nils-herrmann/clean_scirepeval huggingface dataset:
A D53 repression motif induces oligomerization of TOPLESS corepressors and promotes assembly of a corepressor-nucleosome complex

TOPLESS are tetrameric plant corepressors of the conserved Tup1/Groucho/TLE (transducin-like enhancer of split) family. We show that they interact through their TOPLESS domains (TPDs) with two functionally important ethylene response factor–associated amphiphilic repression (EAR) motifs of the rice strigolactone signaling repressor D53: the universally conserved EAR-3 and the monocot-specific EAR-2. We present the crystal structure of the monocot-specific EAR-2 peptide in complex with the TOPLESS-related protein 2 (TPR2) TPD, in which the EAR-2 motif binds the same TPD groove as jasmonate and auxin signaling repressors but makes additional contacts with a second TPD site to mediate TPD tetramer-tetramer interaction. We validated the functional relevance of the two TPD binding sites in reporter gene assays and in transgenic rice and demonstrate that EAR-2 binding induces TPD oligomerization. Moreover, we demonstrate that the TPD directly binds nucleosomes and the tails of histones H3 and H4. Higher-order assembly of TPD complexes induced by EAR-2 binding markedly stabilizes the nucleosome-TPD interaction. These results establish a new TPD-repressor binding mode that promotes TPD oligomerization and TPD-nucleosome interaction, thus illustrating the initial assembly of a repressor-corepressor-nucleosome complex.
Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

We propose a real-time RGB-based pipeline for object detection and 6D pose estimation. Our novel 3D orientation estimation is based on a variant of the Denoising Autoencoder that is trained on simulated views of a 3D model using Domain Randomization. This so-called Augmented Autoencoder has several advantages over existing methods: It does not require real, pose-annotated training data, generalizes to various test sensors and inherently handles object and view symmetries. Instead of learning an explicit mapping from input images to object poses, it provides an implicit representation of object orientations defined by samples in a latent space. Experiments on the T-LESS and LineMOD datasets show that our method outperforms similar modelbased approaches and competes with state-of-the art approaches that require real pose-annotated images.
Entity Recommendations in Web Search

While some web search users know exactly what they are looking for, others are willing to explore topics related to an initial interest. Often, the user’s initial interest can be uniquely linked to an entity in a knowledge base. In this case, it is natural to recommend the explicitly linked entities for further exploration. In real world knowledge bases, however, the number of linked entities may be very large and not all related entities may be equally relevant. Thus, there is a need for ranking related entities. In this paper, we describe Spark, a recommendation engine that links a user’s initial query to an entity within a knowledge base and provides a ranking of the related entities. Spark extracts several signals from a variety of data sources, including Yahoo! Web Search, Twitter, and Flickr, using a large cluster of computers running Hadoop. These signals are combined with a machine learned ranking model in order to produce a final recommendation of entities to user queries. This system is currently powering Yahoo! Web Search result pages.
A more powerful exact test of noninferiority from binary matched-pairs data.

Assessing the therapeutic noninferiority of one medical treatment compared with another is often based on the difference in response rates from a matched binary pairs design. This paper develops a new exact unconditional test for noninferiority that is more powerful than available alternatives. There are two new elements presented in this paper. First, we introduce the likelihood ratio statistic as an alternative to the previously proposed score statistic of Nam (Biometrics 1997; ). Second, we eliminate the nuisance parameter by estimation followed by maximization as an alternative to the partial maximization of Berger and Boos (; 89:1012-1016) or traditional full maximization. Based on an extensive numerical study, we recommend tests based on the score statistic, the nuisance parameter being controlled by estimation followed by maximization.
An Efficient Exact-PGA Algorithm for Constant Curvature Manifolds

Manifold-valued datasets are widely encountered in many computer vision tasks. A non-linear analog of the PCA algorithm, called the Principal Geodesic Analysis (PGA) algorithm suited for data lying on Riemannian manifolds was reported in literature a decade ago. Since the objective function in the PGA algorithm is highly non-linear and hard to solve efficiently in general, researchers have proposed a linear approximation. Though this linear approximation is easy to compute, it lacks accuracy especially when the data exhibits a large variance. Recently, an alternative called the exact PGA was proposed which tries to solve the optimization without any linearization. For general Riemannian manifolds, though it yields a better accuracy than the original (linearized) PGA, for data that exhibit large variance, the optimization is not computationally efficient. In this paper, we propose an efficient exact PGA algorithm for constant curvature Riemannian manifolds (CCM-EPGA). The CCM-EPGA algorithm differs significantly from existing PGA algorithms in two aspects, (i) the distance between a given manifold-valued data point and the principal submanifold is computed analytically and thus no optimization is required as in the existing methods. (ii) Unlike the existing PGA algorithms, the descent into codimension-1 submanifolds does not require any optimization but is accomplished through the use of the Rimeannian inverse Exponential map and the parallel transport operations. We present theoretical and experimental results for constant curvature Riemannian manifolds depicting favorable performance of the CCM-EPGA algorithm compared to existing PGA algorithms. We also present data reconstruction from the principal components which has not been reported in literature in this setting.
IEEE 802 . 15 . 4 e : a Survey

Several studies have highlighted that the IEEE 802.15.4 standard presents a number of limitations such as low reliability, unbounded packet delays and no protection against interference/fading, that prevent its adoption in applications with stringent requirements in terms of reliability and latency. Recently, the IEEE has released the 802.15.4e amendment that introduces a number of enhancements/modifications to the MAC layer of the original standard in order to overcome such limitations. In this paper we provide a clear and structured overview of all the new 802.15.4e mechanisms. After a general introduction to the 802.15.4e standard, we describe the details of the main 802.15.4e MAC behavior modes, namely Time Slotted Channel Hopping (TSCH), Deterministic and Synchronous Multichannel Extension (DSME), and Low Latency Deterministic Network (LLDN). For each of them, we provide a detailed description and highlight the main features and possible application domains. Also, we survey the current literature and summarize open research issues.
A Novel Piezoactuated XY Stage With Parallel, Decoupled, and Stacked Flexure Structure for Micro-/Nanopositioning

This paper presents the design and manufacturing processes of a new piezoactuated XY stage with integrated parallel, decoupled, and stacked kinematics structure for micro-/nanopositioning application. The flexure-based XY stage is composed of two decoupled prismatic-prismatic limbs which are constructed by compound parallelogram flexures and compound bridge-type displacement amplifiers. The two limbs are assembled in a parallel and stacked manner to achieve a compact stage with the merits of parallel kinematics. Analytical models for the mechanical performance assessment of the stage in terms of kinematics, statics, stiffness, load capacity, and dynamics are derived and verified with finite element analysis. A prototype of the XY stage is then fabricated, and its decoupling property is tested. Moreover, the Bouc-Wen hysteresis model of the system is identified by resorting to particle swarm optimization, and a control scheme combining the inverse hysteresis model-based feedforward with feedback control is employed to compensate for the plant nonlinearity and uncertainty. Experimental results reveal that a submicrometer accuracy single-axis motion tracking and biaxial contouring can be achieved by the micropositioning system, which validate the effectiveness of the proposed mechanism and controller designs as well.
From a Federated to an Integrated Automotive Architecture

This paper describes an integrated system architecture for automotive electronic systems based on multicore systems-on-chips (SoCs). We integrate functions from different suppliers into a few powerful electronic control units using a dedicated core for each function. This work is fueled by technological opportunities resulting from recent advances in the semiconductor industry and the challenges of providing dependable automotive electronic systems at competitive costs. The presented architecture introduces infrastructure IP cores to overcome key challenges in moving to automotive multicore SoCs: a time-triggered network-on-a-chip with fault isolation for the interconnection of functional IP cores, a diagnostic IP core for error detection and state recovery, a gateway IP core for interfacing legacy systems, and an IP core for reconfiguration. This paper also outlines the migration from today's federated architectures to the proposed integrated architecture using an exemplary automotive E/E system.
PCB substrate integrated waveguide-filter using via fences at millimeter-wave

In this paper, the implementation and the embedding method of the existing air-filled waveguide-filters at millimeter-wave on general Printed Circuit Board(PCB) substrate are introduced by systematically inserting the vias inside waveguide and mathematically manipulating the simple equations obtained from the classical circular-post waveguide the wave propagation. Because the mass production on PCB is possible without fabricating a large-scaled metal waveguide of WR-22 as input/output ports at millimeter-wave, th Bandpass-Filter(BPF) design procedure. Side walls and poles inside the waveguide are realized by placing two series array of via and tuning the via diameters. The each length of x, y, and z axes is reduced in proportion to root square of employed substrate dielectric constant and, especially, the length of z-axis can be more reduced due to the characteristics of e manufacturing cost can be reduced considerably. Finally, when using multi-layer process like low temperature cofired ceramic(LTCC) for small-sized module, it is one of advantages to use only one layer for the filter fabrication. To evaluate the validity of this novel technique, order-3 Chebyshev BPF centered at 40 GHz-band with a 2.5% Fractional Bandwidth(FBW) was used. The employed substrate has relative dielectric constant of 2.2 and thickness of 10 mils of Rogers RT/Duroid 5880. According to design and measurement results, a good performance of insertion loss of 2 dB and return loss of -30 dB is achieved at full input/output ports.
Using positive tainting and syntax-aware evaluation to counter SQL injection attacks

SQL injection attacks pose a serious threat to the security of Web applications because they can give attackers unrestricted access to databases that contain sensitive information. In this paper, we propose a new, highly automated approach for protecting existing Web applications against SQL injection. Our approach has both conceptual and practical advantages over most existing techniques. From the conceptual standpoint, the approach is based on the novel idea of positive tainting and the concept of syntax-aware evaluation. From the practical standpoint, our technique is at the same time precise and efficient and has minimal deployment requirements. The paper also describes wasp, a tool that implements our technique, and a set of studies performed to evaluate our approach. In the studies, we used our tool to protect several Web applications and then subjected them to a large and varied set of attacks and legitimate accesses. The evaluation was a complete success: wasp successfully and efficiently stopped all of the attacks without generating any false positives.
Keep Your Friends Close and Your Facebook Friends Closer: A Multiplex Network Approach to the Analysis of Offline and Online Social Ties

Social media allow for an unprecedented amount of interactions and information exchange between people online. A fundamental aspect of human social behavior, however, is the tendency of people to associate themselves with like-minded individuals, forming homogeneous social circles both online and offline. In this work, we apply a new model that allows us to distinguish between social ties of varying strength, and to observe evidence of homophily with regards to politics, music, health, residential sector & year in college, within the online and offline social network of 74 college students. We present a multiplex network approach to social tie strength, here applied to mobile communication data calls, text messages, and co-location, allowing us to dimensionally identify relationships by considering the number of channels utilized between students. We find that strong social ties are characterized by maximal use of communication channels, while weak ties by minimal use. We are able to identify 75% of close friendships, 90% of weaker ties, and 90% of Facebook friendships as compared to reported ground truth. We then show that stronger ties exhibit greater profile similarity than weaker ones. Apart from high homogeneity in social circles with respect to political and health aspects, we observe strong homophily driven by music, residential sector and year in college. Despite Facebook friendship being highly dependent on residence and year, exposure to less homogeneous content can be found in the online rather than the offline social circles of students, most notably in political and music aspects.
Real Time Vehicle Security System through Face Recognition

In this modern age there is rapid increase in number of vehicles and so is the number of car theft attempts, locally and internationally. With the invention of strong stealing techniques, owners are in fear of having their vehicles being stolen from common parking lot or from outside their home. Thus the protection of vehicles from theft becomes important due to insecure environment. Real time vehicle security system based on computer vision provides a solution to this problem. The proposed vehicle security system performs image processing based real time user authentication using face detection and recognition techniques and microprocessor based control system fixed on board with the vehicle. As the person enters the parked car overcoming the existing security features, the infrared sensor attached to the driver’s seat of the vehicle activates the hidden camera fixed in appropriate position inside the vehicle. As soon as the image is acquired from the activated camera, face of the person is detected using Viola Jones algorithm. The extracted face is recognized using the enhanced Linear Discriminant Analysis (LDA) algorithm which discriminates much of the features rather than looking for exact pattern based on Euclidean distance and also reliable to be used with large samples of data. Performing authorization involves setting the threshold value and comparing with that of Euclidean distance above which the person is not authenticated. The face of the person which is classified as unknown is sent to the mobile of the owner as a MMS through the operating GSM modem. The owner upon receiving the information commands the system and the fuel is regulated using the relay in accordance with the command of the owner. This would be C. Nandakumar et al 372 effective to authenticate the person under different environment and to have an efficient way of vehicle security.
Mesh Learning for Classifying Cognitive Processes

A relatively recent advance in cognitive neuroscience has been multi-voxel pattern analysis (MVPA), which enables researchers to decode brain states and/or the type of information represented in the brain during a cognitive operation. MVPA methods utilize machine learning algorithms to distinguish among types of information or cognitive states represented in the brain, based on distributed patterns of neural activity. In the current investigation, we propose a new approach for representation of neural data for pattern analysis, namely a Mesh Learning Model. In this approach, at each time instant, a star mesh is formed around each voxel, such that the voxel corresponding to the center node is surrounded by its p-nearest neighbors. The arc weights of each mesh are estimated from the voxel intensity values by least squares method. The estimated arc weights of all the meshes, called Mesh Arc Descriptors (MADs), are then used to train a classifier, such as Neural Networks, k-Nearest Neighbor, Naïve Bayes and Support Vector Machines. The proposed Mesh Model was tested on neuroimaging data acquired via functional magnetic resonance imaging (fMRI) during a recognition memory experiment using categorized word lists, employing a previously established experimental paradigm (Öztekin & Badre, 2011). Results suggest that the proposed Mesh Learning approach can provide an effective algorithm for pattern analysis of brain activity during cognitive processing.
Energy production from biomass (Part 1): Overview of biomass.

The use of renewable energy sources is becoming increasingly necessary, if we are to achieve the changes required to address the impacts of global warming. Biomass is the most common form of renewable energy, widely used in the third world but until recently, less so in the Western world. Latterly much attention has been focused on identifying suitable biomass species, which can provide high-energy outputs, to replace conventional fossil fuel energy sources. The type of biomass required is largely determined by the energy conversion process and the form in which the energy is required. In the first of three papers, the background to biomass production (in a European climate) and plant properties is examined. In the second paper, energy conversion technologies are reviewed, with emphasis on the production of a gaseous fuel to supplement the gas derived from the landfilling of organic wastes (landfill gas) and used in gas engines to generate electricity. The potential of a restored landfill site to act as a biomass source, providing fuel to supplement landfill gas-fuelled power stations, is examined, together with a comparison of the economics of power production from purpose-grown biomass versus waste-biomass. The third paper considers particular gasification technologies and their potential for biomass gasification.
A system for high-volume acquisition and matching of fresco fragments: reassembling Theran wall paintings

Although mature technologies exist for acquiring images, geometry, and normals of small objects, they remain cumbersome and time-consuming for non-experts to employ on a large scale. In an archaeological setting, a practical acquisition system for routine use on every artifact and fragment would open new possibilities for archiving, analysis, and dissemination. We present an inexpensive system for acquiring all three types of information, and associated metadata, for small objects such as fragments of wall paintings. The acquisition system requires minimal supervision, so that a single, non-expert user can scan at least 10 fragments per hour. To achieve this performance, we introduce new algorithms to robustly and automatically align range scans, register 2-D scans to 3-D geometry, and compute normals from 2-D scans. As an illustrative application, we present a novel 3-D matching algorithm that efficiently searches for matching fragments using the scanned geometry.
Foreign body in scrotum following a boat engine blast accident.

Male genital injuries, demand prompt management to prevent long-term sexual and psychological damage. Injuries to the scrotum and contents may produce impaired fertility.We report our experience in diagnosing and managing a case of a foreign body in the scrotum following a boat engine blast accident. This case report highlights the need for a good history and thorough general examination to establish the mechanism of injury in order to distinguish between an embedded penetrating projectile injury and an injury with an exit wound. Prompt surgical exploration with hematoma evacuation limits complications.
DroidJust: automated functionality-aware privacy leakage analysis for Android applications

Android applications (apps for short) can send out users' sensitive information against users' intention. Based on the stats from Genome and Mobile-Sandboxing, 55.8% and 59.7% Android malware families feature privacy leakage. Prior approaches to detecting privacy leakage on smartphones primarily focused on the discovery of sensitive information flows. However, Android apps also send out users' sensitive information for legitimate functions. Due to the fuzzy nature of the privacy leakage detection problem, we formulate it as a justification problem, which aims to justify if a sensitive information transmission in an app serves any purpose, either for intended functions of the app itself or for other related functions. This formulation makes the problem more distinct and objective, and therefore more feasible to solve than before. We propose DroidJust, an automated approach to justifying an app's sensitive information transmission by bridging the gap between the sensitive information transmission and application functions. We also implement a prototype of DroidJust and evaluate it with over 6000 Google Play apps and over 300 known malware collected from VirusTotal. Our experiments show that our tool can effectively and efficiently analyze Android apps w.r.t their sensitive information flows and functionalities, and can greatly assist in detecting privacy leakage.
Efficacy of photodynamic therapy combined with minocycline for treatment of moderate to severe facial acne vulgaris and influence on quality of life

Acne vulgaris is a prevalent skin disorder impairing both physical and psychosocial health. This study was designed to investigate the effectiveness of photodynamic therapy (PDT) combined with minocycline in moderate to severe facial acne and influence on quality of life (QOL).



Ninety-five patients with moderate to severe facial acne (Investigator Global Assessment [IGA] score 3-4) were randomly treated with PDT and minocycline (n = 48) or minocycline alone (n = 47). All patients took minocycline hydrochloride 100 mg/d for 4 weeks, whereas patients in the minocycline plus PDT group also received 4 times PDT treatment 1 week apart. IGA score, lesion counts, Dermatology Life Quality Index (DLQI), and safety evaluation were performed before treatment and at 2, 4, 6, and 8 weeks after enrolment.



There were no statistically significant differences in characteristics between 2 treatment groups at baseline. Minocycline plus PDT treatment led to a greater mean percentage reduction from baseline in lesion counts versus minocycline alone at 8 weeks for both inflammatory (-74.4% vs -53.3%; P < .001) and noninflammatory lesions (-61.7% vs -42.4%; P < .001). More patients treated with minocycline plus PDT achieved IGA score <2 at study end (week 8: 30/48 vs 20/47; P < .05). Patients treated with minocycline plus PDT got significant lower DLQI at 8 weeks (4.4 vs 6.3; P < .001). Adverse events were mild and manageable.



Compared with minocycline alone, the combination of PDT with minocycline significantly improved clinical efficacy and QOL in moderate to severe facial acne patients.