Miracle-dz/UniFAR-FTUs huggingface dataset:
SPECTRAL ENERGY DISTRIBUTIONS OF TYPE 1 ACTIVE GALACTIC NUCLEI IN THE COSMOS SURVEY. I. THE XMM-COSMOS SAMPLE

The “Cosmic Evolution Survey” (COSMOS) enables the study of the spectral energy distributions (SEDs) of active galactic nuclei (AGNs) because of the deep coverage and rich sampling of frequencies from X-ray to radio. Here we present an SED catalog of 413 X-ray (XMM-Newton)-selected type 1 (emission line FWHM > 2000 km s−1) AGNs with Magellan, SDSS, or VLT spectrum. The SEDs are corrected for Galactic extinction, broad emission line contributions, constrained variability, and host galaxy contribution. We present the mean SED and the dispersion SEDs after the above corrections in the rest-frame 1.4 GHz to 40 keV, and show examples of the variety of SEDs encountered. In the near-infrared to optical (rest frame ∼8 μm–4000 Å), the photometry is complete for the whole sample and the mean SED is derived from detections only. Reddening and host galaxy contamination could account for a large fraction of the observed SED variety. The SEDs are all available online.
Ascending Stairway Modeling Live Demo : Toward Autonomous Multi-Floor Exploration

Localization and modeling of stairways by mobile robots can enable multi-floor exploration for those platforms capable of stair traversal. No system yet presented is capable of localizing a stairway on a map and estimating its properties, two functions that would enable stairways to be considered as traversable terrain in a path planning algorithm. The system we propose to demonstrate performs detection and modeling of ascending stairways while performing simultaneous localization and mapping. Our system consists of two parts: a computationally efficient detector that leverages geometric cues from depth imagery to detect sets of ascending stairs, and a stairway modeler that uses multiple detections to infer the location and parameters of a stairway that is discovered during exploration. Modeling the stairway as a whole will enable exploration of higher floors of a building by allowing the stairway to be incorporated into path planning by considering it as a portal to new frontiers. Our intended demonstration will highlight the performance of the system in accurate stairway modeling and localization by observing with a mobile robot a set of portable stairs that we will place in the demo area.
Morphological and Molecular Identification of Ticks Infested in Stray Dogs within Nay Pyi Taw Area, Myanmar

| Rhipicephalus sanguineus, the brown dog tick, is the most widespread tick in the world and transmits broad range of pathogens to dogs. The aim of this study was to identify the tick species infested in dogs by using a combination of LM and molecular analysis. A total of 237 tick samples were collected from dogs and identified by using Light Microscope (LM) and molecular technique. Morphological identification revealed that all of tick infestation in dogs was R. sanguineus spp. and 16SrRNA gene of R. sanguineus species sequences analyses proved 100% sequences identitieswhen compared with the reference data in Genbank records. The present studies confirm R. sanguineus is common tick species infesting in dogs within Nay Pyi Taw area.
Key issues with lightning protection research of the large-scale wind farms

The paper summarized the advances and research fronts regarding lightning protection of the wind farms, for which the following aspects were included: the field observation of lightning strikes to wind farms and long air gaps experiments, the physical mechanism of the lightning attachment process, the lightning risk assessment and optimal design of the lightning protection system (LPS), the damage mechanism of wind turbine blade due to the lightning strikes, the electromagnetic transient effect inside wind turbines and the protection methodology, the testing technology for wind turbine LPS, as well as the new challenges for offshore wind farms. Based on the above analysis, five key issues were proposed for future investigations, namely, the rotation effect of wind turbines on distribution of the space charge, the polarity effect of lightning attachment and the physical model of negative leader propagation, the physical mechanism of multiple upward leaders inception and the lightning shielding effect of the wind farms, the damage mechanism of wind turbine blades due to lightning strikes and the dynamic modelling of the blade explosion effect, and the lightning risk assessment and testing methodology for wind turbines. Appropriate addressing of these pending issues will further improve understanding of the lightning physics with wind farms, and also provide feasible and efficient routes to achieve optimal design of the lightning protection system for wind turbine blades.
FROM CORTICAL NEURAL SPIKE TRAINS TO BEHAVIOR: MODELING AND ANALYSIS

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy FROM CORTICAL NEURAL SPIKE TRAINS TO BEHAVIOR: MODELING AND ANALYSIS By Justin Cort Sanchez May 2004 Chair: Jose C. Principe Major Department: Biomedical Engineering Brain machine interface (BMI) design can be achieved by training linear and nonlinear models with simultaneously recorded cortical neural activity and goal directed behavior. Real-time implementation of this technology requires reliable and accurate signal processing models that produce small error variance in the estimated kinematic trajectories. In this dissertation, the mapping performance and generalization of a recurrent multilayer perceptron (RMLP) is compared with standard linear and nonlinear signal processing models for two species of primates and two behavioral tasks. Each modeling approach is shown to have strengths and weaknesses that are compared experimentally. The RMLP approach shows very accurate peak amplitude estimations with small error variance using a parsimonious model topology. To validate and advance the state-of-the-art of this BMI modeling design, it is necessary to understand how the proposed model represents the neural-to-motor mappings. The RMLP is analyzed here and an interpretation of the neural-to-motor solution of this network is built by tracing the
Evolutions in 3D numerical relativity using fixed mesh refinement

We present results of 3D numerical simulations using a finite difference code featuring fixed mesh refinement (FMR), in which a subset of the computational domain is refined in space and time. We apply this code to a series of test cases including a robust stability test, a nonlinear gauge wave and an excised Schwarzschild black hole in an evolving gauge. We find that the mesh refinement results are comparable in accuracy, stability and convergence to unigrid simulations with the same effective resolution. At the same time, the use of FMR reduces the computational resources needed to obtain a given accuracy. Particular care must be taken at the interfaces between coarse and fine grids to avoid a loss of convergence at higher resolutions, and we introduce the use of 'buffer zones' as one resolution of this issue. We also introduce a new method for initial data generation, which enables higher order interpolation in time even from the initial time slice. This FMR system, 'Carpet', is a driver module in the freely available Cactus computational infrastructure, and is able to endow generic existing Cactus simulation modules ('thorns') with FMR with little or no extra effort.
Modul STEM Berbasis Pemecahan Masalah dengan Tema Rumah dome

This study aims to describe in detail the results of the development of a problem-solving STEM module with the theme of the dome house, and explain the results of the improvement after the use of the module. STEM is an approach that combines science, technology, engineering, and mathematics into a single discipline that is able to realize learning by presenting real problems in everyday life. The STEM module based on the problem-solving ability developed raised the theme of the dome house, which has a function as an earthquake-resistant house which was used as a reconstruction of post-earthquake housing and is permanent, economical, and efficient. Solving problems is one part of high-level thinking, as well as a form of action in solving problems that utilize the knowledge they have. Indicator of achievement of problem solving is analyzing the problem, making a plan for its completion, carrying out planning, and checking again. The development method applied is Research and Development. This module is validated by 5 experts, the results show that the module is very feasible to use. The module was tested on research subjects totaling 20 eighth grade students. The results show that the highest increase in students' problem-solving ability after the implementation of the module is the indicator carrying out the plan with n-gain 0.40, while the lowest increase in the indicator understands the problem with n-gain 0.22. Overall, the STEM module that was developed was able to improve the problem solving ability of state Islamic junior high school students.
On the Robust Variance Estimator in Generalised Estimating Equations

The variance matrix of the estimated regression coeecient in Liang and Zeger's gen-eralised estimating equation approach can be consistently estimated by the so-called sandwich or robust estimator. In this note, we propose a modiication to Liang and Zeger's prescription for implementing the robust variance estimator. Analytical and numerical evidence shows the superior performance of our proposal. Some key words: Generalised estimating equationn Generalised linear modell Longitudinal dataa Sandwich estimator.
Theoretical Formulation and Demand Parameters Optimization for a Proposed Extra-Baggage Service

At present, over 3000 airlines across the globe compete with one another in order to attract passengers and cargo forwarders by offering competitive prices. In recent years, airlines have encountered two major problems: the fluctuation in the freight industry and the cargo capacity imbalance on different routes. Further, as anticipated by the International Air Transport Association (IATA), the use of wide-body aircraft will increase to accommodate the increase in passengers. This will lead to an underutilized aircraft belly hold on some routes; a change which dramatically complicates the estimation of aircraft space utilization and pricing strategies. To compensate for this unfilled space, airlines are encouraged to offer more space for passengers’ extra-baggage with a new pricing policy, besides the prepaid baggage allowance. Accordingly, we have formulated a newsvendor based price model to set a new pricing policy for the new service. The model compares the expected profit from traditional cargo allocation with the expected profit of combining cargo and extrabaggage. As the demand is a function of price, the function coefficients values are important factors in computing the extra-baggage price within acceptable ranges. In this manner, we adopted the Taguchi approach to design suitable demand function coefficients. It is concluded that the slope of cargo demand function is the most effective factor in calculating the extra-baggage prices.
DNA Oxidation as Triggered by H3K9me2 Demethylation Drives Estrogen-Induced Gene Expression

Modifications at the N-terminal tails of nucleosomal histones are required for efficient transcription in vivo. We analyzed how H3 histone methylation and demethylation control expression of estrogen-responsive genes and show that a DNA-bound estrogen receptor directs transcription by participating in bending chromatin to contact the RNA polymerase II recruited to the promoter. This process is driven by receptor-targeted demethylation of H3 lysine 9 at both enhancer and promoter sites and is achieved by activation of resident LSD1 demethylase. Localized demethylation produces hydrogen peroxide, which modifies the surrounding DNA and recruits 8-oxoguanine–DNA glycosylase 1 and topoisomeraseIIβ, triggering chromatin and DNA conformational changes that are essential for estrogen-induced transcription. Our data show a strategy that uses controlled DNA damage and repair to guide productive transcription.
Examining students’ perceptions of innovation and entrepreneurship in physics

The joint AAPT and APS PHYS21 report emphasizes preparing students for diverse career paths, including the need for more opportunities to learn innovation and entrepreneurship in physics. To support these changes, research is needed on students’ interest and perceptions of innovation and entrepreneurship, and suggestions for integration into the undergraduate physics experience. We conducted semi-structured focus groups with 20 physics majors around several concepts related to innovation and entrepreneurship: technology, creativity, design, business, communication, and leadership. Emergent and thematic coding was used to analyze students’ responses. Students have a complex view of innovation and entrepreneurship in physics perceiving creativity as closely related to physics, especially in undergraduate research, while business and leadership skills were distinct from physics and closer to engineering. These findings have implications for understanding students’ perceptions of physics as a disciplinary community and field of study, and can assist departments seeking to better support students’ careers.
Adding semantics and context to media resources to enable efficient construction of learning objects

No matter which pedagogical method of delivery is selected by an instructor, there is a need to develop appropriate content for the learner. The content may be original, published or a combination of both. Published material may take many forms, and one form that is rapidly growing in popularity is that of a sharable learning object. Many repositories are being built where learning objects are stored for sharable access, and meta-data is added to give each learning object a context. Crafting a course of study may require a combination of sharable and personal learning objects. In many instances an instructor/facilitator may only require part of a learning object, such as an image, rather that the entire learning object. This paper describes a meta-data model that would standardize the description of a media resource, by tagging the resource with derived and annotated metadata. Further, this would allow the resources to be given-a context for efficient inclusion into a course.
Mathematics Anxiety and Other Psycho Didactic Aspects in University Students

In Slovakia there is no research into mathematical anxiety and its impact on mathematics. Our goal was to create a tool for measuring mathematical anxiety that would be adapted to Slovak conditions. Our research studied the relationship between individual need for cognitive structure and three forms of anxiety (math, state, and trait). The sample comprised 184 students of two specializations from the Faculty of Education (63 students of primary education – UPV and 121 students of pre-school and elementary education – PEP). We focused on the performance in the Fractions Test, PNS, STAI, and original version of the math anxiety scale (Sarmány-Schuller, & Švecová, 2017). We established the level of the mathematical performance in fractions (MPF) latent variable for every student. We calculated correlations between individual variables (MPF, DFS, RLS, M-Anxiety, SAnxiety, and T-Anxiety) for each group of students. The results show significant differences in the mean values of latent variables between groups (PEP and UPV), UPV students achieved statistically more significant results in MPF. There were no statistically significant differences in other variables. It is noteworthy that UPV students showed lower need for structure and mathematical anxiety but showed higher degree of anxiety. Keyword: math anxiety, personal need for structure, mathematics
Identification of biomarkers and mechanisms of diabetic cardiomyopathy using microarray data.

BACKGROUND The study aimed to uncover the regulation mechanisms of diabetic cardiomyopathy (DCM) and provide novel prognostic biomarkers. METHODS The dataset GSE62203 downloaded from the Gene Expression Omnibus database was utilized in the present study. After pretreatment using the Affy package, differentially expressed genes (DEGs) were identified by the limma package, followed by functional enrichment analysis and protein-protein interaction (PPI) network analysis. Furthermore, module analysis was conducted using MCODE plug-in of Cytoscape, and functional enrichment analysis was also performed for genes in the modules. RESULTS A set of 560 DEGs were screened, mainly enriched in the metabolic process and cell cycle related process. Hub nodes in the PPI network were LDHA (lactate dehydrogenase A), ALDOC (aldolase C, fructose-bisphosphate) and ABCE1 (ATP Binding Cassette Subfamily E Member 1), which were also highlighted in Module 1 or Module 2 and predominantly enriched in the processes of glycolysis and ribosome biogenesis. Additionally, LDHA were linked with ALDOC in the PPI network. Besides, activating transcription factor 4 (ATF4) was prominent in Module 3; while myosin heavy chain 6 (MYH6) was highlighted in Module 4 and was mainly involved in muscle cells related biological processes. CONCLUSIONS Five potential biomarkers including LDHA, ALDOC, ABCE1, ATF4 and MYH6 were identified for DCM prognosis.
Towards Exploiting Background Knowledge for Building Conversation Systems

Existing dialog datasets contain a sequence of utterances and responses without any explicit background knowledge associated with them. This has resulted in the development of models which treat conversation as a sequence-to-sequence generation task (i.e., given a sequence of utterances generate the response sequence). This is not only an overly simplistic view of conversation but it is also emphatically different from the way humans converse by heavily relying on their background knowledge about the topic (as opposed to simply relying on the previous sequence of utterances). For example, it is common for humans to (involuntarily) produce utterances which are copied or suitably modified from background articles they have read about the topic. To facilitate the development of such natural conversation models which mimic the human process of conversing, we create a new dataset containing movie chats wherein each response is explicitly generated by copying and/or modifying sentences from unstructured background knowledge such as plots, comments and reviews about the movie. We establish baseline results on this dataset (90K utterances from 9K conversations) using three different models: (i) pure generation based models which ignore the background knowledge (ii) generation based models which learn to copy information from the background knowledge when required and (iii) span prediction based models which predict the appropriate response span in the background knowledge.
Partial likelihood ratio test for X‐chromosome association models

To determine the genetic association of the X‐chromosome genetic markers and the time to event outcomes, Xu and Hao (2018) develop a partial likelihood model to take the X‐inactivation and inactivation skewness into account. Four different genetic models have been proposed the unified approach of maximizing the partial likelihood (UMP), UMP with random‐effect inactivation skewness (RUMP), the extension of Clayton’s method (CL) and extension of PLINK method (PL). In Page 83 of the paper, the authors proposed a partial likelihood ratio test (LRT):
High Pregnancy, Cord Blood, and Infant Vitamin D Concentrations May Predict Slower Infant Growth

Context The relationship of maternal and infant 25-hydroxyvitamin D concentration [25(OH)D] with infant growth is unclear. Objective Our objective was to explore whether 25(OH)D in pregnancy, umbilical cord blood (UCB), or in infancy was associated with infant growth. Design This study involved 798 healthy infants and their mothers in Finland. We assessed 25(OH)D during pregnancy, from UCB at birth, and from the infant at the age of 12 months. Main Outcome Measures Infant length, weight, length-adjusted weight, and head circumference at 6 and 12 months and midupper-arm circumference at 12 months. Results Of the mothers and infants, 96% and 99% were vitamin D sufficient [25(OH)D ≥50 nmol/L], respectively. Mothers with pregnancy 25(OH)D >125 nmol/L had the shortest, lightest (in weight), and thinnest (in length-adjusted weight) infants at 6 months (P for all < 0.05). For each 10 nmol/L higher UCB 25(OH)D, the infants were 0.03 SD score (SDS) shorter at 6 months (95% CI -0.05 to -0.01), adjusted for birth size, infant 25(OH)D, and parental height. Higher UCB 25(OH)D associated with smaller head circumference at 6 and 12 months (P for all <0.05) but attenuated after adjustments. Mothers with pregnancy 25(OH)D >125 nmol/L had the thinnest infants at 12 months (P = 0.021). For each 10 nmol/L higher infant 25(OH)D, the infants were 0.03 SDS lighter (-0.05 to -0.01) and 0.03 SDS thinner (-0.05 to 0.00) at 12 months. Conclusions Our results suggest that high pregnancy, cord blood, and infant vitamin D concentration may have disadvantageous effects on infant growth.
Identification, characterization, and functional investigation of circular RNAs in subventricular zone of adult rat brain

Adult neural stem cells (NSCs) are able to self‐renew and generate new neural cells. Identifying regulators of NSCs is significant for the development of NSC‐based therapies for neurodegenerative diseases and brain injuries. Recently, circular RNAs (circRNAs) have been characterized in various cell lines and brain tissues, and found to participate in multiple biological processes. However, the expression pattern of circRNAs in adult NSCs is still unknown. Here, the subventricular zone (SVZ) of the lateral ventricle was isolated as the niche of NSCs in adult rat brain for RNA sequencing and the characteristics of circRNAs profiling in both SVZ and cerebral cortex were also investigated. As a result, 29 049 and 31 975 circRNAs were identified in SVZ and cortex, respectively. Among them, 41 were SVZ‐specific and 48 were cortex‐specific. 467 circRNAs were also found to express predominately in SVZ, while the cortex had other 423 circRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the SVZ‐specific circRNAs have close relationship with the regulation of NSC expansion and NSC‐niche interaction, while the other differentially expressed circRNAs might be involved in neural cellular construction and nerve system function. Furthermore, the interactions between circRNAs and microRNAs were also explored, and the result showed that one SVZ‐specific circRNA was capable to competitively bind miR‐138‐5p as a potential derepressive regulator in NSCs proliferation. Hence, our work has laid the foundations to decipher regulation mechanisms of circRNAs in adult NSCs and to develop circRNAs as novel biomarkers for adult NSCs.
Novel Biomarker Approaches in Classic Hodgkin Lymphoma

Abstract Classic Hodgkin lymphoma (cHL) is one of the most common lymphomas in the Western world. Advances in the management of cHL have led to high cure rates exceeding 80%. Nevertheless, relapse or refractory disease in a subset of patients and treatment-related toxicity still represents unsolved clinical problems. The introduction of targeted treatments such as PD-1 blockade and the CD30 antibody drug conjugate, brentuximab vedotin, has broadened treatment options in cHL, emphasizing the critical need to identify biomarkers with the goal to provide rationales for treatment selection, increase effective drug utilization, and minimize toxicity. The unique biology of cHL featuring low abundant tumor cells and numerous nonmalignant immune cells in the tumor microenvironment can provide various types of promising biomarkers related to the tumor cells directly, tumor microenvironment cross-talk, and host immune response. Here, we comprehensively review novel biomarkers including circulating tumor DNA and gene expression–based prognostic models that might guide the ideal management of cHL in the future.