This short communication develops an existence result for a general non-linear parabolic equation. The method of proof comprises a variational approach for establishing a concerning solution existence at each instant of time, related to a model discretized in time.

Chikungunya virus (CHIKV), an arthritogenic alphavirus, is a significant public health threat in endemic and newly affected regions. This study investigates viral kinetics, immune responses, and the potential of monoclonal antibody (mAb) therapies to mitigate viraemia and transmission during acute CHIKV infection, providing novel insights into early intervention strategies. Using data from 29 patients in Cambodia, serial sampling and viral load quantification revealed that the population-average peak viral load occurred approximately 1.87 days prior to symptom onset. Children demonstrated higher peak viral loads and faster replication rates compared to adults, although symptom severity and burden were similar across age groups. IgM antibodies appeared earlier in adults (median: 4.1 days) than in children (median: 5.1 days; p = 0.036). C-reactive protein (CRP) levels were transiently elevated in about 50% of patients but showed no correlation with disease severity. Mathematical modeling highlighted that prophylactic mAb therapies, when administered three days before symptoms onset, could substantially reduce viral load and potentially prevent detectable viraemia. While these findings underscore the potential of mAbs as an early therapeutic strategy, further studies are necessary to evaluate the robustness of these results and assess their practical implications to curb CHIKV outbreaks by minimizing viraemia and pre-symptomatic transmission.

Statements of the problem: Dengue pathogenesis is complex and not fully understood. The virus may evade the immune system through mechanisms like the increased expression and/or secretion of immune inhibitory molecules. This study examines the association of the soluble human leukocyte antigen G (sHLA-G) with dengue in hospitalized patients. Method of study: A total of 238 dengue patients and 118 healthy controls were recruited. Dengue-infected patients were confirmed by real-time RT-PCR and clinically categorized into different severity groups. Laboratory parameters were assessed on admission. Plasma sHLA-G levels were measured by a commercial ELISA. Results: sHLA-G levels were significantly higher in dengue patients (median [range]: 42.7 [7.10 - 1300] U/mL) compared to healthy controls (median [range]: 11.1 [4.7 - 620] U/mL) (p<0.001). After adjusting for age, sex and disease severity, a significant association between sHLA-G plasma levels (log-transformed) and the days of illness was observed (β=0.1, p=0.033). Cases requiring strict medical monitoring presented significantly higher sHLA-G level (median [range]: 51.0 [7.17 - 525] U/mL), compared to cases without warning signs (median [range]: 38.0 [7.10 - 1300] U/mL) (p=0.011). While liver enzymes positively correlated with sHLA-G levels in all patients, total lymphocyte counts inversely correlated with sHLA-G levels in severe cases (r=-0.78, p-value=0.002). Conclusions: sHLA-G levels are associated with dengue warning signs and severe cases, suggesting a role in disease pathogenesis. Thus, this soluble protein might be a valuable marker to improve the accuracy of identifying severe cases and support clinical monitoring.

Runoff estimation in India faces challenges due to diverse climate zones, complex physiographic conditions, and variable rainfall patterns, limiting traditional hydrological models and prompting exploration of advanced deep learning methods for improved streamflow prediction. Existing deep learning hydrological models struggle to estimate discharge at ungauged sites. In this study, we tested eight different deep learning models—four recurrent neural networks (GRU, CudaLSTM, EALSTM, ARLSTM) and four attention-based architectures (Transformer, Informer, Reformer, Linformer)—across 144 watersheds in the Indian subcontinent (ISC). Our training and testing datasets combined meteorological forcing, catchment attributes, and observed discharge records. According to the results, ARLSTM improved prediction accuracy, achieving a median Nash–Sutcliffe Efficiency (NSE) of 0.71 on test basins. ARLSTM performs exceptionally well in specific regions: tropical monsoon areas (median NSE = 0.849), semi-arid regions (median NSE = 0.586), monsoon-influenced subtropical zones (NSE = 0.688), and tropical wet–dry climates (NSE = 0.539), especially in arid zones where traditional hydrological models often struggle. The assessments of high- and low-flow frequencies and durations, mean discharge, and runoff ratios underscore ARLSTM's capability to capture both extreme and average flow conditions. ARLSTM’s reliance on lagged streamflow limits its use in ungauged basins. To address this issue, we developed a novel deep learning architecture, Ungauged Basin LSTM (UBLSTM), to predict the runoff values for any ungauged basin in India. UBLSTM matches the performance of ARLSTM, making it a better choice for areas in India that lack sufficient data or have ungauged basins across various climate zones.

The Major Histocompatibility Complex Class II molecules (MHC II) have the ability to present tumor antigens to CD4+ T cells, playing a critical role in initiating anti-cancer immunity. Recently, the discovery that MHC II is expressed on many atypical antigen-presenting cells (APCs) has exponentially increased interest in MHC II as a potential target for immunotherapy. Tumor immunotherapies targeting MHC II aim to enhance the sensitivity of tumors to CD4+ T-cell-mediated immune responses by increasing MHC II expression in tumor cells, especially in those traditionally classified as ”cold tumors”-tumors with insufficient T cell infiltration. In clinical studies, MHC II-based personalized vaccines, immune checkpoint blockade (ICB) therapy, and combination immunotherapies have yielded encouraging results.In this review, we describe the intricate cancer immunomodulatory network centered around on MHC II expression on both professional and atypical APCs, highlighting the challenges and opportunities for related immunotherapies. In addition, we analyze how the prediction of MHC II as tumor markers and their specific binding affinities can guide the development of precision medicine to address the unique complexity of each type of cancer.

This paper investigates the penetration performance of soil-burrowing probes with different tip designs during shallow-depth penetration in various media, including terrestrial soils (Hostun sand) and well-characterized planetary soil simulants (LHS-1 Lunar regolith simulant and MGS-1 Martian regolith simulant). The analysis evaluates performance based on the pressure required to successfully penetrate the soil, comparing a conical tip design (i.e., the traditional tip design of penetrometers) with a plant root-inspired design. For each soil type, three different levels of soil compaction were considered to verify how initial soil porosity affects penetration performance. The study involves both experimental and numerical analyses. Experimentally, penetration tests were conducted in chambers filled with Hostun sand, LHS-1, and MGS-1. Numerically, a three-dimensional (3D) Discrete Element Model (DEM) was developed to simulate probe penetration in soil packings with geomechanical properties of Hostun sand, LHS-1, and MGS-1, respectively. In accordance with the experimental findings, the modeling results show significant advantages of the plant root-inspired tip design over the conical tip. The plant root-inspired design encountered lower soil resistance pressure during penetration across all soil types and compaction levels.

Introduction: Patients with bronchopulmonary dysplasia (BPD) exhibit significantly reduced lung function compared to healthy children. However, due to the challenges of performing spirometry in children under 5 years, functional behavior remains poorly characterized, and the utility of impulse oscillometry (IOS) in this population, particularly at high altitude, is unknown. Objective: To compare IOS variables between pediatric patients under 5 years of age with a history of BPD and healthy children residing in a high-altitude city. Methods: This retrospective, analytical, cross-sectional study included pediatric patients aged 3 to 5 years with a history of BPD, evaluated between 2019 and 2023 in Bogotá, Colombia. Healthy children of the same age and sex, previously included in a study of IOS reference values at our institution, were used as controls. Results: A total of 111 patients were included, 71 (64%) with BPD. The mean gestational age in the BPD group was 31 weeks (IQR 28–32 weeks), with a mean birth weight of 1350 grams (IQR 993–1800 grams). Most BPD patients exhibited elevated peripheral airway resistance (84.5%, n=60). Pre-bronchodilator mean values for R5, R20, R5-R20, X5, and AX were significantly higher in the BPD group. Conclusions: Children with BPD have elevated resistance levels and more negative reactance in the airways compared to healthy term children. This study identifies a characteristic functional pattern in children with BPD, which may be defined as an obstructive pattern without bronchodilator response. Longitudinal studies are needed to establish functional trajectories in this population.

Ascertaining migraine in electronic healthcare data is challenging because of likely diagnosis underrecording and treatment with over-the-counter analgesics, which cannot be used as disease proxies. Algorithm-identified migraine prevalence may depend on algorithm characteristics and target population. To describe migraine-identifying algorithms implemented in electronic healthcare data sources and summarize validation results and observed migraine prevalence, we searched PubMed for peer-reviewed, English-language, original research articles that identified migraine in adults using electronic algorithms in electronic healthcare data. We summarized algorithms, validation results, and migraine prevalence (PROSPERO: CRD42023491279). Of 360 unique titles and abstracts, 50 articles (14%) were selected for full-text review; of them, 41 articles (82%) were finally included: 16 were conducted in Europe, 13 in North America, and 12 in Asia. Sixteen studies (39%) identified migraine only using diagnosis codes, 5 (12%) only treatments, 9 (22%) diagnosis and/or treatment codes, and 11 (27%) diagnosis codes, treatments, and setting (e.g., primary care, specialist consultation). Reported migraine prevalence in the general population ranged between 4% and 17%. Only 2 studies reported validation results: one identified prevention-eligible patients with migraine (positive predictive value [PPV] = 97%), and one identified migraine on the basis of calculated probabilities with PPVs between 74% and 92%. Finding patients with migraine is feasible in various types of data sources; preferred algorithms vary; algorithm performance is mostly unknown. Identifying chronic migraine or other complex types of migraine requires combining diagnosis codes, treatments, and care settings, which is possible in only some data sources.

In this study we solve intuitionistic fuzzy Volterra  ⊕⊗integral equations by using successive approximations method. Also, uniform ⊕⊗convergence of sequences of intuitionistic fuzzy valued functions is defined and related results are obtained.

E-Learning is suitable when the learners are grouped and facilitated to learn according to their learning parameters and in their own pace. In this line the partition clustering method algorithms are identified to be appropriate and the researcher identified that the K-Medoid clustering better suits the grouping of e-Learners. Identifying the most preferred learning activities of a learner will ensure quicker learning capacities. Out of the existing dimensionality reduction methods, Principal Component Analysis (PCA) best reduces the dimensions, while preserving the integrity of the data set and hence PCA is applied to reduce the learner activities. Apart from that there is a necessity to fix the value of K (cluster size) when the K-Mediod clustering has to be extended for grouping of E-Learners. Hence, the researcher has also identified and proven that the Silhouette method best suits to fix the optimal value for K. The various stages of this research depicted above can be synthesized as a framework for implementing the steps taken throughout the research. In this research article a framework is proposed to grouping of e-Learners by using preferred e-Learning activities through benchmark algorithms.

Objective: To explore the role of inflammatory markers NLR, MLR, PLR, and MPV in the early assessment of lymph node and distant metastasis in patients with non-small cell lung cancer (NSCLC). Methods: This retrospective study involved 411 newly diagnosed NSCLC patients admitted to the People’s Hospital of Lu’an City between 2018 and 2023. Fasting venous blood samples were collected from all patients upon admission for complete blood count analysis, with the calculation of NLR, MLR, and PLR, and the measurement of MPV. Patient information including age, gender, comorbidities, smoking history, alcohol consumption, pathological type, and clinical stage was collected via the electronic medical record system. The correlation between NLR, MLR, PLR, and MPV with lymph node and distant metastasis in NSCLC patients was assessed. Results: Compared with NSCLC patients without metastasis, those with lymph node or distant metastasis showed significantly higher levels of NLR, MLR, and PLR (P < 0.001) and a significantly lower MPV (P < 0.001). ROC curve analysis revealed that the AUCs for NLR, MLR, PLR, and MPV in differentiating NSCLC with metastasis were 0.777, 0.788, 0.697, and 0.620, respectively. Correlation analysis showed that NLR, MLR, and PLR were positively correlated with clinical stage (r = 0.504, P < 0.001; r = 0.498, P < 0.001; r = 0.369, P < 0.001), while MPV was weakly negatively correlated with clinical stage (r = -0.212, P < 0.001). Conclusion: The inflammatory markers NLR, MLR, PLR, and MPV have significant clinical value in the early assessment of lymph node and distant metastasis in NSCLC patients and may provide useful reference for clinicians in rapid prediction.

Recently, time-varying linear equality and inequality equations (TVLEIE) is becoming increasingly crucial for solving problems in various fields. Zeroing neural networks (ZNNs) can also be employed to address the TVLEIE. Generally, the design convergent parameters (DCPs) of ZNN schemes affect the convergent speed. Since the previous fixed-parameter ZNNs (FPZNNs) use fixed parameters, they are not suitable for real-world applications where parameters vary over time. Taking this into account, the varying-parameter ZNNs (VPZNNs) were introduced in this field. Although the VPZNNs surpass the FPZNNs, their DCPs typically continue to increase over time and can even become excessively large in the end. But extremely large parameters are unsuitable. Moreover, the increasing parameters can lead to wasted computing resources, even when the VPZNNs become convergent. According to these considerations, we put forward a novel varying-parameter ZNN (NVPZNN) scheme with prescribed-time (PT) convergence to address the TVLEIE. NVPZNN has the capability to adjust its DCPs to progressively converge to a constant once it achieves convergence within the prescribed time. Subsequently, the global and PT convergence of NVPZNNs and their upper bounds as well as stability are theoretically analyzed. In comparison to other ZNN schemes utilizing common activation functions (AFs), the NVPZNN schemes own faster convergent rate, shorter convergent time and superior stability. Numerical experiments are conducted to validate the effectiveness and advantages of the NVPZNN schemes. Moreover, the successful application of NVPZNN in UR5 Manipulator shows its reliability and industrial application value.

Background: Nasal nitric oxide (nNO) is an established screening tool for primary ciliary dyskinesia (PCD). Customary chemoluminescence-based analyzers preclude large-scale screening for PCD. Portable devices with electrochemical sensors have not been clinically validated. Objective: To compare test success and nNO levels between a chemoluminescence analyzer (CLD88 sp ®) and a portable device (NIOX MINO ®) in clinical routine, and to assess whether a tidal breathing velum-closure (TBVC) technique increases test success. Methods: Measurements were performed in children ≥3 years using a conventional single-breath maneuver against an expiratory resistance (ER) for CLD88, and a breath-hold (BH) technique for NIOX. TBVC was evaluated for both devices. Results: 120 children referred for investigation of respiratory symptoms were included (median age 9.9 yrs, range 3.1–18.5). For conventional breathing techniques, test success increased from preschool age (CLD88 10% and NIOX 3.3%) to adolescence (87.5% and 65%). TBVC increased test success for both devices (preschoolers 80% and 70% vs adolescents 97.5% and 97.5%; p<0.001 for all age groups). Median nNO was higher for CLD88 with 263.3 nL/min (ER) and 283.7 nL/min (TBVC) compared to NIOX with 214.5 nL/min (BH) and 208.1 nL/min (TBVC) (p=0.013 and p<0.001). Conclusion: Test success is low when conventional breathing techniques are applied, especially in younger ages, but can be increased by TBVC. Nasal NO levels are lower for electrochemical sensor devices compared to chemoluminescence analyzers with no difference between conventional and TBVC methods, without clinical relevance. These findings support using portable analyzers with TBVC as a promising screening tool for PCD.

Background: Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infection (LRTI) hospitalisations in infants. Madeira was the first Portuguese region to recommend immunoprophylaxis with nirsevimab, an anti-RSV monoclonal antibody, for all infants in their first RSV season. The immunisation campaign, from November 2023 to March 2024, targeted infants born during the campaign (seasonal group), and those born between April and October, 2023 (catch-up group). This study aimed to assess nirsevimab effectiveness in preventing RSV-related LRTI hospitalisations. Methods: A population-based longitudinal observational study was conducted. Follow-up lasted until 150 days post-immunisation, campaign end (non-recipients), hospitalisation, or death, whichever occurred first. Nirsevimab effectiveness was estimated using an adjusted Cox proportional hazards model. The number needed to immunise (NNI) was calculated from absolute risk reduction. Averted cases were estimated from historical data, excluding the COVID-19 pandemic period. Results: The overall immunisation rate was 97.4% (1710/1756): similar in the seasonal (97.7%, 728/745) and catch-up (97.1%, 982/1011) groups. RSV-related LRTI hospitalisations occurred in 0.4% (6/1710) of nirsevimab recipients versus 4.3% (2/46) of non-recipients, with an estimated effectiveness of 94.6% (95% CI 72.6-98.9). NNI was 25. Supplemental oxygen therapy duration decreased significantly compared to previous seasons ( P=.039). Number of averted cases was 45 (IQR 15-83), with a 79.6% reduction in hospitalisations (IQR 62.6-90.9). Conclusion: Nirsevimab was effective in reducing RSV-related LRTI hospitalisations in a real-world setting, offering useful evidence for future RSV immunisation strategies.

Background: Stepped care is being adopted in many countries as a framework for organizing mental health care in diverse contexts. However, there is a lack of consistency in how it has been defined and operationalized, limiting its effective application in practice. We describe the development of standards for implementing stepped care in Canadian child and youth mental health contexts using a consensus-based approach. These standards are intended to support systems planners in creating more cohesive child and youth mental health systems across Canadian settings. Methods: This study employed learning alliance and Delphi methodologies. A pan-Canadian multi-round Delphi process conducted in English and French was used to derive consensus on the inclusion and wording of individual clauses in the implementation standard. Consensus with a threshold of 70% was set to determine inclusion of individual clauses in the final standard. Results: 68 individuals participated in the Delphi study (with a 76.48% retention rate) representing lived experience, service delivery, policy, and research expertise. Participant feedback indicated a desire for greater specificity, disagreements regarding the concept of shared decision-making, and pragmatic questions about leading systems-wide activities. Over 3 rounds, 29 clause items were revised and reduced to a final list of 24 clause items comprising implementation standards. Discussion: The results of this study represent the first multi-stakeholder, consensus-driven set of standards for implementing stepped care in child and youth mental health settings across Canada. With these standards, we aspire to provide a blueprint for advocacy and reform toward stronger, more coordinated mental health systems.

The sliding mode observer, containing nonlinear discontinuous function, is applicable for estimating the system state and the unknown disturbance. However, the traditional single-layer observer might still suffer from high pulse when the output measurement is mixed with noise. To improve the estimation quality, a new cascade sliding mode observer containing multiple nonlinear discontinuous functions is proposed in this paper. The proposed observer consists of two layers: the first layer is a traditional sliding mode observer, and the second layer is a cascade observer. The measurement noise issue is considered in the source system model. An alternative method about how to design the observer gains of the two layers, together with how to examine the effectiveness of the compensator based closed-loop system, are offered. A numerical example is provided to demonstrate the effectiveness of the proposed method. The observation structure proposed in this paper not only smooths the estimated state but also reduces the control consumption.

Objective Explore parents’ experiences of care before and after stillbirth to identify potential areas for improvement. Design Internet-based survey of parents distributed via International Stillbirth Alliance networks. Setting Global. Population or Sample 2488 parents with a stillborn baby in the previous 5 years Methods Framework analysis of free-text responses, using an a priori framework developed from global respectful maternity care rights and guidelines. Main Outcome Measures Self-reported experience of care Results Four major themes arose: compassionate communication and shared decision making; respect for individuality, autonomy and legal rights; competent staff, facilities, and care systems; and holistic support. Many parents reported individualised, compassionate, and high-quality care, with synergistic community support. Negative experiences involved paternalistic or disrespectful care. Commonly parents felt that not enough information about stillbirth prevention had been provided. Conclusions Bereaved parents want supportive healthcare providers who listen to them, provide information and treat them with kindness and respect. Parents do not want, or expect, all care to come from healthcare providers. Intersection of healthcare with community, charities and spiritual support is important. The option of legal registration and naming of the stillborn baby is important to many parents. Funding The Centre of Research Excellence in Stillbirth (Stillbirth CRE) at the Mater Research Institute, The University of Queensland, Australia funded the survey. The National Health and Medical Research Council (NHMRC) provides core funding to the Stillbirth CRE. Keywords Stillbirth, stillborn, perinatal loss, intra-uterine death, perinatal bereavement, online survey, qualitative, respectful care

PURPOSE : To determine the Diagnostic Accuracy of Quantitative Diffusion and MR Perfusion parameters in characterising, staging and grading endometrial carcinoma (EC). MATERIALS AND METHOD : Diffusion and MR perfusion were performed on forty-five biopsy-proven patients of EC. The deep myometrial invasion (DMI), cervical stromal invasion (CSI) and lymph node metastasis (LNM) were assessed on T2WI. The quantitative diffusion (apparent diffusion coefficient ADC) and perfusion parameters (Ktrans, Kep, Ve, Vp, SImax, SIrel and TTP) were derived. The diagnostic accuracy of these parameters in the characterisation, staging and grading of EC was determined along with their validation with histological type, grading, and stage. Their relationship with type of inflammatory infiltrate and MVD (Micro-vessel density) using CD34 on histopathology was also studied. RESULTS : The ADC and perfusion parameters, Ktrans and Ve, showed significant results (p-value <0.05) for the characterization of tumour type (Endometroid vs non-endometroid), grade (Low grade vs High grade) and FIGO stage. There was substantial agreement between T2WI and HPE for DMI with a sensitivity and specificity of 96.6 % and 68.8 %, respectively. For CSI, sensitivity and specificity were 76.5 % and 85.7 %; for LNM, sensitivity and specificity were 82.4 % and 96.5 % respectively. There was a moderate negative correlation between Ktrans and MVD (Spearman correlation coefficient: 0.48 and p-value <0.001). CONCLUSION : Quantitative Diffusion and MR Perfusion parameters have a significant role in the characterization of EC in terms of histological type, grade and FIGO stage (taking into account DMI, CSI and LNM) on histopathology.

Phenotypic switching in bacteria is an evolutionary adaptation that enhances fitness under changing environmental conditions. Here, we report phenotypic switching in Enterobacter sp. SA187 during the transition from its free-living state in soil to its endophytic state in plant root colonization. SA187 phenotypic switching is not host-restricted but occurs during colonization of various host plants. Genome re-sequencing of switcher colonies revealed consistent mutations in the rpoS gene compared to the ancestral strain. Loss-of-function mutations in the rpoS gene were both necessary and sufficient to trigger the phenotypic change, leading to widespread alterations in gene regulation that affected motility, biofilm formation, metabolism and growth. Metabolic analysis further revealed that SA187 switchers have enhanced capacity to thrive in media mimicking the acidic, sucrose-rich apoplastic compartment of plants. Phenotypic switching can be induced in media mimicking plant cell conditions but can be partially reverted on standard bacterial growth media. Overall, our study unravels the genetic mechanism and pivotal role of phenotypic switching in the evolutionary adaptation of a bacterial symbiont to different environments.

Hail severely impacts humans, crops and infrastructure. Quantifying future trends in hail frequency is extremely challenging due to the complex dynamic, thermodynamic, and microphysical processes involved in the formation of severe convective storms and eventually hail. Here, we combine a km-scale convection-permitting regional climate model and an online hail diagnostic to quantitatively assess changes in hail frequency over Europe imposed by a global warming level of 3{degree sign}C. The results reveal spatially contrasting changes with a strong decrease in summer hail frequency in southwestern Europe and an even larger increase in central and eastern Europe. These contrasting trends are related to changes in low-tropospheric humidity and convective available potential energy. Due to the physical approach to simulate convection and hail, yielding consistent trends in key hail parameters, the high-resolution simulations offer novel opportunities for assessing the socioeconomic implications of hail and its trends with global warming.

Abstract Purpose: To explore key contextual factors influencing the viable implementation of a community health promotion program. Better understanding of how contextual factors in local communities can affect the ability of creating community change is useful for practitioners and researchers working in this field. Methods: A formative evaluation of the implementation of a community program to promote child health in four local communities of a large Danish municipality was conducted. This approach facilitated detailed exploration of how contextual factors—such as community readiness, resource availability, and stakeholder engagement—shape implementation success. Data were collected via 15 semi-structured interviews with professional stakeholders and volunteers across the four local communities. Interviews were audio-recorded, transcribed verbatim, and analyzed using an abductive approach to thematic analysis. Results: The analysis, guided by the ‘program life cycle’ framework, identified three central themes across the program development and implementation phases: Program Planning Elements, Professional Networks Supporting Collective Action, and Adaptations Promoting Ownership. Key contextual factors included the recruitment of both mandated and enthusiastic implementation agents, fostering collaborative networks, and allowing for local program adjustments. These factors collectively enhanced ownership, engagement, and alignment with community needs while maintaining the integrity of core program components. Conclusion: Contextual factors play a pivotal role in promoting the successful implementation of community health promotion programs. Effective strategies include assembling diverse teams of implementation agents, enabling local adaptations, and actively engaging stakeholders throughout all phases of program development and implementation. These findings offer actionable insights for effective implementation of contextually responsive health promotion initiatives.

Objective: To assess whether transvaginal infiltration with anaesthetic only is non-inferior compared to anaesthetic plus corticosteroid for the treatment of myofascial pelvic pain. Design: Randomised, double-blind, parallel-group (1:1) clinical trial. Setting: Department of Obstetrics and Gynaecology, Hospital Universitario “Príncipe de Asturias” from December 2017 to June 2023. Population: Women presenting myofascial perineal pain ≥4 on the visual analogue scale (VAS) 2 months after delivery, with instrumental delivery or prolonged second stage (>3 hours) or foetal weight >4000 g. Methods: Patients were randomised into two groups to receive levobupivacaine 5 mg/mL, or levobupivacaine 5 mg/mL plus betamethasone 3 mg/mL. For each trigger point detected, a transvaginal infiltration was performed using the corresponding treatment. Patients were followed up to 6 months. Main Outcome: Primary endpoint was change in the VAS score from baseline at 6 months. Results: A total of 114 women were enrolled, with 57 randomly assigned to each group. Median (IQR) VAS 2 weeks after infiltration decreased by a similar magnitude: median (IQR) 2 (1-3) in the levobupivacaine group and 2 (1-4) in the levobupivacaine + betamethasone group ( p-value = 0.33). Same trend was observed at 6 months: median (IQR) 1 (1-4) in the levobupivacaine group and 1 (1-2) in the levobupivacaine + betamethasone group ( p-value = 0.85). Conclusions: This study provides evidence that the use of anaesthetic only infiltration is non-inferior compared to anaesthetic plus corticosteroid for the treatment of myofascial perineal pain. Funding: Trial was supported by a grant from the “Príncipe de Asturias” Hospital Foundation. Keywords: infiltration, myofascial pelvic pain, postpartum

This case study examines the implementation of an integrated digital twin system at a major automotive manufacturing facility, combining artificial intelligence (AI), augmented reality (AR), virtual reality (VR), and robotics technologies. The system enables real-time monitoring, predictive maintenance, immersive training, and adaptive control of manufacturing processes through a sophisticated digital representation of physical assets. Over an 18-month deployment period, significant improvements were observed in operational efficiency (27% increase), maintenance cost reduction (35%), training effectiveness (65% improvement), and product quality (defect rate decreased by 42%). This paper presents the architecture, implementation methodology, and quantitative results of this digital transformation initiative, providing valuable insights for similar industrial applications.

This article develops duality principles applicable to originally non-convex primal variational formulations. More specifically, as a first application through a D.C. approach, we establish a convex dual variational formulation for a non-linear Kirchhoff-Love plate model. The results are obtained through basic tools of functional analysis, calculus of variations, duality and optimization theory in infinite dimensional spaces. We emphasize such a convex dual formulation obtained may be applied to a large class of similar models in the calculus of variations. Finally, in the last section, we develop analogous results for a related model in superconductivity.