Miracle-dz/UniFAR-FTUs huggingface dataset:
UvA-DARE ( Digital Academic Repository ) Evaluation of a FRET-peptide substrate to predict virulence in Pseudomonas aeruginosa

Pseudomonas aeruginosa produces a number of proteases that are associated with virulence and disease progression. A substrate able to detect P. aeruginosa-specific proteolytic activity could help to rapidly alert clinicians to the virulence potential of individual P. aeruginosa strains. For this purpose we designed a set of P. aeruginosaspecific fluorogenic substrates, comprising fluorescence resonance energy transfer (FRET)-labeled peptides, and evaluated their applicability to P. aeruginosa virulence in a range of clinical isolates. A FRET-peptide comprising three glycines (3xGly) was found to be specific for the detection of P. aeruginosa proteases. Further screening of 97 P. aeruginosa clinical isolates showed a wide variation in 3xGly cleavage activity. The absence of 3xGly degradation by a lasI knock out strain indicated that 3xGly cleavage by P. aeruginosa could be quorum sensing (QS)-related, a hypothesis strengthened by the observation of a strong correlation between 3xGly cleavage, LasA staphylolytic activity and pyocyanin production. Additionally, isolates able to cleave 3xGly were more susceptible to the QS inhibiting antibiotic azithromycin (AZM). In conclusion, we designed and evaluated a 3xGly substrate possibly useful as a simple tool to predict virulence and AZM susceptibility. Citation: Kaman WE, Arkoubi-El Arkoubi NE, Roffel S, Endtz HP, van Belkum A, et al. (2013) Evaluation of a FRET-Peptide Substrate to Predict Virulence in Pseudomonas aeruginosa . PLoS ONE 8(11): e81428. doi:10.1371/journal.pone. 0081428 Editor: Jamunarani Vadivelu, University of Malaya, Malaysia Received July 17, 2013; Accepted October 12, 2013; Published November 26, 2013 Copyright: © 2013 Kaman et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This research was funded by the European Community's Seventh Framework Programme FP7/2007-2013, TEMPOtest-QC, under grant agreement no. 241742 and an STW Valorisation Grant, TNO SBIR: Bacalyzer no. 16-001. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: AB is employed by BioMerieux. This does not alter the authors' adherence to all of the PLOS ONE policies on sharing data and materials. * E-mail: w.kaman@erasmusmc.nl
Using a Simple, Non Expensive In Vitro Model for Studying ChronicMyeloid Leukemia in Research Laboratories

Background: Chronic myeloid leukemia (CML) is the commonest neoplasm associated with a recurrent chromosomal aberration (fused bcr-abl gene on the Philadelphia chromosome), The current used methods for generating bcr-abl gene are very expensive and not feasible in labs with limited facilities. So this study aimed at using a simple, safe and non expensive method for generating bcr-abl gene to be used in CML researches. Methods: Bcr-abl expression was evaluated in two groups; umbilical cord blood CD34+HSCs (UCBCD34+HSCs) nucleofected with the P210pcDNA3 plasmid (n=5) and UCBCD34+HSCs nucleofected with the GFP-encoding plasmid (pMAX-GFP) (n=5). Then, neomycin (G418) antibiotic selection was done. Stable bcr-abl gene expression in G418 resistant P210pcDNA3 UCBCD34+HSCs clones, was evaluated through quantitative PCR analysis of the expression of interleukin one receptor accessory protein (IL1RAP) gene. IL1RAP gene is newly discovered to be expressed on the surface of bcr-abl positive cells. Results: G418 resistant P210pcDNA3 clones showed up to eleven-fold increase in IL1RAP gene expression compared to pMAX-GFP clones. Our results demonstrated how nucleofection of conventional plasmids is likely to induce gene expression in HSCs. Conclusion: This simple method of generating bcr-abl gene expressing CD34+ HSCs, shall open new revenues for chronic myeloid leukemia research especially in laboratories, not equipped for advanced and expensive cancer research. Furthermore IL1RAP over expression on the surface of bcr-abl +CD34+HSCs, could be used as indicator for successful stable bcr-abl expression.
Secure Processing On-Chip

Abstract : Providing security in embedded systems is in urgent needs while there are many challenges in both software and hardware sides that require further research to understand their implications. This paper discusses microarchitectural and compiler support to address a variety of vulnerabilities due to physical tampering, program behavior exploits, and digital rights management issues. We also advocate the need for protecting intellectual properties programmed in the growing number of FPGA-based embedded systems.
A Novel Spatial Multiplexing Architecture with Finite Rate Feedback

The V-BLAST (vertical Bell Labs layered space-time) architecture with equal rate and power per antenna and a fixed order of detection is known to suffer from poor performance; in a multi-input multi-output (MIMO) Rayleigh fading channel with Mt transmit antennas and Mr receive antennas (MrgesMt), the diversity order is only Mr-Mt+1. There are two remedies available, namely, (a) channel ordered detection at the receiver and (b) allocation of rates and powers at the transmitter. However, given independent coding/decoding at each layer, the diversity gain of V-BLAST even by applying these remedies is fundamentally upper bounded by Mr. In this paper, we show that the story would be dramatically different if the receiver is allowed to feed a few bits of channel state information (CSI) back to the transmitter. We develop an approach of jointly designed ordered detection at the receiver and rate/power allocation at the transmitter. Herein the receiver feeds back a finite number of bits (=log2(Mt! )) to the transmitter regarding the detection order. In particular, we propose what we call the Greedy ordering rate tailored V-BLAST (GRT-VB) scheme which, with independent coding/decoding on each layer, is shown to have the diversity-multiplexing (D-M) gain tradeoff which is close to the optimal one (e.g. it has the maximal diversity gain of MrMt). The simulation result validates the superior performance of the proposed scheme.
Supply Chain Network Economics: Dynamics of Prices, Flows and Profits

This text brings an economics perspective to the decision-making that happens in the management of supply chains. The author provides the foundations for the modeling of the interrelationships among decision-makers in supply chains. These models include both competition and cooperation and provide the resulting product flows and prices in the chains. The author begins with an introduction of the theoretical foundations, then applies the theory to energy supply chains in the form of electric power generation and distribution networks. Subsequent chapters cover environmental supply chain and financial networks with intermediation, dynamics under risk and uncertainty, power plant selection, reverse supply chain management and e-cycling. Throughout the book, the underlying thread is that of transportation networks and how the relationships between supply chain networks and the more-established theory of transportation network equilibria can be used for logistics.
A Computational Aid for Problem Formulation in Early Conceptual Design

Conceptual design is a high-level cognitive activity that draws upon distinctive human mental abilities. An early and fundamental part of the design process is problem formulation, in which designers determine the structure of the problem space they will later search. Although many tools have been developed to aid the later stages of design, few tools exist that aid designers in the early stages. In this paper, we describe Problem Formulator, an interactive environment that focuses on this stage of the design process. This tool has representations and operations that let designers create, visualize, explore, and reflect on their formulations. Although this process remains entirely under the user’s control, these capabilities make the system well positioned to aid the early stages of conceptual design. [DOI: 10.1115/1.4024714]
Towards a Resource-based Theory of Information Strategy

The central aim of this paper is to instigate the construction of a theory of information strategy based on the Resource-based View (RBV) of the firm (Barney, 1986, 1991; Penrose, 1959; Wernerfelt, 1984). Therefore, an initial theoretical framework is proposed within which such a theory could be developed further. In essence, this theoretical framework sheds light on how organizations can realize and sustain above-normal returns by either maintaining or solving information imperfections in factor and product markets. This explicit focus on information as a source of above-normal returns is reflected in a new type of rent, called InfoRent. Hence, information strategy can be conceived as a continuous search for InfoRent, analogous to the notion of strategy within the RBV (cf. Mahoney et al., 1992, p.364). First, the urge for constructing a theory of information strategy will be clarified. Subsequently, the appropriateness of the RBV as theoretical foundation for constructing such a theory will be discussed. Finally, the initial outline of a theoretical framework will be explained and empirical work that exemplifies the relevance and explanatory power of the theory are described shortly.
Navdriver: Adaptive Websites via SaaS

This paper describes Navdriver, a novel Software-as-a-Service technology capable of automatically inserting hyperlinks on subscribers' Web pages. Its functionality leverages hotlink assignment algorithms which have been a subject of study in the last decade. The focus of this paper is on describing the underpinnings of Navdriver from the point of view of its SaaS architecture and its interaction with subscribers' Web sites and their pages' visitors. The paper also presents lessons learned over the past five years since Navdriver was officially launched and deployed in live production websites. Navdriver is freely available and supports the most predominant Web browsers and Web technologies.
Opinion Mining of Sociopolitical Comments from Social Media

Opinions are central to almost all human activities by influencing greatly the decision making process. In this thesis, we present the problems of mining issues, extracting entities and suggestive opinions towards the entities, detecting thoughtful comments, and extracting stances and ideological expressions from online comments in the sociopolitical domain. This study is essential for opinion mining applications that are beneficial for policy makers, government sectors and social organizations. Much work has been done to try to uncover consumer sentiments from online comments to help businesses improve their products and services. However, sociopolitical opinion mining poses new challenges due to complex topic and sentiment expressions. We first present the problem of issue extraction from sociopolitical comments for which we propose an unsupervised approach based on latent variable methods for identifying and extracting the issues in the comments, and linking comments to the issues in the associated article. We evaluate our approach on political speeches and associated comments from social media. In the sociopolitical domain, users express their sentiments on the entities such as individuals or organizations. These sentiments are not only in the form of positive and negative expressions, but also in the form of suggestive opinions towards the entities. We present a new problem of extracting the entities and associated suggestive opinions. We propose a two-stage approach based on conditional random fields (CRF) and clustering for extracting and normalizing the entities and the associated suggestive opinions from the users. A key feature of social media is that it enables anyone to freely express his/her opinions. As a result of the large amount of online comments, there is an urge for extracting opinions which are highly valuable. In terms of thoughtful comment extraction, we study the task of extracting valuable comments from social media. We propose a supervised approach based on natural language processing and linguistics techniques to identify and extract valuable comments in the sociopolitical domain from social media. Users take positions/stances and express opinions towards controversial sociopolitical issues. We present the problem of extracting the topics, stances, and ideological expressions of users from their comments on ideological debates related to sociopolitical domain. We propose an unsupervised approach based on latent variable methods and evaluate on Debatepedia for identifying and extracting the positional words and entities associated with the issues. In summary, this thesis identifies a number of key problems in mining sociopolitical comments and proposes appropriate solutions to these problems.
A New Statistical Active Contour Model for Noisy Image Segmentation

This paper addresses the segmentation problem in noisy image based on Fast Edge Integration (FEI) method in active contour model (ACM) and proposes a new statistical active contour model (SACM). Two modifications are performed in FEI method. First, in order to handle noisy images, maximum log-likelihood estimation is used to replace the minimal variance term proposed by Chan and Vese. Second, a penalising term is employed to replace the time consuming re-initialization process. The proposed SACM is evaluated and compared with the existing ACM-based algorithms in terms of segmentation results and computational time. The proposed SACM outperforms existing methods and requires much less computational time.
Internet-Based Commerce : Implications for Rural Communities

Many have expressed concern about the “digital divide” that exists between various socioeconomic groups and places. Among those places currently lagging in the diffusion and use of advanced information technologies are rural communities. This paper presents a review of available literature and considers the prospects and implications of the rural digital divide. Rural economic characteristics, telecommunications infrastructure, and leadership capacity are evaluated in light of the emerging information-intensive economic realities. Challenges for the rural public sector also are considered, given the growth of electronic commerce and what it may mean to rural public finance. Finally, adaptive strategies are outlined to help close the information technology gap that exists for many rural communities. Those who are concerned about rural economic viability must consider a broader framework of what it means to be competitive in an economy increasingly dependent on advanced information technologies. We need to move beyond emphasis on electronic commerce and Internet tax policy to a fuller range of concerns including strengthening human and institutional capacities and improving access and infrastructure. To remain economically viable, rural communities will require both access and the capacity to utilize technology for a broad range of applications related to learning, institution building, community organization, and services delivery as well as economic uses.
Learning light transport the reinforced way

We introduce a rendering algorithm that is as simple as a path tracer but dramatically improves light transport simulation and even outperforms the Metropolis light transport algorithm. The underlying method of importance sampling learns where radiance is coming from and in fact coincides with reinforcement learning. The cost for the improvement is a data structure similar to irradiance volumes as used in realtime games.
Towards Bin Packing (preliminary problem survey, models with multiset estimates)

The paper described a generalized integrated glance to bin packing problems including a brief literature survey and some new problem formulations for the cases of multiset estimates of items. A new systemic viewpoint to bin packing problems is suggested: (a) basic element sets (item set, bin set, item subset assigned to bin), (b) binary relation over the sets: relation over item set as compatibility, precedence, dominance; relation over items and bins (i.e., correspondence of items to bins). A special attention is targeted to the following versions of bin packing problems: (a) problem with multiset estimates of items, (b) problem with colored items (and some close problems). Applied examples of bin packing problems are considered: (i) planning in paper industry (framework of combinatorial problems), (ii) selection of information messages, (iii) packing of messages/information packages in WiMAX communication system (brief description).
ASSESSING FOREST GAP DYNAMICS AND GROWTH USING MULTI-TEMPORAL LASER-SCANNER DATA

Research on lidar change detection is at its inception with a few studies to monitor coastal erosion and almost none for forest dynamics. While long-term installations and dendrochronology are cost and time intensive, this study highlights potential use of multi-temporal medium density lidar data for studying forest dynamics in a spatially explicit manner, particularly in identifying new canopy gaps and assessing height growth. It also underlines some of the challenges of co-registering multi-temporal lidar datasets, working with large differences in return densities, and developing methodological approaches to compute growth. Two laser-scanner datasets, acquired in 1998 and 2003 over a 6 km area of the mixed boreal forest in Quebec, Canada, were analysed. After coregistration, an automated method to accurately identify new gaps was developed which showed an overall accuracy of 96% when compared with high resolution images. Mean gap size, gap density and rate of gap openings have been in accordance with the reported statistics for the boreal forests. Forest growth was assessed by comparing various lidar statistics for hardwoods and softwoods in three height classes. The measured growth was in general consistent with expected height growth for the concerned species, however, improvements will be needed to increase the accuracy and reliability of results.
Evaluating the Operations Underlying Multisensory Integration in the Cat Superior Colliculus

It is well established that superior colliculus (SC) multisensory neurons integrate cues from different senses; however, the mechanisms responsible for producing multisensory responses are poorly understood. Previous studies have shown that spatially congruent cues from different modalities (e.g., auditory and visual) yield enhanced responses and that the greatest relative enhancements occur for combinations of the least effective modality-specific stimuli. Although these phenomena are well documented, little is known about the mechanisms that underlie them, because no study has systematically examined the operation that multisensory neurons perform on their modality-specific inputs. The goal of this study was to evaluate the computations that multisensory neurons perform in combining the influences of stimuli from two modalities. The extracellular activities of single neurons in the SC of the cat were recorded in response to visual, auditory, and bimodal visual-auditory stimulation. Each neuron was tested across a range of stimulus intensities and multisensory responses evaluated against the null hypothesis of simple summation of unisensory influences. We found that the multisensory response could be superadditive, additive, or subadditive but that the computation was strongly dictated by the efficacies of the modality-specific stimulus components. Superadditivity was most common within a restricted range of near-threshold stimulus efficacies, whereas for the majority of stimuli, response magnitudes were consistent with the linear summation of modality-specific influences. In addition to providing a constraint for developing models of multisensory integration, the relationship between response mode and stimulus efficacy emphasizes the importance of considering stimulus parameters when inducing or interpreting multisensory phenomena.
Generating Synchrony from the Asynchronous: Compensation for Cochlear Traveling Wave Delays by the Dendrites of Individual Brainstem Neurons

Broadband transient sounds, such as clicks and consonants, activate a traveling wave in the cochlea. This wave evokes firing in auditory nerve fibers that are tuned to high frequencies several milliseconds earlier than in fibers tuned to low frequencies. Despite this substantial traveling wave delay, octopus cells in the brainstem receive broadband input and respond to clicks with submillisecond temporal precision. The dendrites of octopus cells lie perpendicular to the tonotopically organized array of auditory nerve fibers, placing the earliest arriving inputs most distally and the latest arriving closest to the soma. Here, we test the hypothesis that the topographic arrangement of synaptic inputs on dendrites of octopus cells allows octopus cells to compensate the traveling wave delay. We show that in mice the full cochlear traveling wave delay is 1.6 ms. Because the dendrites of each octopus cell spread across approximately one-third of the tonotopic axis, a click evokes a soma-directed sweep of synaptic input lasting 0.5 ms in individual octopus cells. Morphologically and biophysically realistic, computational models of octopus cells show that soma-directed sweeps with durations matching in vivo measurements result in the largest and sharpest somatic EPSPs. A low input resistance and activation of a low-voltage-activated potassium conductance that are characteristic of octopus cells are important determinants of sweep sensitivity. We conclude that octopus cells have dendritic morphologies and biophysics tailored to accomplish the precise encoding of broadband transient sounds.
An Artificial Intelligence System to Predict Quality of Service in Banking Organizations

Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly competitive sectors where similar services exist. In this paper, focusing on banking sector, we propose an artificial intelligence system for building a model for the prediction of service quality. While the traditional approach used for building analytical models relies on theories and assumptions about the problem at hand, we propose a novel approach for learning models from actual data. Thus, the proposed approach is not biased by the knowledge that experts may have about the problem, but it is completely based on the available data. The system is based on a recently defined variant of genetic programming that allows practitioners to include the concept of semantics in the search process. This will have beneficial effects on the search process and will produce analytical models that are based only on the data and not on domain-dependent knowledge.