An information theoretic characterisation of auditory encoding.

The entropy metric derived from information theory provides a means to quantify the amount of information transmitted in acoustic streams like speech or music. By systematically varying the entropy of pitch sequences, we sought brain areas where neural activity and energetic demands increase as a function of entropy. Such a relationship is predicted to occur in an efficient encoding mechanism that uses less computational resource when less information is present in the signal: we specifically tested the hypothesis that such a relationship is present in the planum temporale (PT). In two convergent functional MRI studies, we demonstrated this relationship in PT for encoding, while furthermore showing that a distributed fronto-parietal network for retrieval of acoustic information is independent of entropy. The results establish PT as an efficient neural engine that demands less computational resource to encode redundant signals than those with high information content

Fold Designability, Distribution, and Disease

Fold designability has been estimated by the number of families contained in that fold. Here, we show that among orthologous proteins, sequence divergence is higher for folds with greater numbers of families. Folds with greater numbers of families also tend to have families that appear more often in the proteome and greater promiscuity (the number of unique “partner” folds that the fold is found with within the same protein). We also find that many disease-related proteins have folds with relatively few families. In particular, a number of these proteins are associated with diseases occurring at high frequency. These results suggest that family counts reflect how certain structures are distributed in nature and is an important characteristic associated with many human diseases

The PTW microSilicon diode: Performance in small 6 and 15 MV photon fields and utility of density compensation

PURPOSE: We have experimentally and computationally characterized the PTW microSilicon 60023-type diode's performance in 6 and 15 MV photon fields ≥5 × 5 mm2 projected to isocenter. We tested the detector on- and off-axis at 5 and 15 cm depths in water, and investigated whether its response could be improved by including within it a thin airgap. METHODS: Experimentally, detector readings were taken in fields generated by a Varian TrueBeam linac and compared with doses-to-water measured using Gafchromic film and ionization chambers. An unmodified 60023-type diode was tested along with detectors modified to include 0.6, 0.8, and 1.0 mm thick airgaps. Computationally, doses absorbed by water and detectors’ sensitive volumes were calculated using the EGSnrc/BEAMnrc Monte Carlo radiation transport code. Detector response was characterized using K^{fdin, 4cm}_{Qclin, 4cm}, a factor that corrects for differences in the ratio of dose-to-water to detector reading between small fields and the reference condition, in this study 5 cm deep on-axis in a 4 × 4 cm2 field. RESULTS: The greatest errors in measurements of small field doses made using uncorrected readings from the unmodified 60023-type detector were over-responses of 2.6% ± 0.5% and 5.3% ± 2.0% determined computationally and experimentally, relative to the reading-per-dose in the reference field. Corresponding largest errors for the earlier 60017-type detector were 11.9% ± 0.6% and 11.7% ± 1.4% over-responses. Adding even the thinnest, 0.6 mm, airgap to the 60023-type detector over-corrected it, leading to under-responses of up to 4.8% ± 0.6% and 5.0% ± 1.8% determined computationally and experimentally. Further, Monte Carlo calculations indicate that a detector with a 0.3 mm airgap would read correctly to within 1.3% on-axis. The ratio of doses at 15 and 5 cm depths in water in a 6 MV 4 × 4 cm2 field was measured more accurately using the unmodified 60023-type detector than using the 60017-type detector, and was within 0.3% of the ratio measured using an ion chamber. The 60023-type diode's sensitivity also varied negligibly as dose-rate was reduced from 13 to 4 Gy min–1 by decreasing the linac pulse repetition frequency, whereas the sensitivity of the 60017-type detector fell by 1.5%. CONCLUSIONS: The 60023-type detector performed well in small fields across a wide range of beam energies, field sizes, depths, and off-axis positions. Its response can potentially be further improved by adding a thin, 0.3 mm, airgap

Fuzz-ClustNet: Coupled fuzzy clustering and deep neural networks for Arrhythmia detection from ECG signals

Electrocardiogram (ECG) is a widely used technique to diagnose cardiovascular diseases. It is a non-invasive technique that represents the cyclic contraction and relaxation of heart muscles. ECG can be used to detect abnormal heart motions, heart attacks, heart diseases, or enlarged hearts by measuring the heart's electrical activity. Over the past few years, various works have been done in the field of studying and analyzing the ECG signals to detect heart diseases. In this work, we propose a deep learning and fuzzy clustering (Fuzz-ClustNet) based approach for Arrhythmia detection from ECG signals. We started by denoising the collected ECG signals to remove errors like baseline drift, power line interference, motion noise, etc. The denoised ECG signals are then segmented to have an increased focus on the ECG signals. We then perform data augmentation on the segmented images to counter the effects of the class imbalance. The augmented images are then passed through a CNN feature extractor. The extracted features are then passed to a fuzzy clustering algorithm to classify the ECG signals for their respective cardio diseases. We ran intensive simulations on two benchmarked datasets and evaluated various performance metrics. The performance of our proposed algorithm was compared with several recently proposed algorithms for heart disease detection from ECG signals. The obtained results demonstrate the efficacy of our proposed approach as compared to other contemporary algorithms

Density compensated diodes for small field dosimetry: Comprehensive testing and implications for design

Purpose. In small megavoltage photon fields, the accuracies of an unmodified PTW 60017-type diode dosimeter and six diodes modified by adding airgaps of thickness 0.6-1.6 mm and diameter 3.6 mm have been comprehensively characterized experimentally and computationally. The optimally thick airgap for density compensation was determined, and detectors were micro-CT imaged to investigate differences between experimentally measured radiation responses and those predicted computationally. Methods. Detectors were tested on- and off-axis, at 5 and 15 cm depths in 6 and 15 MV fields ≥ 0.5 0.5 cm2. Computational studies were carried out using the EGSnrc/BEAMnrc Monte Carlo radiation transport code. Experimentally, radiation was delivered using a Varian TrueBeam linac and doses absorbed by water were measured using Gafchromic EBT3 film and ionization chambers, and compared with diode readings. Detector response was characterized via the formalism, choosing a 4 4 cm2 reference field. Results. For the unmodified 60017 diode, the maximum error in small field doses obtained from diode readings uncorrected by factors was determined as 11.9% computationally at +0.25 mm off-axis and 5 cm depth in a 15 MV 0.5 0.5 cm2 field, and 11.7% experimentally at -0.30 mm off-axis and 5 cm depth in the same field. A detector modified to include a 1.6 mm thick airgap performed best, with maximum computationally and experimentally determined errors of 2.2% and 4.1%. The 1.6 mm airgap deepened the modified dosimeter's effective point of measurement by 0.5 mm. For some detectors significant differences existed between responses in small fields determined computationally and experimentally, micro-CT imaging indicating that these differences were due to within-tolerance variations in the thickness of an epoxy resin layer. Conclusions. The dosimetric performance of a 60017 diode detector was comprehensively improved throughout 6 and 15 MV small photon fields via density compensation. For this approach to work well with good detector-to-detector reproducibility, tolerances on dense component dimensions should be reduced to limit associated variations of response in small fields, or these components should be modified to have more water-like densities

Performance optimization of a leagility inspired supply chain model: a CFGTSA algorithm based approach

Lean and agile principles have attracted considerable interest in the past few decades. Industrial sectors throughout the world are upgrading to these principles to enhance their performance, since they have been proven to be efficient in handling supply chains. However, the present market trend demands a more robust strategy incorporating the salient features of both lean and agile principles. Inspired by these, the leagility principle has emerged, encapsulating both lean and agile features. The present work proposes a leagile supply chain based model for manufacturing industries. The paper emphasizes the various aspects of leagile supply chain modeling and implementation and proposes a new Hybrid Chaos-based Fast Genetic Tabu Simulated Annealing (CFGTSA) algorithm to solve the complex scheduling problem prevailing in the leagile environment. The proposed CFGTSA algorithm is compared with the GA, SA, TS and Hybrid Tabu SA algorithms to demonstrate its efficacy in handling complex scheduling problems

Facile one-pot synthesis of amoxicillin-coated gold nanoparticles and their antimicrobial activity

Nanomaterials have been the object of intense study due to promising applications in a number of different disciplines. In particular, medicine and biology have seen the potential of these novel materials with their nanoscale properties for use in diverse areas such as imaging, sensing and drug vectorisation. Gold nanoparticles (GNPs) are considered a very useful platform to create a valid and efficient drug delivery/carrier system due to their facile and well-studied synthesis, easy surface functionalization and biocompatibility. In the present study, stable antibiotic conjugated GNPs were synthesised by a one-step reaction using a poorly water soluble antibiotic, amoxicillin. Amoxicillin, a member of the penicillin family, reduces the chloroauric acid to form nanoparticles and at the same time coats them to afford the functionalised nanomaterial. A range of techniques including UV-vis spectroscopy, dynamic light scattering (DLS), transmission electron microscopy (TEM) and thermogravimetric analysis (TGA) were used to ascertain the gold/drug molar ratio and the optimum temperature for synthesis of uniform monodisperse particles in the ca. 30-40 nm size range. Amoxicillin-conjugated gold showed an enhancement of antibacterial activity against Escherichia coli compared to the antibiotic alone

An ex vivo porcine spleen perfusion as a model of bacterial sepsis

An ex vivo, porcine spleen perfusion model was established to study the early events occurring in the spleen prior to the onset of bacterial sepsis, using organs retrieved from animals slaughtered for food production. Porcine spleens were harvested from adult pigs and connected to a normothermic extracorporeal perfusion circuit. Constant perfusion of heparinized blood was performed for 6 hours. After injection of Streptococcus pneumoniae to the circuit, serial samples of both blood and spleen biopsies were collected and analyzed. Functionality of the perfused organs was assessed by monitoring the blood-gas parameters, flow rate and filtering capability of the organ. Interestingly, we observed full clearance of bacteria from the blood and an increase in bacterial counts in the spleen. Classical histology and immunohistochemistry on biopsies also confirmed no major damage in the organ architecture and no changes in the immune cell distribution other than the presence of clusters of pneumococci. A time-course study confirmed that each focus of infection derived from the replication of single pneumococcal cells within splenic macrophages. The model proposed – in line with the 3Rs principles – has utility in the replacement of experimental animals in infection research. Murine models are prevalently used to study pneumococcal infections but are often not predictive for humans due to substantial differences in the immune systems of the two species. This model is designed to overcome these limitations, since porcine immunology, and splenic architecture in particular, closely resemble those of humans

6D supergravity without tensor multiplets

We systematically investigate the finite set of possible gauge groups and matter content for N = 1 supergravity theories in six dimensions with no tensor multiplets, focusing on nonabelian gauge groups which are a product of SU(N) factors. We identify a number of models which obey all known low-energy consistency conditions, but which have no known string theory realization. Many of these models contain novel matter representations, suggesting possible new string theory constructions. Many of the most exotic matter structures arise in models which precisely saturate the gravitational anomaly bound on the number of hypermultiplets. Such models have a rigid symmetry structure, in the sense that there are no moduli which leave the full gauge group unbroken.Comment: 31 pages, latex; v2, v3: minor corrections, references adde

Intraoperative angiography should be standard in cerebral aneurysm surgery

Intraoperative angiography (IOA) has proven to be a safe and effective adjunct to surgical repair of cerebral aneurysms. Substantial practice variation exists regarding use of this modality in different centers, including use of IOA routinely, selectively, or rarely. In this editorial, we discuss our experience and review the existing literature to develop an argument for routine use of IOA during cerebral aneurysm surgery