Miracle-dz/UniFAR-FTUs huggingface dataset:
Graduate over-education in the UK

Abstract: A greater access to education has been the goal of most governments, the corollary of such policies is that doubts have emerged over the capacity of the labour market to absorb a growing proportion of qualified workforce. A large literature on over-education has therefore emerged. However, a clear and un-disputed definition of over-education is still lacking. We stress that pupils with identical qualification are not homogeneous in their endowment of skills. This variation in talent has lead to an over-estimation of the extent and effect of over-education in previous research. We define two categories of over-educated workers. Workers from the first group, called “apparently” over-educated, are satisfied with the match between their education and their position, whereas the “genuinely” overeducated are dissatisfied with this match. The apparently over-qualified group has slightly lower opportunities to get training and is paid nearly 7% less than well-matched graduates. On the other hand, genuinely over-qualified graduates are 12% less likely to be offered employer-funded training and suffer from a pay penalty reaching 33% compare to the reference group. When including a measure of idiosyncratic skills, the pay differential disappears for the “apparently” overeducated workers and is dampened by up to 40% for the “genuinely” over-educated. This study, completed on a sample of two cohorts of UK graduates put some lights on the skill heterogeneity of graduates. Its omission biases the extent of over-education (estimated at 6% of the graduates, compared to previous estimates ranging from 17% to 30%), and its negative effect on earnings.
Updating Description Logics using the AGM Theory

2 Preliminaries We consider the use of belief change techniques to address the problem of updating Knowledge Bases (KBs) based on Description Logics (DLs). We focus on the feasibility of the application of the AGM theory in DL KBs, evaluate the difficulties of the approach and determine the applicability of the method in certain families of DLs. For those DLs that are found compatible with the AGM model, we also describe a contraction operator that satisfies the AGM postulates. Finally, as an application of interest in the area of the Semantic Web, we study OWL, a W3C recommendation, and show that it is incompatible with the AGM model. 2.1 Description Logics The term Description Logics [Baader et al., 2002] refers to a family of knowledge representation languages, heavily used in the Semantic Web. The basic blocks that are used to represent knowledge in DLs are classes (representing concepts), roles (representing binary relationships between concepts) and individuals (representing individual objects). These are used to form more complex expressions (terms) using certain operators. Knowledge is represented using axioms; an axiom represents a certain relationship (such as inclusion, membership and others) between terms using certain connectives. The part of the DL KB dealing with concepts and roles is called the Tbox, while individuals are described in the Abox. The operators and connectives that a certain DL admits determine the type and complexity of the available axioms, which, in turn, determine the expressive power and the reasoning complexity of the DL.
Improved Measure Algorithm Based On Cosamp For Image Recovery

abstract In order to improve the quality of the reconstruction image which using Compressive sensing(CS) algorithm. Based on improved measurement matrix combined with CS Matching Pursuit(CoSaMP)algorithm, this paper presents a kind of Fourier Ring Compressive Sampling Matching Pursuit (FR-CoSaMP) algorithm. The algorithm superimposed deterministic ring measurement matrix to optimize measurement process on the basis of Fourier measurement matrix. And solve the iterative inverse operation by using FFT fast Fourier calculation method, which can make the measurement information more complete, and speed up the signal reconstruction. Then introduces the mathematical framework and algorithmic processes of the FR-CoSaMP algorithm in details. Finally, compare these types of traditional algorithms and the improved algorithm by analysis and simulation. The results show that, under the same image sparsity and measurement scale, the improved FR-CoSaMP algorithm has better performance in terms of the image reconstruction.
Cornwall-Jackiw-Tomboulis effective potential for canonical noncommutative field theories

We apply the Cornwall–Jackiw–Tomboulis (CJT) formalism to the scalar λφ4 theory in canonical-noncommutative space–time. We construct the CJT effective potential and the gap equation for general values of the noncommutative parameter θμν. We observe that under the hypothesis of translational invariance, which is assumed in the effective potential construction, differently from the commutative case (θμν=0), the renormalizability of the gap equation is incompatible with the renormalizability of the effective potential. We argue that our result, is consistent with previous studies, suggesting that a uniform ordered phase would be inconsistent with the infrared structure of canonical noncommutative theories.
Evaluating a Chord-Labelling Algorithm

This paper outlines a method for evaluating a new chordlabelling algorithm using symbolic data as input. Excerpts from full-score transcriptions of 40 pop songs are used. The accuracy of the algorithm’s output is compared with that of chord labels from published song books, as assessed by experts in pop music theory. We are interested not only in the accuracy of the two sets of labels but also in the question of potential harmonic ambiguity as reflected the judges’ assessments. We focus, in this short paper, on outlining the general approach of this research project.
EglC, a New Endoglucanase from Aspergillus niger with Major Activity towards Xyloglucan

ABSTRACT A novel gene, eglC, encoding an endoglucanase, was cloned from Aspergillus niger. Transcription of eglC is regulated by XlnR, a transcriptional activator that controls the degradation of polysaccharides in plant cell walls. EglC is an 858-amino-acid protein and contains a conserved C-terminal cellulose-binding domain. EglC can be classified in glycoside hydrolase family 74. No homology to any of the endoglucanases from Trichoderma reesei was found. In the plant cell wall xyloglucan is closely linked to cellulose fibrils. We hypothesize that the EglC cellulose-binding domain anchors the enzyme to the cellulose chains while it is cleaving the xyloglucan backbone. By this action it may contribute to the degradation of the plant cell wall structure together with other enzymes, including hemicellulases and cellulases. EglC is most active towards xyloglucan and therefore is functionally different from the other two endoglucanases from A. niger, EglA and EglB, which exhibit the greatest activity towards β-glucan. Although the mode of action of EglC is not known, this enzyme represents a new enzyme function involved in plant cell wall polysaccharide degradation by A. niger.
S-BLOSUM: Classification of 2D Shapes with Biological Sequence Alignment

Recent works investigated the possibility to design solutions for pattern recognition problems by exploiting the huge amount of work done in bioinformatics. If the pattern recognition problem is cast in biological terms, then a huge range of algorithms, exploitable for classification, detection, visualization, etc. can be effectively borrowed. In this paper, we exploit biological sequence alignment tools to classify 2D shapes, tailoring the biological parameters of these tools to account for the different semantic of the 2D shape scenario. In particular, we propose a novel substitution matrix, which is the crucial parameter determining the sequence alignment solution. The new matrix, called S-BLOSUM, learns the rates of matches/mismatches in conserved portions of shapes belonging to the same category, and incorporates prior knowledge on the chosen representation for the 2D shape. On one hand, the experimental evaluation showed that the S-BLOSUM provides a significant improvement over the biological counterpart (BLOSUM), on the other hand, classification results prove that our approach is competitive with respect to the state of the art.
Influence of periodic wall roughness on the slip behaviour at liquid/solid interfaces: molecular-scale simulations versus continuum predictions

The influence of surface roughness on the slip behaviour of a Newtonian liquid in steady planar shear is investigated using three different approaches, namely Stokes flow calculations, molecular dynamics (MD) simulations and a statistical mechanical model for the friction coefficient between a corrugated wall and the first liquid layer. These approaches are used to probe the behaviour of the slip length as a function of the slope parameter $ka\,{=}\,2 \pi a/\lambda$, where $a$ and $\lambda$ represent the amplitude and wavelength characterizing the periodic corrugation of the bounding surface. The molecular and continuum approaches both confirm a monotonic decay in the slip length with increasing $ka$ but the rate of decay as well as the magnitude of the slip length obtained from the Stokes flow solutions exceed the MD predictions as the wall feature sizes approach the liquid molecular dimensions. In the limit of molecular-scale wall corrugation, a Green–Kubo analysis based on the fluctuation–dissipation theorem accurately reproduces the MD results for the behaviour of the slip length as a function of $a$. In combination, these three approaches provide a detailed picture of the influence of periodic roughness on the slip length which spans multiple length scales ranging from molecular to macroscopic dimensions.
On the use of ARMAX approach for handwriting system modelization

Modeling handwriting system allows studying movements of the hand and its control signals as integrated electromyographic signals (IEMG) which are detected during muscle contraction involved in the act of writing. Reconstruction of muscle stimuli from written application can have a very important impact especially for the design of support systems for the disabled. In this paper, we propose a new mathematical model to estimate this muscle signal based on identification parameters of a discrete time system, using Auto-Regressive Average with eXternal inputs (ARMAX) models and the Recursive Least Squares algorithm (RLS).
Retrieving Records from a Gigabyte of Text on a Mini-Computer Using Statistical Ranking

Statistically based ranked retrieval of records using keywords provides many advantages over traditional Boolean retrieval methods, especially for end users. This approach to retrieval, however, has not seen widespread use in large operational retrieval systems. To show the feasibility of this retrieval methodology, research was done to produce very fast search techniques using these ranking algorithms, and then to test the results against large databases with many end users. The results show not only response times on the order of 1 and l/2 seconds for 806 megabytes of text, but also very favorable user reaction. Novice users were able to consistently obtain good search results after 5 minutes of training. Additional work was done to devise new indexing techniques to create inverted files for large databases using a minicomputer. These techniques use no sorting, require a working space of only about 20% of the size of the input text, and produce indices that are about 14% of the input text size.
ON THE OPTIMAL REINFORCEMENT OF AN ELASTIC MEMBRANE

We consider an elastic membrane occupying a domain Ω of R under the action of a given exterior load f . The membrane can be reinforced by the addition of a suitable potential term in the energy; this is usually a boundary term but also other situations can be considered. We study the optimal configuration of the stiffeners which provide the best reinforcement of the membrane.
Trayectorias Socioeconómicas Compartidas (SSP): nuevas maneras de comprender el cambio climático y social

Although the scientific community has recently confirmed the role of human activity in greenhouse gas emissions, there are still major challenges to consider future social transformations and their effects on climate and societies. In this paper, we discuss the use of climate change scenarios as a heuristic tool to examine the interactions between terrestrial and social systems. Particularly, we discuss the usefulness of Shared Socioeconomic Trajectories (SSP) to model alternative development futures, which imply different climate change mitigation and adaptation. We consider on their background, applications and potential uses for Mexico.
CD40-Associated TRAF 6 Signaling Is Required for Disease Induction in a Retrovirus-Induced Murine Immunodeficiency

ABSTRACT LP-BM5 retrovirus-infected C57BL/6 mice develop splenomegaly, lymphadenopathy, hypergammaglobulinemia, and immunodeficiency; thus, this disease has been named mouse AIDS. In this syndrome, CD154/CD40 interactions are required for but do not mediate disease by upregulation of CD80 or CD86. We report here that there is nonetheless a necessity for CD40 signaling competence, specifically an intact tumor necrosis factor receptor-associated factor 6 (TRAF 6) binding site.
A stochastic version of Artstein's theorem

The purpose of this paper is to extend to the stochastic context the well-known theorem of Artstein. The aim of the paper is to design an explicit and in a sense "universal" formula for a stabilizing state feedback law for nonlinear stochastic differential systems the drift and diffusion terms of which being affine in the control.
RFID System Information Security Based on Chaotic Encryption

Based on the characteristics of the pseudo-random, unpredictability of chaotic sequences and extreme sensitivity to the initial conditions, the paper proposes a new method of using the discrete chaotic sequence which is uniquely corresponding to the tag to encrypt the information on each RFID tag and also sets forth the corresponding controlling mechanism and working process of the new RFID system.
Improving safety through online driver workload assessment

The continuous increasing number of car embedded systems requires to wonder about the compatibility of the use of such systems while the driving. The richness of their interface, their complexity and their numbers need to ensure that their use doesn't exceed the driver capacity. To bring elements of answer to this question, this paper presents a methodology for the development of a real-time workload estimator. This methodology is based on the simultaneous analysis of objective and subjective data by the mean of an exploratory multivariate approach. Objective data are composed of driving performance indicators while subjective data are results from subjective workload assessments. The data were collected during an experimentation set on a driving situation which was designed to induce several levels of task demand.
A Fast Fault Location Algorithm Based on Pre-computed for Optical Burst Switching Network

Aiming at the disadvantages of existing location algorithms, this paper proposed and experienced an effective method of fault location algorithm based on pre-computed for optical burst switching network. In order to minimize the monitoring cost, we introduced monitoring-cycle by which the network is divided into a number of monitoring domain. Each monitoring domain has a monitor, when faults occurred, fault codes are generated. According to the fault codes, we can search the binary tree algorithm to achieve the pre-computed of faults in the OBS network. Examples prove that the algorithm can not only realize single fault location but also multi-fault location.
Mapping on multi/many-core systems: Survey of current and emerging trends

The reliance on multi/many-core systems to satisfy the high performance requirement of complex embedded software applications is increasing. This necessitates the need to realize efficient mapping methodologies for such complex computing platforms. This paper provides an extensive survey and categorization of state-of-the-art mapping methodologies and highlights the emerging trends for multi/many-core systems. The methodologies aim at optimizing system's resource usage, performance, power consumption, temperature distribution and reliability for varying application models. The methodologies perform design-time and run-time optimization for static and dynamic workload scenarios, respectively. These optimizations are necessary to fulfill the end-user demands. Comparison of the methodologies based on their optimization aim has been provided. The trend followed by the methodologies and open research challenges have also been discussed.
Preclinical and Clinical Effects of Mistletoe against Breast Cancer

Breast cancer is among the most frequent types of cancer in women worldwide. Current conventional treatment options are accompanied by side effects. Mistletoe is amongst the important herbal medicines traditionally used as complementary remedies. An increasing number of studies have reported anticancer activity of mistletoe extracts on breast cancer cells and animal models. Some recent evidence suggests that cytotoxic activity of mistletoe may be mediated through different mechanisms. These findings provide a good base for clinical trials. Various studies on mistletoe therapy for breast cancer patients revealed similar findings concerning possible benefits on survival time, health-related quality of life (HRQoL), remission rate, and alleviating adverse reactions to conventional therapy. This review provides an overview of the recent findings on preclinical experiments and clinical trials of mistletoe for its cytotoxic and antitumor activity and its effect on HRQoL in breast cancer patients. Moreover, studies investigating molecular and cellular mechanisms underlying antitumor activity of mistletoe are discussed in this paper. The analyzed trials provided evidence that there might be a combination of pharmacological and motivational aspects mediated by the mistletoe extract application which may contribute to the clinical benefit and positive outcome such as improved HRQoL and self-regulation in breast cancer patients.
Application of centrality measures in the identification of critical genes in diabetes mellitus

The connectivity of a protein and its structure is related to its functional properties. Many experimental approaches have been employed for the identification of Diabetes Mellitus (DM) associated candidate genes. Therefore, it is of interest to use var ious graph centrality measures integrated with the genes associated with the human Diabetes Mellitus network for the identification of potential targets. We used 2728 genes known to cause Diabetes Mellitus from Jensenlab (Novo Nordisk Foundation Center for Protein Research, Denmark) for this analysis. A protein-protein interaction network was further constructed using a tool Centralities in Biological Networks (CentiBiN) with 1020 nodes after eliminating the duplicates, parallel edges, self -loop edges and unknown Human Protein Reference Database (HPRD) IDS. We used fourteen centralities measures which are useful in identifying the structural characteristic of individuals in the network. The results of the centrality measures are highly correlated. Thus, we identified genes that are critically associated with DM. We further report the top ten genes of all fourteen centrality measures for further consideration as targets for DM.
TO CONGRESS VOLUME III : FATE AND TRANSPORT OF MERCURY IN THE ENVIRONMENT December

This chapter summarizes the results of the atmospheric fate and transport modeling of mercury using the long-range and local models. The general mass balance of elemental mercury gas, divalent mercury gas, and particle-bound mercury from the RELMAP simulation results using the assumed emission speciation profiles are shown in Table 5-1. The mass-balance accounting for the simulation using the meteorological data from the year 1989 shows a total of 141.8 metric tons of mercury emitted to the atmosphere from anthropogenic sources. This simulated emission total differs slightly from the national totals indicated in Volume II since the states of Alaska and Hawaii are not within the model domain. The RELMAP simulation indicates that 47.6 metric tons of anthropogenic mercury emissions are deposited within the model domain and 0.4 metric tons remain in the air within the model domain at the end of the simulation. The remainder, about 93.8 metric tons, is transported outside the model domain and probably diffuses into the global atmospheric reservoir. The simulation also shows 32.0 metric tons of mercury is deposited within the model domain from the global atmospheric reservoir, suggesting that about three times as much mercury is being added to the global reservoir as is being deposited from it. The total amount of mercury deposited in the model domain annually from U.S. anthropogenic emissions and from the global background concentration is estimated to be 79.6 metric tons, or slightly more than one-half of the mass of all atmospheric emissions from anthropogenic sources in the lower 48 United States.
A combined hardware and software architecture for secure computing

Remote code execution becomes more and more important as can be seen by Grid computing or distributed computing projects like SETI@home. However, executing programs on foreign computers leads to security risks if the program contains sensitive data or algorithms. Current operating systems can protect user programs from other malicious programs running on the same host. But this does not prevent attacks from a system administrator or a malicious operating system. Further, even if the operating system is trusted it is possible to physically intercept communication between main memory and processor to gather information about the executed programs. As a result, these security risks prevent the execution of sensitive algorithms or programs computing on sensitive data on not trustworthy remote systemsIn this paper we present a combined hardware and software architecture to provide a secure and tamper resistant computing environment without relying on trusted system administrators and a fully trusted operating system. Our proposed architecture provides a security enhancement implemented on top of a standard processor. Compared to external co-processor solutions, our architecture does not suffer from memory, functionality and performance limitations. Furthermore, normal and protected programs can be run concurrently in a multitasking environment
A practical comparison between Zhang's and Tsai's calibration approaches

With the rise of affordable processing power and off-the-shelf apparatus supporting 3D imaging, there is a growing need for reliable and fast calibration tools, enabling timely accurate data gathering. When confronted with a choice of camera calibration tools, Zhang's and Tsai's are not only the most cited, but also the most widely available solutions. Zhang's calibration is often chosen by default, based on the assumption that it is more accurate. However, it typically involves extensive manual data gathering when compared to the Tsai approach. Here, we demonstrate that there is no significant accuracy gain between Tsai's or Zhang's approach in terms of stereo matching, given the variety of readily available 3D devices tested. Further to this, the trade-off between measurement accuracy compared to setup and data acquisition time is decisively in favour of Tsai. This paper also covers a new algorithm for the extraction of points from images of checkboards attached to calibration objects.