Semiempirical down-scaling of GCM output to the local scale for temperature, precipitation, and runoff

EXTRACT (SEE PDF FOR FULL ABSTRACT): An empirically derived multiple linear regression model is used to relate a local-scale dependent variable (either temperature, precipitation, or surface runoff) measured at individual gauging stations to six large-scale independent variables (temperature, precipitation, surface runoff, height to the 500-mbar pressure surface, and the zonal and meridional gradient across this surface). ...The area investigated is the western United States. ... The calibration data set is from 1948 through 1988 and includes data from 268 joint temperature and precipitation stations, 152 streamflow stations (which are converted to runoff data), and 24 gridded 500-mbar pressure height nodes.

Fixed-rank matrix factorizations and Riemannian low-rank optimization

Motivated by the problem of learning a linear regression model whose parameter is a large fixed-rank non-symmetric matrix, we consider the optimization of a smooth cost function defined on the set of fixed-rank matrices. We adopt the geometric framework of optimization on Riemannian quotient manifolds. We study the underlying geometries of several well-known fixed-rank matrix factorizations and then exploit the Riemannian quotient geometry of the search space in the design of a class of gradient descent and trust-region algorithms. The proposed algorithms generalize our previous results on fixed-rank symmetric positive semidefinite matrices, apply to a broad range of applications, scale to high-dimensional problems, and confer a geometric basis to recent contributions on the learning of fixed-rank non-symmetric matrices. We make connections with existing algorithms in the context of low-rank matrix completion and discuss the usefulness of the proposed framework. Numerical experiments suggest that the proposed algorithms compete with state-of-the-art algorithms and that manifold optimization offers an effective and versatile framework for the design of machine learning algorithms that learn a fixed-rank matrix. © 2013 Springer-Verlag Berlin Heidelberg.

中国水蚀土壤抗剪强度研究

利用野外测试数据、土壤样品的室内理化分析数据和参考文献数据 ,对水蚀区范围内水土流失过程中的土壤抗剪强度进行了初步研究 ,建立了中国水土流失土壤抗剪强度的回归模型 ,总结出水蚀区范围内水蚀过程中有关土壤抗剪强度的 3条结论 :影响水土流失过程中土壤抗剪强度的主导因素是容重、粉 /黏、土壤含水量、土壤有机质含量 ;抗剪强度随土壤类型发生有规律的变化 ;抗剪强度在中国水蚀区范围内有较明显的空间分异规律 (包括水平分异规律和垂直剖面构型规律 )

A field study on the conversion ratio of phytoplankton biomass carbon to chlorophyll-a in Jiaozhou Bay, China

A one-year field study was conducted to determine the conversion ratio of phytoplankton biomass carbon (Phyto-C) to chlorophyll-a (Chl-a) in Jiaozhou Bay, China. We measured suspended particulate organic carbon (POC) and phytoplankton Chl-a samples collected in surface water monthly from March 2005 to February 2006. The temporal and spatial variations of Chl-a and POC concentrations were observed in the bay. Based on the field measurements, a linear regression model II was used to generate the conversion ratio of Phyto-C to Chl-a. In most cases, a good linear correlation was found between the observed POC and Chl-a concentrations, and the calculated conversion ratios ranged from 26 to 250 with a mean value of 56 A mu g A mu g(-1). The conversion ratio in the fall was higher than that in the winter and spring months, and had the lowest values in the summer. The ratios also exhibited spatial variations, generally with low values in the near shore regions and relatively high values in offshore waters. Our study suggests that temperature was likely to be the main factor influencing the observed seasonal variations of conversion ratios while nutrient supply and light penetration played important roles in controlling the spatial variations.

装配系统中缓冲区容量的研究

为了确定装配系统中的缓冲区容量,在建立缓冲区状态数学模型的基础上,根据随机过程的原理,提出了缓冲区被充满概率和缓冲区容量之间的函数关系。以缓冲区被充满概率最小化为目标,确定合理的缓冲区容量。最后给出一种递进算法,通过回归方程计算缓冲区对装配工位生产率的影响,逐步求出由多个工位组成的整个装配系统各个工位之间的缓冲区容量。

地理信息系统支持下的滑坡灾害空间分析预测-以云南小江流域为例

As a typical geological and environmental hazard, landslide has been causing more and more property and life losses. However, to predict its accurate occurring time is very difficult or even impossible due to landslide's complex nature. It has been realized that it is not a good solution to spend a lot of money to treat with and prevent landslide. The research trend is to study landslide's spatial distribution and predict its potential hazard zone under certain region and certain conditions. GIS(Geographical Information System) is a power tools for data management, spatial analysis based on reasonable spatial models and visualization. It is new and potential study field to do landslide hazard analysis and prediction based on GIS. This paper systematically studies the theory and methods for GIS based landslide hazard analysis. On the basis of project "Mountainous hazard study-landslide and debris flows" supported by Chinese Academy of Sciences and the former study foundation, this paper carries out model research, application, verification and model result analysis. The occurrence of landslide has its triggering factors. Landslide has its special landform and topographical feature which can be identify from field work and remote sensing image (aerial photo). Historical record of landslide is the key to predict the future behaviors of landslide. These are bases for landslide spatial data base construction. Based on the plenty of literatures reviews, the concept framework of model integration and unit combinations is formed. Two types of model, CF multiple regression model and landslide stability and hydrological distribution coupled model are bought forward. CF multiple regression model comes form statistics and possibility theory based on data. Data itself contains the uncertainty and random nature of landslide hazard, so it can be seen as a good method to study and understand landslide's complex feature and mechanics. CF multiple regression model integrates CF (landslide Certainty Factor) and multiple regression prediction model. CF can easily treat with the problems of data quantifying and combination of heteroecious data types. The combination of CF can assist to determine key landslide triggering factors which are then inputted into multiple regression model. CF regression model can provide better prediction results than traditional model. The process of landslide can be described and modeled by suitable physical and mechanical model. Landslide stability and hydrological distribution coupled model is such a physical deterministic model that can be easily used for landslide hazard analysis and prediction. It couples the general limit equilibrium method and hydrological distribution model based on DEM, and can be used as a effective approach to predict the occurrence of landslide under different precipitation conditions as well as landslide mechanics research. It can not only explain pre-existed landslides, but also predict the potential hazard region with environmental conditions changes. Finally, this paper carries out landslide hazard analysis and prediction in Yunnan Xiaojiang watershed, including landslide hazard sensitivity analysis and regression prediction model based on selected key factors, determining the relationship between landslide occurrence possibility and triggering factors. The result of landslide hazard analysis and prediction by coupled model is discussed in details. On the basis of model verification and validation, the modeling results are showing high accuracy and good applying potential in landslide research.

Prediction of soil adsorption coefficients from retention parameters on three reversed-phase liquid chromatographic columns

Reversed-phase high-performance liquid chromatographic (RP-HPLC) retention parameters, which are determined by the intermolecular interactions in retention process, can be considered as the chemical molecular descriptors in linear free energy relationships (LFERs). On the basis of the characterization and comparison of octadecyl-bonded silica gel (ODS), cyano-bonded silica gel (CN), and phenyl-bonded silica gel (Ph) columns with linear solvation energy relationships (LSERs), a new multiple linear regression model using RP-HPLC retention parameters on ODS and CN columns as variables for estimation of soil adsorption coefficients was developed. It was tested on a set of reference substances from various chemical classes. The results showed that the multicolumn method was more promising than a single-column method was for the estimation of soil adsorption coefficients. The accuracy of the suggested model is identical with that of LSERs.

对癌症生存者应对资源的研究

A survey study of cancer survivors was conducted to explore the coping resources, which buffers the life of cancer survivors against stressful situation. Participants reported coping strategies, positive affect and negative affect, personality, perceived social support, fighting spirit and helpless/hopeless as well as quality of life through a set of self-assessment questionnaire. The results indicated that the frequency of coping strategies used by cancer survivors from high to low were: growing, problem solving, seeking support,self-controlling, wishful thinking, and distancing. The correlational analysis indicated that among the six sets of coping strategies, growing was positively correlated most strongly with most of the dimensions in quality of life as well as positive affect. Among the five personality, Neuroticism was positively correlated most strongly with helpless/hopeless and negative affect; and was negatively correlated most strongly with fighting spirit and positive affect. Extraversion was positively correlated most strongly with positive affect and negatively correlated most strongly with helpless/hopeless; Agreeableness was negatively correlated most strongly with negative affect; Conscientiousness was positively correlated most strongly with fighting spirit. Subjects with higher score in quality of life reported higher frequency of coping strategies in growing and problem solving and less in wishful thinking. They also reported higher scores in Extraversion, Agreeableness, Conscientiousness as well as lower scores in Neuroticism. The regression analysis displayed that not negative affect but positive affect entered the regression model when all the psychological and social variables in the study were accounted for. Taken together, these data suggested that, growing was the most effective coping strategy among the six sets of strategies for cancer survivors to improve quality of life, to maintain positive affect and to enhance fighting spirit. Neuroticism was vulnerable to resist stressors; Extraversion, Agreeableness, and Conscientiousness were stress-resisted factors. Positive affect may has more adaptational significance than negative affect during chronic stress. These data also implicated that positive affect should be paid more attention to in coping research.

Prevalence of overweight and obesity among nurses in Scotland: A cross-sectional study using the Scottish Health Survey.

Background Increasing prevalence of overweight and obesity represents a global pandemic. As the largest occupational group in international healthcare systems nurses are at the forefront of health promotion to address this pandemic. However, nurses own health behaviours are known to influence the extent to which they engage in health promotion and the public's confidence in advice offered. Estimating the prevalence of overweight and obesity among nurses is therefore important. However, to date, prevalence estimates have been based on non-representative samples and internationally no studies have compared prevalence of overweight and obesity among nurses to other healthcare professionals using representative data. Objectives To estimate overweight and obesity prevalence among nurses in Scotland, and compare to other healthcare professionals and those working in non-heath related occupations. Design Cross-sectional study using a nationally representative sample of five aggregated annual rounds (2008-2012) of the Scottish Health Survey. Setting Scotland. Participants: 13,483 adults aged 17 to 65 indicating they had worked in the past 4 weeks, classified in four occupational groups: nurses (n = 411), other healthcare professionals (n = 320), unqualified care staff (n = 685), and individuals employed in non-health related occupations (n = 12,067). Main outcome measures: Prevalence of overweight and obesity defined as Body Mass Index ≥ 25.0. Methods Estimates of overweight and obesity prevalence in each occupational group were calculated with 95% confidence intervals (CI). A logistic regression model was then built to compare the odds of being overweight or obese with not being overweight or obese for nurses in comparison to the other occupational categories. Data were analysed using SAS 9.1.3. Results 69.1% (95% CI 64.6,73.6) of Scottish nurses were overweight or obese. Prevalence of overweight and obesity was higher in nurses than other healthcare professionals (51.3%, CI 45.8,56.7), unqualified care staff (68.5%, CI 65.0,72.0) and those in non-health related occupations (68.9%, CI 68.1,69.7). A logistic regression model adjusted for socio-demographic composition indicated that, compared to nurses, the odds of being overweight or obese was statistically significantly lower for other healthcare professionals (Odds Ratio [OR] 0.45, CI 0.33,0.61) and those in non-health related occupations (OR 0.78, CI 0.62,0.97). Conclusions Prevalence of overweight and obesity among Scottish nurses is worryingly high, and significantly higher than those in other healthcare professionals and non-health related occupations. High prevalence of overweight and obesity potentially harms nurses’ own health and hampers the effectiveness of nurses’ health promotion role. Interventions are therefore urgently required to address overweight and obesity among the Scottish nursing workforce.

Human papillomavirus detection in women with and without human immunodeficiency virus infection in Colombia

Background: HIV infection leads to a decreasing immune response, thereby facilitating the appearance of other infections, one of the most important ones being HPV. However, studies are needed for determining associations between immunodeficiency caused by HIV and/or the presence of HPV during the course of cervical lesions and their degree of malignancy. This study describes the cytological findings revealed by the Papanicolaou test, laboratory characteristics and HPV molecular profile in women with and without HIV infection. Methods: A total of 216 HIV-positive and 1,159 HIV-negative women were invited to participate in the study; PCR was used for the molecular detection of HPV in cervical samples. Statistical analysis (such as percentages, Chi-square test and Fisher's exact test when applicable) determined human papillomavirus (HPV) infection frequency (single and multiple) and the distribution of six types of high-risk-HPV in women with and without HIV infection. Likewise, a logistic regression model was run to evaluate the relationship between HIV-HPV infection and different risk factors. Results: An association was found between the frequency of HPV infection and infection involving 2 or more HPV types (also known as multiple HPV infection) in HIV-positive women (69.0% and 54.2%, respectively); such frequency was greater than that found in HIV-negative women (44.3% and 22.7%, respectively). Statistically significant differences were observed between both groups (p = 0.001) regarding HPV presence (both in infection and multiple HPV infection). HPV-16 was the most prevalent type in the population being studied (p = 0.001); other viral types had variable distribution in both groups (HIV-positive and HIV-negative). HPV detection was associated with <500 cell/mm(3) CD4-count (p = 0.004) and higher HIV-viral-load (p = 0.001). HPV-DNA detection, <200 cell/mm(3) CD4-count (p = 0.001), and higher HIV-viral-load (p = 0.001) were associated with abnormal cytological findings. Conclusions: The HIV-1 positive population in this study had high multiple HPV infection prevalence. The results for this population group also suggested a greater association between HPV-DNA presence and cytological findings. HPV detection, together with low CD4 count, could represent useful tools for identifying HIV-positive women at risk of developing cervical lesions.

Baseline health-related quality-of-life data as prognostic factors in a phase III multicentre study of women with metastatic breast cancer.

The potential value of baseline health-related quality-of-life (HRQOL) and clinical factors in predicting prognosis was examined using data from an international randomised phase III trial which compared doxorubicin and paclitaxel with doxorubicin and cylophosphamide as first line chemotherapy in 275 women with metastatic breast cancer. The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 and the related breast module (QLQ-BR23) were used to assess baseline HRQOL data. The Cox proportional-hazards regression model was used for both univariate and multivariate analyses of survival. In the univariate analyses, performance status (P<0.001) and number of sites involved (P=0.001) were the most important clinical prognostic factors. The HRQOL variables at baseline most strongly associated with longer survival were better appetite, physical and role functioning, as well as less fatigue (P<0.001). The final multivariate model retained performance status (P<0.001) and appetite loss (P=0.005) as the variables best predicting survival. Substantial loss of appetite was the only independent HRQOL factor predicting poor survival and was strongly correlated (/r/>0.5) with fatigue, role and physical functioning. In addition to known clinical factors, appetite loss appears to be a significant prognostic factor for survival in women with metastatic breast cancer. However, the mechanism underlying this association remains to be precisely defined in future studies.

Aging African American Women and the Impact of Positive Psychological Factors on Quality of Life

Aging African-American women are disproportionately affected by negative health outcomes and mortality. Life stress has strong associations with these health outcomes. The purpose of this research was to understand how aging African American women manage stress. Specifically, the effects of coping, optimism, resilience, and religiousness as it relates to quality of life were examined. This cross-sectional exploratory study used a self-administered questionnaire and examined quality of life in 182 African-American women who were 65 years of age or older living in senior residential centers in Baltimore using convenience sampling. The age range for these women was 65 to 94 years with a mean of 71.8 years (SD = 5.6). The majority (53.1%) of participants completed high school, with 23 percent (N = 42) obtaining college degrees and 19 percent (N = 35) holding advanced degrees. Nearly 58 percent of participants were widowed and 81 percent were retired. In addition to demographics, the questionnaire included the following reliable and valid survey instruments: The Brief Cope Scale (Carver, Scheier, & Weintraub, 1989), Optimism Questionnaire (Scheier, Carver, & Bridges, 1994), Resilience Survey (Wagnild & Young, 1987), Religiousness Assessment (Koenig, 1997), and Quality of Life Questionnaire (Cummins, 1996). Results revealed that the positive psychological factors examined were positively associated with and significant predictors of quality of life. The bivariate correlations indicated that of the six coping dimensions measured in this study, planning (r=.68) was the most positively associated with quality of life. Optimism (r=.33), resilience (=.48), and religiousness (r=.30) were also significantly correlated with quality of life. In the linear regression model, again the coping dimension of planning was the best predictor of quality of life (beta = .75, p <.001). Optimism (beta = .31, p <.001), resilience (beta = .34, p, .001) and religiousness (beta = .17, p <.01) were also significant predictors of quality of life. It appears as if positive psychology plays an important role in improving quality of life among aging African-American women.

Gender differences in the risk of HIV infection among persons reporting abstinence, monogamy, and multiple sexual partners in northern Tanzania.

BACKGROUND: Monogamy, together with abstinence, partner reduction, and condom use, is widely advocated as a key behavioral strategy to prevent HIV infection in sub-Saharan Africa. We examined the association between the number of sexual partners and the risk of HIV seropositivity among men and women presenting for HIV voluntary counseling and testing (VCT) in northern Tanzania. METHODOLOGY/ PRINCIPAL FINDINGS: Clients presenting for HIV VCT at a community-based AIDS service organization in Moshi, Tanzania were surveyed between November 2003 and December 2007. Data on sociodemographic characteristics, reasons for testing, sexual behaviors, and symptoms were collected. Men and women were categorized by number of lifetime sexual partners, and rates of seropositivity were reported by category. Factors associated with HIV seropositivity among monogamous males and females were identified by a multivariate logistic regression model. Of 6,549 clients, 3,607 (55%) were female, and the median age was 30 years (IQR 24-40). 939 (25%) females and 293 (10%) males (p<0.0001) were HIV seropositive. Among 1,244 (34%) monogamous females and 423 (14%) monogamous males, the risk of HIV infection was 19% and 4%, respectively (p<0.0001). The risk increased monotonically with additional partners up to 45% (p<0.001) and 15% (p<0.001) for women and men, respectively with 5 or more partners. In multivariate analysis, HIV seropositivity among monogamous women was most strongly associated with age (p<0.0001), lower education (p<0.004), and reporting a partner with other partners (p = 0.015). Only age was a significant risk factor for monogamous men (p = 0.0004). INTERPRETATION: Among women presenting for VCT, the number of partners is strongly associated with rates of seropositivity; however, even women reporting lifetime monogamy have a high risk for HIV infection. Partner reduction should be coupled with efforts to place tools in the hands of sexually active women to reduce their risk of contracting HIV.

Bacteria localization and chorion thinning among preterm premature rupture of membranes.

OBJECTIVE: Bacterial colonization of the fetal membranes and its role in pathogenesis of membrane rupture is poorly understood. Prior retrospective work revealed chorion layer thinning in preterm premature rupture of membranes (PPROM) subjects. Our objective was to prospectively examine fetal membrane chorion thinning and to correlate to bacterial presence in PPROM, preterm, and term subjects. STUDY DESIGN: Paired membrane samples (membrane rupture and membrane distant) were prospectively collected from: PPROM = 14, preterm labor (PTL = 8), preterm no labor (PTNL = 8), term labor (TL = 10), and term no labor (TNL = 8), subjects. Sections were probed with cytokeratin to identify fetal trophoblast layer of the chorion using immunohistochemistry. Fluorescence in situ hybridization was performed using broad range 16 s ribosomal RNA probe. Images were evaluated, chorion and choriodecidua were measured, and bacterial fluorescence scored. Chorion thinning and bacterial presence were compared among and between groups using Student's t-test, linear mixed effect model, and Poisson regression model (SAS Cary, NC). RESULTS: In all groups, the fetal chorion cellular layer was thinner at rupture compared to distant site (147.2 vs. 253.7 µm, p<0.0001). Further, chorion thinning was greatest among PPROM subjects compared to all other groups combined, regardless of site sampled [PPROM(114.9) vs. PTL(246.0) vs. PTNL(200.8) vs. TL(217.9) vs. TNL(246.5)]. Bacteria counts were highest among PPROM subjects compared to all other groups regardless of site sampled or histologic infection [PPROM(31) vs. PTL(9) vs. PTNL(7) vs. TL(7) vs. TNL(6)]. Among all subjects at both sites, bacterial counts were inversely correlated with chorion thinning, even excluding histologic chorioamnionitis (p<0.0001 and p = 0.05). CONCLUSIONS: Fetal chorion was uniformly thinner at rupture site compared to distant sites. In PPROM fetal chorion, we demonstrated pronounced global thinning. Although cause or consequence is uncertain, bacterial presence is greatest and inversely correlated with chorion thinning among PPROM subjects.

Antisense Gene Silencing and Bacteriophages as Novel Disinfection Processes for Engineered Systems

The growth and proliferation of invasive bacteria in engineered systems is an ongoing problem. While there are a variety of physical and chemical processes to remove and inactivate bacterial pathogens, there are many situations in which these tools are no longer effective or appropriate for the treatment of a microbial target. For example, certain strains of bacteria are becoming resistant to commonly used disinfectants, such as chlorine and UV. Additionally, the overuse of antibiotics has contributed to the spread of antibiotic resistance, and there is concern that wastewater treatment processes are contributing to the spread of antibiotic resistant bacteria.

Due to the continually evolving nature of bacteria, it is difficult to develop methods for universal bacterial control in a wide range of engineered systems, as many of our treatment processes are static in nature. Still, invasive bacteria are present in many natural and engineered systems, where the application of broad acting disinfectants is impractical, because their use may inhibit the original desired bioprocesses. Therefore, to better control the growth of treatment resistant bacteria and to address limitations with the current disinfection processes, novel tools that are both specific and adaptable need to be developed and characterized.

In this dissertation, two possible biological disinfection processes were investigated for use in controlling invasive bacteria in engineered systems. First, antisense gene silencing, which is the specific use of oligonucleotides to silence gene expression, was investigated. This work was followed by the investigation of bacteriophages (phages), which are viruses that are specific to bacteria, in engineered systems.


For the antisense gene silencing work, a computational approach was used to quantify the number of off-targets and to determine the effects of off-targets in prokaryotic organisms. For the organisms of Escherichia coli K-12 MG1655 and Mycobacterium tuberculosis H37Rv the mean number of off-targets was found to be 15.0 + 13.2 and 38.2 + 61.4, respectively, which results in a reduction of greater than 90% of the effective oligonucleotide concentration. It was also demonstrated that there was a high variability in the number of off-targets over the length of a gene, but that on average, there was no general gene location that could be targeted to reduce off-targets. Therefore, this analysis needs to be performed for each gene in question. It was also demonstrated that the thermodynamic binding energy between the oligonucleotide and the mRNA accounted for 83% of the variation in the silencing efficiency, compared to the number of off-targets, which explained 43% of the variance of the silencing efficiency. This suggests that optimizing thermodynamic parameters must be prioritized over minimizing the number of off-targets. In conclusion for the antisense work, these results suggest that off-target hybrids can account for a greater than 90% reduction in the concentration of the silencing oligonucleotides, and that the effective concentration can be increased through the rational design of silencing targets by minimizing off-target hybrids.

Regarding the work with phages, the disinfection rates of bacteria in the presence of phages was determined. The disinfection rates of E. coli K12 MG1655 in the presence of coliphage Ec2 ranged up to 2 h-1, and were dependent on both the initial phage and bacterial concentrations. Increasing initial phage concentrations resulted in increasing disinfection rates, and generally, increasing initial bacterial concentrations resulted in increasing disinfection rates. However, disinfection rates were found to plateau at higher bacterial and phage concentrations. A multiple linear regression model was used to predict the disinfection rates as a function of the initial phage and bacterial concentrations, and this model was able to explain 93% of the variance in the disinfection rates. The disinfection rates were also modeled with a particle aggregation model. The results from these model simulations suggested that at lower phage and bacterial concentrations there are not enough collisions to support active disinfection rates, which therefore, limits the conditions and systems where phage based bacterial disinfection is possible. Additionally, the particle aggregation model over predicted the disinfection rates at higher phage and bacterial concentrations of 108 PFU/mL and 108 CFU/mL, suggesting other interactions were occurring at these higher concentrations. Overall, this work highlights the need for the development of alternative models to more accurately describe the dynamics of this system at a variety of phage and bacterial concentrations. Finally, the minimum required hydraulic residence time was calculated for a continuous stirred-tank reactor and a plug flow reactor (PFR) as a function of both the initial phage and bacterial concentrations, which suggested that phage treatment in a PFR is theoretically possible.

In addition to determining disinfection rates, the long-term bacterial growth inhibition potential was determined for a variety of phages with both Gram-negative and Gram-positive bacteria. It was determined, that on average, phages can be used to inhibit bacterial growth for up to 24 h, and that this effect was concentration dependent for various phages at specific time points. Additionally, it was found that a phage cocktail was no more effective at inhibiting bacterial growth over the long-term than the best performing phage in isolation.

Finally, for an industrial application, the use of phages to inhibit invasive Lactobacilli in ethanol fermentations was investigated. It was demonstrated that phage 8014-B2 can achieve a greater than 3-log inactivation of Lactobacillus plantarum during a 48 h fermentation. Additionally, it was shown that phages can be used to protect final product yields and maintain yeast viability. Through modeling the fermentation system with differential equations it was determined that there was a 10 h window in the beginning of the fermentation run, where the addition of phages can be used to protect final product yields, and after 20 h no additional benefit of the phage addition was observed.

In conclusion, this dissertation improved the current methods for designing antisense gene silencing targets for prokaryotic organisms, and characterized phages from an engineering perspective. First, the current design strategy for antisense targets in prokaryotic organisms was improved through the development of an algorithm that minimized the number of off-targets. For the phage work, a framework was developed to predict the disinfection rates in terms of the initial phage and bacterial concentrations. In addition, the long-term bacterial growth inhibition potential of multiple phages was determined for several bacteria. In regard to the phage application, phages were shown to protect both final product yields and yeast concentrations during fermentation. Taken together, this work suggests that the rational design of phage treatment is possible and further work is needed to expand on this foundation.