Miracle-dz/UniFAR-FTUs huggingface dataset:
Breakpoint refinement of genomic structural variation using split read analysis

BREAKPOINT REFINEMENT OF GENOMIC STRUCTURAL VARIATION USING SPLIT READ ANALYSIS Balanur İçen M.S. in Computer Engineering Advisor: Can Alkan September 2019 Genomic variations that vary from single nucleotide polymorphisms (SNPs), small INDELs to structural variations (SVs) are discovered to have significant phenotypic effects on individuals. Among these genomic variations, SVs are changes that affect more than 50 nucleotides of DNA. SVs are linked to the sources of many genetic diseases such as autism, schizophrenia and chronic myelogenous leukemia. Accurate and precise characterization of these structural variants not only enables us to diagnose genetic diseases that are previously correlated with them but also it provides more reliable information to pursue higher levels of research in the genomic research pipelines. There are many SV detection tools that aim to find the approximate locations of SVs in genome, a further step in the pipeline is to refine those breakpoints of variants by a closer and more focused examination. By this means, genotyping step of structural variations would be faster using k-mer based alignment-free methods and more accurate since locations of SVs will be known with 1-5 base pair resolution compared to 300 500 base pair long confidence intervals. Moreover, further steps in the genomic pipelines based on the results of SV detection algorithms would have more definite data to build up on. In this thesis, we propose BROSV (Breakpoint Refinement of Structural Variation), a breakpoint refinement algorithm to obtain better resolution on SV breakpoints with split read analysis and local assembly methods using Illumina short reads and BWA alignment tool. Implementation is available at https://github.com/BilkentCompGen/brosv.
A Clinical Study of Diabetes Mellitus Type II and its Association with Bacterial Infections

This study was carried out at the Al-Nasiriyah Centre for Endocrinology and Diabetes for the period from 10 October 2013 to 3 September 2014. It was conducted to determine the causal factors of diabetes mellitus type II at Thi-Qar province south of Iraq. The results showed that the incidence of diabetes was high among females (54%). The results also showed that the highest rate (30%) of the diabetes among age group 49-59 years that they have symptoms of diabetes but they have not a history of diabetes (51%). The highest incidence of diabetes was among smoker patients (64%), that the distribution of diabetes among urban was high (62%) than rural (38%). In addition, pathogenic bacteria were isolated from diabetic patients from different infectious sites such as urinary tract, wound and respiratory tract infections. Escherichia coli, Staphylococcus aureus and Klebsiella pneumoniae were isolated at high percentage respectively, while the most bacterial isolates showed resistance to Ampicillin and Amoxycillin, but other isolates showed sensitive to Amikacin, Cefotaxime, Azithromycin and Cefixime. The results from published reports as well as our data suggest that good control of blood sugar in diabetic patients is a necessary aim to prevent of certain infections and to ensure maintenance of normal host defence.
Effects of Macrofungal Polysaccharides Combined with Vemurafenib on Melanoma and Its Associated Mechanism

Fungal polysaccharides have demonstrated various biological functions such as antitumor, immune regulation, and antioxidant activities. It has also been reported to be beneficial in reshaping the immune system’s surveillance on tumor cells and in helping the immune system kill tumor cells. In this study, a melanoma mouse model was constructed, and a macrofungal polysaccharide (MFPS) extracted from Pleurotus ostreatus combined with Vemurafenib monoclonal antibody was used to study their effects against melanoma and its antitumor mechanism by using the lactate dehydrogenase release assay, enzyme-linked immunosorbent assay, and flow typing assay. Results indicated that MFPS enhanced the inhibitory effect of Vemurafenib on tumor growth in melanoma-bearing mice and the secretion of cytokines IFN-γ and IL-12 in PBMCs of melanoma-bearing mice. In addition, the combination of MFPS1 and Vemurafenib can enhance the immunomodulatory activity of melanoma-bearing mice as well as elicit the activation and proliferation of B cells and T cells.
Minimize Magnetic Field disorders by using Antioxidants

The study aimed to investigate the treatment effect of marjoram leaves on brain tissue and some biochemical properties that exposed to magnetic field (MF). Magnetic fields may cause heating of the skin and the tissue, which could lead to several disorders as increase the production of reactive oxygen species. Animals have the effective enzymatic antioxidant defense system including catalase (CAT), superoxide dismutase (SOD), and Glutathione (GSH) and Glutathione reductase (GSH-Px) enzymes. Lipid peroxidation in blood (erythrocytes) was measured as the amount of malon dialdehyde (MDA). This system allow for scavenging of reactive oxygen species ROS and leading to protection of cells from oxidative damage. Fruits, plants and vegetables contain high amounts of antioxidants, like polyphenols, vitamin C, vitamin E, β-carotene, and lycopene. Plants as Marjoram contains several acids as urosolic acid, carnostic acid, and carnosol which used as free radical scavengers. So it protect organs as liver , brain and kidney and enhance the antioxidant activities .
Supplementary Material for Siamese Networks: The Tale of Two Manifolds

Locally Euclidean just means that each point has a neighborhood that is homeomorphic to an open ball in R for some n. Moreover, being a Hausdorff space means that distinct points have disjoint neighborhoods. This property is useful for establishing the notion of a differential manifold, as it guarantees that convergent sequences have a single limit point. The exponential map Expx(·) : TxM → M and its inverse, the logarithm maps, Logx(·) :M→ TxM are defined over Riemannian manifolds to switch between the manifold and its tangent space at x. The exponential operator maps a tangent vector ∆ to a point y on the manifold. The property of the exponential map ensures that the length of ∆ becomes equal to the geodesic distance between x and y. The logarithm map is the inverse of the exponential map, and maps a point on the manifold to the tangent space Tx. The exponential and logarithm maps vary as point x moves along the manifold. A natural way to measure nearness on a manifold is by considering the geodesic distance between two points on the manifold. Such distance is defined as the length of the shortest curve connecting the two points. The shortest curves are known as geodesics and are analogous to straight lines in R. The tangent space at a point x on the manifold, TxM, is a vector space that consists of the tangent vectors of all possible curves passing through x. Note that we will assume that the key conditions needed for these maps to exist are satisfied. Remark 1. In devising the rNAG, we opt for the most general and mathematically rigorous solution that benefits from the exponential map and its inverse. For the sake of discussion, We repeat this general form of rNAG below.
Novel statistical analysis of long-term survival to account for crossover in a phase III trial of sunitinib (SU) vs. placebo (PL) in advanced GIST after imatinib (IM) failure

10524 Background: SU is an oral multitargeted tyrosine kinase inhibitor of KIT, PDGFRs, VEGFRs, FLT3, CSF-1R and RET, approved multinationally for treatment of advanced GIST after IM failure. Interim analysis of a double-blind, PL-controlled phase III trial in this pt population showed a significant difference in OS between pts randomized to SU (50 mg/d administered in 6-wk cycles of 4 wk on treatment, 2 wk off; N=207) or PL (N=105) favoring SU (HR 0.49; P=0.007), without medians having been reached. The study design allowed PL pts to cross over to SU at PD or unblinding of the trial. While efficacy and safety/tolerability continue to be assessed, conventional statistical methods yield biased treatment-effect estimates for mature OS data because of the crossover. Methods: In addition to the log-rank test, Cox model and Kaplan-Meier method, OS was analyzed using the rank-preserving structural failure time (RPSFT) method to account for crossover. Results: Across the entire study (double-blind + open-label p.
Comparative Study of Two Different Rapid Diagnostic Tests with Microscopy Method for Malaria Parasite Detection

Introduction: Accurate rapid diagnosis is one of the most important steps in the effort to reduce morbidity and mortality of malaria. Blood-specific malaria rapid diagnostic tests (RDTs) are currently in use but reports on their sensitivity and specificity and comparison with the established blood film microscopy methods are dearth. The aim of the present study was to evaluate the performance characteristics of Nova and SD bioline RTDs and compare with microscopic method as a reference standard to detect the presence of malaria parasites in the blood. Methods: A total of 100 subjects were conveniently selected from consented subjects attending out-patient Department of Rivers State University Teaching Hospital, Port Harcourt, and the samples were analyzed using blood film examined with Giemsa staining technique and Nova and SD bioline kits. Results: Of the 100 samples examined, 57(57%) were positive for malaria parasite by light microscopy, 37(37%) were positive by Nova and 22 (22%) were positive by SD bioline. The sensitivity of the two RDTs used were found to be 54% for Nova and 30% for SD bioline, the specificity were 86% for Nova and 88% for SD bioline, the PPV for Nova was 83% and 77% for SD bioline while the NPV for Nova was 59% and 49% for SD bioline. Percentage positivity of 50.9% and 49.1% for males and females respectively means that both sexes are equally susceptible to malaria parasites. There was a slight increase in parasitaemia in females (1931±2801) than males (1139±2415) but these results were not statistically significant (P >.27). Conclusion: The SD bioline showed a very poor sensitivity in contrast to Nova and light microscopy. Inspite of the relative advantages of RDTs, microscopy remains the best method of detecting malaria parasite and Nova should be preferred to other RDTs.
Progressive processing of system-behavioral query

System monitoring has recently emerged as an effective way to analyze and counter advanced cyber attacks. The monitoring data records a series of system events and provides a global view of system behaviors in an organization. Querying such data to identify potential system risks and malicious behaviors helps security analysts detect and analyze abnormal system behaviors caused by attacks. However, since the data volume is huge, queries could easily run for a long time, making it difficult for system experts to obtain prompt and continuous feedback. To support interactive querying over system monitoring data, we propose ProbeQ, a system that progressively processes system-behavioral queries. It allows users to concisely compose queries that describe system behaviors and specify an update frequency to obtain partial results progressively. The query engine of ProbeQ is built based on a framework that partitions ProbeQ queries into sub-queries for parallel execution and retrieves partial results periodically based on the specified update frequency. We concretize the framework with three partition strategies that predict the workloads for sub-queries, where the adaptive workload partition strategy (AdWd) dynamically adjusts the predicted workloads for subsequent sub-queries based on the latest execution information. We evaluate the prototype system of ProbeQ on commonly used queries for suspicious behaviors over real-world system monitoring data, and the results show that the ProbeQ system can provide partial updates progressively (on average 9.1% deviation from the update frequencies) with only 1.2% execution overhead compared to the execution without progressive processing.
Easy grasping location learning from one-shot demonstration

—In this paper, we propose a fast learner grasping pipeline able to grasp objects at a speciﬁc location few minutes after being taught by an operator. Our motivation is to ease reconﬁguration of robot according to a speciﬁc task, without any CAD model, nor existing database, nor simulator. We build a CNN pipeline which performs a semantic segmentation of object, and recognizes authorized and prohibited grasping location shown during demonstration. For that we have sim-pliﬁed the input space, created a data augmentation process and proposed a light CNN architecture allowing learning in less than 5 minutes. Validation on a real 7-DOF robot shown good performances ( 70 to 100% depending on the object), with only a one-shoot operator’s demonstration. Performances remain good when grasping similar unseen objects, and with several objects in the robot’s workspace using few demonstrations. A video highlighting the main aspects can be found at https://www.youtube. com/watch? v=rYCIk6njBo4
The cloud simulation in Marine Simulation right now mainly uses 2D texture mapping technology realized by OPENGVS

As the main scenery of sky, the effect of 3D cloud influences the fidelity of visual system and the immersion effect of simulator. In this paper, based on the work of Y. Dobashi and T. Nishita, small region Cellular Automaton is generated and more realistic cloud simulation is improved. The experimental results show that the visual system of simulator can run in real-time and has a relatively higher refresh rate after changeable 3D cloud being applied.
Transmission eigenvalues for the electromagnetic scattering problem in pseudo-chiral media and a practical reconstruction method

In this paper, we consider the two-dimensional Maxwell’s equations with the TM mode in pseudo-chiral media. The system can be reduced to the acoustic equation with a negative index of refraction. We first study the transmission eigenvalue problem (TEP) for this equation. By the continuous finite element method, we discretize the reduced equation and transform the study of TEP to a quadratic eigenvalue problem by deflating all nonphysical zeros. We then estimate half of the eigenvalues are negative with order of O(1) and the other half of eigenvalues are positive with order of O(10). In the second part of the paper, we present a practical numerical method to reconstruct the support of the inhomogeneity by the near-field measurements, i.e., Cauchy data. Based on the linear sampling method, we propose the truncated singular value decomposition to solve the ill-posed near-field integral equation, at one wave number which is not a transmission eigenvalue. By carefully chosen an indicator function, this method produce different jumps for the sampling points inside and outside the support. Numerical results show that our method is able to reconstruct the support reliably.
Discovery of stable and prognostic CT-based radiomic features independent of contrast administration and dimensionality in oesophageal cancer

The aim of this work was to investigate radiomic analysis of contrast and non-contrast enhanced planning CT images of oesophageal cancer (OC) patients in terms of stability, dimensionality and contrast agent dependency. The prognostic significance of CT-based radiomic features was also evaluated. Different 2D and 3D radiomic features were extracted from contrast and non-contrast enhanced CT images of 213 patients from the multi-centre SCOPE1 randomised controlled trial (RCT) in OC. Feature stability was evaluated by randomly dividing patients into three groups and identifying textures with similar distributions among groups with a Kruskal-Wallis analysis. A paired two-sided Wilcoxon signed rank test was used to assess for significant differences in the remaining corresponding 2D and 3D stable features. A prognostic model was constructed using clinical characteristics and remaining filtered features. The discriminative ability of significant variables was tested using Kaplan-Meier analysis. A total of 238 2D and 3D radiomic features were computed from oesophageal CT images. More than 75 features were stable if extracted from homogeneous cohort (contrast or non-contrast enhanced CT images) and inhomogeneous cohort (contrast and non-contrast enhanced CT images). Among the remaining corresponding stable features computed from both cohorts, only 4 features did not show a statistically significant difference if obtained in 2D or in 3D (p-value < 0.05). A Cox regression model constructed using 5 clinical variables (age, sex, tumour, node and metastasis (TNM) stage, WHO performance status and contrast administration) and 4 radiomic variables (inverse varianceGLCM, large distance emphasisGLDZM, zone distance non uniformity normGLDZM, zone distance varianceGLDZM), identified one radiomic feature (zone distance varianceGLDZM) that was significantly associated with overall survival (p-value = 0.032, HR = 1.25, 95% CI = 1.02–1.52). A significant difference in overall survival between groups was found when considering a threshold of zone distance varianceGLDZM equals to 1.70 (X2 = 7.692, df = 1, p-value = 0.006). Zone distance varianceGLDZM was identified as the only stable CT radiomic feature statistically correlated with overall survival, independent of dimensionality and contrast administration. This feature was able to identify high-risk patients and if validated, could be the subject of a future clinical trial aiming to improve clinical decision making and personalise OC treatment.
OTT_A_206517 5053..5067

Jianzhong Wu* Junwei Qu* Haixia Cao Changwen Jing Zhuo Wang Heng Xu Rong Ma 1Research Center for Clinical Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, Jiangsu 210000, People’s Republic of China; 2Laboratory of Pharmaceutical Chemistry, Jiangsu Province Institute of Materia Medica, Nanjing Tech University, Nanjing, Jiangsu 211816, People’s Republic of China
Parents and Children: a Collective Model of Household Behavior and Child Development

There is extensive evidence suggesting that skills developed early in life will have consequences on adult life outcomes. Such findings have motivated a large body of literature analyzing the production of skills in young children. Nonetheless, very little is known about what are the tradeoffs faced by families when making decisions of investments in their children and how such decisions are reached within households. In this article I estimate a collective model of labor supply and investment in skills for children. The parameters estimated are used to simulate the effect of increasing the amount of monetary transfers to poor households. The results show that the way such policies distort the process of intra-household bargaining have significant consequences in the inequalities of skills observed in young children.
ICCBR 2019 Doctoral Consortium

Dynamic difficulty adjustment (DDA) in video games context allows a game to be automatically adjusted and customized based on the player’s performance. Our goal is to build a DDA architecture able to learn from behavioral data and return appropriate feedback to maximize the player’s performance and enjoyment. For our experiments, we use Tetris Analytics video game, which is like a traditional Tetris from the player’s point of view. However, it allows us to extract data from the games such as the movements made by the player, the state of the board, next piece, etc. With this data, we predict the player’s profile and personalize the game.
A Micro Aerial Vehicle with Precise Position and Attitude Sensors

This study shows the potential of navigation technologies in the field of position and orientation determination on a micro aerial vehicle (MAV), which weight does not exceed 5 kg. Although the MAV systems feature high flexibility and capability of flying into areas that are inhospitable or inaccessible to humans, the lack of precision in positioning and attitude estimation on-board decreases the gained value of the captured imagery. This limits their mode of operation to indirect georeferencing. This paper pre-sents the development of a low cost MAV with navigation-sensor payload that shall assure a position and attitude control with accuracy from which either direct or integrated sensor orientation can benefit. After describing the hardware configuration and the synchronization of all measurements we present a case study that evaluates the performance of the positioning component and its application on integrated sensor orientation without ground control. There we show that thanks to the implementation of a multi-frequency, low power GNSS receiver, the system can potentially attain the mapping characteristics of much larger platforms flown on man-operated carriers while keeping the sensor size and weight suitable for MAV operations. The attitude accuracy of the developed board hosting several MEMS-IMUs is evaluated dynamically on a terrestrial vehicle using a reference (navigation grade) INS. Although this method offers continuous evaluation of the orientation accuracy and the obtained results are satisfactory with respect to the foreseen operations, this performance remains to be confirmed in a flight.
Data mining methods applied to healthcare problems

Growing adoption of health information technologies is allowing healthcare providers to capture and store enormous amounts of patient data. In order to effectively use this data to improve healthcare outcomes and processes, clinicians need to identify the relevant measures and apply the correct analysis methods for the type of data at hand. In this dissertation, we present various data mining and statistical methods that could be applied to the type of datasets that are found in healthcare research. We discuss the process of identification of appropriate measures and statistical tools, the analysis and validation of mathematical models, and the interpretation of results to improve healthcare quality and safety. We illustrate the application of statistics and data mining techniques on three real-world healthcare datasets. In the first chapter, we develop a new method to assess hydration status using breath samples. Through analysis of the more than 300 volatile organic compounds contained in human breath, we aim to identify markers of hydration. In the second chapter, we evaluate the impact of the implementation of an electronic medical record system on the rate of inpatient medication errors and adverse drug events. The objective is to understand the impact on patient safety of different information technologies in a specific environment (inpatient pediatrics) and to provide recommendations on how to correctly analyze count data with a large amount of zeros. In the last chapter, we develop a mathematical model to predict the probability of developing post-operative nausea and vomiting based on patient demographics and clinical history, and to identify the group of patients at high-risk.