Effect of finite computational domain on turbulence scaling law in both physical and spectral spaces

The well-known translation between the power law of the energy spectrum and that of the correlation function or the second order structure function has been widely used in analyzing random data. Here, we show that the translation is valid only in proper scaling regimes. The regimes of valid translation are different for the correlation function and the structure function. Indeed, they do not overlap. Furthermore, in practice, the power laws exist only for a finite range of scales. We show that this finite range makes the translation inexact even in the proper scaling regime. The error depends on the scaling exponent. The current findings are applicable to data analysis in fluid turbulence and other stochastic systems

Innovative and Collaborative Use of iPads in Interpreter Education

This article reports on findings from a collaborative action research project that was conducted to investigate the use of iPad in teaching interpreting students. Action research is well documented as a method for encouraging innovation and change in education, and it has been applied in translation and interpreting educational research. The goal of the project was to investigate how iPad technology can be used to enhance the learning experience for interpreting students in a master’s-level Conference Interpreting program, with an evaluation of the benefits of using the iPad generally and in relation to the development of interpreting skills, as well as through one particular iPad application (AudioNote). The project incorporated periodic cycles of evaluation to reflect on the effectiveness of the use of iPads in this teaching context, for instructors and students to share information about what applications they had found, and to design learning and teaching activities together using those applications. The iPad applications downloaded by students can be categorized into three main areas of learning: general study, language enhancement, and interpreting skills. Recommendations are made about how iPads can be used innovatively and creatively in educating interpreting students of any language combination

Interaction of cellulase with three phenolic acids

The activity of cellulase against filter paper was enhanced by 28.32% and 15.17% after the addition of 0.83 mg/ml of ferulic acid and p-coumaric acid, respectively, and by 10.15% after the addition of salicylic acid at 0.67 mg/ml. The effects of three phenolic acids on the structure of cellulase were investigated via ultraviolet spectrophotometry, fluorescence spectroscopy, and circular dichroism (CD) spectroscopy. Ultraviolet spectroscopic results indicated that the peak absorbance of cellulase significantly increased and exhibited a 4–5 nm redshift after the addition of the three phenolic acids, suggesting that the phenolic acids strongly interacted with the enzyme. Fluorescence investigation of the interaction between the enzyme and the phenolic acids showed that ferulic acid and p-coumaric acid covalently reacted with the aromatic amino acid residues in cellulase, whereas salicylic acid interacted non-covalently with cellulase. CD analysis revealed that the addition of the phenolic acids significantly decreased α-helix content but increased β-sheet and random coil contents. The possible mechanism underlying the effects of these phenolic acids on cellulase activity was also discussed.</p

Cure the headache of Transformers via Collinear Constrained Attention

As the rapid progression of practical applications based on Large Language Models continues, the importance of extrapolating performance has grown exponentially in the research domain. In our study, we identified an anomalous behavior in Transformer models that had been previously overlooked, leading to a chaos around closest tokens which carried the most important information. We've coined this discovery the "headache of Transformers". To address this at its core, we introduced a novel self-attention structure named Collinear Constrained Attention (CoCA). This structure can be seamlessly integrated with existing extrapolation, interpolation methods, and other optimization strategies designed for traditional Transformer models. We have achieved excellent extrapolating performance even for 16 times to 24 times of sequence lengths during inference without any fine-tuning on our model. We have also enhanced CoCA's computational and spatial efficiency to ensure its practicality. We plan to open-source CoCA shortly. In the meantime, we've made our code available in the appendix for reappearing experiments.Comment: 16 pages, 6 figure

Preparation of octacosanol from filter mud produced after sugarcane juice clarification

Filter mud from sugarcane juice clarification containing 6.85 g/100 g waxes was used for octacosanol extraction by supercritical CO2 and hot ethanol reflux method, respectively. Comparing with hot ethanol reflux extraction, supercritical CO2 extraction provided a similar yield of waxes but a higher content of octacosanol in the waxes (29.65 g/100 g vs. 22.52 g/100 g). However, saponification of the waxes extracted by hot ethanol reflux extraction has significantly increased octacosanol content to 47.8 g/100 g. For high efficient preparation of octacosanol from filter mud, hot ethanol reflux extraction of waxes followed by saponification was the method of choice.</p

Pediatric Myopia Progression During the COVID-19 Pandemic Home Quarantine and the Risk Factors: A Systematic Review and Meta-Analysis

BackgroundThe COVID-19 pandemic has made many countries adopt restrictive measures like home quarantine. Children were required to study at home, which made parents worried about the rapid myopic progression of their children. To compare myopia progression during the COVID-19 pandemic home quarantine with the time before it and risk factors of myopia progression, we conducted this study.MethodsWe searched PubMed, Embase, the Cochrane Library, and Web of Science to find literature from December 2019 to March 2022 related to COVID-19 pandemic home quarantine and children's myopia progression. Outcomes of myopia progression included axial length and spherical equivalent refraction. Factors of digital screen device time and outdoor activity time were analyzed.ResultsTen studies were included in this meta-analysis. Compared to the same period before the COVID-19 pandemic, spherical equivalent refraction decreased (OR = −0.27; 95% CI = [−0.33, −0.21]; Z = 8.42; P &lt; 0.00001). However, the subgroup analysis showed that there were no significant differences in spherical equivalent refraction between the two groups in higher-grade school-aged children (grades 4 and above, 11 to 18 years old) (OR = 0.01; 95% CI = [−0.05, 0.07]; Z =0.4; P = 0.69). The outcome of axial length showed no significant difference (OR = 0.06; 95% CI = [−0.31, 0.44]; Z = 0.34; P = 0.74). As for risk factors, the forest plots showed that digital screen device time (OR = 4.56; 95% CI = [4.45, 4.66]; Z = 85.57; P &lt; 0.00001) and outdoor activity time (OR = −1.82; 95% CI = [−2.87, −0.76]; Z = 3.37; P = 0.0008) were risk factors of myopia progression.ConclusionCompared with the time before the COVID-19 pandemic, myopia progression in children during COVID-19 pandemic home quarantine was accelerated, especially in younger children. Increased digital screen device and decreased outdoor activity times were risk factors. When home quarantine eases, more time on outdoor activities and less time on digital screen devices are needed for children.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/logout.php

Training Large-Vocabulary Neural Language Models by Private Federated Learning for Resource-Constrained Devices

Federated Learning (FL) is a technique to train models using data distributed across devices. Differential Privacy (DP) provides a formal privacy guarantee for sensitive data. Our goal is to train a large neural network language model (NNLM) on compute-constrained devices while preserving privacy using FL and DP. However, the DP-noise introduced to the model increases as the model size grows, which often prevents convergence. We propose Partial Embedding Updates (PEU), a novel technique to decrease noise by decreasing payload size. Furthermore, we adopt Low Rank Adaptation (LoRA) and Noise Contrastive Estimation (NCE) to reduce the memory demands of large models on compute-constrained devices. This combination of techniques makes it possible to train large-vocabulary language models while preserving accuracy and privacy

Statistics of Dissipation and Enstrophy Induced by a Set of Burgers Vortices

Dissipation and enstropy statistics are calculated for an ensemble of modified Burgers vortices in equilibrium under uniform straining. Different best-fit, finite-range scaling exponents are found for locally-averaged dissipation and enstrophy, in agreement with existing numerical simulations and experiments. However, the ratios of dissipation and enstropy moments supported by axisymmetric vortices of any profile are finite. Therefore the asymptotic scaling exponents for dissipation and enstrophy induced by such vortices are equal in the limit of infinite Reynolds number.Comment: Revtex (4 pages) with 4 postscript figures included via psfi

Precursors and Pathways Leading to Enhanced Secondary Organic Aerosol Formation during Severe Haze Episodes

Publisher Copyright: © 2021 American Chemical SocietyMolecular analyses help to investigate the key precursors and chemical processes of secondary organic aerosol (SOA) formation. We obtained the sources and molecular compositions of organic aerosol in PM2.5in winter in Beijing by online and offline mass spectrometer measurements. Photochemical and aqueous processing were both involved in producing SOA during the haze events. Aromatics, isoprene, long-chain alkanes or alkenes, and carbonyls such as glyoxal and methylglyoxal were all important precursors. The enhanced SOA formation during the severe haze event was predominantly contributed by aqueous processing that was promoted by elevated amounts of aerosol water for which multifunctional organic nitrates contributed the most followed by organic compounds having four oxygen atoms in their formulae. The latter included dicarboxylic acids and various oxidation products from isoprene and aromatics as well as products or oligomers from methylglyoxal aqueous uptake. Nitrated phenols, organosulfates, and methanesulfonic acid were also important SOA products but their contributions to the elevated SOA mass during the severe haze event were minor. Our results highlight the importance of reducing nitrogen oxides and nitrate for future SOA control. Additionally, the formation of highly oxygenated long-chain molecules with a low degree of unsaturation in polluted urban environments requires further research.Peer reviewe