LIO-GVM: an Accurate, Tightly-Coupled Lidar-Inertial Odometry with Gaussian Voxel Map

This letter presents an accurate and robust Lidar Inertial Odometry framework. We fuse LiDAR scans with IMU data using a tightly-coupled iterative error state Kalman filter for robust and fast localization. To achieve robust correspondence matching, we represent the points as a set of Gaussian distributions and evaluate the divergence in variance for outlier rejection. Based on the fitted distributions, a new residual metric is proposed for the filter-based Lidar inertial odometry, which demonstrates an improvement from merely quantifying distance to incorporating variance disparity, further enriching the comprehensiveness and accuracy of the residual metric. Due to the strategic design of the residual metric, we propose a simple yet effective voxel-solely mapping scheme, which only necessities the maintenance of one centroid and one covariance matrix for each voxel. Experiments on different datasets demonstrate the robustness and accuracy of our framework for various data inputs and environments. To the benefit of the robotics society, we open source the code at https://github.com/Ji1Xingyu/lio_gvm

Survival impact and safety of intrathoracic and abdominopelvic cytoreductive surgery in advanced ovarian cancer: a systematic review and meta-analysis

PurposeAchieving no residual disease is essential for increasing overall survival (OS) and progression-free survival (PFS) in ovarian cancer patients. However, the survival benefit of achieving no residual disease during both intrathoracic and abdominopelvic cytoreductive surgery is still unclear. This meta-analysis aimed to assess the survival benefit and safety of intrathoracic and abdominopelvic cytoreductive surgery in advanced ovarian cancer patients.MethodsWe systematically searched for studies in online databases, including PubMed, Embase, and Web of Science. We used Q statistics and I-squared statistics to evaluate heterogeneity, sensitivity analysis to test the origin of heterogeneity, and Egger’s and Begg’s tests to evaluate publication bias.ResultsWe included 4 retrospective cohort studies, including 490 patients, for analysis; these studies were assessed as high-quality studies. The combined hazard ratio (HR) with 95% confidence interval (CI) for OS was 1.92 (95% CI 1.38-2.68), while the combined HR for PFS was 1.91 (95% CI 1.47-2.49). Only 19 patients in the four studies reported major complications, and 4 of these complications were surgery related.ConclusionThe maximal extent of cytoreduction in the intrathoracic and abdominopelvic tract improves survival outcomes, including OS and PFS, in advanced ovarian cancer patients with acceptable complications.Systematic Review RegistrationPROSPERO, identifier CRD4202346809

Artificial Synthesis of Conserved Segment S Gene Fragment of Rift Valley Fever Virus and Preliminary Study of Its Reverse Transcription Loop-Mediated Isothermal Amplification Detection Method

Purpose: To develop a rapid detection method for Rift Valley fever virus (RVFV) diagnosis.Methods: According to the reference sequences of RVFV published in GenBank, nine overlapping polymerase chain reaction (PCR) primers and four specific reverse transcription loop-mediated isothermal amplification (RT-LAMP) primers were designed using DNAStar and LAMP primer design software, respectively. Based on the synthesis of a conserved part of the RVFV S segment gene sequence using overlapping PCR, RT-LAMP assay was first established and evaluated after a series of tests, including, optimization of reaction conditions, and sensitivity and specificity tests.Result: A target RVFV S segment gene fragment of 288 bp was synthesised. The optimal reaction conditions for RT-LAMP assay were 63 °C for 45 min: the assay has a specific ladder-like pattern of amplification bands from about 120 bp. The lowest target gene copy number of RT-LAMP for RVFV detection was 70 copies. The assay showed good specificity as only the synthesised target RVFV gene was amplified with no amplification for the detection of Peste des petits ruminants virus, Epidemic encephalitis B virus, E. coli, Pasteurella multocida, or Salmonella.Conclusion: This study provides a rapid, sensitive, specific RT-LAMP method for RVFV detection.Keywords: Rift valley fever virus, Overlapping polymerase chain reaction, Reverse transcription loopmediated isothermal amplification, Rapid diagnosis tes

Modeling and assessing load redistribution attacks considering cyber vulnerabilities in power systems

Introduction: Load Redistribution (LR) attacks, as a common form of false data injection attack, have emerged as a significant cybersecurity threat to power system operations by manipulating load buses’ measurements at substations. Existing LR attack methods typically assume that any substation can be equally attacked, contributing to the analysis of LR attacks in power systems. However, the diversity of cyber vulnerabilities in substation communication links implies varying costs associated with falsifying load buses’ measurements. Thus, quantitatively evaluating these costs and analyzing the impact of LR attacks on power systems within cost constraints holds practical significance.Methods: In this paper, we employ a Bayesian attack graph model to characterize the intrusion process through cyber vulnerabilities. The costs of falsifying load buses’ measurements at substations are quantitatively evaluated using the mean time-to-compromise model. Subsequently, from the attacker’s perspective, we propose a bi-level optimization model for LR attacks, considering the mean time to compromise in conjunction with limited attack resources and power flow constraints.Results: Simulations conducted on the IEEE 14-bus system illustrate the influence of cyber vulnerabilities on LR attacks within power systems. Furthermore, we verify that the attack scenario of the existing LR attack model aligns with a case of the proposed bi-level LR attack model when there is sufficient attack time to compromise all communication links.Discussion: The findings of this research demonstrate that the impact of cyber vulnerabilities on LR attacks can be quantified by assessing the attack costs. Effective management of LR attacks can be achieved under cost constraints through optimization methods. These insights contribute to enhancing network security strategies for power systems, mitigating potential threats posed by LR attacks in power system operations

TensorMD: Scalable Tensor-Diagram based Machine Learning Interatomic Potential on Heterogeneous Many-Core Processors

Molecular dynamics simulations have emerged as a potent tool for investigating the physical properties and kinetic behaviors of materials at the atomic scale, particularly in extreme conditions. Ab initio accuracy is now achievable with machine learning based interatomic potentials. With recent advancements in high-performance computing, highly accurate and large-scale simulations become feasible. This study introduces TensorMD, a new machine learning interatomic potential (MLIP) model that integrates physical principles and tensor diagrams. The tensor formalism provides a more efficient computation and greater flexibility for use with other scientific codes. Additionally, we proposed several portable optimization strategies and developed a highly optimized version for the new Sunway supercomputer. Our optimized TensorMD can achieve unprecedented performance on the new Sunway, enabling simulations of up to 52 billion atoms with a time-to-solution of 31 ps/step/atom, setting new records for HPC + AI + MD

Assisted reproductive technology and interactions between serum basal FSH/LH and ovarian sensitivity index

ObjectivesThis study aimed to investigate whether the FSH (follicle-stimulating hormone)/LH (Luteinizing hormone) ratio correlates with ovarian response in a cross-sectional retrospective study of a population with normal levels of anti-Müllerian hormone (AMH).MethodsThis was a retrospective cross‐sectional study with data obtained from medical records from March 2019 to December 2019 at the reproductive center in the Affiliated Hospital of Southwest Medical University. The Spearmans correlation test evaluated correlations between Ovarian sensitivity index (OSI) and other parameters. The relationship between basal FSH/LH and ovarian response was analyzed using smoothed curve fitting to find the threshold or saturation point for the population with mean AMH level (1.1<AMH<6μg/L). The enrolled cases were divided into two groups according to AMH threshold. Cycle characteristics, cycle information and cycle outcomes were compared. The Mann-Whitney U test was used to compare different parameters between two groups separated by basal FSH/LH in the AMH normal group. Univariate logistic regression analysis and multivariate logistic regression analysis were performed to find the risk factor for OSI.ResultsA total of 428 patients were included in the study. A significant negative correlation was observed between OSI and age, FSH, basal FSH/LH, Gn total dose, and Gn total days, while a positive correlation was found with AMH, AFC, retrieved oocytes, and MII egg. In patients with AMH <1.1 ug/L, OSI values decreased as basal FSH/LH levels increased, while in patients with 1.1<AMH<6 ug/L, OSI values remained stable with increasing basal FSH/LH levels. Logistic regression analysis identified age, AMH, AFC, and basal FSH/LH as significant independent risk factors for OSI.ConclusionsWe conclude that increased basal FSH/LH in the AMH normal group reduces the ovarian response to exogenous Gn. Meanwhile, basal FSH/LH of 3.5 was found to be a useful diagnostic threshold for assessing ovarian response in people with normal AMH levels. OSI can be used as an indicator of ovarian response in ART treatment

Optimizing the face paradigm of BCI system by modified mismatch negative paradigm

Many recent studies have focused on improving the performance of event-related potential (ERP) based brain computer interfaces (BCIs). The use of a face pattern has been shown to obtain high classification accuracies and information transfer rates (ITRs) by evoking discriminative ERPs (N200 and N400) in addition to P300 potentials. Recently, it has been proved that the performance of traditional P300-based BCIs could be improved through a modification of the mismatch pattern. In this paper, a mismatch inverted face pattern (MIF-pattern) was presented to improve the performance of the inverted face pattern (IF-pattern), one of the state of the art patterns used in visual-based BCI systems. Ten subjects attended in this experiment. The result showed that the mismatch inverted face pattern could evoke significantly larger vertex positive potentials (p < 0.05) and N400s (p < 0.05) compared to the inverted face pattern. The classification accuracy (mean accuracy is 99.58%) and ITRs (mean bit rate is 27.88 bit/min) of the mismatch inverted face pattern was significantly higher than that of the inverted face pattern (p < 0.05)

Chemical ordering suppresses large-scale electronic phase separation in doped manganites

For strongly correlated oxides, it has been a long-standing issue regarding the role of the chemical ordering of the dopants on the physical properties. Here, using unit cell by unit cell superlattice growth technique, we determine the role of chemical ordering of the Pr dopant in a colossal magnetoresistant (La1-yPry)1-xCaxMnO3 (LPCMO) system, which has been well known for its large length-scale electronic phase separation phenomena. Our experimental results show that the chemical ordering of Pr leads to marked reduction of the length scale of electronic phase separations. Moreover, compared with the conventional Pr-disordered LPCMO system, the Pr-ordered LPCMO system has a metal–insulator transition that is ~100 K higher because the ferromagnetic metallic phase is more dominant at all temperatures below the Curie temperature