Number Of Conditions Research Articles

Telehealth Utilization and Associations in the United States During the Third Year of the COVID-19 Pandemic: Population-Based Survey Study in 2022.

The COVID-19 pandemic rapidly changed the landscape of clinical practice in the United States; telehealth became an essential mode of health care delivery, yet many components of telehealth use remain unknown years after the disease's emergence. We aim to comprehensively assess telehealth use and its associated factors in the United States. This cross-sectional study used a nationally representative survey (Health Information National Trends Survey) administered to US adults (≥18 years) from March 2022 through November 2022. To assess telehealth adoption, perceptions of telehealth, satisfaction with telehealth, and the telehealth care purpose, we conducted weighted descriptive analyses. To identify the subpopulations with low adoption of telehealth, we developed a weighted multivariable logistic regression model. Among a total of 6252 survey participants, 39.3% (2517/6252) reported telehealth use in the past 12 months (video: 1110/6252, 17.8%; audio: 876/6252, 11.6%). The most prominent reason for not using telehealth was due to telehealth providers failing to offer this option (2200/3529, 63%). The most common reason for respondents not using offered telehealth services was a preference for in-person care (527/578, 84.4%). Primary motivations to use telehealth were providers' recommendations (1716/2517, 72.7%) and convenience (1516/2517, 65.6%), mainly for acute minor illness (600/2397, 29.7%) and chronic condition management (583/2397, 21.4%), yet care purposes differed by age, race/ethnicity, and income. The satisfaction rate was predominately high, with no technical problems (1829/2517, 80.5%), comparable care quality to that of in-person care (1779/2517, 75%), and no privacy concerns (1958/2517, 83.7%). Younger individuals (odd ratios [ORs] 1.48-2.23; 18-64 years vs ≥75 years), women (OR 1.33, 95% CI 1.09-1.61), Hispanic individuals (OR 1.37, 95% CI 1.05-1.80; vs non-Hispanic White), those with more education (OR 1.72, 95% CI 1.03-2.87; at least a college graduate vs less than high school), unemployed individuals (OR 1.25, 95% CI 1.02-1.54), insured individuals (OR 1.83, 95% CI 1.25-2.69), or those with poor general health status (OR 1.66, 95% CI 1.30-2.13) had higher odds of using telehealth. To our best knowledge, this is among the first studies to examine patient factors around telehealth use, including motivations to use, perceptions of, satisfaction with, and care purpose of telehealth, as well as sociodemographic factors associated with telehealth adoption using a nationally representative survey. The wide array of descriptive findings and identified associations will help providers and health systems understand the factors that drive patients toward or away from telehealth visits as the technology becomes more routinely available across the United States, providing future directions for telehealth use and telehealth research.

Reentry trajectory planning for hypersonic vehicles via an improved sequential convex programming method

The reentry trajectory planning problem of hypersonic vehicles is generally a continuous and nonconvex optimization problem. The solution efficiency and convergence properties of the planning algorithm become an essential point when considering the practical application scenarios. In this paper, an augmented-Lagrange-based improved sequential convex programming algorithm is proposed to solve it and achieve superior solutions with higher accuracy and efficiency. Firstly, the mapped Chebyshev pseudo-spectral method is utilized to convert the continuous optimal control problem into a highly approximately discretized one. In this framework, the discretization technique is employed to discretize the states and control variables at the time interval, which leads to the improvement of ill-conditioned differential matrix and better approximation properties of the variables. Moreover, by introducing slack variables, automatically updated penalty parameters and Lagrange multipliers during the convexification processing, the original nonconvex problem is transformed into an augmented-Lagrange-function-formed relaxed convex one. Then, the arrived convex subproblem can be solved iteratively by the matured interior-point method until the predetermined precision is satisfied. Based on this transformation, it can effectively alleviate the numerical difficulty and improve the convergence property of the proposed improved sequential convex programming algorithm. Finally, Rigorous theoretical analysis is conducted to prove that the solution sequence generated by the proposed algorithm could converge to an approximate global solution of the original problem. Numerical simulations are also presented, and it is demonstrated that the solution time of the proposed algorithm is more than 95% less than that of the traditional nonlinear programming methods without losing the merits of high precision.

Serial indirect effects from childhood maltreatment to adult chronic health conditions through contemporary family relationships and mental health problems: Inquiry into sleep disturbances and stress.

Childhood maltreatment accelerates biological aging, leaving adults vulnerable to chronic health problems. There is robust evidence that social relationships, including those with family members, may influence chronic health problems through psychological pathways, but there is little research considering stress and sleep problems, especially among adults who experienced childhood maltreatment. Furthermore, longitudinal research is lacking related to maltreatment and chronic health problems. The current study examined familial support and strain and subsequent sleep problems and stress in a serial mediational model linking childhood maltreatment to chronic health problems over time. Using three waves of data from the study of Midlife Development in the United States (N = 859; 55.8% female), structural equation modeling was used to examine familial support, strain, stress, and sleep problems in serial mediational model linking maltreatment to the number of chronic health conditions over a 9-year period. Childhood maltreatment was indirectly associated with a number of chronic health conditions through familial support and strain through subsequent reports of stress. Although family support was associated with fewer sleep problems, the bootstrapped indirect effect was not significant. Simple indirect effects from maltreatment to the number of chronic health problems were significant through both sleep problems and stress. Contemporary family relationships and psychological problems are possible points of prevention and intervention reducing the number of chronic health conditions among adults who were maltreated in childhood. Focusing on familial relationships and stress processes may be particularly fruitful. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

294 Strategies for engaging patients in building a model for patient partner engagement to accelerate translational science

OBJECTIVES/GOALS: To describe the strategies our newly created Patient Partners Program has planned for engaging diverse patients in the co-creation of our planned Patient Partner Academy. We will elicit feedback from other CTSAs about their strategies for promoting individual patient partnerships in research. METHODS/STUDY POPULATION: Our program to promote authentic patient-researcher partnerships to advance clinical and translational research is grounded in participatory approaches to maximize meaningful engagement. The process of creating our Patient Partners Academy is co-led by a patient partner and national leader in re-envisioning the role of patients in research, and a University of Michigan faculty member who advocates for patient partnerships in research. Listening sessions and community engagement studios will involve the developers of patient partner training programs, patient partners who have received research capacity training (as well as researchers and patient partners interested in collaborative research. Insights from these sessions will inform the development of learning models and curriculum content. RESULTS/ANTICIPATED RESULTS: Through individual listening sessions and community engagement studios we will collect data on the barriers and facilitators to patient partner engagement in research and the experiences and preferred learning models in patient partner training programs. Both the listening sessions and community engagement studios will be recorded, transcribed, and analyzed for common themes. We aim to answer three questions: What do patient partners need to be meaningfully engaged as equal partners across the research continuum? How can we best engage people who experience serious illness or chronic conditions and may be underserved by healthcare systems? What do researchers, faculty, and clinicians need to create trusting, collaborative relationships with patient partners? DISCUSSION/SIGNIFICANCE: Integrating patient partners into study teams accelerates innovation and translational science, increases the relevance of research findings, improves health outcomes and patient empowerment, and elevates the value of the patient perspective allowing researchers to gain a new point of view from an individual with lived experience.

Liraglutide-Induced Depression with Suicidality in an Obese Adult: A Case Report

Obesity is a major health issue worldwide. Treating adults with obesity often involves lifestyle and diet changes and sometimes medication. Liraglutide is a drug that is being closely studied for treating obesity. However, the potential side effects of liraglutide, particularly its impact on mood and the development of depression, may be of concern. Given the frequent co-occurrence of obesity and depression, it is important to understand how obesity treatments like liraglutide might affect a person’s mood. A 47-year-old schoolteacher with no personal or family history of mental illness or chronic physical condition sought help for his steadily increasing weight. Despite having a sedentary job and reporting no major stress or substance use, he did not attempt to change his diet or activity level, occasionally experiencing sleep difficulties. He was overweight, with a body mass index of 42. The patient was diagnosed with adult obesity and prescribed liraglutide, diet changes, and exercise. Initially, he lost weight, but he also developed depressive symptoms, including fatigue, loss of interest, sleep disturbances, and suicidal ideation. Following cessation of liraglutide treatment, his depression symptoms got better, but his weight slightly increased. This case sheds light on the possible link between liraglutide and depression in managing obesity. It is crucial for healthcare providers to be aware of potential mental health side effects of obesity drugs like liraglutide. Although the exact reasons behind these mood changes are not fully understood, this case emphasizes the need for careful observation and decision-making in treatment. Understanding these issues can help balance the benefits and risks of liraglutide and ensure better care and treatment options for people with obesity.

Analytical solutions for dispersions and waveforms of acoustic logging in a cased hole

Acoustic logging is one of the most promising methods for the quantitative evaluation of cement bond conditions in cased holes. However, inefficient use of full-wave information yields unsatisfactory interpretation accuracy. Fundamentally, this is because the wavefield characteristics have not been thoroughly investigated under various cement bonding conditions. Thus, this study derives analytical solutions of wavefields for a single-cased-hole model and emphasizes the dispersion calculation algorithm. To solve the dispersion equation when solving for the poles of the propagating modes with real wavenumbers, we renormalize the Bessel function related to the borehole fluid by multiplying it with an attenuation factor. For leaky modes with complex wavenumbers, we develop a novel method to find local peaks of the matrix condition number (LPMCN) in the frequency domain to determine dispersion poles, avoiding the local optimization issues resulting from the traditional Gauss-Newton iteration method. Combining these two methods, we establish a fast and accurate workflow for evaluating the dispersion of all modes in cased holes using a relatively fast bisection method to manage the dispersion of the propagating modes and using the LPMCN method to derive the dispersion curves of leaky modes. Furthermore, all propagating modes are individually investigated in the monopole measurement by evaluating the residues of the real poles in a casing-free model. The analysis demonstrates that the first-order pseudo-Rayleigh wave (PR1) and inner Stoneley wave (ST1) are the two strongest modes. Finally, we focus on the waveforms and dispersion characteristics of the outer Stoneley wave (ST2) related to the fluid channel in the cement annulus. The results reveal that as the fluid thickness increases, the phase velocity of the ST2 mode decreases, and its amplitude increases. Therefore, the ST2 mode can potentially evaluate the thickness of the fluid channel in a cement annulus if an effective weak-signal-extraction method is used.

Decentralized Sum-of-Nonconvex Optimization

We consider the optimization problem of minimizing the sum-of-nonconvex function, i.e., a convex function that is the average of nonconvex components. The existing stochastic algorithms for such a problem only focus on a single machine and the centralized scenario. In this paper, we study the sum-of-nonconvex optimization in the decentralized setting. We present a new theoretical analysis of the PMGT-SVRG algorithm for this problem and prove the linear convergence of their approach. However, the convergence rate of the PMGT-SVRG algorithm has a linear dependency on the condition number, which is undesirable for the ill-conditioned problem. To remedy this issue, we propose an accelerated stochastic decentralized first-order algorithm by incorporating the techniques of acceleration, gradient tracking, and multi-consensus mixing into the SVRG algorithm. The convergence rate of the proposed method has a square-root dependency on the condition number. The numerical experiments validate the theoretical guarantee of our proposed algorithms on both synthetic and real-world datasets.

LERE: Learning-Based Low-Rank Matrix Recovery with Rank Estimation

A fundamental task in the realms of computer vision, Low-Rank Matrix Recovery (LRMR) focuses on the inherent low-rank structure precise recovery from incomplete data and/or corrupted measurements given that the rank is a known prior or accurately estimated. However, it remains challenging for existing rank estimation methods to accurately estimate the rank of an ill-conditioned matrix. Also, existing LRMR optimization methods are heavily dependent on the chosen parameters, and are therefore difficult to adapt to different situations. Addressing these issues, A novel LEarning-based low-rank matrix recovery with Rank Estimation (LERE) is proposed. More specifically, considering the characteristics of the Gerschgorin disk's center and radius, a new heuristic decision rule in the Gerschgorin Disk Theorem is significantly enhanced and the low-rank boundary can be exactly located, which leads to a marked improvement in the accuracy of rank estimation. According to the estimated rank, we select row and column sub-matrices from the observation matrix by uniformly random sampling. A 17-iteration feedforward-recurrent-mixed neural network is then adapted to learn the parameters in the sub-matrix recovery processing. Finally, by the correlation of the row sub-matrix and column sub-matrix, LERE successfully recovers the underlying low-rank matrix. Overall, LERE is more efficient and robust than existing LRMR methods. Experimental results demonstrate that LERE surpasses state-of-the-art (SOTA) methods. The code for this work is accessible at https://github.com/zhengqinxu/LERE.

Biased regression algorithms in the quaternion domain

The ill-conditioned matrix problem in quaternion linear regression models is addressed in this paper and several dimension-reduction based regression methods for circumventing this problem are suggested. The algorithms are formulated in a general way and can be easily adapted to different scenarios: widely linear, semi-widely linear and strictly linear processing, in accordance with the properness properties presented by quaternion random vectors. A comparison with existing solutions is carried out by using both laboratory data and a color face database.

Streptococcus agalactiae serotype Ia capsular polysaccharide production from a Brazilian strain

The pathogen S. agalactiae, categorized as Lancefield group B streptococci (GBS), is a Gram-positive bacterium, encapsulated, anaerobic facultative bacillus, which occurs in pairs or short chains. It was responsible for more than 319,000 cases of infections in neonates. Early and late streptococci, in the course of an illness or medical condition, are infections that have high mortality and morbidity rates, with an incidence of 2.0 to 5.0 per 1000 live births in North America, Europe, and Australia. The infection of newborns usually happens through transmission from infected mothers during and after childbirth, with GBS being among the critical bacterial infections in the Brazilian epidemiological picture. S. agalactiae strains isolated from different regions of Brazil, indicate a great diversity among the isolated serotypes but with a higher incidence of serotype Ia. Publications report that, in pregnant women in Brazil, the prevalence of serotype Ia has been constant between 2002 and 2018, followed by serotypes II and IV. Serotypes Ib, III, and V also appear, but with some fluctuations in different regions of the country. The pathogen which causes invasive disease are usually surrounded by a polysaccharide capsule and is its major virulence factor, being that the key antigen in protective response triggered by polysaccharides and, more recently, protein-polysaccharide conjugate vaccines. The development of antibiotic resistance by these microorganisms to different antibiotics has been the guideline in leading therapeutic options against these infections including the use of prophylactic vaccines in pregnant women, immunosuppressed or older people. Such prophylactic alternatives can be constructed from capsular polysaccharides.Based on the experience in the production and purification of Neisseria meningitidis polysaccharides for vaccines, Bio-Manguinhos developed a process for the production, purification and characterization of S. agalactiae Ia polysaccharides. In the present study, the capsular polysaccharide from the strain isolated in clinical material of a public hospital, in Rio de Janeiro – Brazil, was obtained from simple batch cultures, with purification process achieving about 20 mg g−1 in yield for cell dry weight (CDW) and ca. of 100 % of purity. Hence, to prove that the CPS of GBS Ia can be consistently produced, purified, and characterized by NMR, HRGC-MS, and SEC-MALS – from such strain – to be used in vaccine productions against S. agalactiae.

Relaxed static output stabilization of polynomial fuzzy control systems by Lagrange membership functions

AbstractThis article is concerned with the stability analysis of the static output‐feedback polynomial fuzzy‐model‐based (SOF PFMB) control systems through designing a novel membership grade integration (MGI) approach. The nonconvex problems of the SOF PFMB control systems are convexificated into the convex conditions by introducing block diagonal positive‐definite Lyapunov matrix and nonsingular transformation matrix. We proposed new approximate membership functions, that is, Lagrange membership functions (LMFs), which can be introduced into the stabilization process to relieve the conservativeness of stability results. The LMFs are general representations of piecewise‐linear membership functions, which makes the number of stability conditions not limited by the number of sample points. In a fixed subdomain, arbitrary sample points can be employed by the LMFs method and achieve higher approximation capability by increasing more sample points so that membership grades can be incorporated into the system analysis. Furthermore, a novel MGI approach, including the information of premise variables and LMFs, is proposed making the stability conditions more relaxed. Finally, two simulation examples show the merits of the developed techniques.

Construction and forward kinematics of a novel reconfigurable parallel mechanism

In this paper, a kind of hybrid kinematics chain with variable constraints is constructed by using a 6R spatial bifurcated chain and 4-DOF serial limbs, by using them, a 3-DOF Reconfigurable Parallel Mechanisms (RPM) was constructed, which has four motion modes: 3T, 2T1R, 2R1T, and 3R motion modes. Using screw theory, the change of wrench system in the hybrid kinematics chain caused by the reconfiguration of the 6R bifurcated chain is analyzed, which affects the wrench system of the moving platform (MP), and thus causes the reconfiguration of the parallel mechanism (PM). The triangular pyramid fixed to the MP was found as auxiliary geometry and used to intuitively describe the constraint relationship between joint axes in limbs. The latter was used to establish a unified forward kinematics model of the RPM in four motion modes. The general forward kinematics solution procedure for this type of RPM is given. The overall Jacobian matrix was obtained by screw theory for singularity analysis. The condition number of the Jacobian matrix measures the degree to which the mechanism is close to the singular configuration. Based on the Monte Carlo simulation, point cloud images representing the workspace of RPM were obtained.

Band structure calculations of three-dimensional solid-fluid coupling phononic crystals using dual reciprocity boundary element method and wavelet compression method

The algorithm for calculating the band structures of two-dimensional phononic crystals (PCs) using the boundary element method (BEM) has been proposed for many years. However, it has not yet been extended to three-dimensional (3D) PCs because the fundamental solutions of 3D dynamics are complex and are related to angular frequency. In this study, the BEM is applied to calculate the band structures of 3D solid-fluid coupling PCs by combining the dual reciprocity method. The use of the dual reciprocity method can help avoid nonlinear eigenvalue problems. To address the limitation of fully populated matrices in BEM, the wavelet compression method based on B-spline wavelet on the interval is adopted. Some small matrix entries, which are generated by the vanishing moment and local support characteristics, are set to zero using the provided truncation technique. This process results in the production of sparse matrices. The constructed generalized linear eigenvalue equations are modified to tackle the ill-conditioned matrix issues arising from the distinct fundamental solutions of solids and fluids. The results show that this method is superior to the finite element method in terms of calculation efficiency. Compared to conventional BEM, the current wavelet BEM can not only generate sparse matrices but also reduce the integration calculation time when handling large-scale problems.

The least squares finite element method for elasticity interface problem on unfitted mesh

In this paper, we propose and analyze the least squares finite element methods for the linear elasticity interface problem in the stress-displacement system on unfitted meshes. We consider the cases that the interface is $C^2$ or polygonal, and the exact solution $(\bsigma, \bu)$ belongs to $H^s(\div; \Omega_0   \cup \Omega_1) \times H^{1+s}(\Omega_0 \cup \Omega_1)$ with $s > 1/2$. Two types of least squares functionals are defined to seek the numerical solution.  The first is defined by simply applying the $L^2$ norm least squares principle, and requires the condition $s \geq 1$. The second is defined with a discrete minus norm, which is related to the inner product in $H^{-1/2}(\Gamma)$. The use of this discrete minus norm results in a method of optimal convergence rates and allows the exact solution has the regularity of any $s > 1/2$.  The stability near the interface for both methods is guaranteed by the ghost penalty bilinear forms and we can derive the robust condition number estimates.  The convergence rates under $L^2$ norm and the energy norm are derived for both methods.  We illustrate the accuracy and the robustness of the proposed methods by a series of numerical experiments for test problems in two and three dimensions.

Importance of kidney function, number of chronic conditions and medications for hospitalisation in elderly in Blekinge County, Sweden: a case–control study

ObjectivesTo study the association between risk for hospitalisation in an elderly population related to renal function, number of chronic diseases and number of prescribed drugs.DesignA case–control study. Persons hospitalised were...

Comparing the Performance of Two Butcher-Based Block Hybrid Algorithms for the Solution of Initial Value Problems

In this paper, we compare the performances of two Butcher-based block hybrid methods for the numerical integration of initial value problems. We compare the condition numbers of the linear system of equations arising from both methods and the absolute errors of the solution obtained. The results of the numerical experiments illustrate that the better conditioned method outperformed its less conditioned counterpart based on the absolute errors. In addition, after applying our method on some examples, it was discovered that the absolute errors in this work were better than those of a recent study in the literature. Hence, we recommend this method for the numerical solution of stiff and non-stiff initial value problems.

Towards Understanding of the Plastic Zone Thermal Residual Stresses in Functionally Graded Materials

Abstract: Functionally graded materials (FGM’s) are advanced composites consisting of two or more materials whose composition and structure changes gradually over the volume, leading to gradual change in its property. Typically one component is a ceramic, while the other is metal or metal alloy. In common embodiments, the composition can change gradually from all ceramic on one side to all metal on the other side, the ceramic contributing high resistance to temperature with the metal contributing high ductility. It’s a way to incorporate favorable properties of two materials into different locations of a single structure. In ideal cases the composition changes gradually but for manufacturing reasons, the changes occurs in homogeneous layers. The boundaries between the layers cause thermal residual stresses to arise, especially during material processing and in cases of cyclic loading. These thermal residual stresses are a result of differences in the thermal expansion coefficient of the varying compositions of materials. Thermal residual stresses may lead to cracking and ultimate failure of FGM’s. This study investigates the formation of thermal residual stresses for a Nickel-Alumina Ni-Al₂O₃ FGM. The Ni-Al₂O₃ system is chosen because it is one of the most common systems used in practice. This work explores the formation, impact and minimization of thermal residual stresses for a number of practical conditions that may arise during processing. All relevant properties are calculated using the rule of mixture equations.

Evaluation of the Level of Serum Interleukin-10 Depending on the Demographic and General Clinical and Laboratory Characteristics of the Coronavirus Disease-19 in Hospitalized Patients

Evaluation of the Level of Serum Interleukin-10 Depending on the Demographic and General Clinical and Laboratory Characteristics of the Coronavirus Disease-19 in Hospitalized Patients

Minimizing the Formation of Thermal Residual Stresses of the Elastic Zone in Functionally Graded Materials

Abstract: Functionally graded materials (FGM’s) are advanced composites consisting of two or more materials whose composition and structure changes gradually over the volume, leading to gradual change in its property. Typically one component is a ceramic, while the other is metal or metal alloy. In common embodiments, the composition can change gradually from all ceramic on one side to all metal on the other side, the ceramic contributing high resistance to temperature with the metal contributing high ductility. It’s a way to incorporate favorable properties of two materials into different locations of a single structure. In ideal cases the composition changes gradually but for manufacturing reasons, the changes occurs in homogeneous layers. The boundaries between the layers cause thermal residual stresses to arise, especially during material processing and in cases of cyclic loading. These thermal residual stresses are a result of differences in the thermal expansion coefficient of the varying compositions of materials. Thermal residual stresses may lead to cracking and ultimate failure of FGM’s. This study investigates the formation of thermal residual stresses for a Nickel-Alumina Ni-Al₂O₃ FGM. The Ni-Al₂O₃ system is chosen because it is one of the most common systems used in practice. This work explores the formation, impact and minimization of thermal residual stresses for a number of practical conditions that may arise during processing. All relevant properties are calculated using the rule of mixture equations. Abaqus, a non-linear FEA solver, is used for all the simulation work. In addition, the study highlights the need for examining elasto-plastic analysis to illuminate the process of crack development which is our future research goal.

Finite Element Modeling of the Plastic Zone Thermal Residual Stresses in Functionally Graded Materials

Abstract: Functionally graded materials (FGM’s) are advanced composites consisting of two or more materials whose composition and structure changes gradually over the volume, leading to gradual change in its property. Typically one component is a ceramic, while the other is metal or metal alloy. In common embodiments, the composition can change gradually from all ceramic on one side to all metal on the other side, the ceramic contributing high resistance to temperature with the metal contributing high ductility. It’s a way to incorporate favorable properties of two materials into different locations of a single structure. In ideal cases the composition changes gradually but for manufacturing reasons, the changes occurs in homogeneous layers. The boundaries between the layers cause thermal residual stresses to arise, especially during material processing and in cases of cyclic loading. These thermal residual stresses are a result of differences in the thermal expansion coefficient of the varying compositions of materials. Thermal residual stresses may lead to cracking and ultimate failure of FGM’s. This study investigates the formation of thermal residual stresses for a Nickel-Alumina Ni-Al₂O₃ FGM. The Ni-Al₂O₃ system is chosen because it is one of the most common systems used in practice. This work explores the formation, impact and minimization of thermal residual stresses for a number of practical conditions that may arise during processing. All relevant properties are calculated using the rule of mixture equations. Abaqus, a non-linear FEA solver, is used for all the simulation work. In addition, the study includes an elasto-plastic analysis to illuminate the process of crack development.