Computer Microscopy of Biological Fluid Dry Patterns for Medical Diagnostics

We elaborate hardware and software system that implements the principle of diagnosis based on the standard procedure of pattern preparation including digital recognition of image and its computer analysis based on specially developed algorithms by comparing with the expert descriptors and extensive database of dry pattern samples obtained from clinical treatments which include more than 1500 samples to high selective and accuracy recognition of pathologies, for recognition of wide range of pathologies, in particular, the endogenous intoxication. Keywords: biological fluids, image analysis, medical diagnostics, endogenous intoxication

Detection of intention level in response to task difficulty from EEG signals

We present an approach that enables detecting intention levels of subjects in response to task difficulty utilizing an electroencephalogram (EEG) based brain-computer interface (BCI). In particular, we use linear discriminant analysis (LDA) to classify event-related synchronization (ERS) and desynchronization (ERD) patterns associated with right elbow flexion and extension movements, while lifting different weights. We observe that it is possible to classify tasks of varying difficulty based on EEG signals. Additionally, we also present a correlation analysis between intention levels detected from EEG and surface electromyogram (sEMG) signals. Our experimental results suggest that it is possible to extract the intention level information from EEG signals in response to task difficulty and indicate some level of correlation between EEG and EMG. With a view towards detecting patients' intention levels during rehabilitation therapies, the proposed approach has the potential to ensure active involvement of patients throughout exercise routines and increase the efficacy of robot assisted therapies

KAJIAN SIKAP RAKYAT MALAYSIA TERHADAP KESETIAAN KEPADA NEGARA

Allegiance among Malaysians is a matter that should be given priority to ensure national security. The objective of this study is to examine the attitude of Malaysians on their allegiance to the nation based on predetermined areas. This nationwide study involved a total of six zones with 1500 samples taken among Malaysians and was categorised by race. Cross-tabulation analysis was applied on data from questionnaire for reasons of convienience. The results showed that all zones or states were in good condition except for the central zone, represented by the states of Perak, Kuala Lumpur and Selangor which recorded a moderate value of allegiance to the nation. Hence, this study suggests that the current existing programs that can spark allegiance and patriotism to the country should be continued

Scientific Yield of Meteorites Recovered from the Dominion Range, Transantarctic Mountains

The US Antarctic Meteorite Program has visited the Dominion Range in the Transantarctic Mountains during several different seasons, including the 1985, 2003, 2008, 2010, and 2014 seasons. Total recovered meteorites from this region is over 2000. The 1985 (11 samples), 2003 (141 samples), 2008 (521) and 2010 (901 samples) seasons have been fully classified, and the 2014 samples (562) are in the process of being classified and characterized. Given that close to 1500 samples have been classified so far, it seems like a good opportunity to summarize the state of the collection. Here we describe the significant samples documented from this area, as well as a large meteorite shower that dominates the statistics of the region

Efficient Optimization of Echo State Networks for Time Series Datasets

Echo State Networks (ESNs) are recurrent neural networks that only train their output layer, thereby precluding the need to backpropagate gradients through time, which leads to significant computational gains. Nevertheless, a common issue in ESNs is determining its hyperparameters, which are crucial in instantiating a well performing reservoir, but are often set manually or using heuristics. In this work we optimize the ESN hyperparameters using Bayesian optimization which, given a limited budget of function evaluations, outperforms a grid search strategy. In the context of large volumes of time series data, such as light curves in the field of astronomy, we can further reduce the optimization cost of ESNs. In particular, we wish to avoid tuning hyperparameters per individual time series as this is costly; instead, we want to find ESNs with hyperparameters that perform well not just on individual time series but rather on groups of similar time series without sacrificing predictive performance significantly. This naturally leads to a notion of clusters, where each cluster is represented by an ESN tuned to model a group of time series of similar temporal behavior. We demonstrate this approach both on synthetic datasets and real world light curves from the MACHO survey. We show that our approach results in a significant reduction in the number of ESN models required to model a whole dataset, while retaining predictive performance for the series in each cluster

Variance of transmitted power in multichannel dissipative ergodic structures invariant under time reversal

We use random matrix theory (RMT) to study the first two moments of the wave power transmitted in time reversal invariant systems having ergodic motion. Dissipation is modeled by a number of loss channels of variable coupling strength. To make a connection with ultrasonic experiments on ergodic elastodynamic billiards, the channels injecting and collecting the waves are assumed to be negligibly coupled to the medium, and to contribute essentially no dissipation. Within the RMT model we calculate the quantities of interest exactly, employing the supersymmetry technique. This approach is found to be more accurate than another method based on simplifying naive assumptions for the statistics of the eigenfrequencies and the eigenfunctions. The results of the supersymmetric method are confirmed by Monte Carlo numerical simulation and are used to reveal a possible source of the disagreement between the predictions of the naive theory and ultrasonic measurements.Comment: 10 pages, 2 figure

Tunable φ\varphi-Josephson junction with a quantum anomalous Hall insulator

We theoretically study the Josephson current in a superconductor/quantum anomalous Hall insulator/superconductor junction by using the lattice Green function technique. When an in-plane external Zeeman field is applied to the quantum anomalous Hall insulator, the Josephson current $J$ flows without a phase difference across the junction $\theta$. The phase shift $\varphi$ appealing in the current-phase relationship $J\propto \sin(\theta-\varphi$) is proportional to the amplitude of Zeeman fields and depends on the direction of Zeeman fields. A phenomenological analysis of the Andreev reflection processes explains the physical origin of $\varphi$. A quantum anomalous Hall insulator breaks time-reversal symmetry and mirror reflection symmetry simultaneously. However it preserves magnetic mirror reflection symmetry. Such characteristic symmetry property enable us to have a tunable $\varphi$-junction with a quantum Hall insulator.Comment: 10pages, 9figure