Doctor of Philosophy

dissertationChina's reform and transition have dramatically accelerated the socioeconomic development in the last three decades. At the same time, the unequal distributions of wealth and social resources have been intensified. China's regional inequality has attracted more attention from both policy makers and researchers. The central government has listed "reducing regional inequality" as one important goal of national development. This dissertation research intends to quantify China's regional development during the reform era by detecting the multiscale variation of regional inequality, examining the spatial-temporal hierarchy and influence of multimechanisms, and exploring one consequence of regional economic disparity. First, this project investigates China's regional economic inequality from 1978 to 2007. I analyze the multiscalar spatial patterns of economic disparities with Coefficient of Variation (CV), Gini Coefficient, and Theil Index, and explore the spatial-temporal hierarchy of multimechanisms and their specific influences on regional economy through multilevel modeling. The results reveal the significant role of municipalities for shaping the spatial-temporal variation of China's economic development, and indicate the sensitivity of regional inequality to spatial scale. The analysis also illustrates that globalization has become the prominent mechanism of China's development in the recent decade. Second, this study examines health care and health inequalities as an important consequence of an unbalanced regional economy. I apply Geographic Information System (GIS)-based spatial statistical methods such as Coefficient of Variation and Moran's I to detect spatial-temporal patterns of health care, and use multilevel regression to examine the linkages between health care, mortality, and regional economic inequality. The analysis reveals that health care inequality is also sensitive to geographic scale, and demonstrates that the concurrent transitions of decentralization, marketization, globalization, and urbanization in China have interactively contributed to health care inequality and mortality. Third, this research conducts a case study in a less investigated agricultureoriented interior province, Henan Province. Such statistical and GIS methods as CV, Getis-Ord Gi*, and geographically weighted regression (GWR) are used to explore the disparities in economic development and health care level as well as to examine the effects of multiple transitions. The results uncover the significant core-periphery and urban-rural gaps in both economy and health care level

Justice and justification in accounting

We are living in a society in which we are all connected in one way or another; bound together in social cooperation. This thesis is primarily concerned with the terms of our cooperation and with how accounting can contribute to the justice, as fairness, of those terms. Accounting practice, and the principles that shape it, make a significant contribution to the regulation of our social relations, in the business sphere and beyond, by dictating what information should be collected and what is to be disclosed in corporate reports and how; who is to give and who is entitled to receive accounts and of what. Such reports contribute to the governance of society by providing information on which action can be taken, and by having inductive effects on the behaviour of managers and others. I maintain therefore, that accounting, has the potential to help support the development of a more just society and, a fairer system of social cooperation. This is a potential that I hope this thesis can play a part, albeit an entirely theoretical part, in helping to bring to realisation. I turn to the work of the political philosopher John Rawls to guide my consideration of justice in accounting. I use what I see as three stages in the development of Rawls thought as a framework for my analysis. The thesis is therefore divided into three main parts: Firstly, his seminal formulation A Theory of Justice Rawls develops to approach justice and justification; Secondly, the development of his thinking designed to accommodate his recognition of the implications of reasonable pluralism leading to the development of Political Liberalism, and a political conception of justice; Thirdly, the late development of Rawls thinking in response to critique, and in particular his engagement with the critical perspective of Jürgen Habermas, and his turn to a more discursive interpretations of his position. I find, and show, that Rawls provides us with tools that we can use to improve our thinking about justice in accounting. The potential of these tools including the method of reflective equilibrium and the device of the original position has been relatively neglected; I show that given a discursive reading these ideas can and should have an important place in critical accounting thinking. I find that strong, but thin, moral foundations are vital to our justification of concepts of justice and to critique, and I show that we can have such foundations without lapsing into traditional metaphysics. I find that following Rawls in this exploration of justice opens a new perspective on accountability, as justification and a practice of equality. He offers us ways to think about justice in accounting that are better than the utilitarian and intuitionist traditions that have held accounting practice thinking about a fair accounting in their conceptual grip; better justified and better able to account for our considered judgements

Adaptive Activation Network and Functional Regularization for Efficient and Flexible Deep Multi-Task Learning

Multi-task learning (MTL) is a common paradigm that seeks to improve the generalization performance of task learning by training related tasks simultaneously. However, it is still a challenging problem to search the flexible and accurate architecture that can be shared among multiple tasks. In this paper, we propose a novel deep learning model called Task Adaptive Activation Network (TAAN) that can automatically learn the optimal network architecture for MTL. The main principle of TAAN is to derive flexible activation functions for different tasks from the data with other parameters of the network fully shared. We further propose two functional regularization methods that improve the MTL performance of TAAN. The improved performance of both TAAN and the regularization methods is demonstrated by comprehensive experiments.Comment: To appear in AAAI-202

The Anti-Inflammatory Activity of HMGB1 A Box Is Enhanced When Fused with C-Terminal Acidic Tail

HMGB1, composed of the A box, B box, and C tail domains, is a critical proinflammatory cytokine involved in diverse inflammatory diseases. The B box mediates proinflammatory activity, while the A box alone acts as a specific antagonist of HMGB1. The C tail contributes to the spatial structure of A box and regulates HMGB1 DNA binding specificity. It is unknown whether the C tail can enhance the anti-inflammatory effect of A box. In this study, we generated fusion proteins consisting of the A box and C tail, in which the B box was deleted and the A box and C tail were linked either directly or by the flexible linker sequence (Gly4Ser)3. In vitro and in vivo experiments showed that the two fusion proteins had a higher anti-inflammatory activity compared to the A box alone. This suggests that the fused C tail enhances the anti-inflammatory effect of the A box

Multivariate Deep Learning Classification of Alzheimer’s Disease Based on Hierarchical Partner Matching Independent Component Analysis

Machine learning and pattern recognition have been widely investigated in order to look for the biomarkers of Alzheimer’s disease (AD). However, most existing methods extract features by seed-based correlation, which not only requires prior information but also ignores the relationship between resting state functional magnetic resonance imaging (rs-fMRI) voxels. In this study, we proposed a deep learning classification framework with multivariate data-driven based feature extraction for automatic diagnosis of AD. Specifically, a three-level hierarchical partner matching independent components analysis (3LHPM-ICA) approach was proposed first in order to address the issues in spatial individual ICA, including the uncertainty of the numbers of components, the randomness of initial values, and the correspondence of ICs of multiple subjects, resulting in stable and reliable ICs which were applied as the intrinsic brain functional connectivity (FC) features. Second, Granger causality (GC) was utilized to infer directional interaction between the ICs that were identified by the 3LHPM-ICA method and extract the effective connectivity features. Finally, a deep learning classification framework was developed to distinguish AD from controls by fusing the functional and effective connectivities. A resting state fMRI dataset containing 34 AD patients and 34 normal controls (NCs) was applied to the multivariate deep learning platform, leading to a classification accuracy of 95.59%, with a sensitivity of 97.06% and a specificity of 94.12% with leave-one-out cross validation (LOOCV). The experimental results demonstrated that the measures of neural connectivities of ICA and GC followed by deep learning classification represented the most powerful methods of distinguishing AD clinical data from NCs, and these aberrant brain connectivities might serve as robust brain biomarkers for AD. This approach also allows for expansion of the methodology to classify other psychiatric disorders

Parametric analysis and optimization for exergoeconomic performance of a combined system based on solid oxide fuel cell-gas turbine and supercritical carbon dioxide Brayton cycle

Fuel cell-gas turbine hybrid system is a potential field of investigation. This study establishes a modeling and optimization framework for a novel hybrid system consisting of a solid oxide fuel cell, a gas turbine and a supercritical carbon dioxide Brayton cycle. Based on the proposed thermodynamical model, a parametric analysis is investigated to determine the impacts of several key parameters on the system exergoeconomic performance. Meanwhile, bi-objective optimization is conducted for maximizing the exergy efficiency and minimizing the levelized cost of electricity via the Epsilon-constraint approach. The Linear Programming Techniques for Multidimensional Analysis of Preference decision-making approach is further employed to select the Pareto optimum solution from Pareto frontiers. The results show that several extreme values for the exergy efficiency and the levelized cost of electricity exist in a series of sensitivity curves, respectively. The Pareto frontiers indicates that with the increase of the exergy efficiency, the levelized cost of electricity shows a moderately increasing trend at first and increases rapidly afterward. Overall, at the Pareto optimum solution, the combined system can achieve an optimal exergy efficiency and levelized cost of electricity by 68% and 0.0575 $ kWh −1 , respectively

Novi VP2/VP3 rekombinantni senekavirus A izoliran u sjevernoj Kini

Senecavirus A (SVA), previously called the Seneca Valley virus, is the only member of the genus Senecavirus within the family Picornaviridae. This virus was discovered as a serendipitous finding in 2002 and named Seneca Valley virus 001 (SVV-001). SVA is an emerging pathogen that can cause vesicular lesions and epidemic transient neonatal a sharp decline in swine. In this study, an SVA strain was isolated from a pig herd in Shandong Province in China and identified as SVA-CH-SDFX-2022. The full-length genome was 7282 nucleotides (nt) in length and contained a single open reading frame (ORF), excluding the poly (A) tails of the SVA isolates. Phylogenetic analysis showed that the isolate shares its genomic organization, resembling and sharing high nucleotide identities of 90.5% to 99.6%, with other previously reported SVA isolates. The strain was proved by in vitro characterization and the results demonstrate that the virus has robust growth ability in vitro. The recombination event of the SVA-CH-SDFX-2022 isolate was found and occurred between nts 1836 and 2710, which included the region of the VP2 (partial), and VP3 (partial) genes. It shows the importance of faster vaccine development and a better understanding of virus infection and spread because of increased infection rates and huge economic losses. This novel incursion has substantial implications for the regional control of vesicular transboundary diseases, and will be available for further study of the epidemiology of porcine SVA. Our findings provide useful data for studying SVA in pigs.Senekavirus A (SVA), prije nazivan virusom doline Seneca Valley, jedini je pripadnik roda senekavirusa u porodici Picornaviridae. Virus je slučajno otkriven 2002. i nazvan virusom doline Seneca 001 (SVV-001). SVA je novi patogen koji može uzrokovati vezikularne lezije i prolaznu epidemiju novorođene prasadi s naglim gubicima u proizvodnji. U ovom je istraživanju soj SVA izoliran u populaciji svinja iz provincije Shandong u Kini i identificiran kao SVA-CHSDFX-2022. Kompletni genom izolata SVA imao je 7282 nukleotida (nt) u dužini i sadržavao je jedan otvoreni okvir za očitavanje (ORF), bez poli-A repova. Filogenetska je analiza pokazala da izolat u velikoj mjeri sadržava genomsku organizaciju i nukleotidne identitete, od 90,5 % do 99,6 %, s drugim poznatim SVA izolatima. Karakterizacija virusa je pokazala da ima veliku sposobnost rasta in vitro. Pronađena je rekombinacija izolata SVA-CH-SDFX-između nukleotida 1836 i 2710 što je uključilo regiju gena VP2 (parcijalno) i gena VP3 (parcijalno). Zbog visoke stope infektivnosti i golemih ekonomskih gubitaka važan je brži razvoj cjepiva i bolje razumijevanje zaraze. Rezultati ovog istraživanja pružaju korisne podatke za proučavanje SVA virusa, posebno s obzirom na njegovu epidemiologiju u svinja i regionalnu prekograničnu kontrolu vezikularnih bolesti

Analiza genskih varijacija rekombinantnog soja dobivenog iz triju linija virusa-2 reproduktivnog i respiratornog sindroma svinja

Since the rise of the porcine reproductive and respiratory syndrome virus (PRRSV) in China, gene mutations have frequently occurred. To understand the current prevalence and evolution of PRRSV in Shandong Province, 1,528 samples suspected of PRRSV were collected from local pig farms of different sizes. The complete genome sequence of the PRRSV strain SDLY-27 was determined by next-generation sequencing (NGS) technology. The genomic sequence of SDLY-27 was 15,363 nucleotides (nt) in length, comparative analysis of the whole genome sequence suggested that the homology between SDLY 27 and 81 PRRSV strains from China and other countries in genbank was 61.9 ~ 96.4%. This study is the first to detect recombinants from multiple recombination events among the Lineage 8 (JXA1-like strains), Lineage 5 (RespPRRSV-MLV and VR2332 strains) and Sublineage 1.5 (NADC34-like strains) in Shandong, China, and provides new data for the epidemiological study of PRRSV in China. This study enriches the epidemiological data on PRRSV in Shandong Province, China. It provides an important reference for the development of new vaccines and for the prevention and control of PRRSV in China.Usporedno sa širenjem virusa reproduktivnog i respiratornog sindroma svinja (PRRSV) u Kini, sve su češće bile i njegove genske mutacije. Kako bi se ustanovila trenutačna prevalencija i evolucija PRRSV-a u pokrajini Shandong, s lokalnih farmi prikupljeno je 1528 uzoraka svinja različitih kategorija za koje je postojala sumnja na zarazu PRRSVom. Kompletan genomski slijed soja SDLY-27 PRRSV-a određen je tehnologijom sekvenciranja sljedeće generacije (NGS). Slijed je imao dužinu od 15 363 nukleotida (nt), a komparativna analiza cijeloga genomskog slijeda uputila je na to da je homolognost između sojeva SDLY 27 i 81 PRRSV-a iz Kine i uzoraka u banci gena iz drugih zemalja 61,9~96,4%. Ovo je prvo istraživanje koje je otkrilo rekombinantne sojeve iz višestrukih rekombinacija među linijama 8 (sojevi nalik na JXA1), 5 (sojevi RespPRRSV-MLV i VR2332) i podlinije 1,5 (sojevi nalik na NADC34) u Shandongu, Kina.Kao takvo, istraživanje pruža nove podatke o epidemiologiji PRRSV-a u Kini, posebno u pokrajini Shandong, a ujedno predstavlja i važnu referenciju za razvoj novih cjepiva te prevenciju i kontrolu bolesti uzrokovane navedenim virusom

Community-based lung cancer screening by low-dose computed tomography in China:First round results and a meta-analysis

OBJECTIVE: To evaluate the efficiency of low-dose computed tomography (LDCT) screening for lung cancer in China by analyzing the baseline results of a community-based screening study accompanied with a meta-analysis. METHODS: A first round of community-based lung cancer screening with LDCT was conducted in Tianjin, China, and a systematic literature search was performed to identify LDCT screening and registry-based clinical studies for lung cancer in China. Baseline results in the community-based screening study were described by participant risk level and the lung cancer detection rate was compared with the pooled rate among the screening studies. The percentage of patients per stage was compared between the community-based study and screening and clinical studies. RESULTS: In the community-based study, 5523 participants (43.6% men) underwent LDCT. The lung cancer detection rate was 0.5% (high-risk, 1.2%; low-risk, 0.4%), with stage I disease present in 70.0% (high-risk, 50.0%; low-risk, 83.3%), and the adenocarcinoma present in 84.4% (high-risk, 61.5%; low-risk, 100%). Among all screen-detected lung cancer, women accounted for 8.3% and 66.7% in the high- and low-risk group, respectively. In the screening studies from mainland China, the lung cancer detection rate 0.6% (95 %CI: 0.3%-0.9%) for high-risk populations. The proportions with carcinoma in situ and stage I disease in the screening and clinical studies were 76.4% (95 %CI: 66.3%-85.3%) and 15.2% (95 %CI: 11.8%-18.9%), respectively. CONCLUSIONS: The stage shift of lung cancer due to screening suggests a potential effectiveness of LDCT screening in China. Nearly 70% of screen-detected lung cancers in low-risk populations are identified in women