gebhart/patrepeval huggingface dataset:
Prediction of protein binding regions (2010)

Identifying protein binding sites provides important clues to the function of a protein. Experimental methods to identify the binding sites such as determining the crystal structures of protein complexes are extremely laborious and expensive. Here, we present a computational technique called spatial aggregation propensity (SAP) based on molecular simulations to predict protein binding sites. We apply this technique to two model proteins, an IgG1 antibody and epidermal growth factor receptor (EGFR) and demonstrate that SAP predicts protein binding regions with very good accuracy. In the case of the IgG1 antibody, SAP accurately predicts binding regions with the Fc-receptor, protein-A, and protein-G. For EGFR, SAP accurately predicts binding regions with EGF, TGFα, and with another EGFR. The resolution of SAP is varied to obtain a detailed picture of these binding sites. We also show that some of these binding sites overlap with protein self-aggregation prone regions. We demonstrate how SAP analysis can be used to engineer the protein to remove unfavorable aggregation prone regions without disturbing protein binding regions. The SAP technique could be also used to predict the yet unknown binding sites of numerous proteins, thereby providing clues to their function.
Detection and velocity estimation of moving objects in a sequence of single-look SAR images (2002)

A method for detection of point-like moving objects and for estimation of their velocities with airborne synthetic aperture radar (SAR) is presented. This method is based on evaluation of the temporal correlation in a sequence of single-look SAR images which are processed using look filters with different center frequencies. In these images, candidates for moving objects are detected and a displacement vector estimation is performed for each candidate using a block matching algorithm as known from e.g. videotelephony. From the displacement vectors the velocities of the candidates in azimuth direction are calculated. The proposed algorithm has been applied to simulated and real raw data. The azimuth velocity component has been estimated with high accuracy, and a high detection probability with a low false alarm rate is reached.
Effectiveness of the Compensatory Reserve Index in Monitoring Blood Resuscitation in Baboons (2016)

BACKGROUND The Compensatory Reserve Index (CRI) is a machine learning algorithm that detects the body's ability to compensate for blood loss by analysing changes in arterial waveforms. Previous studies have shown CRI to be more accurate than traditional vital signs in estimating an individual's risk of hemodynamic decompensation. However, the effectiveness of the CRI in monitoring volume resuscitation has not been evaluated. The purpose of this study is to assess the ability of CRI to detect volume resuscitation incomparison to traditional vital signs. METHODS This study compared systolic arterial pressure (SAP), heart rate (HR), stroke volume (SV), and CRI during whole blood resuscitation after 25% blood volume hemorrhage in baboons (n=12). The study was conducted at the Texas Biomedical Research Institute (San Antonio, TX)under an approved protocol by their Animal Care and Use Committee. Statistical analysis was performed using two repeated measures ANOVA and linear regression analysis. RESULTS SV, SAP, HR, and CRI were all sensitive to blood resuscitation. SV and SAP overshot baseline during resuscitation, but CRI did not. Target SAP for resuscitation is 80–90 mm Hg. The corresponding CRI value was approximately 0.25–0.30, which aligns with the transition from an unstable to a moderately compromised condition. CONCLUSIONS CRI can detect not only hemorrhage, but also blood resuscitation in baboons. CRI is equally effective as traditional vital signs for detecting blood resuscitation. The ease of tracking CRI makes it a potentially effective clinical tool for monitoring blood resuscitation. Support or Funding Information FUNDING : US Army Medical Research and Materiel Command Combat Casualty Care Research Program
Computational Vector-Magnitude-Based Range Determination for Scientific Abstract Data Types (2010)

As interest mounts in using hardware accelerators to speed up numerical scientific calculations, automation tool support is required to aid designers in mapping applications to custom hardware. One key step in designing this custom hardware is bit-width allocation where the known-art faces challenges when dealing with applications from the scientific computing domain, thus motivating the use of computational methods based on Satisfiability-Modulo Theory. Many real-life applications are, however, specified in terms of vectors and matrices which are of sufficient size to make expansion into scalar equations infeasible. The proposed vector-magnitude method and its extension via block vectors enable computational methods to be leveraged in tackling calculations of practically relevant complexity. Application to case studies confirms that through a more compact computational instance, search efficiency is improved leading to tighter bounds and thus smaller bit-widths.
From Design to Implementation - Algorithm Conversion and Transition to a Mobile Platform for an Artificial Pancreas (2019)

An artificial pancreas system is implemented as a mobile application which connects a glucose sensor, an insulin pump and wearable physical activity sensors. It automatically delivers the optimal insulin amounts, based on a multivariable control algorithm. The algorithm, previously tested on a laptop, is to be hosted on a smartphone. This requires a fast, reliable method to translate the inherent functions. Validation tests of the new mobile application confirm there are no deviations from the original code.
<i>Bacillus</i> minimum genome factory: effective utilization of microbial genome information (2007)

In 1997, the complete genomic DNA sequence of Bacillus subtilis (4.2 Mbp) was determined and 4100 genes were identified [Kunst, Ogasawara, Moszer, Albertini, Alloni, Azevedo, Bertero, Bessieres, Bolotin, Borchert, S. et al. (1997) Nature 90, 249-256]. In addition, B. subtilis, which shows an excellent ability to secrete proteins (enzymes) and antibiotics in large quantities outside the cell, plays an important role in industrial and medical fields. It is necessary to clarify the genes involved in the production of compounds by understanding the network of these 4100 genes and the proceeding analysis of genes of unknown functions. In promoting such a study, it is expected that the regulatory system of B. subtilis can be simplified by the creation of a Bacillus strain with a reduced genome by discriminating genes unnecessary for the production of proteins from essential genes, and deleting as many of these unnecessary genes as possible, which may help to understand this complex network of genes. We have previously distinguished essential and non-essential genes by evaluating the growth and enzyme-producing properties of strains of B. subtilis in which about 3000 genes (except 271 essential genes) have been disrupted or deleted singly, and have successfully utilized the findings from these studies in creating the MG1M strain with an approx. 1 Mbp deletion by serially deleting 17 unnecessary regions from the genome. This strain showed slightly reduced growth in enzyme-production medium, but no marked morphological changes. Moreover, we confirmed that the MG1M strain had cellulase and protease productivity comparable with that of the B. subtilis 168 strain, thus demonstrating that genome reduction does not contribute to a negative influence on enzyme productivity.
A Mathematical Algorithm and Custom Nanoprobes to Improve the Resolution of Magnetic Force Microscopy (MFM) Images (2010)

We are working on developing special nanoprobes and techniques to improve the resolution of Magnetic Force Microscopy, MFM. In this paper we describe the custom probes fabricated at our lab and a mathematical algorithm to improve the resolution of the images obtained with these probes. The algorithm is based on physical principles and not on statistical nor on digital signal processing techniques. Our method consists in reversing the non-uniform interaction that takes place between the magnetized probe tip and the perpendicular magnetic stray field produced by the magnetized sample. We developed a compensation field that when scanned over the originally data points produces the effect of imaging the magnetic field with a flat response probe tip. Using this method we obtained images of higher resolution than those provided by conventional MFM.
The first principle computer simulation and real device characteristics of superlattice phase-change memory (2010)

This paper presents of atomically controlled Ge-Sb-Te films that enable a suppression of switching energy, and an increase in speed faster than that using the composite films in Set and Reset. The first principle computer simulations using NVT ensemble dynamics and real device fabrication based on the model were carried out. We found that the obtained experimental data are in good agreement with the simulation models, and succeeded in suppressing the Reset energy by less than 10%.
MT-Diet: Automated smartphone based diet assessment with infrared images (2016)

In this paper, we propose MT-Diet, a smartphone-based automated diet monitoring system that interfaces a thermal camera with a smartphone and identifies types of food consumed at the click of a button. The system uses thermal maps of a food plate to increase accuracy of segmentation and extraction of food parts, and combines thermal and visual images to improve accuracy in the detection of cooked food. Test results on 80 different types of cooked food show that MT-Diet can isolate food parts with an accuracy of 97.5% and determine the type of food with an accuracy of 88.93%, which is a significant improvement (nearly 25%) over the state-of-the-art.
Shotgun Protein Sequencing by Tandem Mass Spectra Assembly (2004)

The analysis of mass spectrometry data is still largely based on identification of single MS/MS spectra and does not attempt to make use of the extra information available in multiple MS/MS spectra from partially or completely overlapping peptides. Analysis of MS/MS spectra from multiple overlapping peptides opens up the possibility of assembling MS/MS spectra into entire proteins, similarly to the assembly of overlapping DNA reads into entire genomes. In this paper, we present for the first time a way to detect, score, and interpret overlaps between uninterpreted MS/MS spectra in an attempt to sequence entire proteins rather than individual peptides. We show that this approach not only extends the length of reconstructed amino acid sequences but also dramatically improves the quality of de novo peptide sequencing, even for low mass accuracy MS/MS data.
Extreme energy efficiency using water cooled servers inside a chiller-less data center (2012)

The paper summarizes part of a project that was undertaken to develop highly energy efficient warm liquid cooled servers for use in chiller-less data centers that could save significant data center energy use and reduce data center refrigerant and make up water usage. One of the key concepts developed as part of this project is the Dual-Enclosure-Liquid-Cooling (DELC), which comprises of a 100% liquid cooled server cabinet and an outdoor dry cooler unit for heat rejection to the ambient and this configuration is used to reject the Information Technology (IT) equipment heat load directly to the outside ambient air without the use of a chiller. Demonstration hardware for server liquid cooling and a chiller-less data center was built and is operational for a 15 kW rack fully populated with liquid cooled servers which has been designed for use for up to 45°C liquid coolant to the rack. The anticipated benefits of such energy-centric configurations are significant energy savings of as much as 25% at the data center level. This paper builds on recent work that focused on the server liquid cooling, the rack enclosure with heat exchanger cooling and liquid distribution, and the data center level cooling infrastructure and which also presented sample data from experiments in support of the DELC concept. This paper presents experimental data related to the novel data center loop in a new manner, which is used to create a simplified thermodynamic model using curve-fit of surfaces of heat exchanger approach temperatures and power use of cooling devices. The model is validated using experimental data for a 22 hour test that was conducted in August of 2011. Subsequent to model validation, the simplified model is then used to make projections for DELC prototype performance (thermal and energy) under different conditions including different simple control schemes and weather conditions in the US. Weather data from nine different US cities is analyzed for a single day in August and realizable energy and energy cost savings over traditional chiller based data center cooling designs are presented. The results show that the new innovative data center cooling configuration presented could reduce cooling energy use to be less than 3.5% of the IT power for most US locations even in warm summer times of the year.
Library design in combinatorial chemistry by Monte Carlo methods (2000)

Strategies for searching the space of variables in combinatorial chemistry experiments are presented, and a random energy model of combinatorial chemistry experiments is introduced. The search strategies, derived by analogy with the computer modeling technique of Monte Carlo, effectively search the variable space even in combinatorial chemistry experiments of only modest size. Efficient implementations of the library design and redesign strategies are feasible with current experimental capabilities.
A Design Methodology for Wide-Band Continuous-Time MASH ΣΔ ADC Architectures (2016)

This poster presents a design methodology for wideband continuous-time MASH ΣΔ ADCs that takes into account one clock cycle delay for each comparator. This enables the design of high-speed wide-band MASH ΣΔ ADCs, with high sampling rate and low OSR. The purpose of this research is to synthesize a continuous-time MASH ΣΔ ADC architecture suitable for wideband medium resolution ADC applications. The synthesis starts form a discrete-time MASH ΣΔ ADC architecture, with one clock cycle delay modelled for each comparator [1]. Then, discrete-time to continuous-time transformation technique similar as [2] is applied to determine the design parameters of the continuous-time MASH ΣΔ ADC architecture. Extra coefficients are introduced to provide the required additional degrees of freedom. Subsequently, a wide-band continuous-time MASH ΣΔ ADC architecture is synthesized, which is robust against loop delay variations. Extensive simulation results show the robustness and the advantages of the proposed methodology. It delivers a 9-level 1-1-1 wideband MASH ΣΔ ADC topology with 3.25 times larger signal BW when compared to the traditional approach with the same total loop delay and SNDR target. Compared to the state-of-the-art [3], it enlarges the signal BW by a factor of 2 through enabling 2 times higher sampling frequency without losing DR performance. Moreover, it facilitates the design and simulation procedures. All these properties make the proposed methodology very useful for designing wide-band medium resolution ΣΔ ADCs for high performance mixed-signal applications.
A novel soft-switching full-bridge DC/DC converter: analysis, design considerations, and experimental results at 1.5 kW, 100 kHz (1991)

The addition of an external commutating inductor and two clamp diodes to the phase-shifted PWM (pulsewidth modulated) full-bridge DC/DC converter substantially reduces the switching losses of the transistors and the rectifier diodes, under all loading conditions. The authors give analyses, practical design considerations, and experimental results for a 1.5 kW converter with 60 V, 25 A output, operating at 100 kHz clock frequency and 95% efficiency.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Fluoride Based Electrode Materials for Advanced Energy Storage Devices (2007)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 leading journals. To access a ChemInform Abstract, please click on HTML or PDF.
Engineering a simple lateral flow device for animal blood coagulation monitoring (2018)

Increasing numbers of animals are diagnosed with thromboembolism, requiring anticoagulation treatment to prevent thrombotic events. Frequent and periodic coagulation monitoring is critical to ensure treatment effectiveness and patient safety by limiting blood coagulation ability within the desired therapeutic range. Point-of-care diagnostics is an ideal candidate for frequent coagulation monitoring due to rapid test results and no need for laboratory setting. This article reports the first utilization of <i>no-reaction</i> lateral flow assay (nrLFA) device for simple and low-cost animal blood coagulation monitoring in resource-limited setting. The nrLFA device consists of sample pad, analytical membrane and wicking pad, without conjugate pad, reagent printing or membrane drying. Citrated and heparinized animal blood were utilized to mimic different blood coagulation abilities <i>in vitro</i> by adding reversal agents CaCl<sub>2</sub> and protamine sulfate. The travel distance of red blood cells (RBCs) on the nrLFA after a pre-determined test time serves as endpoint marker. Upon adding 500 mM CaCl<sub>2</sub> solution to citrated bovine, canine, rabbit and equine blood, the average travel distance decreases from 10.9 to 9.4 mm, 8.8 to 5.7 mm, 12.6 to 9 mm, and 15.3 to 11.3 mm, respectively. For heparinized bovine and rabbit blood, the average distance decreases from 14.5 to 11.4 mm and from 9.8 to 7.2 mm, respectively, when adding 300 mg/l protamine sulfate solution. The effect of hematocrit on RBC travel distance in the nrLFA was also investigated. The nrLFA device will potentially improve treatment efficiency, patient safety, quality of life, and satisfaction for both animal patients and their owners.
Manhattan rule training for memristive crossbar circuit pattern classifiers (2015)

We investigated batch and stochastic Manhattan Rule algorithms for training multilayer perceptron classifiers implemented with memristive crossbar circuits. In Manhattan Rule training, the weights are updated only using sign information of classical backpropagation algorithm. The main advantage of Manhattan Rule is its simplicity, which leads to more compact hardware implementation and faster training time. Additionally, in case of stochastic training, Manhattan Rule allows performing all weight updates in parallel, which further speeds up the training procedure. The tradeoff for simplicity is slightly worse classification performance. For example, simulation results showed that classification fidelity on Proben1 benchmark for memristor-based implementation trained with batch Manhattan Rule were comparable to that of classical backpropagation algorithm, and about 2.8 percent worse than the best reported results.
Hypothesis Validation of Far-Wall Brightness in Carotid-Artery Ultrasound for Feature-Based IMT Measurement Using a Combination of Level-Set Segmentation and Registration (2012)

Intima-media thickness (IMT) is now being considered as an indicator of atherosclerosis. Our group has developed several feature-based IMT measurement algorithms such as the Completely Automated Layer EXtraction (CALEX) (which is a class of patented AtheroEdge Systems from Global Biomedical Technologies, Inc., CA, USA). These methods are based on the hypothesis that the highest pixel intensities are in the far wall of the common carotid artery (CCA) or the internal carotid artery (ICA). In this paper, we verify that this hypothesis holds true for B-mode longitudinal ultrasound (US) images of the carotid wall. This patented methodology consists of generating the composite image (the arithmetic sum of images) from the database by first registering the carotid image frames with respect to a nearly straight carotid-artery frame from the same database using: (1) B-spline-based nonrigid registration and (2) affine registration. Prior to registration, we segment the carotid-artery lumen using a level-set-based algorithm followed by morphological image processing. The binary lumen images are registered, and the transformations are applied to the original grayscale CCA images. We evaluated our technique using a database of 200 common carotid images of normal and pathologic carotids. The composite image presented the highest intensity distribution in the far wall of the CCA/ICA, validating our hypothesis. We have also demonstrated the accuracy and improvement in the IMT segmentation result with our CALEX 3.0 system. The CALEX system, when run on newly acquired US images, shows the IMT error of about 30 μm. Thus, we have shown that the CALEX algorithm is able to exploit the far-wall brightness for accurate IMT measurements.
Multibit digital watermarking robust against local nonlinear geometrical distortions (2002)

This paper presents an efficient method for the estimation and recovering from nonlinear or local geometrical distortions, such as the random bending attack and restricted projective transforms. The distortions are modeled as a set of local affine transforms, the watermark being repeatedly allocated into small blocks in order to ensure its locality. The estimation of the affine transform parameters is formulated as a robust penalized maximum likelihood (ML) problem, which is suitable for the local level as well as for global distortions. Results with the Stirmark benchmark confirm the high robustness of the proposed method and show its state-of-the-art performance.
Thermally Reversible Hydrogels via Intramolecular Folding and Consequent Self-Assembly of a <i>de Novo</i> Designed Peptide (2003)

A small de novo designed peptide (MAX3) is described that exhibits complete thermoreversible self-assembly into a hydrogel network. Importantly, a prerequisite to hydrogelation is that the peptide must first fold into a conformation conducive to self-assembly. At ambient temperature, MAX3 is unfolded, resulting in a low viscosity aqueous solution. On increasing the temperature, the peptide undergoes a unimolecular folding event, affording an amphiphilic beta-hairpin that consequently self-assembles into a hydrogel network. Increasing the temperature serves to dehydrate the nonpolar residues of the unfolded peptide and trigger folding via hydrophobic collapse. Cooling the resultant hydrogel results in beta-hairpin unfolding and consequent complete dissolution of the hydrogel. The temperature at which folding and consequent self-assembly into a rigid hydrogel occur can be tuned by altering the hydrophobicity of the peptides.