Recombination analysis reveals a double recombination event in hepatitis E virus

Recombination of Hepatitis E Virus (HEV) has rarely been reported. In the present study, phylogenetic and recombination analyses were performed on 134 complete HEV genomes. Three potentially significant recombination events, including both intra-genotype and one inter-genotype, were identified by recombination detection analysis. Recombination events I and II occurred intra-genotype and inter-genotype, respectively, among three isolates, including the lineage represented by CHN-XJ-SW13 (GU119961, swine isolate), E067-SIJ05C (AB369690, human isolate), and JJT-Kan (AB091394, human isolate), and lead to the recombinant swine isolate swCH31 (DQ450072). Recombination event III occurred between the lineage represented by the NA1 (M73218) and K52-87 (L25595), which resulted in the recombinant Xingjiang-1 (D11092). Our analyses proved that that recombination could occur between human and swine HEV strains, double recombination events existed in HEV, and recombination event could happen within ORF2 region of HEV. These results will provide valuable hints for future research on HEV diversity

Composite Analysis-Based Machine Learning for Prediction of Tropical Cyclone-Induced Sea Surface Height Anomaly

Sea surface height anomaly (SSHA) induced by tropical cyclones (TCs) is closely associated with oscillations and is a crucial proxy for thermocline structure and ocean heat content in the upper ocean. The prediction of TC-induced SSHA, however, has been rarely investigated. This study presents a new composite analysis-based random forest (RF) approach to predict daily TC-induced SSHA. The proposed method utilizes TC’s characteristics and pre-storm upper oceanic parameters as input features to predict TC-induced SSHA up to 30 days after TC passage. Simulation results suggest that the proposed method is skillful at inferring both the amplitude and temporal evolution of SSHA induced by TCs of different intensity groups. Using a TC-centered 5°×5° box, the proposed method achieves highly accurate prediction of TC-induced SSHA over the Western North Pacific with root mean square error of 0.024m, outperforming alternative machine learning methods and the numerical model. Moreover, the proposed method also demonstrated good prediction performance in different geographical regions, i.e., the South China Sea and the Western North Pacific subtropical ocean. The study provides insight into the application of machine learning in improving the prediction of SSHA influenced by extreme weather conditions. Accurate prediction of TC-induced SSHA allows for better preparedness and response, reducing the impact of extreme events (e.g., storm surge) on people and property

Framework to Create Cloud-Free Remote Sensing Data Using Passenger Aircraft as the Platform

Cloud removal in optical remote sensing imagery is essential for many Earth observation applications.Due to the inherent imaging geometry features in satellite remote sensing, it is impossible to observe the ground under the clouds directly; therefore, cloud removal algorithms are always not perfect owing to the loss of ground truth. Passenger aircraft have the advantages of short visitation frequency and low cost. Additionally, because passenger aircraft fly at lower altitudes compared to satellites, they can observe the ground under the clouds at an oblique viewing angle. In this study, we examine the possibility of creating cloud-free remote sensing data by stacking multi-angle images captured by passenger aircraft. To accomplish this, a processing framework is proposed, which includes four main steps: 1) multi-angle image acquisition from passenger aircraft, 2) cloud detection based on deep learning semantic segmentation models, 3) cloud removal by image stacking, and 4) image quality enhancement via haze removal. This method is intended to remove cloud contamination without the requirements of reference images and pre-determination of cloud types. The proposed method was tested in multiple case studies, wherein the resultant cloud- and haze-free orthophotos were visualized and quantitatively analyzed in various land cover type scenes. The results of the case studies demonstrated that the proposed method could generate high quality, cloud-free orthophotos. Therefore, we conclude that this framework has great potential for creating cloud-free remote sensing images when the cloud removal of satellite imagery is difficult or inaccurate

Surface electromyography characteristics of patients with anterior cruciate ligament injury in different rehabilitation phases

Background: Anterior cruciate ligament reconstruction (ACLR) is a common treatment for anterior cruciate ligament (ACL) injury. However, after ACLR, a significant proportion of patients do not return to pre-injury levels. Research on muscle function during movement has important implications in rehabilitation.Methods: Sixty patients with unilateral ACL injury were recruited for this study and assigned into three groups: group A, individuals with an ACL injury before 6 months; group B, individuals with ACLR from 6 months to 1 year; and group C, individuals with ACLR 1 year later. Surface electromyography (SEMG) signals were collected from the bilateral rectus femoris (RF), vastus medialis (VM), vastus lateralis (VL), biceps femoris (BF), and semitendinosus (ST). The tasks performed during the experiment included straight leg raising (SLR) training at 30°, SLR training at 60°, ankle dorsiflexion, walking, and fast walking.Results: In the maximum muscle strength test, the affected side of the BF in group A (199.4 ± 177.12) was significantly larger than in group B (53.91 ± 36.61, p = 0.02) and group C (75.08 ± 59.7, p = 0.023). In the walking test, the contralateral side of the RF in group B (347.53 ± 518.88) was significantly greater than that in group C (139.28 ± 173.78, p = 0.029). In the SLR training (60°) test, the contralateral side of the RF in group C (165.37 ± 183.06) was significantly larger than that in group A (115.09 ± 62.47, p = 0.023) and smaller than that in group B (226.21 ± 237.17, p = 0.046); In the ankle dorsiflexion training test, the contralateral side of the RF in group B (80.37 ± 87.9) was significantly larger than that in group C (45.61 ± 37.93, p = 0.046).Conclusion: This study showed the EMG characteristics of patients with ACL injury helped to determine which muscle requires more training and which exercise model would be best suited for intervention

Common and Specific Functional Activity Features in Schizophrenia, Major Depressive Disorder, and Bipolar Disorder

Objectives: Schizophrenia (SZ), major depressive disorder (MDD), and bipolar disorder (BD) are serious mental disorders with distinct diagnostic criteria. They share common clinical and biological features. However, there are still only few studies on the common and specific brain imaging changes associated with the three mental disorders. Therefore, the aim of this study was to identify the common and specific functional activity and connectivity changes in SZ, MDD, and BD.Methods: A total of 271 individuals underwent functional magnetic resonance imaging: SZ (n = 64), MDD (n = 73), BD (n = 41), and healthy controls (n = 93). The symptoms of SZ patients were evaluated by the Positive and Negative Syndrome Scale. The Beck Depression Inventory (BDI), and Beck Anxiety Inventory (BAI) were used to evaluate the symptoms of MDD patients. The BDI, BAI, and Young Mania Rating Scale were used to evaluate the symptoms of MDD and BD patients. In addition, we compared the fALFF and functional connectivity between the three mental disorders and healthy controls using two sample t-tests.Results: Significantly decreased functional activity was found in the right superior frontal gyrus, middle cingulate gyrus, left middle frontal gyrus, and decreased functional connectivity (FC) of the insula was found in SZ, MDD, and BD. Specific fALFF changes, mainly in the ventral lateral pre-frontal cortex, striatum, and thalamus were found for SZ, in the left motor cortex and parietal lobe for MDD, and the dorsal lateral pre-frontal cortex, orbitofrontal cortex, and posterior cingulate cortex in BD.Conclusion: Our findings of common abnormalities in SZ, MDD, and BD provide evidence that salience network abnormality may play a critical role in the pathogenesis of these three mental disorders. Meanwhile, our findings also indicate that specific alterations in SZ, MDD, and BD provide neuroimaging evidence for the differential diagnosis of the three mental disorders

Dual rr-Rank Decomposition and Its Applications

In this paper, we introduce the dual $r$-rank decomposition of dual matrix, get its existence condition and equivalent form of the decomposition, as well as derive some characterizations of dual Moore-Penrose generalized inverse(DMPGI). Based on DMPGI, we introduce one special dual matrix(dual EP matrix). By applying the dual $r$-rank decomposition we derive several characterizations of dual EP matrix, dual idempotent matrix, dual generalized inverses, and the relationships among dual Penrose equations

Hydrocarbon potential assessment of the lacustrine fan delta reservoirs in the Lower Cretaceous syn-rift Xing’anling Formation in the Beier Sag, Hailar Basin, Northeast China

Efficient exploration and development of oil and gas resources in complex geological environments continue to pose significant challenges for the energy industry. The localization and extraction of reservoirs in basins with complex structures, developed faults, and scattered sedimentary sand bodies are topics of international interest. One such basin, the Hailar Basin in northeastern China, represents a complex geological environment with heterogeneous distributions of oil and gas reserves, along with variable reservoir conditions, leading to challenges in hydrocarbon exploration and extraction. The Sudeert oil field, situated within this basin, is known for its high productivity; nevertheless, the underlying factors responsible for its success are not yet fully comprehended. Based on seismic, logging, and core data from the Sudeert oil field, as well as previous research, this study comprehensively analyzed the sedimentary environment, sedimentary facies characteristics, sand body distribution patterns, vertical stacking relationships of sand bodies, and hydrocarbon accumulation potential of the oil reservoirs in the Lower Cretaceous Xing’anling Formation in the Sudeert oil field. The Xing’anling Formation I and II oil reservoirs are deposited in a fan-delta front sedimentary environment, and the sedimentary microfacies that are conducive to the development of reservoir sand bodies include underwater distributary channels, underwater natural levees, estuary dams, front silt beds, and turbidite sands. Among them, the underwater distributary channel microfacies is the main depositional facies for the development of reservoir sand bodies. Three major depositional patterns of fan lobes can be identified within this depositional system: 1) isolated, 2) contact, and 3) superimposed lobes. Different combinations of lobes developed in different blocks and resulted in different sand body depositional patterns. The isolated lobes mainly developed in the western oil-producing (B28 block) due to the scarcity of sand and slowly increasing accommodation space. The contact lobes mainly developed in the central oil-producing block (B14 block) due to sufficient sediment supply and steadily increasing accommodation space across a wide area. The superimposed lobes mainly developed in the southeast oil-producing block (B16 block) due to sufficient sediment input and steadily increasing accommodation space within a restricted area. In the whole study area, the superimposed lobe pattern is the most favorable depositional pattern and forms the highest-quality reservoirs because of the high degree of sand body connectivity. These results also highlight the utility of sedimentary patterns and sand body assemblage studies for the oil exploration and development of similar rifted basins

Scattering Properties of Electromagnetic Waves from Randomly Oriented Rough Metal Plate in the Lower Terahertz Region

An efficient hybrid algorithm is proposed to analyze the electromagnetic scattering properties of an infinitely thin metal plate in the lower terahertz (THz) frequency region. In this region, the metal plate can be viewed as a perfect electrically conductive object with a marginally rough surface. Hence, the THz scattered field from the metal plate can be divided into coherent and incoherent parts. The physical optics and truncated-wedge incremental-length diffraction coefficients methods are used to compute the coherent part, whereas the small perturbation method is used to compute the incoherent part. Then, the radar cross section of the rough metal plate surface is computed by the multilevel fast multipole and proposed hybrid algorithms. The numerical results show that the proposed algorithm has a good accuracy when rapidly simulating the scattering properties in the lower THz region