Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of the Plane Wave Beamformed Acoustic Arrival Structure for the 1992 Barents Sea Coastal Tomography Test

Abstract : In an effort to solve the forward propagation problem associated with the 1992 Barents Sea Polar Front Experiment Tomography Test, the transmission of a 224 Hz pulse signal from a near bottom sound source to a vertical hydrophone array was simulated based on three-dimensional ray theory. based on three- dimensional ray theory. Through numerical raytracing, followed by eigenray searches and estimations of ray amplitudes, searches and estimations of ray amplitudes, phases and travel times, the arrival structure as a function of time and elevation angle was constructed. The simulation was performed for both a two-dimensional and three-dimensional modeled ocean environment in order to examine the significance of three-dimensional effects. The predicted arrival structures compare well with the observed data. Three-dimensional effects proved to be significant only for the latest arrivals. Tomography, Eigenray, Plane wave, Beamformed.
Feature Detector: a support system for tracking satellite detected dynamic and permanent features

Even with today’s technologies many tasks relies on humans to be completed correctly. Engineers must monitor steps in large chains of operations, and verify the results before the next process is allowed to continue. In many such systems, a lot of useful data passes by without ever been stored for efficient future usage. Even though some operations must be verified by an experienced human eye, many, if not all, could benefit from computed assistance. When processing satellite imagery there are a lot of steps involved before there is a final product. This thesis examines one specific part of the process, how to determine if a feature observed is permanent or not. A self learning geographical information system implementation that can determine the state of specific features will be presented. The system is capable of filtering out permanent installations from vessel traffic in highly dense areas. Further we’ll see that with such a system at the core, other useful functionality can easily be extended on top of it. Such functionality could be tracking of vessels, oil spills or ice floes, the latter two which have been implemented. With such a system at hand, the day to day tasks of engineers monitoring satellite observations can be made easier and less error prone. In addition such a historical view of the data can help with improving existing services as well as those still under development.
BEHAVIORAL FINANCE-EVIDENCE FROM TEHRAN STOCK EXCHANGE

A capital market is a vast and controversial issue in financial matters and especially behavioural finance. Indeed, behavioural finance is aim to survived the influence of the psychological variables on financial markets transformation. It should be noted that financial investors may have different level of rational behaviour, which leads to different kinds of effects, which can elaborate market inconsistency. Classical finance assumes the investors as rational peoples who try to select the most lucrative and efficient portfolio considering expected financial risk. Behavioural finance model mainly focus on psychological parameters. Tehran Stock Exchange (TSE) is affected by many financial and economic variables. Investor in this financial market is affected by different data. Present study is aim to examine psychological variables beside political, economic and capital market features factors. Research data collects in 2015 and analysis by LISREL software. The results reveal that political, economic and psychological parameters respectively are the most important variables which affect the investor decision making behaviour. The internal financial reports and market return are less effective factor in their financial decision behavior
Education and Entrepreneurship in Industrialized Countries: A Meta-analysis

This paper provides a meta-analytical review of empirical studies into the impact of schooling on entrepreneurship selection and performance. We first describe the main effects found in the current entrepreneurship literature. We then explain the variance in results across the hundreds of empirical studies by means of an analysis of variance. Five main conclusions result from this meta-analysis. First, we find that the impact of education on selection into entrepreneurship is neither positive nor negative. Second, the effect of education on performance is positive and significant. Third, the return to a marginal year of schooling in terms of the income it generates is 6.1 percent in the U.S.A. Fourth, the effect of education on earnings is smaller for entrepreneurs than for employees in Europe, but equal or larger in the U.S.A. The fifth conclusion from the meta-analysis is the most striking and pertains to the estimated effect of education on performance: all results obtained so far are potentially biased. Estimation and identification strategies used to identify the effect of education on performance have merely measured the (conditional) correlation between education and performance rather than the causal effect, which is the estimate of interest. We finally conclude that the entrepreneurship literature on education can greatly benefit from the technical sophistication used to estimate the returns to schooling for employees by means of twins studies, field experiment or instrumental variables approaches.
Life on the Desert Edge: Seven Thousand Years of Settlement in the Northern Dongola Reach, Sudan

A two-volume report on the Sudan Archaeological Research Society's multi-disciplinary and multi-period project in the Northern Dongola Reach, Sudan. The project surveyed an 80km stretch of land on the east side of the Nile from 1993 to 1996, and conducted one season of excavation in 1997. The 1st volume of the report includes a description of the project's strategies for identifying and recording sites, a preliminary discussion of a geomorphological investigation of the age and sedimentology of the Holocene alluvial sequence of the Nile, a Gazetteer of Sites recorded by the survey, a brief description of the sites tested by excavations, and a catalogue of pottery collected by the survey. The 2nd volume includes specialist reports on pottery, lithics, human and animal remains etc. from the survey and the associated excavations. It also includes a short synthetic discussion of the results of the project, broken down into broad chronological periods from the Neolithic and Kerma periods through to the 20th century.
Injecting Conceptual Constraints into Data Fabrics

Unlike traditional sources managed by DBMSs, data lakes do not provide any guarantee about the quality of the data they store, which can severely limit their use for analysis purposes. The recent notion of data fabric, which introduces a semantic layer allowing uniform access to underlying data sources, makes it possible to tackle this problem by specifying conceptual constraints to which data sources must adhere to be considered meaningful. Along these lines, in this discussion paper, we exploit the data fabric approach by proposing a general methodology for data curation in data fabrics based on: (i) the specification of integrity constraints over a conceptual representation of the data lake and (ii) the automatic translation and enforcement of such constraints over the actual data. We discuss the advantages of this idea and the challenges behind its implementation.
8. The Meaning of Teachers’ Negations in Hong Kong Classrooms Interpreted from their Co-occurring Gestures

Lopez-Ozieblo, R. 2023. The Meaning of Teachers’ Negations in Hong Kong Classrooms Interpreted from their Co-occurring Gestures. In: Roitman, M. (ed.) Negatives and Meaning: Social Setting and Pragmatic Effects: Using Negatives in Political Discourse, Social Media and Oral Interaction, pp. 203–238. Stockholm: Stockholm University Press. DOI: https://doi.org/10.16993/bcd.h. License: CC BY 4.0. 8. The Meaning of Teachers’ Negations in Hong Kong Classrooms Interpreted from their Co-occurring Gestures Renia Lopez-Ozieblo
A Deep Learning CNN based Approach to the Problem of Crypto-Currency Prediction

After the invention of Bitcoin by a man named Satoshi Nakamoto along with other blockchain-based person-to-person payment systems, the cryptocurrency market has instantly gained popularity. Because of this, that is, the volatility of the various cryptocurrency prices. This attracts much attention from both the investors and the researchers. The task of forecasting the prices of crypto-currencies because of the static prices and the arbitrary effects in the market is quite challenging. Cryptocur-rency price forecasting models that are available now mainly focus on analysing extrinsic factors, like macro-financial indicators, data linked to the blockchain, and data from social media – with the goal of enhancing the prediction accuracy. However, the intrinsic noise present in the raw data, caused by market and political conditions worldwide, is complex to interpret. In our research we propose a multiple input convolutional neural network model, specifically a convolutional neural network model for the prediction of future cryptocurrency price. Generally, RNNs and LSTMs are used for problems dealing with timeseries data. We used the concept of residual networks on 1-Dimensional convolutional networks to solve the problem of predicting the price of Bitcoin, the most popular cryptocurrency out there at the moment. Furthermore, we conduct additional experiments on ether, the cryp-tocurrency of Ethereum to further confirm that even CNNs can work equally well, if not better in comparison to the widely used LSTM neural network models.
A Low-Profile Wideband Circularly Polarized Crossed-Dipole Antenna

A low-profile crossed dipole antenna with wide bandwidth is investigated in this letter. The double-sided printing crossed dipoles consisting of four-stepped rectangular patches are fed by a pair of vacant-quarter printed rings, generating circularly polarized radiation. Two adjacent axial-ratio (AR) passbands with AR < 3 dB are generated due to the stepped rectangular patches, and they are merged together by adding an additional dielectric slab above the ground plane, resulting in a very wide AR bandwidth. Also, an irregular ground plane is used for the antenna, which can desirably enhance the boresight gain without involving high-profile cavity. To verify the feasibility of the proposed design, a prototype operating at C-band has been fabricated and measured. Reasonable agreement between the simulated and measured results is obtained. The prototype has a low profile of 0.13 λ0 (in terms of the center frequency of passband), a 10-dB impedance bandwidth of 66.9%, a 3-dB AR bandwidth of 55.1%, and an average gain of approximately 10.4 dBic within passband.
Methods for automation of vascular lesions detection in computed tomography images

This thesis presents a framework for the detection and diagnosis of vascular lesions with a special emphasis on coronary heart disease. Coronary heart disease remains to be the first cause of mortality worldwide. Typically, the problem of vascular lesion identification has been solved by trying to model the abnormalities (lesions). The main drawback of this approach is that lesions are highly heterogeneous, which makes the detection of previously unseen abnormalities difficult. We have selected not to model lesions directly, but to treat them as anomalies which are seen as low probability density points. We propose the use of two classification frameworks based on support vector machines (SVM) for the density level detection problem. The main advantage of these two methods is that the learning stage does not require labeled data representing lesions, which is always difficult to obtain. The first method is completely unsupervised, whereas the second one only requires a limited number of labels for normality. The use of these anomaly detection algorithms requires the use of features such that anomalies are represented as points with low probability density. For this purpose, we developed an intensity based metric, denoted concentric rings, designed to capture the nearly symmetric intensity profiles of healthy vessels, as well as discrepancies with respect to the normal behavior. Moreover, we have selected a large set of alternative candidate features to use as input for the classifiers. Experiments on synthetic data and cardiac CT data demonstrated that our metric has a good performance in the detection of anomalies, when used with the selected classifiers. Combination of other features with the concentric rings metric has potential to improve the classification performance. We defined an unsupervised feature selection scheme that allows the definition of an optimal subset of features. We compared it with existent supervised feature selection methods. These experiments showed that, in general, the combination of features improves the classifiers performance, and that the best results are achieved with the combination selected by our scheme, associated with the proposed anomaly detection algorithms. Finally, we propose to use image registration in order to compare the classification results at different cardiac phases. The objective here is to match the regions detected as anomalous in different time-frames. In this way, more than attract the physician's attention to the anomaly detected as potential lesion, we want to aid in validating the diagnosis by automatically displaying the same suspected region reconstructed in different time-frames
Structural Dynamics and Susceptibility of Anti-Alzheimer’s Drugs Donepezil and Galantamine against Human Acetylcholinesterase

Alzheimer’s disease (AD) is a major public health problem worldwide due to an increase in the elderly population. The current pharmacotherapy for the early stages of AD is mainly dependent on cholinesterase inhibitors. Two of the most commonly used anti-AD drugs, donepezil (DPZ) and galantamine (GLM), are selective inhibitors for human acetylcholinesterase ( h AChE). However, the inhibitory activity of DPZ on h AChE was more potent than GLM by ~85 times. To better understand the molecular basis for differences in mode of inhibition of h AChE by both drugs, molecular dynamics (MD) simulation was performed. The results showed that the active site residues of h AChE/DPZ had the higher hydrogen bond occupancies as compared to h AChE/GLM. Nevertheless, the 2 drugs directly formed hydrogen bonds with the catalytic residue H447 of h AChE. The per-residue free energy decomposition suggested that DPZ interacted with the residues in peripheral anionic site of h AChE, resulting in the greater binding affinity of DPZ than that of GLM toward h AChE. The binding free energy calculation based on MM-PBSA and MM-GBSA methods indicated that van der Waal interactions played a predominant role as the driving force for binding process of DPZ and GLM to h AChE. Moreover, the predicted total binding free energy of h AChE/DPZ was stronger than h AChE/GLM, which was consistent well with the experimental data. We hope that our findings provide useful information for further design of novel h AChE inhibitors
Mental Health and Burnout Syndrome Among Postgraduate Students in Medical and Multidisciplinary Residencies During the COVID-19 Pandemic in Brazil: Protocol for a Prospective Cohort Study

Background: The COVID-19 pandemic has led to high levels of physical, psychological, and social stress among health care professionals, including postgraduate students in medical and multidisciplinary residencies. This stress is associated with the intense fear of occupational exposure to SARS-CoV-2, the virus known to cause COVID-19. These professionals are at risk of developing physical and mental illnesses not only due to the infection but also due to prolonged exposure to multidimensional stress and continued work overload. Objective: This study aims to evaluate the prevalence of symptoms suggestive of mental disorders and burnout syndrome and determine the risk factors for burnout among postgraduate students in medical and multidisciplinary residencies in Brazil during the COVID-19 pandemic. Methods: For this prospective cohort study with parallel groups, participants were recruited between July and September 2020 to achieve a sample size of at least 1144 participants. Research instruments such as Depression, Anxiety, and Stress Scale; Patient Health Questionnaire; Brief Resilient Coping Scale; and Oldenburg Burnout Inventory will be used to collect data. Data will be collected in 2 waves: the first wave will include data related to sample characterization and psychosocial evaluation, and the
Structural , Elastic , and Electronic Properties of Deformed Carbon Nanotubes under Uniaxial Strain . "

We performed ab-initio density functional simulations to study the structural and growth properties of short carbon nanobells. We used a real space approach and the linear combination of atomic orbitals (LCAO) formalism. In the nitrogen-doped carbon nanobells, the nitrogen atoms that are attracted to the open-edge sites of the carbon nanobells play an important role in the growth of the short carbon nanostructures. We present the calculated electronic structure of the short nanobells. The calculated local density of states of the nanobells revealed field emission characteristics that agree with experimental observations. properties with a turn-on field of electron
On the category of finite-dimensional representations of $\OSPrn$: Part I

We study the combinatorics of the category F of finite-dimensional modules for the orthosymplectic Lie supergroup OSP(r|2n). In particular we present a positive counting formula for the dimension of the space of homomorphism between two projective modules. This refines earlier results of Gruson and Serganova. Moreover, for each block B of F we construct an algebra A(B) whose module category shares the combinatorics with B. It arises as a subquotient of a suitable limit of type D Khovanov algebras. It will turn out that A(B) is isomorphic to the endomorphism algebra of a minimal projective generator of B. This provides a direct link from F to parabolic categories O of type B or D, with maximal parabolic of type A, to the geometry of isotropic Grassmannians of types B/D and to Springer fibres of types C/D. We also indicate why F is not highest weight in general.
A Few Logs Suuce to Build (almost) All Trees (i)

A phylogenetic tree (also called an \evolutionary tree") is a leaf-labelled tree which represents the evolutionary history for a set of species, and the construction of such trees is a fundamental problem in biology. Here we address the issue of how many sequence sites are required in order to recover the tree with high probability when the sites evolve under standard Markov-style i.i. d. mutation models. We provide analytic upper and lower bounds for the required sequence length, by developing a new (and polynomial time) algorithm. In particular we show that when the mutation probabilities are bounded the required sequence length can grow surprisingly slowly (a power of log n) in the number n of sequences, for almost all trees.
Comparative petrological studies of some alkaline basalts, western Pannonian Basin, Austria

Alkaline basaltic volcanism commenced in the Late Pliocene and continued until the early Pleistocene. Moreover, the alkaline basaltic magmas were developed in response to passive upwelling and decompressional melting of asthenospheric mantle material. The volcanism is characterized by mafic rock types ranging from highly undersaturated nephelinites (Stradnerkogel & Waltrafelsen) to basanites and alkali basalts (Burgenland).
Collateral Versus Project Screening: A Model of Lazy Banks

Many economists argue that the primary economic function of banks is to provide cheap credit, and to facilitate this function, they advocate the strict protection and enforcement of creditor rights. But banks can serve another important economic function: through project screening they can reduce the number of project failures and thus mitigate their private and social costs. Strict protection of creditor rights would leave the tradeoff between these two banking functions to the market. In this paper, we show that because of market imperfections in the banking industry, strong creditor protection may lead to market equilibria in which cheap credit is inappropriately emphasized over project screening. Restrictions on collateral requirements and the protection of debtors in bankruptcy proceedings may redress this imbalance and increase credit-market efficiency.
Poltica de desarrollo regional o poltica regional de desarrollo

El autor del ensayo, luego de destacar la falacia de la convergencia interregionalque postula la ortodoxia neoclasica, aborda el analisis de la conveniencia de formularuna politica publica regional no sectorial, inclinandose por una Politica Regionalde Desarrollo (PRD), en contraste con otros enfoques existentes. De igual manera,el ensayista subraya que la mayor parte de los estudios empiricos divulgadosen la decada de los noventa coincide en senalar que la brecha entre el crecimientoeconomico y el ingreso interregionales (interdepartamentales) crece cada vez mas,concluyendo que su solucion requiere de un proyecto colectivo y su correspondientegestion territorial. __________ABSTRACT:The author of the rehearsal, after the fallacy of the interregional convergence thatpostulates the neoclassical orthodoxy, highlighting approaches the analysis of theconvenience of no formulating a regional public politics sectoral, leaning for a RegionalPolitcs of the Development (RPD), in contrast with other existent focuses. Ina same way, the essayist underlines that most of the empiric studies disclosed in thedecade of the ninety coincides in pointing out that the breach between the economicgrowth and the interregional entrance (interdepartmental) grows more and more,concluding that her solution requires of a collective project and its correspondingterritorial administration.
Anomaly detection using hardware performance counters on a large scale deployment

—The last recent years witnessed a massive and fast deployment of Internet of Things (IoT) devices. Most of them have not been designed with a careful analysis of security requirements, which makes them likely to include multiple vulnerabilities. Moreover, as these devices include various communication interfaces, they have become a privileged target for attackers. As a consequence, large scale attacks, such as Mirai, must be considered seriously and it is crucial to design and implement protection and intrusion detection mechanisms to mitigate the threats associated to the use of IoT devices in our daily activities as well in critical environments. This paper proposes an anomaly detection approach, in the particular context of a large scale deployment of identical IoT devices. Furthermore, we consider an attacker who can install and execute malicious software while continuing to execute legitimate software, in order to stay invisible as much as possible. The approach is based on the statistical analysis of Hardware Performance Counters (HPC) collected at a regular basis from these identical devices, and to highlight the outliers corresponding to signiﬁcant deviations with respect to normal usage scenarios. This idea relies on the intuition that it is very difﬁcult for the attacker to add some malicious software in a corrupted device without perturbing the HPCs. This paper presents this approach and the ﬁrst experiments carried out to assess its relevance.