167,782 research outputs found
Towards Personalized Synthesized Voices for Individuals with Vocal Disabilities: Voice Banking and Reconstruction
When individuals lose the ability to produce their own speech, due to degenerative diseases such as motor neurone disease (MND) or Parkinsonâs, they lose not only a functional means of communication but also a display of their individual and group identity. In order to build personalized synthetic voices, attempts have been made to capture the voice before it is lost, using a process known as voice banking. But, for some patients, the speech deterioration frequently coincides or quickly follows diagnosis. Using HMM-based speech synthesis, it is now possible to build personalized synthetic voices with minimal data recordings and even disordered speech. The power of this approach is that it is possible to use the patientâs recordings to adapt existing voice models pre-trained on many speakers. When the speech has begun to deteriorate, the adapted voice model can be further modified in order to compensate for the disordered characteristics found in the patientâs speech. The University of Edinburgh has initiated a project for voice banking and reconstruction based on this speech synthesis technology. At the current stage of the project, more than fifteen patients with MND have already been recorded and five of them have been delivered a reconstructed voice. In this paper, we present an overview of the project as well as subjective assessments of the reconstructed voices and feedback from patients and their families
Stochastic dynamics of adaptive trait and neutral marker driven by eco-evolutionary feedbacks
How the neutral diversity is affected by selection and adaptation is
investigated in an eco-evolutionary framework. In our model, we study a finite
population in continuous time, where each individual is characterized by a
trait under selection and a completely linked neutral marker. Population
dynamics are driven by births and deaths, mutations at birth, and competition
between individuals. Trait values influence ecological processes (demographic
events, competition), and competition generates selection on trait variation,
thus closing the eco-evolutionary feedback loop. The demographic effects of the
trait are also expected to influence the generation and maintenance of neutral
variation. We consider a large population limit with rare mutation, under the
assumption that the neutral marker mutates faster than the trait under
selection. We prove the convergence of the stochastic individual-based process
to a new measure-valued diffusive process with jumps that we call Substitution
Fleming-Viot Process (SFVP). When restricted to the trait space this process is
the Trait Substitution Sequence first introduced by Metz et al. (1996). During
the invasion of a favorable mutation, a genetical bottleneck occurs and the
marker associated with this favorable mutant is hitchhiked. By rigorously
analysing the hitchhiking effect and how the neutral diversity is restored
afterwards, we obtain the condition for a time-scale separation; under this
condition, we show that the marker distribution is approximated by a
Fleming-Viot distribution between two trait substitutions. We discuss the
implications of the SFVP for our understanding of the dynamics of neutral
variation under eco-evolutionary feedbacks and illustrate the main phenomena
with simulations. Our results highlight the joint importance of mutations,
ecological parameters, and trait values in the restoration of neutral diversity
after a selective sweep.Comment: 29 page
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Protein evolution speed depends on its stability and abundance and on chaperone concentrations.
Proteins evolve at different rates. What drives the speed of protein sequence changes? Two main factors are a protein's folding stability and aggregation propensity. By combining the hydrophobic-polar (HP) model with the Zwanzig-Szabo-Bagchi rate theory, we find that: (i) Adaptation is strongly accelerated by selection pressure, explaining the broad variation from days to thousands of years over which organisms adapt to new environments. (ii) The proteins that adapt fastest are those that are not very stably folded, because their fitness landscapes are steepest. And because heating destabilizes folded proteins, we predict that cells should adapt faster when put into warmer rather than cooler environments. (iii) Increasing protein abundance slows down evolution (the substitution rate of the sequence) because a typical protein is not perfectly fit, so increasing its number of copies reduces the cell's fitness. (iv) However, chaperones can mitigate this abundance effect and accelerate evolution (also called evolutionary capacitance) by effectively enhancing protein stability. This model explains key observations about protein evolution rates
Mitochondrial targeting adaptation of the hominoid-specific glutamate dehydrogenase driven by positive Darwinian selection
Many new gene copies emerged by gene duplication in hominoids, but little is known with respect to their functional evolution. Glutamate dehydrogenase (GLUD) is an enzyme central to the glutamate and energy metabolism of the cell. In addition to the single, GLUD-encoding gene present in all mammals (GLUD1), humans and apes acquired a second GLUD gene (GLUD2) through retroduplication of GLUD1, which codes for an enzyme with unique, potentially brain-adapted properties. Here we show that whereas the GLUD1 parental protein localizes to mitochondria and the cytoplasm, GLUD2 is specifically targeted to mitochondria. Using evolutionary analysis and resurrected ancestral protein variants, we demonstrate that the enhanced mitochondrial targeting specificity of GLUD2 is due to a single positively selected glutamic acid-to-lysine substitution, which was fixed in the N-terminal mitochondrial targeting sequence (MTS) of GLUD2 soon after the duplication event in the hominoid ancestor ~18â25 million years ago. This MTS substitution arose in parallel with two crucial adaptive amino acid changes in the enzyme and likely contributed to the functional adaptation of GLUD2 to the glutamate metabolism of the hominoid brain and other tissues. We suggest that rapid, selectively driven subcellular adaptation, as exemplified by GLUD2, represents a common route underlying the emergence of new gene functions
Disarming Steganography Attacks Inside Neural Network Models
Similar to the revolution of open source code sharing, Artificial
Intelligence (AI) model sharing is gaining increased popularity. However, the
fast adaptation in the industry, lack of awareness, and ability to exploit the
models make them significant attack vectors. By embedding malware in neurons,
the malware can be delivered covertly, with minor or no impact on the neural
network's performance. The covert attack will use the Least Significant Bits
(LSB) weight attack since LSB has a minimal effect on the model accuracy, and
as a result, the user will not notice it. Since there are endless ways to hide
the attacks, we focus on a zero-trust prevention strategy based on AI model
attack disarm and reconstruction. We proposed three types of model
steganography weight disarm defense mechanisms. The first two are based on
random bit substitution noise, and the other on model weight quantization. We
demonstrate a 100\% prevention rate while the methods introduce a minimal
decrease in model accuracy based on Qint8 and K-LRBP methods, which is an
essential factor for improving AI security
The inevitability of unconditionally deleterious substitutions during adaptation
Studies on the genetics of adaptation typically neglect the possibility that
a deleterious mutation might fix. Nonetheless, here we show that, in many
regimes, the first substitution is most often deleterious, even when fitness is
expected to increase in the long term. In particular, we prove that this
phenomenon occurs under weak mutation for any house-of-cards model with an
equilibrium distribution. We find that the same qualitative results hold under
Fisher's geometric model. We also provide a simple intuition for the surprising
prevalence of unconditionally deleterious substitutions during early
adaptation. Importantly, the phenomenon we describe occurs on fitness
landscapes without any local maxima and is therefore distinct from
"valley-crossing". Our results imply that the common practice of ignoring
deleterious substitutions leads to qualitatively incorrect predictions in many
regimes. Our results also have implications for the substitution process at
equilibrium and for the response to a sudden decrease in population size.Comment: Corrected typos and minor errors in Supporting Informatio
A formal approach for correct-by-construction system substitution
The substitution of a system with another one may occur in several situations
like system adaptation, system failure management, system resilience, system
reconfiguration, etc. It consists in replacing a running system by another one
when given conditions hold. This contribution summarizes our proposal to define
a formal setting for proving the correctness of system substitution. It relies
on refinement and on the Event-B method.Comment: EDCC-2014, Student-Forum, System Substitution, state rRecovery,
correct-bycorrection, Event-B, refinemen
Historical contingency and entrenchment in protein evolution under purifying selection
The fitness contribution of an allele at one genetic site may depend on
alleles at other sites, a phenomenon known as epistasis. Epistasis can
profoundly influence the process of evolution in populations under selection,
and can shape the course of protein evolution across divergent species. Whereas
epistasis between adaptive substitutions has been the subject of extensive
study, relatively little is known about epistasis under purifying selection.
Here we use mechanistic models of thermodynamic stability in a ligand-binding
protein to explore the structure of epistatic interactions between
substitutions that fix in protein sequences under purifying selection. We find
that the selection coefficients of mutations that are nearly-neutral when they
fix are highly contingent on the presence of preceding mutations. Conversely,
mutations that are nearly-neutral when they fix are subsequently entrenched due
to epistasis with later substitutions. Our evolutionary model includes
insertions and deletions, as well as point mutations, and so it allows us to
quantify epistasis within each of these classes of mutations, and also to study
the evolution of protein length. We find that protein length remains largely
constant over time, because indels are more deleterious than point mutations.
Our results imply that, even under purifying selection, protein sequence
evolution is highly contingent on history and so it cannot be predicted by the
phenotypic effects of mutations assayed in the wild-type sequence.Comment: 42 pages, 13 figure
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