Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Pili and Polysaccharide in adherence of Pseudomonas aeruginosa to mammalian epithelial cells ايرتكب قاصتلاب ديركسلا ديدعو بادھلاارود Pseudomonas aeruginosa ةيئلاطلا ايلاخلاب

dherence capability of Pseudomonas aeruginosa isolated from Iraqi patients was tested in accordance to their capability to adhere to epithelial cells. A range of adherence ability was found: The highest capacity with mean number of adhering bacteria of (13.5) was noticed. A sparse content or alginate was detected in these isolates analysis of pilin protein isolated from cultures exposed to ciprofloxacin antibiotic at sub MIC, level using polyacrylamide gel electrophoresis indicated that treatment of cells with /4 MIC show highest activity as compared with others. Results of protein profile followed the same trend of that in adhesion experiment which allows hypothesizing that these isolates are piliated, not mucous. تسملا لخ ص ايرتكبل قاصتللاا ةيلباق تربتخا Pseudomonas aeruginosa نويقارع ىضرمل تانيع نم ةلوزعملا ةيئلاطلا ايلاخلاب قاصتلال اھتيلباق ىلع ادامتعا . ول ح تلازعلا نيب قاصتللاا ىلع ةردقلا نم عساو ىدم ظ قاصتلا طسوتمب ] 5 , 13 [ ةيمك ىلع ىوتحت اھناب دجو ديركسلا ديدع نم تلازعلا ىوتحم ديدحتلو. ةيئلاط/ةيلخ ةطبثم زيكارتب نيساكولفوربيسلا ىتايحلا داضملاب ةلماعم عرازمل بادھلاا تانيتورب ليلحتب نكل. هنم ةليئض ت ح ت ىندلاا دحلا ركلاا ددعتم ملاھ ليحرت مادختسابو ي ناب دجو دياما ل 4 / 3 لا زيكرتلا تحت طبثم دحلا ىندلاا طعي ي زيكارتلا ىقاب عم ةنراقم ةيطيبثت ةيلاعف ىلعا . امم بدھتلا ةليلق هل ةضرعملا ايلاخلا ناب لباقملاب رھظ ةجزل ريغ ةبدھم ايلاخلا هذھ ناب داقتعلال انعفدي . Introduction: Adhesion is considered as important step for colonization of pathogens to living tissue and hence facilitates development of diseases. Infections, such as burns, wounds, urinary tract infection, Otitis externa and respiratory tract infections caused by Pseudomonas aeruginosa started by adhesion of microbes to cells of selected tissues which then increase the severity of infections and aggressiveness of the pathogen. Accordingly, adhesion is categorized as a major virulence factor concerning this bacteria [1 ] . Adherence of Pseudomonad to epithelial cells was found associated with the presence of surface components identified as either pili or / and cxopolysaccharide characterized as alginate [2,3] However, other investigators dout the role of pili in adhesion since non-piliated strains of P. aeruginosabind to the same receptors specified for piliated strains. They concluded that pili have indirect role in carrying adhesion molecules and function in correct presentation of the adherent bacteria to receptors on the cells[4]. The aim of this work is to study the role of pili and polysaccharide in adherence of P. aeruginosa to human mouth cavity epithelial cells. A Journal of Biotechnology Research Center (special edition) Vol.4 No.1 2010
RNA-silencing nanoprobes for effective activation and dynamic imaging of neural stem cell differentiation

To achieve the clinical potential of neural stem cells (NSCs), it is crucial to activate NSC differentiation into neurons and simultaneously monitor the process of NSC differentiation. However, there are many challenges associated with regulating and tracking NSC differentiation. Methods: We developed a redox-responsive multifunctional nanocomplex with a disulfide bond—cvNC—for the delivery of siRNAs to induce NSC differentiation through sequence-specific RNA interference (RNAi) and real-time imaging of sequential mRNA expression during differentiation. The stability and specificity of cvNCs were studied in vitro. Controlled release of siRNA, gene silencing efficiency, as well as real-time imaging of cvNCs on Tubb3 and Fox3 mRNAs during NSC differentiation were evaluated. Results: The introduction of a redox-sensitive disulfide bond not only ensures the remarkable performance of cvNC, such as high stability, controlled siRNA release, and enhanced gene silencing efficiency, but also effectively stimulates NSC differentiation into neurons. More importantly, the cvNC can track NSC differentiation in real-time by monitoring the sequential expression of mRNAs. Conclusion: Our study indicates that cvNC can serve as a robust system for exploring NSCs differentiation process as well as other biological events in living cells.
Learning semantic relationships between words in distributional semantics

Many works on extracting hyponymy relationships between words focus on noun pairs, such as animal and dog. Due to its difficulty, identifying hyponym pairs of verbs has been a big challenge. Yet, the task is vital in various natural language processing tasks like inference and paraphrase. In this paper, I aim to identify hyponymy relations between verb pairs, such as acquire and purchase. By clustering a verb’s direct objects and representing them with normal distribution, given verb pairs were effectively compared. The result shows a high potential of the novel method in hyponym identification of verb pairs.
A P ] 9 J ul 2 01 9 Recurrent Solutions of a Nonautonomous Modified Swift-Hohenberg Equation

We consider recurrent solutions of the nonautonomous modified Swift-Hohenberg equation ut +∆ u+ 2∆u+ au+ b|∇u| + u = g(t, x). We employ Conley index theory to show that, if the forcing g : R → L(Ω) is a recurrent function, then there are at least two recurrent solutions in H 0 (Ω) under appropriate assumptions on the parameters a, b and g.
C A ] 1 0 Ju l 2 01 9 On Ψ-Laplace transform method and its applications to Ψ-fractional differential equations

Motivated by some recent developments in Ψ-fractional calculus, in this paper some new properties and the uniqueness of Ψ-Laplace transform in the settings of Ψ-fractional calculus are established. The final goal of this research is to demonstrate the effectiveness of Ψ-Laplace transform for solving Ψ-fractional ordinary and partial differential equations.
Chitil , Olaf ( 2017 ) A Type Generic Definition for Debugging Lazy Functional Programs by Value Observation

Observing intermediate values helps to understand what is going on when your program runs. Gill presented an observation method for lazy functional languages that preserves the program’s semantics. However, users need to define for each type how its values are observed: a laborious task and strictness of the program can easily be affected. Here we define how any value can be observed based on the structure of its type by applying generic programming. Furthermore we present an extension to specify per observation point how much to observe of a value.
A COMPARATIVE STUDY ON CAMERA CALIBRATION ALGORITHMS

In the recent decade, buildings 3D models are in a high demand by many public and private organizations. The extraction procedure of high accuracy measurements from images is one of the principal tasks of close-range photogrammetry. The particular techniques used in buildings 3D models creation mostly require an accurate calibration process of metric or non-metric digital cameras. Over the years, there were developed many calibration algorithms by several authors, such as: Tsai, Heikkilä & Silven, Bakstein & Halir, Zhang, etc. This paper aims to present a comparison between the intrinsic calibration parameters determined using the Tsai calibration algorithm, respectively the Heikkilä & Silven algorithm and their influence on building 3D model accuracy. In order to obtain the results, the 3D model of the historical monument “Dosoftei House” from Iaşi-City was created, based on image – data acquired with the Nikon Coolpix L810 digital camera. The camera calibration process, was performed using a 3D calibration object and the two algorithms mentioned above.
The Alpha Solver for Lazy-Grounding Answer-Set Programming

The grounding bottleneck is a longstanding issue of Answer-Set Programming (ASP), a well-known Logic Programming formalism widely used for declarative problem solving. Lazy grounding as realized by the recent Alpha system avoids this grounding bottleneck but faces new challenges that are genuine to lazy grounding. This article ﬁrst gives an overview of lazy-grounding ASP solving by Alpha and provides information on how to obtain and use the system. It then presents research issues raised by lazy-grounding and overviews those which have been addressed already.
Algorithm for Encoding Time method for the Wavelet based Fractal Image Compression

In this paper we show the two implementations of fractal (Pure-fractal and Wavelet fractal image compression algorithms) which have been applied on the images in order to investigate the compression ratio and corresponding quality of the images using peak signal to noise ratio (PSNR). And in this paper we also set the threshold value for reducing the redundancy of domain blocks and range blocks, and then to search and match. By this, we can largely reduce the computing time. In this paper we also try to achieve the best threshold value at which we can achieve optimum encoding time.
Joint Inference of Concepts and Networks of Documents

Due to the growing number of publications, scientists face the problem of information overload. Getting an overview of a new research area, finding relevant related work, and grasping connections between different publications are essential but difficult tasks. Recent efforts have been directed towards the automatic discovery of structure in document collections that can help scientists orientate in a research domain. In this thesis, we investigate the problem of finding semantic relationships between documents based on their textual content. In particular, we take an epidemiological view of information diffusion. We assume that documents are connected in a graph of influence, and ideas travel over this graph from document to document. Knowledge of the graph could give valuable information about the relationship between documents and help a user navigate a document collection. Thus, we address the task of inferring a document influence graph. We track ideas by memes keywords, technical terms or short phrases of technical terminology that appear in the document text. Based on a model of the diffusion of memes, we address the task of recovering the document graph from the observations of many memes in the documents. In a further step, we develop a more realistic model in which the contagions are not simple memes but concepts sets of related memes that can mutate in the diffusion process. We present the DocNETINF algorithm to jointly infer concepts and the document network. By experiments on simulated data, we show that DocNETINF can recover ground truth graph and concepts better than baseline methods. We apply our algorithm to scientific papers from the CiteSeerX dataset. To this end, we describe a simple method to extract memes from the paper text. Finally, we present a demo application that allows to use the inferred graph and concepts for exploratory purposes. An anecdotal analysis gives the reader a flavor of the results.
Acting in Good Time – Conceptual Reflections on the Sequencing of Political Reform Processes

Thus far, the sequencing of political reform processes has been discussed on a separate basis in the context of different scientific debates. Existing analysis in macroeconomics and democracy theory focuses on shock-therapeutic versus gradual reform policies, the succession of specific reform steps or the right timing of reforms. An analytical approach to sequences has been elaborated. Theoretical concepts of social change, which refer to path dependence or the punctuated development of historical sequences, have evolved in the context of institutionalist research. The present article summarises the state of research and extends it with conceptual reflections on the motivation of sequential political action, which can then serve as a starting point for differentiation between sequencing processes in further research.
GENERATING INITIAL CONDITIONS FOR ENSEMBLE FORECASTS : MONTE-CARLO VS . DYNAMIC METHODS

Though ensemble forecasting has been operational in the U.S., Europe, and Canada for nearly a decade now, no clear consensus has yet evolved on the best feasible method for generating initial conditions for these ensemble forecasts. In principle, to be consistent with the underlying theory stemming from the Liouville equation (Ehrendorfer 1994), the samples, whether they are drawn randomly or non-randomly, should reflect the probability distribution of plausible analysis states. However, analysis error statistics are highly flow-dependent, and generating such flow-dependent sets of initial conditions is at best computationally very expensive. As a consequence, each of the operational centers have embraced different approaches. The European Centre for Medium-Range Weather Forecasts (ECMWF) have used “singular vector” perturbations (Molteni et al. 1996); the National Centers for Environmental Prediction (NCEP) use a “breeding” method (Toth and Kalnay 1993, 1997); and at the Canadian Meteorological Centre (CMC), a “perturbed observation” 3-dimensional variational assimilation (3D-Var) approach is used (Houtekamer et al. 1996). All of these methods can only approximate generating samples from the distribution of analysis states. In the case of ECMWF’s singular vectors, in principle the initial norm used to measure the size and structure of perturbations should be a flow-dependent analysis-error covariance norm (“AEC”; more later on this); lacking that, ECMWF uses an initial total-energy norm. For NCEP’s breeding method, perturbations are grown and rescaled each analysis cycle, their rescaled size consistent with time-averaged analysis error statistics. Hence, there is limited freedom for them to fully reflect the flow-dependent uncertainty. The CMC perturbed initial conditions, as shown in Hamill et al. (2000) can potentially do a good job of reflecting situational analysis errors, but some compromises are made operationally to lower the computational cost at the expense of some flow dependency.
Competitive Algorithms for Online Conversion Problem with Interrelated Prices

The classical uni-directional conversion algorithms are based on the assumption that prices are arbitrarily chosen from the fixed price interval [m,M] where m and M represent the estimated lower and upper bounds of possible prices 0 < m <= M. The estimated interval is erroneous and no attempts are made by the algorithms to update the erroneous estimates. We consider a real world setting where prices are interrelated, i.e., each price depends on its preceding price. Under this assumption, we derive a lower bound on the competitive ratio of randomized non-preemptive algorithms. Motivated by the fixed and erroneous price bounds, we present an update model that progressively improves the bounds. Based on the update model, we propose a non-preemptive reservation price algorithm RP* and analyze it under competitive analysis. Finally, we report the findings of an experimental study that is conducted over the real world stock index data. We observe that RP* consistently outperforms the classical algorithm.
Appropriateness of Neural Networks in Climate Prediction and Interpolations: A Comprehensive Literature Review

To be familiar with appropriateness of Neural Network in climate prediction and spatial interpolation, e comprehensive literature review of past 50 years is done and offered in this paper. And it is established that Neural Network such as BPN, RBF is best appropriate to be predicted chaotic behavior of climate variables like rainfall, rainfall runoff, and have efficient enough for prediction in long period. It is also found that Neural Network is significant for spatial interpolation of mean climate
Making sense of studying games : using sensemaking as a perspective for game research

The study of games as research objects occurs in a vacuum. In this paper a possible theoretical perspective is explored that can be used to fill up this void. This perspective is based on theories of sensemaking. It is argued that the general properties of these theories have a natural fit with the characteristics of games, making sensemaking a potentially valuable perspective. The paper further outlines the implications of using sensemaking as a perspective for game research.
How to bring HTTPS to the masses ? Measuring issuance in the first year of Let ’ s Encrypt

The World Wide Web is the most popular application of the Internet. Pervasive monitoring affects its users by compromising the confidentiality of their communications. Even where the encryption technology is available to mitigate pervasive monitoring, technical complexity and adverse economic incentives have delayed its widespread deployment. As a result, the bulk of the Web and its users remain powerless against this threat. The question is: how to bring HTTPS to the masses? In a case study, we examine efforts by the certificate authority Let’s Encrypt to address both technical complexity and financial barriers to widespread deployment. We evaluate who has been using Let’s Encrypt in the first year since its inception. To gauge its contribution to the democratization of encryption technology on the Web, we measure growth in domain coverage, adoption by popular and large versus small players, the type of adopters and their perseverance. We find a lower bound of 2% global coverage on the monthly use of Let’s Encrypt aggregated at second level domains. Dominant driver of this growth are hosting companies (68%), in particular those bulk certifying domains of their users (3 companies cover 47%). It is exactly these companies, serving numerous, smaller customers that would otherwise not enable the use of encryption by their visitors. The approach pursued by Let’s Encrypt in its first year of operation is worthy of broader consideration and adoption in the industry. Though issuing for free will not fit the majority of business models, the adoption of its advances in automation may prove pivotal to bring HTTPS to the masses. For security problems more generally, taking a market approach to deploy technical mitigations may be well worth future consideration.
Periodica Polytechnica Chemical Engineering Pharmaceutical and Macromolecular Technologies in the Spirit of Industry 4 . 0

Well designed (multilayer, adaptive, reactive) interphases, being a key element of multicomponent structures, could be tailored to different requirements through controlled technologies. This is the link connecting various green, safe, healthy materials and innovative pharmaceuticals. Upgraded recycling could be performed by interfacial consolidation of self-reinforced composites, the flame retardancy of which is feasible with surprisingly low amount of flame retardant. Examples are shown how the reinforced and foamed forms of thermosetting and thermoplastic biopolymers can play a significant role (after flame retardant modification) in the development of airplanes and electric cars. Biopolymer nanofibres, such as polycaprolactone and polyhydroxybutyrate, could be formed with increased productivity for various medical uses. Raman-based control of the units of integrated continuous technologies has been elaborated including controlled formation of crystals with polymer interlayer for direct tableting.
Finger and gesture recognition with Microsoft Kinect

The Kinect is a cheap and wildly spread sensor array with some interesting features, such as a depth sensor and full body skeleton tracking. The Kinect SDK does not support nger tracking; We have therefore created algorithms to nd nger positions from depth sensor data. With the detected nger position we use dynamic time warping to record and recognize nger gestures. We have created an API that can record and recognize nger gestures. The API was created with focus on ease of use and the possibility to customize and change core algorithms. Even the Kinect can be changed for other similar devices. This opens up a new eld of applications utilizing the Kinect and nger gestures.
Universal Dependencies for Danish

The Universal Dependencies (UD) project aims at developing treebank annotations consistent across many languages. In this paper, we present the conversion of the Copenhagen Dependency Treebank (CDT) into Universal Dependencies (UD). We describe the original CDT annotation and detail the mapping into the new UD formalism, which we accomplish by taking a test-driven approach. We present parsing experiments with both formalisms. Additionally, we quantitatively compare the resulting Danish UD treebank to the other languages available in the UD project (v1.2), discussing constructions that are specific to Danish. Our results show that the newly created Danish UD treebank is closely related to treebanks of typologically similar languages. However, parsing with the new treebank becomes more difficult, relative to the old formalism.
0 61 10 57 v 3 1 0 M ar 2 00 8 Dividing Quantum Channels

We investigate the possibility of dividing quantum channels into concatenations of other channels, thereby studying the semigroup structure of the set of completely-positive trace-preserving maps. We show the existence of ‘indivisible’ channels which can not be written as non-trivial products of other channels and study the set of ‘infinitesimal divisible’ channels which are elements of continuous completely positive evolutions. For qubit channels we obtain a complete characterization of the sets of indivisible and infinitesimal divisible channels. Moreover, we identify those channels which are solutions of time-dependent master equations for both positive and completely positive evolutions. For arbitrary finite dimension we prove a representation theorem for elements of continuous completely positive evolutions based on new results on determinants of quantum channels and Markovian approximations.
Post 2013 2019 Proof-of-familiarity : A privacy-preserved blockchain scheme for collaborative medical decision-making

The current healthcare sector is facing difficulty in satisfying the growing issues, expenses, and heavy regulation of quality treatment. Surely, electronic medical records (EMRs) and protected health information (PHI) are highly sensitive, personally identifiable information (PII). However, the sharing of EMRs, enhances overall treatment quality. A distributed ledger (blockchain) technology, embedded with privacy and security by architecture, provides a transparent application developing platform. Privacy, security, and lack of confidence among stakeholders are the main downsides of extensive medical collaboration. This study, therefore, utilizes the transparency, security, and efficiency of blockchain technology to establish a collaborative medical decision-making scheme. This study considers the experience, skill, and collaborative success rate of four key stakeholders (patient, cured patient, doctor, and insurance company) in the healthcare domain to propose a local reference-based consortium blockchain scheme, and an associated consensus gathering algorithm, proof-of-familiarity (PoF). Stakeholders create a transparent and tenable medical decision to increase the interoperability among collaborators through PoF. A prototype of PoF is tested with multichain 2.0, a blockchain implementing framework. Moreover, the privacy of identities, EMRs, and decisions are preserved by two-layer storage, encryption, and a timestamp storing mechanism. Finally, superiority over existing schemes is identified to improve personal data (PII) privacy and patient-centric outcomes research (PCOR).