Miracle-dz/UniFAR-FTUs huggingface dataset:
Disclosure of information on intellectual capital in Danish IPO prospectuses

Purpose – The purpose of this paper is to examine whether information on intellectual capital (non‐financial information on knowledge based resources) is disclosed in Danish IPO prospectuses. Further, to analyse whether this voluntary disclosure has changed in the period from 1999 to 2001 and to analyse what factors can explain the amount of disclosure in the prospectuses.Design/methodology/approach – The paper uses content analysis to compile a measure of disclosure on each prospectus and statistical analysis to test whether there is an association between disclosure and company type, the existence of managerial ownership before the IPO, the size of the company or the age of the firm.Findings – Based on statistical analysis, it is concluded that the extent of managerial ownership prior to the IPO and industry type affects the amount of voluntary intellectual capital disclosure, while company size and age do not affect disclosure. The results are interpreted in the light of the increasing importance of di.
Active cavity radiometric scale, international pyrheliometric scale, and solar constant

The active cavity radiometer type II, a new and accurate standard detector, has been developed for the absolute measurement of optical radiant flux. The active cavity radiometric scale (ACRS), defined by the active cavity radiometer (ACR), and the international pyrheliometric scale (IPS), defined by a U.S. standard angstrom pyrheliometer, have been compared in recent experiments. Simultaneous measurements of solar irradiance demonstrated an average systematic difference between the two scales of 2.2%, the measurements on the ACRS exceeding those on the IPS. An analytical study of the sensitivity of the ACR to sources of experimental error is presented. The uncertainty in the ACRS is found to be less than +--0.5% at the one solar constant level relative to the absolute scale based on fundamental physical principles. In August 1968 two ACR's measured the solar irradiance at an altitude of 25 km in a balloon-flight experiment. The solar-constant value derived from this measurement was Ho ---- 137.0 mw/cm . Scales for the measurement of radiant energy are established with respect to fundamental physical concepts by standard detectors or standard emitters of radiant energy. Establishment of a scale of radiomerry by a standard emitter usually involves the irradiance of a suitable (nonstandard) detector by a high-temperature blackbody source of thermal radiation. If the properties of the source and the charac
Dominant contribution of oxygenated organic aerosol to haze particles from real-time observation in Singapore during an Indonesian wildfire event in 2015

Abstract. Recurring transboundary haze from Indonesian wildfires in previous decades significantly elevated particulate matter (PM) concentrations in Southeast Asia. During that event on 10 to 31 October 2015, we conducted a real-time observation of non-refractory submicron PM (NR-PM1) in Singapore using an Aerodyne aerosol mass spectrometer. Simultaneously, we characterized carbonaceous components and organic aerosol (OA) tracers from fine PM (PM2.5) samples to support source apportionment of the online measurements. The real-time analysis demonstrated that OA accounted for approximately 80 % of NR-PM1 mass during the wildfire haze period. Source apportionment analysis applied to the OA mass spectra using the multilinear-engine (ME-2) approach resulted in four factors: hydrocarbon-like OA (HOA), biomass burning OA (BBOA), peat burning OA (PBOA), and oxygenated OA (OOA). The OOA can be considered as a surrogate of both secondary organic aerosol (SOA) and oxidized primary organic aerosol (OPOA), while the other factors are considered as surrogates of primary organic aerosol (POA). The OOA accounted for approximately 50 % of the total OA mass in NR-PM1, while POA subtypes from wildfires (BBOA and PBOA) contributed to approximately 30 % of the total OA mass. Our findings highlight the importance of atmospheric chemical processes, which likely include POA oxidation and SOA formation from oxidation of gaseous precursors, to the OOA concentration. As this research could not separately quantify the POA oxidation and SOA formation processes, further studies should attempt to investigate the contribution of gaseous precursor oxidation and POA aging to the OOA formation in wildfire plumes.
VADRA: Visual Adversarial Domain Randomization and Augmentation

We address the issue of learning from synthetic domain randomized data effectively. While previous works have showcased domain randomization as an effective learning approach, it lacks in challenging the learner and wastes valuable compute on generating easy examples. This can be attributed to uniform randomization over the rendering parameter distribution. In this work, firstly we provide a theoretical perspective on characteristics of domain randomization and analyze its limitations. As a solution to these limitations, we propose a novel algorithm which closes the loop between the synthetic generative model and the learner in an adversarial fashion. Our framework easily extends to the scenario when there is unlabelled target data available, thus incorporating domain adaptation. We evaluate our method on diverse vision tasks using state-of-the-art simulators for public datasets like CLEVR, Syn2Real, and VIRAT, where we demonstrate that a learner trained using adversarial data generation performs better than using a random data generation strategy.
Actuator Control for a Rapid Prototyping Railway Bogie, Using a Dynamically Substructured Systems Approach

A rapid prototyping bogie (RPB) has multiple actuators to emulate missing bogie components. In the original RPB hybrid control system, deterioration in the control performance, which was caused by dynamic coupling between the multiple actuators, was observed during the RPB performance tests. To solve this issue, a new controller was developed, based upon the dynamically substructured systems (DSS) method, and trialled on an existing proof-of-concept test rig. Through random excitation tests, it was confirmed that the actuators were well controlled. As a consequence, the DSS approach was determined as a viable framework for future research into the RPB system.
Impact of model developments on present and future simulations of permafrost in a global land-surface model

Abstract. There is a large amount of organic carbon stored in permafrost in the northern high latitudes, which may become vulnerable to microbial decomposition under future climate warming. In order to estimate this potential carbon–climate feedback it is necessary to correctly simulate the physical dynamics of permafrost within global Earth system models (ESMs) and to determine the rate at which it will thaw. Additional new processes within JULES, the land-surface scheme of the UK ESM (UKESM), include a representation of organic soils, moss and bedrock and a modification to the snow scheme; the sensitivity of permafrost to these new developments is investigated in this study. The impact of a higher vertical soil resolution and deeper soil column is also considered. Evaluation against a large group of sites shows the annual cycle of soil temperatures is approximately 25 % too large in the standard JULES version, but this error is corrected by the model improvements, in particular by deeper soil, organic soils, moss and the modified snow scheme. A comparison with active layer monitoring sites shows that the active layer is on average just over 1 m too deep in the standard model version, and this bias is reduced by 70 cm in the improved version. Increasing the soil vertical resolution allows the full range of active layer depths to be simulated; by contrast, with a poorly resolved soil at least 50 % of the permafrost area has a maximum thaw depth at the centre of the bottom soil layer. Thus all the model modifications are seen to improve the permafrost simulations. Historical permafrost area corresponds fairly well to observations in all simulations, covering an area between 14 and 19 million km2. Simulations under two future climate scenarios show a reduced sensitivity of permafrost degradation to temperature, with the near-surface permafrost loss per degree of warming reduced from 1.5 million km2 °C−1 in the standard version of JULES to between 1.1 and 1.2 million km2 °C−1 in the new model version. However, the near-surface permafrost area is still projected to approximately half by the end of the 21st century under the RCP8.5 scenario.
Deep Factors with Gaussian Processes for Forecasting

A large collection of time series poses significant challenges for classical and neural forecasting approaches. Classical time series models fail to fit data well and to scale to large problems, but succeed at providing uncertainty estimates. The converse is true for deep neural networks. In this paper, we propose a hybrid model that incorporates the benefits of both approaches. Our new method is data-driven and scalable via a latent, global, deep component. It also handles uncertainty through a local classical Gaussian Process model. Our experiments demonstrate that our method obtains higher accuracy than state-of-the-art methods.
Structural and Optical Behaviour of MAPbI3 Layers in Nitrogen and Humid Air

The tendency of MA+-containing perovskites to degradation under humid air is still the main challenge which limits the durability of technologies. We indeed frame the behavior of MAPbI3 layer through structural and optical characterization under thermal cycles and using the environmental composition as a variable parameter (humid air, N2, Ar, O2). Within the temperature range explored (RT-80°C) we likely approach the thermal operation of the material under the sun and find that the degradation mechanism is linked to the action of water molecules by the formation of lattice defects. They rise the lattice disorder, especially at the crossover of the tetragonal to cubic transition wherein an acceleration of the degradation kinetics is observed. Nitrogen can help rationalizing solutions to stabilize the materials even at this critical transition step, since it behaves as more than an inert species.
Foreign direct investment, economic growth and structural transformation: The case of West African Economies and Monetary Union Countries

This article examines the long run relationship and the causality between the growth of GDP per capita and FDI in WAEMU countries. Thereafter, it measures the impact of FDI on Total Factor of Productivity (TFP) in the short and long run, for different values of the depreciation of capital stock. Using observation between 1970 and 2012, the econometric analysis provides three key results. First, there is a strong evidence of long run relationship between the growth of GDP per capita and the ratio of FDI inflows. Second, there is bidirectional causality between these two variables. Third, there is a positive and significant effect of FDI on TFP in the long run, conditional on low level of depreciation of capital stock. Therefore, for policy implications, WAEMU countries should intensify their investment in education and health in order to boost the quality of human capital stock and sufficient absorptive capacity necessary to acquire technological transfer from FDI. They should also strengthen their openness, to attract FDI inflows, and invest in infrastructure to better control the depreciation of physical capital stock.
Study of Sodium-Chromium-Iron-Phosphate Glass by XRD, IR, Chemical Durability and SEM

Chromium iron phosphate glass was investigated for use as waste form because of its improved chemical durability. The introduction of chromium in sodium-iron-phosphate glass is used to compare its effect with iron in inhibition of corrosion. The sodium-chromium-iron phosphate glass of composition 10Na2O-30Fe2O3-5Cr2O3-55P2O5 (mol%) was produced by melting batches of (99, 98% pure) Cr2O3, Fe2O3, Na2CO3, and (NH4)2HPO4 at 1080°C for one hour and pouring the liquid into steel mold. The sample was annealed at 680°C for 48 h. We have performed the measurement of X-Ray Diffraction (XRD), Scanning Electronic Microscopy (SEM), Infra-Red spectroscopy (IR), and the chemical durability. The IR of the glass studied, contains two dominant bands, which were characteristic of pyrophosphate groups, (P-O) stretching mode of P-O non bridging oxygen at 1055 cm-1 and sym stretching mode of bridging oxygen at444 cm-1 respectively. There is also a band at603 cm-1 attributed to isolated tetrahedral units (PO4)3-. The chemical durability of the glass was investigated by measuring the weight loss in distilled water at 90°C for 22 days.
Image Blur Detection with Two-Dimensional Haar Wavelet Transform

Image Blur Detection with Two-Dimensional Haar Wavelet Transform by Sarat Kiran Andhavarapu, Master of Science Utah State University, 2015 Major Professor: Dr. Vladimir Kulyukin Department: Computer Science An algorithm is presented for image blur detection with the use of TwoDimensional Haar Wavelet transform (2D HWT). The algorithm classifies an image as blurred or sharp by splitting the image into N x N tiles, applying several iterations of the 2D HWT to each tile, and grouping horizontally, vertically, and diagonally connected tiles with pronounced changes into tile clusters. Images with large tile clusters are classified as sharp. Images with small tile clusters are classified blurred. If necessary, the blur extent can be estimated as the ratio of the total area of the connected tile clusters and the area of the image. When evaluated on a sample of five hundred images, the algorithm performed on par or better than two other blur detection algorithms found in the literature. The effect of blur detection on skewed barcode scanning is investigated by integrating the presented blur detection algorithm into a skewed barcode scanning algorithm. The experimental results show that blur detection had a positive effect on skewed barcode scanning rates and OCR rates. (46 pages)
NFC Secure Element-Based Mutual Authentication and Attestation for IoT Access

Certain resourceful and powered Internet of Things (IoT) can become victims to launch cyber attacks. Near field communication (NFC) can be used for their secure on-demand access. In this paper, we present a novel framework for the NFC secure element (SE)-based mutual authentication and attestation for IoT access with a user device such as a mobile device using NFC-based Host Card Emulation (HCE) mode for the first time. HCE is robust as compared to the other NFC modes. A cloud-based Trusted Certified Authority (TCA) manages all cryptographic credentials and stores them in the tamper-resistant SE and Trusted Platform Module (TPM)-based attestation modules on the devices. It uses a newly proposed NFC SE-based mutual authentication and attestation (NSE-AA) protocol for proof-of-locality, end-to-end anonymous mutual authentication between the SEs and an associated remote attestation for trust. The protocol is robust and lightweight as compared to the existing schemes. We provide its informal and formal security analysis using the Real-Or-Random (ROR) model. A simulation on the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool proves its safety. We also briefly present the details of a prototype with a commercial mid-range priced mobile device and Single Board Computer (SBC)-based IoT device.
Partially Occluded Facial Image Retrieval Based on a Similarity Measurement

We present a partially occluded facial image retrieval method based on a similarity measurement for forensic applications. The main novelty of this method compared with other occluded face recognition algorithms is measuring the similarity based on Scale Invariant Feature Transform (SIFT) matching between normal gallery images and occluded probe images. The proposed method consists of four steps: (i) a Self-Quotient Image (SQI) is applied to input images, (ii) Gabor-Local Binary Pattern (Gabor-LBP) histogram features are extracted from the SQI images, (iii) the similarity between two compared images is measured by using the SIFT matching algorithm, and (iv) histogram intersection is performed on the SIFT-based similarity measurement. In experiments, we have successfully evaluated the performance of the proposed method with the commonly used benchmark database, including occluded facial images. The results show that the correct retrieval ratio was 94.07% in sunglasses occlusion and 93.33% in scarf occlusion. As such, the proposed method achieved better performance than other Gabor-LBP histogram-based face recognition algorithms in eyes-hidden occlusion of facial images.
EXPLOITING SHADOW EVIDENCE AND ITERATIVE GRAPH-CUTS FOR EFFICIENT DETECTION OF BUILDINGS IN COMPLEX ENVIRONMENTS

This paper presents an automated approach for efficient detection of building regions in complex environments. We investigate the shadow evidence to focus on building regions, and the shadow areas are detected by recently developed false colour shadow detector. The directional spatial relationship between buildings and their shadows in image space is modelled with the prior knowledge of illumination direction. To do that, an approach based on fuzzy landscapes is presented. Once all landscapes are collected, a pruning process is applied to eliminate the landscapes that may occur due to non-building objects. Thereafter, we benefit from a graph-theoretic approach to accurately detect building regions. We consider the building detection task as a binary partitioning problem where a building region has to be accurately separated from its background. To solve the two-class partitioning, an iterative binary graph-cut optimization is performed. In this paper, we redesign the input requirements of the iterative partitioning from the previously detected landscape regions, so that the approach gains an efficient fully automated behaviour for the detection of buildings. Experiments performed on 10 test images selected from QuickBird (0.6 m) and Geoeye-1 (0.5 m) high resolution datasets showed that the presented approach accurately localizes and detects buildings with arbitrary shapes and sizes in complex environments. The tests also reveal that even under challenging environmental and illumination conditions (e.g. low solar elevation angles, snow cover) reasonable building detection performances could be achieved by the proposed approach.
Simulation Tools for Small Area Estimation: Introducing the R-package saeSim

The demand for reliable regional estimates from sample surveys has been substantially grown over the last decades. Small area estimation provides statistical methods to produce reliable predictions when the sample sizes in regions are too small to apply direct estimators. Model- and design-based simulations are used to gain insights into the quality of the introduced methods. In this article we present a framework which may help to guarantee the reproducibility of simulation studies in articles and during research. The introduced R-package saeSim is adjusted to provide a simulation environment for the special case of small area estimation. The package may allow the prospective researcher during the research process to produce simulation studies with a minimal eort of coding.
Boosting Black-Box Variational Inference by Incorporating the Natural Gradient

In this paper we present a modification of the popular Black-Box Variational Inference (BBVI) approach which significantly improves the computational efficiency of the inference. We achieve this performance boost by replacing the standard gradient in the stochastic gradient ascent framework of BBVI with the natural gradient. Our experimental results (e.g. training of neutral networks) show that the proposed method outperforms the original BBVI algorithm on both synthetic and real data.
Classifying the embedded young stellar population in Perseus and Taurus and the LOMASS database

Context. The classification of young stellar objects (YSOs) is typically done using the infrared spectral slope or bolometric temperature, but either can result in contamination of samples. More accurate methods to determine the evolutionary stage of YSOs will improve the reliability of statistics for the embedded YSO population and provide more robust stage lifetimes. Aims. We aim to separate the truly embedded YSOs from more evolved sources. Methods. Maps of HCO+J = 4–3 and C18O J = 3–2 were observed with HARP on the James Clerk Maxwell Telescope (JCMT) for a sample of 56 candidate YSOs in Perseus and Taurus in order to characterize the presence and morphology of emission from high density (ncrit > 106 cm-3) and high column density gas, respectively. These are supplemented with archival dust continuum maps observed with SCUBA on the JCMT and Herschel PACS to compare the morphology of the gas and dust in the protostellar envelopes. The spatial concentration of HCO+J = 4–3 and 850 μm dust emission are used to classify the embedded nature of YSOs. Results. Approximately 30% of Class 0+I sources in Perseus and Taurus are not Stage I, but are likely to be more evolved Stage II pre-main sequence (PMS) stars with disks. An additional 16% are confused sources with an uncertain evolutionary stage. Outflows are found to make a negligible contribution to the integrated HCO+ intensity for the majority of sources in this study. Conclusions. Separating classifications by cloud reveals that a high percentage of the Class 0+I sources in the Perseus star forming region are truly embedded Stage I sources (71%), while the Taurus cloud hosts a majority of evolved PMS stars with disks (68%). The concentration factor method is useful to correct misidentified embedded YSOs, yielding higher accuracy for YSO population statistics and Stage timescales. Current estimates (0.54 Myr) may overpredict the Stage I lifetime on the order of 30%, resulting in timescales down to 0.38 Myr for the embedded phase.
Cogging Torque Reduction Technique by Considering Step-Skew Rotor in Permanent Magnet Synchronous Motor

This paper deals with the cogging torque reduction in surface-mounted permanent magnet synchronous motors with overhang by considering the step-skewed rotor method. Firstly, optimal step-skew angle of the rotor is determined not only to minimize cogging torque but also to meet the required output torque. Furthermore, each rotor stack length should be appropriately adjusted to reduce the cogging torque more effectively in the way to make the axial directional flux density distribution on each stack uniformly. The analysis reveals that the proposed step-skew method is useful in minimizing cogging torque, and the experiment results show the validity of the cogging torque reduction model selected by analytical results.
oxicity studies of the aqueous extract of Vernonia amygdalina

The aqueous leaf extract, after six weeks administration to the animals showed no difference in the morphology of the heart, liver, kidney and intestinal tissues of the treated and un-treated animals. Body weights of both the treated and untreated animals rose progressively as the period increased. The plant extract produced no significant changes in packed cell volume (PCV), white blood cell (WBC) and platelet counts. This study suggests that the plant extract is non-hazardous, even when taken for some time.