Miracle-dz/UniFAR-FTUs huggingface dataset:
Weakly supervised sentiment analysis and opinion extraction

In recent years, online reviews have become the foremost medium for users to express their satisfaction, or lack thereof, about products and services. The proliferation of user-generated reviews, combined with the rapid growth of e-commerce, results in vast amounts of opinionated text becoming available to consumers, manufacturers, and researchers alike. This has fuelled an increased focus on automated methods that attempt to discover, analyze, and distill opinions found in text. This thesis tackles the tasks of fine-grained sentiment analysis and aspect extraction, and presents a unified framework for the summarization of opinions from multiple user reviews. Two core concepts form the basis of our methodology. Firstly, the use of neural networks, whose ability to learn continuous feature representations from data, without recourse to preprocessing tools or linguistic annotations, has advanced the state-of-the-art of numerous Natural Language Processing tasks. Secondly, our belief that opinion mining systems applied to real-life applications cannot rely on expensive human annotations and should mostly take advantage of freely available review data. Specifically, the main contributions of this thesis are: (i) The creation of OPOSUM, a new Opinion Summarization corpus which contains over one million reviews from multiple domains. To test our methods, we annotated a subset of the data with finegrained sentiment and aspect labels, as well as extractive gold-standard opinion summaries. (ii) The development of two weakly-supervised hierarchical neural models for the detection and extraction of sentiment-heavy expressions in reviews. Our first model composes segment representations hierarchically and uses an attention mechanism to differentiate between opinions and neutral statements. Our second model is based on Multiple Instance Learning (MIL), and can detect user opinions of potentially opposing polarity. Experiments demonstrate significant benefits from our MIL-based architecture. (iii) The introduction of a neural model for aspect extraction, which requires minimal human involvement. Our proposed formulation uses aspect keywords to help the model target specific aspects, and a multi-tasking objective to further improve its accuracy. (iv) A unified summarization framework which combines our sentiment and aspect detection methods, while taking redundancy into account to produce useful opinion summaries from multiple reviews. Automatic evaluation, on our opinion summarization dataset, shows significant improvements over other summarization systems in terms of extraction accuracy and similarity to reference summaries. A large-scale judgement elicitation study indicates that our summaries are also preferred by human judges.
Resting-state fMRI: comparing default mode network connectivity between normal and low auditory working memory groups

The relationship between resting effective connectivity (EC) among default mode network (DMN) regions and auditory working memory (AWM) performance is still poorly understood. In this work, resting-state functional magnetic resonance imaging (rsfMRI) was used to determine the optimum connectivity model between posterior cingulate cortex (PCC) and medial prefrontal cortex (mPFC) in 40 healthy male volunteers. in low and normal working memory groups of subjects. Correlation between EC with AWM performance and AWM-capacity was also studied. The participants were divided into two groups which are normal and low AWM-capacity groups based on Malay Version Auditory Verbal Learning Test. The AWM performance was assessed using a word-based backward recall task. Both assessments were conducted outside the MRI scanner. The participants were scanned using a 3-T MRI system and the data were analyzed using statistical parametric mapping (SPM12) and spectral Dynamic Causal Modelling (spDCM). Results revealed that PCC and mPFC were significantly interconnected in both groups. Group analyses showed that the connection between PCC and mPFC exhibits an anti-correlated network. The results also indicated that the AWM performance and AWM-capacity were not associated with EC. These findings suggest that EC at rest between the two regions may not significantly influence cognitive abilities important for this AWM task.
Histological Study on the Effect of Hyaluronic Acid Injection (Dermal Filler) on the Skin of the Adult and Aged Albino Rat

Background: Injectable dermal fillers became more popular for improving skin contour defects such as wrinkles, lines, and depressed acne scars. Aim of the work: This work aimed to study different skin changes induced by dermal filler injection in adult and aged albino rat. Material and Methods: Forty five female albino rats were used. The animals were divided into three groups: Group I (Control): Included twenty adult rats. Group ІІ: Included fifteen adult rats, they received an injection of 0.1 ml of hyaluronic acid (HA). The animals were subdivided into three subgroups according to time of sacrification , five rats each: Subgroup IIa: after 7 days. Subgroup IIb: after 60 days. Subgroup IIc: after 90 days. Group ІІІ: Included ten aged rats, they were subdivided into two subgroups, five rats each: Subgroup IIIa: (Control aged group). Subgroup IIIb: the rats were given an injection of HA and were sacrificed after 30 days.Results:Thin skin of HA injected animals revealed significant (< 0.05) increase in the thickness of subcutaneous tissue (SC) and significant increase in collagen and elastic fibers, and significant increase in the CD34 positive endothelial cells as compared to control and aged rats. Active fibroblasts at the site of injection showing euchromatic nuclei. Their cytoplasm contained well developed rER, numerous mitochondria, many vesicles, and centrioles.Conclusion: Hyaluronic acid filler injection stimulated vascularization and enhanced fibroblasts to synthesize collgen and elastic fibers in SC. This protected the skin from aging features in adults,and play a role in improvement of skin defects in aged rats.
Child Human Capital – The Importance of Parenting Style

Investments in the human capital of children during their upbringing determine the opportunities available in adulthood. Recognizing that the parent-child interaction plays a significant role in the accumulation of child human capital, we develop a differential game in which the parent may invest directly in child human capital and the child consumes goods that influence the accumulation of their human capital. We compare the accumulation of child human capital between three different parenting styles, formalized as three different solution concepts to the differential game: (i) the parent and the child maximizes a joint utility function (cooperative solution), (ii) the parent announces a strategy dependent on time only (open-loop Stackelberg), (iii) the parent’s strategy depends on the accrued amount of human capital (feedback Stackelberg). We show that under rather general assumptions the open-loop Stackelberg equilibrium is time consistent, and coincides with a feedback Stackelberg equilibrium. Using cooperative parenting as a benchmark, we find that less or more child human capital may be accumulated over the family’s planning horizon under “open-loop Stackelberg” parenting, depending on parental and child preferences for human capital and wealth at the terminal time of the family’s planning horizon, and on the extent to which child consumption influences the accumulation of their human capital. In particular, if the child’s preference for terminal time wealth is strong enough, more human capital will be accumulated under “open-loop Stackelberg” parenting.
DETECTION OF CMV DNA IN INTRAOCULAR FLUID SAMPLES IN PATIENTS CLINICALLY DIAGNOSED WITH VIRAL UVEITIS BY MOLECULAR METHODS

Background: Latent Cytomegalovirus (CMV) infections may be reactive in consequence of immunosuppression. Recently, CMV-associated uveitis cases have also been reported in immunocompetent individuals. Aim: The aim of this study was to obtain epidemiological data by evaluating CMV DNA PCR results, clinical characteristics and risk factors of patients diagnosed with viral uveitis. Methods: Between the years 2011-2017, anterior chamber fluid samples of 35 patients with viral uveitis sent from the ophthalmology clinic to the Virology Laboratory were included in this study. CMV DNA real-time PCR results were evaluated. Results: CMV DNA positivity was detected in 9 (26%) of the 35 patients. CMV DNA positivity was highest (13%) in over 60 years (p=0.02). Acute recurrent uveitis in 44% (4/9) of patients, single eye involvement in 78% (7/9) and anterior uveitis in 44% (4/9) were found. Conclusion: In this study, CMV DNA positivity was detected in 26% of the patients with viral uveitis. Considering the presentations of a small number of cases related to CMV uveitis in our country, this study is important due to being the most comprehensive study in our country.
Osmotic fragility in essential hypertension revisited: A correlation with Iron status and lipid profile

Essential hypertension is a major public health associated with increased pressure on the vascular walls and red blood cells (RBCs). In the present work, osmotic fragility (OSF) of RBCs was reexamined in the measure of its correlation with two risk factors; iron status and lipid profile. OSF, iron status parameters, and lipid profile components were measured in eighty-eight patients and compared to the results of thirty controls. The results presented a significant increase in all iron indices of hypertensive patients compared to the normotensive group excluding transferrin concentrations and UIBC decreasing in these patients compared to the healthy group. Serum TGs, total cholesterol, VLDLc, and LDLc increased in patients as compared with control group. There is no significant change in OSF between patients and controls. The iron status parameters and LDLc and TG components were dependent on sex and smoking state. Hemoglobin and PCV were correlated significantly with total cholesterol and LDLc. Transferrin saturation showed a positive correlation with cholesterol, LDLc, and TGs, but negatively correlated with HDLc. No significant correlation between all the measured parameters and OSF in patients with HT. There is a significant correlation between serum ferritin and systolic BP and between Hb and systolic BP. Conclusion. Hypertension as a mechanical challenge for RBCs membrane has no significant effect on the OSF in hypertensive patients. Iron status parameters showed an elevation in HT patients as compared with controls. OSF has no significant correlation with iron status parameters or with lipid profile components in HT patients.
Private Equity Real Estate Funds: Returns, Risk Exposures, and Persistence

Using performance data through the fourth quarter of 2017 on 467 funds that came to market between 2000 and 2013, the authors of this article first examine the unconditional performance of closed-end, private equity real estate (PERE) funds over time and across various fund characteristics. The performance metrics they use are the internal rate of return, the multiple on invested capital, and a proxy for the public market equivalent. Using conditional sorts, as well as regression procedures with asset pricing specifications, the authors estimate the exposure of PERE performance to fund-level characteristics and macroeconomic environment risk factors and find that both significantly affect PERE performance. More specifically, they find that PERE performance is positively related to fund size, gross domestic product growth changes, private market real estate returns, interest rate changes, and default spread changes and is negatively related to vintage volume. International funds dramatically underperformed relative to domestic funds during the sample period. The authors also find that fund performance is positively associated with the performance of prior funds raised by the same PERE firm. TOPICS: Statistical methods, real estate, risk management, private equity Key Findings • Fund characteristics, market risks, and macroeconomic risk factors significantly predict PERE performance. • Fund performance is positively associated with the performance of prior funds raised by the same PERE sponsor. • Fund performance is negatively associated with vintage volume.
Color Atlas and Text of Dental Care of the Elderly

The changing populations of elderly people characteristics of older people medical problems in the elderly the ageing mouth the dental health of the elderly population periodontal care and prevention restoration of teeth conventional bridgework restoring the worn dentition the partially dentate patient - removable prosthodontics complete dentures implants oral medicine and pathology oral surgery considerations domiciliary visiting.
Detection of Pedestrian Actions Based on Deep Learning Approach

The pedestrian detection has attracted considerable attention from research due to its vast applicability in the field of autonomous vehicles. In the last decade, various investigations were made to find an optimal solution to detect the pedestrians, but less of them were focused on detecting and recognition the pedestrian's action. In this paper, we converge on both issues: pedestrian detection and pedestrian action recognize at the current detection time (T=0) based on the JAAD dataset, employing deep learning approaches. We propose a pedestrian detection component based on Faster R-CNN able to detect the pedestrian and also recognize if the pedestrian is crossing the street in the detecting time. The method is in contrast with the commonly pedestrian detection systems, which only discriminate between pedestrians and non-pedestrians among other road users.
Real‐time action feature extraction via fast PCA‐Flow

Action recognition is a research hotspot in the field of Internet of Things (IoT). Currently, local pixel‐domain spatiotemporal feature extraction methods have reached the state‐of‐the‐art action recognition performance on many challenging datasets. However, the poor computational complexity of these approaches prevents them from scaling up to real‐time applications. For solving this problem, we present a novel real‐time video feature extraction technique by exploiting the fast PCA‐Flow algorithm. Firstly, we down‐sample video images in form of grid. Based on the down‐sampling images, PCA‐Flow algorithm is used to calculate optical flow among adjacent images. The PCA‐Flow matrices are then expanded to the original video image size by using efficient gCLSR super‐resolution method to keep the inherent geometric structure of the optical flow. Finally, we compute action descriptors based on original pixel frames and the enlarged PCA‐Flow images. The proposed approach is validated on three challenging datasets: UCF50, Hollywood2, and HMDB51. Experimental results indicate that the proposed method is more efficient in computation and can achieve competitive quality than the state‐of‐the‐art methods.
Performance and Statistical Analysis of Chaotic Random Bit Generator

Medical Information transmitted through the internet and secured against any attacks is an international challenging fear. In the present scenario, a fabulous relation emerges between chaos and cryptography. Various features of chaotic systems such as initial state sensitivity, ergodicity, mixing properties and complexity in the structure produce deterministic pseudo randomness in the input data. Chaotic Random Bit Generator (CRBG) makes the bit sequence unpredictable by an intruder, in the field of medical research. In current years, mixture of chaos-based cryptosystems have been projected. To be used in medical field, a CRBG may require in meeting stronger desires than for any other applications. Motivated by all these issues, a novel chaotic random bit generator is proposed based on two different chaotic based logistic maps in parallel and with preliminary self-determining initial conditions. The random bit sequence which is chaotic in character is created by predicting the outputs of both the chaotic logistic maps. Also it is projected to put forward dissimilar tests by stressing some of its alluring arithmetic features, which make it an ideal preference for the expected random bit generation. Lastly, the results of all the statistical tests generated bit sequences, is tested under all the most powerful NIST suit tests for the prediction of randomness: The tests validate the exact expected uniqueness expected of real random sequences.
YÜKSEK ÖĞRETİM VE KALİTE YÖNETİMİ: GELİŞMEKTE OLAN ÜLKE BAĞLAMINDA BİR ARAŞTIRMA - TERTIARY EDUCATION AND MANAGEMENT OF QUALITY: A RESEARCH IN A DEVELOPING COUNTRY CONTEXT

Yuksek ogretim, ulusal duzeyde ekonomik buyumenin en onemli adimlarindan biri olarak kabul edilir. Bununla birlikte, literaturde hem cok kapsamli bir veri setine sahip hem de gelismekte olan ulkeler baglamina dayanan yuksek ogretim kurumlarinin kalite seviyesini artirmaya yonelik cabalar uzerine bilindigi kadariyla cok az arastirma yapilmistir. Calisma bu nedenle Turkiye yuksek ogretim kurumlarinda kalite yonetimi cabalarinin mevcut durumunu incelemeyi amaclamaktadir. Calismada veriler 149 Turk universitesinin 672 unitesinden toplanmistir. Bulgulara gore katilimci kuruluslarin yarisindan fazlasinda herhangi bir kalite yonetimi sertifikasi bulunmamakta veya herhangi bir Kalite yonetimi sertifikasi alma cabasi gostermemektedirler. Bulgularin sonuclarina gore, bazi onemli gelismelere ragmen, kalite calismalarin Turkiye yuksek ogretim kurumlarini tam anlamiyla kapsamasi icin henuz cok uzun ve zor bir yolunun oldugunu gostermistir.
Wilcoxon Analysis to Compare the Open Unemployment Rate Before and After the Implementation of ASEAN Economic Community (EAC) In Indonesia

The implementation of the EAC should be seen positively since it opens the opportunities for job seekers in Indonesia to have a career abroad. With varied employment opportunities, it is expected that the open unemployment rate in Indonesia will decline. The purpose of this study is to compare the level of open unemployment rate in Indonesia before and after the implementation of the ASEAN Economic Community (EAC) using Wilcoxon Analysis. This research is quantitative. Wilcoxon analysis is used to compare the open unemployment rate in Indonesia before and after the EAC is implemented. The result shows that there is no significant difference between the average open unemployment rate before and after the implementation of EAC.
Estimation of a censored food demand system and nutrient elasticities: a cross-sectional analysis of Sri Lanka

A nutritional transition is occurring in Sri Lanka, which steers people away from nutrient-rich diets, contributing to diet-related disease and poor economic performance. This study examines demographic impacts on consumption of major food commodities and estimates price and expenditure elasticities for major food groups and nutrients. Data from the Sri Lankan Department of Census and Statistics Household Income and Expenditure survey are used to estimate price and expenditure elasticities for food commodities and nutrients using the Quadratic Almost Ideal Demand System (QUAIDS). The zero-expenditure problem is circumvented by employing a Tobit model. Results demonstrate the impact of price and income changes on dietary intake of households, and income and nutrition policy recommendations are presented.
Fog-Computing-Based Energy Storage in Smart Grid: A Cut-Off Priority Queuing Model for Plug-In Electrified Vehicle Charging

Electric vehicles (EVs) are likely to become very popular within the next few years. With possibly millions of such vehicles operating across the smart cities, smart grid energy providers can be directly impacted by the charging of EV batteries. In order to reduce this impact and optimize energy saving, in this article, we propose a coordinated model for scheduling the plug-in of EVs for charging and discharging energy. The model is based on a new decentralized Fog architecture for smart grid in order to reduce the completion and communication delay of EV energy demand scheduling. To enhance the scheduling of EV demands and predict the future energy flows, we propose a plug-in system of EVs based on calendar planning. We develop a mathematical formalism based on Markov chains using a multipriority queuing theory with cut-off discipline in order to reduce the waiting time to plug-in. We implement three planning algorithms in order to assign priority levels and then optimize the plug-in time into each EV public supply station. To the best of our knowledge, this is the first article that proposes a model that tries to save energy by planning the plug-in of EVs using a cut-off priority queuing model and a decentralized Fog architecture. We evaluate the performances of our solution via extensive simulations using a realistic energy loads from the city of Toronto, and we compare it with other recent works.
Depression in Diabetic and Non-Diabetic Individuals: Physical Activity, Nutrition, and Diet

About 8.3% of individuals diagnosed with diabetes mellitus (DM) are diagnosed with comorbid depression, a higher rate than the general adult population. This project examined the differences of depression symptoms experienced between diabetic and matched non-diabetic individuals and the relationship of daily activity and nutrition behaviors with depression between these groups. The 2005-2006 National Health and Nutrition Examination Survey (NHANES) was utilized to assess: depression symptoms, diabetic glycemic control as measured by glycoginated hemoglobin (HbA1c), amount of physical activity, percentage of macronutrients, daily frequencies of foods consumed, and the use of nutritional food labels to make food choices. A sample of diabetic (n = 451) and non-diabetic individuals (n = 451) were matched to on age, gender, ethnicity, and education. The diabetic individuals experienced greater depression on both continuous and ordinal diagnostic variables. Counter to expectation, there was no relationship observed between depression and HbA1c in diabetic individuals, r = . 04, p > . 05.