Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust domain decomposition algorithms for multiscale PDEs

In this article, we describe a new class of domain decomposition preconditioners suitable for solving elliptic PDEs in highly fractured or heterogeneous media, such as arise in groundwater flow or oil recovery applications. Our methods employ novel coarsening operators, which are adapted to the heterogeneity of the media. In contrast to standard methods (based on piecewise polynomial coarsening), the new methods can achieve robustness with respect to coefficient discontinuities even when these are not resolved by a coarse mesh. This situation arises often in practical flow computation, in both the deterministic and (Monte‐Carlo simulated) stochastic cases. An example of a suitable coarsener is provided by multiscale finite elements. In this article, we explore the linear algebraic aspects of the multiscale algorithm, showing that it involves a blend of both classical overlapping Schwarz methods and nonoverlapping Schur methods. We also extend the algorithm and the theory from its additive variant to obtain new hybrid and deflation variants. Finally, we give extensive numerical experiments on a range of heterogeneous media problems illustrating the properties of the methods. © 2007 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 23: 859–878, 2007
Load Leveling and Voltage Control of Permanent Magnet Synchronous Generator-Based DG Set for Standalone Supply System

This paper deals with the voltage control and load leveling of permanent magnet synchronous generator (PMSG)-based diesel generator (DG) set for standalone supply system. The proposed system is composed of a PMSG and a prototype of diesel engine (DE), along with the distribution static compensator (DSTATCOM) and battery energy storage system (BESS). The DSTATCOM along with BESS is used for loads leveling and voltage control. It also provides balancing of loads, elimination of harmonics, and compensation of reactive power. The battery on dc link of voltage source converter (VSC) of DSTATCOM is used to supply the active power when the load is more than PMSG rating, and it stores the energy during light load periods. The PMSG is always loaded with an optimum load of 80%-100% of its rating. An optimum loading of DG set helps in improving the fuel efficiency of the DE and also helps in load leveling. The reference source currents are estimated using a hyperbolic tangent function-based least mean square (LMS) algorithm. This control algorithm has reduced computation and provides fast convergence rate to eliminate the effect of noise as compared with other LMS algorithms based on adaptive filtering. The voltage control, load compensation, and fuel efficiency improvement in PMSG-based DG set using BESS and DSTATCOM controlled by hyperbolic tangent function-based LMS algorithm are the main contributions of this paper.
Passivity control based on Euler-Lagrangian model for D-STATCOM with LCL filter

This paper deals with a novel control method for D-STATCOM with LCL filter. LCL filter can effectively attenuate high frequency harmonic of compensation current. By taking the energy dissipation properties of STATCOM with LCL filter into consideration, this paper proposes passivity based control method with Euler-Lagrangian (EL) model and damping injection. The stability of the controllers is analyzed in detail to satisfy static and dynamic performance as well as its ability of suppressing harmonics. The correctness and validity of the proposed control method was verified by the simulation tests based on Matlab/Simulink platform.
Learning Design Engines as Remote Control to Learning Support Environments

Commentary on: Chapter5: An Architecture for Learning Design Engines. (Vogten, Koper, Martens and Tattersall, 2005) Abstract: Chapter 5 of the Learning Design book describes the operational model of a learning design engine based on the concept of finite automata with output alphabet. We rely on this event concept to include pre-existing learning tools in flexibe and rich learning designs. We sketch an approach for the integration of complex learning environments in learning designs. Interactive learning support environments, such as argumentation or modelling tools are pre-existent and have a high potential when integrated in learning designs. We propose an approach that aims at a clear separation of the learning design engine, the specification of the learning flow (as LD documents) and learning environments. According to its current state, the engine controls the learning environment with events (such as "start a new phase"), defined as a vocabulary for a set of environments, that are mapped to the environments' existing functionality (such as "create new workspace"). Thus the engine remotely controls the learning tools while the tools can initiate state transitions in the engine on specific events in the tool. Editors: Colin Tattersall and Rob Koper.
Efficient data layouts for cost-optimized Map-Reduce operations

The MapReduce programming model accepted by Hadoop and other Big Data technologies is a powerful tool to address Big Data analysis problem. It is becoming ubiquitous, but still there are issues in concern with its performance and efficiency. It offers high scalability and fault tolerance in large scale data processing, but gives low efficiency. Hence, how to enhance efficiency with high level of scalability and fault tolerance is a major challenge. The efficiency problem, especially I/O costs can be addressed in two ways: by optimizing I/O operations in Map-Reduce and by utilizing the features of modern hardware such as SSD (Solid State Disk) that can help in minimizing computations in Map-Reduce considerably. This paper explores various existing data layout structures that can improve the efficiency of map-reduce operations and help in overcoming its pitfalls.
A Novel Fingerprint Enhancement Method Based on Gabor Filtering

Fingerprint image enhancement is very important in AFIS (Automatic Fingerprint Identification System). In this paper, a fingerprint enhancement method based on Gabor filtering is introduced. Compared with traditional Gabor-based method, the algorithm uses the improved Gabor filtering to improve the clarity of ridge structures of fingerprints. The improved Gabor filtering can protect the ridge structure and avoid the spurious ridges effectively. In addition, a Fourier- Transformation based method is proposed to compute the orientation field more precisely and efficiently. Experimental results show that the algorithm not only makes improvement on the minutiae extraction accuracy but also saves the time spent on the process. each block, yet the entire structure of ridges in the fingerprint was changed, thus producing some spurious ridges. In this paper, a novel approach, based on Gabor filtering, is introduced to enhance fingerprint images. The features, obtained from the Fourier-domain, are used to estimate the orientations of ridges in fingerprint images, and this estimation can better reduce the impact of noise and save time. To keep the structure of the ridges in fingerprint images, Gabor filters are applied pixel by pixel. In this paper, the features of the ridges in the Fourier-domain are first introduced, which is helpful in estimating the orientation-field, and then the details of the entire algorithm are described.
A General OO-PDE Solver for TCAD Applications*

Technology CAD (TCAD) is a broad area of simulation which is concerned with modeling both the structural and the electrical properties of semiconductor devices. Although TCAD utilizes computational geometry (deposition, etching), monte-carlo methods (ion implantation, “first-principles” device simulation) and other computational approaches, only mesh-based PDE solvers are considered here. The models that these simulators implement have undergone increasing levels of complexity and sophistication. Unfortunately, existing simulators often make assumptions that make it difficult to incorporate new models or take advantage of new computational techniques and technology. To alleviate these difficulties, we are using object-oriented techniques to design a new base code for all of the PDE-based models. To justify the requirements for this code, the PDE models and the limitations of the current simulators are discussed. The requirements for this new base code are laid out. The design methodology and a portion of the final product of the design process are presented. Next, transformation of the design into C++ classes is discussed and an example is presented. Finally, we summarize our experiences in applying the methodology and make some recommendations.
ACE Polymorphism in Colorectal Cancer Patients of Kashmiri Population - A Short Report

Aims: The angiotensin-converting enzyme (ACE) gene in humans has an insertion-deletion (I/D) polymorphic state in intron 16 on chromosome 17q23. This polymorphism has been widely investigated in different cancers and has been implicated as the risk factor for the development of various cancers. To investigate the ACE I/D genotype frequency in CRC cases in Kashmiri population and to correlate it with the known clinicopathological characters of CRC cases. Methods: We designed a case control study, where 86 CRC cases were studied for ACE I/D polymorphism against 150 controls taken from general population. The polymorphisms of ACE gene were investigated using polymerase chain reaction for detection of an I/D polymorphism. Results: Among CRC (86) cases we found the frequency of ACE DD genotype to be 41.86 % (36/86), II 13.95% (12/86) and DI 44.2% (38/86). There was no significant association between the ACE I/D genotype with any of the known clini- copathological characters. Conclusion: The ACE I/D polymorphism is not a significant risk factor in the CRC carcinogenesis in our population.
The Rule of Law: A Reassessment for the Twenty-First Century

This brief radio address attempts to explain the origins of American liberty and to assess its health at the beginning of the 21 century. The notion of rule of law and the emerging science of constitutionalism enabled America’s founding generation to establish a system of political liberty that continues to stand as a model for all human societies to pursue.
Topics in social network analysis and network science

This chapter introduces statistical methods used in the analysis of social networks and in the rapidly evolving parallel-field of network science. Although several instances of social network analysis in health services research have appeared recently, the majority involve only the most basic methods and thus scratch the surface of what might be accomplished. Cutting-edge methods using relevant examples and illustrations in health services research are provided.
SIMULATION OF AN OMNIDIRECTIONAL CATADIOPTRIC VISION SYSTEM WITH HYPERBOLIC DOUBLE LOBED MIRROR FOR ROBOT NAVIGATION

An Omnidirectional Catadioptric Vision System consists of a convex mirror in the front of a camera to get a 360o view of the observed environment. The association of a hyperbolic mirror with a camera of perspective projection produces only one center of projection, generating images free of distortions. Geometric information from an unknown environment can be obtained with stereo vision techniques and one of the limitations of the stereo omnidirectional vision is the formation of an invisible region of the space in the motion direction. A proposed solution to this problem is the use a hyperbolic double lobed mirror. With this type of mirror the pair of stereo images is acquired at the same instant without the need of known relative displacements. More than the solution of this problem is the possibility of working with dynamic environment mapping and the reduction of the processing time at the stage of the correspondence between image pairs, since the search of corresponding points is limited to a radial line. In this work it is presented a model for simulation of the image projections from a virtual hyperbolic double lobed mirror, aiming at the determination of the ideal profile of the mirror and the simulation of its use in specific applications as robot navigation.
A Repeat Sales Index for Residential Property in the Netherlands

In this paper we construct a repeat sales index for residential property in the Netherlands. The index shows the tendency of the Dutch housing market between May 1973 and December 1995. Subsequently, the repeat sales index is utilized as input for investment decisions of homeowners. We calculated correlation matrices of several regions within the Netherlands. Inclusion of residential property investments in a portfolio with stocks and bonds shows that substantial diversification gains can be obtained.
Cooperative Formation Planning and Control of Multiple Mobile Robots

Application of intelligent Wheeled Mobile Robots (WMR) for material handling in the manufacturing environment has been the topic of research in the past decade. Even though researchers have succeeded in applying mobile robots for material handling purpose in the shop floor environment, transporting heavy objects in the assembly line is still a challenge. The dynamical characteristics of a manufacturing environment impose particular abilities a mobile robot should have if it is to operate on the shop floor efficiently, accurately and successfully. Consequently, a WMR needs to adapt itself to everlasting changes. Under such conditions, the use of multiple WMR in closed defined geometric spatial pattern/ formation can be a solution for such applications. One of the essential problems in guiding multiple mobile robots in such dynamically changing environments is to plan, navigate and coordinate the motion of robots, avoiding obstacles as well as each other while transporting the materials/objects towards the goal. Further it requires the robots to control their relative position and orientation between them on the fly. Hence the control of group of mobile robots performing such tasks requires coordination at different levels starting from navigation to formation (Sugar et al., 2001). A variety of strategies and control approaches for formation control of group of coordinated robots, have been adopted in the literature such as Graph Theory (Desai, 2002), Vector Potential Field (Yamaguchi et al., 2001), Virtual Structure (Belta & Kumar, 2004), Leader Follower (Fierro et al., 2002) and Behaviour Based Approaches (Arkin, 1998; Goldberg & Mataric, 2002). Further, a comprehensive review of robotic formation, control approaches and algorithms, applications and their advantages and disadvantages have also been addressed (Chen & Wang, 2005). Among all the approaches mentioned in the literature, behaviour – based and leader – follower approach has been widely adopted and well recognized by the researchers because of their simplicity and scalability. Even though robots are able to move in a closed defined formation when controlled using the various methods reported in the literature, the major limitation has been the difficulty to achieve a stable formation between the robots in the group in dynamically changing, unknown environments filled with obstacles. Under such circumstances, as the number of robots increases, the control methods such as the virtual structure, leader follower and
Price and Wage Rigidities in the Republic of Macedonia: Survey Evidence from Micro- Level Data

This paper exploits the information collected from an ad hoc survey conducted on a sample of Macedonian firms to study the extent of nominal price and wage rigidities in the Republic of Macedonia. The research was motivated by the observation that sticky prices influence the responsiveness of inflation to changes in a central bank’s policy rate. Against this background, the paper investigates the relative importance of most determinants of the frequency of price and wage changes identified in the literature. This paper presents a Bayesian analysis of ordinal data. Posterior inference is carried out using Markov Chain Monte Carlo (MCMC) techniques. Infusing the model with prior information allows us to shrink the parameter space, resulting in more precise and reliable parameter estimates. Our results suggest that higher price flexibility is associated with a higher degree of product market competition. Specifically, we find that firms facing high levels of domestic and international competition tend to adjust prices faster.
Performance measurement systems in supply chains: A framework for contextual analysis

Purpose - The purpose of this article is to propose a common framework for the empirical analysis of supply chain performance measurement systems used in different supply chain contexts. Design/methodology/approach - This is a conceptual paper, which includes an extensive literature review and an illustrative case study. The content, context, process framework is applied to structure the body of knowledge and the case study. Findings - Supply chain performance measurement is a context-dependent process, tailored to specific supply chain requirements. To understand how a performance measurement system in a supply chain has developed and is used there is a need to capture its context, process and content. Research limitations/implications - The framework is illustrated by a single case study. Further empirical research is required to fully appreciate the breadth of application of this framework. Practical implications - The proposed framework can help to develop performance measurement systems that are suitable for certain organisational and supply chain contexts in which a company operates, as well as to compare different systems used across different supply chains. Originality/value - The paper demonstrates an approach for analysing existing supply chain performance measurement systems that can be applied across different supply chains and sectors. This will create an opportunity to use a consistent data collection process across a variety of supply chain situations and thus generate data for further theory development.
Whole-Genome Sequences of Mycobacterium tuberculosis TB282 and TB284, a Widespread and a Unique Strain, Respectively, Identified in a Previous Study of Tuberculosis Transmission in Central Los Angeles, California, USA

ABSTRACT We report here the genome sequences of two Mycobacterium tuberculosis clinical isolates previously identified in central Los Angeles, CA, in the 1990s using a PacBio platform. Isolate TB282 represents a large-cluster strain that caused 27% of the tuberculosis cases, while TB284 represents a strain that caused disease in only one patient.
Neural Evidence for a Distinction between Short-term Memory and the Focus of Attention

It is widely assumed that the short-term retention of information is accomplished via maintenance of an active neural trace. However, we demonstrate that memory can be preserved across a brief delay despite the apparent loss of sustained representations. Delay period activity may, in fact, reflect the focus of attention, rather than STM. We unconfounded attention and memory by causing external and internal shifts of attention away from items that were being actively retained. Multivariate pattern analysis of fMRI indicated that only items within the focus of attention elicited an active neural trace. Activity corresponding to representations of items outside the focus quickly dropped to baseline. Nevertheless, this information was remembered after a brief delay. Our data also show that refocusing attention toward a previously unattended memory item can reactivate its neural signature. The loss of sustained activity has long been thought to indicate a disruption of STM, but our results suggest that, even for small memory loads not exceeding the capacity limits of STM, the active maintenance of a stimulus representation may not be necessary for its short-term retention.
Neuropeptides in the Drosophila central complex in modulation of locomotor behavior

SUMMARY The central complex is one of the most prominent neuropils in the insect brain. It has been implicated in the control of locomotor activity and is considered as a pre-motor center. Several neuropeptides are expressed in circuits of the central complex, and thus may be modulators of locomotor behavior. Here we have investigated the roles of two different neuropeptides, Drosophila tachykinin (DTK) and short neuropeptide F (sNPF), in aspects of locomotor behavior. In the Drosophila brain, DTK and sNPF are expressed in interneurons innervating the central complex. We have directed RNA interference (RNAi) towards DTK and sNPF specifically in different central complex neurons. We also expressed a temperature-sensitive dominant negative allele of the fly ortholog of dynamin called shibirets1, essential in membrane vesicle recycling and endocytosis, to disrupt synaptic transmission in central complex neurons. The spontaneous walking activity of the RNAi- or shibirets1-expressing flies was quantified by video tracking. DTK-deficient flies displayed drastically increased center zone avoidance, suggesting that DTK is involved in the regulation of spatial orientation. In addition, DTK deficiency in other central complex neurons resulted in flies with an increased number of activity–rest bouts. Perturbations in the sNPF circuit indicated that this peptide is involved in the fine regulation of locomotor activity levels. Our findings suggest that the contribution of DTK and sNPF to locomotor behavior is circuit dependent and associated with particular neuronal substrates. Thus, peptidergic pathways in the central complex have specific roles in the fine tuning of locomotor activity of adult Drosophila.
Suicidal behaviour: an epidemiological and genetic study

Background. Psychiatric history, familial history of suicide attempts, and certain traumatic life events are important predictors of suicidal thoughts and behaviour. We examined the epidemiology and genetics of suicidality (i.e. reporting persistent suicidal thoughts or a plan or suicide attempt) in a large community-based sample of MZ and DZ twin pairs. Method. Diagnostic telephone interviews were conducted in 1992–3 with twins from an Australian twin panel first surveyed in 1980–82 (N=5995 respondents). Data were analysed using logistic regression models, taking into account twin pair zygosity and the history of suicidality in the respondent's co-twin. Results. Lifetime prevalence of suicidal thoughts and attempts was remarkably constant across birth cohorts 1930–1964, and across gender. Major psychiatric correlates were history of major depression, panic disorder, social phobia in women, alcohol dependence and childhood conduct problems. Traumatic events involving assault (childhood sexual abuse, rape or physical assault) or status-loss (job loss, loss of property or home, divorce), and the personality trait neuroticism, were also significantly associated with suicide measures. Prevalence of serious suicide attempts varied as a function of religious affiliation. After controlling for these variables, however, history of suicide attempts or persistent thoughts in the respondent's co-twin remained a powerful predictor in MZ pairs (odds ratio=3·9), but was not consistently predictive in DZ pairs. Overall, genetic factors accounted for approximately 45% of the variance in suicidal thoughts and behaviour (95% confidence interval 33–51%). Conclusions. Risk of persistent suicidal thoughts and suicide attempts is determined by a complex interplay of psychiatric history, neuroticism, traumatic life experiences, genetic vulnerability specific for suicidal behaviour and sociocultural risk or protective factors.