Miracle-dz/UniFAR-FTUs huggingface dataset:
Explanation of Hysteresis Curve of a Flux- dependent Memcapacitor (Memory-capacitor) Using Taylor Series and Parametric Functions

Memcapacitor is a two-port circuit element with a memory. When excited by AC current or voltage, it has a zero-crossing charge-voltage hysteresis curve. The memcapacitor hysteresis curve should be taught to engineering students or engineers, who want to work in this area. In this work, an easily-comprehensible explanation of hysteresis curve of flux-dependent memcapacitor is given using Taylor series and parametric functions. Keywords—Memcapacitor, Memcapacitive systems, Hysteresis Curve, Engineering Education.
Optimal Investment Under Transaction Costs: A Threshold Rebalanced Portfolio Approach

We study how to invest optimally in a financial market having a finite number of assets from a signal processing perspective. Specifically, we investigate how an investor should distribute capital over these assets and when he/she should reallocate the distribution of the funds over these assets to maximize the expected cumulative wealth over any investment period. In particular, we introduce a portfolio selection algorithm that maximizes the expected cumulative wealth in i.i. d. two-asset discrete-time markets where the market levies proportional transaction costs in buying and selling stocks. We achieve this using “threshold rebalanced portfolios”, where trading occurs only if the portfolio breaches certain thresholds. Under the assumption that the relative price sequences have log-normal distribution from the Black-Scholes model, we evaluate the expected wealth under proportional transaction costs and find the threshold rebalanced portfolio that achieves the maximal expected cumulative wealth over any investment period. Our derivations can be readily extended to markets having more than two stocks, where these extensions are provided in the paper. As predicted from our derivations, we significantly improve the achieved wealth with respect to the portfolio selection algorithms from the literature on historical data sets under both mild and heavy transaction costs.
Symmetry in Software Synthesis

With the surge of multi- and many-core systems, much research has focused on algorithms for mapping and scheduling on these complex platforms. Large classes of these algorithms face scalability problems. This is why diverse methods are commonly used for reducing the search space. While most such approaches leverage the inherent symmetry of architectures and applications, they do it in a problem-specific and intuitive way. However, intuitive approaches become impractical with growing hardware complexity, like Network-on-Chip interconnect or heterogeneous cores. In this article, we present a formal framework that can determine the inherent local and global symmetry of architectures and applications algorithmically and leverage these for problems in software synthesis. Our approach is based on the mathematical theory of groups and a generalization called inverse semigroups. We evaluate our approach in two state-of-the-art mapping frameworks. Even for the platforms with a handful of cores of today and moderate-sized benchmarks, our approach consistently yields reductions of the overall execution time of algorithms. We obtain a speedup of more than 10 × for one use-case and saved 10% of time in another.
Sparse block circulant matrices for compressed sensing

An undetermined measurement matrix can capture sparse signals losslessly if the matrix satisfies the restricted isometry property (RIP) in compressed sensing (CS) framework. However, existing measurement matrices suffer from high computational burden because of their completely unstructured nature. In this study, the authors propose to construct a novel measurement matrix with a specific structure, called sparse block circulant matrix (SBCM), to reduce the computational burden. The RIP of the proposed SBCM is also guaranteed with overwhelming probability. The simulation results validate that SBCM reduces the computational burden significantly whereas keeps similar signal recovery accuracy as Gaussian random matrices.
Towards adaptive policy-based management

The use of learning, in particular reinforcement learning, has been explored in the context of policy-driven autonomic management as a means of aiding decision making. In this context, the autonomic manager “learns” a model about what actions to take, for example, in certain situations. However, when the set of policies changes, the model is typically discarded or, if used, may yield misleading information. In contrast, this paper presents an approach for “re-using” past knowledge - by transforming a model learned from the use of one set of active policies to a new model when those policies change. This means that some of the “learned” knowledge can be utilized within the new environment. This is possible because our approach to modeling learning and adaptation is dependent only on the structure of the policies. Consequently, changes to policies can be mapped onto transformations specific to the model derived from the use of those policies. In this paper, we describe the model construction and policy modifications and elaborate, with a detailed case study, on how such changes could alter the currently learned model. Our analysis of the different kinds of policy modifications also suggest that, in most cases, most of the learned model can still be reused. This can significantly accelerate the learning process, essentially improving the overall quality of service, as the results presented in this paper demonstrate.
Sildenafil and cardiomyocyte-specific cGMP signaling prevent cardiomyopathic changes associated with dystrophin deficiency

We recently demonstrated early metabolic alterations in the dystrophin-deficient mdx heart that precede overt cardiomyopathy and may represent an early “subclinical” signature of a defective nitric oxide (NO)/cGMP pathway. In this study, we used genetic and pharmacological approaches to test the hypothesis that enhancing cGMP, downstream of NO formation, improves the contractile function, energy metabolism, and sarcolemmal integrity of the mdx heart. We first generated mdx mice overexpressing, in a cardiomyocyte-specific manner, guanylyl cyclase (GC) (mdx/GC+/0). When perfused ex vivo in the working mode, 12- and 20-week-old hearts maintained their contractile performance, as opposed to the severe deterioration observed in age-matched mdx hearts, which also displayed two to three times more lactate dehydrogenase release than mdx/GC+/0. At the metabolic level, mdx/GC+/0 displayed a pattern of substrate selection for energy production that was similar to that of their mdx counterparts, but levels of citric acid cycle intermediates were significantly higher (36 ± 8%), suggesting improved mitochondrial function. Finally, the ability of dystrophin-deficient hearts to resist sarcolemmal damage induced in vivo by increasing the cardiac workload acutely with isoproterenol was enhanced by the presence of the transgene and even more so by inhibiting cGMP breakdown using the phosphodiesterase inhibitor sildenafil (44.4 ± 1.0% reduction in cardiomyocyte damage). Overall, these findings demonstrate that enhancing cGMP signaling, specifically downstream and independent of NO formation, in the dystrophin-deficient heart improves contractile performance, myocardial metabolic status, and sarcolemmal integrity and thus constitutes a potential clinical avenue for the treatment of the dystrophin-related cardiomyopathies.
Bridging the gaps : Special commentary The caring , sharing rat ?

http://dx.doi. org/10.1016/j.pain. 2014.03. 026 0304-3959/ 2014 Published by Elsevier B.V. on behalf of International Association for the Study of Pain. q DOI of original article: http://dx.doi. org/10.1016/j.pain. 2014.03. 019 ‘‘To endow animals with human emotions has long been a scientific taboo. But if we do not, we risk missing something fundamental, about both animals and us. ’’ [Frans de Waal [3]]
Clinical features of ANCA‐positive systemic lupus erythematosus: report of two cases

The real role of anti-neutrophil cytoplasmic antibodies (ANCA) in systemic lupus erythematosus (SLE) patients is not well defined (1–3); recently in our centre we observed two SLE cases in which ANCA positivity was related to the occurrence of typical vasculitic findings. The first patient, a 47-year-old woman, was diagnosed as SLE in June 2002 on the basis of photosensitivity, oral ulcers, alopecia, symmetrical polyarthritis, leucopaenia (white blood count, WBC, 3.3610/mmc), and a positive anti-nuclear antibody (ANA) test (1/640 with a homogeneous pattern on Hep2 cells) (4); antiextractable nuclear antigen (ENA) antibodies were positive with ribonucleoprotein (RNP) specificity, on enzyme-linked immunosorbent assay (ELISA). Lowdose prednisone and hydroxychloroquine were started with clinical benefit. In September 2002, due to the onset of occipital pulsating headache associated with fever (Tmax 38 C̊), the patient was hospitalized in a neurological department. Brain magnetic resonance imaging (MRI) detected diffuse microangiopathic white matter lesions and left acute mastoiditis (Figure 1), while neuropsychological tests showed severe impairment of long-term memory (LTM). In October 2002 she was transferred to our Unit, where infectious processes were excluded and ANCA positivity with cytoplasmic pattern on IFI (1/ 40) and anti-PR3 specificity on ELISA were found. Subsequently she was administered six monthly courses of 750 mg intravenous (i.v.) cyclophosphamide (CTX) and low-dose aspirin; prednisone dosage was first increased to 25 mg/day and then tapered; azathioprine (100 mg/day) was started after CTX withdrawal. The treatment led to SLE control, together with clinical improvement in mastoiditis, amelioration of LTM and ANCA negativity. Patient 2 was a 76-year-old woman with a history of previous pleuritis, admitted to our Unit in October 2003 due to the onset of symmetrical hand arthritis, fever, and malar rash. After exclusion of infectious processes, because of a positive ANA test (1/640 with homogeneous pattern on Hep2 cells) and direct Coomb’s test positivity, a diagnosis of SLE was made. ANCA were also positive, with a perinuclear pattern on IFI (1/40) and anti-myeloperoxidase (MPO) specificity on ELISA. Thereafter, due to occipital headache onset, we performed a computed tomography (CT) brain scan, showing bilateral mastoiditis, microangiopathic lesions, and diffuse cerebrovascular disease of the central lobar white matter (Figure 2); neuropsychological tests showed impairment of LTM. Because of microhaematuria and urinary casts identification on urine-microscopic analysis, a kidney biopsy was performed; the histology showed lesions extending from diffuse hypercellularity to crescentic glomerulonephritis with segmental necrotizing lesions. A small proportion of glomeruli (30%) showed extracapillary proliferation and periglomerular mononuclear infiltrate and a few
Comment on Chambliss's "The Mundanity of Excellence"

Chambliss's (1988) article is strongly oriented to the task of reconceptualizing talent in ways that make it accessible to study. He has attempted to shift the conceptual underpinnings of talent from the realm of internal "states and traits" to the realm of external practices and behaviors, and he has done so in ways that reveal talent to be a "useless concept. " This is certainly an important achievement, and it is on these grounds that Chambliss's article has justifiably been praised (see Kaplan 1989). Yet, to my mind, Chambliss's preoccupation with undermining the notion of talent deflects attention from the more general explanation of stratification which he cites as one of the major purposes of his article. My comment, then, consists of the following: excellence, not merely talent, is a meaningless concept; Chambliss acknowledges this point but fails to develop its theoretical implications for a general theory of stratification. As a result, we learn more about swimming than about stratification. In other words, Chambliss's piece contains an unresolved tension between his discussion of the mundane bases of "how to" succeed in
Implementation of a typed feature structure grammar processing system with numerical heuristics

Abstract The present paper describes theoretical issues underlying an implementation of a typed feature structure grammar processing system with a simple numerical processing component The paper takes its point of departure in an existing system for representation and processing of typed feature-based grammars (ConTroll). The author has developed a similar system with two extensions: the introduction of parametrical types and a processing component based on numerical heuristics.
EBV-LMP 1-targeted DNAzyme induces DNA damage and causes cell cycle arrest in LMP 1-positive nasopharyngeal carcinoma cells

This study aimed to determine the molecular mechanisms underlying the effect of the LMP1-targeted DNAzyme 1 (DZ1) on cell cycle progression in nasopharyngeal carcinoma (NPC) cells. We showed that the active DZ1 inhibited the expression of latent membrane protein 1 (LMP1) and induced a G1 phase arrest. In addition, this cell cycle deregulation was shown to be accompanied by upregulation of the DNA damage marker γ-H2AX, downregulation of the DNA damage response factor p-p53-Ser15 and cell proliferation inhibition. To investigate what affected the cell cycle progression, we examined the expression of two checkpoint-related cyclins and cyclin-dependent kinases (CDKs). We found a decrease of cyclin D1 and cyclin E protein levels at 24 h from the DZ1 treatment. Moreover, we observed inhibition of CDK4 activity and decreased cyclin D1 expression in the complexes immunoprecipitated with CDK4 antibody. We also found a reduction in cdc2 phosphorylation at Thr161 which partially stands for the cdc2 kinase activity in DZ1-treated CNE1-LMP1 cells, although the downregulation of LMP1 expression had no effect on the cyclin B1 and cdc2 expression. Further, we analyzed changes in cdc2 kinase activity induced by DZ1 and found that the downregulation of the LMP1 expression resulted in a 5-fold reduction in cdc2 kinase activity in CNE1-LMP1. The data suggest that the downregulation of the LMP1 expression by DZ1 was able to induce DNA damage, which then further inhibited the cell proliferation and resulted in malfunction of cell cycle checkpoints that led to G1 phase arrest and the decrease in number of cells in G2/M phase.
Algorithmic Improvements in Approximate Counting for Probabilistic Inference: From Linear to Logarithmic SAT Calls

Probabilistic inference via model counting has emerged as a scalable technique with strong formal guarantees, thanks to recent advances in hashing-based approximate counting. State-of-the-art hashing-based counting algorithms use an NP oracle (SAT solver in practice), such that the number of oracle invocations grows linearly in the number of variables n in the input constraint. We present a new approach to hashing-based approximate model counting in which the number of oracle invocations grows logarithmically in n, while still providing strong theoretical guarantees. We use this technique to design an algorithm for #CNF with strongly probably approximately correct (SPAC) guarantees, i.e. PAC guarantee plus expected return value matching the exact model count. Our experiments show that this algorithm outperforms state-of-the-art techniques for approximate counting by 1-2 orders of magnitude in running time. We also show that our algorithm can be easily adapted to give a new fully polynomial randomized approximation scheme (FPRAS) for #DNF.
The Politics of Pollution: Party Regimes and Air Quality in Canada

Environmental concerns often figure prominently in opinion polls. But do election outcomes actually affect the environment? I test the influence of the party in power on urban air pollution in 13 Canadian cities. The government's political stripe is not reliably associated with positive or negative effects on air pollution. Provincial parties on both the right and the left are associated with elevated levels of some air contaminants. Federal effects also go in contrasting directions. Overall it appears a change in government is unlikely to be a reliable predictor of changes in air pollution.
Evolutionary generation of test data for many paths coverage

Generation of test data for path coverage is an important issue of software testing, but previous methods are only suitable for the case that a program only has a small number of paths. We focus on the problem of generating test data for many paths coverage in this paper, and present a method of evolutionary generation of test data for many paths coverage. First, target paths are divided into several groups based on their similarity, and each group forms a sub-optimization problem, which transforms a complicated optimization problem into several simpler sub-optimization problems; then a domain-based fitness is designed when genetic algorithms are employed to solve these problems; finally, these sub-optimization problems are simplified along with the process of generating test data, hence improving the efficiency of generating test data. Our method is applied in 2 benchmark programs, and compared with some previous methods. The experimental results show that our method has advantage in time-consumption and the number of uncovered target paths. Our achievement provides an efficient way for generating test data of complicated software.
An ontology to document a quality scheme specification of a software product

Pressman's (2010) definition of software quality is the conformance to explicitly stated functional and performance requirements, explicitly documented development standards, and implicit characteristics that are expected of all professionally developed software. The achievement of quality is a complex activity that is related with the process quality and product quality. However, still, it is not clear how product quality should apply in the development process. Frequently, the development team does not know what characteristics influence a specific entity and how these characteristics compose the quality of the product. This lack of knowledge reflects the need to define some document that serve as a valid quality specification that should be evaluated along the development process. This contribution addresses this need by introducing an ontology for document a quality scheme based on the product quality model of ISO/IEC 25010. The proposal follows this model with aims to clarify the properties that are normally present in a product and its meaning. The ontology incorporates the metric concept to represent the way in which quality should be measure. The ontology was implemented using Protégé, and it was evaluated using a set of metrics that estimate the required structural characteristics.
Response to ‘Helicobacter pylori infection of AZ-521 cells reveals a type IV secretion defect and VacA-independent CagA phosphorylation’

We are writing in response to the Correspondence from Tegtmeyer and Backert regarding the article by [Nakano et al. (2016)][1]. Two virulence factors, cytotoxin-associated gene A (CagA) and vacuolating cytotoxin (VacA), are required for pathological actions in Helicobacter pylori -infected cells ([
Transient dynamics and rhythm coordination of inferior olive spatio-temporal patterns

The inferior olive (IO) is a neural network belonging to the olivo-cerebellar system whose neurons are coupled with electrical synapses and display subthreshold oscillations and spiking activity. The IO is frequently proposed as the generator of timing signals to the cerebellum. Electrophysiological and imaging recordings show that the IO network generates complex spatio-temporal patterns. The generation and modulation of coherent spiking activity in the IO is one key issue in cerebellar research. In this work, we build a large scale IO network model of electrically coupled conductance-based neurons to study the emerging spatio-temporal patterns of its transient neuronal activity. Our modeling reproduces and helps to understand important phenomena observed in IO in vitro and in vivo experiments, and draws new predictions regarding the computational properties of this network and the associated cerebellar circuits. The main factors studied governing the collective dynamics of the IO network were: the degree of electrical coupling, the extent of the electrotonic connections, the presence of stimuli or regions with different excitability levels and the modulatory effect of an inhibitory loop (IL). The spatio-temporal patterns were analyzed using a discrete wavelet transform to provide a quantitative characterization. Our results show that the electrotonic coupling produces quasi-synchronized subthreshold oscillations over a wide dynamical range. The synchronized oscillatory activity plays the role of a timer for a coordinated representation of spiking rhythms with different frequencies. The encoding and coexistence of several coordinated rhythms is related to the different clusterization and coherence of transient spatio-temporal patterns in the network, where the spiking activity is commensurate with the quasi-synchronized subthreshold oscillations. In the presence of stimuli, different rhythms are encoded in the spiking activity of the IO neurons that nevertheless remains constrained to a commensurate value of the subthreshold frequency. The stimuli induced spatio-temporal patterns can reverberate for long periods, which contributes to the computational properties of the IO. We also show that the presence of regions with different excitability levels creates sinks and sources of coordinated activity which shape the propagation of spike wave fronts. These results can be generalized beyond IO studies, as the control of wave pattern propagation is a highly relevant problem in the context of normal and pathological states in neural systems (e.g., related to tremor, migraine, epilepsy) where the study of the modulation of activity sinks and sources can have a potential large impact.
Sensors based on metal oxide nanostructures synthesized by arc discharge

Different synthetic methods have been developed to fabricate metal oxide nanostructures, but most of them require exotic reagents or are unsuitable for mass production. Till now, we've successfully synthesized zinc oxide (ZnO), tungsten oxide (WO3) and titanium dioxide (TiO2) nanostructures by arc discharge and the ability to tune the morphology of those nanostructures makes this method idea for fabrication of chemical sensing materials. In this paper, we present a review on metal oxide nanostructures synthesized by arc discharge demonstrating that arc discharge is a fast and inexpensive synthesis method which can be used to produce high quality metal oxide nanostructures for chemical sensing measurements. UV and gas sensing properties of ZnO nanostructures have been demonstrated as an example.