Miracle-dz/UniFAR-FTUs huggingface dataset:
On Slot Allocation for Time-Constrained Messages in Dual-Bus Networks

Several access schemes have been suggested for dual-bus network topology, e.g., DQDB, Fasnet, CRMA, and Simple. It is therefore important to provide various services in this type of networks. This paper addresses the issue of guaranteeing the timely delivery of isochronous (real-time) messages with hard deadlines in slotted dual-bus networks. We propose a slot allocation scheme which can allocate bandwidth for a set of isochronous message streams and provide deterministic deadline guarantees. The proposed slot allocation scheme is guaranteed to find a feasible slot allocation in the sense that all messages can be transmitted in a timely manner as long as the total message density is less than or equal to a certain threshold, where the total message density is defined as the summation of the ratio of maximum message size to message deadline over all streams. We also discuss the implementation details of this scheme, and compare our scheme with another bandwidth allocation scheme proposed by D. Saha et al. (1994).
Artificial Bee Colony Algorithm Integrated with fuzzy C-mean operator for Data Clustering

Clustering task aims at the unsupervised classifica tion of patterns in different groups. To enhance th e quality of results, the emerging swarm-based algorithms now-a-days become an alternative to the conventional clustering methods. In this study, an optimization method based on the swarm intelligence algorithm is proposed for the purpose of clustering. The signifi cance of the proposed algorithm is that it uses a F uzzy CMeans (FCM) operator in the Artificial Bee Colony ( ABC) algorithm. The area of action of the FCM operator comes at the scout bee phase of the ABC algorithm as the scout bees are introduced by the FCM operator . The experimental results have shown that the proposed a pproach has provided significant results in terms o f the quality of solution. The comparative study of the p roposed approach with existing algorithms in the li terature using the datasets from UCI Machine learning repository is satisfactory.
Capillary waveguide improvements for laser plasma accelerators

Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration.
Quantification of Hepatic UDP Glucuronosyltransferase 1A Splice Variant Expression and Correlation of UDP Glucuronosyltransferase 1A1 Variant Expression with Glucuronidation Activity

The UDP glucuronosyltransferase (UGT) 1A gene cluster encodes nine UGT1A family members via splicing of individual first exons to common exons 2 through 5. Each of these nine UGT1As can also undergo alternative splicing at their 3′ ends by using an alternate exon 5, resulting in 27 different UGT1A mRNA species with each UGT1A gene encoding three different combinations of 5A and 5B UGT1A exons. To examine the importance of UGT1A exon 5 splice variants on overall UGT1A activity, a nested quantitative polymerase chain reaction assay was developed to accurately assess the combined expression of exon 5 splice variants (termed v2/v3) versus the expression of wild-type (termed v1) for each specific UGT1A. v1 expression was 16-, 17-, 57- and 29-fold higher than that observed for the levels of v2/v3 for UGTs 1A1, 1A4, 1A6, and 1A9, respectively, in normal human liver specimens. In a series of 58 normal human liver specimens, the expression of both UGT1A1 v1 and v2/v3 mRNAs was positively correlated with raloxifene glucuronidation activity in corresponding microsomes prepared from the same specimens (p < 0.0001, r2 = 0.720; p = 0.0002, r2 = 0.241, respectively), with expression of both variants lower in individuals homozygous for the UGT1A1*28 allele (42% for v1, p = 0.041; 53% for v2/v3, p = 0.0075). The expression of UGT1A1 v2/v3 was 1.6-fold higher than v1 (p = 0.03) in HepG2 cells, and short interfering RNA knockdown of HepG2 v2/v3 increased raloxifene glucuronidation activity by 83%. Together, these data suggest that hepatic UGT1A v2/v3 mRNA species are minor form variants in human livers from most individuals.
Minimal adaptive routing with limited injection on Toroidal k-ary n-cubes

Virtual channels can be used to implement deadlock free adaptive routing algorithms and increase network throughput. Unfortunately, they introduce asymmetries in the use of buffers of symmetric networks as the toroidal k-ary n-cubes. In this paper we present a minimal adaptive routing algorithm that tries to balance the use of the virtual channels by limiting the injection of new packets into the network. The experimental results, conducted on a 256 nodes torus, show that it is possible to increase the saturation point and to keep the network throughput stable at high traffic rates. The comparison with the Chaos router, a non minimal cut-through adaptive routing, shows that our algorithm obtains similar performance results using only a small fraction of buffers and a simpler router model.
Pathogen Removal Using Saturated Sand Columns Supplemented with Hydrochar

Sufficient provision of clean drinking water is an essential need for sustaining human-well being. The majority of people suffering from lack of clean water reside in less developed communities, where the financial and technical barriers hamper the implementation of modern water-sanitation systems. The goal of this study is to evaluate hydrochar derived from selected organic wastes as a low cost adsorbent for pathogen removal in water treatment. Pathogen removal efficiency was measured by carrying out breakthrough analysis using a simple 10 cm sand filtration set-up supplemented with hydrochar (1.5 % w/w). Two home-made two-step reverse transcription-quantitative polymerase chain reaction assays were developed using either RevertAid or MMLV reverse transcriptase. Both assays showed competitive efficiency to a selected commercial one-step master kit on analyzing environmental and laboratory samples. The costs of home-made assays were 11 times less than the commercial kit. Successive virus removal experiments were carried out using the home-made assay based on the RevertAid reverse transcriptase. We evaluated the Escherichia coli (E. coli) removal efficiency of hydrochars derived from agricultural residue of maize and stabilized sewage sludge from wastewater treatment plant. Though raw hydrochars showed relatively limited E. coli removal efficiency of ~70 % for maize-hydrochar and ~20 % for sewage sludge-hydrochar, a simple cold-alkali activation of hydrochars using 1M KOH solution enhanced E. coli removal efficiency of both hydrochars (~90 %). Apparently, KOH activation of raw hydrochar removed alkali-soluble and tar-like substances from hydrochar surface, exposing more hydrophobic core and developing more porous surface structure. Also, removal of pathogenic rotavirus and adenovirus were investigated using hydrochar produced from sewage sludge and swine waste. Raw hydrochars (without activation) successfully removed both viruses at efficiencies higher than 99 %. Successive material characterization results suggested that the supplements of the hydrochar adsorbents provided a larger contact surface area with strong hydrophobicity in the sand media, facilitating adsorptive removal of pathogenic microorganisms. This PhD study suggests the potential of hydrothermal carbonization as a technical solution for water-sanitation issues. Through hydrothermal carbonization, hazardous solid wastes containing pathogenic microorganisms will be totally sanitized, and the resulting hydrochars can be used as a pathogen barrier in water and / or wastewater treatment systems.
Gate Voltage Influence on the Channel Hot-Carrier Degradation of High-$k$ -Based Devices

In ultrascaled complimentary metal-oxide-semiconductor technologies, the lucky-electron model does not describe correctly Channel Hot-Carrier (CHC) degradation for typical transistor test conditions independently of the gate dielectric (SiO2 or high- k). A new model to describe the CHC degradation behavior in n-channel metal-oxide field-effect transistors, based on the dominant role of the gate voltage into the total CHC stress, is presented. This new model can be applicable to long- and short-channel transistors with high- k or SiO2 as a dielectric.
Detecting Low Rapport During Natural Interactions in Small Groups from Non-Verbal Behaviour

Rapport, the close and harmonious relationship in which interaction partners are "in sync" with each other, was shown to result in smoother social interactions, improved collaboration, and improved interpersonal outcomes. In this work, we are first to investigate automatic prediction of low rapport during natural interactions within small groups. This task is challenging given that rapport only manifests in subtle non-verbal signals that are, in addition, subject to influences of group dynamics as well as inter-personal idiosyncrasies. We record videos of unscripted discussions of three to four people using a multi-view camera system and microphones. We analyse a rich set of non-verbal signals for rapport detection, namely facial expressions, hand motion, gaze, speaker turns, and speech prosody. Using facial features, we can detect low rapport with an average precision of 0.7 (chance level at 0.25), while incorporating prior knowledge of participants' personalities can even achieve early prediction without a drop in performance. We further provide a detailed analysis of different feature sets and the amount of information contained in different temporal segments of the interactions.
A Technique for High-Performance Data Compression

Data stored on disks and tapes or transferred over communications links in commercial computer systems generally contains significant redundancy. A mechanism or procedure which recodes the data to lessen the redundancy could possibly double or triple the effective data densitites in stored or communicated data. Moreover, if compression is automatic, it can also aid in the rise of software development costs. A transparent compression mechanism could permit the use of "sloppy" data structures, in that empty space or sparse encoding of data would not greatly expand the use of storage space or transfer time; however , that requires a good compression procedure. Several problems encountered when common compression methods are integrated into computer systems have prevented the widespread use of automatic data compression. For example (1) poor runtime execution speeds interfere in the attainment of very high data rates; (2) most compression techniques are not flexible enough to process different types of redundancy; (3) blocks of compressed data that have unpredictable lengths present storage space management problems. Each compression ' This article was written while Welch was employed at Sperry Research Center; he is now employed with Digital Equipment Corporation. 8 m, 2 /R4/OflAb l strategy poses a different set of these problems and, consequently , the use of each strategy is restricted to applications where its inherent weaknesses present no critical problems. This article introduces a new compression algorithm that is based on principles not found in existing commercial methods. This algorithm avoids many of the problems associated with older methods in that it dynamically adapts to the redundancy characteristics of the data being compressed. An investigation into possible application of this algorithm yields insight into the compressibility of various types of data and serves to illustrate system problems inherent in using any compression scheme. For readers interested in simple but subtle procedures, some details of this algorithm and its implementations are also described. The focus throughout this article will be on transparent compression in which the computer programmer is not aware of the existence of compression except in system performance. This form of compression is "noiseless," the decompressed data is an exact replica of the input data, and the compression apparatus is given no special program information, such as data type or usage statistics. Transparency is perceived to be important because putting an extra burden on the application programmer would cause
Drivers and barriers to the adoption of the digital television in portugal: the perspectives of the tv viewers and other main stakeholders

The main goal of the ADOPT-DTV project is to understand what are the most significant factors for the adoption of digital TV by the Portuguese population in the switchover context. On the 26th of April 2012, the analogue terrestrial television switchoff is planned to occur in Portugal, according to the schedule published by the national telecommunication regulator Anacom. Digital terrestrial TV was launched in the country in April 2009, turning Portugal into one of the countries with the most ambitious schedule - or risky, depending on the perspective - for the full transition from analogue to digital terrestrial television. We will start by presenting the objectives, theoretical framework and research design of the ADOPT-DTV project. Next, we will present the first results of the project focused on the barriers and drivers for the adoption of digital TV from two of the empirical studies which integrate it, namely, the quantitative inquiry applied to a representative sample of the Portuguese population and interviews with the main stakeholders in the digital TV area in Portugal. The perspectives of the television viewers are compared with other main stakeholders in this process. A brief discussion of these results and a brief enumeration of the next steps for the project will conclude this paper.
Semi-Supervised Technical Term Tagging With Minimal User Feedback

In this paper, we address the problem of extracting technical terms automatically from an unannotated corpus. We introduce a technology term tagger that is based on Liblinear Support Vector Machines and employs linguistic features including Part of Speech tags and Dependency Structures, in addition to user feedback to perform the task of identification of technology related terms. Our experiments show the applicability of our approach as witnessed by acceptable results on precision and recall.
Map-based estimation of the parameters of a Gaussian Mixture Model in the presence of noisy observations

In this contribution we derive the Maximum A-Posteriori (MAP) estimates of the parameters of a Gaussian Mixture Model (GMM) in the presence of noisy observations. We assume the distortion to be white Gaussian noise of known mean and variance. An approximate conjugate prior of the GMM parameters is derived allowing for a computationally efficient implementation in a sequential estimation framework. Simulations on artificially generated data demonstrate the superiority of the proposed method compared to the Maximum Likelihood technique and to the ordinary MAP approach, whose estimates are corrected by the known statistics of the distortion in a straightforward manner.
Improvement of Earthquake Prediction by using Global Signal Elimination from Environmental Electromagnetic Signals

Anomalous environmental electromagnetic (EM) radiation waves have been reported as the portents of earthquakes. We have been measuring the Extremely Low Frequency (ELF) range all over Japan. Our goal is to predict earthquakes using EM radiation waves. Previously, we proposed a method of detecting anomalous signals by focusing on linear prediction errors. However, this method also sensitively responds to earthquake-unrelated anomaly. For accurate earthquake-prediction, we should eliminate earthquake-unrelated signals. In this paper, we try to reduce false detection rate by global signal elimination using Non-negative Matrix Factorization (NMF) and evaluate the effectiveness of this method.
Modeling induction machines for EMC-Analysis

EMC-analysis of power electronic systems is strongly supported by network simulations. Simulations at the system level provide not only the prediction of EMI but also deep insight into the EMC relevant effects. To model the system properly, it is necessary to model source and target of EMI and also all parts of the coupling paths. EMI-filters can be designed efficiently using network based modeling approaches. In this paper a model for induction machines' EMC behaviour simulation is parameterized in the frequency range from some kHz up to 100 MHz. The high-frequency characteristics of induction machines with power ratings from 370 W up to 45 kW are compared and a model library is set up for both, frequency and time domain.
Elevated PLA2G7 Gene Promoter Methylation as a Gender-Specific Marker of Aging Increases the Risk of Coronary Heart Disease in Females

PLA2G7 gene product is a secreted enzyme whose activity is associated with coronary heart disease (CHD). The goal of our study is to investigate the contribution of PLA2G7 promoter DNA methylation to the risk of CHD. Using the bisulphite pyrosequencing technology, PLA2G7 methylation was measured among 36 CHD cases and 36 well-matched controls. Our results indicated that there was a significant association between PLA2G7 methylation and CHD (adjusted P = 0.025). Significant gender-specific correlation was observed between age and PLA2G7 methylation (males: adjusted r = −0.365, adjusted P = 0.037; females: adjusted r = 0.373, adjusted P = 0.035). A breakdown analysis by gender showed that PLA2G7 methylation was significantly associated with CHD in females (adjusted P = 0.003) but not in males. A further two-way ANOVA analysis showed there was a significant interaction between gender and status of CHD for PLA2G7 methylation (gender*CHD: P = 6.04E−7). Moreover, PLA2G7 methylation is associated with the levels of total cholesterols (TC, r = 0.462, P = 0.009), triglyceride (TG, r = 0.414, P = 0.02) and Apolipoprotein B (ApoB, r = 0.396, P = 0.028) in females but not in males (adjusted P>0.4). Receiver operating characteristic (ROC) curves showed that PLA2G7 methylation could predict the risk of CHD in females (area under curve (AUC) = 0.912, P = 2.40E−5). Our results suggest that PLA2G7 methylation changes with aging in a gender-specific pattern. The correlation between PLA2G7 methylation and CHD risk in females is independent of other parameters including age, smoking, diabetes and hypertension. PLA2G7 methylation might exert its effects on the risk of CHD by regulating the levels of TC, TG, and ApoB in females. The gender disparities in the PLA2G7 methylation may play a role in the molecular mechanisms underlying the pathophysiology of CHD.
A metacognitive contextual intervention to enhance error awareness and functional outcome following traumatic brain injury: A single-case experimental design

Very few empirically validated interventions for improving metacognitive skills (i.e., self-awareness and self-regulation) and functional outcomes have been reported. This single-case experimental study presents JM, a 36-year-old man with a very severe traumatic brain injury (TBI) who demonstrated long-term awareness deficits. Treatment at four years post-injury involved a metacognitive contextual intervention based on a conceptualization of neuro-cognitive, psychological, and socio-environmental factors contributing to his awareness deficits. The 16-week intervention targeted error awareness and self-correction in two real life settings: (a) cooking at home; and (b) volunteer work. Outcome measures included behavioral observation of error behavior and standardized awareness measures. Relative to baseline performance in the cooking setting, JM demonstrated a 44% reduction in error frequency and increased self-correction. Although no spontaneous generalization was evident in the volunteer work setting, specific training in this environment led to a 39% decrease in errors. JM later gained paid employment and received brief metacognitive training in his work environment. JM's global self-knowledge of deficits assessed by self-report was unchanged after the program. Overall, the study provides preliminary support for a metacognitive contextual approach to improve error awareness and functional outcome in real life settings. (JINS, 2006, 12, 54–63.)
Configuration knowledge representations for Semantic Web applications

Today's economy exhibits a growing trend toward highly specialized solution providers cooperatively offering configurable products and services to their customers. This paradigm shift requires the extension of current standalone configuration technology with capabilities of knowledge sharing and distributed problem solving. In this context a standardized configuration knowledge representation language with formal semantics is needed in order to support knowledge interchange between different configuration environments. Languages such as Ontology Inference Layer (OIL) and DARPA Agent Markup Language (DAML+OIL) are based on such formal semantics (description logic) and are very popular for knowledge representation in the Semantic Web. In this paper we analyze the applicability of those languages with respect to configuration knowledge representation and discuss additional demands on expressivity. For joint configuration problem solving it is necessary to agree on a common problem definition. Therefore, we give a description logic based definition of a configuration problem and show its equivalence with existing consistency-based definitions, thus joining the two major streams in knowledge-based configuration (description logics and predicate logic/constraint based configuration).
Dust in Starburst Galaxies

To investigate the nature of starburst dust, we constructed a model of the stars and dust in starburst galaxies and applied it to 30 observed starburst spectral energy distributions (SEDs). The starburst model was constructed by combining two stellar evolutionary synthesis models with a model describing the radiative transfer of stellar photons through dust. The stellar evolutionary synthesis models were used to compute the dust-free SEDs for stellar populations with ages between 1 × 106 and 15 × 109 yr. Using a Monte Carlo radiative transfer model, the effects of dust were computed for average Milky Way (MW) and Small Magellanic Cloud (SMC) dust, two different star/dust geometries, and locally homogeneous or clumpy dust. Using color-color plots, the starburst model was used to interpret the behavior of 30 starbursts with aperture-matched UV and optical SEDs (and IR for 19 of the 30) from previous studies. From the color-color plots, it was evident that the dust in starbursts has an extinction curve lacking a 2175 Å bump, like the SMC curve, and a steep far-UV rise, intermediate between the MW and SMC curves. The star/dust geometry that is able to explain the distribution of the 30 starbursts in various color-color plots has an inner dust-free sphere of stars surrounded by an outer star-free shell of clumpy dust. When combined with other work from the literature on the Orion region and the 30 Dor region of the Large Magellanic Cloud, this work implies a trend in dust properties with star formation intensity.