Search for Evergreens in Science: A Functional Data Analysis

Evergreens in science are papers that display a continual rise in annual citations without decline, at least within a sufficiently long time period. Aiming to better understand evergreens in particular and patterns of citation trajectory in general, this paper develops a functional data analysis method to cluster citation trajectories of a sample of 1699 research papers published in 1980 in the American Physical Society (APS) journals. We propose a functional Poisson regression model for individual papers' citation trajectories, and fit the model to the observed 30-year citations of individual papers by functional principal component analysis and maximum likelihood estimation. Based on the estimated paper-specific coefficients, we apply the K-means clustering algorithm to cluster papers into different groups, for uncovering general types of citation trajectories. The result demonstrates the existence of an evergreen cluster of papers that do not exhibit any decline in annual citations over 30 years.Comment: 40 pages, 9 figure

Application of green GDP concept to the calculating method of economic benefits of the Yangshan deep-water port

With the construction of the first phrase of the Yangshan Deep-water Port, it has successfully brought Shanghai and its surrounding areas billions of dollars benefit income. It is quite obvious that every transportation project is aimed to get the most economic benefit income, but it is also can not denied that certainly negative influences to humans’ health, natural resources and ecologic environment is being brought when the transport project is being built and putting into operating. So it is obvious that any economic benefits making by the Yangshan Deep-water Port should not at the sacrifice of environment and ecology. But refer to the present method of calculating the economic benefits of the Yangshan Deep-water Port, it has mostly focus on the economic evaluation aspects, so we put forward the question of how to apply green gross domestic product (GDP) index which bases on ecologic and environmental aspects into the method of calculating the benefits of the Yangshan Deep-water Port to meet the requirement of sustainable development. In the dissertation, it has divided into following parts. The first chapter is the introduction. This chapter has included the problem formulation, the methodology and purposes of the study and the overall structure of the dissertation. In chapter two, it is the literature review, which has introduced the present methods to calculate economic benefits of a certain transport project. And in chapter three, it will present the background of Yangshan Deep-water Port and “with and without test” which is the present method to calculate the economic benefits of the Yangshan Deep-water Port. The forth chapter is referring to application of green GDP concept into the calculating method of economic benefits of Yangshan Port. There would be three aspects will be influenced from the construction and operating stages of the Yangshan deep-water Port, such as the human being health, natural resources and ecologic environment. And in the last chapter, it discusses the difficulties to apply green GDP concepts into the whole evaluation method. So after a period of time’s researching the relating theories and backgrounds of this problem, and with the help and guidance of Professor Hou Ronghua, I have tried my best to make analysis of the present method of calculating economic benefits of Yangshan Deep-water Port, and provided solutions and recommendations of how to modify the method under the concepts of green GDP

MicroRNA-298 reduces levels of human amyloid-β precursor protein (APP), β-site APP-converting enzyme 1 (BACE1) and specific tau protein moieties

Alzheimer’s disease (AD) is the most common age-related form of dementia, associated with deposition of intracellular neuronal tangles consisting primarily of hyperphosphorylated microtubule-associated protein tau (p-tau) and extracellular plaques primarily comprising amyloid- β (Aβ) peptide. The p-tau tangle unit is a posttranslational modification of normal tau protein. Aβ is a neurotoxic peptide excised from the amyloid-β precursor protein (APP) by β-site APP-cleaving enzyme 1 (BACE1) and the γ-secretase complex. MicroRNAs (miRNAs) are short, single-stranded RNAs that modulate protein expression as part of the RNA-induced silencing complex (RISC). We identified miR-298 as a repressor of APP, BACE1, and the two primary forms of Aβ (Aβ40 and Aβ42) in a primary human cell culture model. Further, we discovered a novel effect of miR-298 on posttranslational levels of two specific tau moieties. Notably, miR-298 significantly reduced levels of ~55 and 50 kDa forms of the tau protein without significant alterations of total tau or other forms. In vivo overexpression of human miR-298 resulted in nonsignificant reduction of APP, BACE1, and tau in mice. Moreover, we identified two miR-298 SNPs associated with higher cerebrospinal fluid (CSF) p-tau and lower CSF Aβ42 levels in a cohort of human AD patients. Finally, levels of miR-298 varied in postmortem human temporal lobe between AD patients and age-matched non-AD controls. Our results suggest that miR-298 may be a suitable target for AD therapy

Mechanical and failure mechanisms of descending thoracic aorta: implications for health and disease

Structural organization of the extracellular matrix components of the aorta is critical to its loading-bearing capacity and homeostasis. Aortic elastic fibers form concentric lamellar layers with a closely interwoven three-dimensional network of collagen and elastic fibers in the narrow interlamellar space. Aging and cardiovascular diseases are closely associated with disrupted microstructural organization, integrity, as well as altered mechanical and failure properties of the aortic wall. The overall goal of this research is to advance the current understanding of the mechanical and failure mechanisms of human descending thoracic aorta and provide insights for aortic remodeling during aging and disease progression using integrated biomechanical testing, imaging, and computational modeling approaches. Biaxial tensile tests revealed anisotropic stiffening of the aortic wall with aging with a more drastic stiffening behavior in the longitudinal direction. A newly developed constitutive model considering collagen crosslinking suggested that collagen crosslinking has an increasing contribution to the stress-stretch behavior and elastic energy storage in aortic senescence. The aorta relies on interlamellar structural components, mainly elastic and collagen fibers, for maintaining its structural and mechanical integrity. Our study using peeling and direct tension tests demonstrated that elastic and collagen fibers both play an important role in bonding of the arterial wall, while collagen fibers dominate the interlamellar stiffness, strength and toughness. Our study further reveals that the interlamellar strength and toughness both increase due to nonenzymatic glycation, which is in accordance with the reported inverse relation between diabetes and a reduced risk of aortic dissection. On the other hand, however, our study showed decreasing interlamellar bonding toughness of the medial layer of human descending thoracic aorta with aging. Avalanches and power-law behavior in dissection propagation was found for all age groups investigated. Finite element simulations incorporating discrete interlamellar collagen fibers successfully recapitulates the power-law behavior and points to prominent structural alterations in interlamellar collagen fibers with aging including reduced fiber density and higher degree of dispersion. In aging and diseases, changes to the extracellular matrix microstructure can trigger a cascade of effects on tissue and cellular function. The knowledge gained from this research provide insights into the microstructural mechanisms in determining the physiological and failure properties of aorta and will potentially generate clinical impact on the developments of new diagnostics and interventions

General Device Integration Strategies for Two-Dimensional Materials

Despite the extraordinary wealth of unique properties of 2D layered materials (2DLM), no large scale commercial application has been achieved so far. The central challenge hereby is the scalable manufacture of these materials. While mechanical exfoliation, also famously known as the scotch-tape method, leads to materials of extremely high quality, the method itself is non-scalable due to the highly stochastic deposition yield. Major advancement has been achieved in recent years regarding the scalable production of 2DLMs, especially using chemical vapour deposition (CVD). It is now common to produce large areas of graphene (Gr) or hexagonal boron nitride (h-BN), which are two members of the family of 2DLMs, in the laboratory using CVD. Often the only limit to the size of the sample is dictated by the dimensions of available equipment. Most studies have targeted the improvement of the quality of the grown material. The focus hereby has been the growth of ever-larger single-crystalline regions by lowering the nucleation density or by merging aligned domains. Most studies fail to acknowledge the actual key challenge. Nearly all emerging applica- tions require the integration of 2DLMs into stacks of so called van der Waals heterostructures and their deposition onto insulating substrates. Since direct deposition of such structures on dielectrics has been proven to be an elusive goal, the most promising approach so far is the growth of 2DLMs on a catalyst with a subsequent transfer to the target substrate. The bottleneck of this approach has been the lack of sufficient transfer methods. A number of these have been proposed for CVD Gr and h-BN. Still the introduction of contamination and damage remain major constraints, which is exceptionally severe in case of heterostructures that rely on atomically clean interfaces. 2DLMs will only be a true candidate for commercial applications if sufficiently clean transfer methods are found that will enable large scale fabrication. The work presented in this thesis addresses this challenge in two ways. The first is to develop new and improved transfer methods for existing combinations of 2DLM and catalyst. Thereby the aim is to base the method on a detailed understanding of their interaction and thus to devise a general rationale for transfer. The proposed method, which is referred to as Lift-Off Transfer (LOT), makes use of the weak interaction between 2DLMs and certain types of catalysts. It is shown how intercalation processes result in the local oxidation of the substrate followed by selective oxide dissolution, which releases the 2DLM film. Not only is the method highly versatile, but it also yields Gr and h-BN films of high quality compared to traditional transfer methods without requiring additional post-transfer annealing. While LOT is a significant improvement over existing transfer method, it still requires bringing the 2DLM into contact with a solution, which is a potential source of contamination. It has been demonstrated, that CVD Gr, when processed using optimized methods, will show similar performance as mechanically exfoliated Gr. While these results are a promising first step towards more scalable processes, it still relies on mechanically exfoliated h-BN, which acts as a stamp that is used to delaminate the Gr from the growth catalyst. Thus, the focus is shifted on how to process and transfer CVD h-BN, which can then be used as the initial capping layer for the transfer of further layers of 2DLMs. To that end, an improved deposition process of h-BN has been developed that allows the growth of h-BN with individual domain exceeding 0.5 mm. More importantly, these h-BN films can be easily transferred using an entirely delamination based approach that makes use of the weak interaction between the specifically chosen catalyst and the h-BN. This enables the sequential pick up additional layers to create multilayer h-BN with atomic precision, and also direct fabrication h-BN/Gr heterostructures. Based on a thorough understanding of the interaction between 2DLMs and their substrate, this thesis presents new strategies for device integration. Hereby not only a method is proposed that is an incremental improvement over existing ones, but an entirely new approach is presented that enables the clean and scalable device integration of 2DLMs. This work paves the path for future large scale applications of 2DLMs.EPSR

Fast, Non-Contact, Wafer-Scale, Atomic Layer Resolved Imaging of 2D Materials by Ellipsometric Contrast Micrography

Adequate characterisation and quality control of atomically thin layered materials (2DM) has become a serious challenge particularly given the rapid advancements in their large area manufacturing and numerous emerging industrial applications with different substrate requirements. Here, we focus on ellipsometric contrast micrography (ECM), a fast intensity mode within spectroscopic imaging ellipsometry, and show that it can be effectively used for non-contact, large area characterisation of 2DM to map coverage, layer number, defects and contamination. We demonstrate atomic layer resolved, quantitative mapping of chemical vapour deposited graphene layers on Si/SiO2-wafers, but also on rough Cu catalyst foils, highlighting that ECM is applicable to all application relevant substrates. We discuss the optimisation of ECM parameters for high throughput characterisation. While the lateral resolution can be less than 1 µm, we particularly explore fast scanning and demonstrate imaging of a 4’’ graphene wafer in 47 min at 10 µm lateral resolution, i.e. an imaging speed of 1.7 cm2/min. Furthermore, we show ECM of mono-layer hexagonal BN (h-BN) and of h-BN/graphene bilayers, highlighting that ECM is applicable to a wide range of 2D layered structures that have previously been very challenging to characterise and thereby fills an important gap in 2DM metrology