Miracle-dz/UniFAR-FTUs huggingface dataset:
Bootstrapping Ontology Learning for Information Retrieval Using Formal Concept Analysis and Information Anchors

We present an innovative approach to information retrieval for domain-specific digital library collections. We use a combi nation of Formal Concept Analysis (FCA) and a notion of information anchorsto facilitate information delivery to the end user. This approach (1) uses ranked o bjects in attribute concepts to facilitate topical queries for experts and expe rtise profiles; (2) formulates (keyword by keyword) context for concept lattice co nstruction via a set of heuristics, including those based on information anchor s f r selecting descriptive phrases, (3) bootstraps the learning of domain-specifi c oncept hierarchies using FCA, and (4) incorporates the learnt concept hierarch ies and WordNet for content-based document classification. To demonstrate the feasibility and utility of this approach, we implemented a prototype online informa tion retrieval systemmemsworldonline.case. edu (MWOL) for the emerging engineering discipline of MEMS (microelectromechanical systems) incorpo rating these ideas. MWOL has been actively used by a non-trivial group of MEMS pra ctitioners; all user queries are processed in a fraction of a second as a resul t of inverse indexing strategy using Berkeley DB. Voluntary user feedback using o nline forms has been encouraging. However, no other systems with similar featur es are available for a comparative study at this point.
Extracellular vesicles derived from renal cancer stem cells induce a pro-tumorigenic phenotype in mesenchymal stromal cells

Renal carcinomas have been shown to contain a population of cancer stem cells (CSCs) that present self-renewing capacity and support tumor growth and metastasis. CSCs were shown to secrete large amount of extracellular vesicles (EVs) that can transfer several molecules (proteins, lipids and nucleic acids) and induce epigenetic changes in target cells. Mesenchymal Stromal Cells (MSCs) are susceptible to tumor signalling and can be recruited to tumor regions. The precise role of MSCs in tumor development is still under debate since both pro- and anti-tumorigenic effects have been reported. In this study we analysed the participation of renal CSC-derived EVs in the interaction between tumor and MSCs. We found that CSC-derived EVs promoted persistent phenotypical changes in MSCs characterized by an increased expression of genes associated with cell migration (CXCR4, CXCR7), matrix remodeling (COL4A3), angiogenesis and tumor growth (IL-8, Osteopontin and Myeloperoxidase). EV-stimulated MSCs exhibited in vitro an enhancement of migration toward the tumor conditioned medium. Moreover, EV-stimulated MSCs enhanced migration of renal tumor cells and induced vessel-like formation. In vivo, EV-stimulated MSCs supported tumor development and vascularization, when co-injected with renal tumor cells. In conclusion, CSC-derived EVs induced phenotypical changes in MSCs that are associated with tumor growth.
The empowering effect of punishment on forgiveness

We examined the process by which punishment enables forgiveness, testing the proposition that punishment restores a sense of justice to victims, an experience that is empowering. In Study 1 (N = 69), university students received insulting feedback and were given the opportunity (or not) to sanction the offender. In Study 2 (N = 91), participants imagined having the opportunity (or not) to recommend punishment for a person who had vandalized their house. A two-step mediation model (punishment justice restoration empowerment forgiveness) was supported in these two studies. In Study 3 (N = 227), punishment options were expanded to test the role of victim voice in the context of third-party and personal retributive and restorative justice responses to workplace bullying, as well as taking into account revenge as an alternative to justice restoration. When victims had voice, empowerment again played a central indirect role in relations between punishment and forgiveness.
Hardware Abstraction and Protocol Optimization for Coded Sensor Networks

The design of the communication protocols in wireless sensor networks (WSNs) often neglects several key characteristics of the sensor's hardware, while assuming that the number of transmitted bits is the dominating factor behind the system's energy consumption. A closer look at the hardware specifications of common sensors reveals, however, that other equally important culprits exist, such as the reception and processing energy. Hence, there is a need for a more complete hardware abstraction of a sensor node to reduce effectively the total energy consumption of the network by designing energy-efficient protocols that use such an abstraction, as well as mechanisms to optimize a communication protocol in terms of energy consumption. The problem is modeled for different feedback-based techniques, where sensors are connected to a base station, either directly or through relays. We show that for four example platforms, the use of relays may decrease up to 4.5 times the total energy consumption when the protocol and the hardware are carefully matched. We conclude that: 1) the energy budget for a communication protocol varies significantly on different sensor platforms; and 2) the protocols can be judiciously adapted to the underlying hardware. The results are cross-validated using real-life measurements.
Node Localization in WSN Based on Weighted Vectors Centroid Algorithm

Centroid algorithm, as relatively simple, depends upon the connectivity of WSN and nodes density, in which the error of node orientation is high, the calculation for the minimum error is too lager and the time which it takes too long. In this paper, a new node localization algorithm uses intelligent particle swarm optimization (PSO) to fast convergence speed based on the proposed weighted vector centroid algorithm. The simulation results show that the localization error of centroid algorithm is decreased rapidly and our proposed algorithm is efficient for WSN.
Has the Reform of the Japanese Healthcare Provision System Improved the Value in Healthcare? A Cost-Consequence Analysis of Organized Care for Hip Fracture Patients

Objectives To assess the value of organized care by comparing the clinical outcomes and healthcare expenditure between the conventional Japanese “integrated care across specialties within one hospital” mode of providing healthcare and the prospective approach of “organized care across separate facilities within a community”. Design Retrospective cohort study. Setting Two groups of hospitals were categorized according to healthcare delivery approach: the first group included 3 hospitals autonomously providing integrated care across specialties, and the second group included 4 acute care hospitals and 7 rehabilitative care hospitals providing organized care across separate facilities. Participants Patients aged 65 years and above who had undergone hip fracture surgery. Measurements Regression models adjusting for patient characteristics and clinical variables were used to investigate the impact of organized care on the improvements to the mobility capability of patients before and after hospitalization and the differences in healthcare resource utilization. Results The sample for analysis included 837 hip fracture surgery cases. The proportion of patients with either unchanged or improved mobility capability was not statistically associated with the healthcare delivery approaches. Total adjusted mean healthcare expenditure for integrated care and organized care were US$28,360 (95% confidence interval: 27,787-28,972) and US$21,951 (21,511-22,420), respectively, indicating an average increase of US$6,409 in organized care. Conclusion Our cost-consequence analysis underscores the need to further investigate the actual contribution of organized care to the provision of efficient and high-quality healthcare.
Differential games in large-scale sensor-actuator networks

Surveillance systems based on sensor network technology have been shown to successfully detect, classify and track targets of interest over a large area. State information collected via the sensor network also enables these systems to actuate mobile agents so as to achieve surveillance goals such as target capture and asset protection. But satisfying these goals is complicated by the fact that track information in a sensor network is routed to mobile agents through multi-hop communication links and is thus subject to delays and losses. In addition, as the sensor network is scaled in size, high throughput rates for all pursuers cannot be sustained at all times, which necessitates a network communication strategy that adapts to pursuer information requirements. In this paper, we concentrate on the formulation of optimal pursuit control strategies in the presence of network effects, assuming that target track information has been established locally in the sensor network. We adapt ideas from the theory of differential games to networked games-including ones involving non-periodic track updates, message losses and message delays-to derive optimal strategies, bounds on the information requirements, and scaling properties of these bounds. Moreover, we present a specific network communication protocol which has the required scalable information characteristics and conclude with the results of experimental studies
Dopaminergic Control of Motivation and Reinforcement Learning: A Closed-Circuit Account for Reward-Oriented Behavior

Humans and animals take actions quickly when they expect that the actions lead to reward, reflecting their motivation. Injection of dopamine receptor antagonists into the striatum has been shown to slow such reward-seeking behavior, suggesting that dopamine is involved in the control of motivational processes. Meanwhile, neurophysiological studies have revealed that phasic response of dopamine neurons appears to represent reward prediction error, indicating that dopamine plays central roles in reinforcement learning. However, previous attempts to elucidate the mechanisms of these dopaminergic controls have not fully explained how the motivational and learning aspects are related and whether they can be understood by the way the activity of dopamine neurons itself is controlled by their upstream circuitries. To address this issue, we constructed a closed-circuit model of the corticobasal ganglia system based on recent findings regarding intracortical and corticostriatal circuit architectures. Simulations show that the model could reproduce the observed distinct motivational effects of D1- and D2-type dopamine receptor antagonists. Simultaneously, our model successfully explains the dopaminergic representation of reward prediction error as observed in behaving animals during learning tasks and could also explain distinct choice biases induced by optogenetic stimulation of the D1 and D2 receptor-expressing striatal neurons. These results indicate that the suggested roles of dopamine in motivational control and reinforcement learning can be understood in a unified manner through a notion that the indirect pathway of the basal ganglia represents the value of states/actions at a previous time point, an empirically driven key assumption of our model.
Apples and oranges: a comparison of RDF benchmarks and real RDF datasets

The widespread adoption of the Resource Description Framework (RDF) for the representation of both open web and enterprise data is the driving force behind the increasing research interest in RDF data management. As RDF data management systems proliferate, so are benchmarks to test the scalability and performance of these systems under data and workloads with various characteristics. In this paper, we compare data generated with existing RDF benchmarks and data found in widely used real RDF datasets. The results of our comparison illustrate that existing benchmark data have little in common with real data. Therefore any conclusions drawn from existing benchmark tests might not actually translate to expected behaviours in real settings. In terms of the comparison itself, we show that simple primitive data metrics are inadequate to flesh out the fundamental differences between real and benchmark data. We make two contributions in this paper: (1) To address the limitations of the primitive metrics, we introduce intuitive and novel metrics that can indeed highlight the key differences between distinct datasets; (2) To address the limitations of existing benchmarks, we introduce a new benchmark generator with the following novel characteristics: (a) the generator can use any (real or synthetic) dataset and convert it into a benchmark dataset; (b) the generator can generate data that mimic the characteristics of real datasets with user-specified data properties. On the technical side, we formulate the benchmark generation problem as an integer programming problem whose solution provides us with the desired benchmark datasets. To our knowledge, this is the first methodological study of RDF benchmarks, as well as the first attempt on generating RDF benchmarks in a principled way.
The Petri Net Baukastenn: an Application-oriented Petri Net Technology

The basic concepts of the Petri Net Baukastenn are introduced. The Petri Net Baukastenn is a Petri net technology and provides Petri net techniques. The Petri Net Baukastenn is consists of the Common Base and three diierent views, the Application Developer View, the Tool Developer View, and the Expert View. The main focus is to support the application developer and the tool developer as well as the Petri net expert.
Synchronization of FBMC based on CAZAC sequence

A synchronization algorithm for FBMC is proposed by combination of CAZAC sequence. Using the CAZAC sequence as the pilot symbols, timing synchronization and frequency synchronization of the FBMC system are realized. Considering the effect of fading on the synchronization, the algorithm combining the CAZAC sequence is rational. Computer simulations verify that the estimation error is about 1e-4 under ordinary signal to noise ratio conditions.
Ant Nestmate and Non-Nestmate Discrimination by a Chemosensory Sensillum

In animal societies, chemical communication plays an important role in conflict and cooperation. For ants, cuticular hydrocarbon (CHC) blends produced by non-nestmates elicit overt aggression. We describe a sensory sensillum on the antennae of the carpenter ant Camponotus japonicus that functions in nestmate discrimination. This sensillum is multiporous and responds only to non-nestmate CHC blends. This suggests a role for a peripheral recognition mechanism in detecting colony-specific chemical signals.
Game analysis on banking risk supervision under asymmetric information

Banks have boosted growth at the country level, at the industry level, and at the firm level. The positive effect of banks on economic development is robust to different econometric methods. Harmonized development of national economy is based on financial stability. Each side of supervision will select its strategy according to the other side of the game to make the revenue maximized. In this paper, we analyze risk taking by banks, i.e. the strategy of banking supervisory. Bank under asymmetric information is anglicized based on game theory, and game model is established under the conditions of asymmetric information and is simulated in order to bring some new ideas for the banking risk supervision of China.
Vehicle Reidentification and Travel Time Measurement in Real-Time on Freeways Using the Existing Loop Detector Infrastructure

This paper presents a new methodology for measuring travel time in real-time on freeways using the existing loop detector infrastructure. The methodology uses vehicle length, a simple signature from paired loop detectors, to extract information about the traffic stream. Other methods of measuring travel time either rely on approximations from aggregate traffic parameters or use expensive, proprietary systems to extract individual vehicle signatures. The reidentification algorithm is tolerant to noise; instead of finding the ‘best match’ for each vehicle, it finds all possible matches. Using a bottom up approach, the algorithm looks for sequences of vehicles from the possible matches. Even with noisy loop detector data, the sequence detection eliminates most of the possible but incorrect matches while the true matches remain. The algorithm is fast, because it compares each pair of vehicles once and only once. Using loop detector speed traps, the communication bandwidth is small compared to other signature based vehicle reidentification methods. The algorithm can also be generalized to the higher resolution, proprietary detection systems. The new methodology will be used to examine the applications and benefits of travel time data on real world traffic, without the expensive costs of a field test. Ordinarily, a travel time measurement system would have to be fully deployed before the benefits can be quantified. The algorithm outlined in this paper is designed to work with existing loop detectors, without any hardware modifications.
Development of a phoneme-to-phoneme (p2p) converter to improve the grapheme-to-phoneme (g2p) conversion of names

It is acknowledged that a good phonemic transcription of proper names is imperative for the success of many modern speech-based services such as directory assistance, car navigation, etc. It is also known that state-of-the-art general-purpose grapheme-to-phoneme (g2p) converters perform rather poorly on many name categories. This paper proposes to use a g2p-p2p tandem comprising a state-of-the-art general-purpose g2p converter that produces an initial transcription and a name category specific phoneme-to-phoneme (p2p) converter that aims at correcting the mistakes made by the g2p converter. The main body of the paper describes a novel methodology for the automatic construction of the p2p converter. The methodology is implemented in a software toolbox that will be made publicly available in a form that will permit the user to design a p2p converter for an arbitrary name category. To give a proof of concept, the toolbox was used for the development of three p2p converters for first names, surnames and geographical names respectively. The obtained systems are small (few rules) and effective: significant improvements (up to 50% relative) of the grapheme-to-phoneme conversion are obtained. These encouraging results call for a further development and improvement of the approach.
EdVidParse : detecting people and content in educational videos

There are thousands of hours of educational content on the Internet, with services like edX, Coursera, Berkeley WebCasts, and others offering hundreds of courses to hundreds of thousands of learners. Consequently, researchers are interested in the effectiveness of video learning. While educational videos vary, they share two common attributes: people and textual content. People are presenting content to learners in the form of text, graphs, charts, tables, and diagrams. With an annotation of people and textual content in an educational video, researchers can study the relationship between video learning and retention. This thesis presents EdVidParse, an automatic tool that takes an educational video and annotates it with bounding boxes around the people and textual content. EdVidParse uses internal features from deep convolutional neural networks to estimate the bounding boxes, achieving a 0.43 AP score on a test set. Three applications of EdVidParse, including identifying the video type, identifying people and textual content for interface design, and removing a person from a picture-in-picture video are presented. EdVidParse provides an easy interface for identifying people and textual content inside educational videos for use in video annotation, interface design, and video reconfiguration. Thesis Supervisor: Robert C. Miller Title: Professor, Department of Electrical Engineering and Computer Science Thesis Supervisor: Antonio Torralba Title: Associate Professor, Department of Electrical Engineering and Computer Science
Radar Principles

Introduction This paper will discuss many of the theoretical and physical principles that underlie the operation of radar systems. The word radar is derived from an acronym for radio detection and ranging. Radar is an electronic and electromagnetic system that uses radio waves to detect and locate objects. Radar operates by transmitting a particular kind of radio frequency waveform and detecting the nature of the reflected echo. When radio waves strike an object, some portion is reflected, and some of this reflected energy is returned to the radar set, where it is detected. The location and other information about these reflective objects, targets, can be determined by the reflected energy. Monostatic radars have transmitters and receivers that are co-located, whereas bistatic radars have transmitters and receivers that are physically separated. This paper will focus on monostatic radar, although many principles developed for monostatic radar can readily be transferred to bistatic radar. Radio waves have many properties including speed, frequency, and power; they display many phenomena such as refraction, attenuation, and reflection. The known speed and reradiation properties of radio waves are fundamental to the theory of radar operation, since radar systems are, at their core, transmitters and receivers of radio waves. Electromagnetic waves are composed of both electric and magnetic fields, both of which oscillate perpendicular to each other and the direction of propagation. These transverse waves can be identified by certain characteristics, such as wavelength and frequency. Wavelength is the distance between successive peaks, whereas frequency is the number of peaks passing a point in a period of time. Radio waves occupy a portion of the electromagnetic spectrum from frequencies of a few kilohertz to a few gigahertz, less than one-billionth of the total electromagnetic spectrum. In a vacuum, radio waves travel in straight lines. The speed of radio wave propagation in a vacuum (310 8 m/s) is a universal constant, c. The speed of wave propagation differs from c if the medium of propagation is matter. When electromagnetic waves travel in nonconducting materials, such as air, the wave speed v, is slower than c and is given by SYRACUSE RESEARCH CORPORATION Page 2 of 2 v = 1 εµ (1) where ε and µ are the permittivity and permeability of the material, respectively. This velocity difference is not significant in air, but can have large effects for radars such as ground penetrating radar. A measure derived from this …
Direct Observation of High-Speed Plasma Outflows Produced by Magnetic Reconnection in Solar Impulsive Events

Spectroscopic observations of a solar limb flare recorded by SUMER on SOHO reveal for the first time hot, fast magnetic reconnection outflows in the corona. As the reconnection site rises across the SUMER spectrometer slit, significant blue- and redshift signatures are observed in sequence in the Fe XIX line, reflecting upflows and downflows of hot plasma jets, respectively. With the projection effect corrected, the measured outflow speed is between ~900 and 3500 km s-1, consistent with theoretical predictions of the Alfvénic outflows in magnetic reconnection region in solar impulsive events. Based on theoretic models, the magnetic field strength near the reconnection region is estimated to be 19-37 G.