Parallel multiple instance learning for extremely large histopathology image analysis.

Science.gov (United States)

Xu, Yan; Li, Yeshu; Shen, Zhengyang; Wu, Ziwei; Gao, Teng; Fan, Yubo; Lai, Maode; Chang, Eric I-Chao

2017-08-03

Histopathology images are critical for medical diagnosis, e.g., cancer and its treatment. A standard histopathology slice can be easily scanned at a high resolution of, say, 200,000×200,000 pixels. These high resolution images can make most existing imaging processing tools infeasible or less effective when operated on a single machine with limited memory, disk space and computing power. In this paper, we propose an algorithm tackling this new emerging "big data" problem utilizing parallel computing on High-Performance-Computing (HPC) clusters. Experimental results on a large-scale data set (1318 images at a scale of 10 billion pixels each) demonstrate the efficiency and effectiveness of the proposed algorithm for low-latency real-time applications. The framework proposed an effective and efficient system for extremely large histopathology image analysis. It is based on the multiple instance learning formulation for weakly-supervised learning for image classification, segmentation and clustering. When a max-margin concept is adopted for different clusters, we obtain further improvement in clustering performance.

Feature selection is the ReliefF for multiple instance learning

NARCIS (Netherlands)

Zafra, A.; Pechenizkiy, M.; Ventura, S.

2010-01-01

Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature selection techniques have been proposed for the traditional settings, where each instance is expected to have a label. In

An instance theory of associative learning.

Science.gov (United States)

Jamieson, Randall K; Crump, Matthew J C; Hannah, Samuel D

2012-03-01

We present and test an instance model of associative learning. The model, Minerva-AL, treats associative learning as cued recall. Memory preserves the events of individual trials in separate traces. A probe presented to memory contacts all traces in parallel and retrieves a weighted sum of the traces, a structure called the echo. Learning of a cue-outcome relationship is measured by the cue's ability to retrieve a target outcome. The theory predicts a number of associative learning phenomena, including acquisition, extinction, reacquisition, conditioned inhibition, external inhibition, latent inhibition, discrimination, generalization, blocking, overshadowing, overexpectation, superconditioning, recovery from blocking, recovery from overshadowing, recovery from overexpectation, backward blocking, backward conditioned inhibition, and second-order retrospective revaluation. We argue that associative learning is consistent with an instance-based approach to learning and memory.

Multi-instance dictionary learning via multivariate performance measure optimization

KAUST Repository

Wang, Jim Jing-Yan

2016-12-29

The multi-instance dictionary plays a critical role in multi-instance data representation. Meanwhile, different multi-instance learning applications are evaluated by specific multivariate performance measures. For example, multi-instance ranking reports the precision and recall. It is not difficult to see that to obtain different optimal performance measures, different dictionaries are needed. This observation motives us to learn performance-optimal dictionaries for this problem. In this paper, we propose a novel joint framework for learning the multi-instance dictionary and the classifier to optimize a given multivariate performance measure, such as the F1 score and precision at rank k. We propose to represent the bags as bag-level features via the bag-instance similarity, and learn a classifier in the bag-level feature space to optimize the given performance measure. We propose to minimize the upper bound of a multivariate loss corresponding to the performance measure, the complexity of the classifier, and the complexity of the dictionary, simultaneously, with regard to both the dictionary and the classifier parameters. In this way, the dictionary learning is regularized by the performance optimization, and a performance-optimal dictionary is obtained. We develop an iterative algorithm to solve this minimization problem efficiently using a cutting-plane algorithm and a coordinate descent method. Experiments on multi-instance benchmark data sets show its advantage over both traditional multi-instance learning and performance optimization methods.

Multi-instance dictionary learning via multivariate performance measure optimization

KAUST Repository

Wang, Jim Jing-Yan; Tsang, Ivor Wai-Hung; Cui, Xuefeng; Lu, Zhiwu; Gao, Xin

2016-01-01

The multi-instance dictionary plays a critical role in multi-instance data representation. Meanwhile, different multi-instance learning applications are evaluated by specific multivariate performance measures. For example, multi-instance ranking reports the precision and recall. It is not difficult to see that to obtain different optimal performance measures, different dictionaries are needed. This observation motives us to learn performance-optimal dictionaries for this problem. In this paper, we propose a novel joint framework for learning the multi-instance dictionary and the classifier to optimize a given multivariate performance measure, such as the F1 score and precision at rank k. We propose to represent the bags as bag-level features via the bag-instance similarity, and learn a classifier in the bag-level feature space to optimize the given performance measure. We propose to minimize the upper bound of a multivariate loss corresponding to the performance measure, the complexity of the classifier, and the complexity of the dictionary, simultaneously, with regard to both the dictionary and the classifier parameters. In this way, the dictionary learning is regularized by the performance optimization, and a performance-optimal dictionary is obtained. We develop an iterative algorithm to solve this minimization problem efficiently using a cutting-plane algorithm and a coordinate descent method. Experiments on multi-instance benchmark data sets show its advantage over both traditional multi-instance learning and performance optimization methods.

Automated gastric cancer diagnosis on H&E-stained sections; ltraining a classifier on a large scale with multiple instance machine learning

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Cosatto, Eric; Laquerre, Pierre-Francois; Malon, Christopher; Graf, Hans-Peter; Saito, Akira; Kiyuna, Tomoharu; Marugame, Atsushi; Kamijo, Ken'ichi

2013-03-01

We present a system that detects cancer on slides of gastric tissue sections stained with hematoxylin and eosin (H&E). At its heart is a classi er trained using the semi-supervised multi-instance learning framework (MIL) where each tissue is represented by a set of regions-of-interest (ROI) and a single label. Such labels are readily obtained because pathologists diagnose each tissue independently as part of the normal clinical work ow. From a large dataset of over 26K gastric tissue sections from over 12K patients obtained from a clinical load spanning several months, we train a MIL classi er on a patient-level partition of the dataset (2/3 of the patients) and obtain a very high performance of 96% (AUC), tested on the remaining 1/3 never-seen before patients (over 8K tissues). We show this level of performance to match the more costly supervised approach where individual ROIs need to be labeled manually. The large amount of data used to train this system gives us con dence in its robustness and that it can be safely used in a clinical setting. We demonstrate how it can improve the clinical work ow when used for pre-screening or quality control. For pre-screening, the system can diagnose 47% of the tissues with a very low likelihood (cancers, thus halving the clinicians' caseload. For quality control, compared to random rechecking of 33% of the cases, the system achieves a three-fold increase in the likelihood of catching cancers missed by pathologists. The system is currently in regular use at independent pathology labs in Japan where it is used to double-check clinician's diagnoses. At the end of 2012 it will have analyzed over 80,000 slides of gastric and colorectal samples (200,000 tissues).

Multiple Time-Instances Features of Degraded Speech for Single Ended Quality Measurement

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Rajesh Kumar Dubey

2017-01-01

Full Text Available The use of single time-instance features, where entire speech utterance is used for feature computation, is not accurate and adequate in capturing the time localized information of short-time transient distortions and their distinction from plosive sounds of speech, particularly degraded by impulsive noise. Hence, the importance of estimating features at multiple time-instances is sought. In this, only active speech segments of degraded speech are used for features computation at multiple time-instances on per frame basis. Here, active speech means both voiced and unvoiced frames except silence. The features of different combinations of multiple contiguous active speech segments are computed and called multiple time-instances features. The joint GMM training has been done using these features along with the subjective MOS of the corresponding speech utterance to obtain the parameters of GMM. These parameters of GMM and multiple time-instances features of test speech are used to compute the objective MOS values of different combinations of multiple contiguous active speech segments. The overall objective MOS of the test speech utterance is obtained by assigning equal weight to the objective MOS values of the different combinations of multiple contiguous active speech segments. This algorithm outperforms the Recommendation ITU-T P.563 and recently published algorithms.

Object instance recognition using motion cues and instance specific appearance models

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Schumann, Arne

2014-03-01

In this paper we present an object instance retrieval approach. The baseline approach consists of a pool of image features which are computed on the bounding boxes of a query object track and compared to a database of tracks in order to find additional appearances of the same object instance. We improve over this simple baseline approach in multiple ways: 1) we include motion cues to achieve improved robustness to viewpoint and rotation changes, 2) we include operator feedback to iteratively re-rank the resulting retrieval lists and 3) we use operator feedback and location constraints to train classifiers and learn an instance specific appearance model. We use these classifiers to further improve the retrieval results. The approach is evaluated on two popular public datasets for two different applications. We evaluate person re-identification on the CAVIAR shopping mall surveillance dataset and vehicle instance recognition on the VIVID aerial dataset and achieve significant improvements over our baseline results.

Predicting Multiple Functions of Sustainable Flood Retention Basins under Uncertainty via Multi-Instance Multi-Label Learning

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Qinli Yang

2015-03-01

Full Text Available The ambiguity of diverse functions of sustainable flood retention basins (SFRBs may lead to conflict and risk in water resources planning and management. How can someone provide an intuitive yet efficient strategy to uncover and distinguish the multiple potential functions of SFRBs under uncertainty? In this study, by exploiting both input and output uncertainties of SFRBs, the authors developed a new data-driven framework to automatically predict the multiple functions of SFRBs by using multi-instance multi-label (MIML learning. A total of 372 sustainable flood retention basins, characterized by 40 variables associated with confidence levels, were surveyed in Scotland, UK. A Gaussian model with Monte Carlo sampling was used to capture the variability of variables (i.e., input uncertainty, and the MIML-support vector machine (SVM algorithm was subsequently applied to predict the potential functions of SFRBs that have not yet been assessed, allowing for one basin belonging to different types (i.e., output uncertainty. Experiments demonstrated that the proposed approach enables effective automatic prediction of the potential functions of SFRBs (e.g., accuracy >93%. The findings suggest that the functional uncertainty of SFRBs under investigation can be better assessed in a more comprehensive and cost-effective way, and the proposed data-driven approach provides a promising method of doing so for water resources management.

The metal-organic framework MIL-53(Al) constructed from multiple metal sources: alumina, aluminum hydroxide, and boehmite.

Science.gov (United States)

Li, Zehua; Wu, Yi-nan; Li, Jie; Zhang, Yiming; Zou, Xin; Li, Fengting

2015-04-27

Three aluminum compounds, namely alumina, aluminum hydroxide, and boehmite, are probed as the metal sources for the hydrothermal synthesis of a typical metal-organic framework MIL-53(Al). The process exhibits enhanced synthetic efficiency without the generation of strongly acidic byproducts. The time-course monitoring of conversion from different aluminum sources into MIL-53(Al) is achieved by multiple characterization that reveals a similar but differentiated crystallinity, porosity, and morphology relative to typical MIL-53(Al) prepared from water-soluble aluminum salts. Moreover, the prepared MIL-53(Al) constructed with the three insoluble aluminum sources exhibit an improved thermal stability of up to nearly 600 °C and enhanced yields. Alumina and boehmite are more preferable than aluminum hydroxide in terms of product porosity, yield, and reaction time. The adsorption performances of a typical environmental endocrine disruptor, dimethyl phthalate, on the prepared MIL-53(Al) samples are also investigated. The improved structural stability of MIL-53(Al) prepared from these alternative aluminum sources enables double-enhanced adsorption performance (up to 206 mg g(-1)) relative to the conventionally obtained MIL-53(Al). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Stochastic Learning of Multi-Instance Dictionary for Earth Mover's Distance based Histogram Comparison

OpenAIRE

Fan, Jihong; Liang, Ru-Ze

2016-01-01

Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover's distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However, up to now, there is no existing multi-instance dictionary learning methods designed for EMD based histogram comparison. To fill this gap, we develop the first EMD-optimal dictionary learning method using stochastic optimization method. In the stoc...

Media and Information Literacy (MIL) in journalistic learning: strategies for accurately engaging with information and reporting news

Science.gov (United States)

Inayatillah, F.

2018-01-01

In the era of digital technology, there is abundant information from various sources. This ease of access needs to be accompanied by the ability to engage with the information wisely. Thus, information and media literacy is required. From the results of preliminary observations, it was found that the students of Universitas Negeri Surabaya, whose major is Indonesian Literature, and they take journalistic course lack of the skill of media and information literacy (MIL). Therefore, they need to be equipped with MIL. The method used is descriptive qualitative, which includes data collection, data analysis, and presentation of data analysis. Observation and documentation techniques were used to obtain data of MIL’s impact on journalistic learning for students. This study aims at describing the important role of MIL for students of journalistic and its impact on journalistic learning for students of Indonesian literature batch 2014. The results of this research indicate that journalistic is a science that is essential for students because it affects how a person perceives news report. Through the reinforcement of the course, students can avoid a hoax. MIL-based journalistic learning makes students will be more skillful at absorbing, processing, and presenting information accurately. The subject influences students in engaging with information so that they can report news credibly.

Stochastic learning of multi-instance dictionary for earth mover’s distance-based histogram comparison

KAUST Repository

Fan, Jihong

2016-09-17

Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover’s distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However, up to now, there is no existing multi-instance dictionary learning methods designed for EMD-based histogram comparison. To fill this gap, we develop the first EMD-optimal dictionary learning method using stochastic optimization method. In the stochastic learning framework, we have one triplet of bags, including one basic bag, one positive bag, and one negative bag. These bags are mapped to histograms using a multi-instance dictionary. We argue that the EMD between the basic histogram and the positive histogram should be smaller than that between the basic histogram and the negative histogram. Base on this condition, we design a hinge loss. By minimizing this hinge loss and some regularization terms of the dictionary, we update the dictionary instances. The experiments over multi-instance retrieval applications shows its effectiveness when compared to other dictionary learning methods over the problems of medical image retrieval and natural language relation classification. © 2016 The Natural Computing Applications Forum

Automatic detection and recognition of multiple macular lesions in retinal optical coherence tomography images with multi-instance multilabel learning

Science.gov (United States)

Fang, Leyuan; Yang, Liumao; Li, Shutao; Rabbani, Hossein; Liu, Zhimin; Peng, Qinghua; Chen, Xiangdong

2017-06-01

Detection and recognition of macular lesions in optical coherence tomography (OCT) are very important for retinal diseases diagnosis and treatment. As one kind of retinal disease (e.g., diabetic retinopathy) may contain multiple lesions (e.g., edema, exudates, and microaneurysms) and eye patients may suffer from multiple retinal diseases, multiple lesions often coexist within one retinal image. Therefore, one single-lesion-based detector may not support the diagnosis of clinical eye diseases. To address this issue, we propose a multi-instance multilabel-based lesions recognition (MIML-LR) method for the simultaneous detection and recognition of multiple lesions. The proposed MIML-LR method consists of the following steps: (1) segment the regions of interest (ROIs) for different lesions, (2) compute descriptive instances (features) for each lesion region, (3) construct multilabel detectors, and (4) recognize each ROI with the detectors. The proposed MIML-LR method was tested on 823 clinically labeled OCT images with normal macular and macular with three common lesions: epiretinal membrane, edema, and drusen. For each input OCT image, our MIML-LR method can automatically identify the number of lesions and assign the class labels, achieving the average accuracy of 88.72% for the cases with multiple lesions, which better assists macular disease diagnosis and treatment.

Co-Labeling for Multi-View Weakly Labeled Learning.

Science.gov (United States)

Xu, Xinxing; Li, Wen; Xu, Dong; Tsang, Ivor W

2016-06-01

It is often expensive and time consuming to collect labeled training samples in many real-world applications. To reduce human effort on annotating training samples, many machine learning techniques (e.g., semi-supervised learning (SSL), multi-instance learning (MIL), etc.) have been studied to exploit weakly labeled training samples. Meanwhile, when the training data is represented with multiple types of features, many multi-view learning methods have shown that classifiers trained on different views can help each other to better utilize the unlabeled training samples for the SSL task. In this paper, we study a new learning problem called multi-view weakly labeled learning, in which we aim to develop a unified approach to learn robust classifiers by effectively utilizing different types of weakly labeled multi-view data from a broad range of tasks including SSL, MIL and relative outlier detection (ROD). We propose an effective approach called co-labeling to solve the multi-view weakly labeled learning problem. Specifically, we model the learning problem on each view as a weakly labeled learning problem, which aims to learn an optimal classifier from a set of pseudo-label vectors generated by using the classifiers trained from other views. Unlike traditional co-training approaches using a single pseudo-label vector for training each classifier, our co-labeling approach explores different strategies to utilize the predictions from different views, biases and iterations for generating the pseudo-label vectors, making our approach more robust for real-world applications. Moreover, to further improve the weakly labeled learning on each view, we also exploit the inherent group structure in the pseudo-label vectors generated from different strategies, which leads to a new multi-layer multiple kernel learning problem. Promising results for text-based image retrieval on the NUS-WIDE dataset as well as news classification and text categorization on several real-world multi

Instance Selection for Classifier Performance Estimation in Meta Learning

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Marcin Blachnik

2017-11-01

Full Text Available Building an accurate prediction model is challenging and requires appropriate model selection. This process is very time consuming but can be accelerated with meta-learning–automatic model recommendation by estimating the performances of given prediction models without training them. Meta-learning utilizes metadata extracted from the dataset to effectively estimate the accuracy of the model in question. To achieve that goal, metadata descriptors must be gathered efficiently and must be informative to allow the precise estimation of prediction accuracy. In this paper, a new type of metadata descriptors is analyzed. These descriptors are based on the compression level obtained from the instance selection methods at the data-preprocessing stage. To verify their suitability, two types of experiments on real-world datasets have been conducted. In the first one, 11 instance selection methods were examined in order to validate the compression–accuracy relation for three classifiers: k-nearest neighbors (kNN, support vector machine (SVM, and random forest. From this analysis, two methods are recommended (instance-based learning type 2 (IB2, and edited nearest neighbor (ENN which are then compared with the state-of-the-art metaset descriptors. The obtained results confirm that the two suggested compression-based meta-features help to predict accuracy of the base model much more accurately than the state-of-the-art solution.

Dual-Layer Density Estimation for Multiple Object Instance Detection

Directory of Open Access Journals (Sweden)

Qiang Zhang

2016-01-01

Full Text Available This paper introduces a dual-layer density estimation-based architecture for multiple object instance detection in robot inventory management applications. The approach consists of raw scale-invariant feature transform (SIFT feature matching and key point projection. The dominant scale ratio and a reference clustering threshold are estimated using the first layer of the density estimation. A cascade of filters is applied after feature template reconstruction and refined feature matching to eliminate false matches. Before the second layer of density estimation, the adaptive threshold is finalized by multiplying an empirical coefficient for the reference value. The coefficient is identified experimentally. Adaptive threshold-based grid voting is applied to find all candidate object instances. Error detection is eliminated using final geometric verification in accordance with Random Sample Consensus (RANSAC. The detection results of the proposed approach are evaluated on a self-built dataset collected in a supermarket. The results demonstrate that the approach provides high robustness and low latency for inventory management application.

Image annotation based on positive-negative instances learning

Science.gov (United States)

Zhang, Kai; Hu, Jiwei; Liu, Quan; Lou, Ping

2017-07-01

Automatic image annotation is now a tough task in computer vision, the main sense of this tech is to deal with managing the massive image on the Internet and assisting intelligent retrieval. This paper designs a new image annotation model based on visual bag of words, using the low level features like color and texture information as well as mid-level feature as SIFT, and mixture the pic2pic, label2pic and label2label correlation to measure the correlation degree of labels and images. We aim to prune the specific features for each single label and formalize the annotation task as a learning process base on Positive-Negative Instances Learning. Experiments are performed using the Corel5K Dataset, and provide a quite promising result when comparing with other existing methods.

Multiple Nebular Gas Reservoirs Recorded by Oxygen Isotope Variation in a Spinel-Rich CAI in CO3 MIL 090019

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Simon, J. I.; Simon, S. B.; Nguyen, A. N.; Ross, D. K.; Messenger, S.

2017-07-01

We conducted NanoSIMS ion imaging studies of a primitive spinel-rich CAI from the MIL 090019 CO3 chondrite. It records radial O-isotopic heterogeneity among multiple occurrences of the same mineral, reflecting distinct nebular O-isotopic reservoirs.

A Fisher Kernel Approach for Multiple Instance Based Object Retrieval in Video Surveillance

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MIRONICA, I.

2015-11-01

Full Text Available This paper presents an automated surveillance system that exploits the Fisher Kernel representation in the context of multiple-instance object retrieval task. The proposed algorithm has the main purpose of tracking a list of persons in several video sources, using only few training examples. In the first step, the Fisher Kernel representation describes a set of features as the derivative with respect to the log-likelihood of the generative probability distribution that models the feature distribution. Then, we learn the generative probability distribution over all features extracted from a reduced set of relevant frames. The proposed approach shows significant improvements and we demonstrate that Fisher kernels are well suited for this task. We demonstrate the generality of our approach in terms of features by conducting an extensive evaluation with a broad range of keypoints features. Also, we evaluate our method on two standard video surveillance datasets attaining superior results comparing to state-of-the-art object recognition algorithms.

Classification and Weakly Supervised Pain Localization using Multiple Segment Representation.

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Sikka, Karan; Dhall, Abhinav; Bartlett, Marian Stewart

2014-10-01

Automatic pain recognition from videos is a vital clinical application and, owing to its spontaneous nature, poses interesting challenges to automatic facial expression recognition (AFER) research. Previous pain vs no-pain systems have highlighted two major challenges: (1) ground truth is provided for the sequence, but the presence or absence of the target expression for a given frame is unknown, and (2) the time point and the duration of the pain expression event(s) in each video are unknown. To address these issues we propose a novel framework (referred to as MS-MIL) where each sequence is represented as a bag containing multiple segments, and multiple instance learning (MIL) is employed to handle this weakly labeled data in the form of sequence level ground-truth. These segments are generated via multiple clustering of a sequence or running a multi-scale temporal scanning window, and are represented using a state-of-the-art Bag of Words (BoW) representation. This work extends the idea of detecting facial expressions through 'concept frames' to 'concept segments' and argues through extensive experiments that algorithms such as MIL are needed to reap the benefits of such representation. The key advantages of our approach are: (1) joint detection and localization of painful frames using only sequence-level ground-truth, (2) incorporation of temporal dynamics by representing the data not as individual frames but as segments, and (3) extraction of multiple segments, which is well suited to signals with uncertain temporal location and duration in the video. Extensive experiments on UNBC-McMaster Shoulder Pain dataset highlight the effectiveness of the approach by achieving competitive results on both tasks of pain classification and localization in videos. We also empirically evaluate the contributions of different components of MS-MIL. The paper also includes the visualization of discriminative facial patches, important for pain detection, as discovered by our

Six to Ten Digits Multiplication Fun Learning Using Puppet Prototype

Science.gov (United States)

Islamiah Rosli, D.'oria; Ali, Azita; Peng, Lim Soo; Sujardi, Imam; Usodo, Budi; Adie Perdana, Fengky

2017-01-01

Logic and technical subjects require students to understand basic knowledge in mathematic. For instance, addition, minus, division and multiplication operations need to be mastered by students due to mathematic complexity as the learning mathematic grows higher. Weak foundation in mathematic also contribute to high failure rate in mathematic subjects in schools. In fact, students in primary schools are struggling to learn mathematic because they need to memorize formulas, multiplication or division operations. To date, this study will develop a puppet prototyping for learning mathematic for six to ten digits multiplication. Ten participants involved in the process of developing the prototype in this study. Students involved in the study were those from the intermediate class students whilst teachers were selected based on their vast knowledge and experiences and have more than five years of experience in teaching mathematic. Close participatory analysis will be used in the prototyping process as to fulfil the requirements of the students and teachers whom will use the puppet in learning six to ten digit multiplication in mathematic. Findings showed that, the students had a great time and fun learning experience in learning multiplication and they able to understand the concept of multiplication using puppet. Colour and materials of the puppet also help to attract student attention during learning. Additionally, students able to visualized and able to calculate accurate multiplication value and the puppet help them to recall in multiplying and adding the digits accordingly.

Constrained Deep Weak Supervision for Histopathology Image Segmentation.

Science.gov (United States)

Jia, Zhipeng; Huang, Xingyi; Chang, Eric I-Chao; Xu, Yan

2017-11-01

In this paper, we develop a new weakly supervised learning algorithm to learn to segment cancerous regions in histopathology images. This paper is under a multiple instance learning (MIL) framework with a new formulation, deep weak supervision (DWS); we also propose an effective way to introduce constraints to our neural networks to assist the learning process. The contributions of our algorithm are threefold: 1) we build an end-to-end learning system that segments cancerous regions with fully convolutional networks (FCNs) in which image-to-image weakly-supervised learning is performed; 2) we develop a DWS formulation to exploit multi-scale learning under weak supervision within FCNs; and 3) constraints about positive instances are introduced in our approach to effectively explore additional weakly supervised information that is easy to obtain and enjoy a significant boost to the learning process. The proposed algorithm, abbreviated as DWS-MIL, is easy to implement and can be trained efficiently. Our system demonstrates the state-of-the-art results on large-scale histopathology image data sets and can be applied to various applications in medical imaging beyond histopathology images, such as MRI, CT, and ultrasound images.

Generalized multiple kernel learning with data-dependent priors.

Science.gov (United States)

Mao, Qi; Tsang, Ivor W; Gao, Shenghua; Wang, Li

2015-06-01

Multiple kernel learning (MKL) and classifier ensemble are two mainstream methods for solving learning problems in which some sets of features/views are more informative than others, or the features/views within a given set are inconsistent. In this paper, we first present a novel probabilistic interpretation of MKL such that maximum entropy discrimination with a noninformative prior over multiple views is equivalent to the formulation of MKL. Instead of using the noninformative prior, we introduce a novel data-dependent prior based on an ensemble of kernel predictors, which enhances the prediction performance of MKL by leveraging the merits of the classifier ensemble. With the proposed probabilistic framework of MKL, we propose a hierarchical Bayesian model to learn the proposed data-dependent prior and classification model simultaneously. The resultant problem is convex and other information (e.g., instances with either missing views or missing labels) can be seamlessly incorporated into the data-dependent priors. Furthermore, a variety of existing MKL models can be recovered under the proposed MKL framework and can be readily extended to incorporate these priors. Extensive experiments demonstrate the benefits of our proposed framework in supervised and semisupervised settings, as well as in tasks with partial correspondence among multiple views.

The boundaries of instance-based learning theory for explaining decisions from experience.

Science.gov (United States)

Gonzalez, Cleotilde

2013-01-01

Most demonstrations of how people make decisions in risky situations rely on decisions from description, where outcomes and their probabilities are explicitly stated. But recently, more attention has been given to decisions from experience where people discover these outcomes and probabilities through exploration. More importantly, risky behavior depends on how decisions are made (from description or experience), and although prospect theory explains decisions from description, a comprehensive model of decisions from experience is yet to be found. Instance-based learning theory (IBLT) explains how decisions are made from experience through interactions with dynamic environments (Gonzalez et al., 2003). The theory has shown robust explanations of behavior across multiple tasks and contexts, but it is becoming unclear what the theory is able to explain and what it does not. The goal of this chapter is to start addressing this problem. I will introduce IBLT and a recent cognitive model based on this theory: the IBL model of repeated binary choice; then I will discuss the phenomena that the IBL model explains and those that the model does not. The argument is for the theory's robustness but also for clarity in terms of concrete effects that the theory can or cannot account for. Copyright © 2013 Elsevier B.V. All rights reserved.

Landmark-based deep multi-instance learning for brain disease diagnosis.

Science.gov (United States)

Liu, Mingxia; Zhang, Jun; Adeli, Ehsan; Shen, Dinggang

2018-01-01

In conventional Magnetic Resonance (MR) image based methods, two stages are often involved to capture brain structural information for disease diagnosis, i.e., 1) manually partitioning each MR image into a number of regions-of-interest (ROIs), and 2) extracting pre-defined features from each ROI for diagnosis with a certain classifier. However, these pre-defined features often limit the performance of the diagnosis, due to challenges in 1) defining the ROIs and 2) extracting effective disease-related features. In this paper, we propose a landmark-based deep multi-instance learning (LDMIL) framework for brain disease diagnosis. Specifically, we first adopt a data-driven learning approach to discover disease-related anatomical landmarks in the brain MR images, along with their nearby image patches. Then, our LDMIL framework learns an end-to-end MR image classifier for capturing both the local structural information conveyed by image patches located by landmarks and the global structural information derived from all detected landmarks. We have evaluated our proposed framework on 1526 subjects from three public datasets (i.e., ADNI-1, ADNI-2, and MIRIAD), and the experimental results show that our framework can achieve superior performance over state-of-the-art approaches. Copyright © 2017 Elsevier B.V. All rights reserved.

Multiple Nebular Gas Reservoirs Recorded by Oxygen Isotope Variation in a Spinel-rich CAI in CO3 MIL 090019

Science.gov (United States)

Simon, J. I.; Simon, S. B.; Nguyen, A. N.; Ross, D. K.; Messenger, S.

2017-01-01

We conducted NanoSIMS O-isotopic imaging of a primitive spinel-rich CAI spherule (27-2) from the MIL 090019 CO3 chondrite. Inclusions such as 27-2 are proposed to record inner nebula processes during an epoch of rapid solar nebula evolution. Mineralogical and textural analyses suggest that this CAI formed by high temperature reactions, partial melting, and condensation. This CAI exhibits radial O-isotopic heterogeneity among multiple occurrences of the same mineral, reflecting interactions with distinct nebular O-isotopic reservoirs.

Learning concept mappings from instance similarity

NARCIS (Netherlands)

Wang, S.; Englebienne, G.; Schlobach, S.

2008-01-01

Finding mappings between compatible ontologies is an important but difficult open problem. Instance-based methods for solving this problem have the advantage of focusing on the most active parts of the ontologies and reflect concept semantics as they are actually being used. However such methods

The removal of bisphenol A from aqueous solutions by MIL-53(Al) and mesostructured MIL-53(Al).

Science.gov (United States)

Zhou, Meimei; Wu, Yi-Nan; Qiao, Junlian; Zhang, Jing; McDonald, Amanda; Li, Guangtao; Li, Fengting

2013-09-01

In this work, metal-organic framework MIL-53(Al){Al(OH)[O2C-C6H4-CO2]} and MIL-53(Al)-F127{Al(OH)[O2C-C6H4-CO2]} were synthesized and used as sorbents to remove bisphenol A (BPA) from aqueous system. The sorption kinetics data of BPA were found to be in agreement with the pseudo-second-order model. The equilibrium sorption amounts of BPA on MIL-53(Al) and MIL-53(Al)-F127 reached 329.2±16.5 and 472.7±23.6 mg g(-1), respectively, far more than that of commercial activated carbons (ranging from 129.6 to 263.1 mg g(-1)). Both MIL-53(Al) and MIL-53(Al)-F127 could remove BPA fast from aqueous solutions, and the required contact time to reach equilibrium was approximately 90 min for MIL-53(Al) and 30 min for MIL-53(Al)-F127, respectively. The optimum pH levels for the removal of BPA using MIL-53 (Al) and MIL-53(Al)-F127 were 4 and 6 separately. The optimum temperature for the sorption behavior of BPA on the two sorbents was 20 °C. The results performed show that the resulting products, as one kind of MOFs, can be regarded as a new class of sorbents for water treatment and could find great applications in the fields of environmental water pollution control and resources reuse. Copyright © 2013 Elsevier Inc. All rights reserved.

Multiple Chaotic Central Pattern Generators with Learning for Legged Locomotion and Malfunction Compensation

DEFF Research Database (Denmark)

Ren, Guanjiao; Chen, Weihai; Dasgupta, Sakyasingha

2015-01-01

on a simulated annealing algorithm. In a normal situation, the CPGs synchronize and their dynamics are identical. With leg malfunction or disability, the CPGs lose synchronization leading to independent dynamics. In this case, the learning mechanism is applied to automatically adjust the remaining legs...... in a physical simulation of a quadruped as well as a hexapod robot and finally in a real six-legged walking machine called AMOSII. The experimental results presented here reveal that using multiple CPGs with learning is an effective approach for adaptive locomotion generation where, for instance, different body...... chaotic CPG controller has difficulties dealing with leg malfunction. Specifically, in the scenarios presented here, its movement permanently deviates from the desired trajectory. To address this problem, we extend the single chaotic CPG to multiple CPGs with learning. The learning mechanism is based...

Représentations de niveau intermédiaire pour la modélisation d'objets

OpenAIRE

Tsogkas , Stavros

2016-01-01

In this thesis we propose the use of mid-level representations, and in particular i) medial axes, ii) object parts, and iii)convolutional features, for modelling objects.The first part of the thesis deals with detecting medial axes in natural RGB images. We adopt a learning approach, utilizing colour, texture and spectral clustering features, to build a classifier that produces a dense probability map for symmetry. Multiple Instance Learning (MIL) allows us to treat scale and orientation as l...

As milícias nacionais

Directory of Open Access Journals (Sweden)

Jeanne Berrance de Castro

1968-03-01

Full Text Available As milícias nacionais — herança ideológica do século XVIII —tiveram na milícia norte-americana e nas Guardas Nacionais francesa e também brasileira expressivos exemplos dessas fôrças paramilitares. O conceito da "nação em armas", institucionalizado, possibilitou ao poder civil o contrôle militar, auxilado de outro lado pela descen-tralização dessas milícias nacionais que, com isso, suplantaram as fôrças militares regulares.

Synthesis and Characterization Studies of MIL-101

Directory of Open Access Journals (Sweden)

Emine Kaya EKİNCİ

2017-12-01

Full Text Available MIL-101 is a kind of Metal Organic Frameworks (MOFs, which have attracted much attention in the past decade due to its promising application in chemical industries. MIL-101 is also known as “Porous Chromium Terephthalate”. It has very high surface area and pore volume. MIL-101 exhibits exceptional stability against moisture and other chemicals and is composed of coordinately unsaturated Cr- sites with high concentration available for catalysis and adsorption. MIL-101 was synthesized by hydrothermal method and characterized by XRD, nitrogen adsorption and desorption analyses and SEM. XRD patterns show the presence of MIL-101’s crystal structure with high surface area (~2400 m2/g. Nitrogen adsorption-desorption analyzes showed that the material exhibited mesoporous material behavior.

Coordination polymer nanobamboos of {Fe(x)In(1-x)}-MIL-88B: induced formation of a virtual In-MIL-88B.

Science.gov (United States)

Park, Shin Ae; Lee, Hee Jung; Cho, Yea Jin; Choi, Sora; Oh, Moonhyun

2014-05-05

A precise fabrication of nanobamboo structures made from hybrid coordination polymers of the type {Fex In1-x }-MIL-88B is demonstrated. The compositions of the hybrid coordination polymer nanobamboos of {Fex In1-x }-MIL-88B (x=0.06, 0.19, or 0.75) are regulated by altering the amount of metal ions used in the reactions. Interestingly, the formation of a virtual In-MIL-88B (precise structure, {Fe0.06 In0.94 }-MIL-88B), which cannot be created in a typical reaction, is induced by the assistance of a Fe-MIL-88B structure. The a and c cell parameters of {Fe0.06 In0.94 }-MIL-88B are calculated at 10.95 and 19.86 Å, respectively. These values of {Fe0.06 In0.94 }-MIL-88B are larger than those of pure Fe-MIL-88B owing to the large ionic size of In(3+) within the framework. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Highly efficient capture of iodine by Cu/MIL-101

Science.gov (United States)

Qi, Bingbing; Liu, Ying; Zheng, Tao; Gao, Qianhong; Yan, Xuewu; Jiao, Yan; Yang, Yi

2018-02-01

In order to improve the uptake capacity of MIL-101 for iodine, Cu nanoparticles doped MIL-101 were successfully synthesized through a facile method. The obtained Cu/MIL-101 was characterized by SEM, XRD, EDS, TEM, IR, TGA and BET to examine the chemical and thermal stabilities. The capture experiments for the adsorbents showed that the capture capacity of Cu/MIL-101 for volatile iodine is 342 wt%, which is higher than that of pure MIL-101. An I2 uptake of 342 wt% is the highest value reported among metal-organic frameworks. Furthermore, Cu/MIL-101 has a cycle ratio of 95% after three cycles and exhibits a better cyclicity than pure MIL-101. Meanwhile, Cu/MIL-101 shows an excellent reversible adsorption of iodine in solution.

Kernel Methods for Mining Instance Data in Ontologies

Science.gov (United States)

Bloehdorn, Stephan; Sure, York

The amount of ontologies and meta data available on the Web is constantly growing. The successful application of machine learning techniques for learning of ontologies from textual data, i.e. mining for the Semantic Web, contributes to this trend. However, no principal approaches exist so far for mining from the Semantic Web. We investigate how machine learning algorithms can be made amenable for directly taking advantage of the rich knowledge expressed in ontologies and associated instance data. Kernel methods have been successfully employed in various learning tasks and provide a clean framework for interfacing between non-vectorial data and machine learning algorithms. In this spirit, we express the problem of mining instances in ontologies as the problem of defining valid corresponding kernels. We present a principled framework for designing such kernels by means of decomposing the kernel computation into specialized kernels for selected characteristics of an ontology which can be flexibly assembled and tuned. Initial experiments on real world Semantic Web data enjoy promising results and show the usefulness of our approach.

Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction

Science.gov (United States)

Wagstaff, Kiri L.; Lane, Terran

2010-01-01

An algorithm was developed to generate crop yield predictions from orbital remote sensing observations, by analyzing thousands of pixels per county and the associated historical crop yield data for those counties. The algorithm determines which pixels contain which crop. Since each known yield value is associated with thousands of individual pixels, this is a multiple instance learning problem. Because individual crop growth is related to the resulting yield, this relationship has been leveraged to identify pixels that are individually related to corn, wheat, cotton, and soybean yield. Those that have the strongest relationship to a given crop s yield values are most likely to contain fields with that crop. Remote sensing time series data (a new observation every 8 days) was examined for each pixel, which contains information for that pixel s growth curve, peak greenness, and other relevant features. An alternating-projection (AP) technique was used to first estimate the "salience" of each pixel, with respect to the given target (crop yield), and then those estimates were used to build a regression model that relates input data (remote sensing observations) to the target. This is achieved by constructing an exemplar for each crop in each county that is a weighted average of all the pixels within the county; the pixels are weighted according to the salience values. The new regression model estimate then informs the next estimate of the salience values. By iterating between these two steps, the algorithm converges to a stable estimate of both the salience of each pixel and the regression model. The salience values indicate which pixels are most relevant to each crop under consideration.

MIL-53(Fe), MIL-101, and SBA-15 porous materials: potential platforms for drug delivery.

Science.gov (United States)

Gordon, Jeff; Kazemian, Hossein; Rohani, Sohrab

2015-02-01

Conventional drug administration suffers from several drawbacks, including a lack of specificity for diseased tissue, the necessity of large and frequent doses, and adverse side effects. Great effort is currently being devoted to developing nanoparticle-based therapeutics capable of prolonging drug administration and providing better control. Here we demonstrate the use of flexible microporous MIL-53(Fe) and mesoporous MIL-101 and SBA-15 as matrices for the adsorption and in vitro drug delivery of acetaminophen, progesterone, and stavudine. A drug loading of 20 wt.% was achieved for each of the nanomaterials using an incipient wetness impregnation procedure. BET, DSC, and XRPD analyses indicated that the entire loaded amount of each of the model drugs had successfully been incorporated within the mesoporous channels of both MIL-101 and SBA-15. DSC analysis evidenced that a portion of each of the model drugs had deposited onto the outer surface of MIL-53(Fe) particles; however, the portion of each drug that had incorporated within the microporous channels was slowly delivered in a diffusion-controlled process, which occurred over a period of up to six days for acetaminophen. These results demonstrate the unique ability of MIL-53(Fe) to adapt its porosity and optimize drug-matrix interactions. Owing to its larger pore diameters and weaker host-guest interactions, MIL-101 release times were shorter, yet still prolonged, as evidenced by the complete release of stavudine after five days. Complete release of each of the drugs from SBA-15 occurred very quickly as a result of rapid drug dissolution and diffusion out of the mesopores. Copyright © 2014 Elsevier B.V. All rights reserved.

Retrieving clinically relevant diabetic retinopathy images using a multi-class multiple-instance framework

Science.gov (United States)

Chandakkar, Parag S.; Venkatesan, Ragav; Li, Baoxin

2013-02-01

Diabetic retinopathy (DR) is a vision-threatening complication from diabetes mellitus, a medical condition that is rising globally. Unfortunately, many patients are unaware of this complication because of absence of symptoms. Regular screening of DR is necessary to detect the condition for timely treatment. Content-based image retrieval, using archived and diagnosed fundus (retinal) camera DR images can improve screening efficiency of DR. This content-based image retrieval study focuses on two DR clinical findings, microaneurysm and neovascularization, which are clinical signs of non-proliferative and proliferative diabetic retinopathy. The authors propose a multi-class multiple-instance image retrieval framework which deploys a modified color correlogram and statistics of steerable Gaussian Filter responses, for retrieving clinically relevant images from a database of DR fundus image database.

Instance-based Policy Learning by Real-coded Genetic Algorithms and Its Application to Control of Nonholonomic Systems

Science.gov (United States)

Miyamae, Atsushi; Sakuma, Jun; Ono, Isao; Kobayashi, Shigenobu

The stabilization control of nonholonomic systems have been extensively studied because it is essential for nonholonomic robot control problems. The difficulty in this problem is that the theoretical derivation of control policy is not necessarily guaranteed achievable. In this paper, we present a reinforcement learning (RL) method with instance-based policy (IBP) representation, in which control policies for this class are optimized with respect to user-defined cost functions. Direct policy search (DPS) is an approach for RL; the policy is represented by parametric models and the model parameters are directly searched by optimization techniques including genetic algorithms (GAs). In IBP representation an instance consists of a state and an action pair; a policy consists of a set of instances. Several DPSs with IBP have been previously proposed. In these methods, sometimes fail to obtain optimal control policies when state-action variables are continuous. In this paper, we present a real-coded GA for DPSs with IBP. Our method is specifically designed for continuous domains. Optimization of IBP has three difficulties; high-dimensionality, epistasis, and multi-modality. Our solution is designed for overcoming these difficulties. The policy search with IBP representation appears to be high-dimensional optimization; however, instances which can improve the fitness are often limited to active instances (instances used for the evaluation). In fact, the number of active instances is small. Therefore, we treat the search problem as a low dimensional problem by restricting search variables only to active instances. It has been commonly known that functions with epistasis can be efficiently optimized with crossovers which satisfy the inheritance of statistics. For efficient search of IBP, we propose extended crossover-like mutation (extended XLM) which generates a new instance around an instance with satisfying the inheritance of statistics. For overcoming multi-modality, we

A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets.

Science.gov (United States)

Fernández, Alberto; Carmona, Cristobal José; José Del Jesus, María; Herrera, Francisco

2017-09-01

Imbalanced classification is related to those problems that have an uneven distribution among classes. In addition to the former, when instances are located into the overlapped areas, the correct modeling of the problem becomes harder. Current solutions for both issues are often focused on the binary case study, as multi-class datasets require an additional effort to be addressed. In this research, we overcome these problems by carrying out a combination between feature and instance selections. Feature selection will allow simplifying the overlapping areas easing the generation of rules to distinguish among the classes. Selection of instances from all classes will address the imbalance itself by finding the most appropriate class distribution for the learning task, as well as possibly removing noise and difficult borderline examples. For the sake of obtaining an optimal joint set of features and instances, we embedded the searching for both parameters in a Multi-Objective Evolutionary Algorithm, using the C4.5 decision tree as baseline classifier in this wrapper approach. The multi-objective scheme allows taking a double advantage: the search space becomes broader, and we may provide a set of different solutions in order to build an ensemble of classifiers. This proposal has been contrasted versus several state-of-the-art solutions on imbalanced classification showing excellent results in both binary and multi-class problems.

Domain Adaptation for Machine Translation with Instance Selection

Directory of Open Access Journals (Sweden)

Biçici Ergun

2015-04-01

Full Text Available Domain adaptation for machine translation (MT can be achieved by selecting training instances close to the test set from a larger set of instances. We consider 7 different domain adaptation strategies and answer 7 research questions, which give us a recipe for domain adaptation in MT. We perform English to German statistical MT (SMT experiments in a setting where test and training sentences can come from different corpora and one of our goals is to learn the parameters of the sampling process. Domain adaptation with training instance selection can obtain 22% increase in target 2-gram recall and can gain up to 3:55 BLEU points compared with random selection. Domain adaptation with feature decay algorithm (FDA not only achieves the highest target 2-gram recall and BLEU performance but also perfectly learns the test sample distribution parameter with correlation 0:99. Moses SMT systems built with FDA selected 10K training sentences is able to obtain F1 results as good as the baselines that use up to 2M sentences. Moses SMT systems built with FDA selected 50K training sentences is able to obtain F1 point better results than the baselines.

Iron metal-organic frameworks MIL-88B and NH2-MIL-88B for the loading and delivery of the gasotransmitter carbon monoxide.

Science.gov (United States)

Ma, Mingyan; Noei, Heshmat; Mienert, Bernd; Niesel, Johanna; Bill, Eckhard; Muhler, Martin; Fischer, Roland A; Wang, Yuemin; Schatzschneider, Ulrich; Metzler-Nolte, Nils

2013-05-17

Crystals of MIL-88B-Fe and NH2-MIL-88B-Fe were prepared by a new rapid microwave-assisted solvothermal method. High-purity, spindle-shaped crystals of MIL-88B-Fe with a length of about 2 μm and a diameter of 1 μm and needle-shaped crystals of NH2-MIL-88B-Fe with a length of about 1.5 μm and a diameter of 300 nm were produced with uniform size and excellent crystallinity. The possibility to reduce the as-prepared frameworks and the chemical capture of carbon monoxide in these materials was studied by in situ ultrahigh vacuum Fourier-transform infrared (UHV-FTIR) spectroscopy and Mössbauer spectroscopy. CO binding occurs to unsaturated coordination sites (CUS). The release of CO from the as-prepared materials was studied by a myoglobin assay in physiological buffer. The release of CO from crystals of MIL-88B-Fe with t(1/2) = 38 min and from crystals of NH2-MIL-88B-Fe with t(1/2) = 76 min were found to be controlled by the degradation of the MIL materials under physiological conditions. These MIL-88B-Fe and NH2-MIL-88B-Fe materials show good biocompatibility and have the potential to be used in pharmacological and therapeutic applications as carriers and delivery vehicles for the gasotransmitter carbon monoxide. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Petits mils

International Development Research Centre (IDRC) Digital Library (Canada)

cinq fois moins d'eau que le riz ? Note d'analyse ... dont une teneur élevée en micronutriments et en fibres alimentaires et un indice glycémique faible. ... Malgré les qualités nutritionnelles supérieures et la résilience au climat des petits mils, ...

Feldspathic Meteorites MIL 090034 and 090070: Late Additions to the Lunar Crust

Science.gov (United States)

Nyquist, L. E.; Shirai, N.; Yamaguchi, A.; Shih, C.-Y.; Park, J.; Ebihara, M.

2016-01-01

Our studies of the Miller Range lunar meteorites MIL 090034, 090036, and 090070 show them to be a diverse suite of rocks from the lunar highlands hereafter referred to as MIL 34, MIL 36, and MIL 70, resp. MIL34 and MIL70, the focus of this work, are crystalline melt breccias. Plagioclase compositions in both peak sharply around An96-97. Mg numbers of olivine vary from 58-65 with a few higher values. MIL36 is a regolith breccia. MIL 34 and MIL 70 have some of the highest Al2O3 abundances of lunar highland meteorites, indicating that they have among the largest modal abundances of plagioclase for lunar meteorites. They have lower Sc and Cr abundances than nearly all lunar highland meteorites except Dho 081, Dho 489 and Dho 733. MIL34 and MIL70 also have similar cosmic ray exposure (CRE) ages of approximately 1-2 Ma indicating they are launch paired. (MIL36 has a larger CRE age approximately greater than 70 Ma). Park et al. found a variation in Ar-Ar ages among subsamples of MIL 34 and MIL70, but preferred ages of 3500+/-110 Ma for the "Dark" phase of MIL 34 anorthite and 3520+/-30 Ma for the "Light" phase of MIL70. Bouvier et al. reported a Pb-Pb age of 3894+/-39 Ma for a feldspathic clast of MIL 34 and a similar age for a melt lithology. Here we reexamine the Rb-Sr and Sm-Nd isotopic data, which show complexities qualitatively consistent with those of the Ar-Ar and Pb-Pb data. The Sm-Nd data in particular suggest that the feldspathic compositions of MIL 34 and MIL 70 formed during initial lunar geochemical differentiation, and REE modeling suggests a relatively late-stage formation.

Metal organic framework MIL-101(Cr) for dehydration reactions

Indian Academy of Sciences (India)

Porous chromium terephthalate MIL-101 (Cr-MIL-101) has been prepared by direct method under hydrothermal conditions and characterized using X-ray diffraction, N2 sorption, TGA and FT-IR. The nitrogen adsorption-desorption isotherm shows that the Cr-MIL-101 possesses BET specific surface area of 2563 m2/g.

An anomaly detection and isolation scheme with instance-based learning and sequential analysis

International Nuclear Information System (INIS)

Yoo, T. S.; Garcia, H. E.

2006-01-01

This paper presents an online anomaly detection and isolation (FDI) technique using an instance-based learning method combined with a sequential change detection and isolation algorithm. The proposed method uses kernel density estimation techniques to build statistical models of the given empirical data (null hypothesis). The null hypothesis is associated with the set of alternative hypotheses modeling the abnormalities of the systems. A decision procedure involves a sequential change detection and isolation algorithm. Notably, the proposed method enjoys asymptotic optimality as the applied change detection and isolation algorithm is optimal in minimizing the worst mean detection/isolation delay for a given mean time before a false alarm or a false isolation. Applicability of this methodology is illustrated with redundant sensor data set and its performance. (authors)

Purification of Contaminated MIL-PRF-83282 Hydraulic Fluid Using the Pall Purifier and Multiple Process Configurations (Preprint)

National Research Council Canada - National Science Library

Snyder, Jr., Carl E; Gschwender, Lois J; Gunderson, Stephen L; Fultz, George W

2006-01-01

.... This report describes a project that evaluated the effectiveness of various hydraulic fluid purification process configurations on the removal of water and particulate contaminants from MIL-PRF-83282...

Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.

Science.gov (United States)

Said, Nadia; Engelhart, Michael; Kirches, Christian; Körkel, Stefan; Holt, Daniel V

2016-01-01

Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.

Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.

Directory of Open Access Journals (Sweden)

Nadia Said

Full Text Available Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.

Stochastic learning of multi-instance dictionary for earth mover’s distance-based histogram comparison

KAUST Repository

Fan, Jihong; Liang, Ru-Ze

2016-01-01

Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover’s distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However

Synergy of mIL-21 and mIL-15 in enhancing DNA vaccine efficacy against acute and chronic Toxoplasma gondii infection in mice.

Science.gov (United States)

Li, Zhong-Yuan; Chen, Jia; Petersen, Eskild; Zhou, Dong-Hui; Huang, Si-Yang; Song, Hui-Qun; Zhu, Xing-Quan

2014-05-23

The synergistic protective efficacy of murine interleukin 21 (mIL-21) and mIL-15 administrated with DNA vaccine against acute and chronic Toxoplasma gondii infection in mice was investigated using T. gondii MIC8 (TgMIC8) as a model. We cloned mIL-21 and mIL-15 from splenic tissues of Kunming mice, and constructed eukaryotic plasmid pVAX/mIL-15, pVAX/mIL-21, and pVAX/mIL-21/mIL-15, respectively. After immunizing with pVAX/TgMIC8 in the presence or absence of these cytokines, immune responses were analyzed using lymphoproliferative assay, cytokine and serum antibody measurements, flow cytometric surface markers on lymphocytes and protection against acute and chronic T. gondii infection. Mice receiving pVAX/TgMIC8 alone developed a strong humoral responses and Th1 type cellular immune responses, and showed an increase of CD4+ and CD8+ T cells compared with all the controls. Adding pVAX/mIL-21 to pVAX/TgMIC8 compared to pVAX/TgMIC8 resulted in only a slight increase in humoral and cellular immune responses, and this immune response was lower than that induced by the pVAX/mIL-15 combined with pVAX/TgMIC8. Co-administration of pVAX/mIL-21/mIL-15 combined with pVAX/TgMIC8 elicited the strongest humoral and cellular immune responses among all the groups, leading to significantly increased survival time against acute infection and the significant reduction of tissue cysts, compared to all the controls. Synergy of mIL-21 and mIL-15 can facilitate specific humoral as well as cellular immune responses elicited by DNA vaccine against acute and chronic T. gondii infection in mice. Copyright © 2014 Elsevier Ltd. All rights reserved.

The flexibility of modified-linker MIL-53 materials.

Science.gov (United States)

Munn, Alexis S; Pillai, Renjith S; Biswas, Shyam; Stock, Norbert; Maurin, Guillaume; Walton, Richard I

2016-03-14

The flexibility of eight aluminium hydroxo terephthalates [Al(OH)(BDC-X)]·n(guest) (BDC = 1,4-benzene-dicarboxylate; X = -H, -CH3, -Cl, -Br, -NH2, -NO2, -(OH)2, -CO2H) crystallising in the MIL-53-type structure was investigated upon thermal dehydration of as-made samples, superhydration and methanol adsorption/desorption using in situ powder X-ray diffraction (PXRD). Profile fitting was used to determine lattice parameters as a function of time and/or temperature to describe their structural evolution. It has thus been shown that while methanol vapour adsorption induces an opening of all the modified frameworks, except the -NH2 material, superhydration only leads to open structures for Al-MIL-53-NO2, -Br and -(OH)2. All the MIL-53 solids, except Al-MIL-53-(OH)2 are present in the open structures upon thermal dehydration. In addition to the exploration of the breathing behavior of this MIL-53 series, the issue of disorder in the distribution of the functional groups between the organic linkers was explored. As a typical illustration, density functional theory calculations were carried out on different structures of Al-MIL-53-Cl, in which the distribution of -Cl within two adjacent BDC linkers is varied. The results show that the most energetically stable configuration leads to the best agreement with the experimental PXRD pattern. This observation supports that the distribution of the selected linker substituent in the functionalised solid is governed by energetics and that there is a preference for an ordering of this arrangement.

Compact, Low-Overhead, MIL-STD-1553B Controller

Science.gov (United States)

Katz, Richard; Barto, Rod

2009-01-01

A compact and flexible controller has been developed to provide MIL-STD- 1553B Remote Terminal (RT) communications and supporting and related functions with minimal demand on the resources of the system in which the controller is to be installed. (MIL-STD-1553B is a military standard that encompasses a method of communication and electrical-interface requirements for digital electronic subsystems connected to a data bus. MIL-STD-1553B is commonly used in defense and space applications.) Many other MIL-STD-1553B RT controllers are complicated, and to enable them to function, it is necessary to provide software and to use such ancillary separate hardware devices as microprocessors and dual-port memories. The present controller functions without need for software and any ancillary hardware. In addition, it contains a flexible system interface and extensive support hardware while including on-chip error-checking and diagnostic support circuitry. This controller is implemented within part of a modern field-programmable gate array.

MEMS and mil/aero: technology push and market pull

Science.gov (United States)

Clifford, Thomas H.

2001-04-01

MEMS offers attractive solutions to high-density fluidics, inertial, optical, switching and other demanding military/aerospace (mil/aero) challenges. However, full acceptance must confront the realities of production-scale producibility, verifiability, testability, survivability, as well as long-term reliability. Data on these `..ilities' are crucial, and are central in funding and deployment decisions. Similarly, mil/aero users must highlight specific missions, environmental exposures, and procurement issues, as well as the quirks of its designers. These issues are particularly challenging in MEMS, because of the laws of physics and business economics, as well as the risks of deploying leading-edge technology into no-fail applications. This paper highlights mil/aero requirements, and suggests reliability/qualification protocols, to guide development effort and to reassure mil/aero users that MEMS labs are mindful of the necessary realities.

Horror Image Recognition Based on Context-Aware Multi-Instance Learning.

Science.gov (United States)

Li, Bing; Xiong, Weihua; Wu, Ou; Hu, Weiming; Maybank, Stephen; Yan, Shuicheng

2015-12-01

Horror content sharing on the Web is a growing phenomenon that can interfere with our daily life and affect the mental health of those involved. As an important form of expression, horror images have their own characteristics that can evoke extreme emotions. In this paper, we present a novel context-aware multi-instance learning (CMIL) algorithm for horror image recognition. The CMIL algorithm identifies horror images and picks out the regions that cause the sensation of horror in these horror images. It obtains contextual cues among adjacent regions in an image using a random walk on a contextual graph. Borrowing the strength of the fuzzy support vector machine (FSVM), we define a heuristic optimization procedure based on the FSVM to search for the optimal classifier for the CMIL. To improve the initialization of the CMIL, we propose a novel visual saliency model based on the tensor analysis. The average saliency value of each segmented region is set as its initial fuzzy membership in the CMIL. The advantage of the tensor-based visual saliency model is that it not only adaptively selects features, but also dynamically determines fusion weights for saliency value combination from different feature subspaces. The effectiveness of the proposed CMIL model is demonstrated by its use in horror image recognition on two large-scale image sets collected from the Internet.

Hydrothermal crystal growth and Vernier structures of the metal benzenedicarboxylates MIL-47 and MIL-53 containing guest molecules of benzenecarboxylic acid

International Nuclear Information System (INIS)

Wang, Xiqu; Jacobson, Allan J.

2016-01-01

The nanoporous frameworks VO(bdc), MIL-47, and M(OH)(bdc), MIL-53; bdc=1,4-benzenedicarboxylate, can absorb various guest species in their channels. As synthesized, the channels are filled with H 2 bdc molecules that have been reported to be disordered, except for [In(OH)bdc](H 2 bdc) 3/4 , 1, which has a inorganic-organic hybrid Vernier structure with the H 2 bdc molecules forming an ordered sublattice. Based on X-ray data from large single crystals grown by hydrothermal techniques, similar Vernier structures have been found for MIL-47, [VO(bdc)](H 2 bdc) 5/7 , 2, MIL-53Al, [Al(OH)(bdc)](H 2 bdc) 11/16 , 3, and MIL-53Ga, [Ga(OH)(bdc)](H 2 bdc) 12/17 , 4. The Vernier structures of 2–4 at room temperature were determined based on superstructure unit cells that index both host and guest sublattices: 2, space group P2 1 , a=23.903(2), b=17.191(2), c=25.722(2) Å, β=105.914(8)°; 3, P2 1 /n, a=105.224(4), b=12.2441(5), c=17.0143(6) Å, β=89.99(1)°; 4, P2 1 , a=114.562(5), b=12.1503(5), c=17.4275(7) Å, β=89.99(1)°. The number of guest H 2 bdc molecules per framework metal ion is determined by the ratio of the repeat distances of the two sublattices which depends on the size of the metal ion in the octahedral chain. The octahedral chains are parallel to [201] in 2, and to [100] in 3 and 4. Remarkably, all atoms in 3 and 4 show significant sinusoidal modulations transverse to the chain axis. - Graphical abstract: The sinusoidal modulation along the channel axis direction involving all atoms in the structure of [Al(OH)(bdc)](H 2 bdc) 11/16 . - Highlights: • Crystal growth of MIL-47, MIL-53Al, and MIL-53Ga. • The Vernier structures have corner-sharing MO6 octrahedral chains and chains of H2BDC molecules. • The stoichiometry is determined by the ratio of the host framework to the guest H2BDC column lengths. • A correlation is established between the stoichiometry and the radius of the metal ion. • All atoms in the Al and Ga compounds show sinusoidal

Project Learning and Virtual Collaboration

DEFF Research Database (Denmark)

Fibiger, Bo; Nielsen, Janni; Sorensen, Elsebeth

2005-01-01

to the modularity and flexibility that characterize the study and allow admission of part-time students, full-time students and students who only sign up for one accredited module. The methodology will be illustrated through empirical snapshots from selected modules in the start-up phase, and the focus...... will be directed towards problems experienced by the students. From an analytical perspective, the paper will identify and discuss fundamental problems related to the organization, flexibility, and implementation of project pedagogy online. MIL is organized around ICT and Learning and the study theme focuses...... on ICT and Learning. In addition, MIL provides a learning space where practice is under constant negotiation and reconstruction as an inherent, integrated part of the learning process. Consequently, we argue that MIL may be seen as an example of best practice in blended learning....

MIL-100 derived nitrogen-embodied carbon shells embedded with iron nanoparticles

Science.gov (United States)

Mao, Chengyu; Kong, Aiguo; Wang, Yuan; Bu, Xianhui; Feng, Pingyun

2015-06-01

The use of metal-organic frameworks (MOFs) as templates and precursors to synthesize new carbon materials with controllable morphology and pre-selected heteroatom doping holds promise for applications as efficient non-precious metal catalysts. Here, we report a facile pyrolysis pathway to convert MIL-100 into nitrogen-doped carbon shells encapsulating Fe nanoparticles in a comparative study involving multiple selected nitrogen sources. The hierarchical porous architecture, embedded Fe nanoparticles, and nitrogen decoration endow this composite with a superior oxygen reduction activity. Furthermore, the excellent durability and high methanol tolerance even outperform the commercial Pt-C catalyst.The use of metal-organic frameworks (MOFs) as templates and precursors to synthesize new carbon materials with controllable morphology and pre-selected heteroatom doping holds promise for applications as efficient non-precious metal catalysts. Here, we report a facile pyrolysis pathway to convert MIL-100 into nitrogen-doped carbon shells encapsulating Fe nanoparticles in a comparative study involving multiple selected nitrogen sources. The hierarchical porous architecture, embedded Fe nanoparticles, and nitrogen decoration endow this composite with a superior oxygen reduction activity. Furthermore, the excellent durability and high methanol tolerance even outperform the commercial Pt-C catalyst. Electronic supplementary information (ESI) available: Material synthesis and elemental analysis, electrochemistry measurements, and additional figures. See DOI: 10.1039/c5nr02346g

Hydrothermal crystal growth and Vernier structures of the metal benzenedicarboxylates MIL-47 and MIL-53 containing guest molecules of benzenecarboxylic acid

Energy Technology Data Exchange (ETDEWEB)

Wang, Xiqu; Jacobson, Allan J., E-mail: ajjacob@uh.edu

2016-04-15

The nanoporous frameworks VO(bdc), MIL-47, and M(OH)(bdc), MIL-53; bdc=1,4-benzenedicarboxylate, can absorb various guest species in their channels. As synthesized, the channels are filled with H{sub 2}bdc molecules that have been reported to be disordered, except for [In(OH)bdc](H{sub 2}bdc){sub 3/4}, 1, which has a inorganic-organic hybrid Vernier structure with the H{sub 2}bdc molecules forming an ordered sublattice. Based on X-ray data from large single crystals grown by hydrothermal techniques, similar Vernier structures have been found for MIL-47, [VO(bdc)](H{sub 2}bdc){sub 5/7}, 2, MIL-53Al, [Al(OH)(bdc)](H{sub 2}bdc){sub 11/16}, 3, and MIL-53Ga, [Ga(OH)(bdc)](H{sub 2}bdc){sub 12/17}, 4. The Vernier structures of 2–4 at room temperature were determined based on superstructure unit cells that index both host and guest sublattices: 2, space group P2{sub 1}, a=23.903(2), b=17.191(2), c=25.722(2) Å, β=105.914(8)°; 3, P2{sub 1}/n, a=105.224(4), b=12.2441(5), c=17.0143(6) Å, β=89.99(1)°; 4, P2{sub 1}, a=114.562(5), b=12.1503(5), c=17.4275(7) Å, β=89.99(1)°. The number of guest H{sub 2}bdc molecules per framework metal ion is determined by the ratio of the repeat distances of the two sublattices which depends on the size of the metal ion in the octahedral chain. The octahedral chains are parallel to [201] in 2, and to [100] in 3 and 4. Remarkably, all atoms in 3 and 4 show significant sinusoidal modulations transverse to the chain axis. - Graphical abstract: The sinusoidal modulation along the channel axis direction involving all atoms in the structure of [Al(OH)(bdc)](H{sub 2}bdc){sub 11/16}. - Highlights: • Crystal growth of MIL-47, MIL-53Al, and MIL-53Ga. • The Vernier structures have corner-sharing MO6 octrahedral chains and chains of H2BDC molecules. • The stoichiometry is determined by the ratio of the host framework to the guest H2BDC column lengths. • A correlation is established between the stoichiometry and the radius of the metal ion

Navy.mil - Photo Galleries

Science.gov (United States)

Personnel Command (NPC) Navy SAPR Navy EEO Inclusion And Diversity Navy Standard Integrated Personnel System (OPSEC) Navy Trademarks Military One Source USA.gov U.S. Office of Special Counsel Social Media Directory Links Navy Reserve Navy.mil Underway Navy Personnel Command (NPC) Navy SAPR Navy EEO Inclusion And

Coarse-Grain QoS-Aware Dynamic Instance Provisioning for Interactive Workload in the Cloud

Directory of Open Access Journals (Sweden)

Jianxiong Wan

2014-01-01

Full Text Available Cloud computing paradigm renders the Internet service providers (ISPs with a new approach to deliver their service with less cost. ISPs can rent virtual machines from the Infrastructure-as-a-Service (IaaS provided by the cloud rather than purchasing them. In addition, commercial cloud providers (CPs offer diverse VM instance rental services in various time granularities, which provide another opportunity for ISPs to reduce cost. We investigate a Coarse-grain QoS-aware Dynamic Instance Provisioning (CDIP problem for interactive workload in the cloud from the perspective of ISPs. We formulate the CDIP problem as an optimization problem where the objective is to minimize the VM instance rental cost and the constraint is the percentile delay bound. Since the Internet traffic shows a strong self-similar property, it is hard to get an analytical form of the percentile delay constraint. To address this issue, we purpose a lookup table structure together with a learning algorithm to estimate the performance of the instance provisioning policy. This approach is further extended with two function approximations to enhance the scalability of the learning algorithm. We also present an efficient dynamic instance provisioning algorithm, which takes full advantage of the rental service diversity, to determine the instance rental policy. Extensive simulations are conducted to validate the effectiveness of the proposed algorithms.

Facilitating Multiple Intelligences Through Multimodal Learning Analytics

Directory of Open Access Journals (Sweden)

Ayesha PERVEEN

2018-01-01

Full Text Available This paper develops a theoretical framework for employing learning analytics in online education to trace multiple learning variations of online students by considering their potential of being multiple intelligences based on Howard Gardner’s 1983 theory of multiple intelligences. The study first emphasizes the need to facilitate students as multiple intelligences by online education systems and then suggests a framework of the advanced form of learning analytics i.e., multimodal learning analytics for tracing and facilitating multiple intelligences while they are engaged in online ubiquitous learning. As multimodal learning analytics is still an evolving area, it poses many challenges for technologists, educationists as well as organizational managers. Learning analytics make machines meet humans, therefore, the educationists with an expertise in learning theories can help technologists devise latest technological methods for multimodal learning analytics and organizational managers can implement them for the improvement of online education. Therefore, a careful instructional design based on a deep understanding of students’ learning abilities, is required to develop teaching plans and technological possibilities for monitoring students’ learning paths. This is how learning analytics can help design an adaptive instructional design based on a quick analysis of the data gathered. Based on that analysis, the academicians can critically reflect upon the quick or delayed implementation of the existing instructional design based on students’ cognitive abilities or even about the single or double loop learning design. The researcher concludes that the online education is multimodal in nature, has the capacity to endorse multiliteracies and, therefore, multiple intelligences can be tracked and facilitated through multimodal learning analytics in an online mode. However, online teachers’ training both in technological implementations and

A Novel Classification Method for Syndrome Differentiation of Patients with AIDS

Directory of Open Access Journals (Sweden)

Yufeng Zhao

2015-01-01

Full Text Available We consider the analysis of an AIDS dataset where each patient is characterized by a list of symptoms and is labeled with one or more TCM syndromes. The task is to build a classifier that maps symptoms to TCM syndromes. We use the minimum reference set-based multiple instance learning (MRS-MIL method. The method identifies a list of representative symptoms for each syndrome and builds a Gaussian mixture model based on them. The models for all syndromes are then used for classification via Bayes rule. By relying on a subset of key symptoms for classification, MRS-MIL can produce reliable and high quality classification rules even on datasets with small sample size. On the AIDS dataset, it achieves average precision and recall 0.7736 and 0.7111, respectively. Those are superior to results achieved by alternative methods.

Automatic classification and detection of clinically relevant images for diabetic retinopathy

Science.gov (United States)

Xu, Xinyu; Li, Baoxin

2008-03-01

We proposed a novel approach to automatic classification of Diabetic Retinopathy (DR) images and retrieval of clinically-relevant DR images from a database. Given a query image, our approach first classifies the image into one of the three categories: microaneurysm (MA), neovascularization (NV) and normal, and then it retrieves DR images that are clinically-relevant to the query image from an archival image database. In the classification stage, the query DR images are classified by the Multi-class Multiple-Instance Learning (McMIL) approach, where images are viewed as bags, each of which contains a number of instances corresponding to non-overlapping blocks, and each block is characterized by low-level features including color, texture, histogram of edge directions, and shape. McMIL first learns a collection of instance prototypes for each class that maximizes the Diverse Density function using Expectation- Maximization algorithm. A nonlinear mapping is then defined using the instance prototypes and maps every bag to a point in a new multi-class bag feature space. Finally a multi-class Support Vector Machine is trained in the multi-class bag feature space. In the retrieval stage, we retrieve images from the archival database who bear the same label with the query image, and who are the top K nearest neighbors of the query image in terms of similarity in the multi-class bag feature space. The classification approach achieves high classification accuracy, and the retrieval of clinically-relevant images not only facilitates utilization of the vast amount of hidden diagnostic knowledge in the database, but also improves the efficiency and accuracy of DR lesion diagnosis and assessment.

Clustering with Instance and Attribute Level Side Information

Directory of Open Access Journals (Sweden)

Jinlong Wang

2010-12-01

Full Text Available Selecting a suitable proximity measure is one of the fundamental tasks in clustering. How to effectively utilize all available side information, including the instance level information in the form of pair-wise constraints, and the attribute level information in the form of attribute order preferences, is an essential problem in metric learning. In this paper, we propose a learning framework in which both the pair-wise constraints and the attribute order preferences can be incorporated simultaneously. The theory behind it and the related parameter adjusting technique have been described in details. Experimental results on benchmark data sets demonstrate the effectiveness of proposed method.

Design of a Networked Learning Master Environment for Professionals

DEFF Research Database (Denmark)

Dirckinck-Holmfeld, Lone

2010-01-01

The paper is presenting the overall learning design of MIL (Master in ICT and Learning). The learning design is integrating a number of principles: 1. Principles of problem and project based learning 2. Networked learning / learning in communities of practice. The paper will discuss how these pri......The paper is presenting the overall learning design of MIL (Master in ICT and Learning). The learning design is integrating a number of principles: 1. Principles of problem and project based learning 2. Networked learning / learning in communities of practice. The paper will discuss how...

Bivalent metal-based MIL-53 analogues: Synthesis, properties and application

International Nuclear Information System (INIS)

Liu, Yongxin; Liu, Dan; Wang, Cheng

2015-01-01

Trivalent metal-based MIL-53 (Al 3+ , Cr 3+ , Fe 3+ , In 3+ ) compounds are interesting metal–organic frameworks (MOFs) with breathing effect and are promising gas sorption materials. Replacing bridging μ 2 -OH group by neutral ligands such as pyridine N-oxide and its derivatives (PNOs), the trivalent metal-based MIL-53 analogous structures could be extended to bivalent metal systems. The introduction of PNOs and bivalent metal elements endows the frameworks with new structural features and physical and chemical properties. This minireview summarizes the recent development of bivalent metal-based MIL-53 analogues (Mn 2+ , Co 2+ , Ni 2+ ), typically, focusing on the synthetic strategies and potential applications based on our own works and literatures. We present the synthetic strategy to achieve structures evolution from single-ligand-walled to double-ligand-walled channel. Properties and application of these new materials in a wide range of potential areas are discussed including thermal stability, gas adsorption, magnetism and liquid-phase separation. Promising directions of this research field are also highlighted. - Graphical abstract: The recent development of bivalent metal-based MIL-53 analogues (Mn 2+ , Co 2+ , Ni 2+ ) on their synthetic strategies, properties and potential applications was reviewed. - Highlights: • Structure features of bivalent metal-based MIL-53 analogues are illustrated. • Important properties and application are presented. • Host–guest interactions are main impetus for liquid-phase separation. • Promising directions of bivalent metal-based MIL-53 analogues are highlighted

Multi-label Learning with Missing Labels Using Mixed Dependency Graphs

KAUST Repository

Wu, Baoyuan; Jia, Fan; Liu, Wei; Ghanem, Bernard; Lyu, Siwei

2018-01-01

This work focuses on the problem of multi-label learning with missing labels (MLML), which aims to label each test instance with multiple class labels given training instances that have an incomplete/partial set of these labels (i.e., some

Study on adsorption refrigeration performance of MIL-101-isobutane working pair

International Nuclear Information System (INIS)

Ma, Liejun; Yang, Huan; Wu, Qi; Yin, Yu; Liu, Zongjian; Cui, Qun; Wang, Haiyan

2015-01-01

Rising concerns about pro-environment and energy conservation bring about the escalating interests in adsorption cooling systems using renewable energy. Adsorption chillers with common refrigerants (water, ethanol, methanol, etc.) face the problem that advanced technologies and intricate design considerations are required to maintain high vacuum. This paper aims at the parameters optimization of adsorption system being operated with the novel working pair, MIL-101-isobutane, under typical conditions of ice making and air-condition. Adsorption isotherms and dynamic of isobutane on MIL-101 are discussed simultaneously. When the hot water inlet temperature, cooling water temperature and desorption time are 95 °C, 30 °C and 30 min, respectively, the cooling capacity is 45.7 kJ/kg, which is 1.7 times as much as that of activated carbon–isobutane pair. Structural stability of MIL-101 subjected to 500 times adsorption/desorption cycles has been successfully verified by XRD (X-ray diffraction). - Highlights: • Adsorption isotherms and kinetic of isobutane on MIL-101 were studied. • A single bed adsorption chiller with MIL-101-isobutane pair was built. • System performed better than that using activated carbon–isobutane pair. • Stability of MIL-101 subjected to 500 ad/desorption cycles has been verified.

Facilitating Multiple Intelligences through Multimodal Learning Analytics

Science.gov (United States)

Perveen, Ayesha

2018-01-01

This paper develops a theoretical framework for employing learning analytics in online education to trace multiple learning variations of online students by considering their potential of being multiple intelligences based on Howard Gardner's 1983 theory of multiple intelligences. The study first emphasizes the need to facilitate students as…

Hydrogen storage behaviors of Ni-doped graphene Oxide/MIL-101 hybrid composites.

Science.gov (United States)

Lee, Seul-Yi; Park, Soo-Jin

2013-01-01

In this work, Ni-doped graphene oxide/MIL-101 hybrid composites (Ni--GO/MIL) were prepared to investigate their hydrogen storage behaviors. Ni--GO/MIL was synthesized by adding Ni--GO in situ during the synthesis of MIL-101 using a hydrothermal process, which was conducted by conventional convection heating with Cr(III) ion as a metal center and telephthalic acid as organic ligands. The crystalline structures and morphologies were measured by X-ray diffraction (XRD) and scanning electron microscopy (SEM), respectively. The specific surface area and micropore volume were investigated by N2/77 K adsorption isotherms using the Brunauer-Emmett-Teller (BET) method and Dubinin-Radushkevic (D-R) equation, respectively. The hydrogen storage capacity was investigated by BEL-HP at 77 K and 1 bar. The obtained results show that Ni--GO/MIL presents new directions for achieving novel hybrid materials with higher hydrogen storage capacity.

Beyond cross-domain learning: Multiple-domain nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan; Gao, Xin

2014-01-01

Traditional cross-domain learning methods transfer learning from a source domain to a target domain. In this paper, we propose the multiple-domain learning problem for several equally treated domains. The multiple-domain learning problem assumes that samples from different domains have different distributions, but share the same feature and class label spaces. Each domain could be a target domain, while also be a source domain for other domains. A novel multiple-domain representation method is proposed for the multiple-domain learning problem. This method is based on nonnegative matrix factorization (NMF), and tries to learn a basis matrix and coding vectors for samples, so that the domain distribution mismatch among different domains will be reduced under an extended variation of the maximum mean discrepancy (MMD) criterion. The novel algorithm - multiple-domain NMF (MDNMF) - was evaluated on two challenging multiple-domain learning problems - multiple user spam email detection and multiple-domain glioma diagnosis. The effectiveness of the proposed algorithm is experimentally verified. © 2013 Elsevier Ltd. All rights reserved.

Beyond cross-domain learning: Multiple-domain nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan

2014-02-01

Traditional cross-domain learning methods transfer learning from a source domain to a target domain. In this paper, we propose the multiple-domain learning problem for several equally treated domains. The multiple-domain learning problem assumes that samples from different domains have different distributions, but share the same feature and class label spaces. Each domain could be a target domain, while also be a source domain for other domains. A novel multiple-domain representation method is proposed for the multiple-domain learning problem. This method is based on nonnegative matrix factorization (NMF), and tries to learn a basis matrix and coding vectors for samples, so that the domain distribution mismatch among different domains will be reduced under an extended variation of the maximum mean discrepancy (MMD) criterion. The novel algorithm - multiple-domain NMF (MDNMF) - was evaluated on two challenging multiple-domain learning problems - multiple user spam email detection and multiple-domain glioma diagnosis. The effectiveness of the proposed algorithm is experimentally verified. © 2013 Elsevier Ltd. All rights reserved.

ML-MG: Multi-label Learning with Missing Labels Using a Mixed Graph

KAUST Repository

Wu, Baoyuan; Lyu, Siwei; Ghanem, Bernard

2015-01-01

This work focuses on the problem of multi-label learning with missing labels (MLML), which aims to label each test instance with multiple class labels given training instances that have an incomplete/partial set of these labels (i.e. some

Master in ICT and Learning

DEFF Research Database (Denmark)

Danielsen, Oluf

2004-01-01

The Master in ICT and Learning (MIL)was started in 2000, and it is owned in collaboration by five Danish universities. It is an accredited virtual part-time 2-year education. MIL is unique in that it builds on the pedagogical framework of project pedagogy and is based in virtual collaboration....... It is organized around ICT and Learning. This is illustrated through a presentation of the study program, the four modules, the projects and the master thesis....

Adsorptive removal of dibenzothiophene from model fuels over one-pot synthesized PTA@MIL-101(Cr) hybrid material

Energy Technology Data Exchange (ETDEWEB)

Jia, Shao-Yi; Zhang, Yan-Fei [School of Chemical Engineering and Technology, Tianjin University, Tianjin (China); Liu, Yong [School of Chemistry and Chemical Engineering, Tianjin University of Technology, Tianjin (China); Qin, Feng-Xiang; Ren, Hai-Tao [School of Chemical Engineering and Technology, Tianjin University, Tianjin (China); Wu, Song-Hai, E-mail: songhaiwu@gmail.com [School of Chemical Engineering and Technology, Tianjin University, Tianjin (China)

2013-11-15

Highlights: • One-pot synthesized PTA@MIL-101(Cr) shows high capacity of benzothiophene. • PTA/MIL-101(Cr) obtained via post-modification performs poor in the adsorption. • PTA and MIL-101(Cr) exhibit synergetic effect on adsorption of benzothiophene. • In the presence of aromatics, PTA@MIL-101(Cr) and MIL-101(Cr) remain their capacity. • PTA-dispersed MOFs adsorb dibenzothiophene through acid–base interaction. -- Abstract: Hybrid nanomaterials comprising phosphotungstic acid (PTA) and MIL-101(Cr) were prepared through one-pot synthesis and post-modification methods and then were used as adsorbents of dibenzothiophene (DBT) from simulated diesel fuels. Samples obtained by different ways (encapsulation and impregnation) were characterized by nitrogen adsorption, transmission electron microscope (TEM), X-ray diffraction (XRD), Fourier transform infrared spectrum (FT-IR) and series of adsorption experiments. The equilibrium adsorption capacities of PTA@MIL-101(Cr) illustrated that the direct introduction of PTA into MIL-101(Cr) during synthesis resulted in a 10.7% increase compared with MIL-101(Cr). However, porous hybrid adsorbent PTA/MIL-101(Cr) prepared via post-modification method exhibited lower adsorption capacity than virgin MIL-101(Cr). The theoretical maximum adsorption capacity (Q{sub 0}) of PTA@MIL-101(Cr) is 136.5 mg S/g adsorbent, 4.2 times of MIL-101(Cr). Even in competitive adsorption between aromatic compounds, which possess strong affinity with MOFs, and DBT, PTA@MIL-101(Cr) and MIL-101(Cr) remained their effectiveness in removal of DBT in the system. Based on these results, it can be presumed that MIL-101(Cr), modified properly, can be used as a promising adsorbent for eliminating aromatics and S-compounds in commercial fuels simultaneously.

Anti-UV Radiation Textiles Designed by Embracing with Nano-MIL (Ti, In)-Metal Organic Framework.

Science.gov (United States)

Emam, Hossam E; Abdelhameed, Reda M

2017-08-23

Protective textiles against harmful solar radiation are quite important materials for outdoor workers to secure their skin from several diseases. Current report focuses on production of anti-ultraviolet radiation (UVR) textiles by incorporation of nano-metal-organic frameworks (n-MOFs). Two different MIL-MOFs, namely, MIL-68(In)-NH 2 and MIL-125(Ti)-NH 2 , were immediately formed inside natural textiles (cotton and silk) matrix in nano size using quite simple and one-pot process. The formation of n-MIL-MOFs inside textiles were confirmed by using electron microscope and X-ray diffraction. Different size and morphology were seen depending on textile type reflecting the textiles' chemical composition role in the nature of prepared MIL-MOFs. For MIL-68(In)-NH 2 , particles with size distribution of 70.6-44.5 nm in cotton and 81.3-52.2 nm in silk were detected, while crystalline disc of MIL-125(Ti)-NH 2 was clearly seen inside textiles. The natural textiles exhibited full UVR blocking after modification, and the UV protection factor (UPF) was linearly proportional with MIL-MOFs and metal contents. Whatever metal type, direct incorporation of MIL-MOF contents greater than or equal to 10.4 g/kg was sufficient to attain excellent UV blocking property. Although 38.5-41.0% of MIL-MOFs was lost during five washings, the washed samples showed very good blocking rate (UPF = 26.7-36.2) supporting good laundering durability.

Late Bombardment of the Lunar Highlands Recorded in MIL 090034, MIL 090036 and MIL 090070 Lunar Meteorites

Science.gov (United States)

Park, J.; Nyquist, L. E.; Shih, C.-Y.; Herzog, G. F.; Yamaguchi, A.; Shirai, N.; Ebihara, M.; Lindsay, F. N.; Delaney, J.; Turrin, B.;

Fracture toughness of Ceramic-Fiber-Reinforced Metallic-Intermetallic-Laminate (CFR-MIL) composites

International Nuclear Information System (INIS)

Vecchio, Kenneth S.; Jiang, Fengchun

2016-01-01

Novel Ceramic-Fiber-Reinforced-Metal-Intermetallic-Laminate (CFR-MIL) composites, Ti–Al 3 Ti–Al 2 O 3 –Al, were synthesized by reactive foil sintering in air. Microstructure controlled material architectures were achieved with continuous Al 2 O 3 fibers oriented in 0° and 90° layers to form fully dense composites in which the volume fractions of all four component phases can be tailored. Bend fracture specimens were cut from the laminate plates in divider orientation, and bend tests were performed to study the fracture behavior of CFR-MIL composites under three-point and four-point bending loading conditions. The microstructures and fractured surfaces of the CFR-MIL composites were examined using optical microscopy and scanning electron microscopy to establish a correlation between the fracture toughness, fracture surface morphology and microstructures of CFR-MIL composites. The fracture and toughening mechanisms of the CFR-MIL composites are also addressed. The present experimental results indicate that the fracture toughness of CFR-MIL composites determined by three- and four-point bend loading configurations are quite similar, and increased significantly compared to MIL composites without ceramic fiber reinforcement. The interface cracking behavior is related to the volume fraction of the brittle Al 3 Ti phase and residual ductile Al, but the fracture toughness values appear to be insensitive to the ratio of these two phases. The toughness appears to be dominated by the ductility/strength of the Ti layers and the strength and crack bridging effect of the ceramic fibers.

Curation and Allocation of the New Antarctic Nakhlite, MIL03346

Science.gov (United States)

McBride, K. M.; Righter, K.; Satterwhite, C. E.; Schwarz, C.; Robinson, P.

2005-01-01

In January 2004, the ANSMET reconnaissance field team (Fig. 1) working in the Miller Range of the Transantarctic Mountains discovered a 715 g achondrite that was instantly recognized as unique. Named MIL03346, initial processing (NASA Johnson Space Center or JSC) and classification (Smithsonian Institution or SI) revealed this achondrite to be a nakhlite (Fig. 2). MIL03346 is the seventh nakhlite recognized in world collections [2], the third nakhlite returned from Antartica, and the first nakhlite in the US Antarctic collection (Table 1). The following is a summary of the steps taken in the processing and allocating of MIL 03346 and some comparisons to some other lunar and martian meteorites processed and allocated at JSC.

Application of Metal-Organic Framework Nano-MIL-100(Fe) for Sustainable Release of Doxycycline and Tetracycline.

Science.gov (United States)

Taherzade, Seyed Dariush; Soleimannejad, Janet; Tarlani, Aliakbar

2017-08-06

Nanostructures of MIL-100 were synthesized and used as a drug delivery platform for two members of the Tetracycline family. Doxycycline monohydrate (DOX) and Tetracycline hydrochloride (TC) were loaded separately on nano-MIL-100 (nanoparticles of drug@carrier were abbreviated as DOX@MIL-100 and TC@MIL-100). Characterizations were carried out using FT-IR, XRD, BET, DLS, and SEM. The FT-IR spectra revealed that the drugs were loaded into the framework of the carrier. The XRD patterns of DOX@MIL-100 and TC@MIL-100 indicated that no free DOX or TC were present. It could be concluded that the drugs are well dispersed into the pores of nano-MIL-100. The microporosity of the carrier was confirmed by BJH data. BET analysis showed a reduction in the free surface for both DOX@MIL-100 and TC@MIL-100. The release of TC and DOX was investigated, and it was revealed that MIL-100 mediated the drug solubility in water, which in turn resulted in a decrease in the release rate of TC (accelerating in DOX case) without lowering the total amount of released drug. After 48 h, 96 percent of the TC was sustain released, which is an unprecedented amount in comparison with other methods.

The multiple reals of workplace learning

Directory of Open Access Journals (Sweden)

Kerry Harman

2014-04-01

Full Text Available The multiple reals of workplace learning are explored in this paper. Drawing on a Foucauldian conceptualisation of power as distributed, relational and productive, networks that work to produce particular objects and subjects as seemingly natural and real are examined. This approach enables different reals of workplace learning to be traced. Data from a collaborative industry-university research project is used to illustrate the approach, with a focus on the intersecting practices of a group of professional developers and a group of workplace learning researchers. The notion of multiple reals holds promise for research on workplace learning as it moves beyond a view of reality as fixed and singular to a notion of reality as performed in and through a diversity of practices, including the practices of workplace learning researchers.

MIL-68 (In) nano-rods for the removal of Congo red dye from aqueous solution.

Science.gov (United States)

Jin, Li-Na; Qian, Xin-Ye; Wang, Jian-Guo; Aslan, Hüsnü; Dong, Mingdong

2015-09-01

MIL-68 (In) nano-rods were prepared by a facile solvothermal synthesis using NaOAc as modulator agent at 100°C for 30 min. The BET test showed that the specific surface area and pore volume of MIL-68 (In) nanorods were 1252 m(2) g(-1) and 0.80 cm(3) g(-1), respectively. The as-prepared MIL-68 (In) nanorods showed excellent adsorption capacity and rapid adsorption rate for removal of Congo red (CR) dye from water. The maximum adsorption capacity of MIL-68 (In) nanorods toward CR reached 1204 mg g(-1), much higher than MIL-68 (In) microrods and most of the previously reported adsorbents. The adsorption process of CR by MIL-68 (In) nano-rods was investigated and found to be obeying the Langmuir adsorption model in addition to pseudo-second-order rate equation. Moreover, the MIL-68 (In) nanorods showed an acceptable reusability after regeneration with ethanol. All information gives an indication that the as-prepared MIL-68 (In) nanorods show their potential as the adsorbent for highly efficient removal of CR in wastewater. Copyright © 2015 Elsevier Inc. All rights reserved.

Veto-Consensus Multiple Kernel Learning

NARCIS (Netherlands)

Zhou, Y.; Hu, N.; Spanos, C.J.

2016-01-01

We propose Veto-Consensus Multiple Kernel Learning (VCMKL), a novel way of combining multiple kernels such that one class of samples is described by the logical intersection (consensus) of base kernelized decision rules, whereas the other classes by the union (veto) of their complements. The

Multifunctional polyoxometalates encapsulated in MIL-100(Fe): highly efficient photocatalysts for selective transformation under visible light.

Science.gov (United States)

Liang, Ruowen; Chen, Rui; Jing, Fenfen; Qin, Na; Wu, Ling

2015-11-07

H3PMo12O40 molecules have been successfully encapsulated in the cavities of MIL-100(Fe) via a facile hydrothermal method (denoted as HPMo@MIL-100(Fe)). A series of characterization has corroborated the insertion of H3PMo12O40 within the cavities of MIL-100(Fe). The resulting HPMo@MIL-100(Fe) nanocomposites have exhibited much higher photoactivity than the original-MIL-100(Fe) toward the photocatalytic selective oxidation of benzylic alcohols and the reduction of Cr(vi) under visible light irradiation (λ≥ 420 nm). The higher photoactivity of HPMo@MIL-100(Fe) can be attributed to the integrative effect of enhanced light absorption intensity and more efficient separation of photogenerated electron-hole pairs. The host porous structure of MIL-100(Fe) can achieve a uniform composition with H3PMo12O40, which is significantly important for producing highly reactive dispersed H3PMo12O40 molecules and enhancing the photocatalytic activity of HPMo@MIL-100(Fe) nanocomposites. And the immobilized H3PMo12O40 molecules are more convenient for recycling. Importantly, almost no Fe and Mo ions leach from the MIL-100(Fe) during the reaction, which verifies the photostability of the HPMo@MIL-100(Fe). In addition, possible photocatalytic redox reaction mechanisms have been investigated.

Comparative analysis of instance selection algorithms for instance-based classifiers in the context of medical decision support

International Nuclear Information System (INIS)

Mazurowski, Maciej A; Tourassi, Georgia D; Malof, Jordan M

2011-01-01

When constructing a pattern classifier, it is important to make best use of the instances (a.k.a. cases, examples, patterns or prototypes) available for its development. In this paper we present an extensive comparative analysis of algorithms that, given a pool of previously acquired instances, attempt to select those that will be the most effective to construct an instance-based classifier in terms of classification performance, time efficiency and storage requirements. We evaluate seven previously proposed instance selection algorithms and compare their performance to simple random selection of instances. We perform the evaluation using k-nearest neighbor classifier and three classification problems: one with simulated Gaussian data and two based on clinical databases for breast cancer detection and diagnosis, respectively. Finally, we evaluate the impact of the number of instances available for selection on the performance of the selection algorithms and conduct initial analysis of the selected instances. The experiments show that for all investigated classification problems, it was possible to reduce the size of the original development dataset to less than 3% of its initial size while maintaining or improving the classification performance. Random mutation hill climbing emerges as the superior selection algorithm. Furthermore, we show that some previously proposed algorithms perform worse than random selection. Regarding the impact of the number of instances available for the classifier development on the performance of the selection algorithms, we confirm that the selection algorithms are generally more effective as the pool of available instances increases. In conclusion, instance selection is generally beneficial for instance-based classifiers as it can improve their performance, reduce their storage requirements and improve their response time. However, choosing the right selection algorithm is crucial.

Synthesis of MIL-100(Fe at Low Temperature and Atmospheric Pressure

Directory of Open Access Journals (Sweden)

Jing Shi

2013-01-01

Full Text Available MIL-100(Fe, a mesoporous metal-organic framework (MOF, has a large BET specific surface area and pore volume with the presence of a significant amount of accessible Lewis acid metal sites upon dehydration. The structural characteristics of MIL-100(Fe make it a good candidate for potential applications in gas storage, separation, and heterogeneous catalysis. Mainly, this MOF is obtained by the hydrothermal synthesis in a Teflon-lined autoclave at high temperature (>150°C under static conditions. However, this method has several disadvantages such as high temperature, high (autogenous pressure, long time, and comparable low MOF yield. Therefore, development of a facile method for synthesis of MIL-100(Fe is vitally important for fundamental understanding and practical application. Herein, MIL-100(Fe is synthesized by a facile low-temperature (90% still could be achieved, suggesting that this simple and energy saving method has the potential to be used practically.

Multiple-choice pretesting potentiates learning of related information.

Science.gov (United States)

Little, Jeri L; Bjork, Elizabeth Ligon

2016-10-01

Although the testing effect has received a substantial amount of empirical attention, such research has largely focused on the effects of tests given after study. The present research examines the effect of using tests prior to study (i.e., as pretests), focusing particularly on how pretesting influences the subsequent learning of information that is not itself pretested but that is related to the pretested information. In Experiment 1, we found that multiple-choice pretesting was better for the learning of such related information than was cued-recall pretesting or a pre-fact-study control condition. In Experiment 2, we found that the increased learning of non-pretested related information following multiple-choice testing could not be attributed to increased time allocated to that information during subsequent study. Last, in Experiment 3, we showed that the benefits of multiple-choice pretesting over cued-recall pretesting for the learning of related information persist over 48 hours, thus demonstrating the promise of multiple-choice pretesting to potentiate learning in educational contexts. A possible explanation for the observed benefits of multiple-choice pretesting for enhancing the effectiveness with which related nontested information is learned during subsequent study is discussed.

An Investigation between Multiple Intelligences and Learning Styles

Science.gov (United States)

Sener, Sabriye; Çokçaliskan, Ayten

2018-01-01

Exploring learning style and multiple intelligence type of learners can enable the students to identify their strengths and weaknesses and learn from them. It is also very important for teachers to understand their learners' learning styles and multiple intelligences since they can carefully identify their goals and design activities that can…

Learning through Work: Exploring Instances of Relational Interdependencies

Science.gov (United States)

Billett, Stephen

2008-01-01

This paper provides an account of the inter-psychological processes that constitute learning through work. It does this by drawing on deliberations about the relative contributions of the immediate social world (i.e., workplace setting) that individuals encounter and the personal premises for individuals' learning. This account is realised through…

Adsorptive removal of dibenzothiophene from model fuels over one-pot synthesized PTA@MIL-101(Cr) hybrid material.

Science.gov (United States)

Jia, Shao-Yi; Zhang, Yan-Fei; Liu, Yong; Qin, Feng-Xiang; Ren, Hai-Tao; Wu, Song-Hai

2013-11-15

Hybrid nanomaterials comprising phosphotungstic acid (PTA) and MIL-101(Cr) were prepared through one-pot synthesis and post-modification methods and then were used as adsorbents of dibenzothiophene (DBT) from simulated diesel fuels. Samples obtained by different ways (encapsulation and impregnation) were characterized by nitrogen adsorption, transmission electron microscope (TEM), X-ray diffraction (XRD), Fourier transform infrared spectrum (FT-IR) and series of adsorption experiments. The equilibrium adsorption capacities of PTA@MIL-101(Cr) illustrated that the direct introduction of PTA into MIL-101(Cr) during synthesis resulted in a 10.7% increase compared with MIL-101(Cr). However, porous hybrid adsorbent PTA/MIL-101(Cr) prepared via post-modification method exhibited lower adsorption capacity than virgin MIL-101(Cr). The theoretical maximum adsorption capacity (Q0) of PTA@MIL-101(Cr) is 136.5mg S/g adsorbent, 4.2 times of MIL-101(Cr). Even in competitive adsorption between aromatic compounds, which possess strong affinity with MOFs, and DBT, PTA@MIL-101(Cr) and MIL-101(Cr) remained their effectiveness in removal of DBT in the system. Based on these results, it can be presumed that MIL-101(Cr), modified properly, can be used as a promising adsorbent for eliminating aromatics and S-compounds in commercial fuels simultaneously. Copyright © 2013 Elsevier B.V. All rights reserved.

Multiple Kernel Learning with Data Augmentation

Science.gov (United States)

2016-11-22

JMLR: Workshop and Conference Proceedings 63:49–64, 2016 ACML 2016 Multiple Kernel Learning with Data Augmentation Khanh Nguyen nkhanh@deakin.edu.au...University, Australia Editors: Robert J. Durrant and Kee-Eung Kim Abstract The motivations of multiple kernel learning (MKL) approach are to increase... kernel expres- siveness capacity and to avoid the expensive grid search over a wide spectrum of kernels . A large amount of work has been proposed to

Molecular simulations of a CO2/CO mixture in MIL-127

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Chokbunpiam, Tatiya; Fritzsche, Siegfried; Parasuk, Vudhichai; Caro, Jürgen; Assabumrungrat, Suttichai

2018-03-01

Adsorption and diffusion of an equimolar feed mixture of CO2 and CO in MIL-127 at three different temperatures and pressures up to 12 bar were investigated by molecular simulations. The adsorption was simulated using Gibbs-Ensemble Monte Carlo (GEMC). The structure of the adsorbed phase and the diffusion in the MIL were investigated using Molecular Dynamics (MD) simulations. The adsorption selectivity of MIL-127 for CO2 over CO at 233 K was about 15. When combining adsorption and diffusion selectivities, a membrane selectivity of about 12 is predicted. For higher temperatures, both adsorption and diffusion selectivity are found to be smaller.

MIL-53(Fe) MOF-mediated catalytic chemiluminescence for sensitive detection of glucose.

Science.gov (United States)

Yi, Xueling; Dong, Wenfei; Zhang, Xiaodan; Xie, Jianxin; Huang, Yuming

2016-12-01

Various analytical applications of metal-organic frameworks (MOFs) have been rapidly developed in the past few years. However, the employment of MOFs as catalysts in chemiluminescence (CL) analysis is rare. Here, for the first time, we found that MIL-53(Fe) MOFs could significantly enhance the CL of luminol in the presence of H 2 O 2 in an alkaline medium. The CL intensity in the luminol-H 2 O 2 -MIL-53(Fe) system was about 20 times higher than that in the luminol-H 2 O 2 system. Moreover, the XRD pattern of MIL-53(Fe) after CL reaction was almost the same as that of the original MIL-53(Fe), confirming the catalytic role of MIL-53(Fe) in the luminol-H 2 O 2 -MIL-53(Fe) system. The possible mechanism behind the enhancing phenomenon was discussed based on the results from the CL spectra, FL probe experiments, and active oxygen species measurements. By coupling with the glucose oxidase-based catalytic oxidation reaction, a sensitive and selective CL method was developed for the detection of glucose. There is a linear relationship between the logarithm of CL intensity and the logarithm of glucose concentration in the range from 0.1 to 10 μM, and a detection limit of 0.05 μM (S/N = 3) is obtained. The proposed method has been applied to the determination of glucose in human serum samples with satisfactory results. Graphical abstract MIL-53(Fe) MOFs are found to greatly enhance the chemiluminescence emission of the luminol-H 2 O 2 system, and this finding resulted in a new chemiluminescence method for biosensing of glucose when coupled with the glucose oxidase.

Organic Linker Defines the Excited-State Decay of Photocatalytic MIL-125(Ti)-Type Materials.

Science.gov (United States)

Santaclara, Jara G; Nasalevich, Maxim A; Castellanos, Sonia; Evers, Wiel H; Spoor, Frank C M; Rock, Kamila; Siebbeles, Laurens D A; Kapteijn, Freek; Grozema, Ferdinand; Houtepen, Arjan; Gascon, Jorge; Hunger, Johannes; van der Veen, Monique A

2016-02-19

Recently, MIL-125(Ti) and NH2 -MIL-125(Ti), two titanium-based metal-organic frameworks, have attracted significant research attention in the field of photocatalysis for solar fuel generation. This work reveals that the differences between these structures are not only based on their light absorption range but also on the decay profile and topography of their excited states. In contrast to MIL-125(Ti), NH2 -MIL-125(Ti) shows markedly longer lifetimes of the charge-separated state, which improves photoconversion by the suppression of competing decay mechanisms. We used spectroelectrochemistry and ultrafast spectroscopy to demonstrate that upon photoexcitation in NH2 -MIL-125(Ti) the electron is located in the Ti-oxo clusters and the hole resides on the aminoterephthalate unit, specifically on the amino group. The results highlight the role of the amino group in NH2 -MIL-125(Ti), the electron donation of which extends the lifetime of the photoexcited state substantially. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CO2/CH4 Separation by a Mixed Matrix Membrane of Polymethylpentyne/MIL-53 Particles

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Reza Abedini

2014-10-01

Full Text Available The effect of Materials Institute Lavoisier-53 (MIL-53 particles on gas transport properties of polymethylpentyne (PMP was investigated. MIL-53 was added to the polymer matrix with different loadings of 10, 20 and 30 wt%. The properties of MIL-53 and prepared membranes were analyzed through FTIR, SEM and TGA methods. The adsorption of CO2 and CH4 was conducted and analyzed accurately through Langmuir equation to investigate the gas transport properties of membranes. The results from TGA showed that degradation temperature (Td increases significantly with increasing MIL-53 loading. SEM images demonstrated that MIL-53 particles dispersed well in polymer matrix with no considerable agglomeration and no non-selective void formation at polymer/filler interface. In addition, CO2 and CH4 permeability measurement along with calculation of CO2/CH4 selectivity were performed. The results showed that the permeability of gases (especially for CO2 increased significantly by increasing the MIL-53 loading. Additionally, CO2/CH4 selectivity showed an increasing trend with increasing the MIL-53 weight percent. Unlike CH4, the CO2 solubility coefficient increased with increasing the MIL-53 loading because of high free volume of membrane and selective adsorption of CO2 with MIL-53. Despite CO2 solubility enhancement its diffusivity coefficient remained more or less unchanged. The enhancement in CH4 permeability has been mainly attributed to its slight incremental diffusivity due to the membrane's increasingly higher free volume. Finally, a comparison between membranes performance and CO2/CH4 Robeson upper bound showed that, the performance of membranes improved due to the presence of MIL-53 which was very close to the Robeson bound.

The role of inertia in modeling decisions from experience with instance-based learning.

Science.gov (United States)

Dutt, Varun; Gonzalez, Cleotilde

2012-01-01

One form of inertia is the tendency to repeat the last decision irrespective of the obtained outcomes while making decisions from experience (DFE). A number of computational models based upon the Instance-Based Learning Theory, a theory of DFE, have included different inertia implementations and have shown to simultaneously account for both risk-taking and alternations between alternatives. The role that inertia plays in these models, however, is unclear as the same model without inertia is also able to account for observed risk-taking quite well. This paper demonstrates the predictive benefits of incorporating one particular implementation of inertia in an existing IBL model. We use two large datasets, estimation and competition, from the Technion Prediction Tournament involving a repeated binary-choice task to show that incorporating an inertia mechanism in an IBL model enables it to account for the observed average risk-taking and alternations. Including inertia, however, does not help the model to account for the trends in risk-taking and alternations over trials compared to the IBL model without the inertia mechanism. We generalize the two IBL models, with and without inertia, to the competition set by using the parameters determined in the estimation set. The generalization process demonstrates both the advantages and disadvantages of including inertia in an IBL model.

Glucose recovery from aqueous solutions by adsorption in metal-organic framework MIL-101: a molecular simulation study.

Science.gov (United States)

Gupta, Krishna M; Zhang, Kang; Jiang, Jianwen

2015-08-05

A molecular simulation study is reported on glucose recovery from aqueous solutions by adsorption in metal-organic framework MIL-101. The F atom of MIL-101 is identified to be the most favorable adsorption site. Among three MIL-101-X (X = H, NH2 or CH3), the parent MIL-101 exhibits the highest adsorption capacity and recovery efficacy. Upon functionalization by -NH2 or -CH3 group, the steric hindrance in MIL-101 increases; consequently, the interactions between glucose and framework become less attractive, thus reducing the capacity and mobility of glucose. The presence of ionic liquid, 1-ethyl-3-methyl-imidazolium acetate, as an impurity reduces the strength of hydrogen-bonding between glucose and MIL-101, and leads to lower capacity and mobility. Upon adding anti-solvent (ethanol or acetone), a similar adverse effect is observed. The simulation study provides useful structural and dynamic properties of glucose in MIL-101, and it suggests that MIL-101 might be a potential candidate for glucose recovery.

Small Explorer Data System MIL-STD-1773 fiber optic bus

Science.gov (United States)

Flanegan, Mark; Label, Ken

1992-01-01

The MIL-STD-1773 Fiber Optic Data Bus as implemented in the GSFC Small Explorer Data System (SEDS) for the Small Explorer Program is described. It provides an overview of the SEDS MIL-STD-1773 bus components system design considerations, reliability figures, acceptance and qualification testing requirements, radiation requirements and tests, error handling considerations, and component heritage. The first mission using the bus will be launched in June of 1992.

1 mil gold bond wire study.

Energy Technology Data Exchange (ETDEWEB)

Huff, Johnathon; McLean, Michael B.; Jenkins, Mark W.; Rutherford, Brian Milne

2013-05-01

In microcircuit fabrication, the diameter and length of a bond wire have been shown to both affect the current versus fusing time ratio of a bond wire as well as the gap length of the fused wire. This study investigated the impact of current level on the time-to-open and gap length of 1 mil by 60 mil gold bond wires. During the experiments, constant current was provided for a control set of bond wires for 250ms, 410ms and until the wire fused; non-destructively pull-tested wires for 250ms; and notched wires. The key findings were that as the current increases, the gap length increases and 73% of the bond wires will fuse at 1.8A, and 100% of the wires fuse at 1.9A within 60ms. Due to the limited scope of experiments and limited data analyzed, further investigation is encouraged to confirm these observations.

Preparation of magnetic MIL-101 (Cr) for efficient removal of ciprofloxacin.

Science.gov (United States)

Bayazit, Şahika Sena; Danalıoğlu, Selen Tuğba; Abdel Salam, Mohamed; Kerkez Kuyumcu, Özge

2017-11-01

Metal organic frameworks are widely used as adsorbent materials in recent years. In this study, the most prepared metal organic framework MIL-101 was prepared by hydrothermal method and featured magnetic property using co-precipitation method Fe 3 O 4 . Then, the prepared composite (MIL-101/Fe 3 O 4 ) was first characterized using XRD, FTIR, SEM-EDS, and surface area analysis, then was used for the adsorptive removal of the most used antibiotic, ciprofloxacin (CIP). The effect of different adsorption variables which may affect the removal of CIP by MIL-101/Fe 3 O 4 was investigated, as well as their adsorbent quantity, initial CIP concentration, pH, temperature, and contact time. The non-linear Langmuir and Freundlich isotherm were applied to experimental data. It was observed that rising solution temperature decreases adsorption efficiency, as the maximum adsorption uptake value was 63.28 mg g -1 at 298 K and 22.93 mg g -1 at 313 K, indicating the exothermic nature of the adsorption. The adsorption was studied kinetically and found to follow the pseudo-second-order kinetic model. The desorption of CIP from the MIL-101/Fe 3 O 4 was investigated using three different eluents, and the results showed that phosphate-buffered solution was the most effective desorption eluent. Graphical abstract Schematic diagram of the preparation steps of MIL-101/Fe3O4.

Glucose recovery from aqueous solutions by adsorption in metal–organic framework MIL-101: a molecular simulation study

Science.gov (United States)

Gupta, Krishna M.; Zhang, Kang; Jiang, Jianwen

2015-01-01

A molecular simulation study is reported on glucose recovery from aqueous solutions by adsorption in metal-organic framework MIL-101. The F atom of MIL-101 is identified to be the most favorable adsorption site. Among three MIL-101-X (X = H, NH2 or CH3), the parent MIL-101 exhibits the highest adsorption capacity and recovery efficacy. Upon functionalization by -NH2 or -CH3 group, the steric hindrance in MIL-101 increases; consequently, the interactions between glucose and framework become less attractive, thus reducing the capacity and mobility of glucose. The presence of ionic liquid, 1-ethyl-3-methyl-imidazolium acetate, as an impurity reduces the strength of hydrogen-bonding between glucose and MIL-101, and leads to lower capacity and mobility. Upon adding anti-solvent (ethanol or acetone), a similar adverse effect is observed. The simulation study provides useful structural and dynamic properties of glucose in MIL-101, and it suggests that MIL-101 might be a potential candidate for glucose recovery. PMID:26242874

Comparative Study of MIL-96(Al) as Continuous Metal-Organic Frameworks Layer and Mixed-Matrix Membrane.

Science.gov (United States)

Knebel, Alexander; Friebe, Sebastian; Bigall, Nadja Carola; Benzaqui, Marvin; Serre, Christian; Caro, Jürgen

2016-03-23

MIL-96(Al) layers were prepared as supported metal-organic frameworks membrane via reactive seeding using the α-alumina support as the Al source for the formation of the MIL-96(Al) seeds. Depending on the solvent mixture employed during seed formation, two different crystal morphologies, with different orientation of the transport-active channels, have been formed. This crystal orientation and habit is predefined by the seed crystals and is kept in the subsequent growth of the seeds to continuous layers. In the gas separation of an equimolar H2/CO2 mixture, the hydrogen permeability of the two supported MIL-96(Al) layers was found to be highly dependent on the crystal morphology and the accompanied channel orientation in the layer. In addition to the neat supported MIL-96(Al) membrane layers, mixed-matrix membranes (MMMs, 10 wt % filler loading) as a composite of MIL-96(Al) particles as filler in a continuous Matrimid polymer phase have been prepared. Five particle sizes of MIL-96(Al) between 3.2 μm and 55 nm were synthesized. In the preparation of the MIL-96(Al)/Matrimid MMM (10 wt % filler loading), the following preparation problems have been identified: The bigger micrometer-sized MIL-96(Al) crystals show a trend toward sedimentation during casting of the MMM, whereas for nanoparticles aggregation and recrystallization to micrometer-sized MIL-96(Al) crystals has been observed. Because of these preparation problems for MMM, the neat supported MIL-96(Al) layers show a relatively high H2/CO2 selectivity (≈9) and a hydrogen permeance approximately 2 magnitudes higher than that of the best MMM.

Multiple reversal olfactory learning in honeybees

Directory of Open Access Journals (Sweden)

Theo Mota

2010-07-01

Full Text Available In multiple reversal learning, animals trained to discriminate a reinforced from a non-reinforced stimulus are subjected to various, successive reversals of stimulus contingencies (e.g. A+ vs. B-, A- vs. B+, A+ vs. B-. This protocol is useful to determine whether or not animals learn to learn and solve successive discriminations faster (or with fewer errors with increasing reversal experience. Here we used the olfactory conditioning of proboscis extension reflex to study how honeybees Apis mellifera perform in a multiple reversal task. Our experiment contemplated four consecutive differential conditioning phases involving the same odors (A+ vs. B- to A- vs. B+ to A+ vs. B- to A- vs. B+. We show that bees in which the weight of reinforced or non-reinforced stimuli was similar mastered the multiple olfactory reversals. Bees which failed the task exhibited asymmetric responses to reinforced and non-reinforced stimuli, thus being unable to rapidly reverse stimulus contingencies. Efficient reversers did not improve their successive discriminations but rather tended to generalize their choice to both odors at the end of conditioning. As a consequence, both discrimination and reversal efficiency decreasedalong experimental phases. This result invalidates a learning-to-learn effect and indicates that bees do not only respond to the actual stimulus contingencies but rather combine these with an average of past experiences with the same stimuli.  

Effect of synthesis solvent on the breathing behavior of MIL-53(Al).

Science.gov (United States)

Mounfield, William P; Walton, Krista S

2015-06-01

This work reports the effect of using dimethylformamide (DMF) as the solvent for synthesizing MIL-53(Al). This well-known breathing MOF is typically prepared using hydrothermal methods. The two materials synthesized in DMF at 120°C and 220°C show significant deviations from the breathing behavior exhibited by the material synthesized hydrothermally. Powder X-ray diffraction confirmed that MIL-53(Al) synthesized in DMF at 120°C remains in the large-pore form under all conditions, while the other material synthesized at 220°C undergoes a more gradual breathing transition than is observed for MIL-53(Al) prepared by traditional methods. Solid-state NMR was employed to elucidate additional structural information and gain insight into the role synthesis solvent plays on breathing behavior. The CO2 and water adsorption of these large-pore stabilized materials were studied, and the differences in adsorption behavior compared to MIL-53(Al) prepared by traditional methods was discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

Nanometric MIL-125-NH₂ Metal-Organic Framework as a Potential Nerve Agent Antidote Carrier.

Science.gov (United States)

Vilela, Sérgio M F; Salcedo-Abraira, Pablo; Colinet, Isabelle; Salles, Fabrice; de Koning, Martijn C; Joosen, Marloes J A; Serre, Christian; Horcajada, Patricia

2017-10-12

The three-dimensional (3D) microporous titanium aminoterephthalate MIL-125-NH₂ (MIL: Material of Institut Lavoisier) was successfully isolated as monodispersed nanoparticles, which are compatible with intravenous administration, by using a simple, safe and low-cost synthetic approach (100 °C/32 h under atmospheric pressure) so that for the first time it could be considered for encapsulation and the release of drugs. The nerve agent antidote 2-[(hydroxyimino)methyl]-1-methyl-pyridinium chloride (2-PAM or pralidoxime) was effectively encapsulated into the pores of MIL-125-NH₂ as a result of the interactions between 2-PAM and the pore walls being mediated by π-stacking and hydrogen bonds, as deduced from infrared spectroscopy and Monte Carlo simulation studies. Finally, colloidal solutions of MIL-125-NH₂ nanoparticles exhibited remarkable stability in different organic media, aqueous solutions at different pH and under relevant physiological conditions over time (24 h). 2-PAM was rapidly released from the pores of MIL-125-NH₂ in vitro.

Understanding and solving disorder in the substitution pattern of amino functionalized MIL-47(V).

Science.gov (United States)

Heinen, Jurn; Dubbeldam, David

2016-03-14

Electronic energies and elastic constants of four amino functionalized MIL-47(V) supercells were computed using plane wave density functional theory to determine the influence of the substituent positions on the organic linker. An inverse relationship between the ab initio energies and the elastic constants was found, indicating that the high electronic stability correlates with high mechanical stability. Torsion in all supercells was induced upon substitution, which caused strain in the NH2-MIL-47(V) supercell. The combined effect of the substituent bulkiness and the induced torsion reduced the pore volume of the NH2-MIL-47(V) structures by >7% and the surface area by >14% with respect to MIL-47(V). This reduction was confirmed by lower saturation capacities of methane, CO2 and benzene. When unfavourable substituent positions are chosen, large torsions caused a further reduction of the saturation capacity. Differences in surface area, pore volume and saturation capacity illustrate the importance of choosing the correct NH2-MIL-47(V) supercell.

Novel composite material polyoxovanadate@MIL-101(Cr): a highly efficient electrocatalyst for ascorbic acid oxidation.

Science.gov (United States)

Fernandes, Diana M; Barbosa, André D S; Pires, João; Balula, Salete S; Cunha-Silva, Luís; Freire, Cristina

2013-12-26

A novel hybrid composite material, PMo10V2@MIL-101 was prepared by the encapsulation of the tetra-butylammonium (TBA) salt of the vanadium-substituted phosphomolybdate [PMo10V2O40](5-) (PMo10V2) into the porous metal-organic framework (MOF) MIL-101(Cr). The materials characterization by powder X-ray diffraction, Fourier transform infrared spectra and scanning electron microscopy confirmed the preparation of the composite material without disruption of the MOF porous structure. Pyrolytic graphite electrodes modified with the original components (MIL-101(Cr), PMo10V2), and the composite material PMo10V2@MIL-101 were prepared and their electrochemical responses were studied by cyclic voltammetry. Surface confined redox processes were observed for all the immobilized materials. MIL-101(Cr) showed one-electron reduction process due to chromium centers (Cr(III) → Cr(II)), while PMo10V2 presented five reduction processes: the peak at more positive potentials is attributed to two superimposed 1-electron vanadium reduction processes (V(V) → V(IV)) and the other four peaks to Mo-centred two-electron reduction processes (Mo(VI) → Mo(V)). The electrochemical behavior of the composite material PMo10V2@MIL-101 showed both MIL-101(Cr) and PMo10V2 redox features, although with the splitting of the two vanadium processes and the shift of the Mo- and Cr- centered processes to more negative potentials. Finally, PMo10V2@MIL-101 modified electrode showed outstanding enhanced vanadium-based electrocatalytic properties towards ascorbic acid oxidation, in comparison with the free PMo10V2, as a result of its immobilization into the porous structure of the MOF. Furthermore, PMo10V2@MIL-101 modified electrode showed successful simultaneous detection of ascorbic acid and dopamine.

Host-guest interaction of styrene and ethylbenzene in MIL-53 studied by solid-state NMR.

Science.gov (United States)

Li, Shenhui; Li, Jing; Tang, Jing; Deng, Feng

Solid-state NMR was utilized to explore the host-guest interaction between adsorbate and adsorbent at atomic level to understand the separation mechanism of styrene (St) and ethylbenzene (EB) in MIL-53(Al). 13 C- 27 Al double-resonance NMR experiments revealed that the host-guest interaction between St and MIL-53 was much stronger than that of EB adsorption. In addition, 13 C DIPSHIFT experiments suggested that the adsorbed St was less mobile than EB confined inside the MIL-53 pore. Furthermore, the host-guest interaction model between St, EB and MIL-53 was established on the basis of the spatial proximities information extracted from 2D 1 H- 1 H homo-nuclear correlation NMR experiments. According to the experimental observation from solid-state NMR, it was found that the presence of π-π interaction between St and MIL-53 resulted in the stronger host-guest interaction and less mobility of St. This work provides direct experimental evidence for understanding the separation mechanism of St and EB using MIL-53 as an adsorbent. Copyright © 2017 Elsevier Inc. All rights reserved.

Augmentation du rendement des producteurs de petits mils par leur ...

International Development Research Centre (IDRC) Digital Library (Canada)

29 avr. 2016 ... Image. Cultivateurs du petit mils en Inde. Une plus grande diversité de variétés de petit mil contribue à réduire la vulnérabilité à l'égard des mauvaises conditions météorologiques. En dépit du fait qu'ils ont une teneur élevée en micronutriments et en fibres alimentaires, présentent un indice glycémique ...

Cross-platform learning: on the nature of children's learning from multiple media platforms.

Science.gov (United States)

Fisch, Shalom M

2013-01-01

It is increasingly common for an educational media project to span several media platforms (e.g., TV, Web, hands-on materials), assuming that the benefits of learning from multiple media extend beyond those gained from one medium alone. Yet research typically has investigated learning from a single medium in isolation. This paper reviews several recent studies to explore cross-platform learning (i.e., learning from combined use of multiple media platforms) and how such learning compares to learning from one medium. The paper discusses unique benefits of cross-platform learning, a theoretical mechanism to explain how these benefits might arise, and questions for future research in this emerging field. Copyright © 2013 Wiley Periodicals, Inc., A Wiley Company.

Novel thymine-functionalized MIL-101 prepared by post-synthesis and enhanced removal of Hg{sup 2+} from water

Energy Technology Data Exchange (ETDEWEB)

Luo, Xubiao, E-mail: luoxubiao@126.com [Key Laboratory of Jiangxi Province for Persistent Pollutants Control and Resources Recycle, Nanchang 330063 (China); College of Environmental and Chemical Engineering, Nanchang Hangkong University, Nanchang 330063 (China); Shen, Tingting; Ding, Lin; Zhong, Weiping; Luo, Jianfeng [Key Laboratory of Jiangxi Province for Persistent Pollutants Control and Resources Recycle, Nanchang 330063 (China); College of Environmental and Chemical Engineering, Nanchang Hangkong University, Nanchang 330063 (China); Luo, Shenglian, E-mail: sllou@hnu.edu.cn [Key Laboratory of Jiangxi Province for Persistent Pollutants Control and Resources Recycle, Nanchang 330063 (China); College of Environmental and Chemical Engineering, Nanchang Hangkong University, Nanchang 330063 (China)

2016-04-05

Highlights: • A novel thymine-functionalized MIL-101 (MIL-101-Thymine) was first synthesized by post-synthesis method. • The resulting MIL-101-Thymine exhibited high Hg{sup 2+} adsorption. • MIL-101-Thymine exhibited excellent selectivity towards Hg{sup 2+} over other metal ions. • MIL-101-Thymine was used to remove trace Hg{sup 2+} with satisfactory recoveries in real water samples. - Abstract: A novel thymine-functionalized MIL-101 (MIL-101-Thymine) material was synthesized using a post-synthesis method to remove mercury at a high efficiency. MIL-101-Thymine was successfully prepared in this work and was confirmed by several characterization methods, such as {sup 13}C nuclear magnetic resonance, X-ray diffraction, and infrared spectroscopy. The Hg{sup 2+} adsorption agreed well with the Langmuir model, and the maximum adsorption capacity was 51.27 mg/g. The adsorption rate fit with the pseudo-second-order kinetic model. Furthermore, MIL-101-Thymine exhibited excellent selectivity towards Hg{sup 2+} over other cations, and the maximum value of the selective coefficient reached 947.34; this result is very likely due to the highly selective interactions of T-Hg{sup 2+}–T in MIL-101-Thymine. The result of X-ray photoelectron spectroscopy also showed that Hg{sup 2+} was coordinated with the N of thymine in MIL-101-Thymine. Moreover, the results of the thermogravimetric analysis and adsorption experiments showed that the Hg atom was two-coordinated with the thymine group. MIL-101-Thymine was used to remove trace Hg{sup 2+} in real water samples, and satisfactory recoveries were obtained.

Another Look at the Draft Mil-Std-1540E Unit Random Vibration Test Requirements

Science.gov (United States)

Perl, E.; Peterson, A. J..; Davis, D.

2012-07-01

The draft Mil-Std-1540E has been updated to reflect lessons learned since its publication as an SMC Standard in 2008, [1], and an earlier Aerospace Corporation Technical Report released in 2006, [2]. This paper discusses the technical rationale supporting some of the unit random vibration test requirements to provide better insight into their derivation and application to programs. It is intended that these requirements be tailored for each program to reflect the customer risk profile. Several tailoring options are provided and a two phase test strategy is discussed to highlight its applicability to utilizing heritage hardware in new applications.

Efficient Pd@MIL-101(Cr) hetero-catalysts for 2-butyne-1,4-diol hydrogenation exhibiting high selectivity

KAUST Repository

Yin, Dongdong

2017-01-05

Pd@MIL-101(Cr) hetero-catalysts have been successfully prepared using the metal-organic chemical vapour deposition (MOCVD) approach, by choosing [Pd(η-CH)(η-CH)] as a volatile precursor, and the hydrothermally stable metal-organic framework, MIL-101(Cr) as a support. The prepared Pd@MIL-101(Cr) hetero-catalysts characterized with various analytical techniques, exhibited highly monodispersed immobilized Pd nanoparticles in the MIL-101(Cr) cavities, while retaining the pristine crystallinity and porosity. The intact hybrid Pd@MIL-101(Cr) has been demonstrated to be an efficient catalyst for 2-butyne-1,4-diol hydrogenation with excellent activity, stability and selectivity (2-butene-1,4-diol (>94%)).

Action Recognition Using Discriminative Structured Trajectory Groups

KAUST Repository

Atmosukarto, Indriyati

2015-01-06

In this paper, we develop a novel framework for action recognition in videos. The framework is based on automatically learning the discriminative trajectory groups that are relevant to an action. Different from previous approaches, our method does not require complex computation for graph matching or complex latent models to localize the parts. We model a video as a structured bag of trajectory groups with latent class variables. We model action recognition problem in a weakly supervised setting and learn discriminative trajectory groups by employing multiple instance learning (MIL) based Support Vector Machine (SVM) using pre-computed kernels. The kernels depend on the spatio-temporal relationship between the extracted trajectory groups and their associated features. We demonstrate both quantitatively and qualitatively that the classification performance of our proposed method is superior to baselines and several state-of-the-art approaches on three challenging standard benchmark datasets.

Protonated MIL-125-NH2: Remarkable Adsorbent for the Removal of Quinoline and Indole from Liquid Fuel.

Science.gov (United States)

Ahmed, Imteaz; Khan, Nazmul Abedin; Yoon, Ji Woong; Chang, Jong-San; Jhung, Sung Hwa

2017-06-21

The removal of nitrogen-containing compounds (NCCs) from fossil fuels prior to combustion is currently of particular importance, and so we investigated an adsorptive method using metal-organic frameworks (MOFs) for the removal of indole (IND) and quinoline (QUI), which are two of the main NCCs present in fossil fuels. We herein employed an amino (-NH 2 )-functionalized MIL-125 (MIL-125-NH 2 ) MOF, which was further modified by protonation (P-MIL-125-NH 2 ). These modified MOFs exhibited extraordinary performance in the adsorption of both IND (as representative neutral NCC) and QUI (as representative basic NCC). These MOFs were one of the most efficient adsorbents for the removal of NCCs. For example, P-MIL-125-NH 2 showed the highest adsorption capacity for QUI among ever reported adsorbent. The improved adsorption of IND was explained by H-bonding and cation-π interactions for MIL-125-NH 2 and P-MIL-125-NH 2 , respectively, while the mechanisms for QUI were H-bonding and acid-base interactions, respectively. This is a rare phenomenon for a single material (especially not with very high porosity) to exhibit such remarkable performances in the adsorption of both basic QUI and neutral IND. The adsorption results obtained using regenerated MIL-125-NH 2 and P-MIL-125-NH 2 also showed that these materials can be used several times without any severe degradation.

Multiple Intelligence and Digital Learning Awareness of Prospective B.Ed Teachers

Science.gov (United States)

Gracious, F. L. Antony; Shyla, F. L. Jasmine Anne

2012-01-01

The present study Multiple Intelligence and Digital Learning Awareness of prospective B.Ed teachers was probed to find the relationship between Multiple Intelligence and Digital Learning Awareness of Prospective B.Ed Teachers. Data for the study were collected using self made Multiple Intelligence Inventory and Digital Learning Awareness Scale.…

Nanometric MIL-125-NH2 Metal–Organic Framework as a Potential Nerve Agent Antidote Carrier

Directory of Open Access Journals (Sweden)

Sérgio M. F. Vilela

2017-10-01

Full Text Available The three-dimensional (3D microporous titanium aminoterephthalate MIL-125-NH2 (MIL: Material of Institut Lavoisier was successfully isolated as monodispersed nanoparticles, which are compatible with intravenous administration, by using a simple, safe and low-cost synthetic approach (100 °C/32 h under atmospheric pressure so that for the first time it could be considered for encapsulation and the release of drugs. The nerve agent antidote 2-[(hydroxyiminomethyl]-1-methyl-pyridinium chloride (2-PAM or pralidoxime was effectively encapsulated into the pores of MIL-125-NH2 as a result of the interactions between 2-PAM and the pore walls being mediated by π-stacking and hydrogen bonds, as deduced from infrared spectroscopy and Monte Carlo simulation studies. Finally, colloidal solutions of MIL-125-NH2 nanoparticles exhibited remarkable stability in different organic media, aqueous solutions at different pH and under relevant physiological conditions over time (24 h. 2-PAM was rapidly released from the pores of MIL-125-NH2 in vitro.

Interpreting Black-Box Classifiers Using Instance-Level Visual Explanations

Energy Technology Data Exchange (ETDEWEB)

Tamagnini, Paolo; Krause, Josua W.; Dasgupta, Aritra; Bertini, Enrico

2017-05-14

To realize the full potential of machine learning in diverse real- world domains, it is necessary for model predictions to be readily interpretable and actionable for the human in the loop. Analysts, who are the users but not the developers of machine learning models, often do not trust a model because of the lack of transparency in associating predictions with the underlying data space. To address this problem, we propose Rivelo, a visual analytic interface that enables analysts to understand the causes behind predictions of binary classifiers by interactively exploring a set of instance-level explanations. These explanations are model-agnostic, treating a model as a black box, and they help analysts in interactively probing the high-dimensional binary data space for detecting features relevant to predictions. We demonstrate the utility of the interface with a case study analyzing a random forest model on the sentiment of Yelp reviews about doctors.

Automatic Knowledge Base Evolution by Learning Instances

OpenAIRE

Kim, Sundong

2016-01-01

Knowledge base is the way to store structured and unstructured data throughout the web. Since the size of the web is increasing rapidly, there are huge needs to structure the knowledge in a fully automated way. However fully-automated knowledge-base evolution on the Semantic Web is a major challenges, although there are many ontology evolution techniques available. Therefore learning ontology automatically can contribute to the semantic web society significantly. In this paper, we propose ful...

Novel thymine-functionalized MIL-101 prepared by post-synthesis and enhanced removal of Hg(2+) from water.

Science.gov (United States)

Luo, Xubiao; Shen, Tingting; Ding, Lin; Zhong, Weiping; Luo, Jianfeng; Luo, Shenglian

2016-04-05

A novel thymine-functionalized MIL-101 (MIL-101-Thymine) material was synthesized using a post-synthesis method to remove mercury at a high efficiency. MIL-101-Thymine was successfully prepared in this work and was confirmed by several characterization methods, such as (13)C nuclear magnetic resonance, X-ray diffraction, and infrared spectroscopy. The Hg(2+) adsorption agreed well with the Langmuir model, and the maximum adsorption capacity was 51.27mg/g. The adsorption rate fit with the pseudo-second-order kinetic model. Furthermore, MIL-101-Thymine exhibited excellent selectivity towards Hg(2+) over other cations, and the maximum value of the selective coefficient reached 947.34; this result is very likely due to the highly selective interactions of T-Hg(2+)-T in MIL-101-Thymine. The result of X-ray photoelectron spectroscopy also showed that Hg(2+) was coordinated with the N of thymine in MIL-101-Thymine. Moreover, the results of the thermogravimetric analysis and adsorption experiments showed that the Hg atom was two-coordinated with the thymine group. MIL-101-Thymine was used to remove trace Hg(2+) in real water samples, and satisfactory recoveries were obtained. Copyright © 2015 Elsevier B.V. All rights reserved.

Hydrogen selective NH{sub 2}-MIL-53(Al) MOF membranes with high permeability

Energy Technology Data Exchange (ETDEWEB)

Zhang, Feng; Zou, Xiaoqin; Gao, Xue; Fan, Songjie; Sun, Fuxing; Ren, Hao; Zhu, Guangshan [State Key Laboratory of Inorganic, Synthesis and Preparative Chemistry, Jilin University, Changchun (China)

2012-09-11

Hydrogen-based energy is a promising renewable and clean resource. Thus, hydrogen selective microporous membranes with high performance and high stability are demanded. Novel NH{sub 2}-MIL-53(Al) membranes are evaluated for hydrogen separation for this goal. Continuous NH{sub 2}-MIL-53(Al) membranes have been prepared successfully on macroporous glass frit discs assisted with colloidal seeds. The gas sorption ability of NH{sub 2}-MIL-53(Al) materials is studied by gas adsorption measurement. The isosteric heats of adsorption in a sequence of CO{sub 2}> N{sub 2}> CH{sub 4}{approx} H{sub 2} indicates different interactions between NH{sub 2}-MIL-53(Al) framework and these gases. As-prepared membranes are measured by single and binary gas permeation at different temperatures. The results of singe gas permeation show a decreasing permeance in an order of H{sub 2}> CH{sub 4}> N{sub 2}> CO{sub 2}, suggesting that the diffusion and adsorption properties make significant contributions in the gas permeation through the membrane. In binary gas permeation, the NH{sub 2}-MIL-53(Al) membrane shows high selectivity for H{sub 2} with separation factors of 20.7, 23.9 and 30.9 at room temperature (288 K) for H{sub 2} over CH{sub 4}, N{sub 2} and CO{sub 2}, respectively. In comparison to single gas permeation, a slightly higher separation factor is obtained due to the competitive adsorption effect between the gases in the porous MOF membrane. Additionally, the NH{sub 2}-MIL-53(Al) membrane exhibits very high permeance for H{sub 2} in the mixtures separation (above 1.5 x 10{sup -6} mol m{sup -2} s{sup -1} Pa{sup -1}) due to its large cavity, resulting in a very high separation power. The details of the temperature effect on the permeances of H{sub 2} over other gases are investigated from 288 to 353 K. The supported NH{sub 2}-MIL-53(Al) membranes with high hydrogen separation power possess high stability, resistance to cracking, temperature cycling and show high reproducibility

Glycine post-synthetic modification of MIL-53(Fe) metal-organic framework with enhanced and stable peroxidase-like activity for sensitive glucose biosensing.

Science.gov (United States)

Dong, Wenfei; Yang, Liaoyuan; Huang, Yuming

2017-05-15

A facile and rapid post-synthetic strategy was proposed to prepare a glycine functionalized MIL-53(Fe), namely glycine-MIL-53(Fe), by a simple mixing of water dispersible MIL-53(Fe) and glycine. The FT-IR, SEM, XRD and zeta potential were used to characterize the glycine-MIL-53(Fe). The result showed that glycine post-synthetic modification of MIL-53(Fe) did not change in the morphology and crystal structure of MIL-53(Fe). Interestingly, compared with MIL-53(Fe), the glycine-MIL-53(Fe) exhibits an enhanced peroxidase-like activity, which could catalyze the oxidation of TMB by H 2 O 2 to produce an intensive color reaction. Kinetic analysis indicated that the K m of glycine-MIL-53(Fe) for TMB was one-tenth of that of MIL-53(Fe). The glycine-MIL-53(Fe) as peroxidase mimetic displays better stability under alkaline or acidic conditions than MIL-53(Fe). The good performance of glycine-MIL-53(Fe) over MIL-53(Fe) may be attributed to the increase of affinity between TMB and the glycine-MIL-53(Fe). With these characteristics, a simple and sensitive method was developed for the detection of H 2 O 2 and glucose. The linear detection range for H 2 O 2 is 0.10-10μM with a detection limit of 49nM, and glucose could be linearly detected in the range from 0.25 to 10μM with a detection limit of 0.13μM. The proposed method was successfully used for glucose detection in human serum samples. Copyright © 2017 Elsevier B.V. All rights reserved.

MilQuant: a free, generic software tool for isobaric tagging-based quantitation.

Science.gov (United States)

Zou, Xiao; Zhao, Minzhi; Shen, Hongyan; Zhao, Xuyang; Tong, Yuanpeng; Wang, Qingsong; Wei, Shicheng; Ji, Jianguo

2012-09-18

Isobaric tagging techniques such as iTRAQ and TMT are widely used in quantitative proteomics and especially useful for samples that demand in vitro labeling. Due to diversity in choices of MS acquisition approaches, identification algorithms, and relative abundance deduction strategies, researchers are faced with a plethora of possibilities when it comes to data analysis. However, the lack of generic and flexible software tool often makes it cumbersome for researchers to perform the analysis entirely as desired. In this paper, we present MilQuant, mzXML-based isobaric labeling quantitator, a pipeline of freely available programs that supports native acquisition files produced by all mass spectrometer types and collection approaches currently used in isobaric tagging based MS data collection. Moreover, aside from effective normalization and abundance ratio deduction algorithms, MilQuant exports various intermediate results along each step of the pipeline, making it easy for researchers to customize the analysis. The functionality of MilQuant was demonstrated by four distinct datasets from different laboratories. The compatibility and extendibility of MilQuant makes it a generic and flexible tool that can serve as a full solution to data analysis of isobaric tagging-based quantitation. Copyright © 2012 Elsevier B.V. All rights reserved.

The effect of multiple intelligence-based learning towards students’ concept mastery and interest in learning matter

Science.gov (United States)

Pratiwi, W. N.; Rochintaniawati, D.; Agustin, R. R.

2018-05-01

This research was focused on investigating the effect of multiple intelligence -based learning as a learning approach towards students’ concept mastery and interest in learning matter. The one-group pre-test - post-test design was used in this research towards a sample which was according to the suitable situation of the research sample, n = 13 students of the 7th grade in a private school in Bandar Seri Begawan. The students’ concept mastery was measured using achievement test and given at the pre-test and post-test, meanwhile the students’ interest level was measured using a Likert Scale for interest. Based on the analysis of the data, the result shows that the normalized gain was .61, which was considered as a medium improvement. in other words, students’ concept mastery in matter increased after being taught using multiple intelligence-based learning. The Likert scale of interest shows that most students have a high interest in learning matter after being taught by multiple intelligence-based learning. Therefore, it is concluded that multiple intelligence – based learning helped in improving students’ concept mastery and gain students’ interest in learning matter.

Por mil devaluados pesos

Directory of Open Access Journals (Sweden)

Annie Rodríguez Collázos

2013-03-01

Full Text Available El estudio de lo popular y lo urbano hasta ahora se ha centrado en el comportamiento y en algunas relaciones de los habitantes con su entorno. “Por mil devaluados pesos. Publicidad popular y urbana”, pretende explorar las formas de publicidad, dispersas en diferentes espacios populares y urbanos en Bogotá, identificando esquemas y formas características de sus propios códigos comunicativos; se centran en un objeto de estudio consistente en las estrategias publicitarias y los códigos comunicativos en los mensajes publicitarios populares en las subculturas de San Victorino, 7 de Agosto y Sanandresito de San José.

Catalytic Performance of Microwave Functionalized NH2-MIL-53 for Cyclic Carbonate Synthesis from CO2 and Epoxides.

Science.gov (United States)

Seok, Han-Geul; Kim, Dong-Woo; Yang, Jeung-Gyu; Kim, Moon-Il; Park, Dae-Won

2016-05-01

The efficacy of microwave irradiation in the quaternization of amino-functionalized MIL-53 metal-organic framework (MOF) as well as the catalytic activity of the resultant MOF in the cycloaddition of carbon dioxide with epoxides under solvent-free conditions has been studied. A series of NH2-MIL-53 were synthesized and quaternized by reacting alkyl halide of various alkyl chains and anions under microwave irradiation. The post-functionalized F-MIL-53-AXs were characterized through solid-state XRD, FT-IR, XPS, and TGA. F-MIL-53-Mel prepared by microwave method showed higher AGC yield than that by the conventional heating method. F-MIL-53-AXs with iodide anion exhibited the best catalytic activity irrespective of the alkyl chain length, in agreement with the generally accepting order of nucleophilicity, ClMIL-53-AX catalysts were found to exhibit high thermal stability and were reusable over than three times, without any significant lowering of activity.

Effect of Diamine in Amine-Functionalized MIL-101 for Knoevenagel Condensation

International Nuclear Information System (INIS)

Kasinathan, Palraj; Seo, You Kyong; Shim, Kyu Eun; Hwang, Young Kyu; Lee, U Hwang; Hwang, Dong Won; Hong, Do Young; Halligudi, Shiva B.; Chang, Jong San

2011-01-01

Have demonstrated that amines with different basicities successfully functionalized into the pores of MIL-101 and amine functionalized chromium terephthalate used as a base catalyst. The catalytic activity of amine functionalized MIL-101 in Knoevenagel condensation of ethylcyanoacetate and benzaldehyde depends on their basi-cities. The reactivity of these catalytic materials could be also affected by their pore size and/or surface area, which governs the facile diffusion of the molecules through the channels of the MIL-101. The present strategy ensures the development of new functionalities and lead to MOF applications of practically useful heterogeneous base catalysts for chemical transformations. Crystalline Metal-Organic Frameworks (MOFs) are currently an important kind of advanced functional materials due to their novel coordination structures, diverse topologies, and potential applications. As one of topical MOFs, porous chromium terephthalate with giant pores labeled MIL-101(Cr) possesses several unique features such as hierarchical pore structure including a mesoporous zeotype architecture, mesoporous cages and microporous windows, outstanding sorption properties, numerous unsaturated metal cation sites, and high hydrothermal and chemical stability. These properties have led to a number of application potential in catalysis, gas storage, drug delivery and adsorptive separation. One important challenge has to realize is funtionalization via incorporation of binding site or reactive centers for catalysis. The functionalization methods of metal organic frameworks (MOFs) in a wide range of applications are two possible approaches including pre- and post-modification with functional groups

Cyber situation awareness: modeling detection of cyber attacks with instance-based learning theory.

Science.gov (United States)

Dutt, Varun; Ahn, Young-Suk; Gonzalez, Cleotilde

2013-06-01

To determine the effects of an adversary's behavior on the defender's accurate and timely detection of network threats. Cyber attacks cause major work disruption. It is important to understand how a defender's behavior (experience and tolerance to threats), as well as adversarial behavior (attack strategy), might impact the detection of threats. In this article, we use cognitive modeling to make predictions regarding these factors. Different model types representing a defender, based on Instance-Based Learning Theory (IBLT), faced different adversarial behaviors. A defender's model was defined by experience of threats: threat-prone (90% threats and 10% nonthreats) and nonthreat-prone (10% threats and 90% nonthreats); and different tolerance levels to threats: risk-averse (model declares a cyber attack after perceiving one threat out of eight total) and risk-seeking (model declares a cyber attack after perceiving seven threats out of eight total). Adversarial behavior is simulated by considering different attack strategies: patient (threats occur late) and impatient (threats occur early). For an impatient strategy, risk-averse models with threat-prone experiences show improved detection compared with risk-seeking models with nonthreat-prone experiences; however, the same is not true for a patient strategy. Based upon model predictions, a defender's prior threat experiences and his or her tolerance to threats are likely to predict detection accuracy; but considering the nature of adversarial behavior is also important. Decision-support tools that consider the role of a defender's experience and tolerance to threats along with the nature of adversarial behavior are likely to improve a defender's overall threat detection.

Modulated synthesis of chromium-based metal-organic framework (MIL-101) with enhanced hydrogen uptake

CSIR Research Space (South Africa)

Ren, Jianwei

2014-08-01

Full Text Available Modulated synthesis of MIL-101(Cr) in high yield and with good reproducibility using formic acid as a modulator is reported. Higher molar ratio of formic acid/CrCl(sub3) was found to form better shape-defined MIL-101(Cr) crystals with higher surface...

Stable ABTS Immobilized in the MIL-100(Fe) Metal-Organic Framework as an Efficient Mediator for Laccase-Catalyzed Decolorization.

Science.gov (United States)

Liu, Youxun; Geng, Yuanyuan; Yan, Mingyang; Huang, Juan

2017-06-02

The successful encapsulation of 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS), a well-known laccase mediator, within a mesoporous metal-organic framework sample (i.e., MIL-100(Fe)) was achieved using a one-pot hydrothermal synthetic method. The as-prepared ABTS@MIL-100(Fe) was characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectroscopy, nitrogen sorption, and cyclic voltammetry (CV). Our ABTS@MIL-100(Fe)-based electrode exhibited an excellent electrochemical response, indicating that MIL-100(Fe) provides an appropriate microenvironment for the immobilization and electroactivity of ABTS molecules. ABTS@MIL-100(Fe) was then evaluated as an immobilized laccase mediator for dye removal using indigo carmine (IC) as a model dye. Through the application of laccase in combination with a free (ABTS) or immobilized (ABTS@MIL-100(Fe)) mediator, decolorization yields of 95% and 94%, respectively, were obtained for IC after 50 min. In addition, following seven reuse cycles of ABTS@MIL-100(Fe) for dye treatment, a decolorization yield of 74% was obtained. Dye decolorization occurred through the breakdown of the chromophoric group by the Laccase/ABTS@MIL-100(Fe) system, and a catalytic mechanism was proposed. We therefore expect that the stability, reusability, and validity of ABTS@MIL-100(Fe) as a laccase mediator potentially render it a promising tool for dye removal, in addition to reducing the high running costs and potential toxicity associated with synthetic mediators.

The Oxygen Isotopic Composition of MIL 090001: A CR2 Chondrite with Abundant Refractory Inclusions

Science.gov (United States)

Keller, Lindsay P.; McKeegan, K. D.; Sharp, Z. D.

2012-01-01

MIL 090001 is a large (>6 kg) carbonaceous chondrite that was classified as a member of the CV reduced subgroup (CVred) that was recovered during the 2009-2010 ANSMET field season [1]. Based on the abundance of refractory inclusions and the extent of aqueous alteration, Keller [2] suggested a CV2 classification. Here we report additional mineralogical and petrographic data for MIL 090001, its whole-rock oxygen isotopic composition and ion microprobe analyses of individual phases. The whole rock oxygen isotopic analyses show that MIL 090001 should be classified as a CR chondrite.

A multiplicative reinforcement learning model capturing learning dynamics and interindividual variability in mice

OpenAIRE

Bathellier, Brice; Tee, Sui Poh; Hrovat, Christina; Rumpel, Simon

2013-01-01

Learning speed can strongly differ across individuals. This is seen in humans and animals. Here, we measured learning speed in mice performing a discrimination task and developed a theoretical model based on the reinforcement learning framework to account for differences between individual mice. We found that, when using a multiplicative learning rule, the starting connectivity values of the model strongly determine the shape of learning curves. This is in contrast to current learning models ...

Enhancing the water stability of Al-MIL-101-NH2 via postsynthetic modification.

Science.gov (United States)

Wittmann, Thomas; Siegel, Renée; Reimer, Nele; Milius, Wolfgang; Stock, Norbert; Senker, Jürgen

2015-01-02

The resistance of metal-organic frameworks towards water is a very critical issue concerning their practical use. Recently, it was shown for microporous MOFs that the water stability could be increased by introducing hydrophobic pendant groups. Here, we demonstrate a remarkable stabilisation of the mesoporous MOF Al-MIL-101-NH2 by postsynthetic modification with phenyl isocyanate. In this process 86 % of the amino groups were converted into phenylurea units. As a consequence, the long-term stability of Al-MIL-101-URPh in liquid water could be extended beyond a week. In water saturated atmospheres Al-MIL-101-URPh decomposed at least 12-times slower than the unfunctionalised analogue. To study the underlying processes both materials were characterised by Ar, N2 and H2 O sorption measurements, powder X-ray diffraction, thermogravimetric and chemical analysis as well as solid-state NMR and IR spectroscopy. Postsynthetic modification decreased the BET equivalent surface area from 3363 to 1555 m(2)  g(-1) for Al-MIL-101-URPh and reduced the mean diameters of the mesopores by 0.6 nm without degrading the structure significantly and reducing thermal stability. In spite of similar water uptake capacities, the relative humidity-dependent uptake of Al-MIL-101-URPh is slowed and occurs at higher relative humidity values. In combination with (1) H-(27) Al D-HMQC NMR spectroscopy experiments this favours a shielding mechanism of the Al clusters by the pendant phenyl groups and rules out pore blocking. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Chi-squared: A simpler evaluation function for multiple-instance learning

National Research Council Canada - National Science Library

McGovern, Amy; Jensen, David

2003-01-01

...) but finds the best concept using the chi-square statistic. This approach is simpler than diverse density and allows us to search more extensively by using properties of the contingency table to prune in a guaranteed manner...

NATO Pallet with Javelin Missiles, MIL-STD-1660 Tests

National Research Council Canada - National Science Library

2004-01-01

The U.S. Army Defense Ammunition Center (DAC), Validation Engineering Division (SJMAC-DEV) conducted tests in accordance with MIL-STD-1660, "Design Criteria for Ammunition Unit Loads" on the NATO pallet with Javelin missiles...

Atomic Layer Deposition of Pt Nanoparticles within the Cages of MIL-101: A Mild and Recyclable Hydrogenation Catalyst

Directory of Open Access Journals (Sweden)

Karen Leus

2016-03-01

Full Text Available We present the in situ synthesis of Pt nanoparticles within MIL-101-Cr (MIL = Materials Institute Lavoisier by means of atomic layer deposition (ALD. The obtained Pt@MIL-101 materials were characterized by means of N2 adsorption and X-ray powder diffraction (XRPD measurements, showing that the structure of the metal organic framework was well preserved during the ALD deposition. X-ray fluorescence (XRF and transmission electron microscopy (TEM analysis confirmed the deposition of highly dispersed Pt nanoparticles with sizes determined by the MIL-101-Cr pore sizes and with an increased Pt loading for an increasing number of ALD cycles. The Pt@MIL-101 material was examined as catalyst in the hydrogenation of different linear and cyclic olefins at room temperature, showing full conversion for each substrate. Moreover, even under solvent free conditions, full conversion of the substrate was observed. A high concentration test has been performed showing that the Pt@MIL-101 is stable for a long reaction time without loss of activity, crystallinity and with very low Pt leaching.

Nanometric MIL-125-NH2 metal–organic framework as a potential nerve agent antidote carrier

NARCIS (Netherlands)

Vilela, S.M.F.; Salcedo-Abraira, P; Colinet, I.; Salles, F.; Koning, M.C. de; Joosen, M.J.A.; Serre, C.; Horcajada, P.

2017-01-01

The three-dimensional (3D) microporous titanium aminoterephthalate MIL-125-NH_2 (MIL: Material of Institut Lavoisier) was successfully isolated as monodispersed nanoparticles, which are compatible with intravenous administration, by using a simple, safe and low-cost synthetic approach (100 °C/32 h

Electro-Synthetic Optimization of Host Material Based on MIL-100(Fe

Directory of Open Access Journals (Sweden)

Witri Wahyu Lestari

2016-05-01

Full Text Available Electro-synthesis of Metal-Organic Frameworks types of MIL-100(Fe (MIL = Material Institute of Lavoisier in ethanol: water (1: 1 with electrolyte TBATFB 0.1 M has been optimized by varying voltage (12, 13, 14 and 15 Volt and temperature (room temperature, 40, 60 and 80 °C. The product showed light brown powder which upon activation becomes dark brown. Optimum condition achieved during use voltage of 15 Volts and at a temperature of 40 °C with 33% yield. The obtained material was characterized by XRD and compared to CCDC 640536 simulated patterns to confirm the phase purity of the product. As comparison hydrothermal and reflux method have been carried out. Characterization by FTIR has also undertaken to ensure the coordination between the metal cation (Fe3+ and the BTC ligand (BTC = 1,3,5-Benzene Tri Carboxylate. Meanwhile pore analysis using SAA confirmed that MIL-100(Fe obtained by electrolysis method has a BET surface area reached till 569.191 m²/g with a total pore volume of 0.4540 cc/g and an average pore diameter reached 16 Å. Based on SEM analysis, morphology material show particle size between 0.4-8.6 μm and has a thermal stability up to 350 °C according thermo-gravimetric analysis. Due to the presence of Lewis acid sites on Fe-trimeric unit, porosity features on MIL-100(Fe and a fairly high thermal stability, this material is potentially used as the host material for the catalyst in the conversion reactions model for green diesel production.

Developing student engagement in networked teaching and learning practices through problem- and project-based learning approaches

DEFF Research Database (Denmark)

Andreasen, Lars Birch; Lerche Nielsen, Jørgen

2012-01-01

This paper focuses on how learner engagement can be facilitated through use of social media and communication technologies. The discussions are based on the Danish Master’s Programme of ICT and Learning (MIL), where students study in groups within a networked learning structure. The paper reflect...

Mil rosas roubadas, Work of Silviano Santiago a Bakhitinian Analysis

Directory of Open Access Journals (Sweden)

Renata Coelho Marchezan

2017-10-01

Full Text Available This article analyzes Mil rosas roubadas, written by Silviano Santiago in 2014, dealing with the notions of (autobiography, (autobiographical novel, metafiction and autofiction. Although the creation of this last word may indicate the existence of a new genre – it is even adopted by the writer himself to name his work –, the article shows the pertinence of placing Mil rosas roubadas in the route of the transformations and stylisations of the (autobiographical novel, such as examined by M. Bakhtin. The novel is, for Bakhtin, a genre without rigid forms, an unfinished genre, as it always follows the inflections of social life. In this way the ressemantization of the self, proposed by Silviano Santiago, is analyzed.

MIL-Ti metal-organic frameworks (MOFs) nanomaterials as superior adsorbents: Synthesis and ultrasound-aided dye adsorption from multicomponent wastewater systems.

Science.gov (United States)

Oveisi, Mina; Asli, Mokhtar Alina; Mahmoodi, Niyaz Mohammad

2018-04-05

Herein, 1,4-benzenedicarboxylate (BDC) and 2-amino-1,4-benzenedicarboxylate (NH 2 -BDC) as organic linkers and tetraisopropyl orthotitanate as a metal source were used to synthesize several metal-organic frameworks (MOFs) nanomaterials. Five Materials Institut Lavoisiers (MILs) as MOFs include MIL-125(Ti), NH 2 -MIL-125(Ti) and three MILs with different organic linkers molar ratios (BDC/NH 2 -BDC: 75/25, 50/50 and 25/75 denoted as MIL-X1, MIL-X2 and MIL-X3, respectively). The synthesized nanomaterials were used for ultrasound-aided adsorption of cationic dyes (Basic Red 46 (BR46), Basic Blue 41 (BB41) and Methylene Blue (MB)) from single and multicomponent (binary) systems. The BET, XRD, FTIR, SEM, TEM, TGA and zeta potential were used for characterizing the MILs. Dye removal followed pseudo-second order kinetics with constant rate of 0.20833, 0.00481 and 0.00051 mg/g min for BR46, BB41 and MB, respectively. In addition dye adsorption obeyed the Langmuir isotherm model and the experimental dye adsorption capacity for BR46, BB41 and MB was 1296, 1257 and 862 mg/g, respectively. The synthesized MIL showed high reusability and stability over three cycles. The adsorption thermodynamics data presented that dye removal was a spontaneous, endothermic and physical reaction. The free Gibbs energy for dye removal by the NH 2 -MIL-125(Ti) at 308K was -19.424, -15.721 and -17.413 kJ/mol for BR46, BB41 and MB, respectively. Copyright © 2017 Elsevier B.V. All rights reserved.

The Answering Process for Multiple-Choice Questions in Collaborative Learning: A Mathematical Learning Model Analysis

Science.gov (United States)

Nakamura, Yasuyuki; Nishi, Shinnosuke; Muramatsu, Yuta; Yasutake, Koichi; Yamakawa, Osamu; Tagawa, Takahiro

2014-01-01

In this paper, we introduce a mathematical model for collaborative learning and the answering process for multiple-choice questions. The collaborative learning model is inspired by the Ising spin model and the model for answering multiple-choice questions is based on their difficulty level. An intensive simulation study predicts the possibility of…

A Hybrid Instance Selection Using Nearest-Neighbor for Cross-Project Defect Prediction

Institute of Scientific and Technical Information of China (English)

Duksan Ryu; Jong-In Jang; Jongmoon Baik; Member; ACM; IEEE

2015-01-01

Software defect prediction (SDP) is an active research field in software engineering to identify defect-prone modules. Thanks to SDP, limited testing resources can be effectively allocated to defect-prone modules. Although SDP requires suffcient local data within a company, there are cases where local data are not available, e.g., pilot projects. Companies without local data can employ cross-project defect prediction (CPDP) using external data to build classifiers. The major challenge of CPDP is different distributions between training and test data. To tackle this, instances of source data similar to target data are selected to build classifiers. Software datasets have a class imbalance problem meaning the ratio of defective class to clean class is far low. It usually lowers the performance of classifiers. We propose a Hybrid Instance Selection Using Nearest-Neighbor (HISNN) method that performs a hybrid classification selectively learning local knowledge (via k-nearest neighbor) and global knowledge (via na¨ıve Bayes). Instances having strong local knowledge are identified via nearest-neighbors with the same class label. Previous studies showed low PD (probability of detection) or high PF (probability of false alarm) which is impractical to use. The experimental results show that HISNN produces high overall performance as well as high PD and low PF.

Automatic analysis of online image data for law enforcement agencies by concept detection and instance search

Science.gov (United States)

de Boer, Maaike H. T.; Bouma, Henri; Kruithof, Maarten C.; ter Haar, Frank B.; Fischer, Noëlle M.; Hagendoorn, Laurens K.; Joosten, Bart; Raaijmakers, Stephan

2017-10-01

The information available on-line and off-line, from open as well as from private sources, is growing at an exponential rate and places an increasing demand on the limited resources of Law Enforcement Agencies (LEAs). The absence of appropriate tools and techniques to collect, process, and analyze the volumes of complex and heterogeneous data has created a severe information overload. If a solution is not found, the impact on law enforcement will be dramatic, e.g. because important evidence is missed or the investigation time is too long. Furthermore, there is an uneven level of capabilities to deal with the large volumes of complex and heterogeneous data that come from multiple open and private sources at national level across the EU, which hinders cooperation and information sharing. Consequently, there is a pertinent need to develop tools, systems and processes which expedite online investigations. In this paper, we describe a suite of analysis tools to identify and localize generic concepts, instances of objects and logos in images, which constitutes a significant portion of everyday law enforcement data. We describe how incremental learning based on only a few examples and large-scale indexing are addressed in both concept detection and instance search. Our search technology allows querying of the database by visual examples and by keywords. Our tools are packaged in a Docker container to guarantee easy deployment on a system and our tools exploit possibilities provided by open source toolboxes, contributing to the technical autonomy of LEAs.

Handling multiple metadata streams regarding digital learning material

NARCIS (Netherlands)

Roes, J.B.M.; Vuuren, J. van; Verbeij, N.; Nijstad, H.

2010-01-01

This paper presents the outcome of a study performed in the Netherlands on handling multiple metadata streams regarding digital learning material. The paper describes the present metadata architecture in the Netherlands, the present suppliers and users of metadata and digital learning materials. It

Reward-related learning via multiple memory systems.

Science.gov (United States)

Delgado, Mauricio R; Dickerson, Kathryn C

2012-07-15

The application of a neuroeconomic approach to the study of reward-related processes has provided significant insights in our understanding of human learning and decision making. Much of this research has focused primarily on the contributions of the corticostriatal circuitry, involved in trial-and-error reward learning. As a result, less consideration has been allotted to the potential influence of different neural mechanisms such as the hippocampus or to more common ways in human society in which information is acquired and utilized to reach a decision, such as through explicit instruction rather than trial-and-error learning. This review examines the individual contributions of multiple learning and memory neural systems and their interactions during human decision making in both normal and neuropsychiatric populations. Specifically, the anatomical and functional connectivity across multiple memory systems are highlighted to suggest that probing the role of the hippocampus and its interactions with the corticostriatal circuitry via the application of model-based neuroeconomic approaches may provide novel insights into neuropsychiatric populations that suffer from damage to one of these structures and as a consequence have deficits in learning, memory, or decision making. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Petits mils, énorme potentiel : diversifiés, nutritifs et adaptés aux ...

International Development Research Centre (IDRC) Digital Library (Canada)

29 avr. 2016 ... La culture des petits mils en complément des cultures existantes ... Redynamiser la production de petits mils pourrait améliorer la nutrition et la santé en Inde, ... que nécessite leur transformation et de la perception négative que l'on en ... Increasing gender equality among small millet farmers in South Asia.

Automatic plankton image classification combining multiple view features via multiple kernel learning.

Science.gov (United States)

Zheng, Haiyong; Wang, Ruchen; Yu, Zhibin; Wang, Nan; Gu, Zhaorui; Zheng, Bing

2017-12-28

Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system

Evaluating the Implementation of the Re-Engineering Systems of Primary Care Treatment in the Military (RESPECT-Mil)

Science.gov (United States)

Wong, Eunice C.; Jaycox, Lisa H.; Ayer, Lynsay; Batka, Caroline; Harris, Racine; Naftel, Scott; Paddock, Susan M.

2015-01-01

Abstract A RAND team conducted an independent implementation evaluation of the Re-Engineering Systems of Primary Care Treatment in the Military (RESPECT-Mil) Program, a system of care designed to screen, assess, and treat posttraumatic stress disorder and depression among active duty service members in the Army's primary care settings. Evaluating the Implementation of the Re-Engineering Systems of Primary Care Treatment in the Military (RESPECT-Mil) presents the results from RAND's assessment of the implementation of RESPECT-Mil in military treatment facilities and makes recommendations to improve the delivery of mental health care in these settings. Analyses were based on existing program data used to monitor fidelity to RESPECT-Mil across the Army's primary care clinics, as well as discussions with key stakeholders. During the time of the evaluation, efforts were under way to implement the Patient Centered Medical Home, and uncertainties remained about the implications for the RESPECT-Mil program. Consideration of this transition was made in designing the evaluation and applying its findings more broadly to the implementation of collaborative care within military primary care settings. PMID:28083389

Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

Science.gov (United States)

He, Dan; Kuhn, David; Parida, Laxmi

2016-06-15

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

Per-Sample Multiple Kernel Approach for Visual Concept Learning

Directory of Open Access Journals (Sweden)

Ling-Yu Duan

2010-01-01

Full Text Available Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

Per-Sample Multiple Kernel Approach for Visual Concept Learning

Directory of Open Access Journals (Sweden)

Tian Yonghong

2010-01-01

Full Text Available Abstract Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

Demonstration of coupling correction below the per-mil limit in the LHC

CERN Document Server

Maclean, Ewen Hamish; Fartoukh, Stephane; Persson, Tobias Hakan Bjorn; Skowronski, Piotr Krzysztof; Tomas Garcia, Rogelio; Wierichs, David Alexander; CERN. Geneva. ATS Department

2016-01-01

Linear coupling between betatron motion in the transverse planes is one of the key optics parameters for any accelerator. It can substantially affect the nonlinear dynamics, influencing both lifetime and the damping of instabilities, as well as affecting the ability to measure and control the linear optics. A review of published material revealed no account of coupling having been corrected significantly below the per-mil level in any hadron accelerator. This note reports the achievement of a sub-per-mil coupling correction during an LHC Machine Development study.

Chromium-based metal-organic framework MIL-101 as a highly effective catalyst in plasma for toluene removal

Science.gov (United States)

Wu, Junliang; Xia, Qibin; Xiao, Jing; Li, Zhong

2017-11-01

Catalytic performance of MIL-101—a type of chromium-based metal-organic frameworks (MOFs)—in a plasma catalysis system for toluene removal was experimentally studied. The MIL-101 was synthesized using a hydrothermal method, and its catalytic performance was compared to two other catalysts, Cr2O3/γ-Al2O3 and γ-Al2O3, in a dielectric barrier discharge (DBD) reactor. Results showed that the presence of a catalyst in plasma changed the voltage and current characteristic substantially, and promoted the performance of the plasma reactor. Among the catalysts, the MIL-101 exhibited a significantly high toluene conversion, which was 20% and 35% higher than Cr2O3/γ-Al2O3 and γ-Al2O3, respectively, under the same testing conditions, as well as higher carbon balance and CO2 selectivity. The analysis of by-products on the surfaces of the catalysts before and after reaction demonstrated that MIL-101 had better resistance towards by-products accumulation compared to Cr2O3/γ-Al2O3 and γ-Al2O3. The loading of MnO x on MIL-101 further promoted its catalytic performance. MIL-101 exhibits attractive catalytic properties as a catalyst in a plasma catalysis system for the decomposition of volatile organic compounds.

Chromium-based metal-organic framework MIL-101 as a highly effective catalyst in plasma for toluene removal

International Nuclear Information System (INIS)

Wu, Junliang; Xia, Qibin; Xiao, Jing; Li, Zhong

2017-01-01

Catalytic performance of MIL-101—a type of chromium-based metal-organic frameworks (MOFs)—in a plasma catalysis system for toluene removal was experimentally studied. The MIL-101 was synthesized using a hydrothermal method, and its catalytic performance was compared to two other catalysts, Cr 2 O 3 / γ -Al 2 O 3 and γ -Al 2 O 3 , in a dielectric barrier discharge (DBD) reactor. Results showed that the presence of a catalyst in plasma changed the voltage and current characteristic substantially, and promoted the performance of the plasma reactor. Among the catalysts, the MIL-101 exhibited a significantly high toluene conversion, which was 20% and 35% higher than Cr 2 O 3 / γ -Al 2 O 3 and γ -Al 2 O 3 , respectively, under the same testing conditions, as well as higher carbon balance and CO 2 selectivity. The analysis of by-products on the surfaces of the catalysts before and after reaction demonstrated that MIL-101 had better resistance towards by-products accumulation compared to Cr 2 O 3 / γ -Al 2 O 3 and γ -Al 2 O 3 . The loading of MnO x on MIL-101 further promoted its catalytic performance. MIL-101 exhibits attractive catalytic properties as a catalyst in a plasma catalysis system for the decomposition of volatile organic compounds. (paper)

Learning of Rule Ensembles for Multiple Attribute Ranking Problems

Science.gov (United States)

Dembczyński, Krzysztof; Kotłowski, Wojciech; Słowiński, Roman; Szeląg, Marcin

In this paper, we consider the multiple attribute ranking problem from a Machine Learning perspective. We propose two approaches to statistical learning of an ensemble of decision rules from decision examples provided by the Decision Maker in terms of pairwise comparisons of some objects. The first approach consists in learning a preference function defining a binary preference relation for a pair of objects. The result of application of this function on all pairs of objects to be ranked is then exploited using the Net Flow Score procedure, giving a linear ranking of objects. The second approach consists in learning a utility function for single objects. The utility function also gives a linear ranking of objects. In both approaches, the learning is based on the boosting technique. The presented approaches to Preference Learning share good properties of the decision rule preference model and have good performance in the massive-data learning problems. As Preference Learning and Multiple Attribute Decision Aiding share many concepts and methodological issues, in the introduction, we review some aspects bridging these two fields. To illustrate the two approaches proposed in this paper, we solve with them a toy example concerning the ranking of a set of cars evaluated by multiple attributes. Then, we perform a large data experiment on real data sets. The first data set concerns credit rating. Since recent research in the field of Preference Learning is motivated by the increasing role of modeling preferences in recommender systems and information retrieval, we chose two other massive data sets from this area - one comes from movie recommender system MovieLens, and the other concerns ranking of text documents from 20 Newsgroups data set.

Implementation of Multiple Intelligences Supported Project-Based Learning in EFL/ESL Classrooms

Science.gov (United States)

Bas, Gokhan

2008-01-01

This article deals with the implementation of Multiple Intelligences supported Project-Based learning in EFL/ESL Classrooms. In this study, after Multiple Intelligences supported Project-based learning was presented shortly, the implementation of this learning method into English classrooms. Implementation process of MI supported Project-based…

Selective recognition of 6-mercaptopurine based on luminescent metal-organic frameworks Fe-MIL-88NH₂.

Science.gov (United States)

Sun, Zhengjuan; Liu, Yali; Li, Yuanfang

2015-03-15

A novel and rapid spectrofluorometry method for the recognition of 6-mercaptopurine (6-MP) has been developed based on luminescent metal-organic frameworks Fe-MIL-88NH2 as fluorescent probe. The strong fluorescence of Fe-MIL-88NH2 at 430 nm could be quenched by 6-MP directly, and the Fe-MIL-88NH2 shows high selectivity for 6-MP compared to other thiol-containing amino acids such as homocysteine (Hcy), cysteine (Cys), glutathione (GSH), etc. Under optimal conditions, the relative fluorescence intensity was linearly proportional to the concentration of 6-MP in the range of 5-600 μM with the detection limit at 1.17 μM (S/N=3). Furthermore, the present approach has been successfully applied to the determination of 6-MP in human serum samples. The possible fluorescence quenching mechanism has also been investigated, where it is revealed that the quenching was attributed to competition of absorption of the light source energy as well as electron transfer between Fe-MIL-88NH2 and 6-MP. Copyright © 2014 Elsevier B.V. All rights reserved.

Effective Adsorption and Removal of Phosphate from Aqueous Solutions and Eutrophic Water by Fe-based MOFs of MIL-101.

Science.gov (United States)

Xie, Qiying; Li, Yan; Lv, Zhaoling; Zhou, Hang; Yang, Xiangjun; Chen, Jing; Guo, Hong

2017-06-12

Although many efforts have been devoted to the adsorptive removal of phosphate from aqueous solutions and eutrophic water, it is still highly desirable to develop novel adsorbents with high adsorption capacities. In this study, Fe-based metal-organic frameworks (MOFs), MIL-101 and NH 2 -MIL-101, are fabricated through a general facile strategy. Their performance as an adsorbent for phosphate removal is investigated. Experiments are performed to study the effects of various factors on the phosphate adsorption, including adsorbent dosage, contact time and co-existing ions. Both MIL-101(Fe) and NH 2 -MIL-101(Fe) show highly effective removal of phosphates from aqueous solutions, and the concentration of phosphates decrease sharply from the initial 0.60 mg·L -1 to 0.045 and 0.032 mg·L -1 , respectively, within just 30 min of exposure. The adsorption kinetics and adsorption isotherms reveal that NH 2 -MIL-101(Fe) has higher adsorption capacity than MIL-101(Fe) possibly due to the amine group. Furthermore, the Fe-based MOFs also exhibit a high selectivity towards phosphate over other anions such as chloride, bromide, nitrate and sulfate. Particularly, the prepared Fe-based MIL-101 materials are also capable of adsorbing phosphate in an actual eutrophic water sample and display better removal effect.

Ru Nanoparticles Supported on MIL-101 by Double Solvents Method as High-Performance Catalysts for Catalytic Hydrolysis of Ammonia Borane

Directory of Open Access Journals (Sweden)

Tong Liu

2015-01-01

Full Text Available Highly dispersed crystalline Ru nanoparticles (NPs were successfully immobilized inside the pores of MIL-101 by a double solvents method (DSM. HRTEM clearly demonstrated the uniform distribution of the ultrafine Ru NPs throughout the interior cavities of MIL-101. The synthesized Ru@MIL-101 catalyst was also characterized by X-ray diffraction (XRD, N2 adsorption desorption, and ICP-AES. The catalytic test indicated that the Ru NPs supported MIL-101 material exhibited exceedingly high activity and excellent durability for hydrogen generation from the catalytic hydrolysis of amine boranes.

Fast generation of multiple resolution instances of raster data sets

NARCIS (Netherlands)

Arge, L.; Haverkort, H.J.; Tsirogiannis, C.P.

2012-01-01

In many GIS applications it is important to study the characteristics of a raster data set at multiple resolutions. Often this is done by generating several coarser resolution rasters from a fine resolution raster. In this paper we describe efficient algorithms for different variants of this

Structure and properties of Al-MIL-53-ADP, a breathing MOF based on the aliphatic linker molecule adipic acid.

Science.gov (United States)

Reinsch, Helge; Pillai, Renjith S; Siegel, Renée; Senker, Jürgen; Lieb, Alexandra; Maurin, Guillaume; Stock, Norbert

2016-03-14

The new aluminium based metal-organic framework [Al(OH)(O2C-C4H8-CO2)]·H2O denoted as Al-MIL-53-ADP-lp (lp stands for large pore) was synthesised under solvothermal conditions. This solid is an analogue of the archetypical aluminium terephthalate Al-MIL-53 based on the aliphatic single-chain linker molecule adipic acid (H2ADP, hexanedioic acid). In contrast to its aromatic counterparts, Al-MIL-53-ADP exhibits a structural breathing behaviour solely upon dehydration/rehydration. The crystal structure of the anhydrous compound denoted as Al-MIL-53-ADP-np (np stands for narrow pore) was determined by a combination of forcefield-based computations and Rietveld refinement of the powder X-ray diffraction data while the structure of the hydrated form Al-MIL-53-ADP-lp was derived computationally by a combination of force field based methods and Density Functional Theory calculations. Both structures were further supported by (1)H, (13)C and (27)Al high-resolution NMR MAS 1D data coupled again with simulations. Al-MIL-53-ADP was further characterised by means of vibrational spectroscopy, elemental analysis, thermogravimetry and water vapour sorption.

Barrio residencial de Gratosoglio, Milán

Directory of Open Access Journals (Sweden)

Giannini, Sandro

1967-04-01

Full Text Available The group of 23 buildings in the residential zone of Gratosoglio, which provide space for 1,000 dwellings, has been built by the firm «Fintech Italcamus». This Italian firms applies in Italy the «Raymond Camus» system, which is a positive aid to heavy prefabrication in housing projects. The above group of buildings constitute part of the General Building Scheme so successfully initiated by the Autonomous Building Institute of the Province of Milan, with the purpose of helping to overcome the extensive lack of housing in the Milan region.El grupo de edificios levantado en el Barrio Residencial de Gratosoglio, Milán (23, con un total de 1.000 viviendas, ha sido construido por la firma «Fintech Italcamus», Sociedad italiana que aplica en Italia el sistema «Raymond Camus» y constituye una aportación positiva de la prefabricación pesada a la edificación residencial. Este conjunto forma parte del Plan General de edificación, emprendido con tanto éxito como acierto por el Instituto Autónomo de la Vivienda de la Provincia de Milán, para solucionar los problemas que la gigantesca presión demográfica planteaba en dicha provincia.

Efficient Pd@MIL-101(Cr) hetero-catalysts for 2-butyne-1,4-diol hydrogenation exhibiting high selectivity

KAUST Repository

Yin, Dongdong; Li, Chuang; Ren, Hangxing; Shekhah, Osama; Liu, Jinxuan; Liang, Changhai

2017-01-01

Pd@MIL-101(Cr) hetero-catalysts have been successfully prepared using the metal-organic chemical vapour deposition (MOCVD) approach, by choosing [Pd(η-CH)(η-CH)] as a volatile precursor, and the hydrothermally stable metal-organic framework, MIL-101

Automatic provisioning, deployment and orchestration for load-balancing THREDDS instances

Science.gov (United States)

Cofino, A. S.; Fernández-Tejería, S.; Kershaw, P.; Cimadevilla, E.; Petri, R.; Pryor, M.; Stephens, A.; Herrera, S.

2017-12-01

THREDDS is a widely used web server to provide to different scientific communities with data access and discovery. Due to THREDDS's lack of horizontal scalability and automatic configuration management and deployment, this service usually deals with service downtimes and time consuming configuration tasks, mainly when an intensive use is done as is usual within the scientific community (e.g. climate). Instead of the typical installation and configuration of a single or multiple independent THREDDS servers, manually configured, this work presents an automatic provisioning, deployment and orchestration cluster of THREDDS servers. This solution it's based on Ansible playbooks, used to control automatically the deployment and configuration setup on a infrastructure and to manage the datasets available in THREDDS instances. The playbooks are based on modules (or roles) of different backends and frontends load-balancing setups and solutions. The frontend load-balancing system enables horizontal scalability by delegating requests to backend workers, consisting in a variable number of instances for the THREDDS server. This implementation allows to configure different infrastructure and deployment scenario setups, as more workers are easily added to the cluster by simply declaring them as Ansible variables and executing the playbooks, and also provides fault-tolerance and better reliability since if any of the workers fail another instance of the cluster can take over it. In order to test the solution proposed, two real scenarios are analyzed in this contribution: The JASMIN Group Workspaces at CEDA and the User Data Gateway (UDG) at the Data Climate Service from the University of Cantabria. On the one hand, the proposed configuration has provided CEDA with a higher level and more scalable Group Workspaces (GWS) service than the previous one based on Unix permissions, improving also the data discovery and data access experience. On the other hand, the UDG has improved its

MIL-L-87177 and CLT:X-10 Lubricants Improve Electrical Connector Fretting Corrosion Behavior

International Nuclear Information System (INIS)

AUKLAND, NEIL R.; HANLON, JAMES T.

1999-01-01

We have conducted a fretting research project using MIL-L-87177 and CLT: X-10 lubricants on Nano-miniature connectors. When they were fretted without lubricant, individual connectors first exceeded our 0.5 ohm failure criteria from 2,341 to 45,238 fretting cycles. With additional fretting, their contact resistance increased to more than 100,000 ohms. Unmodified MIL-L-87177 lubricant delayed the onset of first failure to between 430,000 and over 20,000,000 fretting cycles. MIL-L-87177 modified by addition of Teflon powder delayed first failure to beyond 5 million fretting cycles. Best results were obtained when Teflon was used and also when both the straight and modified lubricants were poured into and then out of the connector. CLT: X-10 lubricant delayed the onset of first failure to beyond 55 million cycles in one test where a failure was actually observed and to beyond 20 million cycles in another that was terminated without failure. CLT: X-10 recovered an unlubricated connector driven deeply into failure, with six failed pins recovering immediately and four more recovering during an additional 420 thousand fretting cycles. MIL-L-87177 was not able to recover a connector under similar conditions

A predictive validity study of the Learning Style Questionnaire (LSQ) using multiple, specific learning criteria

NARCIS (Netherlands)

Kappe, F.R.; Boekholt, L.; den Rooyen, C.; van der Flier, H.

2009-01-01

Multiple and specific learning criteria were used to examine the predictive validity of the Learning Style Questionnaire (LSQ). Ninety-nine students in a college of higher learning in The Netherlands participated in a naturally occurring field study. The students were categorized into one of four

Technology-enhanced instruction in learning world languages: The Middlebury interactive learning program

Directory of Open Access Journals (Sweden)

Cynthia Lake

2015-03-01

Full Text Available Middlebury Interactive Language (MIL programs are designed to teach world language courses using blended and online learning for students in kindergarten through grade 12. Middlebury Interactive courses start with fundamental building blocks in four key areas of world-language study: listening comprehension, speaking, reading, and writing. As students progress through the course levels, they deepen their understanding of the target language, continuing to focus on the three modes of communication: interpretive, interpersonal, and presentational. The extensive use of authentic materials (video, audio, images, or texts is intended to provide a contextualized and interactive presentation of the vocabulary and the linguistic structures. In the present paper, we describe the MIL program and the results of a mixed-methods survey and case-study evaluation of its implementation in a broad sample of schools. Technology application is examined with regard to MIL instructional strategies and the present evaluation approach relative to those employed in the literature.

Multiple goals, motivation and academic learning.

Science.gov (United States)

Valle, Antonio; Cabanach, Ramón G; Núnez, José C; González-Pienda, Julio; Rodríguez, Susana; Piñeiro, Isabel

2003-03-01

The type of academic goals pursued by students is one of the most important variables in motivational research in educational contexts. Although motivational theory and research have emphasised the somewhat exclusive nature of two types of goal orientation (learning goals versus performance goals), some studies (Meece, 1994; Seifert, 1995, 1996) have shown that the two kinds of goals are relatively complementary and that it is possible for students to have multiple goals simultaneously, which guarantees some flexibility to adapt more efficaciously to various contexts and learning situations. The principal aim of this study is to determine the academic goals pursued by university students and to analyse the differences in several very significant variables related to motivation and academic learning. Participants were 609 university students (74% women and 26% men) who filled in several questionnaires about the variables under study. We used cluster analysis ('quick cluster analysis' method) to establish the different groups or clusters of individuals as a function of the three types of goals (learning goals, performance goals, and social reinforcement goals). By means of MANOVA, we determined whether the groups or clusters identified were significantly different in the variables that are relevant to motivation and academic learning. Lastly, we performed ANOVA on the variables that revealed significant effects in the previous analysis. Using cluster analysis, three groups of students with different motivational orientations were identified: a group with predominance of performance goals (Group PG: n = 230), a group with predominance of multiple goals (Group MG: n = 238), and a group with predominance of learning goals (Group LG: n = 141). Groups MG and LG attributed their success more to ability, they had higher perceived ability, they took task characteristics into account when planning which strategies to use in the learning process, they showed higher persistence

CuNi NPs supported on MIL-101 as highly active catalysts for the hydrolysis of ammonia borane

Science.gov (United States)

Gao, Doudou; Zhang, Yuhong; Zhou, Liqun; Yang, Kunzhou

2018-01-01

The catalysts containing Cu, Ni bi-metallic nanoparticles were successfully synthesized by in-situ reduction of Cu2+ and Ni2+ salts into the highly porous and hydrothermally stable metal-organic framework MIL-101 via a simple liquid impregnation method. When the total amount of loading metal is 3 × 10-4 mol, Cu2Ni1@MIL-101 catalyst shows higher catalytic activity comparing to CuxNiy@MIL-101 with different molar ratio of Cu and Ni (x, y = 0, 0.5, 1.5, 2, 2.5, 3). Cu2Ni1@MIL-101 catalyst has the highest catalytic activity comparing to mono-metallic Cu and Ni counterparts and pure bi-metallic CuNi nanoparticles in hydrolytic dehydrogeneration of ammonia borane (AB) at room temperature. Additionally, in the hydrolysis reaction, the Cu2Ni1@MIL- 101 catalyst possesses excellent catalytic performances, which exhibit highly catalytic activity with turn over frequency (TOF) value of 20.9 mol H2 min-1 Cu mol-1 and a very low activation energy value of 32.2 kJ mol-1. The excellent catalytic activity has been successfully achieved thanks to the strong bi-metallic synergistic effects, uniform distribution of nanoparticles and the bi-functional effects between CuNi nanoparticles and the host of MIL-101. Moreover, the catalyst also displays satisfied durable stability after five cycles for the hydrolytically releasing H2 from AB. The non-noble metal catalysts have broad prospects for commercial applications in the field of hydrogen-stored materials due to the low prices and excellent catalytic activity.

Dimensions of problem based learning

DEFF Research Database (Denmark)

Nielsen, Jørgen Lerche; Andreasen, Lars Birch

2013-01-01

The article contributes to the literature on problem based learning and problem-oriented project work, building on and reflecting the experiences of the authors through decades of work with problem-oriented project pedagogy. The article explores different dimensions of problem based learning such...... and Learning (MIL). We discuss changes in the roles of the teachers as supervisors within this learning environment, and we explore the involvement of students as active participants and co-designers of how course and project activities unfold....

The studies on gas adsorption properties of MIL-53 series MOFs materials

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Yuqiu Jiao

2017-08-01

Full Text Available Molecular dynamics (MD, grand canonical Monte Carlo (GCMC and ideal adsorbed solution theory (IAST were used to study the structures and gas adsorption properties of MIL-53(M[M=Cr, Fe, Sc, Al] metal organic framework (MOF materials. The results show that the volumes of those MOF materials increase significantly at high temperature. By analyzing the adsorption isotherms, we found that the temperature had a paramount effect on the gas adsorption behaviors of these MOF materials. For MIL-53(Cr, the orders of the quantities of adsorbed gases were CH4>N2>CO2>H2S, CH4>H2S>CO2>N2 and CH4>CO2>H2S>N2 at 100K, 293K and 623K, respectively. We also calculated the adsorption of several combinations of two gases by MIL-53(Cr at 293K, the results indicate that the material had selective adsorption of CH4 over CO2, H2S and N2. Our calculations provide microscopic insights into the gas adsorption performances of these MOFs and may further guide the practice of gas separation.

The studies on gas adsorption properties of MIL-53 series MOFs materials

Science.gov (United States)

Jiao, Yuqiu; Li, Zhenyu; Ma, Yue; Zhou, Guanggang; Wang, Shuangxi; Lu, Guiwu

2017-08-01

Molecular dynamics (MD), grand canonical Monte Carlo (GCMC) and ideal adsorbed solution theory (IAST) were used to study the structures and gas adsorption properties of MIL-53(M)[M=Cr, Fe, Sc, Al] metal organic framework (MOF) materials. The results show that the volumes of those MOF materials increase significantly at high temperature. By analyzing the adsorption isotherms, we found that the temperature had a paramount effect on the gas adsorption behaviors of these MOF materials. For MIL-53(Cr), the orders of the quantities of adsorbed gases were CH4>N2>CO2>H2S, CH4>H2S>CO2>N2 and CH4>CO2>H2S>N2 at 100K, 293K and 623K, respectively. We also calculated the adsorption of several combinations of two gases by MIL-53(Cr) at 293K, the results indicate that the material had selective adsorption of CH4 over CO2, H2S and N2. Our calculations provide microscopic insights into the gas adsorption performances of these MOFs and may further guide the practice of gas separation.

Post-synthetic modification of MIL-101(Cr) with pyridine for high-performance liquid chromatographic separation of tocopherols.

Science.gov (United States)

Yang, Fang; Yang, Cheng-Xiong; Yan, Xiu-Ping

2015-05-01

Effective separation of tocopherols is challenging and significant due to their structural similarity and important biological role. Here we report the post-synthetic modification of metal-organic framework (MOF) MIL-101(Cr) with pyridine for high-performance liquid chromatographic (HPLC) separation of tocopherols. Baseline separation of four tocopherols was achieved on a pyridine-grafted MIL-101(Cr) packed column within 10 min using hexane/isopropanol (96:4, v/v) as the mobile phase at a flow rate of 0.5 mL min(-1). The pyridine-grafted MIL-101(Cr) packed column gave high column efficiency (85,000 plates m(-1) for δ-tocopherol) and good precision (0.2-0.3% for retention time, 1.8-3.4% for peak area, 2.6-2.7% for peak height), and also offered much better performance than unmodified MIL-101(Cr) and commercial amino-bonded silica packed column for HPLC separation of tocopherols. The results not only show the promising application of pyridine-grafted MIL-101(Cr) as a novel stationary phase for HPLC separation of tocopherols, but also reveal a facile post-modification of MOFs to expand the application of MOFs in separation sciences. Copyright © 2015 Elsevier B.V. All rights reserved.

Learning Multiplication Using Indonesian Traditional game in Third Grade

Directory of Open Access Journals (Sweden)

Rully Charitas Indra Prahmana

2012-07-01

Full Text Available Several previous researches showed that students had difficulty inunderstanding the basic concept of multiplication. Students are morelikely to be introduced by using formula without involving the conceptitself. This underlies the researcher to design a learning trajectory oflearning multiplication using Permainan Tradisional Tepuk Bergambar(PT2B as a context based on the student experience. The purpose ofthis research is to look at the role of PT2B in helping students'understanding in learning multiplication, which evolved from theinformal to formal level in third grade with Pendidikan MatematikaRealistik Indonesia (PMRI approach. The method used is designresearch starting from preliminary design, teaching experiments, andretrospective analysis. This research describes how PT2B make a realcontribution to the third grade students of SDN 179 Palembang tounderstand the concept of multiplication. The results showed PT2Bcontext can stimulate students to understand their knowledge of themultiplication concept. The whole strategy and model that studentsdiscover, describe, and discuss shows how the students construction orcontribution can uses to help their initial understanding of that concept.The stages in the learning trajectory of student have an important rolein understanding the concept of the operation number from informal tothe formal level.Keyword: Design Research, PMRI, Multiplication, Permainan TradisionalTepuk Bergambar DOI: http://dx.doi.org/10.22342/jme.3.2.1931.115-132

MIL-HDBK-338: Environmental Conversion Table Correction

Science.gov (United States)

Hark, Frank; Novack, Steven

2017-01-01

In reliability analysis, especially for launch vehicles, limited data is frequently a problem. Component data from other environments must be used. MIL-HBK-338 has a matrix showing the conversation between environments. Due to round off the conversions are not commutative, converting from A to B will not equal converting from B to A. Agenda: Introduction to environment conversions; Original table; Original table with edits; How big is the problem?; First attempt at correction; Proposed solution.

Cross-Platform Learning: On the Nature of Children's Learning from Multiple Media Platforms

Science.gov (United States)

Fisch, Shalom M.

2013-01-01

It is increasingly common for an educational media project to span several media platforms (e.g., TV, Web, hands-on materials), assuming that the benefits of learning from multiple media extend beyond those gained from one medium alone. Yet research typically has investigated learning from a single medium in isolation. This paper reviews several…

Programming MIL-101Cr for selective and enhanced CO2 adsorption at low pressure by postsynthetic amine functionalization.

Science.gov (United States)

Khutia, Anupam; Janiak, Christoph

2014-01-21

MIL-101Cr fully or partially (p) postsynthetically modified with nitro (-NO2) or amino (-NH2) groups was shown to be a robust, water stable, selective and enhanced carbon dioxide (CO2) adsorption material with the amine-functionality. The highly microporous amine-modified frameworks (up to 1.6 cm(3) g(-1) total pore volume) exhibit excellent thermal stability (>300 °C) with BET surface areas up to 2680 m(2) g(-1). At 1 bar (at 273 K) the gases CO2, CH4 and N2 are adsorbed up to 22.2 wt%, 1.67 wt% and 2.27 wt%, respectively. The two amine-modified MIL-101Cr-NH2 (4) and MIL-101Cr-pNH2 (5) showed the highest gas uptake capacities in the series with high ratios for the CO2 : N2 and CO2 : CH4 selectivities (up to 119 : 1 and 75 : 1, respectively, at 273 K). Comparison with non-modified MIL-101Cr traces the favorable CO2 adsorption properties of MIL-101Cr-NH2 (4) and MIL-101Cr-pNH2 (5) to the presence of the Lewis-basic amine groups. MIL-101Cr-NH2 (4) has a high isosteric heat of adsorption of 43 kJ mol(-1) at zero surface coverage and also >23 kJ mol(-1) over the entire adsorption range, which is well above the heat of liquefaction of bulk CO2. Large CO2 uptake capacities of amine-functionalized 4 and 5, coupled with high adsorption enthalpy, high selectivities and proven long-term water stability, make them suitable candidates for capturing CO2 at low pressure from gas mixtures including the use as a CO2 sorbent from moist air.

Brønsted instead of Lewis acidity in functionalized MIL-101Cr MOFs for efficient heterogeneous (nano-MOF) catalysis in the condensation reaction of aldehydes with alcohols.

Science.gov (United States)

Herbst, Annika; Khutia, Anupam; Janiak, Christoph

2014-07-21

Porous chromium(III) 2-nitro-, 2-amino-, and nonfunctionalized terephthalate (MIL-101Cr) metal organic frameworks are heterogeneous catalysts for diacetal formation from benzaldehyde and methanol (B-M reaction) as well as other aldehydes and alcohols. MIL-101Cr-NO2 obtained by direct reaction between CrO3 and 2-nitro-terephthalate showed the highest activity with 99% conversion in the B-M reaction in 90 min and turnover numbers of 114. The activity decreased in the order MIL-101Cr-NO2 > MIL-101Cr > MIL-101Cr-NH2. Within different samples of nonfunctionalized MIL-101Cr the activity increased with surface area. Methanol gas sorption of the different MIL materials correlates with the BET surface area and pore volume but not with the diacetalization activity. Benzaldehyde adsorption from heptane showed no significant difference for the different MILs. Gas sorption studies of CD3CN to probe for a higher Lewis acidity in MIL-101Cr-NO2 remained inconclusive. A high B-M catalytic activity of wet MIL-101Cr-NO2 excluded significant contributions from coordinatively unsaturated Lewis-acid sites. pH measurements of methanol dispersions of the MIL materials gave the most acidic pH (as low as 1.9) for MIL-101Cr-NO2, which significantly increased over MIL-101Cr (3.0) to MIL-101Cr-NH2 (3.3). The increase in acidity is of short range or a surface effect to the heterogeneous MIL particles as protons dissociating from the polarized aqua ligands (Cr-OH2) have to stay near the insoluble counteranionic framework. The variation in Brønsted acidity of MIL-101Cr-NO2 > MIL-101Cr ≈ MIL-101Cr-NH2 correlates with the withdrawing effect of NO2 and the diacetalization activity. The catalytic B-M activity of soluble, substitution-inert, and acidic Cr(NO3)3·9H2O supports the Brønsted-acid effect of the MIL materials. Filtration and centrifugation experiments with MIL-101Cr-NO2 revealed that about 2/3 of the catalytic activity comes from nano-MOF particles with a diameter below 200 nm. The MIL

Online transfer learning with extreme learning machine

Science.gov (United States)

Yin, Haibo; Yang, Yun-an

2017-05-01

In this paper, we propose a new transfer learning algorithm for online training. The proposed algorithm, which is called Online Transfer Extreme Learning Machine (OTELM), is based on Online Sequential Extreme Learning Machine (OSELM) while it introduces Semi-Supervised Extreme Learning Machine (SSELM) to transfer knowledge from the source to the target domain. With the manifold regularization, SSELM picks out instances from the source domain that are less relevant to those in the target domain to initialize the online training, so as to improve the classification performance. Experimental results demonstrate that the proposed OTELM can effectively use instances in the source domain to enhance the learning performance.

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.

Science.gov (United States)

Moreno-Scott, Jorge Humberto; Ortiz-Bayliss, José Carlos; Terashima-Marín, Hugo; Conant-Pablos, Santiago Enrique

2016-01-01

Constraint satisfaction problems are of special interest for the artificial intelligence and operations research community due to their many applications. Although heuristics involved in solving these problems have largely been studied in the past, little is known about the relation between instances and the respective performance of the heuristics used to solve them. This paper focuses on both the exploration of the instance space to identify relations between instances and good performing heuristics and how to use such relations to improve the search. Firstly, the document describes a methodology to explore the instance space of constraint satisfaction problems and evaluate the corresponding performance of six variable ordering heuristics for such instances in order to find regions on the instance space where some heuristics outperform the others. Analyzing such regions favors the understanding of how these heuristics work and contribute to their improvement. Secondly, we use the information gathered from the first stage to predict the most suitable heuristic to use according to the features of the instance currently being solved. This approach proved to be competitive when compared against the heuristics applied in isolation on both randomly generated and structured instances of constraint satisfaction problems.

Training Lp norm multiple kernel learning in the primal.

Science.gov (United States)

Liang, Zhizheng; Xia, Shixiong; Zhou, Yong; Zhang, Lei

2013-10-01

Some multiple kernel learning (MKL) models are usually solved by utilizing the alternating optimization method where one alternately solves SVMs in the dual and updates kernel weights. Since the dual and primal optimization can achieve the same aim, it is valuable in exploring how to perform Lp norm MKL in the primal. In this paper, we propose an Lp norm multiple kernel learning algorithm in the primal where we resort to the alternating optimization method: one cycle for solving SVMs in the primal by using the preconditioned conjugate gradient method and other cycle for learning the kernel weights. It is interesting to note that the kernel weights in our method can obtain analytical solutions. Most importantly, the proposed method is well suited for the manifold regularization framework in the primal since solving LapSVMs in the primal is much more effective than solving LapSVMs in the dual. In addition, we also carry out theoretical analysis for multiple kernel learning in the primal in terms of the empirical Rademacher complexity. It is found that optimizing the empirical Rademacher complexity may obtain a type of kernel weights. The experiments on some datasets are carried out to demonstrate the feasibility and effectiveness of the proposed method. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multiple Instance Fuzzy Inference

Science.gov (United States)

2015-12-02

Fashion models 5.19 14 Sunset scenes 3.52 15 Cars 4.93 16 Waterfalls 2.56 17 Antique furniture 2.30 18 Battle ships 4.32 19 Skiing 3.34 20 Desserts ...1000, in addition 10% of the Desserts category images were confused with Beach and 20.9% of Mountains and glaciers images were misclassified as

Post synthetic modification of MIL-101(Cr) for S-shaped isotherms and fast kinetics with water adsorption

International Nuclear Information System (INIS)

Teo, How Wei Benjamin; Chakraborty, Anutosh; Kayal, Sibnath

2017-01-01

Highlights: • Modification of parent MIL-101(Cr) metal organic framework (MOF) employing alkali metal ions (Li + , Na + , K + ). • Surface characteristics of the parent and alkali doped MIL-101(Cr) adsorbents. • Water uptakes are measured for the temperatures ranging from 25 °C to 60 °C under static and dynamic conditions. • Isotherms and kinetics data are fitted with Langmuir analogy models. • The 5% Li-doped MIL-101(Cr) is suitable for adsorption cooling. - Abstract: This article presents the surface characteristics of alkali (Li + , Na + , K + ) doped MIL-101(Cr) metal organic frameworks (MOFs), and the structural properties are evaluated by scanning electron micrography (SEM), X-ray diffraction (XRD), thermo-gravimetric analyser (TGA) and N 2 adsorption analysis. The amount of water uptakes are measured by a gravimetric analyser for the temperatures ranging from 298 K to 333 K and pressures up to the saturated conditions. The experimentally measured isotherms and kinetics data are fitted with the equations developed from the concept of Langmuir analogy. The isosteric heat of adsorption is calculated employing Van’t Hoff equation in the pressure-temperature-uptake co-ordinate systems. The hydrophobic length at low pressure regions is shortened by the addition of alkali dopants. It is observed that the alkali (Na, K and Li) ions on MIL-101(Cr) MOF increase the water uptakes at lower relative pressure region with fast kinetics. We have shown here that the alkali doped MIL-101(Cr) MOFs can be used as potential adsorbents for various low temperature heat transmission applications such as adsorption assisted heat pump, cooling and desalination.

Au3+/Au0 Supported on Chromium(III Terephthalate Metal Organic Framework (MIL-101 as an Efficient Heterogeneous Catalystfor Three-Component Coupling Synthesis of Propargylamines

Directory of Open Access Journals (Sweden)

Lili Liu

2017-01-01

Full Text Available Post-synthesis modification is a useful method for the functionalization of metal–organic frameworks (MOFs. A novel catalyst Au@MIL-101-ED-SA (ED = ethylenediamine, SA = salicylaldehyde, containing coexisting Au3+ ions and Au0 nanoparticles, was prepared successfully by post-synthesis modification with ethylenediamine, salicylaldehyde and gold. Gold nanoparticles supported on MIL-101 (Au@MIL-101 were prepared successfully by the impregnation method. Au@MIL-101-ED-SA and Au@MIL-101 were characterized by N2 adsorption–desorption, X-ray diffraction, infrared spectroscopy, thermogravimetric analysis, X-ray photoelectron spectroscopy, and inductively coupled plasma-optical emission spectrometry. Au@MIL-101-ED-SA and Au@MIL-101 were applied as environmentally friendly catalysts in the three-component coupling reaction of aldehydes, amines, and alkynes for the preparation of diverse propargylamines. Au@MIL-101-ED-SA contained a fraction of cationic gold (Au3+/Au0 = 0.9 and showed higher catalytic activity than Au@MIL-101, which was prepared by the impregnation method. Furthermore, the reactions were performed under heterogeneous conditions and the novel catalyst was successfully recycled for four consecutive runs.

MIL-100-Fe derived N-doped Fe/Fe3C@C electrocatalysts for efficient oxygen reduction reaction

Science.gov (United States)

Guo, Dakai; Han, Sancan; Wang, Jiacheng; Zhu, Yufang

2018-03-01

N-doped porous Fe/Fe3C@C electrocatalysts were prepared by the pyrolysis of the hexamethylenetetramine (HMT)-incorporated MIL-100-Fe at different temperatures (700-1000 °C) under N2 atmosphere. Rotary evaporation of MIL-100-Fe and HMT solution could make more N-enriched HMT molecules enter into the pores of MIL-100-Fe, thus improving nitrogen contents of the final pyrolyzed samples. All pyrolyzed samples show porous textures with middle specific surface areas. The X-ray photoelectron spectroscopy (XPS) results demonstrate the successful introduction of N atoms into carbon framework. Sample Fe-N2-800 prepared by annealing the precursors with the HMT/MIL-100-Fe weight ratio of 2 at 800 °C exhibits the best electrocatalytic activity towards the oxygen reduction reaction (ORR) in terms of onset potential and current density because of high graphitic N and pyridinic N content. The enwrapped Fe/Fe3C nanoparticles and Fe-Nx active sites in these samples could also boost the ORR activity synergistically. Moreover, sample Fe-N2-800 demonstrates a dominant four electron reduction process, as well as excellent long-term operation stability and methanol crossover resistance. Thus, the N-doped Fe/Fe3C@C composites derived from the HMT-incorporated MIL-100-Fe are promising electrocatalysts to replace Pt/C for ORR in practical applications.

Fast generation of multiple resolution instances of raster data sets

DEFF Research Database (Denmark)

Arge, Lars; Haverkort, Herman; Tsirogiannis, Constantinos

2012-01-01

In many GIS applications it is important to study the characteristics of a raster data set at multiple resolutions. Often this is done by generating several coarser resolution rasters from a fine resolution raster. In this paper we describe efficient algorithms for different variants of this prob......In many GIS applications it is important to study the characteristics of a raster data set at multiple resolutions. Often this is done by generating several coarser resolution rasters from a fine resolution raster. In this paper we describe efficient algorithms for different variants...... in the main memory of the computer. We also provide two algorithms that solve this problem in external memory, that is when the input raster is larger than the main memory. The first external algorithm is very easy to implement and requires O(sort(N)) data block transfers from/to the external memory....... For this variant we describe an algorithm that runs in (U logN) time in internal memory, where U is the size of the output. We show how this algorithm can be adapted to perform efficiently in the external memory using O(sort(U)) data transfers from the disk. We have also implemented two of the presented algorithms...

Metal organic framework MIL-101(Cr) for dehydration reactions

Indian Academy of Sciences (India)

under vapour phase conditions in the temperature range of 513–533 K and time on stream (TOS) at 513 K. Cr-MIL-101 ... gies and potential applications in gas storage, sep- aration ... these materials have not been explored much. Recently .... The products were collected in ice cold trap and ... There is no change in the crys-.

Ni-Pt nanoparticles growing on metal organic frameworks (MIL-96) with enhanced catalytic activity for hydrogen generation from hydrazine at room temperature.

Science.gov (United States)

Wen, Lan; Du, Xiaoqiong; Su, Jun; Luo, Wei; Cai, Ping; Cheng, Gongzhen

2015-04-07

Well-dispersed bimetallic Ni-Pt nanoparticles (NPs) with different compositions have been successfully grown on the MIL-96 by a simple liquid impregnation method using NaBH4 as the reducing agent. Powder X-ray diffraction, transmission electron microscopy, energy-dispersive X-ray spectroscopy, N2 adsorption-desorption, and inductively coupled plasma-atomic emission spectroscopy measurements were employed to characterize the NiPt/MIL-96. Catalytic activity of NiPt/MIL-96 catalysts was tested in the hydrogen generation from the aqueous alkaline solution of hydrazine at room temperature. These catalysts are composition dependent on their catalytic activity, while Ni64Pt36/MIL-96 exhibits the highest catalytic activity among all the catalysts tested, with a turnover frequency value of 114.3 h(-1) and 100% hydrogen selectivity. This excellent catalytic performance might be due to the synergistic effect of the MIL-96 support and NiPt NPs, while NiPt NPs supported on other conventional supports, such as SiO2, carbon black, γ-Al2O3, poly(N-vinyl-2-pyrrolidone) (PVP), and the physical mixture of NiPt and MIL-96, all of them exhibit inferior catalytic activity compared to that of NiPt/MIL-96.

Research of mercury removal from sintering flue gas of iron and steel by the open metal site of Mil-101(Cr).

Science.gov (United States)

Zhao, Songjian; Mei, Jian; Xu, Haomiao; Liu, Wei; Qu, Zan; Cui, Yong; Yan, Naiqiang

2018-06-05

Metal-organic frameworks (MOFs) adsorbent Mil-101(Cr) was introduced for the removal of elemental mercury from sintering flue gas. Physical and chemical characterization of the adsorbents showed that MIL-101(Cr) had the largest BET surface area, high thermal stability and oxidation capacity. Hg 0 removal performance analysis indicated that the Hg 0 removal efficiency of MIL-101(Cr) increased with the increasing temperature and oxygen content. Besides, MIL-101(Cr) had the highest Hg 0 removal performance compared with Cu-BTC, UiO-66 and activated carbon, which can reach about 88% at 250 °C. The XPS and Hg-TPD methods were used to analyze the Hg 0 removal mechanism; the results show that Hg 0 was first adsorbed on the surface of Mil-101(Cr), and then oxidized by the open metal site Cr 3+ . The generated Hg 2+ was then combined surface adsorbed oxygen of adsorbent to form HgO, and the open metal site Cr 2+ was oxidized to Cr 3+ by surface active oxygen again. Furthermore, MIL-101(Cr) had good chemical and thermal stability. Copyright © 2017 Elsevier B.V. All rights reserved.

Learned Helplessness: Theory and Evidence

Science.gov (United States)

Maier, Steven F.; Seligman, Martin E. P.

1976-01-01

Authors believes that three phenomena are all instances of "learned helplessness," instances in which an organism has learned that outcomes are uncontrollable by his responses and is seriously debilitated by this knowledge. This article explores the evidence for the phenomena of learned helplessness, and discussed a variety of theoretical…

Evaluation of electrical test conditions in MIL-M-38510 slash sheets

Science.gov (United States)

Sandgren, K.

1980-08-01

Adequacy of MIL-M-38510 slash sheet requirements for electrical test conditions in an automated test environment were evaluated. Military temperature range commercial devices of 13 types from 6 manufacturers were purchased. Software for testing these devices and for varying the test conditions was written for the Tektronix S-3260 test system. The devices were tested to evaluate the effects of pin-condition settling time, measurement sequence of the same and different D-C parameters, temperature sequence, differently defined temperature ambients, variable measurement conditions, sequence of time measurements, pin-application sequence, and undesignated pin condition ambiguity. An alternative to current tri-state enable and disable time measurements is proposed; S-3260 'open' and 'ground' conditions are characterized; and suggestions for changes in MIL-M-38510 slash sheet specifications and MIL-STD-883 test methods are proposed, both to correct errors and ambiguities and to facilitate the gathering of repeatable data on automated test equipment. Data obtained showed no sensitivity to measurement or temperature sequence nor to temperature ambient, provided that test times were not excessive. V sub ICP tests and some low current measurements required allowance for a pin condition settling time because of the test system speed. Some pin condition application sequences yielded incorrect measurements. Undefined terminal conditions of output pins were found to affect I sub OS and propagation delay time measurements. Truth table test results varied with test frequency and V sub IL for low-power Schottky devices.

Instance Selection for Classifier Performance Estimation in Meta Learning

OpenAIRE

Marcin Blachnik

2017-01-01

Building an accurate prediction model is challenging and requires appropriate model selection. This process is very time consuming but can be accelerated with meta-learning–automatic model recommendation by estimating the performances of given prediction models without training them. Meta-learning utilizes metadata extracted from the dataset to effectively estimate the accuracy of the model in question. To achieve that goal, metadata descriptors must be gathered efficiently and must be inform...

Development of Multiple Thinking and Creativity in Organizational Learning

Science.gov (United States)

Cheng, Yin Cheong

2005-01-01

Purpose: Based on a typology of contextualized multiple thinking, this paper aims to elaborate how the levels of thinking (data, information, knowledge, and intelligence), and the types of thinking as a whole, can be used to profile the characteristics of multiple thinking in organizational learning, re-conceptualize the nature of creativity in…

Fabrication of metal-organic framework MIL-88B films on stainless steel fibers for solid-phase microextraction of polychlorinated biphenyls.

Science.gov (United States)

Wu, Ye-Yu; Yang, Cheng-Xiong; Yan, Xiu-Ping

2014-03-21

Metal-organic frameworks (MOFs) have received considerable attention as novel sorbents for sample preparation due to their fascinating structures and functionalities such as large surface area, good thermal stability, and uniform structured nanoscale cavities. Here, we report the application of a thermal and solvent stable MOF MIL-88B with nanosized bipyramidal cages and large surface area for solid-phase microextraction (SPME) of polychlorinated biphenyls (PCBs). Novel MIL-88B coated fiber was fabricated via an in situ hydrothermal growth of MIL-88B film on etched stainless steel fiber. The MIL-88B coated fiber gave large enhancement factors (757-2243), low detection limits (0.45-1.32ngL(-1)), and good linearity (5-200ngL(-1)) for PCBs. The relative standard deviation (RSD) for six replicate extractions of PCBs at 100ngL(-1) on MIL-88B coated fiber ranged from 4.2% to 8.7%. The recoveries for spiked PCBs (10ngL(-1)) in water and soil samples were in the range of 79.7-103.2%. Besides, the MIL-88B coated fiber was stable enough for 150 extraction cycles without significant loss of extraction efficiency. The developed method was successfully applied to the determination of PCBs in water samples and soil samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Feedback-related brain activity predicts learning from feedback in multiple-choice testing.

Science.gov (United States)

Ernst, Benjamin; Steinhauser, Marco

2012-06-01

Different event-related potentials (ERPs) have been shown to correlate with learning from feedback in decision-making tasks and with learning in explicit memory tasks. In the present study, we investigated which ERPs predict learning from corrective feedback in a multiple-choice test, which combines elements from both paradigms. Participants worked through sets of multiple-choice items of a Swahili-German vocabulary task. Whereas the initial presentation of an item required the participants to guess the answer, corrective feedback could be used to learn the correct response. Initial analyses revealed that corrective feedback elicited components related to reinforcement learning (FRN), as well as to explicit memory processing (P300) and attention (early frontal positivity). However, only the P300 and early frontal positivity were positively correlated with successful learning from corrective feedback, whereas the FRN was even larger when learning failed. These results suggest that learning from corrective feedback crucially relies on explicit memory processing and attentional orienting to corrective feedback, rather than on reinforcement learning.

Deposition of CdS nanoparticles on MIL-53(Fe) metal-organic framework with enhanced photocatalytic degradation of RhB under visible light irradiation

Energy Technology Data Exchange (ETDEWEB)

Hu, Longxing, E-mail: hulxhhhb@shu.edu.cn [School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444 (China); Deng, Guihua [School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444 (China); Lu, Wencong [College of Sciences, Shanghai University, Shanghai 200444 (China); Pang, Siwei; Hu, Xing [School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444 (China)

2017-07-15

Graphical abstract: The CdS/MIL-53(Fe) photocatalyst has been synthesized by a facile two-step solvothermal method and applied for photocatalytic degradation of organic pollutant RhB under visible light irradiation. - Highlights: • A novel CdS/MIL-53(Fe) photocatalyst was successfully synthesized via a facile two-step solvothermal method. • CdS/MIL-53(Fe) exhibited an enhanced visible-light photocatalytic degradation of RhB in water. • The mechanisms for the formation of CdS/MIL-53(Fe) and photocatalytic degradation of RhB were proposed. - Abstract: A novel composite, CdS/MIL-53(Fe), was successfully fabricated via a facile solvothermal method and characterized with XRD, SEM, TEM, XPS, FT-IR and UV–vis DRS. The results showed that the fabrication was able to result in a good dispersion of CdS nanoparticles onto MIL-53(Fe). The photocatalytic activities of the as-synthesized composite were investigated through the degradation of Rhodamine B (RhB) in water under visible light irradiation. It was found that the composite prepared at the mass ratio of CdS to MIL-53(Fe) of 1.5:1 displayed the highest photocatalytic activity. An approximately 92.5% of photocatalytic degradation of RhB was achieved at 0.5 g/L of 1.5-CdS/MIL dosage, 10 mg/L of initial RhB concentration and 23 °C of reaction temperature under visible light irradiation. The RhB photocatalytic degradation followed well the first-order kinetics equation and the increased catalyst dosage and optimal initial RhB concentration were responsible for the enhanced photocatalytic degradation. Quenching tests revealed that the predominant free radicals in the CdS/MIL-(53)-RhB{sub aq}-visible light system was O{sub 2}{sup −}·; nevertheless, h{sup +} and ·OH also contributed to a certain degree. The enhanced photocatalytic performance was ascribed to the formation of heterojunction structure between CdS and MIL-53(Fe) which significantly suppressed the recombination of photogenerated electron-hole pairs

Deposition of CdS nanoparticles on MIL-53(Fe) metal-organic framework with enhanced photocatalytic degradation of RhB under visible light irradiation

International Nuclear Information System (INIS)

Hu, Longxing; Deng, Guihua; Lu, Wencong; Pang, Siwei; Hu, Xing

2017-01-01

Graphical abstract: The CdS/MIL-53(Fe) photocatalyst has been synthesized by a facile two-step solvothermal method and applied for photocatalytic degradation of organic pollutant RhB under visible light irradiation. - Highlights: • A novel CdS/MIL-53(Fe) photocatalyst was successfully synthesized via a facile two-step solvothermal method. • CdS/MIL-53(Fe) exhibited an enhanced visible-light photocatalytic degradation of RhB in water. • The mechanisms for the formation of CdS/MIL-53(Fe) and photocatalytic degradation of RhB were proposed. - Abstract: A novel composite, CdS/MIL-53(Fe), was successfully fabricated via a facile solvothermal method and characterized with XRD, SEM, TEM, XPS, FT-IR and UV–vis DRS. The results showed that the fabrication was able to result in a good dispersion of CdS nanoparticles onto MIL-53(Fe). The photocatalytic activities of the as-synthesized composite were investigated through the degradation of Rhodamine B (RhB) in water under visible light irradiation. It was found that the composite prepared at the mass ratio of CdS to MIL-53(Fe) of 1.5:1 displayed the highest photocatalytic activity. An approximately 92.5% of photocatalytic degradation of RhB was achieved at 0.5 g/L of 1.5-CdS/MIL dosage, 10 mg/L of initial RhB concentration and 23 °C of reaction temperature under visible light irradiation. The RhB photocatalytic degradation followed well the first-order kinetics equation and the increased catalyst dosage and optimal initial RhB concentration were responsible for the enhanced photocatalytic degradation. Quenching tests revealed that the predominant free radicals in the CdS/MIL-(53)-RhB aq -visible light system was O 2 − ·; nevertheless, h + and ·OH also contributed to a certain degree. The enhanced photocatalytic performance was ascribed to the formation of heterojunction structure between CdS and MIL-53(Fe) which significantly suppressed the recombination of photogenerated electron-hole pairs. Moreover, the

Highly efficient Fenton and enzyme-mimetic activities of NH2-MIL-88B(Fe) metal organic framework for methylene blue degradation.

Science.gov (United States)

He, Jianchuan; Zhang, Yao; Zhang, Xiaodan; Huang, Yuming

2018-03-26

Here, we show that NH 2 -MIL-88B(Fe) can be used as a peroxidase-like catalyst for Fenton-like degradation of methylene blue (MB) in water. The iron-based NH 2 -MIL-88B(Fe) metal organic framework (MOF) was synthesized by a facile and rapid microwave heating method. It was characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, powder X-ray diffraction, and the Brunauer-Emmett-Teller method. The NH 2 -MIL-88B(Fe) MOF possesses intrinsic oxidase-like and peroxidase-like activities. The reaction parameters that affect MB degradation were investigated, including the solution pH, NH 2 -MIL-88B(Fe) MOF and H 2 O 2 concentrations, and temperature. The results show that the NH 2 -MIL-88B(Fe) MOF exhibits a wide working pH range (pH 3.0-11.0), temperature tolerance, and good recyclability for MB removal. Under the optimal conditions, complete removal of MB was achieved within 45 min. In addition, removal of MB was above 80% after five cycles, showing the good recyclability of NH 2 -MIL-88B(Fe). The NH 2 -MIL-88B(Fe) MOF has the features of easy preparation, high efficiency, and good recyclability for MB removal in a wide pH range. Electron spin resonance and fluorescence probe results suggest the involvement of hydroxyl radicals in MB degradation. These findings provide new insight into the application of high-efficient MOF-based Fenton-like catalysts for water purification.

Metal-organic frameworks as potential shock absorbers: the case of the highly flexible MIL-53(Al).

Science.gov (United States)

Yot, Pascal G; Boudene, Zoubeyr; Macia, Jasmine; Granier, Dominique; Vanduyfhuys, Louis; Verstraelen, Toon; Van Speybroeck, Veronique; Devic, Thomas; Serre, Christian; Férey, Gérard; Stock, Norbert; Maurin, Guillaume

2014-08-28

The mechanical energy absorption ability of the highly flexible MIL-53(Al) MOF material was explored using a combination of experiments and molecular simulations. A pressure-induced transition between the large pore and the closed pore forms of this solid was revealed to be irreversible and associated with a relatively large energy absorption capacity. Both features make MIL-53(Al) the first potential MOF candidate for further use as a shock absorber.

Endurance Pump Tests With Fresh and Purified MIL-PRF-83282 Hydraulic Fluid

National Research Council Canada - National Science Library

Sharma, Shashi

1999-01-01

.... Two endurance pump tests were conducted with F-16 aircraft hydraulic pumps, using both fresh and purified MIL-PRF-83282 hydraulic fluid, to determine if fluid purification had any adverse effect on pump life...

Photoelectrochemical detection of the herbicide clethodim by using the modified metal-organic framework amino-MIL-125(Ti)/TiO2

International Nuclear Information System (INIS)

Jin, Dangqin; Yu, Liangyun; Xu, Qin; Hu, Xiaoya

2015-01-01

We describe a sensitive photoelectrochemical (PEC) sensor for the determination of the herbicide clethodim. The PEC sensor was constructed by using amino-MIL-125/TiO 2 (MIL stands for Materials from Institute Lavoisier), an amino-functionalized metal-organic framework (MOF) modified with TiO2. The amino-MIL-125/TiO 2 was synthesized by a simple one-step solvothermal method and placed on a glassy carbon electrode where it displays photoelectrocatalytic activity. Scanning electron microscopy (SEM), Fourier-transform infrared (FTIR) spectroscopy and X-ray diffractometry (XRD) were used to characterize the amino-MIL-125/TiO2. In the sensing process, amino-MIL-125/TiO 2 is illuminated by visible light to produce electrons. These excited electrons are delivered to the glassy carbon electrode, leaving positively charged holes (h+) on the surface of the amino-MIL-125/TiO 2 . The holes react with H 2 O to generate hydroxy radicals (•OH). Clethodim rapidly attacks the hydroxy radicals and improves the efficiency of charge separation, this leading to an enhanced photocurrent. Under the optimal experimental conditions, this photoelectrochemical method enables clethodim to be quantified in the concentration range from 0.2 to 25 μmol L −1 , with a detection limit (3 S/N) of 10 nmol L −1 . The assay was applied to the determination of clethodim in soil samples, and results were in acceptable agreement with data obtained by liquid chromatography/mass spectrometry. (author)

Fluorescent metal-organic framework MIL-53(Al) for highly selective and sensitive detection of Fe3+ in aqueous solution.

Science.gov (United States)

Yang, Cheng-Xiong; Ren, Hu-Bo; Yan, Xiu-Ping

2013-08-06

Fluorescent metal-organic frameworks (MOFs) have received great attention in sensing application. Here, we report the exploration of fluorescent MIL-53(Al) for highly selective and sensitive detection of Fe(3+) in aqueous solution. The cation exchange between Fe(3+) and the framework metal ion Al(3+) in MIL-53(Al) led to the quenching of the fluorescence of MIL-53(Al) due to the transformation of strong-fluorescent MIL-53(Al) to weak-fluorescent MIL-53(Fe), allowing highly selective and sensitive detection of Fe(3+) in aqueous solution with a linear range of 3-200 μM and a detection limit of 0.9 μM. No interferences from 0.8 M Na(+); 0.35 M K(+); 11 mM Cu(2+); 10 mM Ni(2+); 6 mM Ca(2+), Pb(2+), and Al(3+); 5.5 mM Mn(2+); 5 mM Co(2+) and Cr(3+); 4 mM Hg(2+), Cd(2+), Zn(2+), and Mg(2+); 3 mM Fe(2+); 0.8 M Cl(-); 60 mM NO2(-) and NO3(-); 10 mM HPO4(2-), H2PO4(-), SO3(2-), SO4(2-), and HCOO(-); 8 mM CO3(2-), HCO3(-), and C2O4(2-); and 5 mM CH3COO(-) were found for the detection of 150 μM Fe(3+). The possible mechanism for the quenching effect of Fe(3+) on the fluorescence of MIL-53(Al) was elucidated by inductively coupled plasma-mass spectrometry, X-ray diffraction spectrometry, and Fourier transform infrared spectrometry. The specific cation exchange behavior between Fe(3+) and the framework Al(3+) along with the excellent stability of MIL-53(Al) allows highly selective and sensitive detection of Fe(3+) in aqueous solution. The developed method was applied to the determination of Fe(3+) in human urine samples with the quantitative spike recoveries from 98.2% to 106.2%.

Multiple systems for motor skill learning.

Science.gov (United States)

Clark, Dav; Ivry, Richard B

2010-07-01

Motor learning is a ubiquitous feature of human competence. This review focuses on two particular classes of model tasks for studying skill acquisition. The serial reaction time (SRT) task is used to probe how people learn sequences of actions, while adaptation in the context of visuomotor or force field perturbations serves to illustrate how preexisting movements are recalibrated in novel environments. These tasks highlight important issues regarding the representational changes that occur during the course of motor learning. One important theme is that distinct mechanisms vary in their information processing costs during learning and performance. Fast learning processes may require few trials to produce large changes in performance but impose demands on cognitive resources. Slower processes are limited in their ability to integrate complex information but minimally demanding in terms of attention or processing resources. The representations derived from fast systems may be accessible to conscious processing and provide a relatively greater measure of flexibility, while the representations derived from slower systems are more inflexible and automatic in their behavior. In exploring these issues, we focus on how multiple neural systems may interact and compete during the acquisition and consolidation of new behaviors. Copyright © 2010 John Wiley & Sons, Ltd. This article is categorized under: Psychology > Motor Skill and Performance. Copyright © 2010 John Wiley & Sons, Ltd.

Geochemistry of Lunar Highland Meteorites Mil, 090034, 090036 AND 090070

Science.gov (United States)

Shirai, N.aoki; Ebihara, M.; Sekimoto, S.; Yamaguchi, A.; Nyquist, L.; Shih, C.-Y.; Park, J.; Nagao, K.

2012-01-01

Apollo and Luna samples were collected from a restricted area on the near side of the Moon, while the source craters of the lunar meteorites are randomly distributed. For example, Takeda et al. [1] and Yamaguchi et al. [2] found a variety of lithic clasts in Dho 489 and Y 86032 which were not represented by Apollo samples, and some of these clasts have lower rare earth elements (REE) and FeO abundances than Apollo anorthosites, respectively. Takeda et al. [1] and Yamaguchi et al. [2] concluded that Dho 489 and Y 86032 originated from the lunar farside. Therefore, lunar meteorites provide an opportunity to study lunar surface rocks from areas not sampled by Apollo and Luna missions. Three lunar anorthitic breccias (MIL 090034, 090036 and 090070) were found on the Miller Range Ice Field in Antarctica during the 2009-2010 ANSMET season [3]. In this study, we determined elemental abudnances for MIL 090034, 090036 and 090070 by using INAA and aimed to characterize these meteorites in chemical compositions in comparison with those for other lunar meteorites and Apollo samples.

Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval.

Science.gov (United States)

Li, Ke; Pang, Kaiyue; Song, Yi-Zhe; Hospedales, Timothy M; Xiang, Tao; Zhang, Honggang

2017-08-25

We study the problem of fine-grained sketch-based image retrieval. By performing instance-level (rather than category-level) retrieval, it embodies a timely and practical application, particularly with the ubiquitous availability of touchscreens. Three factors contribute to the challenging nature of the problem: (i) free-hand sketches are inherently abstract and iconic, making visual comparisons with photos difficult, (ii) sketches and photos are in two different visual domains, i.e. black and white lines vs. color pixels, and (iii) fine-grained distinctions are especially challenging when executed across domain and abstraction-level. To address these challenges, we propose to bridge the image-sketch gap both at the high-level via parts and attributes, as well as at the low-level, via introducing a new domain alignment method. More specifically, (i) we contribute a dataset with 304 photos and 912 sketches, where each sketch and image is annotated with its semantic parts and associated part-level attributes. With the help of this dataset, we investigate (ii) how strongly-supervised deformable part-based models can be learned that subsequently enable automatic detection of part-level attributes, and provide pose-aligned sketch-image comparisons. To reduce the sketch-image gap when comparing low-level features, we also (iii) propose a novel method for instance-level domain-alignment, that exploits both subspace and instance-level cues to better align the domains. Finally (iv) these are combined in a matching framework integrating aligned low-level features, mid-level geometric structure and high-level semantic attributes. Extensive experiments conducted on our new dataset demonstrate effectiveness of the proposed method.

Performance of metal-organic framework MIL-101 after surfactant modification in the extraction of endocrine disrupting chemicals from environmental water samples.

Science.gov (United States)

Huang, Zhenzhen; Lee, Hian Kee

2015-10-01

The research presented in this paper explored the modification and application of a metal-organic framework, MIL-101, with nonionic surfactant-Triton X-114 in dispersive solid-phase extraction for the preconcentration of four endocrine disrupting chemicals (estrone, 17α-ethynylestradiol, estriol and diethylstilbestrol) from environmental water samples. Triton X-114 molecules could be adsorbed by the hydrophobic surface of the MIL-101 crystals, and thus improved the dispersibility of MIL-101 in aqueous solution by serving as a hydrophilic coating. Cloud point phase separation from Triton X-114 accelerated the separation of extracts from the aqueous matrix. The proposed method combines the favorable attributes of strong adsorption capacity resulting from the porous structure of MIL-101 and self-assembly of Triton X-114 molecules. Post-extraction derivatization using N-methyl-N-(trimethylsilyl)trifluoroacetamide was employed to facilitate the quantitative determination of the extracts by gas chromatography-mass spectrometry. The main factors affecting the preparation of modified MIL-101, and extraction of the analytes, such as the amount of surfactant, the ultrasonic and vortex durations, solution pH and desorption conditions, were investigated in detail. Under the optimized conditions, the present method yielded low limits of detection (0.006-0.023 ng/mL), good linearity from 0.09 to 45 ng/mL (coefficients of determination higher than 0.9980) and acceptable precision (relative standard deviations of 2.2-13%). The surface modified MIL-101 was demonstrated to be effective for the extraction of the selected estrogens from aqueous samples, giving rise to markedly improved extraction performance compared to the unmodified MIL-101. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimizing Multiple-Choice Tests as Learning Events

Science.gov (United States)

Little, Jeri Lynn

2011-01-01

Although generally used for assessment, tests can also serve as tools for learning--but different test formats may not be equally beneficial. Specifically, research has shown multiple-choice tests to be less effective than cued-recall tests in improving the later retention of the tested information (e.g., see meta-analysis by Hamaker, 1986),…

The company objects keep: Linking referents together during cross-situational word learning.

Science.gov (United States)

Zettersten, Martin; Wojcik, Erica; Benitez, Viridiana L; Saffran, Jenny

2018-04-01

Learning the meanings of words involves not only linking individual words to referents but also building a network of connections among entities in the world, concepts, and words. Previous studies reveal that infants and adults track the statistical co-occurrence of labels and objects across multiple ambiguous training instances to learn words. However, it is less clear whether, given distributional or attentional cues, learners also encode associations amongst the novel objects. We investigated the consequences of two types of cues that highlighted object-object links in a cross-situational word learning task: distributional structure - how frequently the referents of novel words occurred together - and visual context - whether the referents were seen on matching backgrounds. Across three experiments, we found that in addition to learning novel words, adults formed connections between frequently co-occurring objects. These findings indicate that learners exploit statistical regularities to form multiple types of associations during word learning.

Dimensions of problem based learning - dialogue and online collaboration in projects

DEFF Research Database (Denmark)

Andreasen, Lars Birch; Nielsen, Jørgen Lerche

2013-01-01

-based learning approach developed in Denmark historically and theoretically, and how it unfolds today discussed through a case of the Danish Master programme in ICT and Learning (MIL), focusing on changes in the roles of teachers as supervisors, and the involvement of students in course and project activities....

Gestion intégrée du mildiou du mil en station au centre régional de ...

African Journals Online (AJOL)

user

Le mil (Pennicetum glaucum) L.R.Br constitue 75% de la production céréalière du Niger. Cependant, son rendement est très faible dû à plusieurs types de contraintes. La maladie du mildiou du mil causé par un champignon Sclerospora graminicola (Sacc) Schroët, occupe une place importante. L'objectif de cette étude.

Using mini-games for learning multiplication and division: A longitudinal effect study

NARCIS (Netherlands)

Bakker, M.

2014-01-01

This thesis reports the findings of a three-year longitudinal research project set up to investigate the effectiveness of employing online mini-games for the learning of multiplication and division, including multiplicative fact knowledge (declarative knowledge), multiplicative operation skills

General Dimensional Multiple-Output Support Vector Regressions and Their Multiple Kernel Learning.

Science.gov (United States)

Chung, Wooyong; Kim, Jisu; Lee, Heejin; Kim, Euntai

2015-11-01

Support vector regression has been considered as one of the most important regression or function approximation methodologies in a variety of fields. In this paper, two new general dimensional multiple output support vector regressions (MSVRs) named SOCPL1 and SOCPL2 are proposed. The proposed methods are formulated in the dual space and their relationship with the previous works is clearly investigated. Further, the proposed MSVRs are extended into the multiple kernel learning and their training is implemented by the off-the-shelf convex optimization tools. The proposed MSVRs are applied to benchmark problems and their performances are compared with those of the previous methods in the experimental section.

Procedural learning during declarative control.

Science.gov (United States)

Crossley, Matthew J; Ashby, F Gregory

2015-09-01

There is now abundant evidence that human learning and memory are governed by multiple systems. As a result, research is now turning to the next question of how these putative systems interact. For instance, how is overall control of behavior coordinated, and does learning occur independently within systems regardless of what system is in control? Behavioral, neuroimaging, and neuroscience data are somewhat mixed with respect to these questions. Human neuroimaging and animal lesion studies suggest independent learning and are mostly agnostic with respect to control. Human behavioral studies suggest active inhibition of behavioral output but have little to say regarding learning. The results of two perceptual category-learning experiments are described that strongly suggest that procedural learning does occur while the explicit system is in control of behavior and that this learning might be just as good as if the procedural system was controlling the response. These results are consistent with the idea that declarative memory systems inhibit the ability of the procedural system to access motor output systems but do not prevent procedural learning. (c) 2015 APA, all rights reserved).

Solid-State NMR Spectroscopy Proves the Presence of Penta-coordinated Sc Sites in MIL-100(Sc).

Science.gov (United States)

Giovine, Raynald; Volkringer, Christophe; Ashbrook, Sharon E; Trébosc, Julien; McKay, David; Loiseau, Thierry; Amoureux, Jean-Paul; Lafon, Olivier; Pourpoint, Frédérique

2017-07-18

Advanced solid-state NMR methods and first-principles calculations demonstrate for the first time the formation of penta-coordinated scandium sites. These coordinatively unsaturated sites were shown during the thermal activation of scandium-based metal-organic frameworks (MOFs). A 45 Sc NMR experiment allows their specific observation in activated Sc 3 BTB 2 (H 3 BTB=1,3,5-tris(4-carboxyphenyl)benzene) and MIL-100(Sc) MOFs. The assignment of the ScO 5 groups is supported by the DFT calculations of NMR parameters. The presence of ScO 5 Lewis acid sites in MIL-100(Sc) explains furthermore its catalytic activity. The first NMR experiment to probe 13 C- 45 Sc distances is also introduced. This advanced solid-state NMR pulse sequence allows the demonstration of the shrinkage of the MIL-100(Sc) network when the activation temperature is raised. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Instance-specific algorithm configuration

CERN Document Server

Malitsky, Yuri

2014-01-01

This book presents a modular and expandable technique in the rapidly emerging research area of automatic configuration and selection of the best algorithm for the instance at hand. The author presents the basic model behind ISAC and then details a number of modifications and practical applications. In particular, he addresses automated feature generation, offline algorithm configuration for portfolio generation, algorithm selection, adaptive solvers, online tuning, and parallelization.    The author's related thesis was honorably mentioned (runner-up) for the ACP Dissertation Award in 2014,

Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments

Science.gov (United States)

Han, Wenjing; Coutinho, Eduardo; Li, Haifeng; Schuller, Björn; Yu, Xiaojie; Zhu, Xuan

2016-01-01

Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an efficient combination of confidence-based Active Learning and Self-Training with the aim of minimizing the need for human annotation for sound classification model training. The proposed method pre-processes the instances that are ready for labeling by calculating their classifier confidence scores, and then delivers the candidates with lower scores to human annotators, and those with high scores are automatically labeled by the machine. We demonstrate the feasibility and efficacy of this method in two practical scenarios: pool-based and stream-based processing. Extensive experimental results indicate that our approach requires significantly less labeled instances to reach the same performance in both scenarios compared to Passive Learning, Active Learning and Self-Training. A reduction of 52.2% in human labeled instances is achieved in both of the pool-based and stream-based scenarios on a sound classification task considering 16,930 sound instances. PMID:27627768

Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments.

Science.gov (United States)

Han, Wenjing; Coutinho, Eduardo; Ruan, Huabin; Li, Haifeng; Schuller, Björn; Yu, Xiaojie; Zhu, Xuan

2016-01-01

Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an efficient combination of confidence-based Active Learning and Self-Training with the aim of minimizing the need for human annotation for sound classification model training. The proposed method pre-processes the instances that are ready for labeling by calculating their classifier confidence scores, and then delivers the candidates with lower scores to human annotators, and those with high scores are automatically labeled by the machine. We demonstrate the feasibility and efficacy of this method in two practical scenarios: pool-based and stream-based processing. Extensive experimental results indicate that our approach requires significantly less labeled instances to reach the same performance in both scenarios compared to Passive Learning, Active Learning and Self-Training. A reduction of 52.2% in human labeled instances is achieved in both of the pool-based and stream-based scenarios on a sound classification task considering 16,930 sound instances.

Reduced multiple empirical kernel learning machine.

Science.gov (United States)

Wang, Zhe; Lu, MingZhe; Gao, Daqi

2015-02-01

Multiple kernel learning (MKL) is demonstrated to be flexible and effective in depicting heterogeneous data sources since MKL can introduce multiple kernels rather than a single fixed kernel into applications. However, MKL would get a high time and space complexity in contrast to single kernel learning, which is not expected in real-world applications. Meanwhile, it is known that the kernel mapping ways of MKL generally have two forms including implicit kernel mapping and empirical kernel mapping (EKM), where the latter is less attracted. In this paper, we focus on the MKL with the EKM, and propose a reduced multiple empirical kernel learning machine named RMEKLM for short. To the best of our knowledge, it is the first to reduce both time and space complexity of the MKL with EKM. Different from the existing MKL, the proposed RMEKLM adopts the Gauss Elimination technique to extract a set of feature vectors, which is validated that doing so does not lose much information of the original feature space. Then RMEKLM adopts the extracted feature vectors to span a reduced orthonormal subspace of the feature space, which is visualized in terms of the geometry structure. It can be demonstrated that the spanned subspace is isomorphic to the original feature space, which means that the dot product of two vectors in the original feature space is equal to that of the two corresponding vectors in the generated orthonormal subspace. More importantly, the proposed RMEKLM brings a simpler computation and meanwhile needs a less storage space, especially in the processing of testing. Finally, the experimental results show that RMEKLM owns a much efficient and effective performance in terms of both complexity and classification. The contributions of this paper can be given as follows: (1) by mapping the input space into an orthonormal subspace, the geometry of the generated subspace is visualized; (2) this paper first reduces both the time and space complexity of the EKM-based MKL; (3

Group-Based Active Learning of Classification Models.

Science.gov (United States)

Luo, Zhipeng; Hauskrecht, Milos

2017-05-01

Learning of classification models from real-world data often requires additional human expert effort to annotate the data. However, this process can be rather costly and finding ways of reducing the human annotation effort is critical for this task. The objective of this paper is to develop and study new ways of providing human feedback for efficient learning of classification models by labeling groups of examples. Briefly, unlike traditional active learning methods that seek feedback on individual examples, we develop a new group-based active learning framework that solicits label information on groups of multiple examples. In order to describe groups in a user-friendly way, conjunctive patterns are used to compactly represent groups. Our empirical study on 12 UCI data sets demonstrates the advantages and superiority of our approach over both classic instance-based active learning work, as well as existing group-based active-learning methods.

Mineralogy and Petrography of MIL 090001, a Highly Altered CV Chondrite from the Reduced Sub-Group

Science.gov (United States)

Keller, Lindsay P.

2011-01-01

MIL 090001 is a large (greater than 6 kg) CV chondrite from the reduced subgroup (CV(sub red)) that was recovered during the 2009-2010 ANSMET field season [1]. The CV(sub red) subgroup meteorites retain primitive characteristics and have escaped the Na and Fe meta-somatism that affected the oxidized (CV(sub ox)) subgroups. MIL 090001 is, however, reported to be altered [1], and thus a major objective of this study is to characterize its mineralogy and petrography and the extent of the alteration.

Resource Planning for Massive Number of Process Instances

Science.gov (United States)

Xu, Jiajie; Liu, Chengfei; Zhao, Xiaohui

Resource allocation has been recognised as an important topic for business process execution. In this paper, we focus on planning resources for a massive number of process instances to meet the process requirements and cater for rational utilisation of resources before execution. After a motivating example, we present a model for planning resources for process instances. Then we design a set of heuristic rules that take both optimised planning at build time and instance dependencies at run time into account. Based on these rules we propose two strategies, one is called holistic and the other is called batched, for resource planning. Both strategies target a lower cost, however, the holistic strategy can achieve an earlier deadline while the batched strategy aims at rational use of resources. We discuss how to find balance between them in the paper with a comprehensive experimental study on these two approaches.

Theoretical study of carbon dioxide adsorption and diffusion in MIL-127(Fe) metal organic framework

Science.gov (United States)

Pongsajanukul, Pavee; Parasuk, Vudhichai; Fritzsche, Siegfried; Assabumrungrat, Suttichai; Wongsakulphasatch, Suwimol; Bovornratanaraks, Thiti; Chokbunpiam, Tatiya

2017-07-01

The UFF force field is found to reproduce the adsorption isotherm of carbon dioxide in MIL-127(Fe) well. It has therefore been used to investigate the structure and self-diffusion of carbon dioxide molecules in the MIL which is a candidate for membrane or adsorption application. The structure of the adsorbed phase shows different regions of high concentration. The highest particle concentration was found in the central regions of the channels. The self-diffusion coefficient slightly increases with the loading for low concentration of guest molecules while for higher concentrations it decreases because of mutual hindrance of guest molecules.

Multiphysics Modeling and Simulations of Mil A46100 Armor-Grade Martensitic Steel Gas Metal Arc Welding Process

Science.gov (United States)

2013-05-23

further. Application of the Scheil additive rule to MIL A46100 yielded the CCT diagram displayed in Fig. 8. The diagram displayed in Fig. 8 is obtained...computational procedure used to construct the TTTand CCT diagrams could be used to predict the incubation time for austenite decomposition under an...of austenite into allotriomorphic ferrite is Fig. 8 MIL A46100 CCT diagram corresponding to the TTT dia- gram displayed in Figure 7(a): CCT curves and

Fabrication Parameters of Asymmetric Mixed Matrix Matrimid-MIL-53/PMHS Membrane for CO2/CH4 Separation

Directory of Open Access Journals (Sweden)

Fatereh Dorosti

2017-03-01

Full Text Available Asymmetrically mixed matrix Matrimid-MIL-53 membranes with silicone cover layer were fabricated. For better understanding of membrane fabrication process, three main parameters of fabrication, Matrimid concentration, silicone concentration and weight percentage of metal organic framework (MIL-53 particles, were optimized by an experimental design method. Cross-section SEM images were used to study the membrane structure and polymer-particles interface. Moreover, thermal resistance of the membranes and the existence of various bonds in them were investigated by FTIR and TGA analyses. The results showed that membranes had porous structure with finger-like morphology. At low and moderate percentages of particles, there were no non-selective voids observed at polymer-particles interface. The thermal resistance of membranes increased with the increase of MIL-53 weight percentage and the destruction temperature of polymer increased from 410°C to 450°C. The permeability tests results showed that the Matrimid (20% wt-MIL-53(15% wt/PMHS (10%wt membrane exhibited the highest level of CO2/CH4 selectivity (23.6. However, in the membrane with 30 wt% particles loading, selectivity decreased due to particles agglomeration and void formation. The experimental design results showed that the concentration of silicone in covering solution had significant effect. CO2 and CH4 permeability decreased and ideal selectivity of CO2/CH4 increased with silicone concentration enhancement. Although the Matrimid concentration had a little effect on CO2/CH4 ideal selectivity, its enhancement increased the selectivity of the gases. The optimization results showed the membrane with 17.8% of Matrimd polymer, 13.2% of silicone polymer and 15.5 wt% of MIL-53 particle displayed the highest selectivity and CO2 permeability.

Deposition of CdS nanoparticles on MIL-53(Fe) metal-organic framework with enhanced photocatalytic degradation of RhB under visible light irradiation

Science.gov (United States)

Hu, Longxing; Deng, Guihua; Lu, Wencong; Pang, Siwei; Hu, Xing

2017-07-01

A novel composite, CdS/MIL-53(Fe), was successfully fabricated via a facile solvothermal method and characterized with XRD, SEM, TEM, XPS, FT-IR and UV-vis DRS. The results showed that the fabrication was able to result in a good dispersion of CdS nanoparticles onto MIL-53(Fe). The photocatalytic activities of the as-synthesized composite were investigated through the degradation of Rhodamine B (RhB) in water under visible light irradiation. It was found that the composite prepared at the mass ratio of CdS to MIL-53(Fe) of 1.5:1 displayed the highest photocatalytic activity. An approximately 92.5% of photocatalytic degradation of RhB was achieved at 0.5 g/L of 1.5-CdS/MIL dosage, 10 mg/L of initial RhB concentration and 23 °C of reaction temperature under visible light irradiation. The RhB photocatalytic degradation followed well the first-order kinetics equation and the increased catalyst dosage and optimal initial RhB concentration were responsible for the enhanced photocatalytic degradation. Quenching tests revealed that the predominant free radicals in the CdS/MIL-(53)-RhBaq-visible light system was O2-rad ; nevertheless, h+ and rad OH also contributed to a certain degree. The enhanced photocatalytic performance was ascribed to the formation of heterojunction structure between CdS and MIL-53(Fe) which significantly suppressed the recombination of photogenerated electron-hole pairs. Moreover, the reusability of 1.5-CdS/MIL composite was also studied.

Synthesis of highly efficient α-Fe{sub 2}O{sub 3} catalysts for CO oxidation derived from MIL-100(Fe)

Energy Technology Data Exchange (ETDEWEB)

Cui, Lifeng; Zhao, Di; Yang, Yang [Environment and Low-Carbon Research Center, School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093 (China); Wang, Yuxin [Institute of Applied Biotechnology, Taizhou Vocation & Technical College, Taizhou, Zhejiang 318000 (China); Zhang, Xiaodong, E-mail: fatzhxd@126.com [Environment and Low-Carbon Research Center, School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093 (China)

2017-03-15

Mesoporous hollow α-Fe{sub 2}O{sub 3} bricks were synthesized via a hydrothermal method to create a precursor MIL-100(Fe) and a subsequent calcination process was applied to prepare the Fe{sub 2}O{sub 3} phase. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) results showed the morphology of hollow α-Fe{sub 2}O{sub 3} bricks which inherited from the MIL-100(Fe) template. The catalytic activities of hollow α-Fe{sub 2}O{sub 3} bricks for CO oxidation are studied in this work. Due to better low temperature reduction behavior, mesoporous hollow α-Fe{sub 2}O{sub 3} bricks obtained at calcination temperature of 430 °C displayed high catalytic activity and excellent stability with a complete CO conversion temperature (T{sub 100}) of 255 °C. - Graphical abstract: Synthesis of highly efficient α-Fe{sub 2}O{sub 3} catalysts for CO oxidation derived from MIL-100(Fe). - Highlights: • α-Fe{sub 2}O{sub 3} is prepared by the thermolysis of a MIL-100(Fe) template. • The morphology of hollow α-Fe{sub 2}O{sub 3} bricks is inherited from MIL-100(Fe) template. • α-Fe{sub 2}O{sub 3} obtained at calcined temperature of 430 °C displays high activity • Enhanced activity is attributed to crystal plane and reduction behavior.

High performance liquid chromatography of substituted aromatics with the metal-organic framework MIL-100(Fe): Mechanism analysis and model-based prediction.

Science.gov (United States)

Qin, Weiwei; Silvestre, Martin Eduardo; Li, Yongli; Franzreb, Matthias

2016-02-05

Metal-organic framework (MOF) MIL-100(Fe) with well-defined thickness was homogenously coated onto the outer surface of magnetic microparticles via a liquid-phase epitaxy method. The as-synthesized MIL-100(Fe) was used as stationary phase for high-performance liquid chromatography (HPLC) and separations of two groups of mixed aromatic hydrocarbons (toluene, styrene and p-xylene; acetanilide, 2-nirtoaniline and 1-naphthylamine) using methanol/water as mobile phase were performed to evaluate its performance. Increasing water content of the mobile phase composition can greatly improve the separations on the expense of a longer elution time. Stepwise elution significantly shortens the elution time of acetanilide, 2-nirtoaniline and 1-naphthylamine mixtures, while still achieving a baseline separation. Combining the experimental results and in-depth modeling using a recently developed chromatographic software (ChromX), adsorption equilibrium parameters, including the affinities and maximum capacities, for each analyte toward the MIL-100(Fe) are obtained. In addition, the pore diffusivity of aromatic hydrocarbons within MIL-100(Fe) was determined to be 5×10(-12)m(2)s(-1). While the affinities of MIL-100(Fe) toward the analyte molecules differs much, the maximum capacities of the analytes are in a narrow range with q*MOFmax,toluene=3.55molL(-1), q*MOFmax,styrene or p-xylene=3.53molL(-1), and q*MOFmax,anilines=3.12molL(-1) corresponding to approximately 842 toluene and 838 styrene or p-xylene, and 740 aniline molecules per MIL-100(Fe) unit cell, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Efficient Multiplicative Updates for Support Vector Machines

DEFF Research Database (Denmark)

Potluru, Vamsi K.; Plis, Sergie N; Mørup, Morten

2009-01-01

(NMF) problem. This allows us to derive a novel multiplicative algorithm for solving hard and soft margin SVM. The algorithm follows as a natural extension of the updates for NMF and semi-NMF. No additional parameter setting, such as choosing learning rate, is required. Exploiting the connection......The dual formulation of the support vector machine (SVM) objective function is an instance of a nonnegative quadratic programming problem. We reformulate the SVM objective function as a matrix factorization problem which establishes a connection with the regularized nonnegative matrix factorization...... between SVM and NMF formulation, we show how NMF algorithms can be applied to the SVM problem. Multiplicative updates that we derive for SVM problem also represent novel updates for semi-NMF. Further this unified view yields algorithmic insights in both directions: we demonstrate that the Kernel Adatron...

Edificio de viviendas. Ca´Granda, Milán

Directory of Open Access Journals (Sweden)

Gandolfi, Vittorio

1959-04-01

Full Text Available Con el nombre de "Ca'Granda" se ha querido designar el distrito, capaz de 6.000 habitantes, que el Ayuntamiento de Milán está construyendo, y en parte ha construido ya, en la zona detrás de las calles Fulvio Testi y Ospedale Maggiore; es decir, en el sector norte de la ciudad correspondiente a la dirección de mayor impulso del desarrollo urbanístico de lo habitado.

Learning of Alignment Rules between Concept Hierarchies

Science.gov (United States)

Ichise, Ryutaro; Takeda, Hideaki; Honiden, Shinichi

With the rapid advances of information technology, we are acquiring much information than ever before. As a result, we need tools for organizing this data. Concept hierarchies such as ontologies and information categorizations are powerful and convenient methods for accomplishing this goal, which have gained wide spread acceptance. Although each concept hierarchy is useful, it is difficult to employ multiple concept hierarchies at the same time because it is hard to align their conceptual structures. This paper proposes a rule learning method that inputs information from a source concept hierarchy and finds suitable location for them in a target hierarchy. The key idea is to find the most similar categories in each hierarchy, where similarity is measured by the κ(kappa) statistic that counts instances belonging to both categories. In order to evaluate our method, we conducted experiments using two internet directories: Yahoo! and LYCOS. We map information instances from the source directory into the target directory, and show that our learned rules agree with a human-generated assignment 76% of the time.

Synthesis of a hybrid MIL-101(Cr)/ZTC composite for hydrogen storage applications

CSIR Research Space (South Africa)

Musyoka, Nicholas M

2016-06-01

Full Text Available Metal–organic frameworks (MOFs) hybrid composites have recently attracted considerable attention in hydrogen storage applications. In this study a hybrid composite of zeolite templated carbon (ZTC) and Cr-based MOF (MIL-101) was synthesised...

Noble metals can have different effects on photocatalysis over metal-organic frameworks (MOFs): a case study on M/NH₂-MIL-125(Ti) (M=Pt and Au).

Science.gov (United States)

Sun, Dengrong; Liu, Wenjun; Fu, Yanghe; Fang, Zhenxing; Sun, Fangxiang; Fu, Xianzhi; Zhang, Yongfan; Li, Zhaohui

2014-04-14

M-doped NH2-MIL-125(Ti) (M=Pt and Au) were prepared by using the wetness impregnation method followed by a treatment with H2 flow. The resultant samples were characterized by powder X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), X-ray absorption fine structure (XAFS) analyses, N2-sorption BET surface area, and UV/Vis diffuse reflectance spectroscopy (DRS). The photocatalytic reaction carried out in saturated CO2 with triethanolamine (TEOA) as sacrificial agent under visible-light irradiations showed that the noble metal-doping on NH2-MIL-125(Ti) promoted the photocatalytic hydrogen evolution. Unlike that over pure NH2-MIL-125(Ti), in which only formate was produced, both hydrogen and formate were formed over Pt- and Au-loaded NH2-MIL-125(Ti). However, Pt and Au have different effects on the photocatalytic performance for formate production. Compared with pure NH2-MIL-125(Ti), Pt/NH2-MIL-125(Ti) showed an enhanced activity for photocatalytic formate formation, whereas Au has a negative effect on this reaction. To elucidate the origin of the different photocatalytic performance, electron spin resonance (ESR) analyses and density functional theory (DFT) calculations were carried out over M/NH2-MIL-125(Ti).The photocatalytic mechanisms over M/NH2-MIL-125(Ti) (M=Pt and Au) were proposed. For the first time, the hydrogen spillover from the noble metal Pt to the framework of NH2-MIL-125(Ti) and its promoting effect on the photocatalytic CO2 reduction is revealed. The elucidation of the mechanism on the photocatalysis over M/NH2-MIL-125(Ti) can provide some guidance in the development of new photocatalysts based on MOF materials. This study also demonstrates the potential of using noble metal-doped MOFs in photocatalytic reactions involving hydrogen as a reactant, like hydrogenation reactions. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Practical Usage of Multiple-Choice Questions as Part of Learning and Self-Evaluation

Directory of Open Access Journals (Sweden)

Paula Kangasniemi

2016-12-01

Full Text Available The poster describes how the multiple-choice questions could be a part of learning, not only assessing. We often think of the role of questions only in order to test the student's skills. We have tested how questions could be a part of learning in our web-based course of information retrieval in Lapland University. In web-based learning there is a need for high-quality mediators. Mediators are learning promoters which trigger, support, and amplify learning. Mediators can be human mediators or tool mediators. The tool mediators are for example; tests, tutorials, guides and diaries. The multiple-choice questions can also be learning promoters which select, interpret and amplify objects for learning. What do you have to take into account when you are preparing multiple-choice questions as mediators? First you have to prioritize teaching objectives: what must be known and what should be known. According to our experience with contact learning, you can assess what the things are that students have problems with and need more guidance on. The most important addition to the questions is feedback during practice. The questions’ answers (wrong or right are not important. The feedback on the answers are important to guide students on how to search. The questions promote students’ self-regulation and self-evaluation. Feedback can be verbal, a screenshot or a video. We have added a verbal feedback for every question and also some screenshots and eight videos in our web-based course.

Active Learning by Querying Informative and Representative Examples.

Science.gov (United States)

Huang, Sheng-Jun; Jin, Rong; Zhou, Zhi-Hua

2014-10-01

Active learning reduces the labeling cost by iteratively selecting the most valuable data to query their labels. It has attracted a lot of interests given the abundance of unlabeled data and the high cost of labeling. Most active learning approaches select either informative or representative unlabeled instances to query their labels, which could significantly limit their performance. Although several active learning algorithms were proposed to combine the two query selection criteria, they are usually ad hoc in finding unlabeled instances that are both informative and representative. We address this limitation by developing a principled approach, termed QUIRE, based on the min-max view of active learning. The proposed approach provides a systematic way for measuring and combining the informativeness and representativeness of an unlabeled instance. Further, by incorporating the correlation among labels, we extend the QUIRE approach to multi-label learning by actively querying instance-label pairs. Extensive experimental results show that the proposed QUIRE approach outperforms several state-of-the-art active learning approaches in both single-label and multi-label learning.

Amine-functionalized MIL-53(Al)-coated stainless steel fiber for efficient solid-phase microextraction of synthetic musks and organochlorine pesticides in water samples.

Science.gov (United States)

Xie, Lijun; Liu, Shuqin; Han, Zhubing; Jiang, Ruifen; Zhu, Fang; Xu, Weiqin; Su, Chengyong; Ouyang, Gangfeng

2017-09-01

The fiber coating is the key part of the solid-phase microextraction (SPME) technique, and it determines the sensitivity, selectivity, and repeatability of the analytical method. In this work, amine (NH 2 )-functionalized material of Institute Lavoisier (MIL)-53(Al) nanoparticles were successfully synthesized, characterized, and applied as the SPME fiber coating for efficient sample pretreatment owing to their unique structures and excellent adsorption properties. Under optimized conditions, the NH 2 -MIL-53(Al)-coated fiber showed good precision, low limits of detection (LODs) [0.025-0.83 ng L -1 for synthetic musks (SMs) and 0.051-0.97 ng L -1 for organochlorine pesticides (OCPs)], and good linearity. Experimental results showed that the NH 2 -MIL-53(Al) SPME coating was solvent resistant and thermostable. In addition, the extraction efficiencies of the NH 2 -MIL-53(Al) coating for SMs and OCPs were higher than those of commercially available SPME fiber coatings such as polydimethylsiloxane, polydimethylsiloxane-divinylbenzene, and polyacrylate. The reasons may be that the analytes are adsorbed on NH 2 -MIL-53(Al) primarily through π-π interactions, electron donor-electron acceptor interactions, and hydrogen bonds between the analytes and organic linkers of the material. Direct immersion (DI) SPME-gas chromatography-mass spectrometry methods based on NH 2 -MIL-53(Al) were successfully applied for the analysis of tap and river water samples. The recoveries were 80.3-115% for SMs and 77.4-117% for OCPs. These results indicate that the NH 2 -MIL-53(Al) coating may be a promising alternative to SPME coatings for the enrichment of SMs and OCPs.

Diverse Expected Gradient Active Learning for Relative Attributes.

Science.gov (United States)

You, Xinge; Wang, Ruxin; Tao, Dacheng

2014-06-02

The use of relative attributes for semantic understanding of images and videos is a promising way to improve communication between humans and machines. However, it is extremely labor- and time-consuming to define multiple attributes for each instance in large amount of data. One option is to incorporate active learning, so that the informative samples can be actively discovered and then labeled. However, most existing active-learning methods select samples one at a time (serial mode), and may therefore lose efficiency when learning multiple attributes. In this paper, we propose a batch-mode active-learning method, called Diverse Expected Gradient Active Learning (DEGAL). This method integrates an informativeness analysis and a diversity analysis to form a diverse batch of queries. Specifically, the informativeness analysis employs the expected pairwise gradient length as a measure of informativeness, while the diversity analysis forces a constraint on the proposed diverse gradient angle. Since simultaneous optimization of these two parts is intractable, we utilize a two-step procedure to obtain the diverse batch of queries. A heuristic method is also introduced to suppress imbalanced multi-class distributions. Empirical evaluations of three different databases demonstrate the effectiveness and efficiency of the proposed approach.

Sustainable Catalysis: Rational Pd Loading on MIL-101Cr-NH2 for More Efficient and Recyclable Suzuki–Miyaura Reactions

Science.gov (United States)

Pascanu, Vlad; Yao, Qingxia; Bermejo Gómez, Antonio; Gustafsson, Mikaela; Yun, Yifeng; Wan, Wei; Samain, Louise; Zou, Xiaodong; Martín-Matute, Belén

2013-01-01

Palladium nanoparticles have been immobilized into an amino-functionalized metal–organic framework (MOF), MIL-101Cr-NH2, to form Pd@MIL-101Cr-NH2. Four materials with different loadings of palladium have been prepared (denoted as 4-, 8-, 12-, and 16 wt %Pd@MIL-101Cr-NH2). The effects of catalyst loading and the size and distribution of the Pd nanoparticles on the catalytic performance have been studied. The catalysts were characterized by using scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier-transform infrared (FTIR) spectroscopy, powder X-ray diffraction (PXRD), N2-sorption isotherms, elemental analysis, and thermogravimetric analysis (TGA). To better characterize the palladium nanoparticles and their distribution in MIL-101Cr-NH2, electron tomography was employed to reconstruct the 3D volume of 8 wt %Pd@MIL-101Cr-NH2 particles. The pair distribution functions (PDFs) of the samples were extracted from total scattering experiments using high-energy X-rays (60 keV). The catalytic activity of the four MOF materials with different loadings of palladium nanoparticles was studied in the Suzuki–Miyaura cross-coupling reaction. The best catalytic performance was obtained with the MOF that contained 8 wt % palladium nanoparticles. The metallic palladium nanoparticles were homogeneously distributed, with an average size of 2.6 nm. Excellent yields were obtained for a wide scope of substrates under remarkably mild conditions (water, aerobic conditions, room temperature, catalyst loading as low as 0.15 mol %). The material can be recycled at least 10 times without alteration of its catalytic properties. PMID:24265270

Metal organic framework MIL-101 for radioiodine capture and storage

Science.gov (United States)

Assaad, Thaer; Assfour, Bassem

2017-09-01

we report on the use of metal organic frameworks(MOFs) for radioiodine recovery and storage. One MOF (namely MIL-101) was prepared and investigated in detail to demonstrate the iodine removal efficiency and capacity of MOFs. The typical sorption kinetics and uptake isotherms were measured using radioactive iodine (123 I) for the first time. Our measurements indicate that MOFs can capture and store radioiodine in very high efficiency and fast kinetics.

Enhanced catalytic activity over MIL-100(Fe) loaded ceria catalysts for the selective catalytic reduction of NO{sub x} with NH{sub 3} at low temperature

Energy Technology Data Exchange (ETDEWEB)

Wang, Peng [School of Environmental Science and Technology, Dalian University of Technology, Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education, China), Dalian 116024 (China); Sun, Hong [School of Environmental & Chemical Engineering, Dalian Jiaotong University, Dalian 116028 (China); Quan, Xie, E-mail: quanxie@dlut.edu.cn [School of Environmental Science and Technology, Dalian University of Technology, Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education, China), Dalian 116024 (China); Chen, Shuo [School of Environmental Science and Technology, Dalian University of Technology, Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education, China), Dalian 116024 (China)

2016-01-15

Highlights: • Nano-ceria was successfully encapsulated into MIL-100(Fe) for the SCR of NO{sub x}. • The incorporated ceria in MIL-100(Fe) showed high content of chemisorbed oxygen. • The added ceria into MIL-100(Fe) improved the formation of adsorbed NO{sub 2} species. • The addition of ceria into MIL-100(Fe) enhanced SCR activity at low temperature. - Abstract: The development of catalysts for selective catalytic reduction (SCR) reactions that are highly active at low temperatures and show good resistance to SO{sub 2} and H{sub 2}O is still a challenge. In this study, we have designed and developed a high-performance SCR catalyst based on nano-sized ceria encapsulated inside the pores of MIL-100(Fe) that combines excellent catalytic power with a metal organic framework architecture synthesized by the impregnation method (IM). Transmission electron microscopy (TEM) revealed the encapsulation of ceria in the cavities of MIL-100(Fe). The prepared IM-CeO{sub 2}/MIL-100(Fe) catalyst shows improved catalytic activity both at low temperatures and throughout a wide temperature window. The temperature window for 90% NO{sub x} conversion ranges from 196 to 300 °C. X-ray photoelectron spectroscopy (XPS) and in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFT) analysis indicated that the nano-sized ceria encapsulated inside MIL-100(Fe) promotes the production of chemisorbed oxygen on the catalyst surface, which greatly enhances the formation of the NO{sub 2} species responsible for fast SCR reactions.

Solving Multiple Isolated, Interleaved, and Blended Tasks through Modular Neuroevolution.

Science.gov (United States)

Schrum, Jacob; Miikkulainen, Risto

2016-01-01

Many challenging sequential decision-making problems require agents to master multiple tasks. For instance, game agents may need to gather resources, attack opponents, and defend against attacks. Learning algorithms can thus benefit from having separate policies for these tasks, and from knowing when each one is appropriate. How well this approach works depends on how tightly coupled the tasks are. Three cases are identified: Isolated tasks have distinct semantics and do not interact, interleaved tasks have distinct semantics but do interact, and blended tasks have regions where semantics from multiple tasks overlap. Learning across multiple tasks is studied in this article with Modular Multiobjective NEAT, a neuroevolution framework applied to three variants of the challenging Ms. Pac-Man video game. In the standard blended version of the game, a surprising, highly effective machine-discovered task division surpasses human-specified divisions, achieving the best scores to date in this game. In isolated and interleaved versions of the game, human-specified task divisions are also successful, though the best scores are surprisingly still achieved by machine discovery. Modular neuroevolution is thus shown to be capable of finding useful, unexpected task divisions better than those apparent to a human designer.

Instance selection in digital soil mapping: a study case in Rio Grande do Sul, Brazil

Directory of Open Access Journals (Sweden)

Elvio Giasson

2015-09-01

Full Text Available A critical issue in digital soil mapping (DSM is the selection of data sampling method for model training. One emerging approach applies instance selection to reduce the size of the dataset by drawing only relevant samples in order to obtain a representative subset that is still large enough to preserve relevant information, but small enough to be easily handled by learning algorithms. Although there are suggestions to distribute data sampling as a function of the soil map unit (MU boundaries location, there are still contradictions among research recommendations for locating samples either closer or more distant from soil MU boundaries. A study was conducted to evaluate instance selection methods based on spatially-explicit data collection using location in relation to soil MU boundaries as the main criterion. Decision tree analysis was performed for modeling digital soil class mapping using two different sampling schemes: a selecting sampling points located outside buffers near soil MU boundaries, and b selecting sampling points located within buffers near soil MU boundaries. Data was prepared for generating classification trees to include only data points located within or outside buffers with widths of 60, 120, 240, 360, 480, and 600m near MU boundaries. Instance selection methods using both spatial selection of methods was effective for reduced size of the dataset used for calibrating classification tree models, but failed to provide advantages to digital soil mapping because of potential reduction in the accuracy of classification tree models.

Ni foam-immobilized MIL-101(Cr) nanocrystals toward system integration for hydrogen storage

CSIR Research Space (South Africa)

Ren, Jianwei

2015-10-01

Full Text Available Metal–organic framework (MOF) materials are only obtained as loose powders with low packing density and thermal conductivity. To enable the developed MOF powdered materials to be utilized in a hydrogen storage system, in this study, MIL-101...

B-1 Aircraft Main Hydraulic Pump Tests With MIL-H-87257 Hydraulic Fluid

National Research Council Canada - National Science Library

Sharma, Shashi

1998-01-01

In an effort to convert the B-1 aircraft from MIL-H-5606 to M1-H-87257, the Air Force sponsored a study conducted by Rockwell International from April 1991 through June 1992, under contract F34601-89-C-0401...

Ship-in-a-bottle CMPO in MIL-101(Cr) for selective uranium recovery from aqueous streams through adsorption

Energy Technology Data Exchange (ETDEWEB)

De Decker, Jeroen [Department of Inorganic and Physical Chemistry, Center for Ordered Materials, Organometallics, and Catalysis (COMOC), Ghent University, Krijgslaan 281-S3, 9000 Ghent (Belgium); Folens, Karel [Laboratory of Analytical Chemistry and Applied Ecochemistry, Ghent University, Coupure Links 653, 9000 Ghent (Belgium); De Clercq, Jeriffa [Department of Materials, Textiles, and Chemical Engineering, Industrial Catalysis and Adsorption Technology (INCAT), Ghent University, Valentin, Vaerwyckweg 1, 9000 Ghent (Belgium); Meledina, Maria; Van Tendeloo, Gustaaf [EMAT, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium); Du Laing, Gijs [Laboratory of Analytical Chemistry and Applied Ecochemistry, Ghent University, Coupure Links 653, 9000 Ghent (Belgium); Van Der Voort, Pascal, E-mail: pascal.vandervoort@ugent.be [Department of Inorganic and Physical Chemistry, Center for Ordered Materials, Organometallics, and Catalysis (COMOC), Ghent University, Krijgslaan 281-S3, 9000 Ghent (Belgium)

2017-08-05

Highlights: • Highly stable metal-organic framework, MIL-101(Cr), for uses in aqueous, acidic adsorption. • Uranium recovery from low concentration acidic solutions. • One-step ship-around-the-bottle synthetic approach to incorporate CMPO in MIL-101(Cr). • Highly selective U(VI) adsorbent in competition with a high variety of metals, incl. rare earths and transition metals. • Regenerable and reusable adsorbent via 0.1 M nitric acid stripping. - Abstract: Mesoporous MIL-101(Cr) is used as host for a ship-in-a-bottle type adsorbent for selective U(VI) recovery from aqueous environments. The acid-resistant cage-type MOF is built in-situ around N,N-Diisobutyl-2-(octylphenylphosphoryl)acetamide (CMPO), a sterically demanding ligand with high U(VI) affinity. This one-step procedure yields an adsorbent which is an ideal compromise between homogeneous and heterogeneous systems, where the ligand can act freely within the pores of MIL-101, without leaching, while the adsorbent is easy separable and reusable. The adsorbent was characterized by XRD, FTIR spectroscopy, nitrogen adsorption, XRF, ADF-STEM and EDX, to confirm and quantify the successful encapsulation of the CMPO in MIL-101, and the preservation of the host. Adsorption experiments with a central focus on U(VI) recovery were performed. Very high selectivity for U(VI) was observed, while competitive metal adsorption (rare earths, transition metals...) was almost negligible. The adsorption capacity was calculated at 5.32 mg U/g (pH 3) and 27.99 mg U/g (pH 4), by fitting equilibrium data to the Langmuir model. Adsorption kinetics correlated to the pseudo-second-order model, where more than 95% of maximum uptake is achieved within 375 min. The adsorbed U(VI) is easily recovered by desorption in 0.1 M HNO{sub 3}. Three adsorption/desorption cycles were performed.

Ship-in-a-bottle CMPO in MIL-101(Cr) for selective uranium recovery from aqueous streams through adsorption

International Nuclear Information System (INIS)

De Decker, Jeroen; Folens, Karel; De Clercq, Jeriffa; Meledina, Maria; Van Tendeloo, Gustaaf; Du Laing, Gijs; Van Der Voort, Pascal

2017-01-01

Highlights: • Highly stable metal-organic framework, MIL-101(Cr), for uses in aqueous, acidic adsorption. • Uranium recovery from low concentration acidic solutions. • One-step ship-around-the-bottle synthetic approach to incorporate CMPO in MIL-101(Cr). • Highly selective U(VI) adsorbent in competition with a high variety of metals, incl. rare earths and transition metals. • Regenerable and reusable adsorbent via 0.1 M nitric acid stripping. - Abstract: Mesoporous MIL-101(Cr) is used as host for a ship-in-a-bottle type adsorbent for selective U(VI) recovery from aqueous environments. The acid-resistant cage-type MOF is built in-situ around N,N-Diisobutyl-2-(octylphenylphosphoryl)acetamide (CMPO), a sterically demanding ligand with high U(VI) affinity. This one-step procedure yields an adsorbent which is an ideal compromise between homogeneous and heterogeneous systems, where the ligand can act freely within the pores of MIL-101, without leaching, while the adsorbent is easy separable and reusable. The adsorbent was characterized by XRD, FTIR spectroscopy, nitrogen adsorption, XRF, ADF-STEM and EDX, to confirm and quantify the successful encapsulation of the CMPO in MIL-101, and the preservation of the host. Adsorption experiments with a central focus on U(VI) recovery were performed. Very high selectivity for U(VI) was observed, while competitive metal adsorption (rare earths, transition metals...) was almost negligible. The adsorption capacity was calculated at 5.32 mg U/g (pH 3) and 27.99 mg U/g (pH 4), by fitting equilibrium data to the Langmuir model. Adsorption kinetics correlated to the pseudo-second-order model, where more than 95% of maximum uptake is achieved within 375 min. The adsorbed U(VI) is easily recovered by desorption in 0.1 M HNO 3 . Three adsorption/desorption cycles were performed.

Revisiting the Aluminum Trimesate-based MOF (MIL-96): from Structure Determination to the Processing of Mixed Matrix Membranes for CO2 Capture.

KAUST Repository

Benzaqui, Marvin; S. Pillai, Renjith; Sabetghadam, Anahid; Benoit, Virginie; Normand, Pé rine; Marrot, Jerome; Menguy, Nicolas; Montero, David; Shepard, William; Tissot, Antoine; Martineau-Corcos, Charlotte; Sicard, Clé mence; Mihaylov, Mihail; Carn, Florent; Beurroeis, Isabelle; Llewellyn, Philip L.; De Weireld, Guy; Hadjiivanov, Konstantin; Gascon, Jorge; Kapteijn, Freek; Maurin, Guillaume; Steunou, Nathalie; Serre, Christian

2017-01-01

A microporous Al trimesate-based metal-organic framework (MOF), denoted MIL-96-(Al), was selected as a porous hybrid filler for the processing of mixed matrix membranes (MMMs) for CO2/N-2 postcombustion separation. First, the structural model of MIL-96-(Al) initially reported was revisited using a combination of synchrotron-based single-crystal X-ray diffraction, solid-state nuclear magnetic resonance spectroscopy, and density functional theory (DFT) calculations. In a second step, pure MIL-96-(Al) crystals differing by their size and aspect ratio, including anisotropic hexagonal platelets and nanoparticles of about 70 nm in diameter, were prepared. Then, a combination of in situ IR spectroscopy, single-gas, and CO2/N-2 coadsorption experiments, calorimetry, and molecular simulations revealed that MIL-96-(Al) nanoparticles show a relatively high CO2 affinity over N-2 owing to strong interactions between CO2 molecules and several adsorption sites such as Al3+ Lewis centers, coordinated water, and hydroxyl groups. Finally, the high compatibility between MIL-96-(Al) nanoparticles and the 6FDA-DAM polymer allowed the processing of homogeneous and defect-free MMMs with a high MOF loading (up to 25 wt %) that outperform pure polymer membranes for CO2/N-2 separation.

Revisiting the Aluminum Trimesate-based MOF (MIL-96): from Structure Determination to the Processing of Mixed Matrix Membranes for CO2 Capture.

KAUST Repository

Benzaqui, Marvin

2017-11-08

A microporous Al trimesate-based metal-organic framework (MOF), denoted MIL-96-(Al), was selected as a porous hybrid filler for the processing of mixed matrix membranes (MMMs) for CO2/N-2 postcombustion separation. First, the structural model of MIL-96-(Al) initially reported was revisited using a combination of synchrotron-based single-crystal X-ray diffraction, solid-state nuclear magnetic resonance spectroscopy, and density functional theory (DFT) calculations. In a second step, pure MIL-96-(Al) crystals differing by their size and aspect ratio, including anisotropic hexagonal platelets and nanoparticles of about 70 nm in diameter, were prepared. Then, a combination of in situ IR spectroscopy, single-gas, and CO2/N-2 coadsorption experiments, calorimetry, and molecular simulations revealed that MIL-96-(Al) nanoparticles show a relatively high CO2 affinity over N-2 owing to strong interactions between CO2 molecules and several adsorption sites such as Al3+ Lewis centers, coordinated water, and hydroxyl groups. Finally, the high compatibility between MIL-96-(Al) nanoparticles and the 6FDA-DAM polymer allowed the processing of homogeneous and defect-free MMMs with a high MOF loading (up to 25 wt %) that outperform pure polymer membranes for CO2/N-2 separation.

ML-MG: Multi-label Learning with Missing Labels Using a Mixed Graph

KAUST Repository

Wu, Baoyuan

2015-12-07

This work focuses on the problem of multi-label learning with missing labels (MLML), which aims to label each test instance with multiple class labels given training instances that have an incomplete/partial set of these labels (i.e. some of their labels are missing). To handle missing labels, we propose a unified model of label dependencies by constructing a mixed graph, which jointly incorporates (i) instance-level similarity and class co-occurrence as undirected edges and (ii) semantic label hierarchy as directed edges. Unlike most MLML methods, We formulate this learning problem transductively as a convex quadratic matrix optimization problem that encourages training label consistency and encodes both types of label dependencies (i.e. undirected and directed edges) using quadratic terms and hard linear constraints. The alternating direction method of multipliers (ADMM) can be used to exactly and efficiently solve this problem. To evaluate our proposed method, we consider two popular applications (image and video annotation), where the label hierarchy can be derived from Wordnet. Experimental results show that our method achieves a significant improvement over state-of-the-art methods in performance and robustness to missing labels.

Ratiometric Fluorescence Sensing and Real-Time Detection of Water in Organic Solvents with One-Pot Synthesis of Ru@MIL-101(Al)-NH2.

Science.gov (United States)

Yin, Hua-Qing; Yang, Ji-Chun; Yin, Xue-Bo

2017-12-19

Ratiometric fluorescence detection attracts much attention because of its decreased environmental influence and easy-to-differentiate color and intensity change. Herein, a guest-encapsulation metal-organic framework (MOF), Ru@MIL-NH 2 , is prepared with 2-aminoterephthalic acid, AlCl 3 , and Ru(bpy) 3 2+ by a simple one-pot method for ratiometric fluorescence sensing of water in organic solvents. The rational selection of the excitation wavelength provides dual emission at 465 and 615 nm from Ru@MIL-NH 2 under a single excitation of 300 nm. High sensitivity, low detection limit (0.02% v/v), wide response range (0-100%), and fast response (less than 1 min) are obtained for ratiometric fluorescence sensing of water under single excitation with Ru@MIL-NH 2 as the probe. Moreover, the result of water content is independent of the concentration of Ru@MIL-NH 2 as the merit of ratiometric fluorescence detection. The response mechanism reveals that the protonation of the nitrogen atom of the MIL-NH 2 , the π-conjugation system, and the stable fluorescence of Ru(bpy) 3 2+ achieve the ratiometric fluorescence. The analysis of real spirit samples confirms the proposed method. A test strip is prepared with Ru@MIL-NH 2 for convenient use. We believe that such turn-on ratiometric host-guest MOFs and the rational selection of excitation wavelength will offer guidance for ratiometric fluorescence detection with wide applications.

Connecting Multiple Intelligences through Open and Distance Learning: Going towards a Collective Intelligence?

Science.gov (United States)

Medeiros Vieira, Leandro Mauricio; Ferasso, Marcos; Schröeder, Christine da Silva

2014-01-01

This theoretical essay is a learning approach reflexion on Howard Gardner's Theory of Multiple Intelligences and the possibilities provided by the education model known as open and distance learning. Open and distance learning can revolutionize traditional pedagogical practice, meeting the needs of those who have different forms of cognitive…

Dye-sensitized MIL-101 metal organic frameworks loaded with Ni/NiOx nanoparticles for efficient visible-light-driven hydrogen generation

Directory of Open Access Journals (Sweden)

Xin-Ling Liu

2015-10-01

Full Text Available The Ni/NiOx particles were in situ photodeposited on MIL-101 metal organic frameworks as catalysts for boosting H2 generation from Erythrosin B dye sensitization under visible-light irradiation. The highest H2 production rate of 125 μmol h−1 was achieved from the system containing 5 wt. % Ni-loaded MIL-101 (20 mg and 30 mg Erythrosin B dye. Moreover, the Ni/NiOx catalysts show excellent stability for long-term photocatalytic reaction. The enhancement on H2 generation is attributed to the efficient charge transfer from photoexcited dye to the Ni catalyst via MIL-101. Our results demonstrate that the economical Ni/NiOx particles are durable and active catalysts for photocatalytic H2 generation.

An Intrinsic Value System for Developing Multiple Invariant Representations with Incremental Slowness Learning

Directory of Open Access Journals (Sweden)

Matthew David Luciw

2013-05-01

Full Text Available Curiosity Driven Modular Incremental Slow Feature Analysis (CD-MISFA;~cite{cdmisfa} is a recently introduced model of intrinsically-motivated invariance learning, which shows how curiosity enables the orderly formation of multiple stable sensory representations, through which the agent can simplify its complex sensory input. Here, we first discuss the computational properties of the CD-MISFA model itself, followed by a discussion of neurophysiological analogs fulfilling similar functional roles. CD-MISFA combines 1. unsupervised representation learning through the slowness principle, 2. generation of an intrinsic reward signal through the learning progress of the developing features, and 3. balancing of exploration and exploitation in order to maximize learning progress and quickly learn multiple feature sets for perceptual simplification. Experimental results on synthetic observations and on the iCub robot show that the intrinsic value system is an essential component to representation learning, further, the model explores such that the representations are typically learned in order from least to most costly, as predicted by the theory of Artificial Curiosity.

MIL-STD-2411-1 Change 3. Notice Impacts to NAVAIR

Science.gov (United States)

2010-07-30

Macedonia ZX Macais Nguema Biyogo MA Madagascar VD Madeira Islands (PO) MI Malawi MY Malaysia MV Maldives ML Mali MT Malta IM Isle of Man (UK) MIL...and Niger) PON Pointe Noire 1948 (Congo) POS Porto Santo 1936 (Porto Santo, Madeira Islands) HIT Prov. S. Chilean (S. Chile, 53 S.) PRPM Prov. S...Asia (Southeast Asia, Singapore) POS SE Base (Porte Santo) (Porto Santo & Madeira Islands) GRA SW Base (Faial, Graciosa, Pico, Sao Jorge, and

Magnetic solid phase extraction of typical polycyclic aromatic hydrocarbons from environmental water samples with metal organic framework MIL-101 (Cr) modified zero valent iron nano-particles.

Science.gov (United States)

Zhou, Qingxiang; Lei, Man; Wu, Yalin; Yuan, Yongyong

2017-03-03

Metal-organic framework material has been paid more attention because of its good physical and chemical properties. Nanoscale zero valent iron is also in the center of concern recently. Combination of their merits will give impressive results. Present study firstly synthesized a new magnetic nanomaterial nano-scale zero valent iron-functionalized metal-organic framworks MIL-101 (Fe@MIL-101) by co-precipitation method. The morphology and structure of the as-prepared Fe@MIL-101 were characterized by transmission electron microscopy and X-ray diffraction, etc. The experimental results showed that Fe@MIL-101 earned good adsorption ability to polycyclic aromatic hydrocarbons. The limits of detection of developed magnetic solid phase extraction were all below 0.064μgL -1 and precision can be expressed as relative standard deviation (RSD, %) and which was better than 4.4% (n=6). The real water analysis indicated that the spiked recoveries were satisfied, and Fe@MIL-101 earned excellent reusability. All these demonstrated that Fe@MIL-101 exhibited excellent adsorption capability to polycyclic aromatic hydrocarbons and would be a good adsorbent for development of new monitoring methods for environmental pollutants. Copyright © 2017 Elsevier B.V. All rights reserved.

Studying different tasks of implicit learning across multiple test sessions conducted on the web

Directory of Open Access Journals (Sweden)

Werner eSævland

2016-06-01

Full Text Available Implicit learning is usually studied through individual performance on a single task, with the most common tasks being Serial Reaction Time task (SRT; Nissen and Bullemer, 1987, Dynamic System Control task (DSC; (Berry and Broadbent, 1984 and artificial Grammar Learning task (AGL; (Reber, 1967. Few attempts have been made to compare performance across different implicit learning tasks within the same experiment. The current experiment was designed study the relationship between performance on the DSC Sugar factory task (Berry and Broadbent, 1984 and the Alternating Serial Reaction Time task (ASRT; (Howard and Howard, 1997. We also addressed another limitation to traditional implicit learning experiments, namely that implicit learning is usually studied in laboratory settings over a restricted time span lasting for less than an hour (Berry and Broadbent, 1984; Nissen and Bullemer, 1987; Reber, 1967. In everyday situations, implicit learning is assumed to involve a gradual accumulation of knowledge across several learning episodes over a larger time span (Norman and Price, 2012. One way to increase the ecological validity of implicit learning experiments could be to present the learning material repeatedly across shorter experimental sessions (Howard and Howard, 1997; Cleeremans and McClelland, 1991. This can most easily be done by using a web-based setup that participants can access from home. We therefore created an online web-based system for measuring implicit learning that could be administered in either single or multiple sessions. Participants (n = 66 were assigned to either a single-session or a multi-session condition. Learning and the degree of conscious awareness of the learned regularities was compared across condition (single vs. multiple sessions and tasks (DSC vs. ASRT. Results showed that learning on the two tasks was not related. However, participants in the multiple sessions condition did show greater improvements in reaction

An Efficient Metric of Automatic Weight Generation for Properties in Instance Matching Technique

OpenAIRE

Seddiqui, Md. Hanif; Nath, Rudra Pratap Deb; Aono, Masaki

2015-01-01

The proliferation of heterogeneous data sources of semantic knowledge base intensifies the need of an automatic instance matching technique. However, the efficiency of instance matching is often influenced by the weight of a property associated to instances. Automatic weight generation is a non-trivial, however an important task in instance matching technique. Therefore, identifying an appropriate metric for generating weight for a property automatically is nevertheless a formidab...

Supporting inquiry learning by promoting normative understanding of multivariable causality

Science.gov (United States)

Keselman, Alla

2003-11-01

Early adolescents may lack the cognitive and metacognitive skills necessary for effective inquiry learning. In particular, they are likely to have a nonnormative mental model of multivariable causality in which effects of individual variables are neither additive nor consistent. Described here is a software-based intervention designed to facilitate students' metalevel and performance-level inquiry skills by enhancing their understanding of multivariable causality. Relative to an exploration-only group, sixth graders who practiced predicting an outcome (earthquake risk) based on multiple factors demonstrated increased attention to evidence, improved metalevel appreciation of effective strategies, and a trend toward consistent use of a controlled comparison strategy. Sixth graders who also received explicit instruction in making predictions based on multiple factors showed additional improvement in their ability to compare multiple instances as a basis for inferences and constructed the most accurate knowledge of the system. Gains were maintained in transfer tasks. The cognitive skills and metalevel understanding examined here are essential to inquiry learning.

Mil doscientos títulos de antropología colombiana: primera parte

Directory of Open Access Journals (Sweden)

Manuel Lucena Salmoral

1969-08-01

Full Text Available La aparición de estos mil doscientos títulos sobre antropología Colombiana representa un esfuerzo juvenil de universitarios javerianos, pertenecientes a distintas ciencias sociales, quienes fueron confluyendo a mis clases de Antropología Cultural guiados por la misma problemática: la búsqueda del hombre.

Collaborative E-Learning with Multiple Imaginary Co-Learner: Design, Issues and Implementation

OpenAIRE

Melvin Ballera; Mosbah Mohamed Elssaedi; Ahmed Khalil Zohdy

2013-01-01

Collaborative problem solving in e-learning can take in the form of discussion among learner, creating a highly social learning environment and characterized by participation and interactivity. This paper, designed a collaborative learning environment where agent act as co-learner, can play different roles during interaction. Since different roles have been assigned to the agent, learner will assume that multiple co-learner exists to help and guide him all throughout the ...

Fabrication of core-shell Fe{sub 3}O{sub 4}@MIL-100(Fe) magnetic microspheres for the removal of Cr(VI) in aqueous solution

Energy Technology Data Exchange (ETDEWEB)

Yang, Qingxiang, E-mail: qxyangzz@163.com; Zhao, Qianqian; Ren, ShuangShuang; Lu, Qiongqiong; Guo, Xinmeng; Chen, Zhijun, E-mail: chenzj@zzuli.edu.cn

2016-12-15

Facile regeneration of an adsorbent is very important for commercial feasibility. One typical highly porous metal-organic framework (MOF) materials based on MIL-100(Fe) and magnetic iron oxide particles (denoted as MMCs) with diameter about of 350 nm were successfully synthesized. The growth of MIL-100(Fe) shell on the surface of Fe{sub 3}O{sub 4} was utilized precursor as crystal seed via in-situ step hydrothermal reaction. It is a simple way to obtain well organized core-shell MOF composites, compared to the step-by-step method. MMCs were firstly used to uptake of Cr(VI) anions in aqueous solution. Adsorption experiments were carried out in batch sorption mode investigating with the factors of contact time (0–1000 min), pH (from 2 to 12), dose of adsorbent (4–25 mg), and initial Cr(VI) concentration (range from 10 to 100 ppm). - Graphical abstract: One typical highly porous metal-organic framework (MOF) materials based on MIL-100(Fe) and magnetic iron oxide particles (denoted as MMCs) were successfully synthesized. Utilizing Fe{sub 3}O{sub 4} precursor as crystal seed to grow MIL-100(Fe) shell by in-situ step hydrothermal reaction. It is a simple way to obtain core-shell MOF composites. MMCs could effectively uptake of Cr(VI) anions in aqueous solution. - Highlights: • Fe{sub 3}O{sub 4}@MIL-100(Fe) composites with core-shell structure were successfully prepared through a simple method. • The influence factors on Cr(VI) adsorption by Fe{sub 3}O{sub 4}@MIL-100(Fe) were investigated. • Cr(VI) can efficiently adsorbed by Fe{sub 3}O{sub 4}@MIL-100(Fe) composites from aqueous solution.

A sensitive and selective sensor for biothiols based on the turn-on fluorescence of the Fe-MIL-88 metal-organic frameworks-hydrogen peroxide system.

Science.gov (United States)

Sun, Zheng Juan; Jiang, Jun Ze; Li, Yuan Fang

2015-12-21

Herein, we present a novel strategy based on a "turn-on" fluorescence system made up of metal-organic frameworks Fe-MIL-88 and H2O2 for detecting biothiols in human serum. The nonfluorescent Fe-MIL-88 gives weak fluorescence in the presence of H2O2. Interestingly, it was found that biothiols such as glutathione (GSH), cysteine (Cys) or homocysteine (Hcy) could induce fluorescence turn-on of the Fe-MIL-88/H2O2 system. Under optimal conditions, the relative fluorescence intensity exhibited a good linear relationship in the range from 50 nM-10 μM for GSH (r = 0.994), 50 nM-10 μM for Cys (r = 0.990), and 50 nM-10 μM (r = 0.992) for Hcy; the detection limits of GSH, Cys and Hcy were 30 nM, 40 nM, and 40 nM respectively. Mechanism investigation reveals that biothiols could associate with Fe-MIL-88 via hydrogen bonding and electrostatic interaction followed by redox reaction between biothiols and Fe(3+) present in the Fe-MIL-88, Fe(3+) was thus reduced to Fe(2+), and then Fe(2+) could efficiently catalyze the decomposition of H2O2 to yield ˙OH radicals through the Fenton reaction. Besides, biothiols were able to reduce H2O2 to produce ˙OH radicals directly. Thus the Fe-MIL-88 as well as biothiols could cooperatively contribute to the activation of H2O2 to generate higher amounts of ˙OH radicals, which in turn oxidize the free ligand terephthalic acid (BDC) outside or within the Fe-MIL-88 structure to strongly fluorescent hydroxylated terephthalic acid (OHBDC), thereby turning on the fluorescence.

MIL-125-NH2@TiO2 Core-Shell Particles Produced by a Post-Solvothermal Route for High-Performance Photocatalytic H2 Production.

Science.gov (United States)

Zhang, Bingxing; Zhang, Jianling; Tan, Xiuniang; Shao, Dan; Shi, Jinbiao; Zheng, Lirong; Zhang, Jing; Yang, Guanying; Han, Buxing

2018-05-02

Metal-organic frameworks (MOFs) have proven to be an interesting class of sacrificial precursors of functional inorganic materials for catalysis, energy storage, and conversion applications. However, the controlled synthesis of MOF-derived materials with desirable compositions, structures, and properties still remains a big challenge. Herein, we propose a post-solvothermal route for the outer-to-inner loss of organic linkers from MOF, which is simple, rapid, and controllable and can be operated at temperature much lower than that of the commonly adopted pyrolysis method. By such a strategy, the MIL-125-NH 2 particles coated by TiO 2 nanosheets were produced, and the thickness of TiO 2 shell can be easily tuned. The MIL-125-NH 2 @TiO 2 core-shell particles combine the advantages of highly active TiO 2 nanosheets, MIL-125-NH 2 photosensitizer, plenty of linker defects and oxygen vacancies, and mesoporous structure, which allows them to be utilized as photocatalysts for the visible-light-driven hydrogen production reaction. It is remarkable that the hydrogen evolution rate by MIL-125-NH 2 @TiO 2 can be enhanced 70 times compared with the pristine MIL-125-NH 2 . Such a route can be easily applied to the synthesis of different kinds of MOF-derived functional materials.

Memory and learning disturbances in multiple sclerosis

International Nuclear Information System (INIS)

Izquierdo, Guillermo; Mir, Jordi; Gonzalez, Manuel; Martinez-Parra, Carlos; Campoy, Francisco Jr

1991-01-01

Thirty-five patients with definite multiple sclerosis (MS) were studied. They underwent neuropsychological testing and magnetic resonance imaging (MRI). The MRI findings at different brain areas levels were compared with the neuropsychological findings. A quantitative system was used to measure MRI-MS lesions. In this series, a positive correlation was established between memory and learning disturbances measured by Battery 144, and the lesions measured by MRI (total, hemispheric and , particularly, periventricular lesions). MRI can detect MS lesions, and this study shows that a correlation between MRI and neuropsychological findings is possible if quantitative methods are used to distinguish different MS involvement areas in relation to neuropsychological tasks. These findings suggest that hemispheric lesions in MS produce cognitive disturbances and MRI could be a useful tool in predicting memory and learning impairment. (author). 20 refs.; 1 fig.; 2 tabs

MIL-STD-1553B Marconi LSI chip set in a remote terminal application

Science.gov (United States)

Dimarino, A.

1982-11-01

Marconi Avionics is utilizing the MIL-STD-1553B LSI Chip Set in the SCADC Air Data Computer application to perform all of the required remote terminal MIL-STD-1553B protocol functions. Basic components of the RTU are the dual redundant chip set, CT3231 Transceivers, 256 x 16 RAM and a Z8002 microprocessor. Basic transfers are to/from the RAM command of the bus controller or Z8002 processor. During transfers from the processor to the RAM, the chip set busy bit is set for a period not exceeding 250 microseconds. When the transfer is complete, the busy bit is released and transfers to the data bus occur on command. The LSI Chip Set word count lines are used to locate each data word in the local memory and 4 mode codes are used in the application: reset remote terminal, transmit status word, transmitter shut-down, and override transmitter shutdown.

A preclustering-based ensemble learning technique for acute appendicitis diagnoses.

Science.gov (United States)

Lee, Yen-Hsien; Hu, Paul Jen-Hwa; Cheng, Tsang-Hsiang; Huang, Te-Chia; Chuang, Wei-Yao

2013-06-01

Acute appendicitis is a common medical condition, whose effective, timely diagnosis can be difficult. A missed diagnosis not only puts the patient in danger but also requires additional resources for corrective treatments. An acute appendicitis diagnosis constitutes a classification problem, for which a further fundamental challenge pertains to the skewed outcome class distribution of instances in the training sample. A preclustering-based ensemble learning (PEL) technique aims to address the associated imbalanced sample learning problems and thereby support the timely, accurate diagnosis of acute appendicitis. The proposed PEL technique employs undersampling to reduce the number of majority-class instances in a training sample, uses preclustering to group similar majority-class instances into multiple groups, and selects from each group representative instances to create more balanced samples. The PEL technique thereby reduces potential information loss from random undersampling. It also takes advantage of ensemble learning to improve performance. We empirically evaluate this proposed technique with 574 clinical cases obtained from a comprehensive tertiary hospital in southern Taiwan, using several prevalent techniques and a salient scoring system as benchmarks. The comparative results show that PEL is more effective and less biased than any benchmarks. The proposed PEL technique seems more sensitive to identifying positive acute appendicitis than the commonly used Alvarado scoring system and exhibits higher specificity in identifying negative acute appendicitis. In addition, the sensitivity and specificity values of PEL appear higher than those of the investigated benchmarks that follow the resampling approach. Our analysis suggests PEL benefits from the more representative majority-class instances in the training sample. According to our overall evaluation results, PEL records the best overall performance, and its area under the curve measure reaches 0.619. The

Time and activity sequence prediction of business process instances

DEFF Research Database (Denmark)

Polato, Mirko; Sperduti, Alessandro; Burattin, Andrea

2018-01-01

The ability to know in advance the trend of running process instances, with respect to different features, such as the expected completion time, would allow business managers to timely counteract to undesired situations, in order to prevent losses. Therefore, the ability to accurately predict...... future features of running business process instances would be a very helpful aid when managing processes, especially under service level agreement constraints. However, making such accurate forecasts is not easy: many factors may influence the predicted features. Many approaches have been proposed...

Institutionalizing Blended Learning into Joint Training: A Case Study and Ten Recommendations

Science.gov (United States)

2014-12-01

mail.mil pbockelman@mesh.dsci.com ABSTRACT In 2011, the Joint Staff J7 (Joint Training) directorate initiated the Continuum of eLearning project in...Orlando, FL. 14. ABSTRACT In 2011, the Joint Staff J7 (Joint Training) directorate initiated the Continuum of eLearning project in order to integrate...dispersed organizations still poses significant challenges. The Joint Staff J7, Deputy Director for Joint Training initiated the Continuum of eLearning

The effects of single instance, multiple instance, and general case training on generalized vending machine use by moderately and severely handicapped students.

OpenAIRE

Sprague, J R; Horner, R H

1984-01-01

This report provides an experimental analysis of generalized vending machine use by six moderately or severely retarded high school students. Dependent variables were training trials to criterion and performance on 10 nontrained "generalization" vending machines. A multiple-baseline design across subjects was used to compare three strategies for teaching generalized vending machine use. Training occurred with (a) a single vending machine, (b) three similar machines, or (c) three machines that...

Synthesis and sonocatalytic performance of a ternary magnetic MIL-101(Cr)/RGO/ZnFe2O4 nanocomposite for degradation of dye pollutants.

Science.gov (United States)

Nirumand, Ladan; Farhadi, Saeed; Zabardasti, Abedin; Khataee, Alireza

2018-04-01

In this study, new ternary magnetic MIL-101(Cr)/RGO/ZnFe 2 O 4 catalyst (with 30% wt of ZnFe 2 O 4 ) was synthesized via a hydrothermal route for sonodegradation of organic dyes. The structural, optical and magnetic properties of the nanocomposite were detected by means of X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), UV-visible spectroscopy (UV-visible), field emission scanning electron microscopy (FESEM), energy dispersive X-ray (EDX) spectroscopy, vibrating sample magnetometer (VSM), atomic force microscopy (AFM), Raman spectroscopy and BET surface area analysis. To evaluate the sonocatalytic activity of the as-prepared MIL-101(Cr)/RGO/ZnFe 2 O 4 nanocomposite, the H 2 O 2 -assisted degradation of organic dyes such as congo red (CR), methylene blue (MB), Rhodamine B (RhB) and methyl orange (MO) in aqueous solution was studied under ultrasound irradiation. The obtained results indicated that the ternary MIL-101(Cr)/RGO/ZnFe 2 O 4 nanocomposite had better performance for sonodegradation of these dyes than MIL-101(Cr)/RGO, pure MIL-101(Cr) or ZnFe 2 O 4 . The enhanced sonocatalytic performance of the as-prepared ternary nanocomposite could be attributed to the fast generation and separation of charge carriers (electrons and holes) in ZnFe 2 O 4 and MIL-101(Cr) and their transfer to the surface of graphene sheets. Moreover, the relatively high specific surface area of the MIL-101(Cr)/rGO and magnetic property of ZnFe 2 O 4 improve the degradation efficiency of the dyes. The recovery of the ternary magnetic sonocatalyst from treated water could be easily achieved using an external magnetic field. The main influence factors on the sonocatalytic activity such as catalyst dosage and dye initial concentration were also investigated. The trapping experiments indicated that OH radicals are the prominent active species in dye degradation. In addition, the reusability test, was also carried out to ensure the stability of the employed sonocatalyst

Effects of ductile phase volume fraction on the mechanical properties of Ti-Al3Ti metal-intermetallic laminate (MIL) composites

International Nuclear Information System (INIS)

Price, Richard D.; Jiang Fengchun; Kulin, Robb M.; Vecchio, Kenneth S.

2011-01-01

Research highlights: → Residual Al improves the mechanical properties of Ti-Al 3 Ti MIL composites. → Residual Al can eliminate intermetallic centerline delaminations in MILs. → Low levels of residual Al increase fracture toughness in MIL composites. → MIL stiffness, strength, and fracture toughness can be optimized at low Al levels. - Abstract: Metal-intermetallic laminate (MIL) composites consisting of alternating layers of Ti, Al, and the intermetallic Al 3 Ti have been fabricated by reactive foil sintering in open air. Six initially identical stacks of alternating Ti-3Al-2.5 V and 1100-Al foils were processed for different lengths of time, yielding specimens with different metal and intermetallic volume fractions. Their mechanical properties have been investigated with an emphasis on the effect of residual Al at the intermetallic centerline on composite strength and fracture toughness, as well as fracture and failure modes. Samples were cut from each composite plate (in layer orientations parallel and perpendicular to the intended load direction) for mechanical testing in compression and four-point bending under quasi-static and high-rate loading conditions. Examination of the damaged specimens and their fracture surfaces by optical and scanning electron microscopy was performed to establish a correlation between the failure mechanisms present, composite strength, and microstructure. Results indicated that regardless of loading direction, cracks always initiated in the intermetallic region, rarely at the centerline, and crack propagation and failure were heavily influenced by the thickness of the residual aluminum layers. There is an ideal residual aluminum volume fraction that represents the amount of ductile reinforcement that maximizes the combined properties of strength, toughness and stiffness.

Pareto-path multitask multiple kernel learning.

Science.gov (United States)

Li, Cong; Georgiopoulos, Michael; Anagnostopoulos, Georgios C

2015-01-01

A traditional and intuitively appealing Multitask Multiple Kernel Learning (MT-MKL) method is to optimize the sum (thus, the average) of objective functions with (partially) shared kernel function, which allows information sharing among the tasks. We point out that the obtained solution corresponds to a single point on the Pareto Front (PF) of a multiobjective optimization problem, which considers the concurrent optimization of all task objectives involved in the Multitask Learning (MTL) problem. Motivated by this last observation and arguing that the former approach is heuristic, we propose a novel support vector machine MT-MKL framework that considers an implicitly defined set of conic combinations of task objectives. We show that solving our framework produces solutions along a path on the aforementioned PF and that it subsumes the optimization of the average of objective functions as a special case. Using the algorithms we derived, we demonstrate through a series of experimental results that the framework is capable of achieving a better classification performance, when compared with other similar MTL approaches.

Scheduling jobs in the cloud using on-demand and reserved instances

NARCIS (Netherlands)

Shen, S.; Deng, K.; Iosup, A.; Epema, D.H.J.; Wolf, F.; Mohr, B.; Mey, an D.

2013-01-01

Deploying applications in leased cloud infrastructure is increasingly considered by a variety of business and service integrators. However, the challenge of selecting the leasing strategy — larger or faster instances? on-demand or reserved instances? etc.— and to configure the leasing strategy with

Separation properties of the MIL-125(Ti) Metal-Organic Framework in high-performance liquid chromatography revealing cis/trans selectivity.

Science.gov (United States)

Van der Perre, Stijn; Liekens, Anuschka; Bueken, Bart; De Vos, Dirk E; Baron, Gino V; Denayer, Joeri F M

2016-10-21

Monodisperse MIL-125(Ti) Metal-Organic Framework crystals were synthesized and studied as stationary phase in high performance liquid chromatography (HPLC). Different pure compounds and model mixtures (including stereoisomer mixtures) were injected from which chromatographic parameters, including selectivities and resolution factors, were determined to evaluate the adsorption properties and separation performance of MIL-125(Ti) in liquid phase. The MIL-125(Ti) framework displayed a trans selectivity for cis/trans difunctionalized cyclohexane molecules with high selectivity and resolution for 1,3-dimethylcyclohexane and 4-ethylcyclohexanol. The slurry-packed column was further characterized via van Deemter analysis. Fitting of the van Deemter equation through the experimental points allowed to define the contributions of the different processes to plate height with a significant proportion of the A-term, reflecting the importance of a good crystal packing. Although high in comparison to commercial HPLC stationary phases, a very good plate height of around 50μm was found. Copyright © 2016 Elsevier B.V. All rights reserved.

Multiple-Machine Scheduling with Learning Effects and Cooperative Games

Directory of Open Access Journals (Sweden)

Yiyuan Zhou

2015-01-01

Full Text Available Multiple-machine scheduling problems with position-based learning effects are studied in this paper. There is an initial schedule in this scheduling problem. The optimal schedule minimizes the sum of the weighted completion times; the difference between the initial total weighted completion time and the minimal total weighted completion time is the cost savings. A multiple-machine sequencing game is introduced to allocate the cost savings. The game is balanced if the normal processing times of jobs that are on the same machine are equal and an equal number of jobs are scheduled on each machine initially.

Multimodality and children's participation in classrooms: Instances of ...

African Journals Online (AJOL)

Multimodality and children's participation in classrooms: Instances of research. ... deficit models of children, drawing on their everyday experiences and their existing ... It outlines the theoretical framework supporting the pedagogical approach, ...

Imbalanced Class Learning in Epigenetics

OpenAIRE

Haque, M. Muksitul; Skinner, Michael K.; Holder, Lawrence B.

2014-01-01

In machine learning, one of the important criteria for higher classification accuracy is a balanced dataset. Datasets with a large ratio between minority and majority classes face hindrance in learning using any classifier. Datasets having a magnitude difference in number of instances between the target concept result in an imbalanced class distribution. Such datasets can range from biological data, sensor data, medical diagnostics, or any other domain where labeling any instances of the mino...

Which is the best intrinsic motivation signal for learning multiple skills?

Directory of Open Access Journals (Sweden)

Vieri Giuliano Santucci

2013-11-01

Full Text Available Humans and other biological agents are able to autonomously learn and cache different skills in the absence of any biological pressure or any assigned task. In this respect, Intrinsic Motivations (i.e. motivations not connected to reward-related stimuli play a cardinal role in animal learning, and can be considered as a fundamental tool for developing more autonomous and more adaptive artificial agents. In this work, we provide an exhaustive analysis of a scarcely investigated problem: which kind of IM reinforcement signal is the most suitable for driving the acquisition of multiple skills in the shortest time? To this purpose we implemented an artificial agent with a hierarchical architecture that allows to learn and cache different skills. We tested the system in a setup with continuous states and actions, in particular, with a cinematic robotic arm that has to learn different reaching tasks. We compare the results of different versions of the system driven by several different intrinsic motivation signals. The results show a that intrinsic reinforcements purely based on the knowledge of the system are not appropriate to guide the acquisition of multiple skills, and b that the stronger the link between the IM signal and the competence of the system, the better the performance.

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

Science.gov (United States)

Korotcov, Alexandru; Tkachenko, Valery; Russo, Daniel P; Ekins, Sean

2017-12-04

Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further

SEDS MIL-STD-1773 fiber optic data bus: Proton irradiation test results and spaceflight SEU data

Energy Technology Data Exchange (ETDEWEB)

LaBel, K.A.; Stassinopoulos, E.G.; Miller, J.T. (NASA/GSFC, Greenbelt, MD (United States)); Marshall, P. (NRL/SFA, Washington, DC (United States)); Dale, C. (NRL, Washington, DC (United States)); Crabtree, C.M. (Hughes/ST Systems Corp., Seabrook, MD (United States)); Gates, M.M. (Jackson and Tull, Seabrook, MD (United States))

1993-12-01

The Small Explorer Data System (SEDS) was launched in July of 1992 as part of the Solar Anomalous Magnetospheric Particle Explorer (SAMPEX) mission. The SEDS utilizes NASA's first MIL-STD-1773 Fiber Optic Multiplexed Data Bus (or 1773 bus) to communicate with other spacecraft subsystems in the space environment. The 1773 bus is the fiber optic version of the MIL-STD-1553 Data Bus, a electronic wire bus used in many avionics applications. The authors present proton test and space flight single event effect data for NASA's first fiber optic data bus. Bit error rate predictions based on a new proton direct ionization model agree well with flight data for proton belt and solar flare effects.

Design of multiple representations e-learning resources based on a contextual approach for the basic physics course

Science.gov (United States)

Bakri, F.; Muliyati, D.

2018-05-01

This research aims to design e-learning resources with multiple representations based on a contextual approach for the Basic Physics Course. The research uses the research and development methods accordance Dick & Carey strategy. The development carried out in the digital laboratory of Physics Education Department, Mathematics and Science Faculty, Universitas Negeri Jakarta. The result of the process of product development with Dick & Carey strategy, have produced e-learning design of the Basic Physics Course is presented in multiple representations in contextual learning syntax. The appropriate of representation used in the design of learning basic physics include: concept map, video, figures, data tables of experiment results, charts of data tables, the verbal explanations, mathematical equations, problem and solutions example, and exercise. Multiple representations are presented in the form of contextual learning by stages: relating, experiencing, applying, transferring, and cooperating.

Enhanced catalytic activity over MIL-100(Fe) loaded ceria catalysts for the selective catalytic reduction of NOx with NH₃ at low temperature.

Science.gov (United States)

Wang, Peng; Sun, Hong; Quan, Xie; Chen, Shuo

2016-01-15

The development of catalysts for selective catalytic reduction (SCR) reactions that are highly active at low temperatures and show good resistance to SO2 and H2O is still a challenge. In this study, we have designed and developed a high-performance SCR catalyst based on nano-sized ceria encapsulated inside the pores of MIL-100(Fe) that combines excellent catalytic power with a metal organic framework architecture synthesized by the impregnation method (IM). Transmission electron microscopy (TEM) revealed the encapsulation of ceria in the cavities of MIL-100(Fe). The prepared IM-CeO2/MIL-100(Fe) catalyst shows improved catalytic activity both at low temperatures and throughout a wide temperature window. The temperature window for 90% NOx conversion ranges from 196 to 300°C. X-ray photoelectron spectroscopy (XPS) and in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFT) analysis indicated that the nano-sized ceria encapsulated inside MIL-100(Fe) promotes the production of chemisorbed oxygen on the catalyst surface, which greatly enhances the formation of the NO2 species responsible for fast SCR reactions. Copyright © 2015 Elsevier B.V. All rights reserved.

A Preliminary Report on the Strength and Metallography of a Bimetallic Friction Stir Weld Joint Between AA6061 and MIL-DTL-46100E High Hardness Steel Armor

Science.gov (United States)

2012-11-26

bimetallic friction stir weld joint between AA6061 and MIL-DTL-46100E High Hardness steel armor. ABSTRACT One half inch thick plates of 6061-T6 aluminum...alloy and High Hardness steel armor (MIL- STD-46100) were successfully joined by the friction stir welding (FSW) process using a tungsten-rhenium...4. TITLE AND SUBTITLE A preliminary report on the strength and metallography of a bimetallic friction stir weld joint between AA6061 and MIL-DTL

Enhancing Undergraduate Chemistry Learning by Helping Students Make Connections among Multiple Graphical Representations

Science.gov (United States)

Rau, Martina A.

2015-01-01

Multiple representations are ubiquitous in chemistry education. To benefit from multiple representations, students have to make connections between them. However, connection making is a difficult task for students. Prior research shows that supporting connection making enhances students' learning in math and science domains. Most prior research…

Self and transport diffusivity of CO2 in the metal-organic framework MIL-47(V) explored by quasi-elastic neutron scattering experiments and molecular dynamics simulations.

Science.gov (United States)

Salles, Fabrice; Jobic, Hervé; Devic, Thomas; Llewellyn, Philip L; Serre, Christian; Férey, Gérard; Maurin, Guillaume

2010-01-26

Quasi-elastic neutron scattering measurements are combined with molecular dynamics simulations to determine the self-diffusivity, corrected diffusivity, and transport diffusivity of CO(2) in the metal-organic framework MIL-47(V) (MIL = Materials Institut Lavoisier) over a wide range of loading. The force field used for describing the host/guest interactions is first validated on the thermodynamics of the MIL-47(V)/CO(2) system, prior to being transferred to the investigations of the dynamics. A decreasing profile is then deduced for D(s) and D(o) whereas D(t) presents a non monotonous evolution with a slight decrease at low loading followed by a sharp increase at higher loading. Such decrease of D(t) which has never been evidenced in any microporous systems comes from the atypical evolution of the thermodynamic correction factor that reaches values below 1 at low loading. This implies that, due to intermolecular interactions, the CO(2) molecules in MIL-47(V) do not behave like an ideal gas. Further, molecular simulations enabled us to elucidate unambiguously a 3D diffusion mechanism within the pores of MIL-47(V).

Intermodal Storage and Transport Frame (ISTF) MIL-STD-1660 Design Criteria for Ammunition Unit Loads Tests

National Research Council Canada - National Science Library

Barickman, Philip

2004-01-01

.... The ISTF was evaluated by the testing procedures set forth in MIL-STD-1660. Stacking, vibration, edgewise rotational drop, incline impact, sling compatibility, forklifting, and disassembly testing were conducted on the ISTF units...

Eu(III)-functionalized MIL-124 as fluorescent probe for highly selectively sensing ions and organic small molecules especially for Fe(III) and Fe(II).

Science.gov (United States)

Xu, Xiao-Yu; Yan, Bing

2015-01-14

A layerlike MOF (MIL-124, orGa2(OH)4(C9O6H4)) has been prepared and chosen as a parent compound to encapsulate Eu(3+) cations by one uncoordinated carbonyl group in its pores. The Eu(3+)-incorporated sample (Eu(3+)@MIL-124) is fully characterized, which shows excellent luminescence and good fluorescence stability in water or other organic solvents. Subsequently, we choose Eu(3+)@MIL-124 as sensitive probe for sensing metal ions, anions, and organic small molecules because of its robust framework. Studying of the luminescence properties reveals that the complex Eu(3+)@MIL-124 was developed as a highly selective and sensitive probe for detection of Fe(3+) (detection limit, 0.28 μM) and Fe(2+) ions through fluorescence quenching of Eu(3+) and MOF over other metal ions. In connection to this, a probable sensing mechanism was also discussed in this paper. In addition, when Eu(3+)@MIL-124 was immersed in the different anions solutions and organic solvents, it also shows highly selective for Cr2O7(2-)(detection limit, 0.15 μM)and acetone. Remarkably, it is the first Eu-doped MOF to exhibit an excellent ability for the detection of Fe(3+) and Fe(2+) in an aqueous environment without any structural disintegration of the framework.

Dye-sensitized MIL-101 metal organic frameworks loaded with Ni/NiO{sub x} nanoparticles for efficient visible-light-driven hydrogen generation

Energy Technology Data Exchange (ETDEWEB)

Liu, Xin-Ling; Wang, Rong; Yuan, Yu-Peng, E-mail: yupengyuan@ahu.edu.cn, E-mail: cxue@ntu.edu.sg [School of Chemistry and Chemical Engineering, and Innovation Lab for Clean Energy and Green Catalysis, Anhui University, Hefei 230036 (China); Zhang, Ming-Yi [Key Laboratory for Photonic and Electronic Bandgap Materials, Ministry of Education, School of Physics and Electronic Engineering, Harbin Normal University, Harbin 150025 (China); Xue, Can, E-mail: yupengyuan@ahu.edu.cn, E-mail: cxue@ntu.edu.sg [Solar Fuels Lab, School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798 (Singapore)

2015-10-01

The Ni/NiO{sub x} particles were in situ photodeposited on MIL-101 metal organic frameworks as catalysts for boosting H{sub 2} generation from Erythrosin B dye sensitization under visible-light irradiation. The highest H{sub 2} production rate of 125 μmol h{sup −1} was achieved from the system containing 5 wt. % Ni-loaded MIL-101 (20 mg) and 30 mg Erythrosin B dye. Moreover, the Ni/NiO{sub x} catalysts show excellent stability for long-term photocatalytic reaction. The enhancement on H{sub 2} generation is attributed to the efficient charge transfer from photoexcited dye to the Ni catalyst via MIL-101. Our results demonstrate that the economical Ni/NiO{sub x} particles are durable and active catalysts for photocatalytic H{sub 2} generation.

Fe-MIL-101 exhibits selective cytotoxicity and inhibition of angiogenesis in ovarian cancer cells via downregulation of MMP.

Science.gov (United States)

Wang, Jiaqiang; Chen, Daomei; Li, Bin; He, Jiao; Duan, Deliang; Shao, Dandan; Nie, Minfang

2016-05-18

Though metal-organic frameworks (MOFs) have inspired potential applications in biomedicine, cytotoxicity studies of MOFs have been relatively rare. Here we demonstrate for the first time that an easily available MOF, Fe-MIL-101, possesses intrinsic activity against human SKOV3 ovarian cancer cells and suppress the proliferation of SKOV3 cells (IC50 = 23.6 μg mL(-1)) and normal mouse embryonic fibroblasts (BABL-3T3, IC50 = 78.3 μg mL(-1)) cells. It was more effective against SKOV3 cells than typical anticancer drugs such as artesunate (ART, IC50 = 96.9 μg mL(-1)) and oxaliplatin (OXA, IC50 = 64.4 μg mL(-1)), but had less effect on normal BABL-3T3 cells compared with ART (IC50 = 36.6 μg mL(-1)) and OXA (IC50 = 13.8 μg mL(-1)). Fe-MIL-101 induced apoptosis of human umbilical vein endothelial cells (HUVECs) via G0/G1 cell cycle arrest and decreased the mitochondrial membrane potential in HUVECs and induced apoptosis. Furthermore, Fe-MIL-101 exhibited stronger antiangiogenic effects in HUVEC cells than antiangiogenic inhibitor (SU5416) via downregulation the expression of MMP-2/9. Our results reveal a new role of Fe-MIL-101 as a novel, non-toxic anti-angiogenic agent that restricted ovarian tumour growth. These findings could open a new avenue of using MOFs as potential therapeutics in angiogenesis-dependent diseases, including ovarian cancer.

Synthesis and structure determination of new open-framework chromium carboxylate MIL-105 or CrIII(OH).{O2C-C6(CH3)4-CO2}.nH2O

International Nuclear Information System (INIS)

Serre, Christian; Millange, Franck; Devic, Thomas; Audebrand, Nathalie; Van Beek, Wouter

2006-01-01

Two new three-dimensional chromium(III) dicarboxylate, MIL-105 or Cr III (OH).{O 2 C-C 6 (CH 3 ) 4 -CO 2 }.nH 2 O, have been obtained under hydrothermal conditions, and their structures solved using X-ray powder diffraction data. Both solids are structural analogs of the known Cr benzenedicarboxylate compound (MIL-53). Both contain trans corner-sharing CrO 4 (OH) 2 octahedral chains connected by tetramethylterephthalate di-anions. Each chain is linked by the ligands to four other chains to form a three-dimensional framework with an array of 1D pores channels. The pores of the high temperature form of the solid, MIL-105ht, are empty. However, MIL-105ht re-hydrates at room temperature to finally give MIL-105lt with pores channels filled with free water molecules (lt: low temperature form; ht: high temperature form). The thermal behaviour of the two solids has been investigated using TGA. Crystal data for MIL-105ht: monoclinic space group C2/c with a = 19.653(1) A, b = 9.984(1) A, c = 6.970(1) A, β = 110.67(1) o and Z = 4. Crystal data for MIL-105lt: orthorhombic space group Pnam with a = 17.892(1) A, b = 11.165(1) A, c = 6.916(1) A and Z = 4

Time efficient optimization of instance based problems with application to tone onset detection

OpenAIRE

Bauer, Nadja; Friedrichs, Klaus; Weihs, Claus

2016-01-01

A time efficient optimization technique for instance based problems is proposed, where for each parameter setting the target function has to be evaluated on a large set of problem instances. Computational time is reduced by beginning with a performance estimation based on the evaluation of a representative subset of instances. Subsequently, only promising settings are evaluated on the whole data set. As application a comprehensive music onset detection algorithm is introduce...

Urea-modified metal-organic framework of type MIL-101(Cr) for the preconcentration of phosphorylated peptides

International Nuclear Information System (INIS)

Yang, Xiaoqing; Xia, Yan

2016-01-01

Mass spectrometry (MS) is the most powerful tool in phosphoproteomics research. However, phosphopeptides usually are present in low concentrations and their preconcentration therefore is highly desired. We describe a two-step method for the synthesis of a metal organic framework of the type MIL-101(Cr) that is modified with urea (then designated as MIL-101(Cr)-UR 2 ). It possesses large surface area, good solvent stability and high affinity for some phosphates. Due to the presence of modified urea functions, this material allows for selective and effective enrichment of phosphorylated peptides. It was successfully applied to the enrichment of phosphopeptides from non-fat-milk. The method was applied to the detection of phosphopeptides in a tryptic digest of β-casein where is showed a detection sensitivity as low as 10 −10 M. (author)

Thin Film Nanocomposite Membrane Filled with Metal-Organic Frameworks UiO-66 and MIL-125 Nanoparticles for Water Desalination

Directory of Open Access Journals (Sweden)

Mohammed Kadhom

2017-06-01

Full Text Available Knowing that the world is facing a shortage of fresh water, desalination, in its different forms including reverse osmosis, represents a practical approach to produce potable water from a saline source. In this report, two kinds of Metal-Organic Frameworks (MOFs nanoparticles (NPs, UiO-66 (~100 nm and MIL-125 (~100 nm, were embedded separately into thin-film composite membranes in different weight ratios, 0%, 0.05%, 0.1%, 0.15%, 0.2%, and 0.3%. The membranes were synthesized by the interfacial polymerization (IP of m-phenylenediamine (MPD in aqueous solution and trimesoyl chloride (TMC in an organic phase. The as-prepared membranes were characterized by scanning electron microscopy (SEM, transmission electron microscopy (TEM, contact angle measurement, attenuated total reflection Fourier transform infrared (ATR FT-IR spectroscopy, and salt rejection and water flux assessments. Results showed that both UiO-66 and MIL-125 could improve the membranes’ performance and the impacts depended on the NPs loading. At the optimum NPs loadings, 0.15% for UiO-66 and 0.3% for MIL-125, the water flux increased from 62.5 L/m2 h to 74.9 and 85.0 L/m2 h, respectively. NaCl rejection was not significantly affected (UiO-66 or slightly improved (MIL-125 by embedding these NPs, always at >98.5% as tested at 2000 ppm salt concentration and 300 psi transmembrane pressure. The results from this study demonstrate that it is promising to apply MOFs NPs to enhance the TFC membrane performance for desalination.

28 CFR 51.46 - Reconsideration of objection at the instance of the Attorney General.

Science.gov (United States)

2010-07-01

... instance of the Attorney General. 51.46 Section 51.46 Judicial Administration DEPARTMENT OF JUSTICE... Processing of Submissions § 51.46 Reconsideration of objection at the instance of the Attorney General. (a... may be reconsidered, if it is deemed appropriate, at the instance of the Attorney General. (b) Notice...

A Mixed Matrix Membrane of Poly (4-methyl-1-pentyne Filled with MIL 53 Particles and Its Application in Carbon Dioxide and Nitrogen Separation

Directory of Open Access Journals (Sweden)

Reza Abedini

2016-05-01

Full Text Available The performance of poly (4-metyl-1-pentyne as mixed matrix membrane (MMM mixed with MIL 53 particles was studied to separate mixtures of carbon dioxide and nitrogen. MIL 53 particles was added to the polymer matrix with 10, 20 and 30 weight percentages. The adsorption of CO2 and N2 gases by MIL 53 was evaluated and the adsorption data was analyzed by Langmuir equation. Structure and thermal/mechanical properties of prepared membranes were characterized by means of FTIR, SEM, TGA and elongation test. Moreover, the gas permeation properties of membranes were studied by measuring the permeation of pure CO2 and N2. Furthermore, for accurate understanding of the gas permeation properties of the membranes, diffusion and solution coefficient of gases in neat membrane and MMMs were calculated using modified time-lag method. The results from TGA analysis showed that the degradation temperature of MMMs was enhanced and increased to 348ºC for membrane containing 30 wt% of MIL 53. The SEM images also illustrated a relatively uniform dispersion of particles with proper polymer/filler interfaces in the polymer matrix. The gas permeation results revealed that the permeability of both gases (especially CO2 increased with increasing MIL 53 loading, in which the permeability of CO2 increased from 98.74 Barrer in neat membrane to 217.65 Barrer in MMM containing 30 wt% filler. Moreover, calculation of CO2/N2 selectivity depicted that the selectivity enhanced from 16.66 to 22.70. Finally, the performance of MMMs was compared with Robeson’s upper bound in CO2/N2 separation and results showed that the MMM having 30 wt% of MIL 53 took over the Robeson bound.

Adsorption of 1,2-dichlorobenzene and 1,2,4-trichlorobenzene in nano- and microsized crystals of MIL-101(Cr): static and dynamic gravimetric studies.

Science.gov (United States)

Bullot, Laetitia; Vieira-Sellaï, Ludivine; Chaplais, Gérald; Simon-Masseron, Angélique; Daou, Toufic Jean; Patarin, Joël; Fiani, Emmanuel

2017-12-01

This work aims to highlight the promising adsorption capacity and kinetic of (poly)chlorobenzene pollutants in the hybrid MIL-101(Cr) type material for technological uses in industrial waste exhaust decontamination. The influence of the MIL-101(Cr) crystal size (nano- and microcrystals) on the adsorption behavior was studied in static and dynamic modes. For this purpose, crystals of MIL-101(Cr) in nano- and micrometric sizes were synthesized and fully characterized. Their sorption properties regarding 1,2-dichlorobenzene were examined using gravimetric method in dynamic (p/p° = 0.5) and static (p/p° = 1) modes at room temperature. 1,2,4-trichlorobenzene adsorption was only performed under static mode because of its too low vapor pressure. 1,2-dichlorobenzene and 1,2,4-trichlorobenzene were used to mimic 2,3-dichlorodibenzo-p-dioxin and 1,2,3,4-tetrachlorodibenzo-p-dioxin, respectively, and more largely dioxin compounds. Adsorptions of these probes were successfully carried out in nano- and microcrystals of MIL-101(Cr). Indeed, in static mode (p/p° = 1) and at room temperature, nanocrystals adsorb 2266 molecules of 1,2-dichlorobenzene and 2093 molecules of 1,2,4-trichlorobenzene per unit cell, whereas microcrystals adsorb 1871 molecules of 1,2-dichlorobenzene and 1631 molecules of 1,2,4-trichlorobenzene per unit cell. In dynamic mode, the 1,2-dichlorobenzene adsorbed amounts are substantially similar to those obtained in static mode. However, the adsorption kinetics are different because of a different scheme of diffusivity of the adsorbate between the two modes. To the best of our knowledge, these adsorption capacities of MIL-101(Cr) as adsorbent for polychlorobenzenes trapping have never been referenced. MIL-101(Cr) appears as a promising material for technological uses in industrial waste exhaust decontamination.

Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

Science.gov (United States)

Chen, Tianle; Zeng, Donglin

2015-01-01

Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419

The Onset and Duration of Action of 0.2% Lidocaine in a One-per-Mil Tumescent Solution for Hand Surgery.

Science.gov (United States)

Prasetyono, Theddeus O H; Lestari, Puri A

2016-05-01

One-per-mil tumescent solution, which contains 0.2% lidocaine with 1:1,000,000 epinephrine, has been reported to be clinically effective for hand surgery under local anesthesia. However, it was lacking in its basic pharmacokinetics profile in regard to the onset of action (OOA) and duration of action (DOA). A randomized, double-blind study was conducted on 12 volunteers who met the inclusion criteria from October to November 2014. All volunteers had their right and left ring finger pulps injected with either one-per-mil solution or 2% lidocaine. Semmes-Weinstein and two-point discrimination tests were used to test sensation. Visual analogue scale was recorded at the time when the finger lost its sensation and when it regained normal sensation to measure the OOA and DOA. The data were then analyzed with a paired t-test and a Wilcoxon signed-rank test. The OOA and DOA of 2% plain lidocaine were 1 minute and 99.67 minutes, respectively. Meanwhile, 0.2% lidocaine in a one-per-mil tumescent solution showed an OOA of 5 minutes and a DOA of 186.83 minutes. The OOA of 0.2% lidocaine in a one-per-mil tumescent solution is statistically shorter than 2% plain lidocaine (P=0.04); while its DOA is statistically longer than 2% plain lidocaine (Pmil tumescent solution is statistically and clinically superior to 2% plain lidocaine in achieving longer duration of local anesthesia.

Una imatge val per mil paraules

Directory of Open Access Journals (Sweden)

Jaume Cabré

1999-11-01

Full Text Available Una vegada hi havia un videoclub ple de pel·lícules i a l'entrada hi havia un rètol lluminós molt bonic que deia el lema d'aquesta casa, que és una imatge val per mil paraules. I vet aquí un dia que la clientela ja se n'havia anat, però encara no havien tancat els llums, van entrar al videoclub dues rates, l'Amàlia i l'Amèlia. I van dir: "Què fem avui?" Aleshores l'Amèlia se'n va anar de seguida cap al racó de la sèrie B i va agafar una pel·lícula poc coneguda, mentre que l'Amàlia va agafar Mort a Venècia. Llavors la va començar a rosegar i l'Amèlia li va dir: "Què, què te'n sembla?", i l'Amàlia li va contestar: "Mmm... Em va agradar més la novel·la."

MIL-HDBK-338-Environmental Conversion Table Correction

Science.gov (United States)

Hark, Frank; Novack, Steve

2017-01-01

In reliability analysis for space launch vehicles, limited data is frequently a challenge due to the pure number of launches. A common solution is to use surrogate historical data of similar components from other industries (military data). The operating environment of the common data may be different from that of the necessary target analysis. The military electronic design handbook (MIL-HDBK-338) has a table for converting Mean Time Between Failure (MTBF) data from one environment to another. However, the table has some discrepancies and rounding of complementary conversions; namely going from environment A to B does not given the same result as going from B to A. This presentation will show the discrepancies in the original conversation table, the greater than expected magnitude, the problem with the updated published table and a suggested corrected table to reference when doing MTBF data environment conversion.

CHISSL: A Human-Machine Collaboration Space for Unsupervised Learning

Energy Technology Data Exchange (ETDEWEB)

Arendt, Dustin L.; Komurlu, Caner; Blaha, Leslie M.

2017-07-14

We developed CHISSL, a human-machine interface that utilizes supervised machine learning in an unsupervised context to help the user group unlabeled instances by her own mental model. The user primarily interacts via correction (moving a misplaced instance into its correct group) or confirmation (accepting that an instance is placed in its correct group). Concurrent with the user's interactions, CHISSL trains a classification model guided by the user's grouping of the data. It then predicts the group of unlabeled instances and arranges some of these alongside the instances manually organized by the user. We hypothesize that this mode of human and machine collaboration is more effective than Active Learning, wherein the machine decides for itself which instances should be labeled by the user. We found supporting evidence for this hypothesis in a pilot study where we applied CHISSL to organize a collection of handwritten digits.

Multiple Intelligences, Motivations and Learning Experience Regarding Video-Assisted Subjects in a Rural University

Science.gov (United States)

Hajhashemi, Karim; Caltabiano, Nerina; Anderson, Neil; Tabibzadeh, Seyed Asadollah

2018-01-01

This study investigates multiple intelligences in relation to online video experiences, age, gender, and mode of learning from a rural Australian university. The inter-relationships between learners' different intelligences and their motivations and learning experience with the supplementary online videos utilised in their subjects are…

Student-Generated Content: Enhancing Learning through Sharing Multiple-Choice Questions

Science.gov (United States)

Hardy, Judy; Bates, Simon P.; Casey, Morag M.; Galloway, Kyle W.; Galloway, Ross K.; Kay, Alison E.; Kirsop, Peter; McQueen, Heather A.

2014-01-01

The relationship between students' use of PeerWise, an online tool that facilitates peer learning through student-generated content in the form of multiple-choice questions (MCQs), and achievement, as measured by their performance in the end-of-module examinations, was investigated in 5 large early-years science modules (in physics, chemistry and…

Optimizing multiple-choice tests as tools for learning.

Science.gov (United States)

Little, Jeri L; Bjork, Elizabeth Ligon

2015-01-01

Answering multiple-choice questions with competitive alternatives can enhance performance on a later test, not only on questions about the information previously tested, but also on questions about related information not previously tested-in particular, on questions about information pertaining to the previously incorrect alternatives. In the present research, we assessed a possible explanation for this pattern: When multiple-choice questions contain competitive incorrect alternatives, test-takers are led to retrieve previously studied information pertaining to all of the alternatives in order to discriminate among them and select an answer, with such processing strengthening later access to information associated with both the correct and incorrect alternatives. Supporting this hypothesis, we found enhanced performance on a later cued-recall test for previously nontested questions when their answers had previously appeared as competitive incorrect alternatives in the initial multiple-choice test, but not when they had previously appeared as noncompetitive alternatives. Importantly, however, competitive alternatives were not more likely than noncompetitive alternatives to be intruded as incorrect responses, indicating that a general increased accessibility for previously presented incorrect alternatives could not be the explanation for these results. The present findings, replicated across two experiments (one in which corrective feedback was provided during the initial multiple-choice testing, and one in which it was not), thus strongly suggest that competitive multiple-choice questions can trigger beneficial retrieval processes for both tested and related information, and the results have implications for the effective use of multiple-choice tests as tools for learning.

Facile synthesis of highly efficient amorphous Mn-MIL-100 catalysts: The formation mechanism and the structure changes during the application for CO oxidation.

Science.gov (United States)

Zhang, Xiaodong; Li, Hongxin; Lv, Xutian; Xu, Jingcheng; Wang, Yuxin; He, Chi; Liu, Ning; Yang, Yiqiong; Wang, Yin

2018-04-13

A comprehensive study was carried out on amorphous metal-organic frameworks Mn-MIL-100 as efficient catalysts towards CO oxidation. This study focuses on explaining the crystalline-amorphous-crystalline transformations during thermolysis process of Mn-MIL-100 and studying the structure changes during the reaction process for CO oxidation. A possible formation mechanism of amorphous Mn-MIL-100 was proposed. Amorphous Mn-MIL-100 obtained by calcination at 250°C (a-Mn-250) showed a smaller specific surface area (4 m2/g), but displayed a high catalytic activity. Furthermore, the structure of amorphous Mn-MIL-100 was labile during the reaction process. When used a-Mn-250 were treated with reaction atmosphere at high temperature (named used a-Mn-250-S), the amorphous catalysts transformed to Mn2O3. Meanwhile, BET surface area (164 m2/g) and the catalytic performance both sharply increased. In addition, used a-Mn-250-S catalyst transformed from Mn2O3 to Mn3O4, resulting in the slightly decrease of catalytic activity under the presence of 1 vol% water vapor in the stream. A schematic of the structure changes during the reaction process was proposed. The achievement of our synthesis relies on the increase of BET surface area using CO as retreatment atmosphere, and the enhanced catalytic activity was attributed to the unique structure, a high quantity of surface active oxygen species, oxygen vacancies and good low temperature reduction behavior. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SIFT Meets CNN: A Decade Survey of Instance Retrieval.

Science.gov (United States)

Zheng, Liang; Yang, Yi; Tian, Qi

2018-05-01

In the early days, content-based image retrieval (CBIR) was studied with global features. Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively studied for over a decade due to the advantage of SIFT in dealing with image transformations. Recently, image representations based on the convolutional neural network (CNN) have attracted increasing interest in the community and demonstrated impressive performance. Given this time of rapid evolution, this article provides a comprehensive survey of instance retrieval over the last decade. Two broad categories, SIFT-based and CNN-based methods, are presented. For the former, according to the codebook size, we organize the literature into using large/medium-sized/small codebooks. For the latter, we discuss three lines of methods, i.e., using pre-trained or fine-tuned CNN models, and hybrid methods. The first two perform a single-pass of an image to the network, while the last category employs a patch-based feature extraction scheme. This survey presents milestones in modern instance retrieval, reviews a broad selection of previous works in different categories, and provides insights on the connection between SIFT and CNN-based methods. After analyzing and comparing retrieval performance of different categories on several datasets, we discuss promising directions towards generic and specialized instance retrieval.

Fabrication of core-shell MIL-101(Cr)@UiO-66(Zr) nanocrystals for hydrogen storage

CSIR Research Space (South Africa)

Ren, Jianwei

2014-09-01

Full Text Available of the individual metal-organic framework (MOF) components and the coreeshell hybrid crystals were also characterized. The hydrogen storage capacity exhibited by the resulting core eshell nanocrystals was 26% and 60% higher than those of pure phase MIL-101 and Ui...

Searching for Variables and Models to Investigate Mediators of Learning from Multiple Representations

Science.gov (United States)

Rau, Martina A.; Scheines, Richard

2012-01-01

Although learning from multiple representations has been shown to be effective in a variety of domains, little is known about the mechanisms by which it occurs. We analyzed log data on error-rate, hint-use, and time-spent obtained from two experiments with a Cognitive Tutor for fractions. The goal of the experiments was to compare learning from…

A Fuzzy Logic Framework for Integrating Multiple Learned Models

Energy Technology Data Exchange (ETDEWEB)

Hartog, Bobi Kai Den [Univ. of Nebraska, Lincoln, NE (United States)

1999-03-01

The Artificial Intelligence field of Integrating Multiple Learned Models (IMLM) explores ways to combine results from sets of trained programs. Aroclor Interpretation is an ill-conditioned problem in which trained programs must operate in scenarios outside their training ranges because it is intractable to train them completely. Consequently, they fail in ways related to the scenarios. We developed a general-purpose IMLM solution, the Combiner, and applied it to Aroclor Interpretation. The Combiner's first step, Scenario Identification (M), learns rules from very sparse, synthetic training data consisting of results from a suite of trained programs called Methods. S1 produces fuzzy belief weights for each scenario by approximately matching the rules. The Combiner's second step, Aroclor Presence Detection (AP), classifies each of three Aroclors as present or absent in a sample. The third step, Aroclor Quantification (AQ), produces quantitative values for the concentration of each Aroclor in a sample. AP and AQ use automatically learned empirical biases for each of the Methods in each scenario. Through fuzzy logic, AP and AQ combine scenario weights, automatically learned biases for each of the Methods in each scenario, and Methods' results to determine results for a sample.

An explicit statistical model of learning lexical segmentation using multiple cues

NARCIS (Netherlands)

Çöltekin, Ça ̆grı; Nerbonne, John; Lenci, Alessandro; Padró, Muntsa; Poibeau, Thierry; Villavicencio, Aline

2014-01-01

This paper presents an unsupervised and incremental model of learning segmentation that combines multiple cues whose use by children and adults were attested by experimental studies. The cues we exploit in this study are predictability statistics, phonotactics, lexical stress and partial lexical

An amino-functionalized magnetic framework composite of type Fe3O4-NH2@MIL-101(Cr) for extraction of pyrethroids coupled with GC-ECD.

Science.gov (United States)

He, Xi; Yang, Wei; Li, Sijia; Liu, Yu; Hu, Baichun; Wang, Ting; Hou, Xiaohong

2018-01-24

An amino-functionalized magnetic framework composite of type Fe 3 O 4 -NH 2 @MIL-101(Cr) was synthesized using a solvothermal method. The material was characterized by scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, nitrogen adsorption, and magnetometry. The composite combines the advantages of amino-modified Fe 3 O 4 and MIL-101(Cr). The presence of amino groups facilitates the fairly specific adsorption of pyrethroids. The composite was employed as a sorbent for magnetic solid phase extraction of five pyrethroids from environmental water samples. Following desorption with acidified acetone, the pyrethroids were quantified by gas chromatography with electron capture detection. The detection limits for bifenthrin, fenpropathrin, λ-cyhalothrin, permethrin, and deltamethrin range from 5 to 9 pg·mL -1 . The method is rapid, accurate, and highly sensitive. The molecular interactions and free binding energies between MIL-101(Cr) and the five pyrethroids were calculated by means of molecular docking. Graphical abstract A novel functionalized magnetic framework composite of type Fe 3 O 4 -NH 2 @MIL-101(Cr) was synthesized. It was applied as a sorbent for magnetic solid phase extraction of pyrethroids prior to their quantitation by gas chromatography with electron capture detection. The molecular interactions of analytes and MIL-101(Cr) were studied.

Intellectual enrichment lessens the effect of brain atrophy on learning and memory in multiple sclerosis.

Science.gov (United States)

Sumowski, James F; Wylie, Glenn R; Chiaravalloti, Nancy; DeLuca, John

2010-06-15

Learning and memory impairments are prevalent among persons with multiple sclerosis (MS); however, such deficits are only weakly associated with MS disease severity (brain atrophy). The cognitive reserve hypothesis states that greater lifetime intellectual enrichment lessens the negative impact of brain disease on cognition, thereby helping to explain the incomplete relationship between brain disease and cognitive status in neurologic populations. The literature on cognitive reserve has focused mainly on Alzheimer disease. The current research examines whether greater intellectual enrichment lessens the negative effect of brain atrophy on learning and memory in patients with MS. Forty-four persons with MS completed neuropsychological measures of verbal learning and memory, and a vocabulary-based estimate of lifetime intellectual enrichment. Brain atrophy was estimated with third ventricle width measured from 3-T magnetization-prepared rapid gradient echo MRIs. Hierarchical regression was used to predict learning and memory with brain atrophy, intellectual enrichment, and the interaction between brain atrophy and intellectual enrichment. Brain atrophy predicted worse learning and memory, and intellectual enrichment predicted better learning; however, these effects were moderated by interactions between brain atrophy and intellectual enrichment. Specifically, higher intellectual enrichment lessened the negative impact of brain atrophy on both learning and memory. These findings help to explain the incomplete relationship between multiple sclerosis disease severity and cognition, as the effect of disease on cognition is attenuated among patients with higher intellectual enrichment. As such, intellectual enrichment is supported as a protective factor against disease-related cognitive impairment in persons with multiple sclerosis.

The application of multiple intelligence approach to the learning of human circulatory system

Science.gov (United States)

Kumalasari, Lita; Yusuf Hilmi, A.; Priyandoko, Didik

2017-11-01

The purpose of this study is to offer an alternative teaching approach or strategies which able to accommodate students’ different ability, intelligence and learning style. Also can gives a new idea for the teacher as a facilitator for exploring how to teach the student in creative ways and more student-center activities, for a lesson such as circulatory system. This study was carried out at one private school in Bandung involved eight students to see their responses toward the lesson that delivered by using Multiple Intelligence approach which is include Linguistic, Logical-Mathematical, Visual-Spatial, Musical, Bodily-Kinesthetic, Interpersonal, Intrapersonal, and Naturalistic. Students were test by using MI test based on Howard Gardner’s MI model to see their dominant intelligence. The result showed the percentage of top three ranks of intelligence are Bodily-Kinesthetic (73%), Visual-Spatial (68%), and Logical-Mathematical (61%). The learning process is given by using some different multimedia and activities to engaged their learning style and intelligence such as mini experiment, short clip, and questions. Student response is given by using self-assessment and the result is all students said the lesson gives them a knowledge and skills that useful for their life, they are clear with the explanation given, they didn’t find difficulties to understand the lesson and can complete the assignment given. At the end of the study, it is reveal that the students who are learned by Multiple Intelligence instructional approach have more enhance to the lesson given. It’s also found out that the students participated in the learning process which Multiple Intelligence approach was applied enjoyed the activities and have great fun.

Diagnostic des systèmes de culture à base de mil [ Pennisetum ...

African Journals Online (AJOL)

Objectif : Le présent travail a pour objectif, de faire un état des lieux des systèmes de production à base de mil en Côte d'Ivoire septentrionale afin de proposer de nouvelles pistes d'amélioration. Méthodologie et résultats : L'approche méthodologique s'est reposée sur une enquête auprès des paysans sur le terrain dans ...

Feature and Region Selection for Visual Learning.

Science.gov (United States)

Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando

2016-03-01

Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.

THE EXECUTION INSTANCE OF THE JUDICIAL JUDGEMENTS SENTENCED IN THE LITIGATIONS OF ADMINISTRATIVE CONTENTIOUS

Directory of Open Access Journals (Sweden)

ADRIANA ELENA BELU

2012-05-01

Full Text Available The instance which solved the fund of the litigation rising from an administrative contract differs depending on the material competence sanctioned by law, in contrast to the subject of the commercial law where the execution instance is the court. In this matter the High Court stated in a decision1 that in a first case the competence of solving the legal contest against the proper forced execution and of the legal contest that has in view the explanation of the meaning of spreading and applying the enforceable title which does not proceed from a jurisdiction organ is in the authority of the court. The Law of the Administrative Contentious no 554/2004 defines in Article 2 paragraph 1 letter t the notion of execution instance, providing that this is the instance which solved the fund of the litigation of administrative contentious, so even in the case of the administrative contracts the execution instance is the one which solved the litigation rising from the contract. Corroborating this disposal with the ones existing in articles 22 and 25 in the Law, it can be shown that no matter the instance which decision is an enforceable title, the execution of the law will be done by the instance which solved the fund of the litigation regarding the administrative contentious.

Chelating agent-free, vapor-assisted crystallization method to synthesize hierarchical microporous/mesoporous MIL-125 (Ti).

Science.gov (United States)

McNamara, Nicholas D; Hicks, Jason C

2015-03-11

Titanium-based microporous heterogeneous catalysts are widely studied but are often limited by the accessibility of reactants to active sites. Metal-organic frameworks (MOFs), such as MIL-125 (Ti), exhibit enhanced surface areas due to their high intrinsic microporosity, but the pore diameters of most microporous MOFs are often too small to allow for the diffusion of larger reactants (>7 Å) relevant to petroleum and biomass upgrading. In this work, hierarchical microporous MIL-125 exhibiting significantly enhanced interparticle mesoporosity was synthesized using a chelating-free, vapor-assisted crystallization method. The resulting hierarchical MOF was examined as an active catalyst for the oxidation of dibenzothiophene (DBT) with tert-butyl hydroperoxide and outperformed the solely microporous analogue. This was attributed to greater access of the substrate to surface active sites, as the pores in the microporous analogues were of inadequate size to accommodate DBT. Moreover, thiophene adsorption studies suggested the mesoporous MOF contained larger amounts of unsaturated metal sites that could enhance the observed catalytic activity.

The Effect of Multiple Intelligences on DDL Vocabulary Learning

Directory of Open Access Journals (Sweden)

Asma’a Abdulrazzaq Al-Mahbashi

2017-01-01

Full Text Available Over the past decades, the potential for the direct use of corpora known as data driven learning (DDL has gained great prominence in English language classrooms. A substantial number of empirical studies demonstrated that DDL instruction positively affects students’ learning. As learning outcomes can be affected by individual differences, some researchers have investigated the efficiency of DDL in the light of learners’ different characteristics to determine the type of learners who were more responsive to DDL. The DDL literature has indicated the need for more research addressing for whom DDL best suits. Therefore, the aim of the current study was to examine whether or not learners’ predominant intelligences were significant predictors of DDL learning outcomes. The sample for this study included 30 female EFL Yemeni students at Sana’a University. The study used three primary instruments:  a multiple intelligence questionnaire, a posttest and a delayed test on the vocabulary that was taught using DDL. The result of the correlation analyses between the participants’ three identified predominant intelligences and their performances in the posttest and delayed test showed an insignificant relationship between the variables. The regression analyses results also revealed that the predominant intelligences insignificantly predicted the participants’ posttest and delayed test performances.  Based on these findings, learners’ needs and preferences should be activated and addressed by classroom instructions for creating a diverse and motivating learning environment.

Multiple Learning Approaches in the Professional Development of School Leaders -- Theoretical Perspectives and Empirical Findings on Self-assessment and Feedback

Science.gov (United States)

Huber, Stephan Gerhard

2013-01-01

This article investigates the use of multiple learning approaches and different modes and types of learning in the (continuous) professional development (PD) of school leaders, particularly the use of self-assessment and feedback. First, formats and multiple approaches to professional learning are described. Second, a possible approach to…

Functionalized MIL-101 with imidazolium-based ionic liquids for the cycloaddition of CO2 and epoxides under mild condition

Science.gov (United States)

Liu, Dan; Li, Gang; Liu, Haiou

2018-01-01

A kind of multi-functional sites metal-organic framework (MOF) composite (MIL-101-IMBr) was successfully prepared by post-synthesis modification of MIL-101 with imidazolium-based ionic liquids. The ionic liquids not only functionalize as basic sites but also provide halide anions, which serve as a nucleophile in cycloaddition reaction. The prepared functional MOF materials were characterized by X-ray diffraction, fourier transform infrared spectroscopy, scanning electron microscopy, energy dispersive spectroscopy, N2 adsorption-desorption and CO2 temperature programmed desorption. The results of fourier transform infrared spectroscopy and energy dispersive spectroscopy show that the MIL-101-IMBr composite was successfully synthesized. The N2 adsorption-desorption results clearly demonstrated that the modified composites still preserve high BET surface area and total pore volume. The composite exhibits high catalytic activity for the cycloaddition of CO2 with epoxides under mild and co-catalyst free conditions. The conversion of propylene oxide was 95.8% and the selectivity of cyclic carbonate was 97.6% under 0.8 MPa at 80 °C for 4 h. Moreover, the catalyst can be used for at least five times.

Effets de la microdose sur la production du niébé, du mil et du ...

African Journals Online (AJOL)

Effets de la microdose sur la production du niébé, du mil et du sorgho en fonction la toposéquence. Fatimata Saba, Sibiri Jean Baptiste Taonda, Idriss Serme, Alimata A. Bandaogo, Augustin P. Sourwema, Adama Kabre ...

Remarkable adsorptive removal of nitrogen-containing compounds from a model fuel by a graphene oxide/MIL-101 composite through a combined effect of improved porosity and hydrogen bonding

Energy Technology Data Exchange (ETDEWEB)

Ahmed, Imteaz; Jhung, Sung Hwa, E-mail: sung@knu.ac.kr

2016-08-15

Highlights: • Metal-organic frameworks (MIL-101) were composed with graphene oxide (GnO). • GnO/MIL-101 showed the highest adsorption capacity for indole and quinoline. • Adsorption mechanism was clearly shown based on adsorption results and FTIR. • GnO/MIL-101 might be applied commercially considering capacity and reusability. - Abstract: A composite was prepared by combining a highly porous metal-organic framework (MOF), MIL-101 (Cr-benzenedicarboxylate), and graphene oxide (GnO). The porosity of the composite increased appreciably by the addition of GnO up to a specific amount in the MOF, though further increases in the quantity of GnO was detrimental to porosity. The improved porosity of the GnO/MIL-101 composite was utilized for adsorptive denitrogenation (ADN) of a model fuel where indole (IND) and quinoline (QUI) were used as nitrogen-containing compounds (NCCs). It was found that both IND and QUI showed improved adsorption on the composite compared with pristine MIL-101 or GnO due to the improved porosity of the composite. Interestingly, the improvement in adsorption of IND was much higher than the quantity estimated for the porosity. Importantly, GnO/MIL-101 showed the highest adsorption capacities for NCCs. Irrespective of the studied solvents and co-presence of IND and QUI, the composite adsorbent performed ADN most effectively. This remarkable improvement is explained by the additional mechanism of hydrogen bonding between the surface functional groups of GnO and the hydrogen attached to the nitrogen atom of IND. This hydrogen bonding mechanism is also supported by the results of the adsorption of pyrrole and methylpyrrole. On the other hand, QUI does not show hydrogen-bonding capability, and therefore, its enhanced adsorption originates from only the increased porosity of the adsorbents.

Remarkable adsorptive removal of nitrogen-containing compounds from a model fuel by a graphene oxide/MIL-101 composite through a combined effect of improved porosity and hydrogen bonding

International Nuclear Information System (INIS)

Ahmed, Imteaz; Jhung, Sung Hwa

2016-01-01

Highlights: • Metal-organic frameworks (MIL-101) were composed with graphene oxide (GnO). • GnO/MIL-101 showed the highest adsorption capacity for indole and quinoline. • Adsorption mechanism was clearly shown based on adsorption results and FTIR. • GnO/MIL-101 might be applied commercially considering capacity and reusability. - Abstract: A composite was prepared by combining a highly porous metal-organic framework (MOF), MIL-101 (Cr-benzenedicarboxylate), and graphene oxide (GnO). The porosity of the composite increased appreciably by the addition of GnO up to a specific amount in the MOF, though further increases in the quantity of GnO was detrimental to porosity. The improved porosity of the GnO/MIL-101 composite was utilized for adsorptive denitrogenation (ADN) of a model fuel where indole (IND) and quinoline (QUI) were used as nitrogen-containing compounds (NCCs). It was found that both IND and QUI showed improved adsorption on the composite compared with pristine MIL-101 or GnO due to the improved porosity of the composite. Interestingly, the improvement in adsorption of IND was much higher than the quantity estimated for the porosity. Importantly, GnO/MIL-101 showed the highest adsorption capacities for NCCs. Irrespective of the studied solvents and co-presence of IND and QUI, the composite adsorbent performed ADN most effectively. This remarkable improvement is explained by the additional mechanism of hydrogen bonding between the surface functional groups of GnO and the hydrogen attached to the nitrogen atom of IND. This hydrogen bonding mechanism is also supported by the results of the adsorption of pyrrole and methylpyrrole. On the other hand, QUI does not show hydrogen-bonding capability, and therefore, its enhanced adsorption originates from only the increased porosity of the adsorbents.

Why Are There Developmental Stages in Language Learning? A Developmental Robotics Model of Language Development.

Science.gov (United States)

Morse, Anthony F; Cangelosi, Angelo

2017-02-01

Most theories of learning would predict a gradual acquisition and refinement of skills as learning progresses, and while some highlight exponential growth, this fails to explain why natural cognitive development typically progresses in stages. Models that do span multiple developmental stages typically have parameters to "switch" between stages. We argue that by taking an embodied view, the interaction between learning mechanisms, the resulting behavior of the agent, and the opportunities for learning that the environment provides can account for the stage-wise development of cognitive abilities. We summarize work relevant to this hypothesis and suggest two simple mechanisms that account for some developmental transitions: neural readiness focuses on changes in the neural substrate resulting from ongoing learning, and perceptual readiness focuses on the perceptual requirements for learning new tasks. Previous work has demonstrated these mechanisms in replications of a wide variety of infant language experiments, spanning multiple developmental stages. Here we piece this work together as a single model of ongoing learning with no parameter changes at all. The model, an instance of the Epigenetic Robotics Architecture (Morse et al 2010) embodied on the iCub humanoid robot, exhibits ongoing multi-stage development while learning pre-linguistic and then basic language skills. Copyright © 2016 Cognitive Science Society, Inc.

Chitosan capped nanoscale Fe-MIL-88B-NH2 metal-organic framework as drug carrier material for the pH responsive delivery of doxorubicin

Science.gov (United States)

Sivakumar, P.; Priyatharshni, S.; Nagashanmugam, K. B.; Thanigaivelan, A.; Kumar, K.

2017-08-01

In recent years nanoscale metal-organic frameworks (NMOFs) are contributing as an effective material for use in drug delivery and imaging applications due to their porous surfaces and easy surface modifications. In this work, Fe-MIL-88B-NH2 NMOFs were successfully synthesized on facile hydrothermal route and 2-aminoterephthalic acid (NH2-BDC) was employed as a bridging ligand to activate amine functional groups on the surface. Amine functional groups not only serve as a structure stabilizing agent but also enhance the loading efficiency of the doxorubicin (DOX) anticancer drug. A pH responsive DOX release was realized by introducing a positively charged chitosan (Chi) capping layer. Upon Chi-coating, cleavage was observed in the Fe-MIL-88B-NH2 structure at acidic pH, while gel-like insoluble structure was formed at basic pH. By utilizing this phenomenon, a pH responsive DOX release system was developed by using Chi capped Fe-MIL-88B-NH2 NMOFs under the designed pH (4.0-8.0). The results suggest the Chi capped Fe-MIL-88B-NH2 can be a promising candidate for future pH responsive drug delivery systems.

Integrated model of multiple kernel learning and differential evolution for EUR/USD trading.

Science.gov (United States)

Deng, Shangkun; Sakurai, Akito

2014-01-01

Currency trading is an important area for individual investors, government policy decisions, and organization investments. In this study, we propose a hybrid approach referred to as MKL-DE, which combines multiple kernel learning (MKL) with differential evolution (DE) for trading a currency pair. MKL is used to learn a model that predicts changes in the target currency pair, whereas DE is used to generate the buy and sell signals for the target currency pair based on the relative strength index (RSI), while it is also combined with MKL as a trading signal. The new hybrid implementation is applied to EUR/USD trading, which is the most traded foreign exchange (FX) currency pair. MKL is essential for utilizing information from multiple information sources and DE is essential for formulating a trading rule based on a mixture of discrete structures and continuous parameters. Initially, the prediction model optimized by MKL predicts the returns based on a technical indicator called the moving average convergence and divergence. Next, a combined trading signal is optimized by DE using the inputs from the prediction model and technical indicator RSI obtained from multiple timeframes. The experimental results showed that trading using the prediction learned by MKL yielded consistent profits.

Integrated Model of Multiple Kernel Learning and Differential Evolution for EUR/USD Trading

Directory of Open Access Journals (Sweden)

Shangkun Deng

2014-01-01

Full Text Available Currency trading is an important area for individual investors, government policy decisions, and organization investments. In this study, we propose a hybrid approach referred to as MKL-DE, which combines multiple kernel learning (MKL with differential evolution (DE for trading a currency pair. MKL is used to learn a model that predicts changes in the target currency pair, whereas DE is used to generate the buy and sell signals for the target currency pair based on the relative strength index (RSI, while it is also combined with MKL as a trading signal. The new hybrid implementation is applied to EUR/USD trading, which is the most traded foreign exchange (FX currency pair. MKL is essential for utilizing information from multiple information sources and DE is essential for formulating a trading rule based on a mixture of discrete structures and continuous parameters. Initially, the prediction model optimized by MKL predicts the returns based on a technical indicator called the moving average convergence and divergence. Next, a combined trading signal is optimized by DE using the inputs from the prediction model and technical indicator RSI obtained from multiple timeframes. The experimental results showed that trading using the prediction learned by MKL yielded consistent profits.

Green synthesis and evaluation of an iron-based metal-organic framework MIL-88B for efficient decontamination of arsenate from water.

Science.gov (United States)

Hou, Shuliang; Wu, Yi-Nan; Feng, Lingyu; Chen, Wei; Wang, Ying; Morlay, Catherine; Li, Fengting

2018-02-13

Iron-containing metal-organic frameworks (MOFs) have gradually emerged as environmentally benign alternatives for reducing the levels of environmental contamination because of their advantages, such as readily obtained raw materials with low cost, nontoxic metal source with good biocompatibility, and distinguished physicochemical features e.g., high porosity, framework flexibility, and semiconductor properties. In this study, we reported an innovative strategy for synthesizing an iron-based MOF, MIL-88B, at room temperature. The novelty of this strategy was the use of ethanol as solvent and the pretreatment of dry milling with neither the bulk use of a toxic organic solvent nor the addition of extremely dangerous hydrofluoric acid or strong alkali. The synthesized MIL-88B(Fe) was evaluated as a sorbent for removing arsenate in water and it exhibited high adsorption capacity (156.7 mg g -1 ) at a low dosage. The removal capacity of trace arsenate on MIL-88B(Fe) was 32.3 mg g -1 at a low equilibrium concentration (6.4 μg L -1 ), which satisfied the arsenic threshold for drinking water. The results of Fourier transform infrared and X-ray photoelectron spectroscopy indicated that the As(v) molecules bonded with the oxygen molecules, which were coordinated with FeO clusters in the framework. This work presented the potential use of the up-scaled MIL-88B as an excellent sorbent for purifying arsenate-contaminated water.

Metal organic framework g-C3N4/MIL-53(Fe) heterojunctions with enhanced photocatalytic activity for Cr(VI) reduction under visible light

Science.gov (United States)

Huang, Wenyuan; Liu, Ning; Zhang, Xiaodong; Wu, Minghong; Tang, Liang

2017-12-01

In this study, hybrid nanocomposites based on Fe-based MOF and graphitic carbon nitride (g-C3N4) were developed by a facile solvothermal method. The as-prepared materials were characterized by XRD, FESEM, TEM, XPS and PL analysis. It was showed that the introduction of a certain amount of g-C3N4 on the surface of MIL-53(Fe) would improve the separation and migration rate of photo-induced charges, consequently resulting in the boost of photocatalytic efficiency. Compared with g-C3N4 and MIL-53(Fe), the CMFe composites displayed more excellent visible light-resposive photocatalytic activity for the reduction of Cr(VI). The optimal doping content of g-C3N4 in g-C3N4/MIL-53(Fe) composite was determined to be 3.0 wt%, and it showed about 2.1 and 2.0 times as high photocatalytic efficiency for the reduction of Cr(VI) as that of pure g-C3N4 and MIL-53(Fe), respectively. Meanwhile, the composite exhibited good reusability and stability in the process of cyclic experiments. A possible photocatalytic reaction mechanism was also investigated in detail by the related electrochemical analysis.

Multiple intelligences and underachievement: lessons from individuals with learning disabilities.

Science.gov (United States)

Hearne, D; Stone, S

1995-01-01

The field of learning disabilities, like education in the main, is undergoing calls for reform and restructuring, an upheaval brought on in great part by the forces of opposing paradigms--reductionism and constructivism. In reexamining our past, we must begin to address the failures of traditional deficit models and their abysmally low "cure" rate. Several new theories have arisen that challenge traditional practices in both general and special education classrooms. Particularly influential has been the work of Howard Gardner, whose theory of multiple intelligences calls for a restructuring of our schools to accommodate modes of learning and inquiry with something other than deficit approaches. At least some current research in the field of learning disabilities has begun to focus on creativity and nontraditional strengths and talents that have not been well understood or highly valued by the schools. In this article, we briefly summarize the findings in our search for the talents of students labeled learning disabled, evidence of their abilities, implications of these for the schools, and a beginning set of practical recommendations.

Instance-Based Question Answering

Science.gov (United States)

2006-12-01

cluster-based query expan- sion, learning answering strategies, machine learning in NLP To my wife Monica Abstract During recent years, question...process is typically tedious and involves expertise in crafting and implement- ing these models (e.g. rule-based), utilizing NLP resources, and...questions. For languages that use capitalization (e.g. not Chinese or Arabic ) for named entities, IBQA can make use of NE classing (e.g. “Bob Marley

Outdoor Natural Science Learning with an RFID-Supported Immersive Ubiquitous Learning Environment

Science.gov (United States)

Liu, Tsung-Yu; Tan, Tan-Hsu; Chu, Yu-Ling

2009-01-01

Despite their successful use in many conscientious studies involving outdoor learning applications, mobile learning systems still have certain limitations. For instance, because students cannot obtain real-time, context-aware content in outdoor locations such as historical sites, endangered animal habitats, and geological landscapes, they are…

Propuesta de una planificación estratégica e indicadores de desempeño para la empresa Talleres Mil Usos

OpenAIRE

Gómez Zhiminaicela, Johanna Elizabeth; Redrován Reyes, Mayra Elizabeth

2014-01-01

En el presente trabajo se realizó una propuesta de Planificación Estratégica y medidores de desempeño para la empresa Talleres Mil Usos, se analizó los diferentes parámetros de la Planificación Estratégica y su importancia dentro de las organizaciones, también se planteó objetivos, estrategias e indicadores desempeño para verificar su desempeño laboral. In this work was carried out a Strategic Planning proposal and performance mediators for the company Talleres Mil Usos, looking at differe...

Locality in Generic Instance Search from One Example

NARCIS (Netherlands)

Tao, R.; Gavves, E.; Snoek, C.G.M.; Smeulders, A.W.M.

2014-01-01

This paper aims for generic instance search from a single example. Where the state-of-the-art relies on global image representation for the search, we proceed by including locality at all steps of the method. As the first novelty, we consider many boxes per database image as candidate targets to

Metabolite identification through multiple kernel learning on fragmentation trees.

Science.gov (United States)

Shen, Huibin; Dührkop, Kai; Böcker, Sebastian; Rousu, Juho

2014-06-15

Metabolite identification from tandem mass spectrometric data is a key task in metabolomics. Various computational methods have been proposed for the identification of metabolites from tandem mass spectra. Fragmentation tree methods explore the space of possible ways in which the metabolite can fragment, and base the metabolite identification on scoring of these fragmentation trees. Machine learning methods have been used to map mass spectra to molecular fingerprints; predicted fingerprints, in turn, can be used to score candidate molecular structures. Here, we combine fragmentation tree computations with kernel-based machine learning to predict molecular fingerprints and identify molecular structures. We introduce a family of kernels capturing the similarity of fragmentation trees, and combine these kernels using recently proposed multiple kernel learning approaches. Experiments on two large reference datasets show that the new methods significantly improve molecular fingerprint prediction accuracy. These improvements result in better metabolite identification, doubling the number of metabolites ranked at the top position of the candidates list. © The Author 2014. Published by Oxford University Press.

Development and validity of mathematical learning assessment instruments based on multiple intelligence

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Helmiah Suryani

2017-06-01

Full Text Available This study was aimed to develop and produce an assessment instrument of mathematical learning results based on multiple intelligence. The methods in this study used Borg & Gall-Research and Development approach (Research & Development. The subject of research was 289 students. The results of research: (1 Result of Aiken Analysis showed 58 valid items were between 0,714 to 0,952. (2 Result of the Exploratory on factor analysis indicated the instrument consist of three factors i.e. mathematical logical intelligence-spatial intelligence-and linguistic intelligence. KMO value was 0.661 df 0.780 sig. 0.000 with valid category. This research succeeded to developing the assessment instrument of mathematical learning results based on multiple intelligence of second grade in elementary school with characteristics of logical intelligence of mathematics, spatial intelligence, and linguistic intelligence.

Petits mils, énorme potentiel : diversifiés, nutritifs et adaptés aux ...

International Development Research Centre (IDRC) Digital Library (Canada)

29 avr. 2016 ... Dans les pays en développement, le manque de diversité dans l'alimentation est l'une des principales causes de la malnutrition et de la prévalence de maladies non transmissibles comme le diabète. La culture des petits mils en complément des cultures existantes pourrait faire partie de la solution.

Memory for Instances and Categories in Children and Adults

Science.gov (United States)

Tighe, Thomas J.; And Others

1975-01-01

Two studies of 7-year-olds and college students tested the hypothesis of a developmental difference in the degree to which subjects' memory performance was controlled by categorical properties vs. specific instance properties of test items. (GO)

Correlation of Gas Permeability in a Metal-Organic Framework MIL-101(Cr)-Polysulfone Mixed-Matrix Membrane with Free Volume Measurements by Positron Annihilation Lifetime Spectroscopy (PALS).

Science.gov (United States)

Jeazet, Harold B Tanh; Koschine, Tönjes; Staudt, Claudia; Raetzke, Klaus; Janiak, Christoph

2013-10-25

Hydrothermally stable particles of the metal-organic framework MIL-101(Cr) were incorporated into a polysulfone (PSF) matrix to produce mixed-matrix or composite membranes with excellent dispersion of MIL-101 particles and good adhesion within the polymer matrix. Pure gas (O2, N2, CO2 and CH4) permeation tests showed a significant increase of gas permeabilities of the mixed-matrix membranes without any loss in selectivity. Positron annihilation lifetime spectroscopy (PALS) indicated that the increased gas permeability is due to the free volume in the PSF polymer and the added large free volume inside the MIL-101 particles. The trend of the gas transport properties of the composite membranes could be reproduced by a Maxwell model.

musical mnemonics aid verbal memory and induce learning related brain plasticity in multiple sclerosis

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Michael eThaut

2014-06-01

Full Text Available Recent research in music and brain function has suggested that the temporal pattern structure in music andrhythm can enhance cognitive functions. To further elucidate this question specifically for memory weinvestigated if a musical template can enhance verbal learning in patients with multiple sclerosis and ifmusic assisted learning will also influence short-term, system-level brain plasticity. We measuredsystems-level brain activity with oscillatory network synchronization during music assisted learning.Specifically, we measured the spectral power of 128-channel electroencephalogram (EEG in alpha andbeta frequency bands in 54 patients with multiple sclerosis (MS. The study sample was randomlydivided into 2 groups, either hearing a spoken or musical (sung presentation of Rey’s Auditory VerbalLearning Test (RAVLT. We defined the learning-related synchronization (LRS as the percent changein EEG spectral power from the first time the word was presented to the average of the subsequent wordencoding trials. LRS differed significantly between the music and spoken conditions in low alpha andupper beta bands. Patients in the music condition showed overall better word memory and better wordorder memory and stronger bilateral frontal alpha LRS than patients in the spoken condition. Theevidence suggests that a musical mnemonic recruits stronger oscillatory network synchronization inprefrontal areas in MS patients during word learning. It is suggested that the temporal structure implicitin musical stimuli enhances ‘deep encoding’ during verbal learning and sharpens the timing of neuraldynamics in brain networks degraded by demyelination in MS

Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers.

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Chen, Chi-Hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen

2017-08-01

Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories based on the commonalities across training stimuli. Experiment 2 replicated the first experiment and further examined whether speakers of Mandarin, a language in which final syllables of object names are more predictive of category membership than English, were able to learn words and form object categories when trained with the same type of structures. The results indicate that both groups of learners successfully extracted multiple levels of co-occurrence and used them to learn words and object categories simultaneously. However, marked individual differences in performance were also found, suggesting possible interference and competition in processing the two concurrent streams of regularities. Copyright © 2016 Cognitive Science Society, Inc.

Development of 30-pin connectors for electronic modules of C and I systems for NPP's confirming to customized MIL STD-1344 requirements

International Nuclear Information System (INIS)

Marathe, P.P.; Madala, Kalyan C.; Ramakrishna, P.

2014-01-01

The electrical connectors form an important constituent of C and I system where customized circuits and hardware is required to be configured meeting the Nuclear Power Plant regulatory requirements. C and I hardware has to handle multiple hundreds of I/O's and the system architectures are made in modular construction having C and I system hardware packaged in plug-in electronic modules in the required form factors. In addition if the system has to satisfy customized JSS 55555 requirements meeting stringent shock, vibration and environmental specifications, the connectors used for the electronic modules shall meet the customized MIL STD-1344 requirements and meet reliability target for the system. 30-pin type special connectors for electronic modules and 2x30 (60) pin field cabling connectors were developed meeting the required qualification specifications. (author)

Learning styles and types of multiple intelligences in dental students in their first and tenth semester. Monterrey, Mexico, 2015.

Directory of Open Access Journals (Sweden)

Juan Solís-Soto

2016-04-01

Full Text Available Introduction: Nowadays the incorporation and validation of learning styles and multiple intelligences enable teachers to obtain positive results in academic performance. This new approach has allowed to appreciate personal differences in dental students and strengthen their underdeveloped aspects, improving teaching and learning skills. Objective: To compare learning styles and multiple intelligences in a sample of Mexican dental students in their first and tenth semester. Materials and Methods: A cross-sectional study using questionnaires on learning styles (Honey-Alonso and Gardner’s multiple intelligences was performed. The study was applied to 123 students in their first semester and 157 in their tenth semester at the School of Dentistry at Universidad Autónoma de Nuevo León, evaluating differences between age and sex. Results: Logical-Mathematical intelligence (p=0.044 and Kinesthetic-Corporal intelligence (p=0.042 showed significant differences between students of both semesters, with intrapersonal and interpersonal intelligences being more prevalent. Within learning styles, the prevalent were Reflexive and Theoretical, showing a significant difference between semesters (p=0.005. Conclusion: The most prevalent learning styles in both groups were Reflexive and Theoretical, with no difference between both sexes. The most prevalent types of multiple intelligences in both sexes and groups were interpersonal and intrapersonal.

Academic Achievement from Using the Learning Medium Via a Tablet Device Based on Multiple Intelligences in Grade 1 Elementary Student.

Science.gov (United States)

Nuallaong, Winitra; Nuallaong, Thanya; Preechadirek, Nongluck

2015-04-01

To measure academic achievement of the multiple intelligence-based learning medium via a tablet device. This is a quasi-experimental research study (non-randomized control group pretest-posttest design) in 62 grade 1 elementary students (33 males and 29 females). Thirty-one students were included in an experimental group using purposive sampling by choosing a student who had highest multiple intelligence test scores in logical-mathematic. Then, this group learned by the new learning medium via a tablet which the application matched to logical-mathematic multiple intelligence. Another 31 students were included in a control group using simple random sampling and then learning by recitation. Both groups did pre-test and post-test vocabulary. Thirty students in the experimental group and 24 students in the control group increased post-test scores (odds ratio = 8.75). Both groups made significant increasing in post-test scores. The experimental group increased 9.07 marks (95% CI 8.20-9.93) significantly higher than the control group which increased 4.39 marks (95% CI 3.06-5.72) (t = -6.032, df = 51.481, p learning from either multiple intelligence-based learning medium via a tablet or recitation can contribute academic achievement, learningfrom the new medium contributed more achievement than recitation. The new learning medium group had higher post-test scores 8.75 times than the recitation group. Therefore, the new learning medium is more effective than the traditional recitation in terms of academic achievement. This study has limitations because samples came from the same school. However, the previous study in Thailand did notfind a logical-mathematical multiple intelligence difference among schools. In the future, long-term research to find how the new learning medium affects knowledge retention will support the advantage for life-long learning.

Preparation of MIL-53(Fe)-Reduced Graphene Oxide Nanocomposites by a Simple Self-Assembly Strategy for Increasing Interfacial Contact: Efficient Visible-Light Photocatalysts.

Science.gov (United States)

Liang, Ruowen; Shen, Lijuan; Jing, Fenfen; Qin, Na; Wu, Ling

2015-05-13

In this work, MIL-53(Fe)-reduced graphene oxide (M53-RGO) nanocomposites have been successfully fabricated by a facile and efficient electrostatic self-assembly strategy for improving the interfacial contact between RGO and the MIL-53(Fe). Compared with D-M53-RGO (direct synthesis of MIL-53(Fe)-reduced graphene oxide nanocomposites via one-pot solvothermal approach), M53-RGO nanocomposites exhibit improved photocatalytic activity compared with the D-M53-RGO under identical experimental conditions. After 80 min of visible light illumination (λ ≥ 420 nm), the reduction ratio of Cr(VI) is rapidly increased to 100%, which is also higher than that of reference sample (N-doped TiO2). More significantly, the M53-RGO nanocomposites are proven to perform as bifunctional photocatalysts with considerable activity in the mixed systems (Cr(VI)/dyes) under visible light, which made it a potential candidate for industrial wastewater treatment. Combining with photoelectrochemical analyses, it could be revealed that the introduction of RGO would minimize the recombination of photogenerated electron-hole pairs. Additionally, the effective interfacial contact between MIL-53(Fe) and RGO surface would further accelerate the transfer of photogenerated electrons, leading to the enhancement of photocatalytic activity of M53-RGO toward photocatalytic reactions. Finally, a possible photocatalytic reaction mechanism is also investigated in detail.

Synthesis, characterization and sorption properties of functionalized Cr-MIL-101-X (X=–F, –Cl, –Br, –CH3, –C6H4, –F2, –(CH3)2) materials

International Nuclear Information System (INIS)

Buragohain, Amlan; Couck, Sarah; Van Der Voort, Pascal; Denayer, Joeri F.M.; Biswas, Shyam

2016-01-01

Four existing and three new functionalized chromium terephthalates having MIL-101 topology and denoted as Cr-MIL-101-X (existing ones with X=–F, 1-F; –Cl, 2-Cl; –Br, 3-Br; –CH 3 , 4-CH 3 ; new ones with X=–C 6 H 4 , 5-C 6 H 4 ; –F 2 , 6-F 2 , –(CH 3 ) 2 , 7-(CH 3 ) 2 ) were synthesized under hydrothermal conditions. All the materials except 5-C 6 H 4 could be prepared by a general synthetic route, in which the mixtures of CrO 3 , H 2 BDC-X (BDC=1,4-benzenedicarboxylate) linkers, conc. HCl and water with a molar ratio of 1:1:3.9:222.2 were reacted at 180 °C for 144 h. Compared to the 144 h of synthesis time, three of the compounds, namely 1-Cl, 2-Br and 5-C 6 H 4 , could be prepared in much shorter reaction times (12–18 h at 180–210 °C). The materials possess high thermal stability up to 270–300 °C in an air atmosphere. The activated compounds exhibit significant porosity (S BET range: 1273–2135 m 2 g −1 ). At 0 °C and 1 bar, the CO 2 adsorption capacities of the compounds fall in the 1.7–2.9 mmol g −1 range. Compounds 1-F and 6-F 2 showed enhanced CO 2 uptake values compared to parent Cr-MIL-101. The benzene adsorption capacities of the compounds lie in the range of 66.2–139.5 molecules per unit cell at 50 °C and p/p 0 =0.35. The increased benzene uptake value of 1-F compared to un-functionalized Cr-MIL-101 and 4-CH 3 suggests that the fluorination has induced more hydrophobicity in Cr-MIL-101 as compared to the methylation. - Graphical abstract: Benzene adsorption by seven functionalized Cr-MIL-101-X metal-organic framework (MOF) materials Display Omitted - Highlights: • Seven functionalized Cr-MIL-101-X materials were synthesized solvothermally. • All Cr-MIL-101-X materials exhibited high thermal stability up to 270–300 °C in air. • All Cr-MIL-101-X compounds displayed considerable porosity towards N 2 , CO 2 and benzene. • Mono- and di-fluorinated Cr-MIL-101 materials showed enhanced CO 2 adsorption capacities. �

Characterization of adsorbed water in MIL-53(Al) by FTIR spectroscopy and ab-initio calculations.

Science.gov (United States)

Salazar, J M; Weber, G; Simon, J M; Bezverkhyy, I; Bellat, J P

2015-03-28

Here, we report ab-initio calculations developed with a twofold purpose: understand how adsorbed water molecules alter the infrared spectrum of the metal-organic framework MIL-53(Al) and to investigate which are the associated physico-chemical processes. The analyzed structures are the two anhydrous narrow (np⊘) and large (lp⊘) pore forms and the hydrated narrow pore form (np-H2O) of the MIL-53(Al). For these structures, we determined their corresponding infrared spectra (FTIR) and we identified the vibrational modes associated to the dominant spectral lines. We show that wagging and scissoring modes of CO2 give flexibility to the structure for facilitating the lp⊘- np⊘ transition. In our studies, this transition is identified by eight vibrational modes including the δCH(18a) vibrational mode currently used to identify the mentioned transition. We report an exhaustive band identification of the infrared spectra associated to the analyzed structures. Moreover, the FTIR for the np-H2O structure allowed us to identify four types of water molecules linked to the host structure by one to three hydrogen bonds.

Augmentation de la production de petits mils en Asie du Sud | CRDI ...

International Development Research Centre (IDRC) Digital Library (Canada)

La production de petits mils, en dépit des vertus nutritionnelles de cette céréale, de sa capacité de croître dans des conditions difficiles et de sa facilité de stockage, a toujours été négligée par les politiques agricoles déployées en Asie du Sud. Ces dernières, en effet, ont privilégié les cultures de rente et les céréales comme ...

Effect of Amine-Functionalized MIL-53 Metal Organic Frameworks on the Performance of Poly(4-methyl-1-pentyne Membrane in CO2/CH4 Separation Gas Mixture

Directory of Open Access Journals (Sweden)

Reza Abedini

2015-06-01

Full Text Available The effect of NH2-MIL 53 metal organic framework (MOF on gas transport properties of poly(4-methyl-1-pentyne (PMP was investigated. Various characterization methods such as FTIR, DSC, SEM and gas adsorption test as well as a series of CO2/CH4 gas separation tests (i.e., pure and mixed gas test were conducted in order to determine the effect of ligand functionalization (–NH2 on the properties of the prepared mixed matrix membranes and their gas transport characteristics. The results of DSC showed that glass transition temperature (Tg increased by increasing NH2-MIL 53 loading. The SEM images also demonstrated that the NH2-MIL 53 particles were dispersed well in the PMP matrix with no noticeable agglomeration. The gas adsorption test of NH2-MIL 53 particles revealed there was a selective adsorption behavior with respect to CO2. It was also found that, incorporation of NH2-MIL 53 into the PMP resulted in an increase in gas permeability (especially towards CO2 and a higher CO2/CH4 selectivity. Adding 30 wt% NH2-MIL 53 into the polymer matrix increased CO2 permeability and CO2/CH4 selectivity of the mixed gas from 83.35 to 210.21 barrer and 7.61 to 19.88, respectively. Rising the temperature from 30 to 60°C led to the permeability increment of both CO2 and CH4 in the mixed gas test, while the CO2/CH4 selectivity decreased. Moreover, the results showed that amino groups required no regeneration and their performance did not decline during 120 h of permeation test. A comparison between the permeation data and those calculated from permeation models revealed that the Bruggeman model could fit the CO2 permeability data better than the Maxwell and Lewis models.

The MORPG-Based Learning System for Multiple Courses: A Case Study on Computer Science Curriculum

Science.gov (United States)

Liu, Kuo-Yu

2015-01-01

This study aimed at developing a Multiplayer Online Role Playing Game-based (MORPG) Learning system which enabled instructors to construct a game scenario and manage sharable and reusable learning content for multiple courses. It used the curriculum of "Introduction to Computer Science" as a study case to assess students' learning…

Juegos de palabras y música en El Cortesano de Luis Milán

Directory of Open Access Journals (Sweden)

Alfonso Colella

2015-12-01

Full Text Available Este artículo analiza cómo, en El Cortesano, la música y la actuación musical se ven fuertemente afectadas por el carácter burlesco e ingenioso de todos los personajes que frecuentan las reuniones de Fernando de Aragón y de la reina Germana de Foix. Por lo tanto, el músico Milán, para cumplir con todas las expectativas de este mundo del entretenimiento y del juego, debe basarse necesariamente en una serie de opciones interpretativas que permitan actuaciones rápidas en función de las demandas de su público. Lo que emerge es una imagen del músico y de la música diferente de lo que se esperaría normalmente. En una sociedad de este tipo, no cuenta la música entendida en su estética y aspectos técnicos, sino la capacidad de gestionar las apariencias y someterse a las pruebas y los mandatos impuestos por los rituales del juego cortesano. Tenemos muchos ejemplos en que Milán se muestra con pasividad y sumisión. Pero es normal, porque esto entra en los códigos de la vida de la corte. This article takes into consideration El Cortesano (1561 by Luis Milán: in this text the musical performance is strongly influenced by the playful attitudes of the individuals who attended the court meetings of Fernando de Aragón and Germana de Foix. Therefore, the musician has to keep in mind every expectation of courtly entertainment and gaming, and morevoer he must open his interpretative options to meet also the demands of the public. What emerges is a picture of the musician and his music that is different from what one would expect in another social context. In such aristocratic society as the Duke of Calabria, music was not understood only in terms of its aesthetic values and technical aspects, but it also required that the player accepted the rituals of the courtly game.

A Mobile Service Oriented Multiple Object Tracking Augmented Reality Architecture for Education and Learning Experiences

Science.gov (United States)

Rattanarungrot, Sasithorn; White, Martin; Newbury, Paul

2014-01-01

This paper describes the design of our service-oriented architecture to support mobile multiple object tracking augmented reality applications applied to education and learning scenarios. The architecture is composed of a mobile multiple object tracking augmented reality client, a web service framework, and dynamic content providers. Tracking of…

Nonlinear Semi-Supervised Metric Learning Via Multiple Kernels and Local Topology.

Science.gov (United States)

Li, Xin; Bai, Yanqin; Peng, Yaxin; Du, Shaoyi; Ying, Shihui

2018-03-01

Changing the metric on the data may change the data distribution, hence a good distance metric can promote the performance of learning algorithm. In this paper, we address the semi-supervised distance metric learning (ML) problem to obtain the best nonlinear metric for the data. First, we describe the nonlinear metric by the multiple kernel representation. By this approach, we project the data into a high dimensional space, where the data can be well represented by linear ML. Then, we reformulate the linear ML by a minimization problem on the positive definite matrix group. Finally, we develop a two-step algorithm for solving this model and design an intrinsic steepest descent algorithm to learn the positive definite metric matrix. Experimental results validate that our proposed method is effective and outperforms several state-of-the-art ML methods.

Data-aware remaining time prediction of business process instances

NARCIS (Netherlands)

Polato, M.; Sperduti, A.; Burattin, A.; Leoni, de M.

2014-01-01

Accurate prediction of the completion time of a business process instance would constitute a valuable tool when managing processes under service level agreement constraints. Such prediction, however, is a very challenging task. A wide variety of factors could influence the trend of a process

Helping Children Learn Mathematics through Multiple Intelligences and Standards for School Mathematics.

Science.gov (United States)

Adams, Thomasenia Lott

2001-01-01

Focuses on the National Council of Teachers of Mathematics 2000 process-oriented standards of problem solving, reasoning and proof, communication, connections, and representation as providing a framework for using the multiple intelligences that children bring to mathematics learning. Presents ideas for mathematics lessons and activities to…

Fe3O4 and metal-organic framework MIL-101(Fe) composites catalyze luminol chemiluminescence for sensitively sensing hydrogen peroxide and glucose.

Science.gov (United States)

Qian Tang, Xue; Dan Zhang, Yi; Wei Jiang, Zhong; Mei Wang, Dong; Zhi Huang, Cheng; Fang Li, Yuan

2018-03-01

In this work, Fe 3 O 4 and metal-organic framework MIL-101(Fe) composites (Fe 3 O 4 /MIL-101(Fe)) was demonstrated to possess excellent catalytic property to directly catalyze luminol chemiluminescence without extra oxidants. We utilized Fe 3 O 4 /MIL-101(Fe) to develop a ultra-sensitive quantitative analytical method for H 2 O 2 and glucose. The possible mechanism of the chemiluminescence reaction had been investigated. Under optimal conditions, the relative chemiluminescence intensity was linearly proportional to the logarithm of H 2 O 2 concentration in the range of 5-150nM with a limit of detection of 3.7nM (signal-to-noise ratio = 3), and glucose could be linearly detected in the range from 5 to 100nM and the detection limit was 4.9nM (signal-to-noise ratio = 3). Furthermore, the present approach was successfully applied to quantitative determination of H 2 O 2 in medical disinfectant and glucose in human serum samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Fabrication, interfacial characterization and mechanical properties of continuous Al{sub 2}O{sub 3} ceramic fiber reinforced Ti/Al{sub 3}Ti metal-intermetallic laminated (CCFR-MIL) composite

Energy Technology Data Exchange (ETDEWEB)

Han, Yuqiang; Lin, Chunfa; Han, Xiaoxiao; Chang, Yunpeng; Guo, Chunhuan, E-mail: guochunhuan@hrbeu.edu.cn; Jiang, Fengchun, E-mail: fengchunjiang@hrbeu.edu.cn

2017-03-14

Continuous Al{sub 2}O{sub 3} ceramic fiber reinforced Ti/Al{sub 3}Ti metal-intermetallic laminated (CCFR-MIL) composite was fabricated using a vacuum hot pressing (VHP) sintering method and followed by hot isostatic pressing (HIP). The microstructure characteristics of the interfaces between Ti and Al{sub 3}Ti, as well as Al{sub 2}O{sub 3} fiber and Al{sub 3}Ti intermetallic were analyzed by scanning electron microscopy (SEM). Elemental distribution in the interfacial reaction zones were quantitatively examined by energy-dispersive spectroscopy (EDS). The phases in the composite were identified by X-ray diffractometer (XRD). The mechanical properties of the CCFR-MIL composite were measured using compression and tensile tests under quasi-static strain rate. The experimental results indicated that the residual Al was found in Al{sub 3}Ti intermetallic layer of CCFR-MIL composite. The interfacial reactions occurred during HIP and the reaction products were determined to be Al{sub 2}Ti, TiSi{sub 2}, TiO{sub 2} and Al{sub 2}SiO{sub 5} phases. Compared to Ti/Al{sub 3}Ti MIL composite without fiber reinforcement, both the strength and failure strain of CCFR-MIL composite under both compressive and tensile stress states increased due to the contribution of the continuous ceramic Al{sub 2}O{sub 3} fiber.

Formation Learning Control of Multiple Autonomous Underwater Vehicles With Heterogeneous Nonlinear Uncertain Dynamics.

Science.gov (United States)

Yuan, Chengzhi; Licht, Stephen; He, Haibo

2017-09-26

In this paper, a new concept of formation learning control is introduced to the field of formation control of multiple autonomous underwater vehicles (AUVs), which specifies a joint objective of distributed formation tracking control and learning/identification of nonlinear uncertain AUV dynamics. A novel two-layer distributed formation learning control scheme is proposed, which consists of an upper-layer distributed adaptive observer and a lower-layer decentralized deterministic learning controller. This new formation learning control scheme advances existing techniques in three important ways: 1) the multi-AUV system under consideration has heterogeneous nonlinear uncertain dynamics; 2) the formation learning control protocol can be designed and implemented by each local AUV agent in a fully distributed fashion without using any global information; and 3) in addition to the formation control performance, the distributed control protocol is also capable of accurately identifying the AUVs' heterogeneous nonlinear uncertain dynamics and utilizing experiences to improve formation control performance. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed results.

Competence-based multiple learning paths: on the road of implementation

Directory of Open Access Journals (Sweden)

María Dolores de Prada

2014-12-01

Full Text Available This article presents the results of an action-research implementation project based on a system that weaves together five different routes to facilitate the development of competences through the use of multiple learning paths for primary and secondary teachers. The first and initial results that the article deals with relate to the experience of math teachers for ages 11 to 14. Other levels and other fields are in the process of being developed. The article deals briefly with the justification, the background and the fundamental principles that underpin the research methodology and introduces a number of elements such as the method followed by the research, the resources and the materials used as well as the results obtained at the end of the second year of this experience. It also justifies the model chosen and the criteria and strategies selected for its reliability and verification. In addition, it provides significant elements of reflection about a number of burning issues: The development of a new profile of the “teacher” in a studentcentred system and the implementation system to be followed, the importance of multiple but integrated learning paths and the relevance as well as the reflection on real cases of competence evaluation.

Facile Synthesis of Potassium Poly(heptazine imide) (PHIK)/Ti-Based Metal-Organic Framework (MIL-125-NH2) Composites for Photocatalytic Applications.

Science.gov (United States)

Rodríguez, Nicolás A; Savateev, Aleksandr; Grela, María A; Dontsova, Dariya

2017-07-12

Photocatalytically active composites comprising potassium poly(heptazine imide) (PHIK) and a Ti-based metal-organic framework (MOF, MIL-125-NH 2 ) are prepared in situ by simply dispersing both materials in water. The driving forces of composite formation are the electrostatic interactions between the solids and the diffusion of potassium ions from PHIK to MIL-125-NH 2 . This mechanism implies that other composites of poly(heptazine imide) salts and different MOFs bearing positive surface charge can potentially be obtained in a similar fashion. The suggested strategy thus opens a new avenue for the facile synthesis of such materials. The composites are shown to have a superior photocatalytic activity in Rhodamine B degradation under blue light irradiation. The reaction rate is doubled compared to that of pure MOF compound and is 7 times higher than the activity of the pristine PHIK. The results of the electron paramagnetic resonance (EPR) investigations and the analysis of the electronic structures of the solids suggest the electron transfer from MIL-125-NH 2 to PHIK in the composite. The possible pathways for the dye degradation and the rationalization of the increased activity of the composites are elaborated.

Ship-in-a-bottle CMPO in MIL-101(Cr) for selective uranium recovery from aqueous streams through adsorption.

Science.gov (United States)

De Decker, Jeroen; Folens, Karel; De Clercq, Jeriffa; Meledina, Maria; Van Tendeloo, Gustaaf; Du Laing, Gijs; Van Der Voort, Pascal

2017-08-05

Mesoporous MIL-101(Cr) is used as host for a ship-in-a-bottle type adsorbent for selective U(VI) recovery from aqueous environments. The acid-resistant cage-type MOF is built in-situ around N,N-Diisobutyl-2-(octylphenylphosphoryl)acetamide (CMPO), a sterically demanding ligand with high U(VI) affinity. This one-step procedure yields an adsorbent which is an ideal compromise between homogeneous and heterogeneous systems, where the ligand can act freely within the pores of MIL-101, without leaching, while the adsorbent is easy separable and reusable. The adsorbent was characterized by XRD, FTIR spectroscopy, nitrogen adsorption, XRF, ADF-STEM and EDX, to confirm and quantify the successful encapsulation of the CMPO in MIL-101, and the preservation of the host. Adsorption experiments with a central focus on U(VI) recovery were performed. Very high selectivity for U(VI) was observed, while competitive metal adsorption (rare earths, transition metals...) was almost negligible. The adsorption capacity was calculated at 5.32mg U/g (pH 3) and 27.99mg U/g (pH 4), by fitting equilibrium data to the Langmuir model. Adsorption kinetics correlated to the pseudo-second-order model, where more than 95% of maximum uptake is achieved within 375min. The adsorbed U(VI) is easily recovered by desorption in 0.1M HNO 3 . Three adsorption/desorption cycles were performed. Copyright © 2017 Elsevier B.V. All rights reserved.

Direction-of-arrival estimation for co-located multiple-input multiple-output radar using structural sparsity Bayesian learning

International Nuclear Information System (INIS)

Wen Fang-Qing; Zhang Gong; Ben De

2015-01-01

This paper addresses the direction of arrival (DOA) estimation problem for the co-located multiple-input multiple-output (MIMO) radar with random arrays. The spatially distributed sparsity of the targets in the background makes compressive sensing (CS) desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to accurately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio (SNR) scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification (MUSIC) algorithm and other CS recovery algorithms. (paper)

HKUST-1 Membranes Anchored on Porous Substrate by Hetero MIL-110 Nanorod Array Seeds.

Science.gov (United States)

Mao, Yiyin; Cao, Wei; Li, Junwei; Sun, Luwei; Peng, Xinsheng

2013-09-02

Great anchors and seeds: Hetero-seeding growth processes and anchored nanorod arrays were successfully utilized in the synthesis of HKUST-1 membranes. These arrays were firmly anchored on porous substrates by using a MIL-110 nanorod array as both the anchor and seed. The resulting HKUST-1 membranes demonstrated good separation factors for binary gases exceeding the Knudson selectivity. Copyright © 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim.

Effets de la microdose sur la production du niébé, du mil et du ...

African Journals Online (AJOL)

respectivement pour le sorgho, le mil et le niébé comparativement au témoin. La microdose a été .... Les prix utilisés sont celui du marché local au moment des semis pour les engrais soit 17500 FCFA pour NPK et ..... Projet « Transfert de la.

Simultaneous processing of information on multiple errors in visuomotor learning.

Science.gov (United States)

Kasuga, Shoko; Hirashima, Masaya; Nozaki, Daichi

2013-01-01

The proper association between planned and executed movements is crucial for motor learning because the discrepancies between them drive such learning. Our study explored how this association was determined when a single action caused the movements of multiple visual objects. Participants reached toward a target by moving a cursor, which represented the right hand's position. Once every five to six normal trials, we interleaved either of two kinds of visual perturbation trials: rotation of the cursor by a certain amount (±15°, ±30°, and ±45°) around the starting position (single-cursor condition) or rotation of two cursors by different angles (+15° and -45°, 0° and 30°, etc.) that were presented simultaneously (double-cursor condition). We evaluated the aftereffects of each condition in the subsequent trial. The error sensitivity (ratio of the aftereffect to the imposed visual rotation) in the single-cursor trials decayed with the amount of rotation, indicating that the motor learning system relied to a greater extent on smaller errors. In the double-cursor trials, we obtained a coefficient that represented the degree to which each of the visual rotations contributed to the aftereffects based on the assumption that the observed aftereffects were a result of the weighted summation of the influences of the imposed visual rotations. The decaying pattern according to the amount of rotation was maintained in the coefficient of each imposed visual rotation in the double-cursor trials, but the value was reduced to approximately 40% of the corresponding error sensitivity in the single-cursor trials. We also found a further reduction of the coefficients when three distinct cursors were presented (e.g., -15°, 15°, and 30°). These results indicated that the motor learning system utilized multiple sources of visual error information simultaneously to correct subsequent movement and that a certain averaging mechanism might be at work in the utilization process.

Trivalent Chromium Process (TCP) as a Sealer for MIL-A-8625F Type II, IIB, and IC Anodic Coatings

National Research Council Canada - National Science Library

Matzdorf, Craig; Beck, Erin; Hilgeman, Amy; Prado, Ruben

2008-01-01

This report documents evaluations of trivalent chromium compositions (TCP) as sealers for MIL-A-8625F Type II, IIB, and IC anodic coatings conducted from March 2001 through December 2007 by Materials Engineering...

Instances or Sequences? Improving the State of the Art of Qualitative Research

Directory of Open Access Journals (Sweden)

David Silverman

2005-09-01

Full Text Available Numbers apparently talk. With few numbers, qualitative researchers appear to rely on examples or instances to support their analysis. Hence research reports routinely display data extracts which serve as telling instances of some claimed phenomenon. However, the use of such an evidential base rightly provokes the charge of (possible anecdotalism, i.e. choosing just those extracts which support your argument. I suggest that this methodological problem is best addressed by returning to those features of our theoretical roots which tend to distinguish what we do from the work of quantitative social scientists. Although SAUSSURE is most cited in linguistics and structural anthropology, he provides a simple rule that applies to us all. In a rebuke to our reli­ance on instances, SAUSSURE tells us "no mean­ing exists in a single item". Everything depends upon how single items (elements are articulated. One everyday activity in which the social world is articulated is through the construction of se­quences. Just as participants attend to the se­quential placing of interactional "events", so should social scientists. Using examples drawn from focus groups, fieldnotes and audiotapes, I argue that the identification of such sequences rather than the citing of instances should constitute a prime test for the adequacy of any claim about qualitative data. URN: urn:nbn:de:0114-fqs0503301

Correlation of Gas Permeability in a Metal-Organic Framework MIL-101(Cr)–Polysulfone Mixed-Matrix Membrane with Free Volume Measurements by Positron Annihilation Lifetime Spectroscopy (PALS)

Science.gov (United States)

Jeazet, Harold B. Tanh; Koschine, Tönjes; Staudt, Claudia; Raetzke, Klaus; Janiak, Christoph

2013-01-01

Hydrothermally stable particles of the metal-organic framework MIL-101(Cr) were incorporated into a polysulfone (PSF) matrix to produce mixed-matrix or composite membranes with excellent dispersion of MIL-101 particles and good adhesion within the polymer matrix. Pure gas (O2, N2, CO2 and CH4) permeation tests showed a significant increase of gas permeabilities of the mixed-matrix membranes without any loss in selectivity. Positron annihilation lifetime spectroscopy (PALS) indicated that the increased gas permeability is due to the free volume in the PSF polymer and the added large free volume inside the MIL-101 particles. The trend of the gas transport properties of the composite membranes could be reproduced by a Maxwell model. PMID:24957061

A Neural Network Model to Learn Multiple Tasks under Dynamic Environments

Science.gov (United States)

Tsumori, Kenji; Ozawa, Seiichi

When environments are dynamically changed for agents, the knowledge acquired in an environment might be useless in future. In such dynamic environments, agents should be able to not only acquire new knowledge but also modify old knowledge in learning. However, modifying all knowledge acquired before is not efficient because the knowledge once acquired may be useful again when similar environment reappears and some knowledge can be shared among different environments. To learn efficiently in such environments, we propose a neural network model that consists of the following modules: resource allocating network, long-term & short-term memory, and environment change detector. We evaluate the model under a class of dynamic environments where multiple function approximation tasks are sequentially given. The experimental results demonstrate that the proposed model possesses stable incremental learning, accurate environmental change detection, proper association and recall of old knowledge, and efficient knowledge transfer.

Basic life support and children with profound and multiple learning disabilities.

Science.gov (United States)

Cash, Stefan; Shinnick-Page, Andrea

2008-10-01

Nurses and other carers of people with learning disabilities must be able to manage choking events and perform basic life support effectively. UK guidelines for assessment of airway obstruction and for resuscitation do not take account of the specific needs of people with profound multiple learning disability. For example, they fail to account for inhibited gag and coughing reflexes, limited body movements or chest deformity. There are no national guidelines to assist in clinical decisions and training for nurses and carers. Basic life support training for students of learning disability nursing at Birmingham City University is supplemented to address these issues. The authors ask whether such training should be provided for all nurses including those caring for children and young people. They also invite comment and discussion on questions related to chest compression and training in basic life support for a person in a seated position.

Multiple Kernel Learning for adaptive graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan; AbdulJabbar, Mustafa Abdulmajeed

2012-01-01

Nonnegative Matrix Factorization (NMF) has been continuously evolving in several areas like pattern recognition and information retrieval methods. It factorizes a matrix into a product of 2 low-rank non-negative matrices that will define parts-based, and linear representation of non-negative data. Recently, Graph regularized NMF (GrNMF) is proposed to find a compact representation, which uncovers the hidden semantics and simultaneously respects the intrinsic geometric structure. In GNMF, an affinity graph is constructed from the original data space to encode the geometrical information. In this paper, we propose a novel idea which engages a Multiple Kernel Learning approach into refining the graph structure that reflects the factorization of the matrix and the new data space. The GrNMF is improved by utilizing the graph refined by the kernel learning, and then a novel kernel learning method is introduced under the GrNMF framework. Our approach shows encouraging results of the proposed algorithm in comparison to the state-of-the-art clustering algorithms like NMF, GrNMF, SVD etc.

Generalized query-based active learning to identify differentially methylated regions in DNA.

Science.gov (United States)

Haque, Md Muksitul; Holder, Lawrence B; Skinner, Michael K; Cook, Diane J

2013-01-01

Active learning is a supervised learning technique that reduces the number of examples required for building a successful classifier, because it can choose the data it learns from. This technique holds promise for many biological domains in which classified examples are expensive and time-consuming to obtain. Most traditional active learning methods ask very specific queries to the Oracle (e.g., a human expert) to label an unlabeled example. The example may consist of numerous features, many of which are irrelevant. Removing such features will create a shorter query with only relevant features, and it will be easier for the Oracle to answer. We propose a generalized query-based active learning (GQAL) approach that constructs generalized queries based on multiple instances. By constructing appropriately generalized queries, we can achieve higher accuracy compared to traditional active learning methods. We apply our active learning method to find differentially DNA methylated regions (DMRs). DMRs are DNA locations in the genome that are known to be involved in tissue differentiation, epigenetic regulation, and disease. We also apply our method on 13 other data sets and show that our method is better than another popular active learning technique.

The Learning Styles and Multiple Intelligences of EFL College Students in Kuwait

Science.gov (United States)

Alrabah, Sulaiman; Wu, Shu-hua; Alotaibi, Abdullah M.

2018-01-01

The study aimed to investigate the learning styles and multiple intelligences of English as foreign language (EFL) college-level students. "Convenience sampling" (Patton, 2015) was used to collect data from a population of 250 students enrolled in seven different academic departments at the College of Basic Education in Kuwait. The data…

The Relationship between Multiplication Fact Speed-Recall and Fluency and Higher Level Mathematics Learning with Eighth Grade Middle School Students

Science.gov (United States)

Curry, Steven James

2012-01-01

This quantitative study investigated relationships between higher level mathematics learning and multiplication fact fluency, multiplication fact speed-recall, and reading grade equivalency of eighth grade students in Algebra I and Pre-Algebra. Higher level mathematics learning was indicated by an average score of 80% or higher on first and second…

Robust Visual Knowledge Transfer via Extreme Learning Machine Based Domain Adaptation.

Science.gov (United States)

Zhang, Lei; Zhang, David

2016-08-10

We address the problem of visual knowledge adaptation by leveraging labeled patterns from source domain and a very limited number of labeled instances in target domain to learn a robust classifier for visual categorization. This paper proposes a new extreme learning machine based cross-domain network learning framework, that is called Extreme Learning Machine (ELM) based Domain Adaptation (EDA). It allows us to learn a category transformation and an ELM classifier with random projection by minimizing the -norm of the network output weights and the learning error simultaneously. The unlabeled target data, as useful knowledge, is also integrated as a fidelity term to guarantee the stability during cross domain learning. It minimizes the matching error between the learned classifier and a base classifier, such that many existing classifiers can be readily incorporated as base classifiers. The network output weights cannot only be analytically determined, but also transferrable. Additionally, a manifold regularization with Laplacian graph is incorporated, such that it is beneficial to semi-supervised learning. Extensively, we also propose a model of multiple views, referred as MvEDA. Experiments on benchmark visual datasets for video event recognition and object recognition, demonstrate that our EDA methods outperform existing cross-domain learning methods.

Learning with multiple representations: an example of a revision lesson in mechanics

Science.gov (United States)

Wong, Darren; Poo, Sng Peng; Eng Hock, Ng; Loo Kang, Wee

2011-03-01

We describe an example of learning with multiple representations in an A-level revision lesson on mechanics. The context of the problem involved the motion of a ball thrown vertically upwards in air and studying how the associated physical quantities changed during its flight. Different groups of students were assigned to look at the ball's motion using various representations: motion diagrams, vector diagrams, free-body diagrams, verbal description, equations and graphs, drawn against time as well as against displacement. Overall, feedback from students about the lesson was positive. We further discuss the benefits of using computer simulation to support and extend student learning.

First instance competence of the Higher Administrative Court

International Nuclear Information System (INIS)

Anon.

1988-01-01

(1) An interlocutory judgement can determine the admissibility of a legal action, also with regard to single procedural prerequisites (following BVerwG decision 14, 273). (2) The first instance competence for disputes about the dismantling of a decommissioned nuclear installation lies with the administrative courts and not with the higher administrative courts. Federal Administrative Court, decision of May 19, 1988 - 7 C 43.88 - (VGH Munich). (orig.) [de

Thermally driven refrigeration by methanol adsorption on coatings of HKUST-1 and MIL-101(Cr)

International Nuclear Information System (INIS)

Kummer, Harry; Baumgartner, Max; Hügenell, Philipp; Fröhlich, Dominik; Henninger, Stefan K.; Gläser, Roger

2017-01-01

Highlights: • A novel approach of shaping MOFs as coatings on Al-substrates used as HX materials. • The efficiency of HKUST-1 and MIL-101(Cr) for refrigeration via Methanol sorption. • The thermal stability of the MOF coatings under application relevant conditions. • Focus on early implementation by use of commercially and pre-industrially MOFs. • Modelling of sorption uptakes under application conditions for apparatus design. - Abstract: A new and versatile binder-based metal organic framework-(MOF-) coating enables efficient use in fast-cycle adsorption chillers for cooling and refrigeration applications. Two different adsorbents were presented, HKUST-1 and Mil-101(Cr), with promising methanol adsorption characteristics and high loading capacities up to 1.22 g g"−"1. Polysiloxane-based coatings containing 65 and 80 wt% of the MOF adsorbents were produced and the adsorption characteristics were studied before and after extensive thermal treatment over 1000 cycles between 20 °C and 130 °C under methanol atmosphere by thermogravimetric analysis and X-ray diffractometry. Using the Dubinin-Astakhov approach, possible methanol loading lifts in a refrigeration process under different application conditions were quantified.

Learning Effects of Interactive Whiteboard Pedagogy for Students in Taiwan from the Perspective of Multiple Intelligences

Science.gov (United States)

Chen, Hong-Ren; Chiang, Chih-Hao; Lin, Wen-Shan

2013-01-01

With the rapid progress in information technology, interactive whiteboards have become IT-integrated in teaching activities. The theory of multiple intelligences argues that every person possesses multiple intelligences, emphasizing learners' cognitive richness and the possible role of these differences in enhanced learning. This study is the…

H5PV2Mo10O40 encapsulated in MIL-101(Cr): facile synthesis and characterization of rationally designed composite materials for efficient decontamination of sulfur mustard.

Science.gov (United States)

Li, Yanqin; Gao, Qi; Zhang, Lijuan; Zhou, Yunshan; Zhong, Yuxu; Ying, Ying; Zhang, Mingcai; Huang, Chunqian; Wang, Yong'an

2018-04-24

Currently extensive effort is compulsively expended to decontaminate efficiently banned chemical war agents. In this work, H5PV2Mo10O40 molecules have been encapsulated in mesoporous MIL-101(Cr), which features two types of mesoporous cages (internal diameters of 29 Å and 34 Å) and microporous windows (diameters of 12 Å and 16 Å), leading to the formation of a new composite H5PV2Mo10O40@MIL-101(Cr) through a simple impregnation method. The composite was characterized thoroughly by elemental analysis, FT-IR spectroscopy, powder X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy, TG/DTA, and textural analysis thereby confirming the encapsulation of the H5PV2Mo10O40 into MIL-101(Cr). The decontamination efficiency of sulfur mustard (4 μL HD in 40 μL of petroleum ether) by 20 mg of the composite is found to be 97.39% in 120 min under ambient conditions. GC-MS analysis on the decontaminated products using 2-chloroethyl ethyl sulfide (CEES), which has been widely used as a simulant of sulfur mustard, showed that MIL-101(Cr) just decontaminates CEES by adsorption, while CEES can be decontaminated under ambient conditions by a synergetic combination of adsorption of MIL-101(Cr) and subsequent chemical oxidation degradation to nontoxic 2-chloroethyl ethyl sulfoxide (CEESO) due to the presence of highly dispersed H5PV2Mo10O40 within the composites.

Elucidating the breathing of the metal-organic framework MIL-53(Sc) with ab initio molecular dynamics simulations and in situ X-ray powder diffraction experiments.

Science.gov (United States)

Chen, Linjiang; Mowat, John P S; Fairen-Jimenez, David; Morrison, Carole A; Thompson, Stephen P; Wright, Paul A; Düren, Tina

2013-10-23

Ab initio molecular dynamics (AIMD) simulations have been used to predict structural transitions of the breathing metal-organic framework (MOF) MIL-53(Sc) in response to changes in temperature over the range 100-623 K and adsorption of CO2 at 0-0.9 bar at 196 K. The method has for the first time been shown to predict successfully both temperature-dependent structural changes and the structural response to variable sorbate uptake of a flexible MOF. AIMD employing dispersion-corrected density functional theory accurately simulated the experimentally observed closure of MIL-53(Sc) upon solvent removal and the transition of the empty MOF from the closed-pore phase to the very-narrow-pore phase (symmetry change from P2(1)/c to C2/c) with increasing temperature, indicating that it can directly take into account entropic as well as enthalpic effects. We also used AIMD simulations to mimic the CO2 adsorption of MIL-53(Sc) in silico by allowing the MIL-53(Sc) framework to evolve freely in response to CO2 loadings corresponding to the two steps in the experimental adsorption isotherm. The resulting structures enabled the structure determination of the two CO2-containing intermediate and large-pore phases observed by experimental synchrotron X-ray diffraction studies with increasing CO2 pressure; this would not have been possible for the intermediate structure via conventional methods because of diffraction peak broadening. Furthermore, the strong and anisotropic peak broadening observed for the intermediate structure could be explained in terms of fluctuations of the framework predicted by the AIMD simulations. Fundamental insights from the molecular-level interactions further revealed the origin of the breathing of MIL-53(Sc) upon temperature variation and CO2 adsorption. These simulations illustrate the power of the AIMD method for the prediction and understanding of the behavior of flexible microporous solids.

Integrating Multiple Intelligences and Learning Styles on Solving Problems, Achievement in, and Attitudes towards Math in Six Graders with Learning Disabilities in Cooperative Groups

Science.gov (United States)

Eissa, Mourad Ali; Mostafa, Amaal Ahmed

2013-01-01

This study investigated the effect of using differentiated instruction by integrating multiple intelligences and learning styles on solving problems, achievement in, and attitudes towards math in six graders with learning disabilities in cooperative groups. A total of 60 students identified with LD were invited to participate. The sample was…

Fe II/Fe III mixed-valence state induced by Li-insertion into the metal-organic-framework Mil53(Fe): A DFT+U study

Science.gov (United States)

Combelles, C.; Ben Yahia, M.; Pedesseau, L.; Doublet, M.-L.

The iron-based metal-organic-framework MIL53(Fe) has recently been tested as a cathode materials for Li-Ion batteries, leading to promising cycling life and rate capability. Despite a poor capacity of 70 mAh g -1 associated with the exchange of almost 0.5Li/Fe, this result is the first evidence of a reversible lithium insertion never observed in a MOF system. In the present study, the MIL53(Fe) redox mechanism is investigated through first-principles DFT+U calculations. The results show that MIL53(Fe) is a weak antiferromagnetic charge transfer insulator at T = 0 K, with iron ions in the high-spin S = 5/2 state. Its reactivity vs elemental lithium is then investigated as a function of lithium composition and distribution over the most probable Li-sites of the MOF structure. The redox mechanism is fully interpreted as a two-step insertion/conversion mechanism, associated with the stabilization of the Fe 3+/Fe 2+ mixed-valence state prior to the complete decomposition of the inorganic-organic interactions within the porous MOF architecture.

The Role of CLEAR Thinking in Learning Science from Multiple-Document Inquiry Tasks

Directory of Open Access Journals (Sweden)

Thomas D. GRIFFIN

2012-10-01

Full Text Available The main goal for the current study was to investigate whether individual differences in domaingeneral thinking dispositions might affect learning from multiple-document inquiry tasks in science.Middle school students were given a set of documents and were tasked with understanding how and why recent patterns in global temperature might be different from what has been observed in the past from those documents. Understanding was assessed with two measures: an essay task and an inference verification task. Domain-general thinking dispositions were assessed with a Commitment to Logic, Evidence, and Reasoning (CLEAR thinking scale. The measures of understanding wereuniquely predicted by both reading skills and CLEAR thinking scores, and these effects were not attributable to prior knowledge or interest. The results suggest independent roles for thinkingdispositions and reading ability when students read to learn from multiple-document inquiry tasks in science.

PA171 Containers on a Wood Pallet with Metal Top Adapter, Air Pressure Tests During MIL-STD-1660 Tests

National Research Council Canada - National Science Library

2004-01-01

... (PM-MAS) to conduct Air Pressure Tests during MIL-STD-1660, "Design Criteria for Ammunition Unit Loads" testing on the PA171 containers on a wood pallet with metal top adapter as manufactured by Alliant Tech...

CLASS-PAIR-GUIDED MULTIPLE KERNEL LEARNING OF INTEGRATING HETEROGENEOUS FEATURES FOR CLASSIFICATION

Directory of Open Access Journals (Sweden)

Q. Wang

2017-10-01

Full Text Available In recent years, many studies on remote sensing image classification have shown that using multiple features from different data sources can effectively improve the classification accuracy. As a very powerful means of learning, multiple kernel learning (MKL can conveniently be embedded in a variety of characteristics. The conventional combined kernel learned by MKL can be regarded as the compromise of all basic kernels for all classes in classification. It is the best of the whole, but not optimal for each specific class. For this problem, this paper proposes a class-pair-guided MKL method to integrate the heterogeneous features (HFs from multispectral image (MSI and light detection and ranging (LiDAR data. In particular, the one-against-one strategy is adopted, which converts multiclass classification problem to a plurality of two-class classification problem. Then, we select the best kernel from pre-constructed basic kernels set for each class-pair by kernel alignment (KA in the process of classification. The advantage of the proposed method is that only the best kernel for the classification of any two classes can be retained, which leads to greatly enhanced discriminability. Experiments are conducted on two real data sets, and the experimental results show that the proposed method achieves the best performance in terms of classification accuracies in integrating the HFs for classification when compared with several state-of-the-art algorithms.

CoFe2O4@MIL-100(Fe) hybrid magnetic nanoparticles exhibit fast and selective adsorption of arsenic with high adsorption capacity

Science.gov (United States)

Yang, Ji-Chun; Yin, Xue-Bo

2017-01-01

In this study, we report the synthesis and application of mesoporous CoFe2O4@MIL-100(Fe) hybrid magnetic nanoparticles (MNPs) for the simultaneous removal of inorganic arsenic (iAs). The hybrid adsorbent had a core-shell and mesoporous structure with an average diameter of 260 nm. The nanoscale size and mesoporous character impart a fast adsorption rate and high adsorption capacity for iAs. In total, 0.1 mg L−1 As(V) and As(III) could be adsorbed within 2 min, and the maximum adsorption capacities were 114.8 mg g−1 for As(V) and 143.6 mg g−1 for As(III), higher than most previously reported adsorbents. The anti-interference capacity for iAs adsorption was improved by the electrostatic repulsion and size exclusion effects of the MIL-100(Fe) shell, which also decreased the zero-charge point of the hybrid absorbent for a broad pH adsorption range. The adsorption mechanisms of iAs on the MNPs are proposed. An Fe-O-As structure was formed on CoFe2O4@MIL-100(Fe) through hydroxyl substitution with the deprotonated iAs species. Monolayer adsorption of As(V) was observed, while hydrogen bonding led to the multi-layer adsorption of neutral As(III) for its high adsorption capacity. The high efficiency and the excellent pH- and interference-tolerance capacities of CoFe2O4@MIL-100(Fe) allowed effective iAs removal from natural water samples, as validated with batch magnetic separation mode and a portable filtration strategy. PMID:28102334

Validation of MIL-F-9490D. General Specification for Flight Control System for Piloted Military Aircraft. Volume III. C-5A Heavy Logistics Transport Validation

Science.gov (United States)

1977-04-01

subjected to extreme environmental climatic tests, including the IdL,-T-5289 test requirement. 5.1.9.2 Invulnerability to Lightning Strikes and Static...specified in Paragraph 3.2.3.2.1. The hydi aulic computing elements were designed to the requirements of MIL-C- 5503 and �-H-8775. I 297 L...and climate in any area of the world using MI,- STD-210, FAA-T3O-(49C, and MIL-F-9490, as applicable. Environmental areas included solar radiation

Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple Cancers

DEFF Research Database (Denmark)

Friis-Nielsen, Jens; Kjartansdóttir, Kristín Rós; Mollerup, Sarah

2016-01-01

have developed a species independent pipeline that utilises sequence clustering for the identification of nucleotide sequences that co-occur across multiple sequencing data instances. We applied the workflow to 686 sequencing libraries from 252 cancer samples of different cancer and tissue types, 32...

Towards protective MOFs: post-synthetic modification of MIL-101 with oxime groups and their interactions with toxic chemicals

NARCIS (Netherlands)

Grol, M. van; Gorzkowska-Sobasb, A.A.; Koning, M.C. de

2017-01-01

In an attempt to broaden the scope of protective MOFs towards toxic compounds, we decided to introduce a reactive (nucleophilic) functionality in MIL101 by post-synthesis modification 1,2. This functionality would complement already existing adsorptive properties with an ability to capture or

MIL SPEC 28 Square Foot Fire Burnback and Extinguishment Testing of FireAde, FlameOut II and Hawk ALLFIRE

National Research Council Canada - National Science Library

Barrett, Kimberly D; Kalberer, Jennifer L

2008-01-01

... for hydrocarbon fuel fires. This report documents the evaluation performed on the fire extinguishing agents FireAde 2000 AFFF LP, FlameOut II and Hawk ALLFORE in accordance with the parameters set forth in Military Specification ( MIL SPEC...

DL-sQUAL: A Multiple-Item Scale for Measuring Service Quality of Online Distance Learning Programs

Science.gov (United States)

Shaik, Naj; Lowe, Sue; Pinegar, Kem

2006-01-01

Education is a service with multiplicity of student interactions over time and across multiple touch points. Quality teaching needs to be supplemented by consistent quality supporting services for programs to succeed under the competitive distance learning landscape. ServQual and e-SQ scales have been proposed for measuring quality of traditional…

Basics of XBRL Instance for Financial Reporting

Directory of Open Access Journals (Sweden)

Mihaela Enachi

2011-10-01

Full Text Available The development of XBRL (eXtensible Business Reporting Language for financial reporting has significantly changed the way which financial statements are presented to differentusers and implicitly the quantity and quality of information provided through such a modern format. Following a standard structure, but adaptable to the regulations from different countriesor regions of the world, we can communicate and process financial accounting information more efficient and effective. This paper tries to clarify the manner of preparation and presentation ofthe financial statements if using XBRL as reporting tool.Keywords: XML, XBRL, financial reporting, specification, taxonomy, instance

Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales, attention and oscillations.

Science.gov (United States)

Grossberg, Stephen; Pilly, Praveen K

2014-02-05

A neural model proposes how entorhinal grid cells and hippocampal place cells may develop as spatial categories in a hierarchy of self-organizing maps (SOMs). The model responds to realistic rat navigational trajectories by learning both grid cells with hexagonal grid firing fields of multiple spatial scales, and place cells with one or more firing fields, that match neurophysiological data about their development in juvenile rats. Both grid and place cells can develop by detecting, learning and remembering the most frequent and energetic co-occurrences of their inputs. The model's parsimonious properties include: similar ring attractor mechanisms process linear and angular path integration inputs that drive map learning; the same SOM mechanisms can learn grid cell and place cell receptive fields; and the learning of the dorsoventral organization of multiple spatial scale modules through medial entorhinal cortex to hippocampus (HC) may use mechanisms homologous to those for temporal learning through lateral entorhinal cortex to HC ('neural relativity'). The model clarifies how top-down HC-to-entorhinal attentional mechanisms may stabilize map learning, simulates how hippocampal inactivation may disrupt grid cells, and explains data about theta, beta and gamma oscillations. The article also compares the three main types of grid cell models in the light of recent data.

Blended learning in health education: three case studies

NARCIS (Netherlands)

de Jong, N.; Savin-Baden, M.; Cunningham, A.M.; Verstegen, D.M.L.

2014-01-01

Blended learning in which online education is combined with face-to-face education is especially useful for (future) health care professionals who need to keep up-to-date. Blended learning can make learning more efficient, for instance by removing barriers of time and distance. In the past

Software support for Motorola 68000 microprocessor at CERN. M68MIL cross macro assembler

International Nuclear Information System (INIS)

Eicken, H. von.

1983-01-01

This document is a user's guide for programming the Motorola 68000 microprocessor in assembly language. It describes the programming model, addressing modes and instruction set of the M 68000 as well as the use of the M68mil cross macro assembler. Version 3.6 of the assembler has been installed at CERN on CDC, DEC VAX, IBM, Norsk Data and Siemens computers. The source code of the assembler is available from CERN on request. (orig.)

Multiple kernel learning using single stage function approximation for binary classification problems

Science.gov (United States)

Shiju, S.; Sumitra, S.

2017-12-01

In this paper, the multiple kernel learning (MKL) is formulated as a supervised classification problem. We dealt with binary classification data and hence the data modelling problem involves the computation of two decision boundaries of which one related with that of kernel learning and the other with that of input data. In our approach, they are found with the aid of a single cost function by constructing a global reproducing kernel Hilbert space (RKHS) as the direct sum of the RKHSs corresponding to the decision boundaries of kernel learning and input data and searching that function from the global RKHS, which can be represented as the direct sum of the decision boundaries under consideration. In our experimental analysis, the proposed model had shown superior performance in comparison with that of existing two stage function approximation formulation of MKL, where the decision functions of kernel learning and input data are found separately using two different cost functions. This is due to the fact that single stage representation helps the knowledge transfer between the computation procedures for finding the decision boundaries of kernel learning and input data, which inturn boosts the generalisation capacity of the model.

Learning with Multiple Representations: An Example of a Revision Lesson in Mathematics

Science.gov (United States)

Wong, Darren; Poo, Sng Peng; Hock, Ng Eng; Kang, Wee Loo

2011-01-01

We describe an example of learning with multiple representations in an A-level revision lesson on mechanics. The context of the problem involved the motion of a ball thrown vertically upwards in air and studying how the associated physical quantities changed during its flight. Different groups of students were assigned to look at the ball's motion…

A novel metal-organic framework composite MIL-101(Cr)@GO as an efficient sorbent in dispersive micro-solid phase extraction coupling with UHPLC-MS/MS for the determination of sulfonamides in milk samples.

Science.gov (United States)

Jia, Xiuna; Zhao, Pan; Ye, Xiu; Zhang, Lianjun; Wang, Ting; Chen, Qinyu; Hou, Xiaohong

2017-07-01

As a novel material, metal-organic framework/graphite oxide (MIL-101(Cr)@GO) has great potential for the pretreatment of trace analytes. In the present study, MIL-101(Cr)@GO was synthesized using a solvothermal synthesis method at the nanoscale and was applied as sorbent in the dispersive micro-solid phase extraction (DMSPE) for the enrichment of the trace sulfonamides (SAs) from milk samples for the first time. Several experimental parameters including kinds of sorbents, the effect of pH, the amount of MIL-101(Cr)@GO, ionic strength, adsorption time, desorption solvent and desorption time were investigated. Under the optimal conditions, the linear ranges were from 0.1 to 10μg/L, 0.2-20μg/L or 0.5-50μg/L for the analytes with regression coefficients (r) from 0.9942 to 0.9999. The limits of detection were between 0.012 and 0.145μg/L. The recoveries ranged from 79.83% to 103.8% with relative standard deviations (RSDs)MIL-101(Cr)@GO exhibited remarkable advantages compared to MIL-101(Cr), MIL-100(Fe), activated carbon and other sorbent materials used in pretreatment methods. A simple, rapid, sensitive, inexpensive and less solvent consuming method of DMSPE-ultra-high performance liquid chromatography-tandem mass spectrometry (DMSPE-UHPLC-MS/MS) was successfully applied to the pre-concentration and determination of twelve SAs in milk samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Ciberprens@. El medio de los ‘diez mil nombres’

Directory of Open Access Journals (Sweden)

Dr. José Álvarez Marcos

2000-01-01

Full Text Available Los chinos han traducido el significado de World Wide Web como "la red de diez mil dimensiones en el cielo y la tierra". La telaraña cibernética no sólo se ha convertido en un gigantesco hipermercado de la información, donde confluyen medios tradicionales e innovadoras propuestas comunicativas, sino que aparece como el fenómeno de mayor impacto social de los últimos años. En un mundo donde la evolución tecnológica acorta cada vez más los ciclos de la innovación, como bien señala Díaz Nosty, Internet tiene visos de consolidarse como el embrión de la primera gran solución sostenible desde que apareció la televisión, al menos en una interpretación hecha desde el campo de análisis de los medios

Motor imagery learning modulates functional connectivity of multiple brain systems in resting state.

Science.gov (United States)

Zhang, Hang; Long, Zhiying; Ge, Ruiyang; Xu, Lele; Jin, Zhen; Yao, Li; Liu, Yijun

2014-01-01

Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning. We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN. These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.

Experimentally determined coordinates for three MILS hydrophones near Ascension Island

International Nuclear Information System (INIS)

Harben, P.E.; Hollfelder, J.R.; Rodgers, A.J.

1999-01-01

We conducted an airgun survey in the waters of Ascension Island in May 1999 to determine new locations and depths for three Missile Impact Location System (MILS) hydrophones (ASC23, ASC24, and ASC26) currently in use by the Prototype International Data Center (PIDC) and the National Data Center (NDC). The nominal and new locations are summarized. Although not rigorous, errors in the new locations and depths are conservatively estimated to be less than 100 m. The hydrophones are either on or near the ocean bottom in all three cases. The new depths are consistent with the following: Direct-phase airgun arrivals; Bathymetry determined along the track of the ship used for this airgun survey; Reflected phases from the airgun data; Depths given in the original hydrophone installation report. (author)

Solving large instances of the quadratic cost of partition problem on dense graphs by data correcting algorithms

NARCIS (Netherlands)

Goldengorin, Boris; Vink, Marius de

1999-01-01

The Data-Correcting Algorithm (DCA) corrects the data of a hard problem instance in such a way that we obtain an instance of a well solvable special case. For a given prescribed accuracy of the solution, the DCA uses a branch and bound scheme to make sure that the solution of the corrected instance

Order of Presentation Effects in Learning Color Categories

Science.gov (United States)

Sandhofer, Catherine M.; Doumas, Leonidas A. A.

2008-01-01

Two studies, an experimental category learning task and a computational simulation, examined how sequencing training instances to maximize comparison and memory affects category learning. In Study 1, 2-year-old children learned color categories with three training conditions that varied in how categories were distributed throughout training and…

Unsupervised multiple kernel learning for heterogeneous data integration.

Science.gov (United States)

Mariette, Jérôme; Villa-Vialaneix, Nathalie

2018-03-15

Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.

SignalSpider: Probabilistic pattern discovery on multiple normalized ChIP-Seq signal profiles

KAUST Repository

Wong, Kachun

2014-09-05

Motivation: Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-Seq) measures the genome-wide occupancy of transcription factors in vivo. Different combinations of DNA-binding protein occupancies may result in a gene being expressed in different tissues or at different developmental stages. To fully understand the functions of genes, it is essential to develop probabilistic models on multiple ChIP-Seq profiles to decipher the combinatorial regulatory mechanisms by multiple transcription factors. Results: In this work, we describe a probabilistic model (SignalSpider) to decipher the combinatorial binding events of multiple transcription factors. Comparing with similar existing methods, we found SignalSpider performs better in clustering promoter and enhancer regions. Notably, SignalSpider can learn higher-order combinatorial patterns from multiple ChIP-Seq profiles. We have applied SignalSpider on the normalized ChIP-Seq profiles from the ENCODE consortium and learned model instances. We observed different higher-order enrichment and depletion patterns across sets of proteins. Those clustering patterns are supported by Gene Ontology (GO) enrichment, evolutionary conservation and chromatin interaction enrichment, offering biological insights for further focused studies. We also proposed a specific enrichment map visualization method to reveal the genome-wide transcription factor combinatorial patterns from the models built, which extend our existing fine-scale knowledge on gene regulation to a genome-wide level. Availability and implementation: The matrix-algebra-optimized executables and source codes are available at the authors\\' websites: http://www.cs.toronto.edu/∼wkc/SignalSpider. Contact: Supplementary information: Supplementary data are available at Bioinformatics online.

The Validity of the earth and space science learning materials with orientation on multiple intelligences and character education

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Liliawati, W.; Utama, J. A.; Ramalis, T. R.; Rochman, A. A.

2018-03-01

Validation of the Earth and Space Science learning the material in the chapter of the Earth's Protector based on experts (media & content expert and practitioners) and junior high school students' responses are presented. The data came from the development phase of the 4D method (Define, Design, Develop, Dissemination) which consist of two steps: expert appraisal and developmental testing. The instrument employed is rubric of suitability among the book contents with multiple intelligences activities, character education, a standard of book assessment, a questionnaires and close procedure. The appropriateness of the book contents with multiple intelligences, character education and standard of book assessment is in a good category. Meanwhile, students who used the book in their learning process gave a highly positive response; the book was easy to be understood. In general, the result of cloze procedure indicates high readability of the book. As our conclusion is the book chapter of the Earth's Protector can be used as a learning material accommodating students’ multiple intelligences and character internalization.

Investigation of ball bond integrity for 0.8 mil (20 microns) diameter gold bonding wire on low k die in wire bonding technology

Science.gov (United States)

Kudtarkar, Santosh Anil

Microelectronics technology has been undergoing continuous scaling to accommodate customer driven demand for smaller, faster and cheaper products. This demand has been satisfied by using novel materials, design techniques and processes. This results in challenges for the chip connection technology and also the package technology. The focus of this research endeavor was restricted to wire bond interconnect technology using gold bonding wires. Wire bond technology is often regarded as a simple first level interconnection technique. In reality, however, this is a complex process that requires a thorough understanding of the interactions between the design, material and process variables, and their impact on the reliability of the bond formed during this process. This research endeavor primarily focused on low diameter, 0.8 mil thick (20 mum) diameter gold bonding wire. Within the scope of this research, the integrity of the ball bond formed by 1.0 mil (25 mum) and 0.8 mil (20 mum) diameter wires was compared. This was followed by the evaluation of bonds formed on bond pads having doped SiO2 (low k) as underlying structures. In addition, the effect of varying the percentage of the wire dopant, palladium and bonding process parameters (bonding force, bond time, ultrasonic energy) for 0.8 mil (20 mum) bonding wire was also evaluated. Finally, a degradation empirical model was developed to understand the decrease in the wire strength. This research effort helped to develop a fundamental understanding of the various factors affecting the reliability of a ball bond from a design (low diameter bonding wire), material (low k and bonding wire dopants), and process (wire bonding process parameters) perspective for a first level interconnection technique, namely wire bonding. The significance of this research endeavor was the systematic investigation of the ball bonds formed using 0.8 mil (20 microm) gold bonding wire within the wire bonding arena. This research addressed low k

Music mnemonics aid Verbal Memory and Induce Learning – Related Brain Plasticity in Multiple Sclerosis

OpenAIRE

Thaut, Michael H.; Peterson, David A.; McIntosh, Gerald C.; Hoemberg, Volker

2014-01-01

Recent research on music and brain function has suggested that the temporal pattern structure in music and rhythm can enhance cognitive functions. To further elucidate this question specifically for memory, we investigated if a musical template can enhance verbal learning in patients with multiple sclerosis (MS) and if music-assisted learning will also influence short-term, system-level brain plasticity. We measured systems-level brain activity with oscillatory network synchronization during ...

DEVELOPMENT OF A WELDING PROCEDURE FOR MIL A 46100 ARMOR STEEL JOINTS USING GAS METAL ARC WELDING

Directory of Open Access Journals (Sweden)

DAVID MAZUERA ROBLEDO

2011-01-01

Full Text Available Se desarrolló un procedimiento de soldadura (WPS para unir láminas de acero para blindaje bajo especificación MIL A46100 usando el proceso GMAW, el cual fue calificado mediante ensayos mecánicos y no destructivos (NDT de acuerdo con los requerimientos de códigos militares. Los resultados obtenidos fueron comparados con procedimientos de soldadura para este material realizados con el proceso SMAW. Los resultados obtenidos mostraron que el WPS diseñado es una opción viable para la soldadura de blindajes de acero MIL A 46100. Además, con el WPS diseñado se obtuvo una reducción en el ancho de la zona afectada térmicamente (ZAT que debería conducir a un mejor desempeño en servicio de los blindajes de acuerdo con los resultados de estudios previos. Finalmente, se encontró un incremento en la energía absorbida en los ensayos de impacto Charpy V comparada con la de soldaduras realizadas con el proceso SMAW.

Pyrolytic in situ magnetization of metal-organic framework MIL-100 for magnetic solid-phase extraction.

Science.gov (United States)

Huo, Shu-Hui; An, Hai-Yan; Yu, Jing; Mao, Xue-Feng; Zhang, Zhe; Bai, Lei; Huang, Yan-Feng; Zhou, Peng-Xin

2017-09-29

In this study, we report a facile, environmental friendly fabrication of a type of magnetic metal-organic framework (MOF) MIL-100 that can be used for magnetic solid-phase extraction (MSPE). The magnetic MOF composites were fabricated using in situ calcination method. The as-synthesized materials exhibited both high porosity and magnetic characteristics. They used for the MSPE of polycyclic aromatic hydrocarbons (PAHs) from water samples. Such MOF-based magnetic solid-phase extraction in combination with gas chromatography equipped with a flame ionization detector (GC-FID), exhibited wide linearity (0.02-250μgL -1 ), low detection limits (4.6-8.9ngL -1 ), and high enrichment factors (452-907) for PAHs. The relative standard deviations (RSDs) for intra- and inter-day extractions of PAHs were ranging from 1.7% to 9.8% and 3.8% to 9.2%, respectively. The recoveries for spiked PAHs (1μgL -1 ) in water samples were in the range of 88.5% to 106.6%. The results showed that the special anion-π orbital (electron donor-acceptor) interaction and π-π stacking between magnetic MIL-100 and PAHs play an important role in the adsorption of PAHs. Copyright © 2017. Published by Elsevier B.V.

Salen- Zr(IV) complex grafted into amine-tagged MIL-101(Cr) as a robust multifunctional catalyst for biodiesel production and organic transformation reactions

Science.gov (United States)

Hassan, Hassan M. A.; Betiha, Mohamed A.; Mohamed, Shaimaa K.; El-Sharkawy, E. A.; Ahmed, Emad A.

2017-08-01

The synthesis of metal-organic frameworks (MOFs), porous coordination polymers with functional groups has received immense interest due to the functional groups can offer desirable properties and allow post-synthetic modification. Herein, for the first time, Zr(IV)-Sal Schiff base complex incorporated into amino-functionalized MIL-101(Cr) framework by salicylaldehyde condensing to amino group, and coordinating Zr(IV) ion have been successfully synthesized. The worthiness of the synthesized material as a catalyst has been examined for the esterification of oleic acid (free fatty acid) with methanol producing biodiesel (methyl oleate), Knoveonagel condensation reaction of aldehydes and Friedel-Crafts acylation of anisole. Our findings demonstrated that Salen-Zr(IV) grafted to framework of NH2-MIL-101(Cr) as a solid acid catalyst exhibited distinct catalytic performance for the production of biodiesel by esterification of oleic acid with methanol, Knoveonagel condensation and Friedel-Crafts acylation. These could be attributed to high surface area which allow high distribution of Zr(IV) species lead to a sufficient contact with the reactants species. Furthermore, the catalyst showed excellent recycling efficiency due to the strong interaction between the Zr(IV) ions and chelating groups in the NH2-MIL-101(Cr)-Sal.

Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis

NARCIS (Netherlands)

Cheplygina, Veronika; de Bruijne, Marleen; Pluim, Josien P. W.

2018-01-01

Machine learning (ML) algorithms have made a tremendous impact in the field of medical imaging. While medical imaging datasets have been growing in size, a challenge for supervised ML algorithms that is frequently mentioned is the lack of annotated data. As a result, various methods which can learn

Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems.

Science.gov (United States)

Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

2016-01-01

It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning.

MULTIPLE INTELLIGENCE THEORY AND FOREIGN LANGUAGE LEARNING:A BRAIN-BASED PERSPECTIVE

Directory of Open Access Journals (Sweden)

Jane Arnold

2004-06-01

Full Text Available Gardner's Multiple Intelligences theory is presented as a cognitive perspective on intelligence which has profound implications for education in general. More specifically, it has led to the application of eight of these frames to language teaching and learning. In this chapter, we will argue in favour of the application of MIT to the EFL classroom, using as support some of the major insights for language teaching from brain science.

Attributional Style and Depression in Multiple Sclerosis: The Learned Helplessness Model

OpenAIRE

Vargas, Gray A.; Arnett, Peter A.

2013-01-01

Several etiologic theories have been proposed to explain depression in the general population. Studying these models and modifying them for use in the multiple sclerosis (MS) population may allow us to better understand depression in MS. According to the reformulated learned helplessness (LH) theory, individuals who attribute negative events to internal, stable, and global causes are more vulnerable to depression. This study differentiated attributional style that was or was not related to MS...

Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

Science.gov (United States)

Zhang, Hang; Long, Zhiying; Ge, Ruiyang; Xu, Lele; Jin, Zhen; Yao, Li; Liu, Yijun

2014-01-01

Background Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning. Methodology/Principal Findings We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN. Conclusions/Significance These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning. PMID:24465577

Mise en place d'une collection de ressources génétiques du mil ...

African Journals Online (AJOL)

Le mil est une céréale importante pour l'alimentation humaine. La Côte d'Ivoire représente un des centres de production et de consommation. Afin de collecter, conserver et étudier les variabilités existantes, une seconde mission a été effectuée dans les zones de culture de cette céréale en 1989 et 1990, faisant suite à la ...

Aging method for electronic components and systems based on MIL-HDBK 217

International Nuclear Information System (INIS)

Declercq, M.; Simoens, F.

1984-01-01

Accelerated aging tests as requested to comply IEEE Std 323-1974, rise the question of the availability of an adequate aging model. After getting through the usual models, the authors describe an aging methodology based on MIL-HDBK 217. The method, taking into account several stress factors, is shown to yield on acceptable acceleration of time, while reducing the relative importance of temperature. Practical implementation of acceleration testing is discussed, and a summary of the gained experience is made and discussed in the scope of the philosophy of IEEE Std 650. Only natural thermal aging and functional aging, excluding irradiation or thermal shocks, are considered [fr

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.

Science.gov (United States)

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-06-19

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification.

The Role of CLEAR Thinking in Learning Science from Multiple-Document Inquiry Tasks

Science.gov (United States)

Griffin, Thomas D.; Wiley, Jennifer; Britt, M. Anne; Salas, Carlos R.

2012-01-01

The main goal for the current study was to investigate whether individual differences in domain-general thinking dispositions might affect learning from multiple-document inquiry tasks in science. Middle school students were given a set of documents and were tasked with understanding how and why recent patterns in global temperature might be…

Touching Mercury in Community Media: Identifying Multiple Literacy Learning through Digital Arts Production

Science.gov (United States)

Arndt, Angela E.

2011-01-01

Educational paradigm shifts call for 21st century learners to possess the knowledge, skills, abilities, values, and experiences associated with multiple forms of literacy in a participatory learning culture. Contemporary educational systems are slow to adapt. Outside of school, people have to be self-motivated and have access to resources in order…

Toppling hierarchies?

DEFF Research Database (Denmark)

Drotner, Kirsten; Kobbernagel, Christian

2014-01-01

This article suggests how we should study media and information literacies (MIL) and do so at a time, when young people nurture these literacies through multiple media practices and across spaces of learning. Our basic argument is this: in order to gain a robust knowledge base for the development...... of MIL we need to study literacy practices beyond print literacy and numeracy, and we need to study these practices beyond formal spaces of learning. The argument is unfolded with particular focus on ethnic minority youth since this group routinely figures as under-achieving in studies of school literacy......, such as Programme for International Student Assessment. Based on a brief overview of literacy studies in view of digitization and a critical examination of recent studies of youthful media practices and ethnicity, the argument is illustrated through an empirical analysis that draws on results from a nationally...

Fabrication of γ-Fe2O3 Nanoparticles by Solid-State Thermolysis of a Metal-Organic Framework, MIL-100(Fe, for Heavy Metal Ions Removal

Directory of Open Access Journals (Sweden)

Shengtao Hei

2014-01-01

Full Text Available Porous γ-Fe2O3 nanoparticles were prepared via a solid-state conversion process of a mesoporous iron(III carboxylate crystal, MIL-100(Fe. First, the MIL-100(Fe crystal that served as the template of the metal oxide was synthesized by a low-temperature (<100°C synthesis route. Subsequently, the porous γ-Fe2O3 nanoparticles were fabricated by facile thermolysis of the MIL-100(Fe powders via a two-step calcination treatment. The obtained γ-Fe2O3 was characterized by X-ray diffraction (XRD, N2 adsorption, X-ray photoelectron spectroscopy (XPS, and scanning electron microscopy (SEM techniques, and then used as an adsorbent for heavy metal ions removal in water treatment. This study illustrates that the metal-organic frameworks may be suitable precursors for the fabrication of metal oxides nanomaterials with large specific surface area, and the prepared porous γ-Fe2O3 exhibits a superior adsorption performance for As(V and As(III ions removal in water treatment.

Exploration of machine learning techniques in predicting multiple sclerosis disease course

OpenAIRE

Zhao, Yijun; Healy, Brian C.; Rotstein, Dalia; Guttmann, Charles R. G.; Bakshi, Rohit; Weiner, Howard L.; Brodley, Carla E.; Chitnis, Tanuja

2017-01-01

Objective To explore the value of machine learning methods for predicting multiple sclerosis disease course. Methods 1693 CLIMB study patients were classified as increased EDSS?1.5 (worsening) or not (non-worsening) at up to five years after baseline visit. Support vector machines (SVM) were used to build the classifier, and compared to logistic regression (LR) using demographic, clinical and MRI data obtained at years one and two to predict EDSS at five years follow-up. Results Baseline data...

The Relationship between Perceptual Learning Style Preferences and Multiple Intelligences among Iranian EFL Learners

Science.gov (United States)

Baleghizadeh, Sasan; Shayeghi, Rose

2014-01-01

The purpose of the present study is to investigate the relationships between preferences of Multiple Intelligences and perceptual/social learning styles. Two self-report questionnaires were administered to a total of 207 male and female participants. Pearson correlation results revealed statistically significant positive relations between…

Portable Tablets in Science Museum Learning: Options and Obstacles

Science.gov (United States)

Gronemann, Sigurd Trolle

2017-06-01

Despite the increasing use of portable tablets in learning, their impact has received little attention in research. In five different projects, this media-ethnographic and design-based analysis of the use of portable tablets as a learning resource in science museums investigates how young people's learning with portable tablets matches the intentions of the museums. By applying media and information literacy (MIL) components as analytical dimensions, a pattern of discrepancies between young people's expectations, their actual learning and the museums' approaches to framing such learning is identified. It is argued that, paradoxically, museums' decisions to innovate by introducing new technologies, such as portable tablets, and new pedagogies to support them conflict with many young people's traditional ideas of museums and learning. The assessment of the implications of museums' integration of portable tablets indicates that in making pedagogical transformations to accommodate new technologies, museums risk opposing didactic intention if pedagogies do not sufficiently attend to young learners' systemic expectations to learning and to their expectations to the digital experience influenced by their leisure use.

TNO at TRECVID 2013: Multimedia Event Detection and Instance Search

NARCIS (Netherlands)

Bouma, H.; Azzopardi, G.; Spitters, M.M.; Wit, J.J. de; Versloot, C.A.; Zon, R.W.L. van der; Eendebak, P.T.; Baan, J.; Hove, R.J.M. ten; Eekeren, A.W.M. van; Haar, F.B. ter; Hollander, R.J.M. den; Huis, R.J. van; Boer, M.H.T. de; Antwerpen, G. van; Broekhuijsen, B.J.; Daniele, L.M.; Brandt, P.; Schavemaker, J.G.M.; Kraaij, W.; Schutte, K.

2013-01-01

We describe the TNO system and the evaluation results for TRECVID 2013 Multimedia Event Detection (MED) and instance search (INS) tasks. The MED system consists of a bag-of-word (BOW) approach with spatial tiling that uses low-level static and dynamic visual features, an audio feature and high-level

Classification of multiple sclerosis lesions using adaptive dictionary learning.

Science.gov (United States)

Deshpande, Hrishikesh; Maurel, Pierre; Barillot, Christian

2015-12-01

This paper presents a sparse representation and an adaptive dictionary learning based method for automated classification of multiple sclerosis (MS) lesions in magnetic resonance (MR) images. Manual delineation of MS lesions is a time-consuming task, requiring neuroradiology experts to analyze huge volume of MR data. This, in addition to the high intra- and inter-observer variability necessitates the requirement of automated MS lesion classification methods. Among many image representation models and classification methods that can be used for such purpose, we investigate the use of sparse modeling. In the recent years, sparse representation has evolved as a tool in modeling data using a few basis elements of an over-complete dictionary and has found applications in many image processing tasks including classification. We propose a supervised classification approach by learning dictionaries specific to the lesions and individual healthy brain tissues, which include white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). The size of the dictionaries learned for each class plays a major role in data representation but it is an even more crucial element in the case of competitive classification. Our approach adapts the size of the dictionary for each class, depending on the complexity of the underlying data. The algorithm is validated using 52 multi-sequence MR images acquired from 13 MS patients. The results demonstrate the effectiveness of our approach in MS lesion classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Leveraging multiple datasets for deep leaf counting

OpenAIRE

Dobrescu, Andrei; Giuffrida, Mario Valerio; Tsaftaris, Sotirios A

2017-01-01

The number of leaves a plant has is one of the key traits (phenotypes) describing its development and growth. Here, we propose an automated, deep learning based approach for counting leaves in model rosette plants. While state-of-the-art results on leaf counting with deep learning methods have recently been reported, they obtain the count as a result of leaf segmentation and thus require per-leaf (instance) segmentation to train the models (a rather strong annotation). Instead, our method tre...

ENHANCEMENT OF ACIDITY AND CATALYTIC ACTIVITY OF ALUMINA BASED METAL ORGANIC FRAMEWORK (MIL-53 Al)

OpenAIRE

Yilmaz, Esra; Sert, Emine; Atalay, Ferhan Sami

2017-01-01

Metal organic frameworks are highly porous materials which are formed bycombination of metal precursor and salts as inorganic part and ligand asorganic part. They have many advantages such as low density, high surface area,tunable pore size and high porosity. Due to peculiar features, such asunsaturated metal active sites, high surface area and easily functionalization,its usage as catalyst are promising.  The MIL-53(Al) structure contains chains of transcorner-sharing [AlO4(OH)2] oc...

Le contentieux camerounais devant les instances sportives internationales

Directory of Open Access Journals (Sweden)

Dikoume François Claude

2016-01-01

Les acteurs du sport depuis lors, utilisent donc les voies de recours au niveau international soit vers les fédérations sportives internationales ou encore et surtout vers le TAS qui s'occupe des litiges de toutes les disciplines sportives. Il est question ici de faire un inventaire casuistique descriptif non exhaustif des requêtes contentieuses camerounaises portées devant les diverses instances sportives internationales ; ceci permettra de questionner l'esprit processuel et la qualité technique de leurs réclamations juridiques en matière sportive.

Machine Learning

CERN Multimedia

CERN. Geneva

2017-01-01

Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

Using Combinatorial Approach to Improve Students' Learning of the Distributive Law and Multiplicative Identities

Science.gov (United States)

Tsai, Yu-Ling; Chang, Ching-Kuch

2009-01-01

This article reports an alternative approach, called the combinatorial model, to learning multiplicative identities, and investigates the effects of implementing results for this alternative approach. Based on realistic mathematics education theory, the new instructional materials or modules of the new approach were developed by the authors. From…