Spectral and Energy Efficiency of IRS-Assisted MISO Communication with Hardware Impairments

In this letter, we analyze the spectral and energy efficiency of an intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) downlink system with hardware impairments. An extended error vector magnitude (EEVM) model is utilized to characterize the impact of radio-frequency (RF) impairments at the access point (AP) and phase noise is considered at the IRS. We show that the spectral efficiency is limited due to the hardware impairments even when the numbers of AP antennas and IRS elements grow infinitely large, which is in contrast with the conventional case with ideal hardware. Moreover, the performance degradation at high SNR is shown to be mainly affected by the AP hardware impairments rather than by the phase noise at the IRS. We further obtain in closed form the optimal transmit power for energy efficiency maximization. Simulation results are provided to verify the obtained results

Violence against doctors is increasing worldwide. will the pandemic revert the trend?

In China the marketisation of health care, media criticism and public shaming led to a spiral of aggressions, write Milo Shaoqing Wang, Mia Raynard and Royston Greenwoo

Multivariate analyses of social-behavioral factors with health insurance coverage among Asian Americans in California

This study aimed to estimate the prevalence of uninsurance among California adults and Asian Americans, and to examine the associations of social-behavioral variables with uninsurance. A total of 24,136 adults (aged 18–64) including 2,060 Asian Americans were selected from the combined 2013–2014 California Health Interview Survey. Weighted univariate and multivariate logistic regression analyses were used to estimate the associations of potential factors with uninsurance. To evaluate the relationship of independent variables, the oblique principal component cluster analysis (OPCCA) was used to classify 9 variables into disjoint clusters. For Whites, African Americans, Latinos, and Asians, the prevalence of uninsurance was 8.5%, 10.3%, 24.7%, and 12.6%, respectively. Among Asians, the prevalence of uninsurance was 15.5%, 9.2%, 6.2%, 20.8% and 12.1% for Chinese, Filipinos, Japanese, Koreans, and Vietnamese, respectively. In the whole sample, multivariate logistic regression analysis revealed that being male, non-citizen, lower education, higher poverty, and current smoking were associated with uninsurance. Among Asians, compared to Koreans, being Filipinos and Vietnamese were associated with lower odds of being uninsured; meanwhile being male, non-citizen, lower education, and higher poverty were significantly associated with increased odds of uninsurance. Elder age groups and current smoking were significantly associated with increased odds of uninsurance in bivariate analysis; however, such associations disappeared after adjusting for other factors. Nine independent variables were divided into 2 clusters, where the variables in the same cluster were strongly correlated but had weak correlations with the variables in the other cluster. In conclusion, there are differences in the prevalence of uninsurance between Asians and Whites, and among Asian subgroups. Being male, non-citizen, lower education, higher poverty and current smoking were positively significantly associated with uninsurance

The Influence of Immigrant Generation on Obesity Among Asian Americans in California from 2013 to 2014

Objectives We aimed to examine the association between immigrant generation and obesity among Californian adults and Asian Americans. Results Overall, 23.3% of the Asian population was obese, and 40.0% was overweight. The percentage of 1st, 2nd, and 3rd generation were 72.7%, 22.6%, and 4.6%, respectively. Overall, 1st generation of Asians had lower odds of being obese compared to Whites (OR = 0.34, 95%CI = 0.26–0.45). Multiple logistic regression analyses showed that overall, 2nd generation (OR = 1.69, 95%CI = 1.10–2.60) and 3rd generation (OR = 2.33, 95%CI = 1.29–4.22) Asians had higher odds of being obese compared to 1st generation Asians. Among Chinese, compared to the 1st generation, the 3rd generation had increased likelihood of being obese (OR = 6.29, 95%CI = 2.38–16.6). Conclusion Compared to Whites, Hispanics, and Blacks, Asian immigrants are less likely to be obese. Among Asians, 2nd and 3rd generations were more likely to be obese compared to 1st generation. The obesity rate seems to increase the longer Asian immigrants remain in the U.S

Geographic Differences in Obesity Prevalence and Its Risk Factors Among Asian Americans: Findings from the 2013–2014 California Health Interview Survey

Geography disparities exist in obesity and obesity related conditions. This study aimed to examine the geographic differences in obesity prevalence and its risk factors among Asian Americans in California. Data (n = 4,000) from the 2013–2014 California Health Interview Survey were used. Obesity (≥27.5 kg/m2) was defined according to the World Health Organization Asian body mass index cut points in Asian groups. Results suggest that 66.5% of Asians lived in urban areas. Among Asian adults, obesity prevalence was highest in Filipinos (33.8%) and lowest in Koreans (12.8%). Compared to rural Vietnamese, obesity prevalence was higher for urban Vietnamese (8.3% vs. 20.2%, p = 0.0318). Weighted multiple logistic regression analyses showed that being 45–64 years (vs. 65 years or above), being Japanese, Filipino, or other Asians (vs. Chinese) were associated with a higher odds of obesity among urban residents; whereas being 18–44 years and being 45–64 years (vs. 65 years or older), being male, having high school education (vs. having graduate education) were associated with a higher odds of obesity among rural residents. Being Vietnamese (vs. Chinese) was associated with 64% decreased odds of obesity only among rural residents (95% confidence interval = 0.14–0.94). The findings show geography disparities in obesity among Asians in California

PRT Spidernet around rail hub for local empowerment of urban passenger transit: from conceptual design to simulation-based assessment methodology, with application to St Denis station of Grand Paris Express

The Spidernet concept consists in making a metropolitan, heavy rail station the hub of a web of elevated guided ways dedicated to small-size cabins driven automatically. Thus, comfortable point-to-point transport service would be provided to passengers, offering both speed and reliability (since its running would be uninterrupted), together with quick access and short wait at egress station were there sufficiently many " podcars ". This specific concept of Personal Rapid Transit (PRT) is purported to empower the local attraction of the heavy network and to develop the hub potential as service centre and urban centre. The paper investigates these issues in the case of the St Denis station in the Grand Paris Express network by the time horizon of implementation. After introducing the territorial context and putting forward a tentative scheme of Spidernet dedicated ways and stations, we turn to simulation to study potential demand, multimodal effects, fare sensitivity and potential revenues, as well as capital and operational costs. Two models are used complementarily: first, a macroscopic, four-step Travel Demand Model at the regional level; then, PRTSim is used for microscopic traffic simulation of both passengers and podcars. Microsimulation is essential to infer realistic enough traffic conditions on the supply side (way capacity, fleet size) as well as on the demand side (effective quality of service, wait time at access station, opportunity of car-sharing). The tentative estimation of revenues and costs suggests that financial profitability might be achieved. Yet a number of important topics still deserve further investigation