Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Operator Site Geometry on Transcriptional Control by the YefM-YoeB Toxin-Antitoxin Complex

ABSTRACT YefM-YoeB is among the most prevalent and well-characterized toxin-antitoxin complexes. YoeB toxin is an endoribonuclease whose activity is inhibited by YefM antitoxin. The regions 5′ of yefM-yoeB in diverse bacteria possess conserved sequence motifs that mediate transcriptional autorepression. The yefM-yoeB operator site arrangement is exemplified in Escherichia coli: a pair of palindromes with core hexamer motifs and a center-to-center distance of 12 bp overlap the yefM-yoeB promoter. YefM is an autorepressor that initially recognizes a long palindrome containing the core hexamer, followed by binding to a short repeat. YoeB corepressor greatly enhances the YefM-operator interaction. Scanning mutagenesis demonstrated that the short repeat is crucial for correct interaction of YefM-YoeB with the operator site in vivo and in vitro. Moreover, altering the relative positions of the two palindromes on the DNA helix abrogated YefM-YoeB cooperative interactions with the repeats: complex binding to the long repeat was maintained but was perturbed to the short repeat. Although YefM lacks a canonical DNA binding motif, dual conserved arginine residues embedded in a basic patch of the protein are crucial for operator recognition. Deciphering the molecular basis of toxin-antitoxin transcriptional control will provide key insights into toxin-antitoxin activation and function.
Analysis of the Interaction between Routing Protocols and MANET Parameters

protocols for a Mobile Ad-hoc Network (MANET) have been of great interest for many years as the underlying Internet routing protocols are mainly intended to support the permanent infrastructure network. This research makes an attempt to conducting a realistic and quantitative performance analysis of several key routing protocols in the same framework within MANET, which eventually helps better understand the protocols' comparative merits and suitability for deployment under different stressful and dynamic scenarios. The four routing protocols that are considered in the analysis are Optimized Link State Routing (OLSR), Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Temporary Ordered Routing Algorithm (TORA). The research asserts the fact of superiority of proactive protocol, over reactive and hybrid ones when routing the same traffic in the network. As the simulation results demonstrate, OLSR protocol has been reckoned to be a very effective and efficient routing protocol for MANET, which ensures its particular suitability, irrespective of network size and mobility. Nonetheless, among the reactive protocols, AODV performs well in a medium and high density network, with particular reference to a case where end-to-end delays are very critical.
A Survey on Disk Oriented Querying and Reasoning on the Semantic Web

This paper presents a description of seven systems, which use database technology to both represent knowledge persistently and make scalable queries on it, in the Semantic Web context. From the study of these systems we can deduce that a lot of work regarding massive storage of knowledge has already been carried out. We can observe an evolution from RDF to OWL in most up-to-date systems. The analyzed approaches carry out a mapping between the (structure of the) ontology and the data model of the persistence management system. Nevertheless, there is still considerable work to be done regarding efficient disk oriented Abox (ontology instances) querying and reasoning. We think that due to the Semantic Web features many problems related to assertional reasoning should be addressed. We also believe that the physical design of the knowledge base is a very important task, which includes the development of both specific storage structures and indexes for knowledge storage and retrieval.
On‐Demand Liquid Transportation Using Bioinspired Omniphobic Lubricated Surfaces Based on Self‐Organized Honeycomb and Pincushion Films

In this work, on‐demand control of liquids is realized by using elastic, patterned omniphobic surfaces. This paves the way for novel microfluidics, as well as liquid harvesting, transportation, and manipulation technologies. Inspired by the lubricating properties of pitcher plants, microstructured 1,2‐polybutadiene honeycomb and pincushion films obtained by self‐organization are fluorinated by the ene‐thiol reaction and infused with fluorinated lubricant to obtain omniphobic liquid‐repellent surfaces. Unlike conventional bioinspired omniphobic surfaces, the liquid repellency of the fabricated surface can be programmed by changing the surface microstructures via patterning of the film. Furthermore, the elasticity of the omniphobic film is suitable for controlling the repellency through external stimuli. The method presented here for the fabrication of lubricant‐infused omniphobic microstructured surfaces is also simple, cost‐effective, and can be scaled for large area fabrication.
Modification of Physico-Mechanical Properties of Chitosan-Tapioca Starch Blend Films Using Nano Graphene

Biodegradable blend films from chitosan-tapioca starch were prepared by the casting method. To improve the properties of chitosan–starch blend films, nano graphene was used. The influences of the loading of graphene on the physico-mechanical properties in terms of water vapor transmission rate (WVTR), thermal stability, and tensile strength of the blend films were investigated. Scanning electron microscopy (SEM) and FTIR were used to investigate the surface morphology and molecular interaction of the blend films, respectively. After the incorporation of nano graphene, the blend film from chitosan-starch showed an increase in tensile strength and thermal stability, and a decrease in WVTR and elongation at the break. These results showed that the combination of a tiny amount of graphene presents a promising method for improving the mechanical and barrier properties of chitosan-starch biocomposite films. The SEM observations indicated that a high amount (3 wt.%) of graphene was easily agglomerated. This caused the mechanical properties of the composite films to be reduced. Among the various compositions studied, chitosan-starch film filled with 0.8 wt. % graphene showed superior properties. The structural properties investigated by FTIR showed a clear interaction between chitosan and starch, forming a new material with enhanced mechanical properties.
Multicondition training of Gaussian PLDA models in i-vector space for noise and reverberation robust speaker recognition

We present a multicondition training strategy for Gaussian Probabilistic Linear Discriminant Analysis (PLDA) modeling of i-vector representations of speech utterances. The proposed approach uses a multicondition set to train a collection of individual subsystems that are tuned to specific conditions. A final verification score is obtained by combining the individual scores according to the posterior probability of each condition given the trial at hand. The performance of our approach is demonstrated on a subset of the interview data of NIST SRE 2010. Significant robustness to the adverse noise and reverberation conditions included in the multicondition training set are obtained. The system is also shown to generalize to unseen conditions.
Selection-channel-aware rich model for Steganalysis of digital images

From the perspective of signal detection theory, it seems obvious that knowing the probabilities with which the individual cover elements are modified during message embedding (the so-called probabilistic selection channel) should improve steganalysis. It is, however, not clear how to incorporate this information into steganalysis features when the detector is built as a classifier. In this paper, we propose a variant of the popular spatial rich model (SRM) that makes use of the selection channel. We demonstrate on three state-of-the-art content-adaptive steganographic schemes that even an imprecise knowledge of the embedding probabilities can substantially increase the detection accuracy in comparison with feature sets that do not consider the selection channel. Overly adaptive embedding schemes seem to be more vulnerable than schemes that spread the embedding changes more evenly throughout the cover.
Cinematized Reality: Cinematographic 3D Video System for Daily Life Using Multiple Outer/Inner Cameras

The purpose of Cinematized Reality is to record unexpected moments in people’s lives and create movies that look as if they were created from real, expertly captured film footage. The approach toward Cinematized Reality is to generate free-view video streams from multiple videos. The proposed system reconstructs 3D models of the capturing space using outer environmental cameras and an inner omni-directional camera, and then generates realistic video of those objects from a designated viewpoint by controlling a virtual camera as an expert would. This prototype system follows the grammar of film language and applies expert knowledge to generate desirable film footage using a sequence of shots taken by the virtual camera.
Dynamic Adjustment of Hidden Node Parameters for Extreme Learning Machine

Extreme learning machine (ELM), proposed by Huang et al., was developed for generalized single hidden layer feedforward networks with a wide variety of hidden nodes. ELMs have been proved very fast and effective especially for solving function approximation problems with a predetermined network structure. However, it may contain insignificant hidden nodes. In this paper, we propose dynamic adjustment ELM (DA-ELM) that can further tune the input parameters of insignificant hidden nodes in order to reduce the residual error. It is proved in this paper that the energy error can be effectively reduced by applying recursive expectation-minimization theorem. In DA-ELM, the input parameters of insignificant hidden node are updated in the decreasing direction of the energy error in each step. The detailed theoretical foundation of DA-ELM is presented in this paper. Experimental results show that the proposed DA-ELM is more efficient than the state-of-art algorithms such as Bayesian ELM, optimally-pruned ELM, two-stage ELM, Levenberg-Marquardt, sensitivity-based linear learning method as well as the preliminary ELM.
Organic Ultraviolet Photodetectors Exhibiting Photomultiplication, Low Dark Current, and High Stability

Organic UV photodetectors can provide a cheap, durable alternative to current technologies used for applications such as missile detection and arc flash protection. The wide‐bandgap semiconductor poly[(9,9‐dioctylfluorenyl‐2,7‐diyl)‐alt‐co‐(bithiophene)] (F8T2), combined disproportionately with the fullerene‐derivative [6,6]‐phenyl‐C71‐butyric acid methyl ester (PC71BM) in weight ratios of 100:4 and 100:1, comprises the active layers of organic UV photodetectors. The small clusters of PC71BM trap charges, enhancing band bending and charge injection and thus enabling photomultiplication. These clusters also prevent electrons from transporting through the device, helping produce a low dark current. Although devices without an electron transfer layer (ETL) exhibit more efficient photomultiplication, they tend to be unstable. Devices with a F8T2:PC71BM weight ratio of 100:4 and with an ETL demonstrate an external quantum efficiency peaking at 5600%, at 360 nm and −40 V bias, and a low dark current of 2.7 × 10−7 mA cm−2 at −1 V bias. These devices are stable and behave well even under strong biases, which enhance the UV‐selectivity and response speed of the devices.
Extracellular Signal-Regulated Kinases 1 and 2 Phosphorylate Gab2 To Promote a Negative-Feedback Loop That Attenuates Phosphoinositide 3-Kinase/Akt Signaling

ABSTRACT The scaffolding adapter protein Gab2 (Grb2-associated binder) promotes cell proliferation, survival, and motility by engaging several signaling pathways downstream of growth factor and cytokine receptors. In particular, Gab2 plays essential roles in mast cells, as it is required for phosphoinositide 3-kinase (PI3K) activation in response to Kit and the high-affinity IgE receptor. While the positive role of Gab2 in PI3K signaling is well documented, very little is known about the mechanisms that attenuate its function. Here we show that Gab2 becomes phosphorylated on multiple proline-directed sites upon stimulation of the Ras/extracellular signal-regulated kinase (ERK) signaling pathway. We demonstrate that ERK1 and ERK2 interact with Gab2 via a novel docking motif, which is required for subsequent Gab2 phosphorylation in response to ERK1/2 activation. We identified four ERK1/2-dependent phosphorylation sites in Gab2 that prevent the recruitment of the p85 regulatory subunit of PI3K. Using bone marrow-derived mast cells to study Gab2-dependent signaling, we found that the inhibition of ERK1/2 activity promotes Akt signaling in response to Kit and the high-affinity IgE receptor. Together, our results indicate that ERK1/2 participates in a negative-feedback loop that attenuates PI3K/Akt signaling in response to various agonists.
Non linear actuation model for lateral electrostatically-actuated DC-contact RF MEMS series switches

In this work, a non linear model to predict actuation characteristics in lateral electrostatically-actuated DC-contact MEMS switches is proposed. In this case a parallel-plate approximation can not be applied. The model is based on the equilibrium equation for an elastic beam. It is demonstrated that the contribution of fringing fields is essential. The model relies on finite-difference discretization of the structures, applying boundary conditions and is solved with a Gauss-Seidel relaxation iteration scheme. Its usefulness is demonstrated in a series MEMS switch with lateral interdigital electrostatic actuation.
Recent advances in molecular lithography

The precise placement of molecular and nanoparticle species at predetermined locations on a substrate surface remains a current challenge. Some barriers are particularly relevant to soft matter such as biomolecules. The advent of DNA Origami, invented by Rothemund, provides partial solutions to some challenges while raising new challenges. In this paper, two particular levels of molecular placement will be discussed, associating large DNA based molecular nanostructures with traditional lithographic nanostructures and the association of molecular scale species with particular locations within large Origami structures. Typical plasmid based DNA Origami nanostructures are approximately 100 nm in diameter. This size scale closely matches that of gold nanoscale structures which are readily produced using ebeam and other lithographic techniques. The strategy for associating large DNA based nanostructures with these lithographic structures employs the placement of thiol terminated DNA molecules within the molecular assembly, positioned to allow tethering of the biomolecular nanostructure to the substrate through gold-thiol bonds. Although a number of soft chemistry mechanisms can be employed to associate DNA molecules with substrates, the use of the origami constructs as substrates suggests that single stranded DNA provides the optimum attachment strategy. A solid state asymmetric PCR process for ssDNA fabrication is therefore described and demonstrated. Structures generated with the three tiered attachment strategy described here are amenable to characterization and assembly verification using AFM and NSOM. While a complete convergence of top down and bottom up approaches cannot be claimed, it is clear that the practice and methods of molecular lithography are rapidly advancing.
Design of Solar Power Optimizer And Eliminating Leakage Current In Multi-Level Inverter For PV Systems

This paper proposes a high step-up Solar Power Optimizer (SPO) harvests maximum energy from a photovoltaic (PV) panel with high efficiency. DC-DC converter structure is used to get high step-up voltage gain. It is the structure designed to coupled inductor and switched capacitor. The inductance energy can be recycled, and it is reducing the voltage stress and power loss. Particle Swarm Optimization(PSO) method based Maximum Power Point Tracking (MPPT) algorithm is used to improve the efficiency of the tracking system. Three phase transformer- less neutral point clamped inverters are used to eliminate the leakage current in photovoltaic systems using the multi- level inverters. The three phase neutral point diode clamped inverter can be designed to provide functions of low pass filters. Diode clamped multi-level inverters are used to reduce the harmonic, and also to eliminate the leakage current in PV panels.
"How old are you?" : Age Estimation with Tensors of Binary Gaussian Receptive Maps

In this paper we describe experiments with a method to automatically estimate human age from facial images. This system extends recent results with the use of a tensorial representation from Gaussian receptive field responses for face recognition to the problem of estimating age. Among other results, we show that inclusion of fourth order Gaussian receptive fields can improve recognition. We describe an optimal tensorial configuration and compare the use of two different configurations with Multilinear Principal Component Analysis to reduce tensor order and Relevance Vector Machines as regressor. Experimental results are demonstrated for the FG-NET and the MORPH aging datasets.
Atomic-scale analysis of light alloys using atom probe tomography

The present paper reviews recent progress in atomic-scale characterisation of composition and nanostructure of light alloy materials using the technique of atom probe tomography. In particular, the present review will highlight atom-by-atom analysis of solid solution architecture, including solute clustering and short-range order, with reference to current limitations of spatial resolution and detector efficiency of atom probe tomography and methods to address these limitations. This leads to discussion of prediction of mechanical properties by simulation and modelling of the strengthening effect exerted by solute clusters and the role of experimental atom probe data to assist in this process. The unique contribution of atom probe tomography to the study of corrosion and hydrogen embrittlement of light alloys will also be discussed as well as a brief insight into its potential application for the investigation of solute strengthening of twinning in Mg alloys.
A machine learning approach to improve congestion control over wireless computer networks

In this paper, we present the application of machine learning techniques to the improvement of the congestion control of TCP in wired/wireless networks. TCP is sub-optimal in hybrid wired/wireless networks because it reacts in the same way to losses due to congestion and losses due to link errors. We thus propose to use machine learning techniques to build automatically a loss classifier from a database obtained by simulations of random network topologies. Several machine learning algorithms are compared for this task and the best method for this application turns out to be decision tree boosting. It outperforms ad hoc classifiers proposed in the networking literature.
Complex Epistasis for Dobzhansky–Muller Hybrid Incompatibility in Solanum

We examined the prevalence of interactions between pairs of short chromosomal regions from one species (Solanum habrochaites) co-introgressed into a heterospecific genetic background (Solanum lycopersicum). Of 105 double introgression line (DIL) families generated from a complete diallele combination of 15 chromosomal segments, 39 (∼38%) showed evidence for complex epistasis in the form of genotypic and/or allelic marker transmission distortion in DIL F2 populations.
Identifying Cognates by Phonetic and Semantic Similarity

I present a method of identifying cognates in the vocabularies of related languages. I show that a measure of phonetic similarity based on multivalued features performs better than "orthographic" measures, such as the Longest Common Subsequence Ratio (LCSR) or Dice's coefficient. I introduce a procedure for estimating semantic similarity of glosses that employs keyword selection and WordNet. Tests performed on vocabularies of four Algonquian languages indicate that the method is capable of discovering on average nearly 75% percent of cognates at 50% precision.
Now Let’s Talk About Now; Identifying Cue Phrases Intonationally

Cue phrases are words and phrases such as now and by the way which may be used to convey explicit information about the structure of a discourse. However, while cue phrases may convey discourse structure, each may also be used to different effect. The question of how speakers and hearers distinguish between such uses of cue phrases has not been addressed in discourse studies to date. Based on a study of now in natural recorded discourse, we propose that cue and non-cue usage can be distinguished intonationally, on the basis of phrasing and accent.
Reducing data distribution bottlenecks by employing data visualization filters

Between 1994 and 1997, researchers at Southwest Research Institute (SwRI) investigated methods for distributing parallel computation and data visualization under the support of an internally funded Research Initiative Program entitled the Advanced Visualization Technology Project (AVTP). A hierarchical data cache architecture was developed to provide a flexible interface between the modeling or simulation computational processes and data visualization programs. Compared to conventional post facto data visualization approaches, this data cache structure provides many advantages including simultaneous data access by multiple visualization clients, comparison of experimental and simulated data, and visual analysis of computer simulation as computation proceeds. However, since the data cache was resident on a single workstation, this approach did not address the issue of scalability of methods for avoiding the data storage bottleneck by distributing the data across multiple networked workstations. Scalability through distributed database approaches is being investigated as part of the Applied Visualization using Advanced Network Technology Infrastructure (AVANTI) project. This paper describes a methodology currently under development that is intended to avoid bottlenecks that typically arise as the result of data consumers (e.g. visualization applications) that must access and process large amounts of data that has been generated and resides on other hosts, and which must pass through a central data cache prior to being used by the data consumer.
Bidirectional Forwarding Detection ( BFD ) for Multihop Paths

This document describes the use of the Bidirectional Forwarding Detection (BFD) protocol over multihop paths, including unidirectional links. Information about the current status of this document, any errata, and how to provide feedback on it may be obtained at in effect on the date of publication of this document. Please review these documents carefully, as they describe your rights and restrictions with respect to this document. Code Components extracted from this document must include Simplified BSD License text as described in Section 4.e of the Trust Legal Provisions and are provided without warranty as described in the Simplified BSD License.
Chronic Fatigue Syndrome: A Review

Chronic fatigue syndrome (CFS) is an illness characterized by disabling fatigue of atleast 6 months accompanied by several other secondary symptoms. Till date there is no approved treatment available in the market. The diagnosis is based on symptoms and no specific diagnostic tests are yet exist. CFS is a heterogeneous condition with multifactorial etiology. Immunological, Infectious, Sleep, Neuroendocrine, oxidative stress and Central nervous system mechanisms have been investigated but still etiology of CFS is not clear. Our review will summarize a current status of Pathophysiology and treatment of chronic fatigue syndrome.