments, induced by regulatory frameworks currently adopted, based on rate-of-return regulation for capital expenditure (CAPEX) and incentive regulation for operational expenditures (OPEX). This issue is exacerbated by the potential of digital-based solutions, that are often overlooked by system operators as they mainly entail operating costs (OPEX), often subject to incentive regulation.

Summary
This work discusses an analytical model, combining total expenditures evaluation with a forward-looking approach (business planning and output-based incentives) and a fixed opex capex share, aiming at overcoming the CAPEX-bias. This is done leveraging on the Italian recent change in infrastructure regulation, introduced by the Italian regulatory authority (ARERA), that builds on a core incentive on productive total efficiency (i.e. CAPEX + OPEX) plus a scheme of output-based rewards and penalties. In the new ROSS (Regolazione per Obiettivi di Spesa e di Servizio) approach, several elements are in place in the first stage (“ROSS base”) to likely mitigate the capital bias effect, even though a more complete approach (“ROSS integrale”), including the forward-looking dimension of planned expenditures, is still under consideration by the Italian regulator.