TEMPERATURE OPTIMIZATION OF LACTIC ACID BATCH FERMENTATION BY LACTOBACILLUS PENTOSUS AND ITS KINETIC MODEL

Currently, lactic acid (LA) is being widely utilized in food industry, chemical industry and poly (lactic acid) synthesis. However, the search for the most favorable fermentation conditions is still desired for the successful commercial development of cost competitive processes. In this work, the effects of temperature on LA batch fermentation from glucose by Lactobacillus pentosus (L. pentosus) were studied. In batch fermentation of pH 6.0, the optimal temperature is 35 °C (agitation speed at 150 rpm, and air flow rate at 25 mL/min), and lower temperature leads to better cell growth while higher temperature results in more efficient glucose utilization and more productive LA generation. A kinetic model was developed to properly simulate batch LA production at 35 °C and pH 6.0 from glucose by L. pentosus

Quality characterization and process design of salmon oil production for human consumption

Thesis (M.S.) University of Alaska Fairbanks, 2007Salmon oil is an abundant source of polyunsaturated fatty acids, especially eicosapentaenoic acid and docosahexaenoic acid. Finding more lucrative markets for this unpurified fish oil requires well designed purification steps to reduce impurities such as free fatty acids (FFA), oxidative components, moisture, minerals, and trace metals. The temperature dependency of the rate constants for lipid oxidation and rheological properties of unpurified oil were measured and modeled using the Arrhenius equation. Performances of chitosan and/or activated earth as adsorbents were investigated to remove impurities from the oil. Activated earth was found more effective in adsorbing primary oxidation products than chitosan. Neither chitosan nor activated earth was effective in reducing FFA from the unpurified oil. Oils purified using activated earth adsorption, neutralization process, and/or combined neutralization and activated earth adsorption processes were characterized for peroxide value (PV), FFA, color, minerals, tocopherols, insoluble impurities, thermal properties, and viscosity. The neutralization process reduced FFA in the unpurified oil but PV increased. The combined method was more effective in reducing impurities than each individual process. The research findings from this study will provide a good model for purifying oil produced from salmon byproducts.1. Thermal and rheological properties and the effects of temperature on the viscosity and oxidation rate of unpuried salmon oil -- 2. Purifying salmon oil using adsorption, neutralization, and a combined neutralization and adsorption process

Hydrodynamics in the Gas-Driven Inverse Liquid-Solid Fluidized Bed

A novel reactor named Gas-Driven Inverse Liquid-Solid Fluidized Bed (GDFB for short) was developed in this research. A vertical baffle divides the column into a riser and a downer. Inverse fluidization is driven by the gas and occurs in the downer, where hydrodynamics and their influencing factors were studied. In the solid-baffle system, four fluidization regimes were observed, including the packed bed, semi-fluidized bed, fully-fluidized bed, and circulating bed. Bed expansion ratio was higher for particles with a higher density and a smaller solids loading. Moreover, the average particle velocity was proportional to superficial gas velocity and higher for denser particles. In the meshed-baffle system, the shifted bed was found between the fully-fluidized bed and the circulating bed, and some hydrodynamics differed from that in the solid-baffle system. Considering the similarity and diversity, a solid baffle or a meshed baffle should be selected depending on the needs of chemical processes

Social-psychological factors in food consumption of rural residents : The role of perceived need and habit within the theory of planned behavior

To address the problem of malnutrition in poor rural areas of China, this study aims to examine the effects of social-psychological factors in food consumption of rural residents in poor counties of Southwest China. In addition, it investigates the role of perceived need and habit within the theory of planned behavior (TPB) in predicting food consumption. A survey with random sampling was conducted on rural residents (n = 424), and the theoretical frameworks of both the standard and extended TPB were applied for comparison purposes. Structural equation modeling was applied to test the relationships among constructs. Consumption of five food items was studied, respectively: meat, eggs, dairy, fish, and fruits. Results showed that incorporation of perceived need and habit substantially increased the explanatory power of the TPB, but these factors only had significant direct effects on intention rather than behavior. Perceived need and habit are stronger predictors of intention than any other TPB construct for consumption of all food items except for meat. We found indirect effects of the constructs in the extended TPB model on consumption to be different across food items. Practical implications to improve consumption of different food items were proposed accordingly.</p

Epidemiology and etiology of pancreatic cancer

Pancreatic cancer is one of the most devastating malignancies with an extremely high fatality, resulting that its mortality rate almost equals to incidence rate. Although primary prevention is of upmost importance, the underlying etiology of this cancer remains largely unknown. Pancreatic cancer is a heterogenetic disease, and the accumulated genetic alterations play an important role in pancreatic pathogenesis. Recent advances in next-generation sequencing have enabled comprehensive cancer genomic studies. However, clinical pancreatic cancer samples are characterized as having low tumor cellularity, as a result of an abundance of stroma in the tumor microenvironment, and this presents a big challenge for direct genomic sequencing for clinical pancreatic cancer samples. In this thesis, we aimed to enrich our knowledge of the etiology of pancreatic cancer with regard to several infectious agents and poor oral hygiene. Of note, we took the challenge to directly sequence clinical pancreatic cancer samples with a broad range of tumor cellularities, and attempted to depict its variant profile. In Study I, we retrieved all hepatitis C virus (HCV) and hepatitis B virus (HBV) infection notifications in Sweden from records in a national surveillance database at the Swedish Institutet for Infectious Disease Control (SMI) from 1990 to 2006, and followed them for pancreatic cancer occurrence by the end of 2008. The pancreatic cancer risk in the exposed population was compared with that in a matched reference population. Hazard ratios (HRs) were derived from Cox proportional hazards regression models. The main finding in this study is that the subjects with HCV infection had a 60% increased risk after adjustment for potential confounders. Therefore, the finding implied that HCV infection may be associated with a higher pancreatic cancer risk but further studies are warranted to confirm the observed association. The point estimate in this study also suggested an excessive risk among subjects with HBV infection, however, without statistical significance due to a lack of study power. In Study II, we took advantage of the population-based prevalence study of oral mucosal lesions conducted in Uppsala County in central Sweden during 1973-74. The study population was followed through linkages with the Swedish population and health registers. A total of 19 924 participants were included in the final analysis, with 126 pancreatic cancer ascertained during an average of 28.7 years of follow-up. Among all tested indicators of poor oral hygiene, we found that fewer teeth at baseline appeared to increase pancreatic cancer risk, although the relative risk estimates were not statistically significant. Among the subjects with more than 10 teeth, subjects with unacceptable dental plaque had a doubled risk of pancreatic cancer compared with those without dental plaque after controlling for potential confounding factors. Subjects with Candida-related or denture-related oral mucosal lesions, or tongue lesions, compared with those without any of the three lesions, showed a 70%, 30% and 80% increased pancreatic cancer risk, respectively. In Study III, we carried out a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, including 448 pancreatic cancer cases and their individually matched control subjects. We measured serum antibodies against Helicobacter pylori (H. pylori) and pepsinogens I and II (markers for presence of chronic corpus atrophic gastritis) by enzyme-linked immunosorbent assays. Conditional logistic regression models were used to estimate odds ratios (ORs). Overall, our results demonstrated that pancreatic cancer risk was neither associated with H. pylori seropositivity nor CagA seropositivity. On the other hand, our findings showed that presence of chronic corpus atrophic gastritis was non-significantly associated with an increased pancreatic cancer risk. Although based on small numbers, the association was particularly prominent among individuals seronegative for both H. pylori and CagA (OR=5.66; 95% confidence interval: 1.59, 20.19; p value for interaction <0.01). In Study IV, we conducted a case-only study that sourced from a population-based case-control study of pancreatic cancer in Stockholm, Sweden. This study included patients with pancreatic ductal adenocarcinoma (PDAC) who underwent resection surgery between 2007 and 2012 (n=73). Patients were followed from diagnosis until death or the end of the study. We used an Anchored Multiplex Polymerase chain reaction (AMP)-based method for profiling variants in a panel of 65 selected genes. Our findings suggested that the AMP-based next-generation sequencing method can detect variants with allelic frequencies as low as 1% given sufficient sequencing depth. KRAS G12 mutations were completely confirmed by Sanger sequencing for high-allele-frequency samples (>5%), and also fully confirmed by allele-specific PCR and digital PCR for low-allele-frequency samples (1%-5%). The results demonstrated that KRAS mutant subtype G12V is related to a worse prognosis in PDAC patients, and transversion variants are more common among smokers. In conclusion, we found that HCV, as an infectious agent, may be associated with a higher pancreatic cancer risk. Our findings also support the hypothesis that poor oral hygiene plays a key role in the development of pancreatic cancer. On the other hand, we observed a null association between H. pylori infection and pancreatic cancer risk in the western European populations, but a suggested positive association between chronic corpus atrophic gastritis and pancreatic cancer risk based on a small sample size. Further studies are warranted to verify whether severe gastric atrophy contributes to pancreatic carcinogenesis. AMP-based next generation sequencing is a sensitive and accurate method for profiling tumor variants in PDAC. Future studies with larger sample sizes are needed to explore the role of tumor variants in PDAC prognosis and the impact of environmental risk factors on tumor mutational profile

Machine learning aided design and prediction of environmentally friendly rubberised concrete

Not only can waste rubber enhance the properties of concrete (e.g., its dynamic damping and abrasion resistance capacity), its rational utilisation can also dramatically reduce environmental pollution and carbon footprint globally. This study is the world’s first to develop a novel machine learning-aided design and prediction of environmentally friendly concrete using waste rubber, which can drive sustainable development of infrastructure systems towards net-zero emission, which saves time and cost. In this study, artificial neuron networks (ANN) have been established to determine the design relationship between various concrete mix composites and their multiple mechanical properties simultaneously. Interestingly, it is found that almost all previous studies on the ANNs could only predict one kind of mechanical property. To enable multiple mechanical property predictions, ANN models with various architectural algorithms, hidden neurons and layers are built and tailored for benchmarking in this study. Comprehensively, all three hundred and fifty-three experimental data sets of rubberised concrete available in the open literature have been collected. In this study, the mechanical properties in focus consist of the compressive strength at day 7 (CS7), the compressive strength at day 28 (CS28), the flexural strength (FS), the tensile strength (TS) and the elastic modulus (EM). The optimal ANN architecture has been identified by customising and benchmarking the algorithms (Levenberg–Marquardt (LM), Bayesian Regularisation (BR) and Scaled Conjugate Gradient (SCG)), hidden layers (1–2) and hidden neurons (1–30). The performance of the optimal ANN architecture has been assessed by employing the mean squared error (MSE) and the coefficient of determination (R2). In addition, the prediction accuracy of the optimal ANN model has ben compared with that of the multiple linear regression (MLR)

Subequivariant Graph Reinforcement Learning in 3D Environments

Learning a shared policy that guides the locomotion of different agents is of core interest in Reinforcement Learning (RL), which leads to the study of morphology-agnostic RL. However, existing benchmarks are highly restrictive in the choice of starting point and target point, constraining the movement of the agents within 2D space. In this work, we propose a novel setup for morphology-agnostic RL, dubbed Subequivariant Graph RL in 3D environments (3D-SGRL). Specifically, we first introduce a new set of more practical yet challenging benchmarks in 3D space that allows the agent to have full Degree-of-Freedoms to explore in arbitrary directions starting from arbitrary configurations. Moreover, to optimize the policy over the enlarged state-action space, we propose to inject geometric symmetry, i.e., subequivariance, into the modeling of the policy and Q-function such that the policy can generalize to all directions, improving exploration efficiency. This goal is achieved by a novel SubEquivariant Transformer (SET) that permits expressive message exchange. Finally, we evaluate the proposed method on the proposed benchmarks, where our method consistently and significantly outperforms existing approaches on single-task, multi-task, and zero-shot generalization scenarios. Extensive ablations are also conducted to verify our design. Code and videos are available on our project page: https://alpc91.github.io/SGRL/.Comment: ICML 2023 Ora