Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Volterra Kernel Methods with Applications to the Visual System

Volterra analysis and its variants have long been prominent among methods for modeling multi-input non-linear systems. The product of Volterra analysis, the Volterra kernels, are particularly suited to quantifying intra- and inter-input interactions. They are also readily interpretable, which means that they can be related directly to physical behaviors, and more distantly, to the underlying processing mechanisms of the system being tested. However, accurate estimation of a sufficient set of classical kernels is often not possible for complex systems because the number of kernels that need to be determined, and hence experiment time, increases radically with system memory, response frequency bandwidth, and non-linear interaction order. Practical approaches to kernel estimation often involve forced reductions of the generality of the analysis that in turn compromise interpretability. Here we illustrate the effects on kernel interpretability of two common reductions, slow-stimulation and the use of binary inputs, using both numerical simulations and data from a Visual Evoked Potential experiment. We show how a non-standard version of binary analysis, involving a different coding of the inputs and the use of particular groupings of kernel slices, improves kernel interpretability. We bring together, in a comprehensive fashion, all of the mathematical considerations needed to apply and interpret the results of Volterra kernel analyses. The input-coding method we describe allows one to correctly quantify multi-input interactive effects that occur both within the separate input channels and across them.
Lazy Bayesian

The naive Bayesian classiier provides a simple and eeective approach to classiier learning, but its attribute independence assumption is often violated in the real world. A number of approaches have sought to alleviate this problem. A Bayesian tree learning algorithm builds a decision tree, and generates a local naive Bayesian classiier at each leaf. The tests leading to a leaf can alleviate attribute inter-dependencies for the local naive Bayesian classiier. However, Bayesian tree learning still suuers from the replication, fragmentation, and small disjunct problems of tree learning. While inferred Bayesian trees demonstrate low average prediction error rates, there is reason to believe that error rates will be higher for those leaves with few training examples. This paper proposes the application of lazy learning techniques to Bayesian tree induction and presents the resulting lazy Bayesian rule learning algorithm, called Lbr. For each test example, it builds a most appropriate rule with a local naive Bayesian classiier as its consequent. It is demonstrated that the computational requirements of Lbr are reasonable in a wide cross-selection of natural domains. Experiments with these domains show that, on average, this new algorithm obtains lower error rates signiicantly more often than the reverse in comparison to a naive Bayesian classiier, C4.5, a Bayesian tree learning algorithm, a constructive Bayesian classiier that eliminates attributes and constructs new attributes using Cartesian products of existing nominal attributes, and a lazy decision tree learning algorithm. It also out-performs, although the result is not statistically signiicant, a selective naive Bayesian classiier.
The Liberalisation of Foreign Ownership and Cross-border M&A in South East Asia since the 1997 Financial Crisis

Since 1997 there has been significant liberalisation of foreign ownership regulations in most of the South East Asian economies. This has been associated with some major increases in the level of cross-border Mergers & Aquisitions (M&A). However, the 1997-2001 surge in cross-border M&A activity has to be seen in the context not only of liberalisation, but also of the short-term availability of distressed assets, the lowering of production costs and the final phases of a global FDI boom which had been increasingly driven by M&A. Similarly, the sharp decline in South East Asian cross-border M&A since 2002 can be explained in terms of the acquisition of the most easily purchased attractive assets and the sharp decline in global M&A activity. However, it is argued that post-1997 liberalisation left in place significant barriers to increased foreign ownership and operation in all the South East Asian economies. In addition to continuing direct restrictions on foreign ownership, a wide range of other regulations inhibit cross-border M&A - notably those effecting bankruptcy, M&A procedures and financial reporting. Perhaps more significant are the limitations on foreign ownership and operation that result from ownership patterns, forms of corporate governance, established business practices and the operation of the bureaucratic, judicial and political systems.
Empirical relation between coupling and attackability in software systems:: a case study on DOS

Over the last decades, software quality attributes such as maintainability, reliability, and understandability have been widely studied. In contrast, less attention has been paid to the field of software security. Attackability is a concept proposed recently in the research literature t to measure the extent that a software system or service could be the target of successful attacks. Like most external attributes, attackability is to some extent disconnected from the internal of software products. To improve the quality of software products we need to be able to affect its internal features. So, for attackability measures to be useful for software products enhancement, we need to identify related internal software attributes. We study in this paper the empirical relationship between attackability as an external software quality attribute with coupling as an internal software attribute. Specifically, we use a case study based on denial of service (DOS) attacks conducted against a on line medical record keeping system. Through regression analysis, we establish that there is a strong correlation between attackability and coupling.
DEFECT LINES, DUALITIES AND GENERALISED ORBIFOLDS

Defects are a useful tool in the study of quantum field theories. This is illustrated in the example of two-dimensional conformal field theories. We describe how defect lines and their junction points appear in the description of symmetries and order-disorder dualities, as well as in the orbifold construction and a generalisation thereof that covers exceptional modular invariants.
Characterization of Alpha AXP performance using TP and SPEC workloads

The characteristics of several commercial and technical workloads on the DEC 7000 AXP system are compared using built-in hardware monitors. The data analyzed include total instructions, cycles, multiple-issued instructions, stall components, cache misses, and instruction types. The data indicates that the two classes of workloads have vastly different characteristics and impose different requirements on the system design. Compared to VAX, Alpha AXP takes advantage of lower cycles per instruction and cycle time to achieve a significant performance advantage. The cache and memory interconnect subsystems are expected to play a crucial role in the performance of future systems. A simple model for evaluating the effects of various design tradeoffs based on the data collected by using hardware monitors is proposed. <<ETX>>
Comparative assessment of two fuzzy logic based control approaches for a flywheel and electrical clutch assist mechanism in FES cycling

Functional electrical stimulation (FES) based cycling exercise for paraplegics, with the aid of a flywheel and electrical clutch mechanism, is introduced. Fuzzy logic controllers are used to control the stimulation intensity on the quadriceps muscle of both legs. The control of the flywheel assist mechanism is achieved using two different fuzzy logic based approaches. The first approach depends on the knee angular velocity of both legs of the trainee while the second approach uses the bicycle's crank cadence, with the angular velocity of the flywheel, to decide on the engagement/disengagement of the flywheel with the crank. A comparative assessment of the two approaches is carried out and the results are discussed. Results show that the second approach is promoting smoother and longer FES cycling exercise due to reduced stimulation intensity on the muscle, however, it requires a sensitive electrical clutch.
Genetic filtering and optimal sampling of Schistosoma mansoni populations

Allelic variation in 6 microsatellite markers was compared between frozen Schistosoma mansoni eggs and laboratory-passaged worms originating from the same 5 fecal samples obtained from Brazilian residents. Based on allelic richness values, the number of alleles detected per locus did not differ between egg and worm DNA templates. However, our ability to score loci differed between these DNA templates, with worms providing more scored loci per individual than eggs. Differences also existed between the worms and eggs in the identity of the specific alleles that were detected. Additionally, we observed a reduction in homozygous genotypes among laboratory-passaged worms relative to the eggs. Allelic diversity curves were calculated by genotyping all worms from a representative host sample to determine the relationship between the number of alleles detected at a locus and the number of worms genotyped. Curves for the 5 residents' worm infrapopulations for each of the loci were very similar. The equation y=19·55×ln(x)+9·992 explained the association between sampling effort (x) and number of alleles detected (y) with an R2 of 0·775. In conclusion, egg DNA templates and allelic diversity curves can benefit efforts to discern the sociological, ecological and evolutionary forces impacting the genetic diversity and disease epidemiology of human schistosomes.
Disruption of Short Term Recognition Memory for Tones: Streaming or Interference?

A sequence of auditory stimuli interpolated between the initial presentation of a tone and a comparison tone impairs recognition performance. Notably, the impairment is much less with interpolated speech than with tones. Six experiments converge on the conclusion that this pattern of impairment is due more to the organization of the interpolated sequence than to its similarity to the to-be-remembered standard. Factors that contribute to the coherence of the interpolated sequence into a stream distinct from the initial tone are primary determinants of the level of impairment. This is demonstrated by manipulating factors that contribute to the coherence of the interpolated sequence by the action of temporal, spatial, timbral, and tonal attributes. However, the relative immunity of recognition performance to the interpolation of unprocessed digit sequences is not explained wholly by such coherence.
Affective prediction in photographic images using probabilistic affective model

With increasing the importance of affective computing, it becomes necessary to retrieve and process images according to human affects or preference. However, judging such affective qualities of images is a highly subjective task. In spite of the lack of firm rules, certain features in images are believed to be more related than certain others. In this paper, we suggest predicting certain affective features include in an image using color composition that constitutes the scene. Using such a feature is inspired from Kobayashi's color scale that studies the relation between colors/color compositions and human's affects. Thus, we propose a Probabilistic Affective Model (PAM) to estimate the probabilities that an image is related to certain affective features. For this, we segment an image using mean-shift clustering algorithm, and extract more important regions, which are called seed regions, based on their properties. Thereafter, we find the dominant color compositions among those seed regions and their neighboring regions. Finally, from such color compositions, we infer the numerical ratings for some affective features. To assess the effectiveness of our PAM, we compared its results with 52 users' affective judgments. It was tested with online photo images, then the results show our PAM produced the recall of 85.22% and the precision of 78.16% on average. Potential applications include content-based image retrieval and design of web page interfaces.
Comparative coalition building and the revitalization of thelabor movement

This paper draws on material from Germany, Britain, and the United States to reflect on the contribution that coalition with other groups in civil society can make to the revitalization of the labor movement. It presents an analytical framework for the analysis of coalition-building that covers the functions and types of coalition and the factors that prompt unions to make use of this method. The paper ends by arguing that there are distinct national patterns of coalition-building that reflect enduring differences in union identity and the institutional context in which unions operate.
A software and hardware architecture for a modular, portable, extensible reliability availability and serviceability system.

This paper provides a very high level overview of a software and hardware architecture for a Reliability Availability and Serviceability system. One of the primary goals of this architecture is portability. The design of the architecture is intentionally modular to provide the extensibility necessary to allow the portions of the system that are not directly portable to be easily added or modified. This architecture is designed for use on systems ranging from commodity clusters to custom Massively Parallel Processing systems.
Vitamin D study in pregnant women and their babies

Background and objectives: Vitamin D deficiency is very common in pregnant women. Deficiencies have been prevalent even in studies where over 90% of the women took prenatal vitamins. The current guidelines for vitamin D intake during pregnancy of 200–400 IU has little scientific support and has been recently challenged. We conducted this study to determine the prevalence of vitamin D deficiency among pregnant women and to evaluate the effectiveness and level of weekly oral 50,000 IU of vitamin D supplementation for the mother and the newborn. Setting and design: Prospective study at Hamad Medical Corporation outpatient unit and delivery room. Patients and Methods: Ninety seven pregnant women were recruited in their first trimester between December 2007 and March 2010. Weekly oral vitamin D (50,000 IU) were prescribed after an initial testing for serum level of 25-hydroxyvitamin D, parathyroid hormone, calcium, phosphorus, total protein and albumin. Other multivitamins supplementations were allowed during pregnancy. The same tests were repeated at each trimester. Umbilical cords vitamin D levels were determined at birth. Results: Out of 97 patients, 8 patients dropped out from the study for several reasons, and 19 patients had pregnancy loss. Data were available for 97 women in the first trimester, 78 women in the second trimester and 61 women in the third trimester. The mean level of vitamin D level in the first trimester and prior to starting vitamin D supplementation was 17.15 ng/ml, 29.08 ng/ml in the second trimester, 27.3 ng/ml in third trimester and 22.36 ng/ml in newborns. There were no toxic levels of vitamin D in any of the women at the second or third trimesters or in the newborns. The mean levels of vitamin D in the second and third trimester were not significantly different in those women who were taking multivitamin supplementation and those who were not. Conclusion: Weekly doses of 50,000 vitamin D during pregnancy maintains acceptable vitamin D level during pregnancy and the newborn's vitamin D level correlates with the mother's levels.
The Announcement Effect of Real Estate Joint Ventures on Returns to Stockholders: An Empirical Investigation

This study compares the market reaction to the announcement of real estate joint venture on returns to stockholders of real estate and non-real estate firms. The main objectives were to examine the presence of a synergy effect associated with real estate joint ventures and to establish whether real estate firms earn higher excess returns due to their unique institutional characteristics (market locality, and/or market segmentation). Two hypotheses were examined: the synergy hypothesis and the informational asymmetries hypothesis. Real estate firms earn higher excess returns when they participate with non-real estate firms than when they participate with real estate firms. The opposite is true for non-real estate firms. Both real estate participants and non-real estate participants earn positive and statistically significant excess returns with no significant difference between the two groups. The result of this study is consistent with the synergy effect as a source of gain from the joint venture. It is also consistent with the notion that real estate firms have institutional characteristics in the form of better information about local real estate markets and/or superior management and technical expertise that allow real estate firms to achieve larger gains from joint ventures at the expense of non-real estate firms.
Discriminative uncorrelated neighborhood preserving projection for facial expression recognition

In this paper, we propose a novel supervised algorithm named discriminative uncorrelated neighborhood preserving projections (DUNPP), which is a variant of Neighborhood preserving projections (NPP). Combining with class relations between data samples in each local area, the DUNPP method can find a discriminative subspace where the within-class structure is preserved, while the margin between points from different classes is maximized. Also, a simple uncorrelated constraint is added to the objective function of DUNPP to remove redundancies contain in original data and ensure the independence of features, so that the recognition performance can be further enhanced. Experimental results on a widely used facial expression database verified the effectiveness and robustness of our proposed method.
Unstructured Text Analytics to Support New Product Development Decisions

OVERVIEW: This article describes how to use unstructured text analytics to support critical product development decisions. It clarifies the difference between structured and unstructured data and proposes an analytical process for using big data and natural language processing tools for unstructured text analytics to support managerial decision-making. The usefulness of unstructured data for product development decisions is demonstrated in real cases. In particular, we illustrate the use of text analytics to develop services, to find new customers, and to assess new product viability. Results and outcomes are presented, and practical considerations for selecting and adopting text analytic capabilities are examined.
Frequent loss of expression without sequence mutations of the DCC gene in primary gastric cancer

Loss of heterozygosity (LOH) on chromosome 18q21 is frequently found in various human cancers, suggesting the presence of tumour suppressor gene(s) in this chromosomal region. DCC is the most likely target of LOH because loss or reduction of DCC expression has been found in many types of cancers. However, few reports have focused on sequence mutations of this gene. We investigated sequence mutations and expression of DCC in primary gastric cancers. We studied mutations in 25 of the 29 DCC exons by PCR-SSCP in 17 primary gastric cancers exhibiting LOH on 18q21. No mutations of DCC were found in any of the tumours, although 78% (47/60) of the primary tumours showed apparent loss or reduction of DCC expression by immunohistochemistry. Analysis of methylation status of DCC revealed that methylation frequently occurred in both primary tumours (75%; 45/60) and corresponding non-cancerous gastric mucosae (72%; 43/60). Methylated status of DCC was significantly correlated with the loss of DCC expression in primary tumours (P < 0.01). These results indicate that DCC is frequently silenced, probably by epigenetic mechanisms instead of sequence mutations in gastric cancer. http://www.bjcancer. com © 2001 Cancer Research Campaign
The Self-Dual String and Anomalies in the M5-brane

We study the anomalies of a charge Q2 self-dual string solution in the Coulomb branch of Q5 M5-branes. Cancellation of these anomalies allows us to determine the anomaly of the zero-modes on the self-dual string and their scaling with Q2 and Q5. The dimensional reduction of the five-brane anomalous couplings then lead to certain anomalous couplings for D-branes.
An unusual presentation of an incisional ventral wall hernia: A case report

Introduction: Abdominal incisional herniae are well known complications after abdominal surgery and many methods for repair of the hernial defect have been tried and developed. These include open repair with or without mesh and laparoscopic repair. Case Report: We present an extremely unusual case where the hernia sac had dissected a plane between anterior sheath and the rectus muscles. Surgical development of this plane is associated with great risk of damage to nerves and vessels therefore not commonly used in hernia repairs. Conclusion: In this highly unusual case where traditional mesh placement was of little value, we chose a unique and as yet undescribed method of retro-anterior sheath mesh placement with good results at third month.
The Role of Shared It-business Understanding

87 During the last two decades the levels of business spending on IT have surged. This growth in IT investments has catalyzed significant interest as to whether, and if so how, the anticipated economic benefits of investments in IT are being realized [4, 5, 7]. However, the disillusionment with IT following the failure of many dot-com ventures and the subsequent economic downturn has led many to question the strategic value of IT. In May 2003, for example, Harvard Business Review published an article by Carr [3] dramatically titled " IT Doesn't Matter, " engendering a huge controversy about the strategic value of IT. Carr's core premise is that IT is a commodity factor of production and therefore provides distinction to none. This article examines the question of IT business value and IT competitive advantage from the perspective of the resource-based view (RBV) and reports the results of an empirical study that sheds light on the conditions that lead some firms to be more successful than others in using commonly accessible IT. We find that Shared IT-Business Understanding— the level of shared domain knowledge and common understanding between the IT and the line managers regarding how IT can be used to improve the performance of a specific Studying why some firms derive more competitive advantage and value than others using IT resources.
Harnessing the GPU for Real-Time Haptic Tissue Simulation

Virtual surgery simulators are emerging as a training method for medical specialists and are expected to provide a virtual environment that is realistic and responsive enough to be able to physically simulate a wide variety of medical scenarios. Haptic interaction with the environment requires an underlying physical model that is dynamic, deformable, and computable in real-time at very high frame rates. By harnessing the GPU, we are able to simulate an environment with soft volumetric tissue that supports real-time deformation and two-way haptic interaction. In particular, we present a parallel algorithm that uses a volumetric mass-spring model to simulate this environment, implemented using NVIDIA CUDA. Our algorithm is implemented and used as an integral part of Virtual Competence Training Area (VICTAR), an extendable virtual surgery simulation software framework by Vrest Medical. We show that our method is capable of simulating a model with over 100 K masses at 1000 Hz on NVIDIA Tesla C2050. We also discuss the scalability and potential future applications of the algorithm.