Search Results (538)

Deep drilling and horizontal wells, as important means of unconventional oil and gas development, face problems with the high energy consumption but low removal efficiency of traditional well washing equipment, the uneven cleaning of horizontal well intervals, and an insufficient degree of automation. This paper proposes a novel hydraulic drive well washing device which consists of two main units. The wellbore cleaning unit comprises a hydraulic drive cutting–flushing module, a well cleaning mode-switching module, and a filter storage module. The unit uses hydraulic and mechanical forces to perform combined cleaning to prevent mud and sand from settling. By controlling the flow direction of the well washing fluid, it can directly switch between normal and reverse washing modes in the downhole area, and at the same time, it can control the working state of corresponding modules. The assembly control unit includes the chain lifting module and the arm assembly module, which can lift and move the device through the chain structure, allow for the rapid assembly of equipment through the use of a mechanical arm, and protect the reliability of equipment through the use of a centering structure. The device converts some of the hydraulic power into mechanical force, effectively improving cleaning and plugging removal efficiency, prolonging the downhole continuous working time of equipment, reducing manual operation requirements, and comprehensively improving cleaning efficiency and energy utilization efficiency. Full article

Edge computing (EC) plays a critical role in advancing the next-generation Industrial Internet of Things (IIoT) by enhancing production, maintenance, and operational outcomes across heterogeneous network boundaries. This study builds upon EC intelligence and integrates graph-based learning to propose a Cross-Layer Controller Tasking Scheme (CLCTS). The scheme operates through two primary phases: task grouping assignment and cross-layer control. In the first phase, controller nodes executing similar tasks are grouped based on task timing to achieve monotonic and synchronized completions. The second phase governs controller re-tasking both within and across these groups. Graph structures connect the groups to facilitate concurrent tasking and completion. A learning model is trained on inverse outcomes from the first phase to mitigate task acceptance errors (TAEs), while the second phase focuses on task migration learning to reduce task prolongation. Edge nodes interlink the groups and synchronize tasking, migration, and re-tasking operations across IIoT layers within unified completion periods. Departing from simulation-based approaches, this study presents a fully implemented framework that combines learning-driven scheduling with coordinated cross-layer control. The proposed CLCTS achieves an 8.67% reduction in overhead, a 7.36% decrease in task processing time, and a 17.41% reduction in TAEs while enhancing the completion ratio by 13.19% under maximum edge node deployment. Full article

Disassembly is a crucial process in industrial operations, especially in tasks requiring high precision and strict safety standards when handling components with collaborative robots. However, traditional methods often rely on rigid and sequential task planning, which makes it difficult to adapt to unforeseen changes or dynamic environments. This rigidity not only limits flexibility but also leads to prolonged execution times, as operators must follow predefined steps that do not allow for real-time adjustments. Although techniques like teleoperation have attempted to address these limitations, they often hinder direct human–robot collaboration within the same workspace, reducing effectiveness in dynamic environments. In response to these challenges, this research introduces an advanced human–robot interaction (HRI) system leveraging a mixed-reality (MR) interface embedded in a head-mounted device (HMD). The system enables operators to issue real-time control commands using multimodal inputs, including voice, gestures, and gaze tracking. These inputs are synchronized and processed via the Robot Operating System (ROS2), enabling dynamic and flexible task execution. Additionally, the integration of deep learning algorithms ensures precise detection and validation of disassembly components, enhancing accuracy. Experimental evaluations demonstrate significant improvements, including reduced task completion times, enhanced operator experience, and compliance with strict adherence to safety standards. This scalable solution offers broad applicability for general-purpose disassembly tasks, making it well-suited for complex industrial scenarios. Full article

This study conducted uniaxial creep tests on coal samples under both natural and water-saturated conditions for durations of about 180 days per sample to study the stability of coal pillar dams of the Daliuta Coal Mine underground reservoir. Combined with synchronized acoustic emission (AE) monitoring, the research systematically revealed the time-dependent deformation mechanisms and damage evolution laws of coal under prolonged water immersion and natural conditions. The results indicate that water-immersed coal exhibits a unique negative creep phenomenon at the initial stage, with the strain rate down to −0.00086%/d, attributed to non-uniform pore compaction and elastic rebound effects. During the steady-state creep phase, the creep rates under water-immersed and natural conditions were comparable. However, water immersion led to an 11.4% attenuation in elastic modulus, decreasing from 2300 MPa to 2037 MPa. Water immersion would also suppress AE activity, leading to the average daily AE events of 128, which is only 25% of that under natural conditions. In the accelerating creep stage, the AE event rate surged abruptly, validating its potential as an early warning indicator for coal pillar instability. Based on the identified long-term strength of the coal sample, it is recommended to maintain operational loads below the threshold of 9 MPa. This research provides crucial theoretical foundations and experimental data for optimizing the design and safety monitoring of coal pillar dams in CMURs. Full article

Background/Objectives: The gold standard of treatment for both melanoma and non-melanoma skin cancers is wide surgical resection to obtain oncological radicality, which occasionally results in functional or aesthetic impairment, potentially affecting quality of life. Despite the increased complexity of the technique, extended duration of hospitalization, and prolonged surgical operative times, microsurgery can facilitate the reconstruction of locally invasive skin cancers following ablative surgery and may yield superior functional and aesthetic outcomes. Consequently, microsurgical reconstruction is more likely to be necessary if a large skin tumor requires excision. However, the impact of this extensive and complex procedure on patients with skin cancer has not yet been fully elucidated. The objective of this research was to critically analyze the utilization of free flap reconstruction subsequent to skin cancer therapy. Through a comprehensive examination of published data, this study aimed to assess the potential benefits and drawbacks associated with this reconstructive approach. Methods: A systematic review of studies that were published from January 2004 to May 2024 was conducted using the MEDLINE online database search. To present an evidence summary and provide a systematic approach and quality assessment, the GRADE^® rating was applied to the results. Results: This review summarizes the oncological and clinical data, including previous interventions, adjuvant and neoadjuvant therapies, nodal status, distant metastasis, and follow-up time. Surgical outcome parameters such as healing time, flap survival, revision rate success, and minor and major complications were documented. Along with the findings, a quality assessment of the studies was also provided. Conclusions: This systematic review underscores the extensive use and efficacy of microsurgery for reconstruction after skin cancer excision; however, the literature remains limited by inconsistent reporting of oncological outcomes and the lack of a standardized approach to evaluate the impact of free flap reconstruction on both immediate and long-term cancer-specific results. Full article

Arsenic contamination in groundwater is a significant public health concern, with As(III) posing a greater and more challenging risk than As(V) due to its higher toxicity, mobility, and weaker adsorption affinity. Fe-Mn-based adsorbents offer a promising solution, simultaneously oxidizing As(III) to As(V), enhancing its adsorption. This study evaluates an Fe-Mn nanocomposite across typical batch (20 mg of adsorbent), fixed-bed column (28 g), and pilot-scale (2.5 kg) studies, bridging the gap between laboratory and real-world applications. Batch experiments yielded maximum adsorption capacities of 6.25 mg/g and 4.71 mg/g in a synthetic matrix and real groundwater, respectively, demonstrating the impact of the water matrix on adsorption. Operational constraints and competing anions led to a lower capacity in the pilot (0.551 mg/g). Good agreement was observed between the breakthrough curves in the pilot (breakthrough at 475 bed volumes) and the fixed-bed column studies (365–587 bed volumes) under similar empty bed contact times (EBCTs). The Thomas, Adams–Bohart, and Yoon–Nelson models demonstrated that lower flow rates and extended EBCTs significantly enhance arsenic removal efficiency, prolonging the operational lifespan. Our findings demonstrate the necessity of continuous-flow experiments using real contaminated water sources and the importance of optimizing flow conditions, EBCTs, and pre-treatment in order to successfully scale up Fe-Mn-based adsorbents for sustainable arsenic removal. Full article

As electric multiple unit (EMU) operations and maintenance demands have expanded, spare parts supply chain management has become increasingly crucial. This study emphasizes the supply challenges of EMU spare parts, including inadequate minimum inventory levels and prolonged response times. Redesigning the OEM–railway bureau vendor-managed inventory (VMI) model contract incentive and penalty system is the key goal. Connecting the spare parts supply system with its characteristics yields a game theory model. This study analyzes and compares the equilibrium strategies and profits of supply chain members under different mechanisms for managing critical spare parts. The findings demonstrate that mechanism contracts can enhance supply chain performance in a Pareto-improving manner. An in-depth analysis of downtime loss costs, procurement challenges, and order losses reveals their effects on supply chain coordination and profit allocation, providing railway bureaus and OEMs with a theoretical framework for supply chain decision-making. This study offers theoretical justification and a framework for decision-making on cooperation between OEMs and railroad bureaus in the management of spare parts supply chains, particularly for extensive EMU operations. Full article

This study creates and tests a machine learning model that can predict fuel use and emissions (NO_x, CO₂, CO, HC, PN) from a marine internal combustion engine when it is running normally. The model learned from data collected from conventional diesel fuel experiments. Subsequently, we evaluated its ability to transfer by employing the parameters associated with waste cooking oil (WCO) biodiesel and its 60/40 diesel mixture. The machine learning model demonstrated exceptional proficiency in forecasting diesel mode (R² > 0.95), effectively encapsulating both long-term trends and short-term fluctuations in fuel consumption and emissions across various load regimes. Upon the incorporation of WCO data, the model maintained its capacity to identify trends; however, it persistently overestimated emissions of CO, HC, and PN. This discrepancy arose primarily from the differing chemical composition of the fuel, particularly in terms of oxygen content and density. A significant correlation existed between indicators of incomplete combustion and the utilization of fuel. Nonetheless, NO_x exhibited an inverse relationship with indicators of combustion efficiency. The findings indicate that the model possesses the capability to estimate emissions in real time, requiring only a modest amount of additional training to operate effectively with alternative fuels. This approach significantly diminishes the necessity for prolonged experimental endeavors, rendering it an invaluable asset for the formulation of fuel strategies and initiatives aimed at mitigating carbon emissions in maritime operations. Full article

The widely utilized TiO₂ nanoparticles (NPs) tend to accumulate in wastewater and affect microbial growth. This work investigated the impacts of prolonged TiO₂ NP addition to filamentous aerobic granular sludge (AGS) using two identical sequencing batch reactors (SBRs, R1 and R2). R1 (the control) had no TiO₂ NP addition. In this reactor, filamentous bacteria from large AGS grew rapidly and extended outward, the sludge volume index (SVI₃₀) quickly increased from 41.2 to 236.8 mL/g, mixed liquid suspended solids (MLSS) decreased from 4.72 to 0.9 g/L, and AGS disintegrated on day 40. Meanwhile, the removal rates of COD and NH₄⁺-N both exhibited significant declines. In contrast, 5–30 mg/L TiO₂ NPs was added to R2 from day 21 to 100, and the extended filamentous bacteria were effectively controlled on day 90 under a 30 mg/L NP dosage, leading to significant reductions in COD and NH₄⁺-N capabilities, particularly the latter. Therefore, NP addition was stopped on day 101, and AGS became dominant in R2, with an SVI₃₀ and MLSS of 48.5 mL/g and 5.67 g/L on day 130. COD and NH₄⁺-N capabilities both increased to 100%. Microbial analysis suggested that the dominant filamentous bacteria—Proteobacteria, Bacteroidetes, and Acidobacteria—were effectively controlled by adding 30 mg/L TiO₂ NPs. XRF analysis indicated that 11.7% TiO₂ NP accumulation made the filamentous bacteria a framework for AGS recovery and operation without NPs. Functional analysis revealed that TiO₂ NPs had stronger inhibitory effects on nitrogen metabolism compared to carbon metabolism, and both metabolic pathways recovered when NP addition was discontinued in a timely manner. These findings offer critical operational guidance for maintaining the stable performance of filamentous AGS systems treating TiO₂ NP wastewater in the future. Full article

To address the challenges of prolonged current isolation times and high dependency on varistors in traditional flexible short-circuit fault isolation schemes for DC systems, this paper proposes a rapid fault isolation circuit design based on an adaptive solid-state circuit breaker (SSCB). By introducing an adaptive current-limiting branch topology, the proposed solution reduces the risk of system oscillations induced by current-limiting inductors during normal operation and minimizes steady-state losses in the breaker. Upon fault occurrence, the current-limiting inductor is automatically activated to effectively suppress the transient current rise rate. An energy dissipation circuit (EDC) featuring a resistor as the primary energy absorber and an auxiliary varistor (MOV) for voltage clamping, alongside a snubber circuit, provides an independent path for inductor energy release after faults. This design significantly alleviates the impact of MOV capacity constraints on the fault isolation process compared to traditional schemes where the MOV is the primary energy sink. The proposed topology employs a symmetrical bridge structure compatible with both pole-to-pole and pole-to-ground fault scenarios. Parameter optimization ensures the IGBT voltage withstand capability and energy dissipation efficiency. Simulation and experimental results demonstrate that this scheme achieves fault isolation within 0.1 ms, reduces the maximum fault current-to-rated current ratio to 5.8, and exhibits significantly shorter isolation times compared to conventional approaches. This provides an effective solution for segment switches and tie switches in millisecond-level self-healing systems for both low-voltage (LVDC, e.g., 750 V/1500 V DC) and medium-voltage (MVDC, e.g., 10–35 kV DC) smart DC distribution grids, particularly in applications demanding ultra-fast fault isolation such as data centers, electric vehicle (EV) fast-charging parks, and shipboard power systems. Full article

The reconstruction of a severely resorbed alveolar bone is a significant challenge in dental implantology and maxillofacial surgery. Traditional bone grafting materials, including autogenous, allogeneic, xenogeneic, and alloplastic materials, have limitations such as donor site morbidity, limited availability, and prolonged maturation periods. To address these challenges, recombinant human bone morphogenetic protein-2 (rhBMP-2) has emerged as a potent osteoinductive factor that facilitates bone regeneration without the need for additional donor site surgery. This study introduces a box technique which combines rhBMP-2 (CowellBMP^®, Cowellmedi, Busan, Republic of Korea) with a 3D-preformed titanium mesh (3D-PFTM), utilizing a mixture of allografts and xenografts for horizontal and vertical alveolar ridge augmentation. The technique leverages the structural stability provided by the OssBuilder^® (Osstem, Seoul, Republic of Korea), a preformed titanium mesh, that allows for simultaneous implant placement and vertical ridge augmentation. This technique not only reduces the treatment time compared to traditional methods but also minimizes post-operative discomfort by eliminating the need for autogenous bone harvesting. Clinical outcomes from this technique demonstrate successful bone regeneration within a shorter period than previously reported techniques, with excellent bone quality and implant stability being observed just four months after vertical augmentation. In conclusion, the so called BOXAM (BMP-2, Oss-builder, Xenograft, Allograft, Maintenance) technique presents a promising therapeutic strategy for alveolar bone reconstruction, particularly in cases of severe bone resorption. Further studies are needed to evaluate the long-term outcomes and potential limitations of this approach, especially in scenarios where the inferior alveolar nerve proximity poses challenges for fixture placement. Full article

Transverse fetal head position during labor is associated with increased rates of operative deliveries and cesarean sections. Traditional assessment methods rely on digital examination, which can be inaccurate in cases of prolonged labor. Intrapartum ultrasound offers improved diagnostic capabilities, but standardized interpretation frameworks are needed. This study aimed to evaluate the significance of appropriate assessment and management of transverse fetal head position during labor, with particular emphasis on the correlation between geometric parameters and delivery outcomes. Additionally, the investigation analyzed the potential role of Artificial Intelligence Dystocia Algorithm (AIDA) as an innovative decision support system in standardizing diagnostic approaches and optimizing clinical decision-making in cases of fetal malposition. This investigation was conducted as a focused secondary analysis of data originally collected for the development and validation of the Artificial Intelligence Dystocia Algorithm (AIDA). The study examined 66 cases of transverse fetal head position from a cohort of 135 nulliparous women with prolonged second-stage labor across three Italian hospitals. Cases were stratified by Midline Angle (MLA) measurements into classic transverse (≥75°), near-transverse (70–74°), and transitional (60–69°) positions. Four geometric parameters (Angle of Progression, Head–Symphysis Distance, Midline Angle, and Asynclitism Degree) were evaluated using the AIDA classification system. The predictive capabilities of three machine learning algorithms (Support Vector Machine, Random Forest, and Multilayer Perceptron) were assessed, and delivery outcomes were analyzed. The AIDA system successfully categorized labor dystocia into five distinct classes, with strong predictive value for delivery outcomes. A clear gradient of cesarean delivery risk was observed across the spectrum of transverse positions (100%, 93.1%, and 85.7% for near-transverse, classic transverse, and transitional positions, respectively). All cases classified as AIDA Class 4 required cesarean delivery regardless of the specific MLA value. Machine learning algorithms demonstrated high predictive accuracy, with Random Forest achieving 95.5% overall accuracy across the study cohort. The presence of concurrent asynclitism with transverse position was associated with particularly high rates of cesarean delivery. Among the seven cases that achieved vaginal delivery despite transverse positioning, none belonged to the classic transverse positions group, and five (71.4%) exhibited at least one parameter classified as favorable. The integration of artificial intelligence through AIDA as a decision support system, combined with intrapartum ultrasound, offered a promising approach for objective assessment and management of transverse fetal head position. The AIDA classification system’s integration of multiple geometric parameters, with particular emphasis on precise Midline Angle (MLA) measurement in degrees, provided superior predictive capability for delivery outcomes compared to qualitative position assessment alone. This multidimensional approach enabled more personalized and evidence-based management of malpositions during labor, potentially reducing unnecessary interventions while identifying cases where expectant management might be futile. Further prospective studies are needed to validate the predictive capability of this decision support system and its impact on clinical decision-making in real-time labor management. Full article

This study aims to explore a new concept for a Power to Heat (P2H) device and demonstrate its effectiveness compared to a thermal heating method. The proposed concept is a medium-temperature system where electro-thermal conversion occurs via the Joule effect in a metallic tube (resistive element). This tube also serves as a heat exchange surface between the heat transfer fluid and the thermal storage medium. The heat storage material here proposed consists of base concrete formulated on purpose to ensure its operation at high temperatures, good performance and prolongated thermal stability. The addition of 10%_wt phase change material (i.e., solar salts) stabilized in shape through a diatomite porous matrix allows the energy density stored in the medium itself to increase (hybrid sensible/latent system). Testing of the heat storage module has been conducted within a temperature range of 220–280 °C. An experimental comparison of charging times has demonstrated that electric heating exhibits faster dynamics compared to thermal heating. In both electrical and thermal heating methods, the concrete module has achieved 86% of its theoretical storage capacity, limited by thermal losses. In conclusion, this study successfully demonstrates the viability and efficiency of the proposed hybrid sensible/latent P2H system, highlighting the faster charging dynamics of direct electrical heating compared to conventional thermal methods, while achieving a comparable storage capacity despite thermal losses. Full article

Aerial tracking is an important service for many Unmanned Aerial Vehicle (UAV) applications. Existing work has failed to provide robust solutions when handling target disappearance, viewpoint changes, and tracking drifts in practical scenarios with limited UAV resources. In this paper, we propose a closed-loop framework integrating three key components: (1) a lightweight adaptive detection with multi-scale feature extraction, (2) spatiotemporal motion modeling through Kalman-filter-based trajectory prediction, and (3) autonomous decision-making through composite scoring of detection confidence, appearance similarity, and motion consistency. By implementing dynamic detection-tracking coordination with quality-aware feature preservation, our system enables real-time operation through performance-adaptive frequency modulation. Evaluated on VOT-ST2019 and OTB100 benchmarks, the proposed method yields marked improvements over baseline trackers, achieving a 27.94% increase in Expected Average Overlap (EAO) and a 10.39% reduction in failure rates, while sustaining a frame rate of 23–95 FPS on edge hardware. The framework achieves rapid target reacquisition during prolonged occlusion scenarios through optimized protocols, outperforming conventional methods in sustained aerial surveillance tasks. Full article

Neck of femur (NOF) fractures are a critical orthopaedic emergency with a high morbidity and mortality prevalence, particularly in people living with Human Immunodeficiency Virus (PLWHIV). A combination of HIV infection, combined antiretroviral therapy (cART), and compromised bone health further increases the risk of fragility fractures. Additionally, HIV-related immune dysfunction, cART-induced osteoporosis, and perioperative infection risks further pose challenges in ongoing surgical management. Despite the rising global prevalence of PLWHIV, no specific guidelines exist for the perioperative and post-operative care of PLWHIV undergoing NOF fracture surgery. This narrative review synthesises the current literature on the surgical management of NOF fractures in PLWHIV, focusing on pre-operative considerations, intraoperative strategies, post-operative complications, and long-term outcomes. It also explores infection control, fracture healing dynamics, and ART’s impact on surgical outcomes while identifying key research gaps. A systematic database search (PubMed, Embase, Cochrane Library) identified relevant studies published up to February 2025. Inclusion criteria encompassed studies on incidence, risk factors, ART impact, and NOF fracture outcomes in PLWHIV. Data were analysed to summarise findings and highlight knowledge gaps. Pre-operative care: Optimisation involves assessing immune status (namely, CD4 counts and HIV-1 viral loads), bone health, and cART to minimise surgical risk. Immunodeficiency increases surgical site and periprosthetic infection risks, necessitating potential enhanced antibiotic prophylaxis and close monitoring of potential start/switch/stopping of such therapies. Surgical management of neck of femur (NOF) fractures in PLWHIV should be individualised based on fracture type (intracapsular or extracapsular), age, immune status, bone quality, and functional status. Extracapsular fractures are generally managed with internal fixation using dynamic hip screws or intramedullary nails. For intracapsular fractures, internal fixation may be appropriate for younger patients with good bone quality, though there is an increased risk of non-union in this group. Hemiarthroplasty is typically favoured in older or frailer individuals, offering reduced surgical stress and lower operative time. Total hip arthroplasty (THA) is considered for active patients or those with pre-existing hip joint disease but carries a higher infection risk in immunocompromised individuals. Multidisciplinary evaluation is critical in guiding the most suitable surgical approach for PLWHIV. Importantly, post-operative care carries the risk of higher infection rates, requiring prolonged antibiotic use and wound surveillance. Antiretroviral therapy (ART) contributes to bone demineralisation and chronic inflammation, increasing delayed union healing and non-union risk. HIV-related frailty, neurocognitive impairment, and socioeconomic barriers hinder rehabilitation, affecting recovery. The management of NOF fractures in PLWHIV requires a multidisciplinary, patient-centred approach ideally comprising a team of Orthopaedic surgeon, HIV Physician, Orthogeriatric care, Physiotherapy, Occupational Health, Dietitian, Pharmacist, Psychologist, and related Social Care. Optimising cART, tailoring surgical strategies, and enforcing strict infection control can improve outcomes. Further high-quality studies and randomised controlled trials (RCTs) are essential to develop evidence-based guidelines. Full article