Miracle-dz/UniFAR-FTUs huggingface dataset:
The epigenome in pediatric acute lymphoblastic leukemia: drug resistance and therapeutic opportunities

Acute lymphoblastic leukemia (ALL) is the most common malignancy of childhood. The genomic landscape of pediatric ALL has been extensively characterized, allowing for the identification of distinct molecular subtypes of this disease. This in turn has facilitated improvements in risk stratification and tailoring of therapy, resulting in dramatic improvements in survival rates over the past several decades. However, despite these improvements, outcomes remain dismal for the ten percent of patients who continue to fail therapy and relapse. Although the genetic landscape of pediatric ALL is well-understood, increasing evidence suggests that genetic alterations alone are insufficient to promote leukemogenesis and the acquisition of chemoresistance that leads to disease relapse. Instead, cooperating epigenetic alterations are now recognized as important contributors to the aberrant gene expression profiles that are characteristic of the molecular subtypes of ALL, and changes in the epigenetic landscape are now thought to underlie the development of chemoresistance and ultimately disease relapse. This review article focuses on the expanding knowledge of the role of the epigenome in ALL pathogenesis, progression, and response to therapy, and highlights preclinical and clinical efforts to target the epigenome as a means of overcoming chemoresistance and improving outcomes for children with ALL.
Formulation of 3 D and Projective Extensions of the Self Affine Feature Transform

The Self Affine Feature Transform (SAFT) can analyze both geometric and photographic 2D image details. It is capable to identify analytical curves and extract their parameters. This is achieved by investigating the invariance of the 2D image against planar affine transformations. This paper presents the spatial extension of this model, which can process vectorized or volumetric 3D information and detect analytical surfaces in space. Projective extensions are introduced also. The goal of the article is to show theoretical equivalence of the described planar and spatial methods. Only very brief test results are given.
Statistical Machine Translation of English Text to API Code Usages :

Statistical Machine Translation of English Text to API Code Usages: A comparison of Word Map, Contextual Graph Ordering, Phrase-based, and Neural Network Translations Dharani Kumar Palani Statistical Machine Translation (SMT) has gained enormous popularity in recent years as natural language translations have become increasingly accurate. In this thesis we apply SMT techniques in the context of translating English descriptions of programming tasks to source code. We evaluate four existing approaches: maximum likelihood word maps, ContextualExpansion, phrase-based, and neural network translation. As a training and test (i.e. reference translation) data set we clean and align the popular developer discussion forum StackOverflow. Our baseline approach, WordMapK, uses a simple maximum likelihood word map model which is then ordered using existing code usage graphs. The approach is quite effective, with a precision and recall of 20 and 50, respectively. Adding context to the word map model, ContextualExpansion, is able to increase the precision to 25 with a recall of 40. The traditional phrase-based translation model, Moses, achieves a similar precision and recall also incorporating the context of the input text by mapping English sequences to code sequences. The final approach is neural network translation, OpenNMT. While the median precision is 100 the recall is only 20. When manually examining the output of the neural translation, the code usages are very small and obvious. Our results represent an application of existing natural language strategies in the context of software engineering. We make our scripts, corpus, and reference translations in the hope that future work will adapt these techniques to further increase the quality of English to code statistical machine translation.
3-Dimensional Model and Simulations of Sperm Movement

In this project we are building a mathematical model to track the movement of spermatozoa during the process of chemotaxis. Our model is built on an off-lattice spherical biased random walk in 3-dimensional space, an extension of previous conventional deterministic 2-dimensional models. The sperm’s type of movement is decided based on a comparison of the current and previous chemoattractant concentration which can be used to see whether it is approaching the egg. From the statistical analysis of the simulation results, we find that chemotaxis is an effective mechanism to increase the number of sperm reaching the egg.
Synthesis and Characterization of Nanoporous Carbon from Sugarcanne Bagasse (Saccharum officianarum) with ZnCl2 Activator by Ultrasonic Irradiation as Electrochemical Energy Storage Material

A study on synthesis and characterization of nanoporous carbon derived from sugarcane bagasse (Saccharum officianarum) by ultrasonik irradiation using ZnCl2 activator for electrochemical capasitor application has been investigated. Nanoporous carbon is a basic material for the electrode in the electrochemical energy storage. Nanoporous carbon has been synthesized based on three-steps procedures, i.e. carbonization in temperature of 350 0C, silica extraction, and activation using ZnCl2 with ultrasonic irradiation. Activated carbon with irradiation showed an increasing in intensity of the –OH functional group stretch at wave number of 3419,79. The results of XRF analysis showed the highest content of oxide compound in the activated carbon was ZnO as 97,06%, and result of XRD analysis showed that activated carbon has both amorphous and crystalline. The result of SEM analysis showed that the pores evolvement of irradiated activated carbon was better than un-irradiated activated carbon, with diameter of the pores 1,5 to 2 µm. The surface area of the carbon in optimum temperature of 30 oC for 60 minutes was 171, 2802 m2/g and the energy storage capacity was 0,3284 x 10-5 F/g.
Paced Chirping: Rapid flow start with very low queuing delay

This paper introduces a promising new direction for getting a traffic flow up to speed fast while keeping the maximum queuing delay that the new flow adds extremely low. It is therefore most interesting in environments where queue delay is already fairly low. Nonetheless, it requires no special network infrastructure, being solely delay-based, so it ought to be applicable to the general Internet. Received wisdom from TCP slow-start is that the faster a flow accelerates, the more it will overshoot the queue before the sender will notice one round trip later. The proposed technique, called paced chirping. escapes that dilemma. The sender pulses the queue increasingly rapidly with trains of packets called ‘chirps’ that it crafts to rapidly estimate available capacity. Critically, the sender relaxes the queue between chirps, so the queue never accumulates more than a few packets. Thus, paced chirping escapes the overshoot dilemma, but still pushes enough against any pre-existing flows, so they yield their capacity. The algorithm has been implemented in Linux and shows great promise from initial evaluation. Work so far has set aside numerous issues that are all important, but not central to proving the concept, e.g. handling delayed ACKs, losses, ECN marking, reordering, variable rate links, etc, The work and the code is being published at this stage to seek review and collaboration around this promising direction.
Tyrosine Kinas Inhibitor and Fertility Mini-Review

Introduction The treatment of CML has been revolutionized with the use of competitive inhibitor of the Bcr-Abl tyrosine kinase, imatinib mesylate, for about two decades in chronic and accelerated phase [1]. Durable response to imatinib is now achievable in a significant number of patients with CML (#51) [2], which are also tolerable and safe [3]. Imatinib inhibits several tyrosine kinases associated with disease, selectively BCR/ABL in CML patients, c-kit in patients with gastrointestinal stromal tumors, and platelet derived growth factor receptor (PDGF-R) in patients with certain myeloproliferative disorders and dermatofibrosarcoma protuberans [4,5]. Most patients appear to tolerate imatinib well, but the potential consequence of the drug on developing fetus is still obscure.
Characterization of Memory Impairment Following Closed-Head Injury in Children Using the Rey Auditory Verbal Learning Test (AVLT)

Memory impairment following closed-head injury (CHI) in children is well documented. Characterization of the memory deficits of children with CHI could contribute to the prediction of academic performance and rehabilitation of these children. Twenty-five children who sustained closed-head injury and 25 matched controls were administered the Rey Auditory Verbal Learning Test (AVLT). The advantage of this memory test is that a number of memory components are measured simultaneously, thus enabling us to study the relations between different aspects of memory within the same patient sample. The findings indicate that the Rey AVLT is a good test for characterization of impaired verbal memory in children following CHI. Transformation of scores derived from the Rey AVLT to Z-scores enables us to determine the relative effect of CHI in children on different memory scores. Raw scores were more vulnerable than relational ones, derived as the difference between two raw scores (e.g., learning, Trial 5−1), to closed-head injury in children, and scores reflecting word span were the least vulnerable. The results are discussed in terms of the possible contribution of the frontal lobes, which are frequently affected in closed-head injuries, to memory performance.
2 nd Micro-Expression Grand Challenge ( MEGC )

The previous Cross-DB challenge in the 1st MEGC [1] used a combination of 2 datasets (CASME II and SAMM), with objective class labels as proposed in [2]. In this 2nd MEGC, the Cross-DB challenge increases its coverage to include the classic SMIC dataset, which is one of the earliest spontaneous micro-expression dataset to be created. To enable all three datasets to be used together, a common reduced set of emotion classes are used, with appropriate mappings from their original emotion classes.
1 APPLICATION OF DATA MINING TECHNIQUES FOR ANALYZING ROAD TRAFFIC INCIDENTS A CASE STUDY OF LIBYA ’ S ROAD TRAFFIC

This paper aims to present the proposed theory to control the traffic management with the application of Data Mining (DM) functionalities by combining intelligent agent based system. A case study was conducted to illustrate the efficiency of Cluster Analysis one of a Data Mining functionalities in combination with the Intelligent Agent Based System. The traffic in all the developed and under development countries is regularized by traffic lights in which most of the traffic lights are based on a fixed cycle protocol. In this paper the causes of accidents and a proposal to avoid the them is presented from DM perspective. The results of this research shows that the use of Data Mining functionalities by combined with various techniques holds high potential to provide Intelligent Transportation System to control and to avoid possible accidents.
Practice of Epidemiology Mediation Analysis for Health Disparities Research

Social epidemiologists often seek to determine the mechanisms that underlie health disparities. This work is typ-ically based on mediation procedures that may not be justified with exposures of common interest in social epidemiology. In this analysis, we explored the consequences of using standard approaches, referred to as the difference and generalized product methods, when mediator-outcome confounders are associated with the exposure. We compared these with inverse probability-weighted marginal structural models, the structural transformation method, doubly robust g-estimation of a structural nested model, and doubly robust targeted minimum loss-based estimation. We used data on 900,726 births from 2003 to 2007 in the Penn Moms study, conducted in Pennsylvania, to assess the extent to which breastfeeding prior to hospital discharge explained the racial disparity in infant mortality. Overall, for every 1,000 births, 3.36 more infant deaths occurred among non-Hispanic black women relative to all other women (95% confidence interval: 2.78, 3.93). Using the difference and generalized product methods to as-sessthe disparity that would remain if everyone breastfed prior to discharge suggested acomplete elimination of the disparity (risk difference = − 0.87 per 1,000 births; 95% confidence interval: − 1.39, − 0.35). In contrast, doubly robust methods suggested a reduction in the disparity to 2.45 (95% confidence interval: 2.20, 2.71) more infant deaths per 1,000 births among non-Hispanic black women. Standard approaches for mediation analysis in health disparities research can yield misleading results.
Evaluation of Amide Proton Transfer-Weighted Imaging for Risk Factors in Stage I Endometrial Cancer: A Comparison With Diffusion-Weighted Imaging and Diffusion Kurtosis Imaging

Background Endometrial cancer (EC) is one of the most common gynecologic malignancies in clinical practice. This study aimed to compare the value of diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), and amide proton transfer-weighted imaging (APTWI) in the assessment of risk stratification factors for stage I EC including histological subtype, grade, stage, and lymphovascular space invasion (LVSI). Methods A total of 72 patients with stage I EC underwent pelvic MRI. The apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), and magnetization transfer ratio asymmetry (MTRasym at 3.5 ppm) were calculated and compared in risk groups with the Mann–Whitney U test or independent samples t-test. Spearman’s rank correlation was applied to depict the correlation of each parameter with risk stratification. The diagnostic efficacy was evaluated with receiver operating characteristic (ROC) curve analysis and compared using the DeLong test. A multivariate logistic regression was conducted to explore the optimal model for risk prediction. Results There were significantly greater MTRasym (3.5 ppm) and MK and significantly lower ADC and MD in the non-adenocarcinoma, stage IB, LVSI-positive, high-grade, and non-low-risk groups (all p < 0.05). The MK and MTRasym (3.5 ppm) were moderately positively correlated with risk stratification as assessed by the European Society for Medical Oncology (EMSO) clinical practice guidelines (r = 0.640 and 0.502, respectively), while ADC and MD were mildly negatively correlated with risk stratification (r = −0.358 and −0.438, respectively). MTRasym (3.5 ppm), MD, and MK were identified as independent risk predictors in stage I EC, and optimal predictive performance was obtained with their combinations (AUC = 0.906, sensitivity = 70.97%, specificity = 92.68%). The results of the validation model were consistent with the above results, and the calibration curve showed good accuracy and consistency. Conclusions Although similar performance was obtained with each individual parameter of APTWI, DWI, and DKI for the noninvasive assessment of aggressive behavior in stage I EC, the combination of MD, MK, and MTRasym (3.5 ppm) provided improved predictive power for non-low-risk stage I EC and may serve as a superior imaging marker.
Effect of lack of vision and of occipital lobectomy upon recovery from unilateral labyrinthectomy in rhesus monkey.

1. We investigated the influence of visual experience upon vestibular compensation in monkeys. Two paradigms were used to elicit vestibular adaptation: artificially imposed motion of images upon the retina during head rotation and unilateral labyrinthectomy. Two groups of animals were investigated: monkeys that underwent a bilateral occipital lobectomy and intact monkeys without a cortical lesion. Occipital lobectomy alone caused only a minor change in the vestibuloocular reflex (VOR); the gain (eye vel/head vel) decreased slightly (10-15%) for high speeds of rotation (180-300 degrees/s). 2. In response to a 4-h period of continuous oscillation of the head (0.25 Hz, 30 degrees/s) with the visual scene made to move in phase with the head (X0 viewing) or out of phase with the head (X2 viewing), intact monkeys showed an average 40% decrease or increase, respectively, of the VOR gain measured in darkness. After occipital lobectomy this adaptive capability was diminished, primarily for increasing the VOR gain after X2 viewing (42% preop to 13% postop). 3. Unilateral labyrinthectomy in either occipital-lobectomized or in otherwise intact monkeys led to a static imbalance with initial (18- to 20-h postlesion) values of spontaneous nystagmus of 22-62 degrees/s measured in darkness and to a dynamic disturbance with an approximately 50% decrease of VOR gain. Compensation for both abnormalities was studied in three groups of animals: previously occipital-lobectomized monkeys kept in the light after labyrinthectomy, intact monkeys kept in the light after labyrinthectomy, and intact monkeys kept in the dark for 4 days after labyrinthectomy and then exposed to light. Spontaneous nystagmus disappeared at the same rate in each group of animals. VOR gain increased in the intact monkeys kept in the light after labyrinthectomy but not in the intact monkeys kept in the dark after labyrinthectomy until they were exposed to light. The occipital-lobectomized monkeys showed some recovery of VOR gain (approximately 25-40%), but only at low speeds of rotation (30-60 degrees/s). Occipital lobectomy performed in monkeys after they had already compensated for a labyrinthectomy caused the VOR gain to drop to values approximately 0.5 but without any recurrence of spontaneous nystagmus. 4. Our results indicate that visual experience after labyrinthectomy is essential for recovery of VOR gain but not for resolution of spontaneous nystagmus. Furthermore, geniculostriate pathways play a major role in providing information about high velocities of retinal image motion that is necessary for the acquisition of VOR gain adaptation. (ABSTRACT TRUNCATED AT 400 WORDS)
Consolidation and maintenance immunotherapy with rituximab improve clinical outcome in patients with B‐cell chronic lymphocytic leukemia

Rituximab in sequential combination with fludarabine (Flu) allowed patients with B‐cell chronic lymphocytic leukemia (B‐CLL) to achieve higher remission rates and longer response duration. Based on their recent experience in indolent non‐Hodgkin lymphomas, in this study, the authors attempted to demonstrate whether consolidation/maintenance therapy with rituximab could prolong the response duration in this patient population.
Adverse outcome pathways and ecological risk assessment: Bridging to population‐level effects

Maintaining the viability of populations of plants and animals is a key focus for environmental regulation. Population‐level responses integrate the cumulative effects of chemical stressors on individuals as those individuals interact with and are affected by their conspecifics, competitors, predators, prey, habitat, and other biotic and abiotic factors. Models of population‐level effects of contaminants can integrate information from lower levels of biological organization and feed that information into higher‐level community and ecosystem models. As individual‐level endpoints are used to predict population responses, this requires that biological responses at lower levels of organization be translated into a form that is usable by the population modeler. In the current study, we describe how mechanistic data, as captured in adverse outcome pathways (AOPs), can be translated into modeling focused on population‐level risk assessments. First, we describe the regulatory context surrounding population modeling, risk assessment and the emerging role of AOPs. Then we present a succinct overview of different approaches to population modeling and discuss the types of data needed for these models. We describe how different key biological processes measured at the level of the individual serve as the linkage, or bridge, between AOPs and predictions of population status, including consideration of community‐level interactions and genetic adaptation. Several case examples illustrate the potential for use of AOPs in population modeling and predictive ecotoxicology. Finally, we make recommendations for focusing toxicity studies to produce the quantitative data needed to define AOPs and to facilitate their incorporation into population modeling. Environ. Toxicol. Chem. 2011;30:64–76. © 2010 SETAC
UNIVERSAL DEPENDENCIES : A PARSING COMPARISON FOR SWEDISH

New annotation approach in the form of Universal Dependencies aims to provide a consistent, languageindependent grammatical annotation scheme for dependency treebanks. However, since UD are not related to any particular language or language group, there is an interest to investigate what impact Universal Dependencies might have on parsing quality in comparison to classic annotation schemes. This article presents results of a parsing study for Swedish, where two independent parsing systems, MaltParser and Stanford NN Parser, were trained and evaluated on the novel UD Treebank as well as on the classic Talbanken non-UD treebank. The results show that Universal Dependencies do not bring any drawbacks to parsing quality, in fact delivering a slight increase of the scores in the evaluation.
Critical Review: In children with hearing loss, is phonological awareness related to literacy development?

This critical review examines whether or not phonological awareness is related to reading development in children with hearing loss. Children with hearing loss often have reading abilities that are below age expectations so determining the relation between phonological awareness and reading ability could guide decisions that clinicians make when developing intervention goals for these children. A literature search using computerized databases was completed resulting in six articles meeting the inclusion criteria. Study designs included: correlational design, case-control design, cohort study and a meta-analysis. The articles were evaluated using a critical appraisal template evaluating the level of evidence, validity and importance of the information included in the article. Overall, the research indicates that phonological awareness is a low-moderate predictor of reading development. This is different than what we might expect for typically developing children. This is further discussed in the review.