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The Western homicide drop is a known fact, but the reasons behind the drop have so far mainly focused on macro explanations. In this study, we argue that to understand the homicide drop, it is necessary to first explore whether the drop is general or specific. We do this by examining the subtypes of homicide together with perpetrator and victim demographic characteristics. This study seeks to describe the nature and scope of homicidal violence in the period 1992-2016 in the Netherlands, disaggregating by subtype of homicide, and perpetrator and victim gender constellation and age. In doing so, we make use of the Dutch Homicide Monitor. Findings show that the Dutch homicide drop is significantly related to homicides resulting from disputes and robberies and intimate partner homicides. The gender constellation and age distribution in all homicide types are further explored. This study highlights the importance of disaggregating data by subtype in unravelling the homicide drop.Forecasting accurate Value-at-Risk (VaR) estimations is a crucial task in applied financial risk management. Even though there have been significant advances in the field of financial econometrics, many crises have been documented throughout the world in the last decades. An explanation for this discrepancy is that many contemporary models are too complex and cannot be easily understood and implemented in the financial industry (Fama in Financ Anal J 5175-80, 1995; Ross in AIMR conference proceedings, vol. SBE-β-CD research buy 1993, no. 6, pp. 11-15, Association for Investment Management and Research, 1993). In order to bridge this theory-practice gap, we present a computational method based on the leverage effect. This method allows us to focus on financial theory and remove complexity. Examining the US stock market (2000-2020), we provide empirical evidence that our newly suggested approach, which uses only the most appropriate observation period, significantly increases the accuracy of the Conventional Delta Normal VaR model and generates VaR estimations which are as accurate as those of advanced econometric models, such as GARCH(1,1).In this paper, we have considered a deterministic epidemic model with logistic growth rate of the susceptible population, non-monotone incidence rate, nonlinear treatment function with impact of limited hospital beds and performed control strategies. The existence and stability of equilibria as well as persistence and extinction of the infection have been studied here. We have investigated different types of bifurcations, namely Transcritical bifurcation, Backward bifurcation, Saddle-node bifurcation and Hopf bifurcation, at different equilibrium points under some parametric restrictions. Numerical simulation for each of the above-defined bifurcations shows the complex dynamical phenomenon of the infectious disease. Furthermore, optimal control strategies are performed using Pontryagin's maximum principle and strategies of controls are studied for two infectious diseases. Lastly using efficiency analysis we have found the effective control strategies for both cases.With the spread of the novel coronavirus disease 2019 (COVID-19) around the world, the estimation of the incubation period of COVID-19 has become a hot issue. Based on the doubly interval-censored data model, we assume that the incubation period follows lognormal and Gamma distribution, and estimate the parameters of the incubation period of COVID-19 by adopting the maximum likelihood estimation, expectation maximization algorithm and a newly proposed algorithm (expectation mostly conditional maximization algorithm, referred as ECIMM). The main innovation of this paper lies in two aspects Firstly, we regard the sample data of the incubation period as the doubly interval-censored data without unnecessary data simplification to improve the accuracy and credibility of the results; secondly, our new ECIMM algorithm enjoys better convergence and universality compared with others. With the framework of this paper, we conclude that 14-day quarantine period can largely interrupt the transmission of COVID-19, however, people who need specially monitoring should be isolated for about 20 days for the sake of safety. The results provide some suggestions for the prevention and control of COVID-19. The newly proposed ECIMM algorithm can also be used to deal with the doubly interval-censored data model appearing in various fields.Rapid communication of viral sicknesses is an arising public medical issue across the globe. Out of these, COVID-19 is viewed as the most critical and novel infection nowadays. The current investigation gives an effective framework for the monitoring and prediction of COVID-19 virus infection (C-19VI). To the best of our knowledge, no research work is focused on incorporating IoT technology for C-19 outspread over spatial-temporal patterns. Moreover, limited work has been done in the direction of prediction of C-19 in humans for controlling the spread of COVID-19. The proposed framework includes a four-level architecture for the expectation and avoidance of COVID-19 contamination. The presented model comprises COVID-19 Data Collection (C-19DC) level, COVID-19 Information Classification (C-19IC) level, COVID-19-Mining and Extraction (C-19ME) level, and COVID-19 Prediction and Decision Modeling (C-19PDM) level. Specifically, the presented model is used to empower a person/community to intermittently screen COVID-19 Fever Measure (C-19FM) and forecast it so that proactive measures are taken in advance. Additionally, for prescient purposes, the probabilistic examination of C-19VI is quantified as degree of membership, which is cumulatively characterized as a COVID-19 Fever Measure (C-19FM). Moreover, the prediction is realized utilizing the temporal recurrent neural network. link2 Additionally, based on the self-organized mapping technique, the presence of C-19VI is determined over a geographical area. Simulation is performed over four challenging datasets. In contrast to other strategies, altogether improved outcomes in terms of classification efficiency, prediction viability, and reliability were registered for the introduced model.[Purpose] Hybrid Assistive Limb® (HAL; Cyberdyne, Tsukuba, Japan) is a wearable robot that assists patients based on their voluntary movements. We report gait training with HAL after botulinum toxin treatment for spasticity of the lower limb in cerebral palsy (CP). [Participant and Methods] The participant was a 36 year-old male with spastic diplegia due to periventricular leukomalacia, with Gross Motor Function Classification System (GMFCS) level II. HAL training was performed in 20-minute sessions (3 sessions/week for 4 weeks). The outcome measures were range of motion, spasticity, walking ability, muscle strength, gross motor function measure (GMFM), Canadian Occupational Performance Measure (COPM), and Pediatric Evaluation of Disability Inventory measured before, immediately after, and one, two, and three months after HAL training. [Results] No adverse events were observed during training. link3 After the HAL intervention, gait speed, step length, cadence, 6-min walking distance (6MD), knee extension strength, GMFM, and COPM increased, and Physiological Cost Index declined. Three months post-intervention, gait speed, step length, cadence, 6MD, and GMFM remained higher than those observed within the first two months. [Conclusion] Gait training with HAL can be a safe and feasible method for patients with CP who undergo botulinum toxin treatment to improve walking ability and motor function.[Purpose] To develop a quantitative motion analysis software specific to boxing (Fist Tactics Support) and to verify its effectiveness based on the percentage of hits that land on the participants. [Participants and Methods] A total of 24 male professional boxers were divided into two groups those who used Fist Tactics Support to analyze fight videos and instituted training changes based on the results (Fist Tactics Support group, 12 participants) and those who did not (control group, 12 participants). The overall percentage of hits that landed on the participants in the fights was compared between the two groups and between pre- and post-intervention. [Results] There were no significant differences between the two groups; however, the percentage of hits that landed on the boxers of the Fist Tactics Support group was significantly lower at post-intervention than at pre-intervention. [Conclusion] The use of scientific analysis results in boxing may facilitate the primary prevention of sports injuries.[Purpose] The characteristics of neck and shoulder pain (NSP) in different age populations have not been sufficiently examined. Therefore, the purpose of this study was to compare and verify the cervicothoracic spinal alignment and neck flexor muscle endurance of young and older adult females with and without NSP. [Participants and Methods] We assessed 72 female participants (39 young participants, 33 elderly participants, 43 NSP, 29 non-NSP) aged 18-82 years who were recruited for this study. Cervicothoracic spinal alignment measurements were obtained with forward head alignment (FHA) along with the upper thoracic angle. The neck flexor endurance test was performed. [Results] There were no significant age-by-group interactions for any of the assessment variables. However, the upper thoracic angle and neck flexor muscle endurance showed significant effects in the groups. Age also had significant effects on FHA and upper thoracic angle. [Conclusion] These results suggested that the neck flexor muscle endurance was more appropriate as an evaluation tool for older adult females with NSP. It was also suggested that the cervical flexor muscle endurance and upper thoracic angle were more appropriate as evaluation tools for young adult females with NSP.[Purpose] A strong correlation exists between low physical activity and the prognosis of patients with chronic obstructive pulmonary disease (COPD). The interaction between psychological factors and low physical activity remains unclear in patients with COPD. Here, we investigated the impact of the health locus of control (HLOC) on the response to an education program in patients with COPD. [Participants and Methods] We assessed the physical activities and HLOC in participants with COPD before and after a five-month education program. We assessed physical activity using the Japanese version of the International Physical Activity Questionnaire (IPAQ). We evaluated the HLOC using the Japanese version of the HLOC scales. We provided an identical educational program to all participants after the initial evaluation. [Results] The total activity and walking scores were significantly elevated after the intervention. We observed a significant negative correlation between the IPAQ Total score after the intervention and the supernatural HLOC. We also observed significant negative correlations between the IPAQ Vigorous score after the intervention and Family HLOC and Chance HLOC. [Conclusion] The response of patients with COPD to self-care educational programs was influenced by the HLOC.[Purpose] We examined the effects of trunk anterior tilt angle (TA) and knee flexion angle (KA) on lower limb muscle activity. [Participants and Methods] Twenty-eight healthy male participants (age, 24.7 ± 4.7 years) performed nine standing tasks with different TA and KA. The participants were instructed to remain still during each task. The nine standing tasks were randomly performed while measurements of muscle activity were obtained for seven muscles gluteus maximus (GMAX), medial hamstrings (MH), lateral hamstrings (LH), rectus femoris (RF), vastus lateralis (VL), medial gastrocnemius (MG), and soleus (SOL). The activities of these muscles were normalized using isometric grade 3 of the manual muscle testing (isoMMT3). The intra-rater reliability for the mean values of the muscle activities measured with the isoMMT3 (intra-class correlation coefficient with 95% confidence interval) was confirmed using equation ICC (1,3). [Results] GMAX, MH, LH, RF, and MG were affected by both TA and KA, whereas VL was affected by KA, and SOL was affected by TA.