Advancing Malaria Prediction in Uganda through AI and Geospatial Analysis Models

The resurgence of locally acquired malaria cases in the USA and the persistent global challenge of malaria transmission highlight the urgent need for research to prevent this disease. Despite significant eradication efforts, malaria remains a serious threat, particularly in regions like Africa. This study explores how integrating Gregor’s Type IV theory with Geographic Information Systems (GIS) improves our understanding of disease dynamics, especially Malaria transmission patterns in Uganda. By combining data-driven algorithms, artificial intelligence, and geospatial analysis, the research aims to determine the most reliable predictors of Malaria incident rates and assess the impact of different factors on transmission. Using diverse predictive modeling techniques including Linear Regression, K-Nearest Neighbor, Neural Network, and Random Forest, the study found that;Random Forest model outperformed the others, demonstrating superior predictive accuracy with an R2 of approximately 0.88 and a Mean Squared Error (MSE) of 0.0534, Antimalarial treatment was identified as the most influential factor, with mosquito net access associated with a significant reduction in incident rates, while higher temperatures correlated with increased rates. Our study concluded that the Random Forest model was effective in predicting malaria incident rates in Uganda and highlighted the significance of climate factors and preventive measures such as mosquito nets and antimalarial drugs. We recommended that districts with malaria hotspots lacking Indoor Residual Spraying (IRS) coverage prioritize its implementation to mitigate incident rates, while those with high malaria rates in 2020 require immediate attention. By advocating for the use of appropriate predictive models, our research emphasized the importance of evidence-based decision-making in malaria control strategies, aiming to reduce transmission rates and save lives.

United States Healthcare Data Breaches: Insights for NIST SP 800-66 Revision 2 from a Review of the NIST SP 800-66 Revision 1

Healthcare security and privacy breaches are occurring in the United States (US), and increased substantially during the pandemic. This paper reviews the National Institute of Standards and Technology (NIST) publication base as an effective solution. The NIST Special Publication 800-66 Revision 1 was an essential standard in US healthcare, which was withdrawn in February 2024 and superseded by SP 800-66 Revision 2. This review investigates the academic papers concerning the application of the NIST SP 800-66 Revision 1 standard in the US healthcare literature. A systematic review method was used in this study to determine current knowledge gaps of the SP 800-66 Revision 1. Some limitations were employed in the search to enforce validity. A total of eleven articles were found eligible for the study. Consequently, this study suggests the necessity for additional academic papers pertaining to SP 800-66 Revision 2 in the US healthcare literature. In turn, it will enhance awareness of safeguarding electronic protected health information (ePHI), help to mitigate potential future risks, and eventually reduce breaches.

Parameter Identification in Traveling Wave Solutions of a Modified Fisher’s Equation

In this work, we focus on the inverse problem of determining the parameters in a partial differential equation from given numerical solutions. For this purpose, we consider a modified Fisher’s equation that includes a relaxation time in relating the flux to the gradient of the density and an added cubic non-linearity. We show that such equations still possess traveling wave solutions by using standard methods for nonlinear dynamical systems in which fixed points in the phase plane are found and their stability characteristics are classified. A heteroclinic orbit in the phase plane connecting a saddle point to a node represents the traveling wave solution. We then design parameter estimation/discovery algorithms for this system including a few based on machine learning methods and compare their performance.

Dynamics and Equilibria of N Point Charges on a 2D Ellipse or a 3D Ellipsoid

We consider the so-called Thomson problem which refers to finding the equilibrium distribution of a finite number of mutually repelling point charges on the surface of a sphere, but for the case where the sphere is replaced by a spheroid or ellipsoid. To get started, we first consider the problem in two dimensions, with point charges on circles (for which the equilibrium distribution is intuitively obvious) and ellipses. We then generalize the approach to the three-dimensional case of an ellipsoid. The method we use is to begin with a random distribution of charges on the surface and allow each point charge to move tangentially to the surface due to the sum of all Coulomb forces it feels from the other charges. Deriving the proper equations of motion requires using a projection operator to project the total force on each point charge onto the tangent plane of the surface. The position vectors then evolve and find their final equilibrium distribution naturally. For the case of ellipses and ellipsoids or spheroids, we find that multiple distinct equilibria are possible for certain numbers of charges, depending on the starting conditions. We characterize these based on their total potential energies. Some of the equilibria found turn out to represent local minima in the potential energy landscape, while others represent the global minimum. We devise a method based on comparing the moment-of-inertia tensors of the final configurations to distinguish them from one another.

资源型城市财源建设的风险识别与制度优化路径--以陕西省延安市为例

1994年财税体制改革促成了此后延续至今的改革红利,但其财政分权的改革远未到位,近年来能源富集区经济发展中遇到的地方税收体系建设滞后、地方政府财政困难、提供基本公共服务能力弱等问题均与此密切相关。今后所实施新一轮改革中,财税体制改革是全面深化经济体制改革的核心之一,应重点解决资源富集区矿产资源开发收益没有得到合理分配对地方政府财源建设所带来的风险。本文以陕西省延安市为例,认真分析财源结构、三次产业税收收入、税收收入与非税收收入的状况,以及省市分税的影响,深入研究现行财政分权影响地方财源建设的四大风险:税收与税源分离的风险、三次产业税源结构调整的风险、财政收支缺口的风险和税制改革滞后所引发的潜在风险,并深入剖析问题根源,积极探索优化资源型城市财源建设的制度路径。

基于ADL-ARCH模型的我国外汇干预目标之实证研究

以外汇干预操作中的冲销干预与非冲销干预理论为基础,基于计量经济学时间序列ADL和ARCH模型分别对我国外汇干预目标特征中的逆风向性、波动性和非对称性三大干预特征进行实证检验。通过对中国1996年1月到2009年8月间外汇干预数据进行实证检验,发现我国外汇干预目标的逆风向性和非对称性因素显著,而波动性因素不明显。数据说明我国央行进行外汇干预的针对目标是汇率的变动而不是市场的波动幅度,并且对于升值贬值的干预幅度明显不同。与前人研究结论不同的是:汇率干预目标对于升值表现了较小程度的外汇干预,而对于贬值所表现的干预力度较大。另外,得出了外汇干预的长期持续性特点的实证结果,从而提出了外汇均衡目标的实现需要长期的货币政策配合调整等政策建议。

Low Thrust Minimum Time Orbit Transfer Nonlinear Optimization Using Impulse Discretization via the Modified Picard–Chebyshev Method

The Modified Picard-Chebyshev Method(MPCM)is implemented as an orbit propagation solver for a numerical optimization method that determines minimum time orbit transfer trajectory of a satellite using a series of multiple impulses at intermediate waypoints.The waypoints correspond to instantaneous impulses that are determined using a nonlinear constrained optimization routine,SNOPT with numerical force models for both Two-Body and J2 perturbations.It is found that using the MPCM increases run-time performance of the discretized lowthrust optimization method when compared to other sequential numerical solvers,such as Adams-Bashforth-Moulton and Gauss-Jackson 8th order methods.

Near Term Hybrid Quantum Computing Solution to the Matrix Riccati Equations

The well-known Riccati differential equations play a key role in many fields,including problems in protein folding,control and stabilization,stochastic control,and cybersecurity(risk analysis and malware propaga-tion).Quantum computer algorithms have the potential to implement faster approximate solutions to the Riccati equations compared with strictly classical algorithms.While systems with many qubits are still under development,there is significant interest in developing algorithms for near-term quantum computers to determine their accuracy and limitations.In this paper,we propose a hybrid quantum-classical algorithm,the Matrix Riccati Solver(MRS).This approach uses a transformation of variables to turn a set of nonlinear differential equation into a set of approximate linear differential equations(i.e.,second order non-constant coefficients)which can in turn be solved using a version of the Harrow-Hassidim-Lloyd(HHL)quantum algorithm for the case of Hermitian matrices.We implement this approach using the Qiskit language and compute near-term results using a 4 qubit IBM Q System quantum computer.Comparisons with classical results and areas for future research are discussed.

A Full Asymptotic Series of European Call Option Prices in the SABR Model with Beta = 1

We develop two new pricing formulae for European options. The purpose of these formulae is to better understand the impact of each term of the model, as well as improve the speed of the calculations. We consider the SABR model (with β=1) of stochastic volatility, which we analyze by tools from Malliavin Calculus. We follow the approach of Alòs et al. (2006) who showed that under stochastic volatility framework, the option prices can be written as the sum of the classic Hull-White (1987) term and a correction due to correlation. We derive the Hull-White term, by using the conditional density of the average volatility, and write it as a two-dimensional integral. For the correction part, we use two different approaches. Both approaches rely on the pairing of the exponential formula developed by Jin, Peng, and Schellhorn (2016) with analytical calculations. The first approach, which we call “Dyson series on the return’s idiosyncratic noise” yields a complete series expansion but necessitates the calculation of a 7-dimensional integral. Two of these dimensions come from the use of Yor’s (1992) formula for the joint density of a Brownian motion and the time-integral of geometric Brownian motion. The second approach, which we call “Dyson series on the common noise” necessitates the calculation of only a one-dimensional integral, but the formula is more complex. This research consisted of both analytical derivations and numerical calculations. The latter show that our formulae are in general more exact, yet more time-consuming to calculate, than the first order expansion of Hagan et al. (2002).

A Poisson Solver Based on Iterations on a Sylvester System

We present an iterative scheme for solving Poisson’s equation in 2D. Using finite differences, we discretize the equation into a Sylvester system, AU +UB = F, involving tridiagonal matrices A and B. The iterations occur on this Sylvester system directly after introducing a deflation-type parameter that enables optimized convergence. Analytical bounds are obtained on the spectral radii of the iteration matrices. Our method is comparable to Successive Over-Relaxation (SOR) and amenable to compact programming via vector/array operations. It can also be implemented within a multigrid framework with considerable improvement in performance as shown herein.

A Possible Role of the Gailitis Resonance in Muon Catalyzed Fusion

In a previous JMP article published May 2013, a comprehensive calculation was presented for all properties of a number of long-life s-state Gailitis resonances lying just above the PS(n = 2) formation threshold in a positron-Hydrogen scattering system. The six open-channel calculation was carried out by solving a set of four hundred thousand coupled linear equations. The modified Faddeev equation was used to obtain the wave-amplitude for each of the six open channels. Details can be found in reference [1] 08D0C9EA79F9BACE118C8200AA004BA90B02000000080000000E0000005F005200650066003400300037003200380034003600370034000000 . This note presents some qualitative properties of Gailitis resonances in the scattering systems of d + tu just above the thresholds of the opening of a new channel of the muonic atoms tu(n) or du(n), n > 2 is the principal quantum number. u is a negatively charged muon, d and t are the nuclei of the two isotopes of the Hydrogen atom with one and two neutrons in the nucleus respectively. We study the possible decay channels of some of the long-life Gailitis resonances. Of particular interest is a transition directly from a Gailitis (3-body) resonance to the bound states dtu molecular ions via a radiative emission of a photon or an external auger ejection of a nearby electron. Possible experimental evidence will be presented.

Long-Range Correlation in Positron-Hydrogen Scattering System near the Threshold of <i>Ps</i>(<i>n</i>= 2) Formation

This is a short report of a recently uncovered resonant phenomenon. The modified Faddeev equation that correctly includes all six open channels is used. The calculation is carried out in s-partial wave. We report a number of resonant peaks in the elastic cross sections as well as the wave amplitudes involved. This is the energy region where the Stark-effect induced electric dipole energy split in the target dominates the physics and the Long-Range behavior of the 3-body scattering system. It is found that when the center of mass collision energy in the new channels is in integer proportion to the corresponding electric dipole energy split, Bremsstrahlung photon mediated resonant scattering occurs. The corresponding wave amplitudes deform into wave-packets hundreds to thousands of Bohr radii in width. The physical implication of this phenomenon will be discussed.

足球在美国:一个边缘化的故事

正如桑巴特指出了美国缺乏他所谓的“社会主义”一样 ,我们又看到了在整个 2 0世纪足球在美国体育文化中的缺乏。美国早期而全面的资产阶级化 ,创造了这两种“例外论” ,其遗产至今尚存。虽然在最近几年 ,美国取得了世界杯赛的胜利 ,但足球在美国的体育文化中始终处于边缘化状态。至少从任何有意义的层面来看 ,美国依然没有足球。

Why and When Can Deep-but Not Shallow-networks Avoid the Curse of Dimensionality: A Review

The paper reviews and extends an emerging body of theoretical results on deep learning including the conditions under which it can be exponentially better than shallow learning. A class of deep convolutional networks represent an important special case of these conditions, though weight sharing is not the main reason for their exponential advantage. Implications of a few key theorems are discussed, together with new results, open problems and conjectures.

Stochastic Gradient Descent for Linear Systems with Missing Data

Traditional methods for solving linear systems have quickly become imprac-tical due to an increase in the size of available data.Utilizing massive amounts of data is further complicated when the data is incomplete or has missing entries.In this work,we address the obstacles presented when working with large data and incom-plete data simultaneously.In particular,we propose to adapt the Stochastic Gradient Descent method to address missing data in linear systems.Our proposed algorithm,the Stochastic Gradient Descent for Missing Data method(mSGD),is introduced and theoretical convergence guarantees are provided.In addition,we include numerical experiments on simulated and real world data that demonstrate the usefulness of our method.

Series Representation of Jointly S˛S Distribution via Symmetric Covariations

We introduce the notion of symmetric covariation,which is a new measure of dependence between two components of a symmetricα-stable random vector,where the stability parameterαmeasures the heavy-tailedness of its distribution.Unlike covariation that exists only whenα∈(1,2],symmetric covariation is well defined for allα∈(0,2].We show that symmetric covariation can be defined using the proposed generalized fractional derivative,which has broader usages than those involved in this work.Several properties of symmetric covariation have been derived.These are either similar to or more general than those of the covariance functions in the Gaussian case.The main contribution of this framework is the representation of the characteristic function of bivariate symmetricα-stable distribution via convergent series based on a sequence of symmetric covariations.This series representation extends the one of bivariate Gaussian.

An infinite-dimensional model of liquidity in financial markets

We consider a dynamic market model of liquidity where unmatched buy and sell limit orders are stored in order books.The resulting net demand surface constitutes the sole input to the model.We model demand using a two-parameter Brownian motion because(i)different points on the demand curve correspond to orders motivated by different information,and(ii)in general,the market price of risk equation of no-arbitrage theory has no solutions when the demand curve is driven by a finite number of factors,thus allowing for arbitrage.We prove that if the driving noise is infinite-dimensional,then there is no arbitrage in the model.Under the equivalent martingale measure,the clearing price is a martingale,and options can be priced under the no-arbitrage hypothesis.We consider several parameterizations of the model and show advantages of specifying the demand curve as a quantity that is a function of price,as opposed to price as a function of quantity.An online appendix presents a basic empirical analysis of the model:calibration using information from actual order books,computation of option prices using Monte Carlo simulations,and comparison with observed data.

Economic relations and the public image of China in Latin America:A cross-country time-series analysis

This article investigates the impact of Chinese economic activities in Latin America on the national image of China in the region.Using economic and public opinion data from 17 Latin American countries from 2001 to 2016,this work relates cross-national time-series variations regarding China’s image in Latin America to changes in the economic ties(such as trade,FDI,and contracts)between the perceiving countries and China.Controlling for the size of the economy and the level of its development,the statis-tical analysis indicates that trade surplus against China in Latin America has a positive effect on the public perceptions of China in the region,while Chinese FDI outflows to Latin America lead to a negative effect.The effects of Chinese contracts,imports,and exports tend not to be statistically significant.We also find less developed Latin American countries with low life expectancy and low educational attainment tend to have a more positive view of China than their richer counterparts in the region.Finally,we find that Latin American countries under presidents with left-wing ideology have a much more positive view of China than countries under presidents with other ideological preferences.Diplomatic relations with China and China’s soft power influence as indexed by the presence of Confucius Institutes do not exhibit a strong impact on China’s national image in Latin America,compared with the dominant political ideology in a Latin American country as reflected in the president’s ideology.

Vegetarian diets,circulating miRNA expression and healthspan in subjects living in the Blue Zone

A long-term vegetarian diet plays a role in the longevity and maintenance of the healthspan,but the underlying mechanisms for these observations are largely unknown.Particularly,it is not known whether a longterm vegetarian dietary pattern may affect the circulating miRNA expression in such a way as to modulate the healthspan.The Adventist Health Study-2(AHS-2)cohort includes a large number of older adults who primarily follow vegetarian dietary patterns and reside in Loma Linda,California,one of five“Blue Zones”in the world in which a higher proportion of the population enjoys a longer than average lifespan.We performedmiRNA-seq in 96 subjects selected from the AHS-2 cohort with different dietary patterns.We identified several differentially expressed miRNAs between vegetarians and non-vegetarians,which are involved in immune response and cytokine signaling,cell growth and proliferation as well as age-related diseases such as cardiovascular diseases and neurodegenerative diseases.Overall,our study showed that a vegetarian diet modulates aging-associated circulating miRNAs in a sex-dependent manner of differential expression for certain miRNAs,which may be related in a beneficial manner to the healthspan.Further investigation is needed to validate these miRNAs as potential biomarkers for diet-modulated longevity in humans.