1,416 research outputs found
Statistical estimation of a growth-fragmentation model observed on a genealogical tree
We model the growth of a cell population by a piecewise deterministic Markov
branching tree. Each cell splits into two offsprings at a division rate
that depends on its size . The size of each cell grows exponentially in
time, at a rate that varies for each individual. We show that the mean
empirical measure of the model satisfies a growth-fragmentation type equation
if structured in both size and growth rate as state variables. We construct a
nonparametric estimator of the division rate based on the observation of
the population over different sampling schemes of size on the genealogical
tree. Our estimator nearly achieves the rate in squared-loss
error asymptotically. When the growth rate is assumed to be identical for every
cell, we retrieve the classical growth-fragmentation model and our estimator
improves on the rate obtained in \cite{DHRR, DPZ} through
indirect observation schemes. Our method is consistently tested numerically and
implemented on {\it Escherichia coli} data.Comment: 46 pages, 4 figure
Vortex-enhanced propulsion
It has been previously suggested that the generation of coherent vortical structures in the near-wake of a self-propelled vehicle can improve its propulsive efficiency by manipulating the local pressure field and entrainment kinematics. This paper investigates these unsteady mechanisms analytically and in experiments. A self-propelled underwater vehicle is designed with the capability to operate using either steady-jet propulsion or a pulsed-jet mode that features the roll-up of large-scale vortex rings in the near-wake. The flow field is characterized by using a combination of planar laser-induced fluorescence, laser Doppler velocimetry and digital particle-image velocimetry. These tools enable measurement of vortex dynamics and entrainment during propulsion. The concept of vortex added-mass is used to deduce the local pressure field at the jet exit as a function of the shape and motion of the forming vortex rings. The propulsive efficiency of the vehicle is computed with the aid of towing experiments to quantify hydrodynamic drag. Finally, the overall vehicle efficiency is determined by monitoring the electrical power consumed by the vehicle in steady and unsteady propulsion modes. This measurement identifies conditions under which the power required to create flow unsteadiness is offset by the improved vehicle efficiency. The experiments demonstrate that substantial increases in propulsive efficiency, over 50 % greater than the performance of the steady-jet mode, can be achieved by using vortex formation to manipulate the near-wake properties. At higher vehicle speeds, the enhanced performance is sufficient to offset the energy cost of generating flow unsteadiness. An analytical model explains this enhanced performance in terms of the vortex added-mass and entrainment. The results suggest a potential mechanism to further enhance the performance of existing engineered propulsion systems. In addition, the analytical methods described here can be extended to examine more complex propulsion systems such as those of swimming and flying animals, for whom vortex formation is inevitable
Evidence That the Product of the Human X-Linked Cgd Gene, Gp91-phox, Is a Voltage-Gated H+ Pathway
Expression of gp91-phox in Chinese hamster ovary (CHO91) cells is correlated with the presence of a voltage-gated H+ conductance. As one component of NADPH oxidase in neutrophils, gp91-phox is responsible for catalyzing the production of superoxide (O2·2). Suspensions of CHO91 cells exhibit arachidonate-activatable H+ fluxes (Henderson, L.M., G. Banting, and J.B. Chappell. 1995. J. Biol. Chem. 270:5909–5916) and we now characterize the electrical properties of the pathway. Voltage-gated currents were recorded from CHO91 cells using the whole-cell configuration of the patch-clamp technique under conditions designed to exclude a contribution from ions other than H+. As in other voltage-gated proton currents (Byerly, L., R. Meech, and W. Moody. 1984. J. Physiol. 351:199–216; DeCoursey, T.E., and V.V. Cherny. 1993. Biophys. J. 65:1590–1598), a lowered external pH (pHo) shifted activation to more positive voltages and caused the tail current reversal potential to shift in the manner predicted by the Nernst equation. The outward currents were also reversibly inhibited by 200 μM zinc. Voltage-gated currents were not present immediately upon perforating the cell membrane, but showed a progressive increase over the first 10–20 min of the recording period. This time course was consistent with a gradual shift in activation to more negative potentials as the pipette solution, pH 6.5, equilibrated with the cell contents (reported by Lucifer yellow included in the patch pipette). Use of the pH-sensitive dye 2′7′ bis-(2-carboxyethyl)-5(and 6) carboxyfluorescein (BCECF) suggested that the final intracellular pH (pHi) was ∼6.9, as though pHi was largely determined by endogenous cellular regulation. Arachidonate (20 μM) increased the amplitude of the currents by shifting activation to more negative voltages and by increasing the maximally available conductance. Changes in external Cl− concentration had no effect on either the time scale or the appearance of the currents. Examination of whole cell currents from cells expressing mutated versions of gp91-phox suggest that: (a) voltage as well as arachidonate sensitivity was retained by cells with only the NH2-terminal 230 amino acids, (b) histidine residues at positions 111, 115, and 119 on a putative membrane-spanning helical region of the protein contribute to H+ permeation, (c) histidine residues at positions 111 and 119 may contribute to voltage gating, (d) the histidine residue at position 115 is functionally important for H+ selectivity. Mechanisms of H+ permeation through gp91-phox include the possible protonation/deprotonation of His-115 as it is exposed alternatively to the interior and exterior faces of the cell membrane (see Starace, D.M., E. Stefani, and F. Bezanilla. 1997. Neuron. 19:1319–1327) and the transfer of protons across an “H-X-X-X-H-X-X-X-H” motif lining a conducting pore
305— Effects of Anthropogenic Noise on Frog Breeding Populations in Geneseo
With both amphibians and their wetland habitats in decline, it is critical to understand what ponds in the local landscape are used as breeding sites. Male frogs advertise for mates in the spring and summer by producing species-specific vocalizations at potential breeding sites. We are using acoustic recordings to examine three local sites for their use for breeding by frogs. Acoustic recordings collected during May 2020 will be analyzed to determine species abundance based on the temporal patterns of activity. By analyzing how the soundscapes and holistic metric of the habitats differ between sites can we understand the frogs\u27 habits. Using Raven Lite we can analyze call frequency to monitor breeding habits of Spring Peepers (Pseudacris crucifer), Northern Gray Treefrog (Dryophytes versicolor), Bullfrog (Lithobates catesbeianus), Wood Frog (Lithobates sylvaticus), and Green Frog (Hylarana erythraea). This research will expand our knowledge about how New York State species use roadside habitat and the behavioral adjustments they have to make to survive there
TabuLa: Harnessing Language Models for Tabular Data Synthesis
Given the ubiquitous use of tabular data in industries and the growing
concerns in data privacy and security, tabular data synthesis emerges as a
critical research area. The recent state-of-the-art methods show that large
language models (LLMs) can be adopted to generate realistic tabular data. As
LLMs pre-process tabular data as full text, they have the advantage of avoiding
the curse of dimensionality associated with one-hot encoding high-dimensional
data. However, their long training time and limited re-usability on new tasks
prevent them from replacing exiting tabular generative models. In this paper,
we propose Tabula, a tabular data synthesizer based on the language model
structure. Through Tabula, we demonstrate the inherent limitation of employing
pre-trained language models designed for natural language processing (NLP) in
the context of tabular data synthesis. Our investigation delves into the
development of a dedicated foundational model tailored specifically for tabular
data synthesis. Additionally, we propose a token sequence compression strategy
to significantly reduce training time while preserving the quality of synthetic
data. Extensive experiments on six datasets demonstrate that using a language
model structure without loading the well-trained model weights yields a better
starting model for tabular data synthesis. Moreover, the Tabula model,
previously trained on other tabular data, serves as an excellent foundation
model for new tabular data synthesis tasks. Additionally, the token sequence
compression method substantially reduces the model's training time. Results
show that Tabula averagely reduces 46.2% training time per epoch comparing to
current LLMs-based state-of-the-art algorithm and consistently achieves even
higher synthetic data utility
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