gebhart/patrepeval huggingface dataset:
OS07W0393 Experimental evaluation of scaffold/biofactor constructs for bone tissue engineering (2003)

Bone tissue engineering utilizes biomaterial scaffolds seeded with biofactors (cells, genes, and/or proteins) to reconstruct bone defects. The scaffolds must be able to temporarily bear load, shape regenerate tissue, and enhance tissue regeneration through biofactor delivery. Thus, scaffold evaluation requires traditional engineering experiments like non-destructive radiographic evaluation and mechanical testing, as well as biological experiments performed in vitro and in vivo. In this paper we present a paradigm for integrating mechanical and biological scaffold evaluation to determine optimal scaffold design parameters. Specific examples of scaffold material evaluation include micro-computed tomography (micro-CT) scanning, voxel finite element modeling, and mechanical testing. In vitro tests evaluate cell growth on scaffold in static culture. Finally, in vivo evaluation includes gene/cell delivery from scaffolds in immunocompromised mice and mandibular defect filling regeneration with engineered scaffolds.
Coherent Exciton Dynamics in Supramolecular Light-Harvesting Nanotubes Revealed by Ultrafast Quantum Process Tomography (2014)

Long-lived exciton coherences have been recently observed in photosynthetic complexes via ultrafast spectroscopy, opening exciting possibilities for the study and design of coherent exciton transport. Yet, ambiguity in the spectroscopic signals has led to arguments against interpreting them in terms of exciton dynamics, demanding more stringent tests. We propose a novel strategy, quantum process tomography (QPT), for ultrafast spectroscopy and apply it to reconstruct the evolving quantum state of excitons in double-walled supramolecular light-harvesting nanotubes at room temperature from eight narrowband transient grating experiments. Our analysis reveals the absence of nonsecular processes, unidirectional energy transfer from the outer to the inner wall exciton states, and coherence between those states lasting about 150 fs, indicating weak electronic coupling between the walls. Our work constitutes the first experimental QPT in a “warm” and complex system and provides an elegant scheme to maximize information from ultrafast spectroscopy experiments.
Privacy-preserving classification of personal text messages with secure multi-party computation : an application to hate-speech detection (2019)

Classification of personal text messages has many useful applications in surveillance, e-commerce, and mental health care, to name a few. Giving applications access to personal texts can easily lead to (un)intentional privacy violations. We propose the first privacy-preserving solution for text classification that is provably secure. Our method, which is based on Secure Multiparty Computation (SMC), encompasses both feature extraction from texts, and subsequent classification with logistic regression and tree ensembles. We prove that when using our secure text classification method, the application does not learn anything about the text, and the author of the text does not learn anything about the text classification model used by the application beyond what is given by the classification result itself. We perform end-to-end experiments with an application for detecting hate speech against women and immigrants, demonstrating excellent runtime results without loss of accuracy.
β-Amyloid Plaque Reduction in the Hippocampus After Focused Ultrasound-Induced Blood–Brain Barrier Opening in Alzheimer’s Disease (2020)

The blood-brain barrier (BBB) limits therapeutic delivery in Alzheimer's disease (AD) and other neurological disorders. Animal models have demonstrated safe BBB opening and reduction in β-amyloid plaque with focused ultrasound (FUS). We recently demonstrated the feasibility, safety, and reversibility of FUS-induced BBB opening in the hippocampus and entorhinal cortex in six participants with early AD. We now report the effect of BBB opening with FUS treatment on β-amyloid plaque. Six participants underwent <sup>18</sup>F-Florbetaben PET scan at baseline and 1 week after the completion of the third FUS treatment (60 days interval). PET analysis comparing the hippocampus and entorhinal cortex in the treated and untreated hemispheres revealed a decrease in the ratio of <sup>18</sup>F-Florbetaben ligand binding. The standard uptake value ratios (SUVr) reduction ranged from 2.7% to 10% with an average of 5.05% (±2.76) suggesting a decrease in β-amyloid plaque.
Improving Microstructured TiO2 Photoanodes for Dye Sensitized Solar Cells by Simple Surface Treatment (2011)

Abstract TiCl 4 surface treatment studies of porous electrode structure of TiO 2 aggregates synthesized using an acidic precursor and CTAB as a templating agent are carried out in order to understand and improve upon recombination kinetics in the photonanode film matrix, together with enhancing the intrinsic light scattering. The key beneficial features of the photoanode included high surface roughness, necessary for superior dye adsorption, nanocrystallite aggregates leading to diffuse light scattering within the film matrix, and a hierarchical macro‐ and mesopore structure allowing good access of electrolyte to the dye, thereby assisting in dye regeneration (enhanced charge transfer). Pre‐treatment of the TiO 2 electrodes reduced recombination at the fluorine‐doped tin oxide (FTO)/electrolyte interface. The post‐treatment study showed enhanced surface roughness through the deposition of a thin overlayer of amorphous TiO 2 on the film structure. This led to a notable improvement in both dye adsorption and inherent light scattering effects by the TiO 2 aggregates, resulting in enhanced energy harvesting. The thin TiO 2 overlayer also acted as a barrier in a core‐shell configuration within the porous TiO 2 matrix, and thereby reduced recombination. This allowed the hierarchical macro‐ and mesoporosity of the film matrix to be utilized more effectively for enhanced charge transfer during dye regeneration. Post‐treatment of the aggregated TiO 2 matrix resulted in a 36% enhancement in power conversion efficiency from 4.41% of untreated cells to 6.01%.
Two distinct conformations of rat liver ribosomal 5S RNA (1982)

Three different conformers of rat liver 5S ribosomal RNA were investigated by partial nuclease cleavage technique using S1 nuclease and cobra venom endoribonuclease (CVE) as conformational probes. Urea-treated and renatured 5S RNA co-migrate on non-denaturing gels, but exhibit distinct differences in their nuclease cleavage patterns. The most prominent differences in S1 nuclease and CVE accessibility of these conformers are located in region 30-50 and around nucleotides 70 and 90. The third form of 5S RNA with higher electrophoretic mobility was generated by EDTA treatment. The cleavage patterns of this 5S RNA conformer are similar to that characteristic for the renatured 5S RNA. The results demonstrate the difference in secondary structure and possibly different tertiary base-pairing interactions of 5S RNA conformers.
Optical Coherence Tomography (OCT) Imaging and Computer Aided Diagnosis of Human Cervical Tissue Specimens (2007)

The keyword for management of cervical cancer is prevention. The present program within the UK, the ‘National Health Service (NHS) cervical screening programme’ (NHSCSP), is based on cytology. Although the program has reduced the incidence of cervical cancer, this program requires patient follow ups and relies on diagnostic biopsying. There is potential for reducing costs and workload within the NHS, and relieving anxiety of patients. In this study, Optical Coherence Tomography (OCT) was investigated for its capability to improve this situation. Our time domain bench top system used a superluminescent diode (Superlum), centre wave length ~1.3 µm, resolution (air) ~15 µm. Tissue samples were obtained according to the ethics approval by Gloucestershire LREC, Nr. 05/Q2005/123. 1387 images of 199 participants have been compared with histopathology results and categorized accordingly. Our OCT images do not reach the clarity and resolution of histopathology. Further, establishing and recognizing features of diagnostic significance seems difficult. Automated classification would allow one to take decision-making to move from the subjective appraisal of a physician to an objective assessment. Hence we investigated a classification algorithm for its ability in recognizing pre-cancerous stages from OCT images. The initial results show promise.
A New Approach to Quantify the Wellhead Performance for Gas Condensate Reservoirs Using Artificial Intelligent Techniques (2022)

Abstract Selecting the optimum choke size that can deliver the optimum gas flow rate is extremely complex in gas condensate wells because of the high unpredictability of two-phase flow behavior and the changes in gas-liquid ratio with pressure and temperature. There are many analytical and empirical correlations in the literature, that describe the two-phase flow through wellhead chokes in critical conditions. However, the nature of the flow in most gas condensate wells is sub-critical, and using these correlations causes severe errors in the estimation of flow parameters. Also, the models available for sub-critical flow are not providing satisfactory accuracy for prediction and are often difficult to use. The objective of this work is to develop reliable models for predicting choke performance. Artificial intelligent (AI) based models were developed to accurately design the optimum wellhead choke size, based on the required flow rate, pressure difference, and gas to liquid ratio. The newly developed models are accurate and easy to be used, comparing to the existing predictive models. In this work, artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) were applied to estimate the gas flow rate from gas condensate wells. Among the developed models, ANFIS with a subtractive clustering approach performed the best with a percentage error of 2.4% and coefficient of determination (R2) of 0.981. The newly developed models can improve production management by proposing the optimum flow parameters that help in regulating the flow rate of two phases from gas condensate wells. Also, they can help in stabilizing the flowing pressure downstream the choke and prevent downhole reservoir formation damage, by providing the required back pressure to avoid excessive drawdown. Overall, the presented models provide an easy
Dual Control ofHelicobacter pyloriHeat Shock Gene Transcription by HspR and HrcA (2004)

The HspR repressor regulates transcription of the groESL, hrcA-grpE-dnaK, and cbpA-hspR-orf operons of Helicobacter pylori. Here we show that two of the HspR-regulated operons, namely, the groESL and dnaK operons, encoding the major cellular chaperone machineries are also regulated by the H. pylori homologue of the HrcA repressor. Similarly to the hspR mutation, deletion of the hrcA gene also leads to complete derepression of the Pgro and Phrc promoters. The presence of both HspR and HrcA is therefore necessary for regulated transcription from these promoters. HrcA binds directly to Pgro and Phrc, likely contacting two inverted repeats with similarity to the CIRCE motif, which are present on both promoters. HrcA regulation is, however, shown to depend on binding of the HspR protein, since deletion of the HspR-binding site of the Pgro promoter leads to loss of heat inducibility of this promoter. In contrast, transcription from the Pcbp promoter is regulated solely by HspR. HspR is also shown to form oligomers in vivo through a stretch of hydrophobic repeats between amino acid positions 66 and 97. The implications of these findings for the elucidation of the networks regulating heat shock gene expression in H. pylori are discussed.
Brillouin microscopy (2018)

Brillouin microscopy is a promising technology under commercial development at present. The technique enables physicians to characterize the biomechanical properties of ocular tissues.
Deep Neural Networks with Multi-Branch Architectures Are Intrinsically Less Non-Convex (2019)

Several recently proposed architectures of neural networks such as ResNeXt, Inception, Xception, SqueezeNet and Wide ResNet are based on the designing idea of having multiple branches and have demonstrated improved performance in many applications. We show that one cause for such success is due to the fact that the multi-branch architecture is less non-convex in terms of duality gap. The duality gap measures the degree of intrinsic non-convexity of an optimization problem: smaller gap in relative value implies lower degree of intrinsic non-convexity. The challenge is to quantitatively measure the duality gap of highly non-convex problems such as deep neural networks. In this work, we provide strong guarantees of this quantity for two classes of network architectures. For the neural networks with arbitrary activation functions, multi-branch architecture and a variant of hinge loss, we show that the duality gap of both population and empirical risks shrinks to zero as the number of branches increases. This result sheds light on better understanding the power of over-parametrization where increasing the number of branches tends to make the loss surface less non-convex. For the neural networks with linear activation function and $\ell_2$ loss, we show that the duality gap of empirical risk is zero. Our two results work for arbitrary depths, while the analytical techniques might be of independent interest to non-convex optimization more broadly. Experiments on both synthetic and real-world datasets validate our results.
Mechanism of exaggerated inflammation in A2A adenosine receptor-deficient mice. (138.28) (2010)

Abstract Extracellular adenosine regulates inflammatory responses via A2A adenosine receptor (A2AR). Indeed, A2AR-deficiency results in much exaggerated inflammatory tissue damage, indicating non-redundancy of adenosine-A2AR pathway in the inhibitory mechanism of immune activation. In this study, we found that intravenous injection of concanavalin A into A2AR-deficient mice induced not only stronger hepatic damage than in wild-type mice but also higher levels of cytokines, i.e. TNF-α, IL-4 and IFN-γ. Since NKT cells are responsible for the early production of these cytokines after concanavalin A injection, NKT cells were suspected to be under physiological control of adenosine-A2AR pathway. To directly examine the role of A2AR in NKT cell activation, we specifically stimulated NKT cells with α-galactosylceramide in the presence of dendritic cells. As a result, cytokine production from NKT cells decreased in the presence of A2AR agonists, suggesting that A2AR signaling can down-regulate NKT cell activation. We further injected α-galactosylceramide into mice and observed higher cytokines production in A2AR-deficient mice comparing to wild-type mice. Correspondingly, α-galactosylceramide induced stronger liver damage in A2AR-deficient mice. These results strongly suggest that NKT cell activation is controlled by endogenous adenosine via A2AR, and this physiological regulatory mechanism of NKT cells is critical in the control of tissue-damaging inflammation.
Non-parametric Structure-Based Calibration of Radially Symmetric Cameras (2015)

We propose a novel two-step method for estimating the intrinsic and extrinsic calibration of any radially symmetric camera, including non-central systems. The first step consists of estimating the camera pose, given a Structure from Motion (SfM) model, up to the translation along the optical axis. As a second step, we obtain the calibration by finding the translation of the camera center using an ordering constraint. The method makes use of the 1D radial camera model, which allows us to effectively handle any radially symmetric camera, including non-central ones. Using this ordering constraint, we show that the we are able to calibrate several different (central and non-central) Wide Field of View (WFOV) cameras, including fisheye, hyper-catadioptric and spherical catadioptric cameras, as well as pinhole cameras, using a single image or jointly solving for several views.
SNR analysis of conventional and optimal fiber optic low-coherence interferometer topologies (2000)

The most straightforward interferometer for optical coherence tomography (OCT) is a simple Michelson interferometer. A low-coherence source illuminates the interferometer. The light is split by a 50/50 beamsplitter into a sample and a reference path. Light retro reflected from the reference and the sample is recombined at the beamsplitter and half is collected by a photodetetor in the detection arm of the interferometer. Half of the light is returned towards the source, where it is lost. In addition, the reference arm light is typically attenuated by orders of magnitude in order to improve signal to noise ratio. Thus, using this typical configuration, virtually 75 percent of the optical power supplied by the source is not used for image formation. We present a family of novel interferometer designs incorporating optical circulators, unbalanced couplers, and/or balanced detection which are designed to optimize optical power efficiency and circulators, unbalanced couplers, and/or balance detection which are designed to optimize optical power efficiency and system signal to noise ratio. We evaluate the expected performance of the novel interferometers as compared with the standard Michelson interferometer. We review signal and noise sources important for the design of OCT interferometers, and specify the design equations for evaluation and optimization of signal to noise ratio. This analysis, based on sound, experimentally verified literature, predicts improved sensitivity for all of the new interferometer designs.
Ultra‐Slim Power Rail (S‐type) (2017)

As a further step to go forward to a more improved performance on the inductive power transfer system (IPTS) for road-powered electric vehicles (RPEVs), an ultra-slim S-type power supply rail, which has a width of only 4 cm, is explained in this chapter. The cross-section of the core has a thin S-shape, and a vertical-wound multiturn coil is displaced inside the core. Therefore, this design provides a very slim power supply rail, which is crucial for the commercialization of RPEVs. The construction of roadway infrastructure, which is responsible for more than 80% of the total deployment cost for RPEVs, can be much easier when the width of the power supply rail is so small. To increase portability and to minimize construction time, a foldable power supply module is also proposed in which flexible power cables connect each foldable power supply module such that no connectors are needed during deployment. An effective winding method for minimizing cable length is proposed, and an optimum core thickness of the proposed power supply rail is determined by FEA simulations and verified by a prototype power supply module. By virtue of the ultra-slim shape, a large lateral displacement of 30 cm at an airgap of 20 cm was experimentally obtained, which is 6 cm larger than that of the I-type power supply rail. In addition to the larger lateral displacement, it is estimated that the S-type one has a lower EMF than the I-type one because the width of the S-type one is narrower than that of the I-type one. The maximum efficiency, excluding the inverter, was 91% and the pick-up power was 22 kW. This chapter is written from the paper by S.Y. Choi, B.W. Gu, S.Y. Jeong, G.C. Lim, and Chun T. Rim, “Ultra slim S-type power supply rails for road powered electric vehicles,” IEEE Trans. on Power Electronics, vol. 30, no. 11, pp. 6456–6468, November 2015. Readers will be able to see not only how to make the power supply rail slim but also how important the modularity design is to carry and deploy.
Space-time signaling in correlated channels (2005)

The performance of space-time codes under channel correlation has been studied in detail recently, and a variety of results have been produced. In this work, we simplify some of the existing derivations as well as present some new results. One of the novel issues raised in this investigation is the loss of the uniform error probability (UEP) property of many codes in the presence of transmit side correlation. Also our error expressions for the general case of jointly spatio-temporally correlated Rayleigh and Rician fading are new, to the best of our knowledge. We also apply our analysis to some of the more recently developed codes for the MIMO channel, including the super-orthogonal codes and the linear dispersion codes.
Targeting PDGF‐mediated recruitment of pericytes blocks vascular mimicry and tumor growth (2018)

Aggressive tumor cells can adopt an endothelial cell-like phenotype and contribute to the formation of a tumor vasculature, independent of tumor angiogenesis. This adoptive mechanism is referred to as vascular mimicry and it is associated with poor survival in cancer patients. To what extent tumor cells capable of vascular mimicry phenocopy the angiogenic cascade is still poorly explored. Here, we identify pericytes as important players in vascular mimicry. We found that pericytes are recruited by vascular mimicry-positive tumor cells in order to facilitate sprouting and to provide structural support of the vascular-like networks. The pericyte recruitment is mediated through platelet-derived growth factor (PDGF)-B. Consequently, preventing PDGF-B signaling by blocking the PDGF receptors with either the small tyrosine kinase inhibitor imatinib or blocking antibodies inhibits vascular mimicry and tumor growth. Collectively, the current study identifies an important role for pericytes in the formation of vascular-like structures by tumor cells. Moreover, the mechanism that controls the pericyte recruitment provides therapeutic opportunities for patients with aggressive vascular mimicry-positive cancer types. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
Behavioral rehabilitation of the eye closure reflex in senescent rats using a real-time biosignal acquisition system (2011)

In this paper the replacement of a lost learning function of rats through a computer-based real-time recording and feedback system is shown. In an experiment two recording electrodes and one stimulation electrode were implanted in an anesthetized rat. During a classical-conditioning paradigm, which includes tone and airpuff stimulation, biosignals were recorded and the stimulation events detected. A computational model of the cerebellum acquired the association between the stimuli and gave feedback to the brain of the rat using deep brain stimulation in order to close the eyelid of the rat. The study shows that replacement of a lost brain function using a direct bidirectional interface to the brain is realizable and can inspire future research for brain rehabilitation.