Miracle-dz/UniFAR-FTUs huggingface dataset:
A W-Band Frequency Tripler with Integrated Waveguide Filter Matching

A W-band Schottky diode based frequency tripler which uses waveguide resonator filters for low loss impedance matching is presented in this paper. Impedance matching of the diodes is achieved by scaling the external quality factors and adjusting the resonant frequencies of the filter cavities. This removes most of the matching structures from the high loss microstrip circuit to the lower loss waveguide resonators. Here the output frequency of the tripler is set to be 90 GHz with a 10% bandwidth. The simulation shows a conversion loss of 13−13.8 dB in the pass-band with an input power of 13−20 dBm. The measured conversion loss over the pass-band is 13.6−15.8 dB for 17 dBm input power and better than 14 dB at 90 GHz for 13−20 dBm input power.
A BIOMASS-BASED MODEL TO ESTIMATE THE PLAUSIBILITY OF EXOPLANET BIOSIGNATURE GASES

Biosignature gas detection is one of the ultimate future goals for exoplanet atmosphere studies. We have created a framework for linking biosignature gas detectability to biomass estimates, including atmospheric photochemistry and biological thermodynamics. The new framework is intended to liberate predictive atmosphere models from requiring fixed, Earth-like biosignature gas source fluxes. New biosignature gases can be considered with a check that the biomass estimate is physically plausible. We have validated the models on terrestrial production of NO, H2S, CH4, CH3Cl, and DMS. We have applied the models to propose NH3 as a biosignature gas on a “cold Haber World,” a planet with a N2–H2 atmosphere, and to demonstrate why gases such as CH3Cl must have too large of a biomass to be a plausible biosignature gas on planets with Earth or early-Earth-like atmospheres orbiting a Sun-like star. To construct the biomass models, we developed a functional classification of biosignature gases, and found that gases (such as CH4, H2S, and N2O) produced from life that extracts energy from chemical potential energy gradients will always have false positives because geochemistry has the same gases to work with as life does, and gases (such as DMS and CH3Cl) produced for secondary metabolic reasons are far less likely to have false positives but because of their highly specialized origin are more likely to be produced in small quantities. The biomass model estimates are valid to one or two orders of magnitude; the goal is an independent approach to testing whether a biosignature gas is plausible rather than a precise quantification of atmospheric biosignature gases and their corresponding biomasses.
A QSAR Study for Analgesic and Anti‐inflammatory Activities of 5‐/6‐Acyl‐3‐alkyl‐2‐Benzoxazolinone Derivatives

In this publication, QSAR models were developed to predict analgesic and anti‐inflammatory activities of some 2‐benzoxazolinone derivatives using multiple linear regression method. The models were validated internally and externally according to the OECD principles. With the help of these models, pronounced molecular properties of these compounds related to activities were also explored. The developed models demonstrated that hydrophobicity, the number of halogens, and the shape of the molecular structure of these candidate drugs are prominent to represent analgesic and anti‐inflammatory activities. Based on the previously tested compounds and the developed models, 77 new compounds were designed as potential analgesic and anti‐inflammatory drugs. Majority of the newly designed compounds demonstrated promising analgesic and anti‐inflammatory activity.
Primary Care Interventions to Prevent Child Maltreatment: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force

Importance Child maltreatment, also referred to as child abuse and neglect, can result in lifelong negative consequences. Objective To update the evidence on interventions provided in or referable from primary care to prevent child maltreatment for the US Preventive Services Task Force. Data Sources PubMed, Cochrane Library, EMBASE, and trial registries through December 18, 2017; references; experts; literature surveillance through July 17, 2018. Study Selection English-language fair- and good-quality randomized clinical trials that (1) included children with no known exposure to maltreatment and no signs or symptoms of current or past maltreatment, (2) evaluated interventions feasible in a primary care setting or that could result from a referral from primary care, and (3) reported abuse or neglect outcomes or proxies for abuse or neglect (eg, injury with a specificity for abuse, visits to the emergency department, hospitalization). Data Extraction and Synthesis Two reviewers independently assessed titles/abstracts, full-text articles, and study quality; a third resolved conflicts when needed. When at least 3 similar trials were available, random-effects meta-analyses were conducted. Main Outcomes and Measures Direct measures (including reports to child protective services and removal of the child from the home) or proxy measures of abuse or neglect; behavioral, emotional, mental, or physical well-being; and harms. Results Twenty-two trials (33 publications) were included (N = 11 132). No significant association was found between interventions and reports to child protective services within 1 year of intervention completion (10.6% vs 11.9%; pooled odds ratio [OR], 0.94 [95% CI, 0.72-1.23]; 10 trials [n = 2444]) or removal of the child from the home within 1 to 3 years of follow-up (3.5% vs 3.7%; pooled OR, 1.09 [95% CI, 0.16-7.28]; 4 trials [n = 609]). No statistically significant associations were observed between interventions and outcomes for emergency department visits in the short term (<2 years), hospitalizations, child development, school performance, and prevention of death. Nonsignificant results from single trials led to a conclusion of insufficient evidence for injuries, failure to thrive, failure to immunize, school attendance, and other measures of abuse or neglect. Inconsistent results led to a conclusion of insufficient evidence for long-term (≥2 years) outcomes for reports to child protective services (ORs range from 0.48 to 1.13; 3 trials [n = 1690]), emergency department visits (1 of 2 trials reported significant differences) and internalizing and externalizing behavior symptoms (3 of 6 trials reported reductions in behavior difficulties). No eligible trials on harms of interventions were identified. Conclusions and Relevance Interventions provided in or referable from primary care did not consistently prevent child maltreatment. No evidence on harms is available.
The examination of the effects of peer coaching on the practices of pre-service teachers

The purpose of this study was to explore the effects of peer coaching on the classroom practices of pre-service teachers. Participants were four teacher interns from the University of North Carolina Wilmington assigned to a high school in southeastern North Carolina. Participants learned the purpose and parameters of peer coaching by engaging in training prior to the study. Pairs of participants observed classes, collected data, and conferred with their coaching partners. Audiotaped interviews, written reflection questions, and raw data from classroom observations were collected and analyzed. These data were examined for themes relevant to training, key elements of peer coaching, and effects on practices. Analysis of the data revealed that training was adequate and peer coaching was effective in altering the practices of the pre-service teachers. Recommendations for integrating peer coaching in the curriculum and intern experience for pre-service teachers are provided.
Automatic Image Stylization Using Deep Fully Convolutional Networks

Color and tone stylization strives to enhance unique themes with artistic color and tone adjustments. It has a broad range of applications from professional image postprocessing to photo sharing over social networks. Mainstream photo enhancement softwares provide users with predefined styles, which are often hand-crafted through a trial-and-error process. Such photo adjustment tools lack a semantic understanding of image contents and the resulting global color transform limits the range of artistic styles it can represent. On the other hand, stylistic enhancement needs to apply distinct adjustments to various semantic regions. Such an ability enables a broader range of visual styles. In this paper, we propose a novel deep learning architecture for automatic image stylization, which learns local enhancement styles from image pairs. Our deep learning architecture is an end-to-end deep fully convolutional network performing semantics-aware feature extraction as well as automatic image adjustment prediction. Image stylization can be efficiently accomplished with a single forward pass through our deep network. Experiments on existing datasets for image stylization demonstrate the effectiveness of our deep learning architecture.
Tumor angiogenesis : an in vitro study

s/Proceedings * Vidic B. Lichtenbeld H. Role of extracellular matrix protein* in determining poitlnatal patterns ol' the airblood barrier differentiation. Transplacental effect of tobacco «moke metabolites. J Cell Biol. Vul. 107(6) part 3; 769a. * Lichtenbeld HC, Blijham GH. Tumor cell spheroids cause endolhelial cell proliferation in vitro. International Symposium on Angiogenesis, March 13-15. 1991, St. Gallen, Switzerland (abstract nr.l) * Lichtenbeld HC. Blijham GH. Tumor cell spheroids cause endothelial cell proliferation in vitro. NIV Internistendagen 18-19 april 1991. Veldhoven. * Lichtenbeld HC, Blijham GH. Muller AD, Van Dam-Mieras MCE. Tumorangiogenesis: endothelial cell tumor cell interactions. NVVC, 28 november 1991, Amsterdam. n/r 799;. • Lichtenbeld HC. Tumorangiogenesis in vitro. Université de Nancy, 12 Mars 1992, département de pathologique, Nancy, France. • Lichtenbeld HC. Education and actions of the LA1OO association. Proceedings of the Federation of Medical Scientific Societies p.22. 21-22 April 1992. * Lichtenbeld HC, Muller AD, Van Dam-Mieras MCE, Blijham GH. Tumor cell induced vesicle formation on endothelial cells is associated with procoagulant properties. Eur.J.Cell Biol. Suppl.37 (vol.60) 1993. • Lichtenbeld HC, Muller AD. Van Dam-Mieras MCE. Blijham GH. Coagulation disorders in cancer: an in vitro study. Thromb. Haemost. 69(6), 1039, 1993.
A KINEMATIC APPROACH TO ASSESSING ENVIRONMENTAL EFFECTS: STAR-FORMING GALAXIES IN A z ∼ 0.9 SpARCS CLUSTER USING SPITZER 24 μm OBSERVATIONS

We present an infrared study of a z = 0.872 cluster, SpARCS J161314+564930, with the primary aim of distinguishing the dynamical histories of spectroscopically confirmed star-forming members to assess the role of cluster environment. We utilize deep MIPS imaging and a mass-limited sample of 85 spectroscopic members to identify 16 24 μm bright sources within the cluster, and measure their 24 μm star formation rates (SFRs) down to ∼6 M☉ yr−1. Based on their line-of-sight velocities and stellar ages, MIPS cluster members appear to be an infalling population that was recently accreted from the field with minimal environmental dependency on their star formation. However, we identify a double-sequenced distribution of star-forming galaxies among the members, with one branch exhibiting declining specific SFRs with mass. The members along this sub-main sequence contain spectral features suggestive of passive galaxies. Using caustic diagrams, we kinematically identify these galaxies as a virialized and/or backsplash population. Moreover, we find a mix of dynamical histories at all projected radii, indicating that standard definitions of environment (i.e., radius and density) are contaminated with recently accreted interlopers, which could contribute to a lack of environmental trends for star-forming galaxies. A cleaner narrative of their dynamical past begins to unfold when using a proxy for accretion histories through profiles of constant (r/r200) × (Δv/σv); galaxies accreted at earlier times possess lower values of (r/r200) × (Δv/σv) with minimal contamination from the distinct infalling population. Therefore, adopting a time-averaged definition for density (as traced by accretion histories) rather than an instantaneous density yields a depressed specific SFR within the dynamical cluster core.
Accuracy of remotely sensed data: Sampling and analysis procedures

A review and update of the discrete multivariate analysis techniques used for accuracy assessment is given. A listing of the computer program written to implement these techniques is given. New work on evaluating accuracy assessment using Monte Carlo simulation with different sampling schemes is given. The results of matrices from the mapping effort of the San Juan National Forest is given. A method for estimating the sample size requirements for implementing the accuracy assessment procedures is given. A proposed method for determining the reliability of change detection between two maps of the same area produced at different times is given.
Artificial Neural Network Approach for Fault Recognition in a Wastewater Treatment Process

The paper deals with fault detection and recognition for WWTP (Wastewater Treatment Plant). The chosen classifier is a feed-forward neural network. Its input is a high-size vector of measured variables, rather than a small-size compressed feature vector. The output of the network points to the recognized fault class. The test was performed on a simulated WWTP, disturbed by 6 different types of faults (sensors and actuators). The results of the test proved a good ability of the neural network to recognize the faults, in 97.2% of the analysed cases.
Policy Irreversibility and Interest Rate Smoothing

Many empirical studies argue that the inertial behavior of policy rates in industrialized countries can be well explained by a linear partial adjustment version of the Taylor rule. However, the explanatory power of the lagged interest rate has been questioned from various points of view. This paper formally examines a situation in which a central bank has an aversion to frequent policy reversals. Imposing an irreversibility constraint on the control space makes the lagged interest rate a state variable. However, the policy function cannot then be expressed as a partial adjustment form, even if the original Taylor rule would be the correct policy function in the absence of the irreversibility constraint. The simulation results reveal that conventional regression tends to falsely support the functionally misspecified partial adjustment model. This implies that the significant role of the lagged interest may simply reflect the central banks aversion to policy reversal.
Trajectory-control using deep System Identication and Model Predictive Control for Drone Control under Uncertain Load.

Machine learning allows to create complex models if provided with enough data, hence challenging more traditional system identification methods. We compare the quality of neural networks and an ARX model when use in an model predictive control to command a drone in a simulated environment. The training of neural networks can be challenging when the data is scarce or datasets are unbalanced. We propose an adaptation of prioritized replay to system identification in order to mitigate these problems. We illustrate the advantages and limits of this training method on the control task of a simulated drone.
A Novel Integrated Framework for Learning both Text Detection and Recognition

In this paper, we propose a novel integrated framework for learning both text detection and recognition. For most of the existing methods, detection and recognition are treated as two isolated tasks and trained separately, since parameters of detection and recognition models are different and two models target to optimize their own loss functions during individual training processes. In contrast to those methods, by sharing model parameters, we merge the detection model and recognition model into a single end-to-end trainable model and train the joint model for two tasks simultaneously. The shared parameters not only help effectively reduce the computational load in inference process, but also improve the end-to-end text detection-recognition accuracy. In addition, we design a simpler and faster sequence learning method for the recognition network based on a succession of stacked convolutional layers without any recurrent structure, this is proved feasible and dramatically improves inference speed. Extensive experiments on different datasets demonstrate that the proposed method achieves very promising results.
Public prescription drug plan coverage for antiretrovirals and the potential cost to people living with HIV in Canada: a descriptive study.

BACKGROUND Antiretrovirals are expensive and people living with HIV may experience a range of financial burdens when accessing these medications. Our aim was to describe the policy of all Canadian public drug insurance programs for antiretroviral drugs and illustrated how these policies might affect patients' annual out-of-pocket expenditures. METHODS In December 2017, we reviewed public drug programs offering antiretroviral coverage in Canada using government websites to summarize eligibility criteria. We estimated the annual out-of-pocket costs incurred by people living with HIV by applying the cost-sharing rules to 2 hypothetical cases, a single man and a married woman with a net household income of $39 000 and $80 000, respectively, receiving identical prescriptions in different jurisdictions. RESULTS We observed substantial variation in the subsidy provided based mainly on geography, income and age. All 5 federal programs and 6 of 13 provincial and territorial jurisdictions offered universal coverage. In the remaining regions, patients spend up to several thousand dollars annually depending on income (Manitoba), age and income (Ontario, Saskatchewan) and age, income and drug costs (Quebec and Newfoundland and Labrador). We found the greatest variation for our higher income case, with out-of-pocket expenses ranging from 0 to over 50% of the antiretroviral cost. INTERPRETATION There is considerable inter- and intra-jurisdiction heterogeneity in the cost-sharing policies for antiretrovirals across Canada's public drug programs. Policy reforms that either eliminate or set national standards for copayments, deductibles or premiums would minimize variation and could reduce the risk of cost-associated non-adherence to HIV therapy.
Optimization of Battery Energy Storage to Improve Power System Oscillation Damping

This paper studies the optimization of both the placement and controller parameters for Battery Energy Storage Systems (BESSs) to improve power system oscillation damping. For each BESS, dynamic power output characteristics of the power converter interface are modeled considering the power limit, State of Charge limit, and time constant. Then, a black-box mixed-integer optimization problem is formulated and tackled by interfacing time-domain simulation with a mixed-integer Particle Swarm Optimization algorithm. The proposed optimization approach is demonstrated on the New England 39-bus system and a Nordic test system. The optimal results are also verified by time-domain simulation. To improve the applicability and efficiency of the proposed method, seasonal load changes and the minimum number of BESS units to be placed are considered. The proposed controller is also compared to other controllers to validate its performance.
Bandpass Filter Based on Skeleton-like Monobloc Dielectric Pucks Made by Additive Manufacturing

This paper presents a 6th order quasi-elliptic bandpass filter working at 11.75 GHz and based on dielectric hollow resonators (pucks). The resonators and their supporting elements have been fabricated altogether in a single part using ceramic (Alumina) additive manufacturing. This part is simply placed in the filter metal housing and therefore limits the number of pieces to be assembled. An important aspect of this work is that no specific, and potentially lossy, third materials (supports, glue) are needed. This assembly route easily allows the dielectric resonators to be placed in the middle of their cavities in order to maximize their Q factor. The proposed principle has been experimentally validated using, for the fast prototyping of this proof of concept, metallized and low cost plastic 3D printing
D3.2.1 Usage Tracking for Ontology Evolution

The world is constantly changing, and so does required and available knowledge, e.g. stored in Digital Libraries. Knowledge workers heavily rely on the availability and accessibility of knowledge contained in such libraries. The sheer mass of knowledge available today, however, requires sophisticated support for searching and, often considered as equally important, personalization. In SEKT we address these challenges by using ontologies. Ontologies by nature make implicit knowledge explicit, they describe relevant parts of the world and make them machine understandable and processable. To be effective, ontologies need to change possibly as fast as the parts of the world they describe. Change discovery aims at generating implicit requirements by inducing ontology changes from existing data. In this deliverable we focus on usage-driven change discovery. Usage data is a very valuable source of contextual information, based on which the ontology can be modified in order to reflect changes in the real world, We describe a framework, in which ontology evolution and discovering potentially useful changes can be formalized as an optimization problem. We introduce the notion of an evaluation function that allows to measure the quality of an ontology with respect to given criteria. We instantiate the framework for the task of ontology pruning based on usage data, and for the task of collaborative evolution in a multi-user scenario, in which users maintain personalized ontologies. A first case study based on the Bibster system shows very promising results.
A Miniaturized Four-Element MIMO Antenna With EBG for Implantable Medical Devices

A miniaturized four-element multiple-input-multiple-output (MIMO) antenna operating in the band of Industrial, Scientific, and Medical (ISM) 2.4–2.48 GHz is investigated to supply sufficient transmission rate and fight against multipath fading. A single antenna integrates with dual radiators, and each radiator is owned by a pair of subantenna units, greatly diminishing the whole dimensions of the implanted MIMO device. A cross-shaped slot etched in the radiator, a branch extending on the conductor ground, and a pair of electromagnetic band gaps are integrated to achieve high isolation. The proposed MIMO antenna has the compact dimensions of 18.5 mm × 18.5 mm × 1.27 mm. The simulation in the three-layer phantom indicates that the impedance matching is good with a bandwidth of 18.64% (2.14–2.58 GHz) and a maximum gain of –15.18 dBi and the mutual coupling is reduced to less than –15.99 dB at the ISM band. An ex-vivo test was implemented in a fresh pork slab, and the measurement results are well matched with the simulation ones. Health safety considerations and link budget are discussed to validate the antenna's availability in biomedical telemetry, and the envelope correlation coefficient is computed, illustrating the high independence between antenna elements.