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Abstract Head and neck squamous carcinoma (HNSC) is a prevalent malignant disease, with the majority of patients being diagnosed at an advanced stage. Endoplasmic reticulum stress (ERS) is considered to be a process that promotes tumorigenesis and impacts the tumor microenvironment (TME) in various cancers. The study aims to investigate the predictive value of ERS in HNSC and explore the correlation between ERS-related genes and TME. A series of bioinformatics analyses were carried out based on mRNA and scRNA-seq data from the TCGA and GEO databases. We conducted RT-qPCR and western blot to validate the signature, and performed cell functional experiments to investigate the in vitro biological functions of the gene. We identified 63 ERS-related genes that were associated with outcome and stage in HNSC. A three-gene signature (ATF6, TRIB3, and UBXN6) was developed, which presents predictive value in the prognosis and immunotherapy response of HNSC patients. The high-risk group exhibited a worse prognosis but may benefit from immunotherapy. Furthermore, there was a significant correlation between the signature and immune infiltration. In the high-risk group, fibroblasts were more active in intercellular communication, and more T cells were observed at the end of the sequential phase. The genes in the ERS-related signature were overexpressed in HNSC cells, and the knockdown of TRIB3 significantly inhibited cell proliferation and migration. This study established a novel ERS-related signature that has potential implications for HNSC therapy and the understanding of TME.

In traditional Chinese medicine (TCM), the kidney is considered the ''innate foundation'', and the abundance or diminution of its essence directly affects the growth, development, physical form, and physiological functions of the human body. As people reach middle age and old age, the essence in the kidney gradually decreases, and the signs of aging become more apparent. Immune aging is a common phenomenon in life, characterized by quantitative or functional changes in cells and molecules within the immune system. It is one of the main causes of organ aging, leading to increased inflammation, decreased immune regulatory capacity and declining organ function. TCM has a rich clinical practice and pharmacological research supporting its efficacy in delaying aging. This review focuses on Chinese medicine and formulas that tonify kidney yang and kidney yin, with the goal of delaying aging by regulating immune mechanisms. It provides a theoretical basis for understanding the role of TCM in anti-aging and prevention of senescence, as well as guiding the development of new products, theories, and directions in anti-aging research.

This study investigates the impacts of assimilating the Microwave Humidity Sounder II (MWHS-2) radiance data carried on the FY-3D and FY-3E satellites on the analyses and forecasts of Typhoon Muifa in 2022 under clear-sky conditions. Data assimilation experiments are conducted using the Weather Research and Forecasting (WRF) model coupled with the Three-Dimensional Variational (3D-Var) Data Assimilation method to compare the different behaviors of FY-3D and FY-3E radiances. Additionally, the data assimilation strategies are assessed in terms of the sequence of applying the conventional and MWHS-2 radiance data. The results show that assimilating MWHS-2 data is able to enhance the dynamic and thermal structures of the typhoon system. The experiment with FY-3E MWHS-2 assimilated demonstrated superior performance in terms of simulating the typhoon’s structure and providing a prediction of the typhoon’s intensity and track than the experiment with FY-3D MWHS-2 did. The two-step assimilation strategy that assimilates conventional observations before the radiance data has improved the track and intensity forecasts at certain times, particularly with the FY-3E MWHS-2 radiance. It appears that large-scale atmospheric conditions are more refined by initially assimilating the Global Telecommunication System (GTS) data, with subsequent satellite data assimilation further adjusting the model state. This strategy has also confirmed improvements in precipitation prediction as it enhances the dynamic and thermal structures of the typhoon system.

The aim of this paper is to study and establish precise asymptotics for complete integral convergence in the law of the logarithm under the sub-linear expectation space. The methods and tools in this paper are different from those used to study precise asymptotics theorems in probability space. We extend precise asymptotics for complete integral convergence from the classical probability space to sub-linear expectation space. Our results generalize corresponding results obtained by Fu and Yang[13]. We further extend the limit theorems in classical probability space.

Abstract Objectives Patients are classified according to the severity of their condition and graded according to the diagnosis and treatment capacity of medical institutions. This study aims to correctly assign patients to medical institutions for treatment and develop patient allocation and medical resource expansion schemes among hospitals in the medical network. Methods Illness severity, hospital level, allocation matching benefit, distance traveled, and emergency medical resource fairness were considered. A multi-objective planning method was used to construct a patient allocation model during major epidemics. A simulation study was carried out in two scenarios to test the proposed method. Results (1) The single-objective model obtains an unbalanced solution in contrast to the multi-objective model. The proposed model considers multi-objective problems and balances the degree of patient allocation matching, distance traveled, and fairness. (2) The non-hierarchical model has crowded resources, and the hierarchical model assigns patients to matched medical institutions. (3) In the “demand exceeds supply” situation, the patient allocation model identified additional resources needed by each hospital. Conclusion Results verify the maneuverability and effectiveness of the proposed model. It can generate schemes for specific patient allocation and medical resource amplification and can serve as a quantitative decision-making tool in the context of major epidemics.

ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continuously evolving, bringing great challenges to the control of the virus. In the present study, we investigated the characteristics of SARS-CoV-2 within-host diversity of human hosts and its implications for immune evasion using about 2,00,000 high-depth next-generation genome sequencing data of SARS-CoV-2. A total of 44% of the samples showed within-host variations (iSNVs), and the average number of iSNVs in the samples with iSNV was 1.90. C-to-U is the dominant substitution pattern for iSNVs. C-to-U/G-to-A and A-to-G/U-to-C preferentially occur in 5′-CG-3′ and 5′-AU-3′ motifs, respectively. In addition, we found that SARS-CoV-2 within-host variations are under negative selection. About 15.6% iSNVs had an impact on the content of the CpG dinucleotide (CpG) in SARS-CoV-2 genomes. We detected signatures of faster loss of CpG-gaining iSNVs, possibly resulting from zinc-finger antiviral protein-mediated antiviral activities targeting CpG, which could be the major reason for CpG depletion in SARS-CoV-2 consensus genomes. The non-synonymous iSNVs in the S gene can largely alter the S protein’s antigenic features, and many of these iSNVs are distributed in the amino-terminal domain (NTD) and receptor-binding domain (RBD). These results suggest that SARS-CoV-2 interacts actively with human hosts and attempts to take different evolutionary strategies to escape human innate and adaptive immunity. These new findings further deepen and widen our understanding of the within-host evolutionary features of SARS-CoV-2. IMPORTANCE Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of the coronavirus disease 2019, has evolved rapidly since it was discovered. Recent studies have pointed out that some mutations in the SARS-CoV-2 S protein could confer SARS-CoV-2 the ability to evade the human adaptive immune system. In addition, it is observed that the content of the CpG dinucleotide in SARS-CoV-2 genome sequences has decreased over time, reflecting the adaptation to the human host. The significance of our research is revealing the characteristics of SARS-CoV-2 within-host diversity of human hosts, identifying the causes of CpG depletion in SARS-CoV-2 consensus genomes, and exploring the potential impacts of non-synonymous within-host variations in the S gene on immune escape, which could further deepen and widen our understanding of the evolutionary features of SARS-CoV-2.

This study aimed to investigate the expression and function of substance P in cervical squamous cell carcinoma. Cancer tissues and adjacent tissues of 20 patients with cervical squamous cell carcinoma in our hospital were collected. The expression of substance P was detected by immunohistochemistry and Western blot analysis. Cervical squamous cell carcinoma line SiHa was treated with different concentrations of substance P. The proliferation of SiHa cells was detected by EdU assay, and the invasion ability of SiHa cells was detected by transwell assay. The phosphorylation of ERK1/2 and the expression of MMP9 were detected by Western blot analysis. The results showed that substance P was expressed in the cytoplasm and some cell membranes of cervical squamous cell carcinoma cells. The expression of substance P in cervical cancer tissues was significantly higher than that in the adjacent tissues. Compared with the control group, substance P significantly promoted the proliferation and invasion of SiHa cells in a concentration dependent manner and activated the phosphorylation of ERK1/2 and upregulated the expression of MMP9 in SiHa cells. In conclusion, substance P is highly expressed in cervical squamous cell carcinoma and can promote cervical cancer cell proliferation and invasion. The mechanism is related to the activation of ERK1/2 pathway to upregulate MMP9.

Organic electrochemical transistors (OECTs) have emerged as an advantageous choice for constructing biosensors due to their remarkable water compatibility, low operating voltage, and inherent amplification capability. However, the current research on bio-sensing based on OECTs predominantly employs p–type material PEDOT:PSS as the channel material. Nevertheless, the utilization of a single material and its depleting characteristics impose significant limitations on device miniaturization and integration applications. We present a high-sensitivity glucose sensor based on n-channel accumulation-type OECT through immobilization the glucose oxidase on Pt gate electrode with an blending approach. The glucose oxidase directly mixed with bovine serum albumin, chitosan and immolizied on the gate electode, demonstrating a stable and sensitive response to the glucose. The modified n-channel organic electrochemical transistor demonstrates a highly sensitive response to glucose across a concentration range from μ M to mM, with a quantified stable sensitivity over 2.69 mmol ^–1 by normalizing the current change with respect to concentration. The device also exhibits selectivity towards glucose (compared with high concentrations of lactic acid, different concentration gradients of ascorbic acid, and uric acid), rendering it suitable for noninvasive glucose detection in body fluid like sweat, saliva etc This flexible and ensitive electrochemical transistor sensor holds immense potential for the development of potable healthcare biosensing.

An accurate visual reporter system to assess homology-directed repair (HDR) is a key prerequisite for evaluating the efficiency of Cas9-mediated precise gene editing. Herein, we tested the utility of the widespread promoterless EGFP reporter to assess the efficiency of CRISPR/Cas9-mediated homologous recombination by fluorescence expression. We firstly established a promoterless EGFP reporter donor targeting the porcine GAPDH locus to study CRISPR/Cas9-mediated homologous recombination in porcine cells. Curiously, EGFP was expressed at unexpectedly high levels from the promoterless donor in porcine cells, with or without Cas9/sgRNA. Even higher EGFP expression was detected in human cells and those of other species when the porcine donor was transfected alone. Therefore, EGFP could be expressed at certain level in various cells transfected with the promoterless EGFP reporter alone, making it a low-resolution reporter for measuring Cas9-mediated HDR events. In summary, the widespread promoterless EGFP reporter could not be an ideal measurement for HDR screening and there is an urgent need to develop a more reliable, high-resolution HDR screening system to better explore strategies of increasing the efficiency of Cas9-mediated HDR in mammalian cells.

Unmanned aerial vehicles (UAVs) can serve as means of delivery to enhance the effectiveness and accuracy of logistics distribution in various scenarios, such as emergency items delivery for disaster areas and logistics services for remote areas. This paper focuses on the problem of route planning for UAVs, which is the basis for UAVs to complete distribution tasks. Besides, to enhance the collaboration of UAVs during the delivery mission, this work also studies wireless resource (spectrum, power) allocation problem for multiple UAVs enabled communication networks. Due to the non-convex and combinatorial characteristics, it is challenging to obtain an optimal strategy for joint route planning and resource allocation issues within a finite time. To this end, the paths of UAVs are planned by the simulated annealing (SA) method in the first stage. Based on the preplanned paths, a double deep Q network (DDQN) based resource allocation method is proposed to maximize the average sum capacity of UAV-to-UAV (U2U) links and reduce transmission delay while minimizing the interference to UAV-to-infrastructure (U2I) links. Multi-UAV communication networks are reconnected according to the positions of UAVs changing in each time slot. Then each U2U link acting as an agent learns to improve spectrum and power allocation policy with imperfect knowledge of the environment. Simulation results demonstrate that the proposed DDQN-based resource management scheme can achieve higher system communication capacity than a random scheme. Moreover, the successful transmission probability of U2U links obtained by the DDQN-based method is much higher than a Particle Swarm Optimization (PSO) based method.

Field-effect gas sensors, integrating the gas sensor and amplification transistor, exhibit excellent sensory performance. Here we report organic thin-film transistors (OTFTs) with nanofiber-textured semiconductor films that exhibit superior ammonia response compared to conventional OTFTs with uniform/flat semiconductor films. The introduce of insulating polymer additives (IPAs) facilitates the formation of semiconducting nanofiber during coating. The effects of IPAs, organic semiconductor/IPA blend ratios and solvents on OTFT-based sensory performance are studied. The results show that the use of SU8 as IPA and chloroform as solvent form intertwined semiconductor nanofibers (∼50 nm in diameter) at the bottom. The resulting OTFTs exhibit extraordinarily high sensitivities to ammonia, which reach 13676%/ppm (current) and 457%/ppm (turn-on voltage), respectively. Finite element analysis is conducted to simulate the adsorption/desorption processes of gas molecules and the effect of specific surface area on sensory performance.

Construction equipment is one of the most significant resources in large construction projects, accounting for a considerable portion of the project budget. Improving the performance of heavy machinery can increase efficiency and reduce costs. However, research on boosting the machine efficiency is limited. This study adopts a mixed review methodology (systematic review and bibliometric analysis) and evaluates emerging technologies such as digital twin, cyber physical systems, geographic information systems, global navigation satellite systems, onboard instrumentation systems, radio frequency identification, internet of things, telematics, machine learning, deep learning, and computer vision for machine productivity, and provides insights into how they can be used to improve the performance of construction equipment. This study defined three major equipment operating areas—monitoring and control, tracking and navigation, and data-driven performance optimization—classified technologies and explored how they can increase machine productivity. Other circumstantial issues affecting machine operation and loopholes in the existing innovative tools used in machine processes have also been highlighted. This study contributes to the goal of deploying digital tools and outlines future directions for the development of automated machines to optimize project efficiency.

Aim: A decision analysis model was constructed to explore the key factors affecting the job satisfaction of hospital nurses and to analyze the key satisfaction gaps in the case hospital. Background: In China, medical institutions are facing greater pressure and challenges in the normalization of epidemic prevention and control. Nurses play a critical role in the delivery of medical care services. Past studies have shown that improving job satisfaction among hospital nurses is important for both reducing nurse turnover and improving the quality of care. Methods: McCloskey/Mueller satisfaction scale (MMSS-31) was used to survey 25 nursing specialists in a case hospital in Zhejiang. Then, the Consistent Fuzzy Preference Relation (CFPR) method was used to analyze the degree of importance of dimensions and corresponding sub-criteria. Finally, the importance-performance analysis method was applied to identify critical satisfaction gaps for the case hospital. Results: In terms of local weight for dimensions, “Control/Responsibility (C8)” ≻ “Praise/Recognition (C7)” ≻ “Extrinsic Rewards (C1)” are the top three key factors for nurses’ work environment satisfaction in the case of a hospital. In addition, the sub-criteria “Salary (C11)”, “Benefits (C13)”, “Child care (C33)”, “Recognition-peers (C73)”, “Encouragement/feedback (C74)”, and “Decision making (C85)” are the key factors for improving clinical nursing satisfaction in the case hospital. Conclusion: The issues that nurses care about but for which they have not attained expectations mainly involved extrinsic rewards, recognition/encouragement and control over their working process. The findings of this study could offer an academic reference for management and remind them to consider the above factors in exploring future reform, further improving nurses' job satisfaction and motivating them to provide better nursing services.

Baicalein (BE) has both antioxidant and anti-inflammatory effects. It has also been reported able to improve cerebral blood circulation in brain ischemic injury. However, its chronic efficacy and metabolomics in Alzheimer's disease (AD) remain unknown. In this study, BE at 80 mg/kg was administrated through the oral route in J20 AD transgenic mice aged from aged 4 months to aged 10 months. Metabolic- and neurobehavioural phenotyping was done before and after 6 months' treatment to evaluate the drug efficacy and the relevant mechanisms. Meanwhile, molecular docking was used to study the binding affinity of BE and poly (ADP-ribose) polymerase-1 (PARP-1) which is related to neuronal injury. The open field test showed that BE could suppress hyperactivity in J20 mice and increase the frequency of the target quadrant crossing in the Morris Water Maze test. More importantly, BE restored cerebral blood flow back to the normal level after the chronic treatment. A 1H NMR-based metabolomics study showed that BE treatment could restore the tricarboxylic acid cycle in plasma. And such a treatment could suppress oxidative stress, inhibit neuroinflammation, alleviate mitochondrial dysfunction, improve neurotransmission, and restore amino homeostasis via starch and sucrose metabolism and glycolipid metabolism in the cortex and hippocampus, which could affect the behavioural and cerebral blood flow. These findings showed that BE is a potential therapeutic agent for AD.

Biobased furfural is a sustainable alternative to petrochemical intermediates for bulk chemicals and fuel production. However, existing methods for the conversion of xylose or lignocelluloses in mono-/bi-phasic systems to furfural involve non-selective sugar isolation or lignin condensation, limiting the valorisation of lignocelluloses. Herein, we used diformylxylose (DFX), a xylose derivative that is formed during the lignocellulosic fractionation process with formaldehyde protection, as a substitute for xylose to produce furfural in biphasic systems. Under kinetically optimized conditions, over 76 mol% of DFX could be converted to furfural in water-methyl isobutyl ketone system at a high reaction temperature with a short reaction time. Finally, isolation of xylan in eucalyptus wood as DFX with formaldehyde protection followed by converting DFX in a biphasic system gave a final furfural yield of 52 mol% (on the basis of xylan in wood), which was more than two times of that without formaldehyde. Combined with the value-added utilization of formaldehyde-protected lignin, this study would enable the full and efficient utilization of lignocellulosic biomass components and further improve the economics of the formaldehyde protection fractionation process.

Neurokinin-1 receptor (NK1R) belongs to tachykinin receptor family. Recent studies have suggested that NK1R was upregulated in cancer tissues including breast cancer, glioma and melanoma. Furthermore, NK1R antagonists have been employed to exert anti-tumor effect and promote cancer cell apoptosis. However, the role of NK1R in cervical cancer remains largely unknown. In this study, we aimed to detect the expression of NK1R in cervical cancer and evaluate the anti-tumor effects of NK1R antagonist on cervical cancer cells. We found that NK1R was highly expressed in cervical cancer tissues than in adjacent normal cervical tissues. Furthermore, by using NK1R antagonist we demonstrated that NK1R antagonist inhibited the viability and induced the apoptosis of cervical cancer cells in a dose-dependent manner, and the mechanism may be related to the inhibition of ERK activation and the regulation of apoptosis proteins Bcl-2 and BAX. In conclusion, these findings suggest that NK1R plays an oncogenic role in cervical cancer and is a promising target for cervical cancer therapy.

It is essential to explore the relationship between drugs and transporters in the process of drug development. Strong background signals in nonhuman MDCK or LLC-PK1 cells and overlapping interference of inhibitors or RNAi in human Caco-2 cells mean that an ideal alternative could be to knock out specific transporter genes in Caco-2 cells. However, the application of gene knockout (KO) to Caco-2 cells is challenging because it is still inefficient to obtain rapidly growing Caco-2 subclones with double-allele KO through long-term monoclonal cultivation. Herein, CRISPR/Cas9, a low cost but more efficient and precise gene editing technology, was utilized to singly or doubly knockout the P-gp, BCRP, and MRP2 genes in Caco-2 cells. By combining this with single cell expansion, rapidly growing transporter-deficient subclones were successfully screened and established. Bidirectional transport assays with probe substrates and three protease inhibitors indicated that more reliable and detailed data could be drawn easily with these KO Caco-2 models. The six robust KO Caco-2 subclones could contribute to efficient in vitro drug transport research.

Due to an extensive usage of heavy machinery, the construction sector is criticized as one of the major CO2 emitters. To address climate concerns, mitigating these greenhouse gas (GHG) emissions is important. This study aimed to strategize for “zero emission construction” by assessing the life cycle environmental impacts of diesel, electric, and hybrid construction machinery. By applying life cycle assessment (LCA) principles with adherence to ISO 14040/44 methodologies, this study scrutinizes the environmental repercussions of a standard excavator over 9200 effective operational hours, from raw material acquisition to end-of-life disposal. The results demonstrate a significant reduction in global warming potential (GWP), ozone depletion potential (ODP), and acidification potential (AP) in transitioning from diesel to hybrid and fully electric machines. A nominal increase due to this shift also occurred and impacted categories such as human carcinogenic toxicity (HT), freshwater eutrophication (EP), and marine ecotoxicity (ME); however, a more significant upsurge was noted in terrestrial ecotoxicity (TE) due to battery production. Thus, this study highlights the need for a careful management of environmental trade-offs in the shift toward electrified machinery and the importance of centering on the environmental profile of the battery. Future work should focus on enhancing the environmental profile of battery production and disposal, with policy decisions encouraging holistic sustainability based on green energies in construction projects.

Though shape-changing devices are promising for future haptic displays, existing designs fail to provide smooth surfaces for the user during tactile exploration. Here, the authors utilize flexible auxetic structures to realize shape displays with smooth surfaces and different Gaussian curvatures.

In this study, the impact of assimilating MWHS2 radiance data under different background conditions on the analyses and deterministic prediction of the Super Typhoon Muifa case, which hit China in 2022, was explored. The fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) data and the Global Forecast System (GFS) analysis data from the National Centers for Environmental Prediction (NCEP) were used as the background fields. To assimilate the Microwave Humidity Sounder II (MWHS2) radiance data into the numerical simulation experiments, the Weather Research and Forecasting (WRF) model and its three-dimensional variational data assimilation system were employed. The results show that after the data assimilation, the standard deviation and root-mean-square error of the analysis significantly decrease relative to the observation, indicating the effectiveness of the assimilation process with both background fields. In the MWHS_GFS experiment, a subtropical high-pressure deviation to the east is observed around the typhoon, resulting in its northeast movement. In the differential field of the MWHS_ERA experiment, negative sea-level pressure differences around the typhoon are observed, which increases its intensity. In the deterministic predictions, assimilating the FY3D MWHS2 radiance data reduces the typhoon track error in the MWHS_GFS experiment and the typhoon intensity error in the MWHS_ERA experiment. In addition, it is found that the Community Radiative Transfer Model (CRTM) and the Radiative Transfer for Tovs (RTTOV) model show similar performance in assimilating MWHS2 radiance data for this typhoon case. It seems that the data assimilation experiment with the CRTM significantly reduces the typhoon track error than the experiment with the RTTOV model does, while the intensity error of both experiments is rather comparable.

In recent years, with the rapid development of deep learning, the research of radar image automatic target recognition (ATR) has made great progress. However, because of the complex environments and special imaging principles, Synthetic Aperture Radar (SAR) image still have the problems of sample scarcity and strong speckle noise, which affects the target recognition performance. To solve the above problems, we proposed a target recognition method of SAR image based on Constrained Naive Generative Adversarial Networks (CN-GAN) and Convolutional Neural Network (CNN). Combining Least Squares Generative Adversarial Networks (LSGAN) and Image-to-Image Translation (Pix2Pix), CN-GAN can overcome these problems of low Signal-to-Clutter-Noise Ratio (SCNR), model instability and the excessive freedom degree of the output, which are produced by conventional naive GAN. Besides, we adopted a shallow network structure design in CNN, which can effectively improve the generalization ability of the model and avoid the problem of model overfitting. The experimental results in this paper demonstrate that CN-GAN has achieved the data generation and data enhancement, the SCNR of generated data is higher than the origin data set and data sets gained by other forms of GANs, the recognition performance based on the extended data set is better than the origin data set, and the recognition rate of data set enhanced by CN-GAN is higher than that of other common data enhancement methods.

The construction industry lacks a comprehensive and holistic way of utilizing Building Information Modeling (BIM) throughout a building's life-cycle, where the transition to Asset Management (AM) and Facility Management (FM) is particularly lacking. Enterprise BIM (EBIM) is an emerging, unexplored, holistic organizational concept that is designed to support and optimize business management throughout the entire life-cycles of buildings and infrastructure. However, current understanding and implementation of EBIM is rare. To fix this gap in knowledge, this paper defines the EBIM concept and assesses associated perspectives from research and practice in order to integrate BIM more strongly into the enterprise's core processes and other needs at different levels within the organization and externally. To achieve a higher and more efficient utilization of building data, however, EBIMs need to develop a clear life-cycle-based information management strategy, including coordination and communication between all stakeholders. The paper highlights and discusses the importance of both available and missing standards related to the effective implementation of EBIM. Several existing open standards have been identified to help strengthen the EBIM concept. The paper identifies a need to develop standards to integrate BIM and IoT (the Internet of Things) and standards that can handle both structured and unstructured data. The authors have conducted a wide-ranging review of research, practice and existing standards and considers today's potential for using EBIM, as well as discusses existing challenges and future research needs. Furthermore, the EBIM concept is contextualized by providing a case study with focus on cleaning. This study identifies a need to develop best practices in interdisciplinary collaborative projects. Such practical implementation requires integrated and standardized information and technology management and the exploitation of the available technologies in interdisciplinary interaction with those involved in the various processes and the flow of information throughout the life-cycle.

With the global epidemic of SARS-CoV-2, it is important to effectively monitor the variation, haplotype subgroup epidemic trends and key mutations of SARS-CoV-2 over time. This is of great significance to the development of new vaccines, the update of therapeutic drugs, and the improvement of detection methods. The AutoVEM tool developed in the present study could complete all mutations detections, haplotypes classification, haplotype subgroup epidemic trends and candidate key mutations analysis for 131,576 SARS-CoV-2 genome sequences in 18 h on a 1 core CPU and 2 GB RAM computer. Through haplotype subgroup epidemic trends analysis of 131,576 genome sequences, the great significance of the previous 4 specific sites (C241T, C3037T, C14408T and A23403G) was further revealed, and 6 new mutation sites of highly linked (T445C, C6286T, C22227T, G25563T, C26801G and G29645T) were discovered for the first time that might be related to the infectivity, pathogenicity or host adaptability of SARS-CoV-2. In brief, we proposed an integrative method and developed an efficient automated tool to monitor haplotype subgroup epidemic trends and screen for the candidate key mutations in the evolution of SARS-CoV-2 over time for the first time, and all data could be updated quickly to track the prevalence of previous key mutations and new candidate key mutations because of high efficiency of the tool. In addition, the idea of combinatorial analysis in the present study can also provide a reference for the mutation monitoring of other viruses.

In our previous work, we developed an automated tool, AutoVEM, for real-time monitoring the candidate key mutations and epidemic trends of SARS-CoV-2. In this research, we further developed AutoVEM into AutoVEM2. AutoVEM2 is composed of three modules, including call module, analysis module, and plot module, which can be used modularly or as a whole for any virus, as long as the corresponding reference genome is provided. Therefore, it’s much more flexible than AutoVEM. Here, we analyzed three existing viruses by AutoVEM2, including SARS-CoV-2, HBV and HPV-16, to show the functions, effectiveness and flexibility of AutoVEM2. We found that the N501Y locus was almost completely linked to the other 16 loci in SARS-CoV-2 genomes from the UK and Europe. Among the 17 loci, 5 loci were on the S protein and all of the five mutations cause amino acid changes, which may influence the epidemic traits of SARS-CoV-2. And some candidate key mutations of HBV and HPV-16, including T350G of HPV-16 and C659T of HBV, were detected. In brief, we developed a flexible automated tool to analyze candidate key mutations and epidemic trends for any virus, which would become a standard process for virus analysis based on genome sequences in the future.

Abstract Parkinson’s disease (PD) is the second most common neurodegenerative disease, and mild cognitive impairment (MCI) is a well-established risk factor for the development of dementia in PD. A growing body of evidence suggests that low expression of glucocerebrosidase (GBA) promotes the transmission of α-synuclein (α-Syn) interpolymers and the progression of PD. However, how GBA mutations affect the pathogenesis of PD via abnormal aggregation of α-Syn is unclear, and no clinically valid PD-MCI genetic markers have been identified. Here, we first located a GBA eQTL, rs12411216, by analysing DHS, eQTL SNP, and transcription factor binding site data using the UCSC database. Subsequently, we found that rs12411216 was significantly associated with PD-MCI (P

A supply chain consists of many stakeholders such as suppliers, carriers and customers. It is often complex due to the rapid development of economic globalization and the intense competition pressure in the market which resulted in information sharing within a supply chain to be fragmented. Blockchain technology can solve this problem by having only a “one trusted ledger” that could reshape the element of data trust. The goal of this paper is to identify and understand the impact of blockchain technology for information sharing within a supply chain. The decentralized nature of blockchain technology offers a high level of transparency and has gained the attention from various sectors to deploy this technology. A systematic literature review in the academic literature was conducted using different databases. Blockchain-enabled information sharing can add value to enhance collaborative work in different types of supply chains such as health and medical, construction and smart city. From our findings, one potential impact of deploying blockchain-enabled information sharing within a supply chain is that it ensures all members in the chain can obtain verified information which enhances collaborative partnerships. Through this in-depth research, we highlighted potential barriers that could impede the development of blockchain technology in supply chain such as the lack of understanding of blockchain technology in businesses and conflict of interests. Future work such as information hiding, in parallel with information sharing, could close the gap in deploying this technology within a supply chain. Understanding the nature of different supply chain is also important to better prepare the deployment of blockchain. We acknowledge that our approach in selecting literatures in our systematic review may exclude certain literatures. Nonetheless, we tried to include as many relevant literatures as possible, to develop a roadmap on the current situation of blockchain-enabled information sharing within a supply chain.

Objective(s): microRNA-29 (miR-29) family miRNAs have been mentioned as tumor suppressive genes in several human cancers. The purpose of this study was to investigate the function of miR-29a in nasopharyngeal carcinoma (NPC) cells. Materials and Methods: Human NPC cell line 5-8F was transfected with mimic, inhibitor or scrambled controls specific for miR-29a. Subsequently, cell viability, migration, apoptosis and expression changes of VEGF were assessed by trypan blue staining, MTT assay, transwell assay, flow cytometry, Western blot and RT-qPCR. TargetScan online database was used to predict the targets of miR-29a, and luciferase reporter assay was carried out for testing the targeting relationship between VEGF and miR-29a. Western blot analysis was performed to determine the expression changes of core proteins in PI3K/AKT and JAK/STAT pathways. Results: Overexpression of miR-29a suppressed 5-8F cells viability and relative migration, but increased apoptotic cell rate. Consistently, Bcl-2 was downregulated, Bax was upregulated, and caspase-3 and -9 were cleaved by miR-29a overexpression. VEGF was a target gene of miR-29a. Besides, VEGF silence exerted similar effects like miR-29a, as the viability and migration were repressed and apoptosis was induced. Finally, we found that PI3K/AKT and JAK/STAT pathways were deactivated by miR-29a or VEGF silence. Conclusion: These findings highlighted the tumor suppressive effects of miR-29a on NPC cells, as its overexpression inhibited 5-8F cells viability, migration, and induced apoptosis. miR-29a exerted tumor suppressive functions might be via targeting VEGF and deactivating PI3K/AKT and JAK/STAT pathways.

Aiming at the problem of radar target recognition of High-Resolution Range Profile (HRRP) under low signal-to-noise ratio conditions, a recognition method based on the Constrained Naive Least-Squares Generative Adversarial Network (CN-LSGAN), Short-time Fourier Transform (STFT), and Convolutional Neural Network (CNN) is proposed. Combining the Least-Squares Generative Adversarial Network (LSGAN) with the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP), the CN-LSGAN is presented and applied to the HRRP denoise. The frequency domain and phase features of HRRP are gained by STFT in order to facilitate feature learning and also match the input data format of the CNN. These experimental results show that the CN-LSGAN has better data augmentation performance and can effectively avoid the model collapse compared to the generative adversarial network (GAN) and LSGAN. Also, the method has better recognition performance than the one-dimensional CNN method and the Long Short-Term Memory (LSTM) network method.

In the past three decades, organic semiconductor field-effect transistors (OFETs) have drawn intense attention as promising candidates for drive circuits of flat panel display, radio frequency identifications, chemical/bio-sensors, and other devices. Generally, the key parameters of OFETs, carrier mobility, threshold voltage, and on/off current ratio are closely related to the degree of order and surface/interface electronic structure of organic semiconductor (OSC) films. The ordering of films is crucially determined by the molecule-substrate interactions. On inert substrates (such as SiO2) OSC films can hardly reach a high degree of ordering without growth templates, while traditional single crystal surfaces usually force the OSC molecules to deviate from their favorite assemble manner resulting in an unstable structure. Recently, the rise of two-dimensional materials (2D) provides a possible solution. The in-plane lattice of 2D materials can offer possible epitaxy templates for OSCs while the weak van der Waals (vdWs) interaction between OSC and 2D layers allows for more flexibility to realize the epitaxy growth of OSCs with their favored assemble manner. In addition, the various band structures tuned by the layer numbers of 2D materials encourage widely modified OSC electronic structures by interface doping between the OSC and 2D layers, which benefits the structure by obtaining high-performance OFETs. In this review, we emphasize and discuss the recent advances of OSC-2D hybrid OFETs. The OSC-2D heterostructures not only promote OFET device performances by film morphology/structure optimization and channel electronic structure modification, but also offer platforms for basic organic solids physics investigation and further functional optoelectronic devices.

A vacuum evaporator is widely used for generating atomic/molecular beams for thin film deposition, and conventionally must be mounted to a vacuum chamber with an upwards angle from the horizontal. In this article, we report a novel kind of evaporator that can be mounted at an arbitrary angle for organic materials. The crucible of the evaporator here is designed to keep the loaded organic materials from falling. The morphology and electrical characteristics of pentacene thin film organic field effect transistors on trichloro(octadecyl)silane modified SiO2 are characterized and compared for commercial and arbitrary mounting angle evaporators. Pentacene films deposited from both evaporators exhibit similar morphology and domain size characterized by atomic force microscope, as well as similar mobility, threshold voltage, and on/off ratio. The results can be used to develop a new configuration for an organic vacuum deposition system, which allows the positioning of shadow masks directly on substrates and thus avoids deformation, enabling fabrication of organic electronics for high resolution over large areas.

Skeletal muscle long non-coding RNAs (lncRNAs) were reported to be involved in the development of type 2 diabetes (T2D). However, little is known about the mechanism of skeletal muscle lncRNAs on hyperglycemia of diabetic Goto-Kakizaki (GK) rats at the age of 3 and 4 weeks. To elucidate this, we used RNA-sequencing to profile the skeletal muscle transcriptomes including lncRNAs and mRNAs, in diabetic GK and control Wistar rats at the age of 3 and 4 weeks. In total, there were 438 differentially expressed mRNAs (DEGs) and 401 differentially expressed lncRNAs (DELs) in skeletal muscle of 3-week-old GK rats compared with age-matched Wistar rats, and 1000 DEGs and 726 DELs between GK rats and Wistar rats at 4 weeks of age. The protein–protein interaction analysis of overlapping DEGs between 3 and 4 weeks, the correlation analysis of DELs and DEGs, as well as the prediction of target DEGs of DELs showed that these DEGs (Pdk4, Stc2, Il15, Fbxw7 and Ucp3) might play key roles in hyperglycemia, glucose intolerance, and increased fatty acid oxidation. Considering the corresponding co-expressed DELs with high correlation coefficients or targeted DELs of these DEGs, our study indicated that these dysregulated lncRNA-mRNA pairs (NONRATG017315.2-Pdk4, NONRATG003318.2-Stc2, NONRATG011882.2-Il15, NONRATG013497.2-Fbxw7, MSTRG.1662-Ucp3) might be related to above biological processes in GK rats at the age of 3 and 4 weeks. Our study could provide more comprehensive knowledge of mRNAs and lncRNAs in skeletal muscle of GK rats at 3 and 4 weeks of age. And our study may provide deeper understanding of the underlying mechanism in T2D of GK rats at the age of 3 and 4 weeks.

The scale of SARS-CoV-2 infection and death is so enormous that further study of the molecular and evolutionary characteristics of SARS-CoV-2 will help us better understand and respond to SARS-CoV-2 outbreaks. The present study analyzed the epidemic and evolutionary characteristics of haplotype subtypes or regions based on 1.8 million high-quality SARS-CoV-2 genomic data. The estimated ratio of the rates of non-synonymous to synonymous changes (Ka/Ks) in North America and the United States were always more than 1.0, while the Ka/Ks in other continents and countries showed a sharp decline, then a slow increase to 1.0, and a dramatic increase over time. H1 (B.1) with the highest substitution rate has become the most dominant haplotype subtype since March 2020 and has evolved into multiple haplotype subtypes with smaller substitution rates. Many evolutionary characteristics of early SARS-CoV-2, such as H3 being the only early haplotype subtype that existed for the shortest time, the global prevalence of H1 and H1-5 (B.1.1) within a month after being detected, and many high divergent genome sequences early in February 2020, indicate the missing of early SARS-CoV-2 genomic data. SARS-CoV-2 experienced dynamic selection from December 2019 to August 2021 and has been under strong positive selection since May 2021. Its transmissibility and the ability of immune escape may be greatly enhanced over time. This will bring greater challenges to the control of the pandemic.

Abstract The monocytic MDSC (M‐MDSC) is one of the major types of MDSCs, which play important roles in suppression of antitumor immunity. However, the mechanisms underlying how M‐MDSCs so heavily accumulate in patients with cancer are still poorly understood. The purpose of this study was to identify miRNAs that regulate the proliferation and differentiation of M‐MDSCs. Microarray analysis was performed to identify differentially expressed miRNAs between tumor‐induced M‐MDSCs (TM‐MDSCs) and their counterparts from tumor‐free mice. The miRNAs and their target genes that regulate the proliferation and differentiation of myeloid cells were predicted by bioinformatics analysis and validated by RT‐qPCR. Luciferase reporter assays were used to analyze the relationships between miRNAs and target genes. Overexpression of candidate miRNAs and target genes in myeloid cells was conducted to verify their functions in cell proliferation, differentiation, and apoptosis. Our data showed that miR‐486 was overexpressed in TM‐MDSCs. Cebpa was predicted to be one of the target genes of miR‐486 that regulates the proliferation of myeloid cells. Expression of Cebpa was inversely correlated with miR‐486 in TM‐MDSCs, and we found that overexpression of miR‐486 suppressed the expression of Cebpa in both 293T cells determined by luciferase reporter assays and in myeloid cells determined by RT‐qPCR. Overexpression of miR‐486 promoted proliferation and suppressed apoptosis in myeloid cells, as opposed to overexpression of Cebpa, which promoted the opposing phenotype. Overexpression of either miR‐486 or Cebpa inhibited differentiation of myeloid cells. This study indicates that miR‐486 promotes proliferation and suppresses apoptosis in myeloid cells by targeting Cebpa in vitro, suggesting that miR‐486 and Cebpa might be involved in the expansion of TM‐MDSCs in tumor‐bearing mice.

The mortality rate of hemorrhagic African swine fever (ASF), which targets domestic pigs and wild boars is caused by African swine fever virus (ASFV), can reach 100%. Since the first confirmed ASF outbreak in China on 3 August 2018, 156 ASF outbreaks were detected in 32 provinces. About 1,170,000 pigs were culled in order to halt further spread. There is no effective treatment or vaccine for it and the present molecular diagnosis technologies have trade-offs in sensitivity, specificity, cost and speed, and none of them cater perfectly to ASF control. Thus, a technology that overcomes the need for laboratory facilities, is relatively low cost, and rapidly and sensitively detects ASFV would be highly valuable. Here, we describe an RAA-Cas12a-based system that combines recombinase aided amplification (RAA) and CRISPR/Cas12a for ASFV detection. The fluorescence intensity readout of this system detected ASFV p72 gene levels as low as 10 aM. For on-site ASFV detection, lateral-flow strip readout was introduced for the first time in the RAA-Cas12a based system (named CORDS, Cas12a-based On-site and Rapid Detection System). We used CORDS to detect target DNA highly specifically using the lateral-flow strip readout and the assay displayed no cross-reactivity to other 13 swine viruses including classical swine fever (CSF). CORDS could identify the ASFV DNA target at femtomolar sensitivity in an hour at 37°C, and only requires an incubator. For ease of use, the reagents of CORDS were lyophilized to three tubes and remained the same sensitivity when stored at 4°C for at least 7 days. Thus, CORDS provide a rapid, sensitive and easily operable method for ASFV on-site detection. Lyophilized CORDS can withstand long-term transportation and storage, and is ready for field-based applications.

The hypothalamus has an integral role in energy homeostasis regulation, and its dysfunctions lead to the development of type 2 diabetes (T2D). Physical activity positively affects the prevention and treatment of T2D. However, there is not much information on the adaptive mechanisms of the hypothalamus. In this study, RNA sequencing was used to determine how acute exercise affects hypothalamic transcriptome from both type 2 diabetic Goto-Kakizaki (GK) and control Wistar rats with or without a single session of running (15 m/min for 60 min). Through pairwise comparisons, we identified 957 differentially expressed genes (DEGs), of which 726, 197, and 98 genes were found between GK and Wistar, exercised GK and GK, and exercised Wistar and Wistar, respectively. The results of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment revealed that lipid metabolism-related terms and pathways were enriched in GK and exercised GK rats, and nervous system related terms and pathways were enriched in exercised GK and Wistar rats. Furthermore, 45 DEGs were associated with T2D and related phenotypes according to the annotations in the Rat Genome Database. Among these 45 DEGs, several genes (Plin2, Cd36, Lpl, Wfs1, Cck) related to lipid metabolism or the nervous system are associated with the exercise-induced benefits in the hypothalamus of GK rats. Our findings might assist in identifying potential therapeutic targets for T2D prevention and treatment.

Physical activity exerts positive effects on glycemic control in type 2 diabetes (T2D), which is mediated in part by extensive metabolic and molecular remodeling of skeletal muscle in response to exercise, while many regulators of skeletal muscle remain unclear. In the present study, we investigated the effects of acute exercise on skeletal muscle transcriptomic responses in the Goto-Kakizaki (GK) rats which can spontaneously develop T2D. The transcriptomes of skeletal muscle from both 8-week-old GK and Wistar rats that underwent a single exercise session (60 min running using an animal treadmill at 15 m/min) or remained sedentary were analyzed by next-generation RNA sequencing. We identified 819 differentially expressed genes in the sedentary GK rats compared with those of the sedentary Wistar rats. After a single bout of running, we found 291 and 598 genes that were differentially expressed in the exercise GK and exercise Wistar rats when compared with the corresponding sedentary rats. By integrating our data and previous studies including RNA or protein expression patterns and transgenic experiments, the downregulated expression of Fasn and upregulated expression of Tbc1d1, Hk2, Lpin1, Ppargc1a, Sorbs1, and Hmox1 might enhance glucose uptake or improve insulin sensitivity to ameliorate hyperglycemia in the exercise GK rats. Our results provide mechanistic insight into the beneficial effects of exercise on hyperglycemia and insulin action in skeletal muscle of diabetic GK rats.

How the human brain differs from those of non-human primates is largely unknown and the complex drivers underlying such differences at the genomic level remain unclear. In this study, we selected 243 brain-related genes, based on Gene Ontology, and identified 184,113 DNaseI hypersensitive sites (DHSs) within their regulatory regions. To performed comprehensive evolutionary analyses, we set strict filtering criteria for alignment quality and filtered 39,132 DHSs for inclusion in the investigation and found that 2,397 (~6%) exhibited evidence of accelerated evolution (aceDHSs), which was a much higher proportion that DHSs genome-wide. Target genes predicted to be regulated by brain-aceDHSs were functionally enriched for brain development and exhibited differential expression between human and chimpanzee. Alignments indicated 61 potential human-specific transcription factor binding sites in brain-aceDHSs, including for CTCF, FOXH1, and FOXQ1. Furthermore, based on GWAS, Hi-C, and eQTL data, 16 GWAS SNPs, and 82 eQTL SNPs were in brain-aceDHSs that regulate genes related to brain development or disease. Among these brain-aceDHSs, we confirmed that one enhanced the expression of GPR133, using CRISPR-Cas9 and western blotting. The GPR133 gene is associated with glioblastoma, indicating that SNPs within DHSs could be related to brain disorders. These findings suggest that brain-related gene regulatory regions are under adaptive evolution and contribute to the differential expression profiles among primates, providing new insights into the genetic basis of brain phenotypes or disorders between humans and other primates.

The Goto Kakizaki (GK) rats which can spontaneously develop type 2 diabetes (T2D), are generated by repeated inbreeding of Wistar rats with glucose intolerance. The glucose intolerance in GK rat is mainly attributed to the impairment in glucose-stimulated insulin secretion (GSIS). In addition, GK rat display a decrease in beta cell mass, and a change in insulin action. However, the genetic mechanism of these features remain unclear. In the present study, we analyzed the population variants of GK rats and control Wistar rats by whole genome sequencing and identified 1,839 and 1,333 specific amino acid changed (SAAC) genes in GK and Wistar rats, respectively. We also detected the putative artificial selective sweeps (PASS) regions in GK rat which were enriched with GK fixed variants and were under selected in the initial diabetic-driven derivation by homogeneity test with the fixed and polymorphic sites between GK and Wistar populations. Finally, we integrated the SAAC genes, PASS region genes and differentially expressed genes in GK pancreatic beta cells to reveal the genetic mechanism of the impairment in GSIS, a decrease in beta cell mass, and a change in insulin action in GK rat. The results showed that Slc2a2 gene was related to impaired glucose transport and Adcy3, Cacna1f, Bmp4, Fam3b, and Ptprn2 genes were related to Ca2+ channel dysfunction which may responsible for the impaired GSIS. The genes Hnf4g, Bmp4, and Bad were associated with beta cell development and may be responsible for a decrease in beta cell mass while genes Ide, Ppp1r3c, Hdac9, Ghsr, and Gckr may be responsible for the change in insulin action in GK rats. The overexpression or inhibition of Bmp4, Fam3b, Ptprn2, Ide, Hnf4g, and Bad has been reported to change the glucose tolerance in rodents. However, the genes Bmp4, Fam3b, and Ptprn2 were found to be associated with diabetes in GK rats for the first time in the present study. Our findings provide a comprehensive genetic map of the abnormalities in GK genome which will be helpful in understand the underlying genetic mechanism of pathogenesis of diabetes in GK rats.

In this paper, we give a review of our theoretical and experimental progress in octahedral spherical hohlraum study. From our theoretical study, the octahedral spherical hohlraums with 6 Laser Entrance Holes (LEHs) of octahedral symmetry have robust high symmetry during the capsule implosion at hohlraum-to-capsule radius ratio larger than 3.7. In addition, the octahedral spherical hohlraums also have potential superiority on low backscattering without supplementary technology. We studied the laser arrangement and constraints of the octahedral spherical hohlraums, and gave a design on the laser arrangement for ignition octahedral hohlraums. As a result, the injection angle of laser beams of 50°–60° was proposed as the optimum candidate range for the octahedral spherical hohlraums. We proposed a novel octahedral spherical hohlraum with cylindrical LEHs and LEH shields, in order to increase the laser coupling efficiency and improve the capsule symmetry and to mitigate the influence of the wall blowoff on laser transport. We studied on the sensitivity of the octahedral spherical hohlraums to random errors and compared the sensitivity among the octahedral spherical hohlraums, the rugby hohlraums and the cylindrical hohlraums, and the results show that the octahedral spherical hohlraums are robust to these random errors while the cylindrical hohlraums are the most sensitive. Up till to now, we have carried out three experiments on the spherical hohlraum with 2 LEHs on Shenguang(SG) laser facilities, including demonstration of improving laser transport by using the cylindrical LEHs in the spherical hohlraums, spherical hohlraum energetics on the SGIII prototype laser facility, and comparisons of laser plasma instabilities between the spherical hohlraums and the cylindrical hohlraums on the SGIII laser facility.

The octahedral spherical hohlraums have natural superiority in maintaining high radiation symmetry during the entire capsule implosion process in indirect drive inertial confinement fusion. While, in contrast to the cylindrical hohlraums, the narrow space between the laser beams and the spherical hohlraum wall is usually commented. In this Letter, we address this crucial issue and report our experimental work conducted on the SGIII-prototype laser facility which unambiguously demonstrates that a simple design of cylindrical laser entrance hole (LEH) can dramatically improve the laser propagation inside the spherical hohlraums. In addition, the laser beam deflection in the hohlraum is observed for the first time in the experiments. Our 2-dimensional simulation results also verify qualitatively the advantages of the spherical hohlraums with cylindrical LEHs. Our results imply the prospect of adopting the cylindrical LEHs in future spherical ignition hohlraum design.

This study aims to improve the interoperability between the application domains of Building Information Modelling (BIM) and Geographic Information Systems (GIS) by linking and harmonizing core information concepts. Many studies have investigated the integration of application schemas and data instances according to the BIM model IFC and the GIS model CityGML. This study investigates integration between core abstract concepts from IFC and ISO/TC 211 standards for GIS—independent of specific application schemas. A pattern was developed for conversion from IFC EXPRESS schemas to Unified Modelling Language (UML) models according to ISO/TC 211 standards. Core concepts from the two application domains were linked in the UML model, and conversions to implementation schemas for the Geography Markup Language (GML) and EXPRESS were tested. The results showed that the IFC model could be described as an ISO/TC 211 compliant UML model and that abstract concepts from ISO/TC 211 standards could be linked to core IFC concepts. Implementation schemas for BIM and GIS formats could be derived from the UML model, enabling implementation in applications from both domains without conversion of concepts. Future work should include refined linking and harmonization of core abstract concepts from the two application domains.

Construction and demolition waste (C&D waste) are widely recognized as the main form municipal solid waste, and its recycling and reuse are an important issue in sustainable city development. Material flow analysis (MFA) can quantify materials flows and stocks, and is a useful tool for the analysis of construction and demolition waste management. In recent years, material flow analysis has been continually researched in construction and demolition waste processing considering both single waste material and mixed wastes, and at regional, national, and global scales. Moreover, material flow analysis has had some new research extensions and new combined methods that provide dynamic, robust, and multifaceted assessments of construction and demolition waste. In this paper, we summarize and discuss the state of the art of material flow analysis research in the context of construction and demolition waste recycling and disposal. Furthermore, we also identify the current research gaps and future research directions that are expected to promote the development of MFA for construction and demolition waste processing in the field of sustainable city development.

This study aims to improve the implementation of models of geospatial information in Web Ontology Language (OWL). Large amounts of geospatial information are maintained in Geographic Information Systems (GIS) based on models according to the Unified Modeling Language (UML) and standards from ISO/TC 211 and the Open Geospatial Consortium (OGC). Sharing models and geospatial information in the Semantic Web will increase the usability and value of models and information, as well as enable linking with spatial and non-spatial information from other domains. Methods for conversion from UML to OWL for basic concepts used in models of geospatial information have been studied and evaluated. Primary conversion challenges have been identified with specific attention to whether adapted rules for UML modelling could contribute to improved conversions. Results indicated that restrictions related to abstract classes, unions, compositions and code lists in UML are challenging in the Open World Assumption (OWA) on which OWL is based. Two conversion challenges are addressed by adding more semantics to UML models: global properties and reuse of external concepts. The proposed solution is formalized in a UML profile supported by rules and recommendations and demonstrated with a UML model based on the Intelligent Transport Systems (ITS) standard ISO 14825 Geographic Data Files (GDF). The scope of the resulting ontology will determine to what degree the restrictions shall be maintained in OWL, and different conversion methods are needed for different scopes.

This study aims to improve interoperability between Geographic Information Systems (GIS) and geospatial databases for Intelligent Transport Systems (ITS). Road authorities maintain authoritative information for legal and safe navigation in GIS databases. This information needs to be shared with ITS databases for route planning and navigation, and for use in combination with local knowledge from vehicle sensors. Current solutions for modelling and exchanging geospatial information in the domains of GIS and ITS have been studied and evaluated. Limitations have been pointed out related to usability in the GIS domain and flexibility for representing an evolving real world. A prototype for an improved information exchange model has been developed, based on ISO/TC 211 standards, Model Driven Architecture (MDA), and concepts from the studied solutions. The prototype contains generic models for feature catalogues and features, with implementation schemas in the Geography Markup Language (GML). Results from a case study indicated that the models could be implemented with feature catalogues from the ITS standard ISO 14825 Geographic Data Files (GDF) and the INSPIRE Transport Networks specification. The prototype can be a candidate solution for improved information exchange from GIS databases to ITS databases that are based on the Navigation Data Standard.