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Solar thermal application is an effective approach to achieve carbon neutrality. The large scale water pit heat storage (PTES) is a key component to ensure the stability of large-scale solar thermal plants. Based on the model of type 1535-1301, this paper performs a 2D simulation investigation of the long-term thermal performance of PTES using Trnsys. The accuracy of this model was verified by comparison with measured data from the solar plant in Dronninglund, Denmark. The results show that the average error between the model and the actual measurements is only 3%. In addition, it can be found that the PTES average temperature decreases from 24°C to 12°C before the 80th day due to heat losses. During the charging period from the 80th to 250th days, the PTES average temperature increases to 68°C. In which the PTES formed a temperature stratification with 80°C at the top and 40°C at the bottom. The sloping soil temperature boundary expands and shows a non-uniform stratification of 70-10°C with 10m thickness. The average temperature of the PTES gradually decreases to 16°C during the discharge period after the 250th day. The actual charging and discharging energy are 11,868 MWh and 11,250 MWh per year, respectively, and the total heat loss is 1,157 MWh. The storage efficiency is as high as 90.1% because PTES is used for both long-term and short-term energy storage. This paper reveals the dynamic thermal process of PTES throughout the year to provide a reference for designers.

Carrots are widely used in home cooking and vegetable processing industries because of their high nutritional value. However, different processing methods may produce a negative impact on carrot texture and nutrition quality. Therefore, the development of better processing methods to preserve the texture and nutrition quality of carrots will be beneficial to the carrot industry.The effects of heat and pulsed electric field (PEF) treatments with different heat temperatures (T) and holding time (tThe results show that PEF heating is beneficial in preventing changes in physicochemical and nutritional properties of carrots compared to traditional heat treatment. PEF has potential as a heating technology in the food industry. © 2022 Society of Chemical Industry.

Background Platymonas helgolandica var. Tsingtaoensis (P. helgolandica) is a marine microalga. It can produce a large amount of starch, especially amylose, with addition of carbon source and specific circadian rhythm. The mechanism behind this phenomenon is still unclear. Analysis of this mechanism can help to develop P. helgolandica into a new green bioengineering chassis organism. Result We explained how circadian rhythm and glucose affect the rate of starch accumulation and starch structure in P. helgolandica based on the transcriptome. The glucose inhibited the photosynthetic system of P. helgolandica, while the circadian rhythm can alleviate the inhibition. Circadian rhythm induced the up-regulation of Embden-Meyerhof-Parnas (EMP) pathway and pentose phosphate pathway (PPP) in P. helgolandica, but had little effect on the tricarboxylic acid cycle (TCA cycle). PPP pathway provides Ribulose-1,5-bisphosphate (RuBP), which may be beneficial for dark reactions and nucleotide synthesis. And PPP pathway provides Nicotinamide adenine dinucleotide phosphate (NADPH), which facilitates energy substance synthesis. This will further upregulate the starch metabolic pathway. The transcript level of the key gene ADP-Glucose pyrophosphorylase (AGPase) is mainly regulated by glucose. The granule-bound starch synthase (gbss), a key gene for amylose synthesis, is mainly influenced by circadian rhythm. In general, the increase of starch synthesis and amylose ratio requires both glucose addition and circadian rhythm. Conclusion We report the first referenced transcriptome of P. helgolandica. Differences between transcripts reveal how circadian rhythm and glucose addition affected the rate of starch synthesis and structural variation. It provides a reference for an in-depth study of starch synthesis in green algae.

Microalgae are known to be abundant in various habitats around the globe, and are rich in high value-added products such as fatty acids, polysaccharides, proteins, and pigments. Microalgae can be exploited as the basic and primitive food source of aquatic animals. We investigated the effects of dietary supplementation with Schizochytrium sp., Spirulina platensis, Chloroella sorokiniana, Chromochloris zofingiensis, and Dunaliella salina on the growth performance, immune status, and intestinal health of zebrafish (Danio rerio). The results showed that these five microalgae diets could improve the feed conversion rate (FCR), especially the D. salina (FCR = 1.02%) and Schizochytrium sp. (FCR = 1.20%) additive groups. Moreover, the microalgae diets decreased the gene expression level of the pro-inflammatory cytokines IL6, IL8, and IL1β at a normal physiological state of the intestine, especially the Schizochytrium sp., S. platensis, and D. salina dietary groups. The expression of neutrophil marker b7r was increased in the C. sorokiniana diet group; after, the zebrafish were challenged with Vibrio anguillarum, improving the ability to resist this disease. We also found that microalgae diets could regulate the gut microbiota of fish as well as increase the relative abundance of probiotics. To further explain, Cetobacterium was significantly enriched in the S. platensis additive group and Stenotrophomonas was higher in the Schizochytrium sp. additive group than in the other groups. Conversely, harmful bacteria Mycoplasma reduced in all tested microalgae diet groups. Our study indicated that these microalgae could serve as a food source supplement and benefit the health of fish. KEY POINTS: • Microalgae diets enhanced the growth performance of zebrafish. • Microalgae diets attenuated the intestinal inflammatory responses of zebrafish. • Microalgae diets modulated the gut microbiota composition to improve fish health.

Supporting Artificial Intelligence (AI)-enhanced intelligent applications on the resource-limited Unmanned Aerial Vehicle (UAV) platform is difficult due to the resource gap between the two. It is promising to partition an AI application into a service function (SF) chain and then dispatch the SFs onto multiple UAVs. However, it is still a challenging task to efficiently schedule the computation and communication resources of multiple UAVs to support a large number of SF chains (SFCs). Under the multi-UAV edge computing paradigm, this paper formulates the SFC scheduling problem as a 0–1 nonlinear integer programming problem. Then, a two-stage heuristic algorithm is put forward to solve this problem. At the first stage, if the resources are surplus, the SFCs are deployed to UAV edge servers in parallel based on our proposed pairing principle between SFCs and UAVs for minimizing the completion time sum of tasks. In contrast, a revenue maximization heuristic method is adopted to deploy the arrived SFCs in a serial service mode when the resource is insufficient. A series of experiments are conducted to evaluate the performance of our proposal. Results show that our algorithm outperforms other benchmark algorithms in the completion time sum of tasks, the overall revenue, and the task execution success ratio

Water pit heat storage has been proven a cheap and efficient storage solution for solar district heating systems. The 60,000 m3 pit storage in Dronninglund represents in many ways the state-of-the-art large-scale heat storage, demonstrating a storage efficiency higher than 90% during its operation. The storage is used for seasonal and short-term heat storage of solar heat generated by a 37,573 m2 solar collector field and supplies heat directly to the district heating grid or is used during winter as an alternative heat source to a heat pump. This study aims to provide an overview of the available information on the Dronninglund water pit heat storage, including a detailed description of the design, ground conditions, and operating strategy. The used dataset (2014–2020) has been the foundation for most investigations and simulations of pit thermal energy storages. However, due to a lack of public documentation, various studies have used different post-processing methods and assumptions, leading to inconsistent results. Therefore, the dataset has been manually quality-controlled, and erroneous data have been removed with the aim of establishing a high-quality reference dataset. Moreover, an overview of the available parameters and metadata is provided, along with example plots. To promote the usage of the quality-controlled dataset, all the developed quality-control routines and Python scripts are made available on GitHub.

Recognizing signals is critical for understanding the increasingly crowded wireless spectrum space in noncooperative communications. Traditional threshold or pattern recognition-based solutions are labor-intensive and error-prone. Therefore, practitioners start to apply deep learning to automatic modulation classification (AMC). However, the recognition accuracy and robustness of recently presented neural network-based proposals are still unsatisfactory, especially when the signal-to-noise ratio (SNR) is low. In this backdrop, this paper presents a hybrid neural network model, called MCBL, which combines convolutional neural network, bidirectional long-short time memory, and attention mechanism to exploit their respective capability to extract the spatial, temporal, and salient features embedded in the signal samples. After formulating the AMC problem, the three modules of our hybrid dynamic neural network are detailed. To evaluate the performance of our proposal, 10 state-of-the-art neural networks (including two latest models) are chosen as benchmarks for the comparison experiments conducted on an open radio frequency (RF) dataset. Results have shown that the recognition accuracy of MCBL can reach 93% which is the highest among the tested DNN models. At the same time, the computation efficiency and robustness of MCBL are better than existing proposals.

Cyanobacteria can utilize CO2 or even N2 to produce a variety of high value-added products efficiently. Plastoquinone (PQ) is an important electron carrier in both of the photosynthetic and respiratory electron transport chain. Although the content of PQ, as well as their redox state, have an important effect on physiology and metabolism, there are relatively few studies on the synthesis of PQ and its related metabolic regulation mechanism in photosynthetic microorganisms. In this study, the strategies of overexpression of Geranyl diphosphate: 4-hydroxybenzoate geranyltransferase (lepgt) and addition of 4-hydroxybenzoate (4-HB) as the quinone ring precursor were adopted to regulate the biosynthesis of PQ in Synechocystis PCC 6803. Combined with the analysis the photosystem activity, respiration rate and metabolic components, we found the changes of intracellular PQ reprogrammed the metabolism of Synechocystis PCC 6803. The results showed that the overexpression of lepgt reduced PQ content dramatically, by 22.18%. Interestingly, both of the photosynthesis and respiration rate were enhanced. In addition, the intracellular lipid and protein contents were significantly increased. Whereas, the addition of low concentrations of 4-HB enhanced the biosynthesis of PQ, and the intracellular PQ contents were increased by 14.76%–70.86% in different conditions. Addition of 4-HB can regulate the photosystem efficiency and respiration and reprogram the metabolism of Synechocystis PCC 6803 efficiently. In a word, regulating the PQ biosynthesis provided a novel idea for promoting the reprogramming the physiology and metabolism of Synechocystis.

Moisture sources release wet-components into and absorb from the indoor air, affecting the occupant health, air-conditioning energy-consumption, and building service-life. Considering the strong dynamic features of wet-component’s evaporation and diffusion, we propose indexes CRI(H)t and CRI(C)t, which can accurately describe dynamical effects of sources on the indoor-environment. Taking a humidifier as a source, we subsequently compare the indexes under various source-parameters and environmental conditions. The results show that according to the variation of CRI(H)t and CRI(C)t, the process of sources influencing humidity and temperature field can be subdivided into rapid-increase/stable-increase/stable stage and decrease/increase stage. The variability and time-ratio of indices can provide a comprehensive understanding of sources with various intensities and water-temperatures affecting the indoor environment at different atmospheric-pressures, temperatures, and humidity. This study will be beneficial for the establishment of transient indoor environmental models, regulation of air-conditioning systems, and sustainable control of indoor environment.

Microalgae has been regarded as a promising method for reducing CO

Latent heat thermal energy storage (LHTES) with Phase Change Materials (PCM) represents an interesting option for Thermal Energy Storage (TES) applications in a wide temperature range. A tubular encapsulation model of an LHTES with PCM was developed, and the calculated data were analyzed. In addition, a parametric analysis for the preferable system geometry is presented. Organic paraffin RT18 with a melting point of 18 ◦C was utilized as PCM for different geometries of LHTES, and the addition of internal and external fins and their influence on LHTES thermal conductivity was investigated. One-step heat exchange from outdoor air to PCM and from PCM to water characterizes the LHTES system in solidification and melting processes, respectively. A 2D axisymmetric model was developed using Comsol Multiphysics 6.0. The LHTES unit performance with PCM organic paraffin RT18 encapsulated in electrospun fiber matrices was analyzed. The study results show that longer internal fins shorten the melting and solidification time. The phase change process was accelerated by 31.12% in the charging compared to the case with no fins of the same external tube diameter. Direct contact of PCM electrospun fiber matrix with 23 ◦C water showed instant melting, and the phase change process was accelerated by 99.97% in the discharging cycle. Latent heat thermal energy storage (LHTES) with Phase Change Materials (PCM) represents an interesting option for Thermal Energy Storage (TES) applications in a wide temperature range. A tubular encapsulation model of an LHTES with PCM was developed, and the calculated data were analyzed. In addition, a parametric analysis for the preferable system geometry is presented. Organic paraffin RT18 with a melting point of 18 °C was utilized as PCM for different geometries of LHTES, and the addition of internal and external fins and their influence on LHTES thermal conductivity was investigated. One-step heat exchange from outdoor air to PCM and from PCM to water characterizes the LHTES system in solidification and melting processes, respectively. A 2D axisymmetric model was developed using Comsol Multiphysics 6.0. The LHTES unit performance with PCM organic paraffin RT18 encapsulated in electrospun fiber matrices was analyzed. The study results show that longer internal fins shorten the melting and solidification time. Direct contact of PCM electrospun fiber matrix with 23 °C water showed instant melting, and the phase change process was accelerated by 99.97% in the discharging cycle.

Background: Premature ventricular complexes (PVCs) from the proximal left bundle branch (LBB) can be ablated in the left ventricular outflow tract but can easily damage normal conduction bundles. Here, we report a case of successful ablation of PVCs from the proximal LBB within the right coronary cusp (RCC). Case presentation: Our patient was a 70-year-old woman with PVCs from the proximal LBB that were successfully ablated via the RCC through radiofrequency catheter ablation with a 3D mapping system; she had a complication of incomplete right bundle branch block (RBBB) and remained asymptomatic during follow-up. Conclusion: The RCC provides an alternative approach for ablating PVCs originating from the proximal LBB, owing to the close relationship between the RCC and proximal LBB.

Microalgae are cosmopolitan organisms in nature with short life cycles, playing a tremendous role in reducing the pressure of industrial carbon emissions. Besides, microalgae have the unique advantages of being photoautotrophic and harboring both prokaryotic and eukaryotic expression systems, becoming a popular host for recombinant proteins. Currently, numerous advanced molecular tools related to microalgal transgenesis have been explored and established, especially for the model species Chlamydomonas reinhardtii (C. reinhardtii hereafter). The development of genetic tools and the emergence of new strategies further increase the feasibility of developing C. reinhardtii chloroplasts as green factories, and the strong genetic operability of C. reinhardtii endows it with enormous potential as a synthetic biology platform. At present, C. reinhardtii chloroplasts could successfully produce plenty of recombinant proteins, including antigens, antibodies, antimicrobial peptides, protein hormones and enzymes. However, additional techniques and toolkits for chloroplasts need to be developed to achieve efficient and markerless editing of plastid genomes. Mining novel genetic elements and selectable markers will be more intensively studied in the future, and more factors affecting protein expression are urged to be explored. This review focuses on the latest technological progress of selectable markers for Chlamydomonas chloroplast genetic engineering and the factors that affect the efficiency of chloroplast protein expression. Furthermore, urgent challenges and prospects for future development are pointed out.

Compared with the well-studied cations, the development of methods for anion detection is relatively slow due to the anion characteristics such as a complex geometry, strong hydration and a low charge density. Herein, a colorimetric and ratiometric fluorescent anion sensing platform based on trihexyltetradecylphosphonium chloride ([THTP][Cl]) was developed for the first time. Such nanosensors exhibited a pH response of 5-7 as well as a high selectivity to perchlorate. The selectivity behavior followed the Hofmeister series in which lipophilic anions were more readily co-extracted. To deviate from the Hofmeister series, anion ionophores should be introduced for selective complexation of the target anions. As a proof of concept, the organomercury compounds ETH9033 and ETH9009 were employed as model ionophores. The obtained nitrate- and chloride-selective [THTP][Cl]-based nanosensors demonstrated prominent colorimetric and spectroscopic transformations specifically induced by the anion species. The fluorescence (

Metal-organic frameworks (MOFs) are porous crystalline materials assembled from organic ligands and metallic secondary building blocks. Their special structural composition gives them the advantages of high porosity, high specific surface area, adjustable pore size, and good stability. MOF membranes and MOF-based mixed-matrix membranes prepared from MOF crystals have ultra-high porosity, uniform pore size, excellent adsorption properties, high selectivity, and high throughput, which contribute to their being widely used in separation fields. This review summarizes the synthesis methods of MOF membranes, including in situ growth, secondary growth, and electrochemical methods. Mixed-matrix membranes composed of Zeolite Imidazolate Frameworks (ZIF), University of Oslo (UIO), and Materials of Institute Lavoisier (MIL) frameworks are introduced. In addition, the main applications of MOF membranes in lithium–sulfur battery separators, wastewater purification, seawater desalination, and gas separation are reviewed. Finally, we review the development prospects of MOF membranes for the large-scale application of MOF membranes in factories.

Eukaryotic microalgae are important primary producers in nature that play an important role in the energy cycle of nature. The eukaryotic microalgae are also regarded as potential bioactive substance producers. In recent years, with the aid of genetic engineering, eukaryotic microalgae have found a wider range of potential applications in medicine, food, health products, cosmetics, and environmental protection. This article reviews the state of the art of microalga genetic engineering from the aspects of gene transfer system, gene editing technology, and screening method, with examples of the enhancement of lipids, carotenoids, polysaccharide, and functional proteins. Potential application scenarios of microalga genetic engineering and their products in the field of food and medicine are also highlighted. Furthermore, strategies for protein expression optimization in eukaryotic microalgae are reviewed. The existing shortcomings of eukaryotic microalga genetic engineering are also analyzed and highlighted.

The uneven (flow) resistance of branched pipes commonly causes local overheating and freezing in solar collector fields. In this paper, the resistance characteristics of the direct return flat plate solar collector field are studied using a numerical model. The accuracy of the model is verified with experimental data, and the maximum relative error is below 10%. A new evaluation index, the ratio of resistance imbalance rate to efficiency (RRIRE), is introduced. In this way, it is possible to comprehensively evaluate the effect of different factors (configuration, flow rate per unit heat collection area, inlet temperature, working medium) on both the resistance characteristics and efficiency of the solar collector field. The results show that, when the number of rows (Nrow) exceeds the number of collectors in each row (Ncol), the inlet temperature is below 40 °C. In addition, the flow rate per unit heat collection area is below 0.06 m3/(h m2). Hence, the RRIRE is smaller and the system has better resistance efficiency. Considering the viscosity change due to the temperature change in the fluid of the solar collector field, a new temperature difference correction method is proposed. This makes it possible to calculate the frictional drag for a fluid in the collector field, which allows a more realistic calculation of flow resistance. This study lays the foundation for improved layout design and parameter optimization in solar collector fields.

Apple pomace, a solid waste produced during industrial processing of apple juice or cider, is a rich source of high value-added compounds such as polyphenols. This review summarizes present studies on the qualitative and quantitative methods, including Folin-Ciocalteu colorimetric, high pressure liquid chromatography (HPLC) and fluorescence spectrum, as well as enhanced extraction methods of polyphenols in apple pomace by different traditional and novel technologies, including ultrasounds (US), microwave (MW), pulsed electric fields (PEF), high voltage electrical discharges (HVED) and enzyme. The principles and characteristics of different effective enhanced extraction technologies of polyphenols in apple pomace were compared. In addition, the different cell disruption analysis methods, such as destructive detection method (electrical conductivity disintegration index

In recent years, reputation management schemes have been proposed as promising solutions to alleviate the blindness during peer selection in distributed P2P environment where malicious peers coexist with honest ones. They indeed provide incentives for peers to contribute more resources to the system and thus promote the whole system performance. But few of them have been implemented practically since they still suffer from various security threats, such as collusion, Sybil attack and so on. Therefore, how to detect malicious peers plays a critical role in the successful work of these mechanisms, and it will also be our focus in this paper. Firstly, we define malicious peers and show their influence on the system performance. Secondly, based on Multiscale Principal Component Analysis (MSPCA) and control chart, a Subspace based MAlicious peeRs deTecting algorithm (SMART) is brought forward. SMART first reconstructs the original reputation matrix based on subspace method, and then finds malicious peers out based on Shewhart control chart. Finally, simulation results indicate that SMART can detect malicious peers efficiently and accurately.

The aim of the study is to investigate the influence of geometry on the thermal capacity and stratifications of a water pit heat storage for solar district heating. A TRNSYS component model for a truncated cone water pit was developed based on the coordinate transformation method and validated by experimental results from the water pit heat storage in Huangdicheng in 2018. The thermal performance of 26 water pits with different heights and side wall slopes was calculated for 10 consecutive years. It takes four to six years for the water pit to reach steady-state operation. The operation data from the tenth year was selected to evaluate the thermal performance of each configuration. The results show that because of the thermal insulation on top of the water pit, the height to diameter ratio of a water pit with minimum annual heat loss was always smaller than 1.0. The annual storage efficiency of a water pit increases with side wall slope due to the reduced side wall area. There is an almost linear increase in the thermal stratification number of a water pit with height. With an increase in the height, thermal stratification in water pits with a steeper slope increased more gradually than water pits with a lower slope. The findings in this paper are relevant for the design optimization of water pits as seasonal thermal energy storages.

The paper summarizes the implementation experiences and lessons learned from the solar water heating (SWH) system mandatory installation policy in China. In-depth interviews, questionnaire surveys and field investigation were conducted to understand the prevailing attitudes of the stakeholders associated with the application of SWH in buildings. Scenario analysis was used to analyze the effect of expanding the coverage of mandatory installation policies. The results show that due to the strong market externalities of SWH building applications, the government must provide inducements to stakeholders through mandatory policies or fiscal incentives to create an impetus for them to use SWH extensively. For China, it is necessary to strengthen and support the utilization of renewable energy policies and extend the mandatory installation policy of SWH systems to taller buildings to fulfill the national renewable energy application goals. The most reasonable technical route, full process control, and attention to system operation and maintenance are the three key factors for the successful implementation of a mandatory installation policy for SWH systems. The policy recommendations presented in this paper can not only be applied to China but also other developing countries as well.

The photovoltaic (PV) roofs have two main energy-saving effects, which are shading and power supply. Considering the shading and power generation gain jointly, a roof is changed from the building energy end to the building energy supply end, thus changing its energy use system greatly. Therefore, this paper carries out research on the comprehensive energy-saving effect integrating the shading and the power supply gain. Three types of PV rooftops, namely, horizontally-mounted overhead PV rooftop, tilted overhead PV rooftop, and attached PV rooftop are studied to explore their impacts on the heat gain and heat loss of the roof and building’s heating and cooling load. In order to estimate the overall energy-saving in different climatic regions in China, an overall energy-saving evaluation method that considers the power generation and shading benefit effects of the PV rooftop is proposed. Based on the climate and solar radiation zones in China, 13 respective cities are selected to be included in the research. The results show that, by considering only the shading effect of PV panels, the tilted PV is more suitable in summer, reducing the heat input, whereas the horizontally-mounted PV is more effective in winter to prevent more heat loss. Regarding the overall energy-saving that considers both the shading and power generation effects of PV panels, building with horizontally-mounted PV rooftop has the highest efficiency in the summer season, while the building with tilted PV rooftop has the highest efficiency in the winter season. The model and analysis of the overall energy-saving presented in this work can provide a guide for the application of rooftop solar PV panels in different climate zones in China.

The ground thermal properties and borehole thermal resistance are the essential parameters for the design of borehole heat exchanger (BHE) field, and they are usually estimated using the experimental inlet/outlet fluid temperatures of BHE in thermal response test (TRT). This paper proposes the coupled two-step parameter estimation procedure (TSPEP) for estimating ground thermal conductivity and borehole thermal resistance of BHE by evaluating the actual averaged–over-the –depth mean fluid temperature (MFT) using the quasi-three-dimensional model inside the borehole. The simulated annealing algorithm (SAA) is used to iteratively find the minimum values of the two objective functions to obtain the optimal estimated results. In TSPEP, the estimated ground volumetric heat capacity and weighted factor f in the 1st step are transferred to calculate MFT using the experimental data in the 2nd step, which guarantees the direct approach based on the infinite line source model (ILSM)applied to improve the accuracy of the estimated borehole thermal resistance. For 50 m depth BHE, the estimated borehole thermal resistance is increased by 12.1% using TSPEP than the effective borehole thermal resistance evaluated by the arithmetic average fluid temperature (AFT). The estimated ground thermal conductivity in TSPEP is almost same with that from the direct approach based on ILSM, and the maximum relative error between them is only 0.91% even though borehole depth of BHE changes from 50 m to 200 m.