Limited Domain Research Articles

Effect of treatment on quality of life of rural asthmatic children

Introduction: Medications relieve symptoms of asthma but affected children are significantly bothered by physical, educational and emotional impairments. Urban studies from India evaluated on how this disease affects quality of life. Aim of our study was to evaluate quality of life of rural asthmatic children both before as well as after the treatment. Methods: Asthmatic children 7 to 17 years visiting to rural tertiary care teaching hospital were included. Tool used for the study was Pediatric Asthma Quality of Life Questionnaire - Standard (PAQLQS) which were measured at the time of inclusion and four weeks after treatment. It assessed the QOL (Quality of Life) under symptoms, activity limitation and emotional function domains. Mean difference in pre and post treatment PAQLQ score was assessed. Results: Total 46 children were included from rural setup. Majority were male 60% and had a normal BMI (54%) which was followed by undernutrition (28%). Majority children in both age group 7-11year and 12-17 year, presented with moderate asthma (80%) and (62%) (according to GINA 2022) respectively followed by mild. The rural cohort post treatment showed significant improvement in individual (p<0.005) as well as in overall PAQLQ post treatment (p<0.002). Conclusion: The study has highlighted that good asthma control even after short duration of treatment helped in improvement quality of life of affected children. To maintain quality of life it is expected that the patient remains adhered to proper treatment.

A new cause-mechanism independence estimation based cross-domain learning method for machining deformation prediction

Monitoring data-based machining deformation prediction is fundamental for accurate deformation control and product quality guarantee. For problems where involved unobservable variables like residual stress that can lead to data distribution bias, causal cross-domain learning methods have prominent advantages over other pure data-driven methods by shifting cause distributions and mechanisms. However, existing causal methods are based on the hypothesis that cause and mechanism are independent, which ignores the corresponding changes of mechanism across domains and can limit accuracies. This paper proposes a new causal cross-domain learning method based on cause-mechanism independence estimation, where the hypothesis is broken by taking the dependence of cause and mechanism into consideration. A cause-mechanism independence estimator is established by introducing the structural integral of mechanism derivative multiplies cause distribution, and the estimation value can measure the cross-domain changes of mechanism. As a result, the proposed method based predicting model can make efficient distribution shifts according to the estimation. The machining of aero-engine casings is taken as a case study, and experimental results show that the proposed method could predict the deformation well with limited target domain data. Besides, the proposed method can be readily extended to other cross-domain regression problems involved with unobservable variables.

Evaluation of patient satisfaction and maximum biting force of three differently constructed bars on two implants retaining mandibular overdenture - one year follow-up (a randomized controlled clinical trial)

BackgroundDifferent bar construction techniques will affect the bar passive fitness, which may induce stresses or strain on the implant and/or tightening screw and sequentially may affect the biting force and patient satisfaction.Aim of the studyThis clinical investigation assessed patient satisfaction and maximum biting force (MBF) using three differently constructed (conventional casting, milling, and 3D printing CAD/CAM techniques) cobalt-chromium (Co-Cr) bar-retained implants mandibular overdentures over a one-year period of follow-up.Materials and methodsThirty edentulous patients seeking for two implants bar-retained mandibular overdentures were randomly assigned into three groups as the following: Group I: 10 patients received a Co-Cr conventional casting bar, Group II: 10 patients received a Co-Cr CAD/CAM milled bar, and Group III: 10 patients received a Co-Cr CAD/CAM 3D-printed bar. All the bar groups were connected to two implants in the canine area bilaterally. Within the first two weeks following implant placement, patients received the definitive prosthesis. Patient satisfaction was evaluated by using the (OHIP-EDENT-19) questionnaire form after 6, and 12 months. Additionally, the maximum biting force was tested at after delivery, 3, 6, and 12 months for each group. The results were collected, tabulated, and statistically analyzed. Trial registration: This study was recorded on ClinicalTrials.gov retrospectively registered (ID: NCT06401187) on 30/04/2024.ResultsAfter one year follow up, regrading patient satisfaction the three groups showed no statistically significant difference. Although, the functional limitation domain was in favor of the milled bar. Regarding the maximum biting force, no statistically significant difference was found among three groups. However, at 12 mouths follow-up the milled bar showed statistically value.ConclusionWithin the limitations of this study, the conventional, milled and 3D printed bar overdentures groups can be used as a satisfactory treatment modality for edentulous mandible in terms of patient satisfaction and maximum biting force.

Reinforcement Learning for Efficient Identification of Soliton System Parameters Across Expansive Domains

Abstract Optical solitons in mode-locked fiber lasers and optical communication links have a wide range of applications. A crucial step in studying the transmission modes of optical solitons is to investigate the relationship between equation parameters and soliton evolution using deep learning techniques. However, current identification models have a limited parameter domain search range and are greatly influenced by initialization, often leading to divergence towards incorrect parameter values. This research harnesses reinforcement learning to revamp the iterative process of the parameter identification model. Through the development of a two-stage optimization strategy, the model is capable of conducting an accurate parameter search across arbitrary domains. The investigation encompasses a series of experiments on various standard and higher-order equations, illustrating that the innovative model overcomes the impact of initialization on the parameter search, and the identified parameters are guided towards their correct values. The enhanced model markedly improves experimental efficiency and holds significant promise for advancing the research of soliton propagation dynamics and addressing intricate scenarios.

Efficacy and Safety of Sarpogrelate on Symptom Improvement in Patients with Peripheral Arterial Disease (PAD) and/or Being at Risk of PAD: A Single Arm, Multi-Centered, Open-Label Trial.

To assess the efficacy and safety of sarpogrelate (300 mg) for symptom improvement in patients having peripheral arterial disease (PAD) and/or being at risk of PAD in clinical practice using the Peripheral Artery Questionnaire (PAQ). Symptomatic changes with antiplatelets in patients with PAD are limited. To determine the effect and safety of sarpogrelate on the PAQ at 24 weeks from baseline. A total of 1003 patients having PAD and/or being at risk of PAD from 17 tertiary hospitals in South Korea who were treated with sarpogrelate, were enrolled in this study. PAQs were collected at baseline and at 12 and 24 weeks, together with physical examination and vital signs measurements. Lifestyle pattern was also investigated. The average PAQ Summary Score in the efficacy evaluation analysis group significantly improved from 62.9 ± 23.7 at baseline to 68.9 ± 21.7 at 24 weeks (P<0.0001). Physical limitation items significantly improved from 69.5 ± 30.0 at baseline to 72.9 ± 28.3 after 24 weeks (P=0.0011). Symptom stability also significantly improved from 52.1 ± 21.6 at baseline to 63.6 ± 22.9 after 24 weeks (P<0.0001). Symptoms, treatment satisfaction, quality of life, and social limitation domains all improved after treatment. A total of 201 patients reported adverse events (20.0%), not directly associated with treatment. Treatment with 300 mg (orally) of sarpogrelate demonstrated statistically significant improvements in all domains and for the summary score of the PAQ at 24 weeks, it gave good results in terms of safety. Sarpogrelate may be helpful in reducing symptoms related to PAD.

Алгоритм для численного решения диффузионно-реакционно-дрейфового уравнения с дробной производной по времени и координате

&lt;p&gt;The paper is devoted to the construction and program implementation of the computational algorithm for modeling a process of diffusion-drift nature based on the fractional diffusion approach. The mathematical model is formulated as an initial-boundary value problem for the time-space fractional diffusion-drift equation in a limited domain. Time and space fractional derivatives are considered in the sense of Caputo and Riemann &amp;ndash; Liouville, respectively. A modified implicit finite-difference scheme is constructed. The concept of the considered mathematical problem provides an example of a deterministic model of the charging process of dielectric materials. An application program has been developed that implements the constructed numerical algorithm. The results were verified using the example of solving a test problem.&lt;/p&gt;

Graphene-enhanced ferroelectric domain wall high-output memristor

Recent studies on memristive materials and technologies have expanded beyond conventional memory elements, driven by their potential application in novel information processing concepts. Among these materials, conductive domain walls in ferroics are especially promising, offering conductive tunability suitable for reconfigurable multi-state devices. However, challenges such as domain stability, time-dependent conductivity, and low current output have impeded progress in the field. Here, we study the graphene/Pb(Zr,Ti)O3/SrRuO3 system, which demonstrates robust domain wall conduction up to 100 nA/μm2 for 2 V bias, while addressing the critical issue of stability of switched domains. The introduction of graphene electrodes enhances low-voltage stochastic domain formation with limited domain expansion that promotes the emergence of multi-domain states. The developed micrometer sized capacitor devices enable electrically programmable multiple distinct conduction states with robust retention combined with high current output and low operation voltage. These features are highly desirable for memristors and mark the significant potential of domain wall electronics for neuromorphic computing.

Preparation of Gradient HEA-DAC/HPA Hydrogels by Limited Domain Swelling Method.

Hydrogels are widely used in biological dressing, tissue scaffolding, drug delivery, sensors, and other promising applications owing to their water-rich soft structures, biocompatibility, and adjustable mechanical properties. However, most of the conventional hydrogels are isotropic. The anisotropic structures existed widely in the organizational structure of plants and animals, which played a crucial role in biological systems. In this work, a method of limited domain swelling to prepare anisotropic hydrogels is proposed. Through spatially controlled swelling, the extension direction of hydrogels can be limited by a tailored mold, further achieving anisotropic hydrogels with concentration gradients. The external solution serves as a swelling solution to promote swelling and extension of the hydrogel matrix in a mold which can control the extension direction. Due to the diversity of external solutions, the method can be applied to prepare a variety of stimulus-responsive polymers. The limited domain swelling method is promising for the construction of anisotropic hydrogels with different structures and properties.

Multisource Modeling Method for Petroleum Production Prediction Models: A Case Study of CO2-Flooding Performance

Summary Accurate prediction of oil production is crucial for formulating oilfield development strategies. With the rapid development of artificial intelligence, research on utilizing deep learning to construct oil production prediction models has been growing, which has partially compensated for the low computational efficiency of numerical simulators. Although the well-trained source domain model maintains high prediction accuracy on target blocks with similar production conditions, the prediction accuracy of the model declines in scenarios where substantial disparities exist between the production conditions of the target block and the source domain. This discrepancy makes the prediction results unreliable and causes a domain shift issue. We propose a multisource model fine-tuning approach, which leverages a limited amount of target domain data to fine-tune the existing source domain model, enabling it to rapidly converge in the target domain while maintaining superior prediction performance. Based on a heterogeneous low-permeability CO2-flooding reservoir development model, we established a series of source domain data sets, encompassing numerous types of well patterns and permeability fields, and specifically prepared various target domain data sets to verify the effectiveness of the model fine-tuning. Experimental outcomes demonstrate that our proposed model fine-tuning approach facilitates the rapid convergence of the existing model on target domain data. Following testing, the fine-tuned model, which attained a prediction accuracy exceeding 97% in the target domain, significantly improved upon the accuracy compared with the unfine-tuned model. The time required is significantly lower than retraining a new model, and it significantly reduces the need for data in the target domain. This provides support for the rapid generation of new prediction models using existing source domain models and limited target domain data.

Efficacy of Danlou tablets in patients with acute coronary syndrome undergoing percutaneous coronary intervention: a multicenter prospective cohort study.

Danlou tablets (DLTs) have been widely used to treat coronary heart disease in China. However, the benefits associated with DLT for patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI) in routine practice require further investigation. To investigate the effectiveness of DLT in patients with ACS undergoing PCI. This multicenter prospective cohort study for patients with ACS undergoing PCI was conducted in 40 centers in mainland China from February 2012 to December 2018. This trial is registered under ChiCTR-OOC-14005552. Patients were assigned to either the DLT group or the conventional medicine (CM) group based on whether they used DLT prior to enrollment. The duration of DLT use (1.5 g, three times a day) was 12 months. The primary endpoint comprised of cardiac death, non-fatal myocardial infarction, and urgent revascularization. Secondary endpoint included rehospitalization owing to ACS, heart failure, stroke, and other thrombotic events. The Seattle Angina Questionnaire (SAQ) was used to assess quality of life (QOL). Primary and secondary endpoints were followed up for 36 months, and the SAQ was followed up for 12 months. The Cox proportional hazards regression model was used to analyze the independent effect of DLT on primary and secondary endpoints. Propensity score matching (PSM) analyses were performed to mitigate bias. Survival estimation was performed using Kaplan-Meier survival curves and log-rank tests in the PSM cohort, and landmark analyses were used for further evaluation of primary and secondary endpoints. Subgroup analyses and interactions confirmed the robustness of the findings. Linear mixed effects models were used to assess the QOL. Overall, 936 patients were enrolled in this cohort study, of whom 875 completed follow-up. The primary and secondary endpoints had no significantly difference between the DLT and CM groups after Cox proportional hazards models. Kaplan-Meier survival curves and log-rank tests performed in the PSM cohort also found no significant differences between the two groups on primary and secondary endpoints. However, landmark analysis showed significant benefit in the primary endpoint for the DLT group after 200 days (hazard ratio [HR] 0.46, 95% confidence interval [CI] 0.22-0.93, P = 0.03). Landmark analysis also showed a significant benefit in the secondary endpoint in the DLT group within 200 days (HR 0.33, 95% CI 0.15-0.73, P = 0.006). Moreover, DLT improves the SAQ summary score, and scores in the physical limitation, treatment satisfaction, and disease perception domains for patients with ACS undergoing PCI. DLT combined with conventional treatment reduced the risk of the primary endpoint after 200 days and the secondary endpoint within 200 days during the 3-year follow-up. Additionally, DLT can improve the QOL without adverse effects.

Dislocation-based finite element method for homogenized limit domain characterization of structured metamaterials

PurposeHeterogeneous and micro-structured materials have been the object of multiscale and homogenization techniques aimed at recognizing the elastic properties of the equivalent continuum. The proposed investigation deals with the mechanical characterization of the heterogeneous material structured metamaterials through analyzing the ultimate strength using the limit analysis of the Representative Volume Element (RVE). To get the desired material strength, a novel finite element formulation based on the derivation of self-equilibrated solutions through the finite elements devoted to calculating the lower bound theorem has been implemented together with the limit analysis in Melàn’s formulation.Design/methodology/approachThe finite element formulation is based on discrete mapping of Volterra dislocations in the structure using isoparametric representation. Using standard finite element techniques, the linear operator V, which relates the self-equilibrated internal solicitation to displacement-like nodal parameters, has been built through finite element discretization of displacement and strain.FindingsThe proposed work presented an elastic homogenization of the mechanical properties of an elementary cell with a geometry known in the literature, the isotropic truss. The matrix of elastic constants was calculated by subjecting the RVE to numerical load tests, simulated with a commercial FEM calculation code. This step showed the dependence of the isotropy properties, verified with Zener theory, on the density of the RVE. The isotropy condition of the material is only achieved for certain section ratios between body-centered cubic (BCC) and face-centered cubic (FCC), neglecting flexural effects at the nodes. The density that satisfies Zener’s conditions represents the isotropic geomatics of the isotropic truss.Originality/valueFor the isotropic case, the VFEM procedure was used to evaluate the isotropy of the limit domain and was compared with the Mises–Schleicher limit domain. The evaluation of residual ductility and dissipation energy allowed a measurement parameter for the limit anisotropy to be defined. The novelty of the proposal consisted in the formulation of both the linearized and the nonlinear limit locus of the material; hence, it furnished the starting point for further limit analysis of the structures whose elementary volume has been described through the proposed approach.

Exploring run-and-tumble movement in confined settings through simulation.

Motion in bounded domains is a fundamental concept in various fields, including billiard dynamics and random walks on finite lattices, and has important applications in physics, ecology, and biology. An important universal property related to the average return time to the boundary, the Mean Path Length Theorem (MPLT), has been proposed theoretically and experimentally confirmed in various contexts. We investigated a wide range of mechanisms that lead to deviations from this universal behavior, such as boundary effects, reorientation, and memory processes. This study investigates the dynamics of run-and-tumble particles within a confined two-dimensional circular domain. Through a combination of theoretical approaches and numerical simulations, we validate the MPLT under uniform and isotropic particle inflow conditions. This research demonstrates that although the MPLT is generally applicable for different step length distributions, deviations occur for non-uniform angular distributions, non-elastic boundary conditions, or memory processes. These results underline the crucial influence of boundary interactions and angular dynamics on the behavior of particles in confined spaces. Our results provide new insights into the geometry and dynamics of motion in confined spaces and contribute to a better understanding of a broad spectrum of phenomena ranging from the motion of bacteria to neutron transport. This type of analysis is crucial in situations where inhomogeneity occurs, such as multiple real-world scenarios within a limited domain.

The relationship between untreated dental caries and quality of life in children aged 6-12 years at elementary school 060970 belawan

Dental caries is a common oral health problem that occurs in all age groups, especially in children. Untreated dental caries can lead to several issues such as pulpitis, ulceration, fistula, abscess, and pulp necrosis. The aim of this study was to determine the relationship between untreated dental caries and quality of life, as well as the most affected domain of quality of life in children aged 8-10 years at Primary School 060970 Belawan in 2023. This was an analytical survey with a cross-sectional design to investigate the association between untreated dental caries measured using the pufa index and the quality of life of children aged 6-12 years using the Child’s Perception Questionnaire 8-10 (CPQ8-10). The subjects of this study were students aged 6-12 years at Primary School 060970 Belawan, selected using total sampling technique where the entire population was included as samples. The study began with oral examinations to determine deft/DMFT and pufa/PUFA scores. Subsequently, interviews were conducted with the respondents to collect data on their quality of life. Data analysis was performed using the Kolmogorov-Smirnov test for normality, which showed that the data were not normally distributed. Spearman correlation test (r=0.600) revealed a significant positive relationship between untreated dental caries and quality of life (p=0.000) with a strong correlation. The social limitations domain of quality of life (r=0.595) was found to be the most affected, indicating a strong association between untreated dental caries and quality of life. In conclusion, an increase in pufa scores is associated with an increase in quality of life scores. An increase in quality of life scores indicates a poor quality of life.

Strong Solutions of the Neuronal Responses System

We explore a connected reaction-diffusion system involving neural responses within limited convex open domains . Utilizing the Classical Faedo-Galerkin technique and employing compactness arguments, we establish the existence, uniqueness, and continuous dependence on initial data for strong solutions.

Liouville theorem of the regional fractional Lane–Emden equations

The purpose of this paper is to study the Liouville property for the Lane–Emden equation involving the regional fractional Laplacian ( − Δ ) Ω s u + Vu = h 1 u p + h 2 in Ω , u = 0 on ∂Ω , where s ∈ ( 0 , 1 ) , p>0, h 1 , h 2 are nonnegative functions and Ω ⊂ R N − 1 × [ 0 , + ∞ ) with N ≥ 2 , is an unbounded domain satisfying Ω t := { x ′ ∈ R N − 1 : ( x ′ , t ) ∈ Ω } with t ≥ 0 having an increasing monotonicity, that is, Ω t ⊂ Ω t ′ for t ′ ≥ t . The potential V ( x ′ , t ) decays as t → + ∞ . The properties of the limit domain Ω ∞ := lim t → ∞ Ω t in R N − 1 play an important role to obtain the nonexistence of positive solutions for semilinear elliptic equations with the regional fractional Laplacian. For s ∈ ( 0 , 1 2 ] , we provide a surprising nonexistence result if Ω ∞ is bounded. This particular phenomenon occurs because of the peculiar properties of the regional fractional Laplacian with the order s ∈ ( 0 , 1 2 ] .

Smart customer service in unmanned retail store enhanced by large language model

In unmanned retail store, providing smart customer service requires two stages: understanding customer needs, and guiding the customer to the product. In this paper, we propose an end-to-end (Customer-to-Shelf) software service framework for unmanned retail. The framework integrates visual recognition technology to detect retail objects, large language models to analyze customer shopping needs and make proper recommendations. First, deep neural network based image recognition models are studied for implementing effective stock keeping units (SKUs) object recognition on the shelf. Second, a novel method is proposed to fine-tune large language models (LLMs) with limited training dataset. Metaheuristic approaches are used to optimize the mask locations in a low dimensional parameter space, resulting a more efficient parameter updating method for limited downstream data. Third, by facilitating an automatic analysis of customer preferences powered by large language models, we present a smart recommender system based on domain-specific knowledge, which completes the Customer-to-Shelf software service framework. Experimental results show that our proposed fine-tuning method, is more efficient than other state-of-the-art training methods for limited downstream domain dataset. Using fine-tuned large models, we can successfully create a seamless shopping experience for customers by understanding personalized needs and providing shopping advice in the unmanned retail store.

Life's Essential 8 and its association with osteoarthritis and disability: a cross-sectional study based on the NHANES 2005-2018 database.

Osteoarthritis (OA) often coexists with risk factors for cardiovascular disease (CVD), worsening symptoms and functional impairment. This cross-sectional study investigated the association between Life's Essential 8 (LE8) and disability in individuals with OA. Data from 8334 United States adults (aged ≥ 20) who participated in the 2005-2018 National Health and Nutrition Examination Survey (NHANES) with complete data on LE8 components and disability status were analyzed. LE8 components, including diet, physical activity (PA), nicotine exposure, sleep, body mass index (BMI), blood lipids, glucose, and blood pressure (BP), were scored on a 0-100 scale, categorizing cardiovascular health (CVH) as low, moderate, or high. Disability mainly caused by OA was assessed using a standardized physical functioning questionnaire. Association analyses were performed using multivariable logistic regression, adjusting for demographic, socioeconomic, lifestyle, and health-related covariates. Individuals with CVH scores 10 points higher had a 15% lower prevalence of OA (95% CI 0.81-0.90). Individuals with OA were more than twice as likely to experience disability. High levels of CVH were associated with a lower prevalence of disability in various domains compared to low levels of CVH (all P < 0.05), such as in activities of daily living (OR 0.32, 95% CI 0.18-0.58). Among the LE8 components, BMI, PA, and sleep health were associated with disabilities in all domains, while blood lipid scores were not. A higher adherence to LE8 is associated with a lower prevalence of different types of disability in domains of physical functioning and functional limitations in individuals with OA.

Imprinted limited domain aptamer electrochemical sensors based on dual signal amplification of GOCS composites and gold nanoparticles for specifically detecting of Cd2+

An ultra-sensitive electrochemical sensor based on glassy carbon electrode (GCE) modified with carbon disulfide functionalized graphene oxide (GOCS)/gold nanoparticles (AuNPs) and dual recognition of aptamer/ion imprinting polymer (IIP) is proposed for the detection of Cd2+. The inherent layered structure of GOCS composites is convenient to provide high specific surface area, AuNP can improve electrode activity and the synergistic effect between the two materials contributes to further modification and signal amplification. The IIP cadmium ion imprinted cavities on the surface of electrode by electropolymerization can achieve the specific detection of Cd2+. Owing to the dual specific recognition provided by IIP and aptamer and the multiple signal amplification provided by GOCS and AuNPs, the sensor exhibits high detection response toward target Cd2+ with a detection limit of 0.15 μg/L in the linear range of 0.4–30 μg / L. The sensor had outstanding selectivity, excellent reproducibility, long-term stability and good reusability. Furthermore, this method can realize the detection of Cd2+ in real water samples with recovery rate of 86.5 % − 104.70 % (RSD=0.07 % − 9.65 %). This electrochemical strategy opens up more possibilities for the construction of trace detection of Cd2+ with record-high selectivity and sensitivity in water samples.

The impact of plasma-rich platelet injection to perianal sphincters on incontinence and quality of life in patients with rectal cancer after low anterior or intersphincteric resection: a prospective cohort study

BackgroundIncontinence is not rare after rectal cancer surgery. Platelet-rich plasma may promote tissue repair and generation but has never been tested for the treatment of anal incontinence. This study evaluated the impact of platelet-rich plasma injection on the severity of incontinence and quality of life after low rectal cancer surgery.MethodsThis is a prospective cohort proof of concept study in a colorectal cancer institution. Patients had undergone low anterior or intersphincteric resection for low rectal cancer and had a Wexner score > 4. Ten milliliters of platelet-rich plasma were injected into the internal and external sphincters under endoanal ultrasound (EAUS) guidance. Primary outcome measure was > 2 point improvement in Wexner score (improved group). The patients were assessed with endo-anal ultrasound examination, manometry, the Wexner Questionnaire and SF-36 Health Surveys, and patients were asked whether they used pads and antidiarrheal medications before and 6 months after PRP injection.ResultsOf 20 patients included in the study, 14 (70%) were men, and the average age was 56.8 (SD = 9.5) years. No statistically significant difference was found in Wexner scores before and after PRP injection (p = 0.66). Seven (35%) patients experienced a > 2 point improvement in Wexner score. Rectal manometry demonstrated improved squeezing pressure (p = 0.0096). Furthermore, physical functioning scoring (p = 0.023), role limitation (p = 0.016), emotional well-being (p = 0.0057) and social functioning (p = 0.043) domains on the SF-36 questionnaire improved. One (5%) and three (15%) patients stopped using pads and antidiarrheal medications.ConclusionPlatelet-rich plasma injection does not restore Wexner scores, but more than one-third of patients may benefit from this application with an improvement of > 2 points in their scores. Platelet-rich plasma injection may improve squeezing pressure and certain life quality measures for incontinent patients after rectal cancer surgery.

Geotechnical risk modeling using an explainable transfer learning model incorporating physical guidance

While Artificial intelligence (AI) has been successfully applied in assessing geotechnical risk, such methods heavily rely on data quality to achieve satisfactory performance, and their results hardly can be interpreted due to their opaque design. With this in mind, this paper aims to address the following research gap: How can we accurately model geotechnical risks using limited data and domain knowledge, and efficiently explain the results of AI model? We develop a physics-guided transfer learning (PGTL) model to enhance the explainability and accuracy of geotechnical risk modeling. With the help of a physical model that simulates the tunnel excavation, a physics-guided dataset with 1000 samples is established and used to train a deep neural network. On these bases, transfer learning is adopted to fuse the features of physics mechanisms and monitoring data, constructing an explainable prediction model of geotechnical risk. To further support risk decision-making, feature relevance techniques are employed to assess the contribution of input parameters to risk. A shield tunnel construction in Wuhan is selected as a case to validate the effectiveness of the proposed method. The PGTL exhibits a more promising accuracy with R2 of 0.777 in contrast to three popular machine learning approaches, and provides insights into parameters that significantly induce risk, enhancing site managers’ understanding of tunnel construction and being conducive to tunnel safety.