In a hyperspectral image, there is a close correlation between spectra and a certain degree of correlation in the pixel space. However, most existing low-rank representation (LRR) methods struggle to utilize these two characteristics simultaneously to detect anomalies. To address this challenge, a novel low-rank representation with dual graph regularization and an adaptive dictionary (DGRAD-LRR) is proposed for hyperspectral anomaly detection. To be specific, dual graph regularization, which combines spectral and spatial regularization, provides a new paradigm for LRR, and it can effectively preserve the local geometrical structure in the spectral and spatial information. To obtain a robust background dictionary, a novel adaptive dictionary strategy is utilized for the LRR model. In addition, extensive comparative experiments and an ablation study were conducted to demonstrate the superiority and practicality of the proposed DGRAD-LRR method. Full article

The finite-difference time-domain (FDTD) method is a versatile electromagnetic simulation technique, widely used for solving various broadband problems. However, when dealing with complex structures and large dimensions, especially when applying perfectly matched layer (PML) absorbing boundaries, tremendous computational burdens will occur. To reduce the computational time and memory, this paper presents a Message Passing Interface (MPI) parallel scheme based on non-uniform conformal FDTD, which is suitable for convolutional perfectly matched layer (CPML) absorbing boundaries, and adopts a domain decomposition approach, dividing the entire computational domain into several subdomains. More importantly, only one magnetic field exchange is required during the iterations, and the electric field update is divided into internal and external parts, facilitating the synchronous communication of magnetic fields between adjacent subdomains and internal electric field updates. Finally, unmanned helicopters, helical antennas, 100−period folded waveguides, and 16 × 16 phased array antennas are designed to verify the accuracy and efficiency of the algorithm. Moreover, we conducted parallel tests on a supercomputing platform, showing its satisfactory reduction in computational time and excellent parallel efficiency. Full article

Saving energy and resources has become increasingly important for industrial applications. Foremost, this requires knowledge about the energy requirement. For this purpose, this paper presents a state-based energy requirement model for mobile robots, e.g., automated guided vehicles or autonomous mobile robots, that determines the energy requirement by integrating the linearized power requirement parameters within each system state of the vehicle. The model and their respective system states were verified using a qualitative process analysis of 25 mobile robots from different manufacturers and validated by comparing simulated data with experimental data. For this purpose, power consumption measurements over 461 operating hours were performed in experiments with two different industrial mobile robots. System components of a mobile robot, which require energy, were classified and their power consumptions were measured individually. The parameters in the study consist of vehicle speed, load-handling duration, load, utilization, material flow and layout data, and charging infrastructure system frequency, yet these varied throughout the experiments. Validation of the model through real experiments shows that, in a $99\%$ confidence interval, the relative deviation in the modeled power requirement for a small-scale vehicle is $[-1.86\%,-1.14\%]$, whereas, for a mid-scale vehicle, it is $[-0.73\%,-0.31\%]$. This sets a benchmark for modeling the energy requirement of mobile robots with multiple influencing factors, allowing for an accurate estimation of the energy requirement of mobile robots. Full article

In this study, we analyze the CSMA Non-Persistent protocol with a finite number of nodes, providing more accurate results for applications like wireless sensor networks. The finite model addresses scenarios where the node count is moderate, capturing realistic system dynamics. Our analysis reveals a dependency on the node count, impacting system throughput. As the node count increases, throughput behavior aligns with Kleinrock’s infinite model. We derive a complex closed-form throughput expression for a finite quantity of nodes in the system, solved numerically, and offer an approximate expression for specific conditions. These insights advance understanding of low-contention network performance, especially in scenarios where the infinite model becomes inadequate. Full article

In this study, we investigated the outcomes and factors influencing treatment efficacy in 93 patients with limited disease small cell lung cancer (LD-SCLC), with a median age of 64 years. We focused on the impact of chemotherapy regimens, prophylactic cranial irradiation (PCI), and patient-related variables. The median follow-up for OS was 17.3 months. We observed a statistically significant difference in PFS between LD-SCLC patients treated with cisplatin and etoposide (EP) and those treated with carboplatin and etoposide (CP) (PFS: EP 13.63 months vs. CP 6.54 months, p < 0.01). Patients treated with EP had better overall survival (OS) than CP-treated patients (OS: EP 26.9 months vs. CP 16.16 months, p < 0.01). Concomitant chemotherapy was associated with improved PFS (p = 0.003) and OS (p = 0.002). Patients receiving PCI showed superior OS (p = 0.05) and a trend towards improved PFS (p = 0.057). Female gender was associated with better OS (p = 0.025). Most patients had an ECOG performance status of 0 (71%). This real-world study underscores the importance of multidisciplinary LD-SCLC management, emphasizing the roles of chemotherapy, radiotherapy, and PCI. These findings inform personalized treatment strategies and emphasize the need for prospective trials to validate these results and optimize LD-SCLC treatment. Full article

A fundamental task in computer vision is the process of differentiation and identification of different objects or entities in a visual scene using semantic segmentation methods. The advancement of transformer networks has surpassed traditional convolutional neural network (CNN) architectures in terms of segmentation performance. The continuous pursuit of optimal performance, with respect to the popular evaluation metric results, has led to very large architectures that require a significant amount of computational power to operate, making them prohibitive for real-time applications, including autonomous driving. In this paper, we propose a model that leverages a visual transformer encoder with a parallel twin decoder, consisting of a visual transformer decoder and a CNN decoder with multi-resolution connections working in parallel. The two decoders are merged with the aid of two trainable CNN blocks, the fuser that combined the information from the two decoders and the scaler that scales the contribution of each decoder. The proposed model achieves state-of-the-art performance on the Cityscapes and ADE20K datasets, maintaining a low-complexity network that can be used in real-time applications. Full article

In this study, graphene quantum dots (GQDs) have been incorporated into the g-C₃N₄/ZIF-67 heterojunction system as a photosensitizer to enhance photocatalytic conversion of CO₂-to-CO. The GQDs are deposited onto the surface of g-C₃N₄/ZIF-67 using a simple water bath procedure. As expected, GQDs/g-C₃N₄/ZIF-67 presents outstanding performance in CO₂ photoreduction. Among the GQDs/g-C₃N₄/ZIF-67 ternary photocatalysts, 7 GQDs-CN/ZIF-67 exhibits the best photocatalytic CO₂ reduction ability with a CO yield of 51.71 μmol g⁻¹, which is 5.05 and 1.87 times more than pristine g-C₃N₄ (10.24 μmol g⁻¹) and g-C₃N₄/ZIF-67 (27.65 μmol g⁻¹), respectively. This result shows that upon combination of GQDs with ZIF-67/g-C₃N₄, GQDs can be used as photosensitizers to improve the optical absorption capacity of the photocatalyst. Furthermore, GQDs serve as electron channels, facilitating the transport of photo-induced electrons from ZIF-67 to g-C₃N₄, which promotes photogenerated carrier separation efficiency. This study innovatively adds GQDs to the heterojunction and applies the prepared ternary composite to the CO₂ photoreduction, which inspires a novel direction for the design of non-noble metal photocatalysts. Full article

In this study, we sought to evaluate the capabilities of radiomics and machine learning in predicting seropositivity in patients with suspected autoimmune encephalitis (AE) from MR images obtained at symptom onset. In 83 patients diagnosed with AE between 2011 and 2022, manual bilateral segmentation of the amygdala was performed on pre-contrast T2 images using 3D Slicer open-source software. Our sample of 83 patients contained 43 seropositive and 40 seronegative AE cases. Images were obtained at our tertiary care center and at various secondary care centers in North Rhine-Westphalia, Germany. The sample was randomly split into training data and independent test data. A total of 107 radiomic features were extracted from bilateral regions of interest (ROIs). Automated machine learning (AutoML) was used to identify the most promising machine learning algorithms. Feature selection was performed using recursive feature elimination (RFE) and based on the determination of the most important features. Selected features were used to train various machine learning algorithms on 100 different data partitions. Performance was subsequently evaluated on independent test data. Our radiomics approach was able to predict the presence of autoantibodies in the independent test samples with a mean AUC of 0.90, a mean accuracy of 0.83, a mean sensitivity of 0.8,4 and a mean specificity of 0.82, with Lasso regression models yielding the most promising results. These results indicate that radiomics-based machine learning could be a promising tool in predicting the presence of autoantibodies in suspected AE patients. Given the implications of seropositivity for definitive diagnosis of suspected AE cases, this may expedite diagnostic workup even before results from specialized laboratory testing can be obtained. Furthermore, in conjunction with recent publications, our results indicate that characterization of AE subtypes by use of radiomics may become possible in the future, potentially allowing physicians to tailor treatment in the spirit of personalized medicine even before laboratory workup is completed. Full article

The mechanism underlying podocyte dysfunction in minimal change disease (MCD) remains unknown. This study aimed to shed light on the potential pathophysiology of MCD using glomerular proteomic analysis. Shotgun proteomics using label-free quantitative mass spectrometry was performed on formalin-fixed, paraffin-embedded (FFPE) renal biopsies from two groups of samples: control (CTR) and MCD. Glomeruli were excised from FFPE renal biopsies using laser capture microdissection (LCM), and a single-pot solid-phase-enhanced sample preparation (SP3) digestion method was used to improve yield and protein identifications. Principal component analysis (PCA) revealed a distinct separation between the CTR and MCD groups. Forty-eight proteins with different abundance between the two groups (p-value ≤ 0.05 and |FC| ≥ 1.5) were identified. These may represent differences in podocyte structure, as well as changes in endothelial or mesangial cells and extracellular matrix, and some were indeed found in several of these structures. However, most differentially expressed proteins were linked to the podocyte cytoskeleton and its dynamics. Some of these proteins are known to be involved in focal adhesion (NID1 and ITGA3) or slit diaphragm signaling (ANXA2, TJP1 and MYO1C), while others are structural components of the actin and microtubule cytoskeleton of podocytes (ACTR3 and NES). This study suggests the potential of mass spectrometry-based shotgun proteomic analysis with LCM glomeruli to yield valuable insights into the pathogenesis of podocytopathies like MCD. The most significantly dysregulated proteins in MCD could be attributable to cytoskeleton dysfunction or may be a compensatory response to cytoskeleton malfunction caused by various triggers. Full article

8-17 DNAzymes (8-17, 17E, Mg5, and 17EV1) are in vitro-selected catalytic DNA molecules that are capable of cleaving complementary RNAs. The conserved residues in their similar catalytic cores, together with the metal ions, were suggested to contribute to the catalytic reaction. Based on the contribution of the less conserved residues in the bulge loop residues (W¹², A¹⁵, A^15.0) and the internal stem, new catalytic cores of 8-17 DNAzymes were programmed. The internal stem CTC-GAG seems to be more favorable for the DNAzymes than CCG-GGC, while an extra W^12.0 led to a significant loss of activity of DNAzymes, which is contrary to the positive effect of A^15.0, by which a new active DNAzyme 17EM was derived. It conducts a faster reaction than 17E. It is most active in the presence of Pb²⁺, with the metal ion preference of Pb²⁺ >> Zn²⁺ > Mn²⁺ > Ca²⁺ ≈ Mg²⁺. In the Pb²⁺ and Zn²⁺-mediated reactions of 17EM and 17E, the same Na⁺- and pH dependence were also observed as what was observed for 17E and other 8-17 DNAzymes. Therefore, 17EM is another member of the 8-17 DNAzymes, and it could be applied as a potential biosensor for RNA and metal ions. Full article

The bubbling flow plays a key role in gas–liquid–solid fluidized beds. To understand the intrinsic fluidization behaviors at the discrete bubble and particle scale, coupled simulations with the volume of fluid model and the discrete element method are performed to investigate the effects of the gas inlet velocity, particle properties and two-orifice bubbling flow on particle fluidization. Three-dimensional simulations are carried out to accurately capture the dynamic changes in the bubble shape and trajectory. A bubbling flow with a closely packed bed is simulated to study the onset of particle fluidization. The obvious phenomena of particle fluidization are presented by both the experiment and simulation. Although an increasing gas inlet velocity promotes particle fluidization, the good fluidization of particles cannot be achieved solely by increasing the gas inlet velocity. When the channel is packed with more particles, the bubbles take a longer time to pass through the higher particle bed, and the bubbles grow larger in the bed. The increase in particle density also extends the time needed for the bubbles to escape from the bed, and it is more difficult to fluidize the particles with a larger density. Even if more particles are added into the channel, the percentage of suspended particles is not significantly changed. The percentage of suspended particles is not increased with a decrease in the particle diameter. The particle suspension is not significantly improved by the bubbling flow with two orifices, while the particle velocity is increased due to the more frequent bubble–particle collisions. The findings from this study will be beneficial in guiding the enhancement of particle fluidization in multiphase reactors. Full article

To address challenges related to the inadequate representation and inaccurate discrimination of pedestrian attributes, we propose a novel method for person re-identification, which leverages global feature learning and classification optimization. Specifically, this approach integrates a Normalization-based Channel Attention Module into the fundamental ResNet50 backbone, utilizing a scaling factor to prioritize and enhance key pedestrian feature information. Furthermore, dynamic activation functions are employed to adaptively modulate the parameters of ReLU based on the input convolutional feature maps, thereby bolstering the nonlinear expression capabilities of the network model. By incorporating Arcface loss into the cross-entropy loss, the supervised model is trained to learn pedestrian features that exhibit significant inter-class variance while maintaining tight intra-class coherence. The evaluation of the enhanced model on two popular datasets, Market1501 and DukeMTMC-ReID, reveals improvements in Rank-1 accuracy by 1.28% and 1.4%, respectively, along with corresponding gains in the mean average precision (mAP) of 1.93% and 1.84%. These findings indicate that the proposed model is capable of extracting more robust pedestrian features, enhancing feature discriminability, and ultimately achieving superior recognition accuracy. Full article

The binding ratio of palmitic acid (PA) at the sn-2 position of triacylglycerols in infant formulas is lower than that in breast milk, resulting in higher levels of fecal PA. Even if the ratio is increased to 40–50%, fecal PA levels in formula-fed infants remain higher than those in breast–fed infants. In Japan, infant formulas with 50% or more of PA bound to sn-2 (high sn-2 PA milk) are commercially available; however, their effects on PA excretion have not been investigated. Therefore, this observational study aimed to preliminarily evaluate whether the feeding volume of high sn-2 PA milk is significantly associated with fecal total/soaped PA levels in newborns. Infant formulas were classified as high (≥50% of PA bound to sn-2) or low sn-2 (<50%) PA milk. Associations between feeding volume of high or low sn-2 PA milk and fecal PA levels were evaluated using multiple regression analysis models. The results showed that the feeding volume of low sn-2 PA milk was positively associated with fecal total/soaped PA levels, while there was no significant association between those of high sn-2 PA milk and fecal total/soaped PA levels. Our preliminary study suggests that high sn-2 PA milk may reduce increased fecal PA levels in formula-fed newborns. Full article

A novel aromatic imine derivative, 2′-(1,4-phenylene)bis[4-[(4-methoxyphenyl)methylene]-5(4H)-oxazolone] (PBMBO), was designed and synthesized as a yellow colorant additive for green color filters used in image sensors. The optical and thermal properties of the newly developed material were evaluated both in solution and within color filter film conditions. PBMBO demonstrated a molar extinction coefficient of 2.24 × 10⁴ L/mol·cm in solution, surpassing that of the commercially employed yellow colorant MBIQO by a factor of 1.82. Color resist (CR) films incorporating PBMBO exhibited outstanding optical characteristics, displaying 0.03% transmittance at 435 nm, 99.3% transmittance at 530 nm, and a sharp slope within the 400 to 550 nm range. The decomposition temperature of PBMBO was 303 °C, indicating relatively superior thermal stability compared to MBIQO. Consequently, PBMBO emerges as a highly promising candidate for a yellow colorant additive in imaging sensor color filters, owing to its exceptional optical and thermal stability. Its potential applications are anticipated to extend across various fields of organic semiconductors. Full article

This paper presents an experimental study of the effect of the mass of dust retained on a fibrous filter bed operating singly and in a “cyclone-filter-bed” system on changes in filtration efficiency and accuracy, as well as the increase in flow resistance. The research was carried out using a novel and unprecedented method, determining the dust absorption coefficient km of the filter baffle under laboratory conditions. A filtration system built of a single cyclone and a cylindrical filter cartridge with an appropriately sized surface set behind it was studied. Conditions corresponding to the actual operating conditions of the air filter were maintained: dust concentration, filtration speed and dust extraction from the cyclone settling tank. The purpose of the research was to evaluate filter materials with different structures in terms of filtration efficiency and accuracy, as well as flow resistance. The study showed that the parameters of the structure of filter materials—permeability, grammage and thickness—affect the process of retaining dust particles. It was shown that the increase in the flow resistance of the filter bed has a higher intensity when dust grains of small sizes are directed at it, which is the case when the bed is operated behind a cyclone, which separates larger dust grains from the air. There is a reduction in the operating time of the filtration system due to the limitation of the permissible resistance ∆p_fdop, and the corresponding dust absorption k_m has a lower value. For a fixed value of the flow resistance, the dust absorption coefficient k_m2 of three different filtration baffles AC, B2, and B, working with a cyclone, take values 50–100% smaller than when working in a single-stage system. It has been shown that the “cyclone-filter baffle” unit, due to its greater dust separation capability, allows the filter cartridge to operate for a longer time until a certain flow resistance is reached. This allows the unit to operate longer at lower flow resistance without changing the filter cartridge, thus saving energy. The k_m values obtained during the tests, using the proposed original method, allow the selection of the filter bed for specific vehicle operating conditions by modelling its course. Full article

Pomelo peel is a natural substance with antibacterial properties. Its extraction process is simple, and the raw materials are abundant. Microcapsules were prepared using melamine resin as the wall material and pomelo peel flavonoids as the core material. The optimization of microcapsule preparation was explored by orthogonal and single-factor experiments. The findings indicated that the optimum process for the preparation of microencapsulation was a 0.12:1 mass ratio of core to wall material, 60 °C microencapsulation reaction temperature, 800 rpm microencapsulation reaction stirring speed, and 2% emulsifier concentration. On this basis, the microcapsules were applied to waterborne coatings at different levels, 0%, 3.0%, 6.0%, 9.0%, 12.0%, and 15.0%, respectively, to prepare paint films, and the properties of the paint films were tested and explored. The test showed that the microcapsules added to the waterborne paint film exhibited antibacterial activity while retaining good optical and mechanical properties. In comparison with Escherichia coli, the microcapsules had a greater antibacterial rate against Staphylococcus aureus. When the content of microcapsules was 6.0%, the general performance of the waterborne paint film was optimal. The antibacterial rate of the paint film against Staphylococcus aureus and Escherichia coli was 40.5% and 50.5%, respectively. The color difference was 3.28. The paint film had a certain elasticity area, the elongation at break was 10.8%, and the roughness was 1.75 μm. We successfully prepared microcapsules capable of improving the antibacterial performance of waterborne paint film, which expands the application field of waterborne coatings and provides a certain reference value for the antibacterial research of waterborne coatings. Full article

In the processing of emotions, the brain prepares and reacts in distinctive manners depending upon the negative or positive nuance of the emotion elicitors. Previous investigations showed that negative elicitors generally evoke more intense neural activities than positive and neutral ones, as reflected in the augmented amplitude of all sub-components of the event-related potentials (ERP) late posterior positivity (LPP) complex, while less is known about the emotion of disgust. The present study aimed to examine whether the LPP complex during the processing of disgust stimuli showed greater amplitude than other emotion elicitors with negative or positive valences, thus confirming it as a neural marker of disgust-related negativity bias at earlier or later stages. Thus, in the present study, we leveraged the ERP technique during the execution of an affective self-administered visual stimuli task to disentangle the neural contributions associated with images of positive, negative, disgust, or neutral images. Crucially, we showed that handling with disgust elicitors prompted the greatest neural activity and the highest delay during self-administration. Overall, we demonstrated progressive neural activities associated with the unpleasantness of the emotion elicitors and peculiar processing for disgust compared with all other emotions. Full article

Background: Endometriosis-associated ovarian cancer (EAOC) is a well-known type of cancer that arises from ovarian endometrioma (OE). OE contains iron-rich fluid in its cysts due to repeated hemorrhages in the ovaries. However, distinguishing between benign and malignant tumors can be challenging. We conducted a retrospective study on magnetic resonance (MR) relaxometry of cyst fluid to distinguish EAOC from OE and reported that this method showed good accuracy. The purpose of this study is to evaluate the accuracy of a non-invasive method in re-evaluating pre-surgical diagnosis of malignancy by a prospective multicenter cohort study. Methods: After the standard diagnosis process, the R2 values were obtained using a 3T system. Data on the patients were then collected through the Case Report Form (CRF). Between December 2018 and March 2023, six hospitals enrolled 109 patients. Out of these, 81 patients met the criteria required for the study. Results: The R2 values calculated using MR relaxometry showed good discriminating ability with a cut-off of 15.74 (sensitivity 80.6%, specificity 75.0%, AUC = 0.750, p < 0.001) when considering atypical or borderline tumors as EAOC. When atypical and borderline cases were grouped as OE, EAOC could be distinguished with a cut-off of 16.87 (sensitivity 87.0%, specificity 61.1%). Conclusions: MR relaxometry has proven to be an effective tool for discriminating EAOC from OE. Regular use of this method is expected to provide significant insights for clinical practice. Full article

A microwave-assisted synthesis of dialkyl and cyclic H-phosphonates via bis(2,2,2 trifluoroethyl) phosphonate (BTFEP) is described. This method enables the synthesis of various cyclic H-phosphonates and hetero-substituted dialkyl H-phosphonates by simple alcoholysis under non-inert and additive-free conditions. Short reaction times and the requirement for only stoichiometric amounts of alcohol render this method attractive for synthetic applications. Full article

This study offers a detailed analysis of building information modeling (BIM) policy and implementation across Europe, significantly contributing to the sector’s digital transformation. By collating data from governmental, academic, and industry sources, it identifies key trends and evaluates the effectiveness of BIM policies in advancing technology within construction. A systematic literature review and text mining across major databases revealed an increasing focus on sustainability, particularly “life cycle assessment” and “energy efficiency”, aligning with the Industry 5.0 initiative. The research shows that 35% of European countries have or plan to introduce BIM mandates, highlighting BIM’s crucial role in enhancing construction practices and influencing policy frameworks. Insights from this study are valuable for researchers, practitioners, and policymakers, guiding the adoption and operationalization of BIM and emphasizing the need for thorough market preparation, including funding, training, and standardization. Additionally, the study suggests a correlation between a country’s economic development and its propensity to enforce BIM mandates. Future research could explore regional policy variations and delve into the theoretical aspects of policy adoption and innovation diffusion to further understand BIM uptake dynamics. Full article

A review of the last 399 years (1624–2023) on fin whales (Balaenoptera physalus) in the Mediterranean Sea was conducted, based on an extensive compilation of records published in the scientific literature, technical reports, public databases, journals, and social media. A total of 10,716 sightings and 575 mortality events have been computed, analysed by semesters and mapped in order to compare the summer–winter seasons especially and their implications on migration–residence. Visual and acoustic detections, feedings, migrations, primary production areas (chlorophyll), threats and causes of death and their relations have been addressed, and a mini-review on heavy metals and pollutants has been carried out on fin whales in the Mediterranean Sea. Mortality events were most frequent between November and April, coinciding with the decreased sighting period. Ship strikes posed the greatest threat, peaking between May and October, when marine traffic tends to increase in the Mediterranean Sea. Two populations coexist in the Mediterranean Sea, one resident and the other migratory, the latter using the Strait of Gibraltar for its biannual movements. Two areas with a presence of calves (up to 7 m in length) between October and February were detected: one scattered in the northern Mediterranean and the Strait of Gibraltar and its surroundings. A critical zone for collisions has been established according to the results for fin whales in the Mediterranean Sea. Full article

Sports-related muscle injuries account for 10–55% of all injuries, which is a growing concern, especially given the aging world population. To evaluate the process of skeletal muscle injury and compare it with muscle lesions observed in humans, we developed a novel in vivo model in sheep. In this model, muscle injury was induced by an ultrasound-guided transverse biopsy at the myotendinous junction of the medial gastrocnemius muscle. Twelve male sheep were examined at 3, 7, 14, and 28 days post-injury. Histological, immunofluorescence, and MRI analyses indicate that our sheep model could resemble key human clinicopathological features. Statistically significant differences (p < 0.05) were observed in collagen I, dMHC, α-SMA, and CD68 immunohistochemical detection when comparing injured and healthy muscles. The injured gastrocnemius muscle exhibited elevated levels of type I collagen, infiltration of CD68(+) macrophages, angiogenesis, and the emergence of newly regenerated dMHC(+) myofibers, which persisted for up to 4 weeks post-injury. Similarly, the progression of muscle injury in the sheep model was assessed using advanced clinical 3 T MRI and compared with MRI scans from human patients. The data indicate that the sheep muscle injury model presents features similar to those observed in human skeletal muscle injuries. This makes it a valuable large animal model for studying muscle injuries and developing novel therapeutic strategies. Full article