The problem of data enrichment to train visual SLAM and VO construction models using deep learning (DL) is an urgent problem today in computer vision. DL requires a large amount of data to train a model, and more data with many different contextual and conditional conditions will create a more accurate visual SLAM and VO construction model. In this paper, we introduce the TQU-SLAM benchmark dataset, which includes 160,631 RGB-D frame pairs. It was collected from the corridors of three interconnected buildings comprising a length of about 230 m. The ground-truth data of the TQU-SLAM benchmark dataset were prepared manually, including 6-DOF camera poses, 3D point cloud data, intrinsic parameters, and the transformation matrix between the camera coordinate system and the real world. We also tested the TQU-SLAM benchmark dataset using the PySLAM framework with traditional features such as SHI_TOMASI, SIFT, SURF, ORB, ORB2, AKAZE, KAZE, and BRISK and features extracted from DL such as VGG, DPVO, and TartanVO. The camera pose estimation results are evaluated, and we show that the ORB2 features have the best results ($Er{r}_d$ = 5.74 mm), while the ratio of the number of frames with detected keypoints of the SHI_TOMASI feature is the best ($r_d=98.97\%$). At the same time, we also present and analyze the challenges of the TQU-SLAM benchmark dataset for building visual SLAM and VO systems. Full article

Migraine is a highly prevalent brain condition with paroxysmal changes in brain excitability believed to contribute to the initiation of an attack. The attacks and their unpredictability have a major impact on the lives of patients. Clinical management is hampered by a lack of reliable predictors for upcoming attacks, which may help in understanding pathophysiological mechanisms to identify new treatment targets that may be positioned between the acute and preventive possibilities that are currently available. So far, a large range of studies using conventional hospital-based EEG recordings have provided contradictory results, with indications of both cortical hyper- as well as hypo-excitability. These heterogeneous findings may largely be because most studies were cross-sectional in design, providing only a snapshot in time of a patient’s brain state without capturing day-to-day fluctuations. The scope of this narrative review is to (i) reflect on current knowledge on EEG changes in the context of migraine, the attack cycle, and underlying pathophysiology; (ii) consider the effects of migraine treatment on EEG features; (iii) outline challenges and opportunities in using EEG for monitoring attack susceptibility; and (iv) discuss future applications of EEG in home-based settings. Full article

Pollen transmission of Camellia oleifera is affected by climate and environment, and the quality of natural pollination is not high, which seriously affects the yield of Camellia oleifera. Artificial pollination is an effective way to solve the low fruit setting rate of natural pollination, but the problem to be solved urgently in artificial pollination is the collection of a large amount of pollen. At present, there is no mechanized equipment for Camellia oleifera flower bud collection, so developing an efficient pollen collection device has become a key problem that restricts the high-quality development of Camellia oleifera. In this paper, on the basis of measuring the tensile force, the shearing force, and the torsional moment required to remove Camellia Oleifera flower bud from the branch, which are 8.968 N, 13.94 N, and 0.0178 N·m, respectively, three types of Camellia oleifera flower bud collecting actuators were designed. According to the results of parameter design, feasibility analysis, and dynamic simulation, the power parameters of three types of Camellia oleifera flower bud collecting actuators were obtained. The experiment of collecting Camellia oleifera flower bud was designed, and the collection time, collection rate, and bud breakage rate of the three collecting actuators were compared. The experimental results show that the collection time of the rotary twist-type collecting actuator was 1.57 s, the collection rate was 91%, and the breakage rate was 4.9%, which can realize the efficient and low-loss collection of Camellia oleifera flowers bud, providing a theoretical basis for subsequent research on a Camellia oleifera flower bud collection robot. Full article

Purpose: Food insecurity and colorectal cancer (CRC) are widely prevalent problems in the U.S. However, the long-term effects of food insecurity among people living with CRC are not well explored (e.g., risk of mortality). Methods: Data from the U.S. National Health and Nutrition Examination Survey (years 1999–2010) were linked with mortality data from the National Death Index up to 31 December 2019. Results: A total of 30,752 adults comprised the analytic sample; 222 were living with CRC and more than a tenth were food-insecure (11.6%). In our adjusted analysis, individuals who were food insecure and had CRC were 4.13 times more likely to die of any cause and 9.57 times more likely to die of cardiovascular diseases (compared to those without CRC and food insecurity). Conclusions: Colorectal cancer is among the top cancers diagnosed in American adults and more than a tenth of adult Americans with CRC live with food insecurity. Given the higher risk of mortality with co-occurring CRC and food insecurity, collaborative healthcare models can help address food insecurity and other social needs of people with CRC, and surveillance measures for food insecurity should be widely implemented across health systems. Full article

Recent advances in the treatment of gastric cancer (GC) with chemotherapy, immunotherapy, anti-angiogenic therapy and targeted therapies have yielded some improvement in survival outcomes; however, metastatic GC remains a lethal malignancy and amongst the leading causes of cancer-related mortality worldwide. Importantly, the ongoing molecular characterisation of GCs continues to uncover potentially actionable molecular targets. Among these, aberrant FGFR2-driven signalling, predominantly arising from FGFR2 amplification, occurs in approximately 3–11% of GCs. However, whilst several inhibitors of FGFR have been clinically tested to-date, there are currently no approved FGFR-directed therapies for GC. In this review, we summarise the significance of FGFR2 as an actionable therapeutic target in GC, examine the recent pre-clinical and clinical data supporting the use of small-molecule inhibitors, antibody-based therapies, as well as novel approaches such as proteolysis-targeting chimeras (PROTACs) for targeting FGFR2 in these tumours, and discuss the ongoing challenges and opportunities associated with their clinical development. Full article

The efficient scheduling of resources within emergency departments (EDs) is crucial to minimizing patient length of stay (LoS) times and maximizing the utilization of limited resources. Reducing patient wait times can enhance the operation of emergency departments and improve patient satisfaction and the quality of medical care. This study develops a simulation model using Discrete Event Simulation (DES) methodology, examining six resource scheduling policies that consider different combinations of general and senior physicians. By leveraging six scheduling policies and machine learning techniques, this model dynamically identifies the most effective scheduling policy, based on a comprehensive dataset of ED visits in South Korea. The ED simulation achieves an accuracy rate of 90% and demonstrates that our proposed integrated machine learning approach reduces average length of stay (LoS) to approximately 322.91 min, compared to 327.10 min under traditional methods. This study underscores the potential of integrating DES and machine learning to enhance resource management in EDs. Full article

Cervical cancer continues to be a public health concern, as it remains the second most common cancer despite screening programs. It is the third most common cause of cancer-related death for women, and the majority of cases happen in developing nations. The standard treatment for locally advanced cervical cancer involves the use of external beam radiation therapy, along with concurrent chemotherapy, followed by an image-guided adaptive brachytherapy (IGABT) boost. The five-year relative survival rate for European women diagnosed with cervical cancer was 62% between 2000 and 2007. Updated cervical cancer treatment guidelines based on IGABT have been developed by the Gynecological working group, which is composed of the Group Européen de Curiethérapie–European Society for Therapeutic Radiology and Oncology. The therapeutic strategy makes use of three-dimensional imaging, which can be tailored to the target volume and at-risk organs through the use of computed tomography or magnetic resonance imaging. Under anaesthesia, the brachytherapy implantation is carried out. Ultrasonography is utilised to assess the depth of the uterine cavity and to facilitate the dilation of the uterine canal during the application insertion. In this study, we examine data from the international literature regarding the application of ultrasound in cervical cancer brachytherapy. Full article

In recent years, the rapid development of the photovoltaic (PV) industry has resulted in a saturation of research on onshore PV power plant construction. However, current studies on the impact of marine PVs on the marine environment remain limited and scarce. In order to facilitate the implementation of carbon reduction goals and promote the sustainable development of the offshore PV industry, this study analyzes the environmental impact of PV sea-use resources based on spatial information technology in the western part of Gaotang Island. The findings show that the MIKE21FM model provides relatively accurate simulations of tidal flow and tide level in the marine PV area. Flow velocity in the marine PV area exhibits a decreasing trend, with an average decrease ranging from 0.03 to 0.07 m/s. This decrease minimally affects surrounding navigational channels and large-scale flow fields. The resulting siltation is also deemed less significant, with an annual deposition from 0.03 to 0.06 m/a. Moreover, offshore PV construction resulted in a total intertidal biological loss of 123.45 t. The suspension of sediment during cofferdam construction and removal has a potential effect on zooplankton and fishery resources. Overall, it is proposed that careful planning, prudent site selection, and the execution of countermeasures during marine PV construction will combine to minimize the impact on the marine environment. Full article

An evaluation of the impact of osteoporosis on loss of spinal stability, with or without intervertebral disc degeneration, using computational analysis is presented. The research also investigates the correlation between osteoporosis and intervertebral disc degeneration. Three-dimensional finite element models of human lumbar spine segments were used to assess the influence of osteoporosis on spinal stability. Five different models of age-related degeneration were created using various material properties for trabecular bone and intervertebral discs. Calculation results indicate that in a spine with osteoporosis, the deformation of the intervertebral discs can increase by more than 30% when compared to a healthy spine. Thus, intervertebral disc deformation depends not only on the degree of degeneration of the discs themselves, but their deformation is also influenced by the degree of osteoporosis of the vertebrae. Additionally, the load-bearing capacity of the spine can decrease by up to 30% with osteoporosis, regardless of the degree of intervertebral disc deformation. In conclusion, osteoporosis can contribute to intervertebral disc degeneration. Full article

To realize the utilization of peanut shell, this study investigates the combustion behavior, chemical kinetics and thermodynamic parameters of peanut shell using TGA under atmospheric air at the heating rates of 10, 20, and 30 K/min. Results indicate that increasing the heating rate leads to higher ignition, burnout, and peak temperatures, as observed in the TG/DTG curves shifting to the right. Analysis of combustion performance parameters suggest that higher heating rates can enhance combustion performances. Kinetic analysis using two model-free methods, KAS and FWO, shows that the activation energy (E_α) ranges from 93.30 to 109.65 kJ/mol for FWO and 89.72 to 103.88 kJ/mol for KAS. The data fit well with coefficient of determination values (R²) close to 1 and the mean squared error values (MSE) less than 0.006. Pre-exponential factors using FWO range from 2.19 × 10⁶ to 8.08 × 10⁷ s^–1, and for KAS range from 9.72 × 10⁵ to 2.25 × 10⁷ s^–1. Thermodynamic analysis indicates a low-energy barrier (≤±6 kJ/mol) between activation energy and enthalpy changes, suggesting easy reaction initiation. Furthermore, variations in enthalpy (ΔH), Gibbs free energy (ΔG), and entropy (ΔS) upon conversion (α) suggest that peanut shell combustion is endothermic and non-spontaneous, with the generation of more homogeneous or well-ordered products as combustion progresses. These findings offer a theoretical basis and data support for the further utilization of agricultural biomass. Full article

Rural landscapes serve as important platforms to determine the landscape characteristics (LCs) of rural areas, demonstrating the landscape characteristics specific to certain regions to the public. However, the development trend of urban and rural areas is continuous and impacts the characteristics of rural landscapes, which directly affects the public’s visual experience and landscape perception. In order to improve the characteristics of rural landscapes, this study evaluates and analyzes their visual quality based on public preferences and eye movement heat maps. The results show that most subjects have a high preference for horizontal, open-view rural landscapes with fields and landform features as the dominant landscape elements. This study also found that the combination of strip-like or planar settlement buildings with regional characteristics and landform features has an active impact on the visual quality of rural landscapes. These results show that rural landscapes characterized by scattered settlement buildings without significant regional characteristics, horizontally curved roads, bridges, and other human-made landscape elements, and mixed and disorderly vegetation have low landscape preference, which degrades their visual quality. These research results provide crucial suggestions for landscape managers to protect and renew rural landscape features. Full article

The Amazon region has the largest diversity of freshwater stingrays; however, there are still places where information about this group is scarce. The present work aims to record the occurrence of freshwater stingrays in the Uatumã river basin, Amazonas, Brazil. For this, collections were carried out in three municipalities bathed by the Uatumã River, Presidente Figueiredo, Itapiranga, and São Sebastião do Uatumã. The rays were collected through fishing using a hand net and, after capture, were identified through the pattern of the dorsal and ventral color of the disc, the absence or presence of the labial groove, and the organization of the row of spines on the tail, and were also measured, weighed, and sexed. In total, 69 specimens of Potamotrygonines were captured, 59 of which were from the genus Potamotrygon and ten individuals from the genus Paratrygon. The present study provides preliminary information on the characteristics of freshwater stingray species that may occur in the Uatumã River. Furthermore, new research is necessary to improve the identification of specimens to determine the diversity and elucidate aspects related to the biology of elasmobranchs in the Uatumã River Basin, Brazil. Full article

This study explores the application effect of the new non-isocyanate polyurethane curing agent on the rapid curing mechanism and bearing characteristics of piles in beach foundations. Through laboratory tests and field tests, the effects of the curing agent on the physical and mechanical properties of sand were systematically analyzed, including compressive strength, shear strength, and elastic modulus, and the effects of water content and cement–sand mass ratio on the properties of sand after curing were investigated. The results show that introducing a curing agent significantly improves the mechanical properties of sand, and the cohesion and internal friction angle increase exponentially with the sand mass ratio. In addition, the increase in water content leads to a decrease in the strength of solidified sand, and the microstructure analysis reveals the change in the bonding effect between the solidified gel and the sand particles. The field static load tests of single piles and pile groups verify the effectiveness of the rapid solidification pile in beach foundations and reveal the significant influence of pile length and pile diameter on the bearing capacity. This study provides a theoretical basis and technical support for the rapid solidification and reinforcement of tidal flat foundations and provides important guidance for related engineering applications. Full article

The role of lncRNA and circRNA in wheat grain development is still unclear. The objectives of this study were to characterize the lncRNA and circRNA in the wheat grain development and to construct the interaction network among lncRNA, circRNA, and their target miRNA to propose a lncRNA–circRNA–miRNA module related to wheat grain development. Full transcriptome sequencing on two wheat varieties (Annong 0942 and Anke 2005) with significant differences in 1000-grain weight at 10 d (days after pollination), 20 d, and 30 d of grain development were conducted. We detected 650, 736, and 609 differentially expressed lncRNA genes, and 769, 1054, and 1062 differentially expressed circRNA genes in the grains of 10 days, 20 days and 30 days after pollination between Annong 0942 and Anke 2005, respectively. An analysis of the lncRNA–miRNA and circRNA–miRNA targeting networks reveals that circRNAs exhibit a more complex and extensive interaction network in the development of cereal grains and the formation of grain shape. Central to these interactions are tae-miR1177, tae-miR1128, and tae-miR1130b-3p. In contrast, lncRNA genes only form a singular network centered around tae-miR1133 and tae-miR5175-5p when comparing between varieties. Further analysis is conducted on the underlying genes of all target miRNAs, we identified TaNF-YB1 targeted by tae-miR1122a and TaTGW-7B targeted by miR1130a as two pivotal regulatory genes in the development of wheat grains. The quantitative real-time PCR (qRT-PCR) and dual-luciferase reporter assays confirmed the target regulatory relationships between miR1130a-TaTGW-7B and miR1122a-TaNF-YB1. We propose a network of circRNA and miRNA-mediated gene regulation in the development of wheat grains. Full article

This research investigates the influence of intellectual capital on the stability of banks in the evolving context of Saudi Arabia’s banking sector. Against the backdrop of rapid economic reforms under Vision 2030 and the challenges imposed by the COVID-19 pandemic, this research incorporates specific metrics related to these contexts and provides a nuanced analysis of how intellectual capital and its components (human capital efficiency (HCE), structural capital efficiency (SCE), and capital employed efficiency (CEE)) affect the financial stability of Saudi banks. This research analyzes a decade-long panel dataset for ten major Saudi banks from 2012 to 2022, utilizing both fixed-effects and cross-section random-effects models to discern the impact of intellectual capital on bank stability. The findings reveal a positive overall influence of intellectual capital on bank stability; however, individual components present a complex relationship, with CEE showing a positive association and HCE and SCE demonstrating unexpected negative correlations with bank stability. The research identifies leverage (LEV) as a significant factor negatively impacting stability. Operational efficiency (OPEF) and size (SIZE) also negatively affect stability. Surprisingly, macroeconomic indicators and bank size exhibit non-significant effects on bank stability. Similarly, the direct impact of the COVID-19 pandemic was found to be non-significant, suggesting a resilient banking environment or the presence of effective mitigating strategies. As Saudi Arabia continues its ambitious economic transformation, this research underscores the critical role of effectively managed intellectual capital in ensuring the banking sector’s stability. It provides a foundation for ongoing research in this vital area. Full article

The significance of developing shared road infrastructure in cities throughout the world is growing. Driven by the need to improve traffic management in ways that enhance multiple sustainability outcomes, developing the tools needed to test shared space proposals is becoming more sought after by responsible agencies. This paper reviews approaches to simulation modeling focused on representing and assessing shared spaces, culminating in a new approach presented here called the Integrated Pedestrian–Vehicle Model (IPVM)—a novel framework that combines social force models, car-following models and other algorithms from the robotics domain to better describe both mobility and activity within a shared space. The IPVM recognizes that while shared spaces are inherently multimodal, past efforts have tended to use pedestrian models as a starting point. Most consider the interaction of pedestrians with other pedestrians and static road infrastructure. Shared space models are generally microscopic models that integrate a social force model with a variety of car-following models to describe the interaction between vehicles and pedestrians. However, there is little research and few practical methodologies that address the long-range conflict avoidance between vehicles and pedestrians. This aspect is crucial for accurately representing the desire lines and pathways of pedestrians and active transport users in complex environments like shared spaces. The IPVM describes and visualizes shared road infrastructure with an absence of separating infrastructure between users and outputs. It generates metrics that can be used in conjunction with the latest evaluation approaches to gauge the sustainability credentials of shared space road proposals. Enhanced modeling of shared space solutions can lead to more effective implementation, which can potentially reduce the presence of cars, increase public and active transport use and lead to a more sustainable transport system. Full article

Biologists and veterinarians rely on dart projectors to inject animals with drugs, take biopsies from specimens, or inject tracking chips. Firearms, air guns, and other launchers are limited in their ability to precisely control the kinetic energy of a projectile, which can injure the animal if too high. In order to improve the safety of remote drug delivery, a lidar-modulated electromagnetic launcher and a soft drug delivery dart were prototyped. A single-stage revolver coilgun and soft dart were designed and tested at distances up to 8 m. With a coil efficiency of 2.25%, the launcher could consistently deliver a projectile at a controlled kinetic energy of 1.00 ± 0.006 J and an uncontrolled kinetic energy of 2.66 ± 0.076 J. Although modifications to charging time, sensors, and electronics could improve performance, our launcher performed at the required level at the necessary distances. The precision achieved with commercial components enables many other applications, from law enforcement to manufacturing. Full article

Silicon represents one of the most attractive anode materials in lithium-ion batteries (LIBs) due to its highest theoretical specific capacity. Thus, there is a most urgent need to prepare Si-based nano materials in a very efficient way and develop some reasonable approaches for their modification in order to resolve the short-falls of Si anodes, which include both low conductivity and huge volume changes during intercalation of lithium ions. In this work, the kerf loss silicon (KL Si) from the photovoltaic industry has been used as an inexpensive Si source for the preparation of a porous silicon/silver/carbon composite (pSi/Ag@C) as an anode material. Porous silicon was embedded with Ag particles via the Ag-catalyzed chemical etching process, providing additional space to accommodate the large volume expansion of silicon. After carbon coating from polymerization of tannic acid on the surface of pSi/Ag, a high-speed conductive network over the surface of silicon was built and contributed to enhancing the electrochemical performance of the anode. The pSi/Ag@C electrode discharge capacity maintained at a stable value of 665.3 mAh g⁻¹ after 100 cycles under 0.5 A g⁻¹ and exhibited good rate performance. Therefore, this study recommends that the method is very promising for producing a silicon anode material for LIBs from KL Si. Full article

As global arid conditions worsen and groundwater resources diminish, drought stress has emerged as a critical impediment to plant growth and development globally, notably causing declines in crop yields and even the extinction of certain cultivated species. Numerous studies on drought resistance have demonstrated that DNA methylation dynamically interacts with plant responses to drought stress by modulating gene expression and developmental processes. However, the precise mechanisms underlying these interactions remain elusive. This article consolidates the latest research on the role of DNA methylation in plant responses to drought stress across various species, focusing on methods of methylation detection, mechanisms of methylation pattern alteration (including DNA de novo methylation, DNA maintenance methylation, and DNA demethylation), and overall responses to drought conditions. While many studies have observed significant shifts in genome-wide or gene promoter methylation levels in drought-stressed plants, the identification of specific genes and pathways involved remains limited. This review aims to furnish a reference for detailed research into plant responses to drought stress through epigenetic approaches, striving to identify drought resistance genes regulated by DNA methylation, specific signaling pathways, and their molecular mechanisms of action. Full article

As nanoparticle syntheses on a large scale usually yield products with broad size and shape distributions, the properties of nanoparticle-based products need to be tuned after synthesis by narrowing the size and shape distributions or via the removal of undesired fractions. The development of property-selective classification processes requires a universal framework for the quantitative evaluation of multi-dimensional particle fractionation processes. This framework must be applicable to any property and any particle classification process. We extended the well-known one-dimensional methodology commonly used for describing particle size distributions and fractionation processes to the multi-dimensional case to account for the higher complexity of the property distribution and separation functions. In particular, multi-dimensional lognormal distributions are introduced and applied to diameter and length distributions of gold nanorods. The fractionation of nanorods via centrifugation and by orthogonal centrifugal and electric forces is modeled. Moreover, we demonstrate that analytical ultracentrifugation with a multi-wavelength detector (MWL-AUC) is a fast and very accurate method for the measurement of two-dimensional particle size distributions in suspension. The MWL-AUC method is widely applicable to any class of nanoparticles with size-, shape- or composition-dependent optical properties. In addition, we obtained distributions of the lateral diameter and the number of layers of molybdenum disulfide nanosheets via stepwise centrifugation and spectroscopic evaluation of the size fractions. Full article

Current orbit uncertainty propagation (OUP) and orbit determination (OD) methods suffer from drawbacks related to high computational burden, limiting their applications in deep space missions. To this end, this paper proposes a multivariate attention-based method for efficient OUP and OD of Earth–Jupiter transfer. First, a neural network-based OD framework is utilized, in which the orbit propagation process in a traditional unscented transform (UT) and unscented Kalman filter (UKF) is replaced by the neural network. Then, the sample structure of training the neural network for the Earth–Jupiter transfer is discussed and designed. In addition, a method for efficiently generating a large number of samples for the Earth–Jupiter transfer is presented. Next, a multivariate attention-based neural network (MANN) is designed for orbit propagation, which shows better capacity in terms of accuracy and generalization than the deep neural network. Finally, the proposed method is successfully applied to solve the OD problem in an Earth–Jupiter transfer. Simulations show that the proposed method can obtain a similar estimation to the UKF while saving more than 90% of the computational cost. Full article

The Internet of Things (IoT) presents great potential in various fields such as home automation, healthcare, and industry, among others, but its infrastructure, the use of open source code, and lack of software updates make it vulnerable to cyberattacks that can compromise access to data and services, thus making it an attractive target for hackers. The complexity of cyberattacks has increased, posing a greater threat to public and private organizations. This study evaluated the performance of deep learning models for classifying cybersecurity attacks in IoT networks, using the CICIoT2023 dataset. Three architectures based on DNN, LSTM, and CNN were compared, highlighting their differences in layers and activation functions. The results show that the CNN architecture outperformed the others in accuracy and computational efficiency, with an accuracy rate of 99.10% for multiclass classification and 99.40% for binary classification. The importance of data standardization and proper hyperparameter selection is emphasized. These results demonstrate that the CNN-based model emerges as a promising option for detecting cyber threats in IoT environments, supporting the relevance of deep learning in IoT network security. Full article