Rushchavez4517

Recently, design thinking has become recognized as a necessity for every student, especially when they engage in design-based learning, as a pedagogical approach to science, technology, engineering, and mathematics education. However, design-based learning is mostly based on forward engineering, in which students' design thinking can be nurtured by designing unknown solutions. Little is known about whether design thinking can be facilitated in the context of reverse engineering, when students learn from already designed products. This study therefore seeks to explore the perceptions of 38 ninth-grade students on the characteristics of design thinking before and after a four-week reverse engineering project, using Likert scales to measure six aspects of design thinking, namely (a) being comfortable with uncertainty and risks, (b) human-centeredness, (c) mindfulness to the process and impacts on others, (d) collaboratively working with diversity, (e) orientation to learning by making and testing, and (f) being confident and optimistic to use creativity. The data were analyzed using descriptive and inferential statistics, including means, standard deviations, paired-samples t-tests, and Wilcoxon signed-rank tests. The results indicate that two aspects, human-centeredness and being confident and optimistic to use creativity, were significant (p = 0.008 and p = 0.043, respectively), with size effects of 0.43 and 0.34, respectively. Based on this potential, reverse engineering can be a design-based learning approach to facilitate students' design thinking. It is recommended that instructional activities involving reverse engineering maintain some degree of ambiguity and risk to prevent design fixation among students.After affecting the world in unexpected ways, the virus has started mutating which is evident with the insurgence of its new variants. The governments, hospitals, schools, industries, and humans, in general, are looking for a potential solution in the vaccine which will eventually be available, but its timeline for eradicating the virus is yet unknown. Several researchers have encouraged and recommended the use of good practices such as physical healthcare monitoring, immunity boosting, personal hygiene, mental healthcare, and contact tracing for slowing down the spread of the virus. In this article, we propose the use of smart sensors integrated with the Internet of Medical Things to cover the spectrum of good practices in an automated manner. We present hypothetical frameworks for each of the good practice modules and propose the VIrus Resistance Framework using the Internet of Medical Things (VIRFIM) to tie all the individual modules in a unified architecture. Furthermore, we validate the realization of VIRFIM framework with two case studies related to physical activity monitoring and stress detection services. We envision that VIRFIM would be influential in assisting people with the new normal for current and future pandemics as well as instrumental in halting the economic losses, respectively. We also provide potential challenges and their probable solutions in compliance with the proposed VIRFIM.This research reviews challenges in building sustainable relationships between the parties involved in the crowdfunding and crowdsourcing projects, which are running in extreme situations, such as the COVID-19 pandemic. This study aims to solve problems that generate the crowdsourcing concerns and to find better alternatives to increase trust for crowdfunding among donors, as this impacts their strategic sustainability in the conditions of turbulence and COVID-induced financial crisis. It was found that factors influence donor decisions in different ways, yet the common tendency for donor activity is non-monotonicity. Future development in the field of sustainable relationships should focus on creating a donor classification system.The COVID-19 pandemic significantly affected data collection for the nation's primary source of household-level labor force data, the Current Population Survey (CPS). In the first four months of the pandemic period (March-June 2020) the average month-over-month nonresponse rate increased by 58 percent, while the size of newly entering cohorts declined by 37 percent relative to the prior 15 months. Together, these factors reduced the overall sample size of the CPS by around 16 percent. We hypothesize that these changes, and significant associated shifts in the demographic composition of the sample, were caused by the cessation of in-person interviewing. Geographic variation in nonresponse over this period does not appear related to variation in COVID case rates across metro areas or states. Using this change in interview method as a natural experiment, we compare labor market outcomes of those who entered the survey pre- and post-COVID pandemic and find that the change in how individuals were recruited into the survey affected estimates of unemployment and labor force participation. In an exercise generating a counterfactual group of "missing" respondents, we estimate that, between April and August of 2020, the average unemployment rate was 0.5 to 0.7 percentage points higher, and the labor force participation rate was 0.4 to 0.8 percentage points lower than estimates using the actual sample of respondents. One implication of these results is that web-based surveys, which are increasingly relied on in empirical labor market studies, may fail to reach important subpopulations of the labor market and that reweighting is unlikely to address the selection on outcomes we document.The lateral flow immunoassay (LFIA) has played a crucial role in early diagnosis during the current COVID-19 pandemic owing to its simplicity, speed and affordability for coronavirus antibody detection. However, the sensitivity of the commercially available LFIAs needs to be improved to better prevent the spread of the infection. Here, we developed an ultra-sensitive surface-enhanced Raman scattering-based lateral flow immunoassay (SERS-based LFIA) strip for simultaneous detection of anti-SARS-CoV-2 IgM and IgG by using gap-enhanced Raman nanotags (GERTs). The GERTs with a 1 nm gap between the core and shell were used to produce the "hot spots", which provided about 30-fold enhancement as compared to conventional nanotags. The COVID-19 recombinant antigens were conjugated on GERTs surfaces and replaced the traditional colloidal gold for the Raman sensitive detection of human IgM and IgG. The LODs of IgM and IgG were found to be 1 ng/mL and 0.1 ng/mL (about 100 times decrease was observed as compared to commercially available LFIA strips), respectively. Moreover, under the condition of common nano-surface antigen, precise SERS signals proved the unreliability of quantitation because of the interference effect of IgM on IgG.An epidemic multi-group model formed by interconnected SEIR-like structures is formulated and used for data fitting to gain insight into the COVID-19 dynamics and into the role of non-pharmaceutical control actions implemented to limit the infection spread since its outbreak in Italy. The single submodels provide a rather accurate description of the COVID-19 evolution in each subpopulation by an extended SEIR model including the class of asymptomatic infectives, which is recognized as a determinant for disease diffusion. The multi-group structure is specifically designed to investigate the effects of the inter-regional mobility restored at the end of the first strong lockdown in Italy (June 3, 2020). In its time-invariant version, the model is shown to enjoy some analytical stability properties which provide significant insights on the efficacy of the implemented control measurements. In order to highlight the impact of human mobility on the disease evolution in Italy between the first and second wave onset, the model is applied to fit real epidemiological data of three geographical macro-areas in the period March-October 2020, including the mass departure for summer holidays. The simulation results are in good agreement with the data, so that the model can represent a useful tool for predicting the effects of the combination of containment measures in triggering future pandemic scenarios. Particularly, the simulation shows that, although the unrestricted mobility alone appears to be insufficient to trigger the second wave, the human transfers were crucial to make uniform the spatial distribution of the infection throughout the country and, combined with the restart of the production, trade, and education activities, determined a time advance of the contagion increase since September 2020.Angiotensin converting enzyme 2 (ACE2) is a terminal carboxypeptidase, which cleaves single terminal residues from several bioactive peptides such as Angiotensin II (AngII). Many investigations indicated that ACE2 functions in angiotensin system and plays a crucial role in inflammatory lung diseases. However, the mechanism behind the involvement of ACE2 in inflammatory lung disease has not been fully elucidated. In this study, BEAS-2B cells were treated with gradient concentration of AngII and lipopolysaccharide (LPS) to induce inflammatory condition. Quantitative RT-PCR was performed to detect the level of ACE2 and miR-143-3p. Western blotting and immunofluorescence assays were performed to measure the expression of related proteins. The levels of inflammatory cytokines and cell viability were respectively measured by ELISA and CCK-8 kits. And ACE2 activity was detected by corresponding commercial kits. Bioinformatics methods were employed to predict the potential microRNA targeting ACE2, which was then confential molecular target for the treatment of lung inflammation.

The purpose of this mixed-methods triangulation study was to assess the face validity and comprehension of a femicide risk assessment tool, the Danger Assessment-Brazil (DA-Brazil) among women seeking care in a one stop center for abused women in Curitiba, Brazil. Our secondary aim was to assess professionals' perceptions of feasibility for using the DA-Brazil in the same setting.

Fifty-five women experiencing relationship violence completed the instrument and participated in cognitive interviews about their experience; professionals attending survivors were also interviewed.

The vast majority of women described the DA-Brazil instrument as being easy to comprehend (

 = 41, 73.2%). Nearly half of participants (

 = 26, 46.4%) had some kind of question regarding the DA-Brazil calendar, a tool to visualize abuse frequency and severity. Queries aligned with five categories recollection of dates, scale, relationship status, terminology, and discomfort. Professionals reported that the DA-Brazil instrument would support referral decision-making.

The overall face validity and comprehension of the DA-Brazil appears to be high. The majority of challenges were around the calendar activity. Professional perceptions of the DA-Brazil suggest a high degree of feasibility for its use in Brazilian healthcare settings. In order for the DA-Brazil to effectively be administered with facilitated support there is a need for training on the best use of the instrument. DIRECT RED 80 Accurate assessment of femicide risk is critical in a country like Brazil with high rates of femicide. The DA-Brazil provides a valid assessment of femicide risk and has the potential to trigger early intervention for those at risk.

The online version contains supplementary material available at 10.1007/s10896-021-00313-1.

The online version contains supplementary material available at 10.1007/s10896-021-00313-1.