Intersession Reliability and Within-Session Stability of a Novel Perception-Action Coupling Task

BACKGROUND: The perception-action coupling task (PACT) was designed as a more ecologically valid measure of alertness/reaction times compared to currently used measures by aerospace researchers. The purpose of this study was to assess the reliability, within-subject variability, and systematic bias associated with the PACT. METHODS: There were 16 subjects (men/women = 9/7; age = 27.8 +/- 3.6 yr) who completed 4 identical testing sessions. The PACT requires subjects to make judgements on whether a virtual ball could fit into an aperture. For each session, subjects completed nine cycles of the PACT, with each cycle lasting 5 min. Judgement accuracy and reaction time parameters were calculated for each cycle. Systematic bias was assessed with repeated-measures ANOVA, reliability with intraclass correlation coefficients (ICC), and within-subject variability with coefficients of variation (CVTE). RESULTS: Initiation time (Mean = 0.1065 s) showed the largest systematic bias, requiring the elimination of three cycles to reduce bias, with all other variables requiring, at the most, one. All variables showed acceptable reliability (ICC > 0.70) and within-subject variability (CVTE <20%) with only one cycle after elimination of the first three cycles. CONCLUSIONS: With a three-cycle familiarization period, the PACT was found to be reliable and stable

Selective Ethylene Glycol Oxidation to Formate on Nickel Selenide with Simultaneous Evolution of Hydrogen

There is an urgent need for cost-effective strategies to produce hydrogen from renewable net-zero carbon sources using renewable energies. In this context, the electrochemical hydrogen evolution reaction can be boosted by replacing the oxygen evolution reaction with the oxidation of small organic molecules, such as ethylene glycol (EG). EG is a particularly interesting organic liquid with two hydroxyl groups that can be transformed into a variety of C1 and C2 chemicals, depending on the catalyst and reaction conditions. Here, a catalyst is demonstrated for the selective EG oxidation reaction (EGOR) to formate on nickel selenide. The catalyst nanoparticle (NP) morphology and crystallographic phase are tuned to maximize its performance. The optimized NiS electrocatalyst requires just 1.395 V to drive a current density of 50 mA cm −2 in 1 potassium hydroxide (KOH) and 1 EG. A combination of in situ electrochemical infrared absorption spectroscopy (IRAS) to monitor the electrocatalytic process and ex situ analysis of the electrolyte composition shows the main EGOR product is formate, with a Faradaic efficiency above 80%. Additionally, C2 chemicals such as glycolate and oxalate are detected and quantified as minor products. Density functional theory (DFT) calculations of the reaction process show the glycol-to-oxalate pathway to be favored via the glycolate formation, where the C-C bond is broken and further electro-oxidized to formate. A combination of in situ and ex situ analysis shows the main product of the ethylene glycol (EG) oxidation reaction (EGOR) is formate with a Faradaic efficiency above 80%, and glycolate and oxalate as minor chemicals on nickel selenide nanoparticles (NPs). Further density functional theory (DFT) calculation reveals the electrooxidation mechanism to these products

The promise and challenges of utility-scale compressed air energy storage in aquifers

Widely distributed aquifers have been proposed as effective storage reservoirs for compressed air energy storage (CAES). This aims to overcome the limitations of geological conditions for conventional utility-scale CAES, which has to date used caverns as the storage reservoirs. As a promising technology, compressed air energy storage in aquifers (CAESA) has received increasing attention as a potential method to deal with the intermittent nature of solar or wind energy sources. This article presents a selective review of theoretical and numerical modeling studies as well as field tests, along with efficiency and economic analyses, to assess the feasibility of the emerging technology. Although some field tests suggest that a large bubble could be created in aquifers to sustain the working cycles at target rates, challenges remain before the technology can be recommended for wide deployment. The geological critical safety factors affecting the gas bubble development and sustainability of operation cycles include the geological structure, aquifer depth, and hydrodynamic and mechanical properties, such as porosity, permeability, compressibility, and mineral composition. Moreover, the injection/withdrawal well configurations and oxidation reactions caused by the oxygen in compressed air should also be considered. The failed attempt of renewable energy combined with CAESA in Iowa is described and the lessons learned are summarized. Combining CAESA with thermal storage, using CO2 as cushion gas, horizontal wells or hydraulic fracturing, and man-made boundaries are proposed to improve CAESA efficiency but need further study for future applications

AIDA directly connects sympathetic innervation to adaptive thermogenesis by UCP1

AIDA最早是由林圣彩教授团队首先鉴定和命名的。2007年林圣彩教授团队与孟安明院士团队合作发现AIDA在斑马鱼体轴发育中的功能(Rui, 2007)。2018年，林圣彩教授团队首次发现了AIDA在哺乳动物中的功能，即AIDA介导的内质网降解途径通过降解脂肪合成途径中的关键酶，而限制膳食脂肪在肠道的吸收这一内在抵御肥胖(Luo, 2018)。而本次成果揭示了AIDA在棕色脂肪组织中特定的功能。这些工作将AIDA引入了脂质应激代谢的重要环节，包括脂质吸收和依赖于脂质的产热过程。该论文的共同第一作者为生命科学学院博士生史猛和硕士生黄晓羽，林圣彩教授和林舒勇教授则为共同通讯作者。【Abstract】The sympathetic nervous system–catecholamine–uncoupling protein 1 (UCP1) axis plays an essential role in non-shivering adaptive thermogenesis. However, whether there exists a direct effector that physically connects catecholamine signalling to UCP1 in response to acute cold is unknown. Here we report that outer mitochondrial membrane-located AIDA is phosphorylated at S161 by the catecholamine-activated protein kinase A (PKA). Phosphorylated AIDA translocates to the intermembrane space, where it binds to and activates the uncoupling activity of UCP1 by promoting cysteine oxidation of UCP1.Adipocyte-specific depletion of AIDA abrogates UCP1-dependent thermogenesis, resulting in hypothermia during acute cold exposure. Re-expression of S161A-AIDA, unlike wild-type AIDA, fails to restore the acute cold response in Aida-knockout mice.The PKA–AIDA–UCP1 axis is highly conserved in mammals, including hibernators. Denervation of the sympathetic postganglionic fibres abolishes cold-induced AIDA-dependent thermogenesis. These findings uncover a direct mechanistic link between sympathetic input and UCP1-mediated adaptive thermogenesis.We thank Y. Li, E. Gnaiger, T. Kuwaki, J. R. B. Lighton, E. T. Chouchani and D. Jiang for technical instruction; X. Li and X.-D. Jiang (Core Facility of Biomedical, Xiamen University) for raising the p-S161-AIDA antibody; the Xiamen University Laboratory Animal Center for the mouse in vitro fertilization service and all the other members of S.C.L. laboratory for their technical assistance. This work was supported by grants from the National Key Research and Development Project of China (grant no. 2016YFA0502001) and the National Natural Science Foundation of China (grant nos 31822027, 31871168, 31690101, 91854208 and 82088102), the Fundamental Research Funds for the Central Universities (grant nos 20720190084 and 20720200069), Project ‘111’ sponsored by the State Bureau of Foreign Experts and Ministry of Education of China (grant no. BP2018017), the Youth Innovation Fund of Xiamen (grant no. 3502Z20206028), the Natural Science Foundation of Fujian Province of China (grant no. 2017J01364) and XMU Training Program of Innovation and Entrepreneurship for Undergraduates (grant no. 2019×0666). 该工作得到了厦门大学实验动物中心和生物医学学部仪器平台的重要协助和国家重点研究和发展项目，国家自然科学基金，厦门大学校长基金等的支持

Real-time Facial Performance Capture and Manipulation

Acquisition and editing of facial performance is an essential and challenging task in computer graphics, with broad applications in films, cartoons, VR systems, and electronic games. The creation of high-resolution, realistic facial animations often involves controlled lighting setups, multiple cameras, active markers, depth sensors, and substantial post-editing from experienced artists. This dissertation focuses on the capture and manipulation of facial performance from regular RGB video. First, a novel method is proposed to reconstruct high-resolution facial geometry and appearance in real-time by capturing an individual-specific face model with fine-scale details, based on monocular RGB video input. Specifically, after the coarse facial model is reconstructed from the input video, it is subsequently refined using shape-from-shading techniques, where illumination, albedo texture, and displacements are recovered by minimizing the difference between the synthesized face and the input RGB video. To recover wrinkle level details, a hierarchical face pyramid is built through adaptive subdivisions and progressive refinements of the mesh from a coarse level to a fine level. The proposed approach can produce results close to off-line methods and better than previous real-time methods. On top of the reconstruction method, two manipulation approaches upon facial expressions and facial appearance are proposed, namely facial expression transformation and face swapping. In facial expression transformation, desired and photo-realistic facial expressions are directly generated on top of input monocular RGB video without the need of any driving source actor. An unpaired learning framework is developed to learn the mapping between any two facial expressions in the facial blendshape space. The proposed method automatically transforms the source expression in an input video clip to a specified target expression through the combination of the 3D face reconstruction, the learned bi-directional expression mapping, and automatic lip correction. It can be applied to new users with different identities, ages, speeches, and expressions, and without additional training. In face swapping, a high-fidelity method is presented to replace the face in a target video clip by the face from a single source portrait image. First, the face reconstruction method is run on both the source image and the target video. Then, the albedo of the source face is modified by a novel harmonization method to match the target face. The face geometry is predicted as the source identity performing the target expression with person-specific wrinkle style. Finally, the source face is re-rendered and blended into the target video using the lighting and camera parameters from the target video. The proposed method runs fully automatically and at a real-time rate on any target face captured by cameras or from legacy videos. More importantly, unlike existing deep-learning- based methods, it does not need to pre-train any models, i.e., pre-collecting a large image/video dataset of the source or target face for model training is not required.Computer Science, Department o

A Multi-Level Strategy Based on Metabolic and Molecular Genetic Approaches for the Characterization of Different <i>Coptis</i> Medicines Using HPLC-UV and RAD-seq Techniques

Coptis plants (Ranunculaceae) to have played an important role in the prevention and treatment human diseases in Chinese history. In this study, a multi-level strategy based on metabolic and molecular genetic methods was performed for the characterization of four Coptis herbs (C. chinensis, C. deltoidea, C. omeiensis and C. teeta) using high performance liquid chromatography-ultraviolet (HPLC-UV) and restriction site-associated DNA sequencing (RAD-seq) techniques. Protoberberine alkaloids including berberine, palmatine, coptisine, epiberberine, columbamine, jatrorrhizine, magnoflorine and groenlandicine in rhizomes were identified and determined based on the HPLC-UV method. Among them, berberine was demonstrated as the most abundant compound in these plants. RAD-seq was applied to discover single nucleotide polymorphisms (SNPs) data. A total of 44,747,016 reads were generated and 2,443,407 SNPs were identified in regarding to four plants. Additionally, with respect to complicated metabolic and SNP data, multivariable statistical methods of principal component analysis (PCA) and hierarchical cluster analysis (HCA) were successively applied to interpret the structure characteristics. The metabolic variation and genetic relationship among different Coptis plants were successfully illustrated based on data visualization. Summarily, this comprehensive strategy has been proven as a reliable and effective approach to characterize Coptis plants, which can provide additional information for their quality assessment