gebhart/patrepeval huggingface dataset:
Development, Characterization, and Applications of Gold and Platinum Bulk Metallic Glasses (2007)

The development of bulk metallic glass alloys is presented with various elemental selection criteria, design strategies, and experimental techniques. The focus was later drawn towards the development of noble bulk metallic glasses based on gold and platinum. To formulate a good bulk glass forming composition, we found that the gold alloys had to be optimized using uncommon approaches. One strategy was to primarily increase the glass transition temperature of the alloy, instead of lowering the melting temperature. The resulting gold bulk metallic glass alloy could be cast fully amorphous up to 5 mm thick. However, the best gold glass former also exhibited many anomalous behaviors; for example, a very high strain rate could induce phase separation in the bulk glass forming liquid. A detail study on the strain rate induced crystallization was carried out systematically to pinpoint the exact conditions that would cause an anomaly. Additionally, a variety of comparative studies were conducted on the gold and platinum bulk metallic glass alloys, including elastic constants measurement, heat capacity measurement, viscosity measurement using three-point beam bending, and time to crystallization study in order to construct a Time-Temperature Transformation diagram. The last chapter switches gears to the engineering and technology aspect of gold and platinum bulk metallic glasses. The thermoplastic soldering technique is introduced as a novel method for joining any two materials at temperatures lower than that of brazing or welding processes. The proposed technique is a new alternative to the lead-free soldering process available to the electronic industry.
Silicon resonant cavity enhanced 12 × 1 photodetector arrays for optical interconnect receiver integration (2004)

This paper presents Si-resonant cavity enhanced (RCE) photodetector arrays that have been fabricated and packaged with silicon based amplifiers to demonstrate the feasibility of a low cost monolithic silicon photoreceiver array. The 12 /spl times/ 1 photodetector arrays were designed for the PAROLI product line specification. The specification calls for 12 photodetectors with between 30 and 80 /spl mu/m photodetector active area in a linear array on a 250 /spl mu/m pitch.
Abnormal venous valves: a cause of early obstruction of saphenous vein bypass grafts. (1983)

Factors other than technical error and poor run-off may account for occlusion or obstruction of aortocoronary vein bypass grafts in the early postoperative period. Four cases are presented in which graft obstruction was caused by venous valves. Discussion of the etiology of this problem and recommendations for its prevention are included.
One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search (2021)

Convolutional neural networks (CNNs) are used in numerous real-world applications such as vision-based autonomous driving and video content analysis. To run CNN inference on various target devices, hardware-aware neural architecture search (NAS) is crucial. A key requirement of efficient hardware-aware NAS is the fast evaluation of inference latencies in order to rank different architectures. While building a latency predictor for each target device has been commonly used in state of the art, this is a very time-consuming process, lacking scalability in the presence of extremely diverse devices. In this work, we address the scalability challenge by exploiting latency monotonicity --- the architecture latency rankings on different devices are often correlated. When strong latency monotonicity exists, we can re-use architectures searched for one proxy device on new target devices, without losing optimality. In the absence of strong latency monotonicity, we propose an efficient proxy adaptation technique to significantly boost the latency monotonicity. Finally, we validate our approach and conduct experiments with devices of different platforms on multiple mainstream search spaces, including MobileNet-V2, MobileNet-V3, NAS-Bench-201, ProxylessNAS and FBNet. Our results highlight that, by using just one proxy device, we can find almost the same Pareto-optimal architectures as the existing per-device NAS, while avoiding the prohibitive cost of building a latency predictor for each device.
Models of Mental Health (2016)

A comprehensive understanding of the different theoretical models in mental health is essential when working with people with mental health difficulties.<br/><br/>Brought together by a multidisciplinary team, this book presents a critical overview of the key theoretical perspectives that underpin mental health practice, examining both traditional and contemporary schools of thought. Offering an accessible foundation for expanding your knowledge, the authors argue that no single theory provides a complete framework for practice on its own, highlighting how each theory has contributions, strengths and limitations.<br/><br/>New to this edition:<br/>- Two brand new chapters exploring intersectional and environmental perspectives<br/>- Expanded coverage of LGBTQIA+ and trauma-informed models, featuring two new authors with expertise in trauma-informed, recovery-focused approaches and evidence reviewing<br/>- Greater focus on service-user led knowledge and experience<br/><br/>Supported by a range of exercises and case studies, this book remains an essential resource for anyone studying or practising in the field of mental health.
Treatment of Chlorinated Solvents by Nitrogen-Fixing and Nitrate-Supplied Methane Oxidizers in Columns Packed with Unsaturated Porous Media (2000)

This study compares the feasibility of employing nitrogen-fixing and nitrate-supplied methane-oxidizing cultures grown in unsaturated porous media to degrade cis-1,2-dichloroethylene (cDCE) and trichloroethylene (TCE) in gas streams. Both nitrate-supplied and nitrogen-fixing columns (supplied with 10% CH4 and 10% O2) degraded TCE completely at a gaseous concentration of 0.7 mg/L for 8−10 days. However, when columns were supplied with 4% CH4 and 10% O2, nitrate-supplied columns were not able to recover after degrading TCE at a gaseous concentration of 0.13 mg/L for 7 days. In contrast, nitrogen-fixing columns recovered after degrading 0.13−0.4 mg/L TCE for 3−10 days and were capable of repeatedly degrading TCE at gaseous concentrations of 0.03−0.14 mg/L during long-term intermittent operation (lasting from 38 to 84 days) that was punctuated by appropriate microbial recovery periods (7−9 days). Both nitrate-supplied and nitrogen-fixing columns were capable of degrading cDCE at concentrations of 0.7−1.0 mg/L for 5−10 days, but only the nitrogen-fixing columns recovered from cDCE exposure. The operating period for columns treating a mixture of TCE and cDCE was significantly shorter than that for treatment of TCE or cDCE alone. Several operating curves (percent chlorinated solvent removal versus mass of chlorinated solvent loaded per mass of methane consumed) were developed to facilitate comparisons between operating conditions and to aid in predicting chlorinated solvent removals in such systems. Nitrogen-fixing columns consistently outperformed nitrate-supplied columns, and columns inoculated with a mixed culture outperformed those inoculated with Methylosinus trichosporium OB3b for TCE removal but not for cDCE removal.
SARS-CoV-2 neutralising antibodies in dogs and cats in the United Kingdom (2021)

Companion animals are susceptible to SARS-CoV-2 infection and sporadic cases of pet infections have occurred in the United Kingdom. Here we present the first large-scale serological survey of SARS-CoV-2 neutralising antibodies in dogs and cats in the UK. Results are reported for 688 sera (454 canine, 234 feline) collected by a large veterinary diagnostic laboratory for routine haematology during three time periods; pre-COVID-19 (January 2020), during the first wave of UK human infections (April-May 2020) and during the second wave of UK human infections (September 2020-February 2021). Both pre-COVID-19 sera and those from the first wave tested negative. However, in sera collected during the second wave, 1.4% (n ​= ​4) of dogs and 2.2% (n ​= ​2) of cats tested positive for neutralising antibodies. The low numbers of animals testing positive suggests pet animals are unlikely to be a major reservoir for human infection in the UK. However, continued surveillance of in-contact susceptible animals should be performed as part of ongoing population health surveillance initiatives.
Entity Matching in the Wild: A Consistent and Versatile Framework to Unify Data in Industrial Applications (2020)

Entity matching -- the task of clustering duplicated database records to underlying entities -- has become an increasingly critical component in modern data integration management. Amperity provides a platform for businesses to manage customer data that utilizes a machine-learning approach to entity matching, resolving billions of customer records on a daily basis. We face several challenges in deploying entity matching to industrial applications at scale, and they are less prominent in the literature. These challenges include: (1) Providing not just a single entity clustering, but supporting clusterings at multiple confidence levels to enable downstream applications with varying precision/recall trade-off needs. (2) Many customer record attributes may be systematically missing from different sources of data, creating many pairs of records in a cluster that appear to not match due to incomplete, rather than conflicting information. Allowing these records to connect transitively without introducing conflicts is invaluable to businesses because they can acquire a more comprehensive profile of their customers without incorrect entity merges. (3) How to cluster records over time and assign persistent cluster IDs that can be used for downstream use cases such as A/B tests or predictive model training; this is made more challenging by the fact that we receive new customer data every day and clusters naturally evolving over time still require persistent IDs that refer to the same entity. In this work, we describe Amperity's entity matching framework, Fusion, and how its design provides solutions to these challenges. In particular, we describe our pairwise matching model based on ordinal regression that permits a well-defined way to produce entity clusterings at different confidence levels, a novel clustering algorithm that separates conflicting record pairs in clusters while allowing for pairs that may appear dissimilar due to missing data, and a persistent ID generation algorithm which balances stability of the identifier with ever-evolving entities.
Tumor uptake and elimination of 2',2'-difluoro-2'-deoxycytidine (gemcitabine) after deoxycytidine kinase gene transfer: correlation with in vivo tumor response. (2001)

These data support the hypothesis that increased expression of dCK cDNA in HT-29 xenografts results in an enhanced dFdCTP accumulation and prolonged elimination kinetics, and ultimately a potentiated in vivo tumor response to dFdCyd. Related to these effects, changes in the overall tumor metabolism of dFdCyd/dFdCTP was detectable by noninvasive F-19 MRS. These data are relevant to future preclinical and clinical studies evaluating dCK gene transfer and dFdCyd therapy.
State-Space Modeling of Proton Exchange Membrane Fuel Cell (2010)

In this paper, a nonlinear state-space model of the 500-W proton exchange membrane (PEM) fuel cell is developed. The open-circuit output voltage of the PEM fuel cell, mass balance, and thermodynamic energy balance inside the PEM fuel cell, voltage losses in the PEM fuel cell, along with the formation of a double layer charge in the PEM fuel cell system are modeled. The model is simulated in MATLAB/Simulink, and the transient response of the PEM fuel cell model over short and long time periods is analyzed. Also, the behavior of the model under the resistive load is studied, and the results are shown.
Intradermal Immunization with Wall Teichoic Acid (WTA) Elicits and Augments an Anti-WTA IgG Response that Protects Mice from Methicillin-Resistant Staphylococcus aureus Infection Independent of Mannose-Binding Lectin Status (2013)

The objectives of this study were to investigate the immune response to intradermal immunization with wall teichoic acid (WTA) and the effect of MBL deficiency in a murine model of infection with methicillin-resistant Staphylococcus aureus (MRSA). WTA is a bacterial cell wall component that is implicated in invasive infection. We tested susceptibility to MRSA infection in wild type (WT) and MBL deficient mice using two strains of MRSA: MW2, a community-associated MRSA (CA-MRSA); and COL, a healthcare-associated MRSA (HA-MRSA). We also performed in vitro assays to investigate the effects of anti-WTA IgG containing murine serum on complement activation and bacterial growth in whole blood. We found that MBL knockout (KO) mice are relatively resistant to a specific MRSA strain, MW2 CA-MRSA, compared to WT mice, while both strains of mice had similar susceptibility to a different strain, COL HA-MRSA. Intradermal immunization with WTA elicited and augmented an anti-WTA IgG response in both WT and MBL KO mice. WTA immunization significantly reduced susceptibility to both MW2 CA-MRSA and COL HA-MRSA, independent of the presence of MBL. The protective mechanisms of anti-WTA IgG are mediated at least in part by complement activation and clearance of bacteria from blood. The significance of these findings is that 1) Intradermal immunization with WTA induces production of anti-WTA IgG; and 2) This anti-WTA IgG response protects from infection with both MW2 CA-MRSA and COL HA-MRSA even in the absence of MBL, the deficiency of which is common in humans.
Detection and manipulation of methylation in blood cancer DNA using terahertz radiation (2019)

DNA methylation is a pivotal epigenetic modification of DNA that regulates gene expression. Abnormal regulation of gene expression is closely related to carcinogenesis, which is why the assessment of DNA methylation is a key factor in cancer research. Terahertz radiation may play an important role in active demethylation for cancer therapy because the characteristic frequency of the methylated DNA exists in the terahertz region. Here, we present a novel technique for the detection and manipulation of DNA methylation using terahertz radiation in blood cancer cell lines. We observed the degree of DNA methylation in blood cancer at the characteristic resonance of approximately 1.7 THz using terahertz time-domain spectroscopy. The terahertz results were cross-checked with global DNA methylation quantification using an enzyme-linked immunosorbent assay. We also achieved the demethylation of cancer DNA using high-power terahertz radiation at the 1.7-THz resonance. The demethylation degrees ranged from 10% to 70%, depending on the type of cancer cell line. Our results show the detection of DNA methylation based on the terahertz molecular resonance and the manipulation of global DNA methylation using high-power terahertz radiation. Terahertz radiation may have potential applications as an epigenetic inhibitor in cancer treatment, by virtue of its ability to induce DNA demethylation, similarly to decitabine.
Current Approaches to the Management of Plantar Heel Pain Syndrome, Including the Role of Injectable Corticosteroids (2007)

Plantar heel pain syndrome, which has a multifactorial and widely disputed etiology, affects more than 2 million people annually. A survey was conducted of members of the American Academy of Podiatric Sports Medicine about their strategies for managing plantar heel pain syndrome, especially the role of injectable corticosteroids. The respondents tended to be experienced (10-24 years in practice) podiatric physicians with a concentration in sports medicine. They reported that for early-stage plantar heel pain syndrome they generally recommend avoidance of wearing flat shoes and walking barefoot (92%), use of over-the-counter arch supports and heel cushions (90%), regular stretching of the calf muscles (88%), strapping of the foot (75%), cryotherapy applied directly to the affected part of the foot (67%), and nonsteroidal anti-inflammatory drug therapy (60%). When these measures fail to relieve heel pain, most of the responding podiatric physicians recommend using custom orthotic devices (60%) and corticosteroid injections (60%) as intermediate therapy. Surgical plantar fasciotomy (88%), cast immobilization (77%), and extracorporeal shockwave therapy (69%) are generally recommended as late-stage therapy for resistant cases. A staged approach seems to yield the best results in treatment of this common condition.
Modeling of GaN-Based Normally-Off FinFET (2014)

In this letter, a macromodel for normally-off (enhancement mode) AlGaN/GaN-based FinFET (2-DEG channel at top with two MOS like sidewall channels) is proposed. AlGaN/GaN-based FinFET devices have improved gate control on the channel due to additional sidewall gates compared with planar structures, but device characteristics exhibit strong nonlinear dependence on fin-width. The proposed model captures both 2-DEG and sidewall channel conduction as well as the fin-width dependency on device characteristics. Model shows excellent agreement with state-of-the-art experimental data.
Thinking Fast and Slow with Deep Learning and Tree Search (2017)

Sequential decision making problems, such as structured prediction, robotic control, and game playing, require a combination of planning policies and generalisation of those plans. In this paper, we present Expert Iteration (ExIt), a novel reinforcement learning algorithm which decomposes the problem into separate planning and generalisation tasks. Planning new policies is performed by tree search, while a deep neural network generalises those plans. Subsequently, tree search is improved by using the neural network policy to guide search, increasing the strength of new plans. In contrast, standard deep Reinforcement Learning algorithms rely on a neural network not only to generalise plans, but to discover them too. We show that ExIt outperforms REINFORCE for training a neural network to play the board game Hex, and our final tree search agent, trained tabula rasa, defeats MoHex, the previous state-of-the-art Hex player.
Evaluation of Potential ITS Strategies Under Non-Recurrent Congestion Using Microscopic Simulation (2003)

This report presents a micro-simulation method to evaluate potential ITS applications. Based on the commercial PARAMICS model, a capability-enhanced PARAMICS simulation environment has been developed through integrating a number of plug- in modules implemented with Application Programming Interfaces (API). This enhanced PARAMICS simulation can thus have capabilities to model not only the target traffic conditions and operations but also various potential ITS strategies. An evaluation study on the effectiveness of potential ITS strategies under the incident scenarios is conducted over a corridor network located at the city of Irvine, California. The potential ITS strategies include incident management, local adaptive ramp metering, coordinated ramp metering, traveler information systems, and the combination of above. Based on the calibrated simulation model, we implement and evaluate these scenarios. The evaluation results show that all ITS strategies have positive effects on the network performance. Because of the network topology (one major freeway with two parallel arterial streets), real-time traveler information system has the greatest benefits among all single ITS components. The combination of several ITS components, such as the corridor control and the combination scenarios, can generate better benefits.
Long-term follow-up of Hirschsprung's disease: review of early and late complications. (1996)

Early complications were seen with equal frequency in patients with either SP or MDP but late complications were seen less often with the SP. Both SP and MDP were equally effective in the definitive treatment of Hirschprung's disease.
A comprehensive investigation of the origins of surface roughness and haze in polyethylene blown films (2002)

Abstract In an earlier publication we showed that the optical haze properties of blown and cast polyethylene (PE) films were adversely affected (i.e., haze increased) as a result of enhanced surface roughness caused by the formation of distinct optically anisotropic “spherulitic‐like” superstructures. In this report we have found that for a very wide variety of PE blown films, the total haze percent exhibited a complex parabolic relationship with the logarithm of the recoverable shear strain parameter, γ ∞ . At low values of γ ∞ , superstructures were developed (as discussed in our previous report) that increased surface roughness and hence total haze. As γ ∞ increased, such superstructures were either significantly diminished in size or altogether absent, giving rise instead to an oriented, row‐nucleated, stacked lamella texture that decreased surface roughness and hence total haze. However, at even higher γ ∞ values, representing highly melt elastic behavior, fine‐scale surface roughness due to high melt elastic instabilities was induced, thereby increasing surface roughness and consequently total haze as well. It was demonstrated in this work that two PE resins could exhibit the same level of total haze as a consequence of two completely different mechanisms or origins. Furthermore, we believe that this is the first time that both very low and very high melt elasticity have been shown as primary causative factors in yielding high haze in PE blown films, albeit for fundamentally very different reasons. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 2396–2411, 2002
Hybrid POS Classification Using Long Short Term Memory (2018)

A Part of Speech classifier is an important tool that is used to develop many NLP tasks. In this paper we described Deep Neural Network based architecture, that given a sentence, outputs a part-of-speech tag sequence. For Part of Speech classification, we trained a LSTM network by semi-supervised learning. We further applied a probabilistic approach to improve Part of Speech prediction of the LSTM network. Word2vec deep learning tool is used for learning high-quality distributed vector representations of words that capture a large number of precise word relationships. By using a small amount of labeled dataset of words and applying cosine similarity we assign Part of Speech tags to words. If some words don't show nearness to any word in labeled dataset, then we apply probabilistic approach for classification of unclassified words of input sentence. This hybrid neural Part of Speech classifier is evaluated over a corpus of 1000 sentences having a total of 7,400 words; part of speech classification system achieved the accuracy of 94.71 %.
Method of monitoring CO concentrations in hydrogen feed to a PEM fuel cell (2023)

The CO concentration in the H.sub.2 feed stream to a PEM fuel cell stack is monitored by measuring current and/or voltage behavior patterns from a PEM-probe communicating with the reformate feed stream. Pattern recognition software may be used to compare the current and voltage patterns from the PEM-probe to current and voltage telltale outputs determined from a reference cell similar to the PEM-probe and operated under controlled conditions over a wide range of CO concentrations in the H.sub.2 fuel stream. The PEM-probe is intermittently purged of any CO build-up on the anode catalyst (e.g., by (1) flushing the anode with air, (2) short circuiting the PEM-probe, or (3) reverse biasing the PEM-probe) to keep the PEM-probe at peak performance levels.