gebhart/patrepeval huggingface dataset:
Videofluoroscopy in elderly patients with aspiration: importance of evaluating both oral and pharyngeal stages of deglutition. (1991)

Oropharyngeal functional impairment increases with age so that radiologists frequently are asked to determine the cause of aspiration in elderly patients. Neuromuscular and cognitive impairment often make it difficult to perform and interpret videofluoroscopic deglutition examinations in these patients. We retrospectively reviewed the barium swallow examinations in 50 elderly patients (mean age, 87 years) who were known to aspirate. We looked for specific patterns of oropharyngeal dysfunction that resulted in bolus misdirection. Analysis revealed that aspiration was due to abnormalities of the oral stage in 23, pharyngeal stage in 10, and both stages in 17. Dysfunction in the oral stage was due to ingestion of large volumes or rapid acquisition rates in nine, failure of containment during processing (bolus manipulation) in 18, and dissociation of lingual delivery and swallowing initiation in the transitional phase in 13. Dysfunction in the pharyngeal stage was due to incomplete transport (bolus retention) in 21 and defective closure of the laryngeal vestibule in 11. No significant relationship between conditions known to cause oropharyngeal dysfunction (dementia, stroke, Parkinson disease, disuse deconditioning) and the specific pattern of dysfunction was identified. These results indicate that an accurate and valid assessment of oropharyngeal dysfunction in elderly patients with aspiration is possible if specific patterns of dysfunction are sought. Our study indicates the importance of evaluating the oral and pharyngeal stages of deglutition in elderly patients who aspirate.
Preparation and characterization of phosphorus‐nitrogen polymers for flameproofing cellulose. I. Polymers of THPC and amines (1971)

Abstract Polymers from tetrakis(hydroxymethyl)phosphonium chloride (THPC) or tris(hydroxymethyl)phosphine (THP) with ammonia show similar thermal degradation, but appear to be of different chemical structure. Solution reaction of THPC with urea or melamine or by solid‐phase reaction with urea gives products ranging from water‐soluble liquids to hard, brittle, insoluble polymers. Reaction of THPC with piperazine yields products of low thermal stability.
Imaging through random media by use of low-coherence optical heterodyning (1995)

Optical heterodyning is a detection scheme that permits the preferential detection of ballistic photons transmitted through a random medium, providing the imaging of absorbing structures within. We introduce a normalized cross-correlation function as a quantitative measure of image quality and employ it to investigate the effect of source coherence length on the ability of optical heterodyning to detect these absorbing structures. The ability to image in transmission is found to be greatly enhanced by use of a reduced-coherence-length source. The effect on image quality of the transport mean-free-path length is quantified and found to depend on source coherence length. The necessity of considering scatterer particle–particle correlations is also presented.
Photovoltaic manufacturing technology, phase 1 (1991)

This report describes the Glasstech Solar design concepts for improved thin-film module production, including three process steps: (1) The front-end step includes washing, transparent conductive oxide (TCO) deposition, and patterning. (2) The P-I-N-M step is that in which the photovoltaic cell structure is deposited, including the back contact, without breaking vacuum. (3) The back end step includes masking, etching, washing, subcell testing and repair, interconnection, and encapsulation. The design is flexible and can be configured to a variety of applications. The front and back sections (steps 1 and 3) include a number of rotate modules and spacer conveyors. These modules and conveyors enable the line to hold and release glass panels according to the requirements of the process stations. 2 refs., 13 figs.
Privacy-aware dynamic feature selection (2015)

Big data will enable the development of novel services that enhance a company's market advantage, competition, or productivity. At the same time, the utilization of such a service could disclose sensitive data in the process, which raises significant privacy concerns. To protect individuals, various policies, such as the Code of Fair Information Practices, as well as recent laws require organizations to capture only the minimal amount of data necessary to support a service. While this is a notable goal, choosing the minimal data is a non-trivial process, especially while considering privacy and utility constraints. In this paper, we introduce a technique to minimize sensitive data disclosure by focusing on privacy-aware feature selection. During model deployment, the service provider requests only a subset of the available features from the client, such that it can produce results with maximal confidence, while minimizing its ability to violate a client's privacy. We propose an iterative approach, where the server requests information one feature at a time until the client-specified privacy budget is exhausted. The overall process is dynamic, such that the feature selected at each step depends on the previously selected features and their corresponding values. We demonstrate our technique with three popular classification algorithms and perform an empirical analysis over three real world datasets to illustrate that, in almost all cases, classifiers that select features using our strategy have the same error-rate as state-of-the art static feature selection methods that fail to preserve privacy.
The assessment of biologic treatment in patients with rheumatoid arthritis using FDG-PET/CT (2012)

The FDG uptake observed in the inflamed RA joints may reflect disease activity. The FDG-PET response was correlated with the clinical response to the biologic treatment of RA.
Joint Estimation of Channel and Oscillator Phase Noise in MIMO Systems (2012)

Oscillator phase noise limits the performance of high speed communication systems since it results in time varying channels and rotation of the signal constellation from symbol to symbol. In this paper, joint estimation of channel gains and Wiener phase noise in multi-input multi-output (MIMO) systems is analyzed. The signal model for the estimation problem is outlined in detail and new expressions for the Cramér-Rao lower bounds (CRLBs) for the multi-parameter estimation problem are derived. A data-aided least-squares (LS) estimator for jointly obtaining the channel gains and phase noise parameters is derived. Next, a decision-directed weighted least-squares (WLS) estimator is proposed, where pilots and estimated data symbols are employed to track the time-varying phase noise parameters over a frame. In order to reduce the overhead and delay associated with the estimation process, a new decision-directed extended Kalman filter (EKF) is proposed for tracking the MIMO phase noise throughout a frame. Numerical results show that the proposed LS, WLS, and EKF estimators' performances are close to the CRLB. Finally, simulation results demonstrate that by employing the proposed channel and time-varying phase noise estimators the bit-error rate performance of a MIMO system can be significantly improved.
Functionalized pyrolytic highly oriented graphite polymer film for surface‐assisted laser desorption/ionization mass spectrometry in environmental analysis (2009)

The pyrolytic highly oriented graphite polymer film (PGS) was first employed to analyze low-mass analytes in environmental analysis by surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS). PGS is a synthetic uniform and highly oriented graphite polymer film with high thermal anisotropic conductivity. We have found that negative ion mode SALDI-MS using oxidized PGS (PGS-SALDI-MS) can be used to detect [M-H]- ions from perfluorooctanoic acid (PFOA) and other perfluoroalkylcarboxylic acids when the PGS surface is modified with the cationic polymer polyethyleneimine (PEI). The signal intensity of PFOA when employing the PEI modification showed a ten-fold increase over that obtained from desorption/ionization on porous silicon (DIOS). PFOA was quantified using PGS-SALDI-MS and the calibration curve showed a wide linear dynamic range of response (20-1000 ppb). The combination of atmospheric pressure ionization and PGS (AP-PGS-SALDI) showed greater signal intensity than vacuum PGS-SALDI for deprotonated PFOA. Several other environmentally important chemicals, including perfluoroalkylsulfonic acid, pentachlorophenol, bisphenol A, 4-hydroxy-2-chlorobiphenyl, and benzo[a]pyrene, were also successfully used to evaluate PGS-SALDI-MS. In addition, we found that nonafluoro-1-butanesulfonic acid was able to produce protonated peptides in positive ion PGS-SALDI-MS, but that perfluoropentanoic acid and trifluoroacetic acid were not. It is suggested that perfluoroalkylsulfonic acids are better protonating agents than perfluoroalkylcarboxylic acids in SALDI-MS.
A Framework for Semi-Automated Fault Detection Configuration with Automated Feature Extraction and Limits Setting (2020)

In today's microelectronics manufacturing facilities, fault detection (FD) is pervasive as the primary advanced process control (APC) capability in use. The current approach to FD, while effective, has a number of shortcomings that impact its cost and effectiveness. The highest among these is the cost in time and resources associated with the largely manual methods used for partitioning and extraction of features of interest in individual traces. Additionally, once these features are extracted, feature-based univariate analysis (UVA) is the primary method used for process monitoring and FD, which fails to incorporate process variable correlations in detecting faults and quality issues. On the other hand, current multivariate analysis (MVA) approaches, such as principal component analysis (PCA), partial least squares (PLS), and their variants, focus on threshold setting in a multivariate space so that they cannot provide direct limit settings on raw (sensor) parameters for decision-making support during online process monitoring. Also, in bypassing feature identification and extraction, the subject matter expert (SME) is largely left out of the loop in MVA analysis; thus, information on the relationship between univariate features and faults is not captured. Furthermore, it is difficult to visualize and understand multivariate limits due to the high dimensionality of the data produced in microelectronics manufacturing processes. Finally, slow and normal process changes often occur in real processes, which can lead to false alarms during implementation when using models trained from offline samples. Thus, a need exists for an FD method that leverages the existing feature-based UVA and provides (1) a method for automated signal partitioning and feature extraction that allows for SME input, (2) an MVA mechanism which considers correlation among parameters and is adaptive to the normal process drift, (3) an automatic approach for limiting UVA features that captures the correlation among parameters, and (4) a methodology for easily viewing these capabilities so that an SME is able to view, understand, and continue to contribute to the FD optimization process. This capability has been developed and successfully applied to microelectronics manufacturing data sets and is proposed as a key component to future microelectronics smart manufacturing systems.
Efficient Distributed Third-Party Data Authentication for Tree Hierarchies (2008)

In the third-party model for the distribution of data, the trusted data creator or owner provides an untrusted distributor D with integrity verification (IV) items that are stored at D in addition to the n data items. When a user U has a subset of n' of those n data items and needs to verify their integrity, U is provided by D with a number of IV items that U uses to verify its data's integrity. The model forbids U from receiving any information about the n-n' data items that the user is not authorized to access, and assumes that D has no signature authority (it stores only pre-signed IVs). Most of the published work in this area uses the Merkle tree or variants thereof, and typically requires D to store a linear or close to linear (in n) number s(n) of IV items that are pre-signed by the trusted authority. Moreover, most of the existing schemes impose on D a non-constant amount of computation work t(n) (typically logarithmic in n) in order to provide U with the IV items that enable U to verify the integrity of its data; we call h(n) the number of such IV items. The h(n) values found in the literature are non-constant, i.e., they actually do depend on the number of data items. The main contribution of this paper is to achieve linear s(n), constant h(n) and constant or logarithmic t(n) when the n data items are organized in a tree hierarchy T, and the user's subset of n' items form a subtree T'. The cases of T' considered are when T' is (i) rooted at a node v and of depth k below v; and (ii) reachable in k hops from v going both up and down in T.
Real-time data driven monitoring and optimization method for IoT-based sensible production process (2013)

Typical challenges that manufacturing enterprises are facing now are compounded by lack of timely, accurate, and consistent information of manufacturing resources of shop floor. Recent developments in wireless sensors, communication and information network technologies have created a new era of the internet of things (IoT). In this paper, an overall architecture of the IoT-enabled manufacturing execution system is presented to provide a new paradigm by extending the techniques of IoT to manufacturing field. Under this architecture, the manufacturing things such as operators, machines, pallets, materials etc. can be embedded with sensors to interact with each other. And the real-time data driven monitoring and optimization for IoT-based sensible production process can be achieved to improve shop-floor productivity and quality, reduce the wastes of manufacturing resources, cut the costs in manufacturing logistics, reduce the risk and improve the efficiency in cross-border customs logistics and online supervision, and improve the responsiveness to production changes.
Modelling information persistence on the web (2006)

Models of web data persistency are essential tools for the designof efficient information extraction systems that repeatedlycollect and process the data. This study models the persistence ofweb data through the measurement of URL and content persistenceacross several snapshots of a national community web, collectedfor 3 years. We found that the lifetimes of URLs and contents aremodelled by logarithmic functions. We gathered statistics on thestructure of the web, identified reasons for URL death andcharacterized persistent URLs and contents. The lasting contentstend to be referenced by different URLs during their lifetime,while half of the contents referenced by persistent URLs do notchange.
Application of heterogeneous multiple camera system with panoramic capabilities in a harbor environment (2009)

In a harbor environment threats like explosives-packed rubber boats, mine-carrying swimmers and divers must be detected in an early stage. This paper describes the integration and use of a heterogeneous multiple camera system with panoramic observation capabilities for detecting these small vessels in the Den Helder New Harbor in the Netherlands. Results of a series of experiments with different targets are presented. An outlook to a future sensor package containing panoramic vision is discussed.
Does Landscape Diversity Slow the Spread of Rotation-Resistant Western Corn Rootworm (Coleoptera: Chrysomelidae)? (2003)

A behavioral change in some western corn rootworm (Diabrotica virgifera virgifera LeConte) populations is threatening the effectiveness of crop rotation, a successful management strategy for controlling this pest. We created a set of simple meteorologic and behavioral models that can be used to predict the spread of the beetle infesting soybean (Glycine max (L.)) throughout the midwestern United States. We used data collected in Illinois, IN, MI, and Ohio to create maps of observations to evaluate the model. We displayed data on the maps using detection thresholds for western corn rootworm in soybean fields of 10 or 20 beetles per 100 sweeps and one or two beetles per yellow sticky trap per day. Counts greater than a detection threshold represent populations with a lack of fidelity to corn (Zea mays L.) and adapted to circumvent corn-soybean rotation. Some of the models invoked a landscape-diversity function that included the proportion of noncorn, nonrotated soybean vegetation on farmland in each county (i.e., extra vegetation). The best model for the period from 1997 to 2001 is based on heavy-storm data, with distance that beetles spread each year reduced by the proportion of extra vegetation in a county. This version is superior to a previously published model and to two new models that do not consider landscape diversity. Most of the models predicted spread at too high a rate between 1997 and 2001, compared with observations, but a few new models with rates of spread reduced by a landscape-diversity function matched the observations relatively well. Results suggest that the conclusions based on a linear model using proportion of extra vegetation as the key parameter are likely to be robust. Thus, we hypothesize that as the landscape diversity represented by the proportion of noncorn and nonrotated soybean vegetation in a geographic region increases, the rate of regional spread of the rotation-resistant western corn rootworm decreases over several years.
Criterion for material selection in design of bulk piezoelectric energy harvesters (2010)

Vibration energy harvesting has gained tremendous attention in the past decade and continues to grow rapidly. There are various transduction mechanisms for converting the vibration energy into electrical energy, out of which the piezoelectric mechanism has been shown to provide advantages at the micro-to-meso scale. In the past few years, several studies have tried to address the question of which piezoelectric composition is better for energy harvesting; however, discussion on this subject continues. The intent of this letter is to provide an answer for this question through a simple criterion which can be used in routine material evaluation.
A Simple Radiological Method for Recognizing Osteoporotic Thoracic Vertebral Compression Fractures and Distinguishing Them From Scheuermann Disease (2009)

In Brief Study Design. Blinded. Objective. Examination of a new radiologic interpretation technique for distinguishing osteoporotic fractures from Scheuermann disease. Study of Background Data. Osteoporotic vertebral fractures are a major clinical problem. A variety of empirically-derived standards have been suggested for their recognition, but the accepted limits for normal variation have been somewhat arbitrary. This report presents and examines a new radiologic technique for distinguishing osteoporotic thoracic vertebral fractures from Scheuermann disease. Methods. Vertebral body height measurements (anterior, middle, and posterior) of thoracic vertebrae T6–T10 in 44 individuals with osteoporotic fractures, 28 individuals with Scheuermann disease and a control group of 120 individuals with unaffected vertebrae, were taken from lateral chest radiographs and measured by a digital caliper. For each vertebra, 4 indexes were calculated: 3 primary derivatives; anterior height/posterior height; anterior height/mid height (A/M); mid height/posterior height (M/P); and a secondary derivate index (A/M)/(M/P). Qualitative analysis was subsequently carried out, using lateral spine radiographs of individuals with osteoporotic vertebral fractures and individuals with Scheuermann disease. Statistical analysis included analysis of variance, paired t tests and t tests. Results. The second derivative (A/M)/(M/P) indexes of thoracic vertebrae T6–T10 were significantly greater in the osteoporosis group than in the control and Scheuermann groups (P < 0.05). Contrary to the control and Scheuermann groups, the M/P indexes (T6–T10) were significantly smaller than the A/M indexes in the osteoporosis group. The anterior height/posterior height indexes (T6–T10) in all 3 groups were statistically indistinguishable. Qualitative analysis showed that the intersection of an anterior-midpoint line and a posterior-midpoint line drawn on the superior vertebral body surface (T6–T10) created an “angle of depression” in the osteoporosis group whereas an “angle of elevation” was identified in the Scheuermann group. Conclusion. Second derivative indexes of vertebral body height parameters allow identification of vertebrae with osteoporotic compression fractures and their distinction from vertebrae with Scheuermann disease. Division of the lateral aspect of vertebral body into 2 segments exposes a previously unrecognized second derivative index apparently specific to diagnosing compression fractures, clearly distinguishing them from Scheuermann disease. This differential diagnosis is clearly visualized by the angle created between 2 drawn lines in the superior vertebral body surface.
Effects of a retroreflective screen on depth perception in a head-mounted projection display (2010)

The perceived depth accuracy is a fundamental performance metrics for an augmented reality display system. Many factors may affect the perceived depth of a head-mounted display (HMD), such as display resolution, interpupillary distance (IPD), conflicting depth cues, stereoacuity, and head tracking error. Besides these typical limiting factors to an HMD-type system, the perceived depth through a head-mounted projection display (HMPD) may be further affected by the usage of a retroreflective screen. In this paper, we will evaluate the perceived depth accuracy of an HMPD system using a perceptual depth matching method. The main factor to be investigated in our study is the position of a retroreflective screen relative to the projection image plane, with the projection image plane placed at different distances to the user. Overall, it is found that the ratio of the judged distance to real distance and the standard deviation of the judged distance increase linearly with the reference object distance. A transition effect from depth underestimation to overestimation has been observed at the reference object distance of around 1.4m. The position of a retroreflective screen only has a significant effect on the depth judgment error around this switching point. The paper also analyzes various effects brought by a retroreflective screen on the depth judgment. The depth cue and the image luminance reduction brought by a retroreflective screen could be the main factors that affect the depth judgment accuracy.