gebhart/patrepeval huggingface dataset:
Neutralization of Interferon Produced Early during Rabies Virus Infection in Mice (1986)

Inoculation of mice (strain C3H/He) with a purified preparation of fixed rabies virus led to the production of interferon with two different peaks of activity detectable in the plasma: an early peak 24 h after inoculation followed by another peak on the 7th day after infection. The level of splenic 2-5A synthetase was enhanced in parallel with the pattern of interferon activity. Neutralization of the first peak of interferon activity by anti-mouse alpha/beta interferon globulin blocked the induction of splenic 2-5A synthetase and modified the development of disease. Infected mice given anti-interferon globulin had a significantly shorter morbidity period than normally infected mice. These results suggest that interferon produced early after virus inoculation plays a role in the onset of rabies disease.
Sensitivity to Gravitational Waves from Compact Binary Coalescences Achieved during LIGO's Fifth and Virgo's First Science Run (2010)

We summarize the sensitivity achieved by the LIGO and Virgo gravitational wave detectors for compact binary coalescence (CBC) searches during LIGO's fifth science run and Virgo's first science run. We present noise spectral density curves for each of the four detectors that operated during these science runs which are representative of the typical performance achieved by the detectors for CBC searches. These spectra are intended for release to the public as a summary of detector performance for CBC searches during these science runs.
Neural Networks: A General Framework for Non-Linear Function Approximation (2006)

The focus of this paper is on the neural network modelling approach that has gained increasing recognition in GIScience in recent years. The novelty about neural networks lies in their ability to model non-linear processes with few, if any, a priori assumptions about the nature of the data-generating process. The paper discusses some important issues that are central for successful application development. The scope is limited to feedforward neural networks, the leading example of neural networks. It is argued that failures in applications can usually be attributed to inadequate learning and/or inadequate complexity of the network model. Parameter estimation and a suitably chosen number of hidden units are, thus, of crucial importance for the success of real world neural network applications. The paper views network learning as an optimization problem, reviews two alternative approaches to network learning, and provides insights into current best practice to optimize complexity so to perform well on generalization tasks.
Distribution of the pinewood nematode in China and susceptibility of some Chinese and exotic pines to the nematode (1989)

From 1983 to 1987 a survey was made to determine the hosts and geographic distribution of the pinewood nematode Bursaphelenchusxylophilus (Steiner and Buhrer), the cause of pine wilt disease, in China. Samples (669) were obtained from dead and dying conifers in 18 provinces and in the federally administrated cities of Beijing and Shanghai. The nematode was only found in samples from Pinusthunbergii and P. massoniana in and around the cities of Nanjing and Zhenjiang (both in Jiansu Province). To determine the susceptibility of Chinese and exotic pines to the pinewood nematode, 15 pine species were inoculated with a Chinese isolate. The 2- to 5-year-old trees, growing at Qingdao (Shandong Province) and Hongjiang (Hunan Province), were inoculated in mid-August to mid-October 1985. The results showed that one pine (P. bungeana) was extremely susceptible to the pinewood nematode, seven were highly susceptible (P. yunnanensis, P. densiflora, P. armandii, P. kwangtungensis, P. elliottii, P. koraiensis, and P. thunbergii), four were moderately susceptible (P. taiwanensis, P. griffithii, P. fenzeliana, and P. sylvestris var. mongolica), and three were resistant (P. taeda, P. massoniana, and P. banksiana). The results are discussed in relation to the needs for quarantine and management of pine wilt disease in the People's Republic of China.
Stochastic Data-driven Hardware Resilience to Efficiently Train Inference Models for Stochastic Hardware Implementations (2019)

Machine-learning algorithms are being employed in an increasing range of applications, spanning high-performance and energy-constrained platforms. It has been noted that the statistical nature of the algorithms can open up new opportunities for throughput and energy efficiency, by moving hardware into design regimes not limited to deterministic models of computation. This work aims to enable high accuracy in machine-learning inference systems, where computations are substantially affected by hardware variability. Previous work has overcome this by training inference model parameters for a particular instance of variation-affected hardware. Here, training is instead performed for the distribution of variation-affected hardware, eliminating the need for instance-by-instance training. The approach is referred to as Stochastic Data-Driven Hardware Resilience (S-DDHR), and it is demonstrated for an in-memory-computing architecture based on magnetoresistive random-access memory (MRAM). S-DDHR successfully address different samples of stochastic hardware, which would otherwise suffer degraded performance due to hardware variability.
[Biological evaluation of a protein mixture intended for enteral nutrition]. (2008)

The quality of the protein blend used in this study is high. It is a good protein source to be used in the development of new enteral nutritional products.
Synchronization of the distributed PWM carrier waves for modular multilevel converters (2014)

The half-bridge modular multilevel converter has proven itself to be a suitable solution for HVDC application. In order to achieve high modularity and fault tolerance, distributed control strategy is one possible solution and is discussed in this paper. When distributed control strategy is used, there is a central controller and a local controller in each sub-module (SM). A problem appears when implementing the modulation using this type of control strategy; this is the lack of synchronization between the internal clocks of the different submodules controllers of the MMC. This will cause a drift between the PWM outputs of each sub-module increasing the total harmonic distortion of the output voltage. This paper presents a solution to synchronize the PWM outputs of the MMC submodules using EtherCAT communication protocol focusing on phase shifted PWM modulation technique.
Structure and expression of c‐<i>erb</i>B‐2 and EGF receptor genes in inflammatory and non‐inflammatory breast cancer: Prognostic significance (1989)

C-erbB-2 and epidermal growth factor receptor (EGFR) genes were independently shown to be associated with breast cancer progression. In this report, we have analyzed the structure and expression of these 2 genes in the same tumor specimens of a large series of breast cancers. Two clinical types of tumor were studied: inflammatory (IBC) and non-inflammatory breast cancers (NBC) obtained from 221 untreated patients at different clinical stages. Amplification and over-expression of the c-erbB-2 proto-oncogene were observed in 27% and 47% of tumors, respectively, and were strongly associated with breast cancers of the most unfavorable prognosis, namely IBC and NBC with multiple positive axillary nodes. EGFR gene was neither amplified nor rearranged. A restriction fragment length polymorphism (RFLP) for HindIII endonuclease was observed. EGFR transcripts were detected in 46% of tumors and observed more frequently in IBC than in NBC (p less than 0.02). In NBC the presence of EGFR transcripts increased linearly with lymph-node involvement and was associated with estrogen-receptor-negative tumors (p = 0.01). Analysis of both genes from the same tumor samples indicated that genes are associated with cancer aggressiveness. Furthermore, in NBC these 2 genes were independently activated, in contrast to IBC in which activated genes were negatively correlated, suggesting that c-erbB-2 and EGFR genes play different roles in NBC and IBC.
Method for phase polarization recording of holograms (1974)

A theoretical justification is given for a holographic method of polarization recording utilizing the Weigert effect (the optically induced pure birefringence) in light-sensitive media. The paraxial approximation is used to demonstrate the reconstruction of the vector field of an object.
Properties of Partially Stabilized Zirconia Fuel Cell (1989)

Much attention has been focused on the solid oxide fuel cell (SOFC). The tubular configuration is being developed by Westinghouse Corporation and pilot plant facilities are operated in the 1 to 5kW range. The other SOFC configurations have now been proposed: monolithic SOFC and planar configuration SOFC. Fully stabilized zirconia (FSZ) was applied to SOFC as electrolytes, since FSZ offers a superior oxygen conductivity. However, yttria doped zirconia has three different modifications: monoclinic, tetragonal, and cubic phases. In FSZ, a high yttria doping retains the normal high-temperature cubic over a wide range of temperature. Partially stabilized zirconia (PSZ), with a lower concentration of yttria dopant, consists mainly of the tetragonal phase and possesses a high strength and a high toughness despite the fact that FSZ is brittle. The mechanical properties of PSZ seem to be derived from the stress-induced tetragonal to monoclinic transition, which may provide an ambiguity on long term stability at high temperature. Advances in ceramics technology allow the fabrication of thin PSZ sheets below the thickness of 0.25 mm. The thin PSZ sheets could provide a new assembly of SOFC through PSZ sheets conductivity is one order lower than that of 1000{degrees}C. Thus, a thin PSZ sheetmore » is a good candidate for a SOFC electrolyte. In this paper, the properties of SOFC using PSZ as an electrolyte are presented.« less
ScoutNode: A Multimodal Sensor Node for Wide Area Sensor Networks (2009)

In this paper, we present a commercial sensor node platform called ScoutNode. It is based on a novel modular architecture that supports three very powerful functionalities - multimodal support with a maximum of twenty five sensors supported on a single node that includes multiple video cameras; a user- friendly API for application development, and interoperability with a variety of 802.x hardware and protocols. ScoutNode architecture has been developed to support the operational concept and requirements of unattended ground sensor (UGS) nodes for net-centric information collection for the military. It offers a very comprehensive sensing, processing, and communication platform for building a variety of military and commercial applications. The ScoutNode platform described in this paper is fully functional and a node based on this platform designed specially for the military was tested successfully by the US Army.
P-100 (2012)

Kim, Byung-Mi; Lee, Boeun; Hongc, Yun-Chul; Park, Hye-Sook; Ha, Mina; Kim, Young Ju; Kim, Yangho; Chang, Namsoo; Kim, Bung-Nyun; Se-young, Oh; Eun-Hee, Ha Author Information
IEEE 1394a_2000 Physical Layer ASIC (2002)

CN4011A is IEEE 1394a_2000 standard compliant physical layer ASIC. It is a 0.18 /spl mu/m mixed-signal ASIC incorporating three analog ports, PLL, reference generator for analog along with the digital control logic. The whole ASIC from specification to GDSII including analog was designed at Controlnet (1) Pvt. Ltd. CN4011A has three 1394a_2000 fully compliant ports that support data transfers at 100/200/400 Mbps. It supports repeating of data over all ports other then receiving port. It is interoperable with other 1394a_2000 compliant physical layers and fully compliant with 1394a_2000 link layer and OHCI. The ASIC operates on a single 24.576 MHz external crystal oscillator. The internal PLL generates 400 MHz clock. This clock is divided to get the clocks required for the internal logic and to transmit and receive data at 100/200/400 Mbps over the serial interface and over the link interface.
User Selection for SDMA Beamforming with Imperfect CSI in MIMO-OFDM Systems (2007)

Leveraging multi-user diversity by selecting users from a user pool has been a critical strategy for realizing a fraction of the MIMO broadcast channel capacity. This paper considers exploiting multi-user diversity in a unique and practical setting that includes - significant transmit correlation, a broadband channel using OFDM, and imperfect CSI at the transmitter derived from channel reciprocity techniques. These imply a higher correlation amongst user channels and an increase in the volume of CSI per user. Under these assumptions, algorithms are presented for selecting <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G</i> out of <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Nu</i> users for applying SDMA beamforming and also for switching off SDMA when the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G</i> selected user channels may not support simultaneous transmission. In a EUTRA-type simulation setting, the algorithms lead to gains on the order of 5-7 dB in coded FER with reasonable costs in terms of CSI, sum-rate and computational complexity.
ANTXR1, a Stem Cell-Enriched Functional Biomarker, Connects Collagen Signaling to Cancer Stem-like Cells and Metastasis in Breast Cancer (2013)

Cancer stem-like cells are thought to contribute to tumor recurrence. The anthrax toxin receptor 1 (ANTXR1) has been identified as a functional biomarker of normal stem cells and breast cancer stem-like cells. Primary stem cell-enriched basal cells (CD49f(+)/EpCAM(-)/Lin(-)) expressed higher levels of ANTXR1 compared with mature luminal cells. CD49f(+)/EpCAM(-), CD44(+)/EpCAM(-), CD44(+)/CD24(-), or ALDEFLUOR-positive subpopulations of breast cancer cells were enriched for ANTXR1 expression. CD44(+)/CD24(-)/ANTXR1(+) cells displayed enhanced self-renewal as measured by mammosphere assay compared with CD44(+)/CD24(-)/ANTXR1(-) cells. Activation of ANTXR1 by its natural ligand C5A, a fragment of collagen VI α3, increased stem cell self-renewal in mammosphere assays and Wnt signaling including the expression of the Wnt receptor-lipoprotein receptor-related protein 6 (LRP6), phosphorylation of GSK3α/β, and elevated expression of Wnt target genes. RNAi-mediated silencing of ANTXR1 enhanced the expression of luminal-enriched genes but diminished Wnt signaling including reduced LRP6 and ZEB1 expression, self-renewal, invasion, tumorigenicity, and metastasis. ANTXR1 silencing also reduced the expression of HSPA1A, which is overexpressed in metastatic breast cancer stem cells. Analysis of public databases revealed ANTXR1 amplification in medullary breast carcinoma and overexpression in estrogen receptor-negative breast cancers with the worst outcome. Furthermore, ANTXR1 is among the 10% most overexpressed genes in breast cancer and is coexpressed with collagen VI. Thus, ANTXR1:C5A interactions bridge a network of collagen cleavage and remodeling in the tumor microenvironment, linking it to a stemness signaling network that drives metastatic progression.
Characterization of Glucosensing Neuron Subpopulations in the Arcuate Nucleus (2007)

Four types of responses to glucose changes have been described in the arcuate nucleus (ARC): excitation or inhibition by low glucose concentrations <5 mmol/l (glucose-excited and -inhibited neurons) and by high glucose concentrations >5 mmol/l (high glucose-excited and -inhibited neurons). However, the ability of the same ARC neuron to detect low and high glucose concentrations has never been investigated. Moreover, the mechanism involved in mediating glucose sensitivity in glucose-inhibited neurons and the neurotransmitter identity (neuropeptide Y [NPY] or pro-opio melanocortin [POMC]) of glucosensing neurons has remained controversial. Using patch-clamp recordings on acute mouse brain slices, successive extracellular glucose changes greater than and less than 5 mmol/l show that glucose-excited, high glucose-excited, glucose-inhibited, and high glucose-inhibited neurons are different glucosensing cell subpopulations. Glucose-inhibited neurons directly detect decreased glucose via closure of a chloride channel. Using transgenic NPY-green fluorescent protein (GFP) and POMC-GFP mice, we show that 40% of NPY neurons are glucose-inhibited neurons. In contrast, <5% of POMC neurons responded to changes in extracellular glucose >5 mmol/l. In vivo results confirm the lack of glucose sensitivity of POMC neurons. Taken together, hypo- and hyperglycemia are detected by distinct populations of glucosensing neurons, and POMC and NPY neurons are not solely responsible for ARC glucosensing.
CD26 (dipeptidyl peptidase IV/DPP IV) as a novel molecular marker for differentiated thyroid carcinoma (1995)

In this report we show that CD26 (dipeptidyl peptidase IV/DPP IV) is a novel molecular marker for differentiated thyroid carcinoma. Northern-blot analysis of 22 various thyroid tissues revealed that CD26 is a more specific marker of differentiated thyroid carcinoma than 3 proto-oncogenes previously reported to increase mRNA expression in thyroid carcinomas: c-met, c-erbB-2 and EGF-R. A comparative study of 3 CD26 assays, Northern blotting, immunohistochemical staining and activity staining clearly showed that CD26 enzyme activity staining is the most specific assay for differentiated thyroid carcinoma, yet the easiest to perform. Activity staining of 216 thyroid tissues detected CD26 in all 52 papillary carcinomas and all 5 follicular carcinomas, while all 58 cases of Graves' disease were CD26-negative. Among benign neoplasms, 54 of 55 adenomatous goiters and 29 of 33 follicular adenomas were CD26 negative. Staining intensity of the enzyme activity was relative to the degree of CD26 mRNA expression. Southern-blot study showed no gene amplification or major translocation of the CD26 gene in 7 papillary carcinomas examined. Based on this study, ectopic expression of CD26 in differentiated thyroid carcinomas is thought to be mainly caused by increased CD26 mRNA expression. In conclusion, CD26 activity staining is a simple, specific assay which should be added to the usual pathological examinations in order to distinguish differentiated thyroid carcinomas from benign thyroid diseases.
Multi-sensor indoor pedestrian navigation system with vision aiding (2012)

In many indoor security and rescue missions, it is essential for the deployed personnel to have accurate positioning information available. If the scene is not explored yet, a map has to be created during the mission and exchanged between different teams, so that subsequent team members benefit from the knowledge about previously visited locations. In this paper, the multi-sensor navigation system called IndoorGuide is presented which accomplishes these tasks. It comprises two lightweight micro-electro-mechanical inertial measurement units for tracking the motion of the user. A monocular camera is integrated in the navigation system which provides attitude and position aiding. The attitude information is extracted by tracking vanishing points in the images of the camera. Position aiding is realized by mapping and recognizing visited locations. For the data fusion, a Kalman Filter and a robust optimization technique based on graphs are compared. Results from experimental test runs are presented and discussed.
Suggesting Comment Completions for Python using Neural Language Models (2020)

Source-code comments are an important communication medium between developers to better understand and maintain software. Current research focuses on auto-generating comments by summarizing the code. However, good comments contain additional details, like important design decisions or required trade-offs, and only developers can decide on the proper comment content. Automated summarization techniques cannot include information that does not exist in the code, therefore fully-automated approaches while helpful, will be of limited use. In our work, we propose to empower developers through a semi-automated system instead. We investigate the feasibility of using neural language models trained on a large corpus of Python documentation strings to generate completion suggestions and obtain promising results. By focusing on confident predictions, we can obtain a top-3 accuracy of over 70%, although this comes at the cost of lower suggestion frequency. Our models can be improved by leveraging context information like the signature and the full body of the method. Additionally, we are able to return good accuracy completions even for new projects, suggesting the generalizability of our approach.
Security for a High Performance Commodity Storage Subsystem (CMU-CS-99-160) (2018)

How do we incorporate security into a high performance commodity storage sub- system? Technology trends and the increasing importance of I/O bound workloads are driving the development of commodity network attached storage devices which deliver both increased functionality and increased performance to end-users. In the network attached world, storage devices co-exist on the network with their clients, application file-managers, and malicious adversaries who seek to bypass system security policies. As storage devices move from behind the protection of a server and become first-class network entities in their own right, they must become actively involved in protecting themselves from network attacks. They must do this while cooperating with higher level applications, such as distributed file systems or database systems, to enforce the application's security policies over storage resources. In this dissertation, I address this problem by proposing a cryptographic capability system which enables application filemanagers to asynchronously make policy decisions while the commodity storage devices synchronously enforce these decisions. This dissertation analyzes a variety of access control schemata that exist in current distributed storage systems. Motivated by the analysis, I propose a basic cryptographic capability system that is flexible enough to efficiently meet the requirements of many distributed storage systems. Next, I explore how a variety of different mechanisms for describing a set of NASD objects can be used to improve the basic capability system. The result is a new design based on remote execution techniques. The new design places more access control processing at the drive in order to deliver increased performance and functional advantages. Based on the performance limitations of software cryptography demonstrated in a prototype implementation of a network attached storage device, I propose and evaluate an alternative to standard message authentication codes. This allows storage devices to precompute some security information and reduces the amount of request-time computation required to protect the integrity of read operations. Finally, I discuss the availability of cryptographic hardware, how much is required for a network attached storage device, and the implications of adding tamper-resistant hardware to a storage device.