gebhart/patrepeval huggingface dataset:
Endoanorectal Ultrasonography (2011)

Endoanorectal ultrasonography (EARUS) may be used for diagnosing various anorectal disorders. EARUS is easy to perform, has a short learning curve, and causes less discomfort than routine digital examination. Anal sphincters can be clearly visualized, and one can easily distinguish between the internal (hypoechoic) and external (hyperechoic) anal sphincters. Other pelvic floor structures, like the puborectalis muscle, can also be visualized. The use of contrast agents can increase the accuracy of EARUS in the assessment of perianal fistulae. In addition, EARUS is an excellent alternative to expensive magnetic resonance imaging. Besides its use in incontinence and perianal sepsis, the presence of slight or massive submucosal invasion in early rectal cancer may be imaged in greater detail. With 3-dimensional EARUS, it is possible to diagnose the anorectal diseases, in multiplane, with high spatial resolution, adding important information about the therapeutic decision. The normal sonographic anatomy of the anorectum, sonographic findings of anorectal diseases, and indications and limitations of endosonography with complementary techniques such as transvaginal and transperineal ultrasound are reviewed in this article.
Solving Sudoku, a constraint satisfaction problem, through structured interactions between stochastically firing excitatory and inhibitory neurons. (2015)

&lt;p&gt;&lt;b&gt;A&lt;/b&gt;. A “hard” Sudoku puzzle with 26 given numbers (left). The solution (right) is defined uniquely by the set of givens and the additional constraints that each digit must appear only once in each row, column and 3×3 subgrid. &lt;b&gt;B&lt;/b&gt;. An implementation of the constraints of the Sudoku game in a spiking neural network consists of overlapping WTA circuits. WTA circuits are ubiquitous connection motifs in cortical circuits &lt;a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003311#pcbi.1003311-Douglas1" target="_blank"&gt;[29]&lt;/a&gt;. A WTA circuit can be modeled by a set of stochastically spiking output neurons that are subject to lateral inhibition (left). The same pyramidal cell can be part of several such WTA motifs (right). In the Sudoku example, each digit in a Sudoku field is associated with four pyramidal cells which vote for this digit when they emit a spike. Each such pyramidal cell participates in four WTA motifs, corresponding to the constraints that only one digit can be active in each Sudoku field, and that a digit can appear only once in each row, column and 3×3 subgrid. &lt;b&gt;C&lt;/b&gt;. A typical network run is shown during the last before the correct solution was found to the Sudoku from panel A (the total solve time was approximately in this run, see panel D for statistics of solve times). The network performance (fraction of cells with correct values) over time is shown at the top. The spiking activity is shown for 3 (out of the 81) WTA motifs associated with the 3 colored Sudoku fields in A and B. In each of these WTA motifs there are 36 pyramidal cells (9 digits and 4 pyramidal cells for each digit). Spikes are colored green for those neurons which code for the correct digit in each Sudoku field (6, 8 and 4 in the example). &lt;b&gt;D&lt;/b&gt;. Histogram of solve times (the first time the correct solution was found) for the Sudoku from panel A. Statistics were obtained from 1000 independent runs. The sample mean is . &lt;b&gt;E&lt;/b&gt;. Average network performance for this Sudoku converges quickly during the first five seconds to a value of , corresponding to % correctly found digits (average taken over 1000 runs; shaded area: standard deviations). Thereafter, from all possible configurations the network spends most time in good approximate solutions. The correct solution occurs particularly often, on average approximately 2% of the time (not shown).&lt;/p&gt;
An adjuvant strategy enabled by modulation of the physical properties of fungal mannans elicits pan-coronavirus reactive anti-SARS-CoV-2 Spike antibodies (2021)

Abstract Activation of the innate immune system via pattern recognition receptors (PRRs) is key to generate long-lasting adaptive immunity. While it is known that PRRs detect unique chemical patterns associated with invading microorganism, if and how the physical properties of PRR ligands influence development of the immune response is largely overlooked. Through the study of fungal mannans we present data that put the physical form of PRR ligands at the center of the process that determines the outcome of the immune response. Soluble mannans are immunosilent in the periphery but elicit a potent pro-inflammatory response in the draining lymph node (dLN). By modulating the physical form of mannans, we developed a formulation that targets both periphery and dLN. When combined with SARS-CoV-2 Spike, this formulation elicits neutralizing anti-SARS-CoV-2 antibodies that cross-react with pathogenic coronaviruses. Thus, the physical properties of fungal ligands can be harnessed for rational adjuvant design and vaccine development.
Ab initio optical study of graphene on hexagonal boron nitride and fluorographene substrates (2012)

The fascinating optical properties of graphene are usually concluded in theory under the assumption that graphene is freestanding. However, in experimentally realizable devices, graphene is usually supported by a substrate, which may influence the optical properties of the graphene. Choosing the right substrate is therefore critical for graphene electromagnetic (EM) devices. In this paper, we studied the influence of two types of two-dimensional (2D) insulating substrates, hexagonal boron nitride (h-BN) and fluorographene (FG), on the graphene optical properties at room temperature. Our work shows that both substrates can preserve well the optical properties of graphene from 0.6 eV to 3.5 eV and the FG substrate can retain graphene’s original properties much better than the h-BN substrate when the photon energy is <0.6 eV or >3.5 eV. Besides, by analyzing the Kubo formula, the relaxation time of non-freestanding graphene, which can reflect the substrate–graphene interaction, is highly dependent on the substrate type and its stacking pattern. A THz graphene surface plasmonic modulator is used to further explain the substrate effect on graphene EM device design. Our results demonstrate that the h-BN substrate may degrade or fail the performance of THz (<0.1 eV) graphene modulator originally designed from freestanding graphene properties, while replacing h-BN with FG substrate or increasing the working frequency (>0.2 eV) can overcome the performance degradation. Finally, the substrate effects on graphene properties are also studied by examining the electronic properties of double-layer structures. Our results on the sensitivity issue that are caused by the stacking pattern and inter-layer distance may provide a reasonable explanation on the inconsistency of substrate-induced bandgap opening in graphene/h-BN heterostructures discussed in recent experimental and theoretical studies.
Taxonomy and genomics of Kazachstania yeasts from sourdough (2016)

Introduction: Yeast diversity has now been well investigated in natural sourdoughs isolated from Asian and European countries. However, the yeast diversity of natural sourdoughs made of organic wheat has never been studied. Microbial and molecular approaches to study this type of sourdoughs from France revealed that Saccharomyces cerevisiae was not the dominant species, questioning its implication as natural baker yeast and most dominant yeast species belong to the Kazachstania clade (Lhomme et al, 2016). Results and Discussion: Using ribosomal RNA gene and protein coding gene sequences, a thorough taxonomic analysis of sourdough strains isolated from France, identified two novel species in a subclade of the Kazachstania clade known to harbor a number of baker’s yeasts, such as Candida humilis and Candida milleri. In addition, two other novel species were identified in this subclade, one from rotting wood in Brazil and one from soil in South Africa, the latter consisting of a strain previously wrongly assigned to the Kazachstania exigua species. Further analysis revealed that the K. exigua species was very heterogeneous and made of haploid, alloploid and hybrid isolates, as suggested by Bon et al. (2000). Comparison of the genome of strains from sourdough and their corresponding type strains identified a number of specific genes, but did not show extensive differences at the genomic level, suggesting that strains isolated from sourdough differ mainly from non-sourdough strains at the transcriptional level. Finally, sequence analysis of major baker’s yeasts revealed several features, such as rearrangements at the mating type loci, distribution of Whole Genome Distribution gene blocks and distribution of transposons. These will be discussed.
Supplementary Methods from The Discovery of SWI/SNF Chromatin Remodeling Activity as a Novel and Targetable Dependency in Uveal Melanoma (2023)

&lt;p&gt;Additional method details for ATAC-Seq Data Analysis and ChIP-qPCR&lt;/p&gt;
Anion-Exchange Nanospheres as Titration Reagents for Anionic Analytes (2015)

We present here anion-exchange nanospheres as novel titration reagents for anions. The nanospheres contain a lipophilic cation for which the counterion is initially Cl(-). Ion exchange takes place between Cl(-) in the nanospheres and a more lipophilic anion in the sample, such as ClO4(-) and NO3(-). Consecutive titration in the same sample solution for ClO4(-) and NO3(-) were demonstrated. As an application, the concentration of NO3(-) in spinach was successfully determined using this method.
Highly Stretchable Fully-Printed CNT-Based Electrochemical Sensors and Biofuel Cells: Combining Intrinsic and Design-Induced Stretchability (2015)

We present the first example of an all-printed, inexpensive, highly stretchable CNT-based electrochemical sensor and biofuel cell array. The synergistic effect of utilizing specially tailored screen printable stretchable inks that combine the attractive electrical and mechanical properties of CNTs with the elastomeric properties of polyurethane as a binder along with a judiciously designed free-standing serpentine pattern enables the printed device to possess two degrees of stretchability. Owing to these synergistic design and nanomaterial-based ink effects, the device withstands extremely large levels of strains (up to 500% strain) with negligible effect on its structural integrity and performance. This represents the highest stretchability offered by a printed device reported to date. Extensive electrochemical characterization of the printed device reveal that repeated stretching, torsional twisting, and indenting stress has negligible impact on its electrochemical properties. The wide-range applicability of this platform to realize highly stretchable CNT-based electrochemical sensors and biofuel cells has been demonstrated by fabricating and characterizing potentiometric ammonium sensor, amperometric enzyme-based glucose sensor, enzymatic glucose biofuel cell, and self-powered biosensor. Highly stretchable printable multianalyte sensor, multifuel biofuel cell, or any combination thereof can thus be realized using the printed CNT array. Such combination of intrinsically stretchable printed nanomaterial-based electrodes and strain-enduring design patterns holds considerable promise for creating an attractive class of inexpensive multifunctional, highly stretchable printed devices that satisfy the requirements of diverse healthcare and energy fields wherein resilience toward extreme mechanical deformations is mandatory.
An intelligent proactive defense against the client‐side DNS cache poisoning attack via self‐checking deep reinforcement learning (2022)

A new class of poisoning attacks has recently emerged targeting the client-side Domain Name System (DNS) cache. It allows users to visit fake websites unconsciously, thereby revealing their information, such as passwords. However, the current DNS defense architecture does not include DNS clients. Although relative encryption solutions can mitigate this attack, they require the cooperation of multiple parties, and the deployment speed is slow. Therefore, we propose an intelligent-driven proactive defense strategy. First, we model the offensive and defensive process as a stochastic game based on moving target defense. Second, we adopt and optimize Proximal Policy Optimization (PPO), a deep reinforcement learning method, to solve problems caused by uncertain attack strategies and unknown state transition probability. Third, we design a self-checking component in PPO to solve the uncertainty of action space caused by game state constraints based on our previous work. Thus the convergence speed and stability of PPO are improved. Finally, to the best of our knowledge, we are the first to game with intelligent attackers besides three conventional ones. Our strategy does not require any modifications to the DNS architecture. Through an extensive experimental campaign, the prototype system is proved to be effective against multiple attack modes. Its success rate is 98.5% approximately, and network round-trip time is about 55 ms. Even for random attackers, our method can achieve the theoretical maximum defensive success rate.
Characterization of a water radiofrequency plasma - An experimental investigation (2009)

Interrelated energy and climate challenges are among the most important global issues of today. The existing supplies of fossil fuels will deplete based on the current rate of consumption; and the increase in anthropogenic carbon dioxide emissions as a result of burning fossil fuels challenges the sustainability of our planet. Therefore, the need to reduce consumption of fossil fuels and a transition into an economy less dependent on hydrocarbons is urgently necessary. On this quest to find alternative energy sources, one proposed solution is to use another secondary energy source besides electricity - hydrogen. Hydrogen as an energy carrier can fulfill a portion of the energy demand, particularly in the transportation sector when used in fuel cells. However, less than four percent of the world's hydrogen is produced via renewable methods, primarily through "clean" electrolysis. The remaining 96% is produced from non-renewable methods including methane steam reformation and coal gasification, with an energy efficiency much higher than that of electrolysis. This project investigates the potential use of a radio-frequency plasma source to dissociate water molecules into their constituent parts, hydrogen and oxygen, for hydrogen production application. A radio-frequency (RF) plasma source with a helicon-type antenna and an axial magnetic field is used in this work. A water plasma is produced and sustained in this source. This presentation characterizes the properties of this water RF plasma source by using the following diagnostics: a Langmuir probe, a residual gas analyzer, and a spectrometer. The Langmuir probe provides information on electron temperature and electron number density. Both the residual gas analyzer and the spectrometer are used to identify the species in the plasma. An estimated energy efficiency for hydrogen production in an RF plasma source is given. Results of this work confirm that it is feasible to break up the O-H bonds in water molecules in an RF plasma source. However, the estimated energy efficiency of this method, in its current configuration and within its permissible range of operating conditions, cannot exceed that of electrolysis.
Sparse-firing regularization methods for spiking neural networks with time-to-first spike coding (2023)

The training of multilayer spiking neural networks (SNNs) using the error backpropagation algorithm has made significant progress in recent years. Among the various training schemes, the error backpropagation method that directly uses the firing time of neurons has attracted considerable attention because it can realize ideal temporal coding. This method uses time-to-first spike (TTFS) coding, in which each neuron fires at most once, and this restriction on the number of firings enables information to be processed at a very low firing frequency. This low firing frequency increases the energy efficiency of information processing in SNNs, which is important not only because of its similarity with information processing in the brain, but also from an engineering point of view. However, only an upper limit has been provided for TTFS-coded SNNs, and the information-processing capability of SNNs at lower firing frequencies has not been fully investigated. In this paper, we propose two spike timing-based sparse-firing (SSR) regularization methods to further reduce the firing frequency of TTFS-coded SNNs. The first is the membrane potential-aware SSR (M-SSR) method, which has been derived as an extreme form of the loss function of the membrane potential value. The second is the firing condition-aware SSR (F-SSR) method, which is a regularization function obtained from the firing conditions. Both methods are characterized by the fact that they only require information about the firing timing and associated weights. The effects of these regularization methods were investigated on the MNIST, Fashion-MNIST, and CIFAR-10 datasets using multilayer perceptron networks and convolutional neural network structures.
Relation of Ventricular Premature Complexes to Heart Failure (from the Atherosclerosis Risk In Communities [ARIC] Study) (2020)

Analogous to rapid ventricular pacing, frequent ventricular premature complexes (VPCs) may predispose over time to cardiomyopathy and subsequent heart failure (HF). We examined the association of frequent VPCs with HF incidence in a population-based cohort, free of HF and coronary heart disease (CHD) at baseline. At study baseline (1987-89), at least one VPC on a 2-minute rhythm ECG strip was seen in 5.5% (739/13486) of the middle aged (45-64 years old at baseline), white and African-American, men and women of the ARIC cohort. Incident HF was defined as the first appearance of ICD code ‘428.x’ in hospital discharge record or death certificate through 2005. Over an average follow up of 15.6 years, incident HF was seen in 10% subjects (19.4% in those with VPCs vs. 9.4% in those without). The age, race, and gender adjusted hazard ratio (HR) of HF for VPCs was 1.89 (95% CI = 1.59, 2.24). After multivariable adjustment for potential confounders, HR (95% CI) of HF for those with any VPC vs. no VPCs was 1.63 (1.36, 1.96). After additional adjustment for incident CHD as a time-varying covariate, the HR (95% CI) was 1.71 (1.42, 2.08). Presence of higher frequency of VPCs or complex VPCs had similar rates of HF as compared to single VPC and all were higher than no VPC group. In conclusion, in this large population based cohort, presence of VPCs is associated with incident HF independent of incident CHD.
CT synthesis in the head & neck and pelvic regions for radiotherapy treatment planning (2016)

International audience
Subsidizing Altruism in Living Organ Donation. (2014)

Background: In 2008 the Department of Health and Human Services began to reimburse donors' travel-related expenses via the National Living Donor Assistance Center (NLDAC). Eligibility is limited to donors and recipients with incomes below 300% of the poverty level. Donors file applications for reimbursement through hospitals. Taking advantage of variation in the time when hospitals signed-up for the program, we estimate the impact of the NLDAC on the number of non-pediatric living donor transplants. Methods: Using UNOS data for all non-pediatric living organ transplants conducted between 2003 and 2012 we construct a data set consisting of the total number of transplants conducted per a month for all transplant centers conducting non-pediatric living donor transplants within the United States. This data is merged with a data set identifying all transplant centers that elected to participate in NLDAC as well as the number of applications filed with NLDAC each year. Additional control variables were constructed to control for a center's current regulatory status with CMS, the length of their current waiting list and time-varying and transplant center controls. Using a difference-in-difference estimation strategy, controlling for the inherent selection problem that arises in this environment, we estimate the causal relationship between participation in the NLDAC program and the effect it has on non-pediatric living organ transplantation. Results: Using a set of control variables to take advantage of the timing when hospitals enroll in NLDAC as well as selection into the program our difference-in-difference estimator estimates the causal relationship between participation in NLDAC and non-pediatric living organ transplantation. We find that the program increased the number of living donor transplants by 12%. Furthermore, we find that the treatment effect is heterogeneous across transplant centers and that these results are robust to empirical falsification tests. Conclusion: Although the returns from receiving a living donor transplant (versus waiting for a deceased donor organ) are large, apparently many donors and recipients are unable or unwilling to incur the upfront travel-related expenses. The NLDAC was an effective subsidy for donor's altruism.
Generation of Mid-IR laser by PPMgLN OPO/DFG configuration (2005)

We generated mid-IR laser in absorptive wavelength region around 6.1 /spl mu/m by combining QPM OPO and extra-cavity QPM DFG. The emission wavelength in OPO deviated from the prediction by reported Sellmeier equation in Mg:LN.
Detection of lipid in atherosclerotic vessels using ultrasound-guided spectroscopic intravascular photoacoustic imaging (2010)

Lipid is a common constituent in atherosclerotic plaques. The location and area of the lipid region is closely related to the progression of the disease. Intravascular photoacoustic (IVPA) imaging, a minimally invasive imaging modality, can spatially resolve the optical absorption property of arterial tissue. Based on the distinct optical absorption spectrum of fat in the near infrared wavelength range, spectroscopic IVPA imaging may distinguish lipid from other water-based tissue types in the atherosclerotic artery. In this study, a bench-top spectroscopic IVPA imaging system was used to ex-vivo image both atherosclerotic and normal rabbit aortas. By combing the spectroscopic IVPA image with the intravascular ultrasound (IVUS) image, lipid regions in the aorta were identified. The results demonstrated that IVUS-guided spectroscopic IVPA imaging is a promising tool to differentiate lipid in atherosclerosis.
Enhancement of SPM Spectral Broadening by Slow Self-Focusing Nonlinearity in Homogeneous Media (2012)

We demonstrate experimentally 400 times enhancement of SPM spectral broadening in bulk crystal by self-focusing nonlinearity that responds only to the time-averaged intensity. The slow nonlinearity enhances and stabilizes the broadening by suppressing the diffraction.