Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding the Progressive Nature of Inter-Organizational Systems (IOS) Adoption

Inter-organizational Systems (IOS) cannot be adopted by any organizations in isolation from their trading partner. Their adoption requires cooperation and collaboration between trading partners and, therefore, is reliant on the nature of relationships between the parties involved. For organizations to progress in their IOS adoption, improvement in relationships between trading partners is required before they can adopt a more sophisticated IOS. In addition, through IOS adoption, trading partners can actually improve their relationships overtime. There has been some research that investigates relationships and how organizations progress from one level to the next level of adoption. However, these studies do not clearly define the concepts of relationship, IOS adoption and IOS adoption maturity. Furthermore, they do not adequately justify the exclusion of other variables in defining the relevant concepts and are not theoretically based. This research extends the Kurnia and Johnston (2000) process model of IOS adoption by incorporating the notion of IOS adoption maturity and reducing the scope from a supply chain to a dyadic level to enable better evaluations of IOS adoption progression. We argue that with the proposed model, the dynamics of IOS adoption maturity can be better examined empirically.
Genetic algorithm for weight assignment in optimum planning of multiple distributed generations to minimize energy losses

Renewable distributed generation (DG) is attracting special attention in order to meet the growing demand. Wind energy will drive rapid growth of distributed renewable energy systems in rural and remote areas worldwide. The one of the major potential benefits offered by DG concept is the reduction of total system losses. Because of the time-varying characteristics of both generation and load, energy loss minimization should be considered instead of power loss minimization. In this paper, a new and simple methodology is proposed to find optimal sizes and locations of DGs in order to minimize energy losses. This method is based on genetic algorithm and weighting factor. The effectiveness of proposed method is tested on the IEEE-30 bus mesh network. The results show that the proposed method is capable of finding the optimal sizing of DG to minimize energy losses for candidate DG buses.
A collaborative filtering recommender system based on user's time pattern activity

Collaborative filtering has been considerably successful in improving recommender systems both in the literature and commercial applications. Most of the algorithms designed up to now consider users' ratings equally and do not pay attention to the fact that users' interests or requirements might change over the time. In this paper a collaborative filtering based recommender system is designed which tries to find each user's interests to each group of items, thus resulting to a better prediction of ratings a user will give to an item in the near future. This goal is achieved through using the ratings' timestamp, predefined groups of items, and defining a new similarity measure among users. Unlike standard collaborative filtering methods and many new ones in which similarity between users is defined as a single number, in this research we define similarity between users as “group similarity” which is an array of similarity values between items of each group rated by two users. Predefined groups for items e.g. genres for movies, are used as groups for items. Also for calculating similarity, different weights will be dedicated to ratings of each user based on the ratings' timestamp, i.e. a rating with higher timestamp will receive a higher weight. Empirical tests show that our proposed algorithm works better than standard User-based and Item-based collaborative filtering methods in the case of predicting users' interests in the near future with higher precision. Also it is empirically shown that our algorithm works considerably well for cold-start users.
Speech segment network approach for optimization of synthesis unit set

Abstract In this paper, a speech segment network approach for the construction of a suitable synthesis unit set with which high-quality speech can be synthesized, and yet which is of small enough size to be practical, is proposed. The speech segment network approach selects a synthesis unit set in which segmental and/or inter-segmental distortions are minimized by using combinatorial optimization methods such as iterative improvement and simulated annealing. Experimental results using diphone segments have shown that the suitable diphone unit sets, with total or maximum of inter-segmental distortion reduced by about 35 and 30%, respectively, can be constructed using this method. This reduction rate was enhanced as the segment candidate population increased. Effectiveness of this unit set design was also perceptually confirmed by a listening test, using speech synthesized with the selected diphone unit set.
The Improved Fast ICA Algorithm in the Application of Vibration Signal Analysis Research

In the process of mechanical equipment condition monitoring, the sensors do not often collect independent source signals of vibration, acquisition is the mixture vibration signals of tested mechanical equipment and the neighbourhood, it brings certain difficulties to the mechanical equipment condition and fault monitoring. Aiming at this problem, it put forward an improved algorithm of fast independent component analysis (Fast ICA), mixed signal can be extracted into separations of acquisition. The algorithm based on maximum negentropy iteration establish the objective function, with the non gaussian signal as the yardstick, then, solve the target function. Finally, the method is verified by mechanical vibration simulation signals that it can effectively separate the mixed signals, separated results show that the algorithm has stability and accuracy, and provide an important guarantee for the mechanical fault diagnosis, practical it has practical significance.
An Evaluation of the Stemness, Paracrine, and Tumorigenic Characteristics of Highly Expanded, Minimally Passaged Adipose-Derived Stem Cells

The use of adipose-derived stem cells (ADSC) in regenerative medicine is rising due to their plasticity, capacity of differentiation and paracrine and trophic effects. Despite the large number of cells obtained from adipose tissue, it is usually not enough for therapeutic purposes for many diseases or cosmetic procedures. Thus, there is the need for culturing and expanding cells in-vitro for several weeks remain. Our aim is to investigate if long- term proliferation with minimal passaging will affect the stemness, paracrine secretions and carcinogenesis markers of ADSC. The immunophenotypic properties and aldehyde dehydrogenase (ALDH) activity of the initial stromal vascular fraction (SVF) and serially passaged ADSC were observed by flow cytometry. In parallel, the telomerase activity and the relative expression of oncogenes and tumor suppressor genes were assessed by q-PCR. We also assessed the cytokine secretion profile of passaged ADSC by an ELISA. The expanded ADSC retain their morphological and phenotypical characteristics. These cells maintained in culture for up to 12 weeks until P4, possessed stable telomerase and ALDH activity, without having a TP53 mutation. Furthermore, the relative expression levels of TP53, RB, and MDM2 were not affected while the relative expression of c-Myc decreased significantly. Finally, the levels of the secretions of PGE2, STC1, and TIMP2 were not affected but the levels of IL-6, VEGF, and TIMP 1 significantly decreased at P2. Our results suggest that the expansion of passaged ADSC does not affect the differentiation capacity of stem cells and does not confer a cancerous state or capacity in vitro to the cells.
Numerical simulations of type III planetary migration – I. Disc model and convergence tests

Planets are believed to form in primordial gas-dust discs surrounding newborn stars. An important breakthrough in our understanding of planetary formation was the discovery of extra-solar planets around sun-like stars, especially the frequent occurrence of giant planets on close orbits (hot Jupiters). The mechanisms involved in the formation of these objects remain uncertain, however the difficulties associated with their formation at their observed orbital radius has awoken an interest in theories for the migration of protoplanetary cores due to gravitational interaction with the disc. There are three fundamental regimes of planet migration. The type I and II migration regimes, driven by the differential Lindblad torques, result mostly in inward migration and concern low- and high-mass planets respectively. Type III migration, driven by the co-orbital gas flow, concerns an intermediate range of planetary masses and does not have a predefined direction.In this thesis the orbital evolution of a high-mass, rapidly (type III) migrating planet is investigated using numerical hydrodynamical simulations. For these simulations we used the state-of-the-art hydrodynamics code FLASH. We focus on the physical aspects of type III migration. However, the problem of rapid migration of such massive planets is numerically challenging, and the disc model has to be chosen carefully, using numerical convergence as a discriminator between models (Paper I). We simulate both inward and outward directed migration (Papers II and III) and provide an extensive description of the co-orbital flow responsible for driving the migration, as well as its time evolution. The migration rate due to type III migration is found to be related to the mass of the planet's co-orbital region, making inward and outward directed migration self-decelerating and self-accelerating processes respectively (for a standard disc model). Rapid migration depends strongly on the flow structure in the planet's vicinity, which makes it sensitive to the amount of mass accumulated by the planet as it moves through the disc. This quantity in turn depends on the structure of the accretion region around the planet. The results of the numerical simulations show a good agreement with the analytical formulation of type III migration (Paper IV).
A new chopper modulator circuit

This paper presents new chopper modulators which can able assign three modulators in one circuit. It consists of Cowan, Ring and amplitude modulators. The proposed circuit is implemented from the different voltage current conveyor, four-MOS transistors switch and two-MOS transistors inverter. The advantage of this proposed circuit is high-input and low-output impedance and is able to connect with any load without buffer and the number of transistor is quite less which is suitable for integrated circuits. The technique is to control the switch by using the square pulse which is obtained from direct signal generator. All simulation results are base on the PSPICE program simulator which confirms the performance of the proposed circuit and technique.
Mastering seeds for genomic size nucleotide BLAST searches.

One of the most common activities in bioinformatics is the search for similar sequences. These searches are usually carried out with the help of programs from the NCBI BLAST family. As the majority of searches are routinely performed with default parameters, a question that should be addressed is how reliable the results obtained using the default parameter values are, i.e. what fraction of potential matches have been retrieved by these searches. Our primary focus is on the initial hit parameter, also known as the seed or word, used by the NCBI BLASTn, MegaBLAST and other similar programs in searches for similar nucleotide sequences. We show that the use of default values for the initial hit parameter can have a big negative impact on the proportion of potentially similar sequences that are retrieved. We also show how the hit probability of different seeds varies with the minimum length and similarity of sequences desired to be retrieved and describe methods that help in determining appropriate seeds. The experimental results described in this paper illustrate situations in which these methods are most applicable and also show the relationship between the various BLAST parameters.
Dynamic Token Based Improving MapReduce Performance in Cloud Computing

In recent years, Hadoop, the open-source implementation of Google's MapReduce, is widely used and has become the de facto standard of big data processing. A typical running environment of Hadoop is cloud computing in which resource heterogeneity is very common due to varied factors including the different hardware of nodes and the different workload on the nodes and etc. The slot-based scheduling in Hadoop causes the inefficient utilization of computing resources in cloud computing environment, which lead to the performance degradation. To solve the problem mentioned above, we propose a dynamic token based method which dynamically controls the number of tasks running on each node according to the available computing resources on a node and the resource requirement of a task. The results of evaluations show that the completion times of single jobs with the proposed method are approaching to the static optimum in the dedicated environment and better than the static optimums in the other two competitive environments. Moreover, the proposed method significantly improves the throughput of mixed workloads in all computing environments and performance in real cloud computing environment have been improved by 45.9% on average.
CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction

We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks.
SocRoutes: safe routes based on tweet sentiments

Location-based services, and in particular personal navigation systems, have become increasingly popular with the widespread use of GPS technology in smart devices. Existing navigation systems are designed to suggest routes based on the shortest distance or the fastest time to a target. In this paper, we propose a new type of route navigation based on regional context---primarily sentiments. Our system, called SocRoutes, aims to find a safer, friendlier, and more enjoyable route based on sentiments inferred from real-time, geotagged messages from Twitter. SocRoutes tailors routes by avoiding places with extremely negative sentiments, thereby potentially finding a safer and more enjoyable route with marginal increase in total distance compared to the shortest path. The system supports three types of traveling modes: walking, bicycling, and driving. We validated the idea based on crime history data from the City of Chicago Portal in December 2012, and sentiments extracted from geotagged tweets during the same time. We discovered that there was a significant correlation between regional Twitter posting sentiments and crime rate, in particular for high-crime and highly negative sentiment areas. We also demonstrated that SocRoutes, by solely utilizing social media sentiments, can find routes that bypass crime hotspots.
Currency boards: are they as strong as they look?

Since Krugman 1979, we know that the fixed exchange rate regimes have a propensity to fail because governments are unable to commit simple monetary rule in order to avoid divergence between base money supply and reserve variations. The currency boards (CB) propose a radical solution: an institutional rule linking base money and reserve. In this context, how to explain the failure of the Argentina CB? We test, in a co-integration model adapted for panel data, the efficiency of the CB rule to run the monetary policy. We conclude that in some situations, as Argentina bi-monetarism, the monetary policy could become inoperative.
Innovation Uptakes: Understanding Consumer Contexts from the Perspective of Consumption

This paper considers a mechanism in which consumers make decisions to take up innovations and suggests that consumer innovation uptakes should be looked at from the consumption point of view. There is a gap in our knowledge of the way consumer cultures of consumption and lifestyles explain their decisions to adopt innovations, as existing research mainly looks at the technical functionalities and the effects of demographic and personality factors. People make small, conscious decisions everyday, and the multiplicity of these decisions contributes to their routines that consist of a number of inter-connected cultural elements and make up lifestyles. Lifestyles are therefore the way people use their resources; they are patterns of action that differentiate people and are sets of practices which make sense in a particular context. Thus, cultures of consumption help explain what people do, why they do it and what doing it means to them. So, a close examination of underlying values, such as meanings of consumption, its contexts and everyday practices, offers us a deeper understanding of the dynamics of consumption activities, and indeed of innovation adoption behaviour. This way, we can identify differences in people’s values, attitudes towards an innovation and their innovation adoption behaviour, and provide a conceptualisation of innovation adoption and diffusion processes on the basis of differences in individual consumer values and behaviours.
Attainment of local drug delivery with paclitaxel-eluting balloon in porcine coronary arteries

ObjectiveOur purpose was to confirm the local drug delivery of a paclitaxel-eluting balloon by percutaneous intervention of single arterial segments or bifurcations of porcine coronary arteries. MethodsEight domestic pigs were subjected to 2×30 s Dior balloon dilatation of the mid left anterior descending, left circumflex and proximal right coronary arteries. Bifurcation intervention was performed in six arteries. The dilated, and the distal and proximal reference segments were prepared for tissue paclitaxel concentration measurement. Tissue samples were harvested at mean 1.5, 12, 24 and 48 h after balloon dilatation and plasma samples were taken at various time points. ResultsThe tissue paclitaxel concentration of the single dilated segment was at 1.5 h postdilatation 1.82±1.60 μmol/l, which decreased significantly to 0.73±0.27 (P=0.032), 0.62±0.34 and 0.44±0.31 μmol/l at 12, 24 and 48 h. The bifurcation intervention resulted in 5.10±1.80 μmol/l tissue paclitaxel amount in the main branch, which at 12 h had diminished to 1.41±1.23 μmol/l (P=0.004). The bifurcation side contained 7.00±4.80 μmol/l paclitaxel at 1.5 h postdilatation, which lowered to 2.72±0.40 μmol/l (P=0.034). The mean paclitaxel concentration of the reference segments decreased gradually from 0.84±0.99 to 0.34±0.36 μmol/l (P=0.09), 0.28±0.16 and 0.19±0.18 μmol/l tissue at 1.5, 12, 24 and 48 h postdilatation, respectively. No paclitaxel was found in the peripheral blood at any time point. ConclusionShort exposure of the coronary artery to paclitaxel with a coated balloon is sufficient for the attainment of an adequate tissue concentration of paclitaxel, which is known to be efficient in inhibiting neointimal growth.
Rebuilding the Tower of Babel: Towards Cross-System Malware Information Sharing

Anti-virus systems developed by different vendors often demonstrate strong discrepancies in how they name malware, which signficantly hinders malware information sharing. While existing work has proposed a plethora of malware naming standards, most anti-virus vendors were reluctant to change their own naming conventions. In this paper we explore a new, more pragmatic alternative. We propose to exploit the correlation between malware naming of different anti-virus systems to create their consensus classification, through which these systems can share malware information without modifying their naming conventions. Specifically we present Latin, a novel classification integration framework leveraging the correspondence between participating anti-virus systems as reflected in heterogeneous information sources at instance-instance, instance-name, and name-name levels. We provide results from extensive experimental studies using real malware datasets and concrete use cases to verify the efficacy of Latin in supporting cross-system malware information sharing.
Production of the Ramoplanin Activity Analogue by Double Gene Inactivation

Glycopeptides such as vancomycin and telavancin are essential for treating infections caused by Gram-positive bacteria. But the dwindling availability of new antibiotics and the emergence of resistant bacteria are making effective antibiotic treatment increasingly difficult. Ramoplanin, an inhibitor of bacterial cell wall biosynthesis, is a highly effective antibiotic against a wide range of Gram-positive bacteria, including methicillin-resistant Staphylococcus aureus, vancomycin-intermediate resistant Clostridium difficile and vancomycin-resistant Enterococcus sp. Here, two tailoring enzyme genes in the biosynthesis of ramoplanin were deleted by double in-frame gene knockouts to produce new ramoplanin derivatives. The deschlororamoplanin A2 aglycone was purified and its structure was identified with LC-MS/MS. Deschlororamoplanin A2 aglycone and ramoplanin aglycone showed similar activity to ramoplanin A2. The results showed that α-1,2-dimannosyl disaccharide at Hpg11 and chlorination at Chp17 in the ramoplanin structure are not essential for its antimicrobial activity. This work provides new precursor compounds for the semisynthetic modification of ramoplanin.
INHIBITION BY NEOMYCIN OF POLYPHOSPHOINOSITIDE TURNOVER IN SUBCELLULAR FRACTIONS OF GUINEA‐PIG CEREBRAL CORTEX IN VITRO

The addition of 10−5 M to 10−3 M neomycin to incubations of subcellular fractions of guinea‐pig cerebral cortex increased the labelling of phosphatidylinositol phosphate and decreased the labelling of phosphatidylinositol diphosphate by [γ‐32P]ATP. The effect was observed in all subcellular fractions tested and depended on the cationic form of the antibiotic. Similar effects on lipid labelling were exerted by related aminoglycosidic antibiotics, by neamine, spermine and poly‐L‐lysine. Other neomycin fragments, antibiotics, local anesthetics or small polyamines were ineffective. Neomycin also inhibited the enzymatic hydrolysis of 32P‐polyphosphoinositides. The addition of the drug to aqueous dispersions of these lipids increased the turbidity and lowered the pH of the suspensions. It is suggested that the effects of neomycin on polyphosphoinositide metabolism result from the formation of an ionic complex between the lipids and the antibiotic.