nils-herrmann/clean_scirepeval huggingface dataset:
Improved community detection in weighted bipartite networks
Venue: Royal Society Open Science

Real world complex networks are composed of non random quantitative interactions. Identifying communities of nodes that tend to interact more with each other than the network as a whole is a key research focus across multiple disciplines, yet many community detection algorithms only use information about the presence or absence of interactions between nodes. Weighted modularity is a potential method for evaluating the quality of community partitions in quantitative networks. In this framework, the optimal community partition of a network can be found by searching for the partition that maximizes modularity. Attempting to find the partition that maximizes modularity is a computationally hard problem requiring the use of algorithms. QuanBiMo is an algorithm that has been proposed to maximize weighted modularity in bipartite networks. This paper introduces two new algorithms, LPAwb+ and DIRTLPAwb+ for maximizing weighted modularity in bipartite networks. LPAwb+ and DIRTLPAwb+ robustly identify partitions with high modularity scores. DIRTLPAwb+ consistently matched or outperformed QuanBiMo, while the speed of LPAwb+ makes it an attractive choice for detecting the modularity of larger networks. Searching for modules using weighted data (rather than binary data) provides a different and potentially insightful method for evaluating network partitions.
Quantitative function and algorithm for community detection in bipartite networks
Venue: Inf. Sci.

Community detection in complex networks is a topic of high interest in many fields. Bipartite networks are a special type of complex networks in which nodes are decomposed into two disjoint sets, and only nodes between the two sets can be connected. Bipartite networks represent diverse interaction patterns in many real world systems, such as predator prey networks, plant pollinator networks, and drug target networks. While community detection in unipartite networks has been extensively studied in the past decade, identification of modules or communities in bipartite networks is still in its early stage. Several quantitative functions proposed for evaluating the quality of bipartite network divisions are based on null models and have distinct resolution limits. In this paper, we propose a new quantitative function for community detection in bipartite networks, and demonstrate that this quantitative function is superior to the widely used Barber's bipartite modularity and other functions. Based on the new quantitative function, the bipartite network community detection problem is formulated into an integer programming model. Bipartite networks can be partitioned into reasonable overlapping communities by maximizing the quantitative function. We further develop a heuristic and adapted label propagation algorithm (BiLPA) to optimize the quantitative function in large scale bipartite networks. BiLPA does not require any prior knowledge about the number of communities in the networks. We apply BiLPA to both artificial networks and real world networks and demonstrate that this method can successfully identify the community structures of bipartite networks.
Community Detection in Bipartite Networks Using a Noisy Extremal Optimization Algorithm
Venue: ISDA

The network community structure detection problem consists in finding groups of nodes that are more connected to each other than to the rest of the network. While many methods have been designed to deal with this problem for general networks, there are few methods that deal with bipartite ones. In this paper we explore the behavior of an optimization method designed for identifying the community structure of unweighted networks when dealing with bipartite networks. We find that by using the specific Barber modularity, results are comparable with those reported in literature.
Carbon emissions and industrial growth: an ARDL analysis for Pakistan

This paper is a direct extension of the work by Hussain et al. (2012) They have investigated a long term relationship between climatic change and economic growth in case of Pakistan. Agricultural sector plays an important role in economic field, whereas industrial sector is the main source of carbon dioxide (CO2) emission. Therefore, this study aims to replace economic growth variable with industrial growth in case of Pakistan.  Investigation is made on the basis of the environmental Kuznets curve by using the time series data during the period 1971 2009. The per capital carbon dioxide (CO2) emission is used as an environmental indicator and per capita industrial income as the economic indicator. Different econometric tools including augmented Dickey Fuller, autoregressive distributed lag and Granger causality test are used to verify this relationship.  The empirical findings will help the policy makers of Pakistan in developing new standards and monitoring networks for reducing CO2 emission. It is essential to extend the current research work at provincial and different sectors levels in order to have clear understanding about the impact of current emission rate.  This study replaces economic growth variable with industrial growth in case of Pakistan because the industrial sector is the main source of carbon dioxide (CO2) emission. This study is to investigate a long term relationship between climatic change and industrial growth in case of Pakistan.
Effect of Green Tea Extract as Antioxidant on Shear Bond Strength of Resin Composite to in Office and Home Bleached Enamel
Venue: Journal of dental biomaterials

Shear bond strength (SBS) of home and office bleached enamel will be compromised by immediate application of composite restoration. Antioxidant agent may overcome this problem.  This in vitro study assessed the effect of green tea extract on shear bond strength of resin composite to in office and home bleached enamel.  In this experimental study, 40 extracted intact human incisors were embedded in cylindrical acrylic resin blocks (2.5 x1.5 cm) with the coronal portion above the cemento enamel junction out of the block. Then, after bleaching labial enamel surfaces of 20 teeth with 15% carbamide peroxide 6 hours a day for 5 days, they were randomly divided into two groups: A1 and A2 (n 10) depending upon whether or not they are treated with antioxidant. Labial enamel surfaces of the remaining 20 teeth were bleached with 38% hydrogen peroxide before being randomly divided into groups B1 and B2 (n 10) again depending on whether or not the antioxidant was used in their treatment The experimental groups (A2,B2) were treated with 5% solution of green tea extract before resin composite restoration was done by a cylindrical Teflon mould (5x2 mm) Shear bond strength of the specimens was tested under a universal testing machine (Zwick/Roell Z020) The SBS data were analyzed by using One way ANOVA and Tukey HSD tests (p 0.05)  There were no statistically significant differences between shear bond strength of the control group (A1) and treated group (A2) but there were statistically significant differences between the groups B1 and B2 (p 0.05)  Application of antioxidant did not increase the shear bond strength of home bleached enamel to resin composite but its application increased the shear bond strength of in office bleached enamel to resin composite.
Effect of Green Tea Extract as Antioxidant on Shear Bond Strength of Resin Composite to in Office and Home Bleached Enamel.

Shear bond strength (SBS) of home and office bleached enamel will be compromised by immediate application of composite restoration. Antioxidant agent may overcome this problem.  This in vitro study assessed the effect of green tea extract on shear bond strength of resin composite to in office and home bleached enamel.  In this experimental study, 40 extracted intact human incisors were embedded in cylindrical acrylic resin blocks (2.5 x1.5 cm) with the coronal portion above the cemento enamel junction out of the block. Then, after bleaching labial enamel surfaces of 20 teeth with 15% carbamide peroxide 6 hours a day for 5 days, they were randomly divided into two groups: A1 and A2 (n 10) depending upon whether or not they are treated with antioxidant. Labial enamel surfaces of the remaining 20 teeth were bleached with 38% hydrogen peroxide before being randomly divided into groups B1 and B2 (n 10) again depending on whether or not the antioxidant was used in their treatment The experimental groups (A2,B2) were treated with 5% solution of green tea extract before resin composite restoration was done by a cylindrical Teflon mould (5x2 mm) Shear bond strength of the specimens was tested under a universal testing machine (Zwick/Roell Z020) The SBS data were analyzed by using One way ANOVA and Tukey HSD tests p 0.05)  There were no statistically significant differences between shear bond strength of the control group (A1) and treated group (A2) but there were statistically significant differences between the groups B1 and B2 p 0.05)  Application of antioxidant did not increase the shear bond strength of home bleached enamel to resin composite but its application increased the shear bond strength of in office bleached enamel to resin composite.  Antioxidant, Green Tea, Shear Bond Strength, Tooth Bleaching, Composite Restoration
Robust and false positive free watermarking in IWT domain using SVD and ABC
Venue: Eng. Appl. Artif. Intell.

Watermarking is used to protect the copyrighted materials from being misused and help us to know the lawful ownership. The security of any watermarking scheme is always a prime concern for the developer. In this work, the robustness and security issue of IWT (integer wavelet transform) and SVD (singular value decomposition) based watermarking is explored. Generally, SVD based watermarking techniques suffer with an issue of false positive problem. This leads to even authenticating the wrong owner. We are proposing a novel solution to this false positive problem; that arises in SVD based approach. Firstly, IWT is employed on the host image and then SVD is performed on this transformed host. The properties of IWT and SVD help in achieving high value of robustness. Singular values are used for the watermark embedding. In order to further improve the quality of watermarking, the optimization of scaling factor (mixing ratio) is performed with the help of artificial bee colony (ABC) algorithm. A comparison with other schemes is performed to show the superiority of proposed scheme.
IBVS and EMG based reach to grasp task planning method for a trans humeral prosthesis
Venue: 2016 IEEE/SICE International Symposium on System Integration (SII)

Prosthesis is a device that replaces a missing body part. These devices are used to reinstate the lost functionality due to an amputation. Above elbow amputees are equipped with trans humeral prostheses. The existing prostheses use biological signals such as electromyography (EMG) in combine with external sensors for the controlling purposes. Vision is the latest addition to external sensor domain to eliminate the drawbacks of existing hybrid prostheses. This paper proposes a vision based task planning method in combination with available EMG signals to plan reach to grasp tasks of a trans humeral prosthesis. The visual servoing system consists of an Image Based Visual Servoing (IBVS) system in conjunction with an Artificial Neural Network (ANN) to center the object in the image frame. Moreover, a gradient descent algorithm is proposed for the elbow motion to reach the palm towards the object of interest. EMG based system is capable of controlling the prosthetic elbow motion with available muscles' signals. EMG based system is fused with the IBVS system to perform elbow motions when an object is visible to the camera. Experiments are carried out using a virtual prosthesis to validate the proposed task planning method.
Connecting best practices in public relations to social media strategies for academic libraries

Academic libraries worldwide use social media to inform and connect with users. Virginia Commonwealth University (VCU) Libraries is no different and must keep up with rapidly evolving platforms and user expectations. When our presence stretched across twenty two channels, we needed to ensure that social media efforts were managed in the most effective and efficient manner possible. To develop a research based, unified vision for communication for new media, we scanned the literature in the library and public relations fields and then surveyed librarians to address identified gaps. Based on results, we offer recommendations focused on best management practices and strong content strategies.
Representation learning for very short texts using weighted word embedding aggregation
Venue: Pattern Recognit. Lett.

We create text representations by weighing word embeddings using idf information.A novel median based loss is designed to mitigate the negative effect of outliers.A dataset of semantically related textual pairs from Wikipedia and Twitter is made.Our method outperforms all word embedding baselines in a semantic similarity task.Our method is out of the box and thus requires no retraining in different contexts. Short text messages such as tweets are very noisy and sparse in their use of vocabulary. Traditional textual representations, such as tf idf, have difficulty grasping the semantic meaning of such texts, which is important in applications such as event detection, opinion mining, news recommendation, etc. We constructed a method based on semantic word embeddings and frequency information to arrive at low dimensional representations for short texts designed to capture semantic similarity. For this purpose we designed a weight based model and a learning procedure based on a novel median based loss function. This paper discusses the details of our model and the optimization methods, together with the experimental results on both Wikipedia and Twitter data. We find that our method outperforms the baseline approaches in the experiments, and that it generalizes well on different word embeddings without retraining. Our method is therefore capable of retaining most of the semantic information in the text, and is applicable out of the box.
Assessment of energetic potential of cherry stones in Poland

Biomass is one of the renewable energy sources that could replace conventional carbonaceous fuels. The remains of timber industry or the agro food sector are attractive sources of biomass taking into account environmental and economic aspects. Stones of fruits such as cherries, peaches or apricots can be converted into heat in the combustion processes. They can also be converted into liquid or gas biofuels in a gasification and pyrolysis processes. The aim of the study was to determine the higher (HHV) and lower heating value (LHV) of cherry stones and to determine their energy potential in Polish market of renewable energy. Relative humidity of dried cherry stones was 5.80+ 0.12% and ash content was equal to 1.43+ 0.04% The higher heating value of crushed cherry stones was 20.6+ 0.7 MJ*kg 1, while the lower heating value 19.2+ 0.8 MJ*kg 1. The theoretical share of thermal energy from combustion cherry stones in the national heat production from renewable energy sources amounted to 0.42% in 2013.
Area and Speed Efficient Implementation of Symmetric FIR Digital Filter through Reduced Parallel LUT Decomposed DA Approach

This brief proposes an area and speed efficient implementation of symmetric finite impulse response (FIR) digital filter using reduced parallel look up table (LUT) distributed arithmetic (DA) based approach. The complexity lying in the realization of FIR filter is dominated by the multiplier structure. This complexity grows further with filter order, which results in increased area, power, and reduced speed of operation. The speed of operation is improved over multiply accumulate approach using multiplier less conventional DA based design and decomposed DA based design. Both the structure requires B clock cycles to get the filter output for the input width of B, which limits the speed of DA structure. This limitation is addressed using parallel LUTs, called high speed DA FIR, at the expense of additional hardware cost. With large number of taps, the number of LUTs and its size also becomes large. In the proposed method, by exploiting coefficient symmetry property, the number of LUTs in the decomposed DA form is reduced by a factor of about 2. This proposed approach is applied in high speed DA based FIR design, to obtain area and speed efficient structure. The proposed design offers around 40% less area and 53.98% less slice delay product (SDP) than the high throughput DA based structure when it's implemented over Xilinx Virtex 5 FPGA device XC5VSX95T 1FF1136 for 16 tap symmetric FIR filter. The proposed design on the same FPGA device, supports up to 607 MHz input sampling frequency, and offers 60.5% more speed and 67.71% less SDP than the systolic DA based design.
Adsorption and diffusion of Li with S on pristine and defected graphene.
Venue: Physical chemistry chemical physics PCCP

Li S batteries are the promising high energy density alternative to current rechargeable battery technologies, particularly since it has been shown that the use of graphene, nanotubes and other nanostructured carbons in the cathode can improve the cyclability. We explore the microscopic interactions between LinS and graphene and diffusion of Li ions through pristine and defected graphene in the presence of S using first principles methods. The introduction of Li weakens the interaction of atomic S with graphene, increasing the height of adsorbed S and leading to the formation of LinS clusters. These LinS clusters are adsorbed accompanied by charge transfer to the graphene. We find that double vacancies in the graphene are sufficient to allow Li ions to pass through the graphene plane. This is impeded in the presence of S due to the binding of Li to LinS clusters, but still can happen for larger clusters. The electronic properties confirm the excellent conductivity of pristine and defected graphene cathodes in contact with LinS clusters.
The Tribological Properties of Aluminium Alloy/ SiC Metal Matrix Composites

The present research involved the selection of aluminium AA2618 alloy matrix composite reinforced with Silicon Carbide particulates for the conduction of dry sliding wear tests in order to determine their tribological properties. The composites were machined to ASTM standards. The dry sliding wear tests were conducted on a pin on disc test rig. The addition of reinforcement particulates into the matrix material increases the wear resistance and reduces the coefficient of friction of the composite material.
Evaluating habitat connectivity methodologies: a case study with endangered African wild dogs in South Africa
Venue: Landscape Ecology

ContextIn fragmented landscapes, connectivity between subpopulations is vital for species' persistence. Various techniques are used to assess the degree of connectivity between habitat patches, yet their performance is seldom evaluated. Models are regularly based on habitat selection by individuals in resident populations, yet dispersers may not require habitat which supports permanent residence.Objectives and methodsUsing a database of African wild dog (Lycaon pictus) occurrence records in north eastern South Africa (n 576) we developed and compared ecological niche models (ENM) for wild dogs packs and dispersers. Additionally, we used least cost path (LCP) and current flow models to assess connectivity. Results were further validated using occurrence records (n 339) for cheetah (Acinonyx jubatus).Results and conclusionsThe ENM for wild dog packs identified large but isolated patches of suitable habitat, while the disperser ENM had greater suitability values for areas in between highly suitable patches. Without disperser specific data, models omitted large areas which were confirmed to have provided connectivity. Although models derived from a potentially subjective cost layer have been criticised, the current flow model outperformed the other connectivity techniques and provided the most meaningful predictions for conservation planning. We identified five priority conservation areas for wild dogs, two of which had a greater feasibility for recolonisation. The scarcity of disperser specific data promotes models using habitat data for resident individuals but here we illustrate the pitfalls thereof. Our study provides insights into the performance of these frequently employed techniques and how they may affect conservation management decisions.
Genetic diversity and spatial genetic structure of African wild dogs (Lycaon pictus) in the Greater Limpopo transfrontier conservation area
Venue: Conservation Genetics

The Greater Limpopo Transfrontier Conservation Area (GLTFCA) is one of the last refuges for the endangered African wild dog and hosts roughly one tenth of the global population. Wild dogs in this area are currently threatened by human encroachment, habitat fragmentation and scarcity of suitable connecting habitat between protected areas. We derived genetic data from mitochondrial and nuclear markers to test the following hypotheses: (i) demographic declines in wild dogs have caused a loss of genetic variation, and (ii) Zimbabwean and South African populations in the GLTFCA have diverged due to the effects of isolation and genetic drift. Genetic patterns among five populations, taken with comparisons to known information, illustrate that allelic richness and heterozygosity have been lost over time, presumably due to effects of inbreeding and genetic drift. Genetic structuring has occurred due to low dispersal rates, which was most apparent between Kruger National Park and the Zimbabwean Lowveld. Immediate strategies to improve gene flow should focus on increasing the quality of habitat corridors between reserves in the GLTFCA and securing higher wild dog survival rates in unprotected areas, with human mediated translocation only undertaken as a last resort.
The Rise of the Creative Class: Revisited

The Rise of the Creative Class: Revisited, first published in 2002, is now in its second edition. The very first aspect of the book that attracts the attention of the reader is the title itself, which alludes to the role of creativity in the economy and society. Indeed, when the book was first published, it became a bestseller and took the world of urban studies, particularly in advanced countries, by storm. Although technically a novel construct, Richard Florida's concept of creativity and creative capital was criticized by several scholars, including the Harvardurban economist, Edward Glaeser, as being not very different from the already established concept of human capital (Glaeser 2004) Human capital is based on the level of skills possessed by an individual, as a result of formal education. Creativity, like human capital, gives rise to new ideas that can spur technological and economic innovation which, in turn, can lead to economic growth. In the second edition of the book, Florida addresses these criticisms and redefines the 'creativeclass' as a socioeconomic group whose distinguishing characteristic is the ability of its members to engage in such work whose function is to 'create meaningful new forms' This ability, Florida claims, by citing the examples of entrepreneurial giants like Steve Jobs and Bill Gates, is regardless of the educational qualifications of its members and hence is fundamentally different from human capital.