1,356 research outputs found
Connecting protein and mRNA burst distributions for stochastic models of gene expression
The intrinsic stochasticity of gene expression can lead to large variability
in protein levels for genetically identical cells. Such variability in protein
levels can arise from infrequent synthesis of mRNAs which in turn give rise to
bursts of protein expression. Protein expression occurring in bursts has indeed
been observed experimentally and recent studies have also found evidence for
transcriptional bursting, i.e. production of mRNAs in bursts. Given that there
are distinct experimental techniques for quantifying the noise at different
stages of gene expression, it is of interest to derive analytical results
connecting experimental observations at different levels. In this work, we
consider stochastic models of gene expression for which mRNA and protein
production occurs in independent bursts. For such models, we derive analytical
expressions connecting protein and mRNA burst distributions which show how the
functional form of the mRNA burst distribution can be inferred from the protein
burst distribution. Additionally, if gene expression is repressed such that
observed protein bursts arise only from single mRNAs, we show how observations
of protein burst distributions (repressed and unrepressed) can be used to
completely determine the mRNA burst distribution. Assuming independent
contributions from individual bursts, we derive analytical expressions
connecting means and variances for burst and steady-state protein
distributions. Finally, we validate our general analytical results by
considering a specific reaction scheme involving regulation of protein bursts
by small RNAs. For a range of parameters, we derive analytical expressions for
regulated protein distributions that are validated using stochastic
simulations. The analytical results obtained in this work can thus serve as
useful inputs for a broad range of studies focusing on stochasticity in gene
expression
Reliability of Decision Support in Cross-spectral Biometric-enabled Systems
This paper addresses the evaluation of the performance of the decision
support system that utilizes face and facial expression biometrics. The
evaluation criteria include risk of error and related reliability of decision,
as well as their contribution to the changes in the perceived operator's trust
in the decision. The relevant applications include human behavior monitoring
and stress detection in individuals and teams, and in situational awareness
system. Using an available database of cross-spectral videos of faces and
facial expressions, we conducted a series of experiments that demonstrate the
phenomenon of biases in biometrics that affect the evaluated measures of the
performance in human-machine systems.Comment: submitted to IEEE International Conference on Systems, Man, and
Cybernetic
Graphene-coated holey metal films: tunable molecular sensing by surface plasmon resonance
We report on the enhancement of surface plasmon resonances in a holey
bidimensional grating of subwavelength size, drilled in a gold thin film coated
by a graphene sheet. The enhancement originates from the coupling between
charge carriers in graphene and gold surface plasmons. The main plasmon
resonance peak is located around 1.5 microns. A lower constraint on the
gold-induced doping concentration of graphene is specified and the interest of
this architecture for molecular sensing is also highlighted.Comment: 5 pages, 4 figures, Final version. Published in Applied Physics
Letter
Nonlinear dynamics of beta induced Alfv\'en eigenmode driven by energetic particles
Nonlinear saturation of beta induced Alfv\'en eigenmode, driven by slowing
down energetic particles via transit resonance, is investigated by the
nonlinear hybrid magnetohyrodynamic gyro-kinetic code (XHMGC). Saturation is
characterized by frequency chirping and symmetry breaking between co- and
counter-passing particles, which can be understood as the the evidence of
resonance-detuning. The scaling of the saturation amplitude with the growth
rate is also demonstrated to be consistent with radial resonance detuning due
to the radial non-uniformity and mode structure
No Need for a Lexicon? Evaluating the Value of the Pronunciation Lexica in End-to-End Models
For decades, context-dependent phonemes have been the dominant sub-word unit
for conventional acoustic modeling systems. This status quo has begun to be
challenged recently by end-to-end models which seek to combine acoustic,
pronunciation, and language model components into a single neural network. Such
systems, which typically predict graphemes or words, simplify the recognition
process since they remove the need for a separate expert-curated pronunciation
lexicon to map from phoneme-based units to words. However, there has been
little previous work comparing phoneme-based versus grapheme-based sub-word
units in the end-to-end modeling framework, to determine whether the gains from
such approaches are primarily due to the new probabilistic model, or from the
joint learning of the various components with grapheme-based units.
In this work, we conduct detailed experiments which are aimed at quantifying
the value of phoneme-based pronunciation lexica in the context of end-to-end
models. We examine phoneme-based end-to-end models, which are contrasted
against grapheme-based ones on a large vocabulary English Voice-search task,
where we find that graphemes do indeed outperform phonemes. We also compare
grapheme and phoneme-based approaches on a multi-dialect English task, which
once again confirm the superiority of graphemes, greatly simplifying the system
for recognizing multiple dialects
Exploring the role of technology in language acquisition
The article explores various technological advancements and their integration into language acquisition methods. It highlights the benefits of technology, such as online language learning platforms, apps for online classes, language learning apps. By discussing real-world examples and success stories, the article provides concrete evidence of the effectiveness and practicality of technology in language acquisition. The article caters to the interests of both educators and students by offering valuable perspectives on how technology can be utilized to enhance language learning experiences within educational environments. It`s a vital source of information for individuals seeking to comprehend the dynamic realm of language acquisition and the significant influence that technology has in shaping it
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