How to get school children access to urban farming by activating vacant land and rooftops

The thesis topic is how to get school children access to urban farming by activating vacant land and rooftops. Phase one focuses on research about the rooftop urban farming systems in New York. As a high density and high land value city, New York is one of the cities with the largest number of rooftop farms in the United States. People use urban rooftop farms as a medium to improve community engagement and improve environmental issues. For phase one, this thesis researched the operation and conditions of existing rooftop farms, and evaluated the advantages and disadvantages of them to figure out the problems they are facing. In addition, phase one discusses what kind of programs could be used to connect-people. Phase two is aiming to combine different urban farming typologies together and explore how to use urban farming to serve children’s education. The specific idea in phase two is how to use urban farming as a method to create outdoor learning classrooms for children and community members. It also expands on ideas about combining different kinds of urban farming, and developing urban farming with the next generation of children. Phase three is aiming to place four urban farming typologies according to local conditions at the thesis site, and making urban farming accessible to school children. This phase investigates how to create the specific urban farming system for this site. In addition, phase three is concerned with expanding the existing urban farming design strategies and systems, and introducing new strategies and systems

To what extent does COVID-19 drive stock market volatility? A comparison between the U.S. and China

This paper presents a novel wavelet-based quantile-on-quantile method for comparing the impact of COVID-19 on stock market volatility between the U.S. and China. Wavelet decomposition shows that the impact has stronger regularity in the lower frequency domain. Compared with oil price fluctuations, COVID-19 is the main reason for the sharp fluctuation of the U.S. stock market. Unlike China, however, the strong growth of daily new cases, which continued for months, has made the U.S. stock market insensitive to COVID-19. In addition, the particularly loose interest rate policy has effectively suppressed the volatility of the U.S. stock market. However, in contrast to China, the near zero interest rate applied by the U.S. makes it difficult to generate sufficient monetary policy space to address a new potential crisis. The result of this study presents the differences of the financial market response under different epidemic management modes. Under the background that COVID-19 is not effectively controlled, a loose monetary policy may be an expedient measure to stabilise the market. This is of great practical significance towards achieving epidemic control and financial market stability under the background of the global spread of COVID-19

TRANSFORM FARMING WITH THE HELP OF SOCIAL MEDIA A PIONEERING CHINESE COMMUNITY SUPPORTED AGRICULTURE (CSA) FARM AND ITS MICRO BLOG USA

This study explores the role of social media technology, especially micro blogging technology in the introduction of a new agricultural business model in China. As the rapid urbanization process brings challenges such as loss of agricultural land and food safety problems, some people try to address the challenges through transforming farming with a new business model, i.e. Community Supported Agriculture (CSA). The CSA model emphasizes risk sharing, and requires significant trust between farmers and consumers. Yet the general public lack awareness of the model when it was first introduced, and trust among each other is quite low in the general public. Social media tools, such as the micro blogging technology, are adopted by the young CSA farmers to develop public awareness of the CSA model and cultivate consumers’ trust toward the farm. Through content analysis of micro blog posts of the CSA pioneers in China, the study contributes to our understanding of the role of micro blogging technology in transforming farming and addressing complex societal problems

Investigating the Impact of Dialogic and Trialogic Interactive Factors on Chinese Advanced L2 learners’ Vocabulary Use in Spoken Contexts

The main objective of this study is to investigate how interactive factors affect the vocabulary usage of second language learners in their spoken language. Participants were 24 L1 Chinese undergraduate students of L2 English at an advanced level. L2 learners’ vocabulary use was assessed via tokens, lexical diversity, and frequency-based lexical sophistication. Participants provided speech data in response to seven persuasive speaking tasks across three speaking modes: two monologic, two dialogic, and three trialogic. This study showed that the interactive factor has a varied effect on L2 learners’ vocabulary usage. It positively influences the use of advanced vocabulary but does not affect the total number of words produced or the diversity of words used. Second, of all three speaking modes, the dialogic speaking mode is the best speaking condition to trigger L2 learners’ use of advanced words. Third, the vocabulary employed in dialogues and trialogues can vary due to the inherent disparities between the two modes of speech. Therefore, we propose the use of the dialogic interactive factor and trialogic interactive factor instead of the term “interactive factor” to encompass two specific conditions in which there was a noticeable difference in the performance of L2 learners

Nonlinear dynamic simulation and parametric analysis of a rotor-AMB-TDB system experiencing strong base shock excitations

The introduction of active magnetic bearings (AMBs) has enabled turbomachinery to increase power density, controllability, and general resilience to external disturbances. However, because of the limited load capacity of AMBs, the base shock condition that "on-board" machines often encounter may result in contact between the rotor and the touchdown bearings (TDBs), which can seriously damage the machine. A challenge in AMB applications is to alleviate this problem. This study presents a dynamic analysis of a rotor-AMB-TDB system under strong base shocks while the AMBs are operating. Detailed TDB and contact models are presented using Hertzian contact theory. A PD controller was then designed considering system saturation and friction, based on the Coulomb model and the effect of lubrication. The dynamic equations were solved for the dynamic trajectory and FFT spectra, STFT spectra, Poincaré maps and bifurcation diagrams were used for the parametric analysis. The results show that the rotor had three motion modes. System parameters, including unbalance eccentricity, magnetic gap clearance and equivalent stiffness and damping ratio, may lead to complex nonlinear dynamic behavior including periodic, KT-periodic, and quasi-periodic responses and jump phenomenon. Suitable designs that consider these parameters may avoid undesirable rotor dynamic behavior. This study reveals the mechanism for nonlinear response, providing a method for its prediction, and core controller parameter designs for rotor re-levitation

Correlation properties of interleaved Legendre sequences and Ding-Helleseth-Lam sequences

Sequences with optimal autocorrelation properties play an important role in wireless communication, radar and cryptography. Interleaving is a very important method in constructing the optimal autocorrelation sequence. Tang and Gong gave three different constructions of interleaved sequences (generalized GMW sequences, twin prime sequences and Legendre sequences). Su et al. constructed a series of sequences with optimal autocorrelation magnitude via interleaving Ding-Helleseth-Lam sequences. In this paper we further study the correlation properties of interleaved Legendre sequences and Ding-Helleseth-Lam sequences

Understanding the Cooperative Interaction between Myosin II and Actin Cross-Linkers Mediated by Actin Filaments during Mechanosensation

AbstractMyosin II is a central mechanoenzyme in a wide range of cellular morphogenic processes. Its cellular localization is dependent not only on signal transduction pathways, but also on mechanical stress. We suggest that this stress-dependent distribution is the result of both the force-dependent binding to actin filaments and cooperative interactions between bound myosin heads. By assuming that the binding of myosin heads induces and/or stabilizes local conformational changes in the actin filaments that enhances myosin II binding locally, we successfully simulate the cooperative binding of myosin to actin observed experimentally. In addition, we can interpret the cooperative interactions between myosin and actin cross-linking proteins observed in cellular mechanosensation, provided that a similar mechanism operates among different proteins. Finally, we present a model that couples cooperative interactions to the assembly dynamics of myosin bipolar thick filaments and that accounts for the transient behaviors of the myosin II accumulation during mechanosensation. This mechanism is likely to be general for a range of myosin II-dependent cellular mechanosensory processes

Estimation of chlorophyll concentration for environment monitoring in Scottish marine water.

Marine Scotland is tasked with reporting on the environmental status of Scottish marine waters, an enormous area of water extending from the shoreline to deep oceanic waters. As one of the most important variables, chlorophyll concentration (Chl) plays an important role in the seawater quality monitoring. Currently, the Chl observation is mostly done by expensive ship-based surveys that have very limited spatio-temporal coverage. Satellite based ocean colour remote sensing has the potential to significantly enhance monitoring capabilities but this opportunity has not been widely adopted by statutory reporting bodies across Europe due to concerns over satellite data quality. To break through this bottleneck, in this paper, we explore to implement advanced machine learning techniques to automatically estimate the Chl via the historic time series of ocean colour remote sensing data during from July 2002 to September 2019