bluuebunny/crossref_metadata_2025 huggingface dataset:
RUL Prediction of Continuous Casting Machine Based on Deep Transfer Learning
Authors: Xu Erbao , Hua Yu , Zou Fangfang , Chen Xi
Published: December 2024

The operation and maintenance of continuous casting machines involve continuous casting rolls with varying degrees of newness, age, and maintenance history. This variability poses challenges in gathering adequate fault failure data for all continuous casting rolls, resulting in limited effectiveness of remaining useful life (RUL) prediction methods based on deep learning. This limitation arises from the insufficient availability of fault labeling data. To tackle this issue, we first construct a CNN-BiLSTM model for predicting the RUL of continuous casting rolls, utilizing available fault failure data. Subsequently, we introduce the concept of transfer learning, where the source domain consists of the old continuous casting roll dataset with ample fault failure data, while the target domain comprises the new continuous casting roll dataset with limited fault failure data. The network structure and parameters of the model are adjusted through the reciprocal exchange of data between the source domain and the target domain. This leads to the development of the TL-CNN-BiLSTM RUL prediction model, which combines transfer learning and deep learning. The efficacy of this model in predicting the RUL of continuous casting rolls with varying levels of fault failure data accumulation is subsequently demonstrated through illustrative examples.
Detailed Study of the Czernik 1 Open Star Cluster Using Gaia DR3: Detection of a Tidal tail and elongated halo
Authors: Ahmed Nasser M. , Darwish Mohamed S.
Published: December 2024

In this paper, we study Czernik 1 Open stars Cluster in more details using Gaia Data Release 3 (DR3). Czernik 1 is a poorly studied open star cluster, for which new results are found in the current study. In order to estimate the membership, we have used pyUPMASK python package, HDBSCAN algorithm. Moreover from photometric and astrometric date of Gaia DR3, all the astrophysical parameters of the cluster, the center, cluster radius, radial density distribution, color-magnitude diagrams, distance, age, and reddening of Czernik 1 are calculated. Also, the luminosity and mass functions, the total mass and the relaxation time of the cluster are estimated.
One of main result, the cluster has a compact core and extended corona which is elongated towards tangent velocity which means the cluster is affected with the tidal force of Galaxy or by shear force embedded in differential rotation. Moreover, the proper motions (µ α cosδ , µ δ), and parallaxes (ϖ) are-2.707 ± 0.251 ,-0.886 ± 0.174 and 0.263 ± 0.042 , respectively. Combine King model with pyUPMASK membership, we get 1449.4± 67.80 stars with total mass 2256.0± 59.50 M ⊙. From PARSEC stellar iscochrones fit , we get all physical parameters. Our estimates for the average cluster age and the relaxation time are 226.0± 12.30 and 143.1± 12.54 Myrs, respectively. The color excess is found to be 1.100 ± 0.040 and then the cluster distance modulus has been determined to be 12.834± 0.080 mag which is corresponding to distance 3688.1± 261.5 parsecs. Finally, The slope value of the mass function (α) of Czernik 1 is found to be 1.77 ± 0.02 which is much more less than Salpeter value.
Numerical Analysis of Hand-Handle Interaction: Evaluating the Influence of Handle Stiffness on Contact Mechanics
Authors: Harih Gregor , Plesec Vasja
Published: December 2024

The interaction between users and handheld products, particularly regarding handle stiffness, plays a critical role in determining comfort and performance. This study investigates the influence of handle material properties on user comfort and task performance in handheld tools. Through advanced numerical modelling and the finite element method, the contact mechanics of human grasping were analysed by simulating the interaction between the distal phalanx of the finger and the handle during a sawing task. The study compares the simulation results with user comfort ratings, demonstrating that stiff plastic handles induce the highest contact pressures, contributing to discomfort and fatigue. In contrast, soft deformable handles alleviate peak pressures but may compromise stability under increased loads. Medium and hard deformable handles yielded optimal comfort levels, underscoring the importance of balancing material stiffness with deformation behaviour. Experimental user analysis further confirmed significant differences in comfort ratings across handle types, indicating that user preferences are task-specific. This research highlights the necessity of integrating computational biomechanics with ergonomic design and subjective user assessments to optimize handheld tool design. The findings offer valuable insights into the material behaviour of handles and establish a framework for developing innovative designs that enhance both user comfort and tool functionality.
Influences of nano-SiO2-CH3 modified release agent on the hydrophobic and hydration properties of cement matrix
Authors: Lin Hui , Sun Xiaojie , Zhang Yufeng , Huang Bing
Published: December 2024

Research on nano-modified release agents can provide valuable guidance for enhancing the apparent quality of precast concrete. In this study, we introduce a novel hydrophobic nano-SiO2-CH3 into the release agent and investigate its effects on the hydrophobic and hydration properties of cement matrix. The results demonstrate that nano-SiO2-CH3 is uniformly dispersed in the release agent through an ultrasonic method. The viscosity of release agent increases with the addition of nano-SiO2-CH3. As the amount of nano-SiO2-CH3 increases, the contact angle significantly rises while the water absorption rate decreases, indicating that the cement matrix treated with the nano-SiO2-CH3 modified release agent exhibits excellent hydrophobic performance. This behavior can be attributed to the chemical bond between hydrophobic nano-SiO2-CH3 and the surface cement. Additionally, the mechanical strength of cement matrix's surface is enhanced by the presence of nano-SiO2-CH3. Furthermore, the introduction of nano-SiO2-CH3 improves the hydration degree of cement without generating new products. This study provides a deeper understanding of the application of nano-SiO2-CH3 in modifying release agents.
Phyllosphere antagonistic bacteria induces growth promotion and effective anthracnose control in cucumber
Authors: Mostofa Mohammad Golam
Published: December 2024

The phyllosphere, aerial parts of plants, serves as a crucial habitat for diverse microorganisms. Phyllosphere bacteria can activate protective mechanisms that help plants resist diseases. This study focuses on isolating and characterizing phyllosphere bacteria from cucurbits to evaluate their potential in controlling Colletotrichum orbiculare, a pathogen causing anthracnose in cucumbers. Among 76 bacterial isolates collected, 11 exhibited strong antagonistic effects against C. orbiculare in vitro. Morphological and 16S rRNA analyses identified these isolates as different Bacillus species, including B. vallismortis, B. velezensis, B. amyloliquefaciens, and B. subtilis. These bacteria demonstrated essential plant-growth-promoting and biocontrol traits, such as motility, biofilm formation, phosphate solubilization, nitrogen fixation, and production of indole acetic acid. Most of the bacterial strains also produced biocontrol compounds like ammonia, acetoin, siderophores, hydrogen cyanide, chitinase, protease, lipase, and cellulase. Application of these bacteria significantly enhanced cucumber growth in both non-manured and organic-manured soils, showing improvements in root and shoot length, chlorophyll content, and biomass accumulation. Additionally, bacterial treatments effectively reduced anthracnose severity, with isolates GL-10 and L-1 showing the highest disease suppression in both soil types. Colonization studies showed that phyllobacteria preferentially colonized healthy leaves over roots and diseased tissues, and were more effective in manure-amended soils. These results suggest that Bacillus phyllobacteria have strong potential as sustainable bio-stimulants and biocontrol agents, offering an effective approach to enhance cucumber growth and disease control under both fertilized and unfertilized soil conditions.
Occupational and Environmental Factors Contributing to Knee Pain in Hospital Staff: Results from a Cross-Sectional Study in Iran
Authors: Zamani Navidreza , Pouragha Hamidreza , Saraei Maryam , Kheiltash Azita , Sharifian Seyed Akbar , Pouryaghoub Gholamraza , Mehrdad Ramin
Published: December 2024

Objective
The present study aimed to investigate the risk factors associated with knee pain among staff at Baharloo Teaching hospital in Tehran, Iran. Given the high prevalence of musculoskeletal disorders and their impact on quality of life and job performance, this research focused on identifying both occupational and non-occupational risk factors contributing to knee pain.
Methods
A cross-sectional study was conducted involving 450 hospital personnel. The study collected information regarding demographic characteristics, employment history—including job type, secondary employment, duration of employment, and work shift—as well as medical history, which encompassed personal and family histories of health issues, knee pain, the presence of any musculoskeletal disorders, and smoking history. Logistic regression analysis was utilized to analyse the collected data.
Results
Of the 450 participants, 229 (51.1%) reported experiencing knee pain. The results indicated that risk factors such as age, female gender, carrying heavy loads, standing for more than four hours a day, using medication for knee pain, and a history of rheumatic and musculoskeletal disorders were associated with the incidence of knee pain. Additionally, individuals with lower job satisfaction scores were at higher risk (P < 0.05).
Conclusion
This study revealed that both occupational and non-occupational risk factors significantly influence the occurrence of knee pain among hospital staff. Identifying these factors can aid in the development of preventive strategies and improve the occupational health of hospital personnel. The findings highlight the need for greater attention to ergonomic and health-related issues in medical work environments.
Deep two-photon voltage imaging with adaptive excitation
Authors: Zhao Shitong , Hebert Eric , Gruzdeva Anna , Mahishi Deepthi , Takahashi Hazuki , Lee Sungmoo , Hao Yukun , Lin Michael , Yapici Nilay , Xu Chris
Published: December 2024

Optical imaging of neuronal voltage dynamics is invaluable to studying brain functions. However, high-speed imaging at significant depth is challenging due to the limitations of the short pixel dwell time and the maximum permissible excitation power in tissues. We report high-speed, deep voltage imaging by applying adaptive excitation, which illuminates the regions of interest only. We imaged neuronal voltage activities across two planes down to 500-630 μm depth in the awake mouse brain. Our techniques can be straightforwardly applied to typical two-photon microscopes.
Synthesis and Characterization of Thiazolidinone Derivatives by Using Novel 1,3-dibutyl-1H- benzo[d]imidazol-3-ium Tetrafluroborate Ionic Liquid
Authors: Ahmad Nadeem Ahmad Ayyub , Aher Sainath Babaji , Bhagat Pundlik Rambhau , Muskawar Prashant Narayan
Published: December 2024

We have synthesized 1,3-dibutyl-1H-benzo[d]imidazol-3-ium tetrafluoroborate [DBBim] BF4 ionic liquid to carry out the synthesis of thiazolidin-2,4-one derivatives through substituted aldehydes, p-toluidine, and thioglycolic acid in a one-pot three-component synthesis. The tetrafluoroborate anion-based ionic liquid has demonstrated noticeably higher activity in shorter reaction time compared to Br̅ based IL and catalysts in the literature. Such TSIL i.e. task-specific ionic liquid [DBBim] BF4 serves as a catalyst and solvent during the synthesis of thiazolidinone derivatives, providing a moderate to good yield. The synthesis of thiazolidinone derivatives was achieved in only 18–30 minutes with [DBBim]BF4 IL catalyst which otherwise typically requires 6–8 hours when using the standard approach. This promising activity with reduced reaction time was not lost upon subsequent runs as observed with other catalysts reported in the literature. Even, the DBBim BF4 IL was conveniently extracted from the reaction medium and reused further. The synthesized compounds were characterized by spectral analysis such as IR, 1H-NMR, 13C-NMR, GC-MS, and HRMS.
A2B adenosine receptor-triggered intracellular calcium mobilization: Cell type-dependent involvement of Gi, Gq, Gs proteins and protein kinase C
Authors: Gao Zhan-Guo , Gao Ray R. , Meyer Clayton K. , Jacobson Kenneth A.
Published: December 2024

Activation of PLCβ enzymes by Giβγ and Gαq/11 proteins is a common mechanism to trigger cytosolic Ca2+ increase. We and others reported that Gαq/11 inhibitor FR900358 (FR) can inhibit both and Gαq- and, surprisingly, Giβγ-mediated intracellular Ca2+ mobilization. Thus, the Gαi-Gβγ-PLCβ-Ca2+ signaling axis depends entirely on the presence of active Gαq, which reasonably explained FR-inhibited Giβγ-induced Ca2+ release. However, the conclusion that Giβγ signaling is controlled by Gαq derives mostly from HEK293 cells. Here we show that indeed in HEK293 cells both Gαq/11 siRNA and Gαq/11 inhibitors diminished Ca2+ increase triggered by native Gq-coupled P2Y1 receptors, or by transfected Gi-coupled A1- or Gs-coupled A2B adenosine receptors (ARs). However, in T24 bladder cancer cells, Gi inhibitor PTX, but not Gαq/11 inhibitors, FR, YM254890 (YM) or Gq/11 siRNA, inhibited Ca2+ increase triggered by native A2BAR activation. Simultaneous inactivation of Gi and Gs further suppressed A2BAR-triggered Ca2+ increase in T24 cells. The Gαq/11 inhibitor YM fully and partially inhibited endogenous P2Y1- and β2-adrenergic receptor-induced Ca2+ increase in T24 cells, respectively. PKC activator PMA partially diminished A2BAR-triggered but completely diminished β2-adrenergic receptor-triggered Ca2+ increase in T24 cells. Neither β-arrestin1 nor β-arrestin2 siRNA affected A2BAR-mediated Ca2+ increase. Unlike in T24 cells, YM inhibited native A2BAR-triggered calcium mobilization in MDA-MB-231 breast cancer cells. Thus, Gαq/11 is vital for Ca2+ increase in some cell types, but Giβγ-mediated Ca2+ signaling can be Gαq/11-dependent or independent based on cell type and receptor activated. Besides G proteins, PKC also modulates cytosolic Ca2+ increase depending on cell type and receptor.
Gravitational Collapse of Bose-Einstein condensate dark matter in Generalized Vaidya spacetime
Authors: Rudra Prabir
Published: December 2024

In this work we study the gravitational collapse procedure in generalized Vaidya spacetime with Bose-Einstein condensate dark matter density profile. We use the generalized Vaidya metric to simulate the spacetime of a big star and subsequently obtain the field equations. Then we proceed to determine the star system's mass parameter by solving the field equations. Then the gravitational collapse mechanism is investigated using the derived solutions. Investigating the nature of the singularity (if formed) as the end state of the collapse is the main goal. Dark matter in the form of Bose-Einstein condensate is expected to play a crucial role in the fate of the collapse. We see that there is a possibility of the formation of both black holes and naked singularities as the end state of the collapse depending upon the initial conditions. The junction conditions are derived with a Vaidya exterior and a Friedmann interior and some important insights are obtained. A Penrose diagram showing the causal relations between the spacetimes is generated and studied in detail.
A Primary User Activity Prediction for Cognitive Radio Using Machine Learning Algorithms with On-The-Go Training
Authors: Younis Muhammad Naveed , Naseer Mudasser , Bukhari Syed Hashim Raza , Ahmed Farooq
Published: December 2024

Wireless communication is experiencing rapid growth, but it faces a significant challenge due to the limited availability of radio frequency spectrum. Cognitive Radio (CR) technology has emerged as a solution for mitigating spectrum scarcity. CR allows for more efficient spectrum utilization by enabling devices to dynamically access available frequency channels. One of the key mechanisms of CR technology is the utilization of Licensed User or Primary User (PU) channels when they are inactive. By intelligently sensing and detecting unused spectrum, CR devices can access these channels without causing interference to the primary users. Machine learning (ML) models have been successfully integrated into CR systems to improve their performance. These models are favored for their ability to accurately predict channel availability and occupancy patterns. Traditional ML approaches typically rely on labeled data and predefined decision boundaries. However, in the context of CR, the decision boundary can shift as devices transition between indoor and outdoor environments. To address this challenge, we have developed a novel model called Support Vector Machine with On-The-Go training (SVM-OTG). This model offers flexibility by allowing the CR system to train itself whenever there is a change in the environment's decision boundary. Additionally, our model undergoes On-The-Go training whenever its predictions do not match the actual output. This adaptive capability allows the CR system to continuously adapt to the changing environment, thereby improving the accuracy of its predictions. Our work has been specifically focused on enhancing spectrum usage within the widely utilized 2.4 GHz Wi-Fi band. Recent studies have indicated that conventional 2.4 GHz Wi-Fi protocols often experience performance bottlenecks. To address this, we applied our SVM-OTG model to a 2.4 GHz Wi-Fi dataset. Through extensive experimentation, we have demonstrated that our proposed model outperforms existing algorithms in this domain, achieving a prediction accuracy of 97.25% in both fixed and dynamic environments. Compared to state-of-the-art approaches such as LSTM, RLMLP, RNN, SHLNN, and DL-Mac, our model consistently delivers superior prediction accuracy. These results underscore the effectiveness of the SVM-OTG model in optimizing spectrum utilization and improving wireless communication in the 2.4 GHz Wi-Fi band.
Metal-organic frameworks encapsulating gold nanoclusters and carbon dots for ratiometric fluorescent detection of formaldehyde in real food samples, construction materials and indoor environments
Authors: Du Man , Song Meimei , Hou Shuang , Zhang Yue , Lv Haijun , Zhao Shuchun , Du Hongxia , Guo Hongyong
Published: December 2024

In this study, a novel fluorescence sensing nanoplatform (CDs/AuNCs@ZIF-8) encapsulating carbon dots (CDs) and gold nanoclusters (AuNCs) within a zeolitic imidazolate framework-8 (ZIF-8) was developed for ratiometric detection of formaldehyde (FA) in the medium of hydroxylamine hydrochloride (NH2OH·HCl). The nanoplatform exhibited pink fluorescence due to the aggregation-induced emission (AIE) effect of AuNCs and the internal filtration effect (IFE) between AuNCs and CDs. Upon reaction between NH2OH·HCl and FA, a Schiff base formed via aldehyde-diamine condensation, releasing hydrochloric acid. The acid triggered the degradation of ZIF-8, releasing CDs and AuNCs, and thereby shifting the fluorescence to blue as the CDs disperse. The nanoplatform demonstrated high sensitivity (LOD of 0.26–2.21 µM), exceptional selectivity, and rapid response time (< 1 min) toward FA. Additionally, test strips and hydrogel films integrated with smartphones were prepared for on-site and visual detection of FA. The portable and smartphone-assisted test strips effectively detected indoor FA gas, while wearable and intelligent hydrogel films provided reliable surface measurements of FA on fruits and vegetables. Real sample analyses achieved satisfactory FA recoveries (97.81–107.64%) with relative standard deviations (RSD) from 1.86–3.81%. The innovative sensing nanoplatform served as a promising approach for FA detection in food, construction materials, and indoor air quality, offering both analytical accuracy and convenient visualization.
The association between potassium intake and diabetic microvascular complications: Insights from UK Biobank data
Authors: Li Chao , Zeng Jingjing , Huang Xufang , Li Ying , Lett Aaron M. , Wu Yucen , You Qiqi , Fu Wan , Xu Shaoyong
Published: December 2024

Background
Potassium plays an important role in glucose metabolism and blood vessel. However, there is a lack of systematic research on the intake of potassium and diabetic microvascular complications. The aim of this study was to explore whether insufficient potassium intake increases the risk of developing diabetic microvascular complications, diabetic nephropathy, diabetic retinopathy, and diabetic neuropathy using the UK Biobank database.
Methods
This study included 26,172 subjects with type 2 Diabetes Mellitus at baseline. Urinary potassium and creatinine were measured by potentiometry and photometric assay respectively. Dietary potassium intake was measured using the 24-hour dietary recall method. The occurrence of microvascular complications was determined using ICD-10 codes from cumulative hospitalization records and death records in the national death registry. Cox proportional hazards models were used to explore the relationship between urinary potassium-to-creatinine ratio, dietary potassium, and overall and individual microvascular complications, generating hazard ratios (HRs) and 95% confidence intervals (CIs).
Results
Compared with the minimum potassium-to-creatinine ratio group, the highest potassium-to-creatinine ratio group had a significantly lower risk of diabetic microvascular complications (HR, 0.700 [95% CI 0.631–0.777]; P for trend < 0.001) and diabetic nephropathy (HR, 0.536 [95% CI 0.469–0.613]; P for trend < 0.001). The group with the highest dietary potassium had a significantly lower risk of diabetic nephropathy (HR, 0.481 [95% CI 0.291–0.795], P for trend = 0.005) than the minimum dietary potassium group. The restricted cubic spline results showed a non-linear relationship between urinary potassium-to-creatinine ratio and overall microvascular complications and diabetic nephropathy, with nonlinear P values of 0.009 and < 0.001, respectively, and a generally declining trend.
Conclusions
The urinary potassium-to-creatinine ratio was significantly negatively associated with overall diabetic microvascular complications and diabetic nephropathy.
Study of aircraft icing forecasting methods and its application scenarios over Eastern China
Authors: Lu Sha , Yang Chen
Published: December 2024

In this study, an aircraft icing diagnosis and forecasting method is constructed and hindcast for 25 collected spring icing cases over Eastern China based on two commonly used aircraft icing diagnostic methods (hereinafter referred to as the IC index method and the TF empirical method respectively) and ERA5 reanalysis data as the atmospheric environmental field for icing occurrence. The spatial and temporal distribution characteristics of aircraft icing accumulation occurrence over typical cities at different latitudes in China are calculated separately, and the spatial and temporal distribution of icing accumulation areas over Xinchang, Zhejiang Province in China during one cold air activity case is simulated. Accordingly, several application scenarios of aircraft icing accumulation forecasting methods are proposed. The results indicate that among the selected icing cases, the diagnosis accuracy of the IC index method is 80%, while the TF empirical method is 92%. The effects of aircraft flight speed and dynamic warming are taken into account by TF empirical method, which has better correlation with ice water particle concentration and cloud cover in medium and low clouds. However, the predicted icing accumulation intensity predicted by TF empirical method is not accurate enough without the real flight speed of the aircraft, and there are more empty forecasts above 400-hPa. In practical applications, both the IC index method and the TF empirical method can better diagnose the icing-prone pressure level and the icing-prone time period, and can effectively forecast the distributions of high pressure levels icing accumulation intensity at a certain station.
PVRE: Privacy-preserving and Verifiable Reputation Evaluation Scheme for VANETs
Authors: Chen Chang , Wu Zhen , Yang Hui , Cheng Hongyuan
Published: December 2024

In order to enhance road safety and traffic efficiency, vehicles disseminate road condition information through Vehicular Ad Hoc Networks (VANETs). However, the authenticity and reliability of this information are highly dependent on the credibility of the source vehicles. Although existing reputation evaluation systems can mitigate malicious activities and improve the trustworthiness of messages to some extent, they often overlook the strict verification of the authenticity of feedback results. Furthermore, many reputation management schemes rely on third-party entities to update the reputations of vehicles, which may be biased due to their own interests. To address these issues, this paper proposes a privacy-preserving and verifiable reputation scheme (PVRE) for VANETs. The proposed scheme utilizes Roadside Units (RSUs) to aggregate feedback from vehicles and employs smart contracts with automatic execution and tamper-proof features to ensure data privacy and security. Vehicles participating in the evaluation process can verify the accuracy of feedback using information broadcasted by a trusted authority (TA). Simulation results and security analysis demonstrate that PVRE can effectively verify the authenticity of feedback results while providing privacy protection for vehicle feedback, all within an acceptable range of computational and communication overhead.
Pd Catalysts Supported on γ-Al2O3 Immobilized with Ionic Liquids: An Efficient and Recyclable System for C-C Bond Formation
Authors: Wang Ya-Jie , Li Guo-Hua , Wang Xu , Sun Hong-Xin
Published: December 2024

A novel γ-Al2O3/IL-Pd catalyst has been designed and synthesized, featuring the highly dispersed deposition of active palladium nanoparticles on the surface of porous γ-Al2O3, which enhances catalytic performance and recyclability. The incorporation of ionic liquids is critical to the catalyst's design, as it facilitates the complete dispersion of active metals through chelation, effectively preventing the formation of palladium black and addressing catalyst deactivation. The interaction between the ionic liquid and the support, likely through specific coordination chemistries, significantly enhances the recovery and reuse capabilities of the catalyst by preventing the leaching and sintering of the palladium nanoparticles. This approach not only resolves the agglomeration issue inherent to γ-Al2O3 but also optimizes the catalyst's performance further. In the Suzuki-Miyaura coupling reaction, the new catalyst demonstrates remarkable catalytic activity, achieving a yield of tetramethoxybiphenyl of up to 99% within a remarkably short reaction time of just 30 minutes, without the need for inert gas protection. Notably, after ten consecutive cycles, the catalyst's performance remained at 94%, outperforming many existing catalysts and confirming its exceptional stability and recyclability. Given its high efficiency, stability, and reusability, this catalyst is positioned to serve as a high-performance multifunctional catalytic platform for a range of significant organic synthesis reactions.
YOLOv8-Based Fracture Detection System
Authors: Shaban Waleed , El-Behaidy Wessam , badawy Wael
Published: December 2024

Emergency departments in hospitals regularly contend with a substantial influx of patients suffering from bone fractures, with pediatric wrist trauma fractures representing a notable portion of these cases. Preceding surgical interventions, pediatric surgeons must gather information about the fracture's cause and analyze the fracture's condition through the interpretation of X-ray images. This process typically requires a blend of skills from radiologists and surgeons, involving extensive training. The rise of deep learning in the field of computer vision has highlighted the development of network models for fracture detection as a crucial area of research. This paper is centered on the utilization of the YOLOv8 algorithm to train models using the GRAZPEDWRI-DX bone fracture dataset after pre-processing with the Contrast Limited Adaptive Histogram Equalization (CLAHE) method, which contains 6,091 pediatric patients X-ray images suffering from wrist trauma. The principal objective is to enhance the detection of fractures in these cases. The results of rigorous experimentation illuminate the merits of various YOLOv8 algorithm models, notably emphasizing the superiority of the YOLOv8m model with a 1024-pixel image size, which achieves an impressive mean average precision (mAP 50) of 0.743.
Fabrication of Self-Assembled Cu Nanochains for Water-Based Lubrication Systems
Authors: Hua Keying , Guo Diange , Zhou Feng , Zhang Xia
Published: December 2024

The development of green and environmentally friendly lubricant additives is crucial in the field of friction. A green modifier, Cardanol polyoxyethylene ether xanthate (CPEOCS2K), was synthesized from natural cashew nut shells derived from Cardanol. Cu nanoparticles were prepared using a simple one-step reduction method, which involved modifying metallic Cu with CPEOCS2K. The long chains of the modifier on the surface of the nanocore interconnected to form a nano-network, and the resulting Cu nanochains exhibited excellent lubrication performance when applied to a water-ethylene glycol (EG) system as a lubricant additive. This encapsulated nanoparticle structure not only enhances the dispersion stability of the nanoparticles but also generates a chemically reactive film that adsorbs onto the wear surface during friction, thereby improving the lubrication effectiveness of the water-based lubricant. The use of natural organic compounds to synthesize modifiers enhances the environmental friendliness of metal nanoparticles as lubricant additives, and the outstanding lubricating performance demonstrates the potential of green lubrication technology.
Zerumbone And Doxorubicin Combination Induces MAPK3 Dependent Apoptosis in Triple Negative Breast Cancer Cells
Authors: Mehraj Umar , Sofi Shazia , Wani Nissar A , Mir Manzoor Ahmad
Published: December 2024

Aim
Doxorubicin (DOX) is one of the most commonly used chemotherapeutic medications for treating several malignancies, including TNBC. However, severe toxicity and the development of resistance to drugs, limits its therapeutic index. As a result, there is a crucial need for the advancement of novel medications that boost the efficacy of Doxorubicin while decreasing its toxicity. Studies have shown that the Z. zerumbet-isolated sesquiterpene zerumbone (ZER) is a potent anti-proliferative molecule against several cancers including BC. This study intended to assess the antitumor activity of ZER in TNBC cells in combination with Doxorubicin.
Methods
MTT and Chou-Talay techniques were used to evaluate cell viability and pharmacodynamic interactions. Western blotting. flow cytometry, and fluorescence microscopy were used to assess the molecular mechanism underlying the anti-tumor activity of DOX-ZER combination.
Results
DOX and ZER combination significantly reduced the cell viability and showed synergistic impact on migration, proliferation, and colony formation potential of TNBC cells. Moreover, DOX-ZER combination resulted in enhanced ROS accumulation, activating MAPK3 mediated apoptosis and cell cycle arrest.
Conclusions
Our findings show that ZER is a potent anticancer molecule that may be used in combination with DOX to enhance therapeutic efficacy and reduce the development of therapeutic resistance.
Aligning syntactic structure to the dynamics of verbal communication: a pipeline for annotating syntactic phrases onto speech acoustics
Authors: Iaia Cosimo , Tavano Alessandro
Published: December 2024

To investigate how the human brain encodes the complex dynamics of natural languages, any viable and reproducible analysis pipeline must rely on either manual annotations or Natural Language Processing (NLP) tools, which extract relevant physical (e.g., acoustic, gestural), and structure- building information from both speech and language signals. However, correctly annotating syntactic structure for a given human language is arguably a harder task than annotating the onset and offset of speech units such as phonemes and syllables, as the latter can be identified by relying at least in part on the physically overt and temporally measurable properties of the signal, while syntactic structure units are generally covert and their labelling is model-driven. We describe and validate a pipeline that takes into account both physical and theoretical aspects of speech and language signals, and operates a theory-driven and explicit alignment between overt speech units and covert syntactic units.
Arctic Ozone Amplifies Stratospheric Circulation Extremes
Authors: Hong Hao-Jhe , Reichler Thomas , Hsu Huang-Hsiung
Published: December 2024

Stratospheric ozone has long been suspected to drive interactions involving chemistry, radiation, and the circulation. However, the significance of these interactions, the underlying mechanisms, and the specific conditions that facilitate them remain poorly understood. In this study, we use a dry-dynamical core model with a simplified linear ozone scheme and a shortwave radiation parameterization to investigate these interactions. Our analysis, based on two long control simulations with either interactive or prescribed ozone, reveals that interactive ozone increases the persistence and interannual variability of the stratospheric circulation during northern spring, a period with sufficient solar radiation over the northern polar cap. This effect is closely linked to late-winter extreme stratospheric circulation events, such as stratospheric sudden warmings (SSWs) and vortex intensifications (VIs). While interactive ozone does not alter the frequency of these events, the ozone perturbations induced by the circulation amplify the associated temperature and wind anomalies. Specifically, late-winter VIs are followed by a colder and more persistent polar vortex in spring when interactive ozone is used, compared to fixed ozone. This results in a five-day delay in the breakdown date of the vortex and a more positive North Atlantic Oscillation at the surface. Although interactive ozone also amplifies perturbations following SSWs, these effects are less pronounced than those observed for VIs. Our findings contribute to a growing body of evidence highlighting the importance of ozone-dynamics interactions for simulating the stratospheric circulation, its variability, and its surface impacts.
AI and Kernel Influences: The Impact of Kernel Optimization on Energy Consumption Forecasting
Authors: Danish Muhammad Umair
Published: December 2024

This study addresses the complexities of short-term energy forecasting in the context of fluctuating consumer behaviors and seasonal variations. Our research primarily focused on the development and evaluation of advanced machine learning models and particularly understanding the effects of Kernels on the proposed HyperNetwork-based LSTM model to enhance the accuracy and reliability of energy predictions. We conducted a comprehensive analysis of various state-ofthe-art models, including MLPs, RNNs, and Transformers, rigorously evaluating them across standard metrics for fair comparisons. A significant contribution of our work is the proposed HyperNetwork-based LSTM model which provides consistently superior forecasting accuracy, particularly in certain seasonal contexts. However, upon seasonal evaluation, our proposed solution is not performing well in all seasons. The Python-based implementation of the entire project is available at GitHub Repository — Advanced AI.
Seasonal Dynamics in Energy Forecasting: A Deep Learning Approach for Student Residences
Authors: Danish Muhammad Umair
Published: December 2024

This study presents a comprehensive analysis of various machine-learning models for energy forecasting across different seasons in students' residential settings. Our research investigates the performance of baseline models, including LSTM, GRU, state-of-the-art forecasting models, including Autoregressive feedforward neural network, Transformer, and hybrid approaches, by evaluating their ability to predict energy usage with high accuracy. Seasonal patterns and the occurrence of anomalous events such as vacations, meteorological shifts, unpredictable nature of human activity leading to sudden spikes and drops in energy consumption are particular challenges. The results demonstrate that no single model uniformly outperforms others across all seasons, which shows the necessity for season-specific model selection or design. Our proposed HyperNetLSTM and MiniAutoEncXGBoost models are delivering robustness in learning to seasonal variations especially in capturing sudden changes in consumption during the summer. The research contributes to the field of energy forecasting by the significance of seasonal insight and model behavior.
Analysis of the Tolerance of 22 Malus baccata Accessions to Alkali Stress
Authors: Zhang Lu , Liu Xuan , Dong Lijuan , Liang Wei , Ma Fengwang , Yu Wenquan , Li Zhengnan , Li Cuiying
Published: December 2024

Alkali stress is an important factor that restricts the growth and yield of crops. Apple (Malus baccata Borkh.) rootstocks have attracted widespread attention because of their wide distribution and ability to exist in various forms. This study reported the tolerance of several M. baccata accessions to alkaline stress using the sand culture method. Nitrogen (N), phosphorus (P), and potassium (K) contents in the roots of 22 M. baccata accessions decreased after 40 days of alkali stress exposure. N and P contents in the leaves of most M. baccata seedlings decreased, whereas K content increased. In addition, the new leaf number and fresh and dry weights of the M. baccata accessions decreased significantly, indicating that alkali stress inhibits the growth of M. baccata seedlings. The 22 M. baccata accessions were divided into three categories: high, moderate, and low tolerance based on the cluster analysis of the resistance coefficients of six growth indices combined with the average resistance coefficient evaluation of the growth indices. These delineations are important for screening M. baccata resources. This study provides a basis for the growth of the apple industry in areas such as northwest China, which suffer from severe salinization.
Transcriptomic Profiling of the Salt Tolerance Response in Roots of the Punica granatum ‘Fuanyihao’
Authors: Liu Chun , Li Jinjin
Published: December 2024

Salt stress is a main factor that harms the growth of horticultural crops. To reveal the molecular mechanism of salt stress, we conducted transcriptome sequencing on samples of pomegranate (Punica granatum ‘Fuanyihao’) roots subjected to salt stress at different time periods and control conditions. A total of 23,798 genes have been identified. Furthermore, 3366 genes, including 758 transcription factors (TFs), showed obvious differential expression in salt-tolerant or salt-sensitive genotypes. There is a certain quantity of differentially expressed genes (DEGs) identified under salt treatment at different time periods. Among them, many encoding TFs were found, such as bHLH-, NAC-, MYB-, ERF-, and WRKY- encoding genes. These DEGs were related to multiple pathways, mainly including the MAPK pathway, Glucosinolate biosynthesis, Cutin, etc. In these enriched pathways, plant hormone signal transduction and MAPK pathway-plant were the most notable. In total, abundant salt-stress response DEGs and pathways between pomegranate root systems treated at different times were identified, which promotes the understanding of salt-stress response mechanisms and are beneficial for improving a salt-resistance molecular breeding in pomegranate.
Topologically ordered steady states in open quantum systems
Authors: Wang Zijian , Dai Xu-Dong , Wang He-Ran , Wang Zhong
Published: December 2024

The interplay between dissipation and correlation can lead to novel emergent phenomena in open systems. Here we investigate “steady-state topological order” defined by the robust topological degeneracy of steady states, which is a generalization of the ground-state topological degeneracy of closed systems. Specifically, we construct two representative Liouvillians using engineered dissipation, and exactly solve the steady states with topological degeneracy. We find that while the steady-state topological degeneracy is fragile under noise in two dimensions, it is stable in three dimensions, where a genuine many-body phase with topological degeneracy is realized. We identify universal features of steady-state topological physics such as the deconfined emergent gauge field and slow relaxation dynamics of topological defects. The transition from a topologically ordered phase to a trivial phase is also investigated via numerical simulation. Our work highlights the essential difference between ground-state topological order in closed systems and steady-state topological order in open systems.
WZW terms without anomalies: Generalised symmetries in chiral Lagrangians
Authors: Davighi Joe , Lohitsiri Nakarin
Published: December 2024

We consider a 4d non-linear sigma model on the coset (\text{SU}(N)_L × \text{SU}(N)_R × \text{SU}(2))/(\text{SU}(N)_{L+R}× \mathrm{U}(1))\cong \text{SU}(N) × S^2(SU(N)L×SU(N)R×SU(2))/(SU(N)L+R×U(1))≅SU(N)×S2, that features a topological Wess–Zumino–Witten (WZW) term whose curvature is \frac{n}{24\pi^2}{Tr}(g^{-1}dg)^3 \wedge \mathrm{Vol}_{S^2}n24π2Tr(g−1dg)3∧VolS2 where gg is the \text{SU}(N)SU(N) pion field. This WZW term, unlike its familiar cousin in QCD, does not match any chiral anomaly, so its microscopic origin is not obviously QCD-like. We find that generalised symmetries provide a key to unlocking a UV completion. The S^2S2 winding number bestows the theory with a 1-form symmetry, and the WZW term intertwines this with the \text{SU}(N)^2SU(N)2 flavour symmetry into a 2-group global symmetry. Like a ‘t Hooft anomaly, the 2-group symmetry should match between UV and IR, precluding QCD-like completions that otherwise give the right pion manifold. We instead construct a weakly-coupled UV completion that matches the 2-group symmetry, in which an abelian gauge field connects the QCD baryon number current to the winding number current of a \mathbb{C}P^1ℂP1 model, and explicitly show how the mixed WZW term arises upon flowing to the IR. The coefficient is fixed to be the number of QCD colours and, strikingly, this matching must be ’tree-level exact’ to satisfy a quantization condition. We discuss generalisations, and elucidate the more intricate generalised symmetry structure that arises upon gauging an anomaly-free subgroup of \text{SU}(N)_{L+R}SU(N)L+R. This WZW term may even play a phenomenological role as a portal to a dark sector, that determines the relic abundance of dark matter.
Relationship selling impact on sales effectiveness: an evaluation from a health insurance agent’s perspective
Authors: Nayak Santosh , Kumar Satish , Rani Chopra Rita , Shetty Ankitha
Published: December 2024

This research paper examines the relationship selling impact on sales effectiveness in Health Insurance from an agent’s perspective. The study analyzed primary data by personal interaction with respondents in the Karnataka region, India, and used descriptive research with stratified sampling. A sample size of 407 health insurance agents was selected for this study from the age group between 18 to 60 years from diverse backgrounds. The research methodology involves constructing a regression model using the SPSS tool to analyze the data. The findings show that personal interaction determinants have positive and statistically significant effects on sales effectiveness, however, customer dependency and self-discipline have negative and statistically significant impacts on sales effectiveness. The results support the models’ reliability and a good measure of construct validity. Variables like Interaction Intensity (II) and Customer Dependence (CD) (0.632), Personal Interaction (PI) and Customer Dependence (CD) (0.464), and Customer Oriented Selling (COS) and Cooperative Intentions (CI) (0.523) have relatively strong positive correlations, suggesting these pairs move together in the same direction. This implies that an agent’s personal resources can affect their ability to convert relationship-selling behavior to tangible sales results that can guide sales force recruitment and training. Similarly, the organizing and structuring of the sales force can be informed by the findings that customer relationship characteristics influence salespeople’s ability to translate relationship selling behavior into sales effectiveness.
SYMBOLS AND RITUALS OF MILITARY AFFAIRS AND THEIR SPECIFIC INFLUENCE ON THE IMAGE OF THE SERVICE MEMBER
Authors: Verhun Denys
Published: December 2024

The article examines the elements of military (combat) traditions and customs (symbols and rituals of military affairs) that give military servicemen a visual identity and represent their readiness for service. The author analyzes the peculiarities of the above elements in the context of building a professional image of military servicemen, emphasizing that the latter belong to a special group – a special team with a core moral imperative of its existence. The symbols and rituals of military affairs, which are important in shaping the image of military servicemen, as they reflect their identity and values, are studied. The author emphasizes that the influence of symbols and rituals of military affairs on the image of military servicemen is manifested both in the internal community and in the perception of external observers. This is due to the fact that they accumulate the glory, courage, resilience, etc. of military servicemen.
Options for Modeling Social Rational-Value Networks: Congruence Issues
Authors: Kondratenko Konstantin
Published: December 2024

The article introduces a new concept designed to describe the social and sociotechnical processes that were triggered by digital transformation and, in their turn, resulted in Industry 5.0. The author described and modelled egocentric, communicative, convergent, and cause-and-effect rational-semantic networks, in which rationality relies on the semantic model of the system and forms some rational concern for its values and meanings to be implemented in behavior. The theoretical side of the research could be represented as a pyramid of conceptual levels that concentrate from philosophy and general science to particular research with statistical, network, and other methods. The author introduced the term of rational-semantic system to study the network contexts of behavior, including that of social network users. The term was also applied to the phenomena and effects of network interaction, e.g. the legitimacy of network power and its effect on user behavior patterns. The methodological character of this research allows for a broader study of social and political networks. The network context revealed some congruence issues, i.e., compatibility of rational-semantic systems. The author believes that eventually all systems can be combined into a single whole.