Miracle-dz/UniFAR-FTUs huggingface dataset:
Audio Event Detection Using Adaptive Feature Extraction Scheme

—Audio event detection is one of the important tasks of multimedia content analysis. The noise like characteristics and the diversity of audio events make the recognition task difﬁcult when compared with music and speech sounds. Therefore, proper application of feature extraction methods is very crucial, as well as feature selection and machine learning algorithms. Here, we propose a novel adaptive feature extraction scheme along with Support Vector Machine (SVM) learner in recognizing audio events. In our scheme, we propose to apply the widely used Mel frequency cepstral coefﬁcients (MFCCs) feature to the problem in an adaptive way. To this end, we analyze each audio event in its frequency space to obtain a dominant frequency and then make use of the determined dominant frequency in the feature extraction phase. Extensive experiments have been conducted on sixteen (16) different audio events namely alert , clear throat , cough , door slam , drawer , keyboard , keys , knock , laughter , mouse , page turn , pen drop , phone , printer , speech , and switch using the IEEE AASP CASA Challenge Dataset to demonstrate the performance of the proposed scheme. The results show that our adaptive feature extraction scheme achieves signiﬁcantly higher recognition accuracy than traditional feature extraction method with an average F-measure value of 72%.
Event Generation for Next to Leading Order Chargino Production at the International Linear Collider

At the International Linear Collider (ILC), parameters of supersymmetry (SUSY) can be determined with an experimental accuracy matching the precision of next-to-leading order (NLO) and higher-order theoretical predictions. Therefore, these contributions need to be included in the analysis of the parameters. We present a Monte-Carlo event generator for simulating chargino pair production at the ILC at next-to-leading order in the electroweak couplings. We consider two approaches of including photon radiation. A strict fixed-order approach allows for comparison and consistency checks with published semianalytic results in the literature. A version with softand hard-collinear resummation of photon radiation, which combines photon resummation with the inclusion of the NLO matrix element for the production process, avoids negative event weights, so the program can simulate physical (unweighted) event samples. Photons are explicitly generated throughout the range where they can be experimentally resolved. In addition, it includes further higher-order corrections unaccounted for by the fixed-order method. Inspecting the dependence on the cutoffs separating the soft and collinear regions, we evaluate the systematic errors due to soft and collinear approximations for NLO and higher-order contributions. In the resummation approach, the residual uncertainty can be brought down to the per-mil level, coinciding with the expected statistical uncertainty at the ILC. We closely investigate the two-photon phase space for the resummation method. We present results for cross sections and event generation for both approaches.
Serum Anti-Interferon Alpha Antibodies in Chronic Hepatitis C Patients Treated with Pegylated Interferon Alpha Containing Therapy

The development of anti-IFNα antibodies is an occurrence described in chronic hepatitis C patients during treatment with Interferonα/PEG-Interferonα. However, its relevance, especially in difficult-to treat patients, has not been defined. We retrospectively measured the serum levels of anti-IFNα antibodies (baseline and week 12) and IFNα levels (week 12) by ELISA in 76 previous non-responders, and in 14 naïve patients treated with Pegylated-IFNα and Ribavirin. A group of 57 Healthy Donors (HD) was also assessed as control. Positivity to anti-IFNα antibodies was established on the values of HD. Baseline anti-IFNα antibodies were detected in 15.5% of patients and in 7% of HD, with significantly higher concentrations in patients than HD (181.5±389.9 vs 95.9±143.0 ng/mL, p=0.0023). All positive patients were IFNα-experienced. At week 12, the prevalence of positivity increased to 22.3 and 28.5% in experienced and naïve patients, respectively, and the levels of anti-IFNα antibodies did not differ between the two groups (391±792.3 vs 384.7±662.6 ng/mL, respectively). IFNα concentrations were significantly lower in antibody-positive patients than in antibody-negatives (988.2±1402 vs 3462±830.8 pg/mL, p≤0.0001) and the levels of antibodies and IFNα were inversely correlated (r=-0.405, p=0.0001). The antibody-positive population clustered in null responders (67%) and 19/21 patients (90%) did not achieve SVR. In Conclusion, the development of anti-IFNα antibodies is a non-negligible occurrence in patients treated with PEG-IFNα, is stable over time, and has a relevant clinical impact when associated with low levels of circulating PEG-IFNα. It should be considered in patients undergoing treatments including PEG-IFNα. Antibodies; IFNα: Interferon-alpha; EVR: Early Virological Response; EOT: End of Treatment response; SVR: Sustained Virological Null
Machine Learning for Chemogenomics on HPC in the ExCAPE Project

—The ExCAPE project is a Horizon 2020 project to advance the state of the art of machine learning (ML) implementations on supercomputing hardware. We have adopted bioactivity predictions for chemogenomics as a challenging use-case to drive development. In this paper, we will give an overview of the challenges in ExCAPE to use supercomputing efﬁciently. We will touch on three key examples dealing with efﬁcient ML workﬂow execution, support for multi-task learning using matrix factorization methods and the challenges originating from the large and very sparse datasets in ExCAPE.
Lending Standards and Consumption Insurance over the Business Cycle ∗

How much do changes in credit supply affect consumers’ ability to insure against income risk over the business cycle and what is the valuation of such insurance? Using loan-level data from the Senior Loan Ofﬁcer Opinion Survey (SLOOS), we construct measures of key credit supply variables, such as lending standards and terms for consumer credit in the U.S. and build a heterogeneous model of unsecured credit and default that accounts for credit supply dynamics as estimated from these data. Our economy is quantitatively consistent with key features of the unsecured credit market, earnings dynamics, and measures of consumption volatility in the U.S. We ﬁnd that variability in standards and terms for credit is welfare improving despite the loss in consumption insurance that such an environment may induce. The key mechanism behind this result is the asymmetric effect that changes in standards induce for loan pricing in good and bad states of the economy. G12, G21, G22
International Journal of Management Sciences and Business Research, May-2022 ISSN (2226-8235) Vol-11, Issue 5

Marriage has been a primordial practice that spans societies and cultures globally, affecting men and women differently. Women’s role in society has undergone a drastic – being a housewife has almost gone out of fashion and being a working woman has become the new trend. However, despite the sense of independence and freedom that working women enjoy, there has been a noticeable change in the subjective well-being (SWB), life satisfaction and happiness of women. The two main theories regarding life satisfaction: bottom-up and top-down theories are explored briefly. Several factors including marital satisfaction, employment satisfaction, spouse satisfaction and parental satisfaction have an overall influence in the happiness level of a married woman’s life. Moreover, the idea that a woman’s ultimate freedom lies in the labor market is challenged as well – several studies show that some housewives have a greater life satisfaction than married working women. However, there are yet other sources that suggest the subjective well-being of a married women lies beyond the income of the household but the context of where they live is also important, such as the economic standing of the country.
Ground-state coding in partially connected neural networks

Patterns over {- 1,0, 1 } define, by their outer products, partially connected neural networks, consisting of intemally strongly connected, externally weakly connected subnet-works. The connectivity patterns may have highly organized structures, such as lattices and fractal trees or nests. Subpattems over {- 1,1 } define the subcodes stored in the sub-networks. The network code is defined as the set of permutations of the subcode words, one from each subnetwork, that agree in their common bits. It is first shown that the code words are locally stable states of the network, provided that each of the subcodes consists of mutually orthogonal words or of, at most, two words. Then it is shown that if each of the subcodes consists of two orthogonal words, the code words are the unique ground states (absolute minima) of the Hamiltonian associated with the network. The regions of attraction associated with the code words are shown to grow with the number of subnetworks sharing each of the neurons. Depending on the particular network architecture, the code sizes of partially connected networks can be vastly greater than those of fully connected ones and their error correction capabilities can be significantly greater than those of the disconnected subnetworks. The codes associated with lattice-structured and hierarchical networks are discussed in some detail.
Impacts of Established Cardiovascular Risk Factors on the Development of Collateral Circulation in Chronic Total Occlusion of Coronary Arteries

Background: Presence and magnitude of coronary collateral circulation, as an adaptive mechanism has been shown to affect prognosis in patients with ischemic coronary artery disease. Thus far, the clinical determinants of the coronary collateral circulation were not well-established. Objective: The objective of the study is to determine possible relationship between medical history, clinical findings and angiographic evidences of collateral coronary blood flow. Methods: In an observational study, all patients who underwent coronary angiography for the first time with total occlusion in at least one coronary artery were participated in the study from February 2012 to February 2013. To determine the status of collateral flow, patients were divided into 4 groups according to Rentrop classification to detect possible factors that may influence collateral formation. Results: A total of 52 patients met the inclusion criteria and entered the study. Statin therapy (67%), smoking (58%) and a positive family history (19%) were the most frequent findings. According to Rentrop classification, 7 (13.5%) patients were in grade 0, 17(32.7%) in grade 1, 21(40.4%) in grade 2, and 7(13.5%) were classified in grade 3 (Table1). There was significant association between myocardial performance and angiographic findings. There was no statistically significant difference between the grades for any of the risk factors (p value >0.05). Conclusion: Although large epicardial or septal collateral vessels has been stated to become visible within two weeks after a complete occlusion of a major coronary vessel, our findings suggest that this vessel formation could not be related to medical history and clinical findings of patients. set of variables as predictors of collateral circulation [3-9]. Since the underlying molecular mechanism for collateral coronary vessel formation are not directly related to the clinical risk factors, there is still a need for well-designed studies with homogenous participants to show possible predictors of collateral circulation formation. This prospective study tends to investigate impacts of established CAD risk factors as well as the effect of two common prescribed drugs on formation of coronary collateral circulation in patients with chronic total occlusion of the coronary artery.
A FUSION APPROACH TO BUILDING-BOUNDARY EXTRACTION USING AIRBORNE LIDAR DATA AND MULTI-SPECTRAL IMAGES

350 words maximum): Urban areas are rapidly changing over time in most of the countries. Buildings are the main entities of urban areas, and building boundaries are one of the key factors for urban mapping and city modelling. Hence, building-boundary extraction from various data sources has been widely studied. Approaches to the buildingboundary extraction can be categorised as either raster-based methods or point-based methods. Many research efforts have been made to raster-based methods, while few point-based methods exist. The main aim of this study is to detect and extract building boundaries from airborne lidar data using a vector-based method. Three steps are applied directly to the raw lidar points rather than the rasterised lidar data. Firstly, an adaptive morphological filter is developed and applied to separate ground and non-ground points. Secondly, a fusion of methods including Normalized Difference Vegetation Index (NDVI), hierarchical clustering and thresholding is developed in order to remove unwanted points such as trees and cars. Finally, building-boundary polygons are extracted and delineated, based on alpha-shape and Douglas-Peucker algorithms. The test results show that the adaptive morphological filter can accurately classify ground and non-ground points. The extracted building-boundary polygons are proven to be reliable statistically and visually. It is concluded that the proposed point-based method is able to achieve accurate results, even though the low-accuracy horizontal coordinates of the lidar data have limited the algorithm design. The proposed algorithm can also be used for more accurate building-boundary extraction if supplemental data resources such as aerial images are provided. Declaration relating to disposition of project thesis/dissertation I hereby grant to the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or in part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all property rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstracts International (this is applicable to doctoral theses only). Signature . Witness . Date The University recognises that there may be exceptional circumstances requiring restrictions on copying or conditions on use. Requests for restriction for a period of up to 2 years must be made in writing. Requests for a longer period of restriction may be considered in exceptional circumstances and require the approval of the Dean of Graduate Research. FOR OFFICE USE ONLY Date of completion of requirements for Award: THIS SHEET IS TO BE GLUED TO THE INSIDE FRONT COVER OF THE THESIS
The Role of Land Surface Schemes in Short-Range, High Spatial Resolution Forecasts

Many studies have demonstrated the importance of land surface schemes in climate change studies using general circulation models (GCMs). However, there have not been many studies that explore the role of land surface schemes in the context of short-range and high spatial resolution precipitation forecasts. The motivation of this study is to examine the sensitivity of simulated precipitation, and sensible and latent heat ﬂuxes, to the use of different land surface schemes at two different spatial resolutions. The meteorological model used is the Mesoscale Compressible Community (MC2) model, and the land surface schemes are the force–restore method and the Canadian Land Surface Scheme (CLASS). Parallel runs have been performed using MC2/CLASS and MC2/force–restore at spatial resolutions of 10 and 5 km to simulate the severe precipitation case of 19–21 July 1996 in the Saguenay region of Que´bec, Canada. Comparisons of the simulated precipitation time series and the simulated 48-h accumulated precipitation at different spatial resolutions with rain gauges indicate that MC2/ CLASS at 5-km resolution gives the best simulated precipitation. The comparison results show the model accuracy of MC2/CLASS at 10 km is comparable to the accuracy of MC2/force–restore at 5 km. The mechanismresponsible for this is that CLASS represents the land surface vegetation characteristics in a more sophisticated manner than the force–restore method. Furthermore, in CLASS, each grid square is divided into a maximum of four separate subareas, and subvariations of the grid surface vegetation characteristics are taken into account. Therefore, for a grid square containing different types of vegetation, the subgrid-scale information can be used by CLASS, and the computed effective variables that are fed back to MC2 on a 10 (cid:51) 10 km 2 grid are equivalent to computing them at a higher effective resolution than 10 km. This higher effective resolution for surface characteristics is not found in the force–restore method. The total simulated domain-averaged precipitation, and the sum of sensible and latent heat ﬂuxes from MC2/CLASS and MC2/force–restore at different spatial resolutions, are similar. The major difference is in the partitioning of the simulated sensible and latent heat ﬂuxes. The positioning of the simulated precipitation has been improved by using CLASS. The overall results suggest that the impact of land surface schemes is indeed signiﬁcant in a short-range precipitation forecast, especially in regions withcomplicated vegetation variations.
HPLC Puriﬁcation of Higher Plant-Dervied Lignin Phenols for Compound Speciﬁc Radiocarbon Analysis

The ability to measure the radiocarbon content of compounds isolated from complex mixtures has begun to revolutionize our understanding of carbon transformations on earth. Because samples are often small, each new compound isolation method must be tested for background carbon contamination (C ex ). Here, we present a new method for compound-speciﬁc radiocarbon analysis (CSRA) of higher plant-derived lignin phenols. To test for C ex , we compared the ∆ 14 C values of unprocessed lignin phenol containing standard materials (woods, leaves, natural vanillin, and synthetic vanillin) with those of lignin phenols liberated by CuO oxidation and puriﬁed by two-dimensional high-pressure liquid chromatography (HPLC) coupled to mass spectrometry (MS) and UV detection. We assessed C ex associated with (1) microwave assisted CuO oxidation of bulk samples to lignin phenol mono-mers, (2) HPLC puriﬁcation, and (3) accelerator mass spectrometry (AMS) sample preparation. The ∆ 14 C of puriﬁed compounds (corrected for C ex ) agreed, within error, with those of bulk materials for samples that were > 10 µ g C. This method will allow routine analysis of the ∆ 14 C of lignin phenols isolated from terrestrial, aquatic, and marine settings, revealing the time scale for the processing of one of the single largest components of active organic carbon reservoirs on earth.
ANTIOXIDANTS OBTAINED FROM NATURAL SOURCE

: Natural antioxidants are widely distributed in food and medicinal plants. These natural antioxidants, especially polyphenols and carotenoids, exhibit a wide range of biological effects, including anti-inflammatory, anti-aging, anti-atherosclerosis and anticancer. The effective extraction and proper assessment of antioxidants from food and medicinal plants are crucial to explore the potential antioxidant sources and promote the application in functional foods, pharmaceuticals and food additives. The present paper provides comprehensive information on the green extraction technologies of natural antioxidants, assessment of antioxidant activity at chemical and cellular based levels and their main resources from food and medicinal plants.
Isolation and characterization of bacteriaophages against virulent Aeromonas hydrophila

Background: Aeromonas hydrophila is an important water-borne pathogen that leads to a great economic loss in aquaculture. Along with the abuse of antibiotics, drug-resistant strains rise rapidly. In addition, the biofilms formed by this bacterium limited the antibacterial effect of antibiotics. Bacteriophages have been attracting increasing attention as a potential alternative to antibiotics against bacterial infections. Results: Five phages against pathogenic A. hydrophila, named N21, W3, G65, Y71 and Y81, were isolated. Morphological analysis by transmission electron microscopy revealed that phages N21, W3 and G65 belong to the family Myoviridae, while Y71 and Y81 belong to the Podoviridae. These phages were found to have broad host spectra, short latent periods and normal burst sizes. They were sensitive to high temperature but had a wide adaptability to the pH. In addition, the phages G65 and Y81 showed considerable bacterial killing effect and potential in preventing formation of A. hydrophila biofilm; and the phages G65, W3 and N21 were able to scavenge mature biofilm effectively. Phage treatments applied to the pathogenic A. hydrophila in mice model resulted in a significantly decreased bacterial loads in tissues. Conclusions: Five A. hydrophila phages were isolated with broad host ranges, low latent periods, and wide pH and thermal tolerance. And the phages exhibited varying abilities in controlling A. hydrophila infection. This work presents promising data supporting the future use of phage therapy.
Comparison of Selection Method of a Membership Function for Fuzzy Neural Networks

Fuzzy neural networks are learning machine that realize the parameters of a fuzzy system (i.e., fuzzy sets, fuzzy rules) by exploiting approximation techniques from neural networks. In this paper, we tend to illustrate a general methodology, based on statistical analysis of the training data, for the choice of fuzzy membership functions to be utilized in reference to fuzzy neural networks. Fuzzy neural networks give for the extraction of fuzzy rules for from artificial neural network architectures. First, the technique is represented and so illustrated utilizing two experimental examinations for determining the alternate approach of the fuzzy neural network
A Computational Procedure for Identifying Bilinear Representations of Nonlinear Systems Using Volterra Kernels

A computational procedure for identifying the state-space matrices corresponding to discrete bilinear representations of nonlinear systems is presented. A key feature of the method is the use of first- and second-order Volterra kernels (first- and second-order pulse responses) to characterize the system. The present method is based on an extension of a continuous-time bilinear system identification procedure given in a 1971 paper by Bruni, di Pillo, and Koch. The analytical and computational considerations that underlie the original procedure and its extension to the title problem are presented and described, pertinent numerical considerations associated with the process are discussed, and results obtained from the application of the method to a variety of nonlinear problems from the literature are presented. The results of these exploratory numerical studies are decidedly promising and provide sufficient credibility for further examination of the applicability of the method.