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As the fifth subversive and innovative technology for computing paradigm after the mainframe computer, personal computer, internet and mobile/social network, blockchain technology has entered into a new phase of development. Nevertheless, more intrinsic issues remain to be explored. With the usage of cryptography and a distributed database, once a block is recorded, it can no longer be changed. To defeat these issues, more existing techniques have emerged. The blockchain system mainly features decentralization, but as the existing architectures of the blockchain system are mixed up, it is hard to determine whether they are centralized or decentralized. Such hybrid feature is derived from the impact of uncertainty of human demands. In this study, we intend to explore the scientific perception of the blockchain technology after its integration with human activities by adopting the method of interaction design. Furthermore, we plan to establish a set of mechanisms on the method of blockchain system-based interaction design, so as to identify the impact of human uncertainty factors on the design of the blockchain system. In addition, we aim to provide theoretical guidance for establishing the decentralized blockchain systems in both standardized and mixed categories and the centralized blockchain system with decentralization as central node. Through the methods of the observational results, the article is summarized and assessed the methods of the interaction design based on blockchain system. Moreover, the evaluation process consists of the analysis of expert evaluation, practical evaluation and participatory evaluation ferments an efficient outcome. &nbsp

The energy consumption of the whole life cycle of the existing buildings in China exceeds 50% of the total energy consumption of the society. With the rapid development of the construction industry, this proportion is still growing. On the whole, there is a lack of analysis of the factors related to energy consumption and comfort in the process of building scheme design at this stage. In addition, designers have insufficient understanding of the theoretical system of low-energy buildings, and it is difficult to optimise the scheme throughout the design. To solve these problems, this research first proposes an integrated design method of green buildings based on building information modelling technology. This method integrates and shares engineering information, problem solving, simulation tools, architectural model applications and architectural team communication platforms, which can effectively address the problem that the current green building projects do not belong to each other when designing. The research also proposes a multi-objective optimisation algorithm based on the genetic algorithm. The proposed method optimises the overall design of green buildings, particularly the design of natural lighting, starting from the influence relationship between targets and targets and between targets and enclosure systems. To obtain the optimal effect, the virtual function of Traind was selected as the training function after testing. In addition, the model obtained a reasonable range of design parameters according to the energy consumption of the building in the uncomfortable time. Finally, the method proposed in the study was tested. The experimental results showed that compared with the overall energy consumption of the initial scheme, that of the optimised scheme was reduced by 10.46%; the natural light coefficient increased by 0.44%; and the pressure differeces pascal hours (PDPH) was optimised by 5.38%. The optimisation scheme can effectively reduce the energy consumption of the building in the whole life cycle and improve comfort.

In many multi criteria group decision making problems, the individual evaluation values offered by experts are with uncertainties. Therefore, when assigning weights to those experts using preferences induced weights allocation, we can have two types of bi-polar preferences. The first one is the optimism-pessimism preference over evaluation values; the second one is the uncertainty aversion preference over the attached numerical certainty/uncertainty degrees. When performing preferences induced weights allocation, the certainty/uncertainty degrees will affect the optimism-pessimism preference induced weights allocation because the magnitudes of those evaluation values might not be the exact ones. Moreover, the importance of those experts in multi criteria group decision making can also have influence over the two types of preference induced weights allocation processes, and the importance can also be with uncertainties and can be expressed using basic uncertain information. Therefore, to handle this situation with multiple inducing variables and uncertainties, we simultaneously consider the influence of the uncertainties attached to evaluation values and the influence of uncertain importance of experts, and thus we at the same time adopt the method of confidence threshold and the method of uncertain importance level function to propose some synthesized method to adjust the induced weights allocation processes. We also propose a complete multi criteria group decision making problems to show the feasibility and reasonability of the proposed decision model for the complex situation where both evaluation values and expert importance are expressed by basic uncertain information.

Due to the complexity of the design of multilayer electromagnetic (EM) wave absorbing materials, it is difficult to establish the relationship between material parameters (type and filling ratios) and EM properties using traditional trial and error methods. Based on the measured EM parameters within a few materials and Boltzmann mixing theory, a database of EM parameters was thereafter built up. In this study, the genetic algorithm (GA) was used to design the multilayer wave-absorbing cement mortar. In order to verify this method, a multilayer mortar was fabricated and measured. The simulated and measured results are well consistent, which convincingly verifies computer-aided design. In addition, the optimized result expresses that the first layer as a matching layer guides EM waves into the interior of the material, while the other layers as absorption layers attenuate EM waves. The multilayer material may not meet the impedance gradient principle but still exhibits better EM wave absorption performance. The reflection loss (RL) of all optimized three layer sample is below –6.89 dB in the full frequency band and the minimum RL is –26.21 dB. This composite absorbing material and the GA method provide more design ideas for the design of future cement-based wave-absorbing materials and save a lot of time and material cost.

Aspect-dependent landslide initiation is an interesting finding, and previous studies have attributed this to the mechanical effects of plant roots. In the present study, an overwhelming landslide probability on a south-facing slope over a north-facing slope was found in a localized area with only granite underneath and high cover of Larix kaempferi. These observations cannot be attributed to plant roots but may result from factors related to hillslope hydrology. Differential weathering associated with hillslope hydrology behaviors such as rainfall water storage and leakage, pore water pressure, particle component, and hillslope stability fluctuation were used to examine these observations. Remote sensing interpretation using the high-resolution GeoEye-1 image, digitalized topography, and field investigations showed that landslides on south-facing slopes have a higher probability, larger basal area, and shallower depth than those on a north-facing slope. The lower limits of the upslope-contributing area and slope gradient condition for south-facing landslides were less than those for north-facing landslides. The higher basal areas of south-facing landslides than those of the north-facing landslides may be attributed to the high peak values and slow dissipation of pore water pressure. The absorbed and drained water flow in a given time interval, together with the calculated water storage and leakage measured during the rainy season, demonstrate that the soil mass above the failure zone for south-facing slope is more prone to pore water pressure, which results in slope failures. In comparison, the two stability fluctuation results from the finite and infinite models further verified that landslides on south-facing slopes may fail under conditions of prolonged antecedent precipitation and intensive rainfall. Meanwhile, those on north-facing slopes may fail only in response to intensive rainfall. The results of this study will deepen our knowledge of aspect-dependent landslide initiation from both classical mechanics and the state of stress.

In the last three years, the capacity of health care systems and the public health policies of governments worldwide were challenged by the spread of SARS-CoV-2. Mortality due to SARS-CoV-2 mainly resulted from the development of acute lung injury (ALI)/acute respiratory distress syndrome (ARDS). Moreover, millions of people who survived ALI/ARDS in SARS-CoV-2 infection suffer from multiple lung inflammation-induced complications that lead to disability and even death. The lung-bone axis refers to the relationship between lung inflammatory diseases (COPD, asthma, and cystic fibrosis) and bone diseases, including osteopenia/osteoporosis. Compared to chronic lung diseases, the influence of ALI on the skeleton has not been investigated until now. Therefore, we investigated the effect of ALI on bone phenotypes in mice to elucidate the underlying mechanisms. In vivo bone resorption enhancement and trabecular bone loss were observed in LPS-induced ALI mice. Moreover, chemokine (C-C motif) ligand 12 (CCL12) accumulated in the serum and bone marrow. In vivo global ablation of CCL12 or conditional ablation of CCR2 in bone marrow stromal cells (BMSCs) inhibited bone resorption and abrogated trabecular bone loss in ALI mice. Furthermore, we provided evidence that CCL12 promoted bone resorption by stimulating RANKL production in BMSCs, and the CCR2/Jak2/STAT4 axis played an essential role in this process. Our study provides information regarding the pathogenesis of ALI and lays the groundwork for future research to identify new targets to treat lung inflammation-induced bone loss.

We elucidate grapevine evolution and domestication histories with 3525 cultivated and wild accessions worldwide. In the Pleistocene, harsh climate drove the separation of wild grape ecotypes caused by continuous habitat fragmentation. Then, domestication occurred concurrently about 11,000 years ago in Western Asia and the Caucasus to yield table and wine grapevines. The Western Asia domesticates dispersed into Europe with early farmers, introgressed with ancient wild western ecotypes, and subsequently diversified along human migration trails into muscat and unique western wine grape ancestries by the late Neolithic. Analyses of domestication traits also reveal new insights into selection for berry palatability, hermaphroditism, muscat flavor, and berry skin color. These data demonstrate the role of the grapevines in the early inception of agriculture across Eurasia.

With fast learning speed and high accuracy, extreme learning machine (ELM) has achieved great success in pattern recognition and machine learning. Unfortunately, it will fail in the circumstance where plenty of labeled samples for training model are insufficient. The labeled samples are difficult to obtain due to their high cost. In this paper, we solve this problem with transfer learning and propose joint transfer extreme learning machine (JTELM). First, it applies cross-domain mean approximation (CDMA) to minimize the discrepancy between domains, thus obtaining one ELM model. Second, subspace alignment (sa) and weight approximation are together introduced into the output layer to enhance the capability of knowledge transfer and learn another ELM model. Third, the prediction of test samples is dominated by the two learned ELM models. Finally, a series of experiments are carried out to investigate the performance of JTELM, and the results show that it achieves efficiently the task of transfer learning and performs better than the traditional ELM and other transfer or nontransfer learning methods.

Objective This study aimed to explore the effects of tea polyphenols (TP) on inflammation of orbital fibroblasts in Graves’ ophthalmopathy (GO) and to provide new ideas for GO treatment. Methods Primary orbital fibroblasts were extracted from orbital adipose/connective tissues of patients with and without GO. Real-time quantitative PCR (RT-qPCR) was used to detect the expression of interleukin (IL)-6, IL-1β, and monocyte chemotactic protein (MCP)-1 in non-GO and GO orbital fibroblasts. The CCK-8 assay was used to determine the appropriate concentration of TP for subsequent experiments. RT-qPCR and enzyme-linked immunosorbent assay (ELISA) were performed to investigate the effects of TP on lipopolysaccharide (LPS)-induced production of inflammatory cytokines. Nuclear factor-κB (NF-κB) expression was measured using Western blotting analysis. NOD-like receptor 3 (NLRP3) expression was detected using both Western blotting analysis and immunofluorescence staining. Results The mRNA levels of IL-6, IL-1β, and MCP-1 in GO orbital fibroblasts were significantly higher than those in non-GO cells. TP treatment significantly inhibited LPS-induced production of inflammatory factors, including IL-6, IL-1β, and MCP-1. TP also inhibited the expression levels of NF-κB and NLRP3. Inflammation in the GO orbital fibroblasts was higher than that in non-GO cells. TP inhibited the production of inflammatory cytokines in GO orbital fibroblasts in vitro through the NF-κB/NLRP3 pathway. Conclusion These findings suggest that TP may have a potential role in GO treatment.

Oviductus ranae (OR) is an animal-based traditional Chinese medicine. In this work, its underlying mechanism of action in mice model of perimenopausal depression (PMD) was investigated. Network pharmacology and molecule docking analysis were conducted to identify potential targets and chemical components of OR in PMD. Subsequently, 60 female mice were ovariectomized and subjected to chronic unpredictable mild stress to establish the PMD model. After 14 days of OR administration on PMD mice, the depression-like behavioral were evaluated using sucrose preference, forced swimming, tail suspension, open field and morris water maze tests. Hippocampal tissues were collected to observe pathological changes via haematoxylin-eosin (H&E) staining, and immunohistochemical analysis was performed to detect the expression of the protein kinase B (AKT), phosphoinositol 3 kinase (PI3K), and oestrogen receptor β (ERβ). Western blot (WB) analysis was Conducted to detect the expression of PI3K/AKT signalling pathway. In the results, 18 potential targets and two chemical components of OR in PMD were identified. KEGG suggested that the PI3K/AKT signaling pathway was frequently involved in treatment of PMD with OR. Molecular docking showed that β-sitosterol in OR had the best docking effect with the target. OR treatment improved depression-like behaviour of PMD mice, significantly improved pPI3K/PI3K, pAKT/AKT, and pCREB/CREB ratios and brain derived neurotrophic factor. These findings suggested that OR may alleviate PMD and increase brain-derived neurotrophic factor levels, and has a certain therapeutic effect on PMD by up-regulating the expression of ERβ and activating the PI3K/AKT pathway. Overall, our study highlights OR as a promising therapeutic candidate for PMD.