Miracle-dz/UniFAR-FTUs huggingface dataset:
Indirect carbon dioxide emissions from producing bioenergy from forest harvest residues

Forest harvest residues are important raw materials for bioenergy in regions practicing forestry. Removing these residues from a harvest site reduces the carbon stock of the forest compared with conventional stem-only harvest because less litter in left on the site. The indirect carbon dioxide (CO2) emission from producing bioenergy occur when carbon in the logging residues is emitted into the atmosphere at once through combustion, instead of being released little by little as a result of decomposition at the harvest sites. In this study (1) we introduce an approach to calculate this indirect emission from using logging residues for bioenergy production, and (2) estimate this emission at a typical target of harvest residue removal, i.e. boreal Norway spruce forest in Finland. The removal of stumps caused a larger indirect emission per unit of energy produced than the removal of branches because of a lower decomposition rate of the stumps. The indirect emission per unit of energy produced decreased with time since starting to collect the harvest residues as a result of decomposition at older harvest sites. During the 100 years of conducting this practice, the indirect emission from average-sized branches (diameter 2 cm) decreased from 340 to 70 kg CO2 eq. MWh 1 and that from stumps (diameter 26 cm) from 340 to 160 kg CO2 eq. MWh . These emissions are an order of magnitude larger than the other emissions (collecting, transporting, etc.) from the bioenergy production chain. When the bioenergy production was started, the total emissions were comparable to fossil fuels. The practice had to be carried out for 22 (stumps) or four (branches) years until the total emissions dropped below the emissions of natural gas. Our results emphasize the importance of accounting for land-use-related indirect emissions to correctly estimate the efficiency of bioenergy in reducing CO2 emission into the atmosphere.
Systematic Evaluation of Image Analysis for Cell-Matrix Adhesion Studies in Cytomics

The cytomic study of cell-matrix adhesions on”in-vitro” cell systems requires automation in order to accomplish analysis on the right scale; that is large scale throughput of image data. These image data need to be properly preprocessed, segmented and subsequently the relevant features need be extracted from the cell-matrix adhesions. The image data represent experiments in which the cells are exposed to various conditions and cellmatrix adhesion kinases are knocked down by different siRNA duplexes; the goal of the measurements and feature extraction is to identify the role of different kinases and different types of cell-matrix adhesions under various experimental conditions and treatments. The aim of this thesis project is to 1: establish a robust image analysis protocol that can be used for automation 2: estimate influence of different image processing methods and different imaging requiring conditions (microscope settings) on the measurements. 3: identify important kinases which have high information in regulation of cell-matrix adhesion ----also called hits extraction. 4: Given a number of classifier, a good one is applied to learn different types of cell-matrix adhesion’s behavior separately, given the features and experimental setup Various image processing methods give rise to some questions that need to be solved. Which noise suppression and which segmentation should be used to get stable measurement of the object of interests? At the same time the segmentations should be subject to a critical evaluation in which we try to estimate how segmentation results are influenced by image conditions. Once an idea on robustness has been developed the features are measured. Before using these features, evaluation of features is done to check whether features are truthfully measured. New context-sensitive and valid features must be added to the family of features that is now common in this field. Several classifiers are tested and one is selected in the classification of cell-matrix adhesions. In the end, a robust image analysis is employed in the workflow of the Cytomic screens as these are applied in the Division of Toxicology department of Leiden Amsterdam Center for drug research (LACDR), Leiden University.
Entropy and Phase Coexistence in Clusters: Metals vs. Nonmetals

Small clusters violate the Gibbs phase rule by exhibiting two or more phases in thermodynamic equilibrium over bands of temperature and pressure. The reason is the small number of particles comprising each system. We review recent results concerning the size ranges for which this behavior is observable. The principal characteristic determining the coexistence range is the transitions entropy change. We review how this happens, using simulations of 13-atom Lennard-Jones and metal clusters to compare dielectric clusters with the more complex clusters of metal atoms. The dominating difference between the narrower coexistence bands of dielectrics and the wider bands of metal clusters is the much higher configurational entropy of the liquid metal clusters.
Social Networks and Reading Behavior in the Blogosphere ID : 149

This paper describes a comprehensive study on social networks of weblogs integrated with analysis of users’ reading behavior. The analyzed data are obtained from a Japanese weblog hosting service, Doblog. Four kinds of social networks are generated and analyzed: citation, comment, trackback, and blogroll networks. In addition, the user log data are used to identify readership relations among bloggers. After analysis of more than 50,000 users for about two years, we reveal some interactions between social relations and readership relations. We first show that bloggers read other weblogs on a regular basis (50% of weblogs that are read at least three times are read every five times a user logs in). We call this relation aregular reading relation (RR relation). Then, prediction of RR relations is done using features from the four kinds of social networks. Lastly, information diffusion on RR relations is analyzed and characterized. Our findings provide an overview of social relations and reading behavior. The results support those of existing studies of social network analysis on the blogosphere.
Governance Norms in Relational Exchange : What We Do Know and What We Do Not Know

Over the past 15 years, relational exchange theory (RET) has increasingly received attention in the marketing literature. Marketing scholars have particularly contributed to the empirical verification of the norm concept which occupies a central role in RET. However, a vast set of potential norms is discussed in the literature. The author provides a review of more than 30 articles drawing upon RET. Based upon this review he identifies a set of ten governance norms which may be considered as being of particular relevance to relational governance.
A New Homogenized Feature Based Multi-spectral Image Registration Method

In this paper, a study aiming to achieve both speed and accuracy of feature based multi-spectral image registration process was carried out. Then a new homogenized feature based image registration method was proposed. The method first use DOH operator to detect features, then a circular filter window is used to adaptively select features based on the spatial distribution and intensity while keeping the features' rotation invariance. The selected features are further described and matched. Experiments show that the selected features are more robust and more uniformly distributed and the method has great advantages in both speed and accuracy.
Inference Processes on Clustered Partial Decision Rules

The aim of the paper is to study efficeient of inference process using clustered partial decision rules. Partial decision rules are constructed by greedy algorithm. They are clustered with Agglomerative Hierarchical Clustering (AHC) algorithm. We study how exact and partial decision rules clustered by AHC algorithm influence on inference process in knowledge base. Clusters of rules are a way of modularization of knowledge bases in Decision Support Systems. Results of experiemnts present how different facors (e.g. rule length, number of facts given as an input knowledge) can influence on the efficiency of inference process.
An Integrated Approach to Multilingual Hypertext Generation 1

Text planning combines the tasks of content determination and discourse planning in order to construct atext plan from a suitably represented generation goal. The sentence planning step involves such tasks as sentence aggregation, referring expression generation, and sometimes lexicalization, and aims at converting text plans into sentence plans. Linguistic realization, finally, converts the sentence plans into surface text through syntactic, morphological and orthographic1 processing. In this paper, we will describe an approach to natural language generation that collapses these three steps into a single process of text realization, converting a generation goal into a surface text without any intermediate representations. In order to achieve this, we adopt a generalized grammar formalism, where phrase structure and text structure can be described by the same kind of rules, and use pragmatic principles inspired by the Gricean maxims of quality and quantity to guide the application of these rules. We call the approach integrated, first because it integrates text planning, sentence planning and linguistic realization into a single process, but also because it permits the integration of different realization techniques, such as canned text, templates and grammar rules, in a flexible and efficient manner. It goes without saying that the integrated approach cannot hope to achieve the same level of sophistication as systems adopting specialized techniques for the different tasks involved in text planning, sentence planning, and linguistic realization. Nevertheless, we believe that it provides a useful alternative for applications which do not require the full power of state of the art methods. It is easy to implement, relatively efficient and robust, and provides more flexibility than simpler approaches relying only on canned text or template filling. The approach has been developed and tested in the context of the TREE project, 2 which deals with multi-lingual generation of employment advertisements on the World Wide Web. Since the TREE application will be used throughout the paper to illustrate our ideas, we will set the stage in section 2 by giving a brief introduction to the architecture of the TREE system. In section 3 we will introduce the generalized grammar formalism and in section 4 we will explain the pragmatic principles guiding the text realization process.
Fully distributed clock skew and offset estimation in wireless sensor networks

In this paper, we propose a fully distributed algorithm for joint clock skew and offset estimation in wireless sensor networks. With the proposed algorithm, each node can estimate its clock skew and offset by communicating only with its neighbors. Such algorithm does not require any centralized information processing or coordination. Simulation results show that estimation mean-square-error at each node converge to the centralized Cramér-Rao bound with only a few number of message exchanges.
Open Food Network: the Role of ICT to Support Regional Food Supply Chains in Australia

Many organizations have introduced various ICT-enabled innovations to improve economic, environmental and social performance. The Open Food Network (OFN) is an example of ICT-enabled innovation that has the potential to enhance the sustainability of regional food supply chain by improving farmers access to local and regional markets and consumers access to fresh local produce, as well as optimizing the regional food distribution and improving local community welfare. OFN has just been recently launched in Australia and currently there is a limited understanding of the actual impacts and appropriate strategies to encourage wider adoption. This research in progress aims to evaluate the effectiveness of the OFN system in connecting and supporting the sustainability of regional food supply chain communities in Australia that will help devise strategies for expanding the use beyond Australia. Through a preliminary focus group with a number of early adopters of the OFN, this study identifies the actual use of OFN, benefits to main stakeholders and a number of challenges. The findings contribute to a longer term research program that investigates how ICT can support sustainability initiatives within organizations and supply chains.
Within- and between-channel gap detection in the human auditory cortex

We examined the neural correlates associated with a short gap between two identical pure tones (within-channel) and between two different tones (between-channel) in an odd-ball paradigm. Gap durations were selected such that a gap between identical tones was as discriminable as a gap between two different tones. Spatio-temporal dipole source modeling of electrophysiological data revealed a significant difference between standard and deviant gap stimuli, with mismatch negativity responses that were comparable in amplitude and latency for within- and between-channel conditions. Therefore, the ability to automatically register discontinuity (i.e., gap) within and between channels is comparable despite significant differences in gap size. The dipole source modeling suggests that both within- and between-gap signals are represented in or near the primary auditory cortex.
Implied Risk Exposures

We show how to reverse-engineer banks' risk disclosures, such as Value-at-Risk, to obtain an implied measure of their exposures to equity, interest rate, foreign exchange, and commodity risks. Factor Implied Risk Exposures (FIRE) are obtained by breaking down a change in risk disclosure into a market volatility component and a bank-specific risk exposure component. In a study of large US and international banks, we show that (1) changes in risk exposures are negatively correlated with market volatility and (2) changes in risk exposures are positively correlated across banks, which is consistent with banks exhibiting commonality in trading.
Post-Translational Modifications in Secreted Peptide Hormones in Plants

More than a dozen secreted peptides are now recognized as important hormones that coordinate and specify cellular functions in plants. Recent evidence has shown that secreted peptide hormones often undergo post-translational modification and proteolytic processing, which are critical for their function. Such ‘small post-translationally modified peptide hormones’ constitute one of the largest groups of peptide hormones in plants. This short review highlights recent progress in research on post-translationally modified peptide hormones, with particular emphasis on their structural characteristics and modification mechanisms.
HeartID: Cardiac biometric recognition

This letter examines the applicability of cardiac signals for biometric recognition. Two physiological signals are considered, namely the Electrocardiogram (ECG) and the Phono-cardiogram (PCG) as it has been shown they bare adequate discriminative information in a population [1–12]. Due to the idiosyncratic properties of ECG and PCG, individual algorithms are developed for feature extraction. Time dependency, a major challenge of cardiac biometrics, is taken to consideration in the design of robust gallery templates. To that end, a wavelet based analysis is introduced to handle noise artifacts and heart rate variability. A bi-modal configuration is presented, to perform decision level fusion of the information. The recognition performance, tested over 21 subjects, is very promising.
Distinguishing between the Board and Management in Company Mission Implications for Corporate Governance

A relationship between board/management “involvement” and “awareness” with organizational mission and their link to “employee commitment” and “organizational performance” was modeled by drawing on previous research. The model was tested with data from 339 large Canadian and US organizations. It was determined that “mission awareness” on the part of both the board and senior management is an important consideration in the determination of employees' commitment to the mission. However, the impact of board and management involvement with the mission is not identical. The results emphasize the strong and important role that the board performs when it is actively engaged in the development of the organization's mission.
A Peer to Peer Prefix Patching Scheme for VOD Servers

In this paper, we propose a new patching scheme, called P2Prefix patching, to improve the performance of the typical patching technique by using both the prefix patching from clients and the regular stream multicast from the server. In our proposed scheme, each client plays the role of a patching server to serve a prefix stream to other clients that request the same video stream. As a result of removing the patching channels from the server, the server bandwidth usage can be reduced. In the performance study, we show that our patching scheme requires less server bandwidth than the existing patching techniques
Interrelationship between Capital Structure and Profitability with Special Reference to Manufacturing Industry in India

The determination of a company’s capital structure constitutes a difficult decision, one that involves several and antagonistic factors, such as risk and profitability. That decision becomes even more difficult, in times when the economic environment in which the company operates presents a high degree of instability. Therefore, the choice among the ideal proportion of debt and equity can affect the value of the company, as much as the return rates can. This study analyses how far the capital structure (cs) affects the Profitability (p) of corporate firms in India. The study tries to establish the hypothesized relationship as to how far the cs affect the business revenue of firms and what the interrelationship is between cs and Profitability. This study is carried out after categorizing the selected firms into three categories based on two attributes, viz. business revenue and asset size. First, firms are grouped into low, medium and high based on business revenue. Second, firms are classified into small, medium and large based on asset size to establish the hypothesized relationship that cs has significant impact on Profitability of Manufacturing firms in India. Regression Analysis in addition to descriptive statistics such as Mean, Standard Deviation, and Ratios has been used. The study proves that there has been a strong one-to-one relationship between Capital Structure variables and Profitability variables, Return on Assets (ROA) and Return on Capital Employed (ROCE) and the Capital Structure has significant influence on Profitability, and increase in use of debt fund in Capital Structure tends to minimize the net profit of the Manufacturing firms listed in Bombay Stock Exchange in India.
Performance of Reed-Solomon block turbo code

Thanks to recent progress in the iterative decoding of concatenated codes, several new fields of investigation have appeared. In this paper, we present a first approach of the iterative decoding of Reed-Solomon (RS) product codes: "Turbo codes RS". Two methods to construct RS product codes are given. The iterative decoding of the RS product codes is based on the soft decoding and the soft decision of the component codes. The performance of RS turbo codes have been evaluated on the Gaussian and Rayleigh channels using Monte Carlo simulation. Coding gains up to 5.5 dB for a BER (bit error rate) of 10/sup -5/ have been obtained on the Gaussian channel. This new coding scheme is very attractive for data storage applications where the RS product codes are often used.
Detection of Alzheimer disease in brain images using PSO and Decision Tree Approach

Alzheimer's disease (AD) is a disease that attacks the brain which worsens as it progresses and it eventually lead to the death. This paper is based on the proposed technique Particle swarm optimization (PSO) for feature reduction and Decision Tree Classifier for classification. Earlier detection of AD is carried out in 3 phases. In the first phase, features such as eigen vectors, eigen brain, mean, variance, skewness, kurtosis, standard deviation, area, perimeter, eccentricity are extracted from MRI Images. In the second phase, feature reduction is carried out by Particle swarm optimization(PSO) and in third phase, Decision Tree Classifier is used to detect whether the brain image is affected by the Alzheimer disease or not. The proposed work is also compared with earlier works.
Impact of Software Quality Standards on Commercial Product Development and Customer Satisfaction for Software Industry in Pakistan

The Global software industry worth about $293 billion in 2011 is plagued by an ironic fact that a huge proportion of the software projects are below their schedules or are not completed due to bad planning, poor specification of software product specifications and technical inadequacies. The concept of software quality management is gaining increasingly more and more popularity as software firms now prefer the use of quality assurance practices to provide software products that are more reliable and efficient. This paper aims to augment earlier research conducted relating to software quality assurance practices and identifies any link between customer satisfaction and optimization of costs associated with the development and maintenance of software products. The gathered data from Clients and development teams is analyzed in SPSS tool to measures the impact of implementing Software Quality Standards on Customer Satisfaction through variations in Product Development Time and Product Safety.
Naive Mechanics Comprehension and Invention in EDISON

Abstract : This paper briefly reports on the current architecture and status of EDISON, a computer model being designed to understand natural language descriptions of mechanical devices and generate novel device representations through heuristic strategies of mutation and analogy. The representational constructs in EDISON must support both of these tasks and include: goal/plan information, spatial relationships, forces, motion, contact, regions, constraints on (and principles of) device operation, levels of abstraction, and naive mechanics dependencies and inferences.
A Distributed Implementation of an N-body Virtual World Simulation

Meeting the challenge of real-time visualization of a complex physical simulation can require several specialized computers. The virtual-world simulation described in this paper combines a highly-parallel computer for physical simulation and a custom graphics engine for display communicating via TCP/IP over an ethernet. Application-level protocols to provide the highthroughput, low-latency communication required to support an interactive virtual world are investigated. Experiments demonstrate that a limited write-ahead protocol gives the best tradeoff between latency and throughput for this application.