Miracle-dz/UniFAR-FTUs huggingface dataset:
Phyto-Mediated Synthesis of Gold Nanoparticles using Aqueous Extract of Momordica cochinchinensis Rhizome and Their Biological Activities

Article history: Received 03 January 2016 Accepted 12 January 2016 Available online 26 February 2016 In the present study, plant mediated synthesis of gold nanoparticles (AuNPs) using aqueous extract of Momordica cochinchinensis rhizome at room temperature as a reducing as well as a stabilizing agent is reported. The gold nanoparticles synthesized by a green chemical approach were characterized by UV– visible spectroscopy; Transmission Electron Microscopy (TEM), Energy Dispersive X-ray (EDX), X-ray Diffraction (XRD) and Fourier transform infrared (FT-IR) spectroscopy. The formation of AuNPs, observed by colour changes from yellow to ruby red is confirmed by UV–visible spectroscopy showing surface plasma resonance band that at 535 nm. The crystalline nature of the AuNPs formed as face centered cubic structure is evident from the selected area electron diffraction (SAED) and XRD pattern. FT-IR spectrum showed the presence of different biomolecules in the Momordica cochinchinensis rhizomes aqueous extract responsible for the reduction and stabilization of AuNPs. Phytosynthesized AuNPs showed better antioxidant activity than the aqueous extract when analysed by using DPPH, NO, H2O2 and reducing power assay methods. Moreover, the biosynthesized AuNPs significantly inhibited the growth of medically important pathogenic gram positive bacteria and gram negative bacteria.
Numerical analysis of combined natural convection-internal heat generation source-surface radiation

Numerical study of combined laminar natural convection and surface radiation with internal heat generation is presented in this paper and computations are performed for an air-filled square cavity whose four walls have the same emissivity. Finite volume method through the concepts of staggered grid and SIMPLER algorithm has been applied, and the view factors are determined by analytical formula. A power scheme is also used in approximating advection-diffusion terms. Representative results illustrating the effects of emissivity and the internal heat generation on the streamlines and temperature contours within the enclosure are reported. In addition, obtained results for local and average convective and radiative Nusselt, for various parametric conditions, show that internal heat generation modifies significantly the flow and temperature fields.
Distributed event-based control strategies for interconnected linear systems

This study presents distributed event-based control strategies for a networked dynamical system consisting of N linear time-invariant interconnected subsystems. Each subsystem broadcasts its state over the network according to certain triggering rules that only depend on local information. The system can converge asymptotically to the equilibrium point under the proposed control design, and the existence of a lower bound for the broadcasting period is guaranteed. A novel model-based approach is derived to reduce the communication between the agents. Simulation results show the effectiveness of the proposed approaches and illustrate the theoretical results.
Isolation, Identification and Extracellular Enzymatic Activity of Culturable Extremely Halophilic Archaea and Bacteria of IncheBoroun Wetland

Extremely halophilic diversity of IncheBroun wetland located in the north of Iran was investigated by using culture-dependent methods. Sampling was carried out in May and September 2014. In each sampling 4 distinct regions of wetland were analyzed by using complex media like MGM, JCM168, MH1 and an alkaliphilic medium containing 23% salts. After incubation at 40°C, a total of 406 isolates and 2.1 × 106 CFU/ml were obtained in culture media. Among them 361 isolates were obtained from MGM and 39 isolates from JCM 168, 3 isolates from MH1 and 3 isolates from the alkaliphilic media. Initial morphological, biochemical and physiological tests were performed. Production of 4 hydrolytic enzymes by 45 selected strains was assayed qualitatively. A total of 38, 19 and 6 strains were able to produce lipase, DNase and amylase activity. Protease activity was not observed among strains. As total 45 strains were selected randomly and phylogenetic analysis of 16S rRNA was performed for them. Among selected strains 40 isolated strians belonged to Haloarchaea and were belonged to the genera: Haloarcula(30%), Halorubrum(27.5%), Haloferax(17.5%), Halobellus (10%), Halogeometricum(5.2%), Halobacterium(2.6%), Halolamina(2.6%), Halorhabdus (2.6%) and Halostagnicola (2.6%). Haloarcula and Halorubrum were the dominant populations. A total of 5 strains belonged to domain of Bacteria and were similar to members of Rhodovibrio (40%), Pseudomonas (40%) and Salicola (20%).
Genomic Simple Sequence Repeat Markers Reveal Patterns of Genetic Relatedness and Diversity in Sesame

Sesame (Sesamum indicum L. syn. Sesamum orientale L.) is an orphan crop species with most molecular genetic research work done in the last decade. In this study, we used a pyrosequencing approach for the development of genomic simple‐sequence repeat (SSR) markers in sesame. Our approach proved successful in identifying 19,816 nonredundant SSRs, 5727 of which were identified in a contig assembly that covers 19.29% of the sesame genome. Mononucleotide repeats were the most abundant SSR type identified in the sesame genome (48.5% of all SSRs), followed by dinucleotide SSRs (45.0%). Adenine–thymine‐rich motifs were predominant, representing 81.7, 51.7, 66.5, and 22.1% of the mononucleotide, dinucleotide, trinucleotide, and tetranucleotide SSRs, respectively. As a result of this work, we introduce 933 experimentally validated sesame specific markers, 849 of which are also applicable in Sesamum mulayanum (syn. Sesamum orientale var. malabaricum Nar.), the wild progenitor of cultivated sesame. Using a subset of the newly identified SSR markers, we analyzed molecular genetic diversity and population structure of a collection of world accessions. Results of the two analyses almost overlapped and suggested correlation between genetic similarity and geographical proximity. Indeed, a pattern of gene flow among sesame diversity centers was apparent, with levels of variability in some regions similar to that seen in the domestication origin of the crop. Taken together with the high rate of genomic marker transferability detected between S. indicum and S. mulayanum, our results represent additional molecular genetic evidence for designating the two taxa as cultivated and wild forms of the same species.
Analytical Derivation of Moments of System Applying Diversity at Micro and Macro Level in Gamma Shadowed Nakagami-m Fading Channels

In this paper, we derive a closed-form expression for moments of system with maximal-ratio combining (MRC) microdiversity and selection combining (SC) macrodiversity reception operating in correlated gamma shadowed Nakagami-m fading channel, and in this way finalize our previous works related to investigation of firstand second-order performance measures of described system. In addition, we focus on research of influence of system and channel parameters on both average output signal and amount of fading (AoF). Keywords-fading; macrodiversity; microdiversity; shadowing; system moment
Stress evaluation of dental implant wall thickness using numerical techniques

Using the Finite Element Method, four implant diameters were evaluated for their effect on the stress distribution at the implant wall. A two-dimensional model of the implant and mandibular bone used triangular and quadrilateral plane strain elements to compute the von Mises stress in the bone with varied masticatory forces and abutment screw preloads. The masticatory force is found to be more influential than abutment screw preload, and implant wall thickness significantly influences the stress magnitude within the implant.
Hydrophobic Interactions of Xenon by Monte Carlo Simulations

Hydrophobic interactions of xenon atoms dissolved in liquid water were studied by NpT Monte Carlo simulations in the temperature range 298.15 to 333K and at ambient pressure. Structural properties of dilute xenon solutions were calculated and compared to those of bulk water in order to show the influence of the hydrophobic solute. It was found that the xenon atoms tend to aggregate with increasing temperature. At low temperatures the aggregates are predominantly solvent-separated pairs; at higher temperatures the quota of contact pairs increases. Furthermore, the residual chemical potentials of xenon and water were calculated with different methods; it was found that the Widom insertion methods works best for this system. For the thermodynamic conditions of this work, the residual chemical potential of water in the presence of xenon was found to be a linear function of temperature.
Branding as an opportunity of SMEs ’ internationalization strategy in B 2 B market Uusitalo , Olavi

Branding theory has its origins in the consumer product markets. The brand is presented as a market signal targeted mostly to the end consumers and enabling them to save time by guaranteeing a certain level of quality, simplifying their choices, and answering to specific needs. Little research has been done to investigate the relevance and the role of brands in industrial markets. Even less research has been done of the brands within SMEs in industrial markets. Brand loyalty can tie the customer very strongly to a supplier. Brand reputation has also been argued to be considered as a psychological factor affecting purchase from a certain supplier. Brand reputation is not necessarily connected to a product or service but can also in business-to-business or service industries be connected to the reputation of a company. The modularity can be helpful for a SME not only creating economies of scale and economies of scope but also in brand creation. We argue that brand creation is important for internationalizing SMEs in the B2B market and that modularity can be used in brand creation. To demonstrate this we give an example of a Finnish SME, KPatents, operating in the global market. The company has created recognition in the industries were they operate by using the “coca-cola bottle effect”. This means that everybody can recognize the KPatents process refractometer by its shape and colour. This effect is the most effective in the case when a SME is internationalizing as a late starter. The cover module has always the same shape and red colour. This paper contributes to the research area of global branding among SMEs in the international industrial market.
Single‐Crystalline Copper Nanowires Produced by Electrochemical Deposition in Polymeric Ion Track Membranes

In the recent past, investigations have focused increasingly on confined systems with micrometer and, in particular, nanometer dimensions. Due to their restricted size, these structures exhibit novel physical and chemical properties, and have opened up a large new field of basic research as well as possible applications. Electrochemical deposition is becoming an increasingly attractive method for the synthesis of new materials and nanostructures.
Arabic Named Entity Recognition Using Topic Modeling

In this article, we introduce novel features for Arabic Named Entity Recognition (NER) based on Latent Dirichlet Allocation (LDA), a widely used topic modeling technique. We investigate and analyze three different approaches for utilizing LDA, including two newly proposed ones, namely Topical Prototypes approach and Topical Word Embeddings approach. Our Experiments show that each of the presented approaches improves the baseline features, among which the Word-Class LDA approach performs the best. Moreover, the combination of these topic modeling approaches provides additive improvements, outperforming traditional word representations as Skip-gram word embeddings and Brown Clustering. The proposed LDA-based features, learned in an unsupervised way, are fully language-independent and have proven to be very effective to enrich and boost NER models for Arabic, a morphologically rich language.
AUTOMATED CLASSIFICATION OF BRAIN MRI USING COLOR-CONVERTED K-MEANS CLUSTERING SEGMENTATION AND APPLICATION OF DIFFERENT KERNEL FUNCTIONS WITH MULTI-CLASS SVM

: This paper proposes a hybrid approach for classification of brain magnetic resonance images (MRI) based on color converted hybrid clustering segmentation algorithm and wrapper based feature selection with multi-class support vector machine (SVM). The texture, color and shape features have been extracted and these features are used to classify MR brain images into three categories namely normal, benign and malignant. The MR images are classified by wrapper approach with Multi class Support Vector Machine classifier (MC-SVM) using color, texture and shape features. Performance of the MC-SVM classifier is compared with different kernel functions. From the analysis and performance measures like classification accuracy, it is inferred that the brain MRI classification is best done using MC-SVM with Gaussian RBF kernel function than linear and polynomial kernel functions. The proposed system can provide best classification performance with high accuracy and low error rate.
Understanding dyadic promoter-stakeholder relations in complex projects

In this study, we propose a Bilateral Double Motive framework of stakeholder cooperation in complex projects. The framework analyses and explains dyadic promoter-stakeholder relationships at a micro level by acknowledging both transactional and relational motives. We demonstrate the framework’s usefulness by illustrating its explanatory power in two instances of cooperation and two of non-cooperation within two health information technology projects. The study contributes to project management theory through its combined focus on transactional and relational motives. Further, the study contributes to practice by providing a tool for planning and evaluating cooperation in health Information Technology projects and similar complex multi-stakeholder environments.
A Qualitative Study on Factors that Influence Students ’ Food Choices

Background: Few adolescents are eating recommended amounts of healthful food items at school. The purpose of this study was to gain an in-depth understanding of participating students’ perception of their school menu, determine what influences their food choices, and solicit suggestions for improving the meals served in their school cafeteria. Methods: Twelve focus groups among a total of 80 students were conducted among 7th to 12th grade students in school classrooms in the Lincoln Parish School District in Louisiana. Five focus groups were conducted with African-American students, five with White students, and two with both races combined. Students were asked about factors that influence their food choices and where they get nutrition knowledge. Responses were organized according to common themes and patterns and were guided by an ecological model. Results: Multiple levels of influence on students’ food choices were indicated, including taste, food appearance, the name of the food and/or familiarity with the food, cultural preferences, and perceived food safety. Students reported receiving little nutrition knowledge from school. Conclusions: To promote healthy food choices in schools, school food service staff should consider offering taste testing sessions for new foods; improve food presentation by making food appealing; ensure food is cooked properly and monitor workers adherence to food safety standards, alleviate long lines during lunch periods and incorporate cultural practices such as seasoning or cooking methods. Nutrition education could be integrated into school curriculum and at the point-of-purchase to enhance these students’ nutrition knowledge.
Green synthesis of gold nanoparticles using plant extract: Mini-review

In this review, we examine the greenest nanoparticles of zero-valent metals, metal oxides and metal salts, with emphasis on recent developments routes. Products from nature or those derived from natural products, such as extracts of several plants or parts of plants, tea, coffee, banana, simple amino acids, as well as wine, table sugar and glucose, have been used as reductants and as capping agents during the present synthesis method. Polyphenols found in plant material often play a key role in the processes mentioned here. The techniques involved are generally one-pot processes, environmentally friendly and simple. Green synthesis of gold nanoparticles using several extracts and spices extracts was conducted, in which aqueous extracts HAuCl4.3H2O reduce to Au° has establishing themselves in specific crystal phase. Synthesized nanoparticles were confirmed by the color change of auric chloride which is yellow. The growth of nanoparticles was monitored by the behavior of surface Plasmon using UV-Vis spectroscopy; also the pH was determined meanwhile. Moreover, this approach is not only of a green rapid synthesis kind and considered as a better alternative to chemical synthesis, but also found to be effective for large scale synthesis of gold nanoparticles.
Re-use of agro-industrial wastes: recovery of valuable compounds by eco-friendly techniques

The global demographic expansion has determined a voracious demand for edible goods, thus also originating the primary issues about the disposal of waste and byproducts with high environmental impact. Waste, by-products and effluents coming from industrial processing and agricultural procedures of vegetables and fruit can be defined as biomass, according to CE directive 2001/77. Those raw materials are currently used as compost, animal feed and biofuel production. In addition, these products can be used as starting substrates for the production of high value-added compounds according to the biorefinery concept. In this review, the biorefinery strategy was applied on waste coming from the industrial processing of lemon and tomato, two of the most abundant vegetables in Italy.
Multi-agent path topology in support of socially competent navigation planning

We present a navigation planning framework for dynamic, multi-agent environments, where no explicit communication takes place among agents. Inspired by the collaborative nature of human navigation, our approach encodes the concept of coordination into an agent’s decision making through an inference mechanism about collaborative strategies of collision avoidance. Each such strategy represents a distinct avoidance protocol, prescribing a distinct class of navigation behaviors to agents. We model such classes as equivalence classes of multi-agent path topology, using the formalism of topological braids. This formalism may naturally encode any arbitrarily complex, spatiotemporal, multi-agent behavior, in any environment with any number of agents into a compact representation of dual algebraic and geometric nature. This enables us to construct a probabilistic inference mechanism that predicts the collective strategy of avoidance among multiple agents, based on observation of agents’ past behaviors. We incorporate this mechanism into an online planner that enables an agent to understand a multi-agent scene and determine an action that not only contributes progress towards its destination, but also reduction of the uncertainty of other agents regarding the agent’s role in the emerging strategy of avoidance. This is achieved by picking actions that compromise between energy efficiency and compliance with everyone’s inferred avoidance intentions. We evaluate our approach by comparing against a greedy baseline that only maximizes individual efficiency. Simulation results of statistical significance demonstrate that our planner results in a faster uncertainty decrease that facilitates the decision-making process of co-present agents. The algorithm’s performance highlights the importance of topological reasoning in decentralized, multi-agent planning and appears promising for real-world applications in crowded human environments.
CHEMICAL VAPOR DEPOSITIONS FOR CARBON NANOTUBES SYNTHESIS

Carbon nanotubes (CNTs) have been under scientific investigation more than fifteen years since their unique properties predestine them for numerous potential applications. The field of nanotechnology and nanoscience push their investigation forward to produce CNTs with suitable parameters for future applications. It is evident that new approaches of their synthesis need to be developed and optimized. In this chapter, brief history, types, structure and especially the different synthesis methods for CNTs preparation are reviewed. The attention is mainly aimed on various types of chemical vapor depositions as CVD methods for uniform vertically aligned CNT synthesis, liquid pyrolysis and solid state pyrolysis.
Tracing Requirements as a Problem of Machine Learning

Software requirement engineering and evolution essential to software development process, which defines and elaborates what is to be built in a project. Requirements are mostly written in text and will later evolve to fine-grained and actionable artifacts with details about system configurations, technology stacks, etc. Tracing the evolution of requirements enables stakeholders to determine the origin of each requirement and understand how well the software’s design reflects to its requirements. Reckoning requirements traceability is not a trivial task, a machine learning approach is used to classify traceability between various associated requirements. In particular, a 2-learner, ontology-based, pseudo-instances-enhanced approach, where two classifiers are trained to separately exploit two types of features, lexical features and features derived from a hand-built ontology, is investigated for such task. The hand-built ontology is also leveraged to generate pseudo training instances to improve machine learning results. In comparison to a supervised baseline system that uses only lexical features, our approach yields a relative error reduction of 56.0%. Most interestingly, results do not deteriorate when the hand-built ontology is replaced with its automatically constructed counterpart.
SOURCE: Sheridan Institutional Repository SOURCE: Sheridan Institutional Repository

John the Ripper (JtR) is an open source software package commonly used by system administrators to enforce password policy. JtR is designed to attack (i.e., crack) passwords encrypted in a wide variety of commonly used formats. While parallel implementations of JtR exist, there are several limitations to them. This research reports on two distinct algorithms that enhance this password cracking tool using the Message Passing Interface. The first algorithm is a novel approach that uses numerous processors to crack one password by using an innovative approach to workload distribution. In this algorithm the candidate password is distributed to all participating processors and the word list is divided based on probability so that each processor has the same likelihood of cracking the password while eliminating overlapping operations. The second algorithm developed in this research involves dividing the passwords within a password file equally amongst available processors while ensuring load-balanced and fault-tolerant behavior. This paper describes John the Ripper, the design of these two algorithms and preliminary results. Given the same amount of time, the original JtR can crack 29 passwords, whereas our algorithms 1 and 2 can crack an additional 35 and 45 passwords respectively.