High Resolution Genome Wide Association Studies Reveal Rich Genetic Architectures of Grain Zinc and Iron in Common Wheat (Triticum aestivum L.)

Biofortification is a sustainable strategy to alleviate micronutrient deficiency in humans. It is necessary to improve grain zinc (GZnC) and iron concentrations (GFeC) in wheat based on genetic knowledge. However, the precise dissection of the genetic architecture underlying GZnC and GFeC remains challenging. In this study, high-resolution genome-wide association studies were conducted for GZnC and GFeC by three different models using 166 wheat cultivars and 373,106 polymorphic markers from the wheat 660K and 90K single nucleotide polymorphism (SNP) arrays. Totally, 25 and 16 stable loci were detected for GZnC and GFeC, respectively. Among them, 17 loci for GZnC and 8 for GFeC are likely to be new quantitative trait locus/loci (QTL). Based on gene annotations and expression profiles, 28 promising candidate genes were identified for Zn/Fe uptake (8), transport (11), storage (3), and regulations (6). Of them, 11 genes were putative wheat orthologs of known Arabidopsis and rice genes related to Zn/Fe homeostasis. A brief model, such as genes related to Zn/Fe homeostasis from root uptake, xylem transport to the final seed storage was proposed in wheat. Kompetitive allele-specific PCR (KASP) markers were successfully developed for two major QTL of GZnC on chromosome arms 3AL and 7AL, respectively, which were independent of thousand kernel weight and plant height. The 3AL QTL was further validated in a bi-parental population under multi-environments. A wheat multidrug and toxic compound extrusion (MATE) transporter TraesCS3A01G499300, the ortholog of rice gene OsPEZ2, was identified as a potential candidate gene. This study has advanced our knowledge of the genetic basis underlying GZnC and GFeC in wheat and provides valuable markers and candidate genes for wheat biofortification

The Medical Segmentation Decathlon

International challenges have become the de facto standard for comparative assessment of image analysis algorithms given a specific task. Segmentation is so far the most widely investigated medical image processing task, but the various segmentation challenges have typically been organized in isolation, such that algorithm development was driven by the need to tackle a single specific clinical problem. We hypothesized that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. To investigate the hypothesis, we organized the Medical Segmentation Decathlon (MSD) - a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities. The underlying data set was designed to explore the axis of difficulties typically encountered when dealing with medical images, such as small data sets, unbalanced labels, multi-site data and small objects. The MSD challenge confirmed that algorithms with a consistent good performance on a set of tasks preserved their good average performance on a different set of previously unseen tasks. Moreover, by monitoring the MSD winner for two years, we found that this algorithm continued generalizing well to a wide range of other clinical problems, further confirming our hypothesis. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms are mature, accurate, and generalize well when retrained on unseen tasks; (2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability; (3) the training of accurate AI segmentation models is now commoditized to non AI experts

Exome Sequencing Identifies ZNF644 Mutations in High Myopia

Myopia is the most common ocular disorder worldwide, and high myopia in particular is one of the leading causes of blindness. Genetic factors play a critical role in the development of myopia, especially high myopia. Recently, the exome sequencing approach has been successfully used for the disease gene identification of Mendelian disorders. Here we show a successful application of exome sequencing to identify a gene for an autosomal dominant disorder, and we have identified a gene potentially responsible for high myopia in a monogenic form. We captured exomes of two affected individuals from a Han Chinese family with high myopia and performed sequencing analysis by a second-generation sequencer with a mean coverage of 30× and sufficient depth to call variants at ∼97% of each targeted exome. The shared genetic variants of these two affected individuals in the family being studied were filtered against the 1000 Genomes Project and the dbSNP131 database. A mutation A672G in zinc finger protein 644 isoform 1 (ZNF644) was identified as being related to the phenotype of this family. After we performed sequencing analysis of the exons in the ZNF644 gene in 300 sporadic cases of high myopia, we identified an additional five mutations (I587V, R680G, C699Y, 3′UTR+12 C>G, and 3′UTR+592 G>A) in 11 different patients. All these mutations were absent in 600 normal controls. The ZNF644 gene was expressed in human retinal and retinal pigment epithelium (RPE). Given that ZNF644 is predicted to be a transcription factor that may regulate genes involved in eye development, mutation may cause the axial elongation of eyeball found in high myopia patients. Our results suggest that ZNF644 might be a causal gene for high myopia in a monogenic form

Formation Behaviors of Coated Reactive Explosively Formed Projectile

The formation behavior of coated reactive explosively formed projectiles (EFP) is studied by the combination of experiments and simulations. The results show that the coated EFP can be obtained by explosively crushing the double-layer liners, and the simulation agrees with the experiment well. Then, the interaction process between the two liners is discussed in detail, and the formation and coating mechanism are revealed. It can be found that there are three phases in the formation process, including the impact, closing and stretching phases. During the impact phase, the velocities of two liners rise in turns with the kinetic energy exchange. In the closing phase, the copper liner is collapsed forward to the axis and completely coats the reactive liner. It is mentioned that the edge of the copper liner begins to form a metal precursor penetrator in this stage. During the stretching phase, the coated reactive EFP is further stretched and fractured, resulting in the separation of the metal precursor penetrator and the following coated reactive projectile. Further studies show both the edge thickness and the curvature radius of the copper liner have significant influences on formation behaviors. By decreasing the edge thickness or the curvature radius, the difficulty of closing decreases, but the tip velocity and the length of precursor penetrator increases. As the thickness and diameter of the reactive liner decrease, the coating velocity increases slightly, but the total length of coated reactive EFP tends to decrease

Video-Restoration-Net: Deep Generative Model with Non-Local Network for Inpainting and Super-Resolution Tasks

Although deep learning-based approaches for video processing have been extensively investigated, the lack of generality in network construction makes it challenging for practical applications, particularly in video restoration. As a result, this paper presents a universal video restoration model that can simultaneously tackle video inpainting and super-resolution tasks. The network, called Video-Restoration-Net (VRN), consists of four components: (1) an encoder to extract features from each frame, (2) a non-local network that recombines features from adjacent frames or different locations of a given frame, (3) a decoder to restore the coarse video from the output of a non-local block, and (4) a refinement network to refine the coarse video on the frame level. The framework is trained in a three-step pipeline to improve training stability for both tasks. Specifically, we first suggest an automated technique to generate full video datasets for super-resolution reconstruction and another complete-incomplete video dataset for inpainting, respectively. A VRN is then trained to inpaint the incomplete videos. Meanwhile, the full video datasets are adopted to train another VRN frame-wisely and validate it against authoritative datasets. We show quantitative comparisons with several baseline models, achieving 40.5042 dB/0.99473 on PSNR/SSIM in the inpainting task, while during the SR task we obtained 28.41 dB/0.7953 and 27.25/0.8152 on BSD100 and Urban100, respectively. The qualitative comparisons demonstrate that our proposed model is able to complete masked regions and implement super-resolution reconstruction in videos of high quality. Furthermore, the above results show that our method has greater versatility both in video inpainting and super-resolution tasks compared to recent models

Failure and Ejection Behavior of Concrete Materials under Internal Blast

In order to investigate the failure and ejection behavior of concrete materials under internal blast, the default Riedel-Hiermaier-Thoma (RHT) concrete model in AUTODYN and a meshfree processor called SPH are employed in this numerical simulation. It is shown that the failure mechanisms are significantly different in these damaged zones. Crushed zone is caused by shear failure while fractured zone is induced by tensile failure, and spalled zone is formed by a combination of shear and tensile failure. In addition, the ejection velocity distribution of the fragmented concrete mass on free surface is examined. The results indicate that the ejection velocity declines monotonously with the increase of the distance to symmetry axis of computational model. On the wall of the prefabricated borehole, two types of fragmented concrete mass are analyzed, and bottom initiation is recommended to eject the fragmented concrete mass effectively. Moreover, an algorithm of average ejection speed is developed to effectively estimate the drill capacity of high velocity, energetic (HE) projectiles. At last, the validity of numerical simulation is verified by physical experiments

Mechanics–thermotics–chemistry coupling response model and numerical simulation method for reactive liner

Aiming at describing the mechanics–thermotics–chemistry coupling response of the reactive material liner under impact loading, the Grüneisen equation of state in the form of P–V–T was derived. Combined with the impact temperature rise theory, heat conduction theory, and Arrhenius chemical reaction kinetic model, the mechanics–thermotics–chemistry coupling response model is established. A numerical simulation framework for the thermodynamic response of reactive materials under impact load was established, and numerical simulation codes for the impact-induced energy release behavior of reactive materials was developed based on the material point method, which realized the numerical simulation of the formation behavior of the reactive material penetrator (jet) under explosion load. The results show that chemical reactions occur in the process of reactive material jet formation, and high temperature and high pressure products make the jet expand and thicken constantly, resulting in the decrease in the density of the jet head and the increase in the cross-sectional area. As such, the jet has hardly any armor-piercing capability at stand-offs of 2.5 times the caliber, and the simulation results are in good agreement with the experimental results

Impact-Initiation Sensitivity of High-Temperature PTFE-Al-W Reactive Materials

Drop-weight tests were conducted to investigate the impact-initiation sensitivity of high-temperature PTFE-Al-W reactive materials. The test results show that the impact-initiation sensitivity of the materials more than doubles with increasing the sample temperature from 25 to 350 °C. Combined with the impact-induced initiation process recorded by high-speed video and the difference between reacted and unreacted residues, the crack-induced initiation mechanism was revealed. The rapid propagation of crack provides a high-temperature and aerobic environment where Al reacts violently to PTFE, which induces the initiation. Moreover, the influence of sample temperature on the sensitivity was discussed and analyzed. The analysis results indicate that the sensitivity shows a temperature interval effect, and 127 and 327 °C are the interval boundaries where the sensitivity changes significantly. The sensitivity may leaps at 127 °C and increases more rapidly in the temperature interval from 127 to 327 °C, but hardly changes after the temperature reaches 327 °C