Formulasi Pemupukan Berimbang Pada Tanaman Lada Di Bangka Belitung

Many factors believed affect the growth and yields of black pepper in Bangka Belitung. The low productivity of black pepper in the areas is mainly attributed to imbalanced manuring, poor management practices and disease incidence. To improve yields of the crop, farmers commonly use fertilizers despite the fact that the amounts and kind of nutrients added might not meet its requirement for optimum growth. A research was established to investigate effects of fertilizer compositions and rates on growth and yields of mature black pepper grown at Bangka, from January to December 2011. Treatments examined were composition of NPK fertilizers, 3 kinds of NPK (15:15:15, 12:12:17, and 12:8:20), consisting of three rates each (1.8, 2.4 and 3.0 kg/tree). The treatments were arranged in randomized block design with 3 replicates and plot size of 16 plants. Results revealed that application of 1.8 kg/tree was likely to be an adequate amount of fertilizer rate that should be added to give comparable growth and yields in black pepper. It means that the added ferlitizers was 25 percent lower than those of the recommended one as much as 2.4 kg of NPK 12:12:17/tree/year. As the recommended fertilizer hard to be obtained in a local place recently, the use of NPK 15:15:15 may therefore be suggested for black pepper growing in Bangka Belitung. For long term purpose, the use of 1.8 kg NPK 12:8:20/tree would however be a preferably added fertilizer in relation to the characteristics of the crop and agro-climatic condition of Bangka Belitung

Effect of Mycorrhiza and NPKmg Fertilizers on Growth and Production of Arabica Coffee

Mycorrhiza is a biological agent that could improve the efficiency of chemical fertilizers (inorganic) due to it can increase the availability of soil nutrients. The study aimed to evaluate the effectiveness of mycorrhiza and NPKMg fertilizers on growth and yield of coffee plants in the field. The research was carried out at KP. Pakuwon, Sukabumi, West Java, from January 2013 to November 2014. The treatments that examined in this study were 3 levels of mycorrhiza application (M0, without mycorrhizal fungi; M1, application of 200 spore/tree; and M2, application of 400 spore/tree), and 4 dosage of NPKMg fertilizers (F1, recommended dose, RD; F2, ¾ RD; F3, ½ RD, and F4, ¼ RD). The treatments were arranged in a ramdomized block design with 3 replications, and the plot size consisted of 4 coffee plants. The recommended dose of fertilizer is 140 g NPKMg/tree/years (40 g urea, 50 g SP-36, 30 g KCl, and 20 g kieserit). NPKMg fertilizers were applied two times, whereas mycorrhiza was given two months after the first application of NPKMg fertilizers. The observed parameters were vegetative characters (plant height, stem diameter, number of branch) and generative character (coffee yield) as well as the infection rates of mycorrizha on roots. The results showed that application of 400 spores of mycorrhizal fungi and 105 g NPKMg/tree/year exhibited the best growth of coffee plants until 15 months after planting (MAP). However, that combination was not significantly affected coffee production. Moreover, application of 200 and 400 spores of mycorrhizal fungi/tree combined with all dosage of NPKMg fertilizers revealed the same infection rates of mycorrizha on roots

Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models trained on Corrupted Data

We provide a framework for solving inverse problems with diffusion models learned from linearly corrupted data. Our method, Ambient Diffusion Posterior Sampling (A-DPS), leverages a generative model pre-trained on one type of corruption (e.g. image inpainting) to perform posterior sampling conditioned on measurements from a potentially different forward process (e.g. image blurring). We test the efficacy of our approach on standard natural image datasets (CelebA, FFHQ, and AFHQ) and we show that A-DPS can sometimes outperform models trained on clean data for several image restoration tasks in both speed and performance. We further extend the Ambient Diffusion framework to train MRI models with access only to Fourier subsampled multi-coil MRI measurements at various acceleration factors (R=2, 4, 6, 8). We again observe that models trained on highly subsampled data are better priors for solving inverse problems in the high acceleration regime than models trained on fully sampled data. We open-source our code and the trained Ambient Diffusion MRI models: https://github.com/utcsilab/ambient-diffusion-mri .Comment: Pre-print, work in progres

Mass-change And Geosciences International Constellation (MAGIC) expected impact on science and applications

Summary The joint ESA/NASA Mass-change And Geosciences International Constellation (MAGIC) has the objective to extend time series from previous gravity missions, including an improvement of accuracy and spatio-temporal resolution. The long-term monitoring of Earth’s gravity field carries information on mass-change induced by water cycle, climate change, and mass transport processes between atmosphere, cryosphere, oceans and solid Earth. MAGIC will be composed of two satellite pairs flying in different orbit planes. The NASA/DLR–led first pair (P1) is expected to be in a near-polar orbit around 500 km of altitude; while the second ESA–led pair (P2) is expected to be in an inclined orbit of 65–70 degrees at approximately 400 km altitude. The ESA–led pair P2 Next Generation Gravity Mission (NGGM) shall be launched after P1 in a staggered manner to form the MAGIC constellation. The addition of an inclined pair shall lead to reduction of temporal aliasing effects and consequently of reliance on de-aliasing models and post-processing. The main novelty of the MAGIC constellation is the delivery of mass-change products at higher spatial resolution, temporal (i.e. sub–weekly) resolution, shorter latency, and higher accuracy than GRACE and GRACE-FO. This will pave the way to new science applications and operational services. In this article, an overview of various fields of science and service applications for hydrology, cryosphere, oceanography, solid Earth, climate change and geodesy is provided. These thematic fields and newly enabled applications and services were analysed in the frame of the initial ESA Science Support activities for MAGIC. The analyses of MAGIC scenarios for different application areas in the field of geosciences confirmed that the double-pair configuration will significantly enlarge the number of observable mass-change phenomena by resolving smaller spatial scales with an uncertainty that satisfies evolved user requirements expressed by international bodies such as IUGG. The required uncertainty levels of dedicated thematic fields met by MAGIC unfiltered Level-2 products will benefit hydrological applications by recovering more than 90% of the major river basins worldwide at 260 km spatial resolution, cryosphere applications by enabling mass change signal separation in the interior of Greenland from those in the coastal zones and by resolving small-scale mass variability in challenging regions such as the Antarctic Peninsula, oceanography applications by monitoring meridional overturning circulation changes on time scales of years and decades, climate applications by detecting amplitude and phase changes of Terrestrial Water Storage (TWS) after 30 years in 64% and 56% of the global land areas and solid Earth applications by lowering the Earthquake detection threshold from magnitude 8.8 to magnitude 7.4 with spatial resolution increased to 333 km.</jats:p

IDSS: deformation invariant signatures for molecular shape comparison

<p>Abstract</p> <p>Background</p> <p>Many molecules of interest are flexible and undergo significant shape deformation as part of their function, but most existing methods of molecular shape comparison (MSC) treat them as rigid bodies, which may lead to incorrect measure of the shape similarity of flexible molecules.</p> <p>Results</p> <p>To address the issue we introduce a new shape descriptor, called Inner Distance Shape Signature (IDSS), for describing the 3D shapes of flexible molecules. The inner distance is defined as the length of the shortest path between landmark points within the molecular shape, and it reflects well the molecular structure and deformation without explicit decomposition. Our IDSS is stored as a histogram which is a probability distribution of inner distances between all sample point pairs on the molecular surface. We show that IDSS is insensitive to shape deformation of flexible molecules and more effective at capturing molecular structures than traditional shape descriptors. Our approach reduces the 3D shape comparison problem of flexible molecules to the comparison of IDSS histograms.</p> <p>Conclusion</p> <p>The proposed algorithm is robust and does not require any prior knowledge of the flexible regions. We demonstrate the effectiveness of IDSS within a molecular search engine application for a benchmark containing abundant conformational changes of molecules. Such comparisons in several thousands per second can be carried out. The presented IDSS method can be considered as an alternative and complementary tool for the existing methods for rigid MSC. The binary executable program for Windows platform and database are available from <url>https://engineering.purdue.edu/PRECISE/IDSS</url>.</p

Using diffusion distances for flexible molecular shape comparison

<p>Abstract</p> <p>Background</p> <p>Many molecules are flexible and undergo significant shape deformation as part of their function, and yet most existing molecular shape comparison (MSC) methods treat them as rigid bodies, which may lead to incorrect shape recognition.</p> <p>Results</p> <p>In this paper, we present a new shape descriptor, named Diffusion Distance Shape Descriptor (DDSD), for comparing 3D shapes of flexible molecules. The diffusion distance in our work is considered as an average length of paths connecting two landmark points on the molecular shape in a sense of inner distances. The diffusion distance is robust to flexible shape deformation, in particular to topological changes, and it reflects well the molecular structure and deformation without explicit decomposition. Our DDSD is stored as a histogram which is a probability distribution of diffusion distances between all sample point pairs on the molecular surface. Finally, the problem of flexible MSC is reduced to comparison of DDSD histograms.</p> <p>Conclusions</p> <p>We illustrate that DDSD is insensitive to shape deformation of flexible molecules and more effective at capturing molecular structures than traditional shape descriptors. The presented algorithm is robust and does not require any prior knowledge of the flexible regions.</p