Hadron energy spectrum in polarized top quark decays considering the effects of hadron and bottom quark masses

We present the analytical expressions for the next-to-leading order corrections to the partial decay width $t(\uparrow) \rightarrow bW^+$, followed by $b\rightarrow H_bX$, for nonzero b-quark mass ($m_b\neq 0$) in the fixed-flavor-number scheme (FFNs). To make the predictions for the energy distribution of outgoing hadrons $H_b$, as a function of the normalized $H_b$-energy fraction $x_H$, we apply the general-mass variable-flavor-number scheme (GM-VFNs) in a specific helicity coordinate system where the polarization of top quark is evaluated relative to the b-quark momentum. We also study the effects of gluon fragmentation and finite hadron mass on the hadron energy spectrum so that hadron masses are responsible for the low-$x_H$ threshold. In order to describe both the b-quark and the gluon hadronizations in top decays we apply realistic and nonperturbative fragmentation functions extracted through a global fit to $e^+e^-$ annihilation data from CERN LEP1 and SLAC SLC by relying on their universality and scaling violations

Connected Simulation for Work Zone Safety Application

Every year, over 60,000 work zone crashes are reported in the United States (FHWA 2016). Such work zone crashes have resulted in over 4,400 fatal and 200,000 non-fatal injuries in the last 5 years (FHWA 2016, BLS 2014). Apart from the physical and emotional trauma, the annual cost of these injuries exceeds $4 million-representing significant wasted resources. To improve work zone safety, this research developed a system architecture for unveiling high-risk behavioral patterns among highway workers, equipment operators, and drivers within dynamic highway work zones. This research implemented the use of a connected virtual environment, which is an immersive hyper-realistic and virtual environment where multiple agents (e.g. workers, drivers, and equipment handlers) control independent simulators but experience an interactive and shared experience. For this project, the team conducted an in-depth analysis of accident investigation, simulated accident scenarios, and tested diverse interventions to prevent high-risk behavior. Overall, the research improved understanding of behavioral patterns that lead to injuries and fatalities of highway workers in order to better protect them in high-risk work environments. As part of making transportation smarter, this project contributes to smart behavioral safety analysis

System-of-Systems Integration for Civil Infrastructures Resiliency Toward MultiHazard Events

Civil infrastructure systems—facilities that supply principal services, such as electricity, water, transportation, etc., to a community—are the backbone of modern society. These systems are frequently subject to multi-hazard events, such as earthquakes. The poor resiliency of these infrastructures results in many human casualties and significant economic losses every year. An outline of a holistic view that considers how different civil infrastructure systems operate independently and how they interact and communicate with each other is required to have a resilient infrastructure system. More specifically a systems engineering approach is required to enable infrastructure to remain resilient in the case of extreme events, including natural disasters. To address these challenges, this research builds on the proposal that the infrastructure systems be equipped with state-of-the-art sensor networks that continuously record the condition and performance of the infrastructure. The sensor data from each infrastructure are then transferred to a data analysis system component that employs artificial intelligence techniques to constantly analyze the infrastructure’s resiliency and energy efficiency performance. This research models the resilient infrastructure problem as a System of Systems (SoS) comprised of the abovementioned components. It explores system integration and operability challenges and proposes solutions to meet the requirements of the SoS. An integration ontology, as well as a data-centric architecture, is developed to enable infrastructure resiliency toward multi-hazard events. The Federal Emergency Management Agency (FEMA), and infrastructure managers, such as Departments of Transportation (DOTs) and the Federal Highway Administration (FHWA), can learn from and integrate these solutions to make civil infrastructure systems more resilient for all

Air Pollution and Economic Sanctions in Iran

This study aims to simulate the future trends of carbon emissions under different international sanction scenarios in Iran. A System Dynamics (SD) model is developed and several variables that capture multiple levels of economic, social, and environmental concepts are taken into account. Our findings indicate that, despite Iran's sluggish economic growth, fossil fuel use and CO2 emissions will rise in the scenarios with international sanctions. Imposed sanctions on Iran exacerbate the environmental negative externalities through increasing energy intensity of economic sectors and consequently cause more CO2 emissions. Thus, based on our findings, prolonging international sanctions could be a major barrier to improving energy intensity and lowering CO2 emissions. Given the potential unintended environmental consequences of international sanctions, this study suggests that international communities, particularly sanctioning countries, should consider the environmental impacts of sanctions in their policy-making decisions in order to reduce emissions and related environmental damages

Towards reflexive land and water management in Iran : linking technology, governance and culture

Key words: Qanat, land and water, sustainability, Industrial and reflexive modernity This PhD thesis is concerned with the causes and consequences of the environmental crisis and explores possible trajectories towards sustainable land and water management in Iran and other countries of the Middle East and North Africa (MENA). The basic assumption underlying the conceptual framework of this thesis is that soil and water technologies, social institutions and environmental mentalities are strongly interconnected; they co-evolve, shaping and reshaping one another in the process. The main research question concerns the changes within this network of technologies, institutions and mentalities that are required for a successful transition from industrial modernity to what sociologists like Ulrich Beck, Anthony Giddens and Scott Lash have called ‘reflexive’ modernity. In order to examine the possibilities and problems of a reflexive turn in land and water management in Iran and other MENA-countries, large-scale empirical studies were conducted among farmers and village informants, soil and water experts, and policymakers. </p

Chronic health effects of sulphur mustard exposure with special reference to Iranian veterans

The widespread use of sulphur mustard (SM) as an incapacitating chemical warfare agent in the past century has proved its long-lasting toxic effects. It may also be used as a chemical terrorist agent. Therefore, all health professionals should have sufficient knowledge and be prepared for any such chemical attack. SM exerts direct toxic effects on the eyes, skin, and respiratory tissue, with subsequent systemic action on the nervous, immunological, haematological, digestive, and reproductive systems. SM is an alkylating agent that affects DNA synthesis, and, thus, delayed complications have been seen since the First World War. Cases of malignancies in the target organs, particularly in haematopoietic, respiratory, and digestive systems, have been reported. Important delayed respiratory complications include chronic bronchitis, bronchiectasis, frequent bronchopneumonia, and pulmonary fibrosis, all of which tend to deteriorate with time. Severe dry skin, delayed keratitis, and reduction of natural killer cells with subsequent increased risk of infections and malignancies are also among the most distressing long-term consequences of SM intoxication. However, despite a lot of research over the past decades on Iranian veterans, there are still major gaps in the SM literature. Immunological and neurological dysfunction, as well as the relationship between SM exposure and mutagenicity, carcinogenicity, and teratogenicity are important fields that require further studies, particularly on Iranian veterans with chronic health effects of SM poisoning. There is also a paucity of information on the medical management of acute and delayed toxic effects of SM poisoning—a subject that greatly challenges health care specialists

A Data-Driven Predictive Model of Reliability Estimation Using State-Space Stochastic Degradation Model

The concept of the Industrial Internet of Things (IIoT) provides the foundation to apply data-driven methodologies. The data-driven predictive models of reliability estimation can become a major tool in increasing the life of assets, lowering capital cost, and reducing operating and maintenance costs. Classical models of reliability assessment mainly rely on lifetime data. Failure data may not be easily obtainable for highly reliable assets. Furthermore, the collected historical lifetime data may not be able to accurately describe the behavior of the asset in a unique application or environment. Therefore, it is not an optimal approach anymore to conduct a reliability estimation based on classical models. Fortunately, most of the industrial assets have performance characteristics whose degradation or decay over the operating time can be related to their reliability estimates. The application of the degradation methods has been recently increasing due to their ability to keep track of the dynamic conditions of the system over time. The main purpose of this study is to develop a data-driven predictive model of reliability assessment based on real-time data using a state-space stochastic degradation model to predict the critical time for initiating maintenance actions in order to enhance the value and prolonging the life of assets. The new degradation model developed in this thesis is introducing a new mapping function for the General Path Model based on series of Gamma Processes degradation models in the state-space environment by considering Poisson distributed weights for each of the Gamma processes. The application of the developed algorithm is illustrated for the distributed electrical systems as a generic use case. A data-driven algorithm is developed in order to estimate the parameters of the new degradation model. Once the estimates of the parameters are available, distribution of the failure time, time-dependent distribution of the degradation, and reliability based on the current estimate of the degradation can be obtained

A novel design of 5-input majority gate in quantum-dot cellular automata technology

Quantum-dot Cellular Automata (QCA) technology is one of the most important technologies, which can be suitable replacement for conventional technologies at Nano-scale. The principle logic elements in the QCA technology are majority gates and inverters. In this paper, a novel design is proposed for 5-input majority gate in the QCA technology. The proposed 5-input majority gate uses half distance. The QCADesigner tool version 2.0.3 is utilized for verifying functionality and layout of the proposed majority gate. The simulation results demonstrate that the proposed 5-input majority gate design provides significant improvements in the logical circuit design in terms of area and the number of required cells in comparison with other majority gates

Computational and experimental studies of bilayer peptide interactions

This thesis describes the combination of experimental (neutron diffraction) and computational techniques (molecular dynamics simulations) to investigate membrane peptide interactions.The first part deals with a comparison of human and rat form of the amyloid inducing peptide islet amyloid polypeptide (IAPP). Lamellar neutron diffraction was performed and a structural comparison on the differing modes of actions of the rat and human forms of IAPP are reported.A computational model for a di-oleoyl phosphatidylcholine (DOPC) bilayer was then constructed. Once this bilayer had been verified with experimental data (namely area per headgroup, volume per lipid, order parameter of the oleoyl chains and electron density profile) a mixed bilayer of DOPC and di-oleoyl phopshatidylglycerol (DOPG) was then constructed. The mixed bilayer was verified in the same mannerA peptide (adenosine diphosphate ribosylation factor-1 (pARF-1)) was then inserted into the pre-equilibrated mixed bilayer. The orientation of this peptide with respect to the membrane was based on previous neutron diffraction studies, carried out by other group members. Four possible orientations had resulted from analysis of the neutron data. The four orientations of pARF-1 were then subjected to molecular dynamics simulations. The time course of these simulations was 4 ns. The simulation's trajectories were analysed for each of the four models. Particular emphasis was placed upon the positional changes of the phenylalanine label positions that were derived from the neutron data. It was concluded that model A was the most likely orientation of pARF-1 in relation to the bilayer.Having established the technique, and confirmed that the most likely orientation of the peptide was what was originally proposed, another peptide, the fusion peptide of simian immunodeficiency virus (SIV) was placed into a previously equilibrated DOPC bilayer. In this case, only the proposed orientation of the SIV fusion peptide in relation to the bilayer was studied utilizing molecular dynamics simulations. The results are interpreted in relation to the actions of SIV fusion peptide upon the membrane, with particular emphasis on the disruption of oleoyl chain order parameters and secondary structure of the membrane bound fusion peptide