microRNAs Are Abundant and Stable in Platelet-Rich Fibrin and Other Autologous Blood Products of Canines

Various microRNAs (miRNAs) present in autologous blood products of canines have not been studied recently. We aimed to elucidate the existence of miRNAs in platelet-rich fibrin (PRF) and the stability of canine autologous blood products under various storage conditions. Total RNAs were isolated from PRF and other autologous blood products following newly adapted protocols used in commercial kits for plasma and tissue samples. Quantitative real-time polymerase chain reaction analysis (qPCR) was used to detect miRNAs in autologous blood products. The miR-16, miR-21, miR-155, and miR-146a were abundant in PRF and other autologous blood products of canines. Furthermore, we found they could maintain stability under protracted freezing temperatures of −30 °C for at least one month. Our findings revealed that PRF might be a stable resource for various canine miRNAs.     

Ensemble learning of diffractive optical networks

A plethora of research advances have emerged in the fields of optics and photonics that benefit from harnessing the power of machine learning.Specifically,there has been a revival of interest in optical computing hardware due to its potential advantages for machine learning tasks in terms of parallelization,power efficiency and computation speed.Diffractive deep neural networks(D²NNs)form such an optical computing framework that benefits from deep learning-based design of successive diffractive layers to all-optically process information as the input light diffracts through these passive layers.D²NNs have demonstrated success in various tasks,including object classification,the spectral encoding of information,optical pulse shaping and imaging.Here,we substantially improve the inference performance of diffractive optical networks using feature engineering and ensemble learning.After independently training 1252 D²NNs that were diversely engineered with a variety of passive input filters,we applied a pruning algorithm to select an optimized ensemble of D²NNs that collectively improved the image classification accuracy.Through this pruning,we numerically demonstrated that ensembles of N=14 and N=30 D²NNs achieve blind testing accuracies of 61.14±0.23%and 62.13±0.05%,respectively,on the classification of GFAR-10 test images,providing an inference improvennent of>16%compared to the average performance of the individual D²NNs within each ensemble.These results constitute the highest inference accuracies achieved to date by any diffractive optical neural network design on the same dataset and might provide a significant leap to extend the application space of diffractive optical image classification and machine vision systems.     

Inactivation of Bacillus spores by the combination of moderate heat and low hydrostatic pressure in ketchup and potage

The combination effect of moderate heat and low hydrostatic pressure (MHP) on the reduction of Bacillus subtilis, Bacillus coagulans and Geobacillus stearothermophilus spores in food materials (potage and ketchup) was investigated. These bacterial spores were suspended in potage (pH 7), acidified potage (pH 4), neutralized ketchup (pH 7) and ketchup (pH 4). The suspensions were treated with and without pressure (100 MPa) and temperatures of 65-85 degrees C for 3 to 12 h. The bacterial spores were inactivated by 4-8 log cycles during MHP treatment in potage, acidified potage and ketchup, whereas the spores were highly resistant to long time heat treatment in potage and neutralized ketchup. The degrees of spore destruction were mostly dependent on pH and medium composition during MHP treatment. The inactivation effect in MHP treatment was higher at the pH 7 than at pH 4 both in ketchup and potage. The bacterial spores showed higher inactivation in potage than ketchup during MHP treatment.     

Mass balance of total mercury and monomethylmercury in coastal embayments of a volcanic island: significance of submarine groundwater discharge

To understand the contribution of submarine groundwater discharge (SGD) to the coastal mass budgets of Hg and monomethylmercury (MMHg), preliminary mass balance estimates were made for Hwasun and Bangdu Bays on Jeju Island, known to have large SGD due to the high permeability of the volcanic rocks. The mass balance results indicate that SGD is a main source of Hg in Hwasun Bay (23 ± 14 × 10(-2) mol yr(-1), 34%) and Bangdu Bay (23 ± 20 × 10(-2) mol yr(-1), 67%), although the contribution from atmospheric deposition was considerable (25% for Hwasun and 23% for Bangdu). MMHg was also discharged primarily from submarine groundwater at Hwasun (0.30 ± 0.17 × 10(-2) mol yr(-1), 55%) and Bangdu (0.65 ± 0.49 × 10(-2) mol yr(-1), 64%), which was higher than atmospheric deposition (6% for Hwasun and 2% for Bangdu) and sediment diffusion flux (5% for Hwasun and 3% for Bangdu). The overall mass balance results suggest that, although there are large spatial variations in SGD rates throughout the region, the coastal mass budgets of Hg and MMHg need to include SGD as well as atmospheric deposition and sediment diffusion as primary sources of Hg and MMHg.     

Rapid Detection of Wheat Blast Pathogen Magnaporthe oryzae Triticum Pathotype Using Genome-Specific Primers and Cas12a-mediated Technology

Wheat blast, caused by the fungus Magnaporthe oryzae Triticum (MoT) pathotype, is a devastating disease persistent in South America and Bangladesh. Since MoT generally fails to cause visual symptoms in wheat until the heading stage when the infection would have advanced, disease control by fungicide application solely based on the detection of visual symptoms is ineffective. To develop an accurate and sensitive method to detect MoT at the seedling and vegetative stages for disease control, we sequenced the genomes of two MoT isolates from Brazil and identified two DNA fragments, MoT-6098 and MoT-6099, that are present in the MoT genome but not in the genome of the rice-infecting Magnaporthe oryzae Oryzae (MoO) pathotype. Using polymerase chain reaction (PCR), we confirmed the specificity of the two markers in 53 MoT and MoO isolates from South America and Bangladesh. To test the efficiency of the two markers, we first established a loop-mediated isothermal amplification (LAMP) method to detect MoT at isothermal conditions, without the use of a PCR machine. Following this, we used the Cas12a protein and guide RNAs (gRNAs) to target the MoT-6098 and MoT-6099 sequences. The activated Cas12a showed indiscriminate single-stranded deoxyribonuclease (ssDNase) activity. We then combined target-dependent Cas12a ssDNase activation with recombinase polymerase amplification (RPA) and nucleic acid lateral flow immunoassay (NALFIA) to develop a method that accurately, sensitively, and cost-effectively detects MoT-specific DNA sequences in infected wheat plants. This novel technique can be easily adapted for the rapid detection of wheat blast and other important plant diseases in the field.     

Failure Investigation of Boiler Water Wall Tubes of a Thermal Power Station

Failure investigation was carried out on boiler water wall tubes of a thermal power plant through visual inspection, chemical analysis, and metallurgical analysis. Failure was in the form of thin/micro cracks along the length of the tubes which were located at the girth welding joint of tubes. Experimental results revealed that the cracking was from inward to outward of the tube thickness. Discontinuities/cavities were observed in the welded region which might have occurred due to lack of fusion of base metal and the weld metal. Cracks were initiated from the sharp corner/crack tip of the cavities/discontinuities present at the welded region under the action of hoop/thermal stress existed during the operation. Nature of the crack propagation indicates the case of typical hydrogen-induced cracking. Moreover, the presence of the cavities/discontinuities reduced the cross-sectional area of tubes resulting increased stress intensity. Increased stress beyond the flow stress of the material assisted by hydrogen-induced effect resulted the cracking of the tubes. In order to mitigate the problem, proper welding of tubes joints should be carried out followed by proper inspection after weld. Secondly, hydrogen dissolution during welding should be prevented and treatment for its removal after welding should be carried out.     

A similarity coefficient measure and machine-parts grouping in cellular manufacturing systems

For more than three decades, similarity coefficient measures one of the important tools for solving group technology problems have gained the attention of the research community in cellular manufacturing systems. A new similarity coefficient measure that uses a set of important characteristic properties for grouping is developed here for use as an intermediate tool to form cohesive cells. A mathematical model that uses this similarity coefficient for optimally solving the cell-formation problems in cellular manufacturing is developed. A heuristic procedure that improves the optimal methodology in term of solution capability of the large instances is devised for an efficient solution. Both the optimal methodology and the heuristic are applied to some well-known problems from literature to compare the grouping efficiencies. The similarity coefficient and the solution methodologies developed are able to solve the cell formation problems efficiently.     

Probabilistic design of ground improvement by vertical drains for soil of spatially variable coefficient of consolidation

The design of soil consolidation via prefabricated vertical drains (PVDs) has been traditionally carried out deterministically and thus can be misleading due to the ignorance of the uncertainty associated with the inherent variability of soil properties. To treat such uncertainty in the course of design of soil improvement by PVDs, more rational probabilistic methods are necessary. In this paper, a simplified probabilistic method is proposed in which the inherent variability of the coefficient of consolidation, which is the most significant uncertain soil parameter that affects the consolidation process, is considered. An easy-to-use design procedure and charts are provided for routine use by practitioners.     

Visualization and concentration measurement of a direct-injection hydrogen jet in a constant-volume vessel using spark-induced breakdown spectroscopy

In this work, spark-induced breakdown spectroscopy (SIBS) was employed to investigate the mixing process of a hydrogen jet in a constant-volume vessel. The local fuel concentration of the hydrogen jet was measured at several locations, using a SIBS sensor. A high-speed camera was used to visualize spark discharge fluctuations, and hydrogen jet concentration measurements were conducted simultaneously. Spectrally resolved atomic emissions from the plasma generated by the spark plug were examined to determine the local equivalence ratio. Direct visualization of the spark discharge provided useful information about the influence of spark discharge characteristics related to the spark timing. Using the developed SIBS sensor, atomic emission spectra were obtained from hydrogen H_α at 656 nm and nitrogen N (I) at 501 nm. Comparison of the intensity peaks of atomic emissions from hydrogen and nitrogen allows the local hydrogen concentration in a measured volume to be determined, and hence also the local equivalence ratio. The measurement results demonstrate the local variation in the equivalence ratio throughout the jet and along its axis. From the results, the spatial structure of the hydrogen jet affects the hydrogen/nitrogen mixing and could be clarified with SIBS technique when the spark is discharged.     

Influence of Elevated Temperature and Stress Ratio on the Fatigue Response of AM60B Magnesium Alloy

The fatigue response of a high pressure die-cast AM60B Mg alloy is studied at room and elevated temperatures. The fatigue tests are conducted with stress ratio of R?=?0.1 and frequency of 30?Hz. The main objective is to determine whether elevated temperature would affect the fatigue response of the alloy. In addition, fatigue crack growth characteristics of the alloy is investigated at room temperature. The purpose of this test is to ascertain the capability and accuracy of a finite element approach coupled with the Walker model in assessing the life cycle of the alloy, in consideration of the influence of stress ratio.