Hasil untuk "Miscellaneous systems and treatments"

Mangayarkarasi Narayanaswamy, Abinaya Suresh, Sournamaalya Dhamodharan et al.

Primary dysmenorrhea affects 50–90% of females aged 18–35 years. It is characterized by lower abdominal pain, nausea, headache, and fatigue owing to the release of prostaglandins from the uterus. Although nonsteroidal anti-inflammatory drugs and hormonal therapies are commonly administered treatments, concerns about their side effects have sparked interest in alternatives such as yoga and acupuncture. Yoga and acupuncture have been found to alleviate pain, lessen emotional distress, and ease the physical discomfort associated with dysmenorrhea. This case series examines three patients with primary dysmenorrhea who underwent 60 days of naturopathy with acupuncture. Pain, emotional distress, and physical discomfort were assessed using the menstrual distress questionnaire, showing reductions from 101 to 59, 117 to 49, and 119 to 58 in patients 1, 2, and 3, respectively. All patients reported symptom improvement without irregular cycles. The findings suggest that naturopathy with acupuncture effectively alleviate pain and distress in primary dysmenorrhea.

Dha-Hyun Choi, Beomku Kang, Heeyoung Moon et al.

Background: Acupuncture needles are widely used to treat various medical conditions, but can occasionally lead to serious adverse events. The therapeutic index (TI), originally developed in pharmacology to quantify the safety margin between effective and toxic doses, provides a valuable potential framework for evaluating anatomical safety in acupuncture. Methods: We applied the TI concept to two commonly used acupoints—GB21 and ST36—by quantifying the TI value, defined as the ratio of the median hazardous depth (HD₅₀) to the median effective depth (ED₅₀), based on ultrasound-guided measurement and de-qi responses. Using ultrasound-guided measurements in 39 participants, we calculated the TI for each point and constructed cumulative distribution functions to visualize the therapeutic window. Results: GB21 demonstrated a TI of 1.54, indicating a relatively wide safety margin, whereas ST36 had a TI of 1.09, reflecting a narrow and potentially risk-prone margin. Conclusions: These findings emphasize the impact of anatomical variability and highlight the need for personalized depth control in acupuncture practice. Our study provides preliminary evidence that integrating the TI concept into acupuncture safety assessment may support more individualized, data-driven needling strategies. These findings should be interpreted as exploratory and require confirmation in larger, demographically diverse populations and at additional acupoints before being generalized to routine clinical practice.

Hafsa Tariq, Khizra Ishfaq, Talha Chauhdari et al.

Background: Parkinson's disease (PD) is a prevalent age-related neurodegenerative condition that develops gradually and is observed in around 1 % of the elderly population. Lately, there has been an increasing curiosity about the possibilities of phyto-components for the treatment of PD due to their rich array of active compounds, notably antioxidants and anti-inflammatory agents. Objective: Our objective was to assess the impact of an ethanolic extract from Dombeya wallichii, which has antioxidant properties, on the Parkinsonian rat's model. Material and methods: Rats received 10 mg/kg paraquat to assess its antiparkinsonian effects. They were treated with ethanolic extract of Dombeya wallichii (200, 400, 600 mg/kg) for 21 days, 1 h after paraquat. Behavioral aspects were evaluated before sacrifice. On day 22, rats were euthanized, and their bodies examined for changes in antioxidant enzymes (superoxide dismutase, glutathione, malondialdehyde, catalase), neurotransmitter levels (dopamine, noradrenaline, serotonin, acetylcholinesterase), mRNA expression and neuroinflammatory cytokines (Interleukin-1β, Tumor Necrosis Factor-α, nuclear factor kappa B, Interleukin-6). Results: The ethanolic extract of Dombeya wallichii reduced paraquat-induced motor deficits in the rotarod, hole board, akinesia, and forelimb hanging tests. It also improved biochemical and neuroinflammatory markers by lowering oxidative stress and inflammatory cytokines, showing antioxidant and anti-inflammatory activities. q-RT-PCR revealed that D. wallichii downregulated α-synuclein, Interleukin-1β, nuclear factor kappa B, and Tumor Necrosis Factor-α, while mRNA expression indicated neuroprotection. Conclusion: These findings suggest that Dombeya wallichii could be a viable candidate for Parkinson's disease treatment, owing to its antioxidant and anti-inflammatory properties.

Ben Larwood, Oliver J. Sutton, Callum Cockburn

Developing high-stakes autonomous systems that include Artificial Intelligence (AI) components is complex; the consequences of errors can be catastrophic, yet it is challenging to plan for all operational cases. In stressful scenarios for the human operator, such as short decision-making timescales, the risk of failures is exacerbated. A lack of understanding of AI failure modes obstructs this and so blocks the robust implementation of applications of AI in smart systems. This prevents early risk identification, leading to increased time, risk and cost of projects. A key tenet of Systems Engineering and acquisition engineering is centred around a "left-shift" in test and evaluation activities to earlier in the system lifecycle, to allow for "accelerated delivery of [systems] that work". We argue it is therefore essential that this shift includes the analysis of AI failure cases as part of the design stages of the system life cycle. Our proposed framework enables the early characterisation of risks emerging from human-autonomy teaming (HAT) in operational contexts. The cornerstone of this is a new analysis of AI failure modes, built on the seminal modelling of human-autonomy teams laid out by LaMonica et al., 2022. Using the analysis of the interactions between human and autonomous systems and exploring the failure modes within each aspect, our approach provides a way to systematically identify human-AI interactions risks across the operational domain of the system of interest. The understanding of the emergent behaviour enables increased robustness of the system, for which the analysis should be undertaken over the whole scope of its operational design domain. This approach is illustrated through an example use case for an AI assistant supporting a Command & Control (C2) System.

Yifei Wang, Han Wang, Kehao Zhuang et al.

The integration of converter-interfaced generation introduces new transient stability challenges to modern power systems. Classical Lyapunov- and scalable passivity-based approaches typically rely on restrictive assumptions, and finding storage functions for large grids is generally considered intractable. Furthermore, most methods require an accurate grid dynamics model. To address these challenges, we propose a model-free, nonlinear, and dissipativity-based controller which, when applied to grid-connected virtual synchronous generators (VSGs), enhances power system transient stability. Using input-state data, we train neural networks to learn dissipativity-characterizing matrices that yield stabilizing controllers. Furthermore, we incorporate cost function shaping to improve the performance with respect to the user-specified objectives. Numerical results on a modified, all-VSG Kundur two-area power system validate the effectiveness of the proposed approach.

Thomas Waite, Yuang Geng, Trevor Turnquist et al.

It remains a challenge to provide safety guarantees for autonomous systems with neural perception and control. A typical approach obtains symbolic bounds on perception error (e.g., using conformal prediction) and performs verification under these bounds. However, these bounds can lead to drastic conservatism in the resulting end-to-end safety guarantee. This paper proposes an approach to synthesize symbolic perception error bounds that serve as an optimal interface between perception performance and control verification. The key idea is to consider our error bounds to be heteroskedastic with respect to the system's state -- not time like in previous approaches. These bounds can be obtained with two gradient-free optimization algorithms. We demonstrate that our bounds lead to tighter safety guarantees than the state-of-the-art in a case study on a mountain car.

Mengze Yu, Wei Wang, Jiaqi Yan

This paper studies distributed resilient consensus problem for a class of uncertain nonlinear multiagent systems susceptible to deception attacks. The attacks invade both sensor and actuator channels of each agent. A specific class of Nussbaum functions is adopted to manage the attack-incurred multiple unknown control directions. Additionally, a general form of these Nussbaum functions is provided, which helps to ease the degeneration of output performance caused by Nussbaum gains. Then, by introducing finite-time distributed reference systems and local-error-based dynamic gains, we propose a novel distributed adaptive backstepping-based resilient consensus control strategy. We prove that all the closed-loop signals are uniformly bounded under attacks, and output consensus errors converge in finite time to a clearly-defined residual set whose size can be reduced by tuning control parameters, which is superior to existing results. Simulation results display the effectiveness of the proposed controllers.

Isabelle Krauss, Victor G. Lopez, Matthias A. Müller

Sample-based observability characterizes the ability to reconstruct the internal state of a dynamical system by using limited output information, i.e., when measurements are only infrequently and/or irregularly available. In this work, we investigate the concept of functional observability, which refers to the ability to infer a function of the system state from the outputs, within a samplebased framework. Here, we give necessary and sufficient conditions for a system to be sample-based functionally observable, and formulate conditions on the sampling schemes such that these are satisfied. Furthermore, we provide a numerical example, where we demonstrate the applicability of the obtained results.

Anandh Srinivasan, S. Senthil Kumar

Abstract Background The shoulder complex with its varied pathology responds differently from patient to patient and so, the best option for progression is a choice of rehabilitation. In the present post-COVID scenario, many patients are referred to acute and sub-acute shoulder pain and dysfunction. It is very difficult to predict the outcome of therapy. Some patients recover even without any modalities. Recurrent or adverse symptoms are also possible. Gender, other demographic features, physiological response, and progressive outcome need to be considered in rehabilitation. This study is intended to evaluate the short-term effects of hydrotherapy post-intra-articular injections of shoulder dysfunctions. Aims and objectives To evaluate the effectiveness of hydrotherapy during early rehabilitation of individuals who have undergone intra-articular injections of shoulder joint on pain and function. Materials and methods In this prospective study, we have studied a total of 59 cases within the age group of 40–70 years with idiopathic frozen shoulder, acromio-clavicular joint dysfunction, and grade-1 untreated rotator cuff injuries. Group A patients were treated with conventional shoulder exercises and group B patients were treated in a hydrotherapy pool. The chief aim was to obtain earlier pain relief with controlled movement patterns and earlier relief from functional disability. The Constant-Murley score (CMS–100 points scale) composing pain and functional parameters was the outcome measure. Results After confounding all the demographic factors, it was found that the experimental group B treated by hydrotherapy revealed a statistically extremely significant difference (p value < 0.0001) at the end of the first week as compared to the conventional group. The treatment protocol was continued for 5 weeks. More than 90% of patients in the hydrotherapy group felt it easier and exercise participation progression was best. Better progression and improvement of shoulder function were achieved in the hydrotherapy group compared to the conventional group. Conclusion From this study, we conclude that hydrotherapy during early management of shoulder dysfunctions post-intra-articular injections is safer and provides excellent relief from pain as early as the first week. Functional progression is better and avoids complications related to mobilization.

Sai Kripa, Mathivadhani Kadiresan

Abstract People all around the world suffer from low back pain (LBP), which frequently results in disability and a lower quality of life. Myths and misconceptions around LBP are still prevalent in both the general public and hospital settings, despite its ubiquitous prevalence. Through dispelling these myths and advocating for evidence-based knowledge, medical professionals can enhance patient education, lessen stigma, and anxiety related to life with post-traumatic stress disorder and enable more successful management techniques. Furthermore, dispelling myths regarding low back pain in the broader public can enable people to actively participate in their own care and support improved outcomes for those who have this crippling illness. The purpose of this evaluation of the literature is to identify and dispel prevalent misconceptions about LBP by examining the available data.

Praveen K. Yadav, Pradeep S. Shindhe, Ramesh S. Killedar et al.

Cystic echinococcosis (CE), which is present in all parts of the world, is caused by the bacterium Echinococcus granulosus. One of the most serious parasitic infectious diseases affecting both humans and animals, CE causes hydatid cysts that can lodge in various host organs, including the liver, lungs, heart, and brain, which can be fatal. Treatment options for cystic echinococcosis are active anthelmintics, surgery, and percutaneous aspiration. Numerous scolicidal chemical agents are in practice, but due to increased drug resistance and adverse reactions associated with drugs, usage is limited. Finding alternative therapies with the least or no side effects to manage the condition is the need of the hour. Here, we report a case of an asymptomatic hydatid lung cyst that was managed using Ayurvedic treatment principles. A 57-year-old businessman, asymptomatic, came with a diagnosis of Hydatid lung disease confirmed by CT scan. Surgery was advised, but the patient approached for Ayurveda treatment. The case was treated with oral medicines like Arogyavardhini gutika, Goarka, Kanchanara guggulu, Vidangasava, Kapalabhati pranayama for a period of 8 months. Complete resolution of the cyst was seen, which was evident by a CT scan. Promising results were seen in the present case, but further research in this area is required to produce evidence-based results.

Saberes Plurais

Zijie Huang, Jeehyun Hwang, Junkai Zhang et al.

Real-world multi-agent systems are often dynamic and continuous, where the agents co-evolve and undergo changes in their trajectories and interactions over time. For example, the COVID-19 transmission in the U.S. can be viewed as a multi-agent system, where states act as agents and daily population movements between them are interactions. Estimating the counterfactual outcomes in such systems enables accurate future predictions and effective decision-making, such as formulating COVID-19 policies. However, existing methods fail to model the continuous dynamic effects of treatments on the outcome, especially when multiple treatments (e.g., "stay-at-home" and "get-vaccine" policies) are applied simultaneously. To tackle this challenge, we propose Causal Graph Ordinary Differential Equations (CAG-ODE), a novel model that captures the continuous interaction among agents using a Graph Neural Network (GNN) as the ODE function. The key innovation of our model is to learn time-dependent representations of treatments and incorporate them into the ODE function, enabling precise predictions of potential outcomes. To mitigate confounding bias, we further propose two domain adversarial learning-based objectives, which enable our model to learn balanced continuous representations that are not affected by treatments or interference. Experiments on two datasets (i.e., COVID-19 and tumor growth) demonstrate the superior performance of our proposed model.

Mehdi Zafari, Divyanshu Pandey, Rahman Doost-Mohammady et al.

In cell-free massive MIMO systems with multiple distributed access points (APs) serving multiple users over the same time-frequency resources, downlink beamforming is done through spatial precoding. Precoding vectors can be optimally designed to use the minimum downlink transmit power while satisfying a quality-of-service requirement for each user. However, existing centralized solutions to beamforming optimization pose challenges such as high communication overhead and processing delay. On the other hand, distributed approaches either require data exchange over the network that scales with the number of antennas or solve the problem for cellular systems where every user is served by only one AP. In this paper, we formulate a multi-user beamforming optimization problem to minimize the total transmit power subject to per-user SINR requirements and propose a distributed optimization algorithm based on the alternating direction method of multipliers (ADMM) to solve it. In our method, every AP solves an iterative optimization problem using its local channel state information. APs only need to share a real-valued vector of interference terms with the size of the number of users. Through simulation results, we demonstrate that our proposed algorithm solves the optimization problem within tens of ADMM iterations and can effectively satisfy per-user SINR constraints.

Emmanuel Junior Wafo Wembe, Adnane Saoud

This paper delves into the problem of computing robust controlled invariants for monotone continuous-time systems, with a specific focus on lower-closed specifications. We consider the classes of state monotone (SM) and control-state monotone (CSM) systems, we provide the structural properties of robust controlled invariants for these classes of systems and show how these classes significantly impact the computation of invariants. Additionally, we introduce a notion of feasible points, demonstrating that their existence is sufficient to characterize robust controlled invariants for the considered class of systems. The study further investigates the necessity of reducing the feasibility condition for CSM and Lipschitz systems, unveiling conditions that guide this reduction. Leveraging these insights, we construct an algorithm for the computation of robust controlled invariants. To demonstrate the practicality of our approach, we applied the developed algorithm to the coupled tank problem.

In-Seon Lee, Yeonhee Ryu, Younbyoung Chae

Gabriela Queiroz Vieira Neves, Waldez Cavalcante Bezerra, Giovanna Bardi

Dentre os públicos-alvo dos serviços da proteção social especializada do Sistema Único de Assistência Social estão as pessoas idosas e/ou com deficiência e suas famílias. O presente artigo tem o objetivo de relatar a prática desenvolvida no Serviço Especializado de Atendimento Domiciliar, especificamente com as cuidadoras das pessoas idosas e/ou com deficiência, destacando as ações desenvolvidas pela terapia ocupacional. A experiência relatada permite refletir sobre a desigualdade nos papeis de gênero na sociedade, uma vez que as cuidadoras eram, em sua maioria, mulheres; e sobre as contribuições da terapia ocupacional nas ações desenvolvidas, marcadas pelo uso das atividades coletivas e pela atuação voltada para o cotidiano das cuidadoras. Destaca-se que prática evidenciou que a terapia ocupacional social é um referencial teórico-metodológico que pode subsidiar o trabalho da categoria nas unidades socioassistenciais, estabelecendo uma coerência entre o fazer terapêutico-ocupacional, as características e demandas do público acompanhado e as requisições da política de assistência social.

Lu Ding, Cui Li, Peiming Zhang et al.

Background: An increasing amount of clinical evidence of acupuncture's effect on protracted opioid abstinence syndrome (POAS) has emerged in recent years. The aim of this study was to evaluating the evidence of efficacy of acupuncture for POAS. clinical and scientific research work. Methods: Four English-language databases (PubMed, Medline, Embase, Cochrane Libraries) and three Chinese-language databases (CNKI, WanFang and VIP Libraries) were searched, with coverage from database inception to March 31, 2022. Randomized clinical trials (RCTs) evaluating the effects of acupuncture and acupuncture-related therapies for prophylaxis or treatment of POAS were included. Data were screened and extracted independently according to pre-set tabular formats. RCT quality was assessed using risk of bias tool in the Cochrane Collaboration. The primary outcome was opiate withdrawal scale. The secondary outcomes are depression, anxiety for assessing protracted symptoms. The scores on the above scales are proportional to the severity of the symptoms. Results: Twenty-eight trials met the inclusion criteria and provided data for the meta-analysis. A total of only 3 studies (11%) were judged to be low-risk overall due to various biases in them. Acupuncture-related therapy showed statistical differences in improving protracted withdrawal symptom scores compared with sham acupuncture (5 studies, Standard mean difference (SMD), -1.85, 95% CI [-3.21, -0.50], P = 0.007), western medicine (7 studies, SMD, -0.72, 95% CI [-1.22, -0.21], P = 0.005) and no treatment (3 studies, SMD,-2.26, 95% CI [-3.82, -0.69], P = 0.005) with high heterogeneity. Conclusions: Acupuncture maybe safe and effective in relieving POAS individuals’ protracted withdrawal symptoms. However, the results of our review should be interpreted with caution because of the high risk of bias of the included trials. Study registration: The protocol of this review has been registered at PROSPERO (CRD42022335505).

Simeon C. Calvert, Stig Johnsen, Ashwin George

Ensuring operational control over automated vehicles is not trivial and failing to do so severely endangers the lives of road users. An integrated approach is necessary to ensure that all agents play their part including drivers, occupants, vehicle designers and governments. While progress is being made, a comprehensive approach to the problem is being ignored, which can be solved in the main through considering Meaningful Human Control (MHC). In this research, an Integrated System Proximity framework and Operational Process Design approach to assist the development of Connected Automated Vehicles (CAV) under the consideration of MHC are introduced. These offer a greater understanding and basis for vehicle and traffic system design by vehicle designers and governments as two important influencing stakeholders. The framework includes an extension to a system approach, which also considers ways that MHC can be improved through updating: either implicit proximal updating or explicit distal updating. The process and importance are demonstrated in three recent cases from practice. Finally, a call for action is made to government and regulatory authorities, as well as the automotive industry, to ensure that MHC processes are explicitly included in policy, regulations, and design processes to ensure future ad-vancement of CAVs in a responsible, safe and humanly agreeable fashion.

David Fellner, Thomas I Strasser, Wolfgang Kastner

Modeling and simulation of electrical power systems are becoming increasingly important approaches for the development and operation of novel smart grid functionalities -- especially with regard to data-driven applications as data of certain operational states or misconfigurations can be next to impossible to obtain. The DeMaDs framework allows for the simulation and modeling of electric power grids and malfunctions therein. Furthermore, it serves as a testbed to assess the applicability of various data-driven malfunction detection methods. These include data mining techniques, traditional machine learning approaches as well as deep learning methods. The framework's capabilities and functionality are laid out here, as well as explained by the means of an illustrative example.