Search Results (203)

Rapid advancements in artificial intelligence and the Internet of Things (IoT) have fueled the growth of furniture, transforming traditional home environments into intelligent living spaces. As consumer adoption accelerates, understanding user concerns and sentiment trends becomes crucial for brands to refine product offerings and enhance market competitiveness. This study systematically investigates consumer concerns and sentiment trends toward furniture products by analyzing user-generated reviews across two major e-commerce platforms: Jingdong and Taobao. Leveraging advanced text-mining methods including TF-IDF keyword extraction, hierarchical clustering, Graph of Words–Latent Dirichlet Allocation (GoW-LDA) topic modeling, and BERT-based sentiment analysis, this research identifies critical user preferences, product satisfaction factors, and platform-specific behavioral patterns. Results reveal distinct cross-platform differences; Jingdong users prioritize service quality, brand trust, and logistical efficiency, whereas Taobao users emphasize product aesthetics, material selection, and cost-effectiveness. The sentiment analysis demonstrates that Jingdong users exhibit more consistent and positive feedback, while sentiment on Taobao displays higher variability due to product-quality discrepancies and price sensitivity. Full article

Let G be a connected graph. The Steiner k-Wiener index $S{W}_k\left(G\right)$ of graph G is defined as $S{W}_k\left(G\right)={\displaystyle \sum _{S\subseteq V\left(G\right),\left|S\right|=k}}{d}_G\left(S\right)$, where $d_G\left(S\right)$ represents the minimum size of a connected subgraph of G that connects S. Using some graph operations, we obtain the minimum value and the second minimum value of the Steiner k-Wiener index for cacti with order n and t cycles, and we characterize the corresponding extremal graphs by exploiting structural symmetries. Full article

Let $\mathfrak{R}$ be a commutative ring with identity $1\ne 0$. The weakly zero-divisor graph of $\mathfrak{R}$, denoted $W_{\Gamma }(\mathfrak{R})$, is the simple undirected graph whose vertex set consists of the nonzero zero-divisors of $\mathfrak{R}$, where two distinct vertices $\mathfrak{a}$ and $\mathfrak{b}$ are adjacent if and only if there exist $r\in \mathrm{ann}(\mathfrak{a})$ and $s\in \mathrm{ann}(\mathfrak{b})$ such that $rs=0$. In this paper, we study the signless Laplacian spectrum of $W_{\Gamma }({\mathbb{Z}}_n)$ for several composite forms of n, including $n=p^2{q}^2$, $n=p^{2}qr$, $n=p^m{q}^m$ and $n=p^{m}qr$, where $p, q, r$ are distinct primes and $m\ge 2$. By using generalized join decomposition and quotient matrix methods, we obtain explicit eigenvalue formulas for each case, along with structural bounds, spectral integrality conditions and Nordhaus–Gaddum-type inequalities. Illustrative examples with computed spectra are provided to validate the theoretical results, demonstrating the interplay between the algebraic structure of ${\mathbb{Z}}_n$ and the spectral properties of its weakly zero-divisor graph. Full article

Smart monitoring of local electricity systems (LESs) with sources based on renewable energy resources (RESs) from the point of view of the requirements of the functions of an intelligent system are hardware and software systems that can solve the tasks of both analysis (optimization) and synthesis (design, planning, control). The article considers the following: a functional scheme of smart monitoring of LESs, describing its main components and scope of application; an assessment of the state of the processes and the state of the equipment of generators and loads; dynamic pricing and a dynamic assessment of the state of use of primary fuel and/or current costs of generators; economic efficiency of generator operation and loads; an assessment of environmental acceptability, in particular, the volume of CO₂ emissions; provides demand-side management, managing maximum energy consumption; a forecast of system development; an assessment of mutual flows of electricity; system resistance to disturbances; a forecast of metrological indicators, potential opportunities for generating RESs (wind power plants, solar power plants, etc.); an assessment of current costs; the state of electromagnetic compatibility of system elements and operation of electricity storage devices; and ensures work on local electricity markets. The application of smart monitoring in the formation of tariffs on local energy markets for transactive energy systems is shown by conducting a combined comprehensive assessment of the energy produced by each individual power source with graphs of the dependence of costs on the generated power. Algorithms for the comprehensive assessment of the cost of electricity production in a transactive system for calculating planned costs are developed, and the calculation of the cost of production per 1 kW is also presented. A visualization of the results of applying this algorithm is presented. Full article

In the context of intelligent coal mine safety monitoring, an integrated prediction and early-warning method named MTGNN-Bayesian-IF-DBSCAN (Multi-Task Graph Neural Network–Bayesian Optimization–Isolation Forest–Density-Based Spatial Clustering of Applications with Noise) is proposed to address the challenges of gas concentration prediction and anomaly detection in coal mining faces. The MTGNN (Multi-Task Graph Neural Network) is first employed to model the spatiotemporal coupling characteristics of gas concentration and wind speed data. By constructing a graph structure based on sensor spatial dependencies and utilizing temporal convolutional layers to capture long short-term time-series features, the high-precision dynamic prediction of gas concentrations is achieved via the MTGNN. Experimental results indicate that the MTGNN outperforms comparative algorithms, such as CrossGNN and FourierGNN, in prediction accuracy, with the mean absolute error (MAE) being as low as 0.00237 and the root mean square error (RMSE) maintained below 0.0203 across different sensor locations (T0, T1, T2). For anomaly detection, a Bayesian optimization framework is introduced to adaptively optimize the fusion weights of IF (Isolation Forest) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise). Through defining the objective function as the F1 score and employing Gaussian process surrogate models, the optimal weight combination (w_if = 0.43, w_dbscan = 0.52) is determined, achieving an F1 score of 1.0. By integrating original concentration data and residual features, gas anomalies are effectively identified by the proposed method, with the detection rate reaching a range of 93–96% and the false alarm rate controlled below 5%. Multidimensional analysis diagrams (e.g., residual distribution, 45° diagonal error plot, and boxplots) further validate the model’s robustness in different spatial locations, particularly in capturing abrupt changes and low-concentration anomalies. This study provides a new technical pathway for intelligent gas warning in coal mines, integrating spatiotemporal modeling, multi-algorithm fusion, and statistical optimization. The proposed framework not only enhances the accuracy and reliability of gas prediction and anomaly detection but also demonstrates potential for generalization to other industrial sensor networks. Full article

Let us consider the finite commutative ring R, whose unity is $1\ne 0.$ Its weakly zero-divisor graph, represented as $W\Gamma \left(R\right)$, is a basic undirected graph with two distinct vertices, $c_1$ and $c_2$, that are adjacent if and only if there exist $r\in$ $\mathrm{ann}\left(c_1\right)$ and $s\in$ $\mathrm{ann}\left(c_2\right)$ that satisfy the condition $rs=0$. Let $D\left(G\right)$ be the distance matrix and $Tr\left(G\right)$ be the diagonal matrix of the vertex transmissions in basic undirected connected graph G. The $D_{\alpha }$ matrix of graph G is defined as $D_{\alpha }\left(G\right)=\alpha Tr\left(G\right)+(1-\alpha )D\left(G\right)$ for $\alpha \in [0,1]$. This article finds the $D_{\alpha }$ spectrum for the graph $W\Gamma \left({\mathbb{Z}}_n\right)$ for various values of n and also shows that $W\Gamma \left({\mathbb{Z}}_n\right)$ for $n={\vartheta }_1{\vartheta }_2{\vartheta }_3\dots {\vartheta }_t{\eta }_1^{d_1}{\eta }_2^{d_2}\dots {\eta }_s^{d_s}(d_i\ge 2,t\ge 1,s\ge 0)$, where ${\vartheta }_i$’s and ${\eta }_i$’s are the distinct primes, is $D_{\alpha }$ integral. Full article

A Roman dominating function f of a graph $G=(V,E)$ assigns labels from the set $\{0,1,2\}$ to vertices such that every vertex labeled 0 has a neighbor labeled 2. The weight of an RDF f is defined as $w\left(f\right)={\sum }_{v\in V}f\left(v\right)$, and the Roman domination number, ${\gamma }_R\left(G\right)$, is the minimum weight among all RDFs of G. This paper studies the domination and Roman domination numbers in Cartesian bundles of cycles. Furthermore, the constructed optimal patterns improve known bounds and suggest even better bounds might be achieved by combining patterns, especially for bundles involving shifts of order $4k$ and $5k$. Full article

Earth–air heat exchangers (EAHXs) use the soil’s thermal capacity to dampen the amplitude of outdoor air temperature oscillations. This effect can be used in hot and dry climates for room cooling with no or very little need for resources other than those used during the EAHX construction, an obvious advantage compared to the significant operational costs of refrigeration machines. Contrary to the streamlined process applied in conventional HVAC design (using refrigeration machines), EAHX design lacks straightforward and well-established rules; moreover, EAHXs struggle to achieve office room design cooling demands determined with conventional indoor thermal environment standards, hindering designers’ confidence and the wider adoption of EAHXs for standalone room cooling. This paper presents a graph-based method to assist in the design of a large-diameter EAHX. One year of post-occupancy monitoring data are used to evaluate this method and to investigate the performance of a large-diameter EAHX with up to 16,000 m³/h design airflow rate. Considering an adaptive standard for thermal comfort, peak EAHX cooling capacity of 28 kW (330 kWh/day, with just 50 kWh/day of fan electricity consumption) and office room load extraction of up to 22 kW (49 W/m²) provided evidence in support of standalone use of EAHX for room cooling. A fair fit between actual EAHX thermal performance and results obtained with the graph-based design method support the use of this method for large-diameter EAHX design. Full article

In complex dynamic environments, the performance of SLAM systems on bionic robots is susceptible to interference from dynamic objects or structural changes in the environment. To address this problem, we propose a semantic visual SLAM (vSLAM) algorithm based on loop closure detection with combinatorial graph entropy. First, in terms of the dynamic feature detection results of YOLOv8-seg, the feature points at the edges of the dynamic object are finely judged by calculating the mean absolute deviation (MAD) of the depth of the pixel points. Then, a high-quality keyframe selection strategy is constructed by combining the semantic information, the average coordinates of the semantic objects, and the degree of variation in the dense region of feature points. Subsequently, the unweighted and weighted graphs of keyframes are constructed according to the distribution of feature points, characterization points, and semantic information, and then a high-performance loop closure detection method based on combinatorial graph entropy is developed. The experimental results show that our loop closure detection approach exhibits higher precision and recall in real scenes compared to the bag-of-words (BoW) model. Compared with ORB-SLAM2, the absolute trajectory accuracy in high-dynamic sequences improved by an average of 97.01%, while the number of extracted keyframes decreased by an average of 61.20%. Full article

In this study, we investigate the fractional Tzitzéica equation, a nonlinear evolution equation known for modeling complex phenomena in various scientific domains such as solid-state physics, crystal dislocation, electromagnetic waves, chemical kinetics, quantum field theory, and nonlinear optics. Using the (G′/G, 1/G)-expansion approach, we derive different categories of exact solutions, like hyperbolic, trigonometric, and rational functions. The beta fractional derivative is used here to generalize the classical idea of the derivative, which preserves important principles. The derived solutions with broader nonlinear wave structures are periodic waves, breathers, peakons, W-shaped solitons, and singular solitons, which enhance our understanding of nonlinear wave dynamics. In relation to these results, the findings are described by showing the solitons’ physical behaviors, their stabilities, and dispersions under fractional parameters in the form of contour plots and 2D and 3D graphs. Comparisons with earlier studies underscore the originality and consistency of the (G′/G, 1/G)-expansion approach in addressing fractional-order evolution equations. It contributes new solutions to analytical problems of fractional nonlinear integrable systems and helps understand the systems’ dynamic behavior in a wider scope of applications. Full article

A vertex–edge Roman $\left\{2\right\}$-dominating function on a graph $G=(V,E)$ is a function $f:V⟶\{0,1,2\}$ satisfying that, for every edge $uv\in E$ with $f\left(v\right)=f\left(u\right)=0$, ${\sum }_{w\in N\left(v\right)\cup N\left(u\right)}f\left(w\right)\ge 2$. The weight of the function f is the sum ${\sum }_{a\in V}f\left(a\right)$. The vertex–edge Roman $\left\{2\right\}$-domination number of G, denoted by ${\gamma }_{veR2}\left(G\right)$, is the minimum weight of a vertex–edge Roman $\left\{2\right\}$-dominating function on G. In this work, we begin the study of vertex–edge Roman $\left\{2\right\}$-domination. We determine the exact vertex–edge Roman $\left\{2\right\}$-domination number for cycles and paths, and we provide a tight lower bound and a tight upper bound for the vertex–edge Roman $\left\{2\right\}$-domination number of trees. In addition, we prove that the decision problem associated with vertex–edge Roman $\left\{2\right\}$-domination is NP-complete for bipartite graphs. Full article

Background. Metabolic dysfunction-associated steatotic liver disease (MASLD) affects more than 30% of the world population. Progression to its inflammatory state, MASH, is associated with increasing liver fibrosis, leading to end-stage liver disease (ESLD) and hepatocellular carcinoma (HCC). SW033291, an inhibitor of 15-PGDH (the PGE2 degradation enzyme), has been shown to increase in vivo regeneration of liver parenchyma, ameliorating oxidative stress and inflammation. We hypothesized that SW033291 abrogates MASH progression by inducing a paucity of the initial apoptotic switch and restoring physiological collagen’s microenvironment. Methods. The expression levels of the cell metabolic proteins FOXO1, mTOR, and SIRT7 were determined in a diet-induced MASH-mouse model at 16, 20, and 24 weeks. Non-targeted metabolomics in mouse plasma were measured by LC-MS/MS. Liver morphology and apoptotic activity were quantified by the NAS score and TUNEL assay, respectively. Statistical analyses between groups (NMC, HFD, and SW033291) were determined by ANOVA, t-test/Tukey’s post hoc test using GraphPad Prism. Metabolomics data were analyzed using R-lab. Results. The treated group showed significant decreases in total body fat, cellular oxidative stress, and inflammation and an increase in total lean mass with improved insulin resistance and favorable modulation of metabolic protein expressions (p < 0.05). SW033291 significantly decreased GS:SG, citric acid, and corticosterone, NAS scores (9.4 ± 0.2 vs. 6.2 ± 0.1, p < 0.05), liver fibrosis scores (1.3 ± 0.5 vs. 0.25 ± 0.1, p < 0.05), and apoptotic activity (43.9 ± 4.6 vs. 0.38 ± 0.1%, p < 0.05) compared with controls at 24W. Conclusions. The inhibition of 15-PGDH appears to normalize the metabolic and morphological disturbances during MASH progression with a paucity of the initial apoptotic switch, restoring normal collagen architecture. SW033291 warrants further investigation for its translation. Full article

Background: Both aging and cognitive fatigue are significant factors influencing alpha activity in the brain. However, the interactive effects of age and mental fatigue on the alpha spectrum and functional connectivity have not been fully elucidated. Methods: Using resting-state EEG data from an open-access dataset (younger: N = 198; older: N = 227) collected before and after a 2 h cognitive task block, we systematically examined the effects of aging and mental fatigue on alpha (8–13 Hz) oscillations via an aperiodic-corrected power spectrum, the weighted phase lag index (wPLI), and graph theory analysis. Results: In both spectral power and network efficiency, mental fatigue primarily modulates low alpha in younger individuals, while high alpha reflects stable age-related changes. The aperiodic offset and exponent decrease with age, while mental fatigue leads to an increase in the exponent. Notable interactions between age and mental fatigue are observed in low-alpha power, the aperiodic exponent, and the network efficiency of both low- and high-alpha bands. Conclusions: This study provides valuable insights into the differential modulation patterns of alpha activity by age and mental fatigue, as well as their interactions. These findings advance our understanding of how aging and mental fatigue differentially and interactively shape neural dynamics. Full article

Wire electrical discharge machining (WEDM) enables the production of complex parts with tight tolerances, although maintaining dimensional accuracy in corners and tapers remains challenging due to wire deflection and vibration. This study optimizes WEDM parameters for achieving high accuracy in machining complex geometrical parts and taper cuts in 6061 aluminum alloy using an Excetek W350G WEDM machine with a copper wire electrode. Parameters including wire tension, pulse on-time, pulse off-time, wire feed rate, open circuit voltage, and flushing pressure were varied using a L18 Taguchi orthogonal array and the response graph method to identify optimal cutting conditions. Experimental results indicated that feature-specific optimization is crucial, as different geometrical features (rectangular fins, triangular fins, gears) exhibited varying critical parameters. Key findings highlighted the importance of wire tension and pulse on-time in maintaining cutting accuracy, although at varying levels for specific features. Response graphs demonstrated the effects of major WEDM parameters on corner and profile accuracies, whereas Taguchi analysis provided the optimum settings of parameters for each feature and taper cutting. These findings will help enhance precision, efficiency, and versatility of the WEDM process in machining complex profiles and corners, contributing to precision manufacturing. Full article

This work establishes the multiplicity of solutions for the fractional Kazdan–Warner equation on finite graphs for the negative case. Our main focus lies in analyzing the nonlinear equation defined on a finite graph $(V,E,\mu ,w)$: ${(-\Delta )}^{s}u=(K+\lambda )e^{2u}-\kappa \mathrm{in}V,$ where the fraction $s\in (0,1)$ and real parameter $\lambda$ are given, and the graph functions K and $\kappa$ satisfy ${\max }_{x\in V}K\left(x\right)=0$, $K\not\equiv 0$ and ${\int }_V\kappa d\mu <0$. We derive the solvability characteristics of the above equation with the help of variational theory and the upper and lower solutions method. Full article