Recent Applications of Deep Learning Algorithms in Medical Image Analysis

Advances in deep learning have enabled researchers in the field of medical imaging to employ such techniques for various applications, including early diagnosis of different diseases. Deep learning techniques such as convolutional neural networks offer the capability of extracting invariant features from images that can improve the performance of most predictive models in medical and diagnostic imaging. This work concentrates on reviewing deep learning architectures along with medical imaging modalities where the crucial applications of such algorithms, including image classification and segmentation, are discussed. Also, brain imaging as a branch of medical imaging which allows scientists to explore the structure and function of the brain is explored, and the applications of deep learning to early diagnose Alzheimer’s Disease, and Autism as the most critical brain disorders are studied. Moreover, the recent research findings revealed that employing deep learning-based semantic segmentation techniques could significantly improve the accuracy of models developed for brain tumor detection. Such advances in early diagnosis of disorders and tumors encourage medical imaging practitioners to implement software applications assisting them to improve their decision-making process

A Dynamic Model of Post-Traumatic Stress Disorder for Military Personnel and Veterans

Post-traumatic stress disorder (PTSD) stands out as a major mental illness; however, little is known about effective policies for mitigating the problem. The importance and complexity of PTSD raise critical questions: What are the trends in the population of PTSD patients among military personnel and veterans in the postwar era? What policies can help mitigate PTSD? To address these questions, we developed a system dynamics simulation model of the population of military personnel and veterans affected by PTSD. The model includes both military personnel and veterans in a “system of systems.” This is a novel aspect of our model, since many policies implemented at the military level will potentially influence (and may have side effects on) veterans and the Department of Veterans Affairs. The model is first validated by replicating the historical data on PTSD prevalence among military personnel and veterans from 2000 to 2014 (datasets from the Department of Defense, the Institute of Medicine, the Department of Veterans Affairs, and other sources). The model is then used for health policy analysis. Our results show that, in an optimistic scenario based on the status quo of deployment to intense/combat zones, estimated PTSD prevalence among veterans will be at least 10% during the next decade. The model postulates that during wars, resiliency-related policies are the most effective for decreasing PTSD. In a postwar period, current health policy interventions (e.g., screening and treatment) have marginal effects on mitigating the problem of PTSD, that is, the current screening and treatment policies must be revolutionized to have any noticeable effect. Furthermore, the simulation results show that it takes a long time, on the order of 40 years, to mitigate the psychiatric consequences of a war. Policy and financial implications of the findings are discussed.United States. Dept. of Defense. Office of the Assistant Secretary of Defense for Health Affairs (W81XWH-12-0016

Comparison of the Effectiveness of Emotion-focused Therapy and Acceptance and Commitment Therapy on Health locus of Control of Patients with Coronary Heart Patients

Introduction: Cardiovascular diseases are the most important cause of mortality in the world. Inaddition to physical problems, they are also influenced by psychological factors and psychologicaltherapies along with biological therapy can help to improve these patients. The purpose of this studywas to compare the effectiveness of acceptance and commitment therapy (ACT) and emotionfocused therapy (EFT) on Health locus of control of coronary heart patients.Method: This was a quasi-experimental study with pretest-posttest design with control group. Thestatistical population of the study included patients with coronary heart disease in the city of Karaj.Patients were 30 to 60 years old who referred to Shahid Rajaee Hospital in Karaj. Samples wereselected using convenient sampling method and were assigned randomly into two experimental andone control group. Data were collected using health locus of control questionnaire. Data wereanalyzed using descriptive statistics and analysis of covariance.Results: outcomes showed that ACT and EFT are effective on adjusting the Health locus of controlin patients with coronary heart disease, and there was a significant difference between theexperimental and control group (F = 7.25, p <0.05).But there was no difference between theefficacy of the two treatments.Conclusion: Psychological therapies such as ACT and EFT increase self-care in cardiac patients byincreasing control and increasing sense of responsibility

Comparison of the Effectiveness of Acceptance and Commitment Therapy and Emotion-focused Therapy on Negative Emotions of Coronary Heart Disease

Introduction: Cardiovascular diseases are the most important cause of mortality in the world. In addition to physical problems, they are also influenced by psychological factors and psychological therapies along with biological therapy can help to improve these patients. The purpose of this study was to compare the effectiveness of acceptance and commitment therapy and emotion-focused therapy on negative emotions of coronary heart disease patients.Method: This was a quasi-experimental study with pretest-posttest design with control group. The statistical population of the study included patients with coronary heart disease in the city of Karaj The age range was 30 to 60 yearswho referred to Shahid Rajaee Hospital in Karaj. Samples were selected using available sampling method and then the samples were randomly divided into two experimental and one control group. Data were collected using D-type personality scale and Buss and Perry hostility scale.Data were analyzed by descriptive statistics and analysis of covariance using SPSS-25 software.Results: The results of this study showed that patients' negative emotion scale scores decreased, indicating the effectiveness of acceptance and commitment therapy and emotion-focused therapy compared to the control group. Conclusion: Considering that one of the most important psychological factors related to heart disease are negative emotions and these emotions can have an accelerating role in the development and progression of heart disease and Due to the effectiveness of the above treatments, their education can be helpful in addition to medical treatment

Decision-making and biases in cybersecurity capability development: Evidence from a simulation game experiment

We developed a simulation game to study the effectiveness of decision-makers in overcoming two complexities in building cybersecurity capabilities: potential delays in capability development; and uncertainties in predicting cyber incidents. Analyzing 1479 simulation runs, we compared the performances of a group of experienced professionals with those of an inexperienced control group. Experienced subjects did not understand the mechanisms of delays any better than inexperienced subjects; however, experienced subjects were better able to learn the need for proactive decision-making through an iterative process. Both groups exhibited similar errors when dealing with the uncertainty of cyber incidents. Our findings highlight the importance of training for decision-makers with a focus on systems thinking skills, and lay the groundwork for future research on uncovering mental biases about the complexities of cybersecurity. Keywords: Cybersecurity; Decision-making; Simulation; Capability developmen

An Optimization-Based Framework for Nonlinear Model Selection and Identification

This paper proposes an optimization-based framework to determine the type of nonlinear model present and identify its parameters. The objective in this optimization problem is to identify the parameters of a nonlinear model by minimizing the differences between the experimental and analytical responses at the measured coordinates of the nonlinear structure. The application of the method is demonstrated on a clamped beam subjected to a nonlinear electromagnetic force. In the proposed method, the assumption is that the form of nonlinear force is not known. For this reason, one may assume that any nonlinear force can be described using a Taylor series expansion. In this paper, four different possible nonlinear forms are assumed to model the electromagnetic force. The parameters of these four nonlinear models are identified from experimental data obtained from a series of stepped-sine vibration tests with constant acceleration base excitation. It is found that a nonlinear model consisting of linear damping and linear, quadratic, cubic, and fifth order stiffness provides excellent agreement between the predicted responses and the corresponding measured responses. It is also shown that adding a quadratic nonlinear damping does not lead to a significant improvement in the results

Modeling and estimating the feedback mechanisms among depression, rumination, and stressors in adolescents

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The systemic interactions among depressive symptoms, rumination, and stress are important to understanding depression but have not yet been quantified. In this article, we present a system dynamics simulation model of depression that captures the reciprocal relationships among stressors, rumination, and depression. Building on the response styles theory, this model formalizes three interdependent mechanisms: 1) Rumination contributes to 'keeping stressors alive'; 2) Rumination has a direct impact on depressive symptoms; and 3) Both 'stressors kept alive' and current depressive symptoms contribute to rumination. The strength of these mechanisms is estimated using data from 661 adolescents (353 girls and 308 boys) from two middle schools (grades 6-8). These estimates indicate that rumination contributes to depression by keeping stressors 'alive'-and the individual activated- even after the stressor has ended. This mechanism is stronger among girls than boys, increasing their vulnerability to a rumination reinforcing loop. Different profiles of depression emerge over time depending on initial levels of depressive symptoms, rumination, and stressors as well as the occurrence rate for stressors; levels of rumination and occurrence of stressors are stronger contributors to long-term depression. Our systems model is a steppingstone towards a more comprehensive understanding of depression in which reinforcing feedback mechanisms play a significant role. Future research is needed to expand this simulation model to incorporate other drivers of depression and provide a more holistic tool forstudying depression.National Institutes of Health (U.S.) (Award R21MH100515)National Institute of Mental Health (U.S.) (Award R21MH100515

Assessing influence of active and passive confinement on flexural behaviour of CFST beams

U radu se analizira utjecaj aktivnog i pasivnog ovijanja na ponašanje pri savijanju betonom ispunjenih čeličnih cijevi. Dvanaest ovijenih uzoraka podvrgnuto je ispitivanju čvrstoće na savijanje u tri točke. Osnovni varijabilni parametri bili su: odnos promjera i debljine cijevi (20, 30 i 60), tlačna čvrstoća betonske jezgre (15 MPa i 45 MPa) i vrsta ovijanja (aktivno ili pasivno). Ispitana je savojna čvrstoća, apsorpcija energije, fleksibilnost i način popuštanja ovijenih uzoraka, isto kao i način pucanja betonske jezgre u točki sloma. Rezultati pokazuju da aktivno ovijanje dovodi do manje duktilnosti uzoraka koji se odlikuju većom čvrstoćom betonske jezgre.The aim of this study is to investigate the effect of active and passive confinement on the flexural behaviour of concrete-filled steel tubes. Three-point flexural test is carried out on twelve confined specimens. The main variable parameters are: tube diameter to thickness ratio (20, 30, and 60), compressive strength of concrete core (15 MPa and 45 MPa), and type of confinement (active or passive). The flexural capacity, energy absorption, flexibility and failure mode of confined specimens, as well as the cracking pattern of concrete core at failure point, are evaluated in this study. The results show that active confinement leads to lower ductile behaviour in specimens with higher strength of concrete core

Odnos između izloženosti buci, umora i subjektivnog mentalnog opterećenja

The aim of this study is to investigate the relationship between noise exposure, fatigue and subjective mental workload (SMWL) in bank employees. This study was performed on 113 bank employees in Iran. Noise pollution in the studied banks was estimated in accordance with the standard ISO 9612 (1997). To determine the SMWL, NASA-TLX method was used. The level of job fatigue of employees was determined using the Swedish Job Fatigue Questionnaire (SOFI-20) and the sensitivity of people to noise was measured using the Weinstein questionnaire. Finally, the predictor variables of mental workload were analyzed using simultaneous multiple linear regression test in SPSS-V16 software. The level equivalent to the noise exposure (Mean ±SD) in the workstations of bank employees was 61.30 dB-A. The Mean ±SD of the final score of SMWL in the studied employees was 71.91±12.79. The results of the simultaneous regression analysis test showed that the fatigue, noise sensitivity, and level of noise exposure predict a total of 0.61 of the variances of SMWL (P < 0.05, df = 112, f = 16.43). Increasing the noise can increase the SMWL of employees by having the effect of increasing fatigue, and this effect is increased by the sensitivity of employees to noise.Cilj ovog rada je istražiti odnos između izloženosti buci, umora i subjektivnog mentalnog opterećenja (SMWL) kod zaposlenika banaka. Istraživanje je provedeno na 113 zaposlenika banaka u Iranu. Onečišćenje bukom u bankama procijenjeno je u suglasnosti sa standardom ISO 9612 (1997.). Kako bi se utvrdio SMWL, korištena je NASA-TLX metoda. Stupanj zamora poslom zaposlenika određen je korištenjem Švedskog upitnika o umoru na poslu (SOFI-20), a osjetljivost ljudi na buku mjerena je Weinstein upitnikom. Konačno, prediktorske varijable mentalnog opterećenja analizirane su korištenjem simultanog testa višestruke linerane regresije u SPSS-V16 softveru. Ekvivalent izloženosti buci (Mean ±SD) na radnim mjestima zaposlenika banke bio je 61,30 dB-A ±6,41. Mean ±SD konačnog rezultata SMWL kod ispitanih zaposlenika bio je 71,91±12,79. Rezultati simultane regresije testa analize pokazali su da umor, osjetljivost na buku te razina izloženosti buci predviđa ukupno 0,61 varijance SMWL (P < 0,05, df = 112, f = 16,43). Povećanje buke može povisiti SMWL kod zaposlenika imajući učinak povećanog umora, a taj učinak povećan je osjetljivošću zaposlenika na buku