Social, environmental and economic impacts of alternative energy and fuel supply chains

Energy supply nowadays, being a vital element of a country’s development, has to independently meet diverse, sustainability criteria, be it economic, environmental and social. The main goal of the present research work is to present a methodological framework for the evaluation of alternative energy and fuel Supply Chains (SCs), consisting of a broad topology (representation) suggested, encompassing all the well-known energy and fuel SCs, under a unified scheme, a set of performance measures and indices as well as mathematical model development, formulated as Multi-objective Linear Programming with the extension of incorporating binary decisions as well (Multi-objective Mixed Integer-Linear programming). Basic characteristics of the current modelling approach include the adaptability of the model to be applied at different levels of energy SCs decisions, under different time frames and for multiple stakeholders. Model evaluation is carried for a set of Greek islands, located in the Aegean Archipelagos, examining both the existing energy supply options as well future, more sustainable Energy Supply Chains (ESCs) configurations. Results of the specific research work reveal the social and environmental costs which are underestimated under the traditional energy supply options' evaluation, as well as the benefits that may be produced from renewable energy based applications in terms of social security and employment

THE ROLE OF LEADERSHIP IN CORRUPTION AND MISCONDUCT SCANDALS IN THE U.S. MILITARY

Includes Supplementary MaterialThis study explores the role of leadership in three high-profile corruption and misconduct scandals—the Fat Leonard scandal, the murder of SPC Vanessa Guillén, and the Abu Ghraib Prison scandal—that occurred in the U.S. military over several decades. Additionally, the research delves into the culture of corrupt military commands and investigates patterns of leadership behavior that set the conditions for wrongdoing to occur. This way, the research goes beyond the often-cited “one bad apple” explanation examining organizational wrongdoing as a process. Using a qualitative research approach and utilizing an existing theoretical model, I categorize and evaluate publicly available data. The research findings illustrate that leaders’ actions or inaction directly triggered corruption or misconduct in two out of three scandals; however, leadership was indirectly involved in the third case study. Organizational culture also had a normalizing effect attracting more severe transgression. Lastly, leaders were found mindful of misbehavior in all cases, tacitly or overtly authorized misconduct, and failed to cultivate an ethical organizational culture. These results show that systemic deficiencies and leadership failures continue afflicting DOD and articulate the need for more drastic policies. Based on the findings, recommendations for the DOD are provided and explained.Outstanding ThesisLohagos, Hellenic ArmyApproved for public release. Distribution is unlimited

Development of a Network of Accurate Ozone Sensing Nodes for Parallel Monitoring in a Site Relocation Study

Recent technological advances in both air sensing technology and Internet of Things (IoT) connectivity have enabled the development and deployment of remote monitoring networks of air quality sensors. The compact size and low power requirements of both sensors and IoT data loggers allow for the development of remote sensing nodes with power and connectivity versatility. With these technological advancements, sensor networks can be developed and deployed for various ambient air monitoring applications. This paper describes the development and deployment of a monitoring network of accurate ozone (O3) sensor nodes to provide parallel monitoring in an air monitoring site relocation study. The reference O3 analyzer at the station along with a network of three O3 sensing nodes was used to evaluate the spatial and temporal variability of O3 across four Southern California communities in the San Bernardino Mountains which are currently represented by a single reference station in Crestline, CA. The motivation for developing and deploying the sensor network in the region was that the single reference station potentially needed to be relocated due to uncertainty that the lease agreement would be renewed. With the implication of siting a new reference station that is also a high O3 site, the project required the development of an accurate and precise sensing node for establishing a parallel monitoring network at potential relocation sites. The deployment methodology included a pre-deployment co-location calibration to the reference analyzer at the air monitoring station with post-deployment co-location results indicating a mean absolute error (MAE) < 2 ppb for 1-h mean O3 concentrations. Ordinary least squares regression statistics between reference and sensor nodes during post-deployment co-location testing indicate that the nodes are accurate and highly correlated to reference instrumentation with R2 values > 0.98, slope offsets < 0.02, and intercept offsets < 0.6 for hourly O3 concentrations with a mean concentration value of 39.7 ± 16.5 ppb and a maximum 1-h value of 94 ppb. Spatial variability for diurnal O3 trends was found between locations within 5 km of each other with spatial variability between sites more pronounced during nighttime hours. The parallel monitoring was successful in providing the data to develop a relocation strategy with only one relocation site providing a 95% confidence that concentrations would be higher there than at the current site

The Applicability of RFID for Indoor Localization

Chapter 11 : The applicability of RFID for indoor localizatio

Herd behavior in the drybulk market: An empirical analysis of the decision to invest in new and retire existing fleet capacity

We examine whether investors herd in their decision to order or scrap vessels in the drybulk market. We decompose herding into unintentional and intentional, and test for herd behavior under asymmetric effects with respect to freight market states, cycle phases, risk-return and valuation profiles, and ownership of the vessel. We detect unintentional herd behavior during down freight markets and contractions. Furthermore, we find evidence of spill-over unintentional herding effects from the newbuilding to the scrap market. Finally, asymmetric herd effects are evident between traditional and liberal philosophy towards the ownership of the vessel, and during extreme risk-return and valuation periods

A Simple and Fast Method for the Formation and Downstream Processing of Cancer-Cell-Derived 3D Spheroids: An Example Using Nicotine-Treated A549 Lung Cancer 3D Spheres.

Although 2D in vitro cancer cell cultures have been used for decades as a first line-of-research tool to investigate antitumoral drugs and treatments, their use presents many drawbacks, including the poor resemblance of such cultures to the characteristics of in vivo tumors. To mitigate these drawbacks, 3D culture models have emerged as a more representative alternative. Cancer cells cultured as 3D structures have the advantage of resembling solid tumors in their architecture and in their resistance to chemotherapeutic drugs, in part because of restrained drug penetration. Additionally, these 3D structures create a more physiological environment for the study of immune cell invasion and migration, comparable to solid tumors. In this paper, we describe a fast and cost-effective step-by-step protocol for the generation of 3D spheres using ultra-low-attachment (ULA) multiwell plates, which can be incorporated into the normal workflow of any laboratory. Using this protocol, spheroids of different human cancer cell lines can be obtained and can then be characterized on the basis of their morphology, viability, and expression of specific markers

Freight options: Price modelling and empirical analysis

This paper discusses an extension of the traditional lognormal representation for the risk neutral spot freight rate dynamics to a diffusion model overlaid with jumps of random magnitude and arrival. Then, we develop a valuation framework for options on the average spot freight rate, which are commonly traded in the freight derivatives market. By exploiting the computational efficiency of the proposed pricing scheme, we calibrate the jump diffusion model using market quotes of options on the trip-charter route average Baltic Capesize, Panamax and Supramax Indices. We show that the jump-extended setting yields important model improvements over the basic lognormal setting

Freight Derivatives Pricing for Decoupled Mean-Reverting Diffusion and Jumps

We develop an accurate valuation setup for freight options, featuring an exponential meanreverting model for the freight rate with distinct reversion scales for its jump and diffusion components. We calibrate to Baltic option prices and analyze the freight rate dynamics. More specifically, we observe that jumps dissipate faster than the diffusive deviations about the equilibrium level. We benchmark against practitioners’ model of choice, i.e., the lognormal model and variants, and find that our approach reduces the pricing error while preserving analytical tractability and computational competence. We also find that neglecting fast mean-reverting jumps leads to nontrivial option mispricings

Shipping equity risk behavior and portfolio management

This paper investigates the dynamics of stock price volatility for different vessel-type segments of the U. S, water transportation industry . We measure market exposure by a portfolio of tanker, dry bulk, container, and gas stocks to examine tail behavior and tail risk dependence. The role of mixture distributions in predicting future volatility is studied from both statistical and economic perspectives. We further test for predictability in co-movements in the tails of sectors returns . Findings indicate that large losses are strongly correlated, supporting asymmetric transmission processes for financial contagion. Finally, using a non-parametric approach, we extend the model to the multivariate case and assess the value of volatility and correlation timing in optimal portfolio selection. The results can help to improve the understanding of time-varying volatility, correlation and tail systemic risk of shipping stock markets, and consequently, have implications for risk management and asset allocation practices, as well as regulatory policies