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Finally, we use convolutional neural networks and long short-term memory networks model to obtain automatically predict the COVID-19 patient's cardiovascular health. Theoretical analysis and experimental results show that our proposal can well solve the above issues and improve the prediction accuracy of cardiovascular disease to 99.29%.Based on a susceptible-infected-susceptible patch model, we study the influence of dispersal on the disease prevalence of an individual patch and all patches at the endemic equilibrium. Specifically, we estimate the disease prevalence of each patch and obtain a weak order-preserving result that correlated the patch reproduction number with the patch disease prevalence. Then we assume that dispersal rates of the susceptible and infected populations are proportional and derive the overall disease prevalence, or equivalently, the total infection size at no dispersal or infinite dispersal as well as the right derivative of the total infection size at no dispersal. Furthermore, for the two-patch submodel, two complete classifications of the model parameter space are given one addressing when dispersal leads to higher or lower overall disease prevalence than no dispersal, and the other concerning how the overall disease prevalence varies with dispersal rate. Numerical simulations are performed to further investigate the effect of movement on disease prevalence.

As areaction to the coronavirus diseases 2019 (COVID-19) pandemic, in individual settings psychotherapy could be conducted online to an unlimited extent in Germany. The attitudes and experiences of psychotherapists with respect to online therapy (OT) have so far been generally poorly studied and particularly with a view to the situation during the pandemic.

The aim of the study was to examine 1)the frequency of utilization of OT during the first lockdown, 2)the satisfaction with OT versus face-to-face therapy and 3)the technology acceptance experience overall and with respect to the guideline procedures.

German psychotherapists licensed and in training, cognitive-behavioral (CB 45.6%), analytic (AP 14%), depth-psychological (DP 34.5%), systemic (SYS 5.8%), were invited to participate in an online survey on demographic and therapeutic data, use of OT, satisfaction with OT vs. face-to-face therapy (

, ZUF-THERA) and technology acceptance (Unified Theory of Acceptance and Use of Technology 2 Questionnaireth face-to-face therapy. Further studies analyzing the reasons for this in detail are urgently recommended.

The frequency of use of OT soared during the first lockdown (March-May 2020, 43% in comparison to the former limit covered by health insurances of 20%). In principle, therapists were highly satisfied with OT but significantly lower than with face-to-face therapy. Further studies analyzing the reasons for this in detail are urgently recommended.The outbreak of corona virus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to a global pandemic. The high infectivity of SARS-CoV-2 highlights the need for sensitive, rapid and on-site diagnostic assays of SARS-CoV-2 with high-throughput testing capability for large-scale population screening. The current detection methods in clinical application need to operate in centralized labs. Though some on-site detection methods have been developed, few tests could be performed for high-throughput analysis. We here developed a gold nanoparticle-based visual assay that combines with CRISPR/Cas12a-assisted RT-LAMP, which is called Cas12a-assisted RT-LAMP/AuNP (CLAP) assay for rapid and sensitive detection of SARS-CoV-2. In optimal condition, we could detect down to 4 copies/μL of SARS-CoV-2 RNA in 40 min. by naked eye. The sequence-specific recognition character of CRISPR/Cas12a enables CLAP a superior specificity. More importantly, the CLAP is easy for operation that can be extended to high-throughput test by using a common microplate reader. The CLAP assay holds a great potential to be applied in airports, railway stations, or low-resource settings for screening of suspected people. To the best of our knowledge, this is the first AuNP-based colorimetric assay coupled with Cas12 and RT-LAMP for on-site diagnosis of COVID-19. We expect CLAP assay will improve the current COVID-19 screening efforts, and make contribution for control and mitigation of the pandemic.The standard rapid approach for the diagnosis of coronavirus disease 2019 (COVID-19) is the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA. The detection of specific anti-SARS-CoV-2 immunoglobulins is crucial for screening people who have been exposed to the virus, whether or not they presented symptoms. PI3K inhibitor Recent publications report different methods for the detection of specific IgGs, IgMs, and IgAs against SARS-CoV-2; these methods mainly detect immunoglobulins in the serum using conventional techniques such as rapid lateral flow tests or enzyme-linked immunosorbent assay (ELISA). In this article, we report the production of recombinant SARS-CoV-2 spike protein and the development of a rapid, reliable, cost-effective test, capable of detecting immunoglobulins in serum and saliva samples. This method is based on interferometric optical detection. The results obtained using this method and those obtained using ELISA were compared. Owing to its low cost and simplicity, this test can be used periodically for the early detection, surveillance, detection of immunity, and control of the spread of COVID-19.3D-HEVC is the state-of-the-art standard to compress three-dimensional videos. One of the 3D-HEVC novel tools is the DIS tool, which is used to efficiently compress smooth and homogeneous areas of depth maps by using four different prediction modes. The decision of which DIS mode will be used is done through the SVDC similarity criterion in the DIS original definition. This article proposes the substitution of the complex SVDC criterion for simpler and more hardware friendly criteria as SATD, SSE, and SAD. These alternative criteria were evaluated in terms of encoding efficiency and hardware impacts in comparison with the SVDC. Dedicated DIS hardware were designed using each one of each criterion and these designs were described in VHDL and synthesized for TSMC 40 nm. The best results were found with SAD criteria, with losses of only 0.2% in coding efficiency and with expressive gains of more than 50 times in power and more than 35 times in area, when compared with SVDC. The reached results showed that the use of a simpler similarity criterion is an important alternative to be used in DIS tool, mainly if an efficient hardware design is required.Recently, various countries from across the globe have been facing the second wave of COVID-19 infections. In order to understand the dynamics of the spread of the disease, much effort has been made in terms of mathematical modeling. In this scenario, compartmental models are widely used to simulate epidemics under various conditions. In general, there are uncertainties associated with the reported data, which must be considered when estimating the parameters of the model. In this work, we propose an effective methodology for estimating parameters of compartmental models in multiple wave scenarios by means of a dynamic data segmentation approach. This robust technique allows the description of the dynamics of the disease without arbitrary choices for the end of the first wave and the start of the second. Furthermore, we adopt a time-dependent function to describe the probability of transmission by contact for each wave. We also assess the uncertainties of the parameters and their influence on the simulations overnmental spheres.Although deterministic compartmental models are useful for predicting the general trend of a disease's spread, they are unable to describe the random daily fluctuations in the number of new infections and hospitalizations, which is crucial in determining the necessary healthcare capacity for a specified level of risk. In this paper, we propose a stochastic SEIHR (sSEIHR) model to describe such random fluctuations and provide sufficient conditions for stochastic stability of the disease-free equilibrium, based on the basic reproduction number that we estimated. Our extensive numerical results demonstrate strong threshold behavior near the estimated basic reproduction number, suggesting that the necessary conditions for stochastic stability are close to the sufficient conditions derived. Furthermore, we found that increasing the noise level slightly reduces the final proportion of infected individuals. In addition, we analyze COVID-19 data from various regions worldwide and demonstrate that by changing only a few parameter values, our sSEIHR model can accurately describe both the general trend and the random fluctuations in the number of daily new cases in each region, allowing governments and hospitals to make more accurate caseload predictions using fewer compartments and parameters than other comparable stochastic compartmental models.Chilean geography exposes the country to high-level risks such as earthquakes and tsunamis. The disasters of 1930, 1960, 2010, and 2014 testify to the continuous link between human survival and disasters. However, new hazards have appeared ever since -i.e. flood waterlogging, wildfires, and landslides-, highlighting the relationship between current land uses and space occupation with increasing levels of disaster risk. This research aims to determine relations and responsibilities of the Chilean developmental approach in urban planning and territorial governance processes that have created new territories prone to disaster risk. We resort to a longitudinal analysis from 1930 to 2018 at the Gran Concepción metropolitan area as a proxy of Chilean industrialization and economic development approaches. To do so, we developed mixed-approach descriptive research, for which we collected data from national development policies and documented land occupation processes during pre-dictatorship, dictatorship and post-dictatorship periods. Semi-structured interviews with decision-makers involved in current territorial policy were also carried out. The findings show how territorial governance resulted from political visions around different development paths, wherein the concept of risk is weakly perceived among decision-makers. This perception is linked to narrow economic goals and the understanding of land as a barely regulated marketable asset, profoundly affected by segregated urban planning.Public health emergencies, especially major infectious diseases, may cause global crises. Timely and effective communication is essential for response to such incidents. However, the emergency response to such incidents usually lasts longer and break out repeatedly, and the existing static emergency communication network (ECN) analysis cannot fully reflect the dynamic information interaction between organizations during the emergency process. Therefore, this article takes the recent COVID-19 epidemic in Hubei, China as a case, and uses social network analysis to reveal the dynamic evolution of communication networks, positions, roles, and tasks of organizations from the time dimension. The results show that (1) the ECN has changed from concentrated to decentralized over time; (2) the positions and roles of participating organizations in the ECN has changed, but there are still a few key organizations that at the central position in all phases of emergency communication; (3) the core tasks have changed due to emergency needs at each stage; (4) under the concentrated management system, the core organization of the ECN mainly comes from government organizations.