Independent Scenarios Research Articles

MISTIC: A prediction tool to reveal disease-relevant deleterious missense variants.

The diffusion of next-generation sequencing technologies has revolutionized research and diagnosis in the field of rare Mendelian disorders, notably via whole-exome sequencing (WES). However, one of the main issues hampering achievement of a diagnosis via WES analyses is the extended list of variants of unknown significance (VUS), mostly composed of missense variants. Hence, improved solutions are needed to address the challenges of identifying potentially deleterious variants and ranking them in a prioritized short list. We present MISTIC (MISsense deleTeriousness predICtor), a new prediction tool based on an original combination of two complementary machine learning algorithms using a soft voting system that integrates 113 missense features, ranging from multi-ethnic minor allele frequencies and evolutionary conservation, to physiochemical and biochemical properties of amino acids. Our approach also uses training sets with a wide spectrum of variant profiles, including both high-confidence positive (deleterious) and negative (benign) variants. Compared to recent state-of-the-art prediction tools in various benchmark tests and independent evaluation scenarios, MISTIC exhibits the best and most consistent performance, notably with the highest AUC value (> 0.95). Importantly, MISTIC maintains its high performance in the specific case of discriminating deleterious variants from benign variants that are rare or population-specific. In a clinical context, MISTIC drastically reduces the list of VUS (<30%) and significantly improves the ranking of “causative” deleterious variants. Pre-computed MISTIC scores for all possible human missense variants are available at http://lbgi.fr/mistic.

Evaluation and Improvement of the Near-Real-Time Linear Fit SO2Retrievals From Suomi NPP Ozone Mapping and Profiler Suite

Changing a logic switch threshold in the linear fit sulfur dioxide (LFSO2) algorithm improves the performance based on the evaluation of the NOAA operational atmospheric SO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> near-real-time (NRT) retrieval. The LFSO2 is used to create estimates from measurements made by the Suomi NPP (S-NPP) Ozone Mapping and Profiler Suite (OMPS). We evaluate the LFSO2 and compare the results to those from a principal component analysis (PCA) offline algorithm. Twenty independent volcanic scenarios and one environmental disaster scenario spread over eight years are selected for this comparison. More than three months of Kilauea volcanic activity in 2018 are monitored and are included in this evaluation and comparison. We found that the operational LFSO2 retrievals at lower troposphere (TRL), mid-troposphere (TRM), and lower stratosphere (STL) exhibited a discontinuity and have a saturation-like relationship if compared with PCA results. Using the new retrieval logic, the discontinuity in LFSO2 retrievals and the saturation appearance in comparisons vanished and a close to a linear relationship with the matchup data from the PCA retrieval products is demonstrated. The minimum detectable values for all three SO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> layer products and the planetary boundary layer (PBL) products are estimated with the updated LFSO2 algorithm. Results for a volcanic cloud over Colombia for the updated LFSO2 for OMPS and a Differential Optical Absorption Spectroscopy (DOAS) algorithm for the Tropospheric Monitoring Instrument (TROPOMI) measurements are also examined. Similar SO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> total mass estimates over the region are obtained from the two products.

F-theory vacua and \u03b1\u2032-corrections

In this work we analyze F-theory and Type IIB orientifold compactifications to study α′-corrections to the four-dimensional, mathcal{N} = 1 effective actions. In particular, we obtain corrections to the Kählermoduli space metric and its complex structure for generic dimension originating from eight-derivative corrections to eleven-dimensional supergravity. We propose a completion of the G2R3 and (∇G)2R2-sector in eleven-dimensions relevant in Calabi-Yau fourfold reductions. We suggest that the three-dimensional, mathcal{N} = 2 Kähler coordinates may be expressed as topological integrals depending on the first, second, and third Chern-forms of the divisors of the internal Calabi-Yau fourfold. The divisor integral Ansatz for the Kähler potential and Kähler coordinates may be lifted to four-dimensional, mathcal{N} = 1 F-theory vacua. We identify a novel correction to the Kähler potential and coordinates at order α′2, which is leading compared to other known corrections in the literature. At weak string coupling the correction arises from the intersection of D7-branes and O7-planes with base divisors and the volume of self-intersection curves of divisors in the base. In the presence of the conjectured novel α′-correction resulting from the divisor interpretation the no-scale structure may be broken. Furthermore, we propose a model independent scenario to achieve non-supersymmetric AdS vacua for Calabi-Yau orientifold backgrounds with negative Euler-characteristic.

Comparative assessment of the GIS based bathtub model and an enhanced bathtub model for coastal inundation

Coastal zones are dynamic spaces where human activities and infrastructure are exposed to natural forces, climate change and extreme weather events such as storm surges. Coastal inundation is regarded as one of the most dangerous and destructive natural hazards, and while there are many studies to analyse these events, GIS based methods are limited. This research aimed at developing a GIS based enhanced Bathtub Model (eBTM) that improves on the widely used simple Bathtub Model (sBTM) to make it more appropriate to a storm surge related coastal inundation context. The eBTM incorporates beach slope, surface roughness and instils hydrological connectivity relevant for event scale coastal flooding, unlike the sBTM which only uses topographic elevation above sea level as input. For a test site in Cape Town, South Africa, inundation levels for 3 independent scenarios were calculated using the average spring tides level, extreme sea level for a 1-in-100-year storm and two sea-level rise scenarios. Each scenario was run on both the sBTM and the eBTM developed through this study. Comparing the results, the eBTM method overall produced more conservative inundation results and also produced less disconnected areas of (unrealistic) inundation. The eBTM also produces inundation water levels relative to structures, thus showing the potential for quantifying the coastal inundation risk to infrastructure, which is of relevance in the disaster response context. Additionally, the impact of using Digital Terrain Models (DTMs) instead of Digital Surface Models (DSM) on the inundation results was tested. The use of a DSM, including buildings and other objects, showed more realistic trajectories of the inundation water moving through the model area.

A robust optimization approach for coordinated operation of multiple energy hubs

The energy hub (EH) has become an important concept in terms of optimizing multi-carrier energy systems’ efficiency and flexibility. In this regard, an optimal operation model for managing multiple EHs with electrical and heat energy demands is proposed, which aims to reduce the total cost of the EHs. The components of each EH include the combined heat and power (CHP) unit, gas boiler, heat storage (HS) unit, wind turbine (WT) and photovoltaic (PV) array. A robust optimization approach is then proposed to deal with the uncertainties of renewable distributed energy resources (RDERs) and electricity prices. Meanwhile, both electrical and thermal demand response (DR) programs are considered in the proposed model. Finally, the optimized dispatch results under three different scheduling scenarios, i.e., the independent scenario, and the aggregation scenarios with and without DR programs are discussed. The simulation results show that the proposed multiple EHs optimization model can effectively reduce the total cost of EHs. Meanwhile, the results also reveal that implementing the DR programs can further reduce the consumers’ total costs through load shifting.

Synergistic generation of energy and water in remote communities: Economic and environmental assessment of current situation and future scenarios

Improving access to energy and water in remote communities is an important step towards sustainable development. However, integrated sustainability studies at the community or household scale are rare compared to industrial or national studies. Thus, this paper presents an integrated approach to the development and evaluation of energy and water supply systems in remote communities in developing countries. Termed here “synergistic generation” (“synergen”), the approach considers simultaneously electricity, heat for cooking and water supply to determine their environmental and economic sustainability on a life cycle basis. Life cycle assessment and life cycle costing are used for this purpose. Both the current situation and future scenarios to 2030 are considered for a representative remote community. The life cycle costs of the current energy and water supply are estimated at 2944 USD/household per year, most of which (91%) is due to bottled water. The latter is also the main cause of current environmental impacts (62%), followed by cooking fuels (33%) and electricity (5%). If business as usual (BAU) continues to 2030, air pollution and eutrophication could be reduced by >40% but other 14 impacts would increase by 2–63% on the current situation due to higher dependence on diesel for electricity generation and bottled water. For the same reason, BAU also has 82% higher life cycle costs (5364 USD/household∙yr) than at present. Assuming full supply self-sufficiency (Independent scenario) leads to a >12% reduction in all impact categories, except terrestrial ecotoxicity, which increases by 5% – both trends are due to utilisation of waste biomass for cooking. The life cycle costs are reduced by 92% (231 USD/household∙yr), mainly due to the phasing out of bottled water. However, capital costs are 21% higher due to the need for multiple renewable energy installations. Pursuing moderate rather than full independence of supply (Transition scenario) would reduce most impacts and costs below those of the current situation. Overall, the Transition and Independent scenarios have lower impacts than at present in almost all environmental categories as well as lower life cycle costs. These findings demonstrate the environmental and economic feasibility of energy and water independence in remote communities as well as highlighting the likely trade-offs that should be considered during the transition.

An integrated sustainability assessment of synergistic supply of energy and water in remote communities

The success of deploying energy and water technologies in remote communities in developing countries can be improved by considering their synergistic relationships and their social, economic and environmental implications. This paper first evaluates social implications of current energy and water supply in a prototypical remote community against five future (2030) scenarios for synergistic provision of electricity, heat for cooking and water. This is followed by an integrated assessment of the social, environmental and economic life cycle sustainability through multicriteria decision analysis. The Business-as-usual (BAU) scenario shows high life cycle health impacts but low impacts from local air pollution. The contrary is true for the Independent and Advanced Independent scenarios which assume community self-sufficiency in energy and water supply. Greater access to electricity and water in the Advanced and Advanced Independent scenarios increases the potential for human development and security of supply, but there is an increase in the risk of accidents and decrease in social acceptability of the water supply. Similarly, a transition towards clean cooking fuels away from traditional solid biomass reduces local air pollution but increases reliance on imported fuels (BAU and Advanced scenarios). The Transition scenario is socially the most sustainable option, while Independent and Advanced Independent are the best options environmentally. They also have the lowest total operating costs, but have higher capital requirements than most other scenarios. Overall, unless extreme preferences for either environmental or social aspects are adopted, the Transition and Independent scenarios emerge as the most sustainable options. This suggests that current energy and water supply to remote communities can be transitioned sustainably to a self-sufficient system that does not depend on imported resources. The scenarios developed in this work present a framework for an integrated design and evaluation of energy and water supply in remote communities with the aim of aiding stakeholders in defining sustainable transition pathways.

Facility Location with Joint Disruptions

Classical facility location problems do not incorporate the possibility of disruptions among facilities and usually result in solutions that do not perform well under disruptions. Existent literature on disreputable facility locations focuses on independent or extreme dependence scenarios where the probability structure is simplistic but has the advantage of allowing for efficient optimization. We propose the use of partially subordinated Markov Chains to model the probability of the dependent risk of disruptions. This parsimonious approach o ers a realistic model for disruptions. We also propose algorithms to calibrate a partially subordinated Markov Chain model and to optimize for the facility locations under dependent disruptions. We calibrate our model on two different cases with four different disruption data sets each and solve for the optimal facility location choice. We show that the resulting solutions significantly outperform those yielded from stronger assumptions like independence or extreme dependence.

Assessment of pre and post-disaster supply chain resilience based on network structural parameters with CVaR as a risk measure

The present study assesses supply chain resilience based on network structural parameters. Resilience is computed as a composite effect of density, centrality, connectivity, and network size of the network. A simulation-based approach is adopted, wherein networks of 23 firms operating in India are subjected to risk combinations of five mutually inclusive independent scenarios of probability levels and five mutually exclusive and exhaustive impact levels. The worst-case performance of the supply chain network when subjected to high impact and low probability risks is captured using conditional-value at risk (CVaR). Results reveal that the firm which has the lowest density and centrality and the highest connectivity and network size, exhibits the highest resilience. Whereas, the firm which has the highest density and high centrality due to an aggregation node exhibits the lowest resilience.The two main contributions of the present study are as follows. First, it derives insights for practicing managers from actual instead of theoretical networks. Second, it captures the worst-case performance of the supply chain network using CVaR, which has not been reported by any study in the supply chain network structure domain. The simulation-based approach can be easily adopted by the managers to assess the resilience of their supply chain networks and their preparedness to face potential risks. The information available in the form of CVaR is an important input to practicing managers to evaluate whether their supply chain network can face severe disruptions or not. The managers can then make informed decisions on how to increase the resilience of their supply chain networks.

Acute human exposure assessment to tetrahydrocannabinol (Δ9-THC).

Delta‐9‐tetrahydrocannabinol (Δ9‐THC) is a naturally occurring psychoactive compound derived from the hemp plant Cannabis sativa. In 2015, EFSA established an acute reference dose (ARfD) of 1 μg/kg body weight (bw) for Δ9‐THC and assessed acute dietary exposure from milk and dairy products. This resulted at the most 3% and 13% of the ARfD for adults and toddlers, respectively. Following the European Commission Recommendation 2016/2115 on the monitoring of the presence of Δ9‐THC in food and the issuing of a new mandate, EFSA assessed the acute human exposure to Δ9‐THC. ‘Standard’ food categories were used as proxies for consumption of hemp and hemp‐based products. Twelve independent scenarios based on single food categories were considered and acute exposure was assessed for consumption days only for all age groups excluding infants. Occurrence data for Total‐Δ9‐THC (588 samples in total) were used for this assessment up to the highest reliable percentile for each food category. The EFSA ARfD of 1 μg/kg bw was exceeded in the adult high consumers of most considered hemp and hemp‐containing products, under the lower‐bound (LB) and upper‐bound (UB) scenario. At the UB, acute exposure in adult high consumers was estimated based on the highest reliable percentile of occurrence, for Hemp seeds (P95, up to 9 μg/kg bw), Hemp oil (P95, up to 21 μg/kg bw), Tea (Infusion) (P95, up to 208 μg/kg bw), Breakfast cereals (P50, up to 1.3 μg/kg bw), Pasta (Raw) (P75, up to 6.4 μg/kg bw), Bread and rolls (P75, up to 1.3 μg/kg bw), Bread and rolls from hemp flour (P90, up to 4.1 μg/kg bw), Cereal bars (P50, up to 0.3 μg/kg bw), Fine bakery wares (P75, up to 5.1 μg/kg bw), Chocolate (Cocoa) products (P75, up to 1.1 μg/kg bw), Energy drinks (P75, up to 0.2 μg/kg bw), Dietary supplements (P75, up to 9.9 μg/kg bw), Beer and beer‐like beverages (P90, up to 41 μg/kg bw). The use of proxies for the consumption of hemp and hemp‐containing products, the limited number of occurrence data and the analytical limitations in the quantification of Δ9‐THC represent the most important sources of uncertainty. Overall, exposure estimates presented in this report are expected to represent an overestimation of acute exposure to Δ9‐THC in the EU.

Simulating the galactic system in interaction AM 2229-735 and the formation of its polar structure

Abstract We study the formation of polar ring galaxies via minor mergers. We used N-body+hydrodynamics simulations to reproduce the dynamics of the observed system AM 2229-735 that is a minor merger whose interaction signals are those of a progenitor for a polar ring galaxy. We used the observational information of the system to get initial conditions for the orbit and numerical realisations of the galaxies to run the simulations. Our simulations reproduce the global characteristics of interaction observed in the system such as arms and a material bridge connecting the galaxies. As a merger remnant, we found a quasi-stable and self gravitating planar tidal stream with dark matter, stars and gas orbiting in a plane approximately perpendicular to the main galaxy disk leading in the future to a polar ring galaxy. We studied the dynamical conditions of the polar structure and found evidence suggesting that this kind of merger remnant can settle down in a disk-like structure with isothermal support, providing inspiring evidence about the process of formation of galactic disks and providing a potentially independent scenario to study the presence of dark matter in this kind of galaxies.

Dynamic Physiological Phenotyping of Drought-Stressed Pepper Plants Treated With "Productivity-Enhancing" and "Survivability-Enhancing" Biostimulants.

The improvement of crop productivity under abiotic stress is one of the biggest challenges faced by the agricultural scientific community. Despite extensive research, the research-to-commercial transfer rate of abiotic stress-resistant crops remains very low. This is mainly due to the complexity of genotype × environment interactions and in particular, the ability to quantify the dynamic plant physiological response profile to a dynamic environment. Most existing phenotyping facilities collect information using robotics and automated image acquisition and analysis. However, their ability to directly measure the physiological properties of the whole plant is limited. We demonstrate a high-throughput functional phenotyping system (HFPS) that enables comparing plants’ dynamic responses to different ambient conditions in dynamic environments due to its direct and simultaneous measurement of yield-related physiological traits of plants under several treatments. The system is designed as one-to-one (1:1) plant–[sensors+controller] units, i.e., each individual plant has its own personalized sensor, controller and irrigation valves that enable (i) monitoring water-relation kinetics of each plant–environment response throughout the plant’s life cycle with high spatiotemporal resolution, (ii) a truly randomized experimental design due to multiple independent treatment scenarios for every plant, and (iii) reduction of artificial ambient perturbations due to the immobility of the plants or other objects. In addition, we propose two new resilience-quantifying-related traits that can also be phenotyped using the HFPS: transpiration recovery rate and night water reabsorption. We use the HFPS to screen the effects of two commercial biostimulants (a seaweed extract –ICL-SW, and a metabolite formula – ICL-NewFo1) on Capsicum annuum under different irrigation regimes. Biostimulants are considered an alternative approach to improving crop productivity. However, their complex mode of action necessitates cost-effective pre-field phenotyping. The combination of two types of treatment (biostimulants and drought) enabled us to evaluate the precision and resolution of the system in investigating the effect of biostimulants on drought tolerance. We analyze and discuss plant behavior at different stages, and assess the penalty and trade-off between productivity and resilience. In this test case, we suggest a protocol for the screening of biostimulants’ physiological mechanisms of action.

Lipper: Speaker Independent Speech Synthesis Using Multi-View Lipreading

Lipreading is the process of understanding and interpreting speech by observing a speaker’s lip movements. In the past, most of the work in lipreading has been limited to classifying silent videos to a fixed number of text classes. However, this limits the applications of the lipreading since human language cannot be bound to a fixed set of words or languages. The aim of this work is to reconstruct intelligible acoustic speech signals from silent videos from various poses of a person which Lipper has never seen before. Lipper, therefore is a vocabulary and language agnostic, speaker independent and a near real-time model that deals with a variety of poses of a speaker. The model leverages silent video feeds from multiple cameras recording a subject to generate intelligent speech of a speaker. It uses a deep learning based STCNN+BiGRU architecture to achieve this goal. We evaluate speech reconstruction for speaker independent scenarios and demonstrate the speech output by overlaying the audios reconstructed by Lipper on the corresponding videos.

On the Role of Syntactic Graph Convolutions for Identifying and Classifying Argument Components

This paper focuses on fundamental research that combines syntactic knowledge with neural studies, which utilize syntactic information in argument component identification and classification (AC-I/C) tasks in argument mining (AM). The following are our paper’s contributions: 1) We propose a way of incorporating a syntactic GCN into multi-task learning models for AC-I/C tasks. 2) We demonstrate the valid effectiveness of our proposed syntactic GCN in fair experiments in some datasets. We also found that syntactic GCNs are promising for lexically independent scenarios. Our code in the experiments is available for reproducibility.1

Post-earthquake Fire Performance of a Generic Fireproofed Steel Moment Resisting Structure

ABSTRACT Post-earthquake fires can result in rapid collapse of structures damaged partially due to prior earthquakes. An investigation is performed here on a seven-story fireproofed steel moment resisting structure designed for the life safety (LS) level of performance and a fire resistance rating (FRR) of 120 min based on the ISO834 fire. Introducing the specifications of fireproofing materials, the structure is first pushed to arrive at its target displacement at the LS level in order to detect the locations where the fireproofing materials have delaminated. The damaged structure is then subjected to three independent fire scenarios in stories 1, 4, and 7. The results indicate that when the fire is in story 1, 4, and 7, the FRR of the structure declines to 48, 39, and 37 min, respectively. A series of sensitivity analyses is also performed to understand how the length of delamination can effect on the FRR. To do this, the delamination lengths are changed to 150%, 75%, and 50% that of the pushover results, and then the PEF analyses are re-performed. The new analyses show that the changes made have no considerable effect on the overall FRR implying that the location of delamination has a dominant role in declining the FRR rather the extent of damage.

Duality of singularities of multiscale damage localization and crack advance: length variety in Theory of Critical Distances

The existence of two singularities related to the stress field at the crack tip and blow-up kinetics of damage localization is considered as the physical basis for the interpretation of the Theory of Critical Distances. The free energy metastability of solid with defects and corresponding free energy release explain the conception of the Finite Fracture Mechanics in the presence of the finite amplitude energy barrier. The variety of crack paths is analyzed as duality of inherently linked two types of singularities related to the singularity of multiscale damage kinetics under crack nucleation and singularity of stress field at the crack tip as the classical framework of fracture mechanics. The singularity of multiscale damage kinetics is a natural precursor of crack nucleation that could provide in some cases the totally independent scenario of fracture from the stress singularity at the crack tips. The influence of two singularities with the nature of intermediate asymptotical solutions for stress at the crack tip and damage localization kinetics over the set of spatial scales represents two attractors, which provides the variety of crack paths for corresponding loading conditions.

Novel aerosol extinction coefficients and lidar ratios over the ocean from CALIPSO–CloudSat: evaluation and global statistics

Abstract. Aerosol extinction coefficients (σa) and lidar ratios (LRs) are retrieved over the ocean from CALIPSO's Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) attenuated backscatter profiles by solving the lidar equation constrained with aerosol optical depths (AODs) derived by applying the Synergized Optical Depth of Aerosols (SODA) algorithm to ocean surface returns measured by CALIOP and CloudSat's Cloud Profiling Radar. σa and LR are retrieved for two independent scenarios that require somewhat different assumptions: (a) a single homogeneous atmospheric layer (1L) for which the LR is constant with height and (b) a vertically homogeneous layer with a constant LR overlying a marine boundary layer with a homogenous LR fixed at 25 sr (two-layer method, 2L). These new retrievals differ from the standard CALIPSO version 4.1 (V4) product, as the CALIOP–SODA method does not rely on an aerosol classification scheme to select LR. CALIOP–SODA σa and LR are evaluated using airborne high-spectral-resolution lidar (HSRL) observations over the northwest Atlantic. CALIOP–SODA LR (1L and 2L) positively correlates with its HSRL counterpart (linear correlation coefficient r&gt;0.67), with a negative bias smaller than 17.4 % and a good agreement for σa (r≥0.78) with a small negative bias (≤|-9.2%|). Furthermore, a global comparison of optical depths derived by CALIOP–SODA and CALIPSO V4 reveals substantial discrepancies over regions dominated by dust and smoke (0.24), whereas Aqua's Moderate resolution Imaging Spectroradiometer (MODIS) and SODA AOD regional differences are within 0.06. Global maps of CALIOP–SODA LR feature high values over littoral zones, consistent with expectations of continental aerosol transport offshore. In addition, seasonal transitions associated with biomass burning from June to October over the southeast Atlantic are well reproduced by CALIOP–SODA LR.

Probabilistic optimization of dose coverage in radiotherapy.

Probabilistic optimization is an alternative to margins for handling geometrical uncertainties in treatment planning of radiotherapy where uncertainties are explicitly incorporated in the optimization. We present a novel probabilistic method based on the same statistical measures as those behind conventional margin based planning. Percentile Dosage (PD) was defined as the dose coverage that a treatment plan meet or exceed to a given probability. For optimization, we used the convex measure Expected Percentile Dosage (EPD) defined as the average dose coverage below a given PD. An iterative method gradually adjusted the constraint tolerance associated with the EPD until the desired target PD was met. It was applied to planning of cervical cancer patients focusing on systematic uncertainty caused by organ deformation. The resulting plans were compared to margin based plans using target and organ at risk PDs. The EPD tolerance converged in less than ten iterations to produce a PD within 0.1 Gy of the requested. The PD was on average within 0.5% of the requested PD when validated versus independent scenarios. The rectum volume, extracted from the PDs, receiving 90% of the intended target dose was decreased with 16% for the same target PD in comparison to margin based plans. The proposed probabilistic optimization method enabled prescription of a dose volume histogram metric to a chosen confidence. The probabilistic plans showed improved target dose homogeneity and decreased rectum dose for the same target dose coverage compared to margin based plans.

α′-Corrections and de Sitter vacua - A mirage?

In this work we analyze the role of α′-corrections to type IIB orientifold compactifications in Kähler moduli stabilization and inflation. In particular, we propose a model independent scenario to achieve non-supersymmetric Minkowski and de Sitter vacua for geometric backgrounds with positive Euler-characteristic and generic number of Kähler moduli. The vacua are obtained by a tuning of the flux superpotential. Moreover, in the one-modulus case we argue for a mechanism to achieve model independent slow-roll.

Magnetic field effects on the proton EDM in a continuous all-electric storage ring

The electric dipole moment of the proton can be searched in an electric storage ring by measuring the spin precession rate of the proton beam on the vertical plane. In the ideal case, the spin precession originates from the coupling between the electric field and the electric dipole moment. In a more realistic scenario, the magnetic field becomes a major systematic error source as it couples with the magnetic dipole moment in a similar way. The beam can see the magnetic field in various configurations which include direction, time dependence, etc. For instance, geometric phase effect is observed when the beam sees the field at different directions and phases periodically. We have simulated the effect of magnetic fields in major independent scenarios and found consistent results with the analytical estimations of the static magnetic field cases. We have set a limit for the magnetic field in each scenario and proposed solutions to avoid systematic errors from magnetic fields.