gebhart/patrepeval huggingface dataset:
First Characterization and Performance Evaluation of Bistatic TanDEM-X Experimental Products (2015)

TanDEM-X is an innovative bistatic and interferometric mission comprising the two twin synthetic aperture radar (SAR) satellites TerraSAR-X and TanDEM-X, which fly in a configurable close formation with the main goal to generate a global, high-accurate, and homogeneous digital elevation model (DEM) of the Earth's surface. The DEM is acquired in bistatic stripmap single polarization mode. On top of that, due to the flexibility offered by operating both satellites in different interferometric and imaging constellations, combinations of several experimental modes are possible. A dedicated science phase of the mission started in October 2014 and opened the full exploitation of such experimental modes. These unique data will support a variety of scientific remote sensing applications and will demonstrate new and innovative SAR techniques. In this paper, the expected SAR and interferometric performance of the operationally processed experimental modes available during the bistatic global DEM acquisition phase is modeled and characterized with in-orbit data. Key parameters for the determination of the quality of an SAR product, such as image resolution or noise equivalent sigma zero, or for the interferometric performance estimation, such as coherence or relative height error, are analyzed. Finally, possibilities to increase the quality of the generated DEMs are addressed.
Meshfree particle method (2003)

Many of the computer vision algorithms have been posed in various forms of differential equations, derived from minimization of specific energy functionals, and the finite element representation and computation have become the de facto numerical strategies for solving these problems. However, for cases where domain mappings between numerical iterations or image frames involve large geometrical shape changes, such as deformable models for object segmentation and nonrigid motion tracking, these strategies may exhibit considerable loss of accuracy when the mesh elements become extremely skewed or compressed. We present a new computational paradigm, the meshfree particle method, where the object representation and the numerical calculation are purely based on the nodal points and do not require the meshing of the analysis domain. This meshfree strategy can naturally handle large deformation and domain discontinuity issues and achieve desired numerical accuracy through adaptive node and polynomial shape function refinement. We discuss in detail the element-free Galerkin method, including the shape function construction using the moving least square approximation and the Galerkin weak form formulation, and we demonstrate its applications to deformable model based segmentation and mechanically motivated left ventricular motion analysis.
Open Computing Grid for Molecular Science and Engineering (2006)

Grid is an emerging infrastructure for distributed computing that provides secure and scalable mechanisms for discovering and accessing remote software and data resources. Applications built on this infrastructure have great potential for addressing and solving large scale chemical, pharmaceutical, and material science problems. The article describes the concept behind grid computing and will present the OpenMolGRID system that is an open computing grid for molecular science and engineering. This system provides grid enabled components, such as a data warehouse for chemical data, software for building QSPR/QSAR models, and molecular engineering tools for generating compounds with predefined chemical properties or biological activities. The article also provides an overview about the availability of chemical applications in the grid.
Compressive Initial Access and Beamforming Training for Millimeter-Wave Cellular Systems (2019)

Initial access (IA) is a fundamental procedure in cellular systems where user equipment (UE) detects base station (BS) and acquires synchronization. Due to the necessity of using antenna arrays for IA in millimeter-wave (mmW) systems, BS simultaneously performs beam training to acquire angular channel state information. The state-of-the-art directional IA (DIA) uses a set of narrow sounding beams in IA, where different beam pairs are sequentially measured, and the best candidate is determined. However, the directional beam training accuracy depends on scanning beam angular resolution, and consequently its improvement requires additional dedicated radio resources, access latency, and overhead. To remedy the problem of access latency and overhead in DIA, this paper proposes to use quasi-omni pseudorandom sounding beams for IA, and develops an algorithm for joint initial access and fine resolution initial beam training without requiring additional radio resources. It comprehensively models realistic timing and frequency synchronization errors encountered in IA. We provide the analysis of the proposed algorithm's miss detection rate under timing synchronization errors, and we further derive Cramér-Rao lower bound of angular estimation under frequency offset, considering the 5G-NR compliant IA procedure. To accommodate the ever increasing bandwidth for beam training in standard evolution beyond 5G, we design the beam squint robust algorithm. For realistic performance evaluation under mmW channels, we use QuaDRiGa simulator with mmMAGIC model at 28 GHz to show that the proposed approach is advantageous to DIA. The proposed algorithm offers orders of magnitude access latency saving compared to DIA, when the same discovery, post training SNR, and overhead performance are targeted. This conclusion holds true in various propagation environments and three-dimensional locations of a mmW pico-cell with up to 140 m radius. Furthermore, our results demonstrate that the proposed beam squint robust algorithm is able to retain unaffected performance with increased beam training bandwidth.
Synthesis of Heterocyclic Compounds from β‐Aminovinyl Ketones of the Adamantane Series. (2004)

Abstract For Abstract see ChemInform Abstract in Full Text.
Wireless passive IDT strain microsensor (1997)

This paper presents the experimental results of wireless passive IDT strain microsensors, which consist of inter-digital transducers (IDTs) on piezoelectric wafers to transmit and receive surface acoustic waves. By connecting the IDTs to a small microwave antenna, the IDT microsensors are wirelessly readable by a microwave reading system. The sensors are calibrated on a static cantilever beam and used to measure the dynamic strain of a vibrating beam wirelessly. The calibrated sensitivity compares reasonably with the theoretical estimation. The feasibility of compensating for temperature variations and reading multiple sensors simultaneously and the ability to combine the sensor and the wireless recognition systems are discussed.
Acellular nerve allografts in peripheral nerve regeneration: A comparative study (2011)

These findings provide evidence that differential processing for removal of cellular constituents in preparing acellular nerve allografts affects recovery in vivo.
Therapeutic stimulation of penile nitric oxide synthase (NOS) andrelated pathways (2000)

The advent of a novel oral treatment for erectile dysfunction appears to have reduced the urgency for seeking alternative therapeutic innovations. However, the currently available therapies can be viewed as simply palliative, requiring on-demand access and having a significant failure rate. Therefore, additional approaches for patients unresponsive to any type of medical treatment require investigation. The modulation of the synthesis of nitric oxide (NO), the main mediator of penile erection, is an attractive target for such an approach. Models for human erectile dysfunction related to aging, diabetes and endocrine disorders have been characterized in the rat. The affected animals exhibit a reduced erectile response to electrical stimulation of the cavernosal nerve and/or a loss of spontaneous erectile reflexes. In virtually all cases, the content and/or enzyme activity of penile NOS is significantly reduced, or NO synthesis may be insufficient to overcome the relatively poor compliance of the penile corpora cavernosa smooth muscle (aging). This led to the proposal that the stimulation of penile NO synthesis may be a viable therapy for erectile dysfunction. The upregulation of penile NOS activity may be achieved by: a) increase in NOS substrate concentration, b) stimulation of NOS activity through related pathways or c) blockade of endogenous NOS inhibitors. We have shown that approach a ameliorated the erectile dysfunction of aging rats by elevating intracavernosal NOS substrate through long-term oral administration of high doses of L-arginine. Evidence supporting approach b is based on our recent discovery that the main stimulating pathway for NOS, the NMDA receptor, is present in the penis. However, NMDA receptor antagonists unpredictably trigger cavernosal relaxation in vitro in a NO-independent pathway. Finally, in the case of approach c we have found that a protein inhibitor of NOS (PIN) is expressed in the corpora cavernosa. Penile NOS content may be pharmacologically increased by: d) induction of NOS expression, and e) gene therapy with NOS cDNA. Approach d applied to the penis ameliorated erectile dysfunction in aging rats, but may be clinically unfeasible because of the risk of side effects. Our laboratory cloned the inducible and neuronal NOS isoforms expressed in the penis (PiNOS and PnNOS, respectively), and showed that approach e, based on gene transfer of PiNOS into the rat corpora cavernosa improved the erectile response. Since PnNOS is a nNOS variant different from the one expressed in the CNS, gene therapy with PnNOS is promising in combination with viral vectors and tissue-specific promoters. The aim is to achieve a long-lasting increase in penile NOS that is responsive to sexual stimulation. Following validation in animal models, oral L-arginine, intracavernosal antagonists of NMDA receptor and PIN, and intracavernosal or systemic PnNOS, may eventually translate to clinical trials.
Thin-Film Lateral SOI PIN Diodes for Thermal Sensing Reaching the Cryogenic Regime (2020)

This paper presents the performance of lateral SOI PIN diodes for temperature sensing in the range of 100 K to 400 K. Experimental results indicate that PIN diodes can be used to implement temperature sensors with high accuracy in cryogenic regime, provided that a suitable temperature range is chosen for calibration. Numerical simulations using Atlas two-dimensional simulator were performed in order to confirm this hypothesis and extend the analysis, verifying the accuracy of the existing model.
Single pairing spike-timing dependent plasticity in BiFeO3 memristors with a time window of 25 ms to 125 μs (2015)

Memristive devices are popular among neuromorphic engineers for their ability to emulate forms of spike-driven synaptic plasticity by applying specific voltage and current waveforms at their two terminals. In this paper, we investigate spike-timing dependent plasticity (STDP) with a single pairing of one presynaptic voltage spike and one post-synaptic voltage spike in a BiFeO3 memristive device. In most memristive materials the learning window is primarily a function of the material characteristics and not of the applied waveform. In contrast, we show that the analog resistive switching of the developed artificial synapses allows to adjust the learning time constant of the STDP function from 25 ms to 125 μs via the duration of applied voltage spikes. Also, as the induced weight change may degrade, we investigate the remanence of the resistance change for several hours after analog resistive switching, thus emulating the processes expected in biological synapses. As the power consumption is a major constraint in neuromorphic circuits, we show methods to reduce the consumed energy per setting pulse to only 4.5 pJ in the developed artificial synapses.
SS‐31 Protects Liver from Ischemia‐Reperfusion Injury via Modulating Macrophage Polarization (2021)

Ischemia-reperfusion injury (IRI) is a common complication in liver surgeries. It is a focus to discover effective treatments to reduce ischemia-reperfusion injury. Previous studies show that oxidative stress and inflammation response contribute to the liver damage during IRI. SS-31 is an innovated mitochondrial-targeted antioxidant peptide shown to scavenge reactive oxygen species and decrease oxidative stress, but the protective effects of SS-31 against hepatic IRI are not well understood. The aim of our study is to investigate whether SS-31 could protect the liver from damages induced by IRI and understand the protective mechanism. The results showed that SS-31 treatment can significantly attenuate liver injury during IRI, proved by HE staining, serum ALT/AST, and TUNEL staining which can assess the degree of liver damage. Meanwhile, we find that oxidative stress and inflammation were significantly suppressed after SS-31 administration. Furthermore, the mechanism revealed that SS-31 can directly decrease ROS production and regulate STAT1/STAT3 signaling in macrophages, thus inhibiting macrophage M1 polarization. The proinflammation cytokines are then significantly reduced, which suppress inflammation response in the liver. Taken together, our study discovered that SS-31 can regulate macrophage polarization through ROS scavenging and STAT1/STAT3 signaling to ameliorate liver injury; the protective effects against hepatic IRI suggest that SS-31 may be an appropriate treatment for liver IRI in the clinic.
Bacterial Plurality as a General Mechanism Driving Persistence in Chronic Infections (2005)

Classical methods for the study of bacterial pathogens have proven to be inadequate to inform with respect to chronic infections including those associated with arthroplasties. Modern methods of analysis have demonstrated that bacterial growth patterns, ecology, and intra-species heterogeneity are more complex than were envisioned by early microbiologists. Cultural methods were developed to study acute, epidemic infections, but it is now recognized that the phenotype associated with these diseases represents only a minor aspect of the bacterial life cycle, which consists of planktonic, attachment, biofilm, and dispersal phases. Over 99% of bacteria in natural populations are found in biofilms which contain multiple ecological niches and numerous phenotypes. Unfortunately, the effort to develop antibiotics has been directed solely at the planktonic minority (associated with systemic illness) which explains our inability to eradicate chronic infections. In this study we establish a new rubric, bacterial plurality, for the understanding of bacterial ecology and evolution with respect to chronic infection. The fundamental tenets of bacterial plurality are that the bacteria within an infecting population display multiple phenotypes and possess multiple genotypes. Phenotypic plurality is embodied in the biofilm paradigm and genotypic plurality is embodied in the concepts of the supra-genome and the distributed genome hypothesis. It is now clear that bacterial diversity provides bacterial populations, as a whole, the ability to persist in the face of a multi-faceted host response.
Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform (2018)

Dense pixelwise prediction such as semantic segmentation is an up-to-date challenge for deep convolutional neural networks (CNNs). Many state-of-the-art approaches either tackle the loss of high-resolution information due to pooling in the encoder stage, or use dilated convolutions or high-resolution lanes to maintain detailed feature maps and predictions. Motivated by the structural analogy between multi-resolution wavelet analysis and the pooling/unpooling layers of CNNs, we introduce discrete wavelet transform (DWT) into the CNN encoder-decoder architecture and propose WCNN. The high-frequency wavelet coefficients are computed at encoder, which are later used at the decoder to unpooled jointly with coarse-resolution feature maps through the inverse DWT. The DWT/iDWT is further used to develop two wavelet pyramids to capture the global context, where the multi-resolution DWT is applied to successively reduce the spatial resolution and increase the receptive field. Experiment with the Cityscape dataset, the proposed WCNNs are computationally efficient and yield improvements the accuracy for high-resolution dense pixelwise prediction.
Autosophy networks yield self-learning robot vision (2002)

Autosophy is a new science which tries to explain self-assembling structures, such as crystals or living trees, in mathematical terms. This research provides algorithms for growing self-learning data networks in memories, similar to the growing of data crystals or data trees, without programming or conventional data processing. The new learning algorithms provide an entirely new technology for building brain-like robot vision systems. Television images from a camera are learned and stored in a peculiar omni dimensional hyperspace library. This will result in enormous data compression because no portion of the image is stored twice. The more images have already been learned the fewer storage locations will be required to store additional images. The omni dimensional hyperspace library allows for near instant search access which is independent of the library size. The resulting brain-like robot vision systems are educated very much like a human child by showing objects to a television camera and associating them with descriptive text or robot arm motions. Autosophy may succeed where conventional data processing has failed in providing intelligent self-organizing robot vision. Text and image learning has been simulated in software to show learning behavior which is strikingly similar to our own brain.
Function of Shaker potassium channels produced by cell-free translation upon injection into Xenopus oocytes (2013)

Voltage-gated ion channels are a class of membrane proteins that temporally orchestrate the ion flux critical for chemical and electrical signaling in excitable cells. Current methods to investigate the function of these channels rely on heterologous expression in living systems or reconstitution into artificial membranes; however these approaches have inherent drawbacks which limit potential biophysical applications. Here, we describe a new integrated approach combining cell-free translation of membrane proteins and in vivo expression using Xenopus laevis oocytes. In this method, proteoliposomes containing Shaker potassium channels are synthesized in vitro and injected into the oocytes, yielding functional preparations as shown by electrophysiological and fluorescence measurements within few hours. This strategy for studying eukaryotic ion channels is contrasted with existing, laborious procedures that require membrane protein extraction and reconstitution into synthetic lipid systems.
Design and Implementation of a Fast and Scalable NTT-Based Polynomial Multiplier Architecture (2019)

In this paper, we present an optimized FPGA implementation of a novel, fast and highly parallelized NTT-based polynomial multiplier architecture, which proves to be effective as an accelerator for lattice-based homomorphic cryptographic schemes. As I/O operations are as time-consuming as NTT operations during homomorphic computations in a host processor/accelerator setting, instead of achieving the fastest NTT implementation possible on the target FPGA, we focus on a balanced time performance between the NTT and I/O operations. Even with this goal, we achieved the fastest NTT implementation in literature, to the best of our knowledge. For proof of concept, we utilize our architecture in a framework for Fan-Vercauteren (FV) homomorphic encryption scheme, utilizing a hardware/software co-design approach, in which polynomial multiplication operations are offloaded to the accelerator via PCIe bus while the rest of operations in the FV scheme are executed in software running on an off-the-shelf desktop computer. Specifically, our framework is optimized to accelerate Simple Encrypted Arithmetic Library (SEAL), developed by the Cryptography Research Group at Microsoft Research, for the FV encryption scheme, where large degree polynomial multiplications are utilized extensively. The hardware part of the proposed framework targets Xilinx Virtex-7 FPGA device and the proposed framework achieves almost 11x latency speedup for the offloaded operations compared to their pure software implementations. We achieved a throughput of almost 800K polynomial multiplications per second, for polynomials of degree 1024 with 32-bit coefficients.
Nonparametric bayesian multitask collaborative filtering (2013)

The dramatic rates new digital content becomes available has brought collaborative filtering systems to the epicenter of computer science research in the last decade. One of the greatest challenges collaborative filtering systems are confronted with is the data sparsity problem: users typically rate only very few items; thus, availability of historical data is not adequate to effectively perform prediction. To alleviate these issues, in this paper we propose a novel multitask collaborative filtering approach. Our approach is based on a coupled latent factor model of the users rating functions, which allows for coming up with an agile information sharing mechanism that extracts much richer task-correlation information compared to existing approaches. Formulation of our method is based on concepts from the field of Bayesian nonparametrics, specifically Indian Buffet Process priors, which allow for data-driven determination of the optimal number of underlying latent features (item characteristics and user traits) assumed in the context of the model. We experiment on several real-world datasets, demonstrating both the efficacy of our method, and its superiority over existing approaches.
Peritoneal Adhesions: Etiology, Pathophysiology, and Clinical Significance (2001)

<i>Aim:</i> To summarize the most common etiologic factors and describe the pathophysiology in the formation of peritoneal adhesions, to outline their clinical significance and consequences, and to evaluate the pharmacologic, mechanical, and surgical adjuvant strategies to minimize peritoneal adhesion formation. <i>Methods:</i> We performed an extensive MEDLINE search of the internationally published English literature of all medical and epidemiological journal articles, textbooks, scientific reports, and scientific journals from 1940 to 1997. We also reviewed reference lists in all the articles retrieved in the search as well as those of major texts regarding intraperitoneal postsurgical adhesion formation. All sources identified were reviewed with particular attention to risk factors, pathophysiology, clinical manifestations, various methods, and innovative techniques for effectively and safely reducing the formation of postsurgical adhesions. <i>Results:</i> The formation of postoperative peritoneal adhesions is an important complication following gynecological and general abdominal surgery, leading to clinical and significant economical consequences. Adhesion occur in more than 90% of the patients following major abdominal surgery and in 55–100% of the women undergoing pelvic surgery. Small-bowel obstruction, infertility, chronic abdominal and pelvic pain, and difficult reoperative surgery are the most common consequences of peritoneal adhesions. Despite elaborate efforts to develop effective strategies to reduce or prevent adhesions, their formation remains a frequent occurrence after abdominal surgery. <i>Conclusions:</i> Until additional information and findings from future clinical investigations exist, only a meticulous surgical technique can be advocated in order to reduce unnecessary morbidity and mortality rates from these untoward effects of surgery.