Clostridium Perfringens Growth from Spore Inocula in Sous-Vide Processed Pork-Based Mexican Entrée

ABSTRACT:  The combined effect of Citricidal® wih irradiation on Clostridium perfringens growth from spores in a sous-vide processed marinated pork meat Mexican entrée was investigated. Citricidal was added at 200 or 800 ppm after mixing pork meat with tomatillo sauce and inoculated with 3 log₁₀ CFU/g of C. perfringens spores. Samples were irradiated at either 0 or 2 kGy, heated to an internal temperature of 71 °C, and stored at 4 °C for 28 d, 15 °C for 45 d, and 25 °C for 26 h. To simulate the conditions that may occur during transportation, distribution, storage, or handling in supermarkets or by consumers, the effect of static temperature abuse on C. perfringens growth was assessed by transferring samples stored at 4 to 25 °C for 13 and 15 h. Total C. perfringens populations were determined by plating diluted samples on tryptose-sulfite-cycloserine agar. Growth was not observed up to 45 d of storage at 15 °C in samples supplemented with 800 ppm of Citricidal. At 25 °C, no significant differences ( P > 0.05) on the lag phase duration due to antimicrobial treatments was observed. The temperature abuse of refrigerated products for up to 15 h did not lead to C. perfringens growth to high infective dose levels of 1 million cells required to cause food poisoning. The results suggest that 800 ppm Citricidal can have significant bacteriostatic activity against C. perfringens and may provide a degree of protection against this pathogen in sous-vide processed marinated pork meat Mexican entrée, under mild temperature abuse (≤ 15 °C) conditions.     

A study of graphics hardware accelerated particle swarm optimization with digital pheromones

Programmable Graphics Processing Units (GPUs) have lately become a promising means to perform scientific computations. Modern GPUs have proven to outperform the number of floating point operations when compared to traditional Central Processing Units (CPUs) through inherent data parallel architecture and higher bandwidth capabilities. They allow scientific computations to be performed without noticeable degradation in accuracy in a fraction of the time compared to traditional CPUs at substantially reduced costs, making them viable alternatives to expensive computer clusters or workstations. GPU programmability however, has fostered the development of a variety of programming languages making it challenging to select a computing language and use it consistently without the pitfall of being obsolete. Some GPU languages are hardware specific and are designed to rake in performance boosts when used with their host GPUs (e.g., Nvidia Cuda). Others are operating system specific (e.g., Microsoft HLSL). A few are platform agnostic lending themselves to be used on a workstation with any CPU and a GPU (e.g., GLSL, OpenCL).Of a number of companies and organizations that implement formal optimization into their processes, only a few utilize GPUs. It is either because the others are either vested much into CPU based computing or they are not fully aware of the benefits of implementing population based optimization routines in GPUs. Literature shows a large number of research publications specifically in the field of optimization utilizing GPUs. However, most of them are limited to a specific GPU hardware or addressed specific problems. The diversity in current GPU hardware and software APIs present overwhelming number of choices making it challenging to decide where and how to begin transitioning to GPU based computing, impeding promising computing avenues that relatively is very cost effective. In this paper, the authors precisely intend to address some of these issues by broadly classifying GPU APIs into three categories: 1) Hardware vendor dependent GPU APIs, 2) Graphical in context APIs, and 3) Platform agnostic APIs. Prior work by the authors demonstrated the capability of digital pheromones within Particle Swarm Optimization (PSO) for searching n-dimensional design spaces with improved accuracy, efficiency and reliability in serial and parallel CPU computing environments. To study the impact of GPUs, the authors have taken this digital pheromone variant of PSO and implemented it on three GPU APIs, each representing a category listed above, in a simplistic sense – delegate unconstrained explicit objective function evaluations to GPUs. While this approach itself cannot be considered novel, the takeaways from implementing it on different GPU APIs provided a wealth of information that the authors believe can help optimization companies and organizations make informed decisions in implementing GPUs in their processes.     

Infrared Spectra of Nickel Cyanide-Ammonia Clathrate Compounds

Nickel cyanide-ammonia forms clathrate compounds with a variety of organic molecules such as aniline, benzene, pyridine, pyrrole, and thiophene. The present results suggest that there is a definite indication of captured molecules and the absorption characteristics of molecules in their environment in nickel cyanide-ammonia cage are similar to those of the molecules in liquid state. In accepting the guest molecules, the nickel cyanide-ammonia structure is not changed, since apart from the appearance of bands due to the trapped molecules, the bands due to pure nickel cyanide-ammonia remain virtually unchanged. The infrared spectra of nickel cyanide-ammonia clathrates in the 100–4000 cm⁻¹ region are described in this investigation.     

Hybrid Image Compression-Encryption Scheme Based on Multilayer Stacked Autoencoder and Logistic Map

Secure transmission of images over a communication channel, with limited data transfer capacity, possesses compression and encryption schemes. A deep learning based hybrid image compression-encryption scheme is proposed by combining stacked auto-encoder with the logistic map. The proposed structure of stacked autoencoder has seven multiple layers, and back propagation algorithm is intended to extend vector portrayal of information into lower vector space. The randomly generated key is used to se...     

Dynamic response of polyurea subjected to nanosecond rise-time stress waves

Shaped charges and explosively formed projectiles used in modern warfare can attain speeds as high as 30,000 ft/s. Impacts from these threats are expected to load the armor materials in the 10 to 100 ns timeframe. During this time, the material strains are quite limited but the strain rates are extremely high. To develop armors against such threats it is imperative to understand the dynamic constitutive behavior of materials in the tens of nanoseconds timeframe. Material behavior in this parameter space cannot be obtained by even the most sophisticated plate-impact and split-Hopkinson bar setups that exist within the high energy materials field today. This paper introduces an apparatus and a test method that are based on laser-generated stress waves to obtain such material behaviors. Although applicable to any material system, the test procedures are demonstrated on polyurea which shows unusual dynamic properties. Thin polyurea layers were deformed using laser-generated stress waves with 1?C2?ns rise times and 16 ns total duration. The total strain in the samples was less than 3%. Because of the transient nature of the stress wave, the strain rate varied throughout the deformation history of the sample. A?peak value of 1.1×10⁵?s^?1 was calculated. It was found that the stress-strain characteristics, determined from experimentally recorded incident and transmitted wave profiles, matched satisfactorily with those computed from a 2D wave mechanics simulation in which the polyurea was modeled as a linearly viscoelastic solid with constants derived from the quasi-static experiments. Thus, the test data conformed to the Time-Temperature Superposition (TTS) principle even at extremely high strain rates of our test. This then extends the previous observations of Zhao et al. (Mech. Time-Depend. Mater. 11:289?C308, 2007) who showed the applicability of the TTS principle for polyurea in the linearly viscoelastic regime up to peak strain rates of?1200?s^?1.     

Dysfunctional Glucose Metabolism in Alzheimer’s Disease Onset and Potential Pharmacological Interventions

Alzheimer’s disease (AD) is the most common age-related dementia. The alteration in metabolic characteristics determines the prognosis. Patients at risk show reduced glucose uptake in the brain. Additionally, type 2 diabetes mellitus increases the risk of AD with increasing age. Therefore, changes in glucose uptake in the cerebral cortex may predict the histopathological diagnosis of AD. The shifts in glucose uptake and metabolism, insulin resistance, oxidative stress, and abnormal autophagy advance the pathogenesis of AD syndrome. Here, we summarize the role of altered glucose metabolism in type 2 diabetes for AD prognosis. Additionally, we discuss diagnosis and potential pharmacological interventions for glucose metabolism defects in AD to encourage the development of novel therapeutic methods.     

Decision support system based on a hybrid genetic algorithm–Kohonen map for combined mode conduction–radiation heat transfer in a porous medium: A comparative assessment of three variations of the Kohonen map

A hybrid genetic algorithm (GA)–Kohonen map, with its three variants, is explored for the first time for the decision-making system in a porous ceramic matrix (PCM)-based burner through determination of the regime of operation. Four different attributes of PCMs such as convective coupling (P₂), extinction coefficient (β), downstream porosity (ϕ₂), and scattering albedo (ω) are selected for determining the regime of operation of a PCM-based burner. Changes in any of these attributes of a PCM lead to significant changes in the temperature profiles of the gas and solid phases. Temperature profiles of the gas and solid phases are computed by developing a numerical model. Various samples corresponding to different regimes are generated and used in a hybrid GA–Kohonen map. The best architectural details such as the neuron number and training epochs are obtained from GA as output. The best Kohonen map is trained with the input data, and regimes of operation for new temperature profiles are predicted. A supervised Kohonen map is able to provide the highest average class prediction of more than 40%. All the variants are assessed under two different types of neuron grids: hexagonal and rectangular. Comparative assessments of the three different variants of Kohonen maps, in terms of CPU time and average class prediction, are carried out.     

Low Trypsin and Chymotrypsin Inhibitor Mutants in Winged Bean(P sophocarpus tetragonolobus(L) DC)

Low trypsin inhibitor (LTI) and chymotrypsin inhibitor (LCTI) mutants have been identified and isolated from the M₅ mutant lines of winged bean. The LTI and LCTI lines demonstrated a true breeding feature in the subsequent generations. Three to five isoinhibitor bands of trypsin and chymotrypsin were absent in different mutants, indicating mutations in the respective gene loci. The LTI and LCTI mutants inhibited insect gut proteases as efficiently as their control counterparts. This could be attributed to a specific group of inhibitors present in all the mutant types.     

Measurement of wear of carbon coated sliders using atomic force microscopy and Raman spectroscopy

Wear of carbon coated sub-ambient pressure “pico” sliders is investigated during sweep testing as a function of interference height, slider design and sliding distance using atomic force microscopy. The wear results from atomic force microscopy measurements are compared with wear measurements of the carbon overcoat using Raman spectroscopy. The effect of interference on wear and disk burnishing is studied using acoustic emission measurements and atomic force microscopy. The results show that wear of a slider is higher for larger interference height and higher stiffness of the air-bearing.