Miracle-dz/UniFAR-FTUs huggingface dataset:
Inactivation of an Iron Transporter in Lactococcus lactis Results in Resistance to Tellurite and Oxidative Stress

ABSTRACT In Lactococcus lactis, the interactions between oxidative defense, metal metabolism, and respiratory metabolism are not fully understood. To provide an insight into these processes, we isolated and characterized mutants of L. lactis resistant to the oxidizing agent tellurite (TeO32−), which generates superoxide radicals intracellularly. A collection of tellurite-resistant mutants was obtained using random transposon mutagenesis of L. lactis. These contained insertions in genes encoding a proton-coupled Mn2+/Fe2+ transport homolog (mntH), the high-affinity phosphate transport system (pstABCDEF), a putative osmoprotectant uptake system (choQ), and a homolog of the oxidative defense regulator spx (trmA). The tellurite-resistant mutants all had better survival than the wild type following aerated growth. The mntH mutant was found to be impaired in Fe2+ uptake, suggesting that MntH is a Fe2+ transporter in L. lactis. This mutant is capable of carrying out respiration but does not generate as high a final pH and does not exhibit the long lag phase in the presence of hemin and oxygen that is characteristic of wild-type L. lactis. This study suggests that tellurite-resistant mutants also have increased resistance to oxidative stress and that intracellular Fe2+ can heighten tellurite and oxygen toxicity.
Adaptive compressive sensing for energy efficient smart objects in IoT applications

The IoT (Internet-of-Things) concept has been introduced as a strategic innovation aspect that will benefit society in many ways. Environmental monitoring, smart traffic control, pollution monitoring, crime prevention, smart metering, etc., have now been made feasible due to the ongoing research and development towards IoT. Smart Objects (SOs) are among the fundamental blocks of an IoT architecture consisting of a sensing element (sensor) that senses the environment, and other software/hardware entities. SOs are interconnected forming wireless sensor networks (WSNs) that often convey sensitive information in a multi-hop fashion. As SOs are severe resource-constrained devices, energy-efficient mechanisms for data collection and transmission are of paramount importance. A popular technique for achieving energy efficiency is Compressive Sensing (CS). CS's major advantage is that it can sample and compress information in a single step. At the same time, CS offers lightweight data encryption during compression. In this work, we propose an adaptive CS scheme where a central SO with enhanced capabilities utilizes a learning phase, associating different sparsity levels with the reconstruction error. Based on this scheme, this SO provides feedback to the rest of the SOs to adapt their CS parameters in order to serve applications with a diverge range of quality-of-service requirements.
Perceptual Latency and Complex Random-Dot Stereograms

Naïve observers of random-dot stereograms depicting complex surfaces often find that they require several tens of seconds before the impression of depth emerges. With practice, however, perception times often decrease markedly: perceptual learning occurs. Current explanations of these effects were assessed in two experiments. In the first experiment the perception times of naïve observers for random-dot stereograms which depicted the same complex shape but contained different ranges of disparity were measured. In the second experiment the minimum times required by experienced observers to perceive a given complex shape in stereograms that contained different ranges of disparity were determined. Perception times for the naïve observers were all very fast (<3 s) and showed no evidence of perceptual learning. There was no effect of disparity range on perception times in either experiment. It was found that very large-disparity (80 min arc) complex stereograms could be perceived quickly, even by naïve observers. It is concluded that the long initial latencies previously reported are not due to surface complexity nor to the range of disparities present. Other factors, such as dot size, dot density, and the correlation of the stereo images, appear to be important determinants of efficient stereoscopic performance when viewing complex random-dot stereograms.
Thermal Characteristics of All-Optical ADM Using Fiber Bragg Gratings and Mach-Zehnder Interferometer for WDM Optical Communication Networks

The output spectrum have been numerically analyzed in order to investigate the temperature characteristics of the all-optical add-drop multiplexer (ADM). It is shown that the center Bragg wavelength shifts by 0.0142237 nm when the temperature increases by 1degC in a range of -30 degC to 110 degC. An experiment was conducted to observe the output spectrum for the all-optical ADM. The experiment results were analyzed and compared to the results of the numerical analysis of the output spectrum of the all-optical ADM. The experiment results show that there is a shift of 0.0112666 nm when the temperature changes by 1 degC and output power is on the average -10 dBm.
Accounting for Debt Service: The Painful Legacy of Credit Booms

This paper documents the main channel through which credit booms affect real economic activity in the future. As a matter of simple accounting, credit booms generate a predictable increase in future debt service that transfers spending power from borrowers to lenders. We document this dynamic pattern in a panel of 17 countries from 1980 to 2015 and identify a robust lead-lag relationship of about 3 years between the peak of credit booms and the peak in debt service. We develop a method to decompose what fraction of future real effects of credit booms is explained by debt service and show that debt service almost fully accounts for several puzzling findings in the recent empirical literature: that high growth in credit predicts low output growth in the future, deeper recessions, and a greater likelihood of financial crises. Explicitly accounting for debt service not only sheds light on the channel behind these findings but also generates stronger empirical relationships. We hope that our results will provide useful guidance for future efforts to model credit cycles.
The Role of Deliberative Versus Implemental Mindsets in Time Prediction and Task Accomplishment

The Model of Action Phases (Gollwitzer, 1990, 2012) distinguishes an implemental mindset evoked by planning goal-directed actions, from a deliberative mindset evoked by pondering pros/cons of adopting a particular goal. The present research demonstrates that mindsets affect time predictions. In Study 1 (N = 151), participants in an implemental mindset made shorter time predictions with respect to completing personal goals than participants in a deliberative mindset. In Study 2 (N = 78), we tested a mediating mechanism for the mindset effect by varying the motivation to return a report. The mindset effect was replicated in the low- but not in the high-motivation condition with participants in an implemental mindset returning the report earlier, and being as accurate in their predictions as participants in a deliberative mindset. Results indicate that an implemental (vs. deliberative) mindset increases motivation and therefore leads to shorter, but equally biased time predictions.
Fast frequency-hopping dynamic multiple-access for cognitive radios: Suboptimum noncoherent maximum-likelihood multiuser detection

We propose a novel dynamic multiple-access (DMA) scheme for application in cognitive radios (CRs). This DMA scheme is implemented by fast frequency hopping with Mary frequency-shift keying (FFH/MFSK) associated with suboptimum noncoherent maximum-likelihood multiuser detection (ML-MUD). In our studies, we assume that the primary users (PUs) and the cognitive radio users (CRUs) are operated in the interweave paradigm. The PUs activate to communicate according to a Poisson process and the duration of an activation obeys exponential distribution. The bit error rate (BER) and throughput performance of the dynamic FFH/MFSK systems are investigated by simulations, when assuming communications over Rayleigh fading channels. Our studies and simulation results demonstrate that the dynamic FFH/MFSK with suboptimum noncoherent ML-MUD constitutes one of the promising candidates for DMA in CRs. It has low-complexity and employs high-flexibility for DMA and seamless transition between different frequency bands.
Performance and Implementation Complexity in Multiprocessor Operating System Kernels

The increasing use of multiprocessor computers require operating system adaptations to take advantage of the computing power. However, porting an operating system kernel to run on a multiprocessor can be very difficult because of a large code base, concurrency issues when dealing with multiple threads of execution, and limited tool support for development. Likewise, it can be difficult to obtain good performance from a ported operating system without sufficient parallelism in the operating system kernel. This thesis examines the tradeoff between performance and implementation complexity in multiprocessor operating system ports and is based on four papers. The first paper is a survey of existing multiprocessor implementation approaches and focuses on the tradeoff between performance and implementation effort. The second paper describes experiences from performing a traditional lock-based multiprocessor port while the third paper presents an alternative porting approach which aims to minimize implementation complexity. The fourth paper, finally, presents a tool for efficient instrumentation of programs, which can be used during the development of large software systems such as operating system kernels. The main contribution of this thesis is an in-depth investigation into the techniques used when porting operating systems to multiprocessors, focusing on implementation complexity and performance. The traditional approach used in the second paper required longer development time than expected, and the alternative approach in the third paper can therefore be preferable in some cases. The need for efficient tools is also illustrated in the fourth paper.
A preliminary study on extracting objects in sketches

Humans have the incredible ability to interpret complex sketch images, but it remains a challenging task for computers to do the same thing. Researchers have made great progress on nature image detection and recognition, but little research has been done on object detection in sketch images. In this paper, we demonstrate that object extraction can be possibly conducted using a Single-Shot Multibox Detector(SSD) frame-work, without the guidance of segmentation information or user interaction. We train and test our model with a synthetic dataset based on TU-Berlin sketch dataset. Experiments on the synthetic dataset show reasonable object detection and recognition results in sketch images.
Allergic Contact Dermatitis in Psoriasis Patients: Typical, Delayed, and Non-Interacting

Psoriasis is characterized by an apoptosis-resistant and metabolic active epidermis, while a hallmark for allergic contact dermatitis (ACD) is T cell-induced keratinocyte apoptosis. Here, we induced ACD reactions in psoriasis patients sensitized to nickel (n = 14) to investigate underlying mechanisms of psoriasis and ACD simultaneously. All patients developed a clinically and histologically typical dermatitis upon nickel challenge even in close proximity to pre-existing psoriasis plaques. However, the ACD reaction was delayed as compared to non-psoriatic patients, with a maximum intensity after 7 days. Whole genome expression analysis revealed alterations in numerous pathways related to metabolism and proliferation in non-involved skin of psoriasis patients as compared to non-psoriatic individuals, indicating that even in clinically non-involved skin of psoriasis patients molecular events opposing contact dermatitis may occur. Immunohistochemical comparison of ACD reactions as well as in vitro secretion analysis of lesional T cells showed a higher Th17 and neutrophilic migration as well as epidermal proliferation in psoriasis, while ACD reactions were dominated by cytotoxic CD8+ T cells and a Th2 signature. Based on these findings, we hypothesized an ACD reaction directly on top of a pre-existing psoriasis plaque might influence the clinical course of psoriasis. We observed a strong clinical inflammation with a mixed psoriasis and eczema phenotype in histology. Surprisingly, the initial psoriasis plaque was unaltered after self-limitation of the ACD reaction. We conclude that sensitized psoriasis patients develop a typical, but delayed ACD reaction which might be relevant for patch test evaluation in clinical practice. Psoriasis and ACD are driven by distinct and independent immune mechanisms.
AN I-VECTOR BASED APPROACH FOR AUDIO SCENE DETECTION

The IEEE-ASSP Scene Classiﬁcation challenge on user-generated content (UGC) aims to classify an audio recording that belongs to a speciﬁc scene such as busystreet, ofﬁce or supermarket. The difﬁ-culty of scene content analysis on UGC lies in the lack of structure and acoustic variability of the data. The i-vector system is state-of-the-art in Speaker Veriﬁcation and Scene Detection, and is outper-forming conventional Gaussian Mixture Model (GMM)-based approaches. The system compensates for undesired acoustic variability and extracts information from the acoustic environment, making it a meaningful choice for detection on UGC. This paper reports our results in the challenge by using a hand-tuned i-vector system and MFCC features. Compared to the MFCC+GMM baseline sys-tem, our system increased the classiﬁcation accuracy by 26.4% to about 65.8%. We discuss our approach and highlight parameters in our system that showed to signiﬁcantly improved our classiﬁcation accuracy.
Women's working models of relationships : the role of parental marital status, attachment style, and perceived family conflict.

WOMEN'S WORKING MODELS OF RELATIONSHIPS: THE ROLE OF PARENTAL MARITAL STATUS, ATTACHMENT STYLE, AND PERCEIVED FAMILY CONFLICT MAY 1995 CATHERINE LANGDON DIMMITT, B.A. , WESLEYAN UNIVERSITY M.Ed., UNIVERSITY OF MASSACHUSETTS AMHERST Ph.D., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Maria Brassard The purpose of this study was to investigate the relationship between experiencing parental divorce as a child and cognitive schemas of primary relationships as an adult. Four questions were of interest: is there a significant relationship between experiencing parental divorce as a child and adult attachment, style? Do women with parents who divorced during their childhood describe their relationships with their parents in different ways than those whose parents stayed married? What, if any, are the differences between the romantic relationships of young women whose parents divorced when they were children and those whose parents are still married? And fourth, what role does conflict play in attachment style and relationship expectations? Subjects were 196 female undergraduate students. A measure of interpersonal schemas was used to determine
Reliability and validity of the self‐report version of the Panic Disorder Severity Scale in Korea

Background: The self‐report version of the Panic Disorder Severity Scale (PDSS‐SR) has been developed recently and has demonstrated good psychometric properties. However, there is no cross‐cultural evaluation of this scale. The purpose of this study was to confirm the reliability and validity of the PDSS‐SR in Korean subjects. Methods: We studied 148 patients with principal DSM‐IV diagnoses of panic disorder who underwent formal structured diagnostic assessment and the PDSS interview. The participants completed self‐report measures including the PDSS‐SR, Anxiety Sensitivity Index‐Revised, Albany Panic and Phobia Questionnaire, Beck Depression Inventory, Beck Anxiety Inventory, and Spielberger State–Trait Anxiety Inventory‐Trait Version. Results: The PDSS‐SR had a single‐factor structure, with all seven items having salient loadings. Cronbach's α for the PDSS‐SR was . 88 and intraclass correlation coefficient was . 71 between PDSS‐SR and PDSS. Also, the scale showed excellent 1‐day test–retest reliability and demonstrated significant correlation with other anxiety‐related measures. In addition, the PDSS‐SR was sensitive to change with pharmacological treatment. Conclusions: The findings of this study strongly support the reliability and validity of the PDSS‐SR. It is expected that this scale will be helpful in clinical settings and research protocols in Korea. Depression and Anxiety, 2009. © 2009 Wiley‐Liss, Inc.
Surface matching by curvature distribution images generated via gaze modeling

In order to realize model-based 3D object recognition, first, we propose a geometric feature extraction method based on a novel gaze modeling. In the modeling process, local surface models are independently estimated for parts of range data restricted by several gaze domains. Hence, since features are independently extracted from each gaze domain, inconsistent or incorrect features may be obtained. Therefore we introduce a stochastic method that enables us to integrate such features by evaluating the reliability of each gaze model. Next, we propose a shape descriptor, curvature distribution image (CDI), to achieve object recognition by surface matching. It is generated based on the ratios between surface curvatures. The main contribution of this paper is experimental analysis of the performance of CDIs generated by various generation parameters.
TÜBITAK UZAY at TRECVID 2009: High-Level Feature Extraction and Content-Based Copy Detection

In this notebook paper, we discuss and give an overview of our participation to the High-Level Feature Extraction (HLFE) and Content-Based Copy Detection (CBCD) tasks of TRECVID 2009. In our HLFE system both visual and audio concept detection has been implemented and also complimentary standalone detectors have been incorporated to the system. For the visual concept detection, a generalized visual feature extraction method based on codebook approach is employed. On the other hand, our audio system is a hierarchic system with continuous static spectral features and Gaussian Mixture Model classifiers. Furthermore, for the CBCD task our group has submitted to video-only, audio-only and audio + video subtasks. Our video-based CBCD system utilizes local interest points and bag-of-words concept and for the audio copy detection voting-based audio fingerprint matching method has been utilized.
Selectivity in glycosaminoglycan binding dictates the distribution and diffusion of fibroblast growth factors in the pericellular matrix

The range of biological outcomes generated by many signalling proteins in development and homeostasis is increased by their interactions with glycosaminoglycans, particularly heparan sulfate (HS). This interaction controls the localization and movement of these signalling proteins, but whether such control depends on the specificity of the interactions is not known. We used five fibroblast growth factors with an N-terminal HaloTag (Halo-FGFs) for fluorescent labelling, with well-characterized and distinct HS-binding properties, and measured their binding and diffusion in pericellular matrix of fixed rat mammary 27 fibroblasts. Halo-FGF1, Halo-FGF2 and Halo-FGF6 bound to HS, whereas Halo-FGF10 also interacted with chondroitin sulfate/dermatan sulfate, and FGF20 did not bind detectably. The distribution of bound FGFs in the pericellular matrix was not homogeneous, and for FGF10 exhibited striking clusters. Fluorescence recovery after photobleaching showed that FGF2 and FGF6 diffused faster, whereas FGF1 diffused more slowly, and FGF10 was immobile. The results demonstrate that the specificity of the interactions of proteins with glycosaminoglycans controls their binding and diffusion. Moreover, cells regulate the spatial distribution of different protein-binding sites in glycosaminoglycans independently of each other, implying that the extracellular matrix has long-range structure.
Using Graphs of Classifiers to Impose Constraints on Semi-supervised Relation Extraction

We propose a general approach to modeling semi-supervised learning constraints on unlabeled data. Both traditional supervised classiﬁcation tasks and many natural semi-supervised learning heuristics can be approximated by specifying the desired outcome of walks through a graph of classiﬁers. We demonstrate the modeling capability of this approach in the task of relation extraction, and experimental results show that the modeled constraints achieve better performance as expected.
Isolation of Pseudomonas pickettii strains that degrade 2,4,6-trichlorophenol and their dechlorination of chlorophenols

Three strains of Pseudomonas pickettii that can grow with 2,4,6-trichlorophenol (2,4,6-TCP) as the sole source of carbon and energy were isolated from different mixed cultures of soil bacterial populations that had been acclimatized to 2,4,6-TCP. These strains released 3 mol of chloride ion from 1 mol of 2,4,6-TCP during the complete degradation of the TCP. Of these strains, P. pickettii DTP0602 in high-cell-density suspension cultures dechlorinated various chlorophenols (CPs). Cells that were preincubated with 2,4,6-TCP converted isomers of 4-CP to the corresponding chloro-p-hydroquinones, but those preincubated with 4-CP converted CPs lacking a chlorine atom(s) at the o position to isomers of chlorocatechol. The ability of DTP0602 to dechlorinate 2,4,6-TCP was induced by 2,6-dichlorophenol, 2,3,6- and 2,4,6-TCP, and 2,3,4,6-tetrachlorophenol and was repressed in the presence of succinate or glucose.
Congestion control for differentiated-services using non-linear control theory

The growing demand of computer usage requires efficient ways of managing network traffic in order to avoid or at least limit the level of congestion in cases where increases in bandwidth are not desirable or possible. Using non-linear control theory we developed and analysed a generic integrated dynamic congestion control (IDCC) scheme for controlling traffic using information on the status of each queue in the network. The IDCC scheme is based on a nonlinear model of the network that is generated using fluid flow considerations. The methodology used is general and independent of technology, as for example TCP/IP or ATM. We assume a differentiated-services network framework and formulate our control strategy in the same spirit as IP Diff-Serv for three types of services: premium service, ordinary service, and best effort service. The three differentiated classes of traffic operate at each output port of a router/switch. An IDCC scheme is designed for each output port, and a powerful, simple to implement controller is designed and analysed. The IDCC methodology has been applied to an ATM network. We use OPNET simulations to demonstrate that the proposed control methodology achieves the desired behaviour of the network, and possesses important attributes, such as: stable and robust behaviour, high utilisation with bounded delay and loss performance, and good steady state and transient behaviour.