Search Results (54,514)

Silts are generally unsuitable for direct use as subgrade fill material due to their low shear strength and deformation resistance. In this study, a novel technique for strengthening silt using enzyme-induced calcium carbonate precipitation (EICP) with the addition of non-fat milk powder is proposed to improve the mechanical properties of silt for use as subgrade fill material. The effect of EICP on the mechanical properties of silt, in terms of internal friction angle and shear strength, was examined through consolidated undrained (CU) triaxial shear tests. The results showed that, with the EICP technique involving non-fat milk powder, the mechanical behaviors of silts were significantly enhanced due to the improved bonding ability of the silt particles. Furthermore, an optimum content of non-fat milk powder of 6 g/L is proposed to increase the mechanical properties. Compared with EICP treatment alone, under the optimum condition of 6 g/L non-fat milk powder and 14 days of curing, the shear strength, cohesion, and internal friction angle increased by 44.1%, 51.86%, and 31.4%, respectively. Finally, microstructural analyses were conducted using Scanning Electron Microscopy (SEM) and X-ray Diffraction (XRD) to provide insight into the mechanisms underlying the improvement of silt. The findings of this study can provide guidance for the application of silt improvement through the EICP technique involving non-fat milk powder. Full article

Consolidated bioprocessing (CBP) is difficult to monitor because enzyme production, lignocellulose degradation, sugar release, and fermentation occur simultaneously under sparse measurement, feedstock variability, and plant–model mismatch conditions. This study proposes a computational sensor-set design framework for digital-twin-assisted CBP monitoring. A five-state virtual plant, consisting of active biomass, cellulolytic enzyme activity, residual insoluble substrate, soluble sugar, and ethanol, was used to evaluate all 16 ethanol-mandatory measurement packages formed from ethanol, sugar, biomass, enzyme, and residual-substrate proxy channels. Candidate sensor sets were assessed using finite-difference output sensitivities, Fisher-information-based state-observability and parameter-identifiability analyses, eigenvalue and parameter-correlation diagnostics, and paired Monte Carlo unscented Kalman filter soft-sensing reconstruction. Within the tested five-state virtual-plant benchmark and with the specified excitation schedule, noise assumptions, burden indices, and scoring objective, ethanol-only sensing provided the weakest support for state-aware CBP digital-twin reconstruction. At a $6\mathrm{h}$ sampling interval, the state-observability log-pseudodeterminant increased from 4.18 with ethanol-only sensing to 8.56 after adding soluble sugar and to 16.42 with full-proxy monitoring. The ethanol–sugar–biomass–substrate package also gave strong reduced state-observability performance, with log-pseudodeterminants of 15.12, 13.76, and 12.51 at 6, 12, and $24\mathrm{h}$, respectively. Biomass and enzyme proxies contributed strongly to parameter learning, and the ethanol–sugar–biomass–enzyme package gave the strongest active parameter-identifiability performance, with log-pseudodeterminants of 10.82, 9.06, and 6.67 at 6, 12, and $24\mathrm{h}$, respectively. In the paired soft-sensing analysis, full-proxy monitoring reduced the mean latent-state RMSE from 1.1899 to 0.3756, followed by ethanol–biomass–enzyme–substrate with 0.3843 and ethanol–sugar–biomass–substrate with 0.4121. The primary aggregate ranking identified ethanol–sugar–biomass–substrate as the best overall package, with a sensor-value score of 0.8432 and a burden index of 7.0, followed by full-proxy monitoring with a score of 0.8173 and a burden index of 10.0. Robustness tests showed that ethanol–sugar–biomass–substrate remained top-ranked under uniform noise scaling, full UKF missingness, delay and bias stress test conditions, most scoring-weight scenarios, and all tested sensor-specific burden workflows. Full-proxy monitoring remained a close competitor under independent sensor-specific noise variation conditions and became top-ranked for some alternative operating trajectories. The proposed framework provides a simulation-based method for prioritizing informative measurement packages before implementing CBP digital twins in laboratory and pilot-plant settings. Full article

The legalization of euthanasia in Spain through Organic Law 3/2021 has intensified debates concerning the relationship between patients’ autonomy, the protection of life, and the freedom of conscience of healthcare professionals. In a context marked by increasing moral and religious pluralism, conscientious objection has emerged as a particularly sensitive issue in the practical implementation of assisted dying. This article adopts a legal and socio-religious approach to analyze the role of conscientious objection in the Spanish euthanasia framework. First, it examines the constitutional foundations of freedom of conscience and its specific regulation under Organic Law 3/2021, with particular attention to the guarantees and limits established for healthcare professionals. Second, it analyses the official positions of the main religious traditions present in Spain regarding euthanasia, assisted suicide, and end-of-life care, identifying both points of convergence and doctrinal diversity. Finally, the article assesses the practical impact of religious and moral convictions on the exercise of conscientious objection, drawing on the limited empirical evidence currently available. The analysis shows that, although most religious traditions oppose active euthanasia while accepting palliative care and the withdrawal of futile treatments, analysis of available empirical evidence suggests that objections are more often grounded in secular ethical or professional reasons than explicitly religious ones. The article concludes that conscientious objection should be understood as a structural feature of pluralist healthcare systems, requiring legal and organizational arrangements capable of safeguarding both freedom of conscience and effective access to legally recognized rights. Full article

Graphene and carbon nanotube (CNT) membranes are promising for filtration, desalination, and water treatment, yet their performance requires the joint interpretation of their architecture, nanoconfined transport, selectivity, fouling, swelling, defects, stability, and operating conditions. Here, GCMembrane-LLM was developed as an evidence-grounded domain-specific large language model. A curated 582-paper corpus generated 12,208 cleaned membrane-specific question–answer pairs for Low-Rank Adaptation (LoRA)-based supervised fine-tuning of Llama-3.1-8B-Instruct, and retrieval-augmented generation provided article-title and page-level traceability. GCMembraneBench included 100 application-oriented questions on graphene oxide (GO) membranes, CNT membranes, GO/CNT hybrids, and cross-material reasoning. Under direct answering without retrieval context, the anonymized and shuffled automatic evaluation showed that GCMembrane-LLM achieved a mean weighted score of 4.237/5.0, exceeding Llama-3.1-8B-Instruct and Doubao-1.5-lite. A stratified 30-question blinded manual assessment showed the same ranking. The application cases further yielded membrane science conclusions: CNT-assisted GO/CNT transport should be evaluated with dispersion, interfacial compatibility, defects, and stability; GO desalination depends on swelling control, interlayer spacing, and defect suppression; and CNT high flux requires joint examination of pore diameter, entrance chemistry, hydration barriers, ion rejection, and operating conditions. GCMembrane-LLM supports source-traceable evidence organization and preliminary hypothesis formulation before experimental validation. Full article

The use of direct reduced iron (DRI) in electric arc furnace (EAF) steelmaking has grown in popularity, yet dephosphorization, as a special concern because of high phosphorous levels, is yet to be fully understood. Here, a dynamic process model, accounting for phosphorus behavior under the circumstance of a continuous charge of raw materials and semi-continuous flushing slag in an industrial DRI-charged EAF, is developed and verified to predict trajectories of steel and slag phosphorus levels and slag chemistry in real time based on process conditions. The model is then employed to evaluate dephosphorization in a wide range of DRI phosphorus levels and process conditions. It is found that dephosphorization in industrial DRI-charged EAFs does not occur in equilibrium, with the phosphorus partition range of 20~70, compared to 130~170 for equilibrium conditions. For the phosphorus content in DRI, ranging from 0.02 wt.% to 0.2 wt.%, a dephosphorization ratio of more than 81% can be achieved at a slag basicity of 2.3. Dephosphorization is likely easily achieved even at a relatively low slag basicity of 1.5~1.7 when DRI containing phosphorus levels as high as ~0.1 wt.% is used, attaining a dephosphorization ratio of more than 70%. The current model can serve as a valuable tool, providing a knowledge base to assist in the design, operation, and optimization of DRI-charged EAF practices. Full article

We designed a label-free fluorescent aptasensor assisted by exonuclease III (Exo III) for sensitive insulin (Ins) detection. The method has high sensitivity, anti-interference properties and repeatability. Additionally, the label-free fluorescent aptasensor assisted by Exo III used to detect Ins has not been reported on yet. In this study, we connected a modified DNA sequence to the 5′ end of an aptamer, modifying it into a hairpin structure and exposing 11 nucleotides at the 3′ end containing the base adenine (A). The A was substituted with base 2-aminopurine (2AP) to provide a label-free stable hairpin fluorescent probe (2AP-hairpin probe). This strategy took advantage of the high binding affinity of the Ins aptamer and the susceptibility of 2AP to the local base stacking environment. When Ins is added to the detection system, the 2AP-hairpin probe binds to Ins, adopts a folded state, and blocks Exo III’s access to the binding site for cutting DNA. 2AP cannot be released, and the fluorescence of the 2AP-hairpin probe/cDNA/Ins/Exo III system cannot be restored. Ins detection is achieved by comparing changes in the fluorescent intensity before and after adding Ins to the detection system. The detection limit of the aptasensor is as low as 1.62 nM with a linear range of 3–130 nM. Furthermore, it is able to selectively and directly detect Ins in biological fluids, demonstrating significant clinical application value and research significance. Full article

Background: Osteochondral lesions of the talus (OLT) remain a challenging condition due to the limited regenerative potential of articular cartilage. Conventional bone marrow stimulation (BMS) techniques often result in fibrocartilage formation with inferior biomechanical properties. This study aimed to evaluate the safety and preliminary clinical efficacy of an arthroscopically assisted, single-stage injection of a heparin-conjugated fibrin hydrogel (HCFH) for OLT treatment. Methods: Twelve patients with symptomatic OLT underwent arthroscopic debridement, microfracturing, and HCFH injection containing autologous mesenchymal stromal cells (MSCs) and growth factors. Safety was assessed through systematic monitoring of adverse events (graded according to Common Terminology Criteria for Adverse Events criteria), wound healing, and serial laboratory inflammatory markers (leukocytes, erythrocyte sedimentation rate, C-reactive protein) during early and late follow-up. Clinical outcomes were evaluated using the Visual Analog Scale (VAS) and American Orthopedic Foot and Ankle Society score (AOFAS) preoperatively and at 6 and 12 months. Morphological assessment was performed using magnetic resonance imaging (MRI) with the modified Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) scoring system, evaluated independently by two blinded musculoskeletal radiologists. Results: No serious adverse events (Grade III–IV) were observed during the 12-month follow-up. All adverse events were mild (Grade I) and self-limited. A transient postoperative elevation in inflammatory markers was observed, returning to clinically acceptable levels by day 14. Significant improvements were noted in pain (VAS decreased from 6.0 to 2.0) and ankle function (AOFAS increased from 70.0 to 90.6) (p < 0.001). MRI demonstrated progressive morphological improvement, with the MOCART score increasing from 34.16 ± 17.1 at 6 months to 75 ± 5.43 at 12 months (p < 0.001). This increase corresponded with imaging features consistent with tissue maturation over time. The favorable MOCART outcomes observed in this study may be explained by the regenerative properties of heparin-conjugated fibrin hydrogels; however, larger randomized controlled trials with longer follow-up are needed to confirm the durability of the regenerated tissue. Interobserver agreement was substantial to almost perfect for MOCART scoring (κ = 0.68–0.84), with perfect agreement observed for surface assessment, bony defect/overgrowth, and cysts. Conclusions: Within the limitations of this study, single-stage HCFH injection demonstrated an acceptable safety profile and favorable preliminary clinical and radiological outcomes at 12 months. These findings suggest potential regenerative capability; however, controlled studies with larger cohorts and longer follow-up are required to determine comparative efficacy and long-term durability. Full article

Coronary artery disease (CAD) is the leading cause of mortality, with percutaneous coronary intervention (PCI) constituting the gold standard treatment. However, in an important proportion of the cases, lesion severity is debatable since conventional angiography provides only a two-dimensional representation of the vessel lumen and fails to quantify ischemic significance or plaque morphology. In these cases, several adjunctive tools considering physiology and imaging guidance may assist in quantifying the severity of the disease. Imaging modalities such as intravascular ultrasonography (IVUS) and optical coherence tomography (OCT), as well as physiology such as fractional flow reserve (FFR) and instantaneous wave-free (iFR), revolutionized revascularization strategy by linking anatomical stenosis to its functional consequence on myocardial perfusion. The present review summarizes and contrasts the available evidence for physiology and imaging guidance, considering the assessment of intermediate lesions during PCI and providing insights for their use in specific lesion subsets. Full article

Higher education increasingly addresses topics that are complex, interdisciplinary, and context-dependent, creating challenges for traditional lecture-based instruction. This study explores the potential of AI-assisted interactive storytelling as a pedagogical approach for such learning contexts, using healthy buildings as an instructional case relevant to architecture, engineering, and construction (AEC) education. Grounded in constructivist learning theory, a set of interactive stories was developed using generative AI and implemented in Twine to create a decision-based learning experience. The intervention was tested in a class using a pretest–posttest design along with a student perception survey. The results showed a significant improvement in knowledge following the intervention. Student feedback was also positive across all measured dimensions, including perceived learning, cognitive engagement, emotional engagement, motivation to learn, and comparison with traditional lectures. These findings suggest that interactive storytelling can support both learning and engagement when teaching complex, multidimensional topics. This study further indicates that generative AI can serve as a practical development partner by reducing the time and technical effort required to create interactive educational materials. Overall, this paper contributes to higher education research by positioning and demonstrating AI-assisted interactive storytelling as a promising instructional approach for complex learning areas. Full article

Introduction: Currently, there is an ongoing debate regarding the benefits of kinematic alignment (KA) versus mechanical alignment (MA) in total knee arthroplasty (TKA). Robotic-assisted TKA has been shown to improve implant positioning and precision of the KA technique, enabling successful kinematic alignment. However, its impact on early postoperative and functional outcomes remains unclear. This study aims to examine how imageless, table-mounted, robotic-assisted KA-TKA compares with conventional MA-TKA. Methods: Registry data of all primary TKAs using ATTUNE™ cruciate-retaining implants (January 2021–December 2024) performed by a single, experienced surgeon in a high-volume arthroplasty center were retrospectively reviewed. A total of 64 patients who underwent robotic-assisted KA-TKA were compared to 39 patients who underwent conventional MA-TKA. The mean age was 70.3 ± 7.71 and 69.3 ± 9.47 in the KA-TKA group and the MA-TKA group, respectively, while the male proportion was 32.8% and 30.7%, respectively. Early postoperative outcomes (static/dynamic pain score, ambulation distance, length of stay) and 6-month functional outcomes (range of motion, Knee Society Score, Oxford Knee Score, SF-36, patient expectation/satisfaction scores) were analyzed. Delta changes in outcome scores and proportion of patients attaining a minimum clinically important difference (MCID) were studied. Results: Robotic-assisted KA-TKA displayed benefits in the majority of the early postoperative outcomes, with significant improvements in ambulation distance (23.3 vs. 14.7 m, p = 0.002) compared to conventional MA-TKA. Both groups showed significant improvements in the majority of the functional outcomes at 6 months. Robotic-assisted KA-TKA also shows significant improvements in selected mental health aspects of SF-36, namely vitality (p = 0.001), mental health (p = 0.048), mental component summary (MCS) (p = 0.004), and a larger proportion attaining SF-36 vitality MCID (p = 0.045). Following false discovery rate correction for multiple comparisons, postoperative ambulation distance, SF-36 vitality, and MCS remained statistically significant between groups. No significant differences in KSS, OKS, and satisfaction/expectation fulfillment were noted. Conclusions: Robotic-assisted KA-TKA demonstrated early rehabilitation and select mental health-related quality of life improvements compared to conventional MA-TKA. Further studies are needed to examine its long-term clinical outcomes. Full article

The rapid emergence of generative AI tools is transforming software development. Consequently, software engineering education must adapt to ensure that students not only learn traditional development methods but also understand how to use these new technologies effectively and responsibly. In particular, project-based courses provide an effective setting in which to explore and evaluate the integration of AI assistance into real-world development practices. This paper presents our approach and a user study conducted in the context of a university programming project in which students collaboratively developed computer games. The study investigates how participants used generative AI tools across different phases of the software development process, identifies the tasks for which these tools were perceived as most useful, and analyzes the challenges students encountered. Building on these insights, we further examine a repository-aware, locally deployed large language model (LLM) assistant designed to provide project-contextualized support. The system employs retrieval-augmented generation (RAG) to ground its responses in relevant documentation and source code, thereby enabling a qualitative analysis of model behavior, parameter sensitivity, and common failure modes. These findings deepen our understanding of context-aware AI support in educational software projects and inform the future integration of AI-based assistance into software engineering curricula. Full article

During the stage of high-quality economic development, the synergy between advancing county industrial structure and employment growth has become a key issue in county governance. Although existing studies confirm that industrial structure has both creation and substitution effects on employment, few have adopted a configurational perspective to reveal how combinations of multiple factors can jointly promote both advanced county industrial structure and employment growth, thereby achieving industry-employment synergy. From the perspective of inclusive growth, this study incorporates six factors-economic level, financial level, innovation level, human capital, fiscal expenditure, and agricultural resources-into a unified analytical framework under the dimensions of efficiency and equity. Using a mixed method that combines dynamic QCA and regression analysis, and taking 1128 Chinese counties as the sample, this study explores configurational pathways that can simultaneously achieve advanced county industrial structure and inclusive employment growth. The findings are as follows: (1) Four configurational pathways lead to advanced county industrial structure: market-driven with efficiency priority (C1), endowment-substituted with factor concentration (C2), endowment-dependent with efficiency-equity coordination (C3), and talent–innovation dual-driven with government assistance (C4). (2) These four pathways differ in their effectiveness in promoting industry–employment synergy. Configurations C1, C2, and C3 achieve coordinated development of county industry and employment, whereas configuration C4 promotes advanced county industrial structure but inhibits employment growth. The conclusions reveal multiple equivalent pathways for synergistically enhancing county industry and employment, providing a basis for local governments to formulate context-specific industry–employment coordination policies. Full article

Trackless rubber-tired vehicles are the important auxiliary transportation equipment in coal mines. The main difficulty of their unmanned driving is that the underground environment information is complex but the onboard computing resources for perception and measurement are limited. To solve this conflict, this paper establishes a lightweight map dimension reduction framework to assist in path planning. Firstly, motivated by the idea of image convolution, the framework using the simplicity kernel is proposed for the high-resolution grid maps, which can reduce planning time while retaining the useful map information. Secondly, the reverse automata based on the greedy strategy are designed to get suitable machine-selected key points, which can solve the problem that some self-selected key points become impassable because of the dimension reduction. Moreover, a Bezier smoothing method based on slope interpolation is presented to avoid the collision between the smooth path and obstacle grid caused by the small number of path points planned on the reduced-dimension map. Finally, comparison experiments and downhole map experiment are carried out and discussed. The results show that using the proposed method to assist path planning can reduce time by 99.77% and reduce the number of redundant path points by 79.60%, and using the improved smoothing method from the framework can avoid collision risks caused by fewer path points. Full article

In artificial breeding of forest musk deer (Moschus berezovskii), common diseases such as abscess, enteritis, pneumonia, and parasitic infections exhibit persistently high morbidity rates. The early symptoms of certain diseases are often insidious and difficult to discern. Conventional manual inspection routines not only fail to achieve accurate diagnosis but also frequently disturb the animals, induce stress responses, and consequently delay optimal treatment windows. To address this practical challenge, this study employs an improved BRW-GPLinker joint entity-relationship extraction approach to perform integrated extraction and structural organization of disease entities, symptom manifestations, etiological associations, and preventive and therapeutic measures from farming literature and clinical records, thereby constructing a disease knowledge graph for forest musk deer. Through the introduction of a Boundary-Aware Module for refined entity boundary detection, a Relative Distance Bias Module to mitigate pairing errors in dense contexts, and a Weighted Sparse Multi-label Cross-Entropy loss function to enhance recall for infrequent relations, the proposed model achieves an F1 score of 0.887 on a self-constructed dataset and demonstrates favorable generalization capability on medical-domain datasets. By transforming fragmented clinical logs and manuals into structured medical associations, this knowledge graph facilitates rapid retrieval of forest musk deer disease information, thereby enhancing veterinary decision-making efficiency and assisting forest musk deer health management. Full article

Increasing the accessibility and portability of precise biomechanical data to sports scientists can assist in making data-driven decisions. The purpose of this study was: (1) Assess the concurrent and convergence validity of discrete and continuous waveform biomechanics of a smartphone-based markerless system. (2) Assess test–retest reliability of the smartphone-based markerless system. Movements were recorded simultaneously with two iPhones using Uplift Labs computer vision software and with Qualisys, a 12-camera marker-based motion capture system. Each participant performed two evaluations, one week apart, consisting of two countermovement jumps. Nested Bland–Altman limits of agreement (LOA), mixed-effect linear regressions, and intraclass correlation coefficients (ICC) were calculated. Twenty participants were included [Age: 24.7 (6.6) years. Height: 178.3 (4.3) cm. Mass: 86.5 (12.4) kg. Dominant Arm (Right): 17 (85%)]. Concurrent validity (LOA: 11.8 (4.4, 19.1)) demonstrated different results compared to convergence validity (Beta: 0.87 (0.68, 1.0)) and test–retest reliability (ICC: Uplift: 95.5 (90.9, 97.8). Qualisys: 94.4 (88.5, 97.3)). Uplift demonstrated greater than the a priori-determined limits of agreement across the CMJ. However, convergence validity was acceptable. Reliability suggests Uplift could be useful for tracking performance within individual athlete sessions. Full article