Transparent Dispersions of Milk Fat-Based Solid Lipid Nanoparticles for Delivery of beta-Carotene

Solid lipid nanoparticles (SLNs) are a category of delivery systems applicable to various bioactive compounds in the food industry. Compared to conventional emulsions that have a fluidic oil phase, the mobility and release of bioactive compounds can be controlled by encapsulation in the solid lipid matrix with appropriate properties. Common approaches of preparing SLNs are high energy methods and solvent evaporation methods, which have can lead to degradation of compounds during processing and residues of organic solvent, respectively. In this thesis, a low energy approach based on the phase inversion temperature method has been used to prepare SLNs based on anhydrous milk fat (AMF). Food grade surfactant Tween 80 was used as a surfactant, and beta-carotene was used as a model lipophilic bioactive compound. AMF and surfactant solution with 0-1.0 M NaCl were mixed to form coarse emulsions that were heated at 80-95 °C [Celsius degree] for 30 min to induce phase inversion, followed by a fast cooling process in ice bath. The phase inversion temperature decreased from \u3e95 °C to 73°C when NaCl increased from 0 to 1.0 M in the aqueous phase. Up to 10% w/w of AMF can be encapsulated in the system as transparent dispersions, with particle mean diameter smaller than 25 nm. The SLN dispersions were dilution and dialysis stable, and the particle size and turbidity maintained unchanged during the 90-day storage at room temperature. Compared with beta-carotene encapsulated in soybean oil-based nanoemulsion, degradation of beta-carotene in SLNs was much reduced. The studied SLNs may find unique applications in incorporating lipophilic bioactive compounds in transparent beverages

Global and Local Hierarchy-aware Contrastive Framework for Implicit Discourse Relation Recognition

Due to the absence of explicit connectives, implicit discourse relation recognition (IDRR) remains a challenging task in discourse analysis. The critical step for IDRR is to learn high-quality discourse relation representations between two arguments. Recent methods tend to integrate the whole hierarchical information of senses into discourse relation representations for multi-level sense recognition. Nevertheless, they insufficiently incorporate the static hierarchical structure containing all senses (defined as global hierarchy), and ignore the hierarchical sense label sequence corresponding to each instance (defined as local hierarchy). For the purpose of sufficiently exploiting global and local hierarchies of senses to learn better discourse relation representations, we propose a novel GLobal and LOcal Hierarchy-aware Contrastive Framework (GLOF), to model two kinds of hierarchies with the aid of contrastive learning. Experimental results on the PDTB dataset demonstrate that our method remarkably outperforms the current state-of-the-art model at all hierarchical levels.Comment: 13 pages, 10 figure

An intelligent video fire detection approach based on object detection technology

PresentationFire that is one of the most serious accidents in chemical factories, may lead to considerable product losses, equipment damages and casualties. With the rapid development of computer vision technology, intelligent fire detection has been proposed and applied in various scenarios. This paper presents a new intelligent video fire detection approach based on object detection technology using convolutional neural networks (CNN). First, a CNN model is trained for the fire detection task which is framed as a regression problem to predict bounding boxes and associated probabilities. In the application phase, videos from surveillance cameras are detected frame by frame. Once fire appears in the current frame, the model will output the coordinates of the fire region. Simultaneously, the frame where the fire region is localized will be immediately sent to safety supervisors as a fire alarm. This will help detect fire at the early stage, prevent fire spreading and improve the emergency response

Multifocal laser direct writing through spatial light modulation guided by scalable vector graphics

Multifocal laser direct writing (LDW) based on phase-only spatial light modulator (SLM) can realize flexible and parallel nanofabrication with high throughput potential. In this investigation, a novel approach of combining two-photon absorption, SLM and vector path guided by scalable vector graphics (SVG) has been developed and tested preliminarily, for fast, flexible and parallel nanofabrication. Three laser focuses are independently controlled with different paths, which are according to SVG, to optimize fabrication and promote time efficiency. The minimum structure width can be as low as 74 nm. Accompanied with a translation stage, a carp structure of 18.16 $\mu$m by 24.35 $\mu$m has been fabricated. This method shows the possibility of developing LDW techniques towards full-electrical system, and provides a potential way to efficiently engrave complex structures on nanoscales

Application of Relative Risk of Meteorological Factors in Power Grid Electricity Load Forecasting

[Introduction] Accurate and efficient short-term electricity load forecasting is a prerequisite for ensuring the safe and reliable operation of power system, and it is also the basis for the rational arrangement of power generation plans in the power grid. Therefore, studying the relationship between meteorology and electricity load is of great significance for load forecasting. [Method] Based on the electricity load data at 15 min intervals during the period between January 1 of 2013 and December 31 of 2021 provided by the State Grid Hebei Electric Power Co., Ltd. as well as the corresponding meteorological observation data of Shijiazhuang station, this paper analyzed the temporal variation characteristics of daily peak electricity load in Shijiazhuang, and in particular, the meteorological conditions corresponding to the samples with a daily peak electricity load that was 10% higher than that of the previous day were analyzed. The Spearman's rank correlation method was used to analyze the correlation between daily peak electricity load in Shijiazhuang and the meteorological factors of the previous day, and significantly correlated meteorological factors were identified. The response curves of the significantly correlated meteorological factors to the next day's peak electricity load were drawn using the smooth curve fitting method, and the analysis revealed the changing trend of daily peak electricity load with the variations of meteorological factors, as well as the response thresholds. For different threshold ranges, the relative risk of meteorological factors to the changes of the daily peak electricity load was calculated based on the Poisson distribution. On this basis, the variation magnitudes of daily peak electricity load caused by per unit change in each meteorological factor within different threshold ranges in Shijiazhuang were calculated, that is, the quantitative impacts of the changes in different meteorological factors on the variation of daily peak electricity load were revealed. [Result] Taking temperature as an example, when the daily average, maximum and minimum temperatures are higher (lower) than the thresholds, the relative risk to the next day′s peak electricity load increases (decreases) by 2.25% (0.62%), 1.92% (0.57%) and 2.07% (0.60%) respectively for every 1 °C increase in temperature. [Conclusion] Based on the relative risk of different meteorological factors to daily peak electricity load in Shijiazhuang, a method for predicting the next day′s peak electricity load is proposed. The test performed using the daily electricity load and meteorological data of Shijiazhuang in 2022 reveals that the prediction effect can meet the needs of daily electricity meteorological service

Research on Theory and Technology of Floor Heave Control in Semicoal Rock Roadway: Taking Longhu Coal Mine in Qitaihe Mining Area as an Example

AbstractAs one of the most common disasters in deep mine roadway, floor heave has caused serious obstacles to mine transportation and normal production activities. The third section winch roadway in the third mining area of Qitaihe Longhu coal mine has a serious floor heave due to the large buried depths of the roadway and the semicoal rock roadway, and the maximum floor heave is 750 mm. For the problem of floor stability, this paper establishes a mechanical model to analyze the stability of roadway floor heave by analogy with the basement heave of deep foundation pit. It provides a model reference for analyzing the problem of roadway floor heave. Aiming at the problem of roadway floor heave in Longhu coal mine, the roadway model is established by using FLAC3D, and the roadway model after support is established according to the on-site support measures. Through the analysis of the distribution of roadway plastic area, stress nephogram, and displacement field simulation results, the results show that the maximum displacement of roadway roof and floor after support is reduced by 15% and 23%, but the maximum floor heave is still 770 mm, which is close to the measured floor heave of roadway. In order to solve the problem of roadway floor heave and integrate economic factors, this paper puts forward three support optimization schemes, simulates the support effect of each scheme, and finally determines that scheme 3 is the best support optimization scheme. Compared with that under the original support, the amount of floor heave is reduced by 81%, and the final amount of floor heave is 150 mm, which can meet the requirements of roadway floor deformation. The results provide a scheme and guidance for roadway support optimization

Synthesis and Photoluminescence Properties of Porous Silicon Nanowire Arrays

Herein, we prepare vertical and single crystalline porous silicon nanowires (SiNWs) via a two-step metal-assisted electroless etching method. The porosity of the nanowires is restricted by etchant concentration, etching time and doping lever of the silicon wafer. The diffusion of silver ions could lead to the nucleation of silver nanoparticles on the nanowires and open new etching ways. Like porous silicon (PS), these porous nanowires also show excellent photoluminescence (PL) properties. The PL intensity increases with porosity, with an enhancement of about 100 times observed in our condition experiments. A “red-shift” of the PL peak is also found. Further studies prove that the PL spectrum should be decomposed into two elementary PL bands. The peak at 850 nm is the emission of the localized excitation in the nanoporous structure, while the 750-nm peak should be attributed to the surface-oxidized nanostructure. It could be confirmed from the Fourier transform infrared spectroscopy analyses. These porous SiNW arrays may be useful as the nanoscale optoelectronic devices

Corporate water disclosure and management : a self-regulation perspective

Worldwide, increasing population and economic growth have provoked an increased demand for water, and global warming has aggravated the instability of water supplies. In the fight for a better environment, water management will soon become a central focus, following the management of carbon emissions. The efficient use of freshwater is essential for sustainable economic development, but a review of the literature reveals that few studies have addressed water management issues at the level of the corporation. Using updated information, gathered from a variety of corporate organizations worldwide, this thesis is timely in addressing water management practices in the business sphere among different industries. Specifically, the central issues of this study are how companies are reacting to increasingly rigid legal requirements in regard to water usage, and what stimulates companies to improve the quality of their water management and ultimately to increase the efficiency of their water usage. To pursue this objective, this study investigates self-disclosed water management practices among corporations worldwide, using data from CDP (previously Carbon Disclosure Project), a non-profit organisation that collects information using questionnaires from hundreds of companies throughout the world on water-specific information, as well as carbon-specific information. In this thesis, three research questions are addressed: why do companies voluntarily participate in the CDP program and disclose information publicly; what causes companies to practice good water management; and does good water management bring benefits to companies. A new theory of self-regulation is proposed and justified by research findings to rationalise corporate attitudes towards water management and disclosure. Three research questions are explored in two chapters, using different methodologies. The contribution of this thesis is threefold. First, few studies have specifically focused on corporate water management to the present time. The present study will fill this gap by providing up-to-date evidence on how companies manage water, in an international setting. From a theoretical perspective, a self-regulation theory is proposed to explain how companies are able to maximize self-interest through disclosure and water management. This study complements the literature by adding new perspectives, with empirical evidence. The self-regulation index and a water-management system are constructed as proxy for self-regulation efforts. Through this study, we will have a better understanding of contemporary sustainable practices in water use, as well as its links to carbon management and long-term sustainability. The results also have practical implications for sustainable water management, which can be used by the government, researchers, and corporations

Fault Sampling of Complex System Under Imperfect Maintenance

When conducting simulation for evaluating complex system reliability or availability, stochastic fault sample method is applied to simulate fault occasions of complex system. Current research of fault sample method generally assumes maintenance activity restores systems to â??good-as-newâ? and â??bad-as-oldâ?, however, system usually keeps its function through imperfect maintenance that restores system to â??partly goodâ? in reality. A stochastic fault sample method for availability evaluation for complex system under imperfect maintenance based on monte-carlo simulation principle is proposed. Firstly, single component fault occurrence process subjected to imperfect maintenance is analyzed and the formula for fault occurrence occasion is given. Secondly, fault sample becomes complicated when maintenance object converts to system with complex reliability structure. Not only fault occurrence occasions but also fault components in the system should be derived from the sample method. Fault sample for parallel system is especially difficult, so the Markov state transition process is embedded into the method to solve this problem .Finally, a numerical case using fault sampling method under imperfect maintenance is given and the number of faults and their occurrence time are obtained . Validity and feasibility of the proposed method is verified