Novel Thermoplastic Elastomers based on Benzofulvene: Synthesis and Mechanical Properties

Thermoplastic elastomers (TPEs) are of great importance both academically and technologically. Currently TPEs are the predominated form of styrene-diene copolymers. However, these styrenic TPEs have serious limitations in applications, especially at higher temperature, because of their low upper service temperature (UST). The work described in this dissertation aimed to developing thermoplastic elastomers with a higher UST and lower cost. In order to develop TPEs with a higher UST, we employed benzofulvene, an anionically polymerizable monomer in hydrocarbon solvent at room temperature, as the glassy block and copolymerized it with isoprene to prepare polybenzofulvene-polyisoprene-polybenzofulvene (FIF) triblock copolymers. Among all triblock copolymers studied, FIF with 14 vol% [volume percentage] of PBF [polybenzofulvene] exhibited a maximum stress of 14.3 MPa [megapascal] and strain at break of 1394 % from tensile tests. Dynamic mechanical analysis showed that the upper service temperature of FIF is 145°C. Microphase separation of FIF triblock copolymers was observed by small angle X-ray scattering, however, without long range order. Additionally, we report the effects of partial and complete hydrogenation on the thermal stability, mechanical and morphological properties of high temperature thermoplastic elastomers comprised of polybenzofulvene-polyisoprene-polybenzofulvene (FIF) triblock copolymers. After hydrogenation of polyisoprene and unsaturated carbon bonds in the five member ring of PBF, ultimate tensile stress was reduced to 11.2 MPa with strain at break of 750%. The upper service temperature also decreased to 125 °C. The fully hydrogenated triblock copolymer demonstrated an ultimate stress of 17. 4 MPa at 744 % strain. The glass transition temperature (Tg) of fully hydrogenated PBF was 130 °C. Thermal stability was greatly improved by both partial and complete hydrogenation. Lastly, we developed a cost efficient method to prepare high molecular weight “comb-shaped” graft copolymers, poly(isoprene-g-styrene), with polyisoprene as the backbone and polystyrene as side chains. The grafted polymers were synthesized via free radical emulsion polymerization by copolymerization of isoprene with a polystyrene macromonomer synthesized using anionic polymerization. A material incorporating 29 wt% [weigh percentage] polystyrene exhibits a disordered microphase separated morphology and elastomeric properties. These materials show promise as new, highly tunable, and potentially low cost thermoplastic elastomers

A Unique "Nonnegative" Solution to an Underdetermined System: from Vectors to Matrices

This paper investigates the uniqueness of a nonnegative vector solution and the uniqueness of a positive semidefinite matrix solution to underdetermined linear systems. A vector solution is the unique solution to an underdetermined linear system only if the measurement matrix has a row-span intersecting the positive orthant. Focusing on two types of binary measurement matrices, Bernoulli 0-1 matrices and adjacency matrices of general expander graphs, we show that, in both cases, the support size of a unique nonnegative solution can grow linearly, namely O(n), with the problem dimension n. We also provide closed-form characterizations of the ratio of this support size to the signal dimension. For the matrix case, we show that under a necessary and sufficient condition for the linear compressed observations operator, there will be a unique positive semidefinite matrix solution to the compressed linear observations. We further show that a randomly generated Gaussian linear compressed observations operator will satisfy this condition with overwhelmingly high probability

Artificial Intelligence (AI) Ethics: Ethics of AI and Ethical AI

Artificial intelligence (AI)-based technology has achieved many great things, such as facial recognition, medical diagnosis, and self-driving cars. AI promises enormous benefits for economic growth, social development, as well as human well-being and safety improvement. However, the low-level of explainability, data biases, data security, data privacy, and ethical problems of AI-based technology pose significant risks for users, developers, humanity, and societies. As AI advances, one critical issue is how to address the ethical and moral challenges associated with AI. Even though the concept of “machine ethics” was proposed around 2006, AI ethics is still in the infancy stage. AI ethics is the field related to the study of ethical issues in AI. To address AI ethics, one needs to consider the ethics of AI and how to build ethical AI. Ethics of AI studies the ethical principles, rules, guidelines, policies, and regulations that are related to AI. Ethical AI is an AI that performs and behaves ethically. One must recognize and understand the potential ethical and moral issues that may be caused by AI to formulate the necessary ethical principles, rules, guidelines, policies, and regulations for AI (i.e., Ethics of AI). With the appropriate ethics of AI, one can then build AI that exhibits ethical behavior (i.e., Ethical AI). This paper will discuss AI ethics by looking at the ethics of AI and ethical AI. What are the perceived ethical and moral issues with AI? What are the general and common ethical principles, rules, guidelines, policies, and regulations that can resolve or at least attenuate these ethical and moral issues with AI? What are some of the necessary features and characteristics of an ethical AI? How to adhere to the ethics of AI to build ethical AI

COVID-19 Pandemic: Balancing Privacy and Saving Lives in Technology Usage

COVID-19 is sweeping across the globe. Some countries are collecting anonymized data to study the movement of people and others are providing more detailed information about individuals in addition to the movement data. Surveillance tools are widely used to stem the spread of the COVID-19. South Korea uses smartphone location data, surveillance camera footage, and credit card data to create a publicly available map that tracks the paths of COVID-19 patients. Austria’s network operators share anonymized location data with the government, but the data may remain at risk from re-identification in the future. The Polish government releases an app for people in quarantine, requiring them to upload geo-located selfies periodically. In some countries, police and military personnel are also involved in enforcing quarantines, curfews, and social distancing, which may encroach on personal freedom and privacy. There is no doubt that the use of technologies, such as geolocation and facial recognition, can help to slow and manage the spread of COVID-19 and enforce social distancing, but people are concerned about the expanded and potentially questionable uses of technologies that may result in privacy issues (Siau & Wang, 2020). Many questions remain to be answered. How the data is being shared? How to deal with the data and the surveillance capabilities once the pandemic subsides? How to prevent unauthorized individuals or institutions from gaining access to the data? Privacy is recognized as a fundamental human right, essential for freedom, democracy, and psychological well-being. As technology developed, especially the progress of mobile devices (Siau & Shen, 2002, 2006), concerns about privacy (location data in particular) increase (Shokri et al. 2011). Some organizations are dedicated to protecting individual privacy while sharing information, and encrypting the data collected to prevent a hacker from accessing identifiable information. However, as evidenced by data breaches, information is increasingly exposed to hacking, which results in information security and privacy issues (Siau & Wang, 2018; Wang & Siau, 2019). This qualitative study will examine how organizations and authorities are dealing with the tradeoff between protecting individual privacy and saving lives in the pandemic. In the first phase of the study, data security and privacy officers in various government and healthcare organizations will be interviewed. In the second phase, the findings from the first phase will be used to design questionnaires, which will be administered in government organizations. This will be a multi-country and multi-culture research