474 research outputs found
Taxing thoughts: Ireland, tax competition and the cost of intellectual capital
peer-reviewedThis paper examines the impact of tax competition on the commodfication of
ideas, and points towards a particular set of negative consequences that
affect the developing world. As multinational business becomes increasingly
independent of national borders, the power relationship between business
and government has shifted from one in which governments imposed tax on
business in return for the privilege of operating within its jurisdiction, to one in
which governments distort their tax system to suit business, in the hope of
enticing them to locate on their shores. The race to the bottom in terms of tax
rates has been well-chronicled in studies such as Christensen et al (2004),
and Murphy (2006)
Countries which were successful at the first round of tax competition are now
finding that tax rates alone will not hold the multinationals on which they have
become so dependent. The economic growth associated with their earlier
success has brought high operating and wage costs. Multinationals who have
remained lightly rooted in the soil of these countries can easily move their
manufacturing to cheaper, emerging economies, taking with them their
coveted jobs and exports. In order to retain them, these first round winning
countries are now encouraging multinationals to locate their research and
development as well as their production facilities with them. They hope that
this is a less mobile activity, less easily replicated in a developing country, and
so will anchor the multinational firmly in their territory.
In this new level of the tax competition game, incentives are given not only for
gross production, but for the production of knowledge. As a consequence,
knowledge itself becomes commodified, and intellectual capital widely defined
and privatised. This means that ideas previously shared must now be bought,
and products previously sold at a price determined by the local market may
now only be sold if the market can support their original, patent-protected
form.
This paper tracks the development from the old to the new rules of tax
competition, using the example of Ireland to illustrate the strategies adopted
at each stage. The rational, self-serving response of multinationals is
explored, and the immediate downstream effects for developing countries
discussed. The writings of Michel Foucault are used to gain perspective on
the idea of intellectual capital. Finally, the sustainability of the new form of tax
competition is questioned, and some hypotheses are formed about the longterm consequences.PUBLISHEDpeer-reviewe
Elementary considerations on gravitational waves from hyperbolic encounters
We examine the main properties of gravitational waves (GWs) emitted by
transient hyperbolic encounters of black holes. We begin by building the set of
basic variables most relevant to setting our problem. After exposing the ranges
of masses and eccentricities accessible at a given GW frequency, we analyze the
dependence of the gravitational strain on those parameters and determine the
trajectories resulting in the most sizeable strains. Some non-trivial behaviors
are unveiled, showing that highly eccentric events can be more easily
detectable than parabolic ones. In particular, we underline the correct way to
extend formulas from hyperbolic to parabolic orbits. Our reasonings are as
general as possible, and we make a point of explaining our considerations
pedagogically.Comment: 10 pages, 4 figure
Drone-based photogrammetry combined with deep-learning to estimate hail size distributions and melting of hail on the ground
Hail is a major threat associated with severe thunderstorms and an estimation of the hail size is important for issuing warnings to the public. Operational radar products exist that estimate the size of the expected hail. For the verification of such products, ground based observations are necessary. Automatic hail sensors, as for example within the Swiss hail network, record the kinetic energy of hailstones and can estimate with this the hail diameters. However, due to the small size of the observational area of these sensors (0.2 m2) the estimation of the hail size distribution (HSD) can have large uncertainties. To overcome this issue, we combine drone-based aerial photogrammetry with a state-of-the-art custom trained deep-learning object detection model to identify hailstones in the images and estimate the HSD in a final step. This approach is applied to photogrammetric image data of hail on the ground from a supercell storm, that crossed central Switzerland from southwest to northeast in the afternoon of June 20, 2021. The hail swath of this intense right-moving supercell was intercepted a few minutes after the passage at a soccer field near Entlebuch (Canton Lucerne, Switzerland) and aerial images of the hail on the ground were taken by a commercial DJI drone, equipped with a 50 megapixels full frame camera system. The average ground sampling distance (GSD) that could be reached was 1.5 mm per pixel, which is set by the mounted camera objective with a focal length of 35 mm and a flight altitude of 12 m above ground. A 2D orthomosaic model of the survey area (750 m2) is created based on 116 captured images during the first drone mapping flight. Hail is then detected by using a region-based Convolutional Neural Network (Mask R-CNN). We first characterize the hail sizes based on the individual hail segmentation masks resulting from the model detections and investigate the performance by using manual hail annotations by experts to generate validation and test data sets. The final HSD, composed of 18209 hailstones, is compared with nearby automatic hail sensor observations, the operational weather radar based hail product MESHS (Maximum Expected Severe Hail Size) and some crowdsourced hail reports. Based on the retrieved drone hail data set, a statistical assessment of sampling errors of hail sensors is carried out. Furthermore, five repetitions of the drone-based photogrammetry mission within about 18 min give the unique opportunity to investigate the hail melting process on the ground for this specific supercell hailstorm and location
Deep Learning-Based Automated Detection of Retinal Breaks and Detachments on Fundus Photography.
PURPOSE
The purpose of this study was to develop a deep learning algorithm, to detect retinal breaks and retinal detachments on ultra-widefield fundus (UWF) optos images using artificial intelligence (AI).
METHODS
Optomap UWF images of the database were annotated to four groups by two retina specialists: (1) retinal breaks without detachment, (2) retinal breaks with retinal detachment, (3) retinal detachment without visible retinal breaks, and (4) a combination of groups 1 to 3. The fundus image data set was split into a training set and an independent test set following an 80% to 20% ratio. Image preprocessing methods were applied. An EfficientNet classification model was trained with the training set and evaluated with the test set.
RESULTS
A total of 2489 UWF images were included into the dataset, resulting in a training set size of 2008 UWF images and a test set size of 481 images. The classification models achieved an area under the receiver operating characteristic curve (AUC) on the testing set of 0.975 regarding lesion detection, an AUC of 0.972 for retinal detachment and an AUC of 0.913 for retinal breaks.
CONCLUSIONS
A deep learning system to detect retinal breaks and retinal detachment using UWF images is feasible and has a good specificity. This is relevant for clinical routine as there can be a high rate of missed breaks in clinics. Future clinical studies will be necessary to evaluate the cost-effectiveness of applying such an algorithm as an automated auxiliary tool in a large practices or tertiary referral centers.
TRANSLATIONAL RELEVANCE
This study demonstrates the relevance of applying AI in diagnosing peripheral retinal breaks in clinical routine in UWF fundus images
Gravitational waves from high-power twisted light
Recent advances in high-energy and high-peak-power laser systems have opened
up new possibilities for fundamental physics research. In this work, the
potential of twisted light for the generation of gravitational waves in the
high frequency regime is explored for the first time. Focusing on Bessel beams,
novel analytic expressions and numerical computations for the generated metric
perturbations and associated powers are presented. Compelling evidence is
provided that the properties of the generated gravitational waves, such as
frequency, polarisation states and direction of emission, are controllable by
the laser pulse parameters and optical arrangements
Bragg spectroscopy of a Bose-Einstein condensate
Properties of a Bose-Einstein condensate were studied by stimulated,
two-photon Bragg scattering. The high momentum and energy resolution of this
method allowed a spectroscopic measurement of the mean-field energy and of the
intrinsic momentum uncertainty of the condensate. The coherence length of the
condensate was shown to be equal to its size. Bragg spectroscopy can be used to
determine the dynamic structure factor over a wide range of energy and momentum
transfers.Comment: 4 pages, 3 figure
Unprecedented atmospheric ammonia concentrations detected in the high Arctic from the 2017 Canadian wildfires
Abstract From 17-22 August 2017 simultaneous enhancements of ammonia (NH3), carbon monoxide (CO), hydrogen cyanide (HCN), and ethane (C2H6) were detected from ground-based solar absorption Fourier transform infrared (FTIR) spectroscopic measurements at two high-Arctic sites: Eureka (80.05°N, 86.42°W) Nunavut, Canada and Thule (76.53°N, 68.74°W), Greenland. These enhancements were attributed to wildfires in British Columbia and the Northwest Territories of Canada using FLEXPART back-trajectories and fire locations from Moderate Resolution Imaging Spectroradiometer (MODIS) and found to be the greatest observed enhancements in more than a decade of measurements at Eureka (2006-2017) and Thule (1999-2017). Observations of gas-phase NH3 from these wildfires illustrates that boreal wildfires may be a considerable episodic source of NH3 in the summertime high Arctic. Comparisons of GEOS-Chem model simulations using the Global Fire Assimilation System (GFASv1.2) biomass burning emissions to FTIR measurements and Infrared Atmospheric Sounding Interferometer (IASI) measurements showed that the transport of wildfire emissions to the Arctic was underestimated in GEOS-Chem. However, GEOS-Chem simulations showed that these wildfires contributed to surface-layer NH3 and enhancements of 0.01-0.11 ppbv and 0.05-1.07 ppbv, respectively, over the Canadian Archipelago from 15-23 August 2017
A Theory of Natural Addiction
Economic theories of rational addiction aim to describe consumer behavior in the presence of habit-forming goods. We provide a biological foundation for this body of work by formally specifying conditions under which it is optimal to form a habit. We demonstrate the empirical validity of our thesis with an in-depth review and synthesis of the biomedical literature concerning the action of opiates in the mammalian brain and their eects on behavior. Our results
lend credence to many of the unconventional behavioral assumptions employed by theories of
rational addiction, including adjacent complementarity and the importance of cues, attention,
and self-control in determining the behavior of addicts. We oer evidence for the special case
of the opiates that "harmful" addiction is the manifestation of a mismatch between behavioral
algorithms encoded in the human genome and the expanded menu of choices faced by consumers in the modern world
Spinor condensates and light scattering from Bose-Einstein condensates
These notes discuss two aspects of the physics of atomic Bose-Einstein
condensates: optical properties and spinor condensates. The first topic
includes light scattering experiments which probe the excitations of a
condensate in both the free-particle and phonon regime. At higher light
intensity, a new form of superradiance and phase-coherent matter wave
amplification were observed. We also discuss properties of spinor condensates
and describe studies of ground--state spin domain structures and dynamical
studies which revealed metastable excited states and quantum tunneling.Comment: 58 pages, 33 figures, to appear in Proceedings of Les Houches 1999
Summer School, Session LXXI
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