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Automated Guided Vehicles (AGVs) are vital to smart factories, enabling autonomous and efficient material transport. However, precise navigation is challenging because LiDAR provides high-dimensional, dynamic spatial data, while Inertial Measurement Unit (IMU) signals are often intermittent, leading to inconsistencies and navigation drift. This work proposes the Screened Inertial Data Fusion Method (SIDFM), a novel framework that systematically screens LiDAR data using a minimal differential function and fuses it with IMU intervals through linear regression learning. The SIDFM approach ensures that only consistent LiDAR points are integrated with IMU data, reducing mismatches and improving motion estimation. SIDFM was validated using a benchmark AGV dataset and compared against baseline LiDAR-IMU fusion methods under varying acceleration conditions. Results show that SIDFM reduces navigation errors by 12.09% at low acceleration and 11.43% at high acceleration while also significantly decreasing positioning errors. These improvements enhance the stability, precision, and safety of AGVs in dynamic manufacturing environments. The findings establish SIDFM as an effective and practical solution for robust AGV navigation, with potential applications in smart factories, warehouses, and autonomous mobility systems that demand both efficiency and reliability.

In this paper, we develop an inexact symmetric proximal alternating direction method of multipliers (ISPADMM) with two convex combinations (ISPADMM-tcc) for solving two-block separable convex optimization problems with linear equality constraints. Specifically, the convex combination technique is incorporated into the proximal centers of both subproblems. We then approximately solve these two subproblems based on relative error criteria. The global convergence, and O ( 1 N ) ergodic sublinear convergence rate measured by the function value residual and constraint violation are established under some mild conditions, where N denotes the number of iterations. Finally, numerical experiments on solving the l 1 -regularized analysis sparse recovery and the elastic net regularization regression problems illustrate the feasibility and effectiveness of the proposed method.

Michler’s Ketone (MK) is widely utilized as an additive in pigments, dyes, and other colorants, and has become a non-negligible environmental presence. Currently, environmental monitoring data and toxicity data for MK are extremely limited, and its specific mechanisms of neurotoxicity remain poorly characterized. A zebrafish model was employed to systematically delineate the neurotoxic mechanisms of MK through the integration of network toxicology predictions, transcriptomic profiling, and RT-qPCR validation. The results demonstrated that MK exposure was found to induce oxidative stress in zebrafish larvae, which subsequently disrupted the calcium signaling pathway and triggered apoptosis, ultimately leading to neurodevelopmental and locomotor behavioral impairments. This study provides a fundamental basis for elucidating MK’s developmental neurotoxicity mechanisms, while also holding significant value for its ecological risk assessment.

Byzantine failures remain a critical threat to Federated Learning (FL), where malicious clients inject adversarial updates to disrupt global model convergence. From the perspective of symmetry, benign client updates typically exhibit statistical symmetry around the global consensus, whereas Byzantine attacks function as “symmetry-breaking” events that introduce skewness and distributional anomalies. Existing defenses often rely on unrealistic assumptions or fail to capture these asymmetric deviations under high-dimensional non-IID settings. In this paper, we propose a symmetry-aware Byzantine-resilient FL framework driven by a Dual-Channel Attention-Driven Anomaly Detector (DAAD). Specifically, DAAD transforms inter-client behaviors into geometrically symmetric interaction matrices—encoding Gradient Cosine Similarities and Loss Euclidean Distances—to construct dual-channel spatial representations. These representations are processed via a Convolutional Neural Network (CNN) enhanced with Squeeze-and-Excitation (SE) attention blocks, which leverage the inherent symmetry of benign consensus to extract robust adversarial signatures. The detector is pre-trained offline on a synthetic dataset incorporating a diverse portfolio of simulated attacks (e.g., Gaussian noise and label flipping). Crucially, this pre-trained model is seamlessly embedded into the online FL loop to filter updates without requiring ground-truth labels. By jointly encoding client behaviors and learning cross-modal attack signatures, our framework enables reliable detection even when over half of the clients are Byzantine. Extensive experiments on MNIST, CIFAR-10, and FEMNIST datasets demonstrate that DAAD consistently outperforms existing robust aggregation baselines in both anomaly detection accuracy and global model performance, especially under high Byzantine ratios and non-IID conditions.

To evaluate the feasibility, safety, and efficacy of the lateral single-incision laparoscopic totally extraperitoneal (L-SILTEP) approach in patients with inguinal hernia who had contraindications to the midline approach. This study included 58 patients who underwent L-SILTEP. Data on their baseline characteristics and perioperative details were collected. Quality of life and cosmetic satisfaction assessments were performed. Of the evaluated patients, 25.9% had a history of middle and lower abdominal surgery and 10.3% had skin diseases around the umbilicus. The mean surgical duration, blood loss volume, and incision length were 53.5 (± 22.3) min, 7.2 (± 9.7) mL, and 2.0 (± 0.13) cm, respectively. Additionally, 29.3% of patients experienced intraoperative peritoneal rupture, and one patient had epigastric vessel bleeding. The 6-, 24-, and 48-h postoperative pain scores were 3.0 (± 0.6), 1.6 (± 0.6), and 1.1 (± 0.4), respectively. Postoperative complications included seroma ( n  = 3), hematoma ( n  = 1), and scrotal edema ( n  = 1). The surgical incision in the L-SILTEP approach was more aesthetically pleasing than that in previous surgeries. Approximately 17.2%, 8.6%, and 10.3% of patients reported pain, mesh sensation, and movement limitation, respectively. Severe or disabling symptoms were not reported, and there were no cases of 30-day readmissions. Hernia recurrence or incisional hernia was not observed over a mean follow-up duration of 14.6 (± 6.1) months. L-SILTEP can be used for patients with contraindications to the midline approach. Furthermore, it is a safe and effective procedure.

Currently, chemoresistance is a major challenge that directly affects the prognosis of patients with colorectal cancer (CRC). In addition, hypoxia is associated with poor prognosis and therapeutic resistance in patients with cancer. Accumulating evidence has shown that α-hederin has significant antitumour effects and that α-hederin can inhibit hypoxia-mediated drug resistance in CRC; however, the underlying mechanism remains unclear. In the present study, viability and proliferation assays were used to evaluate the effect of α-hederin on the drug resistance of CRC cells under hypoxia. Sequencing analysis and apoptosis assays were used to determine the effect of α-hederin on apoptosis under hypoxia. Western blot analysis and reverse transcription-quantitative PCR were used to measure apoptosis-related protein and mRNA expression levels. Furthermore, different mouse models were established to study the effect of α-hederin on hypoxia-mediated CRC drug resistance in vivo. In the present study, the high expression of Bcl2 in hypoxic CRC cells was revealed to be a key factor in their drug resistance, whereas α-hederin inhibited the expression of Bcl2 by reducing AKT phosphorylation in vitro and in vivo, and promoted the apoptosis of CRC cells under hypoxia. By contrast, overexpression of AKT reversed the effect of α-hederin on CRC cell apoptosis under hypoxia. Taken together, these results suggested that α-hederin may overcome hypoxia-mediated drug resistance in CRC by inhibiting the AKT/Bcl2 pathway. In the future, α-hederin may be used as a novel adjuvant for reversing drug resistance in CRC.

The discovery of the Higgs boson with its mass around 125 GeV by the ATLAS and CMS Collaborations marked the beginning of a new era in high energy physics. The Higgs boson will be the subject of extensive studies of the ongoing LHC program. At the same time, lepton collider based Higgs factories have been proposed as a possible next step beyond the LHC, with its main goal to precisely measure the properties of the Higgs boson and probe potential new physics associated with the Higgs boson. The Circular Electron Positron Collider~(CEPC) is one of such proposed Higgs factories. The CEPC is an \\(e^+e^-\\) circular collider proposed by and to be hosted in China. Located in a tunnel of approximately 100~km in circumference, it will operate at a center-of-mass energy of 240~GeV as the Higgs factory. In this paper, we present the first estimates on the precision of the Higgs boson property measurements achievable at the CEPC and discuss implications of these measurements.