Miracle-dz/UniFAR-FTUs huggingface dataset:
A Wisp3 Cre-knockin Allele Produces Efficient Recombination in Spermatocytes during Early Prophase of Meiosis I

Individuals with the autosomal recessive skeletal disorder Progressive Pseudorheumatoid Dysplasia have loss-of-function mutations in WISP3, and aberrant WISP3 expression has been detected in tumors from patients with colon and breast cancer. In mice however, neither absence nor over-expression of WISP3 was found to cause a phenotype, and endogenous Wisp3 expression has been difficult to detect. To confirm that Wisp3 knockout mice have no phenotype and to identify potential sites of endogenous Wisp3 expression, we generated mice with a knockin allele (Wisp3 GFP-Cre) designed to express Green Fluorescent Protein (GFP) and Cre-recombinase instead of WISP3. Heterozygous and homozygous knockin mice were fertile and indistinguishable from their wild-type littermates, confirming that mice lacking Wisp3 have no phenotype. We could not detect GFP-expression from the knockin allele, but we could detect Cre-expression after crossing mice with the knockin allele to Cre-reporter mice; the double heterozygous offspring had evidence of Cre-mediated recombination in several tissues. The only tissue that had high levels of Cre-mediated recombination was the testis, where recombination in spermatocytes occurred by early prophase of meiosis I. As a consequence, males that were double heterozygous for a Wisp3 GFP-Cre and a floxed allele only contributed a recombined allele to their offspring. We detected no evidence of Cre-mediated recombination in the female ovary, although when double heterozygous females contributed the reporter allele to their offspring it had recombined ~7% of the time. Wisp3 GFP-Cre expression therefore occurs less frequently and most likely at a later stage of oocyte development in female mice compared to male mice. We conclude that although WISP3 is dispensable in mice, male mice with a Wisp3 GFP-Cre allele (Jackson Laboratory stock # 017685) will be useful for studying early prophase of meiosis I and for efficiently recombining floxed alleles that are passed to offspring.
Biomarkers of Adverse Response to Mercury: Histopathology versus Thioredoxin Reductase Activity

Exposure to mercury is normally assessed by measuring its accumulation in hair, blood or urine. Currently, the biomarkers of effect that have been proposed for mercurials, such as coproporphyrines or oxidative stress markers, are not sensitive enough and lack specificity. Selenium and selenoproteins are important targets for mercury and thioredoxin reductase (TrxR) in particular was shown to be very sensitive to mercury compounds both in vitro and in vivo. In this study we looked into the relation between the inhibition of thioredoxin reductase (TrxR) activity and histopathological changes caused by exposure to mercurials. Juvenile zeabra-seabreams were exposed to Hg2+ or MeHg for 28 days and histopathological changes were analyzed in the liver and kidney as well as TrxR activity. Both mercurials caused histopathological changes in liver and kidney, albeit Hg2+ caused more extensive and severe lesions. Likewise, both mercurials decreased TrxR activity, being Hg2+ a stronger inhibitor. Co-exposure to Hg2+ and Se fully prevented TrxR inhibition in the liver and reduced the severity of lesions in the organ. These results show that upon exposure to mercurials, histopathological alterations correlate with the level of TrxR activity and point to the potential use of this enzyme as a biomarker of mercury toxicity.
Sixties Ireland: reshaping the economy, state and society 1957–1973

after 1935 and coalesced in response to the BUF’s East End campaign. Tilles argues that Mosley’s antisemitism existed before any concentrated Jewish protests because the ‘antisemitism represented an authentic and organic component of Mosley’s—and by extension the BUF’s—fascist philosophy; the two had developed alongside one another in 1932, and continued to do so over the following years’ (188). He concludes by noting the Jewish community’s activities helped constrain the fascists, encouraged authorities to act and publicly linked the BUF with violence. British Fascist Antisemitism and Jewish Responses, 1932–40 contributes to the scholarship on British fascism by offering a quantitative examination of anti-Jewish rhetoric in fascist literature, charting the evolution of BUF antisemitism and exploring the nuances in the Jewish reaction to fascism. Indeed, Tilles nicely meshes primary source material with the historiography of British fascism throughout the book, showing gaps in earlier studies and successfully demonstrating where his contribution fits in the literature. Yet, the book could have provided wider context, including discussions about antisemitism in broader British politics, to contrast Jewish reactions to other promoters of antisemitism and describe the initial sources of antisemitism for Mosley and the early BUF’s platform. Indeed, elements of Social Darwinism, anti-democracy and racism were issues that spanned across the political spectrum, but how the BUF compared to other political parties is not always clear. Furthermore, the study also could have incorporated wider societal and economic influences that shaped politics of the time, such as the Depression and the National Government. In addition, further concluding analysis about the impact fascist action and Jewish response had on post-war fascism would have been useful to draw wider conclusions beyond the 1930s. This includes strategies against Mosley’s post-war Union Movement and the National Front, such as what opponents used, borrowed and rejected from the 1930s. Nonetheless, the book offers a new approach to inter-war British fascism and antisemitism by providing analysis about the nuanced stages of fascist action and Jewish reaction. The ideas expressed are solely the author’s opinions and do not represent the United States Department of State or any other agency.
New Hardness Results for the Permanent Using Linear Optics

In 2011, Aaronson gave a striking proof, based on quantum linear optics, showing that the problem of computing the permanent of a matrix is #P-hard. Aaronson's proof led naturally to hardness of approximation results for the permanent, and it was arguably simpler than Valiant's seminal proof of the same fact in 1979. Nevertheless, it did not prove that computing the permanent was #P-hard for any class of matrices which was not previously known. In this paper, we present a collection of new results about matrix permanents that are derived primarily via these linear optical techniques. First, we show that the problem of computing the permanent of a real orthogonal matrix is #P-hard. Much like Aaronson's original proof, this will show that even a multiplicative approximation remains #P-hard to compute. The hardness result even translates to permanents over finite fields, where the problem of computing the permanent of an orthogonal matrix is ModpP-hard in the finite field F_{p^4} for all primes p not equal to 2 or 3. Interestingly, this characterization is tight: in fields of characteristic 2, the permanent coincides with the determinant; in fields of characteristic 3, one can efficiently compute the permanent of an orthogonal matrix by a nontrivial result of Kogan. Finally, we use more elementary arguments to prove #P-hardness for the permanent of a positive semidefinite matrix, which shows that certain probabilities of boson sampling experiments with thermal states are hard to compute exactly despite the fact that they can be efficiently sampled by a classical computer.
Enhanced unsupervised segmentation of multispectral Magnetic Resonance images

Image segmentation is an established necessity for an improved analysis of Magnetic Resonance images. Neural network-based clustering has been shown in literature to yield good results, yet the possibility of transforming the input feature space in order to enhance the clustering process has gone largely unexplored. In this paper we focus on brain imaging and present a new algorithm for unsupervised segmentation of multi-spectral images, based on the research, through neuro-fuzzy techniques, of an optimized space in which to perform clustering. Tests performed on both real and simulated MR images show promising results, encouraging the application to different medical targets and further investigation.
Granularity Conscious Modeling for Probabilistic Databases

The convergence of embedded sensor systems and stream query processing suggests an important role for database techniques, in managing data that only partially ­ and of- ten inaccurately ­ capture the state of the world. Reasoning about uncertainty as a first class citizen, inside a database system, becomes an increasingly important operation for processing non deterministic data. An essential step for such an approach lies in the choice of the appropriate un- certainty model, that captures the probabilistic information in the data, both accurately and at the right semantic de- tail level. This paper introduces Hierarchical First-Order Graphical Models (HFGMs), an intuitive and economical representation of the data correlations stored in a Proba- bilistic Data Management system, in a hierarchical setting. HFGM semantics allow for an efficient summarization of the probabilistic model that can be induced from a dataset at various levels of granularity, effectively controlling the trade-off of the model's complexity vs its accuracy.
An active vision system for real-time traffic sign recognition

This paper presents an active vision system for real-time traffic sign recognition. The system is composed of two cameras, one is equipped with a wide-angle lens and the other with a telephoto-lens, and a PC with an image processing board. The system first detects candidates for traffic signs in the wide-angle image using color; intensity, and shape information. For each candidate, the telephoto-camera is directed to its predicted position to capture the candidate in a larger size in the image. The recognition algorithm is designed by intensively using built-in-functions of an off-the-shelf image processing board to realize both easy implementation and fast recognition. The results of on-road real-time experiments show the feasibility of the system.
Beyond term clusters: assigning Wikipedia concepts to scientific documents

We propose a model for assigning Wikipedia Concepts as scientific category labels to scientific documents where their terms are first grouped together using the well-known topic modelling method, Latent Dirichlet Allocation (LDA) and then assigned to Wikipedia Concepts by wikification. We wikify the terms of the topic model of a document to extract related concepts from Wikipedia. We experiment on two different datasets: the abstracts of the documents from the ACM Digital Library and the full papers of the UvT Collection. The ACM dataset includes Computer Science publications whereas UvT includes scientific publications from a range of topics. Domain specific taxonomies are used for evaluation. Results show that our approach is able to assign Wikipedia Concepts to the scientific publications in an automated manner, removing any need for human supervision.
A game of snakes and ladders: Player migratory trajectories in the global football labor market

Globalization theorists have typically described the post-Bosman football labor market as an amalgam of global value-added chains funneling players from (semi-)peripheral countries to Europe’s core leagues. However, due to their cross-sectional design, most globalization studies actually do not observe the longitudinal migratory trajectories through which players move towards, within and out of football’s global core. To fill this lacuna, this study examines a unique longitudinal dataset of 4730 complete careers of male professional football players and identifies four characteristics of their migratory trajectories: (1) recurrent mobility; (2) domestic careers for 60% of the players and frequent cross-border transfers for the other 40%; (3) clear career progress towards the top teams for the elite 10% of players and circulation for the other 90%; (4) a highly skewed distribution of transfer fees leading top teams to earn and spend the bulk of transfer fees. This suggests that football’s labor market is somewhat like a game of snakes and ladders in which an elite minority of players seems to be moving in tightly managed global value-added chains towards the top teams. However, the migratory channels through which the majority of players moves are much more porous, two-directional and complex than usually suggested in the literature.
Sparse Low-Rank Matrix Approximation for Data Compression

Low-rank matrix approximation (LRMA) is a powerful technique for signal processing and pattern analysis. However, its potential for data compression has not yet been fully investigated. In this paper, we propose sparse LRMA (SLRMA), an effective computational tool for data compression. SLRMA extends conventional LRMA by exploring both the intra and inter coherence of data samples simultaneously. With the aid of prescribed orthogonal transforms (e.g., discrete cosine/wavelet transform and graph transform), SLRMA decomposes a matrix into a product of two smaller matrices, where one matrix is made up of extremely sparse and orthogonal column vectors and the other consists of the transform coefficients. Technically, we formulate SLRMA as a constrained optimization problem, i.e., minimizing the approximation error in the least-squares sense regularized by the $\ell _{0}$ -norm and orthogonality, and solve it using the inexact augmented Lagrangian multiplier method. Through extensive tests on real-world data, such as 2D image sets and 3D dynamic meshes, we observe that: 1) SLRMA empirically converges well; 2) SLRMA can produce approximation error comparable to LRMA but in a much sparse form; and 3) SLRMA-based compression schemes significantly outperform the state of the art in terms of rate–distortion performance.
Predicting the Popularity of Trending Arabic Wikipedia Articles Based on External Stimulants Using Data/Text Mining Techniques

Wikipedia is considered to be one of the most famous online encyclopedias. We study the issues related to trending articles on Arabic Wikipedia and how it is influenced by certain external stimulants: for example, breaking news, celebrities' tweets, special events from the past, instant messages on any social media application or any other reasons that could affect the Arabic Wikipedia articles in terms of the number of visitors, which we named the popularity level. By using a data- and text- mining techniques, and the software platform Rapidminer, we developed two models that enabled us to predict the popularity level of Arabic articles on Wikipedia, depending on the features of their stimulants.
Sound Transformations for Message Passing Systems

Typing is a core issue in federated networked distributed applications, which are increasingly modeled as event-based systems. Constraining such a system to globally agreed types for exchanged event objects is impractical, and structural typing typically mediates only between types with attributewise correspondances. This paper advocates a transformation-centric model for federated distributed applications. Our approach is generic in that it assumes the existence of certain global object types, which may be defined by a separate specification language and/or may arise during system deployment. Processes can define their individual sets of local types, and define conformance to global types via explicit transformations of values. Every process can thus be viewed as defining its own context, where transformations of incoming and outgoing objects can be manually programmed or generated. We propose a flexible and expressive language to declare object transformations, covering the full spectrum: from symmetric equivalences between types to asymmetric projections of types or enrichment of objects which structural subtyping can not capture. We present a type system that resolves the relevant transformations and verifies that corresponding functions respect high-level mappings between global and local types. We present empirical evidence of the efficiency of our approach.
Unit — A modular framework for interaction technique design , development and implementation

This thesis presents the Unit Concept, a framework for the development, design and implementation of interaction techniques. Unit’s main goal is to stimulate the progress of new interfaces that go beyond the traditional keyboard/mouse setup. Virtual, Mixed and Augmented Reality are examples of new technologies that demand advanced interaction techniques with concepts such as proprioception, two-handed interaction and physical Interfaces. These are practically impossible to represent within the traditional human-computer interface and new mechanisms are needed to enable their development. Unit places the interaction techniques in an abstraction layer between the input devices and the application, which allows the application developer to separate application functionality from interaction technique and behavior. Unit’s modular approach leads to the design of reusable interaction control components that are independent of the application. Unit’s nature makes it possible to interactively change, tweak and experiment with the behavior of the interaction techniques, but also to switch among different input device configurations.
Observability Analysis of a Matrix Kalman Filter-Based Navigation System Using Visual/Inertial/Magnetic Sensors

A matrix Kalman filter (MKF) has been implemented for an integrated navigation system using visual/inertial/magnetic sensors. The MKF rearranges the original nonlinear process model in a pseudo-linear process model. We employ the observability rank criterion based on Lie derivatives to verify the conditions under which the nonlinear system is observable. It has been proved that such observability conditions are: (a) at least one degree of rotational freedom is excited, and (b) at least two linearly independent horizontal lines and one vertical line are observed. Experimental results have validated the correctness of these observability conditions.
Emerging Opportunities and Challenges in Optimal Aging with Virtual Personal Assistants

Artificial intelligence (AI) is one of the most game-changing yet controversial scientific endeavors of our lifetime. We have already created AIs capable of learning and applying intelligence to a wide variety of tasks in the physical, virtual, and social realms for rapid decision-making in financial, medical, recreational, and transportation systems (Chaboud, Hjalmarsson, & Vega, 2015). Yet none of these come as close to our homes and families as the recently introduced conversational virtual intelligent assistants. Replacing the keyboard, the tablet, and the smartphone screen to connect to the Internet by speaking instead of typing, voice commands are building increased access for these technologies among disabled adults and the rapidly increasing aging population. Known as voice activated personal assistants (VAPAs), devices like Amazon’s Alexa and Google’s Now are the next-generation technology going beyond Apple’s Siri, already ubiquitously found on the smartphone and iPad devices. Interactions with VAPAs are ever more tailored, more personalized, and friendlier due to the improvements in AI, as we talk to rather than through our phones, computers, tablets, and appliances. Designed to be cloud-based, ongoing system improvements make VAPAs smarter, faster, and more deeply personalized, integrating personal data and preferences with environmental data in the background and upgrading seamlessly without active user input. The Google Now device comes with several specific services enabled, but most of the services, like Todoist, are third party apps that have separate chatbots. Amazon’s Alexa has both a shopping and a to-do list built in, and requires users to enable new skills. As of January 2017, Alexa had over 7,000 custom skills that third party developers had built to enhance functionality (Levy, 2017). This rapid development may partially be attributed to the company’s decision to open the Alexa AI platform up to developers and device manufacturers. The purpose of this article is to describe the use of VAPAs among older adults and their potential benefits for enhancing optimal aging. Additionally, it is our goal to identify policy themes surrounding VAPAs’ use in disabled or older populations. While new technology holds much promise for providing efficient and person-centered support to those who are more homebound and aging in place, it is important to recognize the challenges and ethical questions that may be raised in widespread dissemination of new technologies.
Accurate Dense Stereo Matching Based on Image Segmentation Using an Adaptive Multi-Cost Approach

This paper presents a segmentation-based stereo matching algorithm using an adaptive multi-cost approach, which is exploited for obtaining accuracy disparity maps. The main contribution is to integrate the appealing properties of multi-cost approach into the segmentation-based framework. Firstly, the reference image is segmented by using the mean-shift algorithm. Secondly, the initial disparity of each segment is estimated by an adaptive multi-cost method, which consists of a novel multi-cost function and an adaptive support window cost aggregation strategy. The multi-cost function increases the robustness of the initial raw matching costs calculation and the adaptive window reduces the matching ambiguity effectively. Thirdly, an iterative outlier suppression and disparity plane parameters fitting algorithm is designed to estimate the disparity plane parameters. Lastly, an energy function is formulated in segment domain, and the optimal plane label is approximated by belief propagation. The experimental results with the Middlebury stereo datasets, along with synthesized and real-world stereo images, demonstrate the effectiveness of the proposed approach.
Automatic Assessment of OCR Quality in Historical Documents

Mass digitization of historical documents is a challenging problem for optical character recognition (OCR) tools. Issues include noisy backgrounds and faded text due to aging, border/marginal noise, bleed-through, skewing, warping, as well as irregular fonts and page layouts. As a result, OCR tools often produce a large number of spurious bounding boxes (BBs) in addition to those that correspond to words in the document. This paper presents an iterative classification algorithm to automatically label BBs (i.e., as text or noise) based on their spatial distribution and geometry. The approach uses a rule-base classifier to generate initial text/noise labels for each BB, followed by an iterative classifier that refines the initial labels by incorporating local information to each BB, its spatial location, shape and size. When evaluated on a dataset containing over 72,000 manually-labeled BBs from 159 historical documents, the algorithm can classify BBs with 0.95 precision and 0.96 recall. Further evaluation on a collection of 6,775 documents with ground-truth transcriptions shows that the algorithm can also be used to predict document quality (0.7 correlation) and improve OCR transcriptions in 85% of the cases.