Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Diagnostic Genetic Testing Using Solution Capture Enrichment and a Novel Variant-Filtering Interface

Targeted hybridization enrichment prior to next‐generation sequencing is a widespread method for characterizing sequence variation in a research setting, and is being adopted by diagnostic laboratories. However, the number of variants identified can overwhelm clinical laboratories with strict time constraints, the final interpretation of likely pathogenicity being a particular bottleneck. To address this, we have developed an approach in which, after automatic variant calling on a standard unix pipeline, subsequent variant filtering is performed interactively, using AgileExomeFilter and AgilePindelFilter (http://dna.leeds.ac.uk/agile), tools designed for clinical scientists with standard desktop computers. To demonstrate the method's diagnostic efficacy, we tested 128 patients using (1) a targeted capture of 36 cancer‐predisposing genes or (2) whole‐exome capture for diagnosis of the genetically heterogeneous disorder primary ciliary dyskinesia (PCD). In the cancer cohort, complete concordance with previous diagnostic data was achieved across 793 variant genotypes. A high yield (42%) was also achieved for exome‐based PCD diagnosis, underscoring the scalability of our method. Simple adjustments to the variant filtering parameters further allowed the identification of a homozygous truncating mutation in a presumptive new PCD gene, DNAH8. These tools should allow diagnostic laboratories to expand their testing portfolios flexibly, using a standard set of reagents and techniques.
The random graph threshold for k-orientiability and a fast algorithm for optimal multiple-choice allocation

We investigate a linear time greedy algorithm for the following load balancing problem: Assign m balls to n bins such that the maximum occupancy is minimized. Each ball can be placed into one of two randomly choosen bins. This problem is closely related to the problem of orienting the edges of an undirected graph to obtain a directed graph with minimum in-degree. Using differential equation methods, we derive thresholds for the solution quality achieved by our algorithm. Since these thresholds coincide with lower bounds for the achievable solution quality, this proves the optimality of our algorithm (as n → ∞, in a probabilistic sense) and establishes the thresholds for k-orientability of random graphs. This proves an assertion of Karp and Saks.
Une technique de décomposition pour Max-CSP

The objective of the Maximal Constraint Satisfaction Problem (Max-CSP) is to ﬁnd an instantiation which minimizes the number of constraint violations in a constraint network. In this paper, inspired from the concept of inferred disjunctive constraints introduced by Freuder and Hubbe, we show that it is possible to exploit the arc-inconsistency counts, associated with each value of a network, in order to avoid exploring useless portions of the search space. The principle is to reason from the distance between the two best values in the domain of a variable, according to such counts. From this reasoning, we can build a decomposition technique which can be used throughout search in order to decompose the current problem into easier sub-problems. Interestingly, this approach does not depend on the structure of the constraint graph, as it is usually proposed. Alternatively, we can dynamically post hard constraints that can be used locally to prune the search space. The practical interest of our approach is illustrated, using this alternative, with an experimentation based on a classical branch and bound algorithm, namely PFC-MRDAC.
Identification of isolated biomechanical parameters with a wireless body sensor network

The accurate, real-time estimation of biomechanical joint parameters bears a potential benefit for many applications. Examples include the assessment of training success in movement therapy, the use as a quantitative clinical scale for joint rigidity or the use in the derivation of control parameters for active, intelligent orthotic or prosthetic devices. Such a realtime assessment system should be as unobtrusive as possible, minimising instrumentation effort for the user or the clinical staff. Towards this goal we have build a body sensor network (BSN) that is able to measure surface electromyogram and 9-degrees of freedom inertial/magnetic data at high sample rates. The measured data is preprocessed and subsequently used in an Unscented Kalman Filter in a model-based approach employing the nonlinear dynamics of the human knee kinematics. The derivation of biomechanical joint parameters, in our case the knee stiffness, can then be readily obtained from the nonlinear model. To validate BSN measurements, we present a novel test-bench and its corresponding nonlinear model. The biomechanical parameter estimator is validated in pendulum like motions on the test-bench and in experiments where the test subject is undergoing co-activation of extensor and flexor muscles acting on the knee.
The safety of St John's wort (Hypericum perforatum) in pregnancy and lactation: A systematic review of rodent studies

Herbal products are popular among women during the perinatal period. St John's wort (SJW), Hypericum perforatum, is a common remedy for mild depression, a problem prevalent in this population. Although the safety of herbal products must be investigated, ethical issues constrain intervention studies in humans. Hence, animal studies often inform clinical decisions. The objective of this study is to systematically review rodent studies assessing the safety of SJW during the perinatal period. A literature search to November 10, 2017, identified 10 rodent studies that met a priori inclusion criteria. Study quality was evaluated according to both the Systematic Review Centre for Laboratory animal Experimentation tool for assessing bias and recommendations for appropriate reporting of herbal medicine research. Significant methodological limitations were found in each of the studies reviewed. These limitations include the lack of botanical verification and omission of extract characterization, inadequate explanation of dosage rationale, and absence of bias limiting protocols. Critical appraisal with contemporary tools indicates that each of the reviewed studies lacks appropriate rigour, rendering the results unreliable. Despite this, these papers are used in the rationale for recommending or contraindicating SJW during pregnancy and lactation.
Measuring Up as an Intelligent Robot – On the Use of High-Fidelity Simulations for Human-Robot Interaction Research

In this article we describe and discuss how HiFi simulation methods, or Wizard-of-Oz [25], can be employed in a user-centered approach to develop natural language user interfaces for robots with cognitive capabilities. By actively shaping the system both in terms of technology and in interface design the interest of both users and designers are involved in the process as stake-holders. We have analyzed two different simulation studies performed sequentially with different foci, but within the same overall scenario. The data obtained from Hi-Fi simulation studies is to a large extent qualitative, but data can also be used as a resource to be used for component development, e.g. as training data for speech recognizers. The collected data may also be used for quantitative evaluation depending on the experiment design.
Axion inflation in type II string theory

Inflationary models driven by a large number of axion fields are discussed in the context of type IIB compactifications with N = 1 supersymmetry. The inflatons arise as the scalar modes of the R-R two-forms evaluated on vanishing two-cycles in the compact geometry. The vanishing cycles are resolved by small two-volumes or NS-NS B fields which sit together with the inflatons in the same supermultiplets. String world sheets wrapping the vanishing cycles correct the metric of the R-R inflatons. They can help to generate kinetic terms close to the Planck scale and a mass hierarchy between the axions and their nonaxionic partners during inflation. At small string coupling, D-brane corrections are subleading in the metric of the R-R inflatons. However, an axion potential can be generated by D1 instantons or gaugino condensates on D5-branes. Models with a sufficiently large number of axions admit regions of chaotic inflation which can stretch over the whole axion field range for potentials from gaugino condensates. These models could allow for a possibly detectable amount of gravitational waves with tensor to scalar ratio as high as r < 0.14.
A Systematic Search for Periodicities in RXTE ASM Data

We present the results of a systematic search in 8.5 yr of Rossi X-Ray Timing Explorer All-Sky Monitor data for evidence of periodicities. The search was conducted by application of the Lomb-Scargle periodogram to the light curves of each of 458 actually or potentially detected sources in each of four energy bands (1.5-3, 3-5, 5-12, and 1.5-12 keV). A whitening technique was applied to the periodograms before evaluation of the statistical significance of the powers. We discuss individual detections with a focus on relatively new findings.
Le développement social : nouveau discours et idéologie de la Banque Mondiale

En quelques années, le développement social est devenu un thème de prédilection de la Banque Mondiale. Souvent présentée comme la manifestation d’un changement de paradigme, l’approche en termes d’articulation des dimensions économiques, politiques et sociales du développement conduit la Banque Mondiale à concevoir des stratégies de lutte contre la pauvreté fondées sur le principe d’autonomie des pauvres, conjugué avec l’empowerment et la microfinance. Ces stratégies reposent sur des représentations idéalisées du développement et de la société marchande et proposent des réformes bien plus profondes que celles des années 1980 et 1990 : ce sont à présent les structures sociales et politiques, et plus seulement économiques, qui doivent être ajustées à un nouveau modèle de société.
Augmented Lagrangian alternating direction method for matrix separation based on low-rank factorization

The matrix separation problem aims to separate a low-rank matrix and a sparse matrix from their sum. This problem has recently attracted considerable research attention due to its wide range of potential applications. Nuclear-norm minimization models have been proposed for matrix separation and proved to yield exact separations under suitable conditions. These models, however, typically require the calculation of a full or partial singular value decomposition at every iteration that can become increasingly costly as matrix dimensions and rank grow. To improve scalability, in this paper, we propose and investigate an alternative approach based on solving a non-convex, low-rank factorization model by an augmented Lagrangian alternating direction method. Numerical studies indicate that the effectiveness of the proposed model is limited to problems where the sparse matrix does not dominate the low-rank one in magnitude, though this limitation can be alleviated by certain data pre-processing techniques. On the other hand, extensive numerical results show that, within its applicability range, the proposed method in general has a much faster solution speed than nuclear-norm minimization algorithms and often provides better recoverability.
IoNCloud: Exploring application affinity to improve utilization and predictability in datacenters

The intra-cloud network is typically shared in a best-effort manner, which causes tenant applications to have no actual bandwidth guarantees. Recent proposals address this issue either by statically reserving a slice of the physical infrastructure for each application or by providing proportional sharing among flows. The former approach results in overprovisioned network resources, while the latter requires substantial management overhead. In this paper, we introduce a resource allocation strategy that aims at providing an efficient way to predictably share bandwidth among applications and at minimizing resource underutilization while maintaining low management overhead. To demonstrate the benefits of the strategy, we develop IoNCloud, a system that implements the proposed allocation scheme. IoNCloud employs the abstraction of attraction/repulsion among applications according to their temporal bandwidth demands in order to group them in virtual networks. In doing so, we explore the trade-off between high resource utilization (which is desired by providers to achieve economies of scale) and strict network guarantees (necessary for tenants to run jobs predictably). Evaluation results show that IoNCloud can (a) provide predictable network sharing; and (b) reduce allocated bandwidth, resource underutilization and management overhead when compared against state-of-the-art proposals.
Referral and Diagnosis of Developmental Auditory Processing Disorder in a Large, United States Hospital-Based Audiology Service

Abstract Background: Children referred to audiology services with otherwise unexplained academic, listening, attention, language, or other difficulties are often found to be audiometrically normal. Some of these children receive further evaluation for auditory processing disorder (APD), a controversial construct that assumes neural processing problems within the central auditory nervous system. This study focuses on the evaluation of APD and how it relates to diagnosis in one large pediatric audiology facility. Purpose: To analyze electronic records of children receiving a central auditory processing evaluation (CAPE) at Cincinnati Children’s Hospital, with a broad goal of understanding current practice in APD diagnosis and the test information which impacts that practice. Research Design: A descriptive, cross-sectional analysis of APD test outcomes in relation to final audiologist diagnosis for 1,113 children aged 5–19 yr receiving a CAPE between 2009 and 2014. Results: Children had a generally high level of performance on the tests used, resulting in marked ceiling effects on about half the tests. Audiologists developed the diagnostic category “Weakness” because of the large number of referred children who clearly had problems, but who did not fulfill the AAA/ASHA criteria for diagnosis of a “Disorder. ” A “right-ear advantage” was found in all tests for which each ear was tested, irrespective of whether the tests were delivered monaurally or dichotically. However, neither the side nor size of the ear advantage predicted the ultimate diagnosis well. Cooccurrence of CAPE with other learning problems was nearly universal, but neither the number nor the pattern of cooccurring problems was a predictor of APD diagnosis. The diagnostic patterns of individual audiologists were quite consistent. The number of annual assessments decreased dramatically during the study period. Conclusions: A simple diagnosis of APD based on current guidelines is neither realistic, given the current tests used, nor appropriate, as judged by the audiologists providing the service. Methods used to test for APD must recognize that any form of hearing assessment probes both sensory and cognitive processing. Testing must embrace modern methods, including digital test delivery, adaptive testing, referral to normative data, appropriate testing for young children, validated screening questionnaires, and relevant objective (physiological) methods, as appropriate. Audiologists need to collaborate with other specialists to understand more fully the behaviors displayed by children presenting with listening difficulties. To achieve progress, it is essential for clinicians and researchers to work together. As new understanding and methods become available, it will be necessary to sort out together what works and what doesn’t work in the clinic, both from a theoretical and a practical perspective.
Human action recognition based on 3D SIFT and LDA model

How to recognize human action from videos captured by modern cameras efficiently and effectively is a challenge in real applications. Traditional methods which need professional analysts are facing a bottleneck because of their shortcomings. To cope with the disadvantage, methods based on computer vision techniques, without or with only a few human interventions, have been proposed to analyse human actions in videos automatically. This paper provides a method combining the three dimensional Scale Invariant Feature Transform (SIFT) detector and the Latent Dirichlet Allocation (LDA) model for human motion analysis. To represent videos effectively and robustly, we extract the 3D SIFT descriptor around each interest point, which is sampled densely from 3D Space-time video volumes. After obtaining the representation of each video frame, the LDA model is adopted to discover the underlying structure-the categorization of human actions in the collection of videos. Public available standard datasets are used to test our method. The concluding part discusses the research challenges and future directions.
Recent novel approaches to limit oxidative stress and inflammation in diabetic complications

Diabetes is considered a major burden on the healthcare system of Western and non‐Western societies with the disease reaching epidemic proportions globally. Diabetic patients are highly susceptible to developing micro‐ and macrovascular complications, which contribute significantly to morbidity and mortality rates. Over the past decade, a plethora of research has demonstrated that oxidative stress and inflammation are intricately linked and significant drivers of these diabetic complications. Thus, the focus now has been towards specific mechanism‐based strategies that can target both oxidative stress and inflammatory pathways to improve the outcome of disease burden. This review will focus on the mechanisms that drive these diabetic complications and the feasibility of emerging new therapies to combat oxidative stress and inflammation in the diabetic milieu.
Scale transformations, tree-level perturbation theory and the cosmological matter bispectrum

Scale transformations have played an extremely successful role in studies of cosmological large-scale structure by relating the non-linear spectrum of cosmological density fluctuations to the linear primordial power at longer wavelengths. Here, we generalize this approach to investigate the usefulness of scale transformations for non-linear higher order statistics, specifically the bispectrum. We find that the bispectrum predicted by perturbation theory at tree level can be rescaled to match the results of full numerical simulations in the weakly and intermediately non-linear regimes, especially at high redshifts, with an accuracy that is surprising given the simplicity of the procedure used. This discovery not only offers a simple practical way of calculating the matter bispectrum but also suggests that scale transformations may yet yield even deeper insights into the physics of hierarchical clustering.
Activation of Resistance Arteries with Endothelin-1: From Vasoconstriction to Functional Adaptation and Remodeling

Remodeling of resistance arteries is a key feature in hypertension. We studied the transition of vasoconstriction to remodeling in isolated rat skeletal muscle arterioles. Arterioles activated with 10 nM endothelin-1 showed functional adaptation when kept at low distension in a wire myograph setup, where contractile properties shifted towards a smaller lumen diameter after 1 day. Pressurized arteries kept in organoid culture showed physical inward remodeling after 3-day activation with 10 nM endothelin-1, characterized by a reduction in relaxed diameter without a change in the wall cross-sectional area (eutrophic remodeling). The relaxed lumen diameter (at 60 mm Hg) decreased from 169 ± 5 (day 0) to 155 ± 4 µm (day 3). An antibody directed to the β3-integrin subunit (but not one directed to the β1-integrin subunit) enhanced remodeling, from a reduction in relaxed diameter at 60 mm Hg of 15 ± 2.4 to 22 ± 1.8 µm (both on day 3). Collagen gel contraction experiments showed that the antibody directed to the β3-integrin subunit enhanced the compaction of collagen by smooth muscle cells, from 83 ± 1.5 to 68 ± 1.5% of the initial gel diameter. In conclusion, these data show that inward eutrophic remodeling is a response to sustained contraction, which may involve collagen reorganization through β3-integrins.
Digitality and materiality of new media: online TV watching in china

This paper examines issues of digitality and materiality of new media, grounded in a study of online TV watching in China. Particularly, by looking at how people make choices and decisions regarding TV watching in everyday life, we highlight material and digital properties of new media TV, and how they support and condition actions and interactions around them. The study illustrates that materiality and digitality are complementary, instead of one substituting the other, and are highly intertwined in the hybrid media environment around which meaningful experiences are conditioned and produced. It also suggests that an analytic distinction between materiality and digitality is fruitful in unpacking the complex relations between media technologies and social experiences.
A Survey on Antidiscrimination using Direct and Indirect Methods in Data Mining

Data mining is the study of data for relationships that have not previously been discovered. In sociology, discrimination is the hurtful treatment of an individual based on the group, class or category to which that person or things belongs rather than on individual merit: racial and religious intolerance and discrimination. Along with confidentiality, discrimination is a very essential issue when considering the legal and ethical aspects of data mining. It is more than obvious that most people do not want to be discriminated because of their race, gender, religion, nationality, age etc, especially when those attributes are used for making decisions about them like giving them a job, loan, education, insurance etc. Because of this reason, antidiscrimination techniques with discrimination discovery as well as discrimination prevention have been introduced in data mining. Discrimination can be either direct or indirect. Direct discrimination occurs when decisions are taken by considering sensitive attributes. Indirect discrimination occurs when decisions are taken on the basis of nonsensitive attributes which are strongly associated with biased sensitive ones. Here, discrimination prevention in data mining is tackle as well as propose new techniques applicable for direct or indirect discrimination prevention individually or both at the same time. Several decision-making tasks are there which let somebody use themselves to discrimination, such as education, life insurances, loan granting, and staff selection. In many applications, information systems are used for decision-making tasks.