gebhart/patrepeval huggingface dataset:
From waste to energy -- Catalytic steam gasification of broiler litter (1999)

In 1996, the production of broiler chickens in the US was approximately 7.60 billion head. The quantity of litter generated is enormous. In 1992, the Southeast region alone produced over five million tons of broiler litter. The litter removed from the broiler houses is rich in nutrients and often spread over land as a fertilizer. Without careful management, the associated agricultural runoff can cause severe environmental damage. With increasing broiler litter production, the implementation of alternative disposal technologies is essential to the sustainable development of the poultry industry. A process originally developed for the conversion of coals to clean gaseous fuel may provide an answer. Catalytic steam gasification utilities an alkali salt catalyst and steam to convert a carbonaceous feedstock to a gas mixture composed primarily of carbon monoxide, carbon dioxide, hydrogen, and methane. The low to medium energy content gas produced may be utilized as an energy source or chemical feedstock. Broiler litter is an attractive candidate for catalytic steam gasification due to its high potassium content. Experiments conducted in UTSI's bench-scale high-pressure fixed bed gasifier have provided data for technical and economic feasibility studies of the process. Experiments have also been performed to examine the effects of temperature,more » pressure, and additional catalysts on the gasification rate.« less
Explorations of Inmate and Volunteer Choral Experiences in a Prison-based Choir (2007)

The purpose of this investigation was to explore participants' (N=44) experiences in a joint inmate-community volunteer choir at a minimum security prison. Initial survey data provided a demographic profile of both inmate (n=20) and volunteer (n=24) participants, and indicated significant agreement that their participation afforded: (a) means to a peak experience with momentary disappearance of stresses and (b) a sense of accomplishment. Among significant variations between participant responses: (a) inmates perceived more improvement in intrapersonal skills than volunteers and (b) volunteers reported more success in identifying out of tune singing than inmates. Subsequent qualitative data included interviews, field notes, and material culture. A grounded theory, formulated from emergent themes in conversation with relevant literature, suggested that choral music education experiences, approached more comprehensively than simply promoting interaction between individual singers and a musical score, may carry potential for transformative personal and interpersonal change in prison choir contexts.
Dressed-state control of effective dipolar interaction between strongly-coupled solid-state spins (2022)

Strong interactions between spins in many-body solid-state quantum system is a crucial resource for exploring and applying non-classical states. In particular, electronic spins associated with defects in diamond system are a leading platform for the study of collective quantum phenomena and for quantum technology applications. While such solid-state quantum defect systems have the advantage of scalability and operation under ambient conditions, they face the key challenge of controlling interactions between the defects spins, since the defects are spatially fixed inside the host lattice with relative positions that cannot be well controlled during fabrication. In this work, we present a dressed-state approach to control the effective dipolar coupling between solid-state spins; and then demonstrate this scheme experimentally using two strongly-coupled nitrogen vacancy (NV) centers in diamond. Including Rabi driving terms between the m$_s$ = 0 and $\pm$1 states in the NV spin Hamiltonian allows us to turn on and off or tune the effective dipolar coupling between two NV spins. Through Ramsey spectroscopy, we detect the change of the effective dipolar field generated by the control NV spin prepared in different dressed states. To observe the change of interaction dynamics, we then deploy spin-lock-based polarization transfer measurements via a Hartmann-Hahn matching condition between two NV spins in different dressed states. We perform simulations that indicate the promise for this robust scheme to control the distribution of interaction strengths in strongly-interacting spin systems, including interaction strength homogenization in a spin ensemble, which can be a valuable tool for studying non-equilibrium quantum phases and generating high fidelity multi-spin correlated states for quantum-enhanced sensing.
Photoacoustic Tomography for Imaging Nanoparticles (2010)

Nanotechnology is the key to a new, noninvasive photoacoustic imaging technique that could detect early stages of disease tissues. The combination of photoacoustic imaging with nanotechnology holds promise for determining the structural and functional properties of tissues with enhanced sensitivity and specificity and for monitoring the treatment of diseases. In this chapter, we described in detail photoacoustic reconstruction methods and imaging systems. We also review the recent advances in nanoparticles and their in vivo applications in the field of photoacoustic imaging.
Immunolocalization of different forms of neural cell adhesion molecule (NCAM) in rat taste buds (1993)

Taste buds consist of approximately 100 taste cells, including three morphological types of short receptor cells which synapse on the peripheral gustatory nerves. Some of the receptor cells produce neural cell adhesion molecule (NCAM), which may play a role in formation of specific connections in this system. Antibodies directed against different forms of NCAM were utilized in an attempt to define not only the distribution, but also the type of NCAM within taste buds. Within each taste bud approximately 10% of the taste cells exhibit abundant immunoreactivity for 180 kD (ld) or 140 kD (sd) forms of NCAM (i.e., those with an intracellular domain) along virtually the entire surface of the cell. Ultrastructural analysis reveals that these abundantly immunoreactive taste cells are of the intermediate morphological type, although not all of the intermediate taste cells within any bud are immunoreactive. In addition, the ultrastructural studies show that punctate (ld/sd) NCAM-immunoreactivity occurs on the membranes of taste cells and nerve fibers throughout each taste bud. The embryonic form of NCAM (E-NCAM), rich in polysialic acid residues, is present only in association with nerve fibers and other unidentified elongate, thin profiles of a few taste buds. The nerve plexus beneath the gustatory epithelium is also rich in NCAM-immunoreactivity. These fibers occasionally reveal immunoreactivity indicative of only the 120 kD (ssd) form of NCAM, typical of glial cells.
Class of algebraically constructed permutationsfor use in pseudorandom interleavers (1994)

The author shows that Lempel-Costas (LC) arrays when treated as permutations possess ideal properties for use in pseudorandom interleavers. The basic theory of interleavers is reviewed and the necessary conditions imposed on permutations for successful operation of pseudorandom interleavers are given. Proof that LC arrays satisfy the conditions, and a comparison with randomly constructed permutations are given; it is shown that LC permutations perform better than randomly generated permutations.
Theoretical and experimental studies on vortex chamber flows (1986)

Analytical and experimental studies to investigate selected fluid parameters in vortex chambers are presented. From the analytical model, the dimensionless quantities of the core size, static pressure drop across the chamber, and radial static pressure distribution are shown to be functions of the chamber geometry only. Experimental results confirm all of the findings.
Co-Integration Models for Koyna and Warna Reservoirs, India (2015)

Koyna region, a seismically active region, has many time series observations such as seismicity, reservoir water levels, and many bore well water levels. One of these series is used to predict others since these parameters are interlinked. If these series were stationary, we used correlation analysis. However, it is seen that maximum of these time series are nonstationary. In this case, co-integration method is used that is extracted from econometrics and forecast is possible. We have applied this methodology to study time series of reservoir water levels of this region and we find them to be co-integrated. Therefore, forecast of water levels for one of the reservoir is done from the other as these will never drift apart too much. The outcomes demonstrate that a joint modelling of both data sets based on underlying physics resolves to be sparingly useful for understanding predictability issues in reservoir induced seismicity.
An All-Atom Theory of Electron Transfer at Nanocrystal/Molecule Interfaces: A Hybrid LCAO/DFT Approach (2021)

Interfacial electron transfer (IET) probabilities and rates between CdSe and CdS nanocrystals of diameters 2, 4, and 6 nm, and an anthraquinone dimer (AQ₂H⁺), have been studied. To account for electronic configuration mixing, the previously reported all-atom hybrid BA-LCAO/DFT approach to QD/acceptor systems has been extended to include: (a) electron/hole interaction, and (b) exciton–exciton coupling. To carry out these calculations, at first, we generated a one-particle orbital basis of the QDs at the all-atom BA-LCAO level of theory, and orbitals of AQ₂H⁺ at a conventional DFT level. We then applied an exciton interaction theory for treating initial and final states of the quantum dot (“QD” = QD*/AQ₂H⁺) and charge separated (“CS” = QD⁺/AQ₂H) systems, and for evaluating the state-to-state coupling elements. These calculations revealed that (i) singlet–triplet splitting is significant in the QD systems, while practically negligible in the CS systems; (ii) quantum confinement effects are responsible for weak exciton correlation in the small QD and CS systems and much stronger exciton correlation in the larger ones; (iii) IET in all charge separation processes occurs via excitons close to the band edges, and (iv) charge recombination (“CR” = QD/AQ₂H⁺) in the smaller quantum dots proceeds via low energy holes, while a strong involvement of deep VB orbitals (hot holes) was observed in the 6 nm quantum dots. Furthermore, the quantum coupling strength in both CS and CR processes exhibits an exponential decrease with the size of the nanocrystal, as dictated by the corresponding decay of charge density on the surface of these QDs. At the present level of modeling, we find that quantum coupling is stronger in the QD(CdS)/AQ₂H⁺ than in the QD(CdSe)/AQ₂H⁺ dyads.
The crystal structure of apo‐pseudoazurin from Alcaligenes faecalis S‐6 (1995)

The 3D structure of the apo-pseudoazurin (copper free pseudoazurin) from Alcaligenes faecalis strain S-6 is determined and refined at pH 6.7 using X-ray diffraction data to 1.85 A resolution. The final crystallographic R-factor is 0.164. Comparing the structures of apo-pseudoazurin and the native (Cu2+) protein, we observed limited differences ranging between 0.1-0.4 A at the vicinity of the copper site, at the loops connecting the secondary structural elements, at certain beta-strands and at the amino and carboxy termini of the protein.
Forecasting and Evaluating Water Quality of Chao Lake based on an Improved Decision Tree Method (2010)

As the water quality of Chao Lake becomes diverse and eutrophied, predicting and evaluating water quality become more and more important. But prediction and evaluation are complex problems. In this paper, we come up with an improved decision tree learning method making water quality prediction easier and forecast more accurate. The classification standards are based on the evaluation mechanisms provided by the Hong Kong Environment Protection Department. We released an online web forecast system to apply to the classification and prediction of Chao Lake. Experimental results show that the improved method is better than artificial neural network or genetic algorithm with higher recognition rate and forecast accuracy and strong practical value.
Construction of killer industrial yeast Saccharomyces cerevisiae HAU-1 and its fermentation performance (2010)

Saccharomyces cerevisiae HAU-1, a time tested industrial yeast possesses most of the desirable fermentation characteristics like fast growth and fermentation rate, osmotolerance, high ethanol tolerance, ability to ferment molasses, and to ferment at elevated temperatures etc. However, this yeast was found to be sensitive against the killer strains of Saccharomyces cerevisiae. In the present study, killer trait was introduced into Saccharomyces cerevisiae HAU-1 by protoplast fusion with Saccharomyces cerevisiae MTCC 475, a killer strain. The resultant fusants were characterized for desirable fermentation characteristics. All the technologically important characteristics of distillery yeast Saccharomyces cerevisiae HAU-1 were retained in the fusants, and in addition the killer trait was also introduced into them. Further, the killer activity was found to be stably maintained during hostile conditions of ethanol fermentations in dextrose or molasses, and even during biomass recycling.
Mammogram synthesis using a 3D simulation. I. Breast tissue model and image acquisition simulation (2002)

A method is proposed for generating synthetic mammograms based upon simulations of breast tissue and the mammographic imaging process. A computer breast model has been designed with a realistic distribution of large and medium scale tissue structures. Parameters controlling the size and placement of simulated structures (adipose compartments and ducts) provide a method for consistently modeling images of the same simulated breast with modified position or acquisition parameters. The mammographic imaging process is simulated using a compression model and a model of the x-ray image acquisition process. The compression model estimates breast deformation using tissue elasticity parameters found in the literature and clinical force values. The synthetic mammograms were generated by a mammogram acquisition model using a monoenergetic parallel beam approximation applied to the synthetically compressed breast phantom.
Study of Energetic Nitramine Extruded Double-Base Propellants (1998)

This paper gives the results of an experimental study on nitramine extruded double-base (EDB)fonnulationscontaining up to 25 percent RDXin low and high calorimetric value double-base(DB)propellants. The effect of ballistic modifiers on the burn rate and pressure exponent ( 11) of promisingfonnulations has also been investigated. The data generated on various parameters reveal that ( i)nitraniine EDB propellants exhibit relatively superior thennal stability,' (ii) tensile strength andpercentage elongation are drastically altered if RDX concentration exceeds 15 per cent, (iii) 11 islowered significantly in the presence of ballistic modifiers, (iv) characteristic velocity (C*) values arehigher to that for the control tonnulation, and ( v) temperature sensitivity of burn rate is on the lowerside (0,20 -0.25 % / °C as against 0.40 % / °C) in the presence of ballistic modifiers.
Zeolites: Their Nucleation and Growth (1989)

Zeolite synthesis proceeds via nucleation, which is a consequence of local fluctuations, small in extent but considerable in degree of departure from the mean for the solution, followed by spontaneous growth of nuclei exceeding a critical size. A physico-chemical basis for the critical size requirement has been described. There is evidence that chemical events rather than diffusion can govern subsequent linear growth of zeolite crystals. To succeed in synthesis it is essential during growth to stabilise the open structure by inclusion of quest molecules. This requirement has a thermodynamic origin which has been developed and applied to formation of zeolites, porosils and AlPO's. The explanation of some experimentally observed features of zeolite synthesis follows from the treatment. A distinction is made between zeolitic stabilisers and nucleation templates.
Targeting the undruggable: emerging technologies in antibody delivery against intracellular targets (2020)

Despite significant advances in protein delivery technologies, reports of highly efficient transport vehicles are sparse when systemically applied <i>in vivo</i>. Consequently, more detailed mechanistic studies are needed to identify and optimize the molecular 'Achilles heel' of individual methodologies. Ultimately, to target intracellular proteins that have been undruggable in the past, a combination of strategies may be required.
Modified inelastic bouncing ball model of the segregation of binary granular mixture: Numerical simulation (2019)

In a vertically vibrated binary granular mixture, the larger grains rise to top (Brazil Nut Effect, BNE), sink to bottom (Reverse BNE), or remain mixed depending on the grain properties and vibration parameter. Previously, we introduced a model considering the mixture components as two non-interacting inelastic bouncing balls. In particular, segregation is determined from the times-of-flight of the balls, which in turn, depend on the intrinsic properties of the grains represented by transmissibility, Tᵣ, and on the vibration’s dimensionless acceleration Γ. Here, we simulated and tracked the times-of-flight τ of two bouncing balls of different Tᵣ. We determined the segregation phases from the probability-weighted difference ω〈 δ t 〉 between branches of the bifurcation diagrams (dimensionless τ versus Γ). The segregation phases, represented by the segregation phase diagram (ω〈 δ t 〉 versus Γ and Tᵣ) replicated our previous results.
[Dentobasal correction of mandible with a bilateral bisagittal split]. (1989)

The combination of conventional sagittal splitting [Obwegeser 1955] with a sagittal osteotomy of the mandibular basal bone placed mesial to the mental foramen, which is made possible after the separation of the anterior dentoalveolar segment, enables a correction in the transverse, sagittal and vertical planes of the basal and dentoalveolar segments of the mandible.
Coverage Control on the Special Euclidean Groups* (2023)

In this paper, we investigate a coverage strategy for a multi-robot system across a domain of interest for applications involving pose-sensitive event services. The resulting problem is modeled as a coverage control problem on the special Euclidean groups. Based on the geometry inherent to the unimodular Lie groups, the geodesic-based Voronoi cell of a robot in charge of a subdomain and the locational cost function representing the coverage quality are defined. The controller for driving a team of planar robots to a critical point of the locational cost is derived and augmented by a control barrier certificate for the purpose of collision avoidance. The performance of the proposed controller is compared with the situation where the orientations of the robots are ignored during the coverage process using the standard Lloyd’s algorithm for both homogeneous and heterogeneous (in terms of robots’ relative mobility and safe radii) multi-robot teams.
Comparative evaluation of measles virus‐specific RT‐PCR methods through an international collaborative study (2003)

Comparison of RT-PCR assays established in house at various places revealed that laboratories could differ in sensitivity by as much as 1,000-fold in terms of the ability to detect measles virus sequences in clinical samples. The study indicates that PCR findings, positive or negative, are questionable if they are not supported by the associated data demonstrating the overall sensitivity of the assay applied. Measles virus-specific RT-PCR-based assays need to be validated using standard virus preparation or nucleic acid-based target templates. A correlation between real-time quantitative PCR and the conventional PCR for measles virus is highly desirable.
On linear coherent estimation with spatial collaboration (2012)

We consider a power-constrained sensor network, consisting of multiple sensor nodes and a fusion center (FC), that is deployed for the purpose of estimating a common random parameter of interest. In contrast to the distributed framework, the sensor nodes are allowed to update their individual observations by (linearly) combining observations from neighboring nodes. The updated observations are communicated to the FC using an analog amplify-and-forward modulation scheme and through a coherent multiple access channel. The optimal collaborative strategy is obtained by minimizing the cumulative transmission power subject to a maximum distortion constraint. For the distributed scenario (i.e., with no observation sharing), the solution reduces to the power-allocation problem considered by Xiao et. al.. Collaboration among neighbors significantly improves power efficiency of the network in the low local-SNR regime, as demonstrated through an insightful example and numerical simulations.
A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification (2018)

One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs) as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM) classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references.
Robust discourse parsing via discourse markers, topicality and position (2002)

This paper describes a simple discourse parsing and analysis algorithm that combines a formal underspecification utilising discourse grammar with Information Retrieval (IR) techniques. First, linguistic knowledge based on discourse markers is used to constrain a totally underspecified discourse representation. Then, the remaining underspecification is further specified by the computation of a topicality score for every discourse unit. This computation is done via the vector space model. Finally, the sentences in a prominent position (e.g. the first sentence of a paragraph) are given an adjusted topicality score. The proposed algorithm was evaluated by applying it to a text summarisation task. Results from a psycholinguistic experiment, indicating the most salient sentences for a given text as the ‘gold standard’, show that the algorithm performs better than commonly used machine learning and statistical approaches to summarisation.
Multi-feature machine learning model for automatic segmentation of green fractional vegetation cover for high-throughput field phenotyping (2017)

The method described is capable of coping with the environmental challenges faced in field conditions, with high levels of adaptiveness and without the need for adjusting a threshold for each digital image. The proposed method is also an ideal candidate to process a time series of phenotypic information throughout the crop growth acquired in the field. Moreover, the introduced method has an advantage that it is not limited to growth measurements only but can be applied on other applications such as identifying weeds, diseases, stress, etc.