bluuebunny/crossref_metadata_2025_split huggingface dataset:
Targeting Yes‐Associated Protein (YAP) in Breast Cancer: In Silico Molecular Dynamics, Luminescence‐Based In Vitro, and In Vivo Validation of Rauvolfia tetraphylla‐Derived Inhibitors
Authors: Balavaishnavi B. , Kamaraj M. , Nithya T. G. , Sathish Sruthy , Madhavan Thirumurthy , mahajan Megha , Pandiaraj Saravanan 
Published: December 2024

ABSTRACTThe study aims to elucidate the pharmacological mechanism of Rauvolfia tetraphylla against breast cancer through a comprehensive, multi‐faceted approach. This includes molecular docking, molecular dynamics, and experimental validation. Initial screening via ADME analysis and network pharmacology identified key compounds and potential targets. Protein–protein interaction (PPI) network analysis pinpointed Yes‐associated protein‐1 (YAP) as a crucial target. Molecular docking revealed that three compounds—ajmaline, reserpine, and serpentine—exhibited strong binding affinities with YAP, with scores of −6.5 to −6.7 kcal/mol. Molecular dynamics simulations were conducted to assess the stability of these interactions further. Experimental validation showed R. tetraphylla inhibited breast cancer cell proliferation, with an IC50 of 348.69 μg/mL, while demonstrating cytoprotective effects on Vero cells (IC50: 1056.23 μg/mL). Migration assays indicated an 88.5% reduction in cell migration, and increased ROS levels signaled elevated stress in cancer cells. Apoptosis was confirmed by AO/EtBr staining. In vivo validation in a DMBA‐induced mouse model confirmed significant tumor growth inhibition, supported by changes in YAP expression and histopathological analysis. These findings highlight R. tetraphylla as a promising therapeutic candidate against breast cancer, offering insights into its mechanisms and potential for future drug development and clinical applications.
Tongue Squamous Cell Carcinoma and Oral Lichen Planus: A Rare Case Report of a Pregnant Woman
Authors: Moretti David , Cucherousset Joël , Benlagha Nadia , Taïhi Ihsène 
Published: December 2024

ABSTRACTSquamous cell carcinoma (SCC) of oral mucosa is increasingly affecting younger individuals, particularly in the tongue. SCC can develop from disorders like oral lichen planus (OLP). This case highlights the first known instance of OLP and SCC in a pregnant woman, suggesting hormonal changes and HPV as possible risk factors.
Salt template synthesis of CoO@Co nanoparticles encapsulated in 3D porous nitrogen‐doped carbon for oxygen reduction reaction
Authors: Zhang Yao , Song Jing‐Ya , Hu Jun‐Die , Liu Lv‐Fei , Zhang Chun‐Mei , Li Jing‐Sha 
Published: December 2024

AbstractDeveloping high performance and cost‐effective electrocatalysts toward oxygen reduction reaction (ORR) is of critical significance for fuel cells and metal–air batteries. Herein, CoO@Co nanoparticles encapsulated in three‐dimensional (3D) porous nitrogen‐doped carbon (CoO@Co/Co‐N‐C) have been successfully derived from the cobalt–tannin framework via the NH4Cl salt template strategy. Owing to the generated NH3 and HCl gas from NH4Cl during the pyrolysis process, CoO@Co/Co‐N‐C formed a 3D porous carbon architecture with ultrahigh‐specific surface area (1052.5 m2 g−1). This hybrid catalyst exhibits comparable ORR catalytic activity, as well as superior stability to 20 wt% Pt/C in alkaline conditions. This finding offers a novel and facile strategy to synthesize 3D porous carbon as non‐precious metal electrocatalysts for energy conversion and storage applications.
How Green Innovation and Green Corporate Social Responsibility Transform Green Transformational Leadership Into Sustainable Performance? Evidence From an Emerging Economy
Authors: Le Thanh Tiep , Gia Linh Le Cat 
Published: December 2024

ABSTRACTIn light of the rapidly evolving technology nowadays, a green business model is now required for sustainability and long‐term survival, especially for small and medium‐sized enterprises (SMEs) and general businesses. This study aims to investigate how green transformational leadership and sustainable corporate performance for SMEs interact by examining the coordinating functions of green innovation and green corporate social responsibility in a developing nation. The current study followed the quantitative methodology along with a questionnaire for data collection. The survey's target sample consisted of senior and middle‐level executives from Vietnam's printing and FMCG manufacturing industries. Following the survey, 449 valid responses were gathered, and SmartPLS (version 4.1.0.6) structural equation modeling was used to analyze the collected data. This analysis contributes to the body of knowledge by using the natural resource‐based view Theory and Stakeholder Theory to provide a “three‐green‐model” that includes green transformational leadership, green innovation, and green corporate social responsibility, as well as their combined impact on sustainable corporate performance in a developing nation. The study findings confirm that green transformational leadership has a positive impact on sustainable corporate performance, both directly and indirectly, through green innovation and green corporate social responsibility, leading to better financial and environmental results. This study provides useful insights into how green leadership promotes sustainable growth, giving SMEs a method to balance between social and environmental responsibility and economic success.
CCOA‐AdaLS: Hybrid Beamforming Using Chaotic Chebyshev Aquila Optimization for mmWave Massive MIMO
Authors: R. Anandan , Rahman Abdur , S. Seenuvasamurthi , G. Vishnu Vardhan Rao 
Published: December 2024

ABSTRACTThis research aims to design hybrid analog and digital beamforming to improve the signal‐to‐noise ratio (SNR) and spectral efficiency (SE) of communication links. Considering the complexity and cost associated with fully connected multiple‐input multiple‐output (MIMO) communication models, a partially connected system model is adopted for the downlink millimeter‐wave (mmWave) communication model. The analog beamforming utilizes the adaptive search (AdaLS) algorithm to minimize interference and enhance user power, whereas digital beamforming is optimized using the proposed Chaotic Chebyshev Aquila Optimization (CCAO) algorithm. The CCAO algorithm integrates chaotic Chebyshev–based solution mapping with the conventional Aquila Optimization Algorithm to enhance exploration capability. The system model is illustrated, and the problem is formulated to maximize the signal‐to‐interference‐plus‐noise ratio (SINR) through the selection of the required signal at the receiver. The digital beamformer is designed using Lagrange's multiplier, and the analog beamformer is optimized using AdaLS. The proposed CCAO algorithm is detailed, incorporating chaotic dynamics to explore the solution space effectively. The research evaluates the performance of the proposed method against conventional approaches, showcasing improved normalized beam gain and SINR.
Hybrid Optimization Approach for Handoff Strategy–Based Spectrum Allocation in Cognitive Radio Network
Authors: Poonia Renuka , Dalal Priyanka , Singh Vijay Pal 
Published: December 2024

ABSTRACTDevice‐to‐device (D2D) transmission is essential for enhancing the functionality of fifth‐generation (5G) networks. This paper addresses the need for effective power allocation and resource management for D2D users, who operate as secondary users (SUs) alongside primary users (PUs). Ensuring that D2D operations do not disrupt PU interactions is crucial. Traditional bandwidth distribution approaches rely on complete channel state information (CSI) from the base station (BS), leading to uncertainty fin resource allocation. To get rid of these challenges, this paper proposes a novel handoff strategy based on spectrum allocation in cognitive radio networks (CRNs). The data priority–based channel allocation is carried out using proposed hybrid optimization cuttlefish updated dwarf mongoose optimization (CUDMO). It is the combination of both cuttle fish algorithm (CFA) and dwarf mongoose optimization (DMO) algorithms. This optimization considers constraints such as coverage, signal strength, distance, bandwidth and improved strategy like signal‐to‐noise ratio–channel usability (SNR‐CU). Furthermore, an improved fuzzy logic–based proactive handoff mechanism, the fuzzy‐induced modified rules for channel selection (FIMRCS), is introduced. This scheme optimally selects channels, minimizing service interruption during handoff. In the dynamic multichannel selection (DMCS) scheme, parameters like channel rank, channel transmission, and channel usability are considered as the constraints while selecting the channel. They are evaluated against a set of 27 defined rules, ensuring efficient data transmission through the chosen channels. Finally, the performance of proposed CUDMO algorithm is contrasted over state‐of‐the‐art models in terms of various constraints. The CUDMO for Device 450 generated a bandwidth of 1.175 bps, surpassing the lower bandwidth achieved by conventional strategies.
Signal Reconstruction Based on Time‐Varying Sliding Window in WSNs Using Compressed Sensing
Authors: Zeynali Alireza , Ali Tinati Mohammad 
Published: December 2024

ABSTRACTThis paper presents a new algorithm that utilizes compressed sensing (CS) for reconstruction of wireless sensor networks (WSNs) data with spatial and temporal correlation. The proposed method utilizes a time‐varying sliding window mechanism that dynamically adjusts both the window size and the number of measurements. This flexibility allows the algorithm to exploit spatio‐temporal correlations effectively, ensuring that data within the window remains sparse and thus more compressible. By dynamically varying the number of measurements, the algorithm equitably distributes the sampling rate across different time slots, adapting to changes in signal characteristics and minimizing transmission costs. Simulation results demonstrate that our proposed algorithm outperforms other CS reconstruction methods by achieving higher reconstruction precision while requiring fewer transmissions. This is achieved through a decentralized data‐window framework that maximizes the use of prior signal information, leading to improved signal recovery performance in diverse WSN scenarios.
Adaptive Clustering and Trust Aware Routing (ACTAR) for Wireless Sensor Networks in IoT Environments
Authors: Nagamani Vadala , Annapurna K. 
Published: December 2024

ABSTRACTThe Internet of Things (IoT) has emerged as a revolutionary technology, connecting a vast number of people to the internet through various devices such as smartphones, laptops, sensors, and more. An essential component of IoT, the wireless sensor network (WSN), enables automation in processes like sensing, node monitoring, and data transmission. However, the full potential of IoT is hindered by cyber threats and unreliable communication. Although several security algorithms exist, they are not suitable for energy‐constrained sensor nodes. To address this issue, this paper proposes an energy‐efficient security mechanism called adaptive clustering and trust aware routing (ACTAR) for IoT‐WSNs. ACTAR operates in three phases: adaptive and hybrid clustering (AHC), multiobjective function‐based cluster head selection (MOCH), and trust aware routing (TAR). First, AHC utilizes a nonuniform clustering mechanism to categorize the network into nearby and distant clusters. Next, the selection of cluster heads is based on four metrics: coverage, communication cost, residual energy, and node proximity. Finally, TAR calculates the trust degree of sensor nodes by evaluating their direct and indirect behavior in terms of communication interactions and energy consumption. The node with the highest trust degree is selected as the next‐hop forwarding node, followed by the route with the highest trust degree. Extensive simulations of ACTAR demonstrate its performance in terms of malicious detection rate, false‐positive rate, residual energy, and packet delivery ratio. Comparative analysis shows that ACTAR outperforms existing methods, proving its superiority.
Design and Optimization of Dielectric Resonator–Based Two‐Port Filtering Radiator With Machine Learning for Sub‐6 GHz 5G Wireless Applications
Authors: Samarah Ashraf , Bagwari Ashish 
Published: December 2024

ABSTRACTThis paper proposes the structured and investigation of multi‐port ceramic‐based aerial with filtering, high gain, and circular polarization features. The alumina ceramic is excited using a cross‐shaped microstrip line. Defected ground structure (DGS) is utilized to provide good impedance matching within the operating band. Metasurface suspension over the two‐port aerial improves the gain level by an amount of 10.2 dBi. The application of polarization diversity idea helps to improve separation between aerial ports by 25 dB. The prediction of |S11| and axial ratio using random forest and XGBoost‐built machine learning (ML) technique reduces the computational complexity. Fabricated prototype confirms that the designed antenna operates in between 2.55 and 3.45 GHz, and 3‐dB axial ratio is found in between 2.75 and 3.15 GHz. Directive far‐field attributes and suitable amount of diversity parameters confirm its applicability for sub‐6 GHz‐based 5G communication system.
Divergent Synthesis of 4‐Aminotriazoles Through Click Cycloaddition and Generation of Iodonium(III) Triazoles
Authors: Hayashi Takumi , Elboray Elghareeb E. , Sudo Hina , Takenaga Naoko , Satake Hiroyuki , Dohi Toshifumi 
Published: December 2024

AbstractThe divergent synthesis of 4‐amino‐1,2,3‐triazoles was accomplished through the Cu‐catalyzed cycloaddition of organic azides with alkynyliodonium(III) salts, followed by Cu‐catalyzed triazole‐amine coupling involving treatment with amines and amides. The in situ formation of 1,2,3‐triazole iodonium salts is crucial to this approach, and the utilization of a Cu‐catalyst facilitates cycloaddition and C−N bond formation. The synthesis of 1,2,3‐triazolyliodonium(III) salts proposed in this study offers advantages, including mild reaction conditions, a broad substrate scope, and operational simplicity, while also providing efficient access to a complex and diverse range of 4‐amino‐1,2,3‐triazole derivatives.
“Consumers’ Preferences Toward Farmed Salmon in China: Integrating Sensory and Choice Experiments”
Authors: Budhathoki Mausam , Xu Hao , Ma Zixuan , Campbell Danny , Zhang Wenbo , Li Saihong , Newton Richard , Little David 
Published: December 2024

ABSTRACTChina's growing demand for farmed salmon is apparent, with the country importing 190 thousand tonnes valued at over $1.12 billion in 2023. In response, the Chinese government allowed rainbow trout to be labelled and sold as salmon starting in 2018, bridging the gap between domestically produced trout and imported Atlantic salmon. This study aimed to explore how country‐of‐origin information influences Chinese consumers' sensory perceptions and willingness to pay (WTP) for salmon. Using a within‐subject design with two evaluation rounds (blind and informed) we combined hedonic liking where Chinese consumers rated three salmon samples (from Norway, Chile, and China) with a discrete choice experiment.
The results indicated that under the blind taste test, Chinese consumers found no significant difference in sensory preference between domestic rainbow trout and imported Atlantic salmon from Norway and Chile. However, when informed of the product origins, consumer preferences shifted in favor of Norwegian and Chilean Atlantic salmon. Furthermore, consumers' WTP for salmon was unaffected by the country of production unless provenance was disclosed, at which point the origin significantly influenced their preferences. Ecolabels, price, overall liking, education, frequency of aquatic food consumption, and prior experience with salmon were also found to impact WTP for salmon. These insights offer valuable insights for salmon producers/importers/marketers to customize their approaches in response to consumer preferences, refine product positioning, and seize upon opportunities within the competitive salmon market in China.
The GLOBOCAN 2022 cancer estimates: Data sources, methods, and a snapshot of the cancer burden worldwide
Authors: Filho Adalberto M. , Laversanne Mathieu , Ferlay Jacques , Colombet Murielle , Piñeros Marion , Znaor Ariana , Parkin Donald M. , Soerjomataram Isabelle , Bray Freddie 
Published: December 2024

AbstractThe data sources and methods used to develop global cancer incidence and mortality statistics—the GLOBOCAN estimates—for the year 2022 are documented in this article, alongside a brief overview of the global cancer burden. The estimates, made available in 185 countries or territories worldwide for 36 cancer sites by sex and age, are based on the best available local data sources, namely population‐based cancer registries (for incidence) and national vital statistics (for mortality). In males, lung cancer was the most commonly diagnosed cancer worldwide in 2022 (1.57 million new cases [95% UI: 1.56–1.58]), followed by prostate cancer (1.47 million [1.46–1.48]). With 2.30 million (2.28–2.30) new cases estimated in 2022, breast cancer was the most diagnosed cancer in females, followed by lung cancer (0.91 million [0.90–0.91 million]) and cervical cancer (0.66 million [0.66–0.67]). The most common causes of cancer death in males and females were lung cancer (1.23 million [1.22–1.24]) and breast cancer (0.67 million [0.66–0.67]), respectively.
Making covert processes explicit: A disciplinary heuristic for Reading literary text
Authors: Lampi Jodi P. , Rush Leslie S. , Holschuh Jodi Patrick , Reynolds Todd 
Published: December 2024

AbstractIn this article, we argue that the goal of reading literary text is the creation of interpretation, and we advocate for a research‐based disciplinary literacy heuristic that centers on reading and interpreting literary text. The heuristic serves as a guide for designing instruction that incorporates important instructional principles for English/Language Arts: acceptance of literary ambiguity, use of collaborative discussion, and adoption of asset‐based approaches. We unpack the heuristic and recommend instructional approaches that center student voices in the process of interpreting literary texts, supporting them to learn not only how literature works, but also how to engage in their own interpretations.
Recent Advances in Screening and Separating Active Components From Natural Products Based on High‐Speed Countercurrent Chromatography
Authors: Wang Xing‐Cui , Huang Xin‐Yi , Zhang Fu‐Xin , Muhire Jules , Di Duo‐Long , Hai Jun , Pei Dong 
Published: December 2024

ABSTRACTNatural products play a vital role in human health because people find that they can reduce the incidence of many diseases, such as cancer and cardiovascular diseases. Therefore, researchers have developed many effective techniques for screening and separating active compounds from natural products. High‐speed countercurrent chromatography is a unique unsupported liquid–liquid chromatography technology that has been widely used in the separation of natural products. In this paper, the research progress of screening and separating active components from natural products by combining high‐speed countercurrent chromatography technology with other technologies is reviewed from two aspects: pre‐column activity assay and post‐column activity assay. The purpose of this paper is to provide some theoretical support for the screening and separation of natural active compounds by high‐speed countercurrent chromatography. I hope that the contents summarized in this paper can provide more basis for the development of screening and separation of natural active compounds to realize large‐scale preparation.
Perceived Value, Environmental Regulation, and Farmers' Cultivated Land Quality Protection Practices
Authors: Ren Zhong 
Published: December 2024

ABSTRACTPromoting farmers to implement cultivated land quality protection practices is an effective strategy for combating soil degradation in cultivated land. Based on 528 survey data, perceived value and environmental regulation are hereby introduced into the model of farmers' cultivated land quality protection practical decision‐making for the first time, and the Multivariate Probit model and Tobit model are employed to examine the influence of perceived value and environmental regulation on farmers' cultivated land quality protection practices. The results show that: firstly, perceived value and environmental regulation enhance the intensity of farmers' cultivated land quality protection practices, with perceived benefits (0.048) and incentive regulation (0.052) having a more pronounced effect. Secondly, incentive regulation facilitates to improve the practice intensity of farmers with a higher perceived value level, while guiding regulation contributes to improving the practice intensity of farmers with a lower level of perceived risks. Thirdly, the practice intensity of the old generation is mainly influenced by perceived benefits (0.056) and incentive regulation (0.062), while the new generation is primarily influenced by perceived risks (0.039) and guiding regulation (0.061). Therefore, the government should consider the overall effects of perceived value and environmental regulation on farmers in promoting practices for cultivated land quality protection.
Efficiency Assessment of Mutual Fund With Risk and Negative Data: An Improved Two‐Stage Network SBM Model
Authors: Shi Xiao , Pei Zhuo , Liu Xinle 
Published: December 2024

ABSTRACTThis paper innovatively proposes an improved two‐stage network SBM model, which could handle negative data and incorporates the CVaR indicator representing risks in efficiency evaluation. The proposed approach is utilized to evaluate and analyze the overall efficiency and two subsystems' efficiencies of 29 mutual funds in China from 2018 to 2022. Empirical results demonstrate that both operational management efficiency and portfolio management efficiency significantly impact overall efficiency. Funds exhibiting excellent performance in operational management subsystem are more likely to achieve outstanding overall performance. Based on the empirical results, some policy recommendations are proposed.
A Finite Interface Element for Modeling Inclusion‐Matrix Interaction in Magneto‐Active Elastomers
Authors: Klausler Will , Kaliske Michael 
Published: December 2024

ABSTRACTMagneto‐active elastomers (MAEs) are an emerging smart composite material consisting of a compliant elastomer matrix filled with stiff, magnetizable inclusions. Meso‐scale models, which treat the matrix and inclusions as discrete, are currently formulated with the assumption of perfect bonding at the interface. We apply a model for cohesive damage at the material interface and introduce a treatment for the transmission of the magnetic field in the gap. Examples demonstrate the concept and the difference in structural response between samples treated with the conventional and presented approaches.