Miracle-dz/UniFAR-FTUs huggingface dataset:
Even in Emerging Markets, Technical Trading is Hazardous to Your Wealth

ABSTRACT This paper tests for the ability of a variety of technical indicators to generate excess returns at the individual stock level in the seven emerging and frontier markets of the Gulf region. While technical indicators show some early profitability promise, after controlling for the data snooping bias using the False Discovery Rate (FDR) methodology and non-synchronous trading, we fail to find any predictive ability or profitability for technical analysis. We arrive at a similar finding when assessing the risk-adjusted performance of a portfolio composed of stocks chosen based on technical indicators. The findings go to show the failure of technical analysis on the stock level. The findings are also evidence of the Gulf region markets being at least weak-form efficient and carry implications for investors choice of investment tools.
A preclinical small animal imaging platform combining multi-angle photoacoustic and fluorescence projections into co-registered 3D maps

We present the results on development of the 3D imaging platform combining photoacoustic tomography and fluorescence (PAFT) for preclinical and biological research. This combined multimodal imaging instrument addresses known deficiencies in sensitivity, spatial resolution, and anatomical registration of the individual imaging components. Multiangle photoacoustic projections, excited by an OPO operating in the near-infrared window, of a live anesthetized animal are used to reconstruct large volumes (30 cm3) that show deep anatomical vasculature and blood-rich tissues with resolutions exceeding 150 μm. A sCMOS camera is used for simultaneous co-registered multi-angle optical imaging. The images of a fluorescent dual-contrast agent are then reconstructed into a 3D volume using a tomographic algorithm. A separate 532-nm low-energy pulsed laser excitation is used for skin topography and imaging of superficial vasculature. All three imaging channels can be combined to produce spatially accurate in vivo volumes showing an animal’s skin, deep anatomical structures, and distribution of photosensitive molecular contrast agents. PAFT’s photoacoustic sensitivity was assessed using contrast agents in a phantom study. We demonstrate biomedical imaging application of PAFT’s combined imaging modalities by observing biodistribution of a dual-contrast agent injected intravenously to in vivo preclinical murine models.
A wavelet-based approach for business protocol discovery of web services from log files

Recently, business protocol discovery has taken more attention in the ﬁeld of web services. This activity permits a better description of the web service by giving information about its dynamics. The latter is not supported by the WSDL language which concerns only the static part. The problem is that the only information available to construct the dynamic part is the set of log ﬁles saving the runtime interaction of the web service with its clients. In this paper, a new approach based on the Discrete Wavelet Transformation (DWT) is proposed to discover the business protocol of web services. The DWT allows reducing the problem space while preserving essential information. It also overcomes the problem of noise in the log ﬁles. The proposed approach has been validated using artiﬁcially-generated log ﬁles.
Pulmonary Thromboembolism as a Manifestation of Paraneoplastic Disease in a Patient with Subclinical Hairy Cell Leukemia, a Challenge in Diagnosis and Treatment of Cancer

Thromboembolism in cancers is more common in advanced diseases and less common as an occult and in early phase of disease. Incidence of vascular thromboembolism is increased seven-fold when compared with non-cancer patients [1-3]. There is evidence that patients who developed thrombosis three months prior to or shortly after their diagnosis of cancer have poor prognosis [2]. In addition to venous thrombosis, arterial occlusion with stroke and anginal symptoms are relatively common among cancer patients and are possibly related to genetic predisposition. Cancer can affect mortality and morbidity even in very early phase, regardless of tumor volume, tumor type and stage. Other common causes of the thrombosis affect disease behavior, cancer patients with venous thrombosis do not have good prognosis, and also have an increased mortality compared with cancer patients without thrombosis [4-6]. The types of cancer with low volume starting thrombosis and thromboembolisms need to be defined, and their biologic and genetic features are not clear at this time.
Adaptivite Schemes for FEM Approximation of the Higher-Order Generalized Cahn-Hilliard Equations

The Cahn-Hilliard equation was introduced to model the phase separation in two-component alloys. This is one of the mathematical models most used to describe tumor growth through the evolution of healthy, cancerous and dead cells. In this work we present a numerical study of this equation by introducing higher-order derivatives with a nonlinear source term. Our objective is to solve the higher-order anisotropic problem with locally refined meshes in space using the finite element method for the generalized Cahn-Hilliard model. A phenomenological model that can describe the growth of a cancerous tumor will be treated. Numerical simulations are presented to illustrate the effects of higher-order terms on anisotropy and studies with space adaptivity strategy are also presented indicating its computational efficiency when compared to fixed meshes, especially in the case of anisotropic problems.
“This is our first big experiment”: Paris 1900 (1947) and the Eye Filmmuseum’s early collection-building

In this archive piece I share some of the outcomes of my research conducted at the Eye Filmmuseum in Amsterdam in 2017–2018 as scholar in residence, focussing on the institution’s acquisition and distribution of Nicole Vedrès Paris 1900 (1947) in the late 1940s. During my residency, I researched numerous early compilation films that made use of archival footage to explore and reflect on film history through film. These compilation films – of which Eye holds a large unspecified amount – were acquired by the Filmmuseum between its founding year in 1947 and the late 1960s, and were produced or compiled between the 1920s and the late 1960s. In the institution’s foundational years the Filmmuseum offered the films through its distribution catalogue and arranged to screen them in film clubs across the country to teach film history and to emphasize the value of its preservation work (Lameris 2017, 50). Today, these works tend to receive little attention among scholars interested in film appropriation, found footage or early cinema. They are often seen as reflecting purely documentary and educational aspirations and as being too overtly didactic and reductionist, rather than as exploring (film) history in a way that reflects the complexities and uncertainties of doing history. In particular, such films are dismissed because of what scholars today qualify – and for very good reasons – to be simplistic, teleological accounts of film history’s masterpieces. Furthermore, such films perpetuate the narrative of early cinema as a primitive step towards cinema’s maturity. As an example among the films held in Eye’s collection, one needs only consider the introductory intertitle to the historical compilation film Aan de wieg der jongste muze (At the cradle of the youngest muse), compiled by the Filmmuseum in 1961 from materials held in its collection, which states: ‘Film is only a lifetime old. At birth she was only futile and helpless as a baby’. I encountered such rhetorics in several of the compilation films I studied. Yet, in spite of such historiographic assumptions, which we consider problematic today, archival research on early and silent cinema and on the history of film historiography, I contend, benefits from studying early compilation films. Doing so may help us develop more nuanced understandings of how early cinema was represented in compilation films and may unearth exceptional compilation films that offer more complex representations of early cinema than tends to be acknowledged today. Moreover, such research may enable us to better understand how film history was analyzed through
A theoretical analysis of the fluid–solid interactions governing the removal of woody debris jams from cylindrical bridge piers

This paper proposes a theoretical model to describe previous laboratory observations of the dynamics of debris accumulations around bridge piers of cylindrical shape. The model is based on the assumption that the observed dynamics is mainly governed by dynamic changes of the point of application of the drag force exerted on a solid body formed by debris accumulated around a pier. A phase-plane analysis of the resulting nonlinear system of ordinary differential equations shows that the model captures the main patterns observed in previous laboratory experiments, including an oscillatory motion and the removal of debris from the pier by the flow. The model provides a theoretical basis for the analysis of the conditions required for debris jams to remain stable over long periods of exposure to impinging flow. Namely, the model indicates that the stability of debris accumulations primarily depends on geometrical asymmetry and on the length of the extension downstream of the pier. The former induces the torque required to rotate the jam about the pier, while the latter produces a stabilising effect after the body rotates.
A real time face emotion classification and recognition using deep learning model

Facial Detection and recognition research has been widely studied in recent years. The facial recognition applications plays an important role in many areas such as security, camera surveillance, identity verification in modern electronic devices, criminal investigations, database management systems and smart card applications etc. This work presents deep learning algorithms used in facial recognition for accurate identification and detection. The main objective of facial recognition is to authenticate and identify the facial features. However, the facial features are captured in real time and processed using haar cascade detection. The sequential process of the work is defined in three different phases where in the first phase human face is detected from the camera and in the second phase, the captured input is analyzed based on the features and database used with support of keras convolutional neural network model. In the last phase human face is authenticated to classify the emotions of human as happy, neutral, angry, sad, disgust and surprise. The proposed work presented is simplified in three objectives as face detection, recognition and emotion classification. In support of this work Open CV library, dataset and python programming is used for computer vision techniques involved. In order to prove real time efficacy, an experiment was conducted for multiple students to identify their inner emotions and find physiological changes for each face. The results of the experiments demonstrates the perfections in face analysis system. Finally, the performance of automatic face detection and recognition is measured with Accuracy.
Teaching Sustainability in Higher Education Institutions: Assessing Hospitality Students’ Sustainability Literacy

ABSTRACT Currently, higher education (HE) institutions include sustainability concepts into their programs. Previous literature examined the opportunities and challenges of integrating sustainability at an institutional, curricular, and instrumental level. We administered the Sulitest (sustainability literacy test) and a survey to first semester students at one international hospitality management school in Switzerland. While our students scored slightly higher than the Swiss average, the lowest scores recorded derived from the category knowledge – role to play, individual & systemic change. The survey demonstrated students’ high interest and strong support of sustainability in their academic and professional careers. Over 67% of respondents rated sustainability for their professional lives as extremely important. HE institutions have the opportunity to teach sustainability concepts that resonate with students. While research promotes embedding sustainability in all courses, our results show that students’ sustainability knowledge can improve in one intensive course. Further studies must be conducted to confirm retention and engagement.
Consumer Preference for Goat Meat in Jufra Area, Libya

This study was aimed to measure the consumers' preference of goat meat consumption in Jufra Area of Libya. A questionnaire was performed to obtain the data. Data were collected from 128 respondents randomly sampled from settlements in the four main towns of the area, Hun, Waddan, Sokana and Zela during March to Apri, 2015. The collected data were statistically analyzed for means and percentages determination. The study indicated that Goat meat is preferable by the Libyan consumer and ranks only the second to mutton with tendency to increase in demand when compared to other meat types. The data showed that the most preferred meat was that obtained from goats that slaughtered at 3 months old followed by 6 months, 9 months and one year and more than one year. The data indicated the most preferred meat by the consumers was that from male goats followed by those eat goat meat irrespective to sex and then by those prefer female meat. The data also indicated that the majority of the consumers eat goat meat every day. The result indicated that the most preferred cut was the leg followed by the forelimb, ribs, loin and finally the neck. The result revealed that the most preferred cooking method was dry cooking (Roasting) followed by moist cooking method (Braising followed by Stewing method). In general, it was concluded that; through extensive health education campaigns, goat meat is well cherished and efforts should be intensified to encourage its consumption.
Selection of the design of a hot heat exchanger of an automotive thermoelectric generator for an urban driving cycle

It is considered for combustion engines to have nearly 60-70% of fuel energy to be dissipated to the environment by the exhaust gases. Automobile thermoelectric generator (ATEG) application is proved to be a solution for increasing vehicle fuel economy by exhaust gas waste heat recovery. The overall efficiency of ATEG system highly depends on its hot heat exchanger, which is designed to remove heat from the exhaust gases to thermoelectric modules that generate electricity. Intensification of heat transfer in ATEG prototypes is usually achieved by using finning and tabulators. However, the modification of inner side of hot heat exchanger increases the hydraulic resistance of the exhaust system, which adversely affects the power and efficiency of the engine. In this work, we investigate the designs of hot heat exchangers with different configurations of the inner surface and evaluate their impact on the engine power during the modern urban driving cycle.
Near Rectilinear Halo Orbit Determination with Simulated DSN Observations

This paper presents the results of both a high-fidelity simulation of spacecraft orbit determination in a near rectilinear halo orbit (NRHO), as well as investigations of various aspects of NRHO operations, including NRHO insertion and long-horizon orbit maintenance. Others in the literature have examined the NRHO navigation problem with linear covariance analysis, but the highly-nonlinear dynamics of this orbit challenge the assumptions underlying such analyses. The present work builds on similar analysis performed by other authors to contribute a fuller understanding of the operational requirements for NRHO navigation. The present work serves as a check to the assumptions of previous studies and an independent verification of those results. Various trades are performed, including: NRHO insertion cleanup, short-horizon and long-horizon orbit maintenance, tracking cadence, tracking pass placement, filter type, measurement noise, and measurement type. Spacecraft state uncertainty estimates are evaluated as a function of time. Simulated range and range-rate measurements with the Deep Space Network (DSN) ground stations are used to model orbit determination accuracy. Orbit maintenance maneuvers are performed using both shorthorizon and long-horizon stationkeeping targeting. Monte Carlo analysis of orbit determination and stationkeeping is performed.
How to transform all multiple solutions of the Kemeny Ranking Problem into a single solution

Preference aggregation as a problem of a single consensus ranking determination, using Kemeny rule, for m rankings, including ties, of n alternatives is considered in the paper. The Kemeny Ranking Problem (KRP) may have considerably more than one optimal solutions (strict orders or permutations of the alternatives) and, hence, special efforts to deal with this phenomenon are needed. In the paper, there is proposed an efficient formal rule for convolution of the N multiple optimal permutations, the output profile β(N, n), into an exact single final consensus ranking, which can include ties. The convolution rule is as follows: in the final consensus ranking, alternatives are arranged in ascending order of their rank sums (total ranks) calculated for the output profile β; some two alternatives are considered to be tolerant if they have the same rank sums in β. The equivalent convolution rule can be also applied as follows: in the final consensus ranking, alternatives are arranged in descending order of row sums (total scores) calculated for a tournament table built for β; some two alternatives are deemed to be tolerant if they have the same row sums. It is shown that, for any alternative, its total rank and total score are equal in sum to the output profile dimension N×n. The convolution rules are validated using Borda count.
Integration of Wavelet and Recurrence Quantification Analysis in Emotion Recognition of Bilinguals

Background: This study offers a robust framework for the classification of autonomic signals into five affective states during the picture viewing. To this end, the following emotion categories studied: five classes of the arousal-valence plane (5C), three classes of arousal (3A), and three categories of valence (3V). For the first time, the linguality information also incorporated into the recognition procedure. Precisely, the main objective of this paper was to present a fundamental approach for evaluating and classifying the emotions of monolingual and bilingual college students. Methods: Utilizing the nonlinear dynamics, the recurrence quantification measures of the wavelet coefficients extracted. To optimize the feature space, different feature selection approaches, including generalized discriminant analysis (GDA), principal component analysis (PCA), kernel PCA, and linear discriminant analysis (LDA), were examined. Finally, considering linguality information, the classification was performed using a probabilistic neural network (PNN). Results: Using LDA and the PNN, the highest recognition rates of 95.51%, 95.7%, and 95.98% were attained for the 5C, 3A, and 3V, respectively. Considering the linguality information, a further improvement of the classification rates accomplished. Conclusion: The proposed methodology can provide a valuable tool for discriminating affective states in practical applications within the area of human-computer interfaces.
Impacts of climate change on Arctic sea ice

1 University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK 2 National Oceanography Centre, European Way, Southampton, SO14 3ZH, UK 3 Met Office, FitzRoy Road, Exeter, EX1 3PB, UK 4 Centre for Polar Observation and Modelling, Earth Sciences, University College London, London, WC1E 6BS, UK 5 Scottish Association for Marine Science, Oban, PA37 1QA, UK 6 Bristol Glaciology Centre, University of Bristol, Bristol, BS8 1SS, UK 7 Centre for Ocean and Atmospheric Sciences, School of Mathematics, University of East Anglia, Norwich, NR4 7TJ, UK 8 British Antarctic Survey, Cambridge, CB3 0ET, UK
Energy Efficiency in Security of 5G-Based IoT: An End-to-End Adaptive Approach

The challenging problem of energy efficiency in security of the Internet of Things (IoT) is tackled in this article. The authors consider the upcoming generation of mobile networks, 5G, as a communication architecture for the IoT. The concept of adaptive security is adopted, which is based on adjusting the security level as per the changing context. It has the potential of reducing energy consumption by adapting security rather than always considering the worst case, which is energy consuming. The consideration of 5G introduces new dynamics that can be exploited to perform more adaptation. The proposed solution introduces an intelligence in the application of security, from the establishment phase to the use phase (end-to-end). The security level related to the used cryptographic algorithm/key is adapted for each node during the establishment phase, so to match with the duration of the provided services. A new strategy is formulated that considers both IoT and 5G characteristics. In addition, a solution based on the framework of the coalitional game is proposed in order to associate the deployed objects with the optimized security levels. Moreover, the application of security is also adapted during the use phase according to the threat level. Trust management is used to evaluate the threat level among the network nodes, while existing works focus on performing the adaptation during the use phase. The proposed approach achieves more adaptation through the consideration of both IoT and 5G dynamics. The analysis and performance evaluations are conducted to show the effectiveness of the proposed end-to-end approach.
Investigation of Exopolysaccharide Production Capacities of Cyanobacterial Strains Isolated from Lake Uluabat, Turkey

Exopolysaccharides (EPS), important metabolites of microalgae and cyanobacteria, can be used as food additives, drug active substances, and in detergents, adhesives, and waste water treatment processes. Cyanobacterial EPSs are divided into two groups: the first group includes EPSs which are associated with the cell membrane (capsular, sheath), while the second group EPSs are released into the culture medium. The capsular polysaccharides can be found in the form of a sheath, capsule or mucilage. Cyanobacterial EPSs are heteropolymer structures consisting of monosaccharides, lipids, proteins and DNA. In this study, chemical characterization and metal binding properties of 3 different cyanobacterial (Cyanobium sp., Anabaena sp. and Limnothrix sp.) EPSs were investigated. Total protein concentrations ranged between 98,8 mg g-1 and 171,6 mg g-1 and total carbohydrate concentrations ranged between 252,1 mg g-1 and 320,5 mg g-1 per dry weight of the cyanobacterial EPS prepared in the study. Elemental compositions and metal (Cu+2, Cr+6 and Ni+2) adsorption properties of EPSs were determined with SEM-EDS analysis. According to elemental analysis EPS molecules mainly contained carbon (35,63-65,12%) and oxygen (21,39-40,27%).