Miracle-dz/UniFAR-FTUs huggingface dataset:
Layout techniques for radiation hardening of standard CMOS active pixel sensors

This article presents a radiation hardened active pixel sensor implemented in a standard 0.35 μm CMOS process. The integrated circuit is composed of a 64 × 64 pixel matrix with a 25 μm pixel pitch and has four different pixel architectures. There are also test structures to permit the characterization of the MOS transistors. The radiation hardening of the circuit is implemented with two layout techniques: enclosed geometry transistors and guard rings. It is shown that, with these techniques, the sensor is able to operate with total ionization doses that surpass 500 krad, which is more than double of the requirement for our application. Also, the techniques do not compromise the optical response of the pixels. To obtain an electrical model of the designed transistors, an EKV MOSFET Model was extracted.
Stereo Matching for Unconstrained Face Recognition Ph.D. Proposal

Unconstrained face recognition is a problem of fundamental importance in computer vision. We propose to address this problem by using stereo matching to judge the similarity of two, 2D images of faces. Stereo matching allows for arbitrary, physically valid, continuous correspondences. We show that the stereo matching cost provides a very robust measure of similarity of faces that is insensitive to a wide range of variations. To enable this, we show that for conditions common in face recognition, the epipolar geometry of face images can be computed using either four or three feature points. We also provide a straightforward adaptation of a stereo matching algorithm to compute the similarity between faces. The proposed approach has been tested on the CMU PIE dataset and demonstrates superior performance compared to existing methods in the presence of pose variation. We have also studied the problem of face recognition with weight variation. Using this dataset, we empirically study how weight gain and loss affects face recognition performance. We present baseline experiments using a wide variety of existing methods. These show that weight change can significantly degrade the performance of recognition algorithms. Our results also show that correspondence-based methods exhibit the most robust performance as the weight difference increases. The research plans include: building a stereo method for matching in the presence of deformation and illumination change and learning from pose invariant descriptors built using cost and correspondence information.
Harmony potentials for joint classification and segmentation

Hierarchical conditional random fields have been successfully applied to object segmentation. One reason is their ability to incorporate contextual information at different scales. However, these models do not allow multiple labels to be assigned to a single node. At higher scales in the image, this yields an oversimplified model, since multiple classes can be reasonable expected to appear within one region. This simplified model especially limits the impact that observations at larger scales may have on the CRF model. Neglecting the information at larger scales is undesirable since class-label estimates based on these scales are more reliable than at smaller, noisier scales. To address this problem, we propose a new potential, called harmony potential, which can encode any possible combination of class labels. We propose an effective sampling strategy that renders tractable the underlying optimization problem. Results show that our approach obtains state-of-the-art results on two challenging datasets: Pascal VOC 2009 and MSRC-21.
Feature-Based Language Discrimination in Radio Productions via Artificial Neural Training

The current paper focuses on the discrimination of audio content, deriving from radio productions, based on the spoken language. During the implementation several audio features were extracted and subsequently evaluated, containing the spectral, timbre and tempo properties of the implicated voice signals. In this process, the differentiated patterns that appear in radio productions, such as speech signals, phone conversations and music interferences had to be initially detected and classified, leading in the employment of a prequel generic classification scheme. The hierarchical structure of discrimination integrated parametric segmentation with various window lengths, in order to detect the most efficient ones. The conducted experiments were supported by machine learning approaches, and more specifically by artificial neural networks topologies, which demonstrate increased discrimination potentials, when they are implicated in audio semantic analysis problems. The achieved overall and partial classification performances were high, revealing the saliency of the selected parameters and the efficiency of the whole implemented methodology.
Measuring Employee Engagement of South African Managers

Abstract This paper reports the level of employee engagement exhibited by managers in South Africa. The model employed to measure employee engagement was validated as a measuring tool, and consequently the selection thereof as a measurement tool. The paper provides a brief rationale of the validation process, where after it continues to provide the demographic profile of the respondents and the level of employee engagement as measured by the model. The model employs seven employee measurement criteria, namely management and leadership, behavioral engagement, change management and stress-free environment, career growth opportunities, emotional engagement, nature of the job and feeling valued/involved. 260 employee responses were collected by means of a structured questionnaire from a stratified sample of 300. Although all the factors showed high levels of importance towards employee engagement, behavioral engagement was deemed to be the most important factor. Furthermore, correlational analysis indicated that none of the demographic variables significantly influence the employee engagement factors, suggesting that stratified managerial interventions are not required to improve employee engagement.
Bound states and scattering in quantum waveguides coupled laterally through a boundary window

We consider a pair of parallel straight quantum waveguides coupled laterally through a window of a width l in the common boundary. We show that such a system has at least one bound state for any l≳0. We find the corresponding eigenvalues and eigenfunctions numerically using the mode‐matching method, and discuss their behavior in several situations. We also discuss the scattering problem in this setup, in particular, the turbulent behavior of the probability flow associated with resonances. The level and phase‐shift spacing statistics shows that in distinction to closed pseudo‐integrable billiards, the present system is essentially nonchaotic. Finally, we illustrate time evolution of wave packets in the present model.
Term Structure Models and Differences in Beliefs

This paper studies the empirical implications of models with heterogeneous beliefs for the term structure of interest rates. When agents use different models to forecast the economy, they naturally engage in speculative trading, which in turn generates endogenously time-varying prices of risk. Endogeneous risk has tight implications for equilibrium yield curves which we investigate empirically. We study a set of testable restrictions that help distinguish across myopic, speculative, and risk sharing models. Our results show that speculative models help to explain, at the same time, low short term interest rates, bond return predictability, yield curve forecasting factors, realised volatility, and compensation for Treasury volatility risk. JEL classification: D9, E3, E4, G12
Overview of the 2013 ALTA Shared Task

The 2013 ALTA shared task was the fourth in the ALTA series of shared tasks, where all participants attempt to solve the same problem using the same data. This year’s shared task was based on the problem of restoring casing and punctuation. As with last year, we used Kaggle in Class as the framework to submit the results and maintaining a leaderboard. There was a strong participation this year, with 50 teams participating, of which 21 teams submitted results that improved on the published baseline. In this overview we describe the task, the process of building the training set, and the evaluation criteria, and present the results of the submitted systems. We also comment on our experience with using Kaggle in Class.
Evaluating the User Interface of a Ubiquitous Computing system Doorman

Ubiquitous computing systems cannot necessarily be tested in laboratories. Therefore, in many cases the testing of the interfaces has to be done in the actual scene of the action with real life problems. To gather reliable information about human-computer communication it is important to observe the human behaviour in a situation in which they believe to be interacting with a real computer system. [3].
Molecular Characterization of Mutations That Cause Globoid Cell Leukodystrophy and Pharmacological Rescue Using Small Molecule Chemical Chaperones

Globoid cell leukodystrophy (GLD) (Krabbe disease) is an autosomal recessive, degenerative, lysosomal storage disease caused by a severe loss of galactocerebrosidase (GALC) enzymatic activity. Of the >70 disease-causing mutations in the GALC gene, most are located outside of the catalytic domain of the enzyme. To determine how GALC mutations impair enzymatic activity, we investigated the impact of multiple disease-causing mutations on GALC processing, localization, and enzymatic activity. Studies in mammalian cells revealed dramatic decreases in GALC activity and a lack of appropriate protein processing into an N-terminal GALC fragment for each of the mutants examined. Consistent with this, we observed significantly less GALC localized to the lysosome and impairment in either the secretion or reuptake of mutant GALC. Notably, the D528N mutation was found to induce hyperglycosylation and protein misfolding. Reversal of these conditions resulted in an increase in proper processing and GALC activity, suggesting that glycosylation may play a critical role in the disease process in patients with this mutation. Recent studies have shown that enzyme inhibitors can sometimes “chaperone” misfolded polypeptides to their appropriate target organelle, bypassing the normal cellular quality control machinery and resulting in enhanced activity. To determine whether this may also work for GLD, we examined the effect of α-lobeline, an inhibitor of GALC, on D528N mutant cells. After treatment, GALC activity was significantly increased. This study suggests that mutations in GALC can cause GLD by impairing protein processing and/or folding and that pharmacological chaperones may be potential therapeutic agents for patients carrying certain mutations.
A trial of an iPadTM intervention targeting social communication skills in children with autism

This study evaluated a technology-based early intervention for social communication skills in pre-schoolers in a randomised controlled trial. Participants were 54 children aged under 6 years with a diagnosis of autism, assigned to either intervention or control conditions. The app engaged children, who played consistently, regardless of developmental level, and was rated highly by parents. There were no significant group differences in parent-report measures postintervention, nor in a measure of parent–child play at follow-up. Therefore, this intervention did not have an observable impact on real-world social communication skills and caution is recommended about the potential usefulness of iPadTM apps for amelioration of difficulties in interaction. However, positive attitudes among participants, lack of harms and the potential of apps to deliver therapeutic content at low economic cost suggest this approach is worth pursuing further, perhaps targeting other skill domains.
Optimal subchannel assignment in a two-hop OFDM relay

The paper studies subchannel assignment in a two-hop OFDM relay system in which the transmitting nodes (source and relay) have access to channel information and interference-related information. We show that with L-superadditive relay (performance) functions a simple ranking of subchannels leads to the optimal assignment with a very low computational complexity. Numerical results quantify the benefit of subchannel assignment in a frequency-selective channel.
Detecting Corporate Fraud: An Application of Machine Learning

This paper explores the application of several machine learning algorithms to published corporate data in an effort to identify patterns indicative of securities fraud. Generally Accepted Accounting Principles (GAAP) represent a conglomerate of industry reporting standards which US public companies must abide by to aid in ensuring the integrity of these companies. Notwithstanding these principles, US public companies have legal flexibility to maneuver the way they disclose certain items in the financial statements making it extremely hard to detect fraud manually. Here we test several popular methods in machine learning (logistic regression, naive Bayes and support vector machines) on a large set of financial data and evaluate their accuracy in identifying fraud. We find that some variants of SVM and logistic regression are significantly better than the currently available methods in industry. Our results are encouraging and call for a more thorough investigation into the applicability of machine learning techniques in corporate fraud detection.
Klebanov-Witten Theory with Massive Dynamical Flavors

We consider the addition of a large number of massive dynamical flavors to the Klebanov-Witten theory, the quiver gauge theory describing the low energy dynamics of Nc D3-branes at the conifold singularity. Massive flavors are introduced by means of Nf D7-branes which are holomorphically embedded and smeared along the transverse directions. After some general comments on the validity of the smearing procedure, we find the full backreacted supergravity solution corresponding to a particular class of massive embeddings. The solution depends on a running effective number of flavors, whose functional form follows from the smeared embedding. The running reflects the integrating in/out of massive degrees of freedom in the dual field theory as the energy scale is changed. We study how the dynamics of the theory depends on the flavor parameters, mainly focusing on the static quark-antiquark potential. As expected, we find that the dynamical flavors tend to screen the static color charges.
Printed Copies: Model-checking for L 2 Model-checking for L 2

Electronic copies of technical reports are available: Via FTP: URL ftp://ftp.informatik. uni-trier.de/pub/Users-Root/reports Via WWW: URL http://www.informatik. uni-trier.de/Reports/Current.html Via email: Send a mail to ftpmail@ftp.informatik. uni-trier.de, subject ’HELP’, for detailed instructions Printed copies: Trierer Forschungsberichte Fachbereich IV Mathematik / Informatik Universitat Trier .
Using Magnetic Levitation for Non‐Destructive Quality Control of Plastic Parts

Magnetic levitation (MagLev) enables rapid and non-destructive quality control of plastic parts. The feasibility of MagLev as a method to: i) rapidly assess injection-molded plastic parts for defects during process optimization, ii) monitor the degradation of plastics after exposure to harsh environmental conditions, and iii) detect counterfeit polymers by density is demonstrated.
Tissue MicroRNAs as Predictors of Outcome in Patients with Metastatic Colorectal Cancer Treated with First Line Capecitabine and Oxaliplatin with or without Bevacizumab

Purpose We tested the hypothesis that expression of microRNAs (miRNAs) in cancer tissue can predict effectiveness of bevacizumab added to capecitabine and oxaliplatin (CAPEOX) in patients with metastatic colorectal cancer (mCRC). Experimental Design Patients with mCRC treated with first line CAPEOX and bevacizumab (CAPEOXBEV): screening (n = 212) and validation (n = 121) cohorts, or CAPEOX alone: control cohort (n = 127), were identified retrospectively and archival primary tumor samples were collected. Expression of 754 miRNAs was analyzed in the screening cohort using polymerase chain reaction (PCR) arrays and expression levels were related to time to disease progression (TTP) and overall survival (OS). Significant miRNAs from the screening study were analyzed in all three cohorts using custom PCR arrays. In situ hybridization (ISH) was done for selected miRNAs. Results In the screening study, 26 miRNAs were significantly correlated with outcome in multivariate analyses. Twenty-two miRNAs were selected for further study. Higher miR-664-3p expression and lower miR-455-5p expression were predictive of improved outcome in the CAPEOXBEV cohorts and showed a significant interaction with bevacizumab effectiveness. The effects were strongest for OS. Both miRNAs showed high expression in stromal cells. Higher expression of miR-196b-5p and miR-592 predicted improved outcome regardless of bevacizumab treatment, with similar effect estimates in all three cohorts. Conclusions We have identified potentially predictive miRNAs for bevacizumab effectiveness and additional miRNAs that could be related to chemotherapy effectiveness or prognosis in patients with mCRC. Our findings need further validation in large cohorts, preferably from completed randomized trials.
A Novel Method for Fabrication of Free Standing Subwavelength Gratings in Gaas/Algaas

We demonstrate a method for the fabrication of suspended gratings in GaAs/AlGaAs. These gratings are designed to act as high reflectivity mirrors in vertical cavity lasers. The fabrication process used is simple, and with a high yield. Stiction or fracture due to surface tension as well as stiction of grating fingers to one another is circumvented. In particular, we found that in fabrication of freestanding GaAs gratings on a submicron scale, wet processes performed after the definition of the gratings greatly reduces the yield. Contrary to the normal fabrication sequence, the wet sacrificial etch is performed prior to defining the gratings. The process is also useful in producing other high aspect ratio structures
Effects of a Short Physical Exercise Intervention on Patients with Multiple Sclerosis (MS)

Background: The aim of this prospective randomized controlled trial was to investigate if a short-term endurance or combined endurance/resistance exercise program was sufficient to improve aerobic capacity and maximum force in adult patients (18–65 years) with multiple sclerosis (MS). Methods: All patients performed a three-month exercise program consisting of two training sessions per week, lasting 40 min each, with moderate intensity. All patients had a maximum value of 6 (low to moderate disability) on the Expanded Disability Status Scale (EDSS). One group (combined workout group (CWG); 15 females, 4 males) completed a combined endurance/resistance workout (20 min on a bicycle ergometer, followed by 20 min of resistance training), while the other group (endurance workout group (EWG); 13 females, 5 males) completed a 40 min endurance training program. Aerobic capacity was assessed as peak oxygen uptake, ventilatory anaerobic threshold, and workload expressed as Watts. Maximum force of knee and shoulder extensors and flexors was measured using isokinetic testing. Quality of life was assessed with the SF-36 questionnaire, and fatigue was measured using the Modified Fatigue Impact Scale. Results: Both training groups increased in aerobic capacity and maximum force. EWG, as well as CWG, showed improvement in several subscales of the SF-36 questionnaire and decrease of their fatigue. Conclusion: A short exercise intervention increased both aerobic capacity and maximum force independent of whether endurance or combined endurance/resistance workouts were performed.
Empirical Analysis of Collective Stability

When learning structured predictors, collective stability is an important factor for generalization. London et al. (2013) provide the first analysis of this effect, proving that collectively stable hypotheses produce less deviation between empirical risk and true risk, i.e., defect. We test this effect empirically using a collectively stable variant of maxmargin Markov networks. Our experiments on webpage classification validate that increasing the collective stability reduces the defect and can thus lead to lower overall test error.
Very Low Cefotaxime Concentrations Select for Hypermutable Streptococcus pneumoniae Populations

ABSTRACT A mixed culture of an hypermutable hexA Streptococcus pneumoniae mutant strain and its hexA+ isogenic ancestor was challenged with low cefotaxime concentrations. Despite identical original cefotaxime MICs, the hexA mutant population was significantly selected at very low concentrations, and all of the tested selected variants harbored the Thr550→Ala mutation in pbp2x. Since cefotaxime selects hypermutators, the risk of secondary acquisition of antibiotic resistance is increased; as expected, the cefotaxime-resistant mutants had a mutation frequency 10 times higher in response to to ciprofloxacin. The present study presents a model (not necessarily reflecting the clinical setting) illustrating the risk of selection of mutators in the evolution of multiple resistance.
A comparison of the L2 motivational self system between Chinese EFL and ESL learners

Abstract This present study attempts to conduct a comparison of the tripartite model of L2 Motivational Self System in two different learning contexts, Chinese EFL and ESL learning settings. It was designed using a mixed methods approach, with a primary questionnaire instrument being supported by secondary interview data. The quantitative data was submitted to Amos version 18.0 to evaluate proposed models. It was found that L2 learning experience was the most important predictive dimension of intended learning effort for both samples. However, the roles of the other two components, the ideal L2 self and the ought-to L2 self, appeared to be unstable, which concludes that Dörnyei’s tripartite model obtained partial support in both EFL and ESL contexts. The analysis of qualitative data offers strong evidence for the claim that the future self-guides do not necessarily result in intended effort unless some essential conditions are met.
Sufficient conditions for stability of longest-queue-first scheduling: second-order properties using fluid limits

We consider the stability of the longest-queue-first scheduling policy (LQF), a natural and low-complexity scheduling policy, for a generalized switch model. Unlike that of common scheduling policies, the stability of LQF depends on the variance of the arrival processes in addition to their average intensities. We identify new sufficient conditions for LQF to be throughput optimal for independent, identically distributed arrival processes. Deterministic fluid analogs, proved to be powerful in the analysis of stability in queueing networks, do not adequately characterize the stability of LQF. We combine properties of diffusion-scaled sample path functionals and local fluid limits into a sharper characterization of stability.