bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Airport Ground Operations Management on Aviation Safety Performance in Kenya
Authors: Bor Jones , Muthoni Gloria B. , Njora Stephen N 
Published: February 2025

The study sought to examine the role played by airport ground operations management on aviation safety performance in Kenya. The independent variables of the study were; aircraft apron movement control and aircraft refueling procedures whereas the dependent variable is aviation safety performance. Underpinning theory is risk management theory. Explanatory research design was used, the target population comprised of 258 airport ground operations crew working for five domestic airline companies operating from Jomo Kenyatta International Airport, Kenya. A census of all the 258 staff attached to four different departments was carried out. Structured questionnaires were used to collect data, they were administered in person and use of research assistants. Descriptive and inferential statistical analysis techniques were used for data analysis. The findings from the study revealed that aircraft apron movement control had a significant influence on aviation safety performance of the selected domestic airline companies in Kenya (β = 0.220; P=0.000). Additionally, aircraft fueling procedures was found to significantly influence the aviation safety performance Kenya (β = 0.616; P=0.000<0.05). The study concluded that failure to fully embrace airport ground operations protocol had a hand on compromised aviation safety of selected domestic airline companies in Kenya. The study recommends the need for management to uphold employee development and employee safety as a way of promoting employee performance thus steering organizational performance. These findings emphasize the critical role that effective ground handling practices play in enhancing aviation safety.
Advanced Machine Learning Approaches for Credit Card Fraud Detection in the USA: A Comprehensive Analysis
Authors: Sizan Mir Mohtasam Hossain , Chouksey Anchala , Tannier Nikhil Rao , Jobaer Md Abdullah Al , Akter Jasmin , Roy Ashutosh , Ridoy Mehedi Hasan , Sartaz M Saif , Islam Dewan Aminul 
Published: February 2025

Credit card fraud is a financial threat in America, both for financial institutions and for consumers, and it is growing in severity. Traditional fraud detection methods become less effective in countering emerging fraud trends, and for that reason, sophisticated algorithms in machine learning have to be embraced. This research project strived to develop and compare complex algorithms for fraud detection in credit cards in America. With a variety of algorithms including both unsupervised and supervised learning, this study strived towards improving fraud transaction detection rates. This study focuses on real-world credit card transaction datasets from America, offering a robust foundation for comprehending the intricacies of fraud detection in an authentic financial context. Employing actual transaction data, the study aims to replicate and model variation and nuance in fraud and consumer behavior, such that any developed machine learning algorithms will have a basis in real-life realities. For model selection, we deployed several machine learning models, notably Logistic Regression, Random Forest, and XG-Boost Classifier. In evaluating model performance, several key metrics, including Precision, Recall, and the F1-score, were taken into consideration. Random Forest Classifier performed best overall, with relatively high accuracy for fraud prediction, and average recall, with a marginally high level of F1-score. Overall, it can be noticed that Random Forest has the most balanced performance out of the three in fraud detection capabilities, which seems to be a necessity. The integration of real-time fraud prevention with machine learning models is revolutionizing financial institution transaction monitoring. ML models can analyze and process information in real-time, and thus, allow for effective and efficient real-time fraud monitoring. The future of fraud detection holds many exciting avenues for research, most prominently in deep model development. Methods in deep learning, such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs), have been successful in discovering complex structures and sequential relations in transactional information. Another promising avenue for future research is combining AI-powered identity verification with blockchain technology for fraud prevention.
Littératie et capital vidéoludique : approche systématique et textométrique d’un domaine hétéroclite
Authors: Houlmont Pierre-Yves , Dupont Bruno , Hansen Damien 
Published: February 2025

Cet article offre une analyse textométrique de la mobilisation du concept de capital vidéoludique dans la littérature scientifique anglophone. Le capital ludique est un concept qui partage des similitudes avec la littératie, mais qui s’en différencie par bien des aspects, qui n’ont pas encore fait l’objet d’assez d’attention scientifique. Dans cet article, nous avons récupéré de manière systématique des productions scientifiques incluant la notion de capital ludique ainsi que des références à Mia Consalvo, dont les travaux constituent la première théorisation opératoire du capital ludique. Ensuite, grâce à la combinaison d’une analyse par mots-clés et d’une analyse factorielle des correspondances (AFC), nous avons identifié cinq sous-ensembles thématiques clés : 1) les paramètres du capital, 2) l’apprentissage et la compréhension, 3) les études des communautés, 4) les questions d’identité et d’empowerment et 5) les moyens et signes du capital. L’étude met en évidence l’évolution de la littératie, qui dépasse actuellement les enjeux d’éducation. Par l’identification des cinq sous-ensembles, nous mettons en évidence la proximité du concept de capital vidéoludique avec le concept de littératie, mais également des domaines encore en friche pertinents pour les recherches futures en littératie vidéoludique en vue d’une éducation aux médias critique, ainsi que pour une étude plus poussée du champ de recherche lui-même.
Lengthened partial repetitions elicit similar muscular adaptations as full range of motion repetitions during resistance training in trained individuals
Authors: Wolf Milo , Androulakis Korakakis Patroklos , Piñero Alec , Mohan Adam E. , Hermann Tom , Augustin Francesca , Sapuppo Max , Lin Brian , Coleman Max , Burke Ryan , Nippard Jeff , Swinton Paul A. , Schoenfeld Brad J. 
Published: February 2025

Purpose
Resistance training using different ranges of motion may produce varying effects on musclular adaptations. The purpose of this study was to compare the effects of lengthened partial repetitions (LPs) vs. full range of motion (ROM) resistance training (RT) on muscular adaptations.

Methods
In this within-participant study, thirty healthy, resistance-trained participants had their upper extremities randomly assigned to either a lengthened partial or full ROM condition; all other training variables were equivalent between limbs. The RT intervention was an 8-week program targeting upper-body musculature. Training consisted of two training sessions per week, with four exercises per session and four sets per exercise. Muscle hypertrophy of the elbow flexors and elbow extensors was evaluated using B-mode ultrasonography at 45% and 55% of humeral length. Muscle strength-endurance was assessed using a 10-repetition-maximum test on the lat pulldown exercise, both with a partial and full ROM. Data analysis employed a Bayesian framework with inferences made from posterior distributions and the strength of evidence for the existence of a difference through Bayes factors.

Results
Both muscle thickness and unilateral lat pulldown 10-repetition-maximum improvements were similar between the two conditions. Results were consistent across outcomes with point estimates close to zero, and Bayes factors (0.16 to 0.3) generally providing “moderate” support for the null hypothesis of equal improvement across interventions.

Conclusions
Trainees seeking to maximize muscle size should likely emphasize the stretched position, either by using a full ROM or LPs during upper-body resistance training. For muscle strength-endurance, our findings suggest that LPs and full ROM elicit similar adaptations.
Metal Halide Perovskite Single Crystals toward Electroluminescent Applications
Authors: Wang Chaoqiang , Chen Shuai , Jie Jiansheng , Tian Chao , Jia Ruofei , Wu Xiaofeng , Zhang Xiaohong , Zhang Xiujuan 
Published: May 2024

AbstractMetal halide perovskite single crystals (MHP SCs) have attracted extensive attention due to their superior properties, such as higher carrier mobility, longer carrier diffusion length, and better stability than their polycrystalline counterparts. In particular, the suppression of ion migration and Auger recombination endows MHP SCs with excellent electroluminescence (EL) properties, thus holding great potential for highly efficient and stable light‐emitting devices. In this review, general overview of MHP crystal structures are begin, and highlight the merits of MHP SCs in terms of outstanding optoelectronic properties and high stability. Then, appropriate growth methods of high‐quality, thickness‐controlled MHP SCs for EL device applications are systematically summarized. Subsequently, recent advancements in developing MHP SC‐based perovskite light‐emitting diodes (PeLEDs) are discussed, and the effective strategies to further enhance the device performance are reviewed. Moreover, the potential application of MHP SCs for electrically pumped lasers is highlighted. Finally, the review is concluded with a detailed account of the current challenges and a perspective on the key approaches and opportunities on the optimization of SC growth, the improvement of device performance and the integration of SC‐based optoelectronic devices.
2D Perovskite Nanosheet‐Driven Polymeric Nanocomposites as Gate Dielectrics for Flexible Negative‐Capacitance Applications
Authors: Park Se Yeon , Jang Moonjeong , Kim Jin , Cho Sam Yeon , Bu Sang Don , Kang Saewon , Yim Soonmin , Lee Sun Sook , Yoon Dae Ho , An Ki‐Seok 
Published: May 2024

AbstractDesigning composite gate dielectrics tailored by incorporating inorganic perovskite nanofillers into a polymer matrix to develop flexible low‐voltage transistors can be challenging because homogeneous dispersion of nanomaterials in the matrix is difficult to achieve; thus, degradation of the electrically insulating properties of nanocomposite layers is often observed. In this study, nanocomposite dielectrics are presented that consist of 2D Ba5Ta4O15 nanosheets (BTO NSs) for the first time. Perovskite BTO is introduced using the Langmuir–Blodgett method to construct a precise and pinhole‐free interface for the homogeneous assembly of 2D nanosheets. Its high k value and ferroelectric properties, which arise from the perovskite structure, can be harnessed to achieve attractive polarization and remarkable electronic properties. The 2D BTO NSs can also be utilized as phase crystallization fillers to enhance the ferroelectric properties of polyvinylidene fluoride (PVDF). Additionally, the multilayer PVDF/perovskite nanosheet hybrid dielectric, which reaches an unprecedentedly high dielectric constant of 22.4, exhibits effective dielectric relaxation related to the interfacial induced ferroelectric polarization and decisive negative‐capacitance response.
Tailoring the Electronic Structures and Spectral Properties of ZnO with Irradiation Defects Generated Under Intense Electronic Excitation: A Combined Experimental and DFT Approach
Authors: Han Xinqing , Li Runhan , Pan Shangfa , Liu Yong , Niu Chengwang , Crespillo Miguel L. , Zarkadoula Eva , Liu Peng 
Published: May 2024

AbstractThe relationship between the composition of the internal defect states, spectral properties, and correlated electronic structures of wurtzite zinc oxide (ZnO) crystals under 645 MeV Xe35+ irradiation is systematically investigated, employing experimental characterizations combined with first‐principle calculations. Based on the ion irradiation‐induced thermal expansion and relaxation processes, the high concentration of vacancy/interstitial defects produced from the transient disordered phase in molten track states trigger photoelectric changes, as follows: i) the generation of internal defect states effectively reduces the intrinsic bandgap (3.25 eV → 2.66 eV); ii) a large number of defective active sites inhibits the recombination between electron–hole pairs, causing dark conductance and photoconductance to increase with increasing damage levels until optimal fluence is achieved. Based on the density functional theory (DFT) with the GGA + U (GGA = generalized gradient approximation) method, the defective models associated with the different electronic structures, density of states, formation energy, and the nature of the chemical bonding are established. The narrowing of the bandgap observed experimentally and the enhancement of carrier concentration originating from the internal electron defect states are qualitatively verified, therefore laying the foundation for designing future nanoscale photoelectronic devices and microelectronics applications.
Gas Adsorption Mechanism on 2D Materials: The Hyperpolarizability Evolution Analyzed by Nonlinear Optics
Authors: Yen Ting‐Yu , Hung Yang‐Hao , Lee Yu‐Zen , Ho Yen‐Teng , Lan Yann‐Wen , Wu Chiu‐Hsien , Hung Kuan‐Ming , Lo Kuang Yao 
Published: May 2024

AbstractWhile understanding the competitive adsorption behavior of gas sensor is important, it is yet to be unraveled. Especially for the influence of water molecules to the gas adsorbed on 2D materials. This study explores the potential of layered 2D materials as a candidate material for gas sensing, employing non‐destructive measurement, and second harmonic generation (SHG). The investigation focuses on analyzing oxygen, ammonia, and water vapor adsorbed on a WS2 surface by studying the evolutions in electric dipole and electric field. Leveraging the simplified bond hyperpolarizability model (SBHM), a foundation is established for gas sensors utilizing high‐quality 2D materials. This approach facilitates the detection of material modifications in response to environmental influences, including the inevitable water molecules. The obtained hyperpolarizability from SBHM exhibits remarkable consistency with Langmuir's adsorption model, confirming the physical adsorption in the system. In addition, the competitive effects between gases are explored by comparing experimental results with theoretical predictions based on Boltzmann distribution and density functional theory (DFT) calculations. This highlights the effectiveness of SHG and SBHM in studying gas adsorption on layered van der Waals materials.
Phospholipid‐Modified Titanium Surface‐Loaded Apoptotic Extracellular Vesicles Promote Early Angiogenesis and Improve Implant Osseointegration Through Immune Regulation
Authors: Chen Yicheng , Ning Xiaona , Zhu Simin , Xin He , Ren Xiaomin , Wang Pei , Zhang Yu , Zhang Yufan , Chen Yijing , Li Yunpeng , Liu Fuwei , Ding Feng 
Published: May 2024

AbstractTissue‐engineered extraction products, such as apoptotic extracellular vesicles (ApoEVs), significantly promote tissue regeneration, endowing them with the potential to improve osseointegration. However, there is an urgent need to determine how to effectively load these materials onto a material surface to maximize their function. Considering that all such products have a phospholipid bilayer, a phospholipid‐modified implant coating is designed that can effectively load tissue‐engineered products with a phospholipid bilayer structure. ApoEVs are effectively loaded onto the surface and the osteogenic effect improved, achieving good osseointegration. In vitro experiments show that this material improves angiogenesis by promoting macrophage M1 polarization and NO secretion in the early stages. In vivo experiments show that after implantation, it effectively improve the peri‐implant vascularization of the implant, thereby improving the new bone formation ability and osseointegration. This study provides a universal solution for loading vesicular tissue‐engineered products onto an implant surface and validates its ability to improve bone fusion using ApoEVs as an example while exploring its mechanism.
TL‐GNN: Android Malware Detection Using Transfer Learning
Authors: Raza Ali , Qaisar Zahid Hussain , Aslam Naeem , Faheem Muhammad , Ashraf Muhammad Waqar , Chaudhry Muhammad Naman 
Published: May 2024

ABSTRACTMalware growth has accelerated due to the widespread use of Android applications. Android smartphone attacks have increased due to the widespread use of these devices. While deep learning models offer high efficiency and accuracy, training them on large and complex datasets is computationally expensive. Hence, a method that effectively detects new malware variants at a low computational cost is required. A transfer learning method to detect Android malware is proposed in this research. Because of transferring known features from a source model that has been trained to a target model, the transfer learning approach reduces the need for new training data and minimizes the need for huge amounts of computational power. We performed many experiments on 1.2 million Android application samples for performance evaluation. In addition, we evaluated how well our framework performed in comparison with traditional deep learning and standard machine learning models. In comparison with state‐of‐the‐art Android malware detection methods, the proposed framework offers improved classification accuracy of 98.87%, a precision of 99.55%, recall of 97.30%, F1‐measure of 99.42%, and a quicker detection rate of 5.14 ms using the transfer learning strategy.
Bridging Nickel‐MOF and Copper Single Atoms/Clusters with H‐Substituted Graphdiyne for the Tandem Catalysis of Nitrate to Ammonia
Authors: Wang Biwen , Ma Jiahao , Yang Rong , Meng Bocheng , Yang Xiubo , Zhang Qiuyu , Zhang Bin , Zhuo Sifei 
Published: May 2024

AbstractInterfacial engineering of synergistic catalysts is one of the keys to achieving multiple proton‐coupled electron transfer processes in nitrate‐to‐ammonia conversion. Herein, by joining ultrathin nickel‐based metal–organic framework (denoted Ni‐MOF) nanosheets with few‐layered hydrogen‐substituted graphdiyne‐supported copper single atoms and clusters (denoted HsGDY@Cu), a tandem catalyst of Ni‐MOFs@HsGDY@Cu with dual‐active interfaces was developed for the concerted catalysis of nitrate‐to‐ammonia. In such a system, the sandwiched HsGDY layer could serve as a bridge to connect the coordinated unsaturated Ni2+ sites with Cu single atoms/clusters in a limited range of 0 to 3.6 nm. From Ni2+ to Cu, via the hydrogen spillover process, the hydrogen radicals (H⋅) generated at the unsaturated Ni2+ sites could migrate across HsGDY to the Cu sites to participate in the transformation of *HNO3 to NH3. From Cu to Ni2+, bypassing the higher reaction energy for *HNO3 formation on the Ni2+ sites, the NO2− detached from the Cu sites could diffuse onto the unsaturated Ni2+ sites to form NH3 as well. The combined results make this hybrid a tandem catalyst with dual active sites for the catalysis of nitrate‐to‐ammonia conversion with improved Faradaic efficiency at lower overpotentials.
Enantioselektive Dearomatisierung von Pyridiniumsalzen durch kupferkatalysierte C4‐selektive Addition von Siliciumnukleophilen
Authors: Xiao Yao , Zhao Zhi‐Yuan , Kemper Sebastian , Irran Elisabeth , Oestreich Martin 
Published: May 2024

AbstractEs wird über eine kupferkatalysierte C4‐selektive Addition von Siliciumnukleophilen (ausgehend von einem Si−B‐Reagenz) an prochirale Pyridiniumtriflate berichtet. Die Dearomatisierung verläuft unter Verwendung von Cu(CH3CN)4PF6 als Präkatalysator und (R,R)‐Ph‐BPE (1,2‐Bis[(2R,5R)‐2,5‐diphenylphospholan‐1‐yl]ethan) als chiraler Ligand mit hervorragender Enantioselektivität. Eine Carbonylgruppe an C3 ist dafür erforderlich, vermutlich in der Rolle einer schwachen Donorgruppe, die den nukleophilen Angriff präorganisiert und in Richtung C4 lenkt. Die sich ergebenden 4‐silylierten 1,4‐Dihydropyridine können anschließend in funktionalisierte Piperidinderivate überführt werden.
Indium Tin Oxide Induced Internal Positive Feedback and Indium Ion Transport in Perovskite Solar Cells
Authors: Zhan Changling , Luo Chao , Gao Feng , Wang Xianjin , Li Yang , Zhao Qing 
Published: May 2024

AbstractStability is the most pressing challenge hindering the commercialization of perovskite solar cells (PSCs), and previous efforts focused more on enhancing the resistance of PSCs to external stimulus. Here, we found that the indium tin oxide (ITO) will deteriorate the photovoltaic performance of PSCs through positive feedback cycles. Specifically, the perovskite degradation products will cross the electron transport layer to chemically etch the electrode ITO to generate In3+, which will migrate upwards into the perovskite film. Then, the reaction that corrodes ITO consumes the decomposition products of perovskite and shifts the balance of the perovskite decomposition reaction, further promoting the degradation and thus falling into a positive feedback cycle. Moreover, the In3+ in the perovskite film was found to accumulate at the upper surface, which would lead to n‐type doping of perovskite film to form the energy barrier for interface carrier extraction. Subsequently, the chelating molecule ethylenediaminetetraacetic acid disodium salt (EDTA‐2Na) was introduced onto ITO to firmly chelate the In3+ and prevent it from migrating upward, thus breaking this internal positive feedback cycle and significantly enhancing the efficiency and stability of PSCs. This work provides new perspectives for understanding the mechanism of photovoltaic performance loss and ionic transport in PSCs.
Sea turtle strandings in the temperate Southwest Atlantic: Analysis of drivers and potential causes
Authors: Vassallo Martina , Álvarez Cecilia K. , Rodríguez‐Heredia Sergio , Rosenthal Alan F. , Albareda Diego A. , Uhart Marcela M. , González Carman Victoria , Alemany Daniela 
Published: May 2024

Abstract
Marine megafauna are subject to several threats due to the increasing exploitation of marine ecosystems. Mortality is frequently evidenced by the occurrence of stranded individuals in coastal zones; however, conclusive identification of its drivers and causes is challenging.
In this study, we explore the hypothesis that bycatch in trawling is one of the anthropic drivers of sea turtle strandings in the temperate Southwest (SW) Atlantic, where green (Chelonia mydas), loggerhead (Caretta caretta) and leatherback (Dermochelys coriacea) turtles forage seasonally.
Beach survey data during March, April and May from 2014 to 2018 were used to characterize strandings and relate their spatio‐temporal distribution to physical and anthropic variables.
Loggerhead (47.4%) and leatherback turtles (49.3%) were the most common stranded species, whereas green turtles were recorded only occasionally (3.3%). Based on the size distribution, strandings reflected both juvenile and adult mortality, with variations between species. Generalized linear models showed that sea turtle strandings were influenced by winds and sea surface temperature, while there was no evidence of a relationship with fishing effort. Further studies should assess drowning due to bycatch as a cause of turtle death, since interaction with fisheries is commonly reported in the area and drowned animals may or may not wash ashore.
This study raises awareness and assesses, for the first time, the mortality of threatened sea turtle species in a poorly known region of its distribution.