Miracle-dz/UniFAR-FTUs huggingface dataset:
XPROB - A Generalized Pool-Based Anonymous Communication Framework

We propose XPROB, a generalized pool-based anonymous communication framework. XPROB defines a family of infinite pool-based anonymous communication systems with resistance against global active adversary (adversary with all capabilities to monitor all external activities of system, to delay and to create messages in the system). Our proposal is to solve the limitation of APROB Channel that concerns only global delaying adversary. XPROB provides flexibility for users to justify their level of anonymity (and speed) and satisfies probabilistic real-time condition which ensures to deliver any message within a predefined duration with high probability. Experimental evaluation shows that each instance of XPROB provides lower source-hiding property than APROB Channel with the same environment and users' behaviors (rate and number of sent messages).
The Truth Machine: A Social History of the Lie Detector

How do you trap someone in a lie? For centuries, all manner of truth-seekers have used the lie detector. In this eye-opening book, Geoffrey C. Bunn unpacks the history of this device and explores the interesting and often surprising connection between technology and popular culture. Lie detectors and other truth-telling machines are deeply embedded in everyday American life. Well-known brands such as Isuzu, Pepsi Cola, and Snapple have advertised their products with the help of the "truth machine," and the device has also appeared in countless movies and television shows. The Charles Lindbergh "crime of the century" in 1935 first brought lie detectors to the public's attention. Since then, they have factored into the Anita Hill-Clarence Thomas sexual harassment controversy, the Oklahoma City and Atlanta Olympics bombings, and one of the most infamous criminal cases in modern memory: the O. J. Simpson murder trial. The use of the lie detector in these instances brings up many intriguing questions that Bunn addresses: How did the lie detector become so important? Who uses it? How reliable are its results? Bunn reveals just how difficult it is to answer this last question. A lie detector expert concluded that O. J. Simpson was "one hundred percent lying" in a video recording in which he proclaimed his innocence; a tabloid newspaper subjected the same recording to a second round of evaluation, which determined Simpson to be "absolutely truthful. " Bunn finds fascinating the lie detector's ability to straddle the realms of serious science and sheer fantasy. He examines how the machine emerged as a technology of truth, transporting readers back to the obscure origins of criminology itself, ultimately concluding that the lie detector owes as much to popular culture as it does to factual science.
Designed for work, but not from here: rural and remote perspectives on networked technology

While workers in an urban environment typically enjoy full speed, always available, broadband access, those in rural and remote environments do not necessarily have access to the same level of service. In this paper we describe insights from a qualitative study examining the benefits and continued challenges of using networked technologies for work purposes in rural and remote communities. Our findings indicate that work in these areas increasingly depends on networked technology to support in-situ and geographically distributed work practices, and to ameliorate health and safety issues, but that participants experience significant challenges in obtaining signal access and stability. We discuss implications for design and future research that arise from our findings.
Mutations in the BRCT binding site of BRCA1 result in hyper-recombination

We introduced a K1702M mutation in the BRCA1 BRCT domain known to prevent the binding of proteins harboring pS-X-X-F motifs such as Abraxas-RAP80, BRIP1, and CtIP. Surprisingly, rather than impairing homologous recombination repair (HRR), expression of K1702M resulted in hyper-recombination coinciding with an accumulation of cells in S-G2 and no effect on nonhomologous end-joining. These cells also showed increased RAD51 and RPA nuclear staining. More pronounced effects were seen with a naturally occurring BRCT mutant (M1775R) that also produced elevated levels of ssDNA, in part co-localizing with RPA, in line with excessive DNA resection. M1775R induced unusual, thread-like promyelocytic leukemia (PML) nuclear bodies and clustered RPA foci rather than the typical juxtaposed RPA-PML foci seen with wild-type BRCA1. Interestingly, K1702M hyper-recombination diminished with a second mutation in the BRCA1 RING domain (I26A) known to reduce BRCA1 ubiquitin-ligase activity. These in vitro findings correlated with elevated nuclear RAD51 and RPA staining of breast cancer tissue from a patient with the M1775R mutation. Altogether, the disruption of BRCA1 (BRCT)-pS-X-X-F protein binding results in ubiquitination-dependent hyper-recombination via excessive DNA resection and the appearance of atypical PML-NBs. Thus, certain BRCA1 mutations that cause hyper-recombination instead of reduced DSB repair might lead to breast cancer.
A Transient-Enhanced Low-Quiescent Current Low-Dropout Regulator With Buffer Impedance Attenuation

This paper presents a low-dropout regulator (LDO) for portable applications with an impedance-attenuated buffer for driving the pass device. Dynamically-biased shunt feedback is proposed in the buffer to lower its output resistance such that the pole at the gate of the pass device is pushed to high frequencies without dissipating large quiescent current. By employing the current-buffer compensation, only a single pole is realized within the regulation loop unity-gain bandwidth and over 65deg phase margin is achieved under the full range of the load current in the LDO. The LDO thus achieves stability without using any low-frequency zero. The maximum output-voltage variation can be minimized during load transients even if a small output capacitor is used. The LDO with the proposed impedance-attenuated buffer has been implemented in a 0.35-mum twin-well CMOS process. The proposed LDO dissipates 20-muA quiescent current at no-load condition and is able to deliver up to 200-mA load current. With a 1-muF output capacitor, the maximum transient output-voltage variation is within 3% of the output voltage with load step changes of 200 mA/100 ns.
Comparing the performance of the evolvable πGrammatical Evolution genotype-phenotype map to Grammatical Evolution in the dynamic Ms. Pac-Man environment

In this work, we examine the capabilities of two forms of mappings by means of Grammatical Evolution (GE) to successfully generate controllers by combining high-level functions in a dynamic environment. In this work we adopted the Ms. Pac-Man game as a benchmark test bed. We show that the standard GE mapping and Position Independent GE (πGE) mapping achieve similar performance in terms of maximising the score. We also show that the controllers produced by both approaches have an overall better performance in terms of maximising the score compared to a hand-coded agent. There are, however, significant differences in the controllers produced by these two approaches: standard GE produces more controllers with invalid code, whereas the opposite is seen with πGE.
The Alyssa System at TREC QA 2007: Do We Need Blog06?

We describe the participation of the Saarland University LSV group in the DARPA/NIST TREC 2007 Q&A track with the Alyssa system, using an approach that combines cascaded language-model based information retrieval (LMIR) with data-driven learning methods for answer extraction and ranking. To test the robustness of this approach that was previously proven on news data also across document collections of varying levels of subjectivity, we test the hypothesis that the answer accuracy over factoid questions does not decrease significantly if blog data is added. Our results show that on the contrary, the method remains competitive on larger datasets with mixed content, such as the union of the AQUAINT 2 (news) and BLOG 06 (blog) corpora (Macdonald and Ounis, 2006). We also present evaluation results on an unofficial set of questions manually generated from BLOG 06 documents, which were created at LSV.
On the Adaptive Numerical Solution ofNonlinear Partial Di erential Equationsin Wavelet

This work develops fast and adaptive algorithms for numerically solving nonlinear partial di erential equations of the form ut = Lu +N f(u) where L and N are linear di erential operators and f(u) is a nonlinear function. These equations are adaptively solved by projecting the solution u and the operators L and N into a wavelet basis. Vanishing moments of the basis functions permit a sparse representation of the solution and operators. Using these sparse representations fast and adaptive algorithms that apply operators to functions and evaluate nonlinear functions, are developed for solving evolution equations. For a wavelet representation of the solution u that contains Ns signi cant coe cients, the algorithms update the solution using O(Ns) operations. The approach is applied to a number of examples and numerical results are given. 3
The Sociology of Architecture: Constructing Identities

Acknowledgements List of Illustrations Introduction 1. Architecture, Power and Identities: Surveying the Field 2. The Public Discourse of Architecture: Sociolizing Identities 3. Architecture and the Nation: Building an 'Us' 4. Modernity and Mega-Events: Archhtecturing a Future 5. Architecture and Commemoration: The Construction of Memorialization 6. Iconic Architecture and Regeneration: The Forum is the Function 7. 'European' Architecture: Politics in Search of Form and Meaning 8. Conclusion: Sociology, Architecture and the Politics of Building Bibliography Index
Microdissection and the study of cancer pathways.

Abstract: The study of genetic alterations in tumors and their precursor lesions is often hampered by the presence of a heterogeneous background of non-neoplastic elements such as stromal cells, inflammatory cells, and angiogenic elements. Microdissection involves the extraction of specific populations of cells under direct visualization. In this article, we will discuss the currently available techniques of microdissection, and briefly review how this material is being utilized in the study of cancer pathways. Microdissected tissue is amenable for the study of cancer genomics, expression analysis and most recently, cancer proteomics. The purity of reagents obtained from microdissected material has resulted in the successful identification of tumor suppressor genes as well as novel transcripts and proteins that are altered in neoplastic cells. Improved techniques of tissue fixation and microdissection, supplemented with ancillary technology such as pre-amplification, have permitted the use of increasingly smaller quantities of material for the study of cancer pathways. Importantly, it is now possible to analyze many of the genetic changes that precede cancer, thereby identifying populations "at risk" for developing malignancies in the future.
A distortion control scheme for allocating constant distortion in FD-CD video transcoder

Recently, FD (frame dropping)-CD (coefficient dropping) transcoding has been considered, mainly due to the low computational complexity and simple implementation. However, CD errors in the FD-CD transcoding scheme tend to be propagated and they have a significant effect on the qualities of decoded images. We derive the error characteristics incurred by CD operations and propose an effective estimation model that adaptively describes well the characteristics of propagation errors in the compressed domain. Furthermore, we apply the proposed model to distortion control achieving nearly constant distortion allocation among frames. Simulations show that the proposed model is quite accurate in estimating the overall distortions and is effectively applied to distortion control over a range of sequences with varying scene types.
Dependency Parsing with Dilated Iterated Graph CNNs

Dependency parses are an effective way to inject linguistic knowledge into many downstream tasks, and many practitioners wish to efficiently parse sentences at scale. Recent advances in GPU hardware have enabled neural networks to achieve significant gains over the previous best models, these models still fail to leverage GPUs’ capability for massive parallelism due to their requirement of sequential processing of the sentence. In response, we propose Dilated Iterated Graph Convolutional Neural Networks (DIG-CNNs) for graph-based dependency parsing, a graph convolutional architecture that allows for efficient end-to-end GPU parsing. In experiments on the English Penn TreeBank benchmark, we show that DIG-CNNs perform on par with some of the best neural network parsers.
Simple rules govern finite-size effects in scale-free networks

We give an intuitive though general explanation of the finite-size effect in scale-free networks in terms of the degree distribution of the starting network. This result clarifies the relevance of the starting network in the final degree distribution. We use two different approaches: the deterministic mean-field approximation used by Barabási and Albert (but taking into account the nodes of the starting network), and the probability distribution of the degree of each node, which considers the stochastic process. Numerical simulations show that the accuracy of the predictions of the mean-field approximation depend on the contribution of the dispersion in the final distribution. The results in terms of the probability distribution of the degree of each node are very accurate when compared to numerical simulations. The analysis of the standard deviation of the degree distribution allows us to assess the influence of the starting core when fitting the model to real data.
How many users should inform the BS about their channel information?

Simultaneous transmission of multiple data streams from a multiple antenna base station (BS) to multiple single antenna users gives significant gain in spectral efficiency as compared to when a single such user is being served. This simultaneous transmission to multiple users is realizable only if BS knows the forward channels linking its transmitting antennas to these users which requires channel feedback from these users. This feedback overhead could be prohibitively large especially in large user systems, limiting the multi-user transmission gains. Exploiting the channel reciprocity in a time-division duplexed (TDD) broadcast channel, we give a simple transmission strategy, where users feedback independent of their channel realizations. We analyze the sum rate of this multi-user system when the channel acquisition load is completely accounted for. We derive a novel lower bound of the sum rate which allows us to optimize over how many users should inform the BS about their channel information, solving the intriguing trade-off of multiuser diversity, interference cancellation and feedback overhead.
Effects of regular aerobic exercise on physical characteristics, body image satisfaction and self-efficacy of middle-aged women

This study examined the effects of regular aerobic exercise on physical variables, body image satisfaction and self-efficacy levels of sedentary women. An exercise group and a control group consisted of 25 and 20 middle-aged women respectively. The exercise group participated in a 14-week aerobic training programme, whereas the control group did not participate in any special kind of physical activity. In addition to administering the Body Image Satisfaction Questionnaire and the Self-efficacy Scale, anthropometric variables were assessed before the commencement of the study and again immediately afterwards. The data were analysed by a one-way ANCOVA. The main results revealed significant decreases in body mass, body fat, waist-to-hip ratio, as well as significant improvements in body image satisfaction and self-efficacy scores, with large effect sizes after the intervention for the exercise group. Regular aerobic exercise had a positive effect on body image satisfaction and self-efficacy of middle-aged women. This could possibly be due to improvements in their physical characteristics that resulted from the exercise programme. Key words : Aerobic exercise; Body fat; Body Mass Index; Body image satisfaction; Self-efficacy.
Predicting dangerous seismic activity with Recurrent Neural Networks

In this paper we present a solution to the AAIA'16 Data Mining Challenge. The goal of the challenge was to predict, from multivariate time series data, periods of increased seismic activity which may cause life-threatening accidents in underground coal mines. Our solution is based on Recurrent Neural Network with Long Short-Term Memory cells. It requires almost no feature engineering, which makes it easily applicable to other domains with multivariate time series data. The method achieved the 5th place in the AAIA'16 competition, out of 203 teams.
Using Ontologies for Integrated Geographic Information Systems

Today, there is a huge amount of data gathered about the Earth, not only from new spatial information systems, but also from new and more sophisticated data collection technologies. This scenario leads to a number of interesting research challenges, such as how to integrate geographic information of different kinds. The basic motivation of this paper is to introduce a GIS architecture that can enable geographic information integration in a seamless and flexible way based on its semantic value and regardless of its representation. The proposed solution is an ontology‐driven geographic information system that acts as a system integrator. In this system, an ontology is a component, such as the database, cooperating to fulfill the system’s objectives. By browsing through ontologies the users can be provided with information about the embedded knowledge of the system. Special emphasis is given to the case of remote sensing systems and geographic information systems. The levels of ontologies can be used to guide processes for the extraction of more general or more detailed information. The use of multiple ontologies allows the extraction of information in different stages of classification. The semantic integration of aerial images and GIS is a crucial step towards better geospatial modeling.
A conserved αβ transmembrane interface forms the core of a compact T-cell receptor–CD3 structure within the membrane

Significance The T-cell antigen receptor (TCR) is an eight-subunit modular biosensor that detects the presence of pathogen-derived molecular fragments in infected cells and tissues. No atomic-resolution structure has been determined for the intact receptor complex, and the mechanism by which it transmits signals across the cell membrane remains poorly defined. Using a combination of biochemical, biophysical, and computational approaches to study the assembled complex in cellular membranes, we identified an evolutionarily conserved core transmembrane (TM) structure that organizes the complex into an intimately packed eight-helix bundle within the membrane and is critical for the structural integrity of the intact receptor. Our model provides insights into possible structural pathways involved in TM TCR signaling. The T-cell antigen receptor (TCR) is an assembly of eight type I single-pass membrane proteins that occupies a central position in adaptive immunity. Many TCR-triggering models invoke an alteration in receptor complex structure as the initiating event, but both the precise subunit organization and the pathway by which ligand-induced alterations are transferred to the cytoplasmic signaling domains are unknown. Here, we show that the receptor complex transmembrane (TM) domains form an intimately associated eight-helix bundle organized by a specific interhelical TCR TM interface. The salient features of this core structure are absolutely conserved between αβ and γδ TCR sequences and throughout vertebrate evolution, and mutations at key interface residues caused defects in the formation of stable TCRαβ:CD3δε:CD3γε:ζζ complexes. These findings demonstrate that the eight TCR–CD3 subunits form a compact and precisely organized structure within the membrane and provide a structural basis for further investigation of conformationally regulated models of transbilayer TCR signaling.
HW/SW partitioning and code generation of embedded control applications on a reconfigurable architecture platform

This paper studies the use of a reconfigurable architecture platform for embedded control applications aimed at improving real time performance. The HW/SW codesign methodology from POLIS is used. It starts from high-level specifications, optimizes an intermediate model of computation (extended finite state machines) and derives both hardware and software, based on performance constraints. We study a particular architecture platform, which consists of a general purpose processor core, augmented with a reconfigurable function unit and data-path to improve run time performance. A new mapping flow and algorithms to partition hardware and software are proposed to generate implementations that best utilize this architecture. Encouraging preliminary results are shown for automotive electronic control examples.
Scaling Laws of the Throughput Capacity and Latency in Information-Centric Networks

Author(s): Azimdoost, Bita; Westphal, Cedric; Sadjadpour, Hamid R | Abstract: Wireless information-centric networks consider storage as one of the network primitives, and propose to cache data within the network in order to improve latency and reduce bandwidth consumption. We study the throughput capacity and delay in an information-centric network when the data cached in each node has a limited lifetime. The results show that with some fixed request and cache expiration rates, the order of the data access time does not change with network growth, and the maximum throughput order is inversely proportional to the square root and logarithm of the network size $n$ in cases of grid and random networks, respectively. Comparing these values with the corresponding throughput and latency with no cache capability (throughput inversely proportional to the network size, and latency of order $\sqrt{n}$ and $\sqrt{\frac{n}{\log n}}$ in grid and random networks, respectively), we can actually quantify the asymptotic advantage of caching. Moreover, we compare these scaling laws for different content discovery mechanisms and illustrate that not much gain is lost when a simple path search is used.
Identification of Novel Components of the Unfolded Protein Response in Arabidopsis

Unfavorable environmental and developmental conditions may cause disturbances in protein folding in the endoplasmic reticulum (ER) that are recognized and counteracted by components of the Unfolded Protein Response (UPR) signaling pathways. The early cellular responses include transcriptional changes to increase the folding and processing capacity of the ER. In this study, we systematically screened a collection of inducible transgenic Arabidopsis plants expressing a library of transcription factors for resistance toward UPR-inducing chemicals. We identified 23 candidate genes that may function as novel regulators of the UPR and of which only three genes (bZIP10, TBF1, and NF-YB3) were previously associated with the UPR. The putative role of identified candidate genes in the UPR signaling is supported by favorable expression patterns in both developmental and stress transcriptional analyses. We demonstrated that WRKY75 is a genuine regulator of the ER-stress cellular responses as its expression was found to be directly responding to ER stress-inducing chemicals. In addition, transgenic Arabidopsis plants expressing WRKY75 showed resistance toward salt stress, connecting abiotic and ER-stress responses.