Miracle-dz/UniFAR-FTUs huggingface dataset:
Homophily based on English-Name Usage among International Students : A Natural Experiment ∗

Researchers have long observed ethnic homophily in school friendships, but other than homophily based on demographic variables, little is known about homophily based on behavioral characteristics among immigrants of the same origin. This article analyzes homophily based on English-name usage among international students and focuses on not only correlation, but also causation: the causal effect of self English-name usage on friends’ English-name usage. Both the theory of peer selection and peer influence explain the presence of homophily, although prior literature suggests that peer selection plays the vital role while peer influence does not. The data used in this article consists of students receiving undergraduate education in China and graduate education in the U.S. The causation analysis relies on a natural experiment: the difficulty of pronouncing the Chinese name by native English speakers exogenously affects English-name usage, which solves the problem that English-name usage is endogenous. Results show that students with English-name usage have more close friends also with English-name usage.
xBD: A Dataset for Assessing Building Damage from Satellite Imagery

We present xBD, a new, large-scale dataset for the advancement of change detection and building damage assessment for humanitarian assistance and disaster recovery research. Natural disaster response requires an accurate understanding of damaged buildings in an affected region. Current response strategies require in-person damage assessments within 24-48 hours of a disaster. Massive potential exists for using aerial imagery combined with computer vision algorithms to assess damage and reduce the potential danger to human life. In collaboration with multiple disaster response agencies, xBD provides pre- and post-event satellite imagery across a variety of disaster events with building polygons, ordinal labels of damage level, and corresponding satellite metadata. Furthermore, the dataset contains bounding boxes and labels for environmental factors such as fire, water, and smoke. xBD is the largest building damage assessment dataset to date, containing 850,736 building annotations across 45,362 km\textsuperscript{2} of imagery.
Squaring and Scale-Space based Generalization of 3 D Building Data

Three dimensional (3D) city models are often visualized using a Level of Detail (LOD) representation. For the automatic generation of coarser representations from detailed 3D building models, i.e., generalization, an approach is introduced which uses the formally well defined theory of scale-spaces, including mathematical morphology and curvature-space. A number of examples shows the potential of the approach. Because buildings are perceived to mainly consist of orthogonal structures and as our previous investigations have shown that generalization based on scale-spaces works best for those, the focus of this paper lies on the squaring of non-orthogonal structures. Results for the automatic elimination of inclined roof-structures for a coarse model are given while the squaring of walls is still under investigation.
Inertial Sensor-Based Approach for Shot / Pass Classification During a Soccer Match

Coaches and players in soccer are heavily interested in statistics like number of shots and passes during training sessions and competitions. Currently available systems use video or computerized technology to create such statistics and are therefore mainly applicable for elite teams. Thus, the purpose of this paper was to develop a low-cost inertial sensorbased approach for shot/pass classification in soccer, which can be used by teams at amateur level. High intensity peaks were detected in the accelerometer data from the left and right shoe of soccer players. Segmented windows around the peaks were classified regarding shot, pass, and other. The system was evaluated based on data from 12 players during a 60-minute soccer match. The system was able to differentiate between shots and passes with an overall mean classification rate of 84.2 %. The proposed approach is one important step toward a detailed soccer match analysis system, which provides coaches and players of amateur teams with important statistics for performance assessment.
Extraction of representative learning set from measured geospatial data

The efficiency of the application of soft computing methods like Artificial Neural Networks (ANN) or Support Vector Machines (SVM) depends considerably on the representativeness of the learning sample set employed for training the model. In this study a simple method based on the Coefficient of Representativity (CR) is proposed for extracting representative learning set from measured geospatial data. The method eliminating successively the sample points having low CR value from the dataset is implemented in Mathematica and its application is illlustrated by the data preparation for the correction model of the Hungarian gravimetrical geoid based on current GPS measurements.
Serum-Free Spheroid Culture of Mouse Corneal

METHODS. Corneas of C57BL6/J mice were enzyme digested after the epithelium and endothelium were removed. Stromal cells were cultured in serum-free DMEM/F12 (1:1) containing epidermal growth factor (EGF), fibroblast growth factor 2 (FGF2), and B27 supplement. Primary spheres were dissociated by trypsin and subcultured as suspended secondary spheres. Cells from postnatal day (P)6 to P10 spheres were subcultured onto plastic dishes or type I collagen gels for phenotype analysis. The expression of the keratocyte markers keratocan, aldehyde dehydrogenase (Aldh), and CD34, were analyzed by RT-PCR, and vimentin and -smooth muscle actin ( -SMA) were examined by immunocytochemistry.
Impact of PM 10 and meteorological factors on the incidence of hand , foot , and mouth disease in female children in Ningbo , China : a spatiotemporal and time-series study

Hand, foot, and mouth disease (HFMD) is a viral illness that is considered a critical public health challenge worldwide. Previous studies have demonstrated that meteorological parameters are significantly related to the incidence of HFMD in children; however, few studies have focused only on female children. This study quantified the associations of HFMD incidence with meteorological parameters and PM10 (particulate matter with an aerodynamic diameter of 10 μm) among female children. Data were collected on daily HFMD cases, meteorological variables, and PM10 levels in Ningbo, China, from January 2012 to December 2016. Data were assessed using a distributed lag nonlinear model (DLNM) with Poisson distribution. A total of 59,809 female children aged 0−15 years with HFMDwere enrolled. The results showed that highest relative risk (RR) of HFMD for temperature was 3 °C and the lag effect was 3 days. The highest RR for PM10 was 80 mg/m 3 and the lag effect was 5 days. Spatial analysis showed that female HFMD incidence was mainly concentrated in the suburban of Ningbo city indicating that female children in this area should be more paid attention on avoiding this disease outbreak. Our findings suggest that HFMD prevention strategies should focus more attention on local meteorological parameters.
ndocannabinoid Inhibition New Cardioprotective Strategy gainst Doxorubicin Cardiotoxicity

t has been almost 40 years since the quinone-containing nthracycline doxorubicin was first isolated from cultures of treptomyces peucetius var. caesius (1), and it remains one of he most effective and commonly used drugs for treatment f a variety of solid and hematologic malignancies. There is strong correlation between total dose and antitumor fficacy; however, soon after its discovery a second effect ecame evident: patients treated with doxorubicin develped cardiomyopathic changes. This serious side effect has ignificantly limited its potential clinical utility (2). Initial eports documented the highest risk for doses above 450 g/m (3). However, with improved methods of detecting ubtle changes in cardiac function, (e.g., alterations in left entricular wall stress [4]), the incidence of doxorubicin ardiotoxicity is now appreciated to be much higher than reviously suspected. Alterations in wall stress have been ocumented in 65% of long-term survivors of childhood ancer, even at doses as low as 228 mg/m (5).
Network Design and Management with Strategic Agents

Network design is a fundamental problem for which it is important to understand the effects of strategic behavior. Given a collection of self-interested agents who want to form a network connecting certain endpoints, the set of stable solutions (the Nash equilibria) may look quite different from the centrally enforced optimum. We study the price of stability, i.e., the quality of the best Nash equilibrium compared to the optimum network cost. The best Nash equilibrium solution has a natural meaning of stability in this context: it is the optimal solution that can be proposed from which no user will "deviate". We consider two versions of this game: one where agents may divide the cost of the edges they use in any manner they desire, and one where the cost of each such edge is divided equally between the agents whose connections make use of it. We also study the price of stability of a related game where agents are attempting to route their traffic while incurring minimal latency, instead of trying to construct a network of minimal cost. Since "self-interest" could have various meanings, the notion of strategic agents enfolds many types of agents including malicious, altruistic, and obedient agents under a common terminology. For example, we can think of a decentralized algorithm with local knowledge as a set of "self-interested" agents performing local optimizations. The comparisons between stable solutions and the centrally enforced optimum now become concerns about the algorithm's performance compared to a centralized algorithm with global knowledge. We elaborate on this in the contexts of local load balancing and packet routing algorithms, by showing that simple decentralized algorithms with local knowledge can ensure good global properties even in the presence of a powerful adversary. Specifically, we show that in the dynamic load balancing problem, where the arrival and departure of jobs is modeled by an adversary restricted in its power, a classic local balancing algorithm keeps the loads approximately balanced. We extend these results to many other scenarios, with dynamic packet routing as one of them.
Approaching Nested Named Entity Recognition with Parallel LSTM-CRFs

We present the winning system of this year’s PolEval nested named entity competition, as well as the justification of handling the particular problem with multiple models rather than relying on dedicated architectures. The description of working out the final solution (parallel LSTM-CRFs utilizing GloVe and Contextual Word Embeddings) is preceded with information regarding recent advances in flat and nested named entity recognition. Significantly, all the tested solutions were developed on the basis of open source implementations, particularly Flair framework, LM-LSTM-CRF, LayeredLSTM-CRF and Vowpal Wabbit.
Different Views on Pragmatics Workshop at the Institute of Design and Communication University of Southern Denmark , Kolding August 26 , 2014 Universitetsparken 1 , Lokale K-60 . 01 Abstracts Pragmatics and Pragmatism — Philosophical Roots

Pragmatics and Pragmatism — Philosophical Roots Nina Bonderup Dohn, Kolding/Denmark Pragmatics and pragmatism have their philosophical roots in the writings of Peirce, James, Dewey and C. I. Lewis. In this opening talk I shall present an overview of these roots with a focus on the philosophers’ epistemological and ontological claims concerning the relationship between practical activity, experience, inquiry, truth, and reality. Divergences exist between the philosophers on these issues, but common to them all is a tight coupling of ‘practical activity’ and theoretical beliefs; an emphasis on scientific inquiry as an activity; a critique of radical skepticism; a fallibilism concerning theory and method; an inferential account of experience; and a non-representational account of propositional content. These concepts and their relation to one another will all be elaborated upon in the talk. In addition, I shall point at some of the differences between the views of the ‘founding fathers’. Peirce and James thus for instance had a more narrow conception of pragmatism than Dewey did: They saw the term as referring strictly to the ‘pragmatist maxim’ (called Peirce’s principle) that a hypothesis or metaphysical dispute should be clarified by identifying its ‘practical consequences’. If no such practical consequences could be identified, the hypothesis was empty and the dispute eliminable. Dewey for his part developed a wider sense of pragmatism which focused on inquiry as initiated by a practically experienced problem in an indeterminate situation.
THE SEISMICITY OF GAZİANTEP, TURKEY

Although some differences exist between the regional kinematic models in the literature, many studies have proposed that the boundaries between African, Arabian and Anatolian Plates meet at a triple junction in southern-central Turkey. Following the overview made of the previous works on the tectonic models, historical seismicity and the known slip rates along the faults in the region, the study has aimed to point out the northern part of the Dead Sea Fault Zone (DSFZ) in Turkey and Syria, and the western part of the East Anatolian Fault in south-eastern Turkey. It has been seen that the leftlateral slip on the DSFZ is associated with earthquakes of magnitude ~7.5 occurring at intervals of several hundred years on each fault segment. Also, it is interpreted that a possible earthquake could have significant economic and social effects on cities located in the region. The city of Gaziantep, with a population of over 1.000. 000, is one of the cities in this region and located at approximately 37.08 N37.38 E. The study investigates the seismicity and the earthquake hazard of Gaziantep. The seismicity of Gaziantep has been investigated by using the earthquakes M ≥ 3 that occurred in the region for the time interval 1973-2003. A fairly simple study has also been investigated using timeindependent probabilistic model to predict the future earthquakes activities. Evidently, the paper is intended to serve as an additional reference for more advanced approaches and to stimulate discussions and suggestions on region, particularly on the city of Gaziantep.
Export Potential Assessments A methodology to identify export opportunities for developing countries

In order to assist developing countries in identifying promising products for inclusion into export promotion activities, the International Trade Centre (ITC) has developed an export potential assessment methodology. It is based on a decomposition of a country’s potential exports of a product to a given target market into three factors: supply, demand and easiness to trade. Depending on the country’s particular needs, two approaches are available. (i) The Export Potential Indicator (EPI) serves countries that aim to support established export sectors in increasing their exports to existing and new markets. Inspired by a gravity-type framework, the EPI identifies products in which the exporting country has already proven to be internationally competitive and which have good prospects of export success in a given target market. (ii) The Product Diversification Indicator (PDI) serves countries that aim to diversify and develop new export sectors. Based on Hausmann and Hidalgo's notion of the product space, the PDI identifies products which the exporting country does not yet competitively export but which seem feasible given the country's current export basket and the export baskets of similar countries. Additional indicators that reflect policy objectives allow refining the selection of promising products. Results prove to be stable over time, turning them into a suitable information base for a country’s medium-term export strategies or development programmes. 1 The authors are highly indebted to the below listed colleagues for their valuable contributions. Lionel Fontagné has thoroughly reviewed the paper and provided comments that helped improving it considerably. Thanks go also to participants of seminars at ITC and WTO during which the methodology was presented and discussed.
Research on the spatiotemporal variation of rural-urban transformation in underdeveloped regions and its driving mechanisms: Gansu Province in western China as an example

Rural-urban transformation is a process of morphological and functional change of rural system consisting of three dimensions: population, land and industry. Gansu Province is characterized by relatively poor economic development, low per capita income and low level of urbanization, and is thus a typical underdeveloped region in China. By constructing a comprehensive evaluation index system for population-land-industry system at a county scale and a model for quantifying rural-urban transformation degree, this paper quantitatively analyzed rural-urban transformation in Gansu Province and explored its spatiotemporal variation and driving forces by means of hotspot identification and geographical detector model. This paper attempts to clarify rural socioeconomic transformation and development, reveal regional differences in rural development mechanisms, and explore related policies and measures that are suitable for regional characteristics. The results will help coordinate the relationship between urban-rural integration and the construction of a well-off society in underdeveloped regions, explore new modes of rural-urban transformation, and improve the institutional mechanism of regional urban-rural integration. These can provide useful information for region-specific planning and strategic decision making. In addition, this study is conducive to implementing Belt and Road, improving urban and rural layout, and promoting rural sustainable development and rural revitalization in northwest China.
K-means Tracker : A Failure Detectable and Recoverable Tracking Method Against Interfused Bakcground

This paper presents a K-means tracker, which is a novel visual tracking algorithm. One of the most distinctive points of this algorithm is the robustness against interfused background, because this algorithm discriminates “target” pixels from “background” pixels in the tracking region based on K-means clustering using both positive and negative information of the target. Since the clustering is performed in the 5D feature space of position (x, y) and color (y, u, v), target clusters automatically follow the target positions as well as the target colors. This adaptive nature guarantees the robustness against target color change. By using a variable ellipse model to represent both the target shape and the surrounding non-target pixels, the algorithm can cope with the change of the scale and the shape of the target object flexibly. In spite of this robustness, the tracking sometimes fails. In such cases, the algorithm automatically detects the tracking failure and recovers from it based on the positive and negative information. We achieve the video-rate processing by replacing the original K-means clustering algorithm with a newly developed N + 1∞ clustering algorithm. We have implemented a prototype system based on the algorithm and confirmed the effectiveness through extensive experiments.
Nonlinear flexural vibration of AFM multilayered piezoelectric microcantilever under tip-sample interaction

In this paper, the vibration of an AFM microcantilever with one and two layers of piecewise piezoelectric is analyzed. With respect to discontinuities in the MC, due to the piezoelectric layer, the non-uniform beam model is used in the modeling of vibrating motion. The vibration analysis of MC is carried out near the sample surface in the noncontact mode. To solve the nonlinear differential equation of motion, both numerical solution and multiple time scales (MTS) method are used and the results are compared. Comparison of results, at the non-contact mode, shows good agreement between the two solving methods at normal equilibrium distances (d􀂕2nm). MC is modeled with one and two piezoelectric layers; the nonlinear behavior of each MC is studied by investigating the effect of geometrical dimensions of each layer on the nonlinearity of the system. It is then become clear that they can affect the nonlinearity of the system
Application of Fuzzy Multilevel Comprehensive Evaluation Method in Assessment of Scientific Research Subjects

Judgment departments and research parties have always attended the assessment of scientific research subjects.The traditional assessment methods include total/part and weight average.But when the assessment guideline is fuzzy concept and the weight is fuzzy,these methods are not suitable.In this paper,on the basis of analyzing assessment of scientific research subjects,from the viewpoints of qualitative analysis and quantitative analysis,the fuzzy multilevel comprehensive evaluation method is used to assessment scientific research subjects by employing the knowledge of analytic hierarchy process and fuzzy mathematics.The example result shown that the method is believable,its operation is easy and has good applied future.
Hongtao Liu / Yunqi Liu Controlled Chemical Synthesis in CVDGraphene

Due to the unique properties of graphene, single layer, bilayer or even few layer graphene peeled off from bulk graphite cannot meet the need of practical applications. Large size graphene with quality comparable to mechanically exfoliated graphene has been synthesized by chemical vapor deposition (CVD). The main development and the key issues in controllable chemical vapor deposition of graphene has been briefly discussed in this chapter. Various strategies for graphene layer number and stacking control, large size single crystal graphene domains on copper, graphene direct growth on dielectric substrates, and doping of graphene have been demonstrated. The methods summarized here will provide guidance on how to synthesize other twodimensional materials beyond graphene.
Opinion Detection by Transfer Learning 11-742 Information Retrieval Lab Report

Opinion detection is the main task of TREC 2006 Blog track, which identifies opinions from text documents in the TREC blog corpus. Given that it is the first year of the task, there is no available training data provided. Using knowledge about how people give opinions on other domains, for example, movie review, product review and book review, is the best available training data for opinion detection in blog domain. This work describes how to apply transfer learning in opinion detection. A Bayesian logistic regression framework is used and knowledge from training data in other domains is captured by a non-diagonal prior covariance matrix. The experimental results show that the approach is effective and achieve an improvement of 32% from baseline.