bluuebunny/crossref_metadata_2025_split huggingface dataset:
High‐Efficiency Hydrogen Production From Hydrazine Borane Using Cu/MIL‐53(Al) Nanocatalysts: Synthesis, Characterization, and Performance Evaluation Nanocatalysts Supported on MIL‐53(Al)
Authors: Karataş Yaşar 
Published: January 2025

AbstractThis work highlights the novelty of investigating hydrogen production from hydrazine borane (HB) using copper (Cu). This first‐row transition metal is abundant yet underexplored as a catalyst compared to precious metals. We focus on The synthesis of Cu nanoparticles supported on MIL‐53(Al) (Cu/MIL‐53(Al)) through an impregnation‐reduction method and evaluate their performance in HB hydrolysis. Advanced characterization techniques, including X‐ray diffraction (XRD), X‐ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), and TEM‐energy‐dispersive X‐ray spectroscopy (TEM‐EDX), reveal an average Cu nanoparticle size of 3.94 ± 0.32 nm. Notably, the turnover frequency (TOF) for hydrogen production with Cu/MIL‐53(Al) at 298 K was 966 h⁻¹ (16.1 min⁻¹), representing the highest TOF reported for Cu‐based systems in HB hydrolysis. Furthermore, we calculated the activation energy (Ea#), activation enthalpy (ΔH#), and activation entropy (ΔS#) for the Cu/MIL‐53(Al) catalyst as 83.77 kJ mol⁻¹, 81.15 kJ mol⁻¹, and 48.56 J mol⁻¹ K⁻¹, respectively, using the Arrhenius and Eyring‐Polanyi equations. These findings underscore the potential of Cu/MIL‐53(Al) as an efficient and cost‐effective catalyst for hydrogen production, significantly advancing sustainable hydrogen energy technologies.
Mineralogical and Physicochemical Characterization of Natural and Heat‐Treated Kaélé Clay Pellets for Pollutant Removal from Tannery Wastewater in Cameroon
Authors: Nko'o Ebio Guillaume , Zangue Adjia Henriette , Njimou Jacques Romain , Motue Waffo Lys Carelle , Noumi Guy Bertrand 
Published: January 2025

AbstractWater pollution is a critical challenge in developing countries, including Cameroon, necessitating innovative solutions for environmental remediation. This study investigates the formulation and characterization of clay pellets derived from Kaélé clay, focusing on both natural and heat‐treated samples subjected to temperatures of 600, 800, and 1000
°C. Comprehensive mineralogical and physicochemical analyses were performed using FT‐IR, SEM ‐ EDS, TGA/DTG, XRF, and XRD techniques. Results revealed montmorillonite‐type smectite 2:1 as the predominant mineral, highlighting the potential of these clay pellets as effective adsorbents for water purification. Proposed mechanism of pollutant adsorption involves a two‐step process characterized by rapid external diffusion followed by weak interactions between pollutants and the pellet surface, influenced by pH and ionic conditions. Geochemical analysis indicated a high silica (SiO2) content of 44.01%, significant alumina (Al2O3) content of 27.77%, and lower levels of iron oxides (Fe2O3) at 4.55%, along with minimal alkaline (K2O) and alkaline earth (CaO, Na2O, MgO) contents. Rapid elimination of COD by both control and P800 pellets reached equilibrium within 30 minutes, with elimination rates of 86.09% and 98.99% for COD, respectively. This research underscores the innovative use of local clay materials for environmental applications, contributing to sustainable practices in water treatment and pollution control.
Development of Cyclic and Acyclic Fluorescent Chemosensors for Selective Detection of Ions and Biomolecules in Water
Authors: Muwal Pradeep Kumar , Saini Anoop Kumar , Choudhary Komal , Beniwal Vijay , Pani Balaram , Sirohi Siddharth , Mittal Avneesh , Kumar Rajesh , Singh Rohit 
Published: January 2025

AbstractThe intriguing effect of metal ions and biomolecules on various biological entities warrants developing selective and sensitive fluorescent chemosensors in water and other organic solvents. A review of comparable literature in related areas, including material chemistry, environmental science, and supramolecular chemistry, indicates that most of the research work is carried out in varying types of organic solvents. The existing chemosensor research explores the use of various organic solvents, including DMSO/H₂O, methanol, and DMF/HEPES systems, in photoinduced electron transfer (PET)‐based chemosensors. DMSO and DMF are strong polar solvents resulting in strong fluorescence emission. Additionally, dichlorobenzene and chlorobenzene are employed to form selective gels with urea compounds, further improving the sensor's functionality and selectivity. Also, parallel investigations, when carried out in water as a solvent, revealed a decrease in the binding/ detection ability of the guest analytes since the polar molecules form strongly solvated (hydrated) moieties, whereas the non‐polar molecules (or amphiphilic molecules) are found to form aggregations or self‐assemblies. The present review attempts to analyze and characterize water‐soluble fluorescent chemosensors (FCHs) into cyclic and acyclic entities as per their topological and structural architectures. In addition, various seminal examples of synthetic FCHs, included herein, provide an understanding of their rational designs, fundamental properties, supramolecular interactions, and emerging switchable properties in aqueous medium. Thus, the knowledge of the properties of these molecules with high affinity and selectivity would facilitate the synthesis of novel FCHs with potential future applications.
Metabolites in Serum Small Extracellular Vesicles Instead of Small Extracellular Vesicles‐depleted Serum Have Better Diagnostic Value for Cancers at Early Stage
Authors: Su Yun , Peng Zehong , Wang Yuning , Yang Shouzhi , Xu Xiaoyu , Liu Wanshan , Bao Qingui , Jiang Chen , Qian Kun , Fan Xianqun 
Published: January 2025

AbstractSerum is one of the most commonly used biofluids for biomarker exploration. Some studies examine serum directly, while others focus on specific components like small extracellular vesicles (sEVs), which are lipid‐bilayer encapsulated particles carrying a variety of molecular cargos. However, the diagnostic value of serum sEVs versus sEVs‐depleted fractions (EV‐free serum) for early cancer detection are unclear. In the study, size exclusion chromatography (SEC) is employed to separate serum from prostate cancer (PCa) suspects into sEVs‐enriched fractions (EV) and EV‐free serum. Metabolic fingerprints are obtained using ferric nanoparticle‐assisted laser ablation/ionization mass spectroscopy (FeNPALDI‐MS), revealing heterogeneity in metabolic composition. Eleven key metabolites are identified in EV and two in EV‐free serum that differentiate PCa from benign prostatic hyperplasia. The EV key metabolites showed higher diagnostic value in PCa patients with an area under the curve (AUC) of 0.76, p < 0.05 and improved diagnostic efficacy when combined with the prostate‐specific antigen (PSA, AUC = 0.85).
Simultaneous Quantitative Determination of Five Process Relevant Impurities in Menatetrenone
Authors: Agade Suraj , Bhale Nagesh A. , Pulipati Prakash , Shaik Nagoor Meeravali , Samanthula Gananadhamu , Dikundwar Amol G. 
Published: January 2025

ABSTRACTMenatetrenone, a form of vitamin K (MK‐4) is used for various pharmaceutical and agrochemical applications. Monitoring and control of process impurities is crucial in the manufacturing of pharmaceutical‐grade Menatetranone. In this article, we report a gas chromatography (GC)‐based analytical method for the detection and quantification of trace levels of five process‐related impurities in MK‐4 originating from the starting materials and reagents. A GC‐flame ionization detector (GC‐FID)‐based method is presented for simultaneous quantitative estimation of five structurally diverse compounds, some of which are conventionally analyzed by liquid chromatography. After a series of method development trials, an optimized method with a mid‐polar column dura bond‐624 (6% cyanopropyl/phenyl and 94% polydimethylsiloxane) with initial column oven temperature 150°C, detector temperature 280°C was finalized for the separation of these impurities. The developed GC‐FID‐based method was validated for specificity, the limit of detection (LOD), the limit of quantification (LOQ), linearity, range, precision, accuracy, and robustness as relevant to the International Council for Harmonization guidelines. The method was found to be highly sensitive for all the constituents with an LOD ranging from 0.05 to 0.43 pg and a limit of quantification of 0.17–1.41 pg, as estimated by the signal‐to‐noise ratios. This is the first report of an analytical method for the simultaneous quantitative determination of five process impurities of MK‐4.
Behavior of Bolted and Plated Steel Dampers Used on Steel Cross Members Applied in RCF
Authors: Bahadir Fatih , Balik Fatih Suleyman , Emir Furkan 
Published: January 2025

ABSTRACTSteel cross members (SCMs) have been placed between the frame gaps of buildings with insufficient earthquake behavior, and many methods have been developed to strengthen these structures. The application of V‐shaped SCMs into the frame is one of these methods. The biggest problem encountered in the strength of SCMs is buckling in SCMs under the effect of axial load. This buckling in steel elements significantly reduces the contribution of the strengthening application to the reinforced concrete frame (RCF) system. In this experimental study, in strengthening made with SCMs, we aimed to prevent buckling of SCMs under the pressure load. For this purpose, four RCFs with a scale of one‐fourth scale, single span, and single storey, which can reflect the features of existing buildings with insufficient earthquake behavior, have been produced. One RCF is the specimen that we did not strengthen as a reference specimen. Other reference specimen is a specimen with a built‐in support, which is strengthened with SCMs, but no metallic damper is used at the end. The other two specimens were applied at the end of the SCMs with an M5 bolt damper and a steel C plate damper. These specimens were tested under a quasistatic cyclic lateral load while a constant axial load was applied. Because of this study, the metallic dampers formed at the ends of the SCMs made a positive contribution to preventing buckling. It has also been shown that metallic dampers and SCMs increase the initial stiffness values and energy consumption capacities of the specimens.
A Survey Study on the Current Veterinary Practice and Attitudes to Anaesthesia and Analgesia for Spay Surgery in the United Kingdom
Authors: Martino‐Boulton Joanna , Antonopoulou Iliana , Pinnock Hannah , Adami Chiara 
Published: January 2025

ABSTRACTBackgroundIn the United Kingdom, spay surgery is routinely performed in dogs and cats by general practitioners. Data from a decade ago showed that, despite an increased attentiveness of veterinarians to peri‐operative pain compared to the past, analgesia could be further improved.ObjectivesTo investigate the current veterinary practice and attitude towards anaesthesia and analgesia for spay surgery in the United Kingdom.MethodsAn electronic questionnaire composed of 57 questions organised in 6 sections was designed using the Checklist for Reporting Results of Internet E‐Surveys (CHERRIES guidelines) and distributed online via a hyperlink. Participants were recruited through both personalised email invitation and publication of the hyperlink on social media. Data were analysed with descriptive statistics, analysis of means and analysis of proportions, using commercially available software.ResultsEntries from 150 participants were used for data analysis. The proportion of participants who were confident in treating pain did differ by decade of graduation, with a lower proportion of confident colleagues graduated before 2001 (6%) and from 2021 (14%), compared to those graduated in the decades 2001–2010 (43%) and 2011–2020 (37%) (p = 0.007). Colleagues reported to implement multimodal analgesia for spay procedures of cats and dogs in 43% and 44% of cases, respectively. The proportions of participants who reportedly used locoregional blocks, mostly with lidocaine, in dogs (82%), were higher than that in cats (43%) (p < 0.001). Post‐spay surgery pain was perceived by the participants as more intense in dogs than in cats (p < 0.001).ConclusionsDespite an overall good level of attentiveness of British veterinary professionals to feline and canine analgesia during and following spay surgery, this study identified as areas of improvements perception and assessment of feline pain and implementation of locoregional anaesthetic techniques, particularly in cats.
Caudate lobectomy of a massive hepatic cyst in a Cavalier King Charles Spaniel dog
Authors: Corbarieu Théo , Jossier Renaud , Claeys Stéphanie 
Published: January 2025

AbstractA 12‐year‐old, female, entire Cavalier King Charles Spaniel was presented with a 15‐month history of abdominal distension. A computed tomography revealed a very large cystic hepatic mass (24 × 18 cm). The caudate liver lobe was removed surgically. Histopathological examination of the mass revealed necrotic tissue and evidence of haemorrhage with tissue remodelling. This was consistent with a cystic lesion, but atypical cells suggest pre‐tumoral cells. The bacterial and fungal cultures were negative. Follow‐up abdominal ultrasound 1 month after surgery showed no recurrence of the cystic lesion; nonspecific splenic nodules and regional lymphadenopathy were noted. This report details the management of a large hepatic cyst in a dog.
Good Practices in Database Generation for Benchmarking Density Functional Theory
Authors: Karton Amir , de Oliveira Marcelo T. 
Published: January 2025

ABSTRACTThe hundreds of density functional theory (DFT) methods developed over the past three decades are often referred to as the “zoo” of DFT approximations. In line with this terminology, the numerous DFT benchmark studies might be considered the “safari” of DFT evaluation efforts, reflecting their abundance, diversity, and wide range of application and methodological aspects. These benchmarks have played a critical role in establishing DFT as the dominant approach in quantum chemical applications and remain essential for selecting an appropriate DFT method for specific chemical properties (e.g., reaction energy, barrier height, or noncovalent interaction energy) and systems (e.g., organic, inorganic, or organometallic). DFT benchmark studies are a vital tool for both DFT users in method selection and DFT developers in method design and parameterization. This review provides best‐practice guidance on key methodological aspects of DFT benchmarking, such as the quality of benchmark reference values, dataset size, reference geometries, basis sets, statistical analysis, and electronic availability of the benchmark data. Additionally, we present a flowchart to assist users in systematically choosing these methodological aspects, thereby enhancing the reliability and reproducibility of DFT benchmarking studies.
Experimental Validation of Virtual Torque Sensing for Wind Turbine Gearboxes Based on Strain Measurements
Authors: Bosmans Jelle , Gallas Simone , Smeets Victor , Kirchner Matteo , Geens Luk , Croes Jan , Desmet Wim 
Published: January 2025

ABSTRACTIn efforts to reduce the operation and maintenance cost of wind turbines, there is an increasing interest to monitor key turbine quantities such as the torque load on the gearbox. Monitoring the torque paves the way for the calculation of remaining useful lifetime, leading to cost reductions through improved reliability and maintenance planning. In order to avoid expensive direct torque sensors, this paper investigates the potential of virtual torque sensing, a technique based on 3 basic components: first, a set of non‐intrusive sensors installed on the gearbox. Three groups of strain gauges on the gearbox as well an angular encoder are considered in this paper. Second is a physics‐based model, capable of predicting the response of aforementioned sensors. These models are constructed with a purposeful balance between accuracy and computational cost. Model validation and updating are performed to ensure efficient and accurate prediction of the sensor output. Finally, an augmented extended Kalman filter (AEKF) is used to combine the measured response with predictions from the model to infer the gearbox input torque. Since a key factor determining the performance of the AEKF is the tuning of the AEKF covariance matrices, multiple methods are introduced to systematically tune the covariance matrices. Experimental validation results show that the virtual torque sensor can detect the load torque with a normalized mean absolute error (NMAE) between 3.41% and 7.47%, depending on the sensor set. The influence of the amount of sensors used and the tuning method are also investigated.
Wind Speed Probability Distribution Based on Adaptive Bandwidth Kernel Density Estimation Model for Wind Farm Application
Authors: Chau Tin Trung , Nguyen Thu Thi Hoai , Nguyen Linh , Do Ton Duc 
Published: January 2025

ABSTRACTWind speed variables play an important role in exploiting wind power. However, they are fluctuating and random. Therefore, understanding their characteristics and properties is necessary to improve exploitation efficiency. This research investigates various wind speed distribution models, both parametric and nonparametric, to estimate wind speed probability density (WSPD). The distribution models are implemented on various wind speed datasets with distribution characteristics of varying complexity. The assessment of goodness of fit includes statistical tests including Cramér‐von Mises (CvM), Anderson‐Darling (A‐D), Kolmogorov‐Smirnov (K‐S), and chi‐square (), along with indices correlated as mean absolute percent error (MAPE). The study highlights that the adaptive bandwidth kernel density estimation (AKDE) distribution model based on the nearest neighbor estimation (NNE) has superior goodness of fit performance. Wind turbine power curves are applied to calculate and compare expected, distribution‐based, and empirical power output. In addition, the difference between the power output estimated from the AKDE distribution and the estimate from the empirical wind speed is almost zero, so this estimated power is reliable and can be used as a reference for planning or evaluating wind farm efficiency.
Olive Sector Integrated Artificial Intelligence and Modern Technologies: Model for Palestine
Authors: Hanieh Ahmed Abu , Hasan Afif Akel 
Published: January 2025

AbstractOlive sector in Palestine suffers from serious problems starting from cultivation process passing through oil extraction process ending with final treatment. Most of the processes depend on old traditional ways away from modern technologies. The main focus of this paper is to put forward some basis and roadmap for implementing artificial intelligence and new technological components in olive sector processes. The hilly nature of Palestine prevents using heavy duty mechanical instruments for harvesting. Most of olive trees are planted on hilly terrains hence requiring the use of light weight hand-held harvesting tools. Soil moisture and nutrition elements can be determined through sensors to decide the necessity to add fertilizers. Olive fruits can be tested to check the oil content and quality before harvesting and extraction process. The final produced virgin oil can be turned to extra virgin oil by implementing further treatment processes where modern technologies are implemented. Modern technologies can also be integrated in post processes of olive sector like touristic wood works, soap manufacturing, olive fruit pickling, and other oil-based food products.
Criteria-Driven Comparison of Hydrogen, Charcoal and Liquefied Petroleum Gas as Cooking Fuels Based on a Systematic Literature Review
Authors: Sturm Lukas , Severengiz Semih , Salokhe Dhanashri Satish , Bhatia Gaurav 
Published: January 2025

AbstractGreen Hydrogen could be used as a sustainable cooking fuel, especially in countries of the global south in which cooking with carbon-based, or biomass fuels is prevalent. This paper presents a criteria based assessment of the sustainability of cooking with hydrogen in comparison to charcoal and liquefied petroleum gas. The research methodology adopts a systematic literature review to provide a comprehensive overview of the research. Based on this, a morphological analysis is conducted to display possible hydrogen cooking scenarios. A chosen hydrogen scenario is then subjected to a sustainability assessment and compared with the aforementioned conventional cooking methods. The findings of this paper reveal that while hydrogen presents itself as a potential alternative, it is currently not a more sustainable option. Despite its lower climate change impact when compared to liquefied petroleum gas and charcoal, hydrogen falls short in several other sustainability aspects, such as investment costs, marine and freshwater eutrophication or safety concerns related to the usage of the energy source.
Innovating Blended Learning Model for Professional Education in Manufacturing
Authors: Krajnik Peter , Hoier Philipp , Laakso Sampsa 
Published: January 2025

AbstractAdvancements in technology and the increasing prevalence of digitalization in industry require a new approach to professional education. The primary objective is to enhance the skills of working professionals, ensure content is relevant to industry needs, increase learner engagement, and optimize learner and instructor efficiency. To achieve these goals, a new methodology is proposed, utilizing constructive alignment, outcome-based education, and blended learning strategies. This approach incorporates asynchronous digital learning, synchronous online lectures, and interactive debriefing sessions, providing an engaging blend of self-paced learning and active, instructor-led experiences. Evaluation results show an improved course structure and a positive learning experience, despite initial implementation challenges. While not exclusively designed for sustainable manufacturing education, this approach offers innovative learning pathways and has the flexibility to integrate specific modules, such as those related to sustainability. Based on evaluation feedback and measurable learner outcomes, ongoing refinements to this model suggest a promising shift in the approach to professional education within the manufacturing sector.
Developing a Framework for Sustainable Education in a Production Engineering Study Program
Authors: Mintchev Maxim , Eingartner Valentin , Muschard Bernd , Oertwig Nicole 
Published: January 2025

AbstractGiven the current challenges faced by the world regarding climate change and the goals outlined by the United Nations in their Agenda 2030 for Sustainable Development, sustainability is increasingly gaining importance in education and industry. To be able to tackle the challenges of responsible consumption and production, societies need to prepare highly skilled and responsibly thinking engineers, who are fit for the market while also contributing actively to the transformative change towards sustainable economies and societies. The international master program Global Production Engineering (GPE) at Technische Universität Berlin aims to impart knowledge on production, engineering, and management with a major focus on sustainability. In this paper, policies of universities locally and worldwide are reviewed and lecturers of GPE are surveyed to determine which sustainability topics and approaches are integrated in their lectures and in the curriculum. From this, a framework for competence building for sustainable development in the economy is developed. The program is then reviewed and found to be teaching some of the core competencies outlined by the Education for Sustainable Development, albeit with a clear potential for improvement. To address this, corrective measures are proposed.