Design of intelligent financial data management system based on higher-order hybrid clustering algorithm.

Amid the ever-expanding landscape of financial data, the importance of predicting potential risks through artificial intelligence methodologies has steadily risen. To achieve prudent financial data management, this manuscript delves into the domain of intelligent financial risk forecasting within the scope of system design. It presents a data model based on the variational encoder (VAE) enhanced with an attention mechanism meticulously tailored for forecasting a company's financial peril.

Cloud-based configurable data stream processing architecture in rural economic development.

Purpose: This study aims to address the limitations of traditional data processing methods in predicting agricultural product prices, which is essential for advancing rural informatization to enhance agricultural efficiency and support rural economic growth.

Methodology: The RL-CNN-GRU framework combines reinforcement learning (RL), convolutional neural network (CNN), and gated recurrent unit (GRU) to improve agricultural price predictions using multidimensional time series data, including historical prices, weather, soil conditions, and other influencing factors. Initially, the model employs a 1D-CNN for feature extraction, followed by GRUs to capture temporal patterns in the data.

Understanding Users' App-Switching Behavior During the Mobile Search: An Empirical Study from the Perspective of Push-Pull-Mooring Framework.

With the rapid development of mobile applications (apps), various types of mobile apps have become the main channels for smartphone interaction. The user's app switching behavior in mobile search tasks has also received attention from academia. This article uses the push-pull-mooring (PPM) theoretical model to determine the three influencing factors of push, pull, and mooring that affect user's app switching behavior in mobile search.

Cluster formation tracking of networked perturbed robotic systems via hierarchical fixed-time neural adaptive approach.

This paper investigates the fixed-time cluster formation tracking (CFT) problem for networked perturbed robotic systems (NPRSs) under directed graph information interaction, considering parametric uncertainties, external perturbations, and actuator input deadzone. To address this complex problem, a novel hierarchical fixed-time neural adaptive control algorithm is proposed based on a hierarchical fixed-time framework and a neural adaptive control strategy. The objective of this study is to achieve accurate CFT of NPRSs within a fixed time.

Recognition of MCF-7 breast cancer cells using native collagen probes: Collagen source effect.

Developing superior cancer cell recognition probes is crucial for the development of tumor therapy and cancer early screening materials. In this study, we first achieved effective recognition of MCF-7 breast cancer cells using natural collagen probes. Through cell adhesion, cancer cell selective capture, and flow cytometry techniques, the binding efficiency of mammalian-derived collagens (bovine Achilles tendon collagen, porcine skin collagen) and fish-derived collagens (turbot skin collagen, grass carp skin collagen, mandarin fish skin collagen) to cancer cells (MCF-7 breast cancer cells) and normal cells (human umbilical vein endothelial cells, HUVECs) was analyzed and compared.

Digital social media expression and social adaptability of the older adult driven by artificial intelligence.

Introduction: This study examines the impact of digital new media art on the health literacy and digital health literacy of older adults. It explores how digital new media art influences the social adaptability of the older adult, with a focus on variations in their engagement with digital technologies and community activities.

Methods: The research employed interviews and observations of older adult participants from communities and .

Relationship among micro-pollutants, economic growth, renewable energy, nanotechnology and ecological foot prints of China: evidence from panel data analysis.

An important concern is the availability of clean drinking water, which is an essential need for human survival. This issue arises due to the existence of hazardous micropollutants originating from various emission sources. Nanotechnology aids in the mitigation of micropollutants by assimilating and counteracting their effects, hence diminishing their influence on water and other ecosystems.

Research on 3D virtual vision matching based on interactive color segmentation.

Given the prevalent issues surrounding accuracy and efficiency in contemporary stereo-matching algorithms, this research introduces an innovative image segmentation-based approach. The proposed methodology integrates residual and Swim Transformer modules into the established 3D Unet framework, yielding the Res-Swim-UNet image segmentation model. The algorithm estimates the disparateness of segmented outputs by employing regression techniques, culminating in a comprehensive disparity map.

Exploring approaches to tackle cross-domain challenges in brain medical image segmentation: a systematic review.

Introduction: Brain medical image segmentation is a critical task in medical image processing, playing a significant role in the prediction and diagnosis of diseases such as stroke, Alzheimer's disease, and brain tumors. However, substantial distribution discrepancies among datasets from different sources arise due to the large inter-site discrepancy among different scanners, imaging protocols, and populations. This leads to cross-domain problems in practical applications.

The impacts of economy policy uncertainty on peer effects of firms R&D investment: Based on LDA machine learning and regression statistical modeling approach.

The Latent Dirichlet Allocation (LDA) model is used to extract the text themes of newspaper news and construct the Chinese Economic Policy Uncertainty (EPU) Index. On this basis, based on the relevant data of Chinese A-share listed companies from 2008 to 2020, this paper empirically analyzes the impact of EPU on peer effects of firms R&D investment, and finds that EPU will aggravate the peer effects of firms R&D investment. Furthermore, the moderating effect of manager's motivation to maintain reputation on the process of EPU influencing the peer effects of firms R&D investment was tested, and the mechanism of EPU influencing the peer effects of firms R&D investment through financial frictions was verified.

Application of multimodality perception scene construction based on Internet of Things (IoT) technology in art teaching.

Numerous impediments beset contemporary art education, notably the unidimensional delivery of content and the absence of real-time interaction during instructional sessions. This study endeavors to surmount these challenges by devising a multimodal perception system entrenched in Internet of Things (IoT) technology. This system captures students' visual imagery, vocalizations, spatial orientation, movements, ambient luminosity, and contextual data by harnessing an array of interaction modalities encompassing visual, auditory, tactile, and olfactory sensors.

Real-time task parameter selection method of accounting system based on multi-objective optimization and genetic algorithm.

The progress of the digital economy has promoted the enterprise accounting system. To accelerate the update and evolution of accounting systems, we propose a parameter selection method based on multi-objective optimization and genetic algorithm. Firstly, this article proposes an accounting feature extraction method based on multimodal information embedding.

Kinetic pathways of sub-bandgap induced electron transfer in Ag/TiO and the effect on isopropanol dehydrogenation under gaseous conditions.

Electron transfer and its kinetics play a major role in the photocatalysis of metal/semiconductor systems. Using photoconductances, photoabsorption, and photoinduced spectroscopic techniques, the present research aimed to gain a deep insight into electron transfer pathways and their kinetics for Ag/TiO systems under sub-bandgap light illumination and gaseous conditions. The results revealed that electrons generated in TiO can transfer to Ag nanoparticles at fast rates, and plasmon-generated electrons in Ag nanoparticles can also transfer to TiO.

The impact of internet adaptability on internet addiction: the serial mediation effect of meaning in life and anxiety.

Introduction: Previous research has demonstrated the significant role of individual characteristics in adolescent Internet addiction. In line with this, our previous research has introduced the concept of "Internet adaptability" as a potential factor that enables individuals to effectively cope with the negative consequences of Internet use. However, further investigation is required to understand the impact of Internet adaptability on problematic Internet use, including Internet addiction, as well as its associated internal psychological factors.

Longitudinal relationship between internet self-control and problematic internet use among Chinese adolescents: mediating role of meaning in life.

Introduction: While studies indicate that high self-control may serve as a safeguard against problematic internet use, there's evidence suggesting that problematic internet use can, in turn, diminish self-control. This study aimed to elucidate the longitudinal interplay between internet self-control and problematic internet use in adolescents, employing cross-lagged panel modeling. Furthermore, drawing from a positive psychology perspective, we examined the potential role of 'meaning in life' as a protective mediator within this longitudinal relationship.

A novel fluorescent turn on probe derived from Schiff base for highly selective and sensitive detection of Cu ion.

A fluorescent probe (L) of bis Schiff base secondary amine ligand was designed and synthesized from 2,6-pyridinedicarboxylic acid, ethylenediamine and salicylaldehyde by condensation and reduction reaction. Its structure was characterized by IR, UV-Vis, LIF, HNMR, C NMR, MS and elementary analysis. Investigation of binding test indicated that probe L could sensitively and selectively detect Cu ion with striking fluorescent signaling responses in anhydrous ethanol solvent.

Molecular mechanisms and physiological responses of rice leaves co-exposed to submicron-plastics and cadmium: Implication for food quality and security.

The effects of co-exposure to aged submicron particles (aSMPs) and Cd as model contaminants on rice leaves via the foliar route were investigated. Thirty-day-old rice seedlings grown in soil were exposed to Cd (nitrate) through foliar spraying at concentrations of 1, 10, 50, 100, and 500 μM, with or without aSMP at a rate of 30 μg d. It was observed that Cd translocated from leaves to roots via stems even without co-exposure to SMP.

A method of water resources accounting based on deep clustering and attention mechanism under the background of integration of public health data and environmental economy.

Water resource accounting constitutes a fundamental approach for implementing sophisticated management of basin water resources. The quality of water plays a pivotal role in determining the liabilities associated with these resources. Evaluating the quality of water facilitates the computation of water resource liabilities during the accounting process.

Exploring the impact of sustainable marketing on consumer behavior in the sports industry.

The general consensus is that climate change poses a significant danger. Scientists and policymakers are increasingly acknowledging that consumer behavior plays a crucial role in this matter. Specifically, the choices people make regarding what they consume, how they consume it, and the quantities they consume have a direct impact on the environment.

Fermi-level shift, electron separation, and plasmon resonance change in Ag nanoparticle-decorated TiO under UV light illumination.

Noble metal nanoparticles are widely used as co-catalysts for storing and separating electrons in semiconductor photocatalysis. Thus, evaluating this ability is important and meaningful to understand the photocatalytic mechanism. Employing Ag nanoparticles, the present study combined photoconductance and theoretical analysis to evaluate the Fermi-level () shift in a UV-illuminated Ag/TiO system under gaseous conditions.

Hybridizing TiCT Layers with Layered Double Hydroxide Nanosheets at the Molecular Level: A Smart Electrode Material for HO Monitoring in Cancer Cells.

Vertically stacked artificial 2D superlattice hybrids fabricated through molecular-level hybridization in a controlled fashion play a vital role in scientific and technological fields, but developing an alternate assembly of 2D atomic layers with strong electrostatic interactions could be much more challenging. In this study, we have constructed an alternately stacked self-assembled superlattice composite through integration of CuMgAl layered double hydroxide (LDH) nanosheets having positive charge with negatively charged TiCT layers using well-controlled liquid-phase co-feeding protocol and electrostatic attraction and investigated its electrochemical performance in sensing early cancer biomarkers, ., hydrogen peroxide (HO).

The response of C/N/S cycling functional microbial communities to redox conditions in shallow aquifers using in-situ sediment as bio-trap matrix.

Microbial communities are fundamental components driving critical biogeochemical carbon (C), nitrogen (N) and sulfur (S) cycles in groundwater ecosystems. The reduction-oxidation (redox) potential is one important environmental factor influencing the microbial community composition. Here, we developed a bio-trap method using in-situ sediment as a matrix to collect aquifer sediment samples and evaluate the response of microbial composition and C/N/S cycling functions to redox variations created by providing sole O, joint O and H, and sole H to three wells.

How the smart product attributes influence consumer adoption intention.

Compared with traditional products, the connection attributes and intelligence attributes of the smart product are their differentiated competitive advantages. In order to understand how smart product attributes affect consumer attitudes and the influencing mechanism, we carry out this study. In the framework of psychological empowerment, this paper explores the relationship between smart product attributes and consumers' adoption intention.