Interaction effect between mineral zinc-nitrogen fertilization mixture and organic fertilization as compost on yield, nutrients uptake of rice and some soil properties

To study the effect of organic fertilization as compost (20 m3 fed-1), mineral Zinc-Nitrogen fertilization mixture (three Zinc levels (0, 8 and 16 kg Zn fed-1) and three nitrogen rates (0, 30 and 60 kg N fed-1 were mixed alternately) on growth, grain and straw yields, N, P and K uptake for rice crop (Oryza sativa), variety Giza 178, two field trials at El-Serw Agricultural Research Station, Damietta governorate were conducted through summer seasons of 2015 and 2016. Plant height, dry matter, grain and straw yields also, N, P and K-uptake in grain and straw yields increased with increasing levels of zinc and nitrogen fertilization. Moreover, use organic fertilization as compost gave the highest values of the previous parameters. Applying of 16 kg Zn fed-1 + 60 kg N fed-1 with 20 m3 compost fed-1 gave the highest plant height, dry matter, grain and straw yields and N, P and K-uptake in grain and straw. Therefore, it preferably adds 16 kg Zn fed-1 + 60 kg N fed-1 with 20 m3 compost fed-1 to produce a high crop of rice under saline soil condition in North Delta. Concerning to soil properties after rice harvest, mixture 16 kg Zn fed-1 + 60 kg N fed-1 with 20 m3 compost fed-1 surpassed all other treatments in improving soil properties, since available NPK and organic matter content had increased while soil EC and pH in the root zone was decreased

The Developing Human Connectome Project Neonatal Data Release

The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied in utero and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods. Imaging data are complemented by rich demographic, clinical, neurodevelopmental, and genomic information. The project is now releasing a large set of neonatal data; fetal data will be described and released separately. This release includes scans from 783 infants of whom: 583 were healthy infants born at term; as well as preterm infants; and infants at high risk of atypical neurocognitive development. Many infants were imaged more than once to provide longitudinal data, and the total number of datasets being released is 887. We now describe the dHCP image acquisition and processing protocols, summarize the available imaging and collateral data, and provide information on how the data can be accessed

On the utility of input selection and pruning for financial distress prediction models

Analyzes the use of linear and neural network models for financial distress classification, with emphasis on the issues of input variable selection and model pruning. A data-driven method for selecting input variables (financial ratios, in this case) is proposed. A case study involving 60 British firms in the period 1997-2000 is used for illustration. It is shown that the use of the Optimal Brain Damage pruning technique can considerably improve the generalization ability of a neural model. Moreover, the set of financial ratios obtained with the proposed selection procedure is shown to be an appropriate alternative to the ratios usually employed by practitioners

Ratio selection for classification models

This paper is concerned with the selection of inputs for classification models based on ratios of measured quantities. For this purpose, all possible ratios are built from the quantities involved and variable selection techniques are used to choose a convenient subset of ratios. In this context, two selection techniques are proposed: one based on a pre-selection procedure and another based on a genetic algorithm. In an example involving the financial distress prediction of companies, the models obtained from ratios selected by the proposed techniques compare favorably to a model using ratios usually found in the financial distress literature

Variable selection for financial distress classification using a genetic algorithm

This paper is concerned with the use of a genetic algorithm to select financial ratios for corporate distress classification models. For this purpose, the fitness value associated to a set of ratios is made to reflect the requirements of maximizing the amount of information available for the model and minimizing the collinearity between the model inputs. A case study involving 60 failed and continuing British firms in the period 1997-2000 is used for illustration. The classification model based on ratios selected by the genetic algorithm compares favorably with a model employing ratios usually found in the financial distress literature

Giant mesenteric teratoma in a 6 month-old

Objective: We report a case of mesenteric teratoma in a healthy 6 months old baby girl. The purpose of this report is to familiarize the pediatric surgery doctors with the characteristic appearance of this tumor, which is rare. Method: Case report and review of the English-language literature (using PubMed, Ovid, and Proquest databases). Results: Case of mesenteric teratoma occurred in an infant girl to be reported in the English-language literature. Conclusion: Mesenteric teratoma is an uncommon tumor that included all three embryonic layers. Although the presurgical diagnosis might be difficult in some cases, mesenteric teratoma must be kept in the differential of abdominal masses in children. The present case highlights the importance of considering mesenteric teratoma in the clinical and pathological differential diagnosis of intra-abdominal/retroperitoneal masses. Complete Surgical excision is almost always curative