Miracle-dz/UniFAR-FTUs huggingface dataset:
The association of food consumption and nutrient intake with endometriosis risk in Iranian women: A case-control study

Abstract Background Endometriosis, defined as the attendance of endometrial-like lesions in extra uterine locations, causes pain, infertility, and reduced quality of life. Objective To evaluate the relationship between food consumption and nutrient intake with risk of endometriosis. Materials and Methods Of the 156 women approached for the study, 78 women had endometriosis and 78 healthy women were included in the control group. Dietary data were collected using a validated 147-item semi-quantitative Food Frequency Questionnaire (FFQ) with the standard serving size. A logistic regression model was used to determine the association of macronutrients and energy intake with the risk of endometriosis. Results In women with higher intake of protein, especially animal protein, monounsaturated fatty acids, soluble and insoluble fiber, oleic acid, eicosapentaenoic acid, and docosahexaenoic acid endometriosis is less common (p< 0.05). High consumption of vegetables, fruits, red meat, yellow vegetables, potatoes, legumes, dairy products, liquid oil, and low intake of fried potatoes was associated with a lower risk of endometriosis (p< 0.05). Conclusion Regarding the association of dietary intake on endometriosis risk, counseling about improving the dietary structure can contribute toward the prevention and control of endometriosis.
Determination of Factors that Impact Adherence to Warfarin in Patients with Stroke

Objective: Oral anticoagulants are the mainstay in the secondary prevention of stroke. Adherence to drug is an important issue in preventing stroke. The aim of this study was to determine the adherence of patients with stroke to warfarin (anticoagulant agent) and to investigate the factors that may impact adherence. Materials and Methods: This descriptive cross-sectional study was conducted on patients admitted to an outpatient neurology clinic of a tertiary hospital in Istanbul. A total of 99 patients with stroke who were under warfarin treatment for at least 6 months prior to the study were enrolled in the study. Patients were assessed in terms of sociodemographic characteristics, adherence to and knowledge regarding the drug, anxiety and depression, mental and functional state and quality of life using validated scales. Results: The mean adherence score of the patients was 3.3±1.1 (0-4). The reported adherence rates were not considered as low in our sample given that 42% had poor knowledge. Significant negative correlations were determined between drug adherence and age, number of risk factors, and duration of anticoagulant use (r=0.39, r=-0.33, r=-0.52, p<0.001, respectively). The mean drug adherence scores were lower in patients who had experienced drug-related adverse effects compared with those that did not (p=0.018). Significant correlations were found between the adherence scale and all other variables (p<0.05). Multiple linear regression analysis revealed that drug adherence was predicted by experiencing adverse effects, knowledge regarding the drug, and depression. Conclusion: Knowledge regarding the use of warfarin was inadequate in our patients, whereas adherence was reported not to be inadequate. The most influential factors that may impact adherence were adverse effects, knowledge, and depression. Healthcare professionals should be aware of patients who have risk factors for non-adherence.
Culinary Recipe Recommendation based on Text Analytics

Many researchers and practitioners have studied the recipe recommendation, and that problem is not only to find the tasty dishes based on the individual’s preference, but also to generate new ones. In the digital age, understanding and utilizing text data is one of the most important part in the knowledge discovery. In this paper, we proposed how to use text analysis in the recipe recommendation problem and provided the insights to design new recipes.
High‐Dose Oral Garlic is Associated with a Decrease in Intrapulmonary Shunting in Severe Hepatopulmonary Syndrome

Hepatopulmonary syndrome (HPS) is characterized by pathological vasodilation of the pulmonary vasculature that results in an arterial oxygenation defect in patients with liver disease. These intrapulmonary vasodilations are mediated by vasoactive molecules, such as endothelin-1 and nitric oxide. The result is both ventilation-perfusion mismatch and impaired oxygen diffusion, causing a “shunt” of poorly oxygenated blood to the systemic circulation. Clinically, this causes dyspnea and hypoxia, particularly when standing, known as platypnea and orthodeoxia. The diagnosis of HPS is made by demonstrating that the patient with liver disease has a partial pressure of arterial oxygen (PaO2) <80 mm Hg or an A-a gradient >15 mm Hg, as well as an intrapulmonary shunt on a transthoracic contrast-enhanced echocardiogram (TTCE). HPS severity is classified according to the degree of hypoxemia, and the contribution of HPS-induced hypoxemia can be quantified on technetium-9 mm macroaggregated albumin (MAA) scanning. (1) In this scan, labeled biodegradable particles are delivered intravenously and normally become trapped in lung capillaries. However, in HPS they bypass the lungs and become detectable in other organs, such as the brain. Ultimately, patients with HPS have increased mortality from liver disease, and prognosis worsens with increasing severity. Currently, the only cure is liver transplantation. Supplemental oxygen can be used to palliate symptoms. While medical therapies remain limited, there are some data to support the use of oral garlic supplementation. (2,3) In a randomized placebo-controlled trial, patients with HPS who received high-dose garlic (1-2 mg/m2) had a greater increase in PaO2 (24.66% vs. 7.37%; P < 00.1). (3) We are writing to describe the use of high-dose oral garlic in a patient with newly diagnosed severe HPS undergoing assessment for liver transplantation. This 67-year-old woman had Child-Pugh-B7 cirrhosis secondary to nonalcoholic steatohepatitis and presented with dyspnea. She had marked orthodeoxia on room air (PaO2, 97 mm Hg lying and 42 mm Hg standing) and an intrapulmonary shunt on TTCE, quantified to be 38% on MAA scanning (normal <6%). She opted to try Kyolic Aged Garlic Extract 2 g daily, based on its positive trial. (3) After three weeks, her dyspnea had decreased and her only adverse reaction was mild halitosis. Her arterial blood gases (Table 1) showed an increase in oxygenation not attributable to hyperventilation. She underwent MAA scanning to reassess her intrapulmonary shunt (Fig. 1), which had decreased to 32.5% (relative reduction, 14.5%; absolute reduction, 5.5%). She was subsequently waitlisted for transplantation and discharged on home oxygen. This is the first case quantifying the reduction in intrapulmonary shunting associated with high-dose garlic for HPS.
A Survey on Blockchain-Based Identity Management Systems for the Internet of Things

The Internet of Things aims at connecting everything ranging from individuals, organizations, companies to things in the physical and virtual world. The digital identity has always been considered as the keystone for all online services and the foundation for building security mechanisms such as authentication and authorization. However, current literature still lacks of a comprehensive research on the digital identity management for the Internet of Things (IoT). In this paper, we identify digital identity challenges and solutions for the Internet in general. We then focus on how existing solutions cope with IoT requirements such as scalability, interoperability, mobility, security and privacy. We also investigate recent surging blockchain sovereign identity solutions and enumerate some projects and startups which are focusing on IoT identity problems. Furthermore, we elaborate challenges of building identity management systems for the IoT, including access control, privacy preserving, trust and performance respectively. At last, we conclude with the promising future research trends in building IoT identity management systems.
LOW RESOLUTION CONVOLUTIONAL NEURAL NETWORK FOR AUTOMATIC TARGET RECOGNITION

In this work, we present an extended study of image representations for automatic target recognition (ATR). More specifically , we tackle the issue of the image resolution influence on the classification performances, an understudied yet major parameter in image classification. Besides, we propose a parallel between low-resolution image recognition and image classification in a fine-grained context. Indeed, in these two particular cases, the main difficulty is to discriminate small details on very similar objects. In this paper, we evaluate Fisher Vectors and deep representations on two significant publicly available fine-grained oriented datasets with respect to the input image resolution. We also introduce LR-CNN, a deep structure designed for classification of low-resolution images with strong semantic content. This net provides rich compact features and outperforms both pre-trained deep features and Fisher Vectors. We also present visual results of our LR-CNN on Thales near-infrared images.
Epidemiology of Congenital Heart Defects in Iran: A Systematic Review

Background: Congenital heart diseases (CHDs) accounts for more than 30% of all major congenital anomalies worldwide. Regional factors play an important role in the prevalence and incidence of CHDs. The aim of this systematic review was to summarize the incidence and prevalence of CHDs in Iran Data sources: Medline, EMBASE, Web of Sciences, CINHAL, Google Scholar and PubMed, as well as the Persian (language) databases, plus references listed from relevant articles have been searched to address the research question. Eligibility criteria: Either original studies or reviews/meta-analysis reporting the prevalence or/and incidence of CHDs among live births in Iran, in which diagnosis of CHD had been based on, at least, physical examination and echocardiography for diagnosing CHDs. Study appraisal: In this systematic review registered to PROSPERO, the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies was used to appraise the quality of related studies, and the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol (PRISMA) was followed for reporting the results. Result: Among 69 identified publications in English and Farsi, without time restrictions, only 4 studies were eligible to be included in the review. Totally, 114523 live births registered in the referral hospitals, for childbirth in Iran, had been examined for CHDs in which vary prevalence for CHDs were reported from 4 per 1000 in the North East to 8 per 1000 in the Northwest of the country. Conclusions: high prevalent CHDs in Iran underscore the importance of culturally appropriate prevention and management strategies. Also, a wide range of CHD prevalence in different areas, in Iran, suggests epidemiological investigations, preferably a population-based study with adequate sample size or a study compromised all birth setting.
A novel energy efficient virtual machine configuration and migration technique

The recent growth in the data centre usage and the higher cost of managing virtual machines clearly demands focused research in reducing the cost of managing and migrating virtual machines. The cost of virtual machine management majorly includes the energy cost, thus the best available virtual machine management and migration techniques must have the lowest energy consumption. The management of virtual machine is solely dependent on the number of applications running on that virtual machine, where there is a very little scope for researchers to improve the energy. The second parameter is migration in order to balance the load, where a number of researches are been carried out to reduce the energy consumption. This work addresses the issue of energy consumption during virtual machine migration and proposes a novel virtual machine migration technique with improvement of energy consumption. The novel algorithm is been proposed in two enhancements as VM selection and VM migration, which demonstrates over 47% reduction in energy consumption.
External validation of prostate health index-based nomogram for predicting prostate cancer at extended biopsy

Introduction/Objective. Prostate Health Index (PHI)-based nomograms were created by Lughezzani et al. (2012) and Zhu et al. (2015) for predicting prostate cancer (PCa) at extended biopsy. The aim of the study was to externally validate two nomograms in the Serbian population. Methods. This retrospective study comprised 71 patients irrespective of digital rectal examination (DRE) findings, with prostate-specific antigen level < 10 ng/ml, who had undergone prostate biopsies, and PHI testing. Data were collected in accordance with previous nomograms predictors. Independent predictors were identified by using logistic regression. The predictive accuracy was measured by the area under the receiver operating characteristic curve (AUC). The calibration belt was used to assess model calibration. The clinical utility was measured by using decision curve analysis (DCA). Results. There were numerous differences in underlying risk factors between validation dataset and previously available data. Analysis demonstrated that the DRE and PHI were independent predictors. AUCs for both nomograms, in patients with normal DRE had shown to have a good discriminatory ability (77.2? 86.2%). In the entire population AUC of nomogram had exceptional discrimination (92.9%). Zhu et al. nomogram is associated with lower false positive predictions. The calibration belt for Zhu et al. nomogram was acceptable. Our DCA suggested that both nomograms are likely to be clinically useful. Conclusion. We performed external validation of two PHI-based nomograms predicting the presence of PCa in both the initial and the repeat biopsy setting. The PHI-based nomograms displayed adequate accuracy and justifies its use in Serbian patients.
Studying and Assisting the Practice of Java and C# Exception Handling

Programming languages provide features that handle exceptions. These features separate error-handling from regular code and aim to assist software maintenance. Nevertheless, their misuse can cause reliability degradation or even catastrophic failures. Prior studies on exception handling aim to understand the practices of exception handling and their anti-patterns. However, little knowledge was shared about the prevalence of these anti-patterns, nor the relationship between exception handling practices and software quality. In this thesis, I, first, study the exception handling features by enriching the knowledge of handling code with a flow analysis of exceptions. Second, I investigate the prevalence of exception handling anti-patterns. Finally, I investigate the relationship between software quality and: (i) flow characteristics and (ii) 17 handling anti-patterns. Our case study is conducted with over 10K handling blocks, and over 77K related flows from 16 Java and C# projects. I built statistical models of the chance of post-release defects using traditional software metrics and exception handling metrics. Our case study results show the complexity of exception handling. Moreover, I found that although exception handling anti-patterns widely exist in all of our subjects, only a few anti-patterns can be commonly identified. Finally, I conclude that exception flow characteristics in Java projects and some exception handling anti-patterns can provide significant explanatory power to the chance of post-release defects.
A comparison of cross- and single-layer retransmission optimisations for 802.11

Retransmissions in the 802.11 wireless LAN protocol often contain data that was successfully conveyed in the initial message, but is ignored due to corruption during transmission thereby reducing network efficiency. By compartmentalising data, and consequently the corrupted portions of the frame, into distinct sub-fragments 802.11 protocol performance can be further improved. Cross-layer designs provide opportunities to assist in accomplishing this improvement that may not otherwise present themselves in normal architectures using isolated layers. This thesis presents two new and novel schemes, one that is based on cross layer design and the other using the traditional single layer approach. Both schemes are based upon the same principle of compartmentalising corruption. Additionally, a comparison between the two schemes is provided in order to investigate the strengths and weaknesses of cross-layer design, while simultaneously presenting an 802.11 protocol with enhanced spectral efficiency. Both schemes divide layer 2 frames into small fragments separated by frame check sequences in order to facilitate retransmission of data that was corrupted during transmission, while avoiding resending correctly received data. They differ in the meta-data mechanisms relied upon to manage this process, and the layer in which retransmission decisions are made, but are fundamentally similar; permitting a unique opportunity for the informative comparison between crossand singlelayer designs. Moderate bandwidth increases were observed over standard 802.11n with both schemes at medium to high channel error rates, alongside situational decreases in latency. The cross-layer scheme performed slightly worse than the single-layer scheme, however it provided a significant opportunity for further optimisations that were not readily apparent in the single-layer scheme. Statement of Originality This work has not previously been submitted for a degree or diploma in any university. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made in the thesis itself.
Self-Medication with Antibiotics among University Students in LMIC: A systematic review and meta-analysis.

INTRODUCTION Self-medication with antibiotics (SMA) is common among university students in low and middle-income countries (LMICs). However, there has been no meta-analysis and systematic review in the population. METHODOLOGY A literature search was conducted using PubMed, Embase and Web of Science for the period from January 2000 to July 2018. Only observational studies that had SMA among university students from LMICs were included. A random-effects model was applied to calculate the pooled effect size with 95% confidence interval (CI) due to the expected heterogeneity (I2 over 50%). RESULTS The pooled prevalence of SMA of overall included studies was 46.0% (95% CI: 40.3% to 51.8%). Africa had the highest pooled prevalence of SMA among university students (55.30%), whereas South America had the lowest prevalence (38.3%). Among individual LMICs, the prevalence of SMA among university students varied from as low as 11.1% in Brazil to 90.7% in Congo. CONCLUSIONS The practice of SMA is a widespread phenomenon among university students in LMICs and is frequently associated with inappropriate use. Effective interventions such as medication education and stricter governmental regulation concerning antibiotic use and sale are required to be established in order to deal with SMA properly.
The ANTENATAL multicentre study to predict postnatal renal outcome in fetuses with posterior urethral valves: objectives and design

Abstract Background Posterior urethral valves (PUV) account for 17% of paediatric end-stage renal disease. A major issue in the management of PUV is prenatal prediction of postnatal renal function. Fetal ultrasound and fetal urine biochemistry are currently employed for this prediction, but clearly lack precision. We previously developed a fetal urine peptide signature that predicted in utero with high precision postnatal renal function in fetuses with PUV. We describe here the objectives and design of the prospective international multicentre ANTENATAL (multicentre validation of a fetal urine peptidome-based classifier to predict postnatal renal function in posterior urethral valves) study, set up to validate this fetal urine peptide signature. Methods Participants will be PUV pregnancies enrolled from 2017 to 2021 and followed up until 2023 in >30 European centres endorsed and supported by European reference networks for rare urological disorders (ERN eUROGEN) and rare kidney diseases (ERN ERKNet). The endpoint will be renal/patient survival at 2 years postnatally. Assuming α = 0.05, 1–β = 0.8 and a mean prevalence of severe renal outcome in PUV individuals of 0.35, 400 patients need to be enrolled to validate the previously reported sensitivity and specificity of the peptide signature. Results In this largest multicentre study of antenatally detected PUV, we anticipate bringing a novel tool to the clinic. Based on urinary peptides and potentially amended in the future with additional omics traits, this tool will be able to precisely quantify postnatal renal survival in PUV pregnancies. The main limitation of the employed approach is the need for specialized equipment. Conclusions Accurate risk assessment in the prenatal period should strongly improve the management of fetuses with PUV.
Performance and Emission Characteristics of a Miller Cycle Engine

In this study, intake and exhaust cams were designed to perform the late intake valve closing (LIVC) Miller cycle operation using spline functions in a single-cylinder, four-stroke, spark-ignition engine. A special camshaft was manufactured and adapted to the engine to adjust valve opening and closing timings. The experiments were conducted at two different LIVC timing and the results were compared with Otto cycle. The tests were conducted at 1700-3200 rpm engine speed range at wide open throttle (WOT). In the experiments, the variation of brake torque, power output, specific fuel consumption (SFC), thermal efficiency, HC, CO, NOx emissions and exhaust gas temperature versus engine speed were investigated. More power output was obtained with Otto cycle than Miller cycles for all engine speeds. Brake torque and engine power decreased by 5.24%, and 1.17% respectively with MA cycle (Miller cycle A) compared to Otto cycle at 2600 rpm engine speed. Thermal efficiency increased by 1.29%, while the SFC decreased 2.08 % with Otto cycle in comparison with MA cycle at maximum brake torque speed. HC and CO increased by 6.48 % and 11.66% respectively with MA cycle compared to Otto cycle at the same operation condition. NOx decreased up to 7.79% with MA cycle compared to Otto cycle due to the lower exhaust gas temperature at maximum brake torque speed of 2600 rpm.
INVESTIGATION OF METABOLOMICS TECHNIQUES BY ANALYSIS OF MS PROPOLIS DATA: WHICH PRE-TREATMENT METHOD IS BETTER?

Metabolomics data usually undergoes both pre-processing of the raw data and then further pre-treatment before any statistical analysis is carried out. Different pre-treatment methods emphasise various aspects of the data, and each method has advantages and disadvantages. The choice of pre-treatment method depends on the biological question of interest, characteristics of the data and the chosen data analysis. In this paper, we investigate the effects of different pre-treatment methods on four metabolomics data sets arising from chemical analysis of propolis samples collected from honey bee colonies in three different locations in Scotland, and also samples from Libya. Propolis has a variety of biological properties including anti-protozoal and anti-inflammatory effects. As a complex mixture, its biological activity depends on its exact composition, which can be investigated via metabolomic analysis. Two techniques of pre-treatment were applied, namely, transformation and scaling. The choice of method was found to greatly affect the results of the principal component analysis (PCA) used to explain the variation in the data. The results indicated that there was no notable (if any) improvement to be made by using any transformation techniques. It was also found for all four data sets that Pareto scaling, incorporating mean centring, performed better than the other scaling approaches considered here in terms of PCA, the analysis of interest, because the results explain more of the variation in the data.