986 research outputs found
Automatic Debiased Machine Learning of Causal and Structural Effects
Many causal and structural effects depend on regressions. Examples include
average treatment effects, policy effects, average derivatives, regression
decompositions, economic average equivalent variation, and parameters of
economic structural models. The regressions may be high dimensional. Plugging
machine learners into identifying equations can lead to poor inference due to
bias and/or model selection. This paper gives automatic debiasing for
estimating equations and valid asymptotic inference for the estimators of
effects of interest. The debiasing is automatic in that its construction uses
the identifying equations without the full form of the bias correction and is
performed by machine learning. Novel results include convergence rates for
Lasso and Dantzig learners of the bias correction, primitive conditions for
asymptotic inference for important examples, and general conditions for GMM. A
variety of regression learners and identifying equations are covered. Automatic
debiased machine learning (Auto-DML) is applied to estimating the average
treatment effect on the treated for the NSW job training data and to estimating
demand elasticities from Nielsen scanner data while allowing preferences to be
correlated with prices and income
The Role of Endothelial Mechanosensing in Capillary Development and Organization.
Ischemic injury is a leading cause of morbidity and mortality with the most common causes being heart attack, stroke, and peripheral artery disease. Therapies attempt to improve healing, in part, by promoting angiogenesis in these ischemic sites. Angiogenic invasion and maturation into a new capillary network may be affected by the altered microstructure and the mechanical properties of the ischemic tissue, in particular, the extracellular matrix (ECM). It is known that endothelial cells (EC) are mechanosensitive and reorient in response to both shear and normal stresses in vessels. Further, they generate traction forces and displacements in 2D culture to coordinate motion. However, the question of whether EC use cell-generated ECM forces to communicate in 3D culture to direct capillary organization and anastomosis is currently unresolved.
Hydrogels formed from natural extracellular matrix (ECM) proteins readily support the formation of vasculature in vitro. The ECM is a highly ordered meshwork of various macromolecules. This anisotropic microstructure produces non-linear viscoelastic mechanical properties which confound attempts towards modeling the mechanical environment around cells. To overcome these issues, we developed a biosynthetic hydrogel consisting of polyethylene glycol diacrylamide conjugated to macromolecular type-I collagen. Through acrylamide-based cross-links, these materials allow for independent control of physical properties and bulk ligand concentration. Photoencapsulation of EC and fibroblasts within this hydrogel material and their subsequent co-culture led to the formation of capillary vessel-like networks with well-defined hollow lumens. Patterned hydrogel constructs were produced to assess
angiogenic invasion independently of other stages of EC organization. ECM displacements were observed over time and mechanical modeling was used to compute cell-generated stresses and strains. We found that regions of strain exceeding 9% and stress exceeding 1,500 pico-Newtons per square micron co-localized with regions of capillary invasion (r=0.44). Thus, capillaries were found to generate stresses which propagated though the ECM.
Through these studies, we developed an engineered ECM which enabled the magnitudes of cell-generated stresses during a complex 3D morphogenetic process to be quantified for the first time. These findings could yield a better understanding of the physical principles guiding capillary morphogenesis and provide new strategies for treating ischemic disease.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111562/1/rahsingh_1.pd
In Search of an Ideal Test for Diagnosis and Prognosis of Kala-azar
The latex agglutination test (KAtex), direct agglutination test (DAT), and the rK39 immuno-chromatographic strip test (dipstick test) were evaluated for their role in the diagnosis and prognosis of visceral leishmaniasis (kala-azar) in India. Sera and urine samples from 455 subjects—150 confirmed visceral leishmaniasis cases, 160 endemic controls, 100 non-endemic controls, and 45 other febrile diseases—were included in the study. The sensitivity of the KAtex, DAT, and rK39 strip test was 87% [95% confidence interval (CI) 80–96], 93.3% (95% CI 88–100), and 98% (95% CI 93–100) respectively. The specificity of these tests was 98% (95% CI 93–100), 93% (95% CI 87–100), and 89% (95% CI 82–97) for the KAtex, DAT, and rK39 strip test respectively. Fifty cases were followed up and subjected to the KAtex, DAT, and rK39 strip test after 30 days of successful treatment. The DAT and rK39 strip test showed positive results in all the 50 cases whereas the KAtex showed no positive reaction in any case. Based on the results, it is concluded that the sensitivity and specificity of the DAT and rK39 strip test are comparable but the greater convenience of use of the strip test makes it a better tool for the diagnosis of visceral leishmaniasis in the peripheral areas of endemic regions whereas the sensitivity of the KAtex needs to be improved to promote its use as a first-line diagnostic test in the field-setting. It may be used for the prognosis of the disease as antigen becomes undetectable in urine after 30 days of the completion of the treatment. Alternatively, it can be used as an adjunct with rK39 for sero-epidemiological surveys
Bridging Polymeric Turbulence at different Reynolds numbers: From Multiscaling to Multifractality
The addition of polymers modifies a flow in a non-trivial way that depends on
fluid inertia (given by the Reynolds number Re) and polymer elasticity
(quantified by the Deborah number De). Using direct numerical simulations, we
show that polymeric flows exhibit a Re and De dependent multiscaling energy
spectrum. The different scaling regimes are tied to various dominant
contributions -- fluid, polymer, and dissipation -- to the total energy flux
across the scales. At small scales, energy is dissipated away by both polymers
and the fluid. Fluid energy dissipation, in particular, is shown to be more
intermittent in the presence of polymers, especially at small Re. The more
intermittent, singular nature of energy dissipation is revealed clearly by the
multifractal spectrum
Development and evaluation of multi millet thresher
In tribal areas of India, traditional methods of threshing of minor millets like little millet (Panicum sumatrense), M1, kodo millet (Paspalum scrobiculatum), M2, foxtail millet (Setaria italica), M3, proso millet (P. miliaceum), M4, barnyard millet (Echinochloa frumantacea), M5, finger millet (Eleusine coracana), M6 is done of beating by sticks or treading out the crop panicle under the feet of oxen. This operation is most time consuming, labour intensive, drudgery prone, uneconomical, lower output and obtain low quality products. A thresher for these millet crops was developed and optimization of the operating parameters with little millet was done by using Response surface methodology (RSM). The optimized parameters were 7.79% (d.b) moisture content, 105 kgh-1 feed rate, 625 rpm cylinder speed, 5 mm threshing sieve size which gave maximum threshing efficiency of 95.13% and cleaning efficiency of 94.12%. After optimization of parameters the thresher was tested for threshing of all the six minor millets with proper adjustments of sieve. Threshing capacity of M1, M2, M3, M4, M5 and M6 were obtained as 89, 137, 140, 91, 88 and 99 kg/h, respectively with more than 96% threshing efficiency and less than 2% broken grain
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