Excitation and spectral dependence of the rise and decay time responses of Eu2+- and Dy3+-doped strontium aluminates

Journal of Materials Science: Materials in Electronics - In this paper, we study the phosphorescence rise and decay time responses of Eu2+- and Dy3+-doped strontium aluminates prepared by different...     

Nonhypothesis Analysis of a Mutagenic Soybean (Glycine max [L.]) Population for Protein and Fatty‐Acid Composition

Soybean is a major source of oil for food, feed, and biofuel production. Mutagenesis is a tool for creating unique traits useful in breeding programs. The aim of this study is to use nonhypothesis statistical testing methods to make decisions about a mutagenic population. To this end, a total of 1037 mutation lines and 28 wild‐type lines were analyzed for fatty‐acid composition and protein content. Principal component analysis (PCA) was used to analyze the fatty acid profile, multivariate analysis of variance (MANOVA) to build a selection model for seed weight per plant and weight per 10 seeds, and clustering in conjunction with power analysis to determine the minimum number of individuals needed to create a MANOVA selection model for the oil to protein content. Five of the 35 possible entries were identified by PCA analysis for stearic acid and four of 16 possible entries for oleic acid. Interestingly, most of the selected mutants were validated genetically. In fact, selected mutants with high seed stearic acid or high seed oleic acid contents were verified to carry mutations on GmFAD2‐1A, GmFAD2‐1B, and GmSACPD‐C genes. This shows a promising method of identifying smaller portion of the population to screen for desired mutations.     

Adaptive multi-scale segmentation of surface data using unsupervised learning of seed positions

This paper presents a method for multi-scale segmentation of surface data using scale-adaptive region growing. The proposed segmentation algorithm is initiated by an unsupervised learning of optimal seed positions through the surface attribute clustering with a two-criterion score function. The seeds are selected as consecutive local maxima of the clustering map, which is computed by an aggregation of the local isotropic contrast and local variance maps. The proposed method avoids typical segmentation errors caused by an inappropriate choice of seed points and thresholds used in the region-growing algorithm. The scale-adaptive threshold estimate is based on the image local statistics in the neighborhoods of seed points. The performance of this method was evaluated on LiDAR surface images.     

Ultrasound applications in poultry meat processing: A systematic review

Ultrasound (US) is classified as a nonthermal treatment and it is used in food processing at a frequency range between 20 kHz and 1 MHz. Cavitation bubbles occur when the US strength is high enough to generate rarefaction that exceeds the intermolecular attraction forces in the medium. Currently, US is widely used in meat industries to enhance procedures, such as meat tenderization, emulsification mass transfer, marination, freezing, homogenization, crystallization, drying, and microorganism inactivation. In addition, combining ultrasonic energy with a sanitizing agent has a synergistic effect on microbial reduction. When poultry meat is treated using US, the expected quality is often better than the traditional methods, such as sanitization and freezing. US can be considered as a novel green technology for tenderizing and decontamination of poultry meat since both Escherichia coli and Salmonella are sensible to US. US improves the physical and chemical properties of meat proteins and can lead to a decrease in the α-helix in intramuscular protease complex in addition to a reduction in the viscosity coefficients. Therefore, ultrasonic treatment can be applied to enhance the textural properties of chicken meat. US can also be used to improve the drying rate when used under vacuum, compared with other traditional techniques. This review focuses on the potential of US applications in the management of poultry industries as the demand for good quality meat proteins is increasing worldwide.     

Setting adaptive spike detection threshold for smoothed TEO based on robust statistics theory

We propose a novel approach aimed at adaptively setting the threshold of the smoothed Teager energy operator (STEO) detector to be used in extracellular recording of neural signals. In this proposed approach, to set the adaptive threshold of the STEO detector, we derive the relationship between the low-order statistics of its input signal and the ones of its output signal. This relationship is determined with only the background noise component assumed to be present at the input. Robust statistics theory techniques were used to achieve an unbiased estimation of these low-order statistics of the background noise component directly from the neural input signal. In this paper, the emphasis is made on extracellular neural recordings. However, the proposed method can be used in the analysis of different biomedical signals where spikes are important for diagnostic (e.g., ECG, EEG, etc.). We validated the efficacy of the proposed method using synthetic neural signals constructed from real neural recordings signals. Four different sets of extracellular recordings from four distinct neural sources have been exploited to that purpose. The first dataset is recorded from an adult male monkey using the Utath 10×10 microelectrode array implemented in the prefrontal cortex, the second one was obtained from the visual cortex of a rat using a stainless-steel-tipped microelectrode, the third dataset came from recording in a human medial lobe using intracranial electrode, and finally, the fourth one was extracted from recordings in a macaque parietal cortex using a single tetrode. Simulation results show that our approach is effective and robust, and outperforms state-of-the-art adaptive detection methods in its category (i.e., efficient and simple, and do not require a priori knowledge about neural spike waveforms shapes).     

TILLING-by-Sequencing+ to Decipher Oil Biosynthesis Pathway in Soybeans: A New and Effective Platform for High-Throughput Gene Functional Analysis

Reverse genetic approaches have been widely applied to study gene function in crop species; however, these techniques, including gel-based TILLING, present low efficiency to characterize genes in soybeans due to genome complexity, gene duplication, and the presence of multiple gene family members that share high homology in their DNA sequence. Chemical mutagenesis emerges as a genetically modified-free strategy to produce large-scale soybean mutants for economically important traits improvement. The current study uses an optimized high-throughput TILLING by target capture sequencing technology, or TILLING-by-Sequencing⁺ (TbyS⁺), coupled with universal bioinformatic tools to identify population-wide mutations in soybeans. Four ethyl methanesulfonate mutagenized populations (4032 mutant families) have been screened for the presence of induced mutations in targeted genes. The mutation types and effects have been characterized for a total of 138 soybean genes involved in soybean seed composition, disease resistance, and many other quality traits. To test the efficiency of TbyS⁺ in complex genomes, we used soybeans as a model with a focus on three desaturase gene families, GmSACPD, GmFAD2, and GmFAD3, that are involved in the soybean fatty acid biosynthesis pathway. We successfully isolated mutants from all the six gene family members. Unsurprisingly, most of the characterized mutants showed significant changes either in their stearic, oleic, or linolenic acids. By using TbyS⁺, we discovered novel sources of soybean oil traits, including high saturated and monosaturated fatty acids in addition to low polyunsaturated fatty acid contents. This technology provides an unprecedented platform for highly effective screening of polyploid mutant populations and functional gene analysis. The obtained soybean mutants from this study can be used in subsequent soybean breeding programs for improved oil composition traits.