Explore the vast range of titles available.

This study aimed to validate a bias estimation framework for low-cost maritime IMUs by applying it to real-world shipborne data. Six estimation methods—including statistical (mean, median), model-based (least squares, cross-correlation), and signal-processing approaches (FFT, Butterworth filter)—were compared. The results demonstrated that the low-frequency Butterworth filter achieved the smallest residuals, with RMS residuals below 0.038 m/s2 for accelerometers and 0.0035 deg/s for gyroscopes. In particular, AccX and AccZ residuals converged to 3.04 × 10−2 m/s2 and 2.30 × 10−2 m/s2, respectively, while GyroZ achieved 5.58 × 10−4 deg/s. Estimated accelerometer biases were 0.0405 m/s2 (X-axis) and 0.1615 m/s2 (Y-axis), and the optimization successfully converged with an objective function value of 9.314. The findings confirm that the previously proposed bias estimation method, originally validated in simulation, is effective under real-world maritime conditions. However, as ground truth bias values cannot be obtained in shipborne experiments, verification relied on residual statistics and cross-correlation analysis. This limitation has been explicitly stated in the conclusion, and future studies should incorporate sensitivity analyses and controlled experiments to further quantify error sources.

Inertial navigation systems (INSs) provide autonomous position estimation capabilities independent of global navigation satellite systems (GNSSs). However, the high cost of traditional sensors, such as fiber-optic gyroscopes (FOGs), limits their widespread adoption. In contrast, micro-electromechanical system (MEMS)-based inertial measurement units (IMUs) offer a low-cost alternative; however, their lower accuracy and sensor bias issues, particularly in maritime environments, remain considerable obstacles. This study proposes an improved method for bias estimation by comparing the estimated values from a trajectory generator (TG)-based acceleration and angular-velocity estimation system with actual measurements. Additionally, for X- and Y-axis accelerations, we introduce a method that leverages the correlation between altitude differences derived from an INS/GNSS/gyrocompass (IGG) and those obtained during the TG estimation process to estimate the bias. Simulation datasets from experimental voyages validate the proposed method by evaluating the mean, median, normalized cross-correlation, least squares, and fast Fourier transform (FFT). The Butterworth filter achieved the smallest angular-velocity bias estimation error. For X- and Y-axis acceleration bias, altitude-based estimation achieved differences of 1.2 × 10−2 m/s2 and 1.0 × 10−4 m/s2, respectively, by comparing the input bias using 30 min data. These methods enhance the positioning and attitude estimation accuracy of low-cost IMUs, providing a cost-effective maritime navigation solution.

This article proposes a novel initial bias estimation method using a trajectory generator (TG). The accuracy of attitude and position estimation in navigation after using the inertial navigation system/Doppler velocity log (INS/DVL) and INS/DVL/gyrocompass (IDG) for 1 h were evaluated, and the results were compared to those obtained using the conventional Kalman filter (KF) estimation method. The probability of a horizontal position error < 1852 m (1 nautical mile) with a bias interval > 400 s was 100% and 9% for the TG and KF, respectively. In addition, the IDG average horizontal position errors over 1 h were 493 m and 507 m for the TG and KF, respectively. Moreover, the amount of variation was 2 m and 27 m for the TG and the KF, respectively. Thus, the proposed method is effective for initial bias estimation of INS/DVL and IDG using micro-electro-mechanical system sensors on a constantly moving vessel.

Global navigation satellite system (GNSS) spoofing poses a significant threat to maritime logistics. Many maritime electronic devices rely on GNSS time, positioning, and speed for safe vessel operation. In this study, inertial measurement unit (IMU) and Doppler velocity log (DVL) devices, which are important in the event of GNSS spoofing or outage, are considered in conventional navigation. A velocity integration method using IMU and DVL in terms of dead-reckoning is investigated in this study. GNSS has been widely used for ship navigation, but IMU, DVL, or combined IMU and DVL navigation have received little attention. Military-grade sensors are very expensive and generally cannot be utilized in smaller vessels. Therefore, this study focuses on the use of consumer-grade sensors. First, the performance of a micro electromechanical system (MEMS)-based yaw rate angle with DVL was evaluated using 60 min of raw data for a 50 m-long ship located in Tokyo Bay. Second, the performance of an IMU-MEMS using three gyroscopes and three accelerometers with DVL was evaluated using the same dataset. A gyrocompass, which is equipped on the ship, is used as a heading reference. The results proved that both methods could achieve less than 1 km horizontal error in 60 min.

Automatic Identification System (AIS) provides estimated position time along with reception time and a time stamp at the receiving station; however, the exact position estimation time remains unidentified. Therefore, this study examines the extent of positional error when using current AIS reception time. As a result, a maximum positional error of 116.9 m was observed between AIS and RTK-GPS (Real-Time Kinematic GPS). Subsequent time correction reduced this error to less than 10 m, with the product of ship speed and correction time nearly matching the error pre-correction. Consequently, it was concluded that transmitting position estimation time is essential for maintaining the reliability of Position Accuracy transmitted by AIS or VHF Data Exchange System (VDES). Furthermore, VDES may possess the communication capacity to transmit and receive vessel attitude data. Therefore, to assess the required transmission frequency, the data transmission period of roll and pitch attitude data was analysed through the mutual correlation of acceleration and angular velocity. The results indicated that the correlation coefficient for each axis exceeded 0.65 at frequencies of 0.5 Hz or higher.

Salinity stress enhances sugar accumulation in tomato (Solanum lycopersicum) fruits. To elucidate the mechanisms underlying this phenomenon, the transport of carbohydrates into tomato fruits and the regulation of starch synthesis during fruit development in tomato plants cv. 'Micro-Tom' exposed to high levels of salinity stress were examined. Growth with 160 mM NaCl doubled starch accumulation in tomato fruits compared to control plants during the early stages of development, and soluble sugars increased as the fruit matured. Tracer analysis with ¹³C confirmed that elevated carbohydrate accumulation in fruits exposed to salinity stress was confined to the early development stages and did not occur after ripening. Salinity stress also up-regulated sucrose transporter expression in source leaves and increased activity of ADP-glucose pyrophosphorylase (AGPase) in fruits during the early development stages. The results indicate that salinity stress enhanced carbohydrate accumulation as starch during the early development stages and it is responsible for the increase in soluble sugars in ripe fruit. Quantitative RT-PCR analyses of salinity-stressed plants showed that the AGPase-encoding genes, AgpL1 and AgpS1 were up-regulated in developing fruits, and AgpL1 was obviously up-regulated by sugar at the transcriptional level but not by abscisic acid and osmotic stress. These results indicate AgpL1 and AgpS1 are involved in the promotion of starch biosynthesis under the salinity stress in ABA- and osmotic stress-independent manners. These two genes are differentially regulated at the transcriptional level, and AgpL1 is suggested to play a regulatory role in this event.

Skeletal ciliopathies are a heterogenous group of disorders with overlapping clinical and radiographic features including bone dysplasia and internal abnormalities. To date, pathogenic variants in at least 30 genes, coding for different structural cilia proteins, are reported to cause skeletal ciliopathies. Here, we summarize genetic and phenotypic features of 34 affected individuals from 29 families with skeletal ciliopathies. Molecular diagnostic testing was performed using massively parallel sequencing (MPS) in combination with copy number variant (CNV) analyses and in silico filtering for variants in known skeletal ciliopathy genes. We identified biallelic disease-causing variants in seven genes: DYNC2H1 , KIAA0753, WDR19 , C2CD3 , TTC21B , EVC , and EVC2 . Four variants located in non-canonical splice sites of DYNC2H1 , EVC , and KIAA0753 led to aberrant splicing that was shown by sequencing of cDNA. Furthermore, CNV analyses showed an intragenic deletion of DYNC2H1 in one individual and a 6.7 Mb de novo deletion on chromosome 1q24q25 in another. In five unsolved cases, MPS was performed in family setting. In one proband we identified a de novo variant in PRKACA and in another we found a homozygous intragenic deletion of IFT74 , removing the first coding exon and leading to expression of a shorter message predicted to result in loss of 40 amino acids at the N-terminus. These findings establish IFT74 as a new skeletal ciliopathy gene. In conclusion, combined single nucleotide variant, CNV and cDNA analyses lead to a high yield of genetic diagnoses (90%) in a cohort of patients with skeletal ciliopathies.

The corpus callosum, a major white matter tract in the brain, undergoes age-related functional changes. To extend our investigation of age-related gene expression dynamics in the mouse corpus callosum, we compared RNA-seq data from 2 week-old and 12 week-old wild-type C57BL/6 J mice and identified the differentially expressed genes (e.g., Marcksl1 , Chst3 , C4b , Neat1 , Ndrg1 , Emid1 , etc.) between these ages. Interestingly, we found that genes highly expressed in myelinating oligodendrocytes were upregulated in 12 week-old mice compared to 2 week-old mice, while genes highly expressed in oligodendrocyte precursor cells (OPCs) and newly formed oligodendrocytes were downregulated. Furthermore, by comparing these genes with the datasets from 20 week-old and 96 week-old mice, we identified novel sets of genes with age-dependent variations in the corpus callosum. These gene expression changes potentially affect key biological pathways and may be closely linked to age-related neurological disorders, including dementia and stroke. Therefore, our results provide an additional dataset to explore age-dependent gene expression dynamics of oligodendrocyte lineage cells in the corpus callosum.

Background Rotator cuff tears (RCTs) are often associated with severe shoulder pain. Non-steroidal anti-inflammatory drugs, not recommended for long-term use, do not effectively manage RCT-induced pain, resulting in reduced quality of life. To improve management, a better understanding of the fundamental properties of RCT pain is needed. Here, we aimed to compare the expression levels of nerve growth factor (NGF) and cyclooxygenase-2 (COX-2) mRNA in the synovial tissues of patients with RCT-induced pain and patients with non-painful recurrent shoulder dislocation (RSD). Methods The study included 32 patients with RCT who underwent arthroscopic rotator cuff repair and 28 patients with non-painful RSD who underwent arthroscopic Bankart repair. Synovial tissue samples were harvested from subacromial bursa and rotator interval of RCT patients and from the rotator interval of RSD patients. Samples were analyzed quantitatively expression levels for NGF and COX2 mRNA and NGF protein. Results NGF mRNA and protein levels were significantly higher in the rotator interval of RCT patients than in the rotator interval of RSD patients (p = 0.0017, p = 0.012, respectively), while COX2 mRNA levels did not differ significantly between the two patient groups. In RCT patients, COX2 mRNA was more highly expressed in the rotator interval than in the subacromial bursa (p = 0.038), whereas the mRNA and protein levels of NGF did not differ between the two tissues. The expression of NGF mRNA in the synovium of the rotator interval was significantly correlated with the numeric rating scale of pain (ρ = 0.38, p = 0.004). Conclusion NGF mRNA and protein levels were elevated in patients with painful RCT compared with those in patients with non-painful RSD, whereas COX-2 levels were comparable in the two patient groups. These findings provide insights into novel potential strategies for clinical management of RCT.

Computer networks are facing serious threats from the emergence of malware with sophisticated DGAs (Domain Generation Algorithms). This type of DGA malware dynamically generates domain names by concatenating words from dictionaries for evading detection. In this paper, we propose an approach for identifying the callback communications of such dictionary-based DGA malware by analyzing their domain names at the word level. This approach is based on the following observations: These malware families use their own dictionaries and algorithms to generate domain names, and accordingly, the word usages of malware-generated domains are distinctly different from those of human-generated domains. Our evaluation indicates that the proposed approach is capable of achieving accuracy, recall, and precision as high as 0.9989, 0.9977, and 0.9869, respectively, when used with labeled datasets. We also clarify the functional differences between our approach and other published methods via qualitative comparisons. Taken together, these results suggest that malware-infected machines can be identified and removed from networks using DNS queries for detected malicious domain names as triggers. Our approach contributes to dramatically improving network security by providing a technique to address various types of malware encroachment.