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The book summarizes the latest research and developments in dairy
biotechnology and engineering. It provides a strategic approach for
readers relating to fundamental research and practical work with
lactic acid bacteria. The book covers every aspect from
identification, ecology, taxonomy and industrial use. All
contributors are experts who have substantial experience in the
corresponding research field. The book is intended for researchers
in the human, animal, and food sciences related to lactic acid
bacteria. Dr. Heping Zhang is a Professor at the Key Laboratory of
Dairy Biotechnology and Engineering Ministry of Education, Inner
Mongolia Agricultural University, China. Dr. Yimin Cai works in
Livestock and Environment Division, Japan International Research
Center for Agricultural Sciences (JIRCAS), Japan.
The book summarizes the latest research and developments in dairy
biotechnology and engineering. It provides a strategic approach for
readers relating to fundamental research and practical work with
lactic acid bacteria. The book covers every aspect from
identification, ecology, taxonomy and industrial use. All
contributors are experts who have substantial experience in the
corresponding research field. The book is intended for researchers
in the human, animal, and food sciences related to lactic acid
bacteria. Dr. Heping Zhang is a Professor at the Key Laboratory of
Dairy Biotechnology and Engineering Ministry of Education, Inner
Mongolia Agricultural University, China. Dr. Yimin Cai works in
Livestock and Environment Division, Japan International Research
Center for Agricultural Sciences (JIRCAS), Japan.
Multiple complex pathways, characterized by interrelated events and
c- ditions, represent routes to many illnesses, diseases, and
ultimately death. Although there are substantial data and
plausibility arguments suppo- ing many conditions as contributory
components of pathways to illness and disease end points, we have,
historically, lacked an e?ective method- ogy for identifying the
structure of the full pathways. Regression methods, with strong
linearity assumptions and data-basedconstraints onthe extent and
order of interaction terms, have traditionally been the strategies
of choice for relating outcomes to potentially complex explanatory
pathways. However, nonlinear relationships among candidate
explanatory variables are a generic feature that must be dealt with
in any characterization of how health outcomes come about. It is
noteworthy that similar challenges arise from data analyses in
Economics, Finance, Engineering, etc. Thus, the purpose of this
book is to demonstrate the e?ectiveness of a relatively recently
developed methodology-recursive partitioning-as a response to this
challenge. We also compare and contrast what is learned via rec-
sive partitioning with results obtained on the same data sets using
more traditional methods. This serves to highlight exactly
where-and for what kinds of questions-recursive partitioning-based
strategies have a decisive advantage over classical regression
techniques.
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