SEGMENTING NICHE GOAT-MEAT MARKETS

This research report provides an examination of the ratings of an important sensory attribute of chevon (goat meat) with that of beef and pork. Results from an analysis of variance of comparative ratings of the flavor of chevon and that of beef and pork suggest that selected demographic characteristics of U.S. consumers influenced the ratings of chevon'Â’s flavor with that of beef and pork. The findings indicate that Hispanics, blacks, and females should not be treated as homogenous niche markets. The results suggest that there are distinct subdivision preferences within and between these consumer partitions.Agribusiness,

Method to predict the minimum measurement and experiment durations needed to achieve converged and significant results in a wind energy field experiment

Experiments offer incredible value to science, but results must always come with an uncertainty quantification to be meaningful. This requires grappling with sources of uncertainty and how to reduce them. In wind energy, field experiments are sometimes conducted with a control and treatment. In this scenario uncertainty due to bias errors can often be neglected as they impact both control and treatment approximately equally. However, uncertainty due to random errors propagates such that the uncertainty in the difference between the control and treatment is always larger than the random uncertainty in the individual measurements if the sources are uncorrelated. As random uncertainties are usually reduced with additional measurements, there is a need to know the minimum duration of an experiment required to reach acceptable levels of uncertainty. We present a general method to simulate a proposed experiment, calculate uncertainties, and determine both the measurement duration and the experiment duration required to produce statistically significant and converged results. The method is then demonstrated as a case study with a virtual experiment that uses real-world wind resource data and several simulated tip extensions to parameterize results by the expected difference in power. With the method demonstrated herein, experiments can be better planned by accounting for specific details such as controller switching schedules, wind statistics, and postprocess binning procedures such that their impacts on uncertainty can be predicted and the measurement duration needed to achieve statistically significant and converged results can be determined before the experiment.</p

Procedural Memory Following Moderate-Severe Traumatic Brain Injury: Group Performance and Individual Differences on the Rotary Pursuit Task

The impact of traumatic brain injury (TBI) on procedural memory has received significantly less attention than declarative memory. Although to date studies on procedural memory have yielded mixed findings, many rehabilitation protocols (e.g., errorless learning) rely on the procedural memory system, and assume that it is relatively intact. The aim of the current study was to determine whether individuals with TBI are impaired on a task of procedural memory as a group, and to examine the presence of individual differences in performance. We administered to a sample of 36 individuals with moderate-severe TBI and 40 healthy comparisons (HCs) the rotary pursuit task, and then examined their rate of learning, as well as their retention of learning. Our analyses revealed that while individuals with TBI spent a significantly shorter amount of time on target as a group, they did not retain significantly less procedural learning, and as a group their rate of learning was not different from HCs. However, there were high individual differences in both groups, indicating that some individuals might not be able to take advantage of treatment methods designed to leverage intact procedural memory system. Future work is needed to better assess and characterize procedural memory in individuals with TBI across a larger battery of tasks in experimental and clinical setting as memory and learning status may predict rehabilitation success

Multiplierz: An Extensible API Based Desktop Environment for Proteomics Data Analysis

BACKGROUND. Efficient analysis of results from mass spectrometry-based proteomics experiments requires access to disparate data types, including native mass spectrometry files, output from algorithms that assign peptide sequence to MS/MS spectra, and annotation for proteins and pathways from various database sources. Moreover, proteomics technologies and experimental methods are not yet standardized; hence a high degree of flexibility is necessary for efficient support of high- and low-throughput data analytic tasks. Development of a desktop environment that is sufficiently robust for deployment in data analytic pipelines, and simultaneously supports customization for programmers and non-programmers alike, has proven to be a significant challenge. RESULTS. We describe multiplierz, a flexible and open-source desktop environment for comprehensive proteomics data analysis. We use this framework to expose a prototype version of our recently proposed common API (mzAPI) designed for direct access to proprietary mass spectrometry files. In addition to routine data analytic tasks, multiplierz supports generation of information rich, portable spreadsheet-based reports. Moreover, multiplierz is designed around a "zero infrastructure" philosophy, meaning that it can be deployed by end users with little or no system administration support. Finally, access to multiplierz functionality is provided via high-level Python scripts, resulting in a fully extensible data analytic environment for rapid development of custom algorithms and deployment of high-throughput data pipelines. CONCLUSION. Collectively, mzAPI and multiplierz facilitate a wide range of data analysis tasks, spanning technology development to biological annotation, for mass spectrometry-based proteomics research.Dana-Farber Cancer Institute; National Human Genome Research Institute (P50HG004233); National Science Foundation Integrative Graduate Education and Research Traineeship grant (DGE-0654108

Inter-similarity between coupled networks

Recent studies have shown that a system composed from several randomly interdependent networks is extremely vulnerable to random failure. However, real interdependent networks are usually not randomly interdependent, rather a pair of dependent nodes are coupled according to some regularity which we coin inter-similarity. For example, we study a system composed from an interdependent world wide port network and a world wide airport network and show that well connected ports tend to couple with well connected airports. We introduce two quantities for measuring the level of inter-similarity between networks (i) Inter degree-degree correlation (IDDC) (ii) Inter-clustering coefficient (ICC). We then show both by simulation models and by analyzing the port-airport system that as the networks become more inter-similar the system becomes significantly more robust to random failure.Comment: 4 pages, 3 figure

Microfluidic Platform for the Elastic Characterization of Mouse Submandibular Glands by Atomic Force Microscopy

The ability to characterize the microscale mechanical properties of biological materials has the potential for great utility in the field of tissue engineering. The development and morphogenesis of mammalian tissues are known to be guided in part by mechanical stimuli received from the local environment, and tissues frequently develop to match the physical characteristics (i.e., elasticity) of their environment. Quantification of these material properties at the microscale may provide valuable information to guide researchers. Presented here is a microfluidic platform for the non-destructive ex vivo microscale mechanical characterization of mammalian tissue samples by atomic force microscopy (AFM). The device was designed to physically hold a tissue sample in a dynamically controllable fluid environment while allowing access by an AFM probe operating in force spectroscopy mode to perform mechanical testing. Results of measurements performed on mouse submandibular gland samples demonstrate the ability of the analysis platform to quantify sample elasticity at the microscale, and observe chemically-induced changes in elasticity

Multidimensional Methods for the Formulation of Bipharmaceuticals and Vaccines

Determining and preserving the higher order structural integrity and conformational stability of proteins, plasmid DNA and macromolecular complexes such as viruses, virus-like particles and adjuvanted antigens is often a significant barrier to the successful stabilization and formulation of biopharmaceutical drugs and vaccines. These properties typically must be investigated with multiple lower resolution experimental methods, since each technique monitors only a narrow aspect of the overall conformational state of a macromolecular system. This review describes the use of empirical phase diagrams (EPDs) to combine large amounts of data from multiple high-throughput instruments and construct a map of a target macromolecule's physical state as a function of temperature, solvent conditions, and other stress variables. We present a tutorial on the mathematical methodology, an overview of some of the experimental methods typically used, and examples of some of the previous major formulation applications. We also explore novel applications of EPDs including potential new mathematical approaches as well as possible new biopharmaceutical applications such as analytical comparability, chemical stability, and protein dynamics

Cystic fibrosis-related diabetes is caused by islet loss and inflammation

Cystic fibrosis-related (CF-related) diabetes (CFRD) is an increasingly common and devastating comorbidity of CF, affecting approximately 35% of adults with CF. However, the underlying causes of CFRD are unclear. Here, we examined cystic fibrosis transmembrane conductance regulator (CFTR) islet expression and whether the CFTR participates in islet endocrine cell function using murine models of beta cell CFTR deletion and normal and CF human pancreas and islets. Specific deletion of CFTR from murine beta cells did not affect beta cell function. In human islets, CFTR mRNA was minimally expressed, and CFTR protein and electrical activity were not detected. Isolated CF/CFRD islets demonstrated appropriate insulin and glucagon secretion, with few changes in key islet-regulatory transcripts. Furthermore, approximately 65% of beta cell area was lost in CF donors, compounded by pancreatic remodeling and immune infiltration of the islet. These results indicate that CFRD is caused by beta cell loss and intraislet inflammation in the setting of a complex pleiotropic disease and not by intrinsic islet dysfunction from CFTR mutation