The N=1 effective actions of D-branes in Type IIA and IIB orientifolds

We discuss the four-dimensional N=1 effective actions of single space-time filling Dp-branes in general Type IIA and Type IIB Calabi-Yau orientifold compactifications. The effective actions depend on an infinite number of normal deformations and gauge connection modes. For D6-branes the N=1 Kaehler potential, the gauge-coupling function, the superpotential and the D-terms are determined as functions of these fields. They can be expressed as integrals over chains which end on the D-brane cycle and a reference cycle. The infinite deformation space will reduce to a finite-dimensional moduli space of special Lagrangian submanifolds upon imposing F- and D-term supersymmetry conditions. We show that the Type IIA moduli space geometry is captured by three real functionals encoding the deformations of special Lagrangian submanifolds, holomorphic three-forms and Kaehler two-forms of Calabi-Yau manifolds. These elegantly combine in the N=1 Kaehler potential, which reduces after applying mirror symmetry to the results previously determined for space-time filling D3-, D5- and D7-branes. We also propose general chain integral expressions for the Kaehler potentials of Type IIB D-branes.Comment: 61 pages, v2: typos corrected and refs adde

NTRC and TRX-f Coordinately Affect the Levels of Enzymes of Chlorophyll Biosynthesis in a Light-Dependent Manner

This article was supported by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universität zu Berlin.Redox regulation of plastid gene expression and different metabolic pathways promotes many activities of redox-sensitive proteins. We address the question of how the plastid redox state and the contributing reducing enzymes control the enzymes of tetrapyrrole biosynthesis (TBS). In higher plants, this metabolic pathway serves to produce chlorophyll and heme, among other essential end products. Because of the strictly light-dependent synthesis of chlorophyll, tight control of TBS requires a diurnal balanced supply of the precursor 5-aminolevulinic acid (ALA) to prevent the accumulation of photoreactive metabolic intermediates in darkness. We report on some TBS enzymes that accumulate in a light intensity-dependent manner, and their contents decrease under oxidizing conditions of darkness, low light conditions, or in the absence of NADPH-dependent thioredoxin reductase (NTRC) and thioredoxin f1 (TRX-f1). Analysis of single and double trxf1 and ntrc mutants revealed a decreased content of the early TBS enzymes glutamyl-tRNA reductase (GluTR) and 5-aminolevulinic acid dehydratase (ALAD) instead of an exclusive decrease in enzyme activity. This effect was dependent on light conditions and strongly attenuated after transfer to high light intensities. Thus, it is suggested that a deficiency of plastid-localized thiol-redox transmitters leads to enhanced degradation of TBS enzymes rather than being directly caused by lower catalytic activity. The effects of the proteolytic activity of the Clp protease on TBS enzymes were studied by using Clp subunit-deficient mutants. The simultaneous lack of TRX and Clp activities in double mutants confirms the Clp-induced degradation of some TBS proteins in the absence of reductive activity of TRXs. In addition, we verified previous observations that decreased chlorophyll and heme levels in ntrc could be reverted to WT levels in the ntrc/Δ2cp triple mutant. The decreased synthesis of 5-aminolevulinic acid and porphobilinogen in ntrc was completely restored in ntrc/Δ2cp and correlated with WT-like levels of GluTR, ALAD, and other TBS proteins

Context-aware Security for Vehicles and Fleets: A Survey

Vehicles are becoming increasingly intelligent and connected. Interfaces for communication with the vehicle, such as WiFi and 5G, enable seamless integration into the user’s life, but also cyber attacks on the vehicle. Therefore, research is working on in-vehicle countermeasures such as authentication, access controls, or intrusion detection. Recently, legal regulations have also become effective that require automobile manufacturers to set up a monitoring system for fleet-wide security analysis. The growing amount of software, networking, and the automation of driving create new challenges for security. Context-awareness, situational understanding, adaptive security, and threat intelligence are necessary to cope with these ever-increasing risks. In-vehicle security should be adaptive to secure the car in an infinite number of (driving) situations. For fleet-wide analysis and alert triage, knowledge and understanding of the circumstances are required. Context-awareness, nonetheless, has been sparsely considered in the field of vehicle security. This work aims to be a precursor to context-aware, adaptive and intelligent security for vehicles and fleets. To this end, we provide a comprehensive literature review that analyzes the vehicular as well as related domains. Our survey is mainly characterized by the detailed analysis of the context information that is relevant for vehicle security in the future

Carbon Footprint of IT-Services – A comparative Study of energy consumption for Offline and Online Storage Usage

This paper focusses on the Carbon Footprint of IT-Services (CFIS) by presenting a comparative study of energy consumption for Offline and Online Storage. We therefore conducted a case study with an IT-Service provider as well as experimental simulation of customer’s ICT hardware. Based on literature review, we initially present related work and describe underlying concepts e.g. Carbon Footprint of Products, Life Cycle Assessment (LCA) as well as ICT energy and performance measurement. The paper proposes a methodological framework for CFIS based on the phases of LCA. Geared towards the framework we present a comparison of ICT-related energy consumptions for Offline and Online Storage as well as allocation and calculation approaches. Finally, presented carbon footprint results are discussed in terms of limitations and further research directions. The CFIS is an inevitable step to advance Green IS/IT research, since it quantifies dependencies between IT-Services, ICT energy consumption and related greenhouse gas emissions

The Effects of Vitamin D Deficiency on Neurodegenerative Diseases

Approximately 90% of the elderly population in the western countries has at least a mild to moderate vitamin D hypovitaminosis. Besides the well-known function of vitamin D in calcium homeostasis, it has been recently found that several enzymes and receptors involved in its homeostasis are expressed in the nervous system and brain suggesting also an important role in the brain homeostasis. Interestingly, epidemiological and clinical studies found reduced vitamin D level associated with an increased risk of several neurodegenerative disorders. In this chapter, we focus on a potential link between vitamin D and Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, prion disease, and motor neuron disease. Epidemiological studies were summarized, an overview of the known potential underlying pathomolecular mechanisms are given, and results from clinical studies dealing with vitamin D supplementation were presented. As an outlook, recent literature suggesting an impact of vitamin D on autism spectrum disease, depression, and schizophrenia are briefly discussed. In conclusion, the identification of an abundant vitamin D metabolism in the brain and the tight link between the increasing number of several neurological and mental disorders emphasize the need of further research making a clear recommendation of the intake and supplementation of vitamin D in a growing elderly population

Artificial Intelligence in Supply Chain Management: Investigation of Transfer Learning to Improve Demand Forecasting of Intermittent Time Series with Deep Learning

Demand forecasting intermittent time series is a challenging business problem. Companies have difficulties in forecasting this particular form of demand pattern. On the one hand, it is characterized by many non-demand periods and therefore classical statistical forecasting algorithms, such as ARIMA, only work to a limited extent. On the other hand, companies often cannot meet the requirements for good forecasting models, such as providing sufficient training data. The recent major advances of artificial intelligence in applications are largely based on transfer learning. In this paper, we investigate whether this method, originating from computer vision, can improve the forecasting quality of intermittent demand time series using deep learning models. Our empirical results show that, in total, transfer learning can reduce the mean square error by 65 percent. We also show that especially short (65 percent reduction) and medium long (91 percent reduction) time series benefit from this approach

Gender and Rapid Alterations of Hemispheric Dominance during Planning

Background: Mental planning and carrying out a plan provoke specific cerebral hemodynamic responses. Gender aspects of hemispheric laterality using rapid cerebral hemodynamics have not been reported. Method: Here, we applied functional transcranial Doppler sonography to examine lateralization of cerebral hemodynamics of the middle cerebral arteries of 28 subjects (14 women and 14 men) performing a standard planning task. There were easy and difficult problems, and mental planning without motor activity was separated from movement execution. Results: Difficult mental planning elicited lateralization to the right hemisphere after 2 or more seconds, a feature that was not observed during movement execution. In females, there was a dominance to the left hemisphere during movement execution. Optimized problem solving yielded an increased laterality change to the right during mental planning. Conclusions: Gender-related hemispheric dominance appears to be condition-dependent, and change of laterality to the right may play a role in optimized performance. Results are of relevance when considering laterality from a perspective of performance enhancement of higher cognitive functions, and also of psychiatric disorders with cognitive dysfunctions and abnormal lateralization patterns such as schizophrenia. Copyright (C) 2012 S. Karger AG, Base