An Economic History of China

An Economic History of China by Chou Chin-sheng: Subjective idealism, whether Chinese or European, boils down to spiritualism. Pre-Marxist materialism boils down to the reduction of man to a thing, as it fails to recognize that not only does the natural environment (sunspots, China as a continental rather than a seacoast-dominated geographic entity) act on man, but that man reacts on his environment too. The same is true of the school of social or economic materialism founded by Marx. At best, materialism provides the objective element in history; the spiritual element must remain history\u27s motive force. In earliest times the material forces predominated in man\u27s history, but the trend has been for the immaterial forces to grow in strength with time until now they can (as in the accomplishments of modern science) reshape the material forces themselves. Only the historical viewpoint of Sun Yat-sen\u27s People\u27s Livelihood adequately synthesizes the strong points of spiritualism and both varieties of materialism, making them inseparable facets of itself, the center of human history. It sees human progress as a spiritual process, but one inextricably linked to continuous improvement in material production.https://cedar.wwu.edu/easpress/1019/thumbnail.jp

SINGLE MOLECULE DNA MANIPULATION AND ANALYSIS USING NANOFLUIDIC CIRCUITS

Nanofluidic devices have emerged as new powerful tools for biomolecule analysis. Their utility in probing single DNA molecules is of particular interest because of both the biological importance and the ideal polymer physical properties of DNA. Such applications often involve an initial step of capturing the large, globule-shaped molecules from bulk solution and linearizing them in the nanoscale confining structures. The entropic barrier inherent to this process is typically overcome by pulling DNA into a nanoconduit using a large electric field. The resulting high velocity of molecular transport, coupled with the finite temporal resolution of detection, can make single-molecule characterizations difficult. In this dissertation, novel three-dimensional nanofunnels are described that address this problem. Focused ion beam milling is developed to fabricate complex nanostructures. The nanofunnels facilitate the capture process, enabling the introduction of DNA molecules into fluidic nanochannels with significantly lower electric fields. The gradual confinement change of the nanofunnel produces an entropy gradient for DNA molecules transitioning from bulk solution to a nanochannel. Tuning the electric field results in the stable trapping of a single DNA molecule in the nanofunnel. The precisely defined geometry enables an accurate force analysis on the molecule. For confined molecules placed in an electric field, electro-hydrodynamic interactions are discovered that differ from those present in freely diffusing or anchored molecules. Concentration polarization, a phenomenon unique to nanofluidics, is also described for devices containing a nanochannel-nanofunnel structure. The phenomenon is found to correlate with the ionic current rectification, an effect which was previously studied primarily in conical pores. Both phenomena are found to evolve over several minutes in the nanochannel-nanofunnel devices. Moreover, the electro-osmotic flow is found to greatly affect the concentration polarization and ionic current rectification. The discoveries presented in this dissertation have both theoretical and practical importance. A better understanding of the entropic and electrohydrodynamic forces on a large polyion (DNA) was achieved. The nanofunnels developed here have potential applications in nanofluidics-based DNA mapping and sequencing technologies and in the pre-concentration of biomolecules for subsequent on-chip separations or analyses.Doctor of Philosoph

MicroRNA Profiling and Head and Neck Cancer

Head and neck/oral cancer (HNOC) is a devastating disease. Despite advances in diagnosis and treatment, mortality rates have not improved significantly over the past three decades. Improvement in patient survival requires a better understanding of the disease progression so that HNOC can be detected early in the disease process and targeted therapeutic interventions can be deployed. Accumulating evidence suggests that microRNAs play important roles in many human cancers. They are pivotal regulators of diverse cellular processes including proliferation, differentiation, apoptosis, survival, motility, and morphogenesis. MicroRNA expression patterns may become powerful biomarkers for diagnosis and prognosis of HNOC. In addition, microRNA therapy could be a novel strategy for HNOC prevention and therapeutics. Recent advances in microRNA expression profiling have led to a better understanding of the cancer pathogenesis. In this review, we will survey recent technological advances in microRNA profiling and their applications in defining microRNA markers/targets for cancer prediction, diagnostics, treatment, and prognostics. MicroRNA alterations that consistently identified in HNOC will be discussed, such as upregulation of miR-21, miR-31, miR-155, and downregulation of miR-26b, miR-107, miR-133b, miR-138, and miR-139

Patterns and driving forces of dimensionality-dependent charge density waves in 2H-type transition metal dichalcogenides

Two-dimensional (2D) materials have become a fertile playground for the exploration and manipulation of novel collective electronic states. Recent experiments have unveiled a variety of robust 2D orders in highly-crystalline materials ranging from magnetism to ferroelectricity and from superconductivity to charge density wave (CDW) instability. The latter, in particular, appears in diverse patterns even within the same family of materials with isoelectronic species. Furthermore, how they evolve with dimensionality has so far remained elusive. Here we propose a general framework that provides a unfied picture of CDW ordering in the 2H polytype of four isoelectronic transition metal dichalcogenides 2H-MX$_2$ (M=Nb, Ta and X=S, Se). We first show experimentally that whilst NbSe$_2$ exhibits a strongly enhanced CDW order in the 2D limit, the opposite trend exists for TaSe$_2$ and TaS$_2$, with CDW being entirely absent in NbS$_2$ from its bulk to the monolayer. Such distinct behaviours are then demonstrated to be the result of a subtle, yet profound, competition between three factors: ionic charge transfer, electron-phonon coupling, and the spreading extension of the electronic wave functions. Despite its simplicity, our approach can, in essence, be applied to other quasi-2D materials to account for their CDW response at different thicknesses, thereby shedding new light on this intriguing quantum phenomenon and its underlying mechanisms

Towards a digital twin for analytical HPLC

Digital twins for industrial process development are quickly gaining popularity in the pharmaceutical industry as an effective alternative to expensive and time-consuming physical experiments. This work describes the digital model element of a digital twin of High-Performance Liquid Chromatography (HPLC). The model is based on a mechanistic model implemented in gPROMS ModelBuilder and integrated into the MATLAB environment. Unlike other models reported in the literature, our model comprises a more accurate prediction of the injection profile and can predict the elution behaviour for a wide range of HPLC conditions given a reduced number of experiments. The model is compared against experimental data performed to separate a mixture of eight small drug molecules on a C18 column, in gradient elution mode, and under nine different operative conditions (i.e. 3 temperatures × 3 solvent gradient). We will show that by considering only two isotherm parameters for each molecule, the digital model can accurately predict the retention behaviour of the eight analytes. Furthermore, it facilitates HPLC in-silico method development, showcased here via method time minimization through a dynamic solvent strength gradient. The proposed model is intended to be integrated into a digital twin architecture for offline decision support and real-time optimization

Uni3D: Exploring Unified 3D Representation at Scale

Scaling up representations for images or text has been extensively investigated in the past few years and has led to revolutions in learning vision and language. However, scalable representation for 3D objects and scenes is relatively unexplored. In this work, we present Uni3D, a 3D foundation model to explore the unified 3D representation at scale. Uni3D uses a 2D initialized ViT end-to-end pretrained to align the 3D point cloud features with the image-text aligned features. Via the simple architecture and pretext task, Uni3D can leverage abundant 2D pretrained models as initialization and image-text aligned models as the target, unlocking the great potential of 2D models and scaling-up strategies to the 3D world. We efficiently scale up Uni3D to one billion parameters, and set new records on a broad range of 3D tasks, such as zero-shot classification, few-shot classification, open-world understanding and part segmentation. We show that the strong Uni3D representation also enables applications such as 3D painting and retrieval in the wild. We believe that Uni3D provides a new direction for exploring both scaling up and efficiency of the representation in 3D domain.Comment: Code and Demo: https://github.com/baaivision/Uni3

Enhanced nanochannel translocation and localization of genomic DNA molecules using three-dimensional nanofunnels

The ability to precisely control the transport of single DNA molecules through a nanoscale channel is critical to DNA sequencing and mapping technologies that are currently under development. Here we show how the electrokinetically driven introduction of DNA molecules into a nanochannel is facilitated by incorporating a three-dimensional nanofunnel at the nanochannel entrance. Individual DNA molecules are imaged as they attempt to overcome the entropic barrier to nanochannel entry through nanofunnels with various shapes. Theoretical modeling of this behavior reveals the pushing and pulling forces that result in up to a 30-fold reduction in the threshold electric field needed to initiate nanochannel entry. In some cases, DNA molecules are stably trapped and axially positioned within a nanofunnel at sub-threshold electric field strengths, suggesting the utility of nanofunnels as force spectroscopy tools. These applications illustrate the benefit of finely tuning nanoscale conduit geometries, which can be designed using the theoretical model developed here.Forcing a DNA molecule into a nanoscale channel requires overcoming the free energy barrier associated with confinement. Here, the authors show that DNA injected through a funnel-shaped entrance more efficiently enters the nanochannel, thanks to facilitating forces generated by the nanofunnel geometry

Predicting sample injection profiles in liquid chromatography: A modelling approach based on residence time distributions

The pharmaceutical and bio-pharmaceutical industries rely on simulations of liquid chromatographic processes for method development and to reduce experimental cost. The use of incorrect injection profiles as inlet boundary condition for these simulations may, however, lead to inaccurate results. This study presents a novel modelling approach for accurate prediction of injection profiles for liquid chromatographic columns. The model uses the residence time distribution theory and accounts for the residence time of the sample through the injection loop, connecting tubes and heat exchangers that exist upstream of the actual chromatographic column, between the injection point and the column inlet. To validate the model, we compare simulation results with experimental injection profiles taken from the literature for 20 operating conditions. The average errors in the predictions of the mean and variance of the injection profiles result to be 8.98% and 8.52%, respectively. The model, which is based on fundamental equations and actual hardware details, accurately predicts the injection profile for a range of sample volumes and sample loop-filling levels without the need of calibration. The proposed modelling approach can help to improve the quality of in-silico simulation and optimization for analytical chromatography

The impact of mineral compositions on hydrate morphology evolution and phase transition hysteresis in natural clayey silts

The authors are grateful to the National Natural Science Foundation of China, China [51991365]; China Geological Survey Project, China [DD20211350]; Guangdong Major Project of Basic and Applied Basic Research, China [2020B0301030003]; Key Program of Marine Economy Development (Six Marine Industries) of Special Foundation of Department of Natural Resources of Guangdong Province, China [2021]56.Peer reviewedPublisher PD