gebhart/patrepeval huggingface dataset:
Molecular characterization of Pseudomonas putida KT2440 rpoH gene regulation The GenBank accession number for the sequence corresponding to the P. putida KT2440 chromosomal DNA fragment (2891 bp) cloned in pSH27, including the rpoH gene, is AF157048. (2001)

The rpoH gene of Pseudomonas putida KT2440 encoding the heat-shock sigma factor sigma(32) was cloned and sequenced, and the translated gene product was predicted to be a protein of 32.5 kDa. The unambiguous role of the gene as a sigma factor was confirmed because the cloned P. putida gene complemented the growth defect, at 37 and 42 degrees C, of an Escherichia coli rpoH mutant strain. Primer extension analysis showed that in P. putida the rpoH gene is expressed from three promoters in cells growing at 30 degrees C. Two of them, P1 and P3, share homology with the sigma(70)-dependent promoters, while the third one, P2, shows a typical sigma(24)-consensus sequence. The pattern of transcription initiation of the rpoH gene did not change in response to different stresses, i.e. a sudden heat shock or the addition of aromatic compounds. However, the predicted secondary structure of the 5' region of the mRNA derived from the three different promoters suggests regulation at the level of translation efficiency and/or mRNA half-life. An inverted repeat sequence located 20 bp downstream of the rpoH stop codon was shown to function as a terminator in vivo in P. putida growing at temperatures from 18 to 42 degrees C.
Process Variation Aware Analysis of SRAM SEU Cross Sections Using Data Retention Voltage (2018)

Static random access memory (SRAM) is one the most sensitive devices to radiation. It may often exhibit undesired reversals of memory bits, called single-event upsets or soft errors. Sensitivity to such undesired events is widely quantified with the parameter of cross sections, which varies from cell to cell due to process variations. Many efforts have been made to quantify such variations, most commonly using simulations that often become a hurdle especially for commercial-off-the-shelf SRAMs. In this regard, an analysis method is proposed to extract such variations easily from radiation test data. It relies on the data retention voltage, which is an electrical parameter associated with the static noise margin. This voltage can be measured on a desk without special circuits. The validity of the proposed method is experimentally demonstrated using SRAM fabricated in a 65-nm silicon-on-insulator technology, which was exposed to various high-energy heavy ions simulating the effects of galactic and terrestrial cosmic rays. Theoretical discussion provides further evidence, while revealing an interesting relationship between the data retention voltage and power supply voltage. This relationship suggests power-supply voltage tuning to deal with chip-to-chip variations in cross sections and also with similar variations caused by total-dose effects and aging effects such as negative bias temperature instability.
Dithiothreitol Causes HIV-1 Integrase Dimer Dissociation While Agents Interacting With the Integrase Dimer Interface Promote Dimer Formation (2011)

We have developed a homogeneous time-resolved fluorescence resonance energy transfer (FRET)-based assay that detects the formation of HIV-1 integrase (IN) dimers. The assay utilizes IN monomers that express two different epitope tags that are recognized by their respective antibodies, coupled to distinct fluorophores. Surprisingly, we found that dithiothreitol (DTT), a reducing agent essential for in vitro enzymatic activity of IN, weakened the interaction between IN monomers. This effect of DTT on IN is dependent on its thiol groups, since the related chemical threitol, which contains hydroxyls in place of thiols, had no effect on IN dimer formation. By studying mutants of IN, we determined that cysteines in IN appear to be dispensable for the dimer dissociation effect of DTT. Peptides derived from the IN binding domain (IBD) of lens epithelium derived growth factor/transcriptional coactivator p75 (LEDGF), a cellular cofactor that interacts with the IN dimer interface, were tested in this IN dimerization assay. These peptides, which compete with LEDGF for binding to IN, displayed an intriguing equilibrium binding dose-response curve characterized by a plateau rising to a peak, then descending to a second plateau. Mathematical modeling of this binding system revealed that these LEDGF-derived peptides promote IN dimerization and block subunit exchange between IN dimers. This dose-response behavior was also observed with a small molecule that interacts with the IN dimer interface and inhibits LEDGF binding to IN. In conclusion, this novel IN dimerization assay revealed that peptide and small molecule inhibitors of the IN-LEDGF interaction also stabilize IN dimers and promote their formation.
Erosion Prevention Potential of an Over-the-Counter Stabilized SnF2 Dentifrice Compared to 5000 ppm F Prescription-Strength Products. (2015)

Results from both studies demonstrated the OTC dentifrice formulated with stabilized SnF2 provides significantly greater protection against erosive acid attack compared to some of the most popular prescription level (5000 ppm F) fluoride treatments available.
Adaptive model-based motion estimation (1994)

A general discrete-time, adaptive, multidimensional framework is introduced for estimating the motion of one or several object features from their successive nonlinear projections on an image plane. The motion model consists of a set of linear difference equations with parameters estimated recursively from a nonlinear observation equation. The model dimensionality corresponds to that of the original, nonprojected motion space, thus allowing to compensate for variable projection characteristics such as paning and zooming of the camera. Extended recursive least-squares and linear-quadratic tracking algorithms are used to adaptively adjust the model parameters and minimize the errors of either smoothing, filtering or prediction of the object trajectories in the projection plane. Both algorithms are derived using a second order approximation of the projection nonlinearities. All the results presented here use a generalized vectorial notation suitable for motion estimation of any finite number of object features and various approximations of the nonlinear projection. The application of the model-based motion estimator for temporal decimation/interpolation in digital video sequence compression systems is presented.
A Comprehensive Study of Deep Learning for Side-Channel Analysis (2019)

Recently, several studies have been published on the application of deep learning to enhance Side-Channel Attacks (SCA). These seminal works have practically validated the soundness of the approach, especially against implementations protected by masking or by jittering. Concurrently, important open issues have emerged. Among them, the relevance of machine (and thereby deep) learning based SCA has been questioned in several papers based on the lack of relation between the accuracy, a typical performance metric used in machine learning, and common SCA metrics like the Guessing entropy or the key-discrimination success rate. Also, the impact of the classical side-channel counter-measures on the efficiency of deep learning has been questioned, in particular by the semi-conductor industry. Both questions enlighten the importance of studying the theoretical soundness of deep learning in the context of side-channel and of developing means to quantify its efficiency, especially with respect to the optimality bounds published so far in the literature for side-channel leakage exploitation. The first main contribution of this paper directly concerns the latter point. It is indeed proved that minimizing the Negative Log Likelihood (NLL for short) loss function during the training of deep neural networks is actually asymptotically equivalent to maximizing the Perceived Information introduced by Renauld et al. at EUROCRYPT 2011 as a lower bound of the Mutual Information between the leakage and the target secret. Hence, such a training can be considered as an efficient and effective estimation of the PI, and thereby of the MI (known to be complex to accurately estimate in the context of secure implementations). As a second direct consequence of our main contribution, it is argued that, in a side-channel exploitation context, choosing the NLL loss function to drive the training is sound from an information theory point of view. As a third contribution, classical counter-measures like Boolean masking or execution flow shuffling, initially dedicated to classical SCA, are proved to stay sound against deep Learning based attacks.
X‐Ray crystallographic analysis of a ternary intercalation complex between proflavine and the dinucleoside monophosphates CpA and UpG (1984)

Abstract We report the crystal‐structure analysis of a complex involving the drug proflavine and the two dinucleoside monophosphates cytidylyl‐3′,5′‐adenosine (CpA) and uridylyl‐3′,5′‐guanosine (UpG). The planar drug molecule is intercalated between C ⃛G and U ⃛A Watson‐Crick base pairs, in a double‐helical fragmentlike arrangement. Sugar conformations at the 3′‐ends of the two strands are dissimilar. The backbone conformations fall within the ranges of values noted previously for dinucleoside intercalation complexes, and some correlations involving these are noted. The separation of the two strands and the basic twist angle of 16°, compared to other reported complexes, are indicative of sequence‐dependent effects of the drug binding.
On the Privacy–Utility Trade-Off in Differentially Private Hierarchical Text Classification (2022)

Hierarchical text classification consists of classifying text documents into a hierarchy of classes and sub-classes. Although Artificial Neural Networks have proved useful to perform this task, unfortunately, they can leak training data information to adversaries due to training data memorization. Using differential privacy during model training can mitigate leakage attacks against trained models, enabling the models to be shared safely at the cost of reduced model accuracy. This work investigates the privacy–utility trade-off in hierarchical text classification with differential privacy guarantees, and it identifies neural network architectures that offer superior trade-offs. To this end, we use a white-box membership inference attack to empirically assess the information leakage of three widely used neural network architectures. We show that large differential privacy parameters already suffice to completely mitigate membership inference attacks, thus resulting only in a moderate decrease in model utility. More specifically, for large datasets with long texts, we observed Transformer-based models to achieve an overall favorable privacy–utility trade-off, while for smaller datasets with shorter texts, convolutional neural networks are preferable.
Influence of carbohydrate moieties on the immunogenicity of human immunodeficiency virus type 1 recombinant gp160 (1992)

The role of carbohydrates in the immunogenicity of human immunodeficiency virus type 1 (HIV-1) glycoproteins (gp160 and gp120) remains poorly understood. We have analyzed the specificity and neutralizing capacity of antibodies raised against native gp160 or against gp160 deglycosylated by either endo F-N glycanase, neuraminidase, or alpha-mannosidase. Rabbits immunized with these immunogens produced antibodies that recognized recombinant gp160 (rgp160) from HIV-1 in a radioimmunoassay and in an enzyme-linked immunosorbent assay. Antibodies elicited by the different forms of deglycosylated gp160 were analyzed for their reactivity against a panel of synthetic peptides. Compared with anti-native gp160 antisera, serum reactivity to most peptides remained unchanged, or it could increase (peptide P41) or decrease. Only antibodies raised against mannosidase-treated gp160 failed to react with a synthetic peptide (peptide P29) within the V3 loop of gp120. Rabbits immunized with desialylated rgp160 generated antibodies which recognized not only rgp160 from HIV-1 but also rgp140 from HIV-2 at high titers. Although all antisera produced against glycosylated or deglycosylated rgp160 could prevent HIV-1 binding to CD4-positive cells in vitro, only antibodies raised against native or desialylated gp160 neutralized HIV-1 infectivity and inhibited syncytium formation between HIV-1-infected cells and noninfected CD4-positive cells, whereas antibodies raised against alpha-mannosidase-treated gp160 inhibited neither virus replication nor syncytium formation. These findings indicate that the carbohydrate moieties of gp160 can modulate the specificity and the protective efficiency of the antibody response to the molecule.
Induction of Apoptosis by [8]-Shogaol via Reactive Oxygen Species Generation, Glutathione Depletion, and Caspase Activation in Human Leukemia Cells (2010)

Ginger, the rhizome of Zingiber officinale , is a traditional medicine with a carminative effect and antinausea, anti-inflammatory, and anticarcinogenic properties. This study examined the growth inhibitory effects of [8]-shogaol, one of the pungent phenolic compounds in ginger, on human leukemia HL-60 cells. It demonstrated that [8]-shogaol was able to induce apoptosis in a time- and concentration-dependent manner. Treatment with [8]-shogaol caused a rapid loss of mitochondrial transmembrane potential, stimulation of reactive oxygen species (ROS) production, release of mitochondrial cytochrome c into cytosol, and subsequent induction of procaspase-9 and procaspase-3 processing. Taken together, these results suggest for the first time that ROS production and depletion of glutathione that contributed to [8]-shogaol-induced apoptosis in HL-60 cells.
Data from Expression of L1-CAM and ADAM10 in Human Colon Cancer Cells Induces Metastasis (2023)

&lt;div&gt;Abstract&lt;p&gt;L1-CAM, a neuronal cell adhesion receptor, is also expressed in a variety of cancer cells. Recent studies identified &lt;i&gt;L1-CAM&lt;/i&gt; as a target gene of β-catenin-T-cell factor (TCF) signaling expressed at the invasive front of human colon cancer tissue. We found that L1-CAM expression in colon cancer cells lacking L1-CAM confers metastatic capacity, and mice injected in their spleen with such cells form liver metastases. We identified &lt;i&gt;ADAM10&lt;/i&gt;, a metalloproteinase that cleaves the L1-CAM extracellular domain, as a novel target gene of β-catenin-TCF signaling. ADAM10 overexpression in colon cancer cells displaying endogenous L1-CAM enhanced L1-CAM cleavage and induced liver metastasis, and ADAM10 also enhanced metastasis in colon cancer cells stably transfected with L1-CAM. DNA microarray analysis of genes induced by L1-CAM in colon cancer cells identified a cluster of genes also elevated in a large set of human colon carcinoma tissue samples. Expression of these genes in normal colon epithelium was low. These results indicate that there is a gene program induced by L1-CAM in colon cancer cells that is also present in colorectal cancer tissue and suggest that L1-CAM can serve as target for colon cancer therapy. [Cancer Res 2007;67(16):7703–12]&lt;/p&gt;&lt;/div&gt;
G060022 Nitric oxide (NO) prediction for Large Eddy Simulation (LES) of propane jet non-premixed flame (2012)

In this study a LES of propane confined turbulent jet diffusion flame in a cylindrical furnace is performed using Partial Stirred Reactor (PaSR) as combustion model with a 29 species/69 reactions mechanism. In order to speed up simulation, tabulation of the chemistry was done using In Situ Adaptive Tabulation (ISAT) method. NO emissions were estimated in a post-processing way using a nitrogen chemistry sub-mechanism comprising extended Zeldovich, N_2O intermediate, NNH intermediate, prompt and reburning NOx production pathways. On this sub-mechanism, steady-state assumptions were applied to minor radicals considering only a couple of independent reactive species. Results of the finite-rate chemistry PaSR LES were compared to previous experiments and reasonable agreement was obtained.
An Offset Panel Technique for Thick Rigidily Foldable Origami (2014)

A technique for thickness accommodation in origami-inspired mechanism design is introduced. Mathematically, origami panels are generally assumed to be planar with zero thickness. Origami models can be viewed as kinematic mechanisms where folds are revolute joints and panels are links. An origami-inspired mechanism can achieve the same kinematic motion as the paper origami source model if all joints lie along the folds in the zero-thickness plane. The panels are stacked in sequence in the closed (stowed) position. A joint plane is chosen and each panel is given extensions connecting each panel to the chosen plane. The extensions from the stacked panels allow each panel to be rigidly connected to its revolute joint in the chosen plane with all other joints. The accommodation technique utilizes origami models that are rigidly foldable. The height of the extensions are determined by the sum of the thicknesses of all panels between its stowed panel and the chosen joint plane. Any panel thickness can be accommodated, including multiple panel thicknesses within the same mechanism. Process steps for offset panel design of origami-inspired mechanisms are presented.
Deterministic approach to polarization mode dispersion (2004)

Polarization Mode Dispersion (PMD) is considered to be one of the most serious obstacles in the high speed optical telecommunication systems. This thesis focuses on a deterministic approach to both compensation and emulation of PMD. Most PMD compensation schemes in the literature rely on feedback loops to search for the optimum control parameters in the compensator. These schemes often suffer from slow response time and are limited to compensating the low orders of PMD. Adding control parameters to enable higher-order PMD compensation further increases the complexity of the feedback algorithm and its response time. As PMD can vary as fast as on a millisecond time scale, a potential method to alleviate this problem is to employ a deterministic approach to PMD compensation where the PMD parameters are first diagnosed and the compensator then set accordingly. One of the most challenging problems to this deterministic approach is the real-time monitoring of the PMD information. We propose an improved version of the PMD estimation technique using polarization scrambling and optical filtering. Once
Development of a distributed cooperative scheduling system based on negotiations between scheduling agents (2000)

Using a single concentrated scheduling system in a large-scale manufacturing system is problematic. As a result, scheduling systems are being introduced in departmental units, which has resulted in having to repeat schedule adjustments between departments whenever there is a change in one department. Therefore, the authors propose a horizontal distributed scheduling system to create speed and localization in schedule adjustments which occur frequently between departments by introducing a multiagent model to perform negotiations between schedulers by using each department's scheduler as an agent. The negotiations between schedulers in this system are characterized by defining the negotiation protocol which controls the flow of the negotiations so as to maintain consistency between schedulers and by introducing a mechanism to enable simultaneous execution of multiple negotiations so as to create speed in schedule adjustments. In addition, the authors evaluated the application of this system to scheduling problems in a real multiple work job shop. They confirmed that speed was achieved through simultaneous implementation of multiple negotiations while at the same time consistency in schedules was maintained via negotiations between schedulers. © 1999 Scripta Technica, Syst Comp Jpn, 31(1): 92–101, 2000
Origin of the OFF state variability in ReRAM cells (2014)

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
3D MRI-Controlled Transurethral Ultrasound Prostate Therapy: Experimental Validation of Numerical Simulations (2011)

MRI‐guided transurethral ultrasound therapy uses a linear array of transducer elements and active temperature feedback to create volumes of thermal coagulation shaped to predefined prostate geometries in 3‐D. Numerical simulations have been used to determine robust feedback control algorithms, optimal transducer designs, effects of various tissue and imaging parameters, as well as to evaluate potential treatment accuracy and safety in patient‐specific anatomical models. The goal of this work is to evaluate quantitatively the accuracy with which these numerical simulations predict the extent, shape and temperature pattern of 3‐D heating produced in tissue‐mimicking Zerdine* gel phantoms. Methods. Eleven experiments were performed in a 1.5T MRI scanner. Temperature feedback was used to control the rotation rate and ultrasound power of a transurethral device with five 3.5×5 mm transducer elements. Heating patterns shaped to 23 and 11 cc human prostate geometries were generated using devices operating at 4.7 and 8.0 MHz, respectively, and 10 W/cm2 surface acoustic intensity. Transducer surface velocity measurements were acquired using a vibrometer and used to calculate the resulting acoustic pressure distribution in gel. Temperature dynamics were determined according to a FDTD solution to Pennes’ BHTE. Results. The numerical simulations predicted the extent and shape of the coagulation boundary produced in gel to within (mean±stdev [min, max]): 0.1±0.4 [−1.4, 1.7] and 0.0±0.3 [−1.0, 1.5] mm for the treatments at 4.7 and 8.0 MHz, respectively. The temperatures across all MRI thermometry images were predicted to within 10%, and the treatment time (∼20 min) to within 20%. The simulations showed excellent agreement in regions of sharp temperature gradients, near the transurethral and endorectal devices. Conclusion. Heating patterns predicted by the numerical simulations correspond closely to those produced experimentally in gel. This work quantifies the accuracy and demonstrates the validity of using numerical simulations to model MRI‐guided transurethral ultrasound prostate therapy.
Selecting cases and controls for DNA sequencing studies using family histories of disease (2017)

Recent improvements in sequencing technology have enabled the investigation of so-called missing heritability, and a large number of affected subjects have been sequenced in order to detect significant associations between human diseases and rare variants. However, the cost of genome sequencing is still high, and a statistically powerful strategy for selecting informative subjects would be useful. Therefore, in this report, we propose a new statistical method for selecting cases and controls for sequencing studies based on family history. We assume that disease status is determined by unobserved liability scores. Our method consists of two steps: first, the conditional means of liability are estimated with the liability threshold model given the individual's disease status and those of their relatives. Second, the informative subjects are selected with the estimated conditional means. Our simulation studies showed that statistical power is substantially affected by the subject selection strategy chosen, and power is maximized when affected (unaffected) subjects with high (low) risks are selected as cases (controls). The proposed method was successfully applied to genome-wide association studies for type 2 diabetes, and our analysis results reveal the practical value of the proposed methods. Copyright © 2017 John Wiley & Sons, Ltd.