Miracle-dz/UniFAR-FTUs huggingface dataset:
EFFECTS OF SCALE ON LOAD PREDICTION ALGORITHMS

Load prediction is an important tool for grid utilities and power companies for managing the power system. This has traditionally mainly been applied at transmission and subtransmission system levels. However, as the traditional grid evolves into a smart grid, load prediction at smaller scales becomes necessary for efficient management and operation. In this paper we investigate how the qualitative and statistical properties of load time series change as a function of the number of individual loads aggregated in the series, and how these properties influence the predictability of the time series. We study the performance of a traditional autoregressive model, a wavelet-based model, an Echo State Network, and a variation of Case-Based Reasoning (CBR) at the subtransmission (~10000 customers), distribution substation (~150 customers) and single-meter level. For all the four prediction methods, we employ an evolutionary algorithm as a meta-learner to automatically optimize the free parameters for each model-dataset combination. We find that relatively accurate predictions can be made at finer granularity, but care must be taken in choosing, tuning and analyzing the prediction model as the regularity of the consumption patterns decreases.
Active galactic nuclei and massive galaxy cores

Context. Central active galactic nuclei (AGN) are supposed to play a key role in the evolution of their host galaxies. In particular, the dynamical and physical properties of the gas core must be affected by the injected energy. Aims. Our aim is to study the effects of an AGN on the dark matter profile and on the central stellar light distribution in massive early type galaxies. Methods. By performing self-consistent N-body simulations, we assume in our analysis that periodic bipolar outbursts from a central AGN can induce harmonic oscillatory motions on both sides of the gas core. Results. Using realistic AGN properties, we find that the motions of the gas core, driven by such feedback processes, can flatten the dark matter and/or stellar profiles after 4−5 Gyr. These results are consistent with recent observational studies that suggest that most giant elliptical galaxies have cores or are “missing light” in their inner part. Since stars behave as a “collisionless” fluid similar to dark matter, the density profile both of stars and dark matter should be affected in a similar way, leading to an effective reduction in the central brightness.
The index premium and its hidden cost for index funds ☆

☆ This paper is a revised version of Chapter 1 of my d Spiegel, Dimitri Vayanos, Tuomo Vuolteenaho, and Jia grateful to Frank Russell Co. for providing data for this paper was previously entitled “The Index Premium an E-mail address: antti.petajisto@stern.nyu. edu. URL: http://www.petajisto. net/. 1 For example, Shleifer (1986), Holthausen et al. (1 (1997), Kaul et al. (2000), Wurgler and Zhuravskaya stocks tend to deviate further from their fundamental
Key Stakeholders’ Experiences of International Education at one Australian University

Aim: This study aimed to explore the experiences which influenced the perceptions of three key groups of stakeholders: academic and support staff, international students, and their domestic peers, when engaging in International Education at one Australian university. The original research questions for this study were: 1. What experiences influence staff members’ perceptions of International Education at one Australian university? 2. What experiences influence international students’ perception of their education at one Australian university? As directed by theoretical sampling, the views of domestic students were then also sought, to shed light on the following research question: 3. What experiences influence domestic students’ perceptions of International Education at one Australian university? Conceptual Framework: A Social Constructivist theoretical framework was employed within a Case Study approach for a number of reasons. First, institutions have their own specific characteristics, budgets and student populations and so can be studied separately in order that the researcher might develop a detailed critical understanding of the intricacies of the single case. Since International Education is a complex phenomenon, the researcher also needed to include the multiple realities of the different stakeholders involved. The researcher’s personal philosophy aligned with Social Constructivism, which argues that perceptions of reality are subjective to the person experiencing them. As such, Social Constructivist Grounded Theory allowed for the interpretation of both the participants’ views of reality as well as the researcher’s. Finally, this approach allowed for a co-construction of reality through the interactions of the participants and
The Development of Quality Assurance Reviews in the NSW Public School System: What Works? Draft.

This paper provides information about the development of a successful quality-assurance process in the New South Wales, Australia, school system. In 1992 the New South Wales (NSW) government announced its commitment to a program of quality-assurance reviews of schools. During that year, approximately 100 meetings were held with principals, school staff, parents, and other key groups to elicit feedback and introduce the new program. This paper summarizes the key issues discussed at the meetings. The quality-assurance review of sf.alools will take place during the first three terms of 1993. The process will involve schools working with review teams to determine the best way to conduct the reviews. The paper defines quality-assurance reviews and provides a brief historical overview of quality assurance in the NSW Department of School Education, a summary of research and literature related to school review and development, and answers to commonly asked questions about quality assurance. It also describes future directions of the program for the rest of 1993. (LMI) *********************************************************************** Reproductions supplied by EDRS arse the best that can be made * from the original document. *********************************************************************** THE DEVELOPMENT OF QUALITY ASSURANCE REVIEWS IN THE NSW PUBLIC SCHOOL SYSTEM: WHAT WORKS? An information and discussion paper provided as input into the consultation and development process for quality assurance reviews. U.S. DEPARTMENT Of EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERICI fhis document has been reproduced as received from the person or organization originating n CI Minor changes have Wen made to improve reproduction Quality Points of view or opinions staled in the document do not necessarily rePfent official OERI position or policy "PERMISSION TO REPRODUCE THIS MAT RIAL HAS BEEN GRANTED BY TO THE EDUCATIONAL RESOURCES INFORMATION CENTIR (ERIC" Peter Cuttance Assistant Director General (Quality Assurance) NSW Department of School Education File Ref: WHAT WORKS Paper.930402 Draft: 29/04/93 20:40:56
Expanding from Discrete Cartesian to Permutation Gene-pool Optimal Mixing Evolutionary Algorithms

The recently introduced Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) family, which includes the Linkage Tree Genetic Algorithm (LTGA), has been shown to scale excellently on a variety of discrete, Cartesian-space, optimization problems. This paper shows that GOMEA can quite straightforwardly also be used to solve permutation optimization problems by employing the random keys encoding of permutations. As a test problem, we consider permutation flowshop scheduling, minimizing the total flow time on 120 different problem instances (Taillard benchmark). The performance of GOMEA is compared with the recently published generalized Mallows estimation of distribution algorithm (GM-EDA). Statistical tests show that results of GOMEA variants are almost always significantly better than results of GM-EDA. Moreover, even without using local search, the new GOMEA variants obtained the best-known solution for 30 instances in every run and even new upper bounds for several instances. Finally, the time complexity per solution for building a dependency model to drive variation is an order of complexity less for GOMEA than for GM-EDA, altogether suggesting that GOMEA also holds much promise for permutation optimization.
Statistical Parameterization of Heterogeneous Oceanic Convection

Abstract A statistical convective adjustment scheme is proposed that attempts to account for the effects of mesoscale and submesoscale variability of temperature and salinity typically observed in the oceanic convective regions. Temperature and salinity in each model grid box are defined in terms of their mean, variance, and mutual correlations. Subgrid-scale instabilities lead to partial mixing between different layers in the water column. This allows for a smooth transition between the only two states (convection on and convection off) allowed in standard convective adjustment schemes. The advantage of the statistical parameterization is that possible instabilities associated with the sharp transition between the two states, which are known to occasionally affect the large-scale model solution, are eliminated. The procedure also predicts the generation of correlations between temperature and salinity and the presence of convectively induced upgradient fluxes that have been obtained in numerical simulati.
ON SPATIOTEMPORAL SPECTRAL ANALYSIS

The wavenumber-frequency spectrum reveals dynamic features of spatiotemporal processes such as traveling oscillatory components, turbulent structures, and linear transfer functions. It can be used to estimate multidimensional covariance, or to directly perform parameter estimation with reduced computational cost. However, simple extensions of univariate spectral estimators can be shown to have poor statistical properties. In this talk I will extend the univariate multitaper spectrum estimator to the multidimensional case, using optimally bandlimited functions (Slepian functions) for spacelimited Cartesian domains. Multitaper spectrum analysis has the advantage of (a) restricting bias in frequency-wavenumber domain due to usage of Slepian functions (b) variance reduction due to averaging of multiple approximately independent spectral estimates. On a toy example in one spatial dimension and one time dimension, sea surface temperatures are shown to exhibit a strong traveling El Niño Southern Oscillation (ENSO) pattern, from which it is possible to derive velocity and signal strength. In a real data example, we investigate the fluid properties of Von Karmán vortex shedding off a square mounted cylinder in turbulent flow, by high dimensional spectral analysis applied to data from a simulation of fluid flow equations on a complex gridded geometry.
What makes regions in Eastern Europe catching up? The role of foreign investment, human resources and geography

This paper analyses regional growth in Eastern Europe in the second half of the 1990s, when regional disparities sharply increased. We aim to identify the factors behind growth and investigate in particular the role of (foreign) investment, education and innovation as well as geographical factors in a model of economic growth. The key relationships are estimated with spatial econometric tools on empirical data for the period 1995-2000. We find that foreign direct investment was paramount for growth in that period. EU border regions and capital areas clearly outperformed others. Further, regional growth clusters have appeared. Surprisingly, the high level of secondary education played no role to growth. Higher education, in contrast, was important, also for technology transfer.
The Information of Option Volume for Future Stock Prices

We present strong evidence that option trading volume contains information about future stock price movements. Taking advantage of a unique dataset from the Chicago Board Options Exchange, we construct put-call ratios from option volume initiated by buyers to open new positions. On a risk-adjusted basis, stocks with low put-call ratios outperform stocks with high put-call ratios by more than 40 basis points on the next day and more than 1% over the next week. Partitioning our option signals into components that are publicly and non-publicly observable, we find that the economic source of this predictability is non-public information possessed by option traders rather than market inefficiency. We also find greater predictability from option signals for stocks with higher concentrations of informed traders and from option contracts with greater leverage.
running head: Jonsson et al, Truncated semenogelin I binds zinc Truncated semenogelin I binds zinc and is cleaved by prostate-specific antigen

Semenogelins I and II are major coagulum-forming proteins in semen, and they are secreted mainly by the seminal vesicles. These proteins bind Zn and act as substrates for prostatespecific antigen and transglutaminase. A variant semenogelin I lacking 60 amino acids has been described that occurs in different populations with an allele frequency of 1-3%. To better understand the function of the semenogelins in vivo, our aim was to characterize the properties of the variant form and compare with the wild-type . Recombinant proteins were synthesized in insect cells. Binding of Zn was studied by titration of metal ions in the presence of a zinc (II) fluorophore chelator. SDS-PAGE was used to visualize the results of cleavage by prostate-specific antigen and cross-linking with transglutaminase. We found that the truncated and wild-type semenogelin molecules had similar Zn-binding properties (i.e. a stoichiometry of at least 9–10 mol per mol of protein and an average dissociation constant of 5 μM per site), and they showed also similar susceptibility for degradation by prostatespecific antigen. Furthermore, like the wild-type form, the truncated semenogelin I was able to serve as a substrate for transglutaminase. These findings imply that the studied characteristics do not depend on a well-defined tertiary structure, or that the deletion has no major effect on the structure responsible for these features.
Solving the Dmp Model Accurately

An accurate global algorithm is critical for quantifying the dynamics of the Diamond-Mortensen-Pissarides model. Loglinearization understates the mean and volatility of unemployment, overstates the unemployment-vacancy correlation, and ignores impulse responses that are an order of magnitude larger in recessions than in booms. Although improving on loglinearization, the second-order perturbation in logs also induces large errors. We demonstrate these insights in the context of Hagedorn and Manovskii (2008). Once solved accurately, their small surplus calibration fails to explain the Shimer (2005) puzzle. While the volatility of labor market tightness is close to the data, the unemployment volatility is too high.
Do the models of institutional quality differ according to the income level of the countries? The case of the low-income countries

2013SummaryThis paper contributes to the debate about which factors determine the institutional quality of coun-tries. it uses explanatory economic, socio-political and cultural variables for three sub-samples ofcountries with different income level. The results validate the hypothesis that establishes there is notan only valid model of institutional quality for all countries. moreover, the limited explanatory ca-pacity of the model for the low-income level sub-sample of countries has motivated the incorpora-tion of other variables related to colonial origins, geographical location or life expectancy. The re-sults validate the theoretical arguments that propose the use of these variables
A Sparse Image Fusion Algorithm With Application to Pan-Sharpening

Data provided by most optical Earth observation satellites such as IKONOS, QuickBird, and GeoEye are composed of a panchromatic channel of high spatial resolution (HR) and several multispectral channels at a lower spatial resolution (LR). The fusion of an HR panchromatic and the corresponding LR spectral channels is called “pan-sharpening. ” It aims at obtaining an HR multispectral image. In this paper, we propose a new pan-sharpening method named Sparse F usion of Images (SparseFI, pronounced as “sparsify”). SparseFI is based on the compressive sensing theory and explores the sparse representation of HR/LR multispectral image patches in the dictionary pairs cotrained from the panchromatic image and its downsampled LR version. Compared with conventional methods, it “learns” from, i.e., adapts itself to, the data and has generally better performance than existing methods. Due to the fact that the SparseFI method does not assume any spectral composition model of the panchromatic image and due to the super-resolution capability and robustness of sparse signal reconstruction algorithms, it gives higher spatial resolution and, in most cases, less spectral distortion compared with the conventional methods.
Acupoint Injection of Onabotulinumtoxin A for Migraines

Onabotulinumtoxin A (BoNTA) has been reported to be effective in the therapy for migraines. Acupuncture has been used worldwide for the treatment of migraine attacks. Injection of a small amount of drug at acupuncture points is an innovation as compared to traditional acupuncture. The purpose of this study was to evaluate and compare the effectiveness of fixed (muscle)-site and acupoint-site injections of BoNTA for migraine therapy in a randomized, double-blinded, placebo-controlled clinical trial extending over four months. Subjects with both episodic and chronic migraines respectively received a placebo (n = 19) or BoNTA (2.5 U each site, 25 U per subject) injection at fixed-sites (n = 41) including occipitofrontalis, corrugator supercilii, temporalis and trapeziue, or at acupoint-sites (n = 42) including Yintang (EX-HN3), Taiyang (EX-HN5), Baihui (GV20), Shuaigu (GB8), Fengchi (GB20) and Tianzhu (BL10). The variations between baseline and BoNTA post-injection for four months were calculated monthly as outcome measures. BoNTA injections at fixed-sites and acupoint-sites significantly reduced the migraine attack frequency, intensity, duration and associated symptoms for four months compared with placebo (p < 0.01). The efficacy of BoNTA for migraines in the acupoint-site group (93% improvement) was more significant than that in the fixed-site group (85% improvement) (p < 0.01). BoNTA administration for migraines is effective, and at acupoint-sites shows more efficacy than at fixed-sites. Further blinded studies are necessary to establish the efficacy of a low dose toxin (25 U) introduced with this methodology in chronic and episodic migraines.
Capsaicin Synthesis Requires in Situ Phenylalanine and Valine Formation in in Vitro Maintained Placentas from Capsicum chinense

Capsaicinoids (CAP) are nitrogenous metabolites formed from valine (Val) and phenylalanine (Phe) in the placentas of hot Capsicum genotypes. Placentas of Habanero peppers can incorporate inorganic nitrogen into amino acids and have the ability to secure the availability of the required amino acids for CAP biosynthesis. In order to determine the participation of the placental tissue as a supplier of these amino acids, the effects of blocking the synthesis of Val and Phe by using specific enzyme inhibitors were analyzed. Isolated placentas maintained in vitro were used to rule out external sources′ participation. Blocking Phe synthesis, through the inhibition of arogenate dehydratase, significantly decreased CAP accumulation suggesting that at least part of Phe required in this process has to be produced in situ. Chlorsulfuron inhibition of acetolactate synthase, involved in Val synthesis, decreased not only Val accumulation but also that of CAP, pointing out that the requirement for this amino acid can also be fulfilled by this tissue. The presented data demonstrates that CAP accumulation in in vitro maintained placentas can be accomplished through the in situ availability of Val and Phe and suggests that the synthesis of the fatty acid chain moiety may be a limiting factor in the biosynthesis of these alkaloids.
Chromosomal Regions in Prostatic Carcinomas Studied by Comparative Genomic Hybridization, Hierarchical Cluster Analysis and Self-Organizing Feature Maps

Comparative genomic hybridization (CGH) is an established genetic method which enables a genome‐wide survey of chromosomal imbalances. For each chromosome region, one obtains the information whether there is a loss or gain of genetic material, or whether there is no change at that place. Therefore, large amounts of data quickly accumulate which must be put into a logical order. Cluster analysis can be used to assign individual cases (samples) to different clusters of cases, which are similar and where each cluster may be related to a different tumour biology. Another approach consists in a clustering of chromosomal regions by rewriting the original data matrix, where the cases are written as rows and the chromosomal regions as columns, in a transposed form. In this paper we applied hierarchical cluster analysis as well as two implementations of self‐organizing feature maps as classical and neuronal tools for cluster analysis of CGH data from prostatic carcinomas to such transposed data sets. Self‐organizing maps are artificial neural networks with the capability to form clusters on the basis of an unsupervised learning rule. We studied a group of 48 cases of incidental carcinomas, a tumour category which has not been evaluated by CGH before. In addition we studied a group of 50 cases of pT2N0‐tumours and a group of 20 pT3N0‐carcinomas. The results show in all case groups three clusters of chromosomal regions, which are (i) normal or minimally affected by losses and gains, (ii) regions with many losses and few gains and (iii) regions with many gains and few losses. Moreover, for the pT2N0‐ and pT3N0‐groups, it could be shown that the regions 6q, 8p and 13q lay all on the same cluster (associated with losses), and that the regions 9q and 20q belonged to the same cluster (associated with gains). For the incidental cancers such clear correlations could not be demonstrated.
Adaptive Dynamic Programming for Finite-Horizon Optimal Control of Discrete-Time Nonlinear Systems With $\varepsilon$-Error Bound

In this paper, we study the finite-horizon optimal control problem for discrete-time nonlinear systems using the adaptive dynamic programming (ADP) approach. The idea is to use an iterative ADP algorithm to obtain the optimal control law which makes the performance index function close to the greatest lower bound of all performance indices within an -error bound. The optimal number of control steps can also be obtained by the proposed ADP algorithms. A convergence analysis of the proposed ADP algorithms in terms of performance index function and control policy is made. In order to facilitate the implementation of the iterative ADP algorithms, neural networks are used for approximating the performance index function, computing the optimal control policy, and modeling the nonlinear system. Finally, two simulation examples are employed to illustrate the applicability of the proposed method.