Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. Thi...
Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was
Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in ...
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Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.
This paper proposes an efficient architecture for FPGA implementation of MGS-QRD in MIMO wireless communication systems. The proposed architecture is based on the Hardware/Software (HW/SW) design. To achieve the effic...
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This paper proposes an efficient architecture for FPGA implementation of MGS-QRD in MIMO wireless communication systems. The proposed architecture is based on the Hardware/Software (HW/SW) design. To achieve the efficient architecture, the systolic architecture is applied to MGS-QRD and then the conventional QR triangular array of (2m 2 +2m+1) cells onto a linear architecture of m+1 cell is employed to reduce the number of required QR processors. The reduced cells are constructed with a number of basic processing elements such as multipliers and adders etc. The basic elements are constructed by HW architectures. The SW of PowerPC core is used to control to achieve the QR decomposition. In this paper, utilization resource and operation performance in term of equivalent gates and operating cycles are shown.
Purpose: A calibrationless parallel imaging reconstruction method, termed simultaneous autocalibrating and k-space estimation (SAKE), is presented. It is a data-driven, coil-by-coil reconstruction method that does not...
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In this paper, an optimal motion-sensing technique of indoor children's accident prevention system has been developed. There is a drawback in the existing detection algorithm due to the environment in a manner tha...
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ISBN:
(纸本)9781479965427
In this paper, an optimal motion-sensing technique of indoor children's accident prevention system has been developed. There is a drawback in the existing detection algorithm due to the environment in a manner that recognizes the difference between the 1% and more frames of motion recognition accuracy. The proposed motion detection method is based on the background modeling technique to improve the accuracy. The method is obtained using the technique to solve the recognition errors arising from the surrounding environment. We are easy to recognize the danger area using mobile cloud-based smartphone, and provide notification to tell, remote control when children access to danger area. Also, for people to recognize the size of the minimum recognition (blob) to be able to adjust the children and to recognize accurately, we improve the existing algorithms. Through the experiments, based on an improved algorithm, we derived the optimal value for children.
The multi-objective Quadratic Assignment Problem (mQAP) is a hard optimization problem with many real-world applications, such as in hospital layouts. The main purposes of this paper are: (1) the investigation of hybr...
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The multi-objective Quadratic Assignment Problem (mQAP) is a hard optimization problem with many real-world applications, such as in hospital layouts. The main purposes of this paper are: (1) the investigation of hybrid algorithms combining Transgenetic Algorithms and Evolutionary Multi-objective Optimization (EMO) frameworks to deal with mQAP and (2) to compare the ability of EMO algorithms based on Pareto dominance with those based on decomposition to deal with the mQAP. Transgenetic Algorithms (TAs) are evolutionary algorithms based on cooperation as the main evolutionary strategy. Two hybrid algorithms are proposed to deal with the mQAP: NSTA (TA + NSGA-II) and MOTA/D (TA + MOEA/D). To analyze the performance of the proposed algorithms, non-parametric statistical tests and multi-objective quality indicators are used. The proposed algorithms are compared with NSGA-II and MOEA/D in 126 instances of the mQAP. The results demonstrate the superiority of decomposition and transgenetic based algorithms, particularly in MOTA/D.
Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, we conduct a compa...
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Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, we conduct a comparative study on leaf image recognition and propose a novel learning-based leaf image recognition technique via sparse representation (or sparse coding) for automatic plant identification. In our learning-based method, in order to model leaf images, we learn an overcomplete dictionary for sparsely representing the training images of each leaf species. Each dictionary is learned using a set of descriptors extracted from the training images in such a way that each descriptor is represented by linear combination of a small number of dictionary atoms. Moreover, we also implement a general bag-of-words (BoW) model-based recognition system for leaf images, used for comparison. We experimentally compare the two approaches and show unique characteristics of our sparse coding-based framework. As a result, efficient leaf recognition can be achieved on public leaf image dataset based on the two evaluated methods, where the proposed sparse coding-based framework can perform better.
Linear approaches to low-dimensional feature extraction may not be appropriate when statistical data are generated by a nonlinear interaction of parameters. Equally inadequate are linear methods for determining the di...
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Linear approaches to low-dimensional feature extraction may not be appropriate when statistical data are generated by a nonlinear interaction of parameters. Equally inadequate are linear methods for determining the dimension of the feature space. This article estimates the intrinsic dimension of extracellular action potentials (EAPs), which can be viewed as the minimum number of nonlinearly interacting parameters sufficient to describe the data. When combined with nonlinear feature extraction methods, this information may lead to a more faithful, low-dimensional EAP representation. These points are demonstrated using EAPs recorded experimentally by a multi-sensor electrode.
Ultrasonic velocity profiler method is now an accepted tool in modern experimental fluid mechanics and fluid engineering. As a relative new technology, different applications and improvements of the technique are bein...
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ISBN:
(纸本)9781467363846
Ultrasonic velocity profiler method is now an accepted tool in modern experimental fluid mechanics and fluid engineering. As a relative new technology, different applications and improvements of the technique are being researched over the last years. This paper presents an environment to develop new algorithms to improve the ultrasonic velocity estimation technique. The system uses the LabVIEW modular platform integrated with mathematical script language used in many signal-processing software. The phase-shift algorithm was implemented and tested using the proposed system. The results are validated with standard velocity measurements generated by a rotating cylinder.
A novel parallel Remote Center of Motion (RCM) mechanism is proposed for a surgical robot designed to perform minimally invasive needle-based interventions for lung cancer diagnosis and treatment. The proposed robot p...
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A novel parallel Remote Center of Motion (RCM) mechanism is proposed for a surgical robot designed to perform minimally invasive needle-based interventions for lung cancer diagnosis and treatment. The proposed robot provides four degrees of freedom (DOFs) to orient and move a surgical needle within a spherical coordinate system. The RCM is beneath the skin surface to minimize the invasiveness of the surgical procedure while providing the required workspace. This compact, patient-mounted robot benefits from a design capable of measuring the pure interaction forces between the needle and the tissue. In this paper, the mechanism design and its specifications are described. The kinematic analysis is presented and isotropy of the mechanism for targeting tumors is studied. Finally, the performance of the proposed robot is evaluated experimentally.
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