Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated classification of collaborative problem solving interactions in simulated science tasks

We present a novel situational task that integrates collaborative problem solving behavior with testing in a science domain. Participants engage in discourse, which is used to evaluate their collaborative skills. We present initial experiments for automatic classification of such discourse, using a novel classification schema. Considerable accuracy is achieved with just lexical features. A speech-act classifier, trained on out-of-domain data, can also be helpful.
A Robust Registration Algorithm for Automatic and Reliable Geometric Change Detection 1 of Bridges using 3 D Laser Scanning Data 2 3 4 5

1 United States transportation infrastructure facilities, such as bridges, currently have a 2 grade of C+ according to the ASCE annual report card. Long-term spatial changes of bridges can 3 be important precursors of serious structural accidents. Visual inspection methods rely on the 4 experience of engineers for assessing the spatial changes of bridges, but subjective manual 5 change inspection introduces several uncertainties due to the lack of detailed spatial data and 6 comprehensive change analysis methods. 3D laser scanning technology enables change analyses 7 of structures by comparing 3D imageries collected at different times. The challenge of using 3D 8 laser scanning in bridge change analysis is that existing algorithms for point cloud registration 9 are for aligning data sets collected in a scene where no changes occur. Applying these algorithms 10 for aligning data sets that contain long-term changes of bridges using data collected from 11 different times require engineers to manually select parts of environments that do not change 12 before the algorithm can reliably assess changes. Some studies tried to setup control network in 13 the field to overcome this challenge, but maintaining a control network that would not change 14 between data collection sessions could be time-consuming and difficult for outdoor bridge 15 jobsites. This paper presents a robust point cloud data registration algorithm that accurately 16 registers two sets of 3D laser scanning data sets collected at different years and contains changes. 17 The results indicate that this new 3D data registration approach can accurately register the 3D 18 laser scanning data sets collected from different years for effective bridge change analysis. 19 20
Reproductive Biology and Endocrinology Open Access Androgen Receptor Expression in the Rat Prostate Is Down-regulated by Dietary Phytoestrogens

Background: It is well established that the growth of the prostate gland is a hormone-dependent phenomenon involving both androgenic and estrogenic control. Proliferation of prostate cells is, at least in part, under control of estrogen receptor beta (ER-beta). Phytoestrogens bind ER-beta with high affinity and therefore may have antiproliferative effects in the prostate.
Automatic classification of gestures: A context-dependent approach

Gestures represent an important channel of human communication, and they are “co-expressive” with speech. For this reason, in human-machine interaction automatic gesture classification can be a valuable help in a number of tasks, like for example as a disambiguation aid in automatic speech recognition. Based on the hand gesture categorization proposed by D. McNeill in his reference works on gesture analysis, a new approach is here presented which classifies gestures using both their kinematic characteristics and their morphology stored as parameters of the templates pre-classified during the training phase of the procedure. In the experiment presented in this paper, an average of about 90% of correctly classified gesture types is obtained, by using as templates only about 3% of the total number of gestures produced by the subjects.
Dendritic Cell-Dependent Manner System Inflammation in a Plasmacytoid 1-Directed Agonist Reduces Central Nervous A Sphingosine-1-Phosphate Receptor

Gradients of the sphingolipid sphingosine-1-phosphate (S1P) are responsible for the egress of lymphocytes from lymph nodes by activating the S1P1 receptor expressed on the surface of lymphocytes. Small molecule drugs that downregulate S1P receptors induce the sequestration of lymphocytes within lymph nodes, thus preventing lymphocytes from accessing sites of inﬂammation. In particular, FTY720, a pan-S1P receptor agonist, has been efﬁcacious in the treatment of multiple sclerosis as well as its animal model, experimental autoimmune encephalomyelitis (EAE), by virtue of its ability to restrain lymphocytes within the lymph nodes, thus precluding their migration into the CNS. However, multiple leukocyte subsets express S1P receptors of varying types, and although it is beneﬁcial to prevent transmigration of proinﬂammatory lymphocytes into the CNS, allowing access of regulatory leukocyte subsets to the CNS is desirable. In this study, we show that an S1P1-speciﬁc agonist (AUY954) is clinically efﬁcacious in ameliorating pre-established EAE in SJL/J mice. Efﬁcacy of AUY954 correlated with a reduction of lymphocytes in the CNS, but access of plasmacytoid dendritic cells (pDCs) to the CNS was unimpaired, and the presence of pDCs was found to be an important cofactor in mediating the clinical efﬁcacy of AUY954. These results indicate that pDCs
Physiological Imaging of the Lung Real-time lung microscopy

Wolfgang M. Kuebler, Kaushik Parthasarathi, Jens Lindert, and Jahar Bhattacharya Lung and Circulatory Research Laboratory, Institute of Physiology, Charité-Universitätsmedizin, Berlin, Germany; and Lung Biology Laboratory, Department of Physiology and Cellular Biophysics, and Department of Medicine, College of Physicians and Surgeons, Columbia University, and St. Luke’s-Roosevelt Hospital Center, New York, New York
A new fifth parameter for transverse isotropy III: reflection and transmission coefficients

S U M M A R Y The effect of the newly defined fifth parameter, ηκ , of transverse anisotropy to the reflection and transmission coefficients, especially for P-to-S and S-to-P conversion coefficients, is examined. While ηκ systematically affects the P-to-S and S-to-P conversions, in the incidence angle range of the practical interest of receiver function studies, the effect may be asymmetric in a sense that P-wave receiver function is affected more than S-receiver function in terms of amplitude. This asymmetry may help resolving ηκ via extensive receiver function analysis. It is also found that P-wave anisotropy significantly influences P-to-S and S-to-P conversion coefficients that complicates the interpretation of receiver functions, because, for isotropic media, we typically attribute the primary receiver function signals to S-wave velocity changes but not to P-wave changes.
Geometrization Program of Semilinear Elliptic Equations

Understanding the entire solutions of nonlinear elliptic equations in RN such as (0.1) Δu+ f(u) = 0 in R , is a basic problem in PDE research. This is the context of various classical results in literature like the Gidas-Ni-Nirenberg theorems on radial symmetry, Liouville type theorems, or the achievements around De Giorgi’s conjecture. In those results, the geometry of level sets of the solutions turns out to be a posteriori very simple (planes or spheres). On the other hand, problems of the form (0.1) do have solutions with more interesting patterns, and the structure of their solution sets has remained mostly a mystery. A major aspect of our research program is to bring ideas from Differential Geometry into the analysis and construction of entire solutions for two important equations: (1) the AllenCahn equation and (2) the nonlinear Schrodinger equation (NLS). Though simple-looking, they are typical representatives of two classes of semilinear elliptic problems. The structure of entire solutions is quite rich. In this survey, we shall establish an intricate correspondence between the study of entire solutions of some scalar equations and the theories of minimal surfaces and constant mean curvature surfaces (CMC). 1. Part I: Geometrization Program of Allen-Cahn Equation In this section, we survey the studies on entire solutions of Allen-Cahn equation. 1.1. Background. The Allen-Cahn equation in R is the semilinear elliptic problem (1.1) Δu + u− u = 0 in R . Originally formulated in the description of bi-phase separation in fluids [16] and ordering in binary alloys [2], Equation (1.1) has received extensive mathematical study. It is a prototype for the modeling of phase transition phenomena in a variety of contexts. Introducing a small positive parameter ε and writing v(x) := u(ε−1x), we get the scaled version of (1.1), (1.2) εΔv + v − v = 0 in R . c © 2012 American Mathematical Society and International Press
Hybrid dynamic systems: models for continous and hybrid system simulation

The DEVS formalism was defined as a method for modeling and discrete event systems. DEVS theory evolved and it was recently upgraded in order to permit modeling of continuous and hybrid systems. Here, we present a first experience on the use of two of the existing methods for defining continuous variable DEVS models (namely, the QDEVS and the GDEVS formalisms), to develop continuous and hybrid systems simulations. We show how to model these dynamic systems under the discrete event abstraction. Examples of model simulations with their execution results are included. An experimental analysis on quantization methods within models is also presented.
Analyzing the User Inactiveness in a Mobile Social Game

This paper analyzes and evaluates the factors that affect the inactiveness of users and how they are related to inactiveness. A higher inactiveness indicates a user is more likely to be inactive. The analysis locates inactive users, who have not logged in to the system for some time, and evaluates the relationship between inactiveness and three dimensions: social networking, time, and in-app purchase. Based on the operational data from a mobile social game, Barcode Footballer, with more than 100k users and 1 million friendships, it is concluded that social networking, time and in-app purchase are all important factors in inactiveness. The results can be applied to mobile social games to detect potential inactive users such that their operators can retain those users by using encouragements.
ZONE PRICING IN RETAIL OLIGOPOLY Brian Adams Bureau of Labor Statistics

We quantify the welfare effects of zone pricing, or setting common prices across distinct markets, in retail oligopoly. Although monopolists can only increase profits by price discriminating, this need not be true when firms face competition. With novel data covering the retail home improvement industry, we find that Home Depot would benefit from finer pricing but that Lowe’s would prefer coarser pricing. The use of zone pricing softens competition in markets where firms compete, but it shields consumers from higher prices in markets where firms might otherwise exercise market power. Overall, zone pricing produces higher consumer surplus than finer pricing discrimination does. JEL Classification: C13, L67, L81 ∗adams.brian@bls.gov †kevin.williams@yale.edu ‡A previous version of this paper circulated under the title, "Zone Pricing and Strategic Interaction: Evidence from Drywall. " We thank the seminar participants at the University of Minnesota, California State University-East Bay, Marketing Science, University of Wisconsin-Madison, Yale University, Econometric Society Summer Meetings, University of Massachusetts-Amherst, Bureau of Labor Statistics, Department of Justice, Federal Trade Commission, University of Pennsylvania, and the AEA Winter Meetings for useful comments. We thank Bonnie Murphie and Ryan Ogden for their assistance with Bureau of Labor Statistics data. All views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the U.S. Bureau of Labor Statistics.
Orbital metastasis of endocervical stromal sarcoma: a rare tumor and an uncommon metastasis

Endocervical stromal sarcoma (ECSS) is a very rare uterine sarcoma. The most common presentation is pelvic mass and vaginal bleeding. The mainstay of treatment is surgery. There is no consensus on the adjuvant treatment. Relapses are usually in the pelvic and abdominal regions. To a lesser extent, lung, liver and bone metastases may be seen. A 46-year-old woman had total abdominal hysterectomy (TAH) with bilateral salpingo-oophorectomy (BSO) performed due to endometrial polyp and leiomyoma. Six months after the TAH-BSO, she was admitted to the hospital with cough and hemoptysis. A thoracic mass was detected, and a biopsy was done. The diagnosis was low-grade ECSS metastasis. One week after thoracotomy, she was admitted to the hospital with loss of vision in the left eye. An orbital mass was detected with magnetic resonance imaging. Endometrial and cervical pathology preparations were reassessed and were compatible with ECSS. We performed mammography, thorax, and abdomen and cranial imaging to rule out other malignancies that may cause lung and orbital metastasis. Partial remission was achieved with systemic chemotherapy and orbital radiotherapy. Orbital metastasis may be seen in ECSS patients. Although we have less knowledge about the choice of chemotherapeutic agents, ifosfamide and doxorubicin are effective in treating ECSS.
Risk of Myocardial Infarction and Vascular Death After Transient Ischemic Attack and Ischemic Stroke: A Systematic Review and Meta-Analysis

Background— Whether stroke patients should be investigated for asymptomatic coronary artery disease remains matter of debate. Absolute risks of myocardial infarction (MI) and vascular death after a stroke have not been accurately assessed. We performed a systematic review and a meta-analysis to determine the risk of MI and nonstroke vascular death after transient ischemic attack (TIA) and ischemic stroke. Cohort studies of TIA or ischemic stroke patients were included if they were published between 1980 and March 2005, reported risk of MI and nonstroke vascular death, enrolled >100 patients, and had at least 1 year of follow-up. We included 39 studies in a total of 65 996 patients with mean follow-up of 3.5 years. Two reviewers independently carried out data extraction using a standardized form. Absolute annual risks were estimated through weighted meta-regressions with a random effect. To test the predictions of expected event rates derived from our analysis, we used individual patient data. Summary of Review— The annual risks were 2.1% (CI 95%: 1.9 to 2.4) for nonstroke vascular death, 2.2% (1.7 to 2.7) for total MI, 0.9% (0.7 to 1.2) for nonfatal MI and 1.1% (0.8 to 1.5) for fatal MI. The time course of risk was linear. Estimated risks fitted well with observed risks at the individual level. There was no heterogeneity in the absolute risks according to baseline study characteristics. Conclusions— Patients with TIA or stroke have a relatively high risk of MI and nonstroke vascular death. Additional research is needed to identify the determinants of coronary artery disease in stroke patients.
FIGGS: Faint Irregular Galaxies GMRT Survey – overview, observations and first results

The Faint Irregular Galaxies GMRT Survey (FIGGS) is a Giant Metrewave Radio Telescope (GMRT) based HI imaging survey of a systematically selected sample of extremely faint nearby dwarf irregular galaxies. The primary goal of F IGGS is to provide a comprehensive and statistically robust characterization of the neut ral inter-stellar medium properties of faint, gas rich dwarf galaxies. The FIGGS galaxies represent the extremely low-mass end of the dwarf irregular galaxies population, with a median MB � 13:0 and median HI mass of � 3�10 7 M� , extending the baseline in mass and luminosity space for a comparative study of galaxy properties. The HI data is supplemented with observations at other wavelengths. In addition, distances accurate to � 10% are available for most of the sample galaxies. This paper gives an introduction to FIGGS, describe the GMRT observations and presents the first results from the HI observations. From the FIGGS data we confi rm the trend of increasing HI to optical diameter ratio with decreasing optical luminosi ty; the median ratio of DH I/DH o for the FIGGS sample is 2.4. Further, on comparing our data with aperture synthesis surveys of bright spirals, we find at best marginal evidence for a decrea se in average surface density with decreasing HI mass. To a good approximation the disks of gas rich galaxies, ranging over 3 orders of magnitude in HI mass, can be described as being drawn from a family with constant HI surface density.
Conflict Graph Based Channel Allocation in Cognitive Radio Networks

Cognitive radio technology provides a framework for flexible way to utilize the white spaces using the various spectrum sharing techniques. Interference plays an important role in communication when the channels are shared by the licensed and unlicensed users. Further, the signal to interference plus noise ratio also provide the bounds for the channel capacity. For this the authors introduce a conflict graph based approach for optimal channel allocation in cognitive radio networks named as Conflict Graph based Channel Allocation(CGCA) scheme. The proposed CGCA scheme was simulated and observed that the CGCA scheme outperformed Interference Aware Channel Assignment (IACA) scheme in terms of channel allocation. The channel allocation of the proposed CGCA was observed to have increased by 19 channels, when the unlicensed users shared the network as compared to the IACA technique.
Core Tree Optimization in Hybrid Peer to Peer Real Time Broadcasting System

Peer to peer based live multimedia streaming systems over the Internet have been gaining popularity these days because they can be easily deployed without router based IP multicast capabilities. However, the peers frequently join and leave the system so that some peers may experience service disruptions, which degrade the overall quality and reputation of the services. In this situation, a hybrid approach is considered as a viable alternative. In the hybrid approach, the service providers deploy multiple proxies all over the Internet and make them constitute a core tree in the peer to peer system so that the proxies behave as stable nodes that are always on. Thus the system quality can increase. In this paper, we propose a centralized core tree construction scheme based on various optimization algorithms. The scheme focuses on constructing a core tree that maximizes the overall quality of the system. Because the real time multimedia streaming systems have higher QoS requirements than the content distribution such as Akamai, we take into account not only the locations of the proxies but also the topology formed by the proxies. The general framework can obtain a tree for arbitrary performance metrics not only for a specific metric such as minimum delay. Through simulations over diverse scenarios, we show that our optimization based approaches can provide a better core tree than some greedy heuristic approaches.
Learning document structure for retrieval and classification

In this paper, we present a method for the retrieval of document images with chosen layout characteristics. The proposed method is based on statistics of patch-codewords over different regions of image. We begin with a set of wanted and a random set of unwanted images representative of a large heterogeneous collection. We then use raw-image patches extracted from the unlabeled images to learn a codebook. To model the spatial relationships between patches, the image is recursively partitioned horizontally and vertically, and a histogram of patch-codewords is computed in each partition. The resulting set of features give a high precision and recall for the retrieval of hand-drawn and machine-print table-documents, and unconstrained mixed form-type documents, when trained using a random forest classifier. We compare our method to the spatial-pyramid method, and show that the proposed approach for learning layout characteristics is competitive for document images.
A Method for Assessing User-generated Tests for Online Courses Exploiting Crowdsourcing Concept

In this research, we focus on the challenge of user-generated tests, where crowdsourcing of users have the chance of making new and innovative questions that increases the allowance for a teacher to create a new test. This approach replaces the dependence of stored questions/ answers pair that encourage memory skills not learning skills. The limitation of how to accept these questions contents is raised up. In this paper we propose a question acceptance method based on two measures that weight the question's score, which are difficulty and goodness factors. Since the formalization of assessment and goodness which we made in this paper are recursive, we also propose a heuristic algorithm for iteratively calculating both values. Moreover, we show simulation result to confirm that the algorithm converges, and that it reflects the difficulty and the goodness factors.
Self-Assembling Tile Systems that Heal from Small Fragments ∗

Tile systems have proved to be a useful model for understanding self-assembly at the nano scale. Self-healing tile systems, introduced by Winfree, have the property that the self-assembled shape can recover from the loss of arbitrarily many tiles, provided the seed tile of the assembly remains intact and the assembly remains connected. In this paper, we present improved self-healing tile systems for the self-assembly of several interesting classes of shapes, including counters, squares, and Turing-computable shapes. Our tile systems can recover from the loss of arbitrary many tiles, including the seed, provided that a large enough fragment (logarithmic in the size of the desired assembly for the case of counters and squares) is left intact. ∗Research supported by grants from the National Science Foundation.
Towards personalised home care systems

Home care is increasingly seen as a promising alternative to traditional care services. Programming home care systems remains a significant challenge considering the potentially large scale of deployment, the differences between individual care needs, and the progressive nature of ageing. In this paper, we present ongoing work on programming home care systems to support personalisation, adaptability over time, and dependability. A policy-based approach is used to build such systems. We present the technical details of our approach, including a policy language for home care and the corresponding system architecture. Policy examples are used to illustrate how the approach supports personalisation of home care services.
Master-slave robot position coordination based on estimated variables

In this paper we present a controller that solves the problem of position coordination of two (or more) robotic systems, under a master-slave scheme, in the case when only position measurements are available. The controller consists of a feedback control law and two nonlinear observers. It is shown that the controller yields semi-global ultimate uniformly boundedness of the closed loop errors and a relation between the bound of the errors and the gains on the controller is established. Experimental results show, despite obvious model uncertainties, a good agreement with the predicted convergence.
Real Time Driver’s Drowsiness Detection by Processing the EEG Signals Stimulated with External Flickering Light

The objective of this study is development of driver’s sleepiness using Visually Evoked Potentials (VEP). VEP computed from EEG signals from the visual cortex. We use the Steady State VEPs (SSVEPs) that are one of the most important EEG signals used in human computer interface systems. SSVEP is a response to visual stimuli presented. We present a classification method to discriminate between closed eyes and opened eyes. Fourier transforms and power spectrum density features extracted from signals and Multilayer perceptron and radial basis function neural networks used for classification. The experimental results show an accuracy of 97% for test data.