Measuring Primary Health Care Accessibility in Mississippi State Using an Extended Kernel Density 2SFCA Method

The accessibility of primary health care is fundamentally important to people’s life quality and wellbeing. Based on the block group level 2010 census data from the U.S. Census Bureau and primary health care data from Association of American Medical Colleges, this study focuses on measuring the primary health care accessibility using an extended kernel-density two Step Float Catchment Area method. The study area is the Mississippi State, which is ranked last state for health care. The objectives of this study are to calculate the accessibility and analyze the spatial and non-spatial disadvantages of communities in accessibility of primary health care of the Mississippi State. Results showed that the two-step floating catchment area integrated by a Gaussian function method is a viable method of calculating accessibility. Overall, urban and the fringe areas have higher spatial accessibility to primary health care, while lower accessibility areas are the suburban and rural areas. Relatively, Hinds County, Madison County, Rankin County, Lamer County, Forrest County, Jones County, Lauderdale County, and Lee County have higher accessibility, while some counties have lower accessibility, such as Marshall County, Winston County, Noxubee County, Wilkinson County, Smith County, and Greene County. From the factor analysis, those urban areas showed greater mobility disadvantages and higher health care needs. Besides, the attempts to integrate the health needs index and the mobility index with the spatial accessibility helps to balance accessibility with different non-spatial conditions. Additionally, this study provides implications for public policy about the health care distribution and the high health needs population

An Improved Algorithm for Incremental DFS Tree in Undirected Graphs

Depth first search (DFS) tree is one of the most well-known data structures for designing efficient graph algorithms. Given an undirected graph $G=(V,E)$ with $n$ vertices and $m$ edges, the textbook algorithm takes $O(n+m)$ time to construct a DFS tree. In this paper, we study the problem of maintaining a DFS tree when the graph is undergoing incremental updates. Formally, we show: Given an arbitrary online sequence of edge or vertex insertions, there is an algorithm that reports a DFS tree in $O(n)$ worst case time per operation, and requires $O\left(\min\{m \log n, n^2\}\right)$ preprocessing time. Our result improves the previous $O(n \log^3 n)$ worst case update time algorithm by Baswana et al. and the $O(n \log n)$ time by Nakamura and Sadakane, and matches the trivial $\Omega(n)$ lower bound when it is required to explicitly output a DFS tree. Our result builds on the framework introduced in the breakthrough work by Baswana et al., together with a novel use of a tree-partition lemma by Duan and Zhan, and the celebrated fractional cascading technique by Chazelle and Guibas

3D printed biomimetic bone model with micronetwork and -nanohydroxyapatite for breast cancer metastasis study

Currently, metastatic breast cancer (BrCa) provides a crucial clinical challenge. Metastasis occurs as part of a cascade of BrCa evolution, after vascular remodeling and extravasation at the tumor site occur. BrCa tumors commonly metastasize into bone; therefore, it is important to develop a working bone model that accurately simulates the metastasis, arrival, and eventual invasion of BrCa into bone. Here, we propose to use a 3D printing system and nanomaterial to recreate a biomimetic and tunable bone model suitable for the effective simulation and study of metastatic BrCa invading and colonizing a bone environment. For this purpose, we designed and 3D printed a series of scaffolds, comprised of a bone microstructure and nanohydroxyapatites (nHA, inorganic nanocomponents in bone). The size and geometry of the bone microstructure was varied with 250- and 150-µm pores, in repeating square and hexagon patterns, for a total of four different pore geometries. 3D printed scaffolds were subsequently conjugated with nHA, using an acetylation chemical functionalization process and then characterized by scanning electron microscope (SEM). The SEM imaging showed that our designed microfeatures were printable with the predesigned resolutions described earlier. Imaging further confirmed that acetylation effectively attached nHA to the surface of scaffolds and induced a nanoroughness. Metastatic BrCa cell 4 h adhesion and 1-, 3-, and 5-day proliferation was investigated in the bone model in vitro. The cell adhesion and proliferation results showed that all scaffolds are cytocompatible for BrCa cell growth; in particular, the nHA scaffolds with small hexagonal pores had the highest cell density. Given this data, it can be stipulated that our 3D printed nHA scaffolds may make effective biomimetic environments for studying BrCa bone metastasis

Combination resonances of parametric vibration system of the field modulated magnetic gear

Considering the time-varying magnetic coupling stiffness caused by the component eccentricity, the parametric vibration model of the field modulated magnetic gear (FMMG) system is founded and the corresponding dynamic differential equations are deduced. The expressions of the combination resonances are worked out when the excited frequency is close to the combination frequency between the meshing frequency and the natural frequencies, and the resonance responses are discussed. The results show that the resonance amplitudes are much bigger when the excited frequency is close to the combination frequency between the meshing frequency and the natural frequency of the inner rotor torsional mode than when the frequency is close to other combination frequencies. Meanwhile, because the magnetic coupling stiffnesses are much smaller than the supporting stiffness, the resonance displacement of only one degree of freedom is always much bigger than the displacements of other degrees of freedom. The combination resonances make the stability regions of the FMMG system decrease and worsen the dynamic characteristics. All these can lay the foundation for the parameter optimization of the FMMG system