Miracle-dz/UniFAR-FTUs huggingface dataset:
The MegaMapper : a z > 2 spectroscopic instrument for the study of Inflation and Dark Energy Thematic Areas

Greg Aldering1, Stephen Bailey1, Charles Baltay31, Christopher Bebek1, Segev BenZvi30, Robert Besuner3, Guillermo Blanc2, Adam S. Bolton20, Mohamed Bouri4, David Brooks24, Elizabeth Buckley-Geer29, Zheng Cai5, Jeffrey Crane2, Arjun Dey20, Peter Doel24, Xiaohui Fan6, Simone Ferraro1, Andreu Font-Ribera24, Gaston Gutierrez29, Julien Guy1, Henry Heetderks3, Dragan Huterer11, Leopoldo Infante2, Patrick Jelinsky3, Matthew Johns2, Dionysios Karagiannis7, Stephen M. Kent29, Alex G. Kim1, Jean-Paul Kneib8, Luzius Kronig8, Nick Konidaris2, Ofer Lahav24, Michael L. Lampton3, Dustin Lang16, Alexie Leauthaud22, Michele Liguori7, Eric V. Linder3, Christophe Magneville9, Paul Martini19, Mario Mateo11, Patrick McDonald1, Christopher J. Miller11, John Moustakas27, Adam D. Myers21, John Mulchaey2, Jeffrey A. Newman14, Peter E. Nugent1, Nathalie Palanque-Delabrouille9, Nikhil Padmanabhan31, Anthony L. Piro2, Claire Poppett3, Jason X. Prochaska22, Anthony R. Pullen18, David Rabinowitz31, Solange Ramirez2, Hans-Walter Rix10, Ashley J. Ross19, Lado Samushia28, Emmanuel Schaan1, Michael Schubnell11, Uros Seljak1,12,13, Hee-Jong Seo17, Stephen A. Shectman2, Joseph Silber1, Joshua D. Simon2, Zachary Slepian23, Marcelle Soares-Santos15, Greg Tarlé11, Ian Thompson2, Monica Valluri11, Risa H. Wechsler25,26, Martin White6,13, Michael J. Wilson1, Christophe Yèche9, Dennis Zaritsky6
Imaging Tumor Angiogenesis With Contrast Ultrasound and Microbubbles Targeted to (cid:1) v (cid:2) 3

Background —Angiogenesis is a critical determinant of tumor growth and metastasis. We hypothesized that contrast-enhanced ultrasound (CEU) with microbubbles targeted to (cid:1) v -integrins expressed on the neovascular endothelium could be used to image angiogenesis. Methods and Results —Malignant gliomas were produced in 14 athymic rats by intracerebral implantation of U87MG human glioma cells. On day 14 or day 28 after implantation, CEU was performed with microbubbles targeted to (cid:1) v (cid:2) 3 by surface conjugation of echistatin. CEU perfusion imaging with nontargeted microbubbles was used to derive tumor microvascular blood volume and blood velocity. Vascular (cid:1) v -integrin expression was assessed by immunohistochemistry, and microbubble adhesion was characterized by confocal microscopy. Mean tumor size increased markedly from 14 to 28 days (2 (cid:1) 1 versus 35 (cid:1) 14 mm 2 , P (cid:2) 0.001). Tumor blood volume increased by (cid:3) 35% from day 14 to day 28, whereas microvascular blood velocity decreased, especially at the central portions of the tumors. On confocal microscopy, (cid:1) v (cid:2) 3 -targeted but not control microbubbles were retained preferentially within the tumor microcirculation. CEU signal from (cid:1) v (cid:2) 3 -targeted microbubbles in tumors increased significantly from 14 to 28 days (1.7 (cid:1) 0.4 versus 3.3 (cid:1) 1.0 relative units, P (cid:2) 0.05). CEU signal from (cid:1) v (cid:2) 3 -targeted microbubbles was greatest at the periphery of tumors, where (cid:1) v -integrin expression was most prominent, and correlated well with tumor microvascular blood volume ( r (cid:4) 0.86). Conclusions —CEU with microbubbles targeted to (cid:1) v (cid:2) 3 can noninvasively detect early tumor angiogenesis. This technique, when coupled with changes in blood volume and velocity, may provide insights into the biology of tumor angiogenesis and be used for diagnostic applications. ( Circulation . 2003;108:336-341.) echistatin to their shell surface have recently been developed that adhere to the endothelial surface of FGF-2–treated microvessels and to matrigel neovessels. 9 In this study, we hypothesized that microbubbles targeted to (cid:1) v (cid:2) 3 could be used to noninvasively evaluate tumor angiogenesis with ultrasound. To test our hypothesis, targeted imaging of a malignant glioma model in rats was performed and compared with data on tumor blood flow and neovascular blood volume derived from established techniques for CEU perfusion imaging. cannulated with PE50 tubing. CEU of the was performed in the mid-coronal plane using gray-scale pulse-inversion imaging (HDI 5000, Ultra- and a linear-array transducer Transmission and a mechanical were used. The placed at the mid-brain level. Gain settings were opti-mized and kept constant throughout the experiments.
V-band 2-b and 4-b low-loss and low-voltage distributed MEMS digital phase shifter using metal-air-metal capacitors

Low-loss digital distributed phase shifters have been developed using micromachined capacitive shunt switches for V-band applications. Instead or conventional metal-insulator-metal capacitors, high-Q metal-air-metal capacitors were used in series with the microelectromechanical system (MEMS) shunt capacitive switches to minimize the dielectric loss. The operation voltage for the phase shifters was also reduced by applying the bias directly to the MEMS shunt switches through choke spiral inductors. Fabricated 2-b (270/spl deg/) and 4-b (337.5/spl deg/) distributed phase shifters showed low average insertion losses of 2.2 dB at 60 GHz and 2.8 dB at 65 GHz, respectively. The average phase errors for 2-b and 4-b phase shifters were 6.5% and 1.3%, respectively. The return losses are better than 10 dB over a wide frequency range from 40 to 70 GHz. Most of the circuits operated at 15-35-V bias voltages. These phase shifters present promising solution to low-loss integrated phase shifting devices at the V-band and above.
DMD059857 73..81

Renal clearance (CLR), a major route of elimination for many drugs and drug metabolites, represents the net result of glomerular filtration, active secretion and reabsorption, and passive reabsorption. The aim of this study was to develop quantitative structurepharmacokinetic relationships (QSPKR) to predict CLR of drugs or drug-like compounds in humans. Human CLR data for 382 compounds were obtained from the literature. Step-wise multiple linear regression was used to construct QSPKR models for training sets and their predictive performance was evaluated using internal validation (leave-one-out method). All qualified models were validated externally using test sets. QSPKR models were also constructed for compounds in accordance with their 1) net elimination pathways (net secretion, extensive net secretion, net reabsorption, and extensive net reabsorption), 2) net elimination clearances (net secretion clearance, CLSEC; or net reabsorption clearance, CLREAB), 3) ion status, and 4) substrate/inhibitor specificity for renal transporters. We were able to predict 1) CLREAB (Q 2 = 0.77) of all compounds undergoing net reabsorption; 2) CLREAB (Q 2 = 0.81) of all compounds undergoing extensive net reabsorption; and 3) CLR for substrates and/or inhibitors of OAT1/3 (Q = 0.81), OCT2 (Q = 0.85), MRP2/4 (Q = 0.78), P-gp (Q = 0.71), and MATE1/2K (Q = 0.81). Moreover, compounds undergoing net reabsorption/extensive net reabsorption predominantly belonged to Biopharmaceutics Drug Disposition Classification System classes 1 and 2. In conclusion, constructed parsimonious QSPKR models can be used to predict CLR of compounds that 1) undergo net reabsorption/extensive net reabsorption and 2) are substrates and/or inhibitors of human renal
Zuhair Al-Nerabieah, Ettihad Abo Arrag, John C Comisi, Anas Rajab. Effectiveness of a Novel Nano-Silver Fluoride with Green Tea Extract Compared with Silver Diamine Fluoride: A Ran-

1 Pediatric dentistry department, Dental Collage, Damascus University, Al-Mazzeh St. Damascus, Syria. 2 Senior lecturer, Pediatric dentistry department, Dental Collage, Damascus University, Al-Mazzeh St. Damascus, Syria. 3 Associate professor, Restorative Dentistry, Department of Oral Rehabilitation, Medical University of South Carolina, James B. Edwards College of Dental Medicine, Charleston, South Carolina, USA. 4 Associate professor, Organic chemistry department, Faculty of Pharmacy, Syrian private University (SPU), Al-Mazzeh St. Damascus, Syria. International Journal of Dentistry and Oral Science (IJDOS) ISSN: 2377-8075
Glycated hemoglobin level and subsequent mortality among adults in the U.S

This is an uncopyedited electronic version of an article accepted for publication in Diabetes Care. The American Diabetes Association, publisher of Diabetes Care, is not responsible for any errors or omissions in this version of the manuscript or any version derived from it by third parties. The definitive publisherauthenticated version will be available in a future issue of Diabetes Care in print and online at http://care.diabetesjournals. org. Diabetes Care Publish Ahead of Print, published online April 28, 2009
CMAR_A_307166 3991..4002

1Department of Ultrasound, Medical School of Chinese PLA, Beijing, People’s Republic of China; 2Department of Ultrasound, The First Medical Center Chinese PLA General Hospital, Beijing, People’s Republic of China; 3Department of Pathology, The First Medical Center, Chinese PLA General Hospital, Beijing, People’s Republic of China Purpose: Differentiation between follicular thyroid carcinomas (FTCs) and follicular thyroid adenomas (FTAs) is difficult and the sonographic features of FTC are not yet fully established. The purpose of this study is to explore the sonographic features of FTC and the value of sonography in differentiating FTCs from FTAs. Patients and Methods: A total of 28 pathologically proven FTCs and 53 FTAs in 78 patients who were performed thyroid surgery were included in this retrospective study. The sonographic features of each tumor including an interrupted halo, satellite nodule(s) with or without halo ring, local irregularity of margin and cluster of grapes sign were evaluated. A mode image of FTC halo was built up in our study. The frequencies of the sonographic features were compared by chi-square test or Fisher exact test between FTCs and FTAs. The relative risk of malignancy was assessed by logistic regression analysis. Results: Logistic regression analysis showed that a thick, irregular and/or interrupted halo with or without satellite nodule(s), hypoechoic or marked hypoechoic echogenicity, a predominantly solid pattern, cluster of grapes sign, micro-or macro-calcifications, rim calcifications correlated with significant increases in relative risk for FTCs (odds ratio 11.48 (1.37–96.56), 6.74 (1.05–43.30), 17.51 (1.78–172.53), 9.55 (1.44–63.46), 9.36 (1.25–70.15) and 17.45 (1.04–292.65), respectively, p<0.05). Two new sonographic features, an interrupted halo and satellite nodule(s) with or without halo ring, can only be found in FTCs. Conclusion: An interrupted halo and satellite nodule(s) with or without halo ring are specific sonographic features for FTCs. Sonography could play a role in differentiating follicular thyroid carcinoma from adenoma.
Simulation Based Comparative Analysis of Resonant Frequency for Tunable Split Ring Resonator in Different Configurations

Split ring resonators (SRR) are being researched for material sensing applications recently. These structures are easily fabricated and offer moderate quality factor (Q) and resonant frequencies (ƒr). These structures provide limited tunability of ƒr although considerable variation in Q has been established. A simulation based analysis has been carried out to find most appropriate and practical configuration of SSRs to provide considerable shift in ƒr. Simulation results show efficacy of vertically stacked SRR vis-à-vis others configurations to achieve tunability. Keywords—split ring resonator, tunability, vertically stacked split rings, complimentary split rings.
Pulse Equivalent Area Based Orientation of a Class of Under- Actuated System under Constraints

A PEA (Pulse Equivalent Area) approach for orientation control of an under actuated pointing device is proposed. The presented work is a sequel to the earlier work done by the authors for the orientation control of the drill machine. The desired orientation is realized through control pulses during specific roll instants. These pulses are generated through single pair of electromagnets mounted on the housing of the pointing device. Due to practical limitation of the system, there is an additional constraint on the actuating signal. The amplitude of the actuating signal is fixed and the Pulse width or duration of the pulse can vary. A discrete equivalent model of pointing device is also developed. A novel approach based on PEA is developed since the exact solution of discrete equivalent model under constraints was not possible. The simulations are included to compare proposed technique with the existing technique developed for similar systems. The performance is also shown under both nominal and parameter variations through Monte Carlo simulations.
StrayCats. II. An Updated Catalog of NuSTAR Stray Light Observations

We present an updated catalog of StrayCats (a catalog of NuSTAR stray light observations of X-ray sources) that includes nearly 18 additional months of observations. StrayCats v2 has an added 53 sequence IDs, 106 rows, and three new identified stray light (SL) sources in comparison to the original catalog. The total catalog now has 489 unique sequence IDs, 862 entries, and 83 confirmed StrayCats sources. Additionally, we provide new resources for the community to gauge the utility and spectral state of the source in a given observation. We have created long-term light curves for each identified SL source using MAXI and Swift/BAT data when available. Further, source extraction regions for 632 identified SL observations were created and are available to the public. In this paper we present an overview of the updated catalog and new resources for each identified StrayCats SL source.
Gender Artifacts in Visual Datasets

Gender biases are known to exist within large-scale visual datasets and can be reflected or even amplified in downstream models. Many prior works have proposed methods for mitigating gender biases, often by attempting to remove gender expression information from images. To understand the feasibility and practicality of these approaches, we investigate what "gender artifacts" exist in large-scale visual datasets. We define a "gender artifact" as a visual cue correlated with gender, focusing specifically on cues that are learnable by a modern image classifier and have an interpretable human corollary. Through our analyses, we find that gender artifacts are ubiquitous in the COCO and OpenImages datasets, occurring everywhere from low-level information (e.g., the mean value of the color channels) to higher-level image composition (e.g., pose and location of people). Further, bias mitigation methods that attempt to remove gender actually remove more information from the scene than the person. Given the prevalence of gender artifacts, we claim that attempts to remove these artifacts from such datasets are largely infeasible as certain removed artifacts may be necessary for the downstream task of object recognition. Instead, the responsibility lies with researchers and practitioners to be aware that the distribution of images within datasets is highly gendered and hence develop fairness-aware methods which are robust to these distributional shifts across groups.
RRT and RRT* Using Vehicle Dynamics

—The trajectory derived from RRT and RRT* is zagged. A holonomic drive is able to follow this trajectory. But real-life vehicle which has dynamical constraints cannot follow this trajectory. In this work, we are going to modify the RRT and RRT* algorithm to generate a trajectory that a vehicle with dynamical constraint can follow. The continuous nature of a steering control and acceleration control in a real-world vehicle introduces the complexity in its model. To introduce constraint in the vehicle’s motion, while reducing the number of control and hence complexity, we are modeling our vehicle as a Dubins car. A Dubins car has only three controls (turning left, turning right, and moving forward) with a ﬁxed velocity which makes our model simple. We use dubins curve (path that dubins car can follow) to trace the trajectory in RRT and RRT* algorithm.
On the Role of Generalization in Transferability of Adversarial Examples

Black-box adversarial attacks designing adversarial examples for unseen neural networks (NNs) have received great attention over the past years. While several successful black-box attack schemes have been proposed in the literature, the underlying factors driving the transferability of black-box adversarial examples still lack a thorough understanding. In this paper, we aim to demonstrate the role of the generalization properties of the substitute classifier used for generating adversarial examples in the transferability of the attack scheme to unobserved NN classifiers. To do this, we apply the max-min adversarial example game framework and show the importance of the generalization properties of the substitute NN in the success of the black-box attack scheme in application to different NN classifiers. We prove theoretical generalization bounds on the difference between the attack transferability rates on training and test samples. Our bounds suggest that a substitute NN with better generalization behavior could result in more transferable adversarial examples. In addition, we show that standard operator norm-based regularization methods could improve the transferability of the designed adversarial examples. We support our theoretical results by performing several numerical experiments showing the role of the substitute network's generalization in generating transferable adversarial examples. Our empirical results indicate the power of Lipschitz regularization methods in improving the transferability of adversarial examples.
Timeline Design Space for Immersive Exploration of Time-Varying Spatial 3D Data

Timelines are common visualizations to represent and manipulate temporal data. However, timeline visualizations rarely consider spatio-temporal 3D data (e.g. mesh or volumetric models) directly. In this paper, leveraging the increased workspace and 3D interaction capabilities of virtual reality (VR), we first propose a timeline design space for 3D temporal data extending the timeline design space proposed by Brehmer et al. [7]. The proposed design space adapts the scale, layout and representation dimensions to account for the depth dimension and how the 3D temporal data can be partitioned and structured. Moreover, an additional dimension is introduced, the support, which further characterizes the 3D dimension of the visualization. The design space is complemented by discussing the interaction methods required for the efficient visualization of 3D timelines in VR. Secondly, we evaluate the benefits of 3D timelines through a formal evaluation (n=21). Taken together, our results showed that time-related tasks can be achieved more comfortably using timelines, and more efficiently for specific tasks requiring the analysis of the surrounding temporal context. Finally, we illustrate the use of 3D timelines with a use-case on morphogenetic analysis in which domain experts in cell imaging were involved in the design and evaluation process.
Open source software: an approach to controlling usage and risk in application ecosystems

The Open Source Software movement has been growing exponentially for a number of years with no signs of slowing. Driving this growth is the wide-spread availability of libraries and frameworks that provide many functionalities. Developers are saving time and money incorporating this functionality into their applications resulting in faster more feature-rich releases. Despite the growing success and the advantages that open source software provides, there is a dark side. Due to its community construction and largely unregulated distribution, the majority of open source software contains bugs, vulnerabilities and other issues making it highly susceptible to exploits. The lack of oversight in general hinders the quality of this software resulting in a trickle down effect in the applications that use it. Additionally, developers who use open source tend to arbitrarily download the software into their build systems but rarely keep track of what they have downloaded resulting in an excessive amount of open source software in their applications and in their ecosystem. This paper discusses processes and practices that users of open source software can implement into their environments that can safely track and control the introduction and usage of open source software into their applications, and report on some preliminary results obtained in an industrial context. We conclude by discussing governance issues related to the disciplined use and reuse of open source and areas for further improvements.
An infinity of black holes

In general relativity (without matter), there is typically a one parameter family of static, maximally symmetric black hole solutions labeled by their mass. We show that there are situations with many more black holes. We study asymptotically anti-de Sitter solutions in six and seven dimensions having a conformal boundary which is a product of spheres cross time. We show that the number of families of static, maximally symmetric black holes depends on the ratio, λ, of the radii of the boundary spheres. As λ approaches a critical value, λ c , the number of such families becomes infinite. In each family, we can take the size of the black hole to zero, obtaining an infinite number of static, maximally symmetric non-black hole solutions. We discuss several applications of these results, including Hawking–Page phase transitions and the phase diagram of dual field theories on a product of spheres, new positive energy conjectures, and more.
Agricultural Plantation Classification using Transfer Learning Approach based on CNN

Hyper-spectral images are images captured from a satellite that gives spatial and spectral information of speciﬁc region.A Hyper-spectral image contains much more number of channels as compared to a RGB image, hence containing more information about entities within the image. It makes them well suited for the classiﬁcation of objects in a snap. In the past years, the eﬃciency of hyper-spectral image recognition has increased signiﬁcantly with deep learning. The Convolution Neural Network(CNN) and Multi-Layer Perceptron(MLP) has demonstrated to be an excellent process of classifying images. However, they suﬀer from the issues of long training time and requirement of large amounts of the labeled data, to achieve the expected outcome. These issues become more complex while dealing with hyper-spectral images. To decrease the training time and reduce the dependence on large labeled data-set, we propose using the method of transfer learning.The features learned by CNN and MLP models are then used by the transfer learning model to solve a new classiﬁcation problem on an unseen dataset. A detailed comparison of CNN and multiple MLP architectural models is performed, to determine an optimum architecture that suits best the objective. The results show that the scaling of layers not always leads to increase in accuracy but often leads to over-ﬁtting, and also an increase in the training time.The training time is reduced to greater extent by applying the transfer learning approach rather than just approaching the problem by directly training a new model on large data-sets, without much aﬀecting the accuracy.