Effects of plasma non-uniformities and kinetic dispersiveness on the spontaneous excitation of geodesic acoustic mode (GAM) by reversed shear Alfvén eigenmode (RSAE) are investigated numerically. It is found that, due to the turning points induced by the shear Alfvén continuum structure, the nonlinear excitation of GAM is a quasiexponentially growing absolute instability. As the radial dependence of GAM frequency and pump RSAE mode structure are accounted for, the radially inward propagating GAM is preferentially excited, leading to core localized thermal plasma heating by GAM collisionless damping. Our work, thus, suggests that GAM excitation plays a crucial role in not only RSAE nonlinear saturation, but also anomalous fuel ion heating in future reactors.

We investigated whether the one-time application of polymer-coated urea (PCU) before transplanting could simultaneously improve the grain yield and nitrogen use efficiency (NUE) of japonica-indica hybrid rice (JIHR) through a field experiment. The local high-yield JIHR cultivar Chunyou-927 was field grown during the rice-growing seasons in 2019 and 2020. The experiment consisted of three treatments: no nitrogen application (0N), application of conventional urea (CU), and the one-time application of PCU. Grain yield was 1.0–1.3 t/ha higher, and agronomic NUE (kg grain yield increase per kg N applied) was 5.2–5.9 kg/kg higher, respectively, under the PCU treatment compared with the CU treatment across the two study years. When compared with the CU treatment, the PCU treatment could (1) improve root morphological trait, (2) reduce redundant vegetative growth during the early growth period, (3) increase matter production during the mid and late growth period, and (4) increase plant activity during the grain-filling period. Overall, our findings indicate that one-time PCU application before transplanting of the JIHR cultivar holds great promise for increasing grain yield and NUE.

Unmanned aerial vehicle (UAV) swarm coverage is one of the key technologies for multi-UAV cooperation, which plays an important role in collaborative investigation, detection, rescue and other applications. Aiming at the coverage optimisation problem of UAV in the target area, a collaborative visual coverage control method under positioning uncertainty is presented. First, the visual perception area with imprecise localisation, UAV model and sensor model are created based on the given task environment. Second, a regional division algorithm for the target task area is designed based on the principle of Guaranteed Voronoi (GV) diagram. Then a visual area coverage planning algorithm is designed, in which the task area is allocated to the UAV according to the corresponding weight coefficient of each area, and the input control law is adjusted by the expected state information of the UAV, so that the optimal coverage quality target value and the maximum coverage of the target area can be achieved. Finally, three task scenarios for regional division and coverage planning are simulated respectively, the results show that the proposed area coverage planning algorithm can realise the optimal regional distribution and can obtain more than 90% coverage in different scenarios.

We zero in on the expected returns of long-short portfolios based on 204 stock market anomalies by accounting for i) effective bid–ask spreads, ii) post-publication effects, and iii) the modern era of trading technology that began in the early 2000s. Net of these effects, the average anomaly’s expected return is a measly 4 bps per month. The strongest anomalies net, at best, 10 bps after controlling for data mining. Several methods for combining anomalies net around 20 bps. Expected returns are negligible despite cost mitigations that produce impressive net returns in-sample and the omission of additional trading costs, like price impact.

The great demographic pressure brings tremendous volume of beef demand. The key to solve this problem is the growth and development of Chinese cattle. In order to find molecular markers conducive to the growth and development of Chinese cattle, sequencing was used to determine the position of copy number variations (CNVs), bioinformatics analysis was used to predict the function of ZNF146 gene, real-time fluorescent quantitative polymerase chain reaction (qPCR) was used for CNV genotyping and one-way analysis of variance was used for association analysis. The results showed that there exists CNV in Chr 18: 47225201-47229600 (5.0.1 version) of ZNF146 gene through the early sequencing results in the laboratory and predicted ZNF146 gene was expressed in liver, skeletal muscle and breast cells, and was amplified or overexpressed in pancreatic cancer, which promoted the development of tumour through bioinformatics. Therefore, it is predicted that ZNF146 gene affects the proliferation of muscle cells, and then affects the growth and development of cattle. Furthermore, CNV genotyping of ZNF146 gene was three types (deletion type, normal type and duplication type) by Real-time fluorescent quantitative PCR (qPCR). The association analysis results showed that ZNF146-CNV was significantly correlated with rump length of Qinchuan cattle, hucklebone width of Jiaxian red cattle and heart girth of Yunling cattle. From the above results, ZNF146-CNV had a significant effect on growth traits, which provided an important candidate molecular marker for growth and development of Chinese cattle.

Background: This is a population-based retrospective study of cardiac and neurological complications of COVID-19 among Ontario Chinese and South Asians. Methods: From January 1, 2020 to September 30, 2020 using the last name algorithm to identify Ontario Chinese and South Asians who were tested positive by PCR for COVID-19, their demographics, cardiac, and neurological complications including hospitalization and emergency visit rates were analyzed compared to the general population. Results: Chinese (N = 1,186) with COVID-19 were found to be older (mean age 50.7 years) compared to the general population (N = 42,547) (mean age 47.6 years) (p < 0.001), while South Asians (N = 3,459) were younger (age of 42.1 years) (p < 0.001). For neurological complications, the 30-day crude rate for Chinese was 160/10,000 (p < 0.001); South Asians was 40/10,000 (p = 0.526), and general population was 48/10,000. The 30-day all-cause mortality rate was significantly higher for Chinese at 8.1% vs 5.0% for the general population (p < 0.001), while it was lower in South Asians at 2.1% (p < 0.001). Conclusions: Chinese and South Asians in Ontario with COVID-19 during the first wave of the pandemic were found to have a significant difference in their demographics, cardiac, and neurological outcomes.

Based on the theoretical research of 3D printing and circular economy, combined with case studies, this paper analyzes the advantages of 3D printing in realizing circular economy and its influence on designers from the perspectives of “reduce”, “reuse”, “recycle” and distributed manufacturing. As a technological innovation, 3D printing not only promoted the transformation from linear economy to circular economy, but also had a certain impact on the role and skills of traditional designers.

Customer survey data is critical to supporting customer preference modeling in engineering design. We present a framework of information retrieval and survey design to ensure the collection of quality customer survey data for analyzing customers’ preferences in their consideration-then-choice decision-making and the related social impact. The utility of our approach is demonstrated through the survey design for customers in the vacuum cleaner market. Based on the data, we performed descriptive analysis and network-based modeling to understand customers’ preferences in consideration and choice.

The incidence of scarlet fever has increased dramatically in recent years in Chongqing, China, but there has no effective method to forecast it. This study aimed to develop a forecasting model of the incidence of scarlet fever using a seasonal autoregressive integrated moving average (SARIMA) model. Monthly scarlet fever data between 2011 and 2019 in Chongqing, China were retrieved from the Notifiable Infectious Disease Surveillance System. From 2011 to 2019, a total of 5073 scarlet fever cases were reported in Chongqing, the male-to-female ratio was 1.44:1, children aged 3–9 years old accounted for 81.86% of the cases, while 42.70 and 42.58% of the reported cases were students and kindergarten children, respectively. The data from 2011 to 2018 were used to fit a SARIMA model and data in 2019 were used to validate the model. The normalised Bayesian information criterion (BIC), the coefficient of determination (R2) and the root mean squared error (RMSE) were used to evaluate the goodness-of-fit of the fitted model. The optimal SARIMA model was identified as (3, 1, 3) (3, 1, 0)12. The RMSE and mean absolute per cent error (MAPE) were used to assess the accuracy of the model. The RMSE and MAPE of the predicted values were 19.40 and 0.25 respectively, indicating that the predicted values matched the observed values reasonably well. Taken together, the SARIMA model could be employed to forecast scarlet fever incidence trend, providing support for scarlet fever control and prevention.

Background: In Canada, it’s unknown if the prevalence of stroke survivorship differs in the population with active cancer compared to those without cancer. Methods: We analyzed the 2015-2016 iteration of the Canadian Community Health Survey. The prevalence of stroke survivorship was compared across risk factors using descriptive statistics. A multivariable logistic regression model was used to assess the association between cancer and prevalence of stroke survivorship. Covariates were assessed for effect modification and confounding using the maximum likelihood estimation method. Results: We analyzed 89,285 subjects. The prevalence of cancer and the prevalence of suffering from the effects of a stroke were 2.09% and 1.56%, respectively. Cancer was significantly associated with an increased prevalence of stroke survivorship with an odds ratio (OR) of 1.56 (95%CI: 1.24 – 1.98) after adjusting for age, sex, smoking status, education, household income, dyslipidemia, hypertension, diabetes. The association was stronger in younger age groups: the youngest age group (18 – 49 years) had the highest OR (6.49, 95%CI:2.01 – 20.94) for suffering from the effects of a stroke in association with the presence of cancer. Conclusions: In Canada, the presence of active cancer increases the odds of suffering from the effects of a stroke, particularly in the youngest age group.

Background: This is a population-based retrospective study of neurological and cardiac complications of COVID-19 among Ontario visible minorities: Chinese and South Asian Canadians Methods: From January 1, 2020 to September 30, 2020, using the last name algorithm, rates and types of cardiac and neurological complication of these two cohorts along with the general population in Ontario with COVID-19 were analysed by Institue of Clinical Evaluative Sciences. Results: Preliminary results show that Chinese-Canadians (N= 1,186) with COVID-19 are older with a mean age of 50.74 years old compared to general population (N= 42,547) of 47.57 years old (P< .001), while South Asians (N= 3,459) have a younger mean age of 42.08 years old (P< .001). Total cardiac and neurological complication rates, hospitalization rates and ICU admission rates are all higher for Chinese-Canadians while they are lower in South Asians and all achieving statistical significance (P < .001). Overall mortality rate is significantly higher for Chinese-Canadians at 8.1% vs 5.0% general population (P < .001). Conclusions: Chinese-Canadians with COVID-19 in Ontario were much older and have higher cardiac and neurological complication rates and overall mortality rate than the general population. These data have significant implications for proper prevention and appropriate management for these vulnerble elderly Chinese-Canadians.

We live in an age of datafication wherein nearly all aspects of our lives can be transformed into data and evaluated. The authors seek to make sense of the heightened datafication-enabled social control under China’s Social Credit System (SCS) by developing the concept of the data state. A “data state” is defined as a governance model enabling the state to comprehensively monitor, evaluate, and control its subjects through datafication, leaving them little room to defend their autonomy. We identify the multiple functions of the SCS in its development up to 2020 and analyze its inherent defects, including the decontextualized evaluation of individuals and the semi-automated imposition of disproportionate punishment. We argue that, if the SCS were to fully integrate its functions and connect to other data-driven governance initiatives, it would eventually allow the data self, carefully groomed by the state, to dominate the bio-self and turn China into a data state. Whereas China’s SCS may be unique and not easily replicated elsewhere, understanding its intricacies helps to enable the citizens of democratic societies to guard against the relentless growth of datafication that may result in an invincible and irreversible ecosystem for the emergence of a data state.

Do discriminatory US immigration policies affect foreign public opinion about Americans? When examining negative reactions to US actions perceived as bullying on the world stage, existing research has focused either on US policies that involve direct foreign military intervention or seek to influence foreign countries’ domestic economic policy or policies advocating minority representation. We argue that US immigration policies – especially when they are perceived as discriminatory – can similarly generate anti-American sentiment. We use a conjoint experiment embedded in a unique survey of Nigerian expatriates in Ghana. Comparing respondents before and after President Trump surpisingly announced a ban on Nigerian immigration to the United States, we find a large drop (13 percentage points) in Nigerian’s favorability towards Americans.