gebhart/patrepeval huggingface dataset:
Protein Kinase C isoform expression during differentiation of 3T3-F442A preadipocytes (1997)

Conference Article| May 01 1997 Protein Kinase C isoform expression during differentiation of 3T3-F442A preadipocytes I.M. FLEMING; I.M. FLEMING 1Hannah Research Institute, Ayr KA6 5HL, U.K. Search for other works by this author on: This Site PubMed Google Scholar S.J. MacKENZIE; S.J. MacKENZIE *Molecular Pharmacology Group, Department of Biochemistry and Molecular Biology, University of Glasgow, Glasgow G12 8QQ, U.K. Search for other works by this author on: This Site PubMed Google Scholar M.D. HOUSLAY; M.D. HOUSLAY *Molecular Pharmacology Group, Department of Biochemistry and Molecular Biology, University of Glasgow, Glasgow G12 8QQ, U.K. Search for other works by this author on: This Site PubMed Google Scholar E. KILGOUR E. KILGOUR 1Hannah Research Institute, Ayr KA6 5HL, U.K. Search for other works by this author on: This Site PubMed Google Scholar Biochem Soc Trans (1997) 25 (2): 211S. https://doi.org/10.1042/bst025211s Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Cite Icon Cite Get Permissions Citation I.M. FLEMING, S.J. MacKENZIE, M.D. HOUSLAY, E. KILGOUR; Protein Kinase C isoform expression during differentiation of 3T3-F442A preadipocytes. Biochem Soc Trans 1 May 1997; 25 (2): 211S. doi: https://doi.org/10.1042/bst025211s Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsBiochemical Society Transactions Search Advanced Search This content is only available as a PDF. © 1997 Biochemical Society1997 Article PDF first page preview Close Modal You do not currently have access to this content.
Multi-level indexing in a distributed self-organized storage system (2011)

In many systems providing storage and retrieval operations on data, indices are used to make these operations more efficient. Distributed storage systems provide means to distribute the burden of storing and retrieving data onto multiple different computers. Routing indices can answer the central question in these systems: Where should one look for a specified data item? To be able to query for different columns in a relation or different entries in tuples, indexing for multiple dimensions is necessary. Our group applies a swarm-based approach to distributed storage leading to a new class of distributed systems, which are fully self-organized in their behavior and lack any shared global data structures. In this paper, we research whether multiple levels of routing indices can be maintained and used in such a distributed and self-organized storage service. To achieve this, we look into different types of indices and evaluate them in an experiment.
A 16Mb dual-mode ReRAM macro with sub-14ns computing-in-memory and memory functions enabled by self-write termination scheme (2017)

Recent ReRAM devices enable the development of computing-in-memory (CIM) for beyond von Neumann structure. However, wide distribution in ReRAM resistance (R) causes low yield for CIM operations. This work proposes a dual-mode computing (DMc) ReRAM macro structure with a dual-function voltage-mode self-write termination (DV-SWT) scheme to achieve both memory and fundamental CIM functions (AND, OR and XOR operations) with high yield. The DV-SWT increases the read margin for CIM operations by suppressing the R-variations caused by macro-level IR-drop and process variations. A 16Mb DMc-ReRAM full-function macro was fabricated using 1T1R HfO ReRAM devices and 0.15um CMOS process. The measured delay of the CIM operations is less than 14ns, which is 86+x faster than previous ReRAM-based CIM works. This work also represents the first CIM ReRAM macro with ReRAM device and CIM-peripheral circuits fully integrated on the same die.
Exploration of Near-Infrared-Emissive Colloidal Multinary Lead Halide Perovskite Nanocrystals Using an Automated Microfluidic Platform (2018)

Hybrid organic-inorganic and fully inorganic lead halide perovskite nanocrystals (NCs) have recently emerged as versatile solution-processable light-emitting and light-harvesting optoelectronic materials. A particularly difficult challenge lies in warranting the practical utility of such semiconductor NCs in the red and infrared spectral regions. In this context, all three archetypal A-site monocationic perovskites-CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub>, CH(NH<sub>2</sub>)<sub>2</sub>PbI<sub>3</sub>, and CsPbI<sub>3</sub>-suffer from either chemical or thermodynamic instabilities in their bulk form. A promising approach toward the mitigation of these challenges lies in the formation of multinary compositions (mixed cation and mixed anion). In the case of multinary colloidal NCs, such as quinary Cs <sub>x</sub>FA<sub>1- x</sub>Pb(Br<sub>1- y</sub>I <sub>y</sub>)<sub>3</sub> NCs, the outcome of the synthesis is defined by a complex interplay between the bulk thermodynamics of the solid solutions, crystal surface energies, energetics, dynamics of capping ligands, and the multiple effects of the reagents in solution. Accordingly, the rational synthesis of such NCs is a formidable challenge. Herein, we show that droplet-based microfluidics can successfully tackle this problem and synthesize Cs <sub>x</sub>FA<sub>1- x</sub>PbI<sub>3</sub> and Cs <sub>x</sub>FA<sub>1- x</sub>Pb(Br<sub>1- y</sub>I <sub>y</sub>)<sub>3</sub> NCs in both a time- and cost-efficient manner. Rapid in situ photoluminescence and absorption measurements allow for thorough parametric screening, thereby permitting precise optical engineering of these NCs. In this showcase study, we fine-tune the photoluminescence maxima of such multinary NCs between 700 and 800 nm, minimize their emission line widths (to below 40 nm), and maximize their photoluminescence quantum efficiencies (up to 89%) and phase/chemical stabilities. Detailed structural analysis revealed that the Cs <sub>x</sub>FA<sub>1- x</sub>Pb(Br<sub>1- y</sub>I <sub>y</sub>)<sub>3</sub> NCs adopt a cubic perovskite structure of FAPbI<sub>3</sub>, with iodide anions partially substituted by bromide ions. Most importantly, we demonstrate the excellent transference of reaction parameters from microfluidics to a conventional flask-based environment, thereby enabling up-scaling and further implementation in optoelectronic devices. As an example, Cs <sub>x</sub>FA<sub>1- x</sub>Pb(Br<sub>1- y</sub>I <sub>y</sub>)<sub>3</sub> NCs with an emission maximum at 735 nm were integrated into light-emitting diodes, exhibiting a high external quantum efficiency of 5.9% and a very narrow electroluminescence spectral bandwidth of 27 nm.
Relational Query Co-Processing on Graphics Processors 1 (2009)

Graphics processors (GPUs) have recently emerged as a powerful co-processor for general-purpose computation. Compared with commodity CPUs, GPUs have an order of magnitude higher computation power as well as memory bandwidth. Moreover, new-generation GPUs allow writes to random memory locations, provide e‐cient inter-processor communication through on-chip local memory, and support a general-purpose parallel programming model. Nevertheless, many of the GPU features are specialized for graphics processing, including the massively multi-threaded architecture, the Single-Instruction-Multiple-Data processing style, and the execution model of a single application at a time. Additionally, GPUs rely on a bus of limited bandwidth to transfer data from and to the CPU, do not allow dynamic memory allocation from GPU kernels, and have little hardware support for write con∞icts. Therefore, it requires a careful design and implementation to utilize the GPU for co-processing database queries. In this paper, we present our design, implementation, and evaluation of an in-memory relational query co-processing system, GDB, on the GPU. Taking advantage of the GPU hardware features, we design a set of highly optimized data-parallel primitives such as split and sort, and use these primitives to implement common relational query processing algorithms. Our algorithms utilize the high parallelism as well as the high memory bandwidth of the GPU, and use parallel computation and memory optimizations to efiectively reduce memory stalls. Furthermore, we propose co-processing techniques that take into account both the computation resources and the GPU-CPU data transfer cost so that each operator in a query can utilize suitable processors - the CPU, the GPU, or both, for an optimized overall performance. We have evaluated our GDB system on a machine with an Intel quad-core CPU and an NVIDIA GeForce 8800 GTX GPU. Our workloads include microbenchmark queries on memory-resident data as well as TPC-H queries that involve complex data types and multiple query operators on data sets larger than the GPU memory. Our results show that our GPU-based algorithms are 2-27x faster than their optimized CPU-based counterparts on in-memory data. Moreover, the performance of our co-processing scheme is similar to or better than both the GPU-only and the CPU-only schemes.
Guest Packing Motifs within a Supramolecular Nanocapsule and a Covalent Analogue (2013)

Two hosts that utilize the hydrophobic effect to assemble and/or encapsulate guest molecules were studied. The hosts, octa-acid (OA) and hexalene diamine-linked octa-acid (HOA), were shown to complex a broad range of n-alkanes up to n-hexacosane (C26H54). A combination of (1)H NMR, NMR diffusion, COSY, and NOESY experiments revealed four different guest packing motifs, depending on the size of the guest and the nature of the host. As a function of guest size, smooth transitions from one motif to the next were observed and allowed qualification of their relative stabilities. Furthermore, although the two hosts engender ostensibly identical encapsulation environments, their different assembly properties lead to quite distinct packing-motif profiles, i.e., how the motifs change as a function of guest size.
Inhibition of Serum- and Calcium-Induced Differentiation of Human Keratinocytes by HPV16 E6 Oncoprotein: Role of p53 Inactivation (1997)

We have recently shown that human papillomavirus (HPV16) E6 oncoprotein exhibits two separate biological activities in genital keratinocytes (PHKs). E6 protein by itself is capable of inducing colonies of proliferating cells resistant to serum and calcium-induced differentiation, whereas both E6 and E7 are required for immortalization of PHK. Using epitope-tagged E6 carboxy-terminal truncation mutants, we mapped the domain between amino acid residues 132 and 141 as being essential for the induction of differentiation resistance (L. Sherman and R. Schlegel, J. Virol. 70, 3269-3279, 1996). To determine whether E6 protein's ability to alter PHK response to serum and calcium was associated with its ability to inactivate p53, we evaluated each of the above E6 mutants and three E6 natural variants in these respective assays. Our results demonstrate that the E6 region spanning residues 132-141 is required for p53 degradation and for abrogation of p53 transactivation, suggesting a possible correlation between E6 biological activity in altering differentiation and loss of p53 function. To evaluate whether selective inactivation of p53 is sufficient for altering the response of PHK to serum and calcium we investigated the capacity of plasmids encoding a dominant mutant human p53 and human MDM-2 to functionally substitute for E6 in colony formation in PHK. Plasmids were verified for their ability to inactivate wild-type p53 by testing their capacity to abrogate the p53 transactivation function. The results obtained showed that vectors encoding human MDM-2 and mutant p53, while active in inhibition of p53-dependent transactivation and capable of expressing stable proteins in PHK, failed to induce colonies of proliferating cells resistant to serum and calcium differentiation. These data argue that p53 inactivation may not be the sole E6 function required for altering the response of PHK to serum- and calcium-triggered differentiation.
Damage Mechanism Evaluation of Large-Scale Concrete Structures Affected by Alkali-Silica Reaction Using Acoustic Emission (2018)

Alkali-silica reaction has caused damage to concrete structures, endangering structural serviceability and integrity. This is of concern in sensitive structures such as nuclear power plants. In this study, acoustic emission (AE) was employed as a structural health monitoring strategy in large-scale, reinforced concrete specimens affected by alkali-silica reaction with differing boundary conditions resembling the common conditions found in nuclear containments. An agglomerative hierarchical algorithm was utilized to classify the AE data based on energy-frequency based features. The AE signals were transferred into the frequency domain and the energies in several frequency bands were calculated and normalized to the total energy of signals. Principle component analysis was used to reduce feature redundancy. Then the selected principal components were considered as features in an input of the pattern recognition algorithm. The sensor located in the center of the confined specimen registered the largest portion of AE energy release, while in the unconfined specimen the energy is distributed more uniformly. This confirms the results of the volumetric strain, which shows that the expansion in the confined specimen is oriented along the thickness of the specimen.
Packing Lines, Planes, etc.: Packings in Grassmannian Space (2002)

This paper addresses the question: how should N n-dimensional subspaces of m-dimensional Euclidean space be arranged so that they are as far apart as possible? The results of extensive computations for modest values of N, n, m are described, as well as a reformulation of the problem that was suggested by these computations. The reformulation gives a way to describe n-dimensional subspaces of m-space as points on a sphere in dimension (m-1)(m+2)/2, which provides a (usually) lower-dimensional representation than the Pluecker embedding, and leads to a proof that many of the new packings are optimal. The results have applications to the graphical display of multi-dimensional data via Asimov's "Grand Tour" method.
Laryngomalacia: a proposed classification form (1998)

Laryngomalacia is a common cause of stridor in children. The disorder has a heterogenous presentation, from the mildest form, which resolves with maturation, to the most severe form, requiring tracheotomy. While there is a vast literature on the subject, there is neither stratification nor correlation of clinical presentation, endoscopic appearance, treatment and outcome. In order to statistically evaluate the choice of treatment based upon presentation, patients must first be classified by relevant predictors of disease severity. A form is proposed to classify the clinical presentation of laryngomalacia by recording relevant historical and anatomic factors. Historical factors are classified by (1) severity of stridor; (2) weight gain; (3) age at presentation; and (4) neurologic status, forming the mnemonic SWAN. The principal anatomic site of collapse is recorded as: (1) postero-lateral; (2) posterior; or (3) anterior. Endoscopic findings consistent with gastroesophageal reflux disease (GERD) or gross aspiration are noted. Photographic and/or video documentation is performed when possible. A pilot study was undertaken to determine the ease of use of this instrument. Ten children, four boys and six girls, were classified. Ages ranged from 1-day-old to 19 months, with a mean of 9 months. Five children were examined in the clinic and five in the operating room. The form was readily and easily applied, and allowed the heterogeneity of the disorder to be organized. Wider application of this form across institutions, with classification of patients with laryngomalacia by historical and anatomic factors, should allow the accumulation of sufficient numbers of patients to allow statistical analyses of treatment and outcome as they relate to the initial presentation of this disorder of airway dynamics.
Deep Full-Body Motion Network for a Soft Wearable Motion Sensing Suit (2018)

Soft sensors are becoming more popular in wearables as a means of tracking human body motions due to their high stretchability and easy wearability. However, previous research not only was limited to only certain body parts, but also showed problems in both calibration and processing of the sensor signals, which are caused by the high nonlinearity and hysteresis of the soft materials and also by the misplacement and displacement of the sensors during motion. Although this problem can be alleviated through redundancy by employing an increased number of sensors, it will lay another burden of heavy processing and power consumption. Moreover, complete full-body motion tracking has not been achieved yet. Therefore, we propose use of deep learning for full-body motion sensing, which significantly increases efficiency in calibration of the soft sensor and estimation of the body motions. The sensing suit is made of stretchable fabric and contains 20 soft strain sensors distributed on both the upper and the lower extremities. Three athletic motions were tested with a human subject, and the proposed learning-based calibration and mapping method showed a higher accuracy than traditional methods that are mainly based on mathematical estimation, such as linear regression.
Topology Optimization of Optical Waveguide Devices Based on Beam Propagation Method With Sensitivity Analysis (2016)

We present a gradient-based topology optimization method of optical waveguide devices using the beam propagation method (BPM). Efficient topology optimization of an optical waveguide is available by using our approach because it utilizes the adjoint variable method for sensitivity analysis, and the BPM for numerical propagation analysis. In this paper, a way of evaluating sensitivities for a design of longitudinally varying waveguides is newly described in the case that a density method and finite difference BPM are employed. In addition, the validity and availability of our proposed method are verified by optimizing an S-bend and a Y-branch waveguides.
Nutritional status and risk of amyotrophic lateral sclerosis in Japan (2007)

Only a few human studies have reported the relationship between dietary factors and the risk of amyotrophic lateral sclerosis (ALS). We therefore analyzed the relationship between macronutrients (carbohydrate, protein and fat) and the risk of ALS using a case-control study in Japan. The study comprised 153 ALS patients diagnosed by the El Escorial World Federation of Neurology criteria, and 306 gender- and age- matched controls randomly selected from the general population. A self-administered food frequency questionnaire was used to estimate pre-illness intakes of food groups and nutrients. The strength of association between ALS and a potential risk factor was assessed by calculating odds ratios (ORs) and 95% confidence intervals (CIs). A high intake of carbohydrate was significantly associated with an increased risk of ALS (adjusted OR = 2.14, 95% CI 1.05-4.36; the highest versus the lowest tertile). ORs for the second and third tertile of total fat were 0.57 and 0.41 (95% CI 0.21-0.80), respectively. ORs for the highest tertile of intake versus the lowest were 0.41 (95% CI 0.21-0.80) for total fat, 0.30 (95% CI 0.16-0.5) for saturated fatty acids (SFAs), 0.35 (95% CI 0.18-0.69) for monounsaturated fatty acids (MUFAs) and 0.58 (95%CI 0.40-0.96) for polyunsaturated fatty acids (PUFAs). Our findings suggest that high intakes of carbohydrate and low intakes of fat and some kinds of fatty acids may, when combined, increased the risk of ALS.
Utility of microscope-integrated optical coherence tomography (MIOCT) in the treatment of myopic macular hole retinal detachment (2017)

Macular hole-associated retinal detachment in high myopia is described as a final stage in progression of myopic traction maculopathy (MTM).<sup>1â€"3</sup> Shimada <i>et al</i><sup>4</sup> described the progressive stages of MTM from macular retinoschisis to serous retinal detachment in high myopia. Stage 4 MTM is characterised as disappearance of retinoschisis with progression to retinal detachment due to macular hole formation. It is hypothesised that vitreoschisis and abnormal vitreo-retinal interface create the premacular tangential traction.<sup>5 6</sup> Intraoperative triamcinolone acetonide is used to visualise the residual posterior vitreous cortex (PVC). We hereby describe the utility of microscope-integrated optical coherence tomography (MIOCT) in assisting complete removal of PVC and internal limiting membrane (ILM) peeling with multilayered inverted ILM flap in the treatment of myopic macular hole retinal detachment. MIOCT helped identify vitreoschisis and confirm the position of ILM flaps over the macular hole intraoperatively.
Road junction detection from 3D point clouds (2016)

Detecting changing traffic conditions is of primal importance for the safety of autonomous cars navigating in urban environments. Among the traffic situations that require more attention and careful planning, road junctions are the most significant. This work presents an empirical study of the application of well known machine learning techniques to create a robust method for road junction detection. Features are extracted from 3D pointclouds corresponding to single frames of data collected by a laser rangefinder. Three well known classifiers-support vector machines, adaptive boosting and artificial neural networks-are used to classify them into “junctions” or “roads”. The best performing classifier is used in the next stage, where structured classifiers-hidden Markov models and conditional random fields-are used to incorporate contextual information, in an attempt to improve the performance of the method. We tested and compared these approaches on datasets from two different 3D laser scanners, and in two different countries, Germany and Brazil.
Nanosatellite maneuver planning for point cloud generation with a rangefinder (2015)

This paper discusses the application of a single beam laser rangefinder (LRF) to point cloud generation, shape detection, and shape reconstruction for a space-based space situational awareness (SSA) mission. The LRF is part of the payload of a chaser satellite tasked to image a resident space object (RSO). The one-dimensional (1D) nature of LRF returns significantly increases the complexity of the imaging task. To maximize coverage, a method to autonomously detect and fill gaps in sparse point cloud coverage using a narrow field of view (NFOV) camera in conjunction with the LRF is presented. First, relative orbital motion and scanning attitude motion are combined to generate a baseline 3D point cloud of the RSO. The effectiveness of pregenerated command profiles is analyzed by using a weighted edge reconstruction metric that scores how well a point cloud characterizes RSO shape. The design and characterization of multiple relative motion and attitude maneuver profiles, as well as the time and propellant cost of each profile, are presented with the assumption that the entire metrology chain is error free. Next, a three-part algorithm is used that creates a 3D panoramic map from stitched NFOV camera images, correlates the areas of sparse LRF coverage to the map, and generates attitude commands to close the coverage. This provides a consistent and reliable method to register positions of strike points relative to each other and to the NFOV image of the RSO with a priori knowledge of the RSO attitude. Gaps and sparse areas in LRF coverage are covered with strike points; the result is a point cloud of significantly higher resolution than that obtained with preprogrammed attitude profiles. The analysis bears particular relevance to power-constrained nanosatellite missions for space-based SSA for whom a multibeam LRF payload is not feasible. Maneuvers can now be designed on-line in real time; results presented validate the utility of a single-beam LRF as a tool for 3D imaging of RSO shapes.