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Castings' surface-defect detection is a crucial machine vision-based automation technology. This paper proposes a fusion-enhanced attention mechanism and efficient self-architecture lightweight YOLO (SLGA-YOLO) to overcome the existing target detection algorithms' poor computational efficiency and low defect-detection accuracy. We used the SlimNeck module to improve the neck module and reduce redundant information interference. The integration of simplified attention module (SimAM) and Large Separable Kernel Attention (LSKA) fusion strengthens the attention mechanism, improving the detection performance, while significantly reducing computational complexity and memory usage. To enhance the generalization ability of the model's feature extraction, we replaced part of the basic convolutional blocks with the self-designed GhostConvML (GCML) module, based on the addition of p2 detection. We also constructed the Alpha-EIoU loss function to accelerate model convergence. The experimental results demonstrate that the enhanced algorithm increases the average detection accuracy (mAP@0.5) by 3% and the average detection accuracy (mAP@0.5:0.95) by 1.6% in the castings' surface defects dataset. [ABSTRACT FROM AUTHOR]

This study aims to explore strategies for overcoming relational inertia and enhancing their creativity after inter‐firm mobility of inventors. The research sample comprises 591 mobile inventors identified using a patent data‐based model from Chinese communication technology companies. Employing the framework of dynamic network analysis, this study examines the impact of network closure at different time on overcoming relational inertia and investigates the influence of knowledge structure. The findings suggest that a lower level of past and current network closure is more conducive to knowledge sharing and technological innovation after inter‐firm mobility of inventors. Furthermore, mobile inventors with broad and in‐depth knowledge structures demonstrate significantly improved knowledge sharing and technological innovation, effectively mitigating relational inertia. These conclusions offer a systematic research perspective and comprehensive theoretical guidance, emphasizing the importance of optimizing network resources and knowledge structures to help inventors overcome relational inertia after inter‐firm mobility. [ABSTRACT FROM AUTHOR]

Background: Patients with extensive‐stage small cell lung cancer (ES‐SCLC) have an exceptionally poor prognosis and immune checkpoint inhibitors (ICIs) combined with etoposide‐platinum is recommended as standard first‐line therapy. However, which combination pattern is the best still remains unknown. This network meta‐analysis was performed to compare the efficacy and safety of currently available patterns including an antiangiogenic agent containing regimen and probed into the most appropriate therapy for patients. Methods: Hazard ratios (HRs) and odds ratios (ORs) were generated using R software. The outcomes of overall survival (OS), progression‐free survival (PFS), objective response rate (ORR), and adverse events of grade 3 or higher (grade ≥ 3 adverse events [AEs]) were analyzed. Results: A total of 10 randomized controlled trials (RCTs) involving 5544 patients were included for analysis. Drug combination patterns included adebrelimab, atezolizumab, durvalumab, durvalumab plus tremelimumab, ipilimumab, pembrolizumab, serplulimab, benmelstobart plus anlotinib, tislelizumab, tiragolumab plus atezolizumab and toripalimab in combination with chemotherapy. The novel antiangiogenic agent containing regimen benmelstobart + anlotinib + chemotherapy showed the highest possibility to present the best PFS and OS versus chemotherapy. Compared with ICI plus chemotherapy, it also achieved significantly better PFS and presented a tendency of OS benefit. As for safety and toxicity, patients treated with benmelstobart + anlotinib + chemotherapy and durvalumab + tremelimumab + chemotherapy suffered a higher likelihood of more grade ≥ 3 AEs without unexpected AEs. Conclusion: PD‐1/PD‐L1 inhibitors‐based combinations are associated with significant improvement in both PFS and OS for treatment‐naïve ES‐SCLC patients. Benmelstobart plus anlotinib with chemotherapy (CT) yielded better survival benefit versus CT alone or other ICIs + CT with caution for more adverse effects along with the addition of an antiangiogenic agent. [ABSTRACT FROM AUTHOR]

It is difficult to plug the fracture water channeling of a fractured low-permeability reservoir during water flooding by using the conventional acrylamide polymer gel due to its weak mechanical properties. For this problem, micron graphite powder is added to enhance the comprehensive properties of the acrylamide polymer gel, which can improve the plugging effect of fracture water channeling. The chemical principle of this process is that the hydroxyl and carboxyl groups of the layered micron graphite powder can undergo physicochemical interactions with the amide groups of the polyacrylamide molecule chain. As a rigid structure, the graphite powder can support the flexible skeleton of the original polyacrylamide molecule chain. Through the synergy of the rigid and flexible structures, the viscoelasticity, thermal stability, tensile performance, and plugging ability of the new-type gel can be significantly enhanced. Compared with a single acrylamide gel, after adding 3000 mg/L of micrometer-sized graphite powder, the elastic modulus, the viscous modulus, the phase transition temperature, the breakthrough pressure gradient, the elongation at break, and the tensile stress of the acrylamide gel are all greatly improved. After adding the graphite powder to the polyacrylamide gel, the fracture water channeling can be effectively plugged. The characteristics of the networked water flow channel are obvious during the injected water break through the gel in the fracture. The breakthrough pressure of water flooding is high. The experimental results are an attempt to develop a new gel material for the water plugging of a fractured low-permeability reservoir. [ABSTRACT FROM AUTHOR]

Based on the design and measured data of one actual tower, a three-dimensional numerical model for a natural draft dry cooling tower (NDDCT) was created and validated under constant heat load. This enabled the performance improvement mechanism of air equalizing on vertical delta-type radiators (VDRs) to be clarified by detailed analysis of key parameters, such as the exit water temperature, heat transfer coefficient, and mass airflow. Under the impact of typical ambient crosswind, all VDRs were retrofitted with air-side-equalizing devices. It was found that the exit water temperatures of the whole NDDCT decreased by 0.865 °C, 0.593 °C and 0.186 °C under the studied ambient crosswind speeds of 2.5 m/s, 4 m/s and 12 m/s, respectively. The performance improvement mechanism of air-side equalizing was investigated for three VDRs, which were located on the upwind, tower lateral, and downwind sides under crosswind impacts. Besides the studied VDRs, the performance of the neighboring VDRs behind them was also improved by the optimized aerodynamic field and the reduced hot wind recirculation around them. In addition, the average heat transfer coefficients of the VDRs were enhanced, which could lay the foundation for improving the cooling performance of thermodynamic devices with VDRs. [ABSTRACT FROM AUTHOR]

Although nano SiO2 exhibits excellent application potential in the field of oil and gas exploration and development, such as drilling fluid, enhanced oil/gas recovery, etc., it is prone to agglomeration and loses its effectiveness due to the action of cations in saline environments of oil and gas reservoirs. Therefore, it is crucial to study the mechanism of the change in energy between nano SiO2 and cations for its industrial application. In this paper, the effect of cations (Na+, K+, Ca2+, and Mg2+) on the surface energy of nano SiO2 particles is investigated from the perspective of molecular motion and electronic change by density functional theory. The results are as follows: Due to the electrostatic interactions, cations can migrate towards the surface of nano SiO2 particles. During the migration process, monovalent cations are almost unaffected by water molecules, and they can be directly adsorbed on the surface by nano SiO2 particles. However, when divalent cations migrate from a distance to the surface of nano SiO2 particles, they can combine with water molecules to create an energy barrier, which can prevent them from moving forward. When divalent cations break through the energy barrier, the electronic kinetic energy between them and nano SiO2 particles changes more strongly, and the electrons carried by them are more likely to break through the edge of the atomic nucleus and undergo charge exchange with nano SiO2 particles. The change in interaction energy is more intense, which can further disrupt the configuration stability of nano SiO2. The interaction energy between cations and nano SiO2 particles mainly comes from electrostatic energy, followed by Van der Waals energy. From the degree of influence of four cations on nano SiO2 particles, the order from small to large is as follows: K+ < Na+ < Mg2+ < Ca2+. The research results can provide a theoretical understanding of the interaction between nano SiO2 particles and cations during the application of nano SiO2 in the field of oil and gas exploration and development. [ABSTRACT FROM AUTHOR]

The TRIZ theory was used to accurately discover the problems to be solved in the design of roadway surrounding rock control technology. This paper tried to solve the complex issue of surrounding rock control in deep roadways from a new perspective. Based on the functional component analysis and causal axis analysis of the problem's primary reason, simultaneously, the surrounding rock control technology was optimized through technical contradiction analysis, physical contradiction analysis, and substance and field model analysis. As a result, a fully enclosed wire-shell support technology was proposed. Finally, taking the typical soft rock roadway engineering of Pansan Coal Mine in Huainan Mining Area, Anhui Province, China, as the engineering background, the engineering application and effect evaluation were completed. This paper provides a reference for controlling the instability of deep soft rock roadways in coal mines. A new idea of optimizing roadway support engineering based on TRIZ theory was proposed. [ABSTRACT FROM AUTHOR]

According to their resource ownership and resource acquisition channels, this paper constructs an evolutionary game model of enterprises' technological innovation investment channels considering managers' expectations. This results in the strategy of non-alliance firms along the first channel having a significant impact on the evolutionary equilibrium. For non-alliance enterprises, the difference in the amount of investment in the R&D stage has the same impact on the probability of such enterprises following the first channel. The number of active managers, group capacity, the difference in managers' expectations, and the difference in the amount of technological innovation investment in the R&D stage have significant differences in the possibility of choosing the first channel between the two types of enterprises. The research conclusions can provide valuable references for enterprises to make technological innovation decisions. [ABSTRACT FROM AUTHOR]

Technical pre-development has become increasingly crucial for enterprises in making core technological breakthroughs. Using a cross-level analysis framework of ego and whole networks, this study comprehensively considers the network content and structure. Specifically, it introduces the dynamic characteristics of organisational network research over time to study the impact of current knowledge breadth, structural holes, degree centrality, assortativity, and transitivity on the creativity of key inventors in the pre-development stage. The study uses the 4G and 5G patent data of 10 representative telecommunication enterprises as the sample data. The results demonstrate that there is an inverted U-shaped association between the current knowledge breadth and the creativity of key inventors. At the ego-network level, although there is also an inverted U-shaped relationship between the current degree centrality and the creativity of key inventors in theory, within the value range of the sample data, this relationship indicates a monotonically increasing trend. At the whole-network level, assortativity and transitivity have U-shaped and inverted U-shaped significant effects on the creativity of key inventors, respectively. Our study offers a new perspective for the management of the creativity of key inventors in the pre-development stage. [ABSTRACT FROM AUTHOR]

In printing, microreactors, and bioassays, the precise control of micrometer-scale droplet generation is essential but challenging, often restricted by the equipment and nozzles used in traditional methods. We introduce a needle-plate electrode corona discharge technique that injects charges into an oil layer, enabling the precise manipulation of droplet polarization and splitting. This method allows for meticulous adjustment of microdroplet formation regarding location, size, and quantity by modulating the discharge voltage, discharge time, and electrode positioning. It enables the immediate initiation and cessation of droplet production, thereby facilitating on-demand droplet generation. Our study on the voltage-dependent droplet stretch coefficient shows that as the voltage increases, the droplets transition from controlled splitting to regular Taylor cone-like ejections, eventually reaching the Rayleigh limit and fully breaking apart. These advancements significantly improve microfluidic droplet manipulation, offering considerable benefits for applications in targeted drug delivery, rapid disease diagnostics, and precise environmental monitoring.

Background: Moyamoya disease (MMD) is a rare and complex cerebrovascular disorder characterized by the progressive narrowing of the internal carotid arteries and the formation of compensatory collateral vessels. The etiology of MMD remains enigmatic, making diagnosis and management challenging. The MOYAOMICS project was initiated to investigate the molecular underpinnings of MMD and explore potential diagnostic and therapeutic strategies., Methods: The MOYAOMICS project employs a multidisciplinary approach, integrating various omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, to comprehensively examine the molecular signatures associated with MMD pathogenesis. Additionally, we will investigate the potential influence of gut microbiota and brain-gut peptides on MMD development, assessing their suitability as targets for therapeutic strategies and dietary interventions. Radiomics, a specialized field in medical imaging, is utilized to analyze neuroimaging data for early detection and characterization of MMD-related brain changes. Deep learning algorithms are employed to differentiate MMD from other conditions, automating the diagnostic process. We also employ single-cellomics and mass cytometry to precisely study cellular heterogeneity in peripheral blood samples from MMD patients., Conclusions: The MOYAOMICS project represents a significant step toward comprehending MMD's molecular underpinnings. This multidisciplinary approach has the potential to revolutionize early diagnosis, patient stratification, and the development of targeted therapies for MMD. The identification of blood-based biomarkers and the integration of multiple omics data are critical for improving the clinical management of MMD and enhancing patient outcomes for this complex disease., (© 2024. The Author(s).)

In order to meet the efficiency and smooth trajectory requirements of the casting sorting robotic arm, we propose a time-optimal trajectory planning method that combines a heuristic algorithm inspired by the behavior of the Genghis Khan shark (GKS) and segmented interpolation polynomials. First, the basic model of the robotic arm was constructed based on the arm parameters, and the workspace is analyzed. A matrix was formed by combining cubic and quintic polynomials using a segmented approach to solve for 14 unknown parameters and plan the trajectory. To enhance the smoothness and efficiency of the trajectory in the joint space, a dynamic nonlinear learning factor was introduced based on the traditional Particle Swarm Optimization (PSO) algorithm. Four different biological behaviors, inspired by GKS, were simulated. Within the premise of time optimality, a target function was set to effectively optimize within the feasible space. Simulation and verification were performed after determining the working tasks of the casting sorting robotic arm. The results demonstrated that the optimized robotic arm achieved a smooth and continuous trajectory velocity, while also optimizing the overall runtime within the given constraints. A comparison was made between the traditional PSO algorithm and an improved PSO algorithm, revealing that the improved algorithm exhibited better convergence. Moreover, the planning approach based on GKS behavior showed a decreased likelihood of getting trapped in local optima, thereby confirming the effectiveness of the proposed algorithm.