Influence of commercial proteases on the proteolysis of enzyme modified cheese : a thesis presented in partial fulfilment of the requirements for the degree of Master of Technology in Food Technology at Massey University, Palmerston North, New Zealand

The influence of four commercial proteases, Protease A, Protease B, Protease C and a two enzyme blend Protease DE, on proteolysis in an enzyme modified cheese (EMC) base has been investigated. Also, a series of preliminary experiments to determine the basic characteristics of the four enzyme preparations in buffer systems has been undertaken. Generally, the exopeptidase activity of the four enzyme preparations was more stable than the endopeptidase activity of the preparations. The highest enzyme activity for all preparations was given at pH 6.5 and Protease B was found to be sensitive to chelating agents. In addition, Protease B was found to contain at least two exopeptidases. Residual protease activities in EMC using a 55% moisture cheese base were found to be 0.005%, 0.009%, 0.007% and 0.004% (w/v) for Protease A, Protease B, Protease C and Protease DE, respectively, following inactivation by heating at 95°C heating for 30 minutes. Under the same incubation conditions (0.15% enzyme at 40°C for 24 h), Protease DE gave greater proteolysis than the three other enzymes and Protease B was the weakest protease. EMC digestion with a combination of proteases was different from that obtained with individual proteases. The combinations of Protease A/Protease C, Protease DE/Protease C, Protease B/Protease C and Protease DE/Protease A showed that the higher the proportion of the former protease in the combinations, the higher the amounts of total amino acids produced in the EMC. The combinations of Protease A/Protease B and Protease B/Protease DE gave greater amounts of total amino acids with the ratio of each enzyme close to 50:50 than with the individual enzymes. With respect to the molecular mass distribution of peptides in the various EMC digestions, Protease DE produced the greatest amount of peptides of 3 or fewer residues and Protease C gave the greatest amount of more medium sized peptides with 11-20 residues. Compared with Protease C, Protease A was more efficient in giving small peptides, while Protease B gave the lowest levels of medium and small peptides, but a high level of free amino acids. In sensory testing, Protease DE produced EMC with a strong pungent and astringent flavour, Protease C gave bitterness, Protease A gave a sweet flavour at a low concentration but bitter flavours with a high concentration and Protease B produced more savoury flavour without bitterness

The impact of trade promotion services on Canadian exporter performance.

We evaluate the impact of the export promotion program delivered by the Canadian Trade Commissioner Service on various dimensions of export performance. Over the 1999-2006 time period we study, Canadian firms successfully diversified their exports to destinations beyond the United States and smaller firms increased their share of total exports. Both of these achievements are explicit aims of the program, but in order to make causal inferences we rely on various identifying assumptions from the treatment effects literature. The results indicate very robustly that the program had an effect at the intensive margin, boosting the average level of exports to given product-destination markets. Effects at the extensive margins of trade, increasing the number of export destinations or number of products exported, are smaller and more sensitive to the identification assumption. This finding differs from previous studies for several Latin American countries where extensive margin effects were most robust. One reason is that the Canadian program was most effective for larger firms and for firms already active on several export markets.

The impact of trade promotion services on Canadian exporter performance

We evaluate the impact of the programs delivered by the Canadian Trade Commissioner Service (TCS) on export performance by Canadian firms. We draw on a unique set of microdata created by linking three separate firm-level databases: Statistics Canada’s Exporter Register and its Business Register, which provide information on export activity and firm characteristics, and the TCS client management database maintained by Foreign Affairs and International Trade Canada, which contains details on trade promotion services provided to Canadian firms. We apply the treatment effects analytical framework to isolate the effects of public sector trade promotion. We find that TCS programs have a consistent and positive impact on Canadian exporter performance. Exporters that access TCS services export, on average, 17.9 percent more than comparable exporters that do not. Furthermore, we also find that TCS assistance benefits exporters in terms of product and market diversification.Export Promotion, Heterogeneous Firms, Canada

The impact of trade promotion services on Canadian exporter performance.

We evaluate the impact of the programs delivered by the Canadian Trade Commissioner Service (TCS) on export performance by Canadian firms. We draw on a unique set of microdata created by linking three separate firm-level databases: Statistics Canada’s Exporter Register and its Business Register, which provide information on export activity and firm characteristics, and the TCS client management database maintained by Foreign Affairs and International Trade Canada, which contains details on trade promotion services provided to Canadian firms. We apply the treatment effects analytical framework to isolate the effects of public sector trade promotion. We find that TCS programs have a consistent and positive impact on Canadian exporter performance. Exporters that access TCS services export, on average, 17.9 percent more than comparable exporters that do not. Furthermore, we also find that TCS assistance benefits exporters in terms of product and market diversification.

Impact of Drought Stress on Oak Stomatal Size and Density at Thompson Farm, NH

Global climate change is likely to affect northeastern U.S. forests by increasing the frequency and severity of drought events. Historically, droughts rarely occurred in this region, so native tree species are not well-adapted to extreme moisture stress. In the future, the changing climate will likely cause unprecedented levels of low water availability which may have implications on future forest composition. It is hypothesized that trees can respond to these environmental changes by altering their functional traits, also referred to as phenotypic plasticity; for example, by producing leaves with fewer and smaller stomata. To determine the capacity to which oak trees adjust their functional leaf traits in response to water stress, stomatal size and density were measured in northern red oak (Quercus rubra), black oak (Q. velutina), and white oak (Q. alba)using leaves collected in 2020 and 2021 from the UNH Thompson Farm DroughtNet experiment. Imprints of the lower surface of each leaf were made with clear nail polish, mounted on slides, and examined under a light microscope. Images taken from these slides were then counted and measured using ImageJ software. Preliminary results show that both stomatal size and density values were lower in 2021 than 2020. No significant differences were found between drought and control treatments. Variation existed between individual trees of the same species and within different leaves of the same tree

House Republican Budget Plan: State-by-State Impact of Changes in Medicaid Financing

Estimates how the April 2011 Budget Plan passed by the House of Representatives would affect federal Medicaid funding for states between 2012 and 2021 and how in turn this would affect Medicaid spending and enrollment and hospitals under three scenarios

Stochastic Gradient Hamiltonian Monte Carlo

Hamiltonian Monte Carlo (HMC) sampling methods provide a mechanism for defining distant proposals with high acceptance probabilities in a Metropolis-Hastings framework, enabling more efficient exploration of the state space than standard random-walk proposals. The popularity of such methods has grown significantly in recent years. However, a limitation of HMC methods is the required gradient computation for simulation of the Hamiltonian dynamical system-such computation is infeasible in problems involving a large sample size or streaming data. Instead, we must rely on a noisy gradient estimate computed from a subset of the data. In this paper, we explore the properties of such a stochastic gradient HMC approach. Surprisingly, the natural implementation of the stochastic approximation can be arbitrarily bad. To address this problem we introduce a variant that uses second-order Langevin dynamics with a friction term that counteracts the effects of the noisy gradient, maintaining the desired target distribution as the invariant distribution. Results on simulated data validate our theory. We also provide an application of our methods to a classification task using neural networks and to online Bayesian matrix factorization.Comment: ICML 2014 versio

Detecting sources of heat loss in residential buildings from infrared imaging

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 27).Infrared image analysis was conducted to determine the most common sources of heat loss during the winter in residential buildings. 135 houses in the greater Boston and Cambridge area were photographed, stitched, and tallied to characterize nine major causes of heat loss: window frames, window surfaces, window cracks, basements, door cracks, corners, chimneys, roof ridges, and soffits. The nine causes of heat loss were mapped to the three modes of heat transfer: conduction, convection, and radiation. It was found that heat losses through window surfaces, window cracks, chimneys, and soffits dominated as common sources of energy leakage, each represented in more than 70% of the houses analyzed. Opportunities for future work include more thorough examination of losses through ducts and walls, as well as developing methods for improvements.by Emily Chen Shao.S.B

Improving Online Student Engagement in the Online Classroom

This Organizational Improvement Plan seeks to address inadequate online student engagement within online classrooms at University X. Inadequate student engagement risks students’ learning, persistence, performance, and academic achievement (Kuh, Cruce, Shoup, Kinzi, & Gonyea, 2008; Meyer, 2014; Pardo, Han, & Ellis, 2016; Phan, McNeil, & Robin, 2016), demonstrating the pressing need to improve online student engagement. This work is undertaken in the context of substantial growth in online education, accelerated in the short term by a movement to online delivery of face-to-face post-secondary education necessitated by the coronavirus pandemic of 2020. The author considers this problem from a non-traditional leadership role of an adjunct online instructor, and so employs distributed leadership, as enacted through teacher leadership, from the vantage point of constructivism. The assumptions of emergent and continuous change which underpin this result in the selection of Weick and Quinn’s (1999) freeze, rebalance, unfreeze framework for leading change and sensemaking as a tool to conduct a critical organizational analysis, in alignment with the author’s constructivist perspective. The author recommends engaging in a period of individual modifications to her instructional practice, followed by the development of a Community of Practice. This Community of Practice will collaboratively build a definition of online student engagement and develop relevant changes to practice designed to improve online student engagement in the online classrooms of the Community of Practice. Communication is a critical element of this plan as the author must engage colleagues and build momentum with limited resources