COVID-19 emerged in November 2019 leading to a global pandemic that has not only resulted in widespread medical complications and loss of life, but has also impacted global economies and transformed ...daily life. The current rapid response study in a convenience online sample quickly recruited 2,065 participants across the United States, Canada, and Europe in late March and early April 2020. Cross-sectional findings indicated elevated anxiety and depressive symptoms compared to historical norms, which were positively associated with COVID-19 concern more strongly than epidemiological data signifying risk (e.g., world and country confirmed cases). Employment loss was positively associated with greater depressive symptoms and COVID-19 concern, and depressive symptoms and COVID-19 concern were significantly associated with more stringent self-quarantine behavior. The rapid collection of data during the early phase of this pandemic is limited by under-representation of non-White and middle age and older adults. Nevertheless, these findings have implications for interventions to slow the spread of COVID-19 infection.
Wrist-worn smart watches and fitness monitors (ie, wearables) have become widely adopted by consumers and are gaining increased attention from researchers for their potential contribution to ...naturalistic digital measurement of health in a scalable, mobile, and unobtrusive way. Various studies have examined the accuracy of these devices in controlled laboratory settings (eg, treadmill and stationary bike); however, no studies have investigated the heart rate accuracy of wearables during a continuous and ecologically valid 24-hour period of actual consumer device use conditions.
The aim of this study was to determine the heart rate accuracy of 2 popular wearable devices, the Apple Watch 3 and Fitbit Charge 2, as compared with the gold standard reference method, an ambulatory electrocardiogram (ECG), during consumer device use conditions in an individual. Data were collected across 5 daily conditions, including sitting, walking, running, activities of daily living (ADL; eg, chores, brushing teeth), and sleeping.
One participant, (first author; 29-year-old Caucasian male) completed a 24-hour ecologically valid protocol by wearing 2 popular wrist wearable devices (Apple Watch 3 and Fitbit Charge 2). In addition, an ambulatory ECG (Vrije Universiteit Ambulatory Monitoring System) was used as the gold standard reference method, which resulted in the collection of 102,740 individual heartbeats. A single-subject design was used to keep all variables constant except for wearable devices while providing a rapid response design to provide initial assessment of wearable accuracy for allowing the research cycle to keep pace with technological advancements. Accuracy of these devices compared with the gold standard ECG was assessed using mean error, mean absolute error, and mean absolute percent error. These data were supplemented with Bland-Altman analyses and concordance class correlation to assess agreement between devices.
The Apple Watch 3 and Fitbit Charge 2 were generally highly accurate across the 24-hour condition. Specifically, the Apple Watch 3 had a mean difference of -1.80 beats per minute (bpm), a mean absolute error percent of 5.86%, and a mean agreement of 95% when compared with the ECG across 24 hours. The Fitbit Charge 2 had a mean difference of -3.47 bpm, a mean absolute error of 5.96%, and a mean agreement of 91% when compared with the ECG across 24 hours. These findings varied by condition.
The Apple Watch 3 and the Fitbit Charge 2 provided acceptable heart rate accuracy (<±10%) across the 24 hour and during each activity, except for the Apple Watch 3 during the daily activities condition. Overall, these findings provide preliminary support that these devices appear to be useful for implementing ambulatory measurement of cardiac activity in research studies, especially those where the specific advantages of these methods (eg, scalability, low participant burden) are particularly suited to the population or research question.
The metallurgy industry that was crucial in developing Chinese economy also enhanced energy consumption and carbon emissions. This paper examines the impact of economic variables on carbon emissions ...from the metallurgy industry of China, where energy structure, energy intensity, carbon intensity, industrial structure, and labor productivity were utilized in analyzing carbon dioxide emissions within a quantile models framework. Quantile estimates unveiled varying effects of variables across spectrum of carbon emissions and averagely, a unit increase in the above economic variables will influence carbon emissions by 97.2 percent, 100.3 percent, 118.6 percent, 98.4 percent and 100.2 percent approximately. Across all quantiles, results showed that carbon intensity had the greatest impact on carbon dioxide emissions, then energy intensity, labor productivity, industrial structure, and energy structure, most but not all the industry was plagued by carbon intensity, while industrial scale should be minimized optimally, labor productivity should be improved too. Energy intensity is the most influencing factor, prompting an urgent need for technology advancement The uniqueness of the metallurgy industry must be considered when administering economic policies across the industry in China. The enhancement of clean energy technology and optimizing energy structure are crucial for carbon emissions reduction and a review of energy consumption by the industry to accommodate renewable energy is recommended.
Functional micropeptides can be concealed within RNAs that appear to be noncoding. We discovered a conserved micropeptide, which we named myoregulin (MLN), encoded by a skeletal muscle-specific RNA ...annotated as a putative long noncoding RNA. MLN shares structural and functional similarity with phospholamban (PLN) and sarcolipin (SLN), which inhibit SERCA, the membrane pump that controls muscle relaxation by regulating Ca2+ uptake into the sarcoplasmic reticulum (SR). MLN interacts directly with SERCA and impedes Ca2+ uptake into the SR. In contrast to PLN and SLN, which are expressed in cardiac and slow skeletal muscle in mice, MLN is robustly expressed in all skeletal muscle. Genetic deletion of MLN in mice enhances Ca2+ handling in skeletal muscle and improves exercise performance. These findings identify MLN as an important regulator of skeletal muscle physiology and highlight the possibility that additional micropeptides are encoded in the many RNAs currently annotated as noncoding.
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•Myoregulin is a micropeptide encoded by an annotated long noncoding RNA•Myoregulin is a transmembrane alpha helix expressed only in skeletal muscle•Myoregulin regulates Ca2+ handling by inhibiting the pump activity of SERCA•Myoregulin KO mice show improved exercise performance and Ca2+ handling in muscle
Myoregulin is a skeletal muscle-specific micropeptide that regulates muscle performance by modulating intracellular calcium handling.
This research examines the impact of GDP per capita (gross domestic product), energy intensity (EI), carbon intensity (CI), and total population on carbon dioxide emissions in China’s transport ...industry using quantile analysis from 1980 to 2010. Obviously the study on carbon dioxide has garnered attention globally due to climate change and its relation to green house gas emissions and several other factors, and considering the alarming pace of industrialization and urbanization in China which has led to rapid economic growth and high energy consumption. Also, the percentage of oil consumption to total oil demand in the transport industry of China was 38.2% for the year 2010 which has significantly raised the emission level of carbon dioxide. In this study, having confirmed stationarity and that there exist a long term relationship among our variables (carbon emission, gross domestic product, energy intensity, carbon intensity, and urbanization), we checked which variable(s) has a greater impact on carbon emission on different quantiles. Our quantile estimates showed how the effects of the independent variables (gross domestic product, energy intensity, carbon intensity, and urbanization) varies across the levels of the dependent variable (carbon emission), the results showed that these effect are not constant across the spectrum of the dependent variable. Unlike the gross domestic product, energy intensity, carbon intensity, and urbanization had an inconsistent effects across the spectrum of carbon emissions. All variables were statistically significant in all the spectrum of carbon emissions except for urbanization, which was only significant at the tail ends of the distribution (urbanization was only significant at 10th percentile and 90th percentile respectively). The results therefore shows clearly that GDP, energy intensity, carbon intensity has a greater impact on carbon emission than urbanization, this makes sense to an extent in real life comparing the fact that China is still in the process of urbanization, so not all cities are urban for now. However, this shows that where urbanization exist, it can influence carbon emissions alongside other factors immensely.
Curbing the Credit Cycle Aikman, David; Haldane, Andrew G.; Nelson, Benjamin D.
The Economic journal (London),
June 2015, Volume:
125, Issue:
585
Journal Article
Peer reviewed
Credit cycles have been a characteristic of advanced economies for over 100 years. On average, a sustained pick-up in the ratio of credit to GDP has been highly correlated with banking crises. The ...boom phases of the cycle are characterised by large deviations in credit from trend. A range of mechanisms can generate these effects, each of which has strategic complementarity between banks at its core. Macro-prudential policy could curb these credit cycles, both through raising the cost of maintaining risky portfolios and through an expectations channel that operates via banks' perceptions of other banks' actions.
How does bank profitability vary with interest rates? We present a model of a monopolistically competitive bank subject to repricing frictions and test the model's predictions using a unique panel ...data set on UK banks. We find evidence that large banks retain a residual exposure to interest rates, even after accounting for hedging activity operating through the trading book. In the long run, both level and slope of the yield curve contribute positively to profitability. In the short run, however, increases in market rates compress interest margins, consistent with the presence of nonnegligible loan pricing frictions.
China is at the stage of industrialization and urbanization and because the energy demand and consumption for this process is rigid, coupled with emissions and global warming awareness, China is on a ...path to cut back emissions as she focuses on alternative and sustainable way to green the economy. This research investigates determining factors in measuring the dynamic changes in green development growth index (GDGI) over a given time frame. By adopting a non-radial directional distance function (NDDF), where more pollutants are added like sulphur dioxide emissions, solid wastes, waste water, and carbon dioxide emissions instead of using only one pollutant in measurement and using a global distance envelop analysis (DEA) to model green performance by considering both desirable and undesirable outputs, the model was decomposed into efficiency change (EC) index, best practice gap change (BPC) index, and technology gap change (TCG) index and these three indexes were employed to measure the green development performance in thirty provinces across china from 2000 to 2012. Results showed that provinces in the eastern region of China are greener than the central and western regions. Analyzing all three calculated dependent variables from a quantile perspective revealed that effects of EC, BPC, and TGC varied across different quantiles of GDGI. The coefficients of BPC were more significant than EC across quantiles, and TGC coefficients only became significant from Q(0.35), and continued on this path until the last observed quantile Q(0.95) however it was less than EC in terms of significance. The values of pseudo R2 also continued to increase from Q(0.20) until the last observed quantile with 86% accuracy in prediction recorded at Q(0.95). Analyzing the 80th percentile revealed that the coefficient of BPC was highest in this percentile which implies that a unit increase in best practice gap change, will influence green development growth by 102.3 percent, and a unit increase in efficiency change, will accelerate green development growth by 99.41 percent while a unit increase in technical gap ratio change will produce 99.38 percent increase in green development growth of China.
Muscle contraction depends on release of Ca²⁺ from the sarcoplasmic reticulum (SR) and reuptake by the Ca²⁺ adenosine triphosphatase SERCA. We discovered a putative muscle-specific long noncoding RNA ...that encodes a peptide of 34 amino acids and that we named dwarf open reading frame (DWORF). DWORF localizes to the SR membrane, where it enhances SERCA activity by displacing the SERCA inhibitors, phospholamban, sarcolipin, and myoregulin. In mice, overexpression of DWORF in cardiomyocytes increases peak Ca²⁺ transient amplitude and SR Ca²⁺ load while reducing the time constant of cytosolic Ca²⁺ decay during each cycle of contraction-relaxation. Conversely, slow skeletal muscle lacking DWORF exhibits delayed Ca²⁺ clearance and relaxation and reduced SERCA activity. DWORF is the only endogenous peptide known to activate the SERCA pump by physical interaction and provides a means for enhancing muscle contractility.
Chinese nonmetallic mineral products industry is one of the largest electricity consumer in China and has a large impact on overall electricity consumption in China. This paper examines the impact of ...economic variables on the demand for electricity in Chinese nonmetallic mineral products industry where economic growth, sectoral value added per worker, sectoral R&D intensity, and energy price were utilized to analyze sectoral electricity consumption, with an application of quantile model. The paper’s estimates unveiled the varying effects of economic variables across the spectrum of sectoral electricity consumption where the coefficient of economic growth was positive and significant across all quantiles, while sectoral value-added per worker had both positive and negative significant coefficients. An increase in income level and sectoral value added per worker will increase the electricity consumed by the industry, however, the latter will also enhance a decreasing trend in few regions across China and did not influence high energy efficiency but rather enhanced the production of additional outputs, while sectoral R&D intensity and energy price will ensure a substantial decrease in sectoral electricity consumption with the latter having a greater impact. Increase in investment for sectoral R&D intensity will boost technological advancement and is recommended as a cornerstone to ensuring decline in sectoral energy consumption that will buttress sectoral value added per worker coupled with a robust energy price.
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