Miracle-dz/UniFAR-FTUs huggingface dataset:
Standardization of DenverII Developmental Screehing Test in Shanghai and its relative factors

[Objective] To research the new model about DenverⅡ Developmental Screening Test(DDST) in Shanghai,making the moniter means about child health care suit to the demand of the society development. [Methods] The children were located through the Shanghai Department of Social Services.There were 2 826 children between 0～6.5 years in 75 age groups be investigated,include 1 414 boys and 1 412 girls. [Results] The data were analyzed by Logistic regression of SAS software to determine the ages at which the children tested passed each of the items.A large number of observations per item were availabe for imitation bend line,the analysis made it possible to determine when 25%,50%,75% and 90% passing age of each item.These passing ages were compared with those of children’s ages in Denver.The relative contribution of pregnant women contact with computer, illness of pregnant women,illness of childhood and incidendcence factors in these items. [Conclusions] ①DDST has been administered in the standardized manner in Shanghai;②To compare children development in Shanghai With that in Denver,which explore that different tribes,background of cultures and different financial condition result in significant difference of children’s growth between two nations.
Morphological Evaluationof Tomato (Solanum lycopersicumLinn.) Cultivars

Tomato (Solanum lycopersicum Linn.) is widely cultivated and is economically beneficial. Tomato cultivars were obtained from traditional agriculture systems, and their morphological characters were evaluated. The cultivars included Pepper tomato [ED/CH/01], Edo local [ED/CH/02], Golden tomato [ED/CH/03] and Derica tomato [ED/CH/04]. Results of the principal component analyses of 27 morphological characters indicated that two characters accounted for 94.65 % of the observed variations. Scatter plots suggested good tendency of grouping for the four accessions. In the dendrogram, two clusters were formed with ED/CH/01, ED/CH/02 and ED/CH/03 grouped together whereas ED/CH/04 clustered separately. The clustering pattern implicated a common origin and/or gene pool for the cultivars. Cultivars ED/CH/01, ED/CH/03 and ED/CH/04 showed determinate growth type, while ED/CH/02 showed a semi-determinate growth pattern. Further, in terms of plant size, ED/CH/01 and ED/CH/02 were intermediate, while ED/CH/03 and ED/CH/04 were large. The characteristics of the flower and fruits exhibited diversity in terms of the corolla color, style, shape, fruit size at maturity, exterior color of the mature fruit, fruit shoulder, fruit cross-sectional shape, and fruit blossom end shape. These cultivars collectively possess characteristics that can be used by plant breeders. We recommend that further characterization using molecular techniques as well as conservation attention for these local germplasms should be conducted.
Using Agent Based Modelling to Understand Capability Development

The processes of Capability Development (CD) within the Australian Defence Organization (ADO) are described in some detail in the Defence Capability Development Manual (DCDM) 2006. It is recognized in the manual that any process driven approach will find itself in constant need of adaptation and modification to respond to the realities of working within the Defence environment where changes in schedule, funding, personnel, requirements and technology frequently occur during the life of a capability assessment. This paper describes work being undertaken to better understand the dynamics of the CD process using a suite of agent based models which enables us to explore the interactions between the organization elements and individual positions within the Capability Development Executive (CDE). Interviews with CDE and Defence Science and Technology Organization (DSTO) staff involved in selected Capability assessments are being used to understand how CD processes are worked through and how adaptation to the various stresses on these processes come about. This information is being used to guide development of the agent representations of behaviour in the simulation tool. The paper details the models and methods used to develop this simulation tool. It is hoped that as the simulation becomes mature it will prove useful in understanding the effects of exogenous changes such as schedule modifications, funding changes, personnel changes or temporary postings of staff, how outcomes depend on staff types and numbers, the effects of various levels of Industry involvement, the effects of different acquisition strategies, requirements changes driven by new technology, resource contention between assessment efforts, approval delays and such other factors which may be identified as of importance. A more ambitious goal is that the tool will allow recognition of signs of impending performance problems in real assessment programs and suggest remedial actions that should be taken.
Syddansk Universitet Convergence of lateral dynamic measurements in the plasma membrane of live cells from single particle tracking and STED-FCS Lagerholm,

Fluorescence correlation spectroscopy (FCS) in combination with the super-resolution imaging method STED (STED-FCS), and single-particle tracking (SPT) are able to directly probe the lateral dynamics of lipids and proteins in the plasma membrane of live cells at spatial scales much below the diffraction limit of conventional microscopy. However, a major disparity in interpretation of data from SPT and STED-FCS remains, namely the proposed existence of a very fast (unhindered) lateral diffusion coefficient, ⩾5 μm2 s−1, in the plasma membrane of live cells at very short length scales, ≈⩽ 100 nm, and time scales, ≈1–10 ms. This fast diffusion coefficient has been advocated in several high-speed SPT studies, for lipids and membrane proteins alike, but the equivalent has not been detected in STED-FCS measurements. Resolving this ambiguity is important because the assessment of membrane dynamics currently relies heavily on SPT for the determination of heterogeneous diffusion. A possible systematic error in this approach would thus have vast implications in this field. To address this, we have re-visited the analysis procedure for SPT data with an emphasis on the measurement errors and the effect that these errors have on the measurement outputs. We subsequently demonstrate that STED-FCS and SPT data, following careful consideration of the experimental errors of the SPT data, converge to a common interpretation which for the case of a diffusing phospholipid analogue in the plasma membrane of live mouse embryo fibroblasts results in an unhindered, intra-compartment, diffusion coefficient of ≈0.7–1.0 μm2 s−1, and a compartment size of about 100–150 nm. Convergence of lateral dynamic measurements in the plasma membrane of live cells from single particle tracking and STED-FCS Topical Review IOP Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. 5 Author to whom any correspondence should be addressed. 2017
Campylobacter Jejuni Infection and Virulence Genes in Broilers

This study was aimed to assess the presence of Campylobacter jejuni infection and some of its virulence genes in broiler chickens in New Valley and Assiut provinces, Egypt. The study was conducted on 200 broiler chicken samples which obtained from 12 broiler flocks representing 60000 birds. One hundred intestinal (caecal) samples and one hundred liver samples from birds (dead and live broilers suffering from diarrhea) during spring and summer seasons of 2016 were used for bacteriological and molecular examinations. The isolated and identified strains were examined for the presence of virulence factors (VirB11, flaA and Iam genes). Results showed that out of 200 intestinal and liver samples, C. jejuni was isolated in 51 (25.5%). The highest microbial load was in intestinal samples (26%) followed by liver samples (25%). In addition, the virulence genes of C. jejuni were identified in broiler chicken samples as ViroB11 (10%), flaA gene (5%) and iam gene (40%). In conclusion, this study revealed that C. jejuni may represent a threat to poultry production.
Athlete’s Heart with a Systemic Right Ventricle?

Objective: High load of regularly vigorous exercise leads to multiple physiological adaptations. The major cardiovascular effects are hypertrophy and dilation, predominantly of the left ventricle, and bradycardia. However, there are no reports on an athlete’s heart in a systemic right ventricle. Subject: We report on a 23 year old male endurance athlete (177cm, 69kg) with a systemic subaortic right ventricle after atrial redirection (Senning procedure) for simple transposition of the great arteries in infancy. Albeit medical doctors had imposed activity restriction to him, he has lead an active lifestyle from early childhood on, intensifying his sport activities over the years especially in cycling and running to a training volume of about 10 hours per week in winter and about 15 hours per week in summer. In 2009 he performed 1:50h on the half marathon distance. In 2013 he finished his first Marathon in 4:34h. Results: Cardiopulmonary exercise testing revealed a maximum oxygen uptake of 52.3ml/min/kg and a peak work load of 353 Watt, corresponding to 5.1Watt per kilogram body mass. Cardiovascular Magnetic Resonance showed a cardiac index of 2.9ml/min/m2, a tricuspid regurgitation fraction of 4%, and a systemic right ventricle enddiastolic volume of 109ml/m2 with an ejection fraction of 53%. Conclusions: With regular exercise training a systemic right ventricle can become very efficient comparable to healthy amateur athletes. Case Study Muller et al.; CA, 2(4): 293-297, 2014; Article no. CA.2014. 4.014 294
Automatic Image Annotation using Possibilistic Clustering Algorithm

In this paper, the proposed PCMRM (possibilistic based cross-media relevance model) an-notates images based on their visual contents. PCMRM framework relies on unsupervised learning to group the visually similar image regions into homogeneous clusters, along with the cross-media relevance model (CMRM) that is used to estimate the joint distribution of textual keywords and images. Besides, the unsupervised learning task exploits the robustness to noise of a possibilistic clustering algorithm, and generates membership degrees that represent the typicality of image regions with respect to the obtained clusters. To validate and assess the proposed system, we used the standard Corel dataset. PCMRM produced promising results. The reported performance measures proved that the proposed automatic image annotation approach outperforms similar state of the art solutions. This attainment is mainly attributed to the exploitation of the possibilistic membership produced by the clustering algorithm which allowed accurate learning of the association between annotating labels and the visual content of the image regions.
Short-Term Intensive Rehabilitation Induces Recovery of Physical Function After 7 Days of Bed Rest in Older Adults

Purpose:Hospitalization can result in functional loss, especially in older adults. The purpose of the study was to determine the effect of intensive rehabilitation on changes in physical function in healthy older subjects after 1 week of bed rest and 3 days of rehabilitation. Methods:Six healthy subjects older than 60 years completed 7 days of bed rest followed by 3 days of rehabilitation including stretching, strengthening, balance, gait, and stair climbing. Results:Bed rest reduced the distance walked over 6 minutes, slowed gait speeds, and increased sit-to-stand times. Muscle flexibility and isokinetic quadriceps strength varied after bed rest. Three days of rehabilitation restored outcomes measures to baseline levels. Conclusions:A short bout of focused rehabilitation after a week of bed rest restored physical function measures to pre-bed rest levels in healthy older subjects. Similar training protocols may result in increased functional measures in older hospitalized patients.
Social Information Retrieval and Recommendation: state- of-the-art and future research [Recherche d'Information Sociale et Recommandation: Etat d'art et travaux futurs]

The explosion of web 2.0 and social networks has created an enormous and rewarding source of information that has motivated researchers in different fields to exploit it. Our work revolves around the issue of access and identification of social information and their use in building a user profile enriched with a social dimension, and operating in a process of personalization and recommendation. We study several approaches of Social IR (Information Retrieval), distinguished by the type of incorporated social information. We also study various social recommendation approaches classified by the type of recommendation. We then present a study of techniques for modeling the social user profile dimension, followed by a critical discussion. Thus, we propose our social recommendation approach integrating an advanced social user profile model. L’explosion du web 2.0 et des réseaux sociaux a crée une source d’information énorme et enrichissante qui a motivé les chercheurs dans différents domaines à l’exploiter. Notre travail s’articule autour de la problématique d’accès et d’identification des informations sociales et leur exploitation dans la construction d’un profil utilisateur enrichi d’une dimension sociale, et son exploitation dans un processus de personnalisation et de recommandation. Nous étudions différentes approches sociales de RI (Recherche d’Information), distinguées par le type d’informations sociales incorporées. Nous étudions également diverses approches de recommandation sociale classées par le type de recommandation. Nous exposons ensuite une étude des techniques de modélisation de la dimension sociale du profil utilisateur, suivie par une discussion critique. Ainsi, nous présentons notre approche de recommandation sociale proposée intégrant un modèle avancé de profil utilisateur social.
Popularity Prediction of Posts in Social Networks Based on User, Post and Image Features

This paper presents an approach to popularity prediction task. The approach differs from existing works by combining enriched user and post features with statistical features and image object detection related features. Moreover, in this paper, generic popularity prediction models are built that can make predictions for all types of posts from any users which is different from existing works. Briefly, the study contributes by combining various types of features, using more image related visual features and having a dramatically larger dataset compared to previous studies. A specific dataset containing 210.630 posts was crawled from Instagram in order to be used in the study and state-of-the-art Machine Learning algorithms were run on the dataset. Models predicted the log-normalized number of likes of posts as popularity value (ranging between 0 and 18.48) and the results show that the popularity of Instagram posts can be predicted with 0.92 rank-order correlation and 0.4212 Mean Absolute Error. The results indicate that combining user and post features with statistical features and image object detection related features yields good performance on popularity prediction.
Attribute Based Encryption with Efficient Revocation from Lattices

Attribute-based encryption (ABE) can be used in many cloud storage and computing applications, and it is an attractive alternative to identity-based encryption. The feature of the ABE is that it provides a ﬂexible mechanism to achieve ﬁne-grained access control. The revocable ABE (RABE) is an extension of the ABE. The attribute revo-cation is essential because of the factors such as changes of user’s attributes, key exposures and key loss. In this paper, we propose a revocable ciphertext policy ABE (CP-RABE) scheme from lattices, which supports ﬂexible access control and eﬃcient revocation. In our scheme, a binary tree with an attribute revocation list is used to re-voke attributes, and key update is logarithmically related to the number of each user attribute. Finally, the security of the scheme is proved to be selective-attribute secure in the standard model and security can be reduced to hardness of learning with error assumption.
On Positive Feedback Loops in Digital Government Architecture

This research paper starts from the belief that digital government is a systemic process and that by studying the technical architecture it is possible to gain a better understanding of its behavior. Drawing on insights from system dynamics, systems theory, and complex adaptive systems, the paper hypothesizes that by including and reinforcing feedback loops in the architecture, it is possible to obtain significant performance gains. For the sake of testing the hypothesis, and to answer the research question: "How can Systems Theory be used to understand the digital government infrastructure of a country? " the case of Estonia is presented. As a result of the research, it is found that the presence of reinforcement loops in the technical architecture leads to performance gains, that it is possible to observe complex behavior in digital government infrastructure, and demonstrates that systems thinking may be used to analyze digital government systems.
Divide and Conquer Technique for Large Linked Datasets

Significant effort has been dedicated in recent years to the exploitation of very large linked datasets due to the importance of the information they contain and the increase of their availability. Some techniques have been developed that handle the volume of these datasets by aggregating their information based on the data structure or model. Other approaches exploit specific characteristics of the datasets, such as semantic annotations, to present the information to the users in semantically defined ways. In an era that the volume and diversity of the available information increases exponentially and more users are interested in exploring it, it is crucial to provide a technique that will allow the exploitation of diverse and very large linked datasets in a scalable way independent of any characteristics of the input dataset. We present here a generic divide and conquer technique that can offer the required scalability to exploit any input dataset regardless its size and characteristics. The proposed technique has been tested in the context of interactive representation of very large linked datasets as graphs.
Management of Big Textual Data in Qualitative Research: Organizing the Relationships in a Typology based on Logical Properties

In structured indexes, classification systems, thesauri, conceptual structures or semantic networks, relationships are too often vague. For instance, in terminology, the relationships between concepts are often reduced to the distinction established by standard between hierarchical relationships (genus-species relationships and part/whole relationships) and non-hierarchical relationships ("time, space, causal relationships, etc."). The semantics of relationships are vague because the principal users of these relationships are industrial actors (translators of technical handbooks, terminologists, data-processing specialists, etc.). Nevertheless, the consistency of the models built must always be guaranteed. One possible approach to this problem consists in organizing the relationships in a typology based on logical properties. For instance, we typically use only the general relation "Is-a". It is too vague. We assume that general relation "Is-a" is characterized by asymmetry. This asymmetry is specified in: (1) the belonging of one individualizable entity to a distributive class, (2) Inclusion among distributive classes and (3) relation part of (or "composition"). With the view to better designing the knowledge structures underlying the concepts of a field, and more specifically, the indexing of documents and/or information retrieval, we propose a structured set of relationships, based on a linguistic model, the Applicative and Cognitive Grammar (ACG) of Jean-Pierre Descles [7], [8]. This model was extended to terminology by Christophe Jouis [32], and applied by Widad Mustafa and Christophe Jouis, [33], [34], [35] and [36].
IJSRD-International Journal for Scientific Research & Development| Vol. 3, Issue 09, 2015 | ISSN (online): 2321-0613

One of the important research areas in Image processing is the retrieval of images. When size of database increases continuously, the applications involving images face new challenges such as storage management, indexing, knowledge management and retrieval presentation. We need an efficient retrieval mechanism to retrieve images from the multimedia database. CBIRContent-based image retrieval is an image retrieval technique used to retrieve images efficiently by using low level image features like texture, shape and color. This survey paper focuses on different features descriptors for image retrieval and analysis of various retrieval techniques using low level featurescolor, texture and shape –to improve the performance and accuracy in CBIR system.
Identifying Personality Traits for Indonesian User from Twitter Dataset

Social media allows the user to convey their actual self and share their life experiences through numerous ways. This behavior in turn reﬂects the user’s personality. In this paper, we experiment to automatically predict user’s personality based on Big Five Personality Trait on Twitter. Our focus is towards Indonesian user. Not only word n-gram, Twitter metadata is also used in a certain combination to determine the feature that will be used to predict the personality. Our research also attempts to ﬁnd optimum setting based on the number of n-gram, classiﬁer, and twitter metadata. Our experiment yields 0.7482 at most on F-Measure. We conclude that among all scenario, twitter metadata is the least impactful feature, while word n-gram impacts the most.
Towards an Automatic Text Comprehension for the Arabic Question-Answering: Semantic and Logical Representation of Texts

Automatic text comprehension is an arduous task of automatic natural language processing. This task has been addressed in several NLP applications, namely, question-answering, information retrieval, etc. In some cases, these applications require a minimal understanding of the text. The use of this task in question-answering requires that the result must be the accurate answer to a question, instead of a number of references to documents that contain the answer. It makes it possible to construct a coherent representation of the content of a text to answer a question in natural language. In this paper, we propose to construct a semantic and logical representation of Arabic texts (the question and the passages of texts). Therefore, we propose a new approach for the Arabic question-answering. This approach is based on the automatic understanding of Arabic texts (question or passages of texts) to transform them into semantic and logical representations. The experiments results of our approach achieved an accuracy of 74%.