Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical relevance of model based computer-assisted diagnosis and therapy

The ability to acquire and store radiological images digitally has made this data available to mathematical and scientific methods. With the step from subjective interpretation to reproducible measurements and knowledge, it is also possible to develop and apply models that give additional information which is not directly visible in the data. In this context, it is important to know the characteristics and limitations of each model. Four characteristics assure the clinical relevance of models for computer-assisted diagnosis and therapy: ability of patient individual adaptation, treatment of errors and uncertainty, dynamic behavior, and in-depth evaluation. We demonstrate the development and clinical application of a model in the context of liver surgery. Here, a model for intrahepatic vascular structures is combined with individual, but in the degree of vascular details limited anatomical information from radiological images. As a result, the model allows for a dedicated risk analysis and preoperative planning of oncologic resections as well as for living donor liver transplantations. The clinical relevance of the method was approved in several evaluation studies of our medical partners and more than 2900 complex surgical cases have been analyzed since 2002.
Modeling a Dialog System for Movie Recommendations Based on The Movie Database

Many people look for a recommendation, when they are choosing which movie to watch. Some ask friends, others search the internet. In this thesis we introduce another way to get a movie recommendation using a dialog system, that gets to know the users by learning their preferences and then recommend them movie, they might like. The goal of this thesis work is to model and develop a dialog system for movie recommendations based on The Movie Database. The dialog system is implemented as text-based and social recommendation system, using a combination of state-based and frame-based dialog control strategies. The result of the system is a system-directed dialog, in which its main aim is a movie recommendation to the user. To accomplish that the system builds and uses a model of the user and a dialog history. The rst part of the thesis gives an introduction in the theoretical fundamentals, which are used in the following development of the system of the thesis, such as structure and types of dialog systems and recommendation systems. The system implementation is described in the second part of the thesis. In the last part of the thesis the user study, conducted to evaluate the system, and its results are outlined.
Serum leptin concentration in patients with type 2 diabetes

Abstract With the increasing importance of early type 2 diabetes (DM2) and obesity detection, it is useful to reevaluate leptin role in these conditions. Our study aimed at investigating circulating leptin concentrations in a group of patients with DM2, and at assessing in detail whether leptin concentrations correlate with selected biochemical, clinical parameters and markers of systemic inflammation in patients with DM2 and in healthy volunteers. In our work, we analysed samples and data drawn from 71 patients aged 61.4 ± 11.7 years, who have been diagnosed with type 2 diabetes, as well as from a healthy control group (HC) consisting of 51 healthy subjects with a mean age of 57.8 ± 13.7 years. Therein, the concentration of leptin in the DM2 patients was significantly higher than in the HC (p < 0.01), with median value of 16.59 (IQR 8.58-33.39) ng/ml in the DM2, vs median value of 6.66 (IQR 4.52-21.40) ng/ml in the HC. In the analysis of variance, higher leptin concentrations were revealed in the DM2 group as compared to the HC, and this figure remained significant after adjusting for gender and age (p < 0.001). Moreover, it was independent of HOMA-IR (p = 0.003). However, the differences in leptin levels between the groups disappeared when additional adjustments for anthropometric parameters (BMI, waist circumference) were applied (p = 0.088). Beyond the aforementioned, significant positive correlations were found in the DM 2 group between leptin level and CRP (r=0.256; p < 0.05) and IL-6 (r = 0.345; p < 0.01). Among the selected variables, only gender and BMI were included in the predictive model explaining the variability of leptin, and, in total, were responsible for 72.6% of the original variation of the studied adipocytokine. The results of this study have led to conclusion that leptin may participate in the complex pathogenesis of DM2 and be a predictor of the development of this disease. As higher concentrations of leptin coexist with obesity, and this situation correlates positively with markers of inflammation (CRP, IL-6), leptin level, hence, should be considered in the pathogenesis of DM2.
The Finance-Growth Nexus in the Context of Financial Structure

Over recent decades, stock markets across the globe have developed tremendously taking a major role, similar to banks’ role, in financing firms. This persuaded economists to return with the old debate initiated by Goldsmith (1969) regarding financial structure. The bank-based system advocates favor the role of banks and criticize the role of markets in carrying out the financial growth-enhancing functions, whereas the market-based system proponents favor the role of markets and criticize the role of banks. On the other hand, proponents of the financial services and legal views are skeptical about the whole structure debate. Whether the market bank - based debate is genuine or myth; is a controversial question that should assist governments - especially with underdeveloped financial systems - to direct their financial development policies. This study has attempted to explore the finance-growth nexus in the context of the different financial structure hypotheses. Using pooled data from 65 developed and developing countries over the period 1988-2007 and employing graphical, correlation, and OLS regression analyses, the results support the market-based view over the bank-based and financial services views. Furthermore, by dividing the main sample according to the legal origins, evidence supporting the legal view and the relevancy of market-based systems in better legal environments has been found.
Preparation, Physicochemical and Antioxidant Properties of Acid- and Pepsin-Soluble Collagens from the Swim Bladders of Miiuy Croaker (Miichthys miiuy)

Collagen is one of the most useful biomaterials and widely applied in functional food and cosmetics. However, some consumers have paid close attention to the safety of mammalian collagens because of the outbreaks of bovine spongiform encephalopathy (BSE), foot-and-mouth disease (FMD), and other prion diseases. Therefore, there is a strong demand for developing alternative sources of collagen, with one promising source being from the process by-products of commercial fisheries. In this report, acid-soluble collagen (ASC-SB) and pepsin-soluble collagen (PSC-SB) from swim bladders of miiuy croaker (Miichthys miiuy) were isolated with yields of 1.33 ± 0.11% and 8.37 ± 0.24% of dry swim bladder weight. Glycine was the major amino acid present, with a content of 320.5 (ASC-SB) and 333.6 residues/1000 residues (PSC-SB). ASC-SB and PSC-SB had much lower denaturation temperatures compared to mammalian collagen, a consequence of low imino acid contents (196.7 and 199.5 residues/1000 residues for ASC-SB and PSC-SB, respectively). The data of amino acid composition, SDS-PAGE pattern, UV and FTIR spectra confirmed that ASC-SB and PSC-SB were mainly composed of type I collagen. FTIR spectra data indicated there were more hydrogen bonding and intermolecular crosslinks in ASC-SB. These collagens showed high solubility in the acidic pH ranges and low NaCl concentrations (less than 2%). The Zeta potential values of ASC-SB and PSC-SB were 6.74 and 6.85, respectively. ASC-SB and PSC-SB presented irregular, dense, sheet-like films linked by random-coiled filaments under scanning electron microscopy. In addition, ASC-SB and PSC-SB could scavenge DPPH radical, hydroxyl radical, superoxide anion radical, and ABTS radical in a dose-dependent manner. Overall, the results indicate that collagens from the swim bladders of miiuy croaker are a viable substitute for mammalian collagen, with potential functional food and cosmeceutical applications.
Prevalence of metabolic syndrome and its determinants in older Mexican non-diabetic adults.

INTRODUCTION the prevalence of metabolic syndrome (MetS) is high in older people, and several factors have been explored as main determinants. However, few data exist for older people from low- and middle-income countries. Therefore, our objective was to estimate the prevalence of MetS. Secondly, to explore which of the cardio-metabolic, body composition, inflammatory and demographic risk factors were associated with the prevalence of MetS in a population of older Mexican adults. METHODS data for this analysis were collected in subjects over 60 years of age from northwest Mexico. Fasting and two-hour glucose, fasting insulin, homeostasis model assessment of insulin resistance, lipid profiles, markers of adiposity and inflammation, and blood pressure were assessed. In addition, anthropometry and body composition data, levels of physical activity and demographic variables were also considered. MetS was diagnosed by three different criteria. RESULTS: total sample size was 369 subjects. The prevalence of MetS varied widely, from 36% to 52% depending on the criteria applied, but regardless of the criteria, all subjects with MetS were heavier and more overweight, and had higher triglyceride values and lower values of total HDL-cholesterol compared to those without MetS (p < 0.0001). Final models adjusted for age showed that, regardless of the diagnostic criteria applied, fat mass, the homeostasis model assessment and some demographic variables were main determinants of MetS in this sample of older people without diabetes. CONCLUSIONS the prevalence of MetS is relatively high in non-diabetic older adults and it was associated with some biological and demographic factors as the main determinats.
Towards Tonality Detection in Unseen Languages

With half of all spoken languages worldwide in danger of becoming extinct at the end of the century, language preservation is an important challenge that could benefit from machine assistance due to its complexity and current dependency on manual linguistic work. For tonal languages, defining and classifying different tones is a central part of this process, and considering the high number of tonal languages worldwide, a tone recognition system could play an important role in supporting linguists, as well as assisting the development of speech recognition technology. However, previous work on tone recognition was largely developed for the languagespecific context of the speech recognition task. This thesis investigates different approaches to the tone recognition task, with the aim of working towards the long-term goal of developing a universally applicable tone classifier. Using diverse Cantonese speech data, a variety of classifiers are applied to the framewise tone recognition task, indicating that recurrent neural networks, specifically long short-term memory models, are best suited to the challenge. Experiments with numerous network parameters and features lead to a frame error rate of 63.47% for the best-performing system, which is well above chance performance considering classification is conducted across 7 classes. Additionally, the syllable-wise recognition of tone is performed for several neural networks and k-nearest neighbors classifiers, leading to a syllable-error rate of 64.82% for the best-ranking k-nearest neighbor model.
A Practical Study on Feature Selection Methods in Pattern Recognition: Examples of Handwritten Digits and Printed Musical Notation

In the article we present a practical study on methods for numerical feature selection. We compare quality of classification models built on different sets of features. In particular, we consider the problem of handwritten digits recognition and printed musical notation recognition. We apply a suite of index-based and wrapper methods for feature selection. Experiments show that both on regular data set of handwritten digits and on imbalanced data set of printed musical notation we can easily find a subset of more or less 20 features that will assure a highly accurate classification model.
Effects of Expanding Envelope Fluctuations on Consonant Perception in Hearing-Impaired Listeners

This study examined the perceptual consequences of three speech enhancement schemes based on multiband nonlinear expansion of temporal envelope fluctuations between 10 and 20 Hz: (a) “idealized” envelope expansion of the speech before the addition of stationary background noise, (b) envelope expansion of the noisy speech, and (c) envelope expansion of only those time-frequency segments of the noisy speech that exhibited signal-to-noise ratios (SNRs) above −10 dB. Linear processing was considered as a reference condition. The performance was evaluated by measuring consonant recognition and consonant confusions in normal-hearing and hearing-impaired listeners using consonant-vowel nonsense syllables presented in background noise. Envelope expansion of the noisy speech showed no significant effect on the overall consonant recognition performance relative to linear processing. In contrast, SNR-based envelope expansion of the noisy speech improved the overall consonant recognition performance equivalent to a 1- to 2-dB improvement in SNR, mainly by improving the recognition of some of the stop consonants. The effect of the SNR-based envelope expansion was similar to the effect of envelope-expanding the clean speech before the addition of noise.
Communities in transition: changing views on tourism development as a vehicle for economic diversification in Northern Ontario, Canada.

In recent years, an increasing number of protected areas have been established as an attempt to preserve the biodiversity of coastal and terrestrial ecosystems. In Canada, government agencies have set a goal to increase the number of protected areas by establishing more national/provincial parks, marine protected areas (MPAs), national wildlife areas, marine wildlife areas, and migratory bird sanctuaries. Many of these protected areas are being created in rural areas where there is a heavy dependence on natural resources for survival. Recently in Ontario the first National Marine Conservation Area (NMCA) was established on the North Shore of Lake Superior. Due to recent global changes that have affected the resource-based economy in Canada, many rural communities have turned to developing their tourism attributes to diversify their economy. The purpose of this case study is to examine how community stakeholders‘ views toward tourism have changed over the course of the development of the Lake Superior National Marine Conservation Area (LSNMCA). Findings indicated that since the LSNMCA initiative was first introduced, local attitudes have positively changed toward the potential of tourism development in the area; such shifts coincide with the decline and restructuring of the region‘s resource-based industries. Keywords: protected areas, tourism, rural and resource-based communities, Lake Superior National Marine Conservation Area (LSNMCA)
Time-frequency techniques for modal parameters identification of civil structures from acquired dynamic signals

A major trust of modal parameters identification (MPI) research in recent years has been based on using artificial and natural vibrations sources because vibration measurements can reflect the true dynamic behavior of a structure while analytical prediction methods, such as finite element models, are less accurate due to the numerous structural idealizations and uncertainties involved in the simulations. This paper presents a state-of-the-art review of the time-frequency techniques for modal parameters identification of civil structures from acquired dynamic signals as well as the factors that affect the estimation accuracy. Further, the latest signal processing techniques proposed since 2012 are also reviewed. These algorithms are worth being researched for MPI of large real-life structures because they provide good time-frequency resolution and noise-immunity.
Inspection of Multilingual Neural Machine Translation

: In this thesis we explore the ability of the multilingual attention-based encoder-decoder NMT system proposed by Ha et al. (2016) to produce a language independent representation for the sentence it translates. NMT systems are trained to produce translations using large amounts of training data in the form of bilingual texts, the so called parallel corpora. However, for most language pairs high quality training resources are often too scarce in order to sufﬁciently train an NMT system. The ability to abstract from individual languages by using a shared representation across all languages would alleviate the need for large parallel corpora for every individual language pair. Having put forward the hypothesis, that with better abstraction ability of the NMT system the hidden representation of the sentence becomes more independent of the language pair that was involved in its generation, we have explored this independence by measuring the degree of correlation between the hidden representation and the language pair. Of the various hidden representations in the translation system we have chosen to examine the so called context vectors . In order to measure this correlation, we have built classiﬁers based on feed-forward neural networks which, given a context vector, attempt to predict the language pair involved in its generation. Having trained multiple multilingual NMT systems with 5 languages on the source side as well as the target side, we have trained single layer perceptrons to classify the context vectors produced by these systems. Those classiﬁers have achieved rates of correct classiﬁcation of up to 95.75% for 25 possible classes, which indicates that our NMT system does not successfully abstract from the languages involved in the translation. Furthermore, having explored the underlying cause of success in classiﬁcation, we have found present a linear relation in Euclidean space between context vectors of different languages. More precisely, for a pair of languages ( A , B ) we have found a vector b AB , such that for a context vector c with A as its source language, c + b AB is classiﬁed as having B as the source language in 90.9% of the cases. We have found this translation for the source language to be independent of the target language. In conclusion, despite the sentence representation in our NMT systems not being independent of the individual languages, for this representation we have found it to be surprisingly easy to transform the features representing
Novel Approach for Automatic Region of Interest and Seed Point Detection in CT Images based on Temporal and Spatial Data

: Accurately ﬁnding the region of interest is a very vital step for segmenting organs in medical image processing. We propose a novel approach of automatically identifying region of interest in Computed Tomography Image (CT) images based on temporal and spatial data . Our method is a 3 stages approach, 1) We extract organ features from the CT images by adopting the Hounsﬁeld ﬁlter. 2) We use these ﬁltered features and introduce our novel approach of selecting observable feature candidates by calculating contours’ area and automatically detect a seed point. 3) We use a novel approach to track the growing region changes across the CT image sequence in detecting region of interest, given a seed point as our input. We used quantitative and qualitative analysis to measure the accuracy against the given ground truth and our results presented a better performance than other generic approaches for automatic region of interest detection of organs in abdominal CT images. With the results presented in this research work, our proposed novel sequence approach method has been proven to be superior in terms of accuracy, automation and robustness.
Strength training in seniors: The knowledge of positive aspects of eccentric training in elderly is sparse

Eccentric (lengthening) resistance training respectively muscle work requires a lower share of cardiac activity in comparison to concentric (shortening) muscle work. Especially in seniors suffering from cardiovascular diseases (still the most common cause of death in industrialized countries) this kind of activity is predisposed due to its possibility of high stimulation of musculoskeletal system only partly (20-25%) stimulating cardiovascular system. Comprehension of positive aspects was addressed for a sample of people doing regular work out while having access to concentric and eccentric training stations. 38 females (57 ± 15.7 years / 163.3 ± 19.4 cm / 63.6 ± 10.4 kg) and 36 males (57.6 ± 16.9 years / 177.4 ± 6.9 cm / 80.6 ± 8.7 kg) visiting at least once a week a fitness mall with access to eccentric and concentric training stations were asked concerning cardiovascular diseases, their corresponding risk factors and their own experience with eccentric muscle training. Differences in the perception of eccentric muscle training compared to concentric training were reported by 18 women and 24 men, however reported Rates of perceived Exertion measured by BORG-Scale (6-20) did not significantly differ. A positive Bias that especially persons with cardiovascular illnesses respectively risk factors preferred this kind of activity was not detectable and knowledge of positive aspects of eccentric training was sparse. General practitioners are encouraged to inform patients of the existence of positive aspects of eccentric muscle training and to motivate patients to absolve their training respectively.
Real-Time Sentiment Analysis in a Chat Application Deep

The world in recent years has seen a steady rise in the number of users who are getting connected to the Internet. With mobile technology becoming cheaper, affordable, and essential, the number of people who people who now own such devices is increasing which again is a reason more and more people are gaining access to the web. Internet nowadays is like a doorstep solution to almost every trivial problem that one might face. We, as the users of Internet resort to the web for many things such as looking through a product’s review before buying it, posting feedback about a brand/product so that others can refer to it, posting tweets on social media about a subject and so on. This led to emergence of Sentiment Analysis which is concerned with mining the sentiments in the opinions expressed on social media by people. Sentiment Analysis has been found useful and employed by lots of companies and is now a major area of research. Lots of emphasis has been placed on the applications of Sentiment Analysis and how it can be leveraged into decision making. However not much work has been done in the past pertaining to Real-time sentiment analysis and its applications. In this project we have attempted to detect user’s mood by employing Sentiment Analysis. In this report, we will go through the entire process of how we performed real-time sentiment analysis in a chat application by detecting user’s mood based on his/her messages.