Hard-input-hard-output capacity analysis of UWB BPSK systems with timing errors

The hard-input-hard-output capacity of a binary phase-shift keying (BPSK) ultrawideband system is analyzed for both additive white Gaussian noise and multipath fading channels with timing errors. Unlike previous works that calculate the capacity with perfect synchronization and/or multiple-access interference only, our analysis considers timing errors with different distributions, as well as the interpath (IPI), interchip (ICI), and intersymbol (ISI) interferences, as in practical systems. The sensitivity of the channel capacity to the timing error is examined. The effects of pulse shape, the multiple-access technique, the number of users, and the number of chips are studied. It is found that time hopping is less sensitive to the pulse shape and that the timing error has higher capacity than direct sequence due to its low duty of cycle. Using these results, one can choose appropriate system parameters for different applications

Male Clients of Male Sex Workers in China: An Ignored High-Risk Population.

BackgroundThere is a high prevalence of HIV/syphilis among male sex workers, but no formal study has ever been conducted focusing on male clients of male sex workers (MCM). A detailed investigation was thus called for, to determine the burden and sociobehavioral determinants of HIV and syphilis among these MCM in China.MethodsAs part of a multicenter cross-sectional study, using respondent-driven and snowball sampling, 2958 consenting adult men who have sex with men (MSM) were recruited, interviewed, and tested for HIV and syphilis between 2008 and 2009. The distributions of sociodemographic characteristics, risk behaviors, and HIV/syphilis prevalence were determined and compared between MCM and other MSM.ResultsAmong recruited MSM, 5.0% (n = 148) were MCM. HIV prevalences for MCM and other MSM were 7.4% and 7.7%, whereas 18.9% and 14.0% were positive for syphilis, respectively. Condomless anal intercourse (CAI) was reported by 59.5% of MCM and 48.2% of MSM. Multiple logistic regression revealed that compared with other MSM, MCM were more likely to have less education [for ≤ elementary level, adjusted odds ratio (aOR) = 3.13, 95% confidence interval (95% CI): 1.42 to 6.90], higher income (for >500 US Dollars per month, aOR = 2.97, 95% CI: 1.53 to 5.77), more often found partners at parks/restrooms (aOR = 4.01, 95% CI: 2.34 to 6.85), reported CAI (aOR = 1.49, 95% CI: 1.05 to 2.10), reported a larger sexual network (for ≥ 10, aOR = 2.70, 95% CI: 1.44 to 5.07), and higher odds of syphilis (aOR = 1.54, 95% CI: 1.00 to 2.38).ConclusionsThe greater frequency of risk behaviors and high prevalence of HIV and syphilis indicated that HIV/syphilis prevention programs in China need to pay special attention to MCM as a distinct subgroup, which was completely ignored until date

GNNHLS: Evaluating Graph Neural Network Inference via High-Level Synthesis

With the ever-growing popularity of Graph Neural Networks (GNNs), efficient GNN inference is gaining tremendous attention. Field-Programming Gate Arrays (FPGAs) are a promising execution platform due to their fine-grained parallelism, low-power consumption, reconfigurability, and concurrent execution. Even better, High-Level Synthesis (HLS) tools bridge the gap between the non-trivial FPGA development efforts and rapid emergence of new GNN models. In this paper, we propose GNNHLS, an open-source framework to comprehensively evaluate GNN inference acceleration on FPGAs via HLS, containing a software stack for data generation and baseline deployment, and FPGA implementations of 6 well-tuned GNN HLS kernels. We evaluate GNNHLS on 4 graph datasets with distinct topologies and scales. The results show that GNNHLS achieves up to 50.8x speedup and 423x energy reduction relative to the CPU baselines. Compared with the GPU baselines, GNNHLS achieves up to 5.16x speedup and 74.5x energy reduction

Validation of Mentors' Behavior Scale among mentors

The Mentors' Behavior Scale was developed and validated initially among nursing students by assessing the importance of mentors' behavior, showing satisfactory psychometrics and the potential to match mentors with students according to students' expectation. Objectives: This study aims to test the discriminant validity and the structure of the Mentor's Behavior Scale among mentors to assess mentors' performance. Design: A cross-sectional survey was applied in the study. Setting: Data were collected from mentors in seven hospitals in north, south, southwest China in 2016 and 2017. Participant: 871 mentors participated in this study. Methods: Purposeful sampling and online survey was used. Results: Three factors (to guide personal growth, promote professional development, and provide psychosocial support) were identified by exploratory factor analysis. The cumulative contribution of variance was 61.03%. The Cronbach's alpha coefficient of the scale was 0.85, and those of the three subscale's were 0.84, 0.72, and 0.74. The results of discriminant validity showed that mentors who received training and who liked mentoring students scored higher in mentoring behavior. Conclusion: Mentors considered that mentoring behavior were to guide students' personal growth, promote professional development and provide them with psychosocial support. It will be useful to apply The Mentors' Behavior Scale among mentors to guide and evaluate their behaviors

Vagal Blocking for Obesity Control : a Possible Mechanism-Of-Action

14 September 2016 Erratum to: Vagal Blocking for Obesity Control: a Possible Mechanism-Of-Action Helene Johannessen, David Revesz, Yosuke Kodama, Nikki Cassie, Karolina P Skibicka, Perry Barrett, Suzanne Dickson, Jens Holst, Jens Rehfeld, Geoffrey van der Plasse, Roger Adan, Bård Kulseng, Elinor Ben-Menachem, Chun-Mei Zhao, Duan Chen, 2016, 2016. Obesity surgery. In the original article on page 4 the figures are referred to as (Fig. 1b-d) and (Fig. 1e) in the text. The correct reference is (Fig. 1b-e) and (Fig. 1f), respectively. In the original article on page 5 the figures are referred to as (Fig. 3c) and (Fig. 3d) in the text. The correct reference is (Fig. 3c,d) and (Fig. 3e,f), respectively. Peer reviewedPostprin

Simplified HIV Testing and Treatment in China: Analysis of Mortality Rates Before and After a Structural Intervention.

BackgroundMultistage stepwise HIV testing and treatment initiation procedures can result in lost opportunities to provide timely antiretroviral therapy (ART). Incomplete patient engagement along the continuum of HIV care translates into high levels of preventable mortality. We aimed to evaluate the ability of a simplified test and treat structural intervention to reduce mortality.Methods and findingsIn the "pre-intervention 2010" (from January 2010 to December 2010) and "pre-intervention 2011" (from January 2011 to December 2011) phases, patients who screened HIV-positive at health care facilities in Zhongshan and Pubei counties in Guangxi, China, followed the standard-of-care process. In the "post-intervention 2012" (from July 2012 to June 2013) and "post-intervention 2013" (from July 2013 to June 2014) phases, patients who screened HIV-positive at the same facilities were offered a simplified test and treat intervention, i.e., concurrent HIV confirmatory and CD4 testing and immediate initiation of ART, irrespective of CD4 count. Participants were followed for 6-18 mo until the end of their study phase period. Mortality rates in the pre-intervention and post-intervention phases were compared for all HIV cases and for treatment-eligible HIV cases. A total of 1,034 HIV-positive participants (281 and 339 in the two pre-intervention phases respectively, and 215 and 199 in the two post-intervention phases respectively) were enrolled. Following the structural intervention, receipt of baseline CD4 testing within 30 d of HIV confirmation increased from 67%/61% (pre-intervention 2010/pre-intervention 2011) to 98%/97% (post-intervention 2012/post-intervention 2013) (all p < 0.001 [i.e., for all comparisons between a pre- and post-intervention phase]), and the time from HIV confirmation to ART initiation decreased from 53 d (interquartile range [IQR] 27-141)/43 d (IQR 15-113) to 5 d (IQR 2-12)/5 d (IQR 2-13) (all p < 0.001). Initiation of ART increased from 27%/49% to 91%/89% among all cases (all p < 0.001) and from 39%/62% to 94%/90% among individuals with CD4 count ≤ 350 cells/mm3 or AIDS (all p < 0.001). Mortality decreased from 27%/27% to 10%/10% for all cases (all p < 0.001) and from 40%/35% to 13%/13% for cases with CD4 count ≤ 350 cells/mm3 or AIDS (all p < 0.001). The simplified test and treat intervention was significantly associated with decreased mortality rates compared to pre-intervention 2011 (adjusted hazard ratio [aHR] 0.385 [95% CI 0.239-0.620] and 0.380 [95% CI 0.233-0.618] for the two post-intervention phases, respectively, for all newly diagnosed HIV cases [both p < 0.001], and aHR 0.369 [95% CI 0.226-0.603] and 0.361 [95% CI 0.221-0.590] for newly diagnosed treatment-eligible HIV cases [both p < 0.001]). The unit cost of an additional patient receiving ART attributable to the intervention was US$83.80. The unit cost of a death prevented because of the intervention was US$234.52.ConclusionsOur results demonstrate that the simplified HIV test and treat intervention promoted successful engagement in care and was associated with a 62% reduction in mortality. Our findings support the implementation of integrated HIV testing and immediate access to ART irrespective of CD4 count, in order to optimize the impact of ART

A comparative study on the three calculation methods for reproduction numbers of COVID-19

ObjectiveThis study uses four COVID-19 outbreaks as examples to calculate and compare merits and demerits, as well as applicational scenarios, of three methods for calculating reproduction numbers.MethodThe epidemiological characteristics of the COVID-19 outbreaks are described. Through the definition method, the next-generation matrix-based method, and the epidemic curve and serial interval (SI)-based method, corresponding reproduction numbers were obtained and compared.ResultsReproduction numbers (Reff), obtained by the definition method of the four regions, are 1.20, 1.14, 1.66, and 1.12. Through the next generation matrix method, in region H Reff = 4.30, 0.44; region P Reff = 6.5, 1.39, 0; region X Reff = 6.82, 1.39, 0; and region Z Reff = 2.99, 0.65. Time-varying reproduction numbers (Rt), which are attained by SI of onset dates, are decreasing with time. Region H reached its highest Rt = 2.8 on July 29 and decreased to Rt < 1 after August 4; region P reached its highest Rt = 5.8 on September 9 and dropped to Rt < 1 by September 14; region X had a fluctuation in the Rt and Rt < 1 after September 22; Rt in region Z reached a maximum of 1.8 on September 15 and decreased continuously to Rt < 1 on September 19.ConclusionThe reproduction number obtained by the definition method is optimal in the early stage of epidemics with a small number of cases that have clear transmission chains to predict the trend of epidemics accurately. The effective reproduction number Reff, calculated by the next generation matrix, could assess the scale of the epidemic and be used to evaluate the effectiveness of prevention and control measures used in epidemics with a large number of cases. Time-varying reproduction number Rt, obtained via epidemic curve and SI, can give a clear picture of the change in transmissibility over time, but the conditions of use are more rigorous, requiring a greater sample size and clear transmission chains to perform the calculation. The rational use of the three methods for reproduction numbers plays a role in the further study of the transmissibility of COVID-19

Progress on the Co-Pyrolysis of Coal and Biomass

In this chapter, the synergistic mechanism and the resulting influence during co-pyrolysis of coal and biomass, are summarized. The properties of coal and biomass, the release and migration of alkali and alkaline earth metals (AAEMs), the interaction between volatile and char, the characteristics of the resulting volatiles, and the physicochemical structure and reactivity of co-pyrolysis char, are also analyzed. In addition, the influence of AAEMs on the properties of the co-pyrolysis products is reviewed. Moreover, the analysis of the co-pyrolysis industry demonstration is also mentioned. Finally, this chapter also proposes some additional possibilities, based on further literature research