Miracle-dz/UniFAR-FTUs huggingface dataset:
Lethal lung hypoplasia and vascular defects in mice with conditional Foxf1 overexpression

ABSTRACT FOXF1 heterozygous point mutations and genomic deletions have been reported in newborns with the neonatally lethal lung developmental disorder, alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV). However, no gain-of-function mutations in FOXF1 have been identified yet in any human disease conditions. To study the effects of FOXF1 overexpression in lung development, we generated a Foxf1 overexpression mouse model by knocking-in a Cre-inducible Foxf1 allele into the ROSA26 (R26) locus. The mice were phenotyped using micro-computed tomography (micro-CT), head-out plethysmography, ChIP-seq and transcriptome analyses, immunohistochemistry, and lung histopathology. Thirty-five percent of heterozygous R26-Lox-Stop-Lox (LSL)-Foxf1 embryonic day (E)15.5 embryos exhibit subcutaneous edema, hemorrhages and die perinatally when bred to Tie2-cre mice, which targets Foxf1 overexpression to endothelial and hematopoietic cells. Histopathological and micro-CT evaluations revealed that R26Foxf1; Tie2-cre embryos have immature lungs with a diminished vascular network. Neonates exhibited respiratory deficits verified by detailed plethysmography studies. ChIP-seq and transcriptome analyses in E18.5 lungs identified Sox11, Ghr, Ednrb, and Slit2 as potential downstream targets of FOXF1. Our study shows that overexpression of the highly dosage-sensitive Foxf1 impairs lung development and causes vascular abnormalities. This has important clinical implications when considering potential gene therapy approaches to treat disorders of FOXF1 abnormal dosage, such as ACDMPV. Summary: Similar to Foxf1 loss, Foxf1 overexpression in mice is lethal. This finding highlights the need to consider alternatives beyond gene therapy to find a cure for alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV).
Human body deformations using joint-dependent local operators and finite-element theory

This paper discusses the problem of improving the realism of motion not from the joint point-of-view as for robots, but in relation to the deformations of human bodies during animation. Two methods for improving these deformations are described. The Joint-dependent Local Deformation (JLD) approach is convenient when there is no contact between the human being and the environment. A finite element method is used to model the deformations of human flesh due to flexion of members and/or contact with objects.
Mobile Agent Migration Models and Algorithms for Collaborative Processing

The mobile agent based paradigm is a promising computing paradigm in wireless sensor networks, which has many unique advantages over the traditional client/server paradigm. However, the question on how to model the mobile agent itinerary in sensor networks, is left unsolved. The design of the mobile agent migration itinerary has a large impact on the performance of collaborative processing, which is the focus of this paper. We first model both the static and dynamic mobile agent planning problems and design two planning algorithms. Then a performance evaluation between these two algorithms is conducted. Three metrics (energy consumption, network lifetime, and the number of hops) are used in the simulation to quantitatively measure the performance of different itinerary planning methods. Simulation results show that the dynamic itinerary planning has considerable advantages over the static itinerary.
Enfranchising all subjected, worldwide

For cosmopolitans, global democracy is valuable both in itself and as a means to global justice. Their preferred principle of political enfranchisement is the All Affected Principle which, given global interdependencies, means that virtually everyone should have a vote virtually everywhere. Anti-cosmopolitans want to resist that conclusion. They try to do so by appealing instead to the All Subjected Principle. But you are subject to a law whenever it claims to apply to you, and in contemporary practice states typically claim authority to make many laws that apply even to non-nationals abroad. On the All Subjected Principle, they too should have a vote over those laws. The All Subjected Principle would thus have similarly expansionary implications for the franchise as the All Affected Principle, contrary to the fondest hopes of anti-cosmopolitans.
Approximate linear analysis of concrete fracture by R-curves

Using linear elastic fracture analysis, the energy consumed per unit length of fracture (fracture energy) varies with the crack length, as described by the resistance curve (R‐curve). This concept, originally proposed for metals, is developed here into a practical, applicable form for concrete. The energy release rate is determined by an approximate linear elastic fracture analysis based on a certain equivalent crack length, which differs from the actual crack length, and is solved as part of structural analysis. It is shown that such an analysis, coupled with the R‐curve concept, allows achieving satisfactory fits of the presently existing fracture data obtained with three‐point and four‐point bent specimens. Without the R‐curve, the use of an equivalent crack length in linear analysis is not sufficient to achieve a satisfactory agreement with these data. The existing data can be described equally well with various formulas for the R‐curve, and the material parameters in the formula can vary over a relat.
qPrimerDepot: a primer database for quantitative real time PCR

Gene expression studies employing high throughput real time PCR methods require finding uniform conditions for optimal amplification of multiple targets, often a daunting task. We developed a primer database, qPrimerDepot, which provides optimized primers for all human and mouse RefSeq genes. These primers are designed to amplify desired templates under unified annealing temperature. For most intron-bearing genes, primers flank one of the largest introns thus minimizing background noise due to genomic DNA contamination. The qPrimerDepot database can be accessed at and .
Characterizing Energy per Job in Cloud Applications

Energy efficiency is a major research focus in sustainable development and is becoming even more critical in information technology (IT) with the introduction of new technologies, such as cloud computing and big data, that attract more business users and generate more data to be processed. While many proposals have been presented to optimize power consumption at a system level, the increasing heterogeneity of current workloads requires a finer analysis in the application level to enable adaptive behaviors and in order to reduce the global energy usage. In this work, we focus on batch applications running on virtual machines in the context of data centers. We analyze the application characteristics, model their energy consumption and quantify the energy per job. The analysis focuses on evaluating the efficiency of applications in terms of performance and energy consumed per job, in particular when shared resources are used and the hosts on which the virtual machines are running are heterogeneous in terms of energy profiles, with the aim of identifying the best combinations in the use of resources.
Teachers' Perceptions about the Common Core State Standards in Writing.

This article describes findings from a survey completed by 250 K-12 grade teachers from eight states (i.e., Kentucky, Minnesota, Michigan, Maine, Delaware, North Carolina, Georgia, and Mississippi) that had fully implemented the Common Core State Standards (CCSS) by spring 2013. The survey was designed to examine teachers’ perceptions about their preparedness to teach the CCSS in Writing as well as provide information about what teachers perceived as barriers to implementing the standards, their perceptions of the positive and negative effects of CCSS implementation, and their professional development experiences related to implementing the standards. The results of the analyses indicate that teachers vary in their current level of acceptability regarding the CCSS in Writing according to the grade level they teach, their years of teaching experience, and the amount of professional development they have received. Significant differences were not found between teachers from different geographic settings or between schools with high and low numbers of students receiving free or reduced lunch. Implications for professional development and teacher education are discussed.
Constraints for the iscontinuity fro Mot ion

Surface discontinuities are detected in a sequence of images by exploiting physical constraints at early stages in the processing of visual motion. To achieve accurate early discontinuity detection we exploit five physical constraints on the presence of discontinuities: i) the shape of the sum of squared differences (SSD) error surface in the presence of surface discontinuities; G) the change in the shape of the SSD surface due to relative surface motion; G) distribution of optic flow in a neighborhood of a discontinuity; iv) spatial consistency of discontinuities; V) temporal consistency of discontinuities. The constraints are described, and experimental results on sequences of real and synthetic images are presented. The work has applications in the recovery of environmental structure from motion and in the generation of dense optic flow fields.
Are security lending fees priced? Theory and evidence from the U.S. treasury market

I present a dynamic model of short selling when the security borrowing for the short sale is restricted by search frictions. I analyze the case where short-selling demand is driven by hedging needs and contrast it with the case when short-selling demand arises from arbitrageur activity. Frictions lead to security borrowing fees and price premia arise from expected future fees in both cases. However, in the former, price premia are lower than the value of observed future borrowing fees. The Due(1996) result that prices exactly incorporate all future lending fees arises as a special case in the latter. The model features heterogeneity in the extents to which holders participate in repo markets, and explains why securities become “harder to locate” when the short interest is high. I apply the theoretical results to a time-series of repo-market fees and price premia in “on-the-run” U.S. treasury securities and show that repo fees in Treasury securities are primarily driven by hedging needs of short-sellers, rather than arbitrage activity. Additionally, I am able to match the dynamics of auction-cycle related patterns in prices and repo fees. I also show that the hedging benefits implied by specialness in U.S. treasuries are related to economy-wide risk factors, such as the return on the Fama-French book-to-market portfolio, the level of interest rates and the slope of the term-structure.
None But Ourselves Can Free Our Minds: Critical Computational Literacy as a Pedagogy of Resistance

ABSTRACT Critical computational literacy (CCL) is a new pedagogical and conceptual framework that combines the strengths of critical literacy and computational thinking. Through CCL, young people conceptualize, create, and disseminate digital projects that break silences, expose important truths, and challenge unjust systems, all the while building skills such as coding and design. This empirical study of CCL is based at Youth Radio, a nationally recognized multimedia production company in Oakland, California. Using embedded ethnographic methods, we focus on one collaborative project inside Youth Radio's Interactive department, where young people partnered with adult colleagues to produce a web-based interactive map of gentrification in a West Oakland neighborhood. Findings demonstrate a highly sophisticated knowledge production process where youth are simultaneously contending with content, message, audience, aesthetics, design, functionality, execution, and the long-term ramifications or “digital afterlife” of their work. Through learning environments organized around critical computational literacy, young people emerge as critical problem-solvers unified by the technical know-how and the critical consciousness necessary for them to leverage digital tools for social transformation.
Semantic Oscillations: Encoding Context and Structure in Complex Valued Holographic Vectors

In computational linguistics, information retrieval and applied cognition, words and concepts are often represented as vectors in high dimensional spaces computed from a corpus of text. These high dimensional spaces are often referred to as Semantic Spaces. We describe a novel and efficient approach to computing these semantic spaces via the use of complex valued vector representations. We report on the practical implementation of the proposed method and some associated experiments. We also briefly discuss how the proposed system relates to previous theoretical work in Information Retrieval and Quantum Mechanics and how the notions of probability, logic and geometry are integrated within a single Hilbert space representation. In this sense the proposed system has more general application and gives rise to a variety of opportunities for future research.
Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections

We consider stochastic strongly convex optimization with a complex inequality constraint. This complex inequality constraint may lead to computationally expensive projections in algorithmic iterations of the stochastic gradient descent~(SGD) methods. To reduce the computation costs pertaining to the projections, we propose an Epoch-Projection Stochastic Gradient Descent~(Epro-SGD) method. The proposed Epro-SGD method consists of a sequence of epochs; it applies SGD to an augmented objective function at each iteration within the epoch, and then performs a projection at the end of each epoch. Given a strongly convex optimization and for a total number of $T$ iterations, Epro-SGD requires only $\log(T)$ projections, and meanwhile attains an optimal convergence rate of $O(1/T)$, both in expectation and with a high probability. To exploit the structure of the optimization problem, we propose a proximal variant of Epro-SGD, namely Epro-ORDA, based on the optimal regularized dual averaging method. We apply the proposed methods on real-world applications; the empirical results demonstrate the effectiveness of our methods.
The effects of classroom interventions on anxiety disorders in elementary school children: A brief review

The purpose of this brief review was to evaluate the efficacy of classroom interventions for elementary children with anxiety disorders, specifically Generalized Anxiety Disorder, Social Phobia, and test anxiety. Three common interventions for these anxiety disorders are hypnosis, meditation, and cognitive behavioral therapy. Cognitive behavioral therapy as proven to be the most test and reliable intervention for treating anxiety disorders. Early intervention and prevention interventions have also been shown to dramatically decrease the risk of students for developing anxiety disorders later in life. Teachers should also be trained to detect and seek help for children in their classrooms who are suffering from anxiety.
Capacity of MIMO Wireless Systems, with Spatially Correlated Receive Elements

We present a general channel capacity model for a random A.W. G.N. channel in the presence of spatially correlated interference. We consider the case where the channel is random, and full rank and the number of receive elements is allowed to increase indefinitely within a given volume. We show that capacity of the channel does not increase indefinitely for densely packed elements. Moreover, the limit is governed by the correlation properties of the noise and the channel and as such, a power constraint on the receive elements is unnecessary. We examine two cases: the i.i. d. noise case and the spatially correlated noise case and show that bounds exist on the capacity in each case. Monte Carlo simulations are used to verify the results.
Recognition and Teaching of Robot Skills by Fuzzy Time-Modeling

Robot skills are low-level motion and/or grasping ca- pabilities that constitute the basic building blocks from which tasks are built. Teaching and recognition of such skills can be done by Programming-by-Demonstration approach. A human operator demonstrates certain skills while his motions are recorded by a data- capturing device and modeled in our case via fuzzy clustering and Takagi-Sugeno modeling technique. The resulting skill models use the time as input and the operator's actions and reactions as outputs. Given a test skill by the human operator the robot control system recognizes the individual phases of skills and generates the type of skill shown by the operator.
FAMILY SUPPORT FOR WOMEN’S HEALTH-SEEKING BEHAVIOR: A QUALITATIVE STUDY IN RURAL SOUTHERN EGYPT (UPPER EGYPT)

ABSTRACT This qualitative study investigated the influence of family support on women’s health-seeking behavior in rural southern Egypt (Upper Egypt). We carried out separate focus group discussions (FGDs) with 3 groups (6 women with children under 5 years old, 6 men, and 4 elderly women, respectively) in a village in Assiut Governorate, an underprivileged region in Upper Egypt. The FGDs aimed to identify how different types of family support affected women’s health-seeking behavior in areas including maternal health and common illnesses of women and children. Our results showed that maternal health issues were often discussed by husbands and wives, while mothers-in-law had little apparent influence. We also found that women could access support resources more easily than expected through their extended families. Our study showed that husbands had an important role in encouraging women’s health in the family, while the effect of mothers-in-law on women’s health-seeking behavior was not substantial. The study indicated that women received considerable support from co-resident family members, their natal family, and their neighbors, which helped women in seeking health services.
Chapter 3 Uncertainty in Spatial Trajectories

This chapter presents a systematic overview of the various issues and solutions related to the notion of uncertainty in the settings of moving objects trajectories. The sources of uncertainty in this context are plentiful: from the mere fact that the positioning devices are inherently imprecise, to the pragmatic aspect that, although the objects are moving continuously, location-based servers can only be updated in discrete times. Hence come the problems related to modelling and representing the uncertainty in Moving Objects Databases (MOD) and, as a consequence, problems of efficient algorithms for processing various spatio-temporal queries of interest. Given the ever-presence of uncertainty since the dawn of philosophy through modern day nano-level science, after a brief introduction, we present a historic overview of the role of uncertainty in parts of the evolution of the human thought in general, and Computer Science (CS) and databases in particular, which are relevant to this chapter. The focus of this chapter, however, will be on the impact that capturing the uncertainty in the syntax of the popular spatio-temporal queries has on their semantics and processing algorithms. We also consider the impact of different models in different settings – e.g., free motion; road-network constrained motion – and discuss the main issues related to exploiting such semantic dimension(s) for efficient query processing.
An Extension of ToscanaJ for FCA-based Data Analysis over Triple Stores

Classical Business Intelligence (BI) solutions provide different means like OLAP, data mining or case based reasoning to explore structured data. The data is usually stored in dedicated repositories like data warehouses and then explored by standard BI means, which are usually based on mathematical statistics and provide a quantitative analysis of the data. In this paper, we complement this approach in two respects. First of all, FCA, as a qualitative approach for data analysis, is used for analyzing the data. Second, the analyzed data is not stored in a data warehouse, but in a triple store instead. To make this possible, the existing FCA-tool ToscanaJ has been extended in order to act on triple stores. The approach in this paper is exemplified on a dataset of documents crawled from the SAP community network.
Learn Now, Pay Later: A History of Income-Contingent Student Loans in the United States

The idea of financing higher education with the income that comes afterward has been formally proposed and implemented in the United States, in various permutations, since at least 1971. The attractiveness of the concept is exemplified by the political diversity of its proponents, ranging from Senator Ted Kennedy to President Ronald Reagan, and from presidential candidates Michael Dukakis (Democratic governor who ran in 1988) to Jeb Bush (Republican former governor who ran in 2016). This article examines the design of the various proposals over time, the arguments in support and opposition, and the current state of affairs.
A hardware extension of the RISC microprocessor for Attribute Grammar evaluation

Conventional implementations of Attribute Grammar (AG) evaluators in embedded systems today, are solely of software nature. A compiler transforms the parser's specification along with the declarative attribute evaluation rules into a behaviorally equivalent procedural program to be executed on the microprocessor. This approach affects the final system's performance as well as the complexity of the final implementation. Efforts in presenting hardware implementations of AG evaluators, although efficient enough in terms of performance, are usually fully implemented in hardware and as a consequence restricted to a single application. We exploit HW/SW codesign methods in the effort of presenting a hardware implementation of AG evaluators that is both reprogrammable and increases the desired system's performance. We achieve that by extending a conventional RISC microprocessor by combining it with a programmable implementation of a hardware parser to propose a fully programmable AG evaluator that supports the execution of hybrid combinations of declarative-procedural code. The hardware parser increases design efficiency of tree derivations while the RISC microprocessor handles the attribute evaluation computations. As a result, performance is increased while design flexibility required in embedded system applications is preserved.
Fingerprint verification based on dual transformation technique

The Fingerprint is used to authenticate a person for multiple applications. In this paper, we propose Fingerprint Verification Based on Dual Transformation (FVDT). The Fingerprint image size of 300∗480 is segmented into four cells of each size 150∗240. The DCT is applied on each cell to convert from spatial domain to frequency domain. One level DWT is applied on DCT coefficients to derive four sub bands such as LL, LH, HL and HH. The directional information features and the centre area features on LL sub bands are computed. The final feature vector set is formed by concatenating directional information features and centre area features. The matching between database fingerprint and test fingerprint is based on ED, SVM and RF. It is observed that TSR and FRR values are improved in the case of proposed algorithm compared to the existing algorithm.
Person re-identification by features fusion

Person re-identification has an important role in the public security. The methods based on body segmentation have a good performance in distinguishing different people, but it will bring lots of calculation work. To solve this problem, a method combined color distribution fields and Weber Local Descriptor (WLD) is proposed. The method here takes advantage of the color distribution fields to extract the color information; and differential excitation in WLD to extract the texture information in images; and the gradient orientation to extract by orientation in WLD. The experiments show the method in this paper can achieve a good identification results in common data sets.