Crop phenotyping for wheat yield and yield components against drought stress

Water deficit is a most limiting factor for wheat in rain-fed agricultural systems worldwide. The effects of drought stress on some root features and yield and yield components in wheat (Trticum aestivum L.) were carried out in a factorial experiment based on completely randomized design, under greenhouse condition. The four experimental irrigation regimes, irrigation after 75% of the water was depleted (control), irrigation after 65% of the water was depleted (mild stress), irrigation after 55% of the water was depleted (moderate stress) and irrigation after 45% of the water was depleted (severe stress) were randomized for the main plots. The subplot treatments included eight wheat genotypes. Results showed that Interaction Drought stress with Variety had significantly affected on Total Root Volume and Dry Matter, Number of Tiller and also Shoot Dry Matter. Value of Total Root Volume and Dry Matter, Shoot Dry Matter and Number of Tiller in irrigated varieties were more than rainfed in whole of Drought stresses. N-87-20 variety had most amounts of Total Root Dry Matter, Total Root Volume (exception of control) in all of stresses and control. Root properties influence on yield and other morphological traits of wheat. Stress intensification increase root growth than plant organ so that wheat root can uptake water from soil to compensate damage caused by stress

The Growth of Balinese Cows Which Getting Basic Ration of Spear Grass and Angsana Leaf Supplemented with Silk Tree Leaf

The study had been conducted to find out the growth of Balinese cows which getting basic ration of spear grass (Heteropogoncontortus) and Angsana leaf that had been supplemented with Silk tree leaf (Paraserianthes falcataria L.). The study was using complete randomized block design with 4 ration treatments and 3 times repetition. Each repetition was using three Balinese cows. The weight of cows being used were in the range of: 83-181 kg. Basic ration being given was arranged based on the percentage of dry ingredients namely: 80% of spear grass + 20% of Angsana leaf (A), 80% of spear grass + 20% of Angsana leaf + 10% of silk tree leaf (B), 80% of spear grass + 20% of Angsana leaf + 15% of silk tree leaf (C), and  80% of spear grass + 20% of Angsana leaf + 20% of silk tree leaf (D), The variables being measured were: dry ingredients consumption, nutrients consumption, body weight gain and Feed Conversion Ratio. The result of study showed that with administration of 20% of silk tree leaf in basic ration was significantly improving (P< 0.05) the consumption of dry ingredients and nutrient, and daily weight gain. The result of study concluded that with administration of silk tree leaf in basic ration of spear grass and Angsana leaf increased the growth of Balinese ox

Nutrient Digestion and Body Weight Gain of Balinese Cows Getting Basic Ration of Spear Grass and Rosewood Leaves Supplemented with Falcata Tree Leaves

A study had been conducted to find out nutrient digestion and body weight gain of Balinese cows getting a basic ration of spear grass and Rosewood leaves supplemented with Falcata tree leaves. The study was using complete randomized block design with 4 ration treatments and 3 times repetition. Each repetition was using three Balinese cows. The weights of cows being used were in the range of 83-181 kg. Basic ration being given was arranged based on the percentage of dry ingredients namely: 80% of spear grass + 20% of rosewood leaves (A), 80% of spear grass + 20% of rosewood leaves + 10% of falcata tree leaves (B), 80% of spear grass + 20% of rosewood leaves + 15% of falcata tree leaves (C), and  80% of spear grass + 20% of rosewood leaves + 20% of falcata tree leaves (D), The variables being measured were: nutrient digestion and body weight gain. The result of the study showed that with the administration of 20% falcata tree leaves in the basic ration, it differed significantly (P<0.05) in increasing nutrient digestion and daily weight gain. The result of the study concluded that with the administration of falcata tree leaves in the basic ration of spear grass and rosewood leaves capable to increase nutrient digestion so that bacteria would optimally increase the utilization of fodder and led to a high weight gain of Balinese cows.&nbsp

Performance Analysis and Added Value of Industry Processing Beef into Processed Meat Jengken and Shredded in the Kota Kefamenanu District

This research aims to determine the performance of the beef processing industry in Kefamenanu City District and to analyze the amount of added value generated from beef processing in Kefamenanu City District. This research was conducted in the MSMEs VIVI meat processing industry, Kefamenanu City District, North Central Timor Regency. This study used the Surfei method with quantitative descriptive analysis. The variables observed were the performance of the meat processing industry and the added value of beef processing. The application of the balanced scorecard concept in analyzing the performance of VIVI MSMEs shows that from a financial perspective it has a good performance with an infinite CR value; average NPM 8,216%; an average ROA of 15,39% and an average ROI of 2,24 times of the investment value. From the customer perspective, it has a good performance with 51,49% of general customers who are satisfied and 49,79% of partner customers who are satisfied. For the perspective of internal business processes and the perspective of learning and growth have a good performance, respectively, with a value of 60,76% and 54,86%, respectively. It is concluded that the value added of beef products per kilogram of output is Rp. 48.060.00 for shredded products and beef jerky products of Rp. 37.551.00

Thermal conductivity measurements of proton-heated warm dense aluminum.

Thermal conductivity is one of the most crucial physical properties of matter when it comes to understanding heat transport, hydrodynamic evolution, and energy balance in systems ranging from astrophysical objects to fusion plasmas. In the warm dense matter regime, experimental data are very scarce so that many theoretical models remain untested. Here we present the first thermal conductivity measurements of aluminum at 0.5-2.7 g/cc and 2-10 eV, using a recently developed platform of differential heating. A temperature gradient is induced in a Au/Al dual-layer target by proton heating, and subsequent heat flow from the hotter Au to the Al rear surface is detected by two simultaneous time-resolved diagnostics. A systematic data set allows for constraining both thermal conductivity and equation-of-state models. Simulations using Purgatorio model or Sesame S27314 for Al thermal conductivity and LEOS for Au/Al release equation-of-state show good agreement with data after 15 ps. Discrepancy still exists at early time 0-15 ps, likely due to non-equilibrium conditions

Assessment of ion kinetic effects in shock-driven inertial confinement fusion implosions using fusion burn imaging

The significance and nature of ion kinetic effects in D3He-filled, shock-driven inertial confinement fusion implosions are assessed through measurements of fusion burn profiles. Over this series of experiments, the ratio of ion-ion mean free path to minimum shell radius (the Knudsen number, NK) was varied from 0.3 to 9 in order to probe hydrodynamic-like to strongly kinetic plasma conditions; as the Knudsen number increased, hydrodynamic models increasingly failed to match measured yields, while an empirically-tuned, first-step model of ion kinetic effects better captured the observed yield trends [Rosenberg et al., Phys. Rev. Lett. 112, 185001 (2014)]. Here, spatially resolved measurements of the fusion burn are used to examine kinetic ion transport effects in greater detail, adding an additional dimension of understanding that goes beyond zero-dimensional integrated quantities to one-dimensional profiles. In agreement with the previous findings, a comparison of measured and simulated burn profiles shows that models including ion transport effects are able to better match the experimental results. In implosions characterized by large Knudsen numbers (NK3), the fusion burn profiles predicted by hydrodynamics simulations that exclude ion mean free path effects are peaked far from the origin, in stark disagreement with the experimentally observed profiles, which are centrally peaked. In contrast, a hydrodynamics simulation that includes a model of ion diffusion is able to qualitatively match the measured profile shapes. Therefore, ion diffusion or diffusion-like processes are identified as a plausible explanation of the observed trends, though further refinement of the models is needed for a more complete and quantitative understanding of ion kinetic effects

Deep-Learning-based Fast and Accurate 3D CT Deformable Image Registration in Lung Cancer

Purpose: In some proton therapy facilities, patient alignment relies on two 2D orthogonal kV images, taken at fixed, oblique angles, as no 3D on-the-bed imaging is available. The visibility of the tumor in kV images is limited since the patient's 3D anatomy is projected onto a 2D plane, especially when the tumor is behind high-density structures such as bones. This can lead to large patient setup errors. A solution is to reconstruct the 3D CT image from the kV images obtained at the treatment isocenter in the treatment position. Methods: An asymmetric autoencoder-like network built with vision-transformer blocks was developed. The data was collected from 1 head and neck patient: 2 orthogonal kV images (1024x1024 voxels), 1 3D CT with padding (512x512x512) acquired from the in-room CT-on-rails before kVs were taken and 2 digitally-reconstructed-radiograph (DRR) images (512x512) based on the CT. We resampled kV images every 8 voxels and DRR and CT every 4 voxels, thus formed a dataset consisting of 262,144 samples, in which the images have a dimension of 128 for each direction. In training, both kV and DRR images were utilized, and the encoder was encouraged to learn the jointed feature map from both kV and DRR images. In testing, only independent kV images were used. The full-size synthetic CT (sCT) was achieved by concatenating the sCTs generated by the model according to their spatial information. The image quality of the synthetic CT (sCT) was evaluated using mean absolute error (MAE) and per-voxel-absolute-CT-number-difference volume histogram (CDVH). Results: The model achieved a speed of 2.1s and a MAE of <40HU. The CDVH showed that <5% of the voxels had a per-voxel-absolute-CT-number-difference larger than 185 HU. Conclusion: A patient-specific vision-transformer-based network was developed and shown to be accurate and efficient to reconstruct 3D CT images from kV images.Comment: 9 figure

Multifunctional platform based on electrospun nanofibers and plasmonic hydrogel. A smart nanostructured pillow for near-infrared light-driven biomedical applications

Multifunctional nanomaterials with the ability to respond to near-infrared (NIR) light stimulation are vital for the development of highly efficient biomedical nanoplatforms with a polytherapeutic approach. Inspired by the mesoglea structure of jellyfish bells, a biomimetic multifunctional nanostructured pillow with fast photothermal responsiveness for NIR light-controlled on-demand drug delivery is developed. We fabricate a nanoplatform with several hierarchical levels designed to generate a series of controlled, rapid, and reversible cascade-like structural changes upon NIR light irradiation. The mechanical contraction of the nanostructured platform, resulting from the increase of temperature to 42 °C due to plasmonic hydrogel-light interaction, causes a rapid expulsion of water from the inner structure, passing through an electrospun membrane anchored onto the hydrogel core. The mutual effects of the rise in temperature and water flow stimulate the release of molecules from the nanofibers. To expand the potential applications of the biomimetic platform, the photothermal responsiveness to reach the typical temperature level for performing photothermal therapy (PTT) is designed. The on-demand drug model penetration into pig tissue demonstrates the efficiency of the nanostructured platform in the rapid and controlled release of molecules, while the high biocompatibility confirms the pillow potential for biomedical applications based on the NIR light-driven multitherapy strategy

Beam mask and sliding window-facilitated deep learning-based accurate and efficient dose prediction for pencil beam scanning proton therapy

Purpose: To develop a DL-based PBSPT dose prediction workflow with high accuracy and balanced complexity to support on-line adaptive proton therapy clinical decision and subsequent replanning. Methods: PBSPT plans of 103 prostate cancer patients and 83 lung cancer patients previously treated at our institution were included in the study, each with CTs, structure sets, and plan doses calculated by the in-house developed Monte-Carlo dose engine. For the ablation study, we designed three experiments corresponding to the following three methods: 1) Experiment 1, the conventional region of interest (ROI) method. 2) Experiment 2, the beam mask (generated by raytracing of proton beams) method to improve proton dose prediction. 3) Experiment 3, the sliding window method for the model to focus on local details to further improve proton dose prediction. A fully connected 3D-Unet was adopted as the backbone. Dose volume histogram (DVH) indices, 3D Gamma passing rates, and dice coefficients for the structures enclosed by the iso-dose lines between the predicted and the ground truth doses were used as the evaluation metrics. The calculation time for each proton dose prediction was recorded to evaluate the method's efficiency. Results: Compared to the conventional ROI method, the beam mask method improved the agreement of DVH indices for both targets and OARs and the sliding window method further improved the agreement of the DVH indices. For the 3D Gamma passing rates in the target, OARs, and BODY (outside target and OARs), the beam mask method can improve the passing rates in these regions and the sliding window method further improved them. A similar trend was also observed for the dice coefficients. In fact, this trend was especially remarkable for relatively low prescription isodose lines. The dose predictions for all the testing cases were completed within 0.25s