Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Algorithms Performance Analysis for Noise Cancellations using Neural Networks employing real time signals

Noise problems in signals have gained huge attention due to the need of noise-free output signal in mobile communication systems. The principal of adaptive noise cancellation is to acquire an estimation of the unwanted interfering signal and subtract it from the corrupted signal. We proposed signal extraction using Artificial Neural Network Hybrid Back Propagation Adaptive Algorithm (ANNHBPAA) for mobile Applications. ANNHBPAA exploits correlation between the pure speech signal and noise corrupted signal, to generate an estimate of the noise, which in turn subtracts the noise from the noise corrupted signal. The performance analysis of hybrid adaptive algorithms is done based on convergence behaviour, convergence time, correlation coefficients and signal to noise ratio. By taking into considerations of existing algorithms performance proposed hybrid adaptive algorithms gives better convergence behaviour, convergence time, correlation coefficients and signal to noise ratio. Proposed algorithm with only small training sets and it yields good results. Noise cancellation operation is controlled adaptively with the target of achieving improved signal to noise ratio. This paper concentrates upon the analysis of adaptive noise canceller using Recursive Least Square (RLS), Fast Transversal Recursive Least Square (FTRLS) and Gradient Adaptive Lattice (GAL) algorithms. The performance analysis of the algorithms is done based on convergence behaviour, convergence time, correlation coefficients and signal to noise ratio. After comparing all the simulated results we observed that GAL performs the best in noise cancellation in terms of Correlation Coefficient, SNR and Convergence Time. Here RLS Signal to noise ratio is made use as input to generate FTF and GAL signal to noise ratio at 30 DB, at 10 DB and also at -10 DB. Correlation coefficient and convergence time of RLS, FTF and GAL is also generated using neural network techniques.
Research on Similarity Measurements of 3D Models Based on Skeleton Trees

There is a growing need to be able to accurately and efficiently recognize similar models from existing model sets, in particular, for 3D models. This paper proposes a method of similarity measurement of 3D models, in which the similarity between 3D models is easily, accurately and automatically calculated by means of skeleton trees constructed by a simple rule. The skeleton operates well as a key descriptor of a 3D model. Specifically, a skeleton tree represents node features (including connection and orientation) that can reflect the topology and branch features (including region and bending degree) of 3D models geometrically. Node feature distance is first computed by the dot product between node connection distance, which is defined by 2-norm, and node orientation distance, which is defined by tangent space distance. Then branch feature distances are computed by the weighted sum of the average regional distances, as defined by generalized Hausdorff distance, and the average bending degree distance as defined by curvature. Overall similarity is expressed as the weighted sum of topology and geometry similarity. The similarity calculation is efficient and accurate because it is not necessary to perform other operations such as rotation or translation and it considers more topological and geometric information. The experiment demonstrates the feasibility and accuracy of the proposed method.
Robust speaker recognition in the presence of speech coding distortion

iv List of Figures ix List of Tables xi Chapter 1: Introduction 1 1.1 Statement of the Problem 1 1.2 Motivation 1 1.3 Objective of Thesis 2 1.4 Thesis Focus and Organization 3 Chapter 2: Background 5 2.1 Narrow-Band Speech Coding 6 2.1.1 G723.1 6 2.1.2 G729 6 2.1.3 GSM-AMR 7 2.2 Features 7 2.2.1 Linear Prediction 7 2.2.2 Linear Predictive Cepstrum Feature (CEP) 9 2.2. 3 Adaptive Component Weighting (ACW) 11 2.2. 4 Postfilter Cepstrum (PST) 11 vi Table of
Enteropathogenic Viruses: Triggers for Exacerbation in IBD? A Prospective Cohort Study Using Real-time Quantitative Polymerase Chain Reaction

Background:While the role of bacteria as an etiological factor triggering relapse in inflammatory bowel disease (IBD) has been studied extensively, little is known of the role of enteric viruses. We aimed to prospectively study the prevalence and risk factors for common enteropathogenic viruses in IBD patients in relation to disease activity. Methods:IBD patients visiting the outpatient clinic of the Maastricht University Medical Center were included in a prospective cohort with a follow-up of 1 year. Every 3 months and during relapses, fecal samples, demographic, and clinical data were collected and disease activity was scored. A fecal sample from patients at baseline (Crohn’s disease [CD] n = 170, ulcerative colitis [UC] n = 116) and an additional sample from a subgroup with changing disease activity during follow-up (CD n = 57, UC n = 31) were analyzed for the presence of rotavirus, norovirus GI and GII, human astrovirus, and adenovirus using quantitative polymerase chain reaction (qPCR). Results:Overall viral pathogen detection, defined by the detection of at least one of the studied viruses, at baseline was 5.2% and differed neither between CD (6.5%) or UC patients (3.4%) (P = 0.20), nor between active disease (4.7%) and remission (5.5%) (P = 0.79). Within the subgroup of patients with changing disease activity no association was found between overall viral pathogen detection and disease activity (P = 0.39). Using multivariate logistic regression, age, gender, disease subtype, disease activity, medication, and season of sampling were not associated with overall viral pathogen detection. Conclusions:Enteropathogenic viruses are not frequently observed in a consecutive cohort of IBD patients and are not a common trigger for active disease in daily clinical practice.
Risk Analysis of Thrombo-Embolic and Recurrent Bleeding Events in the Management Of Intracranial Haemorrhage Due to Oral Anticoagulation

Abstract Purposes : Intracranial haemorrhage (ICH) is a rare but potentially devastating complication of oral anticoagulants (OAC). This raises the difficult clinical choice between either permanent cessation of OAC, or continuing OAC and if so, when to restart. To make this choice, one needs to balance the thrombo-embolic risk after cessation of OAC against the risk of recurrent intracranial haemorrhage when OAC are restarted. There are few published data to base this difficult clinical decision on. Methods : We present an observational study of a consecutive series of 108 patients, collected prospectively and admitted to our department, with an OAC-related intracranial haemorrhage, in whom we assessed the thrombotic event rate and the recurrent intracranial bleeding rate during follow-up. Results : In the 25 patients in whom OAC were reinstituted no new thrombo-embolic events occurred (0/506 unprotected patient-days). In the group of patients in whom OAC were not restarted (n = 81), the thrombo-embolic event rate was 8/11590 unprotected patient-days, of which only 2 were cerebrovascular thrombo-embolisms. The overall risk of a thrombo-embolic complication can be estimated to be 0.66 events/1000 patient-days at risk (95% exact confidence limits of 0.3 to 1.3 events/1000 patient-days at risk). In three patients the thrombo-embolic event was fatal. We saw recurrent intracranial bleeding in eight patients, 2 of which were fatal. Seven of these occurred before the restarting of the OAC. Conclusions : In OAC-related intracranial haemorrhages, OAC can be stopped safely for a considerable period, with a very low overall thrombotic event rate. The recurrent bleeding risk after restarting OAC is low. Recurrent bleeding mostly occurred before restarting OAC and is probably caused by insufficient or unsustained correction of the initial coagulation deficit. Immediate reversal of anticoagulation provides the patient with the best possible treatment options including surgery. OAC-related intracranial haemorrhages can therefore be actively treated.
Expression of key hypoxia sensing prolyl‐hydroxylases PHD1, ‐2 and ‐3 in pancreaticobiliary cancer

Gossage L, Zaitoun A, Fareed K R, Turley H, Aloysius M, Lobo D N, Harris A L & Madhusudan S (2010) Histopathology 56, 908–920 Expression of key hypoxia sensing prolyl‐hydroxylases PHD1, ‐2 and ‐3 in pancreaticobiliary cancer
Inhomogeneous Metasurfaces With Engineered Dispersion for Broadband Hybrid-Mode Horn Antennas

Metamaterial and metasurface structures, which satisfy the balanced hybrid conditions, have been recently proposed for designing hybrid-mode soft and hard horn antennas. In this paper, we present the design of broadband soft metasurfaces and their applications in hybrid-mode conical horns. These designs exhibit surface characteristics that can be controlled by adjusting the constituent structural elements. The analysis and design of metasurfaces were performed on both a planar platform and in a cylindrical waveguide structure. Such dispersion-engineered metasurfaces with customized surface properties can support the desired hybrid modes in a cylindrical waveguide, facilitating their usage in horn antennas. By engineering the metasurfaces with regard to their surface impedance as well as tailoring their spatial distributions along the wall of the horn, we demonstrate an inhomogeneous metahorn with superior performance and broader bandwidth compared to those with uniform liners. The symmetric far-field radiation patterns with low sidelobe and cross-polarization levels, together with the corresponding aperture field distributions, signifies the hybrid-mode operation of the horn, validating the efficacy and broadband performance of the metasurfaces. Such metasurface-lined horns can be employed as soft feeds in dual polarization antenna systems.
Campaigning on Twitter: Microblogging and Online Social Networking as Campaign Tools in the 2010 General Elections in the Netherlands

The present study focuses on how candidates in the Dutch general elections of 2010 use Twitter, a popular microblogging and social networking service. Specifically the study focuses on explaining why some candidates are more likely to adopt Twitter, have larger networks, and show more reciprocation than other candidates. The innovation hypothesis, predicting that candidates from less established and smaller parties will use Twitter more extensively, is unsupported. This suggests that normalization of campaign practices is present on Twitter, not changing existing communication practices. The findings do show that being an early adopter of these new technologies is more effective than adoption shortly before Election Day.
A Semi-supervised Learning Approach for Microblog Sentiment Classification

Most sentiment classification for microblogs are based on supervised learning methods. The performance of these methods heavily relies on carefully chosen training datasets. These datasets usually cannot be too small. This is cumbersome and makes these methods less attractive for practical use. To address this problem, approaches to automatically generate training datasets have been proposed. However, these approaches are usually rule-based, hence they cannot guarantee the diversity of the training datasets. In particular, the huge imbalance between the subjective classes and objective classes in the sentiment of tweets makes it especially difficult to obtain good recall performance for the subjective class. To address this issue, this paper proposes a semi-supervised learning approach for tweet sentiment classification. Experiments show that the performance of our proposed method is significantly better than the previous work.
Paired-Homeodomain Transcription Factor PAX4 Acts as a Transcriptional Repressor in Early Pancreatic Development

ABSTRACT The paired-homeodomain transcription factor PAX4 is expressed in the developing pancreas and along with PAX6 is required for normal development of the endocrine cells. In the absence of PAX4, the numbers of insulin-producing β cells and somatostatin-producing δ cells are drastically reduced, while the numbers of glucagon-producing α cells are increased. To gain insight into PAX4 function, we cloned a full-length Pax4 cDNA from a β-cell cDNA library and identified a bipartite consensus DNA binding sequence consisting of a homeodomain binding site separated from a paired domain binding site by 15 nucleotides. The paired half of this consensus sequence has similarities to the PAX6 paired domain consensus binding site, and the two proteins bind to common sequences in several islet genes, although with different relative affinities. When expressed in an α-cell line, PAX4 represses transcription through the glucagon or insulin promoters or through an isolated PAX4 binding site. This repression is not simply due to competition with the PAX6 transcriptional activator for the same binding site, since PAX4 fused to the unrelated yeast GAL4 DNA binding domain also represses transcription through the GAL4 binding site in the α-cell line and to a lesser degree in β-cell lines and NIH 3T3 cells. Repressor activity maps to more than one domain within the molecule, although the homeodomain and carboxyl terminus give the strongest repression. PAX4 transcriptional regulation apparently plays a role only early in islet development, since Pax4 mRNA as determined by reverse transcriptase PCR peaks at embryonic day 13.5 in the fetal mouse pancreas and is undetectable in adult islets. In summary, PAX4 can function as a transcriptional repressor and is expressed early in pancreatic development, which may allow it to suppress α-cell differentiation and permit β-cell differentiation.
Injecting 3rd harmonic into the input curent to improve the power factor of DCM buck PFC converter

The conventional Buck PFC converter adopts constant duty cycle control (CDCC), which can improve the PF to some degree. However, the peak and RMS values of the inductor current are large, which also occurs to the switch and diode. This paper derives the expressions of the input current and PF of DCM Buck PFC converter, and based on which, a kind of injecting 3rd current harmonic control (ICHC) is proposed so as to improve the PF in the whole input voltage range. Besides a higher PF, the proposed novel control achieves a lower output voltage ripple, a smaller rms value of the inductor current and a higher efficiency than the conventional control. The experimental results from a 120 W universal input prototype are presented to verify the validity of the proposed method.
Spatial nonuniformity of the resting CBF and BOLD responses to sevoflurane: In vivo study of normal human subjects with magnetic resonance imaging

Pulsed arterial spin labeling magnetic resonance imaging (MRI) was performed to investigate the local coupling between resting regional cerebral blood flow (rCBF) and BOLD (blood oxygen level dependent) signal changes in 22 normal human subjects during the administration of 0.25 MAC (minimum alveolar concentration) sevoflurane. Two states were compared with subjects at rest: anesthesia and no‐anesthesia. Regions of both significantly increased and decreased resting‐state rCBF were observed. Increases were limited primarily to subcortical structures and insula, whereas, decreases were observed primarily in neocortical regions. No significant change was found in global CBF (gCBF). By simultaneously measuring rCBF and BOLD, region‐specific anesthetic effects on the coupling between rCBF and BOLD were identified. Multiple comparisons of the agent‐induced rCBF and BOLD changes demonstrated significant (P < 0.05) spatial variability in rCBF–BOLD coupling. The slope of the linear regression line for AC, where rCBF was increased by sevoflurane, was markedly smaller than the slope for those ROIs where rCBF was decreased by sevoflurane, indicating a bigger change in BOLD per unit change in rCBF in regions where rCBF was increased by sevoflurane. These results suggest that it would be inaccurate to use a global quantitative model to describe coupling across all brain regions and in all anesthesia conditions. The observed spatial nonuniformity of rCBF and BOLD signal changes suggests that any interpretation of BOLD fMRI data in the presence of an anesthetic requires consideration of these insights. Hum Brain Mapp 2008. © 2007 Wiley‐Liss, Inc.
Proving expected sensitivity of probabilistic programs

Program sensitivity, also known as Lipschitz continuity, describes how small changes in a program’s input lead to bounded changes in the output. We propose an average notion of program sensitivity for probabilistic programs—expected sensitivity—that averages a distance function over a probabilistic coupling of two output distributions from two similar inputs. By varying the distance, expected sensitivity recovers useful notions of probabilistic function sensitivity, including stability of machine learning algorithms and convergence of Markov chains. Furthermore, expected sensitivity satisfies clean compositional properties and is amenable to formal verification. We develop a relational program logic called EpRHL for proving expected sensitivity properties. Our logic features two key ideas. First, relational pre-conditions and post-conditions are expressed using distances, a real-valued generalization of typical boolean-valued (relational) assertions. Second, judgments are interpreted in terms of expectation coupling, a novel, quantitative generalization of probabilistic couplings which supports compositional reasoning. We demonstrate our logic on examples beyond the reach of prior relational logics. Our main example formalizes uniform stability of the stochastic gradient method. Furthermore, we prove rapid mixing for a probabilistic model of population dynamics. We also extend our logic with a transitivity principle for expectation couplings to capture the path coupling proof technique by Bubley and Dyer, and formalize rapid mixing of the Glauber dynamics from statistical physics.
Altered WNT Signaling in Human Induced Pluripotent Correspondence BP Stem Cell Neural Progenitor Cells Derived from Four Schizophrenia Patients

Schizophrenia (SZ) is a devastating psychiatric disorder hypothesized to be a neurodevelopmental condition (1,2) arising as a consequence of dysregulation of brain development (3,4). WNT signaling is important for neural patterning, proliferation and migration, and synapse formation (5); converging postmortem (6,7), rodent (8,9), and pharmacologic (10) evidence suggests that WNT signaling may contribute to SZ (11,12). We used human induced pluripotent stem cell (hiPSC) derived forebrain patterned neural progenitor cells (NPCs) (13,14) to investigate canonical WNT activity in a pilot cohort of four patients with SZ. Because all research described herein was performed on deidentified human samples obtained for broadly consented scientific research by either American type culture collection or the Coriell Cell Repository, it was found to be exempt by the Internal Review Committee of the Icahn School of Medicine at Mount Sinai. This work was also reviewed by the Embryonic Stem Cell Research Oversight Committee at the Icahn School of Medicine at Mount Sinai. We compared global transcription of forebrain hiPSC NPCs from six control subjects and four patients with SZ by RNA sequencing (GSE63738) (Table 1), cultured as described (13,14). As previously reported, hiPSC forebrain NPCs differentiate to a mixed neuronal population of glutamatergic and GABAergic neurons; there was no difference in the ability of control or SZ hiPSC NPCs to generate βIII-tubulin–positive neurons (14), and neither transcriptional nor immunohistochemical characterization revealed any diagnosis-dependent differences in the regional patterning of forebrain NPCs (13). Multidimensional scaling resolved most SZ and control hiPSC NPC samples (Figure 1A); 848 genes were significantly differentially expressed (false discovery rate , .05) (Table S1 in Supplement 1), as illustrated by a heat map (Figure 1C) and a volcano plot (Figure 1D). The differentially expressed genes in SZ hiPSC NPCs were significantly 3.6-fold enriched compared with WNT target genes (p , 10e-20) predicted by standard classification and regression tree methods (16). The
Assessment of false positives with the Humphrey Field Analyzer II perimeter with the SITA Algorithm.

PURPOSE To evaluate the effects of false-positive (FP) response errors on mean deviation (MD), pattern standard deviation (PSD), glaucoma hemifield test (GHT), and test duration in the Humphrey Field Analyzer's (HFA II) Swedish Interactive Threshold Algorithm (SITA; Carl Zeiss Meditec, Inc., Dublin, CA). METHODS Five individuals with glaucoma (ages 52, 63, 69, 77, and 78 years) and five individuals with normal, healthy eyes (ages 25, 34, 43, 45, and 52 years), participated in the study. Each subject was experienced in automated perimetry and performed multiple, monocular baseline SITA-standard (SITA-S) 24-2 visual field tests. In addition, normal subjects completed SITA-S 24-2 field examinations in which known frequencies of FP error were introduced (0%, 5%, 10%, 20%, or 33% frequency). Likewise, the subjects with glaucoma completed visual field examinations with 0%, 20%, and 33% error introduced during the test. RESULTS Reported FP errors were significantly lower than the introduced frequency of error. The SITA algorithm more accurately identified FP errors when the MD and PSD diverged from normal. Test duration increased as introduced error frequencies increased. The Statpac single-field analyses indicated that two thirds of the tests with introduced errors produced a "low-patient-reliability" determination. CONCLUSIONS HFA II SITA-S underestimates patients' FP errors, particularly among normal patients. High FP error frequencies can have adverse effects on MD and PSD, leading clinicians and researchers to an inaccurate determination of the amount and severity of visual field loss.
Compact Printed Monopole Antenna with Super-wideband

A compact semi-elliptical patch antenna fed by a tapered coplanar waveguide (CPW) is presented. The simulated and experimental results demonstrate that the antenna possesses the desirable super-wideband (SWB) characteristics, achieving a ratio bandwidth of 19.7:1 for VSWRles2, and exhibits a nearly omni-directional radiation pattern, while its area is only about 0.15 lambda1 times 0.2 1 lambda1, where lambda1 is the wavelength of the lowest operating frequency.
Surface-enhanced Raman spectroscopy using gold-coated horizontally aligned carbon nanotubes

Gold-coated horizontally aligned carbon nanotube (Au-HA-CNT) substrates were fabricated for surface-enhanced Raman spectroscopy (SERS). The Au-HA-CNT substrates, which are granular in nature, are easy-to-prepare with large SERS-active area. Enhancement factors (EFs) of ∼107 were achieved using the Au-HA-CNTs as substrates for rhodamine 6G (R6G) molecules. Maximum enhancement was found when the polarization direction (E-field) of the incident laser beam was parallel to the aligned direction of the HA-CNTs. Simulations using the finite-difference time-domain (FDTD) method were carried out for the granular Au-HA-CNT samples. Enhancement mechanisms and determination of EFs were analyzed. Biological samples, including 13C- and deuterium (D)-labeled fatty acids and Coccomyxa sp. c-169 microalgae cells, were also measured using this SERS substrate. The limits of detection (LODs) of D- and 13C-labeled fatty acids on the SERS substrate were measured to be around 10 nM and 20 nM, respectively. Significantly enhanced Raman signals from the microalgae cells were acquired using the SERS substrate.