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 N‾N\bf{\overline{N}N} 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 $G$-parity transform of the Bonn $NN$ potential. Annihilation into two mesons is described in terms of microscopic baryon-exchange processes including all possible combinations of $\pi,\eta,\rho,\omega,a_0,f_0,a_1,f_1,a_2,f_2,K,K^*$. 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