bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal Deep Neural Network Modified by Advanced Seasons Optimizer for Classification of Olympic Sports Images
Authors: Wang Yanbu , Wang Chao , Wang Yongkang , Liu Linqing
Published: July 2024

Sports image classification has gained increasing significance in various domains, including athlete training, event management, and broadcasting. Nonetheless, accurately classifying these images remains a formidable challenge due to factors such as variations in lighting conditions, pose, and attire. This paper proposes an advanced deep learning approach to address this issue. The proposed method uses a modified Inception-V4 (IV4) architecture, which has exhibited remarkable success in image classification tasks. To further enhance the performance of the IV4 model, an advanced version of the seasons optimizer (ASO), a potent optimization algorithm, has been introduced, which adjusts the learning rate during training. This modified optimizer enables the IV4 model to converge more rapidly and achieve higher accuracy. An evaluation of the proposed method has been conducted using a comprehensive dataset comprising Olympic sports images. The experimental results demonstrate significant enhancements over existing approaches, attaining superior performance across multiple evaluation metrics. These findings underscore the potential of combining cutting-edge deep neural networks with advanced optimization techniques for the precise and efficient classification of sports images.
Digital Twin Modeling for Hydropower System Based on Radio Frequency Identification Data Collection
Authors: Cai Zhi , Wang Yanfeng , Zhang Dawei , Wen Lili , Liu Haiyang , Xiong Zhijie , Wajid Khan , Feng Renhai
Published: July 2024

The safe and steady operation of hydropower generation systems is crucial for electricity output in the grid. However, hydropower stations have complicated interior structures, making defect detection difficult without disassembly inspections. The application of digital modeling to hydropower stations will effectively promote the intelligent transformation of hydropower stations as well as reduce the maintenance costs of the system. This study provides a model of the power generating and transmission system for hydropower plants, with an emphasis on primary equipment and measured data. The model utilizes PSCAD to digitalize state response in hydropower plants with various short-circuit faults. The fault information is identified and learned using the Adaptive Time–Frequency Memory (AD-TFM) deep learning model. It is demonstrated that our proposed method can effectively obtain the fault information through radio frequency identification (RFID). The accuracy of the traditional method is 0.90, while the results for AD-TFM show a fault classification accuracy of 0.92, which is more than enough to identify multiple fault types compared to the existing methods.
Multi-Agent Deep Reinforcement Learning-Based Inference Task Scheduling and Offloading for Maximum Inference Accuracy under Time and Energy Constraints
Authors: Ben Sada Abdelkarim , Khelloufi Amar , Naouri Abdenacer , Ning Huansheng , Aung Nyothiri , Dhelim Sahraoui
Published: July 2024

The journey towards realizing real-time AI-driven IoT applications is facing a significant hurdle caused by the limited resources of IoT devices. Particularly for battery-powered edge devices, the decision between performing task inference locally or by offloading to edge servers, all while ensuring timely results and conserving energy, is a critical issue. This problem is further complicated when an edge device houses multiple local inference models. The challenge of effectively allocating inference models to tasks between local models and edge server models under strict time and energy constraints while maximizing overall accuracy is recognized as a strongly NP-hard problem and has not been addressed in the literature. Therefore, in this work we propose MASITO, a novel multi-agent deep reinforcement learning framework designed to address this intricate problem. By dividing the problem into two sub-problems namely task scheduling and edge server selection we propose a cooperative multi-agent system for addressing each sub-problem. MASITO’s design allows for faster training and more robust schedules using cooperative behavior where agents compensate for each other’s sub-optimal actions. Moreover, MASITO dynamically adapts to different network configurations which allows for high-mobility edge computing applications. Experiments on the ImageNet-mini dataset demonstrate the framework’s efficacy, outperforming genetic algorithms (GAs), simulated annealing (SA), and particle swarm optimization (PSO) in scheduling times by providing lower times ranging from 60% up to 90% while maintaining comparable average accuracy in worst-case scenarios and superior accuracy in best-case scenarios.
Thermal Analysis of Power Transformer Using 2D and 3D Finite Element Method
Authors: Seddik Mohamed S. , Shazly Jehan , Eteiba Magdy B.
Published: July 2024

An accurate simulation and computational analysis of temperature distribution in large power transformers used in power plants is crucial during both the design and operational phases. This study introduces a thermal modeling analysis encompassing two- and three-dimensional (2D and 3D) approaches for power transformers. The mathematical model for heat diffusion follows the Finite Element Method (FEM) approach. Validation of the computed results involves comparing them against measurements from Hyundai’s test report for both 2D and 3D models, aiming to identify the most effective solution. Additionally, the thermal dynamics of power transformers under diverse operational conditions, specifically oil-immersed ones, are examined. The efficacy of this model is confirmed through testing on a step-up transformer at Kureimat station in Egypt, with specifications including three-phase, 50 Hz, 16.5/240 KV, nine taps, and cooling type (ONAN/ONAF1/ONAF2).
Comparative Transcriptome Analysis of Different Mulberry Varieties to Reveal Candidate Genes and Small Secreted Peptides Involved in the Sclerotiniose Response
Authors: Liu Li , Guo Zixuan , Kang Xiaoru , Li Shan , Huang Shuai , Zheng Longyan , Fu Rumeng , Yidilisi Keermula , Chao Nan
Published: July 2024

Mulberry sclerotiniose is a devastating fungal disease of mulberry fruit and has been a limitation for the utility of mulberry fruits and the diversified development of sericulture. In the present study, we presented a workflow for screening candidate sclerotiniose-resistance genes and small secreted peptides (SSPs) based on a genome-wide annotation of SSPs and comparative transcriptome analysis of different mulberry varieties. A total of 1088 SSPs with expression evidence were identified and annotated in mulberry. A comprehensive analysis of the sclerotiniose-related RNA sequencing datasets showed that photosynthesis, plant hormone signaling, and metabolic pathways were the main pathways involved in the response to sclerotiniose. Fifty-two candidate sclerotiniose-response genes (SRGs), including 15 SSPs, were identified based on comparative transcriptome analysis. These SRGs are mainly involved in the hormone signaling pathway and cell wall biogenesis. Transient overexpression in tobacco and the knock-down of five SRGs affected the resistance against Ciboria shiraiana. MaMYB29, MaMES17, and MaSSP15 were primarily determined as negative regulators of plant resistance to C. shiraiana infection. Our results provide a foundation for controlling sclerotiniose in mulberry using genetic engineering and biological approaches such as spraying antifungal peptides.
Biochar Application Improved Sludge-Amended Landscape Soil Fertility Index but with No Added Benefit in Plant Growth
Authors: Chu Shuangshuang , Xiao Mengrui , Peng Weixin , Long Fengling , Wu Daoming , Hu Dongnan , Zeng Shucai
Published: July 2024

Co-application of sewage sludge (SS) with biochar in landscape/forestry soil is a common strategy for enhancing soil fertility and reducing the bioavailability of potential toxic elements (PTEs) derived from SS, such as Cd, Pb, Cu, Zn, and Ni. However, due to variability of biochar quality and uncertainties in responses of different plant species, whether the co-application benefits the landscape/forestry plant system remains elusive. Here, we tested the effectiveness of three types of biochar (SS-derived biochar (SB), rice straw-derived biochar (RB), and litter-derived biochar (LB)), which were added to soil amended with SS at 50% (w/w) at rates of 1.5%, 3%, and 4.5% as growth media for the landscape plant Aglaonema modestum (A. modestum). We analyzed the substrate’s physicochemical properties and assessed the alleviation of phytotoxicity by biochar application. A significant increase in the fertility index of substrate was observed in all the treatments with biochar addition. The addition of biochar reduced the potential mobility of PTEs while increasing their residual fraction in media. Nonetheless, it has been found that the addition of biochar has ineffective or even negative effects on A. modestum growth (height, biomass, root length) and nutrient absorption. Importantly, the reduction in root biomass and the increased activity of root antioxidant enzymes (SOD, POD, CAT, and MDA) indicate contamination stress of biochar on the roots of A. modestum. Toxic elements of concern—namely Cu, Cd, and Pb—were not significantly higher in tissues of A. modestum saplings planted in biochar-SS-amended soil. However, elevated levels of other elements that may pose toxicity concerns, such as Ni and Zn, increased in tissues at high biochar dosages. Based on the Entropy–Weight TOPSIS method, it was further confirmed that compared to the treatment without biochar, all treatments except for 3.0% LB application resulted in poorer A. modestum comprehensive growth. Our results emphasize the need for detailed research on the response of specific plants to biochar in specific environments, including plant adaptability and the unexplored toxicity of biochar, to understand the large variations and mechanisms behind these ineffective or negative effects before the large-scale co-utilization of SS and biochar in landscape/forestry soils.
Forest Canopy Height Retrieval Model Based on a Dual Attention Mechanism Deep Network
Authors: Zhao Zongze , Jiang Baogui , Wang Hongtao , Wang Cheng
Published: July 2024

Accurate estimation of forest canopy height is crucial for biomass inversion, carbon storage assessment, and forestry management. However, deep learning methods are underutilized compared to machine learning. This paper introduces the convolutional neural network–bidirectional long short-term memory (CNN-BiLSTM) model and proposes a Convolutional Neural network–spatial channel attention–bidirectional long short-term memory (CNN-SCA-BiLSTM) model, incorporating dual attention mechanisms for richer feature extraction. A dataset comprising vegetation indices and canopy height data from forest regions in Luoyang, specifically within the 8–20 m range, is used for a comparative analysis of multiple models, with accuracy evaluated based on the mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). The results demonstrate that (1) the CNN-BiLSTM model exhibits strong potential (MAE = 1.6554 m, RMSE = 2.2393 m, R2 = 0.9115) and (2) the CNN-SCA-BiLSTM model, while slightly less efficient (<1%), demonstrates improved performance. It reduces the MAE by 0.3047 m, the RMSE by 0.6420 m, and increases the R2 value by 0.0495. Furthermore, the model is utilized to generate a canopy height map (MAE = 5.2332 m, RMSE = 7.0426 m) for Henan in the Yellow River Basin for the year 2022. The canopy height is primarily distributed around 5–20 m, approaching the accuracy levels of global maps (MAE = 4.0 m, RMSE = 6.0 m).
Pinus banksiana Lamb. Regeneration Patterns in a Lacustrine Dune System
Authors: Danielson Jonathan C. , Warrix Adam R. , Lehman Madison E. , Lehman Andrew C. , Marshall Jordan M.
Published: July 2024

Successional patterns in lacustrine sand dunes along Lake Superior begin with grass-dominated plant communities leading to the establishment of Pinus banksiana Lamb. as initial forests. Using maximum entropy models, we predicted P. banksiana seedling and sapling patterns within the Grand Sable Dunes, Pictured Rocks National Lakeshore, USA, based on slope, aspect, forest basal area, and vegetation types. Across the different vegetation types, there were variable probabilities of seedling and sapling occurrence. For both seedlings and saplings, the higher likelihoods of occurrence were observed in coastal pine barrens vegetation types. P. banksiana regeneration is occurring in the Grand Sable Dunes in the absence of fire, with seedlings establishing and saplings being recruited in a variety of vegetation types. With the greatest probabilities in barrens, there is likely a relationship with seed source and canopy density. Understanding regeneration patterns in dune ecosystems is necessary to predict the future forest arrangement and colonization of P. banksiana into the dunes. These results contribute insights into the dynamics of plant communities in lacustrine dune systems, specifically the establishment of P. banksiana seedlings in various vegetation types. Continued forest establishment and increasing P. banksiana density will influence endangered species and non-native species management strategies for Pictured Rocks National Lakeshore.
Stress Wave Hybrid Imaging for Detecting Wood Internal Defects under Sparse Signals
Authors: Du Xiaochen , Zheng Yilei , Feng Hailin
Published: July 2024

Stress wave technology is very suitable for detecting internal defects of standing trees, logs, and wood and has gradually become the mainstream technology in this research field. Usually, 12 sensors are positioned equidistantly around the cross-section of tree trunks in order to obtain enough stress wave signals. However, the arrangement of sensors is time-consuming and laborious, and maintaining the accuracy of stress wave imaging under sparse signals is a challenging problem. In this paper, a novel stress wave hybrid imaging method based on compressive sensing and elliptic interpolation is proposed. The spatial structure of the defective area is reconstructed by using the advantages of compressive sensing in sparse signal representation and solution of stress waves, and the healthy area is reconstructed by using the elliptic space interpolation method. Then, feature points are selected and mixed for imaging. The comparative experimental results show that the overall imaging accuracy of the proposed method reaches 89.7%, and the high-quality imaging effect can be guaranteed when the number of sensors is reduced to 10, 8, or even 6.
Responses of Physiological Traits and Soil Properties in Pinus thunbergia and Euonymus japonicus Saplings under Drought and Cadmium (Cd) Stress
Authors: Li Shan , Wang Jing , Lu Sen , Li Huan , Guo Junkang
Published: July 2024

Pinus thunbergii and Euonymus japonicus are two species commonly found in arid and semi-arid areas; however, their responses in terms of physiological traits and soil properties under drought and cadmium (Cd) stress are not clear. In this study, we carried out single and combined stress treatments consisting of drought and Cd on saplings of P. thunbergii and E. japonicus and investigated the responses in terms of the physiological traits and soil properties of both species. For both species, under single Cd stress, Cd was observed in both the xylem and phloem, while the root Cd2+ flow rate fluctuated at different levels of Cd stress. Under both single and combined stress, as the stress level increased, the abscisic acid (ABA) content of the leaves and roots increased significantly, while the indole-3-acetic acid (IAA) content of the leaves and roots decreased significantly. Moreover, the non-structural carbohydrate (NSC) content of the leaves, stems, and roots, as well as the leaf chlorophyll content, decreased significantly. Under drought stress, the xylem water potential and hydraulic conductivity significantly decreased, which was exacerbated by Cd stress; this led to a more significant decrease in water potential and hydraulic conductivity under the combined stresses. Meanwhile, no significant changes in the conduit lumen diameter and double-wall thickness were observed, except for the double cell wall thickness of the P. thunbergii tracheid, which increased. In addition, both the single stresses and the combined stress of drought and Cd induced significant changes in the soil properties of the two species, i.e., the ammonium nitrogen, nitrate nitrogen, and effective phosphorus of the soil increased significantly, and the increase in content was more significant under combined stress. The diversity of the soil microbial community of P. thunbergii saplings significantly increased, while no change was found in its microbial community abundance under the single stresses and combined stress; however, the diversity and abundance of the soil microbial community in E. japonicus saplings showed the opposite pattern, which indicates that the effect of Cd on soil microorganisms is more significant than the effect of drought. The activity of sucrase and catalase in P. thunbergii soil fluctuated under the single stress and combined stress when compared, and the activity of sucrase in the soil of the E. japonicus species decreased. However, its catalase activity increased significantly under the single drought and Cd stress and combined stress when compared. We found that the combined stresses exacerbated the effects of the single stress in both species. Our study provides more detailed information on the responses in terms of the physiological traits and soil properties of the two species under single and combined stress consisting of drought and Cd.
Estimation of Picea Schrenkiana Canopy Density at Sub-Compartment Scale by Integration of Optical and Radar Satellite Images
Authors: Wang Yibo , Li Xusheng , Yang Xiankun , Qi Wenchao , Zhang Donghui , Wang Jinnian
Published: July 2024

This study proposes a novel approach to estimate canopy density in Picea Schrenkiana var. Tianschanica forest sub-compartments by integrating optical and radar satellite data. This effort is aimed at enhancing methodologies for forest resource surveys and monitoring, particularly vital for the sustainable development of semi-arid mountainous areas with fragile ecological environments. The study area is the West Tianshan Mountain Nature Reserve in Xinjiang, which is characterized by its unique dominant tree species, Picea Schrenkiana. A total of 411 characteristic factors were extracted from Gaofen-2 (GF-2) sub-meter optical satellite imagery, Gaofen-3 (GF-3) multi-polarization synthetic aperture radar satellite imagery, and digital elevation model (DEM) data. Consequently, 17 characteristic parameters were selected based on their correlation with canopy density data to construct an estimation model. Three distinct models were developed, including a multiple stepwise regression model (a linear approach), a Back Propagation (BP) neural network model (a neural network-based method), and a Cubist model (a decision tree-based technique). The results indicate that combining optical and radar image characteristics significantly enhances accuracy, with an Average Absolute Percentage Precision (AAPP) value improvement in estimation accuracy from 76.50% (with optical image) and 78.50% (with radar image) to 78.66% (with both). Of the three models, the BP neural network model achieved the highest overall accuracy (79.19%). At the sub-component scale, the BP neural network model demonstrated superior accuracy in low canopy density estimation (75.37%), whereas the Cubist model, leveraging radar image characteristics, excelled in medium density estimations (87.46%). Notably, the integrated Cubist model combining optical and radar data achieved the highest accuracy for high canopy density estimation (89.17%). This study highlights the effectiveness of integrating optical and radar data for precise canopy density assessment, contributing significantly to ecological resource monitoring methodologies and environmental assessments.
Carbon Fibers Based on Cellulose–Lignin Hybrid Filaments: Role of Dehydration Catalyst, Temperature, and Tension during Continuous Stabilization and Carbonization
Authors: Unterweger Christoph , Schlapp-Hackl Inge , Fürst Christian , Robertson Daria , Cho MiJung , Hummel Michael
Published: July 2024

Lignocellulose has served as precursor material for carbon fibers (CFs) before fossil-based polymers were discovered as superior feedstock. To date, CFs made from polyacrylonitrile have dominated the market. In search of low-cost carbon fibers for applications with medium strength requirements, cellulose and lignin, either as individual macromolecule or in combination, have re-gained interest as renewable raw material. In this study, cellulose with 30 wt% lignin was dry-jet wet-spun into a precursor filament for bio-based carbon fibers. The stabilization and carbonization conditions were first tested offline, using stationary ovens. Diammonium sulfate (DAS) and diammonium hydrogen phosphate were tested as catalysts to enhance the stabilization process. Stabilization is critical as the filaments’ strength properties drop in this phase before they rise again at higher temperatures. DAS was identified as a better option and used for subsequent trials on a continuous carbonization line. Carbon fibers with ca. 700 MPa tensile strength and 60–70 GPa tensile modulus were obtained at 1500 °C. Upon further carbonization at 1950 °C, moduli of >100 GPa were achieved.
Exploring Summer Variations of Driving Factors Affecting Land Use Zoning Based on the Surface Urban Heat Island in Chiang Mai, Thailand
Authors: Rinchumphu Damrongsak , Srivanit Manat , Iamchuen Niti , Aryupong Chuchoke
Published: July 2024

Numerous studies have examined land surface temperature (LST) changes in Thailand using remote sensing, but there has been little research on LST variations within urban land use zones. This study addressed this gap by analyzing summer LST changes in land use zoning (LUZ) blocks in the 2012 Chiang Mai Comprehensive Plan and their relationship with surface biophysical parameters (NDVI, NDBI, MNDWI). The approach integrated detailed zoning data with remote sensing for granular LST analysis. Correlation and stepwise regression analyses (SRA) revealed that NDBI significantly impacted LST in most block types, while NDVI and MNDWI also influenced LST, particularly in 2023. The findings demonstrated the complexity of LST dynamics across various LUZs in Chiang Mai, with SRA results explaining 45.7% to 53.2% of summer LST variations over three years. To enhance the urban environment, adaptive planning strategies for different block categories were developed and will be considered in the upcoming revision of the Chiang Mai Comprehensive Plan. This research offers a new method to monitor the urban heat island phenomenon at the block level, providing valuable insights for adaptive urban planning.
HBIM for Conservation of Built Heritage
Authors: Alshawabkeh Yahya , Baik Ahmad , Miky Yehia
Published: July 2024

Building information modeling (BIM) has recently become more popular in historical buildings as a method to rebuild their geometry and collect relevant information. Heritage BIM (HBIM), which combines high-level data about surface conditions, is a valuable tool for conservation decision-making. However, implementing BIM in heritage has its challenges because BIM libraries are designed for new constructions and are incapable of accommodating the morphological irregularities found in historical structures. This article discusses an architecture survey workflow that uses TLS, imagery, and deep learning algorithms to optimize HBIM for the conservation of the Nabatean built heritage. In addition to creating new resourceful Nabatean libraries with high details, the proposed approach enhanced HBIM by including two data outputs. The first dataset contained the TLS 3D dense mesh model, which was enhanced with high-quality textures extracted from independent imagery captured at the optimal time and location for accurate depictions of surface features. These images were also used to create true orthophotos using accurate and reliable 2.5D DSM derived from TLS, which eliminated all image distortion. The true orthophoto was then used in HBIM texturing to create a realistic decay map and combined with a deep learning algorithm to automatically detect and draw the outline of surface features and cracks in the BIM model, along with their statistical parameters. The use of deep learning on a structured 2D true orthophoto produced segmentation results in the metric units required for damage quantifications and helped overcome the limitations of using deep learning for 2D non-metric imagery, which typically uses pixels to measure crack widths and areas. The results show that the scanner and imagery integration allows for the efficient collection of data for informative HBIM models and provide stakeholders with an efficient tool for investigating and analyzing buildings to ensure proper conservation.
CCNN-SVM: Automated Model for Emotion Recognition Based on Custom Convolutional Neural Networks with SVM
Authors: Rashad Metwally , Alebiary Doaa M. , Aldawsari Mohammed , El-Sawy Ahmed A. , AbuEl-Atta Ahmed H.
Published: July 2024

The expressions on human faces reveal the emotions we are experiencing internally. Emotion recognition based on facial expression is one of the subfields of social signal processing. It has several applications in different areas, specifically in the interaction between humans and computers. This study presents a simple CCNN-SVM automated model as a viable approach for FER. The model combines a Convolutional Neural Network for feature extraction, certain image preprocessing techniques, and Support Vector Machine (SVM) for classification. Firstly, the input image is preprocessed using face detection, histogram equalization, gamma correction, and resizing techniques. Secondly, the images go through custom single Deep Convolutional Neural Networks (CCNN) to extract deep features. Finally, SVM uses the generated features to perform the classification. The suggested model was trained and tested on four datasets, CK+, JAFFE, KDEF, and FER. These datasets consist of seven primary emotional categories, which encompass anger, disgust, fear, happiness, sadness, surprise, and neutrality for CK+, and include contempt for JAFFE. The model put forward demonstrates commendable performance in comparison to existing facial expression recognition techniques. It achieves an impressive accuracy of 99.3% on the CK+ dataset, 98.4% on the JAFFE dataset, 87.18% on the KDEF dataset, and 88.7% on the FER.
The Biological Roles of microRNAs in Drosophila Development
Authors: Jang Daegyu , Kim Chae Jeong , Shin Bo Hyun , Lim Do-Hwan
Published: July 2024

Drosophila is a well-established insect model system for studying various physiological phenomena and developmental processes, with a focus on gene regulation. Drosophila development is controlled by programmed regulatory mechanisms specific to individual tissues. When key developmental processes are shared among various insects, the associated regulatory networks are believed to be conserved across insects. Thus, studies of developmental regulation in Drosophila have substantially contributed to our understanding of insect development. Over the past two decades, studies on microRNAs (miRNAs) in Drosophila have revealed their crucial regulatory roles in various developmental processes. This review focuses on the biological roles of miRNAs in specific tissues and processes associated with Drosophila development. Additionally, as a future direction, we discuss sequencing technologies that can analyze the interactions between miRNAs and their target genes, with the aim of enhancing miRNA studies in Drosophila development.
Alcoholic Etiology, Severity of Liver Disease, and Post-Transplant Adherence Are Correlated with Worse Stanford Integrated Psychosocial Assessment for Transplantation (SIPAT) in Liver Transplant Candidates
Authors: Zanatta Elisa , Patron Elisabetta , Messerotti Benvenuti Simone , Pelizzaro Filippo , Russo Francesco Paolo , Gambato Martina , Germani Giacomo , Ferrarese Alberto , Zanetto Alberto , Battermann Federica , Buccheri Francesca , Cavalli Chiara , Schiavo Rossana , Ghisi Marta , Pasquato Sara , Feltracco Paolo , Cillo Umberto , Burra Patrizia , Senzolo Marco
Published: July 2024

Introduction: Psychosocial pre-transplant evaluation in patients undergoing liver transplantation (LT) could help identify those patients at higher risk of pharmacological non-adherence, organ rejection, and mortality. The Stanford Integrated Psychosocial Assessment for Transplantation (SIPAT) is a validated tool for assessing LT candidates’ psychosocial well-being. Data on the ability of the SIPAT evaluation to predict post-transplant outcomes are sparse. Material and Methods: clinical and psychosocial data from a sample of 134 candidates for LT were analyzed. Moreover, the association between pre-transplant psychosocial evaluation and post-transplant clinical outcomes, including organ rejection, mortality, and immunosuppressant drug adherence, was calculated. Results: At the pre-transplant evaluation, patients who showed high SIPAT scores (77, 57%) also had more liver disease assessed by model for end-stage liver disease (MELD; F = 5.04; p < 0.05), alcoholic etiology (F = 35.80; p < 0.001), encephalopathy (F = 5.02; p < 0.05), and portal hypertension (F = 7.45; p < 0.01). Of the 51 transplant patients, those who had a high pre-transplant SIPAT score showed lower post-transplant immunosuppressive adherence, linked to more frequent immunological events. Conclusions: Patients with an alcoholic etiology of liver disease and more severe liver dysfunction are likelier to not adhere to medical prescriptions following transplantation. Current data suggests that this specific group of patients could benefit from early psychological pre-habilitation before undergoing liver transplantation.
Incidence of Cervical Kyphosis and Factors Associated with Improvement in Postoperative Cervical Spinal Alignment in Idiopathic Scoliosis with Major Thoracolumbar/Lumbar and Thoracic Curves
Authors: Mizukami Kai , Ohba Tetsuro , Tanaka Nobuki , Oda Kotaro , Katsu Marina , Takei Hayato , Go Goto , Haro Hirotaka
Published: July 2024

Background: This study aimed to compare the incidence and severity of cervical kyphosis before and after surgery between patients with adolescent idiopathic scoliosis (AIS) with major thoracolumbar/lumbar curves (Lenke type 5C group) and those with major thoracic curves (Lenke type 1A group). Further, factors associated with cervical spinal alignment changes after surgery in the two groups were examined. Methods: This study included consecutive patients with AIS who underwent posterior spinal fusion for Lenke type 1A and 5C curves and who were followed up for at least 1 year. To measure changes in sagittal alignment, all patients underwent radiography before, immediately after, and at 1 year after surgery. The correlation coefficients change the value of the C2–C7 angle before and after surgery (ΔC2–ΔC7) and other spinopelvic parameters were examined. Results: In total, 19 of 30 patients in the Lenke type 1A group and 21 of 36 in the Lenke type 5C group presented with cervical kyphosis preoperatively. Hence, the incidence of cervical kyphosis did not significantly differ between the two groups. Further, the two groups had significantly higher thoracic kyphosis (TK) and greater C2–C7 angles postoperatively. The TK of the Lenke type 5C group further increased at 1 year postoperatively. The Lenke 1A type group presented with a significant re-decrease in the C2–C7 angle at 1 year postoperatively. However, the C2–C7 angle of the Lenke type 5C group did not change. The ΔTK was closely associated with the ΔC2–ΔC7 in the Lenke type 1A group, but not in the Lenke type 5C group. Conclusions: In thoracic AIS, postoperative cervical alignment should achieve an adequate TK and promote correction of the coronal plane curve. Moreover, selective corrective surgery can improve postoperative cervical alignment in lumbar AIS.
Bilateral Superior Gluteal Artery Perforator (SGAP) Flap: Modified Concept in Perineal Reconstruction
Authors: Zaussinger Maximilian , Pommer Gabriele , Freller Katrin , Schmidt Manfred , Huemer Georg M.
Published: July 2024

Background/Objectives: Perineal reconstruction after abdominoperineal excision often requires complex closures and is fraught with wound healing complications. Flap-based approaches introduce non-irradiated vascularized tissue to the area of resection to fill a large soft-tissue defect and dead space, reduce the risk of infection, and facilitate wound healing. Employing perforator flaps with their beneficial donor site properties, the authors have developed a concept of bilateral superior gluteal artery perforator (SGAP) flaps to restore extensive perineal defects. Methods: This retrospective case series was conducted between September 2015 and December 2019. We included three patients who received bilateral SGAP flap reconstruction after oncological resection. One deepithelialized SGAP flap was used for obliteration of dead space, combined with the contralateral SGAP flap for superficial defect reconstruction and wound closure. Results: Within this patient population, two male and one female patient, with a median age of 62 years (range, 52–76 years), were included. Six pedicled SGAP flaps were performed with average flap dimensions of 9 × 20 cm (range 7–9 × 19 × 21). No flap loss or no local recurrence were documented. In one case, partial tip necrosis with prolonged serous drainage was observed, which was managed by surgical debridement. No further complications were detected. Conclusions: The combination of two SGAP flaps provides maximal soft tissue for defect reconstruction and obliteration of dead space, while maintaining a very inconspicuous donor site, even with bilateral harvesting. Given these advantages, the authors recommend this promising approach for successful reconstruction of perineal defects.
Restoring Sensation through Abdominal Flap Neurotization in Breast Reconstruction
Authors: Silverstein Max L. , Momeni Arash
Published: July 2024

Breast sensation plays a significant role in the safety and quality of life of women who undergo mastectomy and reconstruction. In 1992, Slezak et al. introduced the concept of abdominal flap neurotization to improve sensation of the reconstructed breast. Over the next 30 years, numerous studies iterated on Slezak’s technique, suggesting technical modifications and new methodologies for assessing sensory recovery. Despite evidence that reinnervation increases patient satisfaction following autologous breast reconstruction, abdominal flap neurotization remains a rarely performed procedure. In this article, we review the evolution of flap neurotization in breast reconstruction and describe our approach to facilitating sensory recovery of the breast while limiting donor site morbidity.
Application of Ophthalmic Electrophysiology in Inflammatory Disorders of Retina and Optic Nerve
Authors: Yu Minzhong , Kurup Shree K.
Published: July 2024

This review covers the utility of electrophysiological studies relevant to inflammatory diseases of the retina in conditions such as acute posterior multifocal placoid pigment epitheliopathy, acute zonal occult outer retinopathy, Adamantiades–Behçet disease, autoimmune retinopathy and neuro-retinopathy, birdshot chorioretinopathy, multiple evanescent white dot syndrome, and Vogt–Koyanagi–Harada disease. Electrophysiological studies can help with the diagnosis, prognostication, evaluation of treatment effects, and follow-up for these conditions.
Diagnostic Usefulness of Disialotransferrin as an Indicator of Binge Drinking in Children and Adolescents
Authors: Cylwik Bogdan , Gruszewska Ewa , Janicka Katarzyna , Olanski Witold , Chrostek Lech
Published: July 2024

Background/Objective: The aim of the study was to evaluate the diagnostic usefulness of changes in transferrin isoforms, especially disialo-Tf, in identifying binge drinking children and adolescents admitted to hospital emergency. Methods: The study group consisted of 122 ambulatory children and adolescents below 18 years of age and 30 healthy subjects. From the group of drinkers, those with acute alcohol intoxication (AAI) were identified (ICD-11, code F10.0). The isoforms of transferrin were separated by capillary electrophoresis into five major fractions: asialo-Tf, disialo-Tf, trisialo-Tf, tetrasialo-Tf, and pentasialo-Tf. The differences between binge drinking youth and nondrinking subjects were evaluated by Mann–Whitney U-test. Results: In the total study group and in both genders, the concentration of disialo-Tf was significantly higher in the binge drinkers compared to the nondrinking youth (p = 0.006). With respect to the gender, the level of disialo-Tf was significantly higher in binge drinking than nondrinking girls (p = 0.028) and the value of trisialo-Tf was lower in binge drinking than nondrinking boys (p = 0.011). In the AAI subgroup, the concentrations of disialo-Tf and tetrasialo-Tf were significantly higher in comparison to nondrinking subjects (p = 0.002, p = 0.039, respectively). There were no significant correlations between the BAC and the transferrin isoforms in the total group and the AAI subgroup. The disialo-Tf reached the highest diagnostic power (AUC = 0.718) in identifying binge drinkers at diagnostic specificity and sensitivity of 86.7% and 51.6%, respectively (at cut-off 0.70), in the total group and it was growing up to AUC = 0.761 with the diagnostic sensitivity of 60% in the AAI subgroup. Conclusions: The disialo-Tf might be a useful biomarker to identify binge drinking children and adolescents.
Scleral Lenses for Managing Dry Eye Disease in the Absence of Corneal Irregularities: What Is the Current Evidence?
Authors: Qiu Sharon X. , Fadel Daddi , Hui Alex
Published: July 2024

Scleral lenses (SLs) are large-diameter rigid contact lenses that are a mainstay treatment for eyes with corneal irregularities. In recent years, there has been increased interest in the role of managing dry eye disease (DED) with SLs, as many patients with DED have reported symptomatic relief with SL wear. The role of SLs for DED management when there are associated corneal irregularities is supported by individual case reports and studies. This has prompted practitioners to begin advocating using SLs in DED cases, even in the absence of associated corneal irregularities and other ocular surface diseases (OSDs). There have also been discussions on potentially placing SLs earlier in the treatment hierarchy of DED, where it currently sits at a more advanced level of intervention (Step 3) in the TFOS DEWS II Report. This review will present the currently available, albeit sparse, evidence that supports and suggests this practice, as well as ancillary evidence supporting the purported benefits of SL wear in DED. The advantages of SL wear, such as corneal healing, absence of tear evaporation and contact lens dehydration, and improved visual acuity with associated increased wear comfort, and how this will benefit DED patients will be explored. Conversely, the challenges associated with fitting SLs in DED patients, including increased midday fogging, poor wettability, and subjective patient satisfaction, will also be presented, as well as a discussion on the key considerations for SL fitting in this population. Overall, while more research is needed to support the use of SLs in DED patients without associated corneal irregularities and other forms of OSD, the use of these lenses may prove to have a potentially wider role given their reported ancillary benefits in these populations.
β1600 Q.Clear Digital Reconstruction of [68Ga]Ga-DOTANOC PET/CT Improves Image Quality in NET Patients
Authors: Di Franco Martina , Fortunati Emilia , Zanoni Lucia , Bonazzi Norma , Mosconi Cristina , Malizia Claudio , Civollani Simona , Campana Davide , Andrini Elisa , Lamberti Giuseppe , Allegri Vincenzo , Fanti Stefano , Ambrosini Valentina
Published: July 2024

Background: Image reconstruction is crucial for improving overall image quality and diagnostic accuracy. Q.Clear is a novel reconstruction algorithm that reduces image noise. The aim of the present study is to assess the preferred Q.Clear β-level for digital [68Ga]Ga-DOTANOC PET/CT reconstruction vs. standard reconstruction (STD) for both overall scan and single-lesion visualization. Methods: Inclusion criteria: (1) patients with/suspected neuroendocrine tumors included in a prospective observational monocentric study between September 2019 and January 2022; (2) [68Ga]Ga-DOTANOC digital PET/CT and contrast-enhanced-CT (ceCT) performed at our center at the same time. Images were reconstructed with STD and with Q.Clear β-levels 800, 1000, and 1600. Scans were blindly reviewed by three nuclear-medicine experts: the preferred β-level reconstruction was independently chosen for the visual quality of both the overall scan and the most avid target lesion < 1 cm (t) and >1 cm (T). PET/CT results were compared to ceCT. Semiquantitative analysis was performed (STD vs. β1600) in T and t concordant at both PET/CT and ceCT. Subgroup analysis was also performed in patients presenting discordant t. Results: Overall, 52 patients were included. β1600 reconstruction was considered superior over the others for both overall scan quality and single-lesion detection in all cases. The only significantly different (p < 0.001) parameters between β1600 and STD were signal-to-noise liver ratio and standard deviation of the liver background. Lesion-dependent parameters were not significantly different in concordant T (n = 37) and t (n = 10). Among 26 discordant t, when PET was positive, all findings were confirmed as malignant. Conclusions: β1600 Q.Clear reconstruction for [68Ga]Ga-DOTANOC imaging is feasible and improves image quality for both overall and small-lesion assessment.
Initial Respiratory System Involvement in Juvenile Idiopathic Arthritis with Systemic Onset Is a Marker of Interstitial Lung Disease: The Results of Retrospective Cohort Study Analysis
Authors: Belozerov Konstantin E. , Isupova Eugenia A. , Solomatina Natalia M. , Gaidar Ekaterina V. , Kaneva Maria A. , Chikova Irina A. , Kalashnikova Olga , Kuznetsova Alla A. , Ivanov Dmitry O. , Kostik Mikhail M.
Published: July 2024

Background: Pulmonary involvement in systemic juvenile idiopathic arthritis (SJIA) is a rare but dangerous complication. The main risk factors are already known, such as macrophage activation syndrome, a refractory course of systemic juvenile arthritis, infusion reaction to interleukin 1 and/or interleukin 6 blockers, trisomy 21, and eosinophilia. However, information about respiratory system involvement (RSI) at the onset of SJIA is scarce. Our study aimed to evaluate the specific features of children with SJIA with RSI and their outcomes. Methods: In a single-center retrospective cohort study, we compared the information from the medical records of 200 children with SJIA according to ILAR criteria or SJIA-like disease (probable/possible SJIA) with and without signs of RSI (dyspnea, shortness of breath, pleurisy, acute respiratory distress syndrome, and interstitial lung disease (ILD)) at the disease onset and evaluated their outcomes (remission, development of chronic ILD, clubbing, and pulmonary arterial hypertension). Results: A quarter (25%) of the SJIA patients had signs of the RSI at onset and they more often had rash; hepato- and splenomegaly; heart (pericarditis, myocarditis), central nervous system, and kidney involvement; hemorrhagic syndrome; macrophage activation syndrome (MAS, 44.4% vs. 9.0%, p = 0.0000001); and, rarely, arthritis with fewer active joints, compared to patients without RSI. Five patients (10% from the group having RSI at the onset of SJIA and 2.5% from the whole SJIA cohort) developed fibrosing ILD. All of them had a severe relapsed/chronic course of MAS; 80% of them had a tocilizumab infusion reaction and further switched to canakinumab. Unfortunately, one patient with Down’s syndrome had gone. Conclusion: Patients with any signs of RSI at the onset of the SJIA are required to be closely monitored due to the high risk of the following fibrosing ILD development. They required prompt control of MAS, monitoring eosinophilia, and routine checks of night oxygen saturation for the prevention/early detection of chronic ILD.
Reply to Brea et al. Comment on “Levitt et al. Approach to Decompensated Right Heart Failure in the Acute Setting. J. Clin. Med. 2024, 13, 869”
Authors: Levitt Catherine V. , Williams Caitlin A. , Ahari Jalil , Pourmand Ali
Published: July 2024

We would like to acknowledge and thank the authors of “Defining the Plethoric IVC” [...]
Surgical Outcomes in Chiari 1 and Chiari 1.5 Malformation Treated by Posterior Fossa Reconstruction: A Comprehensive Analysis of 110 Pediatric Cases and Literature Review
Authors: Poca Maria A. , Lopez-Bermeo Diego , Moncho Dulce , Ferre Alex , Sanchez-Montañez Angel , Mestres Olga , Galve Sandra , Sahuquillo Juan
Published: July 2024

Background/Objectives: The management of Chiari malformations (CMs) remains a clinical challenge and a topic of great controversy. Results may vary between children and adults. The purpose of the current single-center study is to critically assess the one-year surgical outcomes of a cohort of 110 children with CM-1 or CM-1.5 who were treated using “posterior fossa reconstruction” (PFR), a surgical technique described in 1994 that has since been used in both adults and children. We also review the literature and discuss the possible causes of the drawbacks and pitfalls in children in whom PFR was ineffective in controlling the disease. Methods: The present cohort was selected from a prospective registry of adults and children with CMs collected since 2006. Patients included in this study were selected from a group of children with CMs who were operated on in our Pediatric Neurosurgical Unit between 1 January 2007 and 31 November 2023. Surgical outcome was defined based on clinical and neuroradiological results as very good, good, or bad. Results: The mean age of our child cohort was 9.9 ± 4.7 years, with 54 girls (49%) and 56 boys (51%). Sixty-six children had CM-1 (60%) while forty-four had CM-1.5 (40%). Following surgery, there was no neurological worsening or death among the children. Most children (70%) had an uneventful recovery and were discharged home on average one week after surgery. However, in 33 children (30%), we recorded at least one postoperative adverse event. Aseptic meningitis syndrome was the most frequent adverse event (n = 25, 22.7%). The final surgical outcome was evaluated one year after PFR by using both clinical and neuroradiological results. The one-year surgical outcome was excellent in 101 children (91.9%), good in 5 (4.5%), and bad in 4 (3.6%). Conclusions: PFR significantly enlarges the volume of the posterior fossa and recreates a CSF environment that generates buoyancy of the cerebellum, with a high percentage of excellent and good clinical results evaluated one year post-surgery.