Miracle-dz/UniFAR-FTUs huggingface dataset:
Chapter Eight Building an Urban Teacher Re ' d . Th . d S s 1 ency 1 n a ir pace Partnership

In the fall of 2009, the Dean of the College of Education and Human Services at Montclair State University invited the authors and a third faculty member to re-imagine what teacher education could look like. In response to a Teacher Quality Partnership grant from the U.S. Department of Education's Office of Innovation and Improvement, she charged the faculty team to create a math and science teacher residency program in collaboration with the College's longtime partner, the Newark Public Schools. The resulting urban teacher residency program blends knowledge from the university and from the schools to create a "third space" serving the needs of all parties involved. The defining feature of an urban teacher residency is an extended apprenticeship in a school with a highly skilled mentor teacher (Solomon, 2009). Coursework is often intertwined with residents' classroom experiences, and ~ induction program usually supports teachers in their first years ? f teachtng. Research on urban residency programs indicates higher retention r~tes for graduates compared with graduates from traditional teacher education programs and documents the benefits of the extended and intensive fieldwork component (Papay, West, Fullerton, & Kane, 2012)h Residency
Robust, Unsupervised, and Ubiquitous Pose and Object Information for Robot Action Recognition

—Seamless human-robot collaboration requires accurate real-time activity recognition. For this task, human pose and object-interaction information provide essential context for classifying actions. Unfortunately, high ﬁdelity pose information cannot be derived from RGB video, which constitutes the majority of the world’s available data, and object recognition requires costly annotation. We present a technique to extract and utilize object features with no supervision and reliably use pose information from RGB video data. This technique, the Three-Dimensional Spatio-temporal Attention Mechanisms ( 3 DSAM), innovatively represents pose and object information as evolutions of relevant pixel regions over time. 3 DSAM derives contextually important areas from a video, extracts spatio-temporal features with a 3D convolutional neural network, then leverages a novel soft attention mechanism to enhance real-time, ﬁne-grained action recognition essential for human-robot collaboration. We evaluate our approach on challenging datasets, as well as a speciﬁc case study in human-robot collaboration. We demonstrate that 3 DSAM can achieve state-of-the-art RGB-based classiﬁcation on scenarios essential for action recognition for human-robot collaboration.
Signaling pathways of adipose stem cell-derived exosomes promoting muscle regeneration

Abstract Severe muscle injury is still a challenging clinical problem. Exosomes derived from adipose stem cells (ASC-exos) may be a potential therapeutic tool, but their mechanism is not completely clear. This review aims to elaborate the possible mechanism of ASC-exos in muscle regeneration from the perspective of signal pathways and provide guidance for further study. Literature cited in this review was acquired through PubMed using keywords or medical subject headings, including adipose stem cells, exosomes, muscle regeneration, myogenic differentiation, myogenesis, wingless/integrated (Wnt), mitogen-activated protein kinases, phosphatidylinositol-4,5-bisphosphate 3-kinase/protein kinase B (PI3K/Akt), Janus kinase/signal transducers and activators of transcription, and their combinations. We obtained the related signal pathways from proteomics analysis of ASC-exos in the literature, and identified that ASC-exos make different contributions to multiple stages of skeletal muscle regeneration by those signal pathways.
Assessing Urban Flood Risks: The Critical Role of Dynamic Modeling Current and Future Risks

• Urban communities have a higher risk of flooding than current models suggest, making it more vital than ever to ensure that our pavements, buildings, and infrastructure are built to withstand the stresses of future flooding events. Extreme Climate Events (ECEs) resulting in flooding are among the world’s gravest natural hazards, [1] with surface flooding estimated to be the most serious ECE infrastructure damage risk for 39% of the world’s land area [2]. Climate simulation models suggest a future in which extreme climate events will only become more frequent [3,a]. While flooding from ECEs presents a crucial threat to states and provinces, this risk is amplified in cities. As 55% of the world’s population lives in urban areas, and 80% of global GDP is generated in cities, proper design of infrastructure is needed to protect these economic engines and contribute to their sustainable growth [4]. As this brief will show, urban communities have a higher risk of flooding than current models suggest, making it more vital than ever to ensure that our pavements, buildings, and infrastructure are built to withstand the stresses of future flooding events. The world faces two mounting flood threats: overflowing bodies of water referred to as fluvial or coastal flooding and rain storms overwhelming drainage referred to as pluvial flooding. Even though fluvial flood events tend to capture media coverage, pluvial flooding from rain storms actually causes greater cumulative damage due to its greater frequency [5]. Despite
The COVID−19 Vaccination Campaign and Disinformation on Twitter: The Role of Opinion Leaders and Political Social Media Influencers in the Italian Debate on Green Pass

In Italy, the Twitter debate on the green pass ignited a conflict between mainstream positions in favor of restrictions, and opposite opinions extremely critical of government measures, also characterized by disinformation. Drawing from the classic Katz and Lazarsfeld model of influence, this article investigates the role of opinion leaders as well as that of political social media influencers (PSMIs) in fueling disinformation on the green pass. Thanks to a computational analysis of Twitter contents (4 million+) and the use of critical metrics and social network analysis (SNA), we identified a limited number of influential profiles endorsing critical positions on the green pass. Their interaction networks analysis also showed how both opinion leaders and PSMIs spread disinformation and conspiracy theories through a dissemination strategy aimed at diverting their followers from Twitter toward “below-the-radar” channels (e.g., Rumble), where positions on political issues tend to be more hyper-partisan.
Poster abstract: Characterizing Digital Homelessness

Many social and economic expectations of modern society assume that individuals own a personal computer. When this expectation is not met, individuals must rely on shared, public computers, such as those offered at public libraries to meet these expectations. Numerous inequalities stem from this re-liance, both in the suitability of the public computer for social and economic expectations, and in threats to the security and privacy of exclusively- or primarily-public computer users. To identify and characterize these inequalities, we com-pleted a one year study in multiple libraries to characterize the experiences of public-access internet users. We observed that those users who relied on public access computers because they lacked dedicated, internet enabled home computers faced intersecting and compounding inequalities stemming from the absence of a digital ‘home’. Similarly, while access to library computers is important, their current operation does not provide the social function of a personal computer and thereby disadvantage users reliant on these systems. In light of these similarities, we suggest the term digital homelessness to describe the state of relying primarily or exclusively on public computers. Those experiencing digital homelessness are frequently not accounted for in software design, both for regular utilities and for security and privacy tools. Thus, although a complete answer to digital homelessness requires a multifaceted approach, several of the important problems can be addressed with technical solutions.
High-power subnanosecond beams of runaway electrons and volume discharge formation in gases at atmospheric pressure

A non-local criterion for runaway electrons generation is proposed, which is a universal two-valued dependence of the critical voltage U cr on pd for a certain gas (where p is the pressure and d is the interelectrode distance). This dependence subdivides the (U, pd) plane into an area of efficient electron multiplication and an area in which electrons leave the gas gap without multiplication. Electron beams of subnanosecond pulse duration and an amplitude of hundreds of amperes are generated at atmospheric pressure in various gases. A volume nanosecond discharge with a high specific excitation power was realized without the pre-ionization of the discharge gap by using an additional external source. The role of the electron avalanches propagating from the cathode to the anode in a dense gas was considered.
Rings Characterized by a Class of Modules

ABSTRACT Let ℒ be a class of right R-modules. The notions of ℒ-injectivity and ℒ-flatness are used to investigate right ℒ-Noetherian rings, right ℒ-hereditary rings, and right ℒ-coherent rings. For an almost excellent extension S ≥ R, if either ring is the above-mentioned ring, so is the other. Specializing the class ℒ, some known results can be obtained and extended as corollaries.
Stability of periodic points in piecewise isometries of Euclidean spaces

In this paper we complete the analysis of the stability of periodic points of piecewise isometric systems that are defined in the entire Euclidean space. We focus on the case where the determinant of the matrix ${\rm Id}-R_{w}$ is zero, where $R_{w}$ is the linear part of the return map generated by the periodic point whose coding is made of a countable repetition of the block $w$. The case where the determinant of ${\rm Id}-R_{w}$ is non-zero was studied in Mendes and Nicol (Periodicity and recurrence in piecewise rotations of Euclidean spaces. Int. J. Bif. Chaos, 14(7), 2353–2361) but still the statement is included here for the sake of completeness.
The Effect of Ownership Structure on Firm Value in Property and Real Estate Companies

During the economic crisis, property companies are one of the sectors that can survive during that time. This study was conducted to examine the significant influence of ownership structure on firm value. Ownership structure is represented by managerial ownership, institutional ownership, and foreign ownership. Price to Book Value was used to measure Firm value. Using purposive sampling, 72 property & real estate companies data listed on Indonesia Stock Exchange in 2012-2015, were utilized. The result revealed that overall model was significant with adjusted R2 of 41.8%. However, from the three independent variables, institutional ownership was the only variable that positive and statistically significant with firm value. The result indicates that institutional ownership can strengthen the company control by external parties, through the decreasing of agency cost to achive the expected firm value.
RF / Microwave Interaction with Biological Tissues

Preface. Introduction. 1 Fundamentals of Electromagnetics. 1.1 RF and Microwave Frequency Ranges. 1.2 Fields. 1.3 Electromagnetics. 1.4 RF and Microwave Energy. 1.5 Penetration in Biological Tissues and Skin Effect. 1.6 Relaxation, Resonance, and Display. 1.7 Dielectric Measurements. 1.8 Exposure. References. Problems. 2 RF/Microwave Interaction Mechanisms in Biological Materials. 2.1 Bioelectricity. 2.2 Tissue Characterization. 2.3 Thermodynamics. 2.4 Energy. References. Problems. 3 Biological Effects. 3.1 Absorption. 3.2 Nervous System. 3.3 Cells and Membranes. 3.4 Molecular Level. 3.5 Low-Level Exposure and ELF Components. 3.6 Ear, Eye, and Heart. 3.7 Influence of Drugs. 3.8 Nonthermal, Microthermal, and Isothermal Effects. 3.9 Epidemiology Studies. 3.10 Interferences. 3.11 Radiation Hazards and Exposure Standards. References. Problems 150 4 Thermal Therapy. 4.1 Introduction to Thermotherapy. 4.2 Heating Principle. 4.3 Hyperthermia. 4.4 Method of Thermometry. References. Problems. 5 EM Wave Absorbers Protecting Biological and Medical Environment. 5.1 Foundation of EM Wave Absorbers. 5.2 Classification of Wave Absorbers. 5.3 Fundamental Principle. 5.4 Fundamental Theory of EM Wave Absorbers. 5.5 Application of EM Absorber. 5.6 EM Wave Absorbers Based on Equivalent Transformation Method of Material Constant. 5.7 Method for Improving RF Field Distribution in a Small Room. References. Problems. 6 RF/Microwave Delivery Systems for Therapeutic Applications. 6.1 Introduction. 6.2 Transmission Lines and Waveguides for Medical Applications. 6.3 Antennas. 6.4 RF and Microwave Ablation. 6.5 Perfusion Chamber. 6.6 RF Gastroesophageal Reflux Disease. 6.7 Endometrial Ablation. 6.8 Microwave Measurement Techniques: Examples. 6.9 Future Research. References. Problems. Index.
Model Selection and Estimation in Generalized Additive Models and Generalized Additive Mixed Models.

WANG, DONG. Model Selection and Estimation in Generalized Additive Models and Generalized Additive Mixed Models. (Under the direction of Dr. Daowen Zhang.) In this dissertation, we propose a method of model selection and estimation in generalized additive models (GAMs) for data from a distribution in the exponential family. The linear mixed model representation of the smoothing spline estimators of the nonparametric functions is constructed, where the inverse of the smoothing parameters are treated as extra variance components and the importance of these nonparametric functions is controlled by the induced variance components. By maximizing the penalized quasi-likelihood with the adaptive LASSO, we could effectively select the important nonparametric functions. Approximate EM algorithms are applied to achieve the goal of model selection and estimation. In addition, we also calculate the approximate pointwise frequentist and Bayesian confidence intervals for selected functions. The eigenvalueeigenvector decomposition approach is used to approximate the induced random effects from the nonparametric functions in order to reduce the dimensions of matrices and speed up the computation. In the case of longitudinal data, we apply the generalized additive mixed models (GAMMs) to model the relationship. The subject-specific random effects are introduced to accommodate the correlation among the responses. Similarly, we propose the adaptive LASSO for generalized additive mixed models to perform model selection and estimation. To evaluate the method, we investigate simulation studies and provide real data applications. c ⃝ Copyright 2013 by Dong Wang All Rights Reserved Model Selection and Estimation in Generalized Additive Models and Generalized Additive Mixed Models
A 200 MHz surface acoustic wave resonator mass microbalance

Surface acoustic wave (SAW) piezoelectric sensors typically used by researchers in analytical applications are based on SAW delay lines. We report here the development of a 200 MHz SAW instrument based on a SAW resonator instead of a conventional delay line. The instrument is small, compact and uses two separate 200 MHz resonator crystals which operate in the dual difference mode. The difference frequency stability is better than 55× 10−9 (±1 Hz) which is comparable to a 10 MHz bulk crystal (on an absolute frequency basis) and at least an order of magnitude better than other commercially available SAW delay lines that operate at comparable frequencies. The mass sensitivity is about 9 × 1010 Hz cm2/g. Response to temperature change is found to be about 20 Hz/°C from −30 °C to 30 °C. Response to pressure is found to be linear from 760 to 415 Torr at 3 Hz/Torr. Detection limits for HCl vapors were determined to be in the low ppb range using a SAW resonator coated with triethanolamine.
Sequential dependencies in magnitude scaling of loudness

Ten normally hearing listeners used a programmable sone-potentiometer knob to adjust the level of a 1000-Hz sinusoid to match the loudness of numbers presented to them in a magnitude production task. Three different power-law exponents (0.15, 0.30, and 0.60) and a log-law with equal steps in dB were used to program the sone-potentiometer. The knob settings systematically influenced the form of the loudness function. Time series analysis was used to assess the sequential dependencies in the data, which increased with increasing exponent and were greatest for the log-law. It would be possible, therefore, to choose knob properties that minimized these dependencies. When the sequential dependencies were removed from the data, the slope of the loudness functions did not change, but the variability decreased. Sequential dependencies were only present when the level of the tone on the previous trial was higher than on the current trial. According to the attention band hypothesis [Green and Luce, 1974, Perception & Psychophysics] these dependencies arise from a process similar to selective attention, but observations of rapid adaptation of neurons in the inferior colliculus based on stimulus level statistics [Dean et al., 2005, Nature Neuroscience] would also account for the data. [Supported by NIH]
Multifractal spectra of branching measure on a Galton-Watson tree

If Z is the branching mechanism for a supercritical Galton-Watson tree with a single progenitor and E[ZlogZ] < ∞, then there is a branching measure μ defined on ∂Γ, the set of all paths ξ which have a unique node ξ|n at each generation n. We use the natural metric ρ(ξ,η) = e−n , where n = max{k : ξ|k = η|k}, and observe that the local dimension index is d(μ,ξ) = lim n→∞ log(μB(ξ|n))/(-n) = α = logm, for μ-almost every ξ. Our objective is to consider the exceptional points where the above display may fail. There is a nontrivial ‘thin’ spectrum for ̄d(μ,ξ) when p 1 = P{Z = 1} > 0 and Z has finite moments of all positive orders. Because ̱d(μ,ξ) = a for all ξ, we obtain a ‘thick’ spectrum by introducing the ‘right’ power of a logarithm. In both cases, we find the Hausdorff dimension of the exceptional sets.
A novel biosensor method for surfactant determination based on acetylcholinesterase inhibition

A novel enzyme biosensor based on acetylcholinesterase inhibition for the determination of surfactants in aqueous solutions is described. Acetylcholinesterase-based bioselective element was deposited via glutaraldehyde on the surface of conductometric transducers. Different variants of inhibitory analysis of surfactants were tested, and finally surfactant's concentration was evaluated by measuring initial rate of acetylcholinesterase inhibition. Besides, we studied the effect of solution characteristics on working parameters of the biosensor for direct measurement of acetylcholine and for inhibitory determination of surfactants. The biosensor's sensitivity to anionic and cationic surfactants (0.35 mg l−1) was tested. The high operational stability of the biosensor during determination of acetylcholine (RSD 2%) and surfactants (RSD 11%) was shown. Finally, we discussed the selectivity of the biosensor toward surfactants and other AChE inhibitors. The proposed biosensor can be used as a component of the multibiosensor for ecological monitoring of toxicants.
Large area patterned magnetic nanostructures

Magnetic nanostructures are attracting considerable interest due to their unique properties and potential applications. There are various challenges associated with the fabrication of highly ordered large area magnetic nanostructures and the understanding of their magnetization reversal processes. This review focuses on the use of the deep ultraviolet lithography technique in fabricating arrays of magnetic nanostructures of varying geometrical parameters over a large area. Using resolution enhancement techniques such as alternating phase shift and chrome-less phase shift masks (PSMs), arrays of ferromagnetic nanostructures with lateral dimensions below the conventional resolution limit have been fabricated. Comprehensive investigation of the relationship between the swing amplitude and the pattern size using alternating PSM lithography is presented. Double patterning and double exposure with shifts are used to significantly improve the pattern density and manipulate the magnetic nanostructures. In addition, results of systematic investigations of evolution of magnetic spin states, in-plane anisotropy and magnetostatic interaction in arrays of elongated Ni80Fe20 rings and their derivatives are presented. The magnetization reversal mechanism, the switching field distributions and the transition fields between different magnetic configurations are found to be strongly dependent on the inter-ring spacing, film thickness and any missing segments of the ring. A comprehensive investigation of the spin states and magnetic anisotropy in magnetic antidot nanostructures is also presented. The detailed magnetization reversal reveals a very strong pinning of domain walls in the vicinity of anti-structures, the strength of which was found to be strongly dependent on the anti-structure geometry and field orientation.
The Cavermod Device: Hydrodynamic Aspects and Erosion Tests

The Cavermod (CAVitation ERosion MODel) is an erosion test device first described by Dominguez-Cortazar et al. (1992, 1997). Recently, it was modified in two steps: first by increasing its maximum rotation rate (from 4500 to 8000 rpm) and second by shortening its vapor core (from 156 to 66 mm). This paper plans to present the main results which are obtained in both configurations (long and short vortex) and for slow or rapid' regime of rotation. They mainly concern 1. the hydrodynamic aspects of the vapor core collapse, as deduced from observation of rapid films (evolution of the vortex length, collapse velocity), 2. the erosion patterns produced on metallic targets such as pure aluminium and copper. A second companion paper will present the results of force measurements in both configuration and an attempt to estimate the local erosive pressures.
Taming the thermal emissivity of metals: A metamaterial approach

We demonstrate the possibility of realizing temporally coherent, wide-angle, thermal radiation sources based on the metamaterial properties of metallic gratings. In contrast to other approaches, we do not rely on the excitation of surface waves such as phonon-polaritons, plasmon-polaritons, or guided mode resonances along the grating, nor on the absorption resonances of extremely shallow metallic grating. Instead, we exploit the effective bulk properties of a thick metallic grating below the first diffraction order. We analytically model this physical mechanism of temporally coherent thermal emission based on localized bulk resonances in the grating. We validate our theoretical predictions with full-wave numerical simulations.