Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis, structural and magnetic characterization of spinel nanoparticle ferrites with applications for electrochemical sensors.

This thesis deals mainly with the structural and magnetic properties of Cobased nanoferrite samples that were simultaneously and symmetrically substituted by Mg, Sr, Mn and Ba cations. These samples were synthesized by glycol-thermal method from high purity metal chlorides as starting materials. The synthesized compounds included the series of MgxSrxMnxCo1−3xFe2O4 (x = 0, 0.1, 0.2, 0.3 and 1/3), Ba0.5Co0.5Fe2O4, Sr1/3Mn1/3Co1/3Fe2O4 and Ba1/3Mn1/3Co1/3Fe2O4 nanoferrites. The spinel phases were confirmed by X-ray diffraction (XRD). The sample morphologies were studied by high resolution transmission electron microscopy (HRTEM) and high resolution scanning electron microscopy (HRSEM). The synthesized samples show well-defined lattice fringes in HRTEM images indicative of the crystalline structure. The synthesized nanoparticles were obtained in the range of particles sizes from 7 to 9 nm. We have found a strong correlation between density and molecular weight of the synthesized MgxSrxMnxCo1−3xFe2O4 (x = 0, 0.1, 0.2, 0.3 and 1/3) compounds. The magnetic properties were studied by using Fe Mössbauer spectroscopy and magnetization measurements. The results reveal distortions in the hysteresis loops at low temperature which we associate with spin freezing effects. We also find good correlation between saturation magnetization and particle sizes. The temperature dependences of the saturation magnetization and coercive field show interesting trends. The magnetization data can be fitted by the modified Bloch’s law and the coercive fields by Kneller’s law at low temperature below the blocking temperature. The temperature dependent of coercivity follows T law with α ' 0.77. However, the temperature dependence of the coercive field for Ba0.5Co0.5Fe2O4 follows Kneller’s law with α = 1. With increasing values of x, significant correlation between coercive field and the blocking temperatures have been observed. We also report coercive field enhancements at low temperature for the samples with x = 0, 0.1 and 0.2. The Ba1/3Mn1/3Co1/3Fe2O4 sample shows increased magnetization from 66.5±0.3 emu/g at 300 K to 84.4±0.5 emu/g at 4 K. The Brunauer-Emmet-Teller (BET) surface area measurements and Barrett-Joyner-Halenda (BJH) measurements of Ba0.5Co0.5Fe2O4, Sr1/3Mn1/3Co1/3Fe2O4 and Ba1/3Mn1/3Co1/3Fe2O4 nanoparticle sam-
Corneal advanced glycation end products increase in patients with proliferative diabetic retinopathy.

OBJECTIVE To evaluate corneal advanced glycation end product (AGE) fluorescence in patients with diabetes and in healthy control subjects. RESEARCH DESIGN AND METHODS Corneal autofluorescence was measured in 26 eyes of 26 patients with type 2 diabetes (mean age 57.0 years; mean disease duration 12.2 years; mean HbA1c 7.1%) and 13 eyes of 13 healthy age-matched control subjects (mean age 57.9 years). The patients with type 2 diabetes were divided into the following groups: patients without diabetic retinopathy (DR), patients without proliferative diabetic retinopathy (PDR), and patients with PDR. Corneal autofluorescence was measured by fluorophotometry with the wavelength that is characteristic of AGE fluorescence (excitation and emission 360-370 nm and 430-450 nm, respectively). We defined peak corneal autofluorescence levels as corneal AGE fluorescence values. We compared the corneal AGE fluorescence values in the four groups. RESULTS In the PDR group (11.9 +/- 3.9 arbitrary units [mean +/- SD]), the corneal AGE fluorescence values were significantly higher compared with the control subjects (6.9 +/- 1.3 arbitrary units), the patients without DR (7.4 +/- 2.1 arbitrary units), and the patients without PDR (6.9 +/- 2.2 arbitrary units) (P < 0.05). CONCLUSIONS We found that corneal AGEs may increase in patients with diabetes and PDR compared with control subjects, patients without DR, and patients without PDR. In the patients with PDR, increased corneal AGEs may play a role in diabetic keratopathy.
Exploiting the Role of Position Feature in Chinese Relation Extraction

Relation extraction is the task of finding pre-defined semantic relations between two entities or entity mentions from text. Many methods, such as feature-based and kernel-based methods, have been proposed in the literature. Among them, feature-based methods draw much attention from researchers. However, to the best of our knowledge, existing feature-based methods did not explicitly incorporate the position feature and no in-depth analysis was conducted in this regard. In this paper, we define and exploit nine types of position information between two named entity mentions and then use it along with other features in a multi-class classification framework for Chinese relation extraction. Experiments on the ACE 2005 data set show that the position feature is more effective than the other recognized features like entity type/subtype and character-based N-gram context. Most important, it can be easily captured and does not require as much effort as applying deep natural language processing.
Solving systems of polynomial equations: A novel end condition and root computation method

In this paper we present an improvement of the algorithm based on recursive de Casteljau subdivision over an n-dimensional bounded domain (simplex or box). The modification consists of a novel end condition and a way of calculation the root in subdomain. Both innovations are based on linear approximation of polynomials in a system. This improvement results in that our approach takes almost half of the time of the standard approach: it can be stopped much earlier than using standard diameter condition and getting midpoint of a subdomain as a root.
Study of the impact of Enterprise Investment Scheme (EIS) and Venture Capital Trusts (VCT) on company performance

Copyright in the typographical arrangement and design rests with the crown. This publication may be reproduced free of charge in any format or medium provided that it is reproduced accurately and not used in a misleading context. The material must be acknowledged as Crown copyright with the title and source of the publication specified. The views expressed in this report are those of the authors' and do not necessarily represent those of HM Revenue & Customs. The Institute for Employment Studies is an independent, apolitical, international centre of research and consultancy in public employment policy and organisational human resource issues. It works closely with employers in the manufacturing, service and public sectors, government departments, agencies, and professional and employee bodies. For over 35 years the Institute has been a focus of knowledge and practical experience in employment and training policy, the operation of labour markets and human resource planning and development. IES is a not‐for‐profit organisation which has over 60 multidisciplinary staff and international associates. IES expertise is available to all organisations through research, consultancy, publications and the Internet. IES aims to help bring about sustainable improvements in employment policy and human resource management. IES achieves this by increasing the understanding and improving the practice of key decision makers in policy bodies and employing organisations. The School provides programmes in business and economics across the full range of higher education; from undergraduate to MBA. With a worldwide reputation for research and teaching in finance, accounting, economics and management, we aim to produce graduates who will make a real difference to the organisations they work for. The School of Business and Economics is one of the largest schools in the university with 54 full‐time academic staff, more than 800 undergraduate students and over 400 postgraduates. The School has an international reputation for high quality teaching and leading edge research and this was recognised in the 2001 government review of UK universities. vi vii Contents Executive Summary xi Background and objectives of the study xi Setting the context for this study xii Key findings xiv General Capacity Building xiv Profitability xiv Productivity xiv Sector xv Age xv Survival xv
An in-depth study of next generation interface for emerging non-volatile memories

Non-Volatile Memory Express (NVMe) is designed with the goal of unlocking the potential of low-latency, randomaccess, memory-based storage devices. Specifically, NVMe employs various rich communication and queuing mechanism that can ideally schedule four billion I/O instructions for a single storage device. To explore NVMe with assorted user scenarios, we model diverse interface-level design parameters such as PCI Express, NVMe protocol, and different rich queuing mechanisms by considering a wide spectrum of host-level system configurations. In this work, we also assemble a comprehensive memory stack with different types of emerging NVM technologies, which can give us detailed NVMe related statistics like I/O request lifespans and I/O thread-related parallelism. Our evaluation results reveal that, i) while NVMe handshaking is light-weight for flash memory that uses block-based accesses (Block NVM), it can impose tremendous overheads for memristor technology (DRAM-like NVM), ii) in contrast to the common expectation, the performance of an NVMe-equipped system may not improve in a scalable fashion as the queue depth and the number of queues increase, and iii) more- and deeperqueue systems atop a Block NVM can significantly suffer from tremendous host-side memory requirements, whereas a DRAMlike NVM can cause frequent system stalls due to NVMe's inefficient interrupt service routine.
Assessment of Lipiodol Deposition and Residual Cancer for Hepatocellular Carcinoma After Transcatheter Arterial Chemoembolization via Iodine-Based Material Decomposition Images with Spectral Computed Tomography Imaging: A Preliminary Study

Background: It is critical to follow up hepatocellular carcinoma (HCC) after transcatheter arterial chemoembolization (TACE) in clinical practice. Computed tomography (CT) is used to assess lipiodol deposition, whereas it is difficult to assess hypovascular residual cancer masked by lipiodol. In contrast, magnetic resonance imaging (MRI) is superior to CT in showing residual cancer, but cannot display lipiodol deposition. Objectives: The aim of this study was to investigate the value of spectral CT imaging in both lipiodol deposition and residual cancer for HCC patients after TACE. Patients and Methods: Ten HCC patients after treated with TACE underwent Discovery CT750 HD and MRI750 3T examination. Receiver operating characteristic (ROC) curves of iodine-based material decomposition images, monochromatic images and conventional CT images were generated. Results: Consequently, 30 residual lesions were detected in MRI of 10 patients. They were found in iodine-based images and monochromatic images versus 29 in conventional CT images. The area under ROC curves for the lesion-to-normal parenchyma ratio (LNR) on arterial phase (AP) in iodine-based material decomposition images, monochromatic images and conventional CT images were 0.933, 0.833 and 0.817, respectively. Conclusion: The study data highlighted good value of iodine-based material decomposition images of spectral CT in assessment of both lipiodol deposition and residual cancer for follow-up of HCC patients previously treated with TACE.
Goals of Analysis for Visualization and Visual Data Mining Tasks

Extensive work has been done in the area of visual data mining in the last few years. This includes the development of visual and non-visual mining methods for large, heterogeneous and uncertain data. An appropriate selection and parameterization of such mining techniques are sensitive processes, especially if we have to consider highly complex analysis environments. One of the most important factors are goals of analysis, which specify the user’s intentions in the analysis process. This paper describes a new, general specification for goals of analysis. It extends existing approaches by aspects of importance for real-world application scenarios
Implicit-explicit multistep finite element methods for nonlinear parabolic problems

We approximate the solution of initial boundary value problems for nonlinear parabolic equations. In space we discretize by finite element methods. The discretization in time is based on linear multistep schemes. One part of the equation is discretized implicitly and the other explicitly. The resulting schemes are stable, consistent and very efficient, since their implementation requires at each time step the solution of a linear system with the same matrix for all time levels. We derive optimal order error estimates. The abstract results are applied to the Kuramoto-Sivashinsky and the Cahn-Hilliard equations in one dimension, as well as to a class of reaction diffusion equations in R v , v = 2,3.
A Sampling Algebra for Aggregate Estimation

As of 2005, sampling has been incorporated in all major database systems. While efficient sampling techniques are realizable, determining the accuracy of an estimate obtained from the sample is still an unresolved problem. In this paper, we present a theoretical framework that allows an elegant treatment of the problem. We base our work on generalized uniform sampling (GUS), a class of sampling methods that subsumes a wide variety of sampling techniques. We introduce a key notion of equivalence that allows GUS sampling operators to commute with selection and join, and derivation of confidence intervals. We illustrate the theory through extensive examples and give indications on how to use it to provide meaningful estimates in database systems.
The Extraction of Micro-Doppler Signal With EMD Algorithm for Radar-Based Small UAVs’ Detection

The rotation of rotor blades on small unmanned aerial vehicles (UAVs) introduces micro-Doppler (m-D) signatures to discriminate UAVs from other aircrafts or birds. Compared with the Doppler signal induced by the translation of the platform, the m-D signal, however, is rather weak due to the small radar cross section (RCS) of rotor blades. Moreover, the m-D signal always consists of multiple frequency components, most of which are induced by the vibration of the platform. This paper focuses on the extraction of the rotation signal via the empirical mode decomposition (EMD) algorithm, which would decompose an arbitrary signal into a series of intrinsic mode functions (IMFs). The constitution of IMF is investigated by using the partial differential equations (PDEs) to analyze the distribution of the extrema. For separating the rotation signal, the essence is to unify the frequency of extrema in the corresponding IMF exhibiting the rotation features. First, the fitting Doppler signal is constructed from the data with the Doppler property in the IMF. Second, a criterion is proposed to establish the masking signal, after which the rotation components are extracted from the residual m-D signal via another EMD. Simulations are carried out to demonstrate the effectiveness of the proposed method in solving the mode-mixing problem. The results derived from the measured data validate the feasibility of the proposed approach in the identification of small UAVs.
A least-squares approach to joint diagonalization

We present a new least-squares-based approach for the joint diagonalization problem arising in blind beamforming. The resulting estimation criterion turns out to coincide with that proposed by Cardoso and Souloumaic (see IEE Proc. F, Radar Signal Process., vol.140, no.6, p.362-70, Dec. 1993) on intuitive grounds, thus establishing the optimality of their criterion in the least-squares (LS) sense.
Pe-marked Definite Nps in Romanian and Discourse Prominence

" Mismatches " , i.e. linguistic phenomena with 'feature contradictions' on different levels of linguistic structure, like deponentia in Latin (passive morphology with an active semantics), are a recently much discussed linguistic topic (cf. e.g. the volume Mismatch: Form-Function Incongruity and the Architecture of Grammar edited by Elaine J. Francis and Laura A. Michaelis, 2002, CSLI Publications). Therefore, the fifth NEREUS workshop focussed on different cases of mismatches in Romance languages, discussing theoretical aspects as well as concrete cases of e.g. 'problematic' arguments and argument-marking patterns (cf. the contributions by McNally/Espinal, García García and von Heusinger/Chiriacescu), agreement and other mismatches inside DPs (cf. the contributions by Marchis and Pomino), subject verb-agreement and clitics (cf. the contributions by von Heusinger/Kaiser and Fischer), and complex predicates (cf. the contribution by Bartra Kaufmann). While the contributions by McNally/Espinal and Bartra Kaufmann address syntax-semantics mismatches and Marchis a categorial mismatch, García García and von Heusinger/Chiriacescu focus on syntax-morphology mismatches. The contribution of Pomino deals both with syntax-morphology and syntax-phonology mismatches, and the one by von Heusinger/Kaiser with syntax-morphology and syntax-semantics mismatches. The languages discussed range from Catalan and Spanish) to a multitude of different Italo-Romance varieties (Pomino). Though some authors present at the workshop could not include their presentation in this volume, we would like to thank all the contributors and participants at the workshop for their talks and interesting discussion. We would like to thank particularly the University of Zurich (UZH) and the Hochschulstiftung of the University of Zurich (UZH) for funding the workshop, as well as
Challenges of close-range underwater optical mapping

Underwater optical mapping often involves the use of image mosaicing techniques. High quality mosaicing requires the application of blending methods to achieve continuous and artifact-free mosaics. Image blending has a dilated history of over three decades in the terrestrial and aerial fields. Unfortunately, the nature of the underwater medium adds additional difficulties to the mosaicing and blending tasks. In this paper a survey of the blending methods is given, focusing the attention on its applicability to underwater mosaicing. Image acquisition is performed by Autonomous Underwater Vehicles (AUVs) or Remotely Operated Vehicles (ROVs) in the deep ocean, a medium with aggressive light absorption and disrupting scattering effects that requires of the use of artificial lighting. A comprehensive comparison of the basic features and limitations of some of the most important existing blending techniques is presented. The goal is the generation of seamless and visually pleasant large area photo-mosaics of the seafloor, free from double contouring, ghosting and other disturbing and common blending artifacts.
Motivation, Induction, and Challenge: Examining the Initial Phase of International Students' Educational Sojourn.

This study explores the initial higher education experiences of first-year international students in the United Kingdom. Questionnaires and semistructured interviews were carried out with 20 new international students undertaking a business degree at a U.K. university. The students described the key motivating factors for studying abroad and the fundamental issues and challenges they encountered. The language barrier, academic skills and orientation were highlighted as being integral to their development. A comprehension of international students’ initial academic and social needs is important in enabling universities to develop systems that will meet the prevailing needs of these learners.
Applying of network security situation awareness in smart substations

Applying of network security situation awareness in smart substations provides a high level view to understand the security situation of substations. After analyzing security threats faced by smart substations, this paper not only proposes a security situation awareness framework from aspects of physical security, network security, system security, protocol security and data security, but also puts forward a network security monitoring solution for substations, which uses a kind of dedicated smart substation network security situation awareness devices to collect security events, analyze them and generate situation analysis results. Further, we focus on several key technologies used in our framework. Finally, we describe a design scheme including hardware and software for the smart substation network security awareness system and its implementation architecture, in which a multi-layer software architecture is adopted by the system, and a combinatory of the Intel® Sandy Bridge, the bus structure and a modular design technology, is adopted in order to meet the need of high performance.
A COMPUTER SOFTWARE FOR THE EDUCATION OF COMPLEX NETWORK ANALYSIS

Complex network analysis is an attractive tool for capturing the self-organizing principles underlying the social, physical or biological communities. Several software are developed for either analyzing or generating complex networks, including the visualization utilities. We developed an open source software in Microsoft . NET platform for generating networks based on the most common models as Barabasi-Albert, Erdos-Renyi, Watts-Strogatz including the analyzing utilities defining the network like average separation, degree distribution, clustering coefficient etc. In contrast with the well-known software, this software aims to contribute the understanding of the underlying mechanisms of complex networks. It also forms a basis to further developments that should provide an extensive view to network construction. As an open source software, the opportunity of editing the core functions about network dynamics offer a pedagogical approach to learn more about self-organizing networks.
Analytical Study of Connectivity in Wireless Adhoc Networks with Random Beamforming

Random beamforming is a technique in which each node in a wireless ad hoc network directs its main beam in a randomly chosen direction. This paper presents an analytical method for investigating the effect of random beamforming on the connectivity of wireless ad hoc networks. We derive analytically an expression for an effective beamforming gain, which we use to characterize the impact of random beamforming on the number of direct connections for an arbitrary node, i.e. the local connectivity. Our results show that for a path-loss propagation model, random beamforming improves the local connectivity for a path-loss exponent α < 3, while it degrades the local connectivity for larger values of α. The analytical method is validated by comparison with simulation results.
Implementation Of Bayesian Network In FPGA Circuit

The paper presents a novel approach to the implementation of Bayesian network - an implementation in an FPGA circuit. The opportunities and problems connected with the parallel-processing approach of the FPGA circuit are discussed. Modifications of the computation algorithm that are needed due to limited computational capabilities are described. Details of the construction of the main computational blocks are also depicted
The OpenLISP control plane architecture

Among many options tackling the scalability issues of the current Internet routing architecture, the Locator/Identifier Separation Protocol (LISP) appears as a viable solution. LISP improves a network's scalability, flexibility, and traffic engineering, enabling mobility with limited overhead. As for any new technology, implementation and deployment are essential to gather and master the real benefits that it provides. In this article, we present the first complete open source implementation of the LISP control plane. Our implementation is deployed in the worldwide LISP Beta Network and the French LISP-Lab testbed, and includes the key standardized control plane features. Our control plane software is the companion of the existing OpenLISP dataplane implementation, allowing the deployment of a fully functional open source LISP network compatible with any implementation respecting the standards.