Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated geophysical‐petrological modeling of the lithosphere and sublithospheric upper mantle: Methodology and applications

A combined geophysical‐petrological methodology to study the thermal, compositional, density, and seismological structure of lithospheric/sublithospheric domains is presented. A new finite‐element code (LitMod) is used to produce 2‐D forward models from the surface to the 410‐km discontinuity. The code combines data from petrology, mineral physics, and geophysical observables within a self‐consistent framework. The final result is a lithospheric/sublithospheric model that simultaneously fits all geophysical observables and consequently reduces the uncertainties associated with the modeling of these observables alone or in pairs, as is commonly done. The method is illustrated by applying it to both oceanic and continental domains. We show that anelastic attenuation and uncertainties in seismic data make it unfeasible to identify compositional variations in the lithospheric mantle from seismic studies only. In the case of oceanic lithosphere, plates with thermal thicknesses of 105 ± 5 km satisfy geophysical and petrological constraints. We find that Vp are more sensitive to phase transitions than Vs, particularly in the case of the spinel‐garnet transition. A low‐velocity zone with absolute velocities and gradients comparable to those observed below ocean basins is an invariable output of our oceanic models, even when no melt effects are included. In the case of the Archean subcontinental lithospheric mantle, we show that “typical” depleted compositions (and their spatial distribution) previously thought to be representative of these mantle sections are compatible neither with geophysical nor with petrological data. A cratonic keel model consisting of (1) strongly depleted material (i.e., dunitic/harzburgitic) in the first 100–160 km depth and (2) less depleted (approximately isopycnic) lower section extending down to 220–300 km depth is necessary to satisfy elevation, geoid, SHF, seismic velocities, and petrological constraints. This highly depleted (viscous) upper layer, and its chemical isolation, may play a key role in the longevity and stability of cratons.
Development and evaluation of a simultaneous multithreading processor simulator

DEVELOPMENT AND EVALUATION OF A SIMULTANEOUS MULTITHREADING PROCESSOR SIMULATOR by Carla Verbena S. Nuńez Modem processors are designed to achieve greater amounts of instruction level parallelism (ALP) and thread level parallelism (ALP). Simultaneous multithreading (SMT) is an architecture that exploits both ALP and ALP. At improves the utilization of the processor resources by allowing multiple independent threads to reside in the pipeline and dynamically scheduling the available resources among the threads. The first part of this thesis presents the development of a simultaneous multithreading processor simulator. The SMT simulator is derived from SimpleScalar, a superscalar processor simulator widely used in the computer architecture research field. The basic pipeline is expanded to allow multiple threads to be fetched, dispatched, issued, executed, and committed simultaneously. Benchmarks that were executed on the SMT simulator verified its functionality. The simulator produced the correct outputs and the performance levels achieved were similar to those produced by the original authors of the SMUT architecture. The second part of this thesis explores the register file for SMUT processors. The register file size grows with increased issue widths, instruction window sizes, and number of thread contexts; as the register file size increases, so does its access latency. Solutions to the register file problem have been proposed but most of these were designed for and evaluated on superscalar processors. The use-based register cache is one such design and its effectiveness on an SMT architecture is evaluated in this thesis. The SMT simulator is a useful tool for evaluating components designed for superscalar processors on a simultaneous multithreading environment and for testing future designs of SMT architectural elements. DEVELOPMENT AND EVALUATION OF A SIMULTANEOUS MULTITHREADING PROCESSOR SIMULATOR by Carla Verbena S. Nuńez A Thesis Submitted to the Faculty of New Jersey Institute of Technology in Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Engineering Department of Electrical and Computer Engineering
Annual Report of 2005 For the second year project on the Improvement of CWB Global and Regional Spectral Models for Short-range Climate Prediction

The major theme of this project has three folds. The second one for this year is to implement prognostic cloud schemes into CWB regional spectral model (RSM). It is known that precipitation is one of the major meteorological event even in climate prediction, and it is found that prognostic-type of cloud parameterization is better than traditional cumulus parameterization as we knew. The cloud schemes with several type of cloud water are implemented for seasonal climate simulation. In this report, it includes the methods of the cloud schemes, the implementation steps in CWB RSM, and the test of summer and winter cases in daily weather and monthly short-range climate results The results from the tests of winter (20040101) and summer (20050801) show a positive improvement in terms of precipitation. In the winter case, sub-grid-scale rainfall is much less than grid-scale rainfall because the unstable system is large scale in wintertime. For the summer case, the unstable atmosphere inherent to meso-scale, so more sub-gridscale rainfall than grid-scale one. Prognostic cloud scheme tends to carry more water around horizontally, thus there are more grid-scale rainfall from cloud scheme, even help to have more rain for sub-scale one.
Detection of Brain Tumor in MRI Utilizing Supervised Neural Networks and Adaptive HSOFM Algorithm

Brain tumors are one of the major causes of death among people. The chances of survival can be increased if the tumor is detected correctly at its early stage. In this paper feed forward neural networks and Hierarchical Self Organization Feature Map, (HSOFM) algorithm were utilized to detect, isolate and extract the tumor region in brain MR images with and without contrast agent. Intensity in one trail; intensity and standard deviation in second trail and intensity and Gray Level Co-occurrence Matrix, (GLCM) features in the third one were implemented as input features to the feed forward neural network to classify the tumor class adequately. As well as, adaptive HSOFM which is an unsupervised neural network was utilized to cluster brain MR images in order to extract the tumor region depending on the images histogram in one experiment and based on the Fuzzy C-Mean clusters centers in another one. The results showed that the performance of HSOFM was promising compared with the supervised neural networks.
Orthogonality of functions describing electric power quantities in Budeanu's concept

Streszczenie. W artykule przedstawiono wyniki szczegolowej analizy mocy w obwodach z niesinusoidalnymi przebiegami napiecia i prądu wedlug koncepcji zaproponowanej przez Budeanu. Przypomniano, ze osobą ktora pierwsza zaproponowala koncepcje sumowania mocy biernych poszczegolnych harmonicznych byl Bunet. Postulat ten zostal wlączony do tzw. twierdzenia Boucherota. Na podstawie analizy obwodu zawierającego jedynie idealny induktor wykazano blednośc zalozen zarowno w koncepcji Boucherota jak i Budeanu. Zalozenie o addytywności mocy nie zawsze jest prawdziwe. Wykazano rowniez, ze zaproponowane przez Budeanu moce: bierna (reaktywna) i deformacji nie zawsze są ortogonalne. Bezkrytyczne twierdzenie o ortogonalności mocy jest nieuprawnione (Ortogonalnośc funkcji opisujących moce wedlug koncepcji Budeanu).
Adoption of conservation practices by agricultural landowners in three Oregon watersheds

ABSTRACT: A community-based adaptive management framework is applied to the Calapooya Creek, Deer Creek, and Myrtle Creek watersheds within the Umpqua River Basin in Southwestern Oregon. The objectives are to: 1) identify agricultural landowner participation in watershed conservation projects, and 2) determine the characteristics of participating and nonparticipating landowners. Data are derived from a 1998 landowner mail survey with a 53% response rate. Landowners implement upland conservation practices such as off-stream livestock water developments and rotational grazing more often than riparian fencing, riparian tree planting, and installing fish screens on irrigation diversions. The key factors in adoption of conservation practices include the use of irrigation, shared management decisions with a spouse, a belief in scientific experimentation, and discussion of conservation with others. The key factors predicting adoption of best management practices depended on the kind of best management practice implemented.
Affine structure on the Teichmuller spaces and period maps for Calabi-Yau manifolds

In this thesis, we prove that the Hodge metric completion of the Teichmuller space of polarized and marked Calabi-Yau manifolds is a complex affine manifold. As applications, we show that the extended period map from the completion space is injective into the period domain, that the completion space is a bounded domain of holomorphy and admits a complete Kahler-Einstein metric.
Bank interest rates on new loans to non-financial corporations– one first look at a new set of micro data

This note aims at contributing to the assessment of the empirical relevance of a set of determining factors for bank interest rates in Portugal. For such purpose, an innovative dataset is used, considering micro-information on most new loan operations to nonfi nancial corporations in the period June 2012 to February 2013. The results obtained point to the existence of a set of factors that induce discrimination in the setting of interest rates by the different customers. These factors include the risk attached to the customer, the size of the loan and the customer, their private or public nature, and the fact of having or not exporting activity.
Melanin-Concentrating Hormone Receptor-1 is Enriched in Lipid Rafts and the Effects of Lipid Raft Integrity on Receptor Signaling

Introduction Obesity . 2 Appetite hormones use G protein-coupled receptors . 3 Lipid rafts and caveolae . 6 Melanin-concentrating hormone . 9 MCH mouse models . 11 Melanin-concentrating hormone receptors . 14 MCHR-1 mouse models . 16 MCHR mutations are linked to obesity . 18 Caveolae, insulin, and adipocytes . 19 Caveolin-1 mouse models . 20 Significance . 22 Materials and Methods . 23 Results . 28 Discussion . 34 Conclusion . 4 7 Appendix I: Introductory Figures . 48 Appendix Il: Table ofResults . 60 Appendix Ill: Standard Recipes . 68 References . 73
What Derives Female Labor Force Participation in Muslim Countries? A Generalized Method of Moments Inference

Globalization and its social consequences have engendered newer trends that include increasing preferences of women to become economically active. Economic role of women has become a widely discussed topic in recent times in Muslim world. There are different perspectives and norms that determine their decision to become economically active i.e. to join the labor force. Hardly any study addresses this question with reference to Muslim world. Considering the emergence and rise of female employment in Muslim world, this paper formulates an empirical framework for the factors that affect female labor force participation (FLFP). Data is extracted from international databases World Development Indicators (WDI). For 41 Muslim countries the data was available for the time span of 2003-2013. To conduct rigorous statistical analysis of the relevant variables; we use a widely accepted robust estimation technique, known as Generalized Method of Moments (GMM). Findings of this study provide specific recommendations that are helpful in managing the emerging trends of women employment in Muslim world.
Face Recognition Based on Eigeneyes 1

Face recognition is a subject of emergent research that offers great challenges, mainly in adverse conditions. This paper proposes still a larger challenge: to perform face recognition from fragments of face images with approximately 20% of the face, based on eigeneyes techniques. This approach can work with partly occluded or nonideal illuminated images as well as in the cases when a person is disguised or wear a scarf, sun glasses, or mask. Even working with fragments of image, we achieved the recognition rate of 87%. Images were extracted from the Yale Face Database. 1 1
Evaluative Conditioning as Memory-Based Judgment

The article proposes a view of evaluative conditioning (EC) as resulting from judgments based on learning instances stored in memory. It is based on the formal episodic memory model MINERVA 2. Additional assumptions specify how the information retrieved from memory is used to inform specific evaluative dependent measures. The present approach goes beyond previous accounts in that it uses a well-specified formal model of episodic memory; it is however more limited in scope as it aims to explain EC phenomena that do not involve reasoning processes. The article illustrates how the memory-based-judgment view accounts for several empirical findings in the EC literature that are often discussed as evidence for dual-process models of attitude learning. It sketches novel predictions, discusses limitations of the present approach, and identifies challenges and opportunities for its future development.
A Nontrivial Product in the Stable Homotopy of Spheres

Let be an arbitrary odd prime number greater than eleven and be the mod Steenrod algebra. In this paper, it has proved that the product is nontrivial and converges to nontrivially of order in , where , by making use of the Adams spectral sequence.
Domestic saving and investment revised : can the Feldstein-Horioka equation be used for policy analysis?

Based on the relation between investment and domestic saving proposed by Feldsteinand Horioka (1980) to verify capital mobility, this study performs some exogeneitytests in order to determine the capacity of the FH equation of supporting andimplementing economic policies in Brazil. We then use the result of weak exogeneitytest to identify a structural vector autoregressive (SVAR) involving investment andsaving in order to evaluate the effect of exogenous shocks through impulse responsefunctions (IRFs) on both variables. The main findings of this paper are: a) theelasticity of domestic saving estimated using appropriate methods points out to highcapital mobility for Brazil; b) domestic saving is weakly exogenous in the FHequation; c) domestic saving is not strongly exogenous, therefore this equation shouldnot be used to make forecasts for the Brazilian economy; d) superexogeneity isaccepted for domestic saving, meaning that Lucas? criticism does not apply; and e)the IRFs showed that investment is sensitive to contemporaneous innovation onsaving and this effect lasts for a long time. Regarding to domestic saving, the responseof this variable to a non-expected shock on investment has a more is more complicatedescription. Initially domestic saving goes down. After some lags this movementchanges and domestic saving begins to react positively to the shock.
A Computational Intelligence Approach to Modelling Interstate Conflict: Forecasting and Causal Interpretations

The quantitative study of conflict management is concerned with finding models which are accurate and also capable of providing a causal interpretation of results. This dissertation applies computational intelligence methods to study interstate disputes. Both multilayer perceptron neural networks and Takagi-Sugeno neuro-fuzzy models are used to model interstate interactions. The multilayer perceptron neural network is trained in the Bayesian framework, using the Hybrid Monte Carlo method to sample from the posterior probabilities. It is found that the network is able to forecast conflict with an accuracy of 77.3%. A hybrid machine learning method using the neural network and the genetic algorithm is then presented as a method of suggesting how conflict can be brought under control. The automatic relevance determination approach and the sensitivity analysis are used as methods of extracting causal information from the neural network. The Takagi-Sugeno neuro-fuzzy model is optimised, using the Gustafson-Kessel clustering algorithm to partion the input space. It is found that the neuro-fuzzy model predicts conflict with an accuracy of 80.1%. The neuro-fuzzy model is also incorporated into the hybrid machine learning method to suggest how the identified conflict cases can be avoided. The casual interpretation is then formulated by a linguistic approximation of the fuzzy rules extracted from the neuro-fuzzy model. The major finding in this work is that the interpretations drawn from both the neural network and the neuro-fuzzy model are consistent.
Explicit Pricing Formulas for European Option with Asset Exposed to Double Defaults Risk

We derive analytical formulas for European call and put options on underlying assets that are exposed to double defaults risks which include exogenous counterparty default risk and endogenous default risk. The endogenous default risk leads the asset price to drop to zero and the exogenous counterparty default risk induces a drop in the asset price, but the asset can still be traded after this default time. A novel technique is developed to evaluate the European call and put options by first conditioning on the predefault and the postdefault time and then obtaining the unconditional analytic formulas for their price. We also compare the pricing results of our model with default-free option model and counterparty default risk option model.
Preliminary experimental verification of current content sliding modelling techniques

Most analytical studies focusing on the sliding of building contents usually make an assumption that the friction force-sliding displacement behaviour is elasto- plastic (e.g. friction coefficient remains constant during sliding). This preliminary study uses experimental data to verify if this assumption is reasonable. Shake table tests of a desk on common flooring materials were conducted to investigate the factors influencing friction behaviour, and to observe the behaviour of the contents under sinusoidal motion. Up to a 15% decrease in friction coefficient was observed with either an 80% increase in mass or a 20 times decrease in relative velocity, indicating that the friction coefficient is dependent on these two parameters. A comparison of the experimental and analytical sliding response of the desk under a single sinusoidal loading pattern on carpet flooring was conducted. Results show that the displacement amplitude of a single sliding excursion and the general sliding trend is well approximated using the elasto-plastic assumption. As such, despite the dependence of friction coefficient on sliding mass and velocity, the elasto-plastic behaviour assumption appears to be reasonable for the sinusoidal loading pattern examined in this paper.
Axisymmetric gravity currents on a cone

The previously unstudied problem of an axisymmetric gravity current released on a cone is investigated. A formulation of the problem based on the shallow-water equations, with and without entrainment and bottom drag, is given. Analytical asymptotic solutions are found and compared to numerical solutions of the equations. The inclusion of entrainment and drag is seen to play a significant role in limiting the propagation speed of the gravity current and also in altering the shape of the current. These theoretical predictions are compared to laboratory experiments and to two-dimensional numerical simulations. The shallow-water solutions including entrainment are found to provide a much better comparison with the experiments than the solutions without entrainment. In particular, the observed front speed and dilution of the head are in good agreement. Some applications to industrial and environmental problems such as dense gas dispersion are briefly discussed.
Yet another UFO in the X-ray spectrum of a high-z lensed QSO

Ultra-fast outflows (UFO) appear to be common in local active galactic nuclei (AGN) and may be powerful enough ($\dot{E}_{kin}$$\geq$1\% of L$_{bol}$) to effectively quench the star formation in their host galaxies. To test feedback models based on AGN outflows, it is mandatory to investigate UFOs near the peak of AGN activity, that is, at high-z where only a few studies are available to date. UFOs produce Fe resonant absorption lines measured above $\approx$7 keV. The most critical problem in detecting such features in distant objects is the difficulty in obtaining X-ray data with sufficient signal-to-noise. We therefore selected a distant QSO that gravitational lensing made bright enough for these purposes, the z=2.64 QSO MG J0414+0534, and observed it with XMM-Newton for $\approx$78 ks. } The X-ray spectrum of MG J0414+0534 is complex and shows signatures of cold absorption (N$_{H}\approx$4$\times$10$^{22}$ cm$^{-2}$) and of the presence of an iron emission line (E$\approx$6.4 keV, EW$=$95$\pm$53 eV) consistent with it originating in the cold absorber. Our main result, however, is the robust detection (more than 5$\sigma$) of an absorption line at E$_{int}\approx$9.2 keV (E$_{obs}\approx$2.5 keV observer frame). If interpreted as due to FeXXVI, it implies gas outflowing at $v_{out}\approx$0.3c. To our knowledge, this is the first detection of an UFO in a radio-loud quasar at z$\geq$1.5. We estimated that the UFO mechanical output is $\dot{E}_{kin}$$\approx$2.5$L_{bol}$ with $\dot{p}_{out}/\dot{p}_{rad}\approx$17 indicating that it is capable of installing significant feedback between the super-massive black hole (SMBH) and the bulge of the host galaxy. We argue that this also suggests a magnetic driving origin of the UFO.
GMACA ile Hareket Tespiti Yapılan Video Görüntülerde İnsan Hareketlerinin Tanınması

Bu makale arastirmasi kapsaminda insan hareketlerinin taninmasi, Genellestirilmis Coklu Cezbedici Hucresel Otomatlar (Generalized Multiple Attractor Cellular Automata(GMACA)) ile yapilan hareket tespit goruntuleri kullanilarak gerceklestirilmistir. GMACA Hucresel Otomatlarin birden fazla hucreye uygulanan turudur. Hucresel otomatlarin birden fazla hucreye uygulanmasi kural vektoru kullanilarak gerceklestirilir. Literatur arastirmasinda video goruntulerindeki insan hareketlerini tanima gorevinin; neleri icerecegi, onemi, uygulama alanlari vb. konular arastirilmistir. Insan hareketlerinin taninmasi bes asamada gerceklestirilir; insan nesnesinin tespiti ve takibi gerekir, insan nesnesine ait ozelliklerin cikarimi ve bu ozellikler kullanilarak harekete ait ozelliklerin cikarimi, basit hareketlerden olusan etkinliklerin taninmasi. Gelistirilen hareket tanima yonteminde ilk once goruntuler gri renk uzayina donusturulur. Daha sonra hareket tespiti icin kullanilacak GMACA kural vektoru olusturulur. GMACA kullanilarak hareket tespiti yapilir. Hareket tespit goruntulerinden HOG ozellik vektoru cikarilir ve elde edilen HOG ozellik vektorleri ait olduklari harekete gore etiketlendirilir. Bu sekilde veri seti olusturulur. Olusturulan veri seti capraz-dogrula yontemi ile egitim ve test veri setlerine ayristirilir. Insan hareketlerinin taninmasi SVM yontemi ile gerceklestirilir. Deneysel sonuclar karisiklik matrisi ile gosterilmistir. Karisiklik matrisi kullanilarak gelistirilen tanima yonteminin siniflandirma performansi ortaya konmustur. GMACA ile elde edilen hareket tespit goruntuleri ile yapilan hareket tanima uygulamasi mevcut arka plan cikarma calismalari kadar iyi sonuc vermistir. Elde edilen sonuclar GMACA’nin hareket tespitinde ve hareket tanima calismalarinda kullanilabilecegini gostermektedir. GMACA’nin zayif yani ikili oruntuler uzerinde uygulanabiliyor olmasidir. Gelistirdigimiz hareket tespit yontemi onluk tabandaki piksel degerlerinin ikilik tabana donusturulmesinden sonra uygulanabilir.