Photoelectric Properties of DSSCs Sensitized by Phloxine B and Bromophenol Blue

Phloxine B and bromophenol blue as the sensitizers of dye-sensitized solar cells were investigated via UV-Vis spectra, FT-IR spectra, fluorescence spectra, and current-voltage characteristics. The frontier molecular orbital, vibration analysis, and the first hyperpolarizability were calculated with DFT/6-31G(d). The dipole moment, light harvesting efficiency (LHE), and larger absolute value of driving force of electron injection (ΔGinject) were also discussed. The calculated results were compared with the experimental results of phloxine B and bromophenol blue. It was found that, compared with bromophenol blue, bigger dipole moment of phloxine B results in larger open circuit voltage (Voc) according to the correlation between dipole moment and Voc. At the same time, for configuration of phloxine B, it has higher LHE and ΔGinject, which are helpful to enhance the abilities of absorbing sunlight and electron injection. Therefore, higher LHE and ΔGinject for phloxine B produced a larger value of Jsc

FIELD TEST ON THE COOPERATION OF NSM STRENGTHENING AND EXTERNAL TENDON RETROFITTING TECHNIQUE

In this paper, post-tension and steel plate near-surface mounted (NSM) strengthening systems are proposed to strengthen deteriorated and cracked large box girder rigid frame bridge without altering appearance and dimension of the bridge. The reinforcement method mainly improves the bearing capacity through external prestressed tendons, and bonding steel plate can enhance the shear resistance of the bridge. The main purpose is to study the structural mechanical properties before and after the reinforcement of rigid frame bridges. Take a 540m rigid frame box girder bridge as an example. The static load test of the bridge before and after reinforcement is carried out. The deflection and strain of the middle cross section of the span are measured in the static test. A finite element analysis model was also developed and verified static loading test data. The results show that structural bearing capacity and performance of the bridge were enhanced with the post-tension and NSM strengthening systems cooperatively

Treatment of vulval condyloma with a combination of paiteling and cryotherapy, and its effect on late recurrence

Purpose: To study the clinical effectiveness of a combination of Paiteling and cryotherapy in the treatment of vulval condyloma acuminatum (VCA), and its effect on late recurrence. Methods: Eighty-six VCA patients were chosen as research subjects, and were randomized into group A and group B. Group A patients were treated with combination of Paiteling and cryotherapy, while group B patients received cryotherapy only. The clinical effects of the two treatment methods on VCA were evaluated by measuring area of damaged skin, levels of interleukin-6 (IL-6) and C-reactive protein (CRP), as well as degree of recurrence of VCA in the two groups, before and after treatment. Results: Total clinical treatment effectiveness in group A was significantly higher compared with group B (p < 0.05). After treatment, the area of damaged skin, and levels of IL-6 and CRP were markedly lower in group A than in group B (p < 0.001). After 6 months of treatment, disease control was higher in group A than in group B (p < 0.05). There was also a lower incidence of adverse reactions in group A than in group B (p < 0.05). Conclusion: These results indicate that the combination of Paiteling and cryotherapy is more effective than cryotherapy alone in improving treatment effectiveness and reducing late recurrence of VCA. Therefore, the combined treatment has potentials clinical application in the management of VCA

Uni-QSAR: an Auto-ML Tool for Molecular Property Prediction

Recently deep learning based quantitative structure-activity relationship (QSAR) models has shown surpassing performance than traditional methods for property prediction tasks in drug discovery. However, most DL based QSAR models are restricted to limited labeled data to achieve better performance, and also are sensitive to model scale and hyper-parameters. In this paper, we propose Uni-QSAR, a powerful Auto-ML tool for molecule property prediction tasks. Uni-QSAR combines molecular representation learning (MRL) of 1D sequential tokens, 2D topology graphs, and 3D conformers with pretraining models to leverage rich representation from large-scale unlabeled data. Without any manual fine-tuning or model selection, Uni-QSAR outperforms SOTA in 21/22 tasks of the Therapeutic Data Commons (TDC) benchmark under designed parallel workflow, with an average performance improvement of 6.09\%. Furthermore, we demonstrate the practical usefulness of Uni-QSAR in drug discovery domains

Seismic performance of horizontal swivel system of asymmetric continuous girder bridge

The bridge horizontal swivel system generally adopts a symmetrical structure and uses a spherical hinge structure that can adjust the rotation to complete rotation construction. Because of the complexity of railway lines under bridges, some asymmetrical horizontal swivel systems have been increasingly applied in practical engineering in recent years. This system is more suitable for areas with complex railway lines, reduces the bridge span, and provides better economic benefits. However, it is also extremely unstable. In addition, instability can easily occur under dynamic loads, such as earthquake action and pulsating wind effects. Therefore, it is necessary to study their mechanical behavior. Based on the horizontal swivel system of an 11,000-ton asymmetric continuous girder bridge, the dynamic response of the horizontal swivel system to seismic action was studied using the finite element simulation analysis method. Furthermore, using the Peer database, seismic waves that meet the calculation requirements are screened for time-history analysis and compared to the response spectrum method. The mechanical properties of the structural system during and after rotation were obtained through calculations. During rotation, the seismic response of the structure is greater. To reduce the calculation time cost, an optimization algorithm based on the mode shape superposition method is proposed. The calculation result is 87% that of the time-history analysis, indicating a relatively high calculation accuracy

Robust cross-linked Na3V2(PO4)2F3 full sodium-ion batteries

Sodium-ion batteries (SIBs) have rapidly risen to the forefront of energy storage systems as a promising supplementary for Lithium-ion batteries (LIBs). Na3V2(PO4)2F3 (NVPF) as a common cathode of SIBs, features the merits of high operating voltage, small volume change and favorable specific energy density. However, it suffers from poor cycling stability and rate performance induced by its low intrinsic conductivity. Herein, we propose an ingenious strategy targeting superior SIBs through cross-linked NVPF with multi-dimensional nanocarbon frameworks composed of amorphous carbon and carbon nanotubes (NVPF@C@CNTs). This rational design ensures favorable particle size for shortened sodium ion transmission pathway as well as improved electronic transfer network, thus leading to enhanced charge transfer kinetics and superior cycling stability. Benefited from this unique structure, significantly improved electrochemical properties are obtained, including high specific capacity (126.9 mAh g−1 at 1 C, 1 C = 128 mA g−1) and remarkably improved long-term cycling stability with 93.9% capacity retention after 1000 cycles at 20 C. The energy density of 286.8 Wh kg−1 can be reached for full cells with hard carbon as anode (NVPF@C@CNTs//HC). Additionally, the electrochemical performance of the full cell at high temperature is also investigated (95.3 mAh g−1 after 100 cycles at 1 C at 50 oC). Such nanoscale dual-carbon networks engineering and thorough discussion of ion diffusion kinetics might make contributions to accelerating the process of phosphate cathodes in SIBs for large-scale energy storages

Approach towards Sustainable and Smart Coal Port Development: The Case of Huanghua Port in China

This paper focuses on measures towards sustainable development of coal ports based on the economic, environmental, and social dimensions of the triple bottom line, and examines the integration and optimization roles of smart technologies on coal port sustainability in the era of the Internet of Things. By investigating the representative case of Huanghua Port, one of the largest coal transportation ports in China, this paper enables a better understanding of the coal port’s sustainable practices driven by smart technologies. This study provides measures on the intelligent renovation, coal dust pollution treatment, air pollution treatment and sewage treatment, the customer and employee satisfaction improvement, and community involvement as well as social reputation enhancement. The research investigates the effectiveness of measures on the coal port’s sustainability by examining changes in key performance indicators and further examines the integration and optimization roles of smart technologies. The findings show that the approach taken by the port can effectively promote the coal port’s sustainability. The intelligent operation control system linking the separate nodes in operation, the ecological intelligent control system integrating environmental protection functions, and the intelligent service platform linking supply chain members are interrelated and interact to achieve the continuous optimization of decisions towards coal port sustainability. This study offers managerial insights for the port operators and policymakers towards the sustainable and smart development of ports

Detection of Insider Selective Forwarding Attack Based on Monitor Node and Trust Mechanism in WSN

The security problems of wireless sensor networks (WSN) have attracted people’s wide attention. In this paper, after we have summarized the existing security problems and solutions in WSN, we find that the insider attack to WSN is hard to solve. Insider attack is different from outsider attack, because it can’t be solved by the traditional encryption and message authentication. Therefore, a reliable secure routing protocol should be proposed in order to defense the insider attack. In this paper, we focus on insider selective forwarding attack. The existing detection mechanisms, such as watchdog, multipath retreat, neighbor-based monitoring and so on, have both advantages and disadvantages. According to their characteristics, we proposed a secure routing protocol based on monitor node and trust mechanism. The reputation value is made up with packet forwarding rate and node’s residual energy. So this detection and routing mechanism is universal because it can take account of both the safety and lifetime of network. Finally, we use OPNET simulation to verify the performance of our algorithm

Inverse Design of Energy‐Absorbing Metamaterials by Topology Optimization

Abstract Compared with the forward design method through the control of geometric parameters and material types, the inverse design method based on the target stress‐strain curve is helpful for the discovery of new structures. This study proposes an optimization strategy for mechanical metamaterials based on a genetic algorithm and establishes a topology optimization method for energy‐absorbing structures with the desired stress‐strain curves. A series of structural mutation algorithms and design‐domain‐independent mesh generation method are developed to improve the efficiency of finite element analysis and optimization iteration. The algorithm realizes the design of ideal energy‐absorbing structures, which are verified by additive manufacturing and experimental characterization. The error between the stress‐strain curve of the designed structure and the target curve is less than 5%, and the densification strain reaches 0.6. Furthermore, special attention is paid to passive pedestrian protection and occupant protection, and a reasonable solution is given through the design of a multiplatform energy‐absorbing structure. The proposed topology optimization framework provides a new solution path for the elastic‐plastic large deformation problem that is unable to be resolved by using classical gradient algorithms or genetic algorithms, and simplifies the design process of energy‐absorbing mechanical metamaterials