Aspects of quantitative resistance to Xanthomonas campestris pv. oryzae in rice

Quantitative resistance (QR) toXanthomonas campestris pv. oryzae (Xco), the causal organism of bacterial blight in rice, is evident as reduced lesion length and slowed lesion development relative to lesions in susceptible cultivars. QR was evident at all growth stages and leaf ages as a reduction in lesion length following clip inoculation with virulent isolates of the pathogen. QR affects the ability of bacterial cells to establish and multiply within a leaf. No confirmed evidence of cultivar x isolate interactions of QR factors was found. Varying levels of incomplete race-specific major gene resistance were found and were difficult to distinguish from differences in QR.Differences between cultivars for lesion number following spray inoculation varied from the differences in lesion length following clip inoculation, indicating the presence of an extra component of resistance limiting bacterial entry into intact leaves.Multiple QR resistance factors were shown to be present in four moderately resistant cultivars. A minimum of five factors was found in varying combinations in six rice cultivars. The residual effect of the Xa-4 gene for resistance, or a closely linked gene, also imparted some level of QR. Selection using one isolate was effective in improving the level of QR to another isolate.</TT

Machine learning for automated EEG-based biomarkers of cognitive impairment during Deep Brain Stimulation screening in patients with Parkinson's Disease

Objective: A downside of Deep Brain Stimulation (DBS) for Parkinson's Disease (PD) is that cognitive function may deteriorate postoperatively. Electroencephalography (EEG) was explored as biomarker of cognition using a Machine Learning (ML) pipeline.Methods: A fully automated ML pipeline was applied to 112 PD patients, taking EEG time-series as input and predicted class-labels as output. The most extreme cognitive scores were selected for class differentiation, i.e. best vs. worst cognitive performance (n = 20 per group). 16,674 features were extracted per patient; feature-selection was performed using a Boruta algorithm. A random forest classifier was modelled; 10-fold cross-validation with Bayesian optimization was performed to ensure generalizability. The predicted class-probabilities of the entire cohort were compared to actual cognitive performance.Results: Both groups were differentiated with a mean accuracy of 0.92; using only occipital peak frequency yielded an accuracy of 0.67. Class-probabilities and actual cognitive performance were negatively linearly correlated (b =-0.23 (95% confidence interval (-0.29,-0.18))).Conclusions: Particularly high accuracies were achieved using a compound of automatically extracted EEG biomarkers to classify PD patients according to cognition, rather than a single spectral EEG feature.Significance: Automated EEG assessment may have utility for cognitive profiling of PD patients during the DBS screening. (c) 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Neurological Motor Disorder

Machine learning for automated EEG-based biomarkers of cognitive impairment during Deep Brain Stimulation screening in patients with Parkinson’s Disease

Algorithms and the Foundations of Software technolog

Ionization degree of the electron-hole plasma in semiconductor quantum wells

The degree of ionization of a nondegenerate two-dimensional electron-hole plasma is calculated using the modified law of mass action, which takes into account all bound and unbound states in a screened Coulomb potential. Application of the variable phase method to this potential allows us to treat scattering and bound states on the same footing. Inclusion of the scattering states leads to a strong deviation from the standard law of mass action. A qualitative difference between mid- and wide-gap semiconductors is demonstrated. For wide-gap semiconductors at room temperature, when the bare exciton binding energy is of the order of T, the equilibrium consists of an almost equal mixture of correlated electron-hole pairs and uncorrelated free carriers.Comment: 22 pages, 6 figure

Preoperative electroencephalography‐based machine learning predicts cognitive deterioration after subthalamic deepbrain stimulation

Algorithms and the Foundations of Software technolog

Weak Localization Effect in Superconductors by Radiation Damage

Large reductions of the superconducting transition temperature $T_{c}$ and the accompanying loss of the thermal electrical resistivity (electron-phonon interaction) due to radiation damage have been observed for several A15 compounds, Chevrel phase and Ternary superconductors, and $\rm{NbSe_{2}}$ in the high fluence regime. We examine these behaviors based on the recent theory of weak localization effect in superconductors. We find a good fitting to the experimental data. In particular, weak localization correction to the phonon-mediated interaction is derived from the density correlation function. It is shown that weak localization has a strong influence on both the phonon-mediated interaction and the electron-phonon interaction, which leads to the universal correlation of $T_{c}$ and resistance ratio.Comment: 16 pages plus 3 figures, revtex, 76 references, For more information, Plesse see http://www.fen.bilkent.edu.tr/~yjki

Particle swarm optimization for the Steiner tree in graph and delay-constrained multicast routing problems

This paper presents the first investigation on applying a particle swarm optimization (PSO) algorithm to both the Steiner tree problem and the delay constrained multicast routing problem. Steiner tree problems, being the underlining models of many applications, have received significant research attention within the meta-heuristics community. The literature on the application of meta-heuristics to multicast routing problems is less extensive but includes several promising approaches. Many interesting research issues still remain to be investigated, for example, the inclusion of different constraints, such as delay bounds, when finding multicast trees with minimum cost. In this paper, we develop a novel PSO algorithm based on the jumping PSO (JPSO) algorithm recently developed by Moreno-Perez et al. (Proc. of the 7th Metaheuristics International Conference, 2007), and also propose two novel local search heuristics within our JPSO framework. A path replacement operator has been used in particle moves to improve the positions of the particle with regard to the structure of the tree. We test the performance of our JPSO algorithm, and the effect of the integrated local search heuristics by an extensive set of experiments on multicast routing benchmark problems and Steiner tree problems from the OR library. The experimental results show the superior performance of the proposed JPSO algorithm over a number of other state-of-the-art approaches

The relevance of fungi in astrobiology research – Astromycology

Since the very first steps of space exploration, fungi have been recorded as contaminants, hitchhikers, or as part of missions’ crews and payloads. Because fungi can cause human disease and are highly active decomposers, their presence in a space-linked context has been a source of major concern given their possible detrimental effects on crews and space structures. However, fungi can also be beneficial and be used for many space applications. The exact effects on fungi are not always clear as they possess high adaptability and plasticity, and their phenotypes and genotypes can undergo several changes under the extreme conditions found in space, thus leading to different results than those we would have on Earth. Understanding and analysing these aspects is the subject of astromycology, a research field within astrobiology. The impending situation of a resurgent space race is expected to boost astromycology’s visibility and importance. However, researchers lack both a framework and a solid base of knowledge from which to contextualise their work. This critical review addresses this gap by conceptualising the field of astromycology, covering key research and current questions pertaining to the field, and providing a relevant research instrument for future work