Theory of ferromagnetic (III,Mn)V semiconductors

The body of research on (III,Mn)V diluted magnetic semiconductors initiated during the 1990's has concentrated on three major fronts: i) the microscopic origins and fundamental physics of the ferromagnetism that occurs in these systems, ii) the materials science of growth and defects and iii) the development of spintronic devices with new functionalities. This article reviews the current status of the field, concentrating on the first two, more mature research directions. From the fundamental point of view, (Ga,Mn)As and several other (III,Mn)V DMSs are now regarded as textbook examples of a rare class of robust ferromagnets with dilute magnetic moments coupled by delocalized charge carriers. Both local moments and itinerant holes are provided by Mn, which makes the systems particularly favorable for realizing this unusual ordered state. Advances in growth and post-growth treatment techniques have played a central role in the field, often pushing the limits of dilute Mn moment densities and the uniformity and purity of materials far beyond those allowed by equilibrium thermodynamics. In (III,Mn)V compounds, material quality and magnetic properties are intimately connected. In the review we focus on the theoretical understanding of the origins of ferromagnetism and basic structural, magnetic, magneto-transport, and magneto-optical characteristics of simple (III,Mn)V epilayers, with the main emphasis on (Ga,Mn)As. The conclusions we arrive at are based on an extensive literature covering results of complementary ab initio and effective Hamiltonian computational techniques, and on comparisons between theory and experiment.Comment: 58 pages, 49 figures Version accepted for publication in Rev. Mod. Phys. Related webpage: http://unix12.fzu.cz/ms

Determinants in the on-line distribution of digital content: an exploratory analysis

This article shows the phases – and discusses the results – of an empirical analysis addressing the legal business models that are adopted online to distribute digital content

One health in the U.S. military: a review of existing systems and recommendations for the future

2014 Summer.Includes bibliographical references.Background: The merging of the former U.S. Army Veterinary Command (VETCOM) with the former U.S. Army Center for Health Promotion and Preventive Medicine (USACHPPM) into the U.S. Army Public Health Command (USAPHC) in 2011 created an opportunity for the military to fully embrace the One Health concept. That same year, the USAPHC began work on a Zoonotic Disease Report (ZDR) aimed at supporting critical zoonotic disease risk assessments by combining zoonotic disease data from human, entomological, laboratory, and animal data sources. The purpose of this dissertation is to facilitate the creation of a military Zoonotic Disease Surveillance program that combines disease data from both military human and animal sources. Methods: Five of the most commonly used human military medical data systems were systematically reviewed using a standardized template based on Centers for Disease Control and Preventive Medicine (CDC) guidelines. The systems were then compared to each other in order to recommend the one(s) best suited for use in the USAPHC ZDR. The first stage of the comparison focused on each system's ability to meet the specific goals and objectives of the ZDR, whereas the second stage applied capture-recapture methodology to data system queries in order to evaluate each system's data quality (completeness). A pilot study was conducted using Lyme borreliosis to investigate the utility of military pet dogs as sentinel surveillance for zoonotic disease in military populations. Canine data came from 3996 surveys collected from 15 military veterinary facilities from 1 November 2012 through 31 October 2013. Surveys simultaneously collected Borrelia burgdorferi (Bb) seroprevalence and canine risk factor data for each participating pet dog. Human data were obtained by querying the Defense Medical Surveillance System for the same 15 military locations and the same time period. The correlation of military pet dog Bb seroprevalence and military human Lyme disease (borreliosis) data was estimated using the Spearman Rank Correlation. The difference between military pet dog data and civilian pet dog data was examined through the use of the chi-squared test for proportions. Multivariable logistic regression was then used to investigate the potential for identified risk factors to impact the observed association. Results: The comparison of human military medical data systems found the Military Health System Management Analysis and Reporting Tool (M2) data system most completely met the specific goals and objects of the ZDR. In addition, completeness calculation showed the M2 data source to be the most complete source of human data; 55% of total captured cases coming from the M2 system alone. The pilot study found a strong positive correlation between military human borreliosis data and military pet dog Bb seroprevalence data by location (rs = 0.821). The study showed reassuring similarities in pet dog seroprevalence by location for the majority of sites, but also showed meaningful differences between two locations, potentially indicating military pet dogs as more appropriate indicators of Lyme disease risk for military populations than civilian pet dog data. Unfortunately, whether canine Bb seroprevalence is influenced by the distribution of identified risk factors could not be determined due to limited study power. Conclusions: Based on this study M2 was recommended as the primary source of military human medical data for use in the Public Health Command Zoonotic Disease Report. In addition, it was recommended that Service member pet dog data be incorporated as a sensitive and convenient measure of zoonotic disease risk in human military populations. The validity of the data, however, should be evaluated further with either larger sample sizes and/or a zoonotic disease with higher prevalence

Studies in Molecular Recognition: Non-proteogenic Amino Acids for Antibiotic Studies and Chemosensors for Recognition and Reporting of Metal-ions

The field of molecular recognition focuses on the selective and reversible binding of small guest molecules to larger host molecules. This dissertation describes synthesis of small molecules as binding guests for enzymatic substrates as well as molecules as host chemosensors to detect and identify metal ions. Two approaches to new antibiotic drugs have been explored, and an array of sensors for the quantitation of aqueous metals is being commercialized. As strains of deadly bacteria emerge with evolved resistance to known antibiotics, new drugs are needed with novel mechanisms of action. Natural product antibiotics containing enduracididine, a non-canonical amino acid derived from arginine, have been found effective against resistant organisms. Recently, the biosynthesis of enduracididine has been elucidated by the Silvaggi group. Various derivatives of arginine are of interest as guest molecules for the Mpp family of proteins. We have developed a particularly succinct route to γ-hydroxy-arginine, which has also been used as a precursor to other oxidized arginine derivatives. Our route provides quantities of arginine derivatives which have been synthesized via a four step route utilizing an isoxazoline intermediate. The synthetic methods for formation and subsequent reduction of the isoxazoline have been studied extensively; and this succinct and versatile synthesis yields either γ-hydroxy-arginine or the keto acid derived from it by changing the conditions of the reduction. iii In another approach to developing new antibiotic treatment, we have pursued the inhibition of the β-barrel assembly machine (BAM), through a small molecule scaffold that binds β-sheets. BAMa is the only known β-barrel protein that spontaneously folds, while all others require the help of BAMa. The β-barrel membrane proteins include efflux pumps, proteins for active transport that allow bacterial survival by ejection of antibiotic drugs. Inhibition of BAMa may itself prove bactericidal, or used in combination therapy increase efficacy of drugs rendered previously ineffective due to acquired resistance. We have also developed metal ion chemosensors for simulataneous identification and quantitation of multiple metals. These are useful for monitoring metal ion concentrations in industrial wastewater. Current limitations in measuring metal concentration in wastewater can lead to increased costs and excess solid waste in order to meet compliance standards. Our goal is a simple system to allow continuous, real-time measurement of multiple metals on site to decrease over-treatment and detect spikes in pollutant metals. Utilizing UV/VIS absorption an array of semi-selective sensors each with its own spectral response to metal ions allows identification and concentration of pollutants to be determined. Toward this end, we have prepared chemosensors, demonstrated their sensing ability, and covalently attached them to transparent polymers and transparent supports in several ways that allow repeated use for metal-ion measurement. These dyes have been studied in solution and when covalently bound to polymers. Dyes with complementary metal-selectivity allow for high information from a few sensors; a model using three sensors has been demonstrated to simultaneously measure the concentration of seven metals in solution

Resiliency Mechanisms for In-Memory Column Stores

The key objective of database systems is to reliably manage data, while high query throughput and low query latency are core requirements. To date, database research activities mostly concentrated on the second part. However, due to the constant shrinking of transistor feature sizes, integrated circuits become more and more unreliable and transient hardware errors in the form of multi-bit flips become more and more prominent. In a more recent study (2013), in a large high-performance cluster with around 8500 nodes, a failure rate of 40 FIT per DRAM device was measured. For their system, this means that every 10 hours there occurs a single- or multi-bit flip, which is unacceptably high for enterprise and HPC scenarios. Causes can be cosmic rays, heat, or electrical crosstalk, with the latter being exploited actively through the RowHammer attack. It was shown that memory cells are more prone to bit flips than logic gates and several surveys found multi-bit flip events in main memory modules of today's data centers. Due to the shift towards in-memory data management systems, where all business related data and query intermediate results are kept solely in fast main memory, such systems are in great danger to deliver corrupt results to their users. Hardware techniques can not be scaled to compensate the exponentially increasing error rates. In other domains, there is an increasing interest in software-based solutions to this problem, but these proposed methods come along with huge runtime and/or storage overheads. These are unacceptable for in-memory data management systems. In this thesis, we investigate how to integrate bit flip detection mechanisms into in-memory data management systems. To achieve this goal, we first build an understanding of bit flip detection techniques and select two error codes, AN codes and XOR checksums, suitable to the requirements of in-memory data management systems. The most important requirement is effectiveness of the codes to detect bit flips. We meet this goal through AN codes, which exhibit better and adaptable error detection capabilities than those found in today's hardware. The second most important goal is efficiency in terms of coding latency. We meet this by introducing a fundamental performance improvements to AN codes, and by vectorizing both chosen codes' operations. We integrate bit flip detection mechanisms into the lowest storage layer and the query processing layer in such a way that the remaining data management system and the user can stay oblivious of any error detection. This includes both base columns and pointer-heavy index structures such as the ubiquitous B-Tree. Additionally, our approach allows adaptable, on-the-fly bit flip detection during query processing, with only very little impact on query latency. AN coding allows to recode intermediate results with virtually no performance penalty. We support our claims by providing exhaustive runtime and throughput measurements throughout the whole thesis and with an end-to-end evaluation using the Star Schema Benchmark. To the best of our knowledge, we are the first to present such holistic and fast bit flip detection in a large software infrastructure such as in-memory data management systems. Finally, most of the source code fragments used to obtain the results in this thesis are open source and freely available.:1 INTRODUCTION 1.1 Contributions of this Thesis 1.2 Outline 2 PROBLEM DESCRIPTION AND RELATED WORK 2.1 Reliable Data Management on Reliable Hardware 2.2 The Shift Towards Unreliable Hardware 2.3 Hardware-Based Mitigation of Bit Flips 2.4 Data Management System Requirements 2.5 Software-Based Techniques For Handling Bit Flips 2.5.1 Operating System-Level Techniques 2.5.2 Compiler-Level Techniques 2.5.3 Application-Level Techniques 2.6 Summary and Conclusions 3 ANALYSIS OF CODING TECHNIQUES 3.1 Selection of Error Codes 3.1.1 Hamming Coding 3.1.2 XOR Checksums 3.1.3 AN Coding 3.1.4 Summary and Conclusions 3.2 Probabilities of Silent Data Corruption 3.2.1 Probabilities of Hamming Codes 3.2.2 Probabilities of XOR Checksums 3.2.3 Probabilities of AN Codes 3.2.4 Concrete Error Models 3.2.5 Summary and Conclusions 3.3 Throughput Considerations 3.3.1 Test Systems Descriptions 3.3.2 Vectorizing Hamming Coding 3.3.3 Vectorizing XOR Checksums 3.3.4 Vectorizing AN Coding 3.3.5 Summary and Conclusions 3.4 Comparison of Error Codes 3.4.1 Effectiveness 3.4.2 Efficiency 3.4.3 Runtime Adaptability 3.5 Performance Optimizations for AN Coding 3.5.1 The Modular Multiplicative Inverse 3.5.2 Faster Softening 3.5.3 Faster Error Detection 3.5.4 Comparison to Original AN Coding 3.5.5 The Multiplicative Inverse Anomaly 3.6 Summary 4 BIT FLIP DETECTING STORAGE 4.1 Column Store Architecture 4.1.1 Logical Data Types 4.1.2 Storage Model 4.1.3 Data Representation 4.1.4 Data Layout 4.1.5 Tree Index Structures 4.1.6 Summary 4.2 Hardened Data Storage 4.2.1 Hardened Physical Data Types 4.2.2 Hardened Lightweight Compression 4.2.3 Hardened Data Layout 4.2.4 UDI Operations 4.2.5 Summary and Conclusions 4.3 Hardened Tree Index Structures 4.3.1 B-Tree Verification Techniques 4.3.2 Justification For Further Techniques 4.3.3 The Error Detecting B-Tree 4.4 Summary 5 BIT FLIP DETECTING QUERY PROCESSING 5.1 Column Store Query Processing 5.2 Bit Flip Detection Opportunities 5.2.1 Early Onetime Detection 5.2.2 Late Onetime Detection 5.2.3 Continuous Detection 5.2.4 Miscellaneous Processing Aspects 5.2.5 Summary and Conclusions 5.3 Hardened Intermediate Results 5.3.1 Materialization of Hardened Intermediates 5.3.2 Hardened Bitmaps 5.4 Summary 6 END-TO-END EVALUATION 6.1 Prototype Implementation 6.1.1 AHEAD Architecture 6.1.2 Diversity of Physical Operators 6.1.3 One Concrete Operator Realization 6.1.4 Summary and Conclusions 6.2 Performance of Individual Operators 6.2.1 Selection on One Predicate 6.2.2 Selection on Two Predicates 6.2.3 Join Operators 6.2.4 Grouping and Aggregation 6.2.5 Delta Operator 6.2.6 Summary and Conclusions 6.3 Star Schema Benchmark Queries 6.3.1 Query Runtimes 6.3.2 Improvements Through Vectorization 6.3.3 Storage Overhead 6.3.4 Summary and Conclusions 6.4 Error Detecting B-Tree 6.4.1 Single Key Lookup 6.4.2 Key Value-Pair Insertion 6.5 Summary 7 SUMMARY AND CONCLUSIONS 7.1 Future Work A APPENDIX A.1 List of Golden As A.2 More on Hamming Coding A.2.1 Code examples A.2.2 Vectorization BIBLIOGRAPHY LIST OF FIGURES LIST OF TABLES LIST OF LISTINGS LIST OF ACRONYMS LIST OF SYMBOLS LIST OF DEFINITION

An MADM risk-based evaluation-selection model of free-libre open source software tools

Free-Libre Open Source Software (FLOSS) tools are free-cost license highly attractive to be implemented by organizations. However, not of all the FLOSS tools are mature, and failed implementations can occur. Thus, FLOSS evaluation-selection frameworks and FLOSS success-failure implementation factors studies have been conducted. In this research, we advance on such studies through an integrated FLOSS evaluation-selection model with a risk-based decision making approach. Our model was built upon the other two literatures, and it was structured as a Multi-Attribute Decision Making (MADM) model which contains 12 variables grouped in four risk categories: financial, organizational, end-user and technical ones. We illustrated its utilization in the domain of Information Technology Service Management (ITSM) FLOSS tools. Hence, our model contributes to the FLOSS literature with the inclusion of the risk management approach and to the FLOSS evaluation-selection praxis with the provision of an innovative and essential risk-based model

Information Systems and strategic decisions: A literature Review

This paper looks at information systems and the information they provide specifically for strategic decision-making. The study employs a brief review of the recent research on information systems for strategic decision making and presents a framework for better understanding of such systems Future research plans are also given

Optimizing T Cell Manufacturing and Quality Using Functionalized Degradable Microscaffolds

Adoptive cell therapy using chimeric antigen receptor (CAR) T cells have shown promise in treating cancer, but manufacturing large numbers of high quality cells remains challenging. Currently approved T cell expansion technologies involve anti-CD3 and anti-CD28 antibodies, usually mounted on magnetic beads. This method fails to recapitulate many key signals found in vivo and is also heavily licensed by a few companies, limiting its long-term usefulness to manufactures and clinicians. Furthermore, highly potent, anti-tumor T cells are generally less-differentiated subtypes such as central memory and stem memory T cells. Despite this understanding, little has been done to optimize T cell expansion for generating these subtypes, including measurement and feedback control strategies that are necessary for any modern manufacturing process. The goal of this dissertation was to develop a microcarrier-based degradable microscaffold (DMS) T cell expansion system and determine biologically-meaningful critical quality attitudes and critical process parameters that could be used to optimize for highly-potent T cells. We developed and characterized the DMS system, including quality control steps. We also demonstrated the feasibility of expanding high-quality T cells. We used Design of Experiments methodology to optimize the DMS platform, and we developed a computational pipeline to identify and model the effects of measurable critical quality attributes and critical process parameters on the final product. Finally, we demonstrated the effectiveness of the DMS platform in vivo. This thesis lays the groundwork for a novel T cell expansion method which can be utilized at scale for clinical trials and beyond.Ph.D