Dual quaternions have wide applications in automatic differentiation, computer graphics, mechanics and others. Due to its application in control theory, the matrix equation AXB=C has been extensively studied. However, there is currently limited information on matrix equation AXB=C over the dual quaternion algebra. In this paper, we provide the necessary and sufficient conditions for the solvability of the dual quaternion matrix equation AXB=C, and present the expression for the general solution when it is solvable. As an application, we derive the ϕ-Hermitian solutions for the dual quaternion matrix equation AXAϕ=C, where the ϕ-Hermitian extends the concepts of Hermiticity and η-Hermiticity. Lastly, we present a numerical example to verify the main research results of this paper.

Formaldehyde (HCHO) is one of the most important carcinogenic air contaminants. However, the lack of global surface concentration of HCHO monitoring is currently hindering research on outdoor HCHO pollution. Traditional methods are either restricted to small areas or data- demanding for a global scale of research. To alleviate this issue, we adopted neural networks to estimate surface HCHO concentration with confidence intervals in 2019, where HCHO vertical column density data from TROPOMI, in-situ data from HAPs (harmful air pollutants) monitoring network and ATom mission are utilized. Our result shows that the global surface HCHO average concentration is 2.30 μg/m3. Furthermore, in terms of regions, the concentration in Amazon Basin, Northern China, South-east Asia, Bay of Bengal, Central and Western Africa are among the highest. The results from our study provides a first dataset of the global surface HCHO concentration. In addition, the derived confidence interval of surface HCHO concentration adds an extra layer for the confidence to our results. As a pioneer work in adopting confidence interval estimation into AI-driven atmospheric pollutant research and the first global HCHO surface distribution dataset, our paper will pave the way for the rigorous study on global ambient HCHO health risk and economic loss, thus providing a basis for pollutant controlling policies worldwide.

In this paper, we establish the necessary and sufficient conditions for solving a dual split quaternion matrix equation AXB=C, and present the general solution expression when solvability is achieved. As an application, we delve into the necessary and sufficient condition for the existence of Hermitian solution to this equation by using a newly defined real representation method. Furthermore, we obtain the solutions for the dual split quaternion matrix equations AX=C and XB=C. Finally, we provide a numerical example to demonstrate the findings of this paper.

Side-scan sonar (SSS) detection is a key method in applications such as underwater environmental security and subsea resource development. The use of acoustic images for seabed target detection has gradually become a mainstream underwater detection method. However, many existing detection approaches primarily concentrate on tracking the evolution path of optical image object detection tasks, resulting in complex structures and limited versatility. To tackle this issue, we introduce a pioneering Dual-Domain Multi-Frequency Network (D2MFNet) meticulously crafted to harness the distinct characteristics of SSS image detection. In D2MFNet, aiming at the underwater detection requirements of small scenes, we introduce a novel method for optimize and improve the detection sensitivity of different frequency ranges and propose a Multi-Frequency Combined Attention Mechanism (MFCAM). This mechanism amplifies the relevance of dual-domain features across different channels and space. Moreover, recognizing that SSS images can provide richer insights after frequency domain conversion, we introduce a Dual-Domain Feature Pyramid Network (D2FPN). By incorporating frequency domain information representation, D2FPN significantly augments the depth and breadth of feature information in underwater small datasets. Our methods are seamlessly designed for integration into existing networks, offering plug-and-play functionality with substantial performance enhancements. We have conducted extensive experiments to validate the efficacy of our proposed techniques, and the results showcase their state-of-the-art performance. MFCAM improves the mAP by 16.9% in the KLSG dataset and 15.5% in the SCTD dataset. The mAP of D2FPN was improved by 8.4% in the KLSG dataset and by 9.8% in the SCTD dataset. We will make our code and models publicly available at https://dagshub.com/estrellaww00/D2MFNet.

In order to study the acoustic emission characteristics of sandstone under the action of the high temperature-water cooling cycle, the RMT-150B electro-hydraulic servo rock test system and the DS-5 acoustic emission detection and analysis system were used to conduct a single analysis of the sandstone after the high temperature-water cooling cycle. Experimental study on acoustic emission characteristics under axial compression, analyzing the deformation, strength and acoustic emission characteristics of sandstone under different temperatures and cycles. The results of the study show that the high temperature-water cooling action causes changes in the physical properties of the sandstone. The expansion rate of the rock sample decreases first and then increases when the temperature rises, and the strength first increases and then decreases. The number of cycles has little effect on the physical properties of the rock sample; sandstone acoustic emission ringing count increases with the increase of temperature and cycle times, acoustic emission activities become more frequent with the loading process; with the increase of cycle times and temperature, acoustic emission ringing counts and accumulative acoustic emission energy appear earlier The rock sample enters the elastic deformation stage ahead of schedule, the yielding period increases, and the rock sample presents a trend of transition from brittle failure to ductile failure; the ringing count and cumulative energy increase with the increase in temperature and cycle times, and the high-energy ringing count and cumulative energy increase. The simultaneous sharp increase of the rock sample is the harbinger of the failure and instability of the rock sample.

In this study, we de novo assembled whole genomes of two small body-sized West Pacific sciaenids (Larimichthys polyactis and Collichthys lucidus) and compared them with published genome data of two closely-related, large body-sized species (Larimichthys crocea and Miichthys miiuy) and one distantly-related, large body-sized outgroup species (Dicentrarchus labrax). The phylogeny constructed using 7,403 single-copy orthologs shared among the five species indicated that L. crocea and L. polyactis diverged about 42 MYA. The two sibling taxa are more closely-related to C. lucidus than M. miiuy. We further identified four growth-related genes (CDHR2, PGC, PTN and PDGFA) that host five diagnostic amino acid variants on body size traits in the fishes, splitting small-body sized L. polyactis and C. lucidus from large-body sized L. crocea, M. miiuy and D. labrax. The results provide new genomic resources and guidelines to facilitate future endeavors in studying functional genomics and developing selective breeding programs for desirable growth traits in sciaenids.

This paper considers the Hermitian solutions of a new system of commutative quaternion matrix equations, we establish both necessary and sufficient conditions for the existence of solutions. Furthermore, we derive an explicit general expression when it is solvable. To illustrate our main findings, we present two numerical algorithms and examples in this paper.

Nowadays, the world's refractory gold ore production accounts for about 30% of the world's total gold, such gold concentrate leaching rate is low, seriously limiting the efficient use of gold resources. The alkaline preoxidation process can improve the leaching rate of this kind of gold deposit, and has a good development and application prospect. So, it is of great significance to study the oxidation and dissolution behavior of pyrite in alka-line environment. In this paper, the oxidation process of gold-bearing pyrite in alkaline electrolyte was studied by electrochemical techniques, and the oxidation products of pyrite electrode in alkaline solution were characterized by XPS，SEM and other analytical methods. The results show that the optimum pH for pyrite electrochemical oxidation dissolution is about 12, and oxidation potential of pyrite should be above 0.8 V. In that proces of alkaline oxidation dissolution of pyrite, part of S element enters the electrolyte in the form of Sx2-, S2O32-, SO32-and SO42-, and a small amount of S element is adsorbed on the surface of the electrode in the form of S0 and becomes a part of the passive layer. Fe element is adsorbed on the surface of electrode in the form of Fe(OH)2, Fe2O3 and Fe2(SO4)3, which becomes the main component of passivation layer. This study provides a theoretical basis and reference data for the chemical preoxidation treatment of sulfide ores.

We investigate and discuss in detail the structure of the restricted singular value decomposition for a tensor triplet under t-product (T-RSVD). The algorithm is provided with a numerical example illustrating the main result. For applications, we consider color image watermarking processing with T-RSVD.

Wearable assistant devices play an important role in daily life for people with disabilities. Those who are hearing impaired may face dangers while walking or driving on the road. The major danger is their inability to hear warning sounds from cars or ambulances. Thus, the goal of this study is to develop a wearable assistant device for the hearing impaired to recognize emergency vehicle sirens on the road using edge computing. An EfficientNet-based fuzzy rank-based ensemble model was proposed to classify seven audio sounds, including human vocalizations and emergency vehicle sirens. This model was embedded in an Arduino Nano 33 BLE Sense development board. The audio files were respectively obtained from the CREMA-D dataset and Large Scale Audio dataset of emergency vehicle sirens on the road, with a total number of 8756 files. The seven audio sounds included neutral vocalization, anger vocalization, fear vocalization, happy vocalization, car horn sound, siren sound, and ambulance siren sound. The audio signal was converted into a spectrogram by the short-time Fourier transform as the feature. When one of the car horns, sirens, or ambulance sirens was detected, the wearable assistant device presented alarms through vibration and messages on the OLED panel. The performances of the EfficientNet-based fuzzy rank-based ensemble model in offline computing achieved an accuracy of 97.1%, precision of 97.79%, sensitivity of 96.8%, and specificity of 97.04%. In edge computing, the results were an accuracy of 95.2%, precision of 93.2%, sensitivity of 95.3%, and specificity of 95.1%. Thus, the proposed wearable assistant device has the potential benefit of helping the hearing impaired avoid traffic accidents.

SARS-CoV-2 causes severe pneumonia epidemics and probably originated in horseshoe bats, but the intermediate host is unknown. The interaction of SARS-CoV-2 spike protein and its acceptor protein ACE2 is an important issue in determining viral host range and cross-species infection, while the binding capacity of Spike protein to ACE2 of different species is unknown. Here, we used the atomic structure model of SARS-CoV-2 and human ACE2 to assess the receptor utilization capacity of ACE2s from different species including cats, chimpanzees, dogs, cattles. Our results show, domestic cats (Felis catusc) and dogs (Canis lupus familiaris) are more susceptible to infection by SARS-CoV-2 and that they can efficiently transmit the virus to previously uninfected animals that are housed with them. Especially, cats could be a choice of animal model for screening antiviral drugs or vaccine candidates against SARS-CoV-2.

Current COVID-19 vaccines can effectively reduce disease severity and hospitalisation; however, they are not considerably effective in preventing infection and transmission. In this context, mucosal vaccines are pertinent to prevent SARS-CoV-2 infection and spread. In this study, we generated a replication-competent recombinant chimeric influenza A virus (IAV) expressing the receptor-binding domain (RBD) of SARS-CoV-2 prototype in the C-terminus of the neuraminidase (NA) of A/Puerto Rico/08/1934 H1N1 (PR8). The remaining seven segments from A/WSN/1933 H1N1 (WSN) were named PR8NARBD/WSN. We observed that the recombinant virus with the WSN backbone demonstrated improved expression of NA and RBD. A single intranasal dose of PR8NARBD/WSN in mice generated robust mucosal immunity, neutralising antibodies, cellular immunity, and tissue-resident memory T cells specific to SARS-CoV-2 and IAV. Importantly, immunisation with PR8NARBD/WSN viruses effectively protected mice against lethal challenges with H1N1, H3N2 IAV, and SARS-CoV-2 Beta variant and significantly reduced lung viral loads. Overall, our research demonstrates the promising potential of PR8NARBD/WSN as an attractive vaccine against emerging SARS-CoV-2 variants and influenza A virus infections.

Background: Clinical trails have revealed that patients with depression generally accompanied with learning and memory impairment, which critically impact on individual’s health and development. Danggui-Shaoyao-San (DSS), a famous Chinese complex prescription, significantly overcame depression and relieved cognitive disorder based on previous research and publication. However, its effectsand potential mechanism against chronic restraint stress (CRS) remained unknown. Methods: CRS animal model was established and mice were divided to six groups while they were oral administrated with Danggui-Shaoyao-San at doses of 1.25, 2.5 and 5 g/kg for 14 days. Emotional and cognitive performances were detected by behavior tests, meanwhile neural plasticity and its molecular mechanism were examined by Dil staining, western blot and immunofluorescence. Results: DSS treatment dose-dependently improved locomotion ability in open filed test, overcame depression behavior in forced swimming test and elevated plus maze test, enhanced learning and memory ability in Morris water maze test. CRS decreased number of total spines and mushroom spines, while DSS treatment dose-dependently restored these by Dil staining. Expression of BDNF and GluR1 were significantly down-regulated in CRS group, which were significantly normalized by DSS. Conclusions: DSS treatment dose-dependently reversed CRS-induced cognitive impairments by inducing structural remodeling of neurons.