Miracle-dz/UniFAR-FTUs huggingface dataset:
A Compact UWB Antenna with Independently Controllable Notch Bands

A minimally-sized, triple-notched band ultra-wideband (UWB) antenna, useful for many applications, is designed, analyzed, and experimentally validated in this paper. A modified maple leaf-shaped main radiating element with partial ground is used in the proposed design. An E-shaped resonator, meandered slot, and U-shaped slot are implemented in the proposed design to block the co-existing bands. The E-shaped resonator stops frequencies ranging from 1.8–2.3 GHz (Advanced Wireless System (AWS1–AWS2) band), while the meandered slot blocks frequencies from 3.2–3.8 GHz (WiMAX band). The co-existing band ranging from 5.6–6.1 GHz (IEEE 802.11/HIPERLANband) is blocked by utilizing the U-shaped section in the feeding network. The notched bands can be independently controlled over a wide range of frequencies using specific parameters. The proposed antenna is suitable for many applications because of its flat gain, good radiation characteristics at both principal planes, uniform group delay, and non-varying transfer function (S21) for the entire UWB frequency range.
Radio Evolution of Supernova Remnants Including Nonlinear Particle Acceleration: Insights from Hydrodynamic Simulations

We present a model for the radio evolution of supernova remnants (SNRs) obtained by using three-dimensional hydrodynamic simulations coupled with nonlinear kinetic theory of cosmic-ray (CR) acceleration in SNRs. We model the radio evolution of SNRs on a global level by performing simulations for a wide range of the relevant physical parameters, such as the ambient density, supernova (SN) explosion energy, acceleration efficiency, and magnetic field amplification (MFA) efficiency. We attribute the observed spread of radio surface brightnesses for corresponding SNR diameters to the spread of these parameters. In addition to our simulations of Type Ia SNRs, we also considered SNR radio evolution in denser, nonuniform circumstellar environments modified by the progenitor star wind. These simulations start with the mass of the ejecta substantially higher than in the case of a Type Ia SN and presumably lower shock speed. The magnetic field is understandably seen as very important for the radio evolution of SNRs. In terms of MFA, we include both resonant and nonresonant modes in our large-scale simulations by implementing models obtained from first-principles, particle-in-cell simulations and nonlinear magnetohydrodynamical simulations. We test the quality and reliability of our models on a sample consisting of Galactic and extragalactic SNRs. Our simulations give Σ − D slopes between −4 and −6 for the full Sedov regime. Recent empirical slopes obtained for the Galactic samples are around −5, while those for the extragalactic samples are around −4.
Weakly Supervised Stance Learning Using Social-Media Hashtags

Extracting stance from a text is fundamental to automate opinion mining on the web. Recently, many models have been proposed to advance the state-of-the-art. However, most of these models are designed for small hand-labeled datasets that reference a single topic or only a few topics. These models do not generalize to new topics and unseen data. On social media, we have observed that certain hashtags (e.g. ‘climatehoax’) carry stance information. In this research, we propose an approach that uses such hashtags for weak supervision to learn stance in the text. First, we use text sentiment to identify potential hashtags that carry stance information. We call theses hashtags stance-tags. Then, we collect a large amount of Twitter data using these stance-tags. Using the stance of stance-tags, we train two kinds of deeplearning models to predict stance in text that doesn’t necessarily contain hashtags. Further, given a few labeled examples, we model the task of finding stance-tags that are most suitable for stance learning as a multi-armed-bandit problem and find solutions using four optimization strategies. We validate our approach with experiments on a hand-labeled dataset that contains stance on five topics, obtaining results comparable to the state-of-the-art. As many hahstags are used together, they are not completely independent. In the future work section, we propose a search strategy that exploits that similarity
Simulation of the Temperature and Grain Size Dependent Uniaxial Compressive Strength Using3D Wing Crack Model

A number of measurements of uniaxial compressive strength of sea ice and fresh water ice have shown that the strength increases with decreasing temperature. Also the kinetic ice-ice friction increases with decreasing temperature. During compression number of micro-cracks initiate and propagate. Frictional sliding of these cracks play significant role in the deformation process; increase of the strength is a result from the increased friction. In this paper the effect of temperature dependent kinetic friction and the effect of grain diameter on the compressive strength are studied using the new 3D wing crack model. The two dimensional kinematic sliding crack model has been extended into three dimensions to describe the inelastic deformation mechanism. Interaction of cracks and the inhomogeneity of material are considered in the approach. The model has been implemented into finite element software as a user subroutine. The numerical simulations revealed good results compared to experimental results found in the literature. The proposed approach was found to be capable to simulate the increase of the compressive strength with decreasing temperature. In addition the model was found to be capable to simulate the increasing trend of strength as a function of decreasing grain diameter. INTRODUCTION The modelling of brittle failure under compression is one of the greatest challenges in material failure analysis of rock, concrete, ceramics and natural ice. Formation, growth and interaction of (micro) cracks due to the material inhomogeneities and external force is considered to be the mechanism of brittle failure in uniaxial compression (Nemat-Nasser and Horii, 1984). One of the mechanisms proposed for modelling of axial splitting is the sliding or the ‘wing crack’ model. Frictional sliding of internal cracks play significant role in the model. The compressive strength of granular ice is known to be a function of temperature, grain size, strain rate and porosity. At brittle regime temperature and grain size play a significant role; as the grain size or temperature increases the strength decreases (Cole, 1987; Schulson, 1990). The compressive strength increases with decreasing temperature by ~0.3 MPa°C (Schulson and Duval, 2009, p. 245). The strength depends on the grain size through the relationship 1/2 d , where d is the grain diameter (Schulson, 1990). Recent studies have shown that the kinetic ice-ice friction is strongly dependent on temperature and sliding velocity (Makkonen and Tikanmäki, 2014; Schulson and Fortt, 2012). At the velocity range of 10.10 m/s the coefficient of friction decreases with the increasing rate. Similarly the coefficient of friction increases when temperature decreases (Cole, 1987; POAC’15 Trondheim, Norway Proceedings of the 23 International Conference on Port and Ocean Engineering under Arctic Conditions June 14-18, 2015 Trondheim, Norway
Building a classroom-based professional learning community through lesson study: insights from elementary school science teachers

Professional development of in-service teachers requires a sustainable and school-based model which will provide them with opportunities for collaboration in building an environment that supports their capacity-building and pedagogical improvement. In this professional development model, teachers are treated as central to the learning process, allowing them to be engaged in critically assessing their own improvement. A qualitative method was used in this study to explore the positive outcomes of lesson study as a professional development model. Data included transcripts from year-long interaction of the teachers and science education experts taken in various form such as reflective logs, audio and video-tape recordings, non-structured questions and formal written interviews. Analysis was done through the constant comparison method to reveal the coding patterns for the positive impact of lesson study. Teachers’ insights provided positive evidence that lesson study developed them professionally, especially in terms of enhancing their science content knowledge, improving their teaching strategies aligned to inquiry, building a collaborative and professional working environment, and recognizing the significance of post-lesson reflection and discussion. Results therefore show the growing acknowledgement of lesson study as a professional development model for in-service teachers which can possibly be adapted by other Asian and international education settings.
Analytic Enclaves and Analytic Outcome: A Clinical Mystery

I describe a frustrating treatment relationship with a severely traumatized patient and consider what contributed to its successful outcome. Sexually and emotionally abused in childhood, traumatized in adulthood, Dani insistently kept associated memories and affect states sealed off and outside the treatment's scope. Dwelling with me in a deadened therapeutic space dominated by narcissistic imperiousness and apparent obliviousness to the other, Dani seemed unreachable. A single enactment broke into this deadened process and enlivened things, but this shift turned out to be temporary. Yet after years of flat, disengaged process, Dani changed dramatically. Querying the treatment's dynamics, I muse about what happened in our analytic enclave. Despite the clear therapeutic potential of both witnessing and intersubjective exchange in trauma work, there may be times when our tolerance for staying out—for not knowing—is clinically pivotal. By allowing our protected analytic enclave to remain nearly untouched and undisrupted—by keeping trauma out and in this sense un-bridged, this very fragile patient established a nontraumatic relational space within which an alive, hopeful, resilient experience of self imperceptibly coalesced. Earlier versions of this paper were presented at the Winnicott Center, Jerusalem (2010), NYU PostDoctoral Program, New York, (2010), and Division 39 annual meeting, Chicago (2010). I am grateful to Stan Coen, Sue Grand, Adrienne Harris, Margerie Kalb, Stuart Pizer, Annee Ackerman, Leora Trub, and Dafna Fuchs for their very thoughtful feedback on earlier drafts of this essay.
The clinical use of quality-of-life scales in neurological disorders

Objective Quality of life (QoL) is a growing issue in medicine, particularly in the evaluation of rehabilitative care. The concept of QoL is included in and expands the definition of health given by the WHO (World Health Organization) and comprises complete physical, mental, and social well-being. It expresses the degree of satisfaction in various areas as a result of the opportunities that arise during one's lifetime despite the restrictions and impediments that life itself puts forth. The last decade has exponentially increased the number of studies on QoL, although they are still limited. Methods We performed a literature review on the QoL scales used in patients with neurological disorders. Results Recent studies have shown the importance of QoL assessment because standard treatments do not assess the treatment impact felt by the patient. In fact, by understanding the impact of treatment on survival and QoL, one can make a clearer interpretation of the health of the patient. Conclusion This review has adopted an innovative holistic methodological approach, which allowed a global evaluation of the comfort reported by the patients. The scales applied in this study allowed to choose the most suitable therapeutic strategies and programme individual therapeutic treatment.
The smallest eigenvalue distribution in the real Wishart–Laguerre ensemble with even topology

We consider rectangular random matrices of size p × n ? > belonging to the real Wishart–Laguerre ensemble also known as the chiral Gaussian orthogonal ensemble. This ensemble appears in many applications like QCD, mesoscopic physics, and time series analysis. We are particularly interested in the distribution of the smallest non-zero eigenvalue and the gap probability to find no eigenvalue in an interval [ 0 , t ] ? > . While for odd topology &ngr; = n − p ? > explicit closed results are known for finite and infinite matrix size, for even &ngr; > 2 ? > only recursive expressions in p are available. The smallest eigenvalue distribution as well as the gap probability for general even ν is equivalent to expectation values of characteristic polynomials raised to a half-integer power. The computation of such averages is done via a combination of skew-orthogonal polynomials and bosonisation methods. The results are given in terms of Pfaffian determinants both at finite p and in the hard edge scaling limit ( p → ∞ ? > and ν fixed) for an arbitrary even topology ν. Numerical simulations for the correlated Wishart ensemble illustrate the universality of our results in this particular limit. These simulations point to a validity of the hard edge scaling limit beyond the invariant case.
In silico design and assembly of cage molecules into porous molecular materials

Porous materials based on organic cage molecules are an exciting alternative to porous framework materials. Their modular chemistry offers significant structure tunability while their solution processability facilitates their assembly in functional structures in either a crystalline or an amorphous phase. The family of imine cages have been the most widely studied, with several analogues synthesized and tested in applications such noble gas separation, water purification and sensing. The crystals reported so far based on the imine cages obtained by condensation of 1,3,5-triformylbenzene with several vicinal diamines (1,2-diamine) have rather small pore diameters. For example, the benchmark Covalent Cage 3 (CC3) crystal has a pore limiting diameter of 3.65 A, and may experience diffusion limitations hindering its technological applications. The results reported so far suggest that larger cavities are generally not supported in the crystal phase, unless they are stabilized by solvent molecules. In this work, we employ a density functional theory-refined crystal structure prediction approach to perform screening of various CC3 analogues to identify cages that can support stable low density porous structures. Based on the analysis of the crystal energy landscapes, we present a number of synthetically accessible phases that support pore limiting diameters longer than 10 A.
Compact Modeling of Thin-Film Transistors for Flexible Hybrid IoT Design

Editor’s note: Thin-film transistors can be manufactured at low cost and on flexible materials using printing technologies. These characteristics make them very well suited to many IoT applications, particularly wearable electronics. However, circuit and system designers require device models for these new devices. This article describes a SPICE-compatible compact model for a range of thin-film transistors. The authors have validated the models on three thin-film transistor technologies. —Dimitrios Serpanos, University of Patras —Marilyn Wolf, Georgia Institute of Technology
Foreign Investment, Domestic Investment and Economic Growth in China: Does Foreign Investment Crowd in or Crowd out Domestic Investment?

This study assesses the effects of foreign direct investment (FDI) on domestic investment and economic growth, in addition to the extent to which foreign investment either crowds in or crowds out domestic investment in China. Yearly data from 30 Chinese provinces for the period 2000â€“2014 has been used. Pedroni and Kao tests confirmed the existence of long-run relations. We found positive and significant effects of FDI and domestic investment on the economic growth of China using DOLS, FMOLS and GMM estimators; however, domestic investment made a higher contribution to the growth and development of the Chinese economy. As regards crowding in or crowding out, FMOLS showed a neutrality hypothesis, while DOLS and GMM demonstrated that FDI crowded out domestic investment. We conclude that the effects of FDI on domestic investment (in other words, on the economy) are not always favorable.
Endophytic Mycobiota of Jingbai Pear Trees in North China

Endophytic fungi exist in all known plants and play an important role for plant growth and health. As an important forest tree the Jingbai pear (the best quality cultivar of Pyrus ussuriensi Maxim. ex Rupr.) has great ecological as well as economic value in north China. However, the mycobiota of the pear tree is still unknown. In this study, the fungal communities in different organs of the tree and in rhizosphere soils were investigated by Illumina Miseq sequencing of ITS rDNA. For organs, the roots had the highest fungal richness and diversity, while the flowers had the lowest richness and diversity. The results demonstrated that each of the organs investigated harbored a distinctive fungal assemblage. Overall, Ascomycota was the most abundant phyla, followed by Basidiomycota and Zygomycota. Fungal communities from the different soils also differed from each other. The redundancy analysis (RDA) showed that fungal community structure correlated significantly with soil temperature, soil pH, soil nitrogen and soil carbon contents. The results indicate that plant organs, site conditions and soil properties may have important influences on the endophytic fungal community structure associated with Jingbai pear trees.
Qualitative analysis of scanning gate microscopy on epitaxial graphene

We present scanning gate microscopy (SGM) studies of graphene Hall-cross devices where bi-layer graphene (2LG) regions show unexpected signal inversion relative to single-layer graphene (1LG), an observation reproduced via finite element modelling of the current densities. This is attributed to gate-induced charge carrier redistribution between the two layers in 2LG. Hall cross devices were fabricated from epitaxial graphene 6H–SiC(0 0 0 1) and were covered by 1LG/2LG with the area ratio of 85:15%, respectively. Local electric-field sensitivity maps of the devices were obtained in two different measurement geometries using electrical SGM with a conductive tip, where it was observed that the voltage of 2LG islands was inverted relative to anticipated reference maps. Finite element modelling of the current densities and voltage response showed good qualitative agreement with the SGM maps when the effect of the gate was reversed for 2LG. The behaviour is attributed to gate-induced charge carrier redistribution between the two layers in 2LG. The model can be used generally as a tool to predict mixed 1LG/2LG response to electric field. Moreover, regions near the corners of the device show the highest sensitivity when the local electric field was applied to the scanning probe microscopy tip. These regions are capable of detecting highly local electric fields down to 110 kV cm−1.
Likelihood‐Based Volatility Estimators in the Presence of Market Microstructure Noise

Driven by the need for accurate measurement of financial risk using intraday data, high frequency econometric methods have been evolving rapidly, bringing into focus a range of issues that were otherwise unobservable or, in many cases, irrelevant from the perspective of daily and weekly data or lower frequency data. The huge amount of intraday tick-by-tick data provides rich and timely information regarding fluctuations of traded assets and their comovements, which may yield more accurate measurements of volatility and covariance over relatively short horizons than estimates based on years of historical data at low frequency. However, statistical inference with high frequency data presents many challenges. Closer scrutiny of the data reveals the pervasive presence of market microstructure noise, including frictions such as the existence of bid-ask spreads and bounces, the discreteness of price changes, the price impact of some transactions, and informational effects, all of which add volatility to the observed price process. When measuring correlation, the fact that the two assets may not trade or otherwise be observed at exactly the same times, known as observation
Input Encoder Latent Representation Decoder Output

Adversarial attacks are malicious inputs that derail machine-learning models. We propose a scheme to attack autoencoders, as well as a quantitative evaluation framework that correlates well with the qualitative assessment of the attacks. We assess — with statistically validated experiments — the resistance to attacks of three variational autoencoders (simple, convolutional, and DRAW) in three datasets (MNIST, SVHN, CelebA), showing that both DRAW’s recurrence and attention mechanism lead to better resistance. As autoencoders are proposed for compressing data — a scenario in which their safety is paramount — we expect more attention will be given to adversarial attacks on them.
The Sense of Self Inside and Environments Outside: How the Two Grow Together and Become One in Healthy Psychological Development

In contrast to ecopsychology, which segregates a person and environments and assumes that nature automatically provides stimulation which promotes a sense of well-being, I advocate my elaboration of the position of relational psychoanalysis which holds that a person's self and environments, both human and nonhuman, form a dialectical, holistic organization. Based upon research and clinical cases my model proposes that, from the first years of life, a child's experiences with human and nonhuman environments result in the development of embodied metaphors that represent these experiences, give meaning to current environments, and prescribe actions, emotions, and what the person should search for and expect. If these embodied metaphors were constructed during interactions with persons with whom the child had formed attachments that were relatively free of major developmental interferences, this child has the widest range of environments with which to continue negotiating his or her development in future years. I describe a treatment case to illustrate how developmental interferences could result in embodied metaphors which prescribe that the person avoid what human and nonhuman environments have to offer.
On DSGE Models

The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks.