Search Results (36)

Background: First rib stress fractures (FRSFs) are exceptionally rare in skeletally immature athletes and are frequently overlooked because their symptoms mimic more common scapular conditions such as scapular dyskinesis or thoracic outlet syndrome. Early and accurate identification is critical to avoid delayed union, prolonged disability, and misdirected management. Case Presentation: We report a 12-year-old elite baseball pitcher with progressive scapular winging and audible snapping during pitching. Unlike typical posterior-type fractures near the costotransverse joint, imaging revealed a cortical discontinuity precisely at the serratus anterior enthesis, consistent with repetitive traction enthesopathy. High-resolution musculoskeletal ultrasound (MSK-US) identified cortical disruption with periosteal edema, and dynamic ultrasound reproduced the patient’s snapping and pain in real time, establishing a direct clinical–imaging correlation. Conservative three-phase rehabilitation (scapular stabilization, serratus anterior activation, and structured return-to-throwing) led to complete union and pain-free return to sport within 12 weeks. Discussion: This case highlights the superior diagnostic efficacy of MSK-US for FRSFs in adolescents. The posterior scanning approach facilitated bilateral comparison and growth plate assessment. Dynamic examination provided a functional correlation beyond static imaging, identifying a novel snapping mechanism. This underscores the value of MSK-US in visualizing not just anatomy but also pathophysiology. Conclusions: This is among the youngest documented cases of first rib stress fracture diagnosed with dynamic ultrasound. Its novelty lies in the following: (1) occurrence at the serratus anterior enthesis, (2) reproduction of snapping during provocative maneuvers, and (3) expansion of the etiological spectrum of scapular dyskinesis to include rib pathology. Dynamic ultrasound should be considered a frontline modality for adolescent throwers with unexplained periscapular pain. Full article

To address the modeling complexity and multi-objective collaborative optimization challenges in multi-depot and multiple unmanned aerial vehicle (UAV) delivery task planning, this paper proposes a bi-layer planning framework, which comprehensively considers resource constraints, multi-depot coordination, and the coupling characteristics of path execution. The novelty of this work lies in the seamless integration of an enhanced genetic algorithm and tailored swarm optimization within a unified two-tier architecture. The upper layer tackles the task assignment problem by formulating a multi-objective optimization model aimed at minimizing economic costs, delivery delays, and the number of UAVs deployed. The Enhanced Non-Dominated Sorting Genetic Algorithm II (ENSGA-II) is developed, incorporating heuristic initialization, goal-oriented search operators, an adaptive mutation mechanism, and a staged evolution control strategy to improve solution feasibility and distribution quality. The main contributions are threefold: (1) a novel ENSGA-II design for efficient and well-distributed task allocation; (2) an improved PSO-based path planner with chaotic initialization and adaptive parameters; and (3) comprehensive validation demonstrating substantial gains over baseline methods. The lower layer addresses the path planning problem by establishing a multi-objective model that considers path length, flight risk, and altitude variation. An improved particle swarm optimization (PSO) algorithm is proposed by integrating chaotic initialization, linearly adjusted acceleration coefficients and maximum velocity, a stochastic disturbance-based position update mechanism, and an adaptively tuned inertia weight to enhance algorithmic performance and path generation quality. Simulation results under typical task scenarios demonstrate that the proposed model achieves an average reduction of 47.8% in economic costs and 71.4% in UAV deployment quantity while significantly reducing delivery window violations. The framework exhibits excellent capability in multi-objective collaborative optimization. The ENSGA-II algorithm outperforms baseline algorithms significantly across performance metrics, achieving a hypervolume (HV) value of 1.0771 (improving by 72.35% to 109.82%) and an average inverted generational distance (IGD) of 0.0295, markedly better than those of comparison algorithms (ranging from 0.0893 to 0.2714). The algorithm also demonstrates overwhelming superiority in the C-metric, indicating outstanding global optimization capability in terms of distribution, convergence, and the diversity of the solution set. Moreover, the proposed framework and algorithm are both effective and feasible, offering a novel approach to low-altitude urban logistics delivery problems. Full article

This study’s novelty lies in providing first-time insights into the isolated role of Friction Stir Processing (FSP) travel speed on microstructure evolution and mechanical performance (micro-hardness, tensile properties, impact energy, and wear behavior) specifically in hypoeutectic as-cast Al-5 wt.% Si alloys, addressing a critical unaddressed gap in previous works (typically on near-eutectic compositions of Si > 6.5 wt.%). FSP, a solid-state technique, is highly effective for enhancing the properties of cast materials. The FSP was conducted at a fixed rotational speed of 1330 rpm and various travel speeds (26, 33, 42, and 52 mm/min). The FSP improves the mechanical properties of as-cast Al-5Si alloy by refining its grain structure. This leads to higher hardness, ultimate tensile strength (UTS), yield strength (YS), and strain at fracture and toughness compared to the as-cast condition. The specimen processed at 26 mm/min achieved the highest values of YS, UTS, toughness, and wear resistance. The fracture surfaces of the tensile and impact test specimens were examined using scanning electron microscopy (SEM) and discussed. Results indicated that the fracture surfaces revealed a transition from predominantly brittle fracture in the as-cast alloy to ductile fracture at 26 mm/min, changing to a mixed fracture mode at 52 mm/min. These findings underscore the critical importance of optimizing FSP travel speed to significantly tailor and enhance the mechanical performance of as-cast hypoeutectic Al-5Si alloys for industrial applications. Full article

This study presents a comprehensive kinetic and thermodynamic investigation of dried orange peel (OP) combustion, employing thermogravimetric analysis (TGA) and differential thermogravimetry (DTG) at high heating rates (20–80 K min⁻¹). This gap in high heating rate analysis motivates the novelty of present study, by investigating OP combustion at 20, 40, 60, and 80 K min⁻¹ using TGA, to closely simulate rapid thermal conditions typical of industrial combustion processes. Thermal decomposition occurred in three distinct stages corresponding sequentially to the dehydration, degradation of hemicellulose, cellulose, and lignin. Activation energy (E_a) was calculated using six model-free methods—Friedman (FR), Flynn–Wall–Ozawa (FWO), Kissinger–Akahira–Sunose (KAS), Starink (STK), Kissinger (K), and Vyazovkin (VY)—yielding values between 64 and 309 kJ mol⁻¹. The E_a increased progressively from the initial to final degradation stages, reflecting the thermal stability differences among biomass constituents. Further kinetic analysis using the Coats–Redfern (CR) model-fitting method identified that first-order (F1), second-order (F2), and diffusion-based mechanisms (D1, D2, D3) effectively describe OP combustion. Calculated thermodynamic parameters—including enthalpy (ΔH), Gibbs free energy (ΔG), and entropy (ΔS)—indicated the endothermic and increasingly non-spontaneous nature of the reactions at higher conversions. These findings demonstrate the potential of OP, an abundant agricultural waste product, as a viable bioenergy resource, contributing valuable insights into sustainable combustion processes. Full article

The Solar Reflectance Index (SRI) is a standardized metric used to assess the reflective properties of materials in relation to solar radiation and their capacity to emit absorbed heat, particularly within the infrared spectrum. Materials with high SRI values, often referred to as “cool materials”, contribute to ambient temperature regulation, Urban Heat Island (UHI) mitigation, and cooling energy demand reduction. The effectiveness of SRI depends on factors such as solar incidence angles, intrinsic material properties, and varying environmental conditions. Accurate assessments require the implementation of standardized testing and rating methodologies. This paper reviews and compares North American (ASTM E1980, ASTM C1549, ASTM C1371) and European (EN 15976) standards to determine SRI, focusing on the impacts of weathering and climatic factors on material aging. The study highlights the inadequacy of current practices, which typically measure SRI after only three years of exposure, and advocates for long-term performance monitoring across diverse climates. Key findings reveal that high-SRI materials can reduce surface temperatures by up to 20 °C, significantly lowering cooling energy demands. The study recommends the development of comparable standards to measure solar reflectivity on vertical surfaces, emphasizing the importance of assessing long-term performance across various climatic conditions. Findings underscore the importance of advanced modeling, innovative materials development, and effective maintenance strategies to extend the durability and efficacy of cool materials. The novelty of this work lies in its comprehensive framework for SRI assessment, integrating advanced modeling, innovative materials development, and real-world performance monitoring. This study provides actionable insights for policymakers, urban planners, and architects to enhance building energy efficiency and urban resilience. Full article

Recognized as an NP-hard combinatorial challenge, Storage Location Assignment Problem (SLAP) demands heuristic or algorithmic solutions for effective optimization. This paper specifically examines the enhancement of SLAP through the utilization of evolutionary algorithms, as they are particularly suitable for complex cases. Among others, the genetic algorithm (GA) is typically applied to solve this problem. This paper investigates the Bacterial Memetic Algorithm (BMA) as a possible solution for optimization. Though the comparative analysis of the BMA with the previously well-used GA algorithm under certain test parameters reveals that BMA is suitable for SLA optimization, BMA failed to achieve better results. We attribute the unsatisfactory results to the parameter settings, as illustrated by a few specific examples. However, the complexity of the problem and the parameterization does not allow for continuous manual parameter adjustment, which is why we have identified the need for a concept that automatically and adaptively adjusts the parameter settings based on the statistics and fitness values obtained during the execution. The novelty of this paper is to specify the concept of adaptive BMA parameterization and rules. Full article

This article presents a vibration signal analysis method to diagnose helicopter turboshaft engine defects such as bearing imbalance and wear. The scientific novelty of the article lies in the development of a comprehensive approach to diagnosing helicopter turboshaft engine defects based on the vibration signals amplitude and frequency characteristics integral analysis combined with a neural network for probabilistic defect detection. Unlike existing methods, the proposed approach uses the energy criterion for the vibration characteristics. It averages the assessment of unique signal processing algorithms, which ensures reliable defect classification under flight vibration conditions. The method is based on representing vibration signals as a sum of harmonic oscillations supplemented by noise components, which helps to identify deviations from typical values. The developed method includes a state function in which the amplitudes and frequency characteristics from nominal parameters estimate deviations. When the critical threshold is exceeded, the function signals possible malfunctions. A multilayer neural network is used to classify defect types, providing high classification accuracy (from 0.985 to 0.994). Computer experiments on the developed seminaturalistic modeling stand confirm that the method can detect increased vibration levels, which is the potential failure indicator. Comparative analysis shows the proposed method’s accuracy and noise resistance superiority, emphasizing the importance of introducing modern technologies to improve aircraft operation reliability and safety. Full article

Geothermal wells are subjected to higher loads compared to conventional oil and gas wells due to the thermal cycles that occur during both production and non-production phases. These temperature variations can affect the cohesion of the cement within the formation and casing, creating micro-annuli channels that can ultimately compromise the integrity of the well. Therefore, this study employs an intensive finite element methodology to analyze the debonding criteria of casing–cement systems in geothermal wells by examining over 36 independent models. The wellbore cooling and heating processes were simulated using three cohesive zone models (CZM): Type I (tensile), Type II (shear), and mixed (Type I and II simultaneously). The analysis revealed that Type I debonding occurs first during cooling at a temperature of around 10 °C, while Type II is the primary failure mode during heating. Evaluations of interfacial bonding shear strength (IBSS) values indicated that the debonding of the cement would even occur at high IBSS values (3 and 4 MPa) at a differential temperature of 300 °C, while the other IBSS of 1 MPa withstands only 60 °C. However, achieving an IBSS of 4 MPa with current technology is highly unlikely. Therefore, geothermal well operation and construction must be modified to keep the differential temperature below the critical temperature at which the debonding of the cement initiates. The study also found that debonding during cooling happens at lower differential temperatures due to generally lower values for interfacial bonding tensile strength (IBTS), typically less than 1 MPa. The novelty of the study is that it provides new insights into how specific temperatures trigger different types of debonding, highlights that high IBSS values may not prevent debonding at high differential temperatures, and recommends operational adjustments to maintain temperatures below critical levels to enhance cement integrity. Additionally, this study reveals that debonding during cooling occurs at a lower differential temperature change due to the reduced value of the interfacial bonding tensile strength (IBTS). Full article

Renewable energy communities (RECs) have been gaining momentum around the world, as a way to promote sustainable development and combat climate change. These communities are typically composed of individuals, businesses, and organizations that come together to invest in and promote the use of renewable energy sources, such as solar, wind, and hydraulic power. This article focuses on the benefits that renewable energy communities bring to a territory through the diffusion of renewable energy systems, tackling different issues like local depopulation, increasing energy prices, and a lack of jobs, while reducing greenhouse gas emissions and improving air quality. The novelty of this article lies in the results from the first-of-its-kind national call within the Next Appennino program, part of the National Complementary plan, aimed at the formation and proliferation of RECs in the area severed by the 2009 and 2016 earthquakes in Italy, as a way to add social, environmental, and sustainable value to the reconstruction of this territory. The data refer to the municipality of Castelraimondo and Unione Montana dei Monti Azzurri (a consortium of mountain municipalities), both located in the Marche region. Analysis of the consumer and prosumer energy needs, as well as the quantification of the exploitable production from the new renewable generators installed, showed that a total of 6.134 GWh/year can be shared by the community. Full article

Significant waste streams produced during winemaking include winery by-products such as pomace, skins, leaves, stems, lees, and seeds. These waste by-products were frequently disposed of in the past, causing resource waste and environmental issues. However, interest has risen in valorizing vineyard by-products to tap into their latent potential and turn them into high-value products. Wine industry by-products serve as a potential economic interest, given that they are typically significant natural bioactive sources that may exhibit significant biological properties related to human wellness and health. This review emphasizes the significance of winery by-product valorization as a sustainable management resource and waste management method. The novelty of this review lies in its comprehensive analysis of the potential of winery by-products as a source of bioactive compounds, extraction techniques, health benefits, and applications in various sectors. Chemical components in winery by-products include bioactive substances, antioxidants, dietary fibers, organic acids, and proteins, all of which have important industrial and therapeutic applications. The bioactives from winery by-products act as antioxidant, antidiabetic, and anticancer agents that have proven potential health-promoting effects. Wineries can switch from a linear waste management pattern to a more sustainable and practical method by adopting a circular bioeconomy strategy. Consequently, the recovery of bioactive compounds that function as antioxidants and health-promoting agents could promote various industries concomitant within the circular economy. Full article

To initially improve the gas production rate and shorten the payback period for tight gas reservoirs, the multiple-fractured horizontal well (MFHW) model is always applied. However, in the late stages of exploitation, it is difficult to adopt reasonable measures for enhanced gas recovery (EGR), particular for continental sedimentary formation with multiple layers, and efficient strategies for EGR in this type of gas field have not yet been presented. Therefore, in this paper, a typical tight gas reservoir in the late stages of exploitation, the Denglouku gas reservoir in Changling gas field, in which MFHWs were utilized and contributed to the communication of the higher Denglouku formation (0.34 mol% CO₂) and lower Yingcheng formation (27 mol% CO₂) during hydraulic fracturing, is studied comprehensively. Firstly, alongside the seismic, logging, drilling and experimental data, 3D geological and numerical simulation models are developed. According to the differences in CO₂ mole fractions for different formations, the gas production rate of MFHWs produced from Denglouku formation is accurately calculated. Then, the well gas production rate (WGPR) and the well bottom-hole pressure (WBHP) history are matched with the calculated values, and thus the types of remaining gas are provided through the fine reservoir description. Finally, in a combination of gas recovery and economics, the optimal infill well type and the adjustment scheme are determined. The results show that there are three main categories of remaining gas, which are areal distribution, abundant points, and marginal dispersion, and the ratios of reaming gas reserve for these three types are 80.3%, 4.2%, and 15.5%, respectively. For the tight gas reservoir developed by MFHWs with parallel and zipper patterns, the best infilling well type is the vertical well. The combination of patching holes, sidetracking, infilling and boosting can obtain the highest gas recovery, while the scheme with patching holes and sidetracking has the best economic benefits. To balance the gas recovery and economics, the measurement of patching holes, sidetracking and infilling with vertical wells is utilized. In the final production period, compared with the basic schemes, the gas recovery can increase by 5.5%. The primary novelty of this paper lies in the determination of the optimal infilling well types and its presentation of a comprehensive adjustment workflow for EGR in tight gas reservoirs. The conclusions in this paper can provide some guidance for other similar tight gas reservoirs developed with MFHWs in the later period. Full article

The primary goal of this research study is to examine the influence of Brownian motion and thermophoresis diffusion with the impact of thermal radiation and the bioconvection of microorganisms in a symmetrically stretching sheet of non-Newtonian typical Williamson fluid. Structures of the momentum, energy, concentration, and bio-convection equations are interconnected with the imperative partial differential equations (PDEs). Similarity transformations are implemented to translate pertinent complicated partial differential equations into ordinary differential equations (ODEs). The BVP4C approach from the MATLAB assemblage computational methods scheme is extensively impacted by the results of these ODEs. The impact of several physical parameters, including Williamson fluid $We(0.2\le We\le 1.2)$, the magnetic field parameter $M(0.0\le M\le 2.5)$, Brownian motion $Nb(0.0\le Nb\le 1.0)$, thermophoresis diffusion $Nt(0.1\le Nt\le 0.9)$. In addition, various physical quantities of the skin friction ($\sqrt{R{e}_x}{C}_{f_x}$), Nusselt number ($N_{u_x}$), Sherwood number ($S_{h_x}$), and motile microorganisms ($N_{n_x}$) are occupied and demonstrate the visualization of graphs and tabular values. These outcomes are validated with earlier obtained results, displaying excellent synchronicity in the physical parameters. Furthermore, the physical quantities concerning the non-dimensional parameters are anticipated by employing Multiple Linear Regression (MLR) in Machine Learning (ML) as successfully executed a novelty of this study. These innovative techniques can help to advance development and technologies for future researchers. The real-world implications of this research are that bio-remediation, microbial movements in mixed fluids, and cancer prevention therapy are crucial. Full article

Anaerobic digestion (AD) is usually carried out at mesophilic temperatures (25–45 °C) in most countries, whether in temperate or tropical climates, which results in the need for heat injection and consequently increases costs. In this regard, batch AD tests were conducted at 25, 28, and 35 °C, with 25 °C being the lowest ambient temperature in Panama, using thickened secondary sludge (TSS) and digested secondary sludge (DSS) from the Juan Diaz wastewater treatment plant (WWTP) to determine the Biochemical Methane Potential (BMP). The AD study generated maximum mean BMP values of 163 mL CH₄/g VS for DSS and 289.72 mL CH₄/g VS for codigestion at 25 °C. The BMP value of DSS at 25 °C showed that it can still be used for energy generation, using the lowest ambient temperature recorded in Panama City. Likewise, trials at 25 °C showed a 43.48% reduction in the electrical energy produced compared to that generated at 38 °C in WWTP. This results in a reduction in energy, as the use of heat could be omitted and the energy costs required for the process are covered. In this regard, the novelty of this work lies in its investigation of anaerobic digestion at ambient temperatures, which represents a departure from conventional practices that typically require higher temperatures. By exploring the feasibility of anaerobic digestion within the temperature range of 25–35 °C, this study offers a novel approach to optimizing energy efficiency and reducing costs associated with elevated temperatures. Full article

The need for reducing fossil fuel consumption and greenhouse gas (GHG) emissions in internal combustion engines has raised the opportunity for the use of renewable energy sources. For the progressive replacement of fossil fuels like diesel, those derived from the sustainable management of forest resources may be a good option. In Portugal, pine trees (pinus pinaster) are among the most widely cultivated tree species. Turpentine can be extracted from their sap without harming the tree. Turpentine is known to be a good fuel with a lower viscosity than regular diesel but with a comparable caloric value, boiling point and ignition characteristics, although it is not widely used as a compression ignition fuel. Moreover, recent research has highlighted the possibility of substantially increasing the turpentine yield through biotechnology, bringing it closer to economic viability. The present study investigates the performance, pollutant emissions and fuel consumption of a 1.6 L four-cylinder direct-injection diesel engine operating with several blends of commercial diesel fuel and turpentine obtained from pine trees. The aim of this study was to assess whether it would be possible to maintain or even improve the performance, fuel consumption and GHG and pollutant emissions (HC, NO_x, CO and PM) of the engine with the partial incorporation of this biofuel. Turpentine blends of up to 30% in substitution of regular diesel fuel were tested. The main novelties of the present work are related to (i) the careful testing of a still-insufficiently studied fuel that could gain economical attractiveness with the recent developments in yield improvement through biotechnology and (ii) the tests conducted under fixed engine load positions typical of road and highway conditions. The addition of this biofuel only slightly impacted the engine performance parameters. However, a slightly positive effect was observed in terms of torque, with an increase of up to 7.9% at low load for the 15T85D mixture and 6.8% at high load being observed. Power registered an increase of 9% for the 15T85D mixture at low speed and an increase of 5% for the 30T70D mixture at high speed when compared to the reference fuel (commercial diesel fuel). While the efficiency and fossil GHG emissions were improved with the incorporation of turpentine, it had a mixed effect on polluting emissions such as unburned hydrocarbons (HC) and smoke (PM) and a negative effect on nitrogen oxides (NO_x). NO_x emissions increased by 30% for high loads and 20% for low loads, mainly as an indirect effect of the improvement in the engine performance and not so much as a consequence of the marginally higher oxygen content of turpentine relative to commercial diesel fuel. Full article

Laser Induced-Thermionic Vacuum Arc (LTVA) technology was used for depositing uniform intermetallic CoNi thin films of 100 nm thickness. LTVA is an original deposition method using a combination of the typical Thermionic Vacuum Arc (TVA) system and a laser beam provided by a QUANTEL Q-Smart 850 Nd:YAG compact Q-switched laser with a second harmonic module. The novelty is related to the simultaneous deposition of a bi-component metallic thin film using photonic processes of the laser over the plasma deposition, which improves the roughness but also triggers the composition of the deposited thin film. Structural analysis of the deposited thin films confirms the formation of face-centered cubic (fcc) as the main phase CoNi and hexagonal Co₃Ni as the minority phase, observed mainly using high-resolution transmission electron microscopy. The magneto-optical measurements suggest an isotropic distribution of the CoNi alloy thin films for the in-plan angular rotation. From the low coercive field of H_c = 40 Oe and a saturation field at 900 Oe, the CoNi thin films obtained by LTVA are considered semi-hard magnetic materials. Magnetic force microscopy reveals spherical magnetic nanoparticles with mean size of about 40–50 nm. The resistivity was estimated at $\rho$ = 34.16 μΩ cm, which is higher than the values for bulk Co and Ni. Full article