Hasil untuk "Miscellaneous systems and treatments"

Bhavya Vijay, Poornima Devkumar, Gargi Saha et al.

Background: Obesity is a rising risk factor for various diseases including cardiovascular diseases and Cancer. The limitations of targeted obesity-treatment approaches employed in the clinic presently underscore the importance of developing integrative management strategies for identification of specific biomarkers of obesity. Objectives: Given the specificity of exosome/extracellular vesicle (EV) biomarkers, we aimed here to identify the EV biomarkers of Ayurveda treatment – Lekhana Basti – for Obesity. Methodology: A total of eighteen 24-h urine samples from 6 participants with BMI>30 kg/m2 were used in this study, collected over 3 time-points during the Lekhana basti (medicated enema for obesity) treatment. Urine EV were isolated using Polyethylene Glycol (PEG). The proteins were resolved by 1-d gel electrophoresis and identified using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) and quantified by label-free methods. Significant Protein-Protein Interactions, KEGG pathway analysis and enrichment, functional gene ontology (GO) annotation were identified and shortlisted in comparison to Obesity reference genes from DisGeNET. Results: With UniProt as a reference subsequent to LC-MS/MS-identification, a total of 210 exosome proteins were identified. Seventy-three proteins were overexpressed in pathway enrichment analysis. Further, GO functional annotation identified 15 common proteins involved. Finally, the 8 hub proteins associated with obesity were identified and their differential expression profile compared between three different time-points during Lekhana Basti treatment. Six protein markers overexpressed during obesity were downregulated post Lekhana Basti treatment, while 2 markers increased in abundance post-treatment. Conclusion: To our knowledge, this is the first study to isolate and identify urine EV protein abundance profiles from obese female participants of India. The study results indicate significant changes in the differential expression profile of 8 hub proteins involved in obesity, after Lekhana Basti treatment. The biomarker signature of the pilot study indicates the role of Ayurveda treatment and the possible pathways involved in the treatment of Obesity. Further, this study underlines the specificity of urine exosomes/EV as diagnostic markers as well as the potential of Ayurveda treatment in effective management of obesity.

Anh Tung Nguyen, Sribalaji C. Anand, André M. H. Teixeira

This paper quantifies the security of uncertain interconnected systems under stealthy data injection attacks. In particular, we consider a large-scale system composed of a certain subsystem interconnected with an uncertain subsystem, where only the input-output channels are accessible. An adversary is assumed to inject false data to maximize the performance loss of the certain subsystem while remaining undetected. By abstracting the uncertain subsystem as a class of admissible systems satisfying an $\mathcal{L}_2$ gain constraint, the worst-case performance loss is obtained as the solution to a convex semi-definite program depending only on the certain subsystem dynamics and such an $\mathcal{L}_2$ gain constraint. This solution is proved to serve as an upper bound for the actual worst-case performance loss when the model of the entire system is fully certain. The results are demonstrated through numerical simulations of the power transmission grid spanning Sweden and Northern Denmark.

Amila Ravinath, Minhua Ding, Bikshapathi Gouda et al.

The average symbol error probability (SEP) of a 1-bit quantized single-input multiple-output (SIMO) system is analyzed under Rayleigh fading channels and quadrature phase-shift keying (QPSK) modulation. Previous studies have partially characterized the diversity gain for selection combining (SC). In this paper, leveraging a novel analytical method, an exact analytical SEP expression is derived for a 1-bit quantized SIMO system employing QPSK modulation at the transmitter and maximum ratio combining (MRC) at the receiver. The corresponding diversity and coding gains of a SIMO-MRC system are also determined. Furthermore, the diversity and coding gains of a 1-bit quantized SIMO-SC system are quantified for an arbitrary number of receive antennas, thereby extending and complementing prior results.

Adedeji D. Atere, Ebunoluwa O. Oyewole, Yekeen A. Kosamat et al.

Abstract Background Menopause leads to significant physiological and biochemical alterations that impact different aspects of health, such as bone mineral metabolism and glycemic control. It is imperative to comprehend these alterations in order to identify potential health hazards and develop preventative measures. This comparative cross-sectional study aimed to evaluate bone-associated markers and glycemic control indices in postmenopausal women (PMP). Methods A sample of 100 women aged 30 years or older was randomly selected and categorized into three groups: PMP (n = 60), premenopausal (PRM) (n = 20), and women in the reproductive age group (RWA) (n = 20). Venous blood samples were collected, and fasting blood glucose (FBG), calcium, phosphorus, uric acid, and alkaline phosphatase (ALP) levels were analyzed using standard laboratory techniques. The insulin and estrogen levels were evaluated using enzyme-linked immunosorbent assay (ELISA), and Homeostasis model assessment of insulin resistance (HOMA-IR), Quantitative insulin sensitivity check index (QUICKI), and Fasting insulin resistance index (FIRI) were calculated. A significance level of p < 0.05 was used in the statistical analysis conducted using SPSS version 25.0. Results The PMP and PRM groups showed significantly greater mean values of FBG, insulin, and HOMA-IR when compared to RWA (p < 0.05), while these groups had lower QUICKI levels. Similar trends were noted for bone-associated markers, with significant differences among the groups (p < 0.05). The correlation results showed that QUICKI had positive correlations with both ALP and phosphorus, while FBG and FIRI had negative connections with both. Conclusion Postmenopausal women demonstrated higher levels of glycemic control indices and bone-related markers compared to premenopausal and reproductive-age women, indicating potential risks for osteoporosis and obesity.

Haytham M. Elhafez, Huda Adel Mohammed, Ebtesam A Ali

Abstract Background Over the past decade, smartphone users have substantially increased, raising concerns about potential musculoskeletal problems associated with long-term use. Prolonged smartphone usage may cause discomfort in the thumb, shoulder, and neck that can be exacerbated over time, thereby affecting the electrical activity of several muscles, such as the sternocleidomastoid muscle (SCM). Accordingly, we aimed to examine the impact of smartphone addiction on the myoelectric activity of the SCM. Design and method Forty-four smartphone users, both male and female, aged 18–30 years, were recruited from the Faculty of Physical Therapy, Cairo University, in this observational study. The participants were equally allocated into two groups, A and B, based on their Smartphone Addiction Scale-Short Version (SAS-SV) scores. Group A consisted of smartphone-non-addicted users who scored below 31 for males and 33 for females, whereas group B included smartphone-addicted users who scored over 31 for men and 33 for females. Additionally, the electromyography (EMG) device was used to monitor the electrical activity during rest and maximum voluntary contraction (MVC). Results The results showed a significant difference (P < 0.0001) in the electrical activity of the left and right SCMs between the two groups at rest but a nonsignificant difference during MVC. Conclusion Smartphone addiction significantly impacts the myoelectric activity of the SCM at rest among young adult smartphone users, but this impact is not significant during MVC.

Yangjun Zeng, Yiwei Qiu, Jie Zhu et al.

Off-grid renewable power to ammonia (ReP2A) systems present a promising pathway toward carbon neutrality in both the energy and chemical industries. However, due to chemical safety requirements, the limited flexibility of ammonia synthesis poses a challenge when attempting to align with the variable hydrogen flow produced from renewable power. This necessitates the optimal sizing of equipment capacity for effective and coordinated production across the system. Additionally, an ReP2A system may involve multiple stakeholders with varying degrees of operational flexibility, complicating the planning problem. This paper first examines the multistakeholder sizing equilibrium (MSSE) of the ReP2A system. First, we propose an MSSE model that accounts for individual planning decisions and the competing economic interests of the stakeholders of power generation, hydrogen production, and ammonia synthesis. We then construct an equivalent optimization problem based on Karush-Kuhn-Tucker (KKT) conditions to determine the equilibrium. Following this, we decompose the problem in the temporal dimension and solve it via multicut generalized Benders decomposition (GBD) to address long-term balancing issues. Case studies based on a realistic project reveal that the equilibrium does not naturally balance the interests of all stakeholders due to their heterogeneous characteristics. Our findings suggest that benefit transfer or re-arrangement ensure mutual benefits and the successful implementation of ReP2A projects.

Sanjeev Rastogi, Preeti Pandey, Kiran Maurya et al.

Background: Prayer had long been used as a tool to bring hope among patients suffering with intractable diseases. Most clinical researches conducted so far on prayer were done upon indoor patients. Effects of prayer involving patients and health care providers in a hospital outpatient setting have never been explored. Objectives: This cross sectional study aimed to observe the self-perceived changes post prayer among patients and hospital staff involved in the health care delivery and who actually have participated in the prayer sessions. Material and method: Survey was conducted with the help of a structured questionnaire on routine OP days at Ayurveda –Arthritis Treatment and Advanced Research Center, Lucknow. Patients visiting the center for OP based consultation and hospital staff who has participated in any prayer session were eligible to participate in the survey. Results: 49 hospital staff and 85 patients have participated in the survey. Among most important self-reported attributes following the prayer sessions in patients were Positive Attitude (84.70%), Optimism about cure (92.90%), Feeling of well-being (95.30%), Optimism about future (95.30%) and Changes in energy level (89.40%). Among hospital staff the important attributes were related to change in energy level (93.90%), increased empathy (93.90%), feeling of universal good (96.00%), less fatigue post prayer (69.40%), sustained effects (81.60%) and healthier feeling (81.60%). Conclusion: This observational study suggests that a simple prayer session in outpatient department may be helpful in inculcating hope and building self-esteem among patients and can bring a better self-image, efficiency and connectedness in the hospital staff. Eventually, this may help in improving the outcomes and quality of care being provided at outpatient setting at any hospital.

Qingya Lu, Jingyuan Deng, Ying Yu et al.

Objective: To develop a novel diagnostic modality to identify and diagnose stroke in daily life scenarios for improving the therapeutic effects and prognoses of patients. Methods: In this study, 16 stroke patients and 24 age-matched healthy participants as controls were recruited for comparative analysis. Leveraging a portable eye-tracking device and integrating traditional Chinese medicine theory with modern color psychology principles, we recorded the eye movement signals and calculated eye movement features. Meanwhile, the stroke recognition models based on eye movement features were further trained by using random forest (RF), k-nearest neighbors (KNN), decision tree (DT), gradient boosting classifier (GBC), XGBoost, and CatBoost. Results: The stroke group and the healthy group showed significant differences in some eye movement features (P < .05). The models trained based on eye movement characteristics had good performances in recognizing stroke individuals, with accuracies ranging from 77.40% to 88.45%. Under the red stimulus, the eye movement model trained by RF became the best machine learning model with a recall of 84.65%, a precision of 86.48%, a F1 score of 85.47%. Among the six algorithms, RF and CatBoost performed better in classification. Conclusion: This study pioneers the application of traditional Chinese medicine's five-color stimuli to visual observation tasks. On the basis of the combined design, the eye-movement models can accurately identify stroke, and the developed high-performance models may be used in daily life scenarios.

Su-Han Lee, Hye Bin Park, Sang-Keun Sung et al.

Background The ability to control the cell-surface network is widely used to observe the regulation of host-biomaterial interactions, predict cell behavior, and perform solid organ tissue engineering. We further investigated Nafion from the perspective of cell adhesion and biocompatibility. Methods The flexible Nafion micro-patterned mold was fabricated by asilicon master (linewidth, 800 nm; space, 800 nm; depth, 600 nm; line pattern). Four different molds were also fabricated based on PDMS, PUA, acryl, and Teflon. The PUA, acryl, and Teflon molds were exposed under a 365-nm UV lamp for 90 seconds at 40 mJ/s for curing. Results We developed micro-pattern poly(tetrafluoroethylene-co-perfluoro-3,6-dioxa-4-meth­yl-7-octene-sulfonic acid) (Nafion) films fabricated by a molding process. We present the fabrication and characterization of flexible, micro-patterned Nafion films and the evaluation of cell adhesion and alignment on these films. Conclusion We found that cell adhesion and migration/direction could be modulated by controlling the surface architecture.

Lidiele Berriel de Medeiros, Carlos Eduardo Antoniete de Souza, Carolina Gasperin et al.

Este artigo constitui uma narrativa sobre o percurso de dimensionamento da força de trabalho de uma instituição pública referência para atenção à saúde no sul do país, durante o período pandêmico, com os impactos, deslocamentos e invenções possíveis a partir do encontro com o inóspito contexto trazido pela COVID-19. O minucioso planejamento realizado para a tarefa de dimensionar a força de trabalho em saúde, previamente à eclosão da pandemia, estruturava-se em etapas predefinidas e, a partir das experiências anteriores, buscava avaliar o todo da instituição, considerando também outros cenários pesquisados. A pandemia provocou uma mudança de cenário tão drástica que demarcou indelevelmente o quão volátil é o terreno do trabalho em saúde, emaranhando as linhas preestabelecidas e desafiando profissionais a reinventar um modo possível de dimensionar em terreno tão incerto. Frente a este atravessamento, foi preciso desfiar e (re)tecer seu planejamento à realidade que se impunha, criando novos processos e buscando estudar, de modo adaptado, as demandas de cada serviço.

Jafar Vafaei, Omid Akbari, Muhammad Shafique et al.

Triple Modular Redundancy (TMR) is one of the most common techniques in fault-tolerant systems, in which the output is determined by a majority voter. However, the design diversity of replicated modules and/or soft errors that are more likely to happen in the nanoscale era may affect the majority voting scheme. Besides, the significant overheads of the TMR scheme may limit its usage in energy consumption and area-constrained critical systems. However, for most inherently error-resilient applications such as image processing and vision deployed in critical systems (like autonomous vehicles and robotics), achieving a given level of reliability has more priority than precise results. Therefore, these applications can benefit from the approximate computing paradigm to achieve higher energy efficiency and a lower area. This paper proposes an energy-efficient approximate reliability (X-Rel) framework to overcome the aforementioned challenges of the TMR systems and get the full potential of approximate computing without sacrificing the desired reliability constraint and output quality. The X-Rel framework relies on relaxing the precision of the voter based on a systematical error bounding method that leverages user-defined quality and reliability constraints. Afterward, the size of the achieved voter is used to approximate the TMR modules such that the overall area and energy consumption are minimized. The effectiveness of employing the proposed X-Rel technique in a TMR structure, for different quality constraints as well as with various reliability bounds are evaluated in a 15-nm FinFET technology. The results of the X-Rel voter show delay, area, and energy consumption reductions of up to 86%, 87%, and 98%, respectively, when compared to those of the state-of-the-art approximate TMR voters.

Yi Zhang

This paper proposes a set of technological solutions to transform existing transport systems into more intelligent, interactive systems by utilizing optimization and control methods that can be implemented in the near future. This will result in improved public services and quality of life for residents. Three application scenes that are closely related to people's daily life are discussed. We first propose a traffic light scheduling strategy using a model predictive control (MPC) method, with the aim of fairly minimizing delays for both pedestrians and vehicles. Then, a combined dispatching-operation system is proposed to increase control flexibility, with a corresponding implementation solution for boarding control. Finally, a possible scheme to combine both public transport and autonomous vehicle systems is proposed to improve existing public transport systems.

Viviane Durigon, Denise Bueno

Situações que envolvem manejo de pessoas com problemas de saúde crônicos, polimedicadas e que transitam em outros níveis de atenção são comuns na Atenção Primária em Saúde (APS). Proporcionar o uso de medicamentos seguros, na quantidade e pelo tempo adequado, ao menor custo para o indivíduo e para a comunidade, situação que configura o uso racional de medicamentos (URM), é uma necessidade e ao mesmo tempo um desafio para a APS. Este projeto de pesquisa objetiva identificar estratégias de educação na saúde voltadas aos profissionais da APS que possam contribuir no reconhecimento das dimensões relacionadas ao URM. O estudo ocorrerá nos municípios da 27a Região de Saúde do Rio Grande do Sul e terá abordagem descritiva exploratória. Através de um instrumento de pesquisa pretende-se inferir, descobrir e observar as dimensões do URM nas práticas de saúde dos locais pesquisados e a partir da percepção dos entrevistados aprofundar as questões de como o estudo pode contribuir com estratégias de educação em saúde nesta temática. Os dados quantitativos serão analisados através de estatística descritiva e a análise dos dados qualitativos será realizada por descrição do conteúdo. O estudo será conduzido conforme Resolução n° 466/12 que regulamenta a pesquisa envolvendo seres humanos. A partir dos resultados pretende-se realizar o levantamento de potencialidades e fragilidades nas práticas dos profissionais de saúde relacionadas ao URM e produzir materiais e/ou momentos de educação permanente com temas relacionados. Os resultados e produtos da pesquisa poderão ser utilizados posteriormente em ações que visem o URM. Palavras-chave: Educação Permanente. Uso de Medicamentos. Atenção Primária à Saúde.

Igor G. Vladimirov, Ian R. Petersen

This paper is concerned with linear stochastic systems whose output is a stationary Gaussian random process related by an integral operator to a standard Wiener process at the input. We consider a performance criterion which involves the trace of an analytic function of the spectral density of the output process. This class of "covariance-analytic" cost functionals includes the usual mean square and risk-sensitive criteria as particular cases. Due to the presence of the "cost-shaping" analytic function, the performance criterion is related to higher-order Hardy-Schatten norms of the system transfer function. These norms have links with the asymptotic properties of cumulants of finite-horizon quadratic functionals of the system output and satisfy variational inequalities pertaining to system robustness to statistically uncertain inputs. In the case of strictly proper finite-dimensional systems, governed in state space by linear stochastic differential equations, we develop a method for recursively computing the Hardy-Schatten norms through a recently proposed technique of rearranging cascaded linear systems, which resembles the Wick ordering of annihilation and creation operators in quantum mechanics. The resulting computational procedure involves a recurrence sequence of solutions to algebraic Lyapunov equations and represents the covariance-analytic cost as the squared $\mathcal{H}_2$-norm of an auxiliary cascaded system. These results are also compared with an alternative approach which uses higher-order derivatives of stabilising solutions of parameter-dependent algebraic Riccati equations.

Jairo Giraldo, Masood Parvania

The integration of synchronous generators and energy storage systems operated through communication networks introduces new challenges and vulnerabilities to the electric grid, where cyber attacks can corrupt sensor measurements or control inputs and interrupt functions such as frequency regulation. This paper proposes a defense methodology for the design of resilient operating constraints imposed on each generation and storage unit in order to prevent any attack sequence from driving the system's frequency to unsafe conditions. The resilient operating constraints are found by using ellipsoidal approximations of the reachable set of the power system, leading to a convex optimization problem with linear matrix inequalities. Numerical results in a single-area power system with synchronous generation and energy storage demonstrate how the resilient constraints provide security guarantees against any type of attack affecting frequency measurements or controller setpoints.

Yitian Dai, Robin Preece, Mathaios Panteli

Time-based dynamic models of cascading failures have been recognized as one of the most comprehensive methods of representing detailed cascading information and are often used for benchmarking and validation. This paper provides an overview of the progress in the field of dynamic analysis of cascading failures in power systems and outlines the benefits and challenges of dynamic simulations in future grids. The benefits include the ability to capture temporal characteristics of system dynamics and provide timing information to facilitate control actions for blackout mitigation. The greatest barriers to dynamic modelling of cascading failures are the computational burden, and the extensive but often unavailable data requirements for dynamic representation of a power system. These factors are discussed in detail in this paper and the need for in-depth research into dynamic modelling of cascading failures is highlighted. Furthermore, case studies of dynamic cascading simulation of 200-bus and 2000-bus benchmark systems provide initial guidance for the selection of critical parameters to enhance simulation efficiency. Finally, cross-validation and comparison against a quasi-steady state DC power flow model is performed, with various metrics compared.

Felix Biertümpfel, Nantiwat Pholdee, Samir Bennani et al.

This paper presents an approach to compute the worst-case gain of the interconnection of a finite time horizon linear time-variant system and a perturbation. The input/output behavior of the uncertainty is described by integral quadratic constraints (IQCs). A condition for the worst-case gain of such an interconnection can be formulated using dissipation theory as a parameterized Riccati differential equation, which depends on the chosen IQC multiplier. A nonlinear optimization problem is formulated to minimize the upper bound of the worst-case gain over a set of admissible IQC multipliers. This problem can be efficiently solved with a custom-tailored logarithm scaled, adaptive differential evolution algorithm. It provides a fast alternative to similar approaches based on solving semidefinite programs. The algorithm is applied to the worst-case aerodynamic load analysis for an expendable launch vehicle (ELV). The worst-case load of the uncertain ELV is calculated under wind turbulence during the atmospheric ascend and compared to results from nonlinear simulation.

Gangshan Jing, He Bai, Jemin George et al.

We address the problem of model-free distributed stabilization of heterogeneous multi-agent systems using reinforcement learning (RL). Two algorithms are developed. The first algorithm solves a centralized linear quadratic regulator (LQR) problem without knowing any initial stabilizing gain in advance. The second algorithm builds upon the results of the first algorithm, and extends it to distributed stabilization of multi-agent systems with predefined interaction graphs. Rigorous proofs are provided to show that the proposed algorithms achieve guaranteed convergence if specific conditions hold. A simulation example is presented to demonstrate the theoretical results.

Jing Kong, Lulu Liu, Yuanyuan Gao et al.

Objective: The objective of this study was to verify the lipid-lowering effect of Juhe Fang extract (JHFE) and to determine its characteristic chemical profile in vitro and in vivo. Methods: A hyperlipidemia model was established by feeding mice a high-fat diet (HFD). After treatment for 30 days, serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels were measured with an automatic biochemistry analyzer. The components from JHFE obtained from in vivo and in vitro experiments were investigated using an UPLC-Q Exactive-Orbitrap MS/MS. Results: The TC, TG, and LDL-C in the serum significantly decreased and the HDL-C significantly increased after JHFE treatment. A total of 95 compounds from JHEF including 15 phenolic acids (PA), 4 phenylethanoid glycosides (PG), 24 flavonoids (F), 14 triterpenoids (T), 10 diterpenoid glycosides (D), 18 alkaloids (A) and 10 others (O) were identified. Trigonelline was discovered for the first time in a herbal medicine of Juhe Fang. Furthermore, 68 compounds were identified in vivo including 28 prototype compounds and 40 metabolites. The metabolic characteristics of these components were revealed including identification of new metabolites of 4-hydroxyphenyl ethyl-8-O-[α-L- arabinopyranosyl-(1 → 6)]-β-D-glucopyranoside (PEG) and lirinidine. A total of 43 components from JHFE were absorbed and/or metabolized. The contribution rate of each type of chemical component from JHFE to its lipid-lowering effect from high to low were A, F, PG, PA, D and T. Conclusion: The results of this study showed that JHFE demonstrated a significant lipid-lowering effect in a high-fat diet (HFD)-induced hyperlipidemia mouse model. Specific types of PA, PG, F, D, T and A formed the pharmaceutical architecture of the lipid-lowering effect of JHFE. This study should prove useful for clarifying the components responsible for the lipid-lowering effect of JHFE and provide a basis for precision quality control research.

Narayan Bhusal, Mukesh Gautam, Michael Abdelmalak et al.

The frequency of disruptive and newly emerging threats (e.g. man-made attacks--cyber and physical attacks; extreme natural events--hurricanes, earthquakes, and floods) has escalated dramatically in the last decade. Impacts of these events are very severe ranging from long power outage duration, major power system equipment (e.g. power generation plants, transmission and distribution lines, and substation) destruction, and complete blackout. Accurate modeling of these events is vitally important as they serve as mathematical tools for the assessment and evaluation of various operations and planning investment strategies to harden power systems against these events. This paper provides a comprehensive and critical review of current practices in the modeling of extreme events, system components, and system response for resilience evaluation and enhancement, which is a very important stepping stone toward the development of complete, accurate, and computationally attractive modeling techniques. The paper starts with reviewing existing technologies to model the propagation of extreme events and then discusses the approaches used to model impacts of these events on power system components and system response. This paper also discusses the research gaps and associated challenges, and potential solutions to the limitations of the existing modeling approaches.