Search Results (90)

Background/Objectives: Racial and ethnic disparities in cesarean birth and labor management persist in the United States, including among individuals considered low risk. Understanding variation in labor progression and cesarean indications within low-risk nulliparous, term, singleton, vertex (NTSV) births may help clarify potential contributors to inequities. This study examined differences in cesarean rates, cesarean indications, and labor duration by race and ethnicity in a low-risk NTSV cohort. Methods: We conducted a retrospective secondary analysis of electronic medical record data from 13,231 low-risk NTSV births within a Midwestern academic health system. Multivariable logistic regression models were used to evaluate the likelihood of cesarean birth and cesarean indications by race and ethnicity, adjusting for maternal age, gestational age, body mass index, insurance type, and labor onset. Linear regression models examined differences in first-stage, second-stage, and total labor duration. Interaction terms assessed whether associations varied by labor onset. Results: The overall cesarean rate was 29%. Absolute cesarean rates were higher among non-Hispanic Black and Hispanic individuals compared with non-Hispanic White individuals; however, these differences were not statistically significant after adjustment. Labor duration differed significantly by race and ethnicity. Non-Hispanic Black and Hispanic individuals experienced longer median first-stage and total labor durations compared with non-Hispanic White individuals; however, second-stage duration was markedly shorter among non-Hispanic Black individuals. Among induced labors resulting in cesarean birth, non-Hispanic Black and Hispanic individuals had increased odds of cesarean for early arrest of dilation, although these findings should be interpreted as hypothesis-generating, given data limitations in labor onset documentation. Body mass index was positively associated with likelihood of cesarean. Conclusions: In this low-risk NTSV cohort, adjusted cesarean rates did not differ significantly by race or ethnicity; however, differences in labor duration and cesarean indication were observed. These findings underscore the importance of continued investigation into labor management practices and structural contributors to obstetric inequities. Full article

A dominating set of a graph is a subset of vertices such that every vertex is either contained in the set or adjacent to at least one vertex in it. A dominating set is called k-fair if each vertex not in this set is adjacent to exactly k vertices of the set. The domination and k-fair domination problems aim to find such sets of minimum cardinality. Both problems are NP-complete for general graphs, and the domination problem remains NP-complete on grid graphs, whereas the k-fair domination problem remains open on grid graphs. In this paper, we study the 1-fair and 2-fair domination problems on extended supergrid graphs, which generalize grid graphs and include both grid and supergrid graphs as subclasses. We prove that the 1-fair domination problem is NP-complete for these graph classes, even when restricted to planar graphs with maximum degree 4. On the positive side, for rectangular supergrid graphs, we present a linear-time algorithm for computing minimum 1-fair dominating sets. In addition, we formulate an integer linear programming (ILP) model to investigate the 1-fair and 2-fair dominations on small instances and introduce a restricted k-fair domination problem motivated by the experimental observations. Full article

The efficient minus domination problem (EMDP) and the efficient signed domination problem (ESDP) are domination-type problems in graphs. These problems are known to be NP-complete on chordal graphs and polynomially solvable on chain interval graphs, while the complexity on proper interval graphs remained open. By exploiting the totally unimodular structure of the closed-neighborhood matrix induced by a proper interval ordering, we obtain linear programming formulations under which both the EMDP and ESDP become polynomially solvable. The same perspective naturally extends to vertex-weighted settings and to other domination variants defined by similar neighborhood constraints. Full article

Soil heavy metal contamination in mining areas poses a serious environmental challenge, requiring monitoring approaches with both wide coverage and high accuracy. Hyperspectral remote sensing provides an effective solution, yet its performance in complex mining environments is often limited by mixed-pixel effects and nonlinear spectral responses. To address these issues, this study proposes a Physically-Constrained Collaborative Endmember Extraction (PCCEE) framework that integrates spectral unmixing with machine learning for multi-element inversion. Using Gaofen-5 hyperspectral imagery, a collaborative workflow combining Pixel Purity Index (PPI), Vertex Component Analysis (VCA), and prior-spectral-constrained Spectral Angle Mapper (SAM) was developed to improve endmember purity and physical interpretability. Among three unmixing models (LMM, NMF, and SVR), the Linear Mixing Model achieved the best balance between accuracy and efficiency. Random Forest regression using retrieved abundances enabled high-accuracy inversion of eight heavy metals (mean R² = 0.85). Spatial analysis revealed significant co-enrichment of Pb, Cd, and Zn related to sulfide weathering, while PCA distinguished compound and independent pollution sources. The proposed PCCEE framework effectively mitigates mixed-pixel interference and provides a transferable approach for heavy metal monitoring and risk assessment in complex mining environments. Full article

The bichromatic triangle polynomial $P_G\left(k\right)$ counts vertex k-colorings in which every triangle uses exactly two colors. We develop a transfer matrix framework for three canonical families of 2-trees: book graphs $B_n$, 1-fans $F_n^1$, and triangulated ladders $T{L}_m$. In each case, $P_G\left(k\right)$ satisfies a second-order linear recurrence with an explicit closed form; for $T{L}_m$ this yields a Chebyshev representation, while for $F_n^1$ the binary specialization gives $P_{F_n^1}\left(2\right)=2F_{n+1}$. A spectral identity ${\alpha }^2=r_{+}$ links the dominant characteristic roots of the fan and ladder recurrences, implying identical exponential growth rates when indexed by vertex count, whereas book graphs grow strictly faster for $k\ge 4$. In fact, this correspondence is exact: for all $k\ge 2$, the triangulated ladder polynomial coincides with that of a suitably indexed 1-fan. Passing to line graphs, we interpret $P_{L\left(K_n\right)}\left(k\right)$ as counting edge colorings of $K_n$ that forbid both monochromatic and rainbow triangles, and we identify a sharp obstruction threshold at $n\ge 6$. Full article

The regulation of output voltage in power converters often demands nonlinear control techniques; however, their implementation is challenging when deployed on low-cost hardware with limited computational resources. To address this difficulty, the modeling via the sector nonlinearity technique is adopted to represent the converter dynamics as a convex combination of linear vertex models. Building on this representation, this article proposes a vertex-based convex PI controller that significantly reduces the required online computations compared to conventional convex controllers relying on full-state feedback. In the proposed scheme, the inductor current is used solely to evaluate the weighting functions, avoiding the need to compute control gains associated with this state. The effectiveness of the method is demonstrated through offline simulations and validated using hardware-in-the-loop experiments. Full article

Zero-depth nanopores present a promising solution to the challenges associated with ultrathin membranes used in solid-state resistive pulse sensors for DNA sequencing. Most existing fabrication methods are either complex or lack the nanoscale precision required. In this study, we introduce a cost-effective approach that combines PDMS molding at the intersection of silicon micro-blades with an innovative high-resolution nano-positioning technique. These blades are created through photolithography and a two-step KOH wet etching process, allowing for the formation of sub-50 nm 3D rhombic zero-depth nanopores featuring large vertex angles. To address the limitations of SEM imaging—such as dielectric charging and deformation of PDMS membranes under electron beam exposure—we devised a finite element model (FEM) that correlates electrical conductance with pore size and electrolyte concentration. This model aligns closely with experimental data, yielding a mean absolute percentage error of 3.69%, thereby enabling real-time indirect sizing of the nanopores based on the measured conductance. Additionally, we identified a critical channel length beyond which pore resistance becomes negligible, facilitating a linear relationship between conductance and pore diameter. The nanopores produced using this method exhibited a 2.4-fold increase in conductance compared to earlier designs, highlighting their potential for high-precision DNA sequencing applications. Full article

Collaborative experiences are enriched through cross-platform interactions in the context of eXtended Reality (XR) systems. In this paper, we introduce SRVS-C (Spatially Referenced Virtual Synchronization for Collaboration), a centralized framework designed to support co-located, real-time AR (on smartphone) and VR (in headset) interactions over local networks. The framework adopts an architecture of interactive asymmetry, where the interaction roles, input modalities, and rendering responsibilities are adapted to the unique capabilities and constraints of each device. Concurrently, the framework maintains perceptual symmetry, guaranteeing a coherent spatial and semantic experience for all users. This is achieved through anchor-based spatial registration and unified data representations. Compared to prior work that relies on cloud services or symmetric platforms (e.g., VR–VR, AR–AR, and PC–PC pairings), SRVS-C supports seamless communication between AR and VR endpoints, operating entirely over TCP sockets using serialization-agnostic message formats. We evaluated SRVS-C in a dual-user scenario involving a mobile AR and a VR headset, using shared freehand drawing tasks. These tasks include simple linear strokes and geometry-rich drawing content to assess how varying interaction complexity—ranging from low-density sketches to intricate, high-vertex structures— impacted the end-to-end latency, state replication timing, and collaborative fluency. The results show that the system sustains latency between 35 ms and 175 ms, even during rapid, continuous drawing actions that generate a high number of stroke updates per second, and when handling drawings composed of numerous vertices and complex shapes. Throughout these conditions, the system maintains perceptual continuity and spatial alignment across users by applying platform-specific interactive asymmetry. Full article

Additive manufacturing via stereolithography (SLA) enables the fabrication of highly customized lattice structures, yet the interplay between geometry and graded density in defining mechanical behavior remains underexplored. This research investigates the mechanical behavior and failure mechanisms of cylindrical lattice structures considering uniform, linear, and quadratic density variations. Various configurations, including IsoTruss, face-centered cubic (FCC)-type cells, Kelvin structures, and Tet oct vertex centroid, were examined under a complete factorial design that allowed a thorough exploration of the interactions between lattice geometry and density variation. A 3D printer working with SLA was used to fabricate the models. For the analysis, a universal testing machine, following ASTM D638-22 Type I and ASTM D1621-16 standards, was used for tension and compression tests. For microstructural analysis and surface inspection, a scanning electron microscope and a digital microscope were used, respectively. Results indicate that the IsoTruss configuration with linear density excelled remarkably, achieving an impressive energy absorption of approximately 15 MJ/m³ before a 44% strain, in addition to presenting the most outstanding mechanical properties, with a modulus of elasticity of 613.97 MPa, a yield stress of 22.646 MPa, and a maximum stress of 49.193 MPa. On the other hand, the FCC configuration exhibited the lowest properties, indicating lower stiffness and mechanical strength in compression, with an average modulus of elasticity of 156.42 MPa, a yield stress of 5.991 MPa, and the lowest maximum stress of 14.476 MPa. The failure modes, which vary significantly among configurations, demonstrate the substantial influence of the lattice structure and density distribution on structural integrity, ranging from localized bending in IsoTruss to spalling in FCC and shear patterns in Kelvin. This study emphasizes the importance of selecting fabrication parameters and structural design accurately. This not only optimizes the mechanical properties of additively manufactured parts but also provides essential insights for the development of new advanced materials. Overall, the study demonstrates that both lattice geometry and density distribution play a crucial role in determining the structural integrity of additively manufactured materials. Full article

To improve the accuracy of second-order cell-centered finite volume method in near-boundary regions for solving the two-dimensional shallow water equations, a numerical scheme with globally second-order accuracy was proposed. Having the primary objective to overcome the challenge of accuracy degradation in near-boundary regions and to develop a robust numerical framework combining high-order accuracy with strict conservation, the key research objectives had been as follows: Firstly, a physical variable reconstruction method combining a vertex-based nonlinear weighted reconstruction scheme and a monotonic upwind total variation diminishing scheme for conservation laws was proposed. While the overall computational efficiency was maintained, linear-exact reconstruction in near-boundary regions was achieved. The variable reconstruction in interior regions was integrated to achieve global second-order accuracy. Subsequently, a flux boundary condition treatment method based on uniform flow was proposed. Conservative allocation of hydraulic parameters was achieved, and flow stability in inflow regions was enhanced. Finally, a series of numerical test cases were provided to validate the performance of the proposed method in solving the shallow water equations in terms of high-order accuracy, exact conservation properties, and shock-capturing capabilities. The superiority of the method was further demonstrated under high-speed flow conditions. The high-precision numerical model developed in this study holds significant value for enhancing the predictive capability of simulations for natural disasters such as flood propagation and tsunami warning. Its robust boundary treatment methods also provide a reliable tool for simulating free-surface flows in complex environments, offering broad prospects for engineering applications. Full article

Aiming at the problem of model parameter perturbation in vehicle trajectory tracking control, an improved robust model predictive control (RMPC) method is proposed. Based on the two-degree-of-freedom vehicle model and Serret Frenet error model, a multi-cell hypercube vertex modeling is adopted to map the disturbance range of parameters such as vehicle speed and lateral stiffness to a set of vertices, and dynamic linear combination is achieved through normalized weights. The algorithm design mainly focuses on the dual-layer optimization of the switching mechanism, decomposing the infinite time domain problem into finite time domain optimization and terminal constraints. At the same time, it dynamically updates the vertex parameters to match time-varying uncertainties and then combines Lyapunov theory to design a control invariant set. The results show that in complex road conditions and vehicle state transitions, RMPC can reduce the peak lateral deviation from 1.0 m to 0.2 m, converge the heading deviation to within 2 deg, and significantly reduce the mean and root mean square values of control errors compared to traditional MPC, under the influence of vehicle model parameter perturbations. RMPC has good robustness and real-time performance. Full article

A second-order linear differential operator A is defined on a tree of arbitrary topology. Any internal vertex P of the tree divides the tree into $m_p$ branches. The restrictions $A_i,i=1,\dots ,m_p$ of the operator A on each of these branches, where the vertex P is considered the root of the branch and the Dirichlet boundary condition is specified at the root. These restrictions must be, in a sense, asymmetric (not similar) to each other. Thus, the distinguished class of differential operators A turns out to have only simple eigenvalues. Moreover, the matching conditions at the internal vertices of the graph contain a set of parameters. These parameters are interpreted as stiffness coefficients. This paper proves that a finite set of eigenvalues allows one to uniquely restore the set of stiffness coefficients. The novelty of the work is the fact that it is sufficient to know a finite set of eigenvalues of intermediate Weinstein problems for uniquely restoring the required stiffness coefficients. We not only describe the results of selected studies but also compare them with each other and establish interconnections. Full article

Radio mean labeling of a connected graph G is an assignment of distinct positive integers to the vertices of G satisfying a mathematical constraint called radio mean condition. The maximum label assigned to any vertex of G is called the $span$ of the radio mean labeling. The minimum $span$ of all feasible radio mean labelings of G is the radio mean number of G, denoted by $rmn\left(G\right)$. In our previous study, we proved that if G has order n, then $rmn\left(G\right)\in [n,rmn\left(P_n\right)]$ where $P_n$ is a path of order n. All graphs of diameters 1, 2 and 3 have the radio mean number equal to order n. However, they are not the only graphs on n vertices with radio mean number n. Graphs isomorphic to path $P_n$ are the graphs having the maximum diameter among the set of all graphs of order n and they possess the maximum feasible radio mean number. In this paper, we show that, for any integer in the range of achievable radio mean numbers, there always exists a graph of order n with the given integer as its radio mean number. This is approached by introducing a special type of tree whose construction is detailed in the article. The task of assigning radio mean labels to a graph can be considered as an optimization problem. This paper critiques the limitations of existing Integer Linear Programming (ILP) models for assigning radio mean labeling to graphs and proposes a new ILP model. The existing ILP model does not guarantee that the vertex labels are distinct, positive and satisfy the radio mean condition, prompting the need for an improved approach. We propose a new ILP model which involves $n^2$ constraints is the input graph’s order is n. We obtain a radio mean labeling of cycle of order 10 using the new ILP. In our previous study, we showed that, for any graph G, we can extend the radio mean labelings of its diametral paths to the vertex set of G and obtain radio mean labelings of G. This insight forms the basis for an algorithm presented in this paper to obtain radio mean labels for a given graph G with n vertices and diameter d. The correctness and complexity of this algorithm are analyzed in detail. Radio mean labelings have been proposed for cryptographic key generation in previous works, and the algorithm presented in this paper is general enough to support similar applications across various graph structures. Full article

MSP DAGs (short for minimal series-parallel digraphs) can be defined from the single vertex graph by applying the parallel composition and series composition. We prove an upper bound of 6 for the directed clique-width of MSP DAGs and show how a directed clique-width 6-expression can be found in linear time. Our 6-expression can be used to construct an MSP DAG G from its binary decomposition tree $T\left(G\right)$ in linear time. We apply our bound on the directed clique-width to conclude a number of algorithmic consequences for MSP DAGs. Full article

Drones are widely used in urban air pollution monitoring. Although studies have focused on single-drone applications, collaborative applications for air pollution detection are relatively underexplored. This paper presents a 3D cube-based adaptive cooperative search algorithm that allows two drones to collaborate to explore air pollution. The search space is divided into cubic regions, and each drone explores the upper or lower halves of the cubes and collects data from their vertices. The vertex with the highest measurement is selected by comparing the collected data, and an adjacent cube-shaped search area is generated for exploration. The search continues iteratively until any vertex measurement reaches a predefined threshold. An improved algorithm is also proposed to address the divergence and oscillation that occur during the search. In simulations, the proposed method consumed 21 times less CPU time and required 23 times less search distance compared to linear search. Additionally, the cooperative search method using multiple drones was more efficient than single-drone exploration in terms of the same parameters. Specifically, compared to single-drone exploration, the collaborative drone search reduced CPU time by a factor of 2.6 and search distance by approximately a factor of 2. In experiments in real-world scenarios, multiple drones equipped with the proposed algorithm successfully detected cubes containing air pollution above the threshold level. The findings serve as an important reference for research on drone-assisted target exploration, including air pollution detection. Full article