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Intelligent connected adaptive signal control considering pedestrians based on the EXP-DDQN algorithm

With the increasing integration of Connected and Automated Vehicles (CAVs) and Human-Driven Vehicles (HDVs) in urban traffic systems, along with highly variable pedestrian crossing demands, traffic management faces unprecedented challenges. This study introduces an improved adaptive signal control approach using an enhanced dual-layer deep Q-network (EXP-DDQN), specifically tailored for intelligent connected environments. The proposed model incorporates a comprehensive state representation that integrates CAV-HDV car-following dynamics and pedestrian flow variability. Additionally, it features an improved MC Greedy exploration strategy and prioritized experience replay, enabling efficient learning and adaptability in highly dynamic traffic scenarios. These advancements allow the system to dynamically adjust green light durations, phase switches, and pedestrian phase activations, achieving a fine balance between efficiency, safety, and signal stability. Experimental evaluations underscore the model’s distinct advantages, including a 26.9% reduction in vehicle-pedestrian conflicts, a 31.83% decrease in queue lengths, a 32.52% reduction in delays compared to fixed-time strategies, and a 35.17% reduction in pedestrian crossing wait times. Furthermore, EXP-DDQN demonstrates significant improvements over traditional DQN and DDQN methods across these metrics. These results underscore the method’s distinct capability to address the complexities of mixed traffic scenarios, offering valuable insights for future urban traffic management systems.

Fungal diversity and network analysis in rhizosphere soil of Atractylodes macrocephala across different cultivation regions

First insight into oral health misinformation in Jordan; an analysis of web content and information-seeking behaviors

Background Integrating the internet into daily life has profoundly influenced the public's behavior of seeking health information. Free access to cyberspace created a fertile environment for the spread of oral health misinformation, which can have a detrimental impact on the public’s oral health. The prevalence of oral health misinformation in Jordan has not been investigated; therefore, it is crucial to understand how oral health misinformation originates and what contributes to its dissemination. Objectives This study aims to examine the prevalence of oral health misinformation published on web pages in Jordan and to offer insight into the public's information-seeking behaviors regarding oral health. Methods This study is a mixed methods infodemiological analysis of oral health misinformation. A systematic content analysis was executed on web pages published in the Arabic language in Jordan from 2019 to 2023. Results 704 web pages were retrieved, of which 320 relevant web pages were included in the content analysis. Among these, 193 web pages (60.3%) published oral health misinformation. Publishers without a professional background published 185 web pages (95.9%) of the total misinformation-expressing web pages. According to the dental field, the highest frequency of misinformation occurred in oral medicine-101 web pages (52.3%). The validity of published oral health information was significantly influenced by the publishers’ interest (P = 0.006), the articles’ main themes (P = 0.005), and the publishers' professional background (P < 0.001). Contextual analysis of oral health misinformation showed significant differences among dental fields (P = 0.019), with the most frequent occurences related to causes (18.8%), home remedies (15.7%), and treatment (15.5%). Geographical variations in interest in oral health searches were observed across Jordanian governorates (P < 0.001), and temporal trends in interest varied significantly across the five-year period(P = 0.019). Conclusion The findings of this study suggest a need for public health interventions to restrict the dissemination of oral health misinformation.

Comprehensive analysis of cuproptosis and m6A-Target gene signatures for diagnostic significance and immune microenvironment characterization in polycystic ovary syndrome

LRRT*: A robotic arm path planning algorithm based on an improved Levy flight strategy with effective region sampling RRT*

Aiming at the problems of blind sampling points and slow planning speed of path planning Rapidly-exploring Random Trees algorithm, an effective region sampling Levy Rapidly-exploring Random Trees algorithm (LRRT*) is proposed based on the improved Levy flight strategy. Divide the entire path planning process into two stages: quickly finding the initial path and optimizing the path. Goal oriented strategy is used to explore the path when finding the initial path quickly. The Levy flight strategy is used to regenerate nodes after obstacles are encountered to improve the quality of the expansion points. They can quickly plan a collision-free path. In the phase of optimizing the initial path using the effective region sampling method, each sampling is only sampled around the initial path. Meanwhile, node rejection strategy is introduced to reduce the number of collision detection and accelerate the convergence speed. In 2D and 3D environments, the LRRT* algorithm reduces the initial path planning time by 17.6% and 91.9% respectively compared to the RRT* algorithm, and shortens the average planning time by 12.3% and 65.5%, and the path smoothness is 3.4% and 79.4% shorter respectively. Applying the LRRT algorithm to a robotic arm allows for the planning of collision-free paths.

Temporal variation in discriminating Acacia species using optical and radar data

Atypical nucleus pulposus migration and calcification: A specific radiographic sign for lumbar rheumatoid spondylitis

Objective This study aimed to characterize a specific radiographic manifestation of lumbar rheumatoid spondylitis. Methods and materials The patients diagnosed with lumbar rheumatoid spondylitis who underwent posterior lumbar fusion surgery between 1/6/2019 and 30/4/2023 in the Department of Orthopedic Surgery in our hospital were retrospectively studied (RA group). The patients diagnosed with lumbar disc herniation with nucleus pulposus migration (cranial or caudal) were also collected for comparison (control group). The clinical data and radiographic manifestations were compared and analyzed. Results A total of 14 patients in the RA group and 36 patients in the control group were enrolled in the current study. In the RA group, seven patients had nucleus pulposus migration, among whom five patients exhibited distinct calcification (5/7, 71.4%). Of the 36 patients in the control group, 10 patients demonstrated migrated nucleus pulposus calcification (10/36, 27.8%). The migrated nucleus pulposus in the RA patients exhibited diffuse calcification, while the migrated nucleus pulposus in the control group exhibited spot-like or shell-like calcification. In addition, nucleus pulposus migration and calcification in the RA group were more likely to occur in older patients, affect the higher lumbar levels and combine with intervertebral space collapse compared with the control group. Conclusions Nucleus pulposus migration and calcification is specific in RA patients. It may be a characteristic radiographic sign to establish a lumbar rheumatoid spondylitis diagnosis. The potential mechanism is still unclear and need to be further explored.

Study on the evolution mechanism of damage to overburden fissures of repetitive mining of close coal seam groups by positive faults

Abstract For the safety of coal mines and the efficient use of gas resources, precise identification of gas transmission routes and enrichment zones is essential. The mining of the coal seam causes many fissures in the overburdened rock, and the evolution of mining fissures is intimately linked to gas transport channels.In order to study the characteristics of overburden fissures in the mining of close coal seam groups under the influence of faults, Shucheng Mining Area in Guizhou as a Research Context, Research using physical similarity simulation tests and numerical simulation methods. The results show that the location of the overburden rupture line interacts with the faults and together they construct a stable inverted triangular overburden stability structure; Given the existence of faults, the upper seam is subjected to greater stress during mining compared to the lower seam, which makes the fissure development process in the upper seam more active.Mining significantly affects the stress distribution of the overlying rock layer of the upper disc coal seam. The stress of the upper disc coal seam increases with the advancement of mining of the lower disc coal seam, and the stress suffered by the side with fewer fault gaps is greater. The results of the study can provide a theoretical basis for mining close coal seam groups in fault tectonic regions, and promote coal mines to achieve safe and efficient use of gas.

Use of spectral indices and photosynthetic parameters to evaluate the growth performance of hydroponic tomato at different salinity levels

Conventional methods for measuring plant physiological parameters are expensive and time-consuming, and this has promoted the use of optical and sensing techniques. Therefore, this study was conducted to investigate the effect of salinity on the performance of hydroponic tomato plants, based on optical and sensing techniques (i.e., spectral indices and photosynthetic parameters), as well as fruit yield. Four spectral vegetation indices-VIs (Moisture Stress Index “MSI”, Canopy Response Salinity Index “CRSI”, Normalized Difference Nitrogen Index “NDNI” and Green Leaf Index “GLI”) were calculated using spectral measurements collected from tomato plant leaves. Also, four photosynthetic parameters (Net photosynthetic rate “PN”, Water use efficiency “WUE”, Transpiration rate “Tr” and Total stomatal conductance “Gs”) were measured from the same tomato plant leaves. Measurements were recorded for tomato plants grown under three salinity levels (Salinity-1; 2.5 dS m-1), (Salinity-2; 4.0 dS m-1), and (Salinity-3; 6.5 dS m-1) at different growth stages represented by days after transplantation (DAT), as 35 DAT (vegetative stage), 50 DAT (1st cluster flower stage), 60 DAT (3rd cluster flower stage), 75 DAT (fruit development stage) and 85 DAT (fruit ripening stage). Results showed that tomato plants were significantly affected by the imposed salinity treatments. Where, tomato plants treated with salinity-1 was healthier compared to salinily-3 treated plants. This has been concluded from the results of the studied VIs, where the highest mean values of MSI (0.543) and CRSI (0.779) were associated with salinity-3, along with low values of GLI (0.353) and NDNI (0.220), indicating high salinity stress. However, the highest mean values of both NDNI (0.232) and GLI (0.386) were observed for salinity-1, indicated healthy condition. It also proven with the studied photosynthetic parameters, with the highest mean values of PN (9.8 µmol CO2 m-2 s-1),Gs (0.117 mmol H2O m-2 s-1) and Tr (2.236 mmol H2O m-2 s-1) were associated with salinity-1, While the lowest mean values of PN (8.3 µmol CO2 m-2 s-1), Gs (0.102 mmol H2O m-2 s-1) and Tr (1.902 mmol H2O m-2 s-1) were recorded for the plants treated with salinity-1. Moreover, the total tomato fruit yield also decreased significantly at salinity-3 compared to salinity-1.

The impact of perceived restorative destination environments on tourists’ willingness-To-Pay for environmental protection

Machine learning techniques for continuous genetic assignment of geographic origin of forest trees

Origin tracking is important to ensure use of the right seed source and trade with legally harvested timber. Additionally, it can help to reconstruct human-caused historical long-distance seed transfer and to spot mislabelling in forest field trials. So far, genetic assignment approaches were mostly discrete, assigning test samples to predefined groups. The main limitation of this approach is the justification of these discrete groups when genetic variation across the landscape is actually continuous. Here, we compare the accuracy of five continuous assignment methods. Specifically, we test a nearest neighbour method (NN), direct gaussian process regression (GPR-D) using the radial basis kernel function, grid based gaussian process regression (GPR-G) applying the Matérn kernel function, genomic prediction (GP) and deep learning (DL), using two genome-wide single nucleotide polymorphism (SNP) datasets of trees from across Europe. The first dataset comprises 30,000 SNPs from 865 European beech (Fagus sylvatica) trees, the second dataset consists of 381 SNPs from 1,883 pedunculate oak (Quercus robur) trees. The accuracy, as measured by the geographic distance between true and predicted locations, was highest for the GPR-G and DL methods with the beech dataset with a median distance of only 55 km and 76 km, respectively. For the oak data GPR-G and DL also performed best with median distances of 263 km and 278 km, respectively. The relative error (distance/max distance among tree pairs) was below 8% for 90% of all samples for the best method for both datasets. We detected 35 individuals and 10 groups as outliers in the beech data and 27 individuals and 18 groups in the oak data. These outliers may be caused by mislabelling or historical human-caused long distance seed transfer. We discuss the differences in performance of the approaches and highlight future applications and potential for further improvements.

Electroencephalography and optical neuromonitoring predict short-term outcomes in neonates undergoing therapeutic hypothermia for hypoxic-ischemic encephalopathy

Do chimpanzees (Pan troglodytes) mentally represent collaboration?: Action-learning and communication in a partnered task

Non-human primates engage in complex collective behaviours, but existing research does not paint a clear picture of what individuals cognitively represent when they act together. This study investigates chimpanzees’ capacity for co-representation. If individuals represent others’ actions as they relate to their own during a collaborative task, they should more easily learn to reproduce that action when their roles are switched. In a between-subjects design, we trained ten chimpanzees (Pan troglodytes) on a sequential task, in which the first action is performed by either a human partner or a non-social object, and the second action is performed by the subject. We then imposed a breakdown in the action sequence, in which subjects could perform both actions themselves, but received no help from the experimenter or object. We measured subjects’ success in reproducing the first action in the sequence, as well as their attempts to recruit the experimenter’s help using requesting gestures. We found no overall difference in subjects’ ability to perform the first action in the sequence, but we observed significant qualitative differences in their solutions: individuals in the partnered condition replicated the experimenter’s action, while those in the non-social condition achieved the same end using alternative methods. This difference in solution style could indicate that only those chimpanzees in the partnered condition mentally represented the experimenter’s action during the collaborative task. We caution, however, that given the small number of subjects who solved the task, this result could also be driven by individual differences. We also found that subjects consistently produced communicative gestures toward the experimenter, but were more likely to do so after exhausting all actions they could take alone. We suggest that these patterns of behaviour highlight a number of key empirical considerations for the study of coordination in non-human primates.

Pharmacovigilance analysis of spondyloarthritis following HPV vaccination based on the VAERS database

Screening and validation of 3’-Methoxydaidzein as a therapeutic agent in ulcerative colitis based on disulfidptosis-associated molecular clusters

Background Ulcerative colitis (UC) is a recurrent inflammatory condition of the bowel with a multifaceted pathogenesis, including programmed cell death, oxidative stress, and immune-mediated inflammation. As a recently identified type of cell death, disulfidptosis has an unclear role in UC. Methods We analyzed clusters of disulfidptosis-related genes (DRGs) and immune cell infiltration in 361 patients with UC from the GSE73661and GSE92415 datasets. Differentially expressed genes (DEGs) were identified using unsupervised clustering methods, and hub genes were selected using machine learning algorithms. Additionally, potential key components of potential traditional Chinese medicines for the treatment of UC were predicted based on hub genes. Finally, experimental validation was performed through qRT-PCR, western blotting, and immunohistochemistry. Results We identified two molecular clusters related to disulfidptosis, each showing significant heterogeneity in gene expression and immune profiles. Hub genes associated with disulfidptosis, CXCL1, HMGCS2, AQP8, and SLC26A2, were further screened and validated. Additionally, potential traditional Chinese medicines for UC were predicted. 3’-Methoxydaidzein (MHD), a key constituent of Puerariae Radix, inhibited LPS-induced inflammatory responses in Caco2 cells and alleviated DSS-induced colonic injury in UC mice via upregulation of SLC26A2. Conclusion DRGs demonstrate strong discriminatory power in distinguishing UC subtypes. Cluster with high expression of SLC26A2 showed a UC phenotype with a milder degree of damage. Additionally, we identified the hub gene SLC26A2 as playing a significant role in UC, and MHD demonstrates potential as a targeted therapeutic strategy for UC.

Publisher Correction: Establishment and characterization of a novel immortalized human aortic valve interstitial cell line

Do soil health indicators predict carbon and nitrogen functional stability under drought and heat?

Healthier soils are often assumed to retain function better under climate stress. However, links between common soil health indicators and soil functional resilience to stress are elusive. Our goal was to link soil health status with stress response by quantifying the multifunctional carbon (C) and nitrogen (N) cycling response of soils under different management (forest, conventional, or organic) to drought or combined drought and heat stress. We monitored several C and N cycling functions during a 28-d stress and 28-d recovery period and calculated resistance and resilience indices for each function to create multifunctional C and N cycling indices. We related these indices to baseline soil health properties and microbial community characteristics. Traditional soil health indicators (e.g., total organic C, and microbial biomass and activity) were closely associated with N cycle resilience to drought stress. Indicators that distinguished forest from arable soils (e.g., low pH and chemical fertility, and high porosity, relative abundance of Basidiomycetes, and high C to N ratio) were generally positively related to drought resistance but negatively related to resilience. Bacterial and fungal community diversity were unrelated to either resistance or resilience for either cycle. Adding heat to drought created a strong N cycle stress which affected all sites similarly, and soil baseline properties were not related to either resistance or resilience. For both C and N cycles, stress type was the major determinant of resistance while management was the major determinant of resilience. Our results show that response to drought stress differs depending on the temperature at which it occurs, and that pH, chemical fertility, and SOM are all important components in stress response but affect C and N cycles differently.

Calibration-free picosecond LIPS for quantifying heavy metals in soils near Egyptian industrial sites

Abstract Excessive fertilizer and chemical usage have led to soil contamination by toxic heavy metals near the Abu-Zaabal industrial complex in Egypt. We introduce a groundbreaking calibration-free methodology using ultrafast Picosecond Laser-Induced Plasma Spectroscopy (CF-Ps-LIPS) for quantifying contaminant elements (Cd, Zn, Fe, Ni) in soils near Egypt’s Abu-Zaabal industrial complex. This study pioneers applying 170 ps laser pulses (Nd: YAG, 1064 nm) to achieve calibration-free analysis, eliminating matrix-matched standards and offering ± 1% agreement with ICP-OES. By integrating plasma diagnostics (electron density Ne = 1.2–1.5 × 1017 cm− 3 and temperature Te = 8508–10,275 K), we establish CF-Ps-LIPS as a rapid, minimally invasive tool for on-site environmental monitoring, validated through spatial contamination gradients linked to wind patterns. Concentrations of Cd (25.1–136.5 mg/kg), Zn (19.8–146.9 mg/kg), Fe (59.7–62 mg/kg), and Ni (119.4–157.8 mg/kg) were analyzed across seven sampling sites. The seventh site was used as a test sample of unknown concentration to validate CF-Ps-LIPS. Utilizing the Boltzmann distribution with plotting techniques enables precise plasma electron density and temperature determination under local thermodynamic equilibrium (LTE) conditions. The CF-Ps-LIPS study revealed significant concentration variations dependent on trace metal type, sampling location, and facility orientation. The CF-Ps-LIPS method provides calibration-free, rapid, and accurate detection of metal contaminants in Egyptian soils for the first time. This methodology significantly advances environmental monitoring and soil contamination analysis, allowing on-site assessments with higher efficiency and reliability.

Behavioral and Neural correlates of Post-STROKE Fatigue: A randomized controlled trial protocol

Introduction Post-stroke fatigue (PSF) is highly prevalent and lacks of effective management. Recent evidence suggest the use of transcranial direct current stimulation (tDCS) to reduce PSF. However, the effect was not lasting and the working mechanisms was unclear. The purpose of this study is to determine the behavioral and neurophysiological effects of five daily sessions of tDCS on PSF. Methods and analysis This will be a double-blind randomized controlled trial targeting an enrollment of 32 participants with subacute-chronic stroke and significant fatigue (average Fatigue Severity Scale (FSS) > 4). Participants will be equally randomized to either anodal tDCS or sham tDCS groups. The anodal tDCS group will receive 20 minutes of 2-mA anodal tDCS applied to the ipsilesional primary motor cortex (M1) for five consecutive days. The sham tDCS group will receive the same protocol except there will be no active current delivered. Outcome assessments will take place at baseline (prior to randomization), immediately after the intervention, and at one-month follow-up. The primary behavioral outcome will be the FSS and the primary neurophysiological outcome will be an input-output curve of motor cortex excitability derived using transcranial magnetic stimulation. Secondary behavioral outcomes will include Fatigue Scale for Motor and Cognitive Function, Visual Analog Scale-Fatigue, Borg Rating of Perceived Exertion, and Paas Mental Effort Rating Scale. Secondary neurophysiological outcome will be the functional connectivity of the fronto-striato-thalamic network acquired using resting state functional Magnetic Resonance Imaging (MRI). Repeated measure ANOVA or ANCOVA will be conducted for all outcomes to compare the change between groups. Discussion Little is known about effective treatments for PSF and the underlying mechanisms of PSF. tDCS is a promising tool to provide targeted intervention to reduce PSF symptoms. However, its lasting effect and working mechanism on PSF is elusive. The results of this clinical trial will offer critical information for PSF management and investigation. Trial registration This trial was registered in February 1 2024 with ClinicalTrials.gov under the registration number NCT06088914.

Serum growth differentiation factor 15 associates with extra-glandular manifestations and disease activity of primary Sjögren’s syndrome