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Abstract Radiotherapy combined with immune checkpoint blockade holds great promise for synergistic antitumor efficacy. Targeted radionuclide therapy delivers radiation directly to tumor sites. LNC1004 is a fibroblast activation protein (FAP)-targeting radiopharmaceutical, conjugated with the albumin binder Evans Blue, which has demonstrated enhanced tumor uptake and retention in previous preclinical and clinical studies. Herein, we demonstrate that 68Ga/177Lu-labeled LNC1004 exhibits increased uptake and prolonged retention in MC38/NIH3T3-FAP and CT26/NIH3T3-FAP tumor xenografts. Radionuclide therapy with 177Lu-LNC1004 induced a transient upregulation of PD-L1 expression in tumor cells. The combination of 177Lu-LNC1004 and anti-PD-L1 immunotherapy led to complete eradication of all tumors in MC38/NIH3T3-FAP tumor-bearing mice, with mice showing 100% tumor rejection upon rechallenge. Immunohistochemistry, single-cell RNA sequencing (scRNA-seq), and TCR sequencing revealed that combination therapy reprogrammed the tumor microenvironment in mice to foster antitumor immunity by suppressing malignant progression and increasing cell-to-cell communication, CD8+ T-cell activation and expansion, M1 macrophage counts, antitumor activity of neutrophils, and T-cell receptor diversity. A preliminary clinical study demonstrated that 177Lu-LNC1004 was well-tolerated and effective in patients with refractory cancers. Further, scRNA-seq of peripheral blood mononuclear cells underscored the importance of addressing immune evasion through immune checkpoint blockade treatment. This was emphasized by the observed increase in antigen processing and presentation juxtaposed with T cell inactivation. In conclusion, our data supported the efficacy of immunotherapy combined with 177Lu-LNC1004 for cancer patients with FAP-positive tumors.

During long-duration dynamic loads, such as wind loads or seismic effects, the internal temperature and pressure of a damping cylinder escalate rapidly, which induce shifts in the mechanical attributes of viscous fluid dampers (VFDs). This study investigated the mechanical performance of VFD considering the coupling effects of temperature and pressure under long-duration loads. First, we analyzed the mechanical and energy-dissipation performances of the dampers based on the dynamic mechanical tests considering different loading frequencies, displacement amplitude, and loading cycles. The experimental results indicated that both temperature and pressure influenced the output of the dampers, and in the sealed environment of the damper pip, temperature and pressure exerted mutual influence. Furthermore, the relationship between the damping coefficient and temperature–pressure coupling effects was obtained. Subsequently, an improved mathematical model for the mechanical performance of a gap-type VFD was proposed by considering the macroscopic energy balance of the entire fluid within the damper. Finally, the accuracy of the mathematical model for VFD under long-duration dynamic loads was validated by comparing the computational results with the experimental data.

In this study, we investigated the effects of Cu doping on the performance of CoFeSiB amorphous microwires as the core of a fluxgate magnetometer. The noise performance of fluxgate sensors primarily depends on the crystal structure of constituent materials. CoFeSiB amorphous microwires with varying Cu doping ratios were prepared using melt-extraction technology. The microstructure of microwire configurations was observed using transmission electron microscopy, and the growth of nanocrystalline was examined. Additionally, the magnetic performance of the microwire and the noise of the magnetic fluxgate sensors were tested to establish the relationship between Cu-doped CoFeSiB amorphous wires and sensor noise performance. The results indicated that Cu doping triggers a positive mixing enthalpy and the reduced difference in the atomic radius that enhances the degree of nanocrystalline formation within the system; differential scanning calorimetry analysis indicates that this is due to Cu doping reducing the glass formation capacity of the system. In addition, Cu doping affects the soft magnetic properties of amorphous microwires, with 1% low-doping samples exhibiting better soft magnetic properties. This phenomenon is likely the result of the interaction between nanocrystalline organization and magnetic domains. Furthermore, a Cu doping ratio of 1% yields the best noise performance, aligning with the trend observed in the material’s magnetic properties. Therefore, to reduce the noise of the CoFeSiB amorphous wire sensor, the primary goal should be to reduce microscopic defects in amorphous alloys and enhance soft magnetic properties. Cu doping is a superior preparation method which facilitates control over preparation conditions, ensuring the formation of stable amorphous wires with consistent performance.

Replication stress is associated with cancer formation and progression. Here the authors reveal that the macrophage migration inhibitory factor (MIF) functions as 3’ flap nuclease involved in resolving replication stress affecting overall tumor progression.

This article presents a Lyapunov precise integral-based analysis method for seismic structures with added viscous fluid dampers. This study uses the full stress algorithm as the optimization method, considering the mean square of interstory drifts as the optimization objective, the position of the damper as the optimization object, and the random vibration analysis method as the calculation method to optimize seismic frame structures with viscous dampers. A precise integral solution is derived for the Lyapunov equation based on the general expression of the Lyapunov differential equation for the damping system under the excitation of a nonstationary stochastic process using two types of modulation functions: g(t)=1 and g(t)=t. Finally, the optimal damping arrangement is achieved using this method with a six-layer non-eccentric planar frame. In addition, the optimization results of this study are verified with those in the literature using time-history analysis, which verifies the feasibility and effectiveness of the proposed method. This study provides a method for the optimal configuration of dampers for seismic response of structures, which is beneficial for engineering applications and the protection of seismic structures.

How to reduce the content placement cost of cloud content delivery networks (CCDNs) is a hot topic in recent years. Traditional content placement methods mainly reduce the cost of content placement by constructing delivery trees, but they cannot adapt to the dynamic deployment of cloud proxy servers in the CCDNs. In addition, the traditional content placement method only provides delivery paths according to local decision-making without considering global dynamics of the congestion in the CCDNs, which is also one of the main factors causing high cost of content placement. To solve these problems, we propose a content placement model based on Q-learning for the dynamic CCDNs, called Q-content placement model (Q-CPM). This Q-learning approach can lead to better routing decisions due to up-to-date and more reliable congestion values. Then, based on the Q-CPM model, an algorithm is proposed to construct the Q-adaptive delivery tree (Q-ADT). In this algorithm, local and nonlocal congestion information is propagated over network learning packets. Through this algorithm, the paths with low congestion cost will be selected and can adapt to the dynamic cloud delivery environment. The experimental results show that the method can adapt to the dynamic changes of the CCDNs flexibly and reduce the overall congestion cost of content placement effectively.

Convolutional Neural Networks (CNNs) have become one of the most successful machine learning techniques for image and video processing. The most computationally intensive part of the CNN is the convolutional layers, which have the multi-channel image and multiple kernels. However, due to the network pruning operation and the application of RELU activation function operation in the training process, numerous zero values are generated in the network. This paper proposes the convolution split compression calculation (CSCC) algorithm, which improves the performance of the convolution layer by utilizing the sparse characteristic of the feature map. In the CSCC algorithm, first, the feature map is directly converted into a sparse matrix of compressed sparse row (CSR) format, which avoids expanding feature map to an intermediate matrix and reduces the memory space consumption. Second, the convolution kernel is converted into a vector. Finally, the convolution result is obtained by the sparse matrix vector multiplication (SpMV). The experimental results show that the CSCC algorithm has a good advantage in computation speed and memory consumption compared with the other convolution algorithms.

The additional damping ratio (ADR) is an important indicator for evaluating the damping effect of structures with energy-dissipation devices. Most existing methods for determining the ADR require an analysis of the structural dynamic response and complex iterative calculations. An innovative simplified calculation method for determining the ADR of a structure supplemented by nonlinear viscous dampers is proposed. This method does not require the dynamic response of the structure to be calculated and only requires the structural characteristics, excitation frequency, and damper parameters. In this study, several typical calculation methods for the ADR were analysed. Then, a calculation formula for the ADR was derived with consideration of harmonic excitation under the condition where the excitation frequency is equal to the structural natural frequency, without calculation of the structural dynamic response or an iterative process. The effect of the excitation frequency on the calculated value of the ADR with different damping exponents was studied. Accordingly, the response spectrum average period (RSAP) was considered as the excitation period of ground motion to evaluate the excitation frequency, and a simplified calculation method for the ADR considering the effect of the excitation frequency characterised by the RSAP of the ground motion was established. Finally, the accuracy and effectiveness of the proposed method were verified by comparison with ADRs calculated using other methods.

Motion estimation (ME) is a kernel algorithm in many video applications. Full search integer ME (FSIME) can find the best result but it usually takes plenty of time. Traditionally, only intra-frame data reuse is considered for FSIME. In this paper, a new inter-frame data reuse method is proposed to further utilize inter-frame data reuse for true ME. ME in frame rate up-conversion (FRUC-ME), a kind of true ME, is used as a case study. For FRUC-ME with the new inter-frame data reuse method, a frame is loaded to the on-chip buffer only once instead of twice and used for two interpolated frames. Two levels of the new method are proposed, Inter-D and new Inter-E, which give a good tradeoff between off-chip memory bandwidth and on-chip buffer size. New data access order is used to implement the new data reuse method. The proposed data reuse method (Inter-D) demands less off-chip memory bandwidth than its intra-frame counterpart (Intra-D), and the off-chip memory traffic and power consumption are both reduced by 37.5% for FRUC-ME.

Motion estimation (ME) is a time-consuming algorithm to find a matching block in the search area for video applications, such as video compression. Motion estimation algorithm includes full search algorithm and fast search algorithm. If the width of the motion estimation algorithm search area is twice the size of the block, half of the search area for adjacent blocks overlaps. In view of this, this paper proposes a search area data reuse method for fast search motion estimation. With the proposed data reuse implementation, only the first block needs to read the data of the entire search area from the off-chip memory. The other blocks only need to read half the original search area. In this way, time of access to external memory is reduced, and running time of the algorithm is also decreased. Experimental results of diamond search show that the search area data reuse methods can reduce the running time by 40% to 60% compared with the algorithm of no use data reuse, and it can also reduce the power consumption by 62% to 73%. Compared with other methods in the literature, the proposed method also performs better on running time and power consumption.

The accurate prediction of nonlinear structural behaviors under different seismic intensities is an important basis for seismic resilience assessments of building structures. The moment–rotation relationship is often used to characterize the seismic performance of connections, and is widely used in high-efficiency nonlinear structural analysis. In this paper, a method of calculating the curve using a four-linear equivalent model is presented, aiming to quantify the characteristic point parameters of the moment–rotation curves of monolithic precast beam–column (MPBC) connections for engineering design purposes. The method considered the contribution of the elastic flexure of beams and columns, the relative slip of beam longitudinal bars in the core zone, and the formation of plastic hinges at beam ends to the total deflection. Due to the presence of local complex configurations in MPBC connections, the fine fiber section method was used for moment–curvature analysis of critical beam sections. The determination of the sectional analysis processes was controlled by the strain of steel bars or concrete or their coupling effect. In addition, a two-step method was proposed to construct the moment–rotation relationship of cruciform beam–column connections for solving the deformation compatibility of beams on both sides of the column caused by asymmetric reinforcement and the strength difference between new and old concrete. To reflect the current manufacturing level of MPBC connections, 58 representative specimens reported in recent years were analyzed and classified as type 1–5. All types of MPBC connections and their 18 cast-in situ counterparts were calculated using the proposed method for both verification and quantification. The verification showed that the proposed method had good applicability to both cast-in situ and precast beam–column connections. The quantification showed that the characteristic point parameters were slightly different between these two connections. Accordingly, modification coefficients were suggested for MPBC connections to facilitate design.

Peptides hold promise as therapeutics, as they have high bioactivity and specificity, good aqueous solubility, and low toxicity. However, they typically suffer from short circulation half-lives in the body. To address this issue, here, we have developed a method for encapsulation of an innate-immune targeted hexapeptide into nanoparticles using safe non-toxic FDA-approved materials. Peptide-loaded nanoparticles were formulated using a two-stage microfluidic chip. Microfluidic-related factors (i.e., flow rate, organic solvent, theoretical drug loading, PLGA type, and concentration) that may potentially influence the nanoparticle properties were systematically investigated using dynamic light scattering and transmission electron microscopy. The pharmacokinetic (PK) profile and biodistribution of the optimised nanoparticles were assessed in mice. Peptide-loaded lipid shell-PLGA core nanoparticles with designated size (~400 nm) and a sustained in vitro release profile were further characterized in vivo. In the form of nanoparticles, the elimination half-life of the encapsulated peptide was extended significantly compared with the peptide alone and resulted in a much higher distribution into the lung. These novel nanoparticles with lipid shells have considerable potential for increasing the circulation half-life and improving the biodistribution of therapeutic peptides to improve their clinical utility, including peptides aimed at treating lung-related diseases.

2-D-to-3-D conversion is one way to make full use of 2-D contents to produce 3-D contents. Real-time 2-D-to-3-D conversion is required for 3-D consumer electronic devices, which demands fast processing speed especially for high-definition videos. In this paper, we propose a reconfigurable VLSI architecture for real-time 2-D-to-3-D conversion. Two different depth-retrieval methods are implemented in this architecture in order to support the choice of a best method or combination of different methods. The proposed architecture can also support different resolutions (4K, 1080p, and 720p) and the original view can be configured as either left view or right view. In order to overcome the problem of “Memory Wall”, we propose a data reuse method to reduce memory traffic for the proposed architecture so that the overall performance is improved to realize real-time conversion. The experiment result shows that the implemented 2-D-to-3-D architecture can achieve state-of-the-art throughput (4K@30f/s).

It is important to reduce the time cost of video compression for image sensors in video sensor network. Motion estimation (ME) is the most time-consuming part in video compression. Previous work on ME exploited intra-frame data reuse in a reference frame to improve the time efficiency but neglected inter-frame data reuse. We propose a novel inter-frame data reuse scheme which can exploit both intra-frame and inter-frame data reuse for ME in video compression (VC-ME). Pixels of reconstructed frames are kept on-chip until they are used by the next current frame to avoid off-chip memory access. On-chip buffers with smart schedules of data access are designed to perform the new data reuse scheme. Three levels of the proposed inter-frame data reuse scheme are presented and analyzed. They give different choices with tradeoff between off-chip bandwidth requirement and on-chip memory size. All three levels have better data reuse efficiency than their intra-frame counterparts, so off-chip memory traffic is reduced effectively. Comparing the new inter-frame data reuse scheme with the traditional intra-frame data reuse scheme, the memory traffic can be reduced by 50% for VC-ME.

As an important part of the national political system, government audits play a significant role in supervising and restricting enterprises. Since 2010, the National Audit Office of China has repeatedly disclosed the problems regarding enterprises’ M&A to prevent the loss of state-owned assets. This study takes listed companies controlled by the central enterprises of A-shares from 2008 to 2018 as a sample to investigate the impact of government audit supervision on M&A. We find that government audit supervision reduces the number and scale of M&As. Further research shows that government audits can reduce enterprises’ M&A premiums and affect payment methods. Finally, government audits significantly improve the short- and long-term performance of M&As. These findings show that Chinese government audits positively affect corporate governance, curbing M&As that damage enterprise interests. This study provides micro-level evidence of the governance effect of government audits on the scientific decision-making of enterprises.