Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Components to Realize Control of an Electrostatic Actuator

At the University of Tokyo, Higuchi and Yamamoto lab, there is an electrostatic actuator that is capable of moving sheet-like semi-conductive material by electrostatic force. This thesis presents the development of a set of basic components to realize control of the electrostatic actuator. The position of the object that is moved by the actuator is tracked by using a camera and image processing algorithms. Two approaches are presented, one by using OpenCV to track a specific color and one by using ARtoolkit to track a specific marker. The ARtoolkit method is chosen because it is less sensitive to noise and is more stable than the OpenCV method. A PIC micro-controller with an interface on a PC is implemented to allow a computer program to control the electrostatic actuator. Using only the PIC controller and a computer program, the actuator could operate at about 86 mm/s as its maximum speed. The combination of the PIC controller and the position detection program module will allow various motions of the electrostatic motor. Examensarbete MMK 2011:48 MDA 417 Utveckling av komponenter för att realisera reglering av ett elektrostatiskt ställdon
CD69 Limits the Severity of Cardiomyopathy After Autoimmune Myocarditis

Background— Experimental autoimmune myocarditis (EAM), a mouse model of post–infectious cardiomyopathy, reflects mechanisms of inflammatory cardiomyopathy in humans. EAM is characterized by an infiltration of inflammatory cells into the myocardium that can be followed by myocyte fibrosis, edema, and necrosis, leading to ventricular wall dysfunction and heart failure. Different data indicate that CD69 exerts an important immunoregulatory effect in vivo. However, the possible role of CD69 in autoimmune myocarditis has not been studied. Methods and Results— We have explored the role of the leukocyte regulatory molecule CD69 in the inflammation that leads to cardiac dysfunction after myocardial injury in EAM. We have found that after induction of EAM, the draining lymph nodes from CD69-deficient mice developed an exacerbated Th17 inflammatory response, resulting in increases in the numbers of infiltrating leukocytes in the myocardium. In the chronic phase of EAM, transthoracic echocardiography revealed a significantly reduced left ventricular fractional shortening and a decreased ejection fraction in CD69-deficient mice, indicative of an impaired cardiac contractility. This condition was accompanied by a greater extent of myocardial fibrosis, an elevated number of sinus pauses on ECG, and an enhanced ratio of heart weight to body weight in CD69−/− mice. Moreover, both bone marrow transplantation and adoptive transfer of Th17 cells isolated from immunized CD69−/− mice with EAM into naive wild-type recipients reproduced the severity of the disease, demonstrating that CD69 exerts its function within the lymphocyte compartment. Conclusion— Our findings indicate that CD69 negatively regulates heart-specific Th17 responses, cardiac inflammation, and heart failure progression in EAM.
miR-125b-5p functions as a tumor suppressor gene partially by regulating HMGA2 in esophageal squamous cell carcinoma

MicroRNAs (miRNAs) play important roles in the progression of human cancer including esophageal squamous cell carcinoma (ESCC). Although previous reports showed that miR-125b-5p was down-regulated in ESCC, the roles and mechanisms of loss of function of miR-125b-5p in ESCC were still unknown. Using microRNA microarray and GEO datasets, we found and confirmed that miR-125b-5p was down-regulated in ESCC tissues. In-vitro assays showed that ectopic miR-125b-5p expression repressed cell proliferation, migration and invasion, and induced cell senescence. We also found that miR-125b-5p reduced the expressions of cell cycle regulatory genes including CCNA2, CCND1 and CCNE1, and regulated the markers of epithelial to mesenchymal transition (EMT) including E-cadherin, N-cadherin and EMT associated transcription factor Slug, and also decreased the MMPs including MMP2, MMP7 and MMP13. Furthermore, the candidate target gene HMGA2 was negatively regulated by miR-125b-5p both in mRNA and protein levels. Importantly, knockdown of HMGA2 partially phenocopied the effects of miR-125b-5p overexpression on cell cycle regulators and EMT markers. In conclusion, our results suggested that overexpression of miR-125b-5p inhibited cell proliferation, migration and invasion partially by down-regulating HMGA2 in ESCC.
The Impact of Selection Encounters on Applicants: An Experimental Study into Feedback Effects after a Negative Selection Decision

This study investigates the role of feedback in minimizing the psychological impact of a negative selection decision on job applicants. The method and findings of a laboratory experiment into subjects' reactions to rejection, combined with feedback on this decision as well as perceptions of procedural and distributive fairness, are discussed. Subjects participating in the experiment (N=119) were asked to complete two GMA tests and were told they had to belong to the 20% best performers to be invited for a selection interview. Upon completion, all subjects received a rejection message, supposedly based on their performance scores on the two tests. Subjects were randomly assigned to one of two feedback conditions: either a mere rejection message, or a rejection message including performance feedback. Analyses revealed that core self-evaluations and affective well-being of rejected subjects receiving performance feedback significantly decreased compared to that of subjects in the mere rejection message condition. Furthermore, it was found that procedural fairness perceptions interacted with feedback on subjects' core self-evaluations, while distributive fairness perceptions interacted with feedback on affective well-being. These findings raise the question whether performance feedback following a negative selection decision is as advantageous as generally assumed. Implications for giving feedback in rejection situations are discussed in the conclusion.
Analysis and modeling of non-native speech for automatic speech recognition

The performance of automatic speech recognizers has been observed to be dramatically worse for speakers with non-native accents than for native speakers. This poses a problem for many speech recognition systems, which need to handle both native and non-native speech. The problem is further complicated by the large number of non-native accents, which makes modeling separate accents difficult, as well as the small amount of non-native speech that is often available for training. Previous work has attempted to address this issue by building accent-specific acoustic and pronunciation models or by adapting acoustic models to a particular non-native speaker. In this thesis, we examine the problem of non-native speech in a speaker-independent, large-vocabulary, spontaneous speech recognition system for American English, in which a large amount of native training data and a relatively small amount of non-native data are available. We investigate some of the major differences between native and non-native speech and attempt to modify the recognizer to better model the characteristics of nonnative data. This work is performed using the summit speech recognition system in the jupiter weather information domain. We first examine the modification of acoustic models for recognition of non-native speech. We show that interpolating native and non-native models reduces the word error rate on a non-native test set by 8.1% relative to a baseline recognizer using models trained on pooled native and non-native data (a reduction from 20.9% to 19.2%). In the area of lexical modeling, we describe a small study of native and non-native pronunciation using manual transcriptions and outline some of the main differences between them. We then attempt to model non-native word pronunciation patterns by applying phonetic substitutions, deletions, and insertions to the pronunciations in the lexicon. The probabilities of these phonetic confusions are estimated from non-native training data by aligning automatically-generated phonetic transcriptions with the baseline lexicon. Using this approach, we obtain a relative reduction of 10.0% in word error rate over the baseline recognizer on the non-native test set. Using both phonetic confusions and interpolated acoustic models, we further reduce the word error rate to 12.4% below baseline. Finally, we describe a study of language model differences between native and non-native speakers in the jupiter domain. We find that, within the resolution of our analysis, language model differences do not account for a significant part of the degradation in recognition performance between native and non-native test speakers. Thesis Supervisor: James R. Glass Title: Principal Research Scientist
Progress in Organization Development Research

Despite the frequent criticisms of OD in the behavioral science literature, there are four major areas ofprogress in OD: progress in operationalizing the concept of change; progress in improving measurement processes and procedures; and progress in designing statistical procedures used to analyze OD intervention data. The authors are encouraged by recent developments in OD research which point to a more solid base on which to build OD practice and theory.
Perceptual Grouping and High-Order Cognitive Ability

High-order cognitive functions require the integration of information across functionally related modules. This relationship suggests that cognitive ability is related to the efficiency and processing speed of basic integrative function. In order to examine individual differences for this relationship, we compared standardized tests of intelligence to visual perceptual grouping abilities, which represents a basic process of integration. Sixty participants discriminated perceived grouping of dot patterns based upon similarity in luminance. Psychophysical measurements were made of the functional limits and processing speed of grouping. We assessed cognitive abilities with the Wechsler Abbreviated Scale of Intelligence (WASI) and found that measures of grouping efficiency as well as speed varied considerably across subjects, indicating substantial individual differences at this relatively early level of visual processing. Faster grouping speed was associated with higher scores on all WASI subtests, whereas g.
Joint Synchronization and Channel Estimation of ACO-OFDM Systems With Simplified Transceiver

To facilitate the development of asymmetrically clipped optical orthogonal frequency division multiplexing systems, a joint synchronization and channel estimation scheme is proposed. The preamble used in the scheme is based on zero correlation code pair and has impulse-like correlation relationship. This property can let the results of synchronization process be the coarsely estimated channel time response, thus simplifies channel frequency response generation. Also, a transceiver with low complexity is proposed. The proposed transceiver needs only half the amount of multiplications compared with conventional transceiver. Simulation results reveal that the proposed scheme achieves better performance both in synchronization and channel estimation than existing schemes.
Fibro markers for prediction of hepatocellular carcinoma in Egyptian patients with chronic liver disease

It is well known that hepatocellular carcinoma (HCC) develops as a consequence of hepatic fibrosis progression. In this study, we aimed to evaluate the inflammatory and fibrosis markers as predictors for HCC development among patients with hepatitis C virus (HCV) related chronic liver disease to help in early diagnosis and management of HCC. A total of 280 patients with chronic liver disease were included in this retrospective study, out of them 140 had liver cirrhosis with HCC and 140 had cirrhosis without HCC. Eight readily available blood indices King score, Fibro Q, AST‐ALT ratio (AAR), APRI, LOK index, Goteborg University Cirrhosis Index (GUCI), fibro alpha, and Biotechnology Research Center (BRC) were constructed to compare the accuracies of these non invasive scores in predicting HCC development. All fibrosis scores except APRI were significantly higher in HCC. We found that Fibro alpha and BRC had superior diagnostic performance in prediction of HCC based on area under curve of 0.91 and 0.93, respectively compared to other scores with area under curve ranged from poor to failure (0.59–0.66). Almost all cirrhotic cases were secondary to HCV (93.6%), while HBV was detected in 2.1% of cases only. Anti‐HCV positive was reported in 100% of HCC cases (P = 0.002). Fibro alpha and BRC scores can be used for prediction of HCC. J. Med. Virol. 89:1062–1068, 2017. © 2016 Wiley Periodicals, Inc.
The Role of Score Calibration in Speaker Recognition

The performance of speaker recognition, as measured by NIST in its periodic evaluation programs of speaker detection technology, is affected by the predictive accuracy of system decisions as well as the inherent discriminating power of the underlying algorithms. This paper analyses the score calibration accuracy of a few systems that exhibited good performance in the NIST 2010 speaker recognition evaluation (SRE10) and proposes a modified cost function that better represents the accuracy of score calibration in the low false alarm decision region, which is the region of interest for intelligence applications.
Scenario decomposition of risk-averse two stage stochastic programming problems

RRR 1-2012 ON THE REPETITION-FREE SUBTRACTION GAMES AND VILE–DOPEY INTEGERS, Vladimir Gurvich Given two integers n ≥ 0 and k ≥ 3, two players alternate turns taking stones from a pile of n stones. By one move a player is allowed to take any number of stones k′ ∈ {1, . , k − 1}. In particular, it is forbidden to pass. Furthermore, it is not allowed to take the same number of stones as the opponent by the previous move. The player who takes the last stone wins in the normal version of the game and loses in the misère version; (s)he also wins, in both cases, when the opponent has no legal move, that is, after the move from 2 to 1. An integer k ∈ Z≥0 is called vile if the maximum power of 2 that is still a divisor of k is even, or in other words, if the binary representation of k ends with an even number of zeros; otherwise, if this number is odd, k is called dopey. In this short note, we will solve (both the normal and misère versions of) the game when k is vile and obtain partial results when k is dopey. In the normal version, the set of P-positions is an arithmetic progression ak, where a = 0, 1, . , if k is vile. When k is dopey, for the P-positions n0, n1, . , we have n0 = 0, n1 = k + 1, and ni+1 − ni is either k or k + 1 for all i ∈ ZZ≥0. Yet, in the latter case, it seems not easy to choose among k and k + 1. We conjecture that the differences ni+1 − ni between the successive P-positions form a periodical sequence. In the misère version of the game, the P-positions are shifted by +1 with respect to the P-positions of the corresponding normal version.
MCC: A baseline algorithm for fingerprint verification in FVC-onGoing

This paper describes an improved version of the MCC fingerprint matching approach. An in-depth error analysis allowed us to point out the weakest points of the original MCC and to design: i) a more effective minutiae pair selection and ii) a more distortion-tolerant relaxation. The parameters of the new version have been tuned over a new larger dataset and the final algorithm has been evaluated on FVC-onGoing. The results show that MCC compares favorably with some of the most accurate commercial algorithms published in FVC-onGoing.
Spatial Data Analysis with R-INLA with Some Extensions

The integrated nested Laplace approximation (INLA) provides an interesting way of approximating the posterior marginals of a wide range of Bayesian hierarchical models. This approximation is based on conducting a Laplace approximation of certain functions and numerical integration is extensively used to integrate some of the models parameters out. The R-INLA package offers an interface to INLA, providing a suitable framework for data analysis. Although the INLA methodology can deal with a large number of models, only the most relevant have been implemented within R-INLA. However, many other important models are not available for R-INLA yet. In this paper we show how to fit a number of spatial models with R-INLA, including its interaction with other R packages for data analysis. Secondly, we describe a novel method to extend the number of latent models available for the model parameters. Our approach is based on conditioning on one or several model parameters and fit these conditioned models with R-INLA. Then these models are combined using Bayesian model averaging to provide the final approximations to the posterior marginals of the model. Finally, we show some examples of the application of this technique in spatial statistics. It is worth noting that our approach can be extended to a number of other fields, and not only spatial statistics.
Effect of Remifentanil on Mitochondrial Oxygen Consumption of Cultured Human Hepatocytes

During sepsis, liver dysfunction is common, and failure of mitochondria to effectively couple oxygen consumption with energy production has been described. In addition to sepsis, pharmacological agents used to treat septic patients may contribute to mitochondrial dysfunction. This study addressed the hypothesis that remifentanil interacts with hepatic mitochondrial oxygen consumption. The human hepatoma cell line HepG2 and their isolated mitochondria were exposed to remifentanil, with or without further exposure to tumor necrosis factor-α (TNF-α). Mitochondrial oxygen consumption was measured by high-resolution respirometry, Caspase-3 protein levels by Western blotting, and cytokine levels by ELISA. Inhibitory κBα (IκBα) phosphorylation, measurement of the cellular ATP content and mitochondrial membrane potential in intact cells were analysed using commercial ELISA kits. Maximal cellular respiration increased after one hour of incubation with remifentanil, and phosphorylation of IκBα occurred, denoting stimulation of nuclear factor κB (NF-κB). The effect on cellular respiration was not present at 2, 4, 8 or 16 hours of incubation. Remifentanil increased the isolated mitochondrial respiratory control ratio of complex-I-dependent respiration without interfering with maximal respiration. Preincubation with the opioid receptor antagonist naloxone prevented a remifentanil-induced increase in cellular respiration. Remifentanil at 10× higher concentrations than therapeutic reduced mitochondrial membrane potential and ATP content without uncoupling oxygen consumption and basal respiration levels. TNF-α exposure reduced respiration of complex-I, -II and -IV, an effect which was prevented by prior remifentanil incubation. Furthermore, prior remifentanil incubation prevented TNF-α-induced IL-6 release of HepG2 cells, and attenuated fragmentation of pro-caspase-3 into cleaved active caspase 3 (an early marker of apoptosis). Our data suggest that remifentanil increases cellular respiration of human hepatocytes and prevents TNF-α-induced mitochondrial dysfunction. The results were not explained by uncoupling of mitochondrial respiration.
RCM - a multi-layered reconfigurable cluster middleware

DSM systems provide an easy-to-use programming model for parallel and distributed systems, but it is sometimes difficult to reach the performance characteristics of low-level message-passing programs, in particular if these have been optimized towards a specific architecture. In this article, we propose a multi-layered realization of a DSM system which provides different programming abstractions, including a level which allows an explicit control of the data placement. The programmer can select an appropriate level of abstraction for his application and it is even possible to mix program parts realized at different abstraction levels. The article gives a description of the multi-layered model, describes a prototype realization of the system and presents some preliminary experimental results on a heterogeneous system.
Extracting urban functional regions from points of interest and human activities on location‐based social networks

Data about points of interest (POI) have been widely used in studying urban land use types and for sensing human behavior. However, it is difficult to quantify the correct mix or the spatial relations among different POI types indicative of specific urban functions. In this research, we develop a statistical framework to help discover semantically meaningful topics and functional regions based on the co‐occurrence patterns of POI types. The framework applies the latent Dirichlet allocation (LDA) topic modeling technique and incorporates user check‐in activities on location‐based social networks. Using a large corpus of about 100,000 Foursquare venues and user check‐in behavior in the 10 most populated urban areas of the US, we demonstrate the effectiveness of our proposed methodology by identifying distinctive types of latent topics and, further, by extracting urban functional regions using K‐means clustering and Delaunay triangulation spatial constraints clustering. We show that a region can support multiple functions but with different probabilities, while the same type of functional region can span multiple geographically non‐adjacent locations. Since each region can be modeled as a vector consisting of multinomial topic distributions, similar regions with regard to their thematic topic signatures can be identified. Compared with remote sensing images which mainly uncover the physical landscape of urban environments, our popularity‐based POI topic modeling approach can be seen as a complementary social sensing view on urban space based on human activities.
A DVFS-aware cache bypassing technique for multiple clock domain mobile SoCs

Multiple clock domains mobile SoCs typically adopt dynamic voltage and frequency scaling (DVFS) for flexible power/energy management. However, adoption of system-level cache under DVFS-enabled CPU may incur abnormal cache hierarchy (i.e., a delay reversal between the highlevel and low-level caches). It may lead to performanceand energyinefficiency due to slower data delivery and meaningless accesses to intermediate levels of caches. To resolve this problem, we propose a DVFS-aware cache bypassing technique. Our technique profiles latencies of the various levels of the caches. Based on the profiled information, our technique adaptively bypasses intermediate levels of caches in the case of abnormal cache hierarchy and applies power-gating to that cache memory for better energy efficiency. According to our evaluation, our technique reduces L2 and system-level cache energy consumption by up to 14.5% while improving performance by up to 0.13% compared to the baseline.
Role-play Teaching

Within the context of the ongoing debate on the relevance of the teaching approach to effective learning, the quality of teaching should be better understood. To help in this, the article presents a two-dimensional model of roles, based on three streams of knowledge—education, behavioural sciences and drama. It is a generic model, which proposes a conceptual framework for analysing, comparing and contrasting metaphorical masks that lecturers 2 may utilize in their teaching, with particular relevance for management education and learning. It clarifies what these roles are, and how they can be practised to improve the effectiveness of teaching and enhance learning. A number of cases demonstrate the descriptive and analytical power of the model.