1,294 research outputs found
Inferring the dynamics of underdamped stochastic systems
Many complex systems, ranging from migrating cells to animal groups, exhibit
stochastic dynamics described by the underdamped Langevin equation. Inferring
such an equation of motion from experimental data can provide profound insight
into the physical laws governing the system. Here, we derive a principled
framework to infer the dynamics of underdamped stochastic systems from
realistic experimental trajectories, sampled at discrete times and subject to
measurement errors. This framework yields an operational method, Underdamped
Langevin Inference (ULI), which performs well on experimental trajectories of
single migrating cells and in complex high-dimensional systems, including
flocks with Viscek-like alignment interactions. Our method is robust to
experimental measurement errors, and includes a self-consistent estimate of the
inference error
Learning dynamical models of single and collective cell migration: a review
Single and collective cell migration are fundamental processes critical for
physiological phenomena ranging from embryonic development and immune response
to wound healing and cancer metastasis. To understand cell migration from a
physical perspective, a broad variety of models for the underlying physical
mechanisms that govern cell motility have been developed. A key challenge in
the development of such models is how to connect them to experimental
observations, which often exhibit complex stochastic behaviours. In this
review, we discuss recent advances in data-driven theoretical approaches that
directly connect with experimental data to infer dynamical models of stochastic
cell migration. Leveraging advances in nanofabrication, image analysis, and
tracking technology, experimental studies now provide unprecedented large
datasets on cellular dynamics. In parallel, theoretical efforts have been
directed towards integrating such datasets into physical models from the single
cell to the tissue scale with the aim of conceptualizing the emergent behavior
of cells. We first review how this inference problem has been addressed in
freely migrating cells on two-dimensional substrates and in structured,
confining systems. Moreover, we discuss how data-driven methods can be
connected with molecular mechanisms, either by integrating mechanistic
bottom-up biophysical models, or by performing inference on subcellular degrees
of freedom. Finally, we provide an overview of applications of data-driven
modelling in developing frameworks for cell-to-cell variability in behaviours,
and for learning the collective dynamics of multicellular systems.
Specifically, we review inference and machine learning approaches to recover
cell-cell interactions and collective dynamical modes, and how these can be
integrated into physical active matter models of collective migration
CLINICAL EVALUATION OF A SPECIFIC BENZODIAZEPINE ANTAGONIST (RO 15-1788): Studies in Elderly Patients after Regional Anaesthesia under Benzodiazepine Sedation
The efficacy, usefulness and side effects of RO 15-1788 (RO), a specific benzodiazepine (BZD) antagonist, have been evaluated. Sixty-two patients (ASA l-lll, mean age 72±9 yr) scheduled for urological surgery under regional anaesthesia and BZD sedation received placebo or RO in a randomized, double-blind fashion at the end of the procedure, folio wing sedation with midazolam. When compared with placebo, RO improved alertness and collaboration for 15 min, and suppressed anterograde amnesia for 60 min. No major side effect was noted, although five patients became anxious after administration of RO. Two cases of a paradoxical reaction to midazolam were treated successfully by R
Opposite tendency between yield and taste of organic tomato by increasing biochar doses in a slightly humous arenosol
Received: February 4th, 2022 ; Accepted: April 6th, 2022 ; Published: April 28th, 2022 ; Correspondence: [email protected] tomato is the edible berry of the plant Solanum lycopersicum. Tomato plants are
widely grown in temperate climates worldwide and are mostly cultivated as annuals. The
objective of this study was to understand the interrelation between fruit quality of tomato, some
soil biological parameters, and the addition of increasing biochar (BC) soil amendment doses.
BC is an industrial product, made from organic waste by pyrolysis. Its use in the soil is known to
improve fertility and several soil functions. Among organic, ecological conditions, a field
experiment was performed in a type of slightly humous arenosol soil. Effect of increasing doses
of biochar (BC) (0.5-, 1.0-, 2.5-, 5.0, 10 m/m% and control) was studied. Nutrient content and
Total Soluble Solid (TSS) of the fruits, the ripeness, and the marketable/non-marketable ratio of
yield were assessed. The presence of some cultivable microbial physiological groups (fungi,
bacteria) and the soil-dehydrogenase activity (DHA) was estimated. Results represented that the
changes of fruit TSS content was not linear with the increasing doses of BC. The increased yield
(+53%) had an inverse correlation with the TSS content of the berry's pulps, and the content was
lowest at the highest BC dose. Optimum doses of BC were considered, like 1–2.5 m/m%,
supported by the nutritive element content (+55% N, +76% P, +83% K) and enhanced microbial
activities (+45% DHA). Grouping the parameters by Pearson Correlation Coefficient, the biochar
amendment was a driving factor for tomato growth, with certain dose limits in the studied organic
agricultural practice
Security Evaluation of Support Vector Machines in Adversarial Environments
Support Vector Machines (SVMs) are among the most popular classification
techniques adopted in security applications like malware detection, intrusion
detection, and spam filtering. However, if SVMs are to be incorporated in
real-world security systems, they must be able to cope with attack patterns
that can either mislead the learning algorithm (poisoning), evade detection
(evasion), or gain information about their internal parameters (privacy
breaches). The main contributions of this chapter are twofold. First, we
introduce a formal general framework for the empirical evaluation of the
security of machine-learning systems. Second, according to our framework, we
demonstrate the feasibility of evasion, poisoning and privacy attacks against
SVMs in real-world security problems. For each attack technique, we evaluate
its impact and discuss whether (and how) it can be countered through an
adversary-aware design of SVMs. Our experiments are easily reproducible thanks
to open-source code that we have made available, together with all the employed
datasets, on a public repository.Comment: 47 pages, 9 figures; chapter accepted into book 'Support Vector
Machine Applications
Combined Description of Scattering and Annihilation With A Hadronic Model
A model for the nucleon-antinucleon interaction is presented which is based
on meson-baryon dynamics. The elastic part is the -parity transform of the
Bonn potential. Annihilation into two mesons is described in terms of
microscopic baryon-exchange processes including all possible combinations of
. The remaining
annihilation part is taken into account by a phenomenological energy- and state
independent optical potential of Gaussian form. The model enables a
simultaneous description of nucleon-antinucleon scattering and annihilation
phenomena with fair quality.Comment: revised version, REVTEX, 9 pages, 10 figures available from this URL
ftp://ikp113.ikp.kfa-juelich.de/pub/kph140/nucl-th.9411014.u
Measurement of the Omega_c Lifetime
We present the measurement of the lifetime of the Omega_c we have performed
using three independent data samples from two different decay modes. Using a
Sigma- beam of 340 GeV/c we have obtained clean signals for the Omega_c
decaying into Xi- K- pi+ pi+ and Omega- pi+ pi- pi+, avoiding topological cuts
normally used in charm analysis. The short but measurable lifetime of the
Omega_c is demonstrated by a clear enhancement of the signals at short but
finite decay lengths. Using a continuous maximum likelihood method we
determined the lifetime to be tau(Omega_c) = 55 +13-11(stat) +18-23(syst) fs.
This makes the Omega_c the shortest living weakly decaying particle observed so
far. The short value of the lifetime confirms the predicted pattern of the
charmed baryon lifetimes and demonstrates that the strong interaction plays a
vital role in the lifetimes of charmed hadrons.Comment: 15 pages, including 7 figures; gzipped, uuencoded postscrip
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