Energy Markets and the Financial Environment

Energy is an essential component of the modern economy, the amenities it offers, and the impact it has on human lives. This thesis focuses on four important topics in energy markets. Some of the main themes and questions that we address are the following. Liquidity of markets is important as it allows more efficient pricing. How different aspects of market liquidity are connected, and what happens during illiquid periods? Does oil price play a role in energy stocks liquidity? Energy assets’ price differences between different locations are an important aspect of market efficiency and integration. Are oil price differences between two main products, Brent and WTI, affected by fundamental factors? Will electricity prices in European countries move closer together with increased cross-border transmission capacity? Economic growth has been closely linked with increased energy consumption. This has also led to more CO2 emissions. What is the contribution of renewable and nuclear power generation to mitigating CO2 emissions

Secure and Efficient RNS Approach for Elliptic Curve Cryptography

Scalar multiplication, the main operation in elliptic curve cryptographic protocols, is vulnerable to side-channel (SCA) and fault injection (FA) attacks. An efficient countermeasure for scalar multiplication can be provided by using alternative number systems like the Residue Number System (RNS). In RNS, a number is represented as a set of smaller numbers, where each one is the result of the modular reduction with a given moduli basis. Under certain requirements, a number can be uniquely transformed from the integers to the RNS domain (and vice versa) and all arithmetic operations can be performed in RNS. This representation provides an inherent SCA and FA resistance to many attacks and can be further enhanced by RNS arithmetic manipulation or more traditional algorithmic countermeasures. In this paper, extending our previous work, we explore the potentials of RNS as an SCA and FA countermeasure and provide an description of RNS based SCA and FA resistance means. We propose a secure and efficient Montgomery Power Ladder based scalar multiplication algorithm on RNS and discuss its SCAFA resistance. The proposed algorithm is implemented on an ARM Cortex A7 processor and its SCA-FA resistance is evaluated by collecting preliminary leakage trace results that validate our initial assumptions

REDOX MODULATION PROTECTS FROM ANTIGEN-DEPENDENT AND ANTIGEN-INDEPENDENT INJURY IN ISLET TRANSPLANTATION

The preservation of reactive oxygen species (ROS) throughout evolution is evidence that ROS are critical components in immunity. These constituents ignite a multitude of redox-dependent pathways triggering pro-inflammatory cytokine production, dendritic cell maturation, and subsequent T cell activation in response to pathogen, autoimmune, and alloimmune insults. The aim of this thesis is to test the ability of redox modulation to suppress aberrant immune responses in islet transplantation. Presently, islet transplantation is only used in desperate cases of glucose dysregulation due to the high failure rate of the procedure, which forces the majority of recipients to resume exogenous insulin within a year of islet transplantation. Hurdles in islet transplantation include hypoxia during islet isolation and ischemia-reperfusion injury upon transplantation. These insults result in primary non-function of islets, while harsh immunosuppressive agents yield islet toxicity and a multitude of complications for the recipient. We tested a catalytic antioxidant (CA), FBC-007, in islet transplantation based on previous work demonstrating that CA impairs innate-immune ROS and pro-inflammatory cytokine production by inhibiting NFκB-DNA binding, hinders CD4 T cell activation, and prevents the transfer of diabetes into young NOD.scid mice. First, the effects of redox modulation on CD8 T cell effector function in allogeneic and transgenic responses were examined in vitro. Human islets were also used in vitro and murine experiments were performed in vivo to test the ability of CA to protect from streptozotocin-induced islet cell death. Additionally, murine islets were incubated with CA in in vivo models of ischemia-reperfusion injury (antigen-independent) or allogeneic (antigen-dependent) transplantation and separately, CA was used as a systemic therapy for allograft recipients. Further experiments were performed to elucidate in vivo protective mechanisms of CA-treatment. An additional approach of interest is the induction of antigen-specific hyporesponsiveness to replace nonspecific immunosuppression. A negative vaccination strategy delivering apoptotic donor alloantigen in a non-inflammatory adjuvant prior to allograft transplantation, was also tested. Collectively, this work demonstrates 1) CA is a non-toxic, islet-sparing, cytoprotective, and immunomodulatory agent capable of promoting islet-function, 2) CA impairs the alloimmune response to induce antigen-specific hyporesponsiveness, and 3) the negative vaccination protocol achieves long-term allograft tolerance

Green Entrepreneurship and Digital Transformation of SMEs in Food Industry: Α Bibliometric Analysis

The emerging of green entrepreneurship and digital transformation improve businesses’ efficiency and meet consumers’ demand for environmentally sustainable products, reducing the environmental footprint and strengthening corporate responsibility to society. Moreover, the COVID-19 pandemic has become a key event changing our lives while businesses have to change their daily operations and working from home has become the norm. So, it is possible to say that business activities and business models have undergone some form of digital transformation due to the COVID-19 pandemic. In Greece, the Food Industry can be characterized as one of the most dynamic and competitive economic sectors which is distinguished for its growth prospects. The aim of this study is twofold: (i) to investigate the impact of green entrepreneurship and digital transformation into the performance of Greek SMEs in the food sector and (ii) to highlight the new trends integrated in new business models in the sector. To meet the research purpose, a bibliometric and co-citation analysis was used based on the R package and graphene as a subject of research for bibliometric analysis. The knowledge gained in this article shows how the digital transformation changed the functioning of the companies in the food industry. The conclusions of this article are mainly for the enterprises that are considering their own digitalization, which contributes to the long-term sustainability of them

A Bayesian approach for correcting bias of data envelopment analysis estimators

The validity of data envelopment analysis (DEA) efficiency estimators depends on the robustness of the production frontier to measurement errors, specification errors and the dimension of the input-output space. It has been proven that DEA estimators, within the interval (0, 1], are overestimated when finite samples are used while asymptotically this bias reduces to zero. The non-parametric literature dealing with bias correction of efficiencies solely refers to estimators that do not exceed one. We prove that efficiency estimators, both lower and higher than one, are biased. A Bayesian DEA method is developed to correct bias of efficiency estimators. This is a two-stage procedure of super-efficiency DEA followed by a Bayesian approach relying on consistent efficiency estimators. This method is applicable to ‘small’ and ‘medium’ samples. The new Bayesian DEA method is applied to two data sets of 50 and 100 E.U. banks. The mean square error, root mean square error and mean absolute error of the new method reduce as the sample size increases

A Bayesian approach for correcting bias of data envelopment analysis estimators

The validity of data envelopment analysis (DEA) efficiency estimators depends on the robustness of the production frontier to measurement errors, specification errors and the dimension of the input-output space. It has been proven that DEA estimators, within the interval (0, 1], are overestimated when finite samples are used while asymptotically this bias reduces to zero. The non-parametric literature dealing with bias correction of efficiencies solely refers to estimators that do not exceed one. We prove that efficiency estimators, both lower and higher than one, are biased. A Bayesian DEA method is developed to correct bias of efficiency estimators. This is a two-stage procedure of super-efficiency DEA followed by a Bayesian approach relying on consistent efficiency estimators. This method is applicable to ‘small’ and ‘medium’ samples. The new Bayesian DEA method is applied to two data sets of 50 and 100 E.U. banks. The mean square error, root mean square error and mean absolute error of the new method reduce as the sample size increases

Low Power FPGA Implementations of 256-bit Luffa Hash Function

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