Miracle-dz/UniFAR-FTUs huggingface dataset:
Title Blockin(working): Blockina Blockinfacilitated Blockindiffusion Blockinmechanism Blockinestablishes Blockinthe Blockindrosophila Blockindorsal Blockingradient

The transcription factor NF-κB plays an important role in the immune system as an apoptotic and inflammatory factor. In the Drosophila melanogaster embryo, a homolog of NF-κB called Dorsal (dl) patterns the dorsal-ventral (DV) axis in a concentration-dependent manner. During early development, dl is sequestered outside the nucleus by Cactus (Cact), homologous to IκB. Toll signaling at the ventral midline breaks the dl/Cact complex, allowing dl to enter the nucleus where it transcribes target genes. Here we show that dl accumulates on the ventral side of the embryo over the last 5 cleavage cycles and that this accumulation is the result of facilitated diffusion of dl/Cact complex. We speculate that the predominant role for Cact in DV axis specification is to shuttle dl towards the ventral midline. Given that this mechanism has been found in other, independent systems, we suggest it may be more prevalent than previously thought.
Generification by Translation: Designing Generic Systems in Context of the Local

The implementation of large generic systems in organizations is associated with many benefits. Some of these are institutional-wide coverage, streamlining of work practices, and the possibility to reuse systems across many institutional settings. However, many studies have noted how organizations are different and therefore may have diverging needs (e.g., Berg, 1999; Berg & Goorman, 1999; Star & Ruhleder, 1996). Accordingly, it is crucial for an organization’s vendors and project managers to align local needs with technical opportunities in order to establish a well-working system. Pollock and Williams (2008) have coined this process “generification”, and describe it as the vendors’ strategy of making a generic system work in several settings. Together with customization capabilities of the software, generification involves social processes of ordering, prioritizing, and persuading users in order to motivate them to use similar versions of the same system that is installed in different organizations (Pollock & Williams, 2008) Currently, the mechanisms of generification during implementation and use are well known (see, e.g., Pollock & Williams, 2008), but we have less insight about the generification processes in the design phase and to what extent local knowledge is exploited in the process. Therefore, this paper extends the notion of generification to the formative stages of generic systems and provides insight about the key mechanisms at play in this crucial phase.
ASYMMETRIC TURBO CODES FOR LTE SYSTEMS WITH MEDIUM FRAME LENGTH

The selection of the component codes of turbo codes has a major influence on the performance of these codes. In this paper we propose a new type of asymmetric turbo codes for medium length of interleaver, based on the selection algorithm for the generating polynomials matched to a largest spread QPP interleaver. From the performance results one can observe that the new asymmetric turbo codes perform better than the existing ones.
KNN-based color line model for image matting

Image matting is the extraction of a foreground object from an image and determination of the transparency of each pixel. Matting is inherently an ill-posed and underconstrained problem. Therefore, some assumptions need to be made to solve it. Recent methods that provide a closed-form solution to this problem are based on the assumption of either local smoothness or the nonlocal principle, but they cannot always produce satisfactory matting results. In this paper, we propose a K-nearest neighbors (KNN)-based color line model that combines and preserves the advantages of both the above assumptions. The experimental matting results indicate that they are of comparable or higher quality than those obtained by the existing methods based on the above two assumptions.
Committees of Undemocratic Competent Models

Committees of classification and approximation models are used to improve accuracy and decrease the variance of individual models. Each model has an equal right to vote (democratic procedure), despite obvious differences in model competence in different regions of the feature space. Adding competence factors to different models before calculation of the committee decision (undemocratic procedure) improves the quality of the committee. A method for creation of a committee of competent models is described and several real-life empirical tests performed. Significant improvement of results is observed.
A baseline algorithm for face detection and tracking in video

Establishing benchmark datasets, performance metrics and baseline algorithms have considerable research significance in gauging the progress in any application domain. These primarily allow both users and developers to compare the performance of various algorithms on a common platform. In our earlier works, we focused on developing performance metrics and establishing a substantial dataset with ground truth for object detection and tracking tasks (text and face) in two video domains -- broadcast news and meetings. In this paper, we present the results of a face detection and tracking algorithm on broadcast news videos with the objective of establishing a baseline performance for this task-domain pair. The detection algorithm uses a statistical approach that was originally developed by Viola and Jones and later extended by Lienhart. The algorithm uses a feature set that is Haar-like and a cascade of boosted decision tree classifiers as a statistical model. In this work, we used the Intel Open Source Computer Vision Library (OpenCV) implementation of the Haar face detection algorithm. The optimal values for the tunable parameters of this implementation were found through an experimental design strategy commonly used in statistical analyses of industrial processes. Tracking was accomplished as continuous detection with the detected objects in two frames mapped using a greedy algorithm based on the distances between the centroids of bounding boxes. Results on the evaluation set containing 50 sequences (≈ 2.5 mins.) using the developed performance metrics show good performance of the algorithm reflecting the state-of-the-art which makes it an appropriate choice as the baseline algorithm for the problem.
Editorial for the 5th Bibliometric-enhanced Information Retrieval Workshop at ECIR 2017

Following the successful workshops at ECIR 20144, 20155 and 20166 [1], respectively, this workshop was the fifth in a series of events that brought together experts of communities which often have been perceived as different ones: bibliometrics / scientometrics / informetrics on the one hand and information retrieval on the other. Our motivation as organizers of the workshop started from the observation that main discourses in both fields are different, that communities are only partly overlapping and from the belief that a knowledge transfer would be profitable for both sides [2]. This fifth full-day Bibliometric-enhanced Information Retrieval (BIR) workshop7 at ECIR 2017 aimed to foster a common ground for the incorporation of bibliometric-enhanced services into scholarly search engine interfaces. In particular we addressed specific communities, as well as studies on large, cross-domain collections like Web of Science, Scopus or Mendeley. This fifth BIR workshop addressed explicitly both scholarly and industrial researchers.
Kinect based real time obstacle detection for legged robots in complex environments

Legged robots have different terrain traverse capabilities with ground vehicles. They can across steps and grooves, which are obstacles for ground vehicles. Some new challenges are posed for autonomous legged robot navigation in complex environments. In this paper, we present a Kinect based real time obstacle detection algorithm for legged robots. A graph based method is used to label all traversable areas connecting to a starting point. A spiral searching strategy is proposed to find the most ground-like point for graph based traversal. Some time efficient rules are presented to increase the calculation efficiency. Experiments in both indoor and outdoor environment have been done and the results show that our algorithm can be effectively used in autonomous legged robots navigation.
Study on a control mechanism for resource reservation states adjustment

Reserving adequate resources for an application is a prerequisite to guarantee its performance. Resource reservation gains many attentions because it is a basic mechanism for network providing quality of service control. The term, "hidden resource", is defined. Based on the cause analysis of hidden resource phenomenon in the procedure of resource reservation, the solutions aiming at the problem of hidden resource are analyzed. We put forward a resource reservation states adjustment scheme based on arrival rate estimation. Rate envelope is adopted for arrival rate estimation and the traffic feature of self-similarity is considered. The simulation results show that the adjustment scheme can solve the hidden resource problem effectively.
Comparative usability evaluation: critical incidents and critical threads

Em irical usability evaluations (particularly forrna~ive J ev uations [13]) hinge on observing and interpreting critical incidents [8] of use. We proposed [3,5] augmenting critical incident methods by analysis of what we called critical threads: sets of causally related user episodes that, taken together, define major usability themes. This paper extents this work to the comparative usability analysis of a related artifact. We discuss how our earlier claims analysis was used to orient and simplify our current evaluation efforts.
Exchange Rate Pass-Through in Turkey: It is Slow, but is it Really Low?

Using a vector auto-regression (VAR) setup, we estimate the pass-through from exchange rates and import prices to domestic inflation in Turkey, and produce some stylized facts regarding the degree and the adjustment speed of the pass-through on several price measures. Estimations for two distinct periods-before and after the adoption of floating exchange rate regime-yield both good and bad news. The good news is, our impulse responses confirm the common conjecture that pass-through has weakened and slowed down after the adoption of floating exchange rate regime. The bad news is, surprisingly low pass-through in recent years partly owes to the fact that exchange rate shocks were not persistent in direction. In other words, total pass-through might have been sizable had the economy been hit by one-sided shocks such as a persistent depreciation.
The Open World and Closed Societies: Essays on Higher Education Policies "in Transition"

This book is about higher education reforms in the post-socialist states of Central and Eastern Europe and the former Soviet Union, seen through the eyes of somebody who has spent the last decade analyzing these reforms as well as negotiating and supervising reform projects in countries from Serbia and Montenegro to Mongolia. Analyzing the reforms in a broader political, economic and social context and relating these to global higher education developments, the book addresses the complexity of the processes and contradictions among the demands on higher education systems, which in many instances impede positive changes.
Oxidative Stress as a Physiological Pain Response in Full-Term Newborns

This research paper aims to investigate if oxidative stress biomarkers increase after a painful procedure in term newborns and if nonpharmacological approaches, or sex, influence pain degree, and the subsequent OS. 83 healthy term newborns were enrolled to receive 10% oral glucose or sensorial saturation (SS) for analgesia during heel prick (HP). The ABC scale was used to score the pain. Advanced oxidation protein products (AOPP) and total hydroperoxides (TH) as biomarkers of OS were measured at the beginning (early-sample) and at the end (late-sample) of HP. The early-sample/late-sample ratio for AOPP and TH was used to evaluate the increase in OS biomarkers after HP. Higher levels of both AOPP and TH ratio were observed in high degree pain (4–6) compared with low degree pain score (0–3) (AOPP: p = 0.049; TH: p = 0.001). Newborns receiving SS showed a significantly lower pain score (p = 0.000) and AOPP ratio levels (p = 0.021) than those without. Males showed higher TH levels at the end of HP (p = 0.005) compared to females. The current study demonstrates that a relationship between pain degree and OS exists in healthy full-term newborns. The amount of OS is gender related, being higher in males. SS reduces pain score together with pain-related OS in the newborns.
Utility of Hemoglobin A1c for Diagnosing Prediabetes and Diabetes in Obese Children and Adolescents

OBJECTIVE Hemoglobin A1c (A1C) has emerged as a recommended diagnostic tool for identifying diabetes and subjects at risk for the disease. This recommendation is based on data in adults showing the relationship between A1C with future development of diabetes and microvascular complications. However, studies in the pediatric population are lacking. RESEARCH DESIGN AND METHODS We studied a multiethnic cohort of 1,156 obese children and adolescents without a diagnosis of diabetes (male, 40%/female, 60%). All subjects underwent an oral glucose tolerance test (OGTT) and A1C measurement. These tests were repeated after a follow-up time of ∼2 years in 218 subjects. RESULTS At baseline, subjects were stratified according to A1C categories: 77% with normal glucose tolerance (A1C <5.7%), 21% at risk for diabetes (A1C 5.7–6.4%), and 1% with diabetes (A1C >6.5%). In the at risk for diabetes category, 47% were classified with prediabetes or diabetes, and in the diabetes category, 62% were classified with type 2 diabetes by the OGTT. The area under the curve receiver operating characteristic for A1C was 0.81 (95% CI 0.70–0.92). The threshold for identifying type 2 diabetes was 5.8%, with 78% specificity and 68% sensitivity. In the subgroup with repeated measures, a multivariate analysis showed that the strongest predictors of 2-h glucose at follow-up were baseline A1C and 2-h glucose, independently of age, ethnicity, sex, fasting glucose, and follow-up time. CONCLUSIONS The American Diabetes Association suggested that an A1C of 6.5% underestimates the prevalence of prediabetes and diabetes in obese children and adolescents. Given the low sensitivity and specificity, the use of A1C by itself represents a poor diagnostic tool for prediabetes and type 2 diabetes in obese children and adolescents.
Tree-based Dyna-Q agent

This article presented a Dyna-Q learning method based on a world model of tree structures to enhance the efficiency on sampling data in reinforcement learning problem. The Q-Learning mechanism is for policy learning as the tree is learning the world model by observing the transitions between the states after the actions taken. In early stages of learning, the learning agent does not have an accurate model but explores the environment as possible to collect sufficient experiences to approximate the environment model. When the agent develops a more accurate model, a planning method can use the model to produce simulated experiences to accelerate value iterations. Thus, the agent with the proposed method can obtain virtual experiences for updating the policy. Simulations on a mobile robot escaping from a labyrinth to verify the performance of the robot equipped with the proposed method. The result proves that tree-based Dyna-Q agent can speed up the learning process.
Determinants of multisensory integration in superior colliculus neurons. I. Temporal factors

One of the most impressive features of the central nervous system is its ability to process information from a variety of stimuli to produce an integrated, comprehensive representation of the external world. In the present study, the temporal disparity among combinations of different sensory stimuli was shown to be a critical factor influencing the integration of multisensory stimuli by superior colliculus neurons. Several temporal principles that govern multisensory integration were revealed: (1) maximal levels of response enhancement were generated by overlapping the peak discharge periods evoked by each modality; (2) the magnitude of this enhancement decayed monotonically to zero as the peak discharge periods became progressively more temporally disparate; (3) with further increases in temporal disparity, the same stimulus combinations that previously produced enhancement could often produce depression; and (4) these kinds of interactions could frequently be predicted from the discharge trains initiated by each stimulus alone. Since multisensory superior colliculus neurons project to premotor areas of the brain stem and spinal cord that control the orientation of the receptor organs (eyes, pinnae, head), they are believed to influence attentive and orientation behaviors. Therefore, it is likely that the temporal relationships of different environmental stimuli that control the activity of these neurons are also a powerful determinant of superior colliculus-mediated attentive and orientation behaviors.
Offline modeling of nonlinear systems based on least squares support vector machines

Least squares support vector machines (LS-SVM) based on a group of different kernel functions (Linear-Polynomial-Radial Basis Function- Exponential Radial Basis Function) for modeling nonlinear systems is introduced in this paper. A method for selecting the hyperparameters of LS-SVM is presented in details for both the regularization parameter (γ) and the width parameter (σ). To test the validity of the LS-SVM method, this paper demonstrates that the method introduced can be used effectively for the identification of nonlinear systems. Simulation results reveals that the Polynomial kernel function obtain the best performance in comparison to other kernel functions especially RBF which is the most common one in modeling nonlinear systems. LS-SVM with the proposed method for parameter selection provides an attractive approach to study the properties of complex nonlinear system modeling.
A robust interference alignment algorithm in a MIMO interference channel

The sum rate maximization problem in Interference Alignment (IA) is hard to be solved, for the sum rate function is non-convex. The Weighted Minimum Mean Square Error (WMMSE) algorithm settles this problem by converting the original problem into an equivalent convex one. In this paper, an enhanced version of the WMMSE algorithm is presented, which takes the statistical information of the channel estimation error into consideration. Simulation results show that this algorithm has better performance than the original WMMSE algorithm and another distributed IA algorithm. Furthermore, the impact of time varying error caused by Doppler Shift is also investigated.
Quantitative analysis of rock glacier creep by means of digital photogrammetry using multi-temporal aerial photographs; two case studies in the Austrian Alps

This paper presents a special method of measuring surface deformation and flow velocity of creeping rock glaciers based on digital photogrammetry. The underlying concept of automatic measurement of 3-D surface displacement vectors in time-series of multi-year digital aerial photographs is explained. In contrast to standard photogrammetric procedures, image matching is not carried out in the space of the original photos but in quasi-orthophotos derived from the use of rough and preliminary digital terrain models. A software package called ADVM (Automatic Displacement Vector Measurement), written in Visual C for running on a Windowsbased PC, has been developed. The software has been tested within the framework of two case studies which comprise the spatio-temporal analysis of the kinematic behavior of three active rock glaciers in the Austrian Alps. The adjacent Inneres and Aeusseres Hochebenkar rock glaciers in the Oetztal Alps and the Hinteres Langtalkar rock glacier located in the Schober group, Hohe Tauern range, are investigated. Selected results of the photogrammetric evaluation are presented numerically and graphically. Permafrost, Phillips, Springman & Arenson (eds) © 2003 Swets & Zeitlinger, Lisse, ISBN 90 5809 582 7
Recipe popularity prediction based on the analysis of social reviews

In social based Web services systems, some resources gain popularity while others do not. It would be valuable if we can predict the popularity of certain resource. In this work, we study the recipe popularity prediction problem using the Yelp dataset. We investigate various features that can be extracted and help to improve the performance. In particular, we propose to do the sentiment analysis over the reviews and treat the sentimental scores as one of the features. A polynomial regression model is developed to predict the recipe popularity. The experimental results show that our proposed method outperforms the baseline method.
Multi-modal diffeomorphic demons registration based on mutual information

Diffeomorphic demons algorithm is an efficient and robust method in nonrigid image registration. It uses mean squared error as the similarity measure and set the gradient and gray level difference as the interior and exterior force respectively to make the points move. However it cannot deal with multiple modality images. In this paper, mutual information is used as the similarity measure instead of mean squared error and the gradient of mutual information respect to parameters is set as the force to make the points move. Then the diffeomorphic demons algorithm is extended to match multi-modal images. The experiment with magnetic resonance T1 image and magnetic resonance T2 image shows that this method is effective and performs better and more quickly compared with B-spline free-form deformation method.
Incentives for information acquisition

This paper examines necessary conditions for a demand for new information to exist. In this one-period model, investors are homogeneous, have logarithmic utility, and must decide on information acquisition before trading starts, and without knowing what other investors will do. We examine the decision problems under scenarios defined by whether information is costless or costly to acquire, whether aggregate consumption is endogeneous or exogeneously given, and whether investors can or cannot costlessly cooperate. In all cases a demand for new information exists as all investors decide to acquire provided the price is below endogeneously determined bounds.
Prevalence and Risk Factors for Obesity in Adult Dogs from Private US Veterinary Practices

Using a cross-sectional study design, the prevalence of overweight and obesity in dogs over 1 year of age seen by US veterinarians during 1995 was determined. Risk factors for overweight and obesity were also determined from the following variables: age, breed, gender, body condition score, food type, reported concurrent disease, and geographic region. Thirty-four percent of adult dogs (n = 21,754) were overweight or obese. From multivariate analyses, overweight dogs were more likely to be older, of certain breeds (Cocker Spaniel, Labrador Retriever, Dalmatian, Dachshund, Rottweiler, Golden Retriever, Shetland Sheepdog, Mixed-breed), neutered, and to consume a semi-moist food as their major diet source. In addition, overweight adult dogs were most likely to reside in the Pacific, South Central, East North Central, or Northeast regions of the United States and be diagnosed with hyperadrenocorticism, ruptured cruciate ligament, hypothyIntern J Appl Res Vet Med • Vol. 4, No. 2, 2006. Vol4Iss2.qxp 6/18/2006 9:44 AM Page 177