Food Safety Audits, Plant Characteristics, and Food Safety Technology Use in Meat and Poultry Plants

Food safety technology can increase a company’s capacity to prevent a foodborne contamination. A food safety audit—a quality control tool in which an auditor observes whether a plant’s processing practices and technologies are compatible with good food safety practices—can indicate how effectively food safety technology is being used. Fast food restaurants, grocery stores, and other major customers of meat and poultry processing plants conduct their own audits or hire auditors to assess the soundness of a plant’s processing operation. Meat and poultry plants can also audit themselves as a way to help maintain process control. In this report, we document the extent of food safety audits in meat and poultry processing plants. We also examine the associations between the use of audits and plant size, firm structure, and food safety technology use. Results show that larger plants, plants subject to food safety audits, and plants that are part of a multiplant firm use more food safety technology than other plants. Plants subject to both plant-hired and customer-hired audits had greater technology use than single (plant- or customer-hired) audit plants.Meat and poultry processing, safety standards, product recalls, food safety technology, food safety audits, Agribusiness, Food Consumption/Nutrition/Food Safety, Industrial Organization, Livestock Production/Industries,

Aperiodic tilings and entropy

In this paper we present a construction of Kari-Culik aperiodic tile set - the smallest known until now. With the help of this construction, we prove that this tileset has positive entropy. We also explain why this result was not expected

A Particular Universal Cellular Automaton

Signals are a classical tool used in cellular automata constructions that proved to be useful for language recognition or firing-squad synchronisation. Particles and collisions formalize this idea one step further, describing regular nets of colliding signals. In the present paper, we investigate the use of particles and collisions for constructions involving an infinite number of interacting particles. We obtain a high-level construction for a new smallest intrinsically universal cellular automaton with 4 states

A Simple n-Dimensional Intrinsically Universal Quantum Cellular Automaton

We describe a simple n-dimensional quantum cellular automaton (QCA) capable of simulating all others, in that the initial configuration and the forward evolution of any n-dimensional QCA can be encoded within the initial configuration of the intrinsically universal QCA. Several steps of the intrinsically universal QCA then correspond to one step of the simulated QCA. The simulation preserves the topology in the sense that each cell of the simulated QCA is encoded as a group of adjacent cells in the universal QCA.Comment: 13 pages, 7 figures. In Proceedings of the 4th International Conference on Language and Automata Theory and Applications (LATA 2010), Lecture Notes in Computer Science (LNCS). Journal version: arXiv:0907.382

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

The availability of nitrogen represents a key constraint on carbon cycling in terrestrial ecosystems, and it is largely in this capacity that the role of N in the Earth\u27s climate system has been considered. Despite this, few studies have included continuous variation in plant N status as a driver of broad-scale carbon cycle analyses. This is partly because of uncertainties in how leaf-level physiological relationships scale to whole ecosystems and because methods for regional to continental detection of plant N concentrations have yet to be developed. Here, we show that ecosystem CO2 uptake capacity in temperate and boreal forests scales directly with whole-canopy N concentrations, mirroring a leaf-level trend that has been observed for woody plants worldwide. We further show that both CO2 uptake capacity and canopy N concentration are strongly and positively correlated with shortwave surface albedo. These results suggest that N plays an additional, and overlooked, role in the climate system via its influence on vegetation reflectivity and shortwave surface energy exchange. We also demonstrate that much of the spatial variation in canopy N can be detected by using broad-band satellite sensors, offering a means through which these findings can be applied toward improved application of coupled carbon cycle–climate models

Soil respiration in a northeastern US temperate forest: a 22‐year synthesis

To better understand how forest management, phenology, vegetation type, and actual and simulated climatic change affect seasonal and inter‐annual variations in soil respiration (Rs), we analyzed more than 100,000 individual measurements of soil respiration from 23 studies conducted over 22 years at the Harvard Forest in Petersham, Massachusetts, USA. We also used 24 site‐years of eddy‐covariance measurements from two Harvard Forest sites to examine the relationship between soil and ecosystem respiration (Re). Rs was highly variable at all spatial (respiration collar to forest stand) and temporal (minutes to years) scales of measurement. The response of Rs to experimental manipulations mimicking aspects of global change or aimed at partitioning Rs into component fluxes ranged from −70% to +52%. The response appears to arise from variations in substrate availability induced by changes in the size of soil C pools and of belowground C fluxes or in environmental conditions. In some cases (e.g., logging, warming), the effect of experimental manipulations on Rs was transient, but in other cases the time series were not long enough to rule out long‐term changes in respiration rates. Inter‐annual variations in weather and phenology induced variation among annual Rs estimates of a magnitude similar to that of other drivers of global change (i.e., invasive insects, forest management practices, N deposition). At both eddy‐covariance sites, aboveground respiration dominated Re early in the growing season, whereas belowground respiration dominated later. Unusual aboveground respiration patterns—high apparent rates of respiration during winter and very low rates in mid‐to‐late summer—at the Environmental Measurement Site suggest either bias in Rs and Re estimates caused by differences in the spatial scale of processes influencing fluxes, or that additional research on the hard‐to‐measure fluxes (e.g., wintertime Rs, unaccounted losses of CO2 from eddy covariance sites), daytime and nighttime canopy respiration and its impacts on estimates of Re, and independent measurements of flux partitioning (e.g., aboveground plant respiration, isotopic partitioning) may yield insight into the unusually high and low fluxes. Overall, however, this data‐rich analysis identifies important seasonal and experimental variations in Rs and Re and in the partitioning of Re above‐ vs. belowground

Soil Respiration in a Northeastern US Temperate Forest: A 22-Year Synthesis

To better understand how forest management, phenology, vegetation type, and actual and simulated climatic change affect seasonal and inter-annual variations in soil respiration (R$_{s}$), we analyzed more than 100,000 individual measurements of soil respiration from 23 studies conducted over 22 years at the Harvard Forest in Petersham, Massachusetts, USA. We also used 24 site-years of eddy-covariance measurements from two Harvard Forest sites to examine the relationship between soil and ecosystem respiration (R$_{e}$). R$_{s}$ was highly variable at all spatial (respiration collar to forest stand) and temporal (minutes to years) scales of measurement. The response of R$_{s}$ to experimental manipulations mimicking aspects of global change or aimed at partitioning R$_{s}$ into component fluxes ranged from −70% to +52%. The response appears to arise from variations in substrate availability induced by changes in the size of soil C pools and of belowground C fluxes or in environmental conditions. In some cases (e.g., logging, warming), the effect of experimental manipulations on R$_{s}$ was transient, but in other cases the time series were not long enough to rule out long-term changes in respiration rates. Inter-annual variations in weather and phenology induced variation among annual R$_{s}$ estimates of a magnitude similar to that of other drivers of global change (i.e., invasive insects, forest management practices, N deposition). At both eddy-covariance sites, aboveground respiration dominated R$_{e}$ early in the growing season, whereas belowground respiration dominated later. Unusual aboveground respiration patterns—high apparent rates of respiration during winter and very low rates in mid-to-late summer—at the Environmental Measurement Site suggest either bias in R$_{s}$ and R$_{e}$ estimates caused by differences in the spatial scale of processes influencing fluxes, or that additional research on the hard-to-measure fluxes (e.g., wintertime R$_{s}$, unaccounted losses of CO$_{2}$ from eddy covariance sites), daytime and nighttime canopy respiration and its impacts on estimates of R$_{e}$, and independent measurements of flux partitioning (e.g., aboveground plant respiration, isotopic partitioning) may yield insight into the unusually high and low fluxes. Overall, however, this data-rich analysis identifies important seasonal and experimental variations in R$_{s}$ and R$_{e}$ and in the partitioning of R$_{e}$ above- vs. belowground.Organismic and Evolutionary Biolog

Universal Rights and Wrongs

This paper argues for the important role of customers as a source of competitive advantage and firm growth, an issue which has been largely neglected in the resource-based view of the firm. It conceptualizes Penrose’s (1959) notion of an ‘inside track’ and illustrates how in-depth knowledge about established customers combines with joint problem-solving activities and the rapid assimilation of new and previously unexploited skills and resources. It is suggested that the inside track represents a distinct and perhaps underestimated way of generating rents and securing long-term growth. This also implies that the sources of sustainable competitive advantage in important respects can be sought in idiosyncratic interfirm relationships rather than within the firm itself

Automatic Physiological Waveform Processing for fMRI Noise Correction and Analysis

Functional MRI resting state and connectivity studies of brain focus on neural fluctuations at low frequencies which share power with physiological fluctuations originating from lung and heart. Due to the lack of automated software to process physiological signals collected at high magnetic fields, a gap exists in the processing pathway between the acquisition of physiological data and its use in fMRI software for both physiological noise correction and functional analyses of brain activation and connectivity. To fill this gap, we developed an open source, physiological signal processing program, called PhysioNoise, in the python language. We tested its automated processing algorithms and dynamic signal visualization on resting monkey cardiac and respiratory waveforms. PhysioNoise consistently identifies physiological fluctuations for fMRI noise correction and also generates covariates for subsequent analyses of brain activation and connectivity