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Demodulation and decoding are pivotal for the eLoran system's timing and information transmission capabilities. This paper proposes a novel demodulation algorithm leveraging a multiclass support vector machine (MSVM) for pulse position modulation (PPM) of eLoran signals. Firstly, the existing demodulation method based on envelope phase detection (EPD) technology is reviewed, highlighting its limitations. Secondly, a detailed exposition of the MSVM algorithm is presented, demonstrating its theoretical foundations and comparative advantages over the traditional method and several other methods proposed in this study. Subsequently, through comprehensive experiments, the algorithm parameters are optimized, and the parallel comparison of different demodulation methods is carried out in various complex environments. The test results show that the MSVM algorithm is significantly superior to traditional methods and other kinds of machine learning algorithms in demodulation accuracy and stability, particularly in high-noise and -interference scenarios. This innovative algorithm not only broadens the design approach for eLoran receivers but also fully meets the high-precision timing service requirements of the eLoran system. [ABSTRACT FROM AUTHOR]

To analyze the heat transfer characteristics of oil shale under different in situ pyrolysis methods from a microscopic perspective, a combination of experimental and simulation approaches was employed. Initially, high-temperature in situ pyrolysis experiments on single-fracture oil shale were conducted using high-temperature steam and electrical methods. Subsequently, micro-CT scanning technology was utilized to obtain digital rock cores under different in situ pyrolysis conditions. Finally, these digital rock cores were seamlessly integrated with COMSOL 6.0 to achieve numerical simulations of high-temperature steam convective heating and electrical conductive heating in the in situ state. The relevant conclusions are as follows: Firstly, during the in situ pyrolysis of oil shale with high-temperature steam convective heating, the overall temperature increase is uniform and orderly. Heat is conducted gradually from the pores and fractures to the matrix. The uneven distribution of pores and fractures causes an uneven temperature field, but no localized overheating occurs, which can effectively enhance the pyrolysis efficiency. Secondly, the heat transfer direction in electrical conductive heating is primarily inward along the normal direction of the heat source end face. The closer the section is to the heat source end face, the higher the rate of temperature increase. Within 1 s, the temperature rise at 100 μm (near the heat source end face) is 2.27 times that at 500 μm (near the farthest cross-section from the heat source end face). The heat transfer effect of high-temperature steam convective heating consistently surpasses that of electrical conductive heating. The Tc value initially increases and then decreases as pyrolysis progresses, reaching a maximum of 1.61331 at 0.4 s, but Tc remains greater than 1 throughout. Finally, in the initial stages of pyrolysis, the high-temperature region formed by conductive heating is superior to that of convective heating. However, once the heat carrier fluid flow stabilizes, the volume of the high-temperature region formed by convective heating grows rapidly compared to that of conductive heating. At 1 s, the volume of the high-temperature region formed by convective heating reaches 5.22 times that of the high-temperature region formed by conductive heating. [ABSTRACT FROM AUTHOR]

Real-time high-temperature CT scanning and a rock-mechanics test system were employed to investigate the mechanical properties of oil shale at temperatures from 20 to 600 °C. The results reveal that up to 400 °C, the aperture of fractures initially decreases and then increases when loading is perpendicular to the bedding. However, the number and aperture continuously increase when loading is parallel to the bedding. Beyond 400 °C, the number of pores increases and the aperture of the fractures becomes larger with rising temperature. The changes in microstructures significantly impact the mechanical properties. Between 20 and 600 °C, the compressive strength, elastic modulus, and Poisson's ratio initially decrease and then increase under perpendicular and parallel bedding loadings. The compressive strength and elastic modulus reach minimum values at 400 °C. However, for Poisson's ratio, the minimum occurs at 500 °C and 200 °C under perpendicular and parallel bedding loadings, respectively. Simultaneously, while the crack damage stress during perpendicular bedding loading, σcd-per, initially exhibits an upward trend followed by a decline and subsequently increases again with temperature increasing, the initial stress during perpendicular bedding loading, σci-per, parallel bedding loading, σci-par, and damage stress, σcd-par, decrease initially and then increase, reaching minimum values at 400 °C. These research findings provide essential data for reservoir reconstruction and cementing technology in the in situ mining of oil shale. [ABSTRACT FROM AUTHOR]

In recent years, with the rapid development of blockchain technology, the issues of storage load and data security have attracted increasing attention. Due to the immutable nature of data on the blockchain, where data can only be added and not deleted, there is a significant increase in storage pressure on blockchain nodes. In order to alleviate this burden, this paper proposes a blockchain data storage strategy based on a hot and cold block mechanism. It employs a block heat evaluation algorithm to assess the historical and correlation-based heat indicators of blocks, enabling the identification of frequently accessed block data for storage within the blockchain nodes. Conversely, less frequently accessed or "cold" block data are offloaded to cloud storage systems. This approach effectively reduces the overall storage pressure on blockchain nodes. Furthermore, in applications such as healthcare and government services that utilize blockchain technology, it is essential to encrypt stored data to safeguard personal privacy and enforce access control measures. To address this need, we introduce a blockchain data encryption storage mechanism based on threshold secret sharing. Leveraging threshold secret sharing technology, the encryption key for blockchain data is fragmented into multiple segments and distributed across network nodes. These encrypted key segments are further secured through additional encryption using public keys before being stored. This method serves to significantly increase attackers' costs associated with accessing blockchain data. Additionally, our proposed encryption scheme ensures that each block has an associated encryption key that is stored alongside its corresponding block data. This design effectively mitigates vulnerabilities such as weak password attacks. Experimental results demonstrate that our approach achieves efficient encrypted storage of data while concurrently reducing the storage pressure experienced by blockchain nodes. [ABSTRACT FROM AUTHOR]

This paper applied the prevalent acoustic emission (AE) technology to identify the damage modes and critical conditions for FRP/steel-concrete composite beams during the failure process. AE signals generated by the structural damages were classified efficiently by using a novel self-adaptive real-time clustering (SARTC) method; damage modes corresponding to each clustering category were recognized and analyzed, and the dominant damage type at different stages was obtained by comparing the AE activities and feature values. By conducting the AE intensity analysis, the dynamic evolutionary mechanisms and critical conditions of composite beams were identified; the increase in intensity value from 0.2 to 0.3 reflects the process from critical yielding to major fracture. By establishing the non-linear fitting model between local response and cumulative AE energy, the instantaneous status at arbitrary local position of the composite beam can be inverted and predicted quantitatively by independent AE testing. [ABSTRACT FROM AUTHOR]

This study utilized a sample of 2052 participants from government and enterprise sectors to explore the distinct effects of power and sense of power on cognitive flexibility. It also delves into how the three dimensions of reward sensitivity and the comprehensive measure of punishment sensitivity mediate this relationship. The key findings are as follows: (1) There is no significant direct correlation between power and sense of power. (2) Both power and sense of power are substantial positive predictors of cognitive flexibility, with middle- and upper-level employees demonstrating significantly greater cognitive flexibility than their lower-level counterparts, and sense of power having a more pronounced positive influence than objective power. (3) Drive and fun-seeking mediate the relationship between sense of power and cognitive flexibility, yet only when sense of power is the independent variable. (4) No mediating effects are observed for the dimensions of reward sensitivity or punishment sensitivity when power is the independent variable. Exploring reward and punishment sensitivity in the context of power's influence on cognitive flexibility in real organizational settings is of paramount importance. This enhances our understanding of the intricate ways in which power dynamics shape individual behaviors and cognition across diverse cultural landscapes and provides actionable insights for refining organizational management and leadership strategies. [ABSTRACT FROM AUTHOR]

Most species of Papilionidae are large and beautiful ornamental butterflies. They are recognized as model organisms in ecology, evolutionary biology, genetics, and conservation biology but present numerous unresolved phylogenetic problems. Complete mitochondrial genomes (mitogenomes) have been widely used in phylogenetic studies of butterflies, but mitogenome knowledge within the family Papilionidae is limited, and its phylogeny is far from resolved. In this study, we first report the mitogenome of Byasa confusa from the subfamily Papilioninae of Papilionidae. The mitogenome of B. confusa is 15,135 bp in length and contains 13 protein-coding genes, 22 transfer RNA genes, 2 ribosomal RNA genes, and an AT-rich control region (CR), closely mirroring the genomic structure observed in related butterfly species. Comparative analysis of 77 Papilionidae mitogenomes shows gene composition and order to be identical to that of an ancestral insect, and the AT bias, Ka/Ks, and relative synonymous codon usage (RSCU) are all consistent with that of other reported butterfly mitogenomes. We conducted phylogenetic analyses using maximum-likelihood (ML) and Bayesian-inference (BI) methods, with 77 Papilionidae species as ingroups and two species of Nymphalidae and Lycaenidae as outgroups. The phylogenetic analysis indicated that B. confusa were clustered within Byasa. The phylogenetic trees show the monophyly of the subfamily Papilioninae and the tribes Leptocircini, Papilionini, and Troidini. The data supported the following relationships in tribe level on Papilioninae: (((Troidini + Papilionini) + Teinopalpini) + Leptocircini). The divergence time analysis suggests that Papilionidae originated in the late Creataceous. Overall, utilizing the largest number of Papilionidae mitogenomes sequenced to date, with the current first exploration in a phylogenetic analysis on Papilionidae (including four subfamilies), this study comprehensively reveals the mitogenome characteristics and mitogenome-based phylogeny, providing information for further studies on the mitogenome, phylogeny, evolution, and taxonomic revision of the Papilionidae family. [ABSTRACT FROM AUTHOR]

Postmenopausal osteoporosis, characterized by an imbalance between osteoclast-mediated bone resorption and osteoblast-driven bone formation, presents substantial health implications. In this study, we investigated the role of black goat extract (BGE), derived from a domesticated native Korean goat, estrogen-like activity, and osteoprotective effects in vitro. BGE's mineral and fatty acid compositions were analyzed via the ICP-AES method and gas chromatography–mass spectrometry, respectively. In vitro experiments were conducted using MCF-7 breast cancer cells, MC3T3-E1 osteoblasts, and RAW264.7 osteoclasts. BGE exhibits a favorable amount of mineral and fatty acid content. It displayed antimenopausal activity by stimulating MCF-7 cell proliferation and augmenting estrogen-related gene expression (ERα, ERβ, and pS2). Moreover, BGE positively impacted osteogenesis and mineralization in MC3T3-E1 cells through Wnt/β-catenin pathway modulation, leading to heightened expression of Runt-related transcription factor 2, osteoprotegerin, and collagen type 1. Significantly, BGE effectively suppressed osteoclastogenesis by curtailing osteoclast formation and activity in RAW264.7 cells, concurrently downregulating pivotal signaling molecules, including receptor activator of nuclear factor κ B and tumor necrosis factor receptor-associated factor 6. This study offers a shred of preliminary evidence for the prospective use of BGE as an effective postmenopausal osteoporosis treatment. [ABSTRACT FROM AUTHOR]

The investigation of iron under high pressure and temperatures is crucial to understand the Earth's core structure and composition and the generation of magnetic fields. Here, we present new in situ XRD measurements for iron in an off-Hugoniot state by laser-driven ramp compression at pressure of 200–238 GPa. The lattice parameters for the hexagonal (hcp)-Fe phase and the c/a ratios were obtained to compare them with previous static and dynamical data, which provides the direct confirmation of such parameters via the different compression paths and strain rates. This work indicates that laser ramp compression can be utilized to provide crystal structure information and direct key information on the crystal structure of Fe at the ultrahigh pressure–temperature conditions relevant for planetology. [ABSTRACT FROM AUTHOR]

Since light propagation in a multimode fiber (MMF) exhibits visually random and complex scattering patterns due to external interference, this study numerically models temperature and curvature through the finite element method in order to understand the complex interactions between the inputs and outputs of an optical fiber under conditions of temperature and curvature interference. The systematic analysis of the fiber's refractive index and bending loss characteristics determined its critical bending radius to be 15 mm. The temperature speckle atlas is plotted to reflect varying bending radii. An optimal end-to-end residual neural network model capable of automatically extracting highly similar scattering features is proposed and validated for the purpose of identifying temperature and curvature scattering maps of MMFs. The viability of the proposed scheme is tested through numerical simulations and experiments, the results of which demonstrate the effectiveness and robustness of the optimized network model. [ABSTRACT FROM AUTHOR]

This paper proposes a linear consensus protocol QuickBFT based on Vague sets and multi-attribute decision-making methods. QuickBFT simplifies the communication process based on the HotStuff protocol, reduces the four-stage communication to three-stage communication, and reduces the consensus delay. Furthermore, we introduce the Vague set and multi-attribute decision-making theory into the consensus protocol and propose a new leader node selection algorithm, which can prevent Byzantine nodes from becoming leader nodes, thereby improving the protocol performance when the leader node is attacked. Experimental results show that the throughput of QuickBFT is slightly higher than that of the HotStuff protocol without Byzantine nodes, and the consensus delay is reduced by 20%. In the presence of Byzantine nodes, the throughput of QuickBFT is increased by 80% compared with the HotStuff protocol, and the consensus delay is reduced by 60%. [ABSTRACT FROM AUTHOR]

The seriousness of vessel air pollution has forced the International Maritime Organization (IMO) to introduce a series of relevant laws and regulations. This paper proposes a monitoring scheme based on the synergistic operation of motherships and UAVs. This scheme innovatively adopts a harbor sea patrol vessel or the other official vessel (mothership) as the mobile power supply base for UAVs and realizes efficient and accurate monitoring of vessel air pollution in the pre-monitored area at sea by carrying multiple UAVs. The focus of this paper is on the path optimization problem for multi-UAV collaboration with mothership (MUCWM) monitoring, where the objective is to minimize the total monitoring time for MUCWM. The following three main aspects are studied in this paper: (1) multi-UAV monitoring path optimization; (2) the collaboration mechanism between the mothership and multiple UAVs; and (3) mothership traveling path optimization. In order to effectively solve the above problems, this thesis constructs a path optimization model for multi-UAV collaborative mothership monitoring of air pollution from vessels in port waters; solves the model using the improved adaptive differential evolution (IADE) algorithm; and verifies the effectiveness of the model and the algorithm by using the position data in the Automatic Identification System (AIS) of vessels in Ningbo Zhoushan Port. Through the performance comparison and sensitivity analysis of the algorithm, it is confirmed that the algorithm can effectively solve the path planning problem of the collaborative operation between the mothership and multiple UAVs. The research results in this paper not only help to reduce the air pollution level of harbor vessels and improve the efficiency of sea cruising but also play an important supporting role in the enforcement of relevant emission regulations. [ABSTRACT FROM AUTHOR]

Multimodal transport document collaboration is the foundation of multimodal transport operations. Blockchain technology can effectively address issues such as a lack of trust and difficulties in information sharing in current multimodal transport document collaboration. However, in current research on blockchain-based electronic documents, the bottleneck lies in the collaboration aspect of multimodal transport among multiple entities, known as the "one-bill coverage system" collaborative problem. The collaboration problem studied in this paper involves selecting suitable transport routes according to the shipper's transport needs, and selecting the most suitable specific carrier from numerous carriers. To address the collaboration problem among multiple parties in the multimodal transport "one-bill coverage system", a multiparty collaboration mechanism is designed. This mechanism includes two aspects: firstly, designing the architecture of the multimodal transport blockchain transport platform, which reengineers the operation process of the "one-bill coverage system" for container multimodal transport; secondly, constructing a multiparty collaboration decision-making model for the "one-bill coverage system" in multimodal transport. The model is solved and analyzed, and the collaboration strategy obtained is embedded in the application layer of the platform. Smart contracts related to the "one-bill coverage system" for multimodal transport are written in the Solidity language and deployed and executed on the Remix platform. The design of this mechanism can effectively improve the collaboration efficiency of participants in the "one-bill coverage system" for multimodal transport. [ABSTRACT FROM AUTHOR]

Context: Short-chain fatty acids (SCFAs) have been reported to be associated with the pathogenesis of irritable bowel syndrome (IBS), but the results are conflicting. Objective: Here, a systematic review of case–control studies detecting fecal SCFAs in IBS patients compared with healthy controls (HCs) and self-controlled studies or randomized controlled trials (RCTs) investigating fecal SCFA alterations after interventions were identified from several databases. Data sources: A systematic search of databases (PubMed, Web of Science, and Embase) identified 21 studies published before 24 February 2023. Data extractions: Three independent reviewers completed the relevant data extraction. Data analysis: It was found that the fecal propionate concentration in IBS patients was significantly higher than that in HCs, while the acetate proportion was significantly lower. Low-FODMAP diets significantly reduced the fecal propionate concentration in the IBS patients while fecal microbiota transplantation and probiotic administration did not significantly change the fecal propionate concentration or acetate proportion. Conclusions: The results suggested that the fecal propionate concentration and acetate proportion could be used as biomarkers for IBS diagnosis. A low-FODMAP diet intervention could potentially serve as a treatment for IBS while FMT and probiotic administration need more robust trials. [ABSTRACT FROM AUTHOR]

A point cloud is a simple and concise 3D representation, but point cloud generation is a long-term challenging task in 3D vision. However, most existing methods only focus on their effectiveness of generation and auto-encoding separately. Furthermore, both generative adversarial networks (GANs) and auto-encoders (AEs) are the most popular generative models. But there is a lack of related research that investigates the implicit connections between them in the field of point cloud generation. Thus, we propose a new bidirectional network (BI-Net) trained with collaborative learning, introducing more priors through the alternate parameter optimizations of a GAN and AE combination, which is different from the way of combining them at the network structure and loss function level. Specifically, BI-Net acts as a GAN and AE in different data processing directions, where their network structures can be reused. If optimizing only the GAN without the AE, there is no direct constraint of ground truth on the generator's parameter optimization. This unique approach enables better network optimization and leads to superior generation results. Moreover, we propose a nearest neighbor mutual exclusion (NNME) loss to further homogenize the spatial distribution of generated points during the reverse direction. Extensive experiments were conducted, and the results show that the BI-Net produces competitive and high-quality results on reasonable structure and uniform distributions compared to existing state-of-the-art methods. We believe that our network structure (BI-Net) with collaborative learning could provide a new promising method for future point cloud generation tasks. [ABSTRACT FROM AUTHOR]

Fecal calprotectin (FC) is commonly used to assess Crohn's disease (CD) activity. However, standardized cut-off values accounting for bowel resection history and disease location are lacking. In this study, we analyzed data from patients with CD who underwent magnetic resonance enterography, ileocolonoscopy, and FC measurements from January 2017 to December 2018. In 267 cases from 254 patients, the FC levels in the 'operated' patients were higher when the disease was active compared with those who were in the remission group (178 vs. 54.7 μg/g; p < 0.001), and similar findings were obtained for the 'non-operated' patients (449.5 vs. 40.95 μg/g; p < 0.001). The FC levels differed significantly according to the location of inflammation, with lower levels in the small bowel compared to those in the colon. The FC cut-off levels of 70.8 μg/g and 142.0 μg/g were considered optimal for predicting active disease for operated and non-operated patients, respectively. The corresponding FC cut-off levels of 70.8 μg/g and 65.0 μg/g were observed for patients with disease only in the small bowel. In conclusion, different FC cut-off values would be applicable to patients with CD based on their bowel resection history and disease location. Tight control with a lower FC target may benefit those with a history of bowel resection or small-bowel-only disease. [ABSTRACT FROM AUTHOR]

Background: Current guidelines consider atrial fibrillation (AF) type as the prognostic factor for a recommendation of catheter ablation. We aimed to determine whether LA and LA appendage (LAA) volumes measured using multislice computed tomography (MSCT) were related to long-term outcomes in AF following radiofrequency catheter ablation (RFCA). Methods: We evaluated 152 consecutive patients with drug-refractory AF (median age, 55.8 ± 9.6 years), including 110 male patients, who underwent RFCA in a single center. All patients underwent MSCT imaging for anatomical assessment. The endpoint of this study was documented AF recurrence after RFCA. Results: The overall procedure success rate was 77.6% (n = 118) during a mean follow-up period of 12.6 months. The LA volume was significantly larger for those who experienced AF recurrence after RFCA than for the patients without recurrent AF after the procedure (153.8 ± 29.9 mL vs. 139.2 ± 34.1 mL, p = 0.025). However, LAA volumes were nearly equivalent between the patients with and without AF recurrence after RFCA (16.2 ± 6.3 mL and 14.7 ± 6.5 mL, respectively; p = 0.235). LA volume ≥ 153.2 mL was the optimal cutoff value for estimating AF recurrence after RFCA, with 94% sensitivity and 66% specificity. LA volume remained an independent predictor of both AF recurrence and permanent AF. Conclusions: LA volume as assessed by MSCT might be helpful for identifying patients likely to achieve successful AF ablation. LA volume ≥ 153.2 mL, but not LAA volume, showed good accuracy in predicting AF recurrence after RFCA. [ABSTRACT FROM AUTHOR]

Accurate inferior alveolar nerve (IAN) canal segmentation has been considered a crucial task in dentistry. Failing to accurately identify the position of the IAN canal may lead to nerve injury during dental procedures. While IAN canals can be detected from dental cone beam computed tomography, they are usually difficult for dentists to precisely identify as the canals are thin, small, and span across many slices. This paper focuses on improving accuracy in segmenting the IAN canals. By integrating our proposed frequency-domain attention mechanism in UNet, the proposed frequency attention UNet (FAUNet) is able to achieve 75.55 % and 81.35 % in the Dice and surface Dice coefficients, respectively, which are much higher than other competitive methods, by adding only 224 parameters to the classical UNet. Compared to the classical UNet, our proposed FAUNet achieves a 2.39 % and 2.82 % gain in the Dice coefficient and the surface Dice coefficient, respectively. The potential advantage of developing attention in the frequency domain is also discussed, which revealed that the frequency-domain attention mechanisms can achieve better performance than their spatial-domain counterparts. [ABSTRACT FROM AUTHOR]

Simple Summary: As demand for lamb is increasing, shortening the growth cycle and increasing meat production in lambs are major concerns today. Protein and energy are the two nutrients that most directly drive meat production in animals. In lambs, however, too few applications are available through nutrient combinations. We believe it is feasible to encourage animals to improve meat production performance by regulating the simplest nutrients in feed. In this experiment, we investigated the effects of three dietary ingredients with protein-to-fat ratios on growth, slaughter performance, fat deposition and meat quality of Small-Tail Han lambs. The aim of the current research was to gain insights/provide ideas for enhancing nutrient combination effects to improve animal production performance. The purpose of this study was to investigate the effects of feed ingredients with different protein-to-fat ratios on growth, slaughter performance and meat quality of Small-Tail Han lambs. Forty-five Small-Tail Han lambs (♂) (BW = 34.00 ± 2.5 kg, age = 120 ± 9 d) were randomly divided into groups with three different experimental treatments: (1) PF 5, with the ratio of protein to fat (CP:EE) of 50 to 5; (2) PF10, CP: EE = 50:10; (3) PF20, CP: EE = 50:20. Each treatment group had 15 lambs, and each sheep was a repeat. This experiment lasted for 65 days, with feed intake recorded daily, and animals being weighed on days 0, 30, and 65. At the conclusion of the experiment, eight lambs from each group were slaughtered to assess slaughter performance and meat quality. The results showed that the average daily gain (ADG) of the three groups were 315.27, 370.15 and 319.42 g/d, respectively. The PF10 group had the highest ADG (370.15 g) (p < 0.05). Forestomach weights (1216.88 g) of the PF10 group were significantly higher than those of the other groups (p < 0.05). There were no differences (p > 0.05) in fat percentages in various parts of body among treatments. Feed conversion of the PF10 group was higher (p < 0.05) than that of PF 5 and PF 20 groups. Furthermore, the PF10 group had a higher (p > 0.05) carcass weight and slaughter rate and there were few differences between the other groups in terms of dry matter intake, meat quality, organ weight, and fat deposition (p > 0.05). The protein–energy supplement with protein-to-fat ratio, PF10 appeared to be more desirable to promote the growth and development in Small-Tail Han Lambs. [ABSTRACT FROM AUTHOR]

Bulbil of yam (BY) extract contains various active compounds possessing many pharmacological properties. However, little is known about the effect and underlying mechanism of BY extract on ethanol-induced liver damage. The present study explored the beneficial potential of BY extract on ethanol-induced hepatotoxicity. To evaluate its effectiveness, ethanol-induced HepG2 liver cells were pretreated with BY extract. BY extract effectively rescued cells from ethanol treatment through inhibition of apoptotic cell death as well as inhibiting expression of mitogen-activated protein kinase (MAPK) proteins as stress inducers. BY extract increased the expression of typical antioxidants. Furthermore, BY extract significantly inhibited mitochondrial dysfunction and endoplasmic reticulum (ER) stress, which are major ROS-inducing factors. Finally, as an underlying mechanism of the protective effects of BY extract on ethanol-induced liver damage, it activated Nrf2 protein through translocation from the cytosol to the nucleus, which in turn activated its target oxidative stress suppressor genes. Collectively, our findings demonstrate that BY extract has potential antioxidative effects in ethanol-induced liver cells and contributes to the establishment of a treatment strategy for alcohol-derived liver injuries. [ABSTRACT FROM AUTHOR]

5G cellular networks are already more than six times faster than 4G networks, and their packet loss rate, especially in the Internet of Vehicles (IoV), can reach 0.5% in many cases, such as when there is high-speed movement or obstacles nearby. In such high bandwidth and high packet loss network environments, traditional congestion control algorithms, such as CUBIC and bottleneck bandwidth and round-trip propagation time (BBR), have been unable to balance flow fairness and high performance, and their flow rate often takes a long time to converge. We propose a congestion control algorithm based on bottleneck routing feedback using an in-network control mode called bottleneck routing feedback (BRF). We use SDN technology (OpenFlow protocol) to collect network bandwidth information, and BRF controls the data transmission rate of the sender. By adding the bandwidth information of the bottleneck in the option field in the ACK packet, considering the flow fairness and the flow convergence rate, a bandwidth allocation scheme compatible with multiple congestion control algorithms is proposed to ensure the fairness of all flows and make them converge faster. The performance of BRF is evaluated via Mininet. The experimental results show that BRF provides higher bandwidth utilization, faster convergence rate, and fairer bandwidth allocation than existing congestion control algorithms in 5G cellular networks. [ABSTRACT FROM AUTHOR]

The spatiotemporal evolution of photogenerated charge carriers on surfaces and at interfaces of photoactive materials is an important issue for understanding fundamental physical processes in optoelectronic devices and advanced materials. Conventional optical probe-based microscopes that provide indirect information about the dynamic behavior of photogenerated carriers are inherently limited by their poor spatial resolution and large penetration depth. Herein, we develop an ultrafast scanning electron microscope (USEM) with a planar emitter. The photoelectrons per pulse in this USEM can be two orders of magnitude higher than that of a tip emitter, allowing the capture of high-resolution spatiotemporal images. We used the contrast change of the USEM to examine the dynamic nature of surface carriers in an InGaAs/InP avalanche photodiode (APD) after femtosecond laser excitation. It was observed that the photogenerated carriers showed notable longitudinal drift, lateral diffusion, and carrier recombination associated with the presence of photovoltaic potential at the surface. This work demonstrates an in situ multiphysics USEM platform with the capability to stroboscopically record carrier dynamics in space and time. [ABSTRACT FROM AUTHOR]

Pentatricopeptide repeat (PPR) proteins, with tandem 30–40 amino acids, were characterized as one kind of nucleus coding protein. They have been demonstrated to play important roles in RNA editing, plant growth and development, and plant immunity. Although the PPR gene family has been characterized in some plant species, less is known about this family in peanut, especially their functions in response to Ralstonia solanacearum. In this study, we performed a genome-wide analysis to identify PPR genes and their functions in resistance to R. solanacearum. Here, 389, 481, and 1079 PPR genes were identified from Arachis duranensis, Arachis ipaensis, and Arachis hypogaea, respectively. Allopolyploidization was the main reason for the increased number of the AhPPR members. Gene duplication brought about 367 pairs of homologous genes of PPRs in A. hypogaea. Whole-genome replication, tandem repeats, scattered repeats, and unconnected repeats constituted the replication types. The substitution rates of nonsynonymous (Ka) versus synonymous (Ks) of all homologous pairs were less than 1.0, suggesting that the homologous AhPPRs underwent intense purifying selection pressure and remained conserved in both structure and function. RNA-seq and RT-qPCR analyses showed that AhPPR598 gene was highly expressed in the aerial part of peanut and involved in response to R. solanacearum. The transient expression of AhPPR598 in Nicotiana benthamiana induced the HR-mediated cell death, up-regulated expression of resistant marker genes, and enhanced the resistance to R. solanacearum, suggesting AhPPR598 was a positive regulator of immunity by regulating the JA and SA pathways. These results provide a new understanding of the origin, distribution, and evolution of the AhPPR gene family and potential gene resources for peanut-resistant breeding. [ABSTRACT FROM AUTHOR]

Externally-bonded FRP laminate is widely used in structural strengthening due to the many advantages of FRP materials. Further enhancement of the strengthening effect can be achieved by inducing prestress into the FRP laminate. However, FRP debonding is still a main issue of this strengthening method, especially the Intermediate Crack-induced debonding (IC debonding). To better understand the impact of FRP debonding on the strengthening effect, a series of parameter analyses were conducted in this study based on the fatigue life prediction model proposed by the authors. The proposed model involves the fatigue damage accumulation of components of the beam, the mutual interaction between each component, and the impact of FRP fatigue debonding. As a result, a stress threshold for preventing FRP fatigue debonding in strengthening the concrete beam was proposed, which aimed to avoid safety hazards caused by IC debonding in practical engineering. [ABSTRACT FROM AUTHOR]

During perforation in ultra-deep wells, the blast shock wave can induce dynamic responses of the perforating tubing, leading to potential downhole accidents such as vibration, deformation, and even fracture of the perforating tubing. To comprehend the dynamic response characteristics of the perforating tubing under blast impact load, we conducted a joint finite element simulation using SolidWorks, Hypermesh, and LS-DYNA. The simulation included deformation analysis, motion analysis, and strength analysis of the perforating tubing. By analyzing these factors, we obtained the change in velocity, acceleration, and equivalent stress of the perforating tubing over time under the blast load. The finite element analysis indicates the following: (a) the bottom of the perforating tubing is susceptible to significant tension compression cycle; (b) the velocity amplitude variation is smallest at the top of the perforating tubing, while the frequency and peak values of velocity changes are maximal at the bottom of the perforating tubing; and (c) the top and bottom of the tubing string are the vulnerable parts of the perforating tubing system. [ABSTRACT FROM AUTHOR]

To address the challenges posed by the loose lunar surface structure, including the adhesive nature of lunar soil, strong corrosiveness and the slow walking speed of robots using traditional tripod gaits, this paper proposes the design of a small lunar exploration hexapod robot with hollow legs, employing anti-corrosive aerospace materials throughout. Additionally, an inverted gait motion mode is introduced. Simulation analysis is conducted on the displacement, angular velocity, angular acceleration and joint torque of the robot's body under both traditional tripod gaits and the "inverted gait" motion mode. A physical prototype of the robot is developed to validate the rationality of its structure. Our research results indicate that the designed lunar exploration hexapod robot's body structure is reasonable, enabling it to stand and walk normally on the unstructured lunar terrain. The hollow design reduces the adhesion of lunar soil. The inverted gait motion mode expands the effective swinging range of the robot's legs and increases the effective step length during leg swing. Additionally, it improves the robot's movement speed, eliminates vibrations at the joints during motion and improves the robot's stability during the support phase. [ABSTRACT FROM AUTHOR]

Previous studies have discussed the impact of the socioeconomically disadvantaged stereotype threat (SDST) on inhibitory control. But the specific influences of the SDST on inhibitory control in different household income groups are not clear. We hypothesized that the SDST had different effects on inhibitory control in individuals with distinct household income, and the attribution of stimuli would influence it as well, especially the currency value of the stimuli. To investigate it, two studies were conducted, which required inhibiting their motor responses. Specifically, Study 1 explored the influence of the SDST on basic inhibitory control. Study 2 analyzed the influence of the SDST on inhibitory control when the input stimuli included currency values and monetary conception. The results revealed that the inhibitory control ability was worse in the lower income group but not during the processing of stimuli with currency value. For the effect of the SDST, it found that there was a negative effect on those with a lower household income and a positive effect on those with a higher household income. Based on the findings, the effect of the SDST on inhibitory control in human beings is not stable; instead, it varies depending on the traits of the stimuli in different tasks and of the individuals themselves. [ABSTRACT FROM AUTHOR]

Space robots have been playing an important role in space on-orbit operation missions. However, the traditional configuration of space robots only has a single function and cannot meet the requirements of different space missions, and the launch cost of space robots is very high. Thus, the reconfigurable modular space robot system that can carry multiple loads and own mission adaptability is of great significance. Based on the analysis of a robot space mission, combined with the existing reconfigurable robots, this paper develops a configuration design scheme for a modular reconfigurable space robot, and carries out the prototype design. According to the configuration characteristics of the module, the dynamic modeling of the space robot is based on the graph theory analysis and principle of virtual work. Related application scenarios are set up. Function and feasibility of the dynamic modeling methods are verified through assembly experimentation and dynamic simulation. [ABSTRACT FROM AUTHOR]

Production logging (PL) instruments play a pivotal role in the comprehensive management and monitoring of oil and gas reservoirs. These devices facilitate the resolution of complex flow diagnosis challenges throughout the life cycle of hydrocarbon field exploitation. However, the advent of highly deviated well drilling technology has exposed certain limitations inherent in conventional centralized logging sensing techniques. When fluid flow within horizontal wells becomes segregated or even laminar, these traditional methods struggle to accurately decipher the zonal productions of oil, gas, and water. To address this challenge, multi-array production logging tools were developed in the late 1990s. Historically, these tools were characterized by considerable lengths, reaching up to 30 feet for an entire suite incorporating flow speed and holdup sensors that were not always collocated. Despite the integration of multiple sensors, uncertainties in determining flow profiles persisted. In this paper, we propose a novel integrated multi-parameter evaluation method based on measurements from a recently developed ultracompact flow array sensing tool, aimed at enhancing the accuracy of reservoir evaluation. The validity of the multi-parameter method is substantiated through a comparison of the new tool with an industry benchmark array PL tool on the same well. By combining the monitoring results, an optimization strategy for oil and gas extraction is presented, which is expected to improve the oil and gas recovery rate, thereby providing guidance for subsequent extraction endeavors. Moreover, we demonstrate how this innovative integrated workflow significantly enhances energy savings and efficiency, further underlining its value in modern oil and gas field management. [ABSTRACT FROM AUTHOR]

Biogenic synthesis using medicinal plants has less harmful effects as compared to the chemical synthesis of nanoparticles. Here, for the first time, we successfully demonstrated the eco-friendly synthesis of zinc oxide nanoparticles (ZnO NPs) using an aqueous extract of Cissus antractica. The green synthesis method offers great potential for developing new medications that enhance drug bioavailability. The current work highlighted the cytotoxicity, cell death, and routes of apoptosis in lung cancer cells (A549) and inflammatory effects through synthesizing zinc oxide nanoparticles (ZnO NPs) from the Cissus antractica plant using an eco-friendly methodology. UV–visible (UV-Vis) spectroscopy, X-ray diffraction (XRD), transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FT-IR), and energy-dispersive X-ray spectroscopy (EDS) were also used to characterize the synthesized ZnO nanoparticles. The average size of the NPs was 100 nm, and the NPs were crystalline in nature, as confirmed by FE-TEM and XRD analysis, respectively. In addition, the morphology of the nanoparticles analyzed by FE-TEM showed a spherical shape. The cell viability assay indicated that CA-ZnO NPs are non-toxic to normal cell lines at concentrations up to 20 µg/mL but showed significant toxicity in the A549 cell line. The nanoformulation also increased the ROS generation level in A549 lung cancer cells, and cellular apoptosis was confirmed via Hoechst and PI staining. The CA-ZnO NPs showed significant colony inhibition as well as cell migration ability that highlighted the CA-ZnO NPs as an anticancer agent. Additionally, this study demonstrated that NPs reduced the production of reactive oxygen species (ROS) and enhanced the expression of genes for BAX accumulation by releasing Cyto-c, but decreased Bcl-2 gene expression via the mitochondrial-mediated apoptosis pathway. In addition, the anti-inflammatory effect was also investigated; the CA-ZnO NPs showed significant NO inhibition ability with suppression of pro-inflammatory cytokines (TNF-α, iNOS, COX-2, IL-6, IL-8). In conclusion, Cissus antractica can be a source of significant Nano drugs with more advanced research in order to develop future anti-inflammatory and anticancer medications. [ABSTRACT FROM AUTHOR]

The direct growth of ferroelectric films onto flexible substrates has garnered significant interest in the advancement of portable and wearable electronic devices. However, the search for an optimized bottom electrode that can provide a large and stable remnant polarization is still ongoing. In this study, we report the optimization of an oxide-based LaNiO3 (LNO) electrode for high-quality Pb(Zr0.52Ti0.48)O3 (PZT) thick films. The surface morphology and electrical conductivity of sol-gel-grown LNO films on a fluorophlogopite mica (F-mica) substrate were optimized at a crystallization temperature of 800 °C and a film thickness of 120 nm. Our approach represents the promising potential pairing between PZT and LNO electrodes. While LNO-coated F-mica maintains stable electrical conductivity during 1.0%-strain and 104-bending cycles, the upper PZT films exhibit a nearly square-like polarization–electric field behavior under those stress conditions. After 104 cycles at 0.5% strain, the remnant polarization shows decreases as small as ~14%. Under flat (bent) conditions, the value decreases to just 81% (49%) after 1010 fatigue cycles and to 96% (85%) after 105 s of a retention test, respectively. [ABSTRACT FROM AUTHOR]

(1) Background: A large and diverse microbial population exists in the human intestinal tract, which supports gut homeostasis and the health of the host. Short-chain fatty acid (SCFA)-secreting microbes also generate several metabolites with favorable regulatory effects on various malignancies and immunological inflammations. The involvement of intestinal SCFAs in kidney diseases, such as various kidney malignancies and inflammations, has emerged as a fascinating area of study in recent years. However, the mechanisms of SCFAs and other metabolites produced by SCFA-producing bacteria against kidney cancer and inflammation have not yet been investigated. (2) Methods: We considered 177 different SCFA-producing microbial species and 114 metabolites from the gutMgene database. Further, we used different online-based database platforms to predict 1890 gene targets associated with metabolites. Moreover, DisGeNET, OMIM, and Genecard databases were used to consider 13,104 disease-related gene targets. We used a Venn diagram and various protein−protein interactions (PPIs), KEGG pathways, and GO analyses for the functional analysis of gene targets. Moreover, the subnetwork of protein−protein interactions (through string and cytoscape platforms) was used to select the top 20% of gene targets through degree centrality, betweenness centrality, and closeness centrality. To screen the possible candidate compounds, we performed an analysis of the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of metabolites and then found the best binding affinity using molecular docking simulation. (3) Results: Finally, we found the key gene targets that interact with suitable compounds and function against kidney cancer and inflammation, such as MTOR (with glycocholic acid), PIK3CA (with 11-methoxycurvularin, glycocholic acid, and isoquercitrin), IL6 (with isoquercitrin), PTGS2 (with isoquercitrin), and IGF1R (with 2-amino-1-methyl-6-phenylimidazo[4,5-b] pyridine, isoquercitrin), showed a lower binding affinity. (4) Conclusions: This study provides evidence to support the positive effects of SCFA-producing microbial metabolites that function against kidney cancer and inflammation and makes integrative research proposals that may be used to guide future studies. [ABSTRACT FROM AUTHOR]

The increasing frequency of global drought events poses a significant threat to the stability of grassland ecosystems' functionality. The Inner Mongolian grasslands stand out as one of the world's most drought-prone regions, facing elevated drought risks compared to other biomes. An in-depth comprehension of the impact of drought on grassland ecosystems is paramount for their long-term sustainability. Using the Standardized Precipitation Evapotranspiration Index (SPEI) from 1982 to 2018, this study identified various drought events within the Inner Mongolian grasslands, encompassing moderate drought, severe drought, and extreme drought. The resistance of the vegetation to the different drought conditions, assessed through net primary productivity (NPP) as a metric (reflecting its capacity to maintain its original level during drought periods), was examined. The research findings indicated that the period from 2001 to 2018 witnessed a substantial increase in both the frequency and the extent of drought events compared to the period from 1982 to 2000, particularly concerning severe and extreme droughts. The areas most severely impacted by extreme drought were the Xilingol League and the Alxa League. From 1982–2000 to 2001–2018, under moderate drought conditions, vegetation resistance exhibited a minor decrease in the central and eastern regions but experienced a slight increase in the western region. In contrast, under severe drought conditions, the western region saw a significant decrease in vegetation resistance. Remarkably, under extreme drought conditions, the western region showed a substantial increase in vegetation resistance, while the central and eastern regions experienced a slight decrease. Across all three drought conditions, as precipitation levels declined, the resistance of the meadow–steppe–desert ecosystems demonstrated a high–low–high distribution pattern. The temperate desert steppe exhibited a minimal vulnerability to drought, boasting resistance levels exceeding 0.9. Notably, extreme drought had the most pronounced impact on the temperate meadow steppe, temperate steppe, and temperate desert steppe, particularly within the temperate meadow steppe category. Given these findings, the authorities responsible for grassland management should prioritize regions characterized by frequent drought occurrences and low drought resistance, such as Ulanqab City, the Xilingol League, and the western part of Hulun Buir City. Safeguarding steppe ecosystems is of paramount importance for stabilizing vegetation productivity and land carbon sinks, especially under the anticipated exacerbation of climate conditions in the future. [ABSTRACT FROM AUTHOR]

Rapid and non-destructive identification of the suitable storage status of paddy during storage is crucial for controlling the quality of stored grains, which can provide high-quality raw grains for rice processing. Near-infrared (NIR) spectroscopy combined with neighborhood rough set (NRS) and multiple classification methods were used to identify the different storage statuses of paddy. The NIR data were collected in the range of 1000–1800 nm, and three storage statuses from suitable storage to severely unsuitable storage were divided using the measured fatty acid value of paddy. The spectral features were selected using NRS, successive projection algorithm and variable combination population analysis methods. Random forest (RF), extreme learning machine, and soft independent modeling of class analogy classifiers coupled with spectral features were used to establish classification models to distinguish the different storage statuses of paddy. The comparison results indicated that the optimal wavelengths selected by NRS combined with the RF classifier to construct the NRS-RF series models led to satisfactory identification results, with high correct classification rates of 96.31% and 93.68% in the calibration and test sets, respectively; the indicators of sensitivity and specificity ranged from 0.93 to 0.99. Therefore, the combination of NIR technology with NRS and RF algorithms for identifying the storage status of paddy was feasible, as this would be more helpful for rapidly evaluating the changes of stored paddy quality. The proposed method from this study is expected to provide support for the development of non-destructive equipment for the accurate detection of the quality of stored paddy. [ABSTRACT FROM AUTHOR]

The ultrasonic guided wave technique is extensively used for nondestructive structural testing, and one of the key steps is to extract a single mode with certain purity from multi-order mixed modes. In this paper, the propagation of ultrasonic guided waves in the cylindrical rod is simulated first; the appropriate broadband excitation signal is selected to excite the multi-order modes in a specific frequency range; and the time–space signal containing multi-order modes is converted to the frequency-wavenumber domain signal by two-dimensional Fourier transform. In the frequency-wavenumber domain, the frequency-wavenumber ridge is extracted from the multi-mode frequency-wavenumber domain based on the dynamic programming method, and then the time-domain signal corresponding to a single mode can be reconstructed. By comparing the excited multi-order mode and the separated single mode with the theoretical results, it is observed that the two results are consistent. Thus, the employed mode-excitation method can accurately excite the multi-order modes in rod structures. Furthermore, the proposed method enables the separation of a single-mode wave with high purity, providing a foundation for future utilization of isolated modes. [ABSTRACT FROM AUTHOR]

Deinococcus radiodurans (D. radiodurans) can tolerate various extreme environments including radiation. Protein phosphorylation plays an important role in radiation resistance mechanisms; however, there is currently a lack of systematic research on this topic in D. radiodurans. Based on label-free (phospho)proteomics, we explored the dynamic changes of D. radiodurans under various doses of heavy ion irradiation and at different time points. In total, 2359 proteins and 1110 high-confidence phosphosites were identified, of which 66% and 23% showed significant changes, respectively, with the majority being upregulated. The upregulated proteins at different states (different doses or time points) were distinct, indicating that the radio-resistance mechanism is dose- and stage-dependent. The protein phosphorylation level has a much higher upregulation than protein abundance, suggesting phosphorylation is more sensitive to irradiation. There were four distinct dynamic changing patterns of phosphorylation, most of which were inconsistent with protein levels. Further analysis revealed that pathways related to RNA metabolism and antioxidation were activated after irradiation, indicating their importance in radiation response. We also screened some key hub phosphoproteins and radiation-responsive kinases for further study. Overall, this study provides a landscape of the radiation-induced dynamic change of protein expression and phosphorylation, which provides a basis for subsequent functional and applied studies. [ABSTRACT FROM AUTHOR]

Achieving fully autonomous driving requires seamless collaboration between advanced autonomous driving and road infrastructure technologies. As the proportion of autonomous vehicles (AVs) increases, challenges may arise from their insufficient knowledge of the behavior of traffic objects and inability to effectively drive short distances. Therefore, traffic control centers that can proactively control these issues in real time are essential. In this study, first, the terminology is defined and the types of AV-mixed Traffic Information that a traffic control center needs to efficiently collect, store, and analyze to accommodate the coexistence of AVs and conventional vehicles are identified. Second, a generic notation for an AV-mixed Traffic Information model is defined and the results of modeling each AV-mixed Traffic Information type are presented. Third, an AV-mixed Traffic Information services model that included the names, operations, input/output messages, and relationships of all services is suggested. Finally, the importance of the service functionalities is evaluated through a survey. This study will serve as an initial guideline for the design, construction, and operation of traffic control centers and will help proactively address issues that may arise from the interaction between AVs and conventional vehicles on the road. Moreover, it contributes to identifying the types of traffic information and services that traffic control centers must provide in the era of AV-mixed traffic and suggests future directions for analysis and utilization of traffic information. [ABSTRACT FROM AUTHOR]

Hydroxamic acid (HA) derivatives display antibacterial and antifungal activities. HA with various numbers of carbon atoms (C2, C6, C8, C10, C12 and C17), complexed with different metal ions, including Fe(II/III), Ni(II), Cu(II) and Zn(II), were evaluated for their antimycobacterial activities and their anti-biofilm activities. Some derivatives showed antimycobacterial activities, especially in biofilm growth conditions. For example, 20–100 µM of HA10Fe2, HA10FeCl, HA10Fe3, HA10Ni2 or HA10Cu2 inhibited Mycobacterium tuberculosis, Mycobacterium bovis BCG and Mycobacterium marinum biofilm development. HA10Fe2, HA12Fe2 and HA12FeCl could even attack pre-formed Pseudomonas aeruginosa biofilms at higher concentrations (around 300 µM). The phthiocerol dimycocerosate (PDIM)-deficient Mycobacterium tuberculosis H37Ra was more sensitive to the ion complexes of HA compared to other mycobacterial strains. Furthermore, HA10FeCl could increase the susceptibility of Mycobacterium bovis BCG to vancomycin. Proteomic profiles showed that the potential targets of HA10FeCl were mainly related to mycobacterial stress adaptation, involving cell wall lipid biosynthesis, drug resistance and tolerance and siderophore metabolism. This study provides new insights regarding the antimycobacterial activities of HA and their complexes, especially about their potential anti-biofilm activities. [ABSTRACT FROM AUTHOR]

The detection and selection of fault lines in resonant grounding distribution networks pose challenges due to the lack of sufficient state parameters and data. This paper proposes an approach to overcome these limitations by reconstructing the initial criterion for fault occurrence and fault line selection. Firstly, a combination of 15% of the traditional phase voltage and the sum of the zero-sequence voltage gradient is suggested as the initial criterion for fault occurrence. This improves the speed of the line selection device. Additionally, the transient process of high-resistance grounding in a resonant grounding system is analyzed based on the impedance characteristics of high- and low-frequency lines. The line selection criterion is then established by comparing the current and voltage derivative waveforms on high- and low-frequency lines. To verify the effectiveness of the proposed method, simulations are conducted. The results demonstrate that this method can effectively handle high-resistance grounding faults under complex conditions while meeting the required speed for line selection. [ABSTRACT FROM AUTHOR]

With the advancement in big data and cloud computing technology, we have witnessed tremendous developments in applying intelligent techniques in network operation and management. However, learning- and data-based solutions for network operation and maintenance cannot effectively adapt to the dynamic security situation or satisfy administrators' expectations alone. Anomaly detection of time-series monitoring indicators has been a major challenge for network administrative personnel. Monitored indicators in network operations are characterized by multiple instances with high dimensions and fluctuating time-series features and rely on system resource deployment and business environment variations. Hence, there is a growing consensus that conducting anomaly detection with machine intelligence under the operation and maintenance personnel's guidance is more effective than solely using learning and modeling. This paper intends to model the anomaly detection task as a Markov Decision Process and adopts the Double Deep Q-Network algorithm to train an anomaly detection agent, in which the multidimensional temporal convolution network is applied as the principal structure of the Q network and the interactive guidance information from the operation and maintenance personnel is introduced into the procedure to facilitate model convergence. Experimental results on the SMD dataset indicate that the proposed modeling and detection method achieves higher precision and recall rates compared to other learning-based methods. Our method achieves model optimization by using human–computer interactions continuously, which guarantees a faster and more consistent model training procedure and convergence. [ABSTRACT FROM AUTHOR]

Sound waves generate acoustic resonance energy that penetrates deeply and safely into body areas normal mechanical vibrations cannot reach. The sonic balance pad utilizes these sound waves to create an optimal musculoskeletal response. The purpose of this study was to investigate the effects of a 4-week ankle stabilization exercise program using a sonic balance pad on proprioceptive sense and balance ability in individuals with ankle instability. This study was conducted as a randomized control-group pre-and post-test design in 30 participants (21 females and 9 males) who had experienced an ankle fracture or sprain within the last 5 years or who scored 11 points or more on The Identification of Functional Ankle Instability. The ankle stabilization exercise program was conducted for 4 weeks in the experimental group (n = 15), to which sonic pads were applied, and the control group (n = 15), to which balance pads were applied. All participants were assessed for their intrinsic proprioceptive sense of dorsiflexion and plantarflexion, static balance test, dynamic balance test, and long jump test were measured before and after 4 weeks as dependent variables. After 4 weeks of training, a significant difference was shown in the right dorsiflexion error (Balance pad = PRE: 2.47 ± 0.92; POST: 2.33 ± 1.40, Sonic pad = PRE: 3.27 ± 1.39; POST: 1.20 ± 0.77) and the left plantar flexion error (Balance pad = PRE: 2.00 ± 1.36; POST: 2.73 ± 1.22, Sonic pad = PRE: 3.53 ± 1.25; POST: 2.20 ± 1.01) (p < 0.05) between the experimental and control groups in the proprioception test. In the static balance test, there was no significant difference between the experimental and control groups during the pre, post, and variation stages. However, in the Y-Balance test, which is one of the dynamic balance tests, there was a significant difference between the experimental and control groups at various points, including anterior left (Balance pad = PRE: 72.85 ± 19.95; POST: 63.41 ± 8.66, Sonic pad = PRE: 68.16 ± 6.38; POST: 76.17 ± 3.67), posteromedial right (Balance pad = PRE: 78.59 ± 15.34; POST: 81.41 ± 10.37, Sonic pad = PRE: 86.33 ± 16.44; POST: 102.23 ± 11.53), posteromedial left (Balance pad = PRE: 78.00 ± 16.99; POST: 83.36 ± 10.15, Sonic pad = PRE: 88.96 ± 19.92; POST: 102.45 ± 12.98), posterolateral right (Balance pad = PRE: 78.16 ± 14.33; POST: 82.61 ± 10.73, Sonic pad = PRE: 87.95 ± 17.51; POST: 101.34 ± 15.37), and posterolateral left (Balance pad = PRE: 80.86 ± 14.96; POST: 81.31 ± 7.16, Sonic pad = PRE: 91.23 ± 17.35; POST: 104.18 ± 11.78) (p < 0.05). Moreover, in the single-leg long jump test, which is another dynamic balance test, the experimental group (Sonic pad = PRE: 100.27 ± 29.00; POST: 116.80 ± 28.86) also demonstrated a significant difference in the right single-leg long jump compared to the control group (Balance pad = PRE: 91.87 ± 17.74; POST: 97.67 ± 17.70) (p < 0.05). When a sonic balance pad using sound waves was applied in addition to a 4-week ankle stabilization exercise program for participants with ankle stability, it helped to improve proprioception and dynamic balance ability. [ABSTRACT FROM AUTHOR]

Single photon ionization (SPI) based on vacuum ultraviolet (VUV) lamps has been extensively investigated and applied due to its clean mass spectra as a soft ionization method. However, the photon energy of 10.6 eV and photon flux of 1011 photons s−1 of a commercial VUV lamp limits its range of ionizable analytes as well as its sensitivity. This work designs a chemical ionization focusing integrated (CIFI) ionization source time-of-flight mass spectrometry (TOFMS) based on a VUV lamp for the detection of volatile organic compounds (VOCs) and oxygenated volatile organic compounds (OVOCs). The photoelectrons obtained from the VUV lamp via the photoelectric effect ionized the oxygen and water in the air to obtain the reagent ions. The ion–molecule-reaction region (IMR) is constituted by a segmented quadrupole that radially focuses the ions using a radio-frequency electric field. This significantly enhances the yield and transport efficiency of the product ions leading to a great improvement in sensitivity. As a result, a 44-fold and 1154-fold increase in the signal response for benzene and pentanal were achieved, respectively. To verify the reliability of the ionization source, the linear correspondence and repeatability of benzene and pentanal were investigated. Satisfactory dynamic linearity was obtained in the mixing ratio range of 5–50 ppbv, and the relative standard deviation (RSD) of inter-day reached 3.91% and 6.26%, respectively. Finally, the CIFI−TOFMS was applied to the determination of OVOCs, and the LOD of 12 types of OVOCs reached the pptv level, indicating that the ionization source has the potential for accurate and sensitive online monitoring of atmospheric OVOCs. [ABSTRACT FROM AUTHOR]

With the exploration of outer space, the number of space targets has increased dramatically, while the pressures of space situational awareness have also increased. Among them, spacecraft recognition is the foundation and a critical step in space situational awareness. However, unlike natural images that can be easily captured using low-cost devices, space targets can suffer from motion blurring, overexposure, and excessive dragging at the time of capture, which greatly affects the quality of the images and reduces the number of effective images. To this end, specialized or sufficiently versatile techniques are required, with dataset diversity playing a key role in enabling algorithms to categorize previously unseen spacecraft and perform multiple tasks. In this paper, we propose a joint dataset formulation to increase diversity. Our approach involves reformulating two local processes to condition the Conditional Neural Adaptive Processes, which results in global feature resampling schemes to adapt a pre-trained embedding function to be task-specific. Specifically, we employ variational resampling to category-wise auxiliary features, adding a generative constraint to amortize task-specific parameters. We also develop a neural process variational inference to encode representation, using grid density for conditioning. Our evaluation of the BUAA dataset shows promising results, with no-training performance close to a specifically designed learner and an accuracy rate of 98.2% on unseen categories during the joint training session. Further experiments on the Meta-dataset benchmark demonstrate at least a 4.6% out-of-distribution improvement compared to the baseline conditional models. Both dataset evaluations indicate the effectiveness of exploiting dataset diversity in few-shot feature adaptation. Our proposal offers a versatile solution for tasks across domains. [ABSTRACT FROM AUTHOR]

Constructing a surface representation from the sparse point cloud of a satellite is an important task for satellite on-orbit services such as satellite docking and maintenance. In related studies on surface reconstruction from point clouds, implicit neural representations have gained popularity in learning-based 3D object reconstruction. When aiming for a satellite with a more complicated geometry and larger intra-class variance, existing implicit approaches cannot perform well. To solve the above contradictions and make effective use of implicit neural representations, we built a NASA3D dataset containing point clouds, watertight meshes, occupancy values, and corresponding points by using the 3D models on NASA's official website. On the basis of NASA3D, we propose a novel network called GONet for a more detailed reconstruction of satellite grids. By designing an explicit-related implicit neural representation of the Grid Occupancy Field (GOF) and introducing it into GONet, we compensate for the lack of explicit supervision in existing point cloud surface reconstruction approaches. The GOF, together with the occupancy field (OF), serves as the supervised information for neural network learning. Learning the GOF strengthens GONet's attention to the critical points of the surface extraction algorithm Marching Cubes; thus, it helps improve the reconstructed surface's accuracy. In addition, GONet uses the same encoder and decoder as ConvONet but designs a novel Adaptive Feature Aggregation (AFA) module to achieve an adaptive fusion of planar and volume features. The insertion of AFA allows for the obtained implicit features to incorporate more geometric and volumetric information. Both visualization and quantitative experimental results demonstrate that our GONet could handle 3D satellite reconstruction work and outperform existing state-of-the-art methods by a significant margin. With a watertight mesh, our GONet achieves 5.507 CD-L1, 0.8821 F-score, and 68.86% IoU, which is equal to gains of 1.377, 0.0466, and 3.59% over the previous methods using NASA3D, respectively. [ABSTRACT FROM AUTHOR]

The stability of the casing is a crucial prerequisite for implementing the in situ high-temperature steam injection method in oil shale reservoirs. In order to address the issues of substantial expansion, concentrated thermal stresses, and susceptibility to damage observed in traditional straight casings under high temperatures, this paper proposes the utilization of a corrugated casing structure. In this regard, to investigate the impact of the shape and structure of the wellbore casing on its mechanical properties, identical corrugated and straight casings were selected and studied. Uniaxial compression and tensile tests were conducted on the casings, along with coordination deformation experiments between the casing and cement sheath under varying temperatures. Numerical simulations were employed to obtain the deformation characteristics of the corrugated and straight casings under axial compression and tension loads, as well as the stress distribution on the outer casing wall. The results showed that when subjected to the same amount of deformation under axial loading, the corrugated casing experienced lower compressive and tensile loads compared to the straight casing. Moreover, under the sole constraint of cement sheath, increasing the temperature led to lower vertical strains (perpendicular to the ground) at all measuring points of the corrugated casing as compared to the corresponding strains in the straight casing. Numerical simulations revealed that, under the same temperatures, the deformation at the interface between the corrugated casing and the cement sheath was smaller, while the vertical stress at the interface of the corrugated casing was also lower than the straight casing. Overall, the corrugated casing, with its corrugated structure that enabled micro-deformation, effectively mitigated the axial deformation of the casing caused by thermal expansion. Consequently, the corrugated casing reduced the extrusion of wellbore casing on the cement sheath, thereby preserving the integrity and stability of the wellbore cementing structure. [ABSTRACT FROM AUTHOR]

With the progress of society and the diversification of transportation modes, people are faced with more and more complicated travel choices, and thus, multi-criteria route choosing optimization problems have drawn increased attention in recent years. A number of multi-criteria traffic network equilibrium problems have been proposed, but most of them do not involve data uncertainty nor computational methods. This paper focuses on the methods for solving robust multi-criteria traffic network equilibrium problems with path capacity constraints. The concepts of the robust vector equilibrium and the robust vector equilibrium with respect to the worst case are introduced, respectively. For the robust vector equilibrium, an equivalent min–max optimization problem is constructed. A direct search algorithm, in which the step size without derivatives and redundant parameters, is proposed for solving this min–max problem. In addition, we construct a smoothing optimization problem based on a variant version of ReLU activation function to compute the robust weak vector equilibrium flows with respect to the worst case and then find robust vector equilibrium flows with respect to the worst case by using the heaviside step function. Finally, extensive numerical examples are given to illustrate the excellence of our algorithms compared with existing algorithms. It is shown that the proposed min–max algorithm may take less time to find the robust vector equilibrium flows and the smoothing method can more effectively generate a subset of the robust vector equilibrium with respect to the worst case. [ABSTRACT FROM AUTHOR]

In agricultural production, carbendazim and other pesticides are used to prevent soybean root rot. However, carbendazim degrades slowly and affects a series of biochemical processes such as soil biological nitrogen fixation and soil nutrient activation in the natural environment. This study mainly investigated the effects of Rhizophagus intraradices, Acinetobacter calcoaceticus, and carbendazim on soybean biomass, the incidence of root rot, the total number of bacterial colonies and phosphorus-solubilizing bacteria in rhizosphere soil, and carbendazim residue in soybean grains and rhizosphere soil. The results showed that the arbuscular mycorrhizal fungi (AMF) spore density, AMF infection rate, soybean biomass, nodule number, total bacterial colonies, and phosphorus-solubilizing bacteria colonies in the soybean rhizosphere soil were the highest in the R. intraradices and A. calcoaceticus treatment groups under natural soil conditions. Moreover, the incidence of root rot and carbendazim residue in soybean grains and rhizosphere soil were the lowest in the R. intraradices and A. calcoaceticus treatment group under natural soil conditions. This result indicated that R. intraradices and A. calcoaceticus can effectively reduce carbendazim residue in soybean grains and rhizosphere soil. This study provided theoretical support for the development of microbial fertilizer and microbial degradation of pesticide residues and improved the practical basis for ensuring food safety. [ABSTRACT FROM AUTHOR]

Coastal ship tracking is used in many applications, such as autonomous navigation, maritime rescue, and environmental monitoring. Many general object-tracking methods based on deep learning have been explored for ship tracking, but they often fail to accurately track ships in challenging scenarios, such as occlusion, scale variation, and motion blur. We propose a memory-guided perception network (MGPN) to address these issues. MGPN has two main innovative improvements. The dynamic memory mechanism (DMM) in the proposed method stores past features of the tracked target to enhance the model's feature fusion capability in the temporal dimension. Meanwhile, the hierarchical context-aware module (HCAM) enables the interaction of different scales, global and local information, to address the scale discrepancy of targets and improve the feature fusion capability in the spatial dimension. These innovations enhance the robustness of tracking and reduce inaccuracies in the bounding boxes. We conducted an in-depth ablation study to demonstrate the effectiveness of DMM and HCAM. Finally, influenced by the above two points, MGPN has achieved state-of-the-art performance on a large offshore ship tracking dataset, which contains challenging scenarios such as complex backgrounds, ship occlusion, and varying scales. [ABSTRACT FROM AUTHOR]