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Abstract Background Synchronous multiple primary lung cancer (sMPLC) exhibits distinct histopathological characteristics among pulmonary nodules. However, a comprehensive understanding of the somatic mutation landscape and transcriptome heterogeneity is lacking. Therefore, our study aims to meticulously investigate genomic distinctions among multiple pulmonary nodules within individual patients. Methods We performed targeted DNA sequencing on tumor specimens and conducted bulk RNA transcriptome analysis on 53 multiple nodules originating from 26 lung cancer patients. The multiple nodules from the same patient was determined as major nodule and minor nodule. Additionally, the tumor tissues underwent histopathological evaluation through H&E staining, complemented by a comprehensive series of immunohistochemistry (IHC) analyses to detect protein expression. The detected protein markers encompassed PD-L1, Ki67, and others. Results For the 53 nodule samples from 26 MPLCs patients, EGFR was the mostly mutated genes, and the TP53 mutation frequency was notably different between major and minor nodules. Furthermore, pathway enrichment analysis based on the differentially expressed genes (DEGs) between major and minor nodules revealed the significantly active cell cycle and p53 pathways in the major nodules. Additionally, both major and minor nodules demonstrated mostly similar immune microenvironment and PD-L1 protein expression, and a significantly higher expression of Ki67. A noteworthy suppression was observed in the immune microenvironment in nodules, revealed by the expression of macrophage, neutrophils, and NK cells. Furthermore, minor nodules exhibited a modestly elevated expression of macrophages compared to major nodules. Additionally, among the significantly up-regulated cell cycle-related genes in the major nodules when compared with minor nodules, CCNE1 mRNA expression demonstrated significant correlation with poor prognosis in the lung cancer. Furthermore, the MYC inhibitor demonstrated more sensitivity for the major nodules than minor nodules. Conclusions This study validated molecular distinctions between samples from major and minor nodules in patients with sMPLC at both genomic and transcriptomic levels. The major nodules exhibited heightened activity in tumor cell proliferation pathways and demonstrated malignancy-related biological characteristics, which correlated with pathological assessment results.

With the development and maturity of autonomous driving technology, parcel terminal distribution has taken the lead as an application scenario for unmanned delivery vehicles that autonomously perform the task of delivering packages between distribution centres and customers. The traditional terminal delivery model faces challenges such as high costs, low efficiency and time conflicts between delivery and customer convenience. Considering the multiple demands of parcels terminal delivery, this paper proposes a space-time route planning model coordinated with task assignment for autonomous delivery vehicle fleet with the objective of minimizing the total transportation distance and designs a route planning with task assignment algorithm. Firstly, a method of period division and the concept of reliable service time are put forward and a task integration approach is introduced. Then, the task assignment model based on task network and the shortest space-time route planning model are built. According to the characteristics of the model, a route planning with task assignment algorithm by improving the Tabu Search algorithm is designed to gain the best delivery space-time routes of autonomous delivery vehicle fleet. Simulation results show that the approach system of space-time route planning designed in this paper can effectively accomplish task assignment and route planning simultaneously.

After years of development, solar photovoltaic power stations have become increasingly mature and have made great breakthroughs. Building solar photovoltaic power stations in hydropower station reservoirs can not only use the rich sunlight on the water surface of the reservoir, but also make full use of the load regulation speed. The problem of unstable load of solar photovoltaic power plants realizes “water and light complementation” and provides high-quality, reliable and clean energy for the power grid.

Abstract Background 25-hydroxyvitamin D [25(OH)D] concentrations and physical activity (PA) are linked and both are associated with changes in mortality. We examined the association of 25(OH)D and PA with all-cause or cause-specific mortality risk in stroke survivors. Methods The analysis included 677 stroke survivors from National Health and Nutrition Examination Survey (NHANES) 2007–2008 to 2017–2018. Independent and joint associations of 25(OH)D, PA and mortality among stroke survivors were analyzed using weighted Cox regression. Results We identified 133 all-cause deaths [major adverse cardiovascular events (MACE), 34; non-MACE, 79] with a median follow-up of 5.8 years (interquartile, 2.8–8.9 years). In a range of adjusted models, high 25(OH)D was observed with lower all-cause mortality compared to low 25(OH)D (HR, 0.376; 95% CI, 0.233–0.607) and non-MACE (HR, 0.265; 95% CI, 0.143–0.490) mortality was consistently associated. At the same time, compared with no PA, PA was associated with a lower all-cause (HR, 0.280; 95%CI, 0.107–0.733) and non-MACE (HR, 0.266; 95%CI, 0.087–0.810) was associated with a lower risk of death. In addition, pooled analyses showed that stroke survivors with high 25(OH)D and PA had the lowest risk of all-cause death (HR, 0.132; 95%CI, 0.038–0.460) and non-MACE (HR, 0.092; 95%CI, 0.023–0.363), there is an additive interaction between 25(OH)D and PA in non-MACE. Conclusion In conclusion, this study found that combining high 25(OH)D levels and PA showed an enhanced protective effect which demonstrated a synergistic effect between them in reducing mortality among stroke survivors. These findings provide new ideas and possibilities for the prevention and treatment of cardiovascular and cerebrovascular diseases, offering a reference for development of clinical practice guidelines in the future.

Two-dimensional direction of arrival (2D-DOA) estimation, or estimating the azimuth and elevation angles of sources simultaneously, is an increasingly important area in array signal processing. This paper presents a 2D-DOA algorithm together with a novel structure of array named Arc-Array (ArcA). The ArcA is enlarged to a virtual Uniform Circular Array (UCA) through a Deep-Neural-Network (DNN) based covariance matrix completion strategy; afterward, the MUSIC algorithm is performed with the completed covariance matrix. The proposed method is named as ArcA-DNN, and the performance of ArcA-DNN is evaluated by computer simulations. The simulation results indicate that the performance of 2D-DOA estimation in ArcA is able to approach that of a complete UCA; meanwhile, the number of physical elements is substantially reduced compared to the UCA. Moreover, the proposed ArcA-DNN algorithm gives access to implementing underdetermined 2D-DOA estimation with reasonable results.

Abstract In this paper, the blind signal separation problem of complex baseband signal is addressed. A widely linear complex autoregressive process of order one is employed to represent the temporal structure of complex sources. We formulate a new contrast function by a convex combination of generalized autocorrelations and the statistics of the innovation. And the proposed contrast function is optimized by gradient method. Simulation results show that the proposed algorithm is better than the comparison algorithm in convergence speed and convergence accuracy.

Abstract Background Metronidazole, a common antimicrobial agent, can induce encephalopathy in rare cases. After discontinuing metronidazole, most patients show clinical improvement. However, in the face of deteriorating conditions, there have done not to have reports of effective drug treatment. Case presentation A 57-year-old man was admitted to our hospital due to dysarthria and ataxic gait after taking metronidazole at the dose of about 32 g for 20 days. Neurological examination showed that his upward and outward movements of bilateral eyeballs were limited, and horizontal and vertical nystagmus were noted. The brain magnetic resonance imaging showed hyper-intensities in the bilateral cerebellar dentate nuclei, medulla oblongata, midbrain and red nuclei in T2W and FLAIR images. However, the patient’s clinical symptoms worsened after drug cessation. High-dose intravenous methylprednisolone pulse therapy was applied, and this led to a drastic improvement of his symptoms and signs. Conclusions In our case, we suggest that early methylprednisolone intervention can prevent the progression of metronidazole-induced encephalopathy and accelerate neurological recovery. We infer that the progression of encephalopathy is related to the delayed toxicity caused by high dose or concentration of metronidazole.

In this paper, we investigate the performance of two-way multiple relay non-orthogonal multiple access (NOMA) based networks with hardware impairments (HIs). Especially, opportunistic relay selection scheme is applied to enhance the spectral efficiency along with the spatial diversity. With the increasing of relay's processing capacity, decode-and-forward (DF) protocol is considered in the networks. Based on the proposed relay selection scheme and NOMA protocol, the closed-form expressions for the outage probability (OP) of the system are derived. In order to study the energy efficiency (EE) of the system, simulation results for EE are also obtained. Furthermore, for the purpose of observing the impacts of HIs' level, NOMA protocol and the number of relays on the system performance at high signal-to-noise ratios (SNRs), the asymptotic expressions of the OP are also derived. Finally, Monte Carlo (MC) simulation results are presented to verify the correctness of the analytical results.

In this article, we investigate the impact of hardware impairments (HIs) on the performance of non-orthogonal multiple access (NOMA) based integrated satellite-terrestrial relay networks (ISTRNs). Particularly, we obtain the novel closed-form expression for the outage probability (OP) of the considered NOMA-based ISTRNs with HIs. Furthermore, to get further insights of the effect of HIs on the considered system in high signal-to-noise ratios (SNRs) scenario, the asymptotic expression for the OP is also obtained, which provides an efficient way to evaluate the system performance, and effective quantification of different parameters on the system performance. Furthermore, we study the energy efficiency (EE) of the considered system and obtain interesting findings when NOMA scheme is applied. At last, numerical Monte Carlo (MC) results are given to verify the correctness of the theoretical results.

Underdetermined DOA estimation, which means estimating more sources than sensors, is a challenging problem in the array signal processing community. This paper proposes a novel algorithm that extends the underdetermined DOA estimation in a Sparse Circular Array (SCA). We formulate this problem as a matrix completion problem. Meanwhile, we propose an inverse beamspace transformation combined with the Gridless SPICE (GLS) algorithm to complete the covariance matrix sampled by SCA. The DOAs are then obtained by solving a polynomial equation with using the Root-MUSIC algorithm. The proposed algorithm is named GSCA. Monte-Carlo simulations are performed to evaluate the GSCA algorithm, the spatial spectrum plots and RMSE curves demonstrated that the GSCA algorithm can give reasonable results of underdetermined DOA estimation in SCA. Meanwhile, the performance of the algorithm under various configurations of SCA is also evaluated. Numerical results indicated that the GSCA algorithm can provide access to solve the DOA estimation problem in Uniform Circular Array (UCA) when random sensor failures occur.