Miracle-dz/UniFAR-FTUs huggingface dataset:
AB0078 Systemic and local il-17a and mir-223 levels in rheumatoid arthritis patients

Background IL-17 is a proinflammatory cytokine, which overproduction promotes the autoimmune reaction in rheumatoid arthritis (RA). Recent studies have shown that IL-17 production in lymphocytes or its function could be regulated by miR-223 by targeting Roquin ubiquitin ligase or its receptors1–4. Objectives To examine a possible correlation between the expression levels of miR-223 and IL-17A in peripheral blood (PB) and synovial fluid (SF) of RA patients. Methods Expression levels of miR-223 were determined in matched PB and SF samples of RA patients by relative quantitation method 2-ΔΔCt. As reference control for normalisation RNU6B gene was used. Concentrations of IL-17A in matched serum and SF samples were determined by Human IL-17A ELISA kit (Gene probe, Diaclone). The results were compared to healthy control (HCs) as well as within the RA group. Results 58,73% of the RA patients showed overexpression of miR-223 in PB when compared to HCs (p=0.008) with AUC=0.673 (95 CI: 0.562/0.784), with 71.4% sensitivity and 46.9% specificity (p=0.006). miR-223 was overexpressed in 79.17% of RA SF (p=1.64 × 10–3) when compared to HCs SF with AUC=0.841 (95 CI: 0.724/0.958) with 87.5% sensitivity and 72.7% specificity (p=4.6 × 10–4). Within the RA group, SF miR-223 was underexpressed in 58.7% of the patients compared to its systemic levels. Levels of IL-17A were higher in RA SF compared to serum (8.645 pg/ml versus 0.315 pg/ml, p=0.012). Conclusions The difference between the systemic and local levels of miR-223 and IL17A in RA patients shows that the inflammatory disease process leads to their altered expression with a possible role of both molecules in the disease pathogenesis. The opposite changes in their systemic and local levels confirm the data about the possible role of miR-223 in regulating IL-17 function. References [1] Haneklaus M, Gerlic M, O’Neill LA, Masters SL. miR-223: infection, inflammation and cancer. J Intern Med. 2013;274(3):215–226. [2] Khan D, Ansar Ahmed SA. Regulation of IL-17 in autoimmune diseases by transcriptional factors and microRNAs. Front Genet. 2015;6:236. [3] Moriya N, Shibasaki S, Karasaki M, Iwasaki T. The Impact of MicroRNA-223–3p on IL-17 Receptor D Expression in Synovial Cells. PLoS One2017;12(1):e0169702. [4] Schaefer J, Nakra N, Montufar-Solis D, Vigneswaran N, Klein J. Role for miR-223 and Roquin in IL-10 mediated regulation of IL-17. J Immunol2013;190(1 Supplement):171.9. Acknowledgements The study was supported by Grant 14D/2012 and Grant 61/2015 funded by Medical University-Sofia, Bulgaria Disclosure of Interest None declared
Computer Vision on a Parking Management and Vehicle Inventory System

Over time, scientists and engineers have developed technology that has improved everyday living. For every invention, they have found to reinvent it and create a better version of it. An example would be parking lots. From the usual time-in-time-out system; window cashier to parking spot back to window cashier, the hassle of this cycle was reduced through the use of license plate recognition which this study tackled. License plate identification technology has become a useful factor in different issues like parking management, vehicle owner recognition, etc. Computer vision has provided a means to reduce manual labor in parking lots by replacing them with sensors and scanners which would take over. This would be beneficial to the company as this technology would require minimal maintenance. Through image processing and enhancement, the license plates of these cars could be taken account of in real-time and this data could be used to generate the parking bills given the time-in and a time-out of the vehicle. This paper aimed to tackle the problems of car management and to further simplify the parking system.
Electromyography-Driven Exergaming in Wheelchairs on a Mobile Platform: Bench and Pilot Testing of the WOW-Mobile Fitness System

Background Implementing exercises in the form of video games, otherwise known as exergaming, has gained recent attention as a way to combat health issues resulting from sedentary lifestyles. However, these exergaming apps have not been developed for exercises that can be performed in wheelchairs, and they tend to rely on whole-body movements. Objective This study aims to develop a mobile phone app that implements electromyography (EMG)-driven exergaming, to test the feasibility of using this app to enable people in wheelchairs to perform exergames independently and flexibly in their own home, and to assess the perceived usefulness and usability of this mobile health system. Methods We developed an Android mobile phone app (Workout on Wheels, WOW-Mobile) that senses upper limb muscle activity (EMG) from wireless body-worn sensors to drive 3 different video games that implement upper limb exercises designed for people in wheelchairs. Cloud server recordings of EMG enabled long-term monitoring and feedback as well as multiplayer gaming. Bench testing of data transmission and power consumption were tested. Pilot testing was conducted on 4 individuals with spinal cord injury. Each had a WOW-Mobile system at home for 8 weeks. We measured the minutes for which the app was used and the exergames were played, and we integrated EMG as a measure of energy expended. We also conducted a perceived usefulness and usability questionnaire. Results Bench test results revealed that the app meets performance specifications to enable real-time gaming, cloud storage of data, and live cloud server transmission for multiplayer gaming. The EMG sampling rate of 64 samples per second, in combination with zero-loss data communication with the cloud server within a 10-m range, provided seamless control over the app exergames and allowed for offline data analysis. Each participant successfully used the WOW-Mobile system at home for 8 weeks, using the app for an average of 146 (range 89-267) minutes per week with the system, actively exergaming for an average of 53% of that time (39%-59%). Energy expenditure, as measured by integrated EMG, was found to be directly proportional to the time spent on the app (Pearson correlation coefficient, r=0.57-0.86, depending on the game). Of the 4 participants, 2 did not exercise regularly before the study; these 2 participants increased from reportedly exercising close to 0 minutes per week to exergaming 58 and 158 minutes on average using the WOW-Mobile fitness system. The perceived usefulness of WOW-Mobile in motivating participants to exercise averaged 4.5 on a 5-point Likert scale and averaged 5 for the 3 participants with thoracic level injuries. The mean overall ease of use score was 4.25 out of 5. Conclusions Mobile app exergames driven by EMG have promising potential for encouraging and facilitating fitness for individuals in wheelchairs who have maintained arm and hand mobility.
Malware and Exploits on the Dark Web

In recent years, the darknet has become the key location for the distribution of malware and exploits. We have seen scenarios where software vulnerabilities have been disclosed by vendors and shortly after, operational exploits are available on darknet forums and marketplaces. Many marketplace vendors offer zero-day exploits that have not yet been discovered or disclosed. This trend has led to security companies offering darknet analysis services to detect new exploits and malware, providing proactive threat intelligence. This paper presents information on the scale of malware distribution, the trends of malware types offered, the methods for discovering new exploits and the effectiveness of darknet analysis in detecting malware at the earliest possible stage.
Digital filtering algorithms for decorrelation within large least squares problems

The GOCE (Gravity Field and steady-state Ocean Circulation Explorer) mission is dedicated to the determination of the Earth’s gravity field. During the mission period of at least one year the GOCE satellite will collect approximately 100 million highly correlated observations. The gravity field will be described in terms of approximately 70 000 spherical harmonic coefficients. This leads to a least squares adjustment, in which the design matrix occupies 51 terabytes while the covariance matrix of the observations requires 72 760 terabytes of memory. The very large design matrix is typically computed in parallel using supercomputers like the JUMP (Juelich Multi Processor) supercomputer in Jülich, Germany. However, such a brute force approach does not work for the covariance matrix. Here, we have to exploit certain features of the observations, e.g. that the observations can be interpreted as a stationary time series. This allows for a very sparse representation of the covariance matrix by digital filters. This thesis is concerned with the use of digital filters for decorrelation within large least squares problems. First, it is analyzed, which conditions the observations must meet, such that digital filters can be used to represent their covariance matrix. After that, different filter implementations are introduced and compared with each other, especially with respect to the calculation time of filtering. This is of special concern, as for many applications the very large design matrix has to be filtered at least once. One special problem arising by the use of digital filters is the so-called warm-up effect. For the first time, methods are developed in this thesis for determining the length of the effect and for avoiding this effect. Next, a new algorithm is developed to deal with the problem of short data gaps within the observation time series. Finally, it is investigated which filter methods are best adopted for the application scenario GOCE, and several numerical simulations are performed.
A tale of two RlpAs: Studies of cell division in Escherichia coli and Pseudomonas aeruginosa

ii To my beloved Michelle. iii Often when you think you're at the end of something, you're at the beginning of something else. iv ACKNOWLEDGMENTS It is a terrible thing to have to reduce to a few lines the importance of the individuals in my life who have brought me to this point in my education. Know that between these lines are found the tireless efforts, wonderful conversations, and continual encouragements that have made all that follows possible. I would like to say to each of you beforehand, with the deepest sincerity, that you are special and may these words serve as a blessing for all that you have done for me. I would like to acknowledge first David Weiss. As my mentor, I could not have found one better. Your approach to science through critical thinking and careful planning has played no small part in shaping the way I think. Thank you for always making yourself available to me. Because of these, I know my time in your lab has not simply been spent but well spent. I want to next acknowledge my labmates. I thank Atsushi Yahashiri for being a gracious post-doc who constantly challenged me to think differently. I also want to thank Eric Ransom, who I could bounce an idea off of anytime and who picked me up when things just did not want to work, as they are often prone to do in science. I count you both as the best sort of friends to have. I would like to thank Michael Feiss for making my first rotation such a positive experience and introducing me to David. Because of these, I hope the Cubs win the World Series…someday. I would also like to thank the members of my thesis committee for lending their expertise to my projects when called upon. Your direction and advice were invaluable and went a long way to making these stories possible. v I would like to thank Pastor Tim Waldron and the members of Faith Baptist Church in Iowa City. From my first week in Iowa, you welcomed my family into your community and made us feel so at home when we felt so far away from our own. Your loving kindness for our family has made all the difference. We will miss you dearly. To my parents, I want to thank you for providing unending encouragement and support in …
Combining symmetric and standard deep convolutional representations for detecting brain hemorrhage

Brain hemorrhage (BH) is a severe type of stroke resulting in high mortality and morbidity. Detection and diagnosis of BH is commonly performed using neuroimaging tools such as Computed Tomography (CT). We compare and contrast symmetry-aware, symmetry-naive feature representations and their combination for the detection of BH using CT imaging. One of the proposed architectures, e-DeepSymNet, achieves AUC 0.99 [0.97- 1.00] for BH detection. An analysis of the activation values shows that both symmetry-aware and symmetry-naive representations offer complementary information with symmetry-aware representation naive contributing 20% towards the final predictions.
Molecular subclassification of medulloblastoma and its utility for disease prognostication

Medulloblastoma is the most common malignant brain tumour of childhood. Transcriptomic classification of the disease has indicated the existence of discrete molecular subgroups of medulloblastoma, although the precise number, nature and clinical significance of these subgroups remains unclear. Two groups, characterised by activation of the WNT and SHH signalling pathways, are common to all published studies. An assay for the rapid diagnosis of medulloblastoma subgroups was therefore designed, using transcriptomic gene signatures of pathway activation for the WNT and SHH signalling pathways. The successful validation of these gene signatures in vitro and in silico enabled a meta-analysis of 173 new and published cases to be performed, which defined the molecular and clinico-pathological correlates of the disease subgroups more precisely. WNT subgroup cases were associated with CTNNB1 mutation, chromosome 6 loss and classic histology and were diagnosed > 5 years of age. SHH cases predominated in infants and showed an age-dependent relationship to desmoplastic / nodular histology. WNT / SHH independent tumours showed all histologies, peaked at 3 to 6 years and were associated with chromosome 17p loss. A novel DNA methylation array-based approach was next applied to disease subclassification. Using consensus clustering, based on non-negative matrix factorisation, four methylomic subgroups were identified in a training cohort (n = 100), which were robustly validated in a test cohort (n = 130). The subgroups were characterised by significant relationships to specific clinico-pathological and molecular markers. Two subgroups were characterised by activation of the WNT and SHH signalling pathways and showed equivalent clinico-pathological and molecular characteristics to the previously defined transcriptomic subgroups. For the WNT / SHH independent subgroups, group I was associated with a loss of chromosome 17p, whereas group II was enriched for large cell / anaplastic (LCA) histology. The WNT subgroup was associated with a favourable prognosis, while no survival differences were apparent between the remaining subgroups (SHH, group I, group II). Specific methylation biomarkers were identified for the discrimination of all subgroups. Assays of DNA methylation status were robust in derivatives of FFPE tissues, enabling testing in routinely-collected clinical material. Finally, the prognostic potential of methylomic biomarkers was investigated in a large clinical trials-based cohort (n = 191), with particular focus on the non-WNT subgroups (n = 163), where subgroup membership was not prognostic. Using the Cox Boost algorithm, which adds high dimensional data to mandatory clinical covariates to form cross-validated prognostic Cox survival models, the methylation status of MXI1 and IL8 were each identified as independent prognostic markers. These were incorporated into a novel risk stratification scheme, based on the cumulative assessment of disease risk using clinical (metastatic disease; poor prognosis), pathological (LCA…
Implementing the State-Space Representation by the Super Operator Design Pattern

While implementing state-space representation technique of arti(cid:28)cial intelligence we found that the mathematical design suggests having a separate state and operator classes. But this breaks the encapsulation principle of OOP. To solve this we introduce a new structural design pattern, the super operator design pattern. A super operator is a proxy to operators, it has a parameter which decides which operator to call, it returns what the operator returns. In this way one class can represent the state-space representation which contains the operators and the states, so we can preserve encapsulation. On the other hand we break separation of concerns and single responsibility principles, since we do not separate states and operators. The set of methods behind the super operator should have a similar contract, because the super operator can ensure only the common part of the contracts of the methods. If this common part is empty, then this design pattern cannot be used. The new design pattern is applicable if iteration over a set of methods is important; a set of methods have similar contract, for the client is all them same which one is called; the understandability is more important than reusability, e.g., educational purposes; forcing encapsulation over separation of concerns is essential.
FREQUENCY OF EXTENDED DIAPAUSE IN NEBRASKA POPULATIONS OF DIABROTICA BARBERI SMITH AND LAWRENCE.

This study was conducted to measure the frequency of extended diapause in populations of the northern corn rootworm, Diabrotica barberi Smith and Lawrence from eastern Nebraska. Adult D. barberi collections were made during late summer 2008 and 2009 from eight sites each year (seven sites were consistent over years). Eggs were obtained from 12-20 females per site and were held on moist soil under appropriate temperature profiles to facilitate egg survival, diapause development, and diapause termination within and among years. Percentage egg hatch was recorded after the first and second year for the 2008 collection and after the first year for the 2009 collection. Additional extended diapause expression was estimated for the 2008 collection by counting remaining live eggs after the second year egg hatch was completed. This data was also used to estimate each site's maximum egg viability. Results collectively indicate that the extended diapause trait occurred in all eastern Nebraska populations; however, significant variation in the frequency of extended diapause was observed within and among D. barberi populations. Geographically, the highest incidence of extended diapause was found in a north-south transect in eastern counties of Nebraska that parallel the Missouri River. In general, the frequency of extended diapause was lower in sites found west of the north-south transect. This study contributes to the database needed to develop appropriate D. barberi management strategies in Nebraska. Data can be used to pinpoint areas of Nebraska that may have the greatest risk of economic injury in first-year corn when D. barberi densities are high. Extended diapause in Nebraska D.barberi populations may also be a positive attribute from a resistance management perspective. Diapausing individuals will provide a natural refuge which would complement any structured refuge that may be in place when transgenic plants are used to manage corn rootworms. iv ACKNOWLEDGMENTS I would like to thank my advisor, Dr. Lance Meinke for all his help and guidance throughout my research program here at the University of Nebraska. I would also like to thank the other members of my research committee: Dr. Thomas Hunt and Dr. Junwei Zhu. My experiments were completed with great aid from others within the lab. Specifically Jim Brown helped me a great deal as well as Steven Losey who was always available to help count and rear my insects. Additionally Dr. Erin Blankenship aided me with the creation of my statistical programs. Finally I would like to thank …
The combined approach for space weather prediction with a guaranteed method and evolutionary algorithm

The problem of space weather prediction using guaranteed approach and solar wind parameters is considered. The original approach for space weather prediction based on a discrete dynamic model, evolutionary algorithm and a guaranteed interval estimation method is proposed. The problem of discrete model identification is formulated as a nonlinear programming problem with constraints. A new algorithm of Dst-index prediction using guaranteed interval estimation method is described. The model for the prediction of geomagnetic storms was constructed and the interaction between the solar wind parameters and the magnetosphere was discussed. The dependence between prediction accuracy and the forecasting horizon is analyzed.
Structures, properties, and digestibility of resistant starch

iv GENERAL INTRODUCTION 1 DISSERTATION ORGANIZATION 4 CHAPTER 1. LITERATURE REVIEW 5 1. Structure of starch granules 5 2. Thermal property of starch 8 3. Pasting property of starch 10 4. Gel formation of starch 11 5. Amylose-lipid complex 12 6. Enzymatic hydrolysis of starch 13 7. Resistant starch 17 References 21 Figures 32 CHAPTER 2. EFFECTS OF LIPIDS ON ENZYMATIC HYDROLYSIS AND PHYSICAL PROPERTIES OF STARCH 37 Abstract 37
The assessment of detoxification metabolism in fatty acid oxidation deficiencies

v UITTREKSEL . vii ACKNOWLEDGEMENTS . ix LIST OF FIGURES . x LIST OF TABLES . xi LIST OF ABBREVIATIONS . xii CHAPTER 1 INTRODUCTION 1.
Prevention of sudden cardiac death after revascularization for coronary heart disease

Sudden cardiac death (SCD) is the leading cause of death in adults worldwide. Coronary heart disease is the underlying reason for most of the patients with SCD, including acute coronary syndrome and chronic ischemic heart disease. Revascularization is an important treatment technology for coronary heart disease, which includes percutaneous coronary intervention and surgical coronary artery bypass grafting. However, according to the recommended guidelines, even with the use of secondary prevention strategies such as medication treatment and a complete revascularization, there are still a great number of patients who have reduced left ventricular ejection fraction, heart failure, and ventricular arrhythmia at different stages in the course of disease. SCD remains to be a serious challenge in the long-term management of ischemic heart disease patients who have had revascularization. Here, we focus on broader issues of concerns to provide more insights by comprehensive recommendations for the clinical treatment of coronary artery disease after revascularization for SCD prevention.
NeuDetect: A neural network data mining system for wireless network intrusion detection

This thesis proposes an Intrusion Detection System, NeuDetect, which applies Neural Network technique to wireless network packets captured through hardware sensors for purposes of real time detection of anomalous packets. To address the problem of high false alarm rate confronted by the current wireless intrusion detection systems, this thesis presents a method of applying the artificial neural networks technique to the wireless network intrusion detection system. The proposed system solution approach is to find normal and anomalous patterns on preprocessed wireless packet records by comparing them with training data using Backpropagation algorithm. An anomaly score is assigned to each packet by calculating the difference between the output error and threshold. If the anomaly score is positive then the wireless packet is flagged as anomalous and is negative then the packet is flagged as normal. If the anomaly score is zero or close to zero it will be flagged as an unknown attack and will be sent back to training process for re-evaluation.