gebhart/patrepeval huggingface dataset:
Financial Market Sentiment Prediction Technology and Application Based on Deep Learning Model (2022)

In the real world, there are a variety of situations that require strategy control, that is reinforcement learning, as a method for studying the decision-making and behavioral strategies of intelligence. It has received a lot of research and empirical evidence on its functions and roles and is also a method recognized by scholars. Among them, combining reinforcement learning with sentiment analysis is an important theoretical research direction, but so far there is still relatively little research work about it, and it still has the problems of poor application effect and low accuracy rate. Therefore, in this study, we use the features related to sentiment analysis and deep reinforcement learning and use various algorithms for optimization to deal with the above problems. In this study, a sentiment analysis method incorporating knowledge graphs is designed using the characteristics of the stock trading market. A deep reinforcement learning investment trading strategy algorithm for sentiment analysis combined with knowledge graphs from this study is used in the subsequent experiments. The deep reinforcement learning system combining sentiment analysis and knowledge graph implemented in this study not only analyzes the algorithm from the theoretical aspect but also simulates data from the stock exchange market for experimental comparison and analysis. The experimental results illustrate that the deep reinforcement learning algorithm combining sentiment analysis and knowledge graphs used in this study can achieve better gains than the existing traditional reinforcement learning algorithms and has better practical application value.
Simulation-Based Assessment of Workers’ Muscle Fatigue and Its Impact on Construction Operations (2016)

Construction workers are frequently exposed to excessive physical demands due to repetitive lifting and material handling while performing tasks. Consequently, many construction workers suffer from a significant level of muscle fatigue that may negatively impact a project’s performance. Thus, evaluating the level of muscle fatigue prior to work and implementing appropriate interventions to reduce physical demands will help to prevent adverse effects of workers’ fatigue on construction operations. Even though several research efforts have suggested methodologies to evaluate muscle fatigue, the extent to which workers’ muscle fatigue would affect construction performance has not yet been fully studied. To address this issue, a simulation-based framework is proposed to estimate physical demands and corresponding muscle fatigue, and thus to quantitatively evaluate the impact of muscle fatigue during construction operations. Specifically, physical demands from a planned operation modeled using discrete event simulation (DES) are estimated through biomechanical analyses. Then, the proposed dynamic fatigue models estimate the level of muscle fatigue of each worker as a function of the estimated physical demands. Workers’ strategies to mitigate muscle fatigue, such as taking voluntary rests, are, in turn, modeled in the DES to understand how muscle fatigue affects time and cost performance of the planned operation. As a proof of concept, a case study on masonry work was performed to demonstrate the usefulness of the proposed framework, describing the need for taking into account muscle fatigue for operational planning due to possible excessive physical demands. The results from the case study indicate that excessive physical demands beyond workers’ capabilities result in reduction of time and cost performance. The proposed framework helps to better understand workers’ response to physical demands by adding workers’ capabilities as changing variables into traditional DES approaches, enabling pro-active management of human resources. Ultimately, the framework, which combines conventional interests on optimized operations in terms of time and cost with those of ergonomics, provides opportunities to take into account both workers’ health and work performance in early design stages.
Metrics for Evaluation of Ontology-based Information Extraction (2006)

The evaluation of the quality of ontological classification is an important part of semantic web technology. Because this area is under constant development, it requires improvement and standardisation. This paper discusses existing evaluation metrics, and proposes a new method for evaluating the ontology population task, which is general enough to be used in a variety of situations, yet more precise than many current metrics. The paper further describes our first eorts in operationalising the evaluation procedure, including the creation of a semantically annotated corpus that will function as a test bed for the proposed evaluation mechanism, and comparison of dierent evaluation metrics. We conclude that for ontology-based evaluation, a more complex mechanism than is traditionally used is preferable. This mechanism aims to drive a benchmarking assessment tool for the current state-of-the-art of ontology population, and to set a standard for best practice for future evaluation of human language technology for the semantic web.
Doubled critical current density in Bi-2212 round wires by reduction of the residual bubble density (2011)

We have recently shown that the gas present in the only ~ 70% dense filaments of as-drawn Bi-2212 wire agglomerates into large bubbles that fill the entire filament diameter during the melt phase of the heat treatment. Once formed, these bubbles never disappear, although they can be bridged by 2212 grains formed on cooling. In order to test the effect of these bubbles on the critical current Ic, we increased the density of the filaments after drawing using 2 GPa of cold isostatic pressure, finding that the bubble density and size were greatly reduced and that Ic could be at least doubled. We conclude that enhancement of the filament packing density is of great importance for making major Ic improvements in this very useful, round superconducting wire.
Binding and disruption of phospholipid bilayers by supramolecular RNA complexes (2001)

In an RNA world, RNAs would have regulated traffic through normally impermeable bilayer membranes. Using selection-amplification we previously found RNAs that bind stably and increase the ionic conductance of phospholipid membranes at high Mg(2+) and Ca(2+) concentrations. Now selection in reduced divalents yields RNAs that bind phosphatidylcholine liposomes under conditions closer to physiological. Such affinity for phospholipid membranes requires interactions between RNAs. In fact, we detected no functional monomeric membrane-binding RNAs. A membrane-active end-to-end heterotrimer consisting of 2 RNA 9 and 1 RNA 10 is defined by nucleotide protection, oligonucleotide competition, and mutant analysis. Oligomers of the heterotrimer bind stably, cause release of liposome-encapsulated solutes, and disrupt model black membranes. Individual RNA molecules do not show any of these activities. This novel mechanism of RNA binding to lipid membranes may not only regulate membrane permeability, but suggests that arrays of catalytic or structural RNAs on membranes are plausible. Finally, a selection met only by RNA complexes evokes new possibilities for selection-amplification itself.
BMS: Secure Decentralized Reconfiguration for Blockchain and BFT Systems (2021)

Reconfiguration of long-lived blockchain and Byzantine fault-tolerant (BFT) systems poses fundamental security challenges. In case of state-of-the-art Proof-of-Stake (PoS) blockchains, stake reconfiguration enables so-called long-range attacks, which can lead to forks. Similarly, permissioned blockchain systems, typically based on BFT, reconfigure internally, which makes them susceptible to a similar "I still work here" attack. In this work, we propose BMS (Blockchain/BFT Membership Service) offering a secure and dynamic reconfiguration service for BFT and blockchain systems, preventing long-range and similar attacks. In particular: (1) we propose a root BMS for permissioned blockchains, implemented as an Ethereum smart contract and evaluate it reconfiguring the recently proposed Mir-BFT protocol, (2) we discuss how our BMS extends to PoS blockchains and how it can reduce PoS stake unbonding time from weeks/months to the order of minutes, and (3) we discuss possible extensions of BMS to hierarchical deployments as well as to multiple root BMSs.
A Multi-Tone Sound Absorber Based on an Array of Shunted Loudspeakers (2018)

It has been demonstrated that a single shunted loudspeaker can be used as an effective low frequency sound absorber in a duct, but many shunted loudspeakers have to be used in practice for noise reduction or reverberation control in rooms, thus it is necessary to understand the performance of an array of shunted loudspeakers. In this paper, a model for the parallel shunted loudspeaker array for multi-tone sound absorption is proposed based on a modal solution, and then the acoustic properties of a shunted loudspeaker array under normal incidence are investigated using both the modal solution and the finite element method. It was found that each shunted loudspeaker can work almost independently where each unit resonates. Based on the interaction analysis, multi-tone absorbers in low frequency can be achieved by designing multiple shunted loudspeakers with different shunt circuits respectively. The simulation and experimental results show that the normal incidence sound absorption coefficient of the designed absorber has four absorption peaks with values of 0.42, 0.58, 0.80, and 0.84 around 100 Hz, 200 Hz, 300 Hz, and 400 Hz respectively.
Symmetric line graph transforms for inter predictive video coding (2016)

In this paper, we study graph-based transforms for inter predictive video coding. We are motivated by the fact that symmetries in the transform basis are very beneficial for computational efficiency. Based on this, we describe the relationship between bisymmetric matrices and the butterfly structure in fast transform algorithms. We introduce a new class of transforms called Symmetric Line Graph Transforms (SLGTs), of which the discrete cosine transform (DCT) is one particular case. As is well known in the case of the DCT, the bisymmetry property allows us to reduce the number of multiplications by half. We show that, beyond the DCT, useful SLGTs can be defined that have efficient implementation. We propose a specific SLGT that is shown to outperform the DCT for classes of inter residual blocks. While the proposed SLGT approaches the performance of a Karhunen Loeve Transform (KLT) at certain distortion levels, it has lower computation cost.
Effects of the MC4R, CAPN1, and ADSL genes on body weight and purine content in slow-growing chickens (2019)

Consumer preference for slow-growing broiler chickens is rising because of increased demand for high-quality poultry products. Korat chicken (KRC) is a slow-growing chicken generated in Thailand. A goal of the KRC breeding program is to produce meat with a low purine content to benefit an aging population, without interfering with growth performance. Thus, this study aimed to investigate the effects of genes encoding melanocortin 4 receptor (MC4R), calpain 1 (CAPN1), and adenylosuccinate lyase (ADSL) on body weight, muscle fiber, and content of purine and its derivatives (i.e., adenine, guanine, hypoxanthine, and xanthine), to develop molecular markers for breeding programs. Genotypes of MC4R, CAPN1, and ADSL were obtained from 583 KRCs by PCR-single-strand conformation polymorphism. The body weight and purine contents of the KRCs were measured every 2 wk until the KRCs reached market weight at 10 wk of age. A significant association between the MC4R genotype and body weight at 2, 4, and 10 wk of age was detected. KRC possessing the BB genotype of CAPN1 showed significantly heavier body weight at 6 wk of age and guanine content at 4 wk of age, and a smaller muscle fiber diameter in the breast muscle at 10 wk of age, compared with those of the other genotypes. In addition, high expression levels of the CAPN1 and ADSL genes were detected in the breast muscle at 2 wk of age. Although higher purine contents were detected at a young age, no significant associations with the MC4R, CAPN1, and ADSL genes were detected. Our results indicate that MC4R and CAPN1 could be used as genetic markers for growth and meat quality in the slow-growing chicken breeding program.
Nucleus of the Solitary Tract (2019)

Functional Morphology and Chemical Neuroanatomy: Viscerosensory Processing in Nucleus Tractus Solitarii: Structural and Neurochemical Substrates (D.A. Ruggiero, V.M. Pickel, T.A. Milner, M. Anwar, K. Otake, E.P. Mtui, and D.H. Park). Central Projections of Baroreceptor and Chemoreceptor Afferent Fibers in the Rat (J. Ciriello, S.L. Hochstenbach, and S. Roder). Neurobiology of the Gustatory Zone of the Nucleus Tractus Solitarius (R.M. Bradley). Immunohistochemical Localization of Neurochemical Synaptic Circuits of the Nucleus Tractus Solitarii at the Light Microscopic and Ultrastructural Levels (B.E. Maley). Volume Transmission in Transmitter Peptide Costoring Neurons in the Medulla Oblongata (K. Fuxe, L.F. Agnati, R. Covenas, J.A. Narvaez, B. Bunneman, and B. Bjelke). Central Projections and Functional Neural Connections: Ascending Projections of the Solitary Tract Nucleus (G.J. Ter Horst and C. Streefland). Functional Connections of the Rostral Nucleus of the Solitary Tract in Viscerosensory Integration of Ingestion Reflexes (M.C. Whitehead). Projections from the NTS to the Ventrolateral Medulla: Role in Vasomotor Control (R.A.L. Dampney). Role of the NTS in the Medullary Respiratory Network Producing Respiratory Movements (A.L. Bianchi and L. GrTlot). Functional Neural Connections of the Area Postrema (A.V. Ferguson and V.L. Lowes). Synaptic Processing and Integrative Mechanisms in Intrinsic Neural Circuits: Modulation of NTS Function by Multiple Descending Inputs: An Overview (K.M. Spyer). Baroreceptor and Chemoreceptor Afferent Processing in the Solitary Tract Nucleus (R.B. Felder and S.W. Mifflin). Excitatory Amino Acid Receptors and Afferent Synaptic Transmission in the Nucleus Tractus Solitarius (M.C. Andresen and M. Yang). Serotonergic Mechanisms in Baroreceptor Afferent Processing and Cardiovascular Control by the NTS (R. Laguzzi). The Physiology of Adrenergic Systems in the Solitary Tract Nucleus )P.D. Feldman). Transmitter/Peptide Interactio ns in NTS Neuronal Circuits (J.Champagnat). Synaptic Modulation of Isolated Neurons of the Solitary Tract Nucleus (J.A. Drewe and D.L. Kunze). Neurotransmitters/Receptors in Mechanisms of Cardiorespiratory Control: Neuroactive Substances in the Control of Cardiovascular and Visceral Responses: An Overview (W. Talman). GABA-Mediated Neural Transmission in Mechanisms of Cardiovascular Control by the NTS (A.F. Sved). Serotonergic and Catecholaminergic Mechanisms for Baroreflex Regulation in the NTS (R.D. Bunag and H. Itoh). Transmitter/Receptor Mechanisms in Cardiovascular Control by the NTS: Excitatory Amino Acids, Acetylcholine and Substance P. (H.N. Sapru). Opioids and the Nucleus of the Tractus Solitarius: Effects on Cardiovascular and Baroreflex Function (F.J. Gordon). Tonic Influences on Baroreceptor Reflex Sensitivity by Endogenous Neurotension in the Nucleus Tractus Solitarii (J.Y.H. Chan and S.H.H. Chan). Role of Substance P and Dopamine in the Mediation and Modulation of Respiratory Response
Catalytic Mechanism for the Ruthenium-Complex-Catalyzed Synthesis of Amides from Alcohols and Amines: A DFT Study (2013)

Details of the reaction mechanism for the Ru–PNN pincer complex catalyzed amidation from an alcohol and an amine proposed by Milstein et al. was elucidated using M06 density functional theory calculations. In addition, the bifunctional double hydrogen transfer (BDHT) mechanism for the dehydrogenative oxidation step was investigated for comparison. Finally, the BDHT mechanism was found to be preferred over the β-H elimination pathway that was proposed by Milstein et al. On the basis of the analysis of NBO charges and orbital interactions of intermediates and transition states, we designed a new catalyst with the addition of an electron-donating substituent (−NEt2), which provided much reduced energy barriers and a lower potential energy surface along both mechanisms.
Strategic Co-Location in a Hybrid Process Involving Desalination and Pressure Retarded Osmosis (PRO) (2013)

This paper focuses on a Hybrid Process that uses feed salinity dilution and osmotic power recovery from Pressure Retarded Osmosis (PRO) to achieve higher overall water recovery. This reduces the energy consumption and capital costs of conventional seawater desalination and water reuse processes. The Hybrid Process increases the amount of water recovered from the current 66.7% for conventional seawater desalination and water reuse processes to a potential 80% through the use of reclaimed water brine as an impaired water source. A reduction of up to 23% in energy consumption is projected via the Hybrid Process. The attractiveness is amplified by potential capital cost savings ranging from 8.7%-20% compared to conventional designs of seawater desalination plants. A decision matrix in the form of a customizable scorecard is introduced for evaluating a Hybrid Process based on the importance of land space, capital costs, energy consumption and membrane fouling. This study provides a new perspective, looking at processes not as individual systems but as a whole utilizing strategic co-location to unlock the synergies available in the water-energy nexus for more sustainable desalination.
An overview of once‐weekly glucagon‐like peptide‐1 receptor agonists—available efficacy and safety data and perspectives for the future (2011)

Incretin-based therapies, such as the injectable glucagon-like peptide-1 (GLP-1) receptor agonists and orally administered dipeptidyl peptidase-4 (DPP-4) inhibitors, have recently been introduced into clinical practice. At present, the GLP-1 receptor agonists need to be administered once or twice daily. Several once-weekly GLP-1 receptor agonists are in phase 3 development. This review examines the efficacy, safety and perspective for the future of the once-weekly GLP-1 receptor agonists: exenatide once weekly, taspoglutide, albiglutide, LY2189265 and CJC-1134-PC, and compared them to the currently available agonists, exenatide BID and liraglutide QD. A greater reduction in haemoglobin A1c (HbA1c) and fasting plasma glucose was found with the once-weekly GLP-1 receptor agonists compared with exenatide BID, while the effect on postprandial hyperglycaemia was modest with the once-weekly GLP-1 receptor agonist. The reduction in HbA1c was in most studies greater compared to oral antidiabetic drugs and insulin glargine. The reduction in weight did not differ between the short- and long-acting agonists. The gastrointestinal side effects were less with the once-weekly agonists compared with exenatide BID, except for taspoglutide. Antibodies seem to be most frequent with exenatide once weekly, while hypersensitivity has been described in few patients treated with taspoglutide. Injection site reactions differ among the long-acting GLP-1 receptor agonists and are observed more frequently than with exenatide BID and liraglutide. In humans, no signal has been found indicating an association between the once-weekly agonists and C-cell cancer. The cardiovascular safety, durability of glucose control and effect on weight will emerge from several ongoing major long-term trials. The once-weekly GLP-1 receptor analogues are promising candidates for the treatment of type 2 diabetes, although their efficacy may not be superior to once-daily analogue liraglutide.
Role of Epac2A/Rap1 Signaling in Interplay Between Incretin and Sulfonylurea in Insulin Secretion (2014)

Incretin-related drugs and sulfonylureas are currently used worldwide for the treatment of type 2 diabetes. We recently found that Epac2A, a cAMP binding protein having guanine nucleotide exchange activity toward Rap, is a target of both incretin and sulfonylurea. This suggests the possibility of interplay between incretin and sulfonylurea through Epac2A/Rap1 signaling in insulin secretion. In this study, we examined the combinatorial effects of incretin and various sulfonylureas on insulin secretion and activation of Epac2A/Rap1 signaling. A strong augmentation of insulin secretion by combination of GLP-1 and glibenclamide or glimepiride, which was found in Epac2A(+/+) mice, was markedly reduced in Epac2A(-/-) mice. In contrast, the combinatorial effect of GLP-1 and gliclazide was rather mild, and the effect was not altered by Epac2A ablation. Activation of Rap1 was enhanced by the combination of an Epac-selective cAMP analog with glibenclamide or glimepiride but not gliclazide. In diet-induced obese mice, ablation of Epac2A reduced the insulin secretory response to coadministration of the GLP-1 receptor agonist liraglutide and glimepiride. These findings clarify the critical role of Epac2A/Rap1 signaling in the augmenting effect of incretin and sulfonylurea on insulin secretion and provide the basis for the effects of combination therapies of incretin-related drugs and sulfonylureas.
Lithium–Organic Nanocomposite Suspension for High-Energy-Density Redox Flow Batteries (2018)

Organic redox-active materials are promising for redox flow batteries (RFBs) owing to their inherent low-cost, vast abundance, and high structure tunability. However, many organic RFBs suffer from low energy density owing to low solubility. We demonstrate a facile lithium–organic nanocomposite suspension (LIONS) by melting solid organic materials into the void of carbon networks in the semisolid posolyte to achieve high-energy-density Li-RFBs. We demonstrate the first organic-based semisolid Li-RFBs using 10-methylphenothiazine (MPT), delivering a high volumetric capacity (55 Ah L–1) and energy density (190 Wh L–1) with high Coulombic efficiency (>98%) and cycling stability (>100 cycles). The demonstrated volumetric capacity is 8 fold that of the liquid-MPT RFB, achieving the highest energy density among Li–organic-based RFBs. LIONS is a universal approach to enable the use of low-solubility organic materials in RFBs, providing a new direction for all insoluble organic active material to achieve low-cost and high-energy-density RFBs.
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks (2019)

Video restoration tasks, including super-resolution, deblurring, etc, are drawing increasing attention in the computer vision community. A challenging benchmark named REDS is released in the NTIRE19 Challenge. This new benchmark challenges existing methods from two aspects: (1) how to align multiple frames given large motions, and (2) how to effectively fuse different frames with diverse motion and blur. In this work, we propose a novel Video Restoration framework with Enhanced Deformable networks, termed EDVR, to address these challenges. First, to handle large motions, we devise a Pyramid, Cascading and Deformable (PCD) alignment module, in which frame alignment is done at the feature level using deformable convolutions in a coarse-to-fine manner. Second, we propose a Temporal and Spatial Attention (TSA) fusion module, in which attention is applied both temporally and spatially, so as to emphasize important features for subsequent restoration. Thanks to these modules, our EDVR wins the champions and outperforms the second place by a large margin in all four tracks in the NTIRE19 video restoration and enhancement challenges. EDVR also demonstrates superior performance to state-of-the-art published methods on video super-resolution and deblurring. The code is available at https://github.com/xinntao/EDVR.