Detecting Invasive Insects with Unmanned Aerial Vehicles

A key aspect to controlling and reducing the effects invasive insect species have on agriculture is to obtain knowledge about the migration patterns of these species. Current state-of-the-art methods of studying these migration patterns involve a mark-release-recapture technique, in which insects are released after being marked and researchers attempt to recapture them later. However, this approach involves a human researcher manually searching for these insects in large fields and results in very low recapture rates. In this paper, we propose an automated system for detecting released insects using an unmanned aerial vehicle. This system utilizes ultraviolet lighting technology, digital cameras, and lightweight computer vision algorithms to more quickly and accurately detect insects compared to the current state of the art. The efficiency and accuracy that this system provides will allow for a more comprehensive understanding of invasive insect species migration patterns. Our experimental results demonstrate that our system can detect real target insects in field conditions with high precision and recall rates.Comment: IEEE ICRA 2019. 7 page

Optimizing survival outcomes with post-remission therapy in acute myeloid leukemia.

Optimization of post-remission therapies to maintain complete remission and prevent relapse is a major challenge in treating patients with acute myeloid leukemia (AML). Monitoring patients for measurable residual disease (MRD) is helpful to identify those at risk for relapse. Hypomethylating agents are being investigated as post-remission therapy. Identification of recurrent genetic alterations that drive disease progression has enabled the design of new, personalized approaches to therapy for patients with AML. Emerging data suggest that targeted post-remission therapy, alone or in combination with chemotherapy, may improve outcomes. Results of ongoing clinical trials will further define potential clinical benefits

Perturbing parameters to understand cloud contributions to climate change

The sensitivity of cloud feedbacks to atmospheric model parameters is evaluated using a CAM6 perturbed parameter ensemble (PPE). The CAM6 PPE perturbs 45 parameters across 262 simulations, 206 of which are used here. The spread in total cloud feedback and its six components across the CAM6 PPE are comparable to the spread across the CMIP6 and AMIP ensembles, indicating that parametric uncertainty mirrors structural uncertainty. However, the high-cloud altitude feedback is generally larger in the CAM6 PPE than WCRP assessment, CMIP6, and AMIP values. We evaluate the influence of each of the 45 parameters on the total cloud feedback and each of the six cloud feedback components. We also explore whether the CAM6 PPE can be used to constrain the total cloud feedback, with inconclusive results. Further, we find that despite the large parametric sensitivity of cloud feedbacks in CAM6, a substantial increase in cloud feedbacks from CAM5 to CAM6 is not a result of changes in parameter values. Notably, the CAM6 PPE is run with a more recent version of CAM6 (CAM6.3) than was used for AMIP (CAM6.0), and has a smaller total cloud feedback (0.56 W m$^{-2}$ K$^{-1}$) as compared to CAM6.0 (0.81 W m$^{-2}$ K$^{-1}$) owing primarily to reductions in low clouds over the tropics and middle latitudes. The work highlights the large sensitivity of cloud feedbacks to both parameter values and structural details in CAM6

Whole-genome amplification in double-digest RADseq results in adequate libraries but fewer sequenced loci

Whole-genome amplification by multiple displacement amplification (MDA) is a promising technique to enable the use of samples with only limited amount of DNA for the construction of RAD-seq libraries. Previous work has shown that, when the amount of DNA used in the MDA reaction is large, double-digest RAD-seq (ddRAD) libraries prepared with amplified genomic DNA result in data that are indistinguishable from libraries prepared directly from genomic DNA. Based on this observation, here we evaluate the quality of ddRAD libraries prepared from MDA-amplified genomic DNA when the amount of input genomic DNA and the coverage obtained for samples is variable. By simultaneously preparing libraries for five species of weevils (Coleoptera, Curculionidae), we also evaluate the likelihood that potential contaminants will be encountered in the assembled dataset. Overall, our results indicate that MDA may not be able to rescue all samples with small amounts of DNA, but it does produce ddRAD libraries adequate for studies of phylogeography and population genetics even when conditions are not optimal. We find that MDA makes it harder to predict the number of loci that will be obtained for a given sequencing effort, with some samples behaving like traditional libraries and others yielding fewer loci than expected. This seems to be caused both by stochastic and deterministic effects during amplification. Further, the reduction in loci is stronger in libraries with lower amounts of template DNA for the MDA reaction. Even though a few samples exhibit substantial levels of contamination in raw reads, the effect is very small in the final dataset, suggesting that filters imposed during dataset assembly are important in removing contamination. Importantly, samples with strong signs of contamination and biases in heterozygosity were also those with fewer loci shared in the final dataset, suggesting that stringent filtering of samples with significant amounts of missing data is important when assembling data derived from MDA-amplified genomic DNA. Overall, we find that the combination of MDA and ddRAD results in high-quality datasets for population genetics as long as the sequence data is properly filtered during assembly.Organismic and Evolutionary Biolog

Fast and slow shifts of the zonal-mean intertropical convergence zone in response to an idealized anthropogenic aerosol

Previous modeling work showed that aerosol can affect the position of the tropical rain belt, i.e., the intertropical convergence zone (ITCZ). Yet it remains unclear which aspects of the aerosol impact are robust across models, and which are not. Here we present simulations with seven comprehensive atmosphere models that study the fast and slow impacts of an idealized anthropogenic aerosol on the zonal-mean ITCZ position. The fast impact, which results from aerosol atmospheric heating and land cooling before sea-surface temperature (SST) has time to respond, causes a northward ITCZ shift. Yet the fast impact is compensated locally by decreased evaporation over the ocean, and a clear northward shift is only found for an unrealistically large aerosol forcing. The local compensation implies that while models differ in atmospheric aerosol heating, this does not contribute to model differences in the ITCZ shift. The slow impact includes the aerosol impact on the ocean surface energy balance and is mediated by SST changes. The slow impact is an order of magnitude more effective than the fast impact and causes a clear southward ITCZ shift for realistic aerosol forcing. Models agree well on the slow ITCZ shift when perturbed with the same SST pattern. However, an energetic analysis suggests that the slow ITCZ shifts would be substantially more model-dependent in interactive-SST setups due to model differences in clear-sky radiative transfer and clouds. We also discuss implications for the representation of aerosol in climate models and attributions of recent observed ITCZ shifts to aerosol

Radio-Frequency Interference (RFI) Mitigation for the Soil, Moisture Active/Passive (SMAP) Radiometer

The presence of anthropogenic RFI is expected to adversely impact soil moisture measurement by NASA s Soil Moisture Active Passive mission. The digital signal processing approach and preliminary design for detecting and mitigating this RFI is presented in this paper. This approach is largely based upon the work of Johnson and Ruf

Analytical validity of a genotyping assay for use with personalized antihypertensive and chronic kidney disease therapy

Hypertension and chronic kidney disease are inextricably linked. Hypertension is a well-recognized contributor to chronic kidney disease progression and, in turn, renal disease potentiates hypertension. A generalized approach to drug selection and dosage has not proven effective in managing these conditions, in part, because patients with heterogeneous kidney disease and hypertension etiologies are frequently grouped according to functional or severity classifications. Genetic testing may serve as an important tool in the armamentarium of clinicians who embrace precision medicine. Increasing scientific evidence has supported the utilization of genomic information to select efficacious antihypertensive therapy and understand hereditary contributors to chronic kidney disease progression. Given the wide array of antihypertensive agents available and diversity of genetic renal disease predictors, a panel-based approach to genotyping may be an efficient and economic means of establishing an individualized blood pressure response profile for patients with various forms of chronic kidney disease and hypertension. In this manuscript, we discuss the validation process of a Clinical Laboratory Improvement Amendments (CLIA)-approved genetic test to relay information on 72 genetic variants associated with kidney disease progression and hypertension therapy. These genomic-based interventions, in addition to routine clinical data, may help inform physicians to provide personalized therapy

Novel sequential ChIP and simplified basic ChIP protocols for promoter co-occupancy and target gene identification in human embryonic stem cells

<p>Abstract</p> <p>Background</p> <p>The investigation of molecular mechanisms underlying transcriptional regulation, particularly in embryonic stem cells, has received increasing attention and involves the systematic identification of target genes and the analysis of promoter co-occupancy. High-throughput approaches based on chromatin immunoprecipitation (ChIP) have been widely used for this purpose. However, these approaches remain time-consuming, expensive, labor-intensive, involve multiple steps, and require complex statistical analysis. Advances in this field will greatly benefit from the development and use of simple, fast, sensitive and straightforward ChIP assay and analysis methodologies.</p> <p>Results</p> <p>We initially developed a simplified, basic ChIP protocol that combines simplicity, speed and sensitivity. ChIP analysis by real-time PCR was compared to analysis by densitometry with the ImageJ software. This protocol allowed the rapid identification of known target genes for SOX2, NANOG, OCT3/4, SOX17, KLF4, RUNX2, OLIG2, SMAD2/3, BMI-1, and c-MYC in a human embryonic stem cell line. We then developed a novel Sequential ChIP protocol to investigate <it>in vivo </it>promoter co-occupancy, which is basically characterized by the absence of antibody-antigen disruption during the assay. It combines centrifugation of agarose beads and magnetic separation. Using this Sequential ChIP protocol we found that c-MYC associates with the SOX2/NANOG/OCT3/4 complex and identified a novel RUNX2/BMI-1/SMAD2/3 complex in BG01V cells. These two TF complexes associate with two distinct sets of target genes. The RUNX2/BMI-1/SMAD2/3 complex is associated predominantly with genes not expressed in undifferentiated BG01V cells, consistent with the reported role of those TFs as transcriptional repressors.</p> <p>Conclusion</p> <p>These simplified basic ChIP and novel Sequential ChIP protocols were successfully tested with a variety of antibodies with human embryonic stem cells, generated a number of novel observations for future studies and might be useful for high-throughput ChIP-based assays.</p

Safety and efficacy of vismodegib in relapsed/refractory acute myeloid leukaemia: results of a phase Ib trial

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149232/1/bjh15571_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149232/2/bjh15571.pd

Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison

Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modeled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: some models lack the cloudy state of the boundary layer due to the representation of mixed-phase microphysics or to the interaction between micro- and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behavior