Synthesis Of Al2o3 Thin Film As Thermal Interface Materials (Tims) Using Chemical Vapor Deposition (Cvd) Method For Solid State Lighting Applications

Continuous efforts by researchers have improved the design and overall light output of the SSL devices yet there are concerns still remain regarding the reliability of devices under certain circumstances. The rise in driving current would lead to an increase in light output and junction temperature within the devices simultaneously. An excessive rise in junction temperature can cause thermal runaway and affect devices lifetime, ultimately leading to devices failure. Thus, a highly sophisticated thermal management system is needed to compensate with the high performance of SSL devices. In this project, thin film coating technique has been suggested as one of the effective approaches in improving the thermal dissipation system at system level

Characteristics of the global copper raw materials and scrap trade systems and the policy impacts of China's import ban

Copper raw materials (CRM) and copper waste and scrap (CWS) are the two main sources of copper manufactured products. Due to the uneven geographical distribution of copper production and consumption, international CRM and CWS trade developed. However, no study has explored the complicated interdependencies between CRM trade and CWS trade or investigated the characteristics of this multiplex trade system. This study uses trade records from 1988 to 2017 to construct multiplex trade networks: a global CRM trade network and a global CWS trade network. The evolution of copper trade from 1988 to 2017 is reviewed, and the intricate relationships in the multiplex trade network are identified. It is found that CWS trade has a highly positive correlation with CRM trade, but there are obvious differences between CWS trade and CRM trade in the multilateral trade structure. Multilateral trade structures driven by core exporting countries and core importing countries are prominent in CRM trade and CWS trade, respectively. In addition, the impacts of China's restrictive policies on the multiplex trade system are analyzed. The results provide policy implications for countries regarding copper resource security strategies and safeguarding the multiplex trading system.</p

Structure of the Global Plastic Waste Trade Network and the Impact of China's Import Ban

Millions of tonnes (teragrams) of plastic waste are traded around the world every year, which plays an important role in partially substituting virgin plastics as a source of raw materials in plastic product manufacturing. In this paper, global plastic waste trade networks (GPWTNs) from 1988 to 2017 are established using the UN-Comtrade database. The spatiotemporal evolution of the GPWTNs is analyzed. Attention is given to the country ranks, inter- and intra-continental trade flows, and geo-visual communities in the GPWTNs. We also evaluate the direct and indirect impacts of China’s plastic waste import ban on the GPWTNs. The results show that the GPWTNs have small-world and scale-free properties and a core-periphery structure. The geography of the plastic waste trade is structured by Asia as the dominant importer and North America and Europe as the largest sources of plastic waste. China is the unrivaled colossus in the global plastic waste trade. After China’s import ban, the plastic waste trade flows have been largely redirected to Southeast Asian countries. Compared with import countries, export countries are more important for the robustness of GPWTNs. Clearly, developed countries will not announce bans on plastic waste exports; these countries have strong motivation to continue to shift plastic waste to poorer countries. However, the import bans from developing countries will compel developed countries to build new disposal facilities and deal with their plastic waste domestically

Distributed Searchable Symmetric Encryption

Searchable Symmetric Encryption (SSE) allows a client to store encrypted data on a storage provider in such a way, that the client is able to search and retrieve the data selectively without the storage provider learning the contents of the data or the words being searched for. Practical SSE schemes usually leak (sensitive) information during or after a query (e.g., the search pattern). Secure schemes on the other hand are not practical, namely they are neither efficient in the computational search complexity, nor scalable with large data sets. To achieve efficiency and security at the same time, we introduce the concept of distributed SSE (DSSE), which uses a query proxy in addition to the storage provider.\ud We give a construction that combines an inverted index approach (for efficiency) with scrambling functions used in private information retrieval (PIR) (for security). The proposed scheme, which is entirely based on XOR operations and pseudo-random functions, is efficient and does not leak the search pattern. For instance, a secure search in an index over one million documents and 500 keywords is executed in less than 1 second

Federated Learning in Mobile Edge Networks: A Comprehensive Survey

In recent years, mobile devices are equipped with increasingly advanced sensing and computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up countless possibilities for meaningful applications. Traditional cloudbased Machine Learning (ML) approaches require the data to be centralized in a cloud server or data center. However, this results in critical issues related to unacceptable latency and communication inefficiency. To this end, Mobile Edge Computing (MEC) has been proposed to bring intelligence closer to the edge, where data is produced. However, conventional enabling technologies for ML at mobile edge networks still require personal data to be shared with external parties, e.g., edge servers. Recently, in light of increasingly stringent data privacy legislations and growing privacy concerns, the concept of Federated Learning (FL) has been introduced. In FL, end devices use their local data to train an ML model required by the server. The end devices then send the model updates rather than raw data to the server for aggregation. FL can serve as an enabling technology in mobile edge networks since it enables the collaborative training of an ML model and also enables DL for mobile edge network optimization. However, in a large-scale and complex mobile edge network, heterogeneous devices with varying constraints are involved. This raises challenges of communication costs, resource allocation, and privacy and security in the implementation of FL at scale. In this survey, we begin with an introduction to the background and fundamentals of FL. Then, we highlight the aforementioned challenges of FL implementation and review existing solutions. Furthermore, we present the applications of FL for mobile edge network optimization. Finally, we discuss the important challenges and future research directions in F

Distribution and inter-regional relationship of amyloid-beta plaque deposition in a 5xFAD mouse model of Alzheimer’s disease

Alzheimer’s disease (AD) is the most common form of dementia. Although previous studies have selectively investigated the localization of amyloid-beta (Aβ) deposition in certain brain regions, a comprehensive characterization of the rostro-caudal distribution of Aβ plaques in the brain and their inter-regional correlation remain unexplored. Our results demonstrated remarkable working and spatial memory deficits in 9-month-old 5xFAD mice compared to wildtype mice. High Aβ plaque load was detected in the somatosensory cortex, piriform cortex, thalamus, and dorsal/ventral hippocampus; moderate levels of Aβ plaques were observed in the motor cortex, orbital cortex, visual cortex, and retrosplenial dysgranular cortex; and low levels of Aβ plaques were located in the amygdala, and the cerebellum; but no Aβ plaques were found in the hypothalamus, raphe nuclei, vestibular nucleus, and cuneate nucleus. Interestingly, the deposition of Aβ plaques was positively associated with brain inter-regions including the prefrontal cortex, somatosensory cortex, medial amygdala, thalamus, and the hippocampus. In conclusion, this study provides a comprehensive morphological profile of Aβ deposition in the brain and its inter-regional correlation. This suggests an association between Aβ plaque deposition and specific brain regions in AD pathogenesis

Conductive cotton prepared by polyaniline in situ polymerization using laccase

The high-redox-potential catalyst laccase, isolated from Aspergillus, was first used as a biocatalyst in the oxidative polymerization of water-soluble conductive polyaniline, and then conductive cotton was prepared by in situ polymerization under the same conditions. The polymerization of aniline was performed in a water dispersion of sodium dodecylbenzenesulfonate (SDBS) micellar solution with atmospheric oxygen serving as the oxidizing agent. This method is ecologically clean and permits a greater degree of control over the kinetics of the reaction. The conditions for polyaniline synthesis were optimized. Characterizations of the conducting polyaniline and cotton were carried out using Fourier transform infrared spectroscopy, UV–vis spectroscopy, cyclic voltammetry, the fabric induction electrostatic tester, and the far-field EMC shielding effectiveness test fixture.This work was financially supported by the National Natural Science Foundation of China (21274055, 51173071), the Program for New Century Excellent Talents in University (NCET-12-0883), the Natural Science Foundation of Jiangsu Province (BK2011157), the Fundamental Research Funds for the Central Universities (JUSRP51312B), and the Program for Changjiang Scholars and Innovative Research Team in University (IRT1135)