Miracle-dz/UniFAR-FTUs huggingface dataset:
JVirGel 2.0: computational prediction of proteomes separated via two-dimensional gel electrophoresis under consideration of membrane and secreted proteins

MOTIVATION After the publication of JVirGel 1.0 in 2003 we got many requests and suggestions from the proteomics community to further improve the performance of the software and to add additional useful new features. RESULTS The integration of the PrediSi algorithm for the prediction of signal peptides for the Sec-dependent protein export into JVirGel 2.0 allows the exclusion of most exported preproteins from calculated proteomic maps and provides the basis for the calculation of Sec-based secretomes. A tool for the identification of transmembrane helices carrying proteins (JCaMelix) and the prediction of the corresponding membrane proteome was added. Finally, in order to directly compare experimental and calculated proteome data, a function to overlay and evaluate predicted and experimental two-dimensional gels was included. AVAILABILITY JVirGel 2.0 is freely available as precompiled package for the installation on Windows or Linux operating systems. Furthermore, there is a completely platform-independent Java version available for download. Additionally, we provide a Java Server Pages based version of JVirGel 2.0 which can be operated in nearly all web browsers. All versions are accessible at http://www.jvirgel. de
A CMOS Stacked-FET Power Amplifier Using PMOS Linearizer with Improved AM-PM

A linear stacked field-effect transistor (FET) power amplifier (PA) is implemented using a 0.18-μm silicon-on-insulator CMOS process for W-CDMA handset applications. Phase distortion by the nonlinear gate-source capacitance (Cgs) of the common-source transistor, which is one of the major nonlinear sources for intermodulation distortion, is compensated by employing a PMOS linearizer with improved AM-PM. The linearizer is used at the gate of the driver-stage instead of main-stage transistor, thereby avoiding excessive capacitance loading while compensating the AM-PM distortions of both stages. The fabricated 836.5 MHz linear PA module shows an adjacent channel leakage ratio better than —40 dBc up to the rated linear output power of 27.1 dBm, and power-added efficiency of 45.6% at 27.1 dBm without digital pre-distortion.
A Hash based Approach for Secure Keyless Steganography in Lossless RGB Images

This paper proposes an improved steganography approach for hiding text messages in lossless RGB images. The objective of this work is to increase the security level and to improve the storage capacity with compression techniques. The security level is increased by randomly distributing the text message over the entire image instead of clustering within specific image portions. Storage capacity is increased by utilizing all the color channels for storing information and providing the source text message compression. The degradation of the images can be minimized by changing only one least significant bit per color channel for hiding the message, incurring a very little change in the original image. Using steganography alone with simple LSB has a potential problem that the secret message is easily detectable from the histogram analysis method. To improve the security as well as the image embedding capacity indirectly, a compression based scheme is introduced. Various tests have been done to check the storage capacity and message distribution. These testes show the superiority of the proposed approach with respect to other existing approaches.
ALICE: Avaya Labs Innovations Cloud Engagement

We present the architecture and implementation of our enterprise cloud portal named ALICE, Avaya Labs Innovations Cloud Engagement, which provides self-service access to service developers, tenants, and users to various communication and collaboration applications. Currently ALICE is used for field testing of advanced research prototype services based on technologies such as WebRTC and HTML5. This paper describes the current portal and extensions to support multi-tenancy. We describe challenges in creating a self-service multi-tenant SaaS (software-as-a-service) portal to host communications and collaboration applications for small to medium scale businesses. The challenges faced and the techniques used in our architecture relate to security, provisioning, management, complexity, cost savings and multi-tenancy, and are applicable and useful to other cloud deployments of diverse enterprise applications.
New Analysis and Design of a RF Rectifier for RFID and Implantable Devices

New design and optimization of charge pump rectifiers using diode-connected MOS transistors is presented in this paper. An analysis of the output voltage and Power Conversion Efficiency (PCE) is given to guide and evaluate the new design. A novel diode-connected MOS transistor for UHF rectifiers is presented and optimized, and a high efficiency N-stage charge pump rectifier based on this new diode-connected MOS transistor is designed and fabricated in a SMIC 0.18-μm 2P3M CMOS embedded EEPROM process. The new diode achieves 315 mV turn-on voltage and 415 nA reverse saturation leakage current. Compared with the traditional rectifier, the one based on the proposed diode-connected MOS has higher PCE, higher output voltage and smaller ripple coefficient. When the RF input is a 900-MHz sinusoid signal with the power ranging from −15 dBm to −4 dBm, PCEs of the charge pump rectifier with only 3-stage are more than 30%, and the maximum output voltage is 5.5 V, and its ripple coefficients are less than 1%. Therefore, the rectifier is especially suitableto passive UHF RFID tag IC and implantable devices.
Estimates of the overall rate of growth of the intestinal microflora of hamsters, guinea pigs, and mice

The intestinal canal of man and animals harbors vast numbers of bacteria. Unchecked intestinal bacterial proliferation would soon overwhelm the host. Thus, the microorganisms present must be growing well below their potential growth rate. However, estimates of their average rate of proliferation are unavailable. Since the intestinal canal has been likened to a continuous fermentation system (R. M. Donaldson, New Engl. J. Med. 270:938, 1964), the average overall growth rate of all species present must equal the dilution rate. Consequently, if the total number of bacteria lost by excretion
Application to the characterization of wear in internal combustion engine cylinder liners

A state of the art of 3D surface characterization techniques in the automotive and steel industries is presented, and links with mathematical morphology are highlighted. A surface topography decomposition method is described. It decomposes a surface into three elements: reference surface (waviness and form), superficial roughness (related to friction and wear) and valleys (related to lubricant circulation and reservoirs). It is applied to cylinder liners from an internal combustion V6 engine in order to remove form and waviness components. The study of the resulting superficial roughness component allows a precise wear characterization.
Two applications of eng-genes based nonlinear identification

Abstract Nonlinear identification using a novel neural network paradigm, namely eng-genes, is investigated. A set of MATLAB functions for the training and simulation of eng-genes based neural models are described. These functions are then used to investigate the effectiveness of the technique applied to two nonlinear dynamical systems. Experimental data from a pH neutralisation plant and simulation data from a physical model of a CSTR process are used to generate ‘eng-genes’ models. The results are compared with conventional neural models of these plants, showing that simple neural models with better performance and improved transparency are obtainable using the eng-genes paradigm.
Effective Exon Skipping and Dystrophin Restoration by 2′-O-Methoxyethyl Antisense Oligonucleotide in Dystrophin-Deficient Mice

Antisense oligonucleotide (AO)–mediated exon-skipping therapy is one of the most promising therapeutic strategies for Duchenne Muscular Dystrophy (DMD) and several AO chemistries have been rigorously investigated. In this report, we focused on the effect of 2′-O-methoxyethyl oligonucleotides (MOE) on exon skipping in cultured mdx myoblasts and mice. Efficient dose-dependent skipping of targeted exon 23 was achieved in myoblasts with MOE AOs of different lengths and backbone chemistries. Furthermore, we established that 25-mer MOE phosphorothioate (PS) AOs provided the greatest exon-skipping efficacy. When compared with 2′O methyl phosphorothioate (2′OmePS) AOs, 25-mer MOE (PS) AOs also showed higher exon-skipping activity in vitro and in mdx mice after intramuscular injections. Characterization of uptake in vitro corroborated with exon-skipping results, suggesting that increased uptake of 25-mer MOE PS AOs might partly contribute to the difference in exon-skipping activity observed in vitro and in mdx mice. Our findings demonstrate the substantial potential for MOE PS AOs as an alternative option for the treatment of DMD.
Digital ADCs and ultra-wideband RF circuits for energy constrained wireless applications

Ongoing advances in semiconductor technology have enabled a multitude of portable, low power devices like cellular phones and wireless sensors. Most recently, as transistor device geometries reach the nanometer scale, transistor characteristics have changed so dramatically that many traditional circuits and architectures are no longer optimal and/or feasible. As a solution, much research has focused on developing ‘highly digital’ circuits and architectures that are tolerant of the increased leakage, variation and degraded voltage headrooms associated with advanced CMOS processes. This thesis presents several highly digital, mixed-signal circuits and architectures designed for energy constrained wireless applications. First, as a case study, a highly digital, voltage scalable flash ADC is presented. The flash ADC, implemented in 0.18 μm CMOS, leverages redundancy and calibration to achieve robust operation at supply voltages from 0.2 V to 0.9 V. Next, the thesis expands in scope to describe a pulsed, noncoherent ultra-wideband transceiver chipset, implemented in 90 nm CMOS and operating in the 3-to-5 GHz band. The all-digital transmitter employs capacitive combining and pulse shaping in the power amplifier to meet the FCC spectral mask without any off-chip filters. The noncoherent receiver system-on-chip achieves both energy efficiency and high performance by employing simple amplifier and ADC structures combined with extensive digital calibration. Finally, the transceiver chipset is integrated in a complete system for wireless insect flight control. Through the use of a flexible PCB and 3D die stacking, the total weight of the electronics is kept to 1 g, within the carrying capacity of an adult Manduca sexta moth. Preliminary wireless flight control of a moth in a wind tunnel is demonstrated. Thesis Supervisor: Anantha P. Chandrakasan Title: Joseph F. and Nancy P. Keithley Professor of Electrical Engineering
PCD: A privacy-preserving predictive clinical decision scheme with E-health big data based on RNN

As large amount of e-health data is generated exponentially, recurrent neural networks (RNN) can be utilized to make predictive clinical decision which is helpful to improve diagnosis accuracy and reduce diagnosis time. However, it is still a challenging task to guarantee the information security and solve the privacy concerns. We design a new Privacy-preserving Predictive Clinical Decision scheme based on RNN, called PCD, that can predict and alert before diseases occur while preserving the privacy of patients. In PCD, we utilize a homomorphic encryption scheme, so no e-health data will be leaked. PCD could resist various security threats. We design a sequential and an averaged RNN model in real-time systems that is capable to improve prediction accuracy. The experimental results illustrate that our scheme achieves high disease prediction accuracy and time efficiency while protecting privacy of patients.
Instantaneous Pressure‐Volume Relationships and Their Ratio in the Excised, Supported Canine Left Ventricle

We have previously shown in the normally ejecting canine left ventricle that E(t), the time-varying ratio of instantaneous pressure, P(t), to instantaneous volume, V(t), is little affected by end-diastolic volume or aortic pressure. The present study on an excised, supported canine heart preparation indicates that the thesis on E(t) is also valid for either totally isovolumic or auxobaric beats. Intraventricular volume was measured more accurately than it was in the previous study by a new volumetric system. Regression analysis of the data showed that the instantaneous pressure-volume relationship could be approximated by the equation P(t) = E(t). [V(t) − Vd], where Vd is an empirical constant, over a wide range of intraventricular volume. Similar E(t) curves were obtained from both isovolumic and auxobaric beats for a given contractile state. When the contractile state of the preparation was enhanced by a constant-rate infusion (0.2 μg/min) of norepinephrine or isoproterenol into the coronary artery, the peak magnitude of E(t) increased 63% from 3.6 mm Hg/ml and the time to peak E(t) shortened 10% from 175 msec. We conclude that the present investigation substantiates our earlier study which established a link between E(t) and the contractile state of the heart.
On the Genericity Properties in Distributed Estimation: Topology Design and Sensor Placement

In this paper, we consider distributed estimation of linear, discrete-time dynamical systems monitored by a network of agents. We require the agents to exchange information with their neighbors only once per dynamical system time-scale and study the network topology sufficient for distributed observability. To this aim, we provide a novel measurement-based agent classification: Type- α,β, and γ, which leads to the construction of specific graph topologies: <i>G</i><sub>α</sub> and <i>G</i><sub>β</sub>. In particular, in <i>G</i><sub>α</sub>, every Type-α agent has a direct connection to every other agent, whereas, in <i>G</i><sub>β</sub>, every agent has a directed path to every Type-β agent. With the help of these constructs, we formulate an estimator where measurement and predictor-fusion are implemented over <i>G</i><sub>α</sub> and <i>G</i><sub>β</sub>, respectively, and show that the proposed scheme leads to distributed observability, i.e., observability of the distributed estimator. In order to characterize the estimator further, we show that Type-α agents only exist in systems with <i>S</i>-rank (maximal rank of zero/non-zero pattern) deficient system matrices. In other words, systems with full <i>S</i>-rank matrices only have Type-β agents, and thus, a strongly-connected (agent) network is sufficient for full <i>S</i>-rank systems-by the definition of <i>G</i><sub>β</sub> above; however strong-connectivity is not necessary, i.e., there exist weakly-connected networks that result in distributed observability. Furthermore, we show that for <i>S</i> -rank deficient systems, measurement-fusion over <i>G</i><sub>α</sub> is required, and predictor-fusion alone is insufficient. The approach taken in this paper is structural, i.e., we use the concept of structured systems theory and generic observability to derive the results. Finally, we provide an iterative method to compute the local estimator gain at each agent once the observability is ensured using the aforementioned construction.
Bayesian network meta-analysis suggests a similar effectiveness between a monovalent and a pentavalent rotavirus vaccine

To assess the comparative effectiveness of a monovalent and a pentavalent rotavirus vaccine (RV1 and RV5), a Bayesian network meta-analysis was conducted. Data of randomized trials from the Cochrane Review in 2012 were extracted and synthesized. For the prevention of severe rotavirus disease up to 2 years, no statistical difference was found in the effectiveness between the 2 types of vaccine (odds ratio: 2.23, 95% credible interval: 0.71–5.20). Similarly, the comparative effectiveness of RV1 and RV5 appeared equivalent for other rotavirus-associated outcome measures, such as prevention of severe disease up to 1 year and all severity of rotavirus infections for up to both 1- and 2-year follow-ups. These results indicates that, overall, RV1 and RV5 offer similar benefits to prevent rotavirus diseases; nonetheless, credible intervals are generally wide, highlighting the necessity of further meta-analyses including updated information or, ideally, controlled trials comparing both vaccines directly.
Robust Feedback Linearization using Extended High-Gain Observers

We consider a partially feedback linearizable system with stable zero dynamics. The system is uncertain and only the output is measured. Consequently, exact feedback linearization is not applicable. We propose to design an extended high-gain observer to recover unmeasured derivatives of the output and an extra one, which contains information about the uncertainty. The observer can be stabilized via feedback linearization followed by a linear control design, such as pole placement or LQR. After a short peaking period, a partial state vector, which includes the output and its derivatives, will be in a small neighborhood of the state of the observer; therefore, the performance achievable under exact feedback linearization will be recovered
Fire Activity and Severity in the Western US Vary along Proxy Gradients Representing Fuel Amount and Fuel Moisture

Numerous theoretical and empirical studies have shown that wildfire activity (e.g., area burned) at regional to global scales may be limited at the extremes of environmental gradients such as productivity or moisture. Fire activity, however, represents only one component of the fire regime, and no studies to date have characterized fire severity along such gradients. Given the importance of fire severity in dictating ecological response to fire, this is a considerable knowledge gap. For the western US, we quantify relationships between climate and the fire regime by empirically describing both fire activity and severity along two climatic water balance gradients, actual evapotranspiration (AET) and water deficit (WD), that can be considered proxies for fuel amount and fuel moisture, respectively. We also concurrently summarize fire activity and severity among ecoregions, providing an empirically based description of the geographic distribution of fire regimes. Our results show that fire activity in the western US increases with fuel amount (represented by AET) but has a unimodal (i.e., humped) relationship with fuel moisture (represented by WD); fire severity increases with fuel amount and fuel moisture. The explicit links between fire regime components and physical environmental gradients suggest that multivariable statistical models can be generated to produce an empirically based fire regime map for the western US. Such models will potentially enable researchers to anticipate climate-mediated changes in fire recurrence and its impacts based on gridded spatial data representing future climate scenarios.
The Tetraspanin TSPAN33 Controls TLR-Triggered Macrophage Activation through Modulation of NOTCH Signaling

The involvement of NOTCH signaling in macrophage activation by Toll receptors has been clearly established, but the factors and pathways controlling NOTCH signaling during this process have not been completely delineated yet. We have characterized the role of TSPAN33, a tetraspanin implicated in a disintegrin and metalloproteinase (ADAM) 10 maturation, during macrophage proinflammatory activation. Tspan33 expression increases in response to TLR signaling, including responses triggered by TLR4, TLR3, and TLR2 activation, and it is enhanced by IFN-γ. In this study, we report that induction of Tspan33 expression by TLR and IFN-γ is largely dependent on NOTCH signaling, as its expression is clearly diminished in macrophages lacking Notch1 and Notch2 expression, but it is enhanced after overexpression of a constitutively active intracellular domain of NOTCH1. TSPAN33 is the member of the TspanC8 tetraspanin subgroup more intensely induced during macrophage activation, and its overexpression increases ADAM10, but not ADAM17, maturation. TSPAN33 favors NOTCH processing at the membrane by modulating ADAM10 and/or Presenilin1 activity, thus increasing NOTCH signaling in activated macrophages. Moreover, TSPAN33 modulates TLR-induced proinflammatory gene expression, at least in part, by increasing NF-κB–dependent transcriptional activity. Our results suggest that TSPAN33 represents a new control element in the development of inflammation by macrophages that could constitute a potential therapeutic target.
Spoken dialogue grammar induction from crowdsourced data

We design and evaluate various crowdsourcing tasks for eliciting spoken dialogue data. Task design is based on an array of parameters that quantify the basic characteristics of the elicitation questions, e.g., how open-ended is a question. The crowdsourced data are used for and evaluated on the unsupervised induction of semantic classes for speech understanding grammars. We show that grammar induction performance is significantly affected by the crowdsourcing task parameters, e.g., paraphrasing tasks prime high lexical entrain-ment and result in poor corpus/grammar quality. The task parameters along with perplexity filters are used for corpus selection achieving grammar induction performance that is comparable to that of using in-domain spoken dialogue data.
A study on robust detection of pronunciation erroneous tendency based on deep neural network

Compared with scoring feedbacks, instructive feedbacks are more demanded by language learners using computer aided pronunciation training (CAPT) systems, which require detailed information about erroneous pronunciations along with phone errors. Pronunciation erroneous tendency (PET) defines a set of incorrect articulation configurations regarding main articulators and uttering manners for the phones respectively, and its robust detection contributes to the provision of appropriate instructive feedbacks. In our previous works, we designed a set of PET labels for CSL (Chinese as a second language) by Japanese learners, and conducted a preliminary detection study with GMM-HMM. This study is aimed at achieving a more robust detection of PETs by two approaches: employing DNN-HMM as the acoustic modeling, and comparing three kinds of acoustic features: MFCC, PLP, and filter-bank. Experimental results showed that the DNN-HMM PET modeling achieved more robust detection accuracies than the previous GMM-HMM, and the three kinds of features behaved differently. A lattice combination of the results of three feature systems led to the best PET results: FRR of 5.5%, FAR of 35.6%, and DA of 88.6%, which showed its efficiency.