Beyond Coal: Facing our Landscape Legacy & Seeing our Renewable Future

Beyond Coal is a park design project located at the Gateway Mall in St. Louis. Coal has been an essential source of power generation since the 1800s. Coal is a non-renewable resource and causes environmental pollution in the process of using coal to generate electricity. Since the 21st century, there has been a shift from coal to renewable resources. In Missouri, however, coal still generates more than 70 percent of electricity. Coal ash from power generation is buried underground, threatening soil and groundwater resources. Climate change is further exacerbated by the large amounts of greenhouse gases produced by power generation. As a landscape architect living in Missouri, I need to tell the story of coal power to the people who also live in this land. Beyond coal aims to visualize the invisible hazards generated by coal power generation, and make people realize that every kilowatt of electricity we consume is endangering the natural environment and human health. The shape of the Mississippi River is carved on the grounds of the Gateway Mall in St. Louis. Three coal-fired power plants along the river that have a deep impact on St. Louis are being marked on the site. The density of the poles was used as a design tool to represent areas contaminated by coal. At the same time, the project will strongly encourage the use of renewable energy. Solar panels are placed on the facades and roofs of adjacent high-rises to provide power for electric car charging piles on the site. This design is expected to transform the existing park with low popularity through the expression of landscape design. While making the public space more interesting, it also inspires people to think about the pollution caused by coal power generation, thus promoting the transformation from coal to renewable energy.https://openscholarship.wustl.edu/fall2019_stanek/1000/thumbnail.jp

AFS: An Attention-based mechanism for Supervised Feature Selection

As an effective data preprocessing step, feature selection has shown its effectiveness to prepare high-dimensional data for many machine learning tasks. The proliferation of high di-mension and huge volume big data, however, has brought major challenges, e.g. computation complexity and stability on noisy data, upon existing feature-selection techniques. This paper introduces a novel neural network-based feature selection architecture, dubbed Attention-based Feature Selec-tion (AFS). AFS consists of two detachable modules: an at-tention module for feature weight generation and a learning module for the problem modeling. The attention module for-mulates correlation problem among features and supervision target into a binary classification problem, supported by a shallow attention net for each feature. Feature weights are generated based on the distribution of respective feature se-lection patterns adjusted by backpropagation during the train-ing process. The detachable structure allows existing off-the-shelf models to be directly reused, which allows for much less training time, demands for the training data and requirements for expertise. A hybrid initialization method is also intro-duced to boost the selection accuracy for datasets without enough samples for feature weight generation. Experimental results show that AFS achieves the best accuracy and stability in comparison to several state-of-art feature selection algo-rithms upon both MNIST, noisy MNIST and several datasets with small samples.Comment: 9 pages, 5 figures, published in the AAAI 201

Hybrid localized surface plasmon resonance and quartz crystal microbalance sensor for label free biosensing

We report on the design and fabrication of a hybrid sensor that integrates transmission-mode localized surface plasmonic resonance (LSPR) into a quartz crystal microbalance (QCM) for studying biochemical surface reactions. The coupling of LSPR nanostructures and a QCM allows optical spectra and QCM resonant frequency shifts to be recorded simultaneously and analyzed in real time for a given surface adsorption process. This integration simplifies the conventional combination of SPR and QCM and has the potential to be miniaturized for application in point-of-care (POC) diagnostics. The influence of antibody-antigen recognition effect on both the QCM and LSPR has been analyzed and discussed.`

Solidarity tourism: A pathway to revitalising the health of vulnerable war-affected populations?

The struggles of war are felt by all who occupy an affected region (and beyond), irrespective of whether they are in active combat. This experience has physical effects (e.g. injury, illness, malnutrition, disability, sexual violence, and/or death) and emotional impacts (e.g. posttraumatic stress disorder, depression, and anxiety) [1-3]. The terror associated with war disrupts lives and relationships, leaving individuals, families, and communities distressed. Due to such immediate and long-term adverse outcomes, war represents a highly destructive and enduring public health emergency [4]. . .

Tourism experiences reduce the risk of cognitive impairment in the Chinese older adult: A prospective cohort study

Background: Given the etiological complexity of cognitive impairment, no effective cure currently exists for precise treatment of dementia. Although scholars have noted tourism’s potential role in managing cognitive impairment and mild dementia, more robust empirical investigation is needed in this area. This study aimed to examine the associations between tourism and cognitive impairment and dementia in older Chinese adults. Method: From a nationwide community-based cohort, 6,717 individuals aged ≥ 60 were recruited from 2011 to 2014, of whom 669 (9.96%) had had at least one tourism experience in the 2 years prior to enrollment. All the participants were then prospectively followed up until 2018. The association between tourism and cognitive impairment was examined by the Cox proportional hazards regression model. The adjusted hazard ratio (aHR) and its 95% confidence interval (CI) were calculated to evaluate the effect of tourism experience on cognitive impairment and dementia. Results: A total of 1,416 individuals were newly diagnosed with cognitive impairment and 139 individuals with dementia onset during follow-up. The incidence of cognitive impairment was significantly lower among participants with tourism experiences (316.94 per 10,000 person-years) than those without such experiences (552.38 per 10,000 person-years). Cox regression showed that tourism decreased the risk of cognitive impairment (aHR = 0.69, 95% CI: 0.41–0.62) when adjusted for behavioral covariates and characteristics. Compared with participants without tourism experiences, those with 1, 2, and ≥ 3 tourism experiences had a lower risk of cognitive impairment with the aHRs of 0.72 (95% CI: 0.52–0.99), 0.65 (0.42–1.01), and 0.68 (0.44–0.98), respectively. Tourism experiences also reduced participants’ risk of dementia (aHR = 0.41, 95% CI: 0.19–0.89). Conclusion: Our findings demonstrated associations between tourism and reduced risks of cognitive impairment and dementia in older Chinese adults. Thus, tourism could serve as a novel approach to dementia prevention

Hsa-miR-196a2 Rs11614913 Polymorphism Contributes to Cancer Susceptibility: Evidence from 15 Case-Control Studies

BACKGROUND: MicroRNAs (miRNAs) are a family of endogenous, small and noncoding RNAs that negatively regulate gene expression by suppressing translation or degrading mRNAs. Recently, many studies investigated the association between hsa-miR-196a2 rs11614913 polymorphism and cancer risk, which showed inconclusive results. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a meta-analysis of 15 studies that included 9,341 cancer cases and 10,569 case-free controls. We assessed the strength of the association, using odds ratios (ORs) with 95% confidence intervals (CIs). Overall, individuals with the TC/CC genotypes were associated with higher cancer risk than those with the TT genotype (OR=1.18, 95% CI=1.03-1.34, P<0.001 for heterogeneity test). In the stratified analyses, we observed that the CC genotype might modulate breast cancer risk (OR=1.11, 95%CI=1.01-1.23, Pheterogeneity=0.210) and lung cancer risk (OR=1.25, 95%CI=1.06-1.46, Pheterogeneity=0.958), comparing with the TC/TT genotype. Moreover, a significantly increased risk was found among Asian populations in a dominant model (TC/CC versus TT, OR=1.24, 95% CI=1.07-1.43, Pheterogeneity=0.006). CONCLUSIONS: These findings supported that hsa-miR-196a2 rs11614913 polymorphism may contribute to the susceptibility of cancers

Expression of miRNAs and Their Cooperative Regulation of the Pathophysiology in Traumatic Brain Injury

Traumatic brain injury (TBI) is a leading cause of injury-related death and disability worldwide. Effective treatment for TBI is limited and many TBI patients suffer from neuropsychiatric sequelae. The molecular and cellular mechanisms underlying the neuronal damage and impairment of mental abilities following TBI are largely unknown. Here we used the next generation sequencing platform to delineate miRNA transcriptome changes in the hippocampus at 24 hours and 7 days following TBI in the rat controlled cortical impact injury (CCI) model, and developed a bioinformatic analysis to identify cellular activities that are regulated by miRNAs differentially expressed in the CCI brains. The results of our study indicate that distinct sets of miRNAs are regulated at different post-traumatic times, and suggest that multiple miRNA species cooperatively regulate cellular pathways for the pathological changes and management of brain injury. The distinctive miRNAs expression profiles at different post-CCI times may be used as molecular signatures to assess TBI progression. In addition to known pathophysiological changes, our study identifies many other cellular pathways that are subjected to modification by differentially expressed miRNAs in TBI brains. These pathways can potentially be targeted for development of novel TBI treatment

A protocol of Chinese expert consensuses for the management of health risk in the general public

IntroductionNon-communicable diseases (NCDs) represent the leading cause of mortality and disability worldwide. Robust evidence has demonstrated that modifiable lifestyle factors such as unhealthy diet, smoking, alcohol consumption and physical inactivity are the primary causes of NCDs. Although a series of guidelines for the management of NCDs have been published in China, these guidelines mainly focus on clinical practice targeting clinicians rather than the general population, and the evidence for NCD prevention based on modifiable lifestyle factors has been disorganized. Therefore, comprehensive and evidence-based guidance for the risk management of major NCDs for the general Chinese population is urgently needed. To achieve this overarching aim, we plan to develop a series of expert consensuses covering 15 major NCDs on health risk management for the general Chinese population. The objectives of these consensuses are (1) to identify and recommend suitable risk assessment methods for the Chinese population; and (2) to make recommendations for the prevention of major NCDs by integrating the current best evidence and experts’ opinions.Methods and analysisFor each expert consensus, we will establish a consensus working group comprising 40–50 members. Consensus questions will be formulated by integrating literature reviews, expert opinions, and an online survey. Systematic reviews will be considered as the primary evidence sources. We will conduct new systematic reviews if there are no eligible systematic reviews, the methodological quality is low, or the existing systematic reviews have been published for more than 3 years. We will evaluate the quality of evidence and make recommendations according to the GRADE approach. The consensuses will be reported according to the Reporting Items for Practice Guidelines in Healthcare (RIGHT)

Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study

Background The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. Methods We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, Rt, for the two incidence estimates. Findings From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6–0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56–0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38–0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the Rt of B.1.1.7 by a factor of 1·35 (95% CI 1·02–1·69) relative to pre-existing variants. However, Rt fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant. Interpretation The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant. Funding Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society