Numerical Data Research Articles

Ultrasound Characteristics of Carpal Tunnel Syndrome in the Spanish Population.

The aim of this study was to determine the cross-sectional area (CSA) (cm2) of the median nerve and its relationship with patient age and sex, together with the frequency of other qualitative ultrasound patterns in patients with carpal tunnel syndrome (CTS) in the Spanish population. An observational, cross-sectional, prospective, descriptive study was conducted among 79 patients diagnosed with CTS. The CSA of the median nerve was measured at the carpal tunnel inlet (CTI) and outlet (CTO) by ultrasound examination. In addition, qualitative variables such as hyperechoic enhancement, thickening, and loss of ultrasound pattern of the median nerve were measured. The images were analyzed using Image J software. The sample comprised 73.4% women and 26.6% men. In 68.4% of the cases, the dominant hand was involved. Professional cleaners and domestic staff were the most affected (22.8%). The CSA of the median nerve in patients with CTS was 0.16 cm2 (95% CI 0.15-0.18) at the CTI and 0.17 cm2 (95% CI 0.16-0.18) at CTO. At the CTI and CTO, the CSA showed significant differences in men under 50 years. As for the qualitative variables at the CTI and CTO, the most notable finding was the alteration in the ultrasound pattern, which was present in 87.3% and 91.1% of subjects, respectively. The median nerve CSA has a homogeneous value at the CTI and CTO in the Spanish population with CTS. These values show differences in terms of patient age and sex. The alteration in the ultrasound pattern of the nerve and the presence of hyperechoic reinforcement are the most frequent qualitative findings.

Machine Learning based Wildfire Area Estimation Leveraging Weather Forecast Data

Wildfires are increasingly destructive natural disasters, annually consuming millions of acres of forests and vegetation globally. The complex interactions among fuels, topography, and meteorological factors, including temperature, precipitation, humidity, and wind, govern wildfire ignition and spread. This research presents a framework that integrates satellite remote sensing and numerical weather prediction model data to refine estimations of final wildfire sizes. A key strength of our approach is the use of comprehensive geospatial datasets from the IBM PAIRS platform, which provides a robust foundation for our predictions. We implement machine learning techniques through the AutoGluon automated machine learning toolkit to determine the optimal model for burned area prediction. AutoGluon automates the process of feature engineering, model selection, and hyperparameter tuning, evaluating a diverse range of algorithms, including neural networks, gradient boosting, and ensemble methods, to identify the most effective predictor for wildfire area estimation. The system features an intuitive interface developed in Gradio, which allows the incorporation of key input parameters, such as vegetation indices and weather variables, to customize wildfire projections. Interactive Plotly visualizations categorize the predicted fire severity levels across regions. This study demonstrates the value of synergizing Earth observations from spaceborne instruments and forecast data from numerical models to strengthen real-time wildfire monitoring and postfire impact assessment capabilities for improved disaster management. We optimize an ensemble model by comparing various algorithms to minimize the root mean squared error between the predicted and actual burned areas, achieving improved predictive performance over any individual model. The final metric reveals that our optimized WeightedEnsemble model achieved a root mean squared error (RMSE) of 1.564 km2 on the test data, indicating an average deviation of approximately 1.2 km2 in the predictions.

Comprehensive analysis of endoscopic ultrasound (EUS) in mediastinal lesions: patient characteristics, diagnostic outcomes, safety, and efficacy: a multi-country study

BackgroundMediastinal lesions are tumors that develop mainly from structures commonly located in the three compartments of the mediastinum and the paravertebral areas. The diagnosis of these lesions is primarily based on imaging studies such as computed tomography and magnetic resonance imaging, which confirm the presence of the lesions and suspected metastatic disease. The study aims to determine the factors that determine the diagnostic accuracy and yield of endoscopic ultrasound (EUS) in diagnosing mediastinal lesions.MethodsThis multi-country study involved a list of centers providing EUS services across ten countries—the United Kingdom, Algeria, Egypt, Iraq, Kingdom of Saudi Arabia (KSA), Lebanon, Morocco, Pakistan, Romania, and Thailand. The appropriate information was collected regarding EUS-FNA and EUS-FNB procedures, including needle types, nature of lesion, needle passes, and complications of the techniques. The frequency/percentage conveyed data on the qualitative variables. The p-values were obtained using the Chi-square two-tailed exact test. The significance of the analysis was defined as p < 0.05. All the syntheses were performed using the Statistical Package for the Social Sciences (SPSS version 27; SPSS Inc., Chicago, IL, USA).ResultsA total of 439 participants were involved in this study, 255 (58.1%) males and 184 (41.9%) females, with a mean age of 55.73 ± 14.93 years. EUS-FNA and EUS-FNB diagnostic yield was influenced by needle types, needle size, number of needle passes, and lesion size. Among females, 44.6% were diagnosed with EUS-FNA, 42.8% with EUS-FNB, and 50.0% with EUS-FNA and FNB. Conversely, 55.4% of males were diagnosed using EUS-FNA and 57.2% with EUS-FNB. The association between gender and the diagnostic method, however, was statistically insignificant (p = 0.197). Needles with smaller diameters (22G) offered greater diagnostic yield than needles with larger diameters (19G). A minimal number of needle passes (between 2 and 4) showed a higher diagnostic yield than a higher number of needle passes (> 5). EUS-FNB accounted for a 0.5% complication incidence rate each for fever, pain, thoracic pain, and hemorrhage. EUS-FNA had no complication rate. Patients undergoing EUS-FNA, EUS-FNB, or both procedural examinations had no significant complications (p = 0.085).ConclusionThe diagnostic yield of EUS procedures is affected by needle types, number of needle passes, lesion size, and needle size. Besides, EUS-FNA and EUS-FNB are infrequently associated with various complication rates. These techniques are safe and offer higher diagnostic yield when utilized responsibly by endosonographers.

Ab initio investigation of a hypersonic double cone experiment.

This article presents a direct molecular simulation (DMS) of a reactive Mach 8.2 oxygen flow over a double cone geometry. The free stream conditions and article configuration generate a flow with thermal and chemical nonequilibrium, which are common attributes of hypersonic flight. This scenario was first studied experimentally at Calspan University of Buffalo Research Center's test facility. DMS is a particle method that uses quantum mechanically derived interaction potentials to simulate molecular collisions within a flow field. Since these interaction potentials are the only modeling inputs used in the simulation, all flow features can solely be attributed to the ab initio potential energy surfaces. Hence, providing a comparison of a hypersonic ground test and numerical data anchored to quantum mechanics. The fundamental nature of DMS is leveraged to investigate molecular level mechanisms prevalent in the flow, and comparisons with lower fidelity simulations are presented to highlight the role of these first principles calculations as benchmark solutions.

Can muscle synergies shed light on the mechanisms underlying motor gains in response to robot-assisted gait training in children with cerebral palsy?

BackgroundChildren with cerebral palsy (CP) often experience gait impairments. Robot-assisted gait training (RGT) has been shown to have beneficial effects in this patient population. However, clinical outcomes of RGT vary substantially from patient to patient. This study explored the hypothesis that clinical outcomes are associated with changes in muscle synergies in response to RGT.MethodsThirteen children with CP and Gross Motor Function Classification Scale (GMFCS) levels I–IV were recruited in the study. Children participated in a 6 week-RGT intervention and underwent clinical evaluations and gait studies—with focus on the analysis of electromyographic (EMG) data—pre- and post-training. Lower-limb muscle synergies were derived from the EMG recordings. Pre- vs. post-RGT clinical outcomes and muscle synergies were compared to explore potential relationships.ResultsThree and, less often, two muscle synergies were detected in study participants pre-RGT. Linear mixed effect models showed that composition of the muscle synergies and their temporal activation coefficients present deviations from normative data proportional to the severity of functional limitations (i.e., GMFCS levels, p < 0.01). At a group level, changes in muscle synergies pre- vs. post-RGT did not significantly correlate with changes in clinical outcomes (p > 0.05). However, it was observed that participants who displayed prominent changes in muscle synergies also displayed large improvements in clinical scores.ConclusionsGait impairments in children with CP were associated with muscle synergies that deviated from normative. Participants who demonstrated the most substantial improvements in clinical scores following RGT exhibited multiple changes in the muscle synergies. However, no statistically significant correlations were identified at the group level. Future studies relying on larger datasets are needed to further investigate this observation and potential underlying mechanisms.

Line integral compressed ultrafast photography for large time scale measurements

Line integral compressed ultrafast photography for large time scale measurements

On the reduction of imaging time-points for dosimetry in radionuclide therapy

BackgroundThe aim was to develop a theoretical framework for how errors in estimated activities propagate to a dispersion in time-integrated activity in radionuclide-therapy dosimetry and how this affects the comparison of radionuclide-therapy dosimetry schemes.MethodsFormulae for the variance of relative errors of estimated time-integrated activities and relative differences in time-integrated activities between measurement schemes when one or more time-points are removed were derived using the law of propagation of uncertainty for a population of time-activity-curve parameters. The formulae were derived under the assumptions of fixed coefficients of variation for estimated activities, and underlying mono-exponential curves. Analytical predictions were compared with results from numerical simulations and data for kidneys, liver, and spleen from a data-set of 18 patients treated with 177Lu-DOTA-TATE.ResultsThe dispersion in time-integrated activity is minimized if the time-points used for curve fitting have a large dispersion and are centered over the mean of τ=λeff-1 over the population, where λeff is the effective decay constant (i.e., the sum of the biological and physical decay constants). For large dispersions of decay constants in the population, the centering of time-points becomes gradually less important. The analytical expressions replicated the main trends from the numerical simulations. Furthermore, the analytical expressions predicted correctly the optimal reduced imaging schedule in 9 of 12 pairwise comparisons between schedules for patients.ConclusionsThe dispersion of errors and deviations in estimated time-activity curves can be predicted using simple formulae. These formulae have the potential to be used for optimization of dosimetry measurement schemes for established and new radiopharmaceuticals as long as the mean and dispersion of biological half-lives are known in the patient population.

Is it beneficial to use lateral protective crossing K-wires during medial open wedge high tibial osteotomy? A retrospective comparative study

BackgroundAn iatrogenic lateral hinge fracture is a common intraoperative problem that may occur during medial open wedge high tibial osteotomy (MOWHTO). This study aims to assess the significance of using additional crossing lateral K-wires and their advantage in protecting the lateral hinge during MOWHTO procedures.MethodsThe data of patients fulfilling the inclusion criteria who underwent MOWHTO between May 2021 and August 2022 were retrospectively evaluated. One group had additional lateral hinge crossing K-wires (+ MOWHTO group), while the other did not (-MOWHTO group). Both groups were assessed for rate of intraoperative lateral hinge fractures, knee injury and osteoarthritis outcome score − 12 (KOOS-12), medial proximal tibial angle (MPTA), time of union, and time to return to work. The outcomes were compared using the independent T-test for continuous variables and the Fisher Exact test for nominal variables. A p-value of < 0.05 was considered statistically significant for both tests.ResultsThe study included forty-eight patients; twenty-four in each treatment group. The mean follow-up durations were 30.5 ± 3.6 months for + MOWHTO and 31.6 ± 3.2 months for –MOWHTO (p = 0.26). There was no statistically significant difference regarding mean age, sex, KOOS-12, MPTA, and time of surgery between both groups. The + MOWHTO group had a faster time of union (p = 0.001), an earlier return to work (p = 0.002), and a lower rate of intraoperative lateral hinge fractures (p = 0.04).ConclusionThis study demonstrated that using additional crossing lateral K-wires during MOWHTO had a beneficial effect on reducing the rate of iatrogenic lateral hinge fractures, with a faster time of union, and an early return to work. The KOOS-12, MPTA, and mean operative time did not reveal significant differences between treatment groups.Level of evidenceretrospective cohort comparative study; level III.

МОРФОЛОГИЧЕСКИЕ ИЗМЕНЕНИЯ ПАРЕНХИМЫ СЕМЕННИКОВ ДИКОГО КАБАНА ПРИ ХЛАМИДИОЗЕ

A distinctive feature of chlamydia is the often-asymptomatic course of the disease, and without timely, high-quality diagnosis, the pathogen can persist in the body for many months and even years, causing serious diseases and spreading unhindered among animals. The purpose of research is to study the morphological changes in the parenchyma of the testes of wild boar with chlamydia. The objects of the study are the testes of wild boars aged 10–11 months. Histological sections were cut on an MZP-01 technomy microtome with a thickness of 5 microns. The finished histological preparations were stained with hematoxylin-eosin, according to Van Gieson and Pavlovsky. Using microscopy of histological preparations, the structure of the testes and changes in them were studied. Microscopic examinations were carried out with a Micros microscope at a magnification of 200–400 times in 10 fields of view of correctly oriented sections. At least 100 cells were studied. The established numerical data were subjected to variable statistical processing according to Student using MS Excel 2010. When analyzing morphometric studies of the spermatogenic epithelium of the convoluted seminiferous tubules of the testes, it was noted that in the convoluted tubules that retained their structure, the thickness of the spermatogenic epithelium was 14.19 ± 0.23 μm, the number of cells Sertoli are smaller than spermatogonium and spermatocytes. As a result of the studies, we can conclude that in sick animals, already at a young age, the parenchyma is affected with the development of alterative processes, in which there is a decrease in spermatogenesis, which negatively affects the function of the testes, and mechanical transmission of infectious agents during mating is possible.

A multi-dimensional decision framework based on the XGBoost algorithm and the constrained parametric approach

With the wide access to data and advanced technologies, organizations and firms prefer to use data-based and interpretable analytics to deal with uncertain and cognitive decision-making problems. In this regard, this study considers quantitative data and qualitative variables, to propose a multi-dimensional decision framework based on the nested probabilistic linguistic term sets. Under the framework, XGBoost algorithm, one of the machine learning methods, is conducted to capture the importance of attributes by using the historical data, and further calculate the attribute weights. The constrained parametric approach is used to establish membership functions of linguistic variables, and then get the objective probabilities in the linguistic model, so that we can obtain a scientific decision matrix. A case study concerning the ranking of bank credit is applied to present the proposed decision framework, and the process of making a rational decision. According to the comparative analysis, the proposed framework is flexible and the result is stable. Managers and policymakers determine the attribute weights by real data and choose the suitable decision method for a certain application. The framework provides an opportunity for capturing, integrating, analyzing data, and interpreting linguistic variables in the model to consider uncertain and cognitive decision at the both theoretical and practical levels.

Meningkatkan Gaya Hidup Sehat Pekerja Melalui Spiritualitas dan Kohesivitas Keluarga

Non-communicable diseases are emerging among the working-age population in Jakarta during early productive years. This trend may be attributed to a lack of attention to healthy lifestyles and the dynamics of social relationships. This study aimed to determine the significant roles of spirituality and family cohesiveness in the dimensions of a healthy lifestyle, including nutrition, physical activity, stress management, spiritual growth, interpersonal relationships, and health responsibility. The research was correlational in design, with a sample of 195 workers in Jakarta (M = 26.29 years) recruited through convenience sampling. Data were collected using the Health Promoting Lifestyle Profile-II, the Brief Measurement of Religiosity-Spirituality Scale, and the Brief Family Relationship Scale, and were analyzed using multiple regression techniques. The results showed that, simultaneously, spirituality and family cohesiveness significantly contributed to spiritual growth (R2 = 29%; F (2,192) = 39,152; p &lt; ,001), interpersonal relationship (R2 = 26,3%; F (2,192) = 34,183; p &lt; ,001), dimensi stress management (R2 = 16,7%; F (2,192) = 19,194; p &lt; ,05), dan nutrition (R2 = 4,6%; F (2,192) = 4,645; p &lt; ,05). These findings suggest that promoting healthy lifestyles among workers in Jakarta may benefit from an approach that integrates spirituality and family cohesiveness values

Predicting Energy Budgets in Droplet Dynamics: A Recurrent Neural Network Approach

ABSTRACTThe application of neural network‐based modeling presents an efficient approach for exploring complex fluid dynamics, including droplet flow. In this study, we employ Long Short‐Term Memory (LSTM) neural networks to predict energy budgets in droplet dynamics under surface tension effects. Two scenarios are explored: Droplets of various initial shapes impacting on a solid surface and collision of droplets. Using dimensionless numbers and droplet diameter time series data from numerical simulations, LSTM accurately predicts kinetic, dissipative, and surface energy trends at various Reynolds and Weber numbers. Numerical simulations are conducted through an in‐house front‐tracking code integrated with a finite‐difference framework, enhanced by a particle extraction technique for interface acquisition from experimental images. Moreover, a two‐stage sequential neural network is introduced to predict energy metrics and subsequently estimate static parameters such as Reynolds and Weber numbers. Although validated primarily on simulation data, the methodology demonstrates the potential for extension to experimental datasets. This approach offers valuable insights for applications such as inkjet printing, combustion engines, and other systems where energy budgets and dissipation rates are important. The study also highlights the importance of machine learning strategies for advancing the analysis of droplet dynamics in combination with numerical and/or experimental data.

Posting environmental risk: Communicating with numerical and nonnumerical messaging across information modalities.

Risk communicators frequently engage members of the public through social media; therefore, it is important to understand how to effectively communicate risks about environmental and health issues. This experiment with U.S. adults (N=737) explored how message features in risk-focused social media posts-namely, message modality (text-only posts or text with the inclusion of photographs or data presentations) and risk representation (numerical risk details or nonnumerical summaries of risk information)-influence risk perceptions, perceived message informativeness, and intentions to share the content. To do so, we drew from research on visual communication and research on numerical and nonnumerical representations of risk. We assessed the robustness of these effects across three environmental risk domains (asthma, heat waves, and vector-borne diseases). We found that compared to text-only messages, text with a data presentation (i.e., graph or table) led to enhanced risk perceptions, perceptions of informativeness, and sharing intentions. Relative to nonnumerical messages, numerical messages generated greater perceived risk, were rated as more informative, and elicited greater sharing intentions. Additionally, the effects of risk representation depended on participants' numeracy level, such that numerical messages (vs. nonnumerical) elicited greater sharing intentions and perceived informativeness among high-numeracy individuals but had no such effects for low-numeracy individuals. We also found some evidence that message effects on perceived informativeness differed based on risk topic. Our results suggest that communicators can consider designing social media risk messages with numerical details and data visualizations.

Group Writing: Overcoming Challenges and Facilitating Excellence in Group Writing in Blended EFL Classes in Tertiary Contexts in Bangladesh

The study examined the challenges faced by tertiary-level EFL students when collaboratively completing various writing activities inside hybrid EFL classrooms. It also explored synchronous solutions to these obstacles. EFL learners frequently engage in group activities to enhance their writing skills in EFL classes. These collaborative exercises have yielded a significant variety of reflections that are consistently explored in the study. The study utilized an explanatory sequential mixed approach, using a Survey Questionnaire, Focused Group Discussion (FGD), and Participant Observation (PO) to gather primary data. The numeric data was analyzed using class intervals of the scale composite scores, while the qualitative data was studied thematically. The quantitative results indicate that more than one-third of students face significant difficulties in pre and post-writing activities. Among these students, 45% experience moderate-level challenges while writing. According to the Relative Importance Index (RII), students encounter greater challenges in post-writing (0.72) compared to pre-writing (0.68) and while writing (0.64) in group writing. After analyzing the recognized difficulties in different phases, feasible strategies such as fostering a culture of collaborative writing, promoting self-directed learning, and cultivating interpersonal relationships were identified as effective means to improve writing skills in groups for English in the EFL context.

Extracting the symmetries of nonequilibrium quantum many-body systems

Symmetries play a pivotal role in our understanding of the properties of quantum many-body systems. While there are theorems and a well-established toolbox for systems in thermal equilibrium, much less is known about the role of symmetries and their connection to dynamics out of equilibrium. This arises due to the direct link between a system’s thermal state and its Hamiltonian, which is generally not the case for nonequilibrium dynamics. Here we present a pathway to identify the effective symmetries and to extract them from data in nonequilibrium quantum many-body systems. Our approach is based on exact relations between correlation functions involving different numbers of spatial points, which can be viewed as nonequilibrium versions of (equal-time) Ward identities encoding the symmetries of the system. We derive symmetry witnesses, which are particularly suitable for the analysis of measured or simulated data at different snapshots in time. To demonstrate the potential of the approach, we apply our method to numerical and experimental data for a spinor Bose gas. We investigate the important question of a dynamical restoration of an explicitly broken symmetry of the Hamiltonian by the initial state. Remarkably, it is found that effective symmetry restoration can occur long before the system equilibrates. We also use the approach to define and identify spontaneous symmetry breaking far from equilibrium, which is of great relevance for applications to nonequilibrium phase transitions. Our work opens new avenues for the classification and analysis of quantum as well as classical many-body dynamics in a large variety of systems, ranging from ultracold quantum gases to cosmology.

Inverse Properties Estimation of Methanol Adsorption in Activated Carbon to Utilise in Adsorption Cooling Applications: An Experimental and Numerical Study

The precise estimation of influential parameters in adsorption is a key point in conducting simulations for the sensitivity analysis and optimal design of cooling systems. This study explores the critical role of a new type of granular activated carbon (GAC-208C) in adsorption refrigeration systems. By fitting experimental and numerical models to the thermophysical properties of GAC/methanol as a working pair, an advanced methodology is established for the thermal analysis of the adsorption bed, addressing the various operating conditions overlooked in prior studies. The physical properties of the studied carbon sample are determined in a laboratory using surface area and pore volume tests, thermal adsorption analysis, and weight loss. To determine the thermal properties of GAC/methanol, the adsorption process is experimentally tested inside an isolated heat exchanger. A three-dimensional (3D) model is created to simulate the procedure and then coupled with the particle swarm optimisation (PSO) algorithm in MATLAB. The optimal thermal parameters for adsorption are determined by minimising the mean square error (MSE) of the adsorption bed temperature between the numerical and experimental data. The laboratory studies yielded accurate results for the physical properties of GAC, including adsorption capacity, porosity, permeability, specific heat capacity, density, activation energy, and the heat of adsorption. The thermal analysis of the adsorption process identified the ideal values for the Dubinin–Astakhov equation constants, diffusion coefficients, heat transfer coefficients, and contact resistance. The numerical model demonstrated strong agreement with the experimental results, and the dynamic behaviour of pressure and uptake distribution showed good agreement with 1.2% relative error. This research study contributes to the improved estimation of adsorption parameters to conduct more accurate numerical simulations and design new adsorption systems with enhanced performance under different operating conditions.

Development of STEAM teaching materials for understanding volcano disaster prevention systems

Education around volcanic activity and volcanic disaster prevention systems is important in Japan due to its proximity to the Ring of Fire where there are hundreds of active volcanoes. Knowledge and awareness of what to do during volcanic eruptions has the potential to save lives. The science of predicting volcanic eruptions is complex and it is therefore difficult to predict eruptions. Therefore, comprehensive knowledge is crucial to ensure effective disaster mitigation strategies are in place. Dr Shintaro Sato, Faculty of Contemporary Human Studies, Kyoto Notre Dame Women’s University, Japan, leads a team of researchers that is developing STEAM (science, technology, engineering, the arts and maths) teaching materials. The goal is to improve understanding of volcano disaster prevention systems among students and the wider community. This means correctly recognising disaster information provided by the Japan Meterological Agency and other organisations, and using this information to select actions and make decisions in the event of a disaster. This includes understanding of volcanic observation systems, the reading of numerical data obtained and knowledge of natural phenomena related to volcanic eruptions. In doing so, Sato believes the content is more likely to have a positive impact on peoples’ lives. Following the development of the teaching materials, the researchers investigated the effectiveness of the content, in part by comparing the functions of MESH blocks. These include motion, motion-sensing, temperature and humidity, button and LED blocks.

Prediction of Shear Strength in Anisotropic Structural Planes Considering Size Effects

It is essential to elucidate the shear mechanical behavior of structural planes to assess the risk to rock masses and protect them from shear failure. Current research on shear mechanical behavior is focused on isotropic structural planes with the same lithology on both sides. However, anisotropic structural planes, commonly found in nature, may exhibit unique mechanical behavior that differs from isotropic structural planes. Therefore, it is necessary to study the factors affecting the shear strength of the anisotropic structural planes. In this paper, the direct shear numerical tests on anisotropic structural planes were carried out using the three-dimensional distinct element code (3DEC) based on the laboratory test. The numerical test results illustrate that the error between the peak shear strength of the numerical test and the laboratory test is basically within 10%. The shear stress-displacement curves of the numerical and laboratory tests are similar, which verifies the accuracy of the numerical test. According to the Barton standard sections, anisotropic structural plane models with different roughness and size were established, and the direct shear numerical tests with different normal stresses were carried out. To predict the peak shear strength of the anisotropic structural planes, one hundred and eighty-one sets of direct shear numerical test data were selected. Normal stress, roughness, compressive strength of soft and hard rock masses, basic friction angle of soft and hard rock masses, and structural plane size were used as input parameters to establish a back propagation (BP) neural network model. The research results show that, under identical conditions, the shear strength of the anisotropic structural planes decreases as the structural plane size increases. On the contrary, the shear strength increases with the increasing structural plane roughness and normal stress. For the BP neural network prediction model, the root mean square error (RMSE) and coefficient of determination (R2) of the training set are 0.441 and 0.957. For the test set, the RMSE is 0.489, and R2 is 0.947, which indicates that the predicted values are in good agreement with the actual values.

A multi-source data-driven approach for navigation safety integrating computational intelligence and Bayesian networks

Ships often face various risks when sailing at sea, ranging from harsh natural environments to complex traffic conditions. To reduce the impact of these risks on ships and crews, this paper proposes a navigation risk assessment method that integrates computational intelligence (CI) techniques, such as fuzzy logic, with Bayesian networks (BNs) and utility theory. Firstly, a navigation risk assessment system is established using maritime data and expert knowledge, which evaluates risks from a spatial perspective by considering factors such as safeguard and accident conditions across different regions. Secondly, a fuzzy logic-based numerical and expert data transformation method is proposed to derive the prior probabilities of risk factors in BNs. The weighted fuzzy rule base is used to capture the dependencies among the risk factors. Finally, the probability distribution of navigation risk is determined by combining the prior probability and the dependencies, which are converted into risk index values through utility theory. Taking the grid-based navigation risk assessment of the South China Sea as an example, the effectiveness of this method is verified. The results of the study provide theoretical support for navigation risk assessment based on multi-source data and provide a reference for formulate maritime regulatory policies.

Comparison of the Effectiveness of Two Different Methods of Alleviating Pain and Anxiety during Local Anaesthesia Administration in Children: A Split-mouth Study

Abstract Introduction: This study aimed to compare the effectiveness of two different methods, a custom-designed mucosal vibrator and topical benzocaine gel, in alleviating pain and anxiety during local anaesthesia (LA) administration in paediatric patients. Materials and Methods: A randomised, split-mouth controlled trial was conducted with 30 paediatric patients aged 5–10 years. Each child received LA with a custom-designed mucosal vibrator in one session and with topical benzocaine gel in another. Pain perception and anxiety were assessed using the Wong-Baker FACES Pain Rating Scale, Sound–Eye–Motor Scale and pulse rate measurements. The sequence of interventions was randomised using the sequentially numbered, opaque, sealed envelope technique. Results: The study found that the custom-designed mucosal vibrator significantly reduced pain perception compared to the benzocaine gel, as evidenced by both subjective and objective pain scores (P &lt; 0.05). However, the two methods showed no significant difference in anxiety levels, as indicated by similar pulse rate changes (P &gt; 0.05). Conclusion: The custom-designed mucosal vibrator offers a cost-effective and efficient alternative to topical benzocaine for reducing pain during LA in children, though it does not significantly alter anxiety levels. This device could be a valuable tool for paediatric dental practitioners to improve the comfort of their patients during dental procedures.