Miracle-dz/UniFAR-FTUs huggingface dataset:
A Robust Determination of the Time Delay in 0957+561A, B and a Measurement of the Global Value of Hubble's Constant

Continued photometric monitoring of the gravitational lens system 0957+561A, B in the g and r bands with the Apache Point Observatory (APO) 3.5 m telescope during 1996 shows a sharp g-band event in the trailing (B) image light curve at the precise time predicted in an earlier paper. The prediction was based on the observation of the event during 1995 in the leading (A) image and on a differential time delay of 415 days. This success confirms the so-called short delay, and the absence of any such feature at a delay near 540 days rejects the “long delay” for this system, thus resolving a long-standing controversy. A series of statistical analyses of our light-curve data yield a best-fit delay of 417 ± 3 days (95% confidence interval) and demonstrate that this result is quite robust against variations in the analysis technique, data subsamples, and assumed parametric relationship of the two light curves. Recent improvements in the modeling of the lens system (consisting of a galaxy plus a galaxy cluster) allow us to derive a value of the global value (at z = 0.36) of Hubble's constant H0 using Refsdal's method, a simple and direct (single-step) distance determination based on experimentally verified and securely understood physics and geometry. The result is H0 = 64 ± 13 km s-1 Mpc-1 (for Ω = 1), where this 95% confidence interval is dominantly due to remaining lens model uncertainties. However, it is reassuring that available observations of the lensing mass distribution overconstrain the model and thus provide an internal consistency check on its validity. We argue that this determination of the extragalactic distance scale (10% accurate at 1 σ) is now of comparable quality, in terms of both statistical and systematic uncertainties, to those based on more conventional techniques. Finally, we briefly discuss the prospects for improved H0 determinations using gravitational lenses, and some other possible implications and uses of the 0957+561A, B light curves.
4.1 A 3-phase digitally controlled DC-DC converter with 88% ripple reduced 1-cycle phase adding/dropping scheme and 28% power saving CT/DT hybrid current control

Multiphase DC-DC converters are essential to provide good efficiency over a wide range of load current, especially for today's multicore SoCs, which usually have a wide range of current profile. Active-phase-count (APC) control, as proposed in [1-3], is the key technique that offers the wide load range, and dynamically adjusts the number of phases according to load conditions. However, an APC transition induces a voltage disturbance due to current redistribution among phases. This makes the APC control only suitable for a voltage regulator with large output capacitors beyond 1000μF, or with high switching frequency beyond 10MHz [4] that hardly delivers more than 2A current with a good efficiency. To mitigate the disturbance impact, [2] has proposed adding or dropping a phase slowly, to allow the PID control to gradually redistribute the phase currents. However, the load current may change direction spontaneously before the completion of the transition, leading to deterioration in the transient response. This paper presents a fast APC scheme which performs the transition within 1 switching cycle, and only requires 66μF capacitors to limit the voltage ripple within 10mV, an 88% ripple reduction with respect to the optimal PID-only control. The proposed APC scheme utilizes digital phase current data, which is also needed to determine the optimal phase count [1-3]. However, the A/D conversions consume 3mW, which is 28% of the total power consumption. A continuous-time/discrete-time (CT/DT) hybrid current control architecture is introduced to eliminate the 3mW penalty while producing A/D converted data by time sharing of the analog circuitry in the control loop. Moreover, a fast transient response configuration is designed, offering less than 40mV fluctuation during an 8A load transition and less than 5mV fluctuation during a 2V line transition.
C R ] 1 5 A pr 2 01 9 Selfish Mining in Ethereum

As the second largest cryptocurrency by market capitalization and today’s biggest decentralized platform that runs smart contracts, Ethereum has received much attention from both industry and academia. Nevertheless, there exist very few studies about the security of its mining strategies, especially from the selfish mining perspective. In this paper, we aim to fill this research gap by analyzing selfish mining in Ethereum and understanding its potential threat. First, we introduce a 2-dimensional Markov process to model the behavior of a selfish mining strategy inspired by a Bitcoin mining strategy proposed by Eyal and Sirer. Second, we derive the stationary distribution of our Markov model and compute long-term average mining rewards. This allows us to determine the threshold of computational power that makes selfish mining profitable in Ethereum. We find that this threshold is lower than that in Bitcoin mining (which is 25% as discovered by Eyal and Sirer), suggesting that Ethereum is more vulnerable to selfish mining than Bitcoin.
Reactive Shunt Compensation Planning by Optimal Power Flows and Linear Sensitivities

In this paper is presented a methodology for reactive shunt compensation in power systems. The proposed methodology includes stationary and dynamic analysis. Stationary analysis is based on linear sensitivities of voltage with respect to reactive shunt compensation, and optimal power flows (OPF) with an objective function minimizing the installation of reactive shunt compensation through the power system. Both formulations are applied in order to obtain an optimal-cost based compensation scheme, while nodal voltages are maintained between predefined limits. The steady-state final scheme is evaluated under stability- transient conditions in order to define if the shunt compensation are to be continuous or discrete. The application of the proposed methodology is illustrated by a real-life case developed on a transmission network of the Comisión Federal de Electricidad (CFE), and results of both approaches are compared.
A soft computing classifier based on Fourier descriptors within online robots context

Work in progress implementing a new classifier, based on neural networks, is presented. This classifier includes Fourier descriptors. Some results are shown demonstrating the feasibility of using such a classifier in order to assist the user in the remote manipulation, namely the online robots domain. A comparative study with other previous classifiers, including the analysis of advantages and limitations of this kind of strategies within the online-robots context are addressed in this work.
Procedure cloning: a transformation for improved system-level functional partitioning

Functional partitioning assigns the functions of a system's program-like specification among system components, such as standard-software and custom-hardware processors. We introduce a new transformation, called procedure cloning, that significantly improves functional partitioning results. The transformation creates a clone of a procedure for sole use by a particular procedure caller, so the clone can be assigned to the caller's processor, which in turn improves performance through reduced communication. We define several cloning heuristics that seek to clone the minimum number of procedures, a goal necessary to obtain the best improvements. We highlight experiments comparing our cloning heuristics and showing partition improvements with cloning.
Modeling Opinion Influence with User Dual Identity

Exploring the mechanism that explains how a user's opinion changes under the influence of his/her neighbors is of practical importance (e.g., for predicting the sentiment of his/her future opinion) and has attracted wide attention from both enterprises and academics.Though various opinion influence models have been proposed for opinion prediction, they only consider users' personal identities, but ignore their social identities with which people behave to fit the expectations of the others in the same group. In this work, we explore users' dual identities, including both personal identities and social identities to build a more comprehensive opinion influence model for a better understanding of opinion behaviors. A novel joint learning framework is proposed to simultaneously model opinion dynamics and detect social identity in a unified model. The effectiveness of the proposed approach is demonstrated through the experiments conducted on Twitter datasets
Taking a closer look: using statistical process control to identify patterns of improvement in a quality-improvement collaborative

Background Published reports suggest that there is considerable variation in improvement capacity and capability among participants in quality improvement collaboratives. Generating knowledge about why these complex initiatives do or do not work in different contexts requires both qualitative and quantitative approaches. Time-series analysis using line graphs and statistical process control is a rigorous quantitative approach with relatively unexplored potential in evaluating complex quality improvement interventions. Aim The purpose of this study was to apply and illustrate the use of line graphs and statistical process control to identify variation in improvement among practices participating in the Saskatchewan Chronic Disease Management Collaborative. Methods The authors used line graphs and regression analysis to determine whether improvement occurred at the aggregate level, and small multiples, rational ordering and rational subgrouping to examine differences in the level and rate of improvement among practices. Results Small multiples allowed us to observe qualitative differences in patterns of improvement among practices. Stratifying data for all subgroups on one control chart using rational subgrouping provided quantitative evidence for these differences. Stratification by administrative health region using rational ordering showed consistent differences, indicating that the health region in which the practice was located may play a role in these differences. Results from the study are being used to inform a purposive sampling strategy for interviews with participants to explore why these differences occurred.
Correct Algorithms for the Comparison of Complex Patterns

The comparison of complex patterns, i.e. patterns that are obtained by recursively aggregating other patterns, poses serious challenges because of the different ways the component patterns can be matched. In this paper, we investigate the problem of comparing set of patterns when constraints are imposed on the matching between component patterns. This is motivated by a real world example, namely the retrieval of images in a region-based image retrieval system, where images represent complex patterns that are composed of regions, i.e. base patterns. We present both sequential and index-based exact algorithms for solving the problem, and experimentally evaluate them on a medium-size data set.
Transient analysis of the behaviour of grounding systems consisted by driven rods

Grounding systems in general are of major importance. This is not only because they provide a very low resistance path for the transient currents toward the earth but also due to the fact that they insure a nearly constant potential level for all electric and electronic appliances. The usual grounding systems consist of one or more driven rods connected with one another, horizontal rods, grounding mats, two or three dimensional grids, foundation grounding systems or even a combination of the mentioned systems when extremely low resistance paths are required. This behaviour is evaluated by the impulse impedance of the system varying across time. That way the efficiency of the system is evaluated across the whole time that the phenomenon takes place resulting to a more accurate prediction of its behaviour. The prediction of the behaviour of such systems is thus necessary when those are imposed to transient currents such as lightning or internal faults. Transient currents are usually mathematically modelled by a double exponential function or a triple exponential if more accuracy is demanded. The grounding systems been studied are one driven rod and three driven rods connected in parallel and forming an equilateral triangle. The systems are dealt as a combination of R, L, C elements. A mathematical analysis follows regarding the elements as compound and assuming that, in the case of more than one electrodes, the current is equally divided amongst them. The values of the R, L, C elements are computed by formulas derived from field analysis for each system. Given the mathematical equation of the current, using network analysis, the potential difference between the striking point and remote earth is computed in the frequency domain using Laplace transformation. Inverse transform is then applied giving the equation of the potential difference in the time domain. From that point on, the calculation of the transient resistance versus time is merely a case of simple division. An alternative way of solving the problem suggests that we work in the frequency domain only using Laplace transform for the equation which describes the current. The transient resistance of the system is calculated as a function of frequency and then a inverse transform is applied to give the equation as a function of time. The transient resistance is obtained by the above mentioned analysis for the single driven rod and the three connected rods versus time. The impulse impedance is then depicted on a diagram versus time on which the steady state resistance is shown as well. The diagrams show clearly the high resistivity values for the first μsec decreasing by the time to the steady state levels for infinite time. The outcome clearly supports the opinions of the authors who state that the behaviour of grounding systems can be evaluated using mathematical models instead of making experiments which are time and money consuming. Key-Words: Grounding system, transient impedance, impulse current, impulse impedance, driven rod(s)
Depth-aware Instance Segmentation with a Discriminative Loss Function

This work explores the possibility of incorporating depth information into a deep neural network to improve accuracy of RGB instance segmentation. The baseline of this work is semantic instance segmentation with discriminative loss function [1] and the incorporating method is inspired by the work [2]. The baseline work proposes a novel discriminative loss function with which the semantic network can learn a n-D embedding for all pixels belonging to instances. Embeddings of the same instances are attracted to their own centers while centers of different instance embeddings repulse each other. Two limitations are set for attraction and repulsion, namely the in-margin and out-margin. A post-processing procedure (clustering) is required to infer instance indices from embeddings with an important parameter bandwidth, the threshold for clustering. The contribution of the work in this thesis are several new methods to incorporate depth information into the baseline work. One simple method is adding scaled depth directly to RGB embeddings, which is named as scaling. Through theorizing and experiments, this work also proposes that depth pixels can be encoded into 1-D embeddings with the same discriminative loss function and combined with RGB embeddings. Explored combination methods are fusion and concatenation. Additionally, two depth pre-processing methods are proposed, replication and coloring. From the experimental result, both scaling and fusion lead to significant improvements over baseline work while concatenation contributes more to classes with lots of similarities. Master of Science Thesis Z.Wang
Body image among young females with anorexia nervosa and the structure of body image among their mothers bernadetta Izydorczyk Summary

Aim. A comparative study of body image among young females with anorexia nervosa and their mothers. Method. Contour Drawing Rating Scale – CDRS by J.K Thompson, J. Gray. Results. The results of this research revealed the statistically significant correlation between body image evaluation among mothers and the body perception among their daughters with anorexia nervosa. The correlation refers to the “ideal self” (“what I want to look like”) as well as to the “ought self” (“what I should look like”). both mothers and daughters aspire to the ideal body image. The women’s desired body shape is slimmer than their current figure which conforms to the age-appropriate norms. When evaluating their bodies, both groups of females take into account the social norms concerning appearance. Conclusions. Culturally and socially influenced perception of body can significantly affect the development of identity in adolescent females and young women, leading to disharmony.
A Reed-Solomon Code for Disk Storage, and Efficient Recovery Computations for Erasure-Coded Disk Storage

Reed-Solomon erasure codes provide efficient simple techniques for redundantly encoding information so that the failure of a few disks in a disk array doesn’t compromise the availability of data. This paper presents a technique for constructing a code that can correct up to three errors with a simple, regular encoding, which admits very efficient matrix inversions. It also presents new techniques for efficiently computing the sums of streams of data elements in a finite field, such as is needed in recovering data after a
A Integrated Comprehensive Evaluation Method on Tunnel Surrounding Rock Instability Analysis during Construction

With the analysis on the instability characteristics and inherent complications to tunnel surrounding rock during construction, the uniaxial compressive strength, rock quality indicator, rock integrity coefficient, structural plane intensity coefficient is chosen as the evaluation index about such instability, the decision-making hierarchical mechanism and regularizer matrix is erected on the basis of the integrated entropy information, variation coefficient and similarity coefficient from the above instability decisionmaking matix. Through the reasoning process and reckoning operation, the credibility and variability is obtained for the instability monitoring units, and the system accumulation effect evaluation is established on the overall surrounding rock instability, which finally carries on the overall evaluation about the surrounding rock security. Case shows that the model is provided with the scientific, simple and practical features in the surrounding rock instability operation and security evaluation work, whose result could fully reflect the synthesized stability situation about the surrounding rock. 
The Smc5-Smc6 Complex Regulates Recombination at Centromeric Regions and Affects Kinetochore Protein Sumoylation during Normal Growth

The Smc5-Smc6 complex in Saccharomyces cerevisiae is both essential for growth and important for coping with genotoxic stress. While it facilitates damage tolerance throughout the genome under genotoxin treatment, its function during unperturbed growth is mainly documented for repetitive DNA sequence maintenance. Here we provide physical and genetic evidence showing that the Smc5–Smc6 complex regulates recombination at non-repetitive loci such as centromeres in the absence of DNA damaging agents. Mutating Smc6 results in the accumulation of recombination intermediates at centromeres and other unique sequences as assayed by 2D gel analysis. In addition, smc6 mutant cells exhibit increased levels of Rad52 foci that co-localize with centromere markers. A rad52 mutation that decreases centromeric, but not overall, levels of Rad52 foci in smc6 mutants suppresses the nocodazole sensitivity of these cells, suggesting that the Smc6-mediated regulation of recombination at centromeric regions impacts centromere-related functions. In addition to influencing recombination, the SUMO ligase subunit of the Smc5–Smc6 complex promotes the sumoylation of two kinetochore proteins and affects mitotic spindles. These results suggest that the Smc5–Smc6 complex regulates both recombination and kinetochore sumoylation to facilitate chromosomal maintenance during growth.
Dynamic primitives in the control of locomotion

Humans achieve locomotor dexterity that far exceeds the capability of modern robots, yet this is achieved despite slower actuators, imprecise sensors, and vastly slower communication. We propose that this spectacular performance arises from encoding motor commands in terms of dynamic primitives. We propose three primitives as a foundation for a comprehensive theoretical framework that can embrace a wide range of upper- and lower-limb behaviors. Building on previous work that suggested discrete and rhythmic movements as elementary dynamic behaviors, we define submovements and oscillations: as discrete movements cannot be combined with sufficient flexibility, we argue that suitably-defined submovements are primitives. As the term “rhythmic” may be ambiguous, we define oscillations as the corresponding class of primitives. We further propose mechanical impedances as a third class of dynamic primitives, necessary for interaction with the physical environment. Combination of these three classes of primitive requires care. One approach is through a generalized equivalent network: a virtual trajectory composed of simultaneous and/or sequential submovements and/or oscillations that interacts with mechanical impedances to produce observable forces and motions. Reliable experimental identification of these dynamic primitives presents challenges: identification of mechanical impedances is exquisitely sensitive to assumptions about their dynamic structure; identification of submovements and oscillations is sensitive to their assumed form and to details of the algorithm used to extract them. Some methods to address these challenges are presented. Some implications of this theoretical framework for locomotor rehabilitation are considered.
2 Brief Description of ELmD Notation : ‘ ⊕ ’ : bitwise

In this paper, we provide a security analysis of ELmD: a block cipher based Encrypt-Linear-mix-Decrypt authentication mode. As being one of the second-round CAESAR candidate, it is claimed to provide misuse resistant against forgeries and security against blockwise adaptive adversaries as well as 128-bit security against key recovery attacks. We scrutinize ElmD in such a way that we provide universal forgery attacks as well as key recovery attacks. First, based on the collision attacks on similar structures such as Marble, AEZ, and COPA, we present universal forgery attacks. Second, by exploiting the structure of ELmD, we acquire ability to query to the block cipher used in ELmD. Finally, for one of the proposed versions of ELmD, we mount key recovery attacks reducing the effective key strength by more than 60 bits.
Build Chinese Emotion Lexicons Using A Graph-based Algorithm and Multiple Resources

For sentiment analysis, lexicons play an important role in many related tasks. In this paper, aiming to build Chinese emotion lexicons for public use, we adopted a graph-based algorithm which ranks words according to a few seed emotion words. The ranking algorithm exploits the similarity between words, and uses multiple similarity metrics which can be derived from dictionaries, unlabeled corpora or heuristic rules. To evaluate the adopted algorithm and resources, two independent judges were asked to label the top words of ranking list. It is observed that noise is almost unavoidable due to imprecise similarity metrics between words. So, to guarantee the quality of emotion lexicons, we use an iterative feedback to combine manual labeling and the automatic ranking algorithm above. We also compared our newly constructed Chinese emotion lexicons (happiness, anger, sadness, fear and surprise) with existing counterparts, and related analysis is offered.