Miracle-dz/UniFAR-FTUs huggingface dataset:
Balancing Power Demand Through EV Mobility in Vehicle-to-Grid Mobile Energy Networks

Vehicle-to-grid (V2G) technology enables bidirectional energy flow between electric vehicles (EVs) and power grid, which provides flexible demand response management (DRM) for the reliability of smart grid. EV mobility is a unique and inherent feature of the V2G system. However, the inter-relationship between EV mobility and DRM is not obvious. In this paper, we focus on the exploration of EV mobility to impact DRM in V2G systems in smart grid. We first present a dynamic complex network model of V2G mobile energy networks, considering the fact that EVs travel across multiple districts, and hence EVs can be acting as energy transporters among different districts. We formulate the districts' DRM dynamics, which is coupled with each other through EV fleets. In addition, a complex network synchronization method is proposed to analyze the dynamic behavior in V2G mobile energy networks. Numerical results show that EVs mobility of symmetrical EV fleet is able to achieve synchronous stability of network and balance the power demand among different districts. This observation is also validated by simulation with real world data.
Small Changes in Environmental Parameters Lead to Alterations in Antibiotic Resistance, Cell Morphology and Membrane Fatty Acid Composition in Staphylococcus lugdunensis

Staphylococcus lugdunensis has emerged as a major cause of community-acquired and nosocomial infections. This bacterium can rapidly adapt to changing environmental conditions to survive and capitalize on opportunities to colonize and infect through wound surfaces. It was proposed that S. lugdunensis would have underlying alterations in metabolic homeostasis to provide the necessary levels of adaptive protection. The aims of this project were to examine the impacts of subtle variations in environmental conditions on growth characteristics, cell size and membrane fatty acid composition in S. lugdunensis. Liquid broth cultures of S. lugdunensis were grown under varying combinations of pH (6–8), temperature (35–39°C) and osmotic pressure (0–5% sodium chloride w/w) to reflect potential ranges of conditions encountered during transition from skin surfaces to invasion of wound sites. The cells were harvested at the mid-exponential phase of growth and assessed for antibiotic minimal inhibitory concentration (MIC), generation time, formation of small colony variants, cell size (by scanning electron microscopy) and membrane fatty acid composition. Stress regimes with elevated NaCl concentrations resulted in significantly higher antibiotic resistance (MIC) and three of the combinations with 5% NaCl had increased generation times (P<0.05). It was found that all ten experimental growth regimes, including the control and centroid cultures, yielded significantly different profiles of plasma membrane fatty acid composition (P<0.0001). Alterations in cell size (P<0.01) were also observed under the range of conditions with the most substantial reduction occurring when cells were grown at 39°C, pH 8 (514±52 nm, mean ± Standard Deviation) compared with cells grown under control conditions at 37°C with pH 7 (702±76 nm, P<0.01). It was concluded that S. lugdunensis responded to slight changes in environmental conditions by altering plasma membrane fatty acid composition, growth rates and morphology to achieve optimal adaptations for survival in changing environments.
Shifts in Abundance and Diversity of Soil Ammonia-Oxidizing Bacteria and Archaea Associated with Land Restoration in a Semi-Arid Ecosystem

The Grain to Green Project (GGP) is an unprecedented land restoration action in China. The project converted large areas (ca 10 million ha) of steep-sloped/degraded farmland and barren land into forest and grassland resulting in ecological benefits such as a reduction in severe soil erosion. It may also affect soil microorganisms involved in ammonia oxidization, which is a key step in the global nitrogen cycle. The methods for restoration that are typically adopted in semi-arid regions include abandoning farmland and growing drought tolerant grass (Lolium perenne L.) or shrubs (Caragana korshinskii Kom.). In the present study, the effects of these methods on the abundance and diversity of ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA) were evaluated via quantitative real-time PCR, terminal restriction fragment length polymorphism and clone library analysis of amoA genes. Comparisons were made between soil samples from three restored lands and the adjacent farmland in Inner Mongolia. Both the abundance and community composition of AOB were significantly different between the restored lands and the adjacent control. Significantly lower nitrification activity was observed for the restored land. Clone library analysis revealed that all AOB amoA gene sequences were affiliated with Nitrosospira. Abundance of the populations that were associated with Nitrosospira sp. Nv6 which had possibly adapted to high concentrations of inorganic nitrogen, decreased on the restored land. Only a slight difference in the AOB communities was observed between the restored land with and without the shrub (Caragana korshinskii Kom.). A minor effect of land restoration on AOA was observed. In summary, land restoration negatively affected the abundance of AOB and soil nitrification activities, suggesting the potential role of GGP in the leaching of nitrates, and in the emission of N2O in related terrestrial ecosystems.
Antibacterial Activity and Inhibition of Adherence of Streptococcus mutans by Propolis Electrospun Fibers

Mouth-dissolving fibers with antibacterial activity for the oral cavity were prepared by an electrospinning technique. Propolis extract was used as an active ingredient and polyvinylpyrrolidone (PVP) K90 as the polymer matrix. The morphology and diameter of the fibers were characterized by scanning electron microscopy. Antibacterial activity against Streptococcus mutans and the inhibition of S. mutans adhesion on a smooth glass surface during the biofilm formation were tested. Propolis, 5% (w/v), was combined with a PVP K90 solution, 8% (w/v), with or without Tween 80 including flavor additives and electrospun with an applied voltage of 15 kV. Uniform and smooth fibers of propolis-PVP K90 were obtained. The results showed that electrospun fibers with propolis extract can dissolve and release the propolis in water. Propolis-PVP electrospun fibers showed better antibacterial activity by reduction of bacteria adhesion on a smooth glass surface when compared to some commercial mouthwash products. These results indicated the potential of electrospun fibers to be used as mouth-dissolving fibers for effective antibacterial activity in the oral cavity.
Shifting Schemas: Perspectives and Practice in a Learner-Centered Course.

As a profession, we must have a shift in both perspective and practice to transform teaching at all levels. Are pre-service education classrooms preparing students to be flexible, adapt to new situations, and rely on their own expertise and understanding while seeking support when needed? Lieberman and Miller (2004) identify the following shifts for transforming the social realities of teaching: from individualism to professional community; from teaching at the center to learning at the center and from technical and managed work to inquiry and leadership (p. 11). The authors seek to critically examine the perspectives of pre-service teachers participating in a social studies methods course using constructivist practices.
Improved music feature learning with deep neural networks

Recent advances in neural network training provide a way to efficiently learn representations from raw data. Good representations are an important requirement for Music Information Retrieval (MIR) tasks to be performed successfully. However, a major problem with neural networks is that training time becomes prohibitive for very large datasets and the learning algorithm can get stuck in local minima for very deep and wide network architectures. In this paper we examine 3 ways to improve feature learning for audio data using neural networks: 1.using Rectified Linear Units (ReLUs) instead of standard sigmoid units; 2.using a powerful regularisation technique called Dropout; 3.using Hessian-Free (HF) optimisation to improve training of sigmoid nets. We show that these methods provide significant improvements in training time and the features learnt are better than state of the art handcrafted features, with a genre classification accuracy of 83 ± 1.1% on the Tzanetakis (GTZAN) dataset. We found that the rectifier networks learnt better features than the sigmoid networks. We also demonstrate the capacity of the features to capture relevant information from audio data by applying them to genre classification on the ISMIR 2004 dataset.
Maintaining benefits following pulmonary rehabilitation: a randomised controlled trial

The aim of this study was to determine if weekly, supervised, outpatient-based exercise plus unsupervised home exercise following an 8-week pulmonary rehabilitation programme would maintain functional exercise capacity and quality of life at 12 months better than standard care of unsupervised home exercise training. Chronic obstructive pulmonary disease (COPD) subjects completed an 8-week pulmonary rehabilitation programme, were randomised to an intervention group (IG) of weekly, supervised, exercise plus home exercise or to a control group (CG) of unsupervised home exercise and followed for 12 months. Outcome measurements at baseline (after pulmonary rehabilitation), and 3, 6 and 12 months included the 6-min walk test and St George's Respiratory Questionnaire (SGRQ). 59 subjects with moderate COPD (Global Initiative for Chronic Obstructive Lung Disease stage II) were recruited and 48 subjects completed the study. 12-month mean difference showed no significant change from baseline in 6-min walk distance (IG -11 m, 95% CI -21–10 m; CG -6 m, 95% CI -34–11 m) or total SGRQ score (IG 3, 95% CI -0.8–7; CG -3, 95% CI -7–3). 12 months following pulmonary rehabilitation both weekly, supervised, outpatient-based exercise plus unsupervised home exercise and standard care of unsupervised home exercise successfully maintained 6-min walk distance and quality of life in subjects with moderate COPD.
Rate-Compatible Punctured Polar Codes: Optimal Construction Based on Polar Spectra

Polar codes are the first class of constructive channel codes achieving the symmetric capacity of the binary-input discrete memoryless channels. But the corresponding code length is limited to the power of two. In this paper, we establish a systematic framework to design the rate-compatible punctured polar (RCPP) codes with arbitrary code length. A new theoretic tool, called polar spectra, is proposed to count the number of paths on the code tree with the same number of zeros or ones respectively. Furthermore, a spectrum distance SD0 (SD1) and a joint spectrum distance (JSD) are presented as performance criteria to optimize the puncturing tables. For the capacity-zero puncturing mode (punctured bits are unknown to the decoder), we propose a quasi-uniform puncturing algorithm, analyze the number of equivalent puncturings and prove that this scheme can maximize SD1 and JSD. Similarly, for the capacity-one mode (punctured bits are known to the decoder), we also devise a reversal quasi-uniform puncturing scheme and prove that it has the maximum SD0 and JSD. Both schemes have a universal puncturing table without any exhausted search. These optimal RCPP codes outperform the performance of turbo codes in LTE wireless communication systems.
A Particle Swarm Optimization Based Approach for Finding Similar Users on Facebook

: With ever increasing size and use of social networks, there is a large amount of information which users implicitly or explicitly leave behind on social media. This information can be used to identify their personal traits and preferences. In this work, we have proposed a Particle Swarm Optimization (PSO) based approach for clustering users on Facebook (FB) data to identify similar users. Proposed method can be used to recommend people having similar interests. Our results indicate a lesser quantization error than k-means when used for 7 or less clusters. Possible applications of this approach include rope-in exercises for new hires, assigning a resource person to work team, etc.
Insurance and Insurance Markets

Kenneth Arrow and Karl Borch published several important articles in the early 1960s that can be viewed as the beginning of modern economic analysis of insurance activity. This chapter reviews the main theoretical and empirical contributions in insurance economics since that time. The review begins with the role of utility, risk, and risk aversion in the insurance literature and then summarizes work on the demand for insurance, insurance and resource allocation, moral hazard, and adverse selection. It then turns to financial pricing models of insurance and to analyses of price volatility and underwriting cycles; insurance price regulation; insurance company capital adequacy and capital regulation; the development of insurance securitization and insurance-linked securities; and the efficiency, distribution, organizational form, and governance of insurance organizations.
Position transformation: a location privacy protection method for moving objects

The expanding use of location-based services has profound implications on the privacy of personal information. In this paper, we propose a framework for preserving location privacy based on the idea of sending to the service provider suitably modified location information. Agents execute data transformation and the service provider directly processes the transformed dataset. Our technique not only prevents the service provider from knowing the exact locations of users, but also protects information about user movements and locations from being disclosed to other users who are not authorized to access this information. We also define a privacy model to analyze our framework, and examine our approach experimentally.
Empirical Analysis: News Impact on Stock Prices Based on News Density

Analyzing the latent relationship between parallel news articles and stock prices has become an important research issue which attracts more and more researchers¡¯ attention. It is believed that news articles have impact on prices. Many approaches address this issue either from the documents¡¯sentiment point of view or from the word frequency point of view. In this paper, we propose a new model which captures the density of news articles and mines the latent relationship by employing information entropy to explore the news impact on the market. An empirical study is conducted to analyze market news articles¡¯ impact on stock prices. We compare our results with the traditional model which is based on support vector machine (baseline). Experimental results show that our proposed news density model has a better performance on predicting relatively long term news impact.
Bisimilarity in Term Graph Rewriting

textabstractWe present a survey of confluence properties of (acyclic) term graph rewriting. Results and counterexamples are given for different kinds of term graph rewriting: besides plain applications of rewrite rules, extensions with the operations of collapsing and copying, and with both operations together are considered. Collapsing and copying together constitute bisimilarity of term graphs. We establish sufficient conditions for-and counterexamples to-confluence, confluence modulo bisimilarity and the Church-Rosser property modulo bisimilarity. Moreover, we address rewriting modulo bisimilarity, that is, rewriting of bisimilarity classes of term graphs.
Cloud-based collaboration spaces for enterprise networks

The involvement of multiple collaborative enterprise networks in the various stages of the life cycle of complex service-enhanced products represents a clear trend. Effective operation of these networks requires collaboration platforms providing adequate collaboration spaces. In this context, an advanced cloud-based collaboration platform, which copes with dynamic hierarchies of collaboration spaces, is presented, highlighting the proposed novel features. The platform specially targets networks of small and medium enterprises involved in complex products such as solar plants and intelligent buildings. Validation use cases are also described.
Minimization of locally-de(cid:12)ned submodular functions by optimal soft arc consistency

Submodular function minimization is a polynomially-solvable combinatorial problem. Unfortunately the best known general-purpose algorithms have high-order polynomial time complexity. In many applications the objective function is locally-de(cid:12)ned in that it is the sum of cost functions (also known as soft or valued constraints) whose ari-ties are bounded by a constant. We prove that every Valued Constraint Satisfaction Problem with submodular cost functions has an equivalent instance on the same constraint scopes in which the actual minimum value of the objective function is rendered explicit. Such an equivalent instance is the result of establishing optimal soft arc consistency and can hence be found by solving a linear program. From a practical point of view, this provides us with an alternative algorithm for minimizing locally-de(cid:12)ned submodular functions. From a theoretical point of view, this brings to light a previously-unknown connection between submodularity and soft arc consistency.
Demand Shocks, Inflation and the Business Cycle

This paper examines how firms adjust output and prices in response to changes in demand and costs, paying particular attention to the role that capacity utilisation plays in affecting these relationships. It primarily uses qualitative survey data on manufacturing firms’ actual and expected outcomes for these variables, and traces through the short-term effects of changes in demand on costs, output and prices. The survey data also enables an analysis of how firms respond to unexpected shocks to costs and demand. The paper finds that strong demand growth leads to increases in both output and prices, and there is some evidence that capacity constraints do affect this relationship. When capacity utilisation is high, changes in demand have a smaller effect on output and a larger effect on prices, than when capacity utilisation is low. The paper distinguishes between the direct effect that changes in demand have on prices, through changes in margins, and the indirect effect, through demand-induced changes in firms’ costs. It finds that inflationary pressures are predominantly driven by increases in input costs. While margins appear to move pro-cyclically, there is a degree of asymmetry in their behaviour. Movements in margins appear to be largest in recessionary periods with margins falling as the economy goes into recession and then being rebuilt relatively early in the recovery. In boom times pressures on prices come largely through increases in costs, with little additional contribution from changes in margins.
Towards a Discourse Level Coherence Structure

In this paper we argue that coherence relations between discourse units are ultimately based on mentioned discourse entities embedded in the units participating in the relation. Coherence relations as discussed in most literature ((Mann and Thompson, 1988), (Hobbs, 1985), (Grosz and Sidner, 1986) inter alia) are defined between text segments, where a text segment could range from a single utterance to the whole discourse. We show that these coherence relations are formed either directly or indirectly between embedded discourse entities. Other semantic entities might be derived via inference/s based on the mentioned entities and the complexity of these inferences determines some of the types of relations defined in literature. Hence, the coherence relations as defined by (Mann and Thompson, 1988), (Hobbs, 1985) inter alia, existing between text units is essentially an abstraction of these fundamental relations formed between embedded entities. We argue that any representation of discourse coherence structure should entail representation of information down to the resolution level of these embedded entities in order for such structures to be useful for automated language processing tasks. We also show that the commonly accepted tree structure ((Hobbs, 1985),(Marcu, 1996) inter alia) is not sufficient to represent discourse relations to such a resolution level, and propose a semi constrained directed graph as the alternative.
Strengthening forest management in Indonesia through land tenure reform : issues and framework for action

Indonesia has been facing dramatic challenges to protect and manage its forest resources.The archipelago is well known not only for the extraordinary biodiversity and productivity of its forests, but also for its high rates of deforestation and illegal logging, its catastrophic fires, and the social tensions over forest rights between the government and indigenous and other local communities. The purpose of this analysis is to help policy makers and the many stakeholders in Indonesia develop a vision and a plan to advance tenure reforms and strengthen forest management systems. It focuses primarily on the fundamental question of the legal and biophysical rationale upon which the concept of the State Forest Zone is based. This analysis addresses the question of land ownership and sustainable forest resource management. It challenges the widely accepted view that the government, through the Department of Forestry, has jurisdiction over land administration within the Forest Zone. This approach would contribute to energize a policy that recognizes that the Krui lands have not been classified as “State Forest Zone” but some areas do fall within the more general classification of “Forest Zone” where the Department of Forestry has a say in the management of those forests but has no control over the land and cannot award forestry contracts to third parties. Strengthening forest tenure is a clearly needed, albeit complicated and contentious, step towards advancing forest stewardship and human rights in Indonesia. Devising and implementing a national forest tenure reform initiative will require bold leadership from national institutions, including the Ministry of Forestry, the Bureau of Lands and the Parliament, as well as strong support of indigenous and other com experience in similar initiatives or research inputs for a more objective national policy debate. While international assistance could be useful, in the end, progress will depend upon Indonesian leadership and political will.
Video Gesture Classification using Fourier Descriptors and General Fuzzy Min Max Neural Network

— Sign languages are natural languages that use different means of expression for communication in day to day life. There are various sign languages across the world. In India, it’s Indian Sign Language (ISN) which is on the way of standardization & very less work has been done on it. As the sign language is the only communication means for hearing impaired people; we need Sign Language Translator (SLT). The approach proposed in this paper will work on ISL to convert the video of full sentence gesture to text. It will initially identify individual words from the video & covert them to text. Finally, the system will process those words to form a meaningful sentence.