Miracle-dz/UniFAR-FTUs huggingface dataset:
Regulation of X-linked gene expression during early mouse development by Rlim

Mammalian X-linked gene expression is highly regulated as female cells contain two and male one X chromosome (X). To adjust the X gene dosage between genders, female mouse preimplantation embryos undergo an imprinted form of X chromosome inactivation (iXCI) that requires both Rlim (also known as Rnf12) and the long non-coding RNA Xist. Moreover, it is thought that gene expression from the single active X is upregulated to correct for bi-allelic autosomal (A) gene expression. We have combined mouse genetics with RNA-seq on single mouse embryos to investigate functions of Rlim on the temporal regulation of iXCI and Xist. Our results reveal crucial roles of Rlim for the maintenance of high Xist RNA levels, Xist clouds and X-silencing in female embryos at blastocyst stages, while initial Xist expression appears Rlim-independent. We find further that X/A upregulation is initiated in early male and female preimplantation embryos. DOI: http://dx.doi. org/10.7554/eLife.19127. 001
Is there a universal log law for turbulent wall-bounded flows?

The history and theory supporting the idea of a universal log law for turbulent wall-bounded flows are briefly reviewed. The original idea of justifying a log law from a constant Reynolds stress layer argument is found to be deficient. By contrast, it is argued that the logarithmic friction law and velocity profiles derived from matching inner and outer profiles for a pipe or channel flow are well-founded and consistent with the data. But for a boundary layer developing along a flat plate it is not, and in fact it is a power law theory that seems logically consistent. Even so, there is evidence for at least an empirical logarithmic fit to the boundary-friction data, which is indistinguishable from the power law solution. The value of κ≈0.38 obtained from a logarithmic curve fit to the boundary-layer velocity data, however, does not appear to be the same as for pipe flow for which 0.43 appears to be the best estimate. Thus, the idea of a universal log law for wall-bounded flows is not supported by either the theory or the data.
Libidibia ferrea Mature Seeds Promote Antinociceptive Effect by Peripheral and Central Pathway: Possible Involvement of Opioid and Cholinergic Receptors

Libidibia ferrea (LF) is a medicinal plant that holds many pharmacological properties. We evaluated the antinociceptive effect in the LF aqueous seed extract and Lipidic Portion of Libidibia ferrea (LPLF), partially elucidating their mechanisms. Histochemical tests and Gas chromatography of the LPLF were performed to characterize its fatty acids. Acetic acid-induced abdominal constriction, formalin-induced pain, and hot-plate test in mice were employed in the study. In all experiments, aqueous extract or LPLF was administered systemically at the doses of 1, 5, and 10 mg/kg. LF aqueous seed extract and LPLF demonstrated a dose-dependent antinociceptive effect in all tests indicating both peripheral anti-inflammatory and central analgesia properties. Also, the use of atropine (5 mg/kg), naloxone (5 mg/kg) in the abdominal writhing test was able to reverse the antinociceptive effect of the LPLF, indicating that at least one of LF lipids components is responsible for the dose related antinociceptive action in chemical and thermal models of nociception in mice. Together, the present results suggested that Libidibia ferrea induced antinociceptive activity is possibly related to its ability to inhibit opioid, cholinergic receptors, and cyclooxygenase-2 pathway, since its main component, linoleic acid, has been demonstrated to produce such effect in previous studies.
A Fine Grained Technique for Viral Marketing based on Social Network: A Machine Learning Approach

Social networking sites are the platform to share familiar interest, and it is free of charge. But the e-commerce made it possible for the Social applications (specially the games) a potential business sector for different game development firms. Collectively the main focus of Facebook applications is to connect a user with a network and to do so the games are initially free of cost. Although the developing firms can make profit with it but the main earnings are from virtual currency (e-commerce) by providing extra benefits with the game. The problem is to identify and segmenting the potential buyer for a game and how to do marketing. This research presents a machine learning approach to generate some efficient rule based decision for viral marketing.
Early detection of oxidized surfaces using Shewanella oneidensis MR-1 as a tool

Corrosion is a natural global problem of immense importance. Oxidation of iron and steel not only compromises the structural stability of a widely used and versatile material but it also creates an abrasive compound (iron oxide) that can score the surfaces of metals, rendering them useless for the purpose for which they were designed. Clearly, the identification of corrosion in its nascent stages is a high priority for reasons that range from aesthetics to economics. Many bacteria in the facultatively aerobic genus Shewanella have the capacity to respire some metal oxides, such as iron oxide, by way of a variety of oxide-binding proteins lodged in their outer membrane. In this study, a rapid, cost-effective system for the specific early detection of a variety of oxidized steel surfaces is described, taking advantage of bacteria with natural affinities for iron oxides, to identify the sites of nascent corrosion.
Understanding Researchers' Use of a Large, High-Resolution Display Across Disciplines

A driving force behind the design of increasingly large and high resolution displays (LHRDs) has been the need to support the explosion of data in the natural sciences such as physics, chemistry, and biology. However, our experience with an LHRD accessible to researchers across multiple disciplines has shown that they are useful for a wide range of research activities involving large images and data. \ We conducted in-context, semi-structured interviews with researchers from a variety of disciplines about their experiences using the LHRD with their own data. Notably, it became apparent that the size and resolution of the LHRD supported a multitude of activities related to observation, for which zooming or other enlargement methods on standard resolution screens were not sufficient. The interview findings lead to implications for further research into supporting a broader range of disciplines in using large, high-resolution displays.
Why Professional Athletes Need a Prolonged Period of Warm-Up and Other Peculiarities of Human Motor Learning

ABSTRACT Professional athletes involved in sports that require the execution of fine motor skills must practice for a considerable length of time before competing in an event. Why is such practice necessary? Is it merely to warm-up the muscles, tendons, and ligaments, or does the athlete's sensorimotor network need to be constantly recalibrated? In this article, the authors present a point of view in which the human sensorimotor system is characterized by: (a) a high noise level and (b) a high learning rate at the synaptic level (which, because of the noise, does not equate to a high learning rate at the behavioral level). They argue that many heuristics of human skill learning, including the need for a prolonged period of warm-up in experts, follow from these assumptions.
An Open Platform for Seamless Sensor Support in Healthcare for the Internet of Things

Population aging and increasing pressure on health systems are two issues that demand solutions. Involving and empowering citizens as active managers of their health represents a desirable shift from the current culture mainly focused on treatment of disease, to one also focused on continuous health management and well-being. Current developments in technological areas such as the Internet of Things (IoT), lead to new technological solutions that can aid this shift in the healthcare sector. This study presents the design, development, implementation and evaluation of a platform called Common Recognition and Identification Platform (CRIP), a part of the CareStore project, which aims at supporting caregivers and citizens to manage health routines in a seamless way. Specifically, the CRIP offers sensor-based support for seamless identification of users and health devices. A set of initial requirements was defined with a focus on usability limitations and current sensor technologies. The CRIP was designed and implemented using several technologies that enable seamless integration and interaction of sensors and people, namely Near Field Communication and fingerprint biometrics for identification and authentication, Bluetooth for communication with health devices and web services for wider integration with other platforms. Two CRIP prototypes were implemented and evaluated in laboratory during a period of eight months. The evaluations consisted of identifying users and devices, as well as seamlessly configure and acquire vital data from the last. Also, the entire Carestore platform was deployed in a nursing home where its usability was evaluated with caregivers. The evaluations helped assess that seamless identification of users and seamless configuration and communication with health devices is feasible and can help enable the IoT on healthcare applications. Therefore, the CRIP and similar platforms could be transformed into a valuable enabling technology for secure and reliable IoT deployments on the healthcare sector.
Automated delineation and quantitative analysis of blood vessels in retinal fundus image

Automated fundus image analysis plays an important role in the computer aided diagnosis of ophthalmologic disorders. A lot of eye disorders, as well as cardiovascular disorders, are known to be related with retinal vasculature changes. Many studies has been done to explore these relationships. However, most of the studies are based on limited data obtained using manual or semi-automated methods due to the lack of automated techniques in the measurement and analysis of retinal vasculature. In this thesis, a fully automated retinal vessel width measurement technique is proposed. This novel method models the accurate vessel boundary delineation problem in two-dimension into an optimal surface segmentation problem in threedimension. Then the optimal surface segmentation problem is transformed into finding a minimum-cost closed set problem in a vertex-weighted geometric graph. The problem is modeled differently for straight vessel and for branch point because of the different conditions in straight vessel and in branch point. Furthermore, many of the retinal image analysis needs the location of the optic disc and fovea as a prerequisite information, for example, in the analysis of the relationship between vessel width and the distance to the optic disc. Hence, a simultaneous optic disc and fovea detection method is presented, which includes a two-step classification of three classes. The major contributions of this thesis include: 1) developing a fully automated vessel width measurement technique for retinal blood vessels, 2) developing a simultaneous optic disc and fovea detection method, 3) validating the methods
Development and Validation of a Statistical Shape Modeling-Based Finite Element Model of the Cervical Spine Under Low-Level Multiple Direction Loading Conditions

Cervical spinal injuries are a significant concern in all trauma injuries. Recent military conflicts have demonstrated the substantial risk of spinal injury for the modern warfighter. Finite element models used to investigate injury mechanisms often fail to examine the effects of variation in geometry or material properties on mechanical behavior. The goals of this study were to model geometric variation for a set of cervical spines, to extend this model to a parametric finite element model, and, as a first step, to validate the parametric model against experimental data for low-loading conditions. Individual finite element models were created using cervical spine (C3–T1) computed tomography data for five male cadavers. Statistical shape modeling (SSM) was used to generate a parametric finite element model incorporating variability of spine geometry, and soft-tissue material property variation was also included. The probabilistic loading response of the parametric model was determined under flexion-extension, axial rotation, and lateral bending and validated by comparison to experimental data. Based on qualitative and quantitative comparison of the experimental loading response and model simulations, we suggest that the model performs adequately under relatively low-level loading conditions in multiple loading directions. In conclusion, SSM methods coupled with finite element analyses within a probabilistic framework, along with the ability to statistically validate the overall model performance, provide innovative and important steps toward describing the differences in vertebral morphology, spinal curvature, and variation in material properties. We suggest that these methods, with additional investigation and validation under injurious loading conditions, will lead to understanding and mitigating the risks of injury in the spine and other musculoskeletal structures.
D-Hive: Data Bees Pollinating RDF, Text, and Time

Although the problem of integrating IR and DB solutions is considered “old”, the increasing importance of big data analytics and its formidable demands for both enriched functionality and scalable performance creates the need to revisit the problem itself and to see possible solutions from a new perspective. Our goal is to develop a system that will make large corpora aware of entities and relationships (ER), addressing the challenges in searching and analyzing ER patterns in web data and social media. We put forward D-Hive, a system facilitating analytics over RDF-style (SPO) triples augmented with text and (validity / transaction) time capable of addressing the functionality and scalability requirements which current solutions cannot meet. We consider various alternatives for the data modeling, storage, indexing, and query processing engines of D-Hive paying attention to the challenges that must be met, which include i) scalable joint indexing of SPO-text-time tuples (quads, quints, octs, etc.), ii) efficient processing of complex queries that involve RDF star and path joins, filtering and grouping on text phrases, band joins over time, and more, as well as iii) optimizing the execution plans for such analytics.
Surface of glassy GeS[subscript 2]: A model based on a first-principles approach

Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. First-principles calculations within the framework of the density functional theory are used to construct realistic models for the surface of glassy GeS 2 (g-GeS 2). Both calculations at T = 0 K and at finite temperature (T = 300 K) are considered. This allows for a comparison between the structural and electronic properties of surface and bulk g-GeS 2. Although the g-GeS 2 surface recovers the main tetrahedral structural motif of bulk g-GeS 2 , the number of fourfold coordinated Ge atoms and twofold coordinated S atoms is smaller than in the bulk. On the contrary, the surface system features a larger content of overcoordinated S atoms and threefold coordinated Ge atoms. This effect is more important for the g-GeS 2 surface relaxed at 0 K. Maximally localized Wannier functions (WF) are used to inspect the nature of the chemical bonds of the structural units present at the g-GeS 2 surface. We compare the ability of several charge derivation methods to capture the atomic charge variations induced by a coordination change. Our estimate for the charges allows exploiting the first-principles results as a data base to construct a reliable interatomic force field.
In vivo gene transfer using cetylated polyethylenimine.

UNLABELLED This report describes gene transfer in vitro as well as in vivo using cetylated low-molecular mass (600 Da) polyethylenimine (28% of amine groups substituted with cetyl moieties), termed CT-PEI. This compound is hydrophobic and has to be incorporated into liposomes in order to be suitable for gene transfer studies. Serum-induced plasmid DNA degradation assay demonstrated that CT-PEI-containing liposomal carriers could protect complexed DNA (probably via condensation). In vitro luciferase gene expression achieved using medium supplemented with 10% serum was comparable to that achieved in serum-reduced medium and was highest for CT-PEI/cholesterol liposomes, followed by CT-PEI/dioleoylphosphatidylcholine liposomes and PEI 600 Da (uncetylated) carrier. In vivo systemic transfer into mice was most efficient when liposome formulations contained CT-PEI and cholesterol. Higher luciferase expression was then observed in lungs than in liver. IN CONCLUSION liposomes containing cetylated polyethylenimine and cholesterol are a suitable vehicle for investigating systemic plasmid DNA transfer into lungs.
How Does Noise Impact Speech-based Emotion Classification?

As an essential approach to understanding human interactions, emotion classification is a vital component in the design of human-computer interaction (HCI) systems. Speech contains rich information about emotion, but the impact of noise on the classification performance is still not well studied, especially for applications used in noisy mobile environments. For an emotion classification system using support vector machine with a threshold-based fusion mechanism, we study the impact of noisy speech data on the performance of emotion classification for a standard emotion database.
A Space-Bounded Anytime Algorithm for the Multiple Longest Common Subsequence Problem

The multiple longest common subsequence (MLCS) problem, related to the identification of sequence similarity, is an important problem in many fields. As an NP-hard problem, its exact algorithms have difficulty in handling large-scale data and timeand space-efficient algorithms are required in real-world applications. To deal with time constraints, anytime algorithms have been proposed to generate good solutions with a reasonable time. However, there exists little work on space-efficient MLCS algorithms. In this paper, we formulate the MLCS problem into a graph search problem and present two space-efficient anytime MLCS algorithms, SA-MLCS and SLA-MLCS. SA-MLCS uses an iterative beam widening search strategy to reduce space usage during the iterative process of finding better solutions. Based on SA-MLCS, SLA-MLCS, a space-bounded algorithm, is developed to avoid space usage from exceeding available memory. SLA-MLCS uses a replacing strategy when SA-MLCS reaches a given space bound. Experimental results show SA-MLCS and SLA-MLCS use an order of magnitude less space and time than the state-of-the-art approximate algorithm MLCS-APP while finding better solutions. Compared to the state-of-the-art anytime algorithm Pro-MLCS, SA-MLCS and SLA-MLCS can solve an order of magnitude larger size instances. Furthermore, SLA-MLCS can find much better solutions than SA-MLCS on large size instances.
Geo-Replication: Fast If Possible, Consistent If Necessary

Geo-replicated storage systems are at the core of current Internet services. Unfortunately, there exists a fundamental tension between consistency and performance for offering scalable geo-replication. Weakening consistency semantics leads to less coordination and consequently a good user experience, but it may introduce anomalies such as state divergence and invariant violation. In contrast, maintaining stronger consistency precludes anomalies but requires more coordination. This paper discusses two main contributions to address this tension. First, RedBlue Consistency enables blue operations to be fast (and weakly consistent) while the remaining red operations are strongly consistent (and slow). We identify sufficient conditions for determining when operations can be blue or must be red. Second, Explicit Consistency further increases the space of operations that can be fast by restricting the concurrent execution of only the operations that can break application-defined invariants. We further show how to allow operations to complete locally in the common case, by relying on a reservation system that moves coordination off the critical path of operation execution.
The TREC VIdeo Retrieval Evaluation (TRECVID): A Case Study and Status Report

The TREC Video Retrieval Evaluation (TRECVID) is an annual international effort, funded by the US Advanced Research and Development Agency (ARDA) and the National Institute of Standards and Technology (NIST) to promote progress in content-based retrieval from digital video via open, metrics-based evaluation. Now beginning its fourth year, TRECVID aims over time to develop both a better understanding of how systems can effectively accomplish video retrieval and how one can reliably benchmark their performance. This paper is a case study in the development of video retrieval systems and their evaluation as well as a report on the TRECVID status to-date. After an introduction to the evolution of TRECVID over the past 3 years, we report on the most recent evaluation TRECVID 2003 in terms of the 4 tasks (shot boundary determination, high-level feature extraction, story segmentation and classification, search), the data (133 hours of US television news), the measures, the results obtained, and the approaches taken by some of the 24 participating groups.
The Efficacy of Exposure and Response Prevention for Geriatric Obsessive Compulsive Disorder: A Clinical Case Illustration

Obsessive compulsive disorder (OCD) is one of the most frequently occurring psychiatric conditions in older adults. While exposure and response prevention (ERP) is considered the most effective psychological treatment for children and adults with OCD, research investigating its effectiveness for older adults is scarce. This clinical case study investigates the effectiveness of ERP in an 80-year-old man with a 65-year history of OCD. The client received 14 individual, 50-minute ERP treatment sessions. Clinician-based Y-BOCS scores reduced by 65% from 20 (moderate) at pretreatment to 7 (subclinical) at 7-month posttreatment followup. OCI-R total scores reduced by 45% from 38 at baseline to 21 at 7-month follow-up. Despite his long history of the disorder, ERP was effective and well tolerated. The application of ERP for older adults with OCD, including age-specific modifications that may be required for this treatment approach, is discussed.
Research on VRML Modeling for Web-Based Virtual Product Development

In this paper, we present the methods to develop the Web-based virtual product that is capable to dynamically simulate machine processes in solid graphics form through the Internet. The methods include the function-based virtual reality modeling language (VRML)shape modeling, which allows the content creators to describe any complex models with the mapping-based Route and Events description; the interaction of the virtual product realizing with drag sensors (DSs) of VRML, which allows users to be capable of handling virtual product with any desired precision. We illustrate the implementation of the proposed methods on the example of the interactive function-based shape modeling and DSs.