Abstract
The existing multi-person collaborative design scheme of Building Information Modeling (BIM) integrated with blockchain faces problems such as poor reliability of BIM drawing, inconsistent ...drawing information, redundant information, and inaccurate protection of copyright interests. This paper proposes a multi-person collaborative design model for BIM drawing that combines blockchain and InterPlanetary File System (IPFS). This model uses blockchain to store drawing design information to protect the copyright interests of designers and combines IPFS to ensure the reliability of drawing. A cycle division mechanism is designed to solve the problem of drawing information synchronization when multiple people collaborate in design. The Semantic Differential Transaction (SDT) method is used to achieve incremental update of drawing and reduce the information redundancy of the blockchain. Finally, a comparative analysis and validation evaluation of the scheme is carried out, and the usability of the scheme is illustrated with an illustrative example. The results show that: (1) proposed scheme is feasible for multi-person collaborative design; (2) proposed scheme can effectively ensure the reliability of drawing and reduce the redundancy of blockchain information, so as to achieve copyright protection for designers.
P
ropane dehydrogenation(PDH) has become a globe-welcoming technology to meet the massive demand for propylene, but the most commonly used Pt-based catalysts suffer from quick sintering, poor ...selectivity for propylene, and unsatisfied Pt utilization. Herein, a series of Silicalite-1(S-1) zeolite-encaged ultrasmall Pt-Zn clusters with a trace amount of Pt40–180 ppm(parts per million) were developed by using a one-pot ligand-protected direct H
2
reduction method. Interestingly, the extremely low amount of Pt can significantly promote the activity of zeolite-encaged Zn catalysts in PDH reactions. Thanks to the high Pt dispersion, the synergy between Pt and Zn species, and the confinement effect of zeolites, the optimized PtZn@S-1 catalyst with 180 ppm Pt and 1.88%(mass fraction) Zn, exhibited an extraordinarily high propane conversion(33.9%) and propylene selectivity(99.5%) at 550 °C with a weight hourly space velocity (WHSV) of 8 h
−1
, affording an extremely high propylene formation rate of
340.7
mol
C
3
H
6
⋅
g
Pt
−
1
⋅
h
−
1
. This work provides a reference for the preparation of zeolite-encaged metal catalysts with high activity and noble metal utilization in PDH reactions.
Community governance is the basic unit of social governance, and it is also an important direction for building a social governance pattern of co-construction, co-governance and sharing. Previous ...studies have solved the problems of data security, information traceability and participant enthusiasm in the process of community digital governance by building a community governance system based on blockchain technology and incentive mechanisms. The application of blockchain technology can solve the problems of low data security, difficulty in sharing and tracing and low enthusiasm on the part of multiple subjects regarding participation in community governance. The process of community governance involves the cooperation of multiple government departments and multiple social subjects. Under the blockchain architecture, the number of alliance chain nodes will reach 1000 with the expansion of community governance. The existing consensus algorithms for coalition chains are difficult to meet the high concurrent processing requirements under such large-scale nodes. An optimization algorithm has improved the consensus performance to a certain extent, but the existing systems still cannot meet the data needs of the community and are not suitable for community governance scenarios. Since the community governance process only involves the participation of relevant departments in users, all nodes in the network are not required to participate in the consensus under the blockchain architecture. Therefore, a practical Byzantine fault tolerance (PBFT) optimization algorithm based on community contribution (CSPBFT) is proposed here. First, consensus nodes are set according to different roles of participants in community activities, and participants are given different consensus permissions. Second, the consensus process is divided into different stages, and the amount of data processed by each consensus step is reduced. Finally, a two-level consensus network is designed to perform different consensus tasks, and reduce unnecessary communication between nodes to reduce the communication complexity of consensus among nodes. Compared with the PBFT algorithm, CSPBFT reduces the communication complexity from O(N2) to O(N2/C3). Finally, the simulation results show that, through rights management, network level setting and consensus phase division, when the number of nodes in the CSPBFT network is 100-400, the consensus throughput can reach 2000 TPS. When the node in the network is 1000, the instantaneous concurrency is guaranteed to be above 1000 TPS, which can meet the concurrent needs of the community governance scenario.
Background Extremely preterm infants (EPIs) frequently encounter challenges in feeding due to their underdeveloped digestive systems. Attaining full enteral feeding at the earliest possible stage can ...facilitate the removal of vascular catheters and decrease catheter-related complications. Methods We performed a retrospective cohort study comprising 145 extremely preterm infants with a gestational age < 28 weeks who underwent non-invasive mechanical ventilation at Shenzhen Maternity & Child Healthcare Hospital between January 2019 and June 2020. The KMC group received standard nursing care along with KMC, while the control group received standard nursing care without KMC. KMC initiation took place three weeks after admission and continued for a period of two weeks or more while maintaining stable vital signs. We evaluated the rate of exclusive breastmilk feeding within 24 h prior to discharge and the time to full enteral feeding throughout hospitalization. Additionally, we conducted a multiple linear regression analysis to identify the independent factors associated with exclusive breastmilk feeding rates and the time to full enteral feeding. Results The KMC group exhibited a significantly higher rate of exclusive breastmilk feeding in the 24 h before discharge in comparison to the Non-KMC group (52.8% vs. 31.5%, OR 2.43; 95% CI 1.24, 4.78). Moreover, the KMC group achieved full enteral feeding in a shorter duration than the Non-KMC group (43.1 + or - 9.6 days vs. 48.7 + or - 6.9 days, p < 0.001). Multiple linear regression analysis revealed that KMC was an independent protective factor associated with improved exclusive breastmilk feeding rates (OR 2.43; 95% CI 1.24, 4.78) and a reduction in the time to full enteral feeding (beta -5.35, p < 0.001) in extremely preterm infants. Conclusion Kangaroo Mother Care (KMC) can expedite the achievement of full enteral feeding and enhance exclusive breastmilk feeding rates in extremely preterm infants receiving non-invasive assisted ventilation. These findings highlight the beneficial effects of KMC on the feeding outcomes of this vulnerable population, underscoring the importance of implementing KMC as a part of comprehensive care for extremely preterm infants. Keywords: Extremely preterm infants, Full enteral feeding, Breastmilk feeding, Kangaroo mother care
Sharding technology can address the throughput and scalability limitations that arise when single-chain blockchain are applied in the Internet of Things (IoT). However, existing sharding solutions ...focus on addressing issues like malicious nodes clustering and cross-shard transactions. Existing sharding solutions cannot adapt to the performance disparities of edge nodes and the characteristic of three-dimensional data queries in building IoT. This leads to problems such as shard overheating and inefficient data query efficiency. This paper proposes a dual-layer architecture called S-DAG, which combines sharded blockchain and DAG blockchain. The sharded blockchain processes transactions within the building IoT, while the DAG blockchain stores block headers from the sharded network. By designing an Adaptive Balancing Load Algorithm (ABLA) for periodic network sharding, nodes are divided based on their load performance values to prevent the aggregation of low-load performance nodes and the resulting issue of shard overheating. By combining the characteristics of the KD tree and Merkle tree, a block structure known as 3D-Merkle tree is designed to support three-dimensional data queries, enhancing the efficiency of three-dimensional data queries in building IoT. By deploying and conducting simulation experiments on various physical devices, we have verified the effectiveness of the solution proposed in this paper. The results indicate that, compared to other solutions, the proposed solution is better suited for building IoT data management. ABLA is effective in preventing shard overheating issue, and the 3D-Merkle tree significantly enhances data query efficiency.
Neonatal infectious diseases are a serious threat to the health of newborns. The aim was to establish a new detection method for the simultaneous measurement of (1,3)‐β‐d‐glucan and procalcitonin in ...serum for the early screening and efficacy testing of neonatal infectious diseases. We established a sandwich dual‐label time‐resolved fluorescence immunoassay (TRFIA): anti‐(1,3)‐β‐d‐glucan/procalcitonin antibodies immobilized on 96‐well plates captured (1,3)‐β‐d‐glucan/procalcitonin antigens and then banded together with the detection antibodies labeled with europium(III) (Eu3+)/samarium(III) (Sm3+) chelates. Finally, time‐resolved fluorometry was used to measure the fluorescence intensity. The linear correlation coefficient (R2) of the (1,3)‐β‐d‐glucan standard curve was 0.9913, and the R2 of the procalcitonin standard curve was 0.9911. The detection sensitivity for (1,3)‐β‐d‐glucan was 0.4 pg/mL (dynamic range: 0.6–90 pg/mL), and the average recovery was 101.55%. The detection sensitivity for procalcitonin was 0.02 ng/mL (dynamic range: 0.05–95 ng/mL), and the average recovery was 104.61%. There was a high R2 between the present TRFIA method and a commercially available assay (R2 = 0.9829 for (1,3)‐β‐d‐glucan and R2 = 0.9704 for procalcitonin). Additionally, the cutoff values for (1,3)‐β‐d‐glucan and procalcitonin were 23.95 pg/mL and 0.055 ng/mL, respectively. The present TRFIA method has high sensitivity, accuracy, and specificity and is an effective method for early screening and efficient testing of neonatal invasive fungal infection.
Once the newborn has the related clinical symptoms of fever and other infections, this TRFIA method could be employed to detect the (1,3)‐β‐d‐glucan and procalcitonin levels in serum, which would be used for early screening and diagnosis of invasive fungal infections
As a critical component of rotating machinery, rolling bearings are essential for the safe and efficient operation of machinery. Sudden faults of rolling bearings can lead to unscheduled downtime and ...substantial economic costs. Therefore, diagnosing and identifying the equipment status is essential for ensuring the operation and decreasing the additional maintenance costs of the machines. However, extracting the features from the early bearing fault signals is challenging under background noise interference. With the purpose of solving the above problem, we propose an integrated rolling bearing fault diagnosis model based on the improved grey wolf optimized variational modal decomposition (IGVMD) and an improved 1DCNN with a parametric rectified linear unit (PReLU). Firstly, an improved grey wolf optimizer (IGWO) with the fitness function, the minimum envelope entropy, is designed for adaptively searching the optimal parameter values of the VMD model. The performance of the basic grey wolf optimizer (GWO) algorithm by introducing three improvement strategies, the non-linear convergence factor adjustment strategy, the grey wolf adaptive position update strategy, and the Levy flight strategy in the IGWO algorithm, is improved. Then, an improved 1DCNN model with the PReLU activation function is proposed, which extracts the bearing fault features, and a grid search to optimize the model parameters of the 1DCNN is introduced. Finally, the effectiveness of the proposed model is demonstrated well by employing two experimental datasets. The preliminary comparative results of the average identification accuracy in the proposed method in two datasets are 99.98% and 99.50%, respectively, suggesting that this proposed method has a relatively higher recognition accuracy and application values.
Blockchain can ensure data security and reliability during the stage of building operation and maintenance (BOM), provide reliable data for decision-making. However, existing schemes based on ...single-chain architecture have the problems of storage limitation and scalability, and ignore the impact of event's priority and real-time on blockchain transaction. Therefore, for BOM, this paper provides a BOM framework based on sharding blockchain (SBC-BOMF), which constructs two-layer architecture based on master-chain and multiple shards, relieves the storage pressure of blockchain nodes and improves the concurrency capability. Priority-based transaction handling strategy is designed to achieve reasonable and rapid response for multi-level transactions. Finally, an actual BOM project is taken as example to illustrate the effectiveness of proposed scheme; experiments are conducted for performance testing and evaluation. Results show that proposed scheme can effectively solve the scalability problem caused by the application of blockchain in BOM, reduce storage overhead, and realize efficient handling for blockchain transactions.
Objective The present study aims to investigate the levels of illness uncertainty in patients with moyamoya disease and to determine the association of socio-demographic characteristics, perceived ...social support and resilience with illness uncertainty in patients with moyamoya disease. Method A cross-sectional survey using convenience sampling was conducted in two hospitals in China from August to December 2023. A socio-demographic characteristics questionnaire, the Chinese versions of Mishel’s Unsurety in Disease Scale (MUIS), the Chinese version of Connor-Davidson Resilience Scale (CD-RISC), and the Chinese version of Multidimensional Scale of Perceived Social Support (MSPSS) were used to perform this research. The collected data were analyzed using SPSS 24.0 statistical software. The t-test, one-way analysis of variance (ANOVA), pearson correlation analysis and hierarchical regression analysis were used to identify associated factors. Result A total of 263 patients with moyamoya disease were recruited in this survey. The score of illness uncertainty was at a moderate level of (100.03 ± 18.59). The present study identified a negative correlation between illness uncertainty with resilience perceived social support. Hierarchical regression analysis showed that gender, occupation, education level, resilience and perceived social support were the related factors of illness uncertainty. Conclusion Patients with moyamoya disease experienced moderate disease uncertainty on average, which was related to gender, occupation, education level, resilience and perceived social support. Future research is needed to better explore the complex relationships between illness uncertainty, resilience, and perceived social support with different types of moyamoya disease using longitudinal research.
