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Background: The restorative effect of classical music was assessed on the cyclophosphamide-induced animal model of premature ovarian failure (POF). Methods: Mozart’s piano classical music (K.448) was used for up to 4 and 8 weeks. Rats were exposed to music 6 h every day using a stereo system with a volume of 65–70 dB. Sera and ovarian tissue samples were collected for the evaluation of FSH, LH, and E2 and histopathological examination. At the same time points, samples were taken from the hypothalamus and hippocampus to monitor the expression of Ntrk2, Crh, and Pomc using real-time PCR. Mating trial was performed to evaluate the fertility status of POF rats. Results: Histopathological examination revealed a significant increase (p p 2 (p Ntrk2, Crh, and Pomc expressions were down-regulated in POF rats. Music therapy increasaed the expression of Ntrk2 in the hypothalamus of POF rats (p ). In contrast, Crh and Pomc failed to reach the detection limit before intervention and four weeks after the intervention however, these genes were expressed eight weeks after music therapy. Fertility status was increased (p p Conclusion: Results showed that music can exert therapeutic effects on POF rats via the alteration of sex-related hormones.

Understanding the cause of structural damage and loss caused by surface faulting rupture requires research on the fault rupture-foundation interaction and geotechnical mitigation methods. The present study investigated the interaction of reverse-faulting surface rupture and a foundation system comprising a mat foundation and micropiles. The effects of the micropiles on the rotation of the foundation and rupture propagation was examined for different interaction mechanisms. The results suggested that the response was sensitive to the position of the foundation micropiles. It was found that the position of the foundation-micropile system relative to the rupture determined the type of interaction between the soil, rupture, micropiles, and foundation, which is significant for development of geotechnical mitigation methods.

Technology advances—such as improving processing power, battery life, and communication functionalities—contribute to making mobile devices an attractive research area. In 2008, in order to manage mobility, the Internet Engineering Task Force (IETF) developed Proxy Mobile IPv6, which is a network-based mobility management protocol to support seamless connectivity of mobile devices. This protocol can play a key role in volunteer computing paradigms as a user can seamlessly access computing resources. The procedure of user authentication is not defined in this standard; thus, many studies have been carried out to propose suitable authentication schemes. However, in the current authentication methods, with reduced latency and packet loss, some security and privacy considerations are neglected. In this study, we propose a secure and anonymous ticket-based authentication (SATA) method to protect mobile nodes against existing security and privacy issues. The proposed method reduces the overhead of handover authentication procedures using the ticket-based concept. We evaluated security and privacy strengths of the proposed method using security theorems and BAN logic.

The recent surge in the number of machines, appliances, and services connected to the Internet demands secure processing and transmission of sensory data. Authentication plays crucial role in a typical security model used the Internet of Things (IoT), and it protects data communications from various attacks, such as impersonation and denial of service, by verifying and allowing legitimate users to access the IoT resources. However, recent authentication literature has not addressed the need for developing of a scalable and efficient authentication method in this field. This paper proposes a secure and anonymous ticket-based authentication method for the IoT. The proposed method protects network from various security and privacy threats such as data alternation and denial of service, while also offering mutual authentication and sensor anonymity. Our security and performance evaluations confirm the improvement.

Background and Objective. Kinect-based rehabilitation is an effective solution for creating motivation and promoting adherence to rehabilitation programs in stroke patients. The current study was aimed at examining the effects of Kinect-based rehabilitation systems on performance improvement, domains of use, and its limitations for stroke patients. Method. This study was conducted according to Arksey and O’Malley’s framework. To investigate the evidence on the effects of Kinect-based rehabilitation, a search was executed in five databases (Web of Science, PubMed, Cochrane Library, Scopus, and IEEE) from 2010 to 2020. Results. Thirty-three articles were finally selected by the inclusion criteria. Most of the studies had been conducted in the US (22%). In terms of the application of Kinect-based rehabilitation for stroke patients, most studies had focused on the rehabilitation of upper extremities (55%), followed by balance (27%). The majority of the studies had developed customized rehabilitation programs (36%) for the rehabilitation of stroke patients. Most of these studies had noted that the simultaneous use of Kinect-based rehabilitation and other physiotherapy methods has a more noticeable effect on performance improvement in patients. Conclusion. The simultaneous application of Kinect-based rehabilitation and other physiotherapy methods has a stronger effect on the performance improvement of stroke patients. Better effects can be achieved by designing Kinect-based rehabilitation programs tailored to the characteristics and abilities of stroke patients.

Evaluating the performance of photovoltaic panels inevitably involves having the exact model of solar cells. Different approaches to model solar cells have been proposed in literature which can generally be classified as either traditional or intelligent methods. To obtain the accurate model of such highly nonlinear systems, however, is still a challenging task, defying researchers. This study proposes an Improved Lozi Map based Chaotic Optimization Algorithm (ILCOA) algorithm to estimate the unknown parameters of the solar cells. Remarkable local and global searching abilities of the proposed algorithm give it a distinct edge over other optimization methods, enabling it to sift the whole search space for the global optimum. The efficacy of the proposed approach is finally highlighted by comparing its performance with those of three other algorithms including BMO, CWOA, and LCOA in terms of RMSE, Relative Error, Mean Absolute Error (MAE), Normalized MAE, and Mean Bias Error.

In this paper, an efficient stochastic optimization algorithm is presented for parameter identification of nonlinear systems. Due to its robust performance, short running time and desirable potency to find local minimums the Lozi map-based chaotic optimization algorithm is an appropriate choice to estimate unknown parameters of nonlinear dynamic systems. To enhance the identification efficacy and in order to escape local minimum, a modified version of this algorithm with higher stability and better performance is rendered in this paper. An Improved Lozi map-based chaotic optimization algorithm (ILCOA) is employed to identify three nonlinear systems and the performance of the proposed algorithm is compared with other optimization algorithms. The simulation results of identification endorse the effectiveness of the proposed method.

Multiple Sclerosis (MS) is a disease determined by inflammatory demyelination and neurodegeneration in the Central Nervous System (CNS). Despite the extensive utilization of Complementary and Alternative Medicine (CAM) in MS, there is a need to have comprehensive evidence regarding their application in the management of MS symptoms. This manuscript is a Systematic Literature Review and classification (SLR) of CAM therapies for the management of MS symptoms based on the International Classification of Functioning Disability and Health (ICF) model.Studies published between 1990 and 2020 IN PubMed, Science Direct, Scopus, Pro-Quest, and Google Scholar using CAM therapies for the management of MS symptoms were analyzed.Thirty-one papers on the subject were analyzed and classified. The findings of this review clearly show that mindfulness, yoga, and reflexology were frequently used for managing MS symptoms. Moreover, most of the papers used mindfulness and yoga as a CAM therapy for the management of MS symptoms, which mostly devoted to mental functions such as fatigue, depression, cognition, neuromuscular functions such as gait, muscle strength, and spasticity, and sensory function such as balance, in addition to, reflexology is vastly used to management of mental functions of MS patients.Evidence suggested that CAM therapies in patients with MS have the potential to target and enhancement numerous elements outlined in the ICF model. Although the use of CAM therapies in MS symptom management is promising, there is a need for strict clinical trials. Future research direction should concentrate on methodologically powerful studies to find out the potential efficacy of CAM intervention.

In many countries, the Internet of Medical Things (IoMT) has been deployed in tandem with other strategies to curb the spread of COVID-19, improve the safety of front-line personnel, increase efficacy by lessening the severity of the disease on human lives, and decrease mortality rates. Significant inroads have been achieved in terms of applications and technology, as well as security which have also been magnified through the rapid and widespread adoption of IoMT across the globe. A number of on-going researches show the adoption of secure IoMT applications is possible by incorporating security measures with the technology. Furthermore, the development of new IoMT technologies merge with Artificial Intelligence, Big Data and Blockchain offers more viable solutions. Hence, this paper highlights the IoMT architecture, applications, technologies, and security developments that have been made with respect to IoMT in combating COVID-19. Additionally, this paper provides useful insights into specific IoMT architecture models, emerging IoMT applications, IoMT security measurements, and technology direction that apply to many IoMT systems within the medical environment to combat COVID-19., Highlights • An insight on how IoMT systems are currently being utilized within the context of COVID-19. • A review on the associated IoMT architecture, applications and technologies deployed to mitigate COVID-19 pandemic. • Security measures pertaining the IoMT applications and technologies developed to combat COVID-19.

Healthcare is a highly institutionalized industry, subject to multiple regulatory forces, high levels of professionalism, and growing network externalities which may affect the decisions to adopt. Hence, this research integrates the Resource Dependence Theory (RDT), institutional theory along with Human Organization Technology (HOT) fit model as the organization theories to explain the adoption of Hospital Information System (HIS). To examine the effects of inter and intra-organizational potential factors on HIS adoption, within the context of Malaysian public hospitals, a survey method using web-based questionnaire is employed. The role of hospital size in this study is investigated to determine its distinct moderating influence among the relationships of the HIS adoption and significant dimensional factors. The results indicated that system affiliation (p

The Internet of Things (IoT) is an ecosystem that integrates physical objects, software and hardware to interact with each other. Aging of population, shortage of healthcare resources, and rising medical costs make IoT-based technologies necessary to be tailored to address these challenges in healthcare. This systematic literature review has been conducted to determine the main application area of IoT in healthcare, components of IoT architecture in healthcare, most important technologies in IoT, characteristics of cloud-based architecture, security and interoperability issues in IoT architecture and effects, and challenges of IoT in healthcare. Sixty relevant papers, published between 2000 and 2016, were reviewed and analyzed. This analysis revealed that home healthcare service was one of the main application areas of IoT in healthcare. Cloud-based architecture, by providing great flexibility and scalability, has been deployed in most of the reviewed studies. Communication technologies including wireless fidelity (Wi-Fi), Bluetooth, radio-frequency identification (RFID), ZigBee, and Low-Power Wireless Personal Area Networks (LoWPAN) were frequently used in different IoT models. The studies regarding the security and interoperability issues in IoT architecture in health are still low in number. With respect to the most important effects of IoT in healthcare, these included ability of information exchange, decreasing stay of hospitalization and healthcare costs. The main challenges of IoT in healthcare were security and privacy issues.

The modeling, small-signal stability analysis, and control of quasi-Z-Source Matrix Converter (qZSMC), and also its application in Wind Energy Conversion System (WECS) are discussed. First, the small-signal model of the qZSMC, composed of an input filter, a Three-Phase Quasi-Z-Source Network (TPQZSN), and a Matrix Converter (MC), is derived. Then, a comprehensive stability study is carried out and it is shown that, unlike the conventional MC, the qZSMC does not have problem working stable for its entire range of operation. The small-signal model is used to obtain system transfer functions and perform a frequency domain analysis. A guide to choose proper passive components of qZSMC is also presented. The qZSMC is further employed as grid interface by a Permanent Magnet Synchronous Generator (PMSG) based WECS (PMSG-WECS). A modified predictive control (MPC) is developed, allowing shoot-through states to be inserted within the deliberately made sequences of zero switching states in MC switching pulses. The proposed MPC is then compared to its conventional version, showing that by the MPC, the grid-current ripples are reduced considerably. Simulation study is used to assess the effectiveness of proposed WECS and MPC, and to highlight the promising features of the proposed WECS in comparison to Conventional MC-based PMSG-WECS (CMC-WECS).

This work aims to carry out a comprehensive analytical evaluation of a quasi-Z-source matrix converter (qZSMC), which is comprised of a three-phase quasi-Z-source network (TPQZSN) followed by an MC, as the grid interface of a permanent magnet synchonous generator (PMSG)-based wind energy conversion system (PMSG-WECS). First, the small-signal model of the TPQZSN in space domain is obtained by the state-space averaging method, while the parasitic elements are also considered. The TPQZSN's transfer functions are further calculated and analysed. The results together with a frequency-domain analysis are used to render a comprehensive guide for the selection of proper passive components of the TPQZSN. The qZSMC is then employed as the grid interface of a PMSG-WECS. A control system is designed for the grid-connected operation. The small-signal model of the whole system is developed. The qZSMC is compared with conventional MC (CMC) from stability point of view, indicating that, unlike the CMC, the qZSMC has no trouble working stable for all ranges of output power. Furthermore, it is shown that the proposed WECS can operate stably without using digital filter. The system performance is compared with CMC-based WECS.