Exploring Blockchain Adoption Supply Chains: Opportunities and Challenges

Excerpt from the Proceedings of the Nineteenth Annual Acquisition Research SymposiumThrough cyber-enabled industrial espionage, China has appropriated what Keith Alexander, the former Director of the National Security Agency, dubbed “the largest transfer of wealth in history.” Although China disavows intellectual property (IP) theft by its citizens and has set self-sustained research and development as an important goal, it is unrealistic to believe IP theft will slow down meaningfully without changing China’s decision calculus. China and the United States have twice agreed, in principle, to respect one another’s IP rights. However, these agreements have lacked any real enforcement mechanism, so the United States must do more to ensure its IP is better protected from China’s sophisticated hackers. We call for selective interventions in nascent industries—especially those with important implications for national defense. U.S. policymakers must consider both the supply and demand aspects of the “market” for intellectual property theft to make informed decisions as to how to steer resources. This paper offers insight that the supply side of the equation has been given relatively short shrift. We offer a spectrum of potential interventions to address underinvestment in cybersecurity leading to IP theft and discuss where to go from here.Approved for public release; distribution is unlimited

Exploring Blockchain Adoption Supply Chains: Opportunities and Challenges

Excerpt from the Proceedings of the Nineteenth Annual Acquisition Research SymposiumThrough cyber-enabled industrial espionage, China has appropriated what Keith Alexander, the former Director of the National Security Agency, dubbed “the largest transfer of wealth in history.” Although China disavows intellectual property (IP) theft by its citizens and has set self-sustained research and development as an important goal, it is unrealistic to believe IP theft will slow down meaningfully without changing China’s decision calculus. China and the United States have twice agreed, in principle, to respect one another’s IP rights. However, these agreements have lacked any real enforcement mechanism, so the United States must do more to ensure its IP is better protected from China’s sophisticated hackers. We call for selective interventions in nascent industries—especially those with important implications for national defense. U.S. policymakers must consider both the supply and demand aspects of the “market” for intellectual property theft to make informed decisions as to how to steer resources. This paper offers insight that the supply side of the equation has been given relatively short shrift. We offer a spectrum of potential interventions to address underinvestment in cybersecurity leading to IP theft and discuss where to go from here.Approved for public release; distribution is unlimited

Defensive Industrial Policy: Cybersecurity Interventions to Reduce Intellectual Property Theft

Symposium PresentationApproved for public release; distribution is unlimited

Identifying drivers of spatio-temporal dynamics in Barley Yellow Dwarf Virus epidemiology as a critical factor in disease control

Barley yellow dwarf virus (BYDV) is one of the most important viral diseases of small grains worldwide. An understanding of its epidemiology is crucial to control this disease in a sustainable way. The virus moves through the agricultural landscape via cereal aphids as vectors. Understanding movement of these aphids in space and time is of key importance and in doing so, the spatial and temporal variables that influence BYDV epidemiology can be identified. The presence of summer hosts, crop rotation, crop diversity, agricultural practices and climate variables are crucial. Through digitalization, spatial (e.g. land-use) and temporal (e.g. weather) information is becoming more readily available. Including this information into a prediction model could improve decision support systems that will rationalize the decision-making process towards a more integrated control of the disease

MUC1 immunotherapy against a metastatic mammary adenocarcinoma model: Importance of IFN-gamma

Abstract Immunotherapy using mucin 1 (MUC1) linked to oxidised mannan (MFP) was investigated in an aggressive MUC1+ metastatic tumour, DA3-MUC1 because, unlike many MUC1+ tumour models, DA3-MUC1 is not spontaneously rejected in mice making it an alternative model for immunotherapy studies. Further, DA3-MUC1 cells are resistant to lysis by anti-MUC1 cytotoxic T cells (CTLs). The inability of DA3-MUC1 tumours to be rejected in naïve mice as well as vaccination to MUC1 was attributed to a deficiency of expression of MHC class I molecules on the tumour cell surface. In vitro and in vivo analysis of subcutaneous tumours and lung metastases demonstrated that DA3-MUC1 tumour cells have a low expression (&lt; 6%) of MHC class I which can be upregulated (&gt; 90%) following culturing with IFN-γ. Results from flow cytometry analysis and immunoperoxidase staining indicated that the in vitro up-regulation of MHC class I could be maintained for up to seven days in vivo, without affecting the expression levels of MUC1 antigen. Interestingly, MUC1-specific CTL that lyse DA3-MUC1 targets in vitro were induced in MFP immunised mice but failed to protect mice from a DA3-MUC1 tumour challenge. These results highlight the importance of MHC class I molecules in the induction of anti-tumour immunity and the MFP immune response.</jats:p

Supersymmetric Vacua in Random Supergravity

We determine the spectrum of scalar masses in a supersymmetric vacuum of a general N=1 supergravity theory, with the Kahler potential and superpotential taken to be random functions of N complex scalar fields. We derive a random matrix model for the Hessian matrix and compute the eigenvalue spectrum. Tachyons consistent with the Breitenlohner-Freedman bound are generically present, and although these tachyons cannot destabilize the supersymmetric vacuum, they do influence the likelihood of the existence of an `uplift' to a metastable vacuum with positive cosmological constant. We show that the probability that a supersymmetric AdS vacuum has no tachyons is formally equivalent to the probability of a large fluctuation of the smallest eigenvalue of a certain real Wishart matrix. For normally-distributed matrix entries and any N, this probability is given exactly by P = exp(-2N^2|W|^2/m_{susy}^2), with W denoting the superpotential and m_{susy} the supersymmetric mass scale; for more general distributions of the entries, our result is accurate when N >> 1. We conclude that for |W| \gtrsim m_{susy}/N, tachyonic instabilities are ubiquitous in configurations obtained by uplifting supersymmetric vacua.Comment: 26 pages, 6 figure

Anti-nausea effects and pharmacokinetics of ondansetron, maropitant and metoclopramide in a low-dose cisplatin model of nausea and vomiting in the dog: a blinded crossover study

Nausea is a subjective sensation which is difficult to measure in non-verbal species. The aims of this study were to determine the efficacy of three classes of antiemetic drugs in a novel low dose cisplatin model of nausea and vomiting and measure change in potential nausea biomarkers arginine vasopressin (AVP) and cortisol. A four period cross-over blinded study was conducted in eight healthy beagle dogs of both genders. Dogs were administered 18 mg/m2 cisplatin intravenously, followed 45 min later by a 15 min infusion of either placebo (saline) or antiemetic treatment with ondansetron (0.5 mg/kg; 5-HT3 antagonist), maropitant (1 mg/kg; NK1 antagonist) or metoclopramide (0.5 mg/kg; D2 antagonist). The number of vomits and nausea associated behaviours, scored on a visual analogue scale, were recorded every 15 min for 8 h following cisplatin administration. Plasma samples were collected to measure AVP, cortisol and antiemetic drug concentrations

Exploring the measurement of markedness and its relationship with other linguistic variables

Antonym pair members can be differentiated by each word's markedness-that distinction attributable to the presence or absence of features at morphological or semantic levels. Morphologically marked words incorporate their unmarked counterpart with additional morphs (e.g., "unlucky" vs. "lucky"); properties used to determine semantically marked words (e.g., "short" vs. "long") are less clearly defined. Despite extensive theoretical scrutiny, the lexical properties of markedness have received scant empirical study. The current paper employs an antonym sequencing approach to measure markedness: establishing markedness probabilities for individual words and evaluating their relationship with other lexical properties (e.g., length, frequency, valence). Regression analyses reveal that markedness probability is, as predicted, related to affixation and also strongly related to valence. Our results support the suggestion that antonym sequence is reflected in discourse, and further analysis demonstrates that markedness probabilities, derived from the antonym sequencing task, reflect the ordering of antonyms within natural language. In line with the Pollyanna Hypothesis, we argue that markedness is closely related to valence; language users demonstrate a tendency to present words evaluated positively ahead of those evaluated negatively if given the choice. Future research should consider the relationship of markedness and valence, and the influence of contextual information in determining which member of an antonym pair is marked or unmarked within discourse

Beyond element-wise interactions: identifying complex interactions in biological processes

Background: Biological processes typically involve the interactions of a number of elements (genes, cells) acting on each others. Such processes are often modelled as networks whose nodes are the elements in question and edges pairwise relations between them (transcription, inhibition). But more often than not, elements actually work cooperatively or competitively to achieve a task. Or an element can act on the interaction between two others, as in the case of an enzyme controlling a reaction rate. We call “complex” these types of interaction and propose ways to identify them from time-series observations. Methodology: We use Granger Causality, a measure of the interaction between two signals, to characterize the influence of an enzyme on a reaction rate. We extend its traditional formulation to the case of multi-dimensional signals in order to capture group interactions, and not only element interactions. Our method is extensively tested on simulated data and applied to three biological datasets: microarray data of the Saccharomyces cerevisiae yeast, local field potential recordings of two brain areas and a metabolic reaction. Conclusions: Our results demonstrate that complex Granger causality can reveal new types of relation between signals and is particularly suited to biological data. Our approach raises some fundamental issues of the systems biology approach since finding all complex causalities (interactions) is an NP hard problem