Toward a constitutive model for cure dependent modulus of a high temperature epoxy during the cure

A constitutive model, based on Kohlrausch-Williams-Watts (KWW) equations, was developed to simulate the evolution of the dynamic relaxation modulus during the cure of a "high temperature' epoxy. The basic assumption of the modelling methodology proposed is the equivalence of the mechanisms underlying the evolution of the glass transition temperature and the relaxation time shift during the cure, leading to the use of a common potential function. This assumption is verified by the comparison of normalized glass transition data and principal relaxation times, which have been found to follow a single master curve. Results show satisfactory agreement between experimental data and model prediction over the range of chemical conversion considered

Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images

Segmentation of the heart in cardiac cine MR is clinically used to quantify cardiac function. We propose a fully automatic method for segmentation and disease classification using cardiac cine MR images. A convolutional neural network (CNN) was designed to simultaneously segment the left ventricle (LV), right ventricle (RV) and myocardium in end-diastole (ED) and end-systole (ES) images. Features derived from the obtained segmentations were used in a Random Forest classifier to label patients as suffering from dilated cardiomyopathy, hypertrophic cardiomyopathy, heart failure following myocardial infarction, right ventricular abnormality, or no cardiac disease. The method was developed and evaluated using a balanced dataset containing images of 100 patients, which was provided in the MICCAI 2017 automated cardiac diagnosis challenge (ACDC). The segmentation and classification pipeline were evaluated in a four-fold stratified cross-validation. Average Dice scores between reference and automatically obtained segmentations were 0.94, 0.88 and 0.87 for the LV, RV and myocardium. The classifier assigned 91% of patients to the correct disease category. Segmentation and disease classification took 5 s per patient. The results of our study suggest that image-based diagnosis using cine MR cardiac scans can be performed automatically with high accuracy.Comment: Accepted in STACOM Automated Cardiac Diagnosis Challenge 201

Evaluation of Argentine wild sunflower biotypes for drought stress during reproductive stage

As in several regions where sunflower production has moved to areas with limiting water availability, the search for water-stress tolerant genotypes has been intensified. Helianthus annuus ssp. annuus L. constitutes a potential genetic resource because it has naturalized in the semi-arid zone of central Argentina. The assessment of these genetic materials for water deficit tolerance is of interest because they may represent a source of genes for drought tolerance, useful to sunflower breeding. Drought resistant genotypes should be achieved using easily identified phenotypic traits. Parameters like leaf area are widely used to characterize the performance under stress. Leaf temperature is an easily measured physiological parameter that allows an indirect estimate of plant transpiration and is well correlated with water availability. Relative water content indicates the ability to retain water from the soil and expresses plant osmotic adjustment ability. Specific leaf area is a morphological parameter related to leaf thickness. The objectives of this study were to evaluate the drought tolerance of Argentine wild sunflower biotypes and identify morphological and physiological traits expressing differences between stressed biotypes. Wild biotypes were evaluated during three years in the experimental field of the Agronomy Department, Universidad Nacional del Sur, Argentina. Groups of 10-15 plants of each biotype were evaluated under two water conditions, drought (deficit supply) with drip irrigation to cover a half of the potential evapotranspiration during flowering, or with optimal water supply. Soil surface was covered with black polyethylene to exclude rainwater. Wild sunflower comprised five biotypes collected from different habitats in the semiarid region of Argentina. Crosses between the wild biotypes and inbred lines were also included every year. Inbred lines and a commercial hybrid (DK4000) were used as controls. Recorded traits were: plant height, stem diameter, petiole length, leaf area, leaf number, head number and reproductive surface. Leaf parameters were: relative water content (RWC), specific leaf area (SLA), canopy temperature (CT), and chlorophyll content (SPAD). A susceptibility index (SI) was obtained to compare the performance under water stress with that obtained in optimal conditions. Biotype evaluation and parameter characterization were performed separately for each year because water stress levels were different. Wild sunflower responses to water stress were different for all parameters among biotypes, except for plant height and petiole length. Wild biotypes had better RWC and lower SLA than cultivated biotypes. Under water stress wild biotypes showed higher values and greater range of RWC and SPAD than cultivated sunflower. Susceptibility index showed that leaf area of wild sunflower biotypes had lower stress susceptibility than cultivated sunflowers. Nevertheless, wild biotypes showed increased susceptibility to the remaining plant morpho-physiological parameters. RWC and CT had a significant relationship in wild sunflower biotypes under water stress. Drought tolerant type identification was complex because of the complex responses among parameters. Wild biotypes might have a physiological mechanism which allows higher RCA than cultivated sunflower under drought stress. The lower SLA under water deficit could be attributed to a greater leaf thickness and could be related with RCA. Lower leaf area reduction under stress in wild sunflower is an interesting trait that might be used to improve cultivated sunflower. As the RWC is related with CT under stress in wild biotypes, this trait evaluation allows the fast examination of a high number of plants. The assessment of Argentina wild sunflower biotypes for traits associated with drought tolerance has not yet been done. Their identification could increase sunflower crop yield under drought in semiarid regions.Fil: Fernández Moroni, Ivana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Agronomía; ArgentinaFil: Fraysse, M.. Universidad Nacional del Sur. Departamento de Agronomía; ArgentinaFil: Presotto, Alejandro Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Agronomía; ArgentinaFil: Cantamutto, Miguel Ángel. Instituto Nacional de Tecnología Agropecuaria; Argentin

Restrukturisasi Kredit oleh PT. Bank Rakyat Indonesia (Persero) Tbk Cabang Kawi Malang terhadap Perusahaan Otobus Putra Mulia Berkedudukan di Kabupaten Malang (Studi Implementasi Surat Keputusan Direksi PT. Bank Rakyat Indonesia No: S.94–dir/adk/12/2005 T

Artikel ini membahas mengenai proses restrukturisasi kredit oleh PT. Bank Rakyat Indonesia (Persero) Tbk Cabang Kawi Malang terhadap Perusahaan Otobus Putra Mulia berkedudukan di Kabupaten Malang. Penulis hendak meneliti tahap-tahap restrukturisasi kredit, hambatan, dan upaya tentang Restrukturisasi Kredit. Berdasarkan pada Surat Keputusan Direksi PT. Bank Rakyat Indonesia NO:S.94– DIR/ADK/12/2005 Tanggal 30 Desember 2005 Tentang Restrukturisasi Kredit, Restrukturisasi kredit merupakan upaya perbaikan yang dilakukan bank dalam kegiatan perkreditan terhadap debitur yang mengalami kesulitan untuk memenuhi kewajibannya. Pelaksanaan restrukturisasi kredit yang dilakukan PT. Bank Rakyat Indonesia (Persero) Tbk Cabang Kawi Malang terhadap Perusahaan Otobus Putra Mulia meliputi tahap-tahap yaitu prakarsa restrukturisasi kredit, negosiasi, analisis dan evaluasi, putusan restrukturisasi, dokumentasi restrukturisasi, dan monitoring.Adapun materi yang direstrukturisasi terhadap debitur yaitu Perubahan tingkat suku bunga, penjadwalan kembali dan pengelolaan/pengambilalihan asset debitur sesuai ketentuan yang berlaku Hambatan maupun upaya dalam restrukturisasi kredit adalah didalam setiap tahapan restrukturisasi kredit tersebut

Percepcija faktora koji doprinose školskom neuspehu od strane budućih nastavnika i njihova povezanost sa prethodnim ličnim iskustvom uspeha u školi

Factors that pre-service class and subject teachers perceive as significant in explaining the occurrence of school failure were examined using mixed methods strategy. The qualitative phase of the study (N = 74) revealed that pre-service teachers recognize a wide range of causes for school failure (16 distinctive categories). The relative significance of the causes was established in the subsequent quantitative phase. The Scale of school failure causes was constructed, applied to 408 pre-service teachers and subjected to exploratory factor analysis, which pointed to the three latent groups of causes explaining 43% of variance. The lack of ability and motivation in students (1st factor) and the lack of educational support (2nd factor) were perceived as highly contributing to school failure, while moderate importance was attributed to the causes related to family and social context (3rd factor). Compared to pre-service subject teachers, pre-service class teachers were more willing to recognize the teachers' responsibility for the occurrence of school failure. Pre-service teachers' perceptions of different factors were related to prior experiences of school success.Faktori koje budući nastavnici razredne i predmetne nastave opažaju kao značajne za pojavu školskog neuspeha su proučavani pomoću miks metodske strategije. U kvalitativnoj fazi istraživanja (N = 74) se pokazalo da budući nastavnici razredne i predmetne nastave prepoznaju brojne uzroke školskog neuspeha (16 različitih kategorija). Relativni značaj ovih uzroka je ispitan u narednoj, kvantitativnoj fazi. Konstruisana je skala uzroka školskog neuspeha i zadata uzorku od 408 budućih nastavnika razredne i predmetne nastave, a zatim su eksplorativnom faktorskom analizom identifikovana tri latentna faktora koji objašnjavaju 43 % varijanse. Nedostatak sposobnosti i motivacije (1. faktor) i nedostatak obrazovne podrške (2. faktor) su opaženi kao faktori koji najviše doprinose školskom neuspehu, dok se umereni značaj pridaje razlozima koji su povezani sa porodičnim i socijalnim kontekstom (3. faktor). U poređenju sa budućim nastavnicima predmetne nastave, budući nastavnici razredne nastave pokazuju veću spremnost da prepoznaju odgovornost nastavnika za školski neuspeh. Percepcija značaja različitih faktora od strane budućih nastavnika je povezana sa njihovim ranijim iskustvima školskog uspeha

Evaluation of Rope Shovel Operators in Surface Coal Mining Using a Multi-Attribute Decision-Making Model

Rope shovels are used to dig and load material in surface mines. One of the main factors that influence the productivity and energy consumption of rope shovels is the performance of the operator. Existing methods of evaluating operator performance do not consider the relationship between production rate and energy consumption. This thesis presents a method for evaluating rope shovel operators using the Multi-Attribute Decision-Making (MADM) model. Data used in this research were collected from an operating surface coal mine in the southern United States. The MADM model used in this research consists of attributes, their weights of importance, and alternatives. Shovel operators are considered the alternatives in the MADM model. The energy consumption model was developed with multiple regression analysis, and its variables are included in the MADM model as attributes. Formulation of the production rate model is already known, and thus determining the attributes that have a significant influence is straightforward. Preferences with respect to min/max of the defined attributes were obtained with multi-objective optimization. Multi-objective optimization was performed with the overall goal of minimizing energy consumption and maximizing production rate. Weights of importance of the attributes were determined by using the Analytical Hierarchy Process (AHP). The overall evaluation of operators was performed by using one of the MADM models, PROMETHEE II. The research presented here may be used by mining professionals to help evaluate the performance of rope shovel operators in surface mining

Fatigue delamination behaviour of unidirectional carbon fibre/epoxy laminates reinforced by Z-Fiber® pinnin

-Pin reinforced carbon-fibre epoxy laminates were tested under Mode I and Mode II conditions, both quasi-statically and in fatigue. Test procedures were adapted from existing standard or pre-standard tests. Samples containing 2% and 4% areal densities of carbon-fibre Z-pins (0.28mm diameter) were compared with unpinned laminates. Quasi-static tests under displacement control yielded a dramatic increase of the apparent delamination resistance. Specimens with 2% pin density failed in Mode I at loads 170N, equivalent to an apparent GIC of 2kJ/m2. Fatigue testing under load control showed that the presence of the through- thickness reinforcement slowed down fatigue delamination propagation

Coronary Artery Centerline Extraction in Cardiac CT Angiography Using a CNN-Based Orientation Classifier

Coronary artery centerline extraction in cardiac CT angiography (CCTA) images is a prerequisite for evaluation of stenoses and atherosclerotic plaque. We propose an algorithm that extracts coronary artery centerlines in CCTA using a convolutional neural network (CNN). A 3D dilated CNN is trained to predict the most likely direction and radius of an artery at any given point in a CCTA image based on a local image patch. Starting from a single seed point placed manually or automatically anywhere in a coronary artery, a tracker follows the vessel centerline in two directions using the predictions of the CNN. Tracking is terminated when no direction can be identified with high certainty. The CNN was trained using 32 manually annotated centerlines in a training set consisting of 8 CCTA images provided in the MICCAI 2008 Coronary Artery Tracking Challenge (CAT08). Evaluation using 24 test images of the CAT08 challenge showed that extracted centerlines had an average overlap of 93.7% with 96 manually annotated reference centerlines. Extracted centerline points were highly accurate, with an average distance of 0.21 mm to reference centerline points. In a second test set consisting of 50 CCTA scans, 5,448 markers in the coronary arteries were used as seed points to extract single centerlines. This showed strong correspondence between extracted centerlines and manually placed markers. In a third test set containing 36 CCTA scans, fully automatic seeding and centerline extraction led to extraction of on average 92% of clinically relevant coronary artery segments. The proposed method is able to accurately and efficiently determine the direction and radius of coronary arteries. The method can be trained with limited training data, and once trained allows fast automatic or interactive extraction of coronary artery trees from CCTA images.Comment: Accepted in Medical Image Analysi