The mid-term effects of carotid endarterectomy on cognition and regional neural activity analyzed with the amplitude of low frequency fluctuations technique

Purpose The study aims to evaluate the mid-term effects of carotid endarterectomy (CEA) on cognition and resting-state functional magnetic resonance imaging (rs-fMRI) using the Amplitude of Low Frequency Fluctuations (ALFF) technique. Methods In this observational study, patients eligible for CEA were prospectively included. On the same day, within 1 week of the CEA procedure performed and 12 months after the CEA procedure, all patients underwent (i) an MRI examination for rs-fMRI analysis and (ii) a cognitive evaluation using the Italian version of the Mini-Mental State Examination (MMSE) corrected for age and schooling. Pre-CEA and post-CEA MMSE scores were evaluated using paired sample t-tests, adopting a p-value < 0.05 as statistical threshold. The ALFF technique was used for analyzing the differences between pre-CEA and post-CEA rs-fMRI scans in terms of regional neural activation. This was accomplished by applying non-parametric statistics based on randomization/permutation for cluster-level inferences, adopting a cluster-mass p-value corrected for false discovery < 0.05 for cluster threshold, and a p-uncorrected < 0.01 for the voxel threshold. Results Twenty asymptomatic patients were enrolled. The mean MMSE score resulted improved following CEA procedure (p-value = 0.001). The ALFF analysis identified a single cluster of 6260 voxels of increased regional neural activity following CEA, and no cluster of reduced activity. The majority of voxels covered the right precentral gyrus, the right middle frontal gyrus, and the anterior division of the cingulate gyrus. Conclusion Mid-term cognitive improvements observed after CEA are associated to increased regional neural activity of several cerebral regions.

Phylogenetic structure of Shiga toxin-producing Escherichia coli O157:H7 from sub-lineage to SNPs

Sequence similarity of pathogen genomes can infer the relatedness between isolates as the fewer genetic differences identified between pairs of isolates, the less time since divergence from a common ancestor. Clustering based on hierarchical single linkage clustering of pairwise SNP distances has been employed to detect and investigate outbreaks. Here, we evaluated the evidence-base for the interpretation of phylogenetic clusters of Shiga toxin-producing Escherichia coli (STEC) O157:H7. Whole genome sequences of 1193 isolates of STEC O157:H7 submitted to Public Health England between July 2015 and December 2016 were mapped to the Sakai reference strain. Hierarchical single linkage clustering was performed on the pairwise SNP difference between all isolates at descending distance thresholds. Cases with known epidemiological links fell within 5-SNP single linkage clusters. Five-SNP single linkage community clusters where an epidemiological link was not identified were more likely to be temporally and/or geographically related than sporadic cases. Ten-SNP single linkage clusters occurred infrequently and were challenging to investigate as cases were few, and temporally and/or geographically dispersed. A single linkage cluster threshold of 5-SNPs has utility for the detection of outbreaks linked to both persistent and point sources. Deeper phylogenetic analysis revealed that the distinction between domestic UK and imported isolates could be inferred at the sub-lineage level. Cases associated with domestically acquired infection that fall within clusters that are predominantly travel associated are likely to be caused by contaminated imported food.

Implementasi Single Pass Clustering pada Preprocessing Temu Kembali Koleksi Berita Teks

Berita saat ini masih menjadi sumber yang dipercaya untuk mendapatkan informasi. Namun seiring dengan perkembangan teknologi berita yang terbit menjadi semakin banyak jumlahnya. Akibat dari jumlah berita yang banyak diperlukan suatu sistem yang dapat dipergunakan untuk menemukan berita dengan cepat. Sistem Temu Kembali menjadi cara yang dapat dipergunakan untuk membantu menangani masalah tersebut. Sistem temu kembali yang ada masih terus dikaji efisiensinya jika berhubungan dengan jumlah informasi yang sangat besar. Makalah ini melakukan pengujian efektifitas dan efisiensi tambahan preprocessing pada sistem temu kembali. Langkahnya yaitu mengklasterkan informasi yang ada terlebih dahulu. Pada preprocesing ini diimplementasikan metode single pass clustering. Kemudian pencocokan query dengan dokumen disederhanakan kepada pencocokan query dengan centroid klaster. Hasil uji coba efisiensi menunjukkan bahwa sistem temu kembali yang mengimplementasikan single pass clustering mampu mencari berita dengan lebih cepat. Sedangkan pengujian efektifitas untuk mengetahui seberapa tepat berita yang bisa diketahui dari nilai pengujian precision, recall, dan f-score. Dari pengujian tersebut didapatkan hasil jika proses pencarian paling tepat dilakukan pada cluster dengan nilai threshold 0,1. Pengujian pada cluster threshold 0,1, f-score terbaik didapatkan ketika dilakukan proses temu kembali berita dengan keyword ‘4g lte’ bernilai 0,732. Sedangkan pengujian f-score terburuk terdapat pada pengujian dengan keyword ‘aplikasi whatsapp’ dengan nilai 0,111. Sedangkan secara umum, sistem yang diusulkan selalu lebih cepat hanya saja lebih rendah nilai performa precision, recall, dan f-score-nya.

0315 Gray Matter Volume of the Rostral Medial Prefrontal Cortex is Associated with Resilience to Mood Decline During Overnight Sleep Deprivation

Introduction Vulnerability to sleep deprivation (SD) has been attributed to inter-individual trait-like differences in the ability to sustain vigilance and subjective alertness, which may have distinct neurobiological substrates. We have previously shown that reduced suppression of the Default Mode Network (DMN) during a cognitive task was predictive of global vulnerability to SD. However, little is known about vulnerability to mood decrements during SD and the underlying neurobiological mechanisms. Using voxel-based morphometry (VBM), we assessed structural differences in gray matter volume (GMV) of a region of the anterior DMN, the medial prefrontal cortex and its association with self-reported mood during 29 hours of SD. Methods 45 healthy participants (23 male; Ages 20-43) underwent 3T structural magnetic resonance imaging (MRI). Within 4 days, participants underwent an overnight SD session (29 hours awake total) which included hourly mood assessments with several visual analog mood scales (VAMS) assessing positive and negative affect. Hourly VAMS data were converted into a comparative metric of percent worsening of mood scores from 19:00 until noon the next day. These scores were averaged to determine a “mood resilience” score, with higher scores indicating greater mood sustainment. Using SPM12, the mean mood resilience scores were correlated with whole-brain gray matter volume, restricted to the medial prefrontal cortex, p&lt;.05, FWE corrected, with a cluster threshold of 137 voxels. Results Overnight mood resilience was significantly correlated with greater grey matter volume in right rostral medial prefrontal cortex (p&lt;.05, corrected; k=137). Conclusion Individuals with greater gray matter volume within a circumscribed region of the right medial prefrontal cortex demonstrated greater resilience to mood degradation over 29 hours of continuous wakefulness. This same region of the brain has been shown to be critical for the passive maintenance of emotions. We speculate that greater GMV could protect against mood decline by better sustaining emotional state during SD. Support Defense Advanced Research Projects Agency Young Faculty Award: DARPA-12-12-11-YFA11-FP-029

Do group affiliated firms specialize in debt? Evidence from Pakistan

Purpose – The purpose of this paper is to examine the debt structure of group affiliated firms in Pakistan for the period of 2009-2011. The study seeks to know the level of debt specialization in group affiliated firms. If they do; then how are they different from stand-alone firms? Design/methodology/approach – The study primarily uses Herfindahl-Hirschman Index and Excl90 as measures of debt specialization, which are further used in cluster, threshold and conditional analysis. Corporate groups are characterized to subsidize their affiliates through internal debt market and loan guarantee. Logistic regression model is used to analyze association among the measures of debt specialization and firm-specific characteristics for group affiliated and stand-alone firms. Findings – The results show that about 85 percent firms use more than 50 percent of debt from one debt type. However, group affiliated firms are more inclined toward debt specialization than stand-alone firms. Tangibility and book leverage are negatively and significantly associated to the measures of debt specialization. Moreover, internal debt market and loan guarantee are suggestive reasons of debt specialization in group affiliated firms. Practical implications – This study highlights the issue of group affiliation and its significance on firm’s debt structure. It has implications for determination of the optimal financing strategy. In the context of emerging economies, group affiliated firms can create market imperfections as a protection shield. In case of emerging markets, it is recommended to strengthen regulatory mechanism to avoid such market imperfections. Originality/value – Prior studies have explored the phenomenon of debt specialization for rated and unrated firms. However, firm group affiliation is widely studied in the context of capital structure. This is a pioneer study to establish and analyze a link between firm group affiliation and debt specialization.

Confidence of Detection of Fracture Signals Using Acoustic Emission

This paper reports on a practical investigation into methodology confidence of detection (COD) in acoustic emission (AE) testing. The developed technique relies on a commercially available software technique called “source cluster analysis” that examines the number of detected signals over a specific area. Two factors that control cluster analysis are cluster size (the area that signals are detected within) and cluster threshold (the number of detected events required to trigger a cluster). A confidence of detection matrix was developed based on altering cluster size and cluster threshold which was then applied to a practical investigation of a four-point bend test monitored using AE. Fracture length in the specimen was monitored using a foil crack gauge. The varying sizes and thresholds of the confidence matrix were used in a cluster analysis of the recorded AE data, as the initial cluster formed in the fracture region a crack length could be identified (based on the foil crack gauge). Results showed that it was possible to detect a crack length of 0.55 mm with a very high level of confidence.

Asymptotic behaviour of nonlocal effective potentials in two-cluster atomic scattering

Dilation and boost transformations are used to study the nonlocal effective potentials in two-cluster atomic scattering below the lowest three-cluster threshold, where the particles interact via two-body Coulomb potentials and at least one cluster is neutral. Boost analyticity is used to express the rotated potential in a form that displays explicitly its behaviour for large values of the cluster separation. When one cluster is neutral, the nonlocal effective potential falls off, in some sense, as r−4 for large values of r, where r is the distance between the centres of mass of the two clusters. When both clusters are neutral, the nonlocal potential can be shown to fall off as r−5 for large values of r.