Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploitation of Eukaryotic Ubiquitin Signaling Pathways by Effectors Translocated by Bacterial Type III and Type IV Secretion Systems

The specific and covalent addition of ubiquitin to proteins, known as ubiquitination, is a eukaryotic-specific modification central to many cellular processes, such as cell cycle progression, transcriptional regulation, and hormone signaling. Polyubiquitination is a signal for the 26S proteasome to destroy earmarked proteins, but depending on the polyubiquitin chain topology, it can also result in new protein properties. Both ubiquitin-orchestrated protein degradation and modification have also been shown to be essential for the host's immune response to pathogens. Many animal and plant pathogenic bacteria utilize type III and/or type IV secretion systems to inject effector proteins into host cells, where they subvert host signaling cascades as part of their infection strategy. Recent progress in the determination of effector function has taught us that playing with the host's ubiquitination system seems a general tactic among bacteria. Here, we discuss how bacteria exploit this system to control the timing of their effectors' action by programming them for degradation, to block specific intermediates in mammalian or plant innate immunity, or to target host proteins for degradation by mimicking specific ubiquitin/proteasome system components. In addition to analyzing the effectors that have been described in the literature, we screened publicly available bacterial genomes for mimicry of ubiquitin proteasome system subunits and detected several new putative effectors. Our understanding of the intimate interplay between pathogens and their host's ubiquitin proteasome system is just beginning. This exciting research field will aid in better understanding this interplay, and may also provide new insights into eukaryotic ubiquitination processes.
Reinforced temporal structure information for embedded utterance-based speaker recognition

Embedded speaker recognition in mobile devices could involve several ergonomic constraints and a limited amount of computing resources. Even if they have proved their efficiency in more classical contexts, GMM/UBM based systems show their limits in such situations, with good accuracy demanding a relatively large quantity of speech data, but with negligible harnessing of linguistic content. The proposed approach addresses these limitations and takes advantage from the linguistic nature of the speech material into the GMM/UBM framework by using client-customised utterances. The GMM/UBM is then reinforced with new temporal information. Experiments on the MyIdea database are performed when impostors know the client-utterance and also when they do not, highlighting the potential of this new approach. A relative gain up to 45% in terms of EER is achieved when impostors do not know the client utterance and performance is equivalent to the GMM/UBM baseline system in other configurations.
Improved Emotion Recognition with Novel Global Utterance-level Features

Traditional features, which are extracted from each frame, can not reflect the dynamic characteristics of emotion speech signal accurately. To solve this problem, first, without dividing the emotion speech into frames, novel global utterance-level features are proposed with multi-scale optimal wavelet packet decomposition; then, considering the case of little training samples, a fusion strategy through metric learning, which is called weak metric learning in this work, is proposed for fusing the global and traditional features. The experimental results with LIBSVM show that fusing the novel global feature to traditional feature achieves significant improvements about 5.2% to 13.6% than merely using local utterance-level features.
Women offenders: Promoting a holistic approach and continuity of care across criminal justice and health interventions

Analysis of data in this article focuses on the self-reported situations of 21 female respondents who were part of a large-scale study of offenders’ health needs. The findings show an extensive range of physical and psychological problems, often intertwined with substance misuse and other issues, including offending behaviour. Four components of an existing model of ‘continuity of care’ are reviewed to explore the difficulties, but also the potential, for collaborative and co-ordinated interventions with regard to working with women offenders. Concern is expressed about the changes and fragmentation in provision for women brought about by the Transforming Rehabilitation agenda in England and Wales. It is advocated here that policy and practice should be developed across health and criminal justice agencies to provide holistic and integrated approaches which could support women offenders in their attempts to stabilize their lives and to find pathways out of crime.
Pyrosequencing as a tool for better understanding of human microbiomes

Abstract Next-generation sequencing technologies have revolutionized the analysis of microbial communities in diverse environments, including the human body. This article reviews several aspects of one of these technologies, the pyrosequencing technique, including its principles, applications, and significant contribution to the study of the human microbiome, with especial emphasis on the oral microbiome. The results brought about by pyrosequencing studies have significantly contributed to refining and augmenting the knowledge of the community membership and structure in and on the human body in healthy and diseased conditions. Because most oral infectious diseases are currently regarded as biofilm-related polymicrobial infections, high-throughput sequencing technologies have the potential to disclose specific patterns related to health or disease. Further advances in technology hold the perspective to have important implications in terms of accurate diagnosis and more effective preventive and therapeutic measures for common oral diseases.
WHAT HAPPENED TO MACROECONOMETRIC MODELS ? + Testing Macroeconometric Models

Interest in research topics in different fields fluctuates over time, and the field of macroeconomics is no exception. From Jan Tinbergen’s (1939) model-building in the late 1930’s through work in the 1960’s, there was considerable interest in the construction of structural macroeconomic models. The dominant methodology of this period was what I will call the “Cowles Commission” approach. Structural econometric models were specified, estimated, and then analyzed and tested in various ways. One of the major macroeconometric efforts of the 1960’s, building on the earlier work of Lawrence Klein (1950) and Klein and Arthur Goldberger (19X$ was the Brookings model (James Duesenberty et al., 1965, 1969). This model was a joint effort of many individuals, and at its peak it contained nearly 400 equations. Although much was learned from this exercise, the model never achieved the success that was initially expected, and it was laid to rest around 1972. Two important events in the 1970’s contributed to the decline in popularity of the Cowles Commission approach. The first was the commercialization of macroeconometric models. This changed the focus of research on the models. Basic research gave way to the day-to-day needs of keeping the models up-to-date, of subjectively adjusting the forecasts to make them “reasonable,” and of meeting the special needs of clients. The second event was Robert Lucas’s (1976) critique, which argued that the models are not likely to be useful for policy purposes. The Lucas critique led to a line of research that culminated in real-business-cycle theo-
A Scalable Visualization System for Improving Space Situational Awareness

Visualization plays a crucial role in Space Situational Awareness, because it has the expressive power to provide insights to support the assessment and planning process of SSA. As computers become more powerful, SSA modeling and simulation in testbed environments are producing massive amounts of data, including more debris particles at higher fidelity and longer orbital propagations with uncertainty quantification. What is lacking in current visualization systems for SSA is the ability to visualize and exploit these massive amounts of modeling and simulation data in real-time. The main reason for this lack of capability is the underlying assumption that the entire data set can be completely loaded into the main memory before any processing or visualization, which is certainly not the case anymore. One effective strategy for dealing with massive amounts of data that cannot fit in main memory is to use out-of-core, or external memory, algorithms, which operate on smaller subsets of the data, while keeping in memory only as much of the data as needed by the algorithms. In this paper, we present a scalable visualization system for SSA simulation data that operates in an out-of-core fashion for the data access and the rendering process. We utilize an out-of-core octree to spatially partition simulation data points, and we use a realtime rendering approach that incorporates techniques for view frustum culling and discrete level-of-detail. We provide experimental results to demonstrate the efficacy of our proposed visualization system.
Overcoming limitations in diffusion‐weighted MRI of breast by spatio‐temporal encoding

Evaluating the usefulness of diffusion‐weighted spatio‐temporal encoding (SPEN) methods to provide quantitative apparent diffusion coefficient (ADC)‐based characterizations of healthy and malignant human breast tissues, in comparison with results obtained using techniques based on spin‐echo echo planar imaging (SE‐EPI).
A New Approach for Transient Fault Injection Using Symbolic Simulation

One effective fault injection approach involves instrumenting the RTL in a controlled manner to incorporate fault injection, and evaluating the behaviour of the faulty RTL whilst running some benchmark programs. This approach relies on checking the effects of faults whilst the design is executing a specific binary image, and therefore the true impact of the fault is limited by the shadow of the program image. Another limitation of this approach is the use of extra hardware for fault injection which is not needed during the fault-free running of the design. The aim of this paper is to propose a new approach for transient fault injection based on symbolic simulation and model checking that circumvents the problems experienced due to application dependent fault injection and RTL modification. In this paper we present our approach and analyse the effect of transient faults on the fetch unit of a 32-bit multi-cycle RISC processor. Our approach can be applied generally to any faulty design, not necessarily a processor.
A new time-of-flight (TOF) picker for tumor tissue in microwave induced thermo-acoustic tomography (MITAT) system

In this paper, a new method for accurately picking the time-of-flights (TOFs) of tumor is proposed in microwave induced thermo-acoustic tomography (MITAT) system. The proposed method makes use of the properties of induced thermal acoustic signal and combines them with the wavelet transform and Akaike information criterion (AIC). Both numerical simulations and ex vivo experimental results are given to test the performance of the proposed method. Through the simulations and experiment, the proposed method can efficiently and accurately pick the TOFs of tumor target in MITAT system and therefore provide a guarantee for imaging tumor with high accuracy.
Solving Inverse Tomography Problems

1. Introduction. Inverse problems are encountered typically in situations where one makes indirect observations of a quantity of interest. Solving a inverse problem means determining the parameters of a model given a set of measurements. In solving practical inverse problems, accounting for the uncertainty of the solution is important in making decision. In this project, we explored an algorithm for solving a linear two-dimensional tomography inverse problem. In the algorithm we use a wavelet based multires-olution approach in addition to a Bayesian approach in attempts to solve this problem. Additional and background information about wavelets and the Bayesian approach can be found in [4] and [2]
A performability model for soft real-time systems

Presents a simple model that combines the failure to meet deadlines with hardware/software failures in computing the reliability of a real-time system. We define the performability as the probability of meeting deadlines by real-time tasks in the presence of hardware and software failures. Deadline-driven schedules rely on worst-case task execution time. This may be necessary for hard real-time systems, where missed deadlines can be very costly. For soft real-time systems (where a missed deadline is not catastrophic), using worst-case task execution times leads to very inefficient use of processing resources. This is particularly true when worst-case execution occurs very infrequently. Our performability analysis permits task schedules to slide (i.e. require more time than predicted). The amount of slack allowed by the task deadlines can be varied to achieve a desired performability. We are developing a tool that empirically calculates the performability for a task system with specified task profiles and reliability system components. <<ETX>>
Household Electricity Demand Forecast Based on Context Information and User Daily Schedule Analysis From Meter Data

The very short-term load forecasting (VSTLF) problem is of particular interest for use in smart grid and automated demand response applications. An effective solution for VSTLF can facilitate real-time electricity deployment and improve its quality. In this paper, a novel approach to model the very short-term load of individual households based on context information and daily schedule pattern analysis is proposed. Several daily behavior pattern types were obtained by analyzing the time series of daily electricity consumption, and context features from various sources were collected and used to establish a rule set for use in anticipating the likely behavior pattern type of a specific day. Meanwhile, an electricity consumption volume prediction model was developed for each behavior pattern type to predict the load at a specific time point in a day. This study was concerned with solving the VSTLF for individual households in Taiwan. The proposed approach obtained an average mean absolute percentage error (MAPE) of 3.23% and 2.44% for forecasting individual household load and aggregation load 30-min ahead, respectively, which is more favorable than other methods.
Mitigation of the Propagation of Localization Error Using Multi-Hop Bounding

In ad hoc position-location networks, location information is obtained through the sequential estimation of node locations. An unlocalized node can estimate its location based on range and location estimates of nearby localized (";anchor";) nodes, and subsequently provide range and location information to other unlocalized nodes in its vicinity. In such distributed location-estimation scenarios, the accuracy of node location estimates is degraded due to the propagation of localization errors, particularly in NLOS propagation environments. This paper discusses the use of a novel method of mitigating the propagation of localization error using the linear programming framework proposed by the authors in [1]. This method utilizes multi-hop distance estimates to create additional constraints on the feasible region for a node's location, thereby limiting the propagation of error even in NLOS propagation environments.
The Effect of Trust and Perceived Risk on Consumers' Online Purchase Intention

With the rapid growth of e-commerce in Taiwan, B2C domain of e-commerce has been the significant issue recently. According to the importance to understand and predict consumers’ online purchase intention. Based on the Technology Acceptance Model (TAM), this study aims to predict the consumers’ purchase intention by integrating trust and perceived risk into the model to empirically examine the impacts of key drivers. With 705 samples obtained from users of Yahoo! Kimo online vendor, this study applied the Structural Equation Model (SEM) to examine the proposed model. The results indicate that perceived ease of use (PEOU) and perceived usefulness (PU), trust, as well as perceived risk, significantly impact purchase intention. Moreover, trust significantly reduced perceived risk.
Impact of soil amendments on reducing phosphorus losses from runoff in sod.

Received for publication December 22, 2004. Research was initiated to study the interaction between soil amendments (lime, gypsum, and ferrous sulfate) and dissolved molybdate reactive phosphorus [RP(<0.45)] losses from manure applications from concentrated runoff flow through a sod surface. Four run-over boxes (2.2-m2 surface area) were prepared for each treatment with a bermudagrass [Cynodon dactylon (L.) Pers. ] sod surface (using sod blocks) and composted dairy manure was surface-applied at rates of 0, 4.5, 9, or 13.5 Mg ha-1. The three soil amendments were then applied to the boxes. Two 30-min runoff events were conducted and runoff water was collected at 10-min intervals and analyzed for RP(<0.45). Results indicated that the addition of ferrous sulfate was very effective at reducing the level of RP(<0.45). in runoff water, reducing RP(<0.45) from 1.3 mg L(-1) for the highest compost rate with no amendment to 0.2 mg L(-1) for the ferrous sulfate in the first 10 min of runoff. Lime and gypsum showed a small impact on reducing RP(<0.45), with a reduction in the first 10 min to 0.9 and 0.8 mg L(-1), respectively. The ferrous sulfate reduced the RP(<0.45) in the tank at the end of the first runoff event by 66.3% compared with no amendment. In the second runoff event, the ferrous sulfate was very effective at reducing RP(<0.45) in runoff, with no significant differences in RP(<0.45) with application of 13.5 Mg ha(-1) compost compared with no manure application. The results indicate that the addition of ferrous sulfate may greatly reduce RP(<0.45) losses in runoff and has considerable potential to be used on pasture, turfgrass, and filter strips to reduce the initial RP(<0.45) losses from manure application to the environment.
Does virtualization make disk scheduling passé?

We examine whether traditional disk I/O scheduling still provides benefits in a layered system consisting of virtualized operating systems and underlying virtual machine monitor. We demonstrate that choosing the appropriate scheduling algorithm in guest operating systems provides performance benefits, while scheduling in the virtual machine monitor has no measurable advantage. We propose future areas for investigation, including schedulers optimized for running in a virtual machine, for running in a virtual machine monitor, and layered schedulers optimizing both application level access and the underlying storage technology.
Does Poverty Increase the Risk of Social Isolation? Insights Based on Panel Data from Germany

ABSTRACT Sociological literature suggests a causal effect of poverty on the risk of social isolation. While previous research on this link is only based on cross-sectional data, this article presents more valid evidence for this assumption by applying fixed-effects regression methods and panel data (German Socio-economic Panel). First, the study shows that the poverty effect on isolation occurs regardless of time-constant unobserved heterogeneity. Second, it examines whether poverty and isolation are correlated because of a mutual association with critical life events (health deterioration, dissolutions of couple relationships, and job loss) that may increase both the risk for poverty and the risk for isolation. Regarding men, the effect of isolation on poverty is not attributable to the cited biographical transitions. Regarding women, it is only in part—but not in whole—attributable to dissolutions of couple relationships.
Conformational landscape and pathway of disulfide bond reduction of human alpha defensin

Human alpha defensins are a class of antimicrobial peptides with additional antiviral activity. Such antimicrobial peptides constitute a major part of mammalian innate immunity. Alpha defensins contain six cysteines, which form three well defined disulfide bridges under oxidizing conditions. Residues C3‐C31, C5‐C20, and C10‐C30 form disulfide pairs in the native structure of the peptide. The major tissue in which HD5 is expressed is the crypt of the small intestine, an anaerobic niche that should allow for substantial pools of both oxidized and (partly) reduced HD5. We used ion mobility coupled to mass spectrometry to track the structural changes in HD5 upon disulfide bond reduction. We found evidence of stepwise unfolding of HD5 with sequential reduction of the three disulfide bonds. Alkylation of free cysteines followed by tandem mass spectrometry of the corresponding partially reduced states revealed a dominant pathway of reductive unfolding. The majority of HD5 unfolds by initial reduction of C5‐C20, followed by C10‐C30 and C3‐C31. We find additional evidence for a minor pathway that starts with reduction of C3‐C31, followed by C5‐C20 and C10‐C30. Our results provide insight into the pathway and conformational landscape of disulfide bond reduction in HD5.
Excessive ovarian stimulation up-regulates the Wnt-signaling molecule DKK1 in human endometrium and may affect implantation: an in vitro co-culture study.

BACKGROUND High serum estradiol (E2) levels following ovarian stimulation lead to reduced implantation and pregnancy rates, yet the underlying mechanisms remain unknown. We investigated if aberrant expression of genes in the Wnt-signaling pathway may be involved. METHODS Microarray and real-time PCR analysis were performed to analyze gene expression profiles of endometrial samples taken at day hCG + 7 in stimulated cycles, and days LH + 7 and LH + 10 in natural cycles. Expression of several Wnt-signaling transcripts, including Dickkopf homolog 1 (DKK1), DKK2 and secreted frizzled-related protein 4 (sFRP4), was analyzed throughout the menstrual cycle. JAr spheroid/Ishikawa endometrial cell co-culture experiments were established to study effects of DKK1 on spheroid attachment in vitro. RESULTS We identified 351 differentially expressed genes. Endometrial samples taken at hCG + 7 had similar expression profiles to those at LH + 10. DKK1 transcripts were up-regulated and DKK2 and sFRP4 were down-regulated in the stimulated compared with LH + 7 group (all P < 0.05). DKK1 transcripts were low in proliferative phase (PS) and increased in late-secretory phase (LS, P < 0.05), although DKK2 peaked in mid-secretory phase (P < 0.05). sFRP4 transcripts were high in PS. Treatment of spheroid with recombinant human DKK-1 protein dose-dependently suppressed (P < 0.05 versus control) spheroids attachment onto endometrial cells (associated with decreased beta-catenin protein): this suppression was nullified by anti-DKK1 antibody. CONCLUSION Gene expression patterns in stimulated cycles resembled those of LS in natural cycles, when the implantation window is about to close, suggesting high serum E2 and/or progesterone concentrations may advance endometrial development, altering the implantation window and possibly decreasing pregnancy rate. Aberrant expression of DKK1 might impair embryo attachment and implantation in vivo.