Search Results (4,464)

Bassia scoparia is a widespread weedy species in the temperate regions of the world and is valued as a medicinal and ornamental plant. To date, the taxonomic concept of B. scoparia remains insufficiently studied due to a limited number of samples used in the previous phylogenetic analyses. To solve the taxonomy of the B. scoparia complex, we constructed a new phylogeny based on the nuclear ribosomal internal transcribed spacer (ITS), plastid intergenic spacer atpB-rbcL, and plastid region rpL16 intron sequences for numerous samples with diverse morphology. Our analysis revealed a close proximity and intermixed positions of the samples of the B. scoparia group with various morphology. Because of this polyphyly, we prefer to broadly delimit the species. An updated nomenclature of B. scoparia is provided including four new synonyms: Bassia angustifolia, B. littorea, Kochia albovillosa, and K. scoparia subsp. hirsutissima. In its new circumscription, B. scoparia encompasses populations with glabrous or variously hairy leaves and perianths. The original material of Kochia sieversiana, previously considered a species with hairy leaves and inflorescences, has the same diagnostic characters as in B. scoparia s.str. The correct name for more hairy-leaved plants is B. scoparia var. subvillosa. Plants with hairy perianths known as Kochia albovillosa and K. scoparia subsp. hirsutissima have a restricted distribution in Central Asia and South Siberia and have never been recorded as alien in other regions; they can be classified as a separate variety, B. scoparia var. hirsutissima. The ornamental variant of oblong or pyramidal shape may be called B. scoparia var. trichophila. Bassia scoparia is often confused with a similarly looking relative, B. indica, especially in North Africa, a region where secondary ranges of both species overlap. Phylogenetically, these species are sister groups; they share some morphological characters but have different primary distribution ranges. We traced a recent expansion of B. indica in the Mediterranean with the first record reported from the European continent (Spain) and uncovered various introduction pathways of the species in this region. Full article

This study applies panel techniques with macro variables to analyze the connection between date palms production and water management in GCC countries using the Bayesian random and mixed effects models. Also, this study utilizes panel-corrected standard error (PCSE) and feasibly generalized least squares (FGLSs) methods to test the robustness and verify the Bayesian results. By utilizing a Bayesian longitudinal model, this study not only fills in a critical research gap but also provides a fresh perspective on the dynamics of water management practices and their impact on date palm cultivation over time. The results of this study confirm that the posterior means for coefficients of the water efficiencies for all purposes are positive with a magnitude of 11%, 28%, and 125%, respectively, for agriculture, services, and industrial purposes, determining that the Bayesian inference is efficient and reasonable. This result indicates the fit of the model, the validation of the results, and the knowledge that decision-making can suggest water management strategies for date palm cultivation. The findings from the PCSE and FGLSs models confirm that efficient water use in services (β = −0.329, significant at 1%) and agriculture (β = −2.834, significant at 1%) can lead to increased competition for limited water resources, reducing water availability for palm cultivation. Water use efficiency for industrial purposes (β = 0.503, significant at 1%) shows a positive relationship. Industrial water efficiency practices, such as water recycling, can help preserve water resources, managing more water available for agricultural activities. In addition, industrial water efficiency initiatives often involve technological innovations that can be applied to agriculture, improving water management practices in palm production. Developing and implementing comprehensive strategies, such as Integrated Water Resource Management (IWRM), that consider water needs for all purposes and establish coordinated water distribution plans to ensure sustainable water use practices across various sectors are highly recommended for policymakers and stakeholders. Also, further research must be performed to investigate the implications of climate change on water resources and date production to develop adaptation strategies that enhance the resilience of date palm cultivation. This will help the development of sustainable agricultural practices that balance water conservation with agrarian productivity. Full article

Objective: Head and neck cancer (HNC) is a common cancer represented by nearly 80% oral cavity (OC) and oropharyngeal cancers (OPCs). Seventy percent of OPCs are associated with the Human Papilloma Virus (HPV). Immunotherapy holds the promise of future improvements in treating HNC patients. The study objective was to determine whether durvalumab immunotherapy alone, prior to curative surgery, would significantly impact the oral salivary microbiome in a pilot cohort of HPV negative and positive OC and OPC patients. Methods: Early stage OPC patients with squamous cell carcinoma were recruited: 5 HPV+ and 12 HPV−, and treated with two or three administrations of durvalumab given every two weeks, prior to surgery. Unstimulated saliva was collected and processed for bacterial DNA Isolation and V1–V3 16S rRNA gene next generation sequencing, taxa identification, and determination of relative abundance at four time points: baseline prior to surgery (A) and weekly durvalumab treatment timepoints (B, C, and D). Alpha- and beta-diversity differences for the time series were determined in Primer_v7. MaAsLin2 in R was used to identify potential associations with the time series and/or HPV status. Linear decomposition model (LDM) R-package was used to investigate the relationship of salivary microbiome with HPV status. ROC curves were plotted for significant species in common between MaAsLin2 analysis and FDR-corrected Mann-Whitney U-test using XLSTAT. Results: Longitudinal microbiome data across four timepoints (A, B, C, D) were obtained (HPV+: n = 18 samples; HPV−: n = 46 samples). A total of 416 taxa were detected across all time points, ranging from 336 to 373 per group. There were no differences in α- and β-diversities for all longitudinal comparisons (C vs. BCD, AB vs. CD, or A vs. B, C, or D). However, comparison A vs. D showed a significant increase in Prevotella melaninogenica relative abundance, a potentially pathogenic species able to evade the immune system, after three weeks treatment. Moreover, differences in beta-diversity based on HPV status were found. LDM analysis identified Veillonella atypica, overrepresented in HPV+ group, as the top species accounting for HPV status. Conclusions: The results are consistent with findings from previous studies investigating HNC patients treated with chemoradiotherapy. More research is needed to understand possible impact of immunotherapy on opportunistic bacterial species, although negligible impact from durvalumab treatment on salivary microbiome was observed. Full article

Background/Objectives: Localization deficit is often said to be a symptom of Auditory Processing Disorder (APD). However, no clinically viable assessment of localization ability has been developed to date. The current study presents pilot data for a new assessment of absolute auditory localization using headphones. Methods: Speech phrases encoded with non-individualized head-related transfer functions (HRTF) using real-time digital processing were presented to two cohorts of participants with normal hearing. Variations in the simulated environment (anechoic and reverberant) and signal to noise ratio (SNR) were made to assess each of these factors’ influences on localization performance. Experiment 1 assessed 30 young adults aged 21–33 years old and Experiment 2 assessed 28 young adults aged 21–29 years old. All participants had hearing thresholds better than 20 dB HL. Results: Participants performed the localization task with a moderate degree of accuracy (Experiment 1: Mean RMS error = 25.9°; Experiment 2: Mean RMS error 27.2°). Front–back errors (FBEs) were evident, contributing to an average RMS error that was notably elevated when compared to similar free-field tasks. There was no statistically significant influence from the simulated environment or SNR on performance. Conclusions: An exploration of test viability in the pediatric and APD-positive populations is warranted alongside further correction for FBEs; however, the potential for future clinical implementation of this measure of absolute auditory localization is encouraging. Full article

Simultaneous Localization and Mapping (SLAM) technology has garnered significant interest in the robotic vision community over the past few decades. The rapid development of SLAM technology has resulted in its widespread application across various fields, including autonomous driving, robot navigation, and virtual reality. Although SLAM, especially Visual–Inertial SLAM (VI-SLAM), has made substantial progress, most classic algorithms in this field are designed based on the assumption that the observed scene is static. In complex real-world environments, the presence of dynamic objects such as pedestrians and vehicles can seriously affect the robustness and accuracy of such systems. Event cameras, which use recently introduced motion-sensitive biomimetic sensors, efficiently capture scene changes (referred to as “events”) with high temporal resolution, offering new opportunities to enhance VI-SLAM performance in dynamic environments. Integrating this kind of innovative sensor, we propose the first event-enhanced Visual–Inertial SLAM framework specifically designed for dynamic environments, termed E2-VINS. Specifically, the system uses visual–inertial alignment strategy to estimate IMU biases and correct IMU measurements. The calibrated IMU measurements are used to assist in motion compensation, achieving spatiotemporal alignment of events. The event-based dynamicity metrics, which measure the dynamicity of each pixel, are then generated on these aligned events. Based on these metrics, the visual residual terms of different pixels are adaptively assigned weights, namely, dynamicity weights. Subsequently, E2-VINS jointly and alternately optimizes the system state (camera poses and map points) and dynamicity weights, effectively filtering out dynamic features through a soft-threshold mechanism. Our scheme enhances the robustness of classic VI-SLAM against dynamic features, which significantly enhances VI-SLAM performance in dynamic environments, resulting in an average improvement of 1.884% in the mean position error compared to state-of-the-art methods. The superior performance of E2-VINS is validated through both qualitative and quantitative experimental results. To ensure that our results are fully reproducible, all the relevant data and codes have been released. Full article

Background/Objectives: Aniridia is a rare congenital disorder characterized by structural and functional abnormalities in ocular development due to PAX6 haploinsufficiency, leading to complications such as aniridia-associated keratopathy (AAK). Meibomian gland dysfunction (MGD), a prevalent yet underexplored condition in aniridia, exacerbates tear film instability and chronic ocular surface inflammation, contributing to AAK progression. This study investigates the relationship between MGD severity and AAK in individuals with aniridia. Methods: This prospective randomized study included 113 participants (53 with aniridia and 60 controls). Comprehensive ophthalmic evaluations, including noninvasive meibography, were performed. The MGD severity was assessed using a standardized meiboscore scale, while the AAK severity was classified according to established clinical grading criteria. Statistical analyses, including Spearman’s correlation and chi-squared tests, were used to evaluate the relationships among MGD, AAK, and visual acuity. Results: MGD was significantly more prevalent and severe in the aniridia group compared to controls (p < 0.00001). A strong positive correlation was observed between MGD severity and AAK grade (r = 0.72, p < 0.00001), with both conditions associated with reduced best-corrected visual acuity (BCVA; r = −0.80 and −0.86, respectively, p < 0.0001). Age was positively correlated with MGD (r = 0.47, p = 0.0004) and AAK (r = 0.34, p = 0.0123), with gender-specific trends observed in females. Conclusions: MGD significantly contributes to AAK progression and visual impairment in aniridia. Meibography offers valuable insights into MGD severity, supporting early diagnosis and targeted interventions. Addressing MGD through tailored therapies could mitigate AAK progression and improve visual outcomes in this challenging condition. Full article

This study investigates the position of Côte d’Ivoire’s cocoa industry within the global production chain and identifies key influencing factors from 1960 to 2024. Using a Vector Error Correction Model (VECM), the research evaluates the effects of economic and climate variables—cocoa bean production, global cocoa prices, GDP contributions, domestic cocoa grindings, rainfall, and temperature—on cocoa exports. The findings reveal that a 1% increase in global cocoa prices decreases exports by 0.45%, indicating significant price sensitivity. Cocoa bean production accounts for 42.39% of export variance over the long term, while GDP contributions (0.88%) and domestic cocoa grindings (0.34%) enhance competitiveness and value addition. Rainfall negatively impacts productivity, underscoring vulnerabilities to climate variability, whereas temperature has a short-term positive effect on export performance (0.12%). Short-term dynamics demonstrate rapid adjustments toward equilibrium, with adjustment speeds of 41.23% for Côte d’Ivoire and 37.21% for Ghana. The study highlights Côte d’Ivoire’s dependence on raw cocoa exports and its susceptibility to price volatility and climate risks. By comparing Côte d’Ivoire with Ghana, the analysis underscores the advantages of robust domestic processing policies. To ensure long-term sustainability, the study recommends expanding domestic cocoa processing, adopting agroforestry practices to mitigate climate risks, and investing in infrastructure to boost competitiveness and resilience. Full article

Capsule endoscopy is a common method for detecting digestive diseases. The location of a capsule endoscope should be constantly monitored through a visual inspection of the endoscopic images by medical staff to confirm the examination’s progress. In this study, we proposed a computer-aided analysis (CADx) method for the localization of a capsule endoscope. At first, a classifier based on a Swin Transformer was proposed to classify each frame of the capsule endoscopy videos into images of the stomach, small intestine, and large intestine, respectively. Then, a K-means algorithm was used to correct outliers in the classification results. Finally, a localization algorithm was proposed to determine the position of the capsule endoscope in the alimentary tract. The proposed method was developed and validated using videos of 204 consecutive cases. The proposed CADx, based on a Swin Transformer, showed a precision of 93.46%, 97.28%, and 98.68% for the classification of endoscopic images recorded in the stomach, small intestine, and large intestine, respectively. Compared with the landmarks identified by endoscopists, the proposed method demonstrated an average transition time error of 16.2 s to locate the intersection of the stomach and small intestine, as well as 13.5 s to locate that of the small intestine and the large intestine, based on the 20 validation videos with an average length of 3261.8 s. The proposed method accurately localizes the capsule endoscope in the alimentary tract and may replace the laborious real-time visual inspection in capsule endoscopic examinations. Full article

This study explores the effectiveness of the Movement System Impairment (MSI) model compared to traditional physiotherapy for treating knee pain. Fifty patients with unilateral knee pain participated, with their femur, tibia, and knee alignment assessed in nine functional positions. Evaluations included the Tegner Activity Scale, Knee Injury and Osteoarthritis Outcome Score (KOOS), muscle power, extensibility, and pain levels. Patients were randomly assigned to either the MSI treatment group, which focused on identifying and correcting faulty movements, or a routine physiotherapy group that received general strengthening and stretching exercises. Results indicated that both treatment approaches improved muscle power in hip abductors and lateral rotators, as well as scores on the Tegner Activity Scale and the KOOS. Notably, the MSI group demonstrated greater improvements in the muscle power of the hip lateral rotators and knee extensors and a significant reduction in knee pain during walking compared to the routine group (p = 0.005). In conclusion, both treatments enhanced pain, function, and muscle strength, while the MSI model significantly reduced knee pain in walking and improved hip and knee muscle power compared to routine physiotherapy. Full article

Background/Objectives: Functional seizures (FSs) are paroxysmal, time-limited events with motor, sensory, autonomic, or cognitive manifestations related to pathophysiological processes other than abnormal electric discharges in the brain. However, these seizures are often followed by different psychiatric comorbidities. Their impact on the overall quality of life and the cofounding factors, especially the ones that can be treated, were the main investigation aims of this study. Methods: This study comprised 76 patients who were diagnosed with FSs. This study included patients who were diagnosed with FSs via video-EEG telemetry. We used the “Likert scale” from the QOLIE 31 questionnaire to evaluate patients’ subjective perception of their quality of life. We researched the association of various clinical factors with the subjective QoL score. Results: A statistically significant marginal association was shown for seven variables, four of them with a positive association (subjective perception of disease severity, belief in treatments’ positive effects, functional seizure cessation, and not being afraid of next seizure) and three of them with a negative association (age at FS onset, depression symptoms, and current age of life). After Bonferroni correction for multiple testing only symptoms of depression stayed statistically significantly associated with outcome. Multivariable logistic regression following variable selection identified that six variables (age at FS onset, absence of psychiatric testing, perceiving oneself as mentally changed due to the disease, seizure severity, depressive symptoms, and fear of therapy side effects) were statistically significantly negatively associated with the outcome. Conclusions: It seems that patients who have FSs coexisting with depressive symptoms and also those with worse disease perception have less chances to be satisfied with their overall quality of life. Full article

Gear skiving is a highly productive method for manufacturing gears, especially internal gears. Circular arc internal gears are important parts of Rotary Vector (RV) reducers and harmonic reducers. This study presents the implementation of the gear skiving technique using a cylindrical tool to enhance the precision and efficiency of machining circular arc internal gears. By establishing the mathematical model for skiving a circular arc internal gear based on the conjugation theory of two surfaces, the barrel-shaped conjugate surface was solved by deducing gear meshing equations. A design method is proposed for a cylindrical skiving tool by utilizing the barrel-shaped conjugate surface with an off-center tool position along the axis. The cutting edge of the tool rake face was then obtained through cubic spline interpolation from the conjugate surface. The influence of the tool rake face offsets on the cutting rake angle and clearance angle is also discussed by defining the normal cutting plane of the tool. The correctness of the proposed cylindrical skiving tool was validated through simulation and actual skiving experiments. The experimental results demonstrated that the tooth profile error of the gear fell within ±0.004 mm, thereby satisfying the accuracy requirement for pin wheel housing gears. These research findings can contribute to advancements in novel cylindrical skiving tools. Full article

Most life activities of organisms are realized through protein–protein interactions, and these interactions are mainly achieved through residue–residue contact between monomer proteins. Consequently, studying residue–residue contact at the protein interaction interface can contribute to a deeper understanding of the protein–protein interaction mechanism. In this paper, we focus on the research of the trimer protein interface residue pair. Firstly, we utilize the amino acid k-interval product factor descriptor (AAIPF(k)) to integrate the positional information and physicochemical properties of amino acids, combined with the electric properties and geometric shape features of residues, to construct an 8 × 16 multi-feature map. This multi-feature map represents a sample composed of two residues on a trimer protein. Secondly, we construct a CNN-GRU deep learning framework to predict the trimer protein interface residue pair. The results show that when each dimer protein provides 10 prediction results and two protein–protein interaction interfaces of a trimer protein needed to be accurately predicted, the accuracy of our proposed method is 60%. When each dimer protein provides 10 prediction results and one protein–protein interaction interface of a trimer protein needs to be accurately predicted, the accuracy of our proposed method is 93%. Our results can provide experimental researchers with a limited yet precise dataset containing correct trimer protein interface residue pairs, which is of great significance in guiding the experimental resolution of the trimer protein three-dimensional structure. Furthermore, compared to other computational methods, our proposed approach exhibits superior performance in predicting residue–residue contact at the trimer protein interface. Full article

The autonomous navigation of unmanned ground vehicles (UGVs) in unstructured environments, such as agricultural or forestry settings, has been the subject of extensive research by various investigators. The navigation capability of a UGV in unstructured environments requires considering numerous factors, including the quality of data reception that allows reliable interpretation of what the UGV perceives in a given environment, as well as the use these data to control the UGV’s navigation. This article aims to study different PID control algorithms to enable autonomous navigation on a robotic platform. The robotic platform consists of a forestry tractor, used for forest cleaning tasks, which was converted into a UGV through the integration of sensors. Using sensor data, the UGV’s position and orientation are obtained and utilized for navigation by inputting these data into a PID control algorithm. The correct choice of PID control algorithm involved the study, analysis, and implementation of different controllers, leading to the conclusion that the Vector Field control algorithm demonstrated better performance compared to the others studied and implemented in this paper. Full article

Carbon nitrides are polymeric materials with a broad range of applications, including photocatalysis. Among them, graphitic carbon nitride (g-C₃N₄), a low-cost material, is an excellent photocatalyst under visible light irradiation owing to its features such as correct band positions, high stability and non-toxicity. g-C₃N₄ is a metal-free material that is easily synthesized by polymerizing nitrogen-rich compounds and is an efficient heterogeneous catalyst for many reaction procedures due to its distinctive electronic structure and the benefits of the mesoporous texture. In addition, in situ or post-modification of g-C₃N₄ can further improve catalytic performance or expand its application for remediating environmental pollution. Water pollution from organic compounds such as pesticides and pharmaceuticals is increasing dramatically and is becoming a serious problem around the world. These pollutants enter water supplies in a variety of ways, including industrial and hospital wastewater, agricultural runoff, and chemical use. To solve this problem, photocatalysis is a promising technology. Without the use of other oxidative chemicals, g-C₃N₄ uses renewable solar energy to transform harmful pollutants into harmless products. As a result, much recent research has focused on the photocatalytic activity of g-C₃N₄ for wastewater treatment. For this reason, the main objective of this paper is to contribute a chronological overview of the bibliometrics on g-C₃N₄ for the removal of pesticides and pharmaceuticals from water using the tools BibExcel, Bibliometrix and R-Studio IDE. A bibliometric analysis was performed using the Science Citation Index Expanded (WoS^©) database to analyze the scientific literature published in the field over the last 10 years. The results were used to identify limitations and guide future research. Full article

In the context of the Environmental Phillips Curve hypothesis, this study investigates the impact of unemployment on environmental quality in ten emerging economies with the highest carbon emissions, as identified in the International Monetary Fund’s 2015 World Economic Outlook. The primary aim of this study is to estimate the effects of income, natural gas usage, renewable energy usage, unemployment, and population size on carbon dioxide emissions in the selected countries. The study utilizes panel data from 1990 to 2019 and employs an Autoregressive Distributed Lag model (ARDL) to evaluate the short- and long-run relationships between these variables. Findings obtained using the Pooled Mean Group (PMG) estimator indicate that both income and population size have a significant positive impact on air pollution levels, whereas natural gas consumption and the use of renewable energy correlate with a decrease in emissions. The results support a negative correlation between unemployment and environmental degradation, aligning with the EPC. The error correction term suggests that the process returns to equilibrium in about 2.8 years. The findings are validated through robustness tests utilizing the Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) estimators. This study offers important insights for environmental policymaking in these emerging economies, emphasizing the importance of sustainable development strategies and green energy adoption. Full article