bluuebunny/crossref_metadata_2025_split huggingface dataset:
Human Action Recognition Network Containing Hands Based on NPoseC3D59
Authors: Li Rui , Yang Wanjin , Yang Shiqiang , Liu Xutao , Zeng Xin , Wang Jiaxiang 
Published: August 2024

Abstract

\abstract{With the intelligent development of machinery manufacturing, the importance of human-computer interaction has become more prominent, and recognizing human actions is a prerequisite for realizing the intelligence of human-computer interaction. Human limbs and subtle hand movements contain rich communication information, and combining the two in research can more accurately capture human behavior and understand human intentions. PoseC3D-based human action recognition models are favored for their excellent performance and low parameter count and can be friendly to add the key point model of the hand on top of only the body torso. Therefore, in this study, the NPoseC3D human action recognition model is constructed and a human action recognition dataset containing the hand is built for effect validation. Firstly, to improve the recognition accuracy, the ReLU activation function layer, the BN layer, and the downsampling method in the original SlowOnly backbone are adjusted to retain more and more active information, and trained on the NTU RGB+D 60 publicly available dataset for validation, and the recognition accuracy is improved. Secondly, because there is no publicly available dataset containing hands, Whole59, an action recognition dataset containing hand gestures in industrial scenarios, is labeled, and 42 hand keypoint inputs are added to the NPoseC3D model, and trained and tested on the Whole59 dataset, to obtain a human action recognition NPoseC3D59 model containing hand, and the experimental results prove the effectiveness of the proposed method in this research.
The Symmetric Relationship Between Natural Gas Consumption and sustainable Economic Growth in Saudi Arabia
Authors: Alzyadat Jumah Ahmad. 
Published: August 2024

Abstract

This paper attempts to investigate the symmetric relationship between natural gas consumption and economic growth in Saudi Arabia over the period 1990–2021 by extending the production function including capital, labor, external trade, and financial development. The study applied the autoregressive distributed lag (ARDL) technique. The result of Granger causality test indicates a causal relationship from NGC to RGDP, i.e. the results supported the growth hypothesis in KSA which is known in the literature as energy consumption-led growth hypothesis. The short- and long-run results also supported the growth hypothesis that NGC contributes to economic growth. The result also showed that the accumulation of capital, labor force, and economic openness contribute to stimulating economic growth in the KSA in the long run, while the results showed the negative impact of bank credit on economic growth in the long run. The study suggests that it is possible in the near future that KSA will be able to meet its energy needs by adopting renewable energy alternatives. However, energy policies should be implemented sufficiently to promote sustainable economic growth In line with achieving the Kingdom’s Vision 2030.
Amiloride Sensitizes Prostate Cancer Cells to the Reversible Tyrosine Kinase Inhibitor Lapatinib by Modulating ERBB3 Subcellular Localization
Authors: Jathal Maitreyee K , Mudryj Maria M , Dall'Era Marc , Ghosh Paramita M 
Published: August 2024

Abstract

Neoadjuvant therapy (NAT) has been studied in clinically localized prostate cancer (PCa) to improve the outcomes from radical prostatectomy (RP) by ‘debulking’ of high-risk PCa; however, using androgen deprivation at this point risks castration resistant PCa (CRPC) clonal proliferation with potentially profound side effects such as fatigue, loss of libido, hot flashes, loss of muscle mass, and weight gain. Our goal is to identify alternative NAT that reduce hormone sensitive PCa (HSPC) without affecting androgen receptor (AR) transcriptional activity. PCa is associated with increased expression and activation of the epidermal growth factor receptor (EGFR) family, including HER2 and ErbB3. Dimerization between these receptors is required for activation of downstream targets involved in tumor progression. The FDA-approved HER2 inhibitor lapatinib has been tested in PCa but was ineffective due to continued activation of ErbB3. We now demonstrate that this is due to ErbB3 being localized to the nucleus in HSPC and thus protected from lapatinib which affect membrane localized HER2/ErbB3 dimers. Here, we show that the well-established, well-tolerated diuretic amiloride hydrochloride dose dependently prevented ErbB3 nuclear localization via formation of plasma membrane localized HER2/ErbB3 dimers. This in turn allowed lapatinib inactivation of these dimers via inhibition of its target HER2, which dephosphorylated downstream survival and proliferation regulators AKT and ERK1/2. Amiloride combined with lapatinib significantly increased apoptosis but did not affect AR transcriptional activity. Thus, our data indicate that a combination of amiloride and lapatinib could target HSPC tumors without problems associated with androgen deprivation therapy in localized PCa.
Selection of the Compromised Operating Condition of a One-pot Multi-enzymatic Reaction Using Individually Immobilised Enzymes: Production of Lactofructose Syrup
Authors: Clavero Camila , Urrutia Paulina , Conejeros Raúl , Romero Oscar , Wilson Lorena 
Published: August 2024

Abstract

We selected a compromised operating condition (temperature and pH) in a one-pot multienzyme system by considering the stability and initial reaction rate of the catalysts in a single parameter (catalytic potential). The production of lactose-fructose syrup (LFS) was used as model of a multi-enzymatic system. The enzymes used were β-galactosidase (β-gal), extracted from Bifidobacterium bifidum, which was previously immobilised and commercially immobilised glucose isomerase (GI).
The compromised catalytic potential for both enzymes was obtained at a temperature of 50 °C and pH of 6.5, with a catalytic potential of 19,034.9 μmol g-1 for β-gal and 1,894.7 μmol g-1 for GI. Under these conditions, the initial reaction rate of β-gal was 100% and GI was 20%, whereas the half-life was 25 h and 300 h for β-gal and GI, respectively. After 20 batches (equivalent to 40 h of operation), no significant productivity losses were detected (less than 10 %). The average productivity of the first five batches was 0.111 g fructose‧h-1, whereas that of the last five batches was 0.106 g fructose‧h-1.
These results showed the applicability of the catalytic potential as a tool for selecting the operating conditions in a process where two or more enzymes work simultaneously.
Research on the Improvement of Dynamic and Steady-State Performance of Grid-Connected Inverters Based on Fuzzy Adaptive Control under Weak Grid Conditions
Authors: Yu Chang-zhou , Diao Hai-yang , Wang Qin , Liu Zi-yang , Xu Hai-zhen , Li Jia-jia 
Published: August 2024

Abstract

As the penetration rate of renewable energy generation continues to increase, the characteristics of weak grids with low short-circuit ratios (SCR) and high grid impedance at the distribution end become more pronounced. Although the performance of grid-connected inverters can be adaptively adjusted based on SCR to ensure stable operation over a wide range of SCR variations, this significantly reduces their responsiveness, making it difficult to meet grid connection requirements. To address this issue, this paper proposes a control strategy based on a fuzzy adaptive PI controller. First, a mathematical model of the grid-connected inverter is established, and the D-partition method is used to analyze the stability region of conventional PI control parameters, particularly the balance between stability and responsiveness in weak grids. On this basis, a fuzzy adaptive PI controller that combines SCR and current control error is designed, capable of autonomously adjusting control parameters according to the steady-state and dynamic characteristics of the grid. Finally, the effectiveness of this strategy is verified through a hardware-in-the-loop (HIL) simulation platform. The results show that the proposed method improves the stability and dynamic response capability of grid-connected inverters under weak grid conditions.
COHEWL: Classifying and Measuring SemanticCoherence of Short Texts with Language Models
Authors: Junior Osmar de Oliveira Braz , Fileto Renato 
Published: August 2024

Abstract

Traditional text coherence models are unable to detect incoherences caused by word misuse in single-sentence documents, as they focus on sentence ordering and semantic similarity of neighboring sentences.This work investigates methods to classify and measure semantic consistency of words in very short documents. Firstly, we fine-tuned BERT for the tasks of detecting short documents with an incoherent word, and distinguishing original documents from the ones with a word automatically changed by the BERT Masked Language Model (MLM). We also used BERT embeddings to calculate coherence measures.Then we prompted generative Large Language Models (LLMs) to classify and measure semantic coherence.The classifiers based on BERT achieved between \(80%\) and \(87.50%\) accuracy in the task of classifying semantic coherence, depending on the language. They performed even better in the task of distinguishing original documents from the ones with a word changed. However, coherence measures calculated using BERT embeddings did not discriminate well coherent documents from incoherent ones, neither original documents from their respective versions with a word automatically changed.On the other hand, LLaMA, GPT, and Gemini outperformed BERT in the task of semantic coherence classification on our corpus of short questions about data structures, in Portuguese and in English. They also generated semantic coherence measures that discriminate coherent from incoherent documents better than measures based on BERT embeddings.
Development of core outcome domains for the organizational health literacy responsiveness evaluation framework (OHLR-EF)
Authors: Aaby Anna , Heuck Iben Rask , Østergaard Liv Stubbe , Meldgaard Maiken , Iversen Peter Bindslev , Broucke Stephan Van den , Maindal Helle Terkildsen 
Published: August 2024

Abstract

Background:Organizational health literacy responsiveness is the ability of health organizations and systems to recognize and respond to health literacy needs and improve health environments to ensure equitable access to and use of information and services. However, research concerning outcome measures of organizational health literacy responsiveness interventions is scarce, making it difficult to acquire aggregated knowledge on evaluations and compare effect. This study aims to develop an evaluation framework based on core outcome domains of organizational health literacy responsiveness.Methods:First, organizational health literacy responsiveness outcomes were identified through a narrative literature review, and secondly, categorized into domains through a content mapping process. Consensus was reached on core outcome domains through a three-round Delphi process. For this, experts within organizational health literacy research and practice were invited digitally to fill out questionnaires designed to rank and further define potential core outcome domains for the evaluation framework.Results:The literature search resulted in the identification of nine publications. A total of 383 outcomes were identified from these. The content mapping resulted in their categorization into 26 proposed outcome domains. 24 experts participated in the Delphi process, which resulted in consensus on 15 core outcome domains in the final evaluation framework. The core outcome domains were categorized under the five headings: 1) Organizational change, leadership, and management, 2) Workforce responsiveness, 3) Person-centered care and user involvement, 4) Access and navigation, and 5) Partnerships and transitions.Conclusions: Theorganizational health literacy responsiveness evaluation framework (OHLR-EF)enhances the stringency of future evaluations of organizational health literacy responsiveness interventions. The core outcome domains allow interventions of any scope to be easily assessed against the complete organizational health literacy responsiveness concept and the framework facilitates comparisons between methodologically or contextually related interventions.
2,4-Dinitrophenol is toxic on a low caloric diet but extends lifespan of Drosophila melanogaster on nutrient-rich diets without an impact on metabolism
Authors: Strilbytska Olha M. , Semaniuk Uliana , Yurkevych Ihor , Glovyak Andriy , Gospodaryov Dmytro , Bayliak Maria M. , Lushchak Oleh 
Published: August 2024

Abstract

Uncouplers of mitochondrial electron transport chain, such as 2,4-dinitrophehol (DNP), can mimic calorie restriction by decreasing efficiency of adenosine triphosphate (ATP) synthesis. However, DNP is also a toxic substance, whose overdosage can be lethal. In the fruit fly, Drosophila melanogaster model, we have found that DNP in concentrations of 0.05–0.2 g/L, led to a drastic decrease in fruit fly survival on a low caloric diet (1% sucrose and 1% yeast; 1S-1Y). On the 5S-5Y diet, DNP decreased lifespan of flies reared only in concentration 0.2 g/L, whilst on the diet 15S-15Y DNP either did not significantly shortened fruit fly lifespan or extended it. The lifespan extension on the high caloric 15S-15Y diet with DNP was accompanied by lower activity of lactate dehydrogenase and a decrease in activities of mitochondrial respiratory chain complexes I, II, and V, determined by blue native electrophoresis followed by in-gel activity assays. The exposure to DNP also did not affect key glycolytic enzymes, antioxidant and related enzymes, and markers of oxidative stress, such as aconitase activity and amount protein carbonyls. Consumption of DNP-supplemented diet did not affect flies’ resistance to heat stress, though made male flies slightly more resistant to starvation compared with males reared on the control food. We also did not observe substantial changes in the contents of metabolic stores, triacylglycerols and glycogen, in the DNP-treated flies. All this suggest that a nutrient-rich diets provide effective protection against DNP, providing a mild uncoupling of the respiratory chain that allows lifespan extension without considerable changes in metabolism.
Synergistic Spectrum Sensing: MME and Energy Double Thresholding Enhanced byHybrid Whale-Chimp Algorithm
Authors: R Raghavendra L , C Manjunatha R , J SHARATH KUMAR A , M Nethravathi H 
Published: August 2024

Abstract

Spectrum sensing is necessary for cognitive radio networks to locate usable frequency bands without upsetting core users. To enhance energy detection, the adaptive double-threshold method was developed. It constantly alters higher and lower thresholds based on the SNR of cognitive nodes. We present a unique approach in this research to get the weighting coefficients required for threshold modification. We introduce the hybrid Whale-Chimp Optimization Algorithm (WCOA) for effective threshold adjustments, ensuring their stability within an appropriate range and reduced sensitivity to minor fluctuations in weighting coefficients. Through the integration of the double-threshold algorithm with a hybrid approach combining Energy and maximum-minimum Eigenvalue (MME), further optimized by the Innovative Hybrid Whale-Chimp Algorithm, our technique addresses the limitations associated with conventional double-threshold energy detection methods, particularly under conditions of low SNR. Collaborative interactions among cognitive nodes enhance their detection precision, leading to swifter spectrum sensing and heightened detection probabilities. The proposed method presents a potentially efficient approach to spectrum sensing within cognitive radio networks, all while preserving the primary users' integrity.
Unveiling Bar Structures in Galaxy Triplets: AComprehensive Study of Isolated Galaxy Triplets in theLocal Universe
Authors: Tawfeek Amira A 
Published: August 2024

Abstract

A comprehensive analysis of barred galaxiesin triplet systems, drawn from the SDSS-based catalogof isolated galaxy triplets composed of 315 triplet systems (945 galaxy members) is presented. The primaryobjective for this study is to investigate the bar fraction (fbar ) within these systems and explore its correlationwith various intrinsic and extrinsic properties of thetriplets. The final sample reveals a bar fraction of 42% with a bar fraction that significantly increases in nearby systems (with smaller redshift) characterized by highervirial mass (Mvir ), lower radial velocities (σ) amongtheir members, and larger angular separations (rp) andharmonic projected distances (rh) between the tripletmembers. Additionally, it has been noticed that the Large Scale Structure (LSS) influences the bar fraction,with fbar decreasing as the distance from the primarygalaxy (G1) to the first neighborhood increases (dNN). Furthermore, fbar decreases as tidal strength generatedby the galaxies in the LSS (QLSS )increases. These findings suggest that both the dynamical environmentand the local interactions within triplet systems significantly impact the abundance of barred structures.This study provides valuable insights into the role of environmental factors in shaping galaxy morphology, particularly in systems with complex gravitational interactions.
Different exploration strategies along the autism spectrum: Diverging effects of autism diagnosis and autism traits
Authors: Goetmaeckers Fien , Goris Judith , Wiersema Jan , Verguts Tom , Braem Senne 
Published: August 2024

Abstract

When faced with many options to choose from, humans and other agents typically need to explore the utility of new choice options. People with an autism diagnosis or elevated autism traits are thought to avoid exploring such unknown options. In a large sample (N = 588), we investigated the impact of autism diagnosis or elevated autism traits on exploration behavior during value-based decision-making in vast decision spaces. Our findings show that participants with an autism diagnosis were less likely to explore novel choice options and more likely to exploit known high-value options. Computational modeling suggests they engaged in less uncertainty-driven exploration but exhibited equal random exploration and generalization strategies. Interestingly, among non-diagnosed participants, people with elevated autism traits did not explore less. Our findings highlight important differences in exploration strategies between clinical and subclinical populations.
DIGITAL MULTI-SENSORY APPROACHES IN ENGLISH LANGUAGE LEARNING: A CASE STUDY OF MIDDLE SCHOOL STUDENTS IN CIREBON
Authors: Koniah Koniah , Sudimantara Lala Bumela , Ikawati Listiana 
Published: August 2024

The decline in the English Proficiency Index (EPI) in Indonesia raises concerns about the outdated ELT pedagogy in Indonesia. This study aims to determine a learning approach using digital learning resources with an innovative multi-sensory approach for grade 8 students by utilizing selected stories from Aesop's Fables which are curated based on the CEFR (Common European Framework of Reference for Languages) level. This study employs a differentiated learning, student-centered approach to learning and uses reading for emotions as a learning tool to facilitate critical and reflective thinking. Based on the work of Lian (2017) and Sudimantara (2021), this study used a multi-sensory load reduction strategy by utilizing nonverbal elements such as rhythm, intonation, movement, emotion, and aesthetics.The research findings show that utilizing digital multi sensory English learning is a practical and diverse method of teaching narrative texts. Innovative learning resources foster students' enthusiasm for learning and enhance their academic engagement and performance. However, the study revealed that teachers are still hesitant to adopt this new approach and continue to rely on traditional teaching methods, while students are increasingly eager to explore new and innovative ways of learning. This study emphasizes the importance of embracing innovative learning strategies to improve the quality of education in Indonesia and equip students with the skills necessary to succeed in today's interconnected world.
EXPLORING EFL STUDENT’S LITERACY PRACTICES IN THE ERA OF ONLINE LEARNING
Authors: Shofiya Arina , Sri Rahayu Nanik 
Published: August 2024

The shift of learning mode from offline to online as the effect of Pandemic Covid -19 provides more experience about literacy to EFL students. Literacy which is formerly defined as the ability to read and write, has myriad definitions including the ability to use digital media for learning. EFL students nowadays are said as digital native and are assumed as familiar with digital media. The present study intends to explore the EFL students’ digital literacy practices and the contribution of digital technology toward students’ learning. The findings show that EFL students use digital media for some purposes such as learning, working part time, seeking new information, and some others. They are familiar and able to use various types of social media, digital photographs, mobile apps, mp 4 audio, software video sharing, virtual reality, augmented reality, and podcast. The frequent uses of digital media contribute to the students’ learning by increasing their thinking capability, helping them control their emotion, and supporting their interaction with their friends. The outcome of students’ digital literacy practices emerge in various form like short stories, novel, photograph, advertisement, classroom assignment, educational video, picture, animation and some other products that support learning.
Synthesis and Characterization of Fe-Poor Olivine with Applications to the Surface of Mercury
Authors: Anzures Brendan A. , Kaaden Kathleen E. Vander , McCubbin Francis M. , Rowland Richard L. , Moore Gordon M. , Prissel Kelsey , Morris Richard V. , Klima Rachel L. , Stockstill-Cahill Karen R. , Agresti David G. 
Published: August 2024

Abstract
Results from X-ray remote sensing aboard NASA’s MErcury Surface Space ENvironment GEochemistry and Ranging (MESSENGER) spacecraft have demonstrated that Mercury has a low, but measurable, concentration of Fe on its surface. However, ultraviolet to near-infrared spectroscopic measurements of the mercurian surface do not show the 1 µm absorption band characteristic of ferromagnesian silicates. This observation is consistent across multiple Fe-bearing terranes with a range of ages, suggesting the Fe present on Mercury’s surface may not be stored within silicate phases. In order to further constrain the possible mineralogy and composition of Fe-bearing phases on Mercury, we characterized synthetic olivine with minor amounts of Fe (i.e., Fo99.62–Fo99.99), along with more Fe-rich natural olivines, using a variety of spectroscopic techniques. Our results indicate that the characteristic 1 µm absorption band is detectable in reflectance spectra of olivine at a concentration as low as 0.03 wt% FeO as well as 0.01 wt% in continuum removed data. Additionally, MESSENGER’s lack of a 1 µm absorption taking into account Mercury Dual Imaging System (MDIS)’s limited spectral resolution and Mercury Atmospheric and Surface Composition Spectrometer (MASCS)’s high signal-to-noise, suggests there is less than 0.38 wt%, and likely less than 0.01 wt%, FeO on the surface of Mercury. Because the 1 µm band is not observed in surface spectra, these results indicate that the Fe observed on the surface of Mercury is not bound in an olivine structure. Rather, we posit that Fe is present as nano-phase and macroscopic Fe-rich metal or Fe-sulfide that formed as a result of space weathering and igneous smelting processes. Looking forward to ESA/JAXA’s BepiColombo mission that has a planned Mercury orbit arrival time in December 2025, MERTIS mid-infared spectra should provide a mineralogical detection or absence of olivine where MIR spectral features are still present even in synthetic olivines with minor amounts of Fe (Fo99.99).