Neural Network Classification of Environmental Samples

This research develops a general methodology for designing neural network classifiers for real-world environmental problems. This methodology is demonstrated through the design of a multi-layer perceptron to classify stainless steel and actinide samples. Neural networks, sometimes called artificial neural networks, have been shown capable of classifying complex patterns. Artificial neural networks are physiologically motivated computer algorithms which attempt to mimic the function of the large interconnected network of neurons in the human brain, which has extraordinary pattern recognition capabilities. These artificial neural networks learn to map a set of input features, elemental composition, onto a set of outputs such as a binary node whose output (1 or 0) represents steel or not steel. For this reason, neural networks may be used to classify the given environmental data

Early Recognition of Burn- and Trauma-Related Acute Kidney Injury: A Pilot Comparison of Machine Learning Techniques.

Severely burned and non-burned trauma patients are at risk for acute kidney injury (AKI). The study objective was to assess the theoretical performance of artificial intelligence (AI)/machine learning (ML) algorithms to augment AKI recognition using the novel biomarker, neutrophil gelatinase associated lipocalin (NGAL), combined with contemporary biomarkers such as N-terminal pro B-type natriuretic peptide (NT-proBNP), urine output (UOP), and plasma creatinine. Machine learning approaches including logistic regression (LR), k-nearest neighbor (k-NN), support vector machine (SVM), random forest (RF), and deep neural networks (DNN) were used in this study. The AI/ML algorithm helped predict AKI 61.8 (32.5) hours faster than the Kidney Disease and Improving Global Disease Outcomes (KDIGO) criteria for burn and non-burned trauma patients. NGAL was analytically superior to traditional AKI biomarkers such as creatinine and UOP. With ML, the AKI predictive capability of NGAL was further enhanced when combined with NT-proBNP or creatinine. The use of AI/ML could be employed with NGAL to accelerate detection of AKI in at-risk burn and non-burned trauma patients

Magnetic and Plasmonic Contrast Agents in Optical Coherence Tomography

Optical coherence tomography (OCT) has gained widespread application for many biomedical applications, yet the traditional array of contrast agents used in incoherent imaging modalities do not provide contrast in OCT. Owing to the high biocompatibility of iron oxides and noble metals, magnetic and plasmonic nanoparticles, respectively, have been developed as OCT contrast agents to enable a range of biological and pre-clinical studies. Here we provide a review of these developments within the past decade, including an overview of the physical contrast mechanisms and classes of OCT system hardware addons needed for magnetic and plasmonic nanoparticle contrast. A comparison of the wide variety of nanoparticle systems is also presented, where the figures of merit depend strongly upon the choice of biological application

Making the Connection: Using Mobile Devices and PollEverywhere for Experiential Learning for Adult Students

Technology integration has significantly influenced the way students access and retain knowledge gained in the classroom (Ahmed, 2016). This is particularly relevant in classrooms for adult learners who engage in continuing education. This paper used a descriptive case study (Yin, 2014) to share how an instructor utilized mobile learning with a web-based polling tool, PollEverywhere, to gamify experiential learning for adult students in various roles within a southeastern state’s court administration—prosecutors, defense lawyers, magistrates, and jail administrators—and improve students’ engagement in the course and connection to course material

Performance Evaluation of Automated Static Analysis Tools

Automated static analysis tools can perform efficient thorough checking of important properties of, and extract and summarize critical information about, a source program. This paper evaluates three open-source static analysis tools; Flawfinder, Cppcheck and Yasca. Each tool is analyzed with regards to usability, IDE integration, performance, and accuracy. Special emphasis is placed on the integration of these tools into the development environment to enable analysis during all phases of development as well as to enable extension of rules and other improvements within the tools. It is shown that Flawfinder be the easiest to modify and extend, Cppcheck be inviting to novices, and Yasca be the most accurate and versatile

Unbound states of 32Cl and the 31S(p,\gamma)32Cl reaction rate

The 31S(p,\gamma)32Cl reaction is expected to provide the dominant break-out path from the SiP cycle in novae and is important for understanding enrichments of sulfur observed in some nova ejecta. We studied the 32S(3He,t)32Cl charge-exchange reaction to determine properties of proton-unbound levels in 32Cl that have previously contributed significant uncertainties to the 31S(p,\gamma)32Cl reaction rate. Measured triton magnetic rigidities were used to determine excitation energies in 32Cl. Proton-branching ratios were obtained by detecting decay protons from unbound 32Cl states in coincidence with tritons. An improved 31S(p,\gamma)32Cl reaction rate was calculated including robust statistical and systematic uncertainties

Imaging Extracellular Matrix Remodeling In Vitro by Diffusion-Sensitive Optical Coherence Tomography

The mammary gland extracellular matrix (ECM) is comprised of biopolymers, primarily collagen I, that are created and maintained by stromal fibroblasts. ECM remodeling by fibroblasts results in changes in ECM fiber spacing (pores) that have been shown to play a critical role in the aggressiveness of breast cancer. However, minimally invasive methods to measure the spatial distribution of ECM pore areas within tissues and in vitro 3D culture models are currently lacking. We introduce diffusion-sensitive optical coherence tomography (DS-OCT) to image the nanoscale porosity of ECM by sensing weakly constrained diffusion of gold nanorods (GNRs). DS-OCT combines the principles of low-coherence interferometry and heterodyne dynamic light scattering. By collecting co- and cross-polarized light backscattered from GNRs within tissue culture, the ensemble-averaged translational self-diffusion rate, DT, of GNRs is resolved within ∼3 coherence volumes (10 × 5 μm, x × z). As GNRs are slowed by intermittent collisions with ECM fibers, DT is sensitive to ECM porosity on the size scale of their hydrodynamic diameter (∼46 nm). Here, we validate the utility of DS-OCT using pure collagen I gels and 3D mammary fibroblast cultures seeded in collagen/Matrigel, and associate differences in artificial ECM pore areas with gel concentration and cell seed density. Across all samples, DT was highly correlated with pore area obtained by scanning electron microscopy (R2 = 0.968). We also demonstrate that DS-OCT can accurately map the spatial heterogeneity of layered samples. Importantly, DS-OCT of 3D mammary fibroblast cultures revealed the impact of fibroblast remodeling, where the spatial heterogeneity of matrix porosity was found to increase with cell density. This provides an unprecedented view into nanoscale changes in artificial ECM porosity over effective pore diameters ranging from ∼43 to 360 nm using a micron-scale optical imaging technique. In combination with the topical deposition of GNRs, the minimally invasive nature of DS-OCT makes this a promising technology for studying tissue remodeling processes

Feeding microalgae meal (All-G Rich (TM); Schizochytrium limacinum CCAP 4067/2) to beef heifers. II: Effects on ground beef color and palatability

Citation: Phelps, K. J., Drouillard, J. S., O'Quinn, T. G., Burnett, D. D., Blackmon, T. L., Axman, J. E., . . . Gonzalez, J. M. (2016). Feeding microalgae meal (All-G Rich (TM); Schizochytrium limacinum CCAP 4067/2) to beef heifers. II: Effects on ground beef color and palatability. Journal of Animal Science, 94(9), 4030-4039. doi:10.2527/jas2016-0488The objective of this study was to examine the effects of feeding microalgae meal (All-G Rich, Schizochytrium limacinum CCAP 4087/2; Alltech Inc., Nicholasville, KY) to finishing heifers on 85% lean and 15% fat (85/15) ground beef PUFA content, palatability, and color stability. Crossbred heifers (n = 288; 452 +/- 23 kg initial BW) were allocated to pens (36 pens and 8 heifers/pen), stratified by initial pen BW (3,612 +/- 177 kg), and randomly assigned within strata to 1 of 4 treatments: 0, 50, 100, and 150 g center dot heifer(-1) center dot d(-1) of microalgae meal. After 89 d of feeding, a subset of heifers (3/pen) was harvested and the rectus femoris, vastus lateralis, vastus medialis, and vastus intermedius were collected for processing into ground beef. At 42 d postmortem, 85/15 ground beef was formulated and formed into 112-g patties and fatty acid composition, subjective palatability, and 96-h retail color stability analyses were conducted. Increasing dietary microalgae meal concentration increased ground beef 20: 5n-3 and 22: 6n-3 fatty acids (quadratic, P 0.12). Feeding microalgae meal affected (P = 0.02) b* at 24 h and decreased (linear, P = 0.08) b* at 48 h. From h 0 to 36 of display, microalgae affected redness of patties (P 0.20) but tended to affect (P = 0.10) cohesiveness scores. As the amount of microalgae meal fed to heifers increased, beef flavor intensity decreased (linear, P < 0.01) and off-flavor intensity increased (quadratic, P < 0.05). Surface oxymyoglobin and metmyoglobin were impacted by microalgae meal from 12 to 36 h of display (P < 0.01). From 48 to 84 h of display, feeding microalgae meal to heifers decreased (linear, P < 0.09) surface oxymyoglobin and increased (linear, P < 0.02) surface metmyoglobin of patties. Although feeding microalgae meal to heifers increases the PUFA content of 85/15 ground beef, there are undesirable effects on flavor and color stability

Feeding microalgae meal (All-G Rich (TM); Schizochytrium limacinum CCAP 4087/2) to beef heifers. I: Effects on longissimus lumborum steak color and palatibility

Citation: Phelps, K. J., Drouillard, J. S., O'Quinn, T. G., Burnett, D. D., Blackmon, T. L., Axman, J. E., . . . Gonzalez, J. M. (2016). Feeding microalgae meal (All-G Rich (TM); Schizochytrium limacinum CCAP 4087/2) to beef heifers. I: Effects on longissimus lumborum steak color and palatibility. Journal of Animal Science, 94(9), 4016-4029. doi:10.2527/jas2016-0487The objective of this study was to examine effects of 4 levels of microalgae meal (All-G Rich, Schizochytrium limacinum CCAP 4087/2; Alltech Inc., Nicholasville, KY) supplementation to the diet of finishing heifers on longissimus lumborum (LL) steak PUFA content, beef palatability, and color stability. Crossbred heifers (n = 288; 452 +/- 23 kg initial BW) were allocated to pens (36 pens and 8 heifers/ pen), stratified by initial pen BW (3,612 +/- 177 kg), and randomly assigned within strata to 1 of 4 treatments: 0, 50, 100, and 150 g . heifer(-1) . d(-1) of microalgae meal. After 89 d of feeding, cattle were harvested and LL were collected for determination of fatty acid composition and Warner-Bratzler shear force (WBSF), trained sensory panel evaluation, and 7-d retail color stability and lipid oxidation analyses. Feeding microalgae meal to heifers increased (quadratic, P 0.25) but tended (P = 0.10) to increase total PUFA in a quadratic manner (P = 0.03). Total omega-6 PUFA decreased (linear, P = 0.01) and total omega-3 PUFA increased (quadratic, P 0.16); however, off-flavor intensity increased with increasing concentration of microalgae meal in the diet (quadratic, P 0.19); therefore, the negative effects of microalgae on color stability were not due to fiber metabolism differences. Feeding microalgae meal to finishing heifers improves PUFA content of beef within the LL, but there are adverse effects on flavor and color stability

Direct reaction measurements with a 132Sn radioactive ion beam

The (d,p) neutron transfer and (d,d) elastic scattering reactions were measured in inverse kinematics using a radioactive ion beam of 132Sn at 630 MeV. The elastic scattering data were taken in a region where Rutherford scattering dominated the reaction, and nuclear effects account for less than 8% of the cross section. The magnitude of the nuclear effects was found to be independent of the optical potential used, allowing the transfer data to be normalized in a reliable manner. The neutron-transfer reaction populated a previously unmeasured state at 1363 keV, which is most likely the single-particle 3p1/2 state expected above the N=82 shell closure. The data were analyzed using finite range adiabatic wave calculations and the results compared with the previous analysis using the distorted wave Born approximation. Angular distributions for the ground and first excited states are consistent with the previous tentative spin and parity assignments. Spectroscopic factors extracted from the differential cross sections are similar to those found for the one neutron states beyond the benchmark doubly-magic nucleus 208Pb.Comment: 22 pages, 7 figure