Miracle-dz/UniFAR-FTUs huggingface dataset:
In-fiber production of polymeric particles for biosensing and encapsulation

Significance A scalable, chemistry-independent, fluid-instability–mediated in-fiber route for fabricating uniformly sized spherical polymeric particles over a wide span of diameters is developed targeting biomedical applications. Both surface functionalization of solid biocompatible polymer particles for protein–protein interactions and volume encapsulation of a biological material in spherical hollow polymer shells are confirmed, in addition to combining both surface and volumetric functionalities in the same polymeric particle. Polymeric micro- and nanoparticles are becoming a mainstay in biomedicine, medical diagnostics, and therapeutics, where they are used in implementing sensing mechanisms, as imaging contrast agents, and in drug delivery. Current approaches to the fabrication of such particles are typically finely tuned to specific monomer or polymer species, size ranges, and structures. We present a general scalable methodology for fabricating uniformly sized spherical polymeric particles from a wide range of polymers produced with complex internal architectures and continuously tunable diameters extending from the millimeter scale down to 50 nm. Controllable access to such a wide range of sizes enables broad applications in cancer treatment, immunology, and vaccines. Our approach harnesses thermally induced, predictable fluid instabilities in composite core/cladding polymer fibers drawn from a macroscopic scaled-up model called a “preform. ” Through a stack-and-draw process, we produce fibers containing a multiplicity of identical cylindrical cores made of the polymers of choice embedded in a polymer cladding. The instability leads to the breakup of the initially intact cores, independent of the polymer chemistry, into necklaces of spherical particles held in isolation within the cladding matrix along the entire fiber length. We demonstrate here surface functionalization of the extracted particles for biodetection through specific protein–protein interactions, volumetric encapsulation of a biomaterial in spherical polymeric shells, and the combination of both surface and volumetric functionalities in the same particle. These particles used in distinct modalities may be produced from the desired biocompatible polymer by changing only the geometry of the macroscopic preform from which the fiber is drawn.
Self‐Compassion as a Mediator of Mindfulness and Compassion for Others

Mindfulness and self-compassion have garnered interest as tools for improving counselor wellness and performance, yet little is known about how they relate to compassion. Compassion—for oneself and others—is considered important to counselor well-being and effective counseling. In Buddhist and current models, mindfulness is theorized to increase selfcompassion and, subsequently, compassion for others, but the study of these proposed relationships is limited. Using mediation analysis, the author confirmed self-compassion as a mediator of mindfulness and compassion for others among 152 master’s-level counseling interns. Implications and practical application of mindfulness and self-compassion for counselor development are discussed.
NoC contention analysis using a branch-and-prune algorithm

“Many-core” systems based on a Network-on-Chip (NoC) architecture offer various opportunities in terms of performance and computing capabilities, but at the same time they pose many challenges for the deployment of real-time systems, which must fulfill specific timing requirements at runtime. It is therefore essential to identify, at design time, the parameters that have an impact on the execution time of the tasks deployed on these systems and the upper bounds on the other key parameters. The focus of this work is to determine an upper bound on the traversal time of a packet when it is transmitted over the NoC infrastructure. Towards this aim, we first identify and explore some limitations in the existing recursive-calculus-based approaches to compute the Worst-Case Traversal Time (WCTT) of a packet. Then, we extend the existing model by integrating the characteristics of the tasks that generate the packets. For this extended model, we propose an algorithm called “Branch and Prune” (BP). Our proposed method provides tighter and safe estimates than the existing recursive-calculus-based approaches. Finally, we introduce a more general approach, namely “Branch, Prune and Collapse” (BPC) which offers a configurable parameter that provides a flexible trade-off between the computational complexity and the tightness of the computed estimate. The recursive-calculus methods and BP present two special cases of BPC when a trade-off parameter is 1 or ∞, respectively. Through simulations, we analyze this trade-off, reason about the implications of certain choices, and also provide some case studies to observe the impact of task parameters on the WCTT estimates.
Artsonia: A Digital Tool for Enhancing Family Engagement in Perceiving and Responding to Student Artwork

This study focuses on how introducing Artsonia, an online student art gallery, to Narragansett Elementary School families might enhance their response and perception to student artwork. Triangulation was used to collect data from a variety of sources including Artsonia activity, Artsonia comments, Artsonia survey, family interviews, and student-initiated Artsonia discussions. Data demonstrated a high percentage of Narragansett Elementary School families interact with Artsonia in a variety of ways. As a digital tool, Artsonia connected families and friends from across the state and even the country to view and discuss student artwork. Fan club members expressed their gratitude for Artsonia’s ability to view artwork that would otherwise go unknown to extended family members. Through use of the project description feature on Artsonia, the researcher uploaded project descriptions including possible discussion topics to enhance student artwork discussions. Data collected from a variety of sources demonstrates an increased perception of student artwork as project descriptions made learning visible in the art classroom. All participants in the study, including the researcher, families, and students, demonstrate deep interest in Artsonia and its ability to enhance response and perception to student artwork. ARTSONIA: A DIGITAL TOOL FOR STUDENT ARTWORK ! iii TABLE OF CONTENTS Abstract ii List of Tables vii List of Figures viii Chapter One Introduction 1 Background to the Study 2 Personal Interest 2 Existing Research 3 Research Goals 4 Research Questions 4 Conceptual Framework 5 Theoretical Framework 6 Significance of Study 6 Limitations of Study 7 Conclusion 8 Definition of Terms 8 Chapter Two Introduction 9 Research Question 9 Conceptual Framework 9 Review of the Literature 12 ARTSONIA: A DIGITAL TOOL FOR STUDENT ARTWORK ! iv Public Perception of Art Education 12 Visual Thinking Strategies (VTS) 14 Digital Visual Culture 16 Conclusion 18 Chapter Three Design of the Study 20 Research Methods 20 Data Collection 21 Artsonia Activity 22 Artsonia Comments 23 Artsonia Survey 23 Family Interviews 24 Student-Initiated Discussions 25 Data Analysis 26 Unit of Study 26 Artwork Exhibition 27 Classroom-Based Student Artwork Discussion 28 Conclusion 28 Chapter Four Introduction 29 Significance of the Study 29 Bias 31 ARTSONIA: A DIGITAL TOOL FOR STUDENT ARTWORK ! v
Novel Iris Segmentation Method

Iris recognition is a proven, accurate means to identify people. Iris is a part of an eye image. To be possible the uses of this modality, it's indispensable to be detected and segmented. In this paper, we present our both methods: eye image preprocessing by method of Bias-Corrected Fuzzy C-Mean (BCFCM) and iris segmentation based on the active contours “Snake”. The performance of iris recognition system highly depends on segmentation step. For instance, even an effective feature extraction method would not be able to obtain useful information from an iris image that is not segmented properly. This paper presents a straightforward method for segmenting the iris patterns. To prove the performance of our iris method segmentation, we have integrated it in an iris verification system. Experiments are performed using iris images obtained from CASIA V.1 database.
Performance Evaluation of TCP over Routing protocols for Mobile Ad Hoc Networks

In this paper, we investigate the performance of TCP of various (single-hop and multi-hop) routing protocols for mobile ad hoc networks. Using ns-2, we evaluate the TCP window size, throughput and packet delay over a single TCP connection. Our results suggest that these metrics are tightly related, and that TCP performance is tightly coupled with the stability and length of the routing path of each routing protocol.
An efficient solver for volumetric scattering based on fast spherical harmonics transforms

The Helmholtz equation arises in the study of electromagnetic radiation, optics, acoustics, etc. In spherical coordinates, its general solution can be written as a spherical harmonic series which satisfies the radiation condition at infinity, ensuring that the wave is outgoing. The boundary condition at infinity is hard to enforce with a finite element method since a suitable approximation needs to be made within reasonable distance from scatterers. Luckily, the Helmholtz equation can be represented as a Lippmann-Schwinger integral equation which removes the necessity of the boundary approximations and its Green's function can be expanded as a spherical harmonic series which leads to our numerical scheme based on spherical harmonic polynomial transform. In this paper, we present an efficient solver for the Helmholtz equation which costs $O(N\log N)$ operations, where $N$ is the number of the discretization points. We use the fast spherical harmonic transforms which are originally developed in \cite{suda}. The convergence order of the method is tied to the global regularity of the solution. At the lower end, it is second order accurate for discontinuous material properties. The order increases with increasing regularity leading to spectral convergence for globally smooth solutions.
Overexpression of the Epidermal Growth Factor Receptor and Its Ligand Transforming Growth Factor a Is Frequent in Resectable Non-small Cell Lung Cancer but Does Not Predict Tumor Progression' Egfr and Tgf-a Overexpression Was Observed in All Tumor

The epidermal growth factor receptor (EGFR) and its ligand transforming growth factor (TGF) a are hypothesized to form an autocrine growth loop in non-small cell lung cancer (NSCLC) and to play an important role in tumor formation and progression. We studied the association between overexpression of EGFR, TGF-a, or both, and overall survival of patients with resectable NSCLC. Overexpres-sion, defined as >20% of tumor cells staining on immuno-histochemistry, was examined in 96 tumor samples from consecutive patients having resection of previously untreated , well-staged NSCLC who were then followed prospectively (median follow-up, 20.7 months). The expression of three other ligands for EGFR (epidermal growth factor, cripto, and amphiregulin) was examined by Northern analysis to determine whether they might also contribute to a potential growth stimulatory loop. Overall, survival was calculated by the method of Kaplan and Meier, and prog-nostic factors were compared using the log-rank test. Over-expression of EGFR only was found The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertise,nent in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. stages and histological types but was most frequent in squa-mous cell carcinoma. By univariate and multivariate analyses , only tumor stage, not histology or overexpression of EGFR, TGF-a, or both, had a significant impact on overall survival. No expression of epidermal growth factor or cripto was observed at the total cellular RNA level of Northern analysis in tumor or benign lung, suggesting that in NSCLC these ligands may not participate in an autocrine growth stimulatory loop with EGFR. Differential overexpression of amphiregulin in malignant versus normal lung was observed , but this expression pattern did not have a prognostic impact. Thus, EGFR and TGF-a overexpression is frequent in early-stage NSCLC but is not associated with a survival difference. These findings suggest that this growth factor/ receptor loop is more important for lung tumor formation than for tumor progression.
Associations between music and health-related outcomes in adult non-musicians, amateur musicians and professional musicians—Results from a nationwide Danish study

ABSTRACT Previous research in music and health suggests differential long-term health implications for amateur versus professional musicians. The present study focused on (a) self-rated health of adult amateur musicians and professional musicians compared to non-musicians; (b) associations between self-reported music in early childhood homes and choice of staying musically active as adults; (c) associations between involvement in music in one’s early childhood home and adult belief in music as a health resource. Data originated from the Danish Health and Morbidity Survey 2013. The survey was based on a random sample of 25,000 adult Danes (response rate: 57%). Besides standard health-related questions the survey included eight specific music questions. The study revealed significant differences between professional musicians, amateur musicians, and non-musicians and between active and no longer active musicians (both amateurs and professionals). Active professional musicians reported a number of health problems, while active amateur musicians reported a significantly better health than both non-musicians and no longer active amateurs. A clear association was found between singing and playing in childhood and being active as professional or amateur musicians in adult life, and also believing that music activities and experiences can help to stay healthy.
LS104, a non-ATP-competitive small-molecule inhibitor of JAK2, is potently inducing apoptosis in JAK2V617F-positive cells

The activating JAK2V617F mutation has been described in the majority of patients with BCR-ABL-negative myeloproliferative disorders (MPD). In this report, we characterize the small-molecule LS104 as a novel non-ATP-competitive JAK2 inhibitor: Treatment of JAK2V617F-positive cells with LS104 resulted in dose-dependent induction of apoptosis and inhibition of JAK2 autophosphorylation and of downstream targets. Activation of these targets by JAK2 was confirmed in experiments using small interfering RNA. LS104 inhibited JAK2 kinase activity in vitro. This effect was not reversible using elevated ATP concentrations, whereas variation of the kinase substrate peptide led to modulation of the IC50 value for LS104. In line with these data, combination treatment using LS104 plus an ATP-competitive JAK2 inhibitor (JAK inhibitor I) led to synergistically increased apoptosis in JAK2V617F-positive cells. Furthermore, LS104 strongly inhibited cytokine-independent growth of endogenous erythroid colonies isolated from patients with JAK2V617F-positive MPD in vitro, whereas there was no significant effect on growth of myeloid colonies obtained from normal controls. Based on these data, we have recently started a phase I clinical trial of LS104 for patients with JAK2V617F-positive MPDs. To the best of our knowledge, this is the first report on a non-ATP-competitive kinase inhibitor being tested in a clinical trial. [Mol Cancer Ther 2008;7(5):1176–84]
Object-oriented mapping and analysis of urban land use / cover using IKONOS data

There are a number of challenges in applying high-spatial resolution satellite image data for analysis of larger urban areas. This paper explores the use of object-oriented image analysis approaches in mapping urban land cover and land use. The study is based on seven IKONOS images covering the Santa Barbara, CA region. Image processing included geometric and atmospheric correction and image segmentation and classification using spectral and spatial information to separate 9 land cover classes 79 % overall accuracy was achieved with this approach. Specific problems are identified due the spectral and spatial complexity of urban areas, causing confusion between different roof types, roads and bare soil and NPV. Further analysis and refinement of the land cover mapping product (in particular buildings) applied two spatial metrics urban land use and socioeconomic information. The results show the importance, capabilities and challenges of object-oriented approaches in providing detailed and accurate information about the physical structure of urban areas and their relationship to urban land use and socioeconomic characteristics that should be further investigated in related studies.
High Speed 1H Spectroscopic Imaging in Human Brain by Echo Planar Spatial‐Spectral Encoding

We introduce a fast and robust spatial‐spectral encoding method, which enables acquisition of high resolution short echo time (13 ms) proton spectroscopic images from human brain with acquisition times as short as 64 s when using surface coils. The encoding scheme, which was implemented on a clinical 1.5 Tesla whole body scanner, is a modification of an echo‐planar spectroscopic imaging method originally proposed by Mansfield Magn. Reson. Med. 1, 370–386 (1984), and utilizes a series of read‐out gradients to simultaneously encode spatial and spectral information. Superficial lipid signals are suppressed by a novel double outer volume suppression along the contours of the brain. The spectral resolution and the signal‐to‐noise per unit time and unit volume from resonances such as N‐acetyl aspartate, choline, creatine, and inositol are comparable with those obtained with conventional methods. The short encoding time of this technique enhances the flexibility of in vivo spectroscopic imaging by reducing motion artifacts and allowing acquisition of multiple data sets with different parameter settings.
X-ray flares on the UV Ceti-type star CC Eridani: a ``peculiar'' time-evolution of spectral parameters

Context. Weak flares are supposed to be an important heating agent of th e outer layers of stellar atmospheres. However, due to instrumental limitations, only large X-ray flares have been studied in det ail until now. Aims. We used an XMM-Newton observation of the very active BY-Dra type binary star CC Eri in order to investigate the properties of two flares that are weaker than those typically studied in the lit erature. Methods. We performed time-resolved spectroscopy of the data taken with the EPIC-PN CCD camera. A multi-temperature model was used to fit the spectra. We inferred the size of the flaring loops usi ng the density-temperature diagram. The loop scaling laws were applied for deriving physical parameters of the flaring plasma. We also e stimated the number of loops involved in the observed flares. Results. A large X-ray variability was found. Spectral analysis showed that all the regions in the light curve, including the flare segments, are well-described by a 3-T model with variable emission measures but, surprisingly, with constant temperatures (values of 3, 10 and 22 MK). The analysed flares lasted ∼ 3.4 and 7.1 ks, with flux increases of factors 1.5 ‐ 1.9. They oc curred in arcades made of a few tens of similar coronal loops. The size of the flaring loops is much smaller than the distance between the stellar surfaces in th e binary system, and even smaller than the radius of each of the stars. The obtained results are consistent with the following ideas: (i) th e whole X-ray light curve of CC Eri could be the result of a superposition of multiple low-energy flares, and (ii) stellar flares can be scaled-u p versions of solar flares.
Using parallel hierarchical clustering to address spatial big data challenges

Clustering can help to make large datasets more manageable by grouping together similar objects. However, most clustering approaches are unable to scale to very large datasets (e.g. more than 10 million objects). The K-Tree is a data structure and clustering algorithm that has proven to be scalable with large streaming datasets. Here, we apply the K-Tree to spatial data (satellite images) and extend from a single threaded to a multicore environment. We show that the K-Tree is able to cluster larger dataset more efficiently than baseline approaches.
Codon Optimization of the Human Papillomavirus E7 Oncogene Induces a CD8+ T Cell Response to a Cryptic Epitope Not Harbored by Wild-Type E7

Codon optimization of nucleotide sequences is a widely used method to achieve high levels of transgene expression for basic and clinical research. Until now, immunological side effects have not been described. To trigger T cell responses against human papillomavirus, we incubated T cells with dendritic cells that were pulsed with RNA encoding the codon-optimized E7 oncogene. All T cell receptors isolated from responding T cell clones recognized target cells expressing the codon-optimized E7 gene but not the wild type E7 sequence. Epitope mapping revealed recognition of a cryptic epitope from the +3 alternative reading frame of codon-optimized E7, which is not encoded by the wild type E7 sequence. The introduction of a stop codon into the +3 alternative reading frame protected the transgene product from recognition by T cell receptor gene-modified T cells. This is the first experimental study demonstrating that codon optimization can render a transgene artificially immunogenic through generation of a dominant cryptic epitope. This finding may be of great importance for the clinical field of gene therapy to avoid rejection of gene-corrected cells and for the design of DNA- and RNA-based vaccines, where codon optimization may artificially add a strong immunogenic component to the vaccine.
The Infinite Latent Events Model Citation

We present the Infinite Latent Events Model, a nonparametric hierarchical Bayesian distribution over infinite dimensional Dynamic Bayesian Networks with binary state representations and noisy-OR-like transitions. The distribution can be used to learn structure in discrete timeseries data by simultaneously inferring a set of latent events, which events fired at each timestep, and how those events are causally linked. We illustrate the model on a sound factorization task, a network topology identification task, and a video game task.
Task-aware virtual machine scheduling for I/O performance.

The use of virtualization is progressively accommodating diverse and unpredictable workloads as being adopted in virtual desktop and cloud computing environments. Since a virtual machine monitor lacks knowledge of each virtual machine, the unpredictableness of workloads makes resource allocation difficult. Particularly, virtual machine scheduling has a critical impact on I/O performance in cases where the virtual machine monitor is agnostic about the internal workloads of virtual machines. This paper presents a task-aware virtual machine scheduling mechanism based on inference techniques using gray-box knowledge. The proposed mechanism infers the I/O-boundness of guest-level tasks and correlates incoming events with I/O-bound tasks. With this information, we introduce partial boosting, which is a priority boosting mechanism with task-level granularity, so that an I/O-bound task is selectively scheduled to handle its incoming events promptly. Our technique focuses on improving the performance of I/O-bound tasks within heterogeneous workloads by lightweight mechanisms with complete CPU fairness among virtual machines. All implementation is confined to the virtualization layer based on the Xen virtual machine monitor and the credit scheduler. We evaluate our prototype in terms of I/O performance and CPU fairness over synthetic mixed workloads and realistic applications.