gebhart/patrepeval huggingface dataset:
Sweet corrosion inhibition on carbon steel using waste activated sludge extract (2019)

Extracellular polymeric substances (EPS) was extracted from waste activated sludge (WAS) and tested as a green corrosion inhibitor on carbon steel in 3.64% NaCl saturated with CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> at 25°C using the potentiodynamic polarization scan technique. The inhibition performance was 78.9% with 1000 ppm of inhibitor applied. The corrosion inhibitor preparation was done by heating the WAS followed by freeze-thaw process for five times. The extracted EPS was scanned with FTIR and it was assumed that the major functional groups, O-H, N-H, C-N, C=O, and C-H groups, were adsorbed on the metal surface, forming biofilm to slow down corrosion.
Broadband Liner Optimization for the Source Diagnostic Test Fan (2012)

The broadband component of fan noise has grown in relevance with the utilization of increased bypass ratio and advanced fan designs. Thus, while the attenuation of fan tones remains paramount, the ability to simultaneously reduce broadband fan noise levels has become more appealing. This paper describes a broadband acoustic liner optimization study for the scale model Source Diagnostic Test fan. Specifically, in-duct attenuation predictions with a statistical fan source model are used to obtain optimum impedance spectra over a number of flow conditions for three liner locations in the bypass duct. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners aimed at producing impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increased weighting to specific frequencies and/or operating conditions. Typical tonal liner designs targeting single frequencies at one operating condition are first produced to provide baseline performance information. These are followed by multiple broadband design approaches culminating in a broadband liner targeting the full range of frequencies and operating conditions. The broadband liner is found to satisfy the optimum impedance objectives much better than the tonal liner designs. In addition, the broadband liner is found to provide better attenuation than the tonal designs over the full range of frequencies and operating conditions considered. Thus, the current study successfully establishes a process for the initial design and evaluation of novel broadband liner concepts for complex engine configurations.
Interleukin-35 subunit dimerization and stability is unique among IL-12 cytokine family members (134.9) (2010)

Abstract IL-35 is a newly discovered cytokine that contributes to the suppressive capacity of regulatory T cells. IL-35 is a heterodimer consisting of an α chain (p35) and a β chain (Ebi3). It is a member of the IL-12 cytokine family, which is characterized by the sharing of three α (p19, p28, p35) and two β (p40 and Ebi3) subunits, and also includes IL-12 (p35/p40), IL-23 (p19/p40) and IL-27 (p28/Ebi3). In this study, relative pairing and secretion efficiencies and the dimerization interfaces of IL-12 family members were characterized, with emphasis on IL-35. Specific p35 residues that are known to contribute to formation of the IL-12 interface were assessed for their contribution to the IL-35 interface in mutagenesis studies. Similarly, several candidate Ebi3 residues were screened for their contribution to both IL-27 and IL-35 interfaces. Several residues were identified as critical to the IL-12 or IL-27 interfaces. Conversely, no single mutation was identified that completely disrupts p35/Ebi3 pairing, indicating that p35 and Ebi3 may pair differently to form IL-35. Preliminary data also indicate that IL-35 is poorly secreted by transfected cells, compared to IL-12 and IL-27, suggesting IL-35 formation is unfavorable or the secreted protein in unstable. Thus IL-35 appears to be different from other IL-12 family members in terms of both dimerization interface and stability. This work is supported by grants from the NIH and ALSAC.
Audio-visual graphical models for speech processing (2004)

Perceiving sounds in a noisy environment is a challenging problem. Visual lip-reading can provide relevant information but is also challenging because lips are moving and a tracker must deal with a variety of conditions. Typically audio-visual systems have been assembled from individually engineered modules. We propose to fuse audio and video in a probabilistic generative model that implements cross-model self-supervised learning, enabling adaptation to audio-visual data. The video model features a Gaussian mixture model embedded in a linear subspace of a sprite which translates in the video. The system can learn to detect and enhance speech in noise given only a short (30 second) sequence of audio-visual data. We show some results for speech detection and enhancement, and discuss extensions to the model that are under investigation.
<title>Technique for image data hiding and reconstruction without host image</title> (1999)

A new technique for embedding image data that can be recovered in the absence of the original host image, is presented. The data to be embedded, referred to as the signature data, is inserted into the host image in the DCT domain. The signature DCT coefficients are encoded using a lattice coding scheme before embedding. Each block of host DCT coefficients is first checked for its texture content and the signatured codes are appropriately inserted depending on a local texture measure. Experimental results indicate that high quality embedding is possible, with no visible distortions. Signature images can be recovered even when the embedded data is subject to significant lossy JPEG compression.
Dynamic Load Modeling of an HVAC Chiller for Demand Response Applications (2010)

A new dynamic electrical load model for an HVAC chiller for use in demand response applications is presented. The coupling of a building's electrical and thermal characteristics is not adequately captured using existing static models. Therefore a dynamic model is proposed. This allows for more accurate planning of the dispatching of load for demand side response. The model in this paper is derived from tests performed on an actual HVAC system at Drexel University.
Joint base station association and power control for uplink cognitive small cell network (2016)

In this paper, we propose a framework to jointly optimize user association and power control for the uplink cognitive small cell network (CSN). In the considered CSN, small cell base stations (SBSs) are deployed to serve a set of small cell user equipments (SUEs) by sharing the same licensed spectrum with a macrocell base station. The problem of joint user association and power allocation is formulated as an optimization problem, in which the goal is to maximize the overall uplink throughput while guaranteeing the SINR requirements of the served SUEs and MBS protection. To solve this problem, a distributed framework based on dual decomposition is proposed to find sub-optimal solution of the user association and transmit power in distributed manner. Moreover, distributed frameworks to achieve suboptimal solutions with low-computation complexity are also proposed. Simulation results show that the proposed approaches obtain suboptimal solutions with a small number of iterations.
Disk Mirroring with Alternating Deferred Updates (1993)

Mirroring is often used to enhance the reliability of disk systems, but it is usually considered expensive because it duplicates storage cost and increases the cost of writes. Transaction processing applications are often disk arm bound. We show that for such applications mirroring can be used to increase the efficiency of data accesses. The extra disk arms pay for themselves by providing extra bandwidth to the data, so that the cost of the overall system compares favorably with the cost of non-redundant disks. The basic idea is to have the mirrored disks out of phase with one handling reads and the other applying a batch of writes. We also present an effi-cient recovery procedure that allows reconstruction of a failed disk while guaranteeing the same level of read performance as during normal operation. 1
Photomechanical Deformation of Azobenzene-Functionalized Polyimides Synthesized with Bulky Substituents (2017)

Photomechanical effects realized in azobenzene-functionalized polyimides have shown large deformation and an exceptional increase in photogenerated force output. Here, we synthesize and characterize the photomechanical output of a series of linear polyimide materials prepared with a bulky substituent, incorporated via the development of a new bis(azobenzene-diamine) monomer containing a 9,9-diphenylfluorene cardo structure (azoCBODA). All six azoCBODA-containing polyimides are amorphous and exhibit high glass transition temperatures (<i>T</i><sub>g</sub>) ranging from 298 to 358 °C, storage moduli ranging from 2.27 to 3.81 GPa (at 30 °C), and good thermal stability. The magnitude of the photoinduced mechanical response of the azobenzene-functionalized polyimide is correlated to the rotational freedom of the polyimide chains (resulting in extensive segmental mobility) and fractional free volume (FFV > 0.1).
A simple framework for contrastive learning of visual representations (2024)

This paper presents SimCLR: a simple framework for contrastive learning of
visual representations. We simplify recently proposed contrastive
self-supervised learning algorithms without requiring specialized architectures
or a memory bank. In order to understand what enables the contrastive
prediction tasks to learn useful representations, we systematically study the
major components of our framework. We show that (1) composition of data
augmentations plays a critical role in defining effective predictive tasks, (2)
introducing a learnable nonlinear transformation between the representation and
the contrastive loss substantially improves the quality of the learned
representations, and (3) contrastive learning benefits from larger batch sizes
and more training steps compared to supervised learning. By combining these
findings, we are able to considerably outperform previous methods for
self-supervised and semi-supervised learning on ImageNet. A linear classifier
trained on self-supervised representations learned by SimCLR achieves 76.5%
top-1 accuracy, which is a 7% relative improvement over previous
state-of-the-art, matching the performance of a supervised ResNet-50. When
fine-tuned on only 1% of the labels, we achieve 85.8% top-5 accuracy,
outperforming AlexNet with 100X fewer labels.
Functional Human Corneal Equivalents Constructed from Cell Lines (1999)

Human corneal equivalents comprising the three main layers of the cornea (epithelium, stroma, and endothelium) were constructed. Each cellular layer was fabricated from immortalized human corneal cells that were screened for use on the basis of morphological, biochemical, and electrophysiological similarity to their natural counterparts. The resulting corneal equivalents mimicked human corneas in key physical and physiological functions, including morphology, biochemical marker expression, transparency, ion and fluid transport, and gene expression. Morphological and functional equivalents to human corneas that can be produced in vitro have immediate applications in toxicity and drug efficacy testing, and form the basis for future development of implantable tissues.
Performance Evaluation of a Prototype Variable Rate Sprayer for Spot - Specific Application of Bravo® Fungicide in Wild Blueberry (2011)

Wild blueberry yields are highly dependent on fungicides to control floral blight (monilinia and botrytis) and leaf diseases (septoria and rust). Growers apply fungicides uniformly without considering the significant bare spots (30-50% of the total field area). The repeated and excessive use of agrochemicals in bare spots has resulted in an increased cost of production. The over use of the fungicides is harmful to the environment and can contaminate surface and ground water. The proper targeting of fungicide on only foliage has the potential to save a substantial amount of chemical. Therefore, a significant need of an affordable variable rate sprayer for spot application of fungicide is needed for wild blueberry production. The objective of this study was to determine the performance of a prototype variable rate sprayer for spot application of Bravo fungicide in wild blueberry fields. The 6.1 meter VR sprayer was mounted on a all-terrain vehicle. Color cameras were used to detect bare soil areas in wild blueberry fields. Eighteen 6.1 meter wide test plots were selected in a wild blueberry field and the bare soil areas were mapped using RTK-DGPS. Three application rates (uniform, variable and control) were selected at random for each plot. Digital color images were taken at 6 randomly selected locations in each of the 18 plots. Each image was analyzed to calculate green ratio for determining effect of Bravo on wild blueberries. The application tracks were statistically compared with reference to the control tracks. Water sensitive paper was also placed in randomly selected locations for analysis purposes. The results can be used to determine the performance of applying fungicide on site-specific bases using a variable rate sprayer.
Cloning of Mannose 6-phosphate Reductase from Celery. (1995)

In celery, photosynthetic carbon partitioning between mannitol and sucrose is highly dependent on developmental (leaf age) and environmental (salt stress) factors. Mannose 6-phosphate reductase (M6PR) mediates a key step in mannitol biosynthesis and may regulate partitioning between sucrose and mannitol. We have constructed a cDNA library and have isolated M6PR-specific clones. Before library construction, poly(A) + RNA, extracted from newly fully expanded leaves, was translated in vitro. A single polypeptide (35.1 kD), immunoprecipitated with M6PR-specific antisera, accounted for ≈5% of the total 35 S incorporated into TCA-precipitated products. Parity between the molecular masses of the immunoprecipitated product and authentic M6PR indicated minimal posttranslational modification. The unidirectional primary library, constructed in UniZap XR vector (Stratagene), consisted of 1.53 million plaque forming-units (pfus) of which <0.4% were nonrecombinant, as estimated by “blue/white”' screening. After a single amplification, ≈0.14% of the 200,000 pfus screened with M6PR-specific antisera were identified as putative M6PR clones. Following two further rounds of screening and in vivo excision of the pBluescript phagemids their identity as full length M6PR clones was confirmed as follows: 1) IPTG-induced expression of M6PR activity in crude extracts; 2) IPTG-induced expression of a polypeptide that specifically interacted with M6PR antisera and with identical mobility (on SDS gels) to authentic M6PR; 3) 100% sequence homology to an internal peptide from a tryptic digest of purified M6PR. Based on these criteria, we conclude that we successfully cloned M6PR. The sequence is similar to several reductases from both plants and animals including an aldose 6-phosphate reductase from apple. Supported by USDA-NRI grant 940-1439.
An Innovative Device for Passive Control of Surge in Industrial Compression Systems (2000)

The present paper reports a numerical–experimental study on the dynamic behavior of a compression system based on a multistage centrifugal blower and fitted with an innovative device for the dynamic suppression of surge instability. The control device is of passive type and is based on the aeroelastic coupling of the basic compression system with a hydraulic oscillator. The controlled system is modeled at first by using a nonlinear lumped parameter approach. The simulated system dynamics within a wide range of operating conditions allows a parametric analysis to be performed and the optimal values of the control parameters to be singled out. Such optimal values are then used to design the hydraulic oscillator, which results in a technically feasible and very simple configuration. Finally, experimental tests are carried out on the compression plant with and without the passive control device, which demonstrate the effectiveness of the proposed control system in suppressing surge instabilities, at least within the limits predicted by the numerical simulation.
Application of IAPAC Fuel Injection for Low Emissions Small Two-Stroke Engines (1995)

<div class="htmlview paragraph">The implementation of the IFP developed Compressed Air Assisted Fuel Injection Process (named IAPAC) in a two-stroke engine allows the introduction of the fuel separately from the scavenging air, which in consequence minimizes fuel short-circuiting. The inherent mechanical principle of the IAPAC process which uses the crankcase compressed air to finely atomize the fuel, provides the advantages of direct injection but in addition uses conventional low pressure automotive type injection technology with commercially available gasoline injectors.</div> <div class="htmlview paragraph">In earlier work we showed an example of the application of this fuel injection technology to a PIAGGIO single cylinder 125 cc scooter two-stroke engine.</div> <div class="htmlview paragraph">In this paper, an update of the results obtained with this new engine is presented and confirms the ultra-low emissions capability for two-wheeler application. This technology is also used with other IAPAC 2-stroke engines of various size and displacement to demonstrate how the application of IAPAC to marine outboard 2-stroke engines, is a good answer face to the new environmental regulations.</div> <div class="htmlview paragraph">The EPA 2006 regulation can easily be met over the whole outboard engine power range with associated significant fuel economy benefits. The Bodensee stage 1 regulation can be met without catalyst, while the addition of a catalyst (at least for the medium to the high engine power range) will be necessary to meet the Bodensee stage 2 regulation.</div> <div class="htmlview paragraph">It has already been reported in the previous work how careful attention has been paid to ensure that the IAPAC system remains mechanically simple and keep the additional cost as low as possible.</div> <div class="htmlview paragraph">Finally, a brief cost impact analysis of a conversion of conventional 2-stroke engine to IAPAC is here presented. The ways of possible further cost reduction are also discussed.</div>
High throughput data redundancy removal algorithm with scalable performance (2011)

The ever growing need to process and analyze massive amounts of data from diverse sources such as telecom call data records, telescope imagery, web pages, stock markets, medical records and other domains has triggered worldwide research in data intensive computing. A key requirement here involves removing redundancy from data, as this enhances the compute efficiency for downstream data processing. These application domains have an intense need for high throughput data deduplication for huge volumes of data flowing at the rate of 1 GB/s or more. In this paper, we present the design of a novel parallel data redundancy removal algorithm. We also present a queueing theoretic analysis to optimize the throughput of our parallel algorithm on multi-core architectures. For 500M records, our parallel algorithm can perform complete deduplication in 255s, on 16 core Intel Xeon 5570 architecture. This gives a throughput of around 2M records/s. For 2048 byte records, we achieve a throughput of 0.81 GB/s. To the best of our knowledge, this is the highest throughput for data redundancy removal on such massive datasets. We also demonstrate strong and weak scalability of our algorithm for both multi-core Power6 and Intel Xeon 5570 architectures.
Semi-Supervised Learning with Conditional Harmonic Mixing (2006)

Recently graph-based algorithms, in which nodes represent data points and links encode similarities, have become popular for semi-supervised learning. In this chapter we introduce a general probabilistic formulation called `Conditional Harmonic Mixing’, in which the links are directed, a conditional probability matrix is associated with each link, and where the numbers of classes can vary from node to node. The posterior class probability at each node is updated by minimizing the KL divergence between its distribution and that predicted by its neighbours. We show that for arbitrary graphs, as long as each unlabeled point is reachable from at least one training point, a solution always exists, is unique, and can be found by solving a sparse linear system iteratively. This result holds even if the graph contains loops, or if the conditional probability matrices are not consistent. We show how, given a classifier for a task, CHM can learn its transition probabilities. Using the Reuters database, we show that CHM improves the accuracy of the best available classifier, for small training set sizes.
Technique for Reverse Total Shoulder Arthroplasty for Primary Glenohumeral Osteoarthritis with a Biconcave Glenoid (2013)

We presented our results of this procedure in twenty-seven shoulders in twenty-seven patients with a mean duration of follow-up of fifty-four months (range, twenty-four to 139 months).IndicationsContraindicationsPitfalls & Challenges.
Using Word Embedding to Enable Semantic Queries in Relational Databases (2017)

We investigate opportunities for exploiting Artificial Intelligence (AI) techniques for enhancing capabilities of relational databases. In particular, we explore applications of Natural Language Processing (NLP) techniques to endow relational databases with capabilities that were very hard to realize in practice. We apply an unsupervised neural-network based NLP idea, Distributed Representation via Word Embedding, to extract latent information from a relational table. The word embedding model is based on meaningful textual view of a relational database and captures inter-/intra-attribute relationships between database tokens. For each database token, the model includes a vector that encodes these contextual semantic relationships. These vectors enable processing a new class of SQL-based business intelligence queries called cognitive intelligence (CI) queries that use the generated vectors to analyze contextual semantic relationships between database tokens. The cognitive capabilities enable complex queries such as semantic matching, reasoning queries such as analogies, predictive queries using entities not present in a database, and using knowledge from external sources.
Waveguide Bends for Suppressed Mode Coupling (2019)

Waveguide bends are key components of photonic integrated circuits, enabling complex layouts and high packing densities. Often waveguides at bends are wide and consequently multi-mode for lower loss propagation. Higher order modes, which are excited by the bend curvature, may degrade performance for devices downstream, such as extinction ratio in modulators. It is demonstrated that bend curvature functions inspired by window functions used in digital signal processing can greatly suppress the undesirable generation of higher order modes. The proposed curvature functions include sine to the power of n, and Dolph-Chebyshev window. Coupled mode theory provides the insight that the suppression of higher order modes in a bend is related to the side-lobe suppression of the bend curvature Fourier transform. A particular application for the proposed bend geometries is mode division multiplexing, where inter-mode crosstalk may be significantly reduced.