The hepatic deletion of Rbpjκ (Rbpj^F/F::AlbCre) in the mouse leads to exhibition of the Alagille syndrome phenotype during early postnatal liver development with hyperlipidemia and cholestasis due to attenuated disruption of NOTCH signaling. Given the roles of NRF2 signaling in the regulation of lipid metabolism and bile ductal formation, it was anticipated that these symptoms could be alleviated by enhancing NRF2 signaling in the Rbpj^F/F::AlbCre mouse by hepatic deletion of Keap1 in compound Keap1^F/F::Rbpj^F/F::AlbCre mice. Unexpectedly, these mice developed higher hepatic and plasma cholesterol levels with more severe cholestatic liver damage during the pre-weaning period than in the Rbpj^F/F::AlbCre mice. In addition, hypercholesterolemia and hepatic damage were sustained throughout the growth period unlike in the Rbpj^F/F::AlbCre mouse. These enhanced abnormalities in lipid metabolism appear to be due to NRF2-dependent changes in gene expression related to cholesterol synthetic and subsequent bile acid production pathways. Notably, the hepatic expression of Cyp1A7 and Abcb11 genes involved in bile acid homeostasis was significantly reduced in Keap1^F/F::Rbpj^F/F::AlbCre compared to Rbpj^F/F::AlbCre mice. The accumulation of liver cholesterol and the weakened capacity for bile excretion during the 3 pre-weaning weeks in the Keap1^F/F::Rbpj^F/F::AlbCre mice may aggravate hepatocellular damage level caused by both excessive cholesterol and residual bile acid toxicity in hepatocytes. These results indicate that a tuned balance of NOTCH and NRF2 signaling is of biological importance for early liver development after birth. Full article

The platelet-rich plasma (PRP) approach may be an effective treatment for joint and cartilage pathologies. However, the rationale for its effectiveness on joint instability is limited. This study aimed to assess the safety and effectiveness of PRP injections in patients with chronic lateral ankle instability (CLAI). This retrospective study was performed at a single-center outpatient clinic between January 2015 and February 2023 and included pre-intervention assessment and short-term follow-up. Patients were excluded if they had received previous surgical treatment or had constitutional hyperlaxity, systemic diseases, or grade II or III osteoarthritis. The clinical and functional evaluation consisted of the Karlsson score, the Cumberland Ankle Instability Tool (CAIT), Good’s grading system, the patient’s subjective satisfaction level, and the time required to return to exercise. The entire PRP therapy regime consisted of three PRP administrations at 7-day intervals and follow-up appointments. PRP was administered both intraarticularly and into talofibular ligaments. A total of 47 consecutive patients with CLAI were included, 11 were female (23.4%), with a mean age at intervention of 31.19 ± 9.74 years. A statistically significant improvement was found in the CAIT and Karlsson scores at 3 months (27.74 ± 1.68 and 96.45 ± 4.28, respectively) relative to the pre-intervention status (10.26 ± 4.33 and 42.26 ± 14.9, respectively, p < 0.000). The mean follow-up of patients with CLAI was 17.94 ± 3.25 weeks. This study represents successful short-term functional and clinical outcomes in patients with CLAI after PRP treatment, with no adverse effects. It demonstrates the feasibility of a randomized controlled trial to further assess this therapy. Full article

Woven flax-carbon hybrid polyamide biocomposites offer a blend of carbon fibers’ mechanical strength and flax’s environmental advantages, potentially developing material applications. This study investigated their thermal behavior, degradation kinetics, and durability to water uptake and relative humidity exposure and compared them with pure flax and carbon composites with the same matrix. The hybrid composite exhibited intermediate water/moisture absorption levels between pure flax and carbon composites, with 7.2% water absorption and 3.5% moisture absorption. It also displayed comparable thermal degradation resistance to the carbon composite, effectively maintaining its weight up to 300 °C. Further analysis revealed that the hybrid composite exhibited a decomposition energy of 268 kJ/mol, slightly lower than the carbon composite’s value of 288.5 kJ/mol, indicating similar thermal stability. Isothermal lifetime estimation, employing the activation energy (E_d) and degree of conversion facilitated by the Model Free Kinetics method, indicated a 41% higher service life of the hybrid laminate at room temperature compared to the carbon laminate. These insights are crucial for understanding the industrial applications of these materials without compromising durability. Full article

Electromagnetic actuation can support many fields of technology, such as robotics or biomedical applications. In this context, fully understanding the system behavior and proposing a low-cost package for feedback control is challenging. Modeling the electromagnetic force is particularly tricky because it is a nonlinear function of the actuated object’s position and coil’s current. Measuring in real time the position of the actuated object with the precision required for accurate motion control is also nontrivial. In this study, we propose a novel, cost-effective electromagnetic set-up to achieve position control via visual feedback. We actuated vertically and under different experimental conditions a 10 mm diameter steel ball hanging on a low-stiffness spring, demonstrating good tracking performance (the position error remained within ±0.5 mm, with a negligible phase delay in the best scenarios). The experimental results confirm the feasibility of the proposed set-up, which is characterized by minimum complexity and realized with off-the-shelf and cost-effective components. For these reasons, such a contribution helps to understand and apply electromagnetic actuation even further. Full article

Thrust constitutes a pivotal performance parameter for aircraft engines. Thrust, being an indispensable parameter in control systems, has garnered significant attention, prompting numerous scholars to propose various methods and algorithms for its estimation. However, research methods for estimating the thrust of the micro-turbojet engines used in unmanned aerial vehicles are relatively scarce. Therefore, this paper proposes a thrust estimator for micro-turbojet engines based on DBO (dung beetle optimization) utilizing bidirectional long short-term memory (BiLSTM) and a convolutional neural network (CNN). Furthermore, the efficacy of the proposed model is further validated through comparative analysis with others in this paper. Full article

(1) In an era where sustainable behavior is increasingly crucial, understanding the discrepancy between individuals’ sustainability-oriented values and their actual behaviors, known as the inner–outer gap, is vital. This systematic literature review explores the potential of the Tripartite Structure of Sustainability (TSS) framework to address this gap within the context of sustainable education. By reviewing the literature from the APA, ERIC, and Web of Science databases, searched on 25 October 2020, the factors influencing sustainable actions were systematically examined. Articles had to be relevant to the topic (sustainability, morality in relation to sustainability, or morality in general) and report on empirically validated factors that have an impact on the inner-outer gap. (2) By employing a qualitative content analysis approach, 56 articles over a 15-year period were analyzed, identifying 83 factors that either bridged or reinforced the inner–outer gap. These factors were categorized within the TSS framework, which segments sustainability-oriented actions into individual, social, and self-transcendent domains, alongside their activation points: stable, situational, or automated. (3) The analysis revealed that self-focused factors often reinforce the gap, suggesting they are a hindrance to sustainable behavior. Conversely, self-transcendent factors consistently bridged the gap, promoting sustainability. Social factors showed variable impacts based on the ethical and sustainable context they were placed in, suggesting that the social environment’s orientation significantly influences sustainable behavior. (4) This study concludes that the TSS framework offers a promising approach to advancing education for sustainable development (ESD) and contributes insights into how to promote the required paradigm shift towards holistic and interconnected perspectives. Full article

Amid rising energy demands in rural areas, thorough resource assessments for initiatives such as wind power are crucial. This study involves a land resource assessment for wind power generation on the rustic Sibuyan Island in the Philippines, which is currently experiencing an electricity shortage. A comprehensive overview of the island’s suitability for wind energy projects is performed via evaluation and analysis using geospatial data and multi-criteria decision making (MCDM). The research results indicate that 50.44% (220.68 km²) of the island’s land area is categorized as ‘poorly suitable’ since it considers protected areas where developments are not allowed. Only 0.08% (0.35 km²) of the island can be classified as ‘marginally suitable’, while 9.15% (40.73 km²), 36.64% (176.39 km²), and 0.69% (3.05 km²) are labeled as ‘moderately suitable’, ‘suitable’, and ‘highly suitable’, respectively. This confirms the potential for wind energy exploration on the island. Delineating the suitability levels provides a foundational framework for stakeholders that enables them to identify optimal sites for wind power, sustain the island’s resources, and contribute to the renewable energy landscape of this rural location. Overall, this study, underpinned by data analysis, offers invaluable insights for decision making in wind power development, with the presented framework adaptable to other areas of interest. Full article

Undifferentiated carcinoma with osteoclast-like giant cells (UCOGC) of the pancreas represents a rare subtype of pancreatic ductal adenocarcinoma (PDAC). Despite a distinct morphology and specific clinical behavior, UCOGCs exhibit unexpected similarities in regard to DNA mutational profiles with conventional PDAC. Treating pancreatic ductal adenocarcinoma is particularly challenging, with limited prospects for cure. As with many other malignant neoplasms, the exploration of microRNAs (miRNAs, miRs) in regulating the biological characteristics of pancreatic cancer is undergoing extensive investigation to enhance tumor diagnostics and unveil the therapeutic possibilities. Herein, we evaluated the expression of miR-21, -96, -148a, -155, -196a, -210, and -217 in UCOGCs and poorly differentiated (grade 3, G3) PDACs. The expression of miR-21, miR-155, and miR-210 in both UCOGCs and G3 PDACs was significantly upregulated compared to the levels in normal tissue, while the levels of miR-148a and miR-217 were downregulated. We did not find any significant differences between cancerous and normal tissues for the expression of miR-96 and miR-196a in G3 PDACs, whereas miR-196a was slightly, but significantly, downregulated in UCOGCs. On the other hand, we have not observed significant differences in the expression of the majority of miRNAs between UCOGC and G3 PDAC, with the exception of miR-155. UCOGC samples demonstrated lower mean levels of miR-155 in comparison with those in G3 PDACs. Full article

In the context of an evolving socio-economic landscape and rising living standards, the online market for fresh products, encompassing fruits, vegetables, meats, dairy, and eggs, has seen substantial growth, necessitating sophisticated logistics for e-commerce home delivery. This study tackles the distinct challenges of fresh product delivery, which demand rigorous adherence to climate conditions and product mix during transport, significantly influencing the operational strategies and scheduling of delivery platforms. To address these challenges, a comprehensive mathematical model was developed to optimize fresh food home delivery scheduling, focusing on reducing spoilage rates and accommodating the dynamic impact of environmental temperature changes. The model posits assumptions of a consistent and ample supply of fresh goods, standard initial quality loss, and efficient porter assignment for multi-category order combinations. It introduces three objective functions, targeting the minimization of fresh food loss, maximization of customer satisfaction, and reduction of distributor costs. The efficacy of the model and its genetic-algorithm-based solution method was assessed through numerical analysis and case studies, illustrating that the model enhances delivery efficiency and service quality across varying temperature conditions. This substantiates the critical role of environmental temperature management in optimizing fresh food delivery, offering a robust framework for advancing logistical operations in the perishable goods sector and ensuring quality and efficiency in fresh food e-commerce delivery. Full article

Despite the spread of novel-generation cochlear-implant (CI) magnetic systems, access to magnetic resonance imaging (MRI) for CI recipients is still limited due to safety concerns. The aim of this study is to assess and record the experiences of Hires Ultra 3D (Advanced Bionics) recipients who underwent an MRI examination. A multicentric European survey about this topic was conducted focusing on safety issues, and the results were compared with the current literature. We collected a total of 65 MRI scans performed in 9 otologic referral centers for a total of 47 Hires Ultra 3D recipients, including, for the first time, 2 children and 3 teenagers. Preventive measures were represented by scanning time and sedation for children. Head wrapping was used in eight cases, and six of the eight cases received local anesthesia, even if both measures were not needed. Only three patients complained of pain (3/65 examinations, 4.6%) due to the tight head bandage, and one of the three cases required MRI scan interruption. No other adverse events were reported. We believe that these results should encourage MRI execution in accordance with manufacturer recommendations for Ultra 3D recipients. Full article

Rice (Oryza sativa L.) is one of the most important food crops worldwide. However, during direct seeding, rice is extremely vulnerable to flooding stress, which impairs rice’s emergence and seedling growth and results in a significant yield loss. According to our research, chitosan oligosaccharides have the potential to be a chemical seed-soaking agent that greatly increases rice’s resistance to flooding. Chitosan oligosaccharides were able to enhance seed energy supply, osmoregulation, and antioxidant capacity, according to physiological index assessments. Using transcriptome and metabolomic analysis, we discovered that important differential metabolites and genes were involved in the signaling pathway for hormone synthesis and antioxidant capacity. Exogenous chitosan oligosaccharides specifically and significantly inhibit genes linked to auxin, jasmonic acid, and abscisic acid. This suggested that applying chitosan oligosaccharides could stabilize seedling growth and development by controlling associated hormones and reducing flooding stress by enhancing membrane stability and antioxidant capacity. Finally, we verified the effectiveness of exogenous chitosan oligosaccharides imbibed in seeds by field validation, demonstrating that they can enhance rice seedling emergence and growth under flooding stress. Full article

This study aims to assess the contents of different kinds of low-molecular-weight organic acids (LMWOAs) in reclaimed soil filled with fly ash in the Huainan mining area in China using high-performance liquid chromatography (HPLC). Using a mobile phase consisting of 0.1% phosphoric acid and acetonitrile in a volume ratio of 98:2, the detection was performed at a wavelength of 210 nm for 15 min. In addition, a cluster analysis was performed on the detected LMWOAs in the reclaimed soil. The correlations between the LMWOA and nutrient contents in the reclaimed soil were also analyzed. In total, eight and seven LMWOAs were detected in the reclaimed soil and filled fly ash, respectively. In contrast, no LMWOAs were detected in the fresh fly ash from a thermal power plant. The order of total LMWOA contents at different sampling points followed the order of farmland control soil > 1# (Triticum aestivum) > 4# (Phragmites australis) > 5# (Vigna radiata) > 2# (Sorghum bicolor) > 3# (Tamarix ramosissima) > fly ash-filled soil. The farmland control soil and fly ash-filled soil exhibited the highest and lowest LMWOA contents of 648.22 and 85.09 μg·g⁻¹, respectively. The LMWOA contents in the reclaimed soil followed the order of oxalic acid > tartaric acid > malonic acid > lactic acid > acetic acid > citric acid > propionic acid > succinic acid. Indeed, oxalic acids exhibited the highest total amount of 1445.79 μg·g⁻¹ and succinic acids exhibited the lowest total amount of 6.50 μg·g⁻¹. The LMWOA contents in the reclaimed soil decreased with increasing soil depth, showing statistically significant differences between the 0–10 and 10–40 cm soil layers (p < 0.05). According to the obtained clustering results, the detected LMWOAs can be divided into two categories. The first category consisted of oxalic acid, while the second category included the remaining LMWOAs. The soil LMWOA contents of 4# (Phragmites australis) and 5# (Vigna radiata) were significantly different from those at the other sampling points. According to the Pearson correlation analysis results, the occurrence and characteristics of the soil LMWOAs can be controlled by regulating the pH values and available nutrient contents in the soil, thereby improving the eco-environmental conditions of the reclaimed rhizosphere. Full article

Path planning is an indispensable component in guiding unmanned ground vehicles (UGVs) from their initial positions to designated destinations, aiming to determine trajectories that are either optimal or near-optimal. While conventional path-planning techniques have been employed for this purpose, planners utilizing reinforcement learning (RL) exhibit superior adaptability within exceedingly complex and dynamic environments. Nevertheless, existing RL-based path planners encounter several shortcomings, notably, redundant map representations, inadequate feature extraction, and limited adaptiveness across diverse environments. In response to these challenges, this paper proposes an innovative and highly self-adaptive path-planning approach based on Transformer encoder feature extraction coupled with incremental reinforcement learning (IRL). Initially, an autoencoder is utilized to compress redundant map representations, providing the planner with sufficient environmental data while minimizing dimensional complexity. Subsequently, the Transformer encoder, renowned for its capacity to analyze global long-range dependencies, is employed to capture intricate correlations among UGV statuses at continuous intervals. Finally, IRL is harnessed to enhance the path planner’s generalization capabilities, particularly when the trained agent is deployed in environments distinct from its training counterparts. Our empirical findings demonstrate that the proposed method outperforms traditional uniform-sampling-based approaches in terms of execution time, path length, and trajectory smoothness. Furthermore, it exhibits a fivefold increase in adaptivity compared to conventional transfer-learning-based fine-tuning methodologies. Full article

Rice (Oryza sativa), as a staple crop feeding a significant portion of the global population, particularly in Asian countries, faces constant threats from various diseases jeopardizing global food security. A precise understanding of disease resistance mechanisms is crucial for developing resilient rice varieties. Traditional genetic mapping methods, such as QTL mapping, provide valuable insights into the genetic basis of diseases. However, the complex nature of rice diseases demands a holistic approach to gain an accurate knowledge of it. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, enable a comprehensive analysis of biological molecules, uncovering intricate molecular interactions within the rice plant. The integration of various mapping techniques using multi-omics data has revolutionized our understanding of rice disease resistance. By overlaying genetic maps with high-throughput omics datasets, researchers can pinpoint specific genes, proteins, or metabolites associated with disease resistance. This integration enhances the precision of disease-related biomarkers with a better understanding of their functional roles in disease resistance. The improvement of rice breeding for disease resistance through this integration represents a significant stride in agricultural science because a better understanding of the molecular intricacies and interactions underlying disease resistance architecture leads to a more precise and efficient development of resilient and productive rice varieties. In this review, we explore how the integration of mapping and omics data can result in a transformative impact on rice breeding for enhancing disease resistance. Full article

This study explores the deposition of an Fe-MnCrSi/TiC coating on 45 steel surfaces using high-velocity arc spraying technology, examining the microstructure and hot corrosion behavior of the resultant layer. The microstructure of the FeMnCrSi/TiC coating primarily consists of an α-Fe (BCC) solid solution, composed of Fe, Mn, Cr, Si, C, and other elements, with a minor presence of β-Fe (FCC) solid-solution phase and unmelted TiC particles. Following 100 h of cyclic 900 °C hot corrosion, Mn on the coating surface preferentially oxidizes, forming a manganese-rich oxide layer. This process reduces the oxygen partial pressure (O₂) within the coating, prompting the formation of a dense Cr₂O₃ layer on the inner side of the oxide layer. Concurrently, the rapid diffusion of Mn and Cr elements triggers the generation of Mn- and Cr-deficient regions at the metal/oxide layer interface, inducing the transformation of the coated metal primary matrix from an FCC + BCC dual phase to an α-Fe (BCC) single phase. After the reaction, the hot corrosion weight gain of the coating reached 12.43 mg/cm², approximately one-fourteenth of the weight gain of the 45 steel substrates. This weight gain adheres to the parabolic law, suggesting that the FeMnCrSi/TiC coating exhibits excellent corrosion resistance under the given conditions. Full article

Wood possesses several advantageous qualities including innocuity, low cost, aesthetic appeal, and excellent biocompatibility, and its naturally abundant functional groups and diverse structural forms facilitate functionalization modification. As the most sustainable bio-based material, the combination of wood with triboelectric nanogenerators (TENGs) stands poised to significantly advance the cause of green sustainable production while mitigating the escalating challenges of energy consumption. However, the inherent weak polarizability of natural wood limits its development for TENGs. Herein, we present the pioneering development of a flexible transparent wood-based triboelectric nanogenerator (TW-TENG) combining excellent triboelectrical properties, optical properties, and wood aesthetics through sodium chlorite delignification and epoxy resin impregnation. Thanks to the strong electron-donating groups in the epoxy resin, the TW-TENG obtained an open-circuit voltage of up to ~127 V, marking a remarkable 530% enhancement compared to the original wood. Furthermore, durability and stability were substantiated through 10,000 working cycles. In addition, the introduction of epoxy resin and lignin removal endowed the TW-TENG with excellent optical characteristics, with optical transmittance of up to 88.8%, while preserving the unique texture and aesthetics of the wood completely. Finally, we show the application prospects of TW-TENGs in the fields of self-power supply, motion sensing, and smart home through the demonstration of a TW-TENG in the charging and discharging of capacitors and the output of electrical signals in different scenarios. Full article

The endo-β-1,4-xylanase glycosyl hydrolase (GH11) decomposes the backbone of xylan into xylooligosaccharides or xylose. These enzymes are important for industrial applications in the production of biofuel, feed, food, and value-added materials. β-D-xylopyranose (XYP, also known as β-D-xylose) is the fundamental unit of the substrate xylan, and understanding its recognition is fundamental for the initial steps of GH11’s molecular mechanism. However, little is known about the recognition of a single XYP molecule by GH11. In this study, the crystal structures of GH11 from Thermoanaerobacterium saccharolyticum (TsaGH11) complexed with an XYP molecule were determined at a resolution of 1.7–1.9 Å. The XYP molecule binds to subsite −2 of the substrate-binding cleft. The XYP molecule is mainly stabilized by a π–π interaction with the conserved Trp36 residue. The O2 and O3 atoms of XYP are stabilized by hydrogen bond interactions with the hydroxyl groups of Tyr96 and Tyr192. The conformation of the thumb domain of TsaGH11 does not play a critical role in XYP binding, and XYP binding induces a shift in the thumb domain of TsaGH11 toward the XYP molecule. A structural comparison of TsaGH11 with other GH11 xylanases revealed that the XYP molecule forms π–π stacking with the center between the phenyl and indoline ring of Trp36, whereas the XYP molecule unit from xylobiose or xylotetraose forms π–π stacking with the indoline of Trp36, which indicates that the binding modes of the substrate and XYP differ. These structural results provide a greater understanding of the recognition of XYP by the GH11 family. Full article

Soluble starch synthases (SSs) play important roles in the synthesis of cassava starch. However, the expression characteristics of the cassava SSs genes have not been elucidated. In this study, the MeSSIII-1 gene and its promoter, from SC8 cassava cultivars, were respectively isolated by PCR amplification. MeSSIII-1 protein was localized to the chloroplasts. qRT-PCR analysis revealed that the MeSSIII-1 gene was expressed in almost all tissues tested, and the expression in mature leaves was 18.9 times more than that in tuber roots. MeSSIII-1 expression was induced by methyljasmonate (MeJA), abscisic acid (ABA), and ethylene (ET) hormones in cassava. MeSSIII-1 expression patterns were further confirmed in proMeSSIII-1 transgenic cassava. The promoter deletion analysis showed that the −264 bp to −1 bp MeSSIII-1 promoter has basal activity. The range from −1228 bp to −987 bp and −488 bp to −264 bp significantly enhance promoter activity. The regions from −987 bp to −747 bp and −747 bp to −488 bp have repressive activity. These findings will provide an important reference for research on the potential function and transcriptional regulation mechanisms of the MeSSIII-1 gene and for further in-depth exploration of the regulatory network of its internal functional elements. Full article

In this study, poly (ethylene terephthalate) (PETG) was combined with Antimony-doped Tin Oxide (ATO) to create five different composites (2.0–10.0 wt.% ATO). The PETG/ATO filaments were extruded and supplied to a material extrusion (MEX) 3D printer to fabricate the specimens following international standards. Various tests were conducted on thermal, rheological, mechanical, and morphological properties. The mechanical performance of the prepared nanocomposites was evaluated using flexural, tensile, microhardness, and Charpy impact tests. The dielectric and electrical properties of the prepared composites were evaluated over a broad frequency range. The dimensional accuracy and porosity of the 3D printed structure were assessed using micro-computed tomography. Other investigations include scanning electron microscopy and energy-dispersive X-ray spectroscopy, which were performed to investigate the structures and morphologies of the samples. The PETG/6.0 wt.% ATO composite presented the highest mechanical performance (21% increase over the pure polymer in tensile strength). The results show the potential of such nanocomposites when enhanced mechanical performance is required in MEX 3D printing applications, in which PETG is the most commonly used polymer. Full article

Cracks provide the earliest and most immediate visual response to structural deterioration of asphalt pavements. Most of the current methods for crack detection are based on visible light sensors and convolutional neural networks. However, such an approach obviously limits the detection to daytime and good lighting conditions. Therefore, this paper proposes a crack detection technique cross-modal feature alignment of YOLOV5 based on visible and infrared images. The infrared spectrum characteristics of silicate concrete can be an important supplement. The adaptive illumination-aware weight generation module is introduced to compute illumination probability to guide the training of the fusion network. In order to alleviate the problem of weak alignment of the multi-scale feature map, the FA-BIFPN feature pyramid module is proposed. The parallel structure of a dual backbone network takes 40% less time to train than a single backbone network. As determined through validation on FLIR, LLVIP, and VEDAI bimodal datasets, the fused images have more stable performance compared to the visible images. In addition, the detector proposed in this paper surpasses the current advanced YOLOV5 unimodal detector and CFT cross-modal fusion module. In the publicly available bimodal road crack dataset, our method is able to detect cracks of 5 pixels with 98.3% accuracy under weak illumination. Full article

Background: We propose a three-dimensional path-planning method to generate optimized surgical trajectories for steering flexible needles along curved paths while avoiding critical tracts in the context of surgical glioma resection. Methods: Our approach is based on an application of the rapidly exploring random tree algorithm for multi-trajectory generation and optimization, with a cost function that evaluates different entry points and uses the information of MRI images as segmented binary maps to compute a safety trajectory. As a novelty, an avoidance module of the critical neuronal tracts defined by the neurosurgeon is included in the optimization process. The proposed strategy was simulated in real-case 3D environments to reach a glioma and bypass the tracts of the forceps minor from the corpus callosum. Results: A formalism is presented that allows for the evaluation of different entry points and trajectories and the avoidance of selected critical tracts for the definition of new neurosurgical approaches. This methodology can be used for different clinical cases, allowing the constraints to be extended to the trajectory generator. We present a clinical case of glioma at the base of the skull and access it from the upper area while avoiding the minor forceps tracts. Conclusions: This path-planning method offers alternative curved paths with which to reach targets using flexible tools. The method potentially leads to safer paths, as it permits the definition of groups of critical tracts to be avoided and the use of segmented binary maps from the MRI images to generate new surgical approaches. Full article

In order to achieve fast and accurate detection of Gannan navel orange fruits with different ripeness levels in a natural environment under all-weather scenarios and then to realise automated harvesting of Gannan navel oranges, this paper proposes a YOLOv5-NMM (YOLOv5 with Navel orange Measure Model) object detection model based on the improvement in the original YOLOv5 model. Based on the changes in the phenotypic characteristics of navel oranges and the Chinese national standard GB/T 21488-2008, the maturity of Gannan navel oranges is tested. And it addresses and improves the problems of occlusion, dense distribution, small target size, rainy days, and light changes in the detection of navel orange fruits. Firstly, a new detection head of 160 × 160 feature maps is constructed in the detection layer to improve the multi-scale target detection layer of YOLOv5 and to increase the detection accuracy of the different maturity levels of Gannan navel oranges of small sizes. Secondly, a convolutional block attention module is incorporated in its backbone layer to capture the correlations between features in different dimensions to improve the perceptual ability of the model. Then, the weighted bidirectional feature pyramid network structure is integrated into the Neck layer to improve the fusion efficiency of the network on the feature maps and reduce the amount of computation. Lastly, in order to reduce the loss of the target of the Gannan Navel Orange due to occlusion and overlapping, the detection frame is used to remove redundancy using the Soft-NMS algorithm to remove redundant candidate frames. The results show that the accuracy rate, recall rate, and average accuracy of the improved YOLOv5-NMM model are 93.2%, 89.6%, and 94.2%, respectively, and the number of parameters is only 7.2 M. Compared with the mainstream network models, such as Faster R-CNN, YOLOv3, the original model of YOLOv5, and YOLOv7-tiny, it is superior in terms of the accuracy rate, recall rate, and average accuracy mean, and also performs well in terms of the detection rate and memory occupation. This study shows that the YOLOv5-NMM model can effectively identify and detect the ripeness of Gannan navel oranges in natural environments, which provides an effective exploration of the automated harvesting of Gannan navel orange fruits. Full article