Search

Supercritical fluids (e.g., hydrocarbon fuels, water, carbon dioxide, and organic working medium, etc) have been recognized as working media to improve thermal efficiencies in power cycles and energy conversion, and have been used or selected as the working fluids in engineering fields such as aerospace, nuclear power, solar energy, refrigeration, geothermal energy, chemical technology, and so on. To better understand the interesting characteristic or abnormal behaviors of supercritical fluids, most valuable research works (including experimental results and numerical studies) from domestic and abroad have been documented. As such, this paper presents a comprehensive review on heat transfer behaviors of some supercritical fluids in engineering applications. This review focuses on recently available articles published mainly from 2016 up to the present time. The common problems (i.e., heat transfer enhancement and heat transfer deterioration particularly for the supercritical hydrocarbon fuels) in the supercritical field are summarized and some perspectives on future prospects are also included.

Chronic hepatitis B is one of the common chronic infectious diseases in China, which seriously endangers people’s health. Liver fibrosis is a common pathological process of chronic hepatitis B. The routine diagnosis and prediction of the degree of liver fibrosis are of great value and significance to the judgment of liver disease, clinical treatment, and the corresponding late evaluation. However, the traditional detection and treatment methods are often invasive, and the corresponding diagnosis and treatment costs are very high, which makes it difficult for the corresponding patients in clinical and practical applications to accept, and the corresponding liver tissue samples are relatively limited in technology. In this paper, based on ultrasound elastography technology, it will give full play to its advantages of real-time, non-invasive, and repeatable detection, and realize an effective method for non-invasive diagnosis of liver fibrosis. In the practical application, this paper mainly focuses on the study and analysis of the patients with hepatitis B liver fibrosis using the RTE ultrasonic elastic imaging technology. Following this, 120 patients with chronic hepatitis B were selected for the experiment, and a non-invasive diagnostic model of ultrasonic elastic imaging based on a support vector machine was proposed. The experimental results showed that the diagnostic model proposed in this paper improves the diagnostic accuracy by 5% compared with the traditional diagnostic technology, while the corresponding specificity, positive predictive value, and diagnostic advantage are improved. Therefore, as a whole, the ultrasound elastic imaging model proposed in this paper could realize the efficient diagnosis of hepatitis B liver fibrosis and is conducive to the clinical management.

The manufacturing industry undergoes a new age with major changes taking place on several fronts. Companies devoted to digital transformation take their future plants inspired by the Internet of Things (IoT). The IoT is a worldwide network of interrelated physical devices,which is an essential component of the internet, including sensors, actuators, smart apps, computers, mechanical machines, and people. The effective allocation of the computing resources and the carrier is critical in the industrial internet of Things (IIoT) for smart production systems. Indeed, the existing assignment method in the smart production system cannot guarantee that resources meet the inherently complex and volatile requirements of the user are timely. Many research results on resource allocations in auction formats which have been implemented to consider the demand and real-time supply for smart development resources, but safety privacy and trust estimation issues related to these outcomes are not actively discussed. The paper proposes a Hierarchical Trustful Resource Assignment (HTRA) and Trust Computing algorithm (TCA) based on Vickrey–Clarke–Groves (VGCs) in the computer carriers necessary resources to communicate wirelessly among IIoT devices and gateways, and the allocation of CPU resources for processing information at the CPC. Finally, experimental findings demonstrate that when the IIoT equipment and gateways are effective, the utilities of each participant are improved.

BACKGROUND AND OBJECTIVE: The effects of corticosteroid treatment on non-severe COVID-19 pneumonia patients are unknown. To determine the impacts of adjuvant corticosteroid administrated to patients with non-severe COVID-19 pneumonia. METHOD: A retrospective cohort study based on propensity score analysis was designed to explore the effects of corticosteroid on several clinical outcomes. RESULTS: One hundred thirty-two patients satisfied the inclusion criteria and 35 pairs were generated according to propensity score matching. Compared to non-corticosteroid group, the CT score on day 7 was significantly higher in corticosteroid group (8.6 (interquartile range [IQR], 2.8-11.5) versus 12.0 (IQR, 5.0-19.3), P = 0.046). In corticosteroid group, more patients progressed to severe cases (11.4% versus 2.9%, P = 0.353), hospital stay (23.5 days (IQR, 19-29 d) versus 20.2 days (IQR, 14-25.3 d), P = 0.079) and duration of viral shedding (20.3 days (IQR, 15.2-24.8 d) versus 19.4 days (IQR, 11.5-28.3 d), P = 0.669) were prolonged, while fever time (9.5 days (IQR, 6.5-12.2 d) versus 10.2 days (IQR, 6.8-14 d), P = 0.28) was shortened; however, all these data revealed no statistically significant differences. CONCLUSION: Corticosteroid might have a negative effect on lung injury recovery in non-severe COVID-19 pneumonia patients; however, the results of this study must be interpreted with caution because of confounding factors.

Hereditary spastic paraplegias (HSP) are a group of rare neurodegenerative diseases characterized by progressive spastic paraparesis. UBAP1 was recently found to induce a rare type of HSP (SPG80). We identified a family with eight inherited spastic paraplegic patients carrying a novel heterozygous mutation c.279delG (p.S94Vfs*9) of UBAP1. We demonstrated a lack of functional UBAP1 in these patients, resulting in the neurological disorder caused by interceptions of the ESCRT pathway. Extending from the older onset-age identified from this family, we found that comparing with the European and other populations, Asian patients displayed less proportion of severe patients and an older average age at onset. The origins of SPG80 patients associated with both their onset age and their disease severity, while the age at onset was not correlated with the disease severity.

Building and infrastructure construction projects can be viewed as a complex system consisting of many subsystems. Over the last two decades, considerable researches that use system dynamics (SD) as an analytical and modeling approach exist to address construction project management issues. However, only few critical reviews have been conducted to provide an in-depth understanding of SD application in construction project management. Moreover, many studies have failed to apply SD accurately. Therefore, the present study aims to gain an understanding of the current state of play and future directions in applying SD method in construction project management research, by undertaking a comprehensive review of 105 relevant articles published from 1994 to 2018. These articles are analyzed in terms of annual publication rate, key papers and their contribution, critical issues in SD application, and research topics. A significant increase in the number of publications in the last five years has been observed. When applying SD method to model construction system, the following aspects must be carefully considered: Model boundary, model development, model test, and model simulation. In addition, SD has been applied in a wide range of research topics, including (1) sustainable construction; (2) design error, rework, and change management; (3) risk management; (4) resource management; (5) decision making; (6) hybrid modeling; (7) safety management; (8) PPP project; and (9) organization performance. Based on the review findings, this study discusses three future research directions, namely, integration of SD with other methods, uncertainty analysis, and human factor analysis. This study can help researchers gain an in-depth understanding of the critical issues in the application of SD in construction management and the state-of-the-art of SD research.

Formamidinium lead iodide-based (FAPbI3 ) perovskite is widely used in the field of photovoltaics, owing to its suitable bandgap (ca. 1.45 eV) and better thermal stability. FAPbI3 has two polymorphs (black α-FAPbI3 and yellow δ-FAPbI3 ) at ambient temperature. The yellow δ-FAPbI3 , which has no photoactivity, has a chain-like structure that likely hinders electron transport and reduces photovoltaic performance. However, pure-phase black α-FAPbI3 without any yellow phase is difficult to obtain and the underlying mechanism of the phase transition is rarely investigated. In this study, a facile bi-additive method (BA method) has been developed to completely eliminate the yellow δ-FAPbI3 phase by inducing a phase transition from δ-FAPbI3 to α-FAPbI3 . HI and Pb(SCN)2 were employed as dual additives. Based on the investigation of the annealing time and temperature, we determined that the BA method can induce the phase transition and enhance the stability of α-FAPbI3 . Owing to the enhanced crystallization as well as uniform morphology of the BA film, the perovskite solar cells (PSCs) exhibited an increased power conversion efficiency (PCE). Furthermore, the optimal devices displayed excellent stability and maintained over 80 % of initial PCE after aging for 400 h in air. This work provides a new insight into the fabrication of high-quality pure α-FAPbI3 perovskite films and makes high efficiency photovoltaic devices a reality.

The redevelopment of urban villages is a prominent part of urban renewal in China, which has attracted much attention from the academic community. However, the understanding of when and where the redevelopment of urban villages occurs is still limited partly because of the lack of empirical analysis. Through exploratory spatial data and overlay analyses, this study examines the spatio-temporal distribution characteristics based on data from 277 urban village redevelopment projects in Shenzhen, China, between 2010 and 2018. Results demonstrate that the redevelopment of urban villages occurs in central and suburban areas but rarely occurs in the periphery of the city. The overall spatial distribution is spatially clustered, having become increasingly significant from 2010 to 2018. In the beginning, the redevelopment of urban villages was dispersed in diverse areas and partly expanded into adjacent neighbourhoods. A majority of redevelopment took place in areas near the planning urban centres and the planning subway stations, which are almost in Density Zones I–III. The findings of this study contribute to new spatio-temporal perspectives in the global process mechanism of urban village redevelopment and call for special attention to the significant influences of state intervention, which is an informative reference for future sustainable urban development.

Background Clinical symptoms of adults and paediatric inpatients with COVID‐19 disease are conflicting. This meta‐analysis was conducted to assess the effect of age of COVID‐19 inpatient on the severity of the disease. Methods A systematic literature search up to January 2021 was performed and 5 studies included 910 inpatients with COVID‐19 disease at the baseline of the study; 773 of them were adult inpatients, and 137 of them were paediatric inpatients. They reported a comparison between adults and children with COVID‐19 in the level of symptomatic severity, clinical features, computed tomography (CT) results and laboratory results. Odds ratio (OR) with 95% confidence intervals (CIs) were calculated assessing the effect of age of COVID‐19 inpatient on the severity of the disease using the dichotomous method with a random or fixed‐effect model. Results Adults with COVID‐19 disease had significantly lower number of mild cases (OR, 0.18; 95% CI, 0.04‐0.77, P = .02); higher number severe cases (OR, 4.90; 95% CI, 2.03‐11.83, P

Reducing energy consumption in buildings through behavioural changes has been regarded as a relatively low-cost and sustainable method. However, studies that focus on occupant building energy consumption in student residences are few. In the context of shared residences, the energy behaviour could be very different. This is because student–student and student–building system interactions are complex. To address this research gap, this study developed an agent-based simulation model regarding students as heterogeneous individuals. Simulation parameters include student basic information, status of staying at dormitories and applicances using behaviours. All data were obtained from a university campus in Shenzhen, China. Energy-saving scenarios under different strategies were simulated, including different energy-saving strategies and interaction behaviour energy-saving advertising. Results show that (1) occupancy is the most important factor for dormitory energy consumption; (2) reducing the time of air conditioner use has the largest impact on energy-saving; (3) reducing computer standby time has a great energy-saving potential; (4) students’ attitude and awareness of energy conservation and the communication and exchange of energy information amongst students play an important role in energy saving. According to these results, the university can take measures to promote energy saving, which include strengthening education, establishing a energy saving championship system for dormitory energy consumption and implementing a reward-and-punishment mechanism.

The Organic Rankine Cycle (ORC) system is a rather promising technology for waste heat recovery. However, waste heat source generally presents a fluctuating behavior, which is a big challenge to the security and efficiency of the ORC. An improved dynamic model of ORC system with zeotropic mixture is firstly developed, which can be better adapted to the phase change process of working fluid. Accordingly, dynamic behavior of the ORC and dynamic distribution of evaporation stages are investigated. Besides, three control strategies are proposed to improve the performance of steadiness with external controllable conditions. Results show that a sudden abnormal change occurs in specific enthalpy of working fluid at the evaporator outlet when different disturbances are imposed to the system. It is found that the proposed control strategies are adapted to different heat source fluctuation. The control strategies with feedforward control system work well with low frequency variation of heat source temperature.

Supercritical CO2 Rankine cycle has great development potential as a power cycle for converting low-grade thermal energy into electricity. Better understanding of supercritical CO2 heat transfer in helically coiled tubes (HCTs) is required for design and operation of supercritical CO2 Rankine cycle power systems. In this work, the SST k∼ ω model is employed. A new dimensionless buoyancy parameter Ψ is proposed which denotes the ratio of gravitational buoyancy force to overall curvature effect. Furthermore, a flow regimes map is proposed based on the inclination angle of the dividing streamline between the two vortexes and buoyancy parameter Ψ . The mixed convection region in HCT is decomposed into a gravitational buoyancy force dominated heat transfer region (B Region α > 45 ° ) and a curvature effect dominated heat transfer region (C Region α 45 ° ). Subsequently, the effects of HCT geometry on heat transfer mechanisms are respectively investigated in B and C Region, which help us better understanding the relationship of the buoyancy criterion and flow characteristics. The results indicate that the effects of coiled pitch and coiled diameter on heat transfer can be neglected in B Region. In C Region, the heat transfer is suppressed as coiled pitch increases and it will appear oscillation when torsion effect is strong enough. In addition, the heat transfer is enhanced with curvature increases but except for near the pseudo-critical region.

Background Valproic acid (VPA) is a clinical medicine primarily prescribed to control epileptic symptoms. VPA has potential side-effects, such as hepatotoxicity. Fibroblast growth factor 21 (FGF21) is a functional cytokine for metabolic regulation. In this article, we aimed to evaluate the possible clinical application of FGF21 in VPA-treated livers in early undetected liver injury (EULI). Methods Methodologically, plasma samples of VPA-treated epileptic patients were isolated for biochemical and high-performance liquid chromatography tests. In addition, VPA-dosed mice were subjected to determinations of serological parameters, key regulatory effectors and FGF21 expressions through biochemical analyses, enzyme-linked immunosorbent assay, immunohistochemistry stain, immunofluorescence stain, and reverse transcription-polymerase chain reaction (RT-PCR) test, respectively. Results The serological data suggested that VPA-treated epileptic patients showed visibly elevated FGF21 contents in plasma samples. However, other diagnostic parameters showed inconspicuous changes. As revealed in animal study, VPA-dosed mice exhibited undetected morphological alterations and hormonal changes in the liver, pancreas, and kidneys. Furthermore, serological parameters and key regulatory proteins in VPA-dosed livers and controls showed inconspicuous changes. Interestingly, endogenous FGF21 expressions in VPA-dosed mice were increased in sera. In further experiments, the findings showed that intracellular expressions of FGF21 mRNA and protein were upregulated in VPA-dosed livers as revealed in RT-PCR and immunoassay. Conclusions Taken together, these preliminary data reveal that functional FGF21 cytokine may serve as a potent predictor in VPA-related EULI.

Environmentally-friendly working fluid selection and multi-objective evaluation have been paid a great attention in organic Rankine cycle (ORC). Based on a modified analytic hierarchy process, a multi-factor evaluation method for trans-critical ORC (TORC) is developed first. The multi-factor indicator consists of eight indicators including energetic, exergetic, economic and environmental criteria (4E). The net power output, system efficiency, total exergy loss, exergy efficiency, cost per unit of time, electricity production cost, dynamic payback period, and emissions of CO2 equivalent (ECE) during life-time are considered. R134a, R32, R1270, R290 and R1234yf are selected as potential working fluids. The results show that the performance of R134a is the best followed by R32, R290, R1270 and R1234yf when only thermo-economic performances are considered. R290 shows the maximum comprehensive emission reduction of 8019 tons CO2, eq during life-time followed by R1270 being 7529 tons CO2, eq. The primary source of ECE from R134a, R32, R1270 and R290 is fluid leakage, accounting for over 68–83%. In multi-factor evaluation, R290 and R1270 exhibit higher feasibility level than R134a when the environmental impact is paid great attention. The multi-factor evaluation method is effective and valid to conduct comprehensive feasibility evaluation for decision-making.

The preferred cancer treatment is to achieve a high therapeutic effect as well as reduce side effects. In this study, we developed carrier-free nano drugs based on 5-fluorouracil (5FU) and cinnamaldehyde (CA) to meet the above goals. Two model drugs were spliced by acetal linkage and ester bond, which could self-assemble into nano drug particles (5FU–CA NPs) with a size of ∼170 nm. In vitro cell experiments showed 5FU–CA NPs were efficiently internalized by HepG2 cells. They then quickly exerted dual drug activities by the cleavage of acetal and ester bond, resulting in enhanced cell-killing efficacy and apoptosis. Synergistic mechanisms were achieved via the anti-metabolic effects mediated by 5FU–COOH and the oxidative damage induced by CA. In vivo anti-tumor evaluation further indicated that 5FU–CA NPs had higher tumor growth inhibition than 5FU–COOH/CA mixture (5FU–COOH + CA) and exhibited lower systemic toxicity under the same reducing dose of each drug. Overall, this is a successful synergistic anti-tumor attempt through rational self-assembly of drugs with different mechanisms and it can be extrapolated to other agents.

Histone deacetylase inhibitors are currently the most studied drugs because of their beneficial effects on inflammatory response. Emerging data from numerous basic studies and clinical trials have shown that histone deacetylase inhibitors can suppress immune-mediated diseases, such as graft-vs.-host disease (GVHD), while retaining beneficial graft-vs.-leukemia (GVL) effects. These drugs prevent and/or treat GVHD by modifying gene expression and inhibiting the production of proinflammatory cytokines, regulating the function of alloreactive T cells, and upregulating the function and number of regulatory T cells. Some of these drugs may become new immunotherapies for GVHD and other immune diseases.

The ad-ranking module is the core of the advertising recommender system. Existing ad-ranking modules are mainly based on the deep neural network click-through rate prediction model. Recently an innovative ad-ranking paradigm called DNN-MAB has been introduced to address DNN-only paradigms’ weakness in perceiving highly dynamic user intent over time. We introduce the DNN-MAB paradigm into our ad-ranking system to alleviate the Matthew effect that harms the user experience. Due to data sparsity, however, the actual performance of DNN-MAB is lower than expected. In this paper, we propose an innovative ad-ranking paradigm called DNN-VMAB to solve these problems. Based on vectorization and clustering, it utilizes latent collaborative information in user behavior data to find a set of ads with higher relativity and diversity. As an integration of the essences of classical collaborative filtering, deep click-through rate prediction model, and contextual multi-armed bandit, it can improve platform revenue and user experience. Both offline and online experiments show the advantage of our new algorithm over DNN-MAB and some other existing algorithms.

Background To evaluate the effect of Chrysanthemum morifolium Ramat. ethanol extract (CEE) on lipopolysaccharide induced acute lung injury in mice. Methods The ninety C57BL/6 J male mice randomly divided into five groups: control, model and CEE (50, 100, 200 mg/kg) groups for 7 days oral administration. At the last administration, all mice except control were intratracheal instilled with lipopolysaccharide (LPS, 3 mg/kg) for establish the acute lung injury. Then lung histopathologic, lung wet/dry weight, white blood cells, lymphocytes, neutrophils were detected. The pro-inflammation cytokine tumor necrosis factor-α (TNF-α), interleukin (IL)-6, anti-inflammatory cytokine transforming growth factor-β1 (TGF-β1), IL-10 and the marker of antioxides ability total-antioxidant capacity (T-AOC), malondialdehyde (MDA) in lung tissue were measured. Results The result showed that CEE could improve lung histopathological injury, reduce the ratio of wet/dry lung weight and lung index, inhibit the increased number of white blood cells, lymphocytes and neutrophils, and reduce the increased levels of TNF-α and IL-6. While CEE also significantly increased the levels of TGF-β1 and IL-10. Furthermore, CEE also markedly increased the activity of T-AOC, and decreased the contents of MDA with a dose-dependent manner. Conclusions The study exhibited that CEE has a potential protective effect on lipopolysaccharide induced acute lung injury in mice, the action mechanism of CEE may through balance of the pro-inflammatory and anti-inflammatory factors, and the oxygen free radicals inhibition.

Background and Aims: The abnormal liver function and even liver failure related death were reported in the COVID-19 patients, but less of studies focus on the dynamic liver function changes. We analysed the liver function indexes of COVID-19 patients to explore the characteristics of liver function changes in patients with different severity. Methods: This study included 54 moderate, 50 severe, and 31 death nucleic acid-confirmed COVID-19 patients hospitalized at the central hospital of Wuhan, China. Epidemiological histories, clinical features, imaging materials, medications and especially major liver function laboratory tests were collected for analysis. Results: The clinical symptoms did not present any significant difference in the patients at admission, but the older male patients had pronounced mortality risk. The normal ratio of ALT, TB, and DBIL of moderate patients was 96.3%, 94.44%, and 98.15% separately at the first test, but 59.26% of patients showed declined ALB levels. The normal ratio of all liver function indexes declined after admission, but most abnormalities were mild (1-2 times of upper limit unit) and went back normal before discharge. In severe patients, the normal ratio of ALB dropped down to 30.61% at admission along with the dramatic impaired normal ratio of bilirubin at the second test. The severe patients liver function dysfunction was worse than the moderate patients but without a significant difference. The dead patients showed a significantly higher level of DBIL, AST, GGT and CRP than other groups patients in the final test, along with the hypoalbuminemia. What is worse, 16.13% of non-survivors were diagnosed with liver failure. No medication was found to be related to ALT, AST, and GGT abnormality in our study. Conclusion: In moderate and severe patients, liver dysfunction was mild. Patients widely presented lower level of ALB. The higher level of bilirubin, AST, and GGT was likely to indicate the worse outcome. Dynamic monitoring of liver function indexes could be considered and liver failure related death should be noticed and prevented in the early stage.

Zero-shot learning has been a tough problem since no labeled data is available for unseen classes during training, especially for classes with low similarity. In this situation, transferring from seen classes to unseen classes is extremely hard. To tackle this problem, in this paper we propose a self-training based method to efficiently leverage unlabeled data. Traditional self-training methods use fixed heuristics to select instances from unlabeled data, whose performance varies among different datasets. We propose a reinforcement learning framework to learn data selection strategy automatically and provide more reliable selection. Experimental results on both benchmarks and a real-world e-commerce dataset show that our approach significantly outperforms previous methods in zero-shot text classification

Schedule risk is a major concern in infrastructure project management. Existing studies have proposed several models for schedule risk analysis, but few efforts have been made on the dynamics and uncertainty of risks and the generality and practicability of the model. To fill the research gaps, this study develops a hybrid dynamic approach for investigating the effect of risks on infrastructure project schedule performance. This approach combines system dynamics (SD) and discrete event simulation (DES) which have mainly been used to analyze the macroscopic and microcosmic construction issues in isolation, respectively. The model is then verified by data which is collected from a bridge construction project. As an application example, the effect of four selected risks on the schedule was explored. The results show that the proposed SD-DES model could be ease of modifying the model to reflect real situation, performing various sensitivity and uncertainty analysis, and showing simulation results more effectively.

Background/Aims: In this report, we aimed to investigate the distribution and characterization of biomarker-immunolabeled ductal epithelium in advanced pancreatic ductal adenocarcinoma (PDAC). Design: Eighteen patients with PDAC were medically diagnosed prior to being treated periodically. All clinical records were collected and assayed. The PDAC samples were subjected to routine biochemical tests and immuno-stains of immunohistochemistry and immunofluorescence. Results: As results, immunohistochemical findings indicated pancreatic ductal cells in PDAC showed plenty of Ki-67, P53, RP, SAM positive cells expressed in nuclei. In addition, ductal epithelial cells exhibited numerous positive cells of CK7, 18, 19, 20 biomarkers, respectively. Interestingly, compared to non-PDAC controls, immunostaining results showed that endocrine hormones were positively expressed in pancreatic ducts of PDAC, characterized with increased insulin-, Ngn3-, PDX1-fluorescence-labeled cells, and reduced F-box and WD-40 domain protein 7 (Fbxw7)-labeled cells in ducts. Conclusion: These clinicopathologic findings preliminarily disclose that there may be a potential for insulin-producing cells in PDAC, possibly through negatively inducing Fbxw7 ubiquitination in pancreatic ducts.

Design, manufacturing, storage, transportation, and on-site assembly are fundamental processes in prefabricated housing production (PHP) in Hong Kong. However, these processes are fragmented and entail various risks that adversely affect the schedule performance of PHP, thereby causing frequent delay problems in PHP projects and hindering the government from satisfying the high housing demands. Accordingly, many researchers have examined these schedule risks to resolve these delay problems. However, none of these studies developed an effective tool for managing schedule risks of PHP by envisaging the key characteristics of schedule risks and PHP. Most of previous research regarding to the management of prefabrication construction tends to consider risks from static and isolated perspectives, despite that these risks are coherently interrelated with each other and their influence varies throughout the whole PHP process. To fill the research gaps, a hybrid dynamic model is developed in this research to evaluate and simulate the impact of identified schedule risks on the schedule performance of PHP in view of underlying interrelationships and interactions, employing the hybrid system dynamics (SD) and discrete event simulation (DES) method. The resulting hybrid model is validated through a serial of model structure tests and model behavior tests, with the use of data collected from a PHP project in Hong Kong. This study offers an in-depth understanding of how schedule performance of PHP are dynamically influenced by interrelationships and interactions underlying various schedule risk variables. The developed model not only has the benefits of ease of modifying model structure to reflect real schedule situation of PHP project, performing various risk analyses and communicating with simulation results, but also is of value of providing an experiment platform for identifying and determining managerial and technical solutions proposed to minimize and mitigate the influence of corresponding schedule risks prior to implementation.

The construction industry in Hong Kong has been exposed to serious housing production issues such as insufficient manpower, safety, environmental concerns and inefficient housing supply. Prefabrication housing production has shown as efficient construction model which enables to overcome these issues and it is applied in construction industry in Hong Kong. In this paper, hybrid modeling techniques that combine system dynamics and discrete event simulation are used to analyze the interrelationships of schedule risks within the six-day cycle assembly of prefabrication housing production. Moreover, a hybrid dynamic model is developed to simulate and evaluate the impact of schedule risks on the schedule performance of the six-day cycle assembly of PHP via the Anylogic software package. The resulting model is validated by data which is collected from a PHP project in Hong Kong. Based on the simulation results, the first most influential level contains five schedule risks, namely, inefficient verification of precast components because of ambiguous labels, misplacement on the storage site because of carelessness, owner crane breakdown and maintenance, slow quality inspection procedures, and inefficient design data transition that cause average schedule delays of more than 300 min. The second most influential level includes delay of the delivery of precast element to site, design information gap between designer and manufacturer, installation error of precast elements, and logistics information inconsistency because of human errors, with average schedule delays less than 300 min and greater than 200 min. Design change, low information interoperability between different enterprise resource planning systems, and inefficiency of design approval belong to the third level that imposes the least influence on the schedule delay of the assembly. This research contributes to the current knowledge of the management of prefabrication construction by developing an effective model that offers an in-depth understanding of how schedule performance of PHP is dynamically influenced by interrelationships of various risk variables. Also, it provides an experimental platform for simulating and analyzing schedule risks that significantly affect the schedule performance of the six-day cycle assembly of prefabrication housing production. Such critical schedule risks could be identified and managed prior to the implement of prefabrication housing production projects. Compared with traditional techniques, the hybrid dynamic model simultaneously considers macro and micro levels, thereby enabling project managers to gain a deeper insight into schedule management and acquire a multidimensional understanding of schedule delay.

Light absorber is critical to the further applications of thin film solar cells. Here, we report a facile solution-processed method with an annealing temperature below 250°C to fabricate Ag8SnS6 (ATS) light absorber for thin film solar cells. After optimization, the ATS-based thin film solar cells exhibited a reproducible power conversion efficiency (PCE) of about 0.25% and an outstanding long-term stability with 90% of the initial PCE retained after a more than 1,000 h degradation test. This research revealed the potential application of ATS as an earth-abundant, low toxic and chemically stable light absorber in thin film solar cells.

The purpose of this study was to assess the predictive value of angiogenic miRNAs for disease‐free survival (DFS) and overall survival (OS) of patients with non‐small cell lung cancer (NSCLC). In total, 196 patients with NSCLC (tumor lymph nodes metastasis (TNM) stage I–III) were enrolled and peripheral blood samples were collected. Total RNA was extracted from blood samples, and the relative expression levels of candidate miRNAs were evaluated by real time‐polymerase chain reaction (RT‐PCR). The median follow‐up period was 56.7 months, and the final follow‐up date was in August 2016. The median DFS of all patients was 30.0 (14.0–49.0) months, whereas the median OS was 41.5 (23.0–58.0) months. Furthermore, the 5‐year DFS and OS rates were 11.3% and 32.3%, respectively. Kaplan–Meier (K–M) curves showed that high plasma miR‐18a (P

To meet the diversified demand of power and cooling for the distributed energy system, this paper proposes two combined cooling and power (CCP) systems combining the supercritical carbon dioxide cycles with a carbon dioxide ejector refrigeration cycle, which can switch between full power mode (Mode-P), combined cooling and power mode (Mode-PR), and full refrigeration mode (Mode-R) according to the energy demands of users. In the proposed CCP systems, the recompression cycle and modified dual-stage compression cycle are used to replace the regenerative cycle and basic dual-stage compression cycle in two reference systems respectively. The mathematical models of systems are established and verified. Detailed parametric analysis is conducted to investigate the effects of key parameters on the performances of proposed systems and reference systems. Moreover, the modified systems and reference systems are optimized and compared at three modes. Multi-mode analysis is also applied to study the ability of the four CCP systems to convert power into cooling. Finally, detailed exergy analysis and thermoeconomic analysis are performed for the optimal system. The results show that the modified systems can achieve higher exergy efficiency by recovering partial waste heat before the pre-cooler. Under the refrigeration condition (the evaporation temperature is 0 ℃), the exergy efficiencies of the modified single-stage compression (M−S) system are 13.71% and 14.08% higher than those of the reference system at Mode-P and Mode-R, respectively. The cooling capacities of the systems at Mode-PR and Mode-R are positively correlated with their power outputs at Mode-P. The M−S system has the best multi-mode performance owing to its highest exergy efficiency (64.01%) at Mode-P, minimal energy loss at Mode-PR, and the maximum cooling capacity to heat input ratio (1.714 at 0 ℃ and 0.964 at −20 ℃) at Mode-R. Under the freezing condition (the evaporation temperature is −20 ℃), the single-stage compression systems generally perform better than the dual-stage compression systems. During the process of switching from Mode-P to Mode-R, the total product unit cost of the M−S system increases from 12.24 $·GJ−1 to 44.74 $·GJ−1 under the refrigeration condition and from 12.24 $·GJ−1 to 38.15 $·GJ−1 under the freezing condition.

The light interference is an important reason for the false alarm or blindness of the flame detectors, and the effect of sunlight interference is particularly significant. In order to meet the requirements for the evaluation of the anti-sunlight interference performance of the flame detector, it is necessary to classify the solar interference severity according to the light climate data. On this basis, the solar interference simulation equipment and test method with quantitative test are designed. Through tests under different seasons, times and light conditions, the reliability and effectiveness of the test equipment and test methods are verified, the measurement uncertainty is calculated. Test results provide technical support for the standardization of sunlight interference test.

This proposes a novel dual-ejector based organic flash combined power and refrigeration cycle, which replaces the two throttle valves with two ejectors for the basic flash cycle, to provide power and cooling simultaneously for users. Detailed mathematical models of the proposed system are built and validated. The preliminary analysis results show that the exergy efficiency reaches 45.59% under geothermal water at 150℃. Then a parametric analysis is conducted to investigate the effects of five key parameters on system performance. The results show that both an optimal flash pressure and an extraction pressure exist to maximize the exergy efficiency. Finally, the proposed cycle, the separated power and refrigeration cycle consisting of a basic organic flash cycle and an ejector refrigeration cycle, and the basic organic flash cycle are optimized and compared by examining seven different organic fluids such as R245fa, R141b, R123, R245ca, R601, R365mfc, and R600. The results show that the R245fa brings the highest exergy efficiency to both the proposed cycle and organic flash cycle among seven involved organic fluids. Compared with the basic organic flash cycle, the proposed cycle with R245fa has a 4.91% percentage point higher exergy efficiency, 10.44% higher net power output, and an extra 172.6 kW of refrigeration output. Meanwhile, the optimal exergy efficiency and net power output of the proposed cycle are 5.82–6.80% percentage point higher and 15.06–23.87% higher than those of the separated power and refrigeration cycle. An exergy analysis suggests that the throttling losses are indeed significantly reduced by replacing the throttle valves with the ejectors for the organic flash cycle.

Every country is dealing with its own housing problems; however, none compares with Hong Kong where housing has always been a major concern as a result of low supply over the past decades. Against the constraints in delivering sufficient houses, prefabrication as a sustainable solution for housing has been increasingly advocated for its potential merits of better quality, construction safety and cleaner built environment. However, schedule delay caused by various risks affected the prefabrication housing production (PHP) in Hong Kong. This problem can be further worsened when the manufacturing sector of PHP has entirely moved to offshore areas in the Pearl River Delta region. This study applies system dynamics to recognize and investigate the potential effect of various risks on the scheduling of prefabrication housing construction projects through the employment of Vensim software package. The simulation results show that schedule risks, namely low information interoperability between different enterprise resource planning systems (LIIBDERPS), logistics information inconsistency due to human errors probability (LIIHEP), Delay of delivery of precast element to site (DDPES), and Design information gap between designer and manufacturer (DIGDM) significantly contribute to the schedule delay in PHP. However, schedule is more sensitive toward LIIBDERPS than for the other three risks, indicating that LIIBDERPS should be monitored and given priority. The system dynamic model serves as an effective tool for quantitatively evaluating the effect of various risks on the schedule of PHP, offering valuable references for managers though comparing simulation results under different risk scenarios, so that potential risks that might lead to schedule delay could be identified and handled in advance.

Two-dimensional perovskite solar cells (PSCs) with high moisture resistance are a key topic in the photovoltaic field. However, their lower power conversion efficiencies (PCEs) in comparison to 3 D PSCs is still an urgent problem to be solved. It is vital to understand the impact of constituent ratios and ammonium salt sizes on the photovoltaic performance and humidity stability. Based on the formula of (RNH3 )2 (MA)n-1 Pbn I3n+1 (n=1, 3, 5, 7, 9, and 11), a series of 2 D perovskites is prepared by introducing varisized ammonium salts of ethylammonium iodide (EAI), propylammonium iodide (PAI), and butylammonium iodide (BAI). The effects of the constituent ratios and varisized ammonium salts on the properties of the 2 D perovskites were studied. 2 D perovskite devices based on larger n and smaller ammonium salt size are found to exhibit better performances. However, the moisture resistance of the 2 D perovskite devices is higher when n is smaller and the ammonium salt size is larger. Therefore, the EA2 MA10 Pb11 I34 (n=11) 2 D perovskite device displays the best photovoltaic performance, with the highest PCE of 16.93 %, whereas BA2 MA2 Pb3 I10 (n=3) 2 D perovskite, with the largest contact angle of 79.8°, can retain over 85 % of the initial PCE after 1440 h aging at 50 % relative humidity. This work indicates the PCE and stability of 2 D perovskites can be conveniently and effectively adjusted by controlling the 2 D constituent ratios and ammonium salt sizes, so as to obtain efficient 2 D PSCs with high stability.

In this paper, we introduce a negative capacitance independent gate FinFET (NC-IG-FinFET) devices, by stacking the ferroelectric material HfO2 into the front and back gate surfaces of the baseline independent gate FinFET (IG-FinFET) devices with symmetrical gate structure. We exhibit the dual-threshold characteristics of NC-IG-FinFETs by adjusting its gate work function, structural parameters, and ferroelectric material characteristics. The current characteristics of the NC-IG-FinFETs and baseline IG-FinFETs are simulated and verified by TCAD Silvaco. The results show that the proposed NC-IG-FinFETs have steeper subthreshold swing of 42mV/dec and larger switching current ratio than baseline IG-FinFETs. Therefore, the NC-IG-FinFETs offers significant advantages in terms of reduced power consumption.

In this paper, we introduce an independent gate p-type tunneling field-effect transistor using double heterojunction structures (IG-DHJ-pTFET), which has the characteristics of high turn-on current (ION) and high turn-on/turn-off current (ION/IOFF) ratio. The double heterojunction structures consist of an AlInAsSb/InGaAs heterojunction and an InGaAs/GaAsSb heterojunction, which shorten the tunnel distance and improve the on state tunneling probability. We optimize the leakage currents of the IG-DHJ-pTFET devices by varying gate-on-drain overlapping. We obtain high-threshold and low-threshold IG-DHJ-pTFETs by adjusting the gate work function. The TCAD simulation results show that the proposed high-threshold and low-threshold IG-DHJ-pTFETs are logically equivalent to two short-gate (SG) transistors in series and parallel, respectively, with excellent electrical characteristics. The proposed dual-threshold IG-DHJ-pTFETs using double heterojunction structures can reduce the number of transistors used in circuits.

Thalassemia, classified as the main types α‐ and β‐thalassemia, is a single gene disorder resulting from globin chain synthesis impairment through the mutation or deletion of globin genes. The incidence of thalassemia is high worldwide, with high associated mortality. Therefore, treatment is important to improve patient outcomes. This paper reviews the current status of β‐thalassemia major in China, including its epidemiology and treatment.

Psychotropic drugs are frequently used for functional dyspepsia (FD); however, the efficacy of these drugs for treating FD remains controversial. We aimed to comprehensively compare the relative efficacies of different psychotropic drugs for FD in adults.To conduct this study, we searched the PubMed, Embase, and Cochrane Library databases on March 10, 2019, and conducted a frequentist network meta-analysis on the search results. The primary outcome was treatment efficacy estimated by the proportion of patients who achieved a certain percentage decrease in symptoms or who dropped below the threshold of the global FD symptom scores. The secondary outcome was acceptability, defined as all-cause discontinuation. Odds ratios (ORs) were reported with 95% confidence intervals (CIs).We deemed 10 trials to be eligible for analysis, and these trials included 970 participants and 10 psychotropic drugs. Flupentixol + melitracen (F + M) (OR, 10.00; 95% CI, 1.59 to 62.73), tandospirone (3.24, 1.38 to 7.60), imipramine (2.21, 1.02 to 4.79), and amitriptyline (1.71, 1.06 to 3.09) were significantly superior to placebo. According to the surface under the cumulative ranking curve, the most effective treatment was F + M (89.0%), whereas the least effective was R137696 (13.6%). In terms of acceptability, escitalopram (0.32, 0.11 to 0.92) was ranked as the worst drug (12.6%), followed by imipramine and sertraline.The present network meta-analysis suggests that F + M, tandospirone, imipramine, and amitriptyline are more effective than placebo as treatment for FD. Our results indicate that among the ten psychotropic drugs included, F + M is likely to be the most effective drug for alleviating dyspepsia symptoms.

The prediction of building energy consumption plays a crucial role in building energy management and conservation because it contributes to effective building operation, energy efficiency evaluation, fault detection and diagnosis, and demand side management. Although a large number of energy prediction methods have been proposed, each method has its pros and cons and still exhibits the potential to be improved. This study proposes an evolutionary double attention-based long short- term memory model and introduces binary features by using feature combination. The proposed model is adopted to analyse the building energy consumption data of a green building in Shenzhen, China. The prediction performance of the proposed hybrid model measured via root-mean-square-error and mean absolute error are 4.02 and 2.87 respectively, which are evidently better than those of the base models. Results also show that an attention mechanism can improve the efficiency of the long short-term memory algorithm with which the model uses the input time series data. Meanwhile, binary features exert a significant effect on energy consumption. The proposed model is valuable to researchers and practitioners. It helps researchers apply artificial intelligence-based methods to building energy prediction from the perspective of paying selective attention to input data. Practitioners will benefit from developing accurate diagnosis of building energy efficiency and decision support for building retrofitting.

Energy conservation in the building sector is a major target worldwide, and individual’s energy conservation behavior is considered a critical means to meet energy conservation goals. Although individual’s energy conservation behavior has been explored, its formation mechanism in the workplace remains unclear. This study aims to investigate the effect of the determinants of energy conservation behavior in the workplace based on the extended theory of planned behavior model. The novelty of this study is that it extends the theory of planned behavior with the consideration of actual behavior controls. This study is also one of the first studies to identify the effect of user experience on energy saving behavior. Questionnaire survey was used for data collection, and structural equation modeling was applied to develop the structural model. Results show that individual’s comfort is the most critical impact factor, followed by user experience and supervision. Intention has a limited effect on energy saving behavior. Moreover, three strategies were proposed to promote energy conservation behavior in the workplace from the perspectives of design, supervision, and punishment. These findings will not only help researchers in conducting further in-depth research on the mechanism of individual’s energy conservation behavior but also practitioners in proposing other effective strategies to promote energy conservation behavior.

The ionic nature of hybrid perovskites indicates the existence of inevitable and multi-type defects. Design of effective passivation molecules becomes a vital means to suppress charge recombination and reduce the voltage loss in perovskite solar cells. However, most of the reported passivation molecules show single effect and the passivation mechanism of molecules with multiple functional groups is unclear. Herein, on the premise of making sure the combined passivation effect of amine, carbonyl group and benzene ring, we tailored multifunctional passivation molecules (4-fluorobenzamide and 4-chlorobenzamide) by introducing halogen functional group. After employing high-electronegativity halogen groups, the hydrogen bond with organic cations and ionic bond with Pb2+ were formed, which is the key to prevent defect regeneration and ion migration. The perovskites with halogenated passivation molecules displayed reduced trap densities and increased carrier lifetimes. Finally, multifunctional passivation molecules can not only effectively heal defects but also improve the stability of perovskite materials. The optimal devices with 4-fluorobenzamide achieved a 5.6% enhancement of open-circuit voltage (Voc) and the power conversion efficiency yielded to 21.35%. Our findings confirm the enhanced passivation based on the multiple functional groups combination and provide a guideline for new multifunctional passivation molecules in perovskite photovoltaics.

Di-(2-ethylhexyl) phthalate (DEHP), one of the most common plasticizers, is closely associated with a high prevalence of pubertal type 2 diabetes mellitus (T2DM). Numerous studies have indicated that DEHP-induced metabolic toxicity exhibits sex differences. In this study, the sex differences in the effect of DEHP on pubertal T2DM (P-T2DM) mice, the susceptibility of female P-T2DM mice to DEHP-induced metabolic toxicity, and the underlying mechanisms were investigated. DEHP exposure exacerbated metabolic disorders in female P-T2DM mice. Factorial analysis showed that female P-T2DM mice were more sensitive to DEHP exposure than female normal mice and male P-T2DM mice. It was determined by integrated biomarker response results that female P-T2DM mice had higher risks of developing T2DM, metabolic disorders, cardiovascular events and hepatotoxicity than male P-T2DM mice. Moreover, hepatic transcriptome analysis emphasized the effects of DEHP on the expression of oxidative injury- and metabolic function-related genes. Western blotting indicated that DEHP activated Jun-N-terminal kinase (JNK) and impaired insulin sensitivity in the liver, which were the main causes of DEHP-exacerbated metabolic abnormalities in P-T2DM mice. Our study revealed that compared with normal mice and male P-T2DM mice, female P-T2DM mice tend to suffer from increased DEHP-induced metabolic toxicity, which was primarily attributed to hepatotoxicity.

For the advantages of high efficiency and low impact to the environment, CO2 air source heat pump water heater (ASHPWH) is applied to produce domestic water, which also reveals good potential in cold regions. In order to boost the system performance and practicability under low ambient temperature, optimization for CO2 ASHPWH is conducted using non-dominated sorting genetic algorithm (NSGA-II). A validated artificial neural network (ANN) predicts energy parameters for the optimization. And an economic model provides economic and environmental parameters, which considers the influence of housing price, tank volume, and on/off-peak electricity price, rarely taken into account in published studies. Then the optimizing progress is conducted under −20 °C ambient temperature and 9–65 °C water temperature, in which four optimized variables are selected: gas cooler outlet temperature (Tgc), heat rejection pressure (Pgc), compressor displacement (qvh) and water tank volume (Vwt). The final solution of Tgc = 15 °C, Pgc = 8294.1 kPa, Vwt = 0.3647 m3, qvh = 401.33 mL/s results in two objectives (CO2 emission and total annual cost) of 8599.4 kg and 1626.9 $/year, revealing advantages both in energy and economy. It is noteworthy that the cost of the space occupied by system is the fourth important factor in capital cost. These results lay solid foundation for further studies and system application.

The building sector is responsible for 32% of global energy consumption and 19% of all energy-related greenhouse gas emissions. The urgent requirement for energy conservation and greenhouse gas emission reduction in the building sector has been recognised at the highest level of governments around the world. One potential solution, which has yet to be critically considered, is the application of Building Information Modeling (BIM) to overcome building energy performance gap (BEPG), defined as the discrepancy between the designed and actual energy consumption in buildings. This study performs a systematic and comprehensive literature review to identify the specific causes of the BEPG, and then analyses the application of BIM for addressing the BEPG. A life-cycle BIM engaged framework was developed, including the function of “information exchange”, “design review”, “energy-related quality control”, “life-cycle commissioning”, and “real-time operation and maintenance management”. It is expected that the proposed framework will assist researchers and practitioners better understand application of BIM to systematically improve building energy performance.

A novel combined cooling and power (CCP) system integrating a supercritical carbon dioxide recompression Brayton cycle with an ejector transcritical carbon dioxide refrigeration cycle (E-TCRC) is proposed to realize the effective utilization of nuclear power. In the proposed system, a portion of CO2 exiting the pre-cooler is used to drive the E-TCRC for generating cooling and recovering partial waste heat of sCO2 turbine exhaust. The mathematical model and economic model of the proposed system are established under steady-state conditions. Besides, the exergy efficiency and total product unit cost of the system are selected as the main criteria to evaluate system performance. Parametric analysis is applied to study the effects of four key parameters on the system performance. The CCP system, conventional separated cooling and power (C-SCP) system and ejector separated cooling and power (E-SCP) system are optimized by single-objective and multi-objective optimization. Single-objective optimization reveals that the exergy efficiencies of the CCP system are up to 1.08%pt (percentage point), 0.80%pt and 0.47%pt higher than those of the C-SCP system at the corresponding evaporation temperatures (−20 °C, −10 °C and 0 °C). Besides, the CCP system performs better than the E-SCP system at lower turbine inlet pressures. The multi-objective optimization shows that when the evaporation temperature increases from −20 °C to 0 °C, the total product unit cost of the CCP system decreases from 10.087 $/GJ to 9.668 $/GJ, and exergy efficiency increases from 59.25% to 60.97%.

The organic flash cycle is an efficient low-grade energy conversion technology. However, a large space is left for the organic flash cycle to improve the useful energy output due to the throttling processes. To utilize the thermal energy before the low-pressure throttling process in the organic flash cycle driven by the geothermal energy, an ammonia-water absorption refrigeration cycle is adopted to generate cooling by using this part of heat, thereby forming a novel geothermal combined cooling and power (Geo-CCP) system. Eight different organic flash cycle working fluids are investigated, including n-Nonane, n-Octane, n-Heptane, Cyclopentane, i-Pentane, n-Pentane, R365mfc, and R245fa. Detailed thermodynamic modeling, thermoeconomic analysis, parametric analysis, system optimization, and exergy analysis are carried out for the proposed system. The results show that the total product unit cost and exergy efficiency of the proposed systems are 6.52–11.03% lower and 4.10–5.31%pt (percentage point) higher than those of the geothermal separate cooling and power systems. Among the eight considered organic fluids, the n-Nonane brings the lowest total product unit cost and highest exergy efficiency to the Geo-CCP system (11.20 $·GJ−1 and 37.58%). Exergy analysis indicates that the flasher and condenser-I have the first and second highest exergy destructions.

Housing has been a major concern in Hong Kong for the past several decades, increasing pressure on the Hong Kong Housing Authority to pursue ambitious housing plans. As a sustainable construction technology, prefabrication has been increasingly adopted in the delivery of housing plans to alleviate various constraints, such as labor shortage, time, safety, and environmental protection. However, few studies have conducted a strategic analysis of the current situation and planning management of prefabrication housing production (MPHP) in Hong Kong. By performing a strengths, weaknesses, opportunities, and threats (SWOT) analysis, the current study attempts to facilitate a more in-depth understanding of the MPHP development status in housing production in Hong Kong. Data underpinning the SWOT analysis are collected from various channels, including literature review, prefabrication-related regulations, interviews with experts, and government reports. This study provides an opportunity for major stakeholders to perceive the external and internal conditions of prefabrication development in Hong Kong. Internet of Things (IoT)-enabled platform deploying BIM to re-engineer offshore prefabricated construction processes, which are proposed based on the identified SWOTs for solving weaknesses and dealing with threats, are significant for improving MPHP in Hong Kong.

Various schedule risks beset prefabrication housing production (PHP) in Hong Kong throughout the prefabrication supply chain, from design, manufacturing, logistics, to on-site assembly. Previous research on the risks in prefabrication construction projects has mainly focused on the construction stage and has been confined to issues of completeness and accuracy without consideration of stakeholder-related risks and their cause-and-effect relationships. However, in reality, the supply chain is inseparable as precast components should be manufactured and transported to sites to fit in with the schedule of on-site assembly in seamless connection manner, and most risks are interrelated and associated with various stakeholders. This study applies social network analysis (SNA) to recognize and investigate the underlying network of stakeholder-associated risk factors in prefabrication housing construction projects. Critical risks and relationships that have important roles in structuring the entire network of PHP are identified and analyzed. BIM (Building Information Modeling)-centered strategies are proposed to facilitate stakeholder communication and mitigate critical schedule risks and interactions underlying the risk network. This study not only provides an effective method to analyze stakeholder-associated risk factors and to evaluate the effect of these risk factors from a network perspective, but also offers a new visual perspective in the promotion of the use of the Internet of things (IoT) and helps identify housing construction problems in Hong Kong.

China has been conducting large-scale land consolidation (LC) programs since the late 1990s to ensure national food security, stabilize farmland patterns and coordinate urban and rural development. LC activities, as an essential type of public investment, show significant impacts on national/regional social and economic progress. However, it is difficult to analyze a specific impact, especially a socio-economic one, of an LC program due to its’ diversified, far-reaching, and inter-correlated influencing factors. This paper establishes a system dynamics model to simulate the functional mechanism motivated by implementing an LC program, and an LC project in a rural area of mid-eastern China is used as the study case. Four subsystems are included in the proposed system dynamics model, namely the capital input-output subsystem, land use subsystem, agricultural production subsystem and social impact subsystem. All of these four subsystems are connected with each other and each of them is affected by its own “inputs”, those being engineering inputs and resource inputs. The simulation result shows that the proposed system dynamics model can effectively incorporate all influencing factors and demonstrate the desired characteristics (such as systematic, complex, feedback-reenter, long-term and dynamic) of socio-economic impacts of an LC program. The system dynamics model, considering the feedbacks and dynamic nature of LC, can function as a novel method to effectively evaluate the socio-economic impacts of LC.

The gap between the designed and measured building energy consumption is one of the biggest obstacles to the realization of energy conservation goal. The factor analysis method has been typically used in previous studies to explore the individual factors affecting building energy performance gap, while few studies examined the complex interrelationships among the influencing factors. In this research, the interpretive structural modelling approach was developed and applied to identify the key factors and explore the interrelationships among the factors affecting building energy performance gap. This paper first identified 47 factors by reviewing 276 relevant articles. Sixteen representative factors were further identified by interviewing 12 interviewees with 7 to 25 years’ practical experience on building energy management. Second, a six-level hierarchical structure was developed based on interpretive structural modelling to illustrate the intricate interrelationships among the representative factors. Third, “Matrice d’Impacts croises-multipication applique a classement” was applied to demonstrate the driving force and dependence power of the representative factors. Four clusters of factors were identified, namely dependent factors, driving factors, autonomous factors and linkage factors. Fifth and finally, 10 strategies were proposed to address these factors and their interrelationships. The findings of this research will help not only researchers in understanding the factors and their hierarchical structures affecting BEPG but also policymakers and practitioners in understanding the priority of allocating limited resources to address these factors and issues.

The voltage loss which is mainly caused by the nonradiative recombination at the interface has played a serious negative effect on the photovoltaic performance of perovskite solar cells (PSCs). Herein, we firstly designed four halogenated low-dimensional perovskite (LDP) capping layers by the way of employing different benzylammonium-based aromatic cations for high-performance devices. The introduction of halogen functional groups can not only enhance the hydrophobicity but also optimize the photovoltaic characteristics of LDP which play an important role on passivation effect of the interface between perovskite and hole transport materials (HTM) layer. The films with halogenated LDP passivation layers displayed suppressed nonradiative recombination and reduced trap density, leading to significantly reduced voltage loss. As a result, the optimal devices with 4-bromobenzylammonium-based LDP layer achieved the power conversion efficiency (PCE) as high as 21.13% with an enhanced open-circuit voltage (Voc) of 1.14 V. Under the hydrophobic and buffer action of the halogenated LDP layer, the modified devices showed outstanding long-term stability when exposed to moisture, heat and continuous UV irradiation. This work proves the enhanced passivation effect of LDP layer by regulating the chemical property of introduced organic cations for high-performance and stable perovskite photovoltaics.

Trans-critical CO2 Rankine system is a new technology for low-grade heat utilization which has high energy conversion efficiency and exergo-economic efficiency. The gas heater is one of the most important components in trans-critical CO2 Rankine system, which is a crucial challenge for its practical application because of high pressure and abrupt change in thermo-physical properties of supercritical CO2.The aim of this paper is to provide basic background knowledge on trans-critical CO2 Rankine cycle in low-grade heat conversion and present a review of experimental tests and demonstrations on supercritical CO2 operation considering heat-to-power systems. Since the heat transfer criteria and enhancement of supercritical CO2 is vital for its application in the real-scale compact heat exchanger design and system operation, this review further discusses the turbulent convective heat transfer and its enhancement approaches of supercritical CO2 in heating system. A comprehensive summary of the heat transfer mechanisms and criteria as well as their derivation and evaluation methods is conducted to provide some references for the system operation, heat exchanger design and heat transfer enhancement. Some of the shortcomings of the existing research are pointed out. Based on the above discussion, this review presents the basic ideas and approaches of heat transfer enhancement and discus the application of heat transfer criteria in heat transfer enhancements. Finally, the authors bring forward the way of latter researching of supercritical heat transfer and enhanced measures.

Occupant characteristics are critical factors that have a significant impact on electricity consumption in residential buildings, which have attracted increasing attention in the research field of building energy. This study analyses the influencing of occupant characteristic-related factors on electricity consumption in residential buildings with the consideration of different targets of electricity consumption, particularly by developing a statistical model based on a large data set published by the US Department of Energy. Results show that ECRB can be substantially affected by occupant characteristic-related factors, including ‘age of householders’, ‘household size’, ‘income’, ‘education level’, ‘type of occupancy’ and ‘length of residency’. They could explain 10.70% of the variance in electricity consumption. In which, type of occupancy’ has the largest impact, followed by ‘education level’, ‘length of residency’, ‘household size’ and ‘income’. It is also found that there are differences between some occupant characteristics corresponding to different occupant behaviors. Additionally, this study conducted an in-depth analysis of the relationship between occupant behaviour (including the use of energy star appliances, frequency appliances used, energy audit and insulation adding) and occupant characteristic-related factors. The analysis method serves as an effective tool for quantitatively evaluating the effect of various occupant characteristics in occupant behaviour modelling and building energy simulation, offering valuable references for practitioners, such that the appropriate strategies for electricity consumption saving can be selected in advanced.