Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship between Organizational Culture and Knowledge Management Processes A Case Study: The Roads and Urban Development Organization of Chaharmahal and Bakhtiari Province

With the beginning of the knowledge era, the Organizations' knowledge assets have been considered widely as a main key for the ability to create and maintain the competitive advantage and continuous growth. The suitable organizational culture can be very important for knowledge management. Therefore in line with the primary conduct of knowledge management the organizations need to recognize and obtain information on the dominant culture in their enterprise and the degree of organizational culture compatibility with knowledge management activities. The main objective of the research his to analyze the relationship between organizational culture and knowledge management processes. This research was performed in the form of organizational culture and knowledge management literature, which resulted in obtaining a conceptual model of the research. In this organizational culture research, the competitive values framework model (the clan culture, the adhocracy culture, the market culture, and the hierarchical culture) was used and in knowledge management processes, the knowledge management cycle (knowledge creation, knowledge capture, knowledge organization, knowledge storage, knowledge dissemination, and knowledge application) was used. This research is descriptive-survey in objective, application, and nature respects. The statistical community of this research was the official employee of The Roads and Urban Development Organization in Chaparrals and Bakhtiari Province in 2010-2011. The data gathering instrument was questionnaire. To measure the organizational culture and knowledge management processes the assessment instrument for organizational culture of Cameron and Quinn(2006) and the knowledge management assessment instrument of Lawson (2003) were used respectively, and their validity was confirmed by Cronbach's Alpha with 0.886 and 0.889 ratios respectively, and the number of statistical sample was determined 65 people. The descriptive tests, One-sample t-test, Friedman, and Pearson's correlation tests were usedto analyze the data and the examination of the hypothesis. The research findings say that its hypotheses were confirmed and the relation between the organizational culture and knowledge managementprocesses is meaningful. The amount of knowledge creation, knowledge capture, knowledge storage, and knowledge dissemination processes were average and the knowledge organization and knowledge application processes were below the average. The dominant culture in the organization is hierarchical but the corresponding organizational culture with the knowledge management processes is the adhocracy culture; therefore, the successful performance of knowledge management programs depends on the reinforcement of knowledge management processes and emphasizes the adhocracy culture in the organization.
How are arbuscular mycorrhizal associations related to maize growth performance during short-term cover crop rotation?

BACKGROUND Better cover crop management options aiming to maximize the benefits of arbuscular mycorrhizal fungi (AMF) to subsequent crops are largely unknown. We investigated the impact of cover crop management methods on maize growth performance and assemblages of AMF colonizing maize roots in a field trial. The cover crop treatments comprised Italian ryegrass, wheat, brown mustard and fallow in rotation with maize. RESULTS The diversity of AMF communities among cover crops used for maize management was significantly influenced by the cover crop and time course. Cover crops did not affect grain yield and aboveground biomass of subsequent maize but affected early growth. A structural equation model indicated that the root colonization, AMF diversity and maize phosphorus uptake had direct strong positive effects on yield performance. CONCLUSION AMF variables and maize performance were related directly or indirectly to maize grain yield, whereas root colonization had a positive effect on maize performance. AMF may be an essential factor that determines the success of cover crop rotational systems. Encouraging AMF associations can potentially benefit cover cropping systems. Therefore, it is imperative to consider AMF associations and crop phenology when making management decisions. © 2017 Society of Chemical Industry.
Oncolytic viruses: From bench to bedside with a focus on safety

Oncolytic viruses are a relatively new class of anti-cancer immunotherapy agents. Several viruses have undergone evaluation in clinical trials in the last decades, and the first agent is about to be approved to be used as a novel cancer therapy modality. In the current review, an overview is presented on recent (pre)clinical developments in the field of oncolytic viruses that have previously been or currently are being evaluated in clinical trials. Special attention is given to possible safety issues like toxicity, environmental shedding, mutation and reversion to wildtype virus.
Clinical outcomes of patients with diabetes mellitus treated with Absorb bioresorbable vascular scaffolds: a subanalysis of the European Multicentre GHOST‐EU Registry

Data on the clinical performance of bioresorbable scaffolds in patients with diabetes mellitus (DM) are still limited. The present study reported 1‐year clinical outcomes associated with the use of everolimus‐eluting bioresorbable vascular scaffolds (Absorb BVS; Abbott Vascular, Santa Clara, CA) in DM patients.
The Citrus Transcription Factor CsMADS6 Modulates Carotenoid Metabolism by Directly Regulating Carotenogenic Genes1

Citrus CsMADS6 coordinately and positively modulates carotenoid metabolism by directly regulating the expression of LCYb1 and other carotenogenic genes, including PSY, PDS, and CCD1. Although remarkable progress has been made toward understanding carotenoid biosynthesis, the mechanisms that regulate the transcription of carotenogenic genes remain poorly understood. Lycopene β-cyclases (LCYb) are critical enzymes located at the branch point of the carotenoid biosynthetic pathway. Here, we used the promoter sequence of LCYb1 as bait in a yeast one-hybrid screen for promoter-binding proteins from sweet orange (Citrus sinensis). This screen identified a MADS transcription factor, CsMADS6, that was coordinately expressed with fruit development and coloration. Acting as a nucleus-localized transcriptional activator, CsMADS6 directly bound the promoter of LCYb1 and activated its expression. Overexpression of CsMADS6 in citrus calli increased carotenoid contents and induced the expression of LCYb1 and other carotenogenic genes, including phytoene synthase (PSY), phytoene desaturase (PDS), and carotenoid cleavage dioxygenase1 (CCD1). CsMADS6 up-regulated the expression of PSY, PDS, and CCD1 by directly binding to their promoters, which suggested the multitargeted regulation of carotenoid metabolism by CsMADS6. In addition, the ectopic expression of CsMADS6 in tomato (Solanum lycopersicum) affected carotenoid contents and the expression of carotenogenic genes. The sepals of CsMADS6-overexpressing tomato lines exhibited dramatic changes in carotenoid profiles, accompanied by changes in plastid ultrastructure. Global transcriptome analysis of transgenic sepals revealed that CsMADS6 regulates a series of pathways that promote increases in flux through the carotenoid pathway. Overall, these findings establish that CsMADS6 directly regulates LCYb1 and other carotenogenic genes to coordinately and positively modulate carotenoid metabolism in plants, which may provide strategies to improve the nutritional quality of crops.
Learning Robust Object Recognition Using Composed Scenes from Generative Models

Recurrent feedback connections in the mammalian visual system have been hypothesized to play a role in synthesizing input in the theoretical framework of analysis by synthesis. The comparison of internally synthesized representation with that of the input provides a validation mechanism during perceptual inference and learning. Inspired by these ideas, we proposed that the synthesis machinery can compose new, unobserved images by imagination to train the network itself so as to increase the robustness of the system in novel scenarios. As a proof of concept, we investigated whether images composed by imagination could help an object recognition system to deal with occlusion, which is challenging for the current state-of-the-art deep convolutional neural networks. We fine-tuned a network on images containing objects in various occlusion scenarios, that are imagined or self-generated through a deep generator network. Trained on imagined occluded scenarios under the object persistence constraint, our network discovered more subtle and localized image features that were neglected by the original network for object classification, obtaining better separability of different object classes in the feature space. This leads to significant improvement of object recognition under occlusion for our network relative to the original network trained only on un-occluded images. In addition to providing practical benefits in object recognition under occlusion, this work demonstrates the use of self-generated composition of visual scenes through the synthesis loop, combined with the object persistence constraint, can provide opportunities for neural networks to discover new relevant patterns in the data, and become more flexible in dealing with novel situations.
Speech Enhancement using Affine Projection Algorithm and Normalized Kernel Affine Projection Algorithm

The aim of the Speech Enhancement system is to improve the quality of noisy speech signal. This paper emphasize on enhancement of noisy speech by using Affine Projection Algorithm (APA) and Kernel Affine Projection Algorithm (KAPA). Noise is present everywhere in the environment, So Kernel adaptive filters are used to enhance noisy speech signal and shows the good improvement in increasing the Signal to Noise Ratio (SNR) and Mean square error (MSE). The computer simulations are performed using NOIZEUS speech corpus for different SNR values using Affine projection (APA), Kernel Affine projection (KAPA), Recursive least square (RLS), Kernel least mean square (KLMS) and their performance is compared.
Functional Polyethylene Terephthalate with Nanometer‐Sized Bioactive Glass Coatings Stimulating In Vitro and In Vivo Osseointegration for Anterior Cruciate Ligament Reconstruction

Polyethylene terephthalate (PET) artificial ligament has been widely used for treating serious cases of anterior cruciate ligament (ACL) injuries. However, the major drawback of PET artificial ligament is their insufficient surface bioactivity which hinders its osseointegration and mechanical anchorage in the bone tunnel. The aim of the present study is to prepare functional akermanite (AKT) nanocoatings on PET artificial ligaments by pulsed laser deposition (PLD) in order to promote the in vitro osteogenic differentiation of BMSCs and in vivo osteointegration. The results show that AKT glass nanocoatings on PET with uniform nanoparticles (around 30 nm) have been successfully prepared by PLD method. The in vitro study displays that the prepared AKT‐PET grafts support the attachment of BMSCs, and significantly stimulate the proliferation and osteogenic differentiation of BMSCs in comparison to pure PET grafts. AKT coatings on PET grafts promote the regeneration of new bone at the interface of the grafts and host bone tissues, and enhance the bonding strength in vivo as compared to pure PET grafts. The study establishes a viable method to apply PLD technique for preparing bioactive ceramic‐coated PET artificial ligaments with significantly improved osseointegration for ACL reconstruction.
Arabic Speech Act Recognition Techniques

This article presents rule-based and statistical-based techniques for Arabic speech act recognition. The proposed techniques classify an utterance into Arabic speech act categories based on three criteria: surface features, cue words, and contextual information. A rule-based expert system has been developed in a bootstrapping manner based on the fact that Arabic language syntax is inherently rule-based. Various machine-learning algorithms have been used to detect Arabic speech act categories: Decision Tree, Naïve Bayes, Neural Network, and SVM. We compare the experimental results for both techniques (machine-learning and rule-based expert systems). Using a corpus of 1,500 sentences, the rule-based expert system achieved an accuracy rate of 98.92%, while the Decision Tree, Naïve Bayes, Neural Network, and SVM achieved an accuracy rate of 97.09%, 96.48%, 93.50%, and 93.70%, respectively.
One dimensional polymeric photonic crystal doped with second-order nonlinear optical chromophore

Organic nonlinear optical (NLO) materials have attracted much interest for their potential applications over the past two decades mainly because of their faster electronic response and larger optical nonlinearities than the conventional inorganic materials. Especially, electro-optic (EO) polymers have been promising candidates for fast and broadband EO modulators as a result of the development of the 2nd-order NLO chromophore. In this manuscript, we report fabrication and design of one dimensional (1D) polymeric photonic crystals (PCs) to additionally enhance the optical nonlinearities of the organic NLO materials. We fabricated polymeric high-reflection mirrors for 1D PCs by a simple alternatively spin-coating two polymers under control of their optical thickness, in which a novel polymer was applied to the higher refractive index layer. We also designed defect-mode 1D polymeric PC for effective light-localization in the defect layer and discussed their effect for enhancement of the 2nd-order optical nonlinearities.
Differentially private sequential data publication via variable-length n-grams

Sequential data is being increasingly used in a variety of applications. Publishing sequential data is of vital importance to the advancement of these applications. However, as shown by the re-identification attacks on the AOL and Netflix datasets, releasing sequential data may pose considerable threats to individual privacy. Recent research has indicated the failure of existing sanitization techniques to provide claimed privacy guarantees. It is therefore urgent to respond to this failure by developing new schemes with provable privacy guarantees. Differential privacy is one of the only models that can be used to provide such guarantees. Due to the inherent sequentiality and high-dimensionality, it is challenging to apply differential privacy to sequential data. In this paper, we address this challenge by employing a variable-length n-gram model, which extracts the essential information of a sequential database in terms of a set of variable-length n-grams. Our approach makes use of a carefully designed exploration tree structure and a set of novel techniques based on the Markov assumption in order to lower the magnitude of added noise. The published n-grams are useful for many purposes. Furthermore, we develop a solution for generating a synthetic database, which enables a wider spectrum of data analysis tasks. Extensive experiments on real-life datasets demonstrate that our approach substantially outperforms the state-of-the-art techniques.
Query-to-Communication Lifting for BPP

For any n-bit boolean function f, we show that the randomized communication complexity of the composed function f o g^n, where g is an index gadget, is characterized by the randomized decision tree complexity of f. In particular, this means that many query complexity separations involving randomized models (e.g., classical vs. quantum) automatically imply analogous separations in communication complexity.
The Mental Representation of Polysemy across Word Classes

Experimental studies on polysemy have come to contradictory conclusions on whether words with multiple senses are stored as separate or shared mental representations. The present study examined the semantic relatedness and semantic similarity of literal and non-literal (metonymic and metaphorical) senses of three word classes: nouns, verbs, and adjectives. Two methods were used: a psycholinguistic experiment and a distributional analysis of corpus data. In the experiment, participants were presented with 6–12 short phrases containing a polysemous word in literal, metonymic, or metaphorical senses and were asked to classify them so that phrases with the same perceived sense were grouped together. To investigate the impact of professional background on their decisions, participants were controlled for linguistic vs. non-linguistic education. For nouns and verbs, all participants preferred to group together phrases with literal and metonymic senses, but not any other pairs of senses. For adjectives, two pairs of senses were often grouped together: literal with metonymic, and metonymic with metaphorical. Participants with a linguistic background were more accurate than participants with non-linguistic backgrounds, although both groups shared principal patterns of sense classification. For the distributional analysis of corpus data, we used a semantic vector approach to quantify the similarity of phrases with literal, metonymic, and metaphorical senses in the corpora. We found that phrases with literal and metonymic senses had the highest degree of similarity for the three word classes, and that metonymic and metaphorical senses of adjectives had the highest degree of similarity among all word classes. These findings are in line with the experimental results. Overall, the results suggest that the mental representation of a polysemous word depends on its word class. In nouns and verbs, literal and metonymic senses are stored together, while metaphorical senses are stored separately; in adjectives, metonymic senses significantly overlap with both literal and metaphorical senses.
Conductive asphalt concrete: A review on structure design, performance, and practical applications

Conductive asphalt concrete can be used to help pavement snow melting/deicing by an asphalt pavement electrical heater. It is an emerging technology to ensure safety driving during winter time. Based on the Joule heating law, an electric current passing through the conductive asphalt concrete (a conductor) could generate enough heat to prevent snow accumulation and icing on the asphalt pavement surface. This article provides a review on the material design, construction technique, performance evaluation, and engineering applications of conductive asphalt concrete. The literature shows that the conductivity and mechanical properties of conductive asphalt concrete are strongly dependent on the material compositions and mixing programs. Meanwhile, the mechanism of conductivity improvement is identified according to the characteristics of conductive additives. In addition, the effects of service conditions on the resistivity are evaluated. Asphalt pavement electrical heater technique shows some appreciable advantages in environment protection and traffic safety aspects, although it has few applications in the highway industry. It therefore recommends that further investigations on asphalt pavement electrical heater are indispensable and should focus on some covered issues besides the existing research, such as proper material selection, resistivity stability, desirable high operational efficiency, and suitable construction technique.
A New Copper Smelting Technology - Bottom Blown Oxygen Furnace Developed at Dongying Fangyuan Nonferrous Metals

Bottom blown oxygen copper smelting process has been developed in Dongying, China by Dongying Fangyuan Nonferrous Metals Co., Ltd. in commercial scale. This is the first modern copper smelting technology developed in China with the advantages of high oxygen enrichment, low temperature and autothermal operation. Production capacity of more than 100,000 tonnes per year of copper has been achieved through a single bottom blown oxygen furnace with instantaneous feed rates reaching up to 90 t/h. The main features of the bottom blowing smelting process are that high grade matte (up to 72 wt% Cu) can be produced at relatively low temperatures with 2-3 wt% Cu remaining in the smelting slag. Analyses of quenched smelting slag show that significant amount of magnetite crystals are present in the slags at operating temperature which indicates that the operating temperature was much lower than the liquidus temperature of the slag. After four years operation this new technology has shown great potential for expanding production capability and energy saving. Process development continues on the first commercial scale bottom blown furnace at Dongying Fangyuan Nonferrous Metals and a larger bottom blown smelting furnace is under construction.
Network-Based Disease Gene Prioritization by Hitting Time Analysis

Many methods have been published to prioritize genes using network theory. By using protein-protein interaction (PPI) data, it is possible to use mathematical features to rank and prioritize genes products in the network. Taking into account that genes related to the same diseases tend to connect, in the network structure, the prioritization methods search for candidate genes in the neighborhood of other genes already known to be related to a specific phenotype. Unfortunately, some existing algorithms can not deal well with highly connected genes, and some of them end up being related by chance to the disease being studied. We propose a pure method, with no need of adjustments, based on the hitting time of a random walk in PPI networks. This method captures information of the whole network and can equally prioritize genes regardless of its degree. We tested the efficiency of our method prioritizing candidate genes for Attention-Deficit/Hyperactivity Disorder (ADHD). The proposed method was able to give a good rank to genes that have genetic association with ADHD and was able to prioritize a large proportion of genes prioritized by other random-walk-based methods.
Experimental Analysis of the Accessibility of Drawings with Few Segments

The visual complexity of a graph drawing is defined as the number of geometric objects needed to represent all its edges. In particular, one object may represent multiple edges, e.g., one needs only one line segment to draw two collinear incident edges. We study the question if drawings with few segments have a better aesthetic appeal and help the user to asses the underlying graph. We design an experiment that investigates two different graph types (trees and sparse graphs), three different layout algorithms for trees, and two different layout algorithms for sparse graphs. We asked the users to give an aesthetic ranking on the layouts and to perform a furthest-pair or shortest-path task on the drawings.
Survey of Consistent Software-Defined Network Updates

Computer networks have become a critical infrastructure. In fact, networks should not only meet strict requirements in terms of correctness, availability, and performance but they should also be very flexible and support fast updates, e.g., due to policy changes, increasing traffic, or failures. This paper presents a structured survey of mechanism and protocols to update computer networks in a fast and consistent manner. In particular, we identify and discuss the different desirable consistency properties that should be provided throughout a network update, the algorithmic techniques which are needed to meet these consistency properties, and the implications on the speed and costs at which updates can be performed. We also explain the relationship between consistent network update problems and classic algorithmic optimization ones. While our survey is mainly motivated by the advent of software-defined networks and their primary need for correct and efficient update techniques, the fundamental underlying problems are not new, and we provide a historical perspective of the subject as well.