Identification of a Disease on Cocoa Caused by Fusariumin Sulawesi

A disease presumed to be caused by Fusarium was observed in cocoa open fields with few or without shade trees. Within the population of cocoa trees in the field, some trees had died, some had yellowing leaves and dieback, and the others were apparently healthy. In order to demonstrate Fusarium species as the causal pathogen and to obtain information concerning the incidence of the disease, its distribution and its impact on sustainability of cocoa, isolation of the pathogen, inoculation of cocoa seedlings with isolates and a survey of disease has been conducted. Fusarium was isolated from roots and branches, and inoculated onto cocoa seedlings (one month old) via soil. Symptoms appeared within 3-4 weeks after infection. These symptoms consisted of yellowing of leaves beginning from the bottom until the leaves falldown, and browning internal of vascular tissue. Darkened vascular traces in the petiole characteristic of vascularstreak dieback infection were absent. The occurrence of Fusarium in the field was characterized by the absence of obvious signs of fungal infestation on root of infected trees, yellowing of leaves on twigs, dieback, and tree mortality in severe infestations. Disease incidence could reach 77% and in this situation it was difficult for trees recover from heavy infections or to be regenerated in the farm. The study proves that Fusarium is a pathogen causing dieback and the disease is called as Fusarium vascular dieback (FVD). Its development is apparently enhanced by dry conditions in the field

Motivasi Kerja Karyawan Housekeeping di Hotel Zaira Pekanbaru

This research was conducted at Hotel Zaira Pekanbaru. This study aims to determine working motivation of housekeeping at Zaira Hotel. This study aims a). To analyze the factors that influence the working activity of Housekeeping at Zaira Pekanbaru Hotel. b). To know what efforts were made by the company in increasing working motivation of Housekeeping at Zaira Pekanbaru Hotel. The sample used in this study were 9 respondents (people). This research useddescriptive analysis method that is a technique to describes or depicts something, either in the form of drawings or photographs obtained from field data or researcher describes research results with pictures and can also mean to explain with words in thereport for complementarity Boundary problem in this study, the author discusses only working motivation of Housekeeping at Zaira Pekanbaru Hotel and any attempts by the company to improve working motivation of Housekeeping at Zaira Pekanbaru Hotel. Apart from these aspects of the author will not be discussed. The identification of this research to determine how is the working motivation of Housekeeping at Zaira Pekanbaru Hotel? and What attempts did implement by the company to improve it? Keywords: Phisical needs, Security needs, Social needs, Esteem needs, self actualization needs

Preparation and characterization of magnetite (Fe3O4) nanoparticles By Sol-Gel method

The magnetite (Fe3O4) nanoparticles were successfully synthesized and annealed under vacuum at different temperature. The Fe3O4 nanoparticles prepared via sol-gel assisted method and annealed at 200-400ºC were characterized by Fourier Transformation Infrared Spectroscopy (FTIR), X-ray Diffraction spectra (XRD), Field Emission Scanning Electron Microscope (FESEM) and Atomic Force Microscopy (AFM). The XRD result indicate the presence of Fe3O4 nanoparticles, and the Scherer`s Formula calculated the mean particles size in range of 2-25 nm. The FESEM result shows that the morphologies of the particles annealed at 400ºC are more spherical and partially agglomerated, while the EDS result indicates the presence of Fe3O4 by showing Fe-O group of elements. AFM analyzed the 3D and roughness of the sample; the Fe3O4 nanoparticles have a minimum diameter of 79.04 nm, which is in agreement with FESEM result. In many cases, the synthesis of Fe3O4 nanoparticles using FeCl3 and FeCl2 has not been achieved, according to some literatures, but this research was able to obtained Fe3O4 nanoparticles base on the characterization results

Aplikasi Pewarnaan Graf dengan Algoritma Recursive Largest First pada Penjadwalan Mata Kuliah

Penelitian ini merupakan penelitian terapan yang menggunakan algoritma Recursive Largest First (RLF) pada penjadwalan mata kuliah di salah satu program studi pada salah satu universitas di Makassar. Penjadwalan mata kuliah dilakukan dengan merepresentasikan masalah ke dalam bentuk graf berdasarkan data yang diperoleh dengan menganggap mata kuliah sebagai simpul dan dosen sebagai sisi. Dibentuk matriks ketetanggaan dari graf yang terbentuk, kemudian simpulya diwarnai menggunakan algoritma RLF, sehingga diperoleh jadwal kuliah. Penjadwalan mata kuliah menggunakan pewarnaan simpul graf dengan algoritma RLF digunakan VBA for Microsoft Excel 2016 sebagai alat bantu dalam pewarnaan simpul graf. Diperoleh 102 simpul dengan 25 warna yang menunjukkan bahwa dibutuhkan 25 waktu perkuliahan. Jumlah simpul yang diwarnai dengan warna yang sama  6 simpul artinya dalam setiap slot dibutuhkan maksimal 6 ruangan perkuliahan. Mata kuliah yang terjadwal dijamin bahwa tidak ada jadwal dosen yang bersamaan untuk setiap mata kuliah yang diajarkan.Kata Kunci: Graf, Recursive Largest First, Jadwal Kuliah This research discusses the colorization of graph vertex using algorithm of Recursive Largest First (RLF) in scheduling courses in one of the study programs at one of the universities in Makassar. Representation of problems in scheduling courses was done by making it in the shape of the graph assuming subjects as vertex and the presence of the same lecturers teach different courses as a side. The steps in solving a problem that was mapping the lectures data, representing the lectures data as a graph, forming adjacency matrix, coloring the graph vertex using algorithm of RLF, so that the schedule was retrieved. Scheduling of courses using the colorization of graph vertex with algorithm of RLF as well as the help of VBA for Microsoft Excel 2016 at Faculty of Animal Husbandry obtained 102 vertices with 25 colors indicates that it takes 25 of lecture schedules. The number of vertices that were colored with the same color ≤ 6 vertices meaning in every slot needed 6 lecture rooms in maximum. Scheduled courses are guaranteed that no schedule conflicts for each lecturer of courses taught.Keywords: Graph, Recursive Largest First, Lecture Schedules

Learning to segment when experts disagree

Recent years have seen an increasing use of supervised learning methods for segmentation tasks. However, the predictive performance of these algorithms depend on the quality of labels, especially in medical image domain, where both the annotation cost and inter-observer variability are high. In a typical annotation collection process, different clinical experts provide their estimates of the “true” segmentation labels under the influence of their levels of expertise and biases. Treating these noisy labels blindly as the ground truth can adversely affect the performance of supervised segmentation models. In this work, we present a neural network architecture for jointly learning, from noisy observations alone, both the reliability of individual annotators and the true segmentation label distributions. The separation of the annotators’ characteristics and true segmentation label is achieved by encouraging the estimated annotators to be maximally unreliable while achieving high fidelity with the training data. Our method can also be viewed as a translation of STAPLE, an established label aggregation framework proposed in Warfield et al. [1] to the supervised learning paradigm. We demonstrate first on a generic segmentation task using MNIST data and then adapt for usage with MRI scans of multiple sclerosis (MS) patients for lesion labelling. Our method shows considerable improvement over the relevant baselines on both datasets in terms of segmentation accuracy and estimation of annotator reliability, particularly when only a single label is available per image. An open-source implementation of our approach can be found at https://github.com/UCLBrain/MSLS

Plant residue based-composts applied in combination with Trichoderma asperellum improve cacao seedling growth in soil derived from nickel mine area

Cacao is widely grown in Sulawesi close to areas of nickel (Ni) mines indicating a possibility that the plant is affected by this heavy metal. By using soil collected from a Ni mining area, we evaluated three compositions of composted plant residues consisting of firstly gliricidia, billy goat, and rice straw, secondly gliricidia, stalk of palm oil fruit, and rice straw, and thirdly gliricidia, coconut husk, and rice straw, without and with addition of Trichoderma asperellum, in supporting growth of cacao seedling. Treatment with the respective compost types without any addition of T. asperellum caused an increase of seedling height by 18.9%, 28.5%, and 43.8%, stomata opening area by 17.2%, 4.3%, and 41.3%, stomata number by 13.4%, 22.7%, and 14.3%, and leaf Ni content by 3.8%, 12.8%, and 48.8% respectively. Following treatment with the three compost types included T. Asperellum, the increase of seedling height was 36.5%, 45.3%, and 54.7%, stomata opening area 15.9%, 21.3%, and 53.5%, stomata number 5.4%, 7.1%, and 0.0% and leaf Ni content 25.1%, 87.8%, and 161,4% respectively. Leaf analysis indicated that nitrogen content was increased when treated by the combination of composted plant residues and T. asperellum, potassium was increased in all treatments without T. asperellum, while phosphorus was decreased in all treated seedlings. These data suggest that one cause of cacao seedling growth improvement in soil containing Ni by composted plant residues and its combination with T. asperellum was the increase of Ni levels in leaves. Composts treatment could therefore potentially be used for cacao field application around Ni mining areas

Budget line items for immunization in 33 African countries

When seeking to ensure financial sustainability of a health programme, existence of a line item in the Ministry of Health (MOH) budget is often seen as an essential, first step. We used immunization as a reference point for cross-country comparison of budgeting methods in Sub-Saharan African countries. Study objectives were to (1) verify the number and types of budget line items for immunization services, (2) compare budget execution with budgeted amounts and (3) compare values with annual immunization expenditures reported to WHO and UNICEF. MOH budgets for 2016 and/or 2017 were obtained from 33 countries. Despite repeated attempts, budgets could not be retrieved from five countries (Chad, Eritrea, Guinea Bissau, Somalia and South Sudan), and we were only able to gather budget execution from eight countries. The number of immunization line items ranged between 0 and 42, with a median of eight. Immunization donor funding was included in 10 budgets. Differences between budgeted amounts and expenditures reported to WHO and UNICEF were greater than 50% in 66% of countries. Immunization budgets per child in the birth cohort ranged from US$1.37 (Democratic Republic of Congo) to US$67.51 (Central African Republic), with an average of US$10.05. Out of the total Government health budget, immunization comprised between 0.04% (Madagascar) and 5.67% (Benin), with an average of 1.98% across the countries, when excluding on-budget donor funds. It was challenging to obtain MOH budgets in many countries and it was largely impossible to access budget execution reports, preventing us from assessing budget credibility. Large differences between budgets and expenditures reported to WHO and UNICEF are likely due to inconsistent interpretations of reporting requirements, diverse approaches to reporting donor funds, challenges in extracting the relevant information from public financial management systems and broader issues of public financial management capacity in MOH staff

Robust Fusion of Probability Maps

International audienceThe fusion of probability maps is required when trying to analyse a collection of image labels or probability maps produced by several segmentation algorithms or human raters. The challenge is to weight properly the combination of maps in order to reflect the agreement among raters, the presence of outliers and the spatial uncertainty in the consensus. In this paper, we address several shortcomings of prior work in continuous label fusion. We introduce a novel approach to jointly estimate a reliable consensus map and assess the production of outliers and the confidence in each rater. Our probabilistic model is based on Student's t-distributions allowing local estimates of raters' performances. The introduction of bias and spatial priors leads to proper rater bias estimates and a control over the smoothness of the consensus map. Image intensity information is incorporated by geodesic distance transform for binary masks. Finally, we propose an approach to cluster raters based on variational boosting thus producing possibly several alternative consensus maps. Our approach was successfully tested on the MICCAI 2016 MS lesions dataset, on MR prostate delineations and on deep learning based segmentation predictions of lung nodules from the LIDC dataset

A Consistency Check of Concrete Compressive Strength using Pearson’s Correlation Coefficient

The efficiency of the concrete ready mix service provider is undoubtedly and has become a widespread trend among contractors in which facilitates and eliminated a large budget surplus in maintenance, operating costs and is preferred as it reflects more efficient asset utilization. However, the quality assurance of concrete supplied is always raised associated with the inconsistencies of concrete compressive strength at the age of 28 days. The objective(s) of this study are to determine the correlations between the compressive strength of ready mix concrete, to evaluate the consistencies of the results and to identify the irregular sources that lead to the inconsistencies. Based on the compressive strength values obtained from the existing experimental data using different concrete mixes from the batching plant, a statistical analysis was conducted. A total of 90 concrete cubes specimens were attained from 15 concrete batches. A correlation analysis was conducted using the Pearson Correlation calculation to check the consistency of concrete compressive strength. The calculation showed the Pearson correlation coefficient of this study is +0.990. This indicated that there are significant linear relationship exists between the concrete compressive strength and the density of concrete batches which is positively high. In conclusion, the analysis reveals that the design of ready mix concrete compressive strength is in high consistencies and acceptable in practices for the proposed mix design to the contractor. Doi: 10.28991/cej-2021-03091672 Full Text: PD