Investigation of the thermal behavior effect of the surrounding material environment on the swirling flame structure

This paper is focusing on the numerical simulation of a swirling flame, resulting from the interaction of multiple fires, evolving in a free and unlimited environment. A typical system, formed by a central fire source surrounded by four heat sources, is used. Since the thermal characteristic of the surrounding sources is the main engine for the rotation of flame, a detailed study is performed by varying the heating flux of these sources. This study shows that an increase of the heating flux of surrounding sources has as a result an intensification of the penetrating air puffs through the openings between the surrounding four heat sources. These puffs tangentially drive the central flame, thus producing a marked improvement on the angular momentum. Moreover, this study shows that the flame height is strongly affected by the flame rotation. Moreover, two different aspects of the flame height evolution are observed from the flow visualization and the thermal and dynamic fields for the different cases studied.     

On the use of 1g physical models for ground movements and soil-structure interaction problems

The paper focusses on the use of physical modelling in ground movements (induced by underground cavity collapse or mining/tunnelling) and associated soil-structure interaction issues. The paper presents first an overview of using 1g physical models to solve geotechnical problems and soil-structure interactions related to vertical ground movements. Then the 1g physical modelling application is illustrated to study the development of damage in masonry structure due to subsidence and cavity collapse. A large-scale 1g physical model with a 6 m³ container and 15 electric jacks is presented with the use of a three-dimensional (3D) image correlation technique. The influence of structure position on the subsidence trough is analysed in terms of crack density and damage level. The obtained results can improve the methodology and practice for evaluation of damage in masonry structures. Nevertheless, ideal physical model is difficult to achieve. Thus, future improvement of physical models (analogue materials and instrumentation) could provide new opportunities for using 1g physical models in geotechnical and soil-structure applications and research projects.     

Hollow structured Zn0.76Co0.24S–Co9S8 composite with two-phase synergistic effect as bifunctional catalysts

It is of great significance to develop efficient and inexpensive oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) bifunctional catalysts for the current energy crisis. But this is still a long-term and formidable challenge. In this work, a two-phase synergistic effect between transition metal sulfides is applied in the design of ORR/OER bifunctional catalysts. Co-based zeolite imidazolate framework (MOF) is used as a precursor to prepare the hollow Co₉S₈ through vulcanization and heat treatment. At the same time, the phase transformation occurs to form some Zn_0.76Co_0.24S on surface during the heat treatment due to the Zn-polydopamine coating. The hollow structure Zn_0.76Co_0.24S–Co₉S₈ composite has been verified and promotes the diffusion of reactants and products, and the interaction between two phases greatly promotes the catalytic reactions. The coating of Zn-polydopamine forms uniform carbon layer on surface, enhancing the conductivity of Zn_0.76Co_0.24S–Co₉S₈ composite. The Zn_0.76Co_0.24S–Co₉S₈ composite shows much better performance of ORR and OER compared to any of them. The overpotential of OER at a current density of 10 mA/cm² is 330 mV, and the half-wave potential of ORR is 0.83 V. Additionally, the Zn_0.76Co_0.24S–Co₉S₈ composite displays better cyclic stability. The synergistic effect of Zn_0.76Co_0.24S and Co₉S₈ can be considered as the foremost factor for the improvement of catalyst performance, which provides new possibilities for the development of non-precious metal bifunctional catalysts.     

基于VR技术的智能变电站运行仿真培训系统

为了更加真实、直观地呈现智能变电站的运行整体结构,构建基于VR技术的智能变电站运行仿真培训系统。该系统通过5个模块协同完成智能变电站运行仿真培训,结合实际变电站的设备情况,采用二维纹理映射方法完成变电站设备仿真建模;系统利用虚拟现实交互模块呈现培训场景,参与培训人员能够通过人机交互设备,实现场景漫游和相关培训内容操作。测试结果表明:该系统能够较好地模拟出智能变电站的实际运行情况,参与培训的人员可以身临其境地完成整个变电站的巡视,更真实、直观地呈现智能变电站的整体状态。     

Basic human–robot interaction system running on an embedded platform

Robotics will be a dominant area in society throughout future generations. Its presence is currently increasing in most daily life settings, with devices and mechanisms that facilitate the accomplishment of diverse tasks, as well as in work scenarios, where machines perform more and more jobs. This increase in the presence of autonomous robotic systems in society is due to their great efficiency and security compared to human capacity, which is thanks mainly to the enormous precision of their sensor and actuator systems. Among these, vision sensors are of the utmost importance. Humans and many animals naturally enjoy powerful perception systems, but, in robotics, this constitutes a constant line of research. In addition to having a high capacity for reasoning and decision-making, these robots incorporate important advances in their perceptual systems, allowing them to interact effectively in the working environments of this new industrial revolution. Drawing on the most basic interaction between humans, looking at the face, an innovative system is presented in this paper, which was developed for an autonomous and DIY robot. This system is composed of three modules. First, the face detection component, which detects human faces in the current image. Second, the scene representation algorithm, which offers a wider field of view than that of the single camera used, mounted on a servo-pan unit. Third, the active memory component, which was designed and implemented according to two competing dynamics: life and salience. The algorithm intelligently moves the servo-pan unit with the aim of finding new faces, follow existing ones and forgetting those that no longer appear on the scene. The system was developed and validated using a low-cost platform based on a Raspberry Pi3 board.     

A toy or a friend? Children's anthropomorphic beliefs about robots and how these relate to second-language word learning

This study investigates the degree to which children anthropomorphize a robot tutor and whether this anthropomorphism relates to their vocabulary learning in a second-language (L2) tutoring intervention. With this aim, an anthropomorphism questionnaire was administered to 5-year-old children (N = 104) twice: prior to and following a seven-session L2 vocabulary training with a humanoid robot. On average, children tended to anthropomorphize the robot prior to and after the lessons to a similar degree, but many children changed their attributed anthropomorphic features. Boys anthropomorphized the robot less after the lessons than girls. Moreover, there was a weak but significant positive correlation between anthropomorphism as measured before the lessons and scores on a word-knowledge post-test administered the day after the last lesson. There was also a weak but significant positive correlation between the change in anthropomorphism over time and scores on a word-knowledge post-test administered approximately 2 weeks after the last lesson. Our results underscore the need to manage children's expectations in robot-assisted education. Also, future research could explore adaptations to individual children's expectations in child-robot interactions.     

On the bright side: The influence of brightness on overall taste intensity perception

Ambient light luminance (i.e., brightness or dimness) is a frequently used tool by managers to enhance the overall ambience in their restaurants. The current research explores how a change in a restaurant’s ambient brightness influences the overall taste intensity perception of the food that is being served there. We conducted a between-group experiment in a field setting (i.e., a fine-dining restaurant), where we manipulated the illuminance level of the ambient light (dim vs. bright). Guests were served a dish—tailored to our research question—and asked to evaluate its overall taste intensity. The results demonstrate that guests exposed to the bright ambient light perceived the overall taste of the dish as more intense as opposed to guests exposed to the dim ambient light. The results thus show that modifying the ambient illuminance level in a restaurant does not only affect the overall ambience but also changes the overall taste experience of the food being served. This finding is not only theoretically relevant for research on multisensory integration, but it also provides tools for taste modulation, and—as such—for strategies to decrease salt and sugar consumption among diners.     

Effects of breed,farm intensiveness,and cow productivity level on cheese-making ability predicted using infrared spectral data at the population level

Fourier-transform infrared (FTIR) spectra collected during milk recording schemes at population level can be used for predicting novel traits of interest for farm management, cows' genetic improvement, and milk payment systems. The aims of this study were as follows. (1) To predict cheese yield traits using FTIR spectra from routine milk recordings exploiting previously developed calibration equations. (2) To compare the predicted cheese-making abilities of different dairy and dual-purpose breeds. (3) To analyze the effects of herds' level of intensiveness (HL) and of the cow's level of productivity (CL). (4) To compare the patterns of predicted cheese yields with the patterns of milk composition in different breeds to discern the drivers of cheese-making efficiency. The major sources of variation of FTIR predictions of cheese yield ability (fresh cheese or cheese solids produced per unit milk) of individual milk samples were studied on 115,819 cows of 4 breeds (2 specialized dairy breeds, Holstein and Brown Swiss, and 2 dual-purpose breeds, Simmental and Alpine Grey) from 6,430 herds and exploiting 1,759,706 FTIR test-day spectra collected over 7 yr of milk sampling. Calibration equations used were previously developed on 1,264 individual laboratory model cheese procedures (cross-validation R² 0.85 and 0.95 for fresh and solids cheese yields, respectively). The linear model used for statistical analysis included the effects of parity, lactation stage, year of calving, month of sampling, HL, CL, breed of cow, and the interactions breed × HL and breed × CL. The HL and CL stratifications (5 classes each) were based on average daily secretion of milk net energy per cow. All effects were highly significant. The major conclusions were as follows. (1) The FTIR-based prediction of cheese yield of milk goes beyond the knowledge of fat and protein content, partially explaining differences in cheese-making ability in different cows, breeds and herds. (2) Differences in cheese yields of different breeds are only partially explained by milk fat and protein composition, and less productive breeds are characterized by a higher milk nutrient content as well as a higher recovery of nutrients in the cheese. (3) High-intensive herds not only produce much more milk, but the milk has a higher nutrient content and a higher cheese yield, whereas within herds, compared with less productive cows, the more productive cows have a much greater milk yield, milk with a greater content of fat but not of protein, and a moderate improvement in cheese yield, differing little from expectations based on milk composition. Finally, (4) the effects of HL and CL on milk quality and cheese-making ability are similar but not identical in different breeds, the less productive ones having some advantage in terms of cheese-making ability. We can obtain FTIR-based prediction of cheese yield from individual milk samples retrospectively at population level, which seems to go beyond the simple knowledge of milk composition, incorporating information on nutrient retention ability in cheese, with possible advantages for management of farms, genetic improvement of dairy cows, and milk payment systems.     

Four phenolic acids from purple sweet potato and their effects on physicochemical,digestive and structural characteristics of starch

Liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) was employed to investigate free phenols that were released from purple sweet potato (PSP) by alkaline, acid and enzymatic hydrolysis. Four phenolic acids, including ferulic, isoferulic, 4-hydroxybenzoic and caffeic acids, were identified. Based on their effects on the characteristics of purple sweet potato starch (PSPS), the four phenolic acids were studied. Furthermore, scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT–IR) and X-ray diffraction (XRD) techniques were employed to explore the microstructures of the complexes of the phenolic acids and PSPS. The obtained results demonstrated that the pasting, thermal, retrogradation, as well as digestive properties of PSPS were all influenced by the phenolic acids which interacted with PSPS through noncovalent hydrogen bonds. The influence of the four phenolic acids on the properties of PSPS was in the descending order: 4-hydroxybenzoic acid > ferulic acid > caffeic acid > isoferulic acid.     

Double Mutant Cycles as a Tool to Address Folding,Binding, and Allostery

Quantitative measurement of intramolecular and intermolecular interactions in protein structure is an elusive task, not easy to address experimentally. The phenomenon denoted ‘energetic coupling’ describes short- and long-range interactions between two residues in a protein system. A powerful method to identify and quantitatively characterize long-range interactions and allosteric networks in proteins or protein–ligand complexes is called double-mutant cycles analysis. In this review we describe the thermodynamic principles and basic equations that underlie the double mutant cycle methodology, its fields of application and latest employments, and caveats and pitfalls that the experimentalists must consider. In particular, we show how double mutant cycles can be a powerful tool to investigate allosteric mechanisms in protein binding reactions as well as elusive states in protein folding pathways.