Miracle-dz/UniFAR-FTUs huggingface dataset:
A lighweight causal logging scheme for recoverable distributed shared memory

This paper presents a new causal logging scheme for lazy release consistent distributed shared memory systems. For the efficient implementation of causal logging, data structures and operations supported by the lazy release consistency memory model are utilized. Also, unlike the previous scheme which logs the vector clock for each synchronization operation, the proposed scheme adds the minimum information to recreate the corresponding vector clock, into the existing write notice structures. As a result, the additional information carried in each message becomes less than two integers for each synchronization interval, and hence, fault-tolerance can be achieved with very little overhead. Moreover, the size of the additional information is independent of the number of processes in the system, which means that the new scheme can be very effective for the large size systems. To evaluate the performance of the proposed scheme, the logging protocols have been implemented on top of the CVM(Coherent Virtual Machine), and the experimental results show that the proposed scheme achieves 35% 66% of reduction in the log size.
Attribute/Service Model: Design Patterns for Efficient Coordination of Distributed Sensors, Actuators and Tasks in Embedded Systems

This paper proposes the Attribute/Service Model (ASM) and associated design patterns as a general and simple framework for applications that require programming with multiple tasks on multiple embedded processors. This model enables the programming of complex tasks with multiple sensors and actuators on highly distributed yet tightly coupled systems by: using a simple unified protocol for communication; allowing the access to attributes or the running of services to be independent of where such attributes or services reside; protecting shared resources, and simplifying the synchronization of multiple processes in multiple processors. Associated design patterns such as the event/trigger mechanism and general event-driven control are developed on ASM. ASM is designed for the coordination of distributed sensors, actuators and computational tasks on modular self-reconfigurable robots. However it may be used for any multi-threaded distributed embedded control network. Unlike the most existing distributed objects, ASM can be implemented on embedded systems with small footprints. ASM has been implemented both in C on top of VxWorks on the MPC555 embedded microprocessor, and in Java on PC. The Controller Area Network (CAN) has been used as the communication medium. It could be equally implemented on any real-time operating system using any communication media.
SemiNMF-PCA framework for Sparse Data Co-clustering

Several studies have demonstrated the importance of co-clustering which aims to cluster simultaneously the sets of objects and features. The co-clustering is often more effective than one-side clustering, especially when considering sparse high dimensional data. In this paper, we propose a novel way to consider the co-clustering and the reduction of the dimension simultaneously. Our approach takes advantage of the mutual reinforcement between Principal Component Analysis (PCA) which provides a low-dimensional representation of data and Semi-Nonnegative Matrix Factorization (SemiNMF) that learns this low-dimensional representation and lends itself to a co-clustering interpretation. In other words, the proposed framework aims to find an optimal subspace of multi-dimensional variables for effectively identifying a partition of the set of objects. We show that by doing so, our model is able to learn low-dimensional representations that are better suited for co-clustering, outperforming not only spectral methods, but also co-clustering graph-regularized-based methods.
Speeding Coordination by Combining Analytical and Inductive Learning

In a highly dynamic information society, the practical applicability of one filtering framework is usually directly proportional to its flexibility, where this assumes not only an easy integration of novel strategies but also the ability to adapt to new resource conditions. A major drawback of many existing systems, trying to make different synergies between filtering strategies, is usually concerned with an inability to easily integrate new strategies and with not taking care of resource availability, being critical for the realisation of the successful commercial deployments. The cornerstone of the presented filtering framework is in the encapsulation of the searching algorithms inside separate filtering agents whose abilities to be utilised in different runtime situations are efficiently learnt by combining both analytical and inductive learning. The evaluation results demonstrate that analytical learning successfully exploits domain knowledge about filtering strategies while helping inductive learning do faster adaptation.
Presence of Candida Albicans in Root Canal System of Teeth Requiring Endodontic Retreatment with and without Periapical Lesions

INTRODUCTION: An important consideration in endodontic treatment is the elimination of microorganisms, including fungi, from the complex three- dimensional root canal system. Candida Albicans (CA) has a major role in endodontic treatment failure as the most important fungus isolated from the root canal system. The present study was carried out to evaluate the presence of CA in the teeth requiring endodontic retreatment, with or without periapical lesions. MATERIALS AND METHODS: This study was carried out on 60 root canals from human molars requiring endodontic retreatment. The root canals were randomly divided into two equal groups of 30 canals with versus without periapical lesions. Samples were collected from the root canals and cultured on MacConkey and blood agar culture media. The samples suspected of having CA were streaked on Sabouraud’s Dextrose Agar (SDA) and evaluated under a light microscope. Data was analyzed and compared using Chi- square and Kappa tests. RESULTS: CA was found in 11 patients (36.7%) with periapical lesions. In the patients without periapical lesions only 4 samples demonstrated CA in the root canal systems (13.3%). The difference between the two groups as to the presence of CA was statistically significant (p<0.037). In addition, evaluation of salivary samples revealed 15 cases (50%) of CA presence in the patients with periapical lesions and 16 cases (53.3%) of CA in the patients without periapical lesions, demonstrating no statistically significant difference between the two groups. CONCLUSION: Considering the fact that the presence of CA in the root canal systems of teeth with periapical lesions was more noticeable and statistically significant compared to the teeth without periapical lesions, the elimination of this microorganism from the root canal system, using appropriate intracanal solutions and medications is of utmost importance.
Using the Simulation of Ecological Systems to Explain the Wheel of Retailing

Understanding the change in retail structure has been a distinct challenge for many managers and policy analysts since the 1950s. Research has focused on concepts such as the wheel of retailing. However, this theory is more descriptive than explanatory of changes in market structure. In this paper we argue that changes in retail structure (discount stores, specialist stores, department stores and even malls versus online shopping), can be modelled using the ecological simulation concept of competing sessile species, with different growth rates and overgrowth rates based on changing suitability to the environment. Our results show that the application of the COMPETE model [see 1, 2] produce greater and a different diversity of retailers in larger compared to smaller shopping malls.
Fault diagnosis for power systems based on neural networks

Neurocomputing is one of fastest growing areas of research in the fields of Artificial Intelligence and Pattern Recognition. Real time Fault Detection and Diagnosis (FDD) is an important area of research interest in Knowledge Based Expert Systems. This paper explores the suitability of pattern classification approach of neural networks for fault detection and diagnosis. Suitability of using neural network as pattern classifiers for power system fault diagnosis is described in detail. An Analysis of the learning, recall and generalization charecterstisc of the neural network diagnostic system is presented and discussed in detail. A neural network design and simulation environment for real-time FDD is presented.
Schooling as a positional good: the Brazilian metropolitan regions in recent decades

Abstract In this article, I aim to determine whether, in view of the trend of educational expansion in recent decades in Brazil, the role played by schooling in the labor market of Brazilian major metropolitan regions has changed, becoming positional rather than absolute. To this end, I analyze the influence of schooling on people’s income and occupational status. Based on data from the National Household Sample Survey (PNAD-IBGE) for years 1995, 2005 and 2015, I compare ordinary least squares models that use absolute and positional measures of schooling. The results show that the explanatory power is greater for positional measures than for absolute ones, and that this advantage has increased over recent decades. As a result, it is argued that although educational expansion possibly makes the chances of access to a certain absolute schooling level less unequal, it also ends up undermining the opportunity structure related to it.
Do “Undocumented Aliens” Dream of Neoliberal Sheep?: Conditional DREAMing and Decolonial Imaginaries

ABSTRACT Dreams have long been thought to be a space of fantasy and utopic hope. From Paulo Freire to Gloria Anzaldúa to Robin Kelley, many scholars have related the ability to dream with the ability to act collectively, to self-actualize, and to call into being worlds yet to be realized—dreaming as a radical political act. What happens, then, when dreams lose their ability to sense outside of the existing order? What happens when dreams become a mere recapitulation of that which already is? What happens when dreams become legislated and coerced? In conversation with contemporary literature on biopower and psychopower, this article acts as a dream interpretation of the DREAM Act (dreampower), analyzing how the assemblages of immigration, citizenship, and power come together by and through new technologies of governance. Focusing on the role dreams play in the political transformation of “undocumented aliens” into more terrestrial/palatable beings, we examine the ways material and symbolic forms of neoliberal life have been operationalized to patrol and condition what constitutes acceptable dreams and, therefore, who can be a DREAMer. We conclude with a call for a decolonial politics of ensueños: a call for a sleeping and a dreaming of alterity where we wake up in order to dream, and dream in order to wake up.
Bromocresol Green/Mesoporous Silica Adsorbent for Ammonia Gas Sensing via an Optical Sensing Instrument

A meso-structured Al-MCM-41 material was impregnated with bromocresol green (BG) dye and then incorporated into a UV-Vis DRA spectroscopic instrument for the online detection of ammonia gas. The absorption response of the Al-MCM-41/BG ammonia sensing material was very sensitive at the optical absorption wavelength of 630 nm. A high linear correlation was achieved for ppmv and sub-ppmv levels of ammonia gas. The response time for the quantitative detection of ammonia gas concentrations ranging from 0.25 to 2.0 ppmv was only a few minutes. The lower detection limit achieved was 0.185 ppmv. The color change process was fully reversible during tens of cycling tests. These features together make this mesoporous Al-MCM-41 material very promising for optical sensing applications.
A Safety Net for Fast Migrators: Interactions between Gap-opening and Sub-Gap-opening Bodies in a Protoplanetary Disk

Young planets interact with their parent gas disks through tidal torques. An imbalance between inner and outer torques causes bodies of mass ≳0.1 Earth masses (M⊕) to lose angular momentum and migrate inward rapidly relative to the disk; this is known as "Type I" migration. However, protoplanets that grow to gas-giant mass, O(102) M⊕, open a gap in the disk and are subsequently constrained to migrate more slowly, locked into the disk's viscous evolution in what is called "Type II" migration. In a young planetary system, both Type I and Type II bodies likely coexist; if so, differential migration ought to result in close encounters when the former originate on orbits exterior to the latter. We investigate the resulting dynamics, using two different numerical approaches: an N-body code with dissipative forces added to simulate the effect of the gas disk, and a hybrid code that combines an N-body component with a one-dimensional viscous disk model, treating planet-disk interactions in a more self-consistent manner. In both cases, we find that sub-gap-opening bodies have a high likelihood of being resonantly captured when they encounter a gap-opening body. A giant planet thus tends to act as a barrier in a protoplanetary disk, collecting smaller protoplanets outside of its orbit. Such behavior has two important implications for giant planet formation. First, for captured protoplanets it mitigates the problem of the migration timescale becoming shorter than the growth timescale when Mproto ≳ 1 M⊕. Second, it suggests one path to forming systems with multiple giant planets: once the first has formed, it traps (or indeed accretes) the future solid core of the second in an exterior mean-motion resonance, and so on. The most critical step in giant planet formation may thus be the formation of the very first one.
The deficit of the isometric tetanic tension redeveloped after a release of frog muscle at a constant velocity

Frog sartorius muscles tetanized isometrically were released at a constant velocity from lengths lL to lS (delta l = lL -lS; Ls greater than lO). The tension PS redeveloped after the release was lower than the isometric tension PS at LS, and higher than the isometric tension PL at lL. The tension deficit D is defined as the difference PS-PS. The timing of the release during the tetanus did not influence D. D/PO was proportional to delta l/lO. The proportionality constant k was equal to 1.35 +/- 0.19 (n = 8) when the velocity of release was 2.5 mm/s. When the muscles were released the same delta l, D was found to be an exponential decreasing function of the velocity. The tension deficit was also found in experiments performed in the region lS less than lO. The proportionality constant k was smaller, but the influence of the velocity of the release on D was not modified. When the velocity of the release was changed during the release, D changed accordingly, showing that the effects of delta l and V are multiplicative. These facts suggest a working hypothesis based on the concept that the actin filaments which enter the overlap region during a release are strained by the tetanic stress and therefore unable to make normal cross-bridges.
On the Role of Mentions on Tweet Virality

In this paper, we investigate the role of mentions on tweet propagation. We propose a novel tweet propagation model SIR_MF based on a multiplex network framework, that allows to analyze the effects of mentioning on final retweet count. The basic bricks of this model are supported by a comprehensive study of multiple real datasets and simulations of the model show a nice agreement with the empirically observed tweet popularity. Studies and experiments also reveal that follower count, retweet rate & profile similarity are important factors in gaining tweet popularity and allow to better understand the impact of the mention strategies on the retweet count. Interestingly, we analytically identify a critical retweet rate regulating the role of mention on the tweet popularity. Finally, our data driven simulation demonstrates that the proposed mention recommendation heuristic "Easy-Mention" outperforms the benchmark "Whom-To-Mention" algorithm.
Research Proposal for " Using Components for Mapping Activity Processes "

The objective of this research proposal is to see how components can be used to map information from one system to an other. To do this a number of different problems must be addressed, and three groups of problems can be found. The first is how components work and how the other problems can benefit from that. The second is mapping, both syntactically and semantically. What information is needed and how is it going to be used in the components? Lastly, processes need to be found and modelled, that is what activities are actually done in the system and how do they work together? All the problems need to be address iteratively since they depend on each other. The result of this research proposal is the preliminary problem statement " How can components be used and constructed to be able to map information from one system to another while retaining the semantic value of the information? ". This is going to be explored in two projects, the first one using an in-house produced reference database as a prototype. The second project will use the knowledge gathered from the first and apply it to a real-world system. 1 Background Software development is getting more complex for every year [7]. Brooks says that software might be more complex for their size than any other human constructs, this because no two parts are alike [2]. Because of this software development is expensive and takes time, and leads to reluctance to develop new systems when the old ones are still working, although perhaps not as well as every one involved wants. Another problem arising is the communication between systems, old and new. This can be on different levels, the output from one system is not compatible with what the second system expects as input. This problem is in part addressed by XML where information about, for example, an order can be marked with tags to specify the contents. Between systems this is possible by using a message-oriented middle-ware (MOM) which sits between systems and sends messages between them [3]. There is also the problem of the semantics of the information not being compatible, the word " costumer " may have different meaning, a meaning not as easy to mark with XML tags, when dealt with in with different systems. In relation, and as a part of, the above mention problem is the problem of …
Exploring statistics anxiety: Contrasting mathematical, academic performance and trait psychological predictors

Statistics anxiety is experienced by a large numberof psychology students, and previous research has examined a range of potential correlates, including academic performance, mathematical ability and psychological predictors. These varying predictors are often considered separately, although there may be shared variance between them. In the present study a wide range of predictors were measured in a sample of 112 first year undergraduate psychology students. For statistics anxiety, trait anxiety was the clearest predictor, with students who have higher levels of trait anxiety also having higher levels of statistics anxiety. For attitudes towards statistics, students who have better mathematical ability, and greater enjoyment ofand confidence in their maths ability, also having more positive attitudes towards statistics. These findings suggest that models of statistics anxiety need to consider a wide range of predictors, which may in turn necessitate the development of a range of different interventions to alleviate statistics anxiety.
Motion Capture using Body Mounted Cameras in an Unknown Environment

Motion capture has been recently used to provide much of character motion in several recent theatrical releases. It generally requires the recording to be done in an indoor environment with controlled light setting. This prevents directors from capturing motion in a natural setting or a large environment. In this paper we propose a method to solve this problem of motion capture in an unknown and unconstrained environment by using body mounted cameras.
The Evolution of C 2 ” Sensor Positioning and Selection in Sensor Networks for Target Tracking Topic : Modeling and Simulation ( Track 6 )

Current practice in maritime planning operations is the separation in space and time domain. An adaptive and near real time sensor allocation mechanism would mean a significant step forward towards implementing NEC, and would make better use of the distributed sensor resources. To realize a NEC systems concept, the coordination between naval units has to increase. The combat management system has to extend its functionality over multiple networked platforms. Sensor management (SM), as part of the C2 loop, has to be automated and applied across ships. As a step forwards, here we divide automated SM into sensor selection and sensor positioning. The goal is to automatically allocate a network of sensors based on their characteristics. The sensor selection process serves to find the appropriate sensor for doing an observation. Sensor positioning determines the best sensor positions to best deploy the sensor capabilities in the near future. Terminology like ‘appropriate’ and ‘best deployment’ imply an optimization process, minimizing a cost function, that acts as the driver mechanism for sensor selection and positioning. As part of the operational picture compilation process, in this paper sensor selection and positioning are applied to optimize the target track accuracy.
Day-Ahead Scheduling of a Microgrid-Like Fast Charging Station

With the fast spreading of electric vehicles (EVs), the demand for EV fast charging station (FCS) is increasing fast. In this paper, a day-ahead scheduling strategy for a microgrid-like FCS with an in-station photovoltaic system (PVS) and a battery energy storage system (BESS) is proposed. The strategy is modeled as a scenario-based stochastic optimization problem whose objective is to minimize the expected total operation cost in the next day. Considering the power exchange between the FCS and the grid, the operation cost contains the cost of buying power in the day-ahead market, the expected adjustment cost and penalty in the real-time market and the life loss cost of the BESS. A piecewise linear life loss calculation model of the BESS is adopted. The uncertainty of the PVS output and the fast charging demand are considered in the model through randomly generated scenarios. In each scenario the PVS output and fast charging demand are generated using a Monte Carlo simulation method. This strategy considers the life loss cost of the BESS effectively and provide reasonable day-ahead schedules. In the case study, a simulation of the proposed day-ahead scheduling method is demonstrated.