Enhanced zinc oxide and graphene nanostructures for electronics and sensing applications

Zinc oxide and graphene nanostructures are important technological materials because of their unique properties and potential applications in future generation of electronic and sensing devices. This dissertation investigates a brief account of the strategies to grow zinc oxide nanostructures (thin film and nanowire) and graphene, and their applications as enhanced field effect transistors, chemical sensors and transparent flexible electrodes. Nanostructured zinc oxide (ZnO) and low-gallium doped zinc oxide (GZO) thin films were synthesized by a magnetron sputtering process. Zinc oxide nanowires (ZNWs) were grown by a chemical vapor deposition method. Field effect transistors (FETs) of ZnO and GZO thin films and ZNWs were fabricated by standard photo and electron beam lithography processes. Electrical characteristics of these devices were investigated by nondestructive surface cleaning, ultraviolet irradiation treatment at high temperature and under vacuum. GZO thin film transistors showed a mobility of ∼5.7 cm2/V·s at low operation voltage of <5 V and a low turn-on voltage of ∼0.5 V with a sub threshold swing of ∼85 mV/decade. Bottom gated FET fabricated from ZNWs exhibit a very high on-to-off ratio (∼106) and mobility (∼28 cm2/V·s). A bottom gated FET showed large hysteresis of ∼5.0 to 8.0 V which was significantly reduced to ∼1.0 V by the surface treatment process. The results demonstrate charge transport in ZnO nanostructures strongly depends on its surface environmental conditions and can be explained by formation of depletion layer at the surface by various surface states. A nitric oxide (NO) gas sensor using single ZNW, functionalized with Cr nanoparticles was developed. The sensor exhibited average sensitivity of ∼46% and a minimum detection limit of ∼1.5 ppm for NO gas. The sensor also is selective towards NO gas as demonstrated by a cross sensitivity test with N2, CO and CO2 gases. Graphene film on copper foil was synthesized by chemical vapor deposition method. A hot press lamination process was developed for transferring graphene film to flexible polymer substrate. The graphene/polymer film exhibited a high quality, flexible transparent conductive structure with unique electrical-mechanical properties; ∼88.80% light transmittance and ∼1.1742Ω/sq k sheet resistance. The application of a graphene/polymer film as a flexible and transparent electrode for field emission displays was demonstrated.

Mining in Peru: Indigenous and Peasant Communities vs. The State and Mining Capital

The Peruvian economy depends for its growth on the export of natural resources and investment in the mining and hydrocarbon sectors. Peruvian governments and mining corporations have confronted anti-mining protests in different ways. While the current government has introduced policies of social inclusion to soften the negative effects of the operations of mining capital and policies of dialogue to engage social actors with the essence of governmental policies, mining companies use corporate social responsibility programs as a cover for the devastating effects of their operations on the environment and the livelihoods and habitats of the indigenous and peasant communities. Curiously, in the current context of the declining commodity prices and export volumes the Peruvian government strengthens its extractivist model of development. This article argues that whatever government that follows the rules of capital cannot but favor the corporations. It points out the main adversaries of the indigenous and peasant communities and the problems to transform the locally and/or regionally struggle into a nationwide battle for another development model.

The relationship of thymulin activity, immune parameters of HIV disease progression and substance use in a cohort of HIV seropositive alcohol and drug users

Zinc is essential for the activity of thymulin, a thymic hormone involved in T-lymphocyte differentiation and activation. Zinc deficiency is widespread in populations with HIV infection, and HIV+ drug users are particularly susceptible to zinc deficiency and immune suppression. This dissertation explored the relationship of zinc-bound active thymulin to plasma zinc, CD4+ and CD8+ cell count, the CD4+/CD8+ ratio, and drug use in HIV-infected drug users. Zinc-bound active thymulin was assessed in plasma of HIV+ drug users who were participating in a 30 month zinc supplementation trial. Plasma from 80 participants at the 12 month visit, and 40 of these same participants, randomly selected, at the baseline visit were assessed for zinc-bound active thymulin levels using a modification of the rosette inhibition assay. Thymulin activity was directly associated with CD4+ cell count (β = 0.127, p = 0.002) and inversely associated with cocaine use (β = −0.908, p = 0.026; R2 = 0.188, p = 0.019) independent of HIV viral load, age, gender and antiretroviral use. An increase in thymulin activity was 1.4 times more likely when CD4+ cell count increased (OR = 1.402, 95%CI: 1.006–1.956), independent of change in viral load, antiretroviral use, and age. Participants who used cocaine consistently, were 7.6 times less likely to have an increase in thymulin activity (OR = 0.133, 95%CI: 0.017–1.061). There was a direct correlation between change in plasma zinc and change in zinc-bound active thymulin (r = 0.243, p = 0.13). Analysis of CD4+ cell count decline in 222 participants in the zinc supplementation trial across the 30 months showed that both crack cocaine use and heavy alcohol use accelerated CD4+ cell count decline. Thymulin activity is directly associated with HIV disease progression, measured by CD4+ cell count, and is depressed with cocaine use independent of antiretroviral use and HIV viral load. Cocaine and heavy alcohol accelerate CD4+ cell count decline. The effect of cocaine on thymic output requires further evaluation as a mechanism for the association of cocaine use with faster HIV disease progression.

Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.