Miracle-dz/UniFAR-FTUs huggingface dataset:
UvA-DARE ( Digital Academic Repository ) Compositionality : its historic context

The aim of this chapter is to investigate the line from the 19th century, through Frege’s works, to the appearance of the principle of compositionality in modern sciences. It is shown that contextuality and compositionality were discussed at the beginnings of the 19th century, but that contextuality was favoured. Also for Frege contextuality was the basic principle and he always obeyed it. Although he argued that within a given sentence, one may distinguish a compositional structure, he would never accept compositionality as we know it. Carnap was the first to give a formulation of the compositionality principle. In logic, natural language semantics, and computer science, ‘compositionality’ arose independently, and is a generally accepted method, but when a phenomenon is studied that has a strong influence from context, non-compositional methods are used without hesitation. The wide support for compositionality turns out to be for practical reasons, not for principled ones.
What makes e-government a satisfying place employment?An internal perspective on service

The present study is a two-step approach using qualitative and quantitative data to analyse the relationship between governmental work conditions and employees’ job satisfaction with regard to its impact on service quality. The goal of the study is to develop a model of factors determining the service quality within an e-government employment. Based on previous research studies it is assumed that employees’ satisfaction is a direct driver for good service quality. It is not clear yet whether this also applies to the quality of e-government services. Previous literatures have rather focused on the private offline sector from an external perspective. Therefore, this study draws its attention on the public sector from an internal perspective. Twenty-five interviews within a non-profit housing association in North England were conducted with the result of seven factors affecting their job satisfaction. Based on the findings a model was developed and tested by means of a questionnaire. The regression analysis shows that Interpersonal Relationships, Working Morale, Communication Culture, Employer and Leadership Characteristics, and the Quality of Information Technology are related to Service Quality.
Drug screening with Elastic-net multiple kernel learning

We apply Elastic-net Multiple Kernel Learning (MKL) to the MDL Drug Data Report (MDDR) database for the problem of drug screening. We show that combining a set of kernels constructed from fingerprint descriptors, can significantly improve the accuracy of prediction, against a Support Vector Machine trained on each kernel separately. To the best of our knowledge, this is the first application of MKL to the MDDR database for drug screening.
Immobilization of Commercial Cellulase and Xylanase by Different Methods Using Two Polymeric Supports

Industrial applications require enzymes highly stable and economically viable in terms of reusability. Enzyme immobilization is an exciting alternative to improve the stability of enzymatic processes. The immobilization of two commercial enzymes is reported here (cellulase and xylanase) using three chemical methods (adsorption, reticulation, and crosslinking-adsorption) and two polymeric supports (alginate-chitin and chitosan-chitin). The optimal pH for binding was 4.5 for cellulase and 5.0 for xylanase, and the optimal enzyme concentrations were 170 μg/mL and 127.5 μg/mL respectively, being the chitosan and the ideal support. In some cases, a low concentration of crosslinking agent (glutaraldehyde) improved stability of the immobilization process. Biotechnological characterization showed that the reusability of enzymes was the most striking finding, particularly of immobilized cellulase using glutaraldehyde, which after 19 cycles retained 64% activity. These results confirm the economic and biotechnical advantages of enzyme immobilization for a range of industrial applications.
Overview of the IWSLT04 evaluation campaign

This paper gives an overview of the evaluation campaign results of the IWSLT04 1 workshop, which is organized by the C-STAR 2 consortium to investigate novel speech translation technologies and their evaluation. The objectives of this workshop is to provide a framework for the applicability validation of existing machine translation evaluation methodologies to evaluate speech translation technologies. The workshop also strives to find new directions in how to improve current methods.
The Effects of 10-week Integrated Neuromuscular Training on Fundamental Movement Skills and Physical Self-efficacy in 6–7-Year-Old Children

Abstract Duncan, MJ, Eyre, ELJ, and Oxford, SW. The effects of 10-week integrated neuromuscular training on fundamental movement skills and physical self-efficacy in 6–7-year-old children. J Strength Cond Res 32(12): 3348–3356, 2018—Integrated neuromuscular training (INT) has been suggested as an effective means to enhance athletic potential in children. However, few studies have reported the effects of school-based INT programs. This study examined the effect of INT on process and product fundamental movement skill measures and physical self-efficacy in 6–7-year-old children. Ninety-four children from 2 primary schools were randomized into either a 10-week INT program or a control group (CON) (n = 41). Results indicated significantly greater increases in process fundamental movement skill (FMS) scores in INT vs. CON (p = 0.001). For product measures of FMS, 10-m sprint time, counter movement jump, seated medicine ball throw and standing long jump (all p = 0.001), all significantly increased to a greater extent in the INT group vs. CON. A significant group (INT vs. CON) × time (pre vs. post) × gender interaction for physical self-efficacy revealed increased physical self-efficacy pre to post INT, compared with CON but only for boys (p = 0.001). For girls, physical self-efficacy was not significantly different before to after the 10-week period for INT and CON groups. The results of this study suggest that replacing 1 of the 2 weekly statutory physical education (PE) lessons with an INT program over a 10-week period results in positive improvements in fundamental movement skill quality and outcomes in 6–7-year-old children. Integrated neuromuscular training also appears to increase physical self-esteem to a greater extent than statutory PE but only in boys.
Towards Better User Preference Learning for Recommender Systems

In recent years, recommender systems have become widely utilized by businesses across industries. Given a set of users, items, and observed user-item interactions, these systems learn user preferences by collective intelligence, and deliver proper items under various contexts to improve user engagements and merchant profits. Collaborative Filtering is the most popular method for recommender systems. The principal idea of Collaborative Filtering is that users might be interested in the items that are preferred by users with similar preferences. Therefore, learning user preferences is the core technique of Collaborative Filtering. In this thesis, we study new methods to help us better understand user preferences from three perspectives. We first dive into each rating that users give on the items, and study the reasons behind the ratings by analyzing user reviews. We propose a unified model that combines the advantages of aspect-based opinion mining and collaborative filtering, which could extract latent aspects and sentiments from reviews and learn users’ preferences of different aspects of items collectively. In our next work, we study the problem from each user’s perspective, and propose a general and flexible model that embraces several popular models as special cases. The new model achieves better top-N recommendation results on several popular data sets. Finally, we study how to utilize the general structure of the user-item matrix to better apply collaborative filtering methods. We propose a co-clustering based method that first partitions the users and items into several overlapping and focused subgroups, and then applies collaborative filtering methods within each subgroup. The final recommendations for users are aggregated from the results from the subgroups they are involved in. Experimental results show that this method could produce better recommendations than other coclustering methods and methods that directly apply collaborative filtering on the original user-item matrix.
The WiggleZ Dark Energy Survey: the growth rate of cosmic structure since redshift z=0.9

We present precise measurements of the growth rate of cosmic structure for the redshift range 0.1 < z < 0.9, using redshift-space distortions in the galaxy power spectrum of the WiggleZ Dark Energy Survey. Our results, which have a precision of around 10 per cent in four independent redshift bins, are well fitted by a flat Λ cold dark matter (ΛCDM) cosmological model with matter density parameter Ω_m = 0.27. Our analysis hence indicates that this model provides a self-consistent description of the growth of cosmic structure through large-scale perturbations and the homogeneous cosmic expansion mapped by supernovae and baryon acoustic oscillations. We achieve robust results by systematically comparing our data with several different models of the quasi-linear growth of structure including empirical models, fitting formulae calibrated to N-body simulations, and perturbation theory techniques. We extract the first measurements of the power spectrum of the velocity divergence field, P_(θθ) (k), as a function of redshift (under the assumption that P_(gθ) (k) = − √P_(gg)(k)P_(θθ) (k), where g is the galaxy overdensity field), and demonstrate that the WiggleZ galaxy–mass cross-correlation is consistent with a deterministic (rather than stochastic) scale-independent bias model for WiggleZ galaxies for scales k < 0.3 h Mpc^(−1). Measurements of the cosmic growth rate from the WiggleZ Survey and other current and future observations offer a powerful test of the physical nature of dark energy that is complementary to distance–redshift measures such as supernovae and baryon acoustic oscillations.
Do FRR 48 Disclosures Reduce Investors' Uncertainty and Diversity of Opinion about Firms' Market Risk Exposures?: A Trading Volume Analysis

This paper examines whether mandated market risk disclosures under the SEC Financial Reporting Release No. 48 (FRR 48) provide useful information to investors regarding firms' risk exposures. To provide evidence on this issue we investigate whether the SEC disclosures reduce investor uncertainty and diversity of opinion about the implications of market rate or price changes for firm value. We expect this reduced uncertainty and diversity of opinion to manifest itself in a decline in the amount of daily trading volume associated with market rate or price changes after the disclosures are made public. To test this hypothesis we introduce the trading volume risk response coefficient (TVRRC), which measures the association between daily movements in market rates or prices and the daily percentages of a firm's shares traded, after controlling for other factors that affect trading volume. We examine whether downward shifts in the TVRRC occurred after the 10-K filing dates for a sample of firms that first made FRR 48 disclosures in their 1997 SEC reports. We find such downward shifts in the TVRRC for firms disclosing market risk information about interest rate, foreign currency exchange rate, and energy price exposures. We also test for differences in results across the three quantitative disclosure methods allowed by FRR 48 (tabular, sensitivity and value at risk). We find downward TVRRC shifts for firms reporting interest rate exposures using any of the three methods, but only for firms reporting sensitivity or value at risk for exposures to foreign currency exchange rates. To rule out alternative explanations for the results, we focus on two control samples: (1) the original disclosure sample in the year before the SEC rule was effective and (2) a non-disclosure sample consisting of firms subject to the SEC rule that did not make market risk disclosures in the first fiscal year the rule was effective. We do not find significant shifts in TVRRC around these 10-K filing dates in either sample. We therefore interpret the downward shifts in TVRRC for the first-time disclosers as evidence supporting the hypothesis that the SEC-mandated disclosures reduce investor uncertainty and diversity of opinion about the implications of market rate or price changes for firm value.
A Secure Link State Approach for Network Security

The pervasive nature of today’s information infrastructure coupled with recent threats for cyber terrorism makes network (i.e., internal network and Internet) infrastructure security a critical issue for both computer security practitioners and researchers. Among various network security issues, a routing attack (i.e., attacks against routing protocols or attacks using routers) is the most noticeable as it can bring down a network infrastructure without causing any physical damage to the network entities. We discuss these potential attacks and propose a new secure routing framework based on security techniques (authentication and confidentiality) for a link-state routing protocol. The proposed framework emphasizes the use of efficient cryptographic countermeasures for network survivability against security threats to link-state routing protocol. The framework relies on providing information level authentication and information level confidentiality that can be imbedded in link-state routing protocol with assistance of a key management system that uses secure group communication.
Absence of a sharp glass transition in mode coupling theory.

A self-consistent mode coupling model for supercooled fluids is derived from fluctuating nonlinear hydrodynamics (extended to short wavelengths) with attention to detailed balance constraints. The sharp glass transition predicted by mode coupling models based only on pressure nonlinearities does not occur here. Instead, the long time asymptotic behavior of the density autocorrelation function is determined by additional nonlinearities imposed by the detailed balance constraints
c‐Myb and Ets proteins synergize to overcome transcriptional repression by ZEB

The Zfh family of zinc finger/homeodomain proteins was first identified in Drosophila where it is required for differentiation of tissues such as the central nervous system and muscle. ZEB, a vertebrate homolog of Zfh‐1, binds a subset of E boxes and blocks myogenesis through transcriptional repression of muscle genes. We present evidence here that ZEB also has an important role in controlling hematopoietic gene transcription. Two families of transcription factors that are required for normal hematopoiesis are c‐Myb and Ets. These factors act synergistically to activate transcription, and this synergy is required for transcription of at least several important hematopoietic genes. ZEB blocks the activity of c‐Myb and Ets individually, but together the factors synergize to resist this repression. Such repression imposes a requirement for both c‐Myb and Ets for transcriptional activity, providing one explanation for why synergy between these factors is important. The balance between repression by ZEB and transcriptional activation by c‐Myb/Ets provides a flexible regulatory mechanism for controlling gene expression in hematopoietic cells. We demonstrate that one target of this positive/negative regulation in vivo is the α4 integrin, which play a key role in normal hematopoiesis and function of mature leukocytes.
Alternate circulation and genetic variation of human respiratory syncytial virus genotypes in Chengdu, West China, 2009‐2014

Human respiratory syncytial virus (HRSV) is a major pathogen that causes worldwide seasonal epidemic disease in infants due to its genetic variations. However, published information on the molecular epidemiology of HRSV was never reported particularly in Chengdu of West China. During five consecutive seasons (from 2009 to 2014), 433 (23.7%) of 1827 samples from hospitalized patients were identified as HRSV positive. Epidemiological characteristics of HRSV revealed that subtype A viruses (62.7%) prevailed in the first three epidemic seasons and faded in the next two seasons, while subtype B viruses (37.3%) kept circulating in five epidemic periods. According to the phylogenetic analysis of glycoprotein (G) gene, five HRSV genotypes NA1, ON1, BA9, BA‐C, and CB1 were found in Chengdu. The predominant circulating genotype changed from NA1 in the period of 2010–2012 to BA9 of 2013–2014. The newly emerging ON1 was first reported in West China in October 2013. The early genotypes BA‐C and CB1 were replaced by the prevailing BA9 after the third epidemic peak. Genetic mutations in glycosylation sites of G protein were found in HRSV variants, suggesting the virus is able to escape the immune recognition and attack. This study elucidated the local HRSV epidemic was associated with the alternate circulation of multiple genotypes and with the change of glycosylation sites of G protein. J. Med. Virol. 89:32–40, 2017. © 2016 Wiley Periodicals, Inc.
A fuzzy kernel c-means clustering model for handling concept drift in regression

Concept drift, given the huge volume of high-speed data streams, requires traditional machine learning models to be self-adaptive. Techniques to handle drift are especially needed in regression cases for a wide range of applications in the real world. There is, however, a shortage of research on drift adaptation for regression cases in the literature. One of the main obstacles to further research is the resulting model complexity when regression methods and drift handling techniques are combined. This paper proposes a self-adaptive algorithm, based on a fuzzy kernel c-means clustering approach and a lazy learning algorithm, called FKLL, to handle drift in regression learning. Using FKLL, drift adaptation first updates the learning set using lazy learning, then fuzzy kernel c-means clustering is used to determine the most relevant learning set. Experiments show that the FKLL algorithm is better able to respond to drift as soon as the learning sets are updated, and is also suitable for dealing with reoccurring drift, when compared to the original lazy learning algorithm and other state-of-the-art regression methods.
AN EMPIRICAL MODEL OF STUDENT SATISFACTION : CASE OF PAKISTANI PUBLIC SECTOR BUSINESS SCHOOLS

Quality is key determinant for customers before purchasing a product or availing any type of service and it also plays a significant role in measuring the performance of product/service and the organization as well. This issue has realized the organizations from manufacturing and service sector, how to compete and gain competitive edge in the market by delivering quality product or services as per customer requirements. These organizations had integrated quality management principles and quality tools and techniques to gain competitive edge. Education sector is also among the service sector and considered to be the back bone and major contributor in national and economic development. Quality education is also a challenge for the universities and also many of the universities around globe are putting their efforts to deliver quality of educational services to their customers to gain their satisfaction. In Pakistan, service sector is one of the rapidly growing sectors contributing more than 53% of GDP. To gain competitive edge these service organizations require knowledgeable and highly skilled management professionals to cope up with these challenges. This study aims to investigate the service quality of business schools in public sector and how these institutions are successful in gaining student satisfaction. A modified SERVQUAL instrument is used to evaluate the service quality of four business schools working under public sector universities based on student perceptions. Total 501 students from 4 public sector business schools participated in this study. Structure equation modeling was used to develop service quality and student satisfaction model. Results of this study indicate that business schools are successful in gaining student satisfaction. An Empirical Model of Student Satisfaction: Case of Pakistani Public Sector Business Schools 92|
Exploring the Internationalisation of 
Chinese Privately-owned Enterprises (POEs)

Internationalisation has long been a focus of research among international business scholars. However, there is little knowledge about Chinese firms' internationalisation processes. This study is based on the premise that Chinese firms may have different international behaviours, compared to Western firms, given China's distinctive institutional and cultural environments. To test this argument, this thesis examines Chinese firms' internationalisation rationales, approaches and influential factors. It focuses on small and medium-sized privately-owned enterprises (POEs) that are actively engaged in international operations. Interviews were conducted with decision makers of six POEs from four industries, including the telecommunications networks, electronics, meters, and textiles. These firms were located in Guangdong, Fujian and Zhejiang provinces. The data collected were analysed using within-case and cross-case analysis approaches. Findings were then compared to extant literature, including the Uppsala's internationalisation process model (U-model) and the theory associated with international new ventures (INVs). The findings presented here indicate that the Chinese POEs' internationalisation behaviours are not particularly different from their Western counterparts. Even though neither the U-model nor the INVs framework alone could fully capture the complexities of the Chinese POEs' internationalisation processes, both demonstrate their applicability in different ways. The study develops 15 propositions that should enable researchers to develop a better understanding of Chinese POEs' internationalisation processes. The thesis concludes with a discussion of the implications of these findings for theory development and future research, as well as managerial implications. This case study contributes to a wider theoretical understanding of Chinese POEs' internationalisation behaviours.
Integrated single stage standalone solar PV inverter

The proposed Integrated Single Stage Standalone Solar PV Inverter (IS4 PVI), converts the output from the PV panel directly to AC, while maintaining the output voltage constant. The efficiency of the inverter is improved by minimizing the voltage drop across the inductor. The switching loss in this circuit is minimized by operating one power switch in high frequency. Optimization tool is used to find the suitable inductance value in the power circuit with minimum voltage drop and higher efficiency. A hardware setup for 220V, 50Hz, 700W solar inverter is arranged using 1KW solar system and 100Ah, 12V battery to generate 50Hz sinusoidal voltage with constant magnitude