Search Results (6,628)

Magnesium alloys, characterized by high specific strength and low density, have high potential for applications in transportation and aerospace. Nevertheless, ensuring the reliable joining of thin-walled components remains a major technical challenge. This study examines how rotational speed affects the microstructure and mechanical properties of friction stir welded AZ61 magnesium alloy hollow profiles (3 mm thick), with particular focus on the underlying mechanisms. The results show that higher rotational speed during friction stir welding promotes dynamic recrystallization and weakens the basal texture. It also affects microstructural homogeneity, where an optimal rotational speed produces a relatively uniform hybrid microstructure consisting of refined recrystallized and un-recrystallized regions. This balance enhances both texture strengthening and microstructural optimization. The weld joint fabricated at a rotational speed of 1500 rpm showed the best overall mechanical properties, with ultimate tensile strength, yield strength, and elongation reaching peak values of 286.7 MPa, 154.7 MPa, and 9.7%, respectively. At this speed, the average grain size in the weld nugget zone was 4.92 μm, and the volume fraction of second-phase particles was 0.67%. This study establishes a critical process foundation for the reliable joining of thin-walled magnesium alloy structures. The optimized parameters serve as valuable guidelines for engineering applications in lightweight transportation equipment and aerospace manufacturing. Full article

This study was focused on addressing the performance degradation in core microstructures of ultra-heavy steel plates (thickness ≥ 50 mm) caused by non-uniform cooling during thermo-mechanical controlled processing. Using microalloyed DH36 steel as the research subject, we systematically investigated the effects of cooling rate on the nucleation and growth of acicular ferrite and its consequent microstructure-property relationships through an integrated approach combining in situ observation via high-temperature laser scanning confocal microscopy with multiscale characterization techniques. Results demonstrate that the cooling rate significantly affects acicular ferrite formation, with the range of 3–7 °C/s being most conducive to acicular ferrite formation. At 5 °C/s, the acicular ferrite volume fraction reached a maximum of 74% with an optimal aspect ratio (5.97). Characterization confirmed that TiOx-Al₂O₃·SiO₂-MnO-MnS complex inclusions act as effective nucleation sites for acicular ferrite, where the MnS outer layer plays a key role in reducing interfacial energy and promoting acicular ferrite radial growth. Furthermore, the interlocking acicular ferrite structure was shown to enhance microhardness by 14% (HV0.1 = 212.5) compared to conventional ferrite through grain refinement strengthening and dislocation strengthening (with a dislocation density of 2 × 10⁸ dislocations/mm²). These results provide crucial theoretical insights and a practical processing window for strengthening-toughening control of heavy plate core microstructures, offering a viable pathway for improving the comprehensive performance of ultra-heavy plates. Full article

Spinal cord injury (SCI) is a neurological condition often resulting in permanent motor and sensory deficits, for which effective treatments remain limited. RNA interference (RNAi) is a post-transcriptional mechanism of the downregulation of gene expression mediated by small interfering RNAs. RNAi has demonstrated therapeutic efficacy in various neurological disorders, positioning it as a promising yet underexplored therapeutic strategy for SCI. Here, we provide a focused overview of the key pathological processes in SCI, including primary mechanical injury and secondary cascades such as inflammation, mitochondrial dysfunction, excitotoxicity, oxidative stress, multiple forms of cell death, and others. The potential of RNAi to selectively silence genes implicated in these pathological processes, thereby enhancing neuroprotection and functional recovery, is highlighted. We point out that not only protein-coding genes, but non-coding RNAs (ncRNAs) are suitable targets for RNAi. Novel RNAi tools such as CRISPR-Cas13 might revolutionize the field and offer new opportunities for SCI therapy. However, despite all these promising findings, relevant translational studies of RNAi remain scarce. Challenges related to delivery methods, long-term efficacy, and cell-specific targeting must be addressed. Importantly, combining RNAi with other strategies such as cell- or biomaterial-based therapies may enhance therapeutic outcomes. Future investigations should prioritize systematic comparisons of RNAi targets and delivery systems, ideally at single-cell resolution and in different SCI models, to identify the most relevant molecular pathways for clinical translation. Overall, RNAi represents a compelling but still underdeveloped approach for SCI therapy, requiring continued refinement to reach clinical application. Full article

With the rapid advancement of Autonomous Mobile Robots (AMRs) in industrial automation and intelligent logistics, achieving efficient and safe path planning in dynamic environments has become a critical challenge. These environments require robots to perceive complex scenarios and adapt their motion strategies accordingly, often under real-time constraints. Existing methods frequently struggle to balance efficiency, responsiveness, and safety, especially in the presence of continuously changing dynamic obstacles. While Model Predictive Control (MPC) and Deep Reinforcement Learning (DRL) have each shown promise in this domain, they also face limitations when applied individually—such as high computational demands or insufficient environmental exploration. To address these challenges, we propose a hybrid path planning framework that integrates an optimized DRL algorithm with MPC. We replace the Actor’s output with a learnable noisy linear layer whose mean and scale parameters are optimized jointly with the policy via backpropagation, thereby enhancing exploration while preserving training stability. TD3 produces stepwise control commands that evolve into a short-horizon reference trajectory, while MPC refines this trajectory through constraint-aware optimization to ensure timely obstacle avoidance. This complementary process combines TD3′s learning-based adaptability with MPC’s reliable local feasibility. Extensive experiments conducted in environments with varying obstacle dynamics and densities demonstrate that the proposed method significantly improves obstacle avoidance success rate, trajectory smoothness, and path accuracy compared to traditional MPC, standalone DRL, and other hybrid approaches, offering a robust and efficient solution for autonomous navigation in complex scenarios. Full article

De-icing agents play a crucial role in winter road maintenance, yet their excessive application can result in pavement deterioration and environmental issues. Existing dosage guidelines lack comprehensive data on the dynamic response of de-icing agents under low-temperature conditions, particularly regarding stage-specific characteristics and multi-factor interactions. This research systematically evaluated the effectiveness of four de-icing agents (NaCl, CaCl₂, MgCl₂, CH₃COOK) within a temperature range of −5 °C to −25 °C, elucidating the two-phase ice-melting process (solid-phase followed by salt solution de-icing) with distinct kinetic mechanisms—a previously underexplored temporal pattern. The study quantified the differential impacts of particle size (small-particle CaCl₂ exhibiting 12% higher efficiency than sheet-like forms), dosage linear correlation, and negligible effects of ice layer thickness and road surface composition, which have not been systematically validated in prior studies. Temperature sensitivity was further refined: NaCl showed a 42.4% efficiency drop between −5 °C and −25 °C, while MgCl₂ maintained stable performance, supporting its potential as an environmentally sustainable alternative. This work provides a quantitative basis for dynamic dosage regulation by integrating stage characteristics and multi-factor optimization, addressing gaps in existing guidelines. Full article

Dermatofibromas (DFs) are benign neoplasms of the dermis typically found on the extremities of young adults. In approximately 3–5% of cases, basaloid cell hyperplasia (BCH) is observed overlying DFs. BCH is characterized by the proliferation of basaloid cells within the epidermis. BCH and superficial basal cell carcinoma (BCC) share many histological features, making their differentiation challenging. It is therefore unclear if the proliferation of basaloid cells in DFs represents an inductive process or, conversely, a malignant transformation indicative of BCC. The primary objective of our study was to determine whether BCH can be distinguished from superficial BCC using histology and immunhistological techniques. The histological and immunohistochemical characteristics of 43 DF samples with overlying BCH revealed significant similarities in staining patterns with those of superficial BCC described in the literature. These findings point to the need for innovative methods, such as molecular techniques, to refine diagnostic accuracy. Full article

Co-design plays a pivotal role in architectural design and urban planning for the green transition, facilitating collaboration among designers and stakeholders to create contextually appropriate solutions. This study examines the balance between stakeholder input and designer agency within co-design practices aimed at addressing the complex challenges posed by the green transition. Looking at how designers’ mindsets and methods are influenced by co-design, this study is carried out by analysing two contrasting case studies from the Future Island-Island project: Field Operations, an immersive residential on Rathlin Island, and DesignLink, a structured design sprint with organisational partners. Employing the terminologies of autogenic (designer-led) and allogenic design (stakeholder-led), the research critically explores how these modalities influence design outcomes and designers themselves. Field Operations exemplifies a more allogenic approach characterised by collaborative brief development through local immersion, while DesignLink primarily illustrates an autogenic process where predefined objectives guided creative synthesis. The study reveals that effective co-design requires oscillation between these approaches, underscoring the necessity for designers to harness both community insights while ensuring their own creative agency. The findings in this study advocate for a refined co-design framework that optimally integrates stakeholder contributions without compromising the integrity and coherence of the design process, emphasising the importance of contextual sensitivity, innovation, and timely decision-making in addressing complex societal challenges such as the green transition. Full article

Background: Deep vein thrombosis (DVT) is a serious thromboinflammatory complication of acute ischemic stroke (AIS). The true incidence, mechanistic risk factors, and optimal prophylactic strategies remain uncertain, particularly in the era of reperfusion therapy. Methods: This systematic review and meta-analysis (IRIS-DVT) searched PubMed, Embase, Cochrane, Scopus, and Web of Science for studies reporting DVT incidence, risk factors, or prophylaxis in AIS (2004–2025). Random-effects models were used to generate pooled prevalence and effect estimates, and the certainty of evidence was graded using the GRADE framework. Results: Forty-two studies (n = 6,051,729 patients) were included. The pooled prevalence of DVT was 7% (95% CI, 6–9%), approximately seventy-fold higher than in the general population, with wide heterogeneity influenced by screening timing and diagnostic modality. Pathophysiological risk factors included higher stroke severity (NIHSS; SMD 0.41; 95% CI, 0.38–0.43), older age (SMD 0.32; 95% CI, 0.18–0.46), elevated D-dimer (SMD 0.55; 95% CI, 0.38–0.72), female sex (OR 1.33; 95% CI, 1.19–1.50), and malignancy (OR 2.69; 95% CI, 1.56–5.22), supported by moderate-certainty evidence. Respiratory infection and admission hyperglycemia showed weaker, low-certainty associations. Traditional vascular risk factors (hypertension, diabetes, atrial fibrillation, dyslipidemia) were not significantly related to DVT risk. Evidence for prophylaxis with low-molecular-weight heparin, direct oral anticoagulants, or intermittent pneumatic compression was limited and graded very low certainty. Conclusions: DVT complicates approximately one in fourteen AIS cases, reflecting a distinct thromboinflammatory process driven more by acute neurological severity, systemic hypercoagulability, and malignancy than by conventional vascular risk factors. Early systematic screening (≤72 h) and consistent use of mechanical prophylaxis are warranted. Dedicated AIS-specific mechanistic and interventional trials are urgently needed to refine prevention strategies and improve post-stroke outcomes. Full article

Port operations involving ship unloading have traditionally posed significant complexity and have proven difficult to solve optimally using exact methods. This study investigates the long continuous unloading of ships carrying liquid products, where transportation is carried out using full truckload deliveries. For the first time, this work integrates the problem of liquid-based ship unloading with full truckload vehicle routing and truck driver scheduling. The primary objective is to minimize the total transportation costs during the continuous unloading process, while satisfying extra constraints such as driver rest–break–drive regulations, time windows, a heterogeneous fleet structure, and port-specific constraints such as maintaining a minimum number of backup vehicles at the port during unloading. To address this complex problem, a route-based insertion heuristic is employed as an initial step in a column generation framework designed for exact optimization. The approach incorporates a nested label setting algorithm for column generation, enhanced with acceleration techniques involving multi-search strategies, and refined selection methods. Performance analysis, based on artificial datasets closely resembling real-world scenarios and consisting of 112 instances, demonstrates that optimality gaps below 1% can be achieved within computational times considered reasonable in the context of the existing literature, while the total number of customer nodes and the minimum number of required vehicles at the port are at most 100 and 5, respectively. Full article

The surface treated by laser phase transformation hardening exhibits superior hardness, enhanced wear resistance, and refined grain structure. In this study, both single-track and two-track laser phase transformation hardening processes were numerically simulated, with the simulation accuracy being verified experimentally. Furthermore, the optimal overlap rate for laser two-track overlay was predicted based on the simulation results. An S355J2G3 metal block specimen was used as a case, numerical simulations of the phase transformation coupled with the temperature field on the specimen’s surface under laser irradiation were carried out using SYSWELD2019 software. The surface temperature distribution and the evolution of phase volume fractions were analyzed. Additionally, the changes in the temperature field within the softening zone and the distribution of tempering structures resulting from two-track laser overlay were examined. The discrepancy between experimental and simulated results for the hardening layer width was approximately 10%, while the error rates for the hardening layer depth and the tempering softening zone were below 5% and 10%, respectively. Based on simulations conducted with varying overlap rates, the flatness metric produces the best results at 50% overlap under these laser processing parameters. Full article

Offshore reservoirs in the high water-cut stage present significant development challenges, including declining production, complex remaining oil distribution, and the inadequacy of conventional evaluation methods to capture intricate flow dynamics. To overcome these limitations, this study introduces a novel approach based on flow diagnostics for performance evaluation and potential adjustment. The method integrates key metrics such as time-of-flight (TOF) and the dynamic Lorenz coefficient, supported by reservoir engineering principles and numerical simulation, to construct a multi-parameter evaluation system. This system, which also incorporates injection–production communication volume and inter-well fluid allocation factors, precisely quantifies and visualizes waterflood displacement processes and sweep efficiency. Applied to the QHD32 oilfield, this framework was used to establish specific thresholds for operational adjustments. These include criteria for infill drilling (waterflooded ratio < 45%, remaining oil thickness > 6 m, TOF > 200 days), conformance control (TOF < 50 days, dynamic Lorenz coefficient > 0.5), and artificial lift optimization (remaining oil thickness ratio > 2/3, TOF > 200 days). Field validation confirmed the efficacy of this approach: an additional cumulative oil production of 165,600 m³ was achieved from infill drilling in the C29 well group, while displacement adjustments in the B03 well group increased oil production by 2.2–3.8 tons/day, demonstrating a significant enhancement in waterflooding performance. This research provides a theoretical foundation and a technical pathway for the refined development of offshore heavy oil reservoirs at the ultra-high water-cut stage, offering a robust framework for the sustainable management of analogous reservoirs worldwide. Full article

Background: Failure to rescue (FTR), defined as death after major postoperative complications, is a critical quality indicator in pancreatic cancer surgery. Despite advances in surgical techniques and perioperative care, FTR rates remain high and vary across institutions. Methods: This systematic review uses a narrative synthesis followed by PRISMA 2020. A PubMed search (1992–2025) identified 83 studies; after screening, 52 studies (2010–2025) were included. Eligible designs were registry-based, multicenter, single-center, or prospective audits. Given substantial heterogeneity in study designs, FTR definitions, and outcome measures, a narrative synthesis was performed; no formal risk-of-bias assessment or meta-analysis was conducted. Results: Definitions of FTR varied (in-hospital, 30-day, 90-day, severity-based, and complication-specific cases). Reported rates differed by definition: average reported rates were 13.2% for 90-day CD ≥ III (G1); 10.3% for in-hospital/30-day CD ≥ III (G3); and 7.4% for 30-day “serious/major” morbidity (G8). Absolute differences were +3.0 and +2.9 percentage points (exploratory, descriptive comparisons). Five domains were consistently associated with lower FTR: (i) centralization to high-volume centers; (ii) safe adoption/refinement of surgical techniques; (iii) optimized perioperative management including early imaging and structured escalation pathways; (iv) patient-level risk stratification and prehabilitation; and (v) non-technical skills (NTSs) such as decision-making, situational awareness, communication, teamwork, and leadership. Among NTS domains, stress and fatigue management were not addressed in any included study. Limitations: Evidence is predominantly observational with substantial heterogeneity in study designs and FTR definitions; the search was limited to PubMed; and no formal risk-of-bias, publication-bias assessment, or meta-analysis was performed. Consequently, estimates and associations are descriptive/associative with limited certainty and generalizability. Conclusions: NTSs were rarely used or measured across the included studies, with validated instruments; quantitative assessment was uncommon, and no study evaluated stress or fatigue management. Reducing the FTR after pancreatic surgery will require standardized, pancreas-specific definitions of FTR, process-level rescue metrics, and deliberate strengthening of NTS. We recommend a pancreas-specific operational definition with an explicit numerator/denominator: numerator = all-cause mortality within 90 days of surgery; denominator = patients who experience major complications (Clavien–Dindo grade III–V, often labeled “CD ≥ 3”). Addressing the gaps in stress and fatigue management and embedding behavioral metrics into quality improvement programs are critical next steps to reduce preventable mortality after complex pancreatic cancer procedures. Full article

Powder bed fusion of copper has been extensively investigated using both laser-based (PBF-LB/M) and electron beam-based (PBF-EB/M) additive manufacturing technologies. Each technique offers unique benefits as well as specific limitations. Near-infrared (NIR) laser-based LPBF is widely accessible; however, the high reflectivity of copper limits energy absorption, thereby resulting in a narrow processing window. Although optimized parameters can yield relative densities above 97%, issues such as keyhole porosity, incomplete melting, and anisotropy remain concerns. Green lasers, with higher absorptivity in copper, offer broader process windows and enable more consistent fabrication of high-density parts with superior electrical conductivity, often reaching or exceeding 99% relative density and 100% International Annealed Copper Standard (IACS). Mechanical properties, including tensile and yield strength, are also improved, though challenges remain in surface finish and geometrical resolution. In contrast, Electron Beam Powder Bed Fusion (EB-PBF) uses high-energy electron beams in a vacuum, eliminating oxidation and leveraging copper’s high conductivity to achieve high energy absorption at lower volumetric energy densities (~80 J/mm³). This results in consistently high relative densities (>99.5%) and excellent electrical and thermal conductivity, with additional benefits including faster scanning speeds and in situ monitoring capabilities. However, EB-PBF faces its own limitations, such as surface roughness and powder smoking. This paper provides a comprehensive review of the current state of laser-based (PBF-LB/M) and electron beam-based (PBF-EB/M) powder bed fusion processes for the additive manufacturing of copper, summarizing key trends, material properties, and process innovations. Both approaches continue to evolve, with ongoing research aimed at refining these technologies to enable the reliable and efficient additive manufacturing of high-performance copper components. Full article

The primary aim of this study is to develop an effective decision-support system for managing crises related to the release of hazardous airborne substances. Such incidents, which can arise from industrial accidents or intentional releases, necessitate the rapid identification of contaminant sources to enable timely response measures. This work focuses on a novel approach that integrates a modified Sandpile model with advection and employs the (1 + 1)-Evolution Strategy to solve the inverse problem of source localization. The initial section of this paper reviews existing methods for simulating atmospheric dispersion and reconstructing source locations. In the following sections, we describe the architecture of the proposed system, the modeling assumptions, and the experimental framework. A key feature of the method presented here is its reliance solely on concentration measurements obtained from a distributed network of sensors, eliminating the need for prior knowledge of the source location, release time, or emission strength. The system was validated through a two-stage process using synthetic data generated by a Gaussian dispersion model. Preliminary experiments were conducted to support model calibration and refinement, followed by formal tests to evaluate localization accuracy and robustness. Each test case was completed in under 20 min on a standard laptop, demonstrating the algorithm’s high computational efficiency. The results confirm that the proposed (1 + 1)-ES Sandpile model can effectively reconstruct source parameters, staying within the resolution limits of the sensor grid. The system’s speed, simplicity, and reliance exclusively on sensor data make it a promising solution for real-time environmental monitoring and emergency response applications. Full article

Aiming at the problems of low efficiency, high energy consumption, and poor path quality during the multi-mechanism operation of bridge cranes in spatial tasks, an improved Rapidly exploring Random Tree (RRT) algorithm based on multi-strategy fusion is proposed for energy-efficient path planning. First, the improved algorithm introduces heuristic path information to guide the sampling process, enhancing the quality of sampled nodes. By defining a heuristic boundary, the search space is constrained to goal-relevant regions, thereby improving path planning efficiency. Secondly, focused sampling and reconnection strategies are adopted to significantly enhance path quality while ensuring the global convergence of the algorithm. Combined with line segment sampling and probability control strategies, the algorithm balances global exploration and local refinement, further optimizing path selection. Finally, Bezier curves are applied to smooth the generated path, markedly improving path smoothness and feasibility. Comparative experiments conducted on a constructed three-dimensional simulation platform demonstrate that, compared to other algorithms, the proposed algorithm achieves significant optimization in planning time, path cost, number of path nodes, and number of random tree nodes, while generating smoother paths. Notably, under different operational modes, this study provides a quantitative evaluation of operational efficiency and energy consumption based on energy efficiency trade-offs, offering an effective technical solution for the intelligent operation of bridge cranes. Full article