Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of building blocks of an X-band silicon integrated transceiver for FMCW radar

In this paper design of critical building blocks of a 10 GHz silicon integrated circuit of an FMCW radar transceiver is reported. Specifically, design of VCO and LNA is discussed. The targeted transceiver structure will be world's first, commercially available silicon integrated circuit built in SiGe BiCMOS technology and dedicated for low-power radar applications.
Social relationships among adolescents as described in an electronic diary: a mixed methods study

Social relationships among adolescents with mental disorders are demanding. Adolescents with depressive symptoms may have few relationships and have difficulties sharing their problems. Internet may offer reliable and easy to use tool to collect real-time information from adolescents. The aim of this study is to explore how adolescents describe their social relationships with an electronic diary. Mixed methods were used to obtain a broad picture of adolescents’ social relationships with the data gathered from network maps and reflective texts written in an electronic diary. Adolescents who visited an outpatient clinic and used an intervention (N=70) designed for adolescents with signs of depression were invited to use the electronic diary; 29 did so. The quantitative data gathered in the electronic diary were summarized with descriptive statistics, and the qualitative data were categorized using a thematic analysis with an inductive approach. We found that social relationships among adolescents with signs of depression can vary greatly in regards to the number of existing relationships (from lacking to 21) and the quality of the relationships (from trustful to difficult). However, the relationships may change, and the adolescents are also willing to build up their social relationships. Professionals need to be aware of the diversity of adolescents’ social relationships and their need for personalized support.
Ischemic preconditioning attenuates lipid peroxidation and apoptosis in the cecal ligation and puncture model of sepsis

Sepsis and septic shock are are among the major causes of mortality in intensive care units. The lung and kidney are the organs most affected by sepsis. Evidence exists that lipid peroxidation and apoptosis may be responsible for the high mortality due to sepsis. Ischemic preconditioning (IP) is a method for the protection of tissues and organs against ischemia/reperfusion injury by reducing reactive oxygen species levels, lipid peroxidation and apoptosis. In the present study, the effects of IP were investigated in cecal ligation and puncture (CLP)-induced sepsis in rats. The three groups of animals used in the present controlled study were the sham-operated group (sham, n=7), which only underwent a laparotomy; the sepsis group (sepsis, n=7), which underwent cecal ligation and perforation; and the IP + sepsis group (IP+sepsis, n=7), which underwent CLP immediately prior to the application of three cycles of IP to the hind limb. The study was terminated at 6 h after the induction of CLP. Blood, kidney and lung tissue samples were collected for the determination of serum creatinine, blood urea nitrogen (BUN), neutrophil gelatinase-associated lipocalin (NGAL) and lung tissue malondialdehyde (MDA) levels, as well as histological examination. The serum creatinine, plasma NGAL and lung tissue MDA levels in the sepsis group were significantly increased compared with those in the sham and the IP+sepsis groups (P<0.05). Alveolar macrophage counts, histological kidney and lung injury scores, kidney (caspase 3) and lung tissue immuonreactivity (M30) scores in the sepsis group were also significantly increased compared with those in the sham and IP+sepsis groups (P<0.05). The alveolar macrophage count in the IP+sepsis group was increased compared with that in the sham group (P<0.05). In conclusion, IP inhibits lipid peroxidation and attenuates histological injury and apoptosis in the lung and kidney during sepsis.
Rapid Formation of Supermassive Black Hole Binaries in Galaxy Mergers with Gas

Supermassive black holes (SMBHs) are a ubiquitous component of the nuclei of galaxies. It is normally assumed that after the merger of two massive galaxies, a SMBH binary will form, shrink because of stellar or gas dynamical processes, and ultimately coalesce by emitting a burst of gravitational waves. However, so far it has not been possible to show how two SMBHs bind during a galaxy merger with gas because of the difficulty of modeling a wide range of spatial scales. Here we report hydrodynamical simulations that track the formation of a SMBH binary down to scales of a few light years after the collision between two spiral galaxies. A massive, turbulent, nuclear gaseous disk arises as a result of the galaxy merger. The black holes form an eccentric binary in the disk in less than 1 million years as a result of the gravitational drag from the gas rather than from the stars.
LCP MEMS implantable pressure sensor for Intracranial Pressure measurement

Numerous devices for the measurement of Intracranial Pressure (ICP) have been proposed; these include both wired and wireless systems, each of which having their own shortcomings. In this work, the following requirements for minimally invasive measurement of ICP are considered: low infection, biocompatibility, small size, accuracy and ease of use. With these requirements in mind, we propose an implantable ICP sensor based on Microelectromechanical Systems (MEMS). Liquid Crystal Polymer (LCP) is chosen as the biocompatible and flexible structure. This paper describes the significant characteristics of LCP that make it well suited for biomedical applications, and comparisons are made to other polymers in terms of biocompatibility and certification. The proposed LCP pressure sensor has been successfully fabricated, with a membrane area of 2mm × 2mm × 50μm.
Faster Visual Analytics through Pixel-Perfect Aggregation

State-of-the-art visual data analysis tools ignore bandwidth limitations. They fetch millions of records of high-volume time series data from an underlying RDBMS to eventually draw only a few thousand pixels on the screen. In this work, we demonstrate a pixel-aware big data visualization system that dynamically adapts the number of data points transmitted and thus the data rate, while preserving pixel-perfect visualizations. We show how to carefully select the data points to fetch for each pixel of a visualization, using a visualization-driven data aggregation that models the visualization process. Defining all required data reduction operators at the query level, our system trades off a few milliseconds of query execution time for dozens of seconds of data transfer time. The results are significantly reduced response times and a near real-time visualization of millions of data points. Using our pixel-aware system, the audience will be able to enjoy the speed and ease of big data visualizations and learn about the scientific background of our system through an interactive evaluation component, allowing the visitor to measure, visualize, and compare competing visualization-related data reduction techniques.
Enhancement and Characterization of Indoor Propagation Models

Radio signal attenuation and path losses depend on the environment and have been recognized to be difficult to calculate and predict. Past studies of the signal propagation, in an indoor environment have used several models with varying degrees of success and complexity. The aim of this paper is, by a precise description of the analytic model for an indoor environment, and uses it for determining the signal strength in an indoor environment. From the characterization, we propose improving existing channel models by building partitioning technique. Experimental data in this paper were processed in MATLAB. The result shows that the RSS values Vs distance help in determine Path Loss, Free Space path Loss, The results explains the variation in multi-wall model and single wall model, comparison between the empirical model with building partitioned model.
A New Timing Offset Estimation Method for SC-FDE Systems

In SC-FDE (single carrier with frequency domain equalization) systems, timing offset brings ISI (inter-symbol interference). In order to obtain better timing precision in multi-path, a new timing offset estimation method applied to SC-FDE systems is proposed based on the analysis of Schmidl & Cox’s and Minn’s algorithms. By designing new training symbols and introducing corresponding calculation method, performance of timing synchronization can be improved obviously. Finally, three algorithms are compared by computer simulations and the comparison results confirm the effectiveness of the proposed algorithm.
Implementation of IRIS recognition for Securing Online Payment

Iris Recognition is considered as the best among all the biometric security due to its high recognition rate, iris is unique for every human and even uncorrelated for twins. The proposed document focuses on implementing the iris recognition in online payment system by this users identity is more secured. Increase in the credit card fraudulent thefts needs further security for protecting them from phishing attack. The proposed concept also combines the visual cryptography algorithm along with iris recognition. Upcoming mobile phones are to be added with the feature of iris recognition. This method utilizes this feature for its implementation, thereby increasing customer confidence and decreasing identity theft.
Re-theorizing civil society in China: Agency and the discursive politics of civil society engagement

Scholarship on Chinese civil society has produced rich empirical studies, but there have been few attempts to theorize the empirical knowledge acquired. Moreover, the question of how to conceptualize the political agency of civil society in a non-democratic context has received limited systematic attention. In this conceptual article, we draw on a discursive approach to politics to analyse the political agency of Chinese civil society. Our analysis is based on synthesizing insights gained through three separate research projects. We propose a conceptual framework which focuses on how civil society actors position themselves within a structured political space, how they represent social groups and issues through advocacy, how they care for these groups, and how they engage in processes of identity formation. Taken together, these four modalities constitute a framework for analysing the different political dimensions of civil society agency.
Toward a Realistic Interpretation of Blue-spill for Blue-screen Matting

This paper proposes a realistic interpretation of the bluespill problem that affects blue-screen matting in digital image composition. This phenomenon consists in the contamination of the foreground object color by the background color. Based on the notion of mutual illumination introduced by Forsyth and Zisserman [5], we interpret the bluespill phenomenon and propose an extended composition equation explicitly taking this into consideration. Experiments confirm the accuracy of the proposed method. Comparisons are made with the classical composition equation.
Separator-based strategies for efficient message routing

Message routing strategies are given for networks with certain separator properties. These strategies use considerably less space than complete routing tables, keep node names to O(log n) bits, and still route along near-shortest paths. For any network with separators of size at most a small constant c, a total of O(n log n) items of routing information is stored, and any message is routed along a path of length at most (2/α) + 1 times the length of an optimal path, where α ≫ 1 is the positive root of the equation α⌈(c+1)/2⌉ - α - 2 = 0. For planar networks, O(n1+ε) items are stored, for any constant ε, 0 ≪ ε ≪ 1/3, and the length of any message path is at most 7 times that of an optimal path.
Orthographic Disambiguation Incorporating Transliterated Probability

Orthographic variance is a fundamental problem for many natural language processing applications. The Japanese language, in particular, contains many orthographic variants for two main reasons: (1) transliterated words allow many possible spelling variations, and (2) many characters in Japanese nouns can be omitted or substituted. Previous studies have mainly focused on the former problem; in contrast, this study has addressed both problems using the same framework. First, we automatically collected both positive examples (sets of equivalent term pairs) and negative examples (sets of inequivalent term pairs). Then, by using both sets of examples, a support vector machine based classifier determined whether two terms (t1 and t2) were equivalent. To boost accuracy, we added a transliterated probability P (t1|s)P (t2|s), which is the probability that both terms (t1 and t2) were transliterated from the same source term (s), to the machine learning features. Experimental results yielded high levels of accuracy, demonstrating the feasibility of the proposed approach.
Causal Attributions and Corpus Analysis

Although philosophers have often held that causation is a purely descriptive notion, a growing body of experimental work on ordinary causal attributions using questionnaire methods indicates that it is heavily influenced by normative information. These results have been the subject of sceptical challenges. Additionally, those who find the results compelling have disagreed about how best to explain them. In this chapter, we help resolve these debates by using a new set of tools to investigate ordinary causal attributions—the methods of corpus linguistics. We apply both more qualitative corpus analysis techniques and the more purely quantitative methods of distributional semantics to four target questions: (a) Can corpus analysis provide independent support for the thesis that ordinary causal attributions are sensitive to normative information? (b) Does the evidence coming from corpus analysis support the contention that outcome valence matters for ordinary causal attributions? (c) Are ordinary causal attributions similar to responsibility attributions? (d) Are causal attributions of philosophers different from causal attributions we find in corpora of more ordinary language? We argue that the results of our analyses support a positive answer to each of these questions.
Evaluation of OCR Accuracy Using Synthetic Data

We describe an experiment in which an OCR classi(cid:12)er is evaluated on synthetic character images created using a document image defect model. The use of synthetic data permits con-trol of the quality of the test data and quantitative analysis of the e(cid:11)ects of image quality on OCR accuracy. For a particular classi(cid:12)er, we show that good performance | accuracy above a given threshold | occurs within contiguous regions of the space de(cid:12)ned by the range of key parameters of the defect model.
A Aompact and Affordable BLDC Motor Controller for a Microelectronics Remote Laboratory

When compared to other types of motors, brushless DC (BLDC) motors have, larger torque, higher speed, greater efficiency, better control, longer maintenance life and are cleaner. However, their control circuitry is much more complicated than that of an ordinary brushed DC motor, often resulting in designers’ preference for other motor types. This paper will step through the design of both the hardware and firmware required to produce a motor controller that is compact, affordable and expandable (power-wise). We will also show how it can be used for reliable high precision positioning of test probes in our remote microelectronics laboratory.
Prevention of Index-Poisoning DDoS Attacks in Peer-to-Peer File-Sharing Networks

A major security threat to the normal use and legal sharing of peer-to-peer (P2P) resources is DDoS (distributed denial-of-service) attacks caused by file index poisoning. This type of attacks exploits the design vulnerability of P2P networks. By populating unprotected peers with poisoned file indexes, attacker can cause DDoS flooding attacks on arbitrary hosts, even outside of the P2P network. We solve the index-poisoning problem in P2P file-sharing systems using identity-based cryptography to establish peer accountability. With accountability, all peers remain anonymous but their file indexes can be traced back to the original sending address without contacting the sender. We prove that accountability effectively prevents a peer from launching indexpoisoning attacks. A new reliable index-exchange protocol (RIEP) is proposed to enforce peer accountability. This protocol is applicable to all P2P file-sharing networks, either structured or unstructured. The system is designed to allow gradual transition of peers to become RIEP-enabled. We develop analytical models to characterize the poison propagation patterns with and without RIEP defense. These poisoning models are validated by simulated RIEP experiments on P2P networks over one million nodes. The reported experimental results support the advantages predicted by the theoretical models. These results prove the effectiveness of using RIEP to prevent index-poisoning DDoS attacks. We also discuss the implementation of the RIEP scheme and its limitations in real-life P2P networks.
Principles of Traditional Animation

The topic is about the basic principles of traditional 2D handdrawn animation as well as their application to 3D computer animation. In the presentation, the history of their evolution is described and their importance in modern animation is showed. All of the principles aim to achieve natural appealing to the eye action and character. Most of the principles were developed by observing the real world around us and analyzing physical laws behind it as well as studying theater staging and talented actors’ play.
Alterations in Retinal Layer Thickness and Reflectance at Different Stages of Diabetic Retinopathy by En Face Optical Coherence Tomography

Purpose This article reports a method for en face optical coherence tomography (OCT) imaging and quantitative assessment of alterations in both thickness and reflectance of individual retinal layers at different stages of diabetic retinopathy (DR). Methods High-density OCT raster volume scans were acquired in 29 diabetic subjects divided into no DR (NDR) or non-proliferative DR (NPDR) groups and 22 control subjects (CNTL). A customized image segmentation method identified eight retinal layer interfaces and generated en face thickness maps and reflectance images for nerve fiber layer (NFL), ganglion cell and inner plexiform layers (GCLIPL), inner nuclear layer (INL), outer plexiform layer (OPL), outer nuclear layer (ONL), photoreceptor outer segment layer (OSL), and retinal pigment epithelium (RPE). Mean thickness and intensity values were calculated in nine macular subfields for each retinal layer. Results En face thickness maps and reflectance images of retinal layers in CNTL subjects corresponded to normal retinal anatomy. Total retinal thickness correlated negatively with age in nasal subfields (R ≤−0.31; P ≤ 0.03, N = 51). In NDR subjects, NFL and OPL thickness were decreased (P = 0.05), and ONL thickness was increased (P = 0.04) compared to CNTL. In NPDR subjects, GCLIPL thickness was increased in perifoveal subfields (P < 0.05) and INL intensity was higher in all macular subfields (P = 0.04) compared to CNTL. Conclusions Depth and spatially resolved retinal thickness and reflectance measurements are potential biomarkers for assessment and monitoring of DR.
Development of a Novel Polyclonal Antibody-Based Immunoassay for the Quantitation of Non-Albumin Urinary Proteins

Background: Better diagnostic methods to detect urinary proteinuria or albuminuria, important indicators of diabetic kidney disease, are needed. Here, we describe the development and performance qualification of a new immunoassay for the quantitation of non-albumin urinary proteins of 20 to 90 kilodaltons. Methods: Urinary proteins, purified from pooled, 24-hour, diabetic urines, were immunoabsorbed to remove albumin, electrophoretically characterized, and identified by mass spectrometry. Sheep anti-urinary protein polyclonal antibodies were immunoabsorbed to remove albumin reactivity. Major immunoreactive specificities of the polyclonal antibody were identified by Western blot. A polyclonal antibody-based competitive immunoassay was developed and performanceevaluated. An unpaired t-test (α = 0.05) and a receiver-operating characteristic curve were used to evaluate the measurement of 24-hour urinary protein excretion rates in distinguishing between normal, proteinuric, and albuminuric samples. Results: Approximately 380 mg of urinary protein was purified from 6.0 g of total urinary proteins. Mass spectrometry identified more than 36 different proteins in the purified preparation. The anti-urinary protein polyclonal antibody possessed significant immunoreactivity towards transferrin, IgG chains, alpha-1-acid glycoprotein, zinc-alpha-2-glycoprotein, prostaglandin-H2-d-isomerase, and alpha-1-microglobulin. The competitive immunoassay exhibited excellent analytical and clinical performance. Measurement of urinary protein excretion rates could distinguish between normoproteinuric and proteinuric samples (p < 0.0001; area under the curve = 0.6900) and between normoalbuminuric and albuminuric samples (p < 0.0001; area under the curve = 0.8782). Conclusion: Measurement of urinary protein excretion rates using the urinary protein immunoassay is clinically equivalent to laboratory methods of quantitating total urinary protein or albumin in identifying proteinuria and albuminuria.
A feasibility study of on-board data compression for infrared cameras of space observatories

In this paper, the feasibility of on-board data reduction/compression concept described in is evaluated for infrared images taken from space observatories. The method described in, which was initially designed and developed for the PACS (photodetector array camera and spectrometer) instrument, makes use of on-board integration to achieve higher compression ratio (CR) for applications with a modest telemetry rate. The evaluation of the reduction concept takes into account the visual performance (distortion) and the compression ratio. The distortion is assessed by calculating the reconstruction error using 4 metrics, namely, root mean square error (RMSE), signal-to-noise-ratio (SNR), peak-signal-to-noise-ratio (PSNR) and potential information loss (PIL). A quantitative evaluation of the on-board compression concept is performed on data from the infrared camera ISOCAM (infrared space observatory camera). We conclude with a short summary.
Minimum message length hidden Markov modelling

This paper describes a minimum message length (MML) approach to finding the most appropriate hidden Markov model (HMM) to describe a given sequence of observations. An MML estimate for the expected length of a two-part message stating a specific HMM and the observations given this model is presented along with an effective search strategy for finding the best number of states for the model. The information estimate enables two models with different numbers of states to be fairly compared which is necessary if the search of this complex model space is to avoid the worst locally optimal solutions. The general purpose MML classifier 'Snob' has been extended and the new program 'tSnob' is tested on 'synthetic' data and a large 'real world' dataset. The MML measure is found to be an improvement on the Bayesian information criteria (BIG) and the un-supervised search strategy.