Miracle-dz/UniFAR-FTUs huggingface dataset:
Sequential Innovation and Optimal Patent Design

We study optimal patent design in a setting with sequential innovation. Firms innovate by undertaking "research" activities to generate new ideas and by undertaking "development" activities to transform these ideas into viable products. Both innovation incentives and the welfare costs of patent monopoly are multidimensional. We characterize optimal patent policy, and in particular, the tradeoff between patent length and patent breadth in this setting. The optimal size of the patent reward is smaller for patents associated with a higher deadweight loss. For a given reward size, a better patent that generates higher social surplus is shorter but broader. The optimal patent length may be finite or infinite.
MAP Estimation of Continuous Density HMM : Theory and Applications

We discuss maximum a posteriori estimation of continuous density hidden Markov models (CDHMM). The classical MLE reestimation algorithms, namely the forward-backward algorithm and the segmental k-means algorithm, are expanded and reestimation formulas are given for HMM with Gaussian mixture observation densities. Because of its adaptive nature, Bayesian learning serves as a unified approach for the following four speech recognition applications, namely parameter smoothing, speaker adaptation, speaker group modeling and corrective training. New experimental results on all four applications are provided to show the effectiveness of the MAP estimation approach.
Retinal cell addition and rod production depend on early stages of ocular melanin synthesis

Retinal mitosis is regulated by dopa, a melanin precursor present in the developing retinal pigment epithelium. Its absence results in retinal deficits including a failure of ≈30% of the rod population to develop. Here, 3H‐thymidine labelling is used to analyse patterns of cell addition spanning the main period of retinal development in rat litters containing both pigmented and albino phenotypes. Many more thymidine‐labelled cells are found in each cellular layer at maturity in albinos than in their pigmented littermates. Normal spatial patterns of photoreceptor addition are seen in albinos during cone production and for most of the subsequent period of rod addition. However, abnormal spatial patterns of cell addition occur across the retinal when rod production peaks. A delay in the centre to periphery gradient of cell addition is apparent in both nuclear layers. These data are related to deficits in the mature architecture of the albino retina. The results are consistent with there being significant cell cycle and/or exit point irregularities in hypopigmented retinae. It is probable that reduced dopa levels in albinos result in the cell cycle rate not slowing appropriately with development, which may lead to cells missing their exit points. This produces abnormal patterns of cell addition at key stages and delays in the gradient of retinal maturation along with a large cell loss at critical stages of rod production. J. Comp. Neurol. 420:437–444, 2000. © 2000 Wiley‐Liss, Inc.
Efficient smart sampling based full-chip leakage analysis for intra-die variation considering state dependence

Leakage power minimization is critical to semiconductor design in nanoscale CMOS. On the other hand increasing variability with scaling adds complexity to the leakage analysis problem. In this work we seek to achieve tractability in Monte Carlo-based statistical leakage analysis. A novel approach for fast and accurate statistical leakage analysis considering inter-die and intra-die components is proposed. We show that the optimal way to select samples, to capture intra-die variation accurately, is according to the probability distribution function of total process variation. Intelligent selection of samples is performed using a Quasi Monte Carlo technique. Results are presented for benchmarks with sizes varying from approximately 5,000 to 200,000 gates. The largest benchmark with 198461 gates is evaluated in 3 minutes with the proposed approach compared to 23 hours for random sampling with comparable accuracy. Compared to a conventional analytical approach using Wilkinson's approximation, the proposed technique offers superior accuracy while maintaining efficiency. State dependence and multiple sources of variation are considered and the approach is scalable with number of process parameter variables for standard cell characterization cost. We also show reduction in sample size to meet target accuracy for computing leakage distribution due to the inter-die component only when compared to random selection of samples.
Investigating the impacts of epilepsy on EEG-based person identification systems

Person identification using electroencephalogram (EEG) as biometric has been widely used since it is capable of achieving high identification rate. Epilepsy is one of the brain disorders that involves in the EEG signal and hence it may have impact on EEG-based person identification systems. However, this issue has not been investigated. In this paper, we perform person identification on two groups of subjects, normal and epileptic to investigate the impact of epilepsy on the identification rate. Autoregressive model (AR) and Approximate entropy (ApEn) are employed to extract features from these two groups. Experimental results show that epilepsy actually have impacts depending on feature extraction method used in the system.
Transient lysosomal activation is essential for p75 nerve growth factor receptor expression in myelinated Schwann cells during Wallerian degeneration

Myelinated Schwann cells in the peripheral nervous system express the p75 nerve growth factor receptor (p75NGFR) as a consequence of Schwann cell dedifferentiation during Wallerian degeneration. p75NGFR has been implicated in the remyelination of regenerating nerves. Although many studies have shown various mechanisms underlying Schwann cell dedifferentiation, the molecular mechanism contributing to the re-expression of p75NGFR in differentiated Schwann cells is largely unknown. In the present study, we found that lysosomes were transiently activated in Schwann cells after nerve injury and that the inhibition of lysosomal activation by chloroquine or lysosomal acidification inhibitors prevented p75NGFR expression at the mRNA transcriptional level in an ex vivo Wallerian degeneration model. Lysosomal acidification inhibitors suppressed demyelination, but not axonal degeneration, thereby suggesting that demyelination mediated by lysosomes may be an important signal for inducing p75NGFR expression. Tumor necrosis factor-α (TNF-α) has been suggested to be involved in regulating p75NGFR expression in Schwann cells. In this study, we found that removing TNF-α in vivo did not significantly suppress the induction of both lysosomes and p75NGFR. Thus, these findings suggest that lysosomal activation is tightly correlated with the induction of p75NGFR in demyelinating Schwann cells during Wallerian degeneration.
SBQL Object Views-Unlimited Mapping and Updatability

The paper presents updatable object views defined in SBQL. They are unlimited in two important dimensions. First, because they are defined in a query/programming language with the full algorithmic power, they allow for any mapping of stored data onto virtual one. Second, the mechanism does not restrict updates of virtual data. A view definer can explicitly determine view updates intention through procedures (being a part of a view definition) which dynamically overload generic view updating operations. Again, he/she has the full algorithmic power at hand. We follow the Stack-Based Architecture, a theory of object-oriented query languages based on the classical concepts of programming languages, such as environment stack and namingscoping-binding ideas. The described mechanism has been successfully implemented an tested in ODRA, a prototype object-oriented DBMS.
SadC Reciprocally Influences Biofilm Formation and Swarming Motility via Modulation of Exopolysaccharide Production and Flagellar Function

ABSTRACT Pseudomonas aeruginosa has served as an important organism in the study of biofilm formation; however, we still lack an understanding of the mechanisms by which this microbe transitions to a surface lifestyle. A recent study of the early stages of biofilm formation implicated the control of flagellar reversals and production of an exopolysaccharide (EPS) as factors in the establishment of a stable association with the substratum and swarming motility. Here we present evidence that SadC (PA4332), an inner membrane-localized diguanylate cyclase, plays a role in controlling these cellular functions. Deletion of the sadC gene results in a strain that is defective in biofilm formation and a hyperswarmer, while multicopy expression of this gene promotes sessility. A ΔsadC mutant was additionally found to be deficient in EPS production and display altered reversal behavior while swimming in high-viscosity medium, two behaviors proposed to influence biofilm formation and swarming motility. Epistasis analysis suggests that the sadC gene is part of a genetic pathway that allows for the concomitant regulation of these aspects of P. aeruginosa surface behavior. We propose that SadC and the phosphodiesterase BifA (S. L. Kuchma et al., J. Bacteriol. 189:8165-8178, 2007), via modulating levels of the signaling molecule cyclic-di-GMP, coregulate swarming motility and biofilm formation as P. aeruginosa transitions from a planktonic to a surface-associated lifestyle.
Antitumour activity of Terminalia arjuna leaf against Ehrlich ascites carcinoma in mice

Terminalia arjuna Roxb. (Combretaceae), commonly known as ‘Arjuna’, is a large tree occurring throughout the Indian peninsula. This study was undertaken to evaluate the methanol extract of T. arjuna leaf (META) for antitumour activity against Ehrlich ascites carcinoma (EAC) in Swiss albino mice. Twenty-four hours after intraperitonial inoculation of tumour (EAC) cells in mice, META was administered at 100 and 200 mg kg−1 body weights for 9 consecutive days. On day 10, half of the mice were sacrificed and the rest kept alive for an assessment of the increase in life span. The antitumour effect of META was assessed by evaluating tumour volume, tumour weight, viable and non-viable tumour cell counts, median survival time and increase in life span of EAC-bearing hosts. Haematological profiles were estimated. META showed a significant (p<0.001) decrease in tumour volume, tumour weight and viable cell count, and also increased the life span of EAC-bearing mice. Haematological profiles were significantly (p<0.001) restored to normal levels in META-treated mice compared to the EAC control. Therefore, from this study, it can be concluded that T. arjuna leaf exhibited remarkable antitumour activity against EAC in Swiss mice.
Schema Transformation & Optimization

An application structure is best modeled first as a conceptual schema, and then mapped to an internal schema for the target DBMS. Different but equivalent conceptual schemas often map to different internal schemas, so performance may be improved by applying conceptual transformations prior to the standard mapping. This paper discusses recent advances in the theory of schema transformation and optimization within the framework of ORM (Object-Role Modeling). New aspects include object relativity, complex types, a high level transformation language and update distributivity.
Ring a ring o'roses, a patient with Kaposi's? Pazopanib, pazopanib, it might go away. Mediterranean (classic) Kaposi sarcoma responds to the tyrosine kinase inhibitor pazopanib after multiple lines of standard therapy

B. H. L. Harris, J. L. Walsh, R. Neciunaite, P. Manders, A. Cooper and P. De Souza Department of Medical Oncology, Liverpool Hospital, Sydney, Australia; St. Anne’s College, Oxford University, Oxford, UK; St. George’s Hospital, London, UK; Cardiff University School of Medicine, Cardiff, UK; Western Sydney University School of Medicine, Sydney, Australia; and Ingham Institute, Liverpool, Sydney, Australia
Species comparison of pharmacokinetics and metabolism of diltiazem in humans, dogs, rabbits, and rats.

Diltiazem (DTZ) is a calcium antagonist widely used in the treatment of angina and related heart diseases. It is extensively metabolized into a host of metabolites, some of which have potent pharmacological activities. In this study, the pharmacokinetics and metabolism of DTZ was investigated in humans, dogs, rabbits, and rats after each species (n = 4 or 5) was given a single oral dose of DTZ. After the drug administration, blood and urine samples were collected for 12 and 48 hrs, respectively. DTZ and six of its metabolites were quantitated in our laboratory by HPLC. The results indicated that, in humans, the major metabolites in plasma were N-monodesmethyl diltiazem (MA), deacetyl diltiazem (M1), and deacetyl N-monodesmethyl diltiazem (M2). These metabolites were also detected in the plasma of dogs, rabbits, and rats. However, there were quantitative differences. For example, in the humans and dogs, MA was the most abundant metabolite in plasma, while M1 and M2 were most prominent in the rabbits and rats, respectively, and M2 was a relatively minor metabolite in dog plasma. Less than 5% of the dose was recovered as unchanged DTZ in the urine of all the tested species. The most abundant metabolites in urine appeared to be MA and deacetyl N,O-didesmethyl diltiazem, although there were considerable inter- and intra-species variations. Two additional metabolites were detected in the urine of the humans, dogs, and rabbits, but not in the rats. They were tentatively identified as O-desmethyl diltiazem and N-O-didesmethyl diltiazem, using electron impact and ammonia chemical ionization mass spectrometry. (ABSTRACT TRUNCATED AT 250 WORDS)
First Class Call Stacks: Exploring Head Reduction

Weak-head normalization is inconsistent with functional extensionality in the call-by-name $\lambda$-calculus. We explore this problem from a new angle via the conflict between extensionality and effects. Leveraging ideas from work on the $\lambda$-calculus with control, we derive and justify alternative operational semantics and a sequence of abstract machines for performing head reduction. Head reduction avoids the problems with weak-head reduction and extensionality, while our operational semantics and associated abstract machines show us how to retain weak-head reduction's ease of implementation.
Incremental Object Perception in an Attention-Driven Cognitive Architecture

With few exceptions, architectural approaches to modeling cognition have historically emphasized what happens in the mind following the transduction of environmental signals into percepts. To our knowledge, none of these architectures implements a sophisticated, general theory of human attention. In this paper we summarize progress to date on a new cognitive architecture called ARCADIA that gives a central role to attention in both perception and cognition. First, we give an overview of the architecture, comparing it to other approaches when appropriate. Second, we present a model of incremental object construction and property binding in ARCADIA using the well known change blindness phenomena to illustrate the time course of object perception and its dependence on attention. Finally, we discuss near-term challenges and future plans.
Smooth Tubercle Bacilli: Neglected Opportunistic Tropical Pathogens

Smooth tubercle bacilli (STB) including “Mycobacterium canettii” are members of the Mycobacterium tuberculosis complex (MTBC), which cause non-contagious tuberculosis in human. This group comprises <100 isolates characterized by smooth colonies and cordless organisms. Most STB isolates have been obtained from patients exposed to the Republic of Djibouti but seven isolates, including the three seminal ones obtained by Georges Canetti between 1968 and 1970, were recovered from patients in France, Madagascar, Sub-Sahara East Africa, and French Polynesia. STB form a genetically heterogeneous group of MTBC organisms with large 4.48 ± 0.05 Mb genomes, which may link Mycobacterium kansasii to MTBC organisms. Lack of inter-human transmission suggested a yet unknown environmental reservoir. Clinical data indicate a respiratory tract route of contamination and the digestive tract as an alternative route of contamination. Further epidemiological and clinical studies are warranted to elucidate areas of uncertainty regarding these unusual mycobacteria and the tuberculosis they cause.
Function-based object model towards website adaptation

Content understanding is a crucial issue for website adaptation. In this paper we present a Function-based Object Model (FOM) that attempts to understand authors’ intention by identifying Object function instead of semantic understanding. Every Object in a website serves for certain functions (Basic and Specific Function) which reflect authors’ intention towards the purpose of an Object. Based on this consideration we have proposed the FOM model for website understanding. FOM includes two complementary parts: Basic FOM based on the basic functional properties of Object and Specific FOM based on the category of Object. An automatic approach to detect the functional properties and category of Object is presented for FOM generation. Two level adaptation rules (general rules and specific rules) based on FOM are combined for practical adaptation. A system for web content adaptation over Wireless Application Protocol (WAP) is developed as an application example of the proposed model. Experiments have shown satisfactory results and extensibility.
Add Students With and Without Dyslexia Differ in Sensitivity to Rhyme and Alliteration

Children with attention deficit disorder (ADD) and dyslexia (n = 82) made significantly more errors than normally reading children with ADD (n = 83) on a simple auditory test of phonological sensitivity to rhyme and alliteration (Bradley, 1984). A subgroup of children with dyslexia who were sensitive to rhyme and alliteration had higher scores on the Wechsler Intelligence Scale for Children-Revised (WISC-R) Spatial factor than a dyslexic subgroup who were phonologically insensitive. In multiple regression analyses, age-corrected phonological sensitivity scores contributed significantly to the prediction of both reading and spelling Wide Range Achievement Test (WRAT) scores, this beyond the contribution of WISC-R variables. Of interest for dyslexia subtyping theories, Spatial factor scores had a subtractive effect in these regression analyses.
8GSps 6bit DAC in 0.18um SiGe technology

This paper describes the circuit design and measured performance of a 6-bit 8-GS/s current-steering DAC. A CML interface supporting the maximum conversion rate of 8Gbps is integrated in the chip. A PRBS-7 generator is built in the chip for synchronization as well as for data descrambling. In order to realize good linearity performance, a 2-2-2 segmental architecture is proposed for optimizing the performance. Measured DNL and INL are within +0.04/-0.12 LSB and +0.11/-0.11 LSB respectively. SFDR is above 37dBc over the Nyquist bandwidth at the sampling rate of 8 GS/s. The chip measures 1420 ×1405 um2.
Towards a theory of practice in metaheuristics design: A machine learning perspective

A number of methodological papers published during the last years testify that a need for a thorough revision of the research methodology is felt by the operations research community – see, for example, [Barr et al., J. Heuristics 1 (1995) 9–32; Eiben and Jelasity, Proceedings of the 2002 Congress on Evolutionary Computation (CEC'2002) 582–587; Hooker, J. Heuristics 1 (1995) 33–42; Rardin and Uzsoy, J. Heuristics 7 (2001) 261–304]. In particular, the performance evaluation of nondeterministic methods, including widely studied metaheuristics such as evolutionary computation and ant colony optimization, requires the definition of new experimental protocols. A careful and thorough analysis of the problem of evaluating metaheuristics reveals strong similarities between this problem and the problem of evaluating learning methods in the machine learning field. In this paper, we show that several conceptual tools commonly used in machine learning – such as, for example, the probabilistic notion of class of instances and the separation between the training and the testing datasets – fit naturally in the context of metaheuristics evaluation. Accordingly, we propose and discuss some principles inspired by the experimental practice in machine learning for guiding the performance evaluation of optimization algorithms. Among these principles, a clear separation between the instances that are used for tuning algorithms and those that are used in the actual evaluation is particularly important for a proper assessment.
Understanding Software Development Processes, Organizations, and Technologies

Our primary goal is to understand what people do when they develop software and how long it takes them to do it. To get a proper perspective on software development processes we must study them in their context — that is, in their organizational and technological context. An extremely important means of gaining the needed understanding and perspective is to measure what goes on. Time and motion studies constitute a proven approach to understanding and improving any engineering processes. We believe software processes are no different in this respect; however, the fact that software development yields a collaborative intellectual, as opposed to physical, output calls for careful and creative measurement techniques. In attempting to answer the question "what do people do in software development? " we have experimented with two novel forms of data collection in the software development field: time diaries and direct observation. We found both methods to be feasible and to yield useful information about time utilization. In effect, we have quantified the effect of these social processes using the observational data. Among the insights gained from our time diary experiment are 1) developers switch between developments to minimize blocking and maximize overall throughput, and 2) there is a high degree of dynamic reassignment in response to changing project and organizational priorities. Among the insights gained from our direct observation experiment are 1) time diaries are a valid and accurate instrument with respect to their level of resolution, 2) unplanned interruptions constitute a significant time factor, and 3) the amount and kinds of communication are significant time and social factors.
The Voxel-Sweep: A Boundary-based Algorithm for Object Segmentation and Connected-Components Detection

A new approach to the problem of object segmentation and isosurface detection is introduced. Drawing on the fundamental marching cubes algorithm of Lorensen and Cline, it operates with one space sweep through the voxels (hence it is called the voxel-sweep). It detects all isosurfaces and partitions the objects into connected components on the basis of the continuity of the surfaces. The surface of each connected component is obtained as an oriented triangular mesh, and is thus amenable as input to mesh-processing programs and hardware. Each separate component is automatically associated with its topological holes. These properties enable accurate volume and surface-area estimation of each component, as well as noise reduction (by eliminating ismalli components). The runtime of the voxel-sweep is just a negligible increase over the runtime of the marching cubes algorithm. Another option of the voxel-sweep is to visualize the resulting surfaces at the same time as they are being formed. Ideally, this option should enable realtime modication of the iso-values dening the surfaces.