Miracle-dz/UniFAR-FTUs huggingface dataset:
An assessment of positive illusions of the physical attractiveness of romantic partners

Positive illusions about a partner’s physical attractiveness occur when individuals’ ratings of their partner’s attractiveness are more positive than more objective ratings. Ratings that may serve as a’’reality benchmark’ include ratings by the partner him/herself and observer ratings. The present study compared the effects of using different reality benchmarks on the strength of positive partner physical attractiveness illusions (n = 70 couples). Results showed that individuals positively biased both their own and their partner’s physical attractiveness. As a consequence, using a partner’s self-ratings as a reality benchmark results in an underestimation of positive illusions. Presenting participants with photographs had a small effect on physical attractiveness ratings provided by women, showing that photographs, to some extent, might constrain positive illusions.
Bayesian Optimization on Fast Nearest Neighbor Approximation

Computing nearest neighbor matches in high-dimensional space is a computationally expensive task. It constitutes a major component of many computer vision problems. Linear search is the only possible method to solve these high dimensional problems exactly. Approximate algorithms can significantly improve speedup at cost of little loss of accuracy. But these approximate algorithms vary based on the type of dataset and hence choosing optimum parameters for these approximate algorithms is the contribution of Fastest Approximate Nearest Neighbor (FLANN) algorithm. This algorithm uses an optimization technique to choose a parameter set for an algorithm among a set of algorithms that is the best possible approximator for given precision and memory/speed preference for the data. The proposed optimization technique improves the query time with improved precision over current FLANN implementation. The results show that bayesian optimization can reduce the number of queries required to reach the optimal parameters. The parameters thus selected were more close to optimum solution than the original implementation. Our implementation is also available as open sourece demo which we intend to further integrate in the FLANN library.
Title ARF 1 and ARF 4 regulate recycling endosomal morphology and retrograde transport from endosomes to the Golgi apparatus

Small GTPases of the ADP-ribosylation factor (ARF) family, except for ARF6, mainly localize to the Golgi apparatus, where they trigger formation of coated carrier vesicles. We recently showed that class I ARFs (ARF1 and ARF3) localize to recycling endosomes, as well as to the Golgi, and are redundantly required for recycling of endocytosed transferrin. On the other hand, the roles of class II ARFs (ARF4 and ARF5) are not yet fully understood, and the complementary or overlapping functions of class I and class II ARFs have been poorly characterized. In this study, we find that simultaneous depletion of ARF1 and ARF4 induces extensive tubulation of recycling endosomes. Moreover, the depletion of ARF1 and ARF4 inhibits retrograde transport of TGN38 and mannose-6-phosphate receptor from early/recycling endosomes to the trans-Golgi network (TGN) but does not affect the endocytic/recycling pathway of transferrin receptor or inhibit retrograde transport of CD4-furin from late endosomes to the TGN. These observations indicate that the ARF1+ARF4 and ARF1+ARF3 pairs are both required for integrity of recycling endosomes but are involved in distinct transport pathways: the former pair regulates retrograde transport from endosomes to the TGN, whereas the latter is required for the transferrin recycling pathway from endosomes to the
The Fama-French and Momentum Portfolios and Factors in the UK

The primary aim of this paper is to make available the Fama-French and Momentum portfolios and factors for the UK market to the wide community of UK academic and post-graduate researchers. As Michou, Mouselli and Stark (2007) note, there is no freely downloadable equivalent to the data on Ken French’s US website, and this paper is directed at remedying this situation. We depart from the majority of previous UK studies (with the exception of Agarwal and Taffler, 2008) by forming portfolios on 30th September each year, which we argue is more appropriate for the UK. Although we construct factors and portfolios for the UK, by extending tests to portfolios formed on differing bases, we add to the caution expressed in Michou, Mouselli and Stark (2007) on whether such factor models completely capture risk in the UK. Our recommendation is that any tests of long run abnormal returns in UK be based on characteristic-matched portfolios.
Examining the Impact of Regional Integration on Economic Development UN Sabbatical Leave Programme Report

This document presents research undertaken as part of the United Nations Sabbatical Leave Programme. The investigation examines the impact of regional integration on development, particularly in Least Developed Countries (LDCs). It evaluates whether regional integration contributes to achieving development outcomes like economic growth, addressing inequality, and diversification. The analysis covers over 100 countries for the period 1980-2013, and the development clusters for the empirical analysis are LDCs and low-income countries. The impact on Asia-Pacific in comparison to other developing regions is also estimated.
Fast, Generic, and Reliable Control and Simulation of Soft Robots Using Model Order Reduction

Obtaining an accurate mechanical model of a soft deformable robot compatible with the computation time imposed by robotic applications is often considered an unattainable goal. This paper should invert this idea. The proposed methodology offers the possibility to dramatically reduce the size and the online computation time of a finite element model (FEM) of a soft robot. After a set of expensive offline simulations based on the whole model, we apply snapshot-proper orthogonal decomposition to sharply reduce the number of state variables of the soft-robot model. To keep the computational efficiency, hyperreduction is used to perform the integration on a reduced domain. The method allows to tune the error during the two main steps of complexity reduction. The method handles external loads (contact, friction, gravity, etc.) with precision as long as they are tested during the offline simulations. The method is validated on two very different examples of FEMs of soft robots and on one real soft robot. It enables acceleration factors of more than 100, while saving accuracy, in particular compared to coarsely meshed FEMs and provides a generic way to control soft robots.
A multidimensional numerical scheme for two-fluid relativistic magnetohydrodynamics

The paper describes an explicit multi-dimensional numerical scheme for Special Relativistic Two-Fluid Magnetohydrodynamics of electron-positron plasma and a suit of test problems. The scheme utilizes Cartesian grid and the third order WENO interpolation. The time integration is carried out using the third order TVD method of Runge-Kutta type, thus ensuring overall third order accuracy on smooth solutions. The magnetic eld is kept near divergence-free by means of the method of generalized Lagrange multiplier. The test simulations, which include linear and non-linear continuous plasma waves, shock waves, strong explosions and the tearing instability, show that the scheme is suciently robust and conrm its accuracy.
Environmental Impact Assessment Using D-Vikor Approach

Environmental impact assessment (EIA) is an open and important issue depends on factors such as social, ecological, economic, etc. Due to human judgment, a variety of uncertainties are brought into the EIA process. With regard to uncertainty, many existing methods seem powerless to represent and deal with it effectively. A new theory called D numbers, because of its advantage to handle uncertain information, is widely used to uncertainty modeling and decision making. VIKOR method has its unique advantages in dealing with multiple criteria decision making problems (MCDM), especially when the criteria are non-commensurable and even conflicting, it can also obtain the compromised optimal solution. In order to solve EIA problems more effectively, in this paper, a D-VIKOR approach is proposed, which expends the VIKOR method by D numbers theory. In the proposed approach, assessment information of environmental factors is expressed and modeled by D numbers. And a new combination rule for multiple D numbers is defined. Subjective weights and objective weights are considered in VIKOR process for more reasonable ranking results. A numerical example is conducted to analyze and demonstrate the practicality and effectiveness of the proposed D-VIKOR approach.
Size Matters: Covariance Matrix Estimation Under the Alternative

The purpose of this paper is to investigate, using Monte Carlo methods, whether or not Hall's (2000) centered test of overidentifying restrictions for parameters estimated by Generalized Method of Moments (GMM) is more powerful, once the test is size-adjusted, than the standard test introduced by Hansen (1982). The Monte Carlo evidence shows that very little size-adjusted power is gained over the standard uncentered calculation. Empirical examples using Epstein and Zin (1991) preferences demonstrate that the centered and uncentered tests sometimes lead to different conclusions about model specification.
Lepiota maculans, an Unusual Mushroom Rediscovered after 105 years

Abstract During a survey of macrofungi in the Great Smoky Mountains National Park in the summer of 2009, a species of Lepiota was recorded. This specimen is distinct in having pink to salmon to orange colors on the fruiting body and a pink spore deposit. After comparison with type material and a survey of the literature, we conclude this species is L. maculans Peck, described originally and known only from one collection in Missouri. Phylogenetic analysis of DNA sequence data supports placement within Lepiota of the Agaricaceae despite possessing a pink spore deposit. A complete morphological description, a description of the holotype, illustrations, and photographs are presented. This is the first report of L. maculans since its original description in 1905.
2 First Attempt : Masking with One-Time Pads

Analytics such as training machine learning models on sensitive real-world data promise improvements to everything from medical screening to disease outbreak discovery. Such sensitive data is becoming increasingly available through the widespread use of mobile devices for example. However, large-scale collection of sensitive data entails risks to users’ sensitive information. The general setting for secure analytics is to consider n parties that have sensitive data (such as temporal location data) and are not willing to share such data individually, but are willing to share an aggregate computation over joint data. Computation in this case can span from analytics such as SQL queries to learning.
Structure and superconducting characteristics of magnesium diboride, substitution of boron atoms by oxygen and carbon

An x-ray analysis of MgB2-based materials shows that they contain MgB2 and MgO phases. According to a quantitative Auger analysis (taken after removing the oxidized surface layer by Ar ion etching in the microscope chamber) the MgB2 phase contains some amount of oxygen that approximately corresponds to the composition MgB2.2-1.7O0. 4-0.6. Rietveld refinement of the MgB2 phase, based on EDX data with varying B/O content, leads to the composition MgB1.68-1.8O0. 2-0.32. Ab-initio modelling of boron substitution by oxygen in MgB2 (ΔHf = −150.6 meV/atom) shows that this is energetically favourable up to the composition MgB1.75O0.25 (ΔHf = −191.4 meV/atom). In contrast to carbon substitution, where very small levels of doping can dramatically affect the superconducting characteristics of the material with concomitant changes in the electron density, oxygen substitution results in very little change in the superconducting properties of MgB2. The formation of vacancies at the Mg site of both MgB2 and substituted MgB1.75O0.25 was modelled as well, but has shown that such processes are energetically disadvantageous (ΔHf of Mg0.875B2 and Mg0.75B1.75O0.25 are equal to −45.5 and −93.5 meV/atom, respectively).
Time-Dependent Coastal Upwellingl

Linear and nonlinear two-layer ocean circulation models of coastal upwelling on an I-plane are driven by time-dependent winds and solved numerically. Longshore variations in the circulation are neglected and offshore variations in the winds are specified. A technique for generating a realistic broad frequency-band wind stress from a kinetic energy spectrum of wind speed is developed. When results from the two models are compared, nonlinearities are found to be unimportant in explaining the basic upwelling dynamics. However, they do provide a mechanism for wave-wave interactions which broaden all spectral peaks. In the nonlinear model coherence-squared spectra between the winds and zonal current components in the upwelling zone indicate highest coherence at lowest frequencies for both layers, accompanied by a 1800 phase shift from upper to lower layer at frequencies <3 cycles per day. Similar analyses for winds VB meridional current components and winds VB pycnocline height anomalies show a coherence-squared maximum for winds of 5-day period. In the frequency band below and including the inertial, remarkable similarities are observed between the results of the nonlinear model and actual ocean current autospectra. oceanic spectra reveals remarkable similarity in the frequency band below and including the inertial. 2. The two-layer model The following discussion, after O'Brien and Hurlburt (1972), briefly describes the formulation of a twolayered, two-dimensional ocean with bottom topography. For a complete discussion of the n-layered ocean problem, their article should be consulted. Consider a two-layered ocean on an i-plane with all longshore variations neglected. The coordinate system is Cartesian with s increasing upward and x increasing eastward (Fig. 1). The governing equations are au1 au1 a -+"1-+ g-:-(hl+ ht+ D) at ax ax a'll1 -, axI = ftt+(".-,.r.)/(pil)+A '1) O~l -, OXI (2)
DIRECTED TECHNOLOGICAL CHANGE: A KNOWLEDGE-BASED MODEL

In a knowledge-based growth model where skilled workers are used in innovation and production, skill-biased technological change may lower average R&D productivity via an innovation possibilities frontier effect that eliminates scale effects. We show that skill-biased technological change increases the skill premium even if the elasticity of substitution between skilled and unskilled workers is less than two. Trade between developed countries promotes skill-biased technological change, thus raising wage inequality. Trade between developed and developing countries has differing effects: it induces relatively skill-replacing technological change and lowers wage inequality in the developed country but has the opposite effects in the developing country. Finally, we show that trade can stimulate or hurt economic growth.
LncRNA H 19 promotes proliferation and invasion in A 375 human melanoma cell line

Objective: To determine the effects of H19 gene on the proliferation and invasion of A375 human melanoma cells. Methods: A375 cells were infected with a lentiviral vector overexpressing H19 or transfected with H19 RNA interference constructs. The proliferation and invasion of A375/H19+ cells were measured by MTT cell viability and transwell assays, respectively. The mRNA and protein expression levels of matrix metalloproteinase 2 (MMP2) and MMP9 were measured by quantitative PCR (qPCR) and Western blotting, respectively, and the protein expression of Akt, phosphorylated Akt (p-Akt), Slug and E-cadherin were examined by Western blot analysis. Results: The optical density value of A375/H19+ cells increased after incubation with MTT reagent for 12 h (P < 0.05), and the transwell assay showed that the average penetration rate of A375/H19+ cells significantly increased (P < 0.001). The expression levels of MMP2 and MMP9 were significantly increased in A375/H19+ cells, as determined by qPCR and Western blotting (P < 0.001). Moreover, A375/H19+ cells had upregulated levels of Slug and p-Akt and downregulated E-cadherin (P < 0.001). The weight and volume of A375/H19+ cell xenografts in nude mice were significantly increased, but its inhibition rate was smaller (P < 0.05 and P < 0.001, respectively). Conclusions: The results of this study showed that H19 overexpression promoted the proliferation, invasion, and growth of A375 cells. In addition, it upregulated the mRNA and protein expression levels of MMP2 and MMP9, which in turn promoted cell invasion. Furthermore, H19 appeared to enhance Akt phosphorylation, directly suppress E-cadherin, and upregulate Slug expression to promote A375 cell invasion.
Efficient Opinion Summarization on Comments with Online-LDA

Customer reviews and comments on web pages are important information n our daily life. For example, we prefer to choose a hotel with positive comments rom previous customers. As the huge amounts of such information demonstrate the haracteristics of big data, it places heavy burdens on the assimilation of the customercontributed pinions. To overcoming this problem, we study an efficient opinion ummarization approach for a set of massive user reviews and comments associated ith an online resource, to summarize the opinions into two categories, i.e., positive nd negative. In this paper, we proposed a framework including: (1) overcoming the ig data problem of online comments using the efficient online-LDA approach; (2) electing meaningful topics from the imbalanced data; (3) summarizing the opinion f comments with high precision and recall. This framework is different from much f the previous work in that the topics are pre-defined and selected the topics for etter opinion summarization. To evaluate the proposed framework, we perform the xperiments on a dataset of hotel reviews for the variety of topics contained. The esults show that our framework can gain a significant performance improvement on pinion summarization.
Hair Hair Bundle Bundle Development Development by by Destabilizing Destabilizing the the Physical Physical Interaction Interaction between between Harmonin Harmonin and and Sans Sans Usher Usher Syndrome Syndrome Proteins Proteins Graphical

Highlights d Grxcr1, a deglutathionylating enzyme, promotes hair cell mechanoreceptor developmen t d grxcr1 ush1c ush1ga , , and zebrafish mutants have similar hair bundle defects d Glutathionylation of Ush1c promotes the interaction betw een Ush1c and Ush1ga d Grxcr1 prevents physical interaction between Ush1c and Ush1ga Authors Bernardo Blanco-Sá nchez, Auré lie Clé ment, Javier Fierro, Jr., . , Judy L. Peirce, Philip Wash bourne, Monte Westerfield
Comparative Analysis of COPD Assessment test (CAT) with BODE Index as an Tool In Assessing Disease Severity in Stable COPD Patients

BackgroundCOPD, being a multisystem disease is underestimated by FEV1% predicted alone which necessitates use of more comprehensive tools like BODE Index as well as various questionnaires to assess disease impact effectively. AimTo analyse CAT score with BODE Index in assessing disease severity in stable COPD patients. Materials and methodsA cross-sectional study was conducted in 50 patients. BODE Index and CAT score were correlated by Pearson's correlation coefcient. Results Patients were mostly from GOLD (2 and 3) categories with a male predominance and mean age, body mass index,FEV1% predicted, 6 2 minute walk distance, BODE Index and CAT score of 62.56± 8 years, 20.21±2.59 kg/m , 49.92±16.95%, 223.3±60.67 metres, 5.96±2.05 and 21.12±4.88 respectively. CAT score was strongly correlated with the BODE index(r=0.7007, p<0.00001). ConclusionCAT questionnaire, being reliable and sensitive in assessing disease impact should be routinely employed especially in primary health care settings where BODE index estimation may not always be feasible.
Temperature Control System for CMOS-Based Microelectrode Arrays

A temperature control system for CMOS-based MEAs is designed in this project. A thermal model has first demonstrated that aluminum vias need to be implemented in the PCB in order to be able to maintain the cell culture temperature at a constant value. A CMOS PTAT temperature sensor has been designed at the schematic level. Its purpose is to measure the temperature of the neural cells during electrophysiological experiments. An offset cancellation circuit has been implemented in the circuit in order to increase the sensitivity of the sensor. A sensitivity of 20[mV/K] has been obtained in the range of 35◦C to 40◦C. Finally, preliminary work on the design of temperature control circuit has been performed. This circuit reacts to temperature variations in around 1 sec in order to maintain the temperature of the cell culture at 37◦C.
Classification of informal settlements through the integration of 2D and 3D features extracted from UAV data

Abstract. Unmanned Aerial Vehicles (UAVs) are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.