Miracle-dz/UniFAR-FTUs huggingface dataset:
On the design space of MapReduce ROLLUP aggregates

We dene and explore the design space of ecient algorithms to compute ROLLUP aggregates, using the MapReduce programming paradigm. Using a modeling approach, we explain the non-trivial trade-o that exists between parallelism and communication costs that is inherent to a MapReduce implementation of ROLLUP. Furthermore, we design a new family of algorithms that, through a single parameter, allow to nd a \sweet spot" in the parallelism vs. communication cost trade-o. We complement our work with an experimental approach, wherein we overcome some limitations of the model we use. Our results indicate that ecient ROLLUP aggregates require striking the good balance between parallelism and communication for both one-round and chained algorithms.
Cooperative Multi-Robot Path Planning by Heuristic Priority Adjustment

In this paper, a new algorithm for cooperative path planning in a multi-robot system is introduced. The algorithm is specially designed for a distributed system with a large number of robots, all of which should be able to reach their respective goal positions without blocking each other, even if the environment is heavily constricted by obstacles. The basic idea of the approach is based on fully distributed path planning without any central instance, but with the ability of communication and cooperation between the robots. Path planning is done on local sections of the time-space configuration space. Dynamic conflicts between the robots are solved by the heuristic adjustment of priority values. By a continuous enhancement of all plans the algorithm is very robust against dynamic changes and erroneous robot behavior
Revisions of the international criteria for neuroblastoma diagnosis, staging and response to treatment.

PURPOSE AND METHODS: Based on preliminary experience, there was a need for modifications and clarifications in the International Neuroblastoma Staging System (INSS) and International Neuroblastoma Response Criteria (INRC). In 1988, a proposal was made to establish an internationally accepted staging system for neuroblastoma, as well as consistent criteria for confirming the diagnosis and determining response to therapy (Brodeur GM, et al: J Clin Oncol 6:1874-1881, 1988). A meeting was held to review experience with the INSS and INRC and to revise or clarify the language and intent of the originally proposed criteria. Substantial changes included a redefinition of the midline, restrictions on age and bone marrow involvement for stage 4S, and the recommendation that meta-iodobenzylguanidine (MIBG) scanning be implemented for evaluating the extent of disease. Other modifications and clarifications of the INSS and INRC are presented. In addition, the criteria for the diagnosis of neuroblastoma were modified.
Relationship Privacy Protection for Mobile Social Network

Recent scientific results have shown that location-based social networks (LBSNs) can be used to automatically and accurately predict even highly sensitive personal attributes (such as social relationships). To avoid the adversary inferring users' relationship privacy, a relationship privacy protection schema is proposed to protect the user privacy in mobile social network. An algorithm of location privacy protection is designed to calculate the probability of relationship privacy risk, which is used to evaluate whether the users' check-in meet the privacy requirement. Extensive experiments on a real dataset show that our method can effectively protect users' relationship privacy.
Second international campaign for public awareness of the Caulerpa taxifolia problem. An essential tool to collect cartographic data and to slow down the spread of this alga

Accidentaly introduced into the Mediterranean sea in 1984, the tropical alga Caulerpa taxifolia did not stop to spread since then. The ecological and economic threats related to this invasion incited scientist to organize a second international campaign of sensitisation, research and prevention. In 1997, 45.000 leaflets published in 6 languages (French, Italian, Castilian, Catalan, Croatian, and English) were distributed to sea users. The aim is to provide the sea users with precise and updated information on results published since 1990. A description of the alga and advice to reduce man-made dissemination are presented. Divers, yachtsmen, fishermen, and port administrators are requested to warn scientists in charge of C.taxifolia about any new sighting of colonies. This campaign enables the establishment and the consolidation of national and international informant networks which are crucial to the yearly assessment of C.taxifolia spreading in the Mediterranean sea. The expansion of the alga is one of the main element to take into account in the elaboration of a prevention strategy to fight C.taxifolia progression.
Critical Aspects for a Secure IP Mobility Architecture in Vehicular Area Networks (VANETs)

Communication facilities for vehicles became more and more important over the last years. Most time this involves the usage of wireless technologies for communication between vehicles, between vehicles and the roadside, as well as between the vehicle and systems reachable via Wide Area Networks (WANs) such as the Internet. This paper discusses how Internet technologies can be used for supporting the communication of mobile vehicles, which risks are involved performing this mobile communication, and which security technologies can prevent against these risks.
Optimal covering tours with turn costs

We give the first algorithmic study of a class of “covering tour” problems related to the geometric Traveling Salesman Problem: Find a polygonal tour for a cutter so that it sweeps out a specified region (“pocket”), in order to minimize a cost that depends not only on the length of the tour but also on the number of turns. These problems arise naturally in manufacturing applications of computational geometry to automatic tool path generation and automatic inspection systems, as well as arc routing (“postman”) problems with turn penalties. We prove lower bounds (NP-completeness of minimum-turn milling) and give efficient approximation algorithms for several natural versions of the problem, including a polynomial-time approximation scheme based on a novel adaptation of the m-guillotine method.
Delineating Fields Using Mathematical Jargon

Tracing ideas through the scientific literature is useful in understanding the origin of ideas and for generating new ones. Machines can be trained to do this at large scale, feeding search engines and recommendation algorithms. Citations and text are the features commonly used for these tasks. In this paper, we focus on a largely ignored facet of scholarly papers—the equations. Mathematical language varies from field to field but original formulae are maintained over generations (e.g., Shannon’s Entropy equation). Here we extract a common set of mathematical symbols from more than 250,000 LTEX source files in the arXiv repository. We compare the symbol distributions across di↵erent fields and calculate the jargon distance between fields. We find a greater difference between the experimental and theoretical disciplines than within these fields. This provides a first step at using equations as a bridge between disciplines that may not cite each other or may speak di↵erent natural languages but use a similar mathematical language.
A non linear face recognition system using Support Vector Machine

A face recognition system uses face to verify individuals using computing capability. However, its performances often degrade due to high dimensional data and large feature appearance of the face image. This paper present a face recognition system based on non linear feature extraction technique to reduce the dimensionality of the face image, called Locally Linear Embedding. This method considers the hidden layer of face manifold to be the input of a SVM multiclass classifier. The performance is evaluated using the ORL database and achieved better recognition rates than the Principal Component Analysis.
A new approach to enable gesture recognition in continuous data streams

Gesture recognition has great potential for mobile and wearable computing. Most papers in this area focus on classifying different gestures, but do not evaluate the distinctiveness of gestures in continuous recordings of gestures in daily life. This paper presents a new approach for the important and challenging problem of gesture recognition in continuous data streams. We use turning points of arm movements to identify segments of interest in the continuous data stream. The recognition algorithm considers both the direction of movements between turning points and the shape of the turning points for classification. Using the new method, seven gestures of different complexity are evaluated against a realistic background class of daily gestures in five different scenarios.
Modelling Contextual Information in Session-Aware Recommender Systems with Neural Networks

Preparing recommendations for unknown users or such that correctly respond to the short-term needs of a particular user is one of the fundamental problems for e-commerce. Most of the common Recommender Systems assume that user identification must be explicit. In this paper a Session-Aware Recommender System approach is presented where no straightforward user information is required. The recommendation process is based only on user activity within a single session, defined as a sequence of events. This information is incorporated in the recommendation process by explicit context modeling with factorization methods and a novel approach with Recurrent Neural Network (RNN). Compared to the session modeling approach, RNN directly models the dependency of user observed sequential behavior throughout its recurrent structure. The evaluation discusses the results based on sessions from real-life system with ephemeral items (identified only by the set of their attributes) for the task of top-n best recommendations.
Into thin air: contributions of aerodynamic and inertial-elastic forces to wing bending in the hawkmoth Manduca sexta

SUMMARY During flapping flight, insect wings must withstand not only fluid-dynamic forces, but also inertial-elastic forces generated by the rapid acceleration and deceleration of their own mass. Estimates of overall aerodynamic and inertial forces vary widely, and the relative importance of these forces in determining passive wing deformations remains unknown. If aeroelastic interactions between a wing and the fluid-dynamic forces it generates are minor compared to the effects of wing inertia, models of insect flight that account for passive wing flexibility would be far simpler to develop. We used an experimental approach to examine the contributions of aerodynamic and inertial-elastic forces to wing bending in the hawkmoth Manduca sexta. We attached fresh Manduca wings to a motor and flapped them at a realistic wing-beat frequency and stroke amplitude. We compared wing bending in normal air versus helium (approx. 15% air density), in which the contribution of fluid-dynamic forces to wing deformations is significantly reduced. This 85% reduction in air density produced only slight changes in the pattern of Manduca wing deformations, suggesting that fluid-dynamic forces have a minimal effect on wing bending. We used a simplified finite element model of a wing to show that the differences observed between wings flapped in air versus helium are most likely due to fluid damping, rather than to aerodynamic forces. This suggests that damped finite element models of insect wings (with no fluid-dynamic forces included) may be able to predict overall patterns of wing deformation prior to calculations of aerodynamic force production, facilitating integrative models of insect flight.
Table of contents

Web search result clustering aims to facilitate information search on the Web. Rather than presenting the results of a query as a flat list, these are grouped on the basis of their similarity and subsequently shown to the user as a list of possibly labeled clusters. Each cluster is supposed to represent a different meaning of the input query, thus taking into account the language ambiguity issue. However, Web clustering methods typically rely on some notion of textual similarity of search results. As a result, text snippets with no word in common tend to be clustered separately, even if they share the same meaning. In this talk, we present a novel approach to Web search result clustering based on the automatic discovery of word senses from raw text, a task referred to as Word Sense Induction (WSI). Key to our approach is to first acquire the senses (i.e., meanings) of a query and then cluster the search results based on their semantic similarity to the word senses induced. Our experiments, conducted on datasets of ambiguous queries, show that our approach outperforms both Web clustering and search engines in the clustering and diversification of search results.
A deep recurrent approach for acoustic-to-articulatory inversion

To solve the acoustic-to-articulatory inversion problem, this paper proposes a deep bidirectional long short term memory recurrent neural network and a deep recurrent mixture density network. The articulatory parameters of the current frame may have correlations with the acoustic features many frames before or after. The traditional pre-designed fixed-length context window may be either insufficient or redundant to cover such correlation information. The advantage of recurrent neural network is that it can learn proper context information on its own without the requirement of externally specifying a context window. Experimental results indicate that recurrent model can produce more accurate predictions for acoustic-to-articulatory inversion than deep neural network having fixed-length context window. Furthermore, the predicted articulatory trajectory curve of recurrent neural network is smooth. Average root mean square error of 0.816 mm on the MNGU0 test set is achieved without any post-filtering, which is state-of-the-art inversion accuracy.
Regulation of nausea and vomiting by cannabinoids

Considerable evidence demonstrates that manipulation of the endocannabinoid system regulates nausea and vomiting in humans and other animals. The anti‐emetic effect of cannabinoids has been shown across a wide variety of animals that are capable of vomiting in response to a toxic challenge. CB1 agonism suppresses vomiting, which is reversed by CB1 antagonism, and CB1 inverse agonism promotes vomiting. Recently, evidence from animal experiments suggests that cannabinoids may be especially useful in treating the more difficult to control symptoms of nausea and anticipatory nausea in chemotherapy patients, which are less well controlled by the currently available conventional pharmaceutical agents. Although rats and mice are incapable of vomiting, they display a distinctive conditioned gaping response when re‐exposed to cues (flavours or contexts) paired with a nauseating treatment. Cannabinoid agonists (Δ9‐THC, HU‐210) and the fatty acid amide hydrolase (FAAH) inhibitor, URB‐597, suppress conditioned gaping reactions (nausea) in rats as they suppress vomiting in emetic species. Inverse agonists, but not neutral antagonists, of the CB1 receptor promote nausea, and at subthreshold doses potentiate nausea produced by other toxins (LiCl). The primary non‐psychoactive compound in cannabis, cannabidiol (CBD), also suppresses nausea and vomiting within a limited dose range. The anti‐nausea/anti‐emetic effects of CBD may be mediated by indirect activation of somatodendritic 5‐HT1A receptors in the dorsal raphe nucleus; activation of these autoreceptors reduces the release of 5‐HT in terminal forebrain regions. Preclinical research indicates that cannabinioids, including CBD, may be effective clinically for treating both nausea and vomiting produced by chemotherapy or other therapeutic treatments.
Tracking and Understanding Automated Space Shuttle Fault Detection, Isolation and Recovery

Agent-Oriented Fault Detection, Isolation and Recovery and Aspect-Oriented Plug-andPlay Tracking Mechanism. (August 2003) Feilong Chen, B.S., China Agricultural University Chair of Advisory Committee: Prof. Richard Volz Fault detection, isolation, and recovery are some of the most critical activities in which astronauts and flight controllers participate. Recent systems to perform the FDIR activity lack portability and extensibility, and do not provide any explanation of the system’s activity. In this research, we explore the use of an agent-oriented paradigm and Java technology for better performance of FDIR activity. Also, we have explored the use of explanation in agent-oriented systems, and designed a system-activity tracking mechanism that helps the user to understand the agents’ behavior. We have explored different ways to generalize this mechanism for arbitrary agent systems to use. Furthermore, we studied mechanisms to automatically add the tracking mechanism to an existing agent system. By using AspectJ, an aspect-oriented tool, a plug-and-playable tracking system has been built that can add the capability to track the activity of the system to any JACK agent system easily. Our experience can help further research on using aspect-oriented tools with agent-oriented paradigms together to obtain better performance.
An Efficient Approach to Compose Web Services

An intensive work has been done for designing efficient algorithms for combining a series of Web services. However, existing solutions for Web services composition fail to present a specific method which can guide us to compose multiple services step by step. In this paper, we propose an efficient approach to address this issue. We employ Temporal Logic of Actions (TLA) to describe the behavior of services and design an algorithm to cope with the issue. Furthermore, our approach is a formal one when compared with current solutions based on BPEL, WS-CDL, OWL-S, etc. Besides, the approach can be used to both composition and verification while Petri net based method can not.
IMMPDA vehicle tracking system using asynchronous sensor fusion of radar and vision

This paper focuses on recognition and tracking of maneuvering vehicles in dense traffic situations. We present an asynchronous multi obstacle multi sensor tracking method that fuses information from radar and monocular vision. A low level fusion method is integrated into the framework of an IMMPDA Kalman filter. Real world experiments demonstrate that the system combines the complementary strengths of the employed sensors.
A General Formula for Event-Based Stabilization of Nonlinear Systems

In this technical note, a universal formula is proposed for event-based stabilization of general nonlinear systems affine in the control. The feedback is derived from the original one proposed by E. Sontag in the case of continuous time stabilization. Under the assumption of the existence of a smooth Control Lyapunov Function, it is proved that an event-based static feedback, smooth everywhere except at the origin, can be designed so to ensure the global asymptotic stability of the origin. Moreover, the inter-sampling time can be proved not to contract at the origin. More precisely, it is proved that for any initial condition within any given closed set the minimal inter-sampling time is proved to be below bounded avoiding the infinitely fast sampling phenomena. Moreover, under homogeneity assumptions the control can be proved to be smooth anywhere and the inter-sampling time bounded below for any initial condition. In that case, we retrieve a control approach previously published for continuous time stabilization of homogeneous systems.
Electrochemical detection of hybridized DNA using reduction of methylene blue

One of the important roles of a DNA sensor is the capability of detecting genetic diseases or mutations by analyzing DNA sequences. The electrochemical detection method can be simpler and cheaper than other methods available and hence this method was investigated in this paper. For successful electrochemical detection, several aspects should be considered including chemical treatment of the electrode surface, DNA immobilization on an electrode, hybridization, choice of an intercalator to be bound to double stand DNA selectively, and equipment for detecting and analyzing the output signal. The intercalator bound to double strand DNA results in an electrical current. With the electrochemical detection method, double strand DNA was distinguished from single strand DNA or bare gold electrode by measuring the reduction current of intercalator. Also, it was found that the reduction current of the intercalator is proportional to the concentration of target DNA to be hybridized with probe DNA. Therefore, it is possible to realize a simple and cheap DNA sensor using the electrochemical detection method for DNA sequencing.
BDDTCL: an environment for visualizing and manipulating binary decision diagrams

A Binary Decision Diagram (BDD) is a data structure used in hardware verification to represent boolean expressions. Most BDD implementations provide only textual output and require the user to interact with them using a compiled programming language. BDDTCL provides an interpreted language forma-nipulating BDDs and a graphical viewer for manipulating and visualizing them. BDDTCL can draw BDDs with over 4,400 nodes; much larger than can be easily drawn by hand. Two users, a hardware design researcher and a student unfamiliar with BDDs, provided feedback about BDDTCL’S effectiveness for understanding systems modeled by BDDs. These users also provided feedback for improving BDDTCL.
Spectrophotometric Determination of Certain Benzimidazole Proton Pump Inhibitors

Spectrophotometric method for the determination of certain proton pump inhibitors belonging to the benzimidazole class of compounds has been developed. The method is based on the reaction of omeprazole, lansoprazole, pantoprazole, rabeprazole and esomeprazole with iron (III) and subsequent reaction with ferricyanide under neutral condition which yields Prussian blue product with maximum absorption at 720–730 nm. The commonly encountered excipients and additives that often accompany pharmaceutical preparations did not interfere with the determination. The method was applied for the determination of omeprazole, lansoprazole, pantoprazole, rabeprazole and esomeprazole in pharmaceutical preparations and no difference was found statistically. Thus, the spectrophotometric method can be applied as inexpensive, rapid, easy, accurate and precise method for the routine analysis of the five proton pump inhibitors in pharmaceutical preparations.
Socially-Informed Timeline Generation for Complex Events

Existing timeline generation systems for complex events consider only information from traditional media, ignoring the rich social context provided by user-generated content that reveals representative public interests or insightful opinions. We instead aim to generate socially-informed timelines that contain both news article summaries and selected user comments. We present an optimization framework designed to balance topical cohesion between the article and comment summaries along with their informativeness and coverage of the event. Automatic evaluations on real-world datasets that cover four complex events show that our system produces more informative timelines than state-of-the-art systems. In human evaluation, the associated comment summaries are furthermore rated more insightful than editor's picks and comments ranked highly by users.