Search Results (1,247)

The effective design of logistics platform business models is an important means for platform-type logistics enterprises to gain a competitive advantage. This study employs RRS Logistics as a case study to clarify the dynamic environmental mechanisms of logistics platform business models from the perspective of value co-creation and build a novel structural framework for logistics platform business models with community at their core. The research findings are as follows: First, guided by the idea of “value positioning–value co–creation–value support–value maintenance–value capture”, the conceptual framework of business models is redefined. The key steps in designing logistics platform business models, which can provide guidance and assistance for different logistics platforms, are proposed. Second, the design process for logistics platform business models should be dynamically adjusted in real time according to changes and environmental uncertainty. Third, in the process of transitioning to an ecological platform, logistics platforms’ ecosystem service clusters and ecosystem envelope are key factors in achieving a win–win scenario for all the stakeholders in the community. The case studies show that in logistics platform business model design, methods and key steps based on value co-creation could enhance the core competitiveness of logistics platforms. Full article

Background: Intravenous vancomycin remains a key agent in the treatment of complex orthopedic infections, particularly those involving methicillin-resistant Staphylococcus aureus (MRSA). However, its use is associated with significant risks, most notably nephrotoxicity. Despite guideline recommendations, standardized dosing and monitoring protocols are often absent in orthopedic settings, leading to inconsistent therapeutic drug exposure and preventable adverse events. This study evaluated the clinical impact of implementing a structured standard operating procedure (SOP) for intravenous vancomycin therapy in orthopedic inpatients. Methods: We conducted a single-center, pre-post cohort study at a university orthopedic department. The intervention consisted of a standard operating procedure (SOP) for intravenous vancomycin therapy, which mandated weight-based loading doses, renal function-adjusted maintenance dosing, trough level monitoring, and defined dose adjustments. Patients treated before SOP implementation (n = 58) formed the control group; those treated under the SOP (n = 56) were prospectively included. The primary outcome was the incidence of vancomycin-associated acute kidney injury (VA-AKI) defined by KDIGO Stage 1 criteria. Secondary outcomes included therapeutic trough level attainment and infusion-related or ototoxic adverse events. Results: All patients in the post-SOP group received a loading dose (100% vs. 31% pre-SOP, p < 0.001). The range of measured vancomycin trough levels narrowed substantially after SOP implementation (7.1–36.2 mg/L vs. 4.0–80.0 mg/L). The proportion of patients reaching therapeutic trough levels increased, although this was not statistically significant. Most notably, VA-AKI occurred in 17.2% of patients in the control group, but in none of the patients after SOP implementation (0%, p = 0.0013). No cases of ototoxicity were observed in either group. Infusion-related reactions decreased after the implementation of the SOP, though not significantly. Conclusions: The introduction of a structured vancomycin protocol significantly reduced adverse drug events and improved dosing control in orthopedic inpatients. Incorporating such protocols into routine practice represents a feasible and effective strategy to strengthen antibiotic stewardship and clinical quality in surgical disciplines. Full article

This study develops a domain-adaptive multimodal RAG (Retrieval-Augmented Generation) system to improve the accuracy and efficiency of technical question answering based on large-scale structured manuals. Using Hyundai Staria maintenance documents as a case study, we extracted text and images from PDF manuals and constructed QA, RAG, and Multi-Turn datasets to reflect realistic troubleshooting scenarios. To overcome limitations of baseline RAG models, we proposed an enhanced architecture that incorporates sentence-level similarity annotations and parameter-efficient fine-tuning via LoRA (Low-Rank Adaptation) using the bLLossom-8B language model and BAAI-bge-m3 embedding model. Experimental results show that the proposed system achieved improvements of 3.0%p in BERTScore, 3.0%p in cosine similarity, and 18.0%p in ROUGE-L compared to existing RAG systems, with notable gains in image-guided response accuracy. A qualitative evaluation by 20 domain experts yielded an average satisfaction score of 4.4 out of 5. This study presents a practical and extensible AI framework for multimodal document understanding, with broad applicability across automotive, industrial, and defense-related technical documentation. Full article

Background: Hemiplegic migraine (HM) is a rare and severe subtype of migraine with a complex genetic basis. Although pathogenic variants in CACNA1A, ATP1A2, and SCN1A explain some familial cases, a significant proportion of patients remain genetically undiagnosed. Increasing evidence points to an overlap between migraine and cerebral small vessel disease (SVD), implicating vascular dysfunction in HM pathophysiology. Objective: This study aimed to identify rare or novel variants in genes associated with SVD in a cohort of patients clinically diagnosed with HM who tested negative for known familial hemiplegic migraine (FHM) pathogenic variants. Methods: We conducted a case-control association analysis of whole exome sequencing (WES) data from 184 unrelated HM patients. A targeted panel of 34 SVD-related genes was assessed. Variants were prioritised based on rarity (MAF ≤ 0.05), location (exonic/splice site), and predicted pathogenicity using in silico tools. Statistical comparisons to gnomAD’s Non-Finnish European population were made using chi-square tests. Results: Significant variants were identified in several SVD-related genes, including LRP1 (p.Thr4077Arg), COL4A1 (p.Pro54Leu), COL4A2 (p.Glu1123Gly), and TGFBR2 (p.Met148Leu and p.Ala51Pro). The LRP1 variant showed the strongest association (p < 0.001). All key variants demonstrated pathogenicity predictions in multiple computational models, implicating them in vascular dysfunction relevant to migraine mechanisms. Conclusions: This study provides new insights into the genetic architecture of hemiplegic migraine, identifying rare and potentially deleterious variants in SVD-related genes. These findings support the hypothesis that vascular and cellular maintenance pathways contribute to migraine susceptibility and may offer new targets for diagnosis and therapy. Full article

Bridges, owing to their intricacy, represent pivotal yet relatively underexplored assets within the domain of maintenance services in civil engineering. While international evaluation methodologies exist to gauge the overall condition of bridges, they often fall short in establishing interrelationships among individual elements, thereby neglecting insights into the influence exerted by each element’s condition on the bridge’s overall performance. This research introduces an integral fuzzy model evaluation with a preventive approach, designed to assess both the integral condition of a bridge and its constituent elements. Furthermore, the study generates maintenance recommendations, subsequently evaluated by professionals to determine the most suitable course of action based on available resources. To validate the efficacy of the proposed model, a case study involving Bridge 15-016-00.0-0-04.0 PIV, known as “La Cuesta” in Mexico, is presented. The findings indicate that the bridge is in a satisfactory condition and warrants high-priority attention. Bridge analysis is compared with evaluations conducted using the methods of the Secretariat of Infrastructure, Communications, and Transportation (SICT), the American Association of State Highway and Transportation Officials (AASHTO), and the Ministry of Transport and Communications of Peru. The comparative evaluation reveals that our proposed model provides a more detailed representation of deterioration, facilitating more efficient maintenance planning by considering the hierarchical relationships between the bridge’s modules and elements. Full article

Background/Objectives: Upper tract urothelial carcinoma (UTUC) is a rare and biologically distinct subset of urothelial malignancies, comprising approximately 5–10% of urothelial cancers. UTUC presents unique diagnostic and therapeutic challenges, with both a higher likelihood of invasive disease at presentation and a less favorable prognosis compared to urothelial carcinoma of the bladder. Current treatment strategies for UTUC are largely derived from bladder cancer studies, underscoring the need for UTUC-directed research. This review provides a comprehensive overview of UTUC, encompassing diagnostic approaches, systemic and intraluminal therapies, surgical management, and future directions. Methods: A narrative review was conducted synthesizing evidence from guideline-based recommendations, retrospective and prospective clinical studies, and ongoing trials focused on UTUC. Results: Neoadjuvant cisplatin-based chemotherapy is increasingly preferred in UTUC due to the risk of postoperative renal impairment that may preclude adjuvant cisplatin use. Surgical management includes kidney-sparing approaches and radical nephroureterectomy (RNU), with selection guided by tumor risk and patient comorbidities. While endoscopic management (EM) preserves renal function, it carries a higher recurrence and surveillance burden; RNU remains standard for high-risk cases. Systemic therapy for advanced and metastatic UTUC mirrors that of bladder urothelial carcinoma. Enfortumab vedotin (EV) plus pembrolizumab showed superior efficacy over chemotherapy in the EV-302 trial, with improved response rate, progression-free survival, and overall survival across subgroups, including UTUC. For patients ineligible for EV, the CheckMate-901 study supported first-line chemoimmunotherapy with gemcitabine, cisplatin, and nivolumab. Further systemic therapy strategies include maintenance avelumab post-chemotherapy (JAVELIN Bladder 100), targeted therapies such as erdafitinib (THOR trial), and trastuzumab deruxtecan (DESTINY-PanTumor02) in FGFR2/3-altered and HER2-positive disease, respectively. Conclusions: Historically, the therapeutic landscape of UTUC has been extrapolated from bladder cancer; however, ongoing research specific to UTUC is deriving more precise regimens involving the use of immune checkpoint inhibitors, antibody–drug conjugates, and biomarker-driven therapies. Full article

This study focuses on the optimization of valve assemblies in downhole rod pumping units (DRPUs), which remain the predominant artificial lift technology in oil production worldwide. The research addresses the critical issue of premature failures in DRPUs caused by leakage in valve pairs, i.e., a problem that accounts for approximately 15% of all failures, as identified in a statistical analysis of the 2022 operational data from the Uzen oilfield in Kazakhstan. The leakage is primarily attributed to the accumulation of mechanical impurities and paraffin deposits between the valve ball and seat, leading to concentrated surface wear and compromised sealing. To mitigate this issue, a novel valve assembly design was developed featuring a flow turbulizer positioned beneath the valve seat. The turbulizer generates controlled vortex motion in the fluid flow, which increases the rotational frequency of the valve ball during operation. This motion promotes more uniform wear across the contact surfaces and reduces the risk of localized degradation. The turbulizers were manufactured using additive FDM technology, and several design variants were tested in a full-scale laboratory setup simulating downhole conditions. Experimental results revealed that the most effective configuration was a spiral plate turbulizer with a 7.5 mm width, installed without axis deviation from the vertical, which achieved the highest ball rotation frequency and enhanced lapping effect between the ball and the seat. Subsequent field trials using valves with duralumin-based turbulizers demonstrated increased operational lifespans compared to standard valves, confirming the viability of the proposed solution. However, cases of abrasive wear were observed under conditions of high mechanical impurity concentration, indicating the need for more durable materials. To address this, the study recommends transitioning to 316 L stainless steel for turbulizer fabrication due to its superior tensile strength, corrosion resistance, and wear resistance. Implementing this design improvement can significantly reduce maintenance intervals, improve pump reliability, and lower operating costs in mature oilfields with high water cut and solid content. The findings of this research contribute to the broader efforts in petroleum engineering to enhance the longevity and performance of artificial lift systems through targeted mechanical design improvements and material innovation. Full article

During the construction of large-span steel truss arch bridges, challenges such as complex control calculations, frequent adjustments of the cantilever structure, and deviations in the closure state often arise in the process of the assembly and closure of arch ribs. Based on the stress-free state control theory, this paper proposes a precise assembly control method for steel truss arch bridges, which takes the minimization of structural deformation energy and the maintenance of the stress-free dimensions of the closure wedge as the control objectives. By establishing a mathematical relationship between temporary buckle cables and the spatial position of the closure section, as well as adopting the influence matrix method and the quadprog function to determine the optimal parameters of temporary buckle cables (i.e., size, position, and orientation) conforming to actual construction constraints, the automatic approaching of bridge alignment to the target alignment can be achieved. Combined with the practical engineering case of Muping Xiangjiang River Bridge, a numerical calculation study of the precise assembly and closure of steel truss arch bridges was conducted. The calculated results demonstrate that, under the specified construction scheme, the proposed method can determine the optimal combination for temporary buckle cable tension. Considering the actual construction risk and the economic cost, the precise matching of closure joints can be achieved by selectively trimming the size of the closure wedge by a minimal amount. The calculated maximum stress of the structural rods in the construction process is 42% of the allowable value of steel, verifying the feasibility and practicality of the proposed method. The precise assembly method of steel truss arch bridges based on stress-free state control can significantly provide guidance and reference for the design and construction of bridges of this type. Full article

Amid the global shift toward clean energy, wind power has emerged as a critical pillar of the modern energy matrix. To improve the reliability and maintainability of wind farms, this work proposes a novel hybrid fault detection approach that combines expert-driven diagnostic knowledge with data-driven modeling. The framework integrates autoencoder-based neural networks with Failure Mode and Symptoms Analysis, leveraging the strengths of both methodologies to enhance anomaly detection, feature selection, and fault localization. The methodology comprises five main stages: (i) the identification of failure modes and their observable symptoms using FMSA, (ii) the acquisition and preprocessing of SCADA monitoring data, (iii) the development of dedicated autoencoder models trained exclusively on healthy operational data, (iv) the implementation of an anomaly detection strategy based on the reconstruction error and a persistence-based rule to reduce false positives, and (v) evaluation using performance metrics. The approach adopts a fault-specific modeling strategy, in which each turbine and failure mode is associated with a customized autoencoder. The methodology was first validated using OpenFAST 3.5 simulated data with induced faults comprising normal conditions and a 1% mass imbalance fault on a blade, enabling the verification of its effectiveness under controlled conditions. Subsequently, the methodology was applied to a real-world SCADA data case study from wind turbines operated by EDP, employing historical operational data from turbines, including thermal measurements and operational variables such as wind speed and generated power. The proposed system achieved 99% classification accuracy on simulated data detect anomalies up to 60 days before reported failures in real operational conditions, successfully identifying degradations in components such as the transformer, gearbox, generator, and hydraulic group. The integration of FMSA improves feature selection and fault localization, enhancing both the interpretability and precision of the detection system. This hybrid approach demonstrates the potential to support predictive maintenance in complex industrial environments. Full article

A branch of the nucleotide excision repair (NER) pathway, transcription-coupled repair (TCR or TC-NER) specifically operates on the template DNA strand of actively transcribed genes. Initiated by stalling of elongating RNA polymerase complexes at damaged sites, TC-NER has historically been viewed as “accelerated repair”, arguably necessary for the maintenance of vital transcription function. Conversely, the conventional “global genome” (GG-NER) mechanism, operating throughout the genome, is usually regarded as a much slower process, even though it has long been found that differences in repair kinetics between transcribed DNA and the rest of the genome are not manifested for all structural types of DNA damage. Considering that damage detection is the rate-limiting step of overall repair reactions in most cases and that the mechanisms of the initial recognition of modified DNA structure are fundamentally different between TC-NER and GG-NER, it is suggestive to attribute the observed kinetic differences to different damage spectra recognized by the two pathways. This review summarizes current knowledge on the differential requirements of TC-NER and GG-NER towards specific damage types, based on their structural rather than spatial characteristics, and highlights some common features of DNA modifications repaired preferentially or exclusively by TC-NER, while evading other repair mechanisms. Full article

Background and Clinical Significance: Prosthetic rehabilitation in the aesthetic zone of periodontally compromised patients presents a complex clinical challenge, requiring a careful coordination of aesthetic, functional, and biological demands. This case highlights the benefits of digital dentistry, interdisciplinary collaboration, and regular maintenance in achieving long-term success in complex rehabilitations of periodontally compromised patients. Case Presentation: This case report describes the digital minimally invasive rehabilitation of a 39-year-old male patient with Stage III periodontitis, occlusal discrepancies, tooth mobility, and an interincisal diastema. A fully digital workflow—including intraoral scanning, aesthetic previewing, and mandibular motion analysis—was employed to guide diagnosis, treatment planning, and prosthetic execution. Conservative tooth preparations using a biologically oriented approach (BOPT) were combined with customised provisional restorations to support soft tissue conditioning and functional control throughout the provisional phases. Mandibular motion tracking facilitated the design of a personalised anterior guidance to improve occlusion and correct the deep bite. The interincisal diastema was initially maintained then closed during the advanced phase of treatment based on aesthetic simulations and patient preference. One unplanned endodontic treatment was required during the provisional phase, but no other complications occurred. Conclusions: At the four-year follow-up, the patient demonstrated stable periodontal and occlusal conditions, improved clinical indices, and high satisfaction with the aesthetic outcome. Full article

Small-cell lung cancer (SCLC) is an aggressive malignancy with poor prognosis despite initial responsiveness to chemotherapy. Platinum-based chemotherapy with etoposide has long been the standard first-line treatment, but recent advances in immunotherapy have improved outcomes. Phase III trials, including IMpower133 and CASPIAN, demonstrated that adding immune checkpoint inhibitors, such as atezolizumab and durvalumab, to chemotherapy significantly enhances overall survival (OS) and progression-free survival (PFS). This case report describes a 76-year-old former smoker diagnosed with extensive-stage SCLC (ES-SCLC) following the detection of a left lower lung mass. The patient underwent combination therapy with carboplatin, etoposide, and atezolizumab, followed by maintenance atezolizumab. The patient demonstrated a sustained response to treatment, with significant tumor regression and no evidence of disease progression. Despite advanced age and comorbidities, treatment was well-tolerated, with no severe adverse events. Serial imaging over 24 months confirmed sustained disease stability, with regression of mediastinal lymphadenopathy and no new lesions. This case highlights the potential for prolonged disease control in select SCLC patients treated with chemo-immunotherapy. The absence of significant toxicities underscores the feasibility of immunotherapy even in elderly patients with comorbidities. These findings support the role of atezolizumab as a key component of ES-SCLC treatment and suggest the need for further research on predictors of durable response. Full article

Dissolved gas analysis remains the most widely utilized non-intrusive diagnostic method for detecting incipient faults in insulating liquid-immersed transformers. Despite their prevalence, conventional ratio-based methods often suffer from ambiguity and limited potential for automation applicrations. To address these limitations, this study proposes a unified multiclass classification model that integrates traditional gas ratio features with supervised machine learning algorithms to enhance fault diagnosis accuracy. The performance of six machine learning classifiers was systematically evaluated using training and testing data generated through four widely recognized gas ratio schemes. Grid search optimization was employed to fine-tune the hyperparameters of each model, while model evaluation was conducted using 10-fold cross-validation and six performance metrics. Across all the diagnostic approaches, ensemble models, namely random forest, XGBoost, and LightGBM, consistently outperformed non-ensemble models. Notably, random forest and LightGBM classifiers demonstrated the most robust and superior performance across all schemes, achieving accuracy, precision, recall, and F1 scores between 0.99 and 1, along with Matthew correlation coefficient values exceeding 0.98 in all cases. This robustness suggests that ensemble models are effective at capturing complex decision boundaries and relationships among gas ratio features. Furthermore, beyond numerical classification, the integration of physicochemical and dielectric properties in this study revealed degradation signatures that strongly correlate with thermal fault indicators. Particularly, the CIGRÉ-based classification using a random forest classifier demonstrated high sensitivity in detecting thermally stressed units, corroborating trends observed in chemical deterioration parameters such as interfacial tension and CO₂/CO ratios. Access to over 80 years of operational data provides a rare and invaluable perspective on the long-term performance and degradation of power equipment. This extended dataset enables a more accurate assessment of ageing trends, enhances the reliability of predictive maintenance models, and supports informed decision-making for asset management in legacy power systems. Full article

This study investigates the enhancement of condition and the extension of service life in architectural structures of shopping malls through the application of a hybrid methodological framework that integrates Life Cycle Assessment (LCA) and Service Life Planning (SLP). Thisresearch identifies key parameters related to physical performance, sustainability indicators, and functional characteristics of architectural systems that are subject to deterioration and shifting market conditions during the operational phase. The methodology encompasses a theoretical synthesis of LCA/SLP principles and advances in modeling for both the integrated design of new facilities and the monitoring and renewal of existing ones—from data collection and early-stage planning, through construction, use, and maintenance, to end-of-life phases. A second component of the model focuses on quantitative assessment and condition forecasting, based on Markov chain modeling, applied to the case study of the “Deva 1” shopping mall in Serbia. The results demonstrate the model’s ability to correlate physical condition indices with predictive service life scenarios.This study further contributes by integrating time-dependent impact categories, usage profiles, and planning parameters into a unified evaluation matrix, which can be applied to the development and improvement of systems aimed at enhancing the structural, functional, esthetic, and indirectly economic value of shopping mall buildings throughout their entire life cycle—from an architectural perspective. Full article

The purpose of this paper is to present vibration-based condition monitoring of forced-draft fans used in sugar factories. The draft system’s uninterrupted operation is essential for the flawless operation of boilers. Considering its importance, a forced-draft fan was employed as a case study. The vibration and noise in the time and frequency domain, along with the overall vibration and noise levels, were measured from the driving and non-driving ends of forced-draft fans at different intervals of time so that errors in measurement could be avoided. These vibration data were analyzed to identify faults in the different components of the forced-draft fans, along with problems in their operation. The results of this analysis indicate that the fans under study produced more noise and vibration than the recommended standard value. Also, through signature analysis, it was found that the fans needed to be balanced and aligned properly. The problems observed were rectified, and recommendations are given for the proper maintenance of these fans. An effort was made to explore the relationship between patterns of the vibration spectrum and signs of failure in a forced-draft fan. It was found that vibration-based condition monitoring is an effective tool in sugar factories. Full article