TasselNet: Counting maize tassels in the wild via local counts regression network

Accurately counting maize tassels is important for monitoring the growth status of maize plants. This tedious task, however, is still mainly done by manual efforts. In the context of modern plant phenotyping, automating this task is required to meet the need of large-scale analysis of genotype and phenotype. In recent years, computer vision technologies have experienced a significant breakthrough due to the emergence of large-scale datasets and increased computational resources. Naturally image-based approaches have also received much attention in plant-related studies. Yet a fact is that most image-based systems for plant phenotyping are deployed under controlled laboratory environment. When transferring the application scenario to unconstrained in-field conditions, intrinsic and extrinsic variations in the wild pose great challenges for accurate counting of maize tassels, which goes beyond the ability of conventional image processing techniques. This calls for further robust computer vision approaches to address in-field variations. This paper studies the in-field counting problem of maize tassels. To our knowledge, this is the first time that a plant-related counting problem is considered using computer vision technologies under unconstrained field-based environment.Comment: 14 page

A 96-Channel FPGA-based Time-to-Digital Converter

We describe an FPGA-based, 96-channel, time-to-digital converter (TDC) intended for use with the Central Outer Tracker (COT) in the CDF Experiment at the Fermilab Tevatron. The COT system is digitized and read out by 315 TDC cards, each serving 96 wires of the chamber. The TDC is physically configured as a 9U VME card. The functionality is almost entirely programmed in firmware in two Altera Stratix FPGA's. The special capabilities of this device are the availability of 840 MHz LVDS inputs, multiple phase-locked clock modules, and abundant memory. The TDC system operates with an input resolution of 1.2 ns. Each input can accept up to 7 hits per collision. The time-to-digital conversion is done by first sampling each of the 96 inputs in 1.2-ns bins and filling a circular memory; the memory addresses of logical transitions (edges) in the input data are then translated into the time of arrival and width of the COT pulses. Memory pipelines with a depth of 5.5 $\mu$s allow deadtime-less operation in the first-level trigger. The TDC VME interface allows a 64-bit Chain Block Transfer of multiple boards in a crate with transfer-rates up to 47 Mbytes/sec. The TDC also contains a separately-programmed data path that produces prompt trigger data every Tevatron crossing. The full TDC design and multi-card test results are described. The physical simplicity ensures low-maintenance; the functionality being in firmware allows reprogramming for other applications.Comment: 32 pages, 13 figure

Pattern and Predictors of Weight Gain During Pregnancy Among HIV-1-Infected Women from Tanzania

Progression of HIV disease is often accompanied by weight loss and wasting. Gestational weight gain is a strong determinant of maternal and neonatal outcomes; however, the pattern and predictors of weight gain during pregnancy among HIV-positive women are unknown. We obtained monthly anthropometric measurements in a cohort of 957 pregnant women from Tanzania who were HIV infected. We estimated the weekly rate of weight gain at various points during the second and third trimesters of pregnancy and computed rate differences between levels of sociodemographic, nutritional, immunologic, and parasitic variables at the first prenatal visit. The change in mid-upper arm circumference (MUAC) from baseline to delivery was also examined. The rate of weight gain decreased progressively during pregnancy. There was an average decline of 1 cm in MUAC between weeks 12 and 38. Lower level of education and helminthic infections at first visit were associated with decreased adjusted rates of weight gain during the third trimester. High baseline MUAC, not contributing to household income, lower serum retinol and selenium concentrations, advanced clinical stage of HIV disease, and malaria infection were related to decreased rates of weight gain during the second trimester. Low baseline CD4 T-cell counts were related to a poorer pattern of weight gain throughout pregnancy. Prevention and treatment of parasitic infections and improvement of nutritional status are likely to enhance the pattern of gestational weight gain among HIV-infected women

FCN-rLSTM: Deep Spatio-Temporal Neural Networks for Vehicle Counting in City Cameras

In this paper, we develop deep spatio-temporal neural networks to sequentially count vehicles from low quality videos captured by city cameras (citycams). Citycam videos have low resolution, low frame rate, high occlusion and large perspective, making most existing methods lose their efficacy. To overcome limitations of existing methods and incorporate the temporal information of traffic video, we design a novel FCN-rLSTM network to jointly estimate vehicle density and vehicle count by connecting fully convolutional neural networks (FCN) with long short term memory networks (LSTM) in a residual learning fashion. Such design leverages the strengths of FCN for pixel-level prediction and the strengths of LSTM for learning complex temporal dynamics. The residual learning connection reformulates the vehicle count regression as learning residual functions with reference to the sum of densities in each frame, which significantly accelerates the training of networks. To preserve feature map resolution, we propose a Hyper-Atrous combination to integrate atrous convolution in FCN and combine feature maps of different convolution layers. FCN-rLSTM enables refined feature representation and a novel end-to-end trainable mapping from pixels to vehicle count. We extensively evaluated the proposed method on different counting tasks with three datasets, with experimental results demonstrating their effectiveness and robustness. In particular, FCN-rLSTM reduces the mean absolute error (MAE) from 5.31 to 4.21 on TRANCOS, and reduces the MAE from 2.74 to 1.53 on WebCamT. Training process is accelerated by 5 times on average.Comment: Accepted by International Conference on Computer Vision (ICCV), 201

Photon-number-resolution with sub-30-ps timing using multi-element superconducting nanowire single photon detectors

A photon-number-resolving detector based on a four-element superconducting nanowire single photon detector is demonstrated to have sub-30-ps resolution in measuring the arrival time of individual photons. This detector can be used to characterize the photon statistics of non-pulsed light sources and to mitigate dead-time effects in high-speed photon counting applications. Furthermore, a 25% system detection efficiency at 1550 nm was demonstrated, making the detector useful for both low-flux source characterization and high-speed photon-counting and quantum communication applications. The design, fabrication and testing of this detector are described, and a comparison between the measured and theoretical performance is presented.Comment: 13 pages, 5 figure

Analysis of host responses to Mycobacterium tuberculosis antigens in a multi-site study of subjects with different TB and HIV infection states in sub-Saharan Africa.

BACKGROUND: Tuberculosis (TB) remains a global health threat with 9 million new cases and 1.4 million deaths per year. In order to develop a protective vaccine, we need to define the antigens expressed by Mycobacterium tuberculosis (Mtb), which are relevant to protective immunity in high-endemic areas. METHODS: We analysed responses to 23 Mtb antigens in a total of 1247 subjects with different HIV and TB status across 5 geographically diverse sites in Africa (South Africa, The Gambia, Ethiopia, Malawi and Uganda). We used a 7-day whole blood assay followed by IFN-γ ELISA on the supernatants. Antigens included PPD, ESAT-6 and Ag85B (dominant antigens) together with novel resuscitation-promoting factors (rpf), reactivation proteins, latency (Mtb DosR regulon-encoded) antigens, starvation-induced antigens and secreted antigens. RESULTS: There was variation between sites in responses to the antigens, presumably due to underlying genetic and environmental differences. When results from all sites were combined, HIV- subjects with active TB showed significantly lower responses compared to both TST(-) and TST(+) contacts to latency antigens (Rv0569, Rv1733, Rv1735, Rv1737) and the rpf Rv0867; whilst responses to ESAT-6/CFP-10 fusion protein (EC), PPD, Rv2029, TB10.3, and TB10.4 were significantly higher in TST(+) contacts (LTBI) compared to TB and TST(-) contacts fewer differences were seen in subjects with HIV co-infection, with responses to the mitogen PHA significantly lower in subjects with active TB compared to those with LTBI and no difference with any antigen. CONCLUSIONS: Our multi-site study design for testing novel Mtb antigens revealed promising antigens for future vaccine development. The IFN-γ ELISA is a cheap and useful tool for screening potential antigenicity in subjects with different ethnic backgrounds and across a spectrum of TB and HIV infection states. Analysis of cytokines other than IFN-γ is currently on-going to determine correlates of protection, which may be useful for vaccine efficacy trials