Miracle-dz/UniFAR-FTUs huggingface dataset:
In Vitro Selection of Single-Stranded DNA Molecular Recognition Elements against S. aureus Alpha Toxin and Sensitive Detection in Human Serum

Alpha toxin is one of the major virulence factors secreted by Staphylococcus aureus, a bacterium that is responsible for a wide variety of infections in both community and hospital settings. Due to the prevalence of S. aureus related infections and the emergence of methicillin-resistant S. aureus, rapid and accurate diagnosis of S. aureus infections is crucial in benefiting patient health outcomes. In this study, a rigorous Systematic Evolution of Ligands by Exponential Enrichment (SELEX) variant previously developed by our laboratory was utilized to select a single-stranded DNA molecular recognition element (MRE) targeting alpha toxin with high affinity and specificity. At the end of the 12-round selection, the selected MRE had an equilibrium dissociation constant (Kd) of 93.7 ± 7.0 nM. Additionally, a modified sandwich enzyme-linked immunosorbent assay (ELISA) was developed by using the selected ssDNA MRE as the toxin-capturing element and a sensitive detection of 200 nM alpha toxin in undiluted human serum samples was achieved.
Programmed PWM techniques to eliminate harmonics - A critical evaluation

The authors establish the superiority of programmed PWM (pulsewidth modulation) techniques over the conventional carrier-modulated PWMs and provide a critical evaluation of the programmed PWM schemes applied to single and three-phase inverters, thereby providing the framework and guidelines for the selection of the appropriate technique for each application area. Evaluation criteria include harmonic loss factor and total harmonic distortion factors defined at the input and output of the inverter terminals. A simple low-cost solution for obtaining the required PWM switching points is proposed. Selected results are verified experimentally. <<ETX>>
Implementation of Parallel Fast Hartley Transform (FHT) Using Cuda

Implementation of Fast Hartley Transform in parallel manner on Graphics Processing Unit, using CUDA technology is presented in this paper. Calculating FHT in parallel, using multiple threads, gives us huge improvement in calculation speed. Developed CUDA based parallel algorithm, which experimental results compared with results of CPU based sequential algorithm. Edge detection algorithms can be speed up for large images, performing in frequency domain. Here experiments are done on various edge detection filters and different image sizes, using fast Hartlay transform.
High-Frequency Characteristic Fluctuations of Nano-MOSFET Circuit Induced by Random Dopants

As the dimension of semiconductor device shrunk into nanometer scale (nanoscale), characteristic fluctuation is more pronounced, and become crucial for circuit design. In this paper, discrete-dopant-induced characteristic fluctuation of 16-nm-gate metal-oxide-semiconductor field effect transistors (MOSFET) circuit under high-frequency regime is quantitatively studied. The circuit gain, the 3 dB bandwidth and the unity-gain bandwidth of the tested nanoscale transistor circuit are calculated concurrently capturing the discrete-dopant-number- and discrete- dopant-position-induced fluctuations in the large-scale statistically sound ldquoatomisticrdquo device/circuit coupled simulation. For the 16-nm-gate MOSFET circuit, the number of discrete dopants, varying from zero to 14, may result in 5.7% variation of the circuit gain, 14.1% variation of the 3 dB bandwidth, and 10.4% variation of the unity-gain bandwidth. To suppress the high-frequency characteristic fluctuations, an improved doping distribution along the longitudinal diffusion direction from the MOSFET's surface to substrate is further performed to examine the associated fluctuation. The improved vertical doping profile with less dopants locating near surface of channel effectively reduces the fluctuations of the circuit gain, the 3 dB bandwidth and the unity-gain bandwidth dramatically. Compared with the original doping profile, the reduction is 32.3%, 19.4% and 51.8%, respectively. This study provides an insight into random-dopant-induced intrinsic high-frequency characteristic fluctuations and verifies the potential fluctuation suppression technique on high-frequency characteristic fluctuations of nanoscale transistor circuit.
Recognizing the languages in WebPages — A framework for NLP

In this paper we describe an experimental system using java programming language which demonstrates a variety of application level tradeoffs available to distributed NLP applications. In this paper, we proposed language identification system with N-gram-based matching for document retrieval. By using a well known N-gram based algorithm for automatic language identification, we construct a system that dynamically adds language labels for whole documents or text fragments.
An evaluation of methods to determine the porosity of calcium phosphate cements.

The porosity of a material can be determined using a diversity of methods; however, the results from these methods have so far not been compared and analyzed for calcium phosphate cements (CPCs). The aim of this study was to compare a fast and easy method for porosity measurements with some commonly used porosity methods for CPCs. The investigated method is based on the assumption that when a wet cement sample is dried, the volume of the evaporated water is equal to the volume of pores within the cement. Moreover, different methods of drying the cements were evaluated for acidic CPCs. The results showed that drying at room temperature (22 ± 1°C) is preferable, since a phase transformation was observed at higher temperatures. The results also showed that drying for 24 h in vacuum was sufficient to achieve water-free cements. The porosity measured was found to vary between the porosity methods evaluated herein, and to get a complete picture of a cement's porosity more than one method is recommended. Water evaporation, is, however, a fast and easy method to estimate the porosity of CPCs and could simplify porosity measurements in the future.
Linking Objects and their Stories: An API For Exploring Cultural Heritage Using Formal Concept Analysis

In this paper, we describe a distributed systems and Web Services Architecture that supports a content management and collaborative tagging system for a Web- based cultural heritage site. The site uses Formal Concept Analysis to infer semantic associations between objects and drive the navigation of its collection, and we promote an extension of its capability by rendering such functionality via Web Services. The Web Services architecture supports a system called the Virtual Museum of the Pacific - a content and knowledge acquisition tool that permits the machine synthesis of formal concepts and provides a Rich Internet Application in which to display and navigate them. The Web Services also permit the extensible association of digital objects by inducing new attributes and relationships from museum meta-data, and allows for the ability for users and stakeholders to upload, annotate and attach rich media, YouTube or Vimeo links, and voice narratives to the objects. By rendering these capabilities as an open API, we encourage a connected and open approach to the sharing of cultural heritage and provide platform for further research and development - making our application well suited for mobile devices, Web-based mashups, and data exchange between collection databases.
A Simulation-Based Algorithm for Ergodic Control of Markov Chains Conditioned on Rare Events

We study the problem of long-run average cost control of Markov chains conditioned on a rare event. In a related recent work, a simulation based algorithm for estimating performance measures associated with a Markov chain conditioned on a rare event has been developed. We extend ideas from this work and develop an adaptive algorithm for obtaining, online, optimal control policies conditioned on a rare event. Our algorithm uses three timescales or step-size schedules. On the slowest timescale, a gradient search algorithm for policy updates that is based on one-simulation simultaneous perturbation stochastic approximation (SPSA) type estimates is used. Deterministic perturbation sequences obtained from appropriate normalized Hadamard matrices are used here. The fast timescale recursions compute the conditional transition probabilities of an associated chain by obtaining solutions to the multiplicative Poisson equation (for a given policy estimate). Further, the risk parameter associated with the value function for a given policy estimate is updated on a timescale that lies in between the two scales above. We briefly sketch the convergence analysis of our algorithm and present a numerical application in the setting of routing multiple flows in communication networks.
The Design and Use of Interactive Visualization Applets for Teaching Ciphers

Cryptography is a fundamental topic in an information assurance curriculum. Students should understand the basic concepts and weaknesses of both historical and current cipher algorithms. Visualization tools can help students understand these concepts, both in the classroom and as out-of-class exercises. This paper describes a set of such tools designed for a cryptography course at the United States Air Force Academy. The design goals, implementation details, and classroom experiences are addressed
Sensitivity and Specificity of Soluble Triggering Receptor Expressed on Myeloid Cells-1, Midregional Proatrial Natriuretic Peptide and Midregional Proadrenomedullin for Distinguishing Etiology and to Assess Severity in Community-Acquired Pneumonia

Study Design This study aimed to evaluate the diagnostic accuracy of soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), midregional proatrial natriuretic peptide (MR-proANP) and midregional proadrenomedullin (MR-proADM) to distinguish bacterial from viral community-acquired pneumonia (CAP) and to identify severe cases in children hospitalized for radiologically confirmed CAP. Index test results were compared with those derived from routine diagnostic tests, i.e., white blood cell (WBC) counts, neutrophil percentages, and serum C-reactive protein (CRP) and procalcitonin (PCT) levels. Methods This prospective, multicenter study was carried out in the most important children’s hospitals (n = 11) in Italy and 433 otherwise healthy children hospitalized for radiologically confirmed CAP were enrolled. Among cases for whom etiology could be determined, CAP was ascribed to bacteria in 235 (54.3%) children and to one or more viruses in 111 (25.6%) children. A total of 312 (72.2%) children had severe disease. Results CRP and PCT had the best performances for both bacterial and viral CAP identification. The cut-off values with the highest combined sensitivity and specificity for the identification of bacterial and viral infections using CRP were ≥7.98 mg/L and ≤7.5 mg/L, respectively. When PCT was considered, the cut-off values with the highest combined sensitivity and specificity were ≥0.188 ng/mL for bacterial CAP and ≤0.07 ng/mL for viral CAP. For the identification of severe cases, the best results were obtained with evaluations of PCT and MR-proANP. However, in both cases, the biomarker cut-off with the highest combined sensitivity and specificity (≥0.093 ng/mL for PCT and ≥33.8 pmol/L for proANP) had a relatively good sensitivity (higher than 70%) but a limited specificity (of approximately 55%). Conclusions This study indicates that in children with CAP, sTREM-1, MR-proANP, and MR-proADM blood levels have poor abilities to differentiate bacterial from viral diseases or to identify severe cases, highlighting that PCT maintains the main role at this regard.
Bandwidth and Gain Enhancement of Microstrip Patch Antennas Using Reflective Metasurface

Bandwidth and gain enhancement of microstrip patch antennas (MPAs) is proposed using reflective metasurface (RMS) as a superstrate. Two different types of the RMS, namely- the double split-ring resonator (DSR) and double closed-ring resonator (DCR) are separately investigated. The two antenna prototypes were manufactured, measured and compared. The experimental results confirm that the RMS loaded MPAs achieve high-gain as well as bandwidth improvement. The desinged antenna using the RMS as a superstrate has a high-gain of over 9.0dBi and a wide impedance bandwidth of over 13%. The RMS is also utilized to achieve a thin antenna with a cavity height of 6 mm, which is equivalent to λ/21 at the center frequency of 2.45GHz. At the same time, the cross polarization level and front-to-back ratio of these antennas are also examined.
Texture Analysis and Characteristic Identification about Plaque Tissues of IVUS

Intravascular ultrasound can provide clear real-time cross-sectional images, including lumen and plaque. In practice, to identify the plaques tissues in different pathological changes is very important. However, the grayscale differences of them are not so apparent. In this paper a new textural characteristic space vector was formed by the combination of Co-occurrence Matrix and fraction methods. The vector was projected to the new characteristic space after multiplied by a projective matrix which can best classify those plaques according to the Fisher linear discriminant. Then the classification was completed in the new vector space. Experimental results found that the veracity of this classification could reach up to 88%, and it would be an accessorial tool for doctors to identify each plaque.
Influence of outliers on QTL mapping for complex traits

A method was proposed for the detection of outliers and influential observations in the framework of a mixed linear model, prior to the quantitative trait locus (QTL) mapping analysis. We investigated the impact of outliers on QTL mapping for complex traits in a mouse BXD population, and observed that the dropping of outliers could provide the evidence of additional QTL and epistatic loci affecting the 1stBrain-OB and the 2ndBrain-OB in a cross of the abovementioned population. The results could also reveal a remarkable increase in estimating heritabilities of QTL in the absence of outliers. In addition, simulations were conducted to investigate the detection powers and false discovery rates (FDRs) of QTLs in the presence and absence of outliers. The results suggested that the presence of a small proportion of outliers could increase the FDR and hence decrease the detection power of QTLs. A drastic increase could be obtained in the estimates of standard errors for position, additive and additive×environment interaction effects of QTLs in the presence of outliers.
Education, Ethnicity and Reproductive Practice in Cameroon

On observe souvent que les femmes instruites ont moins d’enfants que les femmes moins instruites, ce qui appelle une interpretation en termes de lien de cause a effet. Toutefois, les femmes instruites different de bien d’autres facons des femmes n’ayant jamais frequente l’ecole : les deux facteurs sont lies de facon multiple. Le present article analyse la relation entre instruction et fecondite dans le Cameroun d’aujourd’hui en tant que phenomene a la fois statistique et social, a l’aide de donnees tirees de l’enquete demographique et de sante (EDS) de 1998 au Cameroun, ainsi que des donnees ethnographiques collectees sur le terrain par l’auteur. Ces donnees montrent que les femmes camerounaises instruites se marient plus tardivement et ont moins d’enfants que leurs consœurs non instruites, conformement a des schemas deja etablis. Toutefois, les femmes instruites ont des taux de fecondite prenuptiale annuelle plus eleves que les femmes non instruites, contrairement a ce que predisent la plupart des modeles causaux. Il est affirme ici que ces schemas statistiques resultent du niveau eleve de la selectivite de l’acces a l’ecole. Les filles instruites viennent de communautes plus tolerantes a l’egard des relations sexuelles prenuptiales, qui accordent une plus grande importance au developpement de la personnalite de l’individu, et un role moins primordial au mariage. Ensemble, ces differences sociales ont autant d’importance que l’instruction sur la fecondite.
Generation of a transgenic mouse line for conditional expression of human IL-6

IL-6 is a cytokine that is involved in various physiological and pathological conditions, and approaches using gain-of-function transgenic animals have contributed in elucidating IL-6 function. However, studies of the multiple functions of IL-6 in vivo are very time consuming because they require the generation of transgenic mice that harbor the gene encoding IL-6 under the control of specific promoters to mimic different pathologies. Here, we report the establishment of a conditional human IL-6 transgenic mouse, LGL-IL6, which conditionally expresses human IL-6 by taking advantage of the well-characterized Cre recombinase drivers.
Effect of Accelerator in Green Synthesis of Silver Nanoparticles

Silver nanoparticles (Ag-NPs) were successfully synthesized in the natural polymeric matrix. Silver nitrate, gelatin, glucose, and sodium hydroxide have been used as silver precursor, stabilizer, reducing agent, and accelerator reagent, respectively. This study investigated the role of NaOH as the accelerator. The resultant products have been confirmed to be Ag-NPs using powder X-ray diffraction (PXRD), UV-vis spectroscopy, and transmission electron microscopy (TEM). The colloidal sols of Ag-NPs obtained at different volumes of NaOH show strong and different surface plasmon resonance (SPR) peaks, which can be explained from the TEM images of Ag-NPs and their particle size distribution. Compared with other synthetic methods, this work is green, rapid, and simple to use. The newly prepared Ag-NPs may have many potential applications in chemical and biological industries.
A Fast Inference Algorithm for Stochastic Blockmodel

Stochastic block model is a widely used statistical tool for modeling graphs and networks. Despite its popularity, the development on efficient inference algorithms for this model is surprisingly inadequate. The existing solutions are either too slow to handle large networks, or suffer from convergence issues. In this paper, we propose a fast and principled inference algorithm for stochastic block model. The algorithm is based on the variational Bayesian framework, and deploys the natural conjugate gradient method to accelerate the optimization of the variational bound. Leveraging upon the power of both conjugate and natural gradients, it converges super linearly and produces high quality solutions in practice. In particular, we apply our algorithm to the community detection task and compare it with the state-of-the-art variational Bayesian algorithms. We show that it can achieve up to two orders of magnitude speedup without significantly compromising the quality of solutions.
Improving microRNA target prediction in humans using a highly descriptive graph-based machine-learning model

Computational prediction of animal microRNA target sites imposes a tough challenge on research, since complementarity of functional microRNA-target interactions is usually small, which inevitably leads to a high number of false positive predictions. Prediction programs try to cope with this dilemma by applying additional filtering, but still their current performances are far from optimal. In the course of this thesis, a novel graph-based machine learning model was extended in order to be utilized for microRNA target prediction. Recently published high-throughput datasets of microRNA-target interactions have been compiled to train and test the generated models. Furthermore, the datasets have been analysed in order to study microRNA related characteristics. The principle idea behind the graph-based approach is to encode microRNA-target interactions as graphs, which can be efficiently evaluated using a graph-kernel method in combination with a machine learning model. Moreover, additional features of microRNA interactions can be encoded into the graphs, and their relative contributions on prediction performance can be evaluated. Regarding the obtained results, model training resulted in good predictive performances, while model testing on an independent dataset still has room for improvement. Moreover, analysis of the datasets revealed some interesting insights which should help to improve future prediction studies, especially when working with the analysed datasets.
Reversible Watermarking by Difference Expansion

Reversible watermark has drawn lots of interest recently. Different from other types of digital watermarks, a reversible watermark has a special feature that the original digital content can be completely restored. In this paper we describe a high capacity and high quality reversible watermarking method based on difference expansion. A noticeable difference between our method and others is that we do not need to compress original values of the embedding area. We explore the redundancy in the digital content to achieve reversibility.
Requirements for a layered software architecture supporting cooperative multi-user interaction

Layered interactive systems lend themselves to be adapted for cooperation if inter-layer communication is charged to separated connectors. Point-to-point connectors can be replaced with cooperative connectors multiplexing and demultiplexing I/O between a particular layer and multiple instances of the next lower one. For this technique to be most effective, some general guidelines should be followed that support the design of good quality software where discrimination between heterogeneous functionality at the architectural level allows multiple interacting users to exploit different system features based on their role in the cooperation. This provides a sound basis for augmenting collaboration-transparent layered systems with powerful collaboration support (e.g. complex coordination policies) yet preserving separation of concerns between applicative and cooperative functionality. The paper discusses these issues both in general and with reference to their application within the CSDL framework for cooperative systems design.
Squeeze me: gently please

This paper presents the Squeeze Me, a research-through-design case that explores the emergence of empathic behavior between human and machine by sparking an expression-rich relation. The Squeeze Me is a squeezable device used to grab attention from a robot, providing ground for expressive values to be shared. The expressions exerted on the mediating device by the human are mapped to expressive behaviors of the robot in the modality of motion in forthcoming interaction. We propose a double-layered interaction paradigm in achieving natural and socially acceptable synthesis. Firstly, a direct mapping, inherently exhibiting a natural relationship. Secondly, an amplifying and reductive mapping to construct a personalizing relationship through vivid and lively interactions fed by the intentions of the robot as well as the user. The design case serves to explore consequences of a phenomenological approach on the constitution of empathy in the fields of human and robot interaction. With this work we intend to inspire design engineering to shift from representational and discrete to rich, continuous-sustained and other embodied mechanisms for interaction when targeting empathic behavior to emerge.