Miracle-dz/UniFAR-FTUs huggingface dataset:
PV Power Injection and Active Power Filtering With Amplitude-Clamping and Amplitude-Scaling Algorithms

This paper presents a half-bridge single-phase two-wire (1phi2W) photovoltaic (PV) inverter system that can perform both active power filtering and real power injection. In the proposed system, it needs only two active switches, reducing cost significantly. In addition, output current of the inverter can be controlled to prevent switches from exceeding their current ratings. Thus, power rating of the inverter can be effectively used and power quality can be improved. For controlling inverter output current, an amplitude-clamping algorithm and an amplitude-scaling algorithm are proposed, which can determine inverter current command without needs of complicated calculation. Simulations and experimental results have verified the feasibility of the proposed PV inverter system and the two current control algorithms
On the age heterogeneity of the Pleiades, Hyades, and Sirius moving groups

Aims. We investigate the nature of the classical low-velocity structures in the local velocity field, i.e. the Pleiades, Hyades, and Sirius moving groups. After using a wavelet transform to locate them in velocity space, we study their relation with the open clusters kinematically associated with them. Methods. By directly comparing the location of moving group stars in parallax space to the isochrones of the embedded clusters, we check whether, within the observational errors on the parallax, all moving group stars could originate from the ongoing evaporation of the associated cluster. Results. We conclude that, in each moving group, the fraction of stars making up the velocity-space overdensity superimposed on the background is higher than the fraction of stars compatible with the isochrone of the associated cluster. These observations thus favour a dynamical (resonant) origin for the Pleiades, Hyades, and Sirius moving groups.
Was There Evidence of Credit Rationing in the Czech Republic?

This work contributes to the assessment of the credit rationing hypothesis in the Czech Republic. We estimate the demand for, and supply of, new loans denominated in Czech koruna over the period 1:1997-6:2002 in a disequilibrium framework, specifically allowing the interest rate not to necessarily adjust such that demand equals supply. Based on our estimations, we suggest that the market for new loans denominated in Czech koruna was characterized by a state of moderate excess demand, hence credit rationing, only in the period 1:1999-12:2000. The remaining period appears to be characterized by excess supply.
Influence of Signal Pre-Processing in the Efficiency of Algorithms Based on Neural Networks for Disturbance Classification

Post dispatch analysis of signals obtained from digital disturbances registers provide important information to identify and classify disturbances in power systems, looking for a more efficient management of the supply. In order to enhance the task of identifying and classifying the disturbances $providing an automatic assessment - techniques of digital signal processing can be helpful. The Wavelet Transform has become a very efficient tool for the analysis of voltage or current signals, obtained immediately after disturbances occurrences in the network. This paper presents a methodology based on the discrete wavelet transform to implement this process. It uses a comparison between distribution curves of signals energy, with and without disturbance. This is done for different resolution levels of its decomposition in order to obtain descriptors that permit its classification, using artificial neural networks
Exclusive Breastfeeding and Other Foods in the First Six Months of Life: Effects on Nutritional Status and Body Composition of Brazilian Children

Objective. To evaluate the effect of exclusive breastfeeding and consumption of other foods in the first six months of life in the nutritional status and body composition of children. Methods. A retrospective cohort study with 185 children aged from 4 to 7 years was monitored during the first months of life in a program of support to breastfeeding. We evaluated weight, height, waist circumference, and body composition by using DEXA. The nutritional status was assessed by the BMI/age index. The parameters of adiposity were classified by using as the cutoff point, the 85th percentile of the sample itself, according to gender and age. Confounding factors considered were variables related to maternal, pregnancy, birth, sociodemographic, health, lifestyle, and diet. Bivariate and multivariate analyses were performed, the latter by means of multiple logistic regression. Results. The median exclusive breastfeeding was 3 months. Of the children, 42.7% received cow's milk and 35.7% received infant formula. Regarding nutritional status, 21.1% of the children showed changes. The variables of infant feeding were not independently associated with nutritional status and body composition of the children and there were no differences between the groups studied. Conclusion. Breastfeeding was not a protective factor to overweight and body fat in children.
Adapting sentiment analysis to face-to-face human-agent interactions: From the detection to the evaluation issues

This paper introduces a sentiment analysis method suitable to the human-agent and face-to-face interactions. We present the positioning of our system and its evaluation protocol according to the existing sentiment analysis literature and detail how the proposed system integrates the human-agent interaction issues. Finally, we provide an in-depth analysis of the results obtained by the evaluation, opening the discussion on the different difficulties and the remaining challenges of sentiment analysis in human-agent interactions.
Comparing transcriptional activation and autostimulation by ZEBRA and ZEBRA/c-Fos chimeras

The lytic cycle of Epstein-Barr virus (EBV) can be activated by transfection of the gene for ZEBRA, a viral basic-zipper (bZip) transcriptional activator. ZEBRA and cellular AP-1 bZip activators, such as c-Fos, have homologous DNA-binding domains, and their DNA-binding specificities overlap. Moreover, EBV latency can also be disrupted by phorbol esters, which act, in part, through AP-1 activators. It is not known whether ZEBRA and AP-1 factors play equivalent roles in the initial stages of reactivation. Here the contribution of ZEBRA's basic DNA recognition domain to disruption of latency was analyzed by comparing ZEBRA with chimeric mutants in which the DNA recognition domain of ZEBRA was replaced with the analogous domain of c-Fos. Chimeric ZEBRA/c-Fos proteins overexpressed in Escherichia coli bound DNA with the specificity of c-Fos; they bound a heptamer AP-1 site and an octamer TPA response element (TRE). ZEBRA bound the AP-1 site and an array of ZEBRA response elements (ZREs). In assays with reporter genes, both ZEBRA and ZEBRA/c-Fos chimeric mutants activated transcription from Zp, a promoter of the ZEBRA gene (BZLF1) that contains the TRE and multiple ZREs. However, despite their capacity to activate reporters bearing Zp, neither ZEBRA nor the c-Fos chimeras activated transcription from Zp in the context of the intact latent viral genome. In contrast, ZEBRA but not ZEBRA/c-Fos chimeras activated Rp, a second viral promoter that controls ZEBRA expression. Hence, transcriptional autostimulation by transfected ZEBRA occurred preferentially at Rp. Both ZEBRA and the ZEBRA/c-Fos chimeras activated transcription from reporters with multimerized AP-1 sites. However, in the context of the virus, only ZEBRA activated the promoters of two early lytic cycle genes, BMRF1 and BMLF1, that contain an AP-1 site. Thus, overexpression of an activator that recognized AP-1 and TRE sites was not sufficient to activate EBV early lytic cycle genes.
Contrasting molecular and morphological evidence for the identification of an anomalous Buteo: a cautionary tale for hybrid diagnosis

An adult Buteo was found dead as a road-kill south of Sacramento, California, and was thought to represent the first state record of the eastern Red-shouldered Hawk (B. lineatus lineatus;). It is now a specimen in the Museum of Wildlife and Fisheries Biology (WFB 4816) at the University of California, Davis. We examined this specimen and found that many of its plumage characters differed from all other adult Red-shouldered Hawks examined, including nominate adults. Plumage markings and measurements were intermediate between Red-tailed Hawk (Buteo jamaicensis, ssp calurus) and Red-shouldered Hawk (ssp elegans), leading us to hypothesize that the bird was a hybrid. However, mtDNA sequences and nuDNA microsatellites proved definitively that the bird was a Red-shouldered Hawk, most likely of eastern origin. This case illustrates that apparent hybrids or apparent vagrants could be individuals with anomalous phenotypes caused by rare genetic variation or novel epigenetic effects.
Deenitional Concurrent Constraint Programming

In this paper, deenitional constraint constraint programming, abbreviated as CDC, is presented as a uniform framework for declarative concurrent programming. The new paradigm supports a uniform concurrent computational model unifying functional evaluation, linear deduction and constraint solving. It leads us from a constraint based integration of functional and logic programming to a powerful framework for multiparadigm concurrent constraint programming.
A Dynamic-Reconfigurable Architecture for Protocol Stacks of Networked Systems

This paper proposes a software framework for dynamic- reconfigurable protocol stack The framework presents mechanisms and an algorithm for all required phases for reconfiguration of a running protocol component that include freezing the component in a safe state, changing the component, and state transfer to a new component. Considering that every running protocol component communicates with at least one peer component in another system, we perform the reconfiguration with respect to the peer component.
Multi-model Based Optimization for Stream Query Processing

With recent explosive growth of sensors and instruments, large scale data-intensive and computation-intensive applications are emerging, especially in scientific fields. Helping scientists to efficiently, even in real time, process queries over those large scale scientific streams thus has great demand. However, query optimization for high volume stream applications– in particular its core component, the evaluation model– has not been systematically studied. We observe that evaluating stream query plans should consider three aspects: output rate, computation cost and memory consumption. However, to our knowledge, no existing research on evaluating stream query plans consider all three metrics. In this paper, we propose a new combined optimization goal which leverages all these aspects and develop a multi-model based optimization framework to accomplish this goal. Specifically, we build three models to evaluate a plan’s output rate, computation cost and memory consumption respectively. Based on such three models, we search for an optimal plan while considering systems’s computation resource and memory constraints. We also experimentally evaluate our optimization framework.
Capacity, Output, and Sequential Entry

Two crucial assumptions frequently made in industrial organization are that an established firm deters entry either by a constant high output (the Sylos Postulate) or by high excess capacity (the Excess Capacity Hypothesis). These assumptions may be an accurate description of the observed conduct of firms in some industries. However, when the rules of the post-entry game are clearly specified, the optimal output and investment strategies of an established firm may depart considerably from these behavioral assumptions. Because of this possible inconsistency with rational behavior, any conclusions about the formation of industry based upon either assumption are highly suspect. What is more, these assumptions avoid the main issue of whether entry deterrence is worthwhile at all. This paper presents a dynamic model of entry in which established firms pursue a Cournot Nash (alternatively Stackelberg) strategy toward a potential entrant. The entrant behaves in Cournot-Nash fashion and chooses output on the basis of expected postentry profits at the equilibrium of the post-entry game. Within this framework, a constant output entry-deterring strategy would involve maintenance of an entry-deterring output level before and after entry is threatened. An excess capacity entry-deterring strategy would involve holding excess capacity at an entry-deterring level and increasing output to that level after entry is threatened. Special conditions are presented under which the Sylos Postulate or the Excess Capacity Hypothesis will accurately describe optimal entry-deterring strategies. In addition, special conditions are examined under which the established firm maintains a constant output or holds pre-entry excess capacity when large-scale entry does in fact take place. The analysis shows that in general, established firm reactions to entry are quite different from these special cases. The Sylos Postulate (see Joseph Bain; Paolo Sylos-Labini; Franco Modigliani, 1958) asserts not only that potential entrants expect established firms to maintain their output constant as entry occurs, but that established firms keep output constant at a level that deters entry whether or not it is profitable to do so. Hailed as a "welcome major breakthrough on the oligopoly front" (Modigliani, 1958) the Sylos Postulate underlies many papers in the large theoretical and empirical literature on limit pricing. ' Yet the Sylos Postulate ignores both the strategic interaction between firms and the dynamic aspects of entry.2 Unless the established firm's monopoly output exceeds the entrydeterring level, the established firm with a general cost function able to choose an entry-deterring output level will instead always desire a lower output level before entry. For the special case where capacity is an upper bound on output and the established firm is a Stackelberg leader in the post-entry game,
Research on satellite attitude determination with adaptive filter

When satellite is running, it may be influenced by external factors, and the measurement models of gyro and star sensor are changing with time uncertainly. This situation may lead extended Kalman filter(EKF) divergent. So new adaptive filter can be used in this situation, and it can estimate process noise and measuring noise on-time. This paper has applied Sage-Husa adaptive filter in satellite attitude determination. This adaptive filter algorithm can estimate satellite attitude parameters and gyro drift on-time with high accuracy reaching 10-3 level, and stability of the algorithm is also very good.
Hybrid Heuristic-Based Artificial Immune System for Task Scheduling

Task scheduling problem in heterogeneous systems is the process of allocating tasks of an application to heterogeneous processors interconnected by high-speed networks, so that minimizing the finishing time of application as much as possible. Tasks are processing units of application and have precedence-constrained, communication and also, are presented by Directed Acyclic Graphs (DAGs). Evolutionary algorithms are well suited for solving task scheduling problem in heterogeneous environment. In this paper, we propose a hybrid heuristic-based Artificial Immune System (AIS) algorithm for solving the scheduling problem. In this regard, AIS with some heuristics and Single Neighbourhood Search (SNS) technique are hybridized. Clonning and immune-remove operators of AIS provide diversity, while heuristics and SNS provide convergence of algorithm into good solutions, that is balancing between exploration and exploitation. We have compared our method with some state-of-the art algorithms. The results of the experiments show the validity and efficiency of our method.
Advances in epigenetic glioblastoma therapy

Glioblastoma multiforme (GBM) is the most lethal primary brain tumor in adults despite contemporary gold-standard first-line treatment strategies. This type of tumor recurs in virtually all patients and no commonly accepted standard treatment exists for the recurrent disease. Therefore, advances in all scientific and clinical aspects of GBM are urgently needed. Epigenetic mechanisms are one of the major factors contributing to the pathogenesis of cancers, including glioblastoma. Epigenetic modulators that regulate gene expression by altering the epigenome and non-histone proteins are being exploited as therapeutic drug targets. Over the last decade, numerous preclinical and clinical studies on histone deacetylase (HDAC) inhibitors have shown promising results in various cancers. This article provides an overview of the anticancer mechanisms of HDAC inhibitors and the role of HDAC isoforms in GBM. We also summarize current knowledge on HDAC inhibitors on the basis of preclinical studies and emerging clinical data.
A survey on cloud computing

The long-dreamed vision of “computing as a utility” has finally taken shape in the form of cloud computing. This paradigm shift is the biggest buzz in today's computer world. It can be thought of an evolution of existing technologies rather than a revolution. The basic requirements of cloud are to meet the various needs of enterprise organizations such as scalability, adaptability, extensibility and manageability. The biggest visible change the cloud computing has made in the scenario of computing is moving the data center offsite to a third party and buying services rather than maintaining onsite applications directly. By its use companies can save money on operational costs and they can focus on their core business instead of being worried about different IT obstacles. Moreover true portability is provided by cloud by enabling access to applications and documents anywhere in the world via the internet through commodity hardware only. In this paper we have described the basic concepts of cloud computing in a nutshell so that the readers can get an essence of this newly emerging technology.
Survey of the distribution of lesion size in multiple sclerosis: implication for the measurement of total lesion load

OBJECTIVES Quantitative measurement of lesion load on proton density or T2 weighted brain MRI in multiple sclerosis is a widely used marker of disease progression in treatment trials and natural history studies. However, it has proved difficult to obtain highly reproducible measurements. Several factors account for this, one of which is uncertainties in lesion identification, particularly very small white matter abnormalities. This paper aims to ascertain the significance of very small white matter abnormalities in the measurement of lesion load in multiple sclerosis. METHODS All visible lesion areas identified by an experienced observer on proton density weighted spin echo brain MRI with 5 mm thick slices were measured by using a contouring technique in 15 patients with secondary progressive multiple sclerosis (SPMS) and 13 with relapsing remitting multiple sclerosis (RRMS). The size distribution of these lesions was analysed. RESULTS 80% of the number of the lesions were smaller than 80 mm2. Lesions that were smaller than 10 mm2 (equivalent diameter <3.5 mm) made up nearly 20% of all lesions; their relative contribution to the total lesion load varied from 0.0–5.7% (mean=1.1%, median=0.65%) in individual patients, and was larger when the total lesion load was smaller (r = −0.65, P<0.001). Median lesion size was significantly smaller in the SPMS group than the RRMS group. CONCLUSIONS The results suggest that it is prudent to identify and measure small lesions in evaluating treatment effects, and that measures are undertaken (for example, using thinner slices such as 3 mm) to improve their detection.
Agnostic Online learnability

We study a fundamental question. What classes of hypotheses are learnable in the online learning model? The analogous question in the PAC learning model [12] was addressed by Vapnik and others [13], who showed that the VC dimension characterizes the learnability of a hypothesis class. In his influential work, Littlestone [9] studied the online learnability of hypothesis classes, but only in the realizable case, namely, assuming that there exists a hypothesis in the class that perfectly explains the entire data. In this paper we study the online learnability in the agnostic case, namely, no hypothesis perfectly predicts the entire data, and our goal is to minimize regret. We first present an impossibility result, discovered by Cover in the context of universal prediction of individual sequences, which implies that even a class whose Littlestone’s dimension is only 1, is not learnable in the agnostic online learning model. We then overcome the impossibility result by allowing randomized predictions, and show that in this case Littlestone’s dimension does capture the learnability of hypotheses classes in the agnostic online learning model.
Decoder segment optimization of ROM design in quantum dot cellular automata

Emerging technology proves its superiority through quantum dot cellular automata where confinements of electrons occur from all three dimensions. Effective area optimization in quantum dot cellular automata plays a pivotal role in memory designing. In the design of Read Only Memory(ROM), decoding section decides where specific information will be stored. Optimal design of decoder segment signifies the improved memory design. This paper introduces a new design of 4 bit row/column decoder in the ROM design. Designed decoder shows 25.89% reduction of effective area than the latest design proposed by Rigui Zhou et al at the cost of only four majority voter blocks.
PURCHASING AND ENVIRONMENTAL MANAGEMENT: INTERACTIONS, POLICIES AND OPPORTUNITIES

The mechanisms are examined by which environmentally informed business practices and technologies may diffuse through industry as a result of the ‘greening’ of purchasing and supply. The efforts of official bodies in the UK to raise environmental awareness among industrial purchasers are reviewed. It is then argued that the supply chain model is an important way of interpreting the industrial landscape from a green perspective and that it is in some ways a more hopeful and positive starting point for achieving industrial transformation. The results of an analysis of some UK companies practices in using their purchasing policies to ‘green’ their supply chains are presented and opportunities for further research indicated.