Natural Suppression of Higgsino-Mediated Proton Decay in Supersymmetric SO(10)

In supersymmetric Grand Unified Theories, proton decay mediated by the color--triplet higgsino is generally problematic and requires some fine--tuning of parameters. We present a mechanism which naturally suppresses such dimension 5 operators in the context of SUSY $SO(10)$. The mechanism, which implements natural doublet--triplet splitting using the adjoint higgs, converts these dimension 5 operators effectively into dimension 6. By explicitly computing the higgs spectrum and the resulting threshold uncertainties we show that the successful prediction of $\sin^2\theta_W$ is maintained {\it as a prediction} in this scheme. It is argued that only a weak suppression of the higgsino mediated proton decay is achievable within SUSY $SU(5)$ without fine--tuning, in contrast to a strong suppression in SUSY $SO(10)$.Comment: 39 pages (3 Feynman graphs not included), in Plain LaTeX, BA-93-2

Detection of interictal discharges with convolutional neural networks using discrete ordered multichannel intracranial EEG

Detection algorithms for electroencephalography (EEG) data, especially in the field of interictal epileptiform discharge (IED) detection, have traditionally employed handcrafted features which utilised specific characteristics of neural responses. Although these algorithms achieve high accuracy, mere detection of an IED holds little clinical significance. In this work, we consider deep learning for epileptic subjects to accommodate automatic feature generation from intracranial EEG data, while also providing clinical insight. Convolutional neural networks are trained in a subject independent fashion to demonstrate how meaningful features are automatically learned in a hierarchical process. We illustrate how the convolved filters in the deepest layers provide insight towards the different types of IEDs within the group, as confirmed by our expert clinicians. The morphology of the IEDs found in filters can help evaluate the treatment of a patient. To improve the learning of the deep model, moderately different score classes are utilised as opposed to binary IED and non-IED labels. The resulting model achieves state of the art classification performance and is also invariant to time differences between the IEDs. This study suggests that deep learning is suitable for automatic feature generation from intracranial EEG data, while also providing insight into the dat

Seeing is believing: photon counting computed tomography clearly images directional deep brain stimulation lead segments and markers after implantation

Background and Objectives Directional deep brain stimulation (DBS) electrodes are increasingly used, but conventional computed tomography (CT) is unable to directly image segmented contacts owing to physics-based resolution constraints. Postoperative electrode segment orientation assessment is necessary because of the possibility of significant deviation during or immediately after insertion. Photon-counting detector (PCD) CT is a relatively novel technology that enables high resolution imaging while addressing several limitations intrinsic to CT. We show how PCD CT can enable clear in vivo imaging of DBS electrodes, including segmented contacts and markers for all major lead manufacturers. Materials and Methods We describe postoperative imaging and reconstruction protocols we have developed to enable optimal lead visualization. PCD CT images were obtained of directional leads from the three major manufacturers and fused with preoperative 3T magnetic resonance imaging (MRI). Radiation dosimetry also was evaluated and compared with conventional imaging controls. Orientation estimates from directly imaged leads were compared with validated software-based reconstructions (derived from standard CT imaging artifact analysis) to quantify congruence in alignment and directional orientation. Results High-fidelity images were obtained for 15 patients, clearly indicating the segmented contacts and directional markers both on CT alone and when fused to MRI. Our routine imaging protocol is described. Ionizing radiation doses were significantly lower than with conventional CT. For most leads, the directly imaged lead orientations and depths corresponded closely to those predicted by CT artifact-based reconstructions. However, unlike direct imaging, the software reconstructions were susceptible to 180° error in orientation assessment. Conclusions High-resolution photon-counting CT can very clearly image segmented DBS electrode contacts and directional markers and unambiguously determine lead orientation, with lower radiation than in conventional imaging. This obviates the need for further imaging and may facilitate anatomically tailored directional programming

Deep learning for epileptic intracranial EEG data

Detection algorithms for electroencephalography (EEG) data typically employ handcrafted features that take advantage of the signal's specific properties. In the field of interictal epileptic discharge (IED) detection, the feature representation that provides optimal classification performance is still an unresolved issue. In this paper, we consider deep learning for automatic feature generation from epileptic intracranial EEG data in the time domain. Specifically, we consider convolutional neural networks (CNNs) in a subject independent fashion and demonstrate that meaningful features, representing IEDs are automatically learned. The resulting model achieves state of the art classification performance, provides insights for the different types of IEDs within the group, and is invariant to time differences between the IEDs. This study suggests that automatic feature generation via deep learning is suitable for IEDs and EEG in genera

Elevated circulating amyloid concentrations in obesity and diabetes promote vascular dysfunction

Diabetes, obesity and Alzheimer’s disease (AD) are associated with vascular complications and impaired nitric oxide (NO) production. Furthermore, increased β-site amyloid precursor protein (APP)-cleaving enzyme 1 (BACE1), APP and β-amyloid (Aβ) are linked with vascular disease development and raised BACE1 and Aβ accompany hyperglycemia and hyperlipidemia. However, the causal relationship between obesity and diabetes, raised Aβ and vascular dysfunction is unclear. We report that diet-induced obesity (DIO) in mice raised plasma and vascular Aβ42 that correlated with decreased NO bioavailability, endothelial dysfunction and raised blood pressure. Genetic or pharmacological reduction of BACE1 activity and Aβ42 prevented and reversed, respectively, these outcomes. In contrast, expression of human mutant APP in mice or Aβ42 infusion into control diet-fed mice to mimic obese levels impaired NO production, vascular relaxation and raised blood pressure. In humans, raised plasma Aβ42 correlated with diabetes and endothelial dysfunction. Mechanistically, higher Aβ42 reduced endothelial NO synthase (eNOS), cyclic GMP and protein kinase G (PKG) activity independently of diet whereas endothelin-1 was increased by diet and Aβ42. Lowering Aβ42 reversed the DIO deficit in the eNOS-cGMP-PKG pathway and decreased endothelin-1. Our findings suggest that BACE1 inhibitors may have therapeutic value in the treatment of vascular disease associated with diabetes

The timing and widespread effects of the largest Holocene volcanic eruption in Antarctica.

The caldera collapse of Deception Island Volcano, Antarctica, was comparable in scale to some of the largest eruptions on Earth over the last several millennia. Despite its magnitude and potential for far-reaching environmental effects, the age of this event has never been established, with estimates ranging from the late Pleistocene to 3370 years before present. Here we analyse nearby lake sediments in which we identify a singular event produced by Deception Island's caldera collapse that occurred 3980 ± 125 calibrated years before present. The erupted tephra record the distinct geochemical composition of ejecta from the caldera-forming eruption, whilst an extreme seismic episode is recorded by lake sediments immediately overlying the collapse tephra. The newly constrained caldera collapse is now the largest volcanic eruption confirmed in Antarctica during the Holocene. An examination of palaeorecords reveals evidence in marine and lacustrine sediments for contemporaneous seismicity around the Antarctic Peninsula; synchronous glaciochemical volcanic signatures also record the eruption in ice cores spread around Antarctica, reaching >4600 km from source. The widespread footprint suggests that this eruption would have had significant climatic and ecological effects across a vast area of the south polar region

Financial crises and the attainment of the SDGs: an adjusted multidimensional poverty approach

This paper analyses the impact of financial crises on the Sustainable Development Goal of eradicating poverty. To do so, we develop an adjusted Multidimensional Poverty Framework (MPF) that includes 15 indicators that span across key poverty aspects related to income, basic needs, health, education and the environment. We then use an econometric model that allows us to examine the impact of financial crises on these indicators in 150 countries over the period 1980–2015. Our analysis produces new estimates on the impact of financial crises on poverty’s multiple social, economic and environmental aspects and equally important captures dynamic linkages between these aspects. Thus, we offer a better understanding of the potential impact of current debt dynamics on Multidimensional Poverty and demonstrate the need to move beyond the boundaries of SDG1, if we are to meet the target of eradicating poverty. Our results indicate that the current financial distress experienced by many low-income countries may reverse the progress that has been made hitherto in reducing poverty. We find that financial crises are associated with an approximately 10% increase of extreme poor in low-income countries. The impact is even stronger in some other poverty aspects. For instance, crises are associated with an average decrease of government spending in education by 17.72% in low-income countries. The dynamic linkages between most of the Multidimensional Poverty indicators, warn of a negative domino effect on a number of SDGs related to poverty, if there is a financial crisis shock. To pre-empt such a domino effect, the specific SDG target 17.4 on attaining long-term debt sustainability through coordinated policies plays a key role and requires urgent attention by the international community

Dynamics of Brane-World Cosmological Models

We show that generically the initial singularity is isotropic in spatially homogeneous cosmological models in the brane-world scenario. We then argue that it is plausible that the initial singularity is isotropic in typical brane world cosmological models. Therefore, brane cosmology naturally gives rise to a set of initial data that provide the conditions for inflation to subsequently take place, thereby solving the initial conditions problem and leading to a self--consistent and viable cosmology.Comment: Final version. To appear in Physical Revie

Prototyping open digital tools for urban commoning

The paper will discuss an experimental co-design approach to the development of a digital toolkit prototype and a resulting set of co-design principles, which are put forward as a way of infrastructuring future design of digital tools for urban commoning. Focus is placed on the case study of a commoning hub in a Parisian suburb where the toolkit was co-designed through a series of prototyping workshops, carried out with hub users and addressing key hub needs. The prototyping process explored possibilities for re-appropriating and re-framing existing digital technologies as open toolkits, which can be further re-purposed by users, here and beyond, after the design of an initial toolkit prototype