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The fish gut microbiome is well known for its role in degrading nutrients to improve the host's digestion and absorption efficiency. In this study, we focused on the core physiological adaptability during the various reproductive stages of the black Amur bream (Megalobrama terminalis) to explore the interaction mechanisms among the fish host gut mucosal structure, gut enzyme activity, and gut microbial metabolism in the course of the host's reproductive cycle. Our findings showed that M. terminalis exhibited locomotion metabolic type (aids in sporting) in the reproductive stage, and a change to visceral metabolic type (aids in digestion) during non-reproductive and post-reproductive stage phases. The impact of metabolic type selection and energy demand during various reproductive stages on fish nutrition strategy and digestive function was substantial. Our resulted showed that mitochondria in intestinal epithelial cells of reproductive M. terminalis appeared autophagy phenomenon, and the digestive enzyme activities in the intestines of reproductive M. terminalis were lower than those in the non-reproductive and post-reproductive individuals. Moreover, these differences in nutrition strategy have a prominent impact on the gut microbiome of reproductive M. terminalis, compared to non-reproductive and post-reproductive samples. Our findings showed that reproductive females had lower levels of alpha diversity compared to non-reproductive and post-reproductive females. Our results also showed a greater functional variety and an increase in functional genes related to carbohydrate, lipid, amino acid, cofactors, and vitamin metabolic pathways in the NRS and PRS group. It is noteworthy that an enrichment of genes encoding putative enzymes implicated in the metabolism of taurine and hypotaurine was observed in the RS samples. Our findings illustrated that the stability and resilience of the gut bacterial community could be shaped in the wild fish host–microbiome interactions during reproductive life history. [ABSTRACT FROM AUTHOR]

The effective and comprehensive utilization of forest resources has become the theme of the global "dual-carbon strategy". Forestry restructured wood is a kind of wood-based panel made of wood-based fiber composite material by high-temperature and high-pressure restructuring–molding, and has become an important material in the field of construction, furniture manufacturing, as well as derivative processing for its excellent physical and mechanical properties, decorative properties, and processing performance. Taking Medium Density Fiberboard (MDF) as the recombinant material as the research object, an event-triggered synergetic control mechanism based on interventional three-way decision making is proposed for the viscoelastic multi-field coupling-distributed agile control of the "fixed thickness section" in the MDF continuous flat-pressing process, where some typical quality control problems of complex plate shape deviations including thickness, slope, depression, and bump tend to occur. Firstly, the idea of constructing the industrial event information of continuous hot pressing based on information granulation is proposed, and the information granulation model of the viscoelastic plate shape process mechanism is established by combining the multi-field coupling effect. Secondly, an FMEA-based cyber granular method for diagnosing and controlling the plate thickness diagnosis and control failure information expression of continuous flat pressing is proposed for the problems of plate thickness control failure and plate thickness deviation defect elimination that are prone to occur in the continuous flat-pressing process. The precise control of the plate thickness in the production process is realized based on event-triggered control to achieve the intelligent identification and processing of the various types of faults. The application test is conducted in the international mainstream production line of a certain type of continuous hot-pressing equipment for the production of 18 mm plate thickness; the synergistic effect is basically synchronized after 3 s, the control accuracy reaches 30%, and the average value of the internal bond strength is 1.40, which ensures the integrity of the slab. Practical tests show that the method in the actual production is feasible and effective, with detection and control accuracy of up to ±0.05 mm, indicating that in the production of E0- and E1-level products, the rate of superior products can reach more than 95%. [ABSTRACT FROM AUTHOR]

Fish dietary niche is a core focus, and it reflects the diversity of resources, habitats, or environments occupied by a species. However, whether geographic segregation among different populations triggers dietary diversification and concomitant fish niche shift remains unknown. In the present study, we selected the Black Amur bream (Megalobrama terminalis) is a migratory fish species that plays an important role in the material transfer and energy cycling of river ecosystems, inhabiting southern China drainage with multiple geographic populations. Here, we utilized the combined analyses of 18S rDNA high‐throughput sequencing in fish gut contents and fatty acid (FA) in muscle tissues to evaluate potential spatial patterns of habitat and resource use for M. terminalis in three rivers of southern China. Our results showed that prey items of the Xijiang (XR) population (Pearl River) exhibited the highest species diversity and richness among the three geographic populations. Moreover, diet composition of M. terminalis was affected by spatial differences associated with geographic segregation. Analyses of FA biomarkers indicated that the highest levels of C16:0, C18:3n‐3, and C18:2n‐6c were found in Wanquan (WS) population (Wanquan River). The XR population exhibited a distinct FA profile characterized by higher amounts of arachidonic acid (ARA) and docosahexaenoic acid (DHA). The Moyang (MY) population (Moyang River) acted as the linkage between WS and XR populations and consisted of middle levels of saturated FAs (SFAs) and polyunsaturated FAs (PUFAs). The XR population displayed a greater FA niche width compared with WS population. Furthermore, we observed a close positive relationship between the niche width and α‐diversity indices of dietary resources for FA proflies. Our study provides valued information to develop different conservation strategies among different populations and improve fisheries management for M. terminalis and other endemic species in local rivers. [ABSTRACT FROM AUTHOR]

In this paper, a new gradient-based iterative algorithm is proposed to solve the coupled Lyapunov matrix equations associated with continuous-time Markovian jump linear systems. A necessary and sufficient condition is established for the proposed gradient-based iterative algorithm to be convergent. In addition, the optimal value of the tunable parameter achieving the fastest convergence rate of the proposed algorithm is given explicitly. Finally, some numerical simulations are given to validate the obtained theoretical results.

The hybrid space of robots is divided into task space and joint space, with task space focused on trajectory-tracking accuracy, while joint space considers dynamic responsiveness and synchronization. Therefore, the robot-motion control systems need to effectively integrate both aspects, ensuring precision in task trajectory while promptly responding to unforeseen environmental events. Hence, this paper proposes an online trajectory-generation method for robots in both joint and task spaces. In task space, a planning approach is presented for high-precision NURBS curves. The global NURBS curve is segmented into several rational Bezier curves, establishing local coordinate systems for control points. This ensures that all local control points meet the chord error constraint, guaranteeing trajectory accuracy. To address the feed rate dynamic planning issue for segmented curves, an improved online S-shape feed-rate scheduling framework is introduced. This framework dynamically adjusts the current execution speed to meet task requirements. In joint space, an offline velocity planning based on a time synchronization scheme and a multi-dimensional synchronization technique based on the principle of spatial-coordinate system projection are proposed. Building upon the offline scheme, it allows for the modification of the target state for any sub-dimension during the motion process, with the remaining dimensions adapting accordingly. Simulation and experimentation demonstrate that the two proposed online trajectory generations for robot motion spaces, while ensuring task trajectory accuracy, effectively handle external unexpected events. They ensure joint synchronization and smoothness, carrying significant practical implications and application value for the stability of robot systems. [ABSTRACT FROM AUTHOR]

The bZIP (basic leucine zipper) transcription factors have been identified as key regulators of plant responses to drought stress, which limits plant growth and yield. Overexpression of bZIP genes has shown potential in enhancing drought tolerance in various plant species. However, the constrained types of individual studies and inconsistencies among experimental approaches has resulted in a lack of statistical significance and limited the extrapolation of bZIP transcription factor overexpression for plant improvement. We conducted a meta-analysis to evaluate ten measured parameters of drought tolerance in bZIP transcription factor-expressing plants as well as moderators affecting the performance of transgenic plants. The results showed that seven parameters, including survival rate as well as the content of regulatory substances (proline accumulation, H2O2 concentration, CAT activity, POD activity, SOD activity and MDA accumulation), were most affected while the impact on physiological status indicators is not significant. In addition, donor/recipient species, treatment medium, duration and methods of simulating drought stress all significantly impacted the degree of drought stress tolerance in plants to some extent among the considered moderators. The findings underscore the potential of bZIP transcription factors as key targets for genetic engineering approaches aimed at improving plant resilience to water scarcity. [ABSTRACT FROM AUTHOR]

The three-dimensional reconstruction of forest ecological environment by low-altitude remote sensing photography from Unmanned Aerial Vehicles (UAVs) provides a powerful basis for the fine surveying of forest resources and forest management. A stereo vision system, D-SLAM, is proposed to realize simultaneous localization and dense mapping for UAVs in complex forest ecological environments. The system takes binocular images as input and 3D dense maps as target outputs, while the 3D sparse maps and the camera poses can be obtained. The tracking thread utilizes temporal clue to match sparse map points for zero-drift localization. The relative motion amount and data association between frames are used as constraints for new keyframes selection, and the binocular image spatial clue compensation strategy is proposed to increase the robustness of the algorithm tracking. The dense mapping thread uses Linear Attention Network (LANet) to predict reliable disparity maps in ill-posed regions, which are transformed to depth maps for constructing dense point cloud maps. Evaluations of three datasets, EuRoC, KITTI and Forest, show that the proposed system can run at 30 ordinary frames and 3 keyframes per second with Forest, with a high localization accuracy of several centimeters for Root Mean Squared Absolute Trajectory Error (RMS ATE) on EuRoC and a Relative Root Mean Squared Error (RMSE) with two average values of 0.64 and 0.2 for trel and Rrel with KITTI, outperforming most mainstream models in terms of tracking accuracy and robustness. Moreover, the advantage of dense mapping compensates for the shortcomings of sparse mapping in most Smultaneous Localization and Mapping (SLAM) systems and the proposed system meets the requirements of real-time localization and dense mapping in the complex ecological environment of forests. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has been highly appreciated by several nations and societies as a worldwide strategic developing sector. However, IoT security is seriously threatened by anomalous traffic in the IoT. Therefore, creating a detection model that can recognize such aberrant traffic is essential to ensuring the overall security of the IoT. We outline the main approaches that are used today to detect anomalous network traffic and suggest a Resnet detection model based on fused one-dimensional convolution (Conv1D) for this purpose. Our method combines one-dimensional convolution and a Resnet network to create a new network model. This network model improves the residual block by including Conv1D and Conv2D layers for two-dimensional convolution. This change enhances the model's ability to identify aberrant traffic by enabling the network to extract feature information from one-dimensional linearity and two-dimensional space. The CIC IoT Dataset from the Canadian Institute for Cybersecurity Research was used to assess the effectiveness of the proposed enhanced residual network technique. The outcomes demonstrate that the algorithm performs better at identifying aberrant traffic in the IoT than the original residual neural network. The accuracy achieved can be as high as 99.9%. [ABSTRACT FROM AUTHOR]

Simple Summary: The Nile tilapia (Oreochromis niloticus) (NT) is an aggressive and omnivorous species that competes with native fishes for food resources, and it has successfully invaded much of the Pearl River basin in China. Intensive research has focused on the gut microbiota of Nile tilapia in artificial culture. However, differences in gut microbes between invasive Nile tilapia and indigenous fish are relatively less well characterized. In the present study, we chose the black Amur bream (Megalobrama terminalis) as a native omnivorous fish that shared a common habitat and partially overlapped resource usage with Nile tilapia. Here, we investigated the gut microbiomes of invasive Nile tilapia and indigenous black Amur bream (BA) in the same river section using high-throughput 16S rRNA gene sequencing. The results indicated that the gut microbiome of NT had several special characteristics, e.g., higher alpha diversity and greater niche breadth, compared with the bream. Thus, the aim of the present study was to investigate the role of gut microbiomes between an indigenous fish (black Amur bream) and invasive Nile tilapia from the low region of the Pearl River basin to better understand the microbial complexity and diversity of their gut microbiota. The gut microbiome is thought to play vital roles in host fitness and local adaptation to new environments, thereby facilitating the invasion of the host species. The Nile tilapia (Oreochromis niloticus) (NT) is an aggressive and omnivorous species that competes with native fishes for food resources, and it has successfully invaded much of the Pearl River basin in China. Here, we investigated the gut microbiomes of invasive Nile tilapia and indigenous black Amur bream (BA) in the same river section using high-throughput 16S rRNA gene sequencing. The results indicated that the gut microbiome of NT had several special characteristics, e.g., higher alpha diversity and greater niche breadth, compared with the bream. The gut microbiota of the small size of Nile tilapia (NTS) and small size of black Amur bream (BAS) groups were dominated by Proteobacteria, while those of the NTS and large size of Nile tilapia (NTL) and BAS and large size of black Amur bream (BAL). BAL and NTL were characterized by Firmicutes and Fusobacteriota, respectively. We found that Pseudomonas, Cetobacterium, Ralstonia, and Romboutsia were biomarkers of the NTS, NTL, BAS, and BAL groups, respectively. Moreover, the results collectively suggested that the clustering coefficients of BAL and NTL networks were greater than those of BAS and NTS networks, and BAS had the smallest network among the four groups. Positive interactions between two ASVs dominated the BAS, NTS, and NTL networks, while the proportion of negative interactions between two ASVs in the BAL network was remarkably increased. Low levels of interspecies competition in the NT gut microbiome would contribute to high diversity in the dietary niches and would also benefit the survival and local adaptation of the host. Our results identified specific biomarkers of gut microbial species in invasive Nile tilapia and provided useful information concerning how to monitor and manage invasive Nile tilapia populations. [ABSTRACT FROM AUTHOR]

This study aimed to explore the gill developmental mechanism of the high mortality rate of Paramisgurnus dabryanus larvae in the early life-history process. Based on histological observations with a optical microscope, we studied the ontogeny of the gill of P. dabryanus. The result indicated that external gills first appeared 12 h after hatching. The number of external branchial filaments greatly increased at 2 d after hatching (DAH). The internal branchial filament primordial was formed in the oropharyngeal cavity at 5 DAH. At 9 DAH, none of external branchial filaments were observed outside, but the fish operculum was completed covered. From 15 DAH forward, the filaments and lamellae of gills increased in number and length prominently, and the gills of the larvae were similar to those of juvenile fish. The specific activities of Na+/K+-ATPase steadily increased from 0 to 12 DAH and peaked at 15 DAH. After 15 DAH, the specific activities of Na+/K+-ATPase slightly decreased and then tended to remain steadily stable until the end of the experiment. There were abundant gill lamellae on the gill filaments at 40 DAH. The sensitive period of the development of larval and juvenile P. dabryanus was from 6 to 15 DAH. Our results provide information that may be useful for improving our understanding of the life history and ecology of loaches. [ABSTRACT FROM AUTHOR]

Abiotic stress is one of the environmental conditions that effects plant survival and growth. As a vital model plant and papermaking raw material, it is very important to identify the differentially expressed genes of Populus trichocarpa Torr. & A.Gray ex Hook under abiotic stress in order to cultivate stress-tolerant plants. We analyzed the whole transcription spectrum and potential differentially expressed genes of 54 groups of roots and stem-xylem sequencing sample data under cold, drought, heat and salt stress for different durations. Gene Ontology (GO) enrichment analysis showed that molecular function played a stronger role in stems' response to abiotic stress, and genes in roots could barely respond to both cold stress and heat stress. Degree and betweenness centrality were used to identify transcription factors. It was considered that intermediate centrality is more suitable to determine whether the transcription factor is a hub gene. DNA binding was the biggest enrichment, while transcription factors responded to the abiotic stress. The multipronged approach identified in the roots and stems provides a genetic basis for resistance and more targeted genetic improvement of Populus trichocarpa. The comparison of two centralities can more effectively analyze the importance of complex gene network nodes in plants under corresponding abiotic stresses. [ABSTRACT FROM AUTHOR]

With the development of science and technology, it has had a great impact on the manufacturing industry. The manufacturing industry has higher and higher requirements for industrial manipulators, and the expectations for the quality and function of the industrial manipulators in the manufacturing industry are increasing day by day. At the same time, the requirements for the working accuracy of the manipulators are also getting higher and higher. In this paper, a new method is proposed. An error compensation and calibration algorithm based on parameter separation and integration of the standard DH model (SDH) is used to construct the kinematic model of the manipulator. The six groups of structural parameters of the six-axis manipulator are calibrated once every two groups, thereby eliminating the influence of the singular value of the position of the manipulator. Finally, the feasibility of this scheme is verified by simulation experiments, the accuracy is ensured, and the expected purpose is achieved. Because the method in this paper has high requirements on the posture of the manipulator, it reduces the overall calibration calculation and saves time, which has a certain effect on the improvement of the industrial manipulator in the manufacturing industry. [ABSTRACT FROM AUTHOR]

With the rapid development of integrated circuit technology, GPU computing capabilities continue to improve. Due to the continuous improvement and improvement of GPU programming capabilities, functions, and performance, GPUs have been widely used in the field of high-tech general-purpose computers. This article is aimed at studying the optimization of GPU scheduling algorithm based on AI technology. Through a combination of theoretical analysis and simulation experiments, the concepts of artificial intelligence technology and GPU scheduling are explained, and the impact of GPU architecture and GPGPU load on the energy efficiency of GPGPU is explained. On the basis of comprehensive analysis of GPU cluster characteristics, a new GA-TP scheduling algorithm based on genetic algorithm was designed, and based on the energy efficiency of the cluster, a simulation verification platform was built for the accuracy of simulation. Experimental results show that the acceleration rate of the GA-TP algorithm is significantly lower than that of the HEFT algorithm, the average acceleration rate is reduced by nearly 25%, and the scheduling efficiency of the GA-TP algorithm is higher. [ABSTRACT FROM AUTHOR]

Under the background of urban-rural integration, the frequent flow of urban and rural elements has promoted the close connection between rural transformation (RT) and construction land transition (CLT). How is CLT related to RT? By taking the plain area Linqing County in China as the study area, basing the study on the RT and CLT coupling framework of relevance theory, building an RT and CLT evaluation index system, using the multi-factor evaluation method for the evaluation of RT and CLT from 2010 to 2018, and using the grey correlation model to measure the RT and CLT coupling relationship, the results showed that the level of RT was from 0.04 to 97.42, and the level of CLT was from 14.89 to 82.47, showing the trends of gradual increase and fluctuating increase, respectively. Taking 2013 and 2016 as the time point, RT could be divided into the initial stage, growth stage I, and growth stage II, corresponding to the initial stage, high growth stage, and stable development stage of CLT. The coupling degree between the two was in the range of 0.6–0.8 and was in the stage of a medium to high coupling degree. The correlation degree between the subsystem of RT and CLT was over 0.65. In the subsystem of CLT, the correlation degrees between quantitative structure transition and RT and efficiency transition and RT were both lower than 0.65, which were relatively low. Controlling the scale of construction land and taking efficiency transition are the effective methods to guide the deep exploration of potential and are the inevitable way to strengthen the relationship between CLT and RT and promote urban-rural integration development. [ABSTRACT FROM AUTHOR]

The increasing demand for forestry resources is driving the need for smarter systems capable of saving and protecting forests that can optimize agile forestry production. This study uses the continuous hot-pressing process of wooden medium-density fiberboard (MDF) to investigate the possibility of automatic quality control of the continuous flat pressing process. For this purpose, conceptual digital twin modeling for mechanism and sequence parameter control was conducted based on the cellular automata (CA) theory. A distributed coordination mode framework was constructed, and a craft control programming method was proposed for the quality control of MDF continuous flat pressing. Based on the MDF continuous flat press craft mechanism and control standards, a framework of five distributed flat press cooperative control mode elements for the cylinder array of the continuous panel system (CPS) was defined. To satisfy the distributed distance servo and pressure servo demands of the multi-stage hot pressing craft design, five kinds of synergy collaborative control modes of multiple rack groups were constructed using mode elements: For the four types of typical deviations in slab production, i.e., thickness, slope, depression, and bulge, a multi-zone mutual cooperative mode craft control sequence was programmed. According to the type and intensity of real-time deviation, the corresponding regulation sequence was applied. This effectively counteracts the deviation caused by the uncertainty interference due to the multi-field coupling effect in actual production. The application tests demonstrate that the adjustment and response time of the continuous flat press were greatly improved, and the quality superiority rate is controlled above 95%, thereby confirming the effectiveness of the control strategy. [ABSTRACT FROM AUTHOR]

Gut microbiome is considered as a critical role in host digestion and metabolic homeostasis. Nevertheless, the lack of knowledge concerning how the host-associated gut microbiome underpins the host metabolic capability and regulates digestive functions hinders the exploration of gut microbiome variation in diverse geographic population. In the present study, we selected the black Amur bream (Megalobrama terminalis) that inhabits southern China drainage with multiple geographic populations and relatively high digestive plasticity as a candidate to explore the potential effects of genetic variation and environmental discrepancy on fish gut microbiome. Here, high-throughput 16S rRNA gene sequencing was utilized to decipher the distinct composition and diversity of the entire gut microbiota in wild M. terminalis distributed throughout southern China. The results indicated that mainland (MY and XR) populations exhibited a higher alpha diversity than that of the Hainan Island (WS) population. Moreover, a clear taxon shift influenced by water temperature, salinity (SA), and gonadosomatic index (GSI) in the course of seasonal variation was observed in the gut bacterial community. Furthermore, geographic isolation and seasonal variation significantly impacted amino acid, lipid, and carbohydrate metabolism of the fish gut microbiome. Specifically, each geographic population that displayed its own unique regulation pattern of gut microbiome was recognized as a specific digestion strategy to enhance adaptive capability in the resident environment. Consequently, this discovery suggested that long-term geographic isolation leads to variant environmental factors and genotypes, which made a synergetic effect on the diversity of the gut microbiome in wild M. terminalis. In addition, the findings provide effective information for further exploring ecological fitness countermeasures in the fish population. [ABSTRACT FROM AUTHOR]

The combination of wireless sensor networks and radio technology can form a new type of communication network. The emergence of wireless sensor networks has effectively solved the problems existing in radio technology, but traditional wireless sensor networks and radio technology networks cannot be directly applied to wireless sensors. On this basis, this paper studies the remote sensing of soil nutrient variability in agricultural land using wireless sensors. Due to traditional farmland management and agricultural systems, farmland soil nutrient variability has led to polarization: fertile soil has excess nutrients, reducing the use rate of chemical fertilizers and polluting high-quality farmland. Traditional farming methods can no longer meet the requirements, and modern technology must be used to comprehensively understand the spatiotemporal variability of soil nutrients during plant growth. Remote sensing technology has the advantages of accuracy, speed, economy, and regular monitoring. It provides new ideas and technical guarantees for soil quality evaluation in land development and consolidation projects. This paper also studies the use of statistical quantitative evaluation technology to carry out multidimensional statistical quantification of soil protection function evaluation at a given location. Finally, wireless sensor networks are used to analyze the relationship between several natural factors and quantitative estimation of soil protection. Based on wireless sensor technology, this paper studies the variability of farmland soil nutrients and statistical quantitative evaluation, hoping to lay a foundation for the development of agriculture and statistics. [ABSTRACT FROM AUTHOR]

The Japanese Eel Anguilla japonica is an important migratory fish with great commercial and conservational significance in Asia. The Pearl River in southern China provides important natural growing and rearing grounds for glass eel recruits, but there is very limited information on their population characteristics. We studied the resource status and habitat preferences of Japanese Eels in the Pearl River from 2015 to 2018. In total, 181 Japanese Eels (89 males and 92 females) were collected during the study period. In terms of frequency of occurrence, Japanese Eels contributed less than 1% of the total number of collected fish specimens. Most of the eels were between 255 and 600 mm TL. Redundancy analysis indicated that eels were mainly distributed in the downstream portion of the river and preferred more complex habitats characterized by larger river fractals, higher coefficients of fluvial facies, and greater river widths. Adults preferred to inhabit areas with larger fractals and river widths, whereas juveniles inhabited areas with higher coefficients of fluvial facies. Young‐of‐the‐year eels preferred habitats near the estuary and with high water salinity. Dams have blocked the eels' migration routes and affected their spatial distribution, in turn leading to a reduction in the population. This study was part of a long‐term investigation of wild Japanese Eels in the Pearl River, and the results showed that the Japanese Eel resource in southern China is extremely scarce and its conservation is greatly needed. [ABSTRACT FROM AUTHOR]

Summary: With the development of smart Internet of things devices, intelligent applications are expected to lead further innovation in smart city. However, although cloud computing infrastructure can be used to meet traditional challenges, the scheduling model for new big data intelligent application has still not matured. In this work, we proposed a two‐stage scheduling framework for smart city intelligent application. In the first stage, we propose a virtual machine selection algorithm for edge computing to enhance relative migration benefits. The algorithm defines the invalid virtual machine migration and relative migration benefits from the change in the overall computing resources of the cloud data center after the virtual machine migration. In the second stage, we proposed an energy efficient and resource‐constrained scheduling framework for edge computing. The historical data of the cloud and edge computing workload of the computing node are processed in a sliding window manner, and the median absolute deviation of the historical data is used as the base of the physical reserved resource constraint when the base also changes as the workload changes. The experimental results show that energy‐efficient and resource‐constrained can make the computer resource provide high‐quality services for users in a low‐energy state. [ABSTRACT FROM AUTHOR]

Black Amur bream (Megalobrama terminalis), a dominant species, resides in the Pearl River basin, known for its high plasticity in digestive ability. During spawning season, M. terminalis individuals with large body size and high fertility undergo a spawn migratory phase, while other smaller individuals prefer to settlement over migration. It is well known that gut microbial community often underpins the metabolic capability and regulates a wide variety of important functions in fish. However, little was known about how the gut microbiomes affect fish breeding migration. To investigate the variations in the gut microbiome of M. terminalis during the migration, we used high‐throughput 16S rRNA gene sequencing to reveal the distinct composition and diversity of the whole gut microbiome of migrated and nonmigrated population during period of peak reproduction, respectively. Our results indicated that nonmigrated population in estuary had a higher alpha diversity than that of migrated population in main stem. Additionally, an obvious abundant taxa shift between the gut microbiota community of nonmigrated and migrated M. terminalis was also observed. Change of dominant gut taxa from nonmigrated to migrated population was thought to be closely related to their degradation enzymes. Our results suggested that amino acid metabolism and lipid metabolism in migrated population were higher than that in nonmigrated population, providing a line of evidence for that M. terminalis change from partial herbivorous to partial carnivorous diet during breeding migration. We further concluded that, in order to digest foods of higher nutrition to supply energy to spawning migration, M. terminalis regulate activities of the gut microbiome and degradation enzymes, considered to be a key physiological strategy for reproduction. [ABSTRACT FROM AUTHOR]

With the continuous development of the robot industry, both industrial robots and collaborative robots are developing towards light type and intelligence. The core issue is that how to improve the dynamic control performance of robots and reduce costs. The accurate torque feedback control can be achieved by introducing a joint torque sensor. The disadvantages brought by it are higher cost and the limited performance of the torque sensor. Therefore, on the basis of the traditional current estimated torque, combined with the accurate joint torque data fed back by the torque sensor, a method to estimate the harmonic transmission torque in the joint based on the disturbance observer is proposed, and a joint torque model is constructed. At the same time, the compensation factor is introduced to improve the accuracy of torque estimation. In the method proposed in this paper, the theoretical position and actual position, speed difference and motor current of the dual encoder on the motor side and the link side are used to estimate the harmonic transmission torque through the disturbance observer, and the corresponding coefficient is identified. By calibrating the transmission error compensation term and friction force with the torque sensor, the joint torque estimation model is obtained, and the sensorless joint torque estimation can be realized. This method does not require additional torque error compensation caused by harmonic drive deformation in the controller. Therefore, the torque control method without torque sensor is adopted in batch, which is not affected by the configuration and dynamic parameters of the manipulator. In the experiment, the output data of the joint torque sensor is used for testing and comparison. Through the single joint and redundant robot manipulator integration testing, the effectiveness of the proposed joint torque estimation method is verified. [ABSTRACT FROM AUTHOR]

In order to solve the problems of time-consuming, low-precision, and incomplete image details when extracting soil physical and chemical information, this paper proposes a soil physical and chemical information extraction method based on hyperspectral remote sensing technology. Through graying, filtering, and contrast enhancement of remote sensing image, the extraction model of soil physical and chemical information is established, and the thermal intensity of hyperspectral remote sensing image is adaptively fused. The template matching technology is used to enhance the information of the sand soil hyperspectral remote sensing image. The hyperspectral remote sensing feature is used to extract the image feature, and the brightness component is used to analyze the detail transmission of the image. The simulation results show that the method has high accuracy in extracting physical and chemical information of sand, and the resolution and accuracy of image details are good, which can effectively improve the recognition ability of hyperspectral remote sensing image features of Jerusalem artichoke planting sandy soil. [ABSTRACT FROM AUTHOR]

The function of digestive physiology during ontogenetic development is essential to ensure high survival and growth rates. In order to evaluate the digestive physiological capacity of the black Amur bream (Megalobrama terminalis), changes of morphology and digestive enzyme activity (trypsin, lipase, amylase, pepsin, leucine aminopeptidase and alkaline phosphatase) in larvae were examined from hatching to 40 days after hatching (DAH). Results indicated that fluctuation patterns differed between the total and specific activities of the digestive enzymes. The total activities of these six enzymes gradually increased throughout the fish growth. The specific activity of trypsin peaked at 5 DAH and then decreased dramatically, while it increased remarkably again from 8 to 10 DAH and remained stable level after 20 DAH. Pepsin activity was first examined in M. terminalis at 15 DAH and gradually elevated towards the end of the experiment. The specific activity of lipase displayed obvious peaks at 5 and 20 DAH. For the amylase, its specific activity reached plateau at 4 DAH, underwent sharp decrease, and remained stable after 20 DAH. In addition, we found that the specific activity of alkaline phosphatase raised significantly from hatching to 5 DAH, and tended to keep slight fluctuation after 15 DAH. From the above, we concluded that the specific activities of digestive enzymes in the larvae varied constantly from 3 to 20 DAH and turned relatively stable after 20 DAH. The present study provides effective information that is useful to improve the seedling cultivation and the technology for healthy breeding. [ABSTRACT FROM AUTHOR]

In this paper, a fuzzy failure mode and effects analysis (FMEA) method is proposed by combining fault theory and a failure analysis method. The method addresses the problem of board thickness control failure and the problem of thickness deviation defect blanking, which can occur during continuous hot pressing (CHP) process, which is one of the most important processes in the production of medium-density fiberboard (MDF). The method combines the fault analysis with the Hamming code method and using the Hamming code to calculate and represent the cylinder array of the continuous hot-pressed thickness control execution unit to analyze and process the potential fixed thickness failure modes in MDF hot press production, and then summarizes the decision rules for controlling the board thickness and the level of sheet deviation. By combining the fuzzy FMEA method of the Hamming code and the logical OR operation of the experimental analysis, the method of thickness deviation and recognition control fault information for the CHP of MDF, which is proposed in this paper, permits the increase of the number of error levels, which makes optimization for controller more convenient and improves the efficiency to recognize errors. [ABSTRACT FROM AUTHOR]

We propose a one-layer neural network for solving a class of constrained optimization problems, which is brought forward from the MDF continuous hot-pressing process. The objective function of the optimization problem is the sum of a nonsmooth convex function and a smooth nonconvex pseudoconvex function, and the feasible set consists of two parts, one is a closed convex subset of Rn, and the other is defined by a class of smooth convex functions. By the theories of smoothing techniques, projection, penalty function, and regularization term, the proposed network is modeled by a differential equation, which can be implemented easily. Without any other condition, we prove the global existence of the solutions of the proposed neural network with any initial point in the closed convex subset. We show that any accumulation point of the solutions of the proposed neural network is not only a feasible point, but also an optimal solution of the considered optimization problem though the objective function is not convex. Numerical experiments on the MDF hot-pressing process including the model building and parameter optimization are tested based on the real data set, which indicate the good performance of the proposed neural network in applications. [ABSTRACT FROM AUTHOR]

Under the background of urban–rural integration, balanced development between urban and rural areas has been increasingly advocated. Rural population loss (RPL) is not only due to the laws of social and economic development but also the comprehensive action of natural, social, and economic factors. Taking 774 administrative villages in Laiyang County, which is in a hilly region, as our research area, we comprehensively used spatial analysis and geographic detectors to explore the spatial characteristics and driving factors of RPL, which was significantly correlated with rural planning. The research demonstrated that: (1) The rural population in Laiyang County generally had a low level of RPL (1.9%), but each village varied greatly. The village with the greatest RPL had a rate of 56%. The RPL between urban and rural areas, towns and streets, and villages and villages were unbalanced, and rural population flow mainly occurred between urban and rural areas. (2) RPL in Laiyang County was generally low in the central urban area and high in the northern and southern areas. Population loss presents agglomeration globally and high–low agglomeration locally. (3) The distance from village to county, elevation, cultivated land quantity, collective economic income, village area, and ecological service value were the key factors influencing RPL in Laiyang County. When comparing the dominant factors, the interaction between collective income and elevation was the strongest. Exploring the spatial characteristics and influencing factors of RPL provided us with ideas for the classified promotion of rural revitalization, preparation of rural development planning, and promotion of the integrated development of urban and rural areas. [ABSTRACT FROM AUTHOR]

Pseudocrossocheilus tridentris is an endemic fish species in the upper Pearl River with limited published genetic information. In the current study, the complete mitochondrial genome of P. tridentris was determined using next generation sequencing, which was 16,606 base pairs (bp) in length and 91.65% identical to its closest relative with a genome of P. bamaensis. Phylogenetic analysis showed that P. tridentris had a close relationship with its congener P. bamaensis. [ABSTRACT FROM AUTHOR]

The establishment of a comprehensive framework to identify village development types is crucial to formulate plans for rural development and promote rural revitalization. This study proposed a natural–socioeconomic framework to identify the types of villages based on field survey, statistical data, and multi-source remote sensing images. The framework was constructed by combining the two-dimensional natural suitability/restriction evaluation and the four-dimensional socioeconomic development level evaluation. Then, the modified multiplication-weighted summation method and the coupling coordination degree algorithm were employed to identify the villages' development types. A total of 774 villages of the Laiyang County, eastern China were used as the study areas to examine the framework. The results demonstrated the following. (1) There were 243,318 and 151 villages with high, moderate, low natural suitability, and 62 villages with natural restrictions; and 158,366 and 250 villages with high, moderate, and low economic development level, respectively. The distribution characteristic of natural evaluation was "high in the southwest and low in the northeast", and the socioeconomic development level was generally centered on the urban area, which presented a "high–medium–low" circle-layer distribution structure. (2) There were 247 villages with high-level coupling coordination, 464 villages with intermediate coupling coordination, 1 village with low-level coupling coordination, and 62 villages with disordered coupling. (3) Based on the coupling coordination evaluation results, villages in the study area were grouped into five types: urbanization development (31%), construction development (16%), agglomeration linkage development (27%), decrease and improvement development (18%), and relocation and integration development (8%). The framework of villages' development types identification established in this study can enrich the theory of rural geography, and the applied research results can provide a basis for rural revitalization and development planning. [ABSTRACT FROM AUTHOR]

Summary: Length–weight relationships (LWRs) were estimated for six fish species from the Pearl River. The samples were collected using gillnets, castnets and shrimp cages in Guangxi Province between March 2015 to October 2017. Exponent "b" of the LWR equations varied between 2.161 to 3.288, and r2 values varied between 0.932 and 0.968 for the species studied. [ABSTRACT FROM AUTHOR]

Considering the linear motion of particleboards in the production line, the detection of surface defects in particleboards is a major challenge. In this paper, a method based on moving target tracking is proposed for the detection of surface defects in particleboards. To achieve this, the kernel correlation filter (KCF) target tracking algorithm was modified with the median flow algorithm and used to capture the moving targets of surface defects. The defect images were extracted by a Sobel operator, and the defect number, the defect area, and the degree of damage were calculated. The level of surface defect in particleboards was evaluated by fuzzy pattern recognition. Experiments were then carried out to prove the effectiveness and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

The 3D reconstruction of forests provides a strong basis for scientific regulation of tree growth and fine survey of forest resources. Depth estimation is the key to the 3D reconstruction of inter-forest scene, which directly determines the effect of digital stereo reproduction. In order to solve the problem that the existing stereo matching methods lack the ability to use environmental information to find the consistency of ill-posed regions, resulting in poor matching effect in regions with weak texture, occlusion and other inconspicuous features, LANet, a stereo matching network based on Linear-Attention mechanism is proposed, which improves the stereo matching accuracy by effectively utilizing the global and local information of the environment, thereby optimizing the depth estimation effect. An AM attention module including a spatial attention module (SAM) and a channel attention module (CAM) is designed to model the semantic relevance of inter-forest scenes from the spatial and channel dimensions. The linear-attention mechanism proposed in SAM reduces the overall complexity of Self-Attention from O( n 2 ) to O(n), and selectively aggregates the features of each position by weighted summation of all positions, so as to learn rich contextual relations to capture long-range dependencies. The Self-Attention mechanism used in CAM selectively emphasizes interdependent channel maps by learning the associated features between different channels. A 3D CNN module is optimized to adjust the matching cost volume by combining multiple stacked hourglass networks with intermediate supervision, which further improves the speed of the model while reducing the cost of inferential calculation. The proposed LANet is tested on the SceneFlow dataset with EPE of 0.82 and three-pixel-error of 2.31%, and tested on the Forest dataset with EPE of 0.68 and D1-all of 2.15% both of which outperform some state-of-the-art methods, and the comprehensive performance is very competitive. LANet can obtain high-precision disparity values of the inter-forest scene, which can be converted to obtain depth information, thus providing key data for high-quality 3D reconstruction of the forest., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Liu, Lv and Xing.)

Teleost omnivorous fish that coexist partially sharing resources are likely to modify their gut traits and microbiome as a feedback mechanism between ecological processes and evolution. However, we do not understand how the core gut microbiome supports the metabolic capacity of the host and regulates digestive functions in specialized omnivorous fish gut traits. Therefore, we evaluated the gut microbiome of eight omnivorous fish from a single family (i.e., Cyprinidae) in the current study. We examined the correlation between host phylogeny, diet composition, and intestinal morphological traits related to the intestinal microbiome. The results indicated that cyprinid fish with similar relative gut lengths had considerable gut microbiome similarity. Notably, the SL (short relative gut length) group, as zoobenthos and zooplankton specialists, was abundant in Proteobacteria and was less abundant in Firmicutes than in the ML (medium relative gut length) and LL (long relative gut length) groups. These fish could extract nutrients from aquatic plants and algae. Additionally, we found the relative abundance of Clostridium and Romboutsia to be positively correlated with host relative gut length but negatively correlated with the relative abundance of Cetobacterium , Plesiomonas , Bacteroides , and Lactobacillus , and host-relative gut length. We also show a positive linear relationship between host gut microbiome carbohydrate metabolism and relative gut length, while the amino acid and lipid metabolism of the gut microbiome was negatively correlated with host-relative gut length. In addition, omnivorous species competing for resources improve their ecological adaptability through the specialization of gut length, which is closely related to variation in the synergy of the gut microbiome. Above all, specialized gut microbiota and associated gut morphologies enable fish to variably tolerate resource fluctuation and improve the utilization efficiency of nutrient extraction from challenging food resources., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Li, Li, Li and Zhu.)

This study aims to investigate the effects of TRB3 on the EMT and MAPK signaling pathways in a bleomycin (BLM)-induced pulmonary fibrosis mouse model. TRB3 adenovirus vector with green fluorescent protein (GFP) and TRB3-siRNA adenovirus vector were constructed for overexpression and down-regulation of TRB3, respectively. The pulmonary fibrosis mouse model was induced by bleomycin, and then treated with adenovirus on the next day. The mice were randomly killed at the 7 th (D7), 14 th (D14) and 28 th (D28) day, respectively. The lung tissues were collected for histopathologic observations, hydroxyproline determination, Immunohistochemistry, western blot and RT-qPCR to detect the expression of TRB3 and EMT-related proteins. Overexpression of TRB3 caused more severe pulmonary fibrosis (P<0.05), while downregulation of TRB3 significantly reduced pulmonary fibrosis (P<0.05). The expression of MAPK pathway-related and EMT-related genes and proteins was markedly upregulated by TRB3 overexpression (P<0.05), but prominently downregulated by TRB3-shRNA (P<0.05). In conclusion, exogenous regulation of TRB3 may have effects on bleomycin-induced pulmonary fibrosis in mice., Competing Interests: None., (IJCEP Copyright © 2019.)

As one of the most important applications in peer-to-peer (P2P) networks, the video-on-demand (VoD) system freely supports video cassette recorder (VCR) operation for users. However, the users may experience significant playback delay after frequent VCR operations in the VoD system, which will affect the quality of experience (QoE) of the users. Hence, selecting an appropriate data-prefetching strategy to support better VCR operation is an important approach to improve the QoE. This paper proposes a data-prefetching strategy (DSA) to determine the most suitable anchor interval by considering the playback delay and positioning satisfaction. According to the DSA, we use the multiple-attribute decision-making (MADM) theory to model the selection of intervals of prefetching data blocks (i.e., anchor interval) and the technique for ordering preference by similarity to an ideal solution (TOPSIS) algorithm to solve the MADM. The simulation results show that the DSA strategy obtains higher positioning satisfaction than the existing schemes, which is approximately 60% higher than the anchor points, popular parts of video, and user interests (API)-based method. Moreover, with the increase in network bandwidth, the DSA strategy can minimize the playback delay after VCR operation using relative few extra bandwidths., Competing Interests: The authors declare no conflict of interest.

As a key, yet difficult, issue currently in the quantitative remote sensing analysis of soil, the accurate and stable monitoring of soil salinity content (SSC) in situ should be studied and improved. The purpose of this study is to explore the method of fusing spectra outdoors with spectra indoors and improve the estimation precision of SSC based on near-infrared (NIR) reflectance hyper-spectra. First, samples of saline soil from the Yellow River delta of China were collected and analyzed. We measured three groups of sample spectra using a spectrometer: (1) situ-spectra, measured at sampling points in situ; (2) out-spectra, measured outdoors on air-dried samples; and, (3) lab-spectra, measured in a dark laboratory with the above air-dried samples. Second, four algorithms (multiplicative update, alternating least-squares, sparse affine non-negative matrix factorization (NMF), and gradient projection algorithms) of NMF were used to fuse the situ-spectra or out-spectra with the lab-spectra for the calibration of SSC. Finally, estimation models of SSC were built using the multiple linear regression method based on the first derivatives of the un-fused and fused spectra. The results indicate that using the NMF method to fuse the situ-spectra or out-spectra with the lab-spectra can heighten the correlation between SSC and the outdoor spectra in most wavelength ranges and improve the accuracy of the prediction model. The gradient projection algorithm shows the best performance with fewer variables and highest accuracy of the SSC model based on the NIR spectra., (© The Author(s) 2016.)