A Comprehensive Review of Computer-Aided Diagnosis of Major Mental and Neurological Disorders and Suicide: A Biostatistical Perspective on Data Mining

The World Health Organization (WHO) suggests that mental disorders, neurological disorders, and suicide are growing causes of morbidity. Depressive disorders, schizophrenia, bipolar disorder, Alzheimer’s disease, and other dementias account for 1.84%, 0.60%, 0.33%, and 1.00% of total Disability Adjusted Life Years (DALYs). Furthermore, suicide, the 15th leading cause of death worldwide, could be linked to mental disorders. More than 68 computer-aided diagnosis (CAD) methods published in peer-reviewed journals from 2016 to 2021 were analyzed, among which 75% were published in the year 2018 or later. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was adopted to select the relevant studies. In addition to the gold standard, the sample size, neuroimaging techniques or biomarkers, validation frameworks, the classifiers, and the performance indices were analyzed. We further discussed how various performance indices are essential based on the biostatistical and data mining perspective. Moreover, critical information related to the Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines was analyzed. We discussed how balancing the dataset and not using external validation could hinder the generalization of the CAD methods. We provided the list of the critical issues to consider in such studies

A comprehensive review of the movement imaginary brain-computer interface methods: Challenges and future directions

Brain-computer interface (BCI) aims to translate human intention into a control output signal. In motor-imaginary (MI) BCI, the imagination of movement modifies the cortex brain activity. Such activities are then used in pattern recognition to identify certain movement classes. MI-BCI could be used to enhance the life quality of physically impaired subjects. Several challenges exist in MI-BCI, including selecting appropriate channels, usually linked with a suitable classifier choice. The entire procedure must be real time in practical applications. A variety of channel selection and classification methods were used for MI-BCI in the literature. Also, hybrid machine learning (ML) and deep learning (DL) methods were used in the literature. In this chapter, different channel selection, ML and DL methods, validation frameworks, and performance indices of EEG-based methods were investigated. Three hundred and twenty-two papers published between January 2000 and March 2021 were analyzed in this systematic review. Specific challenges and future directions were then provided.Peer ReviewedPostprint (author's final draft

Synthesis, characterization, and CO2 adsorption properties of pure ETS-10

Synthesis of titanosilicate ETS-10 with high purity and crystallinity is a big challenge due to its limited crystallization region. ETS-10 was synthesized and characterized by SEM, EDX, BET, and TGA/DTA methods. The effect of synthesis parameters including pH of the gel, crystallization temperature and time, and the potassium source, were studied using the one-at-a-time (OFAT) approach. The results showed that the ETS-10 with the highest purity was achieved considering the gel pH of 11.3, and the crystallization time and temperature of 72 h and 230 °C. It was also revealed that there was considerable interaction between the potassium source with other synthesis parameters. Afterward, CO2 adsorption of the pure synthesized sample was obtained at 298 K using a volumetric setup. The Dual-site Langmuir, Toth, and UNILAN isotherms were applied to model the obtained equilibrium adsorption data. The CO2 adsorption capacity of the synthesized pure ETS-10 was obtained equal to 3.37 mmol/g. Finally, the adsorption kinetics data were modeled using the PNO model with n = 3.5. The results showed that about 90% of the equilibrium absorption was achieved in only 25 s, which indicates the remarkable capability of using pure ETS-10 for CO2 capture by the PSA method

Analysis and Designing of a Wireless Charging System for Electric Vehicles Using the Topology of Double Sided llC Compensator

The purpose of the present study is to simulate the equivalent circuit in the MATLAB software in order to implement the desired relationships for both continuous-conduction mode (CCM) and discontinuous-conduction mode (DCM) , and to obtain power and efficiency values at different frequencies. Then it is necessary to optimize the effective values on the power by Particle Swarm Optimization (PSO) algorithm. After optimization, the optimization and pre-optimization results should be compared and, if post-optimization results are not desirable, effective parameters should be reviewed before the optimization stage and the tunable parameters should be changed to achieve the desired results. This process will continue to obtain optimization results. The results show that the highest efficiency is 98% in DCM mode and is 95% in CCM mode. In both methods, we have achieved more favorable results than the baseline using the PSO method. However, DCM mode provides an improvement about 2.6% higher than CCM

An innovative fault injection method in embedded systems via background debug mode

The embedded systems usage in different applications is prevalent in recent years. These systems include a wide range of equipments from cell phones to medical instruments, which consist of hardware and software. In many examples of embedded systems, fault occurrence can lead to serious dangers in system behavior (for example in satellites). Therefore, we try to increase the fault tolerance feature in these systems. Therefore, we need some mechanisms that increase the robustness and reliability of such systems. These objects cause the on-line test to be a great concern. It is not important that these mechanisms work in which level (Hardware level, Software level or Firmware). The major concern is that how well these systems can provide debugging, test and verification features for the user regardless of their implementation levels. Background Debug Module is a real time tool for these features. In this paper we apply an innovative way to use the BDM tool for fault injection in an embedded system

A New Method for an Electric Vehicle Wireless Charging System Using LCC

Nowadays, there is a need for charging electric vehicles (EVs) wirelessly, since it provides a more convenient, reliable, and safer charging option for the EV customers. A wireless charging system using a double-sided LCC compensation topology is proven to be highly efficient; however, the large volume induced by the compensation coils is a drawback. Endocrine links are more useful in transmitting power wirelessly than other links. These links are used in the transmission of low and medium power. In this paper, by analyzing the equivalent circuit of a WPT power transmission system, the optimal value of the inductance was formulated to increase the yield. This can have other applications. In order to neutralize the reactive losses, the series resonance is used in both in primary and secondary sections, among which the lower quantities of series inductors were selected from the initial values to increase the efficiency and power. Furthermore, it is possible to optimize these values using suitable optimization methods. In this study, the PSO algorithm was used for this purpose

Macular surgery using intraoperative spectral domain optical coherence tomography

Purpose: To report the use of intraoperative spectral domain optical coherence tomography (SD-OCT) for detecting anatomical changes during macular surgery. Methods: In a consecutive case series, 32 eyes of 32 patients undergoing concurrent pars plana vitrectomy and intraoperative SD-OCT for macular hole (MH), epiretinal membrane (ERM) and vitreomacular traction (VMT) were enrolled. Intraoperative changes in retinal thickness and dimensions of the macular hole were measured in patients with ERM and VMT following surgical manipulation using a hand-held SD-OCT device (iVue, Optovue Inc., Fremont, CA, USA). Results: SD-OCT images of sixteen eyes with macular hole were subjected to quantitative and qualitative analysis. All MH dimensions remained stable during consecutive stages of surgery except for MH apex diameter, which showed a significant decrease after internal limiting membrane (ILM) peeling (P=0.025). Quantitative analysis of ten patients with ERM showed a significant decrease in retinal thickness after membrane removal (P=0.018) which did not remain significant until the end of the procedure (P=0.8). In three cases, subretinal fluid was formed after ILM peeling. Quantitative analysis of five patients with VMT showed a decrease in retinal thickness during consecutive steps of the surgery, although these changes were not significant. In two cases, subretinal fluid was formed after ILM peeling. Conclusion: Intraoperative SD-OCT is a useful imaging technique which provides vitreoretinal surgeons with rapid awareness of changes in macular anatomy during surgery and may therefore result in better anatomical and visual outcomes

Frequency of TNFR1 36 A/G gene polymorphism in azoospermic infertile men: A case-control study

Background: Tumor necrosis factor-alpha (TNF-&alpha;) is a multifunctional cytokine that regulates different cellular activities related to spermatogenesis. Tumor necrosis factor-alpha receptor 1 (TNFR1) mediates TNF-&alpha; activity and polymorphism in TNFR1 could lead to gene dysfunction and male infertility. Objective: The aim of this study is to determine the association of TNFR1 36 A/G polymorphism with the idiopathic azoospermia in Iranian population. Materials and Methods: This case-control study included 108 azoospermic and 119 fertile men. This research investigated the frequency of TNFR1 36 A/G polymorphism in cases who were idiopathic azoospermic men referred to Yazd Research and Clinical Center for Infertility, Iran in comparison with controls. polymerase chain reaction- restriction fragment length polymorphism (PCR-RFLP) method was used to investigate the polymorphism in both case and control groups. PCR fragments were digested by Mspa1I enzyme and products were appeared by gel electrophoresis. The abundance of A&rarr;G was calculated in the azoospermic and healthy men. Results: According to the present study, GG and AG genotypes frequency in the azoospermic men group were higher than the control group (OR= 2.298 (1.248-4.229), p=0.007), (OR=1.47 (0.869-2.498, p=0.149). Our findings also showed that G allele frequency in azoospermic men had significant difference compared to the control group (OR=2.302 (1.580-3.355), p<0.001). Conclusion: It seems that the GG genotype and G allele have an association with increased risk of non-obstructive azoospermi

Reliable diagnosis and prognosis of COVID-19

The 2019 novel coronavirus disease (COVID-19) epidemic was officially announced by the World Health Organization (WHO) as an international public health emergency. The medical research world is responding to the COVID-19 pandemic at breathtaking speed. Most of the studies related to this outbreak identify the epidemiology and clinical characteristics of infected patients and focus on its short-term effects. However, there are many studies with inappropriate study design, data mining, and statistical analysis. Proper design and reliability assessment of COVID-19 diagnosis systems (e.g., proper feature selection, classification, and performance assessment) must be performed. Also, advanced statistical methods (e.g., multistate and competing risk models) are required to avoid the risk of bias in prognosis systems. Moreover, many studies may be too small and poorly designed to be helpful, merely adding to the COVID-19 noise. Additionally, trials without a control group, non-randomized and imbalanced trials are common problems of experimental designs. Thus, in this chapter, we aim to address the critical methods to use in the diagnosis and prognosis of COVID-19.The research leading to this results has also received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement Nº 712949 (TECNIOspring PLUS) and from the Agency for Business Competitiveness of the Government of Catalonia.Peer ReviewedPostprint (published version